Exit is an inevitable part of any business relationship. However, despite its importance, exit in buyer–supplier relationships is still a poorly understood phenomenon. Building on previous studies, this thesis addressed these concerns by empirically: a) identifying the economic and social antecedents that influence the exit decision; and b) validating how the antecedents of exit are related with the choice of exit strategies. To achieve these objectives, first, a systematic literature review was conducted to identify 82 studies that documented existing research on exit in buyer–supplier relationships. Second, informed by Transaction Cost Economics and Social Exchange Theory, a set of 88 testable hypotheses was developed and a survey captured data from 505 recently terminated relationships involving UK based firms. Finally, for data analysis, statistical techniques were employed including: a) analysis of variance; b) independent sample t–tests; c) multiple logistic regression; and d) multi–nomial logistic regression. The empirical findings of this thesis validated that: a) there are 8 economic and 14 social antecedents that influence the exit decision; b) lending support to extant research on exit, 57 hypotheses were accepted; c) 12 multiple logit models confirmed the relationship between a set of antecedents and exit strategies; and d) 6 multinomial logit models validated the relationship between a set of antecedents and a choice of one exit strategy over another. The results suggest that the influence of antecedents on the choice of exit strategies was subject to how the antecedents were analysed. The contributions of this research to Supply Chain Management literature are that we know now: a) which economic and social antecedents influence the exit decision; b) how individual antecedents affect exit strategies; c) how antecedents combine to affect exit strategies; and d) how antecedents combine to affect the choice of one exit strategy over another. This work provides an exit management tool box comprising a combination of data collection instrument, empirically derived framework and models that enables the managers to timely review the strength and weaknesses of their business relationships and their management processes.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:691025 |
Date | January 2016 |
Creators | Habib, Farooq |
Contributors | Pilbeam, Colin ; Mena, Carlos |
Publisher | Cranfield University |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://dspace.lib.cranfield.ac.uk/handle/1826/10185 |
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