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Indirect or mediated effects constitute a type of relationship between constructs that often occurs in partial least squares (PLS) path modeling. Over the past few years, the methods for testing mediation have become more sophisticated. However, many researchers continue to use outdated methods to test mediating effects in PLS, which can lead to erroneous results. One reason for the use of outdated methods or even the lack of their use altogether is that no systematic tutorials on PLS exist that draw on the newest statistical findings. The paper aims to discuss these issues.

This study illustrates the state-of-the-art use of mediation analysis in the context of PLS-structural equation modeling (SEM).

This study facilitates the adoption of modern procedures in PLS-SEM by challenging the conventional approach to mediation analysis and providing more accurate alternatives. In addition, the authors propose a decision tree and classification of mediation effects.

The recommended approach offers a wide range of testing options (e.g. multiple mediators) that go beyond simple mediation analysis alternatives, helping researchers discuss their studies in a more accurate way.

The purpose of this paper is to analyze the occurrence of terms to identify the relevant topics and then to investigate the area (based on topics) of hospitality services that is highly associated with relationship quality. This research represents an opportunity to fill the gap in the current literature, and clarify the understanding of guests’ affective states by evaluating all aspects of their relationship with a hotel.

This research focuses on natural opinions upon which machine-learning algorithms can be executed: text summarization, sentiment analysis and latent Dirichlet allocation (LDA). Our data set contains 47,172 reviews of 33 hotels located in Las Vegas, and registered with Yelp. A component-based structural equation modeling (partial least squares (PLS)) is applied, with a dual – exploratory and predictive – purpose.

To maintain a truly loyal relationship and to achieve competitive success, hospitality managers must take into account both tangible and intangible features when allocating their marketing efforts to satisfaction-, trust- and commitment-based cues. On the other hand, the application of the PLS predict algorithm demonstrates the predictive performance (out-of-sample prediction) of our model that supports its ability to predict new and accurate values for individual cases when further samples are added.

LDA and PLS produce relevant informative summaries of corpora, and confirm and address more specifically the results of the previous literature concerning relationship quality. Our results are more reliable and accurate (providing insights not indicated in guests’ ratings into how hotels can improve their services) than prior statistical results based on limited sample data and on numerical satisfaction ratings alone.

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.

Within the framework of Total Quality Management (TQM) and the EFQM Excellence Model (EEM), the main objective of this paper is to develop a causal-predictive analysis of the relationships between soft and strategic-hard EFQM factors and the organisational results (customers, people, society and key results).

From a causal-predictive perspective, four EEM models, designed for each organisational result, are compared applying partial least squares structural equation modelling (PLS-SEM) and using a sample with 225 Spanish organisations.

The results confirm that soft and strategic-hard EFQM factors constitute a socio-technical system in which there are multiple direct and indirect relationships, between these factors and the results. Finally, the predictive nature of the proposed models is confirmed, highlighting the predictive performance of the people results model.

The results can lead to an improvement in organisational performance, as the developed models enable managers to anticipate the effects of their management decisions on those results concerning customers, people, society and key business results.

First, a novel way of grouping TQM enabler factors has been proposed within the EEM framework. Second, four research models have been generated, which allow carrying out an in-depth study of the direct and indirect relationships, between soft and strategic-hard EFQM factors and result variables. Finally, this contribution has applied the most updated techniques in order to assess the prediction performance of the four research models posited.

This article examines the mechanisms through which big data analytics capabilities (BDAC) contribute to creating sustainable value and analyzes the mediating roles that supply chain management capabilities (SCMC), as well as circular economy practices (CEP), play through their impact on sustainable performance.

Following a literature review, a serial mediation model is presented. Hypotheses regarding direct and mediating relationships are tested to determine their potential for sustainability impact and circularity. Partial least squares structural equation modeling (PLS-SEM) has been applied for causal and predictive purposes.

The results indicate that big data analytics capabilities do not have a direct positive impact on sustainable performance but influence indirectly through SCMC and CEP.

Although some authors have addressed the associations between IT business value, supply chain (SC), and sustainability, this paper provides empirical evidence related to these relationships. Additionally, this study performs novel predictive analyses.

To analyse the web acceptance and usage between goal‐directed users and experiential users, incorporating intrinsic motives to improve the particular and explanatory TAM (technology acceptance model) value – traditionally related to extrinsic motives.

A survey instrument was used to gather data to test the relationships shown in the research model. Data were collected from a sample of online questionnaires filled out by subscribers located in three discussion‐mailing lists – administered by RedIris – about different topics (e.g. experimental sciences, social sciences and humanities). A structural equation modeling (SEM), specifically partial least squares (PLS), is proposed to assess the relationships between the constructs together with the predictive power of the research model.

The empirical development suggests that there is scope for further extension of TAM to adapt to the web‐based usage and its profitable consequences. The article may help to further the empirical research and to clarify and examine a web acceptance and usage model. In general, experiential and goal‐directed behaviours moderate the key relationships in the model. Experiential and goal‐directed users do not weigh extrinsic and intrinsic motives in the same way when on the web. Goal‐directed users are more driven by instrumental factors and focused on their decision‐making process while experiential users are more motivated by process..

First, constructs of enjoyment and concentration are used to define flow. However, because of the flow definition's conceptual‐vagueness, operationalising the flow construct has been questioned in the previous empirical works. Second, the cross‐sectional study is also an important limitation. Since the users' perception and intention can change over time, it is important to measure these quantities at several points of time. Third, the sample sizes are relatively small. Fourth, the model needs to be tested with more objective measures to compare possible divergences. Finally, the model clearly does not include all the relevant variables.

The results could be used to explain and to improve the experiential and goal‐directed users' experience of being and to return to the web.

The value of this study is to reveal the moderating influences of browsing‐modes on relationship between flow and TAM‐beliefs on the web, and, also, how the flow impacts the attitude and intention to use web between experiential and goal‐directed users.

This paper aims to explore in depth how internal and external knowledge-based drivers actually affect the firms’ green innovation performance. Subsequently, this study analyzes the relationships between absorptive capacity (internal knowledge-based driver), relationship learning (external knowledge-based driver) and green innovation performance.

This study relies on a sample of 112 firms belonging to the Spanish automotive components manufacturing sector (ACMS) and uses partial least squares path modeling to test the hypotheses proposed.

The empirical results show that both absorptive capacity and relationship learning exert a significant positive effect on the dependent variable and that relationship learning moderates the link between absorptive capacity and green innovation performance.

This paper presents some limitations with respect to the particular sector (i.e. the ACMS) and geographical context (Spain). For this reason, researchers must be thoughtful while generalizing these results to distinct scenarios.

Managers should devote more time and resources to reinforce their absorptive capacity as an important strategic tool to generate new knowledge and hence foster green innovation performance in manufacturing industries.

The paper shows the importance of encouraging decision-makers to cultivate and rely on relationship learning mechanisms with their main stakeholders and to acquire the necessary information and knowledge that might be valuable in the maturity of green innovations.

This study proposes that relationship learning plays a moderating role in the relationship between absorptive capacity and green innovation performance.

In the highly competitive hotel industry, it is essential to encourage patterns of continuous repurchase and to retain customers. This may be achieved through the quality of the relationship established with them. The aim of the paper is to test a model of the antecedents and consequences of the quality of the employee‐customer relationship.

Partial least squares (PLS) was used to assess the reliability/validity of the measures and make a causal‐predictive analysis.

The results of the study are useful both for academics and practitioners: they add support for the proposed model and increase its potential for generalisation; results suggest a wide range of measures that hotel managers could undertake to develop and maintain employee‐customer relationship quality.

Future studies should test the model at different times, during other important events in the city and, of course, in other geographical areas. Also new variables should be included in the model. Another research path might be to integrate into a single model all the agents with whom a particular hotel establishment forms relationships.

From the management perspective, results of this study provide useful variables for hotel managers introducing a relationship marketing strategy in their hotels, regardless of their category.

The paper uses PLS methodology to test a proposed model, particularly appropriate in this case since it allows a causal‐predictive analysis in a situation in which complex problems are analysed and previous theoretical knowledge is limited.

The purpose of this paper is to develop a theoretical model for evaluating the international competitiveness of small and medium multinational enterprises (SMNEs) located in Latin American developing countries.

Industrial economics and international business theories were linked for establishing the firm international competitiveness model. Literature on each variable determining of firm competitiveness is reviewed and the linkages between them are discussed.

The use of a global strategy is one of the most important factors to compete abroad. Domestic environment and national industry might help its use. Human resources background of staff working within the SMNEs affects the global strategy as well.

SMNEs should be more taken into account as they are the main generators of the economic development of countries and, consequently, foster the progress of underdeveloped countries through creating jobs.

This study is one of the pioneers in developed a model for evaluating the international competitiveness of firms based on developing countries of Latin America. Researchers and professionals will count on a theoretical tool for evaluating the Latin American international competitiveness in global contexts. Additionally we include the full survey for testing the competitiveness model.

To analyse the implicit relationships among enabler agents of the European excellence model to serve as a framework for the management and improvement of the quality in higher education institutions.

The hypotheses set out are based on the structure and meaning of the EFQM model and a review of the TQM literature. The empirical study was developed in 111 Spanish public university centres, and used the partial least squares (PLS) technique to test these hypotheses.

The results achieved support the relationships hypothesized and indicate the role of enabler agents as a basis for establishing a management model that leads universities towards excellence.

The main limitation is related to the notion of causality. Our study has considered a soft modelling approach directed more towards prediction than causality.

The role of senior management stands out among the key activities. The top management leads the excellence development of key processes in the university through appropriate leadership, strategy formulation, establishment of partnerships, resource allocation, and human resources management.

The current work is one of the first studies dealing with the testing of implicit relationships set out by the EFQM model among enablers. The comprehension of these relationships provides a guide to implement, develop, assess and improve higher education institutions.