The Effect of Open Innovation Implementation on Small Firms' Propensity for Inbound and Outbound Open Innovation Practices

IF 2.6 4区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Big Data Pub Date : 2020-10-12 DOI:10.3233/faia200638

P. Naruetharadhol, W. A. Srisathan, C. Ketkaew

引用次数: 6

Abstract

Small- and medium-sized enterprises (SMEs) face limited resource capability to implement open innovation. Understanding a robust mechanism of knowledge management, organisational structure, and networks can benefit managerial and organisational drivers to achieve open innovation in general. The paper sheds the new light in developing the open innovation implementation as a latent endogenous variable influence inbound OI and outbound OI. We used structural equation modelling (SEM) on a data set of 636 Thai SMEs. The results reveal that open innovation implementation reflected by managerial and organisational dimensions has a positive impact on contributing to both inbound and outbound OI. A key finding is that open innovation’s diffusion helps SMEs to overcome their technological capabilities to implement OI.

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开放创新实施对小企业对内和对外开放创新倾向的影响

中小企业实施开放式创新的资源能力有限。理解一个健全的知识管理、组织结构和网络机制，通常有利于管理和组织驱动因素实现开放式创新。本文将开放式创新作为一个潜在的内生变量来影响入站OI和出站OI，为开放式创新的实施提供了新的思路。我们对636家泰国中小企业的数据集使用结构方程模型(SEM)。研究结果表明，管理和组织维度所反映的开放式创新实施对对内和对外开放创新的贡献均有正向影响。一个重要的发现是，开放式创新的扩散有助于中小企业克服其实施开放式创新的技术能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

9.10

自引率

2.20%

发文量

期刊介绍： Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.