Magical Towns of Mexico, tourism and mining: correlation study of indicators and corporate social responsibility
Main Article Content
Abstract
As part of Corporate Social Responsibility, productive organizations have established programs to contribute to communities in terms of growth and strengthening through ecological, economic promotion, religious, sports and cultural projects; On the other hand, the existence of programs for Mexican populations, which have traditions and customs representative of regions of the country and which are usually attractive for national and foreign tourism, promotes collective actions in order to meet requirements that allow them to be considered Magical Towns. The objective of this research is to analyze the correlation that exists between the indicators to be met, taken from the National Strategy of Magical Towns and the Corporate Social Responsibility programs that mining companies establish within their Management, when their location is adjacent to a community that is considered within the collective imagination to aspire to obtain the designation of Magical Town. The methodology with a mixed approach is based on matrix relationships that lead to the Quality Function Deployment tool -QFD-, which once adapted, generates through its records, the opportunity to create evidence for the application and files to be prepared for a locality to apply as a candidate for the designation of magical town; In addition, the projected scope is to formalize a database or operating system based on artificial intelligence that automates the process.
Abstract: Magical Towns of Mexico, tourism and mining: correlation study of indicators and corporate social responsibility
Downloads
Article Details
Copyright Notices Proposed by Creative Commons
Proposed policy for journals offering deferred open access
Those authors who have publications with this journal, accept the following terms:
1. The authors will retain their copyright and guarantee to the journal the right of first publication of their work, which will be simultaneously subject to the Creative Commons Recognition License CC BY-NC 4.0 (Creative Commons — Attribution-NonCommercial 4.0 International — CC BY-NC 4.0 ) hird parties to share the work provided that its author and its first publication is indicated this journal and no commercial use is made.
2. Authors may adopt other non-exclusive licensing agreements for the distribution of the published version of the work (e.g., deposit it in an institutional telematics file or publish it in a monographic volume) provided that the initial publication is indicated in this journal.
3. Authors are allowed and recommended to disseminate their work over the Internet (e.g. in institutional telematics files or on their website) before and during the submission process, which can produce interesting exchanges and increase citations of the published work. (See The effect of open access: http://opcit.eprints.org/oacitation-biblio.html.