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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References

The study reported here examined the influence of product classification (i.e., search, experience, and credence) on consumer preferences for shopping on the Internet, and the importance of Internet retailers' attributes. In addition, the authors investigated whether the emphasis consumers place on Internet retailer attributes significantly influences their online purchase preference for the different product categories. Based on the review of the product classification literature, products are classified into four categories: search products, two types of experience products, and credence products. Data were collected from adult Internet users in two phases, through self-administered surveys. The findings of the present study support the hypothesis that product classes significantly influence consumers' online purchase preferences. Internet retailer attributes were found to be important as well. In addition, the findings confirm that the importance consumers place upon Internet retailer attributes significantly influences their online purchase preference for different product categories. Managerial and academic implications are discussed.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References

Despite the increase in use and popularity of the Internet over the last few years, the question of why consumers prefer to shop on the Internet for certain products and not for others still remains poorly understood. Empirical research on consumers' preference for shopping on the Internet has not been abundant. Until just a few years ago, the Internet had been relatively new to consumers as a shopping medium, and is still in a growth phase. Lack of familiarity with its use and the risk perceived by consumers in revealing personal information as a part of online purchasing has created uncertainty and wariness about untried e-tailers. In addition, the appeal and adoption of online shopping have been hindered by inferior Internet retail site design and functions. Finally, historical trends have not had sufficient time to accumulate to predict consumer shopping behavior (Peterson et al., 1997).

The euphoria of the early years of online shopping has been replaced by more realistic and cautious projections of e-commerce sales. While use of the Internet for the purposes of shopping, information search, communication, interaction, and entertainment has continued to increase, the actual figures for e-commerce sales have not increased as rapidly as expected. Taylor Nelson Sofres Interactive (TNSI) in June 2001 reported a fifty percent increase in the number of Internet users in thirty-six countries between June 2000 and 2001 (http://www.tnsofres.com/ger2001). However, the U.S. Census Bureau report for the first quarter of 2001 demonstrated that online retail sales in the U.S. have not increased as rapidly as predicted. E-commerce sales in the first quarter of 2001 accounted for 0.9 percent of total sales, compared to 0.7 percent of total sales in the first quarter of 2000.

As online retail sales continue to increase at a slower pace than expected, academicians and practitioners alike are searching for the product categories that consumers will shop for on the Internet. Consumers' preferences for shopping on the Internet may depend on the product type, which will in turn influence the need to obtain product information easily and cost-effectively, or to test or try products before purchasing. In addition, consumers' willingness to purchase on the Internet may vary depending on the attributes that Internet retailers offer for online-shopping (i.e., information and order services, privacy, quality of products, site quality, etc.). In the brick-and-mortar retailing and catalog shopping literature, the published research indicates that the importance of store/mail-order attributes varies by product category (Eastlick & Feinberg, 1999). Lynch, Kent and Srinivasan (2001) found that with respect to e-commerce “the impact of site quality on loyalty and purchase intentions depends on the particular product category” (p.7). Drawing upon the previous literature, the authors propose that product classifications have a significant impact on consumers' preference for shopping on the Internet, and the importance they assign to Internet retailers' attributes.

According to the Ernst and Young Global Online Retailing Report (MacIntosh, 2001), there is a discrepancy between e-tailers and customers regarding why customers visit a site. Retailers were reported to believe that factors such as convenience, reputation/trust, and customer service were most important, while customers were reported to list merchandise assortment and competitive prices as the factors that mattered most to them (McIntosh, 2001). The reason for the discrepancy is perhaps that the type of product purchased is influential in determining which attributes are more important in choosing a retailer to patronize. In the present study, the authors attempt to clarify why e-commerce is not growing as fast as expected and why consumers prefer to purchase certain products online and not others. The findings of the study reported here may assist academic researchers in marketing, advertising, and communication to build paradigms related to e-commerce. It may also help Internet retailers understand which Internet retailer attributes are important to consumers for specific product types so that they can communicate to them with proper messages and convey the appropriate product-related information on their Web sites and in their advertising.

Product Classification Theory

  1. Top of page
  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References

Although it is often speculated that the type of product purchased will have a significant impact on Internet retail patronage, little published research exists investigating the impact of the type of product-purchase on Internet shopping preferences. Several research studies acknowledge that consumers' buying behavior characteristics vary noticeably across product categories. Porter (1974) suggests that consumers may base their purchase decisions on product attributes such as brand image, reliability, styling, and availability of servicing. Porter explains that retailers control some of the attributes which consumers may want in the product. For instance, the reputation and image of a retailer may be reflected in the quality of the product or image of the brand. Recognizing that consumer buying characteristics vary by product type, Porter points out the shortcomings of classifying goods into only two categories: convenience and shopping goods. He argues that the factors such as unit price and purchase frequency do not necessarily distinguish buying behavior between the two product classes.

Although not investigated empirically, the Bloch and Richins (1983) classification of goods theory suggests that consumers' shopping efforts vary with respect to type of product. While Copeland (1923) identifies goods in separate categories such as convenience, shopping, and specialty goods, Aspinwall (1968) and Holton (1958) propose that products reflect shopping effort more appropriately if they are placed along a continuum. Klein (1998) examines the Internet's influence on information search and proposes a consumer information search model using the principles of information economics and a goods classification model based on search, experience, and credence paradigms. She demonstrates how search goods can become experience goods by three routes. Similarly, using search, experience, and credence product classification along a continuum, Brucks, Zeithaml, and Naylor (2000) develop a typology of quality dimensions for durable goods. They draw their model from Nelson (1970), who distinguishes between two categories of products, search and experience, and from Darby and Karni (1973), who add a third product category to Nelson's classification called credence goods.

The first attempts to define the term search, experience and credence were triggered by consumers' skepticism about advertisers' exaggerated claims and consumers' efforts to verify the truthfulness of those claims (Darby & Karni, 1973; Nelson, 1970). Deriving from Stigler's (1961) explanation of the “search” phenomena and the theory of economics of information, Nelson (1970) originally describes the qualities of search and experience goods in the advertising context. Nelson (1974) defines a search good as one whose qualities and suitability a consumer can determine by inspection prior to purchase of the brand. More specifically, a good is a search good when full information for dominant product attributes can be known prior to purchase, whereas an experience good is one whose qualities cannot be determined prior to purchase (Klein, 1998). Nelson (1970, 1974) classifies experience goods as experience durable (low frequency of purchase goods) and experience nondurable (high frequency of purchase goods) and tests for significant differences in the advertising sales ratios for search, and the two experience good classifications. Nelson finds significant differences among the means of advertising sales ratio for the three classifications.

Nelson defines an experience good as one whose qualities a consumer cannot determine prior to purchase. Based on Nelson's work (1974), Kline (1998) provides two criteria for classifying a good as an experience good. A good is an experience good when either (1) full information on dominant attributes cannot be known without direct experience, or (2) information search for dominant attributes is more costly/difficult than direct product experience (Kline, 1998, p. 199). Wright and Lynch (1995) broaden Nelson's definition of experience goods to include “after using” rather than “after purchasing” because of the fact that consumers might receive or test free samples in a store without purchasing the product.

Darby and Karni (1973) originated the definition of a credence good: a good such that the average consumer can never verify the level of quality of an attribute possessed by a brand or even their level of need for the quality supplied by the brand. That is, consumers will have great difficulty in evaluating the quality level of a product such as vitamins with confidence, or similarly a service such as termite fumigation or surgery, “even after purchase or consumption” (Asch, 2001; Brucks, Zeithalm, & Naylor, 2000). Ford, Smith, and Swasy (1988) characterize credence goods as those which for average consumers are mostly taken on trust (Asch, 2001). Credence qualities are primarily found in professional contexts, such as medical services and pension plans, because consumers do not usually have the knowledge to evaluate them (Asch 2001).

Shopping Preferences

  1. Top of page
  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References

Drawing from the previously published research on product typology and using Nelson's (1974) definition of search goods, Kline's (1988) two-fold classifications of experience goods, and Darby and Karni's (1973) definition of credence, the authors suggest that type of product (search, experience-1, experience-2, and credence) will influence consumers' purchase preferences as well as the importance they attach to Internet shopping-related attributes. More recently, Ford, Smith, and Swasy (1988) provided an operational definition of search, experience, and credence qualities in the context of a consumer's effort to verify advertising claims. Ford, Smith, and Swasy (1990) continued with the examination of differences in consumer skepticism for search, experience and credence advertising claims. They reported that consumers are more skeptical of experience attribute claims than search attribute claims and more skeptical of subjective claims than objective claims.

Based on the research findings about consumers' skepticism for search, experience and credence advertising claims, the authors of the present study speculate d that because of the differences in consumers' information needs for different product types, their preference for shopping online will vary across product categories. Particularly, given that the credence products are the hardest to evaluate even after purchase or consumption, consumers' desire to shop online for credence products may be lower than that their desire to shop for search or experience products. Similarly, the consumer's need to test or try out the experience products such as clothing and perfume (experience-1) or cellular phone and television (experience-2) will be higher than the need to experience search products such as books and personal computers. As a result, their desire to shop online for search products will be greater than for experience products. Based on Kline's (1988) classifications of two types of experience goods (experience-1 and experience-2), information search for experience-2 products is more costly and difficult than for experience-1 products. As mentioned earlier, experience-1 products necessitate direct experience compared to experience-2 products. Therefore, the authors speculate that consumers will be more likely to shop online for experience-1 products than experience-2 products. Generally, the type of product is expected to influence consumers' preferences for shopping with an Internet retailer significantly.

More specifically,

  • H1: Consumers' willingness to shop from an Internet retailer for search products will be significantly greater than their willingness to shop for experience-1 products.

  • H2: Consumers' willingness to shop from an Internet retailer for experience-1 products will be significantly greater than their willingness to shop for, experience-2 products.

  • H3: Consumers willingness to shop from an Internet retailer for experience-2 products will be significantly greater than their willingness to shop for credence products.

Internet Retailer Attributes

  1. Top of page
  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References

Several published studies in retailing as well as non-store retailing suggest that consumers' patronage decisions are influenced by the importance of store or non-store attributes such as perceived value and quality of products, responsiveness, convenience, company reputation, customer service, information and order services provided, merchandise assortment, salesperson interaction, shopping from home, and economic utility (Eastlick & Feinberg, 1999; Hansen & Deutscher, 1977-78). The importance of attributes in general is well-established in retailing as well as non-retailing in the context of catalog shopping. Eastlick and Feinberg (1999) investigated consumers' functional and nonfunctional shopping motivations in the context of print-catalog shopping, using sporting goods as the moderate purchase frequency product and clothing as the high purchase frequency product. They suggested perceived value, order services, and convenience as functional motives, and company responsiveness and reputation as nonfunctional motives influencing consumers' preference for catalog shopping. The findings of various studies suggest that larger merchandise assortment (Reynolds, 1974), lower prices (Korgaonkar, 1984; Reynolds, 1974), unique merchandise offerings and convenience (Gillet, 1970; Jasper & Lan, 1992; Korgaonkar, 1984) are the significant motives for catalog shopping. Consistent with the Bellenger and Korgaonkar (1980) classification of recreational shoppers, Westbrook and Black (1985) identified the most prominent motives of highly involved shoppers in the context of retail stores to be economic role enactment, choice optimization, negotiation, affiliation, and sensory stimulation.

In line with the previously published research in retailing, researchers have attempted to assess the importance of various e-tailer attributes, often with mixed and inconclusive results. For instance, Jarvenpaa and Todd (1996-1997) suggested that the most important perceived benefit of Internet shopping was convenience, while poor customer service, poorly designed Websites, and perceived risk were cited by online shoppers as negative factors. Their findings have suggested that consumers' shopping experiences on the Internet were both enjoyable and frustrating. Consumers acknowledged the savings of time and effort compared to traditional shopping, but were not satisfied with online customer service. Further, consumers perceived goods and services on the Internet to be intangible and involve risk.

Szymanski and Hise (2000) investigated the role of online convenience, merchandising (product offerings and product information), site design, and transaction security on consumers' satisfaction online. They found that convenience, product information, site design, and transaction security had a statistically significant influence on satisfaction with online shopping. Keeney (1999) studied the positive and negative aspects of Internet shopping experiences, and concluded that different customers would have different priorities for Internet shopping. Bakos (1997) asserted that the Internet lowers the search cost to acquire information about seller prices and product offerings, and reduces inefficiencies caused by the buyer's search cost. Phau and Poon (2000) found that consumers were more likely to purchase, via the Internet, products and services that have a low outlay, are frequently purchased, have intangible value proposition, and are relatively high on differentiation. Vijayasarathy and Jones (2000) examined the factors that affected consumers' attitudes and intentions to shop using print and Internet catalogs. They found that consumers thought that differences between Internet and print catalog media had to do with differences in reliability, tangibility, and consumer risk. Further, they suggested that factors such as product value, pre-order information, post-selection information, shopping experience, and risk to consumers influenced attitudes and intentions to shop using print and Internet catalogs.

Consumers' online shopping behavior and its characteristics still remain a conceptual domain that demands attention. Vellido, Lisboa, and Meehan (2000) proposed a framework to characterize Internet users' opinions on Web vendors and on-line shopping. They confirmed that consumer risk perception is the main discriminator between Internet shoppers and Internet non-shoppers. They further reported that variables such as age, household income, and Web-usage patterns do not predict Internet purchasing behavior. However, Donthu and Garcia (1999) foundd that Internet shoppers were older and earned higher income than Internet non-shoppers. Moreover, Li, Kuo and Russell (1999) found that education, convenience orientation, experience orientation, channel knowledge, perceived distribution utility, and perceived accessibility are strong predictors of online buying status such as frequent online buyer, occasional online buyer, or non-online buyer.

Rowley (1996) articulated the challenges facing the Internet retailer and shopper. The challenges include locating shops on the Internet, time involved in comparison shopping, security related to financial transactions, the customer base and profile, the nature of the shopping experience, and legal or marketplace control or lack thereof. Rowley pointed out that the Internet has not yet accommodated to the cultural and social issues associated with shopping. Reichheld and Schefter (2000) argued that price is not an important factor for customer loyalty for e-tailers, but trust is the determining factor that is built based on “the delivery of a consistently superior customer experience.”

What has not been investigated extensively is the role that product classification plays in determining the importance of the Internet retailers' attributes. The research findings by Lynch, Kent and Srinivasan (2001) indicated that impact of Internet retailers' attributes such as trust, affect (entertainment), and site quality vary across different product categories. Given the lack of “physical exposure and contact,”Lynch, Kent and Srinivasan (2001) pointed out that trust as an attribute may affect shoppers' willingness to purchase online. More specifically, they anticipated that “trust may be more important in online buying of high-touch (experience) products” (p.17). The results of their study also indicated that site quality explains loyalty or purchase intentions for high-touch goods such as t-shirts (experience products) but not for low-touch goods such as CD players (search products).

Thus, drawing from the literature on consumers' motivations towards store and non-store attributes and their preference for type of products, the authors speculate that product categories will have a significant impact on the importance consumers attach to Internet retailers' attributes, Similarly, consumers' emphasis on Internet retailer attributes will significantly influence their preferences for purchasing online across different product categories. The hypothesized importance of different Internet retailer's attributes and product categories is exhibited in Table 1.

Table 1.  Hypothesized importance of Internet retailer attributes across product categories.
SearchExperienceCredence
ConvenienceMerchandise AssortmentInternet Retailer Reputation
Home ShoppingCustomer ServiceCustomer Service
Order ServicesPerceived Value/InternetPerceived Value/Internet
Economic UtilityRetailer ResponsivenessRetailer Responsiveness
Security/PrivacySecurity/PrivacyInformation Services
  Security/Privacy

More specifically

  • H4: For search products, attributes such as convenience, home shopping, order services, and economic utility will be more important than the other Internet retailer attributes.

  • H5: For experience, products Internet attributes such as merchandise assortment, customer service, and perceived value/responsiveness will be more important than the other Internet retailer attributes.

  • H6: For credence products, Internet attributes such as reputation, customer service, perceived value/responsiveness, and information services will be more important than the other Internet retailer attributes.

  • H7: Security/privacy will be equally important across the different product categories.

  • H8: The importance consumers assign to Internet retailer attribute will significantly influence their preference for purchasing online across different product categories.

Method

  1. Top of page
  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References

Research Instruments and Data Collection

The data for the study was gathered in two stages. In the first stage, data was collected to select products from each of the four classes—search, experience-1, experience-2, and credence—for use in the subsequent study. Thirty graduate students from a large urban university in the Southeastern United States participated in the first phase of the study. The average age of the students was in the mid-thirties. The sample consisted of an equal number of males and females, from clerical, supervisory, and technical professions. Each had used the Internet before on a regular basis. Each of the students was provided with four descriptions of product types as found in the literature (Ford, Smith, & Swasy 1990; Klein, 1998; Nelson, 1974). After each description they were asked to list four products that they believed represented each category. The four descriptions are given below:

The first product class description was for a search product/service whose relevant attribute information could be easily obtained prior to use or purchase. They would be confident of making the purchase decision without using/sampling the product/service prior to its use or purchase.

The second product class description was for an experience-1 product/service whose relevant attribute information could not be known until the product was used. They would not be confident of making the purchase decision without using/sampling the product/service prior to its purchase.

The third product class description was for an experience-2 product/service for which it was more difficult/costly to get the relevant attribute information than actual product/service experience prior to its purchase. They would not be confident of making the purchase decision without using/sampling the product/service prior to its purchase.

Finally, the fourth product class description was for a credence product/service for which relevant attribute information was not available prior to as well as after the use of the product/service. They would not be confident of their purchase decision even after using/sampling the product/service.

A total of 64 products were listed by the respondents under the search product category, 70 products were listed under the experience-1 category, 87 products were listed under the experience-2 category, and 69 products were listed under the credence product category. Based on the examination of the product list provided by the respondents, the authors selected the two most representative products for each product class (see Table 2) to be used in the second stage of the study. We also focused on those products that are more readily available on the Internet so as to make the second stage of the study more relevant to the respondents.

Table 2.  Product categories.
CategoryProducts
SearchBooks and Personal Computers
Experience-1Clothing and Perfume
Experience-2Cell phone and Television
CredenceVitamins and Water Purifier

Second Stage Sample

In the second phase, the data for the study was collected in two major metropolitan areas with a population of 3.9 million residents in the Southeastern United States. The respondents were contacted during different days of the week and different times of the day. The survey was administered only to those who were at least 18 years of age and had used the Internet regularly in the past. The demographic profile of the respondents is shown in Table 3 & 4. In comparing our sample to the Census 2000 of the local area we found that our sample was skewed towards the more highly educated and higher income respondent, and to skilled as well as managerial types of occupations. This was expected as we surveyed only those who were regular users of the Internet. However, the sample profile is similar to the national profile of the Internet users as reflected in the last GVU survey.

Table 3.  Sample demographic characteristics. Note: Percentages do not add to 100 per cent due to missing values. Footnote: Total N=559
Demographic CharacteristicsPercentage
Gender 
 Male43.6
 Female55.6
Occupation 
 Unskilled30.4
 Sales/Office work20.6
 Skilled17.4
 Supervisory non-technical2.5
 Supervisory technical3.4
 Professional10.2
 Managerial2.9
Education level 
 Attended high school3.0
 High school graduate8.8
 Attended technical/trade school0.9
 Technical/Trade school graduate2.5
 Attended college52.6
 College graduate22.7
 Post graduate8.9
Annual household income ($) 
 Under 20,00021.6
 20,000 to 40,00026.7
 40,001 to 60,00020.8
 60,001 to 80,00012.2
 80,001 to 100,0008.1
 Over 100,0009.1
Table 4.  Sample demographic characteristics (continued). The demographic profile of sample respondents of four product categories (actual count).
Demographic CharacteristicsSearch ProductsExperience-1 ProductsExperience-2 ProductsCredence ProductsChi-Sq. Statistics (sig. level)
Gender     
 Male585470622.530
 Female73868468(0.470)
Occupation     
 Unskilled31385249 
 Office/Sales35302624 
 Skilled21293116 
 Supervisory Non-Technical255221.076
 Supervisory Technical7642(0.276)
 Professional16101516 
 Managerial5434 
Education     
 Attended high school4634 
 High school graduate6151612 
 Attended trade school022120.621
 Trade school graduate5441(0.299)
 Attended college68707680 
 College graduate31283929 
 Postgraduate/professional1715144 
Household Income     
 Under 20K31292437 
 20-40K29394734 
 40,001-60K3033322114.076
 60,001-80K18191615(0.520)
 80,001-100K11101311 
 Over 100K1391910 

Second Stage Survey Instrument

The survey instrument had four sections. In section one, we asked each respondent to indicate his or her preference for purchasing from the Internet each of the eight products selected from stage one of the study. The preference for purchasing each product from an Internet Retailer was measured on a five point scale of (1) “May Never Buy” to (5) “May Prefer Buying” for each of the selected eight products. In the second section, we asked the respondents to rate how important each Internet Retailer attribute would be for purchasing the two products from one of the four product classifications on a scale of (1) “Not Important at All” to (5) “Extremely Important.” For example, one group of respondents was asked hoe, assuming they wanted to purchase a product such as a book or personal computers (search) from an Internet retailer, they would rate the importance of various features in choosing a specific Internet retailer to purchase from. The subjects were given a list of 50 statements designed to capture 11 different dimensions of internet retailers. The eleven dimensions that fifty statements measured were Perceived Value (6 items); Convenience (6 items); Economic Utility (6 items); Home Shopping (3 items); Merchandise Assortment (4 items); Order Services (4 items); Company Clientele (4 items); Information Services (7 items); Customer Service (4 items); Security/Privacy (3 items), and Internet Retailer Reputation (3 items). The items were chosen from an exhaustive search of the literature in the area of Internet retailing as well as direct marketing (e.g., Eastlick & Feinberg, 1999; Vijaysarathy & Jones, 2000). A separate set of respondents was asked for the same information but assuming they were purchasing products such as clothing and perfume (experience-1). A third group of respondents was asked for the same information but assuming they were purchasing products such as cellular phones and televisions (experience-2). The fourth group of respondents was asked for the same information assuming they were purchasing products such as vitamins and water purifiers (credence). The administration of the survey instruments was randomized to prevent a response bias. There were no statistically significant differences in the demographic profiles of the four groups of respondents. A total of 559 valid surveys was obtained. The breakdown of the sample size in each product category is as follows: 132 for books and personal computers, 142 for clothing and perfume, 153 for cellular phone and television, and 131 for vitamins and water purifier. The third section of the questionnaire pertained to a variety of shopping orientation statements measured on a Likert scale of (1) “Strongly Agree” to (5) “Strongly Disagree.” Finally, the fourth section pertained to demographics.

Analysis

A first step in the analysis was aimed at ensuring that the survey instrument captured all the attributes of Internet retailer. Hence, Principal Component Analysis with Varimax rotation was performed on the fifty importance of Internet retailer attribute items to examine their discriminant and convergent validity. The analysis produced a clean factor structure with items loading on the appropriate components Table 5. Ten dimensions were obtained with Eigenvalues greater than 1, and 66 percent of the cumulative variance was explained. Only seven items did not load on the underlying dimensions. Among those, two items, “The Internet retailer is well known” and “The Internet retailer is in business for a long time,” that were originally expected to measure IR Reputation loaded on Company Clientele. These two Internet Retailer (IR) Reputation and Company Clientele items were combined under IR Reputation because they seemed more suitable to measure that component. The items, “The Internet retailer allows me to comparison shop” and “Third party evaluations about the Internet retailer's business practices are easily available,” loaded on Information Service rather than Economic Utility and Security/Privacy, respectively. These two items were retained where they loaded because they seemed to be relevant to the respondents' information search; therefore, they were suitable items to measure the Information Service component.

Table 5.  Factor analysis of the Internet retailer attribute ratings
ItemsPerceived Value/Company Responsiveness α= .89Company Clientele/IR Reputation α= .85Convenience α= .88Info. Service α= .84Cust. Service α= .85Security/Privacy α= .80Home Shopping α= .88Order Services α= .80Merch. Assort. α= .76Econ. Utility α= .77
Return for credit.787         
Easy exchange.778         
Dependable products731         
Stands behind.730         
Value for money.663         
Quality products.655         
Friends like IR .865        
Friends know .865        
Friends recommend .864        
IR well-known .612        
Long-time .501        
People like me shop .472        
Saves time  .814       
Saves effort  .807       
Allows shop whenever  .689       
Find what I want  .509       
Downloads fast  .469       
Easy to surf  .464       
Comparison guides   .640      
Product availability   .569      
Search function   .541      
Reviews/evaluation   .535      
Comparison shop   .456 (.529)    
Business practices   .436 (.496)    
Trace   .429      
Close-up   .343*      
Provides info   .462*      
Access to a salesperson    .793     
Responds quickly    .755     
Talk with salesperson    .752     
Knowledgeable    .654     
Keeps info. confidential     .666    
Keeps promises     .627    
Safe to buy     .625    
Privacy of home      .805   
Safety of home      .770   
Comfort of home      .753   
Place orders       .721  
Allows credit card       .713  
Cancel orders       .558  
1-800 freecall       .557  
Many brands        .731 
Wide selection        .632 
Latest styles        .613 
Rare products        .497 
Careful shopper*        .439* 
Free of sales tax         .689
Free shipping         .618
Real bargains         .565
Competitive prices         .498

The items, “The Internet retailer provides information” and “The Internet retailer Web site provides close-up product images,” loaded on both Security/Privacy (slightly higher) and Information Service. Since the two items did not measure either component rigorously, they were eliminated. The item, “Using the Internet retailer, I feel like a careful shopper,” loaded on Merchandise Assortment rather than Economic Utility. The term “careful” may have caused ambiguous interpretation among the respondents. Therefore, it was eliminated. A total of three items out of fifty were deleted. The rest of the items that loaded on the appropriate components produced ten dimensions with high Chronbach Alphas in the range of 0.76 through 0.89. Thus, our analysis confirmed the presence of 10 attributes labeled as follows: 1) Perceived Value, 2) Internet Retailer Reputation, 3) Convenience, 4) Information Services, 5) Customer Service, 6) Security/Privacy, 7) Home Shopping, 8) Order Services, 9) Merchandise Assortment, and 10) Economic Utility. A scale for each attribute was created by summing up the responses to the items loading on the corresponding factor.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References

The preference responses to the two products in each of the four categories were combined to measure the overall preference for purchasing products from each category on the Internet. The reliability alphas of the four product preferences were in the range of 0.73 to 0.91. The first, second and third hypotheses were tested through six paired t-tests evaluating whether each of the four product classes was significantly different from the others, and an F-statistic was calculated to test overall significance. The F statistic indicated overall significance, F(4, 2227) = 48.76 at p < 0.01 level. All six paired t-tests indicated that there were significant differences (p < .01) in the purchase preferences of the four product categories. The results of the t-tests and F tests provided partial support for the three hypotheses. Descriptive statistics including the means and standard deviations are exhibited in Table 6. Hypotheses 1 and 2 were supported; i.e., the mean value of preference for search products was significantly higher than the mean value of preference for experience-1 products, and the mean value of preference for experience-1 products was significantly higher than the mean value of preference for experience-2 products. Hypothesis 3 was partially supported; i.e., the mean value of preference for experience-2 products was significantly different but lower than the mean value of preference for credence products. This shows that products that are costly and difficult to evaluate are the least likely to succeed on the Internet. Examples of the experience-2 products may be automobiles or home appliances such as washers, dryers, air conditioners, television, and refrigerators. These products are costly/difficult to ship because of their weight and size. In addition, they cannot be tried before the purchase. Although automobiles can be test-driven at dealerships, the actual performance cannot be judged by the consumer until use and/or purchase.

Table 6.  Preference for purchasing each product class from Internet retailers.
Search Products (Books & Personal Computers)Experience-1 Products (Clothing & Perfume)Experience-2 Products (Cell Phone & TV)Credence Products (Vitamins & Water Purifier)
  1. a Mean value of the combined preference for the two products

  2. b Standard deviation of the combined preference for the two products.

  3. Footnote: F(4, 2227)=48.76, significant at p < 0.01.

  4. Hypothesis 4 through 7

6.6655a5.51825.36535.5261
(1.904)b(2.1992)(2.2739)(2.2555)
N=553N=550N=553N=555

To test hypotheses 4 through 7, ten separate one-way Analyses of Variance were performed in which product category was the independent variable and the summated score of each importance of Internet retailer attribute component was the dependent variable. Additionally, mean values of each of the 10 Internet retailer attributes for each product class were compared to determine the rank order order of importance for the Internet retailer attributes for each of the product categories.

The results of the ten separate Analyses of Variance to test hypotheses 4 through 7 indicated that product category produced significant differences in two Internet retailer attributes on a summated scale. The two components were Perceived Value (F= 2.87, p < 0.05) and Merchandise Assortment (F= 2.561, p < 0.05). The comparison of the mean values of each Internet retailer attribute importance scores across all product types indicated that Perceived Value was the most important attribute followed by Information Services, followed by Convenience and then IR Reputation Table 7. These attributes were followed by Order Services, Economic Utility, Customer Service, Merchandise Assortment, Security/Privacy, and Shopping from Home. For Search and Credence product types, Information Services had the highest importance, followed by Perceived Value. However, for the Experience-1 and Experience-2 product classes, Perceived Value had the highest importance followed by Information Services. Convenience, IR Reputation, and Order Services ranked third, forth, and fifth respectively for all product types. The remaining rankings of relative importance are shown in Table 7.

Table 7.  Importance ratings of ten Internet retailer attribute components by product categories.
 SearchRank OrderExp.-1Rank OrderExp.-2Rank OrderCredenceRank OrderSig.
  1. **Significant at 0.05 level based on the ten ANOVA tests.

Perceived Value26.42226.93126.86125.6010.04**
Info. Services26.56126.21226.84225.8730.39
Convenience24.57325.17325.03324.1740.24
IR Reputation19.98420.60420.47419.3840.23
Order Services16.61516.67516.37515.8550.15
Economic Utility15.64615.67615.67614.9860.23
Customer Service15.15715.16715.57714.7870.36
Merchandise Assort.14.95815.27815.82814.9480.05**
Security/Privacy13.44913.56913.50913.0390.18
Home Shopping11.331011.621011.481010.93100.26

Internet retailer attributes Convenience, Order Services, and Economic Utility for the search products, Perceived Value/Responsiveness, Merchandise Assortment, and Customer Service for the experience-1 and experience-2 products, and Information Services, Perceived Value/Responsiveness, Reputation, and Customer Service for credence products were rated as important by the respondents. Therefore, hypotheses 4, 5, and 6 were partially supported. Because Security/Privacy was an equally important attribute across all product categories, hypothesis 7 was also supported.

Hypothesis 8

Hypothesis 8 was tested through a two-tailed correlation analysis to determine whether significant associations or correlations exist between the importance of Internet retailer attribute components and online purchase preference for each product class.

The results of the two-tailed correlation analysis indicated that product purchase preference from an Internet retailer had significant associations with Internet retailer attributes table 1. Consumers' online purchase preference for a search product category had significant correlations with Perceived Value, Convenience, Information Services, Customer Service, Home Shopping, Order Services, Merchandise Assortment, and Economic Utility at the 0.01 level, and IR Reputation at 0.05 level. Privacy/Security did not have a significant association with online purchase preference for the search products.

With respect to consumers' online purchase preference for the experience-1 product class, Perceived Value, Information Services, Order Services, Merchandise Assortment and Economic Utility had a significant influence at (p < 0.01), and Convenience, Privacy/Security, and Home Shopping at the 0.05 level. IR Reputation and Customer Service did not have a significant association with the online purchase preference for experience-1 products.

For experience-2 products, IR Reputation, Home Shopping, and Order Services had a significant influence on online purchase preference at the 0.05 level, while Customer Service and Merchandise Assortment were significant at the 0.10 level. Perceived Value, Convenience, Information Services, Privacy/Security, and Economic Utility had no significant effects on online purchase preference for the experience-2 product class.

For the credence products, IR Reputation, Convenience, Information Services, Home Shopping, Order Services, Merchandise Assortment and Economic Utility had a significant influence on online purchase preference at the 0.05 level, and Privacy/Security at the 0.10 level. Perceived Value and Customer Service had no significant effects on online purchase preference for credence products.

In order to ensure that the results were not an artifact of the demographic variables of gender, occupation, education, and income the results were confirmed by running correlations while partialling out the effects of the four demographic variables. The results remain almost identical except for change in the significance of six correlations out of a total of 40. Those changes were primarily the artifact of lower sample sizes as the missing values for the four demographic variables lowered the sample size without changing the correlation coefficients in substance. Thus, the authors found support for hypothesis 8 without the moderating effects of the demographic variables.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References

The findings of the present study support the hypothesis that product categories of search, experience and credence significantly influence consumers' purchase preference from an Internet retailer, as well as the importance consumers place on certain Internet retailer attributes and that the relative importance attached to this attributes vary significantly across the four product classes (search, experience-1, experience-2, and credence). These results have important implications for Internet retailers as well as non-Internet retailers. It is evident from the support of the first through third hypotheses that consumers prefer to purchase certain products online. Specifically, products of the search category such as books, personal computers, and computer accessories, for which information about the characteristics of the product and content are easily/cheaply available prior to purchase, are the most preferred for online purchase. The results of the present study indicate that the search category products are more likely to succeed than the experience and credence category products since online shoppers feel more confident about purchasing them online. The findings are consistent with those of Ford, Smith, and Swasy (1990) that consumers give more credibility to search than experience and to experience than credence advertising claims. The findings also support Nelson's theory that consumers value advertising claims differently across product categories.

Therefore, the results suggest that Internet retailers improve their Web sites by disclosing the relevant product information to support their advertising claims such as price, discount amounts and the time period for the discounts, shipping and handling costs, return and exchange policy, merchandise dimensions, color, manufacturer's name and product model/serial numbers, and even third party evaluations or reviews for the products and/or services.

Rowley (1996) indicates that the primary reason that books and CD/music are the most popular items sold online compared to other goods is the e-tailers' good database management that provide easy access to the relevant information 24 hours a day and seven days a week. Therefore, prompt updating of the information on e-tailers' Web sites is important.

The results of the present study support the hypothesis that online shoppers prefer to purchase experience-1 products online less than they do the search products. The reason may be that information provided online for experience-1 products such as clothing and perfume may not be sufficient for online shoppers to purchase them online with confidence. Shoppers would like to try the product in the store before making a purchase decision. If shoppers cannot find the right size, kind or color, they may choose to order the product on the Internet after seeing and trying it in the store. Alternatively, if shoppers know what they want, or have purchased the products previously, they may choose to buy those products online. Some retailers even provide electronic kiosks inside their stores that allow consumers to read about the product and order the right size or the color of their choice. When consumers order a product through either print catalogs or the Internet, they generally have an idea what the product looks like or what attributes it has because they may have already seen it in the catalogs, magazines, stores, or on television.

Although consumers may prefer to purchase only certain types of products on the Internet, it could be possible for e-tailers to motivate consumers to purchase difficult-to-sell products online by understanding and providing the attributes that are important to consumers. The significant results for hypotheses 4, 5, 6, and 7 provide important insights to retailers and academics concerning the Internet retailer attributes that are important to consumers for each product category.

For search products such as book and personal computers, and credence products such as vitamins and water purifiers, Information Services, Perceived Value/Responsiveness, Convenience, and Reputation, Order Services, and Economic Utility were the six most important Internet retailer attributes. This shows that providing time and effort savings through the product-offering comparison guides with a search function to compare prices and relevant product information easily, maintaining a good reputation, offering relevant information and reviews about the products, providing accessto speak a salesperson, offering competitive prices, and providing free shipping are important when customers purchase search and credence products online.

For the credence products that have different product attributes than the search products, if consumers cannot judge the quality or relevant attributes of a product even after they purchase and use it, they may be hesitant to order it on the Internet. For instance, the quality of credence products such as vitamins, water purifiers, or age-defying cream is not known even after they are consumed and experienced. In that case, consumers may make their decisions based on the important attributes of the Internet retailer distributing the product. Therefore, the authors believe that Internet retailer's reputation, its ability to save consumers' time and effort by providing detailed product information, fast and easy access and navigation on its Website play an important role in influencing consumers' online patronage decisions.

For experience-1 products such as clothing and perfume and experience-2 products such as cellular phone and television, Perceived Value/Responsiveness was the most important attribute. This means that providing the ease and ability for shoppers to exchange or return the product for full credit, and offering dependable and quality products with value are the most important attributes for e-tailers who sell experience products online. In addition, providing comparison guides with a search function, product availability information, third party reviews and evaluations, and the ability to trace the product during shipment are also regarded as very important retailer attributes.

The results of this study also indicate that privacy/security is not as important an attribute to consumers as the other eight attributes across all product categories. This shows that consumers are becoming more confident in purchasing online. That is because they may believe that Internet retailers will secure online shoppers' private information and keep their promises. Since Reputation is rated as the fourth important attribute, as long as the Internet retailers maintain their good reputations, Security/Privacy concerns will be reduced in importance.

In addition, the findings of the hypothesis 8 testing confirm significant associations between the importance of Internet retailer attributes and preference for shopping online for different product categories. The findings are consistent with the previously published research that explains shopping motives. Eastlick and Feinberg (1999) foundd that Perceived Value, Order Services, Convenience, Company Responsiveness, and Reputation were the most important attributes that influenced consumer shopping motives for mail-order catalog shopping. The Internet is a different shopping medium than a print-catalog, with many functions in common, such as providing convenience for shoppers but lacking the ability to offer customers a chance to try the products prior to purchase. Differences in the importance of retailer attributes between the Internet and print catalogs are expected. Regardless, the results of the present study confirm that Perceived Value/Company Responsiveness and Information Services are the most two important attributes followed by Convenience, Reputation, Order Services, and Economic Utility as the major Internet retailer attributes that influence consumers' preference to shop online. Information Services and Economic Utility are the attributes that are more pertinent to the Internet than print catalogs because of the ability that the Internet provides with its search engines to compare prices, product features, shipping costs, and third party reviews and evaluations about the products. The Internet retailers that provide these attributes in addition to the most important attributes will be more likely to succeed.

Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References

We believe that the study findings will be of interest to academicians as well as practitioners in the field of e-commerce. In this study, we tried to explain the Internet attributes that are important to online shoppers when they purchase different types of products, motivated by the facts reported by reputable marketing research firms and the U.S. Department of Commerce that Internet usage has been increasing while Internet sales to consumers have not been increasing at the predicted rate. Understanding and identifying Internet retailer attributes that can be improved to encourage increased online transaction volume has become a priority for e-tailers. In our analyses, we provided evidence that the product category does influence the preference of consumers to shop from an Internet retailer, and identified the attributes that e-tailers need to be aware of in order to produce repetitive sales by online shoppers.

References

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  2. Abstract
  3. Introduction
  4. Product Classification Theory
  5. Shopping Preferences
  6. Internet Retailer Attributes
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. References
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