Do right PLS and do PLS right: A critical review of the application of PLS-SEM in construction management research

Abstract

Partial least squares structural equation modeling (PLS-SEM) is a modern multivariate analysis technique with a demonstrated ability to estimate theoretically established cause-effect relationship models. This technique has been increasingly adopted in construction management research over the last two decades. Accordingly, a critical review of studies adopting PLS-SEM appears to be a timely and valuable endeavor. This paper offers a critical review of 139 articles that applied PLS-SEM from 2002 to 2019. Results show that the misuse of PLS-SEM can be avoided. Critical issues related to the application of PLS-SEM, research design, model development, and model evaluation are discussed in detail. This paper is the first to highlight the use and misuse of PLS-SEM in the construction management area and provides recommendations to facilitate the future application of PLS-SEM in this field.

Graphical abstract

Keywords

PLS / SEM / construction management / literature review / misuse

References

[1] Ashraf M (2004). A critical look at the use of group projects as a pedagogical tool. Journal of Education for Business, 79(4): 213–216

[2] Bagozzi R P (2011). Measurement and meaning in information systems and organizational research: Methodological and philosophical foundations. Management Information Systems Quarterly, 35(2): 261–292

[3] Bagozzi R P, Yi Y (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1): 74–94

[4] Becker J M, Rai A, Ringle C M, Völckner F (2013). Discovering unobserved heterogeneity in structural equation models to avert validity threats. Management Information Systems Quarterly, 37(3): 665–694

[5] Bentler M (1980). Multivariate analysis with latent variables: Causal modeling. Annual Review of Psychology, 31(1): 419–456

[6] Bjorvatn T, Wald A (2018). Project complexity and team-level absorptive capacity as drivers of project management performance. International Journal of Project Management, 36(6): 876–888

[7] Blomquist T, Hällgren M, Nilsson A, Söderholm A (2010). Project-as-practice: In search of project management research that matters. Project Management Journal, 41(1): 5–16

[8] Bollen K, Lennox R (1991). Conventional wisdom on measurement: A structural equation perspective. Psychological Bulletin, 110(2): 305–314

[9] Bröchner J, Björk B C (2008). Where to submit? Journal choice by construction management authors. Construction Management and Economics, 26(7): 739–749

[10] Cao D, Li H, Wang G (2014). Impacts of isomorphic pressures on BIM adoption in construction projects. Journal of Construction Engineering and Management, 140(12): 04014056

[11] Chin W W (1998). The partial least squares approach to structural equation modelling. In: Marcoulides G A, ed. Modern Methods for Business Research. London: Lawrence Erlbaum Associates, 295–336

[12] Chin W W (2010). How to write up and report PLS analyses. In: Esposito Vinzi V, Chin W W, Henseler J, Wang H, eds. Handbook of Partial Least Squares. Berlin: Springer, 655–690

[13] Chin W W, Peterson R A, Brown S P (2008). Structural equation modeling in marketing: Some practical reminders. Journal of Marketing Theory and Practice, 16(4): 287–298

[14] Comrey A L (1993). A First Course in Factor Analysis. London: Psychology Press

[15] Cronbach L J (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3): 297–334

[16] Diamantopoulos A, Riefler P, Roth K P (2008). Advancing formative measurement models. Journal of Business Research, 61(12): 1203–1218

[17] Diamantopoulos A, Winklhofer H M (2001). Index construction with formative indicators: An alternative to scale development. Journal of Marketing Research, 38(2): 269–277

[18] Dijkstra T K (2010). Latent variables and indices: Herman Wold’s basic design and partial least squares. In: Esposito Vinzi V, Chin W W, Henseler J, Wang H, eds. Handbook of Partial Least Squares. Berlin: Springer, 23–46

[19] Fellows R F, Liu A M M (2015). Research Methods for Construction. 4th ed. Hoboken, NJ: John Wiley & Sons

[20] Fornell C, Bookstein F L (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4): 440–452

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

[22] Goertz G, Mahoney J (2012). A Tale of Two Cultures: Qualitative and Quantitative Research in the Social Sciences. Princeton: Princeton University Press

[23] Grant M J, Booth A (2009). A typology of reviews: An analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26(2): 91–108

[24] Gregor S, Klein G (2014). Eight obstacles to overcome in the theory testing genre. Journal of the Association for Information Systems, 15(11): 5

[25] Gudergan S P, Ringle C M, Wende S, Will A (2008). Confirmatory tetrad analysis in PLS path modeling. Journal of Business Research, 61(12): 1238–1249

[26] Hahn C, Johnson M D, Herrmann A, Huber F (2002). Capturing customer heterogeneity using a finite mixture PLS approach. Schmalenbach Business Review, 54(3): 243–269

[27] Hair Jr J F, Howard M C, Nitzl C (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109: 101–110

[28] Hair Jr J F, Ringle C M, Sarstedt M (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2): 139–152

[29] Hair Jr J F, Sarstedt M, Hopkins L, Kuppelwieser V G (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2): 106–121

[30] Hair Jr J F, Sarstedt M, Ringle C M, Mena J A (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3): 414–433

[31] Hartmann A, Hietbrink M (2013). An exploratory study on the relationship between stakeholder expectations, experiences and satisfaction in road maintenance. Construction Management and Economics, 31(4): 345–358

[32] Harwood T G, Garry T (2003). An overview of content analysis. Marketing Review, 3(4): 479–498

[33] Henseler J, Chin W W (2010). A comparison of approaches for the analysis of interaction effects between latent variables using partial least squares path modeling. Structural Equation Modeling, 17(1): 82–109

[34] Hulland J (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2): 195–204

[35] Jarvis C B, MacKenzie S B, Podsakoff M (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research, 30(2): 199–218

[36] Kante M, Chepken C, Oboko R (2018). Partial least square structural equation modelling’s use in information systems: An updated guideline of practices in exploratory settings. Journal of Research & Innovation, 6(1): 49–67

[37] Klein G, Müller R (2019). Quantitative research submissions to project management. Project Management Journal, 50(3): 263–265

[38] Koskela L (2017). Why is management research irrelevant? Construction Management and Economics, 35(1–2): 4–23

[39] Lachenbruch A, Cohen J (1989). Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates

[40] Mohamed S (2002). Safety climate in construction site environments. Journal of Construction Engineering and Management, 128(5): 375–384

[41] Nadhim E A, Hon C K H, Xia B, Stewart I, Fang D (2018). Investigating the relationships between safety climate and safety performance indicators in retrofitting works. Construction Economics and Building, 18(2): 110–129

[42] Ning Y, Ling F Y Y (2013). Reducing hindrances to adoption of relational behaviors in public construction projects. Journal of Construction Engineering and Management, 139(11): 04013017

[43] Nitzl C, Chin W W (2017). The case of partial least squares (PLS) path modeling in managerial accounting research. Journal of Management Control, 28(2): 137–156

[44] Nunnally J (1978). Psychometric Methods. New York: McGraw-Hill Book Co.

[45] Peter J P (1981). Construct validity: A review of basic issues and marketing practices. Journal of Marketing Research, 18(2): 133–145

[46] Petter S, Straub D, Rai A (2007). Specifying formative constructs in information systems research. Management Information Systems Quarterly, 31(4): 623–656

[47] Ringle C M, Sarstedt M, Mitchell R, Gudergan S P (2018). Partial least squares structural equation modeling in HRM research. International Journal of Human Resource Management, 31(12): 1617–1643

[48] Ringle C M, Sarstedt M, Straub D W (2012). A critical look at the use of PLS-SEM in MIS quarterly. Management Information Systems Quarterly, 36(1): iii–xiv

[49] Rossiter J R (2002). The C-OAR-SE procedure for scale development in marketing. International Journal of Research in Marketing, 19(4): 305–335

[50] Sharma P N, Shmueli G, Sarstedt M, Danks N, Ray S (2019). Prediction–oriented model selection in partial least squares path modeling. Decision Sciences, on line, doi: 10.1111/deci.12329

[51] Spector P (1992). Summated Rating Scale Construction. London: Sage Publications Inc.

[52] Streukens S, Leroi-Werelds S (2016). Bootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results. European Management Journal, 34(6): 618–632

[53] Suprapto M, Bakker H L M, Mooi H G, Hertogh M J C M (2016). How do contract types and incentives matter to project performance? International Journal of Project Management, 34(6): 1071–1087

[54] Themistocleous G, Wearne S H (2000). Project management topic coverage in journals. International Journal of Project Management, 18(1): 7–11

[55] Turner J R, Müller R (2003). On the nature of the project as a temporary organization. International Journal of Project Management, 21(1): 1–8

[56] Weir J P (2005). Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. Journal of Strength and Conditioning Research, 19(1): 231–240

[57] Wen Q, Qiang M, An N (2017). Collaborating with construction management consultants in project execution: Responsibility delegation and capability integration. Journal of Construction Engineering and Management, 143(7): 04017021

[58] Wetzels M, Odekerken-Schröder G, van Oppen C (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. Management Information Systems Quarterly, 33(1): 177

[59] Wing C K (1997). The ranking of construction management journals. Construction Management and Economics, 15(4): 387–398

[60] Wold S, Sjöström M, Eriksson L (2001). PLS-regression: A basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58(2): 109–130

[61] Xiong B, Skitmore M, Xia B (2015). A critical review of structural equation modeling applications in construction research. Automation in Construction, 49(Part A): 59–70

Open Access

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

RIGHTS & PERMISSIONS

2021 The Author(s) 2021. This article is published with open access at link.springer.com and journal.hep.com.cn