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The author develops a bilateral Nash bargaining model under value uncertainty and private/asymmetric information, combining ideas from axiomatic and strategic bargaining theory. The solution to the model leads organically to a two-tier stochastic frontier (2TSF) setup with intra-error dependence. The author presents two different statistical specifications to estimate the model, one that accounts for regressor endogeneity using copulas, the other able to identify separately the bargaining power from the private information effects at the individual level. An empirical application using a matched employer–employee data set (MEEDS) from Zambia and a second using another one from Ghana showcase the applied potential of the approach.

Purpose: This chapter discusses the role and use of chatbots adopted by the different categories of banks (private and public sector banks) in India. The chapter presents brief essential services offered by Indian chatbots regarding accuracy, technology providers and virtual assistance, ways to connect, etc. This chapter concluded that most of the questions answered by the Indian chatbots are already available on the banks’ websites, and there is a need for enhancement in the capabilities of Indian chatbots.

Need for the Study: The need for the study is based on the working of banking chatbots, customer query handling, and the efficiency of the chatbots in India. The chapter helps to analyze the services offered by various banks.

Methodology: This chapter is based on secondary data collected from banks’ websites and articles from various journals. The study is based on nine banks (both private and public sectors) those are having working chatbots (SBI, HDFC Bank, ICICI Bank, Yes Bank, IndusInd Bank, Kotak Mahindra Bank, Axis Bank, Andhra Bank, Bank of Baroda). The present study is focused on chatbots, their services, and software applications for various customer-handling capacities.

Findings: The research concluded that Indian banks are investing a small amount in using chatbots, yet Indian chatbots are deficient regarding far too provincial administrations as they are adequate just for standard and basic inquiries. Also, Indian customers are not properly aware of chatbots and virtual assistance.

Practical Implications: This study provides an overview of the working chatbots in India (for both public and private sector banks) and their functions, as well as the capacities of these chatbots. The previous conducted studies are based on the uses, importance, and working of chatbots/artificial intelligence (AI) in banking. In this study, after discussing the different services, it is found that Indian banks need to update their AI/Virtual assistance with more features.

This research sought to examine the differential effect of chatbot banking artificial intelligence (AI) on consumer experience in the banking industry. A positivist paradigm was adopted to sample 389 consumers who were previously exposed to chatbot banking in Zimbabwe. A causal research design was employed whilst a quantitative approach was followed. In analysing data, the research study applied the structural equation modelling (SEM) technique. The authors found that chatbot banking significantly improves customer experience (CX) in the banking industry. Reliability and responsiveness of the chatbot need to be enhanced for effective improvements in CX. A need was also identified to enhance CX through the development of an ease-to-use chatbot which is embedded in everyday messaging applications of consumers. A significant association was also found between perceived benefits of chatbot banking and CX. This study informs the development of competitive advantage by banks and other related companies through AI-based CX management strategies. In times of pandemics and beyond, chatbot banking can be very instrumental in improving CX.

Lean manufacturing, a philosophy that revolutionized the manufacturing industry, is often linked to the Toyota Production System (TPS). At the core of a lean company, one can observe proper implementation of lean manufacturing tools and practices such as just-in-time, work teams, cellular manufacturing, lean layout, etc. The goal of lean production is to minimize the waste producing activities while offering the same or enhanced quality to customers.

The aim of this research is to investigate the implementation degree of lean manufacturing and its tools and practices focusing on the case of an SME in Albania as a concrete example. Higher attention is given to some of the pillars of lean manufacturing such as just-in-time and cellular manufacturing.

In this case study, researchers observed a variety of features of lean production. Just-in-time was implemented to a certain extent and cellular manufacturing at a more surprising level, which was facilitated especially by the U-shaped facility layout designs observed during the site visits. The value stream mapping showed a proper group technology in place and the management displayed signs of engagement and future advancement desire regarding this philosophy.

Purpose: This chapter investigates the current skill gap in small-scale industries, the need for skill development and digital training in micro, small, and medium enterprises (MSME), and reviews policies for skill development and solutions.

Need for the Study: While the legislature and organisations have initiated various considerations for the successful implementation of the Skill Development System in the country’s MSMEs, there are significant challenges that must be addressed quickly to fill the skill gap in workers in this digital era.

Research Methodology: Secondary data has been used for the chapter review. Analysis has been done based on review data from women handloom and handicraft workers in the micro or craft industry who received a Star rating from the National Skill Development Corporation (NSDC) partners in Lucknow. For data collection, a questionnaire based on random sampling was used. The data were analysed using a rudimentary weighted average and a percentage technique.

Findings: The studies provide answers to some fundamental problems: are small industry employees indeed mobilised to be skilled outside the official schooling system? Is the training delivery mechanism adequate to prepare pupils for employment? Would industries be willing to reduce minimum qualification criteria to foster skill development?

Practical Implication: Non-technical aptitudes digital and soft skills for workers in this sector should be emphasised in MSMEs, and significant reforms in MSME sectors and capacity-building education and training programmes should be implemented in the Indian industry to generate small and medium enterprises production and employment.

The existing literature documents mixed evidence toward the association between corporate social responsibility (CSR) and corporate tax planning (e.g., Davis, Guenther, Krull, & Williams, 2016; Hoi, Wu, & Zhang, 2013). In this study, I aim to identify a causal relationship between CSR and tax planning, leveraging the staggered adoptions of constituency statutes in US states, which is a plausibly exogenous shock to firms' emphasis on their social responsibility. In general, the statutes permit firm directors to consider the interests of all constituents when making business decisions, including those who benefit from firms paying their fair share of income taxes. Thus, the adoption of the statutes raises the importance of firms' social responsibility in paying income taxes. Employing a staggered difference-in-differences (DiD) method, I find that firms incorporated in states that have adopted constituency statutes exhibit significantly higher effective tax rates (ETRs) based on current tax expense. This causal relationship suggests that managers, with the legitimacy to consider the social impact of tax avoidance, become less aggressive in tax planning. I further find that the effect of adoption is stronger for financially unconstrained firms and firms in retail businesses, where the demand (cost) for tax avoidance is lower (higher). Finally, I show that my main results are driven by firms located in states with a high sense of social responsibility and firms with high levels of tax avoidance prior to the adoption. Overall, the findings in this chapter contribute to the literature by delineating a negative causal relationship between CSR and tax avoidance and identifying a positive social impact brought by the passage of constituency legislation.

Corporate Social Responsibility (CSR) has been in practice in India even before it was mandated by the Companies Act, 2013. While the objectives of CSR varied from philanthropy, being socially responsible to improving the corporate image, the relationship between financial performance and CSR has not been established. Also only a few companies are aligning their CSR activities with their corporate goals. This chapter builds a framework for integrating business with its CSR activities. The first part of the chapter describes how the concept of CSR evolved over years in general and specifically in India. It also discusses the current status of CSR in India. The second part of the chapter uses a well-known CSR model of e-Choupal to build a framework to integrate CSR with business.

Purpose: In this technologically advanced era, it is crucial to understand how consumers adopt innovations so that producers and marketers can cater to these needs effectively. While existing technology adoption models have good explanatory power, a hybrid model must account for newer contexts.

Need for the Study: Most technology adoption papers in extant literature deal with the phenomenon’s functional, environmental and cognitive aspects. However, a mindset-oriented approach is largely absent from current studies. Mindsets are core beliefs people have about the malleability of human traits and characteristics that ultimately shape consumer behaviour. Investigating the adoption of such technologies through a deeper psychological lens will advance the field substantially.

Methodology: This conceptual paper utilised a literature review and theoretical integration to present a novel technology adoption model. The literature review of secondary data helped identify extant gaps, while academic integration of major concepts helped fill said gaps.

Findings: Based on the existing gaps in the literature, this study conceptualised a novel technology adoption model based on the foundation of Mindset Theory. Overall, relevant constructs, variables and scales have been presented along with future research propositions.

Practical Implications: From a global perspective, the findings of this chapter will enable marketers and practitioners to understand consumer adoption of new-age technologies. Producers of such technologies will also be able to cater to consumers more efficiently as a result of this study.

This chapter aims to highlight the existing applications and future prospects of Artificial Intelligence (AI) in the tourist business. In addition, this chapter investigates the obstacles in using AI in the Indian tourist industry.

To achieve the study's aims, both primary and secondary data are used. Using secondary sources, desk research was conducted to investigate the existing uses and future prospects of AI application in the global tourism industry. In addition, qualitative interviews with 25 executives in the Indian tourist business were undertaken to study the obstacles to using AI in the Indian tourism industry.

The research found that the applications of AI in the worldwide tourist business are extensive. Nonetheless, corporations are actively using AI-based technology to improve the customer experience via chatbots, intelligent forecasting and smart, tailored travel experiences. The qualitative interviews found that the implementation of AI technology in the Indian tourist industry is hindered by budgetary restrictions, knowledge constraints and barriers relating to human resources.

The use of AI in the tourism business may significantly improve the client experience. As a consequence, the use of AI-based chatbots and intelligent travel aides is growing exponentially. The research examined the many uses of AI in the worldwide tourist industry as well as the obstacles associated with the deployment of AI in the Indian tourism industry.