The effect of a website’s enjoyment quality on customer perceived hedonic value and customer relationship outcomes in a B2C e-commerce context

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The effect of a website’s enjoyment quality on customer perceived

hedonic value and customer relationship outcomes in a

B2C e-commerce context.

Melissa Altenriederer (11236248)

University of Amsterdam

Faculty of Economics and Business

Master Thesis: MSc Business Administration

Specialization: Marketing

Supervisor: Frank Slisser

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Statement of Originality

This document is written by Student Melissa Altenriederer who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

This study aimed to examine the influence of a website’s enjoyment quality on customer

perceived hedonic value and customer relationship outcomes in a B2C e-commerce context.

Data was collected from 342 online shoppers via an online questionnaire. Enjoyment quality

was assessed with three variables: (1) Aesthetic design, (2) Playfulness and (3)

Personalization. The results indicated that none of the variables has a direct effect on

customer loyalty, but they do have an indirect effect through the mediators customer

perceived hedonic value and customer satisfaction. Implications of these findings are

discussed.

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1. Introduction

In the last years, there has been a rapid growth of firms engaging in e-commerce, which

intensified the competition within the industry. The intense market competition lead to low

profitability and low survival rates of e-businesses which emphasized the importance of

customer perceived value and customer relationship outcomes, such as customer satisfaction

and loyalty, in gaining a competitive advantage (Chang and Wang, 2011).

A crucial factor influencing these components in a B2C e-commerce context is the

quality of the website. The website is a key determinant of e-business survival, competitive

advantage and long-term success (Homsud and Chaveesuk, 2014). From a customer’s

perspective website quality can be defined as the perceived overall quality of a website,

including not only online features but also offline elements, like product delivery (Shin,

Chung, Oh, and Lee, 2013; Kim, Galliers, Shin, Ryoo and Kim, 2012).

Previous research has identified three key quality dimensions of a website: (1) service,

(2) information and (3) system quality (Delone and McLean, 2003; Kim et al., 2012; Jiang,

Jun and Yang, 2016). Many studies show that these key quality dimensions have a significant

and positive impact on customer satisfaction as well as customer loyalty (Kim et al., 2012).

Furthermore, they play a major role in shaping customer perceived value, which has been

identified as a significant antecedent of customer relationship outcomes (Ha, Janda and

Muthaly, 2008; Tsai and Huang, 2007; Kim et al. 2012; Jiang et al., 2016). Customer

perceived value can be divided into utilitarian value, which describes customers’ trade-off

between functional benefits and sacrifices, and hedonic value, which refers to the trade-off

between emotional benefits and sacrifices in the shopping process (Chang and Wang, 2010;

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However, the key quality dimensions identified by previous research have their

limitations as they mainly focus on utilitarian value (Bauer, Falk and Hammerschmidt, 2006).

In a study by Kim et al. (2012), the relationships of all three key quality dimensions with

customer perceived (hedonic/utilitarian) value and customer relationship outcomes were

investigated. Based on their study, the authors conclude that the key quality aspects appear to

have a substantial impact on utilitarian value and customer relationship outcomes, but the

results regarding hedonic value are very limited (Kim et al., 2012). Furthermore, a recent

study states that utilitarian attributes are no longer sufficient to drive online buying behavior and that today’s online customers seek hedonic value in their online shopping experience

(Bilgihan et al., 2016). Moreover, Bernardo, Marimon and del Mar Alonso-Almeida (2012)

consider the understanding of the role of quality dimensions influencing hedonic value, as

priority line for future research. As a result, future research is called to identify other quality

dimensions than system, information, and service quality that cover hedonic aspects of customer’s quality evaluation (Kim et al., 2012).

Nevertheless, the influence of other website quality scales on hedonic value has

seldom been examined. This can be regarded as major omission as hedonic value is not only

playing an increasingly important role from an academic but also managerial perspective in

the e-commerce field. This is due to the increasing number of hedonic online shoppers, which

describes enjoyment-seeking customers. In contrast to utilitarian shoppers, these online

shoppers put greater emphasis on the hedonic value provided by the online shopping site

(Kim et al., 2012). This claim is supported by Eastman, Iyer and Randall (2009) who state

that the number of people spending substantial time online just for enjoyment is increasing

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Therefore it is important to identify website qualities which shape customer perceived

hedonic value and consequently enhance e-commerce success.

The goal of this study is to fill the gap left by previous studies and investigate the

impact of an additional quality dimension, namely enjoyment quality, on hedonic value and

customer relationship outcomes. Enjoyment quality refers to ‘attractive’ website features that

support an enjoyable online shopping experience (Liu and Arnett 2000; Cao, Zhang and

Seydel, 2005; Bilgihan et al., 2016).

As a result, the following research question will be addressed:

What is the effect of a website’s enjoyment quality on customer perceived hedonic value and customer relationship outcomes in a B2C e-commerce context?

The following sub-questions need to be answered:

What are the key website quality dimensions identified by previous research?

How can a website’s enjoyment quality be defined?

What is the role of customer perceived hedonic value?

What is the relationship between enjoyment quality and customer perceived hedonic value?

What is the relationship between enjoyment quality and customer relationship outcomes?

What is the mediating role of customer perceived hedonic value and customer satisfaction?

1.1. Managerial Relevance

This study will contribute to the understanding of the mechanisms determining customer

perceived value and customer relationship outcomes in a B2C e-commerce context, which are

critical to academics as well as practitioners within this field. Especially for practitioners,

which constantly try to enhance value for their customers, this study will give valuable

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These insights might affect practices which in turn positively affect repurchase behavior and

consequently profitability of B2C e-commerce firms. Improving the understanding of how to

increase website revisits and maximize consumers’ repurchase intentions is critical for the

survival of those businesses. Finally, this study will provide suggestions to establish effective

systems to enhance e-business success.

1.2. Theoretical Contribution

This study contributes to the e-commerce literature by uncovering an additional key quality

dimension, namely enjoyment quality and investigating its impact on hedonic value and

customer relationship outcomes. In doing so, this work responds to the call of research to

identify other website quality dimensions than system, information and service quality that

influence e-commerce success factors, such as hedonic value (Chang and Wang, 2011; Kim et

al., 2012).

This paper will implement the qualityvaluesatisfactionloyalty chain model which

has been widely used in offline marketing settings and apply it to a B2C e-commerce context

(Wang, 2008). Furthermore, the mediating role of hedonic value and customer satisfaction

will be investigated. Different models within the e-commerce literature will be used as a

reference point to define the key constructs. Ultimately the insights gained from this study

will contribute to a better understanding of the underlying mechanisms of customer

relationship outcomes and e-commerce success factors.

The paper is organized in the following matter: First of all, a review of the literature

provides insight into the key website quality dimensions (system, information, and service

quality) and their relationships with customer perceived value and customer relationship

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Based on this insight an additional key quality dimension, namely enjoyment quality, will be

defined. The literature on enjoyment quality will be analyzed, and hypotheses will be

developed and incorporated into a conceptual model. Then, the research design will be

discussed and details about the quantitative research will be provided. Afterward, the results

of the study will be presented and the academic and managerial implications will be

addressed. Finally, the limitations of this study will be listed and suggestions for future

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2. Literature Review

Various studies have focused on e-commerce success factors, but the work of DeLone and

McLean (2003, 2004) has received considerable attention in the academic world. The model proposes that customer’s attitude and behavior are influenced by the customers’ belief about

information, system and service quality of a website.

Later studies focused on these dimensions when defining the quality of a website. In a

study by Kim et al. (2012), the impact of these key quality dimensions on customer perceived

value and customer relationship outcomes was investigated. A model summarizing these

relationships is exhibited in Figure 1. As discussed before, the dimensions and corresponding

variables show only a limited impact on hedonic value. Nevertheless, the model will serve as

a starting point for this examination.

Figure 1 Research model (Kim et al. 2012)

The goal of this chapter is to review the literature and identify an additional quality

dimension which might enhance the thoroughness of the model presented above. The study

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outcomes. For this purpose the qualityvaluesatisfactionloyalty chain model will be

applied. In contrast to the model (Figure 1), this work will not investigate the impact on

utilitarian value as the focus of this study lies on hedonic value only. In order to define the

constructs of this examination, three different streams in the e-commerce literature will be

used. The first one is the website design and information system quality literature, the second

is the e-service quality literature and finally, the quality literature specifically focusing on

enjoyment.

The following sections will provide a short overview of the key website quality

dimensions presented in Figure 1. A short definition of each quality dimension will be

provided and those attributes that have shown to have an effect on either customer perceived

value or customer relationship outcomes or both will be discussed. Subsequently, the

additional quality dimension, namely enjoyment quality, will be presented and discussed in

detail.

2.1. System Quality

System quality measures the technical and functional aspects of a website (DeLone and

McLean, 2003). As can be noted from Figure 1, system quality includes two variables:

accessibility and security. Accessibility refers to the availability of a website ((DeLone and

McLean 2004, Kim et al. 2012). This variable is critical to e-commerce success because,

without access and a stable operation, it is very unlikely that customers will use and purchase

from the online shopping site (Kim et al. 2012). The second factor, namely security, is

concerned with online transaction safety and customer privacy (Jiang et al. 2016). Given the

increasing concern about privacy issues, customers see themselves exposed to an increased

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factor for e-commerce firms. Both factors have shown to have a significant impact on

customer perceived value and customer relationship outcomes (Kim et al., 2012).

There are other studies identifying additional variables of system quality. Examples

include adaptability, usability, ease of use, reliability and response time of a website (DeLone

and McLean, 2004; Cao et al., 2005; Zhou, Lu and Wang, 2009; Zhang et al 2011). However,

discussing all variables in detail is beyond the scope of this work.

2.2. Information Quality

Information quality is concerned with e-commerce content issues (Cao, 2005). “Content is king” and providing information is the basic goal of a website (Huizingh, 2000; Bhattti et al.,

2000). As seen in Figure 1, information quality encompasses two variables: information

variety and currency.

Information variety refers to including diverse information to satisfy different

customer groups (Kim et al., 2012). Different parts of the website should be designed to cover

varying information needs (Cao et al., 2005). This can be facilitated by providing information

search tools and a variety of product lines (Kim et al., 2012). Information currency, on the

other hand, describes to which level customers evaluate the information as novel (Kim et al.,

2012). This attribute highlights the importance of updating existing content as well as adding

new content (Cao et al., 2005). Both variables appear to have an impact customer perceived

value and customer relationship outcomes (Kim et al., 2012). Finally, other studies suggest

that the information on the website should be accurate, adequate, complete and relevant

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2.3. Service Quality

The definition of service quality has its roots in the expectancy disconfirmation theory

(Collier and Bienstock, 2006). This means that customers’ evaluation of service quality

results from comparing expectations of services provided with the perception of actual service

received (Bauer et al., 2006). In other words how well a delivered service level matches or

exceeds customer expectations (Parasuraman, Zeithaml and Berry, 1988).

DeLone and McLean (2004) emphasize that service quality in an e-commerce context

encompasses not only online support but also offline support, for example, rapid product

delivery (DeLone and McLean, 2004). As shown in Figure 1 service quality includes the

following variables: service receptiveness and service quickness. Service receptiveness refers

to providing responsive and reliable service and communicating assurance to customers (Kim

et al., 2012). On the other side, service quickness describes quick answers to a variety of

customer demands, including prompt delivery, response to customer complaints, order

changes, cancellations, returns and refunds (Lin, 2007). As in the case of the other key

qualities discussed before, service receptiveness, as well as service quickness, have a positive

impact on customer perceived value and customer relationship outcomes (Kim et al., 2012).

After this short overview of the key quality dimensions and their corresponding

relationships with customer perceived value and customer relationship outcomes, the

following section will discuss an additional quality dimension, namely enjoyment quality.

2.4. Enjoyment quality

The key website quality dimensions identified by previous research and discussed in earlier

sections have its limitations. As described before, Kim et al. (2012) studied the impact of

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customer relationship outcomes. Although the results show that these quality dimensions have

a substantial impact on utilitarian value and customer relationship outcomes, they show for

instance no significant effect on hedonic value among students. Therefore, the authors call

future research to identify other quality dimensions that might cover hedonic aspects of customer’s quality evaluation (Kim et al., 2012). Moreover, Bernardo et al. (2012) consider

the understanding of the role of quality dimensions influencing hedonic value, as priority line

for future research.

However, most studies focus on the key quality dimensions when defining the quality

of a website and research has paid little attention to investigating different website quality

scales that might have a greater impact on the perception of hedonic value. Bauer et al. (2006)

criticize that most quality scales focus on utilitarian benefits and argue that “not considering hedonic aspects of online shopping (e.g. fun or enjoyment) is a major omission.” (Bauer et al

2006, p. 867). They state that intangible and emotional aspects related to online shopping

should be considered (Bauer et al., 2006). Later studies conclude that utilitarian attributes are

no longer sufficient to drive online buying behavior and that today’s online customers seek

enjoyment and hedonic value in their online shopping experience (Bilgihan et al., 2016). A

superior e-commerce website has an emotional dimension which provides a human touch and

attracts customers to the website (Cao et al., 2005).

This claim is supported by the experiential perspective, which suggests the application

of experiential marketing to website design. The emerging paradigm of experiential marketing

highlights the importance to go beyond the utilitarian or goal-oriented view of shopping and to address customers’ hedonic values. This perspective encourages e-commerce firms to

include experiential elements in their websites in order to turn customers’ shopping sessions

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Improving customers’ online experiences can, for example, lead to longer browsing sessions

which improve the level of interaction (Yun and Good, 2007). Customers who are interacting

with the online shopping provider, are more engaged and therefore more likely to make a

purchase and revisit the online shopping site.

The reason for this is that these interactions can be mentally stimulating and serve as a source

of enjoyment. Providing an enjoyable online experience can help a company to differentiate

itself from its competitors and therefore result in a competitive advantage (Biligihan et al.,

2016).

There are some studies that focus on experiential quality dimensions and attributes,

which include enjoyment, aesthetic design, atmospherics, entertainment, playfulness,

personalization and attractiveness of a website (Liu and Arnett, 2000; Cao et al., 2005, Bauer

et al., 2006; Chang and Chen, 2009, Kassim and Abdullah, 2010; Rose, Clark, Samouel and

Hai., 2012; Ha and Stoel, 2009; Shin et al., 2013). However, the impact of these qualities has

received relatively little attention, especially in a B2C e-commerce context. In order to fill the

gap left by previous research, especially on aspects related to the enjoyment of website use,

this work will introduce enjoyment quality as an additional quality dimension.

Liu and Arnett (2000) suggest focusing on enjoyment when designing a website. This

means including attractive features, promoting customer excitement and motivating customers

to participate (Liu and Arnett, 2000; Cao et al., 2005). Bauer et al. (2006) found out that

enjoyment quality positively influences relationship duration and repurchase intention of

online customers and is, therefore, a major determinant of online shopping behavior.

Furthermore, Bilgihan et al. (2016) show that user interfaces that integrate enjoyment quality

have a considerable impact on online experiences and online shopping outcomes. A review of

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playfulness, and personalization. The following sections will provide a detailed description of

each variable.

Aesthetic design

Previous research shows that aesthetic design is a major factor, which supports customer

enjoyment (Ha and Stoel, 2009). Aesthetic design refers to the attractiveness or visual appeal

of a website (Cao et al., 2005; Yun and Good, 2007).

In a traditional setting aesthetic features like store layout, color scheme, lighting,

music, and odor affect customer shopping behavior (Baker, Levy and Grewal., 1992).

Translated to an online context similarly aesthetic cues can provide sensory stimuli and affect

the online customer experience. These stimuli may include layout, color, graphics, fonts,

product displays and professional design. (Rose et al., 2012). Other studies refer to such aesthetic stimuli as “atmospherics,” which describes the attempt to design a web environment

that triggers customers’ emotional responses, which in turn increases the chances of making a

sale (Chang and Chen, 2009). Floh and Madlberger (2013) argue that atmospheric cues trigger

impulsive buying behaviors and positively influence customer spending. E-commerce firms

can project a certain image and character through the input of aesthetic features, which on the

one hand can help to make visual content easy to read and on the other create an atmosphere,

which makes the online experience more enjoyable for its customers (Bilgihan et al., 2016).

Furthermore, Smith and Merchant (2001) highlight the importance of aesthetic design

in a B2C e-commerce context, by stating that even if customers perceive the quality of

content as high and the website easy to navigate when customers don’t find the website

appealing they are likely to abandon it. Furthermore, Bilgihan et al. (2016) argue that the

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an online shopping site. As customers cannot see or touch the products offered online, it is

harder to evaluate the quality of a product. As a consequence indicators for an online shopping provider’s credibility and commitment are gaining in importance (Yun and Good,

2007).

Moreover, Bauer et al. (2006) found out that online customers strongly associate visually

appealing websites with high efficiency and a high degree of content quality. This might

induce customers to purchase from even unknown online shopping sites (Chang and Chen,

2009). This claim is in line with Luo et al. (2006), which argue that a website which is

visually appealing and pleasing to the eye influences the perceived trustworthiness of the

online shopping provider.

However, a potential problem in this context is that customers consider the aesthetics

of a website as an important feature at first, but after purchasing from the site, it might

become less important, leading to a diminishing effect on customer repurchase (Zhou et al.,

2009). Therefore it is a key challenge for e-commerce firms to create a website that is visually

appealing on first viewing but also designed in a way that it encourages customers to revisit

the website (Kassim and Abdullah, 2010).

To sum it up, it is important to acknowledge that creating enjoyable online experiences

requires an understanding of aesthetic appearance (Bilgihan et al., 2016). The “first

impression” counts and a positive image positively influences customer perceived value and

loyalty intentions (Luo et al., 2006; Kassim and Abdullah, 2010; Yun and Good, 2007).

Therefore, the aesthetic design should be considered not only as a key feature of a

website but also as a marketing strategy as it helps to distinguish the online shopping site

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Playfulness

Online shoppers often seek excitement, entertainment, and interaction when browsing through

online shopping sites as it helps them to escape from daily life (Liu and Arnett, 2000; Bauer et

al., 2006). E-commerce firms can respond to those customers by considering mechanisms that

increase the level of the playfulness of their websites (Cao et al., 2005).

Playfulness or the entertainment of a website helps to attract customers and supports

enjoyable online experiences (Cao et al., 2005; Bilgihan et al., 2016). It includes entertaining

features, for example, online games, that promote enjoyment, motivates customers to

participate and increase customer excitement and concentration (Liu and Arnett, 2000; Chen

2001; Cao et al., 2005; Bilgihan et al., 2016). Moreover, embedding playful features within a

website helps to differentiate the website from others (Cao et al., 2005).

Bilgihan et al. (2016) argue that e-commerce firms can borrow design cues from

gaming to involve customers during their visit and ultimately increase customer activities. As

mentioned before, longer browsing sessions increase the level of interaction leading to more

engaged customers and therefore higher chances of customers revisiting and repurchasing

from the website (Yun and Good, 2007; Bilgihan et al., 2016). Furthermore, those virtual

interactions with a company can be mentally entertaining and therefore serve as a source of

enjoyment (Bilgihan et al., 2016). As a result, playfulness can be considered as another key

attribute of a website, which is likely to influence customer perceived hedonic value and

customer relationship outcomes (Cao et al., 2005).

Personalization

In addition to aesthetic design and playfulness, another important factor influencing

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Personalization, also referred as customization of a website, describes the degree to which

information, products, services and the transactional environment are tailored to the individual

customer (Bauer et al., 2006; Chang and Chen, 2009; Kassim and Abdullah, 2010). Kramer et al. (2000, p.45) state that “features classified as personalization are

wide-ranging, from simple display of the end user's name on a Web page to complex catalog navigation and product customization based on deep models of users’ needs and behaviors.

Similarly, personalization technologies range from the commonplace use of databases,

cookies, and dynamic page generation, to esoteric pattern matching and machine-learning

algorithms, rule-based inferencing, and datamining” (Bilgihan et al., 2016). Personalization includes processes of “data collection,” “profiling” and “matching.” Customer data enables

firms to create user profiles which serve as the basis for adapting user interfaces to individual

customers or customer groups and providing highly customized offerings (Tsai and Huang,

2007; Bilgihan et al., 2016). An example is the recommendation system of the online

shopping site “amazon.com,” which collects data on customers’ previous shopping behavior

and recommends similar products based on their search and purchase histories (Bilgihan et al.,

2016).

Chang and Chen (2009) argue that personalization creates the perception of increased

choice by enabling customers to focus on products and services suitable to their wants and

needs. Moreover, it increases the chances of customers finding something they wish to

purchase, making the online shopping site more attractive for them (Chang and Chen, 2009).

Customers value products and services more when they feel they are personalized for them

because personalization communicates preferential treatment, attention and personal

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Therefore personalization provides not only functional benefits by reducing searching costs of

customers and supporting shopping goals but also emotional benefits by communicating a

feeling of being treated as a unique customer (Chang and Chen, 2009; Tsai and Huang, 2007).

As a result, personalization might not only lead to higher customer perceived utilitarian value

but also to higher perceptions of hedonic value provided by the online shopping site (Chang

and Chen, 2009; Bilihan et al., 2016; Bauer et al., 2006; Ha and Stoel, 2009; Tsai and Huang,

2007).

Bilighan et al. (2016) conclude that personalization is a key feature for providing

positive online experiences. Also, other studies emphasize the importance of personalization

in increasing customer perceived value and building customer loyalty (Tsai and Huang, 2007;

Chang and Chen, 2009).

2.5. Customer perceived Value

Customer perceived value is not only a major antecedent of customer satisfaction but also an

important determinant of customer loyalty and repurchase intention in an offline setting as

well as online setting (Ha et al., 2008; Tsai and Huang, 2007; Chang and Wang, 2011; Kim et

al., 2012; Jiang et al., 2016). Particularly in the highly competitive online environment, it is

crucial for e-commerce firms to understand and deliver customer value to retain customers

(Chang and Wang, 2011; Kim et al., 2012). Tsai and Huang (2007) found out that unique

perceived customer value strengthens the relationship between customers and e-commerce

firms. As a result, customers start ignoring information about alternative options.

Customer perceived value has its root in equity theory and can be defined as

“consumer’s perception of the net benefits gained based on the trade-off between relevant benefits and sacrifices derived from the online shopping process” (Chang and Wang, 2011, p.

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339). A high degree of customer perceived value leads to positive evaluations of products and

services and positive affection for the provider. As a consequence providing superior

customer value will increase switching barriers of customers and at the same time improve

customer loyalty (Tsai and Huang, 2007; Chang and Wang, 2011).

Customer perceived value can be divided into two pervasive and dichotomous

categories: utilitarian value, which is determined by rational, decision-effective and

goal-oriented motivations, and hedonic value, which describes the fun and excitement of a

shopping experience and underlies fun-seeking motivations (Kim et al., 2012). This is line

with another study that concludes that there are two different routes affecting customer loyalty

in online shopping processes: the first one is the rational route, which describes utilitarian

motivations and the second one is the emotional route which refers to hedonic aspects (Chang

and Wang, 2011).

Earlier studies identified online shopping sites as an ideal channel for utilitarian online

shoppers, which can be described as goal-oriented customers (Donthu and Gilliland, 1996).

Utilitarian value is provided when customers’ navigation needs and shopping goals are

successfully fulfilled (Babin et al., 1994). This approach is based on a rational view of

customer behaviors and suggests that customers place a high value on time-saving (Cotte and

Ratneshwar, 2003), convenience and money benefits (Huang, 2005) derived from online

shopping processes (as cited in Bilgihan et al., 2016). For instance, flight booking sites attract

utilitarian-oriented customers as they offer a simple way to compare competitors’ prices and

enable customers to save money and time by conveniently booking a flight online. Based on

equity theory it can be concluded that utilitarian value can be derived from the trade-off of

functional benefits and sacrifices (Chang and Wang, 2010; Bilgihan et al., 2016).

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emotional benefits and sacrifices (Chang and Wang, 2010; Kim et al., 2012; Biligihan et al.,

2016). Recent studies highlight the importance of hedonic value in driving online buying

behavior and building customer loyalty (Kim et al., 2012; Bilgihan et al. 2014). There is an

increasing number of hedonic online shoppers, which seek apart from utilitarian website

features, websites that provide experiential quality and sensual stimulation which ultimately

lead to enjoyment (To et al., 2007; Bauer et al., 2006; Kim et al., 2012). Furthermore,

Eastman et al. (2009) argue that the number of people spending substantial time online just

for enjoyment is increasing and that this type of customer is very likely to purchase online.

Moreover, Sorce et al. (2005) argue that this kind of shoppers represent an important source

of revenue. As a result, e-commerce firms can highly benefit from including website qualities

that create an enjoyable online experience and increase hedonic value (Sorce et al., 2005; Kim

et al., 2012). This further supports the identification of enjoyment quality as a key website

quality dimension in this examination.

Different shopping goals trigger different online shopping behaviors. Therefore

e-commerce firms should include website features that provide not only utilitarian but also

hedonic value (Ha and Stoel, 2009). Hedonic and utilitarian value positively influence online

customer satisfaction, motivate customers to revisit the website and increase repurchase

intention (Liao et al., 2006; Kim et al., 2012). Both are important for relationship marketing

as utilitarian value affects the preference for the online shopping site and hedonic value helps

to differentiate the site from competitors by providing a unique experience (Kim et al., 2012;

Bilgihan et al., 2016). Based on the equity theory it can be concluded, everything else being

equal, a high degree of customer perceived utilitarian and hedonic value enhances customer

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2.6. Customer Relationship Outcomes

This study focuses on two customer relationship outcomes: customer satisfaction and

customer loyalty. Both play a crucial role in shaping B2C relationships and previous research

in the e-commerce field has shown that customer satisfaction serves as a primary antecedent

of customer loyalty (Kim et al. 2012)

Customer loyalty includes two different dimensions, namely an attitudinal and

behavioral dimension (Oliver, 1999). The attitudinal dimension describes a higher-order,

long-term and psychological commitment of customers to repurchase in the future and

continue the relationship with the firm (Oliver, 1999; Shankar et al., 2003). Behavioral

loyalty, also described as action loyalty, refers to actual repeat purchases of customers.

Research tends to focus on attitudinal loyalty and primarily uses customer repurchase

intention to measure customer loyalty. This is because behavioral loyalty is often too difficult

to observe and to measure (Yang and Peterson, 2004). This study will, therefore, use customer

repurchase intention as a proxy for customer loyalty. Repurchase intention describes a customers’ motivation to make another purchase from the online shopping provider on the

basis of previous experiences with the provider (Hellier et al., 2003).

As discussed before customer satisfaction as well as customer loyalty and repeated

purchases are crucial to the success of e-commerce firms which operate in a highly

competitive environment and are confronted with a high risk of customers switching to

alternatives. This is due to low customers’ switching costs and the tremendous amount of

alternative options. Customers can easily compare information, browse through a variety of

websites and ﬁnd other websites that provide similar products or services to fulfill their consumption needs (Kim et al., 2012).

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Consequently, examining factors that influence customer loyalty is highly relevant to

researchers as well as practitioners (Hellier et al., 2003). Moreover, Kim et al. (2012) argue that “Internet shopping businesses cannot survive without understanding the mechanism of

consumers’ repurchase intention.” (Kim et al. 2012, p. 385). This work will address these

mechanisms and investigate the impact of enjoyment quality on repurchase intention and

thereby contribute to the understanding of customer relationship outcomes in a B2C

e-commerce context.

2.7. Development of Hypotheses

Based on the literature review and definitions and corresponding relationships of the key

constructs, this section will develop and present the hypotheses of this work.

Direct effects

Previous research identifies quality as a central construct that drives customer relationship

outcomes and shows that providing superior quality significantly influences the loyalty

intentions of customers (Zeithaml, 2000). This work will analyze the impact of enjoyment

quality, which can be defined by three variables: (1) aesthetic design, (2) playfulness and (3)

personalization.

As mentioned before, aesthetic design refers to the visual appeal of a website, which

supports an enjoyable online experience (Yun and Good, 2007; Bilighian et al., 2016; Hae and

Stoel, 2009). Aesthetic elements like layout, color, graphic, fonts, product displays and

professional design can create a certain “atmosphere,” which triggers consumers’ emotional

responses and affect customer relationship outcomes (Bauer et al., 2006; Chang and Chen,

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Furthermore, the playfulness of a website increases the fun and customers’ excitement

of using an online shopping site (Liu and Arnett, 2000; Chen, 2001; Cao et al., 2005). It

promotes enjoyment, which leads to a positive online shopping experience and highly

engaged customers. Consequently resulting in positive effects on customer relationship

outcomes (Biligihan et al., 2016).

Finally, personalization provided by an e-commerce firm enables customers to find

products and services suitable to their needs (Chang and Chen, 2009). Personalization positively influences customers’ online experience and enjoyment when shopping online

(Bilihan et al., 2016; Bauer et al., 2006; Ha and Stoel, 2009). Furthermore, it communicates a

feeling of being treated as a unique customer with individual needs (Tsai and Huang et al.,

2007). As a result, personalization might lead to higher levels of customer satisfaction and

customer loyalty. Therefore the following hypotheses are proposed:

H1: Aesthetic design (1a), playfulness (1b) and personalization (1c) are positively related to customer loyalty.

H2: Aesthetic design (2a), playfulness (2b) and personalization (2c) are positively related to customer satisfaction.

Additionally, in the literature, it is widely undisputed that customer satisfaction is a major

antecedent of customer loyalty. Therefore the following hypothesis argues that:

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Mediated effects

Previous research has identified not only customer satisfaction but also customer perceived

value as a significant antecedent of customer relationship outcomes (Kim et al., 2012; Jiang et

al., 2016). Applying the qualityvaluesatisfactionloyalty chain model to a B2C

e-commerce context, this work proposes that enjoyment quality influences customer perceived

value and customer satisfaction which in turn has an impact on customer loyalty. This means

that hedonic value and customer satisfaction might play a mediating role. Therefore the

following hypotheses state that:

H4: The relationship between aesthetic design (4a), playfulness, (4b), personalization (4c) and customer loyalty is mediated by hedonic value and customer satisfaction in serial, so that

aesthetic design, playfulness, and personalization lead to an increase in hedonic value, which

in turn positively influences customer satisfaction and subsequently customer loyalty.

H5: The relationship between aesthetic design (5a), playfulness, (5b), personalization (5c) and customer loyalty is mediated by hedonic value, so that aesthetic design, playfulness, and

personalization lead to an increase in hedonic value, which in turn positively influences

customer loyalty.

H6: The relationship between aesthetic design (6a), playfulness, (6b), personalization (6c) and customer loyalty is mediated by customer satisfaction, so that aesthetic design,

playfulness, and personalization lead to an increase in customer satisfaction, which in turn

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2.8. Conceptual Model

In the previous sections, six sets of hypotheses were established. The relationships are

illustrated in the conceptual model (Figure 2).

Figure 2 Conceptual Model

Aesthetic Design Playfulness Personalization Customer Satisfaction Hedonic Value Customer Loyalty

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3. Research Method

This chapter represents the first step of the empirical study. First, the most evident

characteristics of the collected sample will be presented. Afterward, a detailed description of

the measures will be provided, which includes all variables of the questionnaire and their

corresponding reliabilities. Finally, the research design and data collection procedure will be

discussed. See the appendix for the full questionnaire.

3.1. Sample

This study used a non-probability approach and targeted people with previous online

shopping experience. Data was collected via a combination of self-selection, snowball, and

convenience sampling. The survey was distributed via the author’s network. Moreover,

invitations to participate in and forward the survey were posted on social media. Furthermore,

hardcopy questionnaires were distributed in schools, companies, universities and cafes to

sample data from various groups and increase external validity.

Of the 342 respondents that have started the survey, 245 respondents have filled in the

complete survey (response rate 71.64%). Gender was relatively equally represented, with

women (53, 8%) slightly outnumbering men (46, 2%). The largest age group was 25-34 (50.

6%), followed by 18-24 (45.2%). 35-44 (1.9%), 45-54 (1.0%), 55-64 (1.0%), <18 (0.3%). As

a result, the majority of the respondents were between 18-34 years old, representing 96, 2% of

the sample. The academic attainment of the respondents was relatively high, with 54, 3% of

respondents having graduated from university. Followed by respondents having completed at

least high school education, representing 36, 3%. The sample consisted mainly of students

(49, 7%), followed by employed (40, 2%), self-employed (5, 1%), unemployed (2, 2%)

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3.2. Measurement of variables

In order to maximize reliability and internal validity of the study, survey items from previous

e-commerce research were used to develop a questionnaire and measure each construct. All

items were measured on a seven-point Likert scale, ranging from “strongly disagree” (1) to “strongly agree” (7).

Enjoyment quality

Enjoyment quality includes three variables: aesthetic design, playfulness, and personalization.

For the measurement of aesthetic design, the measurement scale of Shobeiri et al.

(2015) was used. The scale includes three items and reports a Cronbach’s α=.892. An

example item is “The way the online shopping site displays its products is attractive.” The

items of the construct were measured by a seven-point Likert scale, with anchors of (1) for “strongly disagree” and (7) for “strongly agree.”

The measurement items for playfulness are based on the study of Cao et al. (2005).

The measurement scale consists of five items, including for example the following item “The

website is entertaining.” Cao et al. (2005) reported a Cronbach’s α=.92 for their scale. The

measurement was conducted by using a seven-point Likert scale, ranging from “strongly disagree” (1) to “strongly agree” (7).

Furthermore, the measurement items of personalization were adapted from the study

of Tsai and Huang (2007). Personalization (Cronbach’s α=.88) includes five items; an item example is “The online shopping site makes purchase recommendations that match my

needs.” The items were measured with a seven-point Likert scale, anchored by “strongly disagree” (1) and “strongly agree” (7).

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Hedonic value

For the measurement of hedonic value, the measurement scale of Kim et al. (2012) was used.

The scale included four measurement items, a Cronbach’s α=.90 was reported. An example

item is “Internet shopping makes me feel as though I have escaped from daily life”

Respondents rated the items on a seven-point Likert scale, ranging from “strongly disagree”

(1) to “strongly agree” (7).

Customer Satisfaction

To measure customer satisfaction the measurement items of Kim et al. (2012) were used.

Satisfaction encompasses four items, including for example “I am relatively satisfied with the

online shopping experience I have had on the online shopping site.” Kim et al. (2012)

reported a Cronbach’s α=.83. The measurement was conducted by using a seven-point Likert

scale, ranging from “strongly disagree” (1) to “strongly agree” (7).

Customer loyalty

Intention to repurchase was used as a proxy for customer loyalty. For the purpose of

measuring repurchase intention, the measurement items of Kim et al. (2012) were adopted.

Intent to repurchase encompasses five items, including for example “Except for any

unanticipated reasons, I intend to continue to use the Internet shopping site that I regularly

use.” The items were measured with a seven-point Likert scale, anchored by “strongly disagree” (1) and “strongly agree” (7). Kim et al. (2012) reported a Cronbach’s α=.84, which

indicates a high level of internal consistency. This is in line with all the values (Cronbach’s α

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Control variables

The results of the study are controlled by four control variables, including age, gender,

education and occupation. These control variables are commonly used in studies on website

quality, hedonic value and customer relationship outcomes in a B2C e-commerce context

(Bauer et al. 2006; Kim et al. 2012; Rose et al. 2012).

3.3. Data collection procedure

This study used descriptive approach and adapted an observational, also known as

correlational research design to test the proposed hypotheses. The method chosen for this

study was a pure survey. A cross-sectional approach was used to collect data regarding the

enjoyment quality (aesthetic design, playfulness, personalization) of online shopping sites and

their effect on customer perceived hedonic value and customer relationship outcomes.

The respondents were asked to recall their last online shopping experience or a

familiar online shopping site and base their responses on that experience. This approach

enabled the respondents to relate the questions to a realistic scenario. First, the questionnaire addressed the respondents’ descriptive information. Afterward, questions related to the

enjoyment quality of the online shopping site and hedonic value were posed, followed by questions about respondent’s satisfaction with the online shopping experience and intention to

continue the relationship with the online shopping provider in the future. The chosen language

for the questionnaire was English.

The questionnaire was designed in Qualtrics and distributed online as well as offline.

Prior to issuing the questionnaires, a representative group of ten respondents was asked to fill

out the survey and give feedback, small adjustments in the questionnaire were made

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They survey administration started on the 8th of November and was closed on 22nd of

November 2016. To perform descriptive statistics and statistical analyses, the Statistical

Software Package for Social Sciences (SPSS) was used.

3.4. Data analysis

In this study, all variables under investigation were checked for missing data. A frequency test

was run to examine if there were any errors in the data. There were no errors found. Then

cases with missing values were excluded listwise, meaning that only cases that had no missing

data in any variable were analyzed. As the study didn’t include counter-indicative items,

recoding was not applicable.

In the next step, descriptive statistics, skewness, kurtosis and normality tests were

performed. Out of the six variables playfulness, personalization, and hedonic value were

normally distributed. Aesthetic design (Skewness=-.882, Kurtosis=-1.018), customer

satisfaction (Skewness=-.688, Kurtosis=.749) and intention to repurchase (Skewness=-.596,

Kurtosis=.239) were moderately negatively skewed, meaning that the scores fall towards the

higher side of the scale and that there are fewer low scores. However, Tabanick and Fidel

(2001) state that with reasonably large samples (>200 cases) the risk of skewness and kurtosis

can be reduced. This study has a sample size of N=342. Therefore skewness and kurtosis

would not make a substantive difference in the analysis.

Furthermore, reliability checks were run for all items of the main variables. All six variables have a Cronbach’s α > .7, which indicates a high level of internal consistency. The

corrected item-total correlations indicate that all items have a good correlation with the total

score of their scale (>.30), except for item 1 of hedonic value (=.213). However, removing this item wouldn’t substantially improve Cronbach’s α of the hedonic value scale. Also, none

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Reliabilities, means, standard deviations and correlations of all variables are exhibited in

Table 1.

Before testing the hypotheses, a principal axis factoring analysis (PAF) was conducted

on the scales for enjoyment quality. The Kaiser–Meyer–Olkin measure verified the sampling

adequacy for the analysis, KMO = .788. Bartlett’s test of sphericity χ² (66) = 1050.029, p <

.001, indicated that correlations between items were sufficiently large for PAF. An initial

analysis was run to obtain eigenvalues for each component in the data. Three factors had

eigenvalues over Kaiser’s criterion of 1. In agreement with Kaiser's criterion, examination of

the scree plot revealed a leveling off after the third factor. Thus, three factors were retained

and rotated with a Varimax with Kaiser normalization rotation. Table 2 shows the factor

loadings after rotation. The items that cluster on the same factors suggest that factor 1

represents aesthetic design, factor 2 playfulness, and factor 3 personalization.

In order to test the proposed hypotheses, regression analyses were computed,

examining the direct relationships as well as mediation effects between the variables. The

direct effects, present in Hypothesis 1, 2 and 3, were examined through a hierarchical

regression for the dependent variables. The results are exhibited in Table 3. In step 1, the

control variables gender, age, education, and occupation were entered into the equitation. In

step 2, the independent variables and mediators, which were treated as independent variables

too, were entered into the model. For the hierarchical regression of customer loyalty,

customer satisfaction was also entered in step 2.

In order to test the mediation effects, as proposed in Hypothesis 4, 5 and 6, the Process

SPSS macro of Hayes (2012) was used. As mentioned earlier, the normality assumption of the

sample distribution can be considered questionable. Therefore, bootstrapping, a

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indirect effects. These confidence intervals are used, as opposed to regression coefficients,

because they adjust for bias and skewness of the data set. Confidence intervals were set on a

95% interval. Hayes (2012) recommendation to resample 5000 times, instead of the default of

1000 times, was applied. Process model 6 was used to analyze the multiple mediation effects.

The model was tested in parts, as Process enables to test the model with one independent

variable at a time. Therefore, the model was tested by running Process (Model 6) three times,

every time with another out of three independent variables (aesthetic design, playfulness,

personalization) and the other two as covariates. In all statistical procedures alpha levels of

.01 (**) and .05 (*) were used to indicate statistically significant effects. In the next chapter,

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4. Results

Below, first, the correlation matrix (Table 1) and the results of the exploratory factor analysis

(Table 2) will be discussed. Then, the results of the regression analyses will be outlined.

Direct relationships between the independent variables and customer relationship outcome

variables are examined (Table 3, 4). Subsequently, the results for the multiple mediation

effects (Table 5, 6, 7) will be presented.

4.1. Correlation Analysis

An overview of the descriptive statistics, correlations, and scale reliabilities are presented in

Table 3. A first observation derived from the table is that all three independent variables are

significantly correlated with both mediators and customer loyalty, measured by repurchase

intention. Aesthetic design has a positive and significant correlation with hedonic value

(r=.48, p<.01), customer satisfaction (r=.35, p<.01) and intention to repurchase (r=.31, p<.01).

Playfulness is positively and significantly related to hedonic value (r=.45, p<.01), customer

satisfaction (r=.24, p<.01) and intention to repurchase (r=.27, p<.01). The third independent

variable, personalization, is positively and significantly correlated with hedonic value (r=.20,

p<.01), customer satisfaction (r=.33, p<.01) and intention to repurchase (r=.26, p<.01). In all

three cases, correlations appeared to be stronger for either hedonic value or customer

satisfaction or both, which might indicate that the effect of the independent variables on

intention to repurchase is mediated through hedonic value and customer satisfaction (see

below for the formal test of mediation). Furthermore, the positive correlations that resemble

the direct relationship between the independent variables and hedonic value, customer

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Of the mediators, customer satisfaction showed a stronger correlation with the

intention to repurchase (r=.60, p<.01) than hedonic value (r=.32, p<.01). Moreover, hedonic

value is also positively and significantly related to customer satisfaction (r=.32, p<.01).

Regarding the control variables, gender positively and significantly correlated with

aesthetic design (r=.17, p<.01), playfulness (r=.13, p<.05) and hedonic value (r=.26, p<.01). It

is also negatively correlated with age (r=.27, p<.01). Age was significantly and positively

related to playfulness (r=.20, p<.01), education (r=.17, p<.01) and occupation (r=.29, p<.01)

and negatively correlated with aesthetic design (r=-.15, p<.05). Finally, education has a

positive and significant correlation with occupation (r=.22, p<.01).

To be able to distinguish between the variables of enjoyment quality, an exploratory

factor analysis was computed. The results are stated in Table 2. All questionnaire items

belonging to aesthetic design reported higher factor loadings on factor 1 than factor 2 or 3,

whereas the questionnaire items belonging to playfulness reported higher factor loadings on

factor 2 than the others. This also applies for personalization which loads highly on factor 3.

These results provided support for the assumption that aesthetic design, playfulness, and

personalization are three separate constructs as mentioned in the literature (Shobeiri et al.,

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Table 1 Means, Standard deviations, Correlations and Reliabilities Variables Number of Items M SD 1 2 3 4 5 6 7 8 9 10 1. Gender ₁ 1.52 .50 - 2. Age ₁ 2.57 .62 -.27** - 3. Education ₁ 2.72 .69 .06 .17** - 4. Occupation ₁ 1.63 .81 -1.10 .29** .22** - 5. Aesthetic Design ₃ 5.70 .85 .17** -.15* .06 .06 (.85) 6. Playfulness ₅ 4.32 1.01 .13* .20** .03 -.04 .49** (.76) 7. Personalization ₅ 4.57 1.05 .11 .04 .08 .04 .25** .41** (.77) 8. Hedonic Value ₄ 4.54 1.18 .26** -.11 .07 .01 .48** .45** .20** (.73) 9. Customer Satisfaction ₄ 5.77 .77 .05 .06 .06 .05 .35** .24** .33** .32** (.71) 10. Intention to repurchase ₅ 5.62 .91 .00 .09 .09 .07 .31** .27** .26** .32** .60** (.76)

Note: N=245, Reliabilities are reported along the diagonal.

* Correlation is significant at the .05 level (one-tailed). ** Correlation is significant at the .01 level (one-tailed).

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Table 2 Exploratory Factor Analysis for Enjoyment Quality- Rotated Factor Matrix

Questionnaire Item Factor 1 Factor 2 Factor 3

Aesthetic Design Item 1 .807 .116 .049 Item 2 .825 .054 .126 Item 3 .753 .155 .118 Playfulness Item 1 .381 .576 .099 Item 2 .396 .539 .198 Item 3 .011 .478 .178 Item 4 .300 .591 .189 Personalization Item 1 .051 .144 .424 Item 2 .042 .237 .628 Item 3 .121 .270 .575 Item 4 .027 .129 .701 Item 5 .213 -.031 .745

Note: N=245, Extraction Method: Principal Axis Factoring with a fixed number of factors. Rotation Method: Variance-maximizing (varimax) with Kaiser

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4.2. Direct Effects

In the first Hypothesis, the direct effects of enjoyment quality on customer loyalty were

addressed. Hierarchical multiple regression was performed to investigate the ability of the

independent variables and mediators to predict levels of customer loyalty, after controlling for

gender, age, education, and occupation. The results are exhibited in Table 3.

In the first step of the hierarchical regression, four predictors were entered: gender,

age, education, and occupation. This model was not statistically significant F (4, 239) = .913;

p<.05. This indicated that these predictors did not significantly explain the variance in

intention to repurchase. When introducing aesthetic design, playfulness, personalization and

the mediators at Step 2 the total variance explained by the model as a whole was 40% F(9,

234)=17.060; p<.01. The introduction of hedonic value and customer satisfaction, when

regarded as independent variables, and the enjoyment quality variables explained additional

38% in intention to repurchase, after controlling for gender, age, education, and occupation

(R² Change=.38; F(5, 234)=29.542;p<.01).

In the final model, one out of nine predictor variables were statistically significant.

The only variable having a direct and significant effect on repurchase intention is customer

satisfaction recording a Beta value of β=.51, p<.01. This means if customer satisfaction

increases for one, intention to repurchase will increase for 0.51. Therefore Hypothesis 3 is

supported. However, the results suggest that there is no direct effect of aesthetic design,

playfulness, and personalization on customer loyalty, measured by repurchase intention.

Therefore, Hypothesis 1 is rejected.

To test the second Hypothesis, the same procedure as described above was applied to

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were entered. This model was not statistically significant F (4, 239) = .691; p<.05. Meaning

that these predictors did not significantly explain the variance in customer satisfaction. This

changed when introducing the independent variables and hedonic value, treated as an

independent variable as well, into the model (F (8, 234) = 8.11; p<.0). After that, the total

variance explained by the model as a whole was 22%. This means that the introduction of the

independent variables and hedonic value at step 2 explained additional 21% in customer

satisfaction, after controlling for gender, age, education, and occupation (R² Change=.21; F(4,

235)=15.36;p<.01). Furthermore, three out of eight predictors were statistically significant.

The variables that appear to have a significantly positive effect on customer satisfaction

include aesthetic design (β=.23, p<.01), personalization (β=.25, p<.01) and hedonic value

(β=.19, <.01). Therefore Hypothesis 2a and 2c are supported whereas Hypothesis 2b has to be

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Table 3 Regression Analysis for Intention to repurchase

Variable Intention to Repurchase

R R² R² Change B SE β T Step 1 .12 .015 Gender .04 .12 .02 .31 Age .11 .10 .08 1.08 Education .09 .09 .07 .99 Occupation .04 .08 .03 .50 Step 2 .63 .40** .38** Gender -.10 .10 -.05 -.99 Age .12 .08 .07 1.29 Education .04 .07 .03 .54 Occupation .01 .06 .01 .14 Aesthetic Design .05 .07 .05 .72 Playfulness .08 .06 .10 1.38 Personalization .02 .05 .02 .37 Hedonic Value .09 .05 .11 1.80 Customer Satisfaction .60 .07 .51** 8.92

Note: N=245, Statistical significance: *p <.05; **p <.01;

Table 4 Regression Analysis for Customer Satisfaction

Variable Customer Satisfaction

R R² R² Change B SE β T Step 1 .11 .01 Gender .04 .10 .06 .95 Age .11 .09 .06 .92 Education .09 .08 .04 .64 Occupation .04 .07 .03 .45 Step 2 .47 .22** .21** Gender -.10 .09 -.04 -.61 Age .12 .08 .09 1.42 Education .01 .07 .00 .07 Occupation .00 .06 .00 -.07 Aesthetic Design .21 .07 .23** 3.18 Playfulness -.03 .06 -.04 -.48 Personalization .18 .05 .25** 3.85 Hedonic Value .13 .05 .19** 2.76

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4.3. Multiple Mediation Effects

As shown in previous sections this study fails to find direct effects of enjoyment quality

variables on customer loyalty. However, there is a relatively broad consensus among

statisticians that there can be a mediated effect between variables even if the total effect is

non-significant (Hayes, 2009). This means that the lack of direct effects of aesthetic design,

playfulness, and personalization on customer loyalty is not a demonstration of the lack of

mediated effects. Therefore this study continued with the analysis of mediation effects in the

relationship between enjoyment quality and customer loyalty.

For the analysis of the multiple mediation effects, the Process macro of Hayes (2012) was

used. As mentioned earlier, the model was tested in parts, as Process enables to test the model

with one independent variable at a time. Therefore, the model was tested by running Process

three times, every time with another out of three independent variables (aesthetic design,

playfulness, and personalization) and the other two as covariates. For this purpose, the

statistical model 6 was used, as it allows to add mediators in sequence. The results for each

independent variable are discussed in the following sections.

Aesthetic Design

The analysis for aesthetic design shows that there is no direct effect of aesthetic design on intention to repurchase, c’=.044, t (244) =.6515, p>0.05. Furthermore, three indirect effects of

aesthetic design on intention to repurchase were examined. The first one is the indirect effect

of aesthetic design on repurchase intention through customer perceived hedonic value,

independently of customer satisfaction. Although there is a significant positive effect of

aesthetic design on hedonic value (a1=.477, p<.001), there is no effect of hedonic value on

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The second indirect effect is the effect of aesthetic design on intention to repurchase,

through hedonic value and customer satisfaction in serial. An online shopping site with a high

level of aesthetic design leads to a significantly higher level of customer perceived hedonic

value, which in turn positively influences customer satisfaction (a3=.120, p<.01) and this

increase in customer satisfaction is further translated in considering repurchasing from the

online shopping site (b2=.628, p<.01). This specific indirect effect is significantly positive

because the bootstrap confidence interval is entirely above zero (indirect effect=.0360,

SE=.0191, CI: .0066 to .0836).

The third indirect effect indicates the specific effect of aesthetic design on repurchase

intention, through customer satisfaction. Customers of online shopping sites with a high level

of aesthetic design experience significantly higher levels of customer satisfaction (a2=.202,

p<.01), which in turn was associated with higher intention to repurchase (b2=.628, p<.01),

regardless of customer perceived hedonic value. This specific indirect effect is significantly

positive (indirect effect=.1267, SE=.0424, CI: .0432 to .2108).

To sum it up, there are two indirect effects of aesthetic design on intention to repurchase.

The first one is the effect of aesthetic design on intention to repurchase mediated by customer

satisfaction. This means that aesthetic design only influences customer satisfaction which

then, in turn, increases intention to repurchase. The second effect is the multiple mediated

effect through hedonic value and customer satisfaction in serial. As a result, Hypothesis 4a

and 6a are supported whereas Hypothesis 5a is rejected. The results are summarized in Table

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Table 4 Multiple Mediation Effects for Aesthetic Design

Note: N=245

Consequent

M (Hedonic Value) M (Customer Satisfaction) Y (Intention to Repurchase)

Antecedent Coeff. SE p Coeff. SE p Coeff. SE p

X (Aesthetic design) a1 .477 .086 <.01 a2 .202 .062 .0015 c’ .0436 .067 .515 M (Hedonic Value) - - - a3 .120 .044 .007 b1 .083 .047 .076 M (Customer Satisfaction) _- _- _- _- _- _- _{b2 .628} _.067 _<.0001 constant im1 .384 .465 .409 im2 3.365 .322 <..01 iY 1.019 .404 .012 R2= .297 R2= .215 R2= .391 F(3,246)=34.617, p<.0001 F(4,245)=16.733, p=.0001 F(5,244)=31.318, p=.0001

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Playfulness

The analysis for playfulness shows that there is no direct effect of playfulness on intention to repurchase, c’=.055, t (244) =.9568, p>0.05. Moreover, three indirect effects of playfulness on

intention to repurchase were examined. The first one is the indirect effect of playfulness on

repurchase intention through customer perceived hedonic value, independently of customer

satisfaction. Although there is a significant positive effect of playfulness on hedonic value

(a1=.343, p<.001), there is no effect of hedonic value on intention to repurchase (b1=.083,

p>0.05), excluding this particular indirect effect.

The second indirect effect is the effect of playfulness on intention to repurchase, through

hedonic value and customer satisfaction in serial. As in the case of aesthetic design, an online

shopping site with a high level of playfulness leads to a significantly higher level of customer

perceived hedonic value, which in turn positively influences customer satisfaction (a3=.120,

p<.01) and this increase in customer satisfaction is further translated in considering

repurchasing from the online shopping site (b2=.628, p<.01). This particular indirect effect is

significantly positive because the bootstrap confidence interval is entirely above zero (indirect

effect=.0258, SE=.0174, CI: .0035 to .0633).

The third indirect effect is the specific effect of playfulness on repurchase intention,

through customer satisfaction. The analysis shows that there is no significant and positive

effect of playfulness on customer satisfaction (a2=-.046, p>.05), whereas customer

satisfaction has indeed a positive and significant effect on intention to repurchase (b2=.628,

p<0.01). This specific indirect is therefore excluded.

In conclusion, there only exists a multiple mediated effect of playfulness on intention to

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mediation of hedonic value and customer satisfaction in sequence and thereby supporting

The effect of a website’s enjoyment quality on customer perceived hedonic value and customer relationship outcomes in a B2C e-commerce context