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Electronic Commerce Modeling Language

January 01, 1970

Electronic Commerce Modeling Language (ECML) is a protocol which enables the e-commerce merchants to standardize their online payment processes. Through the application of ECML, customers' billing information in their digital wallet can be easily transferred to fill out the checkout forms.[1]

There are various companies that have participated in ECML's alliances, including American Express and Mastercard.[1]

As a standard developed by the alliance, ECML has solved the problem of complex and confusing online manual payments caused by diverse web designs, and further reduces the chance of customer dropout (also called shopping cart abandonment).[1] On the other hand, ECML deals with sensitive information such as credit card numbers and home addresses—its data security is controversial, and privacy considerations should be taken.[2][3]

Alliances edit

The members of ECML Alliance listed in alphabetical order below:[1]

  1. American Express (www.americanexpress.com>
  2. AOL (www.aol.com)
  3. Brodia (www.brodia.com)
  4. Compaq (www.compaq.com)
  5. CyberCash (www.cybercash.com)
  6. Discover (www.discovercard.com)
  7. FSTC (www.fstc.org)
  8. IBM (www.ibm.com)
  9. Mastercard (www.mastercard.com)
  10. Microsoft (www.microsoft.com)
  11. Novell (www.novell.com)
  12. SETco (www.setco.org)
  13. Sun Microsystems (www.sun.com)
  14. Trintech (www.trintech.com)
  15. Visa International (www.visa.com)

ECML and customer dropout behaviors edit

Customer dropout is also called shopping cart abandonment—it is a type of behavior which customers display inclination of purchase without completing the final payment. According to a commercial study, there is a rate 25% to 75% that the customer would abandon a transaction before it is completed due to various reasons.[4] Aside from motivational factors such as customer's fundamental needs and spontaneous purchases, emotional factors such as irritation and disappointment also determine whether a transaction would be successful. Research has shown that payment inconvenience and perceived wasting time are factors that would contribute to customer's irritation.[4]

Electronic Commerce Modeling Language could potentially decrease customer irritation in two ways, and further benefit the industry of electronic commerce as a whole. First of all, it provides a standardized set of information fields which would improve the manual process of online payment. Entering relevant information into the checkout form would become an easier task for customers. Secondly, ECML allows a smooth information transfer between customer's digital wallet and e-commerce checkout form. Information does not has to be manually entered into the system.[1]

ECML and customer's privacy expectations edit

The application of ECML requires the online shoppers to disclose their personal information which includes financial, shipping, billing, and preference details.[1] According to relevant research, customers are able to categorize the level of risks associated with different types of information disclosure.[5] Among the information that is required to complete an online order, the user's home address is categorized as secure identifiers which is perceived as the most sensitive by customers. Other secure identifiers include DNA profile, medical history, and social security numbers.[5] Furthermore, other empirical studies has confirmed customers' consistent privacy expectation --- even they have revealed personal information in exchange for services, their expectation of privacy protection is unlikely to change.[6][7] Firms that adopt to ECML should undertake the responsibility and regulate themselves to actively protect the information collected during transactions.[8]

Privacy considerations and suggestions edit

Electronic Commerce Modeling Language is consistent with Platform for Privacy Preferences (P3P),[9] a controversial protocol which addresses online privacy concern. Initially, P3P is designed to simplify users' access and understanding on privacy policies posted on the websites. It has employed a multiple choice format to make connections between human readable privacy notices and privacy policies, as well as offering agents conduct policy evaluations.[2] On the other side, some studies have also argued that P3P has made users' private information more vulnerable.[3] The platform is accused for its exclusive nature that would disadvantage non-compliant websites with good privacy practices, and its lack of privacy policies' enforcements.[3]

Although the developers of electronic commerce modeling language have not explicitly specified how the information can be safely stored and protected, object security protocols (include XML encryption and XMLDsig), and channel security are all possible ways of privacy protection.[10]

Since ECML is an application related with sensitive information such as credit card numbers and home addresses. Privacy considerations thus have became crucial. There are several suggestions listed below to protect customer's privacy:[1][10]

  1. ECML memory of sensitive information cannot exist. If it is installed on a public terminal, the wallet has to be configurable.
  2. A password should be set up and required each time when the user wants to access the stored information.
  3. Users need to have control of whether the stored sensitive information is released or not.

See also edit

Platform for Privacy Preferences

Digital wallet

XML

XML Encryption

XMLDsig

E-commerce

Consumer privacy

References edit

  1. ^ a b c d e f g Goldstein <tgoldstein@brodia.com>, Ted (April 2001). "ECML v1.1: Field Specifications for E-Commerce". tools.ietf.org. Retrieved 2020-10-29.
  2. ^ a b Cranor, L.F. (2003). "P3P: making privacy policies more useful". IEEE Security & Privacy. 1 (6): 50–55. doi:10.1109/msecp.2003.1253568. ISSN 1540-7993.
  3. ^ a b c "Pretty Poor Privacy: An Assessment of P3P and Internet Privacy". epic.org. Retrieved 2020-10-31.
  4. ^ a b Bell, Lynne; McCloy, Rachel; Butler, Laurie; Vogt, Julia (2020-07-03). "Motivational and Affective Factors Underlying Consumer Dropout and Transactional Success in eCommerce: An Overview". Frontiers in Psychology. 11: 1546. doi:10.3389/fpsyg.2020.01546. ISSN 1664-1078. PMC 7351522. PMID 32714258.
  5. ^ a b Milne, George R.; Pettinico, George; Hajjat, Fatima M.; Markos, Ereni (2017). "Information Sensitivity Typology: Mapping the Degree and Type of Risk Consumers Perceive in Personal Data Sharing". Journal of Consumer Affairs. 51 (1): 133–161. doi:10.1111/joca.12111. ISSN 1745-6606.
  6. ^ Martin, Kirsten E. (2019-11-24). "Breaking the Privacy Paradox: The Value of Privacy and Associated Duty of Firms". Rochester, NY. SSRN 3349448. {{cite journal}}: Cite journal requires |journal= (help)
  7. ^ Karwatzki, Sabrina; Dytynko, Olga; Trenz, Manuel; Veit, Daniel (2017-04-03). "Beyond the Personalization–Privacy Paradox: Privacy Valuation, Transparency Features, and Service Personalization". Journal of Management Information Systems. 34 (2): 369–400. doi:10.1080/07421222.2017.1334467. ISSN 0742-1222. S2CID 38167192.
  8. ^ Radin, Tara J. (2001). "The Privacy Paradox: E-Commerce and Personal Information on the Internet". Business & Professional Ethics Journal. 20 (3/4): 145–170. doi:10.5840/bpej2001203/418. ISSN 0277-2027. JSTOR 27801264.
  9. ^ Eastlake 3Rd, Donald E. (March 2003). "RFC 3505 - Electronic Commerce Modeling Language (ECML): Version 2 Requirements". datatracker.ietf.org. Retrieved 2020-10-31.{{cite journal}}: CS1 maint: numeric names: authors list (link)
  10. ^ a b Eastlake 3rd <donald.eastlake@motorola.com>, Donald E. (June 2005). "Electronic Commerce Modeling Language (ECML) Version 2 Specification". tools.ietf.org. Retrieved 2020-11-05.{{cite journal}}: CS1 maint: numeric names: authors list (link)

January 01, 1970
electronic, commerce, modeling, language, ecml, protocol, which, enables, commerce, merchants, standardize, their, online, payment, processes, through, application, ecml, customers, billing, information, their, digital, wallet, easily, transferred, fill, check. Electronic Commerce Modeling Language ECML is a protocol which enables the e commerce merchants to standardize their online payment processes Through the application of ECML customers billing information in their digital wallet can be easily transferred to fill out the checkout forms 1 There are various companies that have participated in ECML s alliances including American Express and Mastercard 1 As a standard developed by the alliance ECML has solved the problem of complex and confusing online manual payments caused by diverse web designs and further reduces the chance of customer dropout also called shopping cart abandonment 1 On the other hand ECML deals with sensitive information such as credit card numbers and home addresses its data security is controversial and privacy considerations should be taken 2 3 Contents 1 Alliances 2 ECML and customer dropout behaviors 3 ECML and customer s privacy expectations 4 Privacy considerations and suggestions 5 See also 6 ReferencesAlliances editThe members of ECML Alliance listed in alphabetical order below 1 American Express www americanexpress com gt AOL www aol com Brodia www brodia com Compaq www compaq com CyberCash www cybercash com Discover www discovercard com FSTC www fstc org IBM www ibm com Mastercard www mastercard com Microsoft www microsoft com Novell www novell com SETco www setco org Sun Microsystems www sun com Trintech www trintech com Visa International www visa com ECML and customer dropout behaviors editCustomer dropout is also called shopping cart abandonment it is a type of behavior which customers display inclination of purchase without completing the final payment According to a commercial study there is a rate 25 to 75 that the customer would abandon a transaction before it is completed due to various reasons 4 Aside from motivational factors such as customer s fundamental needs and spontaneous purchases emotional factors such as irritation and disappointment also determine whether a transaction would be successful Research has shown that payment inconvenience and perceived wasting time are factors that would contribute to customer s irritation 4 Electronic Commerce Modeling Language could potentially decrease customer irritation in two ways and further benefit the industry of electronic commerce as a whole First of all it provides a standardized set of information fields which would improve the manual process of online payment Entering relevant information into the checkout form would become an easier task for customers Secondly ECML allows a smooth information transfer between customer s digital wallet and e commerce checkout form Information does not has to be manually entered into the system 1 ECML and customer s privacy expectations editThe application of ECML requires the online shoppers to disclose their personal information which includes financial shipping billing and preference details 1 According to relevant research customers are able to categorize the level of risks associated with different types of information disclosure 5 Among the information that is required to complete an online order the user s home address is categorized as secure identifiers which is perceived as the most sensitive by customers Other secure identifiers include DNA profile medical history and social security numbers 5 Furthermore other empirical studies has confirmed customers consistent privacy expectation even they have revealed personal information in exchange for services their expectation of privacy protection is unlikely to change 6 7 Firms that adopt to ECML should undertake the responsibility and regulate themselves to actively protect the information collected during transactions 8 Privacy considerations and suggestions editElectronic Commerce Modeling Language is consistent with Platform for Privacy Preferences P3P 9 a controversial protocol which addresses online privacy concern Initially P3P is designed to simplify users access and understanding on privacy policies posted on the websites It has employed a multiple choice format to make connections between human readable privacy notices and privacy policies as well as offering agents conduct policy evaluations 2 On the other side some studies have also argued that P3P has made users private information more vulnerable 3 The platform is accused for its exclusive nature that would disadvantage non compliant websites with good privacy practices and its lack of privacy policies enforcements 3 Although the developers of electronic commerce modeling language have not explicitly specified how the information can be safely stored and protected object security protocols include XML encryption and XMLDsig and channel security are all possible ways of privacy protection 10 Since ECML is an application related with sensitive information such as credit card numbers and home addresses Privacy considerations thus have became crucial There are several suggestions listed below to protect customer s privacy 1 10 ECML memory of sensitive information cannot exist If it is installed on a public terminal the wallet has to be configurable A password should be set up and required each time when the user wants to access the stored information Users need to have control of whether the stored sensitive information is released or not See also editPlatform for Privacy PreferencesDigital walletXMLXML EncryptionXMLDsigE commerceConsumer privacyReferences edit a b c d e f g Goldstein lt tgoldstein brodia com gt Ted April 2001 ECML v1 1 Field Specifications for E Commerce tools ietf org Retrieved 2020 10 29 a b Cranor L F 2003 P3P making privacy policies more useful IEEE Security amp Privacy 1 6 50 55 doi 10 1109 msecp 2003 1253568 ISSN 1540 7993 a b c Pretty Poor Privacy An Assessment of P3P and Internet Privacy epic org Retrieved 2020 10 31 a b Bell Lynne McCloy Rachel Butler Laurie Vogt Julia 2020 07 03 Motivational and Affective Factors Underlying Consumer Dropout and Transactional Success in eCommerce An Overview Frontiers in Psychology 11 1546 doi 10 3389 fpsyg 2020 01546 ISSN 1664 1078 PMC 7351522 PMID 32714258 a b Milne George R Pettinico George Hajjat Fatima M Markos Ereni 2017 Information Sensitivity Typology Mapping the Degree and Type of Risk Consumers Perceive in Personal Data Sharing Journal of Consumer Affairs 51 1 133 161 doi 10 1111 joca 12111 ISSN 1745 6606 Martin Kirsten E 2019 11 24 Breaking the Privacy Paradox The Value of Privacy and Associated Duty of Firms Rochester NY SSRN 3349448 a href Template Cite journal html title Template Cite journal cite journal a Cite journal requires journal help Karwatzki Sabrina Dytynko Olga Trenz Manuel Veit Daniel 2017 04 03 Beyond the Personalization Privacy Paradox Privacy Valuation Transparency Features and Service Personalization Journal of Management Information Systems 34 2 369 400 doi 10 1080 07421222 2017 1334467 ISSN 0742 1222 S2CID 38167192 Radin Tara J 2001 The Privacy Paradox E Commerce and Personal Information on the Internet Business amp Professional Ethics Journal 20 3 4 145 170 doi 10 5840 bpej2001203 418 ISSN 0277 2027 JSTOR 27801264 Eastlake 3Rd Donald E March 2003 RFC 3505 Electronic Commerce Modeling Language ECML Version 2 Requirements datatracker ietf org Retrieved 2020 10 31 a href Template Cite journal html title Template Cite journal cite journal a CS1 maint numeric names authors list link a b Eastlake 3rd lt donald eastlake motorola com gt Donald E June 2005 Electronic Commerce Modeling Language ECML Version 2 Specification tools ietf org Retrieved 2020 11 05 a href Template Cite journal html title Template Cite journal cite journal a CS1 maint numeric names authors list link Retrieved from https en wikipedia org w index php title Electronic Commerce Modeling Language amp oldid 1198966670, wikipedia, wiki, book, books, library,

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