Facing multiple conflicting goals, consumers may attempt to simultaneously pursue multiple goals by choosing mixed vice–virtue bundles in each consumption episode (mixed approach). Alternatively, they may maximize their pursuit of one goal at a time and sequentially manage multiple goals by alternating between pure-virtue and pure-vice bundles across consumption episodes (extreme approach). The current research proposes that consumer preferences between the two approaches depend on mindset abstraction. Across four experimental studies in the domains of food and financial decision-making, we demonstrate that, relative to an abstract mindset, a concrete mindset increases preference for the extreme approach over the mixed approach. Furthermore, by observing actual food choices over a seven-day period, this research provides a comprehensive picture of how a chronic mindset relates to multigoal management in long-term consumption patterns. The findings have both theoretical implications for the goal literature and managerial implications for marketers and policymakers.

Evidence suggests that Latin Americans display elevated levels of emotional expressivity and positivity. Here, we tested whether Latin Americans possess a unique form of interdependence called expressive interdependence, characterized by the open expression of positive emotions related to social engagement (e.g., feelings of closeness to others). In Study 1, we compared Latin Americans from Chile and Mexico with European Americans in the United States, a group known to be highly independent. Latin Americans expressed positive socially engaging emotions, particularly in response to negative events affecting others, whereas European Americans favored positive socially disengaging emotions, such as pride, especially in response to personally favorable circumstances. Study 2 replicated these findings with another group of Latin Americans from Colombia and European Americans in the United States. Study 2 also included Japanese in Japan, who expressed positive emotions less than Latin and European Americans. However, Japanese displayed a higher tendency to express negative socially engaging emotions, such as guilt and shame, compared to both groups. Our data demonstrate that emotional expression patterns align with overarching ethos of interdependence in Latin America and Japan and independence among European Americans. However, Latin Americans and Japanese exhibited different styles of interdependence. Latin Americans were expressive of positive socially engaging emotions, whereas Japanese were less expressive overall. Moreover, when Japanese expressed emotions, they emphasized negative socially engaging emotions. Implications for theories of culture and emotion are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

As a new product that combines finance and digital technology, digital finance is of great significance to the governance of the ecological environment. Based on the panel data of 2128 counties in China from 2014 to 2020, the fixed effect model and a panel threshold model are established, and the direct impact, heterogeneity, and transmission paths of digital finance development on ecological environment quality are empirically analyzed. The results demonstrate that the progress of digital finance has a significant negative effect on ecological environmental performance, and robustness tests support this conclusion. Additionally, industrial agglomeration and structural transformation are crucial mechanisms through which digital finance hinders ecological environmental performance. Moreover, the adverse influence of digital finance development on the ecological environment is particularly pronounced in densely populated areas, county-level cities, and non-poverty-stricken counties. Fourthly, based on the development level of digital finance itself, digital finance has a double threshold effect on the performance of county ecological environment. When digital finance is at a low level and a high level, its negative impact on eco-environmental performance is the greatest. Between the low level and the high level of digital finance, digital finance has the greatest negative impact on the performance of the ecological environment. Finally, suggestions are put forward to promote the green development of digital finance, foster balanced regional development, and expedite industrial transformation in underdeveloped regions.

This research examines how individuals respond differently to recommendation options generated by ChatGPT, an AI-powered language model, in five studies. In contrast to previous research on choice overload, Studies 1 and 2 demonstrate that people tend to respond positively to a large number of recommendation options (60 options), revealing diverse consumer perceptions of AI-generated recommendations. Studies 3 and 4 further illustrate the moderating effect of recommendation agents and indicate that choice overload elicits distinct patterns of consumer reactions depending on whether the recommendations are from a human or AI agent. Lastly, Study 5 directly measures consumer preferences for recommendation agents, revealing a general preference for ChatGPT, particularly when a large number of options are available. These findings have significant implications for recommendation system design and user preferences regarding AI-powered recommendations.

Purpose Fairness concerns in the supply chain management have recently caught much attention in the OM research community. The combined effect of fairness and competition on supply chain coordination and the interplay between them, however, have yet to be thoroughly examined. Design/methodology/approach The authors study a multiplayer supply chain with one supplier and two competing retailers with fairness concerns by a three-player Stackelberg game model. This theoretical study provides equilibrium solutions under different ranges of fairness and competition combinations. Besides theoretical analysis, the authors also conduct standard economic experiments and estimate structural parameters using experimental data. Findings The authors find that a simple wholesale price can coordinate the whole supply chain with certain conditions of fairness and competition. Moreover, although fairness concerns always decrease the wholesale price and increase retailers' profit share, downstream competition weakens such effects and decreases downstream players' market share. The experiments confirm the existence of fairness concerns and the interaction of competition and fairness, as shown in the theoretical analysis. Research limitations/implications A more comprehensive model with both distributional and peer-induced fairness considered could generate better insights in the interactive impact of competition and fairness. Moreover, the authors followed the previous channel competition literature and modeled the demand with linear demand function which makes the game decisions trackable in closed form solution. A more general demand function could result in different solutions and thus new insights. Originality/value The authors’ work provides a comprehensive theoretical study of the interaction between fairness concerns and competition and clarifies the in-depth connection between the effects of competition and fairness concerns in the literature.

This article investigates the macroeconomic consequences of foreign asset-freezing sanctions, a tool utilized by several Western nations amid recent geopolitical tensions. Specifically, it examines the repercussions of such sanctions on open economies, finding that they may experience a sharp recession and currency crisis. To quantify the impact, we develop a new Keynesian dynamic stochastic general equilibrium model with financial frictions and an asset-freezing channel for an open economy. We also calibrate our model to capture the unique structures of the Russian economy. The quantitative analysis of the model demonstrates that an abrupt asset-freezing sanction would lead to large output losses and high inflation increases. Our counterfactual examination reveals that higher elasticity of import substitution and lower elasticity of export substitution could alleviate the impact of foreign sanctions, whereas more aggressive monetary policy may have positive but limited stabilization effects. Notably, the monetary authority must navigate a trade-off between stabilizing output and managing inflation resulting from the cash-in-advance channel.

Global warming is a non-uniform process across space and time. This opens the door to a heterogeneous relationship between CO2 and temperature that needs to be explored going beyond the standard analysis based on mean temperature. We revisit this topic through the lens of a new class of factor models for high-dimensional panel data, called quantile factor models. This technique extracts quantile-dependent factors from the distributions of temperature across a wide range of stable weather stations in the northern and southern hemispheres over 1959–2018. In particular, we test whether the (detrended) growth rate of CO2 concentrations helps to predict the underlying factors of the different quantiles of the distribution of (detrended) temperatures in the time dimension. We document that predictive association is greater at the lower and medium quantiles than at the upper quantiles of temperature in all stations, and provide some conjectures about what could be behind this non-uniformity. These findings complement recent results in the literature documenting steeper trends in lower temperature levels than in other parts of the spatial distribution.

This paper proposes a novel and intuitive indicator to measure market systemic risk. This risk indicator is established by the understanding of market’s needs for risk diversification through cross-border investment and its impact on the stability of global financial system as a whole. We formulate the risk indicator based on a measure of cross-sectional dependence that is robust to persistent and long-memory stochastic processes. In an analysis of 14 global equity markets and 10 hedging assets from January 1999 to December 2021, we demonstrate the usefulness of our indicator by showing its ability of accurately tracking international market fluctuations and its out-of-sample performance for predicting the U.S. equity market. We further analyze the impact of the U.S. macroeconomics news on market systemic risk, with the objectiveness of both measuring the change of market systemic risk and understanding how it links to various macroeconomic factors. In particular, we find that, in the long-run, monetary policy actions have a steady impact on market systemic risk regardless of whether policy changes are expected.

This study examined the role of social media sentiment in identifying irrational herding behavior in the stock market. We selected the Chinese stock market, where majority are retail investors, as the object of analysis, and analyzed the sentiment of 227,353 microblog text messages through deep learning techniques and constructed the identification method of herd behavior. Results show that social media sentiment has a significant impact on irrational herding behavior in the stock market. The findings of the study complement the theory of investor behavior and can aid in investors' trading decisions and financial regulators’ policy recommendations.

The integration of digital technologies and processes presents a multifaceted and complex challenge for family firms, as they must navigate new technologies while maintaining their unique familial attribute. Moreover, the issue of intergenerational inheritance adds an additional layer of complexity, as succession must be effectively executed to ensure the continued success and survival of the family firm in the digital age. Together, these challenges pose a significant threat to the sustainability and competitiveness of family firms. To gain a deeper understanding of how these challenges can be effectively addressed, the study utilizes data from the 2016 Chinese Private Enterprises Survey to identify the factors influencing family firms' digital transformation and the role of entrepreneurs' characteristics in this process. From the perspective of intergenerational inheritance, the study finds that both the willingness of entrepreneurs to hand over power and the willingness of their children to take over firm power have a moderating effect on the relationships between entrepreneurs' characteristics and firms’ digital transformations. This study also verifies the heterogeneous effects from the type of business digitalization, location of the firm, and educational level of the children.

In this study, we develop a data-driven heuristic method to solve the irregular flight recovery problem. Based on operational data from China South Airlines, Beijing, China, we evaluate the importance of a flight in the flight network and the influence of a delay on a flight and its subsequent flights. Then, we classify historical states into three scenarios according to their delay reasons and investigate the recovery patterns for each scenario. Inspired by the results of the data analysis, we develop a heuristic algorithm that imitates dispatcher actions. The algorithm is based on two basic operations: swapping the tail numbers of two flights and resetting their flight departure times. The algorithm can provide multiple recovery plans in real time for different scenarios, and we continue to refine and validate the algorithm for more robust and general solutions through a cost analysis. Finally, we test the efficiency and effectiveness of the recovery method based on the flight schedule, with real and simulated delays, and compare it with two other methods and the recovery actions of dispatchers.

Infectious diseases, such as COVID-19, cause disruptions to normal lives and thus trigger various adaptive reactions. We provide evidence that visual pattern-seeking, which brings perceived control in such disruptions, is one of the adaptive responses. Across five studies, consumers primed with the perceived threat of COVID-19 increase their evaluations of visually patterned advertising images and behavioural intentions to follow visually patterned messages designed to reduce the spread of the virus. The underlying process for this effect is that visual pattern-seeking helps consumers regain control that is threatened by the perceived threat of the pandemic. These findings shed light on the role of visual patterns as an effective source of communication in the COVID-19 era.

Abstract Background: This paper reviews nationally representative public opinion surveys on artificial intelligence (AI) in the United States, with a focus on areas related to health care. The potential health applications of AI continue to gain attention owing to their promise as well as challenges. For AI to fulfill its potential, it must not only be adopted by physicians and health providers but also by patients and other members of the public. Objective: This study reviews the existing survey research on the United States’ public attitudes toward AI in health care and reveals the challenges and opportunities for more effective and inclusive engagement on the use of AI in health settings. Methods: We conducted a systematic review of public opinion surveys, reports, and peer-reviewed journal articles published on Web of Science, PubMed, and Roper iPoll between January 2010 and January 2022. We include studies that are nationally representative US public opinion surveys and include at least one or more questions about attitudes toward AI in health care contexts. Two members of the research team independently screened the included studies. The reviewers screened study titles, abstracts, and methods for Web of Science and PubMed search results. For the Roper iPoll search results, individual survey items were assessed for relevance to the AI health focus, and survey details were screened to determine a nationally representative US sample. We reported the descriptive statistics available for the relevant survey questions. In addition, we performed secondary analyses on 4 data sets to further explore the findings on attitudes across different demographic groups. Results: This review includes 11 nationally representative surveys. The search identified 175 records, 39 of which were assessed for inclusion. Surveys include questions related to familiarity and experience with AI; applications, benefits, and risks of AI in health care settings; the use of AI in disease diagnosis, treatment, and robotic caregiving; and related issues of data privacy and surveillance. Although most Americans have heard of AI, they are less aware of its specific health applications. Americans anticipate that medicine is likely to benefit from advances in AI; however, the anticipated benefits vary depending on the type of application. Specific application goals, such as disease prediction, diagnosis, and treatment, matter for the attitudes toward AI in health care among Americans. Most Americans reported wanting control over their personal health data. The willingness to share personal health information largely depends on the institutional actor collecting the data and the intended use. Conclusions: Americans in general report seeing health care as an area in which AI applications could be particularly beneficial. However, they have substantial levels of concern regarding specific applications, especially those in which AI is involved in decision-making and regarding the privacy of health information.

Managerial multitasking has become a common practice in the mutual fund industry. Although multitasking may have certain benefits for fund companies and portfolio managers, these arrangements have significant drawbacks for fund investors. We find that multitasking is associated with worse fund performance. Moreover, we find significant performance deterioration when a single-tasking manager switches to multitasking. We further demonstrate evidence that suggests that multitasking reduces the attention or limits the investment options a manager can allocate to their funds. Our study prescribes caution when assigning a portfolio manager a greater workload, as doing so adversely affects fund performance and, at some point, the ability of the fund family to attract capital.

The sunk-cost fallacy is a well-documented cognitive bias in the decision-making literature. Although the emerging literature on childhood socioeconomic status suggests that early-life environments shape individuals' decision strategies and have a long-lasting impact on their decisions, little is known about the impact of childhood socioeconomic status on the sunk-cost fallacy. Using two different scenarios and an actual choice task, we provide converging evidence that individuals who grew up in resource-scarce environments (those with lower childhood socioeconomic status) are reluctant to abandon inferior choices merely because they have already invested substantial resources in them, resulting in the sunk-cost fallacy. This fallacy occurs because individuals with lower childhood socioeconomic status tend to perceive the loss of their prior investments as more wasteful than those with higher childhood socioeconomic status.

We present a simple model featuring the supply side of the Bitcoin ecosystem, i.e. the market structure of “mining”, to rationalize the relationship between the Bitcoin price volatility and the market concentration in pool mining. An individual miner optimally chooses to operate individually or to delegate the mining capacity in hashrates to a mining pool. The mining pool entertains the trade-off between compromising the network derived from its market power and maintaining sufficient hashrate delegations from dispersed miners. We show that a mining pool finds it optimal to be self-constrained in size while maintaining a positive probability of compromising the network in equilibrium. As a result, the bounded market concentration in pooled mining caps the Bitcoin price fluctuations. We also document important empirical evidence which is consistent with our model predictions.

This article conceptualizes the Sensitive Word Culture as a new theoretical lens for understanding how Chinese netizens interact with Internet censorship systems. Through the use of 22 in-depth interviews of Chinese Weibo users and netnography as empirical material, eight types of word recoding practices are identified and mapped into two discourse strategies, namely “evading detection” and “expanding interpretability.” Drawing on the concepts of everyday resistance and everyday politics, we analyze the power relations behind these discourse strategies, and also identify the apolitical aspects and scope of the Sensitive Word Culture. One notable finding is that the Sensitive Word Culture is becoming a part of China's digital cultural production, influencing the development of slang and memes. This research offers insights into how censorship from artificial intelligence and human intelligence influences the online discourses on Chinese social media.

The expansion of the internet has provided people with more channels to obtain information. New information about the world and other lifestyles provided by the internet may affect teenagers’ attitudes and change their behavior of first marriage in adulthood. Using data from China Family Panel Studies, this paper explores a national policy reform of the internet in 2000 and combines a difference-in-difference framework with a discrete-time hazard model to estimate the impact of internet exposure in adolescence on women’s age at first marriage. The results show that internet exposure during adolescence significantly reduces the risk of women’s age at first marriage. No change is observed in men of similar age. Further analysis of the mechanism shows that women’s education or search costs in the marriage market cannot explain the findings. In contrast, women’s traditional attitudes toward gender roles vary with internet exposure. Their gender role attitudes become more egalitarian, and their attitudes toward marriage become more open. Exposure to the internet also makes women even more reluctant to enter marriage, an institution that is increasingly differentiated by traditional gender roles.

Household debt is an important part of household financial decision-making, and commercial medical insurance has gradually become an important tool for households to use in improving their household balance sheets. Based on 2017 China Household Finance Survey (CHFS) data, this paper studies the impact of commercial medical insurance participation on household debt and analyzes the heterogeneity of household conditions, such as the location of the household, the age of the household head, and the health status of members. The study found that households participating in commercial medical insurance are more likely to be indebted, and their degree of debt is higher than that of households without commercial medical insurance. For urban households, young households, and households with healthy members, the participation of commercial medical insurance has a high effect on the likelihood and the degree of debt. Therefore, while strengthening household insurance awareness, the government should promote the strengthening of the risk-resistance function of commercial medical insurance and encourage financial institutions to design products that combine insurance and credit to release households’ consumption and investment potential.

(1) Background: Risk perception is a key factor in motivating people to comply with preventive behaviors during the COVID-19 pandemic. Appropriate risk perception is important to enhance beliefs and promote emergency management response to public health events. (2) Objective: This study developed a public risk perception measurement method for social media data to understand the dynamic characteristics of risk perception and emotional expression during public health emergencies. (3) Methods: Utilizing text-mining techniques and deep-learning algorithms, risk perception was calculated from two dimensions (dread and unknown) as well as the emotional expression characteristics of 185,025 posts from 10 January 2020 to 20 March 2020 on Sina Weibo. We also analyzed the characteristics of risk perception at different stages of the crisis life cycle. Furthermore, drawing on arousal theory, we constructed dynamic response relationships between emotion type (angry, fearful, sad, positive, and neutral) and risk perceptions by a vector autoregressive (VAR) model. (4) Results: The results revealed that the public expresses significantly more dread words than unknown words in shaping the risk perception process. As for the characteristics of evolution, public risk perception had been at a high level since the outbreak stage, and there was a sudden increase and a gradual decrease in the level of public risk perception. We also found that there is a significant response relationship between positive emotion, angry emotion, and risk perception. (5) Conclusion: This study provides a theoretical basis for more targeted epidemic crisis interventions. It points out the need for health communication strategy makers to consider the public’s risk perception and emotional expression characteristics during public health emergencies.