493 research outputs found

    Current issues of the management of socio-economic systems in terms of globalization challenges

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    The authors of the scientific monograph have come to the conclusion that the management of socio-economic systems in the terms of global challenges requires the use of mechanisms to ensure security, optimise the use of resource potential, increase competitiveness, and provide state support to economic entities. Basic research focuses on assessment of economic entities in the terms of global challenges, analysis of the financial system, migration flows, logistics and product exports, territorial development. The research results have been implemented in the different decision-making models in the context of global challenges, strategic planning, financial and food security, education management, information technology and innovation. The results of the study can be used in the developing of directions, programmes and strategies for sustainable development of economic entities and regions, increasing the competitiveness of products and services, decision-making at the level of ministries and agencies that regulate the processes of managing socio-economic systems. The results can also be used by students and young scientists in the educational process and conducting scientific research on the management of socio-economic systems in the terms of global challenges

    Towards a human-centric data economy

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    Spurred by widespread adoption of artificial intelligence and machine learning, “data” is becoming a key production factor, comparable in importance to capital, land, or labour in an increasingly digital economy. In spite of an ever-growing demand for third-party data in the B2B market, firms are generally reluctant to share their information. This is due to the unique characteristics of “data” as an economic good (a freely replicable, non-depletable asset holding a highly combinatorial and context-specific value), which moves digital companies to hoard and protect their “valuable” data assets, and to integrate across the whole value chain seeking to monopolise the provision of innovative services built upon them. As a result, most of those valuable assets still remain unexploited in corporate silos nowadays. This situation is shaping the so-called data economy around a number of champions, and it is hampering the benefits of a global data exchange on a large scale. Some analysts have estimated the potential value of the data economy in US$2.5 trillion globally by 2025. Not surprisingly, unlocking the value of data has become a central policy of the European Union, which also estimated the size of the data economy in 827C billion for the EU27 in the same period. Within the scope of the European Data Strategy, the European Commission is also steering relevant initiatives aimed to identify relevant cross-industry use cases involving different verticals, and to enable sovereign data exchanges to realise them. Among individuals, the massive collection and exploitation of personal data by digital firms in exchange of services, often with little or no consent, has raised a general concern about privacy and data protection. Apart from spurring recent legislative developments in this direction, this concern has raised some voices warning against the unsustainability of the existing digital economics (few digital champions, potential negative impact on employment, growing inequality), some of which propose that people are paid for their data in a sort of worldwide data labour market as a potential solution to this dilemma [114, 115, 155]. From a technical perspective, we are far from having the required technology and algorithms that will enable such a human-centric data economy. Even its scope is still blurry, and the question about the value of data, at least, controversial. Research works from different disciplines have studied the data value chain, different approaches to the value of data, how to price data assets, and novel data marketplace designs. At the same time, complex legal and ethical issues with respect to the data economy have risen around privacy, data protection, and ethical AI practices. In this dissertation, we start by exploring the data value chain and how entities trade data assets over the Internet. We carry out what is, to the best of our understanding, the most thorough survey of commercial data marketplaces. In this work, we have catalogued and characterised ten different business models, including those of personal information management systems, companies born in the wake of recent data protection regulations and aiming at empowering end users to take control of their data. We have also identified the challenges faced by different types of entities, and what kind of solutions and technology they are using to provide their services. Then we present a first of its kind measurement study that sheds light on the prices of data in the market using a novel methodology. We study how ten commercial data marketplaces categorise and classify data assets, and which categories of data command higher prices. We also develop classifiers for comparing data products across different marketplaces, and we study the characteristics of the most valuable data assets and the features that specific vendors use to set the price of their data products. Based on this information and adding data products offered by other 33 data providers, we develop a regression analysis for revealing features that correlate with prices of data products. As a result, we also implement the basic building blocks of a novel data pricing tool capable of providing a hint of the market price of a new data product using as inputs just its metadata. This tool would provide more transparency on the prices of data products in the market, which will help in pricing data assets and in avoiding the inherent price fluctuation of nascent markets. Next we turn to topics related to data marketplace design. Particularly, we study how buyers can select and purchase suitable data for their tasks without requiring a priori access to such data in order to make a purchase decision, and how marketplaces can distribute payoffs for a data transaction combining data of different sources among the corresponding providers, be they individuals or firms. The difficulty of both problems is further exacerbated in a human-centric data economy where buyers have to choose among data of thousands of individuals, and where marketplaces have to distribute payoffs to thousands of people contributing personal data to a specific transaction. Regarding the selection process, we compare different purchase strategies depending on the level of information available to data buyers at the time of making decisions. A first methodological contribution of our work is proposing a data evaluation stage prior to datasets being selected and purchased by buyers in a marketplace. We show that buyers can significantly improve the performance of the purchasing process just by being provided with a measurement of the performance of their models when trained by the marketplace with individual eligible datasets. We design purchase strategies that exploit such functionality and we call the resulting algorithm Try Before You Buy, and our work demonstrates over synthetic and real datasets that it can lead to near-optimal data purchasing with only O(N) instead of the exponential execution time - O(2N) - needed to calculate the optimal purchase. With regards to the payoff distribution problem, we focus on computing the relative value of spatio-temporal datasets combined in marketplaces for predicting transportation demand and travel time in metropolitan areas. Using large datasets of taxi rides from Chicago, Porto and New York we show that the value of data is different for each individual, and cannot be approximated by its volume. Our results reveal that even more complex approaches based on the “leave-one-out” value, are inaccurate. Instead, more complex and acknowledged notions of value from economics and game theory, such as the Shapley value, need to be employed if one wishes to capture the complex effects of mixing different datasets on the accuracy of forecasting algorithms. However, the Shapley value entails serious computational challenges. Its exact calculation requires repetitively training and evaluating every combination of data sources and hence O(N!) or O(2N) computational time, which is unfeasible for complex models or thousands of individuals. Moreover, our work paves the way to new methods of measuring the value of spatio-temporal data. We identify heuristics such as entropy or similarity to the average that show a significant correlation with the Shapley value and therefore can be used to overcome the significant computational challenges posed by Shapley approximation algorithms in this specific context. We conclude with a number of open issues and propose further research directions that leverage the contributions and findings of this dissertation. These include monitoring data transactions to better measure data markets, and complementing market data with actual transaction prices to build a more accurate data pricing tool. A human-centric data economy would also require that the contributions of thousands of individuals to machine learning tasks are calculated daily. For that to be feasible, we need to further optimise the efficiency of data purchasing and payoff calculation processes in data marketplaces. In that direction, we also point to some alternatives to repetitively training and evaluating a model to select data based on Try Before You Buy and approximate the Shapley value. Finally, we discuss the challenges and potential technologies that help with building a federation of standardised data marketplaces. The data economy will develop fast in the upcoming years, and researchers from different disciplines will work together to unlock the value of data and make the most out of it. Maybe the proposal of getting paid for our data and our contribution to the data economy finally flies, or maybe it is other proposals such as the robot tax that are finally used to balance the power between individuals and tech firms in the digital economy. Still, we hope our work sheds light on the value of data, and contributes to making the price of data more transparent and, eventually, to moving towards a human-centric data economy.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Georgios Smaragdakis.- Secretario: Ángel Cuevas Rumín.- Vocal: Pablo Rodríguez Rodrígue

    Examining the Relationships Between Distance Education Students’ Self-Efficacy and Their Achievement

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    This study aimed to examine the relationships between students’ self-efficacy (SSE) and students’ achievement (SA) in distance education. The instruments were administered to 100 undergraduate students in a distance university who work as migrant workers in Taiwan to gather data, while their SA scores were obtained from the university. The semi-structured interviews for 8 participants consisted of questions that showed the specific conditions of SSE and SA. The findings of this study were reported as follows: There was a significantly positive correlation between targeted SSE (overall scales and general self-efficacy) and SA. Targeted students' self-efficacy effectively predicted their achievement; besides, general self- efficacy had the most significant influence. In the qualitative findings, four themes were extracted for those students with lower self-efficacy but higher achievement—physical and emotional condition, teaching and learning strategy, positive social interaction, and intrinsic motivation. Moreover, three themes were extracted for those students with moderate or higher self-efficacy but lower achievement—more time for leisure (not hard-working), less social interaction, and external excuses. Providing effective learning environments, social interactions, and teaching and learning strategies are suggested in distance education

    New Concepts for Efficient Consumer Response in Retail Influenced by Emerging Technologies and Innovations

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    The retail industry is continuously confronted with new challenges and experiences a transformation from a supplier’s market to a buyer's market. It is, thus, essential for the retail industry to consequently focus on, anticipate and fulfil consumer’s demands. Technologies and innovative business solutions can help to support to establish a required customer experience and, thereby, gain a competitive advantage. A multitude of new services and products, channels as well as players can already be identified which drive the transformation. Therefore, retailers need to understand current trends and technologies and identify as well as implement relevant solutions for their transformation since otherwise, new players will dominate the market. Hence, this dissertation aims to review and analyse new technologies which are coupled with innovative business activities in order to provide customer-centric retailing. For this purpose, this dissertation consists of five articles and derives four major contributions which introduce different approaches to establishing consumer satisfaction. Firstly, a core technology for retail is artificial intelligence (AI) which can be meaningful applied along the entire value chain and improve retailers’ positions. Two focus areas have been identified in this context which are (i) the optimisation of the entire retail value chain with the help of AI with the aim to derive transparency and (ii) the improvement of consumer satisfaction and relationship. Secondly, focussing on the consumer-retailer relationship in the digital era, a concept with a data architecture is proposed based on a real use case. The outcome was that a specific customer orientation based on data can increase the brand value and sales volume. Thirdly, the work presents that new shopping concepts, named unmanned store concepts, gain continuous growth. Unmanned store concepts employ a variety of new technologies, are characterised by attributes of speed, ease, as well as comfort, and are deemed to be the new ideal of the expectations of modern buyers. Two different directions have been deeper analysed: (i) walk-in stores and (ii) automated vending machines. The critical success factors for the usage of unmanned store solutions are distance as well as high consumer affinity for innovations. In times of the COVID-19 pandemic, which has a huge impact on retail, a continuous innovation capability still needs to be established. Finally, this work introduces a tool for systematic innovation management considering the current circumstances. Taken as a whole, this dissertation with its five articles deals with significant research questions which have not been approached so far. Thereby, the literature is extended by the introduction of novel insights and the provision of a deeper understanding of how retailers can transform their business into a more consumer-oriented way

    The EU Cohesion policy and healthy national development: Management and Promotion in Ukraine

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    Монографія присвячена дослідженню сутності принципів реалізації політики згуртованості Європейського Союзу. Авторами проведено аналіз економічних, екологічних та соціальних аспектів інтеграції досвіду ЄС у державну політику України. У монографії узагальнено підходи до відновлення країни та здорового розвитку. Окрему увагу приділено питанням управління системою охорони здоров’я, тенденціям та перспективам досягнення стану стійкості системи медико-соціального забезпечення населення в умовах впливу COVID-19 на національну економіку. Узагальнено досвід використання маркетингових та інноваційних технологій у контексті здорового національного розвитку.Монография посвящена исследованию сущности принципов реализации политики сплоченности Европейского Союза. Авторами проведен анализ экономических, экологических и социальных аспектов интеграции опыта ЕС в государственную политику Украины. В монографии обобщены подходы к восстановлению и здоровому развитию. Отдельное внимание уделено вопросам управления здравоохранением, тенденциям и перспективам достижения состояния устойчивости системы медико-социального обеспечения населения в условиях влияния COVID-19 на национальную экономику. Обобщен опыт использования маркетинговых и инновационных технологий в контексте здорового национального развития.The monograph focused on the specifics of the principles of the EU Cohesion Policy implementation. The authors conducted an analysis of the economic, ecological and social aspects of the integration of the EU experience into the state policy of Ukraine. The monograph summarizes approaches to the restoration of the country and healthy development. Particular attention is paid to the issues of health care system management, the trends and prospects of achieving the state of resilience of the medical and social provision system of the population in the context of the impact of COVID-19 on the national economy. The experience of using marketing and innovative technologies in the context of healthy national development is summarized. The monograph is generally intended for government officials, entrepreneurs, researchers, graduate students, students of economic, medical, and other specialties

    DDoS Capability and Readiness - Evidence from Australian Organisations

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    A common perception of cyber defence is that it should protect systems and data from malicious attacks, ideally keeping attackers outside of secure perimeters and preventing entry. Much of the effort in traditional cyber security defence is focused on removing gaps in security design and preventing those with legitimate permissions from becoming a gateway or resource for those seeking illegitimate access. By contrast, Distributed Denial of Service (DDoS) attacks do not use application backdoors or software vulnerabilities to create their impact. They instead utilise legitimate entry points and knowledge of system processes for illegitimate purposes. DDoS seeks to overwhelm system and infrastructure resources so that legitimate requests are prevented from reaching their intended destination. For this thesis, a literature review was performed using sources from two perspectives. Reviews of both industry literature and academic literature were combined to build a balanced view of knowledge of this area. Industry and academic literature revealed that DDoS is outpacing internet growth, with vandalism, criminal and ideological motivations rising to prominence. From a defence perspective, the human factor remains a weak link in cyber security due to proneness for mistakes, oversights and the variance in approach and methods expressed by differing cultures. How cyber security is perceived, approached, and applied can have a critical effect on the overall outcome achieved, even when similar technologies are implemented. In addition, variance in the technical capabilities of those responsible for the implementation may create further gaps and vulnerabilities. While discussing technical challenges and theoretical concepts, existing literature failed to cover the experiences held by the victim organisations, or the thoughts and feelings of their personnel. This thesis addresses these identified gaps through exploratory research, which used a mix of descriptive and qualitative analysis to develop results and conclusions. The websites of 60 Australian organisations were analysed to uncover the level and quality of cyber security information they were willing to share and the methods and processes they used to engage with their audience. In addition, semi-structured interviews were conducted with 30 employees from around half of those websites analysed. These were analysed using NVivo12 qualitative analysis software. The difficulty experienced with attracting willing participants reflected the comfort that organisations showed with sharing cyber security information and experiences. However, themes found within the results show that, while DDoS is considered a valid threat, without encouragement to collaborate and standardise minimum security levels, firms may be missing out on valuable strategies to improve their cyber security postures. Further, this reluctance to share leads organisations to rely on their own internal skill and expertise, thus failing to realise the benefits of established frameworks and increased diversity in the workforce. Along with the size of the participant pool, other limitations included the diversity of participants and the impact of COVID-19 which may have influenced participants' thoughts and reflections. These limitations however, present opportunity for future studies using greater participant numbers or a narrower target focus. Either option would be beneficial to the recommendations of this study which were made from a practical, social, theoretical and policy perspective. On a practical and social level, organisational capabilities suffer due to the lack of information sharing and this extends to the community when similar restrictions prevent collaboration. Sharing of knowledge and experiences while protecting sensitive information is a worthy goal and this is something that can lead to improved defence. However, while improved understanding is one way to reduce the impact of cyber-attacks, the introduction of minimum cyber security standards for products, could reduce the ease at which devices can be used to facilitate attacks, but only if policy and effective governance ensures product compliance with legislation. One positive side to COVID-19's push to remote working, was an increase in digital literacy. As more roles were temporarily removed from their traditional physical workplace, many employees needed to rapidly accelerate their digital competency to continue their employment. To assist this transition, organisations acted to implement technology solutions that eased the ability for these roles to be undertaken remotely and as a consequence, they opened up these roles to a greater pool of available candidates. Many of these roles are no longer limited to the geographical location of potential employees or traditional hours of availability. Many of these roles could be accessed from almost anywhere, at any time, which had a positive effect on organisational capability and digital sustainability

    Lineamientos de diseño con enfoque cultural adaptados al entorno peruano: Un caso de estudio en una entidad gubernamental

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    El presente proyecto de fin de carrera tiene como objetivo elaborar lineamientos de diseño para sitios web gubernamentales enfocado en el entorno cultural peruano para incrementar la usabilidad y el nivel de satisfacción de los usuarios gracias al análisis de modelos culturales y la validación de lineamientos de diseño obtenidos mediante evaluación de usabilidad con usuarios. Hoy en día, considerar aspectos de usabilidad en productos de software es de suma importancia para lograr atraer y retener usuarios. Si bien la importancia de la usabilidad ha ido en aumento y es considerada clave, la inclusión de aspectos culturales en el diseño y evaluación de sitios web aún no es ampliamente difundida. Según la revisión de literatura, existen estudios que relacionan la usabilidad con temas culturales en páginas web. Sin embargo, pocos estudios incluyen a Perú dentro de su análisis, así como también son mayormente aplicados en sitios de comercio electrónico por su exposición a usuarios de diferentes culturas. Este proyecto es consistente con los componentes que definen a la usabilidad y realiza un análisis comparativo de elementos de diseño presentes en sitios web y su relación con las características culturales asociadas a un modelo cultural, el cual se selecciona en base a un análisis de modelos culturales presentes en la literatura. Finalmente, el presente estudio obtiene un listado de lineamientos de diseño que incluyen características culturales peruanas, los cuales al ser aplicados pueden demostrar una mejora en el nivel de satisfacción de los usuarios peruanos
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