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In this study, the authors examine how organizational-, systems- and interpersonal-level trust may be required for a smooth functioning of the firms in the sharing economy (SE). The research objective is to explore the trust-building mechanisms of Airbnb, a leading SE organization, and its aim to foster generalized trust. An investigation of the Airbnb's promotion of different trust-building mechanisms will allow to evaluate their effectiveness in how they can help overcome scepticism and distrust between the transacting parties. Consequently, the authors can develop a unique theoretical perspective on generalized trust in SE environments and better understand any trust-related barriers preventing SE transactions.

The authors employ a case study approach to investigate the research questions with the aim to fully understand the abstract and complex nature of trust. They focus on Airbnb as the company enjoys a leading market position, being a sharing economy firm. Moreover, the personal nature of accommodation sharing, which is the business of Airbnb, increases users' trust requirements, and so the company must take active steps to promote trust between the transacting parties. The authors adopt thematic analysis to execute the data analysis of the study's findings, which are derived from emergent themes and directed by the research objectives and relevant literature.

The results show that users of Airbnb are concerned about the danger of opportunistic hosts, although they are primarily motivated to use the company's services due to its economic benefits. Nevertheless, the success of Airbnb platform stems from the trust that the company has succeeded in establishing among its users, in particular interpersonal trust. Analysis reveals that generalized trust is fostered at an interpersonal level in the form of peer reviews, at an organizational level in terms of brand familiarity and at a systems level in regards to interface design.

The authors advance the argument that confidence to transact in the social economy stems from a combination of three levels of trust, including organizational-, systems- and interpersonal-level trust. These findings contribute to the body of trust research in information technology and people literature from its unique investigative setting, whilst simultaneously strengthening the primarily speculative research on SE with in-depth empirical evidence.

The recent proliferation of social media platforms has witnessed a growth in social commerce by using social media to facilitate interactivity between customers and vendors. While emergent studies on social commerce are growing, their focus tends to be on millennials and cross-age groups. Given the growth of digital natives in shaping the online shopping experience of the future, we deemed an application to Generation Z necessary and overdue.

We draw on the existing literature and develop a framework to understand social commerce dynamics for digital natives. We employ PLS and CB-SEM to test our proposed model.

Our findings demonstrate the importance of social commerce information sharing activities in facilitating social support, a sense of warmth and belongingness, and online trust for Generation Z platform users. We also investigate the roles of online trust and perceived risk on intention to purchase and find support for both relationships. Finally, we discuss the findings in terms of theoretical and managerial contributions and conclude the study with limitations and future research directions.

This research is unique by using social commerce theory to explore Gen Z platform users. The finding will contribute to information system literature by expanding the social commerce research stream.

The advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.

This study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.

The authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.

These results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.

The increased digital interactions in the B2B industry have enhanced the importance of customer engagement as a measure of firm performance. This study aims to map and analyze temporal and spatial journeys for customer engagement in B2B markets from a bibliometric perspective.

The extant literature on customer engagement research in the B2B context was analyzed using bibliometric analysis. The citation analysis, keyword analysis, cluster analysis, three-field plot and bibliographic coupling were used to map the intellectual structure of customer engagement in B2B markets.

The research on customer engagement in the B2B context was studied more in western countries. The analysis suggests that customer engagement in B2B markets will take centre stage in the coming times as digital channels make it easier to track critical metrics besides other key factors. Issues like digital transformation, the use of artificial intelligence for virtual engagement, personalization, innovation and salesforce management by leveraging technology would be critical for improved B2B customer engagement.

The study provides a comprehensive reference to scholars working in this domain.

The study makes a pioneering effort to comprehensively analyze the vast corpus of literature on customer engagement in B2B markets for business insights.

The study hypothesized that the impact of board diversity on financial distress (FD) is not direct but rather mediated by the firm’s corporate social responsibility (CSR) activities. Consequently, the purpose of this study is to examine the impact of CSR as a mediator in the board diversity–FD relationship.

The study examined six board diversity dimensions – age, gender, nationality, education and tenure in 81 nonfinancial Pakistan Stock Exchange (PSX)-listed firms from 2010 to 2021. The CSR engagement of the sample firms is evaluated using a multidimensional financial approach and the likelihood of FD is computed using Altman’s Z-score. The system-generalized method of moments estimator is used to meet the study objectives. In addition, several tests are run to determine the robustness of the study’s findings.

Based on the procedure for mediation analysis outlined by Baron and Kenny (1986), the authors found that CSR is significantly inversely associated with the likelihood of FD. Second, board diversity variables age, gender and national diversity were positively associated with CSR. Third, board age, gender and national diversity are significantly inversely related to FD. Finally, it was found that there is partial mediation between board age diversity and FD, whereas full mediation is shown between board age diversity and FD and between board nationality diversity and FD.

This study provides practical insights into PSX’s board diversity for companies, regulators and policymakers.

This research studies the connection between board diversity and FD. In addition, the current study extended the analysis by testing for the first time the mediating role of CSR in the diversity–distress relationship, particularly in the context of an emerging economy.

The main objective of this research is to analyze satisfaction with tourist services linked to the concept of sustainability in the context of a visit to the so-called equestrian show. The equestrian show adds values from the cultures that passed through the city. Specifically, the study focuses on tourist loyalty based on satisfaction with tourist services, satisfaction with the equestrian show and its overall quality. The fieldwork has been conducted in Córdoba, Spain. There are few studies on the relationship between tourist services linked to the concepts of sustainability and loyalty from the perspective of equestrian show management, making this a novel contribution to research.

The methodology used is based on a partial least squares structural equation modeling (PLS-SEM) approach.

To achieve the proposed objective, a structured questionnaire was used, and the results obtained confirm that satisfaction with tourist services linked to the concept of sustainability and the assessment of quality positively influence tourist loyalty. Consequently, they recommend returning to the destination and repeating the visit.

Heritage in Córdoba, Spain, is internationally recognized. Its uniqueness, with four world inscriptions along with the cultures that inhabited it, left a material heritage legacy in the city. Over time, this legacy has made it a magnet for visitors, making it essential to delve into its management and how concepts such as satisfaction with tourist services, combined with sustainability, impact the improvement of the visit.

(1) A mathematical model for the Hybrid nanofluids flow is used as carriers for delivering drugs. (2) The flow conditions are controlled to enable drug-loaded nanofluids to flow through the smaller gap between the two tubes. (3) Hybrid nanofluids (HNFs) made from silver (Ag) and titanium dioxide (TiO₂) nanoparticles are analyzed for applications of drug delivery. (Ag) and (TiO₂) (NPs) are suitable candidates for cancer treatment due to their excellent biocompatibility, high photoactivity, and low toxicity. (4) The new strategy of artificial neural networks (ANN) is used which is machine-based and more prominent in validation, and comparison with other techniques.

The two Tubes are settled in such a manner that the gap between them is uniform. The Control Volume Finite Element Method; Rk-4 and Artificial Neural Network (ANN).

(1) From the obtained results it is observed that the dispersion and distribution of drug-loaded nanoparticles within the body will be improved by the convective motion caused by hybrid nanofluids. The effectiveness and uniformity of drug delivery to target tissues or organs is improved based on the uniform flow and uniform gap. (2) The targeting efficiency of nanofluids is further improved with the addition of the magnetic field. (3) The size of the cylinders, and flow rate, are considered uniform to optimize the drug delivery.

(1)The flow phenomena is considered laminar, one can use the same idea through a turbulent flow case. (2) The gap is considered uniform and will be interesting if someone extends the idea as non-uniform.

(1) To deliver drugs to the targeted area, a suitable mathematical model is required. (2) The analysis of hybrid nanofluids (HNFs) derived from silver (Ag) and titanium dioxide (TiO₂) nanoparticles is conducted for the purpose of drug delivery. The biocompatibility, high photoactivity, and low toxicity of (Ag) and (TiO₂) (NPs) make them ideal candidates for cancer treatment. (3) Machine-based artificial neural networks (ANN) have a new strategy that is more prominent in validation compared to other techniques.

The drug delivery model is a useful strategy for new researchers. (1) They can extend this idea using a non-uniform gap. (2) The flow is considered uniform, the new researchers can extend the idea using a turbulent case. (3) Other hybrid nanofluids flow, in the same model for other industrial usages are possible.

All the obtained results are new. The experimental thermophysical results are used from the existing literature and references are provided.

Intellectual capital (IC) is a paramount resource for competitiveness in the knowledge-based financial sectors of the economy. As financial technology advances, specifically in the banking industry, it is vital to understand the effect of IC on financial performance. This study aims to investigate the effect of IC on return on equity (ROE), with a unique emphasis on the moderating role of board attributes. Previous studies have overlooked this moderating role.

The study sample consists of 17 banks and a panel data set spanning 2016–2021, extracted from annual reports. Antel Pulic’s value-added intellectual coefficient (VAIC) model is used to compute IC. To analyze the data, a generalized least squares analysis is conducted. The robustness of the analysis is ensured by using the two-stage least squares (2SLS) econometric technique.

The findings indicate that both the VAIC and human capital efficiency (HCE) have a significant impact on the ROE of banks. In terms of moderation, it is observed that board size (BS) exerts a negative effect on the association between VAIC, HCE, structural capital efficiency and ROE. Additionally, BS positively compounds the connection between capital employed efficiency and ROE. Similarly, the presence of independent directors (IND) significantly moderates the effects of VAIC and its components on the ROE of banks in Pakistan.

Banks should focus on the HCE for a higher ROE. Moreover, banks ought to prioritize appointing more independent directors in the boardroom for effective utilization of IC and greater ROE.

The findings of the study, which analyzed data from Pakistan’s banking sector, are original and provide additional insights into the literature on IC and board attributes.

This study aims to examine the direct effects of Green Human Resource Management (GHRM) practices on employee green behavior (EGB) in the university setting in Bangladesh and to find the indirect effects of how GHRM promotes EGB through sequentially mediating employee environmental knowledge management (EEKM) (environmental knowledge and knowledge sharing) and green self-efficacy (GSE).

For the empirical study, the researcher uses partial least squares structural equation modeling to test the proposed conceptual model built on existing literature for greening workplaces in the university in Bangladesh. The study has collected data from 288 Bangladeshi university employees using convenient sampling.

The findings that GHRM practices positively and significantly promote EGB, which captures the employee's tendencies to exercise green behavior in daily routine activities such as turning off lights, air conditioning, computers and equipment after working hours, printing on both sides, recycling (reducing, repair, reuse), disseminating good green ideas, concepts, digital skills and knowledge to peers and champion green initiatives at work. Moreover, the findings also revealed the sequential mediation of EEKM (environmental knowledge and knowledge sharing) and GSE of employees between the link GHRM and EGB. At last, the findings suggested that HR managers can implement the GHRM practices to promote green behaviors among the academic and non-academic staff of the university.

This study contributes to the field by extending knowledge of Social Cognition Theory and Social Learning Theory for greening workplaces in Bangladesh, particularly universities. Specifically, this empirical study is unique to the best of our knowledge and highlights the role of EEKM and GSE as mediation between GHRM and EGB association.

This study aims to conduct a comprehensive assessment of the existing literature on green human resource management (GHRM) and its correlation with environmental performance (EP) and energy saving behavior (ESB) by using the PRISMA methodology.

A thorough examination was undertaken involving a total of 25 articles which included a diverse range of years and geographic areas.

The findings suggest a growing emphasis on the intersection of GHRM, EP and ESB, supported by a substantial increase in research in recent times. The literature in question was mostly contributed by Malaysia, Pakistan, Canada and Thailand. Majority of research endeavors were carried out within the context of manufacturing companies. The studies under scrutiny mostly used quantitative research methodologies and often applied the resource-based view (RBV) and theory of planned behavior (TPB) frameworks to investigate the relationships between GHRM, ESB and EP. In addition, structural equation modeling (SEM) has garnered significant attention as a commonly used analytical methodology. This analysis emphasizes the growing importance of GHRM strategies such as green recruiting, green performance management and green remuneration, in fostering sustainable organizational results.

This work offers significant contributions to the existing body of research in this particular sector; shedding light on its present condition and pinpointing prospective avenues for future inquiries.