基于直觉模糊层次分析法的90后知识型员工绩效评价与激励策略研究

以90后知识型员工为研究对象,通过构建直觉模糊层次分析模型对90后知识型员工绩效评价进行研究,结果表明:在90后知识型员工绩效评价中存在4个一级指标和20个二级指标,其中一级指标工作业绩的权重最大,依次为工作业绩工作能力工作态度知识水平.在此基础上,提出了相应的激励策略:构建终身职业培训体系,增强创新创业能力;建立心理契约机制,提升组织认同度和忠诚度;健全激励保健因素,促进创新行为发生;完善多元化薪酬体系,实现知识资本化.     

农机服务组织作业效率影响因素的实证分析

以山东省仓山县农机服务组织作业效率影响因素的实地问卷调查结果为依据,构建了农机服务组织作业效率影响因素指标体系,利用统计方法对农机服务组织作业效率的主要影响因素进行了辩识,并对主要影响因素的指标灵敏度进行了测度研究,得出了影响农机服务组织作业效率的主要因素及其指标灵敏度,指出了当前农机服务组织发展中存在的不足和改进思路.     

考虑指标关联的网络DEA效率测度研究

现有网络DEA模型通常在测度指标相互独立的假设前提下进行生产系统效率测度,然而这一假设并不与现实完全相符.针对网络生产系统效率测度指标间存在关联关系的情形,引入模糊测度理论中的Choquet积分,对传统网络DEA模型进行了扩展·首先,分别给出了Choquet积分和网络DEA模型的相关基础知识;然后以串联DEA模型为例,构建了考虑指标间关联的网络DEA模型(C-NDEA模型),进而定义了指标关联情形下网络生产系统有效性的判定标准,并给出了相关定理及其证明;最后通过一个算例验证了所构建C-NDEA模型的合理性和有效性.     

混合DEA模型的区域工业系统运行效率分析与评价

工业系统的运行效率影响着区域经济子系统的增值模式、成长潜力和可持续发展的能力，测度了区域工业系统发展所承载的生态、环境和能源资源成本；本文从投入产出效率评价的视角出发，构建了基于超效率混合DEA模型的评价体系，该模型能够同时处理满足锥性和不满足锥性的评价指标，通过去除决策单元的白限制条件，可以获得决策单元相对效率指数的绝对排序，避免了因评价指标较多而造成的过多决策单元被判定为相对有效，继而致使评价模型失效；评价体系力求突出评价指标的精练性、统计数据的可获性、评价方法的科学性和实践操作性，以黑龙江省1998—2006年度的统计资料为数据分析基础，剖析了评价体系的操作程序和分析方法。     

关于科研事业单位知识型团队绩效评价的实证分析——基于胜任力模型

我国科研事业单位普遍面临绩效考核困境,不能满足知识经济背景下知识型团队的管理要求。胜任力模型可以有效地对知识型团队成员进行选拔、配置与管理,是团队取得高绩效的关键。本研究采用问卷调查结合行为事件访谈的方法,筛选科研事业单位知识型团队的胜任力特征,并采用主成分分析方法,从7个维度构建了知识型团队胜任力模型。在此基础上,采用层次分析法,对团队业绩、胜任力、行为指标进行两两比较,确认其相对重要性,进一步构建了绩效评价体系。结果发现,在科研事业单位知识型团队中,成员个人能力的提升、团队信息共享和效率以及团队管理者的能力是最重要的团队胜任力特征,而外部支持和人际关系相对次要。胜任力指标在绩效评价体系中占有重要的地位。而团队行为对团队绩效的影响也不可忽视。     

一种基于Spearman秩相关系数与熵的多属性决策方法

本以方案间单个指标的关联系数为基础，引入相关度概念，对以关联系数平均值作为测度的评价方法进行了改进，提出了以方案相关度为测度指标的新的决策方法。     

制造云服务组合柔性的四维属性测度方法

云制造环境下服务资源进行动态组合时不可避免地遇到内、外部环境的不确定性,这些不确定性因素直接影响到制造云服务组合的执行成本、效率和质量。为了有效提升制造云服务组合的柔性,需要对其柔性能力进行测度。在假定某待选云服务集中的各服务资源能够以不同的效率替代完成任务的基础上,建立了考虑制造云服务组合柔性的效率柔性、冗余柔性、路径柔性和任务柔性的四维属性测度方法。最后,结合具体算例对该方法的应用过程进行了分析。     

地区工业发展与资源禀赋协同吗?——基于产业、要素、技术资源的视角

在后工业化时代,如何通过区域资源配置优化推动区域工业发展,提高工业产出效率和区域资源配置效率成为了关键问题。在柯布道格拉斯生产函数的基础上,利用相对前沿技术效率测度、产业投入产出分析、构建区域资源对工业生产带动效应的测度模型,探索区域资源对工业发展的拉动作用,识别各地区工业发展的技术效率、区域产业资源配置效率和要素资源配置效率,能够对工业发展战略和模式的设计提供理论指引。结果表明:区域资源禀赋与工业发展显著相关,区域土地、资本要素、政府服务和农业发展对工业发展拉动效果明显,而劳动力要素禀赋、其他产业(如批发业、建筑业等)发展及区域外资源禀赋对工业发展起负向影响;分地区来看,当前业与资源禀赋不协同;工业发展未能较好的利用区域资源,区域资源禀赋也未能实现对工业的拉动作用,应该根据各地区资源禀赋的使用情况,对工业发展的空间布局、工业发展的资源配置模式进行优化,从而实现工业合理发展,保证资源使用高效率和促进经济平稳、快速增长。     

区域资源禀赋、成本约束与农业生产效率测度

农业是我国基础产业,是保障粮食安全和经济发展的根本。根据经济发展战略要求和区域资源禀赋,合理发展区域农业,提升农业对区域资源使用效率和区域资源产业配置效益,形成区域农业高效发展和资源最优配置,是区域经济发展战略的重要内容。在柯布道格拉斯生产函数的基础上,利用随机前沿技术效率测度、产业投入产出分析、偏离-份额分析,构建农业产业生产效率的测度模型,探索地区农业产出的技术效率、资源利用效率和使用效率,为农业生产和区域资源配置提供参考。结果表明,大部分区域农业产出与资源禀赋未形成最佳匹配,应在大力提高农业对区域内资本资源、政府服务资源和劳动力资源使用效率的同时,鼓励过剩的资源在产业间和区域间进行适度转移,从低使用效益产业转移到高使用效益产业,从低产出弹性区域转移到高产出弹性效益区域。     

行政垄断程度与行业效率相关性的SPSS分析

本文选择行政指标及垄断指标对39个工业行业的行政垄断程度进行测度;利用资本、劳动、技术等指标对工业行业效率定量分析;对行业的行政垄断程度与行业的效率之间的相关性探究,并得出结论两者之间呈倒U型关系;最后提出行业行政垄断管制的重点。     

企业创新网络中跨组织知识共享行为的演化博弈研究

新时期企业创新网络中的跨组织知识共享,成为组织间知识资源有效利用的重要方式。通过构建有限理性、知识位势条件下主客体组织的跨组织知识共享演化博弈模型,研究分析了创新网络中主客体组织跨组织知识共享的策略选择。结果表明企业跨组织知识共享中的合作意愿、合作利益分配、合作双方的知识存量及知识结构差异、知识保护力度、社会联系等均是影响双方合作效率的重要因素。其中,最优的利益分配范围、主客体组织的知识存量及知识结构、知识保护力度等对企业创新网络中跨组织知识共享合作的成功起到关键性作用。     

Scaling knowledge: how does knowledge accrue in systems?

This paper addresses the important and somewhat contentious matter of how knowledge accrues in a system. The matter has at its heart the establishment of a scaling function for knowledge (as distinct from the scaling used for information) which is related to the density of the knowledge structure at any point in the system. We commence with a discussion of whether it is possible at all to scale knowledge, dispensing with any concepts of knowledge as a simple finite resource and making a distinction between the establishment of a metric and the act of measurement itself. First, we draw on the Shannon–Weaver (H) measure to establish how knowledge can be seen as contributing to the partitioning of message sets under the H-measure. This establishes how knowledge contributes to the quantity of information held within a system when viewed as a meta-structure for that information. Second, we build on the idea of knowledge as an endemic property of a structure of interconnections between concepts. We observe that knowledge content can be dense both in structures that are highly interconnected deploying a modest number of concepts and in those where the interconnections are more sparse but where the number of concepts deployed is high. A scaling function exhibiting appropriate properties is then proposed. It can be seen that the scaling associated with knowledge as meta-information and the scaling deriving from the interconnectivity point of view are connected. This scaling function is particularly useful in three ways. Firstly, it outlines the properties of knowledge itself which can be used as criteria for future knowledge-based research. Its application in practice creates the ability to identify areas of knowledge concentration within a system. Finally, this identification of knowledge ‘hotspots’ can be used to direct the investment of resources for the management of knowledge and it provides an indication of the appropriate approach for the management of this knowledge. We make some observations on the limitations of the approach, on its potential as a basis for managerial action (particularly in Knowledge Management) and on its relevance and applicability to OR practice (particularly in respect of systems approaches to knowledge mapping). Lastly, we offer a view on the likely line of research which may result from this work.     

Knowledge management strategy and organizational culture

In an emerging knowledge-based economy, knowledge is a critical source of competitive advantage of organizations. This paper addresses two different strategies based on the tacitness of knowledge, indicating how the dilemmas of the choice of knowledge strategies might be resolved. A successful symbiosis strategy based upon a conducive organizational culture can ease knowledge replication within the organization but presents difficulty in imitation by competitors. Such a culture needs to be pervasive within the organization, but at the same time idiosyncratic and unique to the organization. Optimal knowledge management strategies can cultivate the organizational cultural fit, and maximize the organizational profit. The paper provides researchers and practitioners valuable insights to understand the fundamental relationship between knowledge management and organizational culture, and practical guidance to adopt an appropriate knowledge management strategy to exploit organizational knowledge.     

Validation of Computational Models Based on Multiple Heterogeneous Knowledge Sources

Theories of organizations have brought together multipleheterogeneous theories in computational models. In addition, inartificial intelligence, there has been an emphasis on the generationof knowledge-based systems that include multiple heterogeneousknowledge bases. As a result, increasingly, theory and modeldevelopers have called for the need to validate these computationalmodels. Unfortunately, there has been only limited attention givento validation of multiple knowledge source programs. The primary focus of this paper is on the identification of conflict between multiple knowledge bases. The existence of conflict is particularly critical in those situations where database evaluations are "averaged". For example, what would it mean to average the assessments of supply and demand economists, or surgeons and chemotherapists? Correlational statistics are used to identify conflict situations. In addition, a new approach, referred to as cutpoints, is developed to determine if probability distributions of multiple agents are in conflict. A case study is used to illustrate the problems of combining expertise in multiple agent systems and to demonstrate the approach.     

A regularized pairwise multi-classification knowledge-based machine and applications

This paper presents a novel knowledge-based linear classification model for multi-category discrimination of sets or objects with prior knowledge. The prior knowledge is in the form of multiple polyhedral sets belonging to one or more categories or classes and it is introduced as additional constraints into the formulation of the Tikhonov linear least squares multi-class support vector machine model. The resulting formulation leads to a least squares problem that can be solved using matrix methods or iterative methods. Investigations include the development of a linear knowledge-based classification model extended to the case of multi-categorical discrimination and expressed as a single unconstrained optimization problem. Advantages of this formulation include explicit expressions for the classification weights of the classifier(s) and its ability to incorporate and handle prior knowledge directly to the classifiers. In addition it can provide fast solutions to the optimal classification weights for multi-categorical separation without the use of specialized solver-software. To evaluate the model, data and prior knowledge from the Wisconsin breast cancer prognosis and two-phase flow regimes in pipes were used to train and test the proposed formulation.     

Resource allocation based on the DEA model

The purpose of this paper is to develop an approach to a resource-allocation problem that typically appears in organizations with a centralized decision-making environment, for example, police stations, banks, and universities. The central unit is assumed to be interested in maximizing both the total efficiency and the efficiency of the individual unit by allocating available resources to them. Building upon this, we present a data envelopment analysis-based model for allocating input resources to DMUs (the decision-making units) under the framework of multiple objective programming. Numerical examples are used to illustrate the approach.     

An analysis of interorganizational resource sharing decisions in collaborative knowledge creation

Collaborative relationships between organizations for knowledge creation have received considerable attention in recent literature. For any collaborative endeavor to succeed, adequate allocation and sharing of resources is important. We explored the conditions of resource sharing in which organizations are motivated to collaborate for knowledge creation, as well as the conditions required for the collaboration to continue. Using the game theoretic framework, we modeled the collaboration for knowledge creation as a Stackelberg leader–follower game. Specifically, we modeled two scenarios, the first in which organizations expend current efforts only, and the second in which organizations have made relevant prior efforts. The equilibrium values of current efforts in knowledge creation, the leader organization’s resource participation rate, and the total expected system gain in both of these scenarios were determined. Both within scenario and cross-scenario analyses were conducted. It is important to maintain an optimal ratio between the leader’s and follower’s marginal gains for the formation and continuation of the collaboration.     

Using dialog-controlled rule systems in a maintenance module for knowledge bases

Dialog-controlled rule systems were introduced as a tool to describe the way in which theWimdas system for knowledge-based analysis of marketing data manages its dialog with the user. In this paper we shall discuss how dialog-controlled rule systems can be used to specify a formal language aiding a knowledge engineer in maintaining a system's knowledge base. Although this language is finite, it must be defined generically, being too extensive to be enumerated. In contrast to the well-known traditional methods for defining formal languages — using finite automata, regular expressions or grammars — our method can be applied by a user who need not be an expert in theoretical computer science.Research for this paper was supported by the Deutsche Forschungsgemeinschaft.     

Knowledge Representation, Reasoning and Integration Using Temporal Logic with Clocks

Representation, reasoning about and integrating knowledge based on multiple time granularities in knowledge-based systems is important, especially when talking about events that take place in the real world. Formal approaches based on temporal logics have been successfully applied in many application domains of knowledge-based systems where the evolution of a system and its environment through time is central. This paper presents a methodology based on temporal logic to deal with knowledge based on multiple time granularities in knowledge-based systems. The temporal logic we consider is especially suitable for modelling events with different rates and/or scales of progress. The methodology includes an approach to the representation of timing systems, a method used for representing facts and rules in a knowledge-based system that involve multiple time granularities using temporal logic, and several deductive reasoning techniques. The work presented in this article has been supported in part by The Australian Research Council and Macquarie University. Note that this paper is an extended and revised version of Orgun, Liu and Nayak [37].