Template-Type: ReDIF-Article 1.0 Author-Name: Jin Yan Author-X-Name-First: Jin Author-X-Name-Last: Yan Author-Name: Meng Li Author-X-Name-First: Meng Author-X-Name-Last: Li Author-Name: Xiaoyan Ma Author-X-Name-First: Xiaoyan Author-X-Name-Last: Ma Author-Name: Junmian Wang Author-X-Name-First: Junmian Author-X-Name-Last: Wang Title: Scheduling constraints and implementation in teaching management systems incorporating association rule mining algorithms Abstract: This paper examines class schedules, precautions, and association rule algorithms and builds a more scientific class scheduling system. Data mining technology association rules handle scheduling conflicts. This method extracts efficient negative sequence rules from patterns. Using local utility value and utility confidence, e-HUNSR formalises the problem of efficient negative sequence rules, generates candidate rules and a pruning strategy quickly, designs a data structure to store the necessary information, and proposes an efficient way to compute the antecedent local utility value and a simplified utility value calculation. Association rules and mining are used to solve the scheduling problem. The system can conduct course queries, OSes, and performs well in data mining. After experimental verification, the hybrid method with different scheduling condition criteria obtains 98.12% course selection satisfaction. Rule satisfaction averages 94.98%, and intelligent scheduling system scheduling efficiency is 91.91%. Adding fresh ideas and methods to the intelligent scheduling system increases instructional resources and university scheduling. Smarter university timetable management allocates teaching resources and completes education and teaching plans. Journal: Int. J. of Knowledge-Based Development Pages: 229-248 Issue: 3 Volume: 14 Year: 2024 Keywords: association rules; data mining; scheduling algorithms; scheduling constraints and implementation; teaching management system; incorporating association rule; mining algorithm. File-URL: http://www.inderscience.com/link.php?id=141628 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:3:p:229-248 Template-Type: ReDIF-Article 1.0 Author-Name: Nam Nguyễn Kim Author-X-Name-First: Nam Nguyễn Author-X-Name-Last: Kim Author-Name: Nga Nguyễn Thị Hằng Author-X-Name-First: Nga Nguyễn Thị Author-X-Name-Last: Hằng Title: The relationship between knowledge-oriented leadership, conflict, and knowledge hiding: empirical research in banking Abstract: The aim of this study is to examine the relationship between knowledge-oriented leadership (KOL), conflict, and knowledge-hiding behaviour. Data was collected from employees working in the banking sector. Structural equation modelling (SEM) was used to test the research hypotheses. The results demonstrate the significant role of KOL in reducing task conflict and relationship conflict within the organisation. KOL also helps reduce knowledge-hiding behaviour through the mediating roles of task conflict and relationship conflict. Furthermore, task conflict directly and indirectly affects knowledge-hiding behaviour through the mediating role of relationship conflict. The research findings contribute significantly to both theoretical and practical aspects of knowledge management in the banking sector, within the context of a collectivist culture such as Vietnam. Journal: Int. J. of Knowledge-Based Development Pages: 249-267 Issue: 3 Volume: 14 Year: 2024 Keywords: KOL; knowledge-oriented leadership; relationship conflict; task conflict; knowledge hiding; banking. File-URL: http://www.inderscience.com/link.php?id=141629 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:3:p:249-267 Template-Type: ReDIF-Article 1.0 Author-Name: Özlem Özsoy Author-X-Name-First: Özlem Author-X-Name-Last: Özsoy Author-Name: Metin Gürler Author-X-Name-First: Metin Author-X-Name-Last: Gürler Title: The analysis of the effect of COVID-19 on the innovation capability of the countries to make high-tech exports in Europe Abstract: This study aims to investigate whether the COVID-19 pandemic has breaking points in cases, deaths and vaccinations, as well as whether the pandemic has caused a contraction in the innovation capability of high-tech exporting countries. The test results show that there is a highly positive correlation of 0.842 between normalised European Innovation Scoreboard (EIS) index scores and normalised high-tech exports. The convergence is not high in high-tech exports and innovation capability in EIS countries. It seems that there is divergence for high-tech exports and innovation capability in EU countries. There is a technology creation gap between the member countries. In the manuscript, the breakpoints of COVID-19-related cases, deaths, vaccination and normalised EIS scores and high-tech exports in the country set were analysed and the statistical test results showed that all of the five data series have different results, and it is clear that vaccination has reversed the negative process. Journal: Int. J. of Knowledge-Based Development Pages: 268-289 Issue: 3 Volume: 14 Year: 2024 Keywords: COVID-19 pandemic; economic growth; convergence; high-tech exports; innovation; breakpoints. File-URL: http://www.inderscience.com/link.php?id=141630 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:3:p:268-289 Template-Type: ReDIF-Article 1.0 Author-Name: Morteza Soltani Author-X-Name-First: Morteza Author-X-Name-Last: Soltani Author-Name: Mohammad Ehsan Souri Author-X-Name-First: Mohammad Ehsan Author-X-Name-Last: Souri Author-Name: Bahman Hajipour Author-X-Name-First: Bahman Author-X-Name-Last: Hajipour Author-Name: Hamidreza Yazdani Author-X-Name-First: Hamidreza Author-X-Name-Last: Yazdani Author-Name: Shib Sankar Sana Author-X-Name-First: Shib Sankar Author-X-Name-Last: Sana Title: From mental representation to strategic foresight: a guide to thriving in a VUCA business world Abstract: The purpose of this study is to investigate the relationship between representational complexity and strategic foresight in different volatility, uncertainty, complexity and ambiguity (VUCA) environments. Using the rough set theory, we discovered patterns that indicate the level of representational complexity that leads to better strategic foresight. The findings show that in uncertain and ambiguous environments, simple and less complex representations lead to more useful strategic foresight. However, in complex and volatile environments, complex representations result in more efficacious strategic foresight. This study extends past literature by investigating the previously unstudied relationship between representational complexity and strategic foresight in different contexts. The originality and value of this research lie in its contribution to the understanding of how mental representation can impact the success of strategies in VUCA environments. Journal: Int. J. of Knowledge-Based Development Pages: 314-335 Issue: 3 Volume: 14 Year: 2024 Keywords: managerial cognition; mental representation; rough set theory; strategic decision-making; strategic foresight; VUCA; volatility; uncertainty; complexity and ambiguity. File-URL: http://www.inderscience.com/link.php?id=141631 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:3:p:314-335 Template-Type: ReDIF-Article 1.0 Author-Name: Evgeniya K. Karpunina Author-X-Name-First: Evgeniya K. Author-X-Name-Last: Karpunina Author-Name: Elena A. Yakovleva Author-X-Name-First: Elena A. Author-X-Name-Last: Yakovleva Author-Name: Olga S. Shurupova Author-X-Name-First: Olga S. Author-X-Name-Last: Shurupova Author-Name: Tigran L. Oganesyan Author-X-Name-First: Tigran L. Author-X-Name-Last: Oganesyan Author-Name: Olga N. Gorbunova Author-X-Name-First: Olga N. Author-X-Name-Last: Gorbunova Title: Enhancing BRICS scientific and educational potential as a prerequisite for knowledge-based development and digital leadership Abstract: The paper offers a comprehensive approach to assessing the state of the scientific and educational potential of the Brazil, Russia, India, China and South Africa (BRICS) member countries to determine the possibilities of their advanced development based on knowledge and their achievement of digital leadership. The comparative analysis of the key development indicators allowed the authors to conclude that the BRICS alliance is a real competitive force that is increasing its influence in the global economy, gradually weakening the positions of developed countries. It is proved that by strengthening specific components of scientific and educational potential, the BRICS countries can provide a digital breakthrough in the global economy. The integral indicator of the scientific and educational potential of the BRICS countries has been calculated, as well as the corresponding grouping of countries into 'locomotive countries' and "catching up countries". Tools to strengthen the scientific and educational potential of each selected group of countries as conditions for intensive knowledge-based development and ensuring digital leadership are proposed. Journal: Int. J. of Knowledge-Based Development Pages: 290-313 Issue: 3 Volume: 14 Year: 2024 Keywords: scientific and educational potential; BRICS; Brazil; Russia; India; China and South Africa; knowledge-based development; digital development; global leadership; R%D; locomotive countries; catching up countries. File-URL: http://www.inderscience.com/link.php?id=141632 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:3:p:290-313 Template-Type: ReDIF-Article 1.0 Author-Name: Kirti Dutta Author-X-Name-First: Kirti Author-X-Name-Last: Dutta Author-Name: Guillaume P. Fernandez Author-X-Name-First: Guillaume P. Author-X-Name-Last: Fernandez Author-Name: Bart F. Norré Author-X-Name-First: Bart F. Author-X-Name-Last: Norré Author-Name: Dorota Reykowska Author-X-Name-First: Dorota Author-X-Name-Last: Reykowska Author-Name: Rafal Ohme Author-X-Name-First: Rafal Author-X-Name-Last: Ohme Author-Name: Dunia Harajli Author-X-Name-First: Dunia Author-X-Name-Last: Harajli Author-Name: Joaquin Fernandez Author-X-Name-First: Joaquin Author-X-Name-Last: Fernandez Title: Knowledge of declared behaviour: effect of attitude and intention Abstract: Human behaviour is challenging to explain, and testing times like COVID-19 add another layer of complexity. Based on the theory of planned behaviour (TPB), the current paper traces a path model to understand how declared behaviour was impacted during the pandemic in Germany and Sweden. This study applies response time testing (RTT), which reduces the cognitive biases of self-reporting-based surveys. Results show that attitude and intentions form central elements impacting declared behaviour. Perceived threat has a high impact on declared behaviour, both directly and indirectly via attitude. Thus, political decision-makers need to take attitude into account when designing effective communication to influence behaviour. Journal: Int. J. of Knowledge-Based Development Pages: 133-161 Issue: 2 Volume: 14 Year: 2024 Keywords: TPB; theory of planned behaviour; COVID-19; Germany; Sweden; attitude; intentions. File-URL: http://www.inderscience.com/link.php?id=139361 File-Format: text/html File-Restriction: Open Access Handle: RePEc:ids:ijkbde:v:14:y:2024:i:2:p:133-161 Template-Type: ReDIF-Article 1.0 Author-Name: Johnny C. Chaanine Author-X-Name-First: Johnny C. Author-X-Name-Last: Chaanine Title: Examining the influence of social media in the AI era on employees' performance management in the Lebanese context: an empirical analysis Abstract: The rise of social media use in the workplace has become a major concern for managers. While employees may find social media to be a useful tool for communication, it can also lead to distractions and decreased productivity. Managers must balance their desire to limit social media use with their employees' need to stay connected and engaged. The study investigates how the purpose, type, and rate of social media use impact employees' performance at work. Preliminary results suggest that social media use can have a negative effect on employee performance, but the extent of this impact remains to be seen. It's possible that younger workers who are more comfortable with social media and mobile technology will be better equipped to navigate these challenges and maintain their productivity. Ultimately, managers must carefully consider the impact of social media and develop strategies that balance the benefits of connectivity with the need for productivity. Journal: Int. J. of Knowledge-Based Development Pages: 206-225 Issue: 2 Volume: 14 Year: 2024 Keywords: social media; networking; technology; employee's performance; social media usage; social media; use at work; usage rate; SEM. File-URL: http://www.inderscience.com/link.php?id=139363 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:2:p:206-225 Template-Type: ReDIF-Article 1.0 Author-Name: Murat Avci Author-X-Name-First: Murat Author-X-Name-Last: Avci Author-Name: Serhat Burmaoglu Author-X-Name-First: Serhat Author-X-Name-Last: Burmaoglu Author-Name: Azamat Maksudunov Author-X-Name-First: Azamat Author-X-Name-Last: Maksudunov Title: A transition pathway proposal based on the development context for entrepreneurial university transformation Abstract: In a knowledge economy era, universities have been significant in their knowledge generation role. To provide this role, universities transform themselves by improving their research infrastructure, creating an entrepreneurial ecosystem, and educating students with an applied perspective. There are many review studies on entrepreneurial universities in literature but they are lacking in proposing a transition pathway for higher education institutions in different national development contexts. Therefore, in this study, we aim to explore the cognitive background of entrepreneurial university (EPU) concepts and, based on our findings, propose a transition pathway for higher education institutions by considering different national development contexts. Document citation analysis is applied for understanding the cognitive background of the concept and literature review, and the findings of document citation analysis shed light on while proposing a transition pathway. Journal: Int. J. of Knowledge-Based Development Pages: 162-188 Issue: 2 Volume: 14 Year: 2024 Keywords: EPU; entrepreneurial university; document citation analysis; citation analysis; higher education; transition pathway. File-URL: http://www.inderscience.com/link.php?id=139365 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:2:p:162-188 Template-Type: ReDIF-Article 1.0 Author-Name: Paulo Sergio Altman Ferreira Author-X-Name-First: Paulo Sergio Altman Author-X-Name-Last: Ferreira Title: A knowledge-based view on value co-creation: a cultural-historical activity theory perspective on the development of supplier-customer interactions Abstract: The present research explores cultural-historical activity theory as an approach to expand our current understandings of a knowledge-based view of value co-creation developments. Through the lens of cultural-historical activity theory, this study provides a framework explaining the view of knowing and learning as integral to the managerial practice of value co-creation. By means of an ethnographic case study strategy and using developmental work research tenets, the results of fieldwork describe how knowledge, learning and managing intertwine and transform supplier-customer interactions for co-creating value. Ultimately, this work proposes that value co-creation is a managerial journey of supplier-customer relations to the zone of proximal development through knowledge development of communicating in multi-voiced activity systems, learning the application of novel concepts, roles and relations, and managing multiple perspectives of value. Journal: Int. J. of Knowledge-Based Development Pages: 115-132 Issue: 2 Volume: 14 Year: 2024 Keywords: value co-creation; knowledge; learning; cultural-historical activity theory; inter-organisational process. File-URL: http://www.inderscience.com/link.php?id=139366 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:2:p:115-132 Template-Type: ReDIF-Article 1.0 Author-Name: Manping Niu Author-X-Name-First: Manping Author-X-Name-Last: Niu Title: Exploring the impact of international trade practices on social, economic, and environmental development with the intervening influence of government policies Abstract: International trade practices (ITP) play a pivotal role in sustainable development by facilitating the exchange of eco-friendly technologies, promoting responsible resource utilisation, and enhancing global cooperation. ITPs enable nations to achieve economic growth while addressing environmental and social concerns by fostering a harmonious balance between prosperity and the planet. This study specifically examines the nexus of ITP toward companies' sustainable development (SD) from three major perspectives, i.e., social, environmental, and economic streams within the Chinese market, drawing on international trade theory. The outcomes were obtained using a sample of 761 by utilising the structure equation modelling (SEM) method through SmartPls. The findings assured a positive nexus between ITPs and sustainable development, along with the significant correlation of ITP toward each perspective of SD. The study additionally confirmed a positive moderating connection of government policies between ITP and SD. Journal: Int. J. of Knowledge-Based Development Pages: 189-205 Issue: 2 Volume: 14 Year: 2024 Keywords: ITP; international trade practices; sustainable development; SoD; social development; environmental development; EcD; economic development; government policies. File-URL: http://www.inderscience.com/link.php?id=139367 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:2:p:189-205 Template-Type: ReDIF-Article 1.0 Author-Name: Yingying Zhang Author-X-Name-First: Yingying Author-X-Name-Last: Zhang Author-Name: Huiyu Guo Author-X-Name-First: Huiyu Author-X-Name-Last: Guo Title: Research on a recommendation model for sustainable innovative teaching of Chinese as a foreign language based on the data mining algorithm Abstract: With the continuous development of teaching Chinese as a foreign language, more teaching methods are combined with network teaching. However, it is difficult for network teaching methods to find ways that are suitable for different learners from various teaching resources. Therefore, to help learners obtain appropriate teaching methods from the network teaching platform, the research establishes a network teaching recommendation model for Chinese as a foreign language based on the user's interest similarity. Three experimental schemes are designed to verify the effect of the proposed model. The experimental results show that the mean absolute error (MAE) scores of the model in the three schemes are 0.67, 0.7095, and 0.7428, respectively; the RMSE scores are 0.88, 0.9346, and 0.9695, respectively. Thus, the proposed collaborative filtering recommendation algorithm based on user interest similarity migration has good recommendation performance. Journal: Int. J. of Knowledge-Based Development Pages: 1-18 Issue: 1 Volume: 14 Year: 2024 Keywords: data mining; transfer learning; Chinese as a foreign language; teaching innovation; collaborative filtering. File-URL: http://www.inderscience.com/link.php?id=137589 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:1:p:1-18 Template-Type: ReDIF-Article 1.0 Author-Name: Maria Grace Herlina Author-X-Name-First: Maria Grace Author-X-Name-Last: Herlina Author-Name: Karto Iskandar Author-X-Name-First: Karto Author-X-Name-Last: Iskandar Author-Name: Randy Hadipoespito Author-X-Name-First: Randy Author-X-Name-Last: Hadipoespito Title: Digitalised human needs to support intra-organisational knowledge sharing among knowledge workers Abstract: An organisation's success relies more on dynamic knowledge management (KM). A successful knowledge management system is inextricably linked to employee behaviour, namely intra-organisational knowledge sharing. Individual needs significantly influence human behaviour, such as innovation. Most need-based motivation theories make similar assumptions regarding basic needs such as achievement, affiliation, and power. Using the Rasch Model and structural equation modelling (SEM) methodologies, this research transforms human needs into digital form to enhance intra-organisational knowledge sharing among knowledge workers. The study hypothesis employs SEM. It indicates that the need for achievement, affiliation, and power influence knowledge sharing significantly, with the strongest significant influence being the need for power. Various information and communication technology (ICT) tools have recently been developed based on web, mobile, and desktop applications. The study mapped the three categories of motivators based on the appropriate ICT tools for intra-organisational knowledge sharing. Journal: Int. J. of Knowledge-Based Development Pages: 19-38 Issue: 1 Volume: 14 Year: 2024 Keywords: knowledge worker; need of achievement; need of affiliation; need of power; information communications technology; motivation; David C. McClelland needs theory; Rasch model; person map. File-URL: http://www.inderscience.com/link.php?id=137591 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:1:p:19-38 Template-Type: ReDIF-Article 1.0 Author-Name: Xin Yan Author-X-Name-First: Xin Author-X-Name-Last: Yan Author-Name: Jianlei Han Author-X-Name-First: Jianlei Author-X-Name-Last: Han Title: FOA-ESN in tourism demand forecasting from the perspective of sustainable development Abstract: Nowadays, the tourism industry has made significant contributions to the national economy, and accurately predicting tourism demand is a necessary step to promote the rational allocation of tourism resources and sustainable development. Echo state network (ESN) is an algorithmic model that can effectively handle nonlinear problems. This study first adaptively adjusts the fruit fly optimisation algorithm (FOA) method and obtains the improved fruit fly optimisation algorithm (IFOA). Then, integrate IFOA with ESN (IFOA-ESN). IFOA-ESN mainly utilises IFOA to obtain key parameters of ESN, improving the overall performance. Finally, the simulation results of IFOA-ESN on tourism demand show that the average absolute percentage error (MAPE) and normalised root mean square error (NRMSE) values of IFOA-ESN are 0.40% and 0.61%, respectively, and their prediction accuracy is higher than other models. The predicted results obtained can serve as a reference for resource allocation and related policy decisions in the tourism industry. Journal: Int. J. of Knowledge-Based Development Pages: 39-56 Issue: 1 Volume: 14 Year: 2024 Keywords: FOA; fly optimisation algorithm; ESN; echo state networks; tourism demand forecast; tourism sustainable development. File-URL: http://www.inderscience.com/link.php?id=137593 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:1:p:39-56 Template-Type: ReDIF-Article 1.0 Author-Name: Victor Cabral Author-X-Name-First: Victor Author-X-Name-Last: Cabral Author-Name: Willem van Winden Author-X-Name-First: Willem van Author-X-Name-Last: Winden Title: Exploring the coworking space as an innovation intermediary: a case study in Amsterdam Abstract: This qualitative study investigates the role of coworking spaces as innovation intermediaries, focusing on a specific case study in Amsterdam. We introduce a comprehensive framework that integrates five key coworking space units and delineates three primary innovation intermediary roles: facilitation, configuring, and brokering. Our research underscores the significance of both online and offline managerial interventions that stimulate social interaction, content configuration by staff and community members, active brokering through community managers, and formal/informal events. These strategic interventions collectively enhance information flows and knowledge exchange among entrepreneurs. This study contributes valuable insights into the mechanisms through which coworking spaces facilitate innovation intermediation in support of entrepreneurial endeavours. Journal: Int. J. of Knowledge-Based Development Pages: 87-111 Issue: 1 Volume: 14 Year: 2024 Keywords: innovation intermediary; coworking spaces; entrepreneurs; social networks; managerial interventions; knowledge exchange; knowledge sharing. File-URL: http://www.inderscience.com/link.php?id=137599 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:1:p:87-111 Template-Type: ReDIF-Article 1.0 Author-Name: A. Kalai Selvan Author-X-Name-First: A. Kalai Author-X-Name-Last: Selvan Author-Name: N. Sivakumaran Author-X-Name-First: N. Author-X-Name-Last: Sivakumaran Title: Crime detection and crime hot spot prediction using the BI-LSTM deep learning model Abstract: Crime is defined as any act that is illegal and causes unpredictable discomfort to the common public by affecting quality of life and causing financial loss. The objective of this research work is to develop algorithms to predict crime using machine learning (ML) techniques in emotion data and predict future crime spots using crime incident data using deep learning (DL), then cross-check whether the future crime incidents match with the results of crime incidents detected. Voice-based emotion data is analysed using ML algorithms to detect crimes and crime incident data, includes audio and/or video captured from the scene of a crime with geographic coordinates, place names and timestamps are analysed using DL methods such as convolutional stacked bidirectional long short-term memory (LSTM). Crime detection using ML models provided an accuracy of 97.2% for ensemble classifiers and DL methods achieved an accuracy of 95.64% in crime hot spot forecasting. Journal: Int. J. of Knowledge-Based Development Pages: 57-86 Issue: 1 Volume: 14 Year: 2024 Keywords: crime forecast; deep learning; machine learning; LSTM; long short-term memory; convolutional neural network; multiplicative attention. File-URL: http://www.inderscience.com/link.php?id=137600 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:14:y:2024:i:1:p:57-86