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The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

The main objective of this study is to identify the main determinants of the Islamic banks’ performance in Gulf Cooperation Council (GCC) regions.

The research uses both static model (fixed effects and random effects) and Generalized method of Moments (GMM). The data for this study are obtained from the annual reports of 29 Islamic banks from GCC countries using Bankscope database for the period from 2005 to 2013.

The empirical findings reveal that Islamic banks’ specific factors such as the equity financing and bank size are positive and statistically significant to the profitability of Islamic banks. The operating efficiency ratio is negatively and statistically significant to return on asset. It is also found that macroeconomic variables such as money supply and inflation are negatively and statistically significant to the performance of Islamic banks whereas oil price has been found positive and statistically significant to the performance of Islamic banks in the GCC region.

The present study seeks to fill a demanding gap in the literature by providing new empirical evidence on the factors that influence the profitability of the Islamic banking sector in GCC regions.

These findings have significant contribution to the literature by comprehensively clarifying and critically analyzing the current state of profitability among the Islamic banks in GCC regions.

This research attempts to understand how individuals prevent themselves from exposure to COVID-19 when dining out at a restaurant and what situational factors shaping their COVID-19 preventive behavior (CPB) are. It collects 303 questionnaires responded by restaurant patrons in the United Arab Emirates. The resultant data reveals the ranks of the relative importance among the five CPBs proposed by this study that wearing a mask is considered the most critical CPB. In contrast, wearing gloves is the least desirable CPB. Concerning five health-risk factors under investigation, there is no difference in CPB between the vaccinated and non-vaccinated. People suffering from issues with their immune system show a significant inclination to stress social distancing compared to those without any immune issues. Those having an inflected family member are apt to wear gloves. Further, individuals bearing risk factors concerning chronic illness, an immune problem, and an infected family member are inclined to wash their hands and wear gloves. Lastly, this research finds six situational factors affecting an individual's CPB.

This chapter reports a study that investigates the link between rural small firms’ social networks and their market diversification strategies in the context of the Internet.

Telephone interviews were conducted with a random sample of 142 Scottish small rural and urban firm owners in May 2012. The purpose of the telephone interviews was to understand how Internet usage impacted on the social networks and market diversification experiences of small rural firms. Analysis of the categorical data was performed using a variety of established methods.

Internet usage for many small Scottish rural firms was facilitating both their market reach and social networks. In addition, small rural firms’ most important social network contacts are highly correlated to their origin of sales, and this can be either locally or extra-locally based.

A positive relationship between Internet usage, social networks and market reach expansion offers support for further developing and improving the Internet infrastructure of rural communities.

Internet usage emerges as a critical tool for augmenting the social networks of Scottish rural small firms, which in turn helps to extend their market reach activities.

Introduction: Artificial intelligence (AI) is being extensively used to solve complex problems in the industry. AI provides several benefits such as providing visibility in the processes, reducing time, improving accuracy, saving time, helping in the decision-making process, etc. Due to the range of benefits of AI technologies, organisations readily adopt this technology. However, there are several challenges that the organisation faces during the implementation of AI. These challenges are in context to human resource (HR) development for successful implementation of AI across different functions and are discussed in this chapter.

Purpose: Although we know that AI technology is widely accepted in human resource management (HRM) due to its various benefits. But the organisations face many challenges during the implementation of AI. The focus of the study is to explore the literature on AI in HRM, identify the challenges of implementing AI and provide potential future research direction based on a systematic literature review.

Methodology: To explore the literature on AI in HRM, the study undertakes a systematic literature review. The study identifies, analyse and classifies the literature to provide a holistic view of HR challenges in implementing AI. The study is built on a review of 47 documents, including the articles, book chapters and conference papers using the Scopus database for the past 10 years (2012–27 January 2022).

Findings: The study provides an overview of the documents published in Scopus in this area through a systematic literature review. The study reveals that a significant amount of growth in the publication has been shown in the past 10 years. The maximum and continuous growth is shown after 2017. The maximum number of papers are published in India, the USA and China. The study identifies major eight challenges of AI implementation in HRM. The study also provides a secondary case to deep dive in this area based on a systematic literature review.

Research Limitation/Implication: The challenges identified in the study are not empirically tested. Each of the identified challenges should be empirically examined. This study has expanded the body of knowledge of AI in HRM. This study will help the academicians and practitioners work on the identified challenges and help the organisations ease in adopting AI.

Originality/Value: This study represents the first work that integrates AI implementation challenges in HRM.

This chapter measures total factor productivity growth (TFPG) using Malmquist productivity index (MPI) and the growth of MPI of Indian Textile Industry employing nonparametric data envelopment analysis (DEA), during 1995–2016, exploring company (firm) level Center for Monitoring of Indian Economy (CMIE) Prowess data; examines whether TFPG has improved after the withdrawal of multifiber trade agreement (MFA) since 2005; decomposes TFPG into technical change (TC), technical efficiency change (TEC), and scale efficiency change (SEC); and explains the factors behind the movement of TFPG, considering the effect of R&D (RD), exports (EX), marketing expenditures (MKTs) advertisement expenditures (ADVs), imports (IMP), using second-stage panel regression. Empirical evidence supports fluctuating pattern of TFPG during 1995–2016, with a marginal declining tendency. TFPG has increased in 1999–2000, 2000–01, 2009–10, and 2012–13. After dismantling MFA, MPI level has significantly declined, with an increase in its growth rate, but the increase is not statistically significant. The effect of EX, RD, ADV are nonlinear, U-shaped, and IMP and MKT are inverted U-shaped, implying that the sign effect of any variable depends on its size. There are joint interaction effects of (a) RD and EX; RD and MKT which are positive, (b) ADV and MKT as represented by the ratio (ADV/MKT), having nonlinear inverted U-shaped relation. The joint interaction effect supports that the impact of one variable depends on the magnitude of other. The marginal effect of EX, IMP, and ADV are positive; increase in these variables promotes TFPG. The greater role of ADV over MKT is evident. The marginal effect of RD is negative; the average level of RD is too low to generate positive effects, and, thus, there is an urgency of increasing RD. The promising part of the decomposition analysis is that highest contribution to growth rate of TFPG is the growth rate of TEC followed by growth rate of TC, and thus by increasing TEC and TC, higher growth rate of TFPG is achieved and may be beneficial in the long run and may lead to absorption of economic shocks for an economy facing recession in its output growth. Some policy suggestions are made for boosting up TFPG.

This chapter attempts to explore customer loyalty and retention in the context of Pakistani restaurants. Effects of customer perceived value and service quality as antecedents are tested on customer loyalty and retention along with the mediating effects of customer satisfaction and customer relationship management quality. This chapter is conducted in 15 restaurants from Multan. Results reveal how the restaurant sector lacks a monitoring mechanism that promotes an effective customer relationship. For example, what kinds of measurements the manager could use to enhance a customer's loyalty and retention.

The current era is characterized by hyperturbulence, population growth, attention to food security, the need to identify sustainable strategies to reduce pollution and poverty, and the disparity between developed and undeveloped economies. These circumstances force a global paradigm shift based on sustainable practices and processes that put people and the environment at the core of each activity, contributing to sustainable, social, and economic development and promoting well-being in the community.

In this spirit, a strong impulse can derive from the practices of Green Technology, considered here as that set of processes aimed at eco-sustainability that acquire undisputed relevance, especially for emerging economies.

This chapter focuses on the role that Green technology practices exert in generating local well-being in the world's fifth-largest country: Brazil. Dynamic growth and effective social policies lifted millions of people out of poverty in the 2000s, even if socio-economic development varies widely across the country. Brazil is a leading global agricultural, minerals, and oil producer. The natural environment represents the primary source of Brazil's development that deserves to be protected and push firms and citizens to find new sustainable solutions based on green policies. Drawing inspiration from a Brazilian case study, this chapter proposes a set of building blocks that foster sustainable business practices in emerging countries.

The chapter is organized as follows: the first part introduces the concept of green technology practices; the second highlights the opportunities of green technologies; the third focuses on a single case study.