Sustainable Diffusion of Inter-Organizational Technology in Supply Chains: An Approach to Heterogeneous Levels of Risk Aversion

Daeheon Choi, Chune Young Chung and Kaun Y. Lee
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Daeheon Choi: College of Business Administration, Kookmin University, 77 Jeongneung-ro, Seongbuk-gu, Seoul 02707, Korea
Chune Young Chung: School of Business Administration, College of Business and Economics, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea
Kaun Y. Lee: School of Business Administration, College of Business and Economics, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea

Sustainability, 2018, vol. 10, issue 6, 1-15

Abstract: This paper develops a model to analyze inter-organizational technology adoption in a supply chain. While the basic model is general, this study is motivated by several cases of inter-organizational technology adoption in supply chains. The proposed model in this study considers firms on both levels of the supply chain, namely, supplier firms and buyer firms. These individual firms’ thresholds for adoption should be considered by other firms’ decisions within a network, together with their own organizational attributes. The heterogeneity across the population should be allowed. That is, individual firms make a decision for adopting the technology at different times due to their different network sizes, prior beliefs, and amounts of information observed. The main finding is that this uncertainty decreases as other suppliers adopt the technology, and information about their experiences becomes available. In addition, at any given time, an estimate of the benefit to a supplier depends on the number of supplier firms and on the number of buyer firms that have already adopted the technology. Thus, we seek to capture this dependence and analyze its effect on the adoption of a new inter-organizational technology. The next step is to embed the firm-level adoption model into a population model. The model includes various types of heterogeneity in the population model to capture the factors affecting the speed of diffusion. This allows us to derive an adoption curve that is specified by the accumulated fraction of firms that have adopted the technology in or before any given period. The population model allows us to consider the effect of several strategies observed in practice and numerical experiments yielding many managerial implications in this area.

Keywords: inter-organizational technology; technology diffusion; sustainable supply chain; network effect; dynamic model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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