Template-Type: ReDIF-Article 1.0 Author-Name: Vincent Yao Agbodemegbe Author-X-Name-First: Vincent Yao Author-X-Name-Last: Agbodemegbe Author-Name: Adolf Kofi Awua Author-X-Name-First: Adolf Kofi Author-X-Name-Last: Awua Author-Name: George Kofi Appiah Author-X-Name-First: George Kofi Author-X-Name-Last: Appiah Author-Name: Elikem Kwaku Ahialey Author-X-Name-First: Elikem Kwaku Author-X-Name-Last: Ahialey Title: A study of stakeholders' perspectives to inform management of the development of a civil nuclear power program for electricity generation in Ghana Abstract: The renewed interest in the development of the civil nuclear power program in Ghana has since seen the implementation of sensitisation and educative programs aimed at enhancing knowledge and ensuring buy-in. A compendium of activities constituting stakeholder engagement efforts was conducted since the establishment of the Ghana Nuclear Power Programme Organization (GNPPO). A survey was piloted to measure, the perception, knowledge and interest of a section of the Ghanaian society. The results provided indications to expect that the nationwide survey will make evident, the high dependence on the national grid and appreciable interest for additional capacity (mainly solar and nuclear) to the existing electricity generation mix. Although participants are aware of some adverse effects of the power application of nuclear energy, the majority would likely be willing to accept the inclusion of nuclear power in Ghana's electricity generation mix and advocate for that endeavour. Journal: Int. J. of Knowledge-Based Development Pages: 3-22 Issue: 1 Volume: 13 Year: 2023 Keywords: perception; knowledge; interest; nuclear; electricity. File-URL: http://www.inderscience.com/link.php?id=130188 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:1:p:3-22 Template-Type: ReDIF-Article 1.0 Author-Name: Tahir Masood Qureshi Author-X-Name-First: Tahir Masood Author-X-Name-Last: Qureshi Author-Name: Mahwish Sindhu Author-X-Name-First: Mahwish Author-X-Name-Last: Sindhu Author-Name: Sonia Singh Author-X-Name-First: Sonia Author-X-Name-Last: Singh Title: Transformational leadership, organisational rich culture, and sustainability: a mediating role of an inclusive environment Abstract: Workforce diversity is a rising phenomenon that challenges the role of leadership and organisational culture to attain sustainable performance. The study intends to identify and explore the role of transformational leadership and organisational rich culture as the focal predictors of an inclusive environment that can lead to organisational sustainability. Hypotheses in this deductive research study were developed by covering the research gaps identified in the prior studies. Primary data collected from 392 employees associated with service sector organisations was analysed using SPSS 25.0 to test the hypotheses empirically. The findings revealed that transformational leadership and organisational rich culture are the key predictors of organisational inclusive environment and sustainability. However, organisational inclusive environment partially mediates the relationship between transformational leadership, organisational rich culture, and organisational sustainability. The study benefits the corporate leaders, human resource professionals, and organisations opting for an equal employment opportunity (EEO)/diversity/inclusiveness concept. Journal: Int. J. of Knowledge-Based Development Pages: 23-43 Issue: 1 Volume: 13 Year: 2023 Keywords: EEO; equal employment opportunity; diversity; inclusiveness; organisational culture; transformational leadership; human resource management; sustainability. File-URL: http://www.inderscience.com/link.php?id=130189 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:1:p:23-43 Template-Type: ReDIF-Article 1.0 Author-Name: Gelareh Jamshidnezhad Author-X-Name-First: Gelareh Author-X-Name-Last: Jamshidnezhad Author-Name: Marjan Vahedi Author-X-Name-First: Marjan Author-X-Name-Last: Vahedi Author-Name: Alireza Poursaeed Author-X-Name-First: Alireza Author-X-Name-Last: Poursaeed Author-Name: Hamed Chaharsoughi-Amin Author-X-Name-First: Hamed Author-X-Name-Last: Chaharsoughi-Amin Title: A paradigm for the development of knowledge-intensive enterprises: the case of agricultural knowledge-intensive enterprises in west of Iran Abstract: The present research aimed to qualitatively design a paradigm for the development of agricultural knowledge-intensive enterprises in the west of Iran using grounded theory. The research population was composed of chief executive officers (CEOs) of agricultural knowledge-intensive enterprises. Based on the results; the causal conditions are composed of the components of aspirations, scientific mission, policy-legal factors, cultural factors, and self-esteem. The contextual conditions are composed of the components of governmental support, team making, and economic factors. The core category includes gaining competitive advantage and adaptability, and the intervening conditions include personal factors, wisdom-orientation, the existence of R%D culture, and corporate features. The components constituting strategies are managerial and policymaking factors, educational and research activities, platforms and infrastructure, scientific communications and networks, knowledge dissemination, and entrepreneurship. Finally, the development of knowledge-intensive enterprises will have positive consequences from the perspective of science, economy, and the realisation of Iran's 20-Year Vision Document, human, production, and marketing. Journal: Int. J. of Knowledge-Based Development Pages: 44-69 Issue: 1 Volume: 13 Year: 2023 Keywords: agriculture; development; enterprise; infrastructure; economy; knowledge-based; personal factors; cultural factors; policy-legal factors. File-URL: http://www.inderscience.com/link.php?id=130213 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:1:p:44-69 Template-Type: ReDIF-Article 1.0 Author-Name: Jefferson Lopes La Falce Author-X-Name-First: Jefferson Lopes La Author-X-Name-Last: Falce Author-Name: Aline de Paula Martins Author-X-Name-First: Aline de Paula Author-X-Name-Last: Martins Author-Name: Cristiana Fernandes De Muylder Author-X-Name-First: Cristiana Fernandes De Author-X-Name-Last: Muylder Author-Name: Ernst Verwaal Author-X-Name-First: Ernst Author-X-Name-Last: Verwaal Author-Name: Ludmila de Vasconcelos Machado Guimarães Author-X-Name-First: Ludmila de Vasconcelos Machado Author-X-Name-Last: Guimarães Title: The relationship between organisational culture, knowledge sharing, work satisfaction and knowledge management maturity Abstract: The extent knowledge management literature considers the influence of culture on job satisfaction and knowledge behaviour as vital to organisational performance. However, the specific relationships between these variables has not yet been described and empirically verified in a comprehensive model. This study aims to describe the detailed theoretical relationships between organisational culture job satisfaction, knowledge sharing, and knowledge management maturity and tests them empirically in a comprehensive structural equation model. To achieve this research's objective, descriptive, quantitative research was employed with the use of survey data from 306 respondents of a Brazilian public university. The results support our expectation that culture is a mayor driver of the maturity of knowledge and that this relationship is mediated by knowledge sharing and job satisfaction. We also find that culture and job satisfaction influence knowledge sharing with subsequent positive effects on knowledge management maturity. Our findings inform knowledge management theory and practice on the role of culture in enabling better results in knowledge management. Journal: Int. J. of Knowledge-Based Development Pages: 70-93 Issue: 1 Volume: 13 Year: 2023 Keywords: knowledge management maturity; organisational culture; knowledge sharing; job satisfaction; public university; public management; SEM; structural equations modelling; knowledge behaviour. File-URL: http://www.inderscience.com/link.php?id=130220 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:1:p:70-93 Template-Type: ReDIF-Article 1.0 Author-Name: Dan Li Author-X-Name-First: Dan Author-X-Name-Last: Li Title: Intelligent recommendation of educational resources combining Neu-MF and T-S fuzzy control Abstract: The research uses Takagi-Sugeno (T-S) fuzzy control combined with neural matrix factorization (Neu MF) model to study the intelligent recommendation of educational resources. The recommendation performance of TS-Neu MF model is compared with other similar recommendation algorithm models under two test sets of E's dx and C er. The results of the experiments show that the TS-Neu MF model outperforms Deep FM by 56.6% in root mean square error (RMSE) metrics and 71.5% in mean absolute error (MAE) metrics, and outperforms the Neu MF model by 33.1% in RMSE metrics and 22.5% in MAE metrics under the E dx dataset. The training loss is about 0.04 lower than the Deep FM model, about 0.006 lower than the BPNN model, and about 0.02 lower than the Neu MF model. Journal: Int. J. of Knowledge-Based Development Pages: 94-111 Issue: 1 Volume: 13 Year: 2023 Keywords: Neu MF; T-S fuzzy; educational resources; intelligent recommendation. File-URL: http://www.inderscience.com/link.php?id=130221 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:1:p:94-111 Template-Type: ReDIF-Article 1.0 Author-Name: Jia Xu Author-X-Name-First: Jia Author-X-Name-Last: Xu Title: Research on the cultivation of innovative entrepreneurial talents for digital transformation of enterprises based on association rule algorithm Abstract: A talent development framework for enterprises is proposed to address the new requirements for talent development in the digital transformation stage. Through the study of the enterprise employee training framework, an employee data mining based on the improved Apriori association algorithm is proposed to realise the visual analysis of employee work performance. The experimental results show that the improved Apriori correlation algorithm takes 17s to process 7500 things, which is better than the traditional Apriori correlation algorithm. The performance score of employees is negatively correlated with the business volume of the enterprise. There is a problem of delay in the processing of complex work content by employees. And there is a positive correlation between the time and number of online learning and employee quality in talent development. The content of the study has important reference significance for the digital transformation of enterprises and the management of enterprise performance innovation. Journal: Int. J. of Knowledge-Based Development Pages: 113-130 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: association rule algorithm; talent development framework; performance management; enterprise innovation development. File-URL: http://www.inderscience.com/link.php?id=133319 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:113-130 Template-Type: ReDIF-Article 1.0 Author-Name: Jiemin Yin Author-X-Name-First: Jiemin Author-X-Name-Last: Yin Title: The monopoly dilemma of digital platform economy from the perspective of economic law and the influence of innovation incentive mechanism Abstract: This study aims to analyze the monopoly status and regulatory dilemmas of nowadays digital platform economy from the perspective of law and economics. After a series of quantitative analyses, the results show that reductions in capital income taxes have a greater effect on the economic growth of digital platforms than other types of taxes. An increase in capital income taxation intensifies social welfare losses and has the greatest impact from the angle of social welfare losses. The study further explores the impact of changes in the overall tax burden on various aspects of the Chinese economy. Tax revenues are always negatively correlated with endogenous variables in the economy. The higher the tax rate, the lower the value of the endogenous variables. That provides some evidence for the effectiveness to manage the digital platform economy through innovation incentives, especially tax rate controls. Journal: Int. J. of Knowledge-Based Development Pages: 231-247 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: innovation incentive; monopoly; digital platform economy; production function; quantitative evaluation. File-URL: http://www.inderscience.com/link.php?id=133320 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:231-247 Template-Type: ReDIF-Article 1.0 Author-Name: Jing Hu Author-X-Name-First: Jing Author-X-Name-Last: Hu Author-Name: Yu Shu Author-X-Name-First: Yu Author-X-Name-Last: Shu Title: Research on dynamic evaluation method of periodicals from the perspective of time Abstract: [Purpose/Significance]: This paper introduces the time factor to describe the changes of the academic influence of journals, accurately reflect the academic influence of journals in different periods, and eliminate the different influence of publishing time and subordinate disciplines on the academic evaluation of journals. [Method/Process]: Design the dynamic evaluation index TDJI for journals. Take the dynamic development level of global papers as the benchmark, revise the dynamic change trend of academic influence of journals. Then, the number of citations of journals at different time nodes is given different weight coefficients to accurately reveal and describe the development trend of academic influence of journals. [Results/Conclusion]: The empirical results show that TDJI is highly related to the number of citations, influencing factors and standardised evaluation indicators of each paper, which can eliminate the differences in citations caused by different disciplines and highlight the recent performance of journals. Journal: Int. J. of Knowledge-Based Development Pages: 263-277 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: periodical evaluation; time factor; dynamic evaluation; evaluation method; interdisciplinary evaluation; academic influence; evaluation index design; citation difference. File-URL: http://www.inderscience.com/link.php?id=133321 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:263-277 Template-Type: ReDIF-Article 1.0 Author-Name: Anıl Dinç Demirbilek Author-X-Name-First: Anıl Dinç Author-X-Name-Last: Demirbilek Author-Name: Onur Mengi Author-X-Name-First: Onur Author-X-Name-Last: Mengi Title: The use of open design in the fab lab ecosystems: lessons learnt for knowledge management Abstract: In the last decade, the processes of designing have significantly changed through the emergence of digital technologies and manufacturing tools. Particularly, increasing use of digital technologies and tools, reframes fabrication laboratories (fab labs) as vital ecosystems naturally growing their creative capabilities and evolving knowledge management competences through open design. Then, how the open design (OD) is implemented in such ecosystems? What would be the lessons learnt for the knowledge management regarding the OD processes occurring within the fab labs? This study explores the essential drivers for OD through the meta-analyses of the literature. For the case study, the features of fab labs in Türkiye are analysed with regard to capabilities, events and networking components. The findings reveal three essential drivers that enable OD in fabrication processes, namely open fabrication, co-creation and open service. The paper also provides a framework for knowledge management for the implementation of OD within fab lab ecosystems. Journal: Int. J. of Knowledge-Based Development Pages: 278-293 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: open design; co-creation; open fabrication; open service; fab labs; fab lab ecosystem; knowledge management. File-URL: http://www.inderscience.com/link.php?id=133322 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:278-293 Template-Type: ReDIF-Article 1.0 Author-Name: Shimian Zhang Author-X-Name-First: Shimian Author-X-Name-Last: Zhang Author-Name: Qingqing Li Author-X-Name-First: Qingqing Author-X-Name-Last: Li Title: Research on the analysis of regional economic sustainable development trend based on decision tree classification prediction Abstract: As China's economic development shifts from the stage of high growth to the stage of high quality development, the methods for regional economic sustainable development trend analysis and prediction become increasingly important. In this study, we propose the optimised TGC4.5, SDC4.5 and SGC4.5 models based on decision tree classification and forecasting C4.5 algorithm, combining Taylor series, GINI index, sequence pairs and dynamic time programming, and optimise the data indicators for regional economic sustainability development trend. The experimental results show that the optimised SDC4.5 optimisation algorithm outperforms C4.5 algorithm in modelling speed, with 8 outperforming C4.5 algorithm and 1 tied in the selected 15 dataset experiments. It outperforms C4.5 algorithm in classification accuracy, with 13 outperforming C4.5 algorithm in the selected 15 dataset experiments. The SDC4.5 algorithm model is faster and more accurate as the decision tree depth increases. Journal: Int. J. of Knowledge-Based Development Pages: 131-147 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: regional economy; decision tree; C4.5; sustainable development; trend analysis. File-URL: http://www.inderscience.com/link.php?id=133323 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:131-147 Template-Type: ReDIF-Article 1.0 Author-Name: Bo Yu Author-X-Name-First: Bo Author-X-Name-Last: Yu Title: Modern training model of apprenticeship based on multi-objective optimisation algorithm for sustainable development of school-enterprise cooperation Abstract: With the transformation of vocational education talent training mode to 'modern apprenticeship', this study proposes a 'modern apprenticeship' talent training mode based on multi-objective optimisation algorithm under the sustainable development of school enterprise cooperation. First of all, a talent training model based on pyramid structure is constructed to allocate different talents to different tower floors. Then optimise the model, combined with external storage and fitness function, propose a multi-objective optimisation algorithm based on pyramid structure. Experiments on the algorithm model show that the solution of the improved algorithm model under the prediction function is more uniform and stable in the target space, and the convergence speed of the model is faster. Applying the optimised algorithm model to the individual promotion and function distribution of 'modern apprenticeship' talents under the school enterprise cooperation can further promote the development of modern apprenticeship and provide guarantee for enterprises to accurately transport high-quality talents. Journal: Int. J. of Knowledge-Based Development Pages: 164-180 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: multi-objective; modern apprenticeship; talent training strategy; school-enterprise cooperation; sustainable development; talent structure; intelligent algorithm; Pareto optimal solution. File-URL: http://www.inderscience.com/link.php?id=133324 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:164-180 Template-Type: ReDIF-Article 1.0 Author-Name: Bin Sun Author-X-Name-First: Bin Author-X-Name-Last: Sun Title: Research on the application of improved BPNN algorithm in music education quality evaluation algorithm Abstract: The objective, fair, accurate and reasonable evaluation of teaching quality is the premise to improve the teaching quality of colleges and universities. In this study, based on the traditional BP neural network and the adaptive mutation genetic algorithm, a BP neural network music teaching quality evaluation model with improved adaptive genetic algorithm is proposed. The performance of this model is compared with that of the traditional BP neural network model. The experimental results show that the mean square error sum of the final convergence of the proposed model is 0.15, the convergence speed is increased by 89%, and the mean square error sum is reduced by 75%; After the 21st iteration, the convergence is completed and reaches a stable state. Combined with the above model comparison data and prediction results, it shows that the model can well complete the teaching evaluation prediction. Journal: Int. J. of Knowledge-Based Development Pages: 214-230 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: BP; Music teaching; evaluation model; teaching quality; genetic algorithm; self-adaption; college education. File-URL: http://www.inderscience.com/link.php?id=133325 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:214-230 Template-Type: ReDIF-Article 1.0 Author-Name: Wenfang Li Author-X-Name-First: Wenfang Author-X-Name-Last: Li Title: A study on the evaluation of humanistic literacy cultivation model of University English teaching based on MTCNN Abstract: To give consideration to the speed and accuracy of evaluation and reduce the experimental cost and the error caused by human operation in evaluating humanistic literacy cultivation for University English teaching, an evaluation model based on MTCNN is proposed. On the basis of CNN, AMTL is used as the main tool to adjust the adaptability of different types of subtask loss in the training process, and auxiliary tasks are introduced to iterate the evaluation model to judge the loss function and the weight change of subtasks. Determine the weight value a0 = 0.297 of the method proposed in the study. This result is more accurate than the optimal weight 0.3 obtained by the traditional MTCNN. The accuracy, sensitivity and specificity values of the proposed method are 69.83, 64.94 and 72.79, respectively, which are higher than those of other methods and have good accuracy, sensitivity and specificity. It indicates that the method can mine the information of evaluation indexes and help cultivate all-round development college students. Journal: Int. J. of Knowledge-Based Development Pages: 148-163 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: multitasking; convolutional neural networks; humanistic literacy; nurturing models; evaluation models. File-URL: http://www.inderscience.com/link.php?id=133326 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:148-163 Template-Type: ReDIF-Article 1.0 Author-Name: Wuyan Lou Author-X-Name-First: Wuyan Author-X-Name-Last: Lou Title: Research on talent development for empowering sustainable development of night economy Abstract: The night economy has been expanding in scale in recent years, while the effective screening and training of talents is an important factor for sustainable economic development. At present, the problem of talent recruitment and training of night economy is that it is difficult to exchange information between talents and recruiters. In this study, a talent classification algorithm based on Improved RBF neural network and self-attention mechanism is constructed. The performance test results of the algorithm show that the accuracy of the algorithm reaches up to 93%, the specificity also reaches up to 90%, and the success rate of talent recruitment reaches 21%. These results show that the talent classification algorithm based on the improved RBF has the value of practical application to talent discovery and cultivation in the night economy. Journal: Int. J. of Knowledge-Based Development Pages: 248-262 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: night economy; sustainable development; RBF neural network; self-attentive mechanism; talent development. File-URL: http://www.inderscience.com/link.php?id=133327 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:248-262 Template-Type: ReDIF-Article 1.0 Author-Name: Xiang Li Author-X-Name-First: Xiang Author-X-Name-Last: Li Title: Research on the application of MOSL information retrieval method in educational resource management Abstract: In order to make full use of educational management resources and improve management efficiency, an improved ID3 algorithm is used to build an educational management resource mining system. The experimental results show that the improved ID3 algorithm has higher classification efficiency. The multi objective optimal sequencing learning (MOSL) algorithm has the highest NDCG value in different datasets and better stability. The MOSL algorithm has better noise removal ability. The running time of the MOSL algorithm to achieve the same sorting requirement is 1.87 s, which is more efficient for retrieval compared with the comparison algorithm. The PR The MOSL algorithm contains the largest area in the curve, and its AP value is 0.914, indicating that the retrieval results obtained by the MOSL retrieval method proposed in the study have higher search completion rate and accuracy rate, which can improve the retrieval efficiency and accuracy, and have certain practical value. Journal: Int. J. of Knowledge-Based Development Pages: 198-213 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: improved ID3 algorithm; educational management resources; sequential learning; multi-objective optimisation; information retrieval. File-URL: http://www.inderscience.com/link.php?id=133328 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:198-213 Template-Type: ReDIF-Article 1.0 Author-Name: Limin Zhang Author-X-Name-First: Limin Author-X-Name-Last: Zhang Author-Name: Zhixue Li Author-X-Name-First: Zhixue Author-X-Name-Last: Li Title: The impact of technology optimisation incorporating machine learning algorithms on the financial sustainability of new energy companies Abstract: New energy companies in the industry have differences in financial performance from traditional companies. To help new energy companies develop sustainably, it is necessary to analyse and monitor their financial characteristics. To optimise the financial technology of new energy enterprises, this research uses GoogleNet convolutional neural network to construct a financial risk analysis model, which can judge financial risks and issue early warnings based on enterprise financial data. The experimental results of the financial risk analysis model show that the test loss value of the model is as low as 2.97%, which is very close to the loss value of the training set. The financial risk analysis model shows a large advantage over similar models, with an accuracy rate of 91.14%. In addition, the model's predictive ability and the actual situation are well fitted with an overall accuracy of 85%. In general, the outstanding performance of this model is that its judgment accuracy is significantly higher than that of similar models, and the timeliness of early warning is significantly higher than that of human early warning. Journal: Int. J. of Knowledge-Based Development Pages: 181-197 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: convolutional neural network; machine learning; new energy; financial analysis; sustainable development. File-URL: http://www.inderscience.com/link.php?id=133329 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:181-197 Template-Type: ReDIF-Article 1.0 Author-Name: Jie Yang Author-X-Name-First: Jie Author-X-Name-Last: Yang Title: Optimisation strategy of college English teaching during the epidemic period: taking MOOC resources expressed by interactive features as an example Abstract: The change in epidemic prevention and control situation and rapid development of the internet have promoted the online teaching activity platform based on massive open online courses (MOOC) resources develop greatly. The richness of MOOC resources makes redundant information difficult to eliminate. This paper proposes a MOOCrec model based on the research of constructing heterogeneous information network with meta paths in MOOC resources, adding a multi-head attention mechanism, and considering users' long-term and short-term interest preferences. Through performance test and application analysis of the model, it is found that project click value of the model is more than 0.7, the indicator performance is better than other comparison algorithms, and its interest coverage diversity value is 0.461. MAE value and RMSE value decrease more obviously, and the information extraction of the incidence matrix is more obvious, which reduces the data loss and the dissatisfaction of teachers and students with the teaching resource platform. Journal: Int. J. of Knowledge-Based Development Pages: 294-310 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: English teaching; optimisation strategy; interaction characteristics; MOOC; massive open online courses; interest preference; incidence matrix; HR; sequence information. File-URL: http://www.inderscience.com/link.php?id=133331 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:294-310 Template-Type: ReDIF-Article 1.0 Author-Name: Caihong Li Author-X-Name-First: Caihong Author-X-Name-Last: Li Author-Name: Li Zhuang Author-X-Name-First: Li Author-X-Name-Last: Zhuang Title: Analysis on the collection of paper book resources in primary and secondary school libraries in Pukou District, Nanjing Abstract: As an important part of primary and secondary schools (PSSs), the library plays an important role in ensuring and serving teaching, improving students' learning ability, promoting teachers' professionalism and students' all-round development. However, most libraries in PSSs have been weakened and marginalised to varying degrees, for a long time. This paper takes 12 PSS libraries in compulsory education stages in Pukou District, Nanjing, Jiangsu, China as an example. The collection of paper book resources is analysed in an intelligent book management system developed by STAMINA, and the current situation of this collection is sorted out. Corresponding improvement suggestions are put forward, in view of the unreasonable collection structure of paper book resources. It is expected to provide theoretical support for the construction and development of paper book resources in PSS libraries in the future. Journal: Int. J. of Knowledge-Based Development Pages: 311-326 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: PSS; primary and secondary school; library; paper book; resource; collection. File-URL: http://www.inderscience.com/link.php?id=133332 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:311-326 Template-Type: ReDIF-Article 1.0 Author-Name: Bo Li Author-X-Name-First: Bo Author-X-Name-Last: Li Title: Research and development of e-commerce ERP system based on artificial intelligence technology Abstract: The multi-dimensional and multifuzzy multimedia data warehouse and its data mining technology are studied and constructed for collaborative processing, and then an enterprise resource planning system based on data warehouse and data mining technology is created for e-commerce enterprises to address the significant risks faced by e-commerce in the process of implementing enterprise resource planning (ERP) and ensure the objective and thorough evaluation of the entire process. Additionally, an evaluation system for the ERP system is created to help business managers enhance their decision-making process in light of the assessment's findings. The research results show that the ERP system processes 2987.6 transactions per second on average, and the success rate of user transactions is as high as 98.9%. From the availability analysis of the ERP system, if only the time is considered, risk probability of ERP system implementation is 0.14, and the risk is small. Journal: Int. J. of Knowledge-Based Development Pages: 327-343 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: E-commerce; ERP; enterprise resource planning; multidimensional fuzzy multimedia data warehouse; data mining; evaluation system. File-URL: http://www.inderscience.com/link.php?id=133333 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:327-343 Template-Type: ReDIF-Article 1.0 Author-Name: Laiyang Zhang Author-X-Name-First: Laiyang Author-X-Name-Last: Zhang Author-Name: Hu Li Author-X-Name-First: Hu Author-X-Name-Last: Li Title: The promotion of the concept of sustainable development to the reform of enterprise human resource management Abstract: In order to achieve sustainable HRM, performance management needs to be properly reformed. Improved K-means clustering algorithm is proposed, and the algorithm is used for data mining of factors affecting performance management, and then feedback and suggestions on performance management reform are given according to the analysis results. In the comparison experiments of clustering analysis on 6 simulated and 2 real datasets, the DT-Kmeans algorithm has the highest clustering accuracy and the best stability in 5 simulated and 2 real datasets compared with other algorithms. K-means++ algorithm has slightly better accuracy and stability than the DTKmeans algorithm when analysing simulated dataset 4. It is concluded that the optimised algorithm has significantly improved in terms of accuracy and stability when analysing both simulated and real datasets. In terms of algorithm runtime, the DT-Kmeans algorithm has decreased only for dataset 7 compared with other methods, and has improved in all other datasets. Journal: Int. J. of Knowledge-Based Development Pages: 344-362 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: enterprise; human resources; management reform; sustainable development. File-URL: http://www.inderscience.com/link.php?id=133334 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:344-362 Template-Type: ReDIF-Article 1.0 Author-Name: Congcong Han Author-X-Name-First: Congcong Author-X-Name-Last: Han Title: A study on career planning and development decisions of university students based on improved association rule algorithm Abstract: The study is based on the Apriori algorithm in association rule algorithm to mine student information, and improves the algorithm by using Spark framework. The experimental results show that during the iterations, Algorithm 1 has the lowest MAE value, indicating that Algorithm 1 performs best in the career recommendation of students. After 600 iterations, the accuracy of Algorithm 1 reached 99.64%, which was 0.80% higher than Algorithm 2 and 1.11% higher than Algorithm 3. On the School 2 dataset, when the minimum support was set to 0.44, the running time of Algorithm 1 was 8.3 s. The running time of Algorithm 2 was 25.4 s, and the running time of Algorithm 3 was 273.7 s. The above results indicate that the improved Apriori algorithm proposed in the study is more efficient and accurate, and can effectively provide students with employment information recommendations, thus providing data support for students' career planning and development decisions. Journal: Int. J. of Knowledge-Based Development Pages: 379-393 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: association rule algorithm; apriori algorithm; data mining; career planning; spark framework. File-URL: http://www.inderscience.com/link.php?id=133335 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:379-393 Template-Type: ReDIF-Article 1.0 Author-Name: Yingge Feng Author-X-Name-First: Yingge Author-X-Name-Last: Feng Author-Name: Xiaowei Xu Author-X-Name-First: Xiaowei Author-X-Name-Last: Xu Author-Name: Rongna Wang Author-X-Name-First: Rongna Author-X-Name-Last: Wang Title: A random forest algorithm based customer demand forecasting model for sports enterprises in the real economy Abstract: The study proposes two strategies to optimise the random forest algorithm (RF) by fine-tuning the data distribution and introducing customer life values, constructing the improved random forest algorithm (IRF), and building a customer churn prediction model based on the IRF algorithm. A churn segmentation model is constructed based on the k-means algorithm to classify customers according to their characteristics in order to predict their needs and thus develop differentiated strategies to retain them. The experimental results show that the IRF prediction model has an accuracy of 99.84% and an AUC value of 0.932. The above results show that the accuracy of the IRF algorithm can meet the actual demand, which will contribute to the long-term development of sports enterprises. In the future, it is necessary to consider the relationship and interaction between customers to further improve the prediction accuracy of customer demand. Journal: Int. J. of Knowledge-Based Development Pages: 363-378 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: random forest algorithm; customer churn; data mining; K-means algorithm; customer lifetime value. File-URL: http://www.inderscience.com/link.php?id=133337 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:363-378 Template-Type: ReDIF-Article 1.0 Author-Name: Zhipeng Chang Author-X-Name-First: Zhipeng Author-X-Name-Last: Chang Author-Name: Kai Liu Author-X-Name-First: Kai Author-X-Name-Last: Liu Title: Construction of a personalised online learning resource recommendation model based on self-adaptation Abstract: With the constant advancement of digital technology, the educational paradigm has experienced seismic shifts. Individuals are becoming more comfortable with using network information technology for online learning. This study proposes an adaptive-based personalised online learning resource recommendation system and constructs an adaptive-based generalised matrix factorisation model-long short-term memory (G-LSTM) model. This model combines generalized matrix decomposition with a long short-term memory network, so the fused model can effectively deal with information timing and cold start problems. The results show that in the RN dataset, when K = 10, the hit rate of the G-LSTM model is 80%, and the normalised loss cumulative gain value can reach 0.48. It can be seen that the recommendation model proposed in this study can meet the purpose of recommending online learning resources according to the different needs of users. And it can further promote the development of school education. Journal: Int. J. of Knowledge-Based Development Pages: 394-410 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: adaptive; online learning; personalisation; recommender system; matrix factorisation; LSTM; long short-term memory. File-URL: http://www.inderscience.com/link.php?id=133338 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:394-410 Template-Type: ReDIF-Article 1.0 Author-Name: Qunping Chen Author-X-Name-First: Qunping Author-X-Name-Last: Chen Title: Research on the design of an intelligent platform for marine economic management based on genetic algorithm Abstract: The scheduling of marine resources is becoming increasingly complex, and global consideration is needed to further improve the rationality and science of scheduling in order to maximise the utilisation of resources. In this study, an intelligent marine economic management platform based on a genetic algorithm (GA) is designed. To improve its performance, the GA is improved by using the self organisation mapping net (SOM) and uniform design (UD) method to make it excellent in solving marine resource scheduling problems. In the simulation experiments, the mobilisation schemes derived from it increase the power generation up to 223 × 104 kWh and 186 × 104 kWh than the conventional schemes at the confidence level of 0.95 and 0.90. The intelligent platform designed by the research can provide an excellent scheme for Marine tidal resource scheduling and improve the efficiency of Marine resource scheduling. Journal: Int. J. of Knowledge-Based Development Pages: 434-450 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: marine economy; SOM; SOM; GA; UD; resource scheduling; management platform. File-URL: http://www.inderscience.com/link.php?id=133342 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:434-450 Template-Type: ReDIF-Article 1.0 Author-Name: Jie Chen Author-X-Name-First: Jie Author-X-Name-Last: Chen Title: Evaluation analysis on operational performance of public gyms and stadiums: a case study of Shantou city in China Abstract: The 3rd Asian Youth Games, scheduled for Shantou, China, were cancelled due to the COVID-19 pandemic. The Asian Youth Games were expected to improve Shantou's urban construction, image, culture, and economy. However, public gyms and stadiums in Shantou are facing many operational and managerial obstacles that are rarely studied. Therefore, this study conducted an evaluation analysis of the operational conditions of public gyms and stadiums as the foundation for improvement. Based on responses from users, managers, and employees of Shantou's public gyms and stadiums, 9 secondary and 30 tertiary evaluation indices are developed and their weightage is calculated using axiomatic fuzzy set (AFS) theory and principal component analysis. It is discovered that several secondary indices, e.g., service quality, economic benefits, employee development, and employee rights and interests, significantly characterise the operational performance. Our analysis is expected to improve the operational performances of Shantou's public gyms and stadiums and retain public interest. Journal: Int. J. of Knowledge-Based Development Pages: 411-433 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: public gyms and stadiums; AFS; axiomatic fuzzy set theory; PCA; principal component analysis; evaluation of operational performance. File-URL: http://www.inderscience.com/link.php?id=133343 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:411-433 Template-Type: ReDIF-Article 1.0 Author-Name: Lifeng Li Author-X-Name-First: Lifeng Author-X-Name-Last: Li Title: A study on the application of RBF neural network in the estimation of English language and literature teaching quality Abstract: The quality of education and teaching directly affects the cultivation of talents. Aiming at the problems of low efficiency and low accuracy of current English teaching quality assessment model, a radial basis function (RBF) model combined with genetic algorithm was studied. The model uses genetic algorithm to search RBF parameters, and principal component analysis to reduce the dimension of the index, so as to build the GA-RBF teaching evaluation model. The results show that the mean square error (MSE) of GA-RBF model is 0.2, the precision fluctuation is minimal, and the stability is good. In comparison, GA-RBF mode has a running time of 2.3 s, the evaluation efficiency is faster, and the evaluation accuracy is the highest, reaching 94.28%. The application of this teaching quality evaluation model can improve the quality of school teaching management, enhance the teaching effect, and provide guidance for education reform. Journal: Int. J. of Knowledge-Based Development Pages: 451-466 Issue: 2/3/4 Volume: 13 Year: 2023 Keywords: English language and literature teaching; estimation pattern; RBF network pattern; parameter optimisation; genetic algorithm. File-URL: http://www.inderscience.com/link.php?id=133345 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:451-466