پیش‌‌پردازش تصمیم‌‌گیری چند شاخصه با استفاده از داده‌‌کاوی (مطالعه موردی: انتخاب لجستیک شخص ثالث در برون‌‌سپاری خدمات وارانتی یک شرکت تولیدی تجهیزات الکترونیکی)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشیار، گروه مدیریت صنعتی، دانشکده علوم اجتماعی، دانشگاه بین‌‌المللی امام خمینی (ره)، قزوین، ایران

2 دانش‌آموخته کارشناسی ارشد مدیریت صنعتی، دانشکده علوم اجتماعی، دانشگاه بین‌‌المللی امام خمینی (ره)، قزوین، ایران

چکیده

در سال‌های اخیر، خدمات پس از فروش، یکی از مهم‌‌ترین عوامل مؤثر در رضایت مشتریان بوده است. ارائه خدمات پس از فروش و وارانتی هزینه‌‌های زیادی را به تولید‌‌کننده تحمیل می‌‌کند. ازاین‌‌رو اعمال سیاست‌‌های مناسب در این خصوص، از هزینه‌‌‌های بی‌‌‌مورد جلوگیری می‌‌نماید. امروزه یکی از سیاست‌های رایج وارانتی، برون‌‌سپاری وارانتی است که به آن «وارانتی شخص ثالث» می‌‌گویند. در برون‌‌سپاری وارانتی، با مسئله مهم انتخاب بهترین پیمانکار از بین شرکت‌‌های لجستیک شخص ثالث روبرو هستیم. در این مقاله رویکرد تصمیم‌‌گیری‌‌ چندشاخصه با به‌‌‌کار‌‌بردن داده‌‌کاوی، برای انتخاب شرکت‌‌های وارانتی شخص ثالث، توسعه ‌یافته است. این روش ترکیبی، شامل خوشه‌‌بندی به‌عنوان ابزار داده‌‌کاوی و روش سوارا و ویکور به‌عنوان فنون تصمیم‌‌گیری‌‌ چند‌‌شاخصه است؛ به‌این‌ترتیب که شرکت‌های وارانتی شخص ثالث، پس از شناسایی معیار‌‌های مهم برای برون‌‌سپاری وارانتی ازنظر تولید‌‌کننده، با ابزار‌‌های داده‌‌کاوی خوشه‌‌بندی می‌‌شوند. سپس خوشه‌‌های به‌دست‌آمده با استفاده از روش ویکور رتبه‌‌بندی و بهترین خوشه انتخاب می‌گردد. برای تعیین وزن معیار‌‌های تصمیم در روش ویکور، از روش سوارا استفاده ‌شده است. روش پیشنهادی، در یک شرکت تولید‌‌کننده تجهیزات الکترونیکی مورداستفاده قرارگرفته است. به‌‌کار‌‌گیری داده‌‌کاوی قبل از اجرای تصمیم‌‌گیری، اطلاعات با‌‌ارزش پنهان در داده‌‌های تاریخی شرکت را آشکار ساخته و تصمیم‌‌گیری را بهبود بخشیده است.

کلیدواژه‌ها


عنوان مقاله [English]

Preprocessing Multiple Criteria Decision-Making Using Data Mining (Case Study: Selection of third party logistic in outsourcing warranty services of an electronic facilities company)

نویسندگان [English]

  • safar fazli 1
  • reyhaneh jamaati tafti 2
1 Associate Professor, Department of Industrial Management, Faculty of Social science, Imam Khomeini International University, Qazvin, Iran
2 MA Graduate, Department of Industrial Management, Faculty of Social science, Imam Khomeini International University, Qazvin, Iran
چکیده [English]

In recent years offering after-sales services has been one of the most important factor in achieving customer satisfaction. Providing after-sales services and warranty implies an additional cost to the manufacturer. Therefore appropriate servicing strategy prevents unnecessary costs. Nowadays one of the common warranty Polices is outsourcing services to third-party warranty providers. An important issue that we are facing with is selecting the best provider. This article have developed MADM approach by using data mining for the selection of third-party warranty providers. This integrated approach includes clustering as a data mining tool and Step-wise Weight Assessment Ratio Analysis (SWARA) and VIKOR as the two MADM tools. After identifying the features that are important for outsourcing warranty from the perspective of the manufacturer, first third-party warranty service providers are clustered using data mining tools then VIKOR technique is used to rank the obtained clusters and the best cluster is selected. SWARA technique is used to weight decision criteria in VIKOR technique. Proposed approach was used in an electronic facilities company. Using data mining before the implementation of decision-making discovered the useful information that were hidden among historical data gathered by company and improved decision making process through providing effective information.

کلیدواژه‌ها [English]

  • third party warranty
  • Data Mining
  • Multiple Attribute Decision Making (MADM)
  • SWARA
  • VIKOR

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