یک چارچوب جامع برای انتخاب یک سیستم ERP
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|12280||2004||9 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 4222 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
- تولید محتوا با مقالات ISI برای سایت یا وبلاگ شما
- تولید محتوا با مقالات ISI برای کتاب شما
- تولید محتوا با مقالات ISI برای نشریه یا رسانه شما
پیشنهاد می کنیم کیفیت محتوای سایت خود را با استفاده از منابع علمی، افزایش دهید.
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Project Management, Volume 22, Issue 2, February 2004, Pages 161–169
This paper presents a comprehensive framework for combining objective data obtained from external professional reports and subjective data obtained from internal interviews with vendors to select a suitable Enterprise Resource Planning (ERP) project. A hierarchical attribute structure is proposed to evaluate ERP projects systematically. In addition, fuzzy set theory is used to aggregate the linguistic evaluation descriptions and weights. An actual example in Taiwan demonstrates the feasibility of applying the proposed framework.
An Enterprise Resource Planning (ERP) system is an integrated enterprise computing system to automate the flow of material, information, and financial resources among all functions within an enterprise on a common database . A successful ERP project involves selecting an ERP software system and vendor, implementing this system, managing business processes change (BPC), and examining the practicality of the system. However, a wrong ERP project selection would either fail the project or weaken the system to an adverse impact on company performance  and . Due to limitations in available resources, the complexity of ERP systems, and the diversity of alternatives, selecting an ERP project is a time-consuming task. Several methods have been proposed for selecting a suitable ERP project or management information system , , , , , ,  and . The scoring method  is one of the most popular. Although it is intuitively simple, it does not ensure resource feasibility  and . Teltumbde  suggested 10 criteria for evaluating ERP projects and constructed a framework based on the Nominal Group Technique (NGT) and the analytic hierarchy process (AHP) to make the final choice. Santhanam and Kyparisis  and  proposed a nonlinear programming model to optimize resource allocation and the interaction of factors; their model considered interdependencies of criteria in the information system selection process. Lee and Kim  combined the analytic network process (ANP) and a 0–1 goal-programming model to select an information system. However, these mathematical programming methods can not contain sufficient detailed attributes, above all, which are not easy to quantify, so that the attributes were restricted to some financial factors, such as costs and benefits. Furthermore, many of them involved only the consideration of internal managers, but do not offer a comprehensive process for combining evaluations of different data sources to select an ERP project objectively. Reports made by professional organizations and information collected from interviews with ERP suppliers should be considered in evaluating information of ERP projects. Professional organizations, such as research institutes and consulting companies, employ many experts to analyze information about ERP, including market share, vendor size, system performance, and other data. Their professional studies are very helpful to managers to have an overview of ERP systems and vendors. Furthermore, decision-makers can extract important attributes from these reports. However, the literature lacks studies on integrating the evaluation of objective external professional data sources and subjective internal interview data sources. This study aims to provide a new framework for integrating the two kinds of data evaluation for selecting a suitable ERP project. In reality, selecting a suitable ERP project involves multiple factors. Some of the measures, for example, the risk of the project, the functional fitness, and the ability of a vendor may not be precisely defined. Evaluation ratings under various attributes and the weights of the attributes are frequently assessed in linguistic terms, ‘high’, ‘poor’, among others. A fuzzy multiple-criteria decision-making method (FMCDM) is very useful in integrating various linguistic assessments and weights to evaluate ERP alternatives. This study proposes a comprehensive framework for selecting a suitable ERP project. Decision-makers can effectively integrate objective professional comments and subjective opinions of managers. A measure called, “fuzzy ERP suitability index” is used to account for the ambiguities involved in the evaluation of the appropriateness of ERP alternatives and the importance weights of attributes. An actual case in Taiwan is described to demonstrate the proposed method in practice.
نتیجه گیری انگلیسی
This study has proposed a comprehensive framework for selecting an ERP project that combines data obtained from professional studies with that surveyed from interviews with vendors. A hierarchical attributestructure including project, software, and vendor factors has been provided for evaluating ERP projects. An integration model that uses the fuzzy average method and fuzzy integral ranking has been developed. The final decision is determined by the highest total integral value. The results of a real example indicate that the proposed framework is very useful for selecting a sui- table ERP system selection. The proposed framework offers the following advan- tages in the ERP project. 1. It provides a comprehensive and systematic method. Decision-makers can easily select a sui- table ERP project by following the stepwise procedure. 2. It provides a simple and intuitive procedure for integrating the subjective opinions of decision- makers and the objective professional comments of external experts, thereby avoiding the use of a complex mathematical model. 3. The proposed algorithm considers not only quantitative data but also linguistic data. Man- agers can assess various attributes of a system, particularly in an ill-defined situation, by using linguistic or quantitative values. It can be refined since it flexibly accommodates additional con- siderations. 4. The values of l and k can be changed to deter- mine related changes in the prioritization of projects, with regard to the current business sit- uation, to solidify the final decision