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Retailers begin to create new channel systems to meet changing market environments and innovative information technologies. The growing consumer need and market demand for online sales mean that traditional retailers need to create new integration in their distribution system to serve customers through multiple channels. However, building a successful omni-channel system leads to many challenges. The challenges arise from which customer values perceived by customers. The overall understanding of consumers under the new retail environment is still missing in the literature, and this study conducts an empirical study to close the gap. The author investigates the impact of omni-channel characteristics on customer satisfaction in the context of today's retailing. The findings of this research indicate that although some characteristics of omni-channel have direct impacts on customer satisfaction, relationships between other omni-channel characteristics and customer satisfaction are not supported. Among the constructs, integrated promotion and integrated information access are found to be significant, whereas other constructs are not. Also, the relationship between customer satisfaction and the intention to revisit omni-channel is supported positively. These results raise the need to review the existing strategy and view of omni-channel from the customer's perspective.

•We investigate multichannel assortment planning decisions across retailers.•Retailer’s inventory policy and distribution strategy through an analytical model.•Test relationship between product attributes & retailers’ channel choice.•Retailers are less likely to drop-ship colored/irregularly-sized products.•Detect nonlinearities and thresholds in the effects or product value. [Display omitted] Retailers that sell seasonal products face significant challenges when planning inventory assortment. The incorporation of drop-shipping into their operations, wherein suppliers own and ship products directly to consumers at retailers’ requests, has only complicated these challenges. This study investigates multichannel assortment planning of retailers that sell seasonal products. We first capture structural properties of multichannel retailing of seasonal products through a simple and parsimonious analytical model. The analytical model uncovers key seasonal product attributes that make it more attractive for retailers to allocate a product for sale in the drop-shipping channel than in the store channel. We then empirically assess the findings of the analytical model. Using a rich and unique dataset from the fashion retail industry, we test relationships between product attributes and retailers’ channel choice. The application of a generalized linear latent and mixed model controls for selection bias by jointly estimating retailers’ likelihood of allocating a product’s inventory to the drop-shipping channel and the allocated volume in each channel according to the product’s characteristics. The empirical findings suggest that retailers are less likely to drop-ship products that are colored, irregularly sized, and offered in more style variants. They also unveil cross-channel effects in terms of inventory amounts allocated for sale in each channel according to those characteristics. Our analytical and empirical assessments jointly demonstrate the complementary roles played by drop-shipping and store channels for seasonal products and offer important academic and practical implications.

PurposeThe purpose of this research is to propose and validate a theoretical framework explaining web-rooming and showrooming as a multi-stage decision-making process. The authors have used consumer purchase decision-making theories to propose a model that identifies showrooming and webrooming as a combination of two decisions, channel choice during information search and channel choice during actual purchase. Further, the authors explored how various antecedents of showrooming and webrooming have differential effects on various stages of a purchase decision-making process and how product type moderates the relationships.Design/methodology/approachThe authors have conducted empirical research, whereby 243 responses were obtained from a cross-sectional survey. The authors have used structural equation modeling and multiple regression analysis to validate our theoretical model.FindingsWebrooming or showrooming is a multi-stage decision-making process for the consumers. First, consumers decide whether to search online or offline and then whether to buy online and offline. Different individual, purchase context-related and channel related factors impact these decisions. Product type governs which variables will be more important than others.Originality/valueThe research looks to enhance the understanding of the consumer's decision-making process during showrooming and webrooming while also helping retailers design and implement appropriate strategies that could affect consumers during information search and actual purchase.

•We show the circumstances under which consumers choose D2C over multi-brand webshops.•We provide the pros and cons for brands between D2C and multi-brand webshops.•We find D2C webshops can indeed compete with those of multi-brand retailers.•Deep assortments of exclusive, personalized products that need information are key.•The results differ depending on the phase of the customer journey. In recent years, the emergence of highly successful digital multi-brand retailers has facilitated an omnichannel distribution strategy to become the norm for brands. Rather than relying solely on these multi-brand retailers, it is necessary for companies’ omnichannel strategy to establish strong brand-owned direct-to-consumer (D2C) webstores. To help D2C brands make decisions regarding distribution channel choices, this paper investigates the circumstances under which customers prefer brands’ D2C webstores over digital multi-brand retailers and how these circumstances vary across phases of the customer journey. The results from an extensive experimental study demonstrate that, depending on the customer journey, brands’ D2C webstores can compete with digital multi-brand retailers, particularly in product categories characterized by deep assortments, the need for extensive product information, exclusive products, or a high degree of personalization.

The widespread diffusion of digital technologies along with evolving consumer behaviors and requirements have fostered the emergence of omnichannel businesses, i.e., firms that can exploit integrated processes and information systems to realize a seamless and consistent consumer experience across a plenitude of digital and physical channels. To date, omnichannel research has been cluttered and characterized by significant terminological ambiguity that creates unnecessary challenges for researchers and markeeters trying to navigate and advance research and practice in this area. This fundamentals article seeks to address this problem by presenting a definition of omnichannel business that is grounded in its unique characteristics involving technology, organizational, and market perspectives and clearly distinguishes omnichannel from other terms, such as multi-channel or cross-channel. We leverage this conceptual clarity to analyze and structure the previous research on omnichannel business and conclude with an integrated framework that signifies fields of interest for future omnichannel business research.

The growing number of sales channels through which customers can make purchases has made it imperative for managers to understand how customers decide which channels to use. However, this presents a significant challenge because there is reason to believe the channel decision process evolves over the lifetime of the customer. The authors document the existence and nature of this phenomenon by analyzing the evolution of a customer's channel choice decision process from a trial stage to a posttrial stage. First, they analyze data for a book retailer and replicate their analysis using data from a durables and apparel retailer. Their results suggest that (1) customers' decision processes do evolve, (2) a minority but sizeable segment changes decision processes within the observation period, and (3) customers who change do so from a decision process in which they are highly responsive to marketing to one in which they are less responsive. The authors illustrate and discuss the implications for both managers and researchers.

Surges in e-commerce sales represent a huge challenge for urban freight transport. Parcel lockers constitute a valid solution for addressing the challenges home deliveries imply. In fact, eliminating courier-consumer contact (also relevant for health-related issues, as made evident by the COVID-19 pandemic) and delivering in fewer predefined places might help coping mechanisms for missed deliveries substantially. Furthermore, this option enables consolidated shipping and reduced delivery trip costs. This paper analyses and compares consumer preferences for alternative collection strategies. It investigates home delivery vs. parcel locker use and forecasts their future market shares. This is performed based on both customer socio-economic variables and the attributes characterising these alternative logistic fulfilment strategies. The case study considered tests upon a stated preference survey deployed in the city of Rome. The investigation specifically targeted young people (i.e., population under 30 years) since they represent early adopters. Discrete choice models allow both quantifying the monetary value of parcel lockers attributes (i.e., willingness to pay measures) and estimating the potential demand for this innovative delivery scheme. Results show that distance and accessibility are the main choice determinants. Furthermore, there is an overall high propensity to adopt parcel lockers. This research can support policymakers when implementing such solutions.

Households incur transaction costs when choosing among off-line stores for grocery purchases. They may incur additional transaction costs when buying groceries online versus off-line. We integrate the various transaction costs into a channel choice framework and empirically quantify the relative transaction costs when households choose between the online and off-line channels of the same grocery chain. The key challenges in quantifying these costs are (i) the complexity of channel choice decision and (ii) that several of the costs depend on the items a household expects to buy in the store, and unobserved factors that influence channel choice also likely influence the items purchased. We use the unique features of our empirical context to address the first issue and the plausibly exogenous approach in a hierarchical Bayesian framework to account for the endogeneity of the channel choice drivers. We find that transaction costs for grocery shopping can be sizable and play an important role in the choice between online and off-line channels. We provide monetary metrics for several types of transaction costs, such as travel time and transportation costs, in-store shopping time, item-picking costs, basket-carrying costs, quality inspection costs, and inconvenience costs. We find considerable household heterogeneity in these costs and characterize their distributions. We discuss the implications of our findings for the retailer's channel strategy.

We propose a framework for the joint study of the consumer's decision of where to buy and what to buy. The framework is rooted in utility theory where the utility is for a particular channel/brand combination. The framework contains firm actions, the consumer search process, the choice process, and consumer learning. We develop research questions within each of these areas. We then discuss methodological issues pertaining to the use of experimentation and econometrics. Our framework suggests that brand and channel choices are closely intertwined, and therefore studying them jointly will reveal a deeper understanding of consumer decision making in the modern marketing environment.

This study investigates reverse channel choice for a bi-level closed-loop supply chain consisting of a manufacturer and a retailer. In the forward channel, the manufacturer sells the products through the retailer. We consider three collection channels to collect end-of-use products for the reverse channel: (1) retailer collection (R model), (2) manufacturer and retailer hybrid collection (MRH model), and (3) manufacturer and retailer competitive collection (MRC model). This study considers both manufacturer leadership and retailer leadership for all these three models. After obtaining the members' optimal decisions in the different models using backward induction, the models were applied to a vacuum cleaner company's data in Iran. A comparison of these models shows that the retailer leadership was better than the manufacturer leadership. From the manufacturer leadership perspective, the MRH model is the best one. From the retailer leadership perspective, the prices, the retailer collection rate, and the retail profit are the same in the R and MRH models, while the total collection rate and the total yield are more extensive in the MRH model than in the R model. The MRH model is better than the MRC model at any competition intensity. Moreover, this study indicates that the range of competition intensity between two collection channels in which the MRC model outperforms the R model is different under the retailer leadership and the manufacturer leadership. The results of this study can be used as a reference for reverse channel selection. Finally, we perform a sensitivity analysis for the model parameters.