Zhao Wu’s research while affiliated with University of Electronic Science and Technology of China and other places

This study examines computer based record keeping systems among small and medium sized enterprises (SMEs) in the Obuasi Municipality of Ghana. The study surveyed 200 SME owners or managers in the municipality with three years or longer operating history, using purposive random sampling. Furthermore, the study employed both open and closed-ended questionnaires, formal and informal interviews and desktop studies to gather information from owners and operators in SMEs. The interviews focused on record-keeping abilities, attitudes towards accounting, and the impact of record-keeping on business viability and stability. The findings show that SMEs typically use manual financial record keeping. However, daily sales books are the most common method. Nevertheless, most SMEs do not create financial reports using computerized systems, thereby negatively impacting their operations. Therefore, the study suggests that the National Board for Small Scale Industries (NBSSI) should collaborate with charitable NGOs to establish training opportunities that provide basic ICT skills and development programs to SMEs in other to improve their decision-making and overall performance.

As investors' knowledge on sustainability concerns rises, the concept and interest of sustainable investment continue to expand and become increasingly attractive as the global financial market is considered an effective and powerful tool in the process of developing sustainable economies. Although sustainability is not a new concept in the financial market, its recent recognition and wider adoption has increased as consumers, investors, businesses, and world leaders have become more sensitive and concerned about the future of the planet. Hence, this paper reexamines the impact of environmental, social, and governance (ESG) scores on the financial performance of the listed companies on the German Stock Exchange from 2011 to 2021. With a total of 450 listed firms and 4,950 observations sourced from the Refinitiv database, vector autoregressive (PVAR) together with the system-generalized method of moments (system-GMM) and robust panel multiple regression models were employed to examine the impact and causal relationship between ESG scores and corporate financial performance. The results suggest that ESG scores contribute to organizations' financial performance. We found that better ESG ratings increase companies' systematic risk (volatility), which could boost or increase their stocks' returns. The study however did not find Granger causality between ESG scores and the accounting-based financial performance (ROA), but it did for the market-based financial performance (Tobin's Q). It showed that ESG scores negatively Granger cause firms' financial performance. In a nutshell, organizations' financial performance may be improved by having a higher ESG score and performing better in the social dimension. Overall, the evidence supports the idea that a business case exists for sustainability and corporate social responsibility.

To better understand the actual rating variables that affects Auto insurance Policyholders’ premium, this paper attempts to provide empirical evidence to justify which ones are significant and needed to be considered by insurers by adopting the autoregressive distributed lag (ARDL) model. In satisfying all the conditions for ARDL application, unit root, Heteroskedasticity, normality, dynamic stability and serial correlation tests were conducted. We estimate the effects of each rating variable on Premium taking into consideration whether the policy of the insured is Third-Party or Comprehensive. These rating variables in the ARDL model serves as the independent variables that establishes the short and long-run relationships between them and the Premium as the dependent variable. The results suggest that not all the classical rating variables used in the market significantly impact Premium. Whiles, to some extent, we found a varying degree of variables impact on Premium depending on the insurance type, the autos cubic capacity, which plays a cogent role on the basic Premium in Ghana, is insignificant. Also, policyholders’ age characteristics are statistically significant but are excluded in the premium calculations. Thus, this paper shows the need to consider all the other possible rating variables, including policyholders’ age into the Ghanaian insurance pricing system, whiles autos cubic capacity considering the weight it put on the basic Premium should be re-examined. This would help to obtain a financially balanced and optimal pricing system for policyholders.

Loss distribution plays an influential role in evaluating risks from policyhold-ers' claims. Nevertheless, the auto insurance market in Ghana pays little attention to policyholders' claims distribution, resulting in the market's inefficiency. This study investigates the type of loss distribution function that best approximates policyholders' claims in Ghana. We applied the Kullback-Leibler divergence, Kolmogorov Smirnov, Anderson-Darling statistical tests and maximum likelihood estimation (MLE) to estimate policyholders' claims. The results suggest that Ghana's auto policyholder's claims are better approximated using the lognormal probability distribution. Through the lognormal distribution , the industry can adequately evaluate policyholders' claims to minimize potential loss. Additionally, this distribution could enable the market reach decisions on premiums and expected profits theoretically.

This study examined risk exposure and auto insurance premium determinants in Ghana. We analysed an existing data set of 23 434 policies (without claims = 84.1%, policies with claims = 15.9%; comprehensive policies = 48.0%, third-party policies = 52.0%) applying the Autoregressive Distributed Lag (ARDL) model, controlling for driver demographics, value of car, and car usage variables. Findings indicate policyholders’ age significantly determine premiums charges. Additionally, auto seating capacity significantly influenced third-party rather than comprehensive premiums, and auto’s cubic capacity had no significant impact on premium charges. Pricing system impact premiums were influenced by policyholders’ characteristics more than variables from the insured vehicle. These findings suggest that policyholders’ age (novice drivers) and vehicles with many occupants increases auto insurers risk exposure.

This paper examines the current No-Claim Discount (NCD) system used in Ghana’s auto insurance market as inefficient and outmoded and, therefore, proposes an alternative optimal Bonus-Malus System (BMS) intended to meet the present market conditions and demand. It appears that the existing BMS fails to acknowledge the frequency and severity of policyholders’ claims in its design. We minimized the auto insurance portfolios’ risk through Bayesian estimation and found that the risk is well fitted by gamma, with the claim distribution modeled by the negative binomial law with the expected number of claims (a priori) as 14%. The models presented in this paper recognize the longevity of accident-free driving and fully reward higher discounts to policyholders from the second year when the true characteristics of the hidden risks posed to the pool have been ascertained. The BMS finally constructed using the net premium principle is very optimal and has reasonable punishment and rewards for both good and bad drivers, which could also be useful in other developing economies.

Available statistics indicates that about 90% of all claims or accident in Ghana is caused by human behavior. Therefore, policyholders’ errors are categorized depending on the severity and extend of casualties caused as a result of misinterpretation of road traffic control devices based on their education levels. Hence, in order to ascertain all the possible causes within the human element to reduce the increasing trend of yearly claims, this study report on the influence of education levels on accident/claims frequency and severity drawing upon a purposive sample of 203 policyholders who have experienced at least one accident in a year using structural equation modeling (SEM). The findings from our regression weights gave enough evidence to reject most of our hypotheses with few ones being supported. This study provides enough evidence that education generally to perspective policyholders influence accidents/claims occurrence. However, in terms of education levels of policyholders, we did not have enough evidence in support of any of these levels either causing or reducing claims/accident frequency. Besides accident/claim frequency, we extended our regression analysis on claim severity and also included some well know auto insurance rating factors to ascertain their impacts on accident frequency. Consequently, it was revealed that most of the severe claims or accidents that results into deaths and serious injuries on yearly basis are caused by policyholders or drivers with medium level of education in Ghana with its frequency driving mostly by rating factors such as the vehicle’s age, cubic capacity, mileage, etc.