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Modelling Consumer Responses to Advertising Slogans through Artificial Neural Networks

Author

Listed:
  • Wan-Chen Wang

    (Department of Marketing, Feng Chia University, Taiwan)

  • Maria Manuela Santos Silva

    (Faculty of Economics of the University of Coimbra, Portugal)

  • Luiz Moutinho

    (The Business School, University of Glasgow, U.K.)

Abstract

This study aimed to achieve an in-depth understanding of consumers' emotional responses to advertising slogans and their effect on the development of advertising effectiveness. The current study is based on a survey data. An artificial neural network architecture was applied in this research study and designed to find patterns of non-linearity, especially if one is dealing with the human "emotional corridor." A good root mean squared error was achieved when highlighting research results like the critical role of consumers' cognitive appraisals and personal involvement. The result manages the outcome desirability of consumers from the product desirability itself and appeal to an emotion-laden pleasant environment. The results are relevant and meaningful to marketing communication from storytelling to consumer-generated advertising. The multiple feedforward the neural network has also enabled the fuzziness of the judgemental data to be dealt with.

Suggested Citation

  • Wan-Chen Wang & Maria Manuela Santos Silva & Luiz Moutinho, 2016. "Modelling Consumer Responses to Advertising Slogans through Artificial Neural Networks," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 15(2), pages 89-116, December.
  • Handle: RePEc:ijb:journl:v:15:y:2016:i:2:p:89-116
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    References listed on IDEAS

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    5. Trina Larsen Andras & Srini S. Srinivasan, 2003. "Advertising Intensity and R&D Intensity: Differences across Industries and Their Impact on Firm's Performance," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 2(2), pages 167-176, August.
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    Citations

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    Cited by:

    1. repec:ers:journl:v:vi:y:2018:i:1:p:3-13 is not listed on IDEAS
    2. Paulo Duarte Silveira & Susana Galv√£o & Paulo Bogas, 2018. "The Influence of Customer Retention Time on Slogan Recall and Recognition: An Empirical Study," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 3-13.
    3. Rumpf, Christopher & Boronczyk, Felix & Breuer, Christoph, 2020. "Predicting consumer gaze hits: A simulation model of visual attention to dynamic marketing stimuli," Journal of Business Research, Elsevier, vol. 111(C), pages 208-217.

    More about this item

    Keywords

    emotion; advertising; advertising slogan; artificial neural networks;

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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