Examining Organic Food Purchases and Preferences Within Jordan

Continuing economic development in Jordan provides potential food marketing opportunities as a new group of prospective value-added food product consumers emerges. The growing demand for high-value foods such as organically produced items also provides a new potential value-added market for Jordanian farmers. No studies to our knowledge have examined consumer preferences toward organic food items within Jordan. This study provides an initial attempt to fill this knowledge gap by examining the market for organic food items from a demand perspective in order to increase the knowledge available to Jordanian farmers, food processors, and retailers.     

Exchange Rate Regime and Demand for Reserves: Evidence from Kenya,Mexico and Philippines

This paper empirically investigates the demand for international reserves (and foreign exchange reserves) during fixed and floating exchange rates periods in three developing countries: Kenya, Mexico and Philippines. Based on theoretical models, three factors are identified as important for the demand of international reserves and foreign reserves: average propensity to import, volume of imports and variability of reserves. The paper employs the cointegration methodology and error correction method to investigate the relationships. Cointegration tests results indicate a reliable long-run stationary relationship between the international reserves (and foreign exchange reserves) and the stated explanatory variables across countries and sub-periods of fixed and clean float. The error correction results indicate causality from the explanatory variables to the reserves during both the short and long run. This is true during both the fixed and the floating periods.

International Marketing Ethics from an Islamic Perspective: A Value-Maximization Approach

International marketing practices, embedded in a strong ethical doctrine, can play a vital role in raising the standards of business conduct worldwide, while in no way compromising the quality of services or products offered to customers, or surrendering the profit margins of businesses. Adherence to such ethical practices can help to elevate the standards of behavior and thus of living, of traders and consumers alike. Against this background, this paper endeavors to identify the salient features of the Islamic framework of International Marketing Ethics. In particular, it highlights the capabilities and strengths of this framework in creating and sustaining a strong ethical international marketing culture. At the heart of Islamic marketing is the principle of value-maximization based on equity and justice (constituting just dealing and fair play) for the wider welfare of the society. Selected key international marketing issues are examined from an Islamic perspective which, it is argued, if adhered to, can help to create a value-loaded global ethical marketing framework for MNCs in general, and establish harmony and meaningful cooperation between international marketers and Muslim target markets in particular.     

Buffett’s alpha: further explanations from a behavioral value investing perspective

Warren Buffett has had extraordinary success as an investor, but there is no agreement as to why. Some academic researchers attribute his performance to mere luck. Frazzini et al. (Financ Anal J 74(4):35–55, 2018), concluded that his alpha is due to leveraging safe, high-quality, and cheap stocks. However, there has been no analysis to date of Buffett’s performance from a behavioral perspective. We argue that Buffett’s success is partly due to qualitative and psychological factors, including tenacity, patience, avoidance of overconfidence, organizational culture, and the reputation effect. Using information from shareholder letters, writings, interviews, and speeches by Buffett and his colleague Charlie Munger, we demonstrate how such psychological factors, together with the quantitative findings of Frazzini et al., render a more complete and satisfying explanation of Buffett’s alpha.

     

Does stardom affect the informativeness of a CEO's insider trades?

This study examines whether the celebrity or star status of a chief executive officer (CEO) affects the informativeness of his insider trades. Using three different measures to identify star CEOs in a sample of S&P 1500 firms, we find that trades of non‐star CEOs predict future abnormal returns and earnings innovations and that trades of star CEOs do not. The predictive power of non‐star CEO trades is mostly attributable to opportunistic trades, not routine trades. We also find evidence suggesting that the abnormal returns associated with non‐star CEO insider trades are due to the lower visibility and consequently less scrutiny of non‐star CEOs compared with star CEOs.     

AN APPLICATION OF ACTIVITY BASED COSTING IN THE AIR CONDITIONER MANUFACTURING INDUSTRY

AIRCO is a manufacturer of industrial air conditioner units whose management is concerned that their current traditional cost accounting (TCA) system is not accurately representing their product cost behavior. Under certain operating conditions, an activity based costing (ABC) system can provide relevant and accurate indirect cost information that assists in making customer, product, and process improvement decisions. An ABC system was successfully developed for AIRCO that indicated that their products do not consume overhead costs on a volume basis as represented by their current TCA system. Valuable product and process information were obtained. This case study details the development process that was used and the results that were obtained during the ABC analysis.     

The role of the Securities and Exchange Commission in a developing economy: Implications for IFRS

Due to the widespread adoption of IFRSs throughout the world and little research on IFRS implementation in developing countries, this study investigates the role of the Securities & Exchange Commission (SEC) regarding IFRS implementation in a developing country. Adopting a mixed methodology (39 interviews and 1647 enforcement documents); the findings have raised concerns as to the adequacy of enforcement mechanisms in implementing IFRSs in Bangladesh. More specifically, only 2.6% of enforcement actions were issued over the period of 1998 to 2010. Political connectedness is the major contributing factor for uneven enforcement activities in Bangladesh. The study also finds that inconsistencies with accounting regulatory framework (Companies Act, BSEC ordinances and IFRSs), multiple regulators, and donor agencies' influence impede the effective implementation of IFRSs. The study also provides policy implications for local and national policy makers namely, IASB, the World Bank and the IMF to rethink about the regulation of IFRSs in developing countries.     

A hybrid clustering and classification approach for predicting crash injury severity on rural roads

As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011–2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.