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Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

The importance of transformational leadership (TFL) for improving followers’ work engagement (WE) has been highlighted by management researchers, but little is known about how and why TFL is related to WE. This study develops an integrated model that addresses the questions and uncovers the influence of TFL on employees’ WE through two pathways reflecting simple and parallel mediating effects of employees’ self-efficacy (SE) and trust in the leader.

In a developing country’s organizational context, a total of 376 employees working in four different types of organizations voluntarily participated in the survey. Partial least square structural equation modeling (PLS-SEM) was used to test the study model.

Data supported the joint parallel mediation effect of subordinates’ SE and trust in the leader and partially confirm the role of a single mediator of each between the relationship of TFL and WE.

In public sector, it is a daunting challenge to sustain a high degree of WE of employees so that they may actively involve in the provision of better services planned by policymakers. Therefore, WE has deemed a very important construct for both administrators and researchers in such organizations. The framework and relationships that are discussed and displayed in this study help administrators in understanding the driving forces that cause in to WE.

This research links multiple theories to develop an integrated model. The employees' perceptual data supported predictive power of the model both in-sample and out-of-sample through a rigorous statistical technique. Hence, this study is contributing to narrowing the gap between theory and practice.

Entrepreneurship is one of the significant drivers of economic growth, development and job generation in several countries worldwide. Realizing its significant contribution to the nation’s development, policymakers and educators have also drawn attention to fostering entrepreneurship among the youth. Researchers attempted to comprehend the dynamics and investigate the factors influencing entrepreneurial intention (EI). As is true for other abilities and response tendencies, individual differences exist for EI also. This study aims to explore the relationship of emotional intelligence (EIn) and cognitive flexibility (CF) with EI and mediating effect of entrepreneurial self-efficacy (ESE) in the relationship between CF, EIn and EI.

The cross-sectional survey was conducted to gather responses from 635 individuals aged 17–26 years (M = 19.2, SD = 1.49). The hypotheses were tested using correlation, regression and mediation analysis.

The findings indicated that EIn and CF were significantly and positively related to EI. Furthermore, ESE was found to be a partial mediator between EIn and EI and a full mediator between CF and EI.

Results reflected the critical significance of ESE and implied that EI might be strengthened by intervening in ESE through various sources.

This study adds to the existing literature by incorporating less studied individual factors (EIn and CF) to better understand EI by explaining the mediation mechanism through ESE.

Work-based learning is critical for enhancing employees’ skills and contributing to the firm’s performance. This paper aims to establish the effects of needs assessment on the relationship between training intensity as part of learning and how employees’ skills are reflected in firm performance.

The paper used the World Bank Tanzania Employees Skills Survey (TESS) dataset, which contains 424 firms. This paper estimated the moderated mediation model through partial least squares structural equation modelling (PLS-SEM) and employed the index of moderated mediation to determine if the model was correctly specified.

The results show that among three skills, i.e. technical, interpersonal/communication and work ethic skills, only the level of technical skills mediated the relationship between training and the firm’s performance. The index of moderated mediation suggests a threshold point for the firm’s training needs, above which the indirect effect of training on performance through technical skills starts to decrease. The negative correlation between the firm’s training needs and the indirect effect suggests that employees’ essential human capital qualities, viewed from the angle of their training needs, are among the key factors for executing effective training.

This paper’s conceptual model is limited because it does not incorporate an education variable for the trained employees. In addition, it only conceptualized the perceived most important skills of interpersonal communication, technical skills and work ethic, despite there being other skills that could have been considered. Moreover, the data only measured the present skill level at three on the Likert scale, providing limited room for skill level variance.

Those who decide which training programme deserves priority given limited resources and the firm’s goals need to understand that training is an addition to what their employees already have and, thus, should make extra efforts to equip them with more knowledge relating to their assignments. Moreover, this understanding should extend to the employees themselves.

The paper introduced and showed the necessity of training needs assessment to increase the value of training in enhancing the firm’s performance. We propose a model for assessing training intensity through process analysis. The respective model depicts a threshold point for the firm’s training needs, below which the training will work.

This study aims to investigate whether and how artificial intelligence (AI) awareness affects work withdrawal.

This survey garners participation from a total of 305 hotel employees in China. The proposed hypotheses are examined using Hayes’s PROCESS macro.

The results indicate that AI awareness could positively affect work withdrawal. Negative work-related rumination and emotional exhaustion respectively mediate this relationship. Furthermore, negative work-related rumination and emotional exhaustion act as chain mediators between AI awareness and work withdrawal.

Given the growing adoption of AI technology in the hospitality industry, it is imperative that managers intensify their scrutiny of the psychological changes experienced by frontline service employees and allocate more resources to mitigating the impact of AI on their work withdrawal.

This study contributes to the burgeoning literature on AI by elucidating the chain mediating roles of negative work-related rumination and emotional exhaustion. It also makes a significant forward in examining mediating mechanisms, notably the chain-mediated mechanism, through which AI awareness impacts employee outcomes.

Mobile messaging groups (MMGs) have been widely adopted in construction practice, yet, little is known about how to foster knowledge sharing (KS) in MMGs, characterized by communication visibility. This study is thus motivated to investigate mechanisms for KS in this context.

The paper employs knowledge governance theory to construct a theoretical model and develop hypotheses. Specifically, psychological safety is identified as a mediator between knowledge governance mechanism (KGM) and KS, and promotion regulatory focus is identified as a moderator between KGM and psychological safety. Data from 208 Chinese construction project team members are collected to test the proposed theoretical model.

The results suggest that both formal and informal KGM positively affect psychological safety, which in turn improves KS (quantity and quality). Moreover, the mediating role of psychological safety is confirmed, and the moderating role of promotion regulatory focus is validated.

This study explores how to foster KS in MMGs, which are pervasive in today’s digital age. The findings in this study enhance the understanding of KS in digital environments and afford important insights into knowledge management within construction project teams.

Artificial intelligence (AI) is shaping the future of the marketing world. This study is the first to examine the effect of AI marketing efforts, brand experience (BE) and brand preference (BP) in light of the stimulus-organism-response (SOR) model.

The data collected from 398 participants by the questionnaire method were analyzed by SEM (structural equation modeling) using Smart PLS 4.0 and IBM SPSS 26 programs.

We find that four SOR elements of AI marketing efforts (information, interactivity, accessibility and personalization) positively impact bank customer BE, BP and repurchase intention (RPI). Further, we find that BE plays a mediator role in the relationship between AI marketing efforts, RPI and BP.

The findings of the study have significant implications for the bank marketing literature and the banking industry, given the limited evidence to date regarding AI marketing efforts and bank–customer relationships. Moreover, the study makes important contributions to the AI marketing and brand literature and helps banks increase customer experience with artificial intelligence activities and create long-term relationships with customers.

This study examines how compliance with government and firm's own policy and reverse logistics practices relate with firm environmental performance.

This study draws on insights from stakeholder theory, and follows a two-phase research approach. The first phase utilized an extended literature review that seeks to provide a qualitative and comprehensive understanding of the research problem. The 2001–2023 data was collected from the Web of Science and Scopus databases, complemented with Google Scholar. The second phase involved an empirical study—adopting a quantitative cross-sectional survey design with a self-administered questionnaire to validate the theoretical conceptualizations deriving from the literature review. The empirical data were collected from 203 food and beverages manufacturing firms in Uganda and analysed using the partial least squares structural equation modelling (PLS-SEM) approach.

The study findings suggest that compliance with government policy positively influences firm environmental performance, both directly, and indirectly through fostering reverse logistics practices, and that the relationship between compliance with government policy and reverse logistics practices is contingent upon compliance with the focal firm's own policy.

The study findings will enhance the theoretical and conceptual development of the ideas that underpin stakeholder theory and applications. The Ugandan government will come up with better mechanisms for enforcing compliance with policy regulating the application of reverse logistics practices. In addition, the study advances the use of multi-method approaches in investigating interesting research aspects requiring in-depth examination. However, considering the fact that the empirical study was conducted in a single country context, and focused on firms more or less from the same sub-sector, the findings of the study might not be generalizable globally.

This study provides useful insights to logistics and supply chain managers involved in reverse logistics activities in food and beverages manufacturing firms. These managers can know how to leverage reverse logistics practices to enhance environmental performance of firms amidst environmental policies in the industry where they operate.

This study contributes to the built body of knowledge in operations, logistics and supply chain management literature; understanding about reverse logistics practices as a mechanism through which compliance with government policy influences environmental performance of firms. The interaction between compliance with government policy and compliance with firm policy is essential in explaining the performance effects of reverse logistics practices. In addition, the study advances the use of multi-method approaches in investigating interesting research aspects requiring in-depth examination. Complementing extended literature review with and empirical research to investigate reverse logistics practices influences on firm environmental performance, and incorporating the role of policy in explaining this relationship should make considerable contribution. Besides, the study highlights important areas for future research.

The purpose of this study is to examine the extent to which a firm is able to leverage its information system (IS) innovativeness to improve supply chain resilience through developing and employing its analytics capability. It further considers how this mediating effect of analytics capability can be enhanced by internal and external integration.

Building on the logic of organizational information processing theory, a mediated moderation model is developed and tested using structural equation modeling and partial least squares regression based on survey responses from 247 working professionals.

The results indicate that IS innovativeness improves a firm’s supply chain resilience through enhanced analytics capability, with higher levels of internal and external integration further strengthening the effects of this mediating relationship.

This study is among the first to empirically test the effects of IS innovativeness and analytics capability on supply chain resilience and to examine the impacts of internal and external integration as key factors affecting the strength of these relationships. The findings complement existing literature through providing new insights into the linkage between IS strategy and supply chain resilience and highlighting the importance of relationships throughout the supply chain to enhance the efficacy of a firm’s analytics capability within this domain.

Drawing from the resource-based view (RBV), this study aims to develop a parsimonious model in the context of digital platforms that links strategic network resources (SNR) and firm performance through considering dynamic capabilities (DC) as important mediating mechanisms. In addition, we also investigate how platform monitoring shapes the relationship between SNR and DC.

This study uses the survey data from 162 firms in eastern China.

The findings indicate that both two DC dimensions (i.e., sensing and reconfiguring) significantly mediate the relationship of SNR-performance. Moreover, platform monitoring positively moderates the relationship of SNR and sensing as well as SNR and reconfiguring.

With these findings, this study advances SNR and digital platform research and provides insights into how to transform SNR into superior performance through DC.