Skip to main content

Quantitative Results

  • Chapter
  • First Online:
Responsible Product Innovation

Abstract

This chapter presents the results of our data analysis procedures on the 12 hypotheses about responsible product innovation as described in Chap. 4 on methodology. Specifically, measurement model and structural model assessment was carried out to test hypotheses 1 through 8, MANOVA was performed to evaluate hypotheses 9 and 10, and multigroup analysis was conducted to test hypotheses 11 and 12. Eight of the 12 main hypotheses are supported. Product safety strategy, product safety culture, and NPD process are predictors of product safety performance, but concurrent engineering is not significantly related to product safety.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

References

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 453–460.

    Article  Google Scholar 

  • Bagozzi, R. P., Yi, Y., & Philips, L. W. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 36, 421–458.

    Article  Google Scholar 

  • Bapuji, H., & Beamish, P. W. (2008). Product recalls: Avoid hazardous design flaws. Harvard Business Review, 86(3), 23–26.

    Google Scholar 

  • Beamish, P. W., & Bapuji, H. (2008). Toy recalls and China: Emotion vs. evidence. Management and Organization Review, 4(2), 197–209.

    Article  Google Scholar 

  • Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (2004a). Benchmarking best practices–I. Research Technology Management, 47(1), 31–44.

    Article  Google Scholar 

  • Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (2004b). Benchmarking best practices–II. Research Technology Management, 47(3), 51–59.

    Article  Google Scholar 

  • Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (2004c). Benchmarking best practices–IIII. Research Technology Management, 47(6), 43–55.

    Article  Google Scholar 

  • DeCoster, J. (2004). Data Analysis in SPSS. Retrieved from: http://www.stat-help.com/notes.html. Accessed on 18 June 2010.

  • Doll, W. J., Hendrickson, A., & Deng, X. (1998). Using Davis’s perceived usefulness and ease-of-use instruments for decision making: A confirmatory and multigroup invariance analysis. Decision Sciences, 29(4), 839–869.

    Article  Google Scholar 

  • Ghiselli, E. E., Campbell, J. P., & Zedeck, S. (1981). Measurement theory for the behavioral sciences. San Francisco: W.H. Freeman.

    Google Scholar 

  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Upper Saddle: Pearson Education/Prentice Hall.

    Google Scholar 

  • Koufteros, X., Vonderembse, M., & Doll, W. (2001). Concurrent engineering and its consequences. Journal of Operations Management, 19, 97–115.

    Article  Google Scholar 

  • Land, K. C. (1969). Principles of path analysis. In E. F. Borgatta (Ed.), Sociological methodology (pp. 3–37). San Francisco: Jossey-Bass.

    Google Scholar 

  • Nunnally, J. C. (1978). Psychometric theory (2nd ed.). MacGraw-Hill: New York.

    Google Scholar 

  • Olson, C. L. (1974). Comparative robustness of six tests in multivariate analysis of variance. Journal of the American Statistical Association, 69(348), 894–908.

    Article  Google Scholar 

  • Saraph, J., Benson, P., & Schroeder, R. (1989). An instrument for measuring the critical factors of quality management. Decision Sciences, 20(4), 810–829.

    Article  Google Scholar 

  • White, T., & Pomponi, R. (2003). Gain a competitive edge by preventing recalls. Quality Progress, 36(8), 41–49.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Zhu, A.Y., von Zedtwitz, M., Assimakopoulos, D.G. (2018). Quantitative Results. In: Responsible Product Innovation. Innovation, Technology, and Knowledge Management. Springer, Cham. https://doi.org/10.1007/978-3-319-68451-2_5

Download citation

Publish with us

Policies and ethics