FACULTEIT ECONOMIE EN BEDRIJFSKUNDE

HOVENIERSBERG 24 B-9000 GENT

Tel. : 32 - (0)9 – 264.34.61 Fax. : 32 - (0)9 – 264.35.92

WORKING PAPER

Segmenting Internet shoppers based on

their web-usage-related lifestyle: a cross-cultural validation

Malaika Brengman 1 Maggie Geuens 2 Bert Weijters 3

Scott M. Smith 4 William R. Swinyard 5

December 2003

2003/205

1 Limburgs Universitair Centrum, Ghent University 2 Ghent University, Vlerick Leuven Gent Management School 3 Vlerick Leuven Gent Management School 4,5 Marriott School of Management, Brigham Young University Corresponding author: Maggie Geuens, Ghent University, Department of Marketing, Hoveniersberg 24, 9000 Gent, tel. 32 9 263 35 21, e-mail: maggie.geuens@UGent.be.

D/2003/7012/43

Segmenting Internet shoppers based on

their web-usage-related lifestyle: a cross-cultural validation Abstract

Online surveys in the US and Belgium were conducted to cross-culturally validate the Internet

shopper lifestyle scale (Smith and Swinyard, 2001). Special attention was devoted to sample,

construct and measurement equivalence. In both countries, the same six basic dimensions were

found to underlie the scale: Internet convenience, perceived self-inefficacy, Internet logistics,

Internet distrust, Internet offer, and Internet window-shopping. Except from having the same

basic meaning and structure in Belgium as in the US, the Web-usage-related-lifestyle scale also

led to the same segments in both countries. Four online shopping segments (Tentative

Shoppers, Suspicious Learners, Shopping Lovers and Business Users) and four online non-

shopping segments (Fearful Browsers, Positive Technology Muddlers, Negative Technology

Muddlers and Adventurous Browsers) are profiled with regard to their Web-usage-related

lifestyle, themes of Internet Usage, Internet attitude, psychographic and demographic

characteristics.

Keywords: Internet segmentation, Internet lifestyle, cross-cultural research, e-shoppers, scale validation

3

Segmenting Internet shoppers based on

their web-usage-related lifestyle: a cross-cultural validation Introduction

Recent findings show that despite the prevalent problems of the industry, online shopping is continuing to undergo significant growth worldwide. Responsible for the growth is the growing number of users in emerging markets that are shopping online for the first time, and the increasing confidence in online properties. According to a 36-country - 42,000 interview study by Taylor Nelson Sofres Interactive (TNSi), some 31 percent of the total adult population uses the Internet and Internet shoppers worldwide have increased by 50 percent over the past year (Pastore, 2001). Consequently, retailers can use their Internet presence to reach consumers all around the world (Quelch and Klein, 1996; Jarvenpaa, Tractinsky and Saarinen, 1999). It is therefore vital that vendors in cyberspace understand online consumers (Fram and Grady, 1995). As research on Internet consumer behavior is still very much in its infancy (Hoffman and Novak, 1997; Vellido, 2000), the identification of consumer segments, has been highlighted as one of the important and necessary avenues of research needed in the field of e-commerce (Chang, 1998). To come to a better understanding of the psychology of online shopping, Smith and Swinyard (2001) developed an “Internet shopper lifestyle” measurement instrument that was the basis of their segmentation of US online shoppers and non-shoppers. Although lifestyle research has been said to be particularly interesting in cross-cultural research (Kahle, 1999), a major criticism is that the cross-cultural validity of international life style instruments remains to be demonstrated (Brunsø and Grunert, 1995). Replicating the study of Smith and Swinyard (2001) in Belgium enables us to test for cross-cultural differences in the basic meaning and structure of Internet shopper lifestyle scale. Furthermore, in view of the fact that Belgium can be considered as an emerging market where consumers still hold a rather negative attitude toward online shopping (Geuens, Brengman and S’Jegers, 2000), it is interesting to investigate to what extent similar online segments can be distinguished in Belgium and the US. Web-Usage-Related Lifestyle: The relevance of lifestyle segmentation

Following the idea that Market segmentation can give a competitive edge, several demographic and socio-economic based Internet segmentation attempts recently emerged Crisp, Jarvenpaa and Todd (1997), and Donthu and Garcia (1999). However, demographic and socio-economic descriptors have been neither the most effective in developing segments (Wedel and Kamakura, 2000) nor a good predictor of the propensity to buy on-line (Vellido, 2000). Internet-related psychographic characteristics seem more closely related to actual online purchase behavior. Those who actually purchase online appear to have been using the Internet for a longer time (Dahlén, 1999; Novak, Hoffman and Yung, 2000), to be more frequent web users (Hoffman, Kalsbeek and Novak, 1996) and to spend more time on the Internet (Rangaswamy and Gupta 1999). Moreover, using propensity to adopt Internet shopping as a segmentation base, three segments can be discerned: a group that shops online, a group that has tried to shop online but did not succeed, and a group that has never tried and feels sceptical towards online shopping (Dahlén, 1999; Rangaswamy and Gupta, 1999). Brengman and Geuens (2002) distinguish five Internet shopping adopter groups by classifying online shoppers

4

into two groups based on their time of adoption and non-adopters into three groups based on their online shopping intentions. But again, web-based psychographics do not tell the full story. Individuals differ in important ways above and beyond demographics and psychographics. Starting from consumers’ motivations to use the Internet, McDonald (1996) segmented the Internet audience as “Avid Adventurers”, “Fact Collectors”, “Entertainment Seekers”, and “Social Shoppers”. Vellido, Lisboa and Meehan (1999) investigated consumers’ opinion on online purchasing and online vendors which seem to consist of the underlying dimensions “Control and Convenience”, “Trust and Security”, “Affordability”, “Ease of Use”, and “Effort/Responsiveness”. Using these dimensions as a segmentation base discerns seven segments: “Unconvinced”, “Security conscious”, “Undecided”, “Convinced”, “Complexity Avoiders”, “Cost Conscious”, and “Customer Service Wary”. These studies are very valuable, but one can go still further to understand online consumers. Based on the idea that “the more you know and understand about consumers, the more effectively you can communicate and market to them” (Plummer, 1974), the study of people’s values and lifestyles has become a standard tool for both social scientists and marketers around the world. Conceptual and methodological developments aside (Kahle, 1999), lifestyle segmentation instruments have shown value in segmenting markets, especially when combined with more product-specific variables, such as media-usage (Wedel and Kamakura, 2000. Internet shopper lifestyle scale measurement Smith and Swinyard (2001) have developed an instrument that encompasses interests and opinions towards the Internet, as well as web-specific behaviors that increase the likelihood of obtaining relevant online segments. The instrument contains 38 Internet shopping psychographic statements (Internet shopper lifestyle scale), 14 measures of Internet behavior, and 13 themes of Internet usage. This questionnaire was mailed to a probability sample of 4000 US online households, of which 1738 (43.5 percent) replied and e-mailed to 20,000 e-mail addresses, of which 2477 (12.4 percent). A comparative analysis across sample modes showed demographic differences, but no difference in psychographic profiles. Principal components analysis with Varimax rotation revealed six factors underlying the web-usage-related lifestyle scale. Cluster analysis based on these six factors identified four shopper and four non-shopper segments among US online households. Shoppers were defined as household heads with home Internet access who had made an online purchase in the two months preceding the study. Internet shoppers were divided into these segments: shopping lovers (11.1 percent), Internet explorers (8.9 percent), suspicious learners (9.6 percent), and business users (12.4 percent). Internet non-shoppers were similarly identified as: fearful browsers (10.7 percent), shopping avoiders (15.6 percent), technology muddlers (13.6 percent), and fun seekers (12.1 percent). Shopping lovers are competent computer users who frequently buy online and really enjoy doing so. Internet explorers believe Internet shopping is fun and could be considered opinion leaders for online buying. Suspicious learners are not very computer literate, but are open-minded for learning new things and are suspicious of giving their credit card number. Business users don’t often make personal online purchases. They mainly use the Internet for business purposes and look at the Internet in terms of what it can do for their professional life. Fearful browsers are very computer literate and often practice “Internet-window-shopping.” They do not buy online for the moment since they distrust the security on the Internet, dislike shipping charges and are reluctant to buying things without seeing them in person. Shopping avoiders will be difficult to turn into online shoppers since they do not want

5

to wait for product delivery and want to see things in person before they buy. Technology muddlers don’t spend much time online, are somewhat computer illiterate and are not interested in increasing their computer knowledge— an uninteresting target for online retailers. Fun seekers value the entertainment of the Internet, but are afraid of buying online. Furthermore, they have a relatively low education and income level leaving them not much spending power. Cross-cultural validation of the web-usage-related lifestyle instrument Collecting data in different cultures with the aim of obtaining comparative results requires that the measurement instrument possesses cross-cultural validity. The purpose of this study is to replicate the study of Smith and Swinyard (2001) in Belgium to determine the cross-cultural validity of Smith and Swinyard’s Internet shopper lifestyle scale. In doing so, both conceptual and methodological issues in cross-cultural research are considered. More specifically, sample equivalence, construct equivalence and measurement equivalence are ensured or tested following the guidelines offered by Steenkamp and Ter Hofstede (2001). Afterwards, the instrument is used to segment the US and the Belgian online audience. Sampling equivalence Sampling equivalence is not about obtaining a sample with the same socio-demographic characteristics cross-nationally, nor about drawing a sample representative for the population as a whole, but is about the representativeness of the sample with respect to the relevant target population (Kumar, 2000). The target population in this study is made up of household heads with home Internet and e-mail access. Due to the costs involved in obtaining a sufficiently large representative sample by mail, it was decided not to carry out a mail, but an online e-mail survey. Therefore, both in the US and in Belgium an online sample was drawn in a more or less identical way. The online American sample was obtained through www.postmasterdirect.com. E-mail requests to participate in the survey were sent out to 20,000 representative e-mail users in Spring 2001. The response rate was about 11 percent. In Belgium a random sample of e-mail addresses was also compiled. According to a procedure outlined in Sheehan and Hoy (1999), e-mail addresses were randomly selected from user lists, generated by means of search engines (People Finders), provided by different Belgian Internet Service Providers. An invitation e-mail to visit the site on which the questionnaire was posted was sent out to 11,500 Belgian Internet users in November 2001. 2188 correctly completed questionnaires were returned (response rate of 19.0 percent). In that the purpose of the current study is not to provide a cross-cultural segmentation, but rather to validate a scale and to compare which segments can be detected in the US and in Belgium, the sample sizes of the US and Belgium need not be proportionate to the respective population sizes (Steenkamp and Ter Hofstede, 2001). The characteristics of both the US and the Belgian online samples are described in Table 1. Despite the fact that efforts were taken to obtain representative samples, both the US and Belgian samples turn out to be non-representative of the online populations. Therefore, for subsequent analyses the US data is weighed for age and gender according to the results of Harris Interactive (Anonymous, 2001), while the Belgian data is weighed according to the results of the InSites 2001 telephone survey.

6

Table 1. Characteristics of the US and Belgian Samples

US Belgium Gender

Male 24.1 % 89.1 % Female 75.9 % 10.9 %

Age < 18 4.8 % .5 % 19-29 22.6 % 28.6 % 30-44 40.8 % 46.8 % 45-64 30.1 % 24.2 % +65 1.7 % .9 %

Education Lower 26.7 % 22.8 % Higher 73.3 % 78.2 %

Hours Online At Home Per Week ≤ 5 15.2 % 33.5 % 6-10 18.0 % 29.7 % 11-20 28.6 % 24.0 % > 20 39.2 % 12.8 %

Construct equivalence

In this study construct equivalence mainly deals with the question of whether the Internet shopper lifestyle measurement instrument is equivalent across the US and Belgium. Special attention should be devoted to items that are highly American in content and to dimensions that may not be included in the US scale while they are important for Belgium. With respect to the Internet shopper lifestyle scale, we believe construct equivalence problems are minimal. Items such as “I want to see things in person before I buy” and “I often go to the Internet for product reviews or recommendations” are assumed to have the same meaning in the US and Belgium. Only for the item “I like it that no car is necessary when shopping on the Internet” and for items referring to the price of an Internet purchase, the meaning may be different for Belgians and Americans. In a densely populated country such as Belgium, the distance to the nearest supermarket or shopping mall is on average very small, but parking troubles may make people hesitant of taking their car. In the US, it is quite the opposite, parking usually is no problem but distances are on average much larger. Concerning price, we have to take into account that purchases on the Internet typically are relatively more expensive in Belgium than in the US. The dimensions of the Internet shopper lifestyle scale are expected to cover the main interests and opinions of Belgian Internet users. A recent qualitative Belgian study in which eight focus groups were organized with regard to the “ideal future store”, revealed that to Belgians, the dimensions that mattered included convenience of the Internet (not needing a car, time-saving), the costs involved, the delivery problems, the physical experience and the security threat of insecure payments. However, no aspects were found that are not covered by the 38 item web-usage-related lifestyle scale (Geuens et al., 2000). To conclude, the construct equivalence of the web-usage-related lifestyle scale is assumed moderate to high.

7

Measure equivalence Measure equivalence pertains to whether the variables and items used in the questionnaire are comparable across the US and Belgium. For a distinction between calibration, translation, and score equivalence see Steenkamp and Ter Hofstede (2001). CALIBRATION EQUIVALENCE. Calibration equivalence deals with the question of whether monetary units, measures of weight, distance, volume, etcetera are equivalent across the US and Belgium. The US questionnaire was composed of the web-usage-related lifestyle scale, computer usage items, themes of Internet usage, Internet shopping and Internet spending questions, computer literacy items, demographics and psychographics. Some of the demographic questions or variables involved posed a problem since they are classified in a different way in both countries. Therefore, these variables were rescaled to broad categories. The education measure, for example, was revised to correspond to the norms of the two countries, where higher education for the US means that people have a higher degree than high school while for Belgium it indicates a higher degree than secondary school. Similarly, income was classified to better represent the median income of the respective countries. Spending amounts in dollars were translated in euros. Type of housing (apartment, condominium, mobile/trailer, single unit home) and zip-code were omitted in the Belgian study since they were less relevant or not applicable. TRANSLATION EQUIVALENCE. Translation equivalence pertains to verbatim and meaning equivalence. The US questionnaire was translated both in French and Dutch. A second person backtranslated the questionnaire and adaptations were made where necessary. Afterwards, the questionnaire was pretested and no problems were encountered. SCORE EQUIVALENCE. Score equivalence can be defined as the equivalence of the observed scores on the measures. Lack of score equivalence may be due to cross-national differences, (1) in response styles, or (2) in responses to specific items/questions. Response styles refer to a tendency to respond in a systematic manner to questionnaire items on some other criterion than what the items were designed to measure (Paulhus, 1991). Baumgartner and Steenkamp (2001) outline for five forms of stylistic responses (acquiescence and disacquiescence, extreme response style, midpoint responding, and noncontingent responding), as well as how to measure them and how to correct for these response style biases by regressing the raw summated scale scores on response bias indices. In both samples, our regression analyses revealed significant effects on each of the five response styles. On average the Belgian respondents scored higher on the acquiescence response style (t(4118)=-4.493), while US respondents scored higher on the disacquiescence response style (t(4305)=7.541), extreme response style (t(4128)=8.332), midpoint response style (t(3895)=13.333), and response range (t(4119)=3.299). Therefore, in subsequent analyses “corrected” instead of “observed” scores were used. But most importantly, lack of score equivalence may further arise from cross-national differences. We are especially interested in the question of whether Belgians react differently to the scale than Americans. Multigroup confirmatory factor analysis was used to test this notion, since there is general agreement that this procedure is the most powerful approach to testing for cross-national measurement invariance. As a first step, exploratory factor analysis was carried out on the US sample, followed by confirmatory factor analysis. Afterwards, multigroup confirmatory factor analysis was employed on both the American and Belgian sample.

8

Results A Varimax rotated principal components analysis extracted seven factors that explained 56 percent of the variance. A six-factor solution was identified based on the eigenvalues, screeplot, the interpretability of the factors, and the coefficient alpha’s of the separate factors. Internet Convenience, composed of the items: “for me, shopping in stores is a hassle” (reversed scaled), “I think Internet shopping would avoid the hassle of local shopping”, “I would like not having to leave home when shopping”, “I like it that no car is necessary when shopping on the Internet”, and “I like having products delivered to me at home” (Alpha = .87), Perceived Self-Inefficacy, with items: “I’d have a hard time searching the Internet to find what I need”, “I don’t think Internet stores carry things I want”, “I find the Internet ordering process is hard to understand and use”, and “I don’t know much about using the Internet” (Alpha = .79), Internet Logistics, pointing to the items: “I dislike the delivery problems & backorders of Internet buying”, “I want to see things in person before I buy”, “I don’t like having to wait for products to arrive in the mail”, “it would be a real hassle to return merchandise bought online”, and “it’s hard to judge the quality of merchandise on the Internet” (Alpha = .75), Internet distrust, reflecting the items: “I don’t want to give out my credit card number to a computer” and “I worry about my credit card number being stolen on the Internet” (Pearson r = .65, p < .001), Internet offer, identified by the items: “Local stores have better prices and promotions than Internet stores”, “I think Internet shopping offers better quality than local stores”, and “I think Internet shopping offers better selection than local stores” (reverse scored) (Alpha = .79), and Internet Window Shopping, composed of the items: “I often go to the Internet to preview products” and “I often go to the Internet for product reviews or recommendations” (Pearson r = .68, p < .001). These dimensions resemble the ones distinguished by Smith and Swinyard (2001), and several of them correspond with the ones previously found by Vellido et al. (1999): our Internet Convenience and Internet Logistics factors boil down in their Control and Convenience dimension, our Perceived Self-Efficacy resembles their Ease of Use factor, and our Internet Distrust factor corresponds with their Trust and Security factor. Our Internet Offer and Internet Window Shopping factors, however, do not appear in the Vellido et al. (1999) study, while their Affordability and Effort/Customer Service cannot be revealed in our data. Only 21 of the 38 original web-usage-related lifestyle items were retained. Confirmatory factor analysis using AMOS indicated an acceptable fit for the six-factor structure (GFI = .924, AFGI = .899, TLI = .897, CFI = .914, RMSEA = .066). If the same pattern of factor loadings can be found in the Belgian sample, the basic meaning and structure of the web-usage-related lifestyle scale is said to be equivalent in the US and Belgium. The fit of the multigroup confirmatory factor analysis model was satisfactory (GFI = .927, AGFI = .903, TLI = .887, CFI = .906, RMSEA = .046) indicating that the same factors underlie the web-usage-related lifestyle scale in Belgium as in the US. Factor loadings for both countries are shown in figure 1.

9

Figure 1. PCA result for the American and Belgian samples American sample Belgian sample

10

Online Segments in the US and Belgium As is common in segmentation studies, we clustered respondents on the factors found in the previous analysis, a practice also referred to as the tandem approach (Vellido et al., 1999; Steenkamp and Ter Hofstede, 2001). The cluster analysis was done separately for Internet shoppers and Internet non-shoppers, for each of the American group and Belgian group. Several segments resemble the ones detected in Smith and Swinyard’s previous study. Furthermore, the segment profiles are very similar for the US and Belgium. Table 2 and 3 show the profiles of the eight with respect to their scores on the Web-usage-related lifestyle dimensions, as well as on computer usage themes, psychographics, demographics, and attitude towards the Internet.

Table 2. Profiling the different Internet shopper segments

p Tentative Shoppers

Suspicious learners

Shopping lovers

Business users

US B US B US B US B US B Web-usage-lifestyle

F1: Internet convenience <.01 <.01 - + -- -- ++ ++ + - F2: Perceived self-inefficacy <.01 <.01 + + ++ + -- - - - F3: Internet logistics <.01 <.01 0 - ++ + -- -- 0 + F4: Internet distrust <.01 <.01 - - ++ ++ -- -- + + F5: Internet offer <.01 <.01 - + -- - ++ ++ + - F6: Internet window shopping <.01 <.01 - - -- - ++ ++ + +

Internet usage Shopping 1 <.01 <.01 + 0 -- -- ++ ++ - 0 Fun 2 <.01 <.01 0 - -- - + ++ + + Information 3 <.01 <.01 0 - - - + ++ 0 - Business 4 <.01 <.01 - -- -- -- ++ ++ + ++ Email .77 >.01 ns 0 ns 0 ns - ns +

Webographics Online spendings last 2 months <.01 .07 0 ns - ns + ns - ns Hours per week online .10 <.01 ns + ns + ns - ns 0 % gifts bought online <.01 <.01 0 0 -- ++ ++ -- 0 0 % gifts bought in real stores <.01 .21 + ns + ns -- ns + ns Computer literacy 5 <.01 <.01 + - - - ++ ++ + + Internet literacy 6 <.01 <.01 + - - - ++ ++ + +

Demographics Age .22 <.01 ns + ns 0 ns -- ns - Education <.01 .37 ++ ns - ns 0 ns + ns Personal income .05 <.01 + + - + + -- - 0

Attitude towards the Internet Excited to explore websites <.01 <.01 -- -- -- -- ++ + + ++ Love Internet shopping <.01 <.01 0 0 - -- ++ ++ 0 0 The web contributes to my life <.01 <.01 - - - -- ++ ++ + +

Scale : -- very low - low 0 moderate + high ++ very high

1 shopping: tickets & reservation, retail sites, auctions, financial info (alpha = .62) 2 fun: games, downloading photos and images, chat, software (alpha = .63) 3 information: news & magazines, hobby sites (r = .51, p <.001) 4 business: use Internet to conduct business, get more done, be more competitive (alpha = .65) 5 able to use word-processing programs, install computer software, configure computer drivers, fix system problems, install an operating system (alpha = .88) 6 able to email, browse the internet, use a search engine, make an online purchase, find the best price on the internet, use an internet shopping bot, find internet-retailer ratings (alpha = .81)

11

Table 3. Profiling The Different Internet Non-Shopper Segments

p Fearful browsers

Positive technology muddlers

Negative technology muddlers

Adventurous browsers

US B US B US B US B US B Web-usage-lifestyle

F1: Internet convenience <.01 <.01 - 0 + + -- -- ++ + F2: Perceived self-inefficacy <.01 <.01 - - + + + + - - F3: Internet logistics <.01 <.01 + 0 - 0 ++ ++ -- -- F4: Internet distrust <.01 <.01 + + - - ++ + -- -- F5: Internet offer <.01 <.01 - 0 + + -- -- ++ + F6: Internet window shopping <.01 <.01 + + - - -- - + +

Internet usage Shopping 1 <.01 <.01 0 0 0 0 -- - ++ ++ Fun 2 <.01 <.01 + 0 - - - - + ++ Information 3 .07 <.01 ns 0 ns - ns - ns + Business 4 <.01 <.01 + + 0 0 - - + + Email <.01 <.01 + + 0 - + 0 - 0

Webographics Online spendings last 2 months .16 <.01 ns - ns - ns ++ ns - Hours per week online .03 <.01 - - + + - + ++ - % gifts bought online .02 <.01 0 - + - - ++ 0 - % gifts bought in real stores .27 <.01 ns + ns + ns -- ns + Computer literacy 5 .01 <.01 - + + - + - + ++ Internet literacy 6 <.01 <.01 - + + - ++ - -- ++

Demographics Age .09 .66 ns ns ns ns ns ns ns ns Education .27 <.01 ns ++ ns + ns ++ ns + Personal income <.01 .32 + ns 0 ns 0 ns 0 ns

Attitude towards the Internet Excited to explore websites <.01 <.01 ++ ++ - - - - ++ ++ Love Internet shopping <.01 <.01 - + - + -- - + ++ The web contributes to my life <.01 <.01 0 0 0 0 - - + +

Scale : -- very low - low 0 moderate + high ++ very high

1 shopping: tickets & reservation, retail sites, auctions, financial info (alpha = .62) 2 fun: games, downloading photos and images, chat, software (alpha = .63) 3 information: news & magazines, hobby sites (r = .51, p <.001) 4 business: use Internet to conduct business, get more done, be more competitive (alpha = .65) 5 able to use word-processing programs, install computer software, configure computer drivers, fix system problems, install an operating system (alpha = .88) 6 able to email, browse the internet, use a search engine, make an online purchase, find the best price on the internet, use an internet shopping bot, find internet-retailer ratings (alpha = .81) Internet shopper segments Among Internet users with online shopping experience in the past two months, four segments could be identified: “Tentative Shoppers”, “Suspicious Learners”, “Shopping Lovers” and “Business Users”. Cluster one, the Tentative Shoppers, scores moderate to low on all web-usage-related lifestyle factors. Although they have shopping experience and are not suspicious of giving their credit card number, they do not really enjoy online shopping. Moreover, they are not convinced of the fact that online shopping provides more convenience or a better offer. They are not excited about exploring new websites, and do not consider the Web as a real contribution to their life.

12

Although they e-mail friends and family, they do not excel in social, informative, entertainment or business activities on the net. Representing 14 percent of the Internet shoppers in the US and 13.9 percent in Belgium, Tentative Shoppers form a rather large segment. Retailers should try to give them an added value they appreciate to increase their online shopping frequency. Cluster 2, the Suspicious Learners, are the least computer and Internet literate. From all segments they are the most fearful one and hold the most negative opinion on Internet logistics, the online shopping offer, and the convenience of the Internet. They are least likely to practice online window shopping, make the least online purchases, and use the Internet the least (whether it is for fun, information or business). Their negative attitude may be a result of their computer and Internet illiteracy. This tough segment represents 15.6 percent of the American online shoppers and 8.9 percent of Belgian shoppers. User-friendly procedures, training and guidance, and a solution for online security problems, may turn this segment in convinced shoppers although patience probably is needed. Cluster 3, the Shopping Lovers, is a dream for online retailers. They love Internet shopping and all its facets (the convenience, the offer, and the possibility of window shopping). They frequently buy online, use the Internet for information, fun and business, and are really excited about exploring millions of websites. About 9.8 percent of the US Internet shoppers belong to this segment, while in Belgium it is as large as 15.3 percent. Representing ideal opinion leaders, Internet retailers should try to encourage them even more to spread positive word-of-mouth. The fourth cluster, the Business Users, are confident computer and Internet users who use the Internet mainly for competitive and business purposes. They love to explore websites and see the Internet as a contribution to their life. Business users represent 12 percent of the US and 10.5 percent of the online Belgian shoppers. The Shopping Lovers and Business Users segments are identical than the ones described by Smith and Swinyard (2001). Suspicious Learners in the present and Smith and Swinyard’s study share some characteristics, but an important difference is that in the present study Suspicious Learners do not trust to give their credit card to the computer making it a less interesting target segment for Internet Retailers. Moreover, Smith and Swinyard’s Adventurous Explorers had to be replaced by the less Internet enthusiastic segment, Tentative Shoppers. Comparing the US and Belgian segments, especially the resemblance of the Suspicious Learners and Shopping Lovers is striking. On every variable, the differences between the segments point in the same direction, the only exception being “percent gifts bought online”. Surprisingly Belgian Shopping Lovers score extremely low on this. A possible explanation could be that Belgians are less inclined to use online shopping and express mail to send gifts (flowers, books, etc.), but to shop for gifts in traditional stores. Further research should shed more light on this. For Tentative Shoppers and Business Users a few more differences were detected, although it is clear that in the US and Belgian clusters are the same. Internet non-shopper segments Among Internet users with no online shopping experience in the past two months, also four segments could be discerned: “Fearful Browsers”, “Positive Technology Muddlers”, “Negative Technology Muddlers” and “Adventurous Browsers”. Fearful browsers (14.6 percent in the US, 10.6 percent in Belgium) are well educated, are excited of all the websites they can discover, spend a lot of time window shopping, and use the Internet for e-mail, hobbies and arts. If their Internet distrust and the logistics problems can be resolved, they may turn into an online shopping segment. Positive technology muddlers (14.8 percent in the US, 13.8 percent in Belgium) are computer and Internet illiterate. They consider online purchasing as a difficult task, but do not hold a negative attitude towards online shopping. They do not fear security or logistics

13

problems, and consider online shopping as convenient and providing a good offer. Training and guidance is required to help them to overcome their computer and Internet problems. Negative technology muddlers (9.7 percent in the US, 15.3 percent in Belgium) are also computer and Internet illiterate, and do not use the Internet for many purposes. Moreover, as opposed to Positive Technology Muddlers, they feel most negative towards online shopping (distrust the security and logistics, do not think online shopping is convenient or offers more than traditional shopping). This segment will be hard, if not impossible, to conquer by online retailers. Adventurous browsers (9.5 percent in the US, 13.1 percent in Belgium), on the other hand, are on the verge of making an online purchase. They are most positive of online shopping convenience and the online offer. They do not fear the logistics or security problems. They see themselves as computer experts, spend a lot of time window-shopping, and use the Internet for business, pleasure and information seeking activities. They are very likely to make an online purchase in the very near future and may end up as shopping lovers. Only the Fearful Browser segment is comparable with Smith and Swinyard’s study. Promising is that the non-shopping segments seem to have become more positive towards online shopping. Only Negative Technology Muddlers may not be very prone to take up an online shopping habit, while Smith and Swinyard described three of the four non-shopping segments (Shopping Avoiders, Technology Muddlers and Fun Seekers) as unattractive for online retailers. Concerning differences between the US and Belgium, we can conclude that overall the segments are rather stable, especially for web-usage related lifestyle and Internet usage characteristics. The cross-cultural segment profiles in terms of webographic and demographic characteristics differ a bit more. Conclusion The online audience is a booming market worldwide. Not surprisingly, market segmentation, in the field of electronic commerce has been called for. Because the Internet is more a global than a local issue, a segmentation tool that can be used cross-culturally is very interesting. Indeed, consumers of different countries with similar online habits may have more in common with one another than with other members of their society. However, to make cross-cultural online segmentation studies feasible, cross-cultural validity is needed. The results of the current study suggest that the Web-usage-related lifestyle scale may be such an instrument. This online study, showed that the Web-usage-related lifestyle had the same basic meaning and structure for US and Belgian consumers. In both samples, six basic dimensions underlie the scale: Internet convenience, perceived self-inefficacy, Internet logistics, Internet distrust, Internet offer, and Internet window-shopping. This result is very interesting, especially in view of the fact that Belgium can be considered as an emerging market as far as the Internet is concerned, while the US clearly is an advanced market. Although nations may be different in their progress in the Internet world, consumers that made the decision to have home Internet access may respond rather similar to online issues. Future research should concentrate on a further cross-validation of the Web-usage-related-lifestyle scale in other countries than the US and Belgium. Afterwards, an international segmentation study can be carried out over several countries.

14

References Anonymous. Geographics: U.S. Online Population Holds Steady. cyberatlas.com, 2001. Baumgartner H. Steenkamp J.B.E.M. Response styles in marketing research: a cross-national

investigation. Journal of Marketing Research 2001; 38 (May): 143-156. Brengman M. Geuens M.. Profiling Internet users based on their propensity to adopt online

shopping. Asia Pacific Advances in Consumer Research Conf., Beijing, China, May 16-18 2002.

Brunsø K. Grunert K.G. Development and testing of a cross-culturally valid instrument: Food-related lifestyle. Advances in Consumer Research 1995; 22: 475-480.

Chang, S. Internet Segmentation: State-of-the-art marketing applications. Journal of Segmentation in Marketing 1998; 2(1): 19-34.

Crisp C.B. Jarvenpaa S.L. Todd P.A. Individual differences and Internet shopping attitudes and intentions. Working paper, Austin: University of Texas 1997.

Dahlén M. Closing in on the Web consumer”, In: Bohlin, Brodin, Lundgren, Thorngren, eds. Convergence in Communications & Beyond, Amsterdam: Elsevier Science, 1999. Ch. 12.

Donthu, N. Garcia A. The Internet shopper. Journal of Advertising Research 1999; 39 (May-June): 52-58. Fram E.H. Grady D.B. Internet buyers: will the surfers become buyers?, Direct Marketing 1995; 58(6): 63-65.

Geuens M., Brengman M., S’Jegers R. A Consumer’s View on Grocery Shopping in the Future. In: Evans J.R. Berman B., editors. Retailing 2000: Launching New Millennium, vol. IX, Ohio: Academy of Marketing Science, American Collegiate Retailing Association, 2000. pp.184-188.

Hoffman D.L., Kalsbeek W.D. Novak T.P. Internet and Web use in the United States: baselines for commercial development. Communications of the ACM 1996; 39 (December): 36-46.

Hoffman D.L. Novak T.P. A new marketing paradigm for Electronic Commerce. Information Society 1997; 13(1): 43-54.

Jarvenpaa S.L., Tractinsky N. Saarinen L. Consumer trust in an Internet store: a cross-cultural validation. Journal of Computer-Mediated Communication 1999; 5 (2).

Kahle L.R. Lifestyles, values and psychographics: Perspectives from around the world. European Advances in Consumer Research 1999 ; 4: 1-3.

Kumar V. International Marketing Research, Upper Saddle River, NJ: Prentice Hall, 2000. McDonald W.J. Internet customer segments: An international perspective. In: Droge C.

Calantone R., editors. Enhancing knowledge development in marketing. Chicago, IL: American Marketing Association, 1996. pp. 338-344.

Novak T.P. Hoffman D.L. Yung Y.-F. Measuring the customer experience in online environments: a structural modeling approach. Marketing Science 2000; 19(1), 22-42.

Pastore M. Number of net users shopping online up 50 percent. Cyber Atlas 2001, June 28th, Paulhus D.L. Measurement and control of response bias. In: Robinson, Shaver, Wright, editors.

Measures of Personality & Social Psychological Attitudes. San Diego: Academic Press, 17-59.

Plummer J.T. The Concept and Application of Lifestyle Segmentation. Journal of Marketing 1974, (January), 33.

Rangaswamy A. Gupta S.. “Innovation Adoption and Diffusion in the Digital Environment: Some Research Opportunities”, eBusiness Research Center Working Paper, 02-1999, Penn State.

Sheehan K.B. Hoy M.G. Using E-mail to survey Internet users in the United States: methodology and assessment. Journal of Computer-Mediated Communication 1999; 4(3).

15

Smith Scott M. and Swinyard William R., 2001. "The Identification of Shopping Behaviors Among Internet Users", World Marketing Congress; 2001, Cardiff Business School

Steenkamp J-B E.M. and Ter Hofstede, 2001. “International Market Segmentation: Issues and perspectives”, Accepted for publication in International Journal of Research in Marketing.

Vellido A., 2000. “A methodology for the characterization of Business-to-consumer E-commerce”, Ph.D., Thesis Liverpool John Moores University, September.

Vellido A. Lisboa P.J.G. Meehan K. Segmentation of the on-line shopping market using neural networks. Expert Systems with Applications 1999; 17:303-314.

Wedel M. and Kamakura W., 2000. “Market segmentation: conceptual and methodological foundations, second edition, Kluwer Academic Publishers.

FACULTEIT ECONOMIE EN BEDRIJFSKUNDE HOVENIERSBERG 24 9000 GENT Tel. : 32 - (0)9 – 264.34.61 Fax. : 32 - (0)9 – 264.35.92

WORKING PAPER SERIES 7

01/119 N. GOBBIN, B. VAN AARLE, Fiscal Adjustments and Their Effects during the Transition to the EMU, October 2001, 28 p. (published in Public Choice, 2001).

01/120 A. DE VOS, D. BUYENS, R. SCHALK, Antecedents of the Psychological Contract: The Impact of Work Values and

Exchange Orientation on Organizational Newcomers’ Psychological Contracts, November 2001, 41 p. 01/121 A. VAN LANDSCHOOT, Sovereign Credit Spreads and the Composition of the Government Budget, November

2001, 29 p. 01/122 K. SCHOORS, The fate of Russia’s former state banks: Chronicle of a restructuring postponed and a crisis foretold,

November 2001, 54 p. (published in Europe-Asia Studies, 2003) 01/123 J. ALBRECHT, D. FRANÇOIS, K. SCHOORS, A Shapley Decomposition of Carbon Emissions without Residuals,

December 2001, 21 p. (published in Energy Policy, 2002). 01/124 T. DE LANGHE, H. OOGHE, Are Acquisitions Worthwhile? An Empirical Study of the Post-Acquisition Performance

of Privately Held Belgian Companies Involved in Take-overs, December 2001, 29 p. 01/125 L. POZZI, Government debt, imperfect information and fiscal policy effects on private consumption. Evidence for 2

high debt countries, December 2001, 34 p. 02/126 G. RAYP, W. MEEUSEN, Social Protection Competition in the EMU, January 2002, 20 p. 02/127 S. DE MAN, P. GEMMEL, P. VLERICK, P. VAN RIJK, R. DIERCKX, Patients’ and personnel’s perceptions of

service quality and patient satisfaction in nuclear medicine, January 2002, 21 p. 02/128 T. VERBEKE, M. DE CLERCQ, Environmental Quality and Economic Growth, January 2002, 48 p. 02/129 T. VERBEKE, M. DE CLERCQ, Environmental policy, policy uncertainty and relocation decisions, January 2002, 33 p. 02/130 W. BRUGGEMAN, V. DECOENE, An Empirical Study of the Influence of Balanced Scorecard-Based Variable

Remuneration on the Performance Motivation of Operating Managers, January 2002, 19 p. 02/131 B. CLARYSSE, N. MORAY, A. HEIRMAN, Transferring Technology by Spinning off Ventures: Towards an

empirically based understanding of the spin off process, January 2002, 32 p. 02/132 H. OOGHE, S. BALCAEN, Are Failure Prediction Models Transferable From One Country to Another? An Empirical

Study Using Belgian Financial Statements, February 2002, 42 p. 02/133 M. VANHOUCKE, E. DEMEULEMEESTER, W. HERROELEN, Discrete Time/Cost Trade-offs in Project scheduling

with Time-Switch Constraints? February 2002, 23 p. (published in Journal of the Operational Research Society, 2002)

02/134 C. MAYER, K. SCHOORS, Y. YAFEH, Sources of Funds and Investment Activities of Venture Capital Funds:

Evidence from Germany, Israel, Japan and the UK?, February 2002, 31 p. 02/135 K. DEWETTINCK, D. BUYENS, Employment implications of downsizing strategies and reorientation practices: an

empirical exploration, February 2002, 22 p. 02/136 M. DELOOF, M. DE MAESENEIRE, K. INGHELBRECHT, The Valuation of IPOs by Investment Banks and the

Stock Market: Empirical Evidence, February 2002, 24 p. 02/137 P. EVERAERT, W. BRUGGEMAN, Cost Targets and Time Pressure during New Product Development, March

2002, 21 p. (published in International Journal of Operations and Production Management, 2002). 02/138 D. O’NEILL, O. SWEETMAN, D. VAN DE GAER, The impact of cognitive skills on the distribution of the black-

white wage gap, March 2002, 14 p. 02/139 W. DE MAESENEIRE, S. MANIGART, Initial returns: underpricing or overvaluation? Evidence from Easdaq and

EuroNM, March 2002, 36 p.

FACULTEIT ECONOMIE EN BEDRIJFSKUNDE HOVENIERSBERG 24 9000 GENT Tel. : 32 - (0)9 – 264.34.61 Fax. : 32 - (0)9 – 264.35.92

WORKING PAPER SERIES 8 02/140 K. SCHOORS, Should the Central and Eastern European accession countries adopt the EURO before or after

accession? March 2002, 29p. (published in Economics of Planning, 2002). 02/141 D. VERHAEST, E. OMEY, Overeducation in the Flemish Youth Labour Market, March 2002, 39p. 02/142 L. CUYVERS, M. DUMONT, G. RAYP, K. STEVENS, Wage and Employment Effects in the EU of International

Trade with the Emerging Economies, April 2002, 24 p. (forthcoming in Weltwirtschaftliches Archiv, 2003). 02/143 M. GEUENS, P. DE PELSMACKER, The Role of Humor in the Persuasion of Individuals Varying in Need for

Cognition, April 2002, 19 p. (published in Advances in Consumer Research, 2002). 02/144 M. VANHOUCKE, E. DEMEULEMEESTER, W. HERROELEN, Net Present Value Maximization of Projects with

Progress Payments, April 2002, 23 p. (published in European Journal of Operational Research, 2003) 02/145 E. SCHOKKAERT, D. VAN DE GAER, F. VANDENBROUCKE, Responsibility-sensitive egalitarianism and optimal

linear income taxation, April 2002, 37p. (revised version, co-authored by R. Luttens, forthcoming in Mathematical Social Sciences, 2004).

02/146 J. ANNAERT, J. CROMBEZ, B. SPINEL, F. VAN HOLLE, Value and size effect: Now you see it, now you don’t,

May 2002, 31 p. 02/147 N. HOUTHOOFD, A. HEENE, The quest for strategic groups: Overview, and suggestions for future research, July

2002, 22 p. 02/148 G. PEERSMAN, The transmission of monetary policy in the Euro area: Are the effects different across countries?,

July 2002, 35 p. 02/149 G. PEERSMAN, F. SMETS, The industry effects of monetary policy in the Euro area, July 2002, 30 p. 02/150 J. BOUCKAERT, G. DHAENE, Inter-Ethnic Trust and Reciprocity: Results of an Experiment with Small Business

Entrepreneurs, July 2002, 27 p. (forthcoming in European Journal of Political Economy, 2004) 02/151 S. GARRÉ, I. DE BEELDE, Y. LEVANT, The impact of accounting differences between France and Belgium,

August 2002, 28 p. (published in French in Comptabilité - Controle - Audit, 2002) 02/152 R. VANDER VENNET, Cross-border mergers in European banking and bank efficiency, September 2002, 42 p.

02/153 K. SCHOORS, Financial regulation in Central Europe: the role of reserve requirements and capital rules, September 2002, 22 p.

02/154 B. BAESENS, G. VERSTRAETEN, D. VAN DEN POEL, M. EGMONT-PETERSEN, P. VAN KENHOVE, J.

VANTHIENEN, Bayesian Network Classifiers for Identifying the Slope of the Customer Lifecycle of Long-Life Customers, October 2002, 27 p. (forthcoming in European Journal of Operational Research, 2003).

02/155 L. POZZI, F. HEYLEN, M. DOSSCHE, Government debt and the excess sensitivity of private consumption to

current income: an empirical analysis for OECD countries, October 2002, 19 p.

02/156 D. O’NEILL, O. SWEETMAN, D. VAN DE GAER, Consequences of Specification Error for Distributional Analysis With an Application to Intergenerational Mobility, November 2002, 35 p.

02/157 K. SCHOORS, B. VAN DER TOL, Foreign direct investment spillovers within and between sectors: Evidence from

Hungarian data, November 2002, 29 p. 02/158 L. CUYVERS, M. DUMONT, G. RAYP, K. STEVENS, Home Employment Effects of EU Firms' Activities in Central

and Eastern European Countries, November 2002, 25 p. 02/159 M. VANHOUCKE, Optimal due date assignment in project scheduling, December 2002, 18 p.

FACULTEIT ECONOMIE EN BEDRIJFSKUNDE HOVENIERSBERG 24 9000 GENT Tel. : 32 - (0)9 – 264.34.61 Fax. : 32 - (0)9 – 264.35.92

WORKING PAPER SERIES 9 02/160 J. ANNAERT, M.J.K. DE CEUSTER, W. VANHYFTE, The Value of Asset Allocation Advice. Evidence from the

Economist’s Quarterly Portfolio Poll, December 2002, 35p. (revised version forthcoming in Journal of Banking and Finance, 2004)

02/161 M. GEUENS, P. DE PELSMACKER, Developing a Short Affect Intensity Scale, December 2002, 20 p. (published in

Psychological Reports, 2002). 02/162 P. DE PELSMACKER, M. GEUENS, P. ANCKAERT, Media context and advertising effectiveness: The role of

context appreciation and context-ad similarity, December 2002, 23 p. (published in Journal of Advertising, 2002). 03/163 M. GEUENS, D. VANTOMME, G. GOESSAERT, B. WEIJTERS, Assessing the impact of offline URL advertising,

January 2003, 20 p. 03/164 D. VAN DEN POEL, B. LARIVIÈRE, Customer Attrition Analysis For Financial Services Using Proportional Hazard

Models, January 2003, 39 p. (forthcoming in European Journal of Operational Research, 2003) 03/165 P. DE PELSMACKER, L. DRIESEN, G. RAYP, Are fair trade labels good business ? Ethics and coffee buying

intentions, January 2003, 20 p. 03/166 D. VANDAELE, P. GEMMEL, Service Level Agreements – Een literatuuroverzicht, Januari 2003, 31 p.

(forthcoming in Tijdschrift voor Economie en Management, 2003).

03/167 P. VAN KENHOVE, K. DE WULF AND S. STEENHAUT, The relationship between consumers’ unethical behavior and customer loyalty in a retail environment, February 2003, 27 p.

03/168 P. VAN KENHOVE, K. DE WULF, D. VAN DEN POEL, Does attitudinal commitment to stores always lead to behavioural loyalty? The moderating effect of age, February 2003, 20 p.

03/169 E. VERHOFSTADT, E. OMEY, The impact of education on job satisfaction in the first job, March 2003, 16 p.

03/170 S. DOBBELAERE, Ownership, Firm Size and Rent Sharing in a Transition Country, March 2003, 26 p. (forthcoming in Labour Economics, 2004)

03/171 S. DOBBELAERE, Joint Estimation of Price-Cost Margins and Union Bargaining Power for Belgian Manufacturing,

March 2003, 29 p. 03/172 M. DUMONT, G. RAYP, P. WILLEMÉ, O. THAS, Correcting Standard Errors in Two-Stage Estimation Procedures

with Generated Regressands, April 2003, 12 p. 03/173 L. POZZI, Imperfect information and the excess sensitivity of private consumption to government expenditures,

April 2003, 25 p. 03/174 F. HEYLEN, A. SCHOLLAERT, G. EVERAERT, L. POZZI, Inflation and human capital formation: theory and panel

data evidence, April 2003, 24 p. 03/175 N.A. DENTCHEV, A. HEENE, Reputation management: Sending the right signal to the right stakeholder, April

2003, 26 p. 03/176 A. WILLEM, M. BUELENS, Making competencies cross business unit boundaries: the interplay between inter-unit

coordination, trust and knowledge transferability, April 2003, 37 p. 03/177 K. SCHOORS, K. SONIN, Passive creditors, May 2003, 33 p. 03/178 W. BUCKINX, D. VAN DEN POEL, Customer Base Analysis: Partial Defection of Behaviorally-Loyal Clients in a

Non-Contractual FMCG Retail Setting, May 2003, 26 p. (forthcoming in European Journal of Operational Research) 03/179 H. OOGHE, T. DE LANGHE, J. CAMERLYNCK, Profile of multiple versus single acquirers and their targets : a

research note, June 2003, 15 p.

FACULTEIT ECONOMIE EN BEDRIJFSKUNDE HOVENIERSBERG 24 9000 GENT Tel. : 32 - (0)9 – 264.34.61 Fax. : 32 - (0)9 – 264.35.92

WORKING PAPER SERIES 10 03/180 M. NEYT, J. ALBRECHT, B. CLARYSSE, V. COCQUYT, The Cost-Effectiveness of Herceptin® in a Standard Cost

Model for Breast-Cancer Treatment in a Belgian University Hospital, June 2003, 20 p. 03/181 M. VANHOUCKE, New computational results for the discrete time/cost trade-off problem with time-switch

constraints, June 2003, 24 p. 03/182 C. SCHLUTER, D. VAN DE GAER, Mobility as distributional difference, June 2003, 22 p. 03/183 B. MERLEVEDE, Reform Reversals and Output Growth in Transition Economies, June 2003, 35 p. 03/184 G. POELS, Functional Size Measurement of Multi-Layer Object-Oriented Conceptual Models, June 2003, 13 p.

(published as ‘Object-oriented information systems’ in Lecture Notes in Computer Science, 2003) 03/185 A. VEREECKE, M. STEVENS, E. PANDELAERE, D. DESCHOOLMEESTER, A classification of programmes and

its managerial impact, June 2003, 11 p. (forthcoming in International Journal of Operations and Production Management, 2003)

03/186 S. STEENHAUT, P. VANKENHOVE, Consumers’ Reactions to “Receiving Too Much Change at the Checkout”,

July 2003, 28 p. 03/187 H. OOGHE, N. WAEYAERT, Oorzaken van faling en falingspaden: Literatuuroverzicht en conceptueel verklarings-

model, July 2003, 35 p. 03/188 S. SCHILLER, I. DE BEELDE, Disclosure of improvement activities related to tangible assets, August 2003, 21 p. 03/189 L. BAELE, Volatility Spillover Effects in European Equity Markets, August 2003, 73 p. 03/190 A. SCHOLLAERT, D. VAN DE GAER, Trust, Primary Commodity Dependence and Segregation, August 2003, 18 p 03/191 D. VAN DEN POEL, Predicting Mail-Order Repeat Buying: Which Variables Matter?, August 2003, 25 p.

(published in Tijdschrift voor Economie en Management, 2003) 03/192 T. VERBEKE, M. DE CLERCQ, The income-environment relationship: Does a logit model offer an alternative

empirical strategy?, September 2003, 32 p. 03/193 S. HERMANNS, H. OOGHE, E. VAN LAERE, C. VAN WYMEERSCH, Het type controleverslag: resultaten van een

empirisch onderzoek in België, September 2003, 18 p. 03/194 A. DE VOS, D. BUYENS, R. SCHALK, Psychological Contract Development during Organizational Socialization:

Adaptation to Reality and the Role of Reciprocity, September 2003, 42 p. 03/195 W. BUCKINX, D. VAN DEN POEL, Predicting Online Purchasing Behavior, September 2003, 43 p. 03/196 N.A. DENTCHEV, A. HEENE, Toward stakeholder responsibility and stakeholder motivation: Systemic and holistic

perspectives on corporate sustainability, September 2003, 37 p. 03/197 D. HEYMAN, M. DELOOF, H. OOGHE, The Debt-Maturity Structure of Small Firms in a Creditor-Oriented

Environment, September 2003, 22 p. 03/198 A. HEIRMAN, B. CLARYSSE, V. VAN DEN HAUTE, How and Why Do Firms Differ at Start-Up? A Resource-

Based Configurational Perspective, September 2003, 43 p. 03/199 M. GENERO, G. POELS, M. PIATTINI, Defining and Validating Metrics for Assessing the Maintainability of Entity-

Relationship Diagrams, October 2003, 61 p.

FACULTEIT ECONOMIE EN BEDRIJFSKUNDE HOVENIERSBERG 24 9000 GENT Tel. : 32 - (0)9 – 264.34.61 Fax. : 32 - (0)9 – 264.35.92

WORKING PAPER SERIES 11 03/200 V. DECOENE, W. BRUGGEMAN, Strategic alignment of manufacturing processes in a Balanced Scorecard-based

compensation plan: a theory illustration case, October 2003, 22 p. 03/201 W. BUCKINX, E. MOONS, D. VAN DEN POEL, G. WETS, Customer-Adapted Coupon Targeting Using Feature

Selection, November 2003, 31 p. (forthcoming in Expert Systems with Applications). 03/202 D. VAN DEN POEL, J. DE SCHAMPHELAERE, G. WETS, Direct and Indirect Effects of Retail Promotions,

November 2003, 21 p. (forthcoming in Expert Systems with Applications). 03/203 S. CLAEYS, R. VANDER VENNET, Determinants of bank interest margins in Central and Eastern Europe.

Convergence to the West?, November 2003, 28 p. 03/204 M. BRENGMAN, M. GEUENS, The four dimensional impact of color on shoppers’ emotions, December 2003, 15 p.

(forthcoming in Advances in Consumer Research, 2004)

03/205 M. BRENGMAN, M. GEUENS, B. WEIJTERS, S.C. SMITH, W.R. SWINYARD Segmenting Internet shoppers based on their web-usage-related lifestyle: a cross-cultural validation, December 2003, 15 p. (forthcoming in Journal of Business Research, 2004)