Drivers of eWOM engagement on social media for luxury consumers: Analysis,implications, and future research directions

The rapid industrialization and growth across the world have fostered the consumption of luxury fashion brands. Electronic word-of- mouth on social media (eWOM) is fast becoming an effective and germane strategy to engage luxury consumers through posting pictures, sharing reviews, and communicating information on platforms like Facebook, Instagram, and TikTok. Extant research has not examined the antecedents and drivers that lead to eWOM behavior. We leverage self-congruity theory and through its focal lens, our study addresses this research gap through a survey conducted with 453 consumers in Mexico, Latin America's fastest growing market. Our results indicate that need for status, susceptibility to normative influence, and luxury brand involvement, moderated by authentic pride and social media influencers lead to eWOM behavior on social media. We also demonstrate that luxury brand involvement and susceptibility to normative influence mediate the relationship between need for status and eWOM behavior on social media. The study provides important implications to managers and researchers by suggesting long-term actionable strategies for growth that can help luxury firms develop a sustainable competitive advantage over rivals and competitors.     

Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis

We consider simple methods to improve the growth nowcasts and forecasts obtained by mixed-frequency MIDAS and UMIDAS models with a variety of indicators during the Covid-19 crisis and recovery period, such as combining forecasts across various specifications for the same model and/or across different models, extending the model specification by adding MA terms, enhancing the estimation method by taking a similarity approach, and adjusting the forecasts to put them back on track using a specific form of intercept correction. Among these methods, adjusting the original nowcasts and forecasts by an amount similar to the nowcast and forecast errors made during the financial crisis and subsequent recovery seems to produce the best results for the US, notwithstanding the different source and characteristics of the financial crisis. In particular, the adjusted growth nowcasts for 2020Q1 get closer to the actual value, and the adjusted forecasts based on alternative indicators become much more similar, all unfortunately indicating a much slower recovery than without adjustment, and very persistent negative effects on trend growth. Similar findings also emerge for forecasts by institutions, for survey forecasts, and for the other G7 countries.     

The importance of personal norms and situational expectancies to sustainable behaviors: The norm activation and situational expectancy-value theories

The turn towards sustainability is becoming more critical in every sector, but consumers' lifestyles and behaviors have been slow to transform. Therefore, based on the norm activation model and situational expectancy-value theory, this study investigated the importance of personal norms and the influences of situational factors on sustainable behaviors. A total of 1050 responses obtained through an online survey method were analyzed using SPSS and LISREL. The results revealed that situational factors, such as acceptability of policies, accessibility of facilities, sacrificeability of prices, and environmental activism, can either facilitate or hinder recycling practices and responsible consumption behaviors. Personal norms are a determinant for sustainable behavior. Future research can extend the findings of this study to compare the most and least sustainable states or countries to determine effective interventions for encouraging sustainable behaviors.     

Understanding machine learning-based forecasting methods: A decomposition framework and research opportunities

Machine learning (ML) methods are gaining popularity in the forecasting field, as they have shown strong empirical performance in the recent M4 and M5 competitions, as well as in several Kaggle competitions. However, understanding why and how these methods work well for forecasting is still at a very early stage, partly due to their complexity. In this paper, I present a framework for regression-based ML that provides researchers with a common language and abstraction to aid in their study. To demonstrate the utility of the framework, I show how it can be used to map and compare ML methods used in the M5 Uncertainty competition. I then describe how the framework can be used together with ablation testing to systematically study their performance. Lastly, I use the framework to provide an overview of the solution space in regression-based ML forecasting, identifying areas for further research.     

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.     

The effect of control deprivation on consumers’ adoption of no-pain,no-gain principle

Consumers often base their judgments on a no-pain, no-gain principle—that is, one must pay a cost in order to achieve a beneficial outcome. For example, they infer the quality of a product from its price and judge a bad-tasting medicine to be more effective than a tasty one. Although the use of this principle to infer the value of a product or service has been observed in several domains, the processes that underlie its use have not been fully explored. We find that when people feel out of control, they tend to use the principle because it exemplifies a causal relationship between actions and outcomes and endorsing it reaffirms their belief that they have control over the outcomes of their behavior. Our findings have implications for how marketers might position products and services to attract consumers who perceive themselves as having different levels of control.     

How household food shopping behaviors changed during COVID-19 lockdown period: Evidence from Beijing,China

The COVID-19 pandemic has had a great impact on food shopping behavior. However, changes in food shopping behavior and related decision-making mechanisms remain unexplored. This study conducted a face-to-face questionnaire survey with 900 residents in three communities in Haidian, Beijing, China, to analyze food shopping behavior during the periods of pre-lockdown, lockdown (January–March 2020), and post-lockdown. Our results indicated that the preference for fresh food e-commerce shopping was accelerated by the lockdown with the usage rate increasing by 48%; the wet markets were seriously hit by the lockdown policy and had not fully recovered by the post-lockdown period (with a 75% reduction in the usage rate during lockdown). The psychological mechanisms of changes in food shopping behavior revealed that the context (e.g., community facilities) and the perceived risk of COVID-19 were two significant factors impacting the four shopping choices investigated. Specifically, the context factors affected behavior directly for supermarkets and convenience stores and indirectly for e-commerce and wet markets. The findings are expected to help in guiding emergency responses during a future pandemic as well as the long-term construction of food supply facilities.     

Factors influencing buying behavior of Lebanese consumers towards fashion brands during economic crisis: A qualitative study

The purpose of this article is to contribute to an understanding of the impact of the Lebanese economic crisis on fashion buying behavior. It uses a qualitative approach by conducting semi-structured interviews with 29 Lebanese consumers. The study reveals that consumer fashion purchases are motivated by emotional, social, and functional drivers. It also indicates that subjective norms, such as societal and cultural values dictate buying behaviors. The findings provide further insights into social media and highlight its influence on shaping trends and making fashion products desirable. The article concludes that Lebanese consumers exhibit impulsive buying behavior, and explains how fashion brands can remain relevant amidst a wrenching economic crisis.     

Employee workplace spirituality and pro-environmental behavior in the hotel industry

Pro-environmental behaviors in the workplace are less investigated than those in the public and private spheres. With this in mind, and through the values framework of workplace spirituality (WPS), synthesizing the theories of connectedness and organizational citizenship, the current study proposed a theoretical model to gauge the influence of WPS, a relatively new area of inquiry in organizational research and a neglected field in tourism and hospitality, on hotel employees’ organizational citizenship behavior for the environment (OCBE). In this framework, the emerging concept of connectedness to nature (CNS) – a strong cognitive and affective predictor of pro-environmental behavior – was depicted as a mediator, and the construct of environmental awareness (EA) was deemed a moderator. The intended model received support through empirical testing, and results confirmed that WPS is significantly associated with employees’ OCBE, and CNS indirectly affects the relationship between WPS and OCBE, while EA functions as a booster. The theoretical and practical implications of the study were discussed, and a series of contributory managerial implications were described accordingly.     

Information and Knowledge as Antecedents of Consumer Attitudes and Intentions to Buy and Recommend Fair-Trade Products

The authors propose and empirically test a causal model to understand how the availability of fair-trade information and consumer knowledge about this issue affect consumers’ attitudes and intentions toward fair-trade products. The model is built upon the attitude-behavior paradigm and the premises of agency theory. It is tested through structural equation modeling with a sample of 292 Spanish consumers. The findings are that consumers do not have good knowledge about fair trade and that this is significantly determined by the lack of information about this in the market. It is also observed that consumers’ perceptions about the availability of fair-trade information have negative effects on their concern about this issue and that such information as is available is not effective in reducing consumer skepticism. The research represents an extension of previous fair-trade literature because the role of information and communication in improving consumer attitudes and buying intentions has rarely been explored in the case of ethical products.