Internal resource waste and centralization degree in two-stage systems: An efficiency analysis

Internal resource waste refers to the waste in the intermediate resources between the upstream stage and downstream stage in a production or service system. This study examines a system with a two-stage structure, in which the outputs from the first stage are taken as the inputs for the second stage. Two-stage systems can exist in centralized, decentralized, or mixed organizational modes. In this paper, we propose two-stage DEA models considering a degree of centralization that makes it possible to measure internal resource waste in different system modes. Some managerial insights are tested and verified from the perspective of efficiency analysis. We find that: 1) when there is only one intermediate measure in a centralized two-stage system, internal resource waste can be eliminated completely, and 2) a higher degree of centralization in a two-stage system can lead to less internal resource waste and more expected outputs. Finally, we present a numerical example and two practical real-world examples that illustrate our approach and findings.     

基于主从博弈的两部门并行系统的效率评价

本文研究了一类典型并行系统的效率评价问题：（1）决策单元由两个并行的子单元组成;（2）在整个系统中,某一子单元居于主导地位,另一子单元居于从属地位;（3）两个子单元之间存在部分共享的投入资源,且无法明显区别该资源在不同子单元之间的分配比例。在分析决策单元整体效率及内部子单元效率的基础上,基于主从博弈思想,提出一种能同时确定系统整体效率及内部子单元效率的评价方法,该方法能够在评价系统效率的同时,实现共享资源的有效分配。最后,采用一个实例分析说明了所提方法的合理性和有效性。     

Allocating a fixed cost across the decision making units with two-stage network structures

A prominent issue in many organizations involves the fair allocation of a total fixed cost among a group of entities. This paper extends the traditional fixed cost allocation problem to situations where the decision making units (DMUs) have a two-stage network structure. To this end, this paper first uses the data envelopment analysis (DEA) methodology to determine the relative efficiency while taking the internal structure and possible allocated costs into account. It shows that each DMU can separately maximize its relative efficiency to one through determining a series of allocations and selecting a set of relative weights. Next, we demonstrate that there exists an efficient allocation set based on a set of common weights, using which all DMUs and their two sub-stages can be simultaneously efficient. However, there are alternative allocation plans in the efficient allocation set. According to this non-uniqueness problem, we further optimize the allocation plans by taking the size of operation units into account, such that the allocation result is proportional to current input usages and output productions from a size point of view. In addition, we suggest a min–max model and a feasible computation algorithm for it to generate the final allocation plan in a way that minimizes the deviation between the efficient allocations and size allocations. More importantly, by repeatedly minimizing the maximum deviation, our proposed method can guarantee a unique allocation plan for all DMUs and sub-stages. Finally, both a numerical example modified from previous literature and an empirical application of bank activities are used to demonstrate the efficacy and usefulness of the proposed approach.     

Effort Observability,Incentive Systems,and Organizational Forms

This paper analyses the choice between a centralized and a decentralized organizational structure focusing on the relationship existing between the allocation of decision rights, the degree of observability of effort and the use of different compensation systems. Profitable production is realized thanks to good information being available during the project selection stage and hard work being performed in the implementation stage. Selection of projects may be made by the principal (hierarchy) or by the agent (delegation). Under the hierarchical system, the principal's participation in the design of projects allows her to gather useful information for the design of a more accurate compensation system. Therefore, we analyse the trade‐off between optimal use of available information and accuracy of incentive systems, which emerges in the choice of organizational form.     

DEA-based fixed cost allocation in two-stage systems: Leader-follower and satisfaction degree bargaining game approaches

This paper proposes new fixed cost allocation approaches for allocating a fixed cost among decision-making units (DMUs) with two-stage structures under the framework of data envelopment analysis (DEA). Firstly, we give the set of possible fixed cost allocations, prove that all DMUs can be overall efficient when evaluated by a common set of weights after fixed cost allocation. Secondly, from a centralized point of view, we consider the competition between the DMUs’ two stages in fixed cost allocation and regard these two kinds of stages as two unions. Then, we incorporate leader-follower models to propose a fixed cost allocation approach to handle the situation in which the two unions make decisions sequentially. Based on the result of these models, a concept of satisfaction degree of each union on a fixed cost allocation is presented. A satisfaction degree bargaining game model is then proposed to obtain a fixed cost allocation which is a bargaining equilibrium of the two unions. We show that the proposed approaches always obtain a fixed cost allocation that is proportionally invariant. Additionally, the satisfaction degree bargaining game approach automatically guarantees the uniqueness of the fixed cost allocation. These properties make the fixed cost allocation generated by our approaches more stable and more acceptable. Finally, a numerical example and an application of fixed cost allocation among bank branches are given to illustrate the proposed approach and to compare it with a benchmark approach among the current studies, respectively.     

A Risk-sharing Approach to Transfer Pricing and Incentive Compensation Problems under Exchange Rate Uncertainty*

This study examines the transfer pricing and incentive compensation problems in a multinational enterprise facing currency risk. It is shown that, in the presence of diverse risk preferences among managers, the Hirshleifer (1956) transfer pricing rule results in inefficient resource allocation decisions by division managers. Following the approach developed by Kanodia (1979), two transfer pricing and compensation systems are proposed. The proposed systems enable central management to achieve efficient resource allocation and partial or global risk sharing. It is also argued that the proposed plans can be implemented in conjunction with existing transfer pricing systems that primarily serve tax and tariff concerns.     

Target intermediate products setting in a two-stage system with fairness concern

In a two-stage system with two divisions connected in series, fairly setting the target outputs for the first stage or equivalently the target inputs for the second stage is critical, in order to ensure that the two stages have incentives to collaborate with each other to achieve the best performance of the whole system. Data envelopment analysis (DEA) as a non-parametric approach for efficiency evaluation of multi-input, multi-output systems has drawn a lot of attention. Recently, many two-stage DEA models were developed for studying the internal structures of two-stage systems. However, there was no work studying fair setting of the target intermediate products (or intermediate measures) although unreasonable setting will result in unfairness to the two stages because setting higher (fewer) intermediate measures means that the first (second) stage must make more efforts to achieve the overall production plan. In this paper, a new DEA model taking account of fairness in the setting of the intermediate products is proposed, where the fairness is interpreted based on Nash bargaining game model, in which the two stages negotiate their target efficiencies in the two-stage system based on their individual efficiencies. This approach is illustrated by an empirical application to insurance companies.     

不对称信息下反恐阻止网络设计

当前，我国面临的恐怖主义威胁日益严峻。为防止境外恐怖分子潜入，政府可设计反恐阻止网络，通过在交通网络中有效地分配例如安检仪器、传感设备等阻断资源，来提前识别和拦截正在潜入的恐怖分子。特别地，考虑信息不对称情形，把阻断资源分为"公开"和"隐蔽"两种类型，并假设恐怖分子观察不到"隐蔽"阻断。主要研究政府应如何同时优化两类阻断方案，才能发挥信息优势，设置"陷阱"并降低袭击分析。首先，将该问题构造为双层规划模型，上层规划是关于政府的阻止网络设计问题，下层规划则是关于恐怖分子的袭击节点选择和入侵路径优化问题。随后，设计一类用改进遗传算法处理上层规划，并结合下层规划直接求解的混合算法。其中，改进体现于杂交算子和变异算子的设计。最后，结合喀什地区进行算例分析，并分析"隐蔽"阻断的作用机理。     

Long range planning of U.K. and Japanese corporations—A comparative study

The author conducted mail surveys on long-range planning systems in Japanese and British corporations. He also made a number of visits to corporations in both countries to analyse the similarities and differences in the planning systems.In the U.K., the clarification of goals and the resource allocation are emphasized but in Japan clarification of goals and basic problem finding are stressed.The strategic projects are not necessarily formulated in the long-range planning process. The relationship between the project and the long-range planning was analysed and in both countries, the trend of long-range planning is towards more strategy orientation than quantitative computation.The planning process in Japan is more centralized. The management committee plays an important role in reviewing and making the final decision. In the U.K., the plan initiation is more decentralized, and in the final decision the board of directors plays a more important role. The trends are, however, from bottom up approach to top down approach.Goals expressed in the long-range plan of the U.K. corporations put more emphasis on financial goals, but that of the Japanese corporations emphasizes growth and employee welfare.Regarding the style of strategic decision-making the subjective responses show that it is partly analytical and partly intuitive. There are some differences between two countries, but this problem needs to be analysed further.To cope with uncertainty, multiple scenarios and contingency plans are more frequently used in the U.K., whereas in Japan the sequential decision is more commonly used. British corporations are better prepared for uncertainty than Japanese corporations.The key success factors of long-range planning are similar in both countries. The involvement of top management and cooperation of line management are two important items. Differences are that in the U.K. the planning system is emphasized in addition to the other factors, but in Japan clear goals are more emphasized.     

Centralized resource allocation based on efficiency analysis for step-by-step improvement paths

The existing centralized resource allocation models often assume that all of the DMUs are efficient after resource allocation. For the DMU with a very low efficiency score, it means the dramatic reduction of the resources, which can cause the organizational resistance. In addition, in reality, it is particularly difficult for the DMUs to achieve their target efficiencies in a single step, especially when they are far from the efficient frontier. Thus, gradual progress towards benchmarking targets is gaining importance. In this paper, we present a new approach for resource allocation based on efficiency analysis under a centralized decision-making environment. Through our approach, the central decision-maker can obtain a sequence of intermediate benchmark targets based on efficiency analysis, which provide a level-wise improvement path to direct the DMUs to reach their ultimate targets on the efficient frontier in an implementable and realistic manner. Numerical examples are presented to illustrate the application procedure of the proposed approach.     

需求不确定条件下的制造商订单分配模型

制造商的订单分配作为供应链模型微观层面的重要组成部分,对提升整个供应链效率有很大影响,但需求层面的不确定因素加大了订单分配的难度。以按比例分配为原则,讨论在需求不确定条件下完全信息与不完全信息两类多供应商-单制造商的订单分配模型。重点研究完全信息条件下各方的分散决策和集中决策,由于后者能避免各参与方对其他决策方的边际影响,所以能够实现供应链总利润的最大化;其次又将不完全信息引入模型,讨论制造商如何通过折算因子结合已有信息对供应商的私人信息进行估计,进而做出决策。最后以需求服从正态分布为例对两类模型进行验证。     

Just-in-time scheduling with controllable processing times on parallel machines

We study scheduling problems with controllable processing times on parallel machines. Our objectives are to maximize the weighted number of jobs that are completed exactly at their due date and to minimize the total resource allocation cost. We consider four different models for treating the two criteria. We prove that three of these problems are NP\mathcal{NP} -hard even on a single machine, but somewhat surprisingly, the problem of maximizing an integrated objective function can be solved in polynomial time even for the general case of a fixed number of unrelated parallel machines. For the three NP\mathcal{NP} -hard versions of the problem, with a fixed number of machines and a discrete resource type, we provide a pseudo-polynomial time optimization algorithm, which is converted to a fully polynomial time approximation scheme.     

基于突变的项目组合共享资源竞争拥挤研究

对于以项目方式进行管理或生产的企业来说,共享资源在多项目、特别是项目组合(project portfolio,PP)中的合理配置是企业运营所需要解决的重要问题,对企业实现可持续发展起着关键的支撑作用。本文将突变理论引入项目组合管理问题中,在类比交通系统中车辆对交通资源竞争的基础上,提出了项目组合系统共享资源竞争拥挤概念,并对其基础变量进行了详细分析;其次,本文分析了项目组合共享资源竞争拥挤势函数和竞争稳定性,构建了以系统效率最大化为决策目标的项目组合共享资源竞争拥挤模型;最后,通过HD集团的案例分析对项目组合共享资源竞争拥挤模型的可实践性进行了验证,并以此为基础,针对项目组合管理提出了共享资源的改进管理方案。     

Goal partitioning in a hierarchical organization

A mathematical model of the resource allocation decision process in a two level decentralized organization is presented. The model and solution procedure are capable of representing a wide range of behavioral situations. Some important aspects of the model are: (1) It allows for informational autonomy at both levels of the organization. (2) The structure of the organization can affect the final decision. (3) The goal setting behavior of the superordinate and the subordinates explicitly accounts for the decision maker's “bounded rationality”. (4) The model explicitly allows for both the superordinate and the subordinates to have their own set of goals. (5) A final decision is reached through an iterative information exchange between the superordinate and the subordinates. (6) The solution procedure leads to a resource allocation plan which reflects both the superordinate's goals and the subordinates' goals.     

Interdependent Network Recovery Games

Recovery of interdependent infrastructure networks in the presence of catastrophic failure is crucial to the economy and welfare of society. Recently, centralized methods have been developed to address optimal resource allocation in postdisaster recovery scenarios of interdependent infrastructure systems that minimize total cost. In real-world systems, however, multiple independent, possibly noncooperative, utility network controllers are responsible for making recovery decisions, resulting in suboptimal decentralized processes. With the goal of minimizing recovery cost, a best-case decentralized model allows controllers to develop a full recovery plan and negotiate until all parties are satisfied (an equilibrium is reached). Such a model is computationally intensive for planning and negotiating, and time is a crucial resource in postdisaster recovery scenarios. Furthermore, in this work, we prove this best-case decentralized negotiation process could continue indefinitely under certain conditions. Accounting for network controllers' urgency in repairing their system, we propose an ad hoc sequential game-theoretic model of interdependent infrastructure network recovery represented as a discrete time noncooperative game between network controllers that is guaranteed to converge to an equilibrium. We further reduce the computation time needed to find a solution by applying a best-response heuristic and prove bounds on ε-Nash equilibrium, where ε depends on problem inputs. We compare best-case and ad hoc models on an empirical interdependent infrastructure network in the presence of simulated earthquakes to demonstrate the extent of the tradeoff between optimality and computational efficiency. Our method provides a foundation for modeling sociotechnical systems in a way that mirrors restoration processes in practice.     

一种策略层项目计划的双目标优化方法

针对产品开发项目管理的实际情况,对策略层计划优化方法进行研究。以工作包的工作量估算为基础,以资源投入水平和工期最小化为目标,考虑各种约束条件,提出一种策略层项目计划问题的混合整数规划问题模型。以非支配遗传算法NSGA-II为基础框架,设计了一种改进的双目标遗传算法。该算法针对问题的特点,提出了基于资源平滑的解码算法。参考NSGA-III的关键特征,对拥挤密度计算方法进行改进。通过企业实际项目案例,验证了算法的性能和所提出的策略层项目计划方法的有效性。     

考虑顾客缺货反应的多产品两阶段JIT联合订货

为了解决多产品两阶段联合订货决策问题,综合考虑顾客缺货反应及资源限制对订货决策的影响,提出资源限制条件下考虑CRS的多产品两阶段JIT联合订货策略。在此基础上,以零售商收益最大化为目标,建立了多产品两阶段JIT联合订货决策模型,并从初始解生成和殖民地国家革命方式两方面设计了改进的帝国主义竞争算法。从Gruen调查报告中选取三种不同规模的算例验证了模型和算法的适用性和有效性。研究表明：本文提出的考虑顾客缺货反应的多产品两阶段JIT联合订货方法既可以提高零售商的总收益,也能提高顾客的服务水平;当单位库存资源机会收益相近时,同组产品间不会发生替代情况,而当同组产品间的单位库存资源机会收益差距较大,且高于其他产品组的单位库存资源机会收益时,则该产品组便会出现缺货和替代情况,且若该组缺货产品的剩余资源单位机会收益小于其他组产品的单位资源机会收益,则该产品的剩余资源便会转移给其他缺货产品。研究结论可为零售商多产品两阶段JIT联合订货决策提供有益的参考。     

Exploring the effect of national cultures on organizational commitment of bicultural employees

Many organizations today operate globally and employ a significant number of bicultural employees. Consequently, it is extremely important to conduct research that furthers our understanding of bicultural employees in an organizational context. In addition, research that furthers our understanding of an employee attitude such as the organizational commitment of bicultural employees will have practical significance for organizations seeking to maximize employee commitment. This paper presents two profiles of biculturals based on predominant identification to individualist or collectivist national cultures and offers rationale to support the premise that organizational commitment will differ between collectivist and individualist biculturals. Exploring the national cultural dimensions of organizational commitment of bicultural employees as conceptualized in this paper provides human resource development (HRD) an excellent opportunity to research these two constructs that significantly impact organizational outcomes.     

基于患者两阶段医疗服务过程的病床资源优化

随着医疗需求的日益增长，供需不平衡的矛盾日益显著，病床资源短缺已经成为制约医疗服务发展的重要因素之一。针对病床资源供需失衡的问题，本文构建患者两阶段医疗服务过程的病床资源优化模型。考虑患者的医疗服务是一个两阶段串联排队过程，第一阶段是强制治疗阶段，第二阶段是康复阶段。在患者排队系统中，服务台总数固定的前提下，本文利用增补变量方法给出了该排队系统的概率等式，通过求解偏微分方程得出系统的状态概率，并推导出医院拒绝患者的概率、平均康复时间等相关指标。考虑部分患者因病床资源不足而无法入院和康复阶段患者提前出院两种风险因素，本文基于排队指标构建多病种间的病床分配模型，再利用动态规划的求解思路得到病床分配的最优解。最后，本文采用2017年卫生统计数据和模拟数据相结合进行数值分析。研究结果表明与传统单阶段模型相比，两阶段模型对不同病种间病床数差别影响显著，并且患者入院率对病床分配影响较大。进一步，基于数值结果给出了医疗管理建议和研究展望。     

Two-stage DEA models with undesirable input-intermediate-outputs

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still lacks of more systematical investigation on two-stage DEA with undesirable variables. For instance, depending on its operating model, even whether an intermediate variable is desirable or undesirable can be questionable for a particular two-stage system. Furthermore, most of the existing studies on two-stage systems focus on the case where only the final outputs are undesirable. In this work, we try to systematically examine two-stage DEA models with undesirable input-intermediate-outputs. Particularly, we utilize the free-disposal axioms to construct the production possibility sets (PPS) and the corresponding DEA models with undesirable variables. The proposed models are then used to illustrate some theoretical perspectives by using the data of China׳s listed banks.