شناسایی عوامل مؤثر در سنجش چابکی با رویکردی آمیخته از روشهای کیفی و کمی (مطالعه موردی: صنعت خودروسازی)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مدیریت صنعتی، دانشکده مدیریت، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران

2 گروه مدیریت صنعتی، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران

3 استاد تمام دانشگاه تهران، دانشکده مدیریت، گروه مدیریت صنعتی

چکیده

دستیابی به تولید چابک در هر صنعت تولیدی، در ابتدا نیازمند سنجش وضعیت چابکی در آن صنعت است. هدف این مقاله، شناسایی و تبیین عوامل اصلی سنجش چابکی در صنعت خودروسازی به عنوان مهم‌ترین صنعت غیرنفتی کشور است. این پژوهش، از لحاظ هدف، یک تحقیق کاربردی و از نظر روش، یک تحقیق آمیخته (کیفی و کمی) می‌باشد. جامعه آماری تحقیق را در بخش کیفی، خبرگان دانشگاه و صنعت خودروسازی کشور و در بخش کمی، کارشناسان صنعت مذکور تشکیل می‌دهد و روش گردآوری اطلاعات از طریق پرسشنامه بوده است. در بخش کیفی، ابتدا با جستجوی مقالات پژوهشیِ مرتبط با موضوع به روش فرا ترکیب، 89 منبع انتخاب شده و 27 معیار سنجش چابکی شناسایی گردید. سپس این معیارها با نظرسنجی از 16 نفر از خبرگان صنعت خودروسازی کشور به روش دلفی فازی، مورد تأیید قرار گرفته و به صنعت مذکور تعمیم داده شد. در ادامه، معیارها با استفاده از روش نگاشت شناختی و به کمک 5 نفر از خبرگان صنعت و دانشگاه در 4 خوشه کلی محرک‌های چابکی، توانمندساز‌های چابکی، راهبرد‌های چابکی و قابلیت‌های چابکی دسته‌بندی شدند. در بخش کمی، با توزیع پرسشنامه و نظرسنجی از 286 نفر از کارشناسان صنعت خودروسازی، عوامل استخراج شده در بخش کیفی به روش تحلیل عاملی تأییدی صحه‌گذاری گردیدند. این عوامل و معیارها می‌توانند ابزار مناسبی برای مدیران صنایع تولیدی جهت ارزیابی، سنجش و تحلیل فاصله چابکی سازمان‌های خود باشند. توانمندساز‌های چابکی، راهبرد‌های چابکی و قابلیت‌های چابکی، سطح چابکی فعلی سازمان را اندازه‌گیری نموده و محرک‌های چابکی، سطح چابکی مورد نیاز سازمان را می‌سنجد.

کلیدواژه‌ها


عنوان مقاله [English]

Identifying Agility Assessment Factors using a mixed approach of qualitative and quantitative methods (case study: Automotive Industry)

نویسندگان [English]

  • Eisa Roghani Mamaghani 1
  • Jala Haghighat monfared 2
  • Ahmad Jafarnejad 3
1 Department of Industrial Management , Faculty of Management. Central Tehran Branch, Islamic Azad University, Tehran, Iran
2 Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
3 Department of Industrial Management, University of Tehran, Tehran, Iran
چکیده [English]

To achieve agile manufacturing in any manufacturing industry, needed to measure agility in that industry. The purpose of article is to identify and explain the main factors for measuring agility in the automotive industry as the most important non-oil industry. This research is an applied research in terms of purpose and a mixed qualitative-quantitative research in terms of method. The statistical population of the research in qualitative section is the academics and the automotive industry managers, and in the quantitative section is the experts of the mentioned industry. The method of collecting information has been through a questionnaire. In the qualitative section, First, by researching related articles by meta-synthesis method, 89 sources were selected and 27 criteria for measuring agility were identified. Then the criteria were generalized to the automotive industry by surveying 16 experts using fuzzy Delphi method. Then these criteria were categorized into 4 general clusters of agility drivers, agility enablers, agility strategies and agility capabilities using cognitive mapping method and with the help of 5 industry and university experts. In the quantitative part, by distributing questionnaires and surveys of 286 experts in the automotive industry, the extracted factors were validated by confirmatory factor analysis. These factors and criteria can be a good tool for managers of manufacturing industries to assess and gap analysis of the agility of their organizations. Agility enablers, agility strategies and agility capabilities measure the current level of agility of the organization and agility drivers measure the level of agility required by the organization.

کلیدواژه‌ها [English]

  • Agility Assessment of Automotive Industry
  • Meta-synthesis
  • fuzzy Delphi
  • cognitive mapping
  • factor analysis
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