Consumer desire for personalisation of products and services: cultural antecedents and consequences for customer evaluations

Torrico, Boris Christian Herbas; Frank, Björn

doi:10.1080/14783363.2017.1304819

Cited by 20 publications

(12 citation statements)

References 41 publications

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“…Despite the positive impact of personalized services on customer engagement, not all customers may have the same needs in terms of personalization. In other words, receiving personalized services or products is not equally important for all customers (Herbas Torrico & Frank, 2019;Shen & Dwayne Ball, 2009). In fact, customer traits -such as the need for personalization -influence a wide variety of customer outcomes (Dabholkar & Bagozzi, 2002;Meuter, Bitner, Ostrom, & Brown, 2005), including customer engagement with brands or firms (Islam, Rahman, & Hollebeek, 2017;Shen & Dwayne Ball, 2009).…”

Section: Smartness-engagement Relationship Explained By Personalizati...mentioning

confidence: 99%

“…Building upon this line of thought, we contend that customer engagement with smart service system actors is shaped by a customer's need for personalization. We define the need for personalization as a customer's desire for products and services that resemble the customer's specific needs and preferences (Herbas Torrico & Frank, 2019;Xu et al, 2011). As customers with a high need for personalization are found to value investments of actors in personalized services more than those with a low need for personalization (Herbas Torrico & Frank, 2019), we expect -in line with social exchange theory -that the effect of personalization on customer engagement with different actors in the smart service system is stronger for customers with a high (versus a low) need for personalization.…”

Section: Smartness-engagement Relationship Explained By Personalizati...mentioning

confidence: 99%

See 1 more Smart Citation

The smarter, the better?! Customer well-being, engagement, and perceptions in smart service systems

Henkens

Verleye

Larivière

2021

International Journal of Research in Marketing

106

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Section: Smartness-engagement Relationship Explained By Personalizati...mentioning

confidence: 99%

Section: Smartness-engagement Relationship Explained By Personalizati...mentioning

confidence: 99%

The smarter, the better?! Customer well-being, engagement, and perceptions in smart service systems

Henkens

Verleye

Larivière

2021

International Journal of Research in Marketing

106

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“…Our conceptual model (see Figure 1) summarizes our study about the effects of different types of an athlete endorser's attractiveness on multiple customer equity drivers (purchase intent, perceived product quality, perceived product design, brand attitude, and brand trust: Abulaiti et al, 2011;Ball et al, 2004;Frank & Enkawa, 2009;Herbas Torrico & Frank, 2019;Homburg et al, 2015;Kamolsook et al, 2019) and about the variation in these effects by the match-up in multiple contextual conditions.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

An extended source attractiveness model: the advertising effectiveness of distinct athlete endorser attractiveness types and its contextual variation

Frank

Mitsumoto

2021

European Sport Management Quarterly

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Research question: According to past research, the effectiveness of athlete endorsements of advertised products is low on average and strongly depends on the context. This article extends the source attractiveness model to examine two research questions:(1) How do multiple unexplored types of an athlete endorser's attractiveness affect customer equity drivers? (2) How do these effects vary by the fit of an athlete endorser with the endorsed product and with the consumer's gender and sports experience? Research methods: This research uses hierarchical linear modeling of 1319 consumer evaluations of athlete-endorsed ads in Japan. Results and finding: Among multiple types of an athlete's attractiveness, an athlete's success appeal, personality appeal, and athlete-product similarity, but not sex appeal, positively affect customer equity drivers. Due to gender roles, success appeal and personality appeal have stronger effects and athleteproduct similarity has weaker effects for male athletes. Contrary to conventional wisdom, sex appeal is not more influential for female athletes. Reflecting sexual preferences in opposite-gender evaluations, a female athlete's sex appeal has a stronger positive influence on male consumers, whereas a male athlete's success appeal has a stronger positive influence on female consumers. A consumer's sports experience enhances the influence of an athlete's success appeal. Implications: This research identifies a set of contextual moderators (athlete-product fit; athlete-consumer fit in gender and sports experience) of the effectiveness of different attractiveness types in athlete endorsements of advertised products. It provides guidelines on how to enhance the effectiveness of athlete endorsements by using different types of athlete attractiveness in different contexts.

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“…Recent personalization research suggests that identity-related theories like social identity theory, uniqueness theory, and self-concept theory (e.g. Torrico and Frank, 2017; Tran et al ., 2020a) and impression management theory (e.g. Hess et al ., 2020) are applicable in the context of personalization.…”

Section: Enhancing the Impact Of Personalization Researchmentioning

confidence: 99%

Piloting personalization research through data-rich environments: a literature review and future research agenda

Mehmood

Verleye²,

Keyser³

et al. 2022

JOSM

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PurposeOver the last 50 years, increased attention for personalization paved the way for one-to-one marketing efforts, but firms struggle to deliver on this promise. The purpose of this manuscript is to provide a complete picture on personalization, develop a future research agenda and put forth concrete advice on how to move the field forward from a theoretical, methodological, contextual, and practical viewpoint.Design/methodology/approachThis research follows a systematic literature review process, providing an in-depth analysis of 135 articles (covering 184 studies) to distill the (1) key building blocks and components of personalization and (2) theoretical, contextual, and methodological aspects of the studies.FindingsThis manuscript uncovers six personalization components that can be linked to two personalization building blocks: (1) learning: manner, transparency, and timing and (2) tailoring: touchpoints, level, and dynamics. For each of these components, the authors propose future research avenues to stimulate personalization research that accounts for challenges in today's data-rich environments (e.g. data privacy, dealing with new data types). A theoretical, contextual, and methodological (i.e. industry, country and personalization object) review of the selected studies leads to a set of concrete recommendations for future work: account for heterogeneity, embed theoretical perspectives, infuse methodological innovation, adopt appropriate evaluation metrics, and deal with legal/ethical challenges in data-rich environments. Finally, several managerial implications are put forth to support practitioners in their personalization efforts.Originality/valueThis research provides an integration of personalization research beyond existing and outdated review papers. Doing so, it accounts for the impact of new technologies and Artificial Intelligence and aims to advance the next generation of knowledge development on personalization.

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Consumer desire for personalisation of products and services: cultural antecedents and consequences for customer evaluations

Cited by 20 publications

References 41 publications

The smarter, the better?! Customer well-being, engagement, and perceptions in smart service systems

The smarter, the better?! Customer well-being, engagement, and perceptions in smart service systems

An extended source attractiveness model: the advertising effectiveness of distinct athlete endorser attractiveness types and its contextual variation

Piloting personalization research through data-rich environments: a literature review and future research agenda

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