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The learning objectives have been prepared in accordance with the Blooms Taxonomy (Engelhart et al., 1984). After completion of this case, students would be able to examine and expand the concept of institutions (i.e. a sport as an institution in this case) and understand how important it is to incorporate them in the policy level decision-making (Knowledge); understand a different form of the social institution (i.e. Jallikattu) and capture its relevance for all the involved stakeholders by taking into consideration the challenges that could stem from their interplay (Application); analyze the interests of various stakeholders and their concerns that add to the complexity of a socially relevant issue (Analysis); and integrate the developments of an event (i.e. Jallikattu) over its timeline and develop an action plan for being prepared or for resolving such exigencies, especially for public policy decision making (Synthesis).

The case is centred on Senaapathy Kangayam Cattle Research Foundation whose primary aim is conservation and breeding of native breeds of cattle. The protagonist of the case, Karthikeya Sivasenapathy, managing trustee of this foundation, has invested significant efforts to create awareness on the importance of Jallikattu. Jallikattu is an ancient Indian sport played in the rural regions of Tamil Nadu state in India and has been in existence for over 5,000 years. This issue has come into limelight due to its initial ban by the Supreme Court of India in 2014 and its subsequent stay on the ban in 2016. While there are several arguments surrounding this controversy, the arguments can be broadly classified under those who support the ban (i.e. oppose Jallikattu) and those who oppose the ban (i.e. support Jallikattu). Due to the involvement of various stakeholders (government supreme court, animal welfare boards and breed saviour groups) with conflicting objectives, the dynamics of decision-making to settle this issue became very complicated, confusing and time-consuming for Karthikeya. By using the lens of institutions and stakeholder theory, the authors explain the issue around Jallikattu in this teaching note. Teaching note also documents the unfolding of events that happened after 12 January 2017 which succeeded in lifting the ban on Jallikattu.

The case is written for undergraduate and graduate-level students pursuing business programmes and for senior management professionals participating in the executive education programmes. The case is suitable for those who are expected to work in an environment where there is a multitude of complex, formal as well as informal institutions. This case can be used to teach the concepts of institutions, the dynamics involved and to give the flavour of the interactions between these different institutions in solving a social issue. It will fit well into courses on strategic management, social movement and institutional theory.

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 1: Accounting and Finance.

Finding the optimal maintenance schedules is the primitive aim of preventive maintenance scheduling (PMS) problem dealing with the objectives of reliability, risk and cost. Most of the earlier works in the literature have focused on PMS with the objectives of leveling reserves/risk/cost independently. Nevertheless, very few publications in the current literature tackle the multi-objective PMS model with simultaneous optimization of reliability, and economic perspectives. Since, the PMS problem is highly nonlinear and complex in nature, an appropriate optimization technique is necessary to solve the problem in hand. The paper aims to discuss these issues.

The complexity of the PMS problem in power systems necessitates a simple and robust optimization tool. This paper employs the modern meta-heuristic algorithm, namely, Ant Lion Optimizer (ALO) to obtain the optimal maintenance schedules for the PMS problem. In order to extract best compromise solution in the multi-objective solution space (reliability, risk and cost), a fuzzy decision-making mechanism is incorporated with ALO (FDMALO) for solving PMS.

As a first attempt, the best feasible maintenance schedules are obtained for PMS problem using FDMALO in the multi-objective solution space. The statistical measures are computed for the test systems which are compared with various meta-heuristic algorithms. The applicability of the algorithm for PMS problem is validated through statistical t-test. The statistical comparison and the t-test results reveal the superiority of ALO in achieving improved solution quality. The numerical and statistical results are encouraging and indicate the viability of the proposed ALO technique.

As a maiden attempt, FDMALO is used to solve the multi-objective PMS problem. This paper fills the gap in the literature by solving the PMS problem in the multi-objective framework, with the improved quality of the statistical indices.

Previous research suggests that the compensation offered to customers after a service failure has to be substantial to make customer satisfaction surpass that of an error-free service. However, with the right service recovery strategy, it might be possible to reduce compensation size while maintaining happy customers. The aim of the current study is to test whether an anchoring technique can be used to achieve this goal.

After experiencing a service failure, participants were told that there is a standard size of the compensation for service failures. The size of this standard was different depending on condition. Thereafter, participants were asked how much they would demand to be satisfied with their customer experience.

The compensation demand was relatively high on average (1,000–1,400 SEK, ≈ $120). However, telling the participants that customers typically receive 200 SEK as compensation reduced their demand to about 800 SEK (Experiment 1)—an anchoring effect. Moreover, a precise anchoring point (a typical compensation of 247 SEK) generated a lower demand than rounded anchoring points, even when the rounded anchoring point was lower (200 SEK) than the precise counterpart (Experiment 2)—a precision effect.

Setting a low compensation standard—yet allowing customers to actually receive compensations above the standard—can make customers more satisfied while also saving resources in demand-what-you-want service recovery situations, in particular when the compensation standard is a precise value.

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares differently depending on influencer characteristics (i.e. mega influencer and expert influencer) and brand characteristics (i.e. brand establishment and product involvement).

This study uses a unique real-world data set that combines coded variables (e.g. customization) and objective video performance (e.g. sharing) of 365 sponsored videos to test the hypotheses. A negative binomial model is used to analyze the data set.

This study finds that the effect of video customization on video shares varies across contexts. Video customization positively affects shares if they are made for well-established brands and high-involvement products but negatively influences shares if they are produced by mega and expert influencers.

This study extends the influencer marketing literature by focusing on a new media modality – sponsored video. Drawing on the multiple inference model and the persuasion knowledge theory, this study teases out different conditions under which video customization is more or less likely to foster audience engagement, which both influencers and brands care about. The chosen research setting may limit the generalizability of the findings of this study.

The findings suggest that mega and expert influencers need to consider if their endorsement would backfire on a highly customized video. Brands that aim to engage customers with highly-customized videos should gauge their decision by taking into consideration their years of establishment and product involvement. For video-sharing platforms, especially those that are planning to expand their businesses to include “matching-making services” for brands and influencers, the findings provide theory-based guidance on optimizing such matches.

This paper fulfills an urgent research need to study how brands and influencers should produce sponsored videos to achieve optimal outcomes.

The purpose of this paper is to examine how subjective characteristics of social network sites (SNSs) affect consumers' positive and negative word-of-mouth (WOM) sharing.

The data used for this study were obtained from an online survey with a sample size of 369 consumers. Structural equation modeling was performed to test hypotheses and examine the research questions.

The authors found that the perceived anonymity of an SNS is negatively correlated with its perceived interpersonal closeness of friends, and the number of friends in an SNS is positively correlated with its perceived interpersonal closeness of friends. With regard to positive WOM, the perceived anonymity of the SNS has a significant negative influence on consumers' WOM, and both perceived interpersonal closeness and the number of friends have a significant positive influence on consumers' WOM. But, in the case of negative WOM, only perceived interpersonal closeness of friends has a significant positive influence on consumers' WOM.

When attempting to promote positive WOM, marketers should choose consumers who possess the “right” subjective characteristics of SNSs (i.e. low anonymity, high interpersonal closeness of friends and a large number of friends). At the same time, marketers should monitor the emergence of consumers' negative WOM, especially those consumers who have a high level of interpersonal closeness of friends in SNSs, and respond to the content of negative WOM without delay.

This study investigates the influence that subjective characteristics of SNSs have on consumers' WOM sharing and therefore contributes to the literature on the antecedents of WOM generation and also contributes to the research that compares positive WOM with its negative counterpart.

This paper examines the employment relations (ERs) scenario in Indian organisations. The investigation is based on a questionnaire survey of 137 Indian firms in the manufacturing sector. The analysis of existing literature highlights the role of three key actors (management, unions, and the state) in the management of ERs in Indian organisations. It also shows the significant impact of the competitive pressures created by the liberalisation of the Indian economy in the changing nature of ERs in Indian firms. The study has key implications both for academicians and for practitioners.

The current study aimed to explore the extent of accounting graduates’ abilities (AGAs) in Jordan to use modern information technology systems (MITSs) to make optimal financial decisions (OFDs). To carry out this study, the descriptive analytical approach was used to collect and analyze data. Accordingly, an electronic questionnaire was designed and distributed to 5,000 students in 30 universities in Jordan. However, only 1,067 questionnaires were valid for analysis, which constituted the sample of study. To test the research hypotheses, the descriptive analysis and multivariate regression test were used. The results indicated that the majority of accounting graduates (AGs) in Jordanian universities (JUs) do not realize the importance role of MITSs to make OFDs. In addition, the biggest challenge face AGs in JUs is the weakness of current accounting curricula in JUs in terms of not including materials related to MITSs and the role of these systems in performing accounting tasks. Finally, the study found that the current abilities of AGs in JUs moderate negatively and significantly the positive relationship between the use of MITSs and making OFDs. Accordingly, the study recommended that JUs work on developing accounting curricula through including modern courses related to the use of MITSs in performing accounting tasks.

The purpose of this paper is to advocate an approach to leadership development to support the increasing trend of India‐based executives of multinational companies' (MNC) subsidiaries taking on global roles.

The paper defines distinctive competencies and recommends the alignment of individual development to the organization's evolution.

This approach enables leadership development efforts in MNC subsidiaries to focus on building a pipeline of leadership talent for the global organization.

The paper demonstrates that cultural intelligence, result orientation and thought leadership – the distinctive competencies required for a global career – can be built effectively on job opportunities that India‐based MNC subsidiaries provide.

The health crisis linked to COVID-19 has made digitization a significant issue for companies regardless of their form or geographical location. Our research focuses on the financial technology (Fintech) revolution in the context of international development. Its theoretical framework lies in both the fields of Fintech and factoring. As innovative start-ups that combine finance with new technologies, Fintechs have been able to disrupt the banking world in a few years by challenging its traditional practices. We use the case method to analyze two Fintech in-depth, and our results highlight the upheaval of Fintechs in the factoring sector. The supply of the analyzed Fintech is a limited working capital requirement. Furthermore, Fintechs may threaten classical banks due to the innovation of their offers and business models. However, the Fintech revolution focused on corporate finance is still in its infancy.

The contemporary business environment has been revolutionized by artificial intelligence (AI), which has undoubtedly impacted the operational and competitive strategies of small and medium-sized enterprises (SMEs). In this write-up, we delve into AI’s influence on SMEs by delving into the advantages, obstacles, and prospects associated with adopting AI technology. Based on an exhaustive analysis of current literature, this essay contends that SMEs can optimize their functions, enhance decision-making processes, and deliver superior customer experiences with the adoption of AI. However, SMEs face several challenges in embracing AI technology, including the high cost of implementation, lack of technical expertise, and concerns about data confidentiality and security. This chapter also illuminates prospective opportunities that SMEs can leverage through AI, such as establishing a foothold in new markets and competing effectively with larger enterprises. Overall, this chapter concludes that SMEs must carefully evaluate the costs and benefits of adopting AI, and develop a strategic plan for implementation that aligns with their business goals and resources.