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By reading and understanding this case study, students are expected to: 1.Able to understand and review the impact of unethical practices from accounting perspective; 2.Able to make an analysis of how one unethical act triggers a series of forced unethical acts (ripple effect); 3.Identify the unfair practices as well as be proactive in preventing unfair practices in the business day to day affairs; 4.Able to relate the function of various ratios (current ratio, quick ration, debt to asset ratio, debt to equity ratio etc.) and its impact on the business performance; and 5.Able to apply various lean quality tools, doing the root cause analysis in identifying and solving problems.

T.M. Exports (TME) was an India-based privately owned and operated enterprise. The company had a brilliant employee named Sanjay, who was a 12-year veteran. TME’s Business Intelligence (BI) department at TME head office, Kanpur, India, ostensibly learned on April 8, 2019, from the rumors about a brand-new vehicle dished out to Sanjay by his friend who made fortune worth of millions from certain transactions. To add fuel to the fire, another incident surfaced concerning a warehouse keeper, Mohit, who was also involved in embezzlement in one of the sales offices. On May 16, 2019, BI reported these two incidents to the internal auditor who launched an internal investigation to get to root of this case. Consequently, the company owner, Tariq Mahmood got himself caught up in a dilemma to fire both Sanjay and Mohit only or restructure the organization for better transparency and integrative approach in future. Moreover, the newly appointed Chief Executive Officer had the dilemma of keeping high safety stock to maximize service level or keeping conservative safety stock and rely on-spot market-buying if demand spiked. He decided and instructed all the warehouses to keep higher inventories to meet the forecasted demand, considering unexpected spikes in demand witnessed historically. Thus, increase in inventory caused panic in the sales department as demand was sluggish. He, therefore, offered high discounted prices to liquidate the stock. This study integrated the theories of accounting/financial ratio metrics, accounts reconciliation, business ethics and lean tools. It was demonstrated in this case that the irregularities in sales accounting and their inability of reconciliation had a serious impact on business performance. The concept of total reward was also invoked to understand the disruptive and unscrupulous practices.

This case has been particularly focused on undergraduate and postgraduate early-stage-level students pursuing business or commerce program, particularly those specializing in accounting (sales accounting) and human resource management courses.

Teaching notes are available for educators only.

CSS 1: Accounting and Finance.

Digital skills change management skills problem solving skills.

Al-Rumman Pharma is headquartered in Dubai, is an integrated international pharmaceutical company providing a wide range of pharmaceutical solutions to manufacture high quality and affordable generic medicines. It holds credibility amongst healthcare professionals and patients, across the Middle East and North African (MENA) markets. Their quality assurance is fostered by high levels of reliability and order fulfillment, which differentiates them from their competitors. Recently, they have been facing technology fatigue meant as an organization suffering from overwhelming options and choices in technology, this contributes to turbulent and confused states of mind when considering technology adaptation. This case evolves specifically from a procurement perspective, the pressure of high expectation and severe compliance clauses from key suppliers, particularly large corporations with monopolies in supplies who have the tendency to dominate and dictate terms to the small and medium enterprises (SMEs). For example, forcing SME’s to adopt specific technological frameworks to be trade partners. Another conflict is that while the SME’s do value the contribution of the procurement function, the shift from tactical to strategic mindset is not robust enough. Is this a dilemma? Ms Mary buyer at Al-Rumman Pharma, which is SME in operation, is facing challenges from key suppliers because of her tactical buying approach and adoption of multiple technological frameworks from various key suppliers, which are neither integrated nor compatible with each other. Her transition from traditional buying to a more strategic sourcing approach is what the need of the hour is. Prior information technology role was more as support at Al-Rumman Pharma and Chief Executive Officer Dr Mubeen Ahmad Khan did technology adopted decisions in isolation but today the company needs an integrative approach with forward thinking and also kept the legacy intact. Resistance to change was very inevitable once it was integrated.

This case has been particularly focused on undergraduates in the final semester of management courses, as well as masters level students specializing in supply chain and operation management courses. It is also for practitioner procurement and supply chain managers going for various supply chain management related certification courses. Students who have studied procurement management are most suitable to accomplish this case study. Executives pursuing a business program are also recommended to study this case.

Teaching Notes are available for educators only.

CSS 9: Operations and logistics.

Heat transfer characteristics of a non‐Newtonian fluid on a power‐law stretched surface with suction or injection were investigated. Similarity solutions of the laminar boundary layer equations describing heat transfer flow in a quiescent fluid were obtained and solved numerically. Temperature profiles as well as the Nusselt number Nu, were obtained for two thermal boundary conditions; namely, uniform surface temperature (b=0) and cooled surface temperature (b=–1), for different governing parameters such as Prandtl number Pr, injection parameter d and power‐law index n. It was found that decreasing injection parameter d and power‐law index n and increasing Prandtl number Pr enhanced the heat transfer coefficient.

This study aims to measure the acceptance of digital resources by integrating knowledge management (KM) factors (i.e. acquisition, sharing, application and protection) into the factors of the technology acceptance model (TAM) (i.e. perceived ease of use and perceived usefulness) and their impact on actual system use through behavioural intention.

Using the quantitative research method, a survey was conducted of the public sector universities of Punjab, Pakistan. Data were collected from postgraduate students and analysed using partial least squares structural equation modelling.

The findings showed that the factors of KM with the integration of TAM significantly impact the acceptance of digital resources. The study’s hypotheses are all supported, and the findings demonstrated that knowledge acquisition, knowledge sharing, knowledge application and knowledge protection significantly influenced perceived usefulness and perceived ease of use, and that these factors are positively correlated with behavioural intentions to use digital resources.

This study has considerable significant implications for policymakers, developers and practitioners in designing digital resources. This study will also assist librarians to discover areas for development that may enhance the use of digital resources among users

Since December 2019, global attention has been drawn to the rapid spread of COVID-19. Corona was discovered in India on 30 January 2020. To date, in India, 178,014 disease cases were reported with 14,011 deaths by the Indian Government. In the meantime, with an increasing spread speed, the COVID-19 epidemic occurred in other countries. The survival rate for COVID-19 patients who suffer from a critical illness is efficiently and precisely predicted as more fatal cases can be affected in advanced cases. However, over 400 laboratories and clinically relevant survival rates of all present critically ill COVID-19 patients are estimated manually. The manual diagnosis inevitably results in high misdiagnosis and missed diagnosis owing to a lack of experience and prior knowledge. The chapter presents an option for developing a machine-based prognostic model that exactly predicts the survival of individual severe patients with clinical data from different sources such as Kaggle data.gov and World Health Organization with greater than 95% accuracy. The data set and attributes are shown in detail. The reasonableness of such a mere three elements may depend, respectively, on their representativeness in the indices of tissue injury, immunity and inflammation. The purpose of this paper is to provide detailed study from the diagnostic aspect of COVID-19, the work updates the cost-effective and prompt criticality classification and prediction of survival before the targeted intervention and diagnosis, in particular the triage of the vast COVID-19 explosive epidemic.

Automated machine learning (ML) provides resources and platforms to render ML available to non-ML experts, to boost efficiency in ML and to accelerate research in machine learning. H2O AutoML is used to generate the results (Dulhare et al., 2020). ML has achieved major milestones in recent years, and it is on which an increasing range of disciplines depend. But this performance is crucially dependent on specialists in human ML to perform the following tasks: preprocess the info and clean it; choose and create the appropriate apps; choose a family that fits the pattern; optimize hyperparameters for layout; and models of computer learning post processes. Review of the findings collected is important.

These days, the concept of automated ML techniques is being used in every field and domain, for example, in the stock market, education institutions, medical field, etc. ML tools play an important role in harnessing the massive amount of data. In this paper, the data set relatively holds a huge amount of data, and appropriate analysis and prediction are necessary to track as the numbers of COVID cases are increasing day by day. This prediction of COVID-19 will be able to track the cases particularly in India and might help researchers in the future to develop vaccines. Researchers across the world are testing different medications to cure COVID; however, it is still being tested in various labs. This paper highlights and deploys the concept of AutoML to analyze the data and to find the best algorithm to predict the disease. Appropriate tables, figures and explanations are provided.

As the difficulty of such activities frequently goes beyond non-ML-experts, the exponential growth of ML implementations has generated a market for off-the-shelf ML solutions that can be used quickly and without experience. We name the resulting work field which is oriented toward the radical automation of AutoML machine learning. The third class is that of the individuals who have illnesses such as diabetes, high BP, asthma, malignant growth, cardiovascular sickness and so forth. As their safe frameworks have been undermined effectively because of a common ailment, these individuals become obvious objectives. Diseases experienced by the third classification of individuals can be lethal (Shinde et al., 2020). Examining information is fundamental in having the option to comprehend the spread and treatment adequacy. The world needs a lot more individuals investigating the information. The understanding from worldwide data on the spread of the infection and its conduct will be key in limiting the harm. The main contributions of this study are as follows: predicting COVID-19 pandemic in India using AutoML; analyzing the data set predicting the patterns of the virus; and comparative analysis of predictive algorithms. The organization of the paper is as follows, Sections I and II describe the introduction and the related work in the field of analyzing the COVID pandemic. Section III describes the workflow/framework for AutoML using the components with respect to the data set used to analyze the patterns of COVID-19 patients.

This paper aims to address essential questions regarding social entrepreneurial intentions. Do traits such as perceived social impact, social worth and social network influence, social entrepreneurial intentions among the young populous generation of Pakistan? To get a deeper insight, this paper further raises questions regarding the relationship of these predictors and social entrepreneurial intentions with empathy which is considered as a key determinant and a distinguishing trait to become a social entrepreneur.

This paper involves a quantitative research design using a partial least square structural equation modeling approach to measure the effects of the structural model. For this, a cross-sectional survey was conducted with a purposive sample of 247 university students from Pakistan.

Results showed a positive relationship between antecedents and social entrepreneurial intentions. Overall analysis exhibited social worth as a dominant trait and social network as the least influencing trait to impact social entrepreneurial intentions.

It will help micro and macro-level policymakers including government officials and NGOs and educators to create awareness and provide support and encouragement to individuals who aim to initiate social enterprise.

The present study makes significant contributions to the social entrepreneurship literature, as it is one of the first academic studies on social entrepreneurial intentions in Pakistan. This paper enriches the theoretical foundation by assessing the influence of perceived social impact, social worth and social network on social entrepreneurial intentions. Also, the relationship of Empathy with each of these antecedents is examined for the first time in the social entrepreneurial intentions context which is a valuable contribution both theoretically and practically.

The purpose of this paper is to examine the effect of measures to combat Corona Virus Disease 2019 (COVID-19) pandemic on competitiveness in tourism in Nigeria taking strategic dexterity as the moderating variable.

Survey research design approach was used for the study. A total of 235 valid questionnaires gathered from the personnel of ten urban tourist centres in Nigeria were used to examine the goodness of model fit, measurement model and structural correlations between constructs. Partial least squares structural equation modelling approach (PLS-SEM) using Advanced Analysis for Composite (ADANCO 2.2.1) was used to evaluate the hypotheses.

This study finds that travel restriction, boarder closure and strategic dexterity were significant to competitiveness, among which border closures has generated the highest path coefficient. Moreover, the study finds a significant moderating role of strategic dexterity between travel restrictions, border closure and competitiveness. Future studies can reproduce the study by incorporating mediating variables covering the all-tourist centers in Nigeria.

This study might be valuable for tourism-related stakeholders, researchers and policy makers as the result finds indicate strong effect of travel restrictions, border closure on competitiveness of urban tourism. Equally, the study provides new insight as the findings shows a significant moderating role of strategic dexterity between travel restrictions, border closure and competitiveness.

This study might be valuable for tourism-related stakeholders, researchers and policy makers as the result finds indicate strong effect of travel restrictions, border closure on competitiveness of urban tourism. The study provides new insight as the findings shows a significant moderating role of strategic dexterity between travel restrictions, border closure and competitiveness.

This study is among the few that analyses the effect of measures to combat COVID-19 pandemic on competitiveness in the urban tourism: strategic dexterity as the moderating variables. This study also contributes methodologically through the introduction of PLS-SEM approach.

The concept of Islamic banking (IB) as a discipline and the introduction of the full-fledged Islamic banks and Islamic windows are relatively newer developments in the banking sector in Oman. This paper aims to assess customers’ perceptions of the Islamic banks and IB windows in Oman.

Following the interpretive paradigm and an exploratory research design, data collected through personal interviews with a group of 60 respondents in two of the prominent cities in Oman were analysed qualitatively.

The study found that customers in Oman had mixed feelings about the Islamic Banks. While some of them were not sure if the banks follow the Islamic principles, a majority of them had not opened an account with the Islamic banks or Islamic windows. The study revealed some vulnerabilities in the areas of their operations, marketing practices, staff knowledge of products and customer-dealings, as well as customers’ understanding of Islamic banks, their principles and practices.

As the advent of IB is relatively new to Oman, the insights gained by this study will have wider implications for the growth of IB locally. The outcomes of this study would appraise the officials and regulators of Islamic banks and Islamic windows with customers’ perception of IB. The elimination of the identified weaknesses would help them to improve the knowledge, quality and the marketing and promotion of products and services while competing with the conventional banks.

This study is a pioneering effort to know the status of IB and customers’ motivations in Oman towards IB.

The aim of this study is to provide an insight to international readers into the perspective of doctoral level research in Pakistan. The factors which led to the start of this program and difficulties encountered in this regard at different universities are discussed.

The study is mainly based on review of the literature. Research theses approved at MPhil and PhD level are evaluated. Some information collected from Library and Information Science (LIS) schools through personal communication is also provided.

The problems that did not allow success in the doctoral programs in LIS were: lack of encouragement by seniors in a real sense; low esteem for indigenous PhD degree in the eyes of fellow professionals; little or no impact of early recipients of the degree on profession; and non‐availability of financial assistance to the prospective candidates. Of the findings mention is made of: no fixed criteria for admission; the research topics do not concern the problems; and absence of proper supervision/guidance resulting in poor quality of thesis in most cases. Suggestions include: formation of a high level committee comprising senior library educators under the Higher Education Commission to work out problems and streamline the process; maintenance of close links with library schools in other countries, particularly in the English speaking world, which are interested in global librarianship.

This paper is the only evaluation of postmaster level LIS education in Pakistan. The findings are useful for planners of LIS education at postmaster level in Pakistan as well as in other developing countries.

Corporate social responsibility (CSR) promotes society, reduces risk, and encourages ethical business practices. Due to its relevance, we study how CSR influences firms' sustainable development. We analyze data from 427 New York Stock Exchange (NYSE)-listed firms from 2008 to 2022. The Refinitiv environmental and social score is used to measure CSR, whereas for firms' sustainable development we rely on corporate sustainable growth rate (SGR) and market-based metrics. The analysis employs various econometric techniques, including ordinary least square, fixed effect regression, two-stage least square, generalized method of moment, and simultaneous quantile regression. The results indicate that CSR has a positive and significant effect on firms' sustainable development across all models. This relationship supports the notion that socially responsible business can contribute to long-term financial sustainability in line with “stakeholder theory”, indicating that companies should accommodate the concerns of various stakeholders, including society and the environment, to achieve sustainable development. We evaluate how the conditional distributions of SGR and firms’ value are affected by CSR, categorizing them into high, moderate, and low regimes. The quantile regression estimates indicate that the effect of CSR is more pronounced at upper quantiles, followed by moderate and low regimes. These findings underscore the importance of considering CSR in assessing the SGR and enterprises market value. We also confirm that our results are robust under range of different econometrics' methods. Finally, we enlighten current literature, and our research has useful policy implications for management and investors.