Skip to main content
SpringerLink
Log in

Survey Study

  • Chapter
  • First Online:
Achieving Supply Chain Agility

  • 846 Accesses

Abstract

The chapter presents the survey analysis, using PLS to assess the 6 automotive firms covering IS department, logistics/distribution function, procurement function, manufacturing functions. The survey establishes the hierarchy of the four dimensions of supply chain agility as well as the indirect relationship between data consistency and IS integration.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modelling in practice: A review and recommended two-step approach. Psychological Bulletin,103(3), 411–423.

    Article  Google Scholar 

  • Archer, N., Kang, S., & Kang, C. (2008). Barriers to adoption of online supply chain solution in small and medium enterprises. Supply Chain Management: An International Journal,13(1), 73–82.

    Article  Google Scholar 

  • Auramo, J., Kauremaa, J., & Tanskanen, K. (2005). Benefits of IT in supply chain management: An explorative study of progressive companies. International Journal of Physical Distribution & Logistics Management,35(2), 82–100.

    Article  Google Scholar 

  • Barclay, D., Higgins, C., & Thomson, R. (1995). The partial least square approach to causal modelling, personal computer adoption and use as an illustration. Technology Studies,2(2), 285–309.

    Google Scholar 

  • Brace, N., Kemp, R., & Snelgar, R. (2006). SPSS for psychologists (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Buckingham, A., & Saunders, P. 2004. The survey methods workbook: From design to analysis. Cambridge and Malden: Polity.

    Google Scholar 

  • Childerhourse, P., Hermiz, R., Mason-Jones, R., Popp, A., & Tower, D. R. (2003). Information flows in automotive supply chains-identifying and learning to overcome barriers to change. Industry Management & Data System,103(7), 491–502.

    Article  Google Scholar 

  • Christopher, M. (2005). Logistics and supply chain management: Creating value-adding networks (3rd ed.). Harlow, UK: Prentice Hall.

    Google Scholar 

  • Christopher, M., Lowson, R., & Peck, H. (2004). Creating supply chains agility in fashion industry. International Journal of Retail & Distribution Management,32(8), 367–376.

    Article  Google Scholar 

  • Denolf, J. M., Trienekens, J. H., Wognum, P. M., van der Vorst, J. G. A. J., & Omta, S. W. F. (2015). Towards a framework of critical success factors for implementing supply chain information systems. Computers in Industry,68, 16–26.

    Article  Google Scholar 

  • Devaraj, S., Krajewski, L., & Wei, J. C. (2007). Impact of eBusiness technologies on operational performance: The role of production information integration in the supply chain. Journal of Operations Management,25, 1199–1216.

    Article  Google Scholar 

  • DeVellis, R. F. (1991). Scale development: Theory and applications. Newbury Park: Sage.

    Google Scholar 

  • Efron, B., & Tibshirani, R. (1993). An introduction to the bootstrap. New York: Chapman Hall.

    Book  Google Scholar 

  • Elmuti, D., Minnis, W., & Abebe, M. (2008). Longitudinal assessment of an integrated industrial supply chain. Supply Chain Management: An International Journal,13(2), 151–159.

    Article  Google Scholar 

  • Fawcett, S. E., Magnan, G. M., & McCarter, M. W. (2008). Benefits, barriers, and bridges to effective supply chain management. Supply Chain Management: An International Journal,13(1), 35–48.

    Article  Google Scholar 

  • Ferdows, K., & de Meyer, A. (1990). Last improvement in manufacturing. Journal of Operations Management,9(2), 168–184.

    Article  Google Scholar 

  • Fitzgerald, L., Johnston, R., Brignall, S., Silvestro, R., & Voss, C. (1991). Performance measurement in service business. London: CIMA.

    Google Scholar 

  • Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research,18(1), 39–50.

    Article  Google Scholar 

  • Frohlich, M. T. (2002). e-Integration in the supply chain barriers performance. Decision Science,33(4), 537–556.

    Article  Google Scholar 

  • Gefen, D., Straub, D., & Boudreau, M. (2000). Structural equation modelling and regression: Guidelines for research practice. Communications of AIS,4(7), 1–76.

    Google Scholar 

  • Gunasekaran, A., Lai, K., & Cheng, T. C. (2008). Responsive supply chain: A competitive strategy in a networked economy. Omega,36, 549–564.

    Article  Google Scholar 

  • Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2005). Multivariate data analysis. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Hausman, A., & Stock, J. R. (2003). Adoption and implementation of technological innovations within long-term relationships. Journal of Business Research,56(8), 681–686.

    Article  Google Scholar 

  • Holweg, M. (2005). An investigation into supplier responsiveness-empirical evidence from the automotive industry. International Journal of Logistics Management,16(1), 96–119.

    Google Scholar 

  • Holweg, M., & Pil, F. K. (2008). Theoretical perspectives on the coordination of supply chains. Journal of Operations Management,26, 389–406.

    Article  Google Scholar 

  • Howell, J. M., & Higgins, C. A. (1990). Champions of technological innovation. Administrative Science Quarterly,35(2), 317–341.

    Article  Google Scholar 

  • Huber, G. (1990). A theory of the effects of advanced information technologies on organisational, design, intelligence and decision making. Academy of Management Review,15(1), 47–71.

    Article  Google Scholar 

  • Hufnagel, E. M., & Conca, C. (1994). User response data: The potential for errors and biases. Information Systems Research,5(1), 48–73.

    Article  Google Scholar 

  • Ismail, H. S., & Sharifi, H. (2006). A balanced approach to building agile supply chains. International Journal of Physical Distribution & Logistics Management,36(6), 431–444.

    Article  Google Scholar 

  • Kalakota, R., & Robinson, M. (1999). e-Business: Roadmap for success. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Kerlinger, F. N. (1986). Foundations of behavioural research (4th ed.). Fort Worth and London: Harcourt College.

    Google Scholar 

  • Kinnear, P. R., & Gray, C. (2006). SPSS 14 made simple. Hove and New York: Psychology Press.

    Book  Google Scholar 

  • Kohil, A. K., Jaworski, B. J., & Kumar, A. (1993). Markor: A measure of market orientation. Journal of Marketing Research,30(4), 467–477.

    Article  Google Scholar 

  • Levy, M., & Phillip, P. (1998). SME flexibility and the role of information systems. Small Business Economics,11(2), 183–196.

    Article  Google Scholar 

  • Maiga, A. S., Nilsson, A., & Ax, C. (2015). Relationships between internal and external information systems integration, cost and quality performance and firm profitability. International Journal of Production Economics,169, 422–434.

    Article  Google Scholar 

  • Mondragon, A. E., Lyons, A. C., & Kehoe, D. F. (2004). Assessing the value of information systems in supporting agility in high-tech manufacturing enterprises. International Journal of Operations & Production Management,24, 1219–1246.

    Article  Google Scholar 

  • Naylor, J. B., Naim, M. M., & Berry, D. (1999). Leagility: Integrating the lean and agile manufacturing paradigms in the total supply chain. International Journal of Production Economics,62, 107–118.

    Article  Google Scholar 

  • Neely, A., Gregory, M., & Platts, K. (1995). Performance measurement system design. International Journal of Operations & Production Management,15(4), 80–116.

    Article  Google Scholar 

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

    Google Scholar 

  • Nunnally, J. C., & Berstein, I. H. (1994). Psychometric theory. New York and London: McGraw-Hill.

    Google Scholar 

  • Pagell, M. (2004). Understanding the factors that enable and inhibit the integration of operations, purchasing and logistics. Journal of Operations Management,22, 459–487.

    Article  Google Scholar 

  • Pearcy, D., & Giunipero, L. C. (2008). Using e-procurement applications to achieve integration: What role does firm size play. Supply Chain Management: An International Journal,13(1), 26–34.

    Article  Google Scholar 

  • Prajogo, D., & Olhager, J. (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration. International Journal of Production Economics,135, 514–522.

    Article  Google Scholar 

  • Rai, A., Patnayakuni, R., & Seth, N. (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly, 30(2), 225–246 (Wixon, B. H.).

    Article  Google Scholar 

  • Reichhart, A., & Holweg, M. (2007). Creating the customer-responsive supply chain: A reconciliation of concepts. International Journal of Operations & Production Management,27(11), 1144–1172.

    Article  Google Scholar 

  • Roth, A., & Miller, J. G. (1990). Manufacturing strategy, manufacturing strength, managerial success and economic outcomes. In J. E. Ettlie, M. C. Burnstein, & A. Feigenbaum (Eds.), Manufacturing strategy: The research agenda for the next decade (pp. 85–96). Boston: Kluwer Academic.

    Google Scholar 

  • Sanders, N. R. (2007). An empirical study of the impact of e-business technologies on organisational collaboration and performance. Journal of Operations Management,25, 1332–1347.

    Article  Google Scholar 

  • Sanders, N. R., & Premus, R. (2002). IT applications in supply chain organisations: A link between competitive priorities and organisational benefits. Journal of Business Logistics,23(1), 65–83.

    Article  Google Scholar 

  • Seethamraju, R. (2006). Do enterprise systems enable supply chain integration. ICBE + eBRF Conference, Tampere, Finland, 28 November–2 December 2006.

    Google Scholar 

  • Slack, N., Chambers, S., & Johnston, R. (2007). Operations management (5th ed.). London: Prentice Hall.

    Google Scholar 

  • Swafford, P. M., Ghosh, S., & Murthy, N. (2008). Achieving supply chain agility through IT integration and flexibility. International Journal of Production Economics,116(2), 288–297.

    Article  Google Scholar 

  • Tarn, J. M., Yue, D. C., & Beaumont, M. (2002). Exploring the rationales for ERP and SCM integration. Industry Management & Data Systems,102(1), 26–34.

    Article  Google Scholar 

  • Urbach, N., & Ahlemann, F. (2010). Structual equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application,11(2), 5–40.

    Google Scholar 

  • Van Hoek, R. I., Harrison, A., & Christopher, M. (2001). Measuring agile capabilities in the supply chain. International Journal of Operations & Production Management,21(1/2), 126–147.

    Article  Google Scholar 

  • Vickery, S., Droge, C., & Markland, R. (1997). Dimensions of manufacturing strength in the furniture industry. Journal of Operations Management,15, 317–330.

    Article  Google Scholar 

  • Wixon, B. H., & Watson, H. J. (2001). An empirical investigation of the factors affecting data warehousing success. MIS Quarterly,25(1), 17–41.

    Article  Google Scholar 

  • Zhou, H., & Benton, Jr., W. C. 2007. Supply chain practice and information sharing. Journal of Operations Management, 25, 1348–1365.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Beijing, China

    Yi Wu

Authors
  1. Yi Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2019 The Author(s)

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Wu, Y. (2019). Survey Study. In: Achieving Supply Chain Agility. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-98440-7_7

Download citation

Publish with us

Policies and ethics

Search

Navigation