Knowledge transfer versus good society of the second La Belle Epoque

Współcześnie nastała „druga” la belle epoque charakteryzująca się ogromnymi nierównościami ekonomiczno-społecznymi. Dążenie do osiągnięcia stanu dobrego społeczeństwa celuje w niwelowanie nierówności, uwarunkowanych dostępem do wiedzy, a jednym ze sposobów może być świadome kształtowanie transferu wiedzy między poszczególnymi grupami agentów wiedzy, reprezentującymi zróżnicowane, często nakładające się, kategorie społeczne i organizacyjne. Celem opracowania jest sprawdzenie, jakie subprocesy transferu wiedzy, w których grupach agentów wiedzy są realizowane i jaki jest ich kontekst z perspektywy stosowanych narzędzi, głównych zasad oraz standardów zachowań. Główna hipoteza badawcza to przypuszczenie, że przebieg procesu transferu wiedzy uzależniony jest od tego, których grup agentów wiedzy dotyczy. Wykorzystując metodę analizy krytycznej oraz badania ankietowe wsparte wywiadami pogłębionymi, ustalono, że dzielenie się wiedzą to domena profesjonalistów oraz wymiaru międzypokoleniowego transferu wiedzy. Pozyskiwanie wiedzy jest najczęściej realizowane na poziomie relacji specjalistów z innymi pracownikami oraz międzypokoleniowym. Udostępnianie wiedzy, jest strefą specjalistów i dokonuje się zazwyczaj podczas ich kontaktów z innymi pracownikami a rozpowszechnianie wiedzy to naczelny subproces hierarchicznego wymiaru transferu wiedzy.Currently, we are witnessing the second la belle epoque characterised by huge economic and social inequalities. Striving for a good state of society aims to reduce the inequalities conditioned by access to knowledge. One of the methods to reach this goal can consist of the conscious shaping of knowledge transfer between particular groups of knowledge agents. representing diverse, often overlapping, social and organisational categories. The purpose of this study is to check what sub-processes of knowledge transfer are implemented in specific groups of knowledge agents and what their context is from the perspective of the tools used, the main principles and the standards of behaviour. The main research hypothesis is that the course of knowledge transfer process depends on the fact of which groups of knowledge agents it concerns. Using the method of critical analysis and surveys supported by in-depth interviews, it was determined that knowledge sharing is the domain of professionals and the intergenerational dimension of knowledge transfer. Knowledge acquisition is most often carried out at the level of specialists' relations with other employees and at the intergenerational level. Knowledge sharing is a domain of specialists, and usually takes place during their contacts with other employees, while knowledge dissemination is the prime sub-process of the hierarchical dimension of knowledge transfer

Developing a weighted model to measure knowledge diffusion in a tourism destination network

Efficient knowledge transfer enhances tourism destination competitiveness. Multiple factors, however, affect knowledge transfer, making it a complex process to quantify. To address this complexity, we developed a quantitative tool by integrating a diffusion model with the major antecedents of knowledge transfer identified in the knowledge management literature. We applied this model in the Western Australian tourism industry and demonstrated its practicality. The proposed model provides a quantitative tool for destination management organizations to monitor, assess and improve the efficiency of knowledge diffusion within their tourism destinations. Such improved knowledge diffusion is critical in strengthening a destination\u27s innovative capabilities and competitiveness

Exploring the Nature of Resources and Relationships in a Multi-Stakeholder Collaborative Network

Multi-stakeholder collaborative networks (MSCNs) centered around innovative problem solving have become increasingly popular. These collaborations seek to pool the resources of the various stakeholders in order to address their common issue. The importance of the collaboration members’ awareness of one another’s resources is the basis for this study. This study developed a new analytical method in which to quantify the resource awareness of members of an MSCN and how that relates to features of the network. The MSCN that was the focal organization for this study was as STEM Ecosystem. A perceptual framework was built upon literature from diverse areas including community asset mapping, collaborative innovation management, knowledge transfer, and social capital. The following variables were explored: the resource awareness of the members of a STEM ecosystem; the relationship between the resource awareness and the relational social capital of the ecosystem members; and the relationship between the resource awareness and the structural social capital of the ecosystem network. Quantitative data were collected using an electronic survey that was completed by 86 members of the STEM ecosystem. Data from the survey was analyzed using both traditional statistical methods as well as social network analysis methods. Analysis of the data demonstrated some significant findings and directions for further research are included

Can We `Feel' the Temperature of Knowledge? Modelling Scientific Popularity Dynamics via Thermodynamics

Just like everything in the nature, scientific topics flourish and perish. While existing literature well captures article's life-cycle via citation patterns, little is known about how scientific popularity and impact evolves for a specific topic. It would be most intuitive if we could `feel' topic's activity just as we perceive the weather by temperature. Here, we conceive knowledge temperature to quantify topic overall popularity and impact through citation network dynamics. Knowledge temperature includes 2 parts. One part depicts lasting impact by assessing knowledge accumulation with an analogy between topic evolution and isobaric expansion. The other part gauges temporal changes in knowledge structure, an embodiment of short-term popularity, through the rate of entropy change with internal energy, 2 thermodynamic variables approximated via node degree and edge number. Our analysis of representative topics with size ranging from 1000 to over 30000 articles reveals that the key to flourishing is topics' ability in accumulating useful information for future knowledge generation. Topics particularly experience temperature surges when their knowledge structure is altered by influential articles. The spike is especially obvious when there appears a single non-trivial novel research focus or merging in topic structure. Overall, knowledge temperature manifests topics' distinct evolutionary cycles

INTER-ORGANIZATIONAL NETWORKS FOR INNOVATIONS AND SUSTAINABILITY

The present Thesis is structured as a collection of three essays linked by one core idea: contributing to research knowledge on inter-organizational network dynamics in the context of innovation and the promotion of sustainability. In this Thesis, the author takes a systemic perspective and analyses the interactions between diverse groups of stakeholders, aiming to identify and interpret the logic underlying the formation of inter-organizational partnerships to promote innovation and sustainability. The dynamics of inter-organizational networks are influenced by several internal and external factors, such as strategic cooperation with stakeholders, structural changes (such as an R&I policy change), and exogenous shocks (such as COVID-19). The present work’s value is developing research inputs and providing empirical ground and methodological support for innovation management framed by inter-organizational networks and mission-oriented public policy evolution. The present work is divided into three main chapters, and their abstracts are presented below. Finally, the Thesis ends with conclusions that summarize the outputs of the empirical works. CHAPTER 1 An appropriate starting point to comprehend the inter-organizational networks for sustainability is to deepen the research knowledge on stakeholders’ role in sustainable innovation and disentangle the antecedents, management, and potential sustainable innovation outcomes. Using the Scopus database, we collected papers that represent works carried out in the field of sustainable innovation and stakeholders’ involvement in organizational practices for these innovations. Based on the data process selection method, we carry out a literature review of the 59 selected papers. This literature review aims to describe the sustainable innovation phenomena and offer a comprehensive overview of the knowledge produced on the theme to practitioners and policymakers So, this chapter presents an interpretative framework of extant literature and discuss the following questions related to the inter-organizational resource-management of sustainable innovation: (a) with whom to work; (b) when to work; (c) how to work together; (d) what challenges should organizations learn to face. Theoretical and practical business implications of the proposed framework are discussed. CHAPTER 2 This chapter aims to analyze the inter-organizational R&I collaboration network dynamics at a mesoscopic level as a consequence of an external environment change. In particular, the study’s empirical setting is the policy change that occurred when passing from the EU 7th Framework program (FP7) to the HORIZON 2020 program (H2020). This change’s effect on the patterns of evolution of the inter-organizational networks between financed actors is stressed. In such R&I context, inter-organizational networks play a particularly critical role as innovation catalysts. Using a dataset of more than 22,228 unique projects in FP7 and 22,153 in H2020, we constructed two collaboration networks. We apply network analysis as a research instrument to identify and measure the fundamental structural properties of networks. At the mesoscopic level, the resulting communities for both networks have been analyzed and compared. Results show that under a policy change, the Horizon 2020 network becomes more assortative than the FP7 network. Preferential attachment (reach-club phenomenon) between leading R&I institutions is demonstrated within the system. The network is supported by the sporadic participation of (many) new actors. Also, the work outcomes demonstrate three different architectures of inter-organizational connections that can define network dynamics: (i) persistent stability or knowledge concentration, (ii) expansion of clusters or knowledge spread, and (iii) merging effect or knowledge aggregation. With these results, we contribute to organizational and network theories by detecting and identifying structural patterns for innovation links in such a complex system as the EU framework program stressing the policy’s impact on them as a dynamics booster. CHAPTER 3 The last chapter examines the impact of an exogenous shock on an inter-organizational R&I network. We concentrate on healthcare public-private partnerships and investigate the history dependencies within them and how an exogenous shock such as COVID-19 fosters an evolution of the complex R&I network. In total, data of 2087 funded projects (FP7, HORIZON 2020, and Innovative Medicines Initiative) are involved in this study to understand the evolution process(es) these types of networks manifest under emergency conditions. The results demonstrate that the present crisis’s urgency shifts the healthcare sector to test new working paths. Two opposite behaviors of the actors in these networks are observable: (i) highly innovative partnerships and (ii) strong lock-in effects. Additionally, we state that non-EU countries demonstrated strong cooperation and co-creation openness under this exogenous shock. Furthermore, the urgency conditions in COVID-19 push policymakers to demonstrate vital flexibility and adaptability of the EU R&I call to the societal needs. Finally, it is possible to underline that network analysis is a powerful research tool for developing new knowledge regarding R&I cooperation evolution under external factors. Accordingly, this work provides a theoretical and an empirical framework for managing the inter-organizational innovation network based on a dynamic complex system theory perspective (Simon 1996; Sawyer, 2005). In particular, it is possible to mention the newly developed insight capable of describing the network’s dynamics through the meso and micro levels of analysis.The present Thesis is structured as a collection of three essays linked by one core idea: contributing to research knowledge on inter-organizational network dynamics in the context of innovation and the promotion of sustainability. In this Thesis, the author takes a systemic perspective and analyses the interactions between diverse groups of stakeholders, aiming to identify and interpret the logic underlying the formation of inter-organizational partnerships to promote innovation and sustainability. The dynamics of inter-organizational networks are influenced by several internal and external factors, such as strategic cooperation with stakeholders, structural changes (such as an R&I policy change), and exogenous shocks (such as COVID-19). The present work’s value is developing research inputs and providing empirical ground and methodological support for innovation management framed by inter-organizational networks and mission-oriented public policy evolution. The present work is divided into three main chapters, and their abstracts are presented below. Finally, the Thesis ends with conclusions that summarize the outputs of the empirical works. CHAPTER 1 An appropriate starting point to comprehend the inter-organizational networks for sustainability is to deepen the research knowledge on stakeholders’ role in sustainable innovation and disentangle the antecedents, management, and potential sustainable innovation outcomes. Using the Scopus database, we collected papers that represent works carried out in the field of sustainable innovation and stakeholders’ involvement in organizational practices for these innovations. Based on the data process selection method, we carry out a literature review of the 59 selected papers. This literature review aims to describe the sustainable innovation phenomena and offer a comprehensive overview of the knowledge produced on the theme to practitioners and policymakers So, this chapter presents an interpretative framework of extant literature and discuss the following questions related to the inter-organizational resource-management of sustainable innovation: (a) with whom to work; (b) when to work; (c) how to work together; (d) what challenges should organizations learn to face. Theoretical and practical business implications of the proposed framework are discussed. CHAPTER 2 This chapter aims to analyze the inter-organizational R&I collaboration network dynamics at a mesoscopic level as a consequence of an external environment change. In particular, the study’s empirical setting is the policy change that occurred when passing from the EU 7th Framework program (FP7) to the HORIZON 2020 program (H2020). This change’s effect on the patterns of evolution of the inter-organizational networks between financed actors is stressed. In such R&I context, inter-organizational networks play a particularly critical role as innovation catalysts. Using a dataset of more than 22,228 unique projects in FP7 and 22,153 in H2020, we constructed two collaboration networks. We apply network analysis as a research instrument to identify and measure the fundamental structural properties of networks. At the mesoscopic level, the resulting communities for both networks have been analyzed and compared. Results show that under a policy change, the Horizon 2020 network becomes more assortative than the FP7 network. Preferential attachment (reach-club phenomenon) between leading R&I institutions is demonstrated within the system. The network is supported by the sporadic participation of (many) new actors. Also, the work outcomes demonstrate three different architectures of inter-organizational connections that can define network dynamics: (i) persistent stability or knowledge concentration, (ii) expansion of clusters or knowledge spread, and (iii) merging effect or knowledge aggregation. With these results, we contribute to organizational and network theories by detecting and identifying structural patterns for innovation links in such a complex system as the EU framework program stressing the policy’s impact on them as a dynamics booster. CHAPTER 3 The last chapter examines the impact of an exogenous shock on an inter-organizational R&I network. We concentrate on healthcare public-private partnerships and investigate the history dependencies within them and how an exogenous shock such as COVID-19 fosters an evolution of the complex R&I network. In total, data of 2087 funded projects (FP7, HORIZON 2020, and Innovative Medicines Initiative) are involved in this study to understand the evolution process(es) these types of networks manifest under emergency conditions. The results demonstrate that the present crisis’s urgency shifts the healthcare sector to test new working paths. Two opposite behaviors of the actors in these networks are observable: (i) highly innovative partnerships and (ii) strong lock-in effects. Additionally, we state that non-EU countries demonstrated strong cooperation and co-creation openness under this exogenous shock. Furthermore, the urgency conditions in COVID-19 push policymakers to demonstrate vital flexibility and adaptability of the EU R&I call to the societal needs. Finally, it is possible to underline that network analysis is a powerful research tool for developing new knowledge regarding R&I cooperation evolution under external factors. Accordingly, this work provides a theoretical and an empirical framework for managing the inter-organizational innovation network based on a dynamic complex system theory perspective (Simon 1996; Sawyer, 2005). In particular, it is possible to mention the newly developed insight capable of describing the network’s dynamics through the meso and micro levels of analysis

Understanding the Influence of Perceived Usefulness of Evidence Based Interventions and Employee Morale on the Relationship between Participatory Internal Communication and Program Fidelity

Translation of efficacious programs into real-world settings is an important step in ensuring improved public health outcomes. Yet, the process of translating evidence-based interventions (EBIs) according to fidelity is fraught with challenges. Organizational factors, specifically organizational communication, have been shown to influence translation processes. To date, there is limited research on communication processes within public health organizations implementing prevention programs. To address this gap, this study aimed to understand the association between participatory internal communication (PIC) and program fidelity. This study examined the influence of patterns of PIC within the problem-solving context on program fidelity in Departments of Public Health (DPHs) and Community-Based Organizations (CBOs) implementing an evidence-based HIV program (i.e., RESPECT). To provide insight into the relationship between the patterns of PIC and program fidelity, this study examined the influence of key psychological variables such as perceived usefulness of EBIs and employee morale. To this end, this study investigated the relationship between the patterns of PIC, employees’ perceived usefulness of RESPECT, and employee morale. Lastly, this study examined the influence of employees’ perceived usefulness of EBI and employee morale on the relationship between the patterns of PIC and program fidelity. This dissertation study was guided by a conceptual model developed based on existing literature. Semi-structured in-person and telephone interviews were conducted with executive directors, supervisors, and program delivery staff from a national survey of CBOs and DPHs implementing RESPECT (n= 26). 114 organizational personnel were interviewed to identify the degree of PIC, employee morale, and perceived usefulness. The interview data were manually coded to categorize patterns of PIC, employee morale, and perceived usefulness. A qualitative methodological approach including descriptive, magnitude, and causation coding techniques was used to analyze the data. Three general patterns of PIC were reported and identified across the agencies: (1) full-PIC, (2) partial-PIC, and (3) non-PIC. The findings of this study observed a consistent pattern between the various levels of PIC and program fidelity. However, some inconsistent cases (39%) and an outlier were also observed. Of note, the data on employees’ perceived usefulness and morale showed a significant number of cases (73%) that did not fit in the hypothesized model pathway. The findings of this qualitative study show an association between the patterns of PIC and program fidelity. A critical mass effect was observed in partial-PIC agencies with high fidelity, in that fifty percent or more of the program delivery staff in these agencies were involved in problem-solving communication. This finding suggests that achieving a critical mass of program delivery staff within partial-PIC agencies may be sufficient to facilitate the delivery of EBI programs with fidelity. However, program modification may independently influence program fidelity even when full PIC exists within the organization or a critical mass effect has been attained in partial-PIC agencies. In conclusion, public health administrators need to take into account the effect of critical mass on the patterns of PIC in order to facilitate positive program outcomes in translating EBIs into practice. To promote the delivery of EBIs with fidelity, public health practitioners could use information from this study to inform strategies and protocols for improving internal communication practices within their organizations

Knowledge Diffusion in Complex Networks

International audienc

Knowledge diffusion in complex networks

International audienceModern communication networks and social networks are the main tunnels of knowledge diffusion. Knowledge diffusion in complex networks is different from the epidemic‐like information spreading, because individuals are willing to learn and spread knowledge to their friends and the learning process can hardly be achieved in a few conversations. In this paper, we investigate the important issue as what topological structure is suitable for knowledge diffusion. We propose a new knowledge diffusion model, where both learning and forgetting mechanisms are considered. In this model, individuals can play imparter and learner simultaneously. Comparing knowledge diffusion on a series of complex topologies, we observe that the individuals with a large degree can quickly learn more knowledge, who are beneficial to knowledge diffusion. Our results surprisingly reveal that the networks with high degree‐heterogeneity are likely to be suitable for knowledge diffusion. Our finding suggests that enhancing the degree heterogeneity of existing social networks may help to improve the performance of knowledge diffusion. This result is well confirmed by our extensive simulation results. Our model therefore provides a theoretical framework for understanding knowledge diffusion in complex topologies

Knowledge Diffusion in Complex Networks

International audienc