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.

参考文献

［1］ Vrsmarty G, Dobos I. A literature review of sustainable supplier evaluation with Data Envelopment Analysis［J］. Journal of Cleaner Production, 2020, 264:1-10.
［2］ Li Xingmei, Wang Yaxian, Yan Qingyou, et al. Uncertain mean-variance model for dynamic project portfolio selection problem with divisibility［J］. Fuzzy Optimization and Decision Making, 2019, 18(1):37-56.
［3］ Badunenko O, Kumbhakar S C. When, where and how to estimate persistent and transient efficiency in stochastic frontier panel data models［J］. European Journal of Operational Research, 2016, 255(1):272-287.
［4］ Sueyoshi T, Goto M, Sugiyama M. DEA window analysis for environmental assessment in a dynamic time shift: performance assessment of U.S. coal-fired power plants［J］. Energy Economics, 2013, 40: 845-857.
［5］ Leitman S, Pine W E, Kiker G. Management options during the 2011-2012 drought on the apalachicola river: a systems dynamic model evaluation［J］. Environmental Management, 2016, 58(2): 193-207.
［6］ Daniele D L, Marco P, Giorgio C. Technical problems with dynamic compliance evaluation in neonates and infants［J］. Intensive Care Med, 2012, 38(6): 1082-1083.
［7］ Hao Zhinan, Xu Zeshui, Zhao Hua, et al. A dynamic weight determination approach based on the intuitionistic fuzzy bayesian network and its application to emergency decision making［J］. IEEE Transactions on Fuzzy Systems, 2018, 26(4): 1893-1907.
［8］郭亚军. 带有鼓励(或惩罚)机制的多指标决策方法［J］. 决策与决策支持系统, 1995(4): 109-114.Guo Yajun. A multiple attribute decision making method with encour-agement (or penalty) mechanism［J］. Journal of Decision Making and Decision Support Systems, 1995(4): 109-114.
［9］王欣荣, 樊治平. 上市公司财务状况的动态多指标综合评价方法［J］. 系统工程理论与实践, 2002(4): 54-57+140.Wang Xinrong, Fan Zhiping. Dynamic multiple index synthetical evaluation for financial condition of public corporations［J］. Systems Engineering-Theory & Practice, 2002(4): 54-57+140.
［10］ Zhang Faming, Tadikamalla P R, Shang J. Corporate credit-risk evaluation system: integrating explicit and implicit financial performances［J］. International Journal of Production Economics, 2016, 177: 77-100.
［11］李美娟, 魏寅坤, 徐林明. 基于灰靶理论的区域协同创新能力动态评价与分析［J］. 科学学与科学技术管理, 2017, 38(8): 122-132.Li Meijuan, Wei Yinkun, Xu Linming. Dynamic evaluation and analysis on regional collaborative innovation capabilities based on grey target［J］. Science of Science and Management of S.& T., 2017, 38(8): 122-132.
［12］樊治平, 王欣荣. 时序多指标决策的一种新方法［J］. 预测, 2000(4): 49-50+45.Fan Zhiping, Wang Xinrong. A new method for multiple attribute decision of making problem with time series［J］. Forecasting, 2000(4): 49-50+45.
［13］边旭, 田厚平, 郭亚军. 具有激励特征的供应商动态评价方法［J］. 南开管理评论, 2004(5): 87-90.Bian Xu, Tian Houping, Guo Yajun. The supplier dynamic evaluation method with the character of stimulation［J］. Nankai Business Review, 2004(05):87-90.
［14］李佳瑾, 郭鹏. 运用时序多指标决策的专家库动态优化［J］. 工业工程, 2011, 14(2): 57-60+69.Li Jiajin, Guo Peng. Dynamic optimization of expert-base based on time series muti-attribute decision making［J］. Industrial Engineering Journal, 2011, 14(2): 57-60+69.
［15］李美娟, 陈国宏, 庄花. 具有激励或惩罚特征的区域自主创新能力动态评价与分析［J］. 技术经济, 2009, 28(10): 11-16.Li Meijuan, Chen Guohong, Zhuang Hua. Dynamic evaluation and analysis on regional independent innovation capacity with characteristics of incentive or punishment［J］. Technology Economics, 2009, 28(10): 11-16.
［16］吴飞美,李美娟,徐林明,等.基于理想解和灰关联度的动态评价方法及其应用研究［J］.中国管理科学, 2019, 27(12): 136-142.Wu Feimei, Li Meijuan, Xu Linming, et al. Dynamic evaluation method based on TOPSIS and gray correlation degree and its application［J］. Chinese Journal of Management Science, 2019, 27(12): 136-142.
［17］李美娟,袁宁,徐林明.基于正交投影法的动态评价方法［J］.中国管理科学,2020,28(12):208-219.Li Meijuan, Yuan Ning, Xu Linming. Dynamic evaluation method based on vertical projection method［J］. Chinese Journal of Management Science, 2020, 28(12): 208-219.
［18］易平涛, 郭亚军, 张丹宁. 基于双激励控制线的多阶段信息集结方法［J］. 预测, 2007(3): 39-43.Yi Pingtao, Guo Yajun, Zhang Danning. A multi-phase information aggregation method based on double inspiriting control lines［J］. Forecasting, 2007(3): 39-43.
［19］刘微微. 基于双激励控制线的变化速度动态综合评价［C］//第十二届中国管理科学学术年会, 北京, 《中国管理科学》编辑部, 2010: 29-34.Liu Weiwei. Study on dynamic comprehensive evaluation for change speed based on double inspiriting control lines［C］//The 12th Annual Conference of China Management Science, Beijing, Editorial Department of “Chinese Journal of Management Science”, 2010: 29-34.
［20］张发明. 基于双重激励模型的动态综合评价方法及应用［J］. 系统工程学报, 2013, 28(2): 248-255.Zhang Faming. Dynamic comprehensive evaluation method based on double incentives model and its application［J］. Journal of Systems Engineering, 2013, 28(2): 248-255.
［21］郭亚军, 周莹, 易平涛, 等. 基于全局信息的动态激励评价方法及激励策略［J］. 系统工程学报, 2017, 32(2): 282-288.Guo Yajun, Zhou Ying, Yi Pingtao, et al. Dynamic incentive evaluation based on overall information and incentive strategy［J］. Journal of Systems Engineering, 2017, 32(2): 282-288.
［22］李玲玉, 郭亚军, 易平涛, 等. 基于改进分层激励控制线的多阶段信息集结方法［J］. 东北大学学报(自然科学版), 2018, 39(1): 148-152.Li Lingyu, Guo Yajun, Yi Pingtao, et al. On multi-phase information aggregation methods based on improved stratified incentive control lines［J］. Journal of Northeastern University (Natural Science), 2018, 39(1): 148-152.
［23］ Skinner B F. Contingencies of reinforcement: a theoretical analysis［M］.New York: Appleton-Century-Crofts，1969.
［24］ Jack M. Positive and negative reinforcement, A distinction that is no longer necessary; or a better way to talk about bad things［J］. Behaviorism, 1975, 3(1): 33-44.
［25］ Alan B, Mark G. Positive and negative reinforcement: should the distinction be preserved?［J］. The Behavior analyst, 2005, 28(2): 85-98.
［26］ Marr M J. Through the looking glass: symmetry in behavioral principles［J］. The Behavior Analyst, 2006, 29(1): 125-128.
［27］ Adams J S. Inequity in social exchange［J］. Advances in Experimental Social Psychology, 1965, 2: 267-299.
［28］李海丹, 洪紫怡, 朱侯. 隐私计算与公平理论视角下用户隐私披露行为机制研究［J］. 图书情报知识, 2016(6): 114-124.Li Haidan, Hong Ziyi, Zhu Hou. Influencing factors of User’s privacy disclosure from privacy calculus and jusitic perspectives［J］. Documentation,Information & Knowledge, 2016(6): 114-124.
［29］张肃. 中国城镇居民信息消费水平动态组合评价研究［J］. 数理统计与管理, 2018, 37(3):381-389.Zhang Su. Study on information consumption level dynamic comprehensive evaluation of urban residents in China［J］. Journal of Applied Statistics and Management, 2018, 37(3):381-389.
［30］ Yao Yiyu. Three-way decision and granular computing［J］. International Journal of Approximate Reasoning, 2018, 103: 107-123.
［31］陈洪转, 羊震, 金振鑫. 我国高技术产业科技活动的激励控制动态综合评价［J］. 产业经济研究, 2011(4): 89-94.Chen Hongzhuan, Yang Zhen, Jin Zhenxin. Dynamic comprehensive evaluation on technology activities of high-tech institutions with dual-excitation and control lines［J］. Industrial Economics Research, 2011(4): 89-94.
［32］李美娟. 基于理想解的区域自主创新效率动态评价研究［J］. 科学学与科学技术管理, 2014, 35(2): 114-123.Li Meijuan. Dynamic evaluation on regional independent innovation efficiency based on TOPSIS［J］. Science of Science and Management of S.& T., 2014, 35(2): 114-123.
［33］张发明, 孙文龙. 改进的动态激励综合评价方法及应用［J］. 系统工程学报, 2015, 30(5): 711-718.Zhang Faming, Sun Wenlong. Improved dynamic incentive comprehensive evaluation method and its application［J］. Journal of Systems Engineering, 2015, 30(5): 711-718.
［34］易平涛, 由海燕, 郭亚军, 等. 基于时序增益激励的多阶段评价信息集结方法［J］. 系统工程, 2015, 33(12): 126-131.Yi Pingtao, You Haiyan, Guo Yajun, et al. Multi-phase evaluation method of information aggregation based on phases gain inspiriting［J］. Systems Engineering, 2015, 33(12): 126-131.
［35］杨欢红, 丁宇涛, 周敬嵩, 等. 基于最优权重和区间灰数动态灰靶的变压器状态评估［J］. 电力系统保护与控制, 2019, 47(7): 66-74.Yang Huanhong, Ding Yutao, Zhou Jingsong, et al. A condition assessment method of transformers based on optimal weight and dynamic grey target with interval grey number［J］. Power System Protection and Control, 2019, 47(7): 66-74.

[1]	李伟伟,易平涛,王露. 基于行为特征分析的情境化评价方法及应用[J]. 中国管理科学, 2024, 32(10): 171-180.
[2]	陈雪龙,张钟,李悦. 临机决策视角下的非常规突发事件应急处置方案生成[J]. 中国管理科学, 2024, 32(10): 109-122.
[3]	胡婉婷,丁晶晶,梁樑. 基于期权代储协议的应急物资政企联合储备模型研究[J]. 中国管理科学, 2024, 32(9): 101-112.
[4]	邹清明,刘春,曹裕. 碳交易机制下考虑公平关切产出不确定的低碳供应链减排与融资策略研究[J]. 中国管理科学, 2024, 32(9): 248-259.
[5]	陈强,荣俊美,常旭华,宫磊. 考虑奖惩差异的高校科研考评及专利审查策略研究[J]. 中国管理科学, 2024, 32(9): 313-322.
[6]	聂如欣,田章朋,梁鹤鸣. 社会网络环境下基于行为管理的大群体共识决策方法[J]. 中国管理科学, 2024, 32(9): 35-47.
[7]	陈璐,徐海燕,张瑾木子,何亮. 基于图模型理论的模糊权力不对称冲突研究[J]. 中国管理科学, 2024, 32(9): 59-69.
[8]	沈种,李星梅. 多种协同关系共同作用下的项目组合决策问题研究[J]. 中国管理科学, 2024, 32(8): 139-148.
[9]	李晓娜,马卫民. 需求不确定下高耗水企业节水服务外包决策研究[J]. 中国管理科学, 2024, 32(8): 230-240.
[10]	孙向彦,曲薪池. 药占比管制下过度医疗行为多阶段动态演化研究[J]. 中国管理科学, 2024, 32(8): 308-321.
[11]	李想,李亚男,马红光. 考虑乘客效用的多元化共享出行平台协同定价策略研究[J]. 中国管理科学, 2024, 32(7): 172-180.
[12]	杜恒,卢珂. 供给短缺下考虑消费异质性的零售商定价策略[J]. 中国管理科学, 2024, 32(7): 201-211.
[13]	蒋兰娟,陈武华,陈晓红. 考虑医保报销与交付时间的医药零售商定价及渠道模式选择研究[J]. 中国管理科学, 2024, 32(7): 236-247.
[14]	杨荣庆,唐孝安,张强,黄挺. 分布式乘性偏好环境下考虑决策者偏好调整意愿的最优-最劣多准则决策方法[J]. 中国管理科学, 2024, 32(7): 65-75.
[15]	张磊,叶鑫. 考虑风险态度和自信行为的应急响应等级决策方法[J]. 中国管理科学, 2024, 32(6): 120-128.