1964 Exploring Decision Rules for Sellers in Business-to-Consumer (B2C) Internet Auctions Wilson, R. B. (1987). Auction theory. In J. Eat- well, M. Milgate & P. Newman (Eds.), The new Palgrave: A dictionary of economic theory. London: Macmillan. :LQJ¿HOG 1 (%D\ ZDWFK &RUSRUDWH sellers put the online auctioneer on even faster track Goods from IBM, Disney help dot-com SLRQHHUSRVWDVXUJHLQSUR¿WV:K\PRPDQG pop are mad. Wall Street Journal, A.1. Witt, L. (2005). Building sales on eBay. Retrieved May 10, 2005, from http://www. fortune.com/fortune/smallbusiness/answercen- tral/0,15704,601929 Zanakis, S., & Becerra-Fernandez, I. (2005). Com- petitiveness of nations: A knowledge discovery examination. European Journal of Operational Research, 166(2), 185-211. ENDNOTES 1 It should be noted, however, that this study H[ D P L Q H G W KH V D OHRIVWH U O L QJVL OYHU À D W Z D U H including pieces manufactured in the 1890’s. This study may only demonstrate the fact that sales of collectible items will likely be disproportionately affected by the quality of the item and the level of detail in its descrip- tion. 2 ,QFODVVL¿FDWLRQWUHHVWKHGHSHQGHQWYDULDEOH LVRIWHQUHIHUUHGWRDVWKH³FULWHULRQYDULDEOH´ We will adopt this usage. 1965 Exploring Decision Rules for Sellers in Business-to-Consumer (B2C) Internet Auctions APPENDIX A Table A.1. Academic disciplines investigating Internet auctions and citations of recent studies Economics Marketing Information Systems Computer Science (Budish & Takeyama, 2001; Easley & Tenorio, 2004; Lucking-Reiley, 2000a; Lucking-Reiley, 2000b; McDonald & Slawson, 2002; Sinha & Greenleaf, 2000; Stan- GL¿UG6WDQGL¿UG Roelofs, & Durham, 2004; Wilcox, 2000) (Bruce, Haruvy, & Rao, 2004; Chong & Wong, 2005; Dholakia, 2005b; Dholakia & Soltysinski, 2001; Ding, Elishaberg, Huber, & Saini, 2005; Geng, Stinchcombe, & Whinston, 2001; Gilke- son & Reynolds, 2003; Kannan & Kopalle, 2001; Stafford & Stern, 2002; Subramaniam, Mittal, & Inman, 2004) (Ba & Pavlou, 2002; Ba, Whinston, & Zhang, 2003; Bapna, Goes, & Gupta, 2000; Bapna, Goes, & Gupta, 2001; Bapna, Goes, & Gupta, 2003; Bapna, Goes, Gupta, & Karu- ga, 2002; Gregg & Walczak, 2003; Hu, Lin, Whinston, & Zhang, 2004; Oh, 2002; Pavlou, 2002; Segev, Beam, & Shanthikumar, 2001; Ward & Clark, 2002) (Ottaway, Bruneau, & Evans, 2003; Por- ter & Shoham, 2004) APPENDIX B Table B.1. Binary logistic and multiple regression analyses Variables DVD MP3 Player Criterion (Dependent) Variable Final Bid Number of Bids Final Bid Number of Bids ,QGHSHQGHQW9DULDEOHV Constant 1.972 10.47 -1.49 26.09 Initial Bid Price 0.027 ** -0.89 *** 0.01 *** -0.13 *** Shipping Cost -0.783 -0.57 *** -0.03 0.20 ** Buy-Now Option 2.331 *** 4.06 *** -0.51 2.64 Ending Time: WDM -0.421 ** 0.23 0.65 1.18 Ending Time: WKM -1.288 ** -0.57 -1.02 -4.17 * Ending Time: WKA 0.641 0.03 -0.82 *** 0.11 Auction Duration 0.101 0.09 0.06 -0.05 Log (Positive Feedback) 0.317 ** 0.39 *** 0.13 * -0.10 Number of Negative Feedback Ratings -0.265 * -0.50 *** 0.00 -0.01 Number of Pictures -0.196 -0.10 0.19 ** -0.23 Expedited Delivery -0.569 0.99 -1.30 *** -0.03 International Delivery -0.433 * -0.26 0.31 0.04 Log-likelihood ratio -130.82 *** 86.52 *** F-Value 25.73 *** 32.23 *** Adjusted R 2 55.2% 51.4% p<0.10 p<0.05 p<0.01 This work was previously published in the International Journal of E-Business Research, edited by I. Lee, Volume 4, Issue 1, pp. 1-21, copyright 2008 by IGI Publishing (an imprint of IGI Global). Section VII Critical Issues 7KLVVHFWLRQDGGUHVVHVFRQFHSWXDODQGWKHRUHWLFDOLVVXHVUHODWHGWRWKH¿HOGRIHEXVLQHVVZKLFKLQFOXGH VHFXULW\LVVXHVLQQXPHURXVIDFHWVRIWKHGLVFLSOLQHLQFOXGLQJHEXVLQHVVHWKLFVVHFXULW\LQHEXVLQHVV DSSOLFDWLRQVDQGULVNPDQDJHPHQW:LWKLQWKHVHFKDSWHUVWKHUHDGHULVSUHVHQWHGZLWKDQDO\VLVRIWKH PRVWFXUUHQWDQGUHOHYDQWFRQFHSWXDOLQTXLUHVZLWKLQWKLVJURZLQJ¿HOGRIVWXG\3DUWLFXODUFKDSWHUV DOVR DGGUHVV HEXVLQHVV SURFHVV PDQDJHPHQW DQG LQWHOOHFWXDO SURSHUW\ HEXVLQHVV VWDQGDUGL]DWLRQ DQGHOHFWURQLFVHUYLFHTXDOLW\2YHUDOOFRQWULEXWLRQVZLWKLQWKLVVHFWLRQDVNXQLTXHRIWHQWKHRUHWLFDO TXHVWLRQVUHODWHGWRWKHVWXG\RIHEXVLQHVVDQGPRUHRIWHQWKDQQRWFRQFOXGHWKDWVROXWLRQVDUHERWK QXPHURXVDQGFRQWUDGLFWRU\ 1967 Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 7.1 A Communications Model for Knowledge Sharing Charles E. Beck University of Colorado at Colorado Springs, USA ABSTRACT An integrative, systems-based model of knowl- edge sharing can provide a way of visualizing the interrelated elements that comprise a knowledge management system. This original model, build- ing on a rhetorical process model of communica- tion, includes both the objective and subjective elements within the human cognition. In addition, LWFODUL¿HVWKHSXUSRVHDQGPHWKRGHOHPHQWVDWWKH center for any effective knowledge system. The model centers on the purpose elements of inten- tions and audience, and the method elements of technical tools and human processes. The output of knowledge sharing includes objective products DQGVXEMHFWLYHLQWHUSUHWDWLRQV)HHGEDFNYHUL¿HV WKH WLPHOLQHVVDQGHI¿FLHQF\ LQ WKH SURFHVV RI building both information and knowledge. INTRODUCTION Over the past quarter century, the theme of knowl- edge management (KM) has appeared among the WRS¿YHLQÀXHQFHVLQFKDQJLQJKRZRUJDQL]DWLRQV work (Abell, 2000). Various thinkers, however, focus on different concepts under the heading of knowledge. Idealistically considered, knowledge consists of information in use, and wisdom com- bines knowledge with values (Lloyd, 2000). As a practical aspect of business, successful companies recognize intellectual assets as having an equal VLJQL¿FDQFHZLWKWKHWDQJLEOHDVVHWV:LWKWRGD\¶V economy driven by connectivity, a fundamental shift in business models is occurring, whereby information, knowledge, and relationships un- derpin competitive advantage (Braun, 2002), especially information built on new technologies (Orr, 2004). This chapter paper proposes a systems model of knowledge sharing as a way to create knowl- 1968 A Communications Model for Knowledge Sharing HGJHIULHQGO\ZRUNSODFHV$IWHUEULHÀ\GLVFXVV- ing existing models, the chapter elaborates the communication model that underlies underlying communication. The proposed model begins by clarifying the communication model that un- derlies both explicit and tacit knowledge. It then elaborates the systems elements of the knowledge sharing model: the input status and assumptions; the purpose elements of intention and audiences; the method elements of technical tools and human processes; the chaos creativity that integrates these elements; the output products and interpretations; and system feedback. BACKGROUND: PRIOR MODELS AND HEURISTIC BASIS In general, models help organize information, $FFRUGLQJ WR 9DLO ³0RGHOV HI¿FLHQWO\ capture, store, and help communicate enterprise knowledge in many forms, ranging from stories (verbal models) to diagrams (pictorial models) to spreadsheets (quantitative models)” (p. 10). Among the limited existing models for this new ¿HOG/HRQDUGIRFXVHVRQWKHLQGLYLGXDO consultant in the knowledge industry; however, this comprehensive approach results in a complex and somewhat unwieldy model. Luan and Serban (2002) propose a tiered knowledge management model, capturing tacit knowledge within an orga- nization. Malhotra (2004) provides two models, differing by routine or structured information and nonstructured/routine; however, the models focus more on technology than on the human element. The proposed model of knowledge sharing attempts to overcome and provide a FRPSUHKHQVLYHEXWVLPSOL¿HGPRGHOFDSWXULQJ key relationships in a manageable, visual format (Beck & Schornack, 2005). The proposed model expands on a systems-based model of commu- nication to identify the elements involved in a knowledge sharing system. The model builds on the underlying systems model (Figure 1). The rhetorical process model expands this simple system in two dimensions. The horizontal division separates the objective in the subjective parts of the process. Additionally, the integra- tion section is further divided in half, creating four elements within the central integration (see Figure 2). • The inputs to this process include the objec- tive status and the subjective assumptions. The integration begins at the top center of the model, with the purpose elements of intentions and audiences. • The integration continues at the lower half of the model with the method elements of genre and process. Rather than following a linear process, these four elements of integration interact, labeled here as embodiment. Figure 1. Basic systems model INTEGRATION Feedback INPUT OUTPUT 1969 A Communications Model for Knowledge Sharing • The outputs of the model include both the product and the interpretation. While the products are the objective and observed outputs, the interpretation is more subjective, open to a broader view of the same products, UHÀHFWHGLQWKHQRQSDUDOOHORXWSXWDUURZV • 7KH¿QDODVSHFWRIWKHPRGHOIHHGEDFNRF- curs throughout the entire model, rather than just from the outputs back to the inputs. PROPOSED INTEGRATIVE SYSTEMS MODEL: OVERVIEW The systems model of knowledge sharing takes the elements of this rhetorical process and elaborates those aspects that apply to knowledge manage- ment sharing. In both the objective and subjective halves of the model, inputs and outputs occur at two levels, that of distinct individuals and that of the organization. The critical integration ele- ments of the model clarify purpose (intentions and audience) and method (technical tools and human processes). The interaction of purpose and method embody the process labeled creativ- ity/chaos in the model. The term chaos does not PHDQFRQIXVLRQEXWUHÀHFWVWKHDVSHFWVRIFKDRV theory which recognizes how disparate and ran- dom actions may create patterns out of disparate elements. The chaos/creativity interaction of purpose and method results in output products subject to multiple interpretations. Feedback, FULWLFDOWRWKHSURFHVVUHYLVHVDQGUH¿QHVERWK knowledge and information (Figure 3). Inputs: Status The inputs to the model on the left side include the objective status and subjective assumptions. Although inputs to the knowledge sharing system t e n d t o r e m a i n r a t h e r s t a b l e , t h e y m a y c h a n g e o ve r time, usually changing rather slowly. 6WDWXVWKHREMHFWLYHYHUL¿DEOHHOHPHQWVLQDQ\ human encounter, consists of two parts: the indi- vidual and the organization. All communication begins with the individual, whether a corporate executive or a beginning clerical assistant. At the individual level, status includes both the person’s background (education, experience, gender) and their role in the organization (job title, job de- Figure 2. Rhetorical process model (Adapted from Beck, 1999, p. 32) Genre Process Intentions SUBJECTIVE OBJECTIVE INPUT Audience Feedback INTEGRATION OUTPUT Feedback Assumptions Status Purpose Embodiment Method 1970 A Communications Model for Knowledge Sharing VFULSWLRQVSHFL¿FUHVSRQVLELOLWLHV%HFDXVHWKH k n o w l e d g e s h a r i n g v a r i e s b y t y p e o f o r g a n i z a t i o n , WKHRUJDQL]DWLRQLWVHOIEHFRPHVDVLJQL¿FDQWVWD- tus element, where organization may include the overall company or a single department. Among numerous ways to classify an organization, two VLJ Q L ¿ F D Q W D V S H F W V L Q FO X G H VL ] H D Q G G LYH U V L W \ 6 L ] H indicates the number of people who may need a given type of information or knowledge, based on actual or potential interaction. Increasing numbers raise the challenge of determining how to classify and structure information for both internal and external use (Adams, 2000). Additionally, the diversity of an organization includes the range of backgrounds, types of positions, knowledge requirements, and nature of the tasks. In clarifying the need for knowledge man- agement systems, organizations must identify the information infrastructure, ranging from the external demographics to the informational literacy competencies of the employees (Oman, 2001). Only then can an organization identify the tools and the technologies through which DQ RUJDQL]DWLRQ ³NQRZV ZKDW LW NQRZV´ WKHQ further clarify the practices and incentives that make the information available to those who QHHGLW³1HW5HVXOWV´&RPSDQLHVPLJKW consider a new position of FKLHIOHDUQLQJRI¿FHU or FKLHINQRZOHGJHRI¿FHU who designs, develops, and coordinates new learning initiatives for the organization (Raub & Von Wittich, 2004). Inputs: Assumptions The subjective assumptions within any knowledge sharing system also consist of both individual and organizational elements. For individuals, assumptions include underlying values and ethical standards: People act either from an explicit set of values or from an implicit set of behavioral principles, which they follow without much conscious thought. Individual assumptions also appear through the style in which someone completes a task: informal or formal, deductive or inductive, right-brained or left-brained, uptight or laid-back. According to Zuckerman and Buell UDWKHUWKDQWHFKQRORJ\³LW¶VKXPDQV that drive a company and the information man- agement efforts that are crucial to success” (p. X). Ennals (2003) highlights this human face in Figure 3. Model of knowledge sharing INTENTIONS Few Short Term Long Term Informal - Formal HUMAN PROCESS Individualistic Comprehensive Analytic - Synthetic TECHNICAL TOOLS Limited Extensive Storage - Connectivity AUDIENCES Feedback Timeliness Feedback Efficienty to Knowledge to Information Multiple Internal - External ASSUMPTIONS Purpose CREATIVITY CHAOS Method STATUS Individual Organization Individual Organization 1971 A Communications Model for Knowledge Sharing the process, and White (2004) does so through the implication that KM is neither knowledge nor management. At the organizational level, culture and climate especially convey assumptions. The organiza- tional culture ranges from family or team styles to dictatorship or even anarchy. The culture may determine whether informal or formal norms will guide activities, including such issues as com- munication processes and dress codes. As Safdie DQG(GZDUGVFRQVLGHUNQRZOHGJHVKDULQJDV³D culture, not a system” (1998, p. S2); and this cul- ture must encourage ideas, encourage knowledge VKDULQJDQGUHZDUGLQQRYDWLRQ³1HW5HVXOWV´ 2000). The assumptions also include the climate of the organization. An open climate fosters the sense of creativity and innovation among indi- viduals, where people feel free to ask questions, suggest changes, and brainstorm alternatives. ,QFRQWUDVWDFORVHGRUGHIHQVLYHFOLPDWHVWLÀHV communication and reduces interaction, as people spend psychic energy protecting themselves from real or perceived threats if they step out of bounds (Beck, 1999). An open environment that stimulates intellectual creativity has been termed an infor- mation ecology (Abell, 2000), which increases both individual and corporate capability. Effec- tive knowledge sharing requires an environment that respects individuals (DeTienne & Jackson, 2001) and enhances the information literacy of an organization as essential underpinnings for knowledge sharing and for learning organization practices (Oman, 2001). Integration Purpose: Intentions For an organization to capture and leverage the knowledge assets, it must determine its pur- pose, that is, it must determine what action it intends to take after collecting data. Otherwise, organizations can merely generate data, with OLWWOHXQGHUVWDQGLQJRILWVVLJQL¿FDQFHDQGZKDW should be done because of it. The systems model of knowledge sharing adapts the concept that all human communication systems must begin with D VHQVH RI SXUSRVH E\ FODULI\LQJ WKH VSHFL¿F intentions of the activity and the audience or audiences involved. Intentions, the objectives an organization wishes to achieve, focus on the extent of the NQRZOHGJHQHHGDQGWKHWLPHIUDPHIRUWKH¿QDO product. The extent ranges from informal to for- mal, and the time frame can either be short term or long term. Table 1 presents the quadrants for the purpose element of intentions. Using this framework, organizations ask a series of questions: • Do we need just a single data point or do we need a synthesis of trends? • Are we answering a simple question for a client or preparing a long-term action strat- egy? • :LOODTXLFNUHVSRQVH¿OOWKHQHHGRUPXVW we test and verify before creating our rec- ommendations? • ,VRXUREMHFWLYHWR¿OODRQHWLPHQHHGRUWR establish a long-term commitment? The type of information sought will vary de- pending on the intended use of that information. Overall, a company needs a knowledge-manage- PHQWVWUDWHJ\WKDWUHÀHFWVLWVFRPSHWLWLYHVWUDW- HJ\$FRPSDQ\DWWKLVSRLQWIDFHVDVLJQL¿FDQW challenge: to take unrelated ideas and innova- Table 1. Intentions Long Term Good Will Contract Adequacy Strategy Informal Formal Connections Obligation Quick Answer Tactics Short Term 1972 A Communications Model for Knowledge Sharing tions and bind them together so they have useful application value. Integration Purpose: Audience Levine and Pomerol (2001) show how the audience expectation in contracts, forms the starting point for knowledge models, and Ennals (2003) cautions against getting trapped in spreadsheets rather than knowledge for users. To gain strategic advantage, a company must ensure that information-sharing SUDFWLFHVEHFRPHVLJQL¿FDQWDWDOOOHYHOVRIWKH organization (Launchbaugh, 2002). In adapting to the information age, organizations must rethink WKHQDWXUHRIWKHZRUNSODFH³:RUNSODFHVPXVW be understood as social settings of negotiated meanings in which knowledge becomes inextri- cably and idiosyncraticly embedded within the particular activit y system that is generating these meanings” (Porac & Glynn, 1999, p. 583). As Table 2 indicates, the needs may change if we focus on those external to the organization, ranging from a single user or a narrow market niche to national and international users or gov- ernment regulators. Internal audience. Knowledge sharing inter- nally concerns availability and extent of knowl- edge within an organization. Often described as information literacyWKLVLQWHUQDOIRFXVLGHQWL¿HV an individual’s ability to recognize when infor- mation is needed, then he/she can locate, evalu- ate, and effectively use the needed information (Oman, 2001). Although some theorists envision information literacy as dependant on individual attributes such as intelligence, education, and experience, any one employee only possesses a subset of the knowledge available and that re- TXLUHGE\WKHZKROHRUJDQL]DWLRQ³.QRZOHGJH Management,” 2000). To enhance the process, organizations could establish a chief knowledge RI¿FHU&.2ZKRGHYHORSVLQWHUQDOWD[RQRPLHV RINQRZOHGJHWRKHOSHPSOR\HHV¿QGZKDWWKH\ are looking for (Friedmann, 20001). The faster rate new knowledge information is changing, thereby increasing the obsolescence of knowl- edge in individuals; consequently, the audience must constantly change and produce change, or become extinct. External audiences. The external audience focus involves competitive intelligence (CI), which consists of two phases: developing data, then transforming it into information (McGonagle & Vella, 20002). The developing data phase builds usable information from public sources about the competition, competitors, and the wider market. The transformation phase analyzes the data to create usable information to support busi- ness decisions. As with the internal audience, information may come from anyone within the organization. Sharing beyond the normal orga- nizational boundaries increases security risks, raising concerns about access to information (Malhotra, 2004). With a more narrow concern, external audiences may focus on creating data bases on most-valued customers. Such initiatives take time and effort—valuable if the organiza- tion knows which customers are worth the cost (Davenport, Harris, & Kohli, 20001)—requiring SROLF\ PDNHUV WR FOHDUO\ GH¿QH WKH SURFHVV RI knowledge acquisition. Integration Method: Technical Tools The method portion of the model integrates technology and humanity. Although it may use technology, knowledge sharing itself is not a tech- Table 2. Audiences Multiple Organization International Supervisors National Internal External Colleagues Target Market Self Specific User Few 1973 A Communications Model for Knowledge Sharing nology (Shaw & Hickok, 2000). Rather, method integrates the two central aspects of information processing: information technology and the hu- man thought process. The information age has expanded technology to facilitate information processing, using tools ranging from fast computer chips and expanded memory in personal and mainframe computers, to the changing technology for distance commu- QLFDWLRQXVLQJSKRQHOLQHV¿EHURSWLFFDEOHDQG satellite transmissions. With such tools changing s o r a p i d l y, p e o p l e c a n n o l o n g e r r e l y s olely o n t h e i r experience, which quickly goes out of date. For technical tools, the model considers the capacity and the connectivity, which range from extensive WROLPLWHG7KHWHFKQRORJ\PHUHO\³HQDEOHV´WKH WUDQVIHURILQIRUPDWLRQEXWPRUHVLJQL¿FDQWLV ³WKH DELOLW\ WR DFW RQ´ WKH LQIRUPDWLRQ /LP Ahmed, & Zairi, 1999, p. 615). Although the DUHD RI ³WHFKQLFDO WRROV´ XVXDOO\ LPSOLHV HOHF- tronic systems, the model of knowledge sharing LQFOXGHVPDQXDOVWRUDJHLQQRWHERRNVDQG¿OHV along with conversations to obtain knowledge (see Table 3). The model incorporates storage and connec- tivity, each addressing different KM objectives. Information management tools attempt to cap- ture and manage explicit product and customer knowledge, then codify and organize it in central UHSRVLWRULHV³1HW5HVXOWV´$VDVLJQL¿- cant limitation, however, the technical tools and techniques selected for looking at problems and VLWXDWLRQVWHQGWRLQÀXHQFHZKDWZH¿QG'XII\ 2001b). Furthermore, the technical tools involved in knowledge sharing may represent a fad, includ- LQJVXFKEX]]ZRUGVDV³H[SHUWV\VWHPV.0GDWD mining, intranets, extranets, universal in-boxes, SDSHUOHVV RI¿FHV DQG H[HFXWLYH LQIRUPDWLRQ systems” (Craig & Mittenthall, 2000, p. 38). In contrast to fads, a true focus on knowledge sharing FDSLWDOL]HVRQWKH³EHVWEUDLQV´LQDQRUJDQL]D- tion, regardless of their location or position in that organization (Duffy, 2001a). As an example of integrating the best brains, intranets may consist of four broad categories: (1) internal communica- tion, (2) collaborative/cooperative work, (3) KM, and (4) process redesign (Baker, 2000). Integration Method: Human Processes Human cognition, the central processes in the model, encompasses multiple viewpoints: philosophy (epistemology), psychology, and popular culture. For organizations, clarifying these human processes involves asking the right questions (Zuckerman & Buell, 1998). In creating knowledge, cognitive behavior exhibits a broad UDQJHIURPVSHFL¿FXQLTXHVLWXDWLRQVWRWKHPRVW comprehensive integration of information. The more comprehensive approach involves theory and wisdom, whereas individualistic processes LQYROYHDFTXDLQWDQFHZLWKDVSHFL¿FHYHQWRUD serendipitous one (see Table 4). Table 3. Technical tools Extensive Data Warehouse WWW Mainframe Internet/LAN Storage Connectivity PC/PalmPilot Phone/fax Notbook/file Conversation Limited Table 4. Human processes Comprehensive Theory Wisdom Explanation Imagination Analytic Synthetic Description Intuition Acquaintance Serendipity Individualistic . technical tools and human processes; the chaos creativity that integrates these elements; the output products and interpretations; and system feedback. BACKGROUND: PRIOR MODELS AND HEURISTIC. distinct individuals and that of the organization. The critical integration ele- ments of the model clarify purpose (intentions and audience) and method (technical tools and human processes) technology and the hu- man thought process. The information age has expanded technology to facilitate information processing, using tools ranging from fast computer chips and expanded memory