Diffusion of new products in risk‐sensitive markets

Oren, Shmuel S.; Schwartz, Rick G.

doi:10.1002/for.3980070407

Cited by 59 publications

(32 citation statements)

References 15 publications

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“…Here, the Bayesian approach has been employed in many models to conceptualize this information integration process. Oren and Schwartz [5] show that consumers are Bayesian in that they update their uncertainties by combining observed outcomes with their prior uncertainty through beta-Bernoulli updating. The authors also consider that consumers adopt a technology once they pass a risk aversion threshold.…”

Section: Literature Reviewmentioning

confidence: 99%

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

2018

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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.

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Section: Literature Reviewmentioning

confidence: 99%

“…where π t+1 (s t+1 ) is the optimal strategy in the coming period, as expressed in Equation (5). The firm will adopt in period t if (i) VA t > 0 and (ii) VA t − N A t > 0.…”

Section: Multi-period Modelmentioning

confidence: 99%

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

2018

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“…The Bayesian modeling approach to conceptualizing the information integration process has been employed in many models for technology adoption. Oren and Schwartz [27] shows that consumers are Bayesian in that they update their uncertainties by combining the observed outcomes with their prior uncertainty according to the beta-Bernoulli updating. They also consider that the consumer will adopt once passing a risk-aversion threshold.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Ulu and Smith [34] recently extended that model to consider general probability distributions for benefit and general information signals. Chatterjee and Eliashberg [15] adopt a similar approach to Oren and Schwartz [27]. They applied normal-normal Bayesian updating for the potential adopter's perception of the innovation as one unit of new information is received.…”

Section: Literature Reviewmentioning

confidence: 99%

Adoption and Diffusion Speed of New Technology with Network Externality in a Two-level Supply Chain : An Approach to Relative Factors in Buyer-Supplier Relationships

Choi¹

2013

Journal of the Korean Operations Research and Management Scienc

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Thi s paper devel ops a model to predi ct the adopti on and l evel of usage of network technol ogy i n a two-l evel suppl y chai n wi th buyer-suppl i er rel ati onshi ps. A fi rm's adopti on of a new technol ogy depends not onl y on i ts own bel i efs of the new technol ogy's costs and benefi ts, but al so on the adopti on deci si ons of other fi rms i n the suppl y chai n. A model fi rst anal yzes an i ndi vi dual suppl i er's deci si on about a new technol ogy adopti on consi deri ng wi th mul ti pl e suppl i ers and buyers. Indi vi dual suppl i ers' deci si ons are aggregated wi th a popul ati on model to proj ect how new technol ogy di ffuses across the suppl y chai n and exami ne the pattern of di ffusi on process. Thi s study found that as more fi rms adopt i n i ni ti al peri ods, the total amount of i nformati on to the potenti al adopters i n the popul ati on i ncreases, and then the number of fi rms persuaded by the i nformati on i ncreases as the process moves up the di stri buti on of adopti on process. We consi der three factors i nfl uenci ng the di ffusi on speed of the new technol ogy i n a suppl y chai n network : mean benefi ts, cost shari ng, and i nformati on provi si on. Thi s study exami nes how such factors affect the reducti on of threshol d l evel s, whi ch i mpl i es that reducti ons i n threshol d l evel s have an aggregate effect by accel erati ng the rate of adopti on. In parti cul ar, we expl ore rel ati onshi p factors avai l abl e i n practi ce i n a buyer-suppl i er rel ati onshi p and numeri cal l y exami nes how these rel ati onshi p factors contri bute to i ncrease the di ffusi on speed of the technol ogy i n a two-l evel suppl y chai n Keyword：Technol ogy Adopti on, Di ffusi on Speed, Buyer-Suppl i er Rel ati onshi ps, Two-Level Suppl y Chai n, Network External i ti es 한국경영과학회지 제38권 제3호 2013년 9월 52 최 대 헌

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“…In recent years, attempts have been made by Hiebert (1974), Stoneman (1981), Feder andO'Mara (1982), Jensen (1982), Oren and Schwartz (1988), Eliashberg (1989), andLattin andRoberts (1989) to develop diffusion models by specifying adoption decisions at the individual level. In these models one assumes that, at any time t, a potential adopter's utility for an innovation is based on his uncertain perception of the innovation's Q' Table 6.2.…”

Section: Diffusion Models From Individual Adoption Decisionsmentioning

confidence: 99%