Electronic Business: Concepts, Methodologies, Tools, and Applications (4-Volumes) P251

Semantic Knowledge Transparency in E-Business Processes managing the integration of value chain activities over distributed and heterogeneous information platforms such as the Internet, is a challenging WDVN ZLWK ODUJH SRWHQWLDO EHQH¿WV $OWKRXJK technical integration of systems is essential, a FRPPRQ ODQJXDJH WR H[SUHVV FRQWH[WVSHFL¿F constructs and relevant business rules to assist autonomous system entities and decision makers WRVROYHVSHFL¿FEXVLQHVVSUREOHPVLVHVVHQWLDO (Stal, 2002). Disparate technical systems need the ability to share data, information, and knowl-edge. A common and shared understanding of WKHGRPDLQVSHFL¿FFRQFHSWVDQGWKHUHODWLRQV between them is critical for creating integrative views of information and knowledge in e-business processes. However, there is paucity in research on distributed information and knowledge shar-ing that provides a unifying process perspective to share information and knowledge (Oh & Park, 2003) in a seamless manner. The Semantic Web is a key component for realizing the vision of semantic knowledge trans-parency in e-business processes. The Semantic Web provides the technical foundations to sup-SRUWWKHWUDQVSDUHQWÀRZRIVHPDQWLFNQRZOHGJH representation to automate, enhance, and coordi-nate collaborative inter-organizational e-business processes (Singh, Iyer, et al., 2005). The Semantic Web vision comprises ontologies for common semantics of representation and ways to interpret ontology; knowledge representationfor structured collections of information and inference rules for automated reasoning in a single system; and intelligent agent to collect content from diverse sources and exchange data enriched with seman-tics (Berners-Lee, Hendler, & Lassila, 2001). This vision provides the foundation for the semantic framework proposed in this research. This chapter is structured as follows. First, we conduct a review and analysis of the relevant literature in the areas of e-business, KM, and the Semantic Web. Second, the conceptualization of the e-business process universe of discourse and its description logic are developed.Third, weuse an intelligent infomediary-based e-marketplace as a scenario to illustrate how semantic knowledge transparency can be used to achieve the coordi-nation of activities and resources across inter-organizational systems. Finally, future research issues and conclusions are stated. BACKGROUND Based on existing research in e-business, KM and the Semantic Web, an innovative approach to achieve semantic knowledge transparency is developed. We use a process perspective to integrate knowledge of resources involved in a process and process knowledge including process PRGHOVDQGZRUNÀRZVXVHGLQSURFHVVDXWRPDWLRQ In order to achieve semantic knowledge transpar-ency, we develop theoretical conceptualizations using ontological analysis that will be formalized using DLs. The ontology will support a common vocabulary for transparent knowledge exchange among inter-organizational systems of business partners of a value chain, so that semantic interop-erability can be achieved. The foundations of the proposed approach are conceptually represented in Figure 1 and explanations follow. E-Business Electronic data interchange (EDI) is an informa-tion technology that allows business partners to send and receive commercial documents in an electronic format (Hansen & Hill, 1989). Under EDI proprietary value-added networks data dis-closure and information transparency were not a concern. Interestingly, EDI by itself does not provide market transparency (Zhu, 2004). Nowadays, businesses are moving from EDI WR:HEEDVHGV\VWHPV,QIDFWPDQ\¿UPVKDYH adopted e-business models to improve their collaborative capabilities (Segars & Chatterjee, 2003). Regarding business processes, they are typically modeled as deterministic, action-event 2434 Semantic Knowledge Transparency in E-Business Processes Figure 1. Conceptual representation of semantic knowledge transparency and integration. Semantic Web Ontology, Knowledge Representation, Intelligent Agents Semantic Knowledge Transparency e-Business e-Marketplace, Infomediary Knowledge Management Organizational Knowledge, Interorganizational Processes Coordination VHTXHQFHVLQZRUNÀRZEDVHGLQIRUPDWLRQV\VWHPV DQGZRUNÀRZDXWRPDWLRQV\VWHPV:RUNÀRZV establish the logical order of execution between individual task units that comprise intra-or-ganizational and inter-organizational business SURFHVVHV7KH:RUNÀRZ0DQDJHPHQW&RDOLWLRQ (www.wfmc.org) describes business process as ³DVHTXHQFHRIDFWLYLWLHVZLWKGLVWLQFWLQSXWVDQG outputs and serves a meaningful purpose within an organization or between organizations” (Dust-dar, 2004 p. 460). $ SURFHVV GH¿QLWLRQ LV WKH UHSUHVHQWDWLRQ of a business process in a form which supports automated manipulation, such as modeling, or HQDFWPHQWE\DZRUNÀRZPDQDJHPHQWV\VWHP :I067KHSURFHVVGH¿QLWLRQFRQVLVWVRID network of activities and their relationships, cri-teria to indicate the start and the termination of the process, and information about the individual activities, including participants and data (www. wfmc.org). Business processes can thus be gener-DOL]HGDVKDYLQJD³EHJLQ´DQGDQ³HQG´SRLQWDQG a series of intermediate tasks that are performed in sequence on some entity, object, or activity. In its simplest case, an e-business process may KDYHHDFKZRUNÀRZDFWLYLW\SHUIRUPHGZLWKLQ a single organization; while in the most general and extensible case, each individual activity may be performed by a different partner organization. 0RVWLQWHURUJDQL]DWLRQDOZRUNÀRZVZRXOGIDOO somewhere in between these end points. Singh, Iyer, et al. (2005) explain that e-business processes require transparent information and semantic knowledge transparency among business partners. The consequent lack of transparency in LQIRUPDWLRQÀRZDFURVVWKHYDOXHFKDLQFRQWLQXHV to hinder productive and collaborative partner-VKLSDPRQJ¿UPVLQe-marketplaces. Moreover, the lack of transparency in business-to-business (B2B) e-marketplaces increases the uncertainty and perceived risks and hampers trusted relation-ships among business partners. E-Marketplace The main roles of e-marketplace are: (1) discovery – of buyers and suppliers that meet each other’s requirements; (2) facilitation – of transactions to HQDEOHLQIRUPDWLRQÀRZVOHDGLQJWRWKHÀRZRI good and services among buyers and suppliers; and (3) support – of decision process leading to the development of collaborative relationships 2435 Semantic Knowledge Transparency in E-Business Processes between e-marketplace participants (Bakos, 1998). The value added to the process by the e-marketplace is in providing information to buyers and suppliers about each others’ capabilities and requirements. E-marketplace is a mechanism to VWUHDPOLQHLQIRUPDWLRQÀRZLQVXSSO\FKDLQDQG re-balance the information asymmetry (Zhu, 2002). E-marketplaces offer value-added ser-YLFHVE\OHYHUDJLQJLQGXVWU\VSHFL¿FNQRZOHGJH through deciphering complex information and contribute to transaction cost reduction. How-ever, the lack of integration of information and knowledge across the e-value chain continues to hinder productive and collaborative partnerships DPRQJ¿UPVLQHPDUNHWSODFHV Infomediary In e-marketplaces a new kind of intermediaries has emerged:Infomediary.Grover and Teng (2001) GH¿QHLQIRPHGLDU\DV³HFRPPHUFHFRPSDQLHV leveraging the [power of] the Internet to unite EX\HUVDQGVXSSOLHUVLQDVLQJOHHI¿FLHQWYLUWXDO marketspace to facilitate the consummation of a transaction” (p. 79). In this chapter, we argue that in the context of e-marketplaces, intermediaries have evolved into infomediaries that add value to their stakeholders by deciphering complex product information and matching buyers’ needs with sellers’ products and/or services. Grover and Teng focus on the critical information-providing role of the market and identify the roles played by electronic intermediaries, or infomediaries. An infomediary is an emergent business model adopted by organizations in response to the enormous increase in the volume of information available and the critical role of information in enabling processes in electronic markets. Info-mediaries perform an indispensable function by matching buyers’ needs with suppliers’ products and services to facilitate transactions. There is a wealth of market information exchanged through the infomediaries as they perform these functions. As a result, Infomediaries become vital resources of knowledge about the nature of exchanges in the e-marketplace. An analysis of the infomediary business model shows that individual buyers and suppliers seek distinct goal-oriented information capabilities from the infomediary—they provide decision parameters through their individual demand or supply functions. This is essentially a discovery activity with buyers and suppliers searching for a match of their requirements through infomediar-LHV7KLVGLVFRYHU\SURFHVVLVLQÀXHQFHGE\KLV-torical information including the past experiences of other buyers’ reliability and trustworthiness of the supplier. The infomediary business model can provide valuable information to this deci-sion process through its role as the repository of experiential knowledge of transactional histories for both buyers and suppliers. This information can be used to develop knowledge that informs discovery of buyers and suppliers for subsequent transactions. A realization of the need for greater collaboration among trading partners is fueling the growth of KM to help identify integrative and interrelated elements to enable collaborations. Knowledge Management .0FDQEHGH¿QHGDV³DSURFHVVWKDWKHOSVRU-JDQL]DWLRQV¿QGVHOHFWRUJDQL]HGLVVHPLQDWH and transfer important information and expertise necessary for activities such as problem solving, dynamic learning, strategic planning, and deci-sion making” (Gupta, Iyer, & Aronson, 2000, S.0LQFOXGLQJWKHFRGL¿FDWLRQVWRUDJH retrieval, and sharing of knowledge, transpires in WKHFRQWH[WRIDSURFHVVVFLHQWL¿FJRYHUQPHQWDO or commercial. Explicit knowledge, declarative enough to be represented using standards-based knowledge representation (KR) languages allows for knowledge to be interpreted by software and shared using automated reasoning mechanisms to reach useful inferences. While all knowledge cannot be explicated and be effectively represented and reasoned with using decidable and complete 2436 Semantic Knowledge Transparency in E-Business Processes computational techniques; it is useful to focus on explicit, declarative KR using computationally feasible KR languages to build effective and useful NQRZOHGJHEDVHGV\VWHPV+DPHOLGHQWL¿HV that knowledge transparency is directly related to HDVHRIWUDQVIHU,QOLQHZLWKWKHQRWLRQRI¿UPVDV repositories of productive knowledge (Demsetz, 1998), where knowledge resources are primary concern, managing cooperative relationships is IUHTXHQWO\DSURFHVVRIPDQDJLQJNQRZOHGJHÀRZV (Badaracco, 1991). Furthermore, transparency is critical to busi-ness partnerships, lowering transaction costs EHWZHHQ¿UPVDQGHQDEOLQJFROODERUDWLYHFRP-merce (Tapscott & Ticoll, 2003). We focus on two VSHFL¿FW\SHVRINQRZOHGJHLQWKLVUHVHDUFK Inter-Organizational Process Coordination Inter-organizational processes allow collaborating organizations to provide complementary services through networks of collaborating organizations (Dyer, 2000; Sawhney & Parikh, 2001). Here, WKHUHVRXUFHEDVHGYLHZRI¿UPVZLWKIRFXVHG capabilities is replaced by a network of organi-zations with a focal enterprise that coordinates resources of collaborating organizations to execute processes (Sawhney & Parikh, 2001). Complexities of coordinating inter-organizational processes require knowledge-driven coordination structures to determine decision authority and knowledge sources (Anand & Mendelson, 1997). 1. Component knowledge: Component knowledge includes descriptions of skills, technologies, tangible and intangible resources and is amenable to knowledge exchange (Hamel, 1991; Tallman, Jenkins, Henry, & Pinch, 2004). 2. Process knowledge: Process knowledge is typically embedded in the process models RIZRUNÀRZPDQDJHPHQWV\VWHPVRUH[LVWV as coordination knowledge among human agents to coordinate complex processes. The knowledge-integrated system incorporates the coordination mechanism and offers authorized resource matching in processes. Processes are decomposed into activities organized by gener-alization-specialization hierarchies and require coordination mechanisms to manage dependen-cies (Malone & Crowston, 1994). Coordination RIDFWLYLWLHVLVHPEHGGHGLQSURFHVVZRUNÀRZV and WfMS since they essentially deal with issues of task-task and task-resource dependencies and their coordination (Kishore, Sharman, Zhang, & Ramesh, 2004). Coordination constructs used Component and process knowledge are central to activities of human and software agents in inter-organizational e-business processes; there-fore, the standard representation of both type of knowledge is fundamental to achieve semantic knowledge transparency. Newell (1982) regards NQRZOHGJHDV³ZKDWHYHUFDQEHDVFULEHGWRDQ agent, such that its behavior can be computed according to the principle of rationality” (p. 105). 7KLVGH¿QLWLRQIRUPVDEDVLVIRUIXQFWLRQDO.0 using agents, human, and software when using explicit, declarative knowledge that is represented using standards-based knowledge representation languages that can be processed using reasoning mechanisms to reach useful inferences. in this proposed research are based on Malone, Crowston, and Herman (2003) and are similar to those in Van der Aalst and Kumar (2003). The complexity of coordinating e-business processes and the increasing demand by customers for complete solutions over single products re-quires knowledge-driven coordination to provide intelligent support to determine decision authority and knowledge sources in a value network. Al-liances are seldom forged to co-produce single products; they increasingly entail developing com-plex systems and solutions that require resources of multiple partners (Doz & Hamel, 1998). This requires integrative architecture with reasoning ability using knowledge about business processes within a value network. The integrated informa- 2437 Semantic Knowledge Transparency in E-Business Processes tion system as an integral part of the coordination structure can offer enhanced matchmaking of resources and coordination of activities to allow the value network to respond to dynamic customer GHPDQGHI¿FLHQWO\DQGHIIHFWLYHO\$VRUJDQL]D-tions become increasingly global and distributed in nature, their reliance on inter-organizational LQIRUPDWLRQÀRZVZLWKSDUWQHURUJDQL]DWLRQVLV integral to e-business processes. Integrating knowledge resources across col- is the concept of the Semantic Web. The Semantic Web is an extension of the current Web in which LQIRUPDWLRQLVJLYHQ³ZHOOGH¿QHGPHDQLQJ´WR DOORZPDFKLQHVWR³SURFHVVDQGXQGHUVWDQG´WKH information presented to them (Berners-Lee et al., 2001, p. 35). According to Berners-Lee, the Semantic Web comprises and requires knowledge representation, ontologies, and agents in order to function (Figure 2 shows the different layers of the Semantic Web architecture): laborating organizations requires knowledge transparency for global, inter-organizational, access to knowledge resources. Here, semantic knowledge transparency refers to the dynamic RQGHPDQGDQGVHDPOHVVÀRZRIUHOHYDQWDQG unambiguous, machine-interpretable knowledge resources within organizations and across in-ter-organizational systems of business partners engaged in collaborative processes. A process view of knowledge integration incorporates man-agement of component knowledge and process knowledge for integrated inter-organizational systems that exhibit knowledge transparency. The effective standardizations and adaptability afforded by integrative technologies that support the transparent exchange of information and knowledge make inter-organizational e-business relationships viable. Semantic Web Another theoretical foundation of the semantic knowledge transparency in e-business processes • Knowledge representation:Structured col-lections of information and sets of inference rules that can be used to conduct automated reasoning. Knowledge representations must be linked into a single system. • Ontologies: Systems must have a way to discover common meanings for entity rep-resentations. In philosophy, ontology is a theory about the nature of existence; in sys-tems, ontology is a document that formally GHVFULEHVFODVVHVRIREMHFWVDQGGH¿QHVWKH relationship among them. In addition, we need ways to interpret ontology. • Agents:Programs that collect content from diverse sources and exchange the result with RWKHUSURJUDPV$JHQWVH[FKDQJH³GDWDHQ-riched with semantics.” Intelligent software agents can reach a shared understanding by exchanging ontologies that provide the vocabulary needed for discussion. Agents FDQHYHQ³ERRWVWUDS´ new reasoning capa- Figure 2. Semantic Web representation layers (Berners-Lee et al., 2001) 2438 ... - tailieumienphi.vn