Joseph F. Hair

Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research

Purpose – The authors aim to present partial least squares (PLS) as an evolving approach to structural equation modeling (SEM), highlight its advantages and limitations and provide an overview of recent research on the method across various fields. Design/methodology/approach – In this review article, the authors merge literatures from the marketing, management, and management information systems fields to present the state-of-the art of PLS-SEM research. Furthermore, the authors meta-analyze recent review studies to shed light on popular reasons for PLS-SEM usage. Findings – PLS-SEM has experienced increasing dissemination in a variety of fields in recent years with nonnormal data, small sample sizes and the use of formative indicators being the most prominent reasons for its application. Recent methodological research has extended PLS-SEMs methodological toolbox to accommodate more complex model structures or handle data inadequacies such as heterogeneity. Research limitations/implications – While rese...

Common Beliefs and Reality About PLS Comments on Rönkkö and Evermann (2013)

This article addresses Rönkkö and Evermann’s criticisms of the partial least squares (PLS) approach to structural equation modeling. We contend that the alleged shortcomings of PLS are not due to problems with the technique, but instead to three problems with Rönkkö and Evermann’s study: (a) the adherence to the common factor model, (b) a very limited simulation designs, and (c) overstretched generalizations of their findings. Whereas Rönkkö and Evermann claim to be dispelling myths about PLS, they have in reality created new myths that we, in turn, debunk. By examining their claims, our article contributes to reestablishing a constructive discussion of the PLS method and its properties. We show that PLS does offer advantages for exploratory research and that it is a viable estimator for composite factor models. This can pose an interesting alternative if the common factor model does not hold. Therefore, we can conclude that PLS should continue to be used as an important statistical tool for management and organizational research, as well as other social science disciplines.

Common Beliefs and Reality About PLS

This article addresses Rönkkö and Evermann’s criticisms of the partial least squares (PLS) approach to structural equation modeling. We contend that the alleged shortcomings of PLS are not due to problems with the technique, but instead to three problems with Rönkkö and Evermann’s study: (a) the adherence to the common factor model, (b) a very limited simulation designs, and (c) overstretched generalizations of their findings. Whereas Rönkkö and Evermann claim to be dispelling myths about PLS, they have in reality created new myths that we, in turn, debunk. By examining their claims, our article contributes to reestablishing a constructive discussion of the PLS method and its properties. We show that PLS does offer advantages for exploratory research and that it is a viable estimator for composite factor models. This can pose an interesting alternative if the common factor model does not hold. Therefore, we can conclude that PLS should continue to be used as an important statistical tool for management and organizational research, as well as other social science disciplines.

More than friendship is required: an empirical test of cooperative firm strategies

Purpose – The purpose of this paper is to examine a proposed six‐construct theoretical model of factors influencing successful cooperative relationships and strategy development.Design/methodology/approach – A theoretical model of strategy development and cooperative relationships was tested. Qualitative research among key experts identified 15 successful regional tourism networks. Two successful cooperative networks were selected based on annual revenues. A sample of 254 small and medium‐sized members were surveyed from the two networks in Northern Minnesota, USA.Findings – Strong support was obtained for the proposed model. Hypothesized relationships were tested and the findings were consistent with previous research. Long‐term orientation has a positive effect on friendship, loyalty, trust and commitment. Friendship is related to loyalty and commitment, and loyalty is related to trust. Ultimately, trust and commitment engender successful cooperation. The model can be used as a guide to strategy develop...

Publishing Research in Marketing Journals Using Structural Equation Modeling

This paper takes an objective look at how papers using structural equation models are received in the review process of academic marketing research journals. The focus is examining whether or not papers with structural equation modeling (SEM) applications enjoy an advantage in the review process and what the nature of such an advantage may be. A sample of submission records from a top marketing research journal is used to examine this issue. Results suggest that papers with SEM applications enjoy a modest advantage in the review process but that this difference is partially due to the fact that papers with SEM applications are rated more highly on multiple paper characteristics. For example, authors using SEM tend to have their papers rated more highly than others on the theoretical and conceptual development attribute. Thus, learning and applying SEM may have advantages not directly related to the application of the statistical approach.

Knowledge Creation in Marketing: The Role of Predictive Analytics

Purpose – The purpose of this paper is to provide an overview of predictive analytics, summarize how it is impacting knowledge creation in marketing, and suggest future developments in marketing and predictive analytics for both organizations and researchers.Design/methodology/approach – Survival in a knowledge‐based economy is derived from the ability to convert information to knowledge. To do so, researchers and managers increasingly are relying on the field of predictive analytics. Data mining identifies and confirms relationships between explanatory and criterion variables. Predictive analytics uses confirmed relationships between variables to predict future outcomes. The predictions are most often values suggesting the likelihood a particular behavior or event will take place in the future.Findings – Data mining and predictive analytics are increasingly popular because of the substantial contributions they can make in converting information to knowledge. Marketing is among the most frequent applicati...

Individual Psychological Ownership: Concepts, Evidence, and Implications for Research in Marketing

Psychological ownership has emerged as an important predictor of workplace motivations, attitudes, and behaviors. While components of psychological ownership theory have been recently adapted to marketing contexts as well, much remains to be done. With a more comprehensive application and use of psychological ownership theory in marketing, additional understanding and explanation could be provided for many of the key phenomena, such as customer satisfaction, loyalty, word-of-mouth, and willingness to pay. In this article, we focus on individual psychological ownership–associated concepts and evidence with implications for research in marketing. Our work offers multiple avenues for future research focused on, but not limited to, marketing contexts.

Identifying and treating unobserved heterogeneity with FIMIX-PLS: part I – method

Purpose – The purpose of this paper is to provide an overview of unobserved heterogeneity in the context of partial least squares structural equation modeling (PLS-SEM), its prevalence and challenges for social science researchers. Part II – in the next issue (European Business Review, Vol. 28 No. 2) – presents a case study, which illustrates how to identify and treat unobserved heterogeneity in PLS-SEM using the finite mixture PLS (FIMIX-PLS) module in the SmartPLS 3 software. Design/methodology/approach – The paper merges literatures from various disciplines, such as management information systems, marketing and statistics, to present a state-of-the-art review of FIMIX-PLS. Based on this review, the paper offers guidelines on how to apply the technique to specific research problems. Findings – FIMIX-PLS offers a means to identify and treat unobserved heterogeneity in PLS-SEM and is particularly useful for determining the number of segments to extract from the data. In the latter respect, prior applicati...

Cooperative strategies for improving the tourism industry in remote geographic regions: an addition to trust and commitment theory with one key mediating construct

The success of cooperative relationships is influenced by interorganizational commitment, which is a long‐run goal of networks. Our research examined cooperative relationships in the tourism industry to better understand what makes them successful. The study is an extension of previous empirical research on commitment. The overall research questions were: “What factors lead to interorganizational commitment in remote tourism destinations?” and “What are the relationships between the factors?” A literature search was conducted to identify factors related to organizational commitment. Search findings suggested a model proposing that interpersonal commitment mediates the effect of trust and reciprocity on interorganizational commitment. Data for the model was collected from a sample of tourism firms in successful cooperative networks. The theoretical model was purified based on convergent, nomological and discriminant validity as well as construct reliability. Our findings demonstrated that the relationship between trust and interorganizational commitment is in fact mediated by interpersonal commitment. We confirmed that reciprocity is directly related to interorganizational commitment, and is not mediated by interpersonal commitment. Thus, tourism firms should develop cooperative strategies in their networks by focusing on enhancing interpersonal commitment through trust, thereby ultimately helping to strengthen interorganizational commitment.

Identifying and treating unobserved heterogeneity with FIMIX-PLS: Part II – A case study

Purpose Part I of this article (European Business Review, Volume 28, Issue 1) offered an overview of unobserved heterogeneity in the context of partial least squares structural equation modeling (PLS-SEM), its prevalence and challenges for social sciences researchers. This paper aims to provide an example that explains how to identify and treat unobserved heterogeneity in PLS-SEM by using the finite mixture PLS (FIMIX-PLS) module in the SmartPLS 3 software (Part II). Design/methodology/approach This case study illustrates the application of FIMIX-PLS using a popular corporate reputation model. Findings The case study demonstrates the capability of FIMIX-PLS to identify whether unobserved heterogeneity significantly affects structural model relationships. Furthermore, it shows that FIMIX-PLS is particularly useful for determining the number of segments to extract from the data. Research limitations/implications Since the introduction of FIMIX-PLS, a range of alternative latent class techniques has appeared. These techniques address some of the limitations of the approach relating to, for example, its failure to handle heterogeneity in measurement models, or its distributional assumptions. This research discusses alternative latent class techniques and calls for the joint use of FIMIX-PLS and PLS prediction-oriented segmentation. Originality/value This article is the first to offer researchers, who have not been exposed to the method, an introduction to FIMIX-PLS. Based on a state-of-the-art review of the technique, the paper offers a step-by-step tutorial on how to use FIMIX-PLS by using the SmartPLS 3 software.