Effects Of Open Innovation Research Articles

Dynamics from open innovation to evolutionary change

We created conceptual models that people may use to analyze and forecast the dynamic effects of open innovation, which we applied to the smartphone sector using a model-based analysis approach. In addition, we built an open innovation simulation model for the smartphone sector. The dynamic model of open innovation linked logic and concepts relating to open innovation, complex adaptive systems, and evolutionary change. The model can be used to analyze the dynamic effects of open innovation strategies and open innovation simulation for the selection of future strategies.

Financial effects of open innovation in the manufacturing industry

Purpose – The purpose of this paper is to investigate the long-term financial effects of open innovation in the manufacturing industry. Design/methodology/approach – Drawing upon an open innovation literature, this study examined 671 open innovation announcements made by firms listed on the New York Stock Exchange and National Association of Securities Dealers Automated Quotations during 2003-2012. By employing the event study, the long-term financial performances of the firms that announced open innovation were measured using six dependent performance variables (ROA, ROS, Tobin’s Q, Cost ratio, Sales growth, Asset turnover). Findings – The results indicate that open innovation in the manufacturing industry may lead to long-term improvements in firm profitability, triggering a positive reaction by stockholders. Open innovation also decreased production costs and increased sales volume over the long run. In all, open innovation was found to be beneficial to the firm in terms of profitability, production process improvement, and market benefits. Originality/value – This paper is the first longitudinal empirical study to investigate the long-term effects of open innovation in terms of US manufacturing financial performance. It contributes to the body of knowledge by complementing previous open innovation studies, which generally focus on context-specific issues.

Using functional approach to increase effectiveness of open innovation in chemical engineering

Open innovation has been widely discussed ever since P&G publicly pronounced that “Open innovation is a way for companies to avoid the stale, repetitive thinking that can happen when employees are accustomed to their internal ways of solving problems”. The goal of open innovation is to connect innovation problem to the best existing technical solution to this problem that can be found outside of company's R&D. The general concept of open innovation has been widely accepted and practiced. However, in practice, open innovation frequently works inefficiently because problem at the input is not formulated properly or is a wrong problem to be solved. The objective of this article is to discuss this challenge of open innovation and demonstrate – through the prism of chemical engineering – how one of the main TRIZ tools, functional approach, can increase the effectiveness of open innovation.

The effect of inbound open innovation on firm performance: Evidence from high-tech industry

Academics and practitioners have demonstrated that open innovation is critical to superior performance; firms thereby connect their in-house R&D functions with external partners to enhance their innovation activities. This study extends the open innovation theory and the knowledge-based view to explain how a firm's external knowledge resource acquisition influences its innovation deployment as well as its performance. Specifically, we argue that technology scouting plays an important role as an antecedent to collaboration with horizontal and vertical technology acquisitions. Furthermore, the horizontal technology collaboration and vertical technology collaboration play mediators in determining firm performance returns from executing such acquisitions. Based on a large-scale survey of high-tech firms, the study finds that the ability to build well-developed external connection channels increases the efficacy of inbound open innovation in achieving superior performance.

The Effects of Commercialization Capability in Small and Medium-sized Businesses on Business Performances: Focused on Moderating Effects of Open Innovation

This study aims to set the effects of technology commercializing capabilities (Acquisition / Internalization, market-oriented innovation, and exploitational innovation) on business performances (financial performance, non-financial performance, and innovational performance) as a primary model; examine the moderating effects of open innovation; build up the foundation to promote small and medium enterprises located in industrial complexes in Daegu; and lay groundwork for regional industrial strategies and national policy projects. We examined the relations between variables by conducting correlation measurement with only those variables that went through the above process. And hierarchical regression analysis was done to confirm our research model and hypothesis test.The empirical analysis results of the research are as follows: First, we found that acquisition/internalization affected greatgly the firm’s financial performance and innovation performance (the speed of commercialization, the number of new product developments). Second, technological exploitation has positive effects on on their financial performance and innovation performance (the speed of commercialization, and the number of new product developments). Third, market exploitation also influenced strongly financial and innovative performances. This is because small and medium-sized companies in Korea produce and deliver products that higher level companies order rather than they develop their own products and improve the management performance by selling them to the market. Fourth, small and medium-sized firms seek to overcome the drawbacks coming from geographic proximity by means of open innovation during the process of commercializing the goods with their transferred techniques.

The Effect of Open Innovation on Technology Intelligence in Aviation Industry of Iran

Nowadays, innovation management paradigm has been changed from internal development to networking and cooperation between Science & Technology network. Open innovation approach is also one of the new approaches of new innovation management that has modified internal research and development suppositions to research and development through cooperation. Accessing an appropriate technological environment and continuous awareness require various tools and methods. One of these tools is monitoring of this technological environment by the use of technology intelligence system. The purpose of this study is surveying the effect of open innovation approach on technology intelligence application in Iran’s aviation industry. The sampling method in this article is the stratified sampling of experts from the aviation industry, which includes 81 experts, managers of industrial and researching institutions, designers and superior designers, managers of repairing and maintenance, and a Private company (Aviation Union members). The tool for data gathering is a questionnaire that has been used according to validation of the content validity by experts of industry and academic. In the present research, two standard models, Savioz ( 2004 ) for measuring technology intelligence and Hafkesbrink ( 2010 ) for measuring open innovation approach, have been used. Results show that these two elements can be applied exclusively in organisation for technology trend analysis and technology or idea acquisition approach. Finally, the relationship between the concepts of open innovation and intelligence was investigated.

The effects of entrepreneurial orientation on company performance - Focusing on moderating effect of knowledge creation process and open innovation -

The effects of entrepreneurial orientation on company performance - Focusing on moderating effect of knowledge creation process and open innovation -

An exploratory study of the economic effect of open innovation

Purpose – The purpose of this paper is to discover the economic effects of open innovation investigated the following research questions: do economic effects of open innovation – a certain economic phenomenon or economic paradigm that surpasses the level of the management strategies of individual enterprises – exist? If so, what are the economic effects? Design/methodology/approach – The authors analyse the change of classical economic characteristics, such as diminishing marginal products, economy of scale, and X-inefficiency, which are selected by literature review to find out the effects of open innovation. The authors select long-tailed phenomena and App Store phenomena, which are a direct result of open innovation. From these, the authors find out the effects of open innovation. Findings – Through exploratory-level studies, the economic characteristics of open innovation have been identified: gradual increases of marginal products, the economy of diversity, and X-efficiency improvement. Research limitations/implications – These three economic characteristics of open innovation have been verified through secondary analysis methods based on the long-tailed phenomenon and App Store phenomenon. Open innovation triggers new economic effects. Thus, the authors should create new strategies and policies to treat open innovation that are based on additional deep research. Practical implications – This paper introduces new ideas about open innovation in economics. Social implications – According to the findings, open innovation will give the authors new ways to develop continuously in a knowledge-based economy. Originality/value – For the first time, the authors understand the economic value of open innovation and its implications.

When Is Open Innovation Beneficial? The Role of Strategic Orientation

Various scholars have accomplished a great deal to better understand open innovation effectiveness. Case studies have detailed its performance effects, while other studies showed the effectiveness of an aspect of open innovation, such as collaboration with third parties, external technology commercialization, and cocreation. Though most studies report a positive relation between open innovation and innovation performance, some studies indicate possible negative effects. This has resulted in a call for research on what kind of organizational context suits open innovation best.This study therefore addresses two questions: (1) does performing open innovation activities lead to increased innovation performance, and to which aspects of innovation performance is open innovation most strongly related? (2) what is the moderating impact of various kinds of strategic orientation on the relation between open innovation and innovation performance? In this study, we investigate three types of strategic orientations: entrepreneurial orientation, market orientation, and resource orientation.In a survey among 223 Asian service firms, we first develop and test a comprehensive measurement scale for open innovation that captures the entire range of open innovation activities, including outside‐in activities, inside‐out activities, and coupled activities. The final scale comprises of 10 items and indicates to what extent a firm has implemented open innovation activities.Next, we study the relation between open innovation and innovation performance. The results indicate that performing open innovation activities is significantly and positively related to all four dimensions of innovation performance: new product/service innovativeness, new product/service success, customer performance, and financial performance. The impact of open innovation is not limited to a particular aspect of innovation performance; it positively affects a broad range of innovation performance indicators. Though open innovation is positively related to all four dimensions of innovation performance, the effect sizes are not equal. The impact on new service innovativeness and financial performance is relatively stronger.Regarding the influence of a firm's strategic orientation, we find that all significant moderation effects are positive. This suggests that, in general, having a more explicit strategic orientation enhances the effectiveness of open innovation. When comparing the three strategic orientations, entrepreneurial orientation strengthens the positive performance effects of open innovation significantly more than market orientation and resource orientation do. In turn, market orientation has a significantly stronger moderation effect than resource orientation. These findings provide empirical evidence of the context dependency of open innovation. Especially an entrepreneurial orientation, which is associated with proactive and entrepreneurial processes, seems to create a fertile setting for open innovation.

Introduction of an objective model to measure open innovation and its application to the information technology convergence sector

This study attempts to develop a new objective method to measure open innovation. It proposes a new concept for measuring open innovation using patent information to improve on the ideas of the ‘width’ and ‘depth’ dimensions of open innovation. Based on the review of related literature, three open innovation measures are proposed: Ratio of Open Innovation (ROI), Intensity of Open Innovation (IOI) and Total Level of Open Innovation (TOI). These measures are applied to compare open innovation levels between nations and between firms as well as to analyse the effect of open innovation on firm performance.

Capturing the real value of patent analysis for R&D strategies

Patent information can be used for strategic planning purposes. Conventional patent analysis has commonly focused on factual information and, in particular, on information extraction, visualisation and interpretation. Less scholarly attention has been devoted to the strategic role of an integrated system of patent intelligence in supporting decision-making in R&D investments. Our paper addresses this gap and explores how patent analysis may benefit those firms that intend capturing the beneficial effects of Open Innovation. We also critically discuss the intrinsic limits of both patent information and patent analysis, which should be taken into account by systems of patent intelligence.

Is There Any Difference in the Effect of Open Innovation According to the Product Life Cycle? : Revisiting the Relationship Between Product Life Cycle and Trade

Is There Any Difference in the Effect of Open Innovation According to the Product Life Cycle? : Revisiting the Relationship Between Product Life Cycle and Trade

Abstract LB-2: Open innovation drug discovery: A study in JQ1.

Abstract Collaborative research from our laboratory, in 2010, produced a first-in-class inhibitor of BET bromodomain proteins (JQ1). As an effort to promote a more open-innovation model of drug discovery, we endeavored to provide JQ1 without restriction of cost or delay to the scientific community. Toward this objective, we have optimized and completed a facile scaling synthesis capable of producing 100 g quantities of the active (+)-JQ1 stereoisomer. In the past 30 months, JQ1 has been provided to over 350 laboratories in more than a dozen countries. Through this research, BET bromodomain proteins have emerged as pharmacologically validated targets in multiple model systems of cancer including squamous carcinoma of the lung, head and neck, acute myeloid leukemia, multiple myeloma, Burkitt lymphoma, B-cell acute lymphoblastic leukemia, neuroblastoma and non-small cell lung cancer. More than 800 cancer cell lines and 25 murine models of cancer have been systematically screened with JQ1 for sensitivity to bromodomain inhibition, identifying additional therapeutic opportunities. Open availability of JQ1 has also lead to unexpected innovation outside of cancer research through studies identifying opportunities for BET bromodomain inhibition in such diverse fields as male contraception and HIV therapeutics. Since publication of the chemical structure and synthetic route to JQ1, seven new BET bromodomain inhibitors have appeared in the literature each derivatized from and/or benchmarked to the JQ1 molecule. Importantly, BET bromodomain inhibition has already accomplished clinical translation. To more objectively assess the consequence of open-innovation as a model of drug discovery, we have systematically analyzed metadata collected from published research and our ongoing efforts in compound distribution. Here, we present an interim analysis which relates the effect of open-innovation in drug discovery to the scope, productivity, reproducibility and importantly the pace of scientific research in epigenetic reader proteins. These results identify open-innovation in drug discovery as a catalyst for scientific discovery, bridging a gap between fields of research and the basic and clinical sciences. Citation Format: Daniel L. Shaw, Charles Y. Lin, Richard P. Oakley, Nicholas P. Semenkovich, Jun Qi, James E. Bradner. Open innovation drug discovery: A study in JQ1. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-2. doi:10.1158/1538-7445.AM2013-LB-2

Inbound open innovation for enhanced performance: Enablers and opportunities

Open innovation, defined as a firm's purposive pursuit and integration of external inputs for new product development, offers an alternative perspective on innovation. Drawing on resource-based and capability theories, this study identifies key factors that enable inbound open innovation and increase its efficacy in a business-to-business context. Because open innovation relies on external connections, relational capability—that is, the firm's ability to make and manage relationships with other firms—should enhance the effects of inbound open innovation on firm performance. Two key resources may further enhance the moderating effects of relational capability: network spillovers that indicate knowledge-rich surroundings, and flexibility that allows for responsiveness and adaptability. The authors test these relationships with data from managers in 204 business-to-business high-tech firms, as well as secondary data pertaining to firm performance and flexibility. The results support the expectations that the ability to build interfirm relationships in a knowledge-rich environment increase the efficacy of inbound open innovation for gaining superior financial performance. Interestingly, additional analyses suggest an unexpected nonlinear interaction effect with flexibility. When firms possess strong relational capabilities and adopt an open innovation approach, they achieve higher financial performance if they have a low or a high level of flexibility. The theoretical and managerial implications of these findings are discussed.

The Role of Internal Coupling Activities in Explaining the Effectiveness of Open Innovation

This paper investigates the role of internal contingencies in explaining performance implications of open innovation by addressing the questions: does openness drive innovation performance? And if so, what organizational activities impact the effectiveness of both the inbound and the outbound approaches to openness? The empirical basis of the study is a survey carried out in 321 Danish SMEs in manufacturing industries. The paper finds limited evidence of the direct effects of inbound and outbound open innovation on performance, as measured in terms of innovative output and profitability. It also finds that the effect of openness is mediated by the use of internal coupling activities that give employees latitude, information and skills to work autonomously. A key result is that the benefits of open innovation are fully captured only when firms adopt a number of activities that provide employees with autonomy and empowerment to conduct their work. The paper concludes with implications to theory and practice.

개방형 혁신과 흡수역량의 공진화 : 한국 중소기업의 혁신경로 관점

This study examines the co-evolutionary process between open innovation and firms' absorptive capacity. The effects of open innovation can be maximized through the capacity to absorb the knowledge from the external sources such as universities, government-support research institute, and private R&D centers. This study used data of STEPI technology innovation survey conducted at 2002, 2005, and 2008 (3 points measures). The data were analyzed through a structural equation model. Results suggest that open innovation at t0 point influences positively the absorptive capacity at t1 point, which subsequently enhances the intention of open innovation at t2 point. This result suggests the existence of co-evolutionary process between open innovation and firms' absorptive capacity. When knowledge comes from universities, the co-evolution has sustained; whereas when knowledge comes from private firms' R&D centers, the co-evolution has not effected. Theoretical and practical implications are discussed.

Extending open innovation throughout the value chain by small and medium-sized manufacturers

This study assesses the adoption of open innovation practices during different value chain activities and measures its effect on product and process innovation. Based on a quantitative survey of 293 US small and medium-sized manufacturing companies the empirical research results suggest a broad use of open innovation practices with customers and suppliers throughout the firm’s value chain. Strong interrelationships between open innovation practices along with the varied impact of open innovation practices on product and process innovation performance are presented and discussed. Overall, the study expands the understanding of open innovation beyond its traditional research and development focus, and highlights the importance of a stronger focus on selection of practices and partners for the effectiveness of open innovation.

Open Innovation - A Gold Mine or Fool’s Gold for Young Firms?

Executives often cite innovation as the critical capability necessary for their company’s growth and success. Open innovation has been heralded as an important approach for the acceleration of the innovation process, especially for large, established firms. The impact of open innovation practices of young firms, whose resources and capabilities differ significantly from those of more mature firms, has been left nearly unexplored. In addition, the quantitative analysis of the effects of open innovation on firm performance is scarce. While size comparisons are important, age-specific factors are potentially more influential on the outcomes of open innovation activities. Thus, this research seeks to compare different open innovation activities of young verses established firms, and explore their effects on innovation and financial performance. The analysis of survey-based data from 1,202 UK firms across multiple sectors shows that established firms engage more strongly in inbound activities while young firms are significantly more active in knowledge and technology transfer (outbound activities). However, these preferences are not always fruitful as only selected open innovation activities are beneficial for young and established firms. Different open innovation activities are relevant for different types of performance. This research contributes to theory and practice by questioning the generalizability of the open innovation concept and highlighting activity and age-specific factors that trigger the variability in the effect of open innovation activities on different types of firm performance.

The Effect of Open Innovation and Organizational Learning on Technological Competitive Advantage in Venture Business

The Effect of Open Innovation and Organizational Learning on Technological Competitive Advantage in Venture Business

Distributed Innovation and Evolution of the Market Using Agent-Based Modeling

Distributed innovation in the form of open- and user innovation affects the evolution of the market. This paper presents an agent-based model where the agents are users and firms that both seek to reap the benefits of innovation. We use this model to examine the interaction between firms and users, and provide a better theoretical understanding of the effects of open and user innovation on firm R&D as well as the resulting changes on the innovation ecosystem. Also important will be to look at the changes in social welfare, as distributed innovation is becoming increasingly important.