Resource-constrained O2O service recommended strategy research
by Shuai Huangfu; Xiao Xue; Junfeng Wang
International Journal of Services Technology and Management (IJSTM), Vol. 26, No. 2/3, 2020

Abstract: With the development of internet, the problem of information overload is becoming more and more serious. Recommendation technology can screen out information that is useful to people. Therefore, many scholars pay attention to it. There are two types of internet services: online and offline. At present, recommendation technology has become more and more mature in purely online applications, including news recommendation and commodity recommendation. However, O2O service recommendation needs the support of offline resources. Owing to the constraints of limited resources, many users adopt recommendation result at the same time, which often leads to crowded service points, useless recommendations and poor user experience. How to improve the effectiveness of O2O service recommendation under condition of resource constraints is a crucial issue. This paper proposes a group of O2O service recommendation strategies from the prospect of supply and demand matching to solve the problem step by step. Furthermore, we utilise computational experiment to perform performance comparison analysis for these service strategies. The results show that the adaptive adjustment mechanism based on current supply and demand conditions is conductive to improving effectiveness of O2O service recommendation so as to increase profit of the merchant and improve user experience.

Online publication date: Mon, 20-Apr-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Services Technology and Management (IJSTM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com