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The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

Introduction: Entrepreneurship and frugal innovation have emerged as critical drivers for addressing the Sustainable Development Goals (SDGs) in a global context. The United Nations developed the SDGs to address social, economic, and environmental challenges, ranging from poverty and inequality to climate change and sustainable economic growth. Entrepreneurship and frugal innovation offer a unique approach to achieving these goals by promoting innovation, creativity, and sustainability in business practices.

Purpose: This chapter aims to examine the role of entrepreneurship and frugal innovation in achieving SDGs in a global context. This chapter seeks to identify how entrepreneurship and frugal innovation can contribute towards realising the SDGs and how these concepts can be leveraged to create sustainable and scalable businesses that promote sustainable development.

Methodology: In order to examine how entrepreneurship and frugal innovation contribute to the worldwide achievement of the SDGs, the chapter will use a qualitative research technique. The literature review will involve the qualitative analysis of both developed and developing countries on some specific sectors like transportation, education, health sector, and financial services.

Findings: Through analysing relevant literature, qualitative research, and related examples this chapter provides insights into the challenges and opportunities associated with promoting entrepreneurship and frugal innovation for achieving the SDGs in different contexts.

Practical Implications: The chapter aims to contribute towards a better understanding of the role of entrepreneurship and frugal innovation in achieving SDGs and to provide recommendations for policymakers, entrepreneurs, and other stakeholders on supporting and promoting these concepts globally.

Material extrusion-based additive manufacturing is a prominent manufacturing technique to fabricate complex geometrical three-dimensional (3D) parts. Despite the indisputable advantages of material extrusion-based technique, the poor surface and subsurface integrity hinder the industrial application of this technology. The purpose of this study is introducing the hot air jet treatment (HAJ) technique for surface treatment of additive manufactured parts.

In the presented research, novel theoretical formulation and finite element models are developed to study and model the polishing mechanism of printed parts surface through the HAJ technique. The model correlates reflow material volume, layer width and layer height. The reflow material volume is a function of treatment temperature, treatment velocity and HAJ velocity. The values of reflow material volume are obtained through the finite element modeling model due to the complexity of the interactions between thermal and mechanical phenomena. The theoretical model presumptions are validated through experiments, and the results show that the treatment parameters have a significant impact on the surface characteristics, hardness and dimensional variations of the treated surface.

The results demonstrate that the average value of error between the calculated theoretical results and experimental results is 14.3%. Meanwhile, the 3D plots of Ra and Rq revealed that the maximum values of Ra and Rq reduction percentages at 255°C, 270°C, 285°C and 300°C treatment temperatures are (35.9%, 33.9%), (77.6%,76.4%), (94%, 93.8%) and (85.1%, 84%), respectively. The scanning electron microscope results illustrate three different treatment zones and the treatment-induced and manufacturing-induced entrapped air relief phenomenon. The measured results of hardness variation percentages and dimensional deviation percentages at different regimes are (8.33%, 0.19%), (10.55%, 0.31%) and (−0.27%, 0.34%), respectively.

While some studies have investigated the effect of the HAJ process on the structural integrity of manufactured items, there is a dearth of research on the underlying treatment mechanism, the integrity of the treated surface and the subsurface characteristics of the treated surface.

Based on the affective events and self-concept theories, this study aims to examine the relationship between knowledge sharing system, job crafting, meaningfulness in work and employees' intention to stay with the organization.

In the present study, the authors conducted a time-lagged survey for analyzing the association between knowledge sharing system, job crafting, meaningfulness in work and employees' intention to stay with the organization. The study sample comprises 358 Generation Y employees working in Indian IT organizations. Results were analyzed using Process and Hayes macro process.

The study findings suggest significant relationships between knowledge sharing system, job crafting, meaningfulness in work and intention to stay among Gen Y employees. Moreover, the results demonstrated that knowledge sharing system, directly and indirectly, impacts employees' intention to stay via sequential mediation of job crafting and meaningfulness in work.

In today's era of hyper-competition and “war for talent,” retaining talented professionals has become the topmost priority for organizations. This becomes even more challenging with new generations, Gen Y and Z, entering the workforce driven by entirely different needs compared to earlier generations. Thus, the present study offers an integrated framework that organizational practitioners could utilize to enhance the retention of their young talented professionals.

Despite the emerging interest in the concept of knowledge sharing, few studies investigated the association between knowledge sharing system and intention to stay among Gen Y employees. Also, research still lacks in examining the underlying mechanism of how knowledge sharing system may enhance job crafting and meaningfulness in work, which could fuel Gen Y employees' intention to stay with the organization.

This study aims to identify specific factors that facilitate engagement and stay intention among Generation Z employees in the Indian banking, financial services and insurance (BFSI) context. Furthermore, using the frequency distribution of the identified factors, this study has ranked them in order of their association with stay intention.

Data were collected from 22 Gen Z employees working in the Indian private BFSI sector using unstructured interviews. Inductive content analysis was applied to identify the factors improving engagement and stay intention. Moreover, quantitative content analysis was applied to calculate the frequency distribution of the identified factors.

The study identified six prominent factors, namely, transformational leadership, employee investment practices, egalitarian practices, work-life balance, job crafting and sustainability, which significantly enhance employee engagement and stay intention among Gen Z employees. Moreover, based on the results of quantitative content analysis, it was found that transformational leadership exhibited the highest frequency in association with employee engagement and stay intention. Following this were employee involvement, egalitarian practices, work-life balance, job crafting and sustainability.

In the coming days, Generation Z will contribute to almost one-third of India’s workforce, of which the BFSI sector will be the major employer. However, the issue with this generation is their retention. Hence, the study identifies factors ensuring engagement and stay intention.

Owing to the paucity of research on stay intention as a variable of interest, this study tries to capture the perceptions of Gen Z towards factors inducing their engagement and stay intention. This study assesses intention to stay (ITS) as compared to intention to leave (ITL) as it is a proactive indicator of turnover. Lastly, this study uses a qualitative approach to identify factors influencing stay intention and engagement based on interactions with employees, which, to the best of the authors’ knowledge, no prior study has attempted.

Waste generated from electrical and electronic equipment, collectively known as E-waste, remains a persistent environmental, economic and social problem. Sustainable E-waste management (EWM) has numerous benefits, such as preventing electronic waste from entering landfills, reducing the need for virgin materials by recovering valuable materials from recycling and lowering greenhouse gas emissions. Circular economy (CE) practices are considered the initial steps toward sustainable EWM, but some hurdles have been reported in the adoption of these practices. Therefore, the current study aims to identify the common CE practices, sustainability of the EWM process and the challenges in EWM, and to develop a conceptual framework for effective EWM.

Very few studies have proposed frameworks that acknowledge the challenges and CE practices of EWM. To fill this gap, a systematic literature review (SLR) was performed, and 169 research articles were explored.

A total of seven challenges in the adoption of effective EWM were identified: rules and policy, infrastructure, consumer behaviour, informal sectors, community culture, technology and economy. Eight common CE practices were also found for effective EWM: reuse, recycle, remanufacturing, refurbishment, repair, reduce, recover and repurpose.

A conceptual framework guiding sustainable EWM was proposed, which includes solutions for the identified challenges, and CE practices with sustainable benefits.

India liberalized its economy in 1991, which resulted in intense global competition, quality-conscious and demanding customers. Additionally, significant technological advancements lead to enhancements in products and processes. These forced Indian organizations to adopt innovative business strategies in the past 30 years. Meanwhile, the Lean Six Sigma methodology has significantly grown with vast applicability during the past 30 years. Thus, the purpose of this study is to develop the learning on Lean Six Sigma methodology in the Indian context through investigation of literature.

A three-stage systematic literature review approach was adopted to investigate the literature during the present study. In total, 187 articles published in 62 journals/conference proceedings from 2005 to 2022 (18 years) were shortlisted. The first part of the article summarizes the significant milestones towards the quality journey in the Indian context, along with the evolution of the Lean Six Sigma methodology. The second part examines the shortlisted papers on Lean Six Sigma frameworks, their applicability in industrial sectors, performance metrics, outcomes realized, publication trends, authorship patterns and leading researchers from the Indian perspective.

Lean Six Sigma has emerged as a highly acclaimed and structured business improvement strategy worldwide. The Indian economy has seen remarkable growth in the past decade and is one of the fastest-growing economies in the 21st century. Lean Six Sigma implementation in India has significantly increased from 2014 onward. The study revealed that researchers have proposed several different frameworks for Lean Six Sigma implementation, the majority of which are conceptual. Furthermore, the balanced applicability of Lean Six Sigma in manufacturing and service sectors was observed with the highest implementation in the health-care sector. Additionally, the widely adopted tools, techniques along with performance metrics exploring case studies were reported along with a summary of eminent and leading researchers in the Indian context.

This study is confined to reviewed papers as per the research criteria with a significant focus on the Indian context and might have missed some papers due to the adopted papers selection strategy.

The present study is one of the initial attempts to investigate the literature published on Lean Six Sigma in the Indian context, including perspective on the Indian quality movement. Therefore, the present study will provide an understanding of Lean Six Sigma methodology in the Indian context to graduating students in engineering and management and entry-level executives. The analysis and findings on Lean Six Sigma frameworks, research approach, publications details, etc., will be helpful to potential research scholars and academia. Additionally, analysis of case studies on Lean Six Sigma implementation by Indian industries will assist the managers and professionals in decision making.

The purpose of this paper is to analyse and classify the literature that contributed to three questions, namely, what are the benefits of big data analytics (BDA) in the field of supply chain management (SCM) and logistics, what are the challenges in BDA applications in the field of SCM and logistics and what are the determinants of successful applications of BDA in the field of SCM and logistics.

This paper conducts a systematic literature review (SLR) to analyse the findings of 44 selected papers published in the period from 2016 to 2020, in the area of BDA and its impact on SCM. The designed protocol is composed of 14 steps in total, following Tranfeld (2003). The selected research papers are categorized into four themes.

This paper identifies sets of benefits to be gained from the use of BDA in SCM, including benefits in data analytics capabilities, operational efficiency of logistical operations and supply chain/logistics sustainability and agility. It also documents challenges to be addressed in this application, and determinants of successful implementation.

The scope of the paper is limited to the related literature published until the beginning of Corona Virus (COVID) pandemic. Therefore, it does not cover the literature published since the COVID pandemic.

This paper contributes to the academic research by providing a roadmap for future empirical work into this field of study by summarising the findings of the recent work conducted to investigate the uses of BDA in SCM and logistics. Specifically, this paper culminates in a summary of the most relevant benefits, challenges and determinants discussed in recent research. As the field of BDA remains a newly established field with little practical application in SCM and logistics, this paper contributes by highlighting the most important developments in contemporary literature practical applications.

The study investigates the mediated moderation impact of Memorable Religious Experience (MRE) and Religiosity (REL) on the relationship between Memorable Tourism Experience (MTE) and Attitude towards Pilgrimage (ATT) finally driving Recommend Intention (RCI) of visitors to a religious site. It suggests visitors' incentive variable religiosity can influence their decision to recommend visiting a religious destination.

The research uses a quantitative cross-sectional approach wherein a self-administered survey was used for data collection from 223 pilgrims who visited a popular pilgrimage site. Partial least squares-structural equation modeling (PLS-SEM) was employed for analysis.

The results showed that MTE has a significant influence on ATT which further influences RCI (a dimension of behavioral intention-BI) of visitors towards a religious destination. Further, MRE mediates the relationship between MTE and ATT. Nevertheless, REL illustrated a significant moderation influence on the relationship between MRE and ATT, further verifying the mediated moderation impact of MRE and REL in the model.

Recommendation of existing customers is one of the most powerful indicators of customer loyalty and usually leads to revisit. The research provides destination managers/tourism planners of pilgrimage sites to formulate appropriate marketing strategies to develop RCI and sustainable branding.

This study adds to the empirical studies conducted on REL by constructing a composite picture of the memorable tourism experience within a pilgrimage tourism context. The uniqueness lies in the attempt to investigate the mediated moderation impact of MRE and REL using a symmetric (PLS-SEM) approach.

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.