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on Knowledge Management and Knowledge Economy |
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Issue of 2021‒09‒20
six papers chosen by Laura Ştefănescu Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Wioleta Kucharska (Gdansk University of Technology, Gdansk, Poland) |
| Abstract: | Purpose: This study aims to present the overview of intellectual capital creation micro-mechanisms concerning formal and informal knowledge processes. The organizational culture, transformational leadership, and innovativeness are also included in the investigation as ascendants and consequences of the focal relation of intellectual capital and knowledge processes. Method: The empirical model was developed using the structural equation modeling (SEM) method based on a sample of 1,418 Polish knowledge workers employed in the construction, healthcare, higher education (HE), and information technology (IT) industries. Findings: The study exposes that the essence of transformational leadership innovativeness oriented is developing all intellectual capital components. To do so, leaders must support both formal and informal knowledge processes through the organizational culture of knowledge and learning. Furthermore, for best results of the knowledge transformation into intellectual capital, the learning culture must be shaped by both components: learning climate and acceptance of mistakes. Originality: This study presents the "big picture" of all intellectual capital creation micro- mechanisms linking transformational leadership with organizational innovativeness and explains the "knowledge paradox" identified by Mabey and Zhao (2017). This explanation assumes that intellectual capital components are created informally (i.e., human, and relational ones) and formally (i.e., structural ones). Therefore, for best effects, both formal and informal knowledge processes must be supported. Furthermore, this study exposes that the intensity of all explored micro-mechanisms is industry-specific. Implications: Presented findings can be directly applied to organizations to enhance innovativeness. Namely, leaders who observe that the more knowledge is formally managed in their organizations, the less effective the knowledge exchange is - should put more effort into supporting informal knowledge processes to develop human and relational intellectual capital components smoothly. Shortly, leaders need to implement an authentic learning culture, including the mistakes acceptance component, to use the full organizational potential to achieve intellectual capital growth. Intellectual capital growth is essential for innovativeness. |
| Keywords: | learning culture, knowledge culture, transformational leadership, innovations, intellectual capital, tacit knowledge, knowledge processes, healthcare industry, higher education, IT industry, construction industry, gender studies |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:gdk:wpaper:65&r= |
| By: | Colin Wessendorf; Alexander Kopka; Dirk Fornahl |
| Abstract: | The European Commission summarized six young General Purpose Technologies (GPTs) under the label of European Key Enabling Technologies (KETs) in 2009. GPTs are broad, pervasive and widely diffused technologies that enable knowledge creation and economic growth. This study analyzes to what extent the KETs’ structural relevance within their regional knowledge bases leads to regional knowledge creation. Additionally, we analyze whether the structural relevance and the regional knowledge presence in KETs interact with regards to regional knowledge creation. The ‘structure’ of a regional knowledge base describes the relation of all knowledge being present within a given region, while ‘structural relevance’ describes a technology’s impact on the structure. Our analysis focuses on the time period from 1986-2015 and includes Germany’s 141 Labor Market Regions (LMRs) as regional spatial units. Our database consists of patent data from which we map the structure of the regional knowledge bases, by constructing technological spaces based on technology co-occurrences on patents. The structural relevance is operationalized with the help of Social Network Analysis (SNA), by measuring the changes that the removal of KETs causes in the structure of technological spaces. Our findings indicate that KETs enable knowledge creation in different ways. They show that the effects of KETs on regional knowledge creation activities are KET-specific. Furthermore, it proves essential to distinguish between ‘knowledge presence’ and ‘structural knowledge relevance’ when addressing the innovation-spawning function of KETs. Thus, for both further research and for policy-making, it is a fundamental requirement to address KET-driven knowledge creation in particular KET-specific ways. |
| Keywords: | General purpose technologies, GPT, key enabling technologies, KET, regional innovation, regional knowledge base, knowledge space, technological space, technological integration, German regions |
| JEL: | O31 O33 R11 R58 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2127&r= |
| By: | Hélène Dernis (OECD); Laurent Moussiegt (OECD); Daisuke Nawa (OECD); Mariagrazia Squicciarini (OECD) |
| Abstract: | This study proposes an exploratory analysis of the characteristics of Artificial Intelligence (AI) “actors”. It focuses on entities that deploy AI-related technologies or introduce AI-related goods and services on large international markets. It builds on the OECD Science, Technology and Innovation Micro-data Lab infrastructure, and, in particular, on Intellectual Property (IP) rights data (patents and trademarks) combined with company-level data. Statistics on AI-related patents and trademarks show that AI-related activities are strongly concentrated in some countries, sectors, and actors. Development of AI technologies and/or goods and services is mainly due to start-ups or large incumbents, located in the United States, Japan, Korea, or the People’s Republic of China, and, to a lesser extent, in Europe. A majority of these actors operate in ICT-related sectors. The composition of the IP portfolio of the AI actors indicates that AI is frequently combined with a variety of sector-specific technologies, goods, or services. |
| Date: | 2021–09–22 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaac:121-en&r= |
| By: | Martha Orellano (emlyon business school); Christine Lambey-Checchin (CleRMa - Clermont Recherche Management - ESC Clermont-Ferrand - École Supérieure de Commerce (ESC) - Clermont-Ferrand - UCA - Université Clermont Auvergne); Khaled Medini (LIMOS - Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes - Ecole Nationale Supérieure des Mines de St Etienne - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne - INP Clermont Auvergne - Institut national polytechnique Clermont Auvergne - UCA - Université Clermont Auvergne); Gilles Neubert |
| Abstract: | The notion of sustainable innovation (SI) emerged recently in the academic literature and evokes deep changes in organizations' products, processes, and practices to favour the creation of social and environmental value in addition to economic returns. The development of SI implies a collaborative process that requires the orchestration of several actors and streams of knowledge to be successful. Indeed, companies adopting the SI path need structured methodologies to guide the collaboration process with internal and external actors and support the decision process. Nevertheless, the literature has focused on the analysis of determinants and drivers of sustainable innovation development, while the process perspective has been discussed less. Through an in-depth case study in a large-sized company in France, this article proposes a methodological framework to guide the collaborative process in the early phases of sustainable innovation development. The framework relies on a combination of qualitative research and a multicriteria decision aiding method (AHP). The contributions of this work address two main aspects: (i) the conceptualization of sustainable innovation (SI) and (ii) the collaborative process between internal and external actors to develop SI. Firstly, our study leads to two additional dimensions to complete the concept of SI, traditionally based on the three pillars of sustainability (economic, environmental, and social), by adding the functional and relational dimensions. Secondly, concerning the collaborative process to develop SI, our framework proposes a structured methodology following five steps: definition of the project scope, setting actors' motivations, defining satisfaction criteria, proposing SI solutions, and performing a decision-aiding process to define the preference profiles of the key actors. |
| Keywords: | sustainable innovation,customer-driven innovation,collaboration,decision-aiding,case study research |
| Date: | 2021–08–12 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03328101&r= |
| By: | Elie Ndemba Tshilambu (Université protestante au Congo - Université protestante au Congo) |
| Abstract: | L'objectif du présent article est d'analyser le rôle de la fiscalité et mesurer l'effet de celle-ci à travers son impact sur le capital public, dans la croissance économique en République Démocratique du Congo en s'appuyant sur le modèle de croissance endogène de Barro (1990) et à déterminer le taux optimal de pression fiscale à travers l'estimation du modèle de SCULLY. L'interaction entre la fiscalité et la croissance pourrait avoir une allure non linéaire, sous la forme d'une courbe de LAFFER, le test Hansen va servir à montrer l'effet de seuil dans la relation non linéaire entre la pression fiscale et la croissance économique. Un modèle ARDL a été estimé sur la période 1990-2020 pour analyser la dynamique de ces deux variables. Les résultats obtenus vont dans le sens d'une relation croissante entre la fiscalité et la croissance économique en RDC. Ainsi, à travers l'impôt, les ménages contribuent au financement du capital public qui conduit in fine à améliorer la croissance économique. Il en est ressorti de cette étude que les niveaux des composantes fiscales observés n'ont pas été efficients et optimaux par rapport aux taux de croissance économique observés en RDC durant la période 1990-2020. L'estimation du modèle de SCULLY révèle qu'avec un niveau de 23% de pression fiscale, on peut avoir une croissance économique soutenue. |
| Keywords: | Politique Budgétaire,Croissance économique,Pression fiscale Classification JEL : E62,E22,O40,C11 |
| Date: | 2021–04–28 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03210477&r= |
| By: | W. Addessi; M. Delogu |
| Abstract: | In this paper, we study the optimal labor income taxation to finance infrastructure in developing countries characterized by high informality. We show that the presence of labor market segmentation, induced by a binding minimum wage, affects the optimal level of taxation/infrastructure and influences how the economy reacts to policy changes in terms of both the size of the informal sector and the income distribution among high- and low- skilled workers. |
| Keywords: | Infrastructure;Informality;Optimal Taxation;Development |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:cns:cnscwp:202103&r= |