The Role of Congruity And Rejection Sensitivity

Goncalves, A. R., Meira, A. B., Shuqair, S., & Pinto, D. C. (2023). Artificial Intelligence (AI) in Fintech Decisions: The Role of Congruity And Rejection Sensitivity. International Journal of Bank Marketing. https://doi.org/10.1108/IJBM-07-2022-0295 --- This work received partial support from national funds through FCT (Fundação para a Ciência e a Tecnologia), under the projects - UIDB/04152/2020 - DSAIPA/DS/0113/2019 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS project.Purpose - The digital revolution has changed consumer–service provider interaction, spawning a new generation of FinTech. This paper analyzes consumers' reactions to Artificial Intelligence (AI) (vs. human) decisions. Design/methodology/approach – We tested our predictions by conducting two experimental studies with FinTech consumers (n=503). Findings – The results reveal that consumers' responses to AI (vs. human) credit decisions depend on the type of credit product. For personal loans, the rejection by an AI provider triggers higher levels of satisfaction compared to a credit analyst. This effect is explained via the perceived role congruity. In addition, the findings reveal that consumers' rejection sensitivity determines how they perceive financial services role congruity. Originality/value – To the best of the authors' knowledge, this research is the first to jointly examine AI (vs. human) credit decisions in FinTech and role congruity, extending prior research in the field.authorsversionepub_ahead_of_prin

The role of experiential versus material posts

Pinto, D. C., Shuqair, S., Viglia, G., & Mattila, A. S. (Accepted/In press). Reducing resistance to sponsorship disclosure: The role of experiential versus material posts. Journal of Travel Research. --- The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work received partial support from national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.Despite the growing relevance of influencer marketing, recent research suggests that consumers have negative reactions to social media ads. Our research investigates how different types of disclosure (paid partnership vs. in-text disclosure) and post content (experiential vs. material) mitigate consumers’ negative reactions to social media advertisements. Four preregistered studies, drawing on the social exchange theory, reveal how the post content shapes the sponsorship disclosure effects. In particular, we show that a paid partnership (vs. intext) disclosure has a positive impact on consumers’ responses (engagement and purchase intent) and that persuasion resistance mediates the effects. Furthermore, Study 3 reveals that the type of content (experiential vs. material) moderates the effect, such that consumers' negative reactions to sponsorship disclosure are mitigated with experiential (vs. material) content. Overall, our results provide actionable implications for tourism marketers on how to create advertisements in social media, minimizing negative reactions to sponsorship disclosure.authorsversionepub_ahead_of_prin

A Step-By-Step Guide and AutoML Tool

Castelli, M., Pinto, D. C., Shuqair, S., Montali, D., & Vanneschi, L. (2022). The Benefits of Automated Machine Learning in Hospitality: A Step-By-Step Guide and AutoML Tool. Emerging Science Journal, 6(6), 1237-1254. https://doi.org/10.28991ESJ-2022-06-06-02. Funding:This study was supported by grant DSAIPA/DS/0113/2019 from FCT (Fundação para a Ciência e a Tecnologia), Portugal. This work was also supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.The manuscript presents a tool to estimate and predict data accuracy in hospitality by means of automated machine learning (AutoML). It uses a tree-based pipeline optimization tool (TPOT) as a methodological framework. The TPOT is an AutoML framework based on genetic programming, and it is particularly useful to generate classification models, for regression analysis, and to determine the most accurate algorithms and hyperparameters in hospitality. To demonstrate the presented tool’s real usefulness, we show that the TPOT findings provide further improvement, using a real-world dataset to convert key hospitality variables (customer satisfaction, loyalty) to revenue, with up to 93% prediction accuracy on unseen data.publishersversionepub_ahead_of_prin

The Benefits of Automated Machine Learning in Hospitality: A Step-By-Step Guide and AutoML Tool

The manuscript presents a tool to estimate and predict data accuracy in hospitality by means of automated machine learning (AutoML). It uses a tree-based pipeline optimization tool (TPOT) as a methodological framework. The TPOT is an AutoML framework based on genetic programming, and it is particularly useful to generate classification models, for regression analysis, and to determine the most accurate algorithms and hyperparameters in hospitality. To demonstrate the presented tool’s real usefulness, we show that the TPOT findings provide further improvement, using a real-world dataset to convert key hospitality variables (customer satisfaction, loyalty) to revenue, with up to 93% prediction accuracy on unseen data. Doi: 10.28991/ESJ-2022-06-06-02 Full Text: PD

Leveraging online selling through social media influencers

Shuqair, S., Filieri, R., Viglia, G., Mattila, A. S., & Pinto, D. C. (2024). Leveraging online selling through social media influencers. Journal of Business Research, 171(January), 1-10. [114391]. https://doi.org/10.1016/j.jbusres.2023.114391While prior research suggests that facial expression influences consumer behavior, it remains unclear under which conditions specific emotional expressions on social media drive sales performance and customer engagement. Drawing on the facial feedback hypothesis and the emotional congruence framework, two pre-registered experimental studies (N = 995) demonstrate that the fit between facial expressions (broad vs. slight smile) and endorsement type (hedonic vs. utilitarian) influence engagement and consumers’ purchase intents. Findings indicate that broad (vs. slight) smiles are more likely to enhance consumer responses when paired with hedonic endorsements driven by emotional contagion. Conversely, slight smiles are equally suited for both types of endorsements and do not foster emotional contagion. The findings offer actionable insights for maximizing consumer engagement and purchase intents within social media marketing efforts.publishersversionepub_ahead_of_prin

The role of crowdsourcing cues and relationship norms on customer-brand relationships

Herter, M. M., Shuqair, S., Pinto, D. C., Mattila, A. S., & Zandonai pontin, P. (2023). Does crowdsourcing necessarily lead to brand engagement? The role of crowdsourcing cues and relationship norms on customer-brand relationships. Journal of Product and Brand Management. https://doi.org/10.1108/JPBM-06-2022-4020 --- Funding: This paper received support from the Management of Information Research Center (MagIC), project UIDB/04152/2020, and from the Foundation for Science and Technology (FCT Portugal), project DSAIPA/DS/0113/2019Abstract Purpose This paper aims to examine how the relationship norms established between customers and brands influence customer perceptions of crowdsourcing (vs firm-generated) cues. Design/methodology/approach Four studies (N = 851) examine the moderating role of relationship norms on product labeling cues (crowdsourcing vs firm-generated) effects on brand engagement, and the underlying mechanism of self-brand connection. Findings The findings suggest that crowdsourcing (vs firm-generated) cues lead to higher brand engagement (Studies 1A–1B), mediated by self-brand connection (Studies 2–3). In addition, relationship norms moderate the effects (Study 3), such that under exchange brand relationships crowdsourcing (vs firm-generated) cues yield higher brand engagement, whereas communal brand relationships reverse such effects. Practical implications The findings provide valuable managerial implications by highlighting the importance of using relationship norms as diagnostic cues to successfully implement crowdsourcing initiatives. Originality/value This research adds to the customer-brand relationship literature by revealing an accessibility-diagnosticity perspective of consumers’ reactions to crowdsourcing (vs firm-generated) cues.authorsversionepub_ahead_of_prin

How relationship norms shape moral obligation in cancelation behavior

Shuqair, S., Costa Pinto, D., Cruz-Jesus, F., Mattila, A. S., da Fonseca Guerreiro, P., & Kam Fung So, K. (2022). Can customer relationships backfire? : How relationship norms shape moral obligation in cancelation behavior. Journal of Business Research, 151(November), 463-472. https://doi.org/10.1016/j.jbusres.2022.07.008 ---Funding Information: The authors Diego and Frederico gratefully acknowledge financial support from FCT Fundação para a Ciência e a Tecnologia (Portugal), national funding through research grant Information Management Research Center – MagIC/NOVA IMS (UIDB/04152/2020).While prior research indicates that establishing interpersonal interaction with customers is mostly beneficial, this work reveals that the impact of social ties depends on relationship norms (communal vs. exchange). In three studies, including a real-world field dataset (N = 87,615 customers), the current investigation demonstrates the conditions under which interpersonal relationships can increase or decrease customers’ cancelation behavior. The findings indicate that communal (vs. exchange) relationships can increase customers’ future cancelation behaviors. The findings also demonstrate that perceived moral obligation underlies interpersonal effects on cancelation behavior. That is, when providers develop communal (vs. exchange) ties, consumers feel that their interaction with the providers is in a closed social context, which tends to reduce their obligations towards attending their booking, thus increasing cancelation behavior. Theoretical and practical implications for business researchers and practitioners are discussed.publishersversionpublishe

How relationship norms affects consumers’ responses in sharing economy

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Survey Methodologies and Marketing ResearchThis research reveals a novel perspective on sharing economy peer providers, relationship norms, and customer loyalty. In a series of 16 experimental studies, this thesis demonstrates that customers-provider relationships based on communal (vs. exchange) norms improve customers’ outcomes towards service providers. Chapter 1 explores service failure in sharing economy, suggesting that consumers' emotional and behavioral responses depend on the accommodation provider type: communal (e.g., Airbnb hosts, personal providers) versus exchange (e.g., hotels, commercial hosts). It further shows the key underlying mechanisms that mediate the effects (authenticity and social interactions). Chapter 2 draws on relationship norms to suggest that relationship type—whether communal ("Airbnb host") or exchange ("hotel")—influences consumer forgiveness in a post-recovery context, and this effect is driven via two key processes (1) social recovery (2) communal norms. Chapter 3 and 4 further refine this theory to suggest that perceived warmth and social ties moderate such effects. In particular, the findings indicate that establishing social ties with consumers is beneficial for communal providers, revealing that the impact of social ties depends on relationship norms (communal vs. exchange). It further demonstrates that the strength of social ties has a substantial impact on consumers' loyalty for communal providers but are not expected in exchange relationships

Service Recovery in Collaborative Consumption Settings

Shuqair, S., & Pinto, D. C. (2019). Service Recovery in Collaborative Consumption Settings. In Proceedings of the European Marketing Academy, 48th (pp. 1-11). European Marketing Academy (EMAC). http://proceedings.emac-online.org/pdfs/A2019-4355.pdfA rich body of literature suggests that customers who are victims of service failures are less likely to forgive and tend to switch to another provider. In this paper, we reveal that the type of service provider (collaborative vs. conventional) affects how consumers respond to service failures. In four studies, we show that customers are more likely to forgive and to repurchase after service failures when service providers are collaborative (vs. conventional). We propose a conceptual framework that portrays forgiveness as the underlying process in the relationship between the service provider type and repurchase intentions. Findings indicate that customer’s forgiveness after failure towards a collaborative service provider is higher than to conventional providers, even when there is no service recovery attempt. In addition, tie-strength between customers and service providers moderates the effects of customer’s forgiveness on repurchasing intentions.publishersversionpublishe