Search Results (8)

Many speech coding strategies have been developed over the years, but comparing them has been convoluted due to the difficulty in disentangling brand-specific and patient-specific factors from strategy-specific factors that contribute to speech understanding. Here, we present a comparison with a ‘virtual’ patient, by comparing two strategies from two different manufacturers, Advanced Combination Encoder (ACE) versus HiResolution Fidelity 120 (F120), running on two different implant systems in a computational model with the same anatomy and neural properties. We fitted both strategies to an expected T-level and C- or M-level based on the spike rate for each electrode contact’s allocated frequency (center electrode frequency) of the respective array. This paper highlights neural and electrical differences due to brand-specific characteristics such as pulse rate/channel, recruitment of adjacent electrodes, and presence of subthreshold pulses or interphase gaps. These differences lead to considerably different recruitment patterns of nerve fibers, while achieving the same total spike rates, i.e., loudness percepts. Also, loudness growth curves differ significantly between brands. The model is able to demonstrate considerable electrical and neural differences in the way loudness growth is achieved in CIs from different manufacturers. Full article

This study focuses on a profound paradox in eco-hotel evaluations: why do consumer ratings for location, a static asset, exhibit dynamic fluctuations? To solve this puzzle, we construct a two-stage signal-processing theoretical framework that integrates Signaling Theory and the Elaboration Likelihood Model (ELM). This framework posits that the dynamic trajectory of a hotel’s green attributes (encompassing eco-facilities, sustainable practices, and ecological experiences) constitutes a high-fidelity market signal about its underlying quality. We utilized natural language processing techniques (Word2Vec and LSA) to conduct a longitudinal analysis of over 60,000 real consumer reviews from Booking.com between 2020 and 2023. This study confirms that continuous improvements in green attributes result in significant positive spillovers to location scores, while any degradation triggers strong negative spillovers. More critically, consumer environmental involvement (CEI) acts as an amplifier in this process, with high-involvement consumers reacting more intensely to both types of signals. The research further uncovers complex non-linear threshold characteristics in the spillover effect, subverting traditional linear management thinking. These findings not only provide a dynamic and psychologically deep theoretical explanation for sustainable consumption behavior but also offer forward-thinking practical implications for hoteliers on how to strategically manage dynamic signals to maximize brand value. Full article

Modern commercial organizations have started to embrace the metaverse platform as a new channel for marketing their products and services. As prominent brand representatives, virtual influencers are responsible for strengthening consumer–brand connections in the metaverse. However, the ways in which virtual influencers contribute to consumers’ brand fidelity and evangelistic behaviors remain unknown. To address this gap, this work explores the essential factors that impact consumers’ intention to trust virtual influencers in the metaverse, purchase the products that they promote, and engage in brand evangelistic behaviors. Specifically, a new framework is developed that integrates metaverse virtual influencers’ marketing efforts, perceived coolness, anthropomorphism, brand evangelism, and brand fidelity into a comprehensive conceptual research model. Survey results obtained from 713 respondents in the US demonstrate that marketing efforts, perceived coolness, and anthropomorphism positively influence brand evangelism. The findings also indicate that consumers’ brand fidelity encourages brand evangelism and mediates the relationship between virtual influencers’ features, marketing efforts, and consumers’ brand evangelistic behavior. This study’s significance lies in its focus on the evolving marketing dynamics in the metaverse. It considers how virtual influencers’ features and marketing efforts impact consumers’ brand-related attitudes and behaviors in the metaverse, offering valuable insights for the advancement of metaverse marketing research and practice. Full article

(1) Background: Loyalty programmes are business strategies aimed at increasing customer fidelity to brands. One of the most promising technologies of the 21st century is blockchain, whose application to the management of loyalty programmes can increase transparency and reliability, enable interoperability, and facilitate centralised management. (2) Methods: This study evaluates the antecedents of the acceptance of blockchain-based loyalty programmes (BBLPs) using a model grounded in the technology acceptance model UTAUT2. The four basic constructs of UTAUT, which we call the UTAUT-baseline, are considered explanatory factors: performance expectancy (PER), effort expectancy (EFF), social influence (SOC), and facilitating conditions (FAC). Additionally, we consider the constructs introduced in UTAUT2: hedonic motivation (HED) and perceived price value (PRI), to which we add innovativeness (INN) and trust (TRU), and we refer to these as UTAUT-extended, along with the moderating variables of UTAUT and UTAUT2: gender, age, and experience. The analytical approach used is complexity theory, which aims to capture the configurations that lead to both acceptance and rejection positions regarding BBLPs. This analysis is performed via fuzzy set qualitative comparative analysis (fsQCA). (3) Results: Eight explanatory configurations of the acceptance of BBLPs have been obtained, in which the presence of all UTAUT-baseline and UTAUT-extended constructs is a condition in at least three prime implicates. The constructs with the greatest presence as core conditions are PER, EFF, and TRU. On the other hand, nine configurations leading to the rejection of BBLPs have been identified. The absence of all UTAUT-baseline and UTAUT-extended variables is a condition in at least three configurations. The core conditions with the greatest presence in the rejection of BBLPs are the lack of FAC, HED, and PRI. (4) Practical implications: The results obtained are of great interest to business owners, as they allow for the characterisation of different profiles of people potentially engaged with BBLPs, as well as the profiles of consumers reluctant to adopt them. Full article

Wearable sensors are quickly making their way into psychophysiological research, as they allow collecting data outside of a laboratory and for an extended period of time. The present tutorial considers fidelity of physiological measurement with wearable sensors, focusing on reliability. We elaborate on why ensuring reliability for wearables is important and offer statistical tools for assessing wearable reliability for between participants and within-participant designs. The framework offered here is illustrated using several brands of commercially available heart rate sensors. Measurement reliability varied across sensors and, more importantly, across the situations tested, and was highest during sleep. Our hope is that by systematically quantifying measurement reliability, researchers will be able to make informed choices about specific wearable devices and measurement procedures that meet their research goals. Full article

The purpose of this article is to analyze the relationship between a brand’s trust in consumer decisions and its maintenance over time in a retail chain in northern Brazil known as Bemol. The sample consists of 210 respondents, customers of Bemol, and the methodology used is a model of structural equations. The developed model consists of 22 variables, divided into three constructs: trust, loyalty and brand. The results show the importance of trust in the consumption decision, as well as loyalty, relationship and satisfaction. Trust and loyalty lead to brand relationship, which is why managers must pay special attention to the factors to be provided to their customers so that this triad can be verified. Commercial brands marketed to the public should consider inducing strong feelings towards the brand as an important step in promoting customer satisfaction and loyalty. A brand for which that the consumer develops strong feelings will facilitate and potentiate positive behaviors in the long term. However, some behavioral characteristics, attendance and leadership, are of lesser importance to the consumer. This research presents a limitation as to its application, as the respondents were only customers of one brand, Bemol. Full article

Corporate social responsibility (CSR) and business ethics are perceived as distinct constructs by the consumer, although research from this perspective is scarce. Thus, the objective of this study is to investigate the impact of CSR and business ethics on brand fidelity. A theoretical review of CSR, business ethics, brand attitude, brand love, and brand fidelity was undertaken. From these constructs, a theoretical model was proposed, conducting an empirical study with a sample of 559 North American respondents. Through the statistical treatment of data with PLS-SEM, it was demonstrated that business ethics and CSR exert an indirect positive effect on brand fidelity, with relationships mediated by brand love. In turn, brand attitude exerts an indirect effect on brand fidelity, through the mediation of brand love. Based on the results, this study contributes to the approach of CSR and business ethics as distinct constructs and to the consolidation of the brand fidelity construct and its relationships. For management, this study helps organizations to perceive CSR and business ethics as important allies in a brand’s strategy. We conclude that although CSR remains important, customers value business ethics as a critical factor in their perceptions of the brand, contributing more strongly to brand fidelity. Full article

Modern computational techniques offer new perspectives for the personalisation of food properties through the optimisation of their production process. This paper addresses the personalisation of beer properties in the specific case of craft beers where the production process is more flexible. Furthermore, this work presents a solution discovery method that could be suitable for more complex, industrial setups. An evolutionary computation technique was used to map brewers’ desired organoleptic properties to their constrained ingredients to design novel recipes tailored for specific brews. While there exist several mathematical tools, using the original mathematical and chemistry formulas, or machine learning models that deal with the process of determining beer properties based on the predetermined quantities of ingredients, this work investigates an automated quantitative ingredient-selection approach. The process, which was applied to this problem for the first time, was investigated in a number of simulations by “cloning” several commercial brands with diverse properties. Additional experiments were conducted, demonstrating the system’s ability to deal with on-the-fly changes to users’ preferences during the optimisation process. The results of the experiments pave the way for the discovery of new recipes under varying preferences, therefore facilitating the personalisation and alternative high-fidelity reproduction of existing and new products. Full article