大数据背景下产业链内部间隙弥补与企业运营效率提升

近年来,电子商务从产生到不断壮大,越来越多地受到相关信息技术和商业模式影响。大数据分析和数据挖掘技术逐渐运用于各行各业,电子商务及相关交易作为典型的经济活动,其相互交融与影响对产业经济发展具有重要意义。然而,渠道完备化的电子商务产业链整合由于部分机制的低效性,其内部存在基于要素与终端、数据融通、需求满足层面的诸多间隙,需要通过大数据等技术支撑及渠道、市场的有效对接实现产业链企业的整合。通过对这些作用机制及优化路径的研究发现：应通过价值提升维度实现大数据在产业链内部企业融通中的应用,提高其在目标群体识别和需求预测中的应用,同时提高大数据在企业布局推广中的应用,以有效提升企业运营效率。     

零售商双渠道供应链定价及协调研究

研究了零售商双渠道供应链的定价策略和协调问题,建立制造商和零售商两方博弈模型,分析了集中决策和分散决策两种情境下的定价决策均衡解,并设计收入共享契约来解决零售商双渠道存在的双重边际化效应。结果表明,零售商需要提供合理的收入分配比例才能实现供应链各成员利润的Pareto改进,并最终协调整个双渠道供应链。在双渠道竞争环境下,线上线下不能采取完全同价策略,企业应针对不同渠道的具体情况制定不同的销售价格。     

农机零售连锁经营模式探讨

整合国内农机零售渠道,需借鉴国内外成功的连锁经营模式经验。结合农机市场的特点,农机连锁企业应首先确立以突出选址为重点的经营战略,吸收连锁企业“联邦制”和“集权制”的优点,建立“民主集中制”的管理模式和组织结构,从议价销售起步,逐步实现连锁经营的明码标价,构建以品类计划、OTB计划为主的销售预算和市场调研、战略性现金流管理为重点的经营技术。     

第三方物流外包服务综合绩效评估模型的构建

本文根据全面性、特殊性、可比性、可操作性原则,参考评价第三方物流企业的一般评价指标的选取原则,选取了包括运力资源利用率、固定资产周转率、订单完成率、配送资源利用率等20个具有代表性的指标,详细地构建了第三方企业物流系统综合评价指标体系,并采用主成分因子分析法对企业物流系统进行了综合评价。     

现代服务业供应链整合与上海国际贸易中心建设

在当今经济全球化背景下,供应链日益成为产业组织的一种主流生产模式,高端与专业性服务业的供应链整合尤为重要。服务企业能否形成以其为核心的供应链,关键取决于各自的供应链管理能力。通过考察上海商贸、金融、物流、计算机与信息服务业等涉及国际贸易中心建设的关键服务行业,在分析上海国际贸易中心建设中现代服务业供应链整合发展的现状与存在问题的基础上,提出上海增强服务业供应链整合能力的对策建议。     

网络外部性对双渠道供应链信息分享的影响

研究了网络外部性对双渠道供应链信息分享的影响。分别建立了存在网络外部性和不存在网络外部性下的双渠道供应链模型,通过比较零售商信息分享和不分享下其与制造商的期望利润。研究发现：当未考虑产品的网络外部性时,零售商不与制造商分享其市场需求信息,与已有研究一致。当考虑了产品网络外部性且网络外部性较小时,零售商仍不与制造商分享市场需求信息;然而,当网络外部性较大时,零售商与制造商分享其市场需求信息。此外,零售商与制造商共享其市场需求信息有助于增加制造商和供应链利润。     

基于个性化需求的产品竞争供应链结构选择

基于"制销分离"与"定制一体"两种结构选择,构建个性化产品供应链处于非竞争与竞争环境下的博弈模型,在引入一个实际案例的基础上,运用算例仿真比较分析两种运营模式下的供应链运作策略和盈利差异。结果显示：与制销分离结构相比,个性化产品供应链选择定制一体结构,有利于匹配产品个性化制造、提升产品个性化水平和市场需求、增加供应链的期望收益;个性化产品供应链选择制销分离结构时,适度的批发价格激励能够提升产品个性化水平、更好满足消费者个性化需求、改善供应链的运营绩效,分销商适度让利加大批发价格激励力度可显著促进产品个性化制造互动、提升产品个性化水平;竞争将消减个性化产品供应链的运营绩效,但选择定制一体结构可显著提升竞争力。     

远海岛礁冷链物流体系优化模型及其集成算法

为研究远海岛礁渔获冷链物流的运行方案,本文选择了岛礁冷库储存中转和海上直接收购等两种不同的渔获运输方式,同时考虑了中转冷库选址、中转运输和直接收购船舶配备、航线配置、在渔场停留时间和渔获运输损耗等诸多复杂问题,构建了远海冷链物流体系组合优化模型。求解时,提出了一种以遗传算法（GA）为外部框架,以改进的模拟植物生长算法（PGSA）为内部模块,通过信息传递实现内外连接交互的集成算法。最后,以我国南海远海岛礁及渔场为实例进行分析,取得了较好效果。通过与传统遗传算法对比,本文优化结果、稳定性及计算速度等均有明显提高,从而证明了本文所建模型与算法的合理性和有效性。     

Evaluation of multi-objective optimization approaches for solving green supply chain design problems

This paper evaluates the applicability of different multi-objective optimization methods for environmentally conscious supply chain design. We analyze a case study with three objectives: costs, CO₂ and fine dust (also known as PM – Particulate Matters) emissions. We approximate the Pareto front using the weighted sum and epsilon constraint scalarization methods with pre-defined or adaptively selected parameters, two popular evolutionary algorithms, SPEA2 and NSGA-II, with different selection strategies, and their interactive counterparts that incorporate Decision Maker׳s (DM׳s) indirect preferences into the search process. Within this case study, the CO₂ emissions could be lowered significantly by accepting a marginal increase of costs over their global minimum. NSGA-II and SPEA2 enabled faster estimation of the Pareto front, but produced significantly worse solutions than the exact optimization methods. The interactive methods outperformed their a posteriori counterparts, and could discover solutions corresponding better to the DM preferences. In addition, by adjusting appropriately the elicitation interval and starting generation of the elicitation, the number of pairwise comparisons needed by the interactive evolutionary methods to construct a satisfactory solution could be decreased.     

Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications

In the last decades, green and sustainable supply chain management practices have been developed, trying to integrate environmental concerns into organisations by reducing unintended negative consequences on the environment of production and consumption processes. In parallel to this, the circular economy discourse has been propagated in the industrial ecology literature and practice. Circular economy pushes the frontiers of environmental sustainability by emphasising the idea of transforming products in such a way that there are workable relationships between ecological systems and economic growth. Therefore, circular economy is not just concerned with the reduction of the use of the environment as a sink for residuals but rather with the creation of self-sustaining production systems in which materials are used over and over again.Through two case studies from different process industries (chemical and food), this paper compares the performances of traditional and circular production systems across a range of indicators. Direct, indirect and total lifecycle emissions, waste recovered, virgin resources use, as well as carbon maps (which provide a holistic visibility of the entire supply chain) are presented. The paper asserts that an integration of circular economy principles within sustainable supply chain management can provide clear advantages from an environmental point view. Emerging supply chain management challenges and market dynamics are also highlighted and discussed.