Journal of Information & Knowledge Management

The purpose of this paper is to investigate how information systems are used by knowledge-intensive service firms and identify their effects on client–provider interactions. The paper uses data from case studies of service-related departments of three multinational firms. We identified several broad trends present in all three case companies. The required degree of knowledge specialisation, coupled with the ability to leverage knowledge created during service interactions resulted in high degrees of knowledge asymmetries between service provider and clients, which led to clients becoming the recipients of knowledge rather than co-creators. Differences between the cases related to the varying degrees to which information systems had been used to support service interactions. We therefore provide a model that outlines three key phases of activity. Individualisation involves the categorisation and location of tacit knowledge. This was followed by the codification and leveraging of service interactions through standardisation. Finally, the ability to provide alternative, more customised services, was achieved through modularisation. Increasing levels of specialisation of labour resulted in increasing knowledge asymmetries between service provider and client, reducing the need for client participation and co-production. Firms progress through three stages of development using information systems to support leveraging knowledge required for service delivery. The findings are based on case studies of departments within three multinational firms and would benefit from further empirical testing. The paper contributes to the existing literature in several ways. It focusses specifically on knowledge-intensive service firms, where labour is highly specialised. It gives information systems an explicit and significant role in examining how service elements may be leveraged. Finally, it outlines an exploratory model for managing this process.

Tacit knowledge (TK) is an intangible asset of the organisation and forms a major part of organisational knowledge. TK is personal, context-specific knowledge, difficult to formalise, record or articulate and it is stored in the heads of people. TK is part of informal learning components. TK has received growing attention and popularity due to its uniqueness and significant contributions to organisational performance. Despite its crucial role, the effects of TK on employee learning have often been neglected due to the notion of measurement difficulty. As a result, it poses challenges to capture both knowledge and expertise of individuals. This paper presents and discusses the construct validation of TK. Construct validity is a test that measures the intended construct and is particularly important in the social sciences-related disciplines. This paper deliberates how items development for TK is measured and tested for validation. Structural Equation Modelling (SEM) technique was employed for construct validation in terms of convergent and discriminant validities. Pre- and post-validations were also conducted to detect any validation discrepancies using exploratory factor analysis.

This paper extends a previous study that proposed an integrated model to test knowledge sharing (KS) motivation among information technology (IT) workers. While the previous study focussed on the differences in KS between internal and external IT workers, the perspective of the current paper is broader; it proposes additional hypotheses, and uses both inferential statistics and data mining techniques to detect further practical aspects of the integrated model findings. Because data mining techniques are useful in extracting patterns and gaining insights from data, they are implemented here alongside inferential statistics. The present study also looks into the employment-contract factor, to better capture the differences between internal and external IT workers. The study reveals that external workers score significantly lower than internal workers in almost every component of the integrated KS model. This gives rise to five practical implications of knowledge management (KM) and employment policies, including factors and practises that should be taken into consideration while employing external workers, to help motivate collaborative behaviour in IT departments.

This study aims to overview the research trends in Knowledge Management (KM) using a bibliometric and content analysis. Several research questions pertaining to the annual growth of KM publications, the key topics discussed, popular methodologies, country of origin, and citations analysis are posed and answered. In total, 475 articles published in the Journal of Information & Knowledge Management (JIKM) were retrieved from the Scopus bibliographical database. The results showed a relatively steady growth in the number of articles published in JIKM between 2002 and 2016. US scholars authored 21% of the articles published in JIKM, followed by those from India (almost 10%), Australia (8%), and the UK (7.5%). It is also noteworthy that scientific papers published in JIKM are referenced in highly cited journals of computer science, business, and library and information science. Topics such as knowledge discovery, taxonomy and ontology, and knowledge representation were the major KM research trends to arise from the current phenomena of “big data” and data analytics, as reflected in the subject matter of published works. A comparison between the counts for qualitative and quantitative research methodologies showed a clear tendency toward the latter, including questionnaires, while case studies, content analysis, and framework and conceptual papers also proved to be important for KM researchers.

The successful evolution of money and payment platforms in today’s world requires consumer adoption, which in turn requires access to knowledge about developing financial products. This is particularly the case in developing country contexts where the participation in publicly accessible financial payment platforms has been lauded as a means through which low income people can access financial resources, save, and build wealth. Using a qualitative approach and the knowledge gap hypothesis as a conceptual framework, the current study explores knowledge patterns and knowledge gaps in the context of two financial transitions in Ghana, West Africa. While general patterns in acquired knowledge were observed, income levels appeared to shape observed levels of knowledge. Implications for financial inclusion are discussed.

This paper describes an efficient algorithm for formal concepts generation in large formal contexts. While many algorithms exist for concept generation, they are not suitable for generating concepts efficiently on larger contexts. We propose an algorithm named as HaLoopUNCG algorithm based on MapReduce framework that uses a lightweight runtime environment called HaLoop. HaLoop, a modified version of Hadoop MapReduce, suits better for iterative algorithms over large datasets. Our approach uses the features of HaLoop efficiently to generate concepts in an iterative manner. First, we describe the theoretical concepts of formal concept analysis and HaLoop. Second, we provide a detailed representation of our work based on Lindig’s fast concept analysis algorithm using HaLoop and MapReduce framework. The experimental evaluations demonstrate that HaLoopUNCG algorithm is performing better than Hadoop version of upper neighbour concept generation (MRUNCG) algorithm, MapReduce implementation of Ganter’s next closure algorithm and other distributed implementations of concept generation algorithms.

This paper presents the results of a research work carried out in order to develop a novel gaming model for formative knowledge assessment (FKA). The benefits of FKA are well acknowledged by educators as it aids for better learning. As FKA is more frequent, the students’ willingness to take frequent assessments is poor. Often the students expressed that they felt uncomfortable and this resulted in lack of active participation. These are considered as major challenges to be addressed. Hence, this research aimed to find a way to make the assessments interesting. Based on the positive responses for game-based learning, a theoretical model that integrates the principles of extensive games (EGs) and concept map (CM), namely concept tree game (CTG), has been defined and developed. Further, a qualitative research has been performed to evaluate the impact of the FKA model. Major data gathering techniques used in this work were a class test, proposed FKA method, participant observation, survey and focussed team interview. The data were analysed statistically and the results revealed that it has been effective and useful for educators in assessing the knowledge of students and for students, it aided them to know where they stand and helped them to learn effectively.

The impact of computer self-efficacy (CSE) on acceptance and utilisation of enterprise resource planning (ERP) systems is widely recognised in the literature. However, past ERP adoption research has mostly used CSE as a universal and general computer cognitive variable across the computing domain. While CSE is a multifaceted concept which can be conceptualised and assessed at the general computer or application-specific level, past studies did not differentiate between the general and application self-efficacy belief in examining the acceptance of ERP systems. This study aims to address this issue and make a clear distinction between general computer and application (ERP) self-efficacy beliefs and examines the effects of both types of efficacy beliefs on known determinants of acceptance and use of ERP systems. The results provide strong support for the effects of self-efficacy beliefs at the ERP level. The results show that the effects of CSE beliefs at the ERP level are stronger than those of general CSE beliefs on ERP acceptance behaviour.

The study gives an overview and critique and identifies literature on university knowledge management (KM) research to ascertain gaps for further investigation. A systematic search of articles about university KM research in the Web of Science and Scopus was scrutinised using pre-defined criteria. After screening, 46 articles that met the selection criteria were reviewed. Findings revealed that the academic aspects are over-explored with some KM themes, whereas the non-academic university KM is under-explored. Moreover, the reviewed literature showed that the university KM cut across significant countries of the world with a large concentration of the research articles in USA, UK, and Malaysia. The study proffered ways of advancing university KM research agenda in the future by considering the under-explored contexts for more meaningful contributions to KM practice and theory development.

The clustering is an important data analysis technique. However, clustering high-dimensional data like documents needs more effort in order to extract the richness relevant information hidden in the multidimensionality space. Recently, document clustering algorithms based on metaheuristics have demonstrated their efficiency to explore the search area and to achieve the global best solution rather than the local one. However, most of these algorithms are not practical and suffer from some limitations, including the requirement of the knowledge of the number of clusters in advance, they are neither incremental nor extensible and the documents are indexed by high-dimensional and sparse matrix. In order to overcome these limitations, we propose in this paper, a new dynamic and incremental approach (CS_LSI) for document clustering based on the recent cuckoo search (CS) optimization and latent semantic indexing (LSI). Conducted Experiments on four well-known high-dimensional text datasets show the efficiency of LSI model to reduce the dimensionality space with more precision and less computational time. Also, the proposed CS_LSI determines the number of clusters automatically by employing a new proposed index, focused on significant distance measure. This later is also used in the incremental mode and to detect the outlier documents by maintaining a more coherent clusters. Furthermore, comparison with conventional document clustering algorithms shows the superiority of CS_LSI to achieve a high quality of clustering.

The growth in the availability of number of research journal articles in a digital form is explosive. So more and more researchers have turned towards the publications in digital form, download and maintain them in their standalone personal computers. This increase in a number of publications in digital form has made it difficult for researchers, who have to face the burden of managing, linking and searching the research journal articles on their personal computers. Many reference manager softwares like RefWorks, Zotero, EndNote, and Mendeley are available in the market, which provide an easy way for a researcher to organize and manage the research journal articles. These above said reference managers take the help of extracted basic metadata such as Title, Author, Abstract, etc. to organize the journal articles and maintain a link between them. But the essential feature of “reference linking” is not focused. Reference linking is a feature where a cited article can be tracked from the article citing it, from a large volume of journal article collection. This feature is mostly available for online, but not for offline standalone personal computers. This paper addresses this problem in detail, explores the existing reference linking features which exist for online scholarlty literature, presents the algorithms for retrieving the metadata along with references at the end of each journal article and a way for storing and linking them to the full texts present in the reference management software that works on a standalone personal computer, using semantic technology. A reference management software “sodhanaRef” which includes the reference linking feature and semantic search has been built along with an explanation about its architecture.

Ever growing need for innovation has become a big challenge for organisations. Consequently, Knowledge management (KM) is gaining importance in the business world as one of the critical enablers for innovation. This study answers the question whether KM philosophy helps organisations develop capabilities to induce innovation, especially in the context of developing economies. Based on the empirical evidence from the service sector of Pakistan, we show that knowledge acquisition, knowledge dissemination, and responsiveness to knowledge significantly influence an organisation’s capabilities to produce innovative outputs. We also bring to the fore a mutual relationship of KM components with each other, thereby highlighting that knowledge acquisition is important for knowledge dissemination which in turn determines an organisation’s responsiveness to knowledge. We used structural equation modelling (SEM) to develop a model among three endogenous KM factors and one exogenous factor, innovation. Our findings show a significant relationship of all variables, though the strength of each varies, hence confirming the hypothesis that KM, if implemented effectively, improves organisation’s ability to innovate.