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Product discounts have been widely applied in digital commerce as a method to attract and retain customers to purchase in China. Given that digital channels differ in their attributes, customers may behave differently when they respond to the same discount across channels. However, little attention has been paid to explore the heterogeneity of customer responses to discounts across channels. This study aims to fill in the gap by exploring how customers’ purchase responses to price discounts differ across digital channels.

This study applies a Poisson regression to an unbalanced data set of purchasing history from Chinese footwear brands with 3,510 customers in a two-year time window across the three digital channels (i.e. personal computer [PC], app and mobile website), with a correction for endogeneity by using the Gaussian copula method.

This paper finds that price discounts have the strongest positive effect on consumers’ purchase volumes on the PC channel, followed by the app channel, while discounts show the weakest impact in the mobile website channel. By so, this paper demonstrates that customers respond differently to online and mobile channels, and they also respond differently within mobile channels when they purchase products with price discounts.

This study is original in analyzing the difference in customers’ discount responses across digital channels, offering valuable contributions to existing research on multichannel marketing as well as mobile marketing and providing helpful insights for multichannel merchants to design digital discount strategies.

The purpose of this study is to investigate the effects of consumers' shopping orientation on their satisfaction level with the product search and purchase behavior using multi‐channels.

A total of 181 students in a large US mid‐western university provided usable responses to the survey. Exploratory factor analysis and multiple regression analyses were employed to examine the research questions.

The results showed that more than three quarters of the respondents shopped via the internet and catalogs, and about 95 percent shopped at non‐local retailers. About 60 percent reported that they never shopped from TV shopping channels. Confident/fashion‐conscious shopping orientation and catalog/internet shopping orientation were found to be key predictors of customer satisfaction level with information search via multi‐channels. Both confident/fashion‐conscious consumers and mall shopping‐oriented shoppers were more satisfied with store‐based retail channels for apparel purchases, whereas non‐local store‐oriented shoppers and catalog/internet‐oriented shoppers were more satisfied with non‐store‐based retail channels for their apparel purchases.

The sample of this study was biased by gender and age. For the apparel retail industry, this paper offers practical knowledge about the relationships between shopping orientation and consumer search and purchase behavior in a multi‐channel retailing context.

No study has utilized the shopping orientation framework to explain consumer behavior in a multi‐channel environment. This study provides understanding of consumer product information search behavior on four dimensions (price, promotion, style/trends, and merchandise availability) via multi‐channels.

The purpose of this study was to investigate whether consumers differ in their online or offline purchase intention, depending on which channel with price promotion information they are first exposed to, and to analyse the moderating role of brand trust.

Overall, 174 responses were obtained via an online survey using two contact channels (online/offline) by two levels of brand trust (high/low) between-subject designs.

Spillover effects were found across channels when a consistent price promotion is executed in both online and offline channels, purchase intentions for cross-channel and contact channel increase simultaneously. Although there was a similar effect in the discrepancy of purchase intentions towards the cross-channel according to contact channels, it varied depending on brand trust. When brand trust is high, having contact with offline price-discount information has a large online spillover effect. When brand trust is low, the spillover effect from online to offline is large.

This study expands the multi-channel research by proving the spillover effects between channels and confirming the difference according to brand trust.

Increasing promotion information for online contact is effective in driving offline visits for new brands, and the effective use of promotion information at offline stores can have a positive impact on online channels for well-known brands.

This study explores the cross-channel spillover effect of price promotion and proves that these effects depend on brand trust.

The aim of this research is to advance the understanding of multi-channel behaviour in terms of different generational cohorts' usage and spending patterns.

Building on previous studies on multi-channel behaviour, differences in shopping channel usage and purchase amounts were investigated between baby boomers, Gen X, xennials and millennials.

There were significant differences found between the generations in terms of multi-channel behaviour regarding purchasing frequency and average purchase amounts via a) mobile phone, b) tablet, c) computer, d) social media and e) brick-and-mortar. Fewer differences were found amongst the generational cohorts in terms of amount spent per channel.

The research was successful in analysing variances in multi-channel behaviour amongst the baby boomer, Generation X, xennial and millennial cohorts, while updating the body of literature to consider generational channel usage of mobile and social media in multi-channel retailing.

Marketers should consider xennials’ channel behaviour and focus on converting sales through integrated programmes based on their channel usage. Retailers should also consider millennials' heavy engagement with social media in their lives but spend lower amounts via the medium, which may be an opportunity to use this medium as a viable stand-alone channel in targeting millennials' shopping dollars.

This study updates the body of research on multi-channel behaviour by considering generation as a factor in channel usage and spend amount.

This study aims to examine the influence of attitudes toward particular clothing web sites, specifically favorite ones, on information search at those web sites and on the choice to purchase items from those web sites and from non‐internet channels after finding the items at the web sites.

Using survey data from 414 US college students who had online shopping experience and favorite clothing web sites that they especially like to visit, hypothesized relationships among attitude toward internet web sites, online information search and channel choices for purchasing were tested using path analysis.

Results showed that participants' attitudes toward their favorite clothing web sites had a direct, positive effect on their intentions to search for information at those web sites as well as intentions to purchase clothing items from those web sites after finding the items there. Additionally, operating through information‐search intentions at the web sites, participants' attitudes toward those web sites had an indirect, positive effect on their intentions to purchase clothing items from non‐internet channels after finding the items at the web sites.

Results cannot be generalized to the larger population of young consumers and to other consumer groups. Future research should include other population groups.

This research provides insights into how college students' attitudes toward internet web sites affect their information search at the web sites and their channel choices for purchasing. Our results suggest potential benefits of multi‐channel retailing for online clothing retailers targeting US college students and the importance of building effective web sites to elicit those consumers' positive attitudes toward the web sites.

This study is the first to investigate young adult online shoppers' attitude towards internet web sites and their information search and channel choices for purchasing.

Consumers are increasingly combining distribution channels, thus displaying so-called omni-channel behavior, both to complete a given purchase and between purchases. The authors make a distinction between omni-channel customers, who make use of distribution services in both channels and omni-channel users, who make partial use of the distribution services of one channel to support purchases in another. This paper aims to identify the omni-channel behavior among the customers of a global fast fashion retailer dealing in a wide range of apparel and clothing accessories.

Using a multinomial logit model, the authors perform a customer segmentation based on observed omni-channel behavior, considering the explanatory roles of demographics, distribution service features and customer service policies across the different retail channels.

The authors observe that the key retail channel features for explaining omni-channel customer behavior are product accessibility, both in store and online; the assurance that goods purchased online will satisfy the customer’s needs and expectations; and the option to return goods found unsatisfactory.

The results clearly show that the nature of the visits and purchases made by customers is determined by various components of the companýs customer service policy, which can, therefore, be used to guide the retailer’s segmentation strategy.

Future lines of research should explore the economic implications of this customer segmentation. The price perception data emerging from our findings suggest a greater sensitivity to prices in the mono-channel segment, which might be worth exploring in future research.

Future lines of research should explore the economic implications of this customer segmentation. The price perception data emerging from our findings suggest a greater sensitivity to prices in the mono-channel segment which might be worth exploring in future research.

Los consumidores combinan canales de distribución en el denominado comportamiento omni-canal cada vez en mayor medida, tanto para completar una misma compra como entre distintas compras. Distinguimos entre clientes omni-canal, que hacen uso de los servicios de distribución de ambos canales, y usuarios omni-canal, que hacen solo un uso parcial de los servicios de distribución de un canal para apoyar las compras en el otro canal. En este trabajo identificamos este comportamiento omni-canal entre los clientes de una empresa global del sector de la moda que vende un amplio rango de productos de ropa y complementos.

Mediante un modelo logit multinomial, realizamos una segmentación de los clientes en base a su comportamiento omnicanal. En esta segmentación, consideramos el papel explicativo, no solo de las características de los individuos, sino también el de los servicios de distribución y las políticas en cada canal.

Obtenemos cómo el acceso al producto, tanto en el establecimiento como a la página web, la garantía de que el producto comprado online tendrá las características esperadas y las facilidades para devolver el producto adquirido online si no cumple las expectativas, son rasgos clave de los canales que explican el comportamiento omnicanal de los clientes.

Nuestros resultados muestran claramente que diferentes aspectos de la oferta de servicios y de políticas de la empresa determinan las compras y las visitas y estos aspectos pueden ser utilizados para guiar la estrategia de segmentación del detallista.

En este trabajo contribuimos a la literatura sobre el marketing omnicanal presentando un modelo de segmentación, basado en los servicios de distribución ofertados por los minoristas, para las empresas que comercializan productos a través de distintos canales. Aportamos una distinción conceptual entre usuarios de un canal y compradores que tiene un amplio rango de aplicación.

Es necesario proseguir con las líneas futuras de investigación para investigar las implicaciones financieras de esta segmentación. La percepción de los precios que se detecta en nuestros resultados puede sugerir una sensibilidad mayor a los precios en el segmento mono-canal lo que puede ser una línea interesante a contrastar en investigaciones futuras.

Omni-canal, Moda rápida, Trabajo de investigación, Segmentación, Servicios de distribución, Comercio electrónico

Trabajo de investigación

This paper investigates the degree to which self-selection explains the apparent higher purchase value of research shoppers.

An online survey was administered to 594 retail shoppers. The purchase value of research shoppers and single-channel shoppers was compared before and after propensity score matching to account for self-selection effects.

Prior to matching, research shoppers spend significantly more than single-channel shoppers. This difference persists after accounting for self-selection but is reduced by 25%. The impact of self-selection differs across product categories and channels, with the online channel most likely to lead to higher purchase value.

The findings build on existing literature on the value of omni-channel retail strategies and provide insights for retailers to determine the likely impact of encouraging research shopping among their customers.

The research provides important insights into the role that self-selection plays in the value of multi-channel shoppers, and the likely value to retailers of omni-channel strategies.

This paper analyses how the purchase channel and customer complaint goals affect the sequential choice of post–purchase complaint channels when customers experience a service failure followed by a service recovery failure (double deviation).

An online survey involving a scenario manipulation was conducted with 577 apparel shoppers. The study employs multi-group latent class analysis to estimate latent customer segments within both online and offline groups of shoppers and compare latent classes between the two groups.

The results show that the purchase channel has a lock-in effect on the complaint channel, which is stronger for offline buyers. Moreover, there is evidence of channel synergy effects in the case of having to complain twice: shoppers who complain in store in the first attempt turn to online channels in the second complaint attempt, and vice versa. Complaint goals shape the choice of complaint channels and define different shopper segments.

The present study is the first to adopt a cross-stage approach that analyses the dependencies between the purchase channel and the complaint channel used on two subsequent occasions: the first complaint after a service failure and the second following a service recovery failure.

This paper aims to examine why retail firms seldom achieve full integration of online and offline channels as prescribed in omni-channel literature. It examines the intermediate process of channel integration from an internal, operational perspective.

This study is composed of two parts. In the first part, the authors interviewed informants from nine firms that were engaged in channel integration. In the second part, the authors conducted case studies with three firms from the cosmetics and skincare industry against the backdrop of the COVID-19 pandemic to find evidence to support or negate the propositions made in the first part.

The first part identified six operational challenges to channel integration. The authors categorized these challenges into two groups: inter-channel communication and inter-channel competition. Inter-channel competition carries more weight at the latter stage of integration. The authors also identified two antecedents that affect the seriousness of these challenges: heterogeneity among channels in business operation and external competitive pressure. In the second part, the authors found that both inter-channel communication and inter-channel competition were improved because of the external competitive pressure exerted by the COVID-19 pandemic. However, the heterogeneity of offline channels against online channels in business operation is a double-edged sword.

The study identifies the changing effects of the challenges of channel integration and their antecedents in the midst of integration. The positive influence of a specific dimension of channel heterogeneity against other channels increases and then decreases along channel integration. The identification of the changing effects lays the foundation for a finer stage model of channel integration.