How do customers’ after-sales channel preferences vary across different categories and the factors impacting on after-sales channel preferences

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How do Customers’ After-Sales Channel Preferences

Vary across Different Categories and the Factors

Impacting on After-Sales Channel Preferences

Yumeng Liu (10604316)

MSc. Business Studies, Marketing Track First supervisor: Dr. Umut Konus

Second supervisor: Dr. F.B. Situmeang Final Version

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1. Abstract

After-sales stage, as one of the three purchasing stages of customer purchasing process, has been proved by the scholars to be important to revenue and customer equity. As Vitasec (2005) summarized, after-sales service is often used to describe “services that are provided to the customer after the products have been delivered”. For tangible products, after-sales services are often regarded as “operative activities of some or all members of the distribution chain” (Gaiardelli et al., 2007); while for service providing companies, after-sales services are more seen as “one among several supplementary service elements provided by them” (Oliva and Kallenberg, 2003).

This study contributes to the research of after-sales service on customers’ after-sales channel preferences within different product or service categories. Companies nowadays provide several after-sales service channels for customers, knowing which ones are preferred by the customers helps the marketers to modify the after-sales service channel structure in different product categories and therefore provide better after-sales service for the customers. Moreover, the impact of customer demographic factors on their after-sales service channel preference is also investigated. A survey was conducted to investigate how customers’ after-sales channel preference varies across different categories and the impact of customer demographic factors on their after-sales service channel preference. Results show that in different product or service categories, customers’ preference to physical store, telephone hot-line and

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online help-desk after-sales service channels are completely different. Results also indicated that female customers prefer online after-sales channel than male customers. No evidence showed that there’s different degree of preference to online after-sales service channel between younger and elder customers, and higher-educated and lower-educated customers. Managerial implications of the findings are discussed and suggestions for further research are given.

2. Introduction

In recent years the topic of customer post purchase behavior has received a lot of attention. After-sales, or post purchase is one of the three phases of buying process a customer goes through, which are information search, purchasing and post-purchasing (Frambach et al., 2007). Definitions of after-sales service can be found in many literatures. Except for Vitasec (2005)’s summary mentioned in the last chapter, Ehinlanwo and Zairi (1996), for example, defined after-sales service in their research as “all activities geared towards maintaining the quality and reliability of the car carried out after the customer has taken delivery with the goal of ensuring customer satisfaction”. Johansson and Olhager (2004), in their research within industrial service, defined after-sales service as “the supply of after-sales services, including tangibles such as spare parts and consumables, related to the maintenance of industrial goods”. The term after-sales service is also referred as product service or customer service

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sometimes, according to Goffin (1999). In after-sales stage, not only considerable revenue is generated, but also brand equity of a firm can be strengthened (Ahmad et al. 2011). Therefore it is important for companies to have more knowledge on this buying stage. Profit generated by after-sales services is often higher than the one obtained with sales. The service market can be four or five times larger than the market for products (Bundschuh et al., 2003) and it may generate at least three times the turnover of the original purchase during a given product’s life-cycle (Baumgartner, 1999). As Koskela (2002) indicated, the importance of after sales service can be significant to customer satisfaction, particularly in the B2B environment, and “It is expected that the importance of well-managed services in after sales phase, i.e., care phase will increase, particularly in environments where high capital investments are required and such investments are made over longer periods of time” (Koskela 2002).

Previous researches contributed a lot to the topic of after-sales service; however the after-sales service channel preference of customers is seldom mentioned. The current study focuses on this topic.

Companies nowadays often invest several channels in customer service. It is natural to ask that (1) do these multiple channels receive customer satisfaction and moreover create customer equity, and (2) which after-sales channels do the customers prefer and thus the companies should keep and which of them can be eliminated. This is a compelling issue and of utmost importance to researchers (Peterson & Balasubramanian 2002), as well as practitioners (Reda 2002).

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researched online and off-line channel preference of all the three buying stages and the underlying impacts. In the study of Gensler et al. (2012), they mainly investigated the influence of channel attributes on customer after-sale channel choice and the spillover effect among the three stages. In this study, we focus on a different factor that is assumed to have an impact on customer after-sale service preference, which is the product/service category.

Scholars have indicated that product/service category is influential on customer channel use in the first two buying stages. For example Wang et al. (2011) concluded that the preferences of online and off-line channel usage are different in experience and search goods in the searching and purchasing stages. In the current study seven categories of products/services, varies in tangibility and timeliness. For marketers, it is important to figure out that how customers choose after-sales service channel within different product or service categories, and to understand the reasons of the different preferences. With different product categories, marketers can choose whether to adopt or eliminate a certain after-sales channel, in order to provide better quality after-sales service to their customers.

To sum up, although former studies indicated several factors influencing on customer after-sales service channel preference and the product category’s impact on channel usage, there’s lacking research linking the product category and customer after-sale service preference. To fill in this research gap, this study contributes to the marketing literature and the field of customer after-sale service channel use.

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practical significance. It will help the companies managing the channels better, removing the unnecessary channels in time, providing better after sale service, improving the customers’ satisfaction and making benefit for themselves.

3. Literature Review

3.1 Purchasing Stages in a Multichannel Environment

Previous studies have found that there are three stages that customers go through in their buying process, which are pre-purchase (information search), purchase, post-purchase (after-sales), as presented in Figure 1. In the first stage, customers recognize their need for a product or service, and gather information about it. In the next stage the customers make buying decision and complete purchasing. In the after-sales stage, while using the product/service, the customers may need after-sales service such as professional advices, returning and exchanging products. They may also make decisions about whether or not to repeat purchase the product/service (Neslin et al., 2006; Frambach et al., 2007).

Figure 1. Purchasing stages

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In a multichannel environment, customers have numerous choices of channels to use in each stage of buying process. Neslin et al. (2006) defines channel as “a customer contact point, or a medium through which the firm and the customer interact”. A customer can choose different channels to interact with the product/service provider in his/her three purchasing stages.

For example, when a customer realizes he or she need air-conditioning in his/her bedroom, he/she may firstly go searching information online about the air conditioners and familiarizing him/herself with them in the pre-purchase stage. Next he/she goes to a physical store and picks a certain air conditioner and buys it. In the after-sales stage, he/she receives a variety of services such as maintaining and repairing, by using the telephone to contact the store. The different after-sales services uses can be find in table 1 in chapter 3.3, and the different channels adopted by the customers will be discussed in the next chapter.

3.2 Multichannel

Multichannel recently is a widely discussed topic. As the number of retailers who adopt a multi-channel strategy to service customers keeps growing (Birgelen, Jong, Ruyter, 2006), this particular field is becoming more and more important and significant for scholars to study in. For customers, the opportunity of using different service channels may mean more service outputs, as well as convenience, time savings, and reliability, while the organizational advantages including cross-selling, cost reductions, service innovations, customization and flexibility (Birgelen, Jong,

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Ruyter, 2006).

In the field of customer multichannel management, however, the topic of customer post purchase behavior was rarely discussed. This study will look into the after-sales service channel choice of the customers.

3.3 After-sales Phase of Buying Process

The current research mainly focuses on the last stage of buying process. After-sales activities vary a lot, from warranty, repair service, to caring for negative ecological impacts on the environment (Back-hock, 1992). Other kind of after-sales activities can be found in table 1 below (Back-hock 1992, Potluri et al. 2010, Mupemhi, 2013, Lindfors 2012).

After-sales phase is important as it adds to the product value, and is often treated as a part of the product/service by the customers (Asugman, 1997). According to Cohen et al. (2006), the after-sales market has grown to four or five sizes of the original equipment business in many industries, “in 2001 alone, GM earned more money from $9 billion of after-sales revenues than it did from $150 billion of income from vehicle sales (Cohen et al. 2006)”. After sales is considered to be even more revenue generating than the first two stages (Saccani et al., 2007).

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Table 1. After-sales activities

Activities Note

Warranty

Repair and return service Caring for negative ecological impacts on the environment

Deal with the possible negative

ecological impacts e.g. water pollution. Mostly in manufacturing business.

Purchase follow-up

Update & upgrade E.g. software upgrading. Bug fixing And training Mostly for software products. follow-ups to determine customer

satisfaction after the product purchase and consumption Disposal

Maintenance Delivery

Ahmad et al. (2011) indicated in their research that “the after sales service market is five times larger than the new products market”. The scholars pointed out that after-sale stage not only is important as a revenue source for the companies, but also can be significant to strengthen the brand equity of the firm. They found that after sales service “is related but a separate dimension of consumer based brand equity in

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the automotive sector” (Ahmad et al. 2011). In Wang et al. (2010)’s research, after a negative purchase outcome, the firms can lead the customers to make social comparisons in the after-sale phase, which can improve the post-purchase intention. In after-sales phase, customers seek for after-sales service and evaluate the product or service they purchased and make decisions about whether or not repeat purchasing it. Asugman et al. (1997) defined after-sales service as “activities in which a firm engages after purchase of its product that minimize potential problems related to product use, and maximize the value of the consumption experience”, which can also apply to the current research. In after-sales stage firms provide a number of different services, such as installation, repair service, provision of spare parts of the product, giving advices, provision of support and warranties (Asugman et al. 1997), etc.

Among the many different aspects between after sales stage and the other two purchasing stages, we specially pay attention to the customer channel preference and usage. In the next section this topic will be discussed.

3.4 Customer after-sales service channel use

After-sales activities can be carried out through many channels and actors or “through multiple channels and actors simultaneously” (Saccani et al., 2007). Previous

researches have made some discoveries on the subject of customer after-sales service channel choice. In Kiang et al. (2000)’s literature, the scholars summarized that the channels can be divided into direct and indirect marketing approaches. They indicated that when selecting after-sales channel, customers prefer direct marketing approach if

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the need for service is not critical, and prefer indirect marketing approach if the need for service is critical. Particularly, “For a digital product where need for service is critical, Internet is well suited” (Kiang et al., 2000). The factors that impact the customers’ decisions are waiting time and need for service.

In Frambach et al. (2007)’s research, the scholars indicated that “the channel that will be preferred at this stage is most likely the one that the consumer is most comfortable with” (Frambach et al. 2007) in the after-sales buying stage. The results of their research showed that the online post-purchase service channel is not significantly preferred over the off-line channel among the consumers with high Internet

experiences. The scholars further investigated the drivers of this channel intention. They concluded that “Internet experience and the ability of the offline channel to arouse positive psychosocial feelings are the main drivers” and that accessibility, usefulness and social preference are not important to the consumers in this stage (Frambach et al. 2007).

In another research, Gensler et al. (2012) looked into the impacts of customer channel choice in different buying stages. They mainly considered channel attributes,

experience and spillover effects while examining the customer channel choice

intension. Channel experience effects, as the scholar explained, “occur when using the channel increases the likelihood that the consumer will use the very same channel on the next occasion”, whereas spillover effects “result when the likelihood of using a channel in one stage of the buying process affects the likelihood of choosing that channel in another stage” (Gensler et al. 2012). Different channel attributes have

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different effects on the three buying stages. The scholars conducted a survey among 500 randomly selected German banking customers to do this research. The result showed that the importance of channel attributes, experience, and spillover effects vary among stages of the buying process. In the after sale process, convenient is more important, and experience has a strongest effect compared to the other two processes, which is probably because of that “after-sales is the most frequently recurring stage in the studied product categories”. In this stage, however, the effect of spillover is not significant.

Past research on consumers’ post-purchase behavior has mostly focused on

understanding satisfaction (Mugge, Schifferstein and Schoormans, 2010). Compared to the information search (pre-purchasing) stage and purchasing stage, the number of the existing researches on the customer channel choice making and the impact behind in after-sales stage is relatively short.

Except of the factors above that the former studies indicated to be influential on customer post-purchase service channel choice making, we assume that

product/service category also plays an important role in this. In the following section, the relationship between product categories and customer channel usage will be discussed.

3.5 Product/service categories and customer channel use

Product categories seem to have a significant influence on customer channel usage, specific product categories that are better suited to be sold over a particular channel

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(Inman et al., 2002; Morrison and Roberts, 1998).

Wang et al. (2011)’s research studied the substitution effect between traditional and online channels across different product categories. The result of the research showed that there exists a significant substitution effect between customer traditional and online usage, which was robust across different product categories. In additional there is a direct influence of product involvement on purchase channel choice (Wang et al. 2011).

Ckaufman-scarborough et al. (2002) figured out that “shopping bots’’ or search engines, which “are computer-engineered Web sites that search for specific product categories, tailored to a consumer’s specific tastes”. By providing large amount of information of a particular product category this channel expands “search

convenience”. For these product categories “shopping bots” is a preferred channel by the customers.

In Konus, Verhoef and Neslin (2008)’s study, the authors did a research and segmented consumers by their attitudes toward multiple channels and purchase alternatives. They looked into the association among psychological, economic, and socio demographic covariates and segment membership, explored how customers’ multichannel behavior might differ across different product categories. The scholars found strong evidence of “a multichannel enthusiasts segment that consists of consumers who have positive attitudes toward all channels”. On the other hand, the scholars found no research shopping segment in their aggregate analysis although there were customer segments in few categories with different channels for

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information searching and purchasing. Segment memberships are associated with psychographics (Konus, Verhoef and Neslin, 2008).

Except for customer channel choice, there are also previous studies revealed the influence of product categories on customer channel usage patterns. In Bhatnargar et al. (2004)’s study, they “empirically investigate consumer online information search termination patterns, and relate the differences to product categories and consumer characteristics” (Bhatnargar et al. 2004). To investigate the subject, the scholars developed a model measuring the degree of online search of the time a consumer spends on searching the Internet each time and the frequency of web visit (Bhatnargar et al. 2004). The result of the online survey indicated that “consumer learning occurs when consumers search across search goods, but not when they search across

experience goods” (Bhatnargar et al. 2004).

To sum up, the customer channel choice and usage pattern varies across the different purchasing phases. The influencing factors include the experience/search goods, product involvement level, psychographic reasons and consumer learning, etc.

3.6 Customer demographic factors and channel usage

Although in many researches, the customer demographic factors were set as control variables, there were some scholars shed a light on the relationship between customer characters and customer multichannel usage.

Schoenbachler et al. (2002) indicated that “Demographics such as age, education, income, occupation, and household size are predictors of Internet use, online shopping,

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and catalog shopping and are likely to influence single and multiple channel shopping behavior”. Cortiñas et al. (2010) investigated on the impacts of socio-demographic variables such as age and employment on customer multichannel usage. Results showed that “the age variable has no significant impact on multi-channel behavior, and only the permanently self-employed show high entropy values” (Cortiñas et al. 2010).

In Bhatnargar et al. (2004)’s study, for example, the scholars investigated consumer online information search termination patterns, and relate the differences to” not only product categories, but also the consumer characteristics” (Bhatnargar et al. 2004). They indicated that education may have a statistically significant effect on Web search behavior, and that age has a negative relationship with the degree of search on the Web. Additionally, gender was expected to determine patterns of the search on the Web (Bhatnargar et al. 2004).

The research of Konus et al. (2008) also included customer demographic factors as variables. In their model of customer channel choice, demographic factors such as age, education, household, urbanization, welfare and income were considered. In their opinion, customer income and education have a most consistent and logically sound relationship with multichannel behavior. High income customers tend to shop in varies channels and higher educated customers own the ability of analyzing which channel is the best in purchasing (Konus et al. 2008). However, although the demographic factors do have an influence on customer channel choice making, it is not always significant (Konus et al. 2008).

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In sum, although multichannel field has received great attention of the scholars, the topic of customer after-sales service channel choice and the impact behind is still lacking enough investigation. As can be indicated from the existing literatures, product categories and customer demographic factors both have influence on customer channel choice making in the first two stages of purchasing. One can

assume that the two variables may also have an influence on the post-purchase service customer channel choice.

The customers’ after sales service channel selection was identified as an appealing topic. In Konus, Verhoef and Neslin (2008)’s research, the customers’ information search and post cannel selection were researched, but not the post purchase channel selection. The scholars indicated that future studies may want to shed a light on this. To make contribute to this research gap, this paper intends to investigate the factors influence the customer after-sales service channel preferences.

As concluded above, there is an assumption that product/service categories and customer demographic factors may have an influence on the post-purchase service customer channel choice.

4. Research Question and Conceptual Frame Work

In this study, the research is focused on whether and how people’s after-sales service

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of customer demographic factors on their choice of after-sales service channel. In addition the factors which have impact on customer after-sale service preference will also be discussed.

Figure 2. Conceptual framework

Figure 2 demonstrated the conceptual framework of this study. Except for the product and service categories and demographic factors that impact on customer after-sales channel preference which are investigated in this study, there are many other factors influencing customer after-sales channel preference. For example different psychographic variables lead customers to look into different benefits and have

Customer demographics Customer after‐sales service channel preference Product/service categories Investigated in current study

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different channel preferences (Konus, Verhoef and Neslin 2008). In addition, customer channel choice in one purchasing stage may have a spillover effect on the other two stages, which thus have an influence on customer after-sales channel preferences (Gensler et al., 2012).

In this research, seven categories of products/services will be investigated, which are apparel, grocery, banking products, flight, internet service, electronics and computers. The categories different in tangibility (banking, flight and internet are low in tangibility, and the rest are high in tangibility), and timeliness.

5. Hypotheses development

5.1 Product/service categories and customer after-sales service

channel choice

Although with the trend of multichannel service more business are increasing their channels of after-sales service for their customers, there are still significant

differences of after-sales service channels among different business. For example, in electronic and PC business such as Sony and HP, the companies provide one on one online after-sales service, as well as telephone, fax and physical store service channels. However for the business dealing with food/drink and books, such as Starbucks and Penguin Books, although the companies also provide online service, it is only an online form or email address, much less convenient and fast than the former ones.

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In this part, the factors impact customer after-sales service preferences are assumed. There are different attributes behind different after-sales service channels. For example, online service is more time saving and convenient but with relatively low access to the service, while traditional physical store service is more efficient, since it is face to face service. In different product categories, customer may value different service channel attributes. Thus the impact of different after-sales service choice across different product or service may include the factors of convenience, time-saving, efficiency and accessibility.

For the products of apparel and grocery, for example, the tangibility of them is high. The tangibility of the product may have an influence on customer channel choice (Lian et al., 2008). Since tangible goods require the cooperation of off-line functions to be delivered directly to customers (Cho et al., 2003), customers are unlikely to prefer the online channel for after-sales service. Since the seasonal character of apparel and the short shelf life of food, efficiency and accessibility of after-sales service are valued by the consumers in these two categories of products. Therefore one can assume in these categories of products, consumers prefer physical store channel better for after-sales service. They can easily change or return the products with this channel.

H1: With products of apparel and grocery, customers prefer physical store after-sales service channel over telephone and online service channel.

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For intangible products/services like banking, flight and internet, telephone and internet could be more popular channels for after-sales service. In these categories of products/services, the efficiency of after-sales service is important, and as the

products/services are less tangible, the necessary of going to physical stores is low. Efficiency that customers perceived is proved to be useful in prediction of the decisions to use technology (Davis 1986; Ellen et al. 1991; Hill et al. 1987).

Telephone channel is more convenient and time saving than physical store channel. Internet channel can lower the transaction costs of the customers’ and eliminating time and spatial barriers, and it is suitable for intangible products/services since it can accelerate distribution and provide instant gratification (Vijayasarathy, 2002). Thus one can assume that telephone hot line and internet help-desk are preferred channels for after-sales services in these categories.

H2: With product/service of banking, flight and internet, customers prefer telephone and internet help-desk after-sales service channels over physical store channel.

For products of electronics and computers, internet is assumed to be a more preferred after-sales service channel. Although they are also tangible products, but since the companies of these two categories of products usually provide online service that can be reached immediately the accessibility and convenience of this service channel in these categories of products are highly improved.

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H3: With products of electronics and computers, customers prefer online after-sales service channel over telephone and physical store channel.

5.2 Customer demographic factors and customer after-sales service

channel choice

Individual characters such as customer demographic factors may be another

underlying impact on the different preference of customer after-sale service channel. For example gender and age differences which a lot of scholars in different fields investigated into (e.g., Czaja et al. 2006; Garbarino and Strahilevitz 2004; Morris and Venkatesh 2000; Rodgers and Harris 2003; Venkatesh and Morris 2000), have great influence on people’s individual perceptions, attitudes, and performance (Morris, Venkatesh, and Ackerman 2005).

In Bhatnargar et al. (2004)’s research, they discovered a significant difference between male and female channel usage in the searching stage of purchasing. As the scholars indicated, male consumers may generally spend less time on searching stage of shopping than female. Former studies also pointed out that women feel less

convenient and practical toward online shopping than man do (Rodgers and Harris 2003). That conclusion suggests that in the purchasing stage, men may prefer online channel that women do. Women are also found to perceive a higher risk in online purchasing (Garbarino et al., 2004). Since there is also risk existing in the after-sales stage, and not that convenient perceived by the women, we can assume that women

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may be less likely to use online channel in this phase.

H4: Male customers prefer online after-sales channel over off-line channels than female customers do.

Age is another important factor that can influence people’s attitude and behavior. It is suggested that older individuals are less likely to take risks and more likely to avoid uncertainty (Hofstede 1980). Therefore the older people may be less likely to use online channels. Young people, in contrast, are more open toward new,

Internet-related technologies. They are more willingly to use the new technology due to the convenience and usefulness (Schepers et al, 2007). Thus, one can accordingly that younger people may prefer online channel, which is new technology in after-sales service channel than older people.

H5: Younger customers prefer online after-sales service channel over off-line channels than elder customers do.

As Bhatnargar et al. (2004) indicated, people with higher education degree may more likely be the early adopters of something new, such as the Internet. Therefore one can assume that customers with higher education level may prefer online after-sale service channel over customers with lower education level. Similarly, as young people are usually considered to be early adopters of new things, we assume that younger

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customers prefer online after-sale service channel over customers with elder customers.

H6: Customers with higher education level may prefer online after-sales service channel over off-line channels than customers with lower education level do.

6. Data and Method

6.1 Data Collection

To test the hypotheses, the data is collected from a survey, in consideration of the convenience and response rate. The survey is combined with online survey using the platform of Qualtrics and also delivery and collection questionnaire, therefore the demographic variables varies in the respondents, and the response rate can be ensured. In the online survey, the invitations were sent by e-mails and posted on social networks, stating the identity of the researcher and the research purposes. The confidential guarantee was given.

The data is collected in May 2014, consists of 91 consumers with different nationalities. The respondents are aged between 18 and 54, with both genders. Among the 101 responses received, 10 of them were with mistakes or not fully completed and were deleted. The final data is of 91 respondents.

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6.2 Variables and Survey Design

The survey intended to test the relationship between the independent variable of product/service categories and the dependent variable of customer after-sales channels. The survey was designed including three different types of after-sales service channel: telephone, online helpdesk and physical store, and eight categories of products/services: electronics, books, banking products, clothing, internet service, grocery, and flight.

The respondents were asked to grade each product/ service item with the three matched after-sales service channels of to what extent they will choose each channel for after-sales service of the certain product or service, using a 1-10 scale, with 1 represent for ‘not likely at all’ and 10 represent for ‘very much likely’.

To test the factors impacting on after-sales channel preference, a five-point Likert scale will also be used.

To measure the control variables (demographic factors) of age, gender, education degree and country, the respondents will be ask to fill in their information on these four items.

7. Results

7.1 Data Cleaning

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different nationalities. Among the 101 responses received, 10 of them were with mistakes or missed the majority of the questions and were therefore deleted. The final data consists of 91 respondents.

After checking the missing data, 10 questions distributed in 8 items were found unanswered. There were 1 missing data in each of 6 different items and 2 missing data in other 2 items. These missing data were replaced by mean value of each variable.

7.2 Descriptive Statistics

Results of the descriptive statistics of some demographic variables are provided in the tables below.

Table 2. Gender

Frequency Percent Valid Percent Cumulative Percent

Male 38 41.8 41.8 41.8

Female 53 58.2 58.2 100.0

Total 91 100.0 100.0

Table 3. Highest Level of Education Completed

Frequency Percent Valid Percent Cumulative Percent High School / Secondary School 19 20.9 20.9 20.9 Bachelor's Degree 49 53.8 53.8 74.7 Master's Degree 22 24.2 24.2 98.9 Doctoral Degree 1 1.1 1.1 100.0 Total 91 100.0 100.0

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As can be identified in the results, 38 of 91 respondents are male, consist 41.8 percent of total, and 53 female consist 58.2 percent of the total respondents. Most of the respondents with a bachelor degree as their highest education level completed, respectively 53.8 percent of total. Respondent with high school or secondary school degree and master degree as highest education level completed consist respectively 20.9 percent and 24.2 percent of total. The range of age varies from 18 to 54, with a mean of 28.53.

Table 4. Descriptive Statistics

N Range Minimum Maximum Mean Std. Deviation Age 91 36 18 54 28.53 8.278 Online shopping times in last 1 month 91 15 0 15 2.69 2.682

Internet using hours

per day 91 16 0 16 6.39 2.959

Valid N (listwise) 91

The online shopping frequency varies a lot. In the answer of the question “How many times have you shopped online in last one month”, respondents gave 0 as a minimum number and the 15 as a maximum. The situation is quite similar in internet using patterns, as the least frequent internet-using respondents spend 0 hours online per day and the most frequent internet-using respondents send 16 hours online every day.

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7.3 Manipulating Data

In order to compare the differences of preference of after-sales channel between lower education group and higher education group the five education level groups were collapsed into two groups by recoding the variables. Similar process was done with the age group, the results are provided below.

Table 5. Education Group

Frequency Percent Valid Percent Cumulative Percent less than bachelor 19 20.9 20.9 20.9 bachelor and above 72 79.1 79.1 100.0

Total 91 100.0 100.0

Table 6. Age group

Frequency Percent Valid Percent Cumulative Percent <=30 68 74.7 74.7 74.7

>30 23 25.3 25.3 100.0 Total 91 100.0 100.0

Of all the respondents, 19 were in the group of less than bachelor, and the majority was in the group of bachelor and above. 68 of the respondents were below of at 30 years old, consist 74.7 percent of total, while the number of respondents who were older than 30 is 23, consist 25.3 percent of total.

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7.4 Hypotheses Test

7.4.1 Paired-samples t-test

For hypotheses 1, 2 and 3, we collected data from one group - the whole sample- and on two after-sales service channels as two different occasions. In this case, using paired-t test to compare the two occasions is appropriate; therefore paired-samples t-test was conducted to test hypotheses 1, 2 and 3.

Hypothesis 1: With products of apparel and grocery, customers prefer physical store after-sales service channel over telephone and online service channel.

In hypothesis 1, there are four pairs of variables, respondents’ preference on the physical store after-sales service channel and telephone after-sales service channel in apparel, and respondents’ preference on physical store after-sales service channel and online help-desk service channel on apparel and grocery products.

Table 7. H1 Paired Samples Statistics a

N Std. Deviation t df Sig. (2-tailed) Pair 1 Apparel-Physical Store 91 1.983 Apparel-Telephone 91 1.929 16.660 90 .000 Pair 2 Apparel-Physical Store 91 1.983 Apparel-Online 91 2.545 9.871 90 .000

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The result of the first pair of variables showed a statistically significant difference between respondent’s preference on physical store after-sales service channel (M=7.60, SD=1.98) and telephone hot-line after-sales service channel [M=2.70, SD=1.93 t(90)=16.66, p=0.00] within apparel products. The difference between respondent’s preference on physical store after-sales service channel (M=7.60, SD=1.98) and online help-desk after-sales service channel [M=4.21, SD=2.54 t(90)=9.87, p=0.00] within apparel products is also significant. The results indicated that within apparel product category, respondents prefer physical store after-sales service channel over telephone and online service channel.

Table 8. H1 Paired Samples Statistics b

N Std. Deviation t df Sig. (2-tailed) Pair 1 Grocery-Physical Store 91 1.835 Grocery-Telephone Hot-line 91 2.012 16.056 90 .000 Pair 2 Grocery-Physical Store 91 1.835 Grocery-Online Help-desk 91 2.454 12.080 90 .000

Within grocery product category, there’s a significant difference between respondents preference on physical store after-sales service channel (M=7.99, SD=1.84) and telephone hot-line after-sales service channel [M=2.77, SD=2.01, t(90)=16.06, p=0.00]. A significant difference is also showed between respondent’s preference on

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physical store after-sales service channel (M=7.99, SD=1.84) and online help-desk after-sales service channel [M=4.00, SD=2.45 t(90)=12.08, p=0.00] in this category. The results indicated that within grocery product category, respondents prefer physical store after-sales service channel over telephone and online service channel.

Hypothesis 2: With product/service of banking, flight and internet, customers prefer telephone and online after-sales service channels over physical store channel.

6 pair-samples t-tests were conducted to test hypothesis 2.

Table 9. H2 Paired Samples Statistics a

N Std. Deviation t df Sig. (2-tailed) Pair 1 Banking-Telephone Hot-line 91 2.220 Banking-Physical Store 91 2.061 -2.244 90 .027 Pair 2 Banking-Online Help-desk 91 1.879 Banking-Physical Store 91 2.061 -1.039 90 .302

Results show that within banking product category, the difference between respondents preference on telephone after-sales service channel (M=6.38, SD=2.22) and physical store channel [M=7.08, SD=2.06, t(90)=-2.24, p=0.027] is significant, which indicate that for banking products, respondents prefer physical store after-sales service channel over telephone hot-line. On the other hand, there’s no significant

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difference between respondents preference on online after-sales service channel (M=6.74, SD=1.88) and physical store channel [M=7.08, SD=2.06, t(90)=-1.04, p=0.302] within this category, therefore respondents show a relatively similar preference on the two after-sales channels.

N Std. Deviation t df Sig. (2-tailed) Pair 1 Flight-Telephone Hot-line 91 2.204 Flight-Physical Store 91 1.865 12.604 90 .000 Pair 2 Flight-Online Help-desk 91 1.986 Flight-Physical Store 91 1.865 16.109 90 .000

In the category of flight products, a significant difference is demonstrated between respondents’ preference on telephone after-sales service channel (M=6.99, SD=2.20) and physical store after-sales service channel [M=2.97, SD=1.87, t(90)=12.60, p=0.00]. The difference between respondents’ preference on online after-sales service channel (M=7.36, SD=1.99) and physical store after-sales service channel [M=2.97, SD=1.87, t(90)=16.11, p=0.00] is also significant, indicating that respondents prefer telephone and online after-sales channels over physical store channel in this category.

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Table 11. H2 Paired Samples Statistics c N Std. Deviation t df Sig. (2-tailed) Pair 1 Internet-Telephone Hot-line 91 2.049 Internet-Physical Store 91 1.990 9.049 90 .000 Pair 2 Internet-Online Help-desk 91 2.371 Internet-Physical Store 91 1.990 8.827 90 .000

Within internet service category, difference between respondents’ preference on telephone after-sales service channel (M=6.15, SD=2.05) and physical store after-sales service channel [M=3.87, SD=1.99, t(90)=9.05, p=0.00] is significant. The difference between respondents’ preference on online channel (M=6.68, SD=2.37) and physical store after-sales service channel [M=3.87, SD=1.99, t(90)=8.83, p=0.00] is also significant, therefore one can say that respondents prefer telephone and online after-sales channels over physical store channel in internet service category.

Hypothesis 3: With products of electronics and computers, customers prefer online after-sales service channel over telephone and physical store channel.

Hypothesis 3 refers to 4 pairs of variables; the pair-samples t-tests were also conducted.

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Table 12. H3 Paired Samples Statistics a N Std. Deviation t df Sig. (2-tailed) Pair 1 Electronics-Online Help-desk 91 2.166 Electronics-Telephon e Hot-line 91 2.560 4.103 90 .000 Pair 2 Electronics-Online Help-desk 91 2.166 Electronics-Physical Store 91 2.150 -2.142 90 .035

Within electronics products category, a significant difference was demonstrated between respondents’ preference on online after-sales service channel (M=6.13, SD=2.17) and telephone hot-line after-sales service channel [M=4.78, SD=2.56, t(90)=4.10, p=0.00], showing respondents prefer online after-sales channels over telephone in this category. Significant different is also identified between respondents’ preference on online after-sales service channel (M=6.13, SD=2.17) and physical store after-sales service channel [M=6.90, SD=2.15, t(90)=-2.14, p=0.035], which means that respondents prefer physical store channel over online help-desk channel in this category.

In computer products category, there’s no significant difference between respondents’ preference on online after-sales service channel (M=4.48, SD=2.69) and telephone channel [M=4.70, SD=2.20, t(90)=-0.757, p=0.451]. The difference between respondents’ preference on online after-sales service channel (M=4.48, SD=2.69) and physical store after-sales service channel [M=7.35, SD=1.97, t(90)=-2.17, p=0.00] is

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significant, therefore respondents prefer physical store after-sales channels over online channel within computer products category.

N Std. Deviation t df Sig. (2-tailed) Pair 1 Computer-Online Help-desk 91 2.685 Computer-Telephone Hot-line 91 2.204 -.757 90 .451 Pair 2 Computer-Online Help-desk 91 2.685 Computer-Physical Store 91 1.974 -8.166 90 .000

7.4.2 Independent-samples t-test

In the situations of hypotheses 4, 5 and 6 there are two different groups in each of them. To test these three hypotheses we need to compare the mean score on the continue variable of customers’ online after-sales service channel preference. In this case independent t-test is suitable. Therefore to test hypotheses 4, 5 and 6, independent-samples t-tests were conducted.

First of all, a new variable as the overall preference score for online after-sales service channel was created, by computing average scores. Within this variable the three hypotheses were tested.

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Hypothesis 4: Male customers prefer online after-sales channel than female customers.

Table 14. H4 Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F Sig. t df Sig. (2-tailed) Online Mean Equal variances assumed .104 .748 -2.858 89 .005 Equal variances not assumed -2.880 81.974 .005

Table 15. H4 Group Statistics

Gender N Mean Std. Deviation Std. Error Mean Online Mean Male 38 3.251 .5679 .0921 Female 53 3.606 .5945 .0817

Results show that there’s a significant difference at p=0.005 between male (M=3.25, SD=0.57) and female [M=3.61, SD=0.59, t(89)=-2.86] respondents preference on online after-sales service channel.

Hypothesis 5: Younger customers prefer online after-sales service channel than elder customers.

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Age group N Mean Std. Deviation Std. Error Mean Online Mean <=30 68 3.526 .6497 .0788 >30 23 3.255 .4017 .0838

F Sig. t df Sig. (2-tailed) Online Mean Equal variances assumed 3.427 .067 1.882 89 .063 Equal variances not assumed 2.361 62.179 .021

No significant difference is identified between respondents aged at or less than 30 (M=3.53, SD=0.65) and respondents aged above 30 [M=3.25, SD=0.40, t(89)=1.88, p=0.063] on their preference on online after-sales service channel.

Hypothesis 6: Customers with higher education level prefer online after-sales service channel than customers with lower education level.

education group N Mean Std. Deviation

Std. Error Mean Online

Mean

less than bachelor 19 3.353 .5702 .1308 bachelor and above 72 3.485 .6165 .0727

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F Sig. t df Sig. (2-tailed) Online Mean Equal variances assumed .360 .550 -.840 89 .403 Equal variances not assumed -.880 30.094 .386

There’s no significant difference between respondents with an education level less than bachelor (M=3.35, SD=0.57) and respondents with an education level of or above bachelor [M=3.49, SD=0.62, t(89)=-0.84, p=0.403] on their preference on online after-sales service channel.

Therefore for hypotheses 4, 5 and 6 we can say that female respondents prefer online after-sales service channel than males, while younger and elder respondents, higher-educated and lower-educated respondents show relatively similar preference on online after-sales service channel.

As shown in table 26 below, hypothesis 1 is fully supported by the results and hypotheses 2 and 3 are partially supported by the results. Hypotheses 4, 5 and 6 are rejected by the results.

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Table 20. Hypothesis Supported/Rejected

Hypotheses Supported/ Rejected

H1: With products of apparel and grocery, customers prefer physical store after-sales service channel over telephone and online service channel.

Supported

H2: With product/service of banking, flight and internet, customers prefer telephone and online after-sales service channels over physical store channel.

Partially supported

H3: With products of electronics and computers, customers prefer online after-sales service channel over telephone and physical store channel.

Partially supported

H4: Male customers prefer online after-sales channel than female customers.

Rejected

H5: Younger customers prefer online after-sales service channel than elder customers.

Rejected

H6: Customers with higher education level prefer online after-sales service channel than customers with lower education level.

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8. Discussion and Conclusions

This study aimed at investigating (1) whether and how people’s after-sales service channel preferences vary and differ across different product and service categories and (2) the factors that have impact on customer after-sales service preference. From the results of the hypotheses some implications can be identified.

Results show that customers’ preference of after-sales service channel differs within different product or service categories. Specifically, in product categories of apparel and grocery, customers prefer physical store after-sales service channel over telephone hot-line and online help-desk as we assumed. In these two categories, physical store channel is significantly used more than the other two channels in after-sales service, which fits our expectation based on the theories (Cho et al., 2003). Possible reasons may be that as highly tangible, after-sales service of these two categories of products need offline functions like delivery, repair or exchange, with an especially importance of timeliness. Therefore the physical store channel is more suitable in apparel and grocery categories than telephone and online channels for after-sales service. The results within banking, flight and internet categories, however, partially supported the hypothesis. In banking products, we found higher preference to physical store than telephone hot-line channel, and similar preference to online and physical store channels. The reason behind may be that (1) customer treat products that highly relevant with personal finance with more caution and prefer face to face communication better; (2) bank websites provide much enough information on

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products after-sales service and is easy to access. Results of flight products and internet service fit the previous research and supported the hypotheses, which showed that customer prefer telephone and online channels over physical store channel for after-sales service in these categories. We assume that with products with low tangibility and low relevance with personal finance, customers prefer online and telephone hot-line channels over physical store channel; since the formers are time saving can reduce the cost of transaction (Vijayasarathy, 2002). The hypothesis of electronic and computer products was also partially supported by the results. We assumed that in these categories, customers prefer online after-sales channel than the two off-line channels. The results indicated that in both of the categories, customers showed higher preference to physical store after-sales service channel than online channel, which were completely opposite with the hypothesis. In electronic product categories, online channel is preferred than telephone hot-line channel, and in computer products the two have a similar preference by the customers. Possible explanations for the results is that although companies of these two categories of products provide excellent online after-sales service, offline functions are still required to complete the service, therefore the online channel may not be more efficient than the physical store channel.

Results of the demographic differences on preferences to the after-sales channels were relatively out of expectation. Results show that female customers prefer online after-sales service channel than male customers do, which is opposite to the hypothesis and the relevant theories. For the groups of younger consumers and elder

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consumers, the preference to online after-sales channel is similar. The preference to online after-sales service channel of consumers with higher education and lower education is also similar. The possible explanation of this may be that Internet nowadays is mature and widely used, not a new technology anymore. In the former chapter we assumed that (1) male customers prefer online after-sales channel than female customers, (2) younger customers prefer online after-sales service channel than elder customers and (3) customers with higher education level prefer online after-sales service channel than customers with lower education level. The hypotheses based on the theories that male customers, younger customers and highly-educated customers are early adopters of new technology or prefer to use new technology (Rodgers and Harris 2003, Garbarino et al., 2004, Schepers et al, 2007, Bhatnargar et al. 2004). However nowadays Internet is used for decades and widely adopted, the uncertainty and unsafety are largely reduced than before. Moreover, some of the young and early adopters of Internet decades before now become elder customers in this study. In other words, it is possibly still true that male customers prefer new technology than female customers, younger customers prefer new technology than elder customers and higher-educated customers prefer new technology than lower-educated customers, but since Internet technology is mature and widely-used nowadays, the theories are not suitable in this case anymore. Furthermore, male customers were recognized to prefer online channel than female customers in the searching stage because online channel was regarded to be more time saving. However in the after-sales phase and in some product categories in this study, online

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channel is not more efficient than offline channels, sometimes even less efficient. This may be a reason that the results show that female customers prefer online after-sales service channel than male customers do.

9. Managerial Implications

This study provides some practical implications for marketers on the channel building of after-sales service. For different product or service categories, customers’ preference of after-sales service channel varies.

First of all, as can be identified from the results, in product categories of apparel and grocery, the physical store is the mostly used after-sales service channel compared with the other two channels and in product categories of electronics and computers, physical store is also the mostly used after-sales service channel. Therefore for highly tangible product categories, we suggest the marketers to build strong physical store after-sales service channel and strengthen the face to face service. Particularly, it is noticed that in some countries, e.g. the Netherlands, some of the PC or electronic product companies has very limited number of physical stores. Hewlett-Packard, for example, the users of it can only call their telephone hot-line if they need after-sales service, and a pick-up service may be arranged by the company if necessary. This may because of the situation of human resource or other practical problems, however since it is obvious that customers prefer physical store as after-sales service channel, it is

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suggested that the companies to consider building more brick-and-mortar stores. Furthermore, it is suggested in this study that for intangible products or services like flight and Internet, physical store is the least favored after-sales service channel by customers. However for banking products, customers still like to go to physical stores for after-sales service, compare with the telephone hot-line. For the companies of flight products and Internet service, therefore, it is suggested to cut some physical store after-sales services to reduce the cost, and focus on telephone and online channels. For banking products, physical store channel is as important as online channel, therefore it won’t be a wise decision to cut down physical store service channel. For intangible products and services, it is hard to say that one certain after-sales service channel is preferred, different categories have different situations. At last it should be noticed by the marketers that as Internet is becoming more and more mature and widely adopted, the traditional opinion that elder customers and lower educated customers may not like using online after-sales channel may not be true anymore. Brands and firms focus on these groups should consider building strong online after-sales service channel as well if the product category is suitable.

10. Limitation and Further Research

Some limitations of this study can be recognized. In the first place, as the human resource is restricted, the sample size is limited. Also the range of age of the

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respondents is not wide enough and the education level is to some extent concentrated on bachelor and master degree.

Future researches may want to expand the sample size, the number of product categories and channels compare to the current study. As some scholars pointed out that there is a spill-over effect of channel use among the purchasing phases, the moderating role of spill-over effect may be an interesting topic for the future researches.

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Appendix

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How do customers’ after-sales channel preferences vary across different categories and the factors impacting on after-sales channel preferences