Enhancing Global Sales Skills in Executive Education Programs

The purpose of this article is to examine the need for executive education training in culture, suggest a method for clarifying situations where cultural training is needed, and provide guidelines on the content of executive education training programs for companies pursuing global opportunities

Mktg

A new approach to learning the principles of marketing, MKTG is the Asia–Pacific edition of a proven, innovative solution to enhance the students' learning experience. Concise, yet complete, coverage supported by a suite of online learning aids equips students with the tools required to successfully undertake an introductory marketing course. Paving a new way to both teaching and learning, MKTG is designed to truly connect with today's busy tech-savy student. Students have access to online interactive quizzing, videos, podcasts, flashcards, marketing plans, games and more. An accessible, easy-to-read text along with tear out review cards complete a package which helps students to learn important concepts faster

Integrating the Expanded Task-technology Fit Theory and the Technology Acceptance Model: A Multi-wave Empirical Analysis

Task-technology fit theory proposes that the match between tasks and technologies, known as task-technology fit, has a positive relation with technology use and performance. Researchers have recently extended task-technology fit theory by conceptualizing task-technology misfit, which describes instances in which technology provides too few (too little) or too many (too much) features to perform a task. We link this newly expanded theory, which we label expanded task- technology fit (E-TTF) theory, with the technology acceptance model (TAM). We conducted a study and found that task- technology fit and too little significantly related to the variables in the TAM and that each ultimately had an indirect effect on use. In contrast, too much did not significantly relate to any variable in the TAM. These results support that E-TTF theory explains meaningful variance in the TAM, which suggests that integrating these theories is important for understanding technology use. Likewise, these results emphasize the importance of the multidimensional conceptualization that the E-TTF theory proposes. Too little (too few features) predicted outcomes beyond task- technology fit and meaningfully improved our model’s predictive abilities. In contrast, too much’s (too many features) relationships lacked significance, which emphasizes the need to distinguish types of task-technology misfit. Therefore, our study provides benefits for research on E-TTF theory, the TAM, and their integration

Multilevel modeling for longitudinal data: concepts and applications

Purpose – This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used. Design/methodology/approach – The authors estimate three-level models with repeated measures, offering conditions for their correct interpretation. Findings – From the concepts and techniques presented, the authors can propose models, in which it is possible to identify the fixed and random effects on the dependent variable, understand the variance decomposition of multilevel random effects, test alternative covariance structures to account for heteroskedasticity and calculate and interpret the intraclass correlations of each analysis level. Originality/value – Understanding how nested data structures and data with repeated measures work enables researchers and managers to define several types of constructs from which multilevel models can be used

On the Emancipation of PLS-SEM: A Commentary on Rigdon (2012)

Rigdon's (2012) thoughtful article argues that PLS-SEM should free itself from CB-SEM. It should renounce all mechanisms, frameworks, and jargon associated with factor models entirely. In this comment, we shed further light on two subject areas on which Rigdon (2012) touches in his discussion of CB-SEM and PLS-SEM. Rigdon (2012) highlights ways to make better use of PLS-SEM's predictive capabilities, for example, by reverting to set correlations. We discuss this issue in more detail, highlighting the need to examine the predictive capabilities of models when developing and testing theories, and broach the issue of confirmatory versus exploratory modeling. As a result of our discussion, we call for the continuous improvement of the PLS-SEM method to uncover its capabilities for theory testing while retaining its predictive characte

The impact of organizational compliance culture and green culture on environmental behavior: The moderating effect of environmental commitment

In this research, we aim to examine the moderating effect of environmental commitment on the relationships between organizational compliance culture and green culture on environmental behavior, under the theoretical stream of the Resource Based Theory (RBT) of the firm, and the Value-Belief-Norm theory (VBN). The research used a quantitative research approach, with a non-experimental transactional design. The sample consisted of 148 Mexican companies with a corporate value system that has implemented environmental sustainability practices, most of them incorporating the GRI guidelines, the SDGs and the Ten Principles of the UN Global Compact into their strategies, policies, procedures, and initiatives. This study contributes to the literature in the field of environmental sustainability, with a first theoretical PLS-SEM model that studies moderating and control variables, through organizational compliance on environmental behavior. Our proposed PLS model is a complex hierarchical component model that brings together and simultaneously maps a higher-order construct combined with three lower-order constructs, with moderation effects, multi-group analysis and predictive performance assessment. The major research findings are both the positive impacts between the proposed higher-order construct, organizational compliance culture, and green culture, on environmental behavior, and the moderating effect of environmental commitment on the relationship between green culture and environmental behavior. The insights obtained enhance the understanding of the factors that determine the environmental behavior through organizational compliance culture and green culture, with the moderating effect of environmental commitment, and help senior management in making strategic decisions to align their environmental objectives in compliance with the 2030 agenda in the area of environmental sustainability. This study highlights the need for companies to strengthen the role of environmental commitment to improve the environmental sustainability and it mentions practical implications both for managers of organizations that are responsible for meeting the objectives of sustainable development, specifically in the environmental field, and for policymakers and authorities that guide environmental policies.Departamento de Economía Financiera, Contabilidad y Dirección de Operacione

How to specify, estimate, and validate higher-order constructs in PLS-SEM

Higher-order constructs, which facilitate modeling a construct on a more abstract higher-level dimension and its more concrete lower-order subdimensions, have become an increasingly visible trend in applications of partial least squares structural equation modeling (PLS-SEM). Unfortunately, researchers frequently confuse the specification, estimation, and validation of higher-order constructs, for example, when it comes to assessing their reliability and validity. Addressing this concern, this paper explains how to evaluate the results of higher-order constructs in PLS-SEM using the repeated indicators and the two-stage approaches, which feature prominently in applied social sciences research. Focusing on the reflective-reflective and reflective-formative types of higher-order constructs, we use the well-known corporate reputation model example to illustrate their specification, estimation, and validation. Thereby, we provide the guidance that scholars, marketing researchers, and practitioners need when using higher-order constructs in their studies

Extraordinary Claims Require Extraordinary Evidence: A Comment on “Recent Developments in PLS”

Evermann and Rönkkö (2023) review recent developments in partial least squares (PLS) with the aim of providing guidance to researchers. Indeed, the explosion of methodological advances in PLS in the last decade necessitates such overview articles. In so far as the goal is to provide an objective assessment of the technique, such articles are most welcome. Unfortunately, the authors’ extraordinary and questionable claims paint a misleading picture of PLS. Our goal in this short commentary is to address selected claims made by Evermann and Rönkkö (2023) using simulations and the latest research. Our objective is to bring a positive perspective to this debate and highlight the recent developments in PLS that make it an increasingly valuable technique in IS and management research in general

The shortcomings of equal weights estimation and the composite equivalence index in PLS-SEM

Purpose The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM). Design/methodology/approach The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI. Findings The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM. Research limitations/implications In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison. Practical implications The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights. Originality/value To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators