Journal of Information & Knowledge Management

The white-collar crime attorney is a lawyer who is competent in general legal principles and in the substantive and procedural aspects of the law related to upper-class financial crime. Based on a sample of 310 convicted white-collar criminals and their defence lawyers, this paper presents results from statistical analysis of relationships between crime characteristics and defence characteristics to predict lawyer fame. Statistical regression analysis was applied to the sample, where amount of crime money and years in prison represent crime characteristics, while number of client cases and lawyer income represent defence characteristics. About 91% of the variation in attorney fame is explained by these four independent variables.

Intangible resources, or intellectual capital, are currently known to be the drivers of economic growth. Today's society is known as the knowledge-based society. Knowledge is the main strategic resource that is capable in itself of generating new knowledge. Therefore, intangible resources have become the competitiveness base for any company, as their ownership provides the company with the opportunity to generate sustainable competitive advantage and increases the value of the company. One of the most important dimensions of intellectual capital is the relational capital (Prahalad and Ramaswany, 2000). Relational capital is defined as the knowledge embedded in the relationships with any stakeholder that influences the life of the organisation. Relationships with stakeholders are the necessary condition for building, maintaining and renewing resources, structures and processes over time, as firms can access critical and complementary resources through external relationships. Some authors [Prahalad, CK and V Ramaswamy (2000). Co-opting customer competence, Harvard Business Review, 78(1) 79–87.] suggest that the customer has become a new source of obtaining competitive advantage for the organisation. The customer and satisfaction have become the aim of companies as it is only way to attain sustainable performance. Companies that improve their relations with their clients, and the satisfaction of the latter, will therefore achieve a better business performance and will increase their value. There is a gap in the literature about this topic. Few works have been done in this aspect; for that, our research thus seeks to analyse whether customer satisfaction is reflected in the total value of the intangibles. A sample of the main Spanish companies, those quoted on the IBEX-35 (the main index of reference of the Spanish Stock Exchange, comprising the 35 companies with greatest liquidity on the Spanish Stock Exchange) are included and the relationship between the relational capital, measured by satisfaction of customers variable, and the total value of the company has been analysed. A positive relationship is then obtained between both variables, that is, improved customer satisfaction is positively associated with an increased business value, but that is not statistically significant.

This paper examines the role of knowledge management systems (KMS) for disaster planning and response in the context of social work in Malaysia. The research is focused on the client — the Malaysian Association of Social Workers (MASW), where a web-based system to support disaster management was developed and implemented. The research objectives required the researchers' direct involvement with the MASW. Canonical Action Research (CAR) was used as the research methodology. The process and outcomes of this action research initiative is presented based on the five-stage CAR approach, consisting of (i) problem diagnosis, (ii) action planning, (iii) intervention, (iv) evaluation and (v) learning outcomes. The evaluation of the system is supported by quantitative analysis driven by survey instrumentation. Our findings suggests that successful utilisation of the system in the context of MASW's efforts and roles in disaster management in Malaysia, is contingent upon issues such as acceptance of KMS, and availability of resources to maintain the system. Other issues such as clear definition of the role of Information Technology (IT) for disaster management and willingness to share knowledge are also vital in this regard.

This paper presents the findings of a long-term scientific research about the role of the after-sales services as a major player in both the supply and value chain. Through an investigation in an epistemological and ontological manner about the innovation and business processes, the organisational infrastructures and collaborations, and the information and communication technologies, the results show in an automotive context that these types of services are indeed involved in both the new product development process and in the operations management. Besides, as a part of the service sector, the after-sales service, in this context and this research, provides significant contributions to change management, since it is now a full actor in technology management and beyond.

With incessantly growing amount of information published over Web pages, the World Wide Web (WWW) has become prolific in the field of data mining research. The heterogeneous and semi-structured nature of Web data has made the process of automated discovery a challenging issue. Web Content Mining (WCM) essentially uses data mining techniques to effectively discover knowledge from Web page contents. The intent of this study is to provide a comparative analysis of Machine Learning (ML) techniques available in the literature for WCM. For analysis, the article focuses on issues such as representation techniques, learning methods, datasets used and performance of each method as a criterion. The survey observes that some of the traditional ML algorithms have been efficiently used to work on Web data. Finally, the paper concludes citing some promising issues for further research in this domain.

A knowledge asset has been increasingly recognised as the most valuable asset in organisations as it playing an enabling role in formulating a successful strategies and achieving a sustainable competitive advantage. However, to continuously capture, maintain and reuse the key information, and arbitrates the strategic knowledge assets, KM should be aligned with business process, organisations and IT. Therefore, the aim of the current study is to investigate the direct effect of the contextual factors such as IT infrastructure and skills, existence of CKO and knowledge sharing on the KM strategic alignment between KM and IS strategy (KMSA-IS) in the banking sector at Arabian Gulf countries. However, cultural factors such as openness to change, organisational structure and trust were examined to have indirect effect on KMSA-IS via the knowledge sharing. In addition, the impact of KMSA-IS on the organisational performance was examined. The results revealed that the contextual factors such as IT infrastructure and skills and existence of CKO as well as the knowledge sharing have shown a significant contribution on KMSA-IS. Organisational structure and trust however, revealed to have indirect impact on KMSA-IS via the knowledge sharing. Therefore, executive managers in the Arabian Gulf banking sectors should adopt new rules using flexible organisational culture, reforming and redesigning their organisational structure and incorporating an advanced IT in their operations for competitive advantage. Moreover, they need to establish an alignment between KM and IS strategy in order to move their KM systems in a direction that holds promise for long-lasting competitive advantage.

Knowledge sharing (KS) attitude is a psychological variable that affects individuals' decisions to share or hoard their knowledge. While attitude theory describes attitude as a multi-component construct, past research has overlooked the multidimensional structure of the attitude construct in KS contexts. Accordingly, this study focusses on KS attitude as a concept with cognitive, affective, and behavioural components. Data were collected from 89 participants involved in systems development projects to empirically test the expanded structure of KS attitude. The results provide strong support for the tertiary structure of KS attitude and demonstrate three conceptually and empirically distinguishable components of KS attitudinal. The results also show that the cognitive and affective components of KS attitude have significant effects on behavioural attitude to share knowledge. Several practical and research implications can be drawn from the results of this study.

This article discusses the effectiveness of knowledge sharing (KS) within communities of practice (CoPs) in a financial institution in South Africa. This was achieved through understanding the current state of KS within the CoPs, identifying critical factors for effectively sharing knowledge and thereafter determining reasons for a CoP not being effective in sharing knowledge. The results showed that there is still a long way to go to ensure the effectiveness of KS through CoPs. The CoPs within this financial institution are informal in nature, and therefore not necessarily given the attention that they deserve. Time used for CoPs is not maximised effectively, which reduces the chances of their effectiveness and improvement of productivity. Lack of effective system infrastructure to support KS is also a massive challenge for the CoPs, as is not having virtual Cops to reduce challenges faced in the use of face-to-face CoPs.

The article describes a solution to process large volumes of unstructured health social media data in a scalable fashion using the MapReduce framework. Our work is in the context of health informatics applications involving complex text and language processing as well as large resources such as ontologies, due to which the text processing of a single unit of text takes time. Even with a throughput of an order processing time of one second per unit, it takes over a week to process a million units, which is unacceptable. We present a solution where we take the processing to a MapReduce framework and achieve significant improvement in processing performance by dividing the processing across a cluster of processors. This paper describes the technical details of our work in terms of the design, modeling, and implementation of such an approach. We also present experimental results demonstrating the effectiveness of our approach.

Many methodologies, practices, techniques and tools have been suggested for process improvement, among them knowledge management and agile methodologies, which are the focus of this study. Systematic reviews published on knowledge management and agile methodologies have significantly contributed to detailed and deep discussions surrounding these issues. Nevertheless, we realised that there was a gap between these two areas that needed further clarification. Therefore, the objective of this study was to raise the main topics that emerge from knowledge management in agile methodologies. The research method used in this paper is based on a systematic review. We reviewed studies of knowledge management and agile methodologies, published in major software engineering journals and conference proceedings. The search strategy identified 2879 studies, of which 25 were selected as primary studies. The main topics were taken from these 25 works and, in order for them to be discussed; meta-analysis techniques were used to group these topics. The main discussion generated around these analyses was the preferential use of tacit knowledge, instead of explicit knowledge, and its influence on agile projects. This situation has implications for communication, human and social factors, software development cycle and artifacts, tools for knowledge management and knowledge representation forms.