MEASUREMENT COMPLEXITIES

Identifying and measuring e-commerce transactions is new for statistical agencies and it can be complicated. The simple example of an on-line retail book purchase illustrates some of these complexities and points out some of the measurement issues that remain to be addressed.

• Example--John Doe logs onto his computer, accesses the "Bigbook.com" Internet site, identifies a rather obscure title, and purchases it for $20 plus a $4 delivery charge. John pays with his credit card and is told his book will be delivered in 3-5 days.

This simple example involves Bigbook's use of several additional e-business processes, assuming they are conducted over computer-mediated networks. These processes include electronic marketing to reach John, an electronic search to find the obscure title, electronic procurement and payment to obtain the book from a wholesaler or another dealer, electronic authentication of John's credit card information, electronic processing to obtain payment from a financial institution, electronic shipping arrangements for delivery of the book, and electronic customer support to e-mail John an acknowledgment, order number and expected delivery date. Understanding the effects of these processes on Bigbook's business operations and costs, its supplier and customer relationships, and its competitive industry position are a significant measurement challenge.

This example not only covers many business processes, these processes also involve multiple e-commerce transactions. These transactions include John Doe's purchase of the book from Bigbook and Bigbook's separate transactions with third parties to obtain order fulfillment services, acquire the book for resale, secure credit authentication services, provide payment processing services, and arrange for delivery of the book to John. While comprehensive measures of e-commerce may be wanted to profile all of these transactions, such detailed business statistics coverage would be unprecedented. In addition, the value of e-commerce transactions, like their brick and mortar counterparts, are aggregated and presented by the industry of the business entity selling the goods or services so the industry classification system will impose additional measurement constraints. For example, Bigbook would be classified in North American Industry Classification System (NAICS) retail industry 454110, Electronic Shopping and Mail-Order Houses along with traditional catalog stores. Data on employment, total sales, or e-commerce sales would be provided for the industry as whole; information would not be broken out between electronic shopping and mail order houses. Understanding the industry classification system and its implications for e-commerce and e-business measures is a must for all prospective data users. Moreover, classifying emerging and rapidly evolving businesses engaged in e-commerce activities will remain a challenge for statistical agencies.

An additional complexity is that the transactions relating to John Doe's simple book purchase involve many parties and some play multiple roles. For example, the parties include John, Bigbook, and at least five third party providers of goods or services to Bigbook. Furthermore, several of these parties play multiple roles, such as Bigbook who is both a seller (to John) and buyer (from a supplier) of the book, and Bigbook's third party payment services provider who is a seller of services to both Bigbook and John's credit card company. As in any measurement program, we need to determine from whom to collect needed transaction data, from the buyer or the seller? While we could estimate e-commerce retail sales of books by surveying households (the buyers), this would require a very large sample and be very expensive. Alternatively, we could survey on-line bookstores (the sellers), this would be a much more cost-effective data collection strategy that could provide timely, high quality estimates from a very small sample.

The above example also points out that any given business-to-consumer transaction will involve a larger number of related business-to-business transactions. This transactions multiplier effect is not unique to e-business; however, its expected growth and continued change will add to the challenge of measuring e-business and e-commerce. Growth in transactions is expected because as e-commerce expands related business-to-business transactions will become more fragmented; participants will concentrate on performing their highest valued-activities and rely increasingly on third parties for lower-value added activities. The measurement challenges of this growth include accounting for the increased volumes, identifying the new e-business players, maintaining up-to-date information for the known players, and avoiding double counting the value of related transactions.

Change in the scope and nature of e-commerce transactions is expected because electronic business methods permit the players to change their roles relatively easily and they increasingly will do so. Examples of changes in roles are today seen in manufacturers and wholesalers who now sell directly to consumers, and in the "virtual" integration of firms through informal alliances that link firms electronically. These new arrangements impose additional measurement challenges including identifying the new players and their roles, maintaining up-to-date information on them and how their roles are changing, and updating data collection methods (such as including direct-sale "manufacturers" in an appropriate "retail" sales survey frame).

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