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Consumer Behavior and Cognitive Theories

In: Crowd-Based Business Models

Author

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  • Rajagopal

    (Tecnologico de Monterrey)

Abstract

Social power as a pivot to analyze the power structure of consumers and consumers’ involvement of firms in crowdsourcing. Accordingly, the managerial implications of ‘consumer-firm’ power balance are deliberated in the chapter. Crowdsourcing is a process that explores collective intelligence for resolving the complex behavioral issues by distributing tasks to a large group of people. The learning objectives of this chapter include understanding of how consumer cognitive (thinking) processes and limitations affect beliefs and social influences, and how other contextual factors influence consumer decision-making, choices, and behavior. This chapter focuses on learning from external factors on consumer behavior and relationships with other people that influence their decision-making processes. The behavioral analytics is discussed in this chapter, in the context of motivation and decision theories. Besides, this chapter discusses the role of consumer advocacy and psychodynamics (peer-to-peer opinion dissemination) as a tool for developing crowd-based business models.

Suggested Citation

  • Rajagopal, 2021. "Consumer Behavior and Cognitive Theories," Springer Books, in: Crowd-Based Business Models, chapter 0, pages 197-225, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-77083-9_7
    DOI: 10.1007/978-3-030-77083-9_7
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    Cited by:

    1. Jimmy Alani, 2022. "Estimation of Consumption Functions Using Savings Motive Hypothesis (SMH)," International Econometric Review (IER), Econometric Research Association, vol. 14(1), pages 21-45, March.
    2. Torres Pena, Maria Veronica & Breidbach, Christoph F., 2021. "On emergence in service platforms: An application to P2P lending," Journal of Business Research, Elsevier, vol. 135(C), pages 337-347.
    3. Campbell, Daniel & Grant, Andrew & Thorp, Susan, 2022. "Reducing credit card delinquency using repayment reminders," Journal of Banking & Finance, Elsevier, vol. 142(C).
    4. Toktarova, Alla & Walter, Viktor & Göransson, Lisa & Johnsson, Filip, 2022. "Interaction between electrified steel production and the north European electricity system," Applied Energy, Elsevier, vol. 310(C).
    5. Caputo, Vincenzina & Lusk, Jayson L., 2022. "The Basket-Based Choice Experiment: A Method for Food Demand Policy Analysis," Food Policy, Elsevier, vol. 109(C).
    6. Urbano, Eva M. & Martinez-Viol, Victor & Kampouropoulos, Konstantinos & Romeral, Luis, 2021. "Energy equipment sizing and operation optimisation for prosumer industrial SMEs – A lifetime approach," Applied Energy, Elsevier, vol. 299(C).

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