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Statistical Models in Consumer Behavior

Über Statistical Models in Consumer Behavior

This book narrates the detailed review on stochastic behavior of repeated purchasers and made an attempt to compare expected number of repeated purchase consumers for the experimental data. A new compound distribution with Poisson and Weibull distributions for studying the consumer behavior is presented. It¿s parameters and properties are derived. It can be used for studying the consumer behavioral distribution for varying. Further, this book emphasizes on the brand performance indicators of the Dirichlet model are used to construct a more detailed statistical model for the transition probability matrix, and this model is used to investigate Markovian characteristics. The least square principle is used to estimate the transition model parameters. The stationary probabilities are derived for each state of the Markov chain and analysis is illustrated with an example and also a detailed outline construction of Hidden Markov model is exhibited to capture the relationships, and quantifying the the consumer dynamic attitudes. The transition probability matrices derived with considering the prime factors which influence the consumer behavior with the help of two brands case.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9786206152408
  • Einband:
  • Taschenbuch
  • Seitenzahl:
  • 92
  • Veröffentlicht:
  • 29. Januar 2024
  • Abmessungen:
  • 150x6x220 mm.
  • Gewicht:
  • 155 g.
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Beschreibung von Statistical Models in Consumer Behavior

This book narrates the detailed review on stochastic behavior of repeated purchasers and made an attempt to compare expected number of repeated purchase consumers for the experimental data. A new compound distribution with Poisson and Weibull distributions for studying the consumer behavior is presented. It¿s parameters and properties are derived. It can be used for studying the consumer behavioral distribution for varying. Further, this book emphasizes on the brand performance indicators of the Dirichlet model are used to construct a more detailed statistical model for the transition probability matrix, and this model is used to investigate Markovian characteristics. The least square principle is used to estimate the transition model parameters. The stationary probabilities are derived for each state of the Markov chain and analysis is illustrated with an example and also a detailed outline construction of Hidden Markov model is exhibited to capture the relationships, and quantifying the the consumer dynamic attitudes. The transition probability matrices derived with considering the prime factors which influence the consumer behavior with the help of two brands case.

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