Urban public transport plays a critical role in stimulating economic development of any nation since most of the revenues come from cities. The majority of the city dwellers of any country use public transport. The evaluation of public transport service quality provides a valuable feedback to commuter operators to ensure continuous improvement of level of service and to the government to take appropriate measures for enhancing the quality of public transport service. This paper analyses and evaluates service quality of Road Public Transport (RPT) (i.e. minibuses and buses) and Urban Rail Transport (URT) in Dar es Salaam City, Tanzania. Since service quality and its attributes are intangible and vague, a fuzzy evaluation model is developed and applied. The formulated model is composed of Fuzzy Entropy Method (FEM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The overall evaluation procedure is as follows: initially, an intensive literature search and experts' opinions are employed to establish criteria for evaluating the service quality of public transport in Dar es Salaam City. The developed FEM is used to obtain criteria weight. Lastly, the formulated TOPSIS is used to provide an overall ranking of urban public transport service quality. The overall evaluation shows that urban rail transport outperforms road public transport in terms of service quality. Nevertheless, the urban rail transport service in Dar es Salaam City is currently not well developed as it is provided on very limited routes. Thus, the Tanzania government, the rail transport operator i.e. Tanzania Railway Limited (TRL) and the agency responsible for the provision of rail infrastructure i.e. Reli Assets Holding Company (RAHCO) are advised to design and employ Public-Private-Partnership (PPP) schemes i.e. concession contracts to invest more in rolling stocks, locomotives

Abstract-Transportation is a key to the economy and social welfare; it makes mobility more accessible and enhances the social and economic interactions. On the other hand, the increase of urban population, pollution and other negative impacts has directly affected the existing transportation system in Dar es Salaam City -Tanzania. As the transportation challenges cannot be overcome simultaneously due to the scarcity of financial resources, a decision support tool is needed to prioritize these challenges. In this study, a composite model of Vague Set Theory (VST) and Analytical Hierarchy Process (AHP) is applied to appraise the challenges. The Vague Analytical Hierarchy Process (VAHP) uses opinions of experts collected from a survey questionnaire. The computational results reveal the ranking in descending order of the urban transportation challenges as poor traffic management, inadequacy of proper public transit service and inadequacy of road transport infrastructure. The results also depict that the VAHP model is a useful decision support tool for transport planners, transport policy makers and other industry stakeholders.

The landed cost for oil products in local markets is very often affected by the fluctuation of price related to the international purchasing from oil markets. As a result, oil products are primarily procured via term contracts i.e. derivatives as wholesalers are typically loath to rely heavily on spot supplies as these may be unreliable and exhibit high price volatility. In this study, we apply Grey Theory to evaluate the derivatives based strategies of the Tanzanian oil products imports for hedging the price risk in the local market. After comprehensive evaluation, we find that the applicability of oil derivatives by the Tanzanian importers is high. Thus, the government (i.e. Ministry of Finance and Planning, Ministry of Trade and Industry) and other stakeholders have the obligation to continue bringing awareness on the benefits of the derivative instruments in the purchasing of oil products, which ultimately upon application would bring a relief to all consumers of the oil products in the country. Moreover, as the grey theory can deal with vague and incomplete data, the proposed model can be applied as an evaluation tool for quantifying qualitative data in any industry.  

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