Search results

This study aims to highlight the inconsistency between conventional knowledge push judgements and the price of knowledge push. Also, a three-way decision-based relevant knowledge push algorithm was proposed.

Using a ratio of 80–20%, the experiment randomly splits the data into a training set and a test set. Each video is used as a knowledge unit (structure) in the research, and the category is used as a knowledge attribute. The limit is then determined using the user’s overall rating. To calculate the pertinent information obtained through experiments, the fusion coefficient is needed. The impact of the push model is then examined in comparison to the conventional push model. In the experiment, relevant knowledge is compared using three push models, two push models based on conventional International classification functioning (ICF), and three push models based on traditional ICF. The average push cost accuracy rate, recall rate and coverage rate are metrics used to assess the push effect.

The three-way knowledge push models perform better on average than the other push models in this research in terms of push cost, accuracy rate and recall rate. However, the three-way knowledge push models suggested in this study have a lower coverage rate than the two-way push model. So three-way knowledge push models condense the knowledge push and forfeit a particular coverage rate. As a result, improving knowledge results in higher accuracy rates and lower push costs.

This research has practical ramifications for the quick expansion of knowledge and its hegemonic status in value creation as the main methodology for knowledge services.

To the best of the authors’ knowledge, this is the first theory developed on the three-way decision-making process of knowledge push services to increase organizational effectiveness and efficiency.

Based on interdependence theory, the authors investigated the effect of reward interdependence (RI) on project professionals' knowledge hiding and examined the moderating role of knowledge tacitness (KT) and complexity, in the context of new product development (NPD) teams.

The authors conducted a time-lagged study in the context of NPD teams and collected data from a sample of 231 NPD professionals in China.

The study's findings indicate that RI was negatively associated with knowledge hiding. Knowledge tacitness negatively moderated the relation between RI and knowledge hiding. In contrast, the moderating effect of knowledge complexity (KC) was not significant.

To reduce NPD professionals' knowledge hiding, organizations should not only design incentive plans that cultivate interpersonal relatedness but also address the drawbacks (decreased effectiveness of group rewards) resulting from KT.

The authors' paper provides novel insights into the inconsistent understanding of organizational rewards' effectiveness in managing knowledge withholding by demonstrating the differentiated effects of individual and group rewards on knowledge hiding as well as the differential contingent roles of knowledge attributes.

This paper aims to amplify the retrieval and utilization of historical newspapers through the application of semantic organization, all from the vantage point of a fine-grained knowledge element perspective. This endeavor seeks to unlock the latent value embedded within newspaper contents while simultaneously furnishing invaluable guidance within methodological paradigms for research in the humanities domain.

According to the semantic organization process and knowledge element concept, this study proposes a holistic framework, including four pivotal stages: knowledge element description, extraction, association and application. Initially, a semantic description model dedicated to knowledge elements is devised. Subsequently, harnessing the advanced deep learning techniques, the study delves into the realm of entity recognition and relationship extraction. These techniques are instrumental in identifying entities within the historical newspaper contents and capturing the interdependencies that exist among them. Finally, an online platform based on Flask is developed to enable the recognition of entities and relationships within historical newspapers.

This article utilized the Shengjing Times·Changchun Compilation as the datasets for describing, extracting, associating and applying newspapers contents. Regarding knowledge element extraction, the BERT + BS consistently outperforms Bi-LSTM, CRF++ and even BERT in terms of Recall and F1 scores, making it a favorable choice for entity recognition in this context. Particularly noteworthy is the Bi-LSTM-Pro model, which stands out with the highest scores across all metrics, notably achieving an exceptional F1 score in knowledge element relationship recognition.

Historical newspapers transcend their status as mere artifacts, evolving into invaluable reservoirs safeguarding the societal and historical memory. Through semantic organization from a fine-grained knowledge element perspective, it can facilitate semantic retrieval, semantic association, information visualization and knowledge discovery services for historical newspapers. In practice, it can empower researchers to unearth profound insights within the historical and cultural context, broadening the landscape of digital humanities research and practical applications.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.

Teaching effectiveness is essential to student learning, engagement and success. This study aims to identify the perceived teaching effectiveness attributes from the student’s perspective through a pilot study.

A comprehensive literature review identified 6 demographic and 25 teaching effectiveness characteristics. The Kano model was used to gather and analyze the student’s voices. The research validated the survey instrument using Cronbach’s alpha to ensure internal consistency and Chi-square goodness of fit to test the data distribution. Differences in response patterns were analyzed using Fisher’s exact test. Furthermore, the magnitude of the effect between the teaching effectiveness attributes was determined using Cramer’s V test.

This study determined that students perceived 19 attributes as one-dimensional, 3 as indifferent, 2 as attractive and 1 as one-dimensional and attractive. The analysis found differences in response patterns concerning readings and materials, grading rubrics to set assignment expectations and group/teamwork on projects.

As a pilot study, the sample size was small. Additional research should validate the survey using a larger sample. While the study results are specific to the college surveyed, other educators can use the methodology to identify the attributes important to their students.

Categorizing attributes based on the student’s voice enables instructors to focus on attributes that will improve the learning experience.

This research provides a comprehensive methodology for identifying critical teaching effectiveness attributes from the student’s perspective.

This study aims to promote sustainability-based education in fashion design and merchandising program to enhance students’ knowledge, skills and attitude about sustainability development, organizational responsibility and personal responsibility from the cotton industry perspective.

To conduct this study, three learning components were considered: learning from experts, learning by doing and outreach activity. Sustainability-related topics were strategically incorporated in different courses for one year; project-based learning approach was adopted; and pre–posttest survey was conducted to study the impact of sustainability-based education on student learning outcome. Rand’s principles-attributes matrix was applied to analyze the impact of sustainable education on student learning outcomes.

The results of course projects indicated enhanced student’s abilities on using use different types of cotton materials in product development, creative use of cotton in visual merchandising and development of business plans focused on sustainability. The two-group mean comparisons showed a significant positive impact on students’ knowledge in cotton and sustainability, followed by students’ skills and attitudes.

In response to the lack of systematic approach to incorporate sustainability-related topics in textile and apparel design discipline, this study offered an opportunity to involve approximately 110 students in various sustainability-based teaching and learning projects.

The purpose of this research was first to determine the competencies mandatory of risk managers, and second, to consider the implications of such competencies in determining modules appropriate for inclusion in any prospective undergraduate qualification with specialisation in risk management.

A qualitative research approach was followed, involving academics teaching risk management in a focus group and making use of interactive qualitative analysis (IQA).

The competencies identified were business management skills, financial knowledge, an understanding of the risk management process, governance and compliance, people management and technical skills. These will be explained in greater detail in the paper.

The implications for teaching are that an undergraduate curriculum in risk management will have to combine majors such as business management, financial management, risk management, industrial psychology and communication. These majors need to be complemented by modules in governance and compliance management, as well as information and communication technology.

The implication for practice is that risk management professionals and members of the Institute of Risk Management of South Africa need to avail themselves to serve on an advisory board of academic departments offering risk management qualifications. Risk management is a developing science and requires inputs about research and the curriculation of qualifications.

The implication for public policy is that the South African Qualifications Authority and the Council for Higher Education should reconsider their requirements for designators (specialised qualifications). The implications for research are that IQA provides clarity on the knowledge and skills required to develop a competency-based qualification in risk management. Further research should benchmark qualifications and propose a curriculum for a bachelor’s degree in risk management.

The use of IQA is a novel way of ensuring rigour and objectivity in arriving at a description of the required knowledge, skills, values and attributes of risk managers. This paper will assist in the compilation of a new curriculum for an undergraduate qualification in risk management; thus, ensuring such qualification will provide a competency-based qualification that will meet the needs of the profession.

There is sufficient literature on green knowledge regarding supplier selections. Notwithstanding, there are hardly any empirical studies that analyze green knowledge toward supplier selection through the lenses of green intellectual capital (GIC). This paper aims to analyze green knowledge development toward supplier selection through the lenses of GIC.

This study uses an exploratory case study approach involving seven public universities in Ghana. A purposive sampling technique was used in selecting respondents who were interviewed through face-to-face and focus group discussions with a semistructured interview guide. Atlas ti software was used to generate themes for discussion.

The findings of this study attribute the nonapplication of green criteria to supplier selection to low knowledge among practitioners. Training, collaboration, opportunities for further studies and affiliation with professional bodies were identified as means to enhance green knowledge. Green human capital factors that support knowledge enhancement include commitment, capability, skills and ease of understanding.

Green procurement practitioners in public universities in developing countries stand little chance of integrating green criteria into supplier selection if they do not develop their level of knowledge.

Selecting green suppliers is a complex issue for public organizations, particularly universities. This study would therefore help equip managers of public universities and procurement practitioners with the relevant GIC knowledge for the successful integration of green credentials into supplier selection.

This paper highlights the importance of knowledge in green supplier selection. To the best of the authors’ knowledge, analyzing the role of GIC in knowledge development is considered the first of this kind of study.