Micro, Small And Medium Enterprises And Social Networks In Tourism Industry In Manzanillo, Colima, Mexico
Bibliographic record
Abstract
Nowadays, the use of social media has become an important tool to introduce new products and services in the world. However, in some countries social networks are very important to show what the company is and what they are doing with their businesses, it means that they sharing everything with their customers, like products, services, goals, some cases they try to educate their public about the use of the product or service, among other things.When people started using social networks on the internet, these were conceived as a mean to communicate with relatives or friends. However, with time, the social networks have evolved to a point that they now allow people to use them to generate sales and increase the competitiveness of enterprises.The purpose of this research is to demonstrate the lack of training and knowledge about the use of social networks by local businesses and the barriers they face when they decide to use them as sales platforms, and to demonstrate the impact it could have on their businesses. Four SMEs located in Colima State in Mexico were studied, selected to be sufficiently successful and representative in terms of industry and size, for theoretical generalization purposes. These tourism SMEs stem from various sectors, such as: travel agencies, tour operator, hotel and restaurant. Data were collected through semi-structured tape-recorded interviews, ranging approximately one hour and a half each, with the owner-manager or the manager responsible for social media. Interview transcripts were then coded and analyzed following Miles and Huberman?s (1994) prescriptions with the assistance of the Atlas.ti application.The results allow us to conclude that the investigated companies believe that the use of social networks is extremely important to be able to compete in the market. However, due to a lack of training, they were not able to implement properly the utilization of social networks in their companies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".