Measuring Corporate Digital Transformation: Methodology, Indicators and Applications

转化(遗传学) 过程(计算) 数字化转型 过程管理 数据科学 计算机科学 知识管理 构造(python库) 工业工程 工程类 化学 万维网 生物化学 基因 操作系统 程序设计语言
作者
Limin Zou,Li Wan,Hongyi Wu,Jiawen Liu,Peng Gao
出处
期刊:Sustainability [Multidisciplinary Digital Publishing Institute]
卷期号:16 (10): 4087-4087 被引量:35
标识
DOI:10.3390/su16104087
摘要

With the rapid development of data science, digital technology is integrating deeply with enterprise management, driving companies towards digital transformation to achieve sustainable development. However, digital transformation is a systematic and comprehensive process, posing challenges in accurately depicting firm-level digitalization. Hence, this study systematically reviews measurement methods for digital transformation across various themes related to enterprise digitalization. Existing literature predominantly employs questionnaire analysis, quantitative statistics, and text analysis to gauge the extent of digital transformation. In terms of indicator construction, existing literature mainly relies on input, process, and outcome variables to construct measurement indicators. Nevertheless, due to the subjectivity of questionnaires, the uniqueness of industry data, and the limitations of textual information, these methods and the indicators derived from them possess distinct applicability scopes. Refining the measurement of digital transformation should hinge on both the research objectives and the characteristics of the data. Furthermore, through the analysis of industry cases such as agriculture, manufacturing and service industries, this study also reveals the unique characteristics encountered by these industries in the process of digital transformation, provides a more detailed summary of measurement methods for these specific industries, and emphasizes the importance of selecting measurement methods according to industry characteristics.
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
孙温柔完成签到,获得积分10
1秒前
文献求助完成签到,获得积分10
1秒前
ariki完成签到 ,获得积分10
1秒前
Stella发布了新的文献求助10
2秒前
2秒前
2秒前
Solitude发布了新的文献求助10
3秒前
学术扛把子完成签到 ,获得积分10
4秒前
4秒前
蓝七发布了新的文献求助20
5秒前
Akim应助kkkkkkkk采纳,获得10
7秒前
BEMJ发布了新的文献求助10
7秒前
7秒前
尹小才发布了新的文献求助10
7秒前
隐形友蕊完成签到,获得积分10
8秒前
梁白开完成签到,获得积分10
8秒前
聪慧的小馒头完成签到,获得积分10
9秒前
Untitled应助开心灰狼采纳,获得20
9秒前
9秒前
可爱的函函应助mhb115采纳,获得10
11秒前
aajhajkahna应助奋斗的静竹采纳,获得10
13秒前
Akim应助尹小才采纳,获得10
13秒前
vanco发布了新的文献求助10
15秒前
杂草的生活完成签到,获得积分10
15秒前
雷电法王桃大师完成签到,获得积分10
18秒前
18秒前
19秒前
深情安青应助典雅雅容采纳,获得10
20秒前
21秒前
BEMJ完成签到,获得积分10
23秒前
DDL发布了新的文献求助10
26秒前
26秒前
思源应助derlun采纳,获得10
27秒前
Stella完成签到,获得积分10
27秒前
理想三寻完成签到,获得积分10
27秒前
Untitled完成签到,获得积分10
27秒前
Traveller发布了新的文献求助10
27秒前
Jasper应助可恶的鼠采纳,获得10
28秒前
28秒前
xc完成签到,获得积分10
29秒前
高分求助中
(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
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
Synthesis of P-Chiral Phosphine Ligands and Their Applications in Asymmetric Catalysis 400
Management and the Arts 310
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 7629518
求助须知:如何正确求助?哪些是违规求助? 9203974
关于积分的说明 19736300
捐赠科研通 7199027
什么是DOI,文献DOI怎么找? 3274277
关于科研通互助平台的介绍 2436423
邀请新用户注册赠送积分活动 2270424