DECENT WORK AND INNOVATIVE WORK BEHAVIOUR: THE MEDIATING ROLES OF ORGANISATIONAL LEARNING AND WORK ENGAGEMENT

调解 工作(物理) 先天与后天 结构方程建模 生成语法 工作投入 知识管理 业务 心理学 政治学 社会学 计算机科学 工程类 机械工程 机器学习 人工智能 人类学 法学
作者
Hamfrey Sanhokwe,Willie T. Chinyamurindi,Joe Muzurura
出处
期刊:International Journal of Innovation Management [World Scientific]
卷期号:27 (03n04)
标识
DOI:10.1142/s1363919623500214
摘要

The idea that innovations enable organisations to enjoy adaptive, competitive, and generative advantages has become widely accepted. This recognition has seen many low and middle-income countries (LMICs) add innovation policy to their national policy frameworks. However, most LMICs continue to experience economic stagnation and low productivity growth amid calls for deeper theoretical and practical examination of what could foster and sustain innovative work behaviour (IWB) in such settings. The study developed and tested a conditional mediation model explaining the activation of IWB with a focus on the central role of decent work. A time-lagged study design informed data collection from two probability samples. Employees self-reported using previously validated measures of the constructs in use. The study used covariance-based structural equation modelling (CB-SEM) to test the mediation model. Decent work had significant, positive relationships with organisational learning and work engagement. Organisational learning and work engagement were positively and significantly associated with IWB. Work engagement and organisational learning mediated the effect of decent work on IWB. The results provide complementary insights into how decent work may transform into IWB. Leadership seeking to better harness the innovative capabilities resident in their organisations should develop and nurture enterprise-wide, healthy workplaces anchored on the tenets of decent work. The modelled capabilities are learnable, and hence developable. We discuss the study implications and limitations.
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
陈莹完成签到,获得积分20
刚刚
qi发布了新的文献求助30
1秒前
1秒前
Wyan完成签到,获得积分20
1秒前
我是老大应助通~采纳,获得10
2秒前
Jenny应助淡定紫菱采纳,获得10
2秒前
逆流的鱼完成签到 ,获得积分10
3秒前
3秒前
liuqian完成签到,获得积分10
4秒前
Hou完成签到 ,获得积分10
4秒前
反杀闰土的猹完成签到 ,获得积分20
4秒前
所所应助cc采纳,获得10
5秒前
邵裘完成签到,获得积分10
5秒前
丘比特应助yin采纳,获得10
5秒前
6秒前
6秒前
6秒前
希望天下0贩的0应助sss采纳,获得20
6秒前
拼搏向前发布了新的文献求助10
6秒前
紫罗兰花海完成签到 ,获得积分10
7秒前
琪琪完成签到,获得积分10
8秒前
8秒前
爆米花应助高兴藏花采纳,获得10
8秒前
orixero应助Rrr采纳,获得10
8秒前
9秒前
张今天也要做科研呀完成签到,获得积分10
9秒前
humorlife完成签到,获得积分10
9秒前
打打应助给我找采纳,获得10
10秒前
酷波er应助谦让的含海采纳,获得10
10秒前
10秒前
shrike发布了新的文献求助10
10秒前
心灵美半邪完成签到 ,获得积分10
12秒前
wanci应助星晴遇见花海采纳,获得10
12秒前
12秒前
MILL完成签到,获得积分20
12秒前
卡卡发布了新的文献求助10
12秒前
今后应助九城采纳,获得10
13秒前
13秒前
我是125应助凶狠的乐巧采纳,获得10
13秒前
13秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527884
求助须知:如何正确求助?哪些是违规求助? 3108006
关于积分的说明 9287444
捐赠科研通 2805757
什么是DOI,文献DOI怎么找? 1540033
邀请新用户注册赠送积分活动 716904
科研通“疑难数据库(出版商)”最低求助积分说明 709794