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This work provides a generic review of the existing data mining ontologies (DMOs) and also provides a base platform for ontology developers and researchers for gauging the ontologies for satisfactory coverage and usage.

The study uses a systematic literature review approach to identify 35 DMOs in the domain between the years 2003 and 2021. Various parameters, like purpose, design methodology, operations used, language representation, etc. are available in the literature to review ontologies. Accompanying the existing parameters, a few parameters, like semantic reasoner used, knowledge representation formalism was added and a list of 20 parameters was prepared. It was then segregated into two groups as generic parameters and core parameters to review DMOs.

It was observed that among the 35 papers under the study, 26 papers were published between the years 2006 and 2016. Larisa Soldatova, Saso Dzeroski and Pance Panov were the most productive authors of these DMO-related publications. The ontological review indicated that most of the DMOs were domain and task ontologies. Majority of ontologies were formal, modular and represented using web ontology language (OWL). The data revealed that Ontology development 101, METHONTOLOGY was the preferred design methodology, and application-based approaches were preferred for evaluation. It was also observed that around eight ontologies were accessible, and among them, three were available in ontology libraries as well. The most reused ontologies were OntoDM, BFO, OBO-RO, OBI, IAO, OntoDT, SWO and DMOP. The most preferred ontology editor was Protégé, whereas the most used semantic reasoner was Pellet. Even ontology metrics for 16 DMOs were also available.

This paper carries out a basic level review of DMOs employing a parametric approach, which makes this study the first of a kind for the review of DMOs.

The current work provides a framework for the ranking of ontology development methodologies (ODMs).

The framework is a step-by-step approach reinforced by an array of ranking features and a quantitative tool, weighted decision matrix. An extensive literature investigation revealed a set of aspects that regulate ODMs. The aspects and existing state-of-the-art estimates facilitated in extracting the features. To determine weight to each of the features, an online survey was implemented to secure evidence from the Semantic Web community. To demonstrate the framework, the authors perform a pilot study, where a collection of domain ODMs, reported in 2000–2019, is used.

State-of-the-art research revealed that ODMs have been accumulated, surveyed and assessed to prescribe the best probable ODM for ontology development. But none of the prevailing studies provide a ranking mechanism for ODMs. The recommended framework overcomes this limitation and gives a systematic and uniform way of ranking the ODMs. The pilot study yielded NeOn as the top-ranked ODM in the recent two decades.

There is no work in the literature that has investigated ranking the ODMs. Hence, this is a first of its kind work in the area of ODM research. The framework supports identifying the topmost ODMs from the literature possessing a substantial amount of features for ontology development. It also enables the selection of the best possible ODM for the ontology development.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

The authors present a systematic literature review on microfinance institutions’ (MFIs) effect on poverty and how they can ensure their sustainability. The purpose of this article is to review the effect of MFIs on poverty in South Asian countries. The analysis and review of the selected corpus of literature also provide avenues for future research.

A total of 95 papers from 49 journals in 4 academic libraries and publishers were systematically studied and classified. The authors define the keywords and the inclusion/exclusion criteria for the identification of papers. The review includes an analysis of the selected papers that give insights about publications with respect to themes, number of themes covered in individual publications, nations, scope, methodology, number of methods used and publication trend.

The literature indicates the positive effect of microfinance on poverty but with a varying degree on various categories of poor. The relation between poverty and microfinance is, however, dependent on the nation under the scanner. While sustainability and outreach co-exist, their trade-off is still a matter of debate.

This is the first systematic literature review on MFIs’ effect on poverty in South Asian nations. Additionally, the authors discuss the literature on the trade-off between sustainability and outreach for MFIs.

In mobile banking (m-banking), understanding the factors contributing to customer satisfaction is crucial for bank managers to design effective strategies for enhancing the uptake of mobile banking services. This study assesses the relationships between quality, technology acceptance and credibility factors and behavioural outcomes (actual use, continuance intention and loyalty) and satisfaction with m-banking. It further investigates the moderating influence of economy type, innovation level, connectivity level and sample size on all these relationships.

The study employs a meta-analysis technique and reviews 54 published studies to investigate the antecedents and consequences of satisfaction with m-banking.

The study finds a significant relationship between satisfaction with m-banking and quality, technology acceptance and credibility factors and behavioural outcomes. It concludes that the moderating effect of economy type, innovation level, connectivity level and sample size partially moderate the majority of the hypothesized relationships.

Drawing on a comprehensive literature review, this study presents a novel framework elucidating the antecedents and behavioural outcomes of satisfaction with mobile banking. It contributes to the literature by exploring the moderating effects of sample size and country context on the relationships between these factors, presenting important implications for future mobile banking research.

This study has practical implications for m-banking service providers, offering insights into the factors that drive user satisfaction with mobile banking and highlighting the need for tailored strategies in different country contexts.

This study examines the effects of factors leading to satisfaction and the subsequent outcomes within the context of m-banking. The findings offer fresh perspectives that can be valuable for managers and policymakers, enabling them to enhance customer satisfaction in the realm of m-banking.

The purpose of this study is to develop a conceptual framework which takes into account the perceived risk (PR) and the perceived benefits (PB) of using mobile payment systems (MPS) in the context of COVID-19 pandemic.

The study proposes a conceptual framework incorporating the uncertainties/risks associated with MPS like perceived technology uncertainty (PTU), perceived regulatory uncertainty (PRU), perceived service intangibility (PSI) and perceived information asymmetry (PIA), along with the benefits of using MPS such as trust, mobility, health consciousness (HC) and fear of Coronavirus (FOC). A survey comprising 1,253 participants was conducted in India. The proposed model was empirically examined through partial least square structural equation modelling.

The outcomes of the study revealed a significant positive influence of PTU, PRU, PIA and PSI on PR. On the other hand, HC and FOC were identified as the major antecedents having a significant positive influence on PB. Both PR and PB had a significant influence on the intention to adopt MPS, but the influence of PB was greater than the influence of PR.

The enablers and inhibitors play a crucial role in understanding the intention to adopt MPS. HC and fear of acquiring Coronavirus can be aggressively marketed by the government and service providers as a strategy to maintain social distancing. Government should address the regulatory concerns associated with the usage of MPS so as to alleviate any negative perception among the general public.

The current study is a novel attempt to understand the intention to adopt MPS in India as precautionary health behaviour to curb the transmission of Coronavirus pandemic. The study uses two constructs, HC and FOC, to better understand the behaviour of the people and explain the intention to adopt MPS during the COVID-19 pandemic.

Corruption in India reached a crescendo between 2011 and 2013, with the exposure of the 2G Spectrum scandal and the “Coalgate” report fiasco at the top of all recent events. The largest working democracy is under the scanner. As the third largest economy in Asia, a nuclear power, and an information technology powerhouse, India has a lot to clean up. Current experience shows the failure of the top investigative agencies and the lack of political will to tackle corruption. The spate of high-level corruption scandals has also led to a popular movement in 2011, which also fizzled out, including the newly introduced “Anti-Corruption, Grievance Redressal and Whistleblower Protection Act, 2011.” This chapter examines the several issues involved.

Consumers in India are increasingly using mobile payment systems (MPSs) to make online and offline payments. Digital payment applications are gradually being used as surrogates for cash, checks and plastic money. The motive behind this research is to analyze the different antecedents that impact the users' willingness to continue using the MPS in India.

An extensive study of the literature review supports the creation of a framework that describes the continuance intention of using MPS. Data from a survey of 612 respondents from India were collected to assess the research model. The study used partial least squares (PLS)–structural equation modeling (SEM) technique to empirically validate the framework developed.

The outcomes of the research suggest that service quality, attitude, effort expectancy and perceived risk act as influencing antecedents of continuance intention to use MPS. Determinants like perceived trust, convenience and social value have no influence on users' continuance intention. SEM analysis has verified the proposed model, which explains 50.7% of the variance of the users' continuance intention of using MPSs.

The research is built upon cross-sectional data carried out in India. Hence, the outcomes of the study are limited to this region only.

Engaging with the consumers for a long time and enabling their continuance usage are extremely important for firms offering mobile payment services. The managerial implications provide insights into the different ways to capture new business opportunities to the firms rendering mobile payment services in the wake of changing consumer behavior.

This research tries to analyze users' continuance intention to use MPS in India. Although many research studies have investigated the willingness of the individuals to adopt novel technology in different frameworks, there are hardly any empirical studies carried out to analyze the antecedents of users' continuance intention to use MPSs.

It is worth mentioning that mergers and acquisitions (M&As) have become a popular vehicle for emerging‐markets firms to rapidly access new opportunities and market capabilities. Indeed, privatization and multi‐nationalization have given a greater shore up in raising global and domestic merger deals. Motivated by these factors, the purpose of this paper is to investigate “do mergers produce abnormal returns around the announcement; conversely, do they improve financial performance in the long‐run?”

The study applies earnings management approach (event study) to compute average abnormal returns (AAR) around the merger announcement for select Indian M&A cases. Further, accounting ratios are considered to assess the long‐run financial performance. Thereafter, t‐stat is applied for testing the proposed hypotheses. In particular, it has performed a later test to the means of financial ratios and variables for both services and manufacturing sectors in accounting ratios and cylinder models, respectively.

The select Indian M&A cases show superior performance during the post‐merger period for both manufacturing and services sectors, and observe a balance sheet improvement in the long‐run.

Sample is one of the limitations to the study. Due to small sample of merger cases, this paper has limited scope to generalize the results. Hence, academic researchers may employ the suggested assessment (cylinder)‐models on a large sample.

The research work would help financial analysts, stockbrokers, M&A advisory and regulatory bodies while designing takeover and open offer policies.

This is an original contribution, which has developed new assessment (cylinder)‐models to examine the post‐merger long‐run financial performance of acquiring firms, especially sector‐wise evaluation.

The learning outcomes of this case are in understanding core concepts of brand management and brand dilution. Assessment of macro-economic risks and proper positioning strategies are the key take-away from this case. The case gives an understanding of how brands are built and positioned, and the pitfalls of poor brand planning and assessment that could lead to brand dilution. The case is useful for highlighting the importance of brand management and the challenges of re-positioning. The discussions would shed light on why it is important to plan and manage spending on marketing for brand building activities, and why brands would suffer when spending is reduced. This case is a teaching case and not a research case. It will help participants assimilate available information in combination with existing academic theories and publications to help develop an accurate assessment and prognosis of the events leading until the point of slicing the case.

Reid & Taylor in 2015 had been reduced to a discounter brand offering extended end-of-season sales when most other competitors have ended their promotions. In the 17 years since its big-budget launch in the Indian market in one of the most memorable brand introductions, Reid & Taylor changed its ambassador twice and repositioned itself thrice. The case would allow participants to delve deeper into aspects of marketing spending, brand management, positioning and advertising effectiveness. The case brings to the fore discussions on marketing, specifically on branding, positioning and its related advertising in the textile sector for a brand that has not been studied in academic literature until the present time. The discussion allows for novelty, involving both forward- and backward-looking assessments and evaluations to help participants better imbibe learnings in brand management and positioning.

The case is suitable for a graduate-level (Master’s level) course in marketing and brand management. This case is suitable for elective courses that discuss positioning and brands.

Teaching notes are available for educators only.

CSS 8: Marketing