Do the Hustle! Empowerment from Side-Hustles and Its Effects on Full-Time Work Performance

授权 大裂谷 工作(物理) 情感(语言学) 工作投入 需求方 心理学 社会心理学 政治学 经济 工程类 机械工程 物理 沟通 天文 法学 微观经济学
作者
Hudson Sessions,Jennifer D. Nahrgang,Manuel J. Vaulont,Raseana Williams,Amy Bartels
出处
期刊:Academy of Management Journal [Academy of Management]
卷期号:64 (1): 235-264 被引量:102
标识
DOI:10.5465/amj.2018.0164
摘要

Side-hustles, income-generating work performed alongside full-time jobs, are increasingly common as the gig economy provides opportunities for employees to perform supplementary work. Although scholars have suggested that side-hustles conflict with full-time work performance, we assert that psychological empowerment from side-hustles enriches full-time work performance. We argue that side-hustle complexity—the motivating characteristics of side-hustles—positively relates to empowerment and that side-hustle motives moderate this relationship. A study of 337 employees supports these assertions. We then investigate the spillover of side-hustle empowerment to full-time work performance in a 10-day experience-sampling method study of 80 employee–coworker dyads. We address an affective pathway in which daily side-hustle empowerment enriches full-time work performance through side-hustle engagement and positive affect at work. We also consider a cognitive pathway wherein side-hustle empowerment distracts from full-time work performance through side-hustle engagement and attention residue—persistent cognitions about side-hustles during full-time work. Overall, performance enrichment from side-hustles was stronger than performance conflict. We also consider affective shift from full-time work to side-hustles, finding negative affect from full-time work strengthens the relationship between side-hustle empowerment and engagement. Combined, our two studies examine the source of side-hustle empowerment and how side-hustle empowerment influences affective and cognitive experiences during full-time work.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
2秒前
2秒前
顾矜应助永远永远有采纳,获得10
2秒前
完美的沉鱼完成签到 ,获得积分10
3秒前
June应助Makoto1377采纳,获得10
4秒前
5秒前
6秒前
001015完成签到 ,获得积分10
7秒前
bkagyin应助两张采纳,获得10
7秒前
8秒前
粗犷的翎完成签到 ,获得积分10
8秒前
优美饼干发布了新的文献求助10
9秒前
10秒前
星辰大海应助饭团00采纳,获得10
10秒前
李健应助xuan采纳,获得10
11秒前
呆萌烨华发布了新的文献求助10
12秒前
燧人氏完成签到,获得积分10
13秒前
15秒前
15秒前
sky完成签到,获得积分10
15秒前
15秒前
CodeCraft应助有魅力的臻采纳,获得10
15秒前
Akim应助永远永远有采纳,获得10
15秒前
专注凌柏完成签到,获得积分10
15秒前
lxx发布了新的文献求助10
15秒前
852应助LYF采纳,获得20
16秒前
科研通AI6.4应助木子采纳,获得10
16秒前
勇敢的凤梨完成签到,获得积分10
17秒前
叶小文发布了新的文献求助10
17秒前
19秒前
YZF发布了新的文献求助10
21秒前
Ava应助土豪的秋莲采纳,获得10
22秒前
韩羽丰完成签到,获得积分10
23秒前
24秒前
小蘑菇应助稳重的书双采纳,获得10
24秒前
852应助永远永远有采纳,获得10
24秒前
月月发布了新的文献求助10
24秒前
大喜喜发布了新的文献求助10
24秒前
25秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7584017
求助须知:如何正确求助?哪些是违规求助? 9162760
关于积分的说明 19607883
捐赠科研通 7165908
什么是DOI,文献DOI怎么找? 3266349
关于科研通互助平台的介绍 2431309
邀请新用户注册赠送积分活动 2257911