We examine offline and online channel sales of experience goods, and compare and contrast the sales patterns of existing products and new products between channels. To this end, we obtain the channel-specific time-series sales data from the leading company selling beauty products, both offline and online. By applying the Vector Autoregressive Model, we empirically find out how the relationship between existing products and new products changes between the shopping channels. Our empirical findings are as follows. First, the sales effects from existing products to new products are significantly positive at both offline and online channels, and this positive effect is greater in the offline channel than in the online channel. Second, the influence of new products on existing products is more positive in the offline channel than in the online channel. Third, the impact of existing products sales on new products sales is greater than that of new products on existing products. Lastly, the inertia effect, the effect within the same shopping channel and the same selling product, is significantly positive in the offline channel but not in the online channel, and this asymmetric inertia effect emerges as we focus on experience goods. Moreover, the impulse response function analysis provides the three important implications. First, companies should pay attention to the same channel but different types of products. Second, the offline channel is more vulnerable to market shock than the online channel. Third, new products sales vary by existing products sales to the greater extent, compared to the opposite relationship. We believe our study contributes theoretically and practically to the fields of marketing and knowledge management.
We are motivated by how offline and online firms compete. The Internet made many conventional offline firms build a dynamic online business as another sales channel using their advantages such as brand equity, an existing customer base with comprehensive purchasing data, integrated marketing, economies of scale, and longtime experience with the logistics of order fulfillment and customer service. Even though the hybrid selling using both offline and online channel seems to have advantages over a pure online retailer, all the conventional offline firms are not seen to create an online business. Many conventional offline firms began to launch online business since the Internet era, however, just being online business is not likely to guarantee success. According to Bizate.com's report whether the hybrid channel strategy is successful is still under investigation. For example, consider the classic case of Barnes and Noble versus Amazon.com, Barnes and Noble was already the largest chain of bookstores in the U,S., when Amazon.com was established in 1995, BarnesandNoble.com followed suit in 1997, After suffering losses in its initial years, Amazon finally turned profitable in 2003. In 2004, Amazon's net income was $588 million on revenues of $6.92 billion, while Barnes and Noble earned $143 million on revenues of $4.87 billion, which included BarnesandNoble.com's loss of $21 million on revenues of $420 million. While these examples serve to motivate our thinking, it does not explain when offline firms should venture online. It also does not provide an analytical framework that can generalized to other competitive online-offline situations. We attempt to do this in this paper and analyze a hybrid channel model where a conventional offline firm competes against online firms using its own direct online channels. We are particularly interested in an optimal channel strategy when a conventional offline firm sells its products through its own direct online channel to compete with other rival online firms. We consider two situations where its direct online channel and other online firms are symmetric and asymmetric in the brand effect. The analysis of this paper presents several findings. In the symmetric model where a hybrid firm's online channel is not differentiated from a pure online firm, (i) a conventional offline firm will not launch its online business. In the asymmetric model where a hybrid firm's online channel is differentiated from a pure online firm, (ii) a conventional offline firm can launch its online business if its brand effect is greater than a certain threshold. (iii) there is a positive relationship between its brand effect and online customer costs showing that a conventional offline firm needs more brand effect in order to launch online business as online customer costs decrease. (iv) there is a negative relationship between its brand effect and the number of customers with access to the Internet showing that a conventional offline firm tends to launch its online business when customers with access to the Internet increases.
Journal of the Korean Society of Clothing and Textiles
/
v.37
no.4
/
pp.467-481
/
2013
The study examined the main effect of the reward channel and reward time of customer loyalty programs for on-offline shopping channels; in addition, it investigated the interaction effect of the reward channels and merchandise as well as the interaction effect of the reward time and merchandise. An online apparel shopping web experiment was conducted with a 2 (reward channel: online channel reward vs. offline channel reward) ${\times}2$ (reward time: immediate vs. delayed) ${\times}2$ (merchandise: online channel product vs. offline channel products) between-subject factorial design. An online shopping channel was considered the core-shopping channel and a department store was considered the cross-shopping channel. Loyalty program value, core-channel loyalty and cross-channel loyalty were measured as dependent variables. A total of 845 shoppers (who had experiences in shopping in both channels) participated in the experiment. The results of the study revealed (1) the main effect of the reward channel on loyalty program value, core-channel loyalty and cross-channel loyalty [online>offline channel rewards], (2) the main effect of reward time on loyalty program value, core-channel loyalty and cross-channel loyalty [immediate>delayed reward], and (3) the interaction effect of the reward channel and merchandise on loyalty program value, core-channel loyalty, and cross-channel loyalty. (4) Finally the study found that loyalty program value affected cross-channel loyalty indirectly through core-channel loyalty. This study suggested diverse theoretical and managerial implications for multi-channel retailers.
The purpose of this study is to reveal and compare the differences in the types and characteristics of purchase channel journeys of MZ generation consumers. In this study a survey was conducted on the purchase channel journey of 20 women in the MZ generation using the ethnographic method of in-depth interviews and observations. As a result, three purchase channel journeys were identified: mobile, multi-channel, and offline. These were variously subdivided according to the characteristics of the MZ generations. Gen Z's journey was categorized into types: fashion platform app, Youtube, multi-channel supplement, multi-channel non-planned store visit, offline loyalty store, and impulsive offline store. Gen M's journey was categorized as: an online community bond, portal site, online loyalty store, multi-channel brand involvement, multi-channel efficiency, a multi-channel conversion, offline efficiency and offline task. The difference in mobile journey between generations was found in the time and length of the purchase. Gen M recognized both online and offline search processes to be tiring, while Gen Z enjoyed the search process using the online path. In the offline journey Gen Z began with their own intention to purchase, while Gen M sometimes recognized that purchasing fashion products necessary for work was a cumbersome task.
This study investigates differences in demographic characteristics, shopping orientation, perceived risk, and satisfaction after purchase among consumer types. This study classifies consumer types according to their channel transition behaviors between the online and offline channels with a focus on the steps of information research and buying decision in buying decision-making process. The four consumer groups are as follows: off-off type (offline research-offline purchase), on-on type (online research-online purchase), on-off type (online research-offline purchase) and on/off-off type (online and offline research-offline purchase), off-on type (offline research-online purchase) and on/off-on type (online and offline research-online purchase). Data were collected from adults over 20 years old who had bought clothes within one year. The questionnaire was carried out from July, 2019 using a professional internet research panel; in addition, 500 sets of useful data were analyzed by descriptive statistics, factor analysis, reliability analysis, chi-squared test, ANOVA and Duncan-test using SPSS 21.0. The findings showed significant differences among the classified consumer groups for consumer demographics, shopping orientation, perceived risk, and purchase after satisfaction. The results imply that consumers show a variety of channel transition behaviors based on demographic variables, shopping orientation, and perceived risk. Understanding and adapting to consumer purchase behaviors will allow company distribution channels to be effectively managed and eventually increase consumer satisfaction as well as company sales volume.
I conducted empirical analyses of what happens when an offline channel expands to an online channel and whether the pre-existing offline channel's competitive assets (e.g. brand reputation and level of service satisfaction) can be linked to online channel preference. I found that an offline channel's brand reputation and level of service satisfaction can have a direct influence on offline channel preference and a second-hand influence on online channel preference. Thus, if the competitiveness of the online channel is strong enough and its customers have a higher preference for the offline channel, they will be committed and loyal to the company. The resultant enhanced competitiveness of the offline channel will present opportunities for both present and future success. The main results are the following. First, the management of the distribution channel service quality is more important than that of the brand reputation. Customers' experiences of service and subjective evaluations are not important only as the leading factors in the long-term brand reputation management but also as influential factors in channel preference. SoThus, given that the service quality of the pre-existing channel is not the customers' main concern, a strategy of improving the level of service satisfaction aimed at present customers is more valuable than a wide brand positioning strategy aimed at general and new customers. Second, when an offline channel company establishes an internet shopping mall on an online channel, it is highly likely that the preference and subjective evaluation of the present customers will influence the online channel. This applies not only to the special case of an expansion from an offline intermediary channel to an online one, but also to an online channel acting as an expansion of the business model of a conventional manufacturing or service company: both cases are vertical integrations of marketing channels in an expansion of the distribution channel. My theory applies to a wide range of contexts. Third and finally, any business strategy can grasp the meaning of 'channel expansion. Fundamentally, it is an expansion of the sales activity channel and marketing activity. However, it is also a way of enhancing marketing and sales competitiveness through an expansion to an online or offline channel. The expansion of an offline company to an online channel could be seen not as improvement but as an innovation of the business process by which two goals are achieved with one technique. The former is expected to increase the sales of the offline company, and the latter is also expected to increase sales while also contributing to cost reduction.
Journal of the Korean Society of Clothing and Textiles
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v.42
no.6
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pp.909-923
/
2018
Online retailers' offline channel expansion is rapidly growing as an important consumer incentive strategy, despite the enormous initial costs of establishing a store. This study focuses on the offline channel operation of online shopping malls, and examines the effects and influencing factors of the channel expansion strategy from a consumer perspective. In-depth interviews were conducted with ten customers in their 20s and 30s who had visited online retailers' stores or purchased products. Major issues were extracted based on the framework of a channel effect mechanism proposed by Cao and Li (2015). Subsequently, it was found that existing online retailers could enhance brand image and perception by expanding their channels to offline stores. It was also emphasized that the consumer trust on the quality of the product in offline stores is a key variable, and it has a significant influence on consumer's continuous purchase and revisit intention. This study showed that borderless channel integration was the most important task when expanding channels of online retailers. So it will be necessary to strive for an omni-channel strategy so that channel integration can be strategically executed and consumers can interact regardless of channels.
Due to recent proliferation of the mobile shopping channels, customers increasingly tend to purchase using online channel while experiencing physical products in offline shops. This phenomenon requires traditional offline retailers to consider integrating online channels. In this study, we propose strategic options for the traditional offline retailers regarding the online channel integration, and provide corresponding decision models to maximize the expected profits. We also investigate how the strategic options vary with the product characteristics, by categorizing the products based on inventory cost, demand uncertainty, and fitness to the online channels. By analyzing numerical examples we illustrate how the best online channel integration strategy should be differentiated depending on the product categories.
This research explores the consumers' experience in retailing channel(offline channel and online channel) using the critical incident technique. This research aims to clarify the common incidents within retailing channels which implies decisive factors over the channels, and to clarify the contrasts between channels to compare advantages and disadvantages. Therefore, the research is designed to collect the consumers' narrative of those who have used both channels in 3 months. Classifications are conducted with other researchers majoring consumer science. The results address how impressive experiences are constructed on each channel in three dimensions: product, information search, and the purchase-service dimension. These results are able to provide implications for offline and online retailers and directions for future research.
This study analyzed the effects of consumers' characteristic variables on information search and purchase decisions in a decision-making process that validated the path model in purchasing apparel products. In constructing a structural equation model using AMOS 19.0., the variables including enjoyment pursuit, price pursuit, product involvement and product risk were selected as consumers' characteristic variables affecting the stage of information search. A questionnaire was distributed to consumers over 20 years old who purchased apparel products using offline and online channels within one year; consequently, we were able to analyze 468 effective data. The results were as follows. First, the path model of this research proved to be the appropriate model explaining the effects of consumers' characteristic variables on the stage of purchase decision-making. Second, enjoyment pursuit had a significant positive influence on offline information search; in addition, price pursuit and product risk affected the online information search significantly. Product involvement affected online information search as well as offline information search. Third, the offline information search affected offline purchase and online information search affected online purchase. However, consumer's channel switching behavior between the stage of information search and the stage of purchase decision was not proven. The findings suggest that companies need to develop distribution strategies according to consumers' characteristic factors that effect consumer's purchase decision-making.
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