Decoding the influence of servitization on green transformation in manufacturing firms: The moderating effect of artificial intelligence

转化(遗传学) 实证研究 产业组织 业务 计算机科学 数学 化学 统计 生物化学 基因
作者
Yanwu Song,Niu Niu,Xinghan Song,Bin Zhang
出处
期刊:Energy Economics [Elsevier BV]
卷期号:139: 107875-107875 被引量:29
标识
DOI:10.1016/j.eneco.2024.107875
摘要

This research addresses three crucial dimensions in operations management: the servitization of manufacturing, the utilization of artificial intelligence (AI) platforms, and green transformation. Employing the by-production method, we construct a metric for green transformation applicable to listed firms. Our comprehensive analytical framework integrates the resource-based view and information asymmetry theories, enabling systematic investigation into the influence of manufacturing servitization on firms' green transformation. In addition, we examine the moderating effect of AI platforms on the execution of servitization strategies. The empirical foundation of our study is an annually updated dataset of 554 manufacturing firms listed on China's A-share market. Our findings reveal a strong positive correlation between the deployment of servitization strategies and the green transformation of firms. This association withstands multiple robustness tests, including core variable substitution, outlier removal, and adjustments in clustering standard errors. Our research uncovers notable nuances. The effect of servitization on green total factor productivity is more visible for eastern and central China firms. Also, state-owned enterprises demonstrate a more conspicuous influence from servitization strategies. However, we observe a slight diminishing of this effect in firms audited by the Big Four. An essential contribution of our study is the illumination of the role AI platforms play in enhancing the efficacy of servitization. These AI platforms facilitate the creation of tailored solutions that curtail resource wastage, thus amplifying the positive effect of servitization strategies on green transformation.
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
fsh发布了新的文献求助10
刚刚
唐清羽完成签到,获得积分10
刚刚
带象发布了新的文献求助10
1秒前
NULL完成签到,获得积分10
1秒前
eden完成签到,获得积分10
2秒前
敏感烤鸡发布了新的文献求助10
3秒前
3秒前
jiejie完成签到,获得积分10
3秒前
zasideler完成签到,获得积分10
3秒前
3秒前
山西球迷发布了新的文献求助10
4秒前
烂漫的煎饼完成签到 ,获得积分10
4秒前
万里海天发布了新的文献求助200
4秒前
小曾最棒啦完成签到,获得积分10
5秒前
陈锦新发布了新的文献求助10
6秒前
8秒前
8秒前
sss完成签到,获得积分10
9秒前
HuiLang发布了新的文献求助30
9秒前
9秒前
10秒前
酆阁发布了新的文献求助10
10秒前
11秒前
FashionBoy应助杨潇采纳,获得10
11秒前
Dingdang完成签到,获得积分10
12秒前
12秒前
情怀应助Bruce采纳,获得10
12秒前
斯信荣完成签到,获得积分20
12秒前
12秒前
13秒前
韩萌娇完成签到,获得积分20
13秒前
星辰大海应助饱满的毛巾采纳,获得30
13秒前
慕青应助敏感烤鸡采纳,获得10
14秒前
fy完成签到,获得积分10
14秒前
14秒前
cdercder应助cb1999采纳,获得10
15秒前
15秒前
16秒前
深情安青应助燕不留声采纳,获得10
16秒前
魏猛完成签到,获得积分10
16秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 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
Molecular Mechanisms of Photosynthesis, 4th Edition 1000
Organic Reactions, Volume 116 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 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 7254342
求助须知:如何正确求助?哪些是违规求助? 8876255
关于积分的说明 18741684
捐赠科研通 6934884
什么是DOI,文献DOI怎么找? 3200093
关于科研通互助平台的介绍 2374772
邀请新用户注册赠送积分活动 2174977