Information Management & Computer SecurityE-commerce policies and customer privacy: a longitudinal study (2000-2010)Mayur S. Desai, Kiran J. Desai, Lonnie D. Phelps,

Article information:To cite this document:Mayur S. Desai, Kiran J. Desai, Lonnie D. Phelps, (2012) "E‐commerce policies and customer privacy:a longitudinal study (2000‐2010)", Information Management & Computer Security, Vol. 20 Issue: 3,pp.222-244, https://doi.org/10.1108/09685221211247325Permanent link to this document:https://doi.org/10.1108/09685221211247325

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E-commerce policies andcustomer privacy: a longitudinal

study (2000-2010)Mayur S. Desai

Jesse H. Jones School of Business, Texas Southern University,Houston, Texas, USA, and

Kiran J. Desai and Lonnie D. PhelpsCollege of Business, McNeese State University, Lake Charles,

Louisiana, USA

Abstract

Purpose – The present research is an updated and expanded continuation of an article by Parayitamet al. from 2008. The purpose of this study is to examine several internet policies and whether thecommunication of these policies to the customer has significantly changed during a ten year period.

Design/methodology/approach – The study defines published policies of how a companyoperates with respect to different factors. The policies examined are privacy, security, shipping,returns, and warranty. Each of the policies described above were then rated as per the rating scaledefined by the authors. The 525 e-commerce sites studied were divided into service and product sites,respectively. The e-commerce sites were also separated into 28 industry groups. The data were alsocollected on some of the other factors that were important in this study.

Findings – E-commerce companies do not fully inform their customers. The results showed nosignificant relationships between the policy ratings and any of the other factors taken into account.

Research limitations/implications – The net incomes collected were the companies’ entire income,not exclusively from online sales. The present study used an unbalanced sample size consisting of moreproduct sites than service sites.

Practical implications – People doing business over internet with e-commerce companies need toread the privacy policy carefully and should be aware of how their information will be used by thee-commerce companies.

Originality/value – The study provides valuable information about e-commerce companies incommunicating their customer service policies and very little changes have taken place in the lastten year period.

Keywords Electronic commerce, Internet policies, Computer privacy, Consumer protection, Privacy

Paper type Research paper

IntroductionThe government and e-commerce businesses are making an effort to aide consumers byproviding tips for online shopping. The US Department of Homeland Securityacknowledged that, “attackers can take advantage of online shoppers,” and published,“Cyber Security Tip ST07-001,” to guide consumers through the online purchasingprocess. The American Bar Association posted similar advice on their web site, tellingpeople what to look for when doing business online, because, “Web sellers are not [yet]required by law to maintain the privacy of people who shop and/or order fromtheir sites.” Recently the Obama administration called for legislation to protect

The current issue and full text archive of this journal is available at

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Received 29 October 2011Revised 30 January 2012,6 March 2012

Information Management &Computer SecurityVol. 20 No. 3, 2012pp. 222-244q Emerald Group Publishing Limited0968-5227DOI 10.1108/09685221211247325

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consumers’ privacy. In the Senate, John Kerry is trying to draft a privacy bill of rightswith the support of John McCain (Editorial “A new internet priavacy law?” – NYTimes.com, published: March 18, 2011). The Electronic Privacy Information Center said that itis considering a complaint to the Federal Trade Commission (FTC) that Google’s newsearch feature raises privacy and antitrust concerns (www.usatoday.com/tech/news/story/2012-01-11/google-social-search/52506216/1 (accessed January15, 2012)). This is alegitimate concern for the consumers since several of the e-commerce retailers use Googlesearch engine. USA Today, January 16, 2012 reported that Zappos, the Amazon-ownedshoe and apparel retailer’s, more than 24 million of its customer accounts had beencompromised. This indicates that in spite of the online retailers publishing the privacypolicy there is a continued fear about personal information being hacked.

Previous studies examined customers’ opinion on the need of policies. Our studydiffers in that we look at what companies are actually doing in providing those policies.The present study examined 525 companies over a ten-year period from 2000 to 2010.The five characteristics of these internet policies were studied based on the publishedpolicies appearing on the internet sites of these companies. These examined policiesincluded statements regarding privacy, security, shipping, returns, and warranty. Theprimary focus of this study was to determine if internet companies are concernedabout providing their customers with the best possible service and at the same timeaddressing the above issues. One criteria used to measure these parameters was to seeif these companies have made significant changes regarding the communications oftheir company policies during the three-year period of this study. In addition, the studyanalyzed the e-commerce policies by comparing product providers and serviceproviders, respectively.

The present research is an updated and expanded continuation of theParayitam et al. (2008) article “E-commerce policies, customer privacy and customerconfidence.” This is a follow-up of study that examined several internet policies andwhether the communication of these policies to the user or customer of the serviceprovided by a company providing a service or merchandise has significantly changedduring a two three-year periods between 1999-2001 and 2005-2007.

Online shopping growth, privacy policy, and consumer trustOnline shopping continues to grow every year. According to analytics-based findingsby IBM, the US online retail sector delivered double-digit growth in December 2010compared to the same period in 2009. According to IBM’s findings both Black Friday2010 and Cyber Monday 2010 delivered strong double-digit growth over 2009(www-03.ibm.com/press/us/en/pressrelease/33365.wss (accessed September 19, 2011)).On December 20, 2010, Forbes reported that online retail spending for the 47 days ofthe shopping season through December 17 totaled $27.46 billion, according to new datafrom ComScore, up 12 percent from the comparable period a year ago. Sales in the latestweek were $5.15 billion, up 14 percent from the comparable week in 2009 (www.forbes.com/sites/ericsavitz/2010/12/20/online-holiday-retail-spend-up-12-through-dec-17/(accessed September 19, 2011)). US online retail spending reached a record $43.4 billionduring Q4 2010, according to new data from comScore. This figure is up 11 percentfrom $39 billion in Q4 2009 and 35 percent from $32.1 billion in Q3 2010 (Table I)(www.marketingcharts.com/direct/online-retail-spending-sets-record-15971 (accessedSeptember 19, 2011)). The report further added that while the past five quarters

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represent a marked improvement from the four quarters preceding them, retaile-commerce growth rates were still significantly below those reported during 2007,which ranged from 17 to 23 percent. They are more in line with the respective 11 and 13percent growth rates reported during the first two quarters of 2008. According to thereport ComScore predicts continued double-digit year-over-year growth in US retaile-commerce spending for the upcoming quarters of 2011. These reports imply that theonline shopping has been growing steadily over the past few years.

The US Department of Commerce reports that since 2000, in the USA alone, thepercentage of total retail sales comprising e-commerce transactions has increasedfrom 0.6 to 3.4 percent. In 2005, for example, e-commerce transactions accounted for22 percent of the total amount of business-to-business transactions (Stylianou, 2008).

Online privacy policy is understood as the set of statements explaining howconsumers’ privacy is dealt with and protected by the web merchant (Meziane andKasiran, 2008). The growth in online retail spending may imply that consumers aregaining trust in retailers’ online privacy policies. However, one of the most frequentlycited concerns about online shopping is the security of monetary transactions (Mezianeand Kasiran, 2008). When shopping online, consumers search for information on risksand benefits and weigh them against each other to reach a decision (Meziane andKasiran, 2008). Consumers have usually a number of questions on the shipping,service, payment and product return policies (Ranganathan and Ganapathy, 2002).Another concern of the consumer is the identity theft. The crime of identity theft hasreached a crisis level in American society. The annual report by the FTC finds identitytheft complaints, for the seventh year in a row, the number one concern of USconsumers accounting for 36 percent of the 674,354 complaints received. According tothe FTC, credit card fraud (25 percent) was the most common form of reported identitytheft, followed by phone or utilities fraud (16 percent), bank fraud (16 percent), andemployment fraud (14 percent) (www.epic.org/privacy/pdf/dpsa2007.pdf). Accordingto the FTC, the annual cost to the US economy is over $50 billion, with $5 billionincurred by victims of identity theft. Identity theft affects 10 million people each yearand the FTC reports that identity theft is routinely the number one complaint cited byconsumers (www.epic.org/privacy/idtheft/EPIC_FTC_ID_Theft _Comments.pdf).

Wirtz et al. (2007) conducted an online survey of 182 net shoppers wherebyrespondents were asked to recall a recent web site registration that required them toprovide personal information online. The study found that increased concern forprivacy resulted in higher power-enhancing responses such as the fabrication ofpersonal information, use of privacy-enhancing technologies and refusal to purchase.Storey et al. (2009) study found that the more dependent a firm is on consumer personal

Billions ($)2009 2010 Pct change (%)

January-October actual $100.7 $109.9 9Holiday season forecast (November-December) $29.1a $32.4b 11b

Notes: aActual; bforecastSource: comScore, Inc.; www.comscore.com/Press_Events/Press_Releases/2010/11/comScore_Forecasts_11_Percent_Groth_for_2010_Holiday_E-Commerce_Spending

Table I.Online non-travel (retail)holiday consumerspending excludesauctions and largecorporate purchasestotal US –home/work/universitylocations

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information, the more likely it is to provide strong privacy protection. The studyfurther states that firms that are less dependent on customer information should beviewed with greater scrutiny by customers, because they can afford to use thatinformation for short-term gain at the expense of the customer’s privacy. Meinert et al.( January-March 2006) in their study of 261 students found that respondents were mostwilling to provide information, given a strong privacy statement. The study furtherrevealed that moderate statements proved to be more effective than a weak or no-policystatement. On the other hand, a weak privacy statement was no more effective than notproviding any policy statement. Based on the mean responses for providing personalinformation, it appears that many internet users, particularly younger, well educated,and affluent consumers, would be unwilling to provide personal information online,except when offered a strong privacy policy statement. Van Slyke et al. ( June 2006)study indicate that concern for information privacy (CFIP) affects risk perceptions,trust, and willingness to transact for a well-known merchant, but not for a lesswell-known merchant. In addition, the results indicate that merchant familiarity doesnot moderate the relationship between CFIP and risk perceptions or CFIP and trust.Tsai et al. ( June 2011) study indicates that when privacy information is made moresalient and accessible, some consumers are willing to pay a premium to purchase fromprivacy protective web sites. Cultural variations among consumer seem to have aninfluence on their perception and trust in conducting online shopping. For example,based on the Eurobarometer survey data, Sun (2011) study examined the roles ofexperience and cultural propensity to trust in consumer confidence in conductinge-commerce. Compared with consumers in a low-trust culture (France), consumersfrom a high-trust society (West Germany) exhibit more confidence in conductinge-commerce. This cultural difference is only evident among consumers with no priore-commerce experience but disappears among consumers with prior e-commerceexperience. There is no interaction effect of culture and experience. While consumerconfidence in conducting e-commerce declines with age within each culture, consumersof the same age groups tend to have higher confidence in conducting e-commerce inWest Germany than in France.

In summary, it is found that concerns still exist for the consumers shopping online.These data indicate that consumers’ confidence conducting business online depends onseveral factors such as strength of privacy statement, age of consumers, culturalvariations among consumers, fear of identity theft, and explicit or implicit privacystatement. This implies that the businesses and the government need to understand thereasons for consumers’ concerns about online privacy and accordingly make an effortto alleviate the consumers’ fear and gain trust. The next section discusses the responseto address the consumers’ online concerns by the businesses and the government.

Response to address consumers’ online shopping concerns by businessesand governmentAdvanced technology has increased the capacity of online companies to collect,maintain, analyze and profit from vast amounts of data gathered when consumer visitweb sites (Miyazaki and Krishnamurthy, 2002; Eid and Trueman, 2004). This hasraised both consumer and government concerns regarding online privacy protection.There are a number of studies that suggest ways of gaining trust among consumersshopping online. For example, Pollach (2005) suggests that retailers should behave in

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an ethical manner by posting clearly and unequivocally worded privacy policies. Thestudy further suggests that both privacy advocacy groups and policy makers couldempower internet users by educating them about the use of privacy-enhancingtechnologies such as anonymizers. There is an effort to examine the internet andprivacy policy to protect and provide consumer safety and confidence (Furnell et al.,2001). Regulators can reduce consumer concern by further defining and improving thelegal framework for protecting consumer privacy on the internet (Wirtz et al., 2007). Inaddition, governments should consider overseeing third-party privacy accreditation aswell as firm and industry self-regulation. Gao and Wu’s (2010) study resultsdemonstrates that online marketers and web site designers alike should pay keenattention to elements that may influence an internet shoppers’ cognitive perceptions inorder to nurture consumer’s trust in e-commerce and realize the full potentials of doingbusiness online. The growth of online retailing is forcing businesses to provide bettersupport for consumer decision making on e-commerce web sites. Consequently,researchers in information systems and marketing have been focusing on investigatingthe effectiveness of web-based decision support systems (WebDSS) in providing accurateand satisfying choices for customers (Gudigantala et al., 2008). Gudigantala et al.’s (2008)study showed that compensatory WebDSS performed better than non-compensatoryWebDSS in terms of decision quality, satisfaction, effort, and confidence. The studyexamined 375 US-based company web sites and found that though moderate levels ofsupport exists for consumers to implement non-compensatory choice strategies; virtuallyno support exists for executing multi-attribute-based compensatory choice strategies(Gudigantala et al., 2008).

Unless online retailers cooperate and abide by the laws to protect the consumers’privacy, it is difficult to gain the full trust of the consumers in online shopping. Peeples(2002) suggests that guarantees, seals of approval, testimonials, etc. can help easeconsumer worries since most sites lack track records. Customers weigh the cost ofproducts against the benefits of obtaining them over the internet or by catalog.Lower-priced items may have a greater chance of selling over the internet since thebenefit of shopping in this manner can outweigh the risk of losing a small sum ofmoney. Through these purchases, a company has the opportunity to demonstratequality service and trustworthiness and build a foundation for bigger-ticket itemspurchases (Peeples, 2002). Van Slyke et al. ( June 2006) indicate that mechanismsdesigned to reduce information privacy concerns (e.g. privacy seals) may actually bemost effective when they reduce risk perceptions and increase trust in the vendor.Taylor et al. (2009) suggest that using implicit data collection to personalize onlineinteractions may be risky. Taylor et al. (2009) further indicate that when consumersperceive that information about them is collected implicitly, consumers are concernedabout privacy in spite of their trust in the vendor.

Extant literature in physical retailing suggests that warranties can be a significantvariable in reducing consumers’ perceived risk. Lwin and Williams (2006) examined therole of web site warranties in risk reduction and how warranty information interactswith retailer reputation and brand name as two other risk relievers in an online shoppingenvironment. Their results suggest that warranties can make a positive differencefor online retailers with strong reputations with respect to perceived risk, perceivedproduct quality, and purchase intentions. However, consumers are less influencedby warranty information when dealing with online retailers with weak reputations.

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For the other extrinsic cue, however, their study found that warranty information doesnot have an effect when dealing with brand names, suggesting that a brand name’simpact on online risk reduction remains regardless of the presence of warrantyinformation (Lwin and Williams, 2006).

In response to efforts to legislate the online collection and management of consumerinformation, several private sector organizations have developed self-regulatoryinitiatives in the form of an internet privacy seal of approval program (Miyazaki andKrishnamurthy, 2002). Another way for policy makers to reduce the power of webmerchants in data handling would be to pass privacy legislation, as European Unionmember states have done. The USA primarily has self-regulation in regard tocompanies’ use of cookies. However, the FTC does take measures against companiesthat do not abide by their own privacy policies. In contrast, the European Union hasmore rigid laws regarding the use of cookies by the e-commerce vendors and does notallow the collection of personal information of their users (Hormozi, 2005). Generally,the differences between the USA and the European Union in the e-commerce contextare characterized by the latter being far more consumer protectionist than the former(Stylianou, 2008). While the US tends to focus more on issues like fraud andcyber-crime, the EU has geared many of its policy initiatives toward the ultimate goalof increasing the overall level of e-commerce by building consumer confidence in theelectronic marketplace (Stylianou, 2008).

In summary, there is an ongoing effort on part of both the businesses andgovernment to protect and gain trust of the consumers in online shopping. The nextsection discusses the research methodology and analysis of the results based on thedata collected in studying online policies of the companies studied.

Research methodology and companies studiedThe research method is organized into problem statement, subjects and samplingmethod, research design and data collection/analysis discussion.

Problems statementThe basic premise of this study is that e-commerce web sites do not adequately publishand explain their consumer policies. The study investigates the relationships betweenpolicies and the methods of payments offered by the e-commerce retailers and the linkbetween policies and the company’s net incomes. The research also intends to verifywhether online companies do have and display their policies in such a way thatconsumers are fully informed on every step of the purchasing process.

Subjects and sampling methodThe data for this study were collected from 525 e-commerce web sites. These sites weredivided into two groups – service providers and product providers (See the Appendixfor the list of providers). If the sites provided and sold intangible goods then they wereclassified as service providers and if they provided and sold tangible goods they wereclassified as product providers. Out of 525 e-commerce web sites, 140 sites were serviceproviders and 385 were classified as product providers. The data were furtherseparated into 52 product e-commerce companies and 18 service e-commercecompanies. The most recent annual net incomes for each company was also collected.

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A portion of the service web sites did not have shipping, returns, and warranty policiesbecause these policies did not apply to their operations.

Research designThe study defines published policies as the descriptions of how a company operateswith respect to different factors. The policies examined for this study are privacy,security, shipping, returns, and warranty (Table II). Privacy policies delineate therequirements an organization follows for complying with privacy regulations anddirectives. Security policies provide the set of laws, rules, and measures that regulatehow an organization manages and protects customer information. Shipping policiesoutlines shipping methods such as business days to process before shipping and anyrestrictions on shipping methods. Returns policies describe information pertaining theexchange and return of products by customers. Finally, warranty policies guaranteesatisfaction of item purchased.

Each of the policies described above were then rated as per the rating scaledescribed in Table III. The purpose of the rating was to determine how muchinformation each company was supplying its consumers.

In order to compare the accessibility of each policy by e-commerce site a rating scalewas developed. The rating scale indicates how convenient and easy or difficult it wasfor the customer to access or search a particular policy item. The rating scale anddescription of the scale is shown in Table IV.

Privacy Sharing contact information with other businessSecurity Security measures to prevent the loss, misuse and alteration of customer information

once it is stored in business recordsShipping Shipping methods including business days to process before shipping and any

restrictions on shipping methodReturns Exchange and return methodsWarranty Satisfaction guarantee behind item purchased

Table II.Policy categories

0 No policy stated1 One sentence stating that there is a policy. Actual policy not presented2 One or two sentences stating a brief policy3 Paragraph explanation of the policy. It states how it affects the customer4 Page in depth explanation of the policy. Additional contacts are given5 Extensive explanation of the policy and additional contacts

Table III.Rating scales usedin rating policies

0 Policy page is blank, or no policy mentioned1 Policy under other name (e.g. disclaimer, terms and conditions)2 Policy under FAQ3 Policy under customer service4 Policy on the first page, but hidden5 Policy on the first page, clearly visible

Table IV.Rating scales usedin rating accessibilitiesfor each policy

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As discussed in the previous section, the 525 e-commerce sites were divided intoservice and product sites, respectively. The e-commerce sites were also separated into28 industry groups. The industry group classification was based on the operationsthey performed. Each group was assigned a code. For example, if a company soldbooks, they were a product site with industry code 7, which includes sites which sellbooks. Table V provides a complete list of 28 industry groups.

The data were also collected on some of the other factors that were important in thisstudy. These factors include: updated/effective date of privacy policy, methods ofpayment and net income. Methods of payments accepted include: credit card,E-check/wire transfer, PayPal, gift card/coupon, company credit, bill me later/Ebillme,Google checkout, and money order/cash on delivery. They were measured by using thescale in Table VI. The company web sites were also measured by how often theirprivacy policy updated. The rating scale seen in Table VII was used to collect thesedata. By using Yahoo’s finance page, we collected the most recent annual net incomesfor the 70 publicly traded companies.

Data collection/analysisThe data were collected on companies that either sold products or services online. Eachcompany was identified as product site if a consumer could buy a product from itshome page. The company was identified as a service site if it provided a link tomanufacturer’s site where the consumer could buy the service directly. Any company

1 Construction/home improvement2 Decor3 Outdoor hobbies (sports)4 Auto5 Beauty6 Jewelry7 Books8 Art9 Toys

10 Printing11 Entertainment12 Gifts13 Department stores14 Travel15 Car rental16 Electronics17 Pharmacy18 Clothing19 Shoes20 Pet products21 Food/beverage22 Hygiene23 Baby24 Health25 Energy26 Social networks27 Networking28 Construction/home improvement/decor

Table V.Industry codeclassification

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that performed a service, such as tailoring or networking, was listed as service sites.The data were collected by visiting each online company’s home page. Each of the fivepolicies examined for this study was located on the web sites and was given a rating asper the scale rating showed in Table III. The ease of accessibility rating was assignedto each policy based on the scale found in Table IV. If a company provided an effectivedate or last updated date on its privacy policy, it was noted and rated based on thescale shown in Table VII. The number of different methods of payment for eitherproduct or service sites were also noted based on the scale displayed in Table VI. Anypolicies or other variables examined in this study that were not applicable to acompany were given a rating of N/A. Each company was assigned an industry codebased on the information in Table V. Finally, the most recent annual net incomes werecollected for the companies which are publicly traded.

The data were compiled into one file, and then separated into product sites andservice sites. In order to use a single consistent rating score, a composite rating wascalculated per web site based on the number of policies applicable to each site. For siteshaving all five policies, each policy was weighted 20 percent (100 percent/5) whichresulted in the following formula:

Weighted Average ¼ ððPrivacy Policy rating*20%Þ

þ ðAccessibility of Privacy Policy rating*20%ÞÞ

þ ððSecurity Policy rating*20%Þ

þ ðAccessibility of Security Policy rating*20%ÞÞ

þ ððShipping Policy rating*20%Þ

þ ðAccessibility of Shipping Policy rating*20%ÞÞ

þ ððReturns Policy rating*20%Þ

þ ðAccessibility of Returns Policy rating*20%ÞÞ

þ ððWarranty Policy rating*20%Þ

þ ðAccessibility of Warranty Policy rating*20%ÞÞ:

0 No method of payment available1 One method of payment available2 Two methods of payment available3 Three methods of payment available4 Four methods of payment available5 Five methods of payment available6 Six methods of payment available7 Seven methods of payment available8 Eight methods of payment available

Table VI.Rating scales usedin rating methodsof payment

0 N/A No date available1 8 , 10 years ago 2000-20022 6 , 8 years ago 2003-20043 4 , 6 years ago 2005-20064 2 , 4 years ago 2007-20085 0 , 2 years ago 2009-2010

Table VII.Rating scales used inrating updated date

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For the service sites, some policies were not applicable. For example, a company whichprovides information or ideas as a service would not have shipping, returns, orwarranty policies. Therefore, sites with four applicable policies were weighted25 percent. Sites with three applicable policies were weighted 33 percent. Sites withtwo applicable policies were weighted 50 percent. There were no sites with only oneapplicable policy.

The companies were then ranked from highest to lowest weighted average. We thenbegan to determine if the policies had a significant relationship with other variables inthe study. We hypothesized that companies with higher weighted averages would havemore recently updated their policies. Therefore, based upon our scales, a significantcorrelation, r, would be close to positive 1.

The weighted average of each company’s privacy policy was calculated with thefollowing formula:

Weighted Average of Privacy Policy¼ðPrivacy Policy rating*50%Þ

þðAccessibility of Privacy Policy rating*50%Þ:

The analysis of the companies’ weighted averages of privacy policies and updatescales returned a correlation of 0.332 for the product sites and 0.435 for the servicesites. These coefficients are not significant to determine a sizable relationship betweenpolicy ratings and effective or update dates on policies.

In order to determine how many sites were informing or not informing theircustomers about the payment types they accepted online, the frequencies of methods ofpayment for both product and service sites and as percentages of the whole wasobserved. The histogram in Figure 1 shows that four methods of payment are mostpopular for product sites. However, 46 e-commerce sites did not explain what types ofpayments they accepted. These sites represent 12 percent of all the product sites thatwere examined, shown in the pie chart in Figure 2.

Figure 1.Histogram of methods of

payment product sites

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The histogram in Figure 3 shows the frequencies of the methods of payment for servicesites. All service sites where payment methods were not applicable were eliminated.The histogram clearly shows that most service sites do not divulge any informationas to their methods of payment. There were 42 sites with no information; making it33 percent of all the service sites examined, shown in the pie chart in Figure 4.

The most recent annual net incomes for both product and service sites were thenanalyzed to determine if they were affected by the policies. We hypothesized thatweb sites with high composite ratings would also have positive annual net incomefigures. Therefore, a strong positive correlation coefficient, r, would be close to 1 forboth product and service sites.

Figure 2.Methods of paymentproduct sites

Figure 3.Histogram of methods ofpayment service sites

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Product sites resulted in a coefficient of 20.18, which is both negative and far from 1.In order to determine if there was a possibility of being able to predict a product

company’s income based on their composite rating, we ran a regression analysis. It wasdone at the 5 percent level of significance, however; the significance level was greaterthan 0.05 so we could not develop a model to predict net income. A similar analysis forthe service sites showed a correlation coefficient of 0.346, which is stronger than theproduct sites, but was not statistically significant. The regression analysis also showedthat the significance level was above our a equaling 0.05, therefore, we could notdevelop a model to predict net income. Thus, it is concluded that policy ratings do notsignificantly affect a company’s net income.

If companies are operating in the same industry, then it would be reasonablyexpected for them to have similar ratings. In order to determine if there was anyequality in policy ratings between the product industries and the service industries, weran a one way ANOVA for each set.

Therefore, for the product sites:

(1) H0: mi ¼ mj (excluding industries 10, 14, 15, 24-27). The results can be seen inTable VIII.

The hypothesis for the service sites is:

(2) H0: mi ¼ mj (excluding industries 3, 6, 9, 12, 13, 16, 17, 19, 21-23, 28). The resultsare shown in Table X. Industries with sample sizes of two or less were eliminatedfrom each ANOVA test to prevent them from disrupting the results.

The p-value of less than 0.0001 leads us to reject the null of equal means.

One way ANOVAtable product Sum of squares df Mean squares F-ratio p-value

Between variation 236.892 20 11.845 4.106 ,0.0001Within variation 1047.275 363 2.885Total variation 1284.167 383

Table VIII.One way ANOVA testfor product industries

Figure 4.Methods of payment

service sites

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A separate one way ANOVA test was conducted to determine if the policies’ meansbetween the industries were different from each other at the 5 percent level ofsignificance. From Table IX, the means for 6, 8, 9, and 11 are in italics and show meanslower than every industry.

Table X shows one way ANOVA test for the services. The p-value from this test isalso less than 0.001, which leads us to reject the null of equal means between industriesof our data for service sites.

Table XI displays the means per industry, and it clearly shows the wide range ofmeans from a low of 0.990 to a high of 8.300.

Since the industries are different from each other we ran a separate one wayANOVA test to determine if the policies’ means were different from each other at 5percent level of significance. Therefore, for the product sites:

(3) H0: mi ¼ mj for the means of privacy, security, shipping, returns, and warrantypolicy ratings.

For the service sites:

(4) H0: mi ¼ mj for the means of privacy, security policy ratings.

Industry Mean

1 5.6892 5.5813 5.9654 6.5145 5.3226 4.5387 5.2898 3.4159 4.440

11 3.62212 6.30013 6.39016 5.45617 6.50018 5.36419 6.00020 6.31121 6.47722 5.55023 7.30028 6.800

Table IX.Policies means forproduct industries

One way ANOVA table services Sum of squares df Mean squares F-ratio p-value

Between variation 469.929 12 39.161 13.797 ,0.0001Within variation 334.927 118 2.838Total variation 804.857 130

Table X.One way ANOVA testfor service industries

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The results from hypothesis (3) are shown in Table XII, and the results fromhypothesis (4) are shown in Table XIII.

It can be seen from the results in Tables XII and XIII that we should reject the nullsof equal means for all of the policies both for the product and service sites.Because each company sets the amount of information they chose to disclose in theirpolicies, it was needed to determine which of the policies were most important andwhich were least important to product sites and service sites as a whole. It wasdetermined by calculating the weighted averages of each policy, for example:

Weighted Average of Privacy Policy ¼ ðPrivacy Policy Rating*50%Þ

þ ðAccessibility of Privacy Policy*50%Þ:

We calculated the mean of each applicable policy’s weighted average and ranked themfor both product and service sites. The resulting means and ranks are shown inTable XIV.

Industry Mean

1 1.6002 2.8677 1.2108 0.990

10 4.40011 5.09114 6.19715 6.33318 4.44720 4.20824 6.37525 8.00326 6.200

Table XI.Policies means forservice industries

ANOVAproduct Sum of squares df Mean square F Significance

Privacy Between within total 75.889 20 3.794 2.038 0.006675.796 363 1.862751.685 383

Security Between within total 114.061 20 9.620 3.475 0.000595.772 363 1.629709.833 383

Shipping Between within total 192.404 20 9.027 5.905 0.000591.429 363 1.861783.833 383

Returns Between within total 180.538 20 9.027 4.850 0.000675.688 363 1.861856.227 383

Warranty Between within total 180.538 20 6.582 2.671 0.000675.688 363 2.464856.227 383

Table XII.One way ANOVA test

for product policies

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For the product sites, privacy was the most important policy and warranty was theleast. Shipping, returns, and security were second, third, and fourth, respectively.The service sites also showed the privacy policy to be the most important andwarranty to be the least important. Their shipping, security, and returns policieswere second, third, and fourth, respectively, as well. Their security policy is onlyslightly more important than returns, which suggests that they are almost of equalrank/importance.

Since it was found for privacy policy to be the most important to both product andservice e-commerce sites, there was a need to analyze its positional change over time todetermine if it was increasing, decreasing, or remaining constant in its importance. Thechange for product sites resulted in a general upward movement over ten years, yetwith slight dips in 2003-2004 and 2009-2010. This is shown graphically in Figure 5.

The position change of the privacy policies of service e-commerce sites is alsogenerally upward. They hit a peak of 4.833 in 2005-2006, but fell in 2007-2008. They areclimbing again, yet still have not recovered to the peak of 4.833. This movement isshown graphically in Figure 6.

DiscussionThis study reviewed and analyzed the extent to which e-commerce companies explaintheir policies to consumers. The study concluded that most of the companies that wereanalyzed do not inform consumers about their operations in respect to privacy,security, shipping, returns, and warranty. None of the companies studied received themaximum possible rating of ten out of ten. Based on their weighted average rating, andthe ANOVA test that was performed, the discussed companies do not have the samemeans; therefore they do not assign the same level of importance to each policy.However, according to the comparison of means per policy, the privacy policy wasgiven more attention compared to the rest of the policies. It is also noticed that ratingscores of the privacy policy have changed over the years analyzed.

ANOVAservice Sum of squares df Mean square F Significance

Privacy Between within total 119.855 12 9.988 4.169 0.000282.680 118 2.396402.534 130

Security Between within total 123.950 12 10.329 7.639 0.000159.561 118 1.352283.511 130

Table XIII.One way ANOVA testfor service policies

Privacy Security Shipping Returns Warranty

Means of product sites 4.001 2.392 3.092 3.060 1.386Rank product 1 4 2 3 5Means of service sites 3.629 1.682 1.831 1.658 0.862Rank service 1 3 2 4 5

Table XIV.Means for productsites and service sites

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Our analysis proved industries six ( jewelry), eight (art) and 11 (entertainment) from theproduct sites and industry eight (art) from the service sites have consistently lowermeans than the rest. Further research could expand the sample size of these industriesand reanalyze them, in order to determine if our analysis can be generalized or is just aresult of the sample size.

By using scatter plots, it was found that there was no significant correlationbetween the composite ratings of the companies and the last update of their privacypolicy or their net income. Histograms and pie charts of the methods of payment showthat many companies do not inform their customers of the types of payment theyaccept.

Figure 6.Time series of mean

privacy policy

4.833

4.2503.971

5

6

4

0

2000

-02

2003

-04

2005

-06

2007

-08

2009

-10

1

2

3

4.636 4.731

Figure 5.Time series of mean

privacy product sites

4.523

3.6823.964

5

4.5

4

3.5

2.5

1.5

0.5

0

2000

-02

2003

-04

2005

-06

2007

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2

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The results of the least significant difference (LSD) test for the product sitesdemonstrated that industries six ( jewelry), eight (art), nine (toys) and 11 (entertainment)had the lowest means, compared to the rest of the industries investigated. The same testwas performed for service sites, and the findings exhibited no significant pattern, all ofthe means being significantly different from one another.

This research is subject to various limitations. The net incomes collected were thecompanies’ entire income, not exclusively from online sales. By using publicly tradedcompanies’ 10 K forms, income produced only by online sales could be obtained, as amore specific measure of earnings for e-commerce companies. Also, the present studyused an unbalanced sample size consisting of more product sites than service sites.Adding more service sites to balance with the product sites could change the analysis.By increasing the sample size the study could be replicated to verify the findings andconclusions of the present study.

ConclusionIt is forecasted that online shopping will continue to grow. In order to protect theprivacy and provide the financial security of the consumers’ shopping online newregulations will be necessary. It is the responsibility of the online companies to ensurethat consumers are not misled by their online policy statements. Any violations by theonline companies should be handled legally and the proper actions will have to betaken to control any illegal and unethical behavior. Consumers should carefully readthe online policies and make online purchase decisions carefully.

References

Eid, R. and Trueman, M. (2004), “Factors affecting the success of business-to-businessinternational internet marketing (B-to-B IIM): an empirical study of UK companies”,Industrial Management & Data Systems, Vol. 104 Nos 1/2, p. 16.

Furnell, S.M., Chiliarchaki, P. and Download, P.S. (2001), “Security analysers: administratorassistants or hacker helpers?”, Information Management & Computer Security, Vol. 9No. 2, pp. 93-101.

Gao, Y. and Wu, X. (2010), “A cognitive model of trust in e-commerce: evidence from a field studyin China”, Journal of Applied Business Research, Vol. 26 No. 1, p. 37.

Gudigantala, N., Song, J. and Jones, D.R. (2008), “How well do e-commerce web sites supportcompensatory and non-compensatory decision strategies? An exploratory study”,International Journal of E-Business Research, Vol. 4 No. 4, pp. 43-57.

Hormozi, A.M. (2005), “Cookies and privacy”, Journal Information Security, Vol. 13No. 6, pp. 51-9.

Lwin, M.O. and Williams, J.D. (2006), “Promises, promises: how consumers respondto warranties in internet retailing”, The Journal of Consumer Affairs, Vol. 40 No. 2,pp. 236-60.

Meinert, D.B., Peterson, D.K., Criswell, J.R. and Crossland, M.D. (2006), “Privacy policy statementand consumer willingness to provide personal information”, Journal of ElectronicCommerce in Organizations, Vol. 4 No. 1, pp. 1-17.

Meziane, F. and Kasiran, M.K. (2008), “Evaluating trust in electronic commerce: a study basedon the information provided on merchants’ websites”, The Journal of the OperationalResearch Society, Vol. 59 No. 4, pp. 464-72 (suppl. part special issue: intelligentmanagement system).

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Miyazaki, A.D. and Krishnamurthy, S. (2002), “Internet seals of approval: effects on onlineprivacy policies and consumer perceptions”, The Journal of Consumer Affairs, Vol. 36No. 1, p. 28.

Parayitam, S., Desai, K. and Desai, M. (2008), “E-commerce policies, customerprivacy, and customer confidence”, Vilakshan, XIMB Journal of Management, Vol. 5,pp. 45-58.

Peeples, D.K. (2002), “Instilling consumer confidence in e-commerce”, S.A.M. AdvancedManagement Journal, Vol. 67 No. 4, pp. 26-31 (quarterly journal).

Pollach, I. (2005), “A typology of communicative strategies in online privacy policies: ethics,power and informed consent”, Journal of Business Ethics, Vol. 62, pp. 221-35.

Ranganathan, C., and Ganapathy, S. (2002), “Key dimensions of business-consumer web sites”,Information and Management, Vol. 39, pp. 457-65.

Storey, V.C., Kane, G.C. and Schwaig, K.S. (2009), “The quality of online privacy policies: aresource-dependency perspective”, Journal of Database Management, Vol. 20 No. 2,pp. 19-37.

Stylianou, P. (2008), “Online dispute resolution: the case for a treaty between the United Statesand the European union in resolving cross-border e-commerce disputes”, Syracuse Journalof International Law and Commerce, Vol. 36 No. 1, pp. 117-43.

Sun, T. (2011), “The roles of trust and experience in consumer confidence in conductinge-commerce: a cross-cultural comparison between France and Germany”, InternationalJournal of Consumer Studies, Vol. 35 No. 3, pp. 330-7.

Taylor, D.G., Davis, D.F. and Jillapalli, R. (2009), “Privacy concern and online personalization: themoderating effects of information control and compensation”, Electronic CommerceResearch, Vol. 9, March, pp. 203-23.

Tsai, J.Y., Egleman, S., Cranor, L. and Acquisti, A. (2011), “The effect of online privacyinformation on purchasing behavior: an experimental study”, Information SystemsResearch, Vol. 22 No. 2, pp. 254-268, 415,417.

Van Slyke, C., Shim, J.T., Johnson, R. and Jiang, J. (2006), “Concern for information privacy andonline consumer purchasing”, Journal of the Association for Information Systems, Vol. 7No. 6, pp. 415-31.

Wirtz, J., Lwin, M.O. and Williams, J.D. (2007), “Causes and consequences of consumer onlineprivacy concern”, International Journal of Service Industry Management, Vol. 18 No. 4,pp. 326-48.

Further reading

American Bar Association, Business Law Section (2010), “Privacy: how will youmaintain your privacy?”, available at: www.safeshopping.org/pp.shtml (accessedApril 30, 2010).

Chatferjee, S. and Datta, P. (2008), “Examining inefficiencies and consumer uncertainty ine-commerce”, Communications of the Association for Information Systems, Vol. 22,pp. 525-46.

Cook, D.L. (2002), “Governance mechanisms as a means of increasing consumer trustin online exchanges: a signaling perspective”, dissertation submitted byDon Lloyd Cook, J.D., Doctoral Candidate, Virginia Polytechnic Institute and StateUniversity, Blacksburg, VA.

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Dotan, T. (2002), “How can eBusiness improve customer satisfaction? Case studies in thefinancial service industry”, Journal of Information Technology Case and ApplicationResearch, Vol. 4 No. 4, p. 22.

Edwards, L. and Wilson, C. (2005), “Redress and alternative dispute resolution in EUcross-border e-commerce transactions”, International Review of Law, Computers& Technology, Vol. 21 No. 3, p. 315.

Kundi, G.M. and Shah, B. (2007), “eBusiness in Pakistan: opportunities and threats”, Journal ofInternet Banking and Commerce, Vol. 12 No. 3, pp. 1-14, 16-23.

Leahy, P. (2009), “Personal data privacy and security act of 2009”, available at:www.govtrack.us/congress/billtext.xpd?bill¼s111-1490 (accessed April 30, 2010),Text of s. 1490.

Malhotra, N.K., Kim, S.S. and Agarwal, J. (2004), “Internet users’ information privacy concerns(IUIPC): the construct, the scale, and a causal model”, Information Systems Research,Vol. 15 No. 4, pp. 336-55.

United States Computer Emergency Readiness Team – National Cyber Alert System (2008),“Cyber Security Tip ST07-001”, available at: www.us-cert.gov/cas/tips/ST07-001.html(accessed April 30, 2010).

Yenisey, M.M., Ozok, A.A. and Salvendy, G. (2005), “Perceived security determinants ine-commerce among Turkish university students”, Behavior & Information Technology,Vol. 24, pp. 259-74.

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Appendix

furniture.com ballarddesigns.com tiffany.comikea.com woodcraftsandpatterns.com kay.comlowes.com Farm-home.com ice.comhomedepot.com highfashionhome.com jewelryartdesigns.compotterybarn.com homedecorworld.com novica.comcrateandbarrel.com letmeoutdoors.com guvy.comroomstogo.com cheappoolproducts.com jewelryadviser.comla-z-boy.com kitchenessentials.com jewelryexchange.commodernlinefurniture.com potsandpans.com ross-simons.comethanallen.com autopartswarehouse.com reeds.comstinelumber.com innerauto.com jewelrycentral.combuilddirect.com napaonline.com silpada.comselectfurnitureoutlet.com oreillyauto.com solomonbrothers.comroomstore.com Shop.advanceautoparts.com tommysjewelry.comeverythingfurniture.com jcwhitney.com mauidivers.combedbathandbeyond.com mamotorworks.com satyajewelry.comtractorsupply.com basspro.com ultradiamonds.comgreenhome.com captharry.com claires.comus.kohler.com cabelas.com gordonsjewelers.comexpressdecor.com gofishin.com fashionjewelry24.comfixtureuniverse.com pntball.com myjewelrybox.comajmadison.com lumberliquidators.com charmfactory.comdecorplanet.com soapboxusa.com rembrandtcharms.comefaucets.com baseballexp.com worldofcharms.combathroom-glass-vanities.com baseballwarehouse.com thecharmbarn.comnationalbuidersupply.com eastbay.com chains-and-charms.comhomecenter.com footballamerica.com finejewelers.comhomeclick.com footballequipmentusa.com luxuryfinder.comkitchensource.com horsesaddleshop.com eluxury.comlightinguniverse.atgstores.com jaypro.com barnesandnoble.comlightingdirect.com linedrive.com borders.comlampsplus.com paintball-discounters.com abebooks.comlightingshowplace.com soccer.com powells.combellacor.com soccerpro.com booksamillion.comeco-lights.com soccersaurus.com halfpricebooks.comlouielighting.com sportsauthority.com us.penguingroup.comlamps-lighting.com sportsdepot.com textbooks.comcreativewallcovering.com tennisexpress.com ecampus.comhomedecorators.com tennis-warehouse.com chegg.comwalldecorandhomeaccents.com tennisplaza.com valorebooks.comwroughtirondecorstore.com jtv.com alibris.comtextbookx.com Zales.com biblio.comtextbooksnow.com Jared.com textbooksrus.comphatcampus.com uptempoair.com anthropologie.comwholesalecollegetextbooks.com vistaprint.com fashionbug.comart.com llbean.com gap.resultspage.comdeviantart.com anntaylor.com thelimited.comglobalwholesaleart.com christopherandbanks.com debenhams.comoilpaintingsgallery.com sullivanuniforms.com dog.comtoucanart.com jcpenney.com dogtoys.com

(continued )

Table AI.List of product providers

web sites

E-commercepolicies

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dailypainters.com allheart.com petsmart.comallartclassic.com ocs.landsend.com petedge.com1st-art-gallery.com preownedpartydresses.com delmonte.comcanvaz.com nike.com doghouses.comchinesepaintings.com dhgate.com mypetwhs.compaintyourlife.com bodenusa.com petstreetmall.comthebronzeroom.com rascalsresale.com otomik.comwalmart.com t-shirts.cafepress.com thatpetplace.comtarget.com hannaandersson.com frontgate.comsears.com shoecarnival.com vetrxdirect.comAmazon.com shop.nordstrom.com entirelypets.comoverstock.com jjill.com figis.comkohls.com menswearhouse.com fogdog.comqvc.com rei.com eddiebauer.comalbertsons.com sportsauthority.com rightstart.comwalgreens.com zulily.com chicos.comkmart.com kingsizedirect.com onlineshoes.comtoysrus.com tuttlecatalog.com ninewest.cometoys.com billskhakis.com perchanceboutique.comfisher-price.com orvis.com shoesthatloveyou.combacktobasicstoys.com ralphlauren.com skechers.comfao.com freshpair.com striderite.comlego.com barenecessities.com forever21.comeducationaltoysplanet.com victoriassecret.com landofnod.comoompa.com fredericks.com musthaveshoes.comhasbro.com crocs.com vetmedsforpets.comtoytime.com clogoutlet.com kvsupply.comfandango.com clogscentral.com 1800petmeds.comamcentertainment.com comfortshoesny.com ae.comregmovies.com 6pm.com shoebuy.comcinemark.com candefashions.com shoes.commovietickets.com greatglam.com gap.comharkinstheatres.com shoemall.com shop.guess.commarcustheatres.com jbpet.com kmshoes.competco.com drsfostersmith.com naturalizer.comnewark.com www1.bloomingdales.com overstock.comfrys.com hmponline.com calicocorners.combestbuy.com drugstore.com housefabric.comswipebids.com samsung-store.co.uk trimfabric.commouser.com elmers.com moodfabrics.comcircuitcity.com mars.com decoratorsbest.comnextag.com coca-cola.com verawangonweddings.comtoshibadirect.com pepsi.com dkny.comsonystyle.com fritolay.com kleinfeldbridal.comabt.com dove.us davidsbridal.comcompusa.com candyfavorites.com demetriosbride.comnewegg.com candywarehouse.com buttondrawer.comhp.com fahrneyspens.com macys.comtigerdirect.com finalegloves.com Saksfifthavenue.comjr.com fanniemay.com neimanmarcus.comallelectronics.com onlygloves.com sephora.comcrutchfield.com joonspens.com ulta.comgeeks.com gloves-online.com thepill.com

(continued )Table AI.

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dell.com neutrogena.com kotex.comradioshack.com dermstore.com playtexproductsinc.comelectronics-depot.com folica.com opi.comtechbargains.com swisherpens.com maccosmetics.comconsumerdepot.com theonlinecandyshop.com youravon.comstore.apple.com pensandgifts.com esteelauder.comsecondcircuits.com gerber.com pg.comusa.asus.com huggies.com tresemme.comstore.philips.com trojancondoms.com Nexxus.com2.partstore.com proactiv.com remington-products.comus.sanyo.com acne.org sallybeauty.comsharpusa.com clinique.com aveda.compcrush.com highfashionfabrics.com conair.comelectroline4u.com lucysfabrics.com alconeco.comjameco.com sewingstudio.com makingcosmetics.comgateway.com thefabriccorner.com graftobian.comelectronicsurplus.com candlelightvalleyfabrics.com marykay.comshopping.lycos.com finefabrics.com stadium.dallascowboys.comabesofmaine.com thefabricofourlives.com sallyhansen.comsamsung.com thewashingtonpost.com durex.commusic123.com fashiondex.com cvs.comigo.com nancysnotions.com lifestyles.comfabricdirect.com etsy.com abita.comwarehousefabricsinc.com hancockfabrics.com coorsandco.comstarbucks.com budwieser.com communitycoffee.comkleinpeterdairy.com Table AI.

ashleyfurniturehomestore.com moviecube.com orbitz.comhowellfurniture.com mcspaddenbookbindery.com travelocity.combroyhillfurniture.com bookrepaircentral.com airfares.comhanleywood.com bookrepair.us united.comthomasville.com finebinding.com delta.combassettfurniture.com redbirdbindery.com smartfares.comalliedbuilding.com jmkollar.com allcheapfares.comconstruction.com artrestorationsf.com jetblue.comoihome.com oldprints.com 4.jetcombo.compans.com artrestinc.com dollar.comhomeblue.com restorationworld.com expedia.commyinteriordecorator.com duketailor.com budget.comdecoratingden.com ravistailor.com avis.comhomecontractors.biz garytailor.com enterprise.com1800contractor.com annespang.com hotwire.comsparklingpoolservices.com atailoredsuit.com thrifty.compoolserviceamerica.com customink.com foxrentacar.compaintball.com fishead.net paylesscar.comusexterior.com youdesignit.com moviesunlimited.comwestern-saddle-guide.com gopetplan.com columbiahouse.comjewelry.com petassure.com dvdavenue.comcampusbooks.com Acare.com ehit.com

(continued )

Table AII.List of service providers

web sites

E-commercepolicies

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Corresponding authorMayur S. Desai can be contacted at: desaims@tsu.edu

davescampus.com gopetplan.com cafedvd.comdirecttextbook.com premierpetinsurance.com greencine.comchristianbookstore.com frigidaire.com store.wholesaledvdsforless.comgallery-worldwide.com ellelauri.com zdag.comvangoghgallery.com loveofdresses.com cinflix.comtoys.com onetravel.com pinoymovierentals.comzeum.org onetime.com tigercinema.comgotprint.net southwest.com puritanpicks.comvistaprint.com lowfares.com facetsmovies.compsprint.com fly.com tower.comuprinting.com flights.com wbshop.comprintingforless.com expedia.com hotmoviesale.comprintrunner.com bookcheapflightsonline.com axelmusic.comprintplace.com cheaptickets.com dvdsanddeals.comovernightprints.com cheapflights.com familyvideo.comnetflix.com cheapoair.com dvdempire.comredbox.com priceline.com cduniverse.comblockbuster.com flyasia.com mayoclinic.comhollywoodvideo.com aa.com advanstar.comwedding.theknot.com kayak.com facebook.comweddings.weddingchannel.com stjude.org halliburton.comgoodwill.org memorialhermann.org citgo.commoneysavingmom.com texaschildrens.org conocophillips.comcoupons.com monster.com entergy.comcareerbuilder.comTable AII.

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This article has been cited by:

1. Khadija Ali Vakeel, Saini Das, Godwin J. Udo, Kallol Bagchi. 2017. Do security and privacy policies inB2B and B2C e-commerce differ? A comparative study using content analysis. Behaviour & InformationTechnology 36:4, 390-403. [CrossRef]

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allin

n U

nive

rsity

At 1

7:49

13

Janu

ary

2018

(PT

)