E-Business Knowledge

2011 ◽  
pp. 70-112
Author(s):  
Petter Gottschalk
Keyword(s):  
Knowledge Management ◽  
Knowledge Creation ◽  
Customer Value ◽  
Business Processes ◽  
Empirical Studies ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Business Knowledge ◽  
Key Factor ◽  
Research Propositions

This chapter documents some of the links between e-business and knowledge management systems that might be explored in future empirical research. The research propositions in this chapter illustrate the need for a contingent approach to knowledge management systems that are to support e-business. Knowledge management systems successfully supporting and improving e-business performance have to satisfy several requirements. First, they have to support the chosen e-business model(s). Second, they have to cause improvements through redesign of e-business processes. Furthermore, more advanced stage of knowledge management technology in terms of codification strategy will be more powerful and successful. These are some of the research propositions presented in this chapter, which represents a rich knowledge base for future empirical studies. The main objective of a knowledge management system (KMS) is to support the creation, transfer, and application of knowledge in organizations (Feng et al., 2005). Electronic business (e-business) is marketing, buying, selling, delivering, servicing, and paying for products, services, and information across networks linking an enterprise and its prospects, customers, agents, suppliers, competitors, allies, and complementors (Weill & Vitale, 2002). Several researchers emphasize the important role of knowledge management systems in e-business (e.g., El Sawy, 2001; Fahey et al., 2001; Holsapple & Singh, 2000; Malhotra, 2000, 2002; Plessis & Boon, 2004; Singh et al., 2004; Tsai et al., 2005). Garud and Kumaraswany (2005) argue that knowledge has emerged as a strategically significant resource for the firm. Accordingly, knowledge creation and transfer becomes a key factor to gain and sustain a competitive advantage (Sambamurthy & Subramani, 2005). E-business processes can create additional customer value through knowledge creation with customers (Kodama, 2005).

Developing and Maintaining Knowledge Management Systems for Dynamic, Complex Domains

2011 ◽  
pp. 203-229 ◽  
Author(s):  
Lisa J. Burnell ◽  
John W. Priest ◽  
John R. Durrett
Keyword(s):  
Knowledge Management ◽  
Business Processes ◽  
Systems Development ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Agent Architectures ◽  
Knowledge Resources ◽  
Knowledge Based ◽  
Development Processes

An effective knowledge-based organization is one that correctly captures, shares, applies and maintains its knowledge resources to achieve its goals. Knowledge Management Systems (KMS) enable such resources and business processes to be automated and are especially important for environments with dynamic and complex domains. This chapter discusses the appropriate tools, methods, architectural issues and development processes for KMS, including the application of Organizational Theory, knowledge-representation methods and agent architectures. Details for systems development of KMS are provided and illustrated with a case study from the domain of university advising.

Developing and Maintaining Knowledge Management Systems for Dynamic, Complex Domains

2011 ◽  
pp. 571-592
Author(s):  
Lisa J. Burnell ◽  
John W. Priest ◽  
John R. Durrett
Keyword(s):  
Knowledge Management ◽  
Business Processes ◽  
Systems Development ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Agent Architectures ◽  
Knowledge Resources ◽  
Knowledge Based ◽  
Development Processes

An effective knowledge-based organization is one that correctly captures, shares, applies and maintains its knowledge resources to achieve its goals. Knowledge Management Systems (KMS) enable such resources and business processes to be automated and are especially important for environments with dynamic and complex domains. This chapter discusses the appropriate tools, methods, architectural issues and development processes for KMS, including the application of Organizational Theory, knowledge-representation methods and agent architectures. Details for systems development of KMS are provided and illustrated with a case study from the domain of university advising.

Outsourcing Knowledge

2011 ◽  
pp. 113-191
Author(s):  
Petter Gottschalk
Keyword(s):  
Knowledge Management ◽  
Knowledge Transfer ◽  
Research Literature ◽  
It Outsourcing ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Knowledge Process ◽  
Strategic Intent ◽  
Business Environments ◽  
Research Propositions

With changing business environments, the locus of value creation is no longer within the boundaries of a single firm, but occurs instead at the nexus of relationships between parties. With the growing importance of pooling knowledge resources, knowledge management will have to transcend organizational boundaries. Based on current research literature, this chapter develops research propositions to study causal aspects of knowledge management systems supporting IT outsourcing relationships. Perspectives from the research literature applied in this chapter include knowledge transfer, strategic intent, knowledge management technology stages, intangible assets, resource-based theory, vendor value proposition, value shop, and knowledge strategy (Gottschalk & Solli-Sæther, 2006). Research propositions in this chapter suggest that knowledge transfer is the most important knowledge process in an IT outsourcing relationship, increase in knowledge transfer between vendor and client will improve partnership quality in IT outsourcing relationships, a higher level of strategic intent for IT outsourcing requires a higher stage of knowledge management systems, and vendor and client need to be at the same technology stage of growth to be able to successfully communicate with each other through knowledge management systems.

The Role of Fit in Knowledge Management Systems

2008 ◽  
pp. 2157-2177
Author(s):  
Peter Baloh
Keyword(s):  
Knowledge Management ◽  
Knowledge Creation ◽  
Design Science ◽  
Theoretical Background ◽  
Management Systems ◽  
Evolutionary Information ◽  
Knowledge Management Systems ◽  
Organizational Setting ◽  
Processing Theory ◽  
It Support

While most organizations have deployed knowledge management systems (KMS), only a handful have been able to leverage these investments. Existing knowledge management (KM) research offered valuable insights on how to introduce KMS in a sense of innovation-diffusion, yet little guidance has been offered to KMS developers who need to decide on functionalities of a tool they are to introduce in a particular organizational setting. The goal of this paper is to propose theoretical background for design of IS that successfully support and enable decision making, which is seen as the ultimate form of knowledge creation and utilization. By using principles of the design science, design profiles proposed build upon works from organization and IS sciences, primarily the evolutionary information-processing theory of knowledge creation (Li & Kettinger, 2006) and the task technology fit theory (Zigurs & Buckland, 1998), the latter being amended for particularities of the KM environment. Proposed fit profiles suggest that one-size-fits-all approaches do not work and that organizations must take, in contrast with suggestions of extant literature, a segmented approach to KM activities and fitting IT support.

Knowledge Management Success Models

2011 ◽  
pp. 32-40 ◽  
Author(s):  
Murray E. Jennex
Keyword(s):  
Information System ◽  
Knowledge Management ◽  
Knowledge Creation ◽  
Organizational Memory ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Organizational Processes ◽  
The Past ◽  
Ict System ◽  
Service Components

Alavi and Leidner (2001, p. 114) defined knowledge management systems (KMSs) as “IT-based systems developed to support and enhance the organizational processes of knowledge creation, storage/retrieval, transfer, and application.” They observed that not all KM initiatives will implement an IT solution, but they support IT as an enabler of KM. Maier (2002) expanded on the IT concept for the KMS by calling it an ICT system that supported the functions of knowledge creation, construction, identification, capturing, acquisition, selection, valuation, organization, linking, structuring, formalization, visualization, distribution, retention, maintenance, refinement, evolution, access, search, and application. Stein and Zwass (1995) define an organizational memory information system (OMIS) as the processes and IT components necessary to capture, store, and bring to bear knowledge created in the past on decisions currently being made. Jennex and Olfman (2004) expanded this definition by incorporating the OMS into the KMS and adding strategy and service components to the KMS.

Knowledge Management Success Models

2010 ◽  
pp. 763-771
Author(s):  
Murray E. Jennex
Keyword(s):  
Information System ◽  
Knowledge Management ◽  
Knowledge Creation ◽  
Organizational Memory ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Organizational Processes ◽  
The Past ◽  
Ict System ◽  
Service Components

Alavi and Leidner (2001, p. 114) defined knowledge management systems (KMSs) as “IT-based systems developed to support and enhance the organizational processes of knowledge creation, storage/retrieval, transfer, and application.” They observed that not all KM initiatives will implement an IT solution, but they support IT as an enabler of KM. Maier (2002) expanded on the IT concept for the KMS by calling it an ICT system that supported the functions of knowledge creation, construction, identification, capturing, acquisition, selection, valuation, organization, linking, structuring, formalization, visualization, distribution, retention, maintenance, refinement, evolution, access, search, and application. Stein and Zwass (1995) define an organizational memory information system (OMIS) as the processes and IT components necessary to capture, store, and bring to bear knowledge created in the past on decisions currently being made. Jennex and Olfman (2004) expanded this definition by incorporating the OMS into the KMS and adding strategy and service components to the KMS.

The Role of Situated Embodied Interaction in the Banking Customer Knowledge Creation Process

2010 ◽  
pp. 236-251 ◽  
Author(s):  
Sara Värlander
Keyword(s):  
Knowledge Management ◽  
Knowledge Creation ◽  
Social Processes ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Embodied Interaction ◽  
Creation Process ◽  
Service Production ◽  
Point Of Departure

The increased reliance on Knowledge Management systems has made certain theorists to suggest that this will enable a surpassing of proximal knowledge creation, unequivocally leading up to more effective knowledge creation by easy codification and sharing of knowledge. However, in general, too much focus has been put on the potential of KM systems rather than its limits and the role of supporting social processes of knowledge creation has been largely ignored. The aim of the current research is to start to fill this gap in the KM literature by examining how social processes of knowledge creation are used in banking, taking the point of departure in an approach inspired from phenomenology. The paper illustrates how the increased use of KM systems has not decreased the need for relying on locally embedded service production, due to the invaluable knowledge creation processes that are generated through the embodiments of co-present interactions.

Technologies in Support of Knowledge Management Systems

2010 ◽  
pp. 784-796
Author(s):  
Murray E. Jennex
Keyword(s):  
Knowledge Management ◽  
Case Studies ◽  
Business Processes ◽  
Enterprise Systems ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Knowledge Capture ◽  
International Conference

Knowledge management systems (KMSs) support the various knowledge management (KM) functions of knowledge capture, storage, search, retrieval, and use. To do this, KMSs utilize a variety of technologies and enterprise systems. This chapter surveys the various technologies and enterprise systems. Specific attention is placed on enterprise systems that integrate KM into organizational business processes, and technologies that enhance the effectiveness of these implementations. The chapter is based primarily on research summarized in Case Studies in Knowledge Management (Jennex, 2005a) and articles published by the Knowledge Management Track at the Hawaii International Conference on System Sciences (HICSS).

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