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484
International Journal of Management
Vol. 22 No. 3 September 2005
The Impact of Web Site Image and Consumer Personality on Consumer Behavior Wen-Jung Chen Ming Chuan University, Taiwan Chuan Lee Ming Chuan University, Taiwan Following the phenomenon of the "Internet Bubble," the industry's planning and execution of marketing strategies have begun to show defects. The main objective of this study is to investigate the effect of website image on consumers' behavior. In addition, the effects of consumers' personality and demographics on the website image and consumers' behaviors is examined. Through surveys, the current study found that web site image has a significant effect on the purchasing behavior and purchasing intention of consumers. This study hopes to draft an effective Internet marketing strategy by adopting a strategic viewpoint and the viewpoint of the consumer, and additionally by examining the impact of web site image and consumer personality on the personal preferences of the consumer.
Introduction Since the 1990s, the number of people who use the Internet has increased dramatically. Throughout the world, the number of Internet s was about 160 million in 1998. According the study, from International Data Corp (IDC), more than 600 million people will have accessed the Internet globally by the end of 2002 and spent more than US$ 1 trillion buying goods and services online (Straits Time, 2002). The Gartner Group estimates that the scale of the e-commerce market will be about $7.3 trillion in 2004, the Internet has been the emergent media with a greater developing potential than radio, TV and cable TV. Through the Internet, businesses provide commodity and service information to attract the consumer's attention, cause their interest, arouse their purchasing desire and bring about purchasing action, which is called the AIDA mode. It is expected to make consumers purchase or get the commodity or service to meet their needs over the shortest possible time and at the lowest cost, and maximize benefits for businesses. Different from other medias, the particular features of the Internet call for special attention in marketing programs for its virtuality and its infiuence on consumers. Kotler (2003) argues that people will establish faith, attitude and impression by action and refiection, which will infiuence their purchasing behaviors. The impression felt by individuals will impact on one's behavioral decision. Some scholars apply this concept in the retail field. For example, Kunkel & Berry (1968), Lindquist (1974) and Hansen & Deutscher (1977) explore the infiuence of web site image on consumer behavior and store selection, and develop many facets of web site image. For the Internet marketer, the website is his store, and web site image probably has a large effect on the behavior
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of consumers. But in relevant studies, the factors that make web site image attractive to consumers are rarely discussed. The first major purpose of the study is to discuss important facets of the website image; second is the effect of consumer's characteristics and personality (as involvement, selfmonitoring and perceived risks) on web site image and consumers' behaviors. Results of this study will help the development of effective Internet marketing strategies for building web site image. The article is organized as follows. In the next section we provide the theoretical background and development for hypotheses. Next, we discuss the sample, data, and statistical procedures. The article concludes with a discussion of the results of our hypotheses testing, implications of this study for practitioners and scholars, limitations of the study, and avenues for future research.
Web Site Image
Literature Review
An Internet store indicates the web site, which provides a commodity or service for clients, a chart or sheet for making an order, and accepts online orders of clients. Many scholars advance different definitions of store image. Engel, Blackwell, & Miniard (1990) define store image as the consumer's integrated perception of the property of one store. Based on many studies and opinions, web site image in our study means consumer's integrated perception of properties and functions (such as commodity price, vast information) and psychology (as web site design) which are stressed by consumers about websites providing commodities, service and order functions on the Internet. Many scholars present different store image facets, among which Kunkel & Berry (1968) and Lindquist (1974) are the most elaborate and widely cited by researches. They studied the department stores and 12 facets such as commodity price, quality, salesmen, convenience of site and service as well as 43 properties. Lindquist (1974) puts forward 9 facets as commodity, service, client, physical facilities, convenience and promotion as well as 33 properties. But because of the particular features of the Internet store, some purposes and facilities are not suitable for it, such as parking, business hours, restaurant facilities and so on. In recent years, some scholars have studied advances in the websites of Internet stores and attributes along with relevant consumer usage behavior. Ducoffe (1996) suggests that Internet store website attributes include information, entertainment and fret, which will affect the advertising value of a website and consumer's attitude. Richmond (1996) suggests attributes include payment method, special offers or discounts, interactive entertainment, and virtual reality, which will influence whether the consumer adopts online shopping, and his online time as well as amount of consumption. Dreze & Zufryden (1997) thinks the attributes include background color, image size, sound presentation, celebrity recommendation and so on, which will influence pages and the time the consumer browses the website.
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Though the store image advanced by subsequent researchers somehow complies with the features of the Internet, limited by the study range, the facet of Internet store has not developed as complete as that of the common store. Referring to the common store image facets advanced by Kunkel & Berry (1968) and Lindquist (1974), and the Internet store facets advanced by Ducoffe (1996), Richmond (1996) and Dreze & Zufryden (1997), the study develops 6 facets of the Internet store (commodity, service, convenience, store, promotion, and information) and 21 properties, with expectation to improve on website image. In the model the process of store selection advanced by Engel, Blackwell, & Miniard (1990), there are two reasons to explain whether the consumer chooses a particular store: one is the consumer's own evaluation standards, such as site, price, commodity and so on, and the other is the consumer's perception of store features, that is the store's image, Peterson & Kerin (1983) found that there was a correlation between web site image, selection standard and consumer's purchasing behavior. Thus, consistent with earlier research, it is expected that Website image has a significant influence on consumers' (a) purchasing intention, (b) purchasing behavior. Consumer's Personality Zaichkowsky (1985) defines involvement in of something felt by individuals based on one's need, value and interest in some product, service or affair. When a consumer is not interest in or familiar with ment content, information with high reliability is easier to be accepted, and the relevant ment has a good effect; while the consumer acquaints and understands the product or information well, the content cannot have much influence on him or her (Korgaonkar & Moschis, 1982), Zaichkowsky (1986) also believes that media-ecology is one of the key factors to influence the consumer's involvement in information. Because of the Internet's features of intangibility and long-distance transmission, it stresses the effect of information more than other communication media, Snyder (1974) thinks self-monitoring is the adjustment of individuals to their surroundings, also a kind of inclination to pay attention to social propriety and to modify ones behaviour to comply with it. In another words, individuals with high self-monitoring can adapt their own behavior to different situation or surroundings, while those with low self-monitoring can maintain consistent self-behavior, and emphasize individual value systems and self-expression (Browne & Dennis, 1997), Though few studies have examined correlation between self-monitoring and consumer behavior, it can be deduced that individuals with high degrees of self-monitoring are more easily influenced by Internet shopping fashions or online shopping behaviors of his/her friends. Cox (1967) defines perceived risk as a multiplicative function of the possibility of a negative result perceived by the consumer before purchase and degree of loss perceived by the consumer when he/she is displeased with a purchase. Because of the intangible services provided by the Internet, and the immature Internet circumstances of Taiwan, consumers' insecurity or uncertainty have a large effect on their purchasing intention
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and behavior. Tan (1999) found that when consumers shop on-line, they often shoulder such burdens as data safety, not being able to see the commodity before purchase and uncontrolled circumstances, which influence online purchasing intentions. Donthu and Garcia (1999) found Internet shoppers differ from non-shoppers in age and income, but do not differ from nonshoppers on education and gender. They found Internet shoppers are older and are wealthier than non Internet shoppers. We follow this result, and examine what impact age and income have on perceived web site image. The relationship between demography and web image is not adequately understood. Thus, consistent with earlier research, it is expected that consumers' personality and characteristics have a significant influence on the importance of web site image factors perceived by Internet shoppers. Finally, it is hypothesized that consumers' personality and characteristics have a significant influence on their image of websites, and consumers' (a) purchasing intention, (b) purchasing behavior.
Method To collect data to test the hypotheses, data for the study were obtained via a web survey of Internet store shoppers. Among the websites used were those from the classified introduction by Yam, and the e-Oscar E-Business Internet Golden Award held by ClubEC Netcom International, E-business Research Center of the National Taiwan University of Science and Technology, Extension Education Department of the Chinese Culture University, and the Technology Department ofthe Ministry of Economic Affairs. Those complying with the definition of an Internet store were approached to host the questionnaire on their web site. The questionnaire was hosted for five months from March 2003 to July 2003. In addition, an e-mail newsletter was sent out on 10-15 Feb. to obtain more participants. At the end, the participants were rewarded with a gift. The questionnaire, using five-point scales, was employed to collect data for the constructs of the research model. The Likert scale was used with 1 measuring "strongly disagree" and 5 measuring "strongly agree". Respondents were first asked some general questions about their Internet use and demographics. Next, they were asked short questions to measure their personality, including involvement, self-monitoring, and perceived risk. Finally, they were asked short questions about their perception toward web sites, based on their perceived importance and satisfaction with web site image factors.
Result Profile of the sample In total 751 questionnaires were received. Excluding those in which over 10% questions were not answered or personal data not provided, valid questionnaires totaled 658, comprising 87.6% ofthe total reclaimed questionnaires. Among the retained samples, females were in the majority (68.7%), whose age was 2635 (40.7%), secondly from 36-45 (21.2%) and 21-25(16.8%). Of the interviewees, business people were the most (30.3%), followed by soldiers, civil servants, teachers
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and people engaged in financial insurance (respectively 23.2%). Students ed for 15%. This demonstrates diverse career backgrounds. It seems that the need for the Internet has no direct and distinct relation to career; samples with education above college level 95% of the total, among which those above graduate institute was highest (49.7%). Interviewees from the north ed for half of the total sample (59.4%). As far as income was concerned, those between TWD 40,000 and 80,000 covered half of the total (51.3%), next was TWD 20,000 to 40,000 (17.3%) and TWD 80,000 to 100,000(15.5%). The average amount spent in NT dollars each time was 1001-2500 (15.9%), next was 2501-5000 (12.7%). As for frequency of purchase, once per month and once every 3 months were most common (respectively 15.9% and 12.7%). As far as usage of websites, 1-2 times each week was most, and 21-45 min. for each time was highest (33.6%), 5-20min. was next (21.4%). In of websites browsed, the average purchasing intention of interviewees was 4.28 (graded by 1-7), which shows their high purchasing intention. Results of Variable and Reliability Analysis The results are presented in Table 1. As regards the image of web sites, interviewees paid more attention to such web site image facets of service and information, as insurance (4.70), commodity quality (4.52), easiness to return/change goods (4.45), response (4.38), update rate of information (4.32), integrity of information (4.31), than to facets of convenience, store, ment (3.22), promotion (3.60), store atmosphere (3.70), multiple delivery methods (3.98), clear web site introduction and direction (4.03). Correspondingly, interviewees felt satisfied with such image facets of convenience and information, as store's reputation (3.59), update rate of information (3.57), clear instruction and direction (3.50), integrity of information (3.48), automatic provision of information (3.48), but dissatisfied with facets of promotion and service, ment (3.18), response (3.19), individualized service (3.21), easiness to return/change goods (3.22), brand/reputation (3.36) and insurance (3.40). It appears that among the web site image facets of service and information, professionals do well as regards information, but need to improve on service. Table 2 shows the results of variable and reliability analysis. Among the variables such as self-monitoring, perceived risk and involvement, it was found that interviewees paid most attention to such potential risks as security (53.07) and function (50.71) when browsing the Internet. As regards reliability, this study utilized the a coefficient developed by Cronbach. According to the norms developed by Cronbach (1951), a values greater than 0.70 indicate high credibility, between 0.35 and 0.70 indicate middle credibility, and lower than 0.35 indicate low credibility. The a value for each variable and each structural aspect in this study were all higher than 0.70. This exceeds the Cronbach (1951) norms, and indicates that the questionnaire in this study reached considerable internal consistency.
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Vol. 22 No. 3
September 2005
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Table 1. Importance and Satisfaction with Facets of Web Site Image Web Site Image Facets :Mean Insurance 4.70 Quality 4.52 Easiness to return-change goods 4.45 Response 4.38 Update rate of information 4.32 Integrity of information 4.31 Provide function to search information 4.20 Reasonable price 4.16 Reputation of store 4.13 Automate to provide information 4.10 Individual service 4.07 Provide multiple payment methods 4.04 Easiness of shopping 4.03 Provide clear explanation and 4.03 direction of web site Provide multiple delivery methods 3.98 Provide professional knowledge 3.97 Commodity type 3.96 Commodity brand/reputation 3.75 Atmosphere of store 3.70 Promotion 3.60 AD 3.22
Importance (Satisfaction S.D. Ranking Mear1 S.D. Ranking 1 .61 3.40 13 .91 2 .74 .69 3.48 6 .68 3 3.22 .88 18 .67 4 .86 3.19 20 .72 5 2 3.57 .97 .92 .71 6 3.48 6 .11 7 3.57 2 .83 11 .68 3.42 8 .73 1 .74 9 3.59 .83 .76 10 3.48 .91 6 .73 11 3.21 .87 19 .77 12 3.42 .82 11 .82 4 .79 13 3.53 .71 13 3.50 .85 5 .72 .81 .69 .79 .98 .85 .87
15 16 17 18 19 20 21
3.40 3.47 3.44 3.36 3.30 3.30 3.18
.83 .90 .78 .76 .80 .73 .11
13 9 10 15 16 16 21
Table 2. Results of Self-Monitoring, Perceived Risk anc1 Involvement and Reliability Analysis Variable and Facets Self-Monitoring Perceived risk Financial risk Functional risk Body risk Psychological risk Social risk Time risk Safe risk Involvement
No. of Items Maxi 18 items 79 464 3 items 75 3 items 160 1 item 25 3 items 179 3 items 70 2 items 50 3 items 75 10 items 70
Mini Mean 54.12 37 135 268.87 16 44.95 18 50.71 3 16.83 19 39.38 8 30.66 12 33.28 19 53.07 23 47.57
S.D. Cronbach'sa 7.43 .79 51.77 .66 11.07 .71 15.70 .68 5.94 19.42 .84 10.74 .74 8.76 .69 13.43 .80 8.75 .89
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Web Site Image and Purchasing Behavior, Intention Based on a regression analysis of web site image, purchasing behavior and intention, the results are presented in Table 3, It was found that convenience affects browser's purchasing amounts and web site usage time; store and information affect browser's purchasing frequency. Promotion affects web site usage hours; service affects browser's purchasing intention. Hence, hypothesis (HI) was partially ed, which says that website image has a significant influence on consumers' (a) purchasing intention, (b) purchasing behavior. Analysis of Web Site Image The results are presented in Table 4, With variation in the importance of web site image, its difference is obvious owing to gender, age, educational history, career, residential area and income. It was found from analysis that differences in importance cognitions of interviewees with education above college and university level towards price of commodity, commodity brand/reputation, quality, type, individualized service and response are significant; differences in importance cognition of interviewees with income above 150,000, between 20,000 and 40,000 and between 60,000 and 80,000 toward commodity price were significant. Hence, hypothesis 2 (H2) was partially ed, which says that consumers' personality and characteristics have a significant influence on the importance of web site image factors perceived by Internet shoppers.
Table 3. Regression Analysis: Website Image, Purchasing Behavior, and Purchasing Intention Purchasing Sum
Purchasing Frequency
Website Usage Time
Coefficient P Coefficient p Coefficient p 4,13
Website Usage Hours Coefficient p ,44
1,63
Purchasing Coefficient p 4,06
Intercept
2,46
Commodity
,04
,78
,16
,27
-,05
,59
,09
,35
,01
Service
-,14
,41
-,09
,61
-,14
,18
-,14
,17
,19 ,,05**
Convenience
,38
,(31** *
-,19
,17
,21
02**
,14
,13
,13
,12
Store
-,24
,11
,31
,04**
,06
,48
-,14
,11
,12
,14
Promotion
,06
,60
,19
,12
,07
,35
,18
,02**
,01
,88
Information
-,04
,78
,25
,05*
-,13
,18
,06
,53
,01
,88
L99
,08*
2,06
,07*
1,50
,18
2,04
,06*
1,32
,25
F
p
*p<,l **p<,05 ***p<,01
,95
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Vol. 22 No. 3
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Web Site Image, Personality, Demographics, and Purchasing Behavior Intentions The results of the regression analysis of web site image, personality, and purchasing behavior and intention are presented in Table 5. It was found that involvement has a significant effect on the correlation between website image and purchasing intention. The effects of other personality factors on the correlation between website image and purchasing intention did not reach a significance level of 10%. From further analysis, it seems that the higher the browser's involvement, the more information and service he perceives, and the higher his purchasing intention. Hence, hypothesis 3 (H3) was partially ed, which says that only involvement has a significant influence on website image and purchasing intention.
Table 4. Analysis of Variance: Importance of Website Image Gender
Age
Educational Career history
F
F
P
Reasonable price Quality
.09 .62
.77
Type
1.49
.43 .22
Brand/Reputation
3.04
.08*
2.74 .01** 6.11 .00*** 1.68 .11 4.28 .02** 3.94 .00*** 3.36 .04** .42 .89 6.93 .00***
Individualization Response
2.33 .01
.13 .95
1.59 1.74
.14
Easiness to return/ change goods
.00
.96
1.93
Provide function to search information Insurance
2.67
.10
1.02
.48 .52 .09
Provide multiple payment methods Provide multiple delivery methods Easiness of shopping Provide clear explanation and direction of website Reputation of store
F
P
P
P
.24
.45 .06* .14
2.18 .02** 1.79 1.75 .07* 1.14 1.94 .04** .97
.10 .34
.07*
.89
.81
.63
.69
.66
.42
1.37
.26
2.40 .02** 1.65
.09*
1.08
.38
.49 .47
3.80 .00*** 2.66 4.92 .00*** .72
.07*
1.28
.26
.45
.49
1.39
.21
1.57
.93 .11
3.41 .00*** 1.17 .32
.77
1.66
.12
.58
.56
2.36
.02
1.11
.36
2.66 .02**
3.27 .07* 2.05 4.12 .04** 1.82
.05* .08
.88 1.41
.42 .25
4.70 .00*** 2.13 .02** 2.61 .01** 1.96 .03**
.90 .94
.51
1.94
.15
2.89 .01*** 1.34
.48
.19 .02
.66 .90
.96
.46
2.27
.11
1.73
.19
.63
.73
1.17
Update rate of information 2.69 Integrity of information .85 Automate to provide 1.05 information
.10 .36 .31
2.20 .04** 1.45 1.22 .29 .45 2.13 .04** 1.31
Provide professional knowledge
F
.73
.10
*p<.l **p<.05 ***p<.01
.39
.48
2.89 .01*** 1.28 .93 .49 1.41
P
.97 3.37 .04** 1.99 6.77 .00*** 1.58 .44 .83 .42
.73 4.11 .00*** 1.32
Promotion
F
.63
.37
AD
P
Income area
2.91 .01** .17 .94 .47 2.36 .01*** 2.12 .05*
.83 .73
Atmosphere of store
F
Residential
.45
.61
.72
.60
.73
.42
.89
.31
.20 .66 .69 1.49 .14 3.39 .00*** 2.07 .05** 2.54 .01*** 2.62 .02** 1.84 .08* .91 .54 1.32 .25 2.36 .03** 1.03 .42 1.37 .23
.24
1.15
.34
.64 .27
1.38 1.39
.22 .21
.27
3.54 .00*** 2.46 .03** 1.90 .04** .85 .54 1.02 .43 1.96 .07*
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The results of further regression analysis of web site image, demigraphics, and purchasing behavior and intention, are presented in Table 6. It was found that gender affected purchasing frequency and the effects of residential area on usage hours, and on purchasing intentions. It was also found that career affected the correlation between website image and amount spent on purchasing, and that residential area affected the correlation between website image, usage hours and purchasing intentions respectively. Further analysis indicated that when browsers perceive the high convenience of the website, they may increase the amount they are willing to pay. In addition, north browsers spend more hours and have stronger purchasing intention on those websites with abundant promotion and advertising information, individualized service and quick response to client's needs and problems. This may result from the fact that north browsers are in the majority of all interviewees in the survey. Hence, hypothesis 3 (H3) was partially ed, which says that among consumer's demographics, only career and residential area have a significant influence on the correlation between purchasing behavior and intention.
Table 5. Regression Analysis: Website Image and Consumers' Personality related to Purchasing Behavior and Purchasing Intention Purchasing Sum
2.07 Intercept Website Image .02 Self-Monitoring .07 Website Image .05 X Self-Monitorinjr .21 F P 3.37 Intercept Website Image .01 Perceived Risk .09 Website Image .03 X Perceived Risk .39 F p
Website Usage Time
Website Usage Hours
Purchasing Intention
Coeffi
P
Coeffi
P
Coeffi
P
Coeffi
P
.82 .08* .44
2.57 .07 .21 .15
.49 .03** .10
.03 .12 .08
.66 .10 .35
1.64 .06 .16 .12
.41 03** .15
1.90 .00 .95 .33 .00*** .28 .04**
.22
2.76
.07*
1.39
.25
3.10
.05**
13.24 .00***
.87 .53 .82
4.86 .08 .09 .09
.46 .39 .40
1.46 .01 .04 .02
.80
3.00 .07 .05 .05
.34 .52 .50
4.01 .04 .00 .00
.52 .97 .90
.81
.77
.47
.16
.86
.11
.47
.21
.81
.93 .38 .80
3.02 .09 .16 .12
.40 .12 .29
.02 .01 .01
.80 .94 .89
2.64 .08 .01 .03
.29 .86 .75
3.50 .03
.66
.08 .04
.23 .60
.68
1.64
.20
.04
.96
.57
.57
.95
.39
Coeffi Intercept 4.05 Website Image .02 Involvement .18 Website Image .12 X Involvement 1.54 F p
Purchasing Frequencv
*p<.l **p<.05 ***p<.01
1.23
.85 .62
1.67
P
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Table 6. Regression Analysis: Website Image and Consumers' Demographics related to Purchasing Behavior and Purchasing Intention Purchasing Sum
Intercept Website Image Gender Website Image X Gender F p
Website Usage Hours
Purchasing Intention
P
Coeffi
P
Coeffi
P
Coeffi
P
Coeffi i
P
3.61 .02 .15 .09
.87 .15 .31
5.04 .06 .18 .12
.55 .08* .26
1.56 .02 .04 .04
.78 .56 .49
2.63 .08 .02 .06
.59 .82 .73
3.84 .04 .03 .03
.53 .61 .55
1.03
.36
1.97
.15
.20
.82
.58
.56
.34
.71
.94 .93 .93
4.04 .09 .00 .03
.39 .99 .78
1.35 .04 .17 .15
.59 .02** .11
2.68 .08 .04 .06
.27 .63 .51
4.15 .05 .05 .05
.48 .46 .46
.99
.39
.68
2.64
.07*
.67
.51
.48
.62
.96 .16 .29
4.00 .09 .01 .03
.38 .94 .85
1.53 .02 .03 .02
.79 .66 .77
2.72 .08 .03 .05
.29 .74 .52
4.17 .04 .03 .03
.52 .70 .68
.38
.39
.68
.13
.88
.61
.54
.29
.75
3.60 .02 .85 .31 .00*** .26 .03**
4.14 .09 .04 .05
.40 .72 .59
1.68 .02 .02 .02
.78 .81 .80
2.77 .07 .09 .09
.34 .21 .25
3.95 .05 .01 .03
.51 .87 .72
5.30 .01***
.46
.64
.06
.94
1.34
.27
.22
.80
.08 .07
.43 .29 .34
4.10 .05 .06 .06 .61
Intercept 1.71 Website Image .01 Educational History. 14 Website Image .10 X Educational History F p .99
Intercept 2.57 Website Image .04 Income .13 Website Image .11 X Income F p .79 Intercept 2.75 Website Image .04 Residential area .11 Website Image .09 X Residential area F p .53 *p<.l
Website Usaee Time
Coeffi
Intercept 2.76 Website Image .01 Age .01 Website Image .01 xAge F P .01
Intercept Website Image Career Website Image X Career F p
Purchasing Frequencv
3.96
.35
.06 .08 .08
.58 .44 .51
.46
.70
.74 .31 .52 .59
.71 .21
**p<.05 *** p<.01
1.50 .06 .16
2.44 .06
.09
.46 .03** .23
.50
2.52
.08*
1.13
.33
4.06 .10 .05 .07
.33 .62 .53
1.68 .02 .03 03
.84 .66 .60
2.37 .05 .18 .12
.40 .01** .03**
3.70 .03 .70 .19 .01*** .15 .03**
.51
.60
.13
.88
3.83
.02**
4.12 .02**
.43
.37 .39 .54
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Conclusion & Implications By means of a questionnaire survey, tbe study examines tbe correlation between website image, consumer's purchasing behavior and intention, and the effect of consumer's personality and demographics on the correlation. The conclusion is as follows. As regards website image properties, it was found that browsers pay attention to the facets of service and information such as insurance, commodity quality, easiness to return/change, reactivity, update rate of information and integrity of information. Interviewees also felt satisfied with facets of convenience and information such as reputation of store, update rate of information, clear instruction and direction, integrity of information and automatic provision of information. Among the website image facets of service and information emphasized by browsers, only the information part seems satisfactory, which suggests that professionals should improve the service function. The difference between the importance of website image is surprising due to browsers' gender, age, educational history, career, residential area and income. For example, cognitions of different interviewees toward the importance of price are distinctly different. It was found in the study that different website image facets have a significant influence on browsers' purchasing behavior and intentions. For example, convenience has a significant effect on a browser's purchasing amount, while service has a significant effect on browsers' purchasing intentions. As for personality, involvement has a significant influence on the correlation between website image and purchasing intentions. When the browser with high involvement perceives a large amount of information and service, his or her purchasing intention tends to be enhanced. According to these positive results, some suggestions are presented for Internet professionals. The first is the need to confirm the purpose and demand of targeted customers. It was found that the image facets of professionals stressed by browsers cannot comply with those satisfying them, which suggests that professionals should adapt their own model in accordance with targeted customers' demands and opinions by such methods as market surveys, to enhance their purchasing intentions. The second is to take individual differences into when developing website operation strategies. It was found in this study that involvement affects the correlation between website image, purchasing behavior and intention, a finding which suggests that professionals should consider involvement as a market segmentation variable besides the influence ofsuch demographics as age, educational history and income. In this way, the perceived risk of browsers toward Internet marketing and circumstances should be reduced. It was found in this study that browsers pay attention to such potential risks as security and function and regard them as quite likely, which suggests that Internet professionals should strengthen and improve website security, data secrecy and management, and the reliability of website content, in order to reduce browsers' risks of security and function, and stimulate their consumption and usage. Some suggestions are made for subsequent researchers. The first is to persist in monitoring Internet operations and marketing surroundings. Because the Internet is
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consistently developing in varying surroundings, any particular findings are apt to be limited by time and space (for example, the Internet environment in America is more mature than Taiwan's), making constant monitoring and research necessary. Secondly, the model of the study needs further exploration. This study suggests that the effect of website image facet on purchasing behavior and intention, and the effects of a change in Internet surroundings and in professionals' attributes in the future on browsers' purchasing behavior and intention deserve exploration. Finally, the convenience questionnaire survey adopted in the study may result in 'deviation' by interviewees, a limitation of this study. It is suggested that subsequent research widen the scope of the groups surveyed.
References Browne, B, A, & Dennis, O, K.(1997) Conceptualizing Self-Monitoring: Links to Materialism and Product Involvement, Journal of Consumer Marketing, 14(1), 3144, Cox, D, F,(1967) Risk Taking and Information Handing in Consumer Behavior, in D,F, Cox(eds,) Boston: Harvard University Press, 1-19, Donthu, N, & Garcia, A,( 1999) The Internet Shopper, Journal of Advertising Research, 39(3), 52-58, Dreze, X, & Zufryden, F,(1997) Testing Web Site Design and Promotional Content, Journal of Advertising, 26(1), 77-91, Ducoffe, R, H,(1996) Advertising Value and Advertising on the Web, Journal of Advertising Research, 36(3), 21-35, Engel, J, F,, Blackwell, R, D,, & Miniard, P W.(1990) Consumer Behavior, 6thEd,, Chicago: Dryden Press, Hansen, R, & Deutscher, T,(1977), An Empirical Investigation of Attribute Importance in Retail Store Selection, Journal of Retailing, 67, Kan, A, K, & Tang, Y, E,(2003) Typology of Online Shoppers, Journal of Consumer Marketing, 20(2), 139-156, Kenneth, E, C , Donald, B,, & Chris, F(1998) Reducing Perceived Risk Through Advertising Service Quality Cues, Journal of Professional Services Marketing, 16(2), 151-162, Korgaonkar, P, K, & Moschis, G, P,(1982) An Experimental Study of Cognitive Dissonance, Product Involvement and Product Performance, Journal of Advertising, 11(3), 32-44, Kotler(2003) Marketing Management, 10th Ed,, New Jersey: Prentice-Hall Inc, Kunkel, J, H, & Berry, L, L,(1968), A Behavioral Conception of Retail Image, Journal ofMarketing, 32, 21-27,
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Lindquist, J, D,(1974), Meaning of Image: A Survey of Empirical and Hypothetical Evidence, Journal of Retailing, 50(4), 29-38, Page, C, & Lepkowska-White, E,(2002) Web Equity: A Framework for Building Consumer Value in Online Companies, Journal of Consumer Marketing, 19(3), 231-248, Peterson, R, A, & Kerin, R, A,(1983) Store Image Measurement in Patronage Research: Fact and Artifact, In W, R, Darden & R, F. Lusch(eds.) Patronage Behavior and Retail Management, New York, NY: North-Holland, 297, Richmond, A,(1996) Enticing Online Shoppers to Buy- A Human Behavior Study, Computer Networks & ISDN Systems, 28(7-11), 1469-1480, Straits Time (2002) Global Internet s to Hit 600m This Year, 14(February), 14, Strauss, J, & Frost, R,(1999) Marketing on the Internet, New Jersey, U,S,A,: Prentice Hall, Suh, B, & Han, 1,(2003) The Impact of Customer Trust and Perception of Security Control on the Acceptance of Electronic Commerce, International Journal of Electronic Commerce, 7(3), 135-161, Tan, S, J,(1999) Strategies for Reducing Consumers' Risk Aversion in Internet Purchasing, The Journal of Consumer Marketing, 16, 163-180, Zaichkowsky, J, L,(1985) Measuring the Involvement Construct, Journal of Consumer Research, 12,341-352, Zaichkowsky, J, L,(1986) Conceptualizing Involvement, Journal of Advertising, 15(2), 4-15, Zhang, P, & Dran, G, M,(2002) Expectations and Rankings of Quality Factors in Different Web Site Domains, International Journal of Electronic Commerce, 6(2), 9-33,
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The Impact of Web Site Image and Consumer Personality on Consumer Behavior Wen-Jung Chen Ming Chuan University, Taiwan Chuan Lee Ming Chuan University, Taiwan Following the phenomenon of the "Internet Bubble," the industry's planning and execution of marketing strategies have begun to show defects. The main objective of this study is to investigate the effect of website image on consumers' behavior. In addition, the effects of consumers' personality and demographics on the website image and consumers' behaviors is examined. Through surveys, the current study found that web site image has a significant effect on the purchasing behavior and purchasing intention of consumers. This study hopes to draft an effective Internet marketing strategy by adopting a strategic viewpoint and the viewpoint of the consumer, and additionally by examining the impact of web site image and consumer personality on the personal preferences of the consumer.
Introduction Since the 1990s, the number of people who use the Internet has increased dramatically. Throughout the world, the number of Internet s was about 160 million in 1998. According the study, from International Data Corp (IDC), more than 600 million people will have accessed the Internet globally by the end of 2002 and spent more than US$ 1 trillion buying goods and services online (Straits Time, 2002). The Gartner Group estimates that the scale of the e-commerce market will be about $7.3 trillion in 2004, the Internet has been the emergent media with a greater developing potential than radio, TV and cable TV. Through the Internet, businesses provide commodity and service information to attract the consumer's attention, cause their interest, arouse their purchasing desire and bring about purchasing action, which is called the AIDA mode. It is expected to make consumers purchase or get the commodity or service to meet their needs over the shortest possible time and at the lowest cost, and maximize benefits for businesses. Different from other medias, the particular features of the Internet call for special attention in marketing programs for its virtuality and its infiuence on consumers. Kotler (2003) argues that people will establish faith, attitude and impression by action and refiection, which will infiuence their purchasing behaviors. The impression felt by individuals will impact on one's behavioral decision. Some scholars apply this concept in the retail field. For example, Kunkel & Berry (1968), Lindquist (1974) and Hansen & Deutscher (1977) explore the infiuence of web site image on consumer behavior and store selection, and develop many facets of web site image. For the Internet marketer, the website is his store, and web site image probably has a large effect on the behavior
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of consumers. But in relevant studies, the factors that make web site image attractive to consumers are rarely discussed. The first major purpose of the study is to discuss important facets of the website image; second is the effect of consumer's characteristics and personality (as involvement, selfmonitoring and perceived risks) on web site image and consumers' behaviors. Results of this study will help the development of effective Internet marketing strategies for building web site image. The article is organized as follows. In the next section we provide the theoretical background and development for hypotheses. Next, we discuss the sample, data, and statistical procedures. The article concludes with a discussion of the results of our hypotheses testing, implications of this study for practitioners and scholars, limitations of the study, and avenues for future research.
Web Site Image
Literature Review
An Internet store indicates the web site, which provides a commodity or service for clients, a chart or sheet for making an order, and accepts online orders of clients. Many scholars advance different definitions of store image. Engel, Blackwell, & Miniard (1990) define store image as the consumer's integrated perception of the property of one store. Based on many studies and opinions, web site image in our study means consumer's integrated perception of properties and functions (such as commodity price, vast information) and psychology (as web site design) which are stressed by consumers about websites providing commodities, service and order functions on the Internet. Many scholars present different store image facets, among which Kunkel & Berry (1968) and Lindquist (1974) are the most elaborate and widely cited by researches. They studied the department stores and 12 facets such as commodity price, quality, salesmen, convenience of site and service as well as 43 properties. Lindquist (1974) puts forward 9 facets as commodity, service, client, physical facilities, convenience and promotion as well as 33 properties. But because of the particular features of the Internet store, some purposes and facilities are not suitable for it, such as parking, business hours, restaurant facilities and so on. In recent years, some scholars have studied advances in the websites of Internet stores and attributes along with relevant consumer usage behavior. Ducoffe (1996) suggests that Internet store website attributes include information, entertainment and fret, which will affect the advertising value of a website and consumer's attitude. Richmond (1996) suggests attributes include payment method, special offers or discounts, interactive entertainment, and virtual reality, which will influence whether the consumer adopts online shopping, and his online time as well as amount of consumption. Dreze & Zufryden (1997) thinks the attributes include background color, image size, sound presentation, celebrity recommendation and so on, which will influence pages and the time the consumer browses the website.
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Though the store image advanced by subsequent researchers somehow complies with the features of the Internet, limited by the study range, the facet of Internet store has not developed as complete as that of the common store. Referring to the common store image facets advanced by Kunkel & Berry (1968) and Lindquist (1974), and the Internet store facets advanced by Ducoffe (1996), Richmond (1996) and Dreze & Zufryden (1997), the study develops 6 facets of the Internet store (commodity, service, convenience, store, promotion, and information) and 21 properties, with expectation to improve on website image. In the model the process of store selection advanced by Engel, Blackwell, & Miniard (1990), there are two reasons to explain whether the consumer chooses a particular store: one is the consumer's own evaluation standards, such as site, price, commodity and so on, and the other is the consumer's perception of store features, that is the store's image, Peterson & Kerin (1983) found that there was a correlation between web site image, selection standard and consumer's purchasing behavior. Thus, consistent with earlier research, it is expected that Website image has a significant influence on consumers' (a) purchasing intention, (b) purchasing behavior. Consumer's Personality Zaichkowsky (1985) defines involvement in of something felt by individuals based on one's need, value and interest in some product, service or affair. When a consumer is not interest in or familiar with ment content, information with high reliability is easier to be accepted, and the relevant ment has a good effect; while the consumer acquaints and understands the product or information well, the content cannot have much influence on him or her (Korgaonkar & Moschis, 1982), Zaichkowsky (1986) also believes that media-ecology is one of the key factors to influence the consumer's involvement in information. Because of the Internet's features of intangibility and long-distance transmission, it stresses the effect of information more than other communication media, Snyder (1974) thinks self-monitoring is the adjustment of individuals to their surroundings, also a kind of inclination to pay attention to social propriety and to modify ones behaviour to comply with it. In another words, individuals with high self-monitoring can adapt their own behavior to different situation or surroundings, while those with low self-monitoring can maintain consistent self-behavior, and emphasize individual value systems and self-expression (Browne & Dennis, 1997), Though few studies have examined correlation between self-monitoring and consumer behavior, it can be deduced that individuals with high degrees of self-monitoring are more easily influenced by Internet shopping fashions or online shopping behaviors of his/her friends. Cox (1967) defines perceived risk as a multiplicative function of the possibility of a negative result perceived by the consumer before purchase and degree of loss perceived by the consumer when he/she is displeased with a purchase. Because of the intangible services provided by the Internet, and the immature Internet circumstances of Taiwan, consumers' insecurity or uncertainty have a large effect on their purchasing intention
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and behavior. Tan (1999) found that when consumers shop on-line, they often shoulder such burdens as data safety, not being able to see the commodity before purchase and uncontrolled circumstances, which influence online purchasing intentions. Donthu and Garcia (1999) found Internet shoppers differ from non-shoppers in age and income, but do not differ from nonshoppers on education and gender. They found Internet shoppers are older and are wealthier than non Internet shoppers. We follow this result, and examine what impact age and income have on perceived web site image. The relationship between demography and web image is not adequately understood. Thus, consistent with earlier research, it is expected that consumers' personality and characteristics have a significant influence on the importance of web site image factors perceived by Internet shoppers. Finally, it is hypothesized that consumers' personality and characteristics have a significant influence on their image of websites, and consumers' (a) purchasing intention, (b) purchasing behavior.
Method To collect data to test the hypotheses, data for the study were obtained via a web survey of Internet store shoppers. Among the websites used were those from the classified introduction by Yam, and the e-Oscar E-Business Internet Golden Award held by ClubEC Netcom International, E-business Research Center of the National Taiwan University of Science and Technology, Extension Education Department of the Chinese Culture University, and the Technology Department ofthe Ministry of Economic Affairs. Those complying with the definition of an Internet store were approached to host the questionnaire on their web site. The questionnaire was hosted for five months from March 2003 to July 2003. In addition, an e-mail newsletter was sent out on 10-15 Feb. to obtain more participants. At the end, the participants were rewarded with a gift. The questionnaire, using five-point scales, was employed to collect data for the constructs of the research model. The Likert scale was used with 1 measuring "strongly disagree" and 5 measuring "strongly agree". Respondents were first asked some general questions about their Internet use and demographics. Next, they were asked short questions to measure their personality, including involvement, self-monitoring, and perceived risk. Finally, they were asked short questions about their perception toward web sites, based on their perceived importance and satisfaction with web site image factors.
Result Profile of the sample In total 751 questionnaires were received. Excluding those in which over 10% questions were not answered or personal data not provided, valid questionnaires totaled 658, comprising 87.6% ofthe total reclaimed questionnaires. Among the retained samples, females were in the majority (68.7%), whose age was 2635 (40.7%), secondly from 36-45 (21.2%) and 21-25(16.8%). Of the interviewees, business people were the most (30.3%), followed by soldiers, civil servants, teachers
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and people engaged in financial insurance (respectively 23.2%). Students ed for 15%. This demonstrates diverse career backgrounds. It seems that the need for the Internet has no direct and distinct relation to career; samples with education above college level 95% of the total, among which those above graduate institute was highest (49.7%). Interviewees from the north ed for half of the total sample (59.4%). As far as income was concerned, those between TWD 40,000 and 80,000 covered half of the total (51.3%), next was TWD 20,000 to 40,000 (17.3%) and TWD 80,000 to 100,000(15.5%). The average amount spent in NT dollars each time was 1001-2500 (15.9%), next was 2501-5000 (12.7%). As for frequency of purchase, once per month and once every 3 months were most common (respectively 15.9% and 12.7%). As far as usage of websites, 1-2 times each week was most, and 21-45 min. for each time was highest (33.6%), 5-20min. was next (21.4%). In of websites browsed, the average purchasing intention of interviewees was 4.28 (graded by 1-7), which shows their high purchasing intention. Results of Variable and Reliability Analysis The results are presented in Table 1. As regards the image of web sites, interviewees paid more attention to such web site image facets of service and information, as insurance (4.70), commodity quality (4.52), easiness to return/change goods (4.45), response (4.38), update rate of information (4.32), integrity of information (4.31), than to facets of convenience, store, ment (3.22), promotion (3.60), store atmosphere (3.70), multiple delivery methods (3.98), clear web site introduction and direction (4.03). Correspondingly, interviewees felt satisfied with such image facets of convenience and information, as store's reputation (3.59), update rate of information (3.57), clear instruction and direction (3.50), integrity of information (3.48), automatic provision of information (3.48), but dissatisfied with facets of promotion and service, ment (3.18), response (3.19), individualized service (3.21), easiness to return/change goods (3.22), brand/reputation (3.36) and insurance (3.40). It appears that among the web site image facets of service and information, professionals do well as regards information, but need to improve on service. Table 2 shows the results of variable and reliability analysis. Among the variables such as self-monitoring, perceived risk and involvement, it was found that interviewees paid most attention to such potential risks as security (53.07) and function (50.71) when browsing the Internet. As regards reliability, this study utilized the a coefficient developed by Cronbach. According to the norms developed by Cronbach (1951), a values greater than 0.70 indicate high credibility, between 0.35 and 0.70 indicate middle credibility, and lower than 0.35 indicate low credibility. The a value for each variable and each structural aspect in this study were all higher than 0.70. This exceeds the Cronbach (1951) norms, and indicates that the questionnaire in this study reached considerable internal consistency.
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Table 1. Importance and Satisfaction with Facets of Web Site Image Web Site Image Facets :Mean Insurance 4.70 Quality 4.52 Easiness to return-change goods 4.45 Response 4.38 Update rate of information 4.32 Integrity of information 4.31 Provide function to search information 4.20 Reasonable price 4.16 Reputation of store 4.13 Automate to provide information 4.10 Individual service 4.07 Provide multiple payment methods 4.04 Easiness of shopping 4.03 Provide clear explanation and 4.03 direction of web site Provide multiple delivery methods 3.98 Provide professional knowledge 3.97 Commodity type 3.96 Commodity brand/reputation 3.75 Atmosphere of store 3.70 Promotion 3.60 AD 3.22
Importance (Satisfaction S.D. Ranking Mear1 S.D. Ranking 1 .61 3.40 13 .91 2 .74 .69 3.48 6 .68 3 3.22 .88 18 .67 4 .86 3.19 20 .72 5 2 3.57 .97 .92 .71 6 3.48 6 .11 7 3.57 2 .83 11 .68 3.42 8 .73 1 .74 9 3.59 .83 .76 10 3.48 .91 6 .73 11 3.21 .87 19 .77 12 3.42 .82 11 .82 4 .79 13 3.53 .71 13 3.50 .85 5 .72 .81 .69 .79 .98 .85 .87
15 16 17 18 19 20 21
3.40 3.47 3.44 3.36 3.30 3.30 3.18
.83 .90 .78 .76 .80 .73 .11
13 9 10 15 16 16 21
Table 2. Results of Self-Monitoring, Perceived Risk anc1 Involvement and Reliability Analysis Variable and Facets Self-Monitoring Perceived risk Financial risk Functional risk Body risk Psychological risk Social risk Time risk Safe risk Involvement
No. of Items Maxi 18 items 79 464 3 items 75 3 items 160 1 item 25 3 items 179 3 items 70 2 items 50 3 items 75 10 items 70
Mini Mean 54.12 37 135 268.87 16 44.95 18 50.71 3 16.83 19 39.38 8 30.66 12 33.28 19 53.07 23 47.57
S.D. Cronbach'sa 7.43 .79 51.77 .66 11.07 .71 15.70 .68 5.94 19.42 .84 10.74 .74 8.76 .69 13.43 .80 8.75 .89
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Web Site Image and Purchasing Behavior, Intention Based on a regression analysis of web site image, purchasing behavior and intention, the results are presented in Table 3, It was found that convenience affects browser's purchasing amounts and web site usage time; store and information affect browser's purchasing frequency. Promotion affects web site usage hours; service affects browser's purchasing intention. Hence, hypothesis (HI) was partially ed, which says that website image has a significant influence on consumers' (a) purchasing intention, (b) purchasing behavior. Analysis of Web Site Image The results are presented in Table 4, With variation in the importance of web site image, its difference is obvious owing to gender, age, educational history, career, residential area and income. It was found from analysis that differences in importance cognitions of interviewees with education above college and university level towards price of commodity, commodity brand/reputation, quality, type, individualized service and response are significant; differences in importance cognition of interviewees with income above 150,000, between 20,000 and 40,000 and between 60,000 and 80,000 toward commodity price were significant. Hence, hypothesis 2 (H2) was partially ed, which says that consumers' personality and characteristics have a significant influence on the importance of web site image factors perceived by Internet shoppers.
Table 3. Regression Analysis: Website Image, Purchasing Behavior, and Purchasing Intention Purchasing Sum
Purchasing Frequency
Website Usage Time
Coefficient P Coefficient p Coefficient p 4,13
Website Usage Hours Coefficient p ,44
1,63
Purchasing Coefficient p 4,06
Intercept
2,46
Commodity
,04
,78
,16
,27
-,05
,59
,09
,35
,01
Service
-,14
,41
-,09
,61
-,14
,18
-,14
,17
,19 ,,05**
Convenience
,38
,(31** *
-,19
,17
,21
02**
,14
,13
,13
,12
Store
-,24
,11
,31
,04**
,06
,48
-,14
,11
,12
,14
Promotion
,06
,60
,19
,12
,07
,35
,18
,02**
,01
,88
Information
-,04
,78
,25
,05*
-,13
,18
,06
,53
,01
,88
L99
,08*
2,06
,07*
1,50
,18
2,04
,06*
1,32
,25
F
p
*p<,l **p<,05 ***p<,01
,95
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Web Site Image, Personality, Demographics, and Purchasing Behavior Intentions The results of the regression analysis of web site image, personality, and purchasing behavior and intention are presented in Table 5. It was found that involvement has a significant effect on the correlation between website image and purchasing intention. The effects of other personality factors on the correlation between website image and purchasing intention did not reach a significance level of 10%. From further analysis, it seems that the higher the browser's involvement, the more information and service he perceives, and the higher his purchasing intention. Hence, hypothesis 3 (H3) was partially ed, which says that only involvement has a significant influence on website image and purchasing intention.
Table 4. Analysis of Variance: Importance of Website Image Gender
Age
Educational Career history
F
F
P
Reasonable price Quality
.09 .62
.77
Type
1.49
.43 .22
Brand/Reputation
3.04
.08*
2.74 .01** 6.11 .00*** 1.68 .11 4.28 .02** 3.94 .00*** 3.36 .04** .42 .89 6.93 .00***
Individualization Response
2.33 .01
.13 .95
1.59 1.74
.14
Easiness to return/ change goods
.00
.96
1.93
Provide function to search information Insurance
2.67
.10
1.02
.48 .52 .09
Provide multiple payment methods Provide multiple delivery methods Easiness of shopping Provide clear explanation and direction of website Reputation of store
F
P
P
P
.24
.45 .06* .14
2.18 .02** 1.79 1.75 .07* 1.14 1.94 .04** .97
.10 .34
.07*
.89
.81
.63
.69
.66
.42
1.37
.26
2.40 .02** 1.65
.09*
1.08
.38
.49 .47
3.80 .00*** 2.66 4.92 .00*** .72
.07*
1.28
.26
.45
.49
1.39
.21
1.57
.93 .11
3.41 .00*** 1.17 .32
.77
1.66
.12
.58
.56
2.36
.02
1.11
.36
2.66 .02**
3.27 .07* 2.05 4.12 .04** 1.82
.05* .08
.88 1.41
.42 .25
4.70 .00*** 2.13 .02** 2.61 .01** 1.96 .03**
.90 .94
.51
1.94
.15
2.89 .01*** 1.34
.48
.19 .02
.66 .90
.96
.46
2.27
.11
1.73
.19
.63
.73
1.17
Update rate of information 2.69 Integrity of information .85 Automate to provide 1.05 information
.10 .36 .31
2.20 .04** 1.45 1.22 .29 .45 2.13 .04** 1.31
Provide professional knowledge
F
.73
.10
*p<.l **p<.05 ***p<.01
.39
.48
2.89 .01*** 1.28 .93 .49 1.41
P
.97 3.37 .04** 1.99 6.77 .00*** 1.58 .44 .83 .42
.73 4.11 .00*** 1.32
Promotion
F
.63
.37
AD
P
Income area
2.91 .01** .17 .94 .47 2.36 .01*** 2.12 .05*
.83 .73
Atmosphere of store
F
Residential
.45
.61
.72
.60
.73
.42
.89
.31
.20 .66 .69 1.49 .14 3.39 .00*** 2.07 .05** 2.54 .01*** 2.62 .02** 1.84 .08* .91 .54 1.32 .25 2.36 .03** 1.03 .42 1.37 .23
.24
1.15
.34
.64 .27
1.38 1.39
.22 .21
.27
3.54 .00*** 2.46 .03** 1.90 .04** .85 .54 1.02 .43 1.96 .07*
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The results of further regression analysis of web site image, demigraphics, and purchasing behavior and intention, are presented in Table 6. It was found that gender affected purchasing frequency and the effects of residential area on usage hours, and on purchasing intentions. It was also found that career affected the correlation between website image and amount spent on purchasing, and that residential area affected the correlation between website image, usage hours and purchasing intentions respectively. Further analysis indicated that when browsers perceive the high convenience of the website, they may increase the amount they are willing to pay. In addition, north browsers spend more hours and have stronger purchasing intention on those websites with abundant promotion and advertising information, individualized service and quick response to client's needs and problems. This may result from the fact that north browsers are in the majority of all interviewees in the survey. Hence, hypothesis 3 (H3) was partially ed, which says that among consumer's demographics, only career and residential area have a significant influence on the correlation between purchasing behavior and intention.
Table 5. Regression Analysis: Website Image and Consumers' Personality related to Purchasing Behavior and Purchasing Intention Purchasing Sum
2.07 Intercept Website Image .02 Self-Monitoring .07 Website Image .05 X Self-Monitorinjr .21 F P 3.37 Intercept Website Image .01 Perceived Risk .09 Website Image .03 X Perceived Risk .39 F p
Website Usage Time
Website Usage Hours
Purchasing Intention
Coeffi
P
Coeffi
P
Coeffi
P
Coeffi
P
.82 .08* .44
2.57 .07 .21 .15
.49 .03** .10
.03 .12 .08
.66 .10 .35
1.64 .06 .16 .12
.41 03** .15
1.90 .00 .95 .33 .00*** .28 .04**
.22
2.76
.07*
1.39
.25
3.10
.05**
13.24 .00***
.87 .53 .82
4.86 .08 .09 .09
.46 .39 .40
1.46 .01 .04 .02
.80
3.00 .07 .05 .05
.34 .52 .50
4.01 .04 .00 .00
.52 .97 .90
.81
.77
.47
.16
.86
.11
.47
.21
.81
.93 .38 .80
3.02 .09 .16 .12
.40 .12 .29
.02 .01 .01
.80 .94 .89
2.64 .08 .01 .03
.29 .86 .75
3.50 .03
.66
.08 .04
.23 .60
.68
1.64
.20
.04
.96
.57
.57
.95
.39
Coeffi Intercept 4.05 Website Image .02 Involvement .18 Website Image .12 X Involvement 1.54 F p
Purchasing Frequencv
*p<.l **p<.05 ***p<.01
1.23
.85 .62
1.67
P
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493
Table 6. Regression Analysis: Website Image and Consumers' Demographics related to Purchasing Behavior and Purchasing Intention Purchasing Sum
Intercept Website Image Gender Website Image X Gender F p
Website Usage Hours
Purchasing Intention
P
Coeffi
P
Coeffi
P
Coeffi
P
Coeffi i
P
3.61 .02 .15 .09
.87 .15 .31
5.04 .06 .18 .12
.55 .08* .26
1.56 .02 .04 .04
.78 .56 .49
2.63 .08 .02 .06
.59 .82 .73
3.84 .04 .03 .03
.53 .61 .55
1.03
.36
1.97
.15
.20
.82
.58
.56
.34
.71
.94 .93 .93
4.04 .09 .00 .03
.39 .99 .78
1.35 .04 .17 .15
.59 .02** .11
2.68 .08 .04 .06
.27 .63 .51
4.15 .05 .05 .05
.48 .46 .46
.99
.39
.68
2.64
.07*
.67
.51
.48
.62
.96 .16 .29
4.00 .09 .01 .03
.38 .94 .85
1.53 .02 .03 .02
.79 .66 .77
2.72 .08 .03 .05
.29 .74 .52
4.17 .04 .03 .03
.52 .70 .68
.38
.39
.68
.13
.88
.61
.54
.29
.75
3.60 .02 .85 .31 .00*** .26 .03**
4.14 .09 .04 .05
.40 .72 .59
1.68 .02 .02 .02
.78 .81 .80
2.77 .07 .09 .09
.34 .21 .25
3.95 .05 .01 .03
.51 .87 .72
5.30 .01***
.46
.64
.06
.94
1.34
.27
.22
.80
.08 .07
.43 .29 .34
4.10 .05 .06 .06 .61
Intercept 1.71 Website Image .01 Educational History. 14 Website Image .10 X Educational History F p .99
Intercept 2.57 Website Image .04 Income .13 Website Image .11 X Income F p .79 Intercept 2.75 Website Image .04 Residential area .11 Website Image .09 X Residential area F p .53 *p<.l
Website Usaee Time
Coeffi
Intercept 2.76 Website Image .01 Age .01 Website Image .01 xAge F P .01
Intercept Website Image Career Website Image X Career F p
Purchasing Frequencv
3.96
.35
.06 .08 .08
.58 .44 .51
.46
.70
.74 .31 .52 .59
.71 .21
**p<.05 *** p<.01
1.50 .06 .16
2.44 .06
.09
.46 .03** .23
.50
2.52
.08*
1.13
.33
4.06 .10 .05 .07
.33 .62 .53
1.68 .02 .03 03
.84 .66 .60
2.37 .05 .18 .12
.40 .01** .03**
3.70 .03 .70 .19 .01*** .15 .03**
.51
.60
.13
.88
3.83
.02**
4.12 .02**
.43
.37 .39 .54
494
International Journal of Management
Vol. 22 No. 3 September 2005
Conclusion & Implications By means of a questionnaire survey, tbe study examines tbe correlation between website image, consumer's purchasing behavior and intention, and the effect of consumer's personality and demographics on the correlation. The conclusion is as follows. As regards website image properties, it was found that browsers pay attention to the facets of service and information such as insurance, commodity quality, easiness to return/change, reactivity, update rate of information and integrity of information. Interviewees also felt satisfied with facets of convenience and information such as reputation of store, update rate of information, clear instruction and direction, integrity of information and automatic provision of information. Among the website image facets of service and information emphasized by browsers, only the information part seems satisfactory, which suggests that professionals should improve the service function. The difference between the importance of website image is surprising due to browsers' gender, age, educational history, career, residential area and income. For example, cognitions of different interviewees toward the importance of price are distinctly different. It was found in the study that different website image facets have a significant influence on browsers' purchasing behavior and intentions. For example, convenience has a significant effect on a browser's purchasing amount, while service has a significant effect on browsers' purchasing intentions. As for personality, involvement has a significant influence on the correlation between website image and purchasing intentions. When the browser with high involvement perceives a large amount of information and service, his or her purchasing intention tends to be enhanced. According to these positive results, some suggestions are presented for Internet professionals. The first is the need to confirm the purpose and demand of targeted customers. It was found that the image facets of professionals stressed by browsers cannot comply with those satisfying them, which suggests that professionals should adapt their own model in accordance with targeted customers' demands and opinions by such methods as market surveys, to enhance their purchasing intentions. The second is to take individual differences into when developing website operation strategies. It was found in this study that involvement affects the correlation between website image, purchasing behavior and intention, a finding which suggests that professionals should consider involvement as a market segmentation variable besides the influence ofsuch demographics as age, educational history and income. In this way, the perceived risk of browsers toward Internet marketing and circumstances should be reduced. It was found in this study that browsers pay attention to such potential risks as security and function and regard them as quite likely, which suggests that Internet professionals should strengthen and improve website security, data secrecy and management, and the reliability of website content, in order to reduce browsers' risks of security and function, and stimulate their consumption and usage. Some suggestions are made for subsequent researchers. The first is to persist in monitoring Internet operations and marketing surroundings. Because the Internet is
Internationaljournal of Management
Vol. 22 No. 3
September 2005
495
consistently developing in varying surroundings, any particular findings are apt to be limited by time and space (for example, the Internet environment in America is more mature than Taiwan's), making constant monitoring and research necessary. Secondly, the model of the study needs further exploration. This study suggests that the effect of website image facet on purchasing behavior and intention, and the effects of a change in Internet surroundings and in professionals' attributes in the future on browsers' purchasing behavior and intention deserve exploration. Finally, the convenience questionnaire survey adopted in the study may result in 'deviation' by interviewees, a limitation of this study. It is suggested that subsequent research widen the scope of the groups surveyed.
References Browne, B, A, & Dennis, O, K.(1997) Conceptualizing Self-Monitoring: Links to Materialism and Product Involvement, Journal of Consumer Marketing, 14(1), 3144, Cox, D, F,(1967) Risk Taking and Information Handing in Consumer Behavior, in D,F, Cox(eds,) Boston: Harvard University Press, 1-19, Donthu, N, & Garcia, A,( 1999) The Internet Shopper, Journal of Advertising Research, 39(3), 52-58, Dreze, X, & Zufryden, F,(1997) Testing Web Site Design and Promotional Content, Journal of Advertising, 26(1), 77-91, Ducoffe, R, H,(1996) Advertising Value and Advertising on the Web, Journal of Advertising Research, 36(3), 21-35, Engel, J, F,, Blackwell, R, D,, & Miniard, P W.(1990) Consumer Behavior, 6thEd,, Chicago: Dryden Press, Hansen, R, & Deutscher, T,(1977), An Empirical Investigation of Attribute Importance in Retail Store Selection, Journal of Retailing, 67, Kan, A, K, & Tang, Y, E,(2003) Typology of Online Shoppers, Journal of Consumer Marketing, 20(2), 139-156, Kenneth, E, C , Donald, B,, & Chris, F(1998) Reducing Perceived Risk Through Advertising Service Quality Cues, Journal of Professional Services Marketing, 16(2), 151-162, Korgaonkar, P, K, & Moschis, G, P,(1982) An Experimental Study of Cognitive Dissonance, Product Involvement and Product Performance, Journal of Advertising, 11(3), 32-44, Kotler(2003) Marketing Management, 10th Ed,, New Jersey: Prentice-Hall Inc, Kunkel, J, H, & Berry, L, L,(1968), A Behavioral Conception of Retail Image, Journal ofMarketing, 32, 21-27,
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Vol. 22 No. 3 September 2005
Lindquist, J, D,(1974), Meaning of Image: A Survey of Empirical and Hypothetical Evidence, Journal of Retailing, 50(4), 29-38, Page, C, & Lepkowska-White, E,(2002) Web Equity: A Framework for Building Consumer Value in Online Companies, Journal of Consumer Marketing, 19(3), 231-248, Peterson, R, A, & Kerin, R, A,(1983) Store Image Measurement in Patronage Research: Fact and Artifact, In W, R, Darden & R, F. Lusch(eds.) Patronage Behavior and Retail Management, New York, NY: North-Holland, 297, Richmond, A,(1996) Enticing Online Shoppers to Buy- A Human Behavior Study, Computer Networks & ISDN Systems, 28(7-11), 1469-1480, Straits Time (2002) Global Internet s to Hit 600m This Year, 14(February), 14, Strauss, J, & Frost, R,(1999) Marketing on the Internet, New Jersey, U,S,A,: Prentice Hall, Suh, B, & Han, 1,(2003) The Impact of Customer Trust and Perception of Security Control on the Acceptance of Electronic Commerce, International Journal of Electronic Commerce, 7(3), 135-161, Tan, S, J,(1999) Strategies for Reducing Consumers' Risk Aversion in Internet Purchasing, The Journal of Consumer Marketing, 16, 163-180, Zaichkowsky, J, L,(1985) Measuring the Involvement Construct, Journal of Consumer Research, 12,341-352, Zaichkowsky, J, L,(1986) Conceptualizing Involvement, Journal of Advertising, 15(2), 4-15, Zhang, P, & Dran, G, M,(2002) Expectations and Rankings of Quality Factors in Different Web Site Domains, International Journal of Electronic Commerce, 6(2), 9-33,
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