Mobile money adoption can contribute to achieving Sustainable Development Goals in Uganda but the factors affecting its sustainable adoption remain largely unknown. This paper explores the extent to which mobile money users' trust and risk perceptions affect mobile money services adoption of in Uganda. A survey was conducted with 438 mobile money users from Uganda and data was analyzed using Partial Least Squares (PLS) Structural Equation Modelling (SEM). From the results, we obtained new empirical evidence for applying trust and risk perceptions for analyzing mobile money acceptance. We found that mobile money users rely on the structural soundness of mobile money services providers and their ability to provide mobile money services with low perceived risk. Performance expectancy, perceived risk and structural assurance significantly influenced behavioral intention to adopt mobile money. Trust belief did not significantly influence behavioral intention. These results help us to understand and promote mobile banking services in underdeveloped countries, which is of practical and scientific interests. We finally provide practical implications for mobile money services providers, commercial banks and central banks in Africa.

In this study, we examine the consumers’ attitudes toward Gmarket online shopping in Korea. We use a model to explain that consumers’ attitudes toward online shopping are influenced by psychological, personal, and technological characteristics. We hypothesize that three major behavioral beliefs; perceived trust (psychological), perceived benefits (personal), and perceived website quality (technological) influence consumers’ attitudes toward online shopping. A questionnaire was designed and administered by surveying the Gmarket online shoppers in Korea. A total of 338 valid responses were collected and Partial Least Squares (PLS) Structural Equation Modelling (SEM) was used for data analysis. The findings indicate that consumers’ online shopping attitudes are a function of perceived benefits, trust, and perceived website quality. We found that 57.9 percent of the variation in online shopping attitudes results from perceived benefits, trust, and perceived website quality. Trust was found to be the most important predictor of consumers’ online shopping attitudes. We offer academic and practical implications that are useful in designing e-marketing strategies for competing in the online shopping cyberspace market in Korea. We recommend for the replication of a similar model in other parts of the world like Uganda (Jumia), China (Taobao), Japan (Rakuten), and the United States of America (eBay).

Portfolio Optimization involves choosing proportions of assets to be held in a portfolio, so as to make the portfolio better than any other. In this research, we use a software for statistical computing R to analyse the performance of portfolio optimization models which include; Markowitz's Mean-Variance (MV) model, the VaR model, and Konno and Yamazaki's Mean-Absolute Deviation (MAD) model. We start by analysing multi-asset data for the major indexes in the world followed by historical data of 16 constituent shares listed on the Uganda Securities Exchange (USE) covering 6.5 years. The paper then tests the stock performance of the models using R. We found that GREXP bonds dominated the world market as they accounted for more than 60% of the Maximum Diversified Portfolio (MDP). For the USE, we generated more risk measures like volatility, Sharpe Ratio (SR), Risk Parity (RP), Expected Shortfall (ES) or CVaR which we used to assess stock performance. UMEME, NVL, BATU, JHL, DFCU, EBL, EABL, KCB, SBU and CENT were the bestperforming stocks. By understanding the performance of portfolio optimization models in R, Ugandan investors will develop a better view of the latest performance of the stocks listed on the USE. This will help them to decide on which stocks to include in their investment portfolios, thus prevent wrong investment decisions.

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