Category Archives: The themes of technological innovation, entrepreneurship, and organizing

About the Contributors

Farley S. Nobre (PhD, MSc, BSc) is Professor at the School of Management of Federal University of Parana, Brazil. His research interests include organizations, knowledge management systems, innova­tion and sustainability. He received his PhD at The University of Birmingham (UK) with thesis On Cognitive Machines in Organizations, and he participated in the ARMMS project. He was Guest Re­searcher with the Institute of Organization Theory and the Artificial Intelligence Research Group of the Humboldt University of Berlin, and he participated in the Socionics project. With the multinational NEC he worked in the areas of software process improvement. He received the 1998 NEC Industrial Honor Prize for his contributions in the areas of innovation and quality. Dr. Nobre has authored international books, chapters and papers in journals and conferences worldwide. He is first author of “(Nobre, To­bias & Walker, 2009) Organizational and Technological Implications of Cognitive Machines: Designing Future Information Management Systems, IGI Global, USA.” He is member of SERVAS (a voluntary worldwide institution in support of peace and multi-cultural integration).

David S. Walker is Senior Teaching Fellow at the Business School of The University of Birming­ham UK, where he has taught since 1995. Previous to this he was Professor of Marketing, Head of the Marketing Department and Director of Business Research at Wolverhampton Business School. He com­menced his academic career at Aston Business School where he completed his doctorate in marketing as a Foundation for Management Education Research Fellow. He has throughout his professional life founded and managed several extensive companies in the industrial cleaning and chemical industries, besides current appointments as an external examiner at the Chartered Institute of Marketing, South­ampton Business School, Westminster Business School, Northampton Business School and Brighton Business School. He has published extensively in numerous business and management journals both individually and in co-authorship with Dr. Andrew Tobias and Dr. Farley Nobre.

Robert J. Harris is Associate Director of the Institute for Innovation and Enterprise at the University of Wolverhampton (UK). He has provided consultancy support to over 500 organisations since 1993, working with Banks, Business Link and Regional Development Associations. He currently manages all of the University of Wolverhampton Business School’s Knowledge Transfer Programmes. In 2007 he was presented the Lord Stafford Knowledge Transfer Champion Award in recognition of his work with small and large businesses both in the UK and overseas. He has managed a number of businesses over the last 20 years. Dr. Harris’s research has focused on knowledge transfer and in particular the development of capabilities and innovation within the SME sector. His specialist academic areas are International Business Development and Small Business Marketing and he regularly lectures in these areas in the UK, Europe and S. E.Asia. He is currently external examiner at University of Northampton.

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Nelson Guedes de Alcantara is an Associate Professor of DEMa — UFSCar and Executive Director of the Center for Materials Characterization and Development — CCDM. He was hired by the University in 1976 when he finished his course in Materials Engineering. In 1978 he completed his master’s degree in Mechanical Engineering from the University of Campinas in 1982 and obtained his PhD from the University of Cranfield, England. Since 1982, he established the laboratory for teaching and research in welding in DEMa, and since 1991 he worked in the laboratories and Materials Characterization of the CCDM. In 2008 he conducted his postdoctoral studies at Michigan State University in Management of Technological Innovation, and in 2009 he received the Executive Certificate in Strategy and Innova­tion from MIT / Sloan School of Management, both in the United States. He is currently Vice President of ABM — Brazilian Association of Metallurgy and Materials and Chief Editor of the Book Collection Metallurgy and Materials, ABM.

Thomas Andersson is Professor of International Economics and Industrial Organisation at Jonkoping International Business School since 2004. From 2004 to 2009 he served as President of Jonkoping Uni­versity. Andersson holds several other international board and advisory positions in Europe, Asia and the Middle East. Among these, he is Senior Advisor of Science, Technology and Innovation Policy in the Sultanate of Oman, member of two expert groups of the European Commission, Vice Chairman of division XI of the Royal Swedish Academy of Engineering Science (IVA) on Education and Research Policy, board member of the Swedish Programme on ICT in Developing Regions (SPIDER), and serves on the Steering Committee of the Global Forum. Andersson was previously deputy director of science technology and industry at the OECD, where he headed the technology part of the OECD Jobs Study and co-coordinated the OECD growth study. He has also been assistant under-secretary in the Ministry of Industry and Commerce in Sweden. Andersson graduated in 1983 in Economics at Stockholm School of Economics where he earned a PhD in 1989 and was appointed Associate Professor in 1993. He has been published widely on international economics and industrial organisation and has been a visiting fellow at Harvard University, Bank of Japan, Hitotsubashi University and the University of Sao Paulo.

Oihana Valmaseda Andia is an Assistant Professor of Marketing at the Basque Country University and an Assistant Researcher at the Institute for Advanced Social Studies, which belongs to the Span­ish National Research Council. Her research interests include new product and process development, industry-university collaboration for innovation and academic entrepreneurship. She has taken part in various R&D projects.

Glauco Arbix is Full Professor of the Department of Sociologyofthe University of Sao Paulo (USP). He is a member of (Brazilian) National Council of Science and Technology (CCT) and General Coordi­nator of the Observatory for Innovation of the Institute for Advanced Studies at USP. He is President of the (Brazilian) Institute of Applied Economic Research (IPEA, 2003-2006), General Coordinator of the

Center for Strategic Affairs of the Presidency (NAE, 2003-2006), a member of the Group of Advisers of the United Nations Development Programme (UNDP / UN, 2006 -2009) and Fulbright New Century Scholar (2009-2010). He is a Professor of the Department of Political Science, UNICAMP (1996-1997) and Funda^ao Getulio Vargas (FGV-SP, 1995).

Theodora Asimakou is a Senior Lecturer in Organization Studies at London Metropolitan Business School, UK. She has a PhD in Management from Manchester Business School. She has researched and consulted in a number of projects on management practices, in the areas of CSR, Organizational Knowledge, Learning, and Innovation, and Organizational Change for academic and business purposes in the UK and Greece. Her research interests lie in the area of organizational discourses, and organi­zational knowledge and innovation management; in particular how various and transforming concepts and practices affect the workplace.

Mario Otavio Batalha graduated in Chemical Engineering and MSc in Production Engineering from Universidade Federal de Santa Catarina (Brazil). He holds a Doctorate in Genie des Systemes Indus — triels — Institut National Polytechnique de Lorraine (France). He is Ad hoc consultant to the (Brazilian) National Council for Scientific and Technological Development (CNPq), FAPESP, FINEP, CAPES; a Member of the Technical Chamber of Foods — CTA of the (Brazilian) National Agency for Sanitary Vigilance; Associate Professor III at the Federal University of Sao Carlos; and Chief Editor of the Book Collection (2004-2009) of the Brazilian Production of Production Engineering.

Rachel Bocquet is Assistant Professor of Economics at the University of Savoy, France. Her field of research is centered on the determinants of innovation in small and medium-sized firms. She is also currently investigating the effects of cluster membership on the performance of SMEs. She has published several articles in books and international journals.

Sebastien Brion is Assistant Professor at the Institute of Management of the University of Savoy, France, where he mainly teaches the Management of Innovation and Information Systems. He is the Director of the Master Management and Information Technology. His research deals with the explana­tory factors of innovation process performance and with the organizational forms facilitating innovation.

Michael Brown is Professor of Corporate Reputation and Strategy at Birmingham City Business School and Head of the Centre for Corporate Reputation and Strategy He holds his PhD from York University. For almost 20 years he has headed the research into Britain’s Most Admired Companies (BMAC) survey, published annually in the Economist and Management Today, and the source of numerous academic journal articles. He has been published in British Journal of Management, Long Range Planning, The Service Industries Journal and Measuring Corporate Performance. He is also the co author along with Paul Turner of The Admirable Company in 2008. His industrial experience was gained in the United States.

Marfa Catalina Ramirez Cajiao holds a PhD in Management, Economics and Industrial Engineering from the Politecnico di Milano, a MSc in Industrial Engineering from the Universidad de los Andes, and a BSc in Industrial Engineering from the Pontificia Universidad Javeriana. At present, she works as an

Associate Professor at the School of Engineering at the Universidad de los Andes and is the President of Engineers without Borders in Colombia (ISF Colombia).

Helio Gomes de Carvalho, Dr., holds a Doctorate degree in Industrial Engineering from the Federal University of Santa Catarina (UFSC), Brazil. He is currently a professor at the Federal Technological University of Parana (UTFPR), Brazil, where he has advised over 25 graduate students of the Innova­tion and Technology Graduate Program. He is the lead researcher of the Innovation and Technology Management Group at UTFPR and his research includes Innovation, R&D and Project Management, Competitive intelligence and Strategic management.

Luiz Caseiro is a Graduate Student in Sociology at University of Sao Paulo (USP) and has a Bachelor degree in Social Sciences at the same institution. He has research experience in Sociology of Develop­ment, working mainly with the following themes: public policy, multinationals, innovation, emerging markets and socio-economic development. He is currently a researcher at the Observatory for Innovation and Competitiveness of the Institute of Advanced Studies at USP, Brazil.

Gregorio Martin de Castro, Dr., is Associate Professor at the Business Administration Department in Universidad Complutense de Madrid (Spain). He has several years of research experience at CIC Spanish Knowledge Society Research Centre, he holds an Expert Diploma in Intellectual Capital and Knowledge Management from IN SEAD (France), and he was a Post-Doctoral Research Fellow at Harvard University during 2004-2005. He is author and co-author of several papers concerning Resource-Based View, Intellectual Capital and Knowledge Management.

Jason G. Caudill holds a PhD in Instructional Technology as well as a BS in Business Administration and an MBA. He currently serves as an Assistant Professor of Business at Carson-Newman College in the state of Tennessee, USA. Dr. Caudill’s research interests include technology integration, technology management, and online education.

Steven Cavaleri has co-authored five books on systems thinking, knowledge management and or­ganizational learning. Steven is former editor of The Learning Organization Journal. He is also former president of The Knowledge Management Consortium International and co-founder of KMCI Press imprint of Elsevier Publishing. Dr. Cavaleri holds a PhD from Rensselaer Polytechnic Institute (USA). He was also a Visiting Scholar in the Learning Center at MIT’s Sloan School of Management. Steven has consulted for many well-known companies, such as IBM and Stanley Tools. He is professor of man­agement at Central Connecticut State University (USA). Steven is also a certified Systems Integrator by the Institute of Industrial Engineers.

Claudio Cruz Cazares is an Industrial Engineer who has studied the PhD in Business Economics at the Autonomous University of Barcelona (Spain). He is highly interested in the field of innovation management and firm performance. During the last years he has actively participated in national and international conferences such as ACEDE, ISPIM, EIASM. He has been also involved in several research projects financed by the Spanish Ministry of Education. He is also part of team of the department of Business Economics of the Autonomous University of Barcelona.

Javier Alejandro Carvajal Diaz holds a MSc degree in Engineering (Organisational Management) and Industrial Engineering with emphasis on education from the Universidad de los Andes, Colombia. At present, he works as a researcher and lecturer in Systemic Thinking in Organisations (Pensamiento Sistemico en las Organizaciones) at the Industrial Engineering Department of the Universidad de los Andes. His research areas involve innovation, sustainable development and education in engineering.

Friedrich Grosse Dunker is co-founder of the innovation consultancy Dark Horse GmbH, which is engaged in user-centered innovation and Design Thinking, and also gets involved as a coach in innova­tion and entrepreneurial projects. He graduated at Technische Universitat Munchen, Germany, and holds a degree in Business Administration and Engineering. He wrote his diploma thesis on “Sustainability Innovation Cube — A framework to evaluate sustainability-oriented innovations”. His research interests are innovations and innovation management in the field of sustainability and design-based innovations and business strategies. Friedrich obtained broad academic and practical experiences in Australia, Nor­way, Germany and South Africa.

Gustavo de Boer Endo is a graduate in Business Administration from University of Sao Paulo (USP), Brazil. Gustavo de Boer Endo is consultant at TerraForum and advises companies in knowledge management, maturity models, knowledge strategies and innovation network and clusters and strate­gies. Within innovation management projects, he structured innovation processes for large clients and modeled open innovation structures, partner evaluation and structuring of innovation environments.

Niels R. Faber is Researcher at the Department of Social Sciences of the Frisian Academy (KNAW), and Assistant Professor at the Faculty of Economics and Business of the University of Groningen. His research and publications concentrate on the topics of knowledge management, knowledge technology, decision-support systems, and social sustainability, especially within the domain of agriculture. In 1999, he received his MSc in computer science at the University of Twente. His MSc in Industrial Engineering and Management Science was completed in 2002. In 2006, he received his PhD for his thesis “Knowl­edge in Sustainable Behavior”.

Pilar Fernandez Ferrin is an Assistant Professor of Marketing at the University of Pais Vasco. She has a PhD in BusinessAdministration from the University of Santiago de Compostela (Spain). She teaches and carries out research in the fields of new product development, sales management and consumer behavior. Her work has been published in Journal of Product Innovation Management, Technovation, Industrial Marketing Management, European Journal ofMarketing, Creativity and Innovation Manage­ment, Psychology & Marketing, Revista espanola de Investigacion en Marketig Esic, Revista Europea de Direccion y Economia de la Empresa and Cuadernos de gestion.

Diana A. Filipescu holds a PhD in Business Economics from theAutonomous University ofBarcelona (Spain). Her main research interests are in firms’ technological innovation and internationalization, R&D strategies, and family business. She has presented various studies in important national and international conferences such as ACEDE, McGill International Entrepreneurship, EIBA, EIASM, and AOM. She is also a Professor of International Business and International Marketing Strategies at the Foundation of the Autonomous University of Barcelona.

Jonas Gabrielsson is Associate Professor in Business Administration at the Centre for Innovation, Research and Competence in the Learning Economy (CIRCLE), at Lund University (Sweden). His teaching and research is primarily focused on issues related to entrepreneurship and innovation. He has also a general research interest in corporate governance, primarily related to companies operating in entrepreneurial contexts.

Simone Galina is an Assistant Professor of Innovation and Operations Management at the School of Economics, Business and Accountancy of Ribeirao Preto at University of Sao Paulo, Brazil. She has a PhD in Engineering from Polytechnic School of University of Sao Paulo. She is teacher and advisor of Master and Doctorate students at the Graduate Program in Management of Organizations (PPGAO). She leads the Group of Studies on Innovation and Internationalisation of Companies and her main areas of expertise are innovation management, R&D internationalization and globalization of operations.

Jorge Cruz Gonzalez is PhD Candidate in Business Administration at the Business Administration Department in Universidad Complutense de Madrid (Spain) and member of the Strategy, Knowledge and Innovation Research Group (ECI) of this university. Additionally, he is scholarship holder of the Spanish Ministry of Science and Innovation (University Professorship Formation National Plan). His main research lines are about Knowledge Management and Dynamic Capabilities.

Jose A. Varela Gonzalez is a Professor of Marketing at the University of Santiago de Compostela (Spain). He has a PhD in Business Administration from the University of Santiago de Compostela. His research interests include sales management, new product/new service development and launching, ser­vices marketing and marketing orientation. His work has been published in Journal of Organizational Behavior, Marketing Intelligence & Planning, Technovation, Journal of Product Innovation Manage­ment, The Service Industries Journal, Creativity and Innovation Management, Revista espanola de Investigacion en Marketig Esic, Revista Europea de Direccion y Economia de la Empresa, Informacion Comercial Espanola and Cuadernos de gestion.

Sergio Ronaldo Granemann graduated in Civil Engineering from the University of Santa Catarina. He earned MSc in Production Engineering from Federal University of Santa Catarina, MA in Econom­ics from the Universite d’Aix Marseille II and PhD in Economics from Universite D’Aix Marseille II (France). He is currently a member of the committee of experts from the Ministry of Education, Adjunct Professor at the University of Brasilia and reviewer of Gestao&Produgao Journal.

Jerald Hage is the Director of the Center for Innovation at the University of Maryland. He is a graduate of Columbia University, he is a former chair of the Department of Sociology at the University of Maryland. He has been a visiting professor at four universities and the winner of three international fellowships. In addition, he is the author of 16 books, over 100 papers and chapters, and has a book forthcoming from Stanford University Press on the need for a new policy model based on innovation.

Erik G. Hansen is a senior researcher at the Centre for Sustainability Management (CSM) at Leuphana University Luneburg, Germany. Prior to this appointment he was a Postdoc researcher at Friedrich — Alexander-University Erlangen-Nuremberg, Germany and a visiting researcher at Cranfield University,

Doughty Centre for Corporate Responsibility in the UK. His research interests are innovation, strategy, and governance in the context of corporate responsibility and sustainability. Erik teaches business classes at undergraduate, graduate and executive level. He wrote his doctoral thesis on “Responsible Leader­ship Systems” at Technische Universitat Munchen, Germany. He has also gained broad experience in industry jobs and academic exchanges in Brazil, China, Germany, and Thailand.

Ariane Hin^a (MSc, PMP) is the coordinator of the Industrial Development Observatory under the Industry Federation of Parana (FIEP), in Brazil. She’s holds a bachelor degree in Economics from the Federal University of Parana (UFPR). She obtained her master’s degree in Technology from the Federal Technological University of Parana (UTFPR) where she is currently a doctoral candidate. She is also a researcher at the Innovation and Technology Management Group at UTFPR.

Gretchen Jordan is a Principal Member of Technical Staff with Sandia National Laboratories in the USA. She works with the Sandia Science and Engineering Strategic Management Unit and the US Department of Energy on evaluation and performance measurement and innovative methods of assessing the effectiveness of research organizations. She is Co-Editor of Research Evaluation.

Rene J. Jorna is head of the Social Sciences Department of the Frisian Academy (KNAW) and full Professor in Knowledge Management and Cognition at the faculties of Economics and Business and Behavioural Sciences of the University of Groningen. He studied Analytic Philosophy and Logic (Master in 1981) and Experimental Psychology (Master in 1982) and had his PhD in 1989 in Cognitive Science on knowledge representation. His research and publications refer to cognition, semiotics, knowl­edge management, sustainability and knowledge technology. In 1994, he published Semiotic Aspects of Artificial Intelligence (de Gruyter). From 1990 until 1995 he was manager of a research project on planning (DISKUS), resulting in commercial software and five PhD’s. From 2001 until 2004, he was program manager of the NIDO project on Sustainable Innovation. In 2006 he published the book Plan­ning in Intelligent Systems (Wiley, New York) and also in 2006 Sustainable Innovation (Greenleaf). He published over 150 journal articles and book chapters. He supervises 10 PhD projects on sustainable innovation, planning, cognition and social simulation.

Yuya Kajikawa is a Project Lecturer at the School of Engineering at The University of Tokyo (Ja­pan). He received his PhD degree in Chemical System Engineering from The University of Tokyo in 2004. He also received his BS and MS degrees from the same university in 1999 and 2001, respectively. His research interests include the structuring of engineering knowledge, technology and innovation management, and innovation policy. He has a number of publications in peer-reviewed journals and conference proceedings, which cover a variety of disciplines including engineering, information science, environmental science, and management science.

Jose Carlos Korelo (MSc) is a PhD student in the Business Administration Program, concentrating on Marketing and Consumer Behavior at School of Management of Federal University of Parana, Brazil. He holds a Master in Business Administration (concentration in Marketing and Consumer Behavior) from Federal University of Parana, Brazil, 2009. He is interested in consumer’s innovation adoption behavior and consumer behavior.

Valentina Lazzarotti isAssistant Professor at the Institute ofTechnology of Universita Carlo Cattaneo

— LIUC (Italy). She teaches Business Economics and Organization and Management Control Systems at LIUC. She holds a PhD in Management Engineering from Politecnico of Milan and a Master Degree in Business Administration from Bocconi University. Her research interest concerns R&D performance measurement and accounting for innovative activities. She has published papers in international journals such as International Journal of Innovation Management and Project Management Journal.

Enrique Leff, Mexican born, is a pioneer and one of the main authors on environmentalism, rec­ognized internationally and particularly in Latin America. He got his BA in Chemical Engineering at UNAM in Mexico City and a Doctorat de Troisieme cycle in Economic Development in Paris I-Sorbonne University in France. He works in the fields of Environmental Philosophy, Epistemology and Sociology, Ecological Economics, Political Ecology and Environmental Education. For over 22 years, Enrique Leff was Coordinator of the Environmental Training Network for Latin America and the Caribbean and then Coordinator of the Mexico Office of the United Nations Environment Programme, until May 2008. He is presently full-time researcher at the Institute of Social Research and Professor at the Faculty of Political and Social Sciences at the National Autonomous University of Mexico. He has published extensively in the field of environment and sustainability and is regularly invited as keynote speaker, lecturer and professor to universities throughout Latin America and Spain.

Suzana Monteiro Leonardi is consultant at TerraForum and a specialist in innovation and knowledge management helping companies to implement, manage and improve their innovation processes. She is Professor, with a Master’s Degree in Business Administration, she is working hard to get her doctorate degree in Education at UNICAMP, Brazil.

Jose Emilio Navas Lopez, Dr., is Professor at the BusinessAdministration Department in Universidad Complutense de Madrid (Spain) and Chairman ofthe Strategy, Knowledge and Innovation Research Group (ECI) of this university. He is author and co-author of several books and papers concerning Technology Management, Strategy and Knowledge Management. He has held the first Knowledge Management Chair in Spain at I. U. Euroforum Escorial.

Raffaella Manzini is Associate Professor at the Institute of Technology of Universita Carlo Cattaneo

— LIUC (Italy). She teaches Business Economics and Organization and Technology Strategy at LIUC and Politecnico di Milano. Her research interests concern R&D and innovation management, technology strategy and organization and technological collaborations. She has published more than 40 papers in leading international journals such as R&D Management Journal, Long Range Planning, International Journal ofTechnology Management, and International Journal of Operations & ProductionManagement.

Leonardo J. Melo is an MSc student at the Institute of Economics, Federal University of Rio de Janeiro (IE/UFRJ) and research assistant at the (Brazilian) National Institute of Science and Technol­ogy Policy, Strategy and Development (INCT / PPED). Melo has a Bachelor’s Degree in Business Ad­ministration (focused on Entrepreneurship and Management and Evaluation of Public Policy) from the Catholic University of Rio de Janeiro (PUC-Rio). He works in the field of project management related to innovation and interaction between universities, government and society. Melo researches in the fol­lowing areas: public policy, sustainability and the knowledge economy.

Jonathon Mote is an Assistant Professor of Management at Southern Illinois University in Carbon — dale (USA). His research interests are primarily focused on the interrelationship between organizational environments and the networks of science and innovation. His articles have appeared in The Journal of Engineering and Technology Management, R&D Management, and Research Evaluation, among others.

Caroline Mothe is full Professor of Strategic Management at the University of Savoy, where she mainly teaches strategy and innovation management. Interested in interfirm cooperation and in innova­tive organizations, she actually coordinates several research projects on intra and inter-organizational innovation processes. She has published many articles related to these fields in international journals.

Helen E. Muga, PhD, is an Assistant Professor in Civil Engineering at the University of Mount Union, Alliance, Ohio (USA). She worked as a postdoctoral researcher in the Civil & Environmental Engineering department at the University of South Florida, Tampa, Florida. She received a PhD in En­vironmental Engineering from Michigan Technological University, Michigan, USA, a Masters degree in Chemical Engineering from Curtin University of Technology, Australia, and a Bachelors degree in Chemistry from the University of Papua New Guinea. Her research interests include sustainability, life cycle engineering, green engineering, diffusion and adoption of green technology, and international development work.

Hiroko Nakamura is a Project Researcher at the Centre for Aviation Innovation Research at The University of Tokyo (Japan). She previously worked for Nissan Motor Co. Ltd., as a product planner, making the efforts of engineers attractive to the market. She received her MS degree in Environmental and Ocean Engineering from the University of Tokyo in 2006 and a Special Master’s degree in Indus­trial System Engineering from the Ecole Centrale Paris in 2004. She also received her BS degree from The University of Tokyo in 2003. Her research interests include transition management of innovation.

Christina Oberg is an Assistant Professor in marketing at Lund University. She received her PhD from Linkoping University. She has an industry background and has previously worked in such posi­tions as financial manager and head accountant. Today, she is an authorized accountant. Her research interests are mergers and acquisitions, innovation management and business relationships. She has previously published in journals such as Journal of Business Research, Construction Management and Economics, International Journal of Innovation Management, and Industrial Marketing Management. In addition, Christina has had articles accepted for publication in European Journal of Marketing and The Service Industries Journal.

Luisa Pellegrini, PhD, is Associate Professor of Management Engineering at the faculty of Engi­neering, University of Pisa (Italy) where she teaches Innovation Management and Business Economics and Organisation. She is actively involved in national and international research projects on Knowledge Management and Continuous Innovation. She is member of the Continuous Innovation Network (CINet) and author of numerous international publications.

Jose Tiberio Hernandez Penaloza has a PhD in Informatics from l’Ecole Nationale Superieure de Techniques Avancees, and a MSc in Computing and Systems Engineering from the Universidad de

los Andes. He is a former Dean and Vice-Dean of the School of Engineering at the Universidad de los Andes and currently works as an associate professor and head of the Visual Computing R&D Team in the School of Engineering at the Universidad de los Andes, in Colombia.

Diamanto Politis is Assistant Professor in Entrepreneurship at School of Business and Engineer­ing of Halmstad University, Sweden. She is member of KEEN and CIEL at Halmstad University. Her research interests include entrepreneurial learning, academic entrepreneurship and the value-adding role of business angels in new firms.

Andrew Pollard joined the University of Wolverhampton (UK) in 2002 and was appointed Indus­trial Professor in 2003 with the responsibility to set up and run the ‘Caparo Innovation Centre (CIC)’, a joint collaboration between Caparo plc and the University of Wolverhampton. The CIC team work with inventors to help them commercialize their ideas, earning a royalty on products launched this way. Prof Pollard also works on a consultancy basis for small and large companies, addressing issues in the area of innovation, new product introduction and internationalisation. He has been appointed a Director of Unibyte ltd, a spin-out company from the University, and also sits on the Caparo Engineering Board responsible for strategic development.

Anne Berthinier Poncet is a PhD candidate in Management at the IREGE (Institute of Research in Economics and Management) and teacher at the University of Savoy, France. She’s studying the influence of regional cluster governance on firm’s innovative performance, in particular in technopoles and competitiveness clusters. Her topics of interests cover also innovation in services, and specifically innovation of KIBS.

Paulo Henrique Muller Prado, PhD, is Adjunct Professor of Marketing at the School of Manage­ment, Federal University of Parana, Brazil. He holds a PhD in Marketing, from FGV — Getulio Vargas Foundation, Brazil, 2004; a MSc in Business Administration, (Concentration in Marketing and Consumer Behavior), from Federal University of Parana, Brazil, 1995; and a BSc in Electrical Engineering, from UNICAMP, Brazil. His research interests include: Satisfaction Models, Relationship Quality and Loy­alty, Cognitive Structures and Innovation adoption, Consumer-Brand Relationship, B2B Relationship, Marketing Metrics.

David L. Rainey is an internationally-known author, educator, and business consultant. He is a leading authority on sustainable development, strategic leadership, strategic management, strategic in­novation, product development, and energy management. He is a strategist and pragmatist developing innovative solutions to the challenges in today’s turbulent business environment. Dr. Rainey has over 35 years of experience and leadership in industry and academia. He is a Professor of Management in the Lally School of Management and Technology at Rensselaer Polytechnic Institute. Dr. Rainey is a Visiting Professor at the Technical University of Munich and an Associate of “the Center for the Study of Corporate Sustainability” in Buenos Aires, Argentina. Dr. Rainey is the author of Product Innovation: Leading Change through Integrated Product Development (2005), Sustainable Business Development: Inventing the Future through Strategy, Innovation and Leadership (2006) and Enterprise-wide Strategic Management: Achieving Sustainable Success through Leadership, Strategies and Value Creation (2010).

The books are published by Cambridge University Press. His next books are Full-Spectrum Strategic Leadership: Achieving Sustainable Success through Solutions, Systems and Relationships and Corporate Strategic Management: Achieving Sustainable Success through Visionary Leadership and Strategic In­novation. Dr. Rainey earned a BS in Mechanical Engineering, a MBA, and Master of Science degrees in Engineering Science and Business Management. He earned a PhD from Rensselaer Polytechnic Institute.

Caspar van Rijnbach is Dutch from origin with a Masters degree in Economics and a Masters degree in Political Science. He is a specialist in Innovation Management, partner at TerraForum Consulting in Brazil, Professor at the Brazilian Business School in 2010 and was Professor of the discipline “Innova­tion Management” in the educational course “Knowledge Management in Pratice” — USP — FIA 2006 (one of Brazil’s major universities). He led many in-company courses on innovation and knowledge management. Co-author of “Innovation: Breaking Paradigms” and “Management 2.0’’ — in which he wrote the chapter “Innovation 2.0” (both books in Portuguese). Caspar has given advice about innova­tion and knowledge management to large Brazilian companies and multinationals, such as Vale, Sadia, CPFL, Unilever, Syngenta, Citibank and Mahle.

Felipe Fontes Rodrigues, MSc, is a Professor of Operations Research at the Department of Applied and General Management at the Federal University of Parana (UFPR), Brazil. He was granted a research fellowship at the Industrial Development Observatory at the Industry Federation of Parana (FIEP), and he is a researcher with the Technology Prospective and Regional Technology Development group at the Federal Technology University of Parana (UTFPR).

Renata Lebre La Rovere is Associate Professor at the Institute of Economics of Federal University of Rio de Janeiro (IE/UFRJ) since 1993, and researcher at the (Brazilian) National Institute of Science and Technology Policy, Strategy and Development (INCT / PPED) since 2009. She holds a PhD in Economic Sciences from Universite Paris 7, France, 1990. She was a Visiting Professor at the Manage­ment of Information Sciences Department, University of Arizona, between 1991 and 1992; and took a Post-Doctoral research in Innovation Policies for small enterprises at the Management of Informa­tion Sciences Department at Rostock University, Germany, between 1995 and 1996. Her main areas of research are: innovation policies for small enterprises, Information Technologies and development, entrepreneurship and local development.

Pedro Lopez Saez, Dr., is Associate Professor at the Business Administration Department in Univer­sidad Complutense de Madrid (Spain) and member ofthe Strategy, Knowledge and Innovation Research Group (ECI) of this university. Additionally, he has several years of research experience at CIC Spanish Knowledge Society Research Centre and has been Post-Doctoral Research Fellow at Harvard University during 2004-2005. He is author and co-author of several books and articles concerning Resource-Based View, Intellectual Capital and Knowledge Management.

Javier Amores Salvado is Assistant Professor at the Business Administration Department in Uni­versidad Complutense de Madrid (Spain). He holds the Advanced Studies Diploma from Universidad Complutense de Madrid. His main research lines are Innovation, Environmental Innovation and Sus­tainable Development.

Daniela Tatiane dos Santos graduated in Economics from the Universidade Estadual Paulista Julio de Mesquita Filho (2005). She holds a Masters in Production Engineering from Universidade Federal de Sao Carlos (2007). Currently she is a PhD student in Industrial Engineering (UFSCar) and has experi­ence in Industrial Economics and Technology Management and Innovation.

Horst-Hendrik Scholz received his MSc degree in Engineering Management at The University of Birmingham (UK) after the completion of a BEng degree in Industrial Engineering at the Leuphana Universitaet Lueneburg (Germany). After finishing A-level at the Gymnasium Suederelbe, he worked part-time besides studying on projects like: upgrading an ERP — Systems and implementation of an avia­tion standard (EN9100) in a manufacturing enterprise. To gain work experience abroad he worked for 9 month in several Canadian and American SMEs in Project — and Customer Relationship Management. To apply academic knowledge in financing he worked as a financial adviser; assisting the management of a SME company in the aviation industry.

Laila Del Bem Seleme, MSc, holds a Bachelor degree in Service Management from Mogi das Cru­zes University (UMC) and a Master’s degree in Strategic Management from the Federal University of Parana (UFPR), Brazil. She is a Technical Researcher with the Industrial Development Observatory at the Industry Federation of Parana (FIEP), and a researcher with the Technology Prospective and Regional Technology Development group at the Federal Technology University of Parana (UTFPR).

Danielle Mantovani Lucena da Silva, MSc, is a PhD student in the Business Administration Program, concentrating on Marketing and Consumer Behavior at School of Management of Federal University of Parana, Brazil. She holds a Masters in Business Administration (concentration in Marketing and Con­sumer Behavior), from Federal University of Parana, Brazil, 2006. Her research interests concentrate on the analysis of the psychological and cognitive aspects regarding consumer’s decision making process.

Gavin Smeilus is a Senior Consultant in Product Innovation at the University of Wolverhampton (UK). He is currently enrolled on the University’s Doctoral programme undertaking research into the Integration of Independent Inventors in Open Innovation. Gavin has undertaken new product introduction related consultancy projects on behalf of numerous businesses from sole traders through to multinational corporations.

Marilia de Souza, PhD, is the Manager ofthe Industrial Development Observatory under the Industry Federation of Parana (FIEP), Brazil. Prior to her managerial career she obtained her Doctorate degree in Mechanical Engineering Sciences at the Technology University of Compiegne (UTC), France. She is a Guest Senior Researcher for the Technology Prospective and Regional Technology Development group at the Federal Technology University of Parana (UTFPR).

Shinji Suzuki is a Professor at the Department of Aeronautics and Astronautics and Head of the Center for Aviation Innovation Research at The University of Tokyo (Japan). He received his PhD degree in Engineering from The University of Tokyo in 1986, after his research career at Toyota’s Central R&D Labs, Inc., in Japan. He received his BS and MS degrees from the same university. His main research interests are in the design and control aspects of air safety and unmanned aerial vehicles. Shinji Su-

zuki is currently Vice — President of JSASS, the Board Director of JSME, and an Executive Committee Member of ICAS.

Ken D. Thomas completed his PhD in Civil & Environmental Engineering from the University of South Florida, Tampa, FL, and BSc in Chemical and Process Engineering & MSc in Environmental Engineering from the University of the West Indies, St. Augustine, Trinidad. During the latter stage of the MSc he worked for the state agency of Environmental Management Authority of Trinidad and Tobago in the capacity of Environmental Protection Officer up until commencing PhD studies at the University of South Florida, Tampa, Florida. Ken is currently a Postdoctoral Fellow of The University Honors College, Auburn University, Auburn, AL where he is engaged in teaching sustainability courses and undertaking research on sustainable development.

Paul Turner is Professor of Management Practice at Ashcroft International Business School, Cam­bridge; a Non Executive Director of Blessing White and a Non Executive Director on the European Advisory Board of OPI. He was formerly President of Europe, Middle East and Africa, Employee Care for the Convergys Corporation, Group HR Business Director for Lloyds TSB, Vice President of the CIPD, a Director of BT and Executive in Residence at Nottingham Business School. He holds his PhD from the University of Sheffield. He is the author of HR Forecasting and Planning (2002), Organizational Communication (2003) and co author of Talent (2007). He is also the co author along with Michael Brown of The Admirable Company published in 2008.

Miriam Delgado Verde, Dr., is Assistant Professor at the Business Administration Department in Universidad Complutense de Madrid (Spain) and member of the Strategy, Knowledge and Innovation Research Group (ECI) of this university. Additionally, she has been Post-Doctoral Research Fellow at MIoIR-The University of Manchester during 2009 and University of Edinburgh Business School dur­ing 2010. She is author and co-author of several books and articles concerning Resource-Based View, Intellectual Capital and Technological Innovation.

Eric Viardot is Permanent Professor of Marketing and Strategy at EADA Business School in Barce­lona. He has a Doctorate in Management. He is a graduate of the HEC Business School, Paris, and the Institute of Political Sciences, Paris. He has published various books and articles on strategic manage­ment and marketing with a strong focus on Innovation and Technology Management. He is currently the co-editor of the International Journal of Technology Marketing. He is an active consultant and trainer and has worked with several major multinational corporations, notably with various innovation-driven technology firms.

Belen Bande Vilela is an Assistant Professor of Marketing at the University of Santiago de Com­postela (Spain). She received her PhD in Business Administration from the University of Santiago de Compostela. Her research interests include sales management, consumer behavior and new product development. Her work on these topics has been published in a variety of journals, such as Journal of Organizational Behavior, Journal of Product Innovation Management, Technovation, Industrial Mar­keting Management, European Journal of Marketing, Creativity and Innovation Management, Revista espanola de Investigacion en Marketig Esic, Revista Europea de Direccion y Economia de la Empresa and Cuadernos de gestion.

The focus is on the global business envi­ronment and market spaces. Market spaces

The Roles of Cognitive Machines in Customer — Centric Organizations: Towards Innovations in Computational Organizational Management Networks

Farley Simon Nobre

Federal University of Parana, Brazil

ABSTRACT

This chapter proposes innovative features of future industrial organizations in order to provide them with the capabilities to manage high levels of environmental complexity in the 21st century. For such a purpose the author introduces the concept of Computational Organization Management Networks (COMN), which represents new organizations whose principles of operation are based on the concepts of Hierarchic Cognitive Systems (HCS) along with those of Telecommunications Management Networks (TMN). Structured with functional layers and cognitive roles that range from technical and managerial to institutional levels of analysis, and also equipped with operational, managerial and strategic processes, the concept of Computational Organization Management Networks (COMN) plays an important part in the developments of future organizations where cognitive machines and Cognitive Information Systems (CIS) are prominent actors of governance, automation and control of the whole enterprise. It is in such a context that the new organization COMN will provide customers and the whole environment with in­novations such as immersiveness for the production of services and goods that are most customer-centric.

DOI: 10.4018/978-1-61350-165-8.ch035

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

INTRODUCTION

This chapter mainly relies on principles of incom­patibility, or non-equilibrium, existing between the continuous growth in the level of environmental complexity and the insufficient cognitive capacity of the organization to deal with higher levels of uncertainty, to operate in complex task environ­ments, to attend new market demands, to manage new approaches to customers’ satisfaction and relationship, and to capture effectively information resources from the environment. Such a premise has motivated organizations to pursue higher degrees of cognition, intelligence, autonomy, and learning through principle s of organization de sign (Nobre, Tobias & Walker, 2009a, 2009b, 2009c, 2010; Nobre & Walker, 2011).

Therefore, this chapter focuses on the general picture of organizations pursuing high degrees of cognition in order to improve their capabilities of information processing and uncertainty manage­ment. It assumes that improvements in the degree of organizational cognition can lead the organiza­tion to achieve higher degrees of flexibility and agility, to operate through higher levels of mass customization (Pine, 1999), and to provide cus­tomers with immersiveness. In a broader sense, such improvements extend the capability of the organization to manage higher levels of environ­mental complexity. In such a context, flexibility means capability to reconfigure and to adapt to new operational and management conditions (Toni & Tonchia, 1998); and agility means the ability to manufacture a variety of products, services and goods, at low cost and in a short period of time (Lee, 1998).

This chapter supports existing works on manufacturing systems (Kusiak, 2000; Monfared & Steiner, 1997; Rao et al., 1993) and industrial organizations (Nobre et al, 2009a, 2009c), and additionally, it extends past and present concepts by proposing new technological, managerial and organizational capabilities which have to be developed in order to satisfy the requirements and to configure the new face of the industrial organization in the 21st century. F irst and foremost, this work aims to give insights and answers to the questions in the following whose responses are blended over this full chapter:

a. What is the nature of this new industrial organization?

b. What steps are required to design this new enterprise?

c. What would be the future of these organizations?

Chronologically, this work first introduces concepts of organizations and machines which are fundamental for the understating ofthis research. Such concepts comprise organizational cogni­tion, intelligence, autonomy, and learning, along with uncertainty, environmental complexity, and cognitive machines.

Second, it proposes the concept and the features of Customer-Centric Systems (CCS) which were most developed through literature review and analyses of past and current industrial organiza­tions as researched in (Nobre & Steiner, 2002; Nobre et al., 2009a, 2009c); whereas, in these works, the authors outlined the development of manufacturing systems and organizations, espe­cially in the 20th century, through complementary perspectives of technology, management and organizational systems theory, respectively. As a result of the analyses, they indicate limitations of past and current manufacturing organizations which motivated them the proposal ofthe new fron­tiers, concept, and features of Customer-Centric Systems (CCS). CCS represent new organizing models of production that pursue high degrees of organizational cognition in order to manage high levels of environmental complexity, to operate through intensive mass customization processes, and to provide customers with immersiveness.

Third, from all these interdisciplinary back­grounds, this chapter mainly contributes by presenting the concept, structure and processes of Computational Organization Management Networks (COMN), which are new organizations with the capability to implement the features of Customer-Centric Systems (CCS). In COMN, cognitive machines and Cognitive Information Systems (CIS) are prominent actors ofgovernance, automation and control of the whole enterprise (Nobre et al, 2009a, 2009b, 2009c).

KEY CONCEPTS OF THE ORGANIZATION Customer-Centric Systems: Main Features of Future Industrial Organizations

This subsection introduces the characteristics of Customer-Centric Systems (CCS) which concept was firstly touched in (Nobre & Steiner, 2002), and latterly it was further developed in (Nobre et al., 2009a, 2009c). Briefly, CCS represents organizational models with capabilities to:

1. Manage high levels of environmental complexity.

2. Operate through high levels of mass customization.

3. Pursue high degrees of organizational cogni­tion, intelligence, autonomy, and learning, and consequently, high degrees of flexibility and agility.

4. And provide customers with immersiveness.

This chapter proposes that Customer-Centric Systems (CCS) are firm types which strategically organize their resources and competencies around customers’ values and needs, in order to involve customers into their business. By involving cus­tomers into their task environments and business, CCS-based organizations have the chance to understand and to produce the real needs, goods and services, to their clients.

Industrial Organizations

For the purpose of this chapter, manufacturing organizations are synonymous with industrial organizations; which are classes of organiza­tions that satisfy the concept of open-rational systems (Nobre et al., 2009a; Scott, 1998) and also the perspective of economic organizations (Milgrom & Roberts, 1992). They are highly formalized organizations that pursue specific goals, innovation and sustainable competitive advantage. They produce goods and services. The elements of the organization include goals, social structure, technology, and the participants in the organization (Scott, 1998: 17-23). Moreover, the organization exists in a physical, technological, cultural, and social environment with which the organization interacts (Scott, 1998: 21-23). Par­ticipants are the agents who act in the name of the organization and they subsume humans and cognitive machines (Nobre, 2008; Nobre et al., 2009a, 2009b). Technology expands what orga­nizations can do and it supports the connection of the organization to the environment. Goals and sub-goals are what organizations aim to achieve in order to satisfy people’s desires. Social structure refers to the standards and regularized aspects of the relationships existing among the participants in the organization, whereas it comprises norma­tive and behavioral parts (Scott, 1998).

Limitations of Organizations

Contingency theory (Galbraith, 1973, 1977, 2002) has defined uncertainty as the variable which makes the organization contingent upon the environment. Hence, organization design, and thus organizational choice, depends on the concept of uncertainty. Briefly, uncertainty can be associated with propositions of bounded ra­tionality theory (Simon, 1982a, 1982b, 1997a, 1997b), when carrying the meaning of (Nobre et al., 2009a: Chapter 2):

a. Lack of information, which leads the orga­nization to unpredictability of outcomes.

Figure 1. Uncertainty as lack of information

b. And, insufficiency of cognitive capacity for general information-processing.

The former, lack of information, means that:

• Definition 1: Uncertainty is the difference between the total amount of information that the organization needs to have in order to complete a task, and the amount of infor­mation in possession of the organization.

The latter, insufficiency of cognition, means that:

• Definition 2: Uncertainty is the difference between the degree of cognition that the organization needs to have in order to com­plete a task, and the degree of cognition in possession of the organization.

These two approaches to uncertainty are complementary to each other since the greater the amount of information that the organization needs to have in order to perform and to complete a task, the greater is the degree of cognition that the organization needs to have in order to process and to manage this information for task execution and completion. Figure 1 and Figure 2 illustrate such concepts ofuncertainty using symbolic scales of measurement.

Therefore, the question which rises in our quest is: what to do in order to manage the level of uncertainty that the organization confronts and navigates in? Organizational cognition has an important part into such a perspective and there­fore it is introduced in the next subsection.

Organizational Cognition

Figure 2. Uncertainty as lack of cognition

From such a context, this chapter proposes new principles, concepts and features of Customer — Centric Systems (CCS) which configure the new face of the industrial organization in the 21st cen­tury. These organizations are emerging in order to pursue higher degrees of cognition and greater capabilities ofgeneral information processing and uncertainty management.

Degree of Organizational Cognition

Research on cognition in organizations has its roots in the publications of Simon (1947) on Administrative Behavior, and March and Simon (1958) on Organizations. In these publications, the organization was associated with information processing systems whose picture resembles a nexus of cognitive agents and processes organized through lateral and vertical relations. In this per­spective, the organization benefits individuals and groups by extending their cognitive limitations to more advanced models of rationality (Simon, 1997a, 1997b). However, the meaning ofthis per­spective has been separated by some researchers in two main streams: the computational and the interpretive approaches (Lant & Shapira, 2001). The computational approach investigates the processes by which the organization manipulates information, and it associates the organization with information processing systems. In such a stream, the emphasis is on information and efficiency. This approach is grounded in cogni­tive psychology, cognitive science and artificial intelligence. The interpretive approach examines how meaning is created around information in a social context, and it is related to social collec­tives and knowledge systems. In such a stream, the focus is on knowledge and collectivities. This approach has been grounded in the sociology of knowledge, social psychology of organizations,
social cognition, and, most recently, in knowledge management and organizational learning, whereas this latter subject has also been associated with processes for creating, retaining and transferring knowledge in organizations (Argote, 2007).

Most of the perspectives on organizational cognition are placed somewhere in the continu­ous between such computational and interpre­tive approaches. In this chapter, the authors give special attention to the computational perspective and they use the metaphor of the organization as information processing systems.

In such a perspective, organizational cogni­tion is concerned with the processes which pro­vide agents and organizations with the ability to learn, to make decisions and to solve problems. The main agents of organizational cognition are the participants within the organization and the social networks which they form. In organiza­tions, cognitive processes are supported by their goals, technology and social structure. Moreover, organizational cognition is also influenced by inter-organizational processes and thus by the environment. Therefore, the choice of the organi­zation elements (participants, technology, goals, and social structure), and thus organizational design (Galbraith, 2002), plays a fundamental task in organizational cognition. The cognition of the organization can be represented as a matter of degree whose level depends on the choice of the organization elements. A borader review on organizational cognition is presented in (Nobre et al, 2010; Nobre & Walker, 2011).

In a first perspective, researchers in the field of organizational cognition have associated the concept of cognitive complexity with the degree or level of elaboration in which people, groups and organizations perceive their environment and construct their cognitive maps. In such a case, the degree or level of cognitive complexity can be attributed to the number of hierarchical or vertical levels (or deepness) and the number of horizontal constructs which are integrated into a cognitive map (Calori, Johnson & Sarnin, 1994; Nasser-Carvalho, 2004, 2005); whereas in this association, cognitive maps are viewed as systems (Hall & Fagen, 1956).

In a second perspective, cognitive complexity can also be associated with the concept of degree of cognition in the organization or degree of orga­nizational cognition as introduced in (Nobre et al., 2009a, 2010); whereas degree of cognition can be symbolically associated with tangible and intan­gible measures of processes and representations. Through the participant observation approach, Nobre et al. (2009a: 113-162) presented a case study about an international telecommunications and software business corporation, where they as­sociated the degree of cognition in the organization with levels of organizational process maturity and performance, along with organizational learning results. In a macro view, the level ofthe organiza­tion’s process maturity was defined by the level of elaboration, integration and specification of the technical, managerial and organizational pro­cesses, routines and norms (Nobre et al, 2009a: 122-132), which were most based on the Capa­bility Maturity Model (CMM) policies, recom­mendations and guidelines for software process improvement (Paulk, Weber, Curtis & Chrissis, 1994). In this macro part, the degree of cogni­tion in the organization could be associated with one of the five CMM maturity levels. In a micro view, the organization’s process performance was associated to concepts and measures of customer satisfaction and process quality, whereas these concepts were first socially constructed by a group of software project management and engineering experts in the corporation of study; second, these concepts were explicitly represented through mental models described by IF-THEN linguistic rules; and third, these concepts were mapped into a two-dimensional linguistic phase-plane which indicated the implications ofantecedents (i. e. inde­pendent constructs or variables) to the consequents of customer satisfaction and process quality (i. e. dependent constructs or variables). In this micro part, the organization’s process performance was associated to a set of quantitative indexes about customer satisfaction and process quality which were calculated through the computational mod­eling and simulation of the IF-THEN linguistic rules. Through these approaches, the authors achieved qualitative analyses and quantitative measurements which indicated that improvements in the levels of organization process maturity and performance were associated with improvements in the degree of organizational cognition; and also that improvements in organizational learning could be associated with improvements in the degree organizational cognition.

Similar methods have been adopted by other researchers who associated organizational per­formance and productivity gains with practices of organizational learning (Argote, 2007).

Therefore, in this chapter, the concept of degree of organizational cognition can be understood as synonymous with cognitive complexity at the organizational level of analysis. In such a case, degree of organizational cognition involves a whole picture about the cognitive processes and representations at the organizational level, and this macro picture is greater than the sum of the individual cognitions.

Human vs. Organizational Cognition

Organisms ofthe ecological system have evolved and improved their abilities and mechanisms for fitness and adaptation in the environment. Among such organisms, the human being is the specie that has found the highest probability to survive, to reproduce, and to continue evolving and developing. Such a predominance of humans is a particular privilege provided by the evolution oftheir brain, emotional, and cognitive processes (Heyes & Huber, 2000; Simon, 1983). Among the results of such a continuous evolutionary path are their abilities to search information, to organize knowledge, to make decisions, to learn, and to solve complex problems. Humans adapt to the environment, and they also change the environment to their own needs. In such a con­tinuum, humans have been transferring some of their abilities to systems, and most important, to machines and organizations (Nobre et al., 2009a, 2009b). Certainly, one of the main rationales for organizing can be explained by the perspective that organizations benefit individuals and groups by extending their cognitive, physical, temporal, institutional, and spatial limitations (Carley & Gasser, 1999).

In such a perspective, while human cognition is part of a natural system, cognition in organizations is part of a symbiosis between natural (human) and artificial systems because it involves the art of design (Simon, 1996). Therefore, the cognitive ability in the organization can be changed and im­proved through processes of organization change and design. Hence, the degree of cognition in the organization is contingent upon the goals, the social structure, the participants, the technology and the environment of the organization.

Organizational Intelligence, Autonomy, Learning, and Complexity

Like organizational cognition, definitions of or­ganizational intelligence, autonomy, learning, and complexity are proposed in (Nobre et al, 2009a, 2010; Nobre & Walker, 2011). Nevertheless, they are briefly defined in this subsection.

Organizational Intelligence

Intelligence is a general mental ability (Schmidt & Hunter, 2000), which depends on rational and emotional processes (Goleman, 1994). Rational process or rationality is the ability to follow pro­cedures for decision making and problem solving in the pursuit of goals (Simon, 1997a). When rational processes lead individuals to satisfactory (satisfice) outcomes, rationality can be associated with intelligence. Emotional process (Scherer, 1982) is less procedural than rationality and it is less purposeful in the context of achieving goals. However, researchers have shown that emotions play an important part to motivate, to direct, and to regulate actions in the service of goal pursuit (Bagozzi, 1998; Keltner & Gross, 1999; Keltner & Haidt, 1999). When emotional processes lead individuals to excel in life, emotion can be as­sociated with intelligence. Complementarily, while emotion influences cognitive processes such as attention, learning, decision making, and problem solving (Goleman, 1994), cognition is in the service of emotion when interpreting stimuli (Plutchik, 1982) and regulating emotional pro­cesses and states. Therefore, intelligence, and in particular, intelligent behavior, depends on cognitive and emotional processes.

Organizational intelligence can also be associ­ated with degrees of intelligence in the organiza­tion. However, while organizational cognitions are associated with cognitive processes and representations in the organization, organizational intelligence is associated with the degree in which the organization satisfy or satisfice (Simon, 1997b) its goals and sub-goals. Therefore, the greater the degree of cognition in the organization, the greater is its chance to exhibit intelligent behavior (Nobre et al, 2009a, 2010).

Organizational Autonomy

Autonomy is the ability of individuals, groups, and organizations to act through the use of cognition. Autonomous organisms are continuously in the pursuit of intellectual independence and therefore they are continuously attempting to improve their cognitive abilities. Similarly to cognition and intelligence, autonomy is a matter of degree. The degree of autonomy of individuals, groups and organizations improves as much as they interact with the environment by capturing, processing, creating, storing, exchanging and managing new resources. In such a view, organizations with higher degrees of cognition have higher degrees of autonomy (Nobre et al., 2009a, 2010).

Organizational Learning

Organizational learning has been associated with the creation and management of knowledge in organizations (Argote, 2007; Dierkes, Antal, Child & Nonaka, 2003). In psychology research, learning is the process of making changes in the individu­als’ mind and behavior through experiences along with cognitive, emotional, and environmental influences (Bernstein, Penner, Clarke-Stewart & Roy, 2008; Illeris, 2007; Lefran^oies, 1995; Minsky, 1986; Reed, 1988). In such a process, learning involves acquiring, enhancing, or making changes in one’s knowledge, skills, values, and world views. This work supports this definition and it puts forward the perspective that organizational learning is the process of making changes in the organization’s elements (goals, social structure, technology, and participants) and behavior through experience, cognition, emotion, and environmen­tal influences, for the organization benefits. Such a perspective implies relations on the effect of or­ganizational learning on organizational cognition, and vice-versa. On one hand, it is plausible to say that organizational learning affects organizational cognition, and more specifically, the degree of organizational cognition, by changing cognitive processes and representations in the organization. On the other hand, it is also plausible to state that organizational learning depends on organizational cognition, and more specifically, on cognitive pro — cesses and representations, for the corroboration of change, and for the creation and management of knowledge in the organization. The process of change in the organization follows mechanisms and models which are mostly based on principles of feedback control, adaptive and learning systems originated in the broad fields of cybernetics and general systems theory (Ashby, 1968; Bertalanffy, 1968; Buckley, 1968; Wiener, 1961). Well-known models of organizational learning include single­loop and double-loop types (Argyris & Schon, 1978) along with meta-learning which concept was introduced in Biggs (1985) to describe the state of being aware of and taking control of one’s own learning. Further studies on the concept of meta-learning and its distinction from deuteron and planned-learning are discussed in Visser (2007); and the use of organizational meta-learning for the construct of dynamic core competencies is presented in (Lei, Hitt & Bettis, 1996).

In such a view, cognition is what provides individuals, groups and organizations with the ability to learn. Therefore, organizations with higher degrees of cognition have higher capacity or degree of learning (Nobre et al., 2009a; 2010).

Organizational Complexity

This chapter defines the level of complexity of the organization as contingent upon its degree of cognition. Therefore, the complexity of organiza­tions are synonymous with their cognitions which are processes used to solve complex tasks. Hence, the greater the degree of cognition of the organi­zation, the greater is its ability to solve complex tasks (Nobre et al., 2010).

Environmental Uncertainty and Complexity

Environmental uncertainty can be associated with the level of uncertainty that the organization, groups and participants perceive or sense from the environment (Ducan, 1972). The complexity of the environment is contingent upon the level of uncertainty that it represents to the organization. Similarly, the complexity of a task environment is contingent upon the level of uncertainty that it represents to the organization during task execu­tion and completion. Therefore, it can be asserted that the greater the level of environmental com­plexity, the greater is the level of environmental uncertainty that the organization confronts and needs to manage.

COGNITIVE MACHINES

Initial lines of contribution on the perspectives of cognitive machines in organizations were first touched in (Nobre, 2008; Nobre et al., 2009a, 2009b).

Cognitive machines are information processing and knowledge management systems which unify computational and cognitive strengths of humans and computers. They are necessary when we need to extend the reasoning or mental capacity of hu­mans, groups and organizations to more advanced models of cognition. Cognitive machines are agents whose processes of functioning are mainly inspired by human cognition. Therefore, they have great possibilities to present intelligent behavior. When participating in organizations, cognitive machines are agents of organizational cognition and they contribute to improve the degree of cognition, intelligence, autonomy, and learning of the organization. Intensive and extensive research on the design and analysis of cognitive machines in organizations is proposed in (Nobre et al., 2009a, 2009b). The design of cognitive machines comprises theories of cognition and information — processing systems, and also the mathematical and theoretical background of Fuzzy Systems (FS), Computing with Words (CW) and Computation Theory ofPerceptions (CTP) (Zadeh, 1973, 1999, 2001). This class of machines has the capabilities to carry out complex cognitive tasks in organiza­tions, and in particular the tasks which involve representation and organization ofknowledge via concept identification and categorization along with the manipulation of perceptions (percept), concepts and mental models. The ability of these machines to manipulate complex symbols described in the form of words and sentences of natural language provide s them with higher levels of information-processing than other symbolic — processing machines; and according to the theory of levels of processing in cognition (Reed, 1988) these machines can mimic, even through simple models, cognitive processes of humans.

Similarly to the definitions of organization intelligence, autonomy, learning, and complex­ity, it can be stated that the greater the degree of cognition of the machine, the greater is its chance to present intelligent behavior; the greater is its autonomy; and the greater is its ability to learn and to solve complex tasks.

The concept of cognitive machines plays an important role in the organizations proposed in this research. These machines participate in the organization and they provide the organization with higher degrees of cognition, intelligence, autonomy, and learning as investigated in (Nobre et al, 2009a, 2009b).

The next section demonstrates the application of some of the new features of Customer-Centric Systems and it enhances the roles of cognitive machines, Cognitive Information Systems (CIS) along with the concept of immersiveness in the new Computational Organization Management Networks (COMN).

COMPUTATIONAL ORGANIZATION MANAGEMENT NETWORKS (COMN)

This section introduces a new kind of organization that implements the main features of Customer — Centric Systems. It contributes by presenting the definition, the structure and the processes of Com­putational Organization Management Networks (COMN) as proposed in (Nobre et al, 2009a). COMN are new organizations whose principles of operation are based on the concepts of Hierarchic Cognitive Systems (Nobre, 2008) along with those of Telecommunications Management Networks (ITU-T, 2000). Structured with functional layers and cognitive roles which range from technical and managerial to institutional levels of analysis, and also equipped with operational, managerial and strategic processes, the concept of Computational Organization Management Networks (COMN) plays an important part in the developments of future organizations where cognitive machines and Cognitive Information Systems (CIS) are prominent actors of governance, automation and control of the whole enterprise. Moreover, this section introduces the concept of immersive systems in order to provide the new organization with the capability of immersiveness.

The Scope of the New Organization

Computational Organization Management Net­works (COMN) fall in the class of organizations that pursue high degrees of organizational cogni­tion, intelligence, autonomy, and learning, and consequently, high degrees of agility and flex­ibility, in order to manage high levels of environ­mental complexity, to operate through intensive mass customization, and to provide customers with immersiveness (Nobre et al., 2008, 2009a).

This chapter advocates that such a kind of new organization has to be equipped with high levels of automation in order to pursue the necessary capabilities to govern, to coordinate and to con­trol cognitive tasks of technical, managerial and institutional levels in the whole enterprise. Hence, it focuses attention to the conception of organiza­tions ofthis type. Therefore, the creation of COMN requires intensive investments in information technology, artificial intelligence and knowledge management systems. This section shows the steps of design of such new organizations.

Cognitive Information Systems (CIS)

The processes with the new organization are man­aged by Cognitive Information Systems (CIS):

• Definition 3: Cognitive Information

Systems (CIS) are Knowledge Management Systems (KMS) that pursue high degrees of cognition, intelligence, au­tonomy, and learning. They are particular classes of cognitive machines, and they are designed to participate in the organization by performing cognitive tasks of all levels and by fulfilling managerial roles in all the layers of the whole enterprise (Nobre et al, 2008, 2009a, 2010).

Participation of CIS in the Organization

Cognitive Information Systems (CIS) participate in the organization by performing cognitive tasks and by fulfilling roles of technical, managerial, and institutional levels. From this point of view, this chapter identifies four major areas of CIS ap­plication in the whole enterprise. These areas are classified into four organizational layers:

a. Element Layer: The operational level

b. Network Management Layer: The primary managerial level

c. Service Management Layer: The second­ary managerial level

d. Business Layer: The strategic level

Functional Layers of the New Organization: Steps of Design

Functional layers play the fundamental part in the definition of the structure and processes for the new organization of COMN. Their concepts are based on the definition of Hierarchic Cognitive Systems (HCS) as introduced in (Nobre, 2008) along with the principles of Telecommunications Management Networks (TMN) architectures which have been proposed by International Tele­communication Union (ITU-T); where ITU-T is the designation ofthe United Nations Specialized Agency in the field oftelecommunications (ITU-T,

2000) . In the organizational architectures ofTMN, agents execute tasks in all hierarchical layers of the organization. Similarly, agent technology (Bradshaw, 1997; Watt, 1997) plays important tasks in the functional layers ofthe new organiza­tion of COMN; where in this chapter, agents are also synonymous with cognitive machines and Cognitive Information Systems (CIS).

This subsection proposes four functional layers for the new organization. It also introduces the roles of the agents that participate in the COMN by governing, controlling and coordinating cog­nitive tasks of all levels in all the layers of the whole enterprise.

Step 1: CIS in the Element Layer: The Operational Level

The Element Layer (EL) comprises a Network Element Layer (NEL) and an Element Network Layer (ENL). The former part (NEL) comprises functional elements that work upon an individual basis, and, therefore, each individual element carries its own motives and fulfils micro-roles. The latter part (ENL) comprises a set of intercon­nected functional elements that work in group, and, therefore, they carry common motives and sub-goals, and they also fulfill micro-roles. In this kind of organization, an element is synonymous with an agent, and an agent is synonymous with a cognitive machine; and thus, a group of inter­connected elements is synonymous with a group of agents that has the same meaning of a group of interconnected cognitive machines. Figure 3 illustrates the two parts of an Element Layer (EL), where a0 n) denotes agents, for n integer.

The roles of Cognitive Information Systems (CIS) in the Element Layer (EL) are concerned with the execution of cognitive tasks for operation, control and coordination of individual elements as well as of groups of interconnected elements. These elements, as individuals and groups, par­ticipate in the whole organization by performing cognitive tasks of technical, managerial, and in­stitutional levels. Therefore, in this particular case, the CIS provide operational, control and coordi — native processes to individual agents and group of agents that participate in the organization.

The Element Layer (EL) demands high degrees of cognition, intelligence, autonomy, and learn­ing from the individual machines as well as from the groups of machines. For these requests, the technology of cognitive machines, along with the methodologies of Soft Computing (SC) (Zadeh, 1994), Fuzzy Logic (FL) (Zadeh, 1973), Comput­ing with Words (CW) (Zadeh, 1999), and Com­putational Theory of Perceptions (CTP) (Zadeh,

2001) , play an important part in the conception of Cognitive Information Systems (CIS).

Applications at the level of Element Layer (EL) have received some attention, for instance,

Figure 3. NEL as a controller of individual agents a(1 n} and ENL as a controller of a group of in­tegrated agents

Ґ NEL )

С ENL j

(аГ) (jiT) (aT)

0*0 (a0~CaP

by researchers who have developed information and decision-support systems for manufacturing operations through the background of fuzzy logic, neural networks and genetic algorithms (Kusiak, 2000; Monfared & Steiner, 1997; Rao et al., 1993; Wu, 1994). Nevertheless, despite achieving some successful results, these managerial and decision — support tools of mathematical and computational background have been constrained by the limita­tions of cognition, intelligence, autonomy, and learning of the existing machines which are mostly encountered in the organizations of today. The application of these machines in Flexible Manufacturing Cells and Systems (FMS) and their coordination through Computer Integrated Manufacturing (CIM) technology, have reached thresholds and limitations of contributions be­cause of their insufficient degrees of cognition, intelligence, autonomy, and learning (Nobre et al., 2009a, 2009b).

Step 2: CIS in the Network Management Layer: The Primary Managerial Level

The united work of individual agents and groups of agents in the Element Layer (EL) forms a set of patterns or clusters which represent the main macro-roles in the organization. Each pattern or cluster is synonymous with a functional network.

The Network Management Layer (NML) com­prises the set of individual functional networks in the organization; and it is equipped with an orga­nizing system constituted by normative structure, processes, technologies, agents and sub-goals, in order to provide management to each functional network upon an individual basis. Therefore, the NML provides the individual functional networks ofthe organization with coordination, control and management of processes, operations and infor­mation that flows through the clusters of agents and groups of agents that participate in the whole enterprise. Figure 4 illustrates a NML managing individual Functional Networks FN,, ,, for m

(1…m)’

integer.

The roles of Cognitive Information Systems (CIS) in the Network Management Layer (NML) is concerned with the effective and efficient use of the NML’s organizing system resources in order to execute cognitive tasks for coordination, control and management of the functional net­works upon an individual basis; where, in this case, a functional network is synonymous with a network of agents and also with a network of cognitive machines. In such a perspective, func­tional networks (and thus networks of cognitive machines) participate in the organization by per­forming cognitive tasks of technical, managerial and institutional levels; and they fulfill opera­tional, management and strategic roles in the whole enterprise.

It is important to emphasize that while Cog­nitive Information Systems (CIS) participate in the Network Management Layer (NML) by managing each individual functional network in the organization, they participate in the Element Layer (EL) by operating and controlling individual agents and groups of agents that participate in the functional networks ofthe organization. Therefore, the NML comprises the management of the EL in the organization.

The performance of managerial roles in the organization is contingent upon the capabilities of the managers and also upon the capabilities of the individuals and groups that the managers supervise. Therefore, it can be stated that the higher

Figure 4. NML as the manager of individual

the degree of cognition of Cognitive Information Systems (CIS), the higher is their capability to manage Functional Networks (FN) in the organi­zation; and that the higher the degree of cognition of the elements of a Functional Network (FN), the higher is the capability of CIS to manage the FN.

Step 3: CIS in the Service Management Layer: The Secondary Managerial Level

The set of functional networks in the organiza­tion forms vertical and horizontal processes and involves sub-goals and goals, where sub-goals represent means for the achievement of more complex goals. Therefore, a managerial system is needed in order to coordinate, to control and to mediate all the operations, processes and informa­tion that flow between the functional networks in the organization.

The Service Management Layer (SML) comprises the set of functional networks in the organization; and it is equipped with an organiz­ing system constituted by normative structure, processes, technologies, agents, goals and sub­goals, in order to provide management for the set of functional networks. Therefore, the SML provides the organization with a managerial sys­tem with the capability to coordinate, to control, to integrate, and to mediate all the operations, processes and information that flows between the functional networks in the whole enterprise. Figure 5 illustrates an SML managing a set of integrated Functional Networks FN(1

The roles of Cognitive Information Systems (CIS) in the Service Management Layer (SML) is concerned with the effective and efficient use of the SML’s organizing system resources in order to execute cognitive tasks of integration, coordi­nation, control and thus management of the rela­tions, operations, processes and information that flows through and between the functional networks in the organization; where, in this case, the set of functional networks is synonymous with the set of networks of agents and consequently with the

Figure 5. SML as the manager ofintegrated FN^ m)

set of networks of cognitive machines in the or­ganization. In such a domain, each functional network can be synonymous with a cluster of services, or in short, a service. Therefore, the Cognitive Information Systems (CIS) in the Ser­vice Management Layer (SML) can also be viewed as agents of management of the whole services in the organization.

It is important to emphasize that while CIS participate in the Service Management Layer (SML) by managing the operations, processes and information between all functional networks in the organization, they participate in the Network Management Layer (NML) by managing each functional network upon an individual basis. Therefore, the SML comprises the management of the NML in the organization.

Applications at the SML and NML have re­ceived some contributions with the advances in Enterprise Resources Planning and Management Systems (EPR) that emerged from the 1970’s. ERP are classes of information technology and management systems which are applied to, and implemented in the whole organization with the purposes of integration, control and automation of data, information and processes. Examples of areas of application of ERP systems include: Manufacturing, Supply Chain, Financials, Cus­tomer Relationship Management (CRM), Human Resources, Warehouse Management and Decision Support System. Applications in the level of the Service Management Layer (SML) will receive greater contributions in the proportion of the continuous advancements in Cognitive Informa­tion Systems (CIS) of high degrees of cognition, intelligence, autonomy, and learning; and thus CIS will play an important role in the SML of new organizations.

Step 4: CIS in the Business Management Layer: The Strategic Level

The Business Management Layer (BML) com­prises all the operations, management processes, strategies and services of the previous layers (i. e. the EL, NML and SML respectively); and it is equipped with an organizing system constituted by normative structure, processes, technologies, agents and goals, in order to provide the organi­zation with capabilities to manage the environ­ment. More specifically, the BML provides the enterprise with a managerial system with the capability to coordinate, to control and to mediate the operations, processes and information between the organization and the environment. Figure 6 illustrates the role of the BML in the organization.

The roles of Cognitive Information Systems (CIS) in the Business Management Layer (BML) are less obvious and less present in the organiza­tions of today. It is concerned with the effective and efficient use of the BML’s organizing system resources in order to execute cognitive tasks for coordination, control and thus management ofthe relations, operations, processes and information in between the organization and the environment. To enhance this application, this chapter presents the concept of immersiveness which idea was first spoken in (Nobre & Steiner, 2002), and further developed in (Nobre et al., 2009a).

The Concept of Immersiveness

It was stated in this research that organizations have to be equipped with structure, processes, goals, agents and technologies which are able to provide them with the capability to pursue high levels of immersiveness, where:

• Definition 4: Immersiveness represents the ability of the organization to interact with agents of the market (either humans or machines) in a friendly way, by immers­ing them into the organization’s operations through approaches such as virtual real­ity, simulation or via real world protocols; and it aims to satisfy customers by captur­ing their exact needs, by customizing and managing the design, engineering and pro­duction of their goods and services, and by delivering their products with efficacy and efficiency.

More specifically, either manufacturing or service organizations, they can immerse their customers by providing them with the scope to interact with some of the life cycle stages of their processes of design, engineering and produc­tion, including those processes of requirements analysis, product design, test, prototyping, demand specification, volume and variety choice. Under this perspective, virtual reality will play an im­portant task in the customer immersiveness; the technologies of cognitive information systems and cognitive machines will provide important contributions in the execution of cognitive tasks such as pattern recognition and vision, natural language processing, decision-making, problem-

Figure 6. BML as the manager that mediates between the organization and the environment

solving, learning, and management; additionally, the internet will play an important part in the con­nection of customers into the new organization. This perspective is illustrated in Figure 7 and it is assumed that such an illustrative immersive system can be configured to provide customers with different levels of access and interaction to the technical and managerial operations of the processes of design, engineering and production in the organization. The dotted lines symbolize the internet which connects customers within the organization; and the continuous lines denote the system operational levels that clients can interact with, in order to capture customers’ exact needs and even emotions, to customize and to manage the design, engineering and production of their goods and services.

Definition of COMN

• Definition 5: Computational Organization Management Networks (COMN) are or­ganizations whose structure, processes, participants, goals and technologies are designed according to the concepts of Functional Layers which include Element Layer, Network Management Layer, Service Management Layer and Business Management Layer. COMN pursue high degrees of organizational cognition and their main participants subsume Cognitive Information Systems (CIS) and cognitive machines.

Structure and Processes of COMN

Figure 8 illustrates the structure of Computational Organization Management Networks (COMN) which is composed by Element Layer (EL), Network Management Layer (NML), Service Management Layer (SML) and Business Manage­ment Layer (BML) respectively.

Figure 7. Illustration of an immersive system

Customers

_ / Payment / 7 Delivery

Requirement Analysis / Design

Prototype / Production

Test / J

Simulation /—

Life Cycle Stages

CONCLUSION

This chapter is the result of the analyses of past and current manufacturing organizations through three complementary perspectives of technology, management and organizational systems theory, as researched in (Nobre et al, 2009a, 2009c); whereas it was found that the convergence of manufacturing organizations to the new features of Customer-Centric Systems (CCS) is contingent upon the continuous growth in the level of envi­ronmental complexity. The chapter emphasized that Customer-Centric Systems (CCS) configure the new technological, managerial and organiza­tional faces which industrial organizations need to have if they want to manage higher levels of environmental complexity in the 21st century.

The contributions proposed in this research were motivated by the principle of incompatibility, and the non-equilibrium state, existing between the continuous growths in the level of environ­mental complexity and the insufficient cognitive capacity of current manufacturing organizations. Therefore, this chapter focused on the general picture of organizations pursuing high degrees of cognition in order to improve their capabili­ties for information processing and uncertainty management. It assumed that improvements in the degree of organizational cognition can lead the organization to achieve higher degrees of flex­ibility and agility, to operate through higher levels of mass customization, and to provide customers with immersiveness. In its broader sense, it as­sumed that such improvements can extend the capability of the organization to manage higher levels of environmental complexity. In such a context, this chapter contributed by presenting the concepts of Customer-Centric Systems (CCS) and Computational Organizational Management Networks (COMN). COMN are new computa­tional organizing models with the capability to implement the features of CCS.

The main contributions and further research are highlighted in the next paragraphs.

On Cognitive Machines, Organizations and the Environment

Cognitive machines are agents of organizational cognition and they contribute to improve the degree of cognition of the organization. Conse­quently, improvement in the degree of organiza­tional cognition contributes to manage the level of environmental complexity and uncertainty that the organization confronts.

On Computational Organization Management Networks

Business Management Layer BML (Strategic Level)

Management and mediation between the organization and the environment

Service Management Layer SML

(Secondary Managerial Level)

Management and mediation between the organization’s functional networks

Network Management Layer NML

(Primary Managerial Level)

Management of individual functional networks

Element Layer EL

(Operational Level)

Operation and control of individuals

Figure 8. Structure of computational organization management networks (COMN)

Computational Organization Management Net­works (COMN) implements the new features of Customer-Centric Systems. COMN are organi­zations whose structure, processes, participants, goals and technologies are designed according to the concepts of Functional Layers which comprise Element Layer, Network Management Layer, Service Management Layer and Business Management Layer. COMN pursue high degrees of organizational cognition and their main partici­
pants comprise Cognitive Information Systems (CIS) and cognitive machines.

Such a kind of new enterprise will play a fundamental part in the processes of engineering, production, logistics and management of goods and services along with the processes of man­agement of transactions, business and electronic commerce in the future organizations and markets. According to Nobre et al. (2009a), COMN will be legally supported with nexus of contracts that as­sign the responsibilities to, and define agreements between, the organization and the designer of the cognitive machines (and cognitive information systems) which are the main participants in the layers of the whole organization. The roles of these new participants will be defined in the normative structure of the organization.

The creation of COMN requires intensive investments in information technology, artificial intelligence and knowledge management systems. This chapter introduced the steps of design of such new organizations.

Nevertheless, some implications of Compu­tational Organizational Management Networks (COMN) must be further investigated. COMN may also be used by some corporations and power-holders for their own benefits, who want to reinforce and to continue supporting the contem­porary society, and a political and economic model of maximization of production and consumption which has generated cultural alienation and in­tense materialism. These have, in turn, destroyed environmental resources and eroded the values and social conditions of humanity.

Further Extensions

On Cognitive Machines and Emotions

The topic of machines with emotions and emotion­al processes in organizations was left for further research. However, it deserves some comments due to its importance in the literature. Whether machines should exhibit emotional behavior, and whether they are able to have emotions or not, are controversial topics among the researchers of ar­tificial intelligence, cognition and social sciences.

By assuming that machines may indeed be able to have emotional processes and emotional behav­ior, the question ofwhether emotions are important to machines or not depends on the motivations of their designers and upon the environment with which they relate. On the one hand, machines with emotions, or emotional machines, might form better relations and social networks with humans in organizations than other machines. In such a view, machine emotion would be relevant for researchers on organizational behavior. On the other hand, machines with emotions might have their own motives and might represent additional agents of dysfunctional conflicts in organizations. In such a view, machine emotion would be a prob­lem for researchers of rational theories. Among the institutions which have been researching the field of emotional machines include The MIT Ar­tificial Intelligence Laboratory at Massachusetts (Breazeal, 2000).

On Cognitive Machines vs. Humans in Organizations

Are cognitive machines better agents of organiza­tional cognition and organizational learning than humans? Are they better agents of organization performance and productivity than humans? Such questions rely on the statement that: if we assume that the cognitive roles in organizations have performance and outcomes which can be attributed to either humans or machines, without any distinction, then we are ready to consider machines as participants within the organization similarly to people. This perspective involves a rational comparison between machines and human’s performance if we assume that they compete for the same roles in the organization. Such questions need to be further investigated in order to derive conclusions about the economic, political, social and technological implications of cognitive machines for the society (Nobre et al, 2009a).

Challenges and the Future of the Industrial Organization

While the characteristics of the elements of the organization will change, evolve and develop continuously towards higher levels of cognition and complexity, the purpose of existence of the organization will remain the same or will not change in the same proportion of its elements (Nobre et al., 2009a). The former part, which is concerned with the elements of the organization, will move towards high levels of automation, and it will include machines with high degrees of cognition, mainly in those areas at upper layers and levels of the organization; and thus they will provide organizations with more capabilities of computational capacity along with knowledge and uncertainty management. Therefore, new organizations of this kind will be able to operate in, and to manage higher levels of environmental complexity and uncertainty than organizations of today. These transformations towards new orga­nizations will have implications for the society and this is a topic of further research (Nobre et al, 2008, 2009a, 2009b). The latter part, which is concerned with the purpose and the existence of organizations, will remain the same and for sure will not change in the same proportions to the evolutions in the organization elements. This is because the individual motives and the organizational goals which are pursued by human kind will not change over time into the political, economical and social facets of this society.

One day, perhaps not so far in the 21st century, worldwide organizations and their executives will have the ability to perceive, to sense, to decide and to act based on new models of organizing and management thought which are grounded in concepts of systemic sustainability; whereas these new models should require the reconciliation of en­vironmental, social and economic demands—the “three pillars” of sustainability. It is in such a new context that organizations and their participants will be challenged to decide on whether they are ready to create competitive advantage without affecting the balance and equilibrium of such a triad. It raises the question about the endurance and survival of the human species.

Tools That Drive Innovation: The Role of Information Systems in Innovative Organizations

Jason G. Caudill

Carson-Newman College, USA

ABSTRACT

The purpose of this chapter is to examine computer technology as a tool to support innovation and innovative processes. The primary problem that this chapter is intended to address is the multitude of widely held misconceptions that seem to exist regarding technology and innovation; technology is not innovative in and of itself. The primary method of research for this chapter is a literature review and case study method examining how technology is being successfully integrated into innovative processes in industry. Specifically this chapter focuses on technology’s role in communication and creativity, two of the many activities found in an innovative process. Findings indicate that while directly connecting technology use to innovation is difficult, technology can play a substantial role in facilitating the innova­tive process. Thus, technology is a qualifier for many innovative processes, a resource that is necessary for the work of innovation to take place.

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

INTRODUCTION

In modern, developed countries around the world commerce, and by extension life itself, have changed dramatically in the past few decades. Commerce ultimately touches every aspect of life.

DOI: 10.4018/978-1-61350-165-8.ch034

Businesses produce the goods that people need to live and provide the jobs that people work to earn money to purchase what they need. People’s incomes and spending habits, in capitalist markets, drive businesses in what they do to capture market share and generate profits. While this connection
between people and economic activity is certainly not new, the way in which much of this interac­tion occurs is.

The rise of ecommerce and the globalization of commerce have changed not only the methods by which people consume goods and services, but the very development ofthose goods and services. Innovation is central to this change as, “ICTs (in­formation and communication technologies) foster a broad spectrum of innovation activities which involve the individual, organizational, industrial, and national levels of economic productivity” (Ho, Kauffman, & Liang, 2008, p 1). Markets of all types are more dynamic now than at any time in the past. Product development moves more quickly, products change more often, and consumer expectations are for this to happen and continue to happen. Brynjolfsson and Schrage (2009) explain that, “Technology is transform­ing innovation at its core, allowing companies to test new ideas at speeds—and prices—that were unimaginable even a decade ago.”

In today’s digital age innovation and tech­nology are inexorably linked. Baldwin and von Hippel (2009) explain that technologies like the personal computer and the Internet provide more opportunities for innovative activities to occur in more forms. Many people may feel that technol­ogy by virtue of its existence is innovative, and that applying technology to any situation means that innovation is taking place. While perhaps understandable this is not at all accurate. This chapter will discuss technology as a tool, an aid to the innovative process. There are many different ways that technology can be appropriately applied to innovation, and innovation has benefited from these applications, but an innovative process must exist before technology can serve as an aid to it. Technology in this sense is not in itself a creator of competitive advantage, but it does serve as a facilitator to innovative activities through which advantage can be gained. The focus ofthis chapter is to introduce ideas of technology applications as tools through which innovative activities can be fostered, and with which efficiencies and ef­fectiveness can be improved.

TECHNOLOGY AS A TOOL

Technology is an incredibly powerful force in the developed world. Compounding not only tech­nology’s importance but also its impact, the rise of digital technology and its penetration into the market has been unrivaled in human history. In just a few short years personal computers moved from very expensive diversions for a limited number of technically-engaged hobbyists to a common household appliance. In just a few more years they moved from being stand-alone devices to networked devices that brought the world into living rooms and offices. Ultimately, such connectivity moved from full-sized computers to handheld devices in the form of smartphones.

Such devices are constantly changing and the highly competitive marketplace brings new features and new models to customers on a fre­quent basis. Technology is inherently innovative, particularly where competition among technology providers is concerned. Where misunderstanding often occurs is the idea thatjust by having technol­ogy in a process that process becomes innovative.

Technology is, and always has been, nothing more than a tool. Dosi (1988) explains that, “In very general terms, technological innovation in­volves the solution of problems-for example, on transformation of heat into movement, shaping materials in certain ways, producing compounds with certain properties-meeting at the same time some cost and marketability requirements” (p 1125). Notice that not only does technology solve problems, but it solves problems within the bounds of what is acceptable in the marketplace. The innovation is not the technology, rather the technology helps to find the answers as part of an innovative process.

As a tool technology can serve to enhance in­novation. Better communications, faster analysis of data, greater ability to assess alternatives, and many other factors make digital technology a great asset to the process of innovation. Technology is not a traditional capital investment, but serves a more general purpose for an organization; invest­ments in information technology can contribute to higher productivity and it is such related contributions that provide a return on technol­ogy investments (Brynjolfsson & Hitt, 2000). Not only can technology enhance innovation through providing focused process improvement, it can also impact the innovative nature of an organization as a whole. Bartel, Ichniowski, and Shaw (2007) noted in their study on information technology and innovation that, “.. .the adoption of new computer-based IT also increases the skill requirements of workers, notably technical skills, while also promoting the adoption of new human resource practices” (p 1723). Not only do tools give workers more options, but the presence of new tools can change the practices and capabili­ties of those workers. This chapter will be dealing primarily with today’s digital technology, but the concept of technology and integration holds true for all types oftechnology; effective tools enhance innovative processes.

TECHNOLOGY, INNOVATION, AND COMMUNICATION

Sometimes innovation is the result of a single individual finding enlightenment or inspiration to change the way something is done or made. More often, particularly in organizational contexts, in­novation is the result of collaboration, teamwork, and ultimately communication. Fagerberg (2005) explains that:

Thus, what we think of as a single innovation is often the result of a lengthy process involving many interrelated innovations. This is one of the reasons why many students of technology and innovation find it natural to apply a systems perspective rather than to focus exclusively on individual inventions/innovations (p 4).

Historically, communication technologies have been of substantial importance to humanity. From clay tablets to parchment scrolls to Gutenburg’s printing press the written word made archiving and disseminating information ever more accessible (Schneiderman, 2000). Going forward broadcast media, radio and television, and then the Internet have reached people in remote locations all over the world and changed daily lives in society (Schneiderman, 2000).

Von Hippel (2002) examines innovation net­works as the development mechanism for free and open source software applications. Communica­tion is part of that innovation network, explained in context as, “.individual users do not have to develop everything they need on their own: they can benefit from innovations developed by oth­ers and freely shared within and beyond the user network” (Von Hippel, 2002, p 1). The process of innovation is certainly much more than just communication, but communication does play a key role in innovative activities. Increasingly, this communication takes place through the use of technology.

Herrmann (2008) discusses the field of Com­puter Supported Collaborative Work (CSCW), which focuses on using computers to support creativity. Herrmann’s work explores the idea that while different people engage in the creative process in different ways technology tools are flexible enough to support individuals according to their preferred work habits. These technology tools can take many different forms in CSCW, including: supporting the large picture—visu­alization of rich material, malleability of shared material and stimulation of variations, support of convergence within evolutionary documentation, smooth transitions between modes of creative collaboration, and integration of communication with work on shared material (Herrmann, 2008).

Awazu et. al. (2009) identifies five roles of information and communication technologies (ICTs) in innovation: understanding idea sources; documenting ideas and sources; distribution and sharing ofideas for cross-application; idea design, testing, and refinement; and idea commercializa­tion. These ICT roles mirror Herrmann’s (2008) view ofthe benefits oftechnology tools in CSCW. Supporting the large picture and visualizing rich material can be support functions for document­ing and distributing ideas. Shared material and stimulation of variations can support distribution of ideas as well as idea design, testing, and refine­ment. Support of convergence can benefit idea commercialization. These tools of technology — enabled collaboration align with the innovation benefits of ICT.

In order to successfully fill these roles ICTs must be properly implemented and managed in the firm. This is not a static effort, rather continuing monitoring, assessment, and updating must occur in order for a firm to apply technology towards maintaining continual competitive advantage. McAfee and Brynjolfsson (2008) define a three — step process for doing so:

• Deploy: adopt a uniform technology platform;

• Innovate: design better ways of doing work;

• Propagate: use IT to replicate process innovations.

If technology is properly managed then it can successfully fulfill its role to support communi­cation and collaboration as a component of the innovative process.

Communication and collaboration may be somewhat interchangeable terms. If people pursu­ing innovative work are communicating, they are in effect collaborating, and ifthey are collaborating with others then there must be communication. Regardless ofthis connection the exchange ofideas is critical to the innovative process. The difficulty in many situations is that in any circumstance teamwork poses challenges to organization and management. In an innovative effort, however, a common space must be developed. The “… abstract territory in which design search takes place.” (p 1297) has been termed the design space (Bald­win, Hienerth, & von Hippel, 2006). Herrmann’s

(2008) points about the assistive possibilities of technology and innovation can be part of creating the design space to provide innovation a place in which to happen.

Innovation thrives on the input of multiple perspectives, but often such diverse inputs create overly complex decision environments. Inter-or­ganizational collaboration, partnerships between multiple organizational entities, is an important part of business innovation today, but even with such great potential value as many as 60% of such ventures fail (Faems, Van Looy, & Debackere, 2004). As industry continues to progress towards a more global operating environment there are certainly opportunities for more diverse perspec­tives to act as inputs for innovative processes. Concurrently, there are also many more compli­cating factors, ranging from global differences in time zone, the impracticality of physical meeting spaces, and language barriers. Additionally, tech­nology can increase participation in innovative processes by better incorporating persons with disabilities into active participation. Technology in the form of CSCW can offer technical solutions to these organizational issues and, by eliminating the barriers, enhance innovative activities.

In relation to time zone issues, asynchronous communication technologies are a familiar tool to many today. Discussion boards and other forums, in addition to older technology like e-mail listservs, give contributors the opportunity not only to share their ideas at any time but also to have those ideas archived as a part of the innovative process for later reference. Both the ability to communicate effectively across time zones, effectively creat­ing a 24-hour a day office, and the archiving of conversations can aid everyone involved in the process. If technologies are used that provide for the threading of discussions effectiveness is further enhanced by keeping topics closely connected for better understanding of all involved.

Asynchronous exchanges do have their limitations and sometimes the only way to ef­fectively resolve development issues is through live, synchronous exchanges. Globalization has been a complicating factor in such meetings for many years due to the distances separating team members or contributing groups in different coun­tries. Through the economic downturn that began in 2008 this difficulty has been compounded by the critical need for firms to reduce expenditures, travel being one such cost.

Virtual meeting spaces are a technical solution to the problem. While time zone complications may make scheduling the meeting difficult there are multiple technologies available that support live audio-visual exchanges among multiple par­ticipants from any location while also providing tools to share files, display materials in the group environment, and even share the ability to write and draw on a virtual whiteboard. Such technolo­gies can provide more frequent synchronous work environments than are possible with travel between multiple locations, thus enhancing the innovative process for all involved. Also, many ofthese virtual workspace technologies can record and archive all activity in the room so that valuable ideas are not lost. Not only does the archive preserve information for future reference of attendees, it also allows those individuals who were unable to attend the meeting to experience the full exchange of ideas for a more thorough understanding of the meeting’s conclusions.

Any exchange, whether synchronous or asynchronous, ultimately depends on a common language existing among the participants. While still in its early stages there are technical solutions to language barriers. Software solutions exist that can roughly translate written materials online and display the result in a variety of languages for the reader. Admittedly these technologies are not a substitute for a fluent speaker of the language, but today’s solutions can serve as a stop-gap measure when absolutely necessary. In the future such technologies will hopefully advance to a point that language barriers are virtually invisible through electronically-mediated communication.

All of the previously discussed solutions and others can also be very useful in giving individuals with a broad range of disabilities the opportunity to take an active role in the innovation process. Computer-mediated communications provide users with auditory or visual disabilities many opportunities to engage in the exchange of ideas through either text-to-speech or speech-to-text conversion tools. These tools, properly imple­mented, can provide mediation for such dis­abilities in both synchronous and asynchronous work environments and, by extension, improve the innovation process by bringing more ideas to the table.

Beyond such basic applications technology provides many other valuable opportunities for disabled persons to be incorporated into innova­tion processes. The live streaming of video and synchronous online communication can serve to bring mobility-impaired persons on-site for projects that they could not physically negotiate. By seeing what the group is seeing and having a medium through which they can communicate in live time with the on-site team this process can include people who in the past would have been forced to rely on photographs or videos after the fact. Also, such technologies are not only limited to serving those with disabilities; these processes can also bring contributors unable to physically attend such a meeting into the process. Regardless of who is served, the inclusion of more people in the live environment can produce more insights and improve the overall efficiency of the innova­tive process.

Overall, communication in innovation is mov­ing from the traditional Web 1.0 environment to Web 2.0 solutions. Fischer (2009) approaches technology contributions to innovation from a Web 2.0 perspective, explaining that current technologies have driven a shift from information consumer culture to cultures of participation that create content. This participatory culture is seen as an advance in innovative capabilities, explained as, “End-user development is an essential compo­nent of this transformation, but its impact is much broader: this transformation represents a change and new opportunity for social production, for mass collaboration, for civic and political life, and for education” (Fischer, 2009, p 4). Collaboration in multiple arenas, facilitated by technology, can enhance innovation efforts.

Of particular interest in the incorporation of Web 2.0 technologies is the generational shift occurring in the workforce. As the baby boom­ers begin to exit the workforce organizations are looking at increasing numbers of Generation X members in leadership positions, a generation much more comfortable and familiar with tech­nology. More important to Web 2.0 integration in organizations is the entry of Generation Y mem­bers into the workforce in ever-growing numbers. These workers are easily the most techno-centric workers in history and expect connectivity through social media and online learning to be the standard rather than the exception.

As increasing numbers of workers become comfortable with and demanding of Web 2.0 technologies their work, including innovative pursuits, come to depend on such communication technologies. The impact of these technologies is beyond simply giving workers another com­munication medium. Because of changing work and social practices social media is becoming a necessary tool to engage people in communication and, by extension, innovation.

Communication is the first of the two major categories oftechnical contributions to innovation. Perhaps the best illustration of the value of com­munication to technology today is an observation of how many people use computers. Before the Internet became commoditized and commonplace people often spent time on their home computers just working independently. With Internet con­nectivity an expectation now a computer without access to the network quickly becomes an almost useless device. People expect technology to con­nect them to others.

TECHNOLOGY, INNOVATION, AND CREATIVITY

Leonard and Sensiper (1998) use the definition, “The process of innovation is a rhythm of search and selection, exploration and synthesis, cycles of divergent thinking followed by convergence” (p 116). This innovative process is cyclical, with multiple decision cycles occurring as a part of cre­ative group activity (Leonard & Sensiper, 1998). Leonard and Swap (1999) discuss creativity, and its myths, in relation to innovation. Their defini­tion ofinnovation is that it is, “.the embodiment, combination, and/or synthesis of knowledge in novel, relevant, valued new products, processes, or services” (Leonard & Swap, 1999, p 7). The process of creativity can be difficult to precisely define, yet there is an inherent understanding of what creativity is; it is the creation of a new idea, new device, or new work, something new. The question for the technologist is how to enhance the creative process, the process of innovation, with technical tools. Leonard and Swap’s (1999) definitions of and myths about creativity are listed in Table 1 for reference.

There are multiple approaches in the literature regarding how to support, enhance, and assess creative action and, by extension, innovation. Leonard and Sensiper (1998) explain that creative cooperation is critical to the process of innovation, no matter what the intended product of that in­novation may be. By understanding how creativ­ity works it is possible to connect defined actions to support provided by the inclusion of informa­tion systems in the process. These connections can then serve to improve the correct application of technologies to the creative process.

Huber, Bretschneider, Leimeister, and Krcmar,

(2009) introduce the generator of excellence (GENEX) framework for innovation. The frame­work consists of:

• Collect: searching and browsing digital li­braries, visualizing data and processes;

• Relate: consulting with peers and mentors;

• Create: thinking by free association, ex­ploring solutions (what-if tools), compos­ing artifacts and performances, reviewing and replaying session histories;

• Donate: disseminating results.

Table 1. Definitions of and myths about creativity (Source: Leonard & Swap, 1999)

Definitions of and Myths About Creativity

Definitions of Creativity

Myths About Creativity

•…that process which results in a novel work that is accepted as tenable or useful or satisfying…

•…it is both novel and appropriate, useful, correct, or valuable response to the task at hand…

• A company is creative when its

employees do something new and potentially useful without being directly shown or taught.

•…the production of something that is both new and truly valuable

•…involves a process that is extended in time and character­ized by originality, adaptiveness, and realization

• Creative output depends on a few, often flamboyantly different indi­viduals

• Creativity is a solitary process

• Intelligence is more important than creativity

• Creativity can’t really be managed

• Creative groups are found only in “The Arts” or in high-technology companies

• Creativity is relevant only to Big Ideas

• Creativity only involves coming up with new ideas

While all of these activities have in one way or another always existed as a part of the innova­tion process technology serves to enhance them to improve innovation.

Schneiderman (2000) continues the exploration of the GENEX process. Specifically, he explains that the four phases of the GENEX framework are not strictly linear, rather they may be cyclical and iterative, repeated multiple times to arrive at a conclusive solution. This discussion mirrors Leonard and Sensiper’s (1998) discussion of the innovative process as being similarly cyclical. Such cycles often occur in group contexts and as such require active and archivable communica­tion methods to support the process. Innovation is certainly more than creativity, but as creativity is a key part of innovation and there are parallels between the creative and innovative processes the role of technology in supporting creativity does feed innovation.

Components ofthe GENEX framework can be identified in other creativity research. Shneider — man (2007) addresses technology as a medium through which to engage in creative activities that lead to innovation, explaining that, “Creativity support tools extend users’ capability to make discoveries or inventions from early stages of gathering information, hypothesis generation, and initial production, through the later stages of refinement, validation, and dissemination” (p 2). Creativity support is defined as a combination of two factors, specific tasks that support discovery and the capacity to generate multiple alternatives (Shneiderman, 2007).

Gathering information connects to the GENEX framework concept of collecting. Technology’s role in information collection is difficult to over­emphasize in today’s connected world. Where only fifteen years in the past a team of research­ers might have to make phone calls or written requests via mail to obtain data from past projects performed by others, particularly international works, the same information is now available through digital technology. If the documents are not available directly online then e-mail contact can bring electronic versions of the document as quickly as differing time zones will allow. Such online repositories of knowledge and the digitalization of many older text works greatly enhances people’s ability to collect information. Such technology directly enhances the collection stage ofthe GENEX framework. One technology currently in use is a branch of computer aided information (CAI) called patent analysis/patent map tools that assists “.the users in searching, collecting, analyzing, and visualizing patent data” (Yu, Wu, & Lien, 2008, p 524).

Stage two of GENEX, relate, is a communi­cations aspect of technology. This is a critical component that links the collection of informa­tion to the analysis and use of that information. Communication is the process that transforms data in the collection stage to information in the create stage.

Creation is the point at which the foundational work of collecting and relating grows into new ideas. This GENEX stage can relate to hypothesis generation, initial production, refinement, and validation. In initial stages what innovators create is ideas. Brown (2008) explores the creative prod­uct analysis model, which includes the concepts of novelty, resolution, and style. The primary focus of this work is on the ability of technology to facilitate the creation of more ideas, which by extension lead to more innovative solutions. In support of this concept, Brown cites Linus Paul­ing’s statement that, “The best way to have a good idea is to have lots of ideas.”

Lots of ideas are the foundation of hypoth­eses. From the generation of hypotheses comes the initial production of concepts. This stage too can benefit greatly from technical innovation. A second branch of CAI, Innovative Solution Generation, is one technology that can help us­ers to create innovative problem-solving models (Yu, Wu, & Lien, 2008). The collaborative ben­efits of technology have already been discussed, but initial production can greatly benefit from technology in other ways. The virtualization of products, components, or other parts of an inno­vative product or idea can be greatly enhanced by the use of technology. Rapid prototyping is an industry standard where much time is saved by creating and testing new physical devices in a virtual space. Not only does the speed of the system lead to faster development cycles but the relatively low cost allows for the exploration of many more possibilities. To paraphrase Pauling, lots of ideas better lead to good ideas.

Following this initial production refinement takes place. The value of prototyping and in­vestigative technologies cross over from initial production to refinement as many of the same technologies and same processes can help in­novative workers to refine their many ideas. As the process progresses many ideas are funneled to fewer, more practical and more probable ideas. Refining, much like other stages ofthe process, is enhanced in speed and effectiveness by technical tools. Communication and rapid prototyping are both parts of this refinement.

Past the rapid prototyping technologies testing technologies enhance refinement. At the refine­ment stage the bulk of ideas should be eliminated, with the refinement stage finding and defining shortcomings of sub-optimal ideas. Rej ected ideas at this stage are not failures, and can improve the ultimate solution, a process that is also technology — enhanced. Failure points, and also positive aspects, of ideas discovered during the refinement process can be archived and assessed using technical tools. Ideally, these individual items will be compiled to enhance the final selection. With technology creating more ideas and faster initial production technology is also needed to organize and capi­talize on what is learned by refining the product from so many ideas to only one or a small few.

Once that one or small few ideas have been reached through refinement those selected con­cepts must be confirmed as valid ideas. The same technologies already applied work here and offer many of the same advantages. The validation process can move more quickly through the use of technology and it may also be possible to per­form detailed validation analysis of more ideas, thus providing an in-depth analysis of more ideas than would be possible with other methodologies.

With validation complete and a final solution identified the donate stage ofGENEX, dissemina­tion, is the final part of the innovation process. This may be the easiest technology connection to identify as the communicative and marketplace forces of the Internet make dissemination of new ideas faster and easier than at any previous point in history. Integrating Web 2.0 technologies into the process makes this dissemination even faster as others with an interest in the discovery post and spread the news on their own, independent of the organization.

These individual stages of innovation help to produce a map of where and how technology can enhance the innovative process. The goal of technology integration in any field, however, is to create and enhance an overall system of productiv­ity. Hekkert, Suurs, Negro, Kuhlmann, and Smits

(2007) look beyond individual technologies and address technology tools as part of an overall in­novative system, defining an innovation as, “.. .the successful combination ofhardware, software, and orgware…” (p 414). To understand how innovative systems work, including the role of technology within such systems, Hekkert et al. propose that the activities of an innovation system should be mapped to identify and understand their functions. These functions include: entrepreneurial activi­ties, knowledge development, knowledge diffu­sion through networks, guidance of the search, market formation, resources mobilization, and the creation of legitimacy/counteract resistance to change (Hekkert, et al., 2007).

Hekkert’s (2007) work highlights several important points, not the least of which is the reaction ofpeople in the organization. Regardless of what technologies are applied to the innova­tive process people are the core resource. If the people involved in the process do not support the technologies being applied to innovation then the system as a whole is likely to fail. With that in mind, creating legitimacy and counteracting resistance to change is an early priority in any innovative process. Human resource management sources often identify employee buy-in as one of the very first steps in any change process and that holds true for innovative processes.

Much of the rest of the list proposed by Hek — kert, et. al. involves aspects of innovation and their related technology enhancements that have already been addressed here. The important new aspect highlighted by the list is that while these different components have been identified and discussed as individual components in an overall innovation process they are, in practice, parts of an overall system, each depending on the oth­ers. In this interdependent system of innovation every part of the process shifts when any part of the process shifts. When examining the role that technology plays in such a system the impact of technology enhancements is greatly magnified. Improving the speed or efficiency of a single part of the process or allowing for more exploration in any stage of development impacts the overall performance of the process as a whole. Thus, the potential impact of technology integration in the innovation process can be exponential.

SOLUTIONS AND RECOMMENDATIONS

Utilizing the advantages offered by technology in innovative processes in any kind of organiza­tion is no longer an option; rather the question is how much technology will be used. This situation presents many unique challenges to an organiza­tion engaged in innovative work. The choices of technology, workers’ use of the technology, and overall structure of the effort must all be carefully determined.

Across all categories of technology solutions for innovation training for all involved is highly recommended. At an organizational level there must be decision-makers who understand the role of technology in the organization’s strategy. A fundamental recommendation ofthe Management Information Systems (MIS) field is that strategy should drive technology; technology should never drive strategy. This means that decision-makers need to be properly trained in how to assess the technical needs of their organizational programs and the best ways in which to apply technology to the problems.

Once technology choices are made workers who will interact with the technology must be trained on how to effectively use that technology. For the tools to be effective users must know how and when to apply them, which is where training for personnel enters into the equation. A comprehensive, integrated training program for employees should be established in advance ofnew technical integrations for innovation processes.

Tying into the issue of strategy there should also be a concerted effort towards structuring the use of technology in the organization across all aspects of innovation and other activities. The nature of structure will change for each unique organization as the structure of the technology implementation will need to match the structure of the organization. Executing such a match will require detailed study by a cross-functional team drawn from throughout the organization. Done properly, this effort will help to ensure a successful use oftechnology to enhance innovative processes.

FUTURE RESEARCH DIRECTIONS

There are many opportunities for future research connecting technology and innovation. Part ofthe breadth of opportunities connects to the difficulty of measuring innovation. Because innovation is, by its very nature, the creation of something entirely new there is not necessarily an existing point against which to measure the effort. With the lack of a firm starting point assessment becomes much more challenging. This certainly does not mean that effective research cannot be done, but there are many different approaches that could be useful, with some situations benefitting from multiple studies using varied methodologies.

Future research should drive deeper into the subject and generate data from innovative fields. Possible models for such research may include broad surveys of professionals engaged in innova­tive processes to reveal what technical tools they use and how those tools complement each other and the work preferences of the users. Surveys using a basic Likert scale may be used initially, but the richness ofthe subject matter may demand interviews and ethnographical analysis to reach the best data.

There may be interesting opportunities for innovation research to take place in multiple disciplines. Manufacturing, scientific research, software development, and media development firms could all provide unique study opportunities for the integration of technology in innovative processes. Multiple segments within each disci­pline may offer unique opportunities as well, but at the very least the multiple disciplines should be studied to see how different innovative efforts apply and integrate technology differently.

One significant issue that may merit study is that of necessary speed of development. Different industries face very different competitive environ­ments and their products function on different life cycles. One aim of the research could be to determine if industries are more or less likely to use technology enhancements in their innovation processes, or if they use technology differently, in connection to their needs for fast development cycles.

The technical skill sets of employees in given industries may also be worthy of investigation. The assumption is likely made that more technical industries are more likely to use technology to enhance their innovation efforts. Research could either prove or disprove such assumptions and could serve a function in guiding industries of different technical skill levels in how to effectively pursue technology-enhanced innovation.

These broad opportunities help to define some of the work that may be done in researching the role of technology in innovation. Within each broad category there are many focused opportu­nities for study, some of which may benefit from being replicated across multiple broad categories. One important factor in designing future research in the role of technology in innovation is that the studies may focus more on strategy than on the technology. With that in mind there are likely good research partnerships to be found between strategic management experts, marketing special­ists, and technologists.

CONCLUSION

Technology is an important component of almost every modern organization. Similarly, innovation has become an important part of organizations. Technology and innovation have traditionally been closely related, but the perspective is often one of technology being a source or result of innovation versus technology being a valuable tool in the building of innovation. Going forward, innova­tors need to recognize the value that technology offers as a tool of innovation.

Communication and creativity are the primary contributions that technology can make to innova­tive processes. While speed, efficiency, and other metrics also benefit from a technology-rich inno­vative environment, but all these positive factors ultimately tie to communication and creativity. By strategically implementing the appropriate technical tools an organization can enhance both communication and creativity, the two of which symbiotically assist each other, and advance the innovative cause of the organization as a whole.

The goal of the technologist in an innovative firm should be to successfully align technical tools with the strategy of the organization. Beyond this alignment, training and support should be designed to move organizational members towards effective use of the technology. Ultimately, the approach to applying technology to innovation may of itself be innovative, but the efforts are well worth the positive results.

R&D Internationalization as Mechanism of Innovation in Global Enterprises: A Brazilian Case Study

Simone Vasconcelos Ribeiro Galina

University of Sao Paulo, Brazil

ABSTRACT

Internationalization of Research and Development (R&D) allows transnational companies (TNC) to access different and important resources overseas, which may lead to the improvement of their techno­logical innovation. The literature in this field has been mostly createdfrom studies of TNCs coming from developed countries. This chapter presents some of the main topics the literature addresses on R&D internationalization, then it will explore and verify how companies in developing countries internationalize their R&D activities. In order to do so, a bibliographic review about strategies of internationalization of TNC operations, as well as motivating factors and management of R&D internationalization have been conducted. The chapterfinishes by presenting a case study about international R&D conducted in a Brazilian TNC. The results enabled to evidence that, like developed countries TNCs, developing countries ’ companies also seem to perform internationalization of R&D activities with very similar characteristics.

DOI: 10.4018/978-1-61350-165-8.ch033

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

INTRODUCTION

The success of technological innovation in enter­prises depends on their competences in Research and Development (R&D), since it is one important source ofknowledge and innovation. When R&D is decentralized to worldwide subsidiaries, corpo­rations are able to access knowledge and connect to local markets. Therefore, these corporations improve their competitiveness over firms whose innovations are generated on national basis only (Birkinshaw et al., 1998).

The spreading of global R&D has grown rap­idly over the 1990’s (UNCTAD, 2005); phenom­enon resulting from companies originating from advanced economies such as U SA, European coun­tries, and Japan (von Zedwitz, 2005). However, “internationalization of R&D from developing countries is on the rise” (von Zedwitz, 2005, p. 127), because MNCs from emerging economies are investing in R&D abroad (UNCTAD, 2005).

Inevitably, “most previous research focused on the scenarios of developed economies, thus meaning the issue still needs to be studied from the perspective of developing countries” (Wu, 2007, p. 298). In this manner, this chapter aims at presenting an exploratory research from the Brazilian perspective. In order to do so, it is in­troduced a literature review addressing relevant aspects of R&D internationalization analyzed in a Brazilian company. This bibliographic review is conducted from two approaches: strategy and management. The first approach is based mainly on the strategies of companies to locate operations abroad by Foreign Direct Investments (FDI) and on the driving forces towards R&D Internation­alization. The role of subsidiaries of transnational corporations is the linking topic for strategy and management, once distribution of units globally is strategically determined and the interaction among these global units has to be well managed in order to benefit the whole corporation.

The chapter finishes with a case study of Embraco, a Brazilian manufacturer of electric — electronic products for cooling solutions (hermetic compressors, condensers, evaporators and others). This is an innovative company whose manufac­turing activities are located in three continents (America, Europe, Asia), also internationalizing product development function. This example al­lowed us not only to illustrate topics discussed on the literature section, but also to shed light on R&D internationalization by company from an emerging country.

STRATEGIES FOR ENTERPRISES INTERNATIONALIZATION

Internationalization of companies is quickly in­creasing as shown by United Nations Conference on Trade and Development [UNCTAD] (2009,

2005) . In 1990, the number of worldwide Trans­national Enterprises was about 37,000 and with at least 170,000 foreign affiliates; in 2004 this number increased to 70,000 with at least 690,000 foreign affiliates; and in 2008 the number ofMNCs jumped to 82,000 with 810,000 foreign affiliates half ofthem being located in developing countries.

The internationalization of companies is not a recent scenario. In the 18th century, there are accounts of companies, especially European ones, which held business out of their country of origin. However, several aspects of globalization (financial, commercial, productive, economical, institutional) modified the behavior of companies worldwide, thus intensifying their migration. As it is presented, globalization is relatively recent and was originated amidst the significant growth of the post-World War II international business (Baumann, 1996; UNCTAD, 1994), and has consolidated especially due to the technological development of fundamental areas to base global institutional operation: information technology, communication and logistics.

Table 1. Organizational characteristics of multinational, global, international, and transnational com­panies (Adapted from Bartlett & Ghoshal, 1989)

Multinational

Global

International

Transnational

Assets and resources management

Decentralized and Na­tionally self-sufficient

Centralized and globally sited

Centralized basic compe­tencies resources, other multisite ones

Dispersed, interdepen­dent and specialized

Role of the subsidiaries

Perceive and explore local opportunities

Implement headquarters strategies

Adapt and leverage head­quarters competencies

Differentiated contribu­tions of domestic units to integrated world operations

Development and spread of knowledge

Knowledge developed and kept in each unit

Knowledge developed and kept in the center

Knowledge developed in the center and transferred to overseas units

Knowledge jointly developed and shared all over the world

From works of authors such as Dunning (1993), Bartlett and Ghoshal (1989), and others, it is pos­sible to trace a timeline overview on the global actuation of companies since their first efforts of being overseas to their current globalization strat­egies. Companies which operate internationally present some important behavior changes. In the 1960’s, the major worldwide activity was related to export operations of output or components to the simplified assembly of products to national/ regional markets. From de 1970’s on, there was the building of manufacturing plants in strategic countries in order to improve the performance of local unities and products.

The fierce competition of the 1980’s put pressure on companies to a more emphatic in­ternationalization of production, although not so adjusted as the one witnessed in the 1990’s, when productive activities were fully world-integrated, that is, companies “begin to be described as co­ordinators of an activity network inter-related to add value” (Dunning, 1994, p. 28).

Such history overview also influenced the classification of current global companies. There are a myriad of classifications for worldwide com­panies, that is, those which hold activities out of their home countries. One ofthe most renowned is Bartlett & Ghoshal’s (1989), which classify glob­ally operating corporations as follow (Table 1):

Multinational Corporations (MNC) or Multidomestic: They work using the whole production chain in an overseas country, with independent unities, and mark strong local presence by means of sensitivity and receptivity regarding do­mestic differences.

Global: They are much more centralized in operational and strategic decisions than the MNCs. They have competitive advan­tage in terms of costs by means of opera­tions centralized in global scale, dealing with the world market as a whole. International: They explore knowledge and resources from the headquarters by world diffusion and adaptation. The head­quarters exert considerable influence and control, but less than in a global company. The domestic units are allowed to adapt products and ideas from the headquar­ters, although with less autonomy than the MNCs.

Transnational (TNC): They integrate processes in global scale, making them improved, rationalizing resources, elimi­nating redundancies, and operating world spread products. They seek for efficiency in order to achieve global competitiveness, understand local receptiveness as a tool to obtain flexibility in international opera-

tions, and see innovation as result of a pro­cess which comprises several members of the company.

The differences between these classes can be subtle, and a company may behave in similar man­ners in more than one of them. In order to make the comparison easier, Table 1 shows a sum up of the organizational characteristics of Multinational, Global, International, and Transactional corpora­tions. “Development and knowledge spread” may be the most clearly distinct. The rest of them pres­ent less perceptive difference, for instance, “the role of the subsidiary overseas” of an MNC—to explore local opportunities—is also common to TNC and can also be fundamental to the survival of global and international companies.

Another approach to the International operation is of a Metanational company developed by Doz, Santos and Williamson (2001). The Metanational model focuses on companies coming from coun­tries not among the traditional capital holders or leader industries, hence they can appear to be inappropriate environments to allow local compa­nies to take part in global competition. However, according to the same authors, once the know-how the companies ofthese countries need to compete in a global level is not available in their home countries, they are led to develop competencies in market and technology knowledge in an interna­tional perspective. This is a learning opportunity to place them in an advantageous position.

Besides organizational characteristics, it is important to undestand the strategies which lead companies to locate units globally. There are manners for a company to enter the international market in terms of business involvement, imply­ing different levels of risk and management com­plexity. They usually come by exports, contracts (association between company and institution in a foreign country with no assets investments) or by direct investments abroad (when a company installs subsidiaries in a different country than its original one). Business risks and complex­ity increase as there are more involvement and, consequently, dependence of the company on its foreign businesses. It results according to the means of entrance/operation listed as follows: export, contract, and investment.

There are several models/theories of com­pany internationalization, that is, the strategies it adopts when enter international markets (related to entrance by investment), including Bartlett and Ghoshal (1989) presented above. Economic theories are basically related to currents which study firm internalization and the factors which lead corporations to internalize their operations in another country. One of the most notorious theories is Dunning’s eclectic paradigm (Dunning, 1988, 1993, 1994), which “avows that the greater the net benefits of internalizing cross-border intermediate product markets, the more likely a firm will prefer to engage in foreign production itself, rather than license the right to do so (e. g. by a technical service or franchise agreement) to a foreign firm” (Dunning, 2000, p.164).

The behavioral theories, whose most known ap­proach is the Uppsala Model (Johanson & Vahlne, 1977), relate the incremental internationalization of a company to the level of its learning abroad. That means that a corporation would follow an established order due to the higher or lower level of know-how required: exports, sales unit, opera­tions subsidiary, and Research and Development (R&D) activities engagement.

Nevertheless, despite the relevance of this model and the countless works based on it, this sequence of operation abroad has been questioned by new theories and empirical evidence of corpo­rations’ procedures. It is undebatable that many companie s do not follow the sequence determined by the level of knowledge resulting from their work abroad, that is, they do not follow Uppsala’s model presupposition. The network theory itself (Forsgren & Olsson, 1992), also considered a behavioral theory, is an approach showing that the need for insertion in a global value-added chain strongly interferes in the manner a company enters and operates on international markets, as well as in the role of each affiliated/subsidiary abroad.

Concluding, companies currently operate globally aiming to take competitive advantages in each region/country they locate, and from that on, their management process is substantially changed. An important change refers to techno­logical innovation, approached by means of two trends: products and processes commercialized, developed and manufactured in global scale; and decentralization of their R&D. It modifies not only the management of R&D function itself, but also of other functions related to it such as operations, marketing, and sales.

One ofthe issues emerging from studies on in­ternationalization management is the coordination of subsidiaries distribution and the role of each foreign unit (Bartlett & Ghoshal, 1992; Ferdows, 1997; UNCTAD, 1999). When focusing on R&D internationalization, this subject is highly relevant and it is presented here.

INTERNATIONALIZATION OF R&D ACTIVITIES

The roles ofTNCs’ subsidiaries out oftheir head­quarters’ origin country are not restrained to the as­sistance of local market, but organized in integrated network so that they have the necessary conditions to explore capacities or know-how in each country not only in production terms, but also in technol­ogy development (Cantwell & Santangelo, 1999). Transnational companies locate their activities in sites where there is competitive advantage, and “besides related to production, these activities are related to distribution, marketing, and R&D” (Reddy, 2000, p. 10). TNCs are the main agents of productive globalization and consequently internationalization of R&D (Cantwell, 1994; Gerybadze & Reger, 1999).

Since the 1990’s, it is observed a strong growth of R&D internationalization within global companies. Several studies show that TNC investments in R&D are increasingly oriented toward subsidiaries located outside the home country (UNCTAD, 2005; Doz, et al., 2006). The exposure of a global company to a variety of environmental stimuli is a great advantage over a national company. Thus, there are several argu­ments pro-internationalization of R&D, not only to support local manufacturing activities, but also to create interfaces with local innovation systems (Ohmae, 1990).

There are different nature of studies related to the internationalization of R&D. Some of them discusses the subject under the point of view of TNC and their strategies to globalize R&D activi­ties, taking advantage from local situations in favor of global development (Ronstadt, 1977; Terpstra, 1977; Hakanson, 1990; Bartlett & Ghoshal, 1989). Influencing these strategies are factors that orient the investment in R&D towards specific countries/ regions, and some other works under this approach were carried out (Cantwell, 1992; Reddy, 1997, 2000; Niosi, 1999; Gerybadze & Reger, 1999; UNCTAD, 2005; Cantwell & Santangelo, 1999; Kumar, 2001; Florida, 1997; Patel & Vega, 1999; Pearce, 1999).

Besides these, and yet considering the interna­tionalization of R&D strategies, there are authors who work on market analysis, establishing prod­ucts characteristics which can be standardized to worldwide markets or need to follow local market contingencies in the world perspective, which may or may not influence the R&D centralization or decentralization (Hult, Keillor, & Hightower, 2000).

Some works in this area refer to manners to manage R&D world centers and technologic development activities under different aspects (Chiesa, 2000; Gassmann & von Zedtwitz, 1999), especially on data/information group exchange management (for instance, type, costs, code and infrastructure for the global communication process) and on the organization of work teams around the world (for instance, organizational structures, leadership, and team formalization).

The literature in internalization of R&D also shows that this is not recent practice by compa­nies. Vernon (1966) shows that in the 1960’s the enterprises exploited resources overseas, including to obtain technological know-how. In 1971, the amount that North American enterprises invested in R&D out of their country was 10% of the total invested in R&D (Terpstra, 1977). Reddy (1997) mentioned that the US Tariff Commission had declared in 1973 that North American companies carried R&D in foreign countries yet in the 1960’s. The main industries involved were in the areas of mechanics, electrics, and engineering (including automotive engineering). However, more evidence of this practice emerges only after some works were carried out in the 1970’s, with the famous classification of Ronstadt (1977). It distinguishes the different types of R&D world units, thus validating the practices of internationalization of TNCs development activities.

Another work produced in the 1970’s (Behrman & Fischer, 1980) presents evidence of R&D unit allocation in developing countries such as Brazil and India, especially due to some of their charac­teristics: profitable subsidiaries, growing market, and structure suitable to Science and Technology. The maj or industries to internationalize R&D dur­ing this period were from chemical and food areas.

The distributed execution of R&D up to middle 1970’s was difficult, particularly due to some problems to supervise and control international activities. Such issue was minimized when new information technologies and communication were introduced.

Although internalization of R&D has begun in the 1970’s, it became a “phenomenon” only by the end ofthe 1980’s (Cantwell, 1995). Back then, foreign subsidiaries were involved not only in de­veloping processes and products to both local and global markets, but also in basic research (Reddy, 1997). Those were trends introduced in the 1980’s that remains today, especially for companies from developed countries and their growing need for highly qualified manpower. Internationalization led the enterprises to search for new knowledge and technologies abroad. In the 1980’s, the main industries involved in globalization of R&D ac­tivities were from microelectronics, pharmacy, and civil aeronautics areas.

Adapted from Reddy (1997), Table 2 presents the background process of R&D globalization into enterprises. For each decade relevant to the internationalization of technological development in TNCs, the author shows driving factors, that is, those which leveraged and favored this interna­tionalization, the sort of R&D carried out abroad, and the characteristics of R&D units.

As observed, internalization of R&D is a true fact. However, “the country of origin of TNC is usually the most important place to the techno­logical development ofthe corporation” (Cantwell, 1995, p. 172), although there is solid evidence of the strong growth of R&D expenses in foreign subsidiaries. According to UNCTAD (2005), from 1993 to 2002, these costs rose from 10% to 16% ofthe whole investment in R&D. The same study shows these expenses were geographically con­centrated. In 2002, for instance, the ten major economy investors in R&D represented 86% of the world sum, whereas eight of them are devel­oped countries (China and South Korea, excep­tionally).

Also according to UNCTAD (2005), the sort of R&D performed overseas may vary depend­ing on the region, whereas Asia prevails with the most innovator R&D (particularly China, India, and Korea). Some new members ofthe European Community have attracted activities for technol­ogy innovation; Latin America and the Caribbean have little direct investment in intensive activities and focus on adaptation of technologies or prod­ucts to the local market; some African countries (especially Morocco and South Africa) attract limited investments in R&D.

Table 2. Background process of R&D globalization (adapted from Reddy [1997])

Driving forces

Type of R&D

Forms de R&D

1960s

entry into the local market abroad

adaptation; technology transfer unit (TTU)

own-R&D with manufacturing af­filiate

1970s

build-up market share in the local market abroad; national government policies

product development for the local mar­ket; indigenous technology unit (ITU)

acquisition or green-field invest­ments in own-R&D and production facilities.

1980s

need for worldwide learning and new technology inputs

products and processes development for global markets & basic research; global and corporate technology units (GTU & CTU)

own R&D affiliates; joint venture R&D; inter-firm cooperation; sponsor university research; subcontract R&D

1990s

access to scarce R&D personnel and increasing R&D costs

products and processes development for global and regional markets & basic research (GTU & RTU & CTU)

own R&D affiliates; joint venture R&D; interfirm cooperation; sponsor university research; subcontract R&D

Great part of the studies on R&D localization by foreign enterprises in Brazil (Dias & Salerno, 2009; Galina, Sbragia, & Plonski, 2005; Gomes,

2006) shows that R&D activities done in the coun­try by local subsidiaries are focused on adaptation of products and processes. However, some TNC have considered this country as a guidance of more relevant investment in R&D (Galina, Camillo, & Consoni, 2010).

Considering early discussion, with the world­wide distribution of R&D, companies look for greater competitive advantage. It is known a myriad of arguments favorable to the interna­tionalization of product development not only to support local production, but also to create interfaces of local innovation systems (Ohmae, 1990). In the next section the main reasons that underlie companies’ decision to internationalize R&D are debated.

DRIVING FORCES TO R&D INTERNATIONALIZATION

There are many reasons for R&D resources to be directed to countries other than the company headquarters’. Terpstra (1977) summarizes the most frequently found among TNCs: in response to the pressure applied by host countries; in order to improve international relationships; intending to access foreign skill and resources; to reduce development costs with cheap labor; to obtain advantage on local ideas and products; trying to accelerate development by means of parallel ef­forts of laboratories working simultaneously; in order to sustain development activities performed by companies acquired abroad; to obtain advantage from domestic laws of government incentive.

In general, the pertinent literature presents two major subjects to list the main reasons for R&D internationalization (Chiesa, 1995; Florida, 1997): marketing-related factors (necessity to access markets, responding to local needs and strengthening bonds to clients/consumers), and technology-related factors (qualified labor, out­standing technology). Chiesa (1995) states that factors related to technology and demand are the two main reasons to promote R&D internation­alization. There is also factors regarding finance aspects, such as labor cost reduction and local incentive policies; and some other more subjective factors such as the connection between headquar­ters and subsidiaries in what concerns personal relationship of their respective executives.

The market-related factor is motivated to the adaptation of products to foreign markets and to production/operation technical support. When locating their units abroad, the TNCs look for a better service to their client, with more appropri­ated and faster adaptations of products, essentially.

When establishing development activities in sites next to the clients, the enterprises are better structured in order to understand and to provide local needs more efficiently, especially because in general TNCs have gigantic and extremely red tape organizational structures, thus complicating the decision-making process. The marketing factor is considered less relevant or more superficial, as quoted by Inzelt (2000): “skin-deep collabora­tion.”

The second factor, related to technology, is aimed at guaranteeing access to Science and Tech­nology (S&T) and qualified human capital, and creating bonds with local science communities. Once more intrinsic to the development process, this factor is considered more relevant, since it establishes a deeper relation of dependence between the company and the regions where the subsidiaries are. It is what Inzelt (2000) calls “soul-deep collaboration.”

Yet regarding technological factors, Cantwell (1992) mentions two approaches as main reasons to the internationalization of R&D: to obtain ad­vantage from distinct innovations characteristics in different domestic systems, thus gaining access to further technologies, and to have contact with new threads for technological innovation.

Despite considered more or less relevant, technological and marketing factors are para­mount to attract local investors, thus enabling the transformation of less advanced countries in more advanced ones. It is also common to see companies which consider both factors when guiding their investments in R&D abroad.

The internationalization of R&D is often a result of actions non-related to company strate­gies such as govern requirements, acquisition of foreign units already owning R&D departments, etc. (Granstrand et al., 1992). For Terpstra (1977), governments of countries where MNCs have branches try to maximize the local technological development by means of receiving incentive or pressure. They are more successful with foreign enterprises which buy domestic companies and ensure continuity to R&D processes than pres­suring these foreign companies to start new local R&D activities.

As for financial factors, despite less relevant, companies have shown they take them into account when spreading their development ac­tivities worldwide, especially when they choose developing countries. As mentioned by Reddy (1997), development costs in research centers based in developing countries (India, Brazil) are proportionally lower than in traditional centers.

In what concerns the factor of relation between headquarters and subsidiary, the most subjective of all, it is important to consider that if the com­pany staff involved in strategic decision-making handles good relationship with the subsidiary’s executives, chances are for the local unity sig­nificantly involve in corporate technological development. For Birkinshaw and Hood (1998), a high quality relationship between headquarters and subsidiaries has a positive impact on “enter­prising” subsidiaries, that is, those working for the development of local competencies.

Summarizing, factors (or driving forces) considered by companies to increase internation­alization of R&D are many. They may be related to some companies’ internal aspects (such as internal competence, relationship among units, historical trajectory/path, etc.), to environmental aspects (such as market characteristics, level of wages or existence of competencies on local uni­versities or research centers) or to public policies (direct incentives to internationalization). These factors are motivated mainly by marketing and/ or technological reasons.

MANAGEMENT OF INTERNATIONAL R&D Roles of Subsidiaries

As previously stated in this chapter, transnational organizations structure themselves in order to ob­tain most units abroad. To do so, subsidiaries are given strategic roles and responsibilities and are distributed all over the world so the resources of each country can be reasonably exploited. There are several classifications to the subsidiaries roles of global enterprises (Bartlet; Ghoshal, 1989; Birkinshaw, 1996; Ferdows, 1997; Gupta & Go — vindarajan, 1991, 1994; Pearce & Papanastassiou, 1996; Roth & Morrison, 1992; UNCTAD, 1999).

Figure 1. Strategic roles of subsidiaries (Ferdows, 1997)

The typology presented by Ferdows (1997) is based on a cross between local competencies (high and low) and three clusters of strategic reasons: low production costs, market proximity, and access to skills and knowledge. This combination lead to six subsidiary roles (Figure 1): Offshore (not innova­tive and abiding by corporate decisions); Source (autonomous with regard to certain manufacturing activities); Server (produces for the local market); Contributor (has its own process engineering and products for the local market); Outpost (monitors the local environment for the global corporation); and Lead (creates new processes, products and technologies for the entire organization).

In every one of the subsidiary role classifica­tions (models) mentioned, there are company units in charge of generating technology for the sub­sidiary itself or even for the entire corporation. Ronstadt (1977) shows different types of units which perform overseas R&D (out of the origin country of the company) by TNCs:

• Technology Transfer Units (TTUs):

Enable technology to be transferred from headquarters to subsidiary and provide lo­cal technical services.

• Indigenous Technology Units (ITUs): Develop new products to local market us­ing local technology.

• Global Technology Units (GTUs): Develop new products and processes to major world markets.

• Corporate Technology Units (CTUs): Generate basic long-lasting exploratory technology to be used by the headquarters.

Adding to this typology developed by Ronstadt, Reddy (1997) offers, and quite appropriately so, another class of global R&D units as “certain regional clusters are also becoming stronger despite market integration around standards and technologies” (Reddy, 1997, p. 1822):

• Regional Technology Units (RTUs):

Develop products and processes for re­gional markets.

Ronstadt’s classification is a way to understand that subsidiaries play important roles in innova­tion. Terpstra (1977) suggests that the more a company is engaged in international business, the more significant its businesses are, as well as its R&D activities.

Related to the debate on classifications relating transfer of technology/knowledge to corporation strategies, there is a seminal work by Gupta and Govidarajan (1991, 1994), focused on the subsid­iary roles in the company structure. It identifies four generic roles for TNCs’ abroad units:

• Global Innovator: The subsidiary acts as a leader in the development and knowledge to other unities of a product group particu­lar technology.

• Integrated Player: The subsidiary is as a

source of technology creation as a key user of a technology developed by other unity.

• Implementer: There is little engagement

of the subsidiary to build know-how, and it is strongly dependent of technological transfer from other TNC units.

• Local Innovator: The subsidiary is re­

sponsible for developing technology to key functional areas, although almost to­tally of local use, there is, the knowledge developed by itself is too idiosyncratic to be used in other countries.

This typology was tested by the authors in North American, European and Japanese compa­nies, and the model was then validated. However, they found internal differences in organizations in what concerns the role of know-how and its flow to the subsidiary. Thus, it shows that the role of technology to TNCs unities does not vary only according to their nationality and industry sector, but also depends on the characteristics of the each enterprise. It indicates that this situation is highly complex and that attempting to create a systematic strategic and practical pattern or model in the transfer and allocation of technology may be very troublesome (Howells, 2000).

In short, independently from the typology of subsidiaries roles, a TNC is aimed at coordinat­ing a global network in order to take the best advantage from spatial assets, and once they are specialized and interdependent, the subsidiaries make differentiated contributions to integrated world operations (Blarttlet & Ghoshal, 1989). This logic of the role of operational subsidiaries comprises the development and propagation of knowledge in the world corporation, which is jointly developed by different domestic units and shared all over the world. Since it is important to analyze, that is the subject to be discussed in the next section.

Structure for International R&D

In basic, Hakason (1990) suggests that the structure TNCs use to perform world R&D has three basic stages: centralized, decentralized, and integrated. Gammelgaard (1999) presents a model to the work division of international R&D which initially establishes the difference between centralization and decentralization, besides the specification in case the company chooses a decentralized development. In this case, it is necessary to es­tablish whether the company will operate in top — to-bottom strategy, when the tasks are assigned by the headquarters, or in bottom-to-top strategy, when there is a greater autonomy of the branches, developing products on the subsidiary (bottom) and sending to the headquarters (top), then to the whole organization.

In a little wider view, Bartlett & Ghoshal (1990) present four different structure s to the management of innovation processes:

• Central-for-Global Innovations: The de­velopment of new products and processes is promoted in the home country and trans­ferred to global markets.

• Local-for-Local Innovation: Independent development of new products and pro­cesses occurred in each R&D unit, with worldwide distribution and oriented to the subsidiary local market.

• Locally-Leveraged Innovations: The de­velopment of new products and processes is made in the subsidiaries and distributed to the company as a whole.

• Globally-Linked Innovations: The devel­opment is promoted in collaboration with R&D units located in different countries for operating profits of global markets.

Each ofthese management modalities presents advantages and disadvantages, and is applied according to the company strategies and its busi­ness characteristics. They comprise a number of technological development possibilities in a transnational company, whether centralized or not.

However, in order to decentralize R&D, companies make use of different strategies when distributing their activities and control worldwide. Ronstadt’s typology (1977) presented in the previ­ous section does not include intraorganizational relationships, although widely used as pattern of TNCs international R&D.

The literature shows many models for decen­tralized development management, even with central coordination. In the model developed by Chiesa and Manzini (1996), an analysis of

a number of international subsidiaries of world

enterprises and the interaction among them, there

is a classification with four R&D structures:

• Isolated Specialization Structure: A for­eign laboratory is totally responsible for the development of certain global technol­ogy/product/process. This research center is unique in the TNC on the referred area. It is considered center of excellence, and there is no interaction between units on the course of the project development. The transfer of knowledge is limited mostly to the phase of introduction of products to the subsidiary market, going from the center of excellence to the TNC units. It can be per­formed in different ways, with temporary transfer from the central unit to the sub­sidiary (usually when the product is pro­duced in the local unit) or the employees are trained in the center of competency to provide technical support to the introduc­tion of the product in a local market (usu­ally when the product is produces in a local different from the subsidiary). This struc­ture is also known as Center of Excellence Structure (Chiesa, 2000).

• Supported Specialization Structure: There is a global center responsible for R&D work, as well as in the isolated spe­cialization structure. However, there are many units in different countries which provide the global center with informa­tion useful to the innovation and devel­opment of new products, originated from requirements technology and marketing) of the local environment. Such structure combines the specialization/concentration benefits (efficiency, scale economy, proj­ect coordination low cost) with the pos­sibility of monitoring local opportunities of innovation. “In this structure, the only phase to not imply in transfer of techno-

logical knowledge is development itself (Chiesa, 2000). The phase of creation/ conception takes place in the central unit, but the information originates from other supervision units. The strategies to transfer knowledge are similar to those used in the isolated structure.

Specialized Contributors Structure: A

division of tasks is established among units, thus maintaining a centralized coordina­tion and each subsidiary is attributed indi­vidual activities within the program. The know-how developed in each unit is trans­ferred to the central. In this structure, the interaction between globally spread units is much more complex than the supported specialization structure. In the conception phase, the data flow is ongoing from the units to the center and among the subsid­iaries themselves. The phases to define the project and the technical development are performed by international teams and in­volve different units. That is, in this type of structure, there are much more interaction in the phases of definition and technologi­cal, product and process development.

Integrated Laboratories Structures:

Different laboratories spread across many countries and operating in the same pro­duction segments or technological areas. The TNCs holding such structure tend to give autonomy to foreign laboratories, but their initiatives and activities are centrally monitored in order to avoid duplications, coordinate spread efforts, and engage different markets. Just as in the special­ized contributors structure, the transfer of knowledge is made with close interaction among the many unities in the phases of planning, formulation and technological development. A second name given to such structure is Network Structure (Chiesa, 2000).

These different structures are more frequently used for the development of products. For the research activities, the network structure is more usual since each unit makes its own program under some coordination, but the effort duplication is, in a certain way, allowed (Chiesa, 2000). The build­ing of similar projects by many units at the same time is a way to accelerate the learning process, since each subsidiary work on different manners and under different perspectives, which can lead to internal competition among independent units, thus increasing their creativity and benefiting the company as a whole (Chiesa, 2000).

A classification similar to Chiesa’s was devel­oped by Gassmann and von Zedtwitz (1999), who present five models of structural and behavioral orientation in international R&D organizations:

• Ethnocentric Centralized R&D: Every R&D activity is concentrated in the head­quarters’ country of origin, considered technologically superior to their subsidiar­ies. Their purpose is “to protect” against their competitors technologies regarded as fundamental to the company.

• Geocentric Centralized R&D: It central­izes know-how acquired over the world and technologies available in overseas countries by means of sending R&D em­ployees abroad in order to intensify rela­tionships and collaborate to the local pro­duction, suppliers and key clients. In this manner, it is adopted in companies more dependent on foreign markets and local competencies than those which make use of the ethnocentric model.

• Polycentric Decentralized R&D: It is characterized by local development labo­ratories with no supervision of the corpora­tion center, whose relationship is restricted to the report of activities from the local labs to the headquarters. The subsidiary R&D directors report directly to the man­ager of their own unit.

• R&D Hub Model: The R&D central unit, usually located in the headquarters, is the corporation technological leader since it is the major advanced R&D laboratory. All activities are decentralized, though tightly controlled by the head office. These foreign labs are usually involved in local monitor­ing and focus their activities on predeter­mined technological segments.

• Integrated R&D Network: In this struc­ture, each integrated network unit spe­cializes in a product, component, or tech­nological field, thus becoming center of competency in its segment and has world product mandate for both product devel­opment and introduction to other markets. Differently from the Hub structure, the R&D foreign units play strategic roles, that is, a center of competency should not only supervise potential changes, but also en­gage in defining strategies and prospecting businesses, reaching the TNC as a whole. Once connections are established among the participant units, this structure requires a complex coordination of the R&D inter­national activities.

These structures are not definitively established in a company, that is, the international organization can be — and usually is — continuously modified in order to promote the evolution of R&D pro­cesses. Gassmann & von Zedtwitz (1999) point five currents to this change, all based in two criteria: allocation of R&D activities (centralized or decentralized), and type of integration among teams (competition or cooperation).

The first tendency pointed by the authors emerges from the necessity to align the R&D process with the international market require­ments (increasing cooperation in favor of the development of products and processes), so the R&D center starts to gather outer information and feedback. It characterizes the modification of an ethnocentric to a geocentric structure. Another current presented by Gassmann and von Zedtwitz (1999) intends to create a R&D decentralization, then characterizing the transition from a central­ized structure (ethnocentric or geocentric) to a central coordination model (Hub).

As the R&D local units across the world in­crease their technological competencies, a third current of structural change is identified; an evo­lution based on the autonomy the R&D control center grants to the local units and, due to it, hey become more flexible and free to carry technologi­cal development. This change characterizes the transition from a central coordination structure (Hub) to an Integrated Network.

A fourth tendency identified by Gassmann and von Zedtwitz is related to enterprises whose international R&D growing and strengthening background based on labs is relatively autono­mous. When these companies identify the benefits of integration and interconnection of their inter­national R&D activities, centers of competencies are created, and mechanisms to coordinate them are introduced. This tendency characterizes the transition from a polycentric structure to an inte­grated network.

However, in order to reduce costs, the compa­nies which adopted the Integrated Network struc­ture are forced to focus their efforts on a smaller number of centers of competencies, characterizing a R&D recentralization. This consolidation is aimed at exploring scale effects and improving the coordination of R&D global activities, thus reduc­ing task duplication and intensifying the transfer of technology among laboratories (Gassmann & von Zedtwitz, 1999, p. 246).

The polycentric decentralized model must be highlighted: “is the ‘dying model’ among the five forms of international R&D organization” (Gassmann & von Zedtwitz, 1999, p. 241). In this structure, despite the benefits from strong orientation to local markets, the lack of central coordination increases costs and efforts to promote

R&D. According to the authors and creators of such, the polycentric configuration leads to the central control (Hub) or the integrated network.

Under Gassmann and von Zedtwitz’s consid­eration, the similarities between these structures and those developed by Chiesa are stronger. Furthermore, both classifications complete each other. There are common points, in special those regarding clear divisions between the two main characteristics: development centralization (with or without the participation of development local units), and the integration in favor of the develop­ment (with a stronger or lighter connection with the development local units).

In short, the modes of managing global prod­ucts development may differ from sector to sector, and company to company. There are a myriad of relevant aspects to consider in the international­ized R&D management process, but two of them are more intensely debated. One are related to the division of work among teams distributed throughout global subsidiaries, and the other refers to the organizational structure required to coordinate these R&D functional unities, both studied in the present section.

R&D INTERNATIONALIZATION OF A BRAZILIAN COMPANY

The present section presents an example of international R&D carried out by Embraco, a former Brazilian company now part of the North-American Whirlpool Group. Although it is formally a company from USA, its R&D (like most of its operations) is still managed from Brazil and by Brazilian executives, which make it an interesting case of a ‘Brazilian company’ with North-American capital control.

Embraco is a manufacturer of electric-elec­tronic products for cooling solutions, including hermetic compressors, condensers, and evapora­tors. It employs around ten thousand people, was founded in 1971 and its first FDI was in 1994.

The company exports for more than 80 countries and, besides Brazil, it has factories in Italy, China, and Slovakia. In addition to globally locate its manufacturing activities, it also international­izes product development intentionally (Galina & Moura, 2010).

Methodological Aspects

In order to analyze the R&D function within the company, as well as its internationalization, we looked into the following: the structure of R&D functions, how to implement it, how product development activities are conducted by the com­pany in Brazil and, finally, how they are carried out abroad.

The case study was made by extensive in-depth face-to-face interviews with the R&D director, the manager of product development and the manager ofinternationalization. These interviews were made with a semi-structured questionnaire which addresses specific issues contemplated in this study: the driving forces, roles of subsidiaries, and structure for R&D offshore.

Data used in this study are not only primary, but also secondary, and they were collected be­tween the years of2006 and 2007. The sources of secondary data included: news, scientific articles, reports on internationalization process of Embraco compared to other Brazilian multinationals, and documents gathered directly in the organization (reports, contracts, plans, metrics).

Results and Discussion

The main drive forces that led Embraco to inter­nationalize R&D were as follows:

• Adaptation of products to local markets:

Embraco has, with regard to technologies already dominated by the company, grant­ed autonomy to its subsidiaries to adapt and customize products and manufacturing processes according to the characteristics

of local plants and markets. The company has opted for decentralization because it needs to operate closer to the customer and to respond more quickly, and this means identifying customer needs, translating them into projects and implementing these in a shorter time period than it would be possible if development were centralized. Development of partnerships with lo­cal suppliers: The internationalization of manufacturing activities at Embraco has enabled its offshore plants to develop a lo­cal supplier interface that can not only fos­ter cooperation to improve technology but also improve local product development. Thus, agility is not restricted to the com­pany’s responsiveness to its customers; in fact, it permeates the entire supply chain. Technology monitoring and accessing: Embraco is offshoring R&D activities to China not only because of the rapid growth observed in that market but also because of the large number of engineering gradu­ates and post-graduates entering the job market every year, which is transforming some regions in that country into centers of excellence in technology. The same com­pany also benefits from its local partners to monitor technology development. The company studied indicated that the devel­opment of proprietary technology was also a decisive factor behind internationaliza­tion. It claimed to have signed contracts with competitors to acquire technology for the ultimate purpose of developing prod­ucts of higher quality. In other words, the company attempted, from the very begin­ning, to monitor the overseas technology environment. Many of the technological competencies were internalized from abroad, which then allowed the company to develop its own.

In relation to the role of foreign subsidiaries, two ofthe three plants owned by Embraco outside Brazil have considered proximity to market as strategic reason for being located in the site, but one of them (Italian unit) creates new processes, products and technologies for the entire organiza­tion (in specific niches), being considered ‘Lead’ of the global corporation according to Ferdows

(1997) . According to Ronstadt’s classification, the Italian subsidiary may be classified as Global Technology Unit, and the other two are Regional Technology Units.

It is worth to consider, however, that Embraco’s Server unit in China is going through a process of this kind as the company is considering the pos­sibility of transferring to it certain R&D activities that were handled exclusively in the home country (Brazil). Thus, the plant’s strategic focus is shift­ing from market proximity to access to skills and knowledge, what may lead it to be reclassified as a ‘Lead’ unit (Ferdows, 1997) and a ‘Corporate Technology Unit’ (Ronstadt, 1977). Still with regard to Embraco, the company’s plant in Italy is undergoing a reverse process. At the time of its acquisition, the plant had a product line that the parent company lacked, which offered an opportu­nity for the latter to internalize new competencies. Despite the disadvantages, Embraco opted for a “divestment” strategy, causing the plant to shift its focus to high value-add products and thereby to become operationally sustainable. However, if the situation becomes unsustainable, a plant previ­ously classified as a Lead unit can be reclassified as an Outpost.

Thus, summarizing, the Italian subsidiary is a global technology unit while the one in Slovakia can be regarded as a regional technology unit. Finally, the plant in China is a regional technol­ogy unit that may become a global and corporate technology unit as the company plans to expand the R&D function there.

Concerning to the coordination of R&D in Em — braco, we may consider that the company shows two R&D configurations: one for the development of company-dominated technology, and another for non-dominated technology. In the first case, the offshore units are free to engage in product development activities with very little coordina­tion from the parent company because the purpose is to streamline products and processes for local markets. This configuration could therefore be described as polycentric decentralized. However, with regard to technologies not yet dominated by Embraco, R&D is almost entirely conducted by the headquarters in Brazil. The purpose here is to allow the organization to internalize the knowledge first. Once the technology has been mastered, it is then internationalized to the manufacturing units. Thus, this configuration was regarded as ethnocentric centralized.

The division of the company in dominated — technology and not-dominated-technology proved to be an interesting approach to the management of technological innovations. That management maintains centralized R&D activities for not- dominated-technologies at the same time that it establishes mechanisms for transferring this tech­nology, when dominated, to foreign subsidiaries, disseminating knowledge throughout the organi­zation and enabling that further developments of this technology are carried out also abroad.

CONCLUSION

This chapter presented a theoretical literature review which demonstrated that transnational companies have accessed important resources abroad by internationalizing R&D, and also their R&D investments into foreign subsidiaries have presented strong growth. Most of literature has been based on studies with TNCs from developed countries. Studies on global R&D are neglected for developing countries (Wu, 2007). Corroborating to this discussion, this chapter shows a study with a Brazilian company that have internationalized its product development.

The case study draws two general conclusions: first, Brazilian TNC internationalizes its R&D, thus corroborating with studies pointing tendency to the growing of internationalized R&D in devel­oping countries companies (von Zedwitz, 2005; UNCTAD, 2005). Second, this Brazilian interna­tionalization is performed similarly to developed countries. Similar conclusions are achieved by Wu (2007) in his study on Taiwanese companies, showing that “firms in developing countries appear to follow a similar path towards the globalization of R&D activities” (Wu, 2007, p. 308).

The study presented in this chapter was carried out from gathering important issues on global R&D strategies and management. One of these issues is the driving forces towards R&D internationalization, and the results of the Brazil­ian company are also related to the most known factors that influence corporations: market and/or technology. Another issue is related to the roles of foreign subsidiaries, which are determined by Embraco the same way as companies from devel­oped countries determine specific contributions of affiliates for integrating a global corporative network. Finally, management ofglobal R&D also follows established rules observed in the literature.

From the results, we conclude that Embraco has decided to internationalize its product de­velopment process by looking for better condi­tions for meeting the client’s needs in foreign markets, and this organization has been succeed on this purpose. Competencies and experiences of the R&D team abroad were assimilated into the corporation headquarters (in Brazil) in a way they have intentionally decided to locate an R&D unit in China, intending to access skills and knowledge. R&D activities were thus managed in order to have differentiated contributions of domestic units, leading to jointly development of knowledge, similar to transnational model by Bartlett and Ghoshal (1989). Considering this reality, it raises the question whether companies from emerging countries that recently have been globalized (the called late movers) may follow, some decades later, the same steps to consolidate TNC in terms of R&D internationalization. The answer is positive for the example here analyzed, but it requires additional research to achieve fur­ther conclusions.