Collaborative Innovation Networks Research Articles

Examining the moderating effect of technology spillovers embedded in the intra- and inter-regional collaborative innovation networks of China

Innovation network formulated by the collaborations between entities (firms, universities and research institutes) facilitates the technology spillovers, which usually act as a key factor that boosts indigenous innovation capability. This study analyzes the collaborative innovation network from both intra- and inter-regional dimensions. We use the Chinese biomedical patent co-inventing data between entities to construct the intra- and inter-regional collaborative innovation networks, and examine how they generate the spillover effect by moderating the relationship between RD In the inter-regional dimension, only the clustering coefficient positively moderates the relationship between R&D personnel and innovation output. Our study is also relevant to policy makers.

Intellectual Property in the Brazilian Agricultural Sector

Intellectual property is a legal device that guarantees the individual or legal entity the protection of their creations, be they products or processes, covering copyright, industrial property and sui generis protection, modality in which the plant variety property rights are included. In this sense, this paper analyzes the intellectual property rights in the Brazilian agricultural sector, through a case study of the Inter-University Network for the Development of the Sugar-Energy Sector (RIDESA), by raising data related to research, development and protection of sugarcane cultivars, designated by the prefix Republic of Brazil (RB). In order to do so, a brief historiography of the evolution of legislation on the subject, the conditions and consequences of Brazil's adherence to international agreements such as “Trade Related Aspects of Intellectual Property Rights” (TRIPS) and the convention of “International Union for the Protection of New Varieties of Plants” (UPOV), as well as, a survey about the emergence and role of RIDESA as a collaborative innovation network was also carried out. As a result, it was possible to conclude that the issue of intellectual property rights on cultivars is multidimensional and suggest the need for creation of functional and consolidated models of knowledge management in collaborative innovation network. Among the elements and factors constituting the crisis in the Brazilian sugar-energy sector, mainly on the basis of the varietal census for the states of the northeast region (especially the state of Alagoas), it was possible to point the importance of RIDESA in the context of overcoming crisis of the sugar-energy sector through innovation.

The Collaborative Improvement and Innovation Network project to drive quality improvement.

The purpose is to describe an approach for improvement using an organized collaborative improvement framework where participants learn, apply, and share improvement ideas supported through a 3-year Organ Procurement Transplant Network (OPTN) project called Collaborative Improvement and Innovation Network (COIIN). The COIIN project, proposed as an alternative approach to monitoring transplant performance, supported collaboration, and improvement in 58 transplant hospitals and partner organ procurement organizations. The aim was to increase transplantation with a focus on increasing the utilization of moderate-to-high (50-100%) Kidney Donor Profile Index (KDPI) kidneys. Preliminary findings show increases in transplant rate and utilization of moderate-to-high KDPI kidneys was achieved in many participating organizations. Preliminary COIIN project results suggest that an improvement approach that supports collaborative improvement can be effective in driving improvement. The COIIN project involved the development of a change package of key interventions for three key areas: waitlist management, organ-offer acceptance, and care coordination. Additionally, a balanced scorecard approach using outcome, process, and relationship measures, was used and effective in driving improvement. The preliminary COIIN outcome and process results suggest that collaborative improvement does drive improvement and was well received in the transplant community. In the video, two of the authors describe the content of the review and present the main topics discussed in the article (http://links.lww.com/MOT/A22).

152. Substance Use Screening, Brief Intervention, And Referral To Treatment (SBIRT) In Pediatric Practice: A Quality Improvement Project In The Maryland Adolescent And Young Adult Health Collaborative Improvement And Innovation Network

The Adolescent and Young Adult Health Collaborative Improvement and Innovation Network (AYAH CoIIN) is a national initiative, composed of states including Maryland, designed to improve adolescent preventive services. The Maryland AYAH CoIIN recognized that there is limited data on how pediatric practices in Maryland have integrated evidence-based practice models. The purpose of this Quality Improvement (QI) project was to evaluate the impact of an SBIRT (Screening, Brief Intervention & Referral to Treatment) training intervention on provider knowledge, confidence, adoption of a validated screen for substance use, delivery of a brief intervention, and screening for associated behaviors such as sexual activity. This project implemented the evidence-based SBIRT model of screening for adolescent substance use using the “CRAFFT” screening tool. A “Plan/Do/Study/Act” approach to QI was utilized. This human subjects’ approved project was conducted in a large 9-provider multidisciplinary pediatric practice serving a diverse patient population with a high Medicaid payer mix in a community with higher than national substance use. Prior to the intervention, no standardized screening tool for substance use was being used. To prepare the intervention, baseline data was collected and the CRAFFT was integrated into the practice’s electronic medical records system to screen for substance use at all well adolescent visits for adolescents aged 13-20 years. The Phase 1 training for providers focused on integration of SBIRT into a busy clinical session, management of positive screens, and referral resources. Phase 2 training reviewed Phase 1 performance, motivational interviewing, and trouble-shooting for the next cycle. Process measures included a pre- and post-Phase 1 provider survey (provider knowledge and comfort with screening/motivational interviewing) and chart review (socio-demographic data, substance use and sexual risk behaviors, service delivery). Data were analyzed using bivariate analyses using SPSS 24. Eighty charts were reviewed (40 pre-training, 40 post-Phase 1), and 9 providers were surveyed. Patients were predominantly white (71%), female (55%), Medicaid-insured (51.3%), with a mean age of 15.7 (STD 2.1). Pre-intervention, 12.5% of adolescents were identified as using substances, and 20% post-intervention. The most commonly used substance was marijuana (11.3%), followed by alcohol (6.3%), tobacco (2.5%), opioids (1.3%), and benzodiazepines (1.3%). From pre-intervention to post, the practice increased their frequency of screening with a validated tool (0% to 67.5%, p<0.001), providing any screening for substance use (85% to 97.5%, p=0.048), and providing a brief intervention (7.5% to 27.5%, p=0.019). From pre- to post-intervention, providers’ confidence improved (58.3% to 78.3%, p=0.005), and providers’ percent correct on the knowledge questions of the survey trended towards improvement (48.2% to 63.9%, p=0.082). Documentation regarding sexual health, a related, but non-targeted screening task, did not significantly improve (72.5% to 85%, p=0.17). Among the 31.5% of patients asked about sexual health, sexual activity was associated with substance use (45% versus 6.8%, p<0.001). Pediatric primary care providers trained in SBIRT and motivational interviewing can improve their screening and management of adolescent substance use. Expansion to pediatric practices in Maryland with a 3rd module focused on the relationship of substance use and sexual behavior is warranted.

Using Infant Mortality Data to Improve Maternal and Child Health Programs: An Application of Statistical Process Control Techniques for Rare Events.

Introduction The infant mortality rate (IMR) in the United States remains higher than most developed countries. To understand this public health issue and support state public health departments in displaying and analyzing data in ways that support learning, states participating in the Collaborative Improvement and Innovation Network to Reduce Infant Mortality (IM CoIIN) created statistical process control (SPC) charts for rare events. Methods State vital records data on live births and infant deaths was used to create U, T and G charts for Kansas and Alaska, two states participating in the IM CoIIN who sought methods to more effectively analyze IMR for subsets of their populations with infrequent number of deaths. The IMR and the number of days and number of births between infant deaths was charted for Kansas Non-Hispanic black population and six Alaska regions for the time periods 2013-2016 and 2011-2016, respectively. Established empirical patterns indicated points of special cause variation. Results The T and G charts for Kansas and G charts for Alaska depict points outside the upper control limit. These points indicate special cause variation and an increased number of days and/or births between deaths at these time periods. Discussion T and G charts offer value in examining rare events, and indicate special causes not detectable by U charts or other more traditional analytic methods. When small numbers make traditional analysis challenging, SPC has potential in the MCH field to better understand potential drivers of improvements in rare outcomes, inform decision making and take interventions to scale.

A strategic alignment model for collaborative open innovation networks

Today, the concept of open innovation and collaborative networks attracts great interest. Many organisations use collaborative networks. The success of the innovation of these networks is restricted to their alignment. Hence, this study aims to propose a strategic alignment model for collaborative open innovation networks. The Luftman strategic alignment framework was used as a reference model and was analysed using qualitative and quantitative approaches. In the qualitative part of the study, the meta-synthesis approach was used to find the factors, and then these factors were placed in proper categories using experts' ideas. Next, in the quantitative part, the chi-square test was used to analyse the hypothesis and the Friedman test was used to prioritize the concepts, dimensions, and categories. Finally, 42 concepts and 16 main categories were identified. Moreover, in addition to the six dimensions of the Luftman model, the research and development dimension was identified as an important dimension.

A strategic alignment model for collaborative open innovation networks

Today, the concept of open innovation and collaborative networks attracts great interest. Many organisations use collaborative networks. The success of the innovation of these networks is restricted to their alignment. Hence, this study aims to propose a strategic alignment model for collaborative open innovation networks. The Luftman strategic alignment framework was used as a reference model and was analysed using qualitative and quantitative approaches. In the qualitative part of the study, the meta-synthesis approach was used to find the factors, and then these factors were placed in proper categories using experts' ideas. Next, in the quantitative part, the chi-square test was used to analyse the hypothesis and the Friedman test was used to prioritise the concepts, dimensions, and categories. Finally, 42 concepts and 16 main categories were identified. Moreover, in addition to the six dimensions of the Luftman model, the research and development dimension was identified as an important dimension.

Analysis of the multi-agent's relationship in collaborative innovation network for science and technology SEMs based on evolutionary game theory

The construction of a collaborative innovation network for the science and technology small and middle enterprises (SMEs) is an attempt to effectively combine the advantages of science and technology SMEs. In this paper, the evolutionary game theory is used to establish the three party game model including the government, science and technology SMEs, and college and research institutions. Then, the interaction mechanism among them is analysed. On the basis of analysing each party's cost and benefit under different strategic portfolios of three parties, the stable strategy of the evolutionary game is derived. The research results show that the government can effectively mobilise the enthusiasm of enterprises and the college and research institutions by setting up reasonable subsidies or fines for them, and could also influence and promote the cooperation relations between enterprises and the college and research institutions.

How gender affects collaborative innovation networks performance: the case of the Dutch fashion industry

How gender affects collaborative innovation networks performance: the case of the Dutch fashion industry

Network processes for collaborative innovation

Collaborative innovation networks represent adequate structures within which to foster members' abilities to interact and cooperate in order to increase the level of knowledge and facilitate access to innovation. These systems show a high potential as the best engines to drive innovation. It is supposed that members take advantage of their participation in these networks by creating and extracting value when performing certain deliberate and purposeful processes. Within this paper, we examine such processes by considering two different network models: hierarchical and heterarchical. The first is the classic single hub organisation, where the orchestration model is deemed more appropriate. The second, the choreography model, is characterised by more than one hub and the power of decision is spread among all partners. The main contribution of this paper is to describe in detail the processes within organisations when they are configured in a heterarchical, instead of hierarchical, manner. Our contribution can be considered as valuable in that it offers support for firms to evaluate and pursue the diverse opportunities offered by such models according to their needs.

How gender affects collaborative innovation networks performance: the case of the Dutch fashion industry

The aim of this paper is to study the use of online social networks by male and female fashion entrepreneurs in order to better understand its structure and how it leads to better collaboration and better performance. In particular, we examine whether gender, diversity, and their combined effects influence the performance of start-ups in the fashion industry. We hypothesise that an entrepreneur's diverse online social network ties, including weak ties and strong ties, have different impacts on performance for male and female entrepreneurs. The data for the study was collected through industry surveys and from Facebook. We used ANOVA to test the direct interaction effects of gender and network diversity. The key finding of this study pertains to the interaction effect of gender and network diversity on the performance of a start-up. In general, start-ups established by male entrepreneurs displayed better performance which can be attributed to the diversity of their online social networks compared to female entrepreneurs.

Analysis of the multi-agent's relationship in collaborative innovation network for science and technology SEMs based on evolutionary game theory

The construction of a collaborative innovation network for the science and technology small and middle enterprises (SMEs) is an attempt to effectively combine the advantages of science and technology SMEs. In this paper, the evolutionary game theory is used to establish the three party game model including the government, science and technology SMEs, and college and research institutions. Then, the interaction mechanism among them is analysed. On the basis of analysing each party's cost and benefit under different strategic portfolios of three parties, the stable strategy of the evolutionary game is derived. The research results show that the government can effectively mobilise the enthusiasm of enterprises and the college and research institutions by setting up reasonable subsidies or fines for them, and could also influence and promote the cooperation relations between enterprises and the college and research institutions.

Network processes for collaborative innovation

Collaborative innovation networks represent adequate structures within which to foster members' abilities to interact and cooperate in order to increase the level of knowledge and facilitate access to innovation. These systems show a high potential as the best engines to drive innovation. It is supposed that members take advantage of their participation in these networks by creating and extracting value when performing certain deliberate and purposeful processes. Within this paper, we examine such processes by considering two different network models: hierarchical and heterarchical. The first is the classic single hub organisation, where the orchestration model is deemed more appropriate. The second, the choreography model, is characterised by more than one hub and the power of decision is spread among all partners. The main contribution of this paper is to describe in detail the processes within organisations when they are configured in a heterarchical, instead of hierarchical, manner. Our contribution can be considered as valuable in that it offers support for firms to evaluate and pursue the diverse opportunities offered by such models according to their needs.

The Evolutionary Game Theoretic Analysis for Sustainable Cooperation Relationship of Collaborative Innovation Network in Strategic Emerging Industries

Strategic emerging industries (SEIs) represent the future direction of industrial developments and are crucial in stimulating the overall and long-term development for economy and society. The government plays a key role in promoting the development of SEIs. This paper, for the first time, investigates the cooperation relationship among innovation members, such as enterprises, universities and research institutes in a collaborative innovation network of strategic emerging industries under government intervention. A three-population evolutionary game theory approach was employed under different scenarios for the government acting as the stakeholder, considering the non-profit, definite fit as well as uncertain profit when incentive and punishment policies are adopted. A novel evolutionary game model of the cooperation relationship among collaborative innovation network members under government’s intervention is established. The results of the simulation experiments show that government’s intervention significantly influences the cooperation relationship between enterprises, universities and research institutes. When the sum of financial incentives and punishments is greater than the total additional cost (TAC), enterprises, universities and research institutes should pay for collaborative innovation. Moreover, government’s financial intervention can effectively promote the cooperation between enterprises, universities and research institutes.

Defining functional roles for research institutions in helix innovation networks

This paper presents an empirically grounded case-based analysis of quadruple helix innovation networks. On the basis of qualitative interviews with representatives of 16 heterogeneous networks, we investigate the functional network roles of 172 actors from the fields of academic research, business, government and society. In this article we focus on universities and research and technology organisations, which face the challenge of having to redefine their functional roles and unique value in the face of increased diversification of knowledge sources within current quadruple helix innovation systems. We delineate both existing and potential future roles for academic actors using a typology of functional roles, and present the challenges research establishments must meet in order to fulfil these roles successfully. Finally, we outline the implications of this analysis for the strategic positioning of research institutions, so as to ensure the future inclusion of their innovative capacity in collaborative innovation networks.

Evolutionary Model and Simulation Research of Collaborative Innovation Network: A Case Study of Artificial Intelligence Industry

Based on integrating the fundamental attribute and the unique property of the collaborative innovation network, this paper establishes a collaborative innovation network model of Artificial Intelligence industry through depicting external stimulus conversion progresses and behaviors of network heterogeneous agents. Heterogeneous agents are the network elements of the model which regards the stimulus response as the evolutionary mechanism. Tencent is one of the largest Internet integrated service providers and one of the Internet companies with the largest number of service users in China, which has also set its sights on the development of the AI industry. Taking Tencent’s patent cooperation network in the field of Artificial Intelligence as an example and using system simulation method, we analyze the evolutionary law of the collaborative innovation network topology structure, the coupling evolution phenomenon of the knowledge and the network topology structure, distinct roles that agents play in the network, and relationship between the agents’ openness and the knowledge flow efficiency. We find the phenomenon of small world emergence more than once through the evolution of collaborative innovation network, whose degrees and reasons are also distinctive. There exists coupling evolution between the technological knowledge and the network structure. The collaborative innovation network is always oriented towards competitive industries. The agents’ openness has an essential influence on the lifting range of the technological knowledge. Strengthening the main position of enterprises in AI technological innovation and enhancing the degree of openness among heterogeneous agents are a powerful guarantee for improving the performance of collaborative innovation.

National Quality Improvement Initiative in Home Visiting Services Improves Breastfeeding Initiation and Duration

ObjectiveTo improve breastfeeding through home visiting. MethodsFrom 2013 to 2016, the Home Visiting Collaborative Improvement and Innovation Network (HV CoIIN) enrolled 15 home visiting agencies serving 1000 families in 7 states. Using the Breakthrough Series Collaborative model, HV CoIIN faculty taught a theory of change and continuous quality improvement (CQI) skills, as well as facilitating opportunities for networked learning. ResultsHV CoIIN improved home visitors’ breastfeeding competencies and use of data to inform practice. Breastfeeding initiation increased from 47% to 61%. Exclusive breastfeeding of 3-month-old babies increased from 10% to 13.5%, and for babies 6 months old it increased from 5% to 8%. ConclusionsHome visiting programs can improve breastfeeding among participants with very low baseline breastfeeding rates. Continuous quality improvement and the Breakthrough Series Collaborative model can be used to improve home visiting services in ways that advance national public health priorities.

Evolution Decision, Drivers and Green Innovation Performance for Collaborative Innovation Center of Ecological Building Materials and Environmental Protection Equipment in Jiangsu Province of China

Faced with the bottlenecks and shortcomings brought about by the resource and environmental issues regarding the sustainable development of the economy and society, green innovation has become an important symbol to measure the sustainable competitive advantage of a country and a region. As an important carrier of green innovation, the evolution process of the collaborative innovation network and its green innovation performance are affected by many factors. Therefore, this paper refines the influencing factors of the formation and evolution of collaborative innovation networks and the evaluation indicators of the green innovation performance by literature analysis. According to the characteristics of each evolutionary influence factor, the relationship governance mechanism, relationship strength, and dominant role are defined as decision factors. The rest are defined as drivers. Then, the Analytic Network Process (ANP) is used to empirically analyze the interaction between network evolution decision, driving factors, and green innovation performance, and the interaction relationship model of decision factors, driving factors, and green innovation performance is obtained. The qualitative simulation algorithm based on qualitative simulation (QSIM) basic theory is used to simulate the evolution of a collaborative innovation network, and find the optimal decision to make the green innovation performance reach its relatively high point. Finally, this paper considers the Collaborative Innovation Center of Ecological Building Materials and Environmental Protection Equipment in Jiangsu Province of China as the research object, focusing on its initial stage of growth and maturity. Combining the theory of QSIM with the actual simulation, according to the different development stages of the Collaborative Innovation Center, this paper provides decisions that can promote the rapid improvement of green innovation performance in three aspects: relationship governance mechanism, relationship strength, and core leadership.

Preliminary Findings From the First Pilot Phase of the Collaborative Innovation and Improvement Network.

Preliminary Findings From the First Pilot Phase of the Collaborative Innovation and Improvement Network.

Digitalisation of Development and Supply Networks: Sequential and Platform-Driven Innovations

We draw from an eight-year dataset of 98 organisational entities involved in pre-competitive innovation networks across the UK pharmaceutical sector. These data map into three networks that are representative of: (i) a product development-led sequential pathway that begins with digitalised product development, followed by digitalisation of supply networks, (ii) a supply network-led sequential pathway that starts with digitalised supply networks, followed by digitalisation of product development, and (iii) a parallel — platform-driven — pathway that enables simultaneous digitalisation of development, production, and supply networks. We draw upon extant literature to assess these network structures along three dimensions — strategic intent, the integrative roles of nodes with high centrality, and innovation performance. We conduct within-case and cross-case analyses to postulate 10 research propositions that compare and contrast modalities for sequential and platform-based digitalisation involving collaborative innovation networks. With sequential development, our propositions are congruent with conventional pathways for mitigating innovation risks through modular moves. On the other hand, we posit that platform-based design rules, rather than modular moves, mitigate the risks for parallel development pathways, and lead to novel development and delivery mechanisms.