دانلود مقاله ISI انگلیسی شماره 3671
عنوان فارسی مقاله

سرور ارزیابی هزینه - فایده برای پشتیبانی از تصمیم گیری در کسب و کار الکترونیکی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
3671 2003 17 صفحه PDF سفارش دهید محاسبه نشده
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عنوان انگلیسی
A Cost–Benefit Evaluation Server for decision support in e-business
منبع

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

Journal : Decision Support Systems, Volume 36, Issue 1, September 2003, Pages 81–97

کلمات کلیدی
ارزیابی هزینه و فایده - کسب و کار الکترونیک - پشتیبانی تصمیم گیری -
پیش نمایش مقاله
پیش نمایش مقاله سرور ارزیابی هزینه - فایده برای پشتیبانی از تصمیم گیری در کسب و کار الکترونیکی

چکیده انگلیسی

Business organizations are often faced with decision situations in which the costs and benefits of some competing business specifications such as business offers, product specifications, or negotiation proposals need to be evaluated in order to select the best or desirable ones. In e-business, there is a need to automate the cost–benefit evaluation process to support decision making. This paper presents a general-purpose Cost–Benefit Evaluation Server (CBES) and its underlying Cost–Benefit Decision Model (CBDM), which models benefits in terms of costs and logical scoring and aggregation of preferences associated with products and services. The Server provides build-time tools for users to specify preference and cost information and a run-time engine to perform cost–benefit evaluations. A business scenario involving supplier selection and automated negotiation is given to illustrate the application of the Server and its four evaluation modes.

مقدمه انگلیسی

With the advent of the Internet, collaborative e-business has been attracting more and more attention from both academia and industry [22] and [24]. Various technologies are being developed to support collaborative e-business, such as customer relationship management [27], supply chain management [19] and [20], eMarketplaces [1] and [5], and automated negotiation and auction systems [3], [18], [21] and [32]. In e-business, a business company or person often faces a decision situation in which a cost–benefit analysis (CBA) of a business specification needs to be performed before an appropriate decision can be made or a proper action can be taken. By “business specification”, we mean any business document that specifies terms and conditions of a business transaction, offer, or proposal. For example, in supplier selection, a buyer often needs to evaluate a number of supplier specifications that describe different suppliers' capabilities in order to choose the best one from a list of candidate suppliers. In business negotiation, a company needs to evaluate a negotiation proposal of another company in order to determine the cost and benefit of an offer. In the decision to purchase, a company may receive a number of responses from different vendors after issuing a “request-for-quote”. They need to be evaluated to determine their costs and benefits. A business specification may contain many terms and conditions. Their relative importance to an evaluator and their interrelationship will have to be taken into consideration in a cost–benefit evaluation. Also, a business specification may have different costs and benefits to different evaluators. Subjectivity is unavoidable in cost–benefit evaluation and, for that matter, in decision making. However, it is important to have a quantitative way to calculate the costs and to evaluate the benefits of the terms and conditions given in a specification so that an overall cost–benefit indicator (or value) can be assigned to it and be compared with the overall cost–benefit indicators of other competing specifications. A decision made based on the result of a quantitative evaluation and selection is traceable and justifiable because it can be shown how the best overall cost–benefit value is quantitatively derived based on the subjective opinion of the evaluator. In order for cost–benefit evaluation to be useful in the context of e-business, we need (1) a structured way to present a business specification so that it can be more easily processed by computers, (2) a quantitative Cost–Benefit Decision Model (CBDM) to calculate costs and to capture the preferences of decision makers based on which cost–benefit evaluation of business specifications can be performed, (3) a Cost–Benefit Evaluation Server (CBES) capable of evaluating multiple business specifications concurrently, and (4) a scalable Internet-based information infrastructure to support collaborative e-business. CBA is the comparative analysis of alternatives in terms of their costs and consequences [33]. It is one of the most common and popular evaluation techniques used to evaluate programs and products. Since Eckstein [12] first deployed CBA techniques for benefit estimations using market information, the scope of cost–benefit analysis has been extended to other application areas, such as health care-related economic evaluation [13], [15], [29] and [33], financial decision for business [2], [7] and [19], government management and administration [4], [8], [9], [14] and [28], and environmental damage assessment [6] and [17]. Researchers have introduced different models and approaches with different assumptions and values in the evaluation of costs and benefits to improve the service of CBA [4], [10], [13], [30] and [33]. In these models, both costs and benefits are measured in monetary terms. Cost–benefit analysis is used to determine whether the benefit of a specification measured in dollars outweigh its cost and thus justify the allocation of resources to that specification. The cost–benefit ratio and the net benefit are commonly used as evaluation indices. The evaluation of business specifications in government management and administration model is based on the computer-supported process in which personal data records relating to many people are compared in order to identify cases of interest (or benefit) [4], [14] and [28]. In regard to the valuation of benefit in some other models, the benefit is evaluated according to either what individuals would be willing to pay for the benefit or an individual's value that is measured by the discounted value over time [4], [8] and [33]. The net benefit is the summation of all the comprehensive benefits, including outcomes that are monetary, quantitative, qualitative [6], and/or the estimation of future monetary benefits, if applicable [7], [29] and [33]. Obviously, these evaluation systems are designed for specific purposes and cannot be generically applied. Moreover, the evaluation is too simple to handle specifications with hierarchical structures. The evaluation service implemented in AVICOM [2] and Indent [19] can deal with complicated business specifications with multiple alternatives, but either the evaluation system is predefined or the evaluation is by simulation, thus lacking flexibility. Also, users cannot directly interact with the cost–benefit evaluation tools. The CBDM [30], which is based on the concept of logical scoring of preferences (LSPs), provides a comprehensive cost analysis and an elaborate analysis of benefits expressed in terms of the decision maker's preferences. However, as a general model, it only allows a single value to be specified for each attribute in a business specification. The business specifications that all the existing cost–benefit evaluation systems take as input can only have a single value for each of its attributes. None of them accepts a specification that contains an attribute having an enumeration of discrete values (ENUM type) or a range of values (RANGE type). Consequently, an evaluation system has to be invoked many times to evaluate all the business specifications one by one. For example, a company wants to buy a product and the purchase specification contains, among other attributes and values, the following attributes: {quantity={RANGE[800, 900]}; delivery_day=ENUM{7, 14, 21}}. In this case, the company would accept any quantity between 800 and 900, and the number of days for the delivery can be either 1, 2, or 3 weeks. In a traditional cost–benefit evaluation system, a preprocessor has to be used to take all the value combinations and feed each combination as a different specification into the evaluation tool. This is obviously inefficient. In this paper, we describe a general-purpose CBES, which is implemented based on an extended quantitative CBDM [30], to support e-business. The extended CBDM allows all types of business specifications to be defined in terms of a structure of attributes, each of which can have a range of continuous values or an enumeration of discrete values. Thus, a business specification may specify a number of value combinations, each of which represents an alternative business offer or proposal. These value combinations can be evaluated by CBES at the same time and in different modes of evaluation. CBES provides a set of build-time specification tools and a runtime evaluation engine. The build-time tools provide a set of Web-based interfaces to assist a decision maker to specify his/her preference scoring and aggregation methods, based on which the run-time evaluation engine performs cost and benefit (or preference) analysis on a given business specification. The run-time evaluation engine works in four different modes: EXHAUSTIVE, BEST, WORST, and APPROXIMATE. They have different time complexities in evaluation and can be applied in different decision situations. The main differences between our CBDM and CBES and the existing models and systems are as follows. First, our model captures the subjective preferences of decision makers (i.e., individuals or business organizations) with respect to different attributes and values presented in a business specification, and our system provides the user-friendly GUI tools to capture the information. Second, our model and system allow more elaborate structures to be specified by decision makers for aggregating the preference scores (PS) assigned to attribute–value or attribute–value–range pairs to derive the global preference score (GPS). Third, our system supports a wide spectrum of preference aggregation functions to fit different decision situations. Fourth, the input business specification can contain attributes of RANGE and ENUM types instead of limiting each attribute to have a single value, and the evaluation system is able to calculate preference scores for both discrete values and value ranges. Last, but not the least, CBES offers several different modes of cost–benefit evaluation to meet the different users' needs. The R&D work on CBES is a part of a larger research effort in building an information infrastructure for supporting collaborative e-business. In [31] and [32], Su et al. present an information infrastructure to support Internet-based Scalable E-business Enterprises (ISEE). The ISEE infrastructure consists of a network of ISEE Hubs. Each ISEE Hub contains a number of servers. Each server provides a number of e-services to support collaborative e-business. Business companies register with these distributed ISEE Hubs and make use of their e-services to conduct e-business collaboratively. The Cost–Benefit Evaluation Server presented in this paper is one of the replicable servers of the ISEE infrastructure. This paper is organized as follows. In Section 2, the Cost–Benefit Decision Model is presented. In Section 3, the four run-time evaluation modes and the algorithms for implementing them are presented. The implementation of CBES is discussed in Section 4. In Section 5, an e-business scenario involving supplier selection and automated negotiation is used to illustrate the application of CBES and its evaluation modes. Finally, the key features of CBES are summarized in Section 6.

نتیجه گیری انگلیسی

The design and implementation of a general-purpose Cost–Benefit Evaluation Server for supporting decision making in e-business has been presented. We have extended a Cost–Benefit Decision Model used in our earlier work to allow attributes of a business specification to contain enumerated values or value ranges. It also allows the user to assign preference scores to values and value ranges. Thus, CBES can efficiently evaluate a business specification that contains a number of value combinations. CBES provides a number of build-time GUI tools for capturing preference and cost information from different decision makers and a run-time engine to evaluate business specifications based on the subjective preference scoring methods and aggregation functions selected by different decision makers. In the ISEE infrastructure, multiple CBESs can be installed in multiple ISEE Hubs. Each business company can register and maintain its preference and cost information in its own CBES, thus keeping the information private. CBES has the following features. First, the extended Cost–Benefit Decision Model captures the subjective preferences of decision makers with respect to different attributes and values presented in business specifications. Second, the model allows very elaborate aggregation structures to be specified by decision makers for aggregating the preference scores assigned to individual attribute–value or attribute–value–range pairs. Third, the system supports a wide spectrum of preference aggregation functions to fit different decision situations. Fourth, the input business specification can contain attributes of RANGE and ENUM types instead of limiting each attribute to have a single value, and the evaluation system is able to calculate preference scores for both discrete values and value ranges and to derive evaluation functions by interpolation. Last, but not least, CBES offers several modes of operations to meet the different cost–benefit evaluation needs of the users. In this work, we assume that templates can be predefined for different types of business specifications, thus standardizing the ontology used in business communication and evaluation. We believe that this is a reasonable assumption because several groups in the industry, such as the Open Application Group [23] and RosettaNet [26], have been developing standard terms and structures for specifying business object documents.

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