Ali Mohsan

Περίληψη:
In market-based economies often appear significant decreases of economic activity, which lead to recessionary economic crises. These economic crises have quite negative consequences for firms, as they lead to significant decrease of their sales revenues; firms respond by decreasing on one hand their production and in general operational activities and expenses, personnel employment and materials’ procurement, and on the other hand their investments in production equipment, digital technologies, etc., which leads to technological obsolescence. This reduction of investments, and especially of the ones in digital technologies, due to their importance for firms’ efficiency, effectiveness, and innovation, can have quite negative impact on their future competitiveness, and even put at risk their survival. However, these negative consequences of economic crises differ significantly among firms: some of them exhibit a lower vulnerability to the crisis, so they have less negative consequences, while some other firms exhibit a higher vulnerability, and have more negative consequences; so the competitive position of the former is significantly strengthened with respect to the latter, and finally the former are the ‘winners’ of the crisis, while the latter are the ‘losers’. This paper proposes a methodology for predicting the winner and loser firms of future economic crises with respect to a highly important class of technologies: the digital technologies. In particular, the proposed methodology enables the prediction of the multi-dimensional ‘pattern of digital vulnerability’ of an individual firm to a future economic crisis, which consists of the degrees of reduction of the main types of ‘digital investments’ as well as ‘digital operating expenses’ in a future economic crisis. For this purpose, we are using Machine Learning algorithms, in combination with the Synthetic Minority Oversampling Technique (SMOTE), in order to increase their performance, which are trained using open government data from Statistical Authorities. Furthermore, a first application/validation of the proposed methodology is presented, using open data from the Greek Statistical Authority for 363 firms for the severe Greek economic crisis period 2009-2014, which gave satisfactory results concerning the prediction of nine different aspects of digital vulnerability to economic crisis (five of them concerned the main types of digital investment, and the other four concerned the main types of digital operating expenses).

Περίληψη:
Given the impetus upon the availability and quality of Open Government Data (OGD) as prime considerations for usability, the value derivation through OGD interoperability unleashes vistas for realizing the Sustainable Development Goals (SDGs) via economic activities. Therefore, economic growth and development in terms of the SDGs attainment is possible in the globalized contexts where trade & commerce assume significance. For the present study, SDG-specific OGD across the 4 OGD national portals (UK, US, The Netherlands, Greece) are assessed across the availability-interoperability axes to understand how trade & commerce amongst the 4 trading partners might facilitate the attainment of 17 SDGs with value derivation initiatives across commercial products/services of the stakeholders. Specifically, cosine similarity is assessed for drawing inferences for the availability-interoperability loci. Findings show that most value derivation activities via trade & commerce towards the attainment of SDGs in the 4 countries are facilitated across SDG4 (Quality Education) and SDG11 (Sustainable Cities and Communities) where the availability-interoperability focus is strongest whilst the reverse is true for SDG 5 (Gender Equality); SDG 10 (Reduced Inequality), and SDG 17 (Partnerships for the goals) where the availability-interoperability focus is weakest. The findings are suggestive of the need for the practitioners and policy-makers to institutionalize OGD initiatives with qualitatively robust OGD to stimulate value creation via trade & commerce products/services in the domains linked with the SDGs.

Περίληψη:
As a novel Artificial Intelligence (AI) application, ChatGPT holds pertinence not only for the academic, medicine, law, computing or other sectors, but also for the public sector-case in point being the Open Government Data (OGD) initiative. However, though there has been some limited (as this topic is quite new) research concerning the capabilities ChatGPT in these sectors, there has been no research about the capabilities it can provide to government concerning its wide range of functions and activities. This paper contributes to filling this gap by investigating the capabilities that the ChatGPT can provide concerning one of most recently initiated and novel, and at the same time most promising, activities of government that aims to fuel the emerging data economy and society: the opening of large amounts of government data; furthermore, we investigate the public values that can be promoted through the use of ChatGPT in the area of OGD by both the data publishers as well as their users. At the same time, we investigate the issues that the use of ChatGPT in the area of OGD can pose, which can reduce the capabilities identified as aforesaid as well as the benefits and public values that can be generated from them. For these purposes interviews with 12 experts have been conducted and their responses have been analyzed. Finally, based on our findings we have developed a research agenda concerning the exploitation of ChatGPT application in the OGD domain.