Journal of Information & Knowledge Management

This study aimed to analyse the implementation form and the maturity level of knowledge management (KM) and formulate recommendations of KM implementation strategies for improvement of academic services at universities in Indonesia. The analysis of the KM implementation was conducted at four top universities in Indonesia based on the ranking of the Indonesian Ministry of Research, Technology and Higher Education 2016, viz., ITB, UGM, UI and IPB. Primary data were obtained from the library of ITB, UGM, UI, and IPB and from 510 academicians of IPB, while secondary data was obtained by content analysis. The result showed that the top four universities in Indonesia have had the basic infrastructure for KM implementation; their management have been actively participating in the promotion of KM initiatives by articulating KM strategy and providing budgetary allocations and rewards system. Several pilot projects were undertaken to develop KM application into a higher level. The utilisation of KM application has not been optimal; knowledge sharing has not yet become a culture. The KM maturity implementation in the library of ITB, UGM, UI and IPB is at the third level. The result of the measurement of interoperability maturity level of seven IPB academic service applications just on the average reaches third level and is still in the stage of data integration. The KM implementation strategies that were recommended to improve the academic services at IPB, among other things, the reinforcement of the role of chief knowledge officer, the promotion of knowledge sharing culture with the knowledge repository optimisation, the formation of a community of practices, the development of knowledge portal, the optimisation of e-learning system and the improvement of rewards system.

Many studies focus on the effect of a source’s expertise, but little attention has been paid to what happens in the event of a misalignment between who is knowledgeable (cognitive expertise) and who is regarded as being knowledgeable (social expertise). The emphasis on expertise alignment in this study suggests the importance not of simply having a transactive memory system, but rather, of having an accurate transactive memory system in place. Using experimental data from a sample of 134 participants, the results indicate that the knowledge transfer is greater in the source’s cognitive-social expertise alignment than in the misalignment, but the source’s cognitive expertise could be a more significant criterion for the knowledge transfer in the expertise misalignment. In the view of source-recipient dynamics, knowledge transfer is greater in the low cognitive expertise gap condition than in the high cognitive expertise gap condition. The results contribute to the understanding of the role of a source’s expertise in knowledge transfer from a socio-cognitive perspective.

A typical predictive approach in data mining that produces If-Then knowledge for decision making is rule-based classification. Rule-based classification includes a large number of algorithms that fall under the categories of covering, greedy, rule induction, and associative classification. These approaches have shown promising results due to the simplicity of the models generated and the user’s ability to understand, and maintain them. Phishing is one of the emergent online threats in web security domains that necessitates anti-phishing models with rules so users can easily differentiate among website types. This paper critically analyses recent research studies on the use of predictive models with rules for phishing detection, and evaluates the applicability of these approaches on phishing. To accomplish our task, we experimentally evaluate four different rule-based classifiers that belong to greedy, associative classification and rule induction approaches on real phishing datasets and with respect to different evaluation measures. Moreover, we assess the classifiers derived and contrast them with known classic classification algorithms including Bayes Net and Simple Logistics. The aim of the comparison is to determine the pros and cons of predictive models with rules and reveal their actual performance when it comes to detecting phishing activities. The results clearly showed that eDRI, a recently greedy algorithm, not only generates useful models but these are also highly competitive with respect to predictive accuracy as well as runtime when they are employed as anti-phishing tools.

This study explores students’ acceptance of e-learning technology in Jordanian higher educational institutions. A paucity of studies that were conducted in individual institutions indicated that different cultural perspectives and resistance to change are overlaying the wide adoption of e-learning and influencing users’ perceptions pertaining the technology usefulness and/or ease of use. Our study utilises the technology acceptance model (TAM) and explores the influence of the main antecedents of accepting this technology from users’ perspectives, that is, perceived usefulness (PU) and perceived ease of use (PEU) in order to reveal the country’s readiness to adopt this technology and move from individual innovations to institutional standards. The results obtained using a survey-based methodology from three main public and private institutions distributed in multiple geographical areas show that the actual behaviour of usage is influenced by behavioural intention (BI), which is directed by PU, PEU, and attitude. Based on these results, multiple recommendations pertaining to cultural perspectives and educational institutions readiness are proposed and implications of the study are discussed.

Online reviews are the most valuable sources of information about customer opinions and are considered the pillars on which the reputation of an organisation is built. From a customer’s perspective, review information is key to making a proper decision regarding an online purchase. Reviews are generally considered an unbiased opinion of an individual’s personal experience with a product, but the underlying truth about these reviews tells a different story. Spammers exploit these review platforms illegally because of incentives involved in writing fake reviews, thereby trying to gain an advantage over competitors resulting in an explosive growth of opinion spamming. The present study analyses and categorises the available literature on opinion spamming according to three detection targets: (1) opinion spam, (2) opinion spammers, and (3) collusive opinion spammer groups. The study further highlights and divides opinion spamming into three types based on textual and linguistic, behavioural, and relational features. Moreover, several state-of-the-art machine-learning techniques for opinion spam detection have also been discussed in the study. It concludes with a summary of the research articles on opinion spam detection and some interesting results to assist researchers for further exploration of the domain.

The effectiveness of information technology (IT) depends on its embeddedness into its contingent context. Thus, enabling adequate knowledge management (KM) system design requires awareness of the characteristics of the knowledge that is created. Since related insights are missing, we explore what software developers learn on their projects by conducting interviews based on the Repertory Grid Technique. We assess the characteristics of the identified knowledge and skills and derive suggestions for KM system design accordingly. Our study gives rise to challenge the common idea that KM design should be chosen according to the type of knowledge (explicit versus tacit) to be managed. Incorporating further knowledge characteristics (task domain and volatility of knowledge), our results indicate that organisations should implement a codification strategy or a strategy between codification and personalisation, depending on the knowledge at hand.

The large and constantly growing amounts of available text documents hold great potential for the exploration of knowledge. However, in the light of the vast quantity and variety of available documents, one fact should not be forgotten: the results of a knowledge discovery in texts are only as good as the underlying document collection. That is why analysts have to ensure that document collections adequately represent the specific area under examination and thereby to minimise the bias and to maximise the generalisable nature of the knowledge brought to light. Surprisingly, knowledge management research has barely paid any attention to the problems of such a document quality assessment and rigorous document selection. This paper addresses that research gap and makes two contributions: In the first step, building on a cross-disciplinary exchange with social research, development of a framework for the quality assessment and collection of documents. This artefact provides concrete guidance for compiling suitable, high-quality document collections and makes a contribution to ensuring “document collection quality” within the context of knowledge discovery in texts. In the second step, the framework is evaluated in a practical demonstration. In this context, the demonstration also exemplifies how different document collections influence the results of knowledge discoveries.

The purpose of this paper is to investigate how information and communication technologies are used for service standardisation, customisation, and modularisation by knowledge-intensive service firms through the development and empirical validation of a knowledge-based framework. This paper uses 59 in-depth interviews, observational data, and document analysis from case studies of three service-related departments in high-technology, multinational knowledge-intensive business services (KIBSs). Prior research does not conceptualise the relationships between service customisation, standardisation and modularisation. This paper seeks to overcome this gap by integrating insights from research on the role played by both knowledge and information and communication technologies (ICTs) to construct and validate a framework to deal with this gap. It outlines the implications for service firms’ use of ICT to deal with increasing knowledge intensity as well as indicating the circumstances under which service knowledge is best customised, standardised and modularised. Further testing in other industries would prove useful in extending the usefulness and applicability of the findings. The originality of the paper lies in developing and validating the first framework to outline the relationship between how service knowledge is customised, standardised or modularised and indicating the associated issues and challenges. It emphasises the role of knowledge and technology. The value of this framework increases as more firms deal with increasing knowledge intensity in the services they provide and in their use of ICTs to reap the benefits of appropriate knowledge reuse.

The aim of the study is to determine the impact of online learning activities on learning outcomes of students who participated in the blended learning course, focusing specifically on skill-based courses. The learning outcomes or results of a learner are usually measured by scores, knowledge or skills gained in the course. In blended learning courses, the learning outcomes can be assessed according to many criteria. In this study, interactive activities such as teacher–student interaction, student–student interaction, student–content interaction and student–technology interaction are considered. Undergraduate students participated in the blended learning course in which formative assessment was used to evaluate student learning outcomes by the combination of different learning activities through a learning management system. The quantitative results obtained by using regression analysis of data from the system showed that the students who effectively interacted with learning activities in the course have better results. Quantitative analytical results indicated that student–student interaction has a greater impact on student learning outcomes. These learning activities are used for interactive activities as suggestions for teachers to design and implement learning activities for blended learning courses.

Objectives: This study aimed at exploring the factors that motivated and hindered the medical students to share their knowledge with each other. Method: A survey questionnaire was used to collect the data from 260 medical students selected by proportionate stratified simple random sampling technique from University College of Medicine of The University of Lahore, Pakistan. Results: A total of 252 (96.9%) questionnaires were received from respondents. Of the seven purposes for knowledge sharing (KS) (if grades/exams do matter), two obtained a maximum mean score of 3.88; while one got 4.02 if grades/exams do not matter. Four of the eight motivational factors got top mean scores of 3.59 to 3.88. Of the 11 barriers, “People only share with those who share with them” obtained a highest mean score (3.81). Conclusions: Major findings showed that medical students discussed exam-related matters and enhanced their own understanding by KS. Class participation and group discussion stimulated them to share knowledge with their peers. They considered give-and-take a big barrier of KS. The overall opinions of female students scored higher than males.

Organisational collective knowledge plays an important role in innovation and also provides a competitive advantage. Human Capital (HC) is the sum total of intelligence found in individual human beings and consists of individual’s learning and education, experience and expertise, and personal creativity and innovation. Researchers believed that only innovative organisations are going to survive in future in the knowledge-economy. The present research is aimed to study the impact of HC on Innovative Capability (IC) of a financial institution. This impact is empirically tested through a cross-sectional survey in which randomly selected 170 participants of a commercial bank verified the four proposed hypotheses. The findings endorsed four aspects of the study. First, HC was influenced by bank officers’ skills/competence, knowledge, abilities, personal mastery and their transformational leadership role. Second, IC of the bank has been found influenced by support for innovation available to bank officers, bank officers’ innovative behaviour, and tolerance for difference available to them. Third, the bank officers’ leadership role, personal mastery, and their abilities were significant and positively related to bank’s IC, whereas, bank officers’ knowledge was significant but negatively related to bank’s IC. Finally, the fourth finding of the study suggested that bank’s collective HC is having a positive relationship with bank’s IC. The study would help managers to identify important HC elements suitable for financial organisations that could have an impact on its IC.