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Moderating Effects of Preference Stability and
Cultural Context on Customization-Satisfaction
Relationship
Abstract: The current paper reveals that preference stability does not have any moderating effect on customization-satisfaction relationship, while the cultural context of individualism or collectivism has significant moderating effect on the relationship. It also provides how individualistic culture and collectivistic culture impact consumers’ choices and preferences in the customization process.
MSc Business Studies Thesis (Marketing track) Drs. Frank Slisser
Student name: Xi Chen Student number: 10004195
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Table of Contents
I. Introduction ... 2
II. Literature Review ... 6
Product customization and customer satisfaction ... 6
Consumers’ preference stability ... 10
Consumers’ cultural context of individualism or collectivism ... 13
III. Data Collection ... 2
Description of sample and procedures ... 17
Description of research instruments ... 18
IV. Data Analysis and Results ... 20
Data cleaning and dealing with missing values. ... 20
Recording counter-indicative items. ... 20
Computing reliability ... 20
Descriptive analysis ... 21
Hypothesis Testing... 22
V. Discussion ... 25
VI. Implications ... 33
Implications for marketing theory ... 33
Implications for marketing practice ... 34
VII. Limitations and Future Research ... 35
VIII. Appemdix ... 37
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I. Introductio
n
Corporations are deploying diverse marketing strategies and tactics to create customer
satisfaction as customer satisfaction is a critical source of customer loyalty and competitive
advantages (Woodruff, 1997; Coelho and Henseler, 2009). Kotler (2000) emphasizes the
importance of individual marketing and new management approaches have been introduced to serve the wants of individual customers better. Individual marketing or one-to-one marketing has increasingly attracted a lot of attention of scholars and marketers for
generating customer satisfaction at the individual level (Simonson, 2005; Ansari and Mela,
2003).
One of the most prevalent strategies is customization in individual marketing and customer relationship management (Gilmore and Pine 1997; Peppers, Rogers, and Dorf 1999). The concept of product customization is defined as a product is created and tailored to meet
individual customers’ specific preferences and needs (Coelho and Henseler, 2009; Anderson
et al., 1997). Advances in internet technology and information innovation enable corporations
can customize their offerings according to specific needs and preferences of customers in
order to increase customer satisfaction at the individual level (Syam and Kumar, 2006; Guo,
2013). In many industries, firms have been adopted product customization to satisfy
individual customers in their customer relationship management (Freeland, 2003; Kara and
Kaynak, 1997; Lemon et al., 2002). Generating customer satisfaction at an individual level by
product customization is a crucial concern for companies to succeed in the current fierce
competition (Huffman and Kahn, 1998; Gardyn, 2001).
Many firms in diverse industries are adopting product customization programs for increasing
3 1998; Freeland, 2003; Lemon et al., 2002), such as Dell, Nestle and Nike (Franke and
Schreier, 2008). Typical customized products comprise computers customized with different
combinations of software and hardware; clothes, bags and gloves can be customized in
colors, features, material and other similar options related to product attributes. For instance,
customers can choose a specific size or length that fits for their fingers in the process of
purchasing gloves, or decide where they want to have pockets onto their new coats (Marilyn,
Mohammad, Wen Jang and Lawrence, 2008).
The positive relationship between product customization and customer satisfaction in
customer relationship management is underpinned by the principle that customers prefer
products which are tailored to their own unique needs and expectations (Seybold, 2001).
Product customization will generate customer satisfaction as the company can deliver the
product customized in the way the consumers want (Silveria et al, 2001, Srinivasan et al,
2002 and Miceli et al, 2007). The paper of Franke, Schreier and Kaiser (2010) has concluded
that individuals prefer customized products much more due to the greater preference fit with
their unique preference in this case. Customers are much more satisfied with customized
products not only due to the superior preference fit can be achieved, but also they could have
the sense of accomplishment when they co-create the product in the customizing process
(Moreau, 2011).
Given the understanding of the positive relationship between product customization and
customer satisfaction, little research has been done related to the factors that have moderating
effects on the relationship in academia. The paper of Lee, Lee and Lee (2012) depicts
consumer expertise is moderating the positive effects of product customization on customer
satisfaction based on the research in the industry of fashion items. They suggest customer
4 customize. Chang, Chen and Huang (2009) also confirm that the customization-satisfaction is
significant weaken when customers is lacking of expertise, and enhanced when customers
have sufficient expertise in the customization process.
Previous literature proposed two other possible factors that may moderate the effect of
product customization on customer satisfaction. One possible moderator is preference
stability suggested by several scholars. Preference stability is defined as the consistency of
the choices that one consumer objectively makes among available options with various
attribute values in one product segment (Hoeffler and Ariely, 1999; Simonson, 2005; Amir
and Levav, 2008). Shen and Ball (2011) suggest preference stability could be a moderator in
customization-satisfaction relationship and further empirical research is needed to test the
moderating effect of preference stability. Another paper explains preference stability is a
moderator in the relationship of online customized recommendation and customer satisfaction
(Lee, Lee and Lee, 2012). In their paper, they define the online customized recommendations
as the recommendation services provided by companies to tailor their product
recommendations to each individual customer’s preferences based on available customer
information. Customers are responding more actively to the recommended products if the
customized recommendations are tailored to their specific interests and preferences. They
have concluded that strong preference stability will reinforce the effects of customization.
Furthermore, they suggest preference stability could also moderate the effect of customizing
actual products on customer satisfaction.
Moreover, many marketers and researchers have suggested the level of customer satisfaction
may vary dramatically across cultures, and what the possible moderating effect of customers’
cultural context of individualism-collectivism on customization-satisfaction relationship is
5 Valenzuela, A. Dhar, R. and Zettelmeyer, F. 2009; Kramer, Spolter-Weisfeld, and Thakkar,
2006). Individualism-collectivism is one of the most widely researched cultural concepts
derived from Hofstede (1980), which interprets how individuals consider the importance of
their own goals and preferences compared to the importance of the goals and preferences of a
relevant group, such as family, friends and colleagues. The cultural dimension of
individual-collectivism also has important effects on how individuals perceive themselves, others, the
relevance and interdependence between members in the society (Kramer, Spolter-Weisfeld,
and Thakkar, 2006). Consumers’ context of individualistic or collectivistic culture may have
significant influence on the customization satisfaction generated from product customization
programs. No research has been conducted in a collective culture and an individualistic
culture at the same time to understand whether culture context has a moderating effect in
customization-satisfaction relationship. Thus, empirical research is needed to test what the
moderating effect of consumers’ cultural context on the relationship between product
customization and customer satisfaction.
Given the prevalence of product customization, the research gap in the existing literature is
whether preference stability and the cultural context of individualism or collectivism have a
significant moderating effect on the relationship between product customization and customer
satisfaction. The present paper is aiming to filling the gap by providing empirical research to
test if preference stability and cultural context have moderating effects on the
customization-satisfaction relationship.
Research Question:
How preference stability, and cultural context of individualism or collectivism, influence the relationship between customization and customer satisfaction?
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II. Literature Review
Product customization and customer satisfaction
Generally, customization can be categorized into two major types based on the nature of the
company’s offerings and the industry as product customization and service customization
(Simonson, 2005; Gorden et al., 1998). Customization is considered more important for
service firms in the existing literature due to the service industries have more requirements to
satisfy individual customers’ preferences and needs, as well as they have more abilities and
chances to customize the service for their customers (Sheth et al, 2000; Simonson, 2005;
Lemon, White and Winer, 2002). Therefore, much marketing research has been conducted in
the field of service customization, while marketing research of product customization is much
less. For instance, various scholars has investigated what the outcomes and effects of service
customization (Bardakci and Whitelock, 2003; Tam and Ho, 2005; Ostram and Iacobucci,
1995), and what the moderators in the relationship between service customization and
customer loyalty (Coelho and Henseler, 2009; Simonson, 2005; Li, Kalyanaraman and Du,
2011; etc). The concept of product customization has emerged since the late 1980s and
become one of the most common marketing strategies for companies in product industries to
differentiate their products in the competition (Silveira, Borenstein and Fogliatto, 2001). The
approach of mass customization has been adopted by many product firms, which will still be
the trend in the future (Gilmour and Pine, 1997; Graman and Bukovinsky, 2005; Rust and
Lemon, 2001).
In the past, mass production was pursued in many product industries to take the cost
advantages of economies of scale (Ahlstrom and Westbrook, 1999). However, the
shortcoming of mass production has been recognized by researchers and marketers for a long
7 1995; Jelinek and Goldhar, 1983). The prevalence of product customization is mainly driven
by three driving forces indicated by previous scholars.
The first is the market of many product categories has become extremely competitive with
decreasing profit margins (Novshek and Thoman, 2006). Mass market is breaking down into
fragmented market segments and the general product life cycles are becoming much shorter
(Hart, 1994). Researchers and marketers are striving for new marketing approaches to
differentiate their products in the competition to increase customer satisfaction (Graman and
Bukovinsky, 2005).
Second, consumers are increasingly demanding the uniqueness and variety of products (Pine,
1993). The heterogeneous customer needs of many industries drive the mass market into
fragmented market segments, even to the individual level, where mass production cannot
satisfy customers with specific needs and wants (Hayes and Pisano, 1994). In this case, new
marketing strategies have been developed in customer relationship management as individual
marketing or one-to-one marketing in the last three decades (Peters, 1992).
Lastly, the advanced information technologies and web tools enable companies to customize
goods based on individual customer information at reasonable costs (Hart, 1994). Database
management accelerates the speed of collecting data about individual preferences and needs
from customers, and digital technologies increase the flexibility and variety of the production
(Parvatiyar and Sheth, 2001; Gilmour and Pine, 1997). Pine, Peppers and Rogers (1995) suggest that “Customers want exactly what they want and technology now makes it possible for
companies to give it to them”. Companies could use information technology and more
flexible operating processes to generate customer satisfaction at the individual level by
fulfilling specific customer needs and wants, such as the need of particular product attributes
8 Rust and Chung (2006) asserts product customization determines the customer satisfaction in
customer relationships. Product customization is one of the vital strategies in one-to-one
marketing and customer relationship management as it generates customer satisfaction at the
individual level both for the process and final products (Bharadwaj, Naylor and Hofstede,
2009). Companies are building the customized relationships with their customers in the
customization process, in which consumers form their attitude toward the product
customization and determine the degree of their satisfaction consequently (Simonson, 2005).
Generally, customer satisfaction is created when the customers’ evaluation and judgment of
pleasurable fulfillment from consuming a product is matching their expectations and
preferences (Akubakar, Mokhtar and Abdullateef, 2013).
According to Hunt, Radford and Evans (2013), product customization programs are filling
the gap between the individualized products consumers want and the mass standardized
products in the market. Customized products have a better fit inherently between customer’s
specific preferences and needs than non-customized products (Simonson, 2005; Franke and
Schreier, 2008). Customization programs involve more customer participation in design,
production of products, which is helpful for companies to gain more knowledge and
understanding of the customers’ preferences and tastes (Gilmore and Pine, 1997; Hanson,
2000, Simonson, 2005). Since customer participation can provide more input in the process
of customizing products, chances are better that the final product will better fit the customer’s
preferences (Da Silveira et al., 2001). For example, Nike and Levi are creating customer
satisfaction by achieving a closer fit between their products and individual consumers’
preferences with involving customer participation and engagement in their various product
9 Furthermore, customer are satisfied with customized products not only due to a better fit
between their special preferences and needs, but also the product uniqueness provided by the
product customization for each individual customer (Schreier, 2006; Shen and Ball, 2006;
Simonson, 2005). Consumers have a need to express uniqueness through products to develop
their personal and social images (Tian et al., 2001). The product uniqueness facilitate
differentiation from other customers and their similar products through the product
customization (Fiore et al.,2004; Lynn and Harris, 1997; Micheal et al, 2006; Simonson,
2005). Customized products can deliver more symbolic values to customers and better satisfy
customer needs, such as sense of uniqueness related to the expression of beliefs and
demonstration of social status (Allen and Ng, 1999; Hirschman and Holbrook; 1982). The
uniqueness of customized products enhance the customer satisfaction of the fit between the
customer’s preference and the product attributes (Franke and Schreier, 2008).
On the other hand, customers are much more satisfied not only due to the superior preference
fit and the uniqueness of the products, but also they could have the sense of accomplishment
in the process of participating the product customization (Moreau, 2011). Customized
products can better enhance the self-congruity between a product and customer self-image,
which may result in higher customer satisfaction due to the opportunity to reflect personal
image and style (Chia-Chi, Hui-Yun and I-Chiang, 2009; Fiore, Lee and Kunz, 2004,).
Franke, Schreier and Kaiser (2010) have the similar finding that the customer satisfaction is
increased significantly as consumers have the sense of accomplishment.
However, the level of customer satisfaction may vary when considering the differences of
customer characteristics and cultural context. The empirical research related to which factors
are moderating the effect of product customization on customer satisfaction has been largely
10 moderating effect of two possible moderators in this relationship, which are identified based
on the literature review.
Consumers’ preference stability
Researchers have emphasized consumers’ preference is one of the determinants of customer
satisfaction and their purchase choices (Payne, Bettman and Johnson, 1993). Preferences are
subjective values that consumers develop or uncover in their decision-making process (Dhar
and Novemsky, 2008). In individual marketing and customer relationship management, one
underlying principle is the higher the fit between one customer’s preferences and product
attributes, the more the customer satisfaction (Franke and Schreier, 2008).
There is ample evidence that implies preferences are often stable and preference stability
should be paid more attention in marketing research. Preference stability refers to the choice
consistency among options with different attribute values in the same product category
(Hoeffler and Ariely, 1999; Simonson, 2005; Amir and Levav, 2008). It implies many cases that consumers show same or similar subjective values across different choice settings
(Bettman, Luce and Payne, 1988).
Preferences have been categorized into two major types as inherent preferences and
constructed preferences in the literature of marketing science (Amir and Levav, 2008,
Simonson, 2008). Simonson (2008) defined the concept of inherent preferences as stable
dispositions that one individual has to like or dislike an object or an attribute. Inherent
preferences are pre-existing preferences that exist before making the choice of available
options, which are not influenced by the choice context and product characteristics. For
instance, some consumers have strong preferences for dark chocolate than other types of
11 On the other hand, consumers also learn to construct new preferences or change their existing
preferences as they accumulate purchase experience (Bettman, Luce and Payne, 1988). The
learning experience enable people receive feedback and reaction from external environment,
and then revise their preference structure in the next purchase. It may change previous
preference, but the repetition of purchases may also lead to stronger preference stability
(Hoeffler and Ariely, 1999). Because learning from feedback and experience require efforts
and time, people tend to choose things that are familiar and stick with the stable preferences
(Fischhoff et al., 1980).
Specifically, it assumes that the degree of preference stability differs from one customer to
another (Irwin & Naylor, 2009). Customers discover or develop preferences as they gain
experience in a product domain, Marketers can build a learning relationship with customers
and provide further recommendations and suggestions at the individual level (Peppers and
Rogers, 1997). Consumers’ specific preference patterns can be learned by marketers and
usefully applied to product customization (Simonson, 2005). However, not much research has
been done about how preference stability plays a role in the relationship between product
customization and customer satisfaction.
Lee, Lee and Lee (2012) test the moderating effect of preference stability in the relationship
of online recommendation customization and future commitment. They conclude that
customer commitment for future purchase is stronger for the consumers who have greater
stable preferences, and suggest preference stability may also influence the effect of real
customized products. Shen and Ball (2011) provide similar findings that preference stability
has moderating effect in the relationship between customized recommendation and customer
satisfaction in the context of e-commerce. The question of whether preference stability is also
12 It is assumed a superior fit between the customer’s preferences and the product attributes will
be achieved with the customers having stable preferences and clearly knows what they want
or do not want. The positive effect of product customization on customer satisfaction may be
maximized for those consumers.
Nevertheless, consumers do not always have a well-defined framework of preferences that
can be easily accessed from memory (Irwin & Naylor, 2009). These consumers can be
characterized as consumers having weak preference stability as their preferences are not very
consistent across different decision frames, tasks, and contexts (Kramer, 2007). The context
in which one customer forms his or her preference and interprets the preference decision may
be the dominant factor in customization, in some cases even regardless of the real value of
product attributes (Huber et al., 1982).
Since the preference choices of consumers who do not have stable preferences are mainly
determined by the context of the decision, they may change their preferredchoices frequently
in one product category when the context of preference choices is different in the
customization process. In this case, it is impossible for marketers to know all the information
of each consumer’s decision context. Specifically, Levin and Gaeth (1988) assert some
customers are relying on the framing of options such as how many options available or what
information they can obtain at a certain time. Moreover, Tversky, Sattath and Slovic indicate
(1988) the method of the purchase can also alter the preference choices of those customers.
One example in their paper is that some customers have different preference choices when
they purchase online and do not communicate with marketers face-to-face. Their preferences
are not always objectively associated with product attributes, the context of which consumers
make their preferences choices and decisions plays a dominant role in customization
13 When consumers’ preferences are unstable, they have difficulties to articulate their true
preferences and reflect it to the customized products (Chernev, Mick, and Johnson, 2003).
Marketers may fail to recognize and measure preferences the customer has in product
customization process, which are largely determined by the decision context and difficult for
marketers to learn and customize to. In this case, the chance that the fit of the customized
products and customer preferences can be achieved is very small. Thus, customers who have
unstable preferences are assumed much less satisfied with the customized product.
Hypothesis 1: The relationship between product customization and customer satisfaction in moderated by the customer’s preference stability. The higher the degree
of preference stability, the stronger the relationship between product customization
and customer satisfaction.
Consumers’ cultural context of individualism or collectivism
Culture influences how consumers construct their decisions and how they define their
relationships with the society and other members in the society (Li, Kalyanaraman and Du,
2011). A classic definition of culture from Kroeber and Kluckhohn (1952) is ‘consists of
explicit and implicit patterns of historically derived and selected ideas and their embodiment
in institutions, practices, and artifacts’. Although culture is interpreted from various
perspectives in the field of contemporary marketing research, a fundamental framework is the
cultural dimension of individualism-collectivism developed by Hofstede (1980).
Individualism-collectivism is one of the most influential cultural concepts (Hofstede, 1980),
which implies how individuals consider the importance of their own goals and preferences
compared to the importance of the goals and preferences of a relevant group, such as family,
14 effects on how individuals perceive themselves, others, the relevance and interdependence
between members in the society (Kramer, Spolter-Weisfeld, and Thakkar, 2006).
People in individualistic cultures are considered as more independent and autonomous, their
personal values and preferences are the priority over social values and group preferences. On
the other hand, one person in collectivistic culture defines himself or herself as an aspect of a
collective group, and group objectives are valued more significant than individual preferences
(Markus and Kitayama, 1991).
Typically, the culture of western countries are considered individualistic cultures, whereas
Eastern societies are considered collectivistic ones (Nisbett, 2003). Individualism and
collectivism have important influences on self-concept and relationships between members in
the society. Individualism implies feeling good about personal success and having many
unique and distinctive personal attitudes and opinions, while collectivists are happier by
developing good relationships with others and doing things in groups (Oyserman et al. 2002).
Specifically, customization assumes that consumers rely on their individual preferences when
making choices and will be more satisfied with the products that match their preferences most
closely. While most of the marketing research focuses on western individualistic society
(Lynch and Ariely 2000), the question is: can the success of tailoring product offers to
individual preferences based on western principles always hold for collectivism culture?
Thus, a cross-cultural research with involving both types of cultures is needed to answer the
question.
According to McCrae and Hofstede (2004), since the degree to which individuals want to
express their personality and uniqueness by customizing products may vary across cultures,
the level of customer satisfaction may vary dramatically when the cultural context of the
15 Individualistic cultures of western societies are more self-oriented addressing the values of
individuality and uniqueness, while collectivistic cultures such as China are more
group-oriented with the emphasizes of group connectedness and harmony (Hofstede, 1980; Nisbett,
2003). Thus, Consumers from individualistic cultures may perceive customized products to
be favorable because they view individuality and uniqueness much more important. It is
possible that people from collectivistic cultures, such as Chinese do not enjoy customized
products as much as people from individualistic cultures would. However, no available
research could be found to test the effects of product customization on customer satisfaction
with two groups of participants who have collectivistic cultural context and individualistic
cultural context respectively.
Furthermore, in individualism cultures, individuals tend to view their own personal
preferences and goals irrelevant to others’ preferences and opinions in the society, while the
collectivistic cultural emphasizes connectedness and interdependence between the relevant
social groups (Markus and Kitayanma, 1991). Consumers’ individual preferences are less
important than the preferences of their social group in the cultural context of collectivism,
they tend to make their decisions relying on the group preferences (Morris and Peng, 1994).
Since consumers in collectivistic culture always relate their personal preferences and choices
to collective preferences and social norms (Singelis, 1994; Kramer, Spolter-Weisfeld, and
Thakkar, 2006), they may rely on collective preferences to customize products for expressing
the interdependence and connectedness with others instead of relying on their personal
preferences. Kramer, Spolter, and Thakkar (2007) also argue they are more likely to make
choices based on other members’ expectations and group preferences to express the
interdependence and connectedness. In this case, they are assumed to have less customer
16 product customization and their actual expectations and preferences. Based on the discussion
above, two hypothesis are developed as the following:
Hypothesis 2: The relationship between product customization and customer satisfaction is moderated by the customer’s culture context. The higher the degree of
individualism, the stronger the relationship between product customization and
customer satisfaction; the higher the degree of collectivism, the weaker the
relationship between product customization and customer satisfaction.
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III. Data Collection
Description of sample and procedures
The samples in the current research are selected out of the customers who have experience of
product experience. Since it is difficult to get the full list of all the customers who have
purchased customized products, convenience sampling is used as the non-probability
sampling technique of the research to collect data. Before customers could participate the
research, they are asked if they have had the experience of product customization by an
invitation letter. The survey will be only delivered to the customers who have experience of
product customization.
The population in the research is not limited in terms of age, gender or occupation as long as
individuals are independent consumers who can make purchase decisions and participate in
the customization process. Therefore, the common control variables, such as age, gender and
occupation are not relevant to the current research. However, the research needs participants
have diverse cultural background of individualism and collectivism in order to test the
moderating effects of cultural contexts. Thus, samples are controlled as selecting from Dutch
customers who have typical individualistic cultural context and Chinese customers who have
typical collectivistic cultural context in order to test H2. Dutch participants are Dutch
students from the University of Amsterdam, and Dutch customers in several shops at
Amsterdam who are willing to complete the questionnaire. Even though doing the research
only among students is easier for data collection, it will limit the generalizability of research
results and implications. Thereby the involvement of customers who are not students is very
important.
18 participants. Even though Chinese are generally considered as collectivists and Dutch are
generally considered as individualists, the degree of individualism or collectivism varies
among individuals. Therefore, the degree of the individualism or collectivism is measured for
each participant. Furthermore, customers who can participate in product customization and
make purchase decision are not limited in terms of age, occupations or gender.
Self-administered questionnaires (See Appendix) will be used to collect data from consumers
who have experiences product customization, such as purchasing customized T-shirt,
customized laptop or customized hand bags. As the response rate of this research is expected
between 69% and 87% based upon previous research (Miles, Miles and Cannon, 2012; Sun,
Hsu and Wang, 2012), around 200 questionnaires are sent either in digital version through
internet or paper version hand-by-hand to participants. The data and information of customers
who participate in the research are confidential and anonymous, and will only be used in this
research. The research findings will be sent to participants if they are interested in the results.
Description of research instruments
The dependent variable is customer satisfaction and the independent variable is customization
in the current research. Preference stability and the cultural context of individualism or
collectivism are the two hypothetical moderators that have effects on the positive relationship
between the independent variable and the dependent variable in this case. The measurement
items for each construct are adopted from previous literature and adjusted to fit the context of
product customization, which are most widely used measurement for each concept in existing
literature. The cronbach’s alpha levels of all the measures for each variable are higher than
0.7, which indicates a high level of reliability.
19 measurement items for customization are adopted from previous research (Coelho and
Henseler, 2009; Fornell et al., 1996; Ball et al., 2006), which are “The customization offers
me products that satisfy my specific needs”, “The customization offers products that I
couldn’t find in another company”, and “If I changed between customizations I wouldn’t
obtain products as customized as I have now”. The items are rated on a scale from 1
representing the lowest level (totally disagree) to 7 representing the highest level (totally
agree).
The six questionnaire items for customer satisfaction (α = 0.89) are adopted from previous literature and adjusted to fit in the current research in the market of customized products
(Armstrong and Seng, 2000; Bennet and Rundle-Thiele, 2004; Han and Hyun, 2012; Liverin
and Liljander, 2006;). Two examples of the items are “The customized product meets my
expectations and needs”, “I am completely happy in the process of the customization”. All
the six measurement items are based on a seven-point Likert-type scale from 1 (totally
disagree) to 7 (totally agree).
Consumers’ preference stability (α = 0.73) is measured by a six-item scale (Shen and Ball,
2009; Shen and Ball, 2011). Two examples of the measurement items are “The customization
I prefer fit some sort of pattern” and “It is often difficult to predict which customization I will
really like and which I will not”. The measurement scales are using a seven-point format
from 1 (totally disagree) to 7 (totally agree).
The cultural context of individualism or collectivism (α = 0.77) is measured by five measurement items derived from Kramer, Spolter-Weisfeld and Thakkar (2006), and
Clugston, Howell and Dorfman (2000), such as “I customized the product to express my
20 individual preferences”. All the five measurement items are based on a seven-point
Likert-type scale from 1 (totally disagree) to 7 (totally agree).
IV. Data analysis and Results
Quantitative approach is adopted as the data analysis technique in this research. SPSS software package is used to test the moderating effects of the two factors, preference stability and culture context. All the data has been entered in the software manually before the analysis.
Data cleaning and dealing with missing values.
The first step is to check if there is any missing data of all the variables. Incomplete
questionnaires with missing values are not considered valid data that can be used. After that,
the data is manually entered in SPSS and checked again to ensure no missing data exists. The
“frequencies” command is used in the SPSS analysis to check the number of missing values
in the output. The number is 0 (See Frequency Table in Appendix), which indicates no
missing data exist and all the data is considered as valid.
Recording counter-indicative items.
6 variables are counter-indicative items, 3 from the construct “Preference stability” and 2
from the construct “Cultural context”. As the counter-indicative items are the items
representing a low level of the construct being measured, the 6 items are recoded in order to
analyze it in an indiscriminate way. The old values of each item are changed into new values
as (1=7), (2=6), (3=5), (4=4), (5=3), (6=2), (7=1).
Computing reliability
Even though previous studies provide the reliability of the four constructs, the reliability
index of the four constructs could be different in this particular research. Thereby the
reliability analysis for all the variables is necessarily to repeat, in order to understand how
21 Cronbach’s alpha of the construct “Customization” (3 items) is .975, the item total correlation
is above .93, and the Cronbach’s alpha if item deleted is above .94.
Cronbach’s alpha of the construct “Customer satisfaction” (6 items) is .976, the item total
correlation is above .89, and the Cronbach’s alpha if item deleted is above .96.
Cronbach’s alpha of the construct “Preference stability (6 items) is .985, the item total
correlation is above .95, and the Cronbach’s alpha if item deleted is above .96.
Cronbach’s alpha of the construct “Cultural context” (5 items) is .979, the item total
correlation is above .94, and the Cronbach’s alpha if item deleted is above .96.
Descriptive analysis
A full correlation matrix is formed in EXCEL based on the analysis results in the output of
SPSS software, including means, standard deviations, and reliabilities on the diagonal.
Table 1: Means, Standard Deviations, Correlations
Variables M SD 1 2 3 4
1. Customization 4.9313 1.45757 0.975
2. Customer satisfaction 5.1813 1.11096 0.984 0.976
3. Preference stability 3.8115 0.16732 0.332 0.317 0.985
4. Cultural context 3.5488 0.51798 0.772 0.759 0.473 0.979
Reliabilities are reported along the diagonal.
Correlation is significant at the 0.01 level (2-tailed).
According to the reliability analysis, the Cronbach’s alpha for all the constructs is larger than
.97, the item total correlation for all the constructs is greater than 0.89, and the Cronbach’s
alpha if item deleted for all the constructs is greater than 0.94. All the data in the research is
22 The correlation of customization and customer satisfaction is extremely high (0.984), which
is consistent with the strong relationship between customization and customer satisfaction
provided by previous studies. The two hypothetical moderators are not correlated to each
other as the correlation between them is low (0.473), which indicates the two factors are
independent variables and the current research is valid.
The hypothetical moderator “cultural context” is highly correlated to both dependent variable
“customization” (0.772) and independent variable “customer satisfaction” (0.759). It implies
the possibility that cultural context has moderating effects on customization-satisfaction
relationship is very high. However, the other hypothetical moderator “preference stability”
does not have strong correlation with either customization (0.332) or customer satisfaction
(0.317), which means the tendency to reject H1 is relatively high.
Hypothesis Testing
Regression analysis is applied in SPSS software to test moderating effects of two
hypothetical moderators.
In order to analyse the moderation, independent variable and two hypothetical moderators
should be mean-centred. Thereby three new variables “CusTAT_center”, “PrsTAT_center”,
“CucTAT_center” are computed as the variables that are mean-cantered for regression
analysis. Moreover, two interaction variables are computed to test the interaction effects of
each hypothetical moderator and the independent variable. InterV1 is computed by
“Customization * Preference stability”, whereas “InterV2” is computed by “Customization *
Cultural Context”.
Two models of hierarchical regression for testing the moderating effects of “preference
stability” are run as:
- Model 1: CusTAT_center, PrsTAT_center
23 Two models of hierarchical regression for testing the moderating effects of “Cultural context”
are run as:
- Model 1: CusTAT_center , CucTAT_center
- Model 2: CusTAT_center , CucTAT_center , InterV2
The first model is testing the direct effects of the two hypothetical moderators on customer
satisfaction, and the second model is testing the total effects between constructs. The total
effects in the second model for each hypothetical moderator consists of direct effects and
indirect effects, whereas indirect effects is the interaction effects of customization and
preference stability, the interaction effects of customization and culture context respectively.
The results of regression analysis are shown in Table 2 and Table 3.
Table 2: Summary of Hierarchical Regression Analysis for “Preference stability”.
Variable B SEB Β Model 1 CusTAT_center 0.753 0.011 0.000 PrsTAT_center -0.075 0.100 0.452 Model 2 CusTAT_center 0.752 0.012 0.000 PrsTAT_center -0.070 0.100 0.488 InterV1 0.035 0.069 0.613
According to the results of the regression analysis, the direct effect of preference stability on
customization-satisfaction relationship in the first model is not statistically significant as β (0.452) > 0.05. The results of the second model consistent with the insignificant impact of
preference stability, that either the direct impact (0.488) or the indirect impact (0.613) is
insignificant in the relationship. Thus, H1 is rejected and the conclusion is consumers’
24 customer satisfaction. The degree of customer satisfaction generated from product
customization is not influenced by the consumer’s preference stability.
Table 3: Summary of Hierarchical Regression Analysis for “Cultural context”.
Variable B SEB Β Model 1 CusTAT_center 0.751 0.017 0.000 CusTAT_center -0.004 0.048 0.036 Model 2 CusTAT_center 0.794 0.020 0.000 CucTAT_center -0.151 0.062 0.016 InterV2 0.141 0.040 0.001
The results indicate that the second hypothetical moderator has significant moderating effects
on the customization-satisfaction relationship. The direct effect is significant proved by the
both models as β (0.036) < 0.05 in the first model and β (0.016) < 0.05 in the second model. The indirect interaction effect is also statistically significant as 0.001 in the second model.
Therefore, H2 is confirmed and we can conclude the degree of consumers’ individualism or
collectivism is the moderator of the relationship between product customization and customer
satisfaction.
Furthermore, the higher score of the cultural measurement implies the higher degree of
collectivism, whereas the lower score of the cultural measurement implies the higher degree
of individualism. According to the regression models, the direct moderation effect of the
cultural context is negative, -0.004 in the first model, -0.151 in the second model. The
indirect effect is also negative as -0.141. Therefore, we can conclude that the higher degree of
collectivism, the weaker the relationship between product customization and customer
satisfaction; the higher degree of individualism, the stronger the relationship between product
25 After confirming H2, more findings could be drawn by looking at each measurement
specifically. Thus, five bar charts are made to show how the participants’ choices distribute
when answering the measurement items, which will be discussed in the following section in
details.
V. Discussion
The theory of how customization is related to customer satisfaction is ample in the existing
marketing literature. However, no previous studies investigate what the moderating factors
are in the relationship of customization and customer satisfaction. The current research aims
to understand if the two factors, preference stability and cultural context of individualism or
collectivism, moderate the customization-satisfaction relationship. Since the second
hypothetical moderator has two cultural dimensions of individualism and collectivism, the
moderating test of cultural context involves consumers who have different degree of
individualism or collectivism, in order to understand how individualistic culture and
collectivistic culture impact the customization-satisfaction relationship specifically.
Therefore, the research collects samples from respondents with different nationalities that
implies to the two cultural dimensions.
The first important finding is the high correlation between independent variable
customization and dependent variable customer satisfaction. In fact, not so many studies
provide the correlation figures in the marketing literature of customization. One paper written
by Coelho and Henseler indicates the correlation between customization and customer
satisfaction is 0.71 by adopting the same customization construct and different measurements
of customer satisfaction. Apparently, different measurements of the constructs will lead to
diverse results and conclusion. In this case, the relationship between customization and
26 correlation between these two variables should be high enough to support the positive
customization-satisfaction relationship. However, the correlation is extremely high in this
research because of the measurement items of customization and customer satisfaction are
highly interrelated and intertwined. The measurement items of customer satisfaction are
specially adjusted to the customization context. Moreover, the first measurement of
customization is measuring the degree of customization meets consumers’ specific needs,
which overlaps with the measurement items of customer satisfaction.
The empirical results reject the first hypothesis and imply preference stability is not a
moderator in the relationship of product customization and customer satisfaction. As many
previous scholars assume preference stability will have significant moderating effects on
customization-satisfaction relationship, the conclusion drawn from the empirical research is
actually opposite to what they suggest. This result will have important implications on the
existing marketing theory and practices related to customization.
It is that the construct consumers’ preference stability is very difficult to measure. Since
consumers’ preferences are not always associated with product attributed objectively, it relies
heavily on consumers’ subjective values. The difficulties of measuring consumers’
preference stability can be caused by the following possible reasons. Even though previous
scholars develop clear measurement of preference stability, it may fail to recognize and
measure preferences stability the customer has in product customization process, which are
largely influenced by many factors and difficult for researchers to learn. Future research
could replicate the moderation test of preference stability or develop new measurement to
gain more understanding in the field of product customization. It is also very common that
customers do not realize what their preference pattern is and how stable their preferences are.
Moreover, the degree of preference stability can be changed easily because of different
27 The other major important theoretical finding from this study is that the relationship between
product customization and customer satisfaction is significantly moderated by the consumer’s
individualistic or collectivistic culture, which confirms the assumption proposed by previous
researchers. Consumers with a higher degree of individualism are more satisfied with product
customization. On the other hand, consumers with a higher degree of collectivism are less
satisfied with product customization. Furthermore, customers from a typical individualistic
culture customize products based on individual preferences. In this case, it has a better
preference fit between the product attributes and customers’ real preferences. Consumers also
very happy because of they have a sense of self-accomplishment to show their own
personality and uniqueness, which is used to be distinctive with others. Customers from a
typical collectivistic culture customize products mainly based on the collective preferences.
They take more considerations of other group members’ opinions, collectivistic preferences
and social norms in the customization process. They want to show connectedness and
interrelations with relevant group numbers, the needs of being unique and special are much
less among collectivistic consumers.
We can conclude that the higher degree of collectivism, the weaker the relationship between
product customization and customer satisfaction; the higher degree of individualism, the
stronger the relationship between product customization and customer satisfaction.
To sum up, this research has identified the aforementioned linkage between product
customization and customer satisfaction through studying the cultural and preference factors.
The analyses support the second hypothesis while rejecting the first. It is assumed that the
cultural context of individual customers plays an important role in the relationships between
28 Besides the major findings, several other interesting findings are worthwhile to discuss based
on the following statistical tables of looking at each culture’s measurement specifically.
29 According to the results based on 80 Dutch participants (from typical individualistic culture)
and 80 Chinese participants (from typical collectivistic culture), slightly more than the half of
the total participants perceive individual preferences are more important than group
preferences, which corresponds to the equal number of participants in two culture contexts.
Surprisingly, 61% of them think the customized products do not need to be accepted by other
social members. 73% customize products to express individual personality and preferences,
whereas only 21% of participants customize products to express the connectedness to others.
72% do not like suggestions from others in the relevant social group. With considering the
same numbers of the Chinese participants and Dutch participants, these facts deliver an
interesting finding that more investigated consumers are having obvious characteristics of
individualism, even for consumers from a typical collectivistic culture. One possible reason
could be the dramatic influence of western cultures on Chinese society in the past decades.
Another explanation could be consumers tend to have more individualistic behaviors when
purchasing customized products, compared with their normally purchases of non-customized
30 Furthermore, it would be also very interesting if we compare the answers of the two cultural
groups to understand the cultural effects better. The below graphs illustrate how Dutch
participants and Chinese participate answer each measurement.
1. Group preferences are more important than my individual preferences.
2. The customized product being accepted by others in my social group (e.g. family, friends, colleagues…) is very important.
31 3. I customized the product to express my individual personality and preferences.
32 5. I do not like to have suggestions from others in my social group.
According to the graphs, some essential findings can be noticed. Most of Chinese participants
perceive group preferences are more important than individual preferences in the
customization process, whereas most of the Dutch participants think individual preferences
are much more important. We can also conclude from this study that customers from a typical
individualistic culture (Dutch in this research) customized products based on individual
preferences, while customers from a typical collectivistic culture (Chinese in this research)
customize products mainly based on the collective preferences. The customized product
being accepted by others in the relevant social group is more important for Chinese customers
than for Dutch participants. Moreover, the main reason for Dutch customers to customize
products is expressing individual personality and preferences. But Chinese participants show
multiple motivations to choose customized products. Some of them are expressing individual
33 Dutch participants and Chinese participants both indicate they do not like have suggestions
from others when customizing the product.
VI. Implications
Implications for marketing theory
Marketing literature depicts that customization is strongly related to customer satisfaction,
rather than standardization. The study confirms the theory of positive relationship between
customization and customer satisfaction, and complements the existing theory by testing two
potential moderators in the customization-satisfaction relationship. The most essential
theoretical contribution of this empirical research is consumers’ individualistic or
collectivistic cultural context is the moderator, whereas consumers’ preference stability does
not play a major role in the relationship of customization and customer satisfaction. It
supplements the theoretical framework of the positive customization effects on customer
satisfaction in product industries. The results reject the assumption that preference stability
has moderating effects in this relationship, which indicates that preference stability is not as
important as many of previous studies suggest.
Another important implication is that the findings answer one of the remaining questions in
existing marketing literature “is cultural analysis necessarily needed to understand
customization effects on customer satisfaction?” This study shows that culture has a
significant impact on customization-satisfaction relationship, especially from the perspective
of marketing knowledge, which normally requires the understanding of domestic business
environment and local characteristics. Cultural analysis needs to be taken into account when
understanding customization effects on customer satisfaction in different countries. Cultural
34
Implications for marketing practice
Customization is one of the most prevalent marketing strategies in product industries to
generate customer satisfaction. In many businesses, it is crucial to develop a good
understanding on how customization should fit in the current marketing strategies.
According to the results, preference stability does not have a significant impact on
customization-satisfaction relationship. Marketers could try to fulfill customers’ needs and
preferences, keeping in mind that customer’ preferences or requirements are dynamic and not
always stable. In different periods of product customization, the change of customer
preferences require marketer to be flexible and able to respond quickly.
On the other hand, marketers should take more considerations of cultural effects in the
process of product customization in order to maximize customer satisfaction. Consumers’
individualistic or collectivistic culture context is impactful for achieving maximum customer
satisfaction, especially for multinational corporations operating in diverse cultures and
regions. The strategy of product customization should be integrated with cultural
management.
In the business environment with many customers having a high degree of individualism,
companies should focus on offering uniqueness for each individual customer through product
customization, and helping customers to express their personality or achieve personal goal.
However, the business environment with many customers having a high degree of
collectivism, the product customization needs to be adapted and adjusted in order to fit in the
local needs. Marketers need to pay more attention to collectivistic preferences of the relevant
group the customer has, and also be aware of customers’ personal needs and preferences.
Moreover, marketers could offer product customization programs that particularly target each
35
VII. Limitations and Future Research
The current research provides empirical investigation concerning the moderators of
customization-satisfaction relationship, but it still has several limitations for the
considerations of conducting future research in this field.
According to the results of this study, preference stability does not have moderating effects
on the relationship, which is contradictory with what previous scholars propose. Future
research could replicate the moderating test of preference stability by using different
measurements or research methods, in order to check whether the same conclusion can be
proved repeatedly. Besides, concerning the relationship of customization and customer
satisfaction, the correlation between these two variables is extremely high with adopting the
selected measurements in this research. Additional research can be conducted to use different
measurements or develop new measurements for understanding how customization and
satisfaction actually interrelated to each other. It is expected that the repeated research also
have high correlation, but may be slightly lower than the figure in this research.
For testing the moderating effects of individualism and collectivism, the participants of this
research are Dutch consumers who are normally perceived having individualistic cultural
context, and Chinese consumers who are normally perceived having collectivistic cultural
context. Similar research could be conducted in more countries to understand in more depth
about if there is any difference of culture’s impact on customization-satisfaction relationship
in different countries, such countries as United States, Japan, Australia and South Korea are
very interesting to do the research.
Furthermore, the research focuses on customization in product industries in general,
compared to the customization-satisfaction research in service industries. It is worthwhile to
36 Thereby more specific investigation might be needed for each product category, typically
customized product categories are customized clothing, customized laptop, and customized
furniture. For example, the moderating impact of culture may much stronger in the industry
of clothing as this type of product is more visible and frequently seen by other members in
the society. It is expected consumers with a higher degree of collectivism are relying more on
group preferences to express their interconnectedness and interdependence in a relevant
group, compared to that in other product categories which are less visible in public.
Lastly, limitations of this study should also be considered, as it may also affect the
significance of the results it generated. The sampling techniques are convenience and
theoretical sampling, we aim to find field data relevant to the proposed theoretical
assumptions, however, we could not draw a randomized sample given the scope of this study
is limited. Therefore, convenience sampling is applied to carry out a relatively small-scaled
research. Secondly, the measurement of customer satisfaction are quantified, in order to
develop a deeper understanding on the relationship between customer satisfaction and
customization, the result of our research calls for qualitative studies to explore the influencing
37
VIII. Appendix
Invitation letter: Dear Sir or Madam,
Many companies nowadays are offering product customization to produce their products
according to your specific needs and preferences. If you have experience of product
customization, such as customizing a T-shirt, a laptop or a hand-bag, which was tailored to
your own preferences and requirements, I would like to invite you to participate the research
and your participation is of great importance for us!
The research is being carried out by a Master student of the Amsterdam Business School of
the University of Amsterdam, the Netherlands, seeking to improve our understanding about
how preference stability and cultural context influence your satisfaction about product
customization. We greatly appreciate your kind help and willingness to answer the questions.
Please based on your previous experience of product customization, answer the following
questions.
Thank you very much for participating this survey!
Questionnaire:
Your nationality is: Dutch/Chinese Customization:
1. The customization offers me products that satisfy my specific needs. 2. The customization offers products that I couldn’t find in another company.
3. If I changed between customizations I wouldn’t obtain products as customized as I have now.
Customer satisfaction
1. The customized product meets my expectations and needs. 2. I am completely happy in the process of the customization.
3. I am proud of my relationship with the company providing product customization. 4. I am satisfied with my decision to choose the product customization.
38 5. If I had to purchase again, I would feel differently about the product customization. 6. I am satisfied with the product customization.
Preference stability
1. The customizations I prefer fit some sort of pattern. 2. The customizations I choose do not have a lot in common.
3. If someone kept a record of product customization I choose, he/she would be able to make a pretty good prediction of which customization I might be interested in.
4. Even someone who knows me well will not be able to make a good guess for the next customization that may interest me.
5. I can easily tell which product customization I will really prefer and which I will not. 6. It is often difficult to predict which customization I will really like and which I will
not.
The cultural context of individualism or collectivism
6. Group preferences are more important than my individual preferences.
7. The customized product being accepted by others in my social group (e.g. family, friends, colleagues…) is very important.
8. I customized the product to express my individual personality and preferences. 9. I customized the product to express the connectedness to others.
39 Frequency Table:
40
IX.
References
Fiore, AM., Lee, S-E. and Kunz, G. 2004. Individual differences, motivations, and willingness to use a mass customization option for fashion products. European Journal of Marketing, 38, 835–49.
Hofstede, G. and McCrae, R. R. 2004. Personality and culture revisited: linking traits and dimensions of culture. Cross-Cultural Research, 38, 52–88.
Allen, M. W. and Ng, S. H. 1999. The direct and indirect influences of human values on product ownership. Journal of Economic Psychology, 20, 5–39.
Hirschman, E. C. and Holbrook, M. B. 1982. Hedonic consumption: emerging concepts, methods and propositions. Journal of Marketing. 46:92–101.
Nisbett, R.E. 2003. The geography of thought: How Asians and westerners think differently and why. New York, NY: Free Press.
Bettman, J. R. Luce, M. F. and Payne, J. W. 2008. ‘Preference construction and preference stability: putting the pillow to rest’. Journal of Consumer Psychology. 18(3). 170–174.
Ball, D., Coelho, P.S. and Vilares, M.J. 2006. “Service personalization and loyalty”, Journal of Services Marketing, Vol. 20 No. 6, pp. 391-403.
Hoeffler, S and Ariely, D. 1999. ‘Constructing stable preferences: a look into dimensions of experience and their impact on preference stability’. Journal of Consumer Psychology. 8(2). 113–139.
Amir, O and Levav, J. 2008. ‘Choice construction versus preference construction: the instability of preferences learned in context’. Journal of Marketing Research. 45, 145–158.
Simonson, I. 2005. ‘Determinants of customers’ response to customized offers: conceptual framework and research propositions’. Journal of Marketing. 69. 32–45.
Peppers, D. and Rogers, M. 1997, Enterprise One to One. New York:Currency Doubleday.
Lee, J. Lee, Y. and Lee, Y. 2012. ‘Do customization programs of e-commerce companies lead to better relationship with consumers?’. Electronic Commerce Research and Applications, 262-274.
41 Morris, M, and Peng, K. 1994, “Culture and Cause: American and Chinese Attributions for Social and Physical Events,” Journal of Personality and Social Psychology, 67 (6), 949-971.
Shen, A. and Ball, A. 2011. ‘Preference stability belief as a determinant of response to personalized recommendations’. Journal Of Consumer Behaviour, 10(2), 71-79.
Chang, C., Chen, H. and Huang, I. 2009, ‘Interplay between Customer Participation and Di
fficulty of Design Examples in the Online Designing Process and Its Effect on Customer Satisfaction: Mediational Analyses’. Cyber Psychology & Behavior, 12(2), 147-154.
Singelis, Theodore M. 1994, “The Measurement of Independent and Interdependent Self-Construals,” Personality and Social Psychology Bulletin, 20 (Oct), 580-591.
Hoeffler, S and Ariely, D. 1999. ‘Constructing stable preferences: a look into dimensions of experience and their impact on preference stability’. Journal of Consumer Psychology. 8(2). 113–139.
Kramer, T., Spolter, S. and Thakkar, M. 2007, “The Effect of Cultural Orientation on Consumer Responses to Personalization,” Marketing Science, 26 (2), 246–258.
Huber, J., Payne J. W. and Puto, C. 1982. Adding asymmetrically dominated alternatives: violations of the regularity and similarity hypothesis. Journal of Consumer Research 9: 90– 98.
Chernev, A., Mick, D. G. and Johnson, M. D. 2003. When more is less and less is more: The role of ideal point availability and assortment in consumer choice. Journal of Consumer Research, 30(2), 170−183.
Irwin, J. R., and Naylor, R. W. 2009. Ethical decisions and response mode compatibility: Weighting of ethical attributes in consideration sets formed by excluding versus including
product alternatives. Journal of Marketing Research, 46(2), 234−246.
Kramer, T. Spolter-Weisfeld, S. and Thakkar, M. 2006. ‘Individual Preferences Versus Group Preferences: The Effect of Cultural Orientation on Consumer Receptivity to Customized Offers’. Advances in Consumer Research. 2006, Vol. 33 Issue 1, p462-463.
Kramer, T. 2007. The effect of measurement task transparency on preference construction and evaluations of personalized recommendations. Journal of Marketing Research, 44(2), 224−233.
Frank, N. and Schreier, M. 2010, ‘Why customers value mass-customized products: The importance of process effort and enjoyment’. Journal of product innovation management, 27,7, pp. 1020-1031, Google Scholar, viewed 3 March 2014.
