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After completion of the case study, the students will be able to understand the calculation of cost of individual sources of funds and cost of capital, examine various tools such as economic value added and cash value added analyses which help determining whether a company has added value to its shareholders or not and explore the application of Benford’s law and the Beneish M-score in detecting manipulation of numbers in financial statements.

Nimmy Jacob, a newly recruited research analyst with an equity research firm, was entrusted with tracking the “auto ancillary industry”, specifically “Minda Corporation Ltd” (MIL). MIL was a leading diversified auto components manufacturing companies in India. The company’s share price meteorically rose during February 2021–2022 (Figure 1). The company’s turnover over the past few years had grown at a compounded annual growth rate of 15% during the three preceding years. The company had in the recent past bought a 15% stake in another competitor, Pricol Ltd, for a consideration of INR 400 crores and previously had used joint ventures and acquisitions to scale up its operations. Jacob, apart from the conventional financial analysis, had to ascertain whether all the strategic decisions were adding value to the shareholders’ investments by exploring the various tools available for the same and also calculate the minimum expected rate of return for MIL. Jacob was apprehensive about the financial statements, although the numbers for the company were good. Jacob was skeptical about a high-growth company having the incentive to manipulate its earnings. Manipulations could be in the form of abnormal increase in accruals, inconsistency in expenses and high days of receivables. Therefore, Jacobs used certain analytics/statistical tools to detect any manipulation of numbers in the financial statements of the company and to ascertain apt findings about the company.

This case study is intended for discussion in corporate finance, financial reporting and analysis and financial analytics at Master of Business Administration/undergraduate level.

Teaching notes are available for educators only.

CSS1: Accounting and finance

This paper aims to discuss the effect of Canada’s regulatory framework on the strategies of entrepreneurial businesses during the first phase of legalization of the recreational cannabis industry. Decriminalization of cannabis required a host of regulatory changes at the federal, provincial and municipal levels. Each province developed legal markets independently, differentially impacting entrepreneurial strategies. This paper describes the value chain that emerged in the first phase of the nascent industry, focusing on the actions of the businesses.

The authors develop a qualitative narrative analysis using government publications, press articles (especially from the business press) and personal communications of industry insiders speaking in public settings. The paper includes four short case studies to illustrate the emerging value chain of the nascent industry.

The study’s findings highlight the effect of regulatory frameworks on entrepreneurial strategies. We find that public policies had a significant impact on entrepreneurs and startup strategies. Inter-jurisdictional differences limited expansion into different provinces, with implications for regional economic development. Achieving public policy goals was delayed as a result of regulatory challenges that impacted industry development.

The authors’ findings show enterprises may develop growth strategies that comply with regulations when participating in nascent industries, but they must cope with extra risks, capital costs and uncertainty. The analysis also illustrates the value of engaging in government-industry collaboration to improve emerging regulatory frameworks.

The originality of this research consists of the detailed description of the first phase of Canada’s legalized recreational cannabis industry and the insight gained into the dynamics of nascent industries.

This paper aims to investigate the causal inferences between mobile application adoption and changes in travelers’ purchasing behavior regarding services supported by the travel and tourism industry.

Using a quasi-experiment conducted by an airline, data sets from more than 10,000 travelers were collected, and hypotheses were tested using propensity score matching and difference-in-difference methods.

Mobile application adoption has a significant positive effect on the total purchasing frequency of services and a significant adverse effect on booking tickets in advance and purchasing frequency from self-owned websites. Besides, this finding also suggested that members or travelers who had high average purchases in the past tend to buy more air tickets on average after mobile application adoption, while the number of days to book tickets in advance and purchase auxiliary services declined after mobile application adoption. However, males purchased more auxiliary services via mobile applications.

The study is based on the causal effect of mobile application adoption on purchasing behavior. Nevertheless, the theoretical basis remains relatively weak. Furthermore, the underlying mechanisms that cause the changes in purchasing behavior via mobile applications need to be elucidated.

This study enriches the hospitality and tourism literature on mobile application adoptions, multichannel purchasing behavior and revenue management. First, a quasi-experimental design is used to verify a causal relationship between mobile applications’ adoption and travelers’ purchasing behavior in the travel and tourism industry. Second, this study adds to examining travelers’ multichannel purchasing behavior in the travel and tourism industry. Third, this work enriches the current literature that explores auxiliary services and revenue management in the travel industry.

Mobile application adoption significantly impacted the travel and tourism industry. Besides, To the best of the authors’ knowledge, this is one of the first empirical studies that examined changes in purchasing behavior due to mobile application adoption from the perspective of service type. The findings provide the first evidence of the impact of mobile application adoption on service purchasing in the travel industry.

This study aims to conduct text mining and semantic network analysis of muscle-supportive and posture-corrective wearable robots for the elderly to understand key terms related to the topic and to identify considerations for developing these types of clothing.

The authors searched and identified the key terms wearable robot, muscle-supportive, posture correction and elderly using the text-mining software Textom to extract terms as well as the network analysis software UCINET 6 to process and visualize the relationships among the terms. The authors compared and analyzed the term frequency (TF), the TF-inverse document frequency and the degree centrality of the terms, and the authors visualized and summarized the terms using NetDraw.

The key terms and their relationships in 3–4 groups were identified: wearable robot, muscle-supportive, posture correction and elderly. The authors identified the aspects of designing muscle-supportive and posture-corrective wearable robots for the elderly.

This study contributes to the field of muscle-supportive clothing and wearable robotics by deriving insights into what people are discussing and interested in, and by offering recommendations when developing these types of clothing for the elderly.

Frontline workers (FLWs) constitute a critical part of the implementation cadre within public policies, serving a significant role in the last-mile delivery of public goods and services. FLWs under public programs in low and middle-income countries like India are offered different compensation structures that range from full-time salaries, piece rate honorariums, contractual engagements, to no remuneration. Whilst the rationale for offering different compensations vary, are certain structures more successful in encouraging FLWs to perform a prosocial task? Further, can certain structures encourage FLWs to perform beyond the incentivized policy mandate?

Investigating workers' prosocial effort within policy implementation, the authors conducted a randomized lab-in-the-field inquiry with 344 Anganwadi-based workers (workers under the nutrition policy) in western India. These FLWs were engaged to perform a novel real-effort task that was tied to different incentive structures and their performance was adjudged based on measurable quantity, effort and quality parameters.

Results demonstrate that uncompensated workers invest the greatest amount of effort whilst compromising on task quality, and vice-versa for subjects receiving pay-for-performance compensation. Programs must account for policy focus when offering compensations: volunteer engagement may be counterproductive for quality focus and to the adherence to ancillary task mandates like nature/quality of beneficiary interaction. On the other hand, the distribution of products (like health goods) can rely on volunteer effort.

The study brings together various compensation schemes operating at the field level, under one study using an LFE methodology within the context of policy implementation in India.

Medical disruptive innovation is essential for deepening the reform of health-care system. The theory of general disruptive innovation assumes that innovations can diffuse by benefiting and attracting consumers through observed and objective relative advantages. Yet decision-makers for adoption in health-care settings are safety-sensitive professionals whose cognitions barriers about underperformance in focal attributes will impede further evaluation of innovation's ancillary performance. Existing studies do not answer the question of how such innovations can overcome safety barriers, find early adopters and grow to the early majority. The purpose of this study is to investigate the process, mechanism, and path of early diffusion of medical disruptive innovation.

The authors conduct a longitudinal case study of the diffusion of Enhanced Recovery After Surgery (ERAS) in China during 2011–2018.

The authors find that the diffusion process of medical disruptive innovations can be viewed as a cognitive evolutionary process that sequentially establishes conformity, differentiation and normalization. Cognition reframing of expert, meaning and benefit for professionals is its implicit mechanism. When adoption may trigger cognitive concerns, actors’ very early (dis)adoption is driven by a combination of structural position, innovation attributes and performance perceptions; central actors then play amplifier roles in the development from early adopters to the early majority.

This study proposes a process theoretical framework for the early diffusion of disruptive innovation. By dissecting the key processes and mechanisms from a cognitive perspective, the study offers theoretical contributions and practical insights into the diffusion of disruptive innovation in professional settings.

The surge in pharmaceutical and health supplement usage among consumers aims to enhance personal well-being. This growing opportunity for pharmaceutical brands has resulted in increased market share and intensified industry competition. Using the theory of planned behaviour (TPB), this study aims to identify the factors influencing Malaysians’ choices regarding pharmaceutical and health supplements. In addition, the variable of past behaviour was incorporated to account for consumer decisions based on prior experiences.

Using purposive sampling, 300 questionnaires were gathered and analysed via Statistical Package for the Social Sciences and structural equation modelling technique via Analysis of Moment Structures software to validate the reliability of each variables and the postulated relationships within the research framework.

Results revealed a pronounced impact of past behaviour on the intention to consume pharmaceutical and health supplements. The mediating role of perceived behavioural control in bridging past behaviour and consumption intention was also ascertained. Notably, the findings support the inclusion of past behaviour in the TPB as a pivotal determinant of intention.

The insights gleaned underscore the escalating trend of pharmaceutical consumption in Malaysia, providing strategies to enhance and maintain the competitive edge and market position of pharmaceutical brands.

TourAmerica is negotiating a master contract with Voyager Inn International (Bethesda) for hotel rooms during the 1995 tourist season. Issues under consideration include number of rooms during peak, mid-, and off-periods, room rates, breakfast prices, and the cost of ancillary services. While the hotel manager is evaluated on the basis of several criteria, including adjusted daily rates, occupancy rates, and food and beverage profitability, and is also provided with a utility scheme to facilitate trade-offs among the criteria, TourAmerica uses an effective cost per registrant (adjusted for intangibles). These two approaches provide an opportunity to contrast measurement schemes and to justify the use of utility functions. This case is a role-play exercise and must be used in conjunction with “Voyager Inn International” (UVA-QA-0463).

This paper presents the findings from the assessment of the determinants of cloud computing (CC) deployment by construction organisations. Using the technology-organisation-environment (TOE) framework, the study strives to improve construction organisations' project delivery and digital transformation by adopting beneficial technologies like CC.

This study adopted a post-positivism philosophical stance using a deductive approach with a questionnaire administered to construction organisations in South Africa. The data gathered were analysed using descriptive and inferential statistics. Also, the fusion of structural equation modelling (SEM) and machine learning (ML) regression models helped to gain a robust understanding of the key determinants of using CC.

The study found that the use of CC by construction organisations in South Africa is still slow. SEM indicated that this slow usage is influenced by six technology and environmental factors, namely (1) cost-effectiveness, (2) availability, (3) compatibility, (4) client demand, (5) competitors' pressure and (6) trust in cloud service providers. ML models developed affirmed that these variables have high predictive power. However, sensitivity analysis revealed that the availability of CC and CC's ancillary technologies and the pressure from competitors are the most important predictors of CC usage in construction organisations.

The paper offers a theoretical backdrop for future works on CC in construction, particularly in developing countries where such a study has not been explored.