Design Principles for Diffusion of Reports and Innovative Use of Business Intelligence Platforms

In order to innovate and respond quickly to new requirements, employees frequently supplement their information systems. This particularly applies to the context of business intelligence (BI) because many users supplement their BI platforms with individually tinkered spreadsheets. Unfortunately, these supplements bear numerous threats such as limited report reuse across all potential users. To address this gap, we establish a design science project. First, we qualitatively explore impediments to diffusion of reports and impediments to innovative use. Second, upon our findings and extant literature, we derive meta-requirements for BI platforms that foster diffusion of reports and innovative use. Third, we develop and discuss principles for how to design a BI platform that would meet the identified meta-requirements. The resulting design principles emphasize (1) permanent user sandboxes to improve innovative use and (2) hybrid recommendation agents based on user interaction, collaborative-filtering, and users\u27 social influence to improve diffusion of reports

Policies for capacity development

No description supplie

Impact in networks and ecosystems: building case studies that make a difference

open accessThis toolkit aims to support the building up of case studies that show the impact of project activities aiming to promote innovation and entrepreneurship. The case studies respond to the challenge of understanding what kinds of interventions work in the Southern African region, where, and why. The toolkit has a specific focus on entrepreneurial ecosystems and proposes a method of mapping out the actors and their relationships over time. The aim is to understand the changes that take place in the ecosystems. These changes are seen to be indicators of impact as increased connectivity and activity in ecosystems are key enablers of innovation. Innovations usually happen together with matching social and institutional adjustments, facilitating the translation of inventions into new or improved products and services. Similarly, the processes supporting entrepreneurship are guided by policies implemented in the common framework provided by innovation systems. Overall, policies related to systems of innovation are by nature networking policies applied throughout the socioeconomic framework of society to pool scarce resources and make various sectors work in coordination with each other. Most participating SAIS countries already have some kinds of identifiable systems of innovation in place both on national and regional levels, but the lack of appropriate institutions, policies, financial instruments, human resources, and support systems, together with underdeveloped markets, create inefficiencies and gaps in systemic cooperation and collaboration. In other words, we do not always know what works and what does not. On another level, engaging users and intermediaries at the local level and driving the development of local innovation ecosystems within which local culture, especially in urban settings, has evident impact on how collaboration and competition is both seen and done. In this complex environment, organisations supporting entrepreneurship and innovation often find it difficult to create or apply relevant knowledge and appropriate networking tools, approaches, and methods needed to put their processes to work for broader developmental goals. To further enable these organisations’ work, it is necessary to understand what works and why in a given environment. Enhanced local and regional cooperation promoted by SAIS Innovation Fund projects can generate new data on this little-explored area in Southern Africa. Data-driven knowledge on entrepreneurship and innovation support best practices as well as effective and efficient management of entrepreneurial ecosystems can support replication and inform policymaking, leading thus to a wider impact than just that of the immediate reported projects and initiatives

Artificial Intelligence, International Competition, and the Balance of Power (May 2018)

World leaders, CEOs, and academics have suggested that a revolution in artificial intelligence is upon us. Are they right, and what will advances in artificial intelligence mean for international competition and the balance of power? This article evaluates how developments in artificial intelligence (AI) — advanced, narrow applications in particular — are poised to influence military power and international politics. It describes how AI more closely resembles “enabling” technologies such as the combustion engine or electricity than a specific weapon. AI’s still-emerging developments make it harder to assess than many technological changes, especially since many of the organizational decisions about the adoption and uses of new technology that generally shape the impact of that technology are in their infancy. The article then explores the possibility that key drivers of AI development in the private sector could cause the rapid diffusion of military applications of AI, limiting first-mover advantages for innovators. Alternatively, given uncertainty about the technological trajectory of AI, it is also possible that military uses of AI will be harder to develop based on private-sector AI technologies than many expect, generating more potential first-mover advantages for existing powers such as China and the United States, as well as larger consequences for relative power if a country fails to adapt. Finally, the article discusses the extent to which U.S. military rhetoric about the importance of AI matches the reality of U.S. investments.LBJ School of Public Affair

The future of Cybersecurity in Italy: Strategic focus area

This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management

Innovation policy in the European Union: instruments and objectives

We provide an overview of the specific innovation policies that are implemented at European level, highlighting, where possibile, the connections between these policies and the guidance documents issued by the Community’s institutions. We describe the kinds of policy interventions that are implemented, providing at the same time some useful elements in order to understand the assumptions and theories that underpin them.Innovation policy; European institutions; Lisbon strategy; Structural funds; European research policy; European enterprise policy

The role of urban living labs in a smart city

In a rapidly changing socio-technical environment cities are increasingly seen as main drivers for change. Against this backdrop, this paper studies the emerging Urban Living Lab and Smart City concepts from a project based perspective, by assessing a series of five Smart City initiatives within one local city ecosystem. A conceptual and analytical framework is used to analyse the architecture, nature and outcomes of the Smart City Ghent and the role of Urban Living Labs. The results of our analysis highlight the potential for social value creation and urban transition. However, current Smart City initiatives face the challenge of evolving from demonstrators towards real sustainable value. Furthermore, Smart Cities often have a technological deterministic, project-based approach, which forecloses a sustainable, permanent and growing future for the project outcomes. ‘City-governed’ Urban Living Labs have an interesting potential to overcome some of the identified challenges

Generativity of Business Intelligence Platforms: A Research Agenda Guided by Lessons from Shadow IT

To provide software platforms that are highly adjustable to users’ needs, recent literature proposes generativity, that is, platforms that may be supplemented in order to provide functionality that the designers of the platform did not have in mind. The research stream on generative platforms features a similar phenomenon as the research stream on shadow IT (SIT), because SIT also investigates supplements to integrated software-based systems that the designers of the software initially did not have in mind. Especially the domain of business intelligence (BI) is often flooded with SIT such as additional data marts and spreadsheets. However, while a wide body of literature has emerged that investigates SIT impacts, few, if any, studies examined generativity of platforms in general and BI platforms specifically. In this paper we present a literature review on positive and negative SIT impacts. Building on the results, we suggest a research agenda on generativity of BI platforms