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Demographics are changing and populations are becoming more diverse in many but not all countries. In some countries, an increasing number of businesses are owned by women, visible minorities and other diversity groups. In response, academics and practitioners are starting to pay attention to supplier diversity (SD), which encourages purchasing goods and services from suppliers owned by members of diversity groups. This study focuses on development of SD programs in various countries, along with facilitators or inhibitors of SD adoption. The primary research question is: What national or cultural characteristics make organizations in a country more (or less) likely to have SD programs? Characteristics of interest include ethnic diversity of the population, GDP and Hofstede’s power distance index. Data collection included administration of a survey of purchasing and supply management professionals from 37 countries and gathering of secondary data for 55 countries. / February 2017

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Decision making is a fundamental tool for managers and enable them to make logical decisions in critical situation between different options. This thesis concentrates mainly on seller selection problem or in some cases it also refers to vendor or supplier selection problem (SSP) and demonstrates how the multiple attribute decision making (MADM) methods can be effectively used for vendor selection decision in various situations of project management and supply chain environment. A case study has been carried out within two different countries (Sweden and Iran) in order to help practically managers to choose the best alternatives among their preferences. In this regard, AHP as one of major tools of MADM is also deployed.

This working paper was originally printed in the Working Paper Series of the MIT International Motor Vehicle Program

This working paper was originally printed in the Working Paper Series of the MIT International Motor Vehicle Program

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Many parts used by the automobile manufacturers are provided by outside suppliers. Hence, the chain between the automobile manufacturers and their suppliers has been considered very important for the purchasing department of an automobile factory. Finding qualified suppliers that can meet the demands of the automobile manufacturers is thus an important issue. With the application of neural networks, this thesis develops an approach to help determining the qualification of the suppliers. By using data of the known qualified and unqualified suppliers and by setting a number of features to characterize the capability of the suppliers, neural networks are trained to determine the qualification of the suppliers. In training the neural networks, the features are incrementally removed until optimal classification accuracy is reached. It is hoped that this system can become an effective decision-supporting system in screening the potential suppliers for the automobile manufacturers.