مشخصات مقاله | |
ترجمه عنوان مقاله | استراتژی های کیفیت غذا و موقعیت مکانی تکاملی رستوران ها در بازارهای سفارش و تحویل غذا آنلاین به آفلاین رقابتی: یک رویکرد مبتنی بر عامل |
عنوان انگلیسی مقاله | Evolutionary food quality and location strategies for restaurants in competitive online-to-offline food ordering and delivery markets: An agent-based approach |
انتشار | مقاله سال ۲۰۱۹ |
تعداد صفحات مقاله انگلیسی | ۳۲ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس میباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
۶٫۳۴۴ در سال ۲۰۱۸ |
شاخص H_index | ۱۵۵ در سال ۲۰۱۹ |
شاخص SJR | ۲٫۴۷۵ در سال ۲۰۱۸ |
شناسه ISSN | ۰۹۲۵-۵۲۷۳ |
شاخص Quartile (چارک) | Q1 در سال ۲۰۱۸ |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | دارد |
رفرنس | دارد |
رشته های مرتبط | مدیریت |
گرایش های مرتبط | بازاریابی، مدیریت استراتژیک |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | مجله بین المللی اقتصاد تولید – International Journal of Production Economics |
دانشگاه | School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China |
کلمات کلیدی | مدل مبتنی بر عامل، آنلاین به آفلاین، سفارش غذا، تحویل غذا، موقعیت مکانی |
کلمات کلیدی انگلیسی | agent-based model; online-to-offline; food ordering; food delivery; location |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.ijpe.2018.05.008 |
کد محصول | E13607 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract ۱٫ Introduction ۲٫ Literature review ۳٫ Model description ۴٫ Simulation ۵٫ Results and discussion ۶٫ Conclusions Acknowledgement References |
بخشی از متن مقاله: |
Abstract
In the booming online-to-offline (O2O) food ordering and delivery market, numerous independent restaurants are competing for orders placed by customers via online food ordering platforms. The food quality and location decisions are deemed to be the two principal considerations of restaurants in this emerging market. To investigate the evolutionary food quality and location behaviours of restaurants, we propose an agent-based O2O food ordering model (AOFOM) that consists of three types of agents, namely customers, restaurants, and the online food ordering platform. We explicitly model their adaptive behaviours by optimizing the agents’ benefits. We find that customers’ behaviours have significant impacts on the restaurants’ food quality decisions. Besides, the relationship between the restaurant’s location decisions and customers’ waiting time is less significant in the O2O food ordering market due to the presence of an equalizing delivery service provided by the online platform. We also examine the characters of best restaurants, as well as the impacts of different delivery policies on the food quality and location decisions of restaurants. Introduction Modern information technologies and their offspring, such as computers, the Internet, smart phones, tablets, mobile applications, have fundamentally changed people’s daily lives. With respect to eating, they help people work so efficiently that they almost have no time to dine out; while they also provide people with a new option: order food online, wait, receive the delivered takeaway, and eat. In such online-to-offline (O2O) transactions, the online food ordering platform services large numbers of customers and restaurants in a direct and efficient fashion, sends online orders to restaurants, and even delivers the takeaways to customers. All the three participants are able to benefit from these transactions: (1) For restaurants, this market provides a new revenue source without expanding seating capacity or wait staff. (2) For customers, this service offers a wide variety of options, ratings, reviews, and payment choices. (3) For the online platform, this business model produces a steady stream of commission. Given the above advantages, it is not surprising that the O2O food ordering and delivery market is booming. For example, China’s O2O food ordering and delivery market had grown from 0.15 billion CNY in 2010 to 44.24 billion CNY in 2015, which means that the average daily increase during the six-year period was about 3 million USD. However, from the perspective of restaurants, attracting online takeaway orders will be increasingly difficult as more rivals rush in. More importantly, unlike non-perishable products that can be delivered to distant customers, the time-sensitive nature of takeaway food limits the size of the service area. Therefore, the restaurant’s sales territory covered by an online food ordering platform is bounded. |