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This study examined social media, tax morale, and tax compliance behaviour. Partial Least Square-Structural Equation Modelling (PLS-SEM) was utilized to investigate the quantitative data gathered from 592 salaried and self-employed taxpayers in East Malaysia, comprising two regions – Sabah and Sarawak. The results showed that social media had no significant effect on tax compliance. There was, however, a significant and negative relationship between social media and tax morale. A significant and positive effect of tax morale on tax compliance was also discovered. The bootstrapping technique indicated that tax morale mediates the association between social media and tax compliance. This research is among the earliest in a developing country to investigate the effect of social media in enhancing tax compliance, thus, contributing to the tax literature with a broader focus.

There has been a growing concern about employee silence (ES) within an organization. ES is associated with low creativity and innovativeness, unethical organizational practices, avoidable errors and safety-related issues. The purpose of this study is to evaluate the mediating role of psychological insecurity (PI) in the relationship between leaders’ bullying behaviour (LBB) on defensive (DES) and acquiescent employee silence (AES).

Data were collected among police personnel working in Plateau state Nigeria. In all, a total of 350 responses were found useable for further analysis, of the 398 copies of the questionnaire administered. A structural equation modelling technique was used via SMART-PLS version 3.3.3 to test the hypothesized relationship.

The findings of this study revealed that leaders’ bullying positively and significantly influences both AES and DES, and PI was found to mediate the relationship between LBB and AES and DES.

LBB among the police has been under-researched, even when there is clear evidence of its existence. PI explains the mechanism through which LBB influences officers' silence.

Researchers often stress the predictive goals of their partial least squares structural equation modeling (PLS-SEM) analyses. However, the method has long lacked a statistical test to compare different models in terms of their predictive accuracy and to establish whether a proposed model offers a significantly better out-of-sample predictive accuracy than a naïve benchmark. This paper aims to address this methodological research gap in predictive model assessment and selection in composite-based modeling.

Recent research has proposed the cross-validated predictive ability test (CVPAT) to compare theoretically established models. This paper proposes several extensions that broaden the scope of CVPAT and explains the key choices researchers must make when using them. A popular marketing model is used to illustrate the CVPAT extensions’ use and to make recommendations for the interpretation and benchmarking of the results.

This research asserts that prediction-oriented model assessments and comparisons are essential for theory development and validation. It recommends that researchers routinely consider the application of CVPAT and its extensions when analyzing their theoretical models.

The findings offer several avenues for future research to extend and strengthen prediction-oriented model assessment and comparison in PLS-SEM.

Guidelines are provided for applying CVPAT extensions and reporting the results to help researchers substantiate their models’ predictive capabilities.

This research contributes to strengthening the predictive model validation practice in PLS-SEM, which is essential to derive managerial implications that are typically predictive in nature.

The purpose of this study is to investigate how working from home (WFH) affects the relationship between internal corporate social responsibility (ICSR) and employee creativity in times of uncertainty when employees’ occupational stress increases and their identification with their company decreases.

Applying social identity theory, the authors derive and test the hypotheses presented in this study regarding ICSR’s direct effects on employee creativity, given the amount of time they spent on WFH and the role of threat in this relationship. The authors use partial least squares structural equation modeling to analyze the various effects. Via an online questionnaire and using the snowball technique, the authors collected data from 158 participants in different industries in Germany.

The empirical results of this study show that ICSR activities increase employee creativity, partly by reducing one harmful aspect of stress, namely, threat. In addition, the authors find that WFH moderates this effect, such that the higher the degree of WFH, the weaker the ICSR activities’ effects are.

This study focused on the respondents’ WFH situation during the global COVID-19 pandemic. As such, this research contributes to understanding the roles that modern work practices, human resource management (HRM) and ICSR actions play in respect of employee creativity. The authors expand the theoretical understanding, which is based on social identity theory, by showing that the greater the amount of time spent on WFH, the more it reduces ICSR’s positive effect on employee creativity. The findings of this study open avenues for future research and longitudinal studies that compare the ICSR effects during and after the pandemic, as well as for those that compare WFH and its effects on organizational creativity.

This study shows that managers should encourage appropriate ICSR measures in their organizations and should specifically consider the work setting (i.e. WFH or at the office) as a boundary factor for these measures’ effectiveness. However, ICSR actions, such as anti-discrimination measures, are less effective in respect of building the employee–employer relationship and supporting employees’ identification with and commitment to the company when they work from home. Given the economic benefit of decreased turnover rates and the societal benefit of a company output with higher creativity levels, this study has an impact from both an economic and a societal perspective.

This study sheds light on employee creativity and ICSR’s roles in current HRM practice, which is still underexplored. More importantly, to the best of the authors’ knowledge, this study provides the first empirical evidence of a hitherto overlooked mechanism explaining ICSR activities’ effects on, or their perceived threat to, employee creativity.

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.

Innovation is one of the most important foundations on which to create and sustain competitive advantages in companies, but at the individual level, employee innovative behavior has recently been jeopardized by the situation caused by the COVID-19 pandemic (e.g. changes in workplaces, employee interaction, motivation). This study analyzes wellness programs and actions through which organizations have tried to adapt to the new situation caused by COVID-19 and their effect on employee innovation behavior.

Structural equation modeling by means of the partial least squares technique was used to test the study's hypotheses after collecting survey data from Spanish companies, providing evidence that wellness programs and measures to deal with COVID-19 through perceived organizational support and affective commitment encourage employee innovation behavior.

The results suggest that efforts developed by firms focused on employee well-being to overcome difficulties caused by the pandemic strengthen innovative behaviors by means of intrinsic motivation based essentially on personal commitment. Theoretical and practical implications of the findings are discussed by the paper's authors.

This paper corroborates and extends previous research regarding wellness programs, perceived organization support and affective commitment. It provides a comprehensive model of relationships that predicts employee innovative behavior. It analyzes the influence of enterprise wellness programs based on protective COVID-19 measures.

This study aims to examine the determinants of ethical decision-making (EDM) of professional accountants in Sri Lanka, drawing on Rest’s (1986) four-component EDM model. The level of corporate collapses and fraud, coupled with the high level of corruption in Sri Lanka, has highlighted the importance and the timely nature of this research in the EDM processes of Sri Lankan accountants.

Data was collected from a sample of 315 accountants through a questionnaire survey that included four written ethical vignettes and was analysed using partial least square-structural equation modelling techniques.

The findings revealed a significant relationship between ethical awareness and ethical judgement, providing support for Rest’s model. However, the study does not support Rest’s model on the direct relationship between ethical judgement and ethical intention. Intrinsic religiosity and moral intensity significantly influenced the ethical awareness of accountants. Several determinants including accountants’ age, education, intrinsic religiosity, organisational ethical culture, familiarity with the professional ethical code and moral intensity influenced ethical judgement. However, the findings did not report any significant relationships between the study’s variables and ethical intention.

The study adds to the existing literature by providing a bigger picture of how various determinants work together in one EDM model and demonstrating that the EDM of accountants is multifaceted. The new finding on an insignificant relationship between ethical judgement and ethical intention implies that the Rest’s EDM process may be mediated and moderated by other constraints blocking accountants’ intention to act due to various pressures in a corrupt society, Sri Lanka, where accountants operate.

This study investigates to what extent the values perceived by tourists throughout cultural tours impact their overall satisfaction levels and behavioral intentions related to the destination. This study further examines the moderating role of tour guide competency in the relationship patterns concerned.

Empirical data were collected via a survey from 420 foreign tourists who visited Cappadocia and participated in guided cultural tours. Partial least squares-structural equation modeling was used for data analysis.

Study results reveal that the effects of quality, emotional, monetary and social value perceptions of tourists gained through cultural tour experiences on their overall satisfaction levels and the effects of overall satisfaction on recommendation and revisit intention are positive and significant. Furthermore, the moderating role of tour guide competency is significant and positive in the relationships between quality value and satisfaction and between satisfaction and revisit intention.

This study offers a critical analysis of discoveries concerning the pivotal role of tour guide competency within the cultural tour experience.

Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are two key component-based approaches to structural equation modeling that facilitate the analysis of theoretically established models in terms of both explanation and prediction. This study aims to offer a comparative evaluation of GSCA and PLSPM in a predictive modeling framework.

A simulation study compares the predictive performance of GSCA and PLSPM under various simulation conditions and different prediction types of correctly specified and misspecified models.

The results suggest that GSCA with reflective composite indicators (GSCA_R) is the most versatile approach. For observed prediction, which uses the component scores to generate prediction for the indicators, GSCA_R performs slightly better than PLSPM with mode A. For operative prediction, which considers all parameter estimates to generate predictions, both methods perform equally well. GSCA with formative composite indicators and PLSPM with mode B generally lag behind the other methods.

Future research may further assess the methods’ prediction precision, considering more experimental factors with a wider range of levels, including more extreme ones.

When prediction is the primary study aim, researchers should generally revert to GSCA_R, considering its performance for observed and operative prediction together.

This research is the first to compare the relative efficacy of GSCA and PLSPM in terms of predictive power.

This study proposes and validates an integrated theoretical model involving the theory of planned behavior (TPB), health belief model (HBM), personal norms and information privacy to understand determinants of acceptance and resistance to the use of mobile contact tracing app (MCTA) in a pandemic situation.

This study draws on online surveys of 194 research respondents and uses partial least squares structural equation modeling (PL-SEM) to test the proposed theoretical model.

The study establishes that a positive attitude towards MCTA is the most important predictor of individuals' willingness to use MCTA and resistance to use MCTA. Furthermore, barriers to taking action positively influence resistance to the use of MCTA. Personal norms negatively influence resistance to the use of MCTA. Information privacy showed a negative and positive influence on willingness to use MCTA and use the resistance of MCTA, respectively, but neither was statistically significant. The authors found no significant influence of perceived vulnerability, severity, subjective norms and perceived behavioral control on either acceptance or use resistance of MCTA.

The study has been one of the first in the literature to propose an integrated theoretical model in the investigation of the determinants of acceptance and resistance to the use of MCTA in a single study, thereby increasing the scientific understanding of the factors that can facilitate or inhibit individuals from engaging in the use of a protection technology during a pandemic situation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0533