Is there a CSI-leverage nexus?

We examine how various measures of consumer sentiment index (CSI) affect firms' debt policy decisions. Using U.S. firm-level quarterly data from 1993 to 2017, we provide a strong positive relationship between CSI measures and corporate debt policy, implying that firms use external borrowing during a positive economic outlook and reap the tax-shield benefit. We also find that improved household optimism over financial and business sentiments leads to future household consumption. The CSI-leverage nexus is moderated by the state of firms' financial condition, reputation, and profitability. Importantly, our results are robust to sub-sample analysis, firm-level and macroeconomic controls, econometric specifications, alternative measures of sentiment including Shiller's cyclically adjusted price-earnings ratio (i.e., CAPE_SH), Baker and Wurgler (2006)’s stock market sentiment index (i.e., SENT_BW) and search-based uncertainty measure such as FEARS (i.e., Financial and Economic Attitudes Revealed by Search) index of Da, Engelberg, and Gao (2015).     

A “load-carrier” perspective approach for assessing tourism resource carrying capacity

To address the challenge of global tourism resources being overloaded or underutilization, there requires an adequate method for assessing the tourism resource carrying capacity (TRCC). However, the majority of previous evaluation perspectives on TRCC are limited by thresholds. This paper develops an innovative approach for assessing TRCC from the “load-carrier” perspective. TRCC is assessed by exploring the interaction between the carriers and loads of tourism resources. Chongqing city in China is employed as the case city to demonstrate the application of the established TRCC method. The conclusions are as follows: 1) This study elaborates the new connotation of TRCC from the perspective of “load-carrier”, and establishes the TRCC evaluation system based on the dynamic relationship between the carrier and load of tourism resources. 2) The proposed TRCC evaluation method is proved effective through an empirical study of Chongqing. 3) Chongqing's case unveils that the overload performance of TRCC can be dynamically monitored and predicted. By applying the TRCC evaluation methodology developed in this study, tourism managers and policymakers can identify whether it is the load or the carrier of tourism resources that affect the performance of TRCC, thereby taking targeted policy measures to eliminate potential risks of overload or underutilization.     

Fear appeals and coping appeals for health product promotion: Impulsive purchasing or psychological distancing?

The prevalence of online health communities (OHCs) motivates health product companies to manipulate persuasion-based marketing strategies, including fear appeals and coping appeals, to promote health products. However, whether such a practice is effective remains unclear. Respondents may either impulsively purchase the recommended health products or simply distance themselves psychologically from the information. Building on protection motivation theory (PMT), this study uncovers the mechanisms behind these two coping responses to persuasive messages, namely, the impulsive purchasing and psychological distancing of OHC users. Correspondingly, we evaluated 366 valid questionnaires, and the results reveal that (1) when encountering fear appeals, perceived health threat can evoke cyberchondria, leading to psychological distancing; and (2) when encountering coping appeals, perceived response efficacy leads to product affection, fostering impulsive purchasing. This study provides new insights into the effects of persuasive messages for health product promotion in social commerce. Marketers should design appropriate persuasive messages to foster impulsive purchasing by generating individuals’ product affection and avoiding cyberchondria.     

Green consumption behavior prediction based on fan-shaped search mechanism fruit fly algorithm optimized neural network

Predicting consumption behavior is very important for adjusting supplier production plans and enterprise marketing activities. Conventional statistical methods are unable to accurately predict green consumption behavior because it is characterized by multivariate nonlinear interactions. The paper proposes an optimized fruit fly algorithm (FOA) and extreme learning machine (ELM) model for consumption behavior prediction. First, to address the problem of uneven search direction of FOA leading to insufficient search ability and low efficiency, the paper proposes a sector search mechanism instead of a random search mechanism to improve the global search ability and convergence speed of FOA. Second, to address the issue that the initial weights and hidden layer bias values of the ELM are randomly generated, which affects the learning efficiency and generalization of the ELM, the paper uses an improved FOA to optimize the weights and bias values of ELM for improving the prediction accuracy. Taking the green vegetable consumption behavior of Beijing residents as an example, the results show the optimization of the initial weight and threshold of ELM by the GA, PSO, FOA, and SFOA, the prediction accuracy of the GA-ELM, PSO-ELM, FOA-ELM, and SFOA-ELM models all surpass those of ELM. Compared with BPNN, GRNN, ELM, GA-ELM, PSO-ELM, and FOA-ELM models, the RMSE value of SFOA-ELM was decreased by 9.45%, 8.40%, 11.89%, 5.84%, 2.22%, and 2.69%, respectively. These findings demonstrate the effectiveness of the SFOA-ELM model in green consumption behavior prediction and provide new ideas for the accurate prediction of consumption behaviors of other green products with similar characteristics.     

The bright side of disorganization: When surprise generates low-price signals

The research problem of this paper attempts to understand the effects of disorganized versus organized shelves on search information. Contemporary retail studies have tended to discover how the organization of displays can evoke increased consumer attention. Thus, the purpose is to examine how disorganization cues shelf displays foster surprise through information search and the implications of that process for visualizing low-price signals. In three experiments carried out using eye-tracking devices and face reader techniques (two in the laboratory and one in the field), empirical evidence is presented that disorganization cues can generate an increase in information search generated by cognitive processing, increased emotional surprise manifested levels via schema discrepancy, and perception of low-price provoked by the attempt to reduce the risk of choice.     

Aesthetics of hotel photos and its impact on consumer engagement: A computer vision approach

Visual content has been an essential marketing approach to exerting enjoyable virtual experiences and inducing consumer engagement. However, despite the widespread acknowledgment of the importance of visual content, how would the exerted aesthetic perception affect consumer engagement is still unexplored. Adopting a deep convolutional neural network model, this study quantifies the aesthetics of thumbnail images and managerial photos of hotels and thereby explores the impact of hotel photo aesthetics on consumer engagement. Aesthetically enjoyable photos are shown effective not only to encourage more consumers to engage in word-of-mouth discussions but also to promote consumer ratings. Such impact is also significantly moderated by hotel price. This study illustrates a viable approach to probing the perceived aesthetics of visual content in the hospitality field, and the uncovered significant role of aesthetics highlights the necessity of further attention to the cognitive perceptions of visual marketing content in both theoretical research and practical management.     

Mitigating panic buying behavior in the epidemic: An evolutionary game perspective

The panic buying behavior under public health emergencies will lead to many adverse consequences, such as material waste, price fluctuation and uneven distribution of epidemic prevention materials, which will pose a threat to the social stability and economic development. In this paper, we construct a tripartite game model to explore the strategic choices of the public, merchants and the government in order to effectively respond to the panic buying behavior in the epidemic. The results demonstrate that: (1) Eight evolutionary stable strategies emerge in the panic buying events. The worst scenario can be improved by adjusting some relevant parameters. (2) The probability of the public choosing the strategy of “not involving in panic buying” depends on the potential benefits and losses of snapping up, rather than the extent of price rising. (3) The probability of merchants choosing the strategy of “not bid up price” depends on the intangible benefits. (4) The probability of the government choosing the strategy of “active supervision” depends on the supervision costs and government credibility, rather than the amount of fines. In addition, strategic suggestions to mitigate panic buying behavior are put forward from the perspective of each stakeholder.     

Economic policy uncertainty and imitation behaviors of corporate social responsibility practices: Evidence from China

In this paper, we examine whether firms facing higher economic policy uncertainty (EPU) are more likely to show similar corporate social responsibility (CSR) practices compared with their peer firms. Drawing upon institutional theory, in response to uncertainty under complex circumstances, managers tend to imitate peer firms' strategic actions to acquire legitimacy. Consistent with our theoretical expectations, we find that EPU increases the likelihood that a focal firm will show CSR practices similar to its peer firms. Such a likelihood is amplified for firms that (1) bear more negative media coverage, (2) have higher industry competition intensity, (3) belong to heavy-polluting industries, and (4) for the first-time disclosures. Our results hold when we employ a series of endogeneity tests and robustness checks.     

Predicting inflation expectations: A habit-based explanation under hedging

One of the main challenges monetary policymakers face is predicting the trajectory of short-term inflation, especially considering the consistently flat Phillips curve observed in recent years. A promising approach to tackling this challenge involves modifying the hybrid New Keynesian Phillips curve (HNKPC) by incorporating a hedging factor. This factor accounts for the efforts risk-averse economic agents make to safeguard their spending decisions against uncertainties arising from inflation. Our study provides evidence that the hedging factor plays a crucial role and is a statistically significant predictor of the upcoming year's inflation rate. Specifically, a one-standard-deviation increase in the hedging factor predicts a positive rise in short-term inflation. Furthermore, we demonstrate that the hedging factor significantly determines the common component found in both well-known survey-based and model-based inflation expectation indicators.