Internet of Marketing Things: A Fog Computing Paradigm for Marketing Research
Jacob Hornik and
Matti Rachamim
A chapter in Business, Management and Economics Annual Volume 2024 from IntechOpen
Abstract:
Conventional market research is usually costly, time-consuming, scalability issue, and intrusive, and the generated data may have a short shelf life in fast-moving markets. The latest effort in delivering computing resources as a service to marketing researchers and managers represents a change from computing as an over-the-counter service that is obtained to computing as a service that is provided to users online, over the internet from very large databases. Managing the data and research produced by internet of things (IoT) devices, such as actuators and sensors, is a major issue faced by marketing research and executives when using an IoT system. This paper demonstrates how commonly used cloud-based IoT systems are challenged by the heterogeneity, large amount, and high latency shown in some cloud marketing ecosystems. We introduce academia and managers to a recent major development, "Fog Computing," a transpiring computational framework that decentralizes strategies, applications, and data analysis into the network itself using a federated and distributed computing system. It converts centralized cloud to distributed fog by bringing computation and storage near the end user. Fog computing is regarded as a novel market paradigm which can assist artificial intelligence and marketing research and strategies, specifically for the architecture of more advanced research systems.
Keywords: fog computing; cloud computing; recommender system; internet-of-things (IoT); marketing analytics (search for similar items in EconPapers)
JEL-codes: M00 M2 (search for similar items in EconPapers)
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.intechopen.com/chapters/89195 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:325908
DOI: 10.5772/intechopen.114333
Access Statistics for this chapter
More chapters in Chapters from IntechOpen
Bibliographic data for series maintained by Slobodan Momcilovic ().