Statistical power of structural equation models in SCM research

Journal of Purchasing and Supply Management

Volumn 20, Issue 3, 2014, Pages 208-212

  Riedl, Dominik F ^a   Kaufmann, Lutz ^a   Gaeckler, Julia ^a  

^a WHU OTTO BEISHEIM SCHOOL OF MANAGEMENT   (Germany)

Author keywords

Sample size; Statistical power; Structural equation modeling

Indexed keywords

EID: 84907084722     PISSN: 14784092     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.pursup.2014.05.004     Document Type: Article

References (42)

1. Bagozzi R.P., Yi Y. On the evaluation of structural equation models. J. Acad. Market. Sci. 1988, 36(2):421-458.
2. Bandalos D.L. The effects of item parceling on goodness-of-fit and parameter estimate bias in structural equation modeling. Struct. Equ. Model. 2002, 9(1):78-102.
3. Blair E., Zinkhan G. Nonresponse and generalizability in academic research. J. Acad. Market. Sci. 2006, 34(1):4-7.
4. Brewer B.L., Ashenbaum B., Carter J.R. Understanding the supply chain outsourcing cascade: when does procurement follow manufacturing out the door?. J. Supply Chain Manage. 2013, 49(3):90-110.
5. Brock J.K.-U. The 'power' of international business research. J. Int. Bus. Stud. 2003, 34(1):90-99.
6. Cashen L.H., Geiger S.W. Statistical power and the testing of null hypotheses: a review of contemporary management research and recommendations for future studies. Organ. Res. Methods 2004, 7(2):151-167.
7. Chin W.W. Issues and opinion on structural equation modeling. MIS Q. 1998, 22(1):VII-XVI.
8. Combs J.G. From the editors: big samples and small effects: let's not trade relevance and rigor for power. Acad. Manage. J. 2010, 51(1):9-13.
9. Cortina J.M. Big things have small beginnings: an assortment of "minor" methodological misunderstandings. J. Manage. 2002, 28(3):339-362.
10. De Beuckelaer A., Wagner S.M. Small sample surveys: increasing rigor in supply chain management research. Int. J. Phys. Distrib. Logist. Manage. 2012, 42(7):615-639.
11. Eltantawy R.A., Giunipero L. An empirical examination of strategic sourcing dominant logic: strategic sourcing centricity. J. Purch. Supply Manage. 2013, 19(4):215-226.
12. Fan X., Thompson B., Wang L. Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Struct. Equ. Model. 1999, 6(1):56-83.
13. Ferguson T.D., Ketchen D.J. Organizational configurations and performance: the role of statistical power in extant research. Strategic Manage. J. 1999, 20(4):385-395.
14. Fornell C., Larcker D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Market. Res. 1981, 18(1):39-50.
15. Fugate B.S., Stank T.P., Mentzer J.T. Linking improved knowledge management to operational and organizational performance. J. Oper. Manage. 2009, 27(3):247-264.
16. Giunipero L.C., Hooker R.E., Joseph-Matthews S., Yoon T.E., Brudvig S. A decade of SCM literature: past, present and future implications. J. Supply Chain Manage. 2008, 44(4):66-86.
17. Graham J.W. Missing data analysis: making it work in the real world. Annu. Rev. Psychol. 2009, 60:549-576.
18. Hair J.F., Black W.C., Babin B.J., Anderson R.E., Tatham R.L. Multivariate Data Analysis 2006, Pearson/Prentice Hall, Upper Saddle River, NJ.
19. Howard G.S., Maxwell S.E., Fleming K.J. The proof of the pudding: an illustration of the relative strengths of null hypothesis, meta-analysis, and bayesian analysis. Psychol. Methods 2000, 5(3):315-332.
20. Kim K.H. The relation among fit indexes, power, and sample size in structural equation modeling. Struct. Equ. Model. 2005, 12(3):368-390.
21. Kline R.B. Principles and Practice of Structural Equation Modeling 2005, Guilford Press, New York, NY.
22. MacCallum R.C., Austin J.T. Applications of structural equation modeling in psychological research. Annu. Rev. Psychol. 2000, 51(1):201-226.
23. MacCallum R.C., Browne M.W., Sugawara H.M. Power analysis and determination of sample size for covariance structure modeling. Psychol. Methods 1996, 1(2):130-149.
24. Malhotra M.K., Grover V. An assessment of survey research in POM: from constructs to theory. J. Oper. Manage. 1998, 16(4):407-425.
25. Maxwell S.E. The persistence of underpowered studies in psychological research: causes, consequences, and remedies. Psychol. Methods 2004, 9(2):147-163.
26. Maxwell S.E., Kelley K., Rausch J.R. Sample size planning for statistical power and accuracy in parameter estimation. Annu. Rev. Psychol. 2008, 59(1):537-563.
27. McQuitty S. Statistical power and structural equation models in business research. J. Bus. Res. 2004, 57(2):175-183.
28. Menachof D.A., Gibson B.J., Hanna J.B., Whiteing A.E. An analysis of the value of supply chain management periodicals. Int. J. Phys. Distrib. Logist. Manage. 2009, 39(2):145-165.
29. Mone M.A., Mueller G.C., Mauland W. The perceptions and usage of statistical power in applied psychology and management research. Pers. Psychol. 1996, 49(1):103-120.
30. Oke A., Kach A. Linking sourcing and collaborative strategies to financial performance: the role of operational innovation. J. Purch. Supply Manage. 2012, 18(1):46-59.
31. Peng D.X., Lai F. Using partial least squares in operations management research: a practical guideline and summary of past research. J. Oper. Manage. 2012, 30(6):467-480.
32. Raykov T., Widaman K.F. Issues in applied structural equation modeling research. Struct. Equ. Model. 1995, 2(4):289-318.
33. Reuter C., Goebel P., Foerstl K. The impact of stakeholder orientation on sustainability and cost prevalence in supplier selection decisions. J. Purch. Supply Manage. 2012, 18(4):270-281.
34. Saris W.E., Satorra A., van der Veld W.M. Testing structural equation models or detection of misspecifications?. Struct. Equ. Model. 2009, 16(4):561-582.
35. Satorra A., Saris W. Power of the likelihood ratio test in covariance structure analysis. Psychometrika 1985, 50(1):83-90.
36. Schmidt F.L., Hunter J.E. Eight common but false objections to the discontinuation of significance testing in the analysis of research data. What If There Were No Significance Tests? 1997, 37-64. Erlbaum, Hillsdale, NJ. L.L. Harlow, S.A. Mulaik, J.H. Steiger (Eds.).
37. Shah R., Goldstein S.M. Use of structural equation modeling in operations management research: looking back and forward. J. Oper. Manage. 2006, 24(2):148-169.
38. Shook C.L., Ketchen D.J., Hult G.T.M., Kacmar K.M. An assessment of the use of structural equation modeling in strategic managment research. Strategic Manage. J. 2004, 25(4):397-404.
39. Verma R., Goodale J.C. Statistical power in operations management research. J. Oper. Manage. 1995, 13(2):139-152.
40. Wagner S.M., Kemmerling R. Handling nonresponse in logistics research. J. Bus. Logist. 2010, 31(2):357-381.
41. Wu Y., Cegielski C.G., Hazen B.T., Hall D.J. Cloud computing in support of supply chain information system infrastructure: understanding when to go to the cloud. J. Supply Chain Manage. 2013, 49(3):25-41.
42. Zsidisin G.A., Smith M.E., McNally R.C., Kull T.J. Evaluation criteria development and assessment of purchasing and supply management journals. J. Oper. Manage. 2007, 25(1):165-183.