Harnessing Big Data for Soft Power: A Sentiment Analysis of FIFA Qatar 2022

Transport infrastructure, if well-developed and regularly updated, is one of the most important factors of economic growth of the country and regions. Article shows relations between investment in surface transport infrastructure and stimulation of entrepreneurship, it also demonstrates the crucial role played by European Structural Funds in the improvement of infrastructure. During the systemic transformation, Poland and other countries of the former communist block received an opportunity to refurbish their economic and social landscape. Thanks to European structural funds in 2004 – 2006 and 2007 – 2013 periods, preceded by pre-accession funds, Poland achieved a notable economic success, surpassing many expectations. Investment in the infrastructure allowed for improvement in all walks of life. The progress in socio-economic indicators seen during the systemic transformation in Poland and other New Member States was overwhelmingly due to assistance in the form of EU funding, which flooded into those countries on unprecedented scale. Article looks at conditions for development of the transport infrastructure in Poland and attempts to provide answers to questions on the nature of relationship between the transport infrastructure and its crucial end users: entrepreneurs. This paper aims to: demonstrate that investment in transport infrastructure is the key to improve the role of entrepreneurship in the development of a country and a region, and relations between the number of businesses and the quality and spatial prominence of the transport infrastructure; answer the questions: which instruments on the national and European level support the process of improvements to infrastructure and consequent better access of businesses to markets. Method adopted in the research involved questionnaires. Entrepreneurs responded to questions concerning their activity and its dependence on proximity of the motorway and neighboring local transportation networks. The second method of research was statistical data received from the Polish Statistical Office about the number of enterprises and proximity of available infrastructure. The main finding of the research is that the development of small and medium enterprises is not overwhelmingly dependent on the proximity of a highway. The larger the investment in regional transport infrastructure, less so motorways (often toll roads) and more national, regional and local roads, the more visible are financial and economic outcomes achieved by SMEs. Regional and national level planning documents acknowledge that the present day quality of transport infrastructure leaves a lot of room for improvement and actions should be taken to address this issue in short time horizon, if Poland is to have a cohesive transport infrastructure on par with the rest of EU. Creating good infrastructural conditions is the most important factor to create a favorable environment for entrepreneurship. DOI: http://dx.doi.org/10.5755/j01.eis.0.6.1511

In today’s competitive landscape, technology firms increasingly turn to advanced data analytics as a strategic tool for boosting revenue growth and operational efficiency. This review explores how leveraging sophisticated analytical techniques can enable these organizations to extract actionable insights from vast datasets, thereby enhancing decision-making processes and driving business performance. Advanced data analytics encompasses a range of methodologies, including predictive analytics, machine learning, and big data analysis, which collectively empower firms to identify trends, optimize resources, and tailor products to meet evolving customer demands. One of the primary benefits of utilizing advanced data analytics is the ability to enhance revenue growth through improved customer targeting and segmentation. By analyzing customer behaviors and preferences, technology firms can develop personalized marketing strategies that resonate with their target audiences, resulting in increased conversion rates and customer loyalty. Moreover, data analytics facilitates the identification of new market opportunities, enabling firms to innovate and expand their product offerings effectively. Operational efficiency is another critical area where advanced data analytics proves invaluable. By monitoring key performance indicators (KPIs) and operational metrics, technology firms can streamline their processes, reduce costs, and minimize waste. Predictive analytics, in particular, allows organizations to anticipate potential disruptions in their operations, enabling proactive measures to mitigate risks and maintain smooth workflows. This capability not only enhances productivity but also fosters a culture of continuous improvement. Additionally, advanced data analytics supports informed strategic planning by providing insights into market dynamics and competitive positioning. Firms can leverage these insights to make data-driven decisions, allocate resources effectively, and align their business strategies with market trends. In conclusion, advanced data analytics serves as a catalyst for revenue growth and operational efficiency in technology firms. By embracing these analytical techniques, organizations can harness the power of data to drive innovation, improve customer engagement, and achieve sustainable competitive advantage. As technology continues to evolve, the strategic implementation of advanced data analytics will be essential for firms seeking to thrive in an increasingly data-driven world. Keywords: Advanced Data Analytics, Revenue Growth, Operational Efficiency, Technology Firms, Predictive Analytics, Customer Targeting, Strategic Planning.

This thesis uses the 2018 World Cup in Russia to engage with the processes of neoliberal restructuring and the conception of soft power. Based on a comparison of the host cities of Ekaterinburg and Volgograd, it unpacks the World Cup at multiple scales of analysis and offers a light and revisable framework for understanding mega-events. Grounded in primary qualitative and secondary documentary data, the thesis demonstrates multiple dimensions of Potemkinism in the articulation of this World Cup. Inspired by but moving beyond traditional post-colonial thought, it attempts to make good on the premise of theorizing from anywhere, making a case for the relatively invisible cities of the Global East in a landscape of urban theory dominated by the hegemonic North or the subaltern South. This ambition represents the overall frame for the thesis, while the work itself focuses more specifically on the planning and impacts of hosting the World Cup. This work is composed of two central thrusts. Within an understanding of mega-events as fundamentally urban events, the first thrust explores hosting as the vanguard of neoliberal restructuring, one of the traditional means of making sense of mega-events. In this view, bidding and hosting are seen as a strategy for inter-urban competition and a ploy to attract increased flows of tourists and capital. This is understood as one of the markers of a shift to a more entrepreneurial mode of urban governance and is part of wider global political economic restructuring that de-emphasizes the national in favor of regional or municipal scales. Using Neil Brenner’s conceptualization of rescaled competition state regimes, this part of the thesis explores how rescaling worked on the ground in Russia and demonstrates that these processes of neoliberalization are not as easily understood as they might first appear. Instead, what is revealed in the articulation of the Russian World Cup is a seemingly paradoxical combination of national state-led projects to develop the peripheries in regionally and municipally specific ways, for the purposes of interurban differentiation and competition. The thesis proposes the notion of Potemkin neoliberalism to make sense of these seeming paradoxes and, further, traces some of the uneven developments within the host cities. This is framed within an emphasis on the superficial rather than the substantive, meaning an attention towards aesthetics and appearance rather than on structural reforms and durable infrastructural improvements. The second thrust investigates Joseph Nye’s notion of soft power, which is another traditional way of understanding the rationales for hosting mega-events. Soft power analyses typically frame hosting through the lens of foreign policy, a view that tends to ignore the domestic component entirely. Separate from this, some mega-event studies focus on hosting as a strategy for nation- or identity building, but typically these do not situate this domestic concern within the conceptual apparatus of soft power. Combining these two approaches, this thesis takes the Russian World Cup as a primarily domestic affair, both to develop the urban peripheries (as demonstrated in the first thrust), and to inculcate certain soft power narratives within the domestic population. Conceptualizing the narrative project as soft power allows a tracing of each element in the soft power equation: narrative generation, the mechanisms of distribution, and the reception (or lack thereof) among host city residents. This is presented as discursive Potemkinism, whereby a certain set narratives were promoted as the official way to understand the mega-event, though with little attention to the realities underneath. Finally, the thesis explores the final element in the soft power equation – the impacts on host city residents – through an attention to the micro level of everyday life. In this, it engages with de Certeau and Lefebvre to create a spectrum of tactics employed by residents to disalienate themselves by various degrees from World Cup developments. The thesis emphasizes the individual and the quotidian to offer a more nuanced, human level approach to understanding mega-event-led urban development. Situated in a relational comparative urbanism that valorizes the Global East, these two thrusts represent the core contributions of this monograph. Overall, the thesis presents an investigation of the 2018 men’s Football World Cup that takes stock of global political economic processes, Russian national state spatial strategies, uneven municipal developments, the creation and distribution of soft power narratives to the domestic audience, and the adoption, reworking, or outright refusal of those narratives among host city residents.

Fiscal policy competition for a multinational enterprise (MNE) resulting in the same location of firms is widely recognized as harmful owing to losses of the host government’s budget without gains from firms’ behavior. In this study, we provide a plausible explanation why fiscal competition for an MNE keeping firms’ location choices unchanged can be beneficial by incorporating governments’ decisions on public investments in transport infrastructure, such as ports, which reduces the trade costs between two competing countries. Our model divides transport costs into infrastructure-independent and infrastructure-dependent; investments in infrastructure reduce infrastructure-dependent costs. We show that fiscal competition increases countries’ investments in infrastructure under low infrastructure-independent transport costs without affecting firms’ locations. Furthermore, we show that the host country benefits from fiscal competition, although it pays a subsidy to the MNE. Moreover, as investments in infrastructure generate positive spillovers, fiscal competition that improves transport infrastructure benefits non-host countries and improves global welfare.

This paper provides a broad overview of the infrastructure investment landscape in Canada and our reputation as a competitive destination for such investment. We compare the Canadian infrastructure investment environment and recent outcomes with those of a set of peer nations (G7 countries plus Australia). Canada has serious reputational issues relative to our peer group when it comes to attracting investment in infrastructure, and these issues correspond to declining rates of foreign direct investment inflows. Federal government spending on infrastructure is also declining, implying an overall lack of investment in infrastructure. This lack of investment is, in turn, manifesting as an increase in Canada’s infrastructure deficit and an overall decline in the reputation of the quality of existing infrastructure. Estimates of Canada’s infrastructure deficit range up to $600 billion, and the investment shortfalls contributing to this deficit are particularly apparent in transportation and trade infrastructure. Canada has fallen sharply to last place relative to the G7 and Australia in terms of infrastructure and logistics quality. The most prominent issues driving Canada’s declining reputation as a destination for investment include a sharp slide in the ease of doing business, which, in turn, is caused by perceived regulatory and bureaucratic delays (including the time required for construction permits). An inconsistency in federal infrastructure funding programs and policies (tied to federal election cycles) is similarly problematic. While most of Canada’s public infrastructure investment is made by provincial and municipal governments, their smaller and more variable shares of tax revenues do not ensure stable and sufficient levels of infrastructure investment in many regions. This pattern also serves to promote regional inequality, since regions suffering from poor infrastructure may not have the resources required to overcome local infrastructure deficits. Reliance on PPPs (public-private partnerships) to bolster infrastructure investment may well prove fruitless given the negative experiences Canada’s peers have had with PPPs and the already evident frustrations with Canada’s existing pursuits in this area. Falling tax rates have failed to attract foreign direct investment flows into Canada, suggesting that tax competitiveness is not a sufficient incentive to overcome the reputational issues associated with inconsistent federal investment policies and growing regulatory and bureaucratic delays. Addressing these issues will require a stable and long-term strategy (one not subject to Canada’s federal electoral cycles) and a serious look at the timeframes and delays for regulatory and bureaucratic processes. We suggest the federal government place a higher priority on infrastructure investments in critical areas such as trade and transportation infrastructure. These types of infrastructure play an outsized role in supporting national productivity and income. Further, attracting significant levels of private investment will likely benefit from a consistent and predictable trade and transportation infrastructure strategy. Canada requires an integrated and strategic national approach to infrastructure policy and investment. This approach must be based around a long-term focus and will require coordination among federal, provincial, municipal and First Nations governments and the private sector (including coordination with Canada’s large pension funds, which represent a significant untapped source of financial capital). Provincial governments have already expressed an interest and willingness to collaborate on a national infrastructure strategy based on the corridor concept, and the Senate Standing Committee on Banking, Trade and Commerce has similarly acknowledged the potential merits of applying the corridor concept. Given these endorsements and the evidence presented above, it is incumbent on the federal and other governments to act on formulating a stable, long-term and strategic national infrastructure strategy that pairs government investment and policies to attract private sector investment in all kinds of infrastructure, but most notably in transportation, warehousing and logistics infrastructure. As part of this, it is critical that Canada address its serious issue of regulatory and policy uncertainty, delays and burdens as these appear to be the most critical aspects of our declining reputation and the most pernicious impediments to achieving infrastructure investment goals and priorities.

In an era where environmental risks pose significant challenges to the U.S. geology sector, this paper meticulously explores the integration of data analytics techniques to enhance risk assessments. The study delves into the intricate relationship between geological processes and human activities, underscoring the necessity for advanced analytical methodologies in mitigating environmental risks. The background sets the stage, highlighting the evolving perception of risk and sustainability in geological activities, and the critical role of reliable construction practices and engineering investigations. The aim of this paper is to synthesize and critically evaluate the current methodologies in data analytics, particularly their impact on reducing environmental risks associated with geological activities. The scope encompasses a detailed examination of the evolution from traditional to modern analytical methods, emphasizing the integration of predictive analytics, machine learning, big data, and Geographic Information Systems (GIS) in geological predictions and risk management. The main findings reveal a significant advancement in data analytics, marked by the integration of AI and machine learning with traditional geological methods. This fusion enhances the accuracy, efficiency, and comprehensiveness of risk assessments. The study concludes with recommendations for continued integration of advanced data analytics in geological studies, advocating for sustainable and responsible practices. It emphasizes the importance of international collaboration and harmonization of regulatory standards to enhance environmental risk assessments in geology. This paper provides valuable insights for researchers, policymakers, and practitioners in the field, offering a roadmap for future advancements in geological data analytics and environmental risk management.

Implementing fair lending practices is crucial for financial institutions to ensure equal access to credit and comply with regulatory requirements. Advanced data analytics approaches offer powerful tools for detecting and mitigating potential biases in lending decisions. This paper provides a comprehensive framework for leveraging advanced data analytics techniques to enhance fair lending practices and maintain regulatory compliance. The review begins by outlining the importance of fair lending and the role of advanced data analytics in achieving this goal. It then discusses the regulatory landscape governing fair lending and the risks associated with non-compliance. The paper emphasizes the significance of data collection, management, and security in implementing fair lending practices. Next, it delves into advanced data analytics techniques such as predictive modeling, machine learning, text mining, and geospatial analysis for identifying and addressing potential biases in lending practices. The importance of establishing a fair lending framework, developing robust risk assessment methodologies, and implementing model validation procedures is highlighted. Furthermore, the review emphasizes the need for continuous monitoring and reporting of fair lending performance, as well as engaging with regulatory agencies to ensure compliance. Case studies and best practices are presented to illustrate successful implementations of advanced analytics for fair lending. In conclusion, the paper underscores the ongoing commitment required to maintain fair lending practices and regulatory compliance in the evolving financial landscape. It also discusses future trends and developments in fair lending and data analytics. Keywords: Fair Lending, Advanced Data Analytics, Regulatory Compliance, Bias Detection, Predictive Modeling, Machine Learning, Text Mining, Geospatial Analysis.

This paper explores the role of advanced data analytics in optimizing renewable energy systems to achieve clean energy objectives. As the world transitions towards sustainable energy sources, the intermittency and variability of renewable sources present significant challenges. Traditional approaches to managing these challenges often fall short in terms of efficiency and scalability. However, advanced data analytics offers promising solutions by leveraging large volumes of data to optimize energy production, storage, and distribution. This paper discusses various techniques such as predictive modeling, optimization algorithms, and grid management strategies enabled by advanced data analytics. Case studies highlight real-world applications in wind and solar energy optimization, showcasing the effectiveness of data-driven approaches in improving renewable energy output and grid integration. Despite the potential benefits, challenges such as data privacy, security, and regulatory frameworks remain important considerations. Looking ahead, the integration of IoT and sensor technologies holds promise for further enhancing the performance of renewable energy systems. By fostering collaboration between researchers, policymakers, and industry stakeholders, we can accelerate the adoption of advanced data analytics and propel the transition towards a clean energy future. Keywords: Renewable Energy, Advanced Data Analytics, Predictive Modeling, Optimization Algorithms, Grid Integration, Sustainability.

Background: Transport is a sector of the economy that is subject to general economic laws, including with regard to issues related to investing in real assets, developing means of production, and ensuring expanded reproduction. Along with this, transport is a strategic sector at the state level, ensuring the functioning of the economy as a whole. In this regard, there are certain contradictions associated with the assessment of the effectiveness of investments in transport infrastructure. In most cases, investments in transport infrastructure are valued similarly to investments in a business project. After the issuance of Decree of the Government of the Russian Federation No. 1512 dated November 26, 2019, the approach to evaluating the effectiveness of investments with state participation has expanded, but it does not fully cover the issues of project effectiveness for the state. Along with this, the classical methods for evaluating the effectiveness of investment projects are subject to great subjectivity in relation to the calculation of social effects, as a result of which their applicability to projects at the national economic level is ineffective.
 Aim: to consider the list of effects arising from the construction of transport infrastructure and determine the methodology for calculating the effects for the state.
 Materials and methods: the research methodology is based on the analysis of methods for financial and economic evaluation of investment projects, as well as macroeconomic methods. The information base of the study is based on the official legal and methodological information of the authorities of the Russian Federation.
 Results: as a result of the study, a list of effects for the state arising from the implementation of transport infrastructure development projects was determined, and the procedure for their calculation was substantiated.
 Conclusion: the study confirms that the currently used methods for evaluating the effectiveness of investments in infrastructure projects for the state do not fully and objectively reflect economic realities. The proposed approach to the assessment will make it possible to carry out a comprehensive assessment of the socio-economic effects from the construction of cargo maglev transport lines and improve the quality of management decisions in the transport sector.

The objective of this paper is to investigate the regional incidence of the effects of public investment in transportation infrastructures in Portugal. Our methodological approach consists of estimating vector autoregressive (VAR) models for the national economy as well as for each of the five administrative regions in the country. In the regional models, both public investment in transportation infrastructures in the region and public investment in transportation infrastructures elsewhere are considered, thereby taking into consideration the potential existence of regional spillovers. Empirical results suggest that although public investment in transportation infrastructures has been a powerful instrument to promote long-term growth, it does so in a way that is rather unbalanced across regions. We show that public investment in transportation infrastructures has markedly contributed to the concentration of economic activity in Lisbon, the largest region in the country, and therefore has contributed markedly to the macrocephaly of the country.

In April 2016, the People's Republic of China (PRC) launched the "football development plan in the medium and long term (2016-2050)." The Chinese Government's goal is clear: making the Asian country a worldwide football superpower. This article will showhow the Chinese strategy is organized in its three stages, with commitments and goals to be reached at the end of each one of them. Including the President Xi Jinping "three dreams of World Cup" audacious plans: return to dispute the FIFA World Cup, host a World Cup edition and, finally, win a World Cup to thus consolidate the country 's football power in the most popular sport on the planet. The article also intents to demonstrates how the Chinese state induces private investment in football and sports industry. Showing that the large Chinese conglomerates have beeing collaborated in a crucial manner so that the government achieves the objectives outlined in its plan. And while China is moving towards the development of the most popular sport on the planet, the article brings to the theoretical discussion issues such as soft power and sport's influence, especially football, in the identity and national pride. Brought to a conclusion that the Chinese state has taken advantage of the football popularity to exercise 'soft power', strengthening diplomatic ties and placing the country in the Asian and worldwide context, but also to reinforce their people sense of national identity. For this, the article resorts to the bibliographic review, comparative study, in addition to analyzing the football development plan.

The rising government funding in transport infrastructure has sparked political and academic debates on the economic impacts of transport infrastructure investment in the United States. Although numerous empirical studies have examined the transport infrastructure-growth nexus, existing literature has mixed conclusions of the economic effects of expanding transport infrastructure. The main objective of this paper is to assess the short- and long-run impacts of transport and non-transport public infrastructure on economic growth to provide an implication of the effectiveness of these fiscal policy tools in the short- and long-term. For this purpose, we employ a modern autoregressive distributed lag (ARDL) approach to explore the dynamic relationships among transport infrastructure, non-transport public infrastructure, private capital, labor hours, GDP, and exports. In the long run, we find that a bidirectional relationship exists between transport infrastructure and GDP, suggesting that expanding transport infrastructure improves aggregated economic output, and enhanced economic output increases public investment in transport infrastructure. However, the magnitude of the impact of transport infrastructure on GDP is smaller than that of non-transport public infrastructure, implying that non-transport infrastructure investment is a more effective long-term fiscal stimulus than expanding transport infrastructure.

The share of investment in transport infrastructure of the gross domestic product (GDP) has risen substantially in central and eastern European countries, and the effectiveness of public investment in transport infrastructure to improve economic performance is receiving increasing attention. This paper explores the dynamic impact of transport infrastructure on employment, GDP, exports, and industry production in European countries. With the use of data from 1995 to 2010, the paper analyzes the causality among variables in a dynamic panel framework. The results reveal that transport infrastructure and macroeconomic indicators are cointegrated and a significant unidirectional causal relationship exists from public investment in transport infrastructure to economic performance. The findings of this paper support the traditional notion that an increase in government spending on transport infrastructure contributes to economic growth. More specifically, the paper finds that transport infrastructure is a forcing variable of economic output and exports of European countries. Examination of the economic impacts of transport infrastructure between developed and developing economies shows that economic performance of central and eastern European countries is more sensitive to a change in investment in transport infrastructure than that of Western European countries. A major policy implication of these findings is that expanding transportation infrastructure could be an effective fiscal policy tool to boost economic performance of developing European economies.

In the rapidly evolving health industry, the integration of advanced data analytics has become pivotal in enhancing customer experience and driving market penetration. This review explores how leveraging data analytics can transform health services, offering personalized care, improving patient outcomes, and expanding market reach. Advanced data analytics enables health providers to harness vast amounts of patient data to gain actionable insights. By analyzing trends, patterns, and patient behaviors, providers can offer personalized and predictive care, tailoring treatments to individual needs. This personalization enhances patient satisfaction, leading to better adherence to treatment plans and improved health outcomes. Moreover, real-time analytics facilitate proactive interventions, allowing for timely responses to potential health issues, thereby improving overall patient care. In addition to enhancing patient care, data analytics plays a critical role in market penetration. By identifying underserved populations and market segments, health providers can strategically expand their services. Analytics-driven marketing strategies, informed by demographic, behavioral, and psychographic data, enable targeted outreach and effective communication with potential customers. This targeted approach not only attracts new patients but also fosters loyalty among existing ones by addressing their specific needs and preferences. Furthermore, advanced analytics provide health organizations with insights into operational efficiencies and cost-saving opportunities. By optimizing resource allocation, streamlining administrative processes, and reducing waste, providers can enhance their service delivery while maintaining cost-effectiveness. This operational excellence is crucial for maintaining a competitive edge in the health industry. Case studies of successful implementations of data analytics in the health sector illustrate the tangible benefits of these strategies. For instance, predictive analytics have been used to anticipate patient needs and allocate resources effectively, while sentiment analysis has provided valuable feedback on patient experiences, driving continuous improvement. In conclusion, advanced data analytics is a transformative tool in the health industry, significantly enhancing customer experience and market penetration. By embracing data-driven strategies, health providers can deliver personalized care, optimize operations, and strategically expand their market presence, ultimately leading to better health outcomes and sustainable growth.

Audit firms are increasingly engaging with advanced data analytics to improve the efficiency and effectiveness of external audits through the automation of audit work and obtaining a better understanding of the client’s business risk and thus their own audit risk. This paper examines the process by which audit firms adopt advanced data analytics, which has been left unaddressed by previous research. We derive a process theory from expert interviews which describes the activities within the process and the organizational units involved. It further describes how the adoption process is affected by technological, organizational and environmental contextual factors. Our work contributes to the extent body of research on technology adoption in auditing by using a previously unused theoretical perspective, and contextualizing known factors of technology adoption. The findings presented in this paper emphasize the importance of technological capabilities of audit firms for the adoption of advanced data analytics; technological capabilities within audit teams can be leveraged to support both the ideation of possible use cases for advanced data analytics, as well as the diffusion of solutions into practice.