Investigating Consumer Behavior to Create Expected Customer Value, using Big Data Analytics

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Mousavi Sayed Mohsen; Amiri Aghdaie Seyed Fathollah

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: CONSUMER BEHAVIOR STUDIES Year:2020 | Volume:7 | Issue:1 Page(s): 160-182

Download Full-Text

Persian Verion

View:

299

Download:

Cites:

Information Journal Paper

Title

Investigating Consumer Behavior to Create Expected Customer Value, using Big Data Analytics

Author(s)

Mousavi Sayed Mohsen | Amiri Aghdaie Seyed Fathollah | Issue Writer Certificate

Keywords

Value Creation

Big Data

Perceived Value

Machine learning

Text Mining

Abstract

The concept of “ value” in a business is a potential product or service that a business promises to deliver to the customer and in general, it is the reason why a customer chooses a brand and prefers it over competing brands. In recent years, with the increasing presence of consumers in social networks, it has become possible to access data related to the interests and expected values of consumers. The purpose of this study is to identify the components of value, in order to create and present value to the customer, using the analysis of comments and content produced by consumers in social networks. For this purpose, 41, 904 customer comments, regarding the "cell phone" product were collected from the Digikala online store site and analyzed using "Big Data analytics" methods (Opinion Mining and Latent Dirichlet allocation). According to this study, five main groups of values were detected: 1. Functional values, 2. Economic values, 3. Qualitative values, 4. Emotional values, 5. Social values. Also, the components related each group was identified. The results show that by using Big Data analytics, a clearer picture of the customer's expected values can be obtained with more speed and less waste of resources, in order to provide products tailored to the needs and desires of the consumer.

Cites

No record.

References

No record.

Cite

APA: Copy

Mousavi, Sayed Mohsen, & Amiri Aghdaie, Seyed Fathollah. (2020). Investigating Consumer Behavior to Create Expected Customer Value, using Big Data Analytics. CONSUMER BEHAVIOR STUDIES, 7(1 ), 160-182. SID. https://sid.ir/paper/961881/en

Vancouver: Copy

Mousavi Sayed Mohsen, Amiri Aghdaie Seyed Fathollah. Investigating Consumer Behavior to Create Expected Customer Value, using Big Data Analytics. CONSUMER BEHAVIOR STUDIES[Internet]. 2020;7(1 ):160-182. Available from: https://sid.ir/paper/961881/en

IEEE: Copy

Sayed Mohsen Mousavi, and Seyed Fathollah Amiri Aghdaie, “Investigating Consumer Behavior to Create Expected Customer Value, using Big Data Analytics,” CONSUMER BEHAVIOR STUDIES, vol. 7, no. 1 , pp. 160–182, 2020, [Online]. Available: https://sid.ir/paper/961881/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops