InterJournal Complex Systems, 904
Status: Accepted
Manuscript Number: [904]
Submission Date: 2004
An Exploration into the Uses of Agent-Based Modeling in Innovation/New Product Development Research
Author(s): Rosanna Garcia

Subject(s): CX.4



Utilizing the power of ABMs in business applications is still in its infancy. The possible applications for ABMs in the study of new product development and innovations have not yet been fully discovered. In this paper we explore the benefit and problems with modeling new product development/ innovation research using agent-based modeling. We introduce three potential areas of research; diffusion of innovations, organizational strategy, and knowledge/ information flows. We provide a few examples of possible research issues that could be addressed by agent-based models. These include, but are by no means limited to: 1. Diffusion of innovations · effects of network externalities, · word-of-mouth networks, · modeling tipping points, · social networks and viral marketing. 2. Organizations · innovation networks & collaboration, · co-evolution of competitive strategies, · R&D 'emergence' of innovations, · portfolio management, · innovation strategies & external environmental influences. 3. Knowledge/Information flows · supply chain networks, · innovation/R&D collaboration (inter and intra-organizational), · technology transfer (inter and intra-organizational & to/from customers-lead users), · strategy planning (organizational). We also provide a simplistic example of an agent-based model to address the research question of how should firms allocate resources to research (exploration) and development (exploitation) projects. The exploration for new technologies and the exploitation of existing knowledge is a central theme in the innovation process. Both activities compete for scarce resources and organizations must often make explicit decision-making policies for allocating resources between the two different types of projects. Levinthal and March (1981) warn of the dangers of exclusively engaging in either exploration or exploitation. Organizations that engage in exploration to the exclusion of exploitation are likely to find that they suffer the costs of experimentation without gaining many of its benefits. Conversely, systems that engage in exploitation to the exclusion of exploration are likely to find themselves trapped in suboptimal equilibria. We extend this theory to the innovative firms that must allocate resources to research (exploration) and development (exploitation). Maintaining an appropriate balance between the two different types of projects is a major dilemma for many innovative firms. Utilizing an agent-based model, we address this problem: 'how should a firm allocate limited resources to the two different types of project in a dynamic marketspace to maximize profitability?'. We base this model on the research and development strategy of an US-based consumer electronics manufacturer. We interviewed top management personnel in the software development group to ascertain the strategies they utilize in allocating resources to different project types. We use the innovation strategy guidelines of this consumer electronics manufacturer and Levinthal and March's (1981) organizational model of adaptive exploration and exploitation search to examine our research question. In this model, two firms, manufacturer1 and manufacturer2 compete for customers by 'manufacturing' and 'selling' two different types of products, incremental and innovative. Customers having a preference for incremental products are labeled as Late Adopters (LA) and customers preferring innovative products are labeled as Early Adopters (EA). Customers 'buy' products from manufacturers based on a set constant demand. Manufacturers must decide which innovation strategy will optimize performance by meeting an unknown product demand for incremental and innovative products. As in most agent-based models, both customers and manufacturers possess heterogeneous characteristics in a number of respects. The results of this study is just one example of how agent-based models can be used in the study of innovations.

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