Modeling the Crowdsourcing Effective Factors on Marketing in Tourism Industry

Rouhollah Tavallaee; Nasim Hosseinzadeh Nosrati; Mohammadreza Hosseini; Bahar Hosseinzadeh Nosrati

doi:doi:10.11648/j.ajomis.20200501.11

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Modeling the Crowdsourcing Effective Factors on Marketing in Tourism Industry

Rouhollah Tavallaee, Nasim Hosseinzadeh Nosrati, Mohammadreza Hosseini, Bahar Hosseinzadeh Nosrati

Published in American Journal of Operations Management and Information Systems (Volume 5, Issue 1)

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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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
SP  - 1
EP  - 12
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
IS  - 1
ER  -

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Author Information

Rouhollah Tavallaee

Management Department, Shahid Beheshti University, Tehran, Iran
Nasim Hosseinzadeh Nosrati

Management & Accounting Department, Seraj University, Tabriz, Iran
Mohammadreza Hosseini

Management Department, Central Branch, Islamic Azad University, Tehran, Iran
Bahar Hosseinzadeh Nosrati

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

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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}
}

Copy | Download

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
SP  - 1
EP  - 12
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
IS  - 1
ER  -

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