Capital structure of multinational and domestic corporations – a cross‐country comparison

This study investigates whether the determinants of capital structure between multinational corporations (MCs) and domestic corporations (DCs) vary across Australia, U.S., Japan, U.K. and Malaysia. Results show (i) the debt holding capacity and majority of the explanatory factors vary between DCs and MCs and also across countries; (ii) Australia, Japan, U.K. and Malaysian MCs hold significantly less long‐term debt relative to U.S. firms; (iii) DCs and MCs that operate under an imputation tax system hold significantly less short‐ and long‐term debt; and (iv) DCs and MCs operating under common law have significantly less short‐term debt and significantly higher long‐term debt.     

Corporate Governance and Ethics: A Feminist Perspective

The mainstream literature on corporate governance is based on the premise of conflicts of interest in a competitive game played by variously defined stakeholders and thus builds explicitly and/or implicitly on masculinist ethical theories. This article argues that insights from feminist ethics, and in particular ethics of care, can provide a different, yet relevant, lens through which to study corporate governance. Based on feminist ethical theories, the article conceptualises a governance model that is different from the current normative orthodoxy.     

Covid-19 and heuristic biases: evidence from India

Stock markets worldwide have witnessed high volatility during the year 2020 owing to the eruption of Covid-19. Due to the world’s unprecedented economic challenges, this study could potentially guide financial advisors and individual investors in dealing with pandemics. An association between investors’ perception toward the intensity of Covid-19 and heuristic biases is analyzed using the responses of 290 stock investors of National Capital Region (NCR), India. The data are validated through Cronbach’s alpha, and the model fit is analyzed using EFA. Confirmatory factor analysis (CFA) is employed to investigate the relationship between Covid-19 and heuristic biases. Covid-19 does not have any influence on the overconfidence of investors. A significant positive relationship is found between Covid-19 and the remaining three heuristics, i.e., availability, anchoring, and representativeness. The present study analyzes the association between Covid-19 and specific investors’ bias only and should not be interpreted for causality. The study has the potential to guide investors in understanding the errors they are making while investing during the pandemic and the ways to deal with them. The study could provide insights to the financial advisors in understanding their customers. The implications of the study may include inputs of the errors committed by them during the pandemic. Despite the fact that an enormous amount of literature exists in the field of investors’ sentiment, a scarcity of literature is available that measures the relationship between heuristic biases and the perceived impact of the pandemic. The current study attempts to fill this gap in the literature.

     

The use of an online learning and teaching system for monitoring computer aided design student participation and predicting student success

In this paper we report on the use of a purpose built Computer Support Collaborative learning environment designed to support lab-based CAD teaching through the monitoring of student participation and identified predictors of success. This was carried out by analysing data from the interactive learning system and correlating student behaviour with summative learning outcomes. A total of 331 undergraduate students, from eight independent groups at the University of Surrey took part in this study. The data collected included: time spent on task, class attendance; seating location; and group association. The application of ANOVA and Pearson correlation to quantized data demonstrated that certain student behaviours enhanced their learning performance. The results indicated that student achievement was positively correlated with attendance, social stability in terms of peer grouping, and time spent on task. A negative relationship was shown in student seating distance relative to the lecturer position. Linear regression was used in the final part of this study to explore the potential for embedding predictive analytics within the system to identify students at-risk of failure. The results were encouraging. They suggest that learning analytics can be used to predict student outcomes and can ensure that timely and appropriate teaching interventions can be incorporated by tutors to improve class performance.     

Effects of the workplace social context and job content on nurse burnout

Job burnout is a continuing concern for human resource management, as it affects employee productivity and well‐being. In particular, the nursing profession is widely recognized as a stressful occupation that leads to burnout. The present study examines the relative significance of workplace social context in a health care setting and the job content of the nursing profession for influencing the three dimensions of job burnout: emotional exhaustion, depersonalization, and personal accomplishment (Maslach & Jackson, 1981). Data were collected through a questionnaire survey of a random sample of 1,190 nurses working in 43 public hospitals in Hong Kong. The results indicate that although both the workplace social context and job content have significant effects on burnout dimensions, the effects of the workplace social context were significantly stronger. In addition, the workplace social context had a significant negative effect on personal accomplishment, whereas job content influenced personal accomplishment positively. Implications of these findings are discussed in the context of devising management interventions for dealing with job burnout in the nursing profession. © 2011 Wiley Periodicals, Inc.     

The mixed attribute model in SFAS 133 cash flow hedge accounting: implications for market pricing

In this study, we examine the pricing of cash flow hedge adjustments reported in other comprehensive income (OCICF), under the mixed attribute model in SFAS 133 Accounting for Derivative Instruments and Hedging Activities. Our OCICF pricing investigation integrates empirical research on the derivatives use that gives rise to such mark-to-market adjustments with the accounting information pricing literature. Based on this integration, we generalize mispricing theory for the SFAS 133 mixed attribute model and predict both the direction and magnitude of OCICF pricing. Screening on U.S. multinationals with ex ante exposure to currency risk, we provide evidence of OCICF mispricing in the expected direction, consistent with the notion that SFAS 133 cash flow hedge accounting results in a mixed attribute problem (Gigler et al. in J Account Res 45:257–287, 2007). Moreover, we find that both OCICF gains and losses are inversely related to future cash flows and of the expected magnitude, consistent with our predictions based on valuation theory (for example, Ohlson in Rev Account Stud 4:145–162, 1999). Our results support the Financial Accounting Standards Board’s concern that the SFAS 133 mixed attribute model does not provide the information necessary for investors to understand the net economic effects of derivatives use (FASB in Accounting for financial instruments and revisions to the accounting for derivative instruments and hedging activities. FASB, Norwalk, 2010).     

Risk,return and mean‐variance efficiency of Islamic and non‐Islamic stocks: evidence from a unique Malaysian data set

We find that Islamic stocks are more mean–variance efficient than non‐Islamic stocks and the market because they reduce risk of the same level of returns. We combine a unique Malaysian data set of individual Islamic stocks (as opposed to aggregate stock indices) since 1997 with a new method where we apply Islamic business activity and financial ratio screens to the universe of Malaysian stocks. Both data sets show that Islamic stocks have an annualised standard deviation that is on average 3.43–3.78 percent points lower compared to non‐Islamic stocks. This lower variance of Islamic stocks is exclusively driven by financial ratio screens.