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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.

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.

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.

This study examines how the characteristics of innovation knowledge exchanged among affiliate firms affect the ownership strategies adopted for their foreign subsidiaries.

This study employs a cross-classified multilevel model to examine a sample of 185 Korean manufacturing affiliates derived from 49 Chaebols engaged in international diversification, along with their 1,110 foreign manufacturing subsidiaries.

While exploratory innovation knowledge exchange lowers the affiliate's level of ownership in its foreign subsidiary, exploitative innovation knowledge exchange rather increases the affiliate's level of ownership in its foreign subsidiary.

This study advances the literature on intrafirm knowledge exchange by highlighting it as a determinant of ownership strategies. The study further shows that the characteristics of knowledge exchanged at the affiliate level not only determine the ownership structure but also have the potential to shape the direction in which the subsidiary develops its competencies.

This study has practical implications for the managers of business group affiliates. The results suggest that managers should adapt their ownership strategies according to the type of knowledge exchanged at the affiliate level to achieve a balanced and synergistic effect on intraorganizational knowledge exchange.

Previous studies have extensively explored the performance implications related to knowledge exchange. However, there is a notable gap in understanding the mechanisms through which the value of knowledge transferred within an affiliate is realized. To address this gap, this study focuses on ownership strategy as a crucial factor and empirically examines how the characteristics of innovation knowledge exchanged among affiliate firms influence the ownership strategies adopted for their foreign subsidiaries. By investigating this relationship, this study provides valuable insights into the complex dynamics of knowledge exchange and its effect on ownership decisions within business group affiliates.

This paper aims to focus on the characteristics of a two-tier network featuring internal subject cooperation and external embedded cooperation in the context of regional innovation systems (RISs) and explore the influence of network characteristics on knowledge emergence.

Using social network analysis, a two-tier internal and external cooperation network of a RIS is constructed. A negative binomial regression method is used to explore the effects of the characteristics of these two-tier internal and external networks on knowledge emergence, the moderating effect of the cooperation knowledge base in this context is investigated and grouping and quantile regressions are used to conduct heterogeneity analysis.

The scale of the internal cooperation network has a positive effect on knowledge emergence, and the betweenness centralization of the internal cooperation network has an inverted U-shaped effect on knowledge emergence. The scale and structural holes of the external embedded network have an inverted U-shaped effect on knowledge emergence. Furthermore, the internal cooperation knowledge base weakens the influence of the external embedded network on knowledge emergence.

This research may enlighten policymakers with respect to improving the scale and structure of the RIS cooperation network and matching the embedded network based on the internal cooperation knowledge base to promote knowledge emergence.

This research contributes to the study of knowledge emergence by exploring the influence of a two-tier network structure and scale characteristics on knowledge emergence in RISs. This paper also extends the framework of relevant research by integrating the internal cooperation knowledge base into the analysis of externally embedded cooperation and knowledge emergence.

Effectively engaging patients is critical for the sustainable development of online health communities (OHCs). Although physicians’ general knowledge-sharing, which is free to the public, represents essential resources of OHCs that have been shown to promote patient engagement, little is known about whether such knowledge-sharing can backfire when superfluous knowledge-sharing is perceived as overwhelming and anxiety-provoking. Thus, this study aims to gain a comprehensive understanding of the role of general knowledge-sharing in OHCs by exploring the spillover effects of the depth and breadth of general knowledge-sharing on patient engagement.

The research model is established based on a knowledge-based view and the literature on knowledge-sharing in OHCs. Then the authors test the research model and associated hypotheses with objective data from a leading OHC.

Although counterintuitive, the findings revealed an inverted U-shape relationship between general knowledge-sharing (depth and breadth of knowledge-sharing) and patient engagement that is positively associated with physicians’ number of patients. Specifically, the positive effects of depth and breadth of general knowledge-sharing increase and then decrease as the quantity of general knowledge-sharing grows. In addition, physicians’ offline and online professional status negatively moderated these curvilinear relationships.

This study further enriches the literature on knowledge-sharing and the operations of OHCs from a novel perspective while also offering significant specific implications for OHCs practitioners.

This research investigates performance determinants of service sector foreign-owned subsidiaries located in an emerging market. The focus is on the two dimensions of organizational networks (Who do you know?) and competencies (What do you know?).

Data were collected via a large-scale survey of managing directors located in the midrange emerging economy of Taiwan. The data are analyzed using partial least squares structured equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) techniques.

The results show the importance of intraorganizational network strength as a key determinant of subsidiary performance, and that combinations of interorganizational network strength and competencies can determine performance in several subsidiaries.

This article offers new insights by testing a theoretical framework based on network perspective and the competence-based view of the firm in an emerging market context. It also offers an additional twist by employing symmetric (PLS-SEM) and nonsymmetric (fsQCA) methods to test the framework. This allows to arrive at robust conclusions about the complementarity and substitutability of the applied theories. This research also contributes to the current literature by providing fine-grained insights into the nature and impact of competencies and networks. It is also one of the few studies to focus specifically on service sector subsidiaries.