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Modeling the Crowdsourcing Effective Factors on Marketing in Tourism Industry

Received: 1 December 2019     Accepted: 12 February 2020     Published: 18 February 2020
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Abstract

Current era is customer-orientation era and organizations try hard to satisfy their customers and do their best in marketing. There are numerous factors affect customer satisfaction. One of these important factors is crowdsourcing. Crowdsourcing is one of the emerging Web based phenomenon which has attracted great attention from both customers and researchers over the years. Therefore, to investigate it and its effective factors is needed. So, this research is modeling the crowdsourcing effective factors on marketing in tourism industry. Current research is applied one and seeks to identify crowdsourcing effective factors on customer satisfaction in tourism industry. Also, research method is descriptive-survey. So, the independent and dependent variables have been introduced at the first part by literature review. Then, the identified factors in the model has been validated by using judgmental method and 7 experts’ viewpoints in tourism field. To present the final conceptual model, fuzzy cognitive mapping and expert mind map drawing have been used. Findings have indicated that among the technology factor indexes, the “social networks” index had the most effect; among environmental factor indexes, the “applying competitive competitiveness” index had the most effect; among the product market price factor indexes, the “consumer price elasticity” index had the most effect; among the executive decisions factor indexes, the “high income for better planning” index had the most effect; among the financial flows factor indexes, the “organizing suitable individual” index had the most effect; among the motive forces factor indexes, the “task attractiveness” index had the most effect; among the main factors indexes, the “using the newest sources” index had the most effect and among task features indexes, the “creativity in performing the task” index had the most effect. Also, recommendations have been presented.

Published in American Journal of Operations Management and Information Systems (Volume 5, Issue 1)
DOI 10.11648/j.ajomis.20200501.11
Page(s) 1-12
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Information & Communication Technology, Crowdsourcing, Marketing, Tourism Industry, Fuzzy Cognitive Mapping

References
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Cite This Article
  • APA Style

    Rouhollah Tavallaee, Nasim Hosseinzadeh Nosrati, Mohammadreza Hosseini, Bahar Hosseinzadeh Nosrati. (2020). Modeling the Crowdsourcing Effective Factors on Marketing in Tourism Industry. American Journal of Operations Management and Information Systems, 5(1), 1-12. https://doi.org/10.11648/j.ajomis.20200501.11

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    ACS Style

    Rouhollah Tavallaee; Nasim Hosseinzadeh Nosrati; Mohammadreza Hosseini; Bahar Hosseinzadeh Nosrati. Modeling the Crowdsourcing Effective Factors on Marketing in Tourism Industry. Am. J. Oper. Manag. Inf. Syst. 2020, 5(1), 1-12. doi: 10.11648/j.ajomis.20200501.11

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    AMA Style

    Rouhollah Tavallaee, Nasim Hosseinzadeh Nosrati, Mohammadreza Hosseini, Bahar Hosseinzadeh Nosrati. Modeling the Crowdsourcing Effective Factors on Marketing in Tourism Industry. Am J Oper Manag Inf Syst. 2020;5(1):1-12. doi: 10.11648/j.ajomis.20200501.11

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  • @article{10.11648/j.ajomis.20200501.11,
      author = {Rouhollah Tavallaee and Nasim Hosseinzadeh Nosrati and Mohammadreza Hosseini and Bahar Hosseinzadeh Nosrati},
      title = {Modeling the Crowdsourcing Effective Factors on Marketing in Tourism Industry},
      journal = {American Journal of Operations Management and Information Systems},
      volume = {5},
      number = {1},
      pages = {1-12},
      doi = {10.11648/j.ajomis.20200501.11},
      url = {https://doi.org/10.11648/j.ajomis.20200501.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajomis.20200501.11},
      abstract = {Current era is customer-orientation era and organizations try hard to satisfy their customers and do their best in marketing. There are numerous factors affect customer satisfaction. One of these important factors is crowdsourcing. Crowdsourcing is one of the emerging Web based phenomenon which has attracted great attention from both customers and researchers over the years. Therefore, to investigate it and its effective factors is needed. So, this research is modeling the crowdsourcing effective factors on marketing in tourism industry. Current research is applied one and seeks to identify crowdsourcing effective factors on customer satisfaction in tourism industry. Also, research method is descriptive-survey. So, the independent and dependent variables have been introduced at the first part by literature review. Then, the identified factors in the model has been validated by using judgmental method and 7 experts’ viewpoints in tourism field. To present the final conceptual model, fuzzy cognitive mapping and expert mind map drawing have been used. Findings have indicated that among the technology factor indexes, the “social networks” index had the most effect; among environmental factor indexes, the “applying competitive competitiveness” index had the most effect; among the product market price factor indexes, the “consumer price elasticity” index had the most effect; among the executive decisions factor indexes, the “high income for better planning” index had the most effect; among the financial flows factor indexes, the “organizing suitable individual” index had the most effect; among the motive forces factor indexes, the “task attractiveness” index had the most effect; among the main factors indexes, the “using the newest sources” index had the most effect and among task features indexes, the “creativity in performing the task” index had the most effect. Also, recommendations have been presented.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - Modeling the Crowdsourcing Effective Factors on Marketing in Tourism Industry
    AU  - Rouhollah Tavallaee
    AU  - Nasim Hosseinzadeh Nosrati
    AU  - Mohammadreza Hosseini
    AU  - Bahar Hosseinzadeh Nosrati
    Y1  - 2020/02/18
    PY  - 2020
    N1  - https://doi.org/10.11648/j.ajomis.20200501.11
    DO  - 10.11648/j.ajomis.20200501.11
    T2  - American Journal of Operations Management and Information Systems
    JF  - American Journal of Operations Management and Information Systems
    JO  - American Journal of Operations Management and Information Systems
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    PB  - Science Publishing Group
    SN  - 2578-8310
    UR  - https://doi.org/10.11648/j.ajomis.20200501.11
    AB  - Current era is customer-orientation era and organizations try hard to satisfy their customers and do their best in marketing. There are numerous factors affect customer satisfaction. One of these important factors is crowdsourcing. Crowdsourcing is one of the emerging Web based phenomenon which has attracted great attention from both customers and researchers over the years. Therefore, to investigate it and its effective factors is needed. So, this research is modeling the crowdsourcing effective factors on marketing in tourism industry. Current research is applied one and seeks to identify crowdsourcing effective factors on customer satisfaction in tourism industry. Also, research method is descriptive-survey. So, the independent and dependent variables have been introduced at the first part by literature review. Then, the identified factors in the model has been validated by using judgmental method and 7 experts’ viewpoints in tourism field. To present the final conceptual model, fuzzy cognitive mapping and expert mind map drawing have been used. Findings have indicated that among the technology factor indexes, the “social networks” index had the most effect; among environmental factor indexes, the “applying competitive competitiveness” index had the most effect; among the product market price factor indexes, the “consumer price elasticity” index had the most effect; among the executive decisions factor indexes, the “high income for better planning” index had the most effect; among the financial flows factor indexes, the “organizing suitable individual” index had the most effect; among the motive forces factor indexes, the “task attractiveness” index had the most effect; among the main factors indexes, the “using the newest sources” index had the most effect and among task features indexes, the “creativity in performing the task” index had the most effect. Also, recommendations have been presented.
    VL  - 5
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Author Information
  • Management Department, Shahid Beheshti University, Tehran, Iran

  • Management & Accounting Department, Seraj University, Tabriz, Iran

  • Management Department, Central Branch, Islamic Azad University, Tehran, Iran

  • Management Department, University College of Nabi Akram, Tabriz, Iran

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