泛强化激励动态评价模型及应用

doi:10.16381/j.cnki.issn1003-207x.2020.1888

摘要/Abstract

摘要： 针对动态激励评价理论性、系统性与规范性不足，且机动性与可扩展性较差等问题，引入强化理论、公平理论与权变理论，构建一种泛强化激励动态评价的方法论模型。首先，以强化理论等过程型激励理论作为内在理论支撑，并以数据分析方法作为外在方法支持，提出模型的主体功能模块“泛强化激励算子”；其次，对算子中的各参数进行具体阐释，并探讨了相关性质；最后，给出模型的具象化表示方式、应用流程及注意事项。通过参数普适性检验及算例对比分析表明，该模型是一个可行的方法论体系，且具有一定的普适性；同时，有利于决策者更为广泛且深入地挖掘特定问题背景下被评价对象的特定动态特征与发展潜力，拉开被评价对象之间的档次并实现更为全面的分类优选。

关键词: 动态激励评价；强化理论；方法论；数据分析；权变

Abstract: In order to solve the problems in dynamic incentive evaluation, such as the lack of systematization, theory basis, normalization, maneuverability and scalability, a methodological model of dynamic incentive evaluation is constructed by introducing reinforcement theory, equity theory and contingency theory. Firstly, using process incentive theories mainly of reinforcement theory as the internal basis, and the data analysis method as the external support, the principal functional module “Generic Reinforcement Incentives” operator is proposed; secondly, each parameter of the operator is explained in detail, and the related properties are discussed; finally, the representational expression, application route and attentions are illustrated respectively. Through the parameters’ universality test and comparative analysis of numerical example, it shows that a feasible methodology system is provided by this model with significant universal ability, so as to help decision-maker to explore the specific dynamic characteristics and development potential of the evaluated object in specific background broadly and thoroughly, effectively widen the grades between the evaluated objects and bring about a more comprehensive classified selection.

Key words: dynamic incentive evaluation; reinforcement theory; methodology; data analysis; contingency

中图分类号:

C934

牛玉飞, 张发明, 袁胜军. 泛强化激励动态评价模型及应用[J]. 中国管理科学, 2023, 31(6): 241-252.

NIU Yu-fei, ZHANG Fa-ming, YUAN Sheng-jun. Dynamic Evaluation with Generic Reinforcement Incentives and Its Application[J]. Chinese Journal of Management Science, 2023, 31(6): 241-252.

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