Identifying appropriate international distributors for small and medium-sized enterprises (SMEs) in the software industry for overseas markets can determine a firm's future endeavors in international expansion. SMEs lack the complex skills in market research and decision analysis to identify suitable partners to engage in global market entry. Foreign distributors hold responsibility to represent, sell, market, and add value to the software manufacturer's products in local markets. Identifying appropriate attributes to determine a suitable distributor is essential in assuring success in new export markets. Methods for partner selection have been addressed in the international marketing and information systems literature. Building on this literature, this dissertation develops an improved method for identifying suitable distributors in the SME software industry. The partner selection conundrum is modeled as a binary classification problem in that it involves predicting whether an alliance relationship will survive over a specific period. The challenge presented to researchers is not just the large number of variables involved in the selection process but also the inherent uncertainty in the decision making process. This study uses a Bayesian methodology for this classification task. A Naïve Bayes (NB) classification model was developed factoring sixteen alliance attributes identified in the partner selection literature and validated by domain experts who scored the importance of these attributes. Thirty years of partnership data that contributed to relationship longevity trained the model and held-back data was used to validate the model. The NB classification model returned accurate predictions in both the group of foreign distributors that succeeded and failed to reach the relationship longevity threshold of five years. The study's contribution to the software SME business community and its practitioners was the identification of an improved methodology for predictive success. The approach employed a simple Bayesian prediction model utilizing key alliance attributes to help software SMEs identify potential foreign distributor partners who can sustain relationship longevity from which to build a strong business partnership. Keeping the methodology simple is critical for SMEs who struggle with an abundance of challenges to maintain their corporate viability in the market place.

M. Tech. (Department of Logistics Management, Faculty of Management Sciences), Vaal University of Technology. / The food retail industry is an important contributor to the economy. Buyers and suppliers in this industry work in collaboration with each other to achieve superior supply chain performance. To achieve this, they have to find ways and methods to improve it. The purpose of this study was to investigate the drivers of supply chain performance in the food retail industry in the Gauteng province. This study considers three of these drivers, namely buyer-supplier trust, buyer-supplier commitment and supply chain relationship longevity. A quantitative approach was adopted in which a survey questionnaire was used to collect data from 429 managers and staff members from food retailing firms in the Gauteng province. The study used a non-probability convenience sampling technique to select respondents. Data were analysed with the aid of two software packages, namely the Statistical Package for the Social Sciences (SPSS version 24.0) and the Analysis of Moment Structures (AMOS version 24.0). A confirmatory factor analysis was applied in examining and testing the relationships between observed constructs and their causal latent constructs while structural equation modelling was used to test the hypothesised relationships between constructs. The results of the research revealed that buyer-supplier trust, buyer-supplier commitment and supply chain relationship longevity positively and significantly influence supply chain performance. Buyer-supplier trust exerted a positive and significant influence on both buyersupplier commitment and relationship longevity. Also, the results showed that buyer-supplier commitment has a positive and significant influence on relationship longevity. The study concludes that to achieve greater supply chain performance, food retailers should expedite the levels of trust, commitment and length of relationships with their suppliers. The results of this study provide useful insights on how businesses in the food retail industry could benefit from trust, commitment and relationship longevity as well as on how to improve supply chain performance. The results of this study contribute to the existing body of knowledge by generating new information on buyer-supplier relationships. Therefore, the study is useful to buyers and suppliers in the food retail industry who wish to enhance supply chain performance and develop better relationships.