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This case study is related to start-up post-listing investment analysis. Through this case study, students will be able to perform the business analysis guided by the Venture Evaluation Metric tool, perform financial analysis using the discounted cash flow methods and perform investment analysis recommendation with justifications from the business and financial analysis performed above.

This case study sets out the study of a scalable start-up, Zomato, which is a successfully listed start-up firm in India. Despite the start-up development success in the pre-listing, the firm has exhibited a continuous unprofitable finance performance in the post-listing and has further experienced a volatile share price performance, both of which have puzzled existing and potential investors. In addition, some analysts are in the opinions that the firm share price valuation have been inflated with overvaluation since in the initial public offering stage and remain traded with overvaluation in the market. Notably, considering the negative indicators mentioned above, investors are concerned about long-term sustainability of the firm business and financial performance. In the context of post-listing investment, the following questions are material to investors: What is the realistic growth trajectory for Zomato in the medium term? What is Zomato’s share fair value in the medium term? Can one see opportunities or risks ahead of investing in Zomato’s shares? What will be the investment strategy for new investors?

This case study is suited to bachelor’s and master’s level in business schools studying entrepreneurial finance analysis.

Teaching notes are available for educators only.

CSS 1: Accounting and finance.

The purpose of this study is to investigate the extent to which a sample of the Australian cybersecurity industry is impacted by burnout.

Based on the review of the literature, this research investigates the following three hypotheses. Gender will significantly predict burnout scores. Those who identify as women will score higher on average than those who identify as men (because of being in a male-dominated industry). Self-reported burnout will differ across job roles. In addition, the authors expect these relationships to hold across the three dimensions of burnout, namely, emotional exhaustion, depersonalisation and professional efficacy. Sleep quality will be associated with burnout.

Gender and job role were significant predictors of emotional exhaustion, but not depersonalisation or professional efficacy. The interaction between gender and job role was also significant. Senior managers experienced poorer quality sleep, and poorer sleep quality was associated with greater reported emotional exhaustion at work. For emotional exhaustion, female respondents who worked in security consultant roles tended to score higher than their male counterparts.

Left unaddressed, the high level of workplace burnout may add to the well-being and retention problems developing within the cybersecurity community. These results indicate that organisations should look to measure the well-being of their own cyber workforce and implement meaningful changes if they wish to keep their cyber talent and enable them to thrive at work.

This research paper is an extension of a previous paper by the same authors which is titled “Is Your CISO Burnt Out Yet”. This paper examined the demographic differences in workplace burnout among cybersecurity professionals.

This research paper aims to empirically explore how stock market investors’ perceptions are affected by extreme climatic events like El Nino and floods in Malaysia.

This study uses structural equation modelling (SEM) to analyse the empirical data gathered through a questionnaire survey involving 273 individual investors from Bursa Malaysia between January and June 2019.

Results reveal that companies’ efforts, especially for agriculture and plantation-based industries, to adapt to climate change risk at the production, business and stock market levels significantly impact investors’ behaviour and investment decisions. Moreover, stock market investors’ climate change knowledge shows a significant moderating effect on corporate climate change adaptation initiatives and investors’ decisions to invest in Malaysian agricultural and plantation industry stocks.

This research has significant implications for practice and policy, as it measures the stock market investors’ level of awareness about climate change events and explores the companies’ strategies to reduce climatic risks to their business model.

This study shows the way to adjust the climate change information in the stock market investment decision to improve market efficiency and sustainable stock exchanges initiative.

To the best of the authors’ knowledge, this paper is the pioneer one to provide a comprehensive link between climate change events and business performances at production level, business level and stock market levels by drawing inferences from empirical data on investors’ behaviours. This study also added value in investment theories and financial literature by observing the climate change as an important factor to determine the investors’ decisions in the stock market.

This paper aims to explore the factors affecting cybersecurity implementation in organizations in various countries and develop a cybersecurity framework to improve cybersecurity practices within organizations for cybersecurity risk management through a systematic literature review (SLR) approach.

This SLR adhered to RepOrting Standards for Systematics Evidence Syntheses (ROSES) publication standards and used various research approaches. The study’s article selection process involved using Scopus, one of the most important scientific databases, to review articles published between 2014 and 2023.

This review identified the four main themes: individual factors, organizational factors, technological factors and governmental role. In addition, nine subthemes that relate to these primary topics were established.

This research sheds light on the multifaceted nature of cybersecurity by exploring factors influencing implementation and developing an improvement framework, offering valuable insights for researchers to advance theoretical developments, assisting industry practitioners in tailoring cybersecurity strategies to their needs and providing policymakers with a basis for creating more effective cybersecurity regulations and standards.

Career preparedness is critical to successfully transitioning from college to a full-time work environment. Being prepared means students have the technical and non-technical skills to help an organization meet its strategic goals. In many instances, students lack the requisite career competencies and collaborative skills. This study proposes designing an instructor-led, career-driven quasi-virtual internship to address this issue and improve students’ preparedness and teamwork.

Our research integrates and expands the four-step processes outlined in instructional and course redesign theories, including analysis, design and development, implementation and evaluation. In the evaluation phase, a survey is used to collect data, and natural language processing is applied to identify the emerging themes. The sample included 104 undergraduate students enrolled in an information systems degree program, which resulted in a digital corpus of 40,744 words for analysis.

Results indicate that the implementation of instructor-led quasi-virtual internships offered a comprehensive career experience comparable to an onsite or virtual company-sponsored internship in five notable areas: (1) application of technical knowledge, (2) critical thinking, (3) time management, (4) application of IT project management and (5) collaborative skills.

Our study only evaluated participants in our treatment group. Future research should examine the differences between students who complete sponsored versus instructor-led quasi-virtual internships. Researchers can add a control group of students who receive a theoretically based capstone course. Future research can simulate randomized controlled trials (RCT) (Chalmers et al., 1981) to measure the effectiveness of quasi-virtual internships. A benefit of this research is that an open-ended survey allows for collecting rich, multifaceted primary data. The second limitation is that the study included only single-item questions. Future authors can create and validate a survey instrument based on the themes and concepts emanating from our investigation. For example, they can operationalize team dynamics and career preparedness using a reflective model in which the underlying construct drives the indicators, requiring multiple items to examine each construct (Coltman et al., 2008). Third, the sample size in the study was relatively small. We can increase the sample size using a time-series dataset with multiple measurement periods. The fourth limitation is context; this study was conducted at a public university; other institutions may have varied teaching approaches, student demographics and resources. By expanding our study using a multi-site approach (Ballantyne et al., 2012), we can increase cross-sectional sample sizes and improve the generalizability of the study’s results.

This study provides several practical insights for educators by examining quasi-virtual internships. Academic institutions that want to offer internships but struggle to establish industry partners can implement the quasi-internship model as an alternative approach. The study highlights that students gain critical insight into their future careers during these internships by being familiar with industry concepts and tools. We also provide insights into engaging students in “meaningful collaboration.” We suggest the instructor provide some time during the class sessions for group work to improve coordination and introduce industry-level tools that provide a more applied approach to IS education.

The National Survey of College Internships (NSCI) 2021 indicates that underrepresented and first-generation students were less likely to participate in internships. Our research may positively impact diverse communities since the quasi-virtual internship allows all students to participate once they are enrolled in a capstone class.

To our knowledge, this study is the first to utilize latent semantic analysis to analyze students’ feedback to improve course design, career preparedness and team dynamics.

Considering the role of analysts in disseminating information, the paper explains the idiosyncratic volatility puzzle of China's stock market. As the largest developing country, China's research can provide meaningful reference for the research of financial markets in other new countries.

From the perspective of behavior, establishing a direct link between individual investor attention and stock price overvaluation.

The authors find that there is a significant idiosyncratic volatility puzzle in China's stock market. Due to the role of mispricing, individual investor attention significantly enhances the idiosyncratic volatility effect, that is, as individual investor attention increases, the greater the idiosyncratic volatility, the lower the expected return. Attention can explain the idiosyncratic volatility puzzle in China's stock market. In addition, due to the role of information production and dissemination, securities analysts can reduce the degree of market information asymmetry and enhance the transparency of market information.

China is the second largest economy in the world, and few scholars analyze it from the perspective of investors' attention. The authors believe this paper has the potential in contributing to the academia.

Findings in the literature indicate leading financial analysts attract high levels of market attention and provide more accurate earnings forecasts prior to becoming all-star analysts. Furthermore, these analysts significantly impact the investment decisions of other market participants and thus the market price of assets. Therefore, this study examines the information role of leading financial analysts and identifies two significant conclusions. First, the positive outcomes of these analyst leaders are more informative and attract more followers. Second, informational herding by followers of these analysts is not as naïve as suggested in previous studies, as followers who smartly use information from analyst leaders tend to perform better. We also find that analysts who practice smart learning by studying and selectively employing analyst-leader decisions achieve better career outcomes.

Surprisingly little is known of the various methods of security analysis used by financial analysts with industry-specific knowledge. Financial analysts’ industry knowledge is a favored and appreciated attribute by fund managers and institutional investors. Understanding analysts’ use of industry-specific valuation models, which are the main value drivers within different industries, will enhance our understanding of important aspects of value creation in these industries. This paper contributes to the broader understanding of how financial analysts in various industries approach valuation, offering insights that can be beneficial to a wide range of stakeholders in the financial market.

This paper systematically reviews existing research to consolidate the current understanding of analysts’ use of valuation models and factors. It aims to demystify what can often be seen as a “black box”, shedding light on the valuation tools employed by financial analysts across diverse industries.

The use of industry-specific valuation models and factors by analysts is a subject of considerable interest to both academics and investors. The predominant model in several industries is P/E, with some exceptions. Notably, EV/EBITDA is favored in the telecom, energy and materials sectors, while the capital goods industry primarily relies on P/CF. In the REITs sector, P/AFFO is the most commonly employed model. In specific sectors like pharmaceuticals, energy and telecom, DCF is utilized. However, theoretical models like RIM and AEG find limited use among analysts.

This is the first paper systematically reviewing the research on analyst’s use of industry-specific stock valuation methods. It serves as a foundation for future research in this field and is likely to be of interest to academics, analysts, fund managers and investors.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.

The purpose of the study is to identify the soft skills and abilities that are crucial to success in the fields of operations management (OM) and supply chain management (SCM), using the O*NET database and the classification of a set of professional figures integrating values for task skills and abilities needed to operate successfully in these professions.

The study used the O*NET database to identify the soft skills and abilities required for success in OM and SCM industries. Correlation analysis was conducted to determine the tasks required for the job roles and their characteristics in terms of abilities and soft skills. ANOVA analysis was used to validate the findings. The study aims to help companies define specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the job position.

As a result of the work, a set of soft skills and abilities was defined that allow, through correlation analysis, to explain a large number of activities required to work in the operations and SCM (OSCM) environment.

The work is inherently affected by the database used for the professional figures mapped and the scores that are attributed within O*NET to the analyzed elements.

The information resulting from this study can help companies develop specific assessments and tests for the roles of OM and SCM to measure individual attitudes and correlate them with the requirements of the job position. The study aims to address the need to identify soft skills in the human sphere and determine which of them have the most significant impact on the OM and SCM professions.

The originality of this study lies in its approach to identify the set of soft skills and abilities that determine success in the OM and SCM industries. The study used the O*NET database to correlate the tasks required for specific job roles with their corresponding soft skills and abilities. Furthermore, the study used ANOVA analysis to validate the findings in other sectors mapped by the same database. The identified soft skills and abilities can help companies develop specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the requirements of the job position. In addressing the necessity for enhanced clarity in the domain of human factor, this study contributes to identifying key success factors. Subsequent research can further investigate their practical application within companies to formulate targeted growth strategies and make appropriate resource selections for vacant positions.