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This study investigates the influence of consumption values on green Fast-Moving Consumer Goods (FMCG) purchase behaviour in the context of green household cleaning products in the Western Province of Sri Lanka.

We used the survey strategy and 326 effective responses as the sample of this study.

Our findings reveal that specific consumption values, specifically functional, conditional and epistemic values, significantly impact green FMCG purchase behavior towards green household cleaning products. However, social and emotional values did not substantially influence this behavior.

The results of our study suggest practical implications for green FMCG marketers aiming to boost consumer adoption of green household cleaning products in Sri Lanka. To achieve this, marketers should focus on enhancing consumer value perceptions and strategically emphasize the consumption values consumers prioritize. Green FMCG marketers have a competitive advantage in the Sri Lankan market by doing so.

This research addresses a notable gap in the literature concerning green FMCG purchase behavior related to green household cleaning products within international and local contexts. Furthermore, this study distinguishes itself by adopting the Theory of Consumption Values as its foundational theory, offering fresh insights compared to previous research employing alternate theories, such as the Theory of Planned Behavior and the Theory of Reasoned Action, to examine similar phenomena.

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.

Purpose: This chapter investigates the moderating impact of personality and demographic factors on the association between work–life balance (WLB) and the well-being (WB) of Ayurveda doctors in Sri Lanka.

Need for the Study: WB is necessary for everyone’s life. Individuals must meet proper WLB between their private and career life scenarios. On the other hand, employee WB and WLB are considered under the sustainable development goals. Hence, it is required to investigate the effect of WLB on WB.

Methodology: This quantitative, cross-sectional study was conducted with minimal researcher interference. The primary data were collected using structured questionnaires from Ayurvedic Doctors in Sri Lanka. The correlation, regression, and hierarchical regression analyses with multivariate assumptions were conducted using SPSS.

Findings: The findings reveal a robust positive association between the WLB and WB, indicating the same association between the WLB and personality. Moreover, there is a strong positive association between personality and WB. The results of the moderator analysis presented that there is a marginal moderator impact from the personality towards the association between WLB and WB.

Practical Implications: Ayurveda Practitioners and policymakers can use the generated knowledge in decision-making. The results of this study can be used as a reference by all industrial practitioners to improve their business practices. They can do this by raising employee WLB to enhance WB, which will help them keep the best employees within the company.

Purpose: This chapter aims to unveil the challenges of adopting and using banking chatbots in India and identify the challenges of Chat Generative Pre-trained Transformer (ChatGPT) for future banking.

Need for the study: Unveiling the challenges of chatbots and ChatGPT in the banking industry in India is crucial to understand the limitations and areas of improvement to enhance customer experience, ensure data security, and maintain regulatory compliance.

Methodology: The researchers conducted a narrative review systematically summarising and analysing existing literature on chatbots and ChatGPT, providing a comprehensive overview of the challenges faced in the industry.

Findings: The authors identify perceived risk, platform quality, connectivity and infrastructure, data privacy and security, user education and acceptance, existing legacy systems, and regulatory guidelines as the challenges of adopting chatbots. Additionally, the findings reveal that the challenges posed by ChatGPT in future banking include the potential reduction of traditional banking jobs, linguistic diversity, data privacy and security, ethical considerations and bias mitigation, explainability and accountability, integration with existing banking systems, and user trust and acceptance. However, implementing these new technologies also presents opportunities for individuals with unique human skills, such as critical thinking, empathy, and creativity, which are difficult to replace with technology.

Practical implications: By minimising the challenges of ChatGPT and chatbots, the banking industry could achieve improved customer service, cost efficiency, automation of routine tasks, and 24/7 availability, leading to enhanced customer satisfaction and operational efficiency in the banking industry. Additionally, these artificial intelligence (AI) tools enable data-driven insights, personalised experiences, scalability, and efficient handling of large customer volumes, contributing to better decision-making and enhanced customer engagement.

This study examines the impact of financial services employees’ engagement on the attitude toward artificial intelligence (AI) in Sri Lanka. The model developed in this study comprises three constructs to demonstrate employee engagement (EE), namely, psychological state engagement (PSE), trait engagement (TE), and cognitive engagement (CE). Further, the model tests the moderating effect of age and gender on the relationship between EE and attitude toward AI. The authors conducted this research through a survey of 200 employees at Sri Lankan financial service firms. The findings indicate that EE substantially impacts attitudes regarding AI. Additionally, PSE, CE, and attribute engagement substantially affect how people feel about AI. Further, age has a moderating effect on the association between EE and attitude toward AI among financial services personnel. Based on the findings and discussion, the researcher recommends AI’s most significant importance in promoting a high level of engagement. The results would be helpful for both academic researchers and practitioners, especially HR managers, to understand the status of AI in Sri Lanka and formulate strategies to expedite EE.

Digital transformation has made enormous changes in the banking domain, where FinTech is the salient driving force inside it. Especially in the banking industry, Artificial Intelligence (AI) and Blockchain technology act as the most innovative technologies. Similarly, Chatbots in commercial banking and Robo-advisors in investment banking has shifted banks into the entire virtual environment. In this context, the main objectives of this chapter are: to determine the current application of AI and blockchain in the banking industry, to identify the challenges faced by banks in adapting AI and blockchain technology, and to provide new insights on future banking in the industry 5.0 in this digital era. This chapter discusses the application of two robotic platforms widely used in banking, chatbots, and Robo-advisors. Chatbots are more like frontline employees of banks who are commonly engaged in customer relationship management, sales, and marketing. In contrast, Robo-advisors are a relatively advanced AI tool involved in investment and portfolio management. Blockchain will accelerate digital transformation where a decentralized digital ledger system is used for banking transactions. However, this is entirely the opposite of conventional centralized digital banking, and the adoption of these technologies is still in its infancy. Employment, performance, security, privacy and trust, cost, ethical and regulatory challenges are the most common challenges. To avoid the challenges, banks should concern with strategies like collaboration with robots, increasing the platforms’ performance, etc. Finally, the chapter provides insights on banking at industry 5.0. In the future, banking customers can experience completely virtual and customer-oriented banking services. In this regard, the fusion of all technologies and collaborative human effort is essential.