职工薪酬分配比例、产权性质与企业价值

随着现代企业的发展，职工在企业中扮演的角色越来越重要，职工激励问题对企业的重要性也不言而喻。已有研究主要集中于薪酬和期权等绝对激励，关于职工激励对企业的影响程度的研究则较少。 利用2003年至2013年中国上市公司数据，基于公平理论构建职工薪酬分配比例与企业价值关系的OLS模型，对职工薪酬分配比例对企业价值的影响进行实证检验。 研究结果表明，全样本中职工薪酬分配比例越高，企业价值越低；区分产权性质后，国有企业薪酬分配比例明显高于民营企业，继续提高国有企业薪酬分配比例会降低国有企业价值，民营企业薪酬分配比例仍有提升空间；行业收入较高会弱化提高薪酬分配比例带来的激励作用；劳动密集度会提高薪酬分配比例带来的激励作用；薪酬分配比例显著影响企业价值，产权性质、行业收入差距和劳动密集度影响薪酬分配比例与企业价值的关系。研究结论在用工具变量和外生事件考虑二者的内生性问题后仍然成立。 研究结果丰富了企业价值的影响因素和薪酬契约激励经济后果方面的研究，也为职工薪酬分配比例对企业价值的影响提供了新的经验证据，同时对上市公司制定合理的薪酬激励政策和中国当前提高劳动分配比例的政策具有重要的借鉴意义。建议监管者在制定薪酬管制政策时应根据公司的实际情况(如产权性质和非货币性福利等)对不同的公司进行监管，以促进企业发展。     

A hybrid algorithm based on variable neighbourhood for the strip packing problem

This paper addresses the strip packing problem, which has a wide range of real-world applications. Our proposed algorithm is a hybrid metaheuristic that combines an improved heuristic algorithm with a variable neighbourhood search. Different neighbourhoods are constructed based on the concept of block patterns. The proposed algorithm has three interesting features. First, a least-waste strategy is used to improve the constructive heuristics. Second, a better sorting sequence is selected to generate an initial solution. Finally, different neighbourhoods are constructed based on block patterns. The computational results from a diverse set of problem instances show that the proposed algorithm performs better than algorithms reported in the literature for most of the problem sets compared.     

Exact and heuristic methods for a class of selective newsvendor problems with normally distributed demands

In this paper we study a class of selective newsvendor problems, where a decision maker has a set of raw materials each of which can be customized shortly before satisfying demand. The goal is then to select which subset of customizations maximizes expected profit. We show that certain multi-period and multi-product selective newsvendor problems fall within our problem class. Under the assumption that the demands are independent and normally, but not necessarily identically, distributed we show that some problem instances from our class can be solved efficiently using an attractive sorting property that was also established in the literature for some related problems. For our general model we use the KKT conditions to develop an exact algorithm that is efficient in the number of raw materials. In addition, we develop a class of heuristic algorithms. In a numerical study, we compare the performance of the algorithms, and the heuristics are shown to have excellent performance and running times as compared to available commercial solvers.     

Heuristics for scheduling in a flowshop with setup,processing and removal times separated

The problem of scheduling in a flowshop, where setup, processing and removal times are separable, is considered with the objective of minimizing makespan. Heuristic algorithms are developed by the introduction of simplifying assumptions into the scheduling problem under study. An improvement method is incorporated in the heuristics to enhance the quality of their solutions. The proposed heuristics and an existing heuristic are evaluated by a large number of randomly generated problems. The results of an extensive computational investigation for various values of parameters are presented.     

Parallel machine scheduling subject to auxiliary resource constraints

This paper is motivated by scheduling photolithography machines in semiconductor manufacturing wherein reticle requirements are the auxiliary resource constraints. As the problem is NP hard, two different heuristic solution approaches are developed. The performance of our network-based mathematical model and heuristics are evaluated through an extensive set of problem instances. The best performing heuristic method typically produces solutions that are 1.72% above optimal. If this method is used as the seed solution for a Tabu search-based post processing algorithm, schedules that are 0.78% above the optimal solution, on average, are possible.     

A cyclical view of the relationship between corporate governance and strategic management

The vast majority of research on the relationship between corporate governance and strategic management focuses on the impact of corporate governance on strategic management. In this article we propose a cyclical model, highlighting that strategic decisions can also affect corporate governance through shaping firm ownership structure. We discuss the impacts of strategic decisions on firm ownership structure and corporate governance in the contexts of publicly traded firms, private firms, and the privatization of state-owned enterprises. We hope that our cyclical model can promote researchers to develop a more complete view about the relationships between strategic management, ownership structure, and corporate governance.     

Effective heuristics for the blocking flowshop scheduling problem with makespan minimization

The blocking flowshop scheduling problem with makespan criterion has important applications in a variety of industrial systems. Heuristics that explore specific characteristics of the problem are essential for many practical systems to find good solutions with limited computational effort. This paper first presents two simple constructive heuristics, namely weighted profile fitting (wPF) and PW, based on the profile fitting (PF) approach of McCormick et al. [Sequencing in an assembly line with blocking to minimize cycle time. Operations Research 1989;37:925-36] and the characteristics of the problem. Then, three improved constructive heuristics, called PF-NEH, wPF-NEH, and PW-NEH, are proposed by combining the PF, wPF, and PW with the enumeration procedure of the Nawaz-Enscore-Ham (NEH) heuristic [A heuristic algorithm for the m-machine, n-job flow shop sequencing problem. OMEGA-International Journal of Management Science 1983;11:91-5] in an effective way. Thirdly, three composite heuristics i.e., PF-NEH_LS, wPF-NEH_LS, and PW-NEH_LS, are developed by using the insertion-based local search method to improve the solutions generated by the constructive heuristics. Computational simulations and comparisons are carried out based on the well-known flowshop benchmarks of Taillard [Benchmarks for basic scheduling problems. European Journal of Operation Research 1993;64:278-85] that are considered as blocking flowshop instances. The results show that the presented constructive heuristics perform significantly better than the existing ones, and the proposed composite heuristics further improve the presented constructive heuristics by a considerable margin. In addition, 17 new best-known solutions for Taillard benchmarks with large scale are found by the presented heuristics.     

A Comparative Revenue Analysis of Hotel Yield Management Heuristics

Yield management is the dynamic pricing, overbooking, and allocation of perishable assets across market segments in an effort to maximize short-term revenues for the firm. Numerous optimization heuristics for allocation and overbooking exist for the airline industry, whose perishable asset is the airplane seat. When an airplane departs, no revenue is gained from the empty seat(s). In the hotel industry, the perishable asset is the hotel room-once a room is left empty for a night, that night's revenue cannot be recaptured. The literature on yield management heuristics for the hotel industry is sparse. For the hotel operating environment, no research has adequately (1) integrated overbooking with allocation, (2) modeled the phenomenon of hotel patrons extending or contracting their stay at a moment's notice, or (3) performed a realistic performance comparison of alternative heuristics. This research develops (1) two hotel-specific algorithms that both integrate overbooking with the allocation decisions, (2) a simulation model to reproduce realistic hotel operating environments, and (3) compares the performance of five heuristics under 36 realistic hotel operating environments. Seven conclusions are reached with regard to which heuristic(s) perform best in specific operating environments. Generally, heuristic selection is very much dependent on the hotel operating environment. A counterintuitive result is that in many operating environments, the simpler heuristics work as well as the more complex ones.     

政府补贴、所有权性质与企业研发决策

本文将企业研发行为分为"是否研发"和"投入多少"两个阶段,就政府补贴对不同所有制企业研发决策的影响进行研究.理论方面,构建企业研发决策的两阶段模型,讨论了补贴对企业研发投资的作用机制.实证方面,以中国工业企业为对象,选择Heckman两步法和2SLS分别处理了样本选择性偏误及变量间的内生性问题,对来自国有、私营和外资企业的分类样本进行了检验,结果表明:在不同的所有权性质下,政府补贴对企业研发投资的作用存在一定差别,国有企业面对优惠政策的倾斜和需要担负的社会责任,从事技术创新活动的概率较高,但由于特殊的产权关系和预算软约束等原因,缺乏扩大研发投入的动力;对于治理机制完善的外资企业和处于市场竞争弱势地位的私营企业而言,政府补贴的研发激励效果更为明显.     

政治关联与财务困境公司的政府补助——来自中国ST公司的经验证据

本文以2002-2007年沪深两市的ST公司为样本,实证研究了企业的政治关联对财务困境公司获取政府补助的影响.结果显示:(1)民营企业的政治关联对企业处于财务困境时获取政府补助有显著影响,但对国有企业作用不显著.(2)考虑企业所处的地区环境差异之后,本文发现民营企业的政治关联优势受到地区财政富余程度的显著影响,而地方政府干预要起作用也受到地区财政状况的制约.只有在地方财政有充足财力的情况下,民营企业才可能利用政治关联获得更多的政府补助.(3)从政府补助的效果来看,政府补助虽然可以在救助当年明显改善公司业绩,但对公司长期业绩的提升作用却因企业政治关联程度和企业性质的不同而存在差异:政治关联较弱的民营企业获得的政府补助对公司长期业绩的提高作用显著,但对于国有企业以及具有较强政治关联的民营企业作用则不显著,这在一定程度上说明政治关联导致了政府补助资金的低效运作.     

政府控制与企业高管人员薪酬绩效敏感度

根据我国新的国有资产管理体制特征,着眼于我国政府对国有企业实行分级管理的背景,将国有上市公司分为中央政府控股的上市公司和地方政府控股的上市公司2类。由于政府对这2类公司监管程度的差异、企业面对的市场风险的不同,以及这2类公司高管人员对薪酬的关注程度存在差异,说明薪酬在这2类国有上市公司中的重要性并不一致。研究结果表明,国有上市公司高管人员薪酬的业绩敏感性与政府控制人的行政级别相关,中央政府控制企业的高管人员的薪酬业绩敏感性更低。     

混合寡头竞争条件下的购买势力研究

基于一个具有购买势力的连锁企业在若干个相互分割的市场上分别与一个没有购买势力的地方企业进行Cournot竞争的经济学模型,我们分别讨论了连锁企业是私营企业和部分国有企业时,购买势力对企业利润、消费者剩余以及社会福利的影响。研究表明:当连锁企业是私营企业时,随着其购买势力的增强,其企业利润不断增加,消费者剩余及社会福利不断降低,而上游企业与地方企业的利润变动则取决于地方企业国有股的比重和连锁企业购买势力的大小;当连锁企业是部分国有企业时,随着连锁企业购买势力的增大,连锁企业的利润、消费者剩余以及社会福利会持续升高,而上游企业与地方企业的利润持续降低。     

Approaches to real world two-dimensional cutting problems

We consider a real world generalization of the 2-Dimensional Guillotine Cutting Stock Problem arising in the wooden board cutting industry. A set of rectangular items has to be cut from rectangular stock boards, available in multiple formats. In addition to the classical objective of trim loss minimization, the problem also asks for the maximization of the cutting equipment productivity, which can be obtained by cutting identical boards in parallel. We present several heuristic algorithms for the problem, explicitly considering the optimization of both objectives. The proposed methods, including fast heuristic algorithms, Integer Linear Programming models and a truncated Branch and Price algorithm, have increasing complexity and require increasing computational effort. Extensive computational experiments on a set of realistic instances from the industry show that high productivity of the cutting equipment can be obtained with a minimal increase in the total area of used boards. The experiments also show that the proposed algorithms perform extremely well when compared with four commercial software tools available for the solution of the problem.     

Assortment optimisation problem: A distribution-free approach

Assortment optimisation is a critical decision that is regularly made by retailers. The decision involves a trade-off between offering a larger assortment of products but smaller inventories of each product and offering a smaller number of varieties with more inventory of each product. We propose a robust, distribution-free formulation of the assortment optimisation problem such that the assortment and inventory levels can be jointly optimised without making specific assumptions on the demand distributions of each product. We take a max-min approach to the problem that provides a guaranteed lower bound to the expected profit when only the mean and variance of the demand distribution are known. We propose and test three heuristic algorithms that provide solutions in O(nlog (n)) time and identify two cases where one of the heuristics is guaranteed to return optimal policies. Through numerical studies, we demonstrate that one of the heuristics performs extremely well, with an average optimality gap of 0.07% when simulated under varying conditions. We perform a sensitivity analysis of product and store demand attributes on the performance of the heuristic. Finally, we extend the problem by including maximum cardinality constraints on the assortment size and perform numerical studies to test the performance of the heuristics.     

基于差异产品的外资渗透、私有化程度与社会福利研究

考虑到企业产品差异性、企业的私有化程度、外国资金的渗透等因素,研究了伯川德竞争情形下私有化程度、外资渗透与社会福利之间的关系以及私有化程度、外资渗透对混合双寡头市场的影响。首先建立混合双寡头的伯川德竞争模型,得出伯川德均衡解,然后在社会福利最大化下分产品为替代产品和互补产品两种情形分别得出了最优私有化程度的解,进而分析了外资渗透（或国内控股）对私有化程度与混合双寡头市场的影响。研究表明,生产替代性产品的企业进行价格竞争时,部分私有化企业为纯公共企业时社会福利达到最大,企业国内控股比例的增加将增大最优社会福利;生产互补性产品的企业在价格竞争下,实行国有企业公司制股份制改革时社会福利达到最大,并且国内控股比例的增加将降低最佳私有化程度,社会福利最大化下政府要鼓励产品多样化和减少国外资金的渗透。从整个社会和企业角度看,国有企业股份制改革策略为最佳策略。     

A Multi-Exchange Neighborhood for Minimum Makespan Parallel Machine Scheduling Problems

We propose new local search algorithms for minimum makespan parallel machine scheduling problems, which perform multiple exchanges of jobs among machines. Inspired by the work of Thompson and Orlin (1989) on cyclic transfer neighborhood structures, we model multiple exchanges of jobs as special disjoint cycles and paths in a suitably defined improvement graph, by extending definitions and properties introduced in the context of vehicle routing problems (Thompson and Psaraftis, 1993) and of the capacitated minimum spanning tree problem (Ahuja et al., 2001). Several algorithms for searching the neighborhood are suggested.We report the results of a wide computational experimentation, on different families of benchmark instances, performed for the case of identical machines. This problem has been selected as a case study to perform a comparison among the alternative algorithms, and to discover families of instances for which the proposed neighborhood may be promising in practice. Based on the results of the experiments, we can suggest which among the many possible variants of the proposed approaches may be more promising for developing local search algorithms based on multi-exchange moves for related problems. Also, on some families of instances, which are very hard to solve exactly, the most promising multi-exchange algorithms were observed to dominate, in solution quality and in computational time, competitive benchmark heuristics.     

On cutting stock with due dates

Classical stock cutting calls for fulfilling a given demand of parts, minimizing raw material needs. With the production of each part type regarded as a job due within a specific date, a problem arises of scheduling cutting operations. We here propose an exact integer linear programming formulation, and develop primal heuristics, upper bounds and an implicit enumeration scheme. A computational experience carried out for the one-dimensional problem shows that our primal heuristics outperform known ones, and that the formulation has good features for finding exact solutions of non-trivial instances.     

TECHNOLOGICAL PROGRESS AND TECHNOLOGY ACQUISITION: STRATEGIC DECISION UNDER UNCERTAINTY

We develop a stochastic programming model to aid manufacturing firms in making strategic decisions in technology acquisition. The proposed model maximizes the firm's expected profit under the condition of the uncertainty in technological progress and development. To solve this large‐scale problem, we decompose future uncertainties through scenarios and then develop an algorithm to solve the resulting non‐linear subproblems efficiently. Finally, we develop a heuristic to eliminate the infeasibility in the master problem and obtain best solutions. Numerical results show that our heuristic solutions are very close to the optimal solutions and meaningful insights are derived.     

公交系统随机平衡网络设计模型及求解算法

本文根据公交网络的具体特点,对公交网络进行了系统的描述,提出一个双层规划模型来描述随机平衡公交网络设计问题。在双层规划模型中,上层模型为一个标准的公交网络设计模型,下层模型是一个公交网络随机平衡配流模型。针对所提出的模型,设计了基于灵敏度分析的求解算法。最后,给出一个简单算例加以证明。     

On linear bilevel problems with multiple objectives at the lower level

Bilevel programming problems provide a framework to deal with decision processes involving two decision makers with a hierarchical structure. They are characterized by the existence of two optimization problems in which the constraint region of the upper level problem is implicitly determined by the lower level optimization problem. This paper focuses on bilevel problems for which the lower level problem is a linear multiobjective program and constraints at both levels define polyhedra. This bilevel problem is reformulated as an optimization problem over a nonconvex region given by a union of faces of the polyhedron defined by all constraints. This reformulation is obtained when dealing with efficient solutions as well as weakly efficient solutions for the lower level problem. Assuming that the upper level objective function is quasiconcave, then an extreme point exists which solves the problem. An exact and a metaheuristic algorithm are developed and their performance is analyzed and compared.