Supply chain relationship quality and performance in technological turbulence: an artificial neural network approach

A well-functioning supply chain management relationship cannot only develop seamless coordination with valuable members, but also improve operational efficiency to secure greater market share, increased profits and reduced costs. An accurate decision-making system considering multifactor relationship quality is highly desired. This study offers an alternative perspective and characterisation of the supply chain relationship quality and performance. A decision-making model is proposed with an artificial neural network approach for supply chain continuous performance improvement. Supply chain performance is analysed via a supervised learning back-propagation neural network. An ‘inverse’ neural network model is proposed to predict the supply chain relationship quality conditions. Optimal performance parameters can be obtained using the proposed neural network scheme, providing significant advantages in terms of improved relationship quality. This study demonstrates a new solution with the combination of qualitative and quantitative methods for performance improvement. The overall accuracy rate of the decision-making model is 88.703%. The results indicated that trust has the greatest influence on the supply chain performance. Relationship quality among supply chain partners impacts performance positively as the pace of technological turbulence increases.     

A review on the buyer–supplier dyad relationships in sustainable procurement context: past,present and future

Sustainable development is currently being applied in most fields of research. Procurement, focused on the buyer–supplier dyad, is one such discipline where sustainability is being widely applied. This paper provides a review of these research studies, conducting a systematic content analysis in order to present the state of the art in this domain. The paper carries out a detailed review of articles in international scientific journals and well-known international conferences related to green and sustainable supplier selection published between 2008 and 2014 inclusive. Seven designed research questions are proposed and answered based on this bibliography. Interesting results are reported in each section and gaps in the current body of literature are identified. The purpose of this review is to provide important future directions and limitations in this research topic.     

Supply chain resilience: model development and empirical analysis

The purpose of this study is to develop a hierarchy-based model for supply chain resilience (SCRES), explaining the dynamics between various enablers and validating the model empirically. Literature review and a survey identified the enablers. Interpretive structural modelling (ISM) is used to analyse the levels of relationships among enablers. Based on their driving power and dependence, these enablers are also classified into different categories. Structural equation modelling is used to validate the hierarchical SCRES model and test the path analytical model. The study provides empirical justification for a framework that identifies 13 key enablers of resilient supply chain practices and describes the relationship among them using ISM. It also classifies them using Matrix of Cross Impact Multiplications Applied to Classification analysis on the basis of their driver power and dependence. The key finding is that using the proposed model, organisations can enhance their resilience potential by modifying their strategic assets. The model was tested using rigorous statistical tests including convergent validity, discriminant validity and reliability. The holistic view offered by the proposed model depicts the relationship among enablers to achieve SCRES.     

Methodological approaches to supply chain design1

This paper reviews methodological approaches to the design (or redesign) of the supply chain (SC), including comprehensive approaches (proposals concerning the entire process of designing the SC) and those that deal with four specific aspects of the process (definition of the SC objectives, reverse SC, finance, and generation and use of scenarios) that have a decisive influence on the whole design of the SC. The comprehensive approaches include those based on typologies of products, markets and SCs and those that propose a succession of the stages to follow through the design process. The discussion shows that the use of typologies is not adequate to face SC design and that the methods proposing a succession of stages may suit, provided that they are developed and presented in a manner appropriate to their use for practitioners. The discussion leads also to suggest several research lines.     

关于建筑业供应链管理问题的探讨

供应链管理是一种全新的管理模式,即把供应链上的各个企业作为一个不可分割的、协调发展的有机体。建筑业虽然与制造业不同,但却是典型的订单式生产,在建筑业实施供应链管理具有重要意义。本文主要探讨在建筑业实施供应链管理的可能性和作用,论述建筑业供应链管理的方法以及有待进一步研究的问题。     

供应链的竞争力——顾客满意

从供应链管理的角度对顾客满意进行了分析,指出了让最终顾客更满意应成为供应链全体成员的共同目标,而顾客满意的实质是顾客获得超出他们承担的产品价格以上的那部分“价值”。     

三级供应链管理的一般问题及其改进

分析了三级供应链管理存在的不确定因素、合作关系、组织边界、库存成本、顾客满意程度、运作规则和信息系统等方面的问题,并提出了相应的解决措施。最后,研究了沈阳一家电机公司三相绕线型异步电动机供应链的建立及改进实例。     

神经网络技术在供应链管理中的应用

神经网络技术已被成功地应用在许多商业领域,包括供应链管理。本文首次系统地总结了神经网络技术在供应链管理中的应用。首先介绍了神经网络的本质和特性,接着详细介绍了神经网络技术在供应链管理中的５个方面的应用：优化、预测、决策支持、建模和仿真和全局化管理;然后运用ＢＰ型神经网络对上海市场自行车的需求量进行了预测;最后指出阻碍神经网络技术发展的两个障碍以及神经网络技术发展的方向。     

A fuzzy multi-criteria decision-making approach for managing performance and risk in integrated procurement–production planning

Nowadays in Supply Chain (SC) networks, a high level of risk comes from SC partners. An effective risk management process becomes as a consequence mandatory, especially at the tactical planning level. The aim of this article is to present a risk-oriented integrated procurement–production approach for tactical planning in a multi-echelon SC network involving multiple suppliers, multiple parallel manufacturing plants, multiple subcontractors and several customers. An originality of the work is to combine an analytical model allowing to build feasible scenarios and a multi-criteria approach for assessing these scenarios. The literature has mainly addressed the problem through cost or profit-based optimisation and seldom considers more qualitative yet important criteria linked to risk, like trust in the supplier, flexibility or resilience. Unlike the traditional approaches, we present a method evaluating each possible supply scenario through performance-based and risk-based decision criteria, involving both qualitative and quantitative factors, in order to clearly separate the performance of a scenario and the risk taken if it is adopted. Since the decision-maker often cannot provide crisp values for some critical data, fuzzy sets theory is suggested in order to model vague information based on subjective expertise. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution is used to determine both the performance and risk measures correlated to each possible tactical plan. The applicability and tractability of the proposed approach is shown on an illustrative example and a sensitivity analysis is performed to investigate the influence of criteria weights on the selection of the procurement–production plan.