2554 The Regulation of New Forms of Electronic Fund Transfers in Japan Focusing on Electronic Money Electronic payment and legislation (p.596). Tokyo: Yuhikak u. 19 7KH¿UVWUHSRUW³7KHURXQGWDEOHFRQIHUHQFH for Electronic Money and electronic payment” (May 23, 1997) concluded that the Bill and 6LPLODU&HUWL¿FDWHV&RQWURO/DZZRXOGQRW apply to IC-chip type (pp.39-40). Retrieved March 15, 2007, from http://www.fsa.go.jp/ p_mof/singikai/kinyusei/tosin/1a1201.htm 20 Osaka District Court Judgment, September 14, 2001. 21 FSA. (2004). Financial Advisory Agency No Action Letter of April 20, 2004 to Barclay Vouchers K.K. Retrieved March 15, 2007, from http://www.fsa.go.jp/common/noact/ kaitou/001/001_06b.pdf and FSA. (2004). Financial Advisory Agency No Action Letter of July 9, 2004, to K.K. Daiichi-Bussan. Retrieved March 15, 2007, from http://www.fsa.go.jp/common/noact/ kaitou/001/001_08b.pdf 22 Iwahara, S. (2003). Electronic payment and legislation (pp.596). Tokyo: Yuhikaku. Mr. Fujiike, on the other hand, has suggested that Electronic Money will fall within he GH¿QLWLRQRI³H[FKDQJHWUDQVDFWLRQV´RQO\ if is has both General Cashability and ver- satility together. This conclusion is realistic, however, the reasons why both the elements are necessary in order for Electronic Money WREHFODVVL¿HGDV³H[FKDQJHWUDQVDFWLRQV´ are not clear. Fujiike, T. (2002). Public regu- lations on settlement services by operating FRPSDQLHVWKDWLVQRW¿QDQFLDOLQVWLWXWLRQV Kinyu-houmu-jijo. 1631, pp.19-26, Tokyo: Kinzai. 23 Nakazaki, T. (2007). Anti-money laundering laws of Japan. In Anti-money laundering International law and practice, pp. [uncer- tain, to be published by the end of March]. London: Wiley & Sons. 24 Kubota, T. (2003). Legal issues related to fund settlement systems (pp.179-208). Tokyo: Kokusai-shoin. 25 3OHDVHVHHWKHGH¿QLWLRQDWWKHVHFWLRQ$RI ³([LVWLQJ5HJXODWLRQVRQ(OHFWURQLF0RQH\² 3DUW,,,²&DVKDELOLW\²WKH'HSRVLW/DZ³ 26 Kubota, T. (2003). Legal issues related to fund settlement systems (p.191). Tokyo: Kokusai- shoin. 27 Kubota, T. (2003). Legal issues related to fund settlement systems (p.194). Tokyo: Kokusai- shoin. 28 Concretely speaking, Item 2, Paragraph 6 , Article 7 of the new rule would be the point. 29 Kubota, T. (2003). Legal issues related to fund settlement systems (p.192). Tokyo: Kokusai- shoin. 30 Kubota, T. (2003). Legal issues related to fund settlement systems (p.193). Tokyo: Kokusai- shoin. 31 E-gold is one of famous worldwide e-currency companies and provides multinational online payment service backed up by gold and other metals. For more details, please visit the fol- lowing URL: http://www.e-gold.com/ 32 Iwahara, S. (2005). The ideal future of regulations on electronic money. In The First Subgroup of the Study Group on the Financial System of the Japanese Bankers Association (Zenginkyo), E-money legislation (pp. 68-76). Tokyo: Zenginkyo. 33 Maeda, Y. (2005). Ideal future legislation on electronic money. In The First Subgroup of the Study Group on the Financial System of the Japanese Bankers Association (Zengin- kyo), E-money legislation (pp. 1-5). Tokyo: Zenginkyo. 34 7KHJDPHZDV³5DJQDURN2QOLQH´RQHRIWKH most popular multiplayer online role playing games in Japan. 35 )RUH[DPSOH³6HFRQG/LIH´www.secon- dlife.comRI¿FLDOO\DQQRXQFHGVWDUWLQJWKHLU service in Japanese from April 2007 early 2007. 36 FSA. (2004). Financial Advisory Agency No Action Letter of April 20, 2004 to Barclay 2555 The Regulation of New Forms of Electronic Fund Transfers in Japan Focusing on Electronic Money Vouchers K.K. Retrieved March 15, 2007, from http://www.fsa.go.jp/common/noact/ kaitou/001/001_06b.pdf 37 Sugiura, N. (2003). Legal issues related to point-based rewards programs. Kinyu- zaisei-jijo, No.2561, p.41. Tokyo: Kinzai. See also Sugiura, N., & Kataoka, Y. (2003). Future Electronic Money and its legal infra- structure (p.38). Retrieved March 15, 2007, from http://www.fsa.go.jp/frtc/seika/discus- sion/2003/20030828-2.pdf 38 Maeda, S. (2005). Regulations on electronic money. In The First Subgroup of the Study Group on the Financial System of the Japanese Bankers Association (Zenginkyo), E-money legislation (pp.48-67). Tokyo: Zenginkyo. 39 Nomura Research Institute. (2006). Esti- mates for nine major industries in Japan for WKH ¿VFDO \HDU Retrieved March 15, 2007, from (http://www.nri.co.jp/english/ news/2006/060816.html 40 Nomura Research Institute. (2006). Business currency in 2010. Tokyo: Toyo Keizai Inc. 41 Mr. Nakazaki. (2007). Three articles are listed as dealing with predictable legal is- sues arising from economic transactions in Second Life in one of the largest IT news portal Web sites in Japan, ITMediaBiz Web site (http://www.itmedia.co.jp/bizid/) as fol- lows: Nakazaki, T. (2007). Will real money trading be a legitimate business? Retrieved March 15, 2007, from http://www.itmedia. co.jp/bizid/articles/0701/26/news008.html; Nakazaki, T. (2007). Converting in-game cur- rency in U.S. Dollars at “Second Life”— is this violating the investment law? Retrieved March 15, 2007, from http://www.itmedia. co.jp/bizid/articles/0702/15/news109.html; Nakazaki, T. (2007). Will a game contest of- fering big money prizes in the virtual world constitute an illegal gamble? Retrieved March 15, 2007, from http://www.itmedia. co.jp/bizid/articles/0703/16/news046.html 42 Five articles are listed as follows: Lemley, M. A. (2002). Place and cyberspace. California Law Review, 91, pp.521-549; Lastowka, F. G., & Hunter, D. The laws of the virtual worlds. California Law Review, forthcoming; Wu, T. (2003). When code isn’t law. Virginia Law Review, 89, pp.101-170; G r i m m el m a n n , J. T. L . ( 2 0 0 4) . V i r t u a l w o r l d s as comparative law. New York Law School Law Review, 47, pp.147-184; )DLU¿HOG-9LUWXDOSURSHUW\%RVWRQ University Law Review, 85, pp.1047-1102. 43 FSA. (2007). March 2007 newsletter in English (pp.23-25). Retrieved March 15, 2007, from http://www.fsa.go.jp/en/newslet- ter/2007/02.pdf This work was previously published in Cyberlaw for Global E-business: Finance, Payments, and Dispute Resolution, edited by T. Kubota, pp. 142-167, copyright 2008 by Information Science Reference (an imprint of IGI Global). 2556 Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 8.12 Pricing Strategy of Online Knowledge Market: The Analysis of Google Answers Zuopeng (Justin) Zhang Eastern New Mexico University, USA Sajjad M. Jasimuddin University of Wales at Aberystwyth, UK ABSTRACT This article addresses the different levels of pricing strategies for an online knowledge mar- ket. Based on the best practice from Google Answers, an online knowledge market is mod- eled as a marketplace where consumers ask and researchers answer questions to make knowledge transactions. Consumers optimally price their TXH V W LRQ V W RREW DL QD Q VZH U VDQG D¿ U PPDL QW DL Q V the online knowledge market by determining the optimal price allocation to researchers. Our study LGHQWL¿HVWZRW\SHVRIFRQVXPHUVVSLQRIIDQG mainstream, based on whether additional utilities will be derived from the market. In addition, we LQYHVWLJDWH KRZWKH ¿UP FDQXVH PLQLPDO DQG maximal posting prices to regulate the knowl- edge market. INTRODUCTION: ONLINE KNOWLEDGE MARKET Recent years have seen an enormous growth and development of e-business. Internet technologies have revolutionized the shopping behaviors of FRQVXPHUVDQGWKHZD\V¿UPVDUHGRLQJEXVLQHVV Firms launch electronic storefronts to advertise their products and attract consumers to shop on- line. According to the Global e-Commerce Report by the Taylor Nelson Sofres (TNS) in 2002, 28% of global Internet users and 32% of U.S. Internet users have shopped online already or plan to do so. The TNS report also indicates that U.S. is the nation with the greatest proportion of Internet users in the world who are engaged in online shopping. Although online security remains the biggest single concern for those Internet users 2557 Pricing Strategy of Online Knowledge Market who have not yet shopped online, the undispu- table fact is that more and more people are using the Internet as the medium to browse product LQIRUPDWLRQ¿UVWDQGWKHQPDNHSXUFKDVHV7KH development of Internet technologies and the proliferation of electronic intermediaries make RQOLQHVKRSSLQJVLJQL¿FDQWO\HDV\EHFDXVHRQOLQH shopping can save time and transportation costs DVZHOODVSURYLGHFXVWRPHUVDGGLWLRQDOEHQH¿WV such as product reviews, comparison of similar products, best price search, and other advantages ZKLFKDUHGLI¿FXOWWRREWDLQZKHQWKH\VKRSLQ local stores. For example, Half.com and Ebay.com provide online marketplaces for people around the world to meet and make transactions, which has VLJQL¿FDQWO\UHPRYHGRUUHOD[HGWKHWUDGLWLRQDO constraints of time and location. Internal knowledge markets have been found in every organization (Matson, Patiath, & Shavers, 2003) in which knowledge experts and knowledge seekers interact electronically to exchange their knowledge. In a similar vein, recent years have also seen the steady growth of online knowledge markets specializing in various domain knowledge and pricing systems. There are various online knowledge markets available in the economy, such as Intota.com, InfoRocket.com, Kasamba.com, Knexa.com, Keen.com, eBrainx.com, Liveadvice. com, Allexperts.com, and Swapsmarts.com. For example, Intota Expert Knowledge Services (www.intota.com) is a specialized service for science and engineering, materials science, in- dustry and technology, and business question answering. Customers select an expert and contact him(her) directly. Kasamba (www.kasamba.com) KDVH[SHUWVLQD¿HOGZKRPFXVWRPHUVFRQWDFW directly with their questions and a bid price. Keen (www.keen.com) and LiveAdvice (www. liveadvice.com) provide services to customers who bid their questions to experts and will be called back on the phone. Customers then pay by the minute. Allexperts (www.allexperts.com) RIIHUVFRQ¿GHQWLDOVHUYLFHVDQGXVHVGLUHFWHPDLO to experts for customers’ questions. SwapSmarts (www.swapsmarts.com) allows users to choose prices for their posted questions. These business practices provide classic examples for research on external knowledge markets. Google Answers (answer.google.com) is the online market place similar to Half.com in the sense that potential buyers and sellers can meet to transact electronically. However, in contrast to the traditional transaction of physical goods, buyers VHWWKHLUSULFHVIRUWKH³JRRGV´WKHNQRZOHGJH that they want to purchase, and sellers choose from available offers from buyers to make trans- actions. At Google Answers, customers can post their questions and set a price between $2 and $200. Researchers hired by Google browse all the posted questions and decide whether or not to answer the questions based on their own valu- ations. A question can only be answered by one researcher; once the answer is complete, 75% of the price for the question will go to the researcher, and the other 25% will remain to Google for its maintenance fee. Given the growing popularity of using online knowledge markets to acquire knowledge, it is naturally interesting to understand the working mechanism behind the online knowledge market. 6SHFL¿FDOO\ZKDWDUHWKHRSWLPDOGHFLVLRQVIRU D¿UPWRPDLQWDLQDQRQOLQHNQRZOHGJHPDUNHW" How should a consumer optimally price his(her) questions? When will a knowledge researcher choose to answer questions posted by request- ors? Different levels of pricing strategies are inves- tigated in this article. First, a consumer’s pricing strategy is analyzed, and two types of consumers are discovered on the knowledge market, spin-off and mainstream consumers, based on whether additional utilities are derived from the knowl- edge market. Second, the reasons of specifying minimal and maximal posting prices for the NQRZOHGJHPDUNHWDUHLQYHVWLJDWHGWKH¿UPPD\ e l i m i n a t e s o me s pi n - o f f c o n s u m e r s b y d e s i g n a t i n g DPLQLPDOSRVWLQJSULFHDQGLQFUHDVHLWVSUR¿WE\ mandating a maximal posting price. Third, the 2558 Pricing Strategy of Online Knowledge Market optimal pricing strategy to researchers, or the proportion allocated to researchers, is studied by comparing the effects on market structure, transaction price, and probability of questions being answered when the allocation changes. The article proceeds as follows. The next section reviews relevant literature from the per- spectives on knowledge market. The third section outlines an analytical model of online knowledge markets. The fourth section details our analysis and discussion. The last section concludes the article. LITERATURE The principle of knowledge market has been recently applied to facilitate knowledge transfer within an organization, which has also gained growing attention in research. Davenport and Prusak (1998) illustrate the concept of internal knowledge market within organizations, and they propose to employ the necessary IT support as well as the indispensable incentives to build an effective internal knowledge market for knowl- edge transfer. Desouza, Awazu, Yamakawa, and 8PH]DZDGH¿QHNQRZOHGJHPDUNHWDV³DQ environment where buyers and sellers can trade WKHLUNQRZKRZZLWKLQGH¿QHGSULFLQJDQGWUDG- ing rules”. Following the initial idea of knowledge market within an organization, Ba, Stallaert, and Whinston (2001) demonstrate that knowledge c o m p on e nt s c a n b e o p t i m a l l y t r a d e d w it h a G r o ve - Clarke-like mechanism within different bundles LQDQLQWHUQDORUJDQL]DWLRQPDUNHWVRWKDWD¿UP can optimally choose the knowledge bundles for investment. While conducting a research, Desouza et al. (2005) develop a mathematical analytics to show the viability of the market mechanism for knowledge management in organizations. Mueller, Spiliopoulou, and Lenz (2002) formally consider the electronic marketplace as an approach to sharing knowledge assets. The characteristics of knowledge as tradable goods to be transacted on the e-marketplace are investigated within two types of frameworks: the pricing system and the quality evaluation method. In addition, internal knowledge market is compared with the inter- organizational knowledge market from various perspectives in this study. Drawing from the lessons from mini-cases, Desouza and Awazu GH¿QHWKHQHFHVVDU\FRPSRQHQWVRIDQ internal knowledge market and outline several important caveats in association with econom- ics literature when devising the market: market of lemons, chicken-and-egg predicament, black markets, and advertising strategies. Several researchers have investigated the online marketplace. Most notably, Bakos (1997) regards an online marketplace as a special type of electronic marketplace and proposes that HOHFWURQLFPDUNHWSODFHVUHGXFHLQHI¿FLHQFLHVE\ lowering buyers’ cost to acquire information about sellers’ prices and product offerings. Bakos (1998) also adds that electronic marketplaces serve the role of matching buyers and sellers and facilitat- ing transactions, where increasing differentia- tions and lower cost of product information can be observed. Nevertheless, there lacks research on online knowledge markets, especially how they function and with what types of consum- ers they deal. Several studies (Edelman, 2004; Kenney, McGovern, Martinez, & Heidig, 2003) have recently attempted to study the impact and implications of an online knowledge market from the inspirations of Google Answers. In a study conducted by Cornell University Library (Ken- ney et al., 2003), its digital reference services are compared with those of Google Answers, which provides an opportunity for librarians to borrow valuable insights from Google’s approach to service development and delivery. From the behavioral perspective, Edelman (2004) analyzes all auctions since the inception of the Google $QVZHUV VHUYLFH $FFRUGLQJ WR KLV ¿QGLQJV there exist certain notable trends in research- ers’ behaviors. More experienced researchers provide answers with more added value asked 2559 Pricing Strategy of Online Knowledge Market by the requestors, receiving higher rankings as a result. A researcher’s rate of earnings increases in his(her) experience. In addition, a researcher who only answers questions in particular categories will provide answers of higher quality but will earn less. However, these studies have not investigated the working mechanism behind an online knowl- edge market, that is, the pricing strategies of FRQVXPHUVDQGWKH¿UPZKRPDLQWDLQVWKHRQOLQH knowledge market. Our research addresses this JDSE\VSHFL¿FDOO\LQYHVWLJDWLQJWKHPRGHODSSOLHG by Google Answers and makes contributions to the literature by identifying two types of consumers on the knowledge market. Our assertion is dif- ferent from the prior literature on horizontally- differentiated markets (Anderson & Palma, 1992; Bockem, 1994; Cohen & Whang, 1997; Lancaster, 1990), where consumers are assumed to have different preferences on products with respect to quality, color, or other characteristics. Hence, WKH¿UPVRQWKHPDUNHWPD\EHEHWWHURIIWRRIIHU SURGXFWVZLWKGLIIHUHQWVSHFL¿FDWLRQVLPSOHPHQW discriminating pricing policies, or collaborate with competitors so as to manipulate the market. Our research does not make assumptions on consum- ers’ preferences, and they are only different with UHVS H F WWRW KHL U VHD UFK LQJV N L O O V:H¿ Q GWKDW HYHQ the consumers with the same searching skills can belong to different types, either the spin-off or the mainstream type, depending on whether they are utilizing the knowledge market seriously to derive additional utilities. The detailed analysis and discussion start from the next section. THE MODEL OF ONLINE KNOWLEDGE MARKET This section outlines our analytical model and shows some preliminary results for further DQDO\VLV:H¿UVWGHVFULEHWKHPRGHOZLWKVRPH assumptions and then formulate the maximization problem of each stakeholder on the knowledge market. :HFRQVLGHUD¿UPWKDWKLUHVNQRZOHGJHUH- searchers to answer questions posted by customers on the online knowledge market. The competi- tion for people to be recruited as a researcher E\WKH¿UPLV¿HUFHVRWKH¿UPFDQDOZD\V¿QG the most intelligent and capable individuals to work as researchers for the knowledge market. Customers come to the knowledge market, post their questions, and set the prices p for them. Since customers do not know who will eventually answer their questions before setting the prices, they may always price their questions as suggested by the guidelines of Google Answers: ³ 7 KH P R U HU HVH D UFK U H TX L UH G W R¿ QG D QD Q V Z H U the higher the price you should set for your ques- tion Setting a price too low to compensate for the time required may result in your question not receiving an answer. The more you are prepared to pay, the more likely your question is to get answered quickly.” When a question is posted on the knowledge market, all the researchers will have the equal opportunity to answer it, depending on who no- WLFHVLW¿UVWEHFDXVHRIWKHORFNLQJPHFKDQLVP HPSOR\HGE\WKH¿UP%DVLFDOO\DQRSHQTXHVWLRQ can be locked by a researcher for a certain period of time so that only one researcher is allowed to work on it at a time. Consequently, either the question is answered and not available anymore, or it becomes open again to all the researchers if the one who locked it was not able to answer it. Therefore, researchers try to catch questions within their knowledge domains as quickly as they can from the knowledge market. However, a researcher cannot negotiate price with customers, EXWZLOO LQVSHFW WKHGLI¿FXOW\RIHDFKTXHVWLRQ and the price tag attached to it to decide whether or not to answer the question. A question m has its type q m RIGLI¿FXOW\ZKLFKLVGLVWULEXWHGZLWK the probability function H(q m ) between 0 and 1. $PRUHGLI¿FXOWTXHVWLRQKLJKHUq m ) requires a 2560 Pricing Strategy of Online Knowledge Market researcher to have a higher knowledge level or exert more effort to answer it. Therefore, a researcher tries to maximize his(her) total surplus by determining whether or not to answer the questions he(she) observes RQWKHPDUNHW)RUDVSHFL¿FTXHVWLRQm priced at p, if he(she) answers it, a researcher will get a net payoff as S r = Dp – T(p, k i ) q m (1) where DLVWKHSURSRUWLRQDOORFDWHGE\WKH¿UP for answering each question with price p and T(p, k i ) is the disutility a researcher with knowledge level k i will incur by answering this question, including the effort cost and the risk of getting a bad evaluation. The knowledge level k i is not observable, but can be inferred from a known distribution G(k i ). We assume that T(p, k i ) is an increasing function in p and a decreasing func- tion in k i with T(0, k i ) = 0. It is also assumed that 2 T 2 i k DQG 2 Tp 2 &RQVHTXHQWO\WKH following lemma can be obtained. Lemma 1. Only those researchers with knowledge levels k i ˆ i k will answer the question m with a price p, where ˆ i k is the threshold knowledge level such that; D p = T(p, ˆ i k ) q m . (2) Proof: A researcher will only answer a question when his(her) total payoff from this question is positive. For a given question m with price p, only those researchers with k i ˆ i k will have positive payoffs, where Dp = T(p, ˆ i k ) q m Ŷ 7 KL V O H P P DL G H QW L ¿ H VW KH WK UH VK R O G N Q RZOH G J H level ˆ i k ; for those researchers with a knowledge level higher than or equal to ˆ i k , they will prefer to answer the question m with a price p since they will get a non-negative surplus, whereas for those lower than ˆ i k , they will not answer the question. From another perspective, if a question mLVPRUHGLI¿FXOWq m is larger), it will require a resea rcher t o be m or e k n owle dge able to be able to answer it because the threshold knowledge level ˆ i k increases in q m . D proportion of price allocated to researchers c() FRVWRI¿QGLQJWKHDQVZHUZLWKRWKHUPHWKRGV k i researcher i’s knowledge level F(s j ) cumulative distribution of consumer skill level G(k j ) cumulative distribution of knowledge level H(q m ) FXPXODWLYHGLVWULEXWLRQRITXHVWLRQGLI¿FXOW\ p price of a question set by knowledge consumers p minimal posting price on the knowledge market ˆ p maximal posting price on the knowledge market U() probability of yielding an additional utility q m GLI¿FXOW\RIDTXHVWLRQm s j level of search skills for consumer j T() disutility of a researcher answering a question Table 1. Summary of notation 2561 Pricing Strategy of Online Knowledge Market In addition, the above lemma assumes that a researcher’s disutility in answering a question is positively related to its price, which stems from WKHUHSXWDWLRQUDWLQJV\VWHPDGRSWHGE\WKH¿UP for the knowledge market. In general, questions with a higher price are more vulnerable to getting a lower rate from their originators for the quality of the answer, because those questions are gener- DOO\PRUHGLI¿FXOWDQGFXVWRPHUVDUHOHVVHDVLO\ pleased for a larger amount of payment. In this sense, although questions with high price tags VHHPPRUHSUR¿WDEOHWKH\DUHPRUHVXVFHSWLEOH to bad evaluations; therefore, researchers from a long-term perspective may not be willing to risk their reputations to answer those expensive ques- tions. In contrast, questions with low price tags, DOWKRXJKWKH\DUH OHVVSUR¿WDEOHPD\EHPRUH popular to researchers because they may help build the long-term reputations on the market. Following the above lemma, a question with a price p to be answered is 1 () i ii k gk dk ³ ˆ , where g(k i ) is the probability density function of researchers’ knowledge levels and we assume that k i is uniformly distributed in [0, 1]. From the above discussion, it can be seen that the probability of a question to be answered decreases with its price, whereas the quality of the answer increases in its price because it will be answered by a researcher with a higher knowledge level. If the question m is not answered, a customer j will incur a cost c(s j , q m ) for exerting effort to get the answer by himself(herself) or from other means in order to enjoy the utility u, where s j describes the ability of the customer jLQ¿QGLQJWKHDQVZHUZLWKRXWWKH help of Google Answers. For instance, customers m a y u s e t h e G o o g l e s e a r c h e n g i n e t o s e a r c h fo r t he relevant documents by themselves. The amount of time they spend varies with their skills in us- ing the search engine. Typically, a more skillful consumer (a higher s j ) incurs less cost c(s j , q m )for ¿ QG L Q J W KHD QV ZH U W RW KH V D PH T X H VW L R Q , IK LV KH U question mLV¿ QDOO\D QVZHUHGW KHFXVWRPHUZKR sets the price p for his(her) question m may get additional utility 'u(q m ) with the probability U(p), which increases in the price. The probability U(p) of obtaining additional utility being an increasing IXQFWLRQRIWKHSULFHFDQEHMXVWL¿HGIURPWKHIRO- lowing two aspects. First, questions with higher prices will be answered by researchers with higher knowledge levels; therefore, consumers may get better answers if they set higher prices for their questions. Second, as shown later, a question with a higher price implies that its originator is more knowledgeable or values his(her) question more; hence, researchers will try to provide a better answer in order to be well evaluated. A consumer’s level of searching skills s j is XQNQRZQWRUHVHDUFKHUVDQGWKH¿UPDQGFDQ only be perceived from a probability distribution function f(s j ). Therefore, a customer with the skill level s j maximizes his(her) expected surplus, [()()] cm upuqp ' 1 () [ ( )] i ii jm k gk dk u cs q ³ 1 1() i ii k gk dk ªº «» «» ¬¼ ³ (3) E\¿QGLQJDEHVWSULFHp for his(her) question on the knowledge market. Given the questions posted RQWKHNQRZOHGJHPDUNHWWKH¿UPPD[LPL]HVLWV expected payoff from these questions, 1 (1 ) ( ) mj i qs i i k EE p gkdk ªº «» «» ¬¼ ³ (4) by specifying the appropriate allocation D. The allocation D, the actual proportion of payment researchers will get for answering each question, c a n b e r eg a r d e d a s t h e i n c e nt iv e t o i n d uc e r e s e a r c h - ers to answer questions because they get more out of answering each question for a larger D. In addition, it can be inferred from Lemma 1 that a larger D increases the success rate of knowledge 2562 Pricing Strategy of Online Knowledge Market ³WUDQVDFWLRQ´TXHVWLRQVEHLQJDQVZHUHGVLQFH the threshold knowledge level ˆ i k decreases in D. Intuitively, if a researcher can get more from DQVZHULQJHDFKTXHVWLRQRULIWKH¿UPDVVLJQVD higher D), he(she) will be willing to answer those questions with lower prices because he(she) will be able to extract positive surpluses from these questions with a higher allocation D. Therefore, each researcher will be willing to answer more questions with a larger allocation D, which implies that a question will become lucrative to more researchers, increasing its probability of being answered. On the negative side, increasing the allocation D may jeopardize the quality of answers WRHDFKTXHVWLRQDQGGHFUHDVHWKH¿UP¶VQHWSUR¿W +HQFHWKH¿UPKDVWREDODQFHWKHVHWUDGHRIIVWR choose a best allocation to researchers. ANALYSIS AND DISCUSSION This section details our analysis and discussion on various pricing strategies of an online knowledge market. Beginning with the individual consumer’s best pricing strategy, we identify two types of consumers on the knowledge market, spin-off information consumers and mainstream knowl- edge consumers, with regard to whether addi- tional utilities can be derived from the knowledge market. Based upon this differentiation, we then discuss the purpose of specifying minimal and PD[LPDOSRVWLQJSULFHVDQG¿QDOO\DQDO\]HWKH ¿UP¶VRSWLPDODOORFDWLRQWRUHVHDUFKHUV Consumers’ Pricing Strategy A knowledge consumer’s best pricing strategy is investigated in this subsection, leading to the differentiation of two types of consumers on the knowledge market. First of all, a knowledge consumer will always set his(her) best price for a posted question on the market. Assuming a uniform distribution for G(k i ), we can rewrite a consumer j’s total surplus from Equation 3 as c (( ))[() ( )](1) jm jm i ucsq pucsq p k ' where the second term is contingent on ˆ i k , the lowest knowledge level required to answer the TXHVWLRQ ZKLFKÀXFWXDWHV ZLWK WKH FXVWRPHU¶V price p according to Lemma 1. Hence, the cus- tomer can price his(her) question according to the following lemma. Lemma 2: A knowledge consumer will set his(her) question with the optimal price p * where () 1 () ( ) jm pu pucsq p c ' ' 1 i i p k k ww (5) and Up * 'u p * – c(s j , q m ). Proof:7KH¿UVWRUGHUFRQGLWLRQRIS c with respect to p is (1 – ˆ i k )(U'(p) 'u – 1) – (U(p) 'u + c(s j , q m ) ˆ i k p w w = 0 and the second order derivative is 2 2 c p w w (1 – ˆ i k )U''(p) 'u – (U(p) 'u + c(s j , q m ) – p 2 2 i k p w w ˆ < 0 if U(p) 'XS * – c(s j , q m ) EHFDXVH 2 ˆ i k S 2 > 0, which can be derived from Lemma 1 and our assumptions about a researcher’s disutility that 2 T/l 2 i k 0 and 2 Tp 2 0 Ŷ L e m m a 2 s u g g e st s t h a t t he r e e x i s t s a b e s t p r i c e p * IRUDFXVWRPHUWRSRVWDVSHFL¿FTXHVWLRQWR maximize his(her) surplus because the LHS of 2563 Pricing Strategy of Online Knowledge Market Equation (5) decreases and the RHS increases in p. Therefore, an intersection always exists be- tween the curves of LHS and RHS with respect to the price p. For a consumer with a better skill level (larger s j ) or a larger additional utility, the LHS increases, resulting in a larger p * . However, the condition, U(p * ) 'u p * – c (s j , q m ), has to be VDWLV¿HGZKLFKLPSOLHVWKDWDFXVWRPHUVKRXOG always offer a price p * less than his(her) own cost c(s j , q m RI¿QGLQJWKHDQVZHUXQOHVVWKHH[SHFWHG additional utility U(p) 'u he(she) may derive from WKHNQRZOHGJHPDUNHWFDQEHMXVWL¿HGE\RIIHU- ing the price. A knowledge consumer’s pricing strategy critically depends on the additional utility 'u he(she) may obtain from the knowledge market. It can be inferred from Equation 5 that under certain conditions, a knowledge consumer will set a higher price for a question if the answer can bring more additional utility 'u, which is stated in the following proposition. Proposition 1: A consumer will set a higher price p * for his(her) question if he(she) can derive more additional utility 'u from it and () 1 () ( ) jm p ppcsq c ! (6) Proof: The derivative of RHS of Equation 5 with respect to 'u is zero. Hence, the optimal price p * will increase with the additional utility 'u if U'(p * ) (c(s j , q m ) – p * ) + U(p * ), the derivative of LHS of Equation (5) with respect to 'u is greater than zero, which is true if the above condition KROGV Ŷ The condition in the above proposition par- allels that in Lemma 2, implying again that the cost c(s j , q m ) is a critical point for a consumer to decide whether or not to increase his(her) price when he(she) may derive more additional utility from the answer of the question. The condition sug- gests that when p is less than c(s j , q m ), the condition always holds, whereas when p is greater than c(s j , q m ), the condition may not hold. When the addi- tional utility keeps increasing, the optimal price increases as well until the critical point c(s j , q m ), beyond which point the consumer has to consider whether keeping or increasing the optimal price will increase the probability of obtaining the additional utility so that the increased cost of payment can be compensated. In summary, when a consumer seriously seeks answers from the knowledge market to derive DGGLWLRQDOXWLOLWLHVKHVKHPD\¿QGDEHVWSULFH to post his(her) question on the market under certain general conditions. However, when the additional utility 'u is very small, especially when 'Xĺ0, a consumer’s pricing strategy will change dramatically, which is presented in the next proposition. Proposition 2: When 'XĺRUQRDGGLWLRQDO utility is derived from the answer of his(her) ques- tion, a consumer will set the price at p for his(her) question, where p is the minimal price required to post a question on the market. Proof: When 'XĺDNQRZOHGJHFRQVXPHU¶V expected payoff is S c = (u – c(s j , q m )) + [c(s j , q m ) – p](1 – ˆ i k ), ZKHUHWKHVHFRQGWHUPWKHEHQH¿WGHULYHGIURP the knowledge market, decreases in the price p. Therefore, the optimal price is achieved as the boundary solution, that is, the consumer will set the price at p , the minimal price to post a question RQWKHPDUNHW Ŷ The phenomena described in the above propo- sition can be truly observed from the knowledge market maintained by Google Answers; about 15% of questions are priced at the minimal posting price, $2. In such case, the consumers do not care whether they will be able to derive any additional utilities from the market, but regard the market as . Forms of Electronic Fund Transfers in Japan Focusing on Electronic Money Electronic payment and legislation (p.596). Tokyo: Yuhikak u. 19 7KH¿UVWUHSRUW³7KHURXQGWDEOHFRQIHUHQFH for Electronic. http://www.fsa.go.jp/common/noact/ kaitou/001/001_08b.pdf 22 Iwahara, S. (2003). Electronic payment and legislation (pp.596). Tokyo: Yuhikaku. Mr. Fujiike, on the other hand, has suggested that Electronic Money will fall within he GH¿QLWLRQRI³H[FKDQJHWUDQVDFWLRQV´RQO if. Allexperts.com, and Swapsmarts.com. For example, Intota Expert Knowledge Services (www.intota.com) is a specialized service for science and engineering, materials science, in- dustry and technology, and