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This study aims to ascertain the intentions of risk managers to use artificial intelligence in performing their tasks by examining the factors affecting their motivation.

The study employs an integrated theoretical framework that merges the third version of the technology acceptance model 3 (TAM3) and the unified theory of acceptance and use of technology (UTAUT) based on the application of the structural equation model with partial least squares structural equation modeling (PLS-SEM) estimation on data gathered through a Likert-based questionnaire disseminated among Italian risk managers. The survey reached 782 people working as risk professionals, but only 208 provided full responses. The final response rate was 26.59%.

The findings show that social influence, perception of external control and risk perception are the main predictors of risk professionals' intention to use artificial intelligence. Moreover, performance expectancy (PE) and effort expectancy (EE) of risk professionals in relation to technology implementation and use also appear to be reasonably reliable predictors.

Thus, the study offers a precious contribution to the debate on the impact of automation and disruptive technologies in the risk management domain. It complements extant studies by tapping into cultural issues surrounding risk management and focuses on the mostly overlooked dimension of individuals.

Yet, thanks to its quite novel theoretical approach; it also extends the field of studies on artificial intelligence acceptance by offering fresh insights into the perceptions of risk professionals and valuable practical and policymaking implications.

This techno-centric and too much busy day-to-day living style of citizens pressurizes the implementation of E-ticketing service to adapt with change. Thus, this study aims to examine the factors influencing railway passengers’ E-ticketing service acceptance and usage intention in Bangladesh and to extend the widely used Technology Acceptance Model through inserting two new constructs.

This paper employs structural equation modeling to test model’s paths developed through theoretical research framework. Moreover, a structured questionnaire was administered at different railway stations in northern and western parts of Bangladesh to collect data. Total of 302 responses were considered for statistical analysis to test hypotheses after considering anomalies and outliers in raw data.

The study results show that technology trust (TT) has the strongest impact on passengers’ E-ticketing usage intention rather than perceived ease of use and perceived usefulness (PU). Meanwhile, the easiness of using technology to reserve tickets does matter to female passengers rather than male passengers wherein PU and TT do not do that.

The findings of this study might be helpful for the railway authorities to improve the ticket reservation service quality online by developing the advanced booking application and minimizing the pressure on other transportation. Therefore, this empirical study will contribute to this domain for further study that ensures full satisfaction of passengers and uplift the railway passengers’ usage intention for E-ticketing which then helps the government to implement the digitization slogan with efficiency and effectiveness.

Islam describes business as a legitimate means of halal income. However, little is known about what attracts people towards Islamic entrepreneurship or halalpreneurship. By applying the theory of planned behaviour, this study aims to contribute to this underexplored area by investigating the factors that affect Islamic entrepreneurial intention (IEI).

This study examined a mediation model using two country samples. First, the hypotheses were tested on a sample recruited from a high-income economy (i.e. Saudi Arabia) using structural equation modelling in AMOS V26. The authors then conducted a replication study to investigate the robustness of the findings using a sample recruited from a lower-middleincome economy (i.e. Bangladesh) and a different analysis technique, the PROCESS mediation model in SPSS V25.

The findings suggest that IEI depends on four antecedents, namely, attitude towards Islamic entrepreneurship, general entrepreneurial self-efficacy, Islamic entrepreneurial self-efficacy and perceived halal income. These antecedents also mediate the relationship between moral judgement and IEI.

This study offers an empirical framework that captures several perspectives on the formation of IEI. The findings contribute to entrepreneurial intention and motivation research by suggesting factors that motivate individuals to engage in Islamic entrepreneurship.

The findings imply that the framework of IEI can withstand diverse socioeconomic contexts. A novel perspective of this study is that Muslims who are motivated by perceived halal income show greater interest in becoming Islamic entrepreneurs.

Perceived risk and benefits have been proposed as crucial elements in consumers’ technology adoption intention. Therefore, this study aims to use the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, with perceived risks and benefits, to explore how they affect consumers’ Buy-Now-Pay-Later (BNPL) behavioural intention.

An online survey was conducted among 537 users of BNPL. Partial least square structural equation modelling analysis was performed to examine the hypothesized relationships.

The study found that perceived benefits, performance expectancy, effort expectancy, habit and social influence increase consumers’ behavioural intention towards BNPL. In contrast, perceived risk reduces the consumer’s intention to use. Additionally, the study revealed that consumers’ intention towards BNPL services positively affects their usage.

The lack of information makes consumers hesitant to use BNPL. Therefore, marketers should optimize facilitating conditions, such as user-friendly interfaces, accessible resources and efficient customer support, which should be the business strategy of BNPL service providers to ensure a seamless user experience.

The research empirically investigates the effect of perceived benefits on consumer behavioural intention. This contribution is crucial because while there was speculation about benefits as a driving force to consumers’ adoption intention, there was a lack of sufficient empirical evidence to support it.

Wine consumer behavior has long been a topic of discussion among scholars and industry professionals aiming to understand the underlying predictors of key behavioral outcomes. To help explain wine consumer behavior, concepts such as involvement, expertise, loyalty, satisfaction and perceived risk are often examined. The overarching objective of this study is to determine the relationship between these predictors and their impact on wine purchase intention utilizing a meta-analytical structural equation modeling (MASEM) technique.

As MASEM provides substantive evidence regarding the relationships between theoretical constructs through the combination of multiple studies, the researchers’ aim is to make definitive statements about the predictors of purchase intention.

Findings revealed several relationships that support previous research but also identified relationships that contradict previous literature. This study contributes valuable insights into consumer behavior that wine brands can utilize to improve their marketing efforts.

Wine marketers with a greater understanding of the stronger predictors of purchase intention should be able to create marketing plans that drive wine sales.

Despite the abundance of research that has utilized these theoretical constructs to demonstrate their propensity for determining behavioral outcomes such as purchase intention, no previous attempts have synthesized this body of literature through the use of meta-analysis.

The study proposes to empirically test a model that illustrates how identical elements (IEs), transfer design and trainer performance as training predictors affect trainees' motivation to improve work through learning (MTIWL) and training transfer (TT) in the Indian context.

An online survey was conducted to validate the study model. The quantitative data collected from 360 executives and managers were analyzed using the covariance-based structural equation modeling (CB-SEM) technique.

The study finds that trainees' MTIWL has a full mediation impact between transfer design, trainer performance and TT. However, a partial mediating impact of MTIWL was found between IEs and TT.

This is the first study that empirically explores the mediating mechanism of MTIWL between IEs, transfer design, trainer performance and TT. This study extends the current understanding of trainees' MTIWL that links the cumulative influence of training predictors to TT.

This study aims to develop and test multivariable psychosocial prediction models of perceived post-traumatic stress disorder (PTSD) and complex post-traumatic stress disorder (CPTSD) symptoms development among trauma-exposed Ukrainian adults (n = 761) after 1.5 years of the 2022 Russian invasion of Ukraine.

This research was designed as a survey in line with the methodology of “Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis” checklist. The survey included a questionnaire on sociodemographic characteristics and specifics of trauma exposure, as well as validated self-reported inventories: The International Trauma Questionnaire, Acceptance and Action Questionnaire – version 2, Connor–Davidson Resilience Scale-10 and the Modified BBC Subjective Well-being Scale.

Regression analysis revealed different prediction models for PTSD and CPTSD symptoms, explaining 18.4% and 41.4% of their variance with five and eight predictors, respectively. Four variables were similar in predicting PTSD and CPTSD: war-relatedness of trauma, living with a friend, perceived physical health and regret for the past. War-relatedness of trauma the respondents were exposed to was among the strongest predictors for PTSD and CPTSD severity. However, living with a friend was almost equally strong in mitigating these mental consequences. Regret for past and lowly rated physical health were assessed as relatively weaker but statistically significant predictors in this study.

Upon the original theoretical framework, two psychosocial prediction models were developed for PTSD and CPTSD symptoms in a non-clinical sample of trauma-exposed Ukrainian adults.

This study aims to develop and test a multivariable psychosocial prediction model of subjective well-being in Ukrainian adults (n = 1,248) 1.5 years after the 2022 Russian invasion of Ukraine.

The research design followed the “Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis” checklist. The online survey combined a questionnaire on sociodemographic characteristics and specifics of living in wartime, as well as validated self-reported inventories: The Modified BBC Subjective Well-being Scale, Acceptance and Action Questionnaire – Version 2 and Connor–Davidson Resilience Scale-10.

The initially developed model was tested through regression analysis, which revealed nine variables as predictors of the subjective well-being scores within the sample, explaining 49.3% of its variance. Among them, the strongest were living with a friend and receiving mental health care systematically. They were almost twice as influential as forced displacement abroad and trauma exposure, which predicted lower well-being, and living with a spouse, which forecasted higher well-being scores. Two resilience subscales – adjustment and restoring and resistance – as predictors of better well-being and perceived unsuccess in life and age as predictors of lower well-being were relatively weaker but statistically significant.

The obtained results support the previous evidence on the essential role of accessible mental health services and social support in times of war, as well as the deteriorative effect of trauma exposure and forcible taking refuge on subjective well-being.

Increasing the need for education for sustainable development in universities requires an understanding of the predictors of students’ environmental concern (EC). In this paper, the authors focus on the EC of business students because of their future responsibility for business operations regarding the exploitation of natural resources. The aim of the study is to examine the predictors of business students’ environmental concern.

Based on the Norm Activation Model as the theoretical framework, this study hypothesizes the model of EC with two main predictors: ascription of responsibility for the environment (AOR), driven by locus of control and self-efficacy (LC/SE), and awareness of positive consequences of consumption reduction on the environment (AOC), driven by perceived environmental knowledge. Structural equation modelling was applied to confirm the conceptual model based on the responses of business students from six countries (Czech Republic, Croatia, Hungary, Poland, Slovakia and Spain) collected through an online survey.

The environmental concern of business students is predicted both by the ascription of responsibility and by awareness of consequences; however, the ascription of responsibility is a stronger predictor of EC. A strong impact was found for internal locus of control and self-efficacy on AOR, as well as a weaker influence of perceived environmental knowledge on AOC.

Sustainability education dedicated to business students should provide environmental knowledge and strengthen their internal locus of control and self-efficacy in an environmental context.

For decades, consumer identification and motivation, either alone or jointly, have been essential constructs for behavioral researchers. The resultant output is significant in terms of both quality and quantity. However, at a deeper level, a lack of conceptual clarity in the relationship between these constructs has led to theoretical and practical irregularities, which this study aims to address.

An online questionnaire was distributed to sport consumers aged over 18 participating in an online panel, prompted 293 completed responses. Structural equations modeling was used to examine the data.

Findings show that identification mediates the effects of intrinsic and extrinsic motivation on sport supporters’ loyalty and explain 90% of the variance in that construct. In addition, identification mediates the adverse effects of extrinsic motivation on loyalty and strengthens loyalty when levels of satisfaction decline.

This study extends previous work by providing a theoretical perspective that clarifies the relationship between motivation and consumer identification; deepens theory by empirically observing the relationship at different levels of consumer satisfaction; and presents a parsimonious, valid and reliable method that managers can leverage to strengthen sport supporters’ loyalty.