مدیریت زنجیره تامین پایدار: مدل تصمیم گیری
ترجمه نشده

مدیریت زنجیره تامین پایدار: مدل تصمیم گیری

عنوان فارسی مقاله: مدیریت زنجیره تامین پایدار: مدل تصمیم گیری برای کمال و دگرگونی
عنوان انگلیسی مقاله: Sustainable supply chain management: Decision models for transformation and maturity
مجله/کنفرانس: سیستم های پشتیبانی تصمیم – Decision Support Systems
رشته های تحصیلی مرتبط: مهندسی صنایع، مدیریت
گرایش های تحصیلی مرتبط: لجستیک و زنجیره تامین، مدیریت صنعتی
کلمات کلیدی فارسی: زنجیره تامین؛ پایداری؛ دلفی؛ مدل تصمیم گیری؛ تکامل؛ دگرگونی
کلمات کلیدی انگلیسی: Supply Chains; Sustainability; Delphi; Decision Models; Maturity; Transformation
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.dss.2018.07.002
دانشگاه: Cranfield University – School of Management – United Kingdom
صفحات مقاله انگلیسی: 44
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2018
ایمپکت فاکتور: 5.421 در سال 2018
شاخص H_index: 127 در سال 2019
شاخص SJR: 1.536 در سال 2018
شناسه ISSN: 0167-9236
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: بله
کد محصول: E8596
فهرست مطالب (انگلیسی)

Abstract

1- Introduction

2- Literature review

3- SSCM Delphi study

4- Decision models for sustainable transformation and maturity of supply chains

5- Discussion and conclusion

References

بخشی از مقاله (انگلیسی)

Abstract

: Academics and practitioners have realized that supply chains with their many interactions and impacts have to be investigated in order to meet corporate sustainability imperatives. Research has thus far offered only limited theoretical guidance while practical applications often lack a systematic approach. The realization of sustainability goals is impeded by disconnects between supply chain vision, strategy, and execution. This research bridges this gap and offers guidance through the identification and description of influential factors and decision models. An exploratory Delphi study involved supply chain and sustainability experts with the goal to explore and propose factors and decision processes for sustainable supply chain management. This study builds upon the insights offered by seminal models and leverages the Delphi mechanisms of exploration and controlled feedback in order to design, refine, and validate decision models through three consecutive rounds. This Delphi facilitated the identification and assessment of vital relationships and influential factors for sustainable supply chain management. The study culminates in the design and validation of models specifically targeted at the transformation and on-going maturity development of sustainable supply chains. The combination of research outcomes provides targeted decision support to supply chain managers which is desperately needed in order to drive sustainability development and implementation. The main contributions of the study thus are (1) the design of prescriptive artefacts that describe relationships in SSCM, (2) to offer targeted and evaluated decision support functionalities for sustainable supply chains, and (3) to provide fertile ground for future research enquiries. 

Introduction

Corporate sustainability is about addressing and managing business decisions with regard to economic, social, and environmental dimensions in a balanced and integrated manner (Elkington, 1998). Supply chains (SC) are integral to almost all commercial activities nowadays and often involve global interactions as well as unknown and potentially adverse impacts. Hence, SCs need to be at the very core of sustainability developments (Kleindorfer, Singhal, & Van Wassenhove, 2005). External forces such as competitors, regulations, globalization effects, as well as stakeholder and customer demands pressure SCs to integrate sustainability principles into their strategy and daily operations (Carter & Rogers, 2008; Jayaraman, Klassen, & Linton, 2007; McIntyre, 2007; Seuring & Müller, 2008b). Sustainable supply chain management (SSCM) has emerged as a field of research and practice to address related challenges.