Multichannel Behavior Research Articles

Market segmentation based on consumers' multi-channel behaviours on e-retail purchases

Consumers use online retailing to purchase and collect information about products. The main purpose of this research is to identify the characteristics of online consumers, focusing especially on low-involvement products according to their multi-channel behaviour. The study population consists of individuals residing in Erzurum, Turkey, and the sample was selected using the convenience sampling method. The data from a sample of 300 participants were collected through online surveys. The link to the survey forms was sent to the participants via e-mail and telephone. The collected data was analyzed with factor analysis - principles components, reliability analysis - Cronbach Alpha, clustering analysis - Two Steps, and correlation analysis - Pearson. Cluster analysis based on consumers' online shopping preferences identified four different consumer groups in detail, focusing on the purchasing channels of online stores and the media touch points of mobile devices and personal computers. The cluster analysis also includes the psychographic and demographic characteristics of the participants. The results of this study can contribute to retailers better shaping their strategies and marketing efforts by providing greater insight into consumers' behaviour in online shopping. It also aims to contribute to the academic literature by emphasizing the importance of low-involvement products in online purchasing processes.

Predicting the Use of Chatbots for Consumer Channel Selection in Multichannel Environments: An Exploratory Study

Online consumers are increasingly looking for more convenient ways to purchase products and services, and chatbots are becoming increasingly popular in multichannel environments due to their ability to provide an efficient service. In this context, managing digital complexity with the help of artificial intelligence and supporting decisions in a multichannel context is an appealing perspective for the retailer, who must find the right strategy to win and keep customers online. The present empirical study aims to better understand consumer behaviour in the multichannel environment in the context of four categories of products and services (retail banking, mobile communications, fashion, and consumer electronics) from the perspective of identifying determinants of channel selection when the consumer uses chatbots. Data were collected from 936 respondents with multichannel retail experience to conduct an empirical investigation on social media platforms, including Twitter, Facebook, and Instagram; these data were then analysed using structural equation modelling (SEM). We found that the online consumer’s multichannel behaviour was not only a reality in the field of broad purchasing decisions but already a norm, and consumers had good reasons to use more channels in the context of chatbots. Research results suggest that chatbots can represent a decision-making aid for managers in retail companies who want to develop an efficient and optimal logistics service strategy in multichannel environments.

A Multiscale Approach to Deep Blind Image Quality Assessment.

Faithful measurement of perceptual quality is of significant importance to various multimedia applications. By fully utilizing reference images, full-reference image quality assessment (FR-IQA) methods usually achieves better prediction performance. On the other hand, no-reference image quality assessment (NR-IQA), also known as blind image quality assessment (BIQA), which does not consider the reference image, makes it a challenging but important task. Previous NR-IQA methods have focused on spatial measures at the expense of information in the available frequency bands. In this paper, we present a multiscale deep blind image quality assessment method (BIQA, M.D.) with spatial optimal-scale filtering analysis. Motivated by the multi-channel behavior of the human visual system and contrast sensitivity function, we decompose an image into a number of spatial frequency bands by multiscale filtering and extract features for mapping an image to its subjective quality score by applying convolutional neural network. Experimental results show that BIQA, M.D. compares well with existing NR-IQA methods and generalizes well across datasets.

Profiling ROPO Shoppers: Shopping Value Perspective

Today’s consumers are multichannel shoppers, that is, they have many channel options for searching product-related information and purchase. This study focuses on one such form of multichannel shopping behavior of online search and offline purchase sequence known as ROPO (research online and purchase offline) behavior in the post-COVID-19 pandemic context. As shoppers return to stores post-COVID-19 pandemic, understanding this ROPO behavior will help retailers to develop strategies to meet their needs. This study attempts to profile the shoppers showing ROPO behavior based on the theory of perceived value of shopping, that is, shoppers select the channels at each stage of shopping that provide maximum value considering the various costs associated with those channels. Six drivers of ROPO behaviors are confirmed based on the sample of 526 respondents using confirmatory factor analysis. Furthermore, three distinct segments of shoppers—risk averters, value maximizers, and convenience seekers—showing ROPO behaviors are identified using k-means cluster analysis. Knowledge of these distinct shopper segments will provide managerial insight for retailers to provide an excellent shopping experience to their customers during the post-COVID-19 pandemic.

A matter of value? Predicting channel preference and multichannel behaviors in retail

The Internet has changed consumer shopping behaviors and purchasing habits. Consumers use the channels that best suit their needs at any given time to have an enhanced shopping experience, forcing companies to innovate in their channel offerings and the ways they manage these channels. This makes it necessary to detect and predict shoppers’ multi-channel behaviors and channel preferences. Based on the idea of value creation and the different aspects of the value perceived by consumers, this study aims to identify the variables predicting channel preference and multi-channel behaviors in retailing. To build a predictive model, the research identifies five categories related to perceived value (perceived quality, monetary costs, non-monetary costs, hedonic elements, and brand knowledge), adding demographic characteristics and variables related to lock-in effects in multichannel shopping behavior. The theoretical predictive model is then empirically tested by comparing the results of traditional and machine learning techniques and algorithms with data from an online questionnaire answered by a representative sample of Spanish consumers of clothing and apparel products. The study contributes to a better understanding of the variables predicting multi-channel behaviors and channel preference, providing companies with actionable insight into how they should manage their multi-channel offering to increase sales.

The multi-generation

PurposeThe aim of this research is to advance the understanding of multi-channel behaviour in terms of different generational cohorts' usage and spending patterns.Design/methodology/approachBuilding 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.FindingsThere 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.Research limitations/implicationsThe 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.Practical implicationsMarketers 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.Originality/valueThis study updates the body of research on multi-channel behaviour by considering generation as a factor in channel usage and spend amount.

Multichannel behaviour in the retail industry: evidence from an emerging market

ABSTRACT With today’s proliferation of channel options, the retail industry should strive to provide a pleasurable experience to customers as they surf across different channels, in order to keep them connected. This study attempts to investigate channel choice in the retail industry in a multichannel environment. It examines the association between three sets of factors namely, psychographic factors, sociodemographic factors and channel experience factors and channel use for search versus purchase by customers. Data was drawn from a sample of 252 customers in the retail industry in Egypt and analysed using structural equation modelling using partial least squares (PLS-SEM). Significant differences were found with regards to psychographic, sociodemographic as well as channel experience factors, between customers who use channels for search and those who use them for purchase. With regards to psychographics, significant differences were found between customers who use channels for search vs. purchase in terms of (innovativeness, internet experience, perceived risk and time pressure). As for demographics (age and education) were significant factors, and as for channel experience factors (price advantage, trust and customisation) were significant factors distinguishing between channel use for search vs. purchase. This study provides useful insights for further research and managerial implications.

Multichannel customer journeys and their determinants: Evidence from motor insurance

This study focuses on channel choices in motor insurance. Our aims are twofold: to fill a gap of empirical studies on the determinants of multichannel behavior in the insurance industry and to help companies improve their retail strategies by better predicting customers’ channel decisions. The paper adopts a broad set of personal and digital channels and several dimensions of customer profiling, including psychographic and channel-experience variables. We identify four different customer journeys, based on channel combinations. Our web-based survey, which has turned out 338 valid responses, shows that the majority of insurance customers adopt multichannel search behaviors. However, although most of the search is carried out through digital media, such channels generate low search-to-purchase conversion rates. Most customer journeys are, instead, finalized in the personal channels (namely, the insurance agents), thus evidencing an interesting webrooming effect. We test our set of hypotheses on the determinants of customer journeys with a multinomial logistic regression. Our findings show that multichannel journeys can serve several purposes: they may reflect the customer need to collect more information, the customer preference for shopping innovation, and his/her preference for shopping convenience. Corporate channel management strategies and practices shall consider such determinants and be revised accordingly.

How to measure quality in multi-channel retailing and not die trying

In multi-channel contexts, interactions between retailers and shoppers may occur in two or more channels along the shopping process. Besides making a revision of both service and e-service quality models, this study proposes a unified model for multi-channel contexts across four dimensions: in-store experience, reliability and fulfillment, security and privacy, and customer service. Moreover, it empirically tests this model using a questionnaire administered to a sample of Spanish shoppers (N = 432) of clothing and apparel. The results suggest an alternative factor configuration of four components: store design; delivery options; reliability, fulfillment and product information; and facilitation of touch and feel experiences. The research includes a practical application example of the resulting conceptualization of quality by exploring the relationship between its dimensions and single-channel or multi-channel behaviors. The results also show that store design has a positive relationship with single-channel behaviors and reliability, and that fulfillment-related aspects are associated with multi-channel behavior.

Generation Y multichannel behaviour for complex services: the need for human contact embodied through a distance relationship

This paper investigates Generation Y’s channel choice decisions and influencers in the service sector from the pre-purchase to the post-purchase phase. Qualitative interviews conducted with 56 respondents show that, contrary to expectations, a large majority of Generation Y members still need human contact for information searching and purchasing, and does not rely on social media for purchasing complex service products, such as insurance policies. We identify three profiles according to the channel path. Human contact seekers heavily depend on parents in their decision process, they look for a personalized relationship and they need to interact with a salesperson whether in an agency or via distance relationship channels. Independent and parental advice seekers rarely visit a store but show the need to develop a distance relationship with the salesperson. Human interaction with the salesperson can be embodied through a distance relationship with traditional communication tools (e.g. telephone) and new digital communication tools (e.g. videoconference; chat).

Achieving Superior Customer Experience: An Investigation of Multichannel Choices in the Travel and Tourism Industry of an Emerging Market

The travel and tourism industry is seeking to achieve consistently seamless experience for customers to stay connected with brands. This study offers an analysis of the interconnected customer experience journey based on an understanding of multichannel behavior. In particular, it identifies the psychographic and sociodemographic factors associated with three segments of multichannel consumers: multichannel shoppers, multichannel searchers, and store-prone shoppers of the travel and tourism industry. Data from a sample of 315 customers from the travel and tourism sector in Egypt were collected and analyzed using multinomial logistic regression. The findings indicate that psychographic variables (shopping enjoyment, convenience seeking, customer innovativeness, perceived risk, Internet experience, frequency of travel, and channel experience) and some demographic variables (i.e., age and income) distinguish among the categories of multichannel shoppers, multichannel searchers, and store-prone shoppers. The study concludes with useful insights into the potential for developing multichannel strategy to achieve superior customer experience.

패션 상품 구매 과정에서의 다중 경로 활용과 경로별 위험 지각 차이 -대학생 성별에 따른 비교-

This study investigated consumers' multi-channel behavior for fashion product purchases and compared perceived risks by channel type. A survey involving male and female college students was conducted in the Daegu and Gyungbuk area in December 2013. A total of 400 responses were analyzed using descriptive statistics, chi-square analysis, independent sample t-test, paired t-test, factor analysis, and reliability analysis. An internet shopping mall was the most frequently chosen retailer type for fashion product purchases and information searches. In addition, respondents also preferred independent branded stores, department stores, and non-branded stores. The number of retailer types for clothing item purchases ranged from 1 to 6 and the average was 3.06. The number of retailer types was significantly higher in women groups according to gender variables. Perceived risk had the highest evaluation score for internet shopping malls. Department stores were recognized as a reliable retailer type. The construct of perceived risk was shown as similar in off-line stores such as department stores, independent branded stores, and non-branded stores. Instead, the construct was differentiated from the case of internet shopping malls. Some insightful suggestions were suggested for future research and industrial marketing plans based on the results.

Fitting International Segmentation for Emerging Markets: Conceptual Development and Empirical Illustration

The increasing attractiveness of emerging markets (EMs), alongside the progression of internationalization, raises the question whether setting up a unified marketing strategy for EMs and high-income countries is appropriate. In this study, the authors use institutionally induced heterogeneity, which refers to distinct consumer patterns evoked by contextual differences, to elaborate on the requirements of an international segmentation that includes EMs, such as microlevel analyses and the inclusion of institutional effects. The authors numerically illustrate the established requirements by applying a multilevel finite mixture modeling of global consumer multichannel (search and purchase) behavior. Doing so provides an initial large-scale analysis that compares consumers from EMs and high-income countries. The findings broadly support the suggested requirements, contributing to the international segmentation and EM literature. Practitioners can apply the insights of this investigation to establish an international marketing strategy. The key recommendation proposes that a case-by-case analysis of EMs is necessary and that solely considering EMs derives incorrect conclusions about international segmentation.

An Information Stock Model of Customer Behavior in Multichannel Customer Support Services

We develop a model to understand and predict customers’ observed multichannel behavior in a customer support setting. Using individual-level data from a U.S.-based health insurance firm, we model a customer’s query frequency and choice of using the telephone or web channel for resolving queries as a stochastic function of her latent “information stock.” The information stock is a function of the customer’s “information needs” (which arise when customers file health insurance claims) and “information gains” (which customers obtain when they resolve their queries through the telephone and web support channels), and other factors such as seasonal effects (for instance, queries that arise at the time of annual contract renewal). We find that average information gain from a telephone call is twice as much as that from visiting the web portal; customers prefer the telephone channel for health event-related information but prefer the web portal for structured seasonal information; and customers are polarized in their propensities of using the web channel and can be broadly classified into “web avoiders” and “web seekers.” Our model provides superior in-sample and out-of-sample fit than multiple benchmark models for aggregate and individual-level customer activity and has several managerial uses, such as capacity planning.

Channel Interactions in a Vertically Differentiated Channel Structure: The Case of Factory Outlet Stores

This study develops and estimates a model of multi-channel customer purchase behavior in a vertically differentiated channel structure. In recent years many retailers have added exclusively sourced factory outlet stores into their channel mix to achieve market expansion and customer segmentation. However, there are two main concerns for retailers who offer a lower quality alternative channel under the same brand name: cannibalization and the impact of the adoption of the lower quality channel on total spending with the retailer. The current literature has two conflicting predictions regarding the impact of adoption of the outlet channel on total spending with the retailer. Multichannel customer behavior research suggests that customer interaction using more channels would be beneficial for the retailer and lead to increased spending. Brand extension research, on the other hand, suggests that adoption of the lower quality channel might run the risk of brand dilution and lead to decreased spending. Using an individual level customer transaction data set from a large specialty apparel retailer, we investigate the impact of adoption of the outlet channel. We jointly model customer purchase timing, channel choice and expenditure decisions. Our results show that on average, overall spending with the retailer increases after the adoption of the outlet channel due to increased purchase frequency. More surprisingly, in addition to incremental spending at the outlet channel, there is a positive spillover that results in increased spending at the retail store channel. Ours is the first empirical study investigating multichannel customer behavior in a vertically differentiated channel structure. Our results showcase the effectiveness of this channel structure in customer segmentation. We find that by offering the lower quality, lower price channel the retailer is able to significantly increase the purchase frequency and spending of the customers on the lower end of the pre-outlet adoption expenditure distribution with no cannibalization on the higher end.

An Information Stock Model of Customer Behavior in Multichannel Customer Support Services

We develop a model to understand and predict customers’ observed multichannel behavior in a customer support setting. Using individual-level data from a US-based health insurance firm, we model a customer's query frequency and choice of using the telephone or web channel for resolving queries as a stochastic function of her latent “information stock.” The information stock is a function of the customer’s “information needs” (which arise when customers file health insurance claims) and “information gains” (which customers obtain when they resolve their queries through the telephone and web support channels), and other factors such as seasonal effects (for instance, queries that arise at the time of annual contract renewal). We find that: average information gain from a telephone call is twice as much as that from visiting the web portal; customers prefer the telephone channel for health event-related information but prefer the web portal for structured seasonal information; and customers are polarized in their propensities of using the web channel and can be broadly classified into “web avoiders” and “web seekers.” Our model provides superior in-sample and out-of-sample fit than multiple benchmark models for aggregate and individual-level customer activity, and has several managerial uses, such as capacity planning.

How to improve e-government use: An empirical examination of multichannel marketing instruments

Citizens interact with government agencies through a variety of channels, e.g., front desk, telephone, website and e-mail. Regardless of these possibilities, they prefer the traditional channels like the front desk. Government agencies strive for a balance between service delivery resulting in customer satisfaction and cost efficiency in their operations. Through better use of the online services by citizens, they can achieve a balance between these aspects. So, government agencies should strive to change citizens' enduring preference for the traditional channels. These preferences can be altered through the use of multichannel marketing (MCM) instruments. In order to use these instruments successfully, not only knowledge on citizen multichannel behavior is required but also on the effects of these instruments. Questions such as how do citizens perceive the various instruments and to what extent are the instruments associated with each other rise up. Based on qualitative depth interviews we formulate constructs to measure citizens' perceptions on the MCM instruments. Subsequently, we empirically test the constructs with a quantitative survey amongst almost 2,000 citizens. As a result, this research increases the knowledge on government MCM and the possibilities to influence enduring citizen channel preferences.

Marketers' perceptions of the implementation difficulties of multichannel marketing

This paper identifies implementation difficulties associated with multichannel marketing as perceived by senior marketers. While, multichannel marketing is being increasingly used because of its revenue enhancing and cost reduction opportunities, it appears more difficult to implement than ‘traditional’ single channel marketing. Traditional strategy implementation frameworks as typified by Miles and Snow and Porter, do not appear to address the implementation complexities of multichannel strategies especially when considering the dynamism of contemporary external environments. Using the methodology of thematic analysis, three implementation difficulty themes were identified: (1) understanding multichannel customer behaviour; (2) delivering sales, service and pre-purchase information; and (3) dealing with organisational politics and conflict caused by emerging channels. We propose that dynamic strategic frameworks can better address complexity and uncertainty, and overcome implementation difficulties. The paper concludes with general and specific research propositions to test the effectiveness of dynamic strategic frameworks in terms of the three themes.

On the Implementation of a Hardware Architecture for an Audio Data Hiding System

Data hiding systems have emerged as a solution against the piracy problem, particularly those based on quantization have been widely used for its simplicity and high performance. Several data hiding applications, such as broadcasting monitoring and live performance watermarking, require a real-time multi-channel behavior. While Digital Signal Processors (DSP) have been used for implementing these schemes achieving real-time performance for audio signal processing, custom hardware architectures offer the possibility of fully exploiting the inherent parallelism of this type of algorithms for more demanding applications. This paper presents an efficient hardware implementation of a Rational Dither Modulation (RDM) algorithm-based data hiding system in the Modulated Complex Lapped Transform (MCLT) domain. In general terms, the proposed hardware architecture is conformed by an MCLT processor, an Inverse MCLT processor, a Coordinate Rotation Digital Computer (CORDIC) and an RDM-QIM processor. Results of implementing the proposed hardware architecture on a Field Programmable Gate Array (FPGA) are presented and discussed.

Does satisfaction matter more if a multichannel customer is also a multicompany customer?

PurposeThis research aims to investigate the moderating influence of both multichannel and multicompany usage on the impact that customer satisfaction has on share of wallet (SOW).Design/methodology/approachThe data used in the analyses were collected as part of both survey and transactional data of 802 households of a large financial services provider. Within class regression models were employed to test the moderating effects of different segments that were identified based on multichannel‐multicompany customer differences.FindingsThe findings confirm that using multiple channels has an overall positive moderating impact on the satisfaction‐SOW link and that customer satisfaction matters more when the customer adopts multiple channels; online channel usage in addition to offline usage. Furthermore, this effect is even more pronounced for customers that transact with multiple providers. That is, the group of customers that use both the company's and competitors' offline and online channels reveal a higher satisfaction‐SOW association than the group of customers that only adopted the offline channel with the company and competitor.Originality/valueThis study broadens the understanding of multichannel behavior by comparing single (offline) and multiple channels (offline and online) for customers of multiple companies (two competitors).