Executing and interpreting applications of PLS-SEM: Updates for family business researchers

Arzubiaga, 2018, Entrepreneurial orientation and innovation in family SMEs: Unveiling the (actual) impact of the board of directors, Journal of Business Venturing, 33, 455, 10.1016/j.jbusvent.2018.03.002

Astrachan, 2014, A comparative study of CB-SEM and PLS-SEM for theory development in family firm research, Journal of Family Business Strategy, 5, 116, 10.1016/j.jfbs.2013.12.002

Astrachan, 2002, The F-PEC scale of family influence: A proposal for solving the family business definition Problem1, Family Business Review, 15, 45, 10.1111/j.1741-6248.2002.00045.x

Bascle, 2008, Controlling for endogeneity with instrumental variables in strategic management research, Strategic Organization, 6, 285, 10.1177/1476127008094339

Basco, 2019, Transgenerational entrepreneurship around the world: Implications for family business research and practice, Journal of Family Business Strategy, 10, 10.1016/j.jfbs.2018.03.004

Basco, 2019, They are not all the same! Investigating the effect of executive versus non-executive family board members on firm performance, Journal of Small Business Management, 57, 637, 10.1111/jsbm.12535

Berrone, 2012, Socioemotional wealth in family firms: Theoretical dimensions, assessment approaches, and agenda for future research, Family Business Review, 25, 258, 10.1177/0894486511435355

Binz, 2013, Exploring the effect of distinct family firm reputation on consumers’ preferences, Journal of Family Business Strategy, 4, 3, 10.1016/j.jfbs.2012.12.004

Binz Astrachan, 2014, A comparative study of CB-SEM and PLS-SEM for theory development in family firm research, Journal of Family Business Strategy, 5, 116, 10.1016/j.jfbs.2013.12.002

Binz Astrachan, 2019, Marketing and branding in family business: Assessing the landscape and charting a path forward, Journal of Family Business Strategy, 10, 3, 10.1016/j.jfbs.2019.02.003

Cepeda Carrión, 2016, Prediction-oriented modeling in business research by means of PLS path modeling, Journal of Business Research, 69, 4545, 10.1016/j.jbusres.2016.03.048

Chin, 2020, Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research, Industrial Management & Data Systems, 10.1108/IMDS-10-2019-0529

Chua, 2012, Sources of heterogeneity in family firms: An introduction, Entrepreneurship Theory and Practice, 36, 1103, 10.1111/j.1540-6520.2012.00540.x

Danks, 2018, Predictions from partial least squares models, 35

Dawson, 2011, Private equity investment decisions in family firms: The role of human resources and agency costs, Journal of Business Venturing, 26, 189, 10.1016/j.jbusvent.2009.05.004

Dibrell, 2019, A brief history and a look to the future of family business heterogeneity: An introduction, 1

Ebbes, 2016, Dealing with endogeneity: A nontechnical Guide for marketing researchers

Evermann, 2016, Assessing the predictive performance of structural equation model estimators, Journal of Business Research, 69, 4565, 10.1016/j.jbusres.2016.03.050

Farrell, 2010, Insufficient discriminant validity: A comment on Bove, Pervan, Beatty, and Shiu (2009), Journal of Business Research, 63, 324, 10.1016/j.jbusres.2009.05.003

Fornell, 1981, Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18, 39, 10.1177/002224378101800104

Franke, 2019, Heuristics versus statistics in discriminant validity testing: A comparison of four procedures, Internet Research, 29, 430, 10.1108/IntR-12-2017-0515

García-Ramos, 2011, Board characteristics and firm performance in public founder- and nonfounder-led family businesses, Journal of Family Business Strategy, 2, 220, 10.1016/j.jfbs.2011.09.001

González-Cruz, 2016, When Does Family Involvement Produce Superior Performance in SME Family Business?, Journal of Business Research, 69, 1452, 10.1016/j.jbusres.2015.10.124

Goodhue, 2012, Does PLS Have Advantages for Small Sample Size or Non-Normal Data?, MIS Quarterly, 36, 981, 10.2307/41703490

Hair, 2020, Assessing measurement model quality in PLS-SEM using confirmatory composite analysis, Journal of Business Research, 109, 101, 10.1016/j.jbusres.2019.11.069

Hair, 2020, Data, measurement, and causal inferences in machine learning: Opportunities and challenges for marketing, Journal of Marketing Theory & Practice

Hair, 2020, Next generation prediction metrics for composite-based PLS-SEM, Industrial Management & Data Systems

Hair, 2019, Factors versus composites: Guidelines for choosing the right structural equation modeling method, Project Management Journal, 50, 619, 10.1177/8756972819882132

Hair, 2017

Hair, 2016, Identifying and treating unobserved heterogeneity with FIMIX-PLS: Part I - method, European Business Review, 28, 63, 10.1108/EBR-09-2015-0094

Hair, 2019, Partial least squares structural equation modeling-based discrete choice modeling: An illustration in modeling retailer choice, Business Research, 12, 115, 10.1007/s40685-018-0072-4

Hair, 2019, When to use and how to report the results of PLS-SEM, European Business Review, 31, 2, 10.1108/EBR-11-2018-0203

Hair, 2012, The use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications, Long Range Planning, 45, 320, 10.1016/j.lrp.2012.09.008

Hair, 2019, Rethinking some of the rethinking of partial least squares, European Journal of Marketing, 53, 566, 10.1108/EJM-10-2018-0665

Hauswald, 2016, Attracting New Talent to Family Firms: Who is Attracted and under what Conditions?, Entrepreneurship Theory and Practice, 40, 963, 10.1111/etap.12153

Hayes, 2018

Henseler, 2014, Common beliefs and reality about partial least squares: Comments on Rönkkö & Evermann (2013), Organizational Research Methods, 17, 182, 10.1177/1094428114526928

Henseler, 2015, A new criterion for assessing discriminant validity in variance-based structural equation modeling, Journal of the Academy of Marketing Science, 43, 115, 10.1007/s11747-014-0403-8

Hult, 2018, Addressing endogeneity in international marketing applications of partial least squares structural equation modeling, Journal of International Marketing, 26, 1, 10.1509/jim.17.0151

Hwang, 2020, A concept analysis of methodological research on composite-based structural equation modeling: Bridging PLSPM and GSCA, Behaviormetrika, 47, 219, 10.1007/s41237-019-00085-5

JCGM/WG1, 2008, Joint committee for guides in Metrology/Working group on the expression of uncertainty in measurement (JCGM/WG1)

Jöreskog, 1982, The ML and PLS techniques for modeling with latent variables: Historical and comparative aspects, 263

Kahlert, 2017, Revealing the family: Effects of being perceived as a family firm in the recruiting market in Germany, Journal of Family Business Management, 7, 21, 10.1108/JFBM-10-2015-0037

Khan, 2019, Methodological research on partial least squares structural equation modeling (PLS-SEM): An analysis based on social network approaches, Internet Research, 29, 407, 10.1108/IntR-12-2017-0509

Liengaard, 2020, Prediction: Coveted, yet forsaken? Introducing a cross-validated predictive ability test in partial least squares path modeling, Decision Sciences

Louviere, 2000

Lu, 2011, Two new methods for estimating structural equation models: An illustration and a comparison with two established methods, International Journal of Research in Marketing, 28, 258, 10.1016/j.ijresmar.2011.03.006

Lude, 2020, Experimental studies in family business research, Journal of Family Business Strategy

Mathews, 2015, A sequential choice model of family business succession, Small Business Economics, 45, 15, 10.1007/s11187-015-9628-2

Matthews, 2016, Identifying and treating unobserved heterogeneity with FIMIX-PLS: Part II – A case study, European Business Review, 28, 208, 10.1108/EBR-09-2015-0095

Matzler, 2015, The impact of family ownership, management, and governance on innovation, The Journal of Product Innovation Management, 32, 319, 10.1111/jpim.12202

Nitzl, 2017, The case of partial least squares (PLS) path modeling in managerial accounting, Journal of Management Control, 28, 137, 10.1007/s00187-017-0249-6

Nitzl, 2016, Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models, Industrial Management & Data Systems, 119, 1849, 10.1108/IMDS-07-2015-0302

Park, 2012, Handling endogenous regressors by joint estimation using copulas, Marketing Science, 31, 567, 10.1287/mksc.1120.0718

Pieper, 2010, Non Solus: Toward a psychology of family business, Journal of Family Business Strategy, 1, 26, 10.1016/j.jfbs.2010.02.003

Pieper, 2020, What time may tell: An exploratory study of the relationship between religiosity, temporal orientation, and goals in family business, Journal of Business Ethics, 163, 759, 10.1007/s10551-019-04386-3

Radomir, 2020, Discriminant validity of the customer-based corporate reputation scale: Some causes for concern, Journal of Product and Brand Management, 29, 457, 10.1108/JPBM-11-2018-2115

Rhemtulla, 2020, Worse than measurement error: Consequences of inappropriate latent variable measurement models, Psychological Methods, 25, 30, 10.1037/met0000220

Richter, 2016, European management research using partial least squares structural equation modeling (PLS-SEM): Editorial, European Management Journal, 34, 589, 10.1016/j.emj.2016.08.001

Richter, 2020, When predictors of outcomes are necessary: Guidelines for the combined use of PLS-SEM and NCA, Industrial Management & Data Systems, 10.1108/IMDS-11-2019-0638

Rigdon, 2012, Rethinking partial least squares path modeling: In praise of simple methods, Long Range Planning, 45, 341, 10.1016/j.lrp.2012.09.010

Rigdon, 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

Rigdon, 2019, Factor indeterminacy as metrological uncertainty: Implications for advancing psychological measurement, Multivariate Behavioral Research, 54, 429, 10.1080/00273171.2018.1535420

Rigdon, 2020, Quantify uncertainty in behavioral research, Nature Human Behaviour, 4, 329, 10.1038/s41562-019-0806-0

Rigdon, 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

Ringle, 2020, Partial least squares structural equation modeling in HRM research, International Journal of Human Resource Management, 31, 1617, 10.1080/09585192.2017.1416655

Rönkkö, 2013, A critical examination of common beliefs about partial least squares path modeling, Organizational Research Methods, 16, 425, 10.1177/1094428112474693

Santiago, 2019, Family presence, family firm reputation and perceived financial performance: Empirical evidence from the Philippines, Journal of Family Business Strategy, 10, 49, 10.1016/j.jfbs.2019.02.002

Sarstedt, 2019, How to specify, estimate, and validate higher-order constructs in PLS-SEM, Australasian Marketing Journal, 27, 197, 10.1016/j.ausmj.2019.05.003

Sarstedt, 2016, Estimation issues with PLS and CBSEM: Where the Bias Lies!, Journal of Business Research, 69, 3998, 10.1016/j.jbusres.2016.06.007

Sarstedt, 2020, Structural model robustness checks in PLS-SEM, Tourism Economics, 26, 531, 10.1177/1354816618823921

Sarstedt, 2017, Partial least squares structural equation modeling, 1

Sarstedt, 2017, Treating unobserved heterogeneity in PLS-SEM: A multi-method approach, 197

Sarstedt, 2020, Beyond a tandem analysis of SEM and PROCESS: Use of PLS-SEM for mediation analyses!, International Journal of Market Research, 62, 288, 10.1177/1470785320915686

Sarstedt, 2014, On the emancipation of PLS-SEM: A commentary on Rigdon (2012), Long Range Planning, 47, 154, 10.1016/j.lrp.2014.02.007

Sarstedt, 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

Sharma, 2019, PLS-based model selection: The role of alternative explanations in information systems research, Journal of the Association for Information Systems, 20

Sharma, 2020, Prediction-oriented model selection in partial least squares path modeling, Decision Sciences

Shmueli, 2010, To explain or to predict?, Statistical Science, 25, 289, 10.1214/10-STS330

Shmueli, 2016, The elephant in the room: Evaluating the predictive performance of PLS models, Journal of Business Research, 69, 4552, 10.1016/j.jbusres.2016.03.049

Shmueli, 2019, Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict, European Journal of Marketing, 53, 2322, 10.1108/EJM-02-2019-0189

Smith, 2014, An investigation of the effect of family influence on commitment–Trust in retailer–Vendor strategic partnerships, Journal of Family Business Strategy, 5, 252, 10.1016/j.jfbs.2013.11.005

van Gils, 2019, Unraveling the impact of family antecedents on family firm image: A serial multiple-mediation model, Journal of Family Business Strategy, 10, 17, 10.1016/j.jfbs.2019.02.001

Voorhees, 2016, Discriminant validity testing in marketing: An analysis, causes for concern, and proposed remedies, Journal of the Academy of Marketing Science, 44, 119, 10.1007/s11747-015-0455-4

Wilson, 2014, Method trends and method needs: Examining methods needed for accelerating the field, Journal of Family Business Strategy, 5, 4, 10.1016/j.jfbs.2014.01.011

Wold, 1982, Soft modeling: The basic design and some extensions, 1