Gains and pains from the open innovation framework

While firms increasingly adopt open innovation, little is known about whether firms gain or lose from this innovation approach. Motivated by this research gap in the literature, the thesis explores the antecedents and performance implications of open innovation strategies, particularly collaboration and contractual forms of relationships for innovation (i.e. innovation cooperation and R&D outsourcing/external R&D). The thesis is empirical and relates the various results to the data used. The first one with German Community Innovation Survey (CIS), the second one with Danish CIS and the third one with the patent enhanced German CIS. The empirical analyses suggest that a value-enhancing objective rather than a cost-minimization purpose is the main factor that stimulates companies to engage in open innovation strategies. The research also reveals that firms engage in various innovation strategies simultaneously (i.e. international external R&D, innovation cooperation partnerships and internal R&D), but they fail to combine these instruments successfully for product innovation, implying that the single innovation strategy is performing better than combining different knowledge sourcing strategies in open innovation. Furthermore, the thesis provides evidence that sourcing R&D inputs from a domestic R&D provider can be a risky strategy when a firm aims to generate breakthrough product innovations. Instead, the firm should seek to acquire knowledge inputs from international marketplaces. The research also indicates that those firms outsourcing R&D activities are more likely to generate inventions than their counterparts that do not invest in this R&D strategy. However, this positive performance implication of R&D outsourcing does not appear to hold for invention quality

“Frenemies” of innovation: understanding the role of coopetition in service innovation in emerging markets

open access articleCoopetition is considered an important strategy for innovation. However, the literature provides limited evidence on how coopetition relates to innovation in service sector, particularly in emerging markets. Moreover, little is known about the effects of the formal and informal aspects of coopetition on innovation and how absorptive capacity of firm may influence this relationship. Against this background, using the official national innovation surveys of Nigeria (2008 and 2011), this study contributes to the ongoing debate by empirically examining the innovation endeavors of 421 Nigerian SMEs. The study employs logistic regression methods to model and explore the relationships between coopetition and innovation in the sample. The results show that that formal coopetition hinders innovation while informal coopetition supports it and absorptive capacity moderates these relationships. The study provides important insights about the concept of coopetition in emerging markets, especially vis-à-vis their institutional idiosyncrasies. Finally, the study highlights its implications and suggests some avenues for future research

Data-based Startup Profile Analysis in the European Smart Specialization Strategy: A Text Mining Approach

AbstractThe aim of the paper is to develop novel scientific metrics approach to the European Smart Specialization Strategy. The European Union (EU) has introduced Smart Specialization Strategy (S3) to increase the innovation and competitive potential of its member states by identifying promising economic areas for investment and specialization. While the evaluation of Smart Specialization Strategy requires measurable criteria for the comparison of rate and level of development of countries and regions, policy makers lack efficient and viable tools for mapping promising sectors for smart specialization. To cope with this issue, we used a text mining approach to analyze the business description of startups from Nordic and Baltic countries in order to identify sectors in which entrepreneurs from these regions see new business opportunities. In particular, a topic modeling, Latent Dirichlet Allocation approach is employed to classify business descriptions and to identify sectors, in which start-up entrepreneurs identify possibilities of smart specialization. The results of the analysis show country-specific differences in national startup profiles as well as variations among entrepreneurs coming from developed and less developed EU regions in terms of detecting business opportunities. Finally, we present policy implications for the European Smart Specialization Strategy. </div

Evaluation of the Implementation of Smart Specialisation Strategy in Lithuanian Industry

This article provides data-driven analyses of Lithuanian foreign trade activities. We combine Herfindahl-Hirschman Index (HHI) and Lauraéus-Kaivo-oja Index (LKI) measures to identify key changes and trends in export and import structures of the Lithuanian economy. The findings suggest that the export and import portfolios of the Lithuanian economy have been successfully diversified and the Lithuanian Smart Specialisation Strategy (S3) successful implemented in years 2015 through 2020. Presented in the form of HHI and LKI time series, our findings and the corresponding conclusions will be relevant to both the Lithuanian export and import industry and to industrial and economic policymakers in Lithuania and in international export and import agencies.</p

Mapping the Wave of Industry Digitalization by Co-Word Analysis: An Exploration of Four Disruptive Industries

This paper aims to identify global digital trends across industries and to map emerging business areas by co-word analysis. As the industrial landscape has become complex and dynamic due to the rapid pace of technological changes and digital transformation, identifying industrial trends can be critical for strategic planning and investment policy at the firm and regional level. For this purpose, the paper examines industry and technology profiles of top startups across four industries (i.e. education, finance, healthcare, manufacturing) using CrunchBase metadata for the period 2016-2018 and studies in which subsector early-stage firms bring digital technologies on a global level. In particular, we apply word co-occurrence analysis to reveal which subindustry and digital technology keywords/keyphrases appear together in startup company classification. We also use network analysis to visualize industry structure and to identify digitalization trends across sectors. The results obtained from the analysis show that gamification and personalization are emerging trends in the education sector. In the finance industry, digital technologies penetrate in a wide set of services such as financial transactions, payments, insurance, venture capital, stock exchange, asset and risk management. Moreover, the data analyses indicate that health diagnostics and elderly care areas are at the forefront of the healthcare industry digitalization. In the manufacturing sector, startup companies focus on automating industrial processes and creating smart interconnected manufacturing. Finally, we discuss the implications of the study for strategic planning and management

Perception or capabilities? An empirical investigation of the factors influencing the adoption of social media and public cloud in german SMEs

Social media and public cloud computing (SM&PC) have emerged as important resources of small and medium enterprises (SMEs), but not all SMEs use SM&PC. The existing research predominantly focuses on the role of either the features of social media and cloud computing in relation to the perceptions of decision makers or the internal capabilities of organization concerning new innovation adoption. By integrating multidisciplinary literature, we, instead, argues that both the perception- and capability-related factors could play an important role in the adoption of new ICT technology, such as SM&PC. Therefore, we empirically investigated the decision maker’s perception-related and SME’s capability-related factors that may influence the adoption of SM&PC in SMEs in Germany. We used quantitative research methods to examine the proposed hypotheses on a sample of 2,404 SMEs from 17 industrial sectors. The results demonstrate that the decisions of German SMEs to engage in social media and cloud computing are not only influenced by the perceptions of SME owners about the usefulness, security aspects, and the implementation costs of SM&PC, but also by the internal capabilities of an SME, namely the innovativeness of an SME. The results and potential contributions of our research are discussed.</p

Evaluation of the implementation of smart specialisation strategy in Lithuanian industry

This article provides data-driven analyses of Lithuanian foreign trade activities. We combine Herfindahl-Hirschman Index (HHI) and Lauraéus-Kaivo-oja Index (LKI) measures to identify key changes and trends in export and import structures of the Lithuanian economy. The findings suggest that the export and import portfolios of the Lithuanian economy have been successfully diversified and the Lithuanian Smart Specialisation Strategy (S3) successful implemented in years 2015 through 2020. Presented in the form of HHI and LKI time series, our findings and the corresponding conclusions will be relevant to both the Lithuanian export and import industry and to industrial and economic policymakers in Lithuania and in international export and import agencies

Mapping the Wave of Industry Digitalization by Co-Word Analysis : An Exploration of Four Disruptive Industries

This paper aims to identify global digital trends across industries and to map emerging business areas by co-word analysis. As the industrial landscape has become complex and dynamic due to the rapid pace of technological changes and digital transformation, identifying industrial trends can be critical for strategic planning and investment policy at the ¯rm and regional level. For this purpose, the paper examines industry and technology pro¯les of top startups across four industries (i.e. education, ¯nance, healthcare, manufacturing) using CrunchBase metadata for the period 2016–2018 and studies in which subsector early-stage ¯rms bring digital technologies on a global level. In particular, we apply word co-occurrence analysis to reveal which subindustry and digital technology keywords/keyphrases appear together in startup company classification. We also use network analysis to visualize industry structure and to identify digitalization trends across sectors. The results obtained from the analysis show that gamification and personalization are emerging trends in the education sector. In the finance industry, digital technologies penetrate in a wide set of services such as financial transactions, payments, insurance, venture capital, stock exchange, asset and risk management. Moreover, the data analyses indicate that health diagnostics and elderly care areas are at the forefront of the healthcare industry digitalization. In the manufacturing sector, startup companies focus on automating industrial processes and creating smart interconnected manufacturing. Finally, we discuss the implications of the study for strategic planning and management