Journal of Information & Knowledge Management

The software industry being highly resource-oriented tries to ensure that knowledge residing in the minds of the employees is effectively utilised for leveraging core business competencies. Therefore, providing effective knowledge management systems (KMSs) to utilise this knowledge for optimising business processes has become crucial for enterprises to stay competitive. This paper attempts to assess the effectiveness of KMS implementations from a knowledge workers’ perspective via six dimensions of the Jennex and Olfman (J&O) KMS success model. Quantitative data was collected through a web-based survey questionnaire from knowledge workers in 25 Indian software companies. Statistical analysis of the study’s model was conducted using SmartPLS® (version 2.0.M3) software for assessment of both measurement and structural models. The empirical analysis of the model’s hypotheses indicated that a knowledge worker’s intent to use a KMS is significantly dependent on Service and Knowledge/Information Quality dimensions of J&O KMS success model. This paper implies that the J&O KMS success model seems to have adequate predictive power for most implied variables with the exception of System Quality. The J&O KMS success model from a practical point of view offers a means for organisations to evaluate and predict the effectiveness of KMS implementations. The results produced in this study may allow KM practitioners to know more about the levers that help to improve their KMS and thus suitably prioritise their investment plans accordingly.

There are many studies discussing how knowledge management and market orientation (MO) are positively related to innovation, but an examination of the impact of the knowledge management processes (KMP) — as we conceptualize the four in this study — and MO on the innovation capability of organisations which in turn impact organisational performance has never been done. Hence, this study formulates a comprehensive conceptual framework which encompasses KMP (knowledge creation, intra-organisational knowledge sharing and application, external knowledge acquisition, and knowledge storage and documentation), MO (customer orientation, competitor orientation and inter-functional coordination), innovation capability (product, process, marketing and organisational innovation), and organisational performance (product quality, operational performance and financial performance). Then empirically test the relationships among the study models with the focus on the mediating role of innovation capability. The design of the study is based on a survey of 210 Jordanian manufacturing and service organisations. The sample of this study encompasses the mid-level managers of the organisations. About 440 self-administered questionnaires were distributed among the respondents. Confirmatory factor analysis is undertaken to assess statistically the validity of the study measures. Then the structural equation modelling (SEM) path analysis is used to assess the structural relationship of KMP, MO with innovation capability, and organisational performance. The results of the study reveal that engagement in KMP and MO can lead to better innovation capability in the organisations which in turn can lead to better organisational performance. The results we observe concerning this sample of companies may not be applicable to a greater population of companies from other countries with a different technological base or to specific subsectors of the manufacturing industry (e.g. the food industry). Moreover, the study represents only snapshots since it utilized self-administered questionnaires which also have no qualitative data. For the practicing managers intending to increase the rate of innovation in their firms, this means that KMP and MO are important activities to master. Additionally, managers should put additional emphasis on innovation as it is an important element for achieving improved overall firm’s performance and sustainable competitive power.

This paper analyses the impact of the use of electronic resources and Health InterNetwork Access to Research Initiative (HINARI) services for medical research libraries in Bangladesh, emphasising the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). Purposeful use of e-resources, time and cost-saving benefits, research impact, and challenges of using HINARI are discussed. The basic study was conducted at icddr,b in January–February 2014, using a mixed methodology, combining qualitative and quantitative approaches, including a background literature review, usage data shared from the HINARI secretariat at the World Health Organization (WHO), questionnaires, personal observations, and interviews with staff members of icddr,b. Findings revealed that icddr,b is the heaviest user of HINARI (a major source of public health and medical e-resources) in Bangladesh, with demonstrable increases of health research journal articles after introducing HINARI in 2003.

Organizing web information is an important aspect of finding information in the easiest and most efficient way. We present a new method for web document clustering called WeDoCWT, which exploits the discrete wavelet transform and term signal, to improve the document representation. We studied different methods for document segmentation to construct the term signals. We used two datasets, UW-CAN and WebKB, to evaluate the proposed method. The experimental results indicated that dividing the documents into fixed segments is preferable to dividing them into logical segments based on HTML features because the web pages do not have the same structure. Mean TF–IDF reduction technique gives the best results in most cases. WeDoCWT gives $F$-measure better than most of the previous approaches described in the literature. We used Munkres assignment algorithm to assign each produced cluster to the original class in order to evaluate the clustering results.

The automatic bug severity prediction will be useful in prioritising the development efforts, allocating resources and bug fixer. It needs historical data on which classifiers can be trained. In the absence of such historical data cross project prediction provides a good solution. In this paper, our objective is to automate the bug severity prediction by using a bug metric summary and to identify best training candidates in cross project context. The text mining technique has been used to extract the summary terms and trained the classifiers using these terms. About 63 training candidates have been designed by combining seven datasets of Eclipse projects to develop the severity prediction models. To deal with the imbalance bug data problem, we employed two approaches of ensemble by using two operators available in RapidMiner: Vote and Bagging. Results show that k-Nearest Neighbour (k-NN) performance is better than the Support Vector Machine (SVM) performance. Naive Bayes f-measure performance is poor, i.e. below 34.25%. In case of k-NN, developing training candidates by combining more than one training datasets helps in improving the performances (f-measure and accuracy). The two ensemble approaches have improved the f-measure performance up to 5% and 10% respectively for the severity levels having less number of bug reports in comparison of major severity level. We have further motivated the paper with a cross project bug severity prediction between Eclipse and Mozilla products. Results show that Mozilla products can be used to build reliable prediction models for Eclipse products and vice versa in case of SVM and k-NN classifiers.

Implementation of Knowledge Management (KM) brings significant changes at various levels of an organisation. Knowledge sharing is one of the aspects that plays a significant role in the success of KM. This paper uses empirical research. It will analyse the applicability of KM as a new change in an organisation, while taking into account the aspects influencing knowledge sharing. The research identifies the aspects related to knowledge sharing which will be assessed. This case study has been realised by using a questionnaire at an Iranian research organisation. The five factors of trust, commitment, job satisfaction, learning and organisational communication have been identified and studied as aspects affecting knowledge sharing. The results show that during the implementation of KM there would be a lot of resistance from people. While people seem to welcome this change and find it effective in organisational growth, the assessment shows that there is no adequate preparation in terms of knowledge sharing and KM.

The purpose of this study was to assess the impact of Information and Communication Technology (ICT) on research activities in selected institutes of the Council for Scientific and Industrial Research (CSIR). The research methodology adopted for this study was the case study approach, specifically multiple cases. This study employed structured questionnaires and semi-structured interviews as a data collection instrument to collect data from respondents in the five selected research institutes of CSIR. The study shows that ICTs have a positive impact on research activities. ICT tools have been proven to be very helpful to researchers and other non-core staff of CSIR in finding needed information quickly and easily, expedition in the research process, improvement in job performance and have also helped in information access, management and communication. The study also identified lack of training in ICT, insufficient computer hardware and suitable software applications, lack of competent Information Technology (IT) professionals, non-existent budgetary allocations for ICT and lack of required Internet bandwidth as the major hindrances faced by the researchers and senior staff in the CSIR. The study recommended improvement in ICT infrastructure, appointment of competent IT personnel and proper training and guidance for optimum utilisation of ICT-based technologies.

Knowledge is the primary asset of today’s organisations; thus, knowledge management has been focused on discovery, representation, modification, transformation, and creation of knowledge within an enterprise. A knowledge map is a knowledge management tool that makes organisational processes more visible, feasible, and practicable. It is a graphical representation of decision-related information. What happens, how various events can be managed, and why they happened: all can be demonstrated very precisely by a well-designed knowledge map. There are diverse knowledge-related roles; for example, each university dean’s office — as an instance of a knowledge-based organisation — usually relies upon their institutional memory to make daily decisions. However, utilising a knowledge map greatly facilitates any individual’s or group’s decision-making process, by proposing or establishing key required information. In this study, two important managerial roles — Associate Deans of Research and Education — were selected; then we reviewed their key managerial decisions and proposed three different techniques for supporting their decisions. The chief superiority of the approach offered here was in the creation of role-based knowledge maps, including an expertness map and a collaboration map for the Associate Dean of Research, which were formed using clustering, taxonomy formation, and information retrieval methods. A third map was created for the Associate Dean of Education, including a Bayesian reasoning map based on an Improved PC (IPC) algorithm, which learned the structure and the parameters of a Bayesian network to describe decision-making in the domain of education. To evaluate the proposed approaches, structural and functional evaluation measures and standard datasets (in the available cases) were chosen. The results found that the approaches were comparable to the selected benchmarks within the real data; even after considering the challenging nature of the real data, which included problems such as incomplete and unclean data extracted from the University of Tehran’s education and research management information systems.

The ongoing transition to the patient-centred healthcare paradigm suggests that patients adopt an active role in managing their health conditions. As a result, the Internet is becoming an important source of health-related information. Internet-based health support groups allow patients to access diverse information relevant to their particular situation by participating in online discussions. The quality of such information may have effects on the patients’ health outcomes. The purpose of the present study was to investigate the effects of knowledge construction in health support group online discussions on perceived information quality, information quality from the perspective of information consumers, and on information integrity, that is, validity from the point of view of the current state of scientific knowledge. It was hypothesised that knowledge construction results in better perceived information quality and in higher information integrity. A health support group online discussion site devoted to weight management was used as a source of data. Quantitative content analysis was used with a discussion thread as a unit of analysis. Based on the findings, the study suggested that moderators of health support group online discussions should promote explicitation or lower level knowledge construction by encouraging clarifications and refinements of health-related recommendations. Moreover, participation of qualified health practitioners is desirable to promote health-related behaviours based on evidence-based knowledge and to expose recommendations that have uncertain or even dangerous effects.