This study investigates risk-taking behavior among contestants on the TV show Do You Want to Be a Millionaire?, contributing to a literature that has largely focused on Western European and North American contexts. To reduce the influence of contestants' factual knowledge on observed choices, the analysis focuses on decisions made immediately after the use of the 50/50 lifeline, where the decision environment more closely resembles a binary risky choice and the role of factual knowledge is reduced. Logistic regression is applied to a sample of 200 contestants. The results reveal statistically significant relationships between risk-taking, marital status, and the number of children. The relationship between the number of children and risk-taking appears non-monotonic. Contestants with one child and those with three or more children show significantly higher odds of taking risks, while the coefficient for two children is not statistically significant. Gender does not have a statistically significant effect in any of the model specifications.
Using a comprehensive data set containing organizational histories of all television soap operas that aired in the United States from 1949 to 2012, we focus on endogenous institutional dynamics that ultimately led to the dramatic decline of the once thriving form. Specifically, we focus on the rise of "institutionally central" soap operas that gave legitimacy to the form. We show that these soap operas, more than others, led to both the dramatic success and deep institutionalization of the form in the years following its emergence on television and also to the stagnation and decline of the form more recently. By defining the form in the minds of audiences in fairly narrow terms and attractive a lion's share of viewers, these institutional central soap operas crowded out existing competitors and new entrants that may have given the industry added dynamism and diversity that would have helped it weather a changing industry landscape.
Despite growing academic interest in Cultural and Creative Industries, empirical evidence on how firms manage their financial resources remains limited. This gap is particularly evident in the video game development sector, where research has largely focused on platforms, consumers, or innovation outcomes, overlooking firms' balance-sheet structures. This study examines the relationship between financial structure and organizational outcomes-release activity, production timing, and firm continuity-among European video game studios using a longitudinal dataset combining Orbis and IGDB data (2009-2020). The results show that stronger internal capitalization is associated with greater release activity, faster production timing, and lower inactivity. Liquidity plays a differentiated role: structures oriented toward operational deployment are linked to higher activity, whereas liquidity held as short-term buffers is associated with slower and less frequent releases and a higher risk of inactivity. This study contributes by linking internal financial configurations to firm dynamics in the video game industry.
This paper investigates whether the entry and subsequent expansion of the sports broadcaster DAZN in the German Bundesliga media market influenced the temporal allocation of top-team matches. Following regulatory changes, DAZN acquired rights to broadcast Friday fixtures in 2019 and both Friday and Sunday fixtures from 2021 onward. Using a match-level panel dataset across six Bundesliga seasons (2017/18-2022/23), we estimate a linear probability model (LPM) with interaction terms to determine whether top teams became more likely to appear in DAZN-controlled time slots. Our findings reveal no significant changes following DAZN's initial entry but a measurable redistribution of top-team fixtures to DAZN slots after the 2021 rights expansion. These results are robust across alternative top-team definitions and a team-season panel analysis. They suggest that broadcasters may exert indirect influence on fixture allocation through strategic match selection and thus bear important implications for policymakers, league organizers, and the governance of scheduling practices.
This study investigates the impact of stage-specific media sentiment on IPO underpricing in China's A-share market during the transitional period of registration-based reform. Using computer-assisted content analysis of 5,988 news articles covering 239 IPOs in 2022, we identify pronounced temporal dynamics in financial media coverage. Media attention peaks before listing, while tone shifts from predominantly negative pre-IPO to markedly positive on the IPO day, before moderating post-IPO. Empirical results show that pre-IPO sentiment significantly predicts first-day returns: more negative coverage is associated with greater underpricing, whereas positive sentiment corresponds to lower initial returns. Sentiment reversal from the pre-IPO stage to the listing day is also positively related to first-day returns, suggesting that short-term expectation revisions may contribute to underpricing. By contrast, media attention exerts only limited and firm-size-contingent effects. These findings are consistent with ex-ante uncertainty and prospect theory, suggesting that pessimistic pre-IPO framing may elevate perceived uncertainty and lead to more conservative offer pricing in a retail-dominated market. While based on a transitional regulatory year, causal interpretation remains subject to potential endogeneity. Future research using multi-year data and stronger identification strategies could further clarify the causal and long-term valuation effects.
Often called the "superstar effect," the presence of large right tails has been studied in a number of areas including film, music, and software. This paper highlights the superstar effect of the video game industry through the lens of private equity investment, that is, through the value accretion of video game investment and investor returns. We show that video game investments have exhibited a Pareto distribution, very close to the Pareto law of 80/20, and exhibit a more pronounced right tail than private equity investments in entertainment, software, general private equity, and even general venture capital. The pronounced right tail in private video game investment has led to poor median outcomes relative to comparables, which is to say, private video game investments have exhibited starker "hit or miss" outcomes. That said, the right tail in private video game investments has been sufficiently strong so as to generate aggregate value accretion and investor returns that have been typically on par with or better than comparables, and even relatively small portfolios of video game investments could mitigate the outsized reliance on outlier investments to the point of having delivered median performance on par with or superior to comparables.
This study applied niche theory to examine competition among four media platforms through 20 in-depth interviews with users, four in-depth interviews with podcast executives, and a survey of 1200 respondents. It reached four conclusions: (1) Five gratifications were identified, with YouTube ranking highest, followed by podcasts, digital radio, and traditional radio. (2) YouTube's ads were seen as intrusive, and it was less suited for multitasking. (3) Podcasts were preferred for multitasking, and their audio ads were well-received. (4) Users viewed YouTube and podcasts as similar, while digital and traditional radio were also seen as comparable. The findings highlight distinct user preferences and media strengths.
This study examines Black-owned broadcast stations from 2009 to 2023, using FCC data. Our analysis reveals persistently low Black ownership and significant gender disparities, exposing enduring systemic barriers. Drawing on media political economy and epistemic rights frameworks, these findings indicate current economic and regulatory systems violate communities' rights to knowledge production and distribution. The dismantling of federal DEI initiatives now threatens to further exacerbate these disparities. This analysis suggests the need for targeted policies and practices to dismantle these obstacles and foster equitable media ownership.
This paper examines the impact of political uncertainty intensified through social media platforms on the U.S. stock market. Using both the event study approach and the fixed-effect model, we analyze a unique dataset of Trump tweets that were flagged for containing false and misleading information. These flagged tweets serve as a novel proxy for political uncertainty during the 2020 U.S. Presidential Election and the COVID-19 pandemic. We find that on days when at least one Trump tweet was flagged, S&P 500 firms experience statistically significant increases in abnormal returns, heightened intraday volatility, and surges in trading volume. These effects are more pronounced in policy-sensitive industries, such as defense, healthcare, finance, and infrastructure, compared to less regulated sectors. Our findings offer wide-ranging implications for policymakers, investors, and regulators of social media platforms.
The rise of finfluencer's financial content communication on social media platforms has transformed how individual investors absorb financial information and execute investment decisions. Considering this critical research theme, this study explores how finfluencers, as new-age attention-based economic agent within the digital media ecosystem, stimulate emotions, intentions and reframe the investment behavior with their specific financial narratives. The structural relationship and mediation model are empirically validated using partial least squares structural equation modeling (PLS-SEM) based on survey data from Indian retail investors.' The results demonstrate that the emotional engagement perceived from asset tips and financial education influences investment intention and behavior. Trading strategies, investment reviews and market analysis of the other conjunctions failed to have a notable effect. The findings imply that the investor's response to finfluencer content is molded less by rational utility maximization and more driven by behavioral and informational economics notions. This provides useful insights for finfluencers, educators and policymakers seeking to promote more informed and intellectually balanced financial communication strategies and investment behavior in the digital economy.
Over-the-top (OTT) services have introduced substantial challenges, such as subscriber attrition and declining profitability, to the pay-TV market. As preventing market loss in the pay-TV market is difficult, developing market strategy for retaining current subscribers is critical for survival in the market. This calls for an understanding of how additional OTT subscriptions and their associated increases in household expenditure on media content influence consumer choices regarding pay-TV services. Hence, this study investigates consumer preferences for pay-TV services by considering the introduction of an OTT service market. The results show that only 1.1% of respondents engaging in newly paid OTT subscriptions opt for cord-cutting; however, 8.2% are inclined toward cord-shaving, underscoring it as a more pronounced threat to the pay-TV market. Additionally, revenue loss in the pay-TV market is also analyzed. This study offers insights into forecasting market changes and developing strategic management strategies for the pay-TV market.
This study examines the Southeastern European press market from 2019 to 2023, focusing on the relationship between advertising revenue and readership across print and digital media. The period is marked by declining print and rising digital revenue, driven by shifting audience preferences. Using pooled OLS regression with regional and time controls, the analysis identifies press freedom (WPFI) as a key determinant of market performance: greater press freedom correlates with higher advertising revenues, while limited freedom drives audiences toward digital press for alternative viewpoints. Political corruption in the region further undermines the digital press's ability to monetize effectively through advertising. Demographically, print press remains more popular among older audiences, while digital usage by younger groups shows a negative correlation. The relationship between digital and print media is complex: while digital advertising revenue increases with higher print readership - suggesting a form of cross-platform support - greater digital use is negatively associated with print advertising revenue. These mixed patterns point to both complementary and substitutional tendencies, shaped by broader economic and institutional factors. The findings offer useful insights into the evolving media landscape, where traditional and digital formats interact in overlapping and sometimes competing ways.
We examined how the amount of violence depicted in a webcomic episode was related to readers' ratings of the episode and their perceptions of violence. Furthermore, we investigated how the relationships varied depending on whether the webcomic was action-oriented. To measure violence and readers' perceptions, we used computational methods based on deep learning, and the relationships between the variables were analyzed using regression models. We analyzed 251 episodes from 23 webcomics. The results revealed that the number of violent scenes in a webcomic episode was negatively associated with the ratings of the episode, regardless of whether the webcomic was action-oriented. However, the negative association was stronger for non-action-oriented webcomics than for action-oriented ones. We found that the number of violent scenes in an episode was positively associated with the number of viewers who perceived violence in the episode negatively and that this relationship was stronger for non-action-oriented webcomics.
AI awards serve as a mechanism for legitimizing technological innovation. Recognition through such awards positions recipients as influential actors in shaping how AI is applied within journalism. But why do some countries lead in journalistic AI award recognition while others lag behind? Drawing on Innovation Systems Theory, this study explores how national innovation capacity, media system structures, and journalistic role orientations influence international recognition for AI-driven journalism innovation. Using a cross-national comparative design, the analysis links secondary data on national indicators of innovation capacity, media system characteristics, and journalistic professionalism to international AI award recognition in the 2024 and 2025 Global Media Awards, organized by the International News Media Association (INMA). Results show that countries with strong national innovation capacity and watchdog-oriented journalistic cultures are more likely to receive recognition for AI innovation, while traditional media system characteristics and general professionalism show limited predictive power. The results highlight the importance of systemic conditions, rather than just organizational factors, in shaping how AI innovation is adopted in journalism. The study contributes to scholarship on media innovation and the global diffusion of AI in journalism.
