基于JMI模式的农产品供应链管理研究

联合库存管理(Jointly Managed Inventory,JMI),是对供应链进行管理的一种有效方法;系统动力学是一门基于系统论、吸取反馈理论与信息论精髓的、借助计算机进行模拟的交叉性新学科.本文应用系统动力学的相关理论和方法,从系统性和动态性的角度对传统库存管理模式与联合库存管理模式进行了仿真分析和对比,并借助Vensim仿真软件对二者皆建立了系统动力学模型,并说明了JMI模式较之传统模式,在削减上、中、下游企业节点库存方面具有较大的优越性.     

供应链网络系统的牛鞭效应时滞因素分析与库存控制策略研究

牛鞭效应的存在严重影响了供应链系统的运作效率,增加了供应链管理的复杂性。本文基于供应链网络库存状态的内部系统动力学机制,构建了供应链网络库存系统的状态转移模型,并引入时滞影响因素,通过供应链网络库存系统的波动状态描述牛鞭效应。在此模型基础上,针对供应链网络系统的牛鞭效应问题,提出了一类新的基于库存波动状态的动态供应链库存控制策略,并运用系统稳定性理论,将该策略的参数优化求解问题转化成线性矩阵不等式的求解问题。最后通过系统仿真深入分析了供应链网络库存系统对库存控制策略参数以及系统时滞因素的敏感性,并验证了该动态库存控制策略可以有效地抑制牛鞭效应。     

基于系统动力学第三方直通集配中心模式研究

采用定性分析与系统动力学建模定量研究相结合的研究方法,首先对供应链库存管理的第三方直通集配中心模式做了较为系统的分析和界定;其次,建立了第三方直通集配中心模式下的供应链系统动力学模型;最后,对第三方直通集配中心模式供应链库存管理案例进行了仿真分析,证明了该模式相对分散式VMI模式的比较优势,并对第三方直通集配中心的运营策略提出了优化建议.     

基于系统动力学的库存优化控制研究

本文首先对库存成本进行分解,在介绍传统库存管理方法如ABC分类法、定量订货法和定期订货法实施库存管理的途径的基础上.找出其在实施动态库存管理方面的不足,用系统动力学的思想和方法来建立延迟购买条件下的经济批量模型.并结合实际经济活动中存在的价格上涨情况对本模型进行修正,对库存管理活动进行优化.     

应用工业工程和信息系统促进后勤仓库管理

本文应用现代工业工程的理论与方法,论述加强仓储管理问题。从后勤库存工作量大,决策困难的库存管理系统入手,使仓库不仅具有高效率的储存功能,而且应具有控制后勤库存目标,并依据经济效益和物流系统的观点,运用计算机辅助库存管理,寻找实现仓库优化的管理信息系统,并提出实现后勤仓库管理库存优化的数学模型。     

一种考虑原材料库存成本的变质物品EPQ模型

在库存管理研究中,单独实现产成品或原材料库存成本最小,往往无法获得整个库存系统的最优控制策略.本文提出了一种同时考虑产成品和原材料库存成本的变质物品EPQ集成模型.运用迭代寻优法得到模型最优解,得出计划期内最优原材料订购次数,原材料订购周期内的最优生产次数和最优服务水平,并对主要参数进行了灵敏度分析,为生产制造企业的库存管理提供了决策依据.     

基于系统动力学的供应链中牛鞭效应的研究

本文运用系统动力学的原理和VENSIM软件构建了啤酒游戏的供应链模型.通过增加供应链模型节点个数并对其仿真结果进行分析,证明随着供应链长度的增加,牛鞭效应也愈加明显;对VMI库存管理模式与传统库存管理模式的系统结构及运营绩效进行了比较,说明供应链成员间的信息共享可以有效地弱化牛鞭效应.     

基于供应链间品牌竞争的库存管理策略研究

分析两个供应链间竞争的系统,每条供应链由一个供应商和一个零售商组成,供应商通过各自零售商销售具有品牌差异的产品,不同品牌产品之间存在替代度,零售商面临不确定性需求.在此系统上,存在供应商间的竞争、零售商间的竞争,和供应链内上下游之间的竞争,三种竞争交织.每条供应链有两种管理库存的方式,即零售商管理库存和供应商管理库存.通过对比不同库存管理方式下系统成员收益,发现,把不确定性需求风险从零售商转移给供应商,并非能增加零售商收益,或减少供应商收益;同时,通过分析了不同库存管理方式对供应链系统竞争均衡状态的影响,指出,在一定条件下,供应商管理库存方式能加强供应商端的竞争,使得零售商和供应商共同受益.     

不确定需求环境下多级库存系统优化与协调模型研究

论文首先将模糊随机变量扩展为混合随机变量,并用来描述不确定需求.然后对多级单周期库存系统在模糊随机和混合随机需求环境下的优化与协调问题作了研究,提出了通过集成库存管理使库存系统整体收益期望值最大化的优化模型和协调合作伙伴利益的数量折扣契约模型,并根据遗传算法理论和计算机模拟技术设计了求解模型的智能算法.最后通过实例对模型进行了仿真分析.     

基于VMI和TPL理论的汽车整车物流的系统动力学分析

本文针对我国汽车整车物流链库存成本居高不下的现状,基于VMI和TPL理论,运用系统动力学方法对汽车整车物流系统进行了改进,根据系统绩效指标的对比分析,说明改进系统有效性.     

Evaluation of management information systems

The economic evaluation of Management Information Systems may be based on the following theories and techniques: Control Theory, System Dynamics, (discrete-event) simulation, and gaming. Applications of these approaches are summarized. Advantages and disadvantages of the various approaches are presented.     

Systemdynamiken als anonyme Fehlerquellen

System dynamics as anonymous causes of failure Dynamics of problem solving, dynamics of communication as well as dynamics of success are basic challenges in organizations. To ignore them may bring about severe failures in terms of economics and of the personnel. Therefore, it is important to clearly discern these various dynamics and to cope with them.     

Discussing feedback system thinking in relation to scenario evaluation in a balanced scorecard setup

Since the emergence of the Balanced Scorecard (BSC) at the beginning of the 1990s, literature has intensively discussed the problems of the cause-and-effect relationships, the time-delay elements between measures and perspectives and the concepts of feedback loops. This article focuses on the use of the System Dynamics Modelling approach to deal with these three problems, an approach first suggested by Forrester back in 1958. The wide scope of application of BSC as a decision-supporting instrument continues to spur the interest in BSC. We have used an actual case as inspiration on which our model construction and our simulation scenarios are based. Our findings suggest that the idea of linking BSC and System Dynamics together based on properties of the systems dynamic nature seem to be both a natural and a relevant development. Furthermore, our simulations demonstrate the ability to: (1) provide a scheme for the translation of the strategy into operational terms and at the same time (2) offer possibilities for the decision maker to be able to evaluate the plan–do–review results based on the feedbacks, specifically in a risk evaluating context.     

System dynamics modeling

The System Dynamics approach to modeling social systems appears to be gaining rapid acceptance as a legitimate tool of management science even as it still evokes controversy. Some of its basic assumptions, strategies and conventions are indicated. Modeling with this methodology is described. Primarily for pedagogical reasons, four approaches to starting a model are identified with some indications as to which of some of the published models might have used them. Finally, the issue of nonlinear relationships is raised. Some of the ways in which this matter can be dealt with are sketched.     

Book Reviews

Books reviewed:
Office International Des Epizooties (World Organization for Animal Health) World Animal Health in 1998, Part 1: Reports on the Animal Health Status and Disease Control Methods and Tables on Incidence of List A Diseases and Part 2: Tables on the Animal Health Status and Disease Control Methods
Peter Sedlmeier. Lawrence Erlbaum Associates, Mahwah Improving Statistical Reasoning: Theoretical Models and Practical Implications
Andrew Ford. Island Press Modeling the Environment. An Introduction to System Dynamics Modeling of Environmental Systems
Jacob I. Bregman. Lewis Publishers, Boca Raton Environmental Impact Statements, Second Edition     

Book Reviews

Books reviewed: S. Moolgavkar, D. Krewski, L. Zeise, E. Cardis, and H. Møller, Quantitative Estimation and Prediction of Human Cancer Risks Jacqueline Karnell Corn, Environmental Public Health Policy for Asbestos in Schools: Unintended Consequences Andrew Ford, Modeling the Environment. An Introduction to System Dynamics Modeling of Environmental Systems James Hamilton and W. Kip Viscusi, Calculating Risks? The Spatial and Political Dimensions of Hazardous Waste Policy Sharon M. Friedman, Sharon Dunwoody, and Carol L. Rogers, Communicating Uncertainty: Media Coverage of New and Controversial Science     

Scrutinising the interplay between governance and resilience in supply chain management: A systems thinking framework

Supply chain disruptions recurrently challenge end-to-end operations owing to the ambiguous understanding of the role of governance in impacting supply network resilience. This paper scrutinises the relevant literature to understand the plethora of interpretations in supply chain governance and resilience while further providing a new perspective on the representation of the interplay between governance and resilience in supply chains. In this regard, the Systems Thinking lens is adopted to pull together the typologies and constructs of supply chain governance and resilience from the literature. Methodologically, System Dynamics modelling principles are leveraged to capture the underpinning structural interdependencies in a causal loop diagram. The study reveals that endogenous and exogenous supply chain governance processes and mechanisms support the intrinsic and extrinsic resilience in networks. Overall, this research contributes to the supply chain risk management domain by synthesising the interplay between governance and resilience, identifying pertinent typologies, and articulating research propositions that can inform decision-making at policy and management levels.     

The Impact of Product Lifecycle on Capacity Planning of Closed‐Loop Supply Chains with Remanufacturing

Product recovery operations in reverse supply chains face rapidly changing demand due to the increasing number of product offerings with reduced lifecycles. Therefore, capacity planning becomes a strategic issue of major importance for the profitability of closed‐loop supply chains. This work studies a closed‐loop supply chain with remanufacturing and presents dynamic capacity planning policies developed through the methodology of System Dynamics. The key issue of the paper is how the lifecycles and return patterns of various products affect the optimal policies regarding expansion and contraction of collection and remanufacturing capacities. The model can be used to identify effective policies, to conduct various “what‐if” analyses, and to answer questions about the long‐term profitability of reverse supply chains with remanufacturing. The results of numerical examples with quite different lifecycle and return patterns show how the optimal collection expansion/contraction and remanufacturing contraction policies depend on the lifecycle type and the average usage time of the product, while the remanufacturing capacity expansion policy is not significantly affected by these factors. The results also show that the collection and remanufacturing capacity policies are insensitive to the total product demand. The insensitivity of the optimal policies to total demand is a particularly appealing feature of the proposed model, given the difficulty in obtaining accurate demand forecasts.     

A simulation system for corporate planning

This paper describes the structure and use of a general purpose simulation package developed for the interactive construction of dynamic computer-based simulation models. The package consists of a system of computer programs written in the BASIC language for a Digital PDP 11/70 time-sharing computer.The framework upon which the package is based is essentially an amalgamation of the System Dynamics and Input-Output approaches to the modelling of complex organizations. Networks of levels and flows provide the basis for dynamic, modular representation, while matrix algebra features provide the basis for aggregational flexibility and the analysis of multi- product multi-process industrial systems.The package is designed to provide planning managers with the ability to construct flexible models, localized or ‘corporate’, financial or non-financial, without the need for any programming in the conventional sense. A flow diagram of the system to be modelled guides the model builder in responding to computer terminal prompts which determine the model structure as a set of programmed relationships. This in turn gives rise to a further series of prompts at the terminal for the entry of all data pertinent to the model. Model editing and computation then proceeds, with user interaction, if desired, for amendments, monitoring of computations, and report generation.Two specific applications of the package are discussed in the latter part of the paper, and sample output from runs of both of the resultant models is provided.     

A dynamic business modelling approach to design and experiment new business venture strategies

Business Modelling has evolved as a key activity to reflect new business venture strategy by framing the way a firm will operate and how it will function in achieving its goals (e.g., profitability, growth, innovation, social impact). However, scholars and practitioners have criticized the adoption of a too static perspective in the design and use of conventional Business Model representations. Such a static perspective prevents nascent entrepreneurs experimenting with their Business Models and, as a result, identifying the most effective strategies, especially in terms of business sustainability and profitability. In this paper, we argue that combining conventional Business Model schemas with System Dynamics modelling results in a strategy design tool that may overcome several limitations related to a static view of Business Model representation. Mapping the different key elements underlying value creation processes into a system of causal interdependencies – through the use of simulation – allows strategy analysts and entrepreneurs to experiment and learn how the business reacts to strategic and organizational changes in terms of performance, innovation and value creation. As such, Dynamic Business Models provide useful insights to strategy formulation and business venturing by capturing how critical Business Model elements interact to produce enduring competitive advantages over time.