دانلود مقاله ISI انگلیسی شماره 7498
ترجمه فارسی عنوان مقاله

یکپارچه سازی ابزار داده کاوی مبتنی بر وب با مدل های کسب و کار برای مدیریت دانش

عنوان انگلیسی
Integrating web-based data mining tools with business models for knowledge management
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
7498 2003 10 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Decision Support Systems, Volume 35, Issue 1, April 2003, Pages 103–112

ترجمه کلمات کلیدی
- داده کاوی مبتنی بر وب - مدیریت دانش - مدل های کسب و کار - هوش کسب و کار - بینش های کسب و کار - مزیت رقابتی
کلمات کلیدی انگلیسی
پیش نمایش مقاله
پیش نمایش مقاله  یکپارچه سازی ابزار داده کاوی مبتنی بر وب با مدل های کسب و کار برای مدیریت دانش

چکیده انگلیسی

As firms begin to implement web-based presentation and data mining tools to enhance decision support capability, the firm's knowledge workers must determine how to most effectively use these new web-based tools to deliver competitive advantage. The focus of this study is on evaluating how knowledge workers integrate these tools into their information and knowledge management requirements. The relationship between the independent variables (web-based data mining software tools and business models) and the dependent variable (strategic performance capabilities) is empirically tested in this study. The results from this study demonstrate the positive interaction effect between the tools and models application on strategic performance capability.

مقدمه انگلیسی

As firms expand and begin to compete in the global marketplace, senior managers are positioning their firms using strategic business initiatives designed to produce competitive advantage. These initiatives range from acquiring new computer-based decision support applications that help increase efficiency and improve effectiveness of the firm to moving massive paper-based information sources into electronic form, to facilitating data mining and insight generation. As these strategic initiatives are implemented, the information storage requirements have caused the firms' data warehouses to expand geometrically. In 1999, it was estimated that 30% of firms' data warehouses contained greater than one trillion characters of data [4]. As a result, the firm's knowledge workers have been presented with a plethora of data to be understood and to be mined. As a part of the integrated effort in managing information and knowledge, firms are increasingly required to use web-based business intelligence and data mining tools coupled with on-line analytical processing technology to make sense of and to gain competitive insight into this vast volume of data. Hence, the implementation of web-based data mining tools has become one of the key priorities for the firm's Chief Information Officer (CIO) [22]. Business intelligence capability can be used in the decision support infrastructure to assist the firm's knowledge workers in the development of strategic business opportunities and can alert the knowledge workers to investigate potential problem areas in current business operations. The firm's knowledge workers can use these intelligence presentation tools and data mining software to uncover market opportunity, monitor product performance, understand changing customer requirements, and manage customer relationships in real-time. Therefore, it can be inferred that with the proper use of these web-based knowledge generation tools, the firm can achieve a significant competitive advantage as knowledge workers develop greater insights into the marketplace [28] and [29]. As firms have realized the potential of knowledge-based business decisions to achieve competitive advantage, the business intelligence and data mining software tool industry has exploded [26]. This software industry segment has grown from over US$2 billion in sales in 1998 to an estimated US$4 billion in sales in 2001 [4]. Yet, as CIOs race to satisfy the demands of their senior management to provide the knowledge workers with these leading-edge software tools, they have realized a low implementation success rate. Approximately, 25% of the implementation projects begun by firms have been a complete failure resulting in the abandonment of the adopted business intelligence software tools. Among the remaining 75% of these implementation projects, many firms are not utilizing these software tools' functionality as originally intended or are not getting the full value from their resource investment. Expert practitioners in this field have stated that these software applications are high-risk/high-return projects and that these projects are expensive to implement [2], [14], [16], [20], [27] and [30]. Further, despite the importance placed on these knowledge-based systems, only 32% of the firms surveyed were satisfied with the information provided by the resulting applications [17]. There are a variety of reasons to explain the relatively low implementation success rate and the relatively low satisfaction ratings from these projects. The typical reasons identified from recent studies include technical complexity issues, lack of senior management focus, inflexibility of the software tools, and difficulty in assessing benefits provided to the firm. Yet, in spite of these dismal implementation project success and satisfaction ratings, this software tool industry segment continues to experience a dramatic 40% compounded annual sales growth rate. It appears that firms looking to develop a competitive advantage are pushing their IT department to deliver these web-based insight generation tools for their firms' information and knowledge management. Therefore, the firm must determine how to overcome the typical reasons for implementation failure [1], then they must successfully implement these new tools for managing knowledge, and finally, they must determine how to use these web-based tools to deliver competitive advantage. This study develops and empirically tests a conceptual model of integrated web-based knowledge management.

نتیجه گیری انگلیسی

The main effect for the web-based data mining tools and for the use of business models was significant at the 0.01 level. The X1·X2 interaction effect was also significant at the 0.05 level. At the low business models level, web-based data mining tools with guided analysis functionality enable the novice knowledge worker to achieve insight and success with relatively little investment in effort. At the medium business models level, web-based data mining tools provides the knowledge worker with the functionality required to perform in-depth analysis to gain insights, yet the knowledge worker does not have the capability to utilize the results. At the high business models level, web-based data mining tools with the presentation management functionality enables the knowledge worker to generate more options and to evaluate more alternatives. The positive interaction effects indicate a synergistic effect that is occurring between the business models and data mining tools. A model was proposed highlighting the integration between technology and knowledge worker capability and its impact on the firm's competitive advantage. As such, this research has focused on investigating the relationship of web-based tools and business models on strategic performance capabilities. To develop leading-edge competitive insights, knowledge workers must have access to web-based data mining tools that are integrated with the firm's strategic business models. This integration will manifest itself as firms require knowledge workers to become skilled in strategic opportunity identification. In addition, web-based data mining tools must integrate business application models and various external data sources to provide the knowledge workers with a complete picture of the turbulent, dynamic competitive environment leading to effective knowledge management. As previously described, the knowledge workers' mental model provides the initial knowledge base for the firm. Their mental models of the environment are based on many things including proven strategic business models and their paradigm of the industry and market in which the firm operates. Their paradigms indicate when to apply various analytic models. The decision problem yields strategic performance measures involved in understanding the environmental situation. Web-based data mining tools provide the ability to understand and interpret the generated information. Combined, they provide the knowledge worker with the ability to focus. Thus, business intelligence is viewed as the ability of the knowledge worker in the firm to apply specific knowledge to respond proactively to the environment. Then, specific knowledge is formulated into action plans. This market-oriented approach to planning recognizes that environmental scanning, sense-making, customer-value, and strategic planning activities must be shared throughout the firm [25]. It is a core competency of the firm that must be developed and shared in its decision support system. In fact, the ability to manage knowledge may be the only remaining source of competitive advantage for the firm. In this knowledge era, all of the stakeholders in the firm must be involved in the environmental scanning and sense-making function of the firm. The results provide an insight into the combined effect from these web-based software tools and business models in improving strategic performance capabilities. Understanding the synergistic improvement effect can help to explain why web-based software tools alone experience the identified implementation failure rates and low satisfaction ratings. A combination of business model application and integration with web-based software tools is required. Firms that are oriented towards continuous learning and knowledge management will have less unconverted data than their less learning oriented competitors. In turbulent environments, firms should have a corporate culture with knowledge management processes that yield the flow of the right information and knowledge to the right people at the right time for the right reason. Firms are implementing web-based data mining tools to develop the speed that enables the firm to achieve competitive advantage in the global marketplace. Yet, web-based data mining tools embedded in the decision support system are not the ultimate panacea. The road to success is not paved with gold and a one-size business intelligence or data mining tool does not fit all firms. Those firms intent on achieving success must be cognizant of the caveats and must provide their knowledge workers with the appropriate web-based business intelligence and data mining tools, business models, and training required to achieve strategic insights that ultimately translate to competitive advantage.