Who are the multichannel shoppers and how can retailers use them? Evidence from the French apparel industry

Abstract

PurposeThis study aims to identify, within the context of the French fashion industry, the characteristics of multichannel shoppers, that is, consumers who use more than one channel in a single shopping trip. We especially investigate whether consumers' focus on quality versus price affects their multichannel shopping tendency and their flexibilities in their shopping lists (basket flexibility).Design/methodology/approachWe surveyed a representative sample of 400 French shoppers regarding fashion apparel purchasing. We use a logistic regression framework to measure the probability of a shopper becoming a multichannel shopper based on the key constructs and a battery of control variables.FindingsThe analysis shows that, in fashion buying, shoppers focused on quality and those with high basket flexibility have a higher probability of becoming multichannel shoppers. The probability becomes even greater when a shopper is both quality oriented and has basket flexibility.Research limitations/implicationsWe focus on the fashion apparel market for a deeper understanding of multichannel usage of products with both experience and search features. Future research can investigate other industries for higher generalizability.Practical implicationsOur research provides insights into multichannel fashion companies whose managements aim to effectively manage high-value customers who tend to use more channels when shopping. Specifically, an omnichannel marketing strategy should focus on capturing the quality-oriented and highly basket-flexible segment of consumers.Originality/valueOur study provides evidence that for products having high experiential as well as search features, quality-oriented and highly flexible shoppers engage more in multichannel shopping. Because these characteristics are related to the long-term value of customers, we provide the link between multichannel marketing and firm profitability in the context of the fashion industry.

Consumer decision‐making in omnichannel retailing: Literature review and future research agenda

“…Regarding data analysis, all the case studies are qualitative and used multiple data sources and analysed data using transcription, coding, theme generation and complemented the findings with the analysis of observations and secondary data. On the contrary, empirical survey‐based studies have majorly applied structural equation modelling as a primary data analysis method to analyse the linear relationship among selected variables (Dahl et al., 2019; Hallikainen et al, 2019; Hamouda, 2019; Jo et al., 2020, Kang, 2019; Lee, 2020; Li et al., 2018; Ma, 2017; Shen et al., 2018; Song et al., 2019b).…”

“…), Theory of Planned Behaviour (Jo et al., 2020; Xu & Jackson, 2019a), Theory of Reasoned Action (Park & Kim, 2019) and the Extended unified theory of acceptance and use of technology (Juaneda‐Ayensa et al., 2016; Kazancoglu & Aydin, 2018) were applied in a number of studies aiming to empirically examine the technology‐based offering of omnichannel retailing. Second, there is a growing interest in investigating consumer motivation, trust, preference, value and fear in the omnichannel retailing setting, with theories such as commitment‐trust theory (Xu & Jackson, 2019a), situated cognition theory (Hilken et al., 2018), self‐determination theory (Zhang et al., 2018b), and formal disappointment theory (Du et al(2018) employed to decipher these issues.…”

“…Along these lines, the majority of studies relied on data from multiple industries (Alexander & Cano, 2019; Buldeo Rai et al., 2019b; Jocevski et al., 2019; Larke et al., 2018; Saghiri et al., 2017; Valentini et al., 2020; Yrjölä et al., 2018a). Some sector‐specific studies employed data from the fashion (Jo et al., 2020; Juaneda‐Ayensa et al., 2016; Sebald & Jacob, 2020; Silva et al., 2020; Wollenburg et al., 2018a; Ye et al., 2018) and apparel sectors (Aw, 2019; Fisher et al., 2019; Frasquet et al., 2019; Rodríguez‐Torrico et al., 2017; Rosenmayer et al., 2018). The vast majority of studies were conducted in developed economies, leaving other geographic areas and markets largely unexplored.…”

Luxury Hospitality Service Adoption Amongst Indian Millennial: An Analytical Approach

“…In recent years Indian tourism service industry market has acquired a significant position with its diversity to reach every potential consumer where the millennials with (Maghnati & Ling, 2013), cosmetic brands (Ajitha & Sivakumar, 2017), perfumes, and apparels (Chihab & Abderrezzak, 2016;Jo, Kim & Choi, 2020;Woodside & Fine, 2019). Some studies have focused on the driving force of tourists and developed the luxury value behavior in hotels (Chen & Peng, 2014), luxury shopping (Correia, Kozak & Kim, 2019) and were conducted in other destinations whereas the studies that could sufficiently identify the Indian especially millennial consumers' value sets that determine their attitude and intentions to travel or purchase a luxury tourism and hospitality services are still few or lacking.…”

Customer segment transition through the customer loyalty program

“…The conceptualization of the customer journey during the pre-purchase, purchase and post-purchase stages has been shown based on the theory of market or business strategy (Handarkho, 2020; Lemon and Verhoef, 2016; Grewal and Roggeveen, 2020). Recent empirical studies have focused on touchpoints across multichannel or omnichannel retailing, and large-scale data analysis based on the static models of the customer journey have provided implications for customer segments and customer experience management (de Haan et al , 2018; Chen et al , 2019; Handarkho, 2020; Jo et al , 2020). However, the existing empirical research models rarely consider the transitions between customer segments and the performance forecast by all customers in the customer journey.…”