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Tips to use partial least squares structural equation modelling (PLS-SEM) in knowledge management

Cepeda-Carrion, Gabriel, Cegarra-Navarro, Juan-Gabriel, Cillo, Valentina·2019·Journal of Knowledge Management

Abstract

Purpose: Structural equation modelling (SEM) has been defined as the combination of latent variables and structural relationships. The partial least squares SEM (PLS-SEM) is used to estimate complex cause-effect relationship models with latent variables as the most salient research methods across a variety of disciplines, including knowledge management (KM). Following the path initiated by different domains in business research, this paper aims to examine how PLS-SEM has been applied in KM research, also providing some new guidelines how to improve PLS-SEM report analysis. Design/methodology/approach: To ensure an objective way to analyse relevant works in the field of KM, this study conducted a systematic literature review of 63 publications in three SSCI-indexed and specific KM journals between 2015 and 2017. Findings: Our results show that over the past three years, a significant amount of KM works has empirically used PLS-SEM. The findings also suggest that in light of recent developments of PLS-SEM reporting, some common misconceptions among KM researchers occurred mainly related to the reasons for using PLS-SEM, the purposes of PLS-SEM analysis, data characteristics, model characteristics and the evaluation of the structural models. Originality/value: This study contributes to that vast KM literature by documenting the PLS-SEM-related problems and misconceptions. Therefore, it will shed light for better reports in PLS-SEM studies in the KM field.

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Research works printed but not linked: 91

  1. 2017, Verifying relationship of knowledge management initiatives and the empowerment of human resources, Journal of Knowledge Management
  2. 2017, An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research, International Journal of Contemporary Hospitality Management
  3. 2016, How do collaboration and investments in knowledge management affect process innovation in services?, Journal of Knowledge Management, 20, 1004, 10.1108/JKM-11-2015-0429 · DOI · Paper page
  4. 2016, How to address endogeneity in partial least squares path modeling, 1
  5. 2015, Better knowledge with social media? Exploring the roles of social capital and organizational knowledge management, Journal of Knowledge Management, 19, 456, 10.1108/JKM-11-2014-0467 · DOI
  6. 2009, A follow‐up ranking of academic journals, Journal of Knowledge Management, 13, 16, 10.1108/13673270910931134 · DOI
  7. 2017, Exploring the role of human capital, renewal capital and entrepreneurial capital in innovation performance in high-tech and low-tech firms, Knowledge Management Research and Practice, 15, 369, 10.1057/s41275-017-0069-3 · DOI
  8. 2017, The influence of knowledge absorptive capacity on shared value creation in social enterprises, Journal of Knowledge Management
  9. 2017, Linking procedural memory with organizational learning through knowledge corridors, Journal of Knowledge Management
  10. 2012, Creating patient e-knowledge for patients through telemedicine technologies, Knowledge Management Research and Practice, 10, 153, 10.1057/kmrp.2011.47 · DOI
  11. 2016, Prediction-oriented modeling in business research by means of PLS path modeling: introduction to a JBR special section, Journal of Business Research, 69, 4545, 10.1016/j.jbusres.2016.03.048 · DOI
  12. 2017, Knowledge reuse through electronic knowledge repositories: a multi theoretical study, Journal of Knowledge Management, 21, 741, 10.1108/JKM-03-2016-0126 · DOI
  13. 1998, The partial least squares approach to structural equation modeling, Modern Methods for Business Research, 295, 295
  14. 1998, The partial least squares approach for structural equation modeling, 295
  15. 2010, How to write up and report PLS analyses, 655, 10.1007/978-3-540-32827-8_29 · DOI
  16. 2016, Knowledge processes, absorptive capacity and innovation: a mediation analysis, Knowledge and Process Management, 23, 207, 10.1002/kpm.1507 · DOI
  17. 2015, Relationships between social and intellectual capital: empirical evidence from IC statements, Knowledge and Process Management, 22, 99, 10.1002/kpm.1470 · DOI
  18. 2011, Linear indices in nonlinear structural equation models: best fitting proper indices and other composites. Quality and, Quality & Quantity, 45, 1505, 10.1007/s11135-010-9359-z · DOI
  19. 2015, Consistent and asymptotically normal PLS estimators for linear structural equations, Computational Statistics and Data Analysis, 81, 10, 10.1016/j.csda.2014.07.008 · DOI · Paper page
  20. 2017, Are winemaker consultants just another source of knowledge for innovation?, Journal of Knowledge Management, 21, 1523, 10.1108/JKM-01-2017-0025 · DOI
  21. 2016, Customer’s role in knowledge management and in the innovation process: effects on innovation capacity and marketing results, Knowledge Management Research & Practice, 14, 195, 10.1057/kmrp.2015.19 · DOI
  22. 2011, An update and extension to SEM guidelines for admnistrative and social science research, MIS Quarterly, 35, 3
  23. 2017, Knowledge management, problem solving and performance in top Italian firms, Journal of Knowledge Management, 21, 355, 10.1108/JKM-03-2016-0113 · DOI
  24. 2012, Does PLS have advantages for small sample size or non-normal data?, MIS Quarterly, 36, 981, 10.2307/41703490 · DOI
  25. 2016, Thinking about U: theorizing and testing U- and inverted U-shaped relationships in strategy research, Strategic Management Journal, 37, 1177, 10.1002/smj.2399 · DOI
  26. 2014, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM): Long Range Planning
  27. 2013, Partial least squares structural equation modeling: rigorous applications, better results and higher acceptance, Long Range Planning, 46, 1
  28. 2014, Partial least squares structural equation modeling (PLS-SEM), European Business Review, 26, 106, 10.1108/EBR-10-2013-0128 · DOI · Paper page
  29. 2018, Advanced Issues in Partial Least Squares Structural Equation Modeling
  30. 2016, What drives employees to share their tacit knowledge in practice?, Knowledge Management Research & Practice, 14, 295, 10.1057/kmrp.2014.32 · DOI
  31. 2013, The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis, Psychological Science, 24, 1918, 10.1177/0956797613480187 · DOI · Paper page
  32. 2017, Bridging design and behavioral research with variance-based structural equation modeling, Journal of Advertising, 46, 178, 10.1080/00913367.2017.1281780 · DOI · Paper page
  33. 2018, Partial least squares path modeling: Quo vadis?, Quality & Quantity, 52, 1, 10.1007/s11135-018-0689-6 · DOI · Paper page
  34. 2016, Testing measurement invariance of composites using partial least squares, International Marketing Review, 33, 405, 10.1108/IMR-09-2014-0304 · DOI · Paper page
  35. 2013, Goodness-of-fit indices for partial least squares path modeling, Computational Statistics, 28, 565, 10.1007/s00180-012-0317-1 · DOI
  36. 2017, Exploring the antecedents and consequences of the transactive memory system: an empirical analysis, Journal of Knowledge Management
  37. 2015, The use of intellectual capital to obtain competitive advantages in regional small and medium enterprises, Knowledge Management Research and Practice, 13, 486, 10.1057/kmrp.2014.4 · DOI
  38. 2011, Doing your literature review: traditional and sistematic techniques
  39. 2015, Sourcing knowledge for innovation: knowledge reuse and creation in project teams, Journal of Knowledge Management, 19, 932, 10.1108/JKM-01-2015-0039 · DOI
  40. 2016, The impact of knowledge management on job satisfaction, Journal of Knowledge Management, 20, 621, 10.1108/JKM-10-2015-0398 · DOI · Paper page
  41. 2017, The effect of compliance knowledge and compliance support systems on information security compliance behavior, Journal of Knowledge Management, 21, 986, 10.1108/JKM-08-2016-0353 · DOI
  42. 2014, Pulling the Sobel test up by its bootstraps, More Statistical and Methodological Myths and Urban Legends, 224
  43. 2016, IT and relationship learning in networks as drivers of green innovation and customer capital: evidence from the automobile sector, Journal of Knowledge Management, 20, 444, 10.1108/JKM-05-2015-0203 · DOI
  44. 2017, Setting a knowledge boundary across teams: knowledge protection regulation for inter-team coordination and team performance, Journal of Knowledge Management, 21, 254, 10.1108/JKM-04-2016-0163 · DOI
  45. 2015, Mechanisms to motivate knowledge sharing: integrating the reward systems and social network perspectives, Journal of Knowledge Management, 19, 212, 10.1108/JKM-05-2014-0209 · DOI
  46. 1989, Predictive vs. structural modeling: PLS vs. ML, 199, 10.1007/978-3-642-52512-4_5 · DOI · Paper page
  47. 2016, The team absorptive capacity triad: a configurational study of individual, enabling, and motivating factors, Journal of Knowledge Management, 20, 1083, 10.1108/JKM-11-2015-0433 · DOI
  48. 2017, Antecedents and effects of individual absorptive capacity: a micro-foundational perspective on open innovation, Journal of Knowledge Management
  49. 2015, Supply and demand effects on supply chain flexibility: an empirical exploration, Knowledge and Process Management, 22, 206, 10.1002/kpm.1475 · DOI
  50. 2015, The mediating role of affective commitment in the rewards–knowledge transfer relation, Journal of Knowledge Management, 19, 1167, 10.1108/JKM-03-2015-0114 · DOI
  51. 2017, Investigating the impact of organizational climate, motivational drivers, and empowering leadership on knowledge sharing, Knowledge Management Research and Practice, 15
  52. 2017, Increasing the impact of wikis on project performance: fine-tuning functional quality and knowledge sharing, Knowledge and Process Management, 24, 96, 10.1002/kpm.1535 · DOI
  53. 2005, Business performance management and unlearning process, Knowledge and Process Management, 12, 161, 10.1002/kpm.233 · DOI
  54. 2016, Mediation analysis in partial least squares path modeling, Industrial Management & Data Systems, 116, 1849, 10.1108/IMDS-07-2015-0302 · DOI · Paper page
  55. 2015, HR-related knowledge protection and innovation performance: the moderating effect of trust, Knowledge and Process Management, 22, 220, 10.1002/kpm.1476 · DOI
  56. 2017, Is social networking a waste of time? The impact of social network and knowledge characteristics on job performance, Knowledge Management Research & Practice
  57. 2015, Effects of intra- and inter-team dynamics on organisational learning: role of knowledge-sharing capability, Knowledge Management Research & Practice, 1
  58. 2016, IT-enabled knowledge management for the competitive performance of manufacturing SMEs: an absorptive capacity-based view, Knowledge and Process Management, 23, 110, 10.1002/kpm.1503 · DOI
  59. 2016, European management research using partial least squares structural equation modeling (PLS-SEM), European Management Journal, 34, 589, 10.1016/j.emj.2016.08.001 · DOI
  60. 2012, Rethinking partial least squares path modeling: in praise of simple methods, Long Range Planning, 45, 341
  61. 2014, Rethinking partial least squares path modeling: breaking chains and forging ahead, Long Range Planning, 47, 161, 10.1016/j.lrp.2014.02.003 · DOI
  62. 2016, Choosing PLS path modeling as analytical method in European management research: a realist perspective, European Management Journal, 34, 598, 10.1016/j.emj.2016.05.006 · DOI · Paper page
  63. 2017, On comparing results from CB-SEM and PLS-SEM: five perspectives and five recommendations, Marketing ZFP, 39, 4, 10.15358/0344-1369-2017-3-4 · DOI · Paper page
  64. 2005, SmartPLS 2.0
  65. 2013, A critical examination of common beliefs about partial least squares path modeling, Organizational Research Methods, 16, 425, 10.1177/1094428112474693 · DOI · Paper page
  66. 2016, Knowledge management view of environmental sustainability in manufacturing SMEs in the Philippines, Knowledge Management Research & Practice, 14, 514, 10.1057/kmrp.2015.30 · DOI
  67. 2016, Steps in research process (Partial Least Square of Structural Equation Modeling (PLS-SEM), International Journal of Social Science and Business, 1, 55
  68. 2016, Estimation issues with PLS and CBSEM: where the bias lies!, Journal of Business Research, 69, 3998, 10.1016/j.jbusres.2016.06.007 · DOI
  69. 2016, Guidelines for treating unobserved heterogeneity in tourism research: a comment on Marques and Reis (2015), Annals of Tourism Research, 57, 279, 10.1016/j.annals.2015.10.006 · DOI
  70. 2014, Partial least squares structural equation modeling (PLS-SEM): a useful tool for family business researchers, Journal of Family Business Strategy, 5, 105, 10.1016/j.jfbs.2014.01.002 · DOI · Paper page
  71. 2016, Exploration of multi-layered knowledge sharing participation: the roles of perceived benefits and costs, Journal of Knowledge Management, 20, 1247, 10.1108/JKM-01-2016-0044 · DOI
  72. 2016, Negotiate, reciprocate, or cooperate? The impact of exchange modes on inter-employee knowledge sharing, Journal of Knowledge Management, 20, 687, 10.1108/JKM-10-2015-0394 · DOI
  73. 2016, Understanding counterproductive knowledge behavior: antecedents and consequences of intra-organizational knowledge hiding, Journal of Knowledge Management, 20, 1199, 10.1108/JKM-05-2016-0203 · DOI
  74. 2016, Effects of knowledge management on client-vendor relationship quality: the mediating role of global mindset, Journal of Knowledge Management, 20, 1268, 10.1108/JKM-03-2016-0099 · DOI
  75. 2016, The elephant in the room: predictive performance of PLS models, Journal of Business Research, 69, 4552, 10.1016/j.jbusres.2016.03.049 · DOI · Paper page
  76. 2017, Factors affecting web 2.0 adoption: exploring the knowledge sharing and knowledge seeking aspects in healthcare professionals, Journal of Knowledge Management
  77. 2017, How gamification of an enterprise collaboration system increases knowledge contribution: an affordance approach, Journal of Knowledge Management, 21, 416, 10.1108/JKM-10-2016-0429 · DOI
  78. 2005, PLS path modeling, Computational Statistics & Data Analysis, 48, 159, 10.1016/j.csda.2004.03.005 · DOI · Paper page
  79. 2003, Towards a methodology for developing evidence-informed management knowledge by means of systematic review, British Journal of Management, 14, 207, 10.1111/1467-8551.00375 · DOI · Paper page
  80. 2017, Stop eulogizing, complicating or straitjacketing the concept of organizational unlearning, please, The Learning Organization, 24, 78, 10.1108/TLO-11-2016-0084 · DOI
  81. 2016, Serious games in favour of knowledge management and double-loop learning?, Knowledge Management Research & Practice, 14, 470, 10.1057/kmrp.2015.29 · DOI
  82. 2015, The impact of knowledge management and social capital on dynamic capability in organizations, Knowledge Management Research & Practice, 13, 401, 10.1057/kmrp.2013.59 · DOI
  83. 2016, Organizational trust dimensions as antecedents of organizational commitment, Knowledge and Process Management, 23, 46, 10.1002/kpm.1497 · DOI
  84. 2017, Performance and intellectual capital: how enablers drive value creation in organisations, Knowledge and Process Management, 24, 114, 10.1002/kpm.1537 · DOI
  85. 2016, Harnessing network-based intellectual capital in online academic networks: from the organizational policies and practices towards competitiveness, Journal of Knowledge Management, 20, 594, 10.1108/JKM-05-2015-0208 · DOI
  86. 2015, Absorptive capacity and technology knowledge: enhancing relational capital, Knowledge and Process Management, 22, 305, 10.1002/kpm.1494 · DOI
  87. 2015, Encouraging knowledge contribution in IT support: social context and the differential effects of motivation type, Journal of Knowledge Management, 19, 315, 10.1108/JKM-08-2014-0356 · DOI
  88. 2017, Business analytics-enabled decision-making effectiveness through knowledge absorptive capacity in health care, Journal of Knowledge Management, 21, 517, 10.1108/JKM-08-2015-0301 · DOI
  89. 2016, Assessing tacit knowledge and sharing intention: a knowledge internalization perspective, Knowledge and Process Management, 23, 194, 10.1002/kpm.1505 · DOI
  90. 1974, Spline functions in data analysis, Technometrics, 16, 1, 10.1080/00401706.1974.10489142 · DOI · Paper page
  91. 2017, How does individuals’ exchange orientation moderate the relationship between transformational leadership and knowledge sharing?, Journal of Knowledge Management, 21, 1622, 10.1108/JKM-03-2017-0120 · DOI

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Metadata

Authors
Cepeda-Carrion, G., Cegarra-Navarro, J.-G., & Cillo, V.
Venue
Journal of Knowledge Management
Publisher
Emerald
Published
2019-01-14
Volume
23
Issue
1
Pages
67-89
ISSN
1367-3270 (ISSN-L)
OpenAlex
W2904158023
Cited by
667
References
9
FWCI
34.18
Type
journal article
Language
en
Open access
closed
Licence
www.emerald.com/insight/site-policies (tdm)

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