This study aims to investigate the effects of open innovation (OI) and big data analytics (BDA) on reflective knowledge exchange (RKE) within the context of complex collaborative networks. Specifically, it considers the relationships between sourcing knowledge from an external environment, transferring knowledge to an external environment and adopting solutions that are useful to appropriate returns from innovation.
This study analyzes the connection between the number of patent applications and the amount of OI, as well as the association between the number of patent applications and the use of BDA. Data from firms in the 27 European Union countries were retrieved from the Eurostat database for the period 2014–2019 and were investigated using an ordinary least squares regression analysis.
Because of its twofold lens based on both knowledge management and OI, this study sheds light on OI collaboration modes and highlights the crucial role they could play in innovation. In particular, the results suggest that OI collaboration modes have a strong effect on innovation performance, stimulating the search for RKE.
This study furthers a deeper understanding of RKE, which is shown to be an important mechanism that incentivizes firms to increase their efforts in the innovation process. Further, RKE supports firms in taking full advantage of the innovative knowledge they generate within their inter-organizational network.
Purpose – This paper aims to investigate three key factors (i.e. cognitive dimensions, the knowledge-driven approach and absorptive capacity) that are likely to determine the preference for informal inbound open innovation (OI) modes, through the lens of the OI model and knowledge-based view (KBV). The innovation literature has differentiated these collaborations into informal inbound OI entry modes and formal inbound OI modes, offering an advocative and conceptual view. However, empirical studies on these collaborations are still limited.
Design/methodology/approach – Building on the above-mentioned theoretical framework, the empirical research was performed in two stages. First, data were collected via a closed-ended questionnaire distributed to all the participants from the sample by e-mail. Second, to assess the hypotheses, structural equation modelling (SEM) via IBM® SPSS® Amos 20 was applied.
Findings – The empirical research was conducted on 175 small to medium enterprises in the United Kingdom, suggesting that the knowledge-driven approach is the strongest determinant, leading to a preference for informal inbound OI modes. The findings were obtained using SEM and are discussed in line with the theoretical framework.
Research limitations/implications – Owing to the chosen context and sector of the empirical analysis, the research results may lack generalisability. Hence, new studies are proposed.
Practical implications – The paper includes implications for the development of informal inbound OI led by knowledge-driven approach.
Originality/value – This paper offers an empirical research to investigate knowledge-driven preferences in informal inbound OI modes.
В статье представлен анализ факторов, определяющих конкурентный преимущества компаний в период кризиса. Мы хотим найти в своем исследовании подтверждение того, что компании могут выигрывать даже на кризисных рынках, если смогут грамотно построить свою инвестиционную политику. Эта гипотеза была протестирована на базе данных 300 европейских компаний. Мы проанализировали статистически их деятельности в период экономического процветания, а также в период глобального экономического кризиса 2008-2009 г.г. Эта работа делает вклад в эмпирические корпоративные финансы, так как представляет доказательство того, что рестриктивная инвестиционная политика не является лучшим ответом компаний на рецессию.
Purpose – This paper aims to provide a substantial overview of features and channels of knowledge and technology transfer in light of achieving impact from science and research.
Design/methodology/approach – The paper is conceptual with substantial desk research undertaken. A taxonomy of transfer channels is proved and levels of impact from STI proposed.
Findings – It is found that there are different levels of value generated from science, technology and innovation, each featuring different stakeholders with different agendas and expectations. It is argued that to make knowledge and technology transfer impactful and sustainable, a long-term and holistic view and approach is required.
Originality/value – Against most papers about technology and knowledge transfer, this work presents an overarching overview of objects, channels and features of partners involved in transfer. It is features technology and knowledge transfer from a holistic perspective and provides useful background for future empiric studies and impact assessments.