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The purpose of this study is to assess how Sustainable food consumption (SFC) can improve the quality of life for consumers and encourage green food production. Sustainable consumption is an important factor in achieving the sustainable development goals (SDGs) proposed by the United Nations. However, achieving SFC requires government policies, consumer environmental values and accessible channels.

This paper investigates how to promote SFC intentions using a sample of 386 students from Chinese universities. By using SPSS Process software, this study developed and tested a theoretical model grounded in the stimulus-organism-response (SOR) framework.

The findings indicate that environmental emotions mediate the relationship between sustainability knowledge and SFC intentions. Contextual factors such as green self-efficacy (GSE) moderate both the direct relationship between environmental emotions and SFC intentions and the indirect relationship between sustainability knowledge and SFC intentions via environmental emotions. The paper continues with a discussion of the findings and their practical implications.

This paper applied the SOR model to the context of students’ sustainability knowledge and SFC intentions. This also presents environmental emotions as a mediation variable, and green self-efficacy as a moderating factor, and constructs the moderated mediation model. This is one of the novel contributions to the literature on SFC intentions and sustainability knowledge.

To improve the thermal performance of base fluid, nanoparticles of three types are dispersed in the base fluid. A novel theory of non-Fourier heat transfer is used for design and development of models. The thermal performance of sample fluids is compared to determine which types of combination of nanoparticles are the best for an optimized enhancement in thermal performance of fluids. This article aims to: (i) investigate the impact of nanoparticles on thermal performance; and (ii) implement the Galerkin finite element method (GFEM) to thermal problems.

The mathematical models are developed using novel non-Fourier heat flux theory, conservation laws of computational fluid dynamics (CFD) and no-slip thermal boundary conditions. The models are approximated using thermal boundary layer approximations, and transformed models are solved numerically using GFEM. A grid-sensitivity test is performed. The accuracy, correction and stability of solutions is ensured. The numerical method adopted for the calculations is validated with published data. Quantities of engineering interest, i.e. wall shear stress, wall mass flow rate and wall heat flux, are calculated and examined versus emerging rheological parameters and thermal relaxation time.

The thermal relaxation time measures the ability of a fluid to restore its original thermal state, called thermal equilibrium and therefore, simulations have shown that the thermal relaxation time associated with a mono nanofluid has the most substantial effect on the temperature of fluid, whereas a ternary nanofluid has the smallest thermal relaxation time. A ternary nanofluid has a wider thermal boundary thickness in comparison with base and di- and mono nanofluids. The wall heat flux (in the case of the ternary nanofluids) has the most significant value compared with the wall shear stresses for the mono and hybrid nanofluids. The wall heat and mass fluxes have the highest values for the case of non-Fourier heat and mass diffusion compared to the case of Fourier heat and mass transfer.

An extensive literature review reveals that no study has considered thermal and concentration memory effects on transport mechanisms in fluids of cross-rheological liquid using novel theory of heat and mass [presented by Cattaneo (Cattaneo, 1958) and Christov (Christov, 2009)] so far. Moreover, the finite element method for coupled and nonlinear CFD problems has not been implemented so far. To the best of the authors’ knowledge for the first time, the dynamics of wall heat flow rate and mass flow rate under simultaneous effects of thermal and solute relaxation times, Ohmic dissipation and first-order chemical reactions are studied.

This chapter is about the role Islamic finance has been able to stay on the track of facing social–economical predicaments and on the way to sustainable development with the involvement of social prosperity. When trying to investigate the convergence between social finance and Islamic standards, what is argued is that a need for observing financial operations in the same way as prodevelopment theories arise. It is considered that in a holistic approach, which assumed a social justice as the basic ethic of the Islamic financial system, the final result tends to be more appropriate. One of the main elements that makes Islamic banking stand up in a high grade is maqasid al-Shari'ah due to its responsibility to assess social performance and apply new updated technologies for sustainable growth based on Sustainable Development Goals (SDGs). In addition to that, the situation is critically observed and the gap between ambitions functions and the reality in Islamic banking and finance is also pointed out to find some reconciliation between aspirations and facts. While its ancient foundations did point to the prospect of Islamic banking to serve as a major contributor to the social and economic development, the industry players of today have now been preoccupied with the profit-making objectives and financial performance rather than social banking. This chapter focuses on the role of Islamic finance as a breakthrough force and shows the way that this influence could shape the discussions of financial systems, so that economics follow, and ethical principles and become factors for the national economy to grow more robustness.

The objective is to develop a more effective model that simplifies and accelerates the news classification process using advanced text mining and deep learning (DL) techniques. A distributed framework utilizing Bidirectional Encoder Representations from Transformers (BERT) was developed to classify news headlines. This approach leverages various text mining and DL techniques on a distributed infrastructure, aiming to offer an alternative to traditional news classification methods.

This study focuses on the classification of distinct types of news by analyzing tweets from various news channels. It addresses the limitations of using benchmark datasets for news classification, which often result in models that are impractical for real-world applications.

The framework’s effectiveness was evaluated on a newly proposed dataset and two additional benchmark datasets from the Kaggle repository, assessing the performance of each text mining and classification method across these datasets. The results of this study demonstrate that the proposed strategy significantly outperforms other approaches in terms of accuracy and execution time. This indicates that the distributed framework, coupled with the use of BERT for text analysis, provides a robust solution for analyzing large volumes of data efficiently. The findings also highlight the value of the newly released corpus for further research in news classification and emotion classification, suggesting its potential to facilitate advancements in these areas.

This research introduces an innovative distributed framework for news classification that addresses the shortcomings of models trained on benchmark datasets. By utilizing cutting-edge techniques and a novel dataset, the study offers significant improvements in accuracy and processing speed. The release of the corpus represents a valuable contribution to the field, enabling further exploration into news and emotion classification. This work sets a new standard for the analysis of news data, offering practical implications for the development of more effective and efficient news classification systems.

This book is essential for anyone in artificial intelligence (AI) and destination management in the tourism industry or government. The book includes both theoretical and practical writings for stakeholders. In all chapters, we provide titles including AI, regenerative and green destinations, sustainable tourism, tourist motivations and expectations, good examples of smart destinations and regions, the regeneration of the tourism industry via AI, rethinking tourism activities and products, current issues in robots, self-service technology, effect of pandemic on smart destinations, sustainable gastronomy and regenerative tourism and tourism issues are discussed in the management plans of the centralisation. This book provides cases and empirical studies that deal in depth with the current situation, challenges, solutions and future strategies after technological development of tourism and increasing interest on smart destinations from a responsible perspective, for readers with an equitable interest or involvement with the organizations in inquiry.

By any count or criterion, Pakistan is a national security state. It always was. The country has fought four wars with India, and it continues to suffer the devastating consequences of confrontation with its formidable neighbor – India; it has been put under siege for more than 40 years by the terrorist and religious extremist groups; it has suffered long spells of military rule; its political structure remains fragile; its civil society organizations are vulnerable, weak, and toothless; and its media, universities, research institutes, and judiciary are under huge stress. Given the state of affairs, the realization is rather slow to grow that human development strengthens national power and national security much more than weapons. It is in this context that a study on food insecurity in Pakistan has been undertaken. It aims to explain as to how a predominantly agricultural country has been reduced into a food resource poor country, and how has the neglect of social, economic, and cultural sectors made Pakistan more insecure. This study covers a number of related issues as well, but it mainly looks for answer to two questions: first, should food insecurity be studied in isolation as a separate issue or as a part of the larger issue of governance, security, and people; and second, isn't there a need to drastically restructure the economic, political, and security landscape and framework to significantly diminish poverty, illiteracy, and food insecurity in the country?

The advent of the digital technologies (DTs), coincided with the pandemic and global conflicts, has proven to be an unprecedented and transformative era for supply chain management (SCM). DTs are reshaping the way organizations plan, execute, and optimize their SC operations. Throughout this book, we posit that the adoption of digital supply chain management (DSCM) has become essential for staying competitive and responsive in a rapidly evolving business environment. However, amid technological advancements and digital solutions, there exists a critical factor that often goes overlooked – the significance of intangible assets, specifically intellectual capital (IC). This chapter comprehensively explores the role of an organization's IC in the adoption and performance of DSCM. We employ a comprehensive analytical approach, drawing upon existing literature from various sources to elucidate the relationship between IC and DSCM. Synthesizing insights from the literature, the chapter shows how each constituent of IC contributes to the adoption, operation, and performance improvement of DSCM. The discussion in the chapter shows that human capital (HC) forms foundations, as the knowledge, skills, and abilities (KSAs) of the employees are prerequisites essential for understanding, adopting, and capitalizing on DTs in SCM. The analysis also reveals that SC, which represents organizational processes, digital tools, and knowledge repositories, supports the seamless integration of DTs within SCs. Similarly, RC, by nurturing trust, open communication, and collaborative networks, plays an instrumental role in establishing ecosystems that help the adoption and effective functioning of DSCM. This chapter makes a convincing case to consider IC as the strategic component while DSCM adoption and performance.

Knowledge is the source of competitive advantage, but when shared at all levels. Unfortunately, there is a universal unruly present in the form of knowledge hiding at employees’ level, but the causes and remedies are still vague as past studies have rarely investigated the causes of daily knowledge hiding behavior. Against this backdrop, this study aims to entail a daily diary method investigation of the role of daily abusive supervision in daily employees’ knowledge hiding through the mediation of dehumanization and moderation of psychological capital.

The data for this study is collected using a daily diary method approach, which estimates the daily workplace events and their continuous influence on employees’ feelings (i.e. dehumanization) and actions (knowledge hiding). The daily responses of 279 respondents were considered useful for analysis purposes.

The findings of the study revealed that the daily events of abusive supervision have both direct and indirect (through dehumanization) influence on employees’ daily knowledge hiding behavior. Moreover, psychosocial capital has a significant conditional influence in the relationships of negative workplace treatments (abusive supervision and dehumanization) and their outcomes (i.e. knowledge hiding).

The study provides some theoretical and practical insights by providing the explanatory and coping mechanism between continuous abusive supervision and daily knowledge hiding behavior.

There is a dearth of literature that has focused on daily episodes of abusive supervision, dehumanization and knowledge hiding behavior. Furthermore, the moderating role of psychological capital has also been rarely investigated.

This paper aims to examine how the diversity of educational levels within bank boards influences the efficiency and stability of banks operating in the Middle East and North Africa (MENA) region. Unlike previous studies, this analysis also investigates the role of board gender diversity in moderating the relationship between board educational level diversity and bank efficiency and financial stability in MENA.

In this study, a sample of 77 banks in the MENA region spanning the years 2011 to 2018 is used. The relationship between the presence of highly educated directors on the board, bank efficiency and stability is assessed using the ordinary least squares method. Additionally, the authors use the Generalized Method of Moments technique to correct endogeneity problem.

This study establishes a positive association between the presence of directors with advanced educational backgrounds on bank boards and bank efficiency and stability. Furthermore, the inclusion of women on the board strengthens this relationship.

These findings have important implications for policymakers and regulators in the MENA region, suggesting that promoting diversity policies that encourage the participation of highly educated directors on bank boards can contribute to enhanced efficiency and financial stability. Policymakers may also consider implementing quotas or guidelines to improve gender diversity in board appointments, thereby fostering bank performance in the region.

This study stands out for its innovation and distinctiveness, as it delves into the connection between board educational level diversity and bank efficiency in the MENA region. Notably, it surpasses previous research by investigating the moderating role of board gender diversity, thus offering valuable insights into the complex interplay between these two facets of board diversity. This contribution enriches the existing literature by providing novel perspectives on board composition dynamics and its influence on bank efficiency and stability.

Extant literature investigating the tax payment behaviour of politically connected firms largely supports the notion that politically connected firms have tax sheltering incentives, i.e. politically connected firms pay significantly less tax. Our paper adds to this stream of literature by considering the tax payment behaviour of two different groups of politically connected firms in Pakistan, viz. civil connected firms and military connected firms.

The paper sheds light on the tax payment behaviour of politically connected firms and provides evidence that the tax incentives of politically connected firms are shaped by the institutional structure and contextual factors.

The results indicate that civil (military) connected firms pay significantly lower (higher) tax than non-connected firms. The findings hold in the face of a number of robustness tests, including the use of alternative proxies for the tax variable and endogeneity concerns.

These results make a significant contribution to the existing literature examining the tax payment behaviour of politically connected firms by providing evidence suggesting that tax sheltering is not the only viable option for politically connected firms; rather, some groups of connected firms have tax under-sheltering incentives. Our findings add to the political cost hypothesis and the signalling hypothesis in relation to tax payment incentives of politically connected firms.