Overconfidence and Resistance to Abandoning Unprofitable Capital Budgeting Projects: The Effects of Autonomy,Internal Audit,and Accountability

The purpose of this study is to investigate the effects of managers' autonomy in choosing a capital budgeting project has on their confidence in managing the project. Furthermore, this study examines the role that internal audit reports and accountability play in mitigating the impact of autonomy on managers' resistance to abandoning unprofitable capital budgeting projects. Building on motivated reasoning theory, we hypothesize and find that managers who are given autonomy to choose their own projects are more confident that their projects will be successful than managers who are assigned the projects by their superiors. This study also shows that internal audit reports and accountability are effective mechanisms for reducing the influence of prior decisions on managers' resistance to abandoning unprofitable projects.     

Improving collaboration between large and small-medium enterprises in automobile production

ABSTRACT

Inter-organisational collaboration is important for achieving qualitative and quantitative performance improvement in the global competitive environment. In particular, the extent of collaboration between the mother company and its suppliers is important for the profitability and sustainability of a company in the automobile industry, which is carried out using a customisation and order production system. As a result of the empirical analysis in this study, the collaborative information sharing cycle is shortened and the collaborative information sharing scope is widened. Therefore, the level of collaboration is improved by constructing an IT collaboration system.     

A network text analysis of published papers in service business, 2007–2017: research trends in the service sector

The service sector has become the most important part of the global economy. Thus, Service Business: An International Journal (SB) was launched in 2007 to deliver innovative studies that can provide resonating insights to researchers and practitioners in services. This study analyzed 311 articles published in SB during the past 10+ years (2007–2017) by conducting network text analysis (NTA). The published papers’ keywords link relations were analyzed to create network maps of research topics, ranging from traditional to emerging ideas of researchers. Influential research topics and their clusters were identified using centrality and community analyses. Research trends were identified for the first 5 years (Volume 1–5) and later years (Volume 6–11) separately through NTA. The results reveal interesting change in research topics over time. Common keywords of studies published in the first 5 years were: Service, Innovation, Customer, Strategy, Tourism, and Quality. The primary frequent keywords of articles published during 2012–2017 were: Customer, Quality, Satisfaction, Innovation, Mobile, and Technology. The results of the study shed valuable insights to the researchers and practitioners in the service sector. Applications of keyword network building and analysis methods provided in this study would be helpful to researchers who are interested in exploring trends of emerging new topics.     

How foreign direct investment affects CO2 emission levels in the Chinese manufacturing industry: Evidence from panel data

This study explores how inflows of foreign direct investment (FDI) affect a country’s carbon dioxide (CO₂) emission levels. To investigate this relationship, we use panel data (2002–2015) from the 28 subsectors of the Chinese manufacturing sector. We also perform panel framework analysis to verify the characteristics of the panel data before establishing the panel estimator meant to test the relationships between carbon dioxide emissions, FDI inflows, industrial GDP, industry openness, net domestic fixed capital stock and cleaner production. The results of the panel framework analysis suggest the need to eliminate dynamic panel bias and produce more efficient and consistent parameter estimates. To do so, we use System Generalized Method of Moments (GMM) estimators with time dummies. Ultimately, the results of the analysis show that FDI is a positive predictor of environmental quality in the host country, which serves as evidence of the halo effect that FDI reduces CO₂ emission levels. The study also finds evidence that industrial GDP and cleaner production improve environmental quality. However, the domestic capital stock has a negative effect on environmental quality. By showing that past carbon dioxide emissions significantly influence current emissions, our findings demonstrate the importance of consistency and persistence in efforts to reduce those emissions. Accordingly, we discuss some policy implications based on these results.     

Foreign currency borrowing surrounding the global financial crisis: Evidence from Korea

We present a complete profile of firms’ foreign currency borrowing surrounding the 2007 global financial crisis. Employing extensive data from Korean firms during 2002–2012, we find that foreign currency borrowing is significantly related to firm attributes of export revenues, firm size, tangible assets and asset growth, as well as to macro-level factors. These results offer two important implications. First, macroeconomic factors alone cannot fully explain firms’ foreign currency borrowing. Second and more importantly, these firm attributes are indicative of a lower default probability and larger collateral value, which would not only facilitate borrowers’ access to foreign currency debt markets but also offer lenders a better protective cushion from possible loan defaults in the face of exchange rate changes and information asymmetry on borrowers’ credits. Period wise, asset-related firm attributes have more pronounced effects in the post- than pre-crisis period. We further show that banking regulations following the crisis effectively limit the access to foreign currency borrowing by Korean firms, most significantly by those belonging to large business groups.     

On the complete monotonicity of the compound geometric convolution with applications in risk theory

We prove that the complete monotonicity is preserved under mixed geometric compounding, and hence show that the ruin probability, the Laplace transform of the ruin time, and the density of the tail of the joint distribution of ruin and the deficit at ruin in the Sparre Andersen model are completely monotone if the claim size distribution has a completely monotone density.     

Engaging Employees in Sustainable Development – a Case Study of Environmental Education and Awareness Training in Hong Kong

Environmental education and awareness training can help to develop and encourage a transition to a greener corporate culture. A series of environmental education and awareness training programmes of The Hongkong and Shanghai Banking Corporation Limited (HSBC) (Hong Kong) was used as a case study to assess how learning transfers through nature‐based environmental education and awareness training and to investigate the possible outcomes of providing nature‐based training to employees. Evaluation of the training outcomes, in terms of changes in employees’ environmental knowledge, attitudes and behaviour, was surveyed by using retrospective post‐ and then‐test questionnaires. Results showed that employees who joined these programmes gained knowledge and changed their values and behaviour towards the environment significantly. The study also indicated the establishment of trust in and satisfaction with the organization among employees through the training, which in turn promoted employees’ organizational commitment towards corporate sustainability. Copyright © 2015 John Wiley & Sons, Ltd and ERP Environment     

Empirical Analyses of Extreme Value Models for the South African Mining Index

While the classical normality assumption is simple to implement, it is well known to underestimate the leptokurtic behaviour demonstrated in most financial data. After examining properties of the Johannesburg Stock Exchange Mining Index returns, we propose two extreme value models to fit its negative tail with a higher degree of accuracy. The generalised extreme value distribution (GEVD) is fitted using the block maxima approach, while the generalised Pareto distribution (GPD) is fitted using the peaks‐over‐threshold method. Numerical assessment of value‐at‐risk (VaR) estimates indicates that both GEVD and GPD increasingly outperform the normal distribution as we move further into the lower tail. In addition, GEVD produces lower estimates relative to that of the historical VaR, and GPD provides slightly more conservative estimates for adequate capitalisation.