Can decision intelligence help organizations retain employees? Serial multiple mediation of job characteristics and meaningful work

IF 1.6 Q2 PSYCHOLOGY, MULTIDISCIPLINARY

Cogent Psychology Pub Date : 2023-10-23 DOI:10.1080/23311908.2023.2258475

Miriam O’Callaghan

{"title":"Can decision intelligence help organizations retain employees? Serial multiple mediation of job characteristics and meaningful work","authors":"Miriam O’Callaghan","doi":"10.1080/23311908.2023.2258475","DOIUrl":null,"url":null,"abstract":"New artificial intelligence (AI) powered technologies such as OpenAI’s ChatGPT model, intelligent decision support systems, and autonomous robots are transforming decision making leading to the increased prevalence of decision intelligence in organizations. This paper explores the relationship between decision intelligence, job characteristics, meaningful work, and employees’ intentions to leave the organization or turnover intentions. The research model is based on robust theoretical foundations and was tested with data collected from a survey on Prolific. The study utilizes PLS SEM (partial least squares structural equation modeling) method to test the hypotheses. Three categories of model fit indices are used to assess the final model. The results interpreted from direct effects revealed a positive relationship between decision intelligence and intention to leave. Nevertheless, the mediation analysis within the path model demonstrated that this relationship transformed into a negative one when mediated by job characteristics and meaningful work. In its conclusion, the paper discusses research findings, addresses limitations, and underscores contributions, thus paving the path for integrating decision intelligence into academic literature and industry practices.","PeriodicalId":46323,"journal":{"name":"Cogent Psychology","volume":"11 1","pages":"0"},"PeriodicalIF":1.6000,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cogent Psychology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23311908.2023.2258475","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

New artificial intelligence (AI) powered technologies such as OpenAI’s ChatGPT model, intelligent decision support systems, and autonomous robots are transforming decision making leading to the increased prevalence of decision intelligence in organizations. This paper explores the relationship between decision intelligence, job characteristics, meaningful work, and employees’ intentions to leave the organization or turnover intentions. The research model is based on robust theoretical foundations and was tested with data collected from a survey on Prolific. The study utilizes PLS SEM (partial least squares structural equation modeling) method to test the hypotheses. Three categories of model fit indices are used to assess the final model. The results interpreted from direct effects revealed a positive relationship between decision intelligence and intention to leave. Nevertheless, the mediation analysis within the path model demonstrated that this relationship transformed into a negative one when mediated by job characteristics and meaningful work. In its conclusion, the paper discusses research findings, addresses limitations, and underscores contributions, thus paving the path for integrating decision intelligence into academic literature and industry practices.

查看原文本刊更多论文

决策情报能帮助组织留住员工吗?工作特征与有意义工作的序列多重中介作用

新的人工智能(AI)驱动的技术，如OpenAI的ChatGPT模型，智能决策支持系统和自主机器人正在改变决策制定，导致决策智能在组织中越来越普遍。本文探讨了决策智力、工作特征、有意义的工作与员工离职意向或离职意向之间的关系。该研究模型建立在坚实的理论基础之上，并通过对多产网站调查收集的数据进行了测试。本研究采用偏最小二乘结构方程模型(PLS SEM)方法对假设进行检验。采用三类模型拟合指标对最终模型进行评价。从直接效应的角度解释的结果揭示了决策智力与离职意图之间的正相关关系。然而，路径模型内的中介分析表明，在工作特征和有意义工作的中介作用下，这一关系转化为负向关系。在结论部分，本文讨论了研究成果，指出了局限性，并强调了贡献，从而为将决策智能整合到学术文献和行业实践中铺平了道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Cogent Psychology PSYCHOLOGY, MULTIDISCIPLINARY-

CiteScore

2.90

自引率

0.00%

发文量

审稿时长

12 weeks

期刊介绍： One of the largest multidisciplinary open access journals serving the psychology community, Cogent Psychology provides a home for scientifically sound peer-reviewed research. Part of Taylor & Francis / Routledge, the journal provides authors with fast peer review and publication and, through open access publishing, endeavours to help authors share their knowledge with the world. Cogent Psychology particularly encourages interdisciplinary studies and also accepts replication studies and negative results. Cogent Psychology covers a broad range of topics and welcomes submissions in all areas of psychology, ranging from social psychology to neuroscience, and everything in between. Led by Editor-in-Chief Professor Peter Walla of Webster Private University, Austria, and supported by an expert editorial team from institutions across the globe, Cogent Psychology provides our authors with comprehensive and quality peer review. Rather than accepting manuscripts based on their level of importance or impact, editors assess manuscripts objectively, accepting valid, scientific research with sound rigorous methodology. Article-level metrics let the research speak for itself.