Government Public Policy, Regulatory Intervention, and Their Impact on IPO Underpricing: The Case of Malaysian IPOs

This study examines the impact of government initial public offering (IPO) regulation intending on promoting public policy. The study examines the results of the implementation of a Malaysian government policy in 1976, which mandated that at least 30 percent of any new shares on an IPO offer be sold to the indigenous Bumiputera population or to mutual funds owned by them. The study examined the short-run and long-run underpricing of Malaysian IPOs and found that Malaysian IPOs are highly underpriced compared to IPOs in developing countries, creating a market microstructure effect. It also confirmed that the Malaysian government's regulatory intervention in spite of noble public policy intentions appeared to be the significant factor for the emergence of an average first-day underpricing increase of Malaysian IPOs by 61 percent during the period after the regulatory economic policy was instituted. Furthermore, the study found that this high underpricing persists even for the long run, in contrast to the long-run performance of IPOs in the United States.     

Transparency and empowerment in an investment environment

In a laboratory-controlled environment we provide experimental evidence on the effects of transparency (complete over incomplete information) and empowerment on trust and trustworthiness. We implement a simple version of the standard two-person investment game in a repeated game context with multiple treatments under two information environments. We find that when principals are empowered by being able to penalize agents who may not act in a way the principal believes is in the principal's best interest, the level of trust and investment increases over that which is realized in the absence of empowerment regardless of the degree of transparency. In transparent environments the effect of empowerment is about the same regardless of whether empowerment is introduced or removed. However, in opaque environments, the loss of empowerment has a substantially greater negative effect on trust than the positive effect associated with the introduction of empowerment.     

Owner liability and financial reporting information as predictors of firm default in bank loans

We examine the effects of owner liability and non-accounting and financial accounting information on the probability of default as defined in Basel II in bank loan contracted by non listed firms. We model default as a function of owner liability and accounting and non-accounting information of non-listed firms, drawing on 43,117 annual accounts of 16,029 firms over a 7-year period. Our estimations based on mixed logistic regressions with random parameters show that the predicted default probability of full-liability firms is 0.72 times that of limited liability firms. The likelihood ratio test for omitted variables confirms the additional predictive ability of liability status over and above other non-accounting and financial accounting information. A Heckman self-selection model does not indicate sampling bias. The particular definition of default used in the study enables the findings to be generalizable across other institutional contexts.     

The exit decision in the European venture capital market

This article analyses the exit decision in the European venture capital market, studying when to exit and how it interacts with the exit form. Using a competing risks model we study the impact on the exit decision of the characteristics of venture capital investors, of their investments and of contracting variables. Our results reveals that the hazard functions are non-monotonic for all exit forms and suggest that, in Europe, Initial Public Offering candidates take longer to be selected than trade sales. Moreover our results show that, in Europe, venture capitalists associated with financial institutions have quicker exits (stronger for trade sales), and highlight the importance of contracting variables on the exit decision. An unexpected result is that the presence on the board of directors leads to longer investment durations.     

Attitudes to pay systems:an exploratory study within and across cultures

The present study investigates employees’preferences for criteria that are used in pay systems, namely, performance, cost of living, tenure, educational qualification, collective bargaining, skill, market rate, responsibility and special demands. The study also explored variation and similarities of employees’preferences for the criteria across four countries, namely Australia (N = 162), Indonesia (N = 100), Malaysia (N = 129) and Hong Kong (N = 39). The results indicate that the respondents prefer multiple criteria to determine their pay. Preferences for length of service and educational attainment were found to be significantly different across countries, particularly between Australian and Asian samples (Indonesian and Malaysia). This variation is, in part, attributed to cultural differences. Other variables, such as age, educational qualification, position, and industry sector, have been found to be significant correlates of preference for pay systems. Implications for reward management have been discussed.     

Measuring and explaining the efficiencies of the United Arab Emirates banking system

Using newly collected data from a survey distributed to all banks in the United Arab Emirates (UAE), this article measures economic efficiency in the banking industry, namely allocative, technical, pure technical and scale efficiency. Employing a nonparametric Data Envelopment Analysis (DEA) approach, the study estimates the efficiency for a cross section of the UAE banks in 2004. The results indicate that the dominant source of inefficiency in the UAE banking is stemming from allocative inefficiency rather than technical inefficiency. Furthermore, the main source of the relatively small size, technical inefficiency in the UAE banking industry is not the scale inefficiency but rather pure technical inefficiency. The results further indicate that the UAE banks are able to use their input resources more efficiently when they have more branches, and that newer banks are performing better than older banks on average. Moreover, the results also show that short experiences of employees affect efficiencies negatively and government ownership tends to reduce efficiency (as the government shares increase in the bank, the efficiency scores get lower). Finally, the most interesting results have to do with finding higher average efficiencies in banks that employ more women, more managers and less national citizens of the UAE.     

Assessing the impact of cost optimization based on infrastructure modelling on CO2 emissions

Traditionally, logistics design is driven by a need to reduce costs and improve customer service. Recently, the environmental concerns from transport have been increasingly discussed. The traffic levels and associated energy consumption are influenced by supply chain structure, modal split and vehicle utilization. This paper aims to assess the impact of the traditional cost optimization approach to strategic modelling on overall logistics costs and CO₂ emissions by taking into account the supply chain structure (number of depots) and different freight vehicle utilization ratios (90%, 75% and 60%). The simulation model, based on a European case study from the automotive industry, considers strategic and operational level decisions simultaneously. The analysis shows that the optimum design based on costs does not necessary equate to an optimum solution for CO₂ emissions, therefore there is a need to address economical and environmental objectives explicitly as part of the logistics design.     

An enhanced approach for Trend Impact Analysis

Decision makers in governments, corporations and institutions all need to forecast the future. Usually, traditional quantitative forecasting techniques are applied for this purpose. But the limitation of such methods is well known since all quantitative methods that are built solely on historical data (whether time-series or causal methods) produce forecasts by extrapolating such data into the future ignoring the effects of unprecedented future events that could cause deviation from the original surprise-free forecast if they were to occur. In the meanwhile, pure qualitative methods that don't utilize historical data miss its sound foundation. In the field of future studies, attempts are often made to combine quantitative and qualitative approaches using various hybrid methods such as Trend Impact Analysis. This paper introduces an advanced algorithm to enhance Trend Impact Analysis that adds another level of sophistication to the current algorithm. This advanced algorithm takes into account not only the impact of unprecedented future events' occurrences on the future trend, but also the different severity degrees with which the event might occur. This idea of severity degrees is novel, and its implementation is the main contribution of this paper.