Resumo

Título do Artigo

INNOVATION EXPLAINING LOYALTY: EXTENSION OF THE ACSI MODEL
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Palavras Chave

consumer satisfaction and loyalty
ACSI model
perceived innovation

Área

Marketing

Tema

Varejo, Omni-Channel, Serviços, Franquia e B2B

Autores

Nome
1 - Eduardo Mesquita de Sousa
UNIVERSIDADE NOVE DE JULHO (UNINOVE) - Vergueiro
2 - Evandro Luiz Lopes
UNIVERSIDADE NOVE DE JULHO (UNINOVE) - Programa de Pós-graduação em Administração
3 - Eliane Herrero
PPGA - Universidade Nove de Julho - Memorial
4 - Priscila Rezende da Costa
UNIVERSIDADE NOVE DE JULHO (UNINOVE) - PPGA

Reumo

Loyal customers bring advantage and improve the profitability of the companies (Hogreve et al., 2017). Consumer loyalty is investigated through many models to establish the relationships between it and consumer satisfaction. The American Customer Satisfaction Index - ACSI (Fornell et al., 1996) is used to evaluate retail segments and the third sector. The ACSI model has never been tested by adding perceived innovation in services (which improves both purchase intention and behavior) to the original before.
Our research problem regards the understanding of the role of perceived innovation in services to explain loyalty. Our objective in this paper was to use the American Customer Satisfaction Index (ACSI) (Fornell et al., 1996) model to measure consumer loyalty in the context of services, adding to the model the perception of innovation as an antecedent variable. This tool is used to measure the consumer satisfaction index and its predictors, the attention given to the complaint, generating recovery from failure, and loyalty.
The ACSI model is an efficient model for measuring the performance of the company that delivers customer service (Fornell et al., 1996), bringing the dimensions of perceived quality, expectation, perceived value, recovery from failures and the subsequent satisfaction and loyalty. Perceived service innovation can predict repurchase behavior, as it affects the assessment of the service (Lee et al., 2015). The acceptance of new technologies by the consumer influences the evaluation and brings a perception of higher quality of the service provided.
We applied the ACSI model to assess consumer satisfaction and loyalty, adding to the original model the perception of innovation as an antecedent of satisfaction. This study is quantitative, conducted through a single cross-sectional survey. This research is conclusive/descriptive as it has well-defined objectives, formal procedures and is structured to solve problems. Respondents to this survey were selected based on convenience, and the sample was composed by 232 clients from three gyms in the state of São Paulo.
We used the ACSI model to measure consumer loyalty services in a sample of clients of gyms in São Paulo, together with measuring the innovation perceived by the consumers. The results showed that all variables, including perceived innovation, explained customer satisfaction and loyalty, except for perceived quality, which did not show a significant path in explaining satisfaction.Our model found robust results in the relationship between perceived innovation in services and consumer satisfaction. The perception of service innovation was an indirect predictor of customer loyalty.
The perceived innovation, incorporated into the ACSI model, proved to be a relevant antecedent in explaining consumer loyalty in services. The results pointed out to marketing managers the need for attention and for agility in providing services regarding attention by employees, fulfillment of promises made, attention to customer doubts and general quality of services offered.
Fornell, C., Johnson, M. D., Anderson, E. W., Cha, J., & Bryant, B. E. (1996). The American customer satisfaction index: Nature, purpose, and findings. Journal of marketing, 60(4), 7–18. Hogreve, J., Iseke, A., Derfuss, K., & Eller, T. (2017). The service–profit chain: A meta-analytic test of a comprehensive theoretical framework. Journal of Marketing, 81(3), 41–61. Lee, J., Ardakani, H. D., Yang, S., & Bagheri, B. (2015). Industrial big data analytics and cyber-physical systems for future maintenance & service innovation. Procedia Cirp, 38, 3–7.