Evaluation of Target Area Concentration (TAC) Programme in Malaysia’s Integrated Cattle and Oil Palm Farming

Malaysia’s beef production falls under three types of production methods: traditional system, intensive system of cattle feedlots, and integrated farming system. The objective of this study is to investigate and evaluate the effectiveness of the target area concentration (TAC) programme conducted by the Department of Veterinary Services (DVS) that focuses on the integrated farming system between cattle and oil palm plantation. This study intends to identify the programme’s achievement through context, input, process, and product (CIPP) analysis. The analysis reveals that the real needs of the programme context are being met by TAC; the provision meets the needs of inputs but there are some constraints; the implementation of the TAC programme is running well and receives good cooperation from farmers, but there are some constraints; and there is a positive impact of the programme in terms of production, income, employment, changes in knowledge, skill, attitude, and practice. Overall, the TAC programme has thus far achieved its objectives, but it needs some improvements.     

Using GIS to visualise and evaluate student travel behaviour

Using GIS to evaluate travel behaviour is an important technique to increase our understanding of the relationship between accessibility and transport demand. In this paper, the activity space concept was used to identify the nature of participation in activities (or lack of it) amongst a group of students using a 2 day travel-activity diary. Three different indicators such as the number of unique locations visited, average daily distance travelled, and average daily activity duration were used to measure the size of activity spaces. These indicators reflect levels of accessibility, personal mobility, and the extent of participation, respectively. Multiple regression analyses were used to assess the impacts of students socio-economic status and the spatial characteristics of home location. Although no differences were found in the levels of accessibility and the extent of participation measures, home location with respect to a demand responsive transport (DRT) service was found to be the most important determinant of their mobility patterns. Despite being able to travel longer distances, students who live outside of the DRT service area were found to be temporally excluded from some opportunities. Student activity spaces were also visualised within a GIS environment and a spatial analysis was conducted to underpin the evaluation of the performance of the DRT. This approach was also used to identify the activity spaces of individuals that are geographically excluded from the service. Evaluation of these results indicated that although the service currently covers areas of high demand, 90% of the activity spaces remained un-served by the DRT service. Using this data six new routes were designed to meet the coverage goal of public transport based on a measure of network impedance based on inverse activity density. Following assessment of public transport service coverage, the study was extended using a spatial multi criteria evaluation (SMCE) technique to assess the effect of service provision on patronage.     

When Crises Hit Home: How U.S. Higher Education Leaders Navigate Values During Uncertain Times

Journal of Business Ethics - Against the backdrop of a global pandemic, this study investigates how U.S. higher education leaders have centered their crisis management on values and guiding ethical...     

Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China

The current research aims to launch effective accounting fraud detection models using imbalanced ensemble learning algorithms for China A-Share listed firms. Based on a sample of 33,544 Chinese firm-year instances from 1998 to 2017, this research respectively established one logistic regression and four ensemble learning classifiers (AdaBoost, XGBoost, CUSBoost, and RUSBoost) by 12 financial ratios and 28 raw financial data. Additionally, we divided the sample into the train and test observations to evaluate the classifiers' out-of-sample performance. In detail, we applied two metrics, namely, Area under the ROC (receiver operating characteristic) curve (AUC) and Area under the Precision-Recall curve (AUPR), to evaluate classifiers' discriminability. In the supplement test, this study put forward an algebraic fused model on the basis of the four ensemble learning classifiers and introduced the sliding window technique. The empirical results showed that the ensemble learning classifiers can detect accounting fraud for the imbalanced China A-listed firms far more effectively than the logistic regression model. Moreover, imbalanced ensemble learning classifiers (CUSBoost and RUSBoost) effectively performed better than the common ensemble learning models (AdaBoost and XGBoost) in average. The algebraic fused model in the supplement test also obtained the highest average AUC and AUPR among all the employed algorithms. Our results offer firm support for the potential role of Machine Learning (ML)-based Artificial Intelligence (AI) approaches in reliably predicting accounting fraud with high accuracy. Similarly, for the Chinese settings, our ML-based AI offers utmost advantage in forecasting accounting fraud. Finally, this paper fills the research gap on the applications of imbalanced ensemble learning in accounting fraud detection for Chinese listed firms.     

Understanding Conflicting Interests of a Government and a Tobacco Manufacturer: A Game-Theoretic Approach

Rice is the staple food of nearly half of the population of the world, most of whom live in developing countries. Ensuring a domestic supply of rice from outside sources is difficult for developing countries as less than 5% of the total world’s production is available for international trade. Hence, in order to ensure domestic food security, e.g., food availability and access, governments provide subsidies in agriculture. In many occasions, public money used for the subsidy goes toward promoting undesirable crops like tobacco. Although the strategic interaction between governments and manufacturers is critical, it has not been studied in the literature. This study fills this gap by considering a game between a government (of a developing country) and a tobacco manufacturer in which the government decides on a mix of subsidies and the tobacco manufacturer decides on declaring a purchasing price of tobacco. We provide a numerical study to show that controlling the output harvest price is more effective in reaching the desired end result for both the government and the tobacco manufacturer. A subsidy in fertilizer results in the measurable increase in the government spending but does not have significant effect in reaching the production target. The fertilizer subsidy should be provided only when the output price is too high to be affordable for the population.     

Does mobile money use increase firms’ investment? Evidence from Enterprise Surveys in Kenya,Uganda, and Tanzania

Private investment can be an important engine of economic growth in East African countries that are plagued with adverse economic conditions, despite recent growth rates. Against this backdrop, there has been substantial penetration of mobile money, moving beyond simple person-to-person exchanges towards adoption by private firms. This study explores whether there is a relationship between firm adoption of mobile money and firm investment. Using firm-level data that are nationally representative of the private sector in three East African countries—Kenya, Tanzania, and Uganda—a positive relationship is found between mobile money use and firm’s purchase of fixed assets. This relationship is attributed to reduced transaction costs, increased liquidity, and increased credit worthiness associated with the use of mobile phone financial services. The finding is largely driven by small- and medium-sized enterprises (SMEs).     

An investigation of consumer evaluation of brand extensions

This paper deals with the effects of perceived quality, perceived fit and perceived difficulty, and interaction between perceived quality and fit on consumer evaluations of brand extension. We used multi‐item scales to measure these constructs. Data were analysed via structural equation models. Results show that both perceived quality and perceived fit have direct positive effects on consumer evaluation of extensions. We find support for the chance of transferring the positive values of a brand to an extension is greater when consumers see the extension as a good fit with the original brand and the original brand is considered as of high quality.     

Sequential Betting Behavior: A Test of Asymmetric Inconsistencies in Group Decision Making

Previous research has shown that individual decision makers tend to bet more than initially planned after experiencing a loss but not after a gain. This research tests whether groups in consensus decision‐making contexts also demonstrate similar asymmetric inconsistencies. Two experiments, one at the individual level and one with three‐person groups, were carried out based on a gambling‐type betting task. Although individuals planned more conservatively than groups regarding their betting behavior after the first outcome, both individuals and groups misestimated their own betting behavior after losses but not after gains. Negative, but not positive, emotional reactions to previous decision outcomes were also misestimated, leading to incorrect predictions of future behavior. Implications for theory and future research are discussed.