Probability modelling of supplier development investment decisions under uncertainty

  • Jiahui Yang

Student thesis: Doctoral Thesis


Supplier development involves activities intended to improve a supplier's performance and to add value on a buying firm's business benefit. Typically, such activities require significant resource investment and there is a risk that the benefit to be obtained from supplier development may not be enough to offset the expenses incurred. This thesis develops quantitative models to inform buyer decisions on whether it is worth investing in a supplier development activity and, if so, how much should be invested. The proposed models are built from a buyer's perspective to support analysis of the benefit obtained from the development activity. In particular, the models take account of the uncertainty of the benefit and associate it with the stochastic characteristics of a supplier's performance.;More specifically, the two models are relevant for types of supplier performance data. The first model considers the case of developing a supplier whose undesirable performance is measured in categorical form, such as classes corresponding to degrees of late delivery. The multinomial distribution is used to represent the uncertainty of a supplier's performance. The second model considers a case of developing a supplier whose undesirable performance is measured in counting form, such as, the number of non-conformances. The non-homogenous Poisson process (NHPP) model is used to represent the uncertainty of a supplier's performance.;The two proposed models provide decision makers with an optimal investment level, which is the maximum amount of investment to be made for the development activity as well as an expected return. Numerical investigations are carried out to examine the behaviour of the models and to illustrate key theoretical properties. An industry case study is conducted to provide an empirical demonstration of modelling for analysis of supplier databases. This also qualitatively investigates how the models align with supplier development management decision making in practice.
Date of Award31 Jul 2020
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SponsorsUniversity of Strathclyde
SupervisorLesley Walls (Supervisor) & John Quigley (Supervisor)

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