Identifying and prioritizing technology capability drivers in the supply chain using the fuzzy hierarchical analysis process (Case study: Iran Khodro and Saipa Automotive Company)

سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 153

فایل این مقاله در 18 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_RIEJ-12-1_007

تاریخ نمایه سازی: 5 اردیبهشت 1402

چکیده مقاله:

This study aims to identify and prioritize the effect of technology capability drivers on the supply chain performance of automotive companies. Technology capability indicators are ranked and prioritized using the fuzzy hierarchical analysis technique. The research method is applied in terms of purpose, is described as the data collection method, and is considered quantitative research. After reviewing the theoretical literature of the research, the drivers of technology capability on the organization's performance were identified for prioritization; they were weighed by a number of experts in the field of automotive companies using questionnaires and fuzzy hierarchical analysis. Indicators and sub-indices of variable technology capability were ranked and prioritized. Based on the results of this research model, it was found that of the eight indicators examined, "strategic technology capability", "product technology capability", and "supplier technology" was the most important, and of the ۳۸ technology capability sub-indicators examined, "Technology Development" is the most important.

نویسندگان

Ali Ehsani

Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

Hassan Mehrmanesh

Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

Mahmoud Mohammadi

Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :