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Educators in the accounting discipline are faced with the challenge of finding innovative ways to accommodate the flexible learning styles of Millennial students, using “in classroom/contact time” effectively and decreasing transactional distance between students and educators in large classes. In an attempt to address these challenges, this paper aims to describe the implementation of basic e-learning tools (podcasts, vodcasts and voice-over-PowerPoint) as supplementary and substitutional tools in an undergraduate taxation curriculum. The tools were implemented as part of a student-centred approach to the facilitation of learning, embedded in the Blended Learning Theory. The paper reports on students’ use and experience of various basic e-learning tools, as well as the impact of the use of these tools on student performance.

An action research methodology was followed, and data were collected by way of a voluntary, descriptive student survey and student class lists. A total of 387 students completed the survey.

Students appear to have access to devices and data to use e-learning tools. They perceive these tools as helpful study aids and prefer synchronous, substitutional tools. Use of the tools does not have a significant impact on performance; however, it does appear to have a positive impact on the learning environment and student engagement.

The results of the study may be of benefit to educators and curriculum designers who are responsible for reviewing and updating the content delivery methods of undergraduate taxation curricula in large classes with diverse student populations. These results add to the limited body of knowledge on the implementation of basic e-learning tools in a South African accounting education setting.

Positioned within a framework of challenges facing universities, this paper aims to focus on challenges faced by teachers of accounting as a business discipline to ensure it remains relevant in a fast-moving and changing environment.

Drawing on a variety of sources, this paper explores a number of issues surrounding teaching and learning in the current university environment. The seven papers that make up the special issue are located within a framework which is used to illustrate how each one contributes to the field. This paper is primarily discursive in nature.

The theoretical, methodological and empirical approaches used in the papers that make up this special issue are described. In addition, the paper suggests that to remain relevant, teaching and learning will remain an important area for future research.

This paper on teaching and learning is of interest to accounting teachers and researchers, university managers and members of the accounting profession.

This special issue provides a range of examples of research relevant to teaching and learning and sets an agenda for future research.

Individual students have different learning styles, and lecturers can no longer afford to ignore this. Lecturers have a responsibility to accommodate students’ different learning styles by including learning style flexibility in the offered learning opportunities. The purpose of this study is to map a teaching case study against the Herrmann Whole Brain® model to determine whether learning style flexibility has been incorporated in the teaching case study.

A teaching case study was developed and delivered as part of an undergraduate level course at a South African residential university. The case study’s primary intention was to illustrate the practical evaluation of general controls in an information technology environment. The teaching case study was analysed in terms of the Herrmann Whole Brain® model to determine whether learning style flexibility had been accommodated in the learning opportunity.

Based on an analysis of the teaching case study against the Herrmann Whole Brain® model, it is evident that the teaching case study incorporated activities that addressed all four quadrants of the Whole Brain® model. It can therefore be concluded that the learning opportunity incorporated learning style flexibility.

This paper contributes to the literature in accounting education by focusing on learning style flexibility specifically using the Herrmann Whole Brain® model, as it appears that limited examples of the use of this model in accounting education have yet been published. Although this paper discusses the use of an auditing case study, the results may be of interest to lecturers in other subject areas across the academic spectrum.

This paper aims to focus on the thinking styles of a group of Accounting students, and to determine whether team teaching by two criteria-specific lecturers can be an effective collaborative teaching approach to accommodate students’ diverse learning preferences. Research on thinking and learning processes led to a four-quadrant whole-brain model of people’s thinking styles and associated learning preferences. The model can be used to identify and accommodate students’ diverse thinking styles and learning preferences.

A case study approach was followed, using multiple data collection methods. The thinking styles of 288 students and two lecturers were surveyed using a thinking style questionnaire and the Herrmann Brain Dominance Instrument. The results of the collaborative teaching approach were obtained by way of a survey questionnaire providing both quantitative and qualitative feedback, as well as a SWOT analysis completed by the involved lecturers.

The main results suggest that a collaborative teaching approach can address students’ diverse learning preferences, although some students may find constant switching between lecturers distracting.

The collaborative teaching approach in the teaching interaction cannot be isolated. Collaborative teaching was not repeated or extended due to resource constraints.

Academics from all disciplines recognise a need for a teaching practice that addresses students’ diverse learning preferences. Hitherto, outside of special education, collaborative teaching has received little scholarly attention, especially as an approach to address tertiary students’ diverse learning preferences.

This paper aims to describe how the COVID-19 pivot to online teaching enabled a student-produced podcast assessment to be created and substituted for the final examination in an MBA accounting course.

This paper provides instructors’ reflections and feedback from students on the usefulness of podcasts as an assessment tool in accounting education. Also included are the assignment instructions and a marking rubric which can be adapted as a sharing network.

The pivot to the authentic podcast assessment proved to be a very positive outcome during COVID-19 for instructors and students. The students embraced and enjoyed the task, and importantly it was an efficient learning experience that connected theory to practice, while preserving authenticity.

Podcasts have grown in popularity and have been widely used with students as receivers. The accounting education literature is however devoid of instances where podcasts have been used as an assessment tool. Although the assessment was changed because of the COVID-19 pandemic, it has ongoing applicability as a useful assignment in future semesters.

The gradual increase in geriatric issues and global imbalance of the ratio between patients and healthcare professionals have created a demand for intelligent systems with the least error-prone diagnosis results to be used by less medically trained persons and save clinical time. This paper aims at investigating the development of image-based colourimetric analysis. The purpose of recognising such tests is to support wider users to begin a colourimetric test to be used at homecare settings, telepathology and so on.

The concept of an automatic colourimetric assay detection is delivered by utilising two cases. Training deep learning (DL) models on thousands of images of these tests using transfer learning, this paper (1) classifies the type of the assay and (2) classifies the colourimetric results.

This paper demonstrated that the assay type can be recognised using DL techniques with 100% accuracy within a fraction of a second. Some of the advantages of the pre-trained model over the calibration-based approach are robustness, readiness and suitability to deploy for similar applications within a shorter period of time.

To the best of the authors’ knowledge, this is the first attempt to provide colourimetric assay type classification (CATC) using DL. Humans are capable to learn thousands of visual classifications in their life. Object recognition may be a trivial task for humans, due to photometric and geometric variabilities along with the high degree of intra-class variabilities, it can be a challenging task for machines. However, transforming visual knowledge into machines, as proposed, can support non-experts to better manage their health and reduce some of the burdens on experts.

This study aims to investigate the risk-return trade-off in the Indian equity market at both the aggregate equity market level and in the cross-sections of stock return using alternative risk measures.

The study uses weekly and monthly data of 3,085 Bombay Stock Exchange-listed stocks spanning over 20 years from January 2000 to December 2019. The study evaluates the risk-return trade-off at the aggregate equity market level using the value-weighted and the equal-weighted broader portfolios. Eight different risk proxies belonging to the conventional, downside and extreme risk categories are considered to analyse the cross-sectional risk-return relationship.

The results show a positive equity premium on the value-weighted portfolio; however, the equal-weighted portfolio of these stocks shows an average return lower than the return on the 91-day Treasury Bills. The inverted size premium mainly causes this anomaly in the Indian equity market as the small stocks have lower returns than big stocks. The study presents a strong negative risk-return relationship across different risk proxies. However, under the subsample of more liquid stocks, the low-risk anomaly regarding other risk proxies becomes moderate except the beta-anomaly. This anomalous relationship seems to be caused by small and less liquid stocks having low institutional ownership and higher short-selling constraints.

The findings have important implications for investors, managers and practitioners. Investors can incorporate the effects of different highlighted anomalies in their investment strategies to fetch higher returns. Managers can also use these findings in their capital budgeting decisions, resource allocations and other diverse range of direct and indirect decisions, particularly in emerging markets such as India. The findings provide insights to practitioners while valuing the firms.

The study is among the earlier attempts to examine the risk-return trade-off in an emerging equity market at both the aggregate equity market level and in the cross-sections of stock returns using alternative measures of risk and expected returns.

The novel coronavirus (COVID-19) has caused financial stress and limited their lending agility, resulting in more non-performing loans (NPLs) and lower performance during the II wave of the coronavirus crisis. Therefore, it is essential to identify the risky factors influencing the financial performance of Indian banks spanning 2018–2022.

Our sample consists of a balanced panel dataset of 75 scheduled commercial banks from three different ownership groups, including public, private and foreign banks, that were actively engaged in their operations during 2018–2022. Factor identification is performed via a fixed-effects model (FEM) that solves the issue of heterogeneity across different with banks over time. Additionally, to ensure the robustness of our findings, we also identify the risky drivers of the financial performance of Indian banks using an alternative measure, the pooled ordinary least squares (OLS) model.

Empirical evidence indicates that default risk, solvency risk and COVAR reduce financial performance in India. However, high liquidity, Z-score and the COVID-19 crisis enhance the financial performance of Indian banks. Unsystematic risk and systemic risk factors play an important role in determining the prognosis of COVID-19. The study supports the “bad-management,” “moral hazard” and “tail risk spillover of a single bank to the system” hypotheses. Public sector banks (PSBs) have considerable potential to achieve financial performance while controlling unsystematic risk and exogenous shocks relative to their peer group. Finally, robustness check estimates confirm the coefficients of the main model.

This study contributes to the knowledge in the banking literature by identifying risk factors that may affect financial performance during a crisis nexus and providing information about preventive measures. These insights are valuable to bankers, academics, managers and regulators for policy formulation. The findings of this paper provide important insights by considering all the risk factors that may be responsible for reducing the probability of financial performance in the banking system of an emerging market economy.

The empirical analysis has been done with a fresh perspective to consider unsystematic risk, systemic risk and exogenous risk (COVID-19) with the financial performance of Indian banks. Furthermore, none of the existing banking literature explicitly explores the drivers of the I and II waves of COVID-19 while considering COVID-19 as a dependent variable. Therefore, the aim of the present study is to make efforts in this direction.

Enhanced revenue mobilization is essential in developing countries such as South Africa. However, it is inevitably a complex process, both from economic and political perspectives. Increasing the rate of value-added tax (VAT) has been identified as one option to increase tax revenue, although the likely effect of VAT rate changes on tax compliance behaviour is undetermined. This study considers the impact of such a change on the tax compliance behaviour of small business entities. In order to address the impact of VAT rate changes on tax compliance behaviour, a between-subjects pre-test/post-test online field experiment was conducted and designed to identify the implications of rate changes of various directions and magnitude.

Statistical analysis of the data obtained from the experiment indicated that small business entities are inclined to reduce the VAT liability when there is an increase in the VAT rate, and to do so by overstating purchases rather than under-declaring sales. This leads to an increase in non-compliance. The greater the magnitude of the VAT rate increase, the greater the level of non-compliance. In contrast, no significant relationships were identified between a decrease in the VAT rate and tax compliance.

Consumer knowledge has been one of the most studied variables in marketing due to its strong influence on consumer behaviour. Knowledge level has traditionally been measured through objective knowledge and the number of correct answers in a battery of items about product characteristics. The authors argue that this analysis could be complemented with other information, that is, the structure of non-knowledge. The main objective of this work is to explore the nature and explanatory potential of this new dimension on consumer behaviour in the agrifood context. The principal hypothesis is that, while they may have similar levels of objective knowledge, there are significant differences between the behaviour of consumers who have a predominant pattern of ignorance (tendency to answer “I don't know”) and those who are in error (tendency to give wrong answers).

The present study draws on data derived from five case studies examining consumer knowledge about agrifood products (olive oils, Iberian ham and orange juice) and certain aspects of consumer behaviour. A sample of 4,112 participants was classified into two non-knowledge profiles: wrong, if most items answered incorrectly in a questionnaire were wrong; or ignorant, if most items answered incorrectly were “don't know”.

The results obtained supported the argument that complementing the study of consumer knowledge with an analysis of the structure of non-knowledge is worthwhile, as differences within the structure are associated with different patterns of consumer behaviour.

In the present study, it is proposed that the measurement of knowledge be complemented with an analysis of the consumer's non-knowledge structure (items not answered correctly), given its effects on behaviour, an aspect hitherto unconsidered in the literature. To do so, a new index is proposed.