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A firm's resources and capabilities can form the basis for performance differences among firms. The question is “how do firms face the challenge of acquiring resources and developing capabilities during their day-to-day activities in order to face competition?” Case study research involving day-to-day activities of a project-firm in a B2B context suggests that social capital – the sum of structural, relational and cognitive resources – built in networks increases the ability to face the challenge of resource acquisition and capability development even during daily activities. A communication network study clearly maps this influence of social capital. More precisely, dominant or powerful employees should be avoided. Next to organizational structures characterized by hierarchy, high and low communications are also not desirable. Moreover, too much trust can harm firms’ abilities to develop capabilities when performing day-to-day activities. Even a complete shared vision hinders firms’ capability development during their day-to-day activities. This study supports the negative impact of overembeddedness; shows the value of articles discussing the downside of social capital and confirms the paradox of embeddedness: overembeddedness as well as underembeddedness has negative implications for a firm's performance. Moreover, from the research results important managerial lessons can be deducted, such as (1) the basis for performance differences can be formed during day-to-day activities and (2) social capital management is a critical success factor in outperforming competitors. Therefore, managers should be aware of the potential value embedded in their day-to-day activities and relationships based on economic transactions. They can leverage their day-to-day activities and relationships based on economic transactions and consider them as sources for resources and capabilities that can be deployed in their search for a competitive position. Moreover, managers should not only pay attention to their financial and human capital but also to the social capital built in the firm's networks and in their employees’ networks. Social capital can influence – among others – divisional learning and divisional capability development.

The purpose of this paper is to provide adaptive access to learning resources in the digital library.

A novel method using ontology-based multi-attribute collaborative filtering is proposed. Digital libraries are those which are fully automated and all resources are in digital form and access to the information available is provided to a remote user as well as a conventional user electronically. To satisfy users' information needs, a humongous amount of newly created information is published electronically in digital libraries. While search applications are improving, it is still difficult for the majority of users to find relevant information. For better service, the framework should also be able to adapt queries to search domains and target learners.

This paper improves the accuracy and efficiency of predicting and recommending personalized learning resources in digital libraries. To facilitate a personalized digital learning environment, the authors propose a novel method using ontology-supported collaborative filtering (CF) recommendation system. The objective is to provide adaptive access to learning resources in the digital library. The proposed model is based on user-based CF which suggests learning resources for students based on their course registration, preferences for topics and digital libraries. Using ontological framework knowledge for semantic similarity and considering multiple attributes apart from learners' preferences for the learning resources improve the accuracy of the proposed model.

The results of this work majorly rely on the developed ontology. More experiments are to be conducted with other domain ontologies.

The proposed approach is integrated into Nucleus, a Learning Management System (https://nucleus.amcspsgtech.in). The results are of interest to learners, academicians, researchers and developers of digital libraries. This work also provides insights into the ontology for e-learning to improve personalized learning environments.

This paper computes learner similarity and learning resources similarity based on ontological knowledge, feedback and ratings on the learning resources. The predictions for the target learner are calculated and top N learning resources are generated by the recommendation engine using CF.

With the continuous development of the global COVID-19 epidemic, mobile learning has become one of the most significant learning approaches. The mobile learning resource is the basis of mobile learning; it may directly affect the effectiveness of mobile learning. However, the current learning resources cannot meet users' needs. This study aims to analyze the influencing factors of accepting open data as learning resources among users.

Based on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT), this study proposed a comprehensive theoretical research model. Data were obtained from 398 postgraduates from several universities in central China. Confirmatory factor analysis was used to determine the reliability and validity of the measurement model. Data has been analyzed using SPSS and AMOS software.

The results suggested that perceived usefulness, performance expectancy, social influence and facilitating conditions have a positive influence on accepting open data as learning resources. Perceived ease of use was not found significant. Moreover, it was further shown in the study that behavioural intention significantly influenced the acceptance of open data as learning resources.

There is a lack of research on open data as learning resources in developing countries, especially in China. This study addresses the gap and helps us understand the acceptance of open data as learning resources in higher education. This study also pays attention to postgraduates' choice of learning resources, which has been little noticed before. Additionally, this study offers opportunities for further studies on the continuous usage of open data in higher education.

The purpose of this study is to analyze from multiple perspectives, so as to form an effective massive open online course (MOOC)personalized recommendation method to help learners efficiently obtain MOOC resources.

This study introduced ontology construction technology and a new semantic association algorithm to form a new MOOC resource personalized recommendation idea. On the one hand, by constructing a learner model and a MOOC resource ontology model, based on the learner’s characteristics, the learner’s MOOC resource learning preference is predicted, and a recommendation list is formed. On the other hand, the semantic association algorithm is used to calculate the correlation between the MOOC resources to be recommended and the learners’ rated resources and predict the learner’s learning preferences to form a recommendation list. Finally, the two recommendation lists were comprehensively analyzed to form the final MOOC resource personalized recommendation list.

The semantic association algorithm based on hierarchical correlation analysis and attribute correlation analysis introduced in this study can effectively analyze the semantic similarity between MOOC resources. The hybrid recommendation method that introduces ontology construction technology and performs semantic association analysis can effectively realize the personalized recommendation of MOOC resources.

This study has formed an effective method for personalized recommendation of MOOC resources, solved the problems existing in the personalized recommendation that is, the recommendation relies on the learner’s rating of the resource, the recommendation is specialized, and the knowledge structure of the recommended resource is static, and provides a new idea for connecting MOOC learners and resources.

This paper seeks to apply the dynamic capability framework to explore why store managers within the same chain of restaurants perform differently. Specifically, this paper argues that knowledge resources and learning mechanisms are critical to the development of dynamic capabilities.

The approach takes the form of an empirical data analysis. Hypotheses are tested on 132 store managers in a leading fast‐food restaurant chain in Taiwan.

The findings indicate that dynamic capabilities increase store performance, and that both knowledge resources and learning mechanisms have a positive effect on dynamic capabilities. In addition, the effect of knowledge resources on dynamic capabilities is partially mediated by the type of learning mechanism.

Store managers must be able to develop dynamic capabilities if they are to deal with the rapidly changing environment they are facing. Knowledge resources and learning mechanisms both improve the development of dynamic capabilities.

This paper conceptualizes and empirically tests the relationships between knowledge resources, learning mechanisms, dynamic capabilities, and performance in the restaurants of a fast‐food chain. In addition, this paper investigates how dynamic capabilities work from a process perceptive by examining the mediation effect of the learning mechanisms.

This paper seeks to assess the differences between learning performance and the satisfaction of learners who use digital resources in the Taiwan Libraries' History Digital Library (organized digital resources) and the Google search engine (unorganized digital resources) in problem‐solving learning for the same subject via the problem‐based learning (PBL) mode. The paper aims to explore the advantages and characteristics of using digital archives to support PBL and to offer suggestions that are helpful when using digital archives to support e‐learning.

The study adopted the quasi‐experimental design method to assign all participants into an experimental group and control group to evaluate differences in learning performance and the satisfaction of learners who use different digital resources during PBL processes. A statistical analysis scheme was employed to evaluate the learning performance of learners during PBL supported by different digital resources in terms of learning processes, PBL outcomes, and a questionnaire.

The study obtained the following conclusions: learning performance and the satisfaction of learners in the experimental group during PBL processes supported by digital archival resources were superior to those of control‐group learners who were supported by search engine resources; compared with search engine resources, the digital archival resources provide benefits in the learning phase, such as “action” (i.e. doing), in the proposed PBL mode, which has three learning phases; and compared with resources accessed through the Google search engine, PBL supported by digital archival resources should enhance searching performance and thereby increase learner willingness to use digital archives during e‐learning.

Using digital archives to support e‐learning is a new trend in the library sciences field; however, few studies have developed useful learning modes for effective e‐learning supported by digital archives. Evidential research related to e‐learning supported by digital archives is also lacking; most studies used digital archives as digital course materials, thus ignoring the principal property of digital archives – excellent resource organization.

The paper shows that by integrating the PBL mode with digital archives one can identify the advantages of digital archives in supporting e‐learning, resulting in innovative and valuable research.

Proposes to evaluate 5/99 content for reusability as learning objects.

Presents the criteria developed specifically for this particular set of content, and the process by which they were developed. Some data are given on how the projects fared in the evaluation.

In 2001 a JISC study gathered data about 27 of its 5/99 projects, mapping content categories and approaches to reusability, metadata and interoperability. A total of 18 were chosen for evaluation, based on availability of content, and coverage of content categories. Appropriate reusability evaluation criteria were developed specifically for the study in four areas: aggregation level; reusability; subject specificity; and vertical reusability. The projects showed high levels of awareness of, and willingness to plan for, reusability and interoperability. Planning from the start for developing reusable resources is imperative, if the potential of learning technology for sharing resources is to be fulfilled.

This paper is useful for those planning to use 5/99 content.

Drawing from social cognitive theory, the purpose of this study is to examine how personal, environmental and behavioral factors can interplay to influence people's use of YouTube as a learning resource.

This study proposed a conceptual model, which was then tested with data collected from a survey with 150 participants who had the experience of using YouTube for learning. The bootstrap method was employed to test the direct and mediation hypotheses in the model.

The results revealed that personal factors, i.e. learning outcome expectations and attitude, had direct effects on using YouTube as a learning resource (person → behavior). The environmental factor, i.e. the sociability of YouTube, influenced the attitude (environment → person), while the behavioral factor, i.e. prior experience of learning on YouTube, affected learning outcome expectations (behavior → person). Moreover, the two personal factors fully mediated the influences of sociability and prior experience on YouTube usage for learning.

The factors and their relationships identified in this study provide important implications for individual learners, platform designers, educators and other stakeholders who encourage the use of YouTube as a learning resource.

This study draws on a comprehensive theoretical perspective (i.e. social cognitive theory) to investigate the interplay of critical components (i.e. individual, environment and behavior) in YouTube's learning ecosystem. Personal factors not only directly influenced the extent to which people use YouTube as a learning resource but also mediated the effects of environmental and behavioral factors on the usage behavior.

This pilot study aims to investigate how parents use electronic resources to encourage children’s reading and learning interests through the 5E instructional model. Moreover, this study explores the public’s current electronic reading (e-reading) preferences, parents’ teaching process and the effectiveness of electronic resources in encouraging children to read and learn.

This study used a quantitative research method with a 5- to 10-min online survey based on the 5E instructional model. A total of 101 respondents participated in the survey.

Technology has changed the public’s current e-reading preferences. More than 65% of parent respondents preferred to use the electronic reading format for their children’s teaching and learning. Parents generally agreed on the teaching and learning effectiveness of using electronic resources, especially for engaging their children. However, the parents showed no significant gender differences.

This pilot study is a new attempt to use the 5E instructional model to quantitatively analyse the parenting process of using electronic resources to encourage children to read and learn, especially in an Asian context.