Purpose This study aims to unlock the path of growth for sustainable economic development and accomplish the government's vision 2030 by ameliorating the productivity of the manufacturing sector in Laos. Design/methodology/approach This study applied cross-sectional data of 2,009 firms from the national firm survey, namely the Economic Census Survey (ECS), in 2012/13 in addition to employing the stochastic frontier analysis (SFA) to assess the production frontier and factors behind the technical inefficiency to arrive at policy recommendations. Findings The study found that the efficiency level varied across subindustries with an average of 72.51% in full potential production. Out of the five classified groups, Sub4 (chemical and plastic) was found to be the most efficient manufacturer, while the rest in order are Sub1 (food and beverage), Sub5 (furniture and others), Sub2 (garment and textile), and Sub3 (paper and printing), providing the evidence to improve the technical efficiency. This study discovered that the firm's size, accounting system and credit access are crucial to enhancing the production efficiency of all sampling firms. However, these factors might be subject to specific industries. Practical implications For the implication to the business community and policymakers, the findings of this study could be a reference in terms of which areas they should concentrate on to improve the technical efficiency as a part of productivity in the manufacturing industry. For instance, it suggests that firms could improve their production efficiency by introducing the accounting system, laborers' skills (education of managers) and engaging in international trade activities. Additionally, it asks policymakers to help private firms by improving the infrastructure, credit access, training and trade facilitation. Originality/value It is believed that, as the major contribution in Lao literature, this study is the first research applying the largest data from the national survey – the Lao ECS – examining the technical efficiency in the manufacturing sector in the country, and overcoming the gap of the previous research which recruited few policy variables and applied a small sample size in one specific industry. Therefore, the findings of this study impart more insights into the analysis, providing more effective and credible recommendations to policymakers and firms to improve their technical efficiency and, consequently, their competitiveness.

Purpose The purpose of this study is to examine the financial autonomy that affects the financial accounting information quality of public organizations. This study also tests the impact of the financial autonomy on support from leadership. How this impact has affected elements of accounting information systems such as hardware, software, communications technology and chief accountant to support providing the quality of the financial accounting information. Design/methodology/approach The research model is in the SEM form and measurement models are reflective scales so this study applies the PLS-SEM analysis technique on the Smart PLS 3.2.7 software to test the research hypotheses. Analytical data is collected through survey questionnaires with observed variables measured using the typical 7-point Likert scales. The result obtained after cleaning the data includes 164 Vietnamese public organizations with the different levels of the financial autonomy. Findings This research has three primary findings: firstly, FA has a positive direct effect on FAIQ and SL. Secondly, SL influences FAIQ through four mediate variables including AM, HW, SW and CN. Finally, SL also acts as a mediate variable in the relationship of FA and FAIQ. Originality/value This is one of the first empirical studies to examine the role of financial autonomy in leadership support to improve the quality of the accounting information in the public sector in the context of the Vietnamese government is promoting the financial autonomy of public organizations.

Purpose Financial health of a corporation is a great concern for every investor level and decision-makers. For many years, financial solvency prediction is a significant issue throughout academia, precisely in finance. This requirement leads this study to check whether machine learning can be implemented in financial solvency prediction. Design/methodology/approach This study analyzed 244 Dhaka stock exchange public-listed companies over the 2015–2019 period, and two subsets of data are also developed as training and testing datasets. For machine learning model building, samples are classified as secure, healthy and insolvent by the Altman Z-score. R statistical software is used to make predictive models of five classifiers and all model performances are measured with different performance metrics such as logarithmic loss (logLoss), area under the curve (AUC), precision recall AUC (prAUC), accuracy, kappa, sensitivity and specificity. Findings This study found that the artificial neural network classifier has 88% accuracy and sensitivity rate; also, AUC for this model is 96%. However, the ensemble classifier outperforms all other models by considering logLoss and other metrics. Research limitations/implications The major result of this study can be implicated to the financial institution for credit scoring, credit rating and loan classification, etc. And other companies can implement machine learning models to their enterprise resource planning software to trace their financial solvency. Practical implications Finally, a predictive application is developed through training a model with 1,200 observations and making it available for all rational and novice investors (Abdullah, 2020). Originality/value This study found that, with the best of author expertise, the author did not find any studies regarding machine learning research of financial solvency that examines a comparable number of a dataset, with all these models in Bangladesh.

Purpose This study investigates the impact of derivatives as risk management strategy on the value of Malaysian firms. This study also examines the interaction effect between derivatives and managerial ownership on firm value. Design/methodology/approach The study examines 200 nonfinancial firms engaged in derivatives for the period 2012–2017 using the generalized method of moments (GMM) to establish the influence of derivatives and managerial ownership on firm value. The study refers to two related theories (hedging theory and managerial aversion theory) to explain its findings. Firm value is measured using Tobin's Q with return on assets (ROA) and return on equity (ROE) as robustness checks. Findings The study found evidence on the positive influence of derivatives on firm value as proposed by the hedging theory. However, the study concludes that managers less hedge when they owned more shares based on the negative interaction between derivatives and managerial ownership on firm value. Hedging decision among managers in Malaysian firms therefore does not subscribe to the managerial aversion theory. Research limitations/implications This study focuses on the derivatives (foreign currency derivatives, interest rate derivatives and commodity derivatives) and managerial ownership that is deemed relevant and important to the Malaysian firms. Other forms of ownership such as state-/foreign owned and institutional ownership are not covered in this study. Practical implications This study has important implications to managers and investors. First is on the importance of risk management using derivatives to increase firm value, second, the influence of derivatives and managerial ownership on firm value and finally, the quality reporting on derivatives exposure by firms in line with the required accounting standard. Originality/value There is limited empirical evidence on the impact of derivatives on firm value as well as the influence of managerial ownership on hedging decisions of Malaysian firms. This study analyzes the influence of derivatives on firm value during the period in which reporting on derivatives in financial reports is made mandatory by the Malaysian regulator, hence avoiding data inaccuracy unlike the previous studies on Malaysia. This study therefore fills the gap in the literature in relation to the risk management strategies using derivatives in Malaysia.

Purpose This study aims to pinpoint gaps in the literature on corporate governance and remuneration by producing a comprehensive bibliometric review for the period 1990–2020. Design/methodology/approach Bibliometric analysis is the quantitative study of the bibliographic material in a specific research field. It allows an analyst to classify that material by paper, journal, author, indexation, institution or country, among other possibilities. This study reviews a total of 298 Web of Science–indexed journal articles on corporate governance and top-management remuneration schemes. Findings The authors find five distinct research strands: (1) firm performance and remuneration of top management, (2) the remuneration and independence of boards of directors and the efficiency of boards of directors as a governance system, (3) outside-director remuneration and the efficiency of outside directors as a monitoring system, (4) director remuneration and the corporate governance of companies and (5) the role of ownership structure and top managers' compensation schemes as corporate-governance tools. The authors identify gaps in the literature and avenues for future research for each of these strands. Practical implications The authors’ findings have implications for board diversity (e.g. gender diversity), remuneration policy for top-level managers and governance issues (independent directors, separation of ownership with control). This study is the only one to summarize the key topics on which top research has been focused and can be broadly used for corporate governance management perspective. Originality/value This paper provides an overview of how the literature on corporate governance and remuneration has developed and a synopsis of the most influential and most productive authors, countries and journal sources. It creates an opportunity for other researchers to focus on this area. This study will also serve as a foundation for future meta-analyses.