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The purpose of this study is to examine the extent to which Indian insurance companies have adapted socially responsible reporting practices, HR disclosures and also to identify areas of corporate social reporting and HR disclosures.

The study adopts longitudinal design and has analyzed qualitative data by using content analysis in 26 insurance companies in India disclosed in annual reports. The paper focuses on annual reports of Indian insurance companies starting from the financial year 2002‐2003 to 2009‐2010, which are analyzed with regard to the nature of their human resource disclosures and social reporting. Finally, a test of legitimacy theory is then conducted.

The study found that the non‐life insurance companies disclosed significantly less social information than life insurance companies. The study also reveals that public life insurers disclosed significantly more social information than the other life insurance companies. On the other hand, a paired difference t‐test shows private general insurance companies disclose more social information as the difference significant.

The study has ignored longitudinal variations and the sample organizations comprised 26 government and private insurance organizations, restricting generalizations to the companies examined in the study.

The study recommends that a checklist of disclosures should be developed jointly by the Insurance Regulatory and Development Authority (IRDA), the Institute of Chartered Accountants of India (ICAI), and the Securities and Exchange Board of India (SEBI).

The study, while providing valuable insights, highlights the dearth of research of corporate social reporting in emerging economies and opens up many avenues for further research.

The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.

We provide an overview of how artificial intelligence is transforming the identification, structuring, and prioritization of customer needs – known as the voice of the customer (VOC). First, we summarize how the VOC helps firms gain insights on using user-generated data. Second, we discuss the types of user-generated data and the challenges associated with analyzing each type of data. Third, we describe common methods, matched to the firms' goals and the structure of the data, that are used to analyze the VOC. Fourth, and most importantly, we map the methods to relevant applications, providing guidance to select the appropriate method to address the desired research questions.

The case presents an ideal platform for discussing the branding strategy, brand elements and the factors that contributed to success of an entrepreneurial venture in the quick-service restaurant (QSR) segment. Further, it enables students to discuss changes that are necessitated as the firm looks for new growth avenues. After working through the case and assignment questions, students will be able to analyze the entrepreneurial journey of a startup in red ocean markets by assessing the factors that contributed to its success; comprehend the importance of branding strategy for small business – choosing/designing of brand elements and selecting the positioning strategy; and assess changes needed in the branding strategy over time and devise strategies for the continued success of the firm.

Kolkata-based QSR chain Wow! Momo was bootstrapped with a meager INR 30,000 in 2008 by two school friends Sagar Daryani and Binod Kumar. It went on to become India’s Wow! Momo very first QSR specializing in momos. By the year 2019, Wow! Momo was dishing out India’s favourite street food, “momos” from 300 outlets across 15 cities. It also claimed to have captured 90% market share in the organized momo business. The startup grew at a CAGR of over 50% between 2015 and 2019 and reported INR 1.19bn revenue in financial year 2019 with an EBITDA of 9.3%. Wow Momo Foods Pvt. Ltd (WMF), the parent company of Wow! Momo, had tasted stupendous success within a short period and set an ambitious goal of achieving revenue of INR 10bn by 2023–2024. Wow! Momo had achieved top of mind recall among the target customers and was also vying for the same share of wallet as formidable international giants such as McDonald’s, Domino’s, Burger King and KFC. However, compared to these large players, Wow! Momo offered a limited menu and a smaller average ticket size. At the same time, Wow! Momo’s market share was also threatened by a host of branded momo players that offered a similar menu and pricing. Both these factors did not argue well for WMF’s mammoth growth objective. Achieving revenue of INR 1.19bn in a matter of just 10 years was no small feat, but reaching targeted INR 10bn in half that time needed a different game plan altogether. The founders clearly needed to rethink their strategies for the next phase of growth. What would be the next growth driver for the company? Should it look for greener pastures outside India? Was it time to diversify the menu and think beyond momos? If so, then should new items be added to existing menu or a new brand be launched altogether? The case maps the journey of two entrepreneurs as they went on to set up a successful QSR chain. It examines their trials and tribulations as well as successful implementation of marketing strategy. It also looks at the dilemmas faced by a startup as it searches for new avenues for growth.

Graduate and postgraduate courses in Management.

Teaching Notes are available for educators only.

CSS 8: Marketing.

The aim of this review is to reflect the current state of Financial Technology (FinTech) research along with its journey of development. Further, a conceptual framework showing the interaction of independent, mediating, and moderating variables with dependent variables (acceptance of FinTech products and services) along with propositions is prepared to facilitate the future researchers. This systematic literature review consists of 110 articles from 78 journals indexed in two academic databases (Scopus and/or Web of Science), extracting facts and figures about FinTech during 2016–2021. Our findings contribute to the literature by exemplifying that FinTech is a mixed set of threats and opportunities. In the present review only 18 articles belong to 2016–2017 but 54 articles are considered from 2020–2021, the increasing number of FinTech articles in high-ranking journals indicate the speedily growing popularity of FinTech. Similarly, secondary data based articles are dominating the primary data based ones. Further, regression analysis and PLS-SEM are the most popular statistical techniques among the authors of FinTech articles. To the best of knowledge of the authors, this is a unique study in which the latest FinTech research findings are skimmed.

The objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.

To accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.

In the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.

Employing the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.

This research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.

With growing environmental and social issues worldwide, sustainability disclosures and reporting have become a focal point of discussion. This study aims to investigate the role played by gender diversity in sustainability disclosures in the context of India, over a period of eight years.

The study devises a unique sustainability reporting quality index and employs the generalized ordered logit model, which ensures that results are parsimonious even if the assumptions under a logit model are violated.

The results suggest that with an increase in the percentage of women directors and the number of independent women directors on board, the sustainability reporting quality is likely to improve.

The results of the study shall play a significant role for the corporate houses established in India, as it encourages them to modify their directors' selection process and ensure that women are able to break the “glass ceiling” to reach the upper echelon in the firms.

The study gives an insight into the role played by women directors in sustainability reporting quality aspect, and therefore, the regulatory bodies, as well as policymakers of the Indian economy, shall formulate such regulations which can advance the presence of women on the board and in the decision-making process.

This study is among the first to investigate the relationship between gender diversity and sustainability reporting quality using the generalized ordered logit model which is an improvement over the previously used techniques. Moreover, the unique cultural and institutional setting offered by India, which is an emerging economy, provides a fertile ground for understanding the role of women leaders in the workforce.

This study examines the conceptual domain of international marketing following substantial growth in its development. With the objective to investigate recent patterns and development in the literature this study evaluates 1,816 research articles on international marketing published between 1990 and 2012. The classification of conceptual domain has yielded 57 configurational contents under seven prime research streams. Simple meta-analysis on international marketing literature created a clear depiction of attention of contributors toward research streams and the number of contributors, and worthy sources of literature. Several directions for advancement of knowledge in international marketing, identified fields, and their implications for future research are discussed.

The purpose of this study is to develop a novel comprehensive three-dimensional computational model to predict the transient thermal behavior and residual stresses resulting from the layer-by-layer deposition in the direct metal laser sintering process.

In the proposed model, time integration is performed with an implicit scheme. The equations for heat transfer are discretized by a finite volume method with thermophysical properties of the metal powder and an updated convection coefficient at each time step. The model includes convective and radiative boundary conditions for the exposed surfaces of the part and constant temperatures for the bottom surface on the build plate. The laser source is modeled as a moving radiative heat flux along the scanning pattern, while the thermal gradients are used to calculate directional and von Mises residual thermal stresses by using a quasi-steady state assumption.

In this study, four different scanning patterns are analyzed, and the transient temperature and residual thermal stress fields are evaluated from these patterns. It is found that the highest stresses occur where the laser last leaves off on its scanning pattern for each layer.

The proposed model is designed to capture the layer-by-layer deposition for a three-dimensional geometry while considering the effect of the instantaneous melting of the powder, melt pool, dynamic calculation of thermophysical properties, ease of parametrization of various process parameters and the vectorization of the code for computational efficiency. This versatile model can be used for process parameter optimization of other laser powder bed fusion additive manufacturing techniques. Furthermore, the proposed approach can be used for analyzing different scanning patterns.

This study explores the factors impacting user adoption and trust in blockchain-based food delivery systems, with a spotlight on the Open Network for Digital Commerce (ONDC). In the evolving food delivery sector, blockchain offers transparency and efficiency. Through the Unified Theory of Acceptance and Use of Technology (UTAUT) lens, this research provides insights for businesses and policymakers, highlighting the importance of blockchain’s integration into food delivery.

The research employed the UTAUT and its extensions as the theoretical framework. A structured questionnaire was developed and disseminated to users of the ONDC platform, and responses were collected on a seven-point extended Likert scale. The analyses were undertaken employing the partial least squares (PLS) methodology and structural equation modelling (SEM).

Key factors like performance expectancy, effort expectancy and social influence were found influential for adoption. Trust played a central role, while perceived risk didn’t significantly mediate the adoption process. Digital culture didn’t significantly moderate the adoption intention.

This research adds to the existing body of knowledge by providing empirical insights into user adoption and trust in blockchain-based food delivery platforms. It is among the pioneer studies to apply the UTAUT model in the realm of blockchain-based food delivery platforms, thereby offering a unique perspective on the dynamics of user behaviour in this emerging field.