Hasil untuk "Capital. Capital investments"

Alig BAGHİROV, Emine Arzu Imren KARAOSMANOĞLU, Rafał PITERA

This study aims to analyze the long-term effects of key tourism variables on macroeconomic growth in Bulgaria, Georgia, Romania, the Russian Federation, Turkey, Ukraine, and Azerbaijan over the period 1995–2024. Conducted within the framework of the extended Solow growth hypothesis, the study applies long-run DOLS and MG-DOLS panel cointegration methods to examine dynamics at both the panel and country levels, taking into account common long-term trends as well as structural heterogeneity across countries to ensure robust results. Panel-level MG-DOLS cointegration analysis indicates that tourism capital investments, gross fixed capital formation, and international tourist arrivals have significant and positive effects on economic growth, thereby supporting the extended Solow hypothesis. Country-level DOLS analyses reveal heterogeneity in these effects; while tourism and capital indicators exhibit positive and significant relationships with economic growth in Azerbaijan and Turkey, structural differences in the other countries prevent full confirmation of the hypothesis. The findings highlight tourism’s strategic importance for economic growth and the necessity of integrating it into the economic structure. Policy reforms, investment strategies, sectoral prioritization, revenue diversification, infrastructure improvements, and enhanced investment efficiency are essential to maximize growth potential. Overall, the study demonstrates that tourism plays a positive and strategic role in supporting macroeconomic growth and emphasizes coordinated policies and targeted investments to fully realize its economic contribution across the analyzed countries.

Arnold Tóth, Ramin Astanli, Erika Varga

Objective: The article aims to examine the impact of digitisation on employment and productivity in the financial sector and provide a comparative analysis between the Central European and the Baltic countries as no study has yet compared these two regions in terms of digitalisation and information and communication technology (ICT) usage despite similar economic backgrounds. Research Design & Methods: To address this, we applied a two-pronged approach that combines a literature review with an empirical analysis of secondary data. We used multivariate analysis of variance (MANOVA) to estimate the simultaneous total effect of ICT use on employment and productivity and ordinary least squares (OLS) regression to examine the specific relationships identified by MANOVA. Findings: Central European countries generally exhibit higher levels of employment and productivity than their Baltic counterparts, highlighting regional differences in economic conditions and labour market dynamics. ICT has a major impact on productivity but is also associated with declining employment levels, which raises concerns about potential job displacement. Investments in the financial sector have a positive effect on employment, which highlights its crucial role in supporting employment growth. Implications & Recommendations: By implementing best practices and encouraging a culture of ongoing learning and innovation, the digital transformation of Central Europe and the Baltic countries can become smooth and successful. Regional comparative analysis further provides valuable contextual insights, highlighting the need for tailored policy interventions. Contribution & Value Added: The analysis shows that investments do not have a significant direct effect on productivity. Capital investment does not guarantee an increase in output, just emphasises the need for a strategic investment approach.

Victor, CHEN

This study investigates the relationship between innovation activities and firm-level productivity among early-stage high-tech startups in China. Using a proprietary dataset encompassing patent records, R&D expenditures, capital valuation, and firm performance from 2020 to 2024, we examine whether and how innovation, measured by patents and R&D input, translates into economic output. Contrary to established literature, we find that patent output does not significantly contribute to either income or profit among the sampled firms. Further investigation reveals that patents may primarily serve a signaling function to external investors and policymakers, rather than reflecting true innovative productivity. In contrast, R&D expenditure shows a consistent and positive association with firm performance. Through mechanism analysis, we explore three channels (organizational environment, employee quality, and policy-driven incentives) to explain the impact of R&D, identifying capital inflow and valuation as key drivers of R&D investment. Finally, heterogeneity analysis indicates that the effects of R&D are more pronounced in sub-industries such as smart terminals and digital creativity, and for firms based in Shenzhen. Our findings challenge the prevailing assumption that patent output is a universal indicator of innovation success and underscore the context-dependent nature of innovation-performance linkages in emerging markets.

Mohammadhossien Rashidi

Exit timing after an IPO is one of the most consequential decisions for venture capital (VC) investors, yet existing research focuses mainly on describing when VCs exit rather than evaluating whether those choices are economically optimal. Meanwhile, large language models (LLMs) have shown promise in synthesizing complex financial data and textual information but have not been applied to post-IPO exit decisions. This study introduces a framework that uses LLMs to estimate the optimal time for VC exit by analyzing monthly post IPO information financial performance, filings, news, and market signals and recommending whether to sell or continue holding. We compare these LLM generated recommendations with the actual exit dates observed for VCs and compute the return differences between the two strategies. By quantifying gains or losses associated with following the LLM, this study provides evidence on whether AI-driven guidance can improve exit timing and complements traditional hazard and real-options models in venture capital research.

Ariel Favier, Christine Hedde-von Westernhagen, Meghan Krieg et al.

More than half of the world's population now lives in urban environments, which concentrate services and infrastructure to satisfy the material needs of a growing number of inhabitants. The interdependencies between physical infrastructure systems are required for cities to function efficiently, but simultaneously expose cities to new hazards. Failures that emerge from one infrastructure system and cascade through these interdependencies are becoming larger and more frequent due to climate change and growing urban environments. Because of the uneven distribution of resources and basic services, cascade failures often exacerbate pre-existing socioeconomic inequalities. Human communities rely on both social capital and infrastructure services to prepare for, manage, and recover from these challenging scenarios, but the overlap between social and physical infrastructure creates unpredictable feedback dynamics. While prior research has focused on either social capital or physical infrastructure in urban disaster management, an integrative view of these two perspectives is seldom explored. In this paper, the feedback mechanisms between the physical and social layers of different urban designs are identified and analyzed to optimize relief response. Methodologically, we identify cities with high accessibility that have undergone disasters. From these cities, we measure their physical and social resilience indicators before and after disaster as a means to evaluate the impact of accessibility on disaster relief and preparedness. We will supplement this empirical analysis with a simulation that captures a cascade failure/disaster through a multilayer infrastructure and social network model.

Rick Chen, Joseph Ternasky, Afriyie Samuel Kwesi et al.

Benchmarks such as SWE-bench and ARC-AGI demonstrate how shared datasets accelerate progress toward artificial general intelligence (AGI). We introduce VCBench, the first benchmark for predicting founder success in venture capital (VC), a domain where signals are sparse, outcomes are uncertain, and even top investors perform modestly. At inception, the market index achieves a precision of 1.9%. Y Combinator outperforms the index by a factor of 1.7x, while tier-1 firms are 2.9x better. VCBench provides 9,000 anonymized founder profiles, standardized to preserve predictive features while resisting identity leakage, with adversarial tests showing more than 90% reduction in re-identification risk. We evaluate nine state-of-the-art large language models (LLMs). DeepSeek-V3 delivers over six times the baseline precision, GPT-4o achieves the highest F0.5, and most models surpass human benchmarks. Designed as a public and evolving resource available at vcbench.com, VCBench establishes a community-driven standard for reproducible and privacy-preserving evaluation of AGI in early-stage venture forecasting.

L. Toschi, S. Torrisi, A. Fronzetti Colladon

Media reputation plays an important role in attracting venture capital investment. However, prior research has focused too narrowly on general media exposure, limiting our understanding of how media truly influences funding decisions. As informed decision-makers, venture capitalists respond to more nuanced aspects of media content. We introduce the concept of media memorability - the media's ability to imprint a startup's name in the memory of relevant investors. Using data from 197 UK startups in the micro and nanotechnology sector (funded between 1995 and 2004), we show that media memorability significantly influences investment outcomes. Our findings suggest that venture capitalists rely on detailed cues such as a startup's distinctiveness and connectivity within news semantic networks. This contributes to research on entrepreneurial finance and media legitimation. In practice, startups should go beyond frequent media mentions to strengthen brand memorability through more targeted, meaningful coverage highlighting their uniqueness and relevance within the broader industry conversation.

Ali Hasanvand

Housing is a critical economic sector, with its growth benefiting households. However, rising prices in recent years have diminished household welfare. Using provincial-level data (2011–2021) and a spatial econometric approach, this study analyzed the factors driving housing price increases. The findings revealed that urbanization and economic growth positively influenced housing prices, while financial development had negative spillover effects, underscoring the role of traders in price determination. Although industrialization had no direct effect, its spillover effects were found to be positive, highlighting the service sector’s influence. The study confirmed the housing price divergence and recommended enforcing tax laws on vacant properties and increasing financing in the housing sector to improve Iran’s housing market.IntroductionHousing is considered a unique commodity due to its dual nature as both a consumption good and a capital asset, along with its inelastic supply, essential role as shelter for primary households, and lack of substitutes. In the short term, housing supply remains inelastic to price changes due to the structural characteristics of durable goods. Given the significant capital aspect of housing, it is consistently subject to price fluctuations, much like other capital goods markets. Urbanization plays a dual role in housing demand: it increases consumption demand while simultaneously creating investment opportunities, driving up demand for housing as an asset. Another key factor influencing housing prices is the credit ratio. A higher credit-to-GDP ratio suggests the expansion of rentier markets—such as speculative housing transactions—that lack real added value, ultimately leading to price increases. Therefore, analyzing the factors influencing housing prices is both important and valuable.Materials and MethodsThe present research relied on theoretical and empirical literature (i.e., Cook et al., 2018; Kavlihua and Kameti, 2019; Su et al., 2021) to identify the factors influencing housing prices. Accordingly, Equation (1) was used to analyze these factors.(1)In Equation (1), pric represents the price per square meter of housing, gdp denotes real gross domestic product, indus refers to industrialization (measured as the ratio of industry value added to total value added), and cred is the ratio of bank credit to GDP, serving as an indicator of financial development. Additionally, urban represents the urbanization rate, calculated as the ratio of the urban population to the total population. Research data was collected from the Central Bank of Iran and the Statistical Center of Iran. To apply the spatial econometric approach, the study used the Moran test to examine spatial effects of the research variables.Results and DiscussionWhen spillover effects were not considered, financial development in each province had a positive and significant effect on the housing price. This is primarily because the production sector lacks more profitable investment opportunities than housing, leading to a substantial portion of credit flowing into the housing market and driving up prices. A high credit-to-GDP ratio indicates a surplus of financial resources, which, in turn, accelerates the growth of rentier activities. As a result, part of the credit expansion’s effect on housing demand stems from speculative investment, while another part is driven by increased access to credit for lower-decile households and consumer demand.The second factor influencing the housing price is GDP, which has a positive and significant effect. The rise in GDP can be analyzed from two perspectives: the macroeconomic level and the household (microeconomic) level. At the household level, an increase in GDP leads to higher per capita income, boosting purchasing power. Consequently, demand for housing—considered a normal good—rises, which drives up prices. This hypothesis is supported by two key observations: first, a relatively high proportion of households do not own homes, and second, there is a significant diversity in housing options. At the macro level, part of the increased economic growth can be attributed to the expansion of the housing sector, which led to a greater supply of housing. However, since micro-level effects outweigh macro-level effects in this case, housing prices still rose. Given that economic growth in the 1990s was below one percent, the impact of this factor was not particularly significant.The spatial camera approach was employed to examine the spatial effects of factors on the housing price. The results indicated that increased urbanization in neighboring provinces does not significantly impact the housing price in a specific province. This suggests that the opportunities and benefits of urbanization are not transferred between provinces. However, other research variables showed a significant spatial effect on the housing price. According to the estimates, a rise in the credit ratio in neighboring provinces reduces speculative demand for housing in a specific province, leading to a decline in the housing price. An increase in the credit ratio indicates greater prosperity in non-value-added speculative activities. The movement of these sources to certain provinces results in declining housing prices in others. Moreover, as GDP rises in neighboring provinces, employment opportunities become more attractive, making those provinces more desirable places to live. This then leads to a drop in the housing price.ConclusionThe rise in the housing price has long been one of the biggest challenges in ensuring affordable housing for households. As housing prices increase and a larger portion of household income is spent on essential goods, overall household welfare declines significantly. In contemporary Iran, the existing legal texts emphasize financing housing for households and enforcing the Production Leap Law. Therefore, analyzing the factors influencing housing prices is crucial for shaping an effective policy roadmap. The results indicated that rising urbanization, the credit-to-GDP ration, and GDP itself have a positive and significant effect on the housing price. Furthermore, convergence analysis suggests that housing prices in Iranian cities are diverging. The negative spatial correlation of housing prices between cities reflects the dominance of housing as a capital asset rather than a consumer good. A key factor behind traders’ strong influence in the housing market is their greater access to financial credits compared to consumer buyers. However, the positive effects of urbanization have not been widely transferable across many cities due to its benefits. Furthermore, the high share of the service sector in GDP and the positive spillover effects of industrialization across provinces have led to an inverse relationship in housing prices—rising prices in neighboring provinces have contributed to price declines in specific provinces. To improve housing conditions, the most critical policy measures include enhancing financial access for low-income households and diversifying housing options to increase their chances of securing affordable housing.AcknowledgmentsThe author sincerely thanks all colleagues and individuals who contributed to the completion of this article.

David Zámek, Liudmyla Zakharkina

In the context of rapid technological development, digitalization and transparency have a critical impact on national security, promoting transparency and combating corruption, while posing challenges to cybersecurity due to the increased availability of information. The purpose of this study is to identify, based on bibliometric analysis, trends and subject areas in research on the impact of digitalization and transparency on national security. To achieve this goal, a comprehensive bibliometric analysis of scientific works on the role of digitalization and transparency in national security published in the publications indexed by the Scopus database for 1991-2023 was conducted, which formed the statistical basis of the analysis. The bibliometric programs Vosviewer and SciVal were chosen as research tools, which allowed for an in-depth analytical review and identification of the main trends and interrelationships between different research areas, confirming the hypothesis of increasing interest in the study of digitalization and transparency in the context of national security. Based on the analysis of the common use of keywords, seven clusters were identified, covering a wide range of topics from digital transformation and adaptive governance for national security to global political and economic strategies, each of which reveals unique interrelationships between digitalization, transparency, innovation and their impact on national security, including cybersecurity challenges, ethics in governance, and the importance of transparency for democracy and human rights. The analysis of the evolutionary trends in research allowed us to identify four key periods of development of scientific interest in the impact of digitalization and transparency on national security: 1) the period from 2014 to 2016 is characterized by initial research on the role of digitalization in national security and mainly concerns e-government studies; 2) during 2017-2018, research focuses on the growing attention to transparency and its role in national security 3) in the period from 2019 to 2021, there is an increase in the number of studies related to cybersecurity and the impact of digital technologies on democracy; 4) from 2022 to the present, there is further in-depth research on topics related to artificial intelligence The spatial clustering of studies shows a high level of international integration in research on the impact of digitalization and transparency on national security. The findings can be used by state institutions to improve national security strategies, in particular by adapting the legislative framework to the challenges of digitalization and ensuring transparency at all levels of government and public life, including macro (national), meso (regional) and micro (local) levels, ensuring openness and accountability in all spheres of government and public control, which will ultimately contribute to ensuring stability and security at the national level.

Gökçen Aydınbaş

This study aims to investigate the relationship between “trade openness” which represents international trade, and the employment rate, capital stock and GDP per capita for 9 countries selected among emerging market economies (Turkiye, Russia, China, Singapore, Thailand, South Korea, Argentina, Brazil and South Africa) with annual data for the period 1991-2019. In this study, it was used the panel causality analysis. According to the findings of the study, the variables with bidirectional causality relationship are trade openness and GDP per capita, trade openness and employment rate and capital stock. In conclusion, even though international trade is recognized as a powerful engine for economic growth, policies are needed to ensure that the opportunities it offers are shared equally. This requires efforts to promote free and fair trade, a combination of education and infrastructure investments in support of local development, and ultimately a mutually beneficial relationship between countries and their global counterparts.

J. Hirshleifer

Naser Izadinia, Hasan FattahiNafchi

One of the goals of firms is to optimize their capital structure. Due to transaction costs, the actual capital structure is always deviated from the optimal and cannot be immediately adjusted. Therefore, examining the factors affecting the financial leverage adjustment speed can be important. This research aims to investigate the effect of economic uncertainty and investment increase on the financial leverage adjustment speed. For hypothesis testing, a sample of 130 companies listed on the Tehran Stock Exchange during the period 2016-2021 was selected, and hypothesis testing was carried out using multiple regression and panel data. The results of hypothesis testing show that economic uncertainty has a positive and significant effect on the financial leverage adjustment speed in firms with excessive financial leverage, but this effect is not significant in firms with lower financial leverage. Additionally, firms with excessive financial leverage have a slower rate of leverage adjustment during periods of investment increase than during normal periods. However, investment increase has no effect on the financial leverage adjustment speed in firms with lower financial leverage. Moreover, the results show that in conditions of investment increase, firms with excessive financial leverage and low economic uncertainty have a leverage adjustment speed close to zero, while economic uncertainty has no effect on the financial leverage adjustment speed in firms with lower financial leverage during periods of investment increase.IntroductionMany studies on capital structure have shown that firms continuously adjust their financial leverage based on changes in their internal and external environment to maximize their financial security, financing, and value. One of the factors affecting the financial leverage adjustment speed of firms is the uncertainty of economic policies. Economic policies including monetary, financial, regulatory, and tax policies, shape the business environment. Economic uncertainty can be a major reason for the financial leverage adjustment speed of firms due to its intangible nature (Dang et al., 2012; Fernando et al., 2021; Im et al., 2022). On the other hand, periods of investment growth provide valuable opportunities to achieve a theoretical framework for corporate capital structure decisions because major investments usually require external financing (Tan et al., 2021). Therefore, this study examines the impact of economic uncertainty on the speed of adjustment of financial leverage and the role of economic uncertainty in the intensity of the effect of investment growth on the financial leverage adjustment speed in firms with excessive and lower financial leverage. Methods & MaterialA sample of 130 companies listed on the Tehran Stock Exchange during the period 2016-2021 was selected for testing hypotheses. Multiple regression and panel data were used to examine the hypotheses. The dependent variable is the financial leverage adjustment speed, and the independent variables are economic uncertainty and investment growth. The research hypotheses were examined separately in companies with excessive and lower financial leverage.FindingThe study's findings reveal that high economic uncertainty in firms with excessive financial leverage leads to an increase in the speed of financial leverage adjustment. However, in firms with less financial leverage, economic uncertainty has no significant effect on the speed of adjustment. The results also suggest that firms with excessive financial leverage exhibit a slower leverage adjustment speed during periods of increased investment. Conversely, firms with less financial leverage are unaffected by an increase in investment and exhibit no significant difference in the speed of leverage adjustment. Furthermore, other findings have also shown that in firms with excessive financial leverage and low economic uncertainty, an increase in investment does not impact the financial leverage adjustment speed. Finally, contrary to expectations, in conditions of increased investment, firms with lower financial leverage and less uncertainty do not have a greater leverage adjustment speed. Conclusion & ResultsWhen there is high economic uncertainty and a firm has excessive debt, then due to pressure from financial suppliers, firms are forced to reduce their debt. As a result, the financial leverage adjustment speed increases. In firms with less-than-optimal levels of financial leverage, since the leverage ratios of such firms are almost below the optimal level, economic uncertainty does not significantly affect the cost of increasing debt and the financial leverage adjustment speed. When there is an increase in investment in a year and the company also has excessive debt, then the increase in investment due to increased financial supply pressure causes firms to adjust financial leverage towards the target leverage at a slower pace. To avoid the direct and indirect costs of increasing financial leverage, such firms try to finance the increase in investment from other sources rather than increasing financial leverage. In firms with excessive financial leverage and low economic uncertainty, an increase in investment did not have much effect on the financial leverage adjustment speed. This could be because if the increase in investment is reliant on financing debt, highly leveraged firms facing low economic uncertainty will deviate from their leverage goals during the investment period and the financial leverage adjustment speed will become negative or close to zero. Ultimately, contrary to expectations, it was observed that in conditions of increased investment, firms with less financial leverage did not have a higher speed of adjusting their financial leverage than those with excessive financial leverage facing low uncertainty. This is probably because in firms with less financial leverage facing low uncertainty, financing investment through debt is not possible and managers use other options such as issuing shares. * Corresponding author

Francesco Farina, Mike Arpaia, Harpal Khing et al.

The optimal portfolio size for a venture capital (VC) fund is a topic often debated, but there is no consensus on the best strategy. This is because it is a function of many factors. It is not easy to find a general formula that can be applied to all situations, and it largely depends on the goal of the fund. In this report, we will go through the different factors step by step, studying how they affect fund returns and the optimal portfolio size, starting with some basic assumptions and then increasing the complexity of the model.

Christophe Jurczak

Building on decades of fundamental research, new applications of Quantum Science have started to emerge in the fields of computing, sensing and networks. In the current phase of deployment, in which quantum technology is not yet in routine use but is still transitioning out of the laboratory, Venture Capital (VC) is critical. In association with public funding programs, VC supports startups born in academic institutions and has a role to play in structuring the priorities of the ecosystem, guiding it towards applications with the greatest impact on society. This paper illustrates this thesis with a case-study: the experience of the first dedicated quantum fund, Quantonation I, chronicling its impacts on the production of scientific knowledge, job creation and funding of the industry. The paper introduces concepts to support the emergence of new startups and advocates for funding of scale-up quantum companies. The paper concludes with proposals to improve the impact of the industry by taking steps to better involve society-at-large and with a call for collaboration on projects focused on the applications with a large societal benefit.

Refiloe Julia Lekgau, Tembi Maloney Tichaawa

This study departs from the premise that COVID-19 has fast-tracked the transition to the virtual environment in the global meetings, incentives, conference/convention, and exhibition (MICE) events sector. Using South Africa as a case study, the research explores the use of virtual and hybrid events in enhancing the resilience of MICE events. Adopting a mixed methods approach, data was collected from 19 purposively selected MICE tourism stakeholders (involved in the planning and organizing of the MICE sector) as well as 500 MICE event attendees. The findings reveal that virtual and hybrid MICE events ensured the business continuity of the MICE sector during COVID-19. Additionally, these events were found to be essential for information sharing and proved valuable in times of uncertainty. The study further found that these events provided substantial market opportunities for MICE stakeholders in the country. However, the study uncovered that certain sub-sector of MICE, as well as some key functions, cannot be easily replicated in the virtual space. Moreover, several challenges surfaced when hosting such events, including the matter of internet connectivity and the significant capital investments required for their execution. Overall, the study concludes that virtual events have emerged as a valuable tool for enhancing the resilience of MICE events to crises, and hybrid events are postulated to become a prominent feature in MICE events offerings in the future.

Maryam Mehrara, Amir Gholami, Seyed Mohammad Mehdi Ahmadi

Due to the importance of balancing internal and external of the economy, research on the interaction effects of the budget deficit, savings gap, and current account deficit has always been a major issue for policymakers. The main purpose of this study was to test the validity of the triple deficit hypothesis during the period 1978-2019 in the Iranian economy with the presence of the degree of trade openness for two models of oil trade and without oil trade. In the present paper, by providing a theoretical framework and using the Johansen - Juselius cointegration test method and the error correction mechanism, long-term and short-term relationships of the variables of this research are investigated. The results showed that the long-run relationship among the components of the triple deficit hypothesis is established in the two models of oil trade and without oil trade, but the validity of the triple deficit hypothesis is not confirmed in the short run. Through the Impulse response functions, decisions were made about the interrelationships among the variables, and the results of this method confirmed the validity of the triple deficit hypothesis for the oil trade model and the occurrence of the inverse mechanism for the oil-free trade model. Finally, in the oil trade model, internal and external imbalances reduced trade openness, and in the non-oil trade model, only the savings gap played such a role. This emphasized the key role of the private sector in reducing internal and external imbalances.

V. S. Levin, E. V. Satalkina

The paper is devoted to the research of foreign direct investment accounting in the capital of Russian companies, identifies the similarities and differences in approaches to identifying direct investments in accordance with international and domestic legal norms, detects the problems of inward foreign direct investment accounting and in statistical reports. The subject of the study is the problems of theory and practice of foreign direct investment accounting. The research is based on general scientific principles and research methods: systematization, induction and deduction, synthesis and analysis. Correct identification of direct foreign investments in accounts and reliable disclosure of the accounting information and statistical reporting, at present, causes difficulties for economic entities. The solution to these problems is available through the implementation of the professional judgment of the accountant. The work results having theoretical and applied significance, can be used as a basis for the development of a company’s accounting policy.

Grace H. Wolff, Cuihua Shen

This study examines how active participation, financial commitment, and passive participation in the leading social live-streaming service, Twitch.tv, relate to individuals' psychological well-being. The three dimensions of social capital-structural, relational, and cognitive-as well as parasocial relationship are explored as mediators. Cross-sectional survey data from 396 respondents was analyzed by comparing two fully saturated structural equation models. Findings indicate actively participating in a favorite streamers' Chat is positively associated with increased well-being. Structural social capital, or having more social interaction ties, positively mediates the relationship between active participation and well-being, as well as financial commitment and well-being. Greater cognitive social capital, or shared values and goals with a favorite streamer, is related to decreased well-being. Parasocial relationship does not significantly mediate the relationship between use and well-being. Our results demonstrate the importance of tangible social ties over the perceived relationships or identification with a favorite streamer.

Merton H. Miller, Myron S. Scholes

Linda Schultz, Julie Ruel-Bergeron

School health and nutrition (SHN) interventions are among the most ubiquitous public health investments and comprise a key mechanism for reaching populations that are otherwise difficult to reach through the health system. Despite the critical role of monitoring these multisectoral programs to enable data-informed adaptive programming, information to guide program implementers is scant. This manuscript provides an overview of how monitoring indicators can be selected across a SHN program's logical framework, with specific examples across five SHN implementation models. Adaptation of SHN programs in times of school closures, such as those currently being experienced globally due to the emergence of COVID-19, is also addressed. Key aspects of SHN program monitoring are explored, including: (1) why monitor; (2) what to measure; (3) how to measure; and (4) who measures. In situations of school closures, strategies to shift both program activities and corresponding monitoring mechanisms are critical to understanding the rapidly evolving situation and subsequently guiding policy actions to protect vulnerable populations.