Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. By means of a simulation study, we show that these approaches do not reliably detect the lack of discriminant validity in common research situations. We therefore propose an alternative approach, based on the multitrait-multimethod matrix, to assess discriminant validity: the heterotrait-monotrait ratio of correlations. We demonstrate its superior performance by means of a Monte Carlo simulation study, in which we compare the new approach to the Fornell-Larcker criterion and the assessment of (partial) cross-loadings. Finally, we provide guidelines on how to handle discriminant validity issues in variance-based structural equation modeling.

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A new criterion for assessing discriminant validity in variance-based structural equation modeling

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

Most methodological fields undertake regular critical reflections to ensure rigorous research and publication practices, and, consequently, acceptance in their domain. Interestingly, relatively little attention has been paid to assessing the use of partial least squares structural equation modeling (PLS-SEM) in marketing research—despite its increasing popularity in recent years. To fill this gap, we conducted an extensive search in the 30 top ranked marketing journals that allowed us to identify 204 PLS-SEM applications published in a 30-year period (1981 to 2010). A critical analysis of these articles addresses, amongst others, the following key methodological issues: reasons for using PLS-SEM, data and model characteristics, outer and inner model evaluations, and reporting. We also give an overview of the interdependencies between researchers’ choices, identify potential problem areas, and discuss their implications. On the basis of our findings, we provide comprehensive guidelines to aid researchers in avoiding common pitfalls in PLS-SEM use. This study is important for researchers and practitioners, as PLS-SEM requires several critical choices that, if not made correctly, can lead to improper findings, interpretations, and conclusions.

An assessment of the use of partial least squares structural equation modeling in marketing 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-SEM's methodological toolbox to accommodate more complex model structures or handle data inadequacies such as heterogeneity Research limitations/implications – While rese

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

The objective of this paper is to provide a basic framework for researchers interested in reporting the results of their PLS analyses. Since the dominant paradigm in reporting Structural Equation Modeling results is covariance based, this paper begins by providing a discussion of key differences and rationale that researchers can use to support their use of PLS. This is followed by two examples from the discipline of Information Systems. The first consists of constructs with reflective indicators (mode A). This is followed up with a model that includes a construct with formative indicators (mode B).

How to Write Up and Report PLS Analyses

The cumulative capability or the ‘sand cone’ model (Ferdows and De Meyer, 1997 has been central in the debate on relations among dimensions of manufacturing performance. The central thesis of this model is that manufacturing performance is cumulative and sequential, with quality performance forming the foundation. An implicit assumption underlying the model is that the indirect effects of quality leading to delivery, then to flexibility and finally cost are stronger than direct effects among these same performance dimensions. Despite its frequent use, the sand cone model has not been empirically tested for direct and indirect effects or for the sequence of effects. Most tests have used correlations or regression relationships that only establish positive relationships among dimensions, not the specific sand cone sequence. We conduct two new tests of the actual sequence of the sand cone theory using data from 189 manufacturing plants. We do not find universal support for the sand cone theory, since some plants in our data appear to be following the sand cone sequence, while others are not. Our empirical tests support other limited evidence in the literature that a contingency theory is needed rather than an outright rejection or acceptance of the sand cone model.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1763440_code1616803.pdf?abstractid=1763440&mirid=2

The Cumulative Capability ‘Sand Cone’ Model Revisited: A New Perspective for Manufacturing Strategy

Impact of Women in the Invention Team on Product Development Outcomes

The surgical box supply chain management can be problematic through the surgical scheduling without an effective management control of the forecast, the stock, and the pulled demand. This research study analyzes just in time application with the use of the Kanban in the surgical box supply chain management. The researchers realized this study between December 2016 and July 2018. The main objective of the study is to apply the just in time as a management tool for the surgical boxes. The research has two periods: the observational and the tool management adoptions analysis periods. The results section presents three subsections: “the inventory,” “the integration among software, systems, and people,” and the “participative management.” The discussion brings two stages named: “the first stage-structuring the just in time delivery” and “the second stage-the just in time delivery.” The authors conclude that the supply chain can be dynamic and customized. The mass customization can be inserted and the industry can bring contributions with new opportunities like the Kanban to implement the just in time application.

Rachna Shah

Papers

The Cumulative Capability ‘Sand Cone’ Model Revisited: A New Perspective for Manufacturing Strategy

Impact of Women in the Invention Team on Product Development Outcomes

The just in Time Application in the Surgical Box Supply Chain Management