Decision support tools for optimizing supply chain management information systems

本研究的目的是设计和评估一个新的模型和方法，使从业人员更充分地分析其实施的供应链管理信息系统（SCM IS）的功能差距。对知识的主要贡献是理解管理企业信息系统的有效设计和评估的理论原则。一个规定性的模型，提出了协助确定最佳的供应链管理信息系统能力。还提出了一个测量模型，用于分析实施SCM IS的期望和实现的能力之间的差距。这两种模型都采用模糊逻辑模型的不确定性和接地在以前的研究适合供应链配置和信息系统的能力。第一个目标是设计和评估的最佳供应链管理信息系统能力的规定性模型：（a）确定设计原则和模糊规则，分析供应链和推荐最佳的供应链管理信息系统能力;（B）创建一个计算机模拟预测的性能不同的组合的供应链和供应链管理信息系统配置;和（c）分析模拟结果，以验证模糊模型。第二个目标是设计和评估差距分析测量模型：（a）设计一个基于网络的决策支持系统（DSS），用于分析SCM IS配置，确定功能差距存在的地方，并解释如何优化配置;（B）评估DSS使用现场研究和实验，以反复评估和改进差距分析决策工具的设计。文献的贡献预计在：（1）新的设计和评估方法的需求工程结合模糊集理论和配置理论;（2）新的模糊逻辑模型分析供应链配置和紧急信息系统的能力;和（3）新的模拟和决策支持工具，评估供应链配置和信息系统能力的不同组合的影响。此外，研究计划将提供决策者的设计，评估和优化供应链信息系统的实际指导，旨在提高他们的效用。

This research aims to design and evaluate a new model and methodology that enables practitioners to more fully analyze the functional gaps in their implemented supply chain management information systems (SCM IS). The primary contribution to knowledge is in understanding the theoretical principles governing the effective design and evaluation of enterprise information systems. A prescriptive model is proposed to assist with determining optimal SCM IS capabilities. A measurement model is also proposed for analyzing gaps between desired and realized capabilities of an implemented SCM IS. Both models incorporate fuzzy logic to model uncertainty and are grounded in prior studies of fit between supply chain configurations and information systems capabilities. The first objective is to design and evaluate a prescriptive model of optimal SCM IS capabilities by: (a) identifying design principles and fuzzy rules for analyzing supply chains and recommending optimal SCM IS capabilities; (b) creating a computer simulation for predicting the performance of different combinations of supply chain and SCM IS configurations; and (c) analyzing the simulation results to validate the fuzzy model. The second objective is to design and evaluate a gap analysis measurement model by: (a) designing a web-based decision support system (DSS) for analyzing SCM IS configurations, determining where functional gaps exist, and explaining how to optimize the configuration; and (b) evaluating the DSS using field studies and experiments to iteratively evaluate and improve the design of the gap analysis decision tools. Contributions to the literature are expected in: (1) new design and evaluation methods for requirements engineering incorporating fuzzy set theory and configurational theory; (2) new fuzzy logic models for analyzing supply chain configurations and emergent information systems capabilities; and (3) new simulation and decision support tools for evaluating the impact of different combinations of supply chain configurations and information systems capabilities. Furthermore, the research program will provide decision-makers with practical guidance on the design, evaluation, and optimization of SCM IS, with an aim to improve their utility.