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Drawing on the notion of channel capability, we develop a theoretical ramework for understanding the interactions between mobile and traditional online channels for products with different characteristics. Specifically, we identify two channel capabilities-access and search capabilities-that differentiate mobile and online channels, and two product characteristics that are directly related to the channel capabilities-time criticality and information intensity. Based on this framework, we generate a set of predictions on the differential effects of mobile channel introduction across different product categories. We test the predictions by applying a counterfactual analysis based on vector autoregression to a large panel data set from a leading e-market in Korea that covers a 28-month period and contains all of the transactions made through the online and mobile channels before and after the mobile channel introduction. Consistent with our theoretical predictions, our results suggest that the performance impact of the mobile channel depends on the two product characteristics and the resulting product-channel fit. We discuss implications for theory and multichannel strategy.

The Internet has brought consumers increased access to information to make purchase decisions. One of the expected consequences is an increase in the price elasticity of demand, or the percent change in demand caused by a percent change in price, because consumers are better able to compare offerings from multiple suppliers. In this paper, we analyze the impact of the Internet on demand, by comparing the demand functions in the Internet and traditional air travel channels. We use a data set that contains information for millions of records of airline ticket sales in both online and offline channels. The results suggest that consumer demand in the Internet channel is more price elastic for both transparent and opaque online travel agencies (OTAs), in part, because of more leisure travelers self-selecting the online channel, relative to business travelers. Yet, after controlling for this channel self-selection effect, we still find differences in price elasticity across channels. We find that the opaque OTAs are more price elastic than the transparent OTAs, which suggests that product information can mitigate the price pressures that arise from Internet-enabled price comparisons. We discuss the broader implications for multichannel pricing strategy and for the transparency-based design of online selling mechanisms.

The beverage industry is undergoing a dynamic transition in terms of how and where consumers buy products. In an era of rapid digitalization and shifting consumer behaviors, this study investigates how Germany’s wine producers reach consumers and how the distribution landscape of German wine has transformed. A survey of more than 1000 German wine producers allowed us to explore multichannel strategies. Home-country distribution stands for 84% of the production, while export represents 16% of sales. Indirect sales via food retail safeguard a large portion of distribution, but direct sales to consumers matter in value-driven sales. The findings confirm the continued dominance of indirect retail, particularly food retail, while also highlighting a rebound in direct-to-consumer sales, value market approaches, and on-premises distribution. The results of this study contribute to closing data gaps by underlining that gastronomy has been re-established as a relevant distribution channel and that German wine has not profited from global growth in wine trading. Multichannel strategies are increasingly common, but they vary significantly in their depth and reach depending on different business models. We conducted a cluster analysis and identified three strategic groups: (1) consumer-centric, predominantly direct-to-consumer-oriented estates (63%); (2) industrial, multichannel producers with a strong presence in food retail and export (8%); and (3) hybrid operators balancing value and volume strategies (29%). This study contributes to the development of a more nuanced understanding of multichannel distribution in the wine sector and provides empirical insights into the strategic implications of firm heterogeneity.

The study compares the relative performance among bricks-and-mortar, clicks-and-mortar, and pure-click firms. The research model was tested in the Taiwan service industry using a Taiwan Economic Journal dataset of 1448 firms. Using regression analysis, the study provides empirical evidence that clicks-and-mortar firms outperform pure-click firms in terms of efficiency, but not better in profitability and even worse in efficiency than bricks-and-mortar firms. Pure-click firms need to improve their accounts receivable turnover ratio and total assets turnover. While the findings are not in full congruence with past studies, we provide theoretical explanations. Based on the findings, a strategic guide on going clicks and mortar is provided to practitioners.

This work analyzes the behavior of two variables which can determine the use of different channels available to citizens to access public services (face-to-face, mail, phone and Internet). To do so, we will go deeply into the knowledge of the elements which determine the citizens’ satisfaction with face-to-face administration, as well as variables (gender and age) which can moderate the level of satisfaction with the different channels. We also analyze the citizen’s preference for the distribution channel, studying the moderator role which gender, age, marital status, religious beliefs and employment status can play in this. Use is made of data from the 2014 survey of CIS (Spain’s Center of Sociological Investigations) with a sample of 2479 people. The results indicate the presence of a moderator effect of gender and age on the face-to-face and phone channels but not on the rest. In the case of preference, all the variables analyzed moderate the level of preference for the different channels.

The goal of this paper is to investigate the implementation of multichannel strategies in the service sector and to understand objectives, difficulties faced by companies, synergies and competitive effects among channels, and future areas of investment. The research questions used in-depth interviews with a sample of insurance directors responsible for the multichannel strategy of the major French insurance players.

Purpose This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation. Design/methodology/approach This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity. Findings This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers. Research limitations/implications The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings. Practical implications This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS. Originality/value This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

Cooperative spectrum sensing (CSS) is a promising technique in cognitive radio networks (CRNs) that utilises multi-user diversity to mitigate channel instability and noise uncertainty. In this study, the relationship between ‘cooperation mechanisms’ and ‘spatial-spectral diversity’ over multiple channels jointly sensing is investigated in the presence of an imperfect reporting channel. The multiple channels are sensed at the receiver built on the filter bank-based multi-carrier system. The multi-channel CSS strategies are modelled by the introduced ‘cooperative ratio’ to balance the requirements on ‘sensing accuracy’, ‘efficiency’ and ‘overhead’, which is quantitatively characterised by the energy consumption. The target of CSS is to maximise the aggregate opportunistic throughput of secondary users (SUs) by jointly considering constraints on sensing overhead and the aggregate interference to primary users (PUs). The optimisation is divided into two sequential sub-optimisation processes, ‘multi-user diversity optimisation’ and ‘multi-channel diversity optimisation’. An approach is developed from generic algorithms to solve the two sub-problems. Numerical results show that the optimal CSS scheme is effective in improving channel utilisation for SUs with low interference to PUs. This study establishes a valuable cooperative model for the design of multi-channel spectrum sensing algorithms in CRNs.

This chapter discusses how to form a multichannel strategy. It describes how to choose communication channels and reviews simple steps which the marketer can take to develop a more rational channel strategy. They are based on Cranfield's work over a number of years with the blue‐chip members of the Cranfield Customer Management Forum, such as HSBC, BP, British Gas, and IBM. The multichannel strategy process applies equally in business‐to‐business and business‐to consumer contexts, and also to both goods and services. The chapter considers some additional considerations in the case of goods that require physical distribution. Marketing channel decisions for goods are key decisions which involve the choice of an intermediary and detailed consideration of the physical distribution implications of all the alternatives, in addition to the other considerations for both goods and service sectors. The evaluation of distributors is, therefore, of significant importance.

This chapter elaborates on ways to select and prepare a most appropriate multichannel plan for competitive advantage in market. The best form of segmentation for forming multichannel strategy is one based on different customer needs or buying criteria. A thorough understanding of customers’ current channel chains is essential if the channel chains are to be redesigned to provide added value to the customer, lower costs or both. Coverage maps are useful for allocating scarce, expensive channel resource where it is most needed, and making the best use of lower cost channels. The channel curve helps to assess a proposed future channel strategy in terms of what is in it for the customer and what is the likely impact on sales. Understanding of costs information per channel chain is important. The final step before full implementation of a new channel strategy is to pilot any changes to the route to market.