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on Knowledge Management and Knowledge Economy |
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Issue of 2025–01–20
ten papers chosen by Laura Nicola-Gavrila, Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Berliant, Marcus; Fujita, Masahisa |
| Abstract: | Knowledge creation either in isolation or joint with another person, using either face to face or internet contact and incorporating internet search ability is analyzed. Both a conceptual phase and a technical phase of research are analyzed, allowing workers to choose endogenously their mode of communication. In addition to formal knowledge, tacit knowledge plays an essential role in the knowledge production process. Lead time for face to face communication plays a key role in the optimal choice of communication mode. The sink point is inefficient. Our framework is applied to pandemic restrictions on face to face communication. |
| Keywords: | Knowledge creation; Tacit knowledge; Multimodal communication; Pandemic restrictions |
| JEL: | D83 L86 |
| Date: | 2024–12–09 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:122940 |
| By: | Jun Cui |
| Abstract: | Drawing upon Resource-Based Theory (RBT) and the Knowledge-Based View (KBV), this study investigates the impact of Knowledge-Based Organizational Support (KOS), AI-Driven Knowledge Sharing (KS), Organizational Learning (OL), and Knowledge Management Dynamic Capabilities (KMDC) on Organizational Performance (OP) in Chinese firms. In particular, this research explores the relationships among these factors, alongside control variables such as education level, staff skills, and technological innovation, to provide a comprehensive understanding of their influence on performance management. While recent studies on organizational performance have predominantly concentrated on digital business strategies and high-level decision-making, limited attention has been given to the role of digital maturity, workplace activities, and communication-related dynamics. This study addresses these gaps by consolidating critical factors that contribute to overarching job performance within organizations. Moreover, to empirically test the proposed hypotheses, data were collected from 129 valid questionnaires completed by employees across various Chinese firms. The research employed confirmatory factor analysis (CFA) to validate the measurement constructs and structural equation modeling (SEM) to evaluate the hypothesized relationships. The findings reveal several significant insights: (1) KOS, KS with AI, KMDC, and OL each have a direct positive effect on OP, emphasizing their critical roles in enhancing organizational outcomes. (2) Control variables, including education level, staff skills, and technological innovation, significantly moderate the relationships between KOS, KS with AI, KMDC, OL, and OP, further amplifying their impact. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2501.02468 |
| By: | Mitsch, Frieder; Hassel, Anke; Soskice, David |
| Abstract: | This paper examines Germany’s distinctive path toward the knowledge economy, emphasizing the role of regional innovation dynamics and governance, with a focus on Southern Germany’s high-innovation clusters. Unlike other advanced economies that pivoted toward high-tech services, Germany has prioritized digital advancements within its manufacturing base, creating a model driven by smart manufacturing and Industry 4.0. We argue that regional growth coalitions, formed by firms, social partners, and local governments, foster institutional configurations supporting knowledge-based and innovation-focused competition. This regionalized governance has enabled Southern Germany to capitalize on Germany’s innovation agenda, a success that other regions have struggled to replicate. By analysing multi-scalar dynamics—interactions across regional, national, and EU levels—our study expands evolutionary economic geography (EEG) and political economy literature, challenging traditional, nation-centric frameworks. Our findings highlight that cohesive regional governance can enhance national and supranational innovation strategies, underscoring the importance of regional institutions in advancing and sustaining knowledge economy innovation. |
| JEL: | N0 R14 J01 |
| Date: | 2024–12–05 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:126264 |
| By: | Flamand, Marina; Frigant, Vincent; Miollan, Stéphane; Dimitrova, Zlatina; Sauve, Henri |
| Abstract: | At the heart of the Technological Innovation Systems (TIS) approach is the knowledge production function. Its evaluation requires the study and characterization of the TIS knowledge base and its evolution. Although patents are often used to study this knowledge production function, current techniques for mobilizing these data can be improved. In this article, we propose to work in two directions. Firstly, most studies focus on a singular knowledge base associated with the focal TIS. However, the knowledge spaces associated with a technology are themselves plural, comprising a variety of constituent elements that must be considered separately. In this way, we have broken down the knowledge base required to develop the focal TIS into different technological building blocks. These building blocks have been classified according to three different levels of analysis: type of technological solution, challenges to be met and field of application. Secondly, most studies measure the knowledge production function by the number of patents applications. However, the sheer volume of patents is a biased indicator. A more comprehensive approach to patent analysis is recommended, based on cross-checking several indicators to ensure the accuracy of patent statistics. From this perspective, we evaluate three sets of patent indicators - persistence, commitment, and coherence - to determine, for each subset, whether there is a sufficient level of knowledge created to promote the development of the TIS. All in all, this article proposes a new method of multi-criteria analysis of the knowledge production function in four stages. The relevance and operability of this method is illustrated in the case of hydrogen storage TIS. |
| Keywords: | Technological Innovation System, Knowledge production, Metrics, Patent, Hydrogen storage technologies |
| JEL: | O31 O33 Q55 |
| Date: | 2024–12–19 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:123050 |
| By: | Schilirò, Daniele |
| Abstract: | This paper aims to analyze the competitive capacity of the Sicilian production system in a region that has historically exhibited a delayed development. It argues, first, that innovation is the most critical driver for fostering competitiveness, as it enhances total factor productivity. Second, investing in knowledge emerges as the optimal strategy to increase the efficiency of production factors and serves as a cornerstone for achieving long-term growth and development. The ability to create and utilize knowledge is fundamental to the competitive advantage of companies and the generation of wealth in the economy. Furthermore, it is argued that institutions must foster competitiveness and growth through a simple, clear, and less bureaucratic regulatory framework. This is particularly crucial in regions that have historically invested significant public resources but achieved relatively modest outcomes in terms of income and employment growth. Specifically, this paper emphasizes the necessity of substantial public investments to strengthen infrastructure, the education and training sector, and research. Equally important are private investments, not only to expand the production base but, more critically, to enhance it qualitatively through new digital technologies, thereby raising the level of total factor productivity. |
| Keywords: | Competitiveness; Sicilian Economy; Productive Districts; Innovation; Knowledge; Institutions. |
| JEL: | O1 O30 R1 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:122879 |
| By: | Manuel Hoffmann; Sam Boysel; Frank Nagle; Sida Peng; Kevin Xu |
| Abstract: | Recent advances in artificial intelligence (AI) technology demonstrate considerable potential to complement human capital intensive activities. While an emerging literature documents wide-ranging productivity effects of AI, relatively little attention has been paid to how AI might change the nature of work itself. How do individuals, especially those in the knowledge economy, adjust how they work when they start using AI? Using the setting of open source software, we study individual level effects that AI has on task allocation. We exploit a natural experiment arising from the deployment of GitHub Copilot, a generative AI code completion tool for software developers. Leveraging millions of work activities over a two year period, we use a program eligibility threshold to investigate the impact of AI technology on the task allocation of software developers within a quasi-experimental regression discontinuity design. We find that having access to Copilot induces such individuals to shift task allocation towards their core work of coding activities and away from non-core project management activities. We identify two underlying mechanisms driving this shift - an increase in autonomous rather than collaborative work, and an increase in exploration activities rather than exploitation. The main effects are greater for individuals with relatively lower ability. Overall, our estimates point towards a large potential for AI to transform work processes and to potentially flatten organizational hierarchies in the knowledge economy. |
| Keywords: | generative artificial intelligence, digital work, open source software, knowledge economy |
| JEL: | H40 O30 J00 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11479 |
| By: | Musibau, Hammed; Vespignani, Joaquin; Yanotti, Maria Belen |
| Abstract: | This paper explores the impact of education quality on economic growth in 37 OECD countries. We developed a new dataset that combines mixed-frequency data, including low-frequency data (every three years) from the Programme for International Student Assessment (PISA) and annual data from the World Development Indicators (WDI), covering the period from 2000 to 2018. Our study investigates the relationship between education quality and economic growth. We found that a 1% increase in educational quality contributes to an annual economic growth rate of 2.8%. This result is significantly higher than previous research, which, based on cross-sectional PISA data, reported growth rates ranging from 0.4% to 2.3%. |
| Keywords: | economic growth, education , PISA data |
| JEL: | E00 I2 O4 |
| Date: | 2024–12–01 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:122859 |
| By: | Samir Mirdasse (Université Ibn Zohr = Ibn Zohr University [Agadir]) |
| Abstract: | Understanding the process of using human resource information systems (HRIS) in organizations is crucial to grasp the associated challenges and opportunities. By analyzing the different dimensions of the use of information systems (IS), it is possible to evaluate their effectiveness and their impact on organizational performance. The central objective of this research is to predict HRIS usage behavior within companies, by integrating a human-organization-technology (HOT-fit) fit framework into the analysis of existing theories. The results obtained made it possible to formulate a conceptual model to anticipate the use of HRIS, taking into account the interactions between human, organizational and technological dimensions. In conclusion, this study consolidates knowledge on the subject and provides practical guidance for its deployment and effective management in companies. This model thus provides a solid basis for the strategic implementation of HRIS, allowing organizations to take full advantage of these technologies to optimize their overall performance and competitive advantage. |
| Abstract: | La compréhension du processus d'utilisation des systèmes d'information des ressources humaines (SIRH) dans les organisations est cruciale pour saisir les défis et opportunités associés. En analysant les différentes dimensions de l'utilisation des systèmes d'information (SI), il est possible d'évaluer leur efficacité et leur impact sur la performance organisationnelle. Cette recherche avait pour objectif central de prévoir le comportement d'utilisation du SIRH au sein des entreprises, en intégrant un cadre d'ajustement humain-organisation-technologie (HOT-fit) dans l'analyse des théories existantes. Les résultats obtenus ont permis de formuler un modèle conceptuel intégratif pour anticiper l'utilisation du SIRH, en tenant compte des interactions entre les dimensions humaines, organisationnelles et technologiques. En conclusion, cette étude consolide les connaissances sur le sujet et fournit des orientations pratiques pour son déploiement et sa gestion efficace dans les entreprises. Ce modèle offre ainsi une base solide pour la mise en œuvre stratégique des SIRH, permettant aux organisations de tirer pleinement parti de ces technologies pour optimiser leur performance globale et leur avantage concurrentiel. |
| Keywords: | HRIS, Forecast, Usage behaviour, Business, Fit (HOT-fit) framework, SIRH, Prévision, Comportement d'utilisation, Entreprise, Cadre d'ajustement (HOT-Fit) |
| Date: | 2024–04–30 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04853850 |
| By: | Jürgen Huber; Michael Kirchler; Teresa Steinbacher |
| Abstract: | In this study we explore the knowledge and beliefs regarding behavioral biases among behavioral scientists, financial professionals, and the general population. We investigate knowledge about ten prominent biases and collect beliefs about the knowledge levels of each of these subject pools by conducting an online survey with 547 participants. We find that knowledge about the selected biases is highest among behavioral scientists and lowest in the general population. Potential explanatory variables, such as age, gender, income, and financial literacy, show almost no impact on knowledge levels. Regarding accuracy of beliefs about knowledge of the own and the other groups, each subject pool has the highest accuracy rates for their own group, and behavioral scientists assessing other behavioral scientists have by far the highest accuracy rate. |
| Keywords: | Behavioral biases, expert beliefs, behavioral scientists, financial professionals. |
| JEL: | C91 G40 G53 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:inn:wpaper:2024-13 |
| By: | Dixon Dumba; Mary W. Muthoga; Partson Paradza; Winnet K. Ngarakana |
| Abstract: | Universities have always been touted as agents of social and economic change as they advance the boundaries of knowledge and propel innovation through research and knowledge transfer. This paper aims to review the different approaches universities use to promote green environments by examining the extent to which green technologies and curricula, and sustainable campuses are embraced within tertiary institutions (Universities) in Botswana. The methodology involved administering a questionnaire to all Universities in Gaborone to elicit responses on efforts to go green. The sample size was determined at a 90% confidence level with a margin (standard) error of 10% using a purposive sampling technique for analysis purposes. The data used in this study was collected using interviews with various key informants (lecturers in the built environment and facilities managers) for the Universities. It was found that some Universities are trying to become green campuses, though none have attained bespoke green campus status yet because of different challenges. Therefore, it is recommended that Universities, as think tanks of the society, should lead by example and become points of reference for the society to benchmark the concept of green and sustainable development. |
| Keywords: | Carbon trading; Education for Sustainable Development (ESD); green campus; sustainability; Sustainable Development |
| JEL: | R3 |
| Date: | 2024–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:afr:wpaper:afres2024-022 |