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

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. Howeve

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 devel

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 eff

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 mon

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 compleme

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 polic

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