Analyzing the factors influencing the creation of a toxic workplace in the electronics industry:a fuzzy cognitive map approach

IF 1.8 Q3 MANAGEMENT Journal of Modelling in Management Pub Date : 2024-05-09 DOI:10.1108/jm2-05-2023-0090

Reza Salehzadeh, Mehran Ziaeian, Pooria Malekinejad, Mohammad Ali Zare

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Abstract

Purpose

This study aims to identify the factors influencing the creation of a toxic workplace and to examine how to improve a toxic workplace in the electronics industry.

Design/methodology/approach

First, the factors that influence the creation of a toxic work environment were identified by reviewing the research literature. Then, the current status of each identified factor in Iran’s electronics industry was evaluated by developing a questionnaire. Based on the survey data, a relationship map between the factors influencing the toxic workplace was created using the fuzzy cognitive mapping technique. Finally, scenarios were designed to improve the toxic workplace.

Findings

The results show that the “workplace bullying” factor is the factor with the highest centrality in relation to other factors. The results of the scenario design indicate the effectiveness of the “unrealistic expectations at work” factor as a scenario trigger.

Originality/value

This study helps reduce the toxic workplace in the organization, which plays an important role in improving the employees’ work performance and the organization’s development.

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分析电子工业有毒工作场所的影响因素：模糊认知图法

设计/方法/途径首先，通过查阅研究文献，确定了影响有毒工作环境产生的因素。然后，通过编制调查问卷，对伊朗电子行业中每个已确定因素的现状进行评估。在调查数据的基础上，使用模糊认知绘图技术绘制了影响有毒工作环境因素之间的关系图。结果结果表明，"工作场所欺凌 "因素是与其他因素相比中心度最高的因素。情景设计的结果表明，"工作中不切实际的期望 "因素作为情景触发器是有效的。原创性/价值本研究有助于减少组织中的有毒工作场所，这对提高员工的工作绩效和组织的发展具有重要作用。

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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.