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UBC Theses and Dissertations

Developing decision support models for partnership evaluation in the forest products supply chain Piltan, Mehdi


The forest sector in Canada has been losing its competitiveness due to globalization and rapid change in technology. Partnership is one of the strategies that could help companies remain competitive; however, partnership is costly and has a high failure rate, according to the literature. Therefore, it is essential to monitor the performance of a partnership and evaluate the factors that affect its performance. Previous studies reveal that the performance of an ongoing partnership is influenced directly by a number of components, which are joint decision-making, information sharing, risk/reward sharing and relationship-specific assets. However, there is a gap for a comprehensive study that investigates partnerships and their components in the forest industry. In this study, first a survey is conducted from the forest companies in British Columbia, Canada, to investigate existing and potential partnerships and the factors that influence the performance of existing ones. The respondents are asked to subjectively evaluate partnership performance and the influencing factors using the Likert scale. The results of regression analysis indicate the degree of joint decision-making, relationship-specific assets, and risk/reward sharing as the best predictors of the performance of the surveyed companies. Then, two multi-criteria decision support models are developed to evaluate partnership performance and components quantitatively. Multiple quantitative criteria are used in the models. Interpretive Structural Modeling (ISM) and Analytic Network Process (ANP) are used in order to address the interdependency and the importance of criteria, respectively. Fuzzy Logic (FL) is used to capture the uncertainty in the criteria for evaluating partnership performance. The outputs of these two models are the importance of the criteria and two single numbers for the overall partnership performance and components in each period, named as Partnership Performance Index (PPI) and Partnership Component Index (PCI). The proposed models are applied to a partnership between a logging company and a sawmill in Canada, to find PPIs and PCIs in three different periods. The rankings of the criteria from the models are compared to the ones estimated by the managers, and the results show the rankings are compatible. The results are assessed by sensitivity analysis and validated by the managers.

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