Product pricing decision support fuzzy systems through the Internet

2002 ◽  
Author(s):  
R. Gomes ◽  
R. Pacheco ◽  
A. Martins ◽  
R. Weber ◽  
R. Barcia
Keyword(s):  
Decision Support ◽  
Fuzzy Systems ◽  
The Internet ◽  
Product Pricing ◽  
Pricing Decision

Similarity-Based Decision Support for Internet Enabled Supply-Web Interactions

1998 ◽  
Author(s):  
Raj Veeramani ◽  
Narayanan Viswanathan ◽  
Shailesh M. Joshi
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Manufacturing Industry ◽  
Job Shop ◽  
The Internet ◽  
Agent Based ◽  
New Approaches ◽  
Effective Decision ◽  
Use Of The Internet ◽  
Effective Decision Making

Abstract New approaches for decision making are emerging to support the use of the Internet for supply-web interactions in the manufacturing industry. In this paper, we discuss one such paradigm, namely similarity-based decision support. It recognizes that knowledge of similar experiences can support rapid and effective decision making in various forms of supply-web interactions. We illustrate this approach using two prototype systems, WebScout (an agent-based system for customer–supplier matchmaking in the job-shop machining industry context) and TOME (Treasury of Manufacturing Experiences — an Intranet application to aid manufacturability assessment in foundries).

Fuzzy system approaches to negotiation pricing decision support

2015 ◽  
Vol 29 (2) ◽  
pp. 685-699 ◽  
Author(s):  
Xin Fu ◽  
Xiao-Jun Zeng ◽  
Di Wang ◽  
Di Xu ◽  
Longzhi Yang
Keyword(s):  
Decision Support ◽  
Fuzzy System ◽  
Pricing Decision ◽  
System Approaches

scholarly journals A FUZZY LOGIC ENHANCED BARGAINING MODEL FOR BUSINESS PRICING DECISION SUPPORT IN JOINT VENTURE PROJECTS / FUZZY LOGINIO PASIKEITIMŲ VERTINIMO METODO TAIKYMAS JUNGTINĖS VEIKLOS PROJEKTŲ VERTEI NUSTATYTI

2011 ◽  
Vol 12 (2) ◽  
pp. 234-247 ◽  
Author(s):  
Min-Ren Yan
Keyword(s):  
Decision Support ◽  
Set Theory ◽  
Joint Venture ◽  
Bargaining Model ◽  
Decision Support Model ◽  
Short Term ◽  
Bargaining Process ◽  
Pricing Decisions ◽  
Pricing Decision ◽  
Bargaining Positions

Project businesses are increasingly emerging and many companies cooperatively participate in various projects by the manner of joint venture (JV) for creating synergistic competitiveness. In a project-based short-term JV, the project tasks of JV parties can be properly allocated based on complementary specialties but the rewards sharing is always a challenge in the bargaining process. For improving the manager's reasoning process of pricing decisions, this paper incorporates game theory and fuzzy set theory for the development of a bargaining model, which can be used to estimate acceptable prices for JV parties in accordance with each party's costs and each party's need for the project's revenue. The proposed decision support model can assist JV companies to understand their bargaining positions and select a bargaining strategy in a systematic and rational manner. Irrational offers and alternatives can also be detected and eliminated during the dynamic bargaining process, so as to maintain right businesses. Santrauka Verslo projektai savo dydžiu, tematika, pobūdžiu ir kitais aspektais nuolat kinta, todėl dauguma kompanijų, siekdamos išlaikyti konkurencinį pranašumą bei rengdamos įvairius projektus, jungiasi į tam tikras jungtines įmones, kurios vykdo jungtines veiklas, skirtas tik tam projektui įgyvendinti. Tokios įmonės, kurios apribotos projekto trukmės, įgauna tam tikrų savybių, kai tikėtina nauda iš šio susijungimo yra neapibrėžta ir nuolat kinta. Šio straipsnio autoriai, siekdami pagerinti motyvacinę vadovų sistemą, priimdami sprendimus dalyvauti jungtinėje veikloje ir įvertindami priimtiną santykį tarp investuojamos sumos dydžio ir tikėtinos naudos, taiko žaidimų teoriją bei Fuzzy metodą.

scholarly journals Metode Simple Additive Weighting (SAW) Dalam Pemilihan Sim Card Provider

2020 ◽  
Vol 1 (2) ◽  
pp. 97-108
Author(s):  
Andy Widya Putera ◽  
Anna Mukhayaroh ◽  
Samudi
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
The Internet ◽  
Community Activities ◽  
Internet Connection ◽  
Sim Card ◽  
Using Data ◽  
Simple Additive Weighting ◽  
Selection Of

With the development of technology at this time Sim Card Provider is needed to support community activities. In Indonesia alone many Sim Card Provider many services and also ease of accessing the internet, sonsumers are required to see which Sim Card Provider suits their needs. To overcome the problem of selecting the Sim Card Provider, a Decision Support System will be made using the Simple Additive Weighting (SAW) method using data taken from questionnaires distributed to Sim Card Provider users, which is expected to help in the selection of the appropriate Sim Card Provider with Consumer needs. The author uses six criteria, namely Signal, Price, Internet Package, Internet Connection, Phone Bonus, SMS Bonus. By using five alternatives namely Simpati, XL, Indosat, Smartfren, Three (3). The final result of this study indicated that alternative 5 or Three (3) has the biggest result of 3,245 and alternative 3 namely Indosat has the lowest result among the alternatives which is 2,625.   Keywords: Criteria, Sim Card Provider, Simple Additive Weighting   Abstrak   Dengan berkembangnya teknologi pada saatini Sim Card Provider sangat dibutuhkan untuk menunjang aktivitas masyarakat. Di Indonesia sendiri banyak Sim Card Provider banyak menyediakan layanan dan juga kemudahan dalam mengakses internet, konsumen dituntut untuk melihat manakah Sim Card Provider yang sesuai dengan kebutuhan. Untuk mengatasi masalah pemilihan Sim Card Provider tersebut maka akan dibuat Sistem Pendukung Keputusan dengan menggunakan Metode Simple Additive Weighting (SAW) dengan menggunakan data yang diambil dari kuesioner yang dibagikan kepada para pengguna Sim Card Provider, yang diharapkan dapat membantu dalam pemilihan Sim Card Provider yang sesuai dengan kebutuhan Konsumen. Penulis menggunakan enam kriteria yaitu Sinyal, Harga, Paket Internet, Koneksi Internet, Bonus Telpon, Bonus Sms. Dengan menggunakan lima alternatif yaitu Simpati, XL, Indosat, Smartfren, Three (3). Hasil akhir dari penelitian ini menunjukan bahwa alternatif 5 atau Three (3) memiliki hasil terbesar yaitu 3,245 dan alternatif 3 yaitu Indosat memiliki hasil terendah diantara alternatif yang ada yaitu 2,625. Kata kunci: Kriteria, Sim Card Provider, Simple Additive Weighting

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