Decision support tools for optimizing supply chain management information systems

本研究旨在设计和评估一种新的模型和方法，使从业者能够更全面地分析其实施的供应链管理信息系统(SCM IS)中的功能差距。对知识的主要贡献在于理解指导企业信息系统有效设计和评估的理论原则。提出了一个规范的模型来帮助确定最优的供应链管理系统能力。还提出了一个度量模型，用于分析已实施的供应链管理信息系统的期望能力和已实现能力之间的差距。这两个模型都结合了模糊逻辑来模拟不确定性，并且都基于先前关于供应链配置和信息系统能力之间匹配的研究。第一个目标是通过以下步骤设计和评估最优供应链管理信息系统能力的规范模型：(A)确定用于分析供应链并推荐最优供应链管理信息系统能力的设计原则和模糊规则；(B)创建计算机模拟以预测供应链和供应链管理信息系统配置的不同组合的性能；以及(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)，用于分析供应链管理系统的配置，确定存在功能差距的地方，并解释如何优化配置；以及(B)使用实地研究和实验来评估DSS，以反复评估和改进差距分析决策工具的设计。(1)结合模糊集合论和构型理论的新的需求工程设计和评估方法；(2)用于分析供应链配置和紧急信息系统能力的新的模糊逻辑模型；(3)用于评估供应链配置和信息系统能力的不同组合的影响的新的模拟和决策支持工具。此外，该研究计划将为决策者在供应链管理信息系统的设计、评估和优化方面提供实践指导，以期提高其实用性。

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.