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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.

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.

This study aims to verify the influence of perceived value dimensions on customer satisfaction and loyalty in the banking sector, comparing these relationships between traditional banks and fintechs. Also, it was verified whether satisfaction mediates the relationships between the dimensions of perceived value and customer loyalty to traditional banks and fintechs, comparing them.

Data were collected through two online questionnaires with 792 total respondents, 411 from traditional banks and 381 from fintechs. For data analysis, the authors used the Partial Least Squares - Structural Equation Modeling (PLS-SEM) and PLS-SEM multigroup analysis (PLS-MGA).

The influence of customer satisfaction on loyalty tends to be greater in traditional banks than in fintechs; the effect of reliability on satisfaction tends to be greater in fintechs than in traditional banks and the effect of price on satisfaction tends to be greater in traditional banks than in fintechs. Indirectly, empathy, price and competence influence loyalty through satisfaction, and in all these relationships, the strength of the effect is significantly greater in traditional banks when compared to fintechs.

The findings, on the one hand, indicate that banks' investments in customer satisfaction, empathy, price and competence tend to generate positive results by expanding customer loyalty in addition to the return on similar investments made by fintechs. On the other hand, when fintechs invest in reliability, they tend to capture better results in increasing customer satisfaction compared to traditional banks.

The comparison of the effect of the dimensions of perceived value on satisfaction and loyalty between traditional banks and fintechs stands out, which is a novelty in the literature. This comparison can support strategies that aim to strengthen relationships with customers and increase the recurrence of business, both for traditional banks and fintechs.

Expanded awareness and application of recent PLS-SEM reporting practices were again called for by Hair (2022) in his PLS 2022 Keynote Address. This paper aims to analyze and extend the application of PLS-SEM in Industrial Management and Data Systems (IMDS) to focus on trends emerging in the more recent 2016–2022 period.

A review of PLS-SEM applications in information systems studies published in IMDS and MISQ for the period 2012–2022 identifies and comments on a total of 135 articles. Selected emerging advanced analytical PLS-SEM applications are also highlighted to expand awareness of their value in more rigorously evaluating model results.

There is a continually increasing maturity of the information systems field in applying PLS-SEM, particularly for IMDS authors. Model complexity and improved prediction assessment as well as other advanced analytical options are increasingly identified as reasons for applying PLS-SEM.

Findings demonstrate the continued use and acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is the preferred SEM method in many research settings, but particularly when the research objective is prediction to the population, mediation and mediated moderation, formative constructs are specified, constructs must be modeled as higher-order and for competing model comparisons.

This update on PLS-SEM applications and recent methodological developments will help authors to better understand and apply the method, as well as publish their work. Researchers are encouraged to engage in more complete analyses and include enhanced reporting procedures.

Applications of PLS-SEM for prediction, theory testing and confirmation are increasing. Information systems scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for both exploratory and confirmatory research.

Online education can facilitate inclusive societal development. In emerging countries with low investment per capita in school and universities, it helps students overcome infrastructure constraints to continue their learning and reach their full potential, and it helps educational institutes to save costs and improve quality of learning. This study aims to develop and empirically evaluate a conceptual model for predicting digital loyalty (DL) among participants in online accounting courses, as a key lever to execute an inclusive societal development agenda and ensure sustainability of education in an emerging country.

The study used quantitative primary data collected from survey questionnaires administered to 167 respondents in India and employed partial least squares structural equation modelling (PLS SEM) to analyse the data.

We observed that perceived learning (PL) significantly mediated the relationship between learning performance (LP) and digital loyalty to an online accounting programme.

Students’ attitudes and preferences have changed remarkably in recent years. Online education encourages participants to complete their courses, learn new and relevant skills, improve their quality of life and recommend online education to others. This facilitates an inclusive, open society with opportunities for all. The results of this study have certain implications. First, as a novel extension of Abrantes et al.’s (2007) work, the DL construct added a new key dimension to the model. Second, the use of PLS Predict introduced methodological rigour to measures such as R² and blindfolding processes, improving the understanding of the PLS Predict algorithm’s application to prediction studies.

The study established PL as a mediating variable in the associations between LP and DL and between pedagogical affect (PA) and DL. These findings have practical implications for course design and execution programmes in educational institutes, especially those aiming to democratise education and ensure inclusivity. Online education service providers should focus on equipping students with updated, cross-functional and integrated skills.

Online education can foster an inclusive and open society by overcoming the twin limitations of geographical distance and infrastructure constraints resulting from scarce learning resources, especially in emerging markets, such as India. The study makes an original contribution by collecting participant data for online accounting courses in India to establish clearly the antecedents of DL. This study empirically demonstrates the role of LP as the most significant antecedent of PL and DL.

This study aims to correct errors in, and comment on the claims made in the comment papers of Rigdon (2022) and Henseler and Schuberth (2022), and to tidy up any substantive oversights made in Cadogan and Lee (2022).

The study discusses and clarifies the gap between Rigdon’s notion of scientific realism and the metaphysical, semantic and epistemological commitments that are broadly agreed to be key principles of scientific realism. The study also examines the ontological status of the variables that Henseler and Schuberth claim are emergent using emergence logic grounded in the notion that variables are only truly emergent if they demonstrate a failure of generative atomism.

In scientific realism, hypothetical causal contact between the unobserved and the observed is a key foundational stance, and as such, Rigdon’s concept proxy framework (CPF) is inherently anti-realist in nature. Furthermore, Henseler and Schuberth’s suggestion that composite-creating statistical packages [such as partial least squares (PLS)] can model emergent variables should be treated with skepticism by realists.

Claims made by Rigdon regarding the realism of CPF are unfounded, and claims by Henseler and Schuberth regarding the universal suitability of partial least squares (PLS) as a tool for use by researchers of all ontological stripes (see their Table 5) do not appear to be well-grounded.

Those aspiring to do science according to the precepts of scientific realism need to be careful in assessing claims in the literature. For instance, despite Rigdon’s assertion that CPF is a realist framework, we show that it is not. Consequently, some of Rigdon’s core criticisms of the common factor logic make no sense for the realist. Likewise, if the variables resulting from composite creating statistical packages (like PLS) are not really emergent (contrary to Henseler and Schuberth) and so are not real, their utility as tools for scientific realist inquiry are called into question.

This study assesses PLS using the Eleatic Principle and examines H&S’s version of emergent variables from an ontological perspective.

This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of promoting the adoption of PPP housing scheme in Nigeria.

The research design adopts the census sampling approach by using well-structured questionnaires distributed to stakeholders involved in PPP-procured mass housing projects, i.e. consultants, in-house professionals, contractors and the organized private sector, registered with PPP departments in the Federal Capital Territory Development Authority, Abuja, Nigeria. Sixty-three risk factors, nine risk allocation criteria and nine project delivery indices were submitted for the respondents to rank on a Likert scale of 7. Two hypotheses were formulated to test whether the risk allocation criteria impacted PPP mass housing delivery or otherwise. The study adopts partial least square-structural equation modeling to model the effect of risk on risk allocation criteria on project delivery indices and risk severity.

The finding shows that project risk allocation criteria have less effect on project delivery indices than on risk severity. The study concludes that risk allocation principles do not directly affect the delivery of PPP-procured mass housing projects. This is evident by the path coefficient of 0.724 values, which is not statistically significant at a 5% alpha protection value. The study concludes that allocating critical risk factors influences the performance of PPP-procured mass housing projects, as the path coefficient of 0.360 is also not significantly far from 0 and at a 5% alpha protection value.

The study is one of the recent studies conducted in PPP-procured mass housing projects in Nigeria owing to the novelty of procurement option in the sector. It highlights the risk factors that can jeopardize the PPP-procured mass housing project objectives. The study is of immense value to PPP actors in the sector by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP mass housing projects.

It is widely evident that trust and commitment are important pillars for strengthening the relationship between financial service firms and their customers. However, it has not been explored how the service quality, perceived cost and role of agents are important for financial service firms. To overcome this gap, this study aims to investigate the role of service quality, perceived cost and the role of agents as the commitment–trust factors in the financial insurance service (Takaful) in Malaysia, enhancing customer satisfaction.

The study follows a quantitative design in which primary data was collected using a survey instrument. The measurement instrument was adapted from the previous research, and data were collected from 264 customers of the Takaful financial service organizations in Malaysia. The data were analyzed using variance-based structural equational modeling in Smart-PLS software.

This research has revealed several useful insights that demonstrate a significant impact on service quality, perceived cost and the agents’ role in forging close relationships with their customers. Corporate image has a moderating role in relationships and has significantly impacted takaful insurance companies. The results imply that regardless of the corporate image of the financial service organizations, customers are concerned about the prices and the quality of the agents’ services.

In this study, only the predictors such as service quality, perceived costs and agents’ roles as trust–commitment factors were examined to determine customer satisfaction. Other investigations are highly recommended, such as value co-creation in takaful, takaful customer experience and takaful trust. This study offers insights to takaful insurance companies on how to keep up a positive corporate image, which will boost their trust–commitment factors and ultimately increase customer satisfaction.

By presenting commitment–trust factors and company image in an identifiable framework, the current study has expanded the discussion on takaful financial insurance services. The methodology is developed and rigorously tested to gauge customer satisfaction in takaful financial service organizations’ context.

Open banking, with its promise to revolutionise electronic transactions through open application programming interfaces (APIs), aims to bridge the gap between banks and non-banks, enhancing lending, payments, investments and funds distribution. However, does this bold innovation truly resonate with consumers? This study delves into consumer intentions to adopt open banking in Indonesia by leveraging the technology readiness model, scrutinising its antecedents and moderating factors, and identifying the key attributes that users anticipate.

Through quantitative and qualitative approaches, this study answers the following questions: (1) Are financial service users ready to use open banking/open API applications? (2) What are the key attributes that consumer expects of open banking/open API? First, the authors developed a structural model based on the technology readiness model, distributed the questionnaire in eight major cities in Indonesia, analysed it using PLS-SEM and utilised a machine learning approach to unpack the main attributes expected from open banking.

This study’s findings indicate that customers are generally prepared to embrace open banking innovations. Nonetheless, to enhance public acceptance, certain factors should be emphasised, including organisational support, user-friendly technology, a comprehensive range of features, consumer financial literacy and banks' readiness to adopt open banking. In contrast to prior research, this study reveals that loyalty to traditional banking positively moderates the connection between customer value and the intention to utilise open banking. Additionally, the authors did not observe a significant moderating effect of financial literacy on the relationship between perceived customer value and the intention to use open banking.

To the best of the authors’ knowledge, this study is one of the few that comprehensively analyses the consumers' readiness for open banking in developing contexts. This study is expected to produce a theoretical contribution as well as effective and optimal policies for the financial services sector.

The urgency to address climate change and its devastating consequences has never been more pressing. As societies become increasingly aware of the detrimental impact of traditional housing on the planet, there is a growing demand for eco-friendly housing solutions that prioritize energy efficiency, resource conservation and reduced carbon emissions. Therefore, this study aims to investigate the factors that influence customers’ priority toward eco-friendly house purchasing intention.

This study collected 386 data using a quantitative research strategy and purposive sampling method. This study uses a hybrid analysis technique using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approaches to identify the influencing factors.

The PLS-SEM analysis found that attitude toward the eco-friendly house, subjective norms, performance expectancy, environmental knowledge and environmental sensitivity have a positive influence on eco-friendly house purchasing intention. However, perceived behavioral control and willingness to pay were found to have insignificant effect on customers’ intention to purchase eco-friendly houses. The fsQCA results further revealed complex causal relationships between the influencing factors.

This research will not only contribute to academic knowledge but also provide practical guidance to real estate developers, policymakers and individuals looking to make environmentally responsible choices. By understanding the factors that influence consumers’ intentions to purchase eco-friendly houses, we can pave the way for a more sustainable and resilient future.

This study has used a hybrid analysis technique, combining PLS-SEM and fsQCA, to enhance the predictive accuracy of eco-friendly house purchase intentions among individuals residing in densely populated and highly polluted developing countries, such as Bangladesh.