Social Media Roadmaps. Exploring the futures triggered by social media.

Social media refers to a combination of three elements: content, user communities and Web 2.0 technologies. This foresight report presents six roadmaps of the anticipated developments of social media in three themes: society, companies, and local environment. One of the roadmaps, the meta-roadmap, is the synthesis of them all. The society sub-roadmap explores societal participation through communities. There are three sub-roadmaps relating to companies: interacting with companies through communities, social media in work environment, and social media enhanced shopping. The local environment sub-roadmap looks at social media in local environment. The roadmapping process was carried out through two workshops at VTT. The results of the report are crystallized into five main development lines triggered by social media. First development line is transparency referring to its increasing role in society, both with positive and negative consequences. The second development line is the rise of ubiquitous participatory communication model. This refers to an increase of two-directional and community-based interactivity in every field, where it has some added value. The third development is reflexive empowerment. This refers to the role of social media as an enabler of grass-root community collaboration. The fourth development line is the duality personalization/fragmentation vs. mass effects/integration. Personalization /fragmentation emphasises the tailoring of the web services and content. This development is counterweighted by mass effects/integration, like the formation of super-nodes in the web. The fifth development line is the new relations of physical and virtual worlds. This development line highlights the idea that practices induced by social media, e.g. communication, participation, co-creation, feedback and rating, will get more common in daily environment, and that virtual and physical worlds will be more and more interlinked.</p

The impact of enterprise information management capability on sustainable competitive advantage

In today’s economic environment, intense competition in the corporate world has prompted organizations to focus on creating and maintaining a sustainable competitive advantage (SCA). The purpose of this study is to explore the impact of enterprise information management capability (EIMC) on SCA. This study focuses on EIMC as An essential organizational dynamic capability and empirically examines the relationship between EIMC and SCA, both directly and indirectly, via two mediators: knowledge management (KM) and total quality management (TQM). This study used the theory of dynamic capability (DC) as the theoretical framework. Four constructs (EIMC, KM, TQM, and SCA) were developed and nine research hypotheses were examined. A mixed methods research design was used to collect primary data. The data was collected from twelve (12) semi-structured interviews with twelve (12) decision-makers from different organizations in the UAE. In addition, an online cross-sectional survey produced 144 responses from middle-level managers in UAE organizations. The survey data was analyzed using a partial least squares (PLS) approach to structural equation modeling. The results of the PLS measurement model suggest that the items used to measure the constructs were valid and reliable, and the results of the structural equation model supported every one of the research hypotheses. Moreover, the qualitative interviews’ data also supported every one of the research hypotheses. Therefore, the study results suggest that EIMC impacts positively on organizations’ SCA, both directly and indirectly. The indirect relationship is mediated through KM and TQM, and is serially mediated via both KM and TQM. These findings are generally consistent with the extant literature and support the notion of direct and indirect relationships between EIMC and SCA. However, the literature to date has paid little attention to these relationships. This research contributes to the knowledge concerning EIMC, TQM, and KM by providing empirical evidence of their ability to create and sustain a competitive advantage. In short, if EIMC is properly developed, it helps organizations to achieve KM, TQM and thus gain and sustain competitive advantage. Understanding the direct and indirect impacts of EIMC on SCA can positively affect organizations’ performance. Further research has been recommended to further critique an investigate the proposed model, especially in non-UAE contexts, and to extend the model by examining other mediators between EIMC and SCA

Enablers in Crisis Information Management: A Literature Review

Social media often plays a central role in crisis informatics as it is an important source for assessing, understanding, and locating crises quickly and accurately. In addition, social media enables actors to react more effectively and efficiently when managing crises. However, enablers of crisis information management have not been carved out explicitly in a systematic view. Therefore, we perform a literature review to synthesize the existing literature on crisis information management with a focus on technical enablers and their classification into the crisis-management phases. As our results show, searching for crisis informatics mostly results in social media-related publications. We found that Twitter is one of the most important technical enablers but that research on other social media platforms is underrepresented. Also, most publications center on the post-crisis phases of crisis management, leaving out the pre-crisis phases

Knowledge Management and Information Technology: Enablers of E-Commerce Development

Information and Communication Technologies provide the platform for development across economic and other sectors. Knowledge and information are interconnected. The effective use of information and knowledge, however, depend on the availability of an efficient information technology. This in turn will accelerate the establishment of e-commerce in developing economies. This paper examines the relationship between knowledge, information, information technology and how they can be enablers for the development of e-commerce in Afric

Strategically Constructed Narratives on Artificial Intelligence: What Stories Are Told in Governmental AI Policies?

What stories are told in national artificial intelligence (AI) policies? Combining the novel technique of structural topic modeling (STM) and qualitative narrative analysis, this paper explores and examines the policy narratives in 33 countries’ national AI policies. We uncover six common narratives that are dominating the political agenda concerning AI. Our findings show that the policy narratives’ salience vary across time and countries. The paper makes several contributions. First, our narratives describe well‐grounded, supportable conceptions of AI in governments, so as to contextualize and order a novel, multilayered, and controversial phenomenon. Building on the premise that human sensemaking is best represented and supported by narration, the paper addresses the applied rhetoric of governments to either belittle the risks or exalt the opportunities of AI. Second, we uncover the three prominent roles governments aim to take with regard to AI implementation, these are the role as enabler, leader, or regulator. Third, we make a methodological contribution toward data-driven computationally intensive theory development. Our methodological approach and identified narratives present key starting points for further research

The Operational Process Dashboard for Manufacturing

AbstractAgility is a critical success factor for manufacturers in today's volatile global environment and requires employees monitoring their performance and reacting quickly to turbulences. Thus, comprehensive information provisioning on all hierarchy levels is neces- sary. Yet, existing IT systems, e. g., Manufacturing Execution Systems, scarcely address information needs of workers on the shop floor level. This causes uncoordinated waiting times, inflexibility and costly communication. To address these issues, we present the Operational Process Dashboard for Manufacturing (OPDM), a mobile dashboard for shop floor workers. We identify process- oriented information needs, develop technical dashboard services and define IT requirements for an implementation

Recruitment systems nowadays: how XAI can improve trust

openThe use of artificial intelligence systems has a strong impact on people’s lives. One of the fields of application in which these systems are being tested is job recruitment. The use of artificial intelligence allows to manage a more complex number of data and to automate some phases of the management of these, making the recruitment process more fluid. It is necessary, therefore, that both the candidate and the human resource manager can trust the choices made by the system. In this thesis we develop the topic of artificial intelligence, focusing in particular on the use of XAI (eXplainable Artificial Intelligence). The implementation of XAI systems significantly improves the level of trust that people have in AI systems. Finally, we offer food for thought on the minimum technical measures to be taken at the design stage so that these systems can operate on European territory, following the guidelines set out in the AI ACT, act promoted by the European Commission to regulate in the field of Artificial Intelligence

Catalyzing Water for Sustainable Development and Growth

This report is an independent evidence-based analysis of how water can be addressed in a development agenda beyond 2015. It forecasts what might be needed in terms of financial investment, governance, and capacity and examines what these needs imply for implementation

Root cause analysis for resilient production systems through Industry 4.0 technologies

Creating and developing resilient production systems is critical if manufacturing companies are to thrive in a globally competitive market. Being flexible and agile, resilient systems can avoid, withstand, adapt to and recover from disturbances. A crucial ability is learning from experienced disturbances so they can be avoided in future. This is commonly done in manufacturing companies by performing a root cause analysis. However, the current practiceof root cause analysis lacks efficiency and effectiveness, which contributes to the high reoccurrence of disturbances encountered daily by manufacturing companies. Fortunately, with the introduction of Industry 4.0 technologies, the process of root cause analysis is expected to change greatly. With the aim of supporting practitioners in improving their root cause analysis processes, this research focuses on: (1) describing the current challenges; (2) describing the requirements for new technological solutions; and (3) identifying and designing new technological solutions, given the context of Industry 4.0. To do so, a qualitative approach was adopted, inspired by design science research (DSR) and based on six studies involving manufacturing companies and technology providers.Regarding the main challenges, the results of this research indicate that manufacturing companies are still performing unstructured root cause analysis, relying on experts to identify root causes and struggling to know how to analyse and integrate relevant data effectively. Furthermore, regarding requirements, the results of this research indicate that technological solutions for root cause analysis should be data-driven and easy to use. They should integrate different data sources, allow secure collaboration and support employee learning. Based on the requirements, the results of this research indicate that the leading technological solutions involve such things as data analytics, the development of thesauruses of disturbances and their causes, the design of specific data architectures and systems for root cause analysis and the design of platforms for stronger collaboration. Finally, in this research, specific high-level designs are proposed for an application to support root cause analysis of machine stops; and a collaborative platform for root cause analysis at the value-chain level. This research has practical and theoretical implications. Its results may be used directly by practitioners to gaininsight into potential improvements to their practices and as input for developing specific root cause analysis applications. The results of this research also advance knowledge in the field of root cause analysis by providing empirical evidence of challenges, requirements and solutions