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This study tests convergence in energy diversification, per-capita income and financial development and explores their interrelationships.

Club convergence tests, Granger tests and panel regressions are employed on 134 countries from 1995 to 2019.

While overall convergence is absent across the entire sample, countries have converged within specific clubs. Low- and lower-middle-income countries show convergence in energy diversification and per-capita income. Positive bidirectional relationships are found between energy diversification and per-capita income, and between financial development and per-capita income. A U-shaped relationship between oil prices and energy diversification is identified.

The findings suggest that achieving a shared equilibrium in energy diversification, economic prosperity and financial development is feasible through technological progress within convergence clubs. Investments in human capital and technology are crucial prerequisites for sustainable development.

This study pioneers testing energy diversification, per-capita income and financial development convergence, investigating the tri-directional relationship between them, and exploring the U-shaped relationship between oil prices and energy diversification.

The importance of workplace inclusion continues to gain scholarly acclaim. However, in reality, many employees choose to ostracize their colleagues post workplace relationship strife. With this notion the present study aims to delve into the intricate linkages between workplace relationship conflict (WRC) and employee ostracism behavior (EOB), exploring the serial mediating roles of relational identification (RI) and emotional energy (EE). Additionally, the study examines the potential moderating effect of perceived forgiveness climate (PFC) to understand how forgiveness climate may serve as a boundary condition in shaping these crucial relationships.

The analysis utilized five-wave time-tagged data collected from 228 employees through scenario and survey methods. The Hayes PROCESS Macro was employed to examine the proposed hypotheses.

The results indicate a positive influence of WRC on EOB. Additionally, RI and EE sequentially mediate the relationship between WRC and EOB. Furthermore, PFC moderates the serial mediation process (RI and EE) between WRC and EOB as well as the adverse effects of WRC on RI.

Grounded in the theoretical framework of conservation of resource (COR) theory and cognitive-affective personality system (CAPS) theory, the present study offers new insights. By establishing the complicated interplay of RI and EE between WRC and EOB along with the moderating role of PFC, the study extends the understanding of the mechanisms involved, providing a more comprehensive perspective. By shedding light on these complicated interconnected links, the study paved the way for positive social dynamics at work.

This research aims to uncover how the adoption process of a mobile payment solution unfolds in its local use. We examined micro-enterprises’ adoption of UPI-based payment system in India.

We employed an ethnographic approach to study the micro-entrepreneurs’ daily practice and adopted a relational ontology to conduct an “in-practice” enquiry of the UPI payment adoption process.

Applying the practice perspective of Technology Affordances and Constraints Theory, we found that UPI adoption was shaped through a dynamic interplay of emerging affordances and constraints. New features, such as All-in-one QR, enabled actions like cross-platform money transfer but also introduced challenges like fraud. Advancements in the technology addressed previous challenges but also created new hurdles. This cycle of evolving affordances and constraints within the contextual use of UPI payment technology shaped its adoption process.

The findings contribute to the existing body of mobile payment literature by elucidating the role of localized and ongoing enactment of affordances and constraints. Unlike existing adoption theories, using relational concepts of affordances and constraints revealed how the integration of mobile payment into practice leads to emergent use patterns and widespread adoption.

We emphasize the need for solutions that address localized challenges and contextual needs. The study advises policymakers to consider technology’s benefits and limitations in interventions.

The study offers a unique view on mobile payment adoption, highlighting the role of technological materiality and temporality. It reveals how the changing materiality of technology shapes the adoption process through localized affordances and constraints.

This case study will frame the significance of the business model for a company. The reader will understand business model innovation and how it helps enhance entrepreneurial rewards. The students will be able to identify the entrepreneurial traits which lead to business model innovation. The readers will know about the components of a business model and will be able to apply the understanding in creating a business model canvas.

The real-life case is of a tech start-up founded in Ahmedabad by three friends. Their diverse educational background helped them in creating a successful venture that later transformed into a public company. They were always trying to make their business model competitive and innovative. Being a start-up, there were critical business decisions taken and strategies formed by the founding team. They were facing a dilemma after making the company public, as their responsibility towards the stakeholders increased. They need to keep in mind the needs of all the stakeholders and the enterprise itself. They were at a crossroads in deciding about their business model.

This case study is suitable for honours or postgraduate level or entrepreneurship training.

Teaching notes are available for educators only.

CSS 11: Strategy.

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.

Generative artificial intelligence (GAI) can disrupt how consumers search for information on retail products/services online by reducing information overload. However, the risk associated with GAI is high, and its widespread adoption for product/service information search purposes is uncertain. This study examined psychological drivers that impact consumer adoption of GAI platforms for retail information search.

We conducted 31 in-depth, semi-structured interviews with the lead GAI users regarding product/service information search. The data were analysed using a grounded theory paradigm and thematic analysis.

Results show that consumers experience uncertainty about GAI’s functioning. Their trust in GAI impacts the adoption and usage of this technology for information search. GAI provides unique settings to investigate potential additional factors, leveraging UTAUT as a theoretical basis. This study identified three overarching themes – technology characteristics, technology readiness and information characteristics – as possible drivers of adoption.

Consumers seek exhaustive and reliable information for purchase decisions. Due to the abundance of online information, they experience information overload. GAI platforms reduce information overload by providing synthesized and customized product/service search results. However, its reliability, trustworthiness and accuracy have been questioned. The functioning of GAI is opaque; the popular technology adoption model such as UTAUT is general and is unlikely to explain in totality the adoption and usage of GAI. Hence, this research provides the adoption drivers for this unique technology context. It identifies the determinants/antecedents of relevant UTAUT variables and develops an integrated conceptual model explaining GAI adoption for retail information search.

The purpose of this study is to investigate the behaviour of M40 grade of self-compacting concrete (SCC) with high volume of ground granulated blast furnace slag (GGBS) (50%) and recycled concrete aggregate (RCA) content up to 100% to assess the mechanical properties of SCC. As per guidelines of IS: 383 – 2016, the RCA can be replaced up to 20% of natural coarse aggregate up to M25 grade of concrete. This study assesses the mechanical properties of SCC beyond 20% of RCA content. Based on the experimental investigations, the compressive strength of mixes decreases as the content of RCA increases. It is found that concrete mixes with 20% RCA and shows the maximum compressive strength at 56 days.

The fresh properties as per EFNARC and IS: 10262–2019 guidelines, ultrasonic pulse velocity testing, mechanical properties and microstructure analysis have been conducted to evaluate the performance of SCC with RCA for practical applications.

From the experimental investigations, it is found that up to 50% of recycled coarse aggregate can be used for structural applications.

The environmental pollution and dumping of waste on green land can be reduced by effective utilization of recycled coarse aggregate and GGBS in the production of SCC.

The objective of this work is twofold: firstly, to develop a model for assessing healthcare service quality (HSQ), and secondly, to evaluate the effectiveness of machine learning algorithms in predicting the quality of healthcare services.

In this study, a comprehensive literature review has been performed to identify key quality dimensions in the healthcare services domain. Delphi’s method has been used to confirm the criticality of these dimensions based on experts’ opinions and proposed a novel CIRMQUAL model. Factor analysis techniques have been used to further validate the CIRMQUAL model. Using the data collected through a questionnaire survey, a number of machine learning models have been developed to predict the customer satisfaction level based on the service quality (SQ) performance of a healthcare unit on different dimensions of the CIRMQUAL model.

The study developed a CIRMQUAL model with 14 dimensions (quality of care, safety and security, skill and conduct, staff attitude, tangibles, quality of the atmosphere, patient rights, follow-up, communication, cost of treatment, availability of resources, accessibility, waiting time and services), and these dimensions have been clubbed into four major dimensions, i.e. clinical quality, infrastructural quality, relationship and managerial quality. Furthermore, the application of machine learning algorithms has demonstrated significant accuracy in predicting SQ, highlighting its ability to improve healthcare services and the satisfaction level of patients.

Managers of healthcare units work hard to identify and address the pain points of the patients and improve the working of the healthcare units being managed by them. The availability of many scales with numerous dimensions adds to their confusion in selecting a suitable scale. The current work addresses this confusion and provides four clear areas for assessing the quality of healthcare units. By using this scale, managers can assess the quality of services provided by them, identify the dimensions of low performance, plan and take suitable corrective actions to improve the performance of their healthcare units.

A comprehensive SQ model, i.e. CIRMQUAL has been proposed as a new scale to assess SQ in healthcare units. The model has been developed after analyzing the dimensions used by many researchers available in the literature. This model can be used by future researchers to assess the SQ in healthcare units. Moreover, an attempt has been made to use artificial intelligence-based techniques for predicting customer satisfaction. Such attempts are in the initial stage for healthcare sector. Future researchers can take this concept forward and test the applicability of different machine learning techniques in different functional areas of healthcare.

Good health is of utmost importance for all human beings. In spite of the expenditure of substantial time and efforts by various stakeholders, the service delivery doesn’t match the expectations of patients. Many times, the service providers are not aware of this dissatisfaction and specific aspects of service delivery that need to be improved to reduce dissatisfaction. The model proposed will help the service providers in this regard and the service providers will be able to take focused steps. Such initiatives will definitely improve patient’s satisfaction and their social well-being.

This work is unique because it uses a novel technique to redefine the quality of services in healthcare by using a dual methodology. The research presents a model that includes various factors and it is specially developed to evaluate the quality of services in healthcare settings. This study advances the area’s progress by implementing computational tools for accurate evaluation of HSQ. The healthcare decision-makers may use this novel perspective to evaluate and enhance the quality of service.

This research explores the relationships between financial awareness and investor satisfaction about retirement planning, particularly in the Indian context. We developed a conceptual model involving double moderation effects of post-retirement objectives and external factors influencing investor satisfaction.

A carefully crafted survey instrument was designed to collect data from the 480 employees working in six administrative departments in the northern part of India. After checking the measurement properties of the survey instrument through the Lisrel package of structural equation modeling, the hypotheses were tested using Hayes PROCESS macros.

The results indicate that financial awareness is positively related to (1) investor satisfaction and (2) investment purpose; investment purpose is positively related to investor satisfaction; post-retirement objectives moderate the relationship between financial awareness and investment purpose; external factors moderate the moderated relationship between financial awareness and post-retirement objectives (first moderator) and investor satisfaction mediated through investment purpose.

The outcomes of this study have important implications for the employees embarking on making decisions concerning their retirement. The conceptual model provides a simple framework explaining how financial awareness and investor satisfaction are affected by the post-retirement objectives of individuals. This study highlights the importance of considering the effect of external factors influencing financial decisions.

The three-way interactions in this exploratory research contribute to the growing literature on behavioral finance, particularly concerning retirement planning involving pension.

Particularly in the rapidly expanding beauty and personal care sector, affiliate electronic word of mouth (eWOM) from affiliates has grown to be a dependable and trustworthy source of information. Guided by Signaling Theory, this paper aims to conduct a comprehensive analysis to understand the intricate dynamics of affiliate eWOM within the context of Iranian beauty and personal care products.

The study polled 330 consumers who have purchased beauty and personal care products in Iran. Data were gathered using a convenience sample, and the partial least square structural equation modeling model was used to examine and assess the hypotheses.

The results demonstrated a significant impact of information quality, rating, helpfulness and number of reviews, along with user-generated videos and photos, on the customer’s actual purchase and intention to purchase the beauty and personal care products. However, the ranking and recency of reviews do not significantly contribute to the stated relationship.

This research is first of its kind to analyze affiliate eWOM cues in the case of cosmetics e-commerce.