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Research on international experience notes its positive influence on subsequent international expansion by firms. We test this relationship in the context of the Indian software industry whose offerings, unlike many other services, are storable implying that delivery can be separated from production.

We analyzed the domestic expansion of a sample of publicly listed Indian software firms over the period 2000–2009 with help of Poisson regression.

We find that even internationally experienced Indian software firms might prefer to expand domestically because of limited financial and managerial resources and concerns about diluting their cost advantage. The storable and separable nature of software services will support this strategy of serving clients remotely. The domestic expansion of assets will, however, be slower for firms with the highest level of industry accreditation. It will also be slower if there are institutional pressures in the form of rivals locating development centers near clients in developed countries.

Our results demonstrate that international experience alone is not sufficient for firms to expand overseas.

This chapter investigates pandemic impact in a variety of industries, including food, travel, education and pharmaceuticals, considering elements such as isolation, emotions and social influences, which can lead to panic buying. The goal of this research is to ascertain how COVID-19 influences the buying decisions of customers. Additionally, the study aims to identify consumer consumption trends for a spectrum of products and services, including fast-moving consumer goods (FMCGs), entertainment, pharmaceuticals, travel and tourism. A comprehensive review of different research papers is done to conclude. The papers considered are from 2020 to 2022. Different keywords are used to search the relevant papers such as ‘pandemic’, ‘COVID-19’, ‘behaviour’, ‘impulsive’, etc. TCCM framework has been applied while reviewing the articles. During the isolation, consumer behaviour moved to panic buying and stockpiling, favouring organic basics, and encouraging e-commerce, as well as economic nationalism favouring made-in-India products. This study helps in knowing the reasons for change in consumers' behaviour for different products and services due to unforeseeable situations like COVID-19 and can find possible ways to deal with them. Business owners learn about changing consumer purchasing behaviours and how to modify products. The government can change policies to improve medical tourism and social protection.

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.

The manner in which publicly traded companies’ management teams handle their firm’s free cash flows (FCF) has been an issue for many decades, because it is difficult to determine whether these management teams work for their own benefit or for that of their shareholders. Recent financial scandals have heightened mistrust of management. This mistrust, in turn, may have increased the pressure to reduce the portion of FCF left under management’s control. Boards of directors control dividend payout decisions, thus determining the portion of FCF available to corporate management. This paper examines whether the 2002 legal response to corporate financial reporting scandals, which came in the form of many new initiatives and requirements imposed by the Sarbanes–Oxley Act of 2002 (SOX) on all publicly traded firms, was relevant to dividend payouts. This question is investigated by noting that the impact of these new requirements differed among firms. Some firms had already introduced the use of independent directors and fully independent committees prior to SOX making them compulsory in 2002. This paper examines whether these “pre-adopters” experienced less change in their dividend payout policies than those firms that were forced to change the composition of their board and committees.

This investigation examines the effect on dividend payouts for listed firms attributable to the SOX and concurrent changes in stock exchange regulations that compelled increased use of independent directors and fully independent committees. To study the impact of SOX and the associated, required, changes in the composition of boards of directors for many firms, the difference-in-differences methodology is employed to overcome the endogeneity concerns that have consistently challenged prior governance studies. This was accomplished by examining the effects on dividend payouts associated with the exogenously forced addition of independent directors to the boards of publicly listed firms. The results reveal that there is a significant positive relationship between firms that were compelled by law to change their boards and increases in average changes in dividend payouts and percentage changes in dividends paid, when compared to firms that had pre-adopted the Sarbanes–Oxley corporate board composition requirements. A further exploratory analysis showed that the same significant positive relationship is detected for increases in average changes in total dollars distributed, where stock repurchase dollars are combined with dividend payouts. These findings imply that these board composition changes led to decisions that increased dividend payouts in percentage terms, as well as dividend payouts and total dollars distributed in aggregate dollar amount terms.

Introduction: Many organisations nowadays use artificial intelligence (AI) in human resource (HR) activities like talent acquisition, onboarding of new employees, learning and development, succession planning, retention of employees, and automation of administrative tasks. When AI is integrated with HR practices, it helps HR personnel to focus more on the strategic aspects of the HR function and relieve them from routine HR activities.

Purpose: The readiness of employees to accept any change depends on organisational facilitation to change, employee willingness to accept the change, the requirement for change, situational factors, etc. This research studies the factors influencing employees’ change readiness towards acceptance of AI in HR practices. The researchers also strive to develop a conceptual technology adoption model for AI in HR practices by studying the earlier models. Finally, the research explores the acceptance of AI by various service sector employees and identifies whether there is any difference in their acceptance of AI based on demographic variables.

Methodology: A conceptual framework was derived using a combination of previous models, including the Technology Readiness Index (TRI), Change Readiness Scale, Technology Acceptance Model (TAM), Technology, Organization, and Environment (TOE) model, and change readiness scale. A structured questionnaire was designed and distributed to 228 respondents from the service sector based on the conceptual framework. An exploratory factor analysis (EFA) was used to determine the elements that influence employees’ level of change readiness.

Findings: The exploratory results on data collected from 228 respondents show that the model can be used for further research if a confirmatory factor analysis and validity and reliability test are performed. Employees are aware of AI and how it is used in HR practices, based on the study results. Moreover, while most respondents favour using AI in their company’s HR practices, they are wary of some aspects of AI.

Introduction: Artificial intelligence (AI) assists recruiters in effectively and efficiently nominating applicants precisely and accurately. It helps in the screening of resumes without biasness. This chapter will identify different AI technology and various organisations using it fully or partially.

Purpose: This chapter aims to get insights about various AI tools that assist human recruiters, save time and cost, and provide modern experiences. It will help identify various applications that are currently in use and their features. It also helps in finding out the benefits and the challenges faced by the recruiters and the applicants while assimilating those applications in hiring.

Need for the Study: The study will be helpful to all those recruiting firms who are presently using AI or not using it to understand the benefits and challenges they might face.

Methodology: The chapter will be based on reviews and industry reports. This chapter will include a study related to human resource (HR) functions where AI is used. To give more insights into AI technology, this study mentions various applications like Mya, Brazen, etc., and their usefulness in recruitment. Also, special emphasis would be given to the recruitment functions as most companies use AI. Some companies like Deloitte and Oracle are using AI fully or partially will also be incorporated.

Findings: The study finds out that although many companies have started to use AI tools for recruitment, they have not explored all the algorithms that can be used to complete the whole recruitment and selection process. Companies like Loreal use AI for candidate applications and recruiter screening, but human recruiters stand strong for assessments and interviews. AI’s widespread use presents human resource management (HRM) practitioners with both opportunities and challenges.

Practical implications: The basic idea of the study is to scrutinise the related literature and find out the features, advantages and limitations/challenges of using AI which would be helpful for recruiters in better understanding of the technology-driven recruitment.