"... In PAGE 10: ... viii List of Tables Page Table 1: Retailers Selected in This Study 52 Table 2: Fruits Selected in This Study 53 Table 3: F Test 56 Table 4: Demographics Profile of Respondents 59 Table 5: Reasons for Not Buying Fruits Online 61 Table 6: Fruit Consumption and Buying Habits 62 Table 7: Likelihood of Buying Fruits Online in the Next Three to Twelve Months 63 Table 8: Likelihood of Buying Fruits Online Given Certain Criteria 63 Table9 : t tests on Prices 64 Table 10: Proportion of Times the Minimum Internet Price is less than 65 the Minimum Conventional Price Table 11: Important Factors to Consider when Choosing an Online Fruit Seller 68 Table 12: Convenience, Time Saving, Extra Information and Extra Services 69 Table 13: Price Factor 69 Table 14: Descriptive Data on Price Changes 70 Table 15: Proportion of Times Price Dispersion is Lower on the Internet 72 Table 16: Useful Services 74 Table 17: Summary of Findings for all Hypotheses 76 ... In PAGE 76: ...The results of the t tests are displayed in Table9 . Our results suggest that the prices charged for fruits are higher instead of lower on the Internet than in conventional stores: by $0.... ..."

"... In PAGE 20: ...xpected. The pricing schedules punish rather than reward usage. (See Table 6b). ------------------- Insert Table6 about here ------------------- One can access the internet through ISPs. Table 6c presents charges for ISPs in local area, or on a G-Net, which includes a package of device and monthly service.... In PAGE 20: ...xpected. The pricing schedules punish rather than reward usage. (See Table 6b). ------------------- Insert Table 6 about here ------------------- One can access the internet through ISPs. Table6 c presents charges for ISPs in local area, or on a G-Net, which includes a package of device and monthly service. Avantgo in US, SeedyTomato in Europe, and Halebop in Sweden are consumer frien- dly portals for for M-Internet like AOL is for fixed internet.... ..."

"... In PAGE 35: ... On the other hand, it does appear that as the age of the car increases, it affects more the value of the car in the Internet than it does affect its value in a physical market, suggesting that this could be a mechanism through which adverse selection is observed. Table7 presents the same evidence on the full sample (i.... ..."

"... In PAGE 35: ...7 repeats the analysis with a censored normal regression in which the reservation price is used as the censoring point. Consider first the regressions conditional on sales in Table6 . The data here presents mixed evidence on the existence of more adverse selection in the electronic auction than in the physical market.... ..."

"... In PAGE 9: ... For our online demonstration7, we use the Google Web Toolkit8 to develop a dedicated Web-based user interface which analyzes the QoS-related ontologies, generates appropriate GUI to ask for user inputs and automatically formulate the ontology- based user preferences and goal descriptions for the discov- ery process. Table1 shows the results of an (illustrative) example service discovery query for a file hosting service offer- ing DownloadSpeed higher than 25KB/s and UploadSpeed higher than 10KB/s. The user is willing to pay at most 10 Euros for her subscription and her Internet connection speed is ADSL 5Mbps.... ..."

"... In PAGE 10: ... viii List of Tables Page Table 1: Retailers Selected in This Study 52 Table 2: Fruits Selected in This Study 53 Table 3: F Test 56 Table 4: Demographics Profile of Respondents 59 Table 5: Reasons for Not Buying Fruits Online 61 Table 6: Fruit Consumption and Buying Habits 62 Table 7: Likelihood of Buying Fruits Online in the Next Three to Twelve Months 63 Table 8: Likelihood of Buying Fruits Online Given Certain Criteria 63 Table 9: t tests on Prices 64 Table 10: Proportion of Times the Minimum Internet Price is less than 65 the Minimum Conventional Price Table 11: Important Factors to Consider when Choosing an Online Fruit Seller 68 Table 12: Convenience, Time Saving, Extra Information and Extra Services 69 Table 13: Price Factor 69 Table 14: Descriptive Data on Price Changes 70 Table15 : Proportion of Times Price Dispersion is Lower on the Internet 72 Table 16: Useful Services 74 Table 17: Summary of Findings for all Hypotheses 76 ... In PAGE 84: ...Across all time periods, the range of prices on the Internet is lower than the range in conventional stores 100% of the time for apple, banana, papaya and watermelon ( Table15 ). For orange and pineapple, our data suggest that dispersion on the Internet is larger t han dispersion among conventional prices.... ..."

"... In PAGE 36: ... If, as argued in the previous section, the Internet involves more important informational asymmetries, we expect individual dealers and rental car companies to profit from these asymmetries by being more likely to sell undesirable cars than large leasing companies (who are more likely to simply want to sell all cars coming off-lease as efficiently as possible). Table9 tests these hypotheses. The table shows that we can clearly reject the hypothesis that individual dealers are perceived to sell lower quality cars over the internet than institutional ones.... ..."

"... In PAGE 3: ... For example, most of the countries with a high percentage of wireless lines in Asia have wireless competition, while most with very low percentage of wireless lines do not. See Table4... ..."