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on Knowledge Management and Knowledge Economy |
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Issue of 2021‒08‒30
six papers chosen by Laura Ştefănescu Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Ouail Kharraz (UAE, ENCG Tanger -Groupe de recherche "Management & Systèmes d'information"-); Yassine Boussenna (GRMSI - UAE, ENCG Tanger -Groupe de recherche "Management & Systèmes d'information"- - UAE, ENCG Tanger -Groupe de recherche "Management & Systèmes d'information"-) |
| Abstract: | The huge amount of information in our daily life and the continuous work to organize and use it in the best possible way has led to the emergence of knowledge management. This work has two main objectives, first we test the existence of a correlation relationship between the application of knowledge management and organizational performance of Abdelmalek Essaadi University, and secondly, we verify the moderating role of organizational culture on the intensity of this relationship, by collecting the views of the Abdelmalek Essaadi University teacher-researchers, through a hypothetico-deductive reasoning approach and a quantitative working method. Our questionnaire was administered to a representative sample of 88 teacher-researchers from the different institutions of the university under study. The results obtained show a strong correlation between knowledge management and organizational performance. Also, the results confirm the moderating and positive role of organizational culture, on the intensity of the relationship between the application of the K.M and (Training, research, publication, and governance) as indicators of organizational performance retained in this work for the university in question. |
| Keywords: | organizational culture,knowledge management,organizational performance |
| Date: | 2021–07–29 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03312376&r= |
| By: | Andres, Antonio Rodriguez; Otero, Abraham; Amavilah, Voxi Heinrich |
| Abstract: | Missing values and the inconsistency of the measures of the knowledge economy remain vexing problems that hamper policy-making and future research in developing and emerging economies. This paper contributes to the new and evolving literature that seeks to advance better understanding of the importance of the knowledge economy for policy and further research in developing and emerging economies. In this paper we use a supervised machine deep learning neural network (DLNN) approach to predict the knowledge economy index of 71 developing and emerging economies during the 1995-2017 period. Applied in combination with a data imputation procedure based on the K-closest neighbor algorithm, DLNN is capable of handling missing data problems better than alternative methods. A 10-fold validation of the DLNN yielded low quadratic and absolute error (0,382 +- 0,065). The results are robust and efficient, and the model’s predictive power is high. There is a difference in the predictive power when we disaggregate countries in all emerging economies versus emerging Central European countries. We explain this result and leave the rest to future endeavors. Overall, this research has filled in gaps due to missing data thereby allowing for effective policy strategies. At the aggregate level development agencies, including the World Bank that originated the KEI, would benefit from our approach until substitutes come along. |
| Keywords: | Machine deep learning neural networks; developing economies, emerging economies, knowledge economy, knowledge economy index, World Bank |
| JEL: | C45 C53 O38 O41 O57 P41 |
| Date: | 2021–04–15 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:109137&r= |
| By: | Amavilah, Voxi Heinrich; Otero, Abraham; Andres, Antonio Rodriguez |
| Abstract: | Knowledge economy (KE) has been a central issue in the political economic literature of advanced economies, but little research has focused on the transition towards a KE in Africa. Using a latent profile analysis, six clusters of the KE were found in the region. The clusters range from very prepared with good performance in all KE dimensions (institutional, education, and innovation output) to very unprepared with low performance inf each KE dimension. Lastly, we offer policy recommendations that shed some light on the national and international economic policies towards a more knowledge-oriented environment. One such recommendation is that effective policies should consider both the similarities and dissimilarities of African knowledge economies. How precise that can be done is one direction future research can take. |
| Keywords: | Africa, model-based clustering; knowledge economy; cross-country comparisons; exploratory analysis |
| JEL: | C45 O10 O34 O35 O55 P00 P48 |
| Date: | 2021–03–15 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:109188&r= |
| By: | Zouhair El Arhlabi (Université Mohammed V de Rabat [Agdal]) |
| Abstract: | The term human capital is seen as a key element in enhancing an organization's assets. It refers to the set of employees with sustainable competitive advantages that increase the efficiency and performance of their company. Some organizational specialists, such as Henry MINTZBERG or Michel CROZIER, apply the rules of human capital theory to prove their ability to create competition between companies by developing individual human resources. Several studies have studied the role of human capital in the organization and its impact on the company and on the motivation of its staff, in particular those of (PAUL & SUSAN 1996) and (MORIN & AUBE 2007). The present work is therefore a collection of knowledge and previous work aimed at shedding light on this topic. This work indicates that the common index, proving to be crucial at all levels of change management in the organization, is human competence. Those who work in the core center of the organization need to develop higher competencies. It is important that these people have sufficient knowledge, information, innovation, adaptation and creativity to increase customer satisfaction and create a competitive advantage for the organization. |
| Abstract: | Le terme capital humain est considéré comme un élément clé pour améliorer les atouts d'une organisation. Il s'agit de l'ensemble des employés disposant d'avantages concurrentiels durables qui font augmenter l'efficacité et le rendement de leur entreprise. Certains spécialistes de l'organisation, tels que Henry MINTZBERG ou Michel CROZIER, appliquent les règles de la théorie du capital humain pour prouver leur capacité à créer des compétitions entre les entreprises en développant des ressources humaines individuelles. Plusieurs recherches ont étudié le rôle du capital humain dans l'organisation et son impactent sur l'entreprise et sur la motivation de son personnel, notamment celles de (PAUL ET SUSAN 1996) et (MORIN ET AUBE 2007). Le présent travail constitue donc un recueil de connaissances et de travaux précédents visant à éclairer cette thématique. Ces travaux indiquent que l'indice commun, se révélant cruciaux à tous les niveaux de gestion de changement de l'organisation, qui est la compétence humaine. Ceux qui travaillent dans le centre noyau de l'organisation doivent développer des compétences plus élevées. Il importe que ces personnes possèdent suffisamment de connaissances, d'informations, d'innovation, d'adaptation et de créativité pour augmenter la satisfaction du client et créer un avantage concurrentiel pour l'organisation. |
| Keywords: | Human Capital,Organizational Change,Motivation,Competence,Compétence,Changement Organisationnel,Capital Humain |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03312407&r= |
| By: | Ahmad, Abdul-Rahim; Tasadduq, Imran A.; Imam, Muhammad Hasan; Al-Ahmadi, Mohammad Saad; Ahmad, Muhammad Bilal; Tanveer, Muhammad; Mahmood, Haider |
| Abstract: | In the era of knowledge-based decision-making, there is an increasing need for administrators and instructors of engineering degree programs to make informed decisions on the currency, relevancy, and efficacy of instructional efforts. Academic accreditation through ABET provides the best practices and the means to establish the requisite quality improvement processes. Various regulatory and funding agencies for these engineering degree programs also actively call for accreditations. Nevertheless, the tedious, time-consuming, resource-intensive, and knowledge-based nature of these processes and decisions pronounces the need for a knowledge-based tool to intelligently support and automate various pertinent activities. Such activities span from information collection, aggregation, and analysis to decision analysis, support, and monitoring of outcomes. We propose a conceptual framework for researching, designing, and developing such a knowledge-based system. The proposed conceptual framework seeks to automate not only various tedious and complex activities but also facilitate knowledge-based decision analysis/support in continuous quality improvement processes. The focus is on the decisions, processes, and activities related to Course Assessments, Course Learning Outcomes, and Student Outcomes. This framework is expected to deliver systems that promise significant improvement in the efficiency and efficacy of instructors, administrators, and accreditors. |
| Keywords: | Expert Systems; Decision Support Systems; Intelligent Systems; Soft Computing; Academic Accreditation; ABET AccreditationExpert Systems; Decision Support Systems; Intelligent Systems; Soft Computing; Academic Accreditation; ABET Accreditation |
| JEL: | I2 I29 |
| Date: | 2021–08–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:109151&r= |
| By: | Rihn, Alicia; Khachatryan, Hayk; Wei, Xuan |
| Keywords: | Agribusiness, Institutional and Behavioral Economics, Marketing |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea21:312671&r= |