شناسایی و اولویت‌بندی عوامل حیاتی کسب‌وکار الکترونیک بر اساس روش بهترین- بدترین

حسینی دهشیری, سید جلال‌الدین; آقایی, مجتبی; تقوی فرد, محمدتقی

doi:10.22054/ims.2018.9742

نوع مقاله : مقاله پژوهشی

نویسندگان

¹ دانشجوی دکتری مدیریت صنعتی، مدیریت تولید و عملیات، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران.

² دانشجوی دکتری مدیریت صنعتی، تحقیق در عملیات، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران.(نویسنده مسئول)؛mojtaba_aghaei68@yahoo.com

³ دانشیار، گروه مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران.

https://doi.org/10.22054/ims.2018.9742

چکیده

امروزه بهره‌گیری از کسب‌وکار الکترونیک برای پاسخ‌گویی به چالش‌های محیطی اهمیت دارد. برای اجرای کسب‌وکار الکترونیک، عوامل مهمی به نام عوامل حیاتی موفقیت وجود دارد که اجرای آن را آسان نموده و در صورت فقدان مناسب این عوامل، اجرای آن ممکن است با شکست مواجه شود؛ بنابراین با توجه به اهمیت کسب‌وکار الکترونیک و نقش عوامل حیاتی موفقیت در پیاده‌سازی آن، در این پژوهش به شناسایی و اولویت‌بندی عوامل حیاتی موفقیت برای اجرای کسب‌وکار الکترونیک پرداخته شد.در ابتدا با بررسی جامع ادبیات تحقیق، چارچوبی جامع برای شناسایی جامع عوامل حیاتی موفقیت تدوین شد. سپس با بهره‌گیری از روش دلفی فازی و نظرات خبرگان عوامل شناسایی شده، تعدیل و نهایی شدند. در مرحله بعد با بهره‌گیری از روش بهترین- بدترین که از جدیدترین و دقیق‌ترین تکنیک‌های وزن دهی است، عوامل حیاتی موفقیت تائید شده از مرحله قبلی اولویت‌بندی شدند. نتایج نشان داد که عوامل حمایت مناسب مدیریت و مالکیت، حمایت مالی کافی و هم‌راستایی و ارتباط بین فناوری اطلاعات و استراتژی کسب‌وکار به‌عنوان مهم‌ترین عوامل حیاتی موفقیت شناسایی شدند.

کلیدواژه‌ها

عنوان مقاله [English]

Schematic Design of Hotel Recommendation Systems by user Precedence on Twitter

نویسندگان [English]

Seyyed Jalaladdin Hosseini Dehshiri ¹
Mojtaba Aghaei ²
Mohammad’Taghi Taghavifard ³

¹ Ph.D. student of Operation and Production Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran.

² Ph.D. student of Operation Research, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran. (Corresponding Author: mojtaba_aghaei68@yahoo.com)

³ Associate Professor, Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabatabaei University,Tehran

چکیده [English]

Recommender systems utilization has proven sales enhancement in most e-commerce platforms. This system objected to provide more options, comfort and flexibility to user which could make him interested, as well as providing better chance for companies to increase sells in their products and services. Flourishing popularity of web site has originated intrigue for recommendation systems. By penetrating in infinite fields, recommendation systems give deceptive suggestion on services compatible with user precedence. Integrating recommender systems by data management techniques to can targeted such issues and quality of suggestions will be improved considerably. Recent research reveals an idea of utilizing social network data to refine weakness points of traditional recommender system and improve prediction accuracy and efficiency. In this paper we represent views of recommender systems based on Twitter social network data by usage of variety interfaces, content analysis Methods, computational linguistics techniques and MALLET topic modeling algorithm. By deep exploration of objects, methodologies and available data sources, this paper will helps interested people to develop travel recommendation systems and facilitates future research by achieved direction.

کلیدواژه‌ها [English]

Recommender System
Social Network
Twitter
Topic Modeling

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