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Partial least squares structural equation modeling (PLS-SEM) is an important statistical technique in the toolbox of methods that researchers in marketing and other social sciences disciplines frequently use in their empirical analyses. The purpose of this paper is to shed light on several misconceptions that have emerged as a result of the proposed “new guidelines” for PLS-SEM. The authors discuss various aspects related to current debates on when or when not to use PLS-SEM, and which model evaluation metrics to apply. In addition, this paper summarizes several important methodological extensions of PLS-SEM researchers can use to improve the quality of their analyses, results and findings.

The paper merges literature from various disciplines, including marketing, strategic management, information systems, accounting and statistics, to present a state-of-the-art review of PLS-SEM. Based on these findings, the paper offers a point of orientation on how to consider and apply these latest developments when executing or assessing PLS-SEM-based research.

This paper offers guidance regarding situations that favor the use of PLS-SEM and discusses the need to consider certain model evaluation metrics. It also summarizes how to deal with endogeneity in PLS-SEM, and critically comments on the recent proposal to adjust PLS-SEM estimates to mimic common factor models that are the foundation of covariance-based SEM. Finally, this paper opposes characterizing common concepts and practices of PLS-SEM as “out-of-date” without providing well-substantiated alternatives and solutions.

The paper paves the way for future discussions and suggests a way forward to reach consensus regarding situations that favor PLS-SEM use and its application.

This paper offers guidance on how to consider the latest methodological developments when executing or assessing PLS-SEM-based research.

This paper complements recently proposed “new guidelines” with the aim of offering a counter perspective on some strong claims made in the latest literature on PLS-SEM. It also clarifies some misconceptions regarding the application of PLS-SEM.

The purpose of this paper is to explore the knowledge infrastructure of methodological research on partial least squares structural equation modeling (PLS-SEM) from a network point of view. The analysis involves the structures of authors, institutions, countries and co-citation networks, and discloses trending developments in the field.

Based on bibliometric data downloaded from the Web of Science, the authors apply various social network analysis (SNA) and visualization tools to examine the structure of knowledge networks of the PLS-SEM domain. Specifically, the authors investigate the PLS-SEM knowledge network by analyzing 84 methodological studies published in 39 journals by 145 authors from 106 institutions.

The analysis reveals that specific authors dominate the network, whereas most authors work in isolated groups, loosely connected to the network’s focal authors. Besides presenting the results of a country level analysis, the research also identifies journals that play a key role in disseminating knowledge in the network. Finally, a burst detection analysis indicates that method comparisons and extensions, for example, to estimate common factor model data or to leverage PLS-SEM’s predictive capabilities, feature prominently in recent research.

Addressing the limitations of prior systematic literature reviews on the PLS-SEM method, this is the first study to apply SNA to reveal the interrelated structures and properties of PLS-SEM’s research domain.

The purpose of this paper is to provide a comprehensive, yet concise, overview of the considerations and metrics required for partial least squares structural equation modeling (PLS-SEM) analysis and result reporting. Preliminary considerations are summarized first, including reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power and the need for goodness-of-fit testing. Next, the metrics as well as the rules of thumb that should be applied to assess the PLS-SEM results are covered. Besides presenting established PLS-SEM evaluation criteria, the overview includes the following new guidelines: PLSpredict (i.e., a novel approach for assessing a model’s out-of-sample prediction), metrics for model comparisons, and several complementary methods for checking the results’ robustness.

This paper provides an overview of previously and recently proposed metrics as well as rules of thumb for evaluating the research results based on the application of PLS-SEM.

Most of the previously applied metrics for evaluating PLS-SEM results are still relevant. Nevertheless, scholars need to be knowledgeable about recently proposed metrics (e.g. model comparison criteria) and methods (e.g. endogeneity assessment, latent class analysis and PLSpredict), and when and how to apply them to extend their analyses.

Methodological developments associated with PLS-SEM are rapidly emerging. The metrics reported in this paper are useful for current applications, but must always be up to date with the latest developments in the PLS-SEM method.

In light of more recent research and methodological developments in the PLS-SEM domain, guidelines for the method’s use need to be continuously extended and updated. This paper is the most current and comprehensive summary of the PLS-SEM method and the metrics applied to assess its solutions.

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.

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.

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.

While research on the PLS-SEM method has gained momentum during the last decade, there are ample research opportunities on subjects such as mediation or multigroup analysis, which warrant further attention.

This article provides an introduction to PLS-SEM for researchers that have not yet been exposed to the method. The article is the first to meta-analyze reasons for PLS-SEM usage across the marketing, management, and management information systems fields. The cross-disciplinary review of recent research on the PLS-SEM method also makes this article useful for researchers interested in advanced concepts.

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).

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.

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.

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.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

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.

Information and communications technology (ICT) offers enormous opportunities for individuals, businesses and society. The application of ICT is equally important to economic and non-economic activities. Researchers have increasingly focused on the adoption and use of ICT by small and medium enterprises (SMEs) as the economic development of a country is largely dependent on them. Following the success of ICT utilisation in SMEs in developed countries, many developing countries are looking to utilise the potential of the technology to develop SMEs. Past studies have shown that the contribution of ICT to the performance of SMEs is not clear and certain. Thus, it is crucial to determine the effectiveness of ICT in generating firm performance since this has implications for SMEs’ expenditure on the technology. This research examines the diffusion of ICT among SMEs with respect to the typical stages from innovation adoption to post-adoption, by analysing the actual usage of ICT and value creation. The mediating effects of integration and utilisation on SME performance are also studied. Grounded in the innovation diffusion literature, institutional theory and resource-based theory, this study has developed a comprehensive integrated research model focused on the research objectives. Following a positivist research paradigm, this study employs a mixed-method research approach. A preliminary conceptual framework is developed through an extensive literature review and is refined by results from an in-depth field study. During the field study, a total of 11 SME owners or decision-makers were interviewed. The recorded interviews were transcribed and analysed using NVivo 10 to refine the model to develop the research hypotheses. The final research model is composed of 30 first-order and five higher-order constructs which involve both reflective and formative measures. Partial least squares-based structural equation modelling (PLS-SEM) is employed to test the theoretical model with a cross-sectional data set of 282 SMEs in Bangladesh. Survey data were collected using a structured questionnaire issued to SMEs selected by applying a stratified random sampling technique. The structural equation modelling utilises a two-step procedure of data analysis. Prior to estimating the structural model, the measurement model is examined for construct validity of the study variables (i.e. convergent and discriminant validity).

The estimates show cognitive evaluation as an important antecedent for expectation which is shaped primarily by the entrepreneurs’ beliefs (perception) and also influenced by the owners’ innovativeness and culture. Culture further influences expectation. The study finds that facilitating condition, environmental pressure and country readiness are important antecedents of expectation and ICT use. The results also reveal that integration and the degree of ICT utilisation significantly affect SMEs’ performance. Surprisingly, the findings do not reveal any significant impact of ICT usage on performance which apparently suggests the possibility of the ICT productivity paradox. However, the analysis finally proves the non-existence of the paradox by demonstrating the mediating role of ICT integration and degree of utilisation explain the influence of information technology (IT) usage on firm performance which is consistent with the resource-based theory. The results suggest that the use of ICT can enhance SMEs’ performance if the technology is integrated and properly utilised. SME owners or managers, interested stakeholders and policy makers may follow the study’s outcomes and focus on ICT integration and degree of utilisation with a view to attaining superior organisational performance.

This study urges concerned business enterprises and government to look at the environmental and cultural factors with a view to achieving ICT usage success in terms of enhanced firm performance. In particular, improving organisational practices and procedures by eliminating the traditional power distance inside organisations and implementing necessary rules and regulations are important actions for managing environmental and cultural uncertainties. The application of a Bengali user interface may help to ensure the productivity of ICT use by SMEs in Bangladesh. Establishing a favourable national technology infrastructure and legal environment may contribute positively to improving the overall situation. This study also suggests some changes and modifications in the country’s existing policies and strategies. The government and policy makers should undertake mass promotional programs to disseminate information about the various uses of computers and their contribution in developing better organisational performance. Organising specialised training programs for SME capacity building may succeed in attaining the motivation for SMEs to use ICT. Ensuring easy access to the technology by providing loans, grants and subsidies is important. Various stakeholders, partners and related organisations should come forward to support government policies and priorities in order to ensure the productive use of ICT among SMEs which finally will help to foster Bangladesh’s economic development.

Partial least squares (PLS) has been introduced as a “causal-predictive” approach to structural equation modeling (SEM), designed to overcome the apparent dichotomy between explanation and prediction. However, while researchers using PLS-SEM routinely stress the predictive nature of their analyses, model evaluation assessment relies exclusively on metrics designed to assess the path model’s explanatory power. Recent research has proposed PLSpredict, a holdout sample-based procedure that generates case-level predictions on an item or a construct level. This paper offers guidelines for applying PLSpredict and explains the key choices researchers need to make using the procedure.

The authors discuss the need for prediction-oriented model evaluations in PLS-SEM and conceptually explain and further advance the PLSpredict method. In addition, they illustrate the PLSpredict procedure’s use with a tourism marketing model and provide recommendations on how the results should be interpreted. While the focus of the paper is on the PLSpredict procedure, the overarching aim is to encourage the routine prediction-oriented assessment in PLS-SEM analyses.

The paper advances PLSpredict and offers guidance on how to use this prediction-oriented model evaluation approach. Researchers should routinely consider the assessment of the predictive power of their PLS path models. PLSpredict is a useful and straightforward approach to evaluate the out-of-sample predictive capabilities of PLS path models that researchers can apply in their studies.

Future research should seek to extend PLSpredict’s capabilities, for example, by developing more benchmarks for comparing PLS-SEM results and empirically contrasting the earliest antecedent and the direct antecedent approaches to predictive power assessment.

This paper offers clear guidelines for using PLSpredict, which researchers and practitioners should routinely apply as part of their PLS-SEM analyses.

This research substantiates the use of PLSpredict. It provides marketing researchers and practitioners with the knowledge they need to properly assess, report and interpret PLS-SEM results. Thereby, this research contributes to safeguarding the rigor of marketing studies using PLS-SEM.

E-wallet is one of the financial technology (fintech) products. In Indonesia, e-wallet is still in the growing stage. Many e-wallet providers are attracted to join the market every year, and the competition becomes tighter, focusing on customer acquisition. Promotion is launched, burning much cash in making the promotion. However, cash-burning does not guarantee that customers will use one e-wallet. Customer satisfaction is an important key element of success and continuous use in information systems and e-commerce contexts. This research aims to investigate the satisfaction of e-wallet customer in Indonesia, focusing on and extending the trust role. This study adopted the model proposed by Geebren, Jabbar, and Luo (2021), which is an extension of information system success model. This research used Structural Equation Modeling with Partial Least Squares to analyze the data. It was found that factors that influence customer satisfaction are trust, system quality, information quality, service quality, and structural assurance. The authors found that trust positively affects customer satisfaction, and trust plays a vital role in customer satisfaction. Also, trust has a role as partial and full mediators. It is suggested that e-wallet providers should consider enhancing customer satisfaction.

Researchers often use partial least squares structural equation modeling (PLS-SEM) to estimate path models that include formatively specified constructs. Their validation requires running a redundancy analysis, which tests whether the formatively measured construct is highly correlated with an alternative measure of the same construct. Extending prior knowledge in the field, this paper aims to examine the conditions favoring the use of single vs multiple items to measure the criterion construct in redundancy analyses.

Merging the literatures from a variety of fields, such as management, marketing and psychometrics, we first provide a theoretical comparison of single-item and multi-item measurement and offer guidelines for designing and validating suitable single items. An empirical comparison in the context of hospitality management examines whether using a single item to measure the criterion variable yields sufficient degrees of convergent validity compared to using a multi-item measure.

The results of an empirical comparison in the context of hospitality management show that, when the sample size is small, a single item yields higher degrees of convergent validity than a reflective construct does. However, larger sample sizes favor the use of reflectively measured multi-item constructs, but the differences are marginal, thus supporting the use of a global single item in PLS-SEM-based redundancy analyses.

This study is the first to research the efficacy of single-item versus multi-item measures in PLS-SEM-based redundancy analyses. The results illustrate that a convergent validity assessment of formatively measured constructs can be implemented without triggering a pronounced increase in survey length.

The purpose of this study is to use empirical data to examine the hierarchical impact of the Internet of things capability on supply chain integration (SCI), supply chain capability (SCC) and firm performance (FP) in the UK retail industry.

A deductive approach was employed to carry out this research. Structural equation modelling (SEM) was performed using the partial least square method (SmartPLS 3.3.3) to test theoretical predictions which underlie the relationships among Internet of things capability (IoTC), SCI, SCC and FP. Data are collected using an online survey completed by senior executives of 66 large, medium and small firms within the UK retail industry.

The empirical results of this research reveal that IoTC has a significant positive effect on the UK retail industry FP through the mediating role of SCI and SCC.

The research results from this study provide useful management insights for firms within the retail industry into the development of effective strategies for integrating their supply chain alongside the adoption of IoTC into SCI, consequently leading to improvements in FP.

Although previous studies have explored the impact of IoT on FP through the sequential mediating role of SCI and SCC, few have explored the impact of the IoT capability (IoTC) on FP through sequential mediators, i.e. SCI and SCC. This study examines the relationship between IoTC, SCI, SCC and FP in the UK retail industry supply chain to address this knowledge gap. Moreover, this study examines the effects of IoTC on FP by applying partial least square (PLS)-SEM techniques. Testing the sequential mediating role of SCI and SCI is undertaken, and the relationships among IoT-enabled SCI and SCC is analysed to improve FP. The robustness check's result through PLSpredict analysis also confirms the power of the model proposed in this study.