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The Adoption Time Period for Some Transportation Innovations

Author

Listed:
  • John E. Ettlie

    (DePaul University)

  • David B. Vellenga

    (Iowa State University)

Abstract

Six transportation firms (one in each mode) participated in an exploratory study to investigate factors that influence the time lag in decision making over the adoption and implementation stages for innovation. For a sample of 32 innovations, the single best predictor of the amount of time required to progress from one stage of the decision-making process to the next was the cost of the innovation (R 2 = 0.23, p 2 ) in the innovation and adoption time period. A recursive, multi-stage path model was constructed and in general it was found that secondary innovation attributes act as intervening variables for the influence of climate, union reaction, and government regulation and intervention on the innovation and adoption time period. The results of the study suggest that the key leverage point at the firm level for influencing the adoption time period is the risk-taking climate of an organization. If an organization climate exists or can be created which is characterized as supporting calculated risks, then, significantly, the following impacts are likely to occur: (1) the relative advantage necessary for consideration and adoption will be lower than for more conservative firms, but this lower required relative advantage will also stimulate RD&E spending; (2) innovations considered for adoption are likely to have fewer concrete performance criteria; and (3) innovations are likely to be viewed as less complex but more time will be required to reduce this complexity through learning. The results of the study also suggest that individuals with high risk-taking propensity will not be a sufficient single condition to change or alter the risk-taking climate of an organization. The conversion from a conservative climate to one supporting calculated risk is obviously not an easy matter nor is it likely to happen in a short period of time. It is likely to be the product of a group or team-building effort, recognizing the value of diversity in organization membership. Individuals seem to stimulate the innovation process most when a recent manpower flow is involved; that is, the crossing of an organizational boundary by a key organizational member coming to the organization or department of the transportation firm. Influencing the risk-taking climate of an organization alone will not have an impact on the perceived compatibility of the innovations considered for adoption nor the relative ease of testing or trying innovations on a limited basis, even though these two innovation attributes vary significantly and directly. One possible explanation for this result is that during the trial period, the innovation is modified to make it more compatible with organization constraints. Based on the results of this study, with a limited sample of transportation innovations, some mechanism other than organization climate will have to be sought to achieve a fit between innovation, organization and environment. The significant findings of this study do not immediately suggest this approach. Concerning innovation policy and government intervention and action which influences the adoption process, several implications from these data are apparent. First, government action has the least pervasive influence in a model of adoption time period, which suggests that the influence of government actions might be on other aspects of the adoption process: for example, the type of innovations that are considered, the agenda for decision making and an organizational mechanism which builds slowly over time to cope with government in a classically regulated industry. Second, there is some evidence, albeit weak, that government action can have a long-range impact on the adoption process by drawing attention to particular innovations or reordering decision-making or spending priorities or perhaps by increasing the consistency of agency treatments of firms.

Suggested Citation

  • John E. Ettlie & David B. Vellenga, 1979. "The Adoption Time Period for Some Transportation Innovations," Management Science, INFORMS, vol. 25(5), pages 429-443, May.
  • Handle: RePEc:inm:ormnsc:v:25:y:1979:i:5:p:429-443
    DOI: 10.1287/mnsc.25.5.429
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    Citations

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    Cited by:

    1. Scott A. Shane & Karl T. Ulrich, 2004. "50th Anniversary Article: Technological Innovation, Product Development, and Entrepreneurship in Management Science," Management Science, INFORMS, vol. 50(2), pages 133-144, February.
    2. Chen, Chung-Jen, 2009. "Technology commercialization, incubator and venture capital, and new venture performance," Journal of Business Research, Elsevier, vol. 62(1), pages 93-103, January.
    3. van Hezewijk, A.P. & van Assen, M.F. & van de Velde, S.L., 2003. "The impact of innovation and organizational factors on APS adoption: Evidence from the Dutch discrete parts industry," ERIM Report Series Research in Management ERS-2003-084-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Costa, Álvaro & Fernandes, Ruben, 2012. "Urban public transport in Europe: Technology diffusion and market organisation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 269-284.
    5. Kang, Jae Hyeung & Matusik, James G. & Kim, Tae-Yeol & Phillips, J. Mark, 2016. "Interactive effects of multiple organizational climates on employee innovative behavior in entrepreneurial firms: A cross-level investigation," Journal of Business Venturing, Elsevier, vol. 31(6), pages 628-642.
    6. Yang, Yefei & Yee, Rachel W.Y., 2022. "The effect of process digitalization initiative on firm performance: A dynamic capability development perspective," International Journal of Production Economics, Elsevier, vol. 254(C).

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