Sonic seasoning refers to the way in which music can influence multisensory tasting experiences. To date, the majority of the research on sonic seasoning has been conducted in Europe or the USA, typically in a within-participants experimental context. In the present study, we assessed the applicability of sonic seasoning in a large-scale between-participants setting in Asia. A sample of 1611 participants tasted one sample of chocolate while listening to a song that evoked a specific combination of cross-modal and emotional consequences. The results revealed that the music’s emotional character had a more prominent effect than its cross-modally corresponding attributes on the multisensory tasting experience. Participants expressed a higher buying intention for the chocolate and rated it as having a softer texture when listening to mainly positive (as compared to mainly negative) music. The chocolates were rated as having a more intense flavor amongst those participants listening to ‘softer’ as compared to ‘harder’ music. Therefore, the present study demonstrates that music is capable of triggering a combination of specific cross-modal and emotional effects in the multisensory tasting experience of a chocolate.

The purpose of this study is to determine how consumer perceptions of brand ethical behavior can affect their commitment to brands during turbulent times. A study of the effects of perceived ethical behavior of brands in Colombia during the initial months of the COVID-19 outbreak was conducted in May 2020 in Bogota, Colombia, to ascertain customer perception of brand ethical actions during the first 2 months of the COVID-19 outbreak. A Bayesian model was developed to assess the impact of brands' ethical behavior on brand recognition benefits, brand image, and brand commitment. The selection of the initial months of the outbreak for this project was important because the COVID-19 pandemic had the potential to augment consumer perception of brands' ethical actions at a pivotal moment in consumers' lives. Our findings demonstrate that customers expressed a positive perception of brands' ethical actions during the early months of the pandemic, which resulted in high commitment intention to these brands in the model examined. The findings highlight the critical nature of the perception of ethical behavior in the eyes of customers during a major global health crisis. More than ever, organizations must commit their brands to fully live out their publicly expressed ethical principles and continuously monitor consumer perceptions of brand attributes and behaviors associated with ethical actions regardless of market conditions. Commitment to living the brand's stated ethical principles can be demonstrated via branding activities in ways that can be especially welcomed by customers during turbulent times. The insights mentioned in this article are crucial for brands already present in South America or exploring expansion into these regions. The findings provide compelling evidence of the impact of ethical actions on consumer commitment to brands, suggesting that brands must now, more than ever, stay in touch with their customers and truthfully live the ethical values they transmit to customers.

Mounting empirical evidence suggests that the observed extreme prices within a trading period can provide valuable information about the volatility of the process within that period. In this paper we define a class of stochastic volatility models that uses opening and closing prices along with the minimum and maximum prices within a trading period to infer the dynamics underlying the volatility process of asset prices and compare it with similar models presented previously in the literature. The paper also discusses sequential Monte Carlo algorithms to fit this class of models and illustrates its features using both a simulation study and real data.

Summary: This manuscript proposes a new approach for unveiling existing linkages within the international oil market across multiple driving factors beyond production. A multilayer, multicountry network is extracted through a novel Bayesian graphical vector autoregressive model, which allows for a more comprehensive, dynamic representation of the network linkages than do traditional or static pairwise Granger-causal inference approaches. Building on previous work, the layers of the network include country- and region-specific oil production levels and rigs, both through simultaneous and lagged temporal dependences among key factors, while controlling for oil prices and a world economic activity index. The proposed approach extracts relationships across all variables through a dynamic, cross-regional network. This approach is highly scalable and adjusts for time-evolving linkages. The model outcome is a set of time-varying graphical networks that unveil both static representations of world oil linkages and variations in microeconomic relationships both within and between oil producers. An example is provided, illustrating the evolution of intra- and inter-regional relationships for two major interconnected oil producers: the United States, with a regional decomposition of its production and rig deployment, and the Arabian Peninsula and key Middle Eastern producers, with a country-based decomposition of production and rig deployment, while controlling for oil prices and global economic indices. Production is less affected by concurrent changes in oil prices and the overall economy than rigs. However, production is a lagged driver for prices, rather than rigs, which indicates that the linkage between rigs and production may not be fully accounted for in the markets.

Firm–employee relationships are a prerequisite for customer–firm relationships and, consequently, to organizational success. The development of such relationships can be particularly challenging for retailers because of the complexity of the service component inherent to the environment in which they usually operate. For this reason, organizations need to align employee behaviors with the corporate brand promise so that they can perform a more active role as brand ambassadors. This issue becomes even more complex for organizations with a presence in foreign markets. This study focuses on how the adoption of in-role branding behavior by front-line employees (FLEs) can be influenced by the level of commitment FLEs display towards the corporate brand and how commitment is consequently influenced by corporate brand identity and corporate brand identity FLES’ perception of their role within the organization. The object of the study was the employees of Falabella, a multinational retailer based in Chile with a strong presence in the Colombian market. Results obtained demonstrate that brand commitment positively and significantly impacts FLE brand-oriented behavior in the retail context examined. More specifically, brand identity and role clarity positively impact brand commitment, leading to a positive impact on FLE brand behavior and job satisfaction. The results of this study offer valuable insight for scholars and practitioners regarding employee brand behavior’s engendering process within a retail environment in an emerging market.

This article proposes the use of computationally efficient inverse regression Bayesian method for analysis of tweet propagation of political messages. Our example focuses on the Colombian case, though our method can be used in any election where social media messaging has a direct impact on political outcomes. We find strong evidence that politicians were able to identify the combination of sensitive words to enhance the probability of retweet of the message, which, in turn, had an impact on political outcomes. The contributions of our work entail: (a) an examination of a neglected unit of analysis (trigram) in a language less studied (i.e. Spanish), (b) based on an innovative Bayesian efficient approach and (c) exploiting the predictive power that retweets have on electoral results as an informational diffusion tool in social media. A practical implication of this new methodology is the possibility to adjust political messages as a means to increase voters engagement in political campaigns.