Knowledge Management for Public Administrations: Technical Realizations of an Enterprise Attention Management System

The improvement of governments’ efficiency has gained great importance and validity especially in the current times of economic downturn. E-Government constitutes the most contemporary techno-managerial proposition in the track of possible interventions. The paper addresses, more specifically, empowerments necessitated by Public Administration (PA) organizations. Anchored on the needs of three real-life cases, the paper describes the conception and the realization of an IT artefact together with its methodological appeals aiming at improving information access and delivery and thus PAs’ decision making capacity. Our proposition constitutes a novel approach for managing users’ attention in knowledge intensive organizations which goes beyond informing a user about changes in relevant information towards proactively supporting the user to react on changes. The approach is based on an expressive attention model, which is realized by combining ECA (Event-Condition-Action) rules with ontologies. The technical realizations described in the paper constitute the underlying infrastructure of an Enterprise Attention Management System

A theory-grounded framework of Open Source Software adoption in SMEs

This is a post-peer-review, pre-copyedit version of an article published in European Journal of Information Systems. The definitive publisher-authenticated version Macredie, RD and Mijinyawa, K (2011), "A theory-grounded framework of Open Source Software adoption in SMEs", European Journal of Informations Systems, 20(2), 237-250 is available online at: http://www.palgrave-journals.com/ejis/journal/v20/n2/abs/ejis201060a.html.The increasing popularity and use of Open Source Software (OSS) has led to significant interest from research communities and enterprise practitioners, notably in the small business sector where this type of software offers particular benefits given the financial and human capital constraints faced. However, there has been little focus on developing valid frameworks that enable critical evaluation and common understanding of factors influencing OSS adoption. This paper seeks to address this shortcoming by presenting a theory-grounded framework for exploring these factors and explaining their influence on OSS adoption, with the context of study being small- to medium-sized Information Technology (IT) businesses in the U.K. The framework has implications for this type of business – and, we will suggest, more widely – as a frame of reference for understanding, and as tool for evaluating benefits and challenges in, OSS adoption. It also offers researchers a structured way of investigating adoption issues and a base from which to develop models of OSS adoption. The study reported in this paper used the Decomposed Theory of Planned Behaviour (DTPB) as a basis for the research propositions, with the aim of: (i) developing a framework of empirical factors that influence OSS adoption; and (ii) appraising it through case study evaluation with 10 U.K. Small- to medium-sized enterprises in the IT sector. The demonstration of the capabilities of the framework suggests that it is able to provide a reliable explanation of the complex and subjective factors that influence attitudes, subjective norms and control over the use of OSS. The paper further argues that the DTPB proved useful in this research area and that it can provide a variety of situation-specific insights related to factors that influence the adoption of OSS

Reflecting on the usability of research on culture in designing interaction

The concept of culture has been attractive to producers of interactive\ud systems who are willing to design useful and relevant solutions to users\ud increasingly located in culturally diverse contexts. Despite a substantial body of\ud research on culture and technology, interaction designers have not always been\ud able to apply these research outputs to effectively define requirements for\ud culturally diverse users. This paper frames this issue as one of understanding of\ud the different paradigms underpinning the cultural models being applied to\ud interface development and research. Drawing on different social science theories,\ud the authors discuss top-down and bottom-up perspectives in the study of users‟\ud cultural differences and discuss the extent to which each provides usable design\ud knowledge. The case is made for combining bottom-up and top-down perspectives\ud into a sociotechnical approach that can produce knowledge useful and usable by\ud interaction designers. This is illustrated with a case study about the design of\ud interactive systems for farmers in rural Kenya

Challenges to describe QoS requirements for web services quality prediction to support web services interoperability in electronic commerce

Quality of service (QoS) is significant and necessary for web service applications quality assurance. Furthermore, web services quality has contributed to the successful implementation of Electronic Commerce (EC) applications. However, QoS is still the big issue for web services research and remains one of the main research questions that need to be explored. We believe that QoS should not only be measured but should also be predicted during the development and implementation stages. However, there are challenges and constraints to determine and choose QoS requirements for high quality web services. Therefore, this paper highlights the challenges for the QoS requirements prediction as they are not easy to identify. Moreover, there are many different perspectives and purposes of web services, and various prediction techniques to describe QoS requirements. Additionally, the paper introduces a metamodel as a concept of what makes a good web service

Global board games project:a cross-border entrepreneurship experiential learning initiative

Entrepreneurship training and development in the context of higher education has grown tremendously over the past four decades. What began as offerings of a handful of courses aimed primarily at business planning and small business management has evolved into over 3.000 higher education institutions around the world offering degree programs and concentrations in entrepreneurship on both undergraduate and graduate levels (Morris, Kuratko and Cornwall, 2013). Universities – particularly in the USA, UK and EU – have invested into developing entrepreneurship curricula but also extra-curricular programs and infrastructure aimed at supporting enterprise development. It is consensus among educators that entrepreneurship can be taught (Kuratko, 2005). Indeed, entrepreneurship education research has become a field in its own right (Fayolle, Gailly and Lassas‐Clerc, 2006; Pittaway and Cope, 2007; Penaluna, Penaluna and Jones, 2012; Fayolle, 2013; Fayolle and Gailly, 2015; Pittaway et al., 2015; Nabi et al., 2017). As literature indicates, entrepreneurship education can have an important impact on a variety of outcomes, including entrepreneurial intentions and behaviours. Intentions are a motivation to engage in certain behaviour that is geared towards venture creation (Gibb, 2008, 2011) as well as recognition and exploitation of opportunities (Shane and Venkataraman, 2000). Moreover, research has also identified the impact of entrepreneurship education on more subjective indicators such as attitudes (Boukamcha, 2015), perceived feasibility (Rauch and Hulsink, 2015), and skills and knowledge (Greene and Saridakis, 2008). Recently, the literature on the best practices in entrepreneurship education has centred on the importance of experiential learning allowing students to create knowledge from their interactions with the environment (Kolb, 1984). The key to effective experiential learning is engaging students individually and socially in a situation that enables them to interact with elements of the entrepreneurial context thus moving them away from text-driven to action-driven learning mode (Morris, Kuratko and Cornwall, 2013). Increasingly, digital technologies have been leveraged to create a learning environment that provides opportunities for experiential learning (Onyema and Daniil, 2017). This chapter provides findings of a study related to the development and implementation of a collaborative, digitally supported simulation project aimed at enhancing entrepreneurial social skills in an international context

Weak signal identification with semantic web mining

We investigate an automated identification of weak signals according to Ansoff to improve strategic planning and technological forecasting. Literature shows that weak signals can be found in the organization's environment and that they appear in different contexts. We use internet information to represent organization's environment and we select these websites that are related to a given hypothesis. In contrast to related research, a methodology is provided that uses latent semantic indexing (LSI) for the identification of weak signals. This improves existing knowledge based approaches because LSI considers the aspects of meaning and thus, it is able to identify similar textual patterns in different contexts. A new weak signal maximization approach is introduced that replaces the commonly used prediction modeling approach in LSI. It enables to calculate the largest number of relevant weak signals represented by singular value decomposition (SVD) dimensions. A case study identifies and analyses weak signals to predict trends in the field of on-site medical oxygen production. This supports the planning of research and development (R&D) for a medical oxygen supplier. As a result, it is shown that the proposed methodology enables organizations to identify weak signals from the internet for a given hypothesis. This helps strategic planners to react ahead of time