4.5 Article

Digitalization, business models, and SMEs: How do business model innovation practices improve performance of digitalizing SMEs?

期刊

TELECOMMUNICATIONS POLICY
卷 43, 期 9, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.telpol.2019.101828

关键词

Big data; Business model experimentation; Business model innovation; Digitalization; SME; Social media

资金

  1. European Community [645791]
  2. H2020 Societal Challenges Programme [645791] Funding Source: H2020 Societal Challenges Programme

向作者/读者索取更多资源

Digital transformation is requiring companies to rethink and innovate their business models (BMs). However, small- and medium-sized enterprises (SMEs) have scarce time and resources for experimenting with their BMs and implementing new strategies. This paper examines whether SMEs that undergo digital transformation perform better if they allocate more resources for BM experimentation and engage more in strategy implementation. An empirical study was conducted on 321 European SMEs that actively use social media, big data, and information technology to innovate their BMs. Furthermore, structural equation modelling showed positive overall firm performance effects of more resource allocation to BM experimentation and more engagement in practices of strategy implementation. These effects were mediated by BM experimentation practices and company innovativeness. Moreover, fuzzy-set qualitative comparative analysis (fsQCA) revealed the presence of equifinality by identifying different configurations in which these antecedent conditions affect overall firm overall performance. The results of two methodological approaches showed that SMEs may take different routes to improve their performance when digital transformation is changing their BM. This paper is one of the first to analyse how SMEs can handle the impact of digitalization by spending more time and effort on innovating their BMs. Practical and policy implications are discussed.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据