集成供应链系统生产决策行为混沌特性研究

供应链集成是当前供应链管理领域研究的热点和难点问题。近年来许多学者以整个供应链系统为对象,通过优化供应链上各种资源,使供应链整体效应达到最优,降低局部生产决策对整个供应链的影响。然而,由于集成供应链系统生产过程是一个复杂的非线性系统,集成供应链系统局部生产决策的复杂性导致集成建模的复杂性。现有的研究成果还难以实现集成供应链整体协调,研究方法具有很大的局限性。本文针对局部生产决策对整个集成供应链系统的影响,基于柯布—道格拉斯函数进行集成建模,并通过相空间重构确定系统的关联维数和计算最大李雅普诺夫指数来界定集成供应链系统混沌特性,为研究供应链集成的复杂性提供理论依据。     

Use of Multicriteria Decision Analysis to Support Weight of Evidence Evaluation

Weight of evidence (WOE) methods are key components of ecological and human health risk assessments. Most WOE applications rely on the qualitative integration of diverse lines of evidence (LOE) representing impact on ecological receptors and humans. Recent calls for transparency in assessments and justifiability of management decisions are pushing the community to consider quantitative methods for integrated risk assessment and management. This article compares and contrasts the type of information required for application of individual WOE techniques and the outcomes that they provide in ecological risk assessment and proposes a multicriteria decision analysis (MCDA) framework for integrating individual LOE in support of management decisions. The use of quantitative WOE techniques is illustrated for a hypothetical but realistic case study of selecting remedial alternatives at a contaminated aquatic site. Use of formal MCDA does not necessarily eliminate biases and judgment calls necessary for selecting remedial alternatives, but allows for transparent evaluation and fusion of individual LOE. It also provides justifiable methods for selecting remedial alternatives consistent with stakeholder and decision‐maker values.     

CAPACITY AND PRODUCTION DECISIONS IN STOCHASTIC MANUFACTURING SYSTEMS: AN ASYMPTOTIC OPTIMAL HIERARCHICAL APPROACH

We present a new paradigm of hierarchical decision making in production planning and capacity expansion problems under uncertainty. We show that under reasonable assumptions, the strategic level management can base the capacity decision on aggregated information from the shopfloor, and the operational level management, given this decision, can derive a production plan for the system, without too large a loss in optimality when compared to simultaneous determination of optimal capacity and production decisions. The results are obtained via an asymptotic analysis of a manufacturing system with convex costs, constant demand, and with machines subject to random breakdown and repair. The decision variables are purchase time of a new machine at a given fixed cost and production plans before and after the purchase. The objective is to minimize the discounted costs of investment, production, inventories, and backlogs. If the rate of change in machine states such as up and down is assumed to be much larger than the rate of discounting costs, one obtains a simpler limiting problem in which the random capacity is replaced by its mean. We develop methods for constructing asymptotically optimal decisions for the original problem from the optimal decisions for the limiting problem. We obtain error estimates for these constructed decisions.     

互动公平、委员会决策程序公平与员工决策承诺:基于公平启发理论与不确定管理理论的实证研究

借助层级团队形式制定决策,决策者能激发员工的决策承诺,确保决策的有效执行。以委员会作为决策者的层级团队为例,本文探讨了以下问题:当存在个体对自身胜任力的自信、专用性人力资本投资这两个因素的影响时,互动公平与委员会决策程序公平效应及它们之间的交互效应会发生什么变化?引入公平启发理论与不确定管理理论,本文假设并检验了上述四个因素如何交互作用于员工决策承诺。以两家大型商业银行信贷业务人员为研究对象,实证研究表明:(1)自信和专用性人力资本投资对委员会决策程序公平效应有着显著调节作用,但它们对互动公平效应的调节作用不显著;(2)当存在自信和专用性人力资本投资的影响时,较强的互动公平与委员会决策程序公平之间的交互效应更稳定一些,而较低的互动公平感知与程序公平之间的交互效应在方向上发生变化。本文有助于管理者理解"公平何时能引致员工合作"这一问题,帮助其更好地把握决策过程以获得员工对其决策的支持。本研究的假设完全基于公平启发理论(FHT)和不确定管理理论(UMT)的理论逻辑做出,实证结果与FHT和UMT的理论预测以及已有实证研究结果相一致,这意味着本研究具有较高可信性和可靠性,能为进一步理论探索提供了比较坚实的基础。     

LOGISTICS MANAGEMENT SYSTEM: AN ADVANCED DECISION SUPPORT SYSTEM FOR THE FOURTH DECISION TIER DISPATCH OR SHORT-INTERVAL SCHEDULING

The Logistics Management System (LMS) is a real-time transaction-based system combining decision technologies from AI, MS/OR, and decision support system that serves very successfully as a dispatcher or short-interval scheduler by monitoring and controlling the manufacturing flow of IBM's semiconductor facility near Burlington, Vermont. LMS coordinates the actions and decisions of several logically isolated participants in a serially dependent system of activities. Therefore, it balances the requirements of several goals (cycle time, output, serviceability, and inventory management) that compete for the same resource, exploits emerging opportunities on the manufacturing floor, and reduces the distortion from unplanned events. This paper provides an overview of the LMS application, the concept of interrelated decision tiers in manufacturing decision making, and the need for the dispatch decision tier to successfully reduce apparent randomness. Historically, production and operations management has ignored this decision tier. This has significantly limited our ability to make an impact on the performance of the manufacturing operation.     

Decision knowledge sharing: flexible supply chains in KM context

Supply chain excellence has a real impact on business strategy. Building supply chains as flexible systems represents one of the most exciting opportunities to create value and one of the most challenging tasks for the policy makers. It requires integrated decision making amongst autonomous chain partners with effective decision knowledge sharing between them. The key to success lies in knowing which decision has more impact on the overall performance and this can be achieved by appropriate knowledge sharing. In this context, knowledge management (KM) can be used as an effective approach to achieve knowledge sharing and decision synchronisation in supply chains. Flexible supply chains (FSC_s) are more complex and involve multiple autonomous players with varying technical cultures (affects knowledge mindsets), managerial background (affects decision knowledge) and supply chain management (SCM) exposures (affects knowledge sharing attitudes). Thus there is a need to develop demo models that can encourage chain managers towards collaborative knowledge sharing in the supply chains. This paper presents the application of one such model based on decision knowledge sharing (DKS) for improved supply chain management. A simulation model of a flexible supply chain based on DKS framework is developed for demo purposes. The key results are highlighted along with industry implications. The cost based performance of DKS at different levels of flexibility is studied. Thus a careful analysis of the chain with a focus on collaborative decisions is useful to ensure success. This paper addresses this interesting and challenging domain.     

Learning from the Piper Alpha Accident: A Postmortem Analysis of Technical and Organizational Factors

The accident that occurred on board the offshore platform Piper Alpha in July 1988 killed 167 people and cost billions of dollars in property damage. It was caused by a massive fire, which was not the result of an unpredictable "act of God" but of an accumulation of errors and questionable decisions. Most of them were rooted in the organization, its structure, procedures, and culture. This paper analyzes the accident scenario using the risk analysis framework, determines which human decision and actions influenced the occurrence of the basic events, and then identifies the organizational roots of these decisions and actions. These organizational factors are generalizable to other industries and engineering systems. They include flaws in the design guidelines and design practices (e.g., tight physical couplings or insufficient redundancies), misguided priorities in the management of the tradeoff between productivity and safety, mistakes in the management of the personnel on board, and errors of judgment in the process by which financial pressures are applied on the production sector (i.e., the oil companies' definition of profit centers) resulting in deficiencies in inspection and maintenance operations. This analytical approach allows identification of risk management measures that go beyond the purely technical (e.g., add redundancies to a safety system) and also include improvements of management practices.     

Development and teaching a computer-assisted course in production planning

Abstract. Course development and student activities are described for a successful computer-assisted senior level course in production planning. Development was guided by the view that students must (1) understand the elements being integrated, (2) understand the problems that are being resolved through integration, and (3) participate in the integration activity. Production planning is treated as a hierarchy of individual decision situations which are to be integrated. Each decision is assisted by a software-based technique. A menu program and a common database were developed to allow a student to become the 'integrator' by directing the information flow among the individual decision situations. The paper describes the development tasks, the course elements, and student activities which provide guidelines for others developing similar courses.     

Beyond Make‐Buy: Internalization and Integration of Design and Production

Much recent attention in industrial practice has been centered on the question of which activities a manufacturing firm should complete for itself and for which it should rely on outside suppliers. This issue, generally labeled the “make‐buy” decision, has received substantial theoretical and empirical attention. In this paper, we broaden the scope of the make‐buy decision to include product design decisions, as well as production decisions. First, we examine independently the decisions of whether to internalize design and production, and then we consider how design and production organizational decisions are interdependent. The specific research questions we address are: (1) How can design and production sourcing decisions be described in richer terms than “make” and “buy”? (2) Do existing theories of vertical integration apply to product design activities as well as production decisions? (3) What is the relationship between the organization of design and the organization of production? (4) What organizational forms for design and production are seen in practice? After developing theoretical arguments and a conceptual framework, we explore these ideas empirically through an analysis of design and production sourcing decisions for bicycle frames in the U. S. mountain bicycle industry.     

Zur Rolle versunkener Kosten in aufeinander folgenden IT-Outsourcing-Entscheidungen

Despite the ongoing theoretical and practical investigations of IT outsourcing, there are still a large number of projects that are unsuccessful or even fail all along the line. Studies in the decision-making literature indicate that psychological effects in the evaluation of decision-relevant facts may be one relevant reason for unsuccessful decisions. By conducting a quantitative empirical study with German IT decision makers, we investigate the influence of non-rational factors within consecutive IT outsourcing decisions. We show that beside the rational economic factors (transaction, production and the rational part of switching costs) also non-rational switching costs in terms of sunk cost do significantly contribute to the explanation of consecutive IT outsourcing decisions. Furthermore, we examine moderating effects that affect the non-rational behavior of IT decision makers. Besides the theoretical contribution to analyze the effects of sunk cost on both an individual and organizational level, we also derive practical implications. In consecutive IT outsourcing decisions, the non-rational behavior triggered by sunk cost can for example be reduced by replacing the decision maker or consult a decision team when sunk cost play a considerable role.     

Robustness of linear models in dynamic multivariate predictions

Linear aggregation models employing unit and equal weights have been shown to be superior to human decisions in a surprising range of decision situations. In addition, decisions based on these models have often been found to be superior to those based on linear regression models (LRMs). This general issue was explored for repetitive decisions in production planning. The problem considered differs in several aspects from the types of problems investigated previously: (1) the problem is dynamic rather than static; (2) a set (or vector) of interactive decisions dependent on previous decisions is required to be made, where a decision in stage t, the dependent variable, becomes an independent variable in stage t + 1; and (3) the criterion function is cost with a quadratic loss function (rather than the correlation measure of R²). Moreover, since repetitive decisions were involved, the parameters of the models were estimated using past human decisions. These were used to predict specific values of the decision variables (rather than rank order), which in turn were employed recursively to predict values of the decision variables at subsequent stages. While decisions from equal weighting rules were found to be superior to human decisions and not greatly inferior to decisions from linear regression models, decisions from unit weighting rules performed poorly. The rationale for such performance is discussed, indicating that previous theoretical and empirical research on linear weighting models is not generally applicable to dynamic, multivariate interactive decisions problems with lagged variables.     

A generic accounting model to support operations management decisions

Information systems are generally unable to generate information about the financial consequences of operations management decisions. This is because the procedures for determining the relevant accounting information for decision support are not formalised in ways that can be implemented in information systems. This paper describes a formalised procedure, which is based on the following theoretical propositions: (i) cost behaviour is described on the basis of a company's contracts for purchasing and selling resources, and (ii) hierarchical relationships between decisions are recognised, because some decisions have to be made earlier than others. Earlier decisions determine the feasible alternatives for later decisions (e.g. through constraints in available production capacity or components), and the plans that supported the earlier decisions serve as instructions for later decisions. The procedure can be implemented in information systems to provide accounting information in case later decisions deviate from these instruc tions (within the limits of the real-world constraints) because new information becomes available.     

What Can Decision Analysis Do for Invasive Species Management?

Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach.     

A CONCEPTUAL DESCRIPTION OF A FINANCIAL PLANNING MODEL FOR COMMERCIAL BANKS

This paper describes a conceptually sound and powerful model to aid bank managers in short and long range decision making for the management of the financial performance of the bank. The planning model is a key element in an integrated computer-based planning system which includes a forecast of economic, monetary, and loan market conditions, an analysis of internal relationships, and a system of reports which provide management with access to historical data and planning summaries. The planning model at the heart of the system, contains an imbedded linear programming algorithm to optimize “balance sheet management” decisions within liquidity and capital adequacy constraints. The model recognizes the interaction between assets and liabilities, it recognizes the time value of money, and it accommodates the difference between the net marginal yield for decision making, and the gross average yield used for determining revenue. Finally, the model recognizes the crucial role of liquidity with an important treatment of gross cash flows from normal asset turnover as a major source of liquidity, and the liquidity aspects of liabilities, as well as the more traditional concept of asset marketability.     

Decision Making and Cognition in Multi‐Echelon Supply Chains: An Experimental Study

Supply chain performance often depends on the individual decisions of channel members. Even when individuals have access to relevant information, order variation tends to increase when moving up the supply chain, a phenomenon known as the bullwhip effect. While prior research has investigated several structural/environmental factors which can mitigate the bullwhip effect, the underlying behavioral factors contributing to it are an open question. Using a production and distribution decision‐making simulation representing a four‐stage serial supply chain, we find that the cognitive profile of decision makers contributes to the bullwhip effect. We found that the specific decision tendency to underweight the supply line is linked to an individual's level of cognitive reflection. Furthermore, performance differs for entire supply chains and for specific echelons, and holds under standard mitigation efforts. The findings have implications for supply chain design, education, and industry.     

Adoption of Individual Flood Damage Mitigation Measures in New York City: An Extension of Protection Motivation Theory

This study offers insights into factors of influence on the implementation of flood damage mitigation measures by more than 1,000 homeowners who live in flood‐prone areas in New York City. Our theoretical basis for explaining flood preparedness decisions is protection motivation theory, which we extend using a variety of other variables that can have an important influence on individual decision making under risk, such as risk attitudes, time preferences, social norms, trust, and local flood risk management policies. Our results in relation to our main hypothesis are as follows. Individuals who live in high flood risk zones take more flood‐proofing measures in their home than individuals in low‐risk zones, which suggests the former group has a high threat appraisal. With regard to coping appraisal variables, we find that a high response efficacy and a high self‐efficacy play an important role in taking flood damage mitigation measures, while perceived response cost does not. In addition, a variety of behavioral characteristics influence individual decisions to flood‐proof homes, such as risk attitudes, time preferences, and private values of being well prepared for flooding. Investments in elevating one's home are mainly influenced by building code regulations and are negatively related with expectations of receiving federal disaster relief. We discuss a variety of policy recommendations to improve individual flood preparedness decisions, including incentives for risk reduction through flood insurance, and communication campaigns focused on coping appraisals and informing people about flood risk they face over long time horizons.     

A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach

Large-scale multinational manufacturing firms often require a significant investment in production capacity and extensive management efforts in strategic planning in an uncertain business environment. In this research we first discuss what decision terms and boundary conditions a holistic capacity management model for the manufacturing industry must contain. To better understand how these decision terms and constraints have been employed by the recent model developers in the area of capacity and resource management modelling for manufacturing, 69 optimisation-based (deterministic and stochastic) models have been carefully selected from 2000 to 2018 for a brief comparative analysis. The results of this comparison shows although applying uncertainty into capacity modelling (in stochastic form) has received a greater deal of attention most recently (since 2010), the existing stochastic models are yet very simplistic, and not all the strategic terms have been employed in the current model developments in the field. This lack of a holistic approach although is evident in deterministic models too, the existing stochastic counterparts proved to include much less decision terms and inclusive constraints, which limits them to a limited applications and may cause sub-optimal solutions. Employing this set of holistic decision terms and boundary conditions, this work develops a scenario-based multi-stage stochastic capacity management model, which is capable of modelling different strategic terms such as capacity level management (slight, medium and large capacity volume adjustment to increase/decrease capacity), location/relocation decisions, merge/decomposition options, and product management (R&D, new product launch, product-to-plant and product-to-market allocation, and product phase-out management). Possibility matrix, production rates, different financial terms and international taxes, inflation rates, machinery depreciation, investment lead-time and product cycle-time are also embedded in the model in order to make it more practical, realistic and sensitive to strategic decisions and scenarios. A step-by-step open-box validation has been followed while designing the model and a holistic black-box validation plan has been designed and employed to widely validate the model. The model then has been verified by deploying a real-scaled case of Toyota Motors UK (TMUK) decision of mothballing one of their production lines in the UK after the global recession in 2010.     

An integrative framework for studying sustainable practices and its adoption in the AEC industry: A case study

The diversity of priorities and differing awareness of sustainable practices among stakeholders in the architecture, engineering and construction industry is critically shaping the adoption of green technology, and the rate at which the industry is shifting towards more sustainable practices. In this paper, we develop an integrated framework that allows reorganization and integration of existing sustainability research in the architecture, engineering, and construction (AEC) industry, emphasizing the perspective of decision-makers and stakeholders. Further, an agent-based model is introduced that allows study of the decision-maker with the decision context, thus making them an integral part of the decision-making process rather than independent of it. The coupled system is adaptive and dynamically organizes itself to reflect complex bottom-up interactions between individual stakeholders, their contexts and the constraints driving their decisions even as they implement or respond to top-down decisions pertaining to the adoption of sustainable practices. The contention of this research is that an integrative systems approach to top-down decision-making and an understanding of bottom-up influences in stakeholder decisions is critical to the understanding sustainable practices and decisions that lead to their adoption in the AEC industry.     

Subordinate Participation in Audit Budgeting Decisions: A Comparison of Decisions Influenced by Organizational Factors to Decisions Conforming with the Vroom-Jago Model*

This study examines the role of subordinate participation in the effectiveness of audit hours budget decisions in accounting firms. The study compares decisions influenced by organizational factors (such as organizational policies or the preferences of the superior) to decisions that conform to the Vroom-Jago (VJ) model. Our results indicate that actual level of participation used in budget decisions appears to be based primarily on perceived preferences of superiors and participation styles available under the circumstancesof the individual audit. However, results also indicate that decisions consistent with the Vroom-Jago model are characterized by higher decision quality and increased subordinatedevelopment. Since managers are apparently reluctant to use decision styles that conflictwith organizational factors, accounting firms may wish to gather information regarding the attributes of the decision context and use the VJ model to establish their available decision styles and determine the preferences of superiors. Doing so has the advantage of considering decision-specific attributes while enhancing the probability of manager compliance with a desired decision style.