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					        THE IMPORTANCE OF ATTITUDE IN MEDIATING THE
              CONSTRUCTS OF PERSONAL FACTORS
             TO THE OUTCOMES OF INTERNET USAGES
                AND ONLINE PURCHASE INTENTION
                                Mark Ng and Monica Law
          Department of Business Administration, Hong Kong Shue Yan University
                          10 Wai Tsui Crescent, Braemar Hill Road, North Point
                                         chng@hksyu.edu


                                           ABSTRACT

        This study seeks to understand adult consumers’ Internet usages and online purchase
intentions with the mediation effect of attitude. With more than 600 questionnaires were
collected from adults of 41 to 70 years old in Hong Kong, two exogenous constructs are
investigated in this model, which include personal innovativeness and perceived online skills.
Those consumers who have higher evaluations to those personal factors may have positive
attitude and then they may use the Internet more and/ or purchase online more likely.
Therefore, the keys for online shopping companies to attract more middle-aged and senior
consumers are to change their attitude and enhance their personal skills and interests. The
paper concludes with a discussion of the research findings, the study limitations, and the
directions for future research.

Key words:    Attitude, Perceived Innovativeness, Perceived Online Skills, Online Usage
              and Online Purchase Intention.



                                       INTRODUCTION

         Although the online marketplace has been largely youth-driven, the middle-aged and
older adult segment has become increasingly important in the online market recently. First of
all, this adult segment comprises a large and growing segment of the population. According
to the U.S. Census Bureau, the global population aged 40 and above was estimated to be 2.11
billion, an increase of 0.21 billion since 2003. The proportion of this population segment
increased from 30% in 2003 to 32% in 2007. It is expected that this segment of population
will continue to grow rapidly. In Hong Kong, the population aged 40 and above was
estimated to be 3.47 million people in 2007, an increase of 0.22 million people since midyear
2003. Population ageing is therefore a global phenomenon, which is more commonly found
in the developed countries. Most importantly, this segment of the population becomes a
lucrative market. The increased influence of senior market then requires marketers to pay
more attention (Burnett, 1991; Eastman & Iyer, 2004), for instance, investigating what factors
determine adult consumers’ intention to make purchase online.

        More and more researchers start to investigate the major aspects of using information
technology by the elderly, which include their psychological benefits (Billipp, 2001),
effectiveness of computer training (Temple & Gavillet, 1990), and the use of technology to
support their living (Finn, 1997). However, few academic studies address the middle-aged
people and the senior’s uses and attitudes towards the Internet and online stores. Considering


                                                1
the rapid growth of this demographic and the increasing attention of online marketers,
exploration of the key determinants to their Internet usages and online shopping intention is a
critical area of examination.

         Traditionally, the usage rate of the Internet by middle-aged people and seniors has
been the lowest of any demographic group. To increase the usage rates, we should address
the barriers and means necessary to allow them to join the Internet community. This study
builds on the work of Reisenwitz, Iver, Kuhlmeier & Eastman (2007), to examine how
middle-aged and senior citizens use of the Internet and what are the determinants affecting
their usage and online shopping intentions in Hong Kong. In this paper, we aim to extend the
earlier research done on mature consumers and their Internet use by examining how their use
of Internet affected by their attitudes, perceived innovativeness, and their perceived online
skills.


           THEORETICAL BACKGROUND OF THE RESEARCH MODEL

       The use and adoption of new technologies has long been an area of inquiry. For
example, many researchers investigate the factors behind the acceptance of various
technologies such as personal computer applications (Igbaria, Guimaraes, & Davis, 1995), e-
mail applications (Karahanna & Straub, 1999), and the World Wide Web (Lin & Lu, 2000;
Moon & Kim, 2001). The theoretical models commonly discussed in this research area are the
Theory of Reasoned Action (TRA) by Fishbein & Ajzen (1975), and Technology Acceptance
Model (TAM) by Davis (1989).

       Theory of Reasoned Action (TRA) argues that two kinds of beliefs, which include
behavioral belief and normative beliefs, affect the behavior intention and hence, actual
behaviors of the buyers (Fisher & Ajzen, 1975). Ajzen (1985) extended the model by adding
“perceived behavioral control” to the original theory and resulted in a new theory called the
Theory of Planned Behavior (TPB). Perceived behavioral control refers to an individuals’
general belief of the ease with the behavior can be performed. This model has been
supported and perceived behavioral control is found to be an important predictor of
behavioral intentions (Ajzen & Driver, 1991).

        Technology Acceptance Model (TAM) examines impact of the perceived usefulness
and perceived ease of use on attitude towards use, and hence the behavioral intentions and
actual usage (Davis, 1989; Gefen, Karahanna, & Straub, 2003). In contrast with the TRB,
TAM argues that the attitude impacts the behavioral intentions, as a result, affecting the
actual behaviors. TAM has been widely used in explaining different forms of technological
adoption (Venkatesh & Davis, 2000), such as the adoption of intranet (Horton et al., 2001),
handheld Internet services (Bruner & Kumar, 2005), and e-commerce (Keat & Mohan, 2004).
TAM is believed as the most robust and influential model in explaining technological
adoption behaviors (Davis, 1989). Many studies extend the model by adding some external
variables such as consumer skills, compute anxiety, and perceived self-efficacy (Wang et al. 2003)
to improve the model’s predictive power.

        This study wants to contribute to the literature by providing a framework for
understanding adult consumers’ Internet usages and online purchasing intentions with the
mediation effect of attitude. We extend the TAM model by investigate how two personal
factors, perceived innovativeness and perceived online skills, influence the attitudes toward


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using and buying on the Internet, and hence, their purchase intention.

        Perceived innovativeness is defined as a consumer’s willingness to try out new
fashion of consumption, which can be regarded as an antecedent for his/ her adoption of new
products and innovations (Agarwal & Karahanna, 2000). Less innovative customers tend to
make more routine buying responses to a static set of products (Hischman, 1980).
Traditionally, there are two major ways to conceptualize the constructs of consumer
innovativeness (Im et al., 2003). Consumer innovativeness refers to domain specific
characteristics and actual acquisitions of new information and products on that domain
(Hirschman, 1980). For example, it is defined as the purchase intentions, new products
owned, and the relative time of adoption for a particular kind of new product (e.g. internet).
In contrast, consumer innovativeness can be defined as a generalized personality trait, which
is “innovative predisposition” across different product classes (Goldsmith & Hofacker, 1991).
This personality trait of innovativeness is similar to the measures of the receptivity to new
experiences (Goldsmith, 1984). The domain-specific innovativeness is found more useful in
predicting an individual’s adoption behaviors than the generalized innovativeness (Gatignon
& Robertson, 1985). As a result, we would also adopt a domain-specific measurement to in
this study.

        Adopting a domain-specific conception of innovativeness, Goldsmith & Bridges
(2000) provide an empirical support that innovative consumers are more likely to perceive
that the Internet was fun, quicker, safer, and cheaper to use, and they may have more
confidence in using Internet. Furthermore, they usually spend more hours on the Internet,
and more likely to make online purchase in future (Goldsmith, 2001). Thus, there is a close
relationship between consumer innovativeness, their attitudes towards internet, and their
internet purchase intentions (Chiu, Lin & Tang, 2005; Citrin et al., 2000; Goldsmith, 2002).
We apply these concepts to middle-aged and senior consumers with the following hypothesis:

       Hypothesis 1: If middle-aged and senior persons have higher perceived innovativeness,
                      they may have positive attitude towards using Internet.

        Yamauchi & Markman (2000) suggest that consumers often use their existing
knowledge to learn about technologically advanced products. Facing with something new,
consumers may use their familiar knowledge to understand and comprehend the new
technology. Thus, whether people would develop good attitudes toward the use of Internet
services, it may depend on their familiarities with the Internet. If they perceived themselves
have higher online skills, they are more likely to adopt the new services of the Internet. Iyer
& Eastman (2006) also investigate how the confidence in computer ability affects the use of
Internet and e-commerce in the elderly market. It also supports that those seniors who are
more confident in their abilities to use the Internet would be more likely to use it for
comparison shopping. As a result, we propose the second hypothesis:

       Hypothesis 2: If middle-aged and senior persons have higher perceived online skills,
                     they may have positive attitude towards using Internet.

        Attitude theory suggests that intentions toward the idea are mainly explained by the
attitudes toward that idea and the attitudes toward behavior (Fishbein & Ajzen, 1975). The
construct of attitude is widely used for predicting consumer’s adoption of innovative products
(Erevelles, 1998). Consumers’ attitudes towards the product would affect whether they
would use the product or not. Bao (2006) also supports that the relationship between attitude


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and behavioral intentions. This study infers that attitude toward internet are the determinants
of internet usage; and their attitude toward buying on the internet are the determinants of
online purchase intentions. Consequently, two hypotheses are set as follows:

       Hypothesis 3: If middle-aged and senior persons have positive attitude towards using
                     Internet, they may have more online usage.

       Hypothesis 4: If middle-aged and senior persons have positive attitude towards using
                     Internet, they may have higher online purchase intention.

        To sum up, the aim of this research paper is to extend the TAM model that
investigates the factors influencing the use of Internet and the online purchase intention. In
particular, perceived innovativeness and perceived skills of Internet users are used to explain
consumers’ differences in attitudes and behaviors in using Internet. Specifically, this paper
suggests that the impacts of personal innovativeness and perceived online skills on purchase
intentions are mediated by the attitudes towards internet.

METHODOLOGY

Sampling and Procedure

        The sample for this study was composed of middle-aged and senior persons aged over
40 in Hong Kong who had online experiences before. The main survey was conducted with a
convenience sampling method. Research fieldworkers were employed for this research and
they had attended a briefing session before conducting the survey. Their major duties were to
invite respondents, read questions and mark answers. Cover letter was also attached to each
questionnaire in order to explain the purposes of the survey and to provide assurance of the
anonymity, which showed to all the respondents at the beginning of the interviews. In
addition, the questionnaire was prepared both in Chinese and in English. Although it initially
constructed in English, each item then was translated into Chinese and back translated
independently into English, by an independent researcher (Brislin, 1980). The major purpose
was to assure the equivalence of Chinese and English versions.

        There were 626 returned questionnaires. Amongst them, 57 questionnaires were
classified as incomplete and/or not useful. As a result, 569 questionnaires were taken for this
survey. About 53 percent of the respondents are male and 47 percent are female. The
distribution of age groups was: 41-50 (with 69 percent), 51-60 (with 27 percent), 61 or above
(with 4 percent).


Measures

        Most of the measurement items used in the survey were based on the related literature
studies. Unless stated, all measures adopted a five-point Likert scale, described by “Strongly
agree” (= 5) and “Strongly disagree” (= 1).

       Perceived innovativeness. There were four items to measure this construct. All of
them were taken from the studies of Chiu et al. (2005) and McKnight et al. (2002). One of
the examples is: “I like to explore new websites.”



                                             4
        Perceived online skills. Four items were used for the measurement. Two of them
were taken from the study of Mathwick & Rigdon (2004); for example, “I consider myself
knowledgeable about good techniques in using the Internet”. In addition, two more new
items were added in order to ask about the respondents’ problem-solving skills and their
overall evaluation to their online skills. They are: “When I find a problem in using the
Internet, I can solve it by myself” and “I am satisfied with my current skills for using the
Internet”.

        Attitude. Three items were adopted from the study of Chiu et al. (2005), which had
taken the items prepared by Taylor & Todd (1995a,b). However, some of the wordings were
amended. For example, one of the original statements – “Using the Internet to buy CCP is a
good idea” – was changed to be “Using the Internet is a good idea”, in order to suit the
purpose of this research.

        Online usage. Four items were adopted. Amongst them, three were taken from the
study of Mathwick & Rigdon (2004). One of the examples is: “I am a heavy Internet user”.
One more item was added in order to indicate whether the respondents treated surfing the
Internet as their daily life practice or not. It is: “Surfing the Internet is a part of my life”.

         Online purchase intention. Three items were taken from the study of Chiu et al.
(2005), which were prepared by Taylor & Todd (1995a, b). Once again, some of the
wordings were amended. For example, the original statement was – “I intend to use the
Internet to buy CCP” and finally it was changed to be “I intend to purchase online”, in order
to suit the purpose of this research.

Data Analysis and Results

        A two-step procedure involving principle component factor analysis and structural
equations modeling (Anderson & Gerbing, 1988; Medsker et al., 1994) was employed to test
the hypotheses. In the first step, principle component with eigenvalues over 1 was used to
extract the factors used in the study. Ultimately, all the items were retained after the detection
of variables with more than one factor, or removal of low factor loadings. In line with
recommendations by Mishra et al. (1998), the Kaiser-Meyer-Olkin (KMO) was used to
determine whether the items used in this study share a common core. The result (.89) was
higher than the acceptable exploratory standard (.50) suggested by Nunnally (1978). The
data then were rotated by the varimax method and reliabilities of the extracted factors were
assessed using Cronbach’s alpha coefficient (Mishra et al., 1998). The reliabilities were all
over .70, thus fulfilling the minimum acceptable level suggested by Nunnally (1978).

        Next, the measurement model comprised of all the items, was tested with the global
fit indexes (²/df = 2.03; goodness-of-fit index [GFI] = .88, comparative fit index [CFI] = .99,
normed fit index [NFI] = .99, incremental fit index [IFI] = .99, and root mean square error of
approximation [RMSEA] = .04) with LISREL software (version 8.80). The result revealed
that the hypothesized factor structure fitted the data well, indicating the model was acceptable.

       After the validation of the measurement models, another step was to test the
hypotheses. A structural model was suggested and the five constructs – perceived
innovativeness, perceived online skills, attitude, online usage and online purchase intention –
were used. First, all the global fit indexes (²/df = 2.87; GFI = .84, CFI = .99, NFI = .98, IFI
= .99, and RMSEA = .06) were reached the acceptable levels. Second, the relationships


                                              5
between each construct were investigated. All of the relationships were significant. Four
hypotheses were supported based on the parameter estimates and t-values for the
hypothesized relationships. The links between perceived innovativeness and attitude (H1: t =
6.62), and perceived online skills and attitude (H2: t = 10.93) were supported. Attitude was
found to be positively related to online usage (H3: t = 16.93) and online purchase intention
(H4: t = 11.27). The estimated path coefficients of the hypothesized model are shown in
Figure 1.


       Figure 1
       Structural Model



                     perceived                                       online usage
                   innovativeness
                                     .33**                .88**




                                               attitude



                                      .56**                  .51**
                      perceived                                      online purchase
                     online skills                                      intention


                                                                      **p<.01




                                             DISCUSSION


        Innovation adoption is affected by both the characteristics of innovation products and
the psychological process of consumer decision-making. This study examines how middle-
aged and senior consumers adopt innovation and how their personal factors affect their
attitude of innovations. The findings are largely consistent with literature of Technology
Acceptance Model (TAM), which postulates that consumers’ behavioral intention is affected
by their attitudes towards using internet (Goldsmith, 2000).

        As suggested by the TAM, consumers’ attitude towards Internet plays a dominant role
in affecting the usage of Internet and the behavioral intention of consumers. Those mature
consumers view using Internet as useful and enjoy pleasant experience may spend a lot of
their spare time on the Internet and treat surfing the Internet as a part of their lives. They also
have more experience in performing online purchase and have higher intention to do online
shopping in future.

        This study also found that perceived innovativeness and perceived online skill had
significant impacts on middle-aged and senior persons’ use of and feelings about the Internet.


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These people with high levels of perceived innovativeness on Internet had more favorable
attitude toward the use of Internet, then used the Internet more, and more likely made
purchase online. This finding is consistent with previous studies on perceived innovativeness
(Goldsmith & Bridges, 2000). When those mature consumers view themselves as innovative
online shoppers, they tend to use the internet more, have more experience online, and feel
more comfortable and more satisfied using the internet. In contrast to the pessimistic view of
mature market segment (e.g. Lenhart, 2000), this study shows that the innovative mature
consumers are willing to shop online.

        Additionally, as prior purchase experience has a significant influence on their
perceived online skills, the result of this study supports the view that online shopping is
significantly influenced by the experience qualities of online consumers (Gabbott & Hogg,
1998). As mature Internet users may use online more hours and more frequently, they are
becoming more and more comfortable with using the Internet and make purchase online
(Rohm & Swaminathan, 2004). After gaining experience and developing more positive
attitude towards Internet, they are more likely to purchase online. That is, the results found in
the youth market can now be generalized to the more mature market.

        Given the growth and financial power of the Internet as well as the mature consumers
and senior market, online retailers are interested in serving more customers online,
motivating them to make more purchases, and promoting customers loyalty. To attract this
segment, marketers need to understand the role that innovativeness and perceived Internet
skills play as those mature consumers who see themselves as being innovative and capable to
use Internet may be the most attractive target within the mature consumer segment. Thus,
marketers should consider how to reach more innovative mature consumers and how to
enhance the perceived internet skills of mature consumers. For example, as suggested by
Polyak (2000), the marketers may make use of multiple media and channels to reach and
serve the mature market to enhance their experience online. After they have gained
experience of online shopping, they are likely to continue in future (Goldsmith, 2002).

        Several major limitations concerning this study need to be acknowledged. First of all,
future research needs to determine if these results can be replicated with a national random
sample. Additionally, research is needed to investigate the major determinants of mature
consumers’ experience with the internet. For example, is there a relationship between how
they learned to use the internet and their future online experiences? Is there any mechanism
for the mature consumers to gain more experience online? Finally, this research limited the
scope of study to only two personal factors and the psychological process of technological
adoption. Future research may need to address other psychological factors such as perceived
risks, trust, and pervious experiences online to have better understanding on the needs of
consumers.




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