Pub Date : 2010-07-18DOI: 10.5465/AMBPP.2012.11644ABSTRACT
Suli Zheng, X. Pan
The advance of globalization has deeply changed the form of competition and the resource base of firms. At the same time, the forming and development of global production network opened an opportunity window for Chinese firms to accumulate new resources and enhance their capabilities. Extending prior researches on network resource and innovation, this paper first elaborated a theoretical framework in which firms' network resources affects innovation performance through technological capabilities and relative bargaining power. Then a survey was taken out in Chinese domestic firms engaging in global production networks. We used hierarchical regressions to test the mechanism of network resources and innovation performance. Results showed that network resources are important sources of competitive advantage. However, the effect of network resources on firms' innovation performance was rather complicate: besides direct influences, the effect on innovation performance was partly achieved through the mediating role of technological capability and relative bargaining power. From the point of value creation, accessed resources directly enhanced innovation performance and embedded resources facilitate the technological capability and hence enhanced innovation performance. From the point of value capturing, excess use of accessed resources will cause dependency on partner firms and reduce the proportion of value appreciated by the focal firm.
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Pub Date : 2010-07-18DOI: 10.1142/S0219877012500265
Brent A. Zenobia, C. Weber
Artificial markets (AMs) are an emerging form of agent-based simulation (ABS), in which agents represent individual consumers, firms, or industries interacting under simulated market conditions. The validity of the method depends on the ability of researchers to construct simulated agents that faithfully capture the key behavior of targeted entities. Without such a correspondence the simulation cannot be considered to be a valid representation of market dynamics. To date, no such correspondence has been established. Yet, for artificial markets to achieve their potential as a tool for marketing practice it is crucial that closer ties be forged with mainstream methods for consumer behavioral research, especially qualitative methods. The primary contribution of this article is a novel method combining qualitative marketing research (inductive case studies, grounded theory, and sequence analysis) and software engineering techniques to synthesize simulation-ready theories of consumer behavior. We provide a step-by-step explanation and a demonstrative example of theory-building from the consumer technology adoption domain. The outcome is a theory of consumer adoption behavior that is sufficiently precise and formal to be expressed in Unified Modeling Language (UML). The article concludes with a discussion of the limitations of the method, recommendations for its implementation in the study of diffusion of innovation (DOI) and suggestions for further research. The arguments and findings in this article that pertain to artificial markets can be generalized with respect to most agent-based simulations, including those applied to the study of diffusion of innovation. The results of an ABS of innovation diffusion cannot be relied upon unless the agents are based on a theory of adoption that grounded in empirical observations of the targeted entities — regardless of whether those entities are consumers, firms or industries. Qualitative research of adoption behavior is thus a useful precursor to successful agent-based approaches to studying the diffusion of innovations.
{"title":"Bridging the gap between artificial market simulations and qualitative research in diffusion of innovation","authors":"Brent A. Zenobia, C. Weber","doi":"10.1142/S0219877012500265","DOIUrl":"https://doi.org/10.1142/S0219877012500265","url":null,"abstract":"Artificial markets (AMs) are an emerging form of agent-based simulation (ABS), in which agents represent individual consumers, firms, or industries interacting under simulated market conditions. The validity of the method depends on the ability of researchers to construct simulated agents that faithfully capture the key behavior of targeted entities. Without such a correspondence the simulation cannot be considered to be a valid representation of market dynamics. To date, no such correspondence has been established. Yet, for artificial markets to achieve their potential as a tool for marketing practice it is crucial that closer ties be forged with mainstream methods for consumer behavioral research, especially qualitative methods. The primary contribution of this article is a novel method combining qualitative marketing research (inductive case studies, grounded theory, and sequence analysis) and software engineering techniques to synthesize simulation-ready theories of consumer behavior. We provide a step-by-step explanation and a demonstrative example of theory-building from the consumer technology adoption domain. The outcome is a theory of consumer adoption behavior that is sufficiently precise and formal to be expressed in Unified Modeling Language (UML). The article concludes with a discussion of the limitations of the method, recommendations for its implementation in the study of diffusion of innovation (DOI) and suggestions for further research. The arguments and findings in this article that pertain to artificial markets can be generalized with respect to most agent-based simulations, including those applied to the study of diffusion of innovation. The results of an ABS of innovation diffusion cannot be relied upon unless the agents are based on a theory of adoption that grounded in empirical observations of the targeted entities — regardless of whether those entities are consumers, firms or industries. Qualitative research of adoption behavior is thus a useful precursor to successful agent-based approaches to studying the diffusion of innovations.","PeriodicalId":345430,"journal":{"name":"PICMET 2010 TECHNOLOGY MANAGEMENT FOR GLOBAL ECONOMIC GROWTH","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124887540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-18DOI: 10.1142/S0219877012500320
R. Vatananan, N. Gerdsri
Technology roadmapping (TRM) is gaining momentum as a strategic management tool for an organization to integrate technology into business strategy. This paper reviews over a hundred of TRM related publications to provide the community with the current state of roadmapping research and practice. From the literature, the issue of keeping a roadmap alive has been identified as the key challenge in the field. To address this challenge, operationalization and effective implementation of TRM are highlighted as the potential areas for future research.
{"title":"The current state of technology roadmapping (TRM) research and practice","authors":"R. Vatananan, N. Gerdsri","doi":"10.1142/S0219877012500320","DOIUrl":"https://doi.org/10.1142/S0219877012500320","url":null,"abstract":"Technology roadmapping (TRM) is gaining momentum as a strategic management tool for an organization to integrate technology into business strategy. This paper reviews over a hundred of TRM related publications to provide the community with the current state of roadmapping research and practice. From the literature, the issue of keeping a roadmap alive has been identified as the key challenge in the field. To address this challenge, operationalization and effective implementation of TRM are highlighted as the potential areas for future research.","PeriodicalId":345430,"journal":{"name":"PICMET 2010 TECHNOLOGY MANAGEMENT FOR GLOBAL ECONOMIC GROWTH","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116084253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-18DOI: 10.1108/14636681211222429
K. Laakso, Anita Rubin, Hannu Linturi
Mobile communication has grown out of its original scope and scale. Mobile operators have played a significant role in this phenomenon. Since the mobile operator business is highly regulated, the effects of regulation on the industry have been analyzed. The potential effects in the years up to 2015 are also considered. The aim of this paper is to discuss the possibilities of a futures-oriented method — i.e. the Delphi method, to estimate the effect of regulation on the mobile operator business. The challenge is that the method was originally created to assess experts' opinions about the course of development of a certain technology or phenomenon in the future and then, by using a scenario technique, to draw conclusions about its possible futures. Now the Delphi method is also being used to estimate past development, i.e. experts' opinions of the causes and effects of laws and other regulations in the past few decades. The paper forms a part of a larger study, the aim of which is to analyze the effects of changes in the regulatory framework for the mobile operator industry in Finland. According to this research the ultimate goals of the regulator, set as early as in the middle of the 1980s, have been actualized: In Finland there are several competing nationwide mobile operators and the use of mobile phones is cheap compared to many other countries.
{"title":"Delphi method analysis: The role of regulation in the mobile operator business in Finland","authors":"K. Laakso, Anita Rubin, Hannu Linturi","doi":"10.1108/14636681211222429","DOIUrl":"https://doi.org/10.1108/14636681211222429","url":null,"abstract":"Mobile communication has grown out of its original scope and scale. Mobile operators have played a significant role in this phenomenon. Since the mobile operator business is highly regulated, the effects of regulation on the industry have been analyzed. The potential effects in the years up to 2015 are also considered. The aim of this paper is to discuss the possibilities of a futures-oriented method — i.e. the Delphi method, to estimate the effect of regulation on the mobile operator business. The challenge is that the method was originally created to assess experts' opinions about the course of development of a certain technology or phenomenon in the future and then, by using a scenario technique, to draw conclusions about its possible futures. Now the Delphi method is also being used to estimate past development, i.e. experts' opinions of the causes and effects of laws and other regulations in the past few decades. The paper forms a part of a larger study, the aim of which is to analyze the effects of changes in the regulatory framework for the mobile operator industry in Finland. According to this research the ultimate goals of the regulator, set as early as in the middle of the 1980s, have been actualized: In Finland there are several competing nationwide mobile operators and the use of mobile phones is cheap compared to many other countries.","PeriodicalId":345430,"journal":{"name":"PICMET 2010 TECHNOLOGY MANAGEMENT FOR GLOBAL ECONOMIC GROWTH","volume":"275 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131410311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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