Toward Deep Understanding of Persuasive Product Recommendation Agents

نویسندگان

  • Tian Yu
  • Izak Benbasat
  • Ronald T. Cenfetelli
چکیده

Product recommendation agents (PRA) are systems built to facilitate customers’ products purchase on e-commerce websites. Prior literature focuses on the “shaping” effects of PRA to customers’ decision making. More challengingly, PRA can be built to change customers’ product choice by combining with persuasive features. This paper explores this new type of PRA “persuasive product recommendation agents” (PPRA). In this paper, we make a distinction of PPRA with neutral and deceptive ones. The basic functioning principle of PPRA is stated and a classification of persuasive tactics is made. We propose the mechanism via which PPRA work by incorporating elaboration likelihood model, 4w and theory of reasoned action together. Despite marketing usage, the proposed PPRA can be used to benefit society by promoting green purchases or encouraging charity. The theory also has the generalizability to be used in decision making contexts like healthcare and education. Discussion and future research directions are made.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparing Persuasiveness of Different Recommendation Agents As Customer Decision Support Systems in Electronic Commerce

Recommendation agents are computer agents used as customer decision support systems in electronic commerce; they make product recommendations from among a very large number of online product alternatives. Grounded on a persuasion theory, this paper builds a model to identify the most persuasive recommendation agent type and explain why it is so. Three major types of recommendation agents – cons...

متن کامل

Persuasive product recommendation

Online shops and B2C sites in diverse domains such as ’quality & taste’, consumer electronics or e-tourism require on the one side persuasive Web presentation and on the other side deep product knowledge. In that context recommender applications may help to create an enjoyable shopping experience for online users. The Advisor Suite framework is a knowledge-based conversational recommender syste...

متن کامل

Persuasive Recommendation: Serial Position Effects in Knowledge-Based Recommender Systems

Recommender technologies are crucial for the effective support of customers in online sales situations. The state-of-the-art research in recommender systems is not aware of existing theories in the areas of cognitive and decision psychology and thus lacks of deeper understanding of online buying situations. In this paper we present results from user studies related to serial position effects in...

متن کامل

Persuasion in Knowledge-Based Recommendation

Recommendation technologies support users in the identification of interesting products and services. Beside the wide-spread approaches of collaborative and content-based filtering, knowledge-based recommender technologies gain an increasing importance due to their capability of deriving recommendations for complex products such as financial services, technical equipment, or consumer goods. The...

متن کامل

Toward the Next Generation of Recommender Systems: Applications and Research Challenges

Recommender systems are assisting users in the process of identifying items that fulfill their wishes and needs. These systems are successfully applied in different e-commerce settings, for example, to the recommendation of news, movies, music, books, and digital cameras. The major goal of this book chapter is to discuss new and upcoming applications of recommendation technologies and to provid...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011