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The purpose of this paper is to explore the relationship between high-performance HR practices (HPHRPs), psychological climate (PC), work engagement (WE) and organizational citizenship behaviors (OCBs) among IT professionals. This study further intends to provide a framework to understand and predict factors affecting organizational citizenship performance in the Indian IT sector.

The analysis is based on a sample of 464 IT employees working in 29 information-intensive global organizations, and the statistical method employed is structural equation modeling.

The results of the present study demonstrated the significance of employees’ perceptions of PC through which HPHRPs can boost employees’ WE, which, in turn, has come out to be the principal mechanism through which HPHRPs and PC have impact on OCBs.

The results have established a platform where HR managers can be motivated to open up new avenues to employees where they can be psychologically involved in work roles and feel highly motivated to bring their good spirits at the workplace in order to benefit the organization at large.

This research explores the changing dynamics of Indian business scenario in the IT context. IT professionals may perceive and react differently to the HR system in the organization and have higher expectations of congenial working conditions that enhance their capability to employ personal skills and resources in the realization of organizational goals. Thus, the study tries to tap their experiences and perceptions and map their performances in the organization.

The authors have attempted to understand how big data and predictive analytics (BDPA) can help retain employees in the organization.

This study is grounded in the positivism philosophy. The authors have used a resource-based view (RBV) to develop their research hypotheses. The authors tested their research hypotheses using primary data gathered using a single-informant questionnaire. The authors obtained 254 usable responses. The authors performed the assumptions test, performed confirmatory factor analysis (CFA) to test the validity of the proposed theoretical model, and further tested their research hypotheses using hierarchical regression analysis.

The statistical result suggests that the various human resource management strategies play a significant role in improving retention under the mediating effect of the BDPA.

The authors have grounded their study in the positivism philosophy. Moreover, the authors tested their hypotheses using single-informant cross-sectional data. Hence, the authors cannot ignore the effects of the common method bias on their research findings. Moreover, the research findings are based on a particular setting. Thus, the authors caution the readers that their findings must be examined in the light of their study limitations.

The study provided empirical findings based on survey data. Hence, the authors provide numerous guidelines to the practitioners that how the organization can invest in creating BDPA that helps analyze complex data to extract meaningful and relevant information. This information related to employee turnaround may guide top management to reduce the dissatisfaction level among the employees working in high-stress environments resulting from a high degree of uncertainty.

The study helps understand the complex factors that affect the morale of the employee. In the high-paced environment, the employees are often exposed to various negative forces that affect their morale which further affect their productivity. Due to lack of awareness and adequate information, most of the employees and their issues are not dealt with effectively and efficiently by their line managers. Thus, the BDPA can help tackle the most complex problem of society in a significant way.

This study offers some useful contributions to the literature which attempts to unfold the complex nexus between human resource management, information management and strategy. The study contributes to the BDPA literature and how it helps in the retention of employees is one of the areas which still remains elusive to the academic community. Moreover, the managers are still skeptical about the application of BDPA in understanding human-related issues due to a lack of understanding of how and to what extent the employee-related information can be stored and processed. This study’s findings further open the new avenues of research that need to be tackled.

This study aims to focus on understanding the work–family conflict of Indian women engineers through the lens of identity conflict.

Semi-structured interviews conducted with 20 Indian women engineers working in India and abroad of varying ages and work experience helped in understanding the types, sources and coping decisions about work–family conflicts experienced by them. Thematic analysis was conducted to analyse the qualitative data.

The findings reveal that as women engineers negotiate their “engineering” and “woman” identities, work–family conflict manifests as a battle of time and responsibilities, psychological strain and behaviour-based conflict. Furthermore, self-expectations and negative social sanctions play an important role in augmenting the experiences of these conflicts. The results also reveal how women re-strategize their career decisions to conciliate their conflicting identities.

This study furthers the literature on resolving work–family conflict by taking an identity perspective. Recommendations in literature such as work flexibility and part-time work, place the onus on women to increase their capacities to perform different roles better. Examining work–family conflict from an identity perspective allows us to look at the psychological processes underlying the challenges women face in balancing work and home in a male-dominated profession. These give insights into the need to go beyond accommodations in the workplace to redefine gender roles and relations for equal participation of women in the modern workforce.

This study investigates the antecedents of women entrepreneurs’ performance in an emerging economy. Based on the review of extant literature, six antecedents of women entrepreneurs’ performance, namely, motivation, networking, socio-cultural, business environment, training and development, and financials were proposed and subsequently empirically examined.

Gaps in the literature were identified, based on which the theoretical background of the study was formulated. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were applied to confirm the factor-item structure. The impact of explanatory variables was investigated using the structural equation modeling (SEM) based path analysis.

The study concludes that motivation, networking, socio-cultural, business environment, training and development, and financials have a significant positive influence on the performance of the women entrepreneurs.

There is a dearth of quality research that holistically investigates the key antecedents of performance among women entrepreneurs. Most existing studies have not considered the possible antecedents of performance concomitantly. Additionally, the relationships have been measured individually rather than at the construct level. Further, a majority of the existing studies investigating the performance of women entrepreneurs have been confined to settings within developed countries. By providing insight into the antecedents of women entrepreneurs’ performance elsewhere, the present study attempts to bridge these identified gaps. This study is expected to advance the knowledge about the factors influencing the performance of women entrepreneurs in emerging economies such as India. These insights will likely be valuable when creating policies related to this crucial aspect of economic development.

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.

The purpose of the chapter was to examine the impact of customer care chatbots on customer satisfaction levels in the mobile telephony industry in Zimbabwe, with a special focus on the company Econet Wireless. This chapter shows the conceptual framework used. An online questionnaire was administered to a sample of 100 Econet Wireless subscribers who were selected using probability stratified random sampling from Zimbabwe’s 10 provinces. The research data were collected and analysed for correlation, and a multiple regression analysis was carried out to identify the relationship between customer satisfaction and the three customer service improvements brought in by the introduction of customer service chatbots. The study discovered that there is a positive relationship between customer satisfaction levels and each of the three customer service improvements brought in by customer service chatbots, namely customer service convenience, speed of response, and omnichannel strategies. This study thereby proves that the introduction of customer service chatbots in the mobile telephony industry in Zimbabwe can lead to an improvement in customer satisfaction levels. However, addressing service quality only as a determinant of customer satisfaction in isolation is not sufficient to fully improve customer satisfaction levels. Therefore, organisations that seek to improve their customer satisfaction should consider strategies that address all determinants of customer satisfaction, namely price, product quality, service quality, situational factors, and personal factors. This study contributes to the body of knowledge, particularly regarding the use of artificial intelligence (AI) for customer service in developing economies.

The purpose of this study is to look at the factors that drive people to participate in the sharing economy (SE). Based on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), the study proposes a mathematical model. The study’s ultimate objective is to help businesses attract more involved customers and promote collaborative consumption as a sustainable alternative to typical consumption patterns. The study offers a conceptual framework established via a thorough literature review to examine Indian customers’ use behavior toward SE platforms. A one-sample two-tailed t-test is used to assess the framework’s efficacy. The research fills gap in the literature on the SE by investigating the factors that determine subjective norms (SN), attitudes (A), and perceived behavioral control (PBC). A framework is provided that takes behavioral intention (BI) contemplated as a mediating variable. The research improves TAM and TPB by including new factors such as technical characteristics. This research adds to the body of knowledge on the digital SE by underlining the relevance of usage behavior in comprehending Indian customers, where A, SN, and PBC are important aspects. The research presents a paradigm for better understanding customers’ attitudes and behaviors toward various SE platforms, which might help academics, practitioners, and policy makers situate their initiatives within the larger field of sharing. The study’s categorizations of Indian consumers’ A, SN, PBC, and BI toward the SE might potentially advise on future research and government policies.

Escalation in the number of online food ordering platforms, along with extensive junk food marketing, lucrative offers and discounts, innovation in food flavors, and doorstep delivery of food, have triggered the consumption of high-calorie and unhealthy food products which pose serious threats to the health and future well-being of individuals by making them more obese. To date, several public policy frameworks have been developed to confront obesity; however, their efficacy seems debatable. Directionally, the objective of this study is to highlight the potential influence of “digital nudging” which aims at steering individuals in desired directions, at the same time delimiting their freedom of choice. The study also establishes the effectiveness of digital nudges promoting a healthy lifestyle by steering individuals toward healthier food choices. The author strongly believes that this conceptual perusal will offer immense inputs to healthy food marketers and researchers alike in addressing the matters of obesity. Addressing the menace of obesity calls for joint efforts of the government, the public, researchers, and more specifically food product manufacturers/marketers who should incorporate healthier food options into their portfolios. E-tailers are also urged to adopt such practices in virtual markets and promote healthier food options to effectively tackle obesity.

Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.

This study investigates the motivation among customers to be more loyal to online food delivery applications (OFDA) services even after the COVID-19 epidemic by using perceived service quality aspects in Sri Lanka. The data were gathered by physically distributing a self-administrated questionnaire to clients in Sri Lanka who continue to use OFDA services on platform to customer (P2C) service delivery platforms to buy food despite the COVID-19 outbreak. Multiple regression is employed to analyse 287 effective observations, and the data revealed the significant positive effect of interaction, environment, outcome, and food qualities on customer loyalty to OFDA services. In fact, there is no impact from the delivery quality on customer loyalty to OFDA services due to outsourced food delivery. The findings suggest regular improvements in attributes such as interaction, environment, outcome, and food qualities in this hyper-competitive business environment. Further, this study sets substantial facts for the interested parties to establish an exemplary delivery system and other technological advancements to have a sustainable competitive advantage and solid customer base in the long run.