Four decades of innovation research in forestry and the forest-based industries – A systematic literature review

Innovations play an important role in achieving competitiveness and long-term economic growth at all levels of the economic hierarchy. More recently, the role of sustainability-oriented innovation in achieving economic growth has become equally important. However, there is a scientific debate about the possibility of effective commercialization of sustainability-oriented innovations. The existence of such scientific debate, as well as the absence of citation-based systematic literature reviews, became a prerequisite for conducting a comparative literature review of research on the effective commercialization of conventional and sustainability-oriented innovations. The purpose of the study is to conduct a comparative review and analysis of research on the commercialization efficiency of conventional and sustainability-oriented innovations. The analysis was conducted on the basis of a citation-based systematic literature review method. The results show that sustainable innovation research is more focused on the relationship between commercialization and firm performance. In the field of conventional innovations, research trends have shifted from studying the impact of technology transfer office (TTO) size, staffing, compensation practices to how strategic factors affect the efficiency of commercialization. In the area of sustainability-oriented innovation, the issues of the strategic orientation impact cause the most sustained interest, while managerial concerns and the stringency of environmental regulations have been actively explored in the past few years. It was revealed that the commercialization efficiency of sustainability-oriented innovations is characterized by so called sustainability-oriented criteria. A distinctive output criterion for commercialization efficiency of sustainability-oriented innovation is the improvement of the firm’s image. In addition, content analysis identified possible research directions to be investigated.

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Investigating Current Directions in Cross-Industry Innovation Research – a Systematic Literature Review

10.21203/rs.2.19792/v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Torben Andreas Mahnken

Keyword(s):

Literature Review ◽

Semantic Similarity ◽

Systematic Literature Review ◽

Relevant Literature ◽

Similarity Analysis ◽

New Approach ◽

Innovation Research ◽

Constant Change ◽

Review Protocol ◽

Semantic Similarity Analysis

Abstract Background: The companies’ operative environment is covered by a constant change through digitization, industry 4.0, artificial intelligence and megatrends, which pose enormous challenges. In order to master these challenges, the development of knowledge from foreign industries is a possible solution. This phenomenon is called cross-industry innovation. The aim of this study is to identify major directions in cross-industry innovation research. An essential part of science is to build on and enhance already published knowledge. In order to identify this knowledge and to offer a comprehensible and reproducible process, a systematic approach is required. For this study, a systematic literature review will be applied. During the review of the relevant literature, an understanding of the broad and deep nature of the literature emerges and it is possible to identify research gaps, which is often based on qualitative analyses. We will develop a new approach for analyzing literature based on semantic similarity analysis. Methods: In order to achieve the research objectives a systematic literature review is applied and slightly modified. First, we will apply a systematic literature review protocol to establish reproducible results. Second, we develop a new approach for analyzing literature using a combination of semantic similarity analysis and a cluster analysis. Conclusion: This review will aid in determining the directions of cross-industry innovation. Overall, six directions of cross-industry innovation research can be identified. Furthermore, this study offers a new approach for analyzing literature based on quantitative analysis like semantic similarity analysis.

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