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The objective is to address financing challenges with an innovative technical approach and provide financial support to facilitate the sustainable development of characteristic tourist towns.

In this study, a novel decision model is proposed, which utilizes the CRITIC improved G1 weighting method to analyze financing factors and applies GRA to enhance the TOPSIS model under a Z-Number fuzzy environment. Finally, sensitivity analysis and comparative assessment were conducted to validate the findings and the model.

The findings indicate that equity financing is the optimal mode of financing for characteristic tourist towns, with bond financing serving as a viable alternative. Key factors influencing financing include economic benefit, social benefit and policy risk. Managers should carefully consider these factors when selecting financing methods in order to enhance efficiency and mitigate risks.

As a new business model and value creation method of cultural and tourism integration, the financing decision of a characteristic tourism town has always been the key to the overall promotion and operation. The research constructs a financing index system for characteristic tourism towns based on benefit and risk considerations, using the hot spring town in Anhui Province, China, as a case study to evaluate eight financing models.

The present findings aim to investigate the thermal behavior of water-based nanofluid flow over a rotating surface, focusing on understanding the effects of different types of nanoparticles on thermal efficiency, considering thermal radiation and variable viscosity effects. By considering four distinct nanoparticles – silicon dioxide titanium dioxide, aluminum oxide and molybdenum disulfide – the study aims to provide insights into how nanoparticle addition influences heat production, thermal boundary layer thickness and overall thermal performance.

The study employs computational methods, utilizing the BVP mid-rich algorithm for the solution procedure. The computational approach allows for a detailed investigation of the thermal behavior of nanofluid flows across a rotating surface under varying conditions.

The study concludes that adding nanoparticles in the base liquid increases heat production in the system, resulting in enhanced thermal boundary layer thickness. The comparative analysis shows that different nanoparticle types exhibit varying effects on thermal efficiency, suggesting that careful selection of nanoparticles can optimize heat transport and thermal management processes. Moreover, there's a noteworthy uptrend in the radial velocity profile concerning the stretching parameter, whereas a converse trend is observed in the thermal profile.

This study contributes original insights by comprehensively investigating the thermal behavior of water-based hybrid nanofluid flow over a rotating surface.

This chapter critically examines the unique challenges and opportunities faced by family-owned startups in emerging economies, a topic that has received limited attention in existing literature. Recognizing the high failure rate of startups, particularly in family firms, this study seeks to understand the factors contributing to their success or failure. Employing a qualitative analysis, the chapter explores various economic, legal, and cultural dimensions that influence these businesses. It provides a comparative perspective, drawing insights from various emerging economies to identify patterns and differences in the experiences of family-owned startups. The chapter aims to fill the knowledge gap by offering a comprehensive view of the success and failure dynamics in family-owned startups, with a focus on strategic, managerial, and operational aspects. This approach offers valuable insights for both academics and practitioners, aiming to guide future research and practical interventions to support the sustainability and growth of family firms in these dynamic markets.

Mobile payment (or m-payment), a relatively new digital banking system targeting Pakistani customers, is rapidly expanding. This study aims to explore the elements that impact customer behaviour and encourage the adoption of m-payment in Pakistan.

This study used a quantitative research design, surveying 315 m-payment users residing in three Pakistani cities. A conceptual framework was developed by extending the meta-unified theory of acceptance and use technology (meta-UTAUT) model to incorporate institutional privacy concerns (IPC) and institutional source reliability (ISR). Data analysis was conducted using partial least squares structural equation modelling via Smart PLS 4.0 software.

This study’s results indicate that behavioural intention (BI) is the primary driver ofm-payment use behaviour. The findings also reveal that attitude (AT), performance expectancy (PE), facilitating conditions (FC), social influence (SI), effort expectancy (EE), IPC and ISR significantly influence BI. Notably, PE and FC are positively associated with AT, while EE and SI have no significant impact on AT.

This study has two key limitations. First, its focus on only Pakistani m-payment users limits the broader applicability of the results. Second, the cross-sectional design overlooks potential longitudinal changes in users’ attitude. Future research should aim to recruit diverse country samples and conduct comparative studies, thereby enhancing the understanding of m-payment adoption.

This study provides insights for service providers and marketers, identifying key factors that influence m-payment adoption. Convenience emerges as a critical consideration, suggesting it may drive customer behaviour.

This research significantly advances the field of m-payment studies by investigating the key factors influencing Pakistani consumers’ adoption of m-payment, extending the meta-UTAUT model to include IPC and ISR. By applying this extended framework to the context of Pakistani consumers’ acceptance and use of m-payment, this study provides new insights into the complex factors driving m-payment adoption in developing Asian countries like Pakistan, addressing a significant research gap and paving the way for future studies.

This paper investigates the interactional relationships between sustainable human resource management (SHRM) and organizational performance (OP). Sustainable HRM is an approach that links HRM and sustainability. These studies focused on integrating HR with sustainable developments, such as economic and social aspects, in favour of focusing on the environmental aspect. Organizational change is an ongoing process that has to be managed effectively to keep the change in place for a long time.

A framework was offered to estimate the cause-and-effect relation of the SHRM and OP factors. Data is gathered from professionals from various pharmaceutical industries. This study applied two methods, Fuzzy AHP and DEMATEL Type II. These techniques are used to understand the cause-and-effect factors and their interactions.

It was observed from the findings that the factor of SHRM, such as Social Justice (F2), Green Job Design (F5), Green Training (F6) and Implementation of Green Policy (F8), was the most critical for the pharmaceutical sector that effects Financial performance (F13), Customer Satisfaction (F15) and Market performance (F14). Pharmaceutical firms ought to coordinate public health advocacy efforts, engage in healthcare initiatives and provide financial support for environmentally friendly efforts that improve social and economic conditions.

For this sustainability, managers concentrate on creating an environment that is healthy and acceptable, and they work hard to mitigate the impact of natural factors and repair damage done to the environment; it is essential to move towards sustainable development to resolve environmental problems. Improving HR efficiency is among essential HRM responsibilities, as they expand the knowledge base of the workforce, enhance human capital, and eventually create valuable intangible assets and promote and encourage sustainable pharmaceutical products for some years.

This research paper has presented exclusive worth to the SHRM and organizational performance literature as it employs fuzzy FAHP and DEMATEL type 2. There is less research on SHRM in the pharmaceutical sector with these factors. In addition, FAHP and TYPE 2 DEMATEL are used in very few researches on SHRM approaches.

An efficient e-waste management system is developed, aided by deep learning techniques. Here, a smart bin system using Internet of things (IoT) sensors is generated. The sensors detect the level of waste in the dustbin. The data collected by the IoT sensor is stored in the blockchain. Here, an adaptive deep Markov random field (ADMRF) method is implemented to determine the weight of the wastes. The performance of the ADMRF is boosted by optimizing its parameters with the help of the improved corona virus herd immunity optimization algorithm (ICVHIOA). Here, the main objective of the developed ADMRF-based waste weight prediction is to minimize the root mean square error (RMSE) and mean absolute error (MAE) rate at the time of testing. If the weight of the bins is more than 80%, then an alert message will be sent to the waste collector directly. Optimal route selection is carried out using the developed ICVHIOA for efficient collection of wastes from the smart bin. Here, the main objectives of the optimal route selection are to reduce the distance and time to minimize the operational cost and the environmental impacts. The collected waste is then considered for recycling. The performance of the implemented IoT and blockchain-based smart dustbin is evaluated by comparing it with other existing smart dustbins for e-waste management.

The developed e-waste management system is used to collect the waste and to avoid certain diseases caused by the dumped waste. Disposal and recycling of the e-waste is necessary to decrease pollution and to manufacture new products from the waste.

The RMSE of the implemented framework was 33.65% better than convolutional neural network (CNN), 27.12% increased than recurrent neural network (RNN), 22.27% advanced than Resnet and 9.99% superior to long short-term memory (LSTM).

The proposed E-waste management system has given an enhanced performance rate in weight prediction and also in optimal route selection when compared with other conventional methods.

This paper aims to illuminate the nuanced dynamics of green supply chain management (GSCM), specifically focusing on the intersections of supplier relationships, supplier governance and organizational agility. Recognizing a gap in the understanding of how these elements confluence to promote green purchasing, the paper uses a quantitative study on data collected from the Australian food industry. Advanced analysis techniques provide empirical evidence underscoring the pivotal roles these elements play, expanding on current GSCM literature within a resource-based view.

This study, based on a questionnaire sent to Australian food professionals, used higher-order reflective constructs to assess supplier relationships and governance. Data was analyzed using partial least squares structural equation modeling and Hayes PROCESS, considering factors like firm revenue and manager experience. Both the reliability of measures and mediation hypotheses were stringently validated using established guidelines.

The comprehensive study validated supplier governance's key influence on green purchasing and supplier relationships. Notably, organizational agility emerged as a crucial mediator, underscoring the interplay of these constructs. Concurrently, the reflective measurement model exhibited robust validity and reliability. Interestingly, demographic factors such as company size, revenue and managerial experience showed no discernible impact on green purchasing practices.

In the Australian food sector, supplier governance and relationships are pivotal for advancing green purchasing. This study emphasizes the value of organizational agility in amplifying these practices. Managers, when aligning with supplier relationships enhanced by communication and mutual aid, can foster robust green initiatives. Embracing these insights and the critical importance of supplier governance, managers can drive more sustainable, informed supply chain decisions in the industry.

In pursuit of understanding the relationship between supplier governance, supplier relationships and green purchasing, this research uniquely situates itself within the resource-based view (RBV) to reveal critical theoretical and practical implications. By focusing on the Australian food industry, the study spotlights the often-overlooked mediating role of organizational agility in linking supplier relationships with green purchasing efforts. In doing so, this research not only strengthens the argument for fortified supplier relationships – as a catalyst for enhancing agility and thereby green practices – but also re-contextualizes the RBV in a fresh light. This new perspective provides managers with an enriched model, emphasizing the imperative of solid supplier governance for sustainable, agile and green supply chain operations in the food domain.

The purpose of this study is to examine the linear and non-linear relationship between capital structure (CS) and firm performance (FP) and the moderating and mediating roles of agency costs in the CS-FP nexus.

This study used static and quadratic panel data regression models to examine the linear and non-linear relationships and structured equation models to analyze the mediating effect of agency costs in the CS-FP nexus of 38 listed non-financial Mauritian firms from 2009 to 2019.

Leverage has a significant negative effect on FP supporting the pecking order theory. Agency costs are significantly and positively associated with FP. There is a strong non-linear relationship between leverage and FP supporting the trade-off and agency cost theories. Agency costs are an important moderator and mediator in the CS-FP nexus. Overall, the sensitivity analyses showed that the results were robust.

Firms need to carefully consider the levels and types of debt and equity in their CS involving the use of dynamic strategies to adjust CS in response to changing economic conditions and FP. The moderating effect of agency costs may guide firms in optimizing CS and may contribute to corporate governance discussions, emphasizing the importance of aligning interests to foster sustainable business practices.

This study adds to the extant literature by providing new evidence on the non-linear relationship between leverage and FP and the moderating and mediating roles of agency costs in the CS-FP nexus in emerging capital markets, where such studies are rare.

This chapter delves into the crucial intersection of Destination Social Responsibility (DSR) and sustainable development within the context of coastal marine tourism destinations. The research objective is to offer a comprehensive analysis of how DSR practices influence the trajectory of sustainable development in these unique environments. Employing a qualitative interview with key stakeholders, content analysis of policy documents and quantitative surveys of tourists, this study endeavours to attain a holistic knowledge of the intricate dynamics at play. By triangulating these methods, we aim to establish a robust foundation for comprehending the multifaceted relationship between DSR initiatives and sustainable development outcomes. The findings reveal a nuanced interplay between DSR and sustainable development indicators. Notably, the integration of socially responsible practices positively correlates with enhanced environmental conservation efforts, increased community engagement and heightened visitor satisfaction levels. This research advances our comprehension of the interdependency between DSR and sustainable development. Hence, it is important to acknowledge its limitations. The practical implications of this study are manifold. Policymakers, destination managers, as well as industry stakeholders stand to benefit from a nuanced understanding of how DSR practices can be leveraged to drive sustainable development. This chapter is responsible for the current literature by offering an extensive analysis of the interplay between DSR as well as sustainable development in coastal marine tourism destinations. By synthesising empirical findings and theoretical frameworks, this research provides a valuable resource for scholars, policymakers and industry practitioners seeking to navigate the complex landscape of responsible tourism development.

This study investigates the influence of social media marketing (SMM) functionalities on perceived destination image (DI) and its dimensions, which in turn impact residents’ support for sustainable tourism development (SSTD). The study also examines the moderated mediation effect of the residency length and resident’s income in the indirect relationship between SMM and SSTD through the DI.

The best technique found appropriate for this study was the survey approach. To gather empirical data, people who currently reside in Alexandria completed 351 questionnaires via an online survey. The questionnaire was translated into Arabic while adhering to back-translation guidelines. SPSS and AMOS software were used to analyze the collected data.

It is found that there is a direct effect of SMM and its functionalities on overall DI and its dimensions. In addition, DI mediates the relationship between SMM and SSTD. These results hold valuable insights for academicians and practitioners in the tourism industry, potentially informing SMM strategies to support tourism activities.

This research introduces a novel framework emphasizing the functionalities of the SMM as a tool for enhancing both affective and cognitive DI and supporting sustainable tourism development. It contributes to the SMM and SSTD literature by examining the links between SMM functionalities and sustainable tourism development in emerging countries such as Egypt.