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Technological advancements and global societal changes reshapes manufacturing industry emphasizing needs for competence development of industrial professionals. The purpose of this paper is to study how organizational learning supports the development of academic structures, creating agile and sustainable formal educational models meeting novel competence needs.

The qualitative case study, part of a longitudinal research study, focuses on internal academic processes supporting a new formal educational model. Qualitative data was collected through five focus groups, incorporating 32 informants from different HEI function categories.

Changing traditional academic structures requires joint engagement between all HEI functions, emphasizing organizational learning with subprocesses of searching, creating, sustaining and exchanging knowledge in a learning loop. Results show a consensus among the different HEI functions regarding the value of the HEI’s coproduction with society; however, bureaucracy and academic structure hinder flexibility. Cross-functional teams building a “chain-of-trust” throughout the HEI coupled with full management support show opportunities to progress into a learning organization.

Organizational learning within HEIs requires trustful and open communication, multifunction knowledge exchange, holistic views of processes and system thinking, achieved through cross-functional teams and continuous improvement through learning loops.

Industry-academic collaboration on formal education for lifelong learning needs to become both agile and resilience to meet technological advancement and sustainability.

Novel technology, digitalization and sustainability gain ground and require that society and organizations, including academia, change and learn. This means that academia is meeting new challenges and needs to develop internal processes.

This study identifies the policing pre-deployment training content for Korean experts based on needs assessments. Korean policing is at an excellent level to transfer knowledge and skills. Pre-deployment training should be designed systematically and training of trainers approaches should be implemented.

This study used T-tests, Borich needs assessments, and Locus for Focus model analyses to determine the priorities of needs for pre-deployment training in policing. A survey of 116 experienced experts was conducted, with 87 responding (75%).

The study identified 26 factors that deployed law enforcement professionals want to learn from pre-deployment training. These factors were categorized into three areas: research, training design and methods and understanding of partner countries and international development cooperation. The nine highest priorities for training needs were related to understanding the status and conditions of police training in the country to which policing experts are deployed.

This study was limited to Korean policing experts. And the study did not evaluate the validity of the training curriculum or indicators.

Technical assistance in international policing development cooperation aims to train future trainers who can train local police. This study found that limited learner information and poor communication skills can lead to ineffective technical assistance.

This study highlights the importance of knowledge transfer and effective pre-deployment training for policing. The findings can be used to improve training programs and police human resource development.

Marketing tourism is essential for long-term tourism development which requires gaining knowledge about the motivation and needs of tourists. In order to help tourists gain a hospitable experience, information regarding the needs, perception, and their behavior while on site is important. This research attempts to explore the priority of tourists’ needs in visiting historical sites. It also tries to conceptualize new forms of hospitality strategies for smart tourism development. Based on grounded theory, Maslow’s hierarchy of needs is conceptualized for historical tourists and used as the main framework for this work. The Persepolis-Pasargadae Historical Range (PPHR) is chosen as the case study of the research because of the historical and cultural attractions located in this historical range. Results indicate that tourists interested in visiting this destination are looking to fulfill their growth needs. These growth needs can be complemented by new technologies while on site such as virtual reality (VR) goggles that help tourists gain knowledge about the reality of these destinations. The research concludes with findings and suggestions that can contribute to the planning of an effective marketing plan based on tourists’ motivation and needs for visiting historical destinations.

This study employed self-determination theory (SDT) and the “Motivational affordance–Psychological outcomes–Behavioral outcomes” framework to investigate the relationship between gamification features and knowledge-sharing behavior in online communities.

A theoretical model was tested with 281 Chinese users from an online social question and answer (Q&A) community. Partial least square structural equation modeling was applied to analyze the data.

The empirical results revealed that competence mediated the effects of immersion and achievement-related gamification features on knowledge sharing. Moreover, relatedness mediated the effects of immersion, achievement and social-related gamification features on knowledge sharing.

This study was conducted on a Chinese Q&A platform, and the results may not be generalizable to other cultures or service providers with different goals.

The study's findings indicate that gamification could serve as an effective toolkit for incentivizing and promoting knowledge sharing in online communities. The findings thus provide strategic insights for administrators of online communities seeking to leverage gamification designs to encourage user participation in knowledge-sharing activities.

Research on the role of gamification in promoting knowledge sharing has been limited in scope and has focused on tourism comment communities. Little evidence exists on the effect of gamification within social Q&A communities. Further, the finding of gamification's positive role in motivating knowledge sharing indicates the need for the knowledge-sharing field to focus on contextual factors.

Customers can participate in new product development (NPD) in many ways. Drawing on the knowledge-based view (KBV) and innovation literature, this study aims to contrast two main product development activity types, i.e. problem-solving and decision-making. It proposes customers play distinct roles if they get involved in these activities, which influence NPD outcomes differently. It also explores customer need specificity as a boundary condition for the above-mentioned relationships.

The authors collected survey data from 308 managers in the innovation domain.

Customer involvement in problem-solving and decision-making distinctively influences new product innovativeness and development speed. Customer need specificity interacts with the two co-development types differently to impact these NPD outcomes further.

This research extends the KBV and addresses the inconsistent findings in the literature regarding customer involvement as co-developers in innovation. It also provides novel insights into how knowledge characteristics like customer need specificity can direct co-developing activities to generate distinct NPD results.

This paper offers practical implications for firms on how to involve customers in developing innovative new products while managing development speed.

Prior research has yet to distinguish customer responsibilities related to co-development activities. This research fills this gap and offers novel insights that problem-solving and decision-making have opposite impacts on different NPD outcomes. This research demonstrates that finer knowledge about customer involvement responsibilities is needed for critical NPD outcomes.

This study aims to evaluate the information behavior of the Banarasi Sarees weaving community and propose an information-focused policy tailored to their needs.

This study was conducted in seven weaver-centered areas in Varanasi and was designed around semi-structured interviews to explore various information-related aspects among the weavers. It aims to focus on their knowledge of weaving, their information needs, seeking behavior, preferred communication channels, prioritization of information and methods for enhancing information-related situations.

It was found that a lack of information among weavers significantly impacts their livelihoods and businesses. They struggle to make product, pricing and marketing decisions without access to accurate, timely and relevant information. They cannot expand their businesses and invest in new equipment and materials. The weavers need a library with a specialized collection and a qualified librarian to guide them in using the information sources. They also need a dedicated information system and community information centers to provide better information services.

This study is a work whose expected results and findings would help policymakers adopt measures to encourage providing information services through public libraries and community information centers. The results of this study may be further used to frame information policy for weavers and other occupational communities.

To address the shortcomings of existing academic user information needs identification methods, such as low efficiency and high subjectivity, this study aims to propose an automated method of identifying online academic user information needs.

This study’s method consists of two main parts: the first is the automatic classification of academic user information needs based on the bidirectional encoder representations from transformers (BERT) model. The second is the key content extraction of academic user information needs based on the improved MDERank key phrase extraction (KPE) algorithm. Finally, the applicability and effectiveness of the method are verified by an example of identifying the information needs of academic users in the field of materials science.

Experimental results show that the BERT-based information needs classification model achieved the highest weighted average F1 score of 91.61%. The improved MDERank KPE algorithm achieves the highest F1 score of 61%. The empirical analysis results reveal that the information needs of the categories “methods,” “experimental phenomena” and “experimental materials” are relatively high in the materials science field.

This study provides a solution for automated identification of academic user information needs. It helps online academic resource platforms to better understand their users’ information needs, which in turn facilitates the platform’s academic resource organization and services.

Fish quarantine is a measure to prevent the entry and spread of quarantine fish pests and diseases abroad and from one area to another within Indonesia's territory. Based on these backgrounds, this study aims to identify the knowledge, knowledge management (KM) processes and knowledge management system (KMS) priority needs for quarantine fish and other fishery products measures (QMFFP) and then develop a classification model and web-based decision support system (DSS) for QMFFP decisions.

This research methodology uses combination approaches, namely, contingency factor analysis (CFA), the cross-industry standard process for data mining (CRISP-DM) and knowledge management system development life cycle (KMSDLC). The CFA for KM solution design is performed by identifying KM processes and KMS priorities. The CRISP-DM for decision classification model is done by using a decision tree algorithm. The KMSDLC is used to develop a web-based DSS.

The highest priority requirements of KM technology for QMFFP are data mining and DSS with predictive features. The main finding of this study is to show that web-based DSS (functions and outputs) can support and accelerate QMFFP decisions by regulations and field practice needs. The DSS was developed using the CTree algorithm model, which has six main attributes and eight rules.

This study proposes a novel comprehensive framework for developing DSS (combination of CFA, CRISP-DM and KMSDLC), a novel classification model resulting from comparing two decision tree algorithms and a novel web-based DSS for QMFFP.

This study aims to investigate how the public formed their need for information in the early stage of the COVID-19 outbreak. Exploring the formation of information needs can reveal why the public's information needs differ and provide insights on targeted information service during health crises at an essential level.

The data were collected through semi-structured interviews with 46 participants and analyzed using the grounded theory approach. Concepts, sub-categories and categories were developed, and a model was built to examine how the public formed the need for information about the pandemic.

The authors found that participants were stimulated by information asymmetry, severity of the pandemic and regulations to control the pandemic, which triggered their perceptions of information credibility, threat and social approval. After the participants perceived that there was a threat, it activated their basic needs and they actively formed the need for information based on cognitive activities. Moreover, information delivered by different senders resulted in a passive need for information. Participants' individual traits also influenced their perceptions after being stimulated.

Long-term follow-up research is needed to help researchers identify more detailed perspectives and do comparative studies. Besides, this study conducted interviews through WeChat voice calls and telephone calls, and might be limited compared with face-to-face interviews.

The findings of this study provide theoretical contributions to the information needs research and practical implications for information services and public health management.

There is little systematic research on how the public formed information needs in the early stage of the COVID-19 outbreak.