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Partial least squares structural equation modeling (PLS-SEM) has become popular in the information systems (IS) field for modeling structural relationships between latent variables as measured by manifest variables. However, while researchers using PLS-SEM routinely stress the causal-predictive nature of their analyses, the model evaluation assessment relies exclusively on criteria designed to assess the path model's explanatory power. To take full advantage of the purpose of causal prediction in PLS-SEM, it is imperative for researchers to comprehend the efficacy of various quality criteria, such as traditional PLS-SEM criteria, model fit, PLSpredict, cross-validated predictive ability test (CVPAT) and model selection criteria.

A systematic review was conducted to understand empirical studies employing the use of the causal prediction criteria available for PLS-SEM in the database of Industrial Management and Data Systems (IMDS) and Management Information Systems Quarterly (MISQ). Furthermore, this study discusses the details of each of the procedures for the causal prediction criteria available for PLS-SEM, as well as how these criteria should be interpreted. While the focus of the paper is on demystifying the role of causal prediction modeling in PLS-SEM, the overarching aim is to compare the performance of different quality criteria and to select the appropriate causal-predictive model from a cohort of competing models in the IS field.

The study found that the traditional PLS-SEM criteria (goodness of fit (GoF) by Tenenhaus, R2 and Q2) and model fit have difficulty determining the appropriate causal-predictive model. In contrast, PLSpredict, CVPAT and model selection criteria (i.e. Bayesian information criterion (BIC), BIC weight, Geweke–Meese criterion (GM), GM weight, HQ and HQC) were found to outperform the traditional criteria in determining the appropriate causal-predictive model, because these criteria provided both in-sample and out-of-sample predictions in PLS-SEM.

This research substantiates the use of the PLSpredict, CVPAT and the model selection criteria (i.e. BIC, BIC weight, GM, GM weight, HQ and HQC). It provides IS researchers and practitioners with the knowledge they need to properly assess, report on and interpret PLS-SEM results when the goal is only causal prediction, thereby contributing to safeguarding the goal of using PLS-SEM in IS studies.

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.

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.

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.

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 applications of FIMIX-PLS restricted their focus to a very limited set of criteria, but future studies should broaden the scope by considering information criteria, theory and logic.

Since the introduction of FIMIX-PLS, a range of alternative latent class techniques have emerged to address some of the limitations of the approach relating, for example, to the technique’s inability to handle heterogeneity in the measurement models and its distributional assumptions. The second part of this article (Part II) discusses alternative latent class techniques in greater detail and calls for the joint use of FIMIX-PLS and PLS prediction-oriented segmentation.

This paper 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 in Part I, Part II follows up by offering a step-by-step tutorial on how to use FIMIX-PLS in SmartPLS 3.

This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).

Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.

LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.

This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.

The purpose of this study is to review the use of partial least squares-structural equation modeling (PLS-SEM) in the field of hospitality and tourism and thereby to assess whether the PLS-SEM-based papers followed the recommended application guidelines and to investigate whether a comparison of journal types (hospitality vs tourism) and journal qualities (top-tier vs other leading) reveal significant differences in PLS-SEM use.

A total of 206 PLS-SEM based papers published between 2000 and April 2017 in the 19 SSCI-indexed hospitality and tourism journals were critically analyzed using a wide range of guidelines for the following aspects of PLS-SEM: the rationale of using the method, the data characteristics, the model characteristics, the model assessment and reporting the technical issues.

The results reveal that some aspects of PLS-SEM are correctly applied by researchers, but there are still some misapplications, especially regarding data characteristics, formative measurement model evaluation and structural model assessment. Furthermore, few significant differences were found on the use of PLS-SEM between the two fields (hospitality and tourism) and between the journal tiers (top-tier and other leading).

To enhance the quality of research in hospitality and tourism, the present study provides recommendations for improving the future use of PLS-SEM.

The present study fills a sizeable gap in hospitality and tourism literature and extends the previous assessments on the use of PLS-SEM by providing a wider perspective on the issue (i.e. includes both hospitality and tourism journals rather than the previous reviews that focus on either tourism or hospitality), using a larger sample size of 206 empirical studies, investigating the issue over a longer time period (from 2000 to April, 2017, including the in-press articles), extending the scope of criteria (guidelines) used in the review and comparing the PLS-SEM use between the two allied fields (hospitality and tourism) and between the journal tiers (top-tier and other leading).

This paper aims to examine project management segments based on customer satisfaction drivers and loyalty rather than traditional demographic or behavioural variables.

Data were gathered over 18 consecutive months, and 3,129 surveys were completed using a questionnaire. The statistical methods included partial least squares (PLS) structural equation modelling, finite mixture segmentation, prediction-oriented segmentation (PLS-POS) and multi-group analysis (PLS-MGA).

The findings indicate the existence of three segments among system delivery project customers based on the differences in the strengths of the path coefficients in the customer-centric structural model. In Segment 1, satisfaction based on the proposal was crucial for loyalty, with the value-for-money construct negatively impacting the repurchase intent construct. Segment 2 had a solid value-for-money orientation. In Segment 3, the critical path indicated that satisfaction drove repurchase intention, with satisfaction based mainly on the installation.

The research contributes to the segmentation theory by introducing a new way to segment the systems delivery projects customers based on the perceived strength of the relationships in a customer-centric structural model, which aligns with traditional segmentation theory in a way that most segmentation analyses do not. A new segmentation approach to the domain of project management theory is presented. Based on the results, treating the system delivery project customer base as a single homogenous group can lead to managerially misleading conclusions.

The objective of this study is to investigate how country risk, different political actions from the government and bureaucratic behavior influence the activities in industry supply chains (SCs) in emerging markets. The main objective of this study is to investigate the influence of these external stakeholders’ elements to the demand-side and supply-side drivers and barriers for improving competitiveness of Ready-Made Garment (RMG) industry in the way of analyzing supply chain. Considering the phenomenon of recent change in the RMG business environment and the competitiveness issues this study uses the principles of stakeholder and resource dependence theory and aims to find out some factors which influence to make an efficient supply chain for improving competitiveness. The RMG industry of Bangladesh is the case application of this study. Following a positivist paradigm, this study adopts a two phase sequential mixed-method research design consisting of qualitative and quantitative approaches. A tentative research model is developed first based on extensive literature review. Qualitative field study is then carried out to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. A survey is carried out with sample of top and middle level executives of different garment companies of Dhaka city in Bangladesh and the collected quantitative data are analyzed by partial least square-based structural equation modeling. The findings support eight hypotheses. From the analysis the external stakeholders’ elements like bureaucratic behavior and country risk have significant influence to the barriers. From the internal stakeholders’ point of view the manufacturers’ and buyers’ drivers have significant influence on the competitiveness. Therefore, stakeholders need to take proper action to reduce the barriers and increase the drivers, as the drivers have positive influence to improve competitiveness.

This study has both theoretical and practical contributions. This study represents an important contribution to the theory by integrating two theoretical perceptions to identify factors of the RMG industry’s SC that affect the competitiveness of the RMG industry. This research study contributes to the understanding of both external and internal stakeholders of national and international perspectives in the RMG (textile and clothing) business. It combines the insights of stakeholder and resource dependence theories along with the concept of the SC in improving effectiveness. In a practical sense, this study certainly contributes to the Bangladeshi RMG industry. In accordance with the desire of the RMG manufacturers, the research has shown that some influential constructs of the RMG industry’s SC affect the competitiveness of the RMG industry. The outcome of the study is useful for various stakeholders of the Bangladeshi RMG industry sector ranging from the government to various private organizations. The applications of this study are extendable through further adaptation in other industries and various geographic contexts.

In order to determine the status quo of PLS path modeling in international marketing research, we conducted an exhaustive literature review. An evaluation of double-blind reviewed journals through important academic publishing databases (e.g., ABI/Inform, Elsevier ScienceDirect, Emerald Insight, Google Scholar, PsycINFO, Swetswise) revealed that more than 30 academic articles in the domain of international marketing (in a broad sense) used PLS path modeling as means of statistical analysis. We assessed what the main motivation for the use of PLS was in respect of each article. Moreover, we checked for applications of PLS in combination with one or more additional methods, and whether the main reason for conducting any additional method(s) was mentioned.

In management accounting research, the capabilities of Partial Least Squares Structural Equation Modelling (PLS-SEM) have only partially been utilized. These yet unexploited capabilities of PLS-SEM are a useful tool in the often explorative state of research in management accounting. After reviewing eleven top-ranked management accounting journals through the end of 2013, 37 articles in which PLS-SEM is used are identified. These articles are analysed based on multiple relevant criteria to determine the progress in this research area, including the reasons for using PLS-SEM, the characteristics of the data and the models, and model evaluation and reporting. A special focus is placed on the degree of importance of these analysed criteria for the future development of management accounting research. To ensure continued theoretical development in management accounting, this article also offers recommendations to avoid common pitfalls and provides guidance for the advanced use of PLS-SEM in management accounting research.