Innovation effects of Industry 4.0 and inbound open innovation: individual and synergistic effects

Industry 4.0 (I4.0) technologies have demonstrated their potential to significantly drive innovation and enhance the performance of firms. However, I4.0 implementation is complex, requiring the application of diverse fields of knowledge and skill. Furthermore, although open innovation may contribute to the implementation of I4.0 technologies, the literature is still not clear about which open innovation practices best leverage the adoption of I4.0 technologies or how they might lead to improvements in product and process innovations, particularly when firms are facing turbulent environments. The present article aims to reduce this gap by investigating the relationships between open innovation, the adoption of I4.0 technologies, and product and process innovation performance, considering technological and market turbulence as moderating variables. As a research method, we carried out a quantitative survey of 246 industrial companies in Brazil. The results revealed that inbound open innovation flows can be used to support the adoption of I4.0 technologies, which in turn improves both process and product innovation performance. Our findings also indicate that in more technologically turbulent environments, the relationship between inbound open innovation and the adoption of I4.0 is stronger. Unexpectedly, the moderating role of market turbulence was not confirmed. The discussion arising from these findings addresses theoretical implications for the digitalisation of manufacturing, innovation management and contingency theory, as well as offering practical insights for managers and policymakers interested in performing I4.0-based innovation.

This paper examines a question of long standing: How can one obtain operational indexes of inventive and innovative activity and technical change? Specifically, for a sample of fifty-seven pharmaceutical manufacturing firms, we attempt to determine how well a simple count of invention patents serves as a surrogate for two alternative measures of technical change: the number of research and development personnel employed, reflecting inputs into the innovative process, and the value of new product sales, which reflects outputs of the process.

Artificial intelligence capabilities, open innovation, and business performance – Empirical insights from multinational B2B companies

The effects of inbound open innovation, outbound open innovation, and team role diversity on open source software project performance

Open Innovation remains the process of enabling inflow and outflow of knowledge, ideas, design, plus technologies throughout the organization during the various stages of the innovation process. This Innovation consists of inbound and outbound open innovations, whereby inbound open Innovation is the influx of knowledge, while outbound open innovation remains the outward flow of knowledge. Previously, studies related to open innovation have only focused specifically on the business world, the industrial sector while less focused on strategy and its implementation in the education sector. This study aims to fill this gap by studying open innovation in ordinary day secondary schools due to their significant contribution to development Malaysian education. Based on an open innovation model and a theory of views based on resources, this study will analyse the role of open and innovative innovation activities government support in determining the innovative capabilities of secondary schools. In this conceptual paper, the author develops the conceptual model that will be used in further research activities in education sector and will contribute to a better understanding of open innovation activities and their practices in secondary schools in Malaysia.

Empirical work on the causes and effects of inventive activity has had difficulty in finding measures that can indicate when and where changes in either inventive inputs or inventive output have occurred. The recent computerization of the U.S. Patent Office's data base may prove helpful in this context, but there is the problem that a priori we do not know the relationships between patent applications and economically meaningful measures of these inputs and outputs. To help solve this problem, this paper investigates the dynamic relationships among the number of successful patent applications of firms, a measure of the firm's investment in inventive activity (its R & D expenditures), and an indicator of its inventive output (the stock market value of the firm). (This abstract was borrowed from another version of this item.)

PurposeThe purpose of this paper is to examine the relationship between open innovation (OI) and innovative performance, and to explore the moderating effect of knowledge structure, including component knowledge and architectural knowledge, on this particular relationship.Design/methodology/approachThe proposed model was tested with regression analysis of data collected through a questionnaire survey of 231 employees of Chinese manufacturing firms.FindingsThe findings indicate that inbound OI is positively related to innovative performance and that outbound OI has an inverted U-shaped effect on innovative performance. By presenting empirical evidence of the moderating effects of component and architectural knowledge, our analysis of results demonstrates that the strong alignment between knowledge structure and OI results in superior innovative performance.Originality/valueThis study addresses the controversial issues brought up by previous studies with findings of an inverted U-shaped effect of outbound OI on innovative performance. By exploring the moderating effect of knowledge structure, the authors provide insights into how internal contextual factors in relation to organizational knowledge can affect the efficacy of the inbound and outbound OI on innovative performance.

Purpose This paper aims to examine the interrelation between two innovating strategies (product and process) on total factor productivity (TFP) growth and the dynamic linkages between these strategies, for Colombia. The authors first explore whether ex ante more productive firms are those that introduce innovations (the self-selection hypothesis) and if the introduction of innovations boosts TFP growth (the returns-to-innovation hypothesis). Second, the authors study the firm’s joint dynamic decision to implement process and/or product innovations. The authors use Colombian manufacturing data from the Annual Manufacturing and the Technological Development and Innovation Surveys. Design/methodology/approach This study uses a four-stage procedure. First, the authors estimate TFP using a modified version of Olley and Pakes (1996) and Levinsohn and Petrin (2003), proposed by De Loecker (2010), that implements an endogenous Markov process where past firm innovations are endogenized. This TFP would be estimated by GMM, Wooldridge (2009). Second, the authors use multivariate discrete choice models to test the self-selection hypothesis. Third, the authors explore, using multi-value treatment evaluation techniques, the life span of the impact of innovations on productivity growth (returns to innovation hypothesis). Fourth, the authors analyse the joint likelihood of implementing process and product innovations using dynamic panel data bivariate probit models. Findings The investigation reveals that the self-selection effect is notably more pronounced in the adoption of process innovations only, as opposed to the adoption of product innovations only or the simultaneous adoption of both process and product innovations. Moreover, our results uncover distinct temporal patterns concerning innovation returns. Specifically, process innovations yield immediate benefits, whereas implementing both product innovations only and jointly process and product innovations exhibit significant, albeit delayed, advantages. Finally, the analysis confirms the existence of dynamic interconnections between the adoption of process and product innovations. Originality/value The contribution of this work to the literature is manifold. First, the authors thoroughly investigate the relationship between the implementation of process and product innovations and productivity for Colombian manufacturing explicitly recognising that firms’ decisions of adopting product and process innovations are very likely interrelated. Therefore, the authors start exploring the self-selection and the returns to innovation hypotheses accounting for the fact that firms might implement process innovations only, product innovations only and both process and product innovations. In the analysis of the returns of innovation, the fact that firms may choose among a menu of three innovation strategies implies the use of evaluation methods for multi-value treatments. Second, the authors study the dynamic inter-linkages between the decisions to implement process and/or product innovations, that remains under studied, at least for emerging economies. Third, the estimation of TFP is performed using an endogenous Markov process, where past firms’ innovations are endogenized.

“Innovation has a lot to do with your ability to recognise surprising and unusual phenomena.”―Herbert Simon

The open innovation paradigm emphasizes that firms can improve their innovation performance by collaborating with other firms. However, there is no consensus in the open innovation literature regarding what drives firms' implementation of inbound and outbound open innovation and how the two types of open innovation influence innovation and firm performance. The present meta‐analysis synthesizes previous research to advance our understanding of open innovation by reexamining its antecedents and its moderating effects on innovation and firm performance. Using data from 157 articles, our results show that appropriation strategy, formal organizational structure, learning culture and top manager competence drive inbound open innovation, while innovation strategy, appropriation strategy, learning culture, and top manager competence drive outbound open innovation. In addition, we find that absorptive capacity positively moderates the positive impact of inbound and outbound open innovation on innovation performance. However, industry type (i.e., high‐ and low‐tech) is not found to moderate the effect of open innovation on innovation or firm performance, suggesting that both high‐ and low‐tech firms can equally reap benefits from open innovation. Furthermore, this study also partially supports the moderating effects of firm size and cultural value (individualism vs. collectivism) on the open innovation—performance relationship. These findings collectively suggest that the effects of inbound and outbound open innovation on performance are subject to contextual factors. Although this meta‐analysis does not allow us to generate new theories in the open innovation literature, it offers valuable insights to both academics and practitioners regarding factors affecting the implementation of open innovation and its performance implications.

PurposeThere is a dearth of empirical research on the impact of external knowledge search on innovation performance in different categories of service firms. This study explores the effectiveness of the breadth of external search on product and process innovations in German firms. In particular, the author modelled a non-linear relationship between the breadth of knowledge and product and process innovations.Design/methodology/approachDrawing on the Mannheim Innovation Panel (MIP) data for the German service firms in the period 2014–2016, the author reported findings from a bivariate probit model which took into account mutual interdependence between product and process innovations. Moreover, the model was separately estimated for knowledge-intensive business services (KIBS) and other services. For comparative purposes, the author also estimated the model for manufacturing firms.FindingsEmpirical findings uniformly indicated an inverted U-shaped effect of the breadth of knowledge on both product and process innovations. Furthermore, the results demonstrated that using up to three knowledge sources increases the probability of a joint implementation of product and process innovations. These findings hold for both KIBS firms and other services. However, those service firms that focussed on a single type of innovation experienced diminishing returns to external knowledge when exploiting more than one source of knowledge. These results indicated that a simultaneous introduction of different types of innovation required diverse knowledge sources. In contrast, when focussing on a single type of innovation, service firms experienced diminishing returns when multiple sources were used. However, this finding was only partially found for manufacturing firms. Accordingly, this study’s findings provided support for the demarcation approach, insofar as the breadth of knowledge had a heterogenous impact on innovation in manufacturing relative to service firms.Originality/valuePrevious studies on the breadth of knowledge search mostly examined its influence on innovation performance without separately analysing manufacturing and service firms. The present study focussed on service firms that were further divided into KIBS and other service firms. By investigating potentially non-linear relationships between knowledge breadth and product and process innovations, it illustrated how different innovation strategies were affected by a diverse pool of external knowledge sources.

PurposeThis paper aims to explore the direct effects of open innovation (OI) on firms’ innovative performance, and to examine the moderating effects of knowledge attributes, including knowledge distance, knowledge embeddedness and partner opportunism on this relationship.Design/methodology/approachSurvey data of 247 samples from China were used to test the proposed model through hierarchical regression analysis.FindingsThe findings indicate that the dimensions of OI are positively related to innovative performance. The results also reveal that knowledge distance positively moderates the relationship between inbound OI and innovative performance, whereas knowledge embeddedness negatively affects that relationship. Knowledge embeddedness negatively affects the relationship between inbound OI and innovative performance, whereas knowledge distance positively moderates that relationship. Thus, a new finding is proposed that knowledge attributes could align effectively with specific OI type to achieve superior innovation outcomes. In addition, the empirical results suggest that partner opportunism plays a negative moderating role on the relationship between outbound OI and innovative performance.Originality/valueThe proposed view that a firm’s innovation outputs will be superior when its knowledge attributes effectively align with OI enriches studies of the OI context and expands the literature of both the resource-based view and the knowledge-based view. Furthermore, this study provides insights into how OI benefits can be influenced by external contexts from the perspective of partners’ opportunistic behaviour.

Purpose: This study examined how inbound open innovation and dynamic capabilities (sensing, seizing, and transforming capacity) work together to explain innovation performance. Methodology: The study used a case research method that involved interviewing ten purposively selected managers of micro and small furniture industries in Arusha, Dar es Salaam and Mbeya cities of Tanzania. Subsequently, the study used illustrative and content analysis methods to compare and align predetermined theoretical relationships on how dynamic capabilities and inbound open innovation explain innovation performance to empirical results.Originality: The use of illustrative analysis to compare extant theoretical relationships between dynamic capabilities, inbound open innovation, and innovation performance to case studies’ processes in this study is novel to the open innovation literature. Also, the resultant conceptual framework and relationships linking inbound open innovation to innovation performance through systematic processes of dynamic capabilities are novel.Main results: This study showed that inbound open innovation explains innovation performance through systematic complementary processes of dynamic capabilities. Moreover, the study showed that if inbound open innovation generates complex external ideas, micro and small firms adopt coupled open innovation as a predecessor of dynamic capabilities to unlock complexity.Theoretical contributions: This study has integrated the theories of open innovation and dynamic capabilities by developing a conceptual framework and relationships that show how inbound open innovation explains innovation performance through dynamic capabilities.Practical contributions: This study has revealed alternative combinations of dynamic capabilities that business managers need to benefit innovation performance from inbound open innovation.

Since the term Open Innovation (OI) was coined by Henry Chesbrough in 2003, OI studies have been frequently conducted. Surprisingly, OI insights, in the context of Indonesian firms, are scarce. Furthermore, there are no existing OI studies that use data derived from innovation surveys. Hence, this study attempts to close the gap in the literature, by providing insights into Indonesian firms’ openness toward external knowledge, and its impact on innovation performance. The main aim of this study is to investigate the impact of OI practices on Indonesian manufacturing firms’ propensity to innovate (i.e. their product, process, organization, and marketing) and innovation performance. Product and process innovations are grouped under the term technological innovation, while organization and marketing innovations are classified as non-technological innovation. Data used in this study were derived from the Indonesia Innovation Survey (IIS) 2011 that covered the period from 2009-2010. Following Laursen and Salter’s (2006) study, OI indicators consist of external search breadth (i.e. the number of external sources or search channels that firms rely upon in their innovative activities) and depth (the extent to which firms draw deeply from the different external sources or search channels) in innovation process. Undertaking logistic and tobit regressions, this study shows that in general, both breadth and depth significantly and positively affect technological and non-technological innovation, as well as innovation performance. However, the over-search on external knowledge, measured by breadth squared and depth squared, negatively and significantly influence innovation and innovation performance. This indicates that too much external knowledge, sourced during the innovation process will diminish the return of innovation. This study also finds an indication of a complementary relationship existing between internal R&D and external knowledge; meaning that the implementation of one knowledge-sourcing strategy (either sourcing from internal R&D or external knowledge) increases the marginal returns from another. Lastly, important implications related to theoretical and innovation strategies are proposed.

This study examines how process management implementation and product quality affect technological innovation in Taiwan's information and electronics industry. This study also resolves inconsistencies in earlier research concerning the effects of the age and size of a firm on technological innovation. By testing the associated hypotheses after dividing technological innovation into process and product innovations, the empirical results herein indicate that a firm's implementation of process management promotes process innovation activity, and that product quality is positively correlated with product innovation. Hierarchical regression analyses reveal that the age and size of the firm affect only process innovation and not product innovation. The authors assert that successful management of technological innovation may require that product and process innovations be carefully evaluated. Different strategic choices between emphasising product versus process innovations may differently transform companies.