Search results

In this study the authors examine the nature and contents of key audit matters (KAMs), and the consequences of KAMs reporting on audit quality in the context of a developing country, Bangladesh. The authors’ proxies of audit qualities are discretionary accruals, small positive earnings surprise, audit report lag, earnings management via below the line items and audit fees.

The authors use content analysis of the KAMs for the period 2018–2021 to understand the nature and extent of KAMs reported by auditors in Bangladesh. The authors then use multivariate regression analysis to examine the effect of the number and content characteristics of KAMs on audit quality by using multivariate regression analysis.

Auditors in Bangladesh disclose a higher number of KAMs compared to other countries, disclose short descriptions of KAMs and industry generic KAMs. The authors document significant cross-sectional variations in the number and content characteristics of KAMs reported by auditors in Bangladesh. The authors’ pre-post analysis suggest that audit quality has improved after the adoption of KAMs. Cross-sectional analysis suggests that KAMs number and content characteristics are related to audit quality.

The authors’ findings imply that the KAMs reporting has the potential to play significant monitoring role in reducing the opportunistic behavior of managers. Hence, KAMs reporting can play a significant role in reducing the agency problem. For regulators, shareholders and corporate managers, the authors’ findings imply that if the audit quality is to be increased, the audit effort should be supported by an appropriate amount of audit fee.

The content characteristics of KAMs significantly influence managerial reporting behavior and affect the level of audit efforts.

Unlike developed countries (Gutierrez et al., 2018; Lennox et al. 2022), this study supports that KAMs reporting improves audit quality and control opportunistic behavior of managers in developing countries. The authors show that even though the KAMs disclosure quality is poor, it has the potential to improve financial reporting quality.

This study enables one to critique the importance of adapting and innovating during challenging times to sustain and grow a business and also emphasizes the need for businesses to be flexible, resilient and willing to make necessary changes to stay relevant and thrive in dynamic and unpredictable environments.

In the competitive world of India’s quick-service restaurants industry, Shilpa Bhatt Bahuguna, the young entrepreneur behind “Pizza Italia,” aimed to secure the top spot in Uttarakhand. Despite facing setbacks by closing six out of the eight outlets during the COVID-19 pandemic, Bahuguna’s focus on product quality and localization had garnered word-of-mouth publicity for her brand. Now, with a limited budget for promotions, Bahuguna sought below-the-line strategies to ensure profitability and success for new outlets. Her determination to establish Pizza Italia as an indigenous brand and her plans for global expansion through franchising reflected her vision for growth and impact in the market. With her entrepreneurial spirit, Bahuguna remained poised to achieve even greater success in the future. Bahuguna aimed to leverage her product quality and word-of-mouth promotion to capture the market. She planned to expand her brand globally and open new outlets in Uttarakhand and London. However, Bahuguna was challenged to promote her brand on a limited budget, favoring “below-the-line” strategies.

This case study is appropriate for an undergraduate- or graduate-level program in marketing management.

Teaching notes are available for educators only.

CSS 11: Strategy

The purpose of this study is to explore and use artificial intelligence (AI) techniques for identifying the relevant attributes necessary to file a suspicious activity report (SAR) using historical customer transactions. This method is known as predictive modeling, a statistical approach which uses machine learning algorithm to predict outcomes by using historical data. The models are applied to a modified data set designed to mimic transactions of retail banking within the USA.

Machine learning classifiers, as a subset of AI, are trained using transactions that meet or exceed the minimum threshold amount that could generate an alert and report a SAR to the government authorities. The predictive models are developed to use customer transactional data to predict the probability that a transaction is reportable.

The performance of the machine learning classifiers is determined in terms of accuracy, misclassification, true positive rate, false positive rate and false negative rate. The decision tree model provided insight in terms of the attributes relevant for SAR filing based on the rule-based criteria of the algorithm.

This research is part of emerging studies in the field of compliance where AI/machine learning technology is used for transaction monitoring to identify relevant attributes for suspicious activity reporting. The research methodology may be replicated by other researchers, Bank Secrecy Act/anti-money laundering (BSA/AML) officers and model validation analysts for BSA/AML compliance models.

The paper aims to examine agrochemical traders’ tax morale in three Ghanaian regions.

Primary data were collected from 92 respondents using structured questionnaires. A multistage sampling technique was employed and used in selecting respondents.. Descriptive statistics, factor analysis and quantile regression analysis were used to analyse data obtained via the questionnaires.

The study found tax reporting knowledge, tax calculating knowledge and tax payment knowledge to be the keen factors influencing agrochemical traders’ tax knowledge. It was also revealed that age, religion and marriage positively influence the tax morale of traders. Inversely, gender, high level of education and monthly sales were found to affect tax morale negatively. Moreover, trust (respect, trustworthiness and expertise knowledge) negatively influenced tax morale. Authorities’ tax knowledge and power (sanction and lockdown) were revealed to impact tax morale positively. However, tax morale decreases amongst agrochemical traders with higher tax morale when sanction increases.

Unlike previous studies which focussed on tax morale amongst individuals and firms outside the agribusiness sector, this study examined the tax morale within the informal agrochemical trading sector, which has recently attracted colossal patronage due to the high usage of agrochemicals amongst farmers in Africa and Ghana. This study also assumed tax morale to be at different levels; hence the factors that affect the morale at different levels differ. Therefore, the study examined the factors influencing tax morale amongst agrochemical traders by segregating tax morale into quartiles. Relating to theory, the economic deterrence theory was used to ground the study, which is not usually used in most tax morale studies.

This study aims to examine whether the newly available auditor tenure information is associated with non-GAAP earnings, as the recent requirement to disclose the initial year of auditor-client relationship in audit reports may give the impression that longer auditor tenure may be related to lower audit quality.

Using a sample of firm-quarters from 2017 to 2020, the authors conduct both univariate and regression analyses. We use hand-collected data for auditor tenure, SEC comment letters, and non-GAAP variables.

First, the authors find that the likelihood of disclosing non-GAAP earnings monotonically increases with auditor tenure on a univariate basis. Second, auditor tenure is negatively associated with aggressive non-GAAP reporting. Third, the authors document evidence of aggressive reporting in general; that is, items excluded in calculating non-GAAP earnings are associated with future performance. However, the association declines with longer auditor tenure. Finally, the authors report evidence that the likelihood of receiving an SEC comment letter that contains non-GAAP comments decreases with longer auditor tenure.

The results show that regulators need to consider both GAAP and non-GAAP disclosures’ costs and benefits when enacting auditor tenure regulation. Investors can benefit from the findings in evaluating the quality of non-GAAP earnings. The findings are also relevant to the SEC when allocating limited resources in monitoring non-GAAP reporting.

To the best of the authors’ knowledge, this is the first study showing that auditor tenure is associated with the quality of non-GAAP earnings. Given that financial reporting quality should be understood as a comprehensive system comprising both mandatory and voluntary disclosures, this study complements the literature that examines the effect of auditor tenure on financial reporting quality using GAAP reporting.

This study aims to explore the relationship between principals’ performance on the Pennsylvania Framework for Leadership evaluation tool and the corresponding self-reported degree of self-efficacy and growth mindset.

The data analysis involved linear regression of principal performance on principals’ mindset, moral leadership self-efficacy and instructional self-efficacy scores. Additionally, correlation matrices identified the presence and direction of relationships between self-efficacy levels and the degree of growth mindset reported by principals.

The results demonstrated a positive association between principals’ instructional self-efficacy reports and their overall performance evaluation. Alternatively, both growth mindset and moral leadership self-efficacy evidenced a negative association. There was no association reflected between growth mindset and either the overall self-efficacy measure or the sub-scale self-efficacy measures. A secondary relationship revealed a negative association between school performance profile and growth mindset. This relationship held true in subsequent regression analyses.

The study adds to the limited research available on examining the relationship between principals’ self-efficacy levels and their performance ratings on a common tool.

The purpose of our study is to study the impact of chief executive officer (CEO) optimism and narcissism on the company's capital structure.

(1) The authors opt for regression, machine learning and text analysis to explore the impact of narcissism and optimism on the capital structure. (2) We analyze CEO interviews and employ three methods to evaluate narcissism: the dictionary proposed by Anglin, which enabled us to assess the following components: authority, superiority, vanity and exhibitionism; count of first-person singular and plural pronouns and count of CEO photos displayed. Following this approach, we were able to make a more thorough assessment of corporate narcissism. (3) Latent Dirichlet allocation (LDA) technique helped to find the differences in the corporate rhetoric of narcissistic and non-narcissistic CEOs and to find differences between the topics of interviews and letters provided by narcissistic and non-narcissistic CEOs.

Our research demonstrates that narcissism has a slight and nonlinear impact on capital structure. However, our findings suggest that there is an impact of pessimism and uncertainty under pandemic conditions when managers predicted doom and completely changed their strategies. We applied various approaches to estimate the gender distribution of CEOs and found that the median values of optimism and narcissism do not depend on sex. Using LDA, we examined the content and key topics of CEO interviews, defined as positive and negative. There are some differences in the topics: narcissistic CEOs are more likely to speak about long-term goals, projects and problems; they often talk about their brand and business processes.

First, we examine the COVID-19 pandemic period and evaluate how CEO optimism and pessimism affect their financial decisions under specific external conditions. The pandemic forced companies to shift the way they worked: either to switch to the remote work model or to interrupt operations; to lose or, on the contrary, attract clients. In addition, during this period, corporate management can have a different outlook on their company’s financial performance and goals. The LDA technique helped to find the differences in the corporate rhetoric of narcissistic and non-narcissistic CEOs. Second, we use three methods to evaluate narcissism. Third, the research is based on a set of advanced methods: machine learning techniques (random forest to reveal a nonlinear impact of CEO optimism and narcissism on capital structure).

The purpose of this study is to examine the impact of the marketing mix, customer perceptions, and religion on the buying decision of Islamic banking products in an emerging market namely the United Arab Emirates (UAE).

This study adopts a quantitative approach to analyze the data of 435 respondents collected through an online survey during January–February 2022. Data analysis of direct and moderating relationships are done through Smart PLS (partial least squares) using structural equation modelling (SEM) technique.

The results indicate that marketing mix (product, price, place and promotion) and customer perceptions have a positive direct relation with the buying decision of Islamic banking products in the UAE. However, moderation analysis shows that religion is a non-significant moderator for the above relationships.

This study combines potential variables from the perspectives of marketing, human mindset, and individual beliefs. The findings of this study provide a wider understanding of consumer behavior toward Islamic banking products. Marketers of the Islamic banking industry can utilize these findings for effective market segmentation and well-crafted marketing strategies. This will ultimately contribute to the sustainable growth and development of the Islamic banking industry in the UAE and other regions.

Aligning corporate communications through different information sources is a great challenge for marketers, especially those operating in the tourism sector, which has been harshly affected by the recent COVID-19 pandemic. This paper provides a deep analysis of the implementation of seven basic principles of the integrated marketing communications (IMC) paradigm in a crisis situation.

In-depth interviews with tourism and hospitality service providers were conducted in the fourth quarter of 2021 in Croatia, a destination that showed remarkable results in terms of the number of international tourist arrivals during the pandemic.

Most firms successfully transitioned from tactical to strategic IMC implementation. Some problems were reported in the coordination of communication tools and channels. Whereas the use of digital technology was enhanced, database management did not receive sufficient attention. Message clarity represented the greatest challenge, while consumer-centric communication was the most neglected principle. Relationship building was pursued mainly through B2B rather than B2C communication, whereas brand equity development pursued through communication mix mostly focused on increases in awareness, perceived quality and attitudinal loyalty.

This research is qualitative in nature and provides opinions on IMC adoption from the managerial perspective only.

This paper provides guidelines for the successful integration of marketing communications (marcom) in an extremely ambiguous and uncertain environment.

The contribution of this work lies in the proposal of a new refined and expanded theoretical framework of IMC principles and numerous marcom strategies for operating during the COVID-19 pandemic, thus providing relevant implications for academia and industry.