企业社会责任与组织对求职者吸引力的相互作用：系统动态研究

IF 1.8 Q3 MANAGEMENT Journal of Modelling in Management Pub Date : 2024-06-06 DOI:10.1108/jm2-11-2023-0274

Esrafil Ali, B. Satpathy, S. K. Prusty

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引用次数: 0

摘要

目的本文旨在了解企业社会责任（CSR）与组织对求职者的吸引力（AOJS）之间的双向互动关系。设计/方法/途径本文以因果循环图（CLD）的形式建立了一个系统动力学模型，动态地解释了企业社会责任与组织对求职者的吸引力之间的互动关系。为了检验所建立模型的可信度，使用了调查数据来验证因果循环图中的因果关系。研究结果本研究发现，通过捕捉企业社会责任的各种基本要素来制定有效的战略或工具，可以吸引潜在的求职者。

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Interaction of corporate social responsibility and attractiveness of organization to job seekers: a system dynamic study

Purpose This paper aims to understand the two-way interaction between corporate social responsibility (CSR) and the attractiveness of organization to job seekers (AOJS). Design/methodology/approach A system dynamics model is developed in the form of a causal loop diagram (CLD) that explains the CSR-AOJS interaction dynamically. To test the credibility of the developed model, the survey data are used to validate the causal relationships in the CLD. Findings This study found that developing an effective strategy or tool by capturing various essential CSR elements can attract potential job seekers. Originality/value The developed model is relevant to policymakers, decision-makers and managers when strategizing the CSR plan to attract potential job seekers.

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来源期刊

Journal of Modelling in Management MANAGEMENT-

CiteScore

5.50

自引率

12.50%

发文量

期刊介绍： Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.