Miao Miao, Hideho Numata and Kayo Ikeda
This study adopts complexity theory to explore behavioural brand loyalty (BBL) development by investigating brand perceptional components and loyalty programs (LPs) in the…
Abstract
Purpose
This study adopts complexity theory to explore behavioural brand loyalty (BBL) development by investigating brand perceptional components and loyalty programs (LPs) in the Japanese fashion market through a qualitative comparative study. The authors address two research questions: (1) Under the potential influence of the COVID-19 pandemic, do brand perceptions and LPs contribute to young generation's BBL toward three types of brands with different scales of store numbers and prices? (2) If so, under what conditions do these factors positively influence BBL?
Design/methodology/approach
This study considers the effects of complex factors and conditions on BBL formation by testing the asymmetric relationships that exist among brand perceptions, LPs, and BBL via fuzzy-set qualitative comparative analysis (fsQCA). The authors surveyed 751 Japanese consumers (aged 18–25 years) who had chosen 26 Japanese fashion brands as their favourites and participated in the LPs of those brands. The use of fsQCA supplements the existing research by explaining how causal variables affect BBL both positively and negatively.
Findings
The results (1) present multiple causal solutions in predicting high BBL by profiling young shoppers based on their psychological and behavioural characteristics; (2) show how causal factors and consumer characteristics work differently when developing BBL for different types of brands. The findings established that brand perceptions and LPs could affect BBL positively and negatively, depending on the characteristics of fashion brands and shoppers.
Originality/value
This study offers theoretical and practical implications in two main aspects: (1) the authors adopted a mixed methodology with quantitative and qualitative analysis to propose an integrated model that connects perceptional brand loyalty and LPs with BBL, based on three types of Japanese fashion brands; (2) the results offer multiple solutions for predicting the high level of BBL by profiling shoppers' characteristics, considering the impacts of the COVID-19 pandemic.
Details
Keywords
Miao Miao, I. Go, Cui Linyuan, Kayo Ikeda and Hideho Numata
To investigate (1) the relationship between young adults' behavioural brand loyalty (BBL) and Japanese fashion companies' financial performance (FP) and (2) FP improvement from…
Abstract
Purpose
To investigate (1) the relationship between young adults' behavioural brand loyalty (BBL) and Japanese fashion companies' financial performance (FP) and (2) FP improvement from the perspectives of social media brand engagement (BE) and loyalty programmes (LPs) by applying the complexity theory.
Design/methodology/approach
A mixed methodology was employed by combining qualitative and quantitative approaches to examine the prediction of outcomes by various variables in a realistic context. The integrated model associated BE and LPs with BBL and FP, which are essential for fashion companies. We selected 14 fashion brands belonging to 14 publicly traded Japanese fashion companies and surveyed 183 Japanese consumers (aged 18–25 years) who chose these brands as their favourites, engaged with the brands and participated in LPs.
Findings
The findings reveal the positive and negative effects of the variables (BE and LP) on the outcomes (short- and long-term FP). They offer marketing implications regarding brand strategy and financial improvement by considering various combinations of causal factors and complex situations, such as the fashion brands' and consumers' characteristics.
Originality/value
Existing empirical studies consider consumers' symmetric reactions to the benefits and losses from variables (BE, LP and BBL) but do not realistically reveal the negative and positive effects on outcomes (FP). This study addresses this gap by applying the complexity theory and offers multiple solutions to target different consumer types to predict high FP.