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In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

This paper aims to examine the relationship between workplace toxicity and psychological capital (PsyCap). It also investigates the moderating role of gratitude in the toxicity–PsyCap link.

The study is based on explorative-cum-descriptive research design. The sample comprises 411 employees engaged in banking, insurance, IT, automobile and oil and gas companies. The collected data is explored for reliability, validity, multicollinearity and common method variance estimates. Also, the relationship between workplace toxicity and PsyCap and the moderating effect of gratitude are examined using structural equation modelling.

The findings report a negative association between toxicity and PsyCap. Also, the study concludes a significant moderating effect of gratitude. The study recommends the institutionalisation of a gratitude-based organisation to reduce the impact of workplace bullying and uncivil behaviour.

The study is based on primary data and one of the few studies that explore psychological capital as a dependent variable, which is influenced by toxic behaviours at work.

This study aims to investigate the effect of social influence and value-driven mobile marketing activities on consumers’ acceptance of mobile marketing offers.

The method used is survey questionnaire. A proposed model was tested by using structural model analysis and data gathered from 356 Mexico consumers and 346 US consumers.

The study shows the number of peers and providing information are the main predictor variables of consumer acceptance of mobile marketing offers in both countries. These results suggest that social value factors are important variables for explaining consumers’ responses to mobile marketing offers across two countries characterized by dissimilar macro-environmental conditions.

The study’s overall implication about standardization vs adaptation is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries. One limitation in this study is the use of a convenience sample of undergraduate college students. This study did not control for different types of mobile phones and the screen sizes of mobile phones.

The overall implication of standardization vs adaptation from the study results is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries.

Unlike previous studies where the emphasis is to explicate the effect of value-oriented mobile activity, this study examines the combined effect of social influence and value-driven mobile activities on acceptance of mobile marketing.

The mental healthcare is experiencing an ever-growing surge in understanding the consumer (e.g., patient) engagement paradox, aiming to vouch for the quality of care. Despite this surge, scant attention has been given in academia to conceptualize and empirically investigate this particular aspect. Thus, drawing on the Stimulus-Organism-Response (S-O-R) paradigm, the study explores how patients engage with healthcare service providers and how they perceive the quality of the healthcare services.

Data were collected from 279 respondents, and the derived conceptual model was tested by using Smart PLS 3.2.7 and PROCESS. To complement the findings of partial least squares (PLS)-based structural equation modeling (SEM), the present study also applied fuzzy set qualitative comparative analysis (fsQCA) to identify the necessary and sufficient conditions to explore substitute conjunctive paths that emerge.

Findings show that patients’ perceived intimacy (PI), cohesion and privacy enhance the quality of mental healthcare service providers. The results also suggest that patients’ PI, cohesion and privacy have indirect effects on the perceived quality of care (PQC) by the service providers through consumer engagement. The fsQCA results derive that the relationship among conditions leading to patients’ perception of the quality of care in regard to mental healthcare service providers is complex and is best reflected as multiple and conjectural causation configurations.

The findings from this research contribute to the advancement of studies on patients’ experiences by empirically examining the unique dynamics of interaction between consumers (patients) and mental healthcare service providers, thereby enriching both the literature on social interactions and the understanding of the consumer–provider relationship.

The results of this study provide practical implications for mental healthcare service providers on how to combine the study variables to enhance the quality of care and satisfy more patients.

A significant research gap has ascertained the inter-relationship between PI, cohesion, privacy, engagement and PQC from the perspective of mental healthcare service providers. This research is one of the primary studies from a managerial and methodological standpoint. The study contributes by combining symmetric and asymmetric statistical tools in service marketing and healthcare research. Furthermore, the application of fsQCA helps to understand the interactions that might not be immediately obvious through traditional symmetric methods.

Consumers and businesses are becoming increasingly conscious of sustainable business practices and are often willing to pay a premium for responsibly sourced and manufactured products. Many countries and organizations have implemented regulations and standards for sustainability and companies face penalties or are barred from exporting for not meeting the requirements. Rooted in the resource-based view theory, this study aims to test a moderated mediation model to improve the sustainability performance of exporting firms.

Textile firms generating more than 25% of export revenues were targeted for this research. The data collected from 245 middle management-level employees were tested for reliability and validity. The structural equation modelling in AMOS 26 was used to test hypotheses.

Organizational readiness for green innovation (ORGI) has a direct positive effect on sustainability performance. The mediation analysis implies that ORGI translates into sustainability performance through improvement in green innovation performance. The moderating effect of knowledge integration highlights the importance of being prepared internally and actively seeking and incorporating external knowledge to improve green innovation performance.

The findings offer a solid foundation for informed decision-making, policy development and strategies to improve sustainability performance while aligning with the global nature of the textile industry and its inherent challenges. The proposed model and practical implications guide policymakers and managers of exporting firms to foster a culture of green innovation to leverage the effect of their readiness for green innovation on sustainability performance.

The potential growth in cryptocurrencies has raised serious ethical and religious issues leading to a new investment rethinking. This paper aims to identify the influence of religiosity on cryptocurrency acceptance through an extended technology acceptance model (TAM) model.

In the first phase, this research develops a conceptual model that extends the theory of the TAM by integrating the religiosity component. In the second phase, the proposed model is tested using search volume queries in daily frequencies from 01/01/2018 to 31/12/2022 and structural equation modeling (SEM).

The empirical results demonstrate a significant positive effect of religiosity on the intention to use cryptocurrency, the users' perceived usefulness (PU) and ease of use (PEOU). Besides, the authors note that PEOU positively influences the intention. Furthermore, religiosity indirectly affects the intention through the PEOU and positively impacts the intention through the PU. In the same way, PEOU has a considerable indirect effect on the intention through PU.

This study has practical and theoretical contributions by providing insights into the cryptocurrency acceptance factors. In other words, it contributes to the literature by extending TAM models. Practically, it helps managers determine factors affecting the intention to use cryptocurrencies. Therefore, they can adjust their industry according to the suitable characteristics for creating successful projects.

Identifying the effect of religiosity on cryptocurrency users' choices and decisions has a social added value as it provides an understanding of the evolution of psychological variants.

The findings emphasize the importance of integrating big data to analyze users' attitudes. Besides, most studies on cryptocurrency acceptance are investigated based on one kind of religion, such as Christianity or Islam. Nevertheless, this paper integrates the effect of five types of faith on the users' intentions.

Stab-resistant body armor (SRBA) is used to protect the body from sharp knives. However, most SRBA materials currently have the disadvantages of large weight and thickness. This paper aims to prepare lightweight and high-performance SRBA by 3D printing truss structure and resin-filling method.

The stab resistance truss structure was prepared by the fused deposition modeling method, and the composite structure was formed after filling with resin for dynamic and quasi-static stab tests. The optimized structural plate can meet the standard GA68-2019. Digital image correlation technology was used to analyze the local strain changes during puncture. The puncture failure mode was summarized by the final failure morphologies. The explicit dynamics module in ANSYS Workbench was used to analyze the design of the overlapped structure stab resistance process in this paper.

The stab resistance performance of the 3D-printed structural plate is affected by the internal filling pattern. The stab resistance performance of 3D-printed structural parts was significantly improved after resin filling. The 50%-diamond-PLA-epoxy, with a thickness of only 5 mm was able to meet the stab resistance standard. Resins are used to increase the strength and hardness of the material but also to increase crack propagation and reduce the toughness of the material. The overlapping semicircular structure was inspired by the exoskeleton structure of the demon iron beetle, which improved the stab resistance between gaps. The truss structure can effectively disperse stress for toughening. The filled resin was reinforced by absorbing impact energy.

The 3D-printed resin-filled truss structure can be used to prepare high-performance stab resistance structural plates, which balance the toughness and strength of the overall structure and ultimately reduce the thickness and weight of the SRBA.