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This research focuses on developing and testing a conceptual model that explores customer behavioural responses (engagement, experience and recommendation) towards generative artificial intelligence (AI)-enabled chatbots. It highlights the significant influence of anthropomorphic characteristics in enhancing perceptions of competence and warmth, further enhancing perceived authenticity. In addition, this study aims to investigate how the need for social interactions moderates these relationships.

This study used a self-administered questionnaire distributed on Prolific Academic to gather data from 282 eligible participants worldwide. This study uses a structural equation modelling approach to answer the research questions.

The findings reveal that anthropomorphic characteristics of generative AI-enabled chatbots are positively associated with perceived competence. Moreover, the findings show that the perceived competence and warmth of generative AI-enabled chatbots are significantly associated with perceived authenticity. Furthermore, the results highlight that the perceived authenticity of generative AI-enabled chatbots is positively associated with customer engagement, experience and recommendation. Finally, the results illustrate that the impact of anthropomorphic characteristics on perceived warmth is significantly moderated by the need for social interaction.

This study enriches the generative AI literature and guides organizations in understanding consumer interactions for leveraging generative AI-enabled chatbots. Furthermore, this study contributes to the social response theory literature as this study investigates how user behavioural intentions towards generative AI-enabled chatbots are influenced by their perceived level of anthropomorphic characteristics.

Heritage is a crucial aspect of national identity, and preserving it is essential for safeguarding cultural and historical continuity. In India, there are numerous policies and laws aimed at the preservation and management of cultural and natural heritage. This study aims to review the existing policies and programs for the preservation of cultural heritage in India, focusing specifically on an ancient Jain temple located in Subaiee village, Koraput District, Odisha. It also seeks to document the temple’s condition, history and religious significance and to evaluate local awareness of the heritage through public archaeology methodology.

The research involved a detailed review of preservation policies and programs at both state and central levels in India. It included documentation of the Jain Temple’s current condition, historical background and its role in the region’s religious history. Additionally, a public archaeology approach was used to assess local awareness and engagement with the temple’s heritage.

The study found that the Jain Temple complex has significant historical and architectural value. The current condition of the temple and its relics indicates a need for effective management strategies to prevent further damage and increase local awareness of the temple’s heritage value.

The research highlights the importance of preserving the ancient Jain Temple complex and calls for national and local efforts to identify, restore and maintain this valuable cultural heritage for future generations.

This research aimed to identify the optimal plasma cutting parameters for enhancing the quality and efficiency of steel alloy processing. Systematic experiments, supported by microstructure analyses and the Taguchi method, were conducted to determine the ideal settings for minimizing defects and resource consumption while ensuring high-quality cuts.

The study employed a systematic approach to determine optimal plasma cutting parameters for enhancing steel alloy processing. Experiments were conducted using a Kawasaki RS-010L robotic manipulator, powered by a DS 120P.33 inverter power supply. A range of plasma cutting parameters, including current, voltage, cutting speed and airflow, were carefully examined to achieve high-quality cuts while minimizing resource consumption. The Taguchi method was applied to optimize key responses – cutting angle, cutting width and burr formation – providing deeper insights into the influence of each parameter and identifying conditions for further refinement.

The study successfully identified the optimal plasma cutting parameters for steel alloy processing. Practical experimentation determined that a current of 50 A, voltage of 118 V, cutting speed of 3,200 mm/min and airflow of 1.9 × 10^–3 m³/s produced a smooth cutting surface, minimal burr formation and a cutting angle within ±4° relative to the surface. The Taguchi method determined optimal settings to minimize angle and cutting width: 126 V, 4,400 mm/min and airflow of 2.3 × 10^–3m³/s for angle and 118 V, 4,400 mm/min and 1.9 × 10^–3m³/s for cutting width. Microstructure analysis confirmed uniformity and conformed to International Organization for Standardization 9013:2002 standards for cut quality.

This research advances steel alloy processing by combining experimental methods and the Taguchi method to determine optimal plasma cutting parameters for 6 mm thick steel 09G2S, addressing a gap in studies focused on specific materials. Unlike general studies, these results are tailored to low-carbon, low-alloy steels, providing actionable guidance for achieving efficient, high-quality cuts while minimizing waste and improving weldability and ductility. This work contributes to cost-effective and sustainable practices in the metal fabrication industry.

The purpose of this study is to analyse the impact of corporate attributes like a company’s profitability, size, age, leverage and board size on companies’ sustainability reporting as measured through India’s new business responsibility and sustainability reporting (BRSR) framework.

A random sample of 130 companies was taken from the top 1,000 listed companies on the National Stock Exchange. Sequential mixed methods research approach was used to prepare a sustainability quality index. Then, a hierarchical multiple regression analysis was performed to examine the impact on the quality of reporting by Indian companies.

Interestingly, the analysis revealed that traditional metrics like age, profitability, board size and leverage did not have significant associations with reporting quality. Rather, the size of a company in terms of market capitalisation was found to have a strong positive impact on sustainability reporting.

This was a cross-sectional study, as time series data for BRSR reporting is not yet available. Also, only five parameters were taken for analysis. Lastly, subjective judgment in content analysis may be involved.

This suggests that only larger companies in India are prioritising sustainability reporting over smaller ones. It affirms the legitimacy and stakeholder theory in the Indian context.

To the best of the authors’ knowledge, this study is one of the first endeavours to assess the efficacy of the new Indian BRSR framework and test its primary objectives. Furthermore, significant implications have been given for managers to catalyse and reinforce the sustainability momentum down the lane across companies of all sizes in India.

In a rapidly evolving recruitment landscape, virtual reality (VR) emerges as a transformative tool for human resource management (HRM). This chapter delves into the profound impact VR can have on attracting, assessing and onboarding talent. Furthermore, VR services have been already included in other areas where it has been shown its essence to be useful for those industries.

The current study explores how VR simulations can provide immersive experiences, allowing candidates to virtually step into the workplace and interact with potential colleagues and tasks. This fosters a deeper understanding of the role and company culture, leading to better-matched hires and improved candidate experience.

This chapter also examines the potential of VR for skills assessments, offering a more realistic and engaging evaluation process compared to traditional methods.

Finally, this study discusses the challenges and considerations for integrating VR into HRM practices, ensuring a successful implementation of this innovative technology in the realm of recruitment.

Purpose: This study investigates the influence of inflation and oil price fluctuations on stock prices and returns. A thorough bibliometric analysis of research articles published in the last 22 years has been conducted to achieve this objective.

Need for the Study: Inflation and oil prices are critical macroeconomic variables that significantly impact the economy, including the stock market. It is crucial for investors and policymakers to understand the complex relationship between these economic variables and the stock market.

Methodology: The study employed a bibliometric analysis to identify the most influential authors, institutions, and research themes related to the impact of inflation and oil prices on stock prices.

Findings: The study identified that the fluctuations of the stock market are significantly influenced by both inflation and oil prices. This relationship has been extensively studied in the literature, with several key research themes identified. These themes include the effects of inflation and oil prices on various sectors and industries, the role played by monetary and fiscal policy, and the impact of international trade and global economic conditions.

Practical Implications: The insights that have emerged have significant implications for investors and policymakers. It highlights the need for risk management strategies and mitigation of macroeconomic factors’ impact on stock prices.

The study aims to examine the association between virtual communication effectiveness (VCE), leadership effectiveness (LE) and the role of emotional intelligence (EI) in the post-pandemic era.

A survey was conducted among 305 employees in the Indian IT sector using an online questionnaire. Data were analyzed using reliability, validity and moderated regression analysis.

The findings reveal that VCE is a significant predictor of LE. EI plays a significant moderating role between VCE and LE.

This study establishes the role of EI in pre-empting LE. Furthermore, it results in the advancement of improved tools for the selection, training and development of leadership talent. Research on virtual communication (VC) and EI enhances our understanding of effective leadership. To the best of the authors’ knowledge, the present research is one of the first to link and standardize various practices of VC, and EI to increase LE in the post-pandemic era.

The aim of this study reported in this paper was to explore the application of operational excellence methodologies in a global context.

A qualitative interview approach was used to understand the current state, benefits, challenges, success factors, tools and techniques of operational excellence methodology implementation with relevance to logistics companies worldwide. About 16 interviews were undertaken with practitioners working in leading companies and with leading academics in Asia, Europe, Africa, North America, South America and Australia.

The findings show that operational excellence methodologies including Lean, Six Sigma, Lean Six Sigma and Agile can apply in logistics firms to improve operations and productivity and save costs. Top management support and involvement play an important role in the success of operational excellence projects in the logistics service.

The findings will be of interest to top and middle managers and logistics practitioners, with a dual aim of improving logistics performance and saving costs.

The present study has been one of the first global study attempts to explore the implementation of operational excellence methodologies in the logistics sectors.

The study aims to assess the impact of disruptive frugal digital technology and small and medium-sized enterprises' (SMEs') innovation performance on the food sector in Masvingo urban, Zimbabwe. A descriptive research design was used, and quantitative data were obtained using a questionnaire survey on 50 restaurant employees and 100 customers. The empirical findings demonstrated that the performance of SMEs was significantly improved by social media, cloud computing, virtual reality (VR), augmented reality (AR), and robotics. The study concludes that disruptive digital technologies (social media, cloud computing, AR, VR and robots affect the performance of SMEs by improving food production, streamlining information transfer, and utilizing cutting-edge technical applications. This chapter recommends that the government, through those in charge of formulating policy, educate and encourage the adoption of disruptive digital technology. The application of social media, cloud computing, VR, AR, and robotics will increase local food producers' access to the market. Digitalization will have a significant effect on Zimbabwe's local food system in the future.