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Personal data protection compliance assessment: A privacy policy scoring approach and empirical evidence from Thailand's SMEs
Privacy policies, intended to provide information to individuals regarding how their personal data is processed, are often complex and challenging for users to understand. Businesses often demonstrate non-compliance with personal data protection laws, ranging from the absence of privacy policies to...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10597812/ https://www.ncbi.nlm.nih.gov/pubmed/37886776 http://dx.doi.org/10.1016/j.heliyon.2023.e20648 |
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author | Chatsuwan, Panchapawn Phromma, Tanawat Surasvadi, Navaporn Thajchayapong, Suttipong |
author_facet | Chatsuwan, Panchapawn Phromma, Tanawat Surasvadi, Navaporn Thajchayapong, Suttipong |
author_sort | Chatsuwan, Panchapawn |
collection | PubMed |
description | Privacy policies, intended to provide information to individuals regarding how their personal data is processed, are often complex and challenging for users to understand. Businesses often demonstrate non-compliance with personal data protection laws, ranging from the absence of privacy policies to the existence of policies that do not adhere to legal requirements. This paper aims to (1) develop a quantitative and systematic tool for evaluating privacy policies' compliance with the Personal Data Protection Act (PDPA), (2) assess compliance among Small and Medium Enterprises (SMEs) in Thailand, and (3) provide recommendations for enhancing compliance practices. To achieve this, we proposed a multi-criteria privacy policy scoring model integrated with comprehensive statistical data analyses. The privacy policy scoring model consists of ten privacy principles and 31 privacy criteria, providing a structured framework for evaluating privacy policies. During a two-year postponement period for enforcing the PDPA law, we conducted a stratified random-sampling survey of 384 SMEs to evaluate their privacy policies using the proposed scoring model. The accomplished results revealed significantly lower scores than anticipated, with the nationwide average score of SMEs reaching only 6.1909 out of 100 points. More than half of the SMEs collected personal data without announcing privacy policies, and those with privacy policies adhered to an average of only 12.15 out of 31 privacy criteria. These findings highlight the pressing need to improve compliance practices among SMEs in Thailand. The proposed methodology can be customized and applied to align with the requirements of personal data protection laws in other countries. Additionally, our findings indicate that compliance with the PDPA is influenced by the Thailand Standard Industrial Classification (TSIC) sections, suggesting the adoption of tailored approaches by policymakers to address the specific needs of different TSIC sections. |
format | Online Article Text |
id | pubmed-10597812 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-105978122023-10-26 Personal data protection compliance assessment: A privacy policy scoring approach and empirical evidence from Thailand's SMEs Chatsuwan, Panchapawn Phromma, Tanawat Surasvadi, Navaporn Thajchayapong, Suttipong Heliyon Research Article Privacy policies, intended to provide information to individuals regarding how their personal data is processed, are often complex and challenging for users to understand. Businesses often demonstrate non-compliance with personal data protection laws, ranging from the absence of privacy policies to the existence of policies that do not adhere to legal requirements. This paper aims to (1) develop a quantitative and systematic tool for evaluating privacy policies' compliance with the Personal Data Protection Act (PDPA), (2) assess compliance among Small and Medium Enterprises (SMEs) in Thailand, and (3) provide recommendations for enhancing compliance practices. To achieve this, we proposed a multi-criteria privacy policy scoring model integrated with comprehensive statistical data analyses. The privacy policy scoring model consists of ten privacy principles and 31 privacy criteria, providing a structured framework for evaluating privacy policies. During a two-year postponement period for enforcing the PDPA law, we conducted a stratified random-sampling survey of 384 SMEs to evaluate their privacy policies using the proposed scoring model. The accomplished results revealed significantly lower scores than anticipated, with the nationwide average score of SMEs reaching only 6.1909 out of 100 points. More than half of the SMEs collected personal data without announcing privacy policies, and those with privacy policies adhered to an average of only 12.15 out of 31 privacy criteria. These findings highlight the pressing need to improve compliance practices among SMEs in Thailand. The proposed methodology can be customized and applied to align with the requirements of personal data protection laws in other countries. Additionally, our findings indicate that compliance with the PDPA is influenced by the Thailand Standard Industrial Classification (TSIC) sections, suggesting the adoption of tailored approaches by policymakers to address the specific needs of different TSIC sections. Elsevier 2023-10-17 /pmc/articles/PMC10597812/ /pubmed/37886776 http://dx.doi.org/10.1016/j.heliyon.2023.e20648 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Chatsuwan, Panchapawn Phromma, Tanawat Surasvadi, Navaporn Thajchayapong, Suttipong Personal data protection compliance assessment: A privacy policy scoring approach and empirical evidence from Thailand's SMEs |
title | Personal data protection compliance assessment: A privacy policy scoring approach and empirical evidence from Thailand's SMEs |
title_full | Personal data protection compliance assessment: A privacy policy scoring approach and empirical evidence from Thailand's SMEs |
title_fullStr | Personal data protection compliance assessment: A privacy policy scoring approach and empirical evidence from Thailand's SMEs |
title_full_unstemmed | Personal data protection compliance assessment: A privacy policy scoring approach and empirical evidence from Thailand's SMEs |
title_short | Personal data protection compliance assessment: A privacy policy scoring approach and empirical evidence from Thailand's SMEs |
title_sort | personal data protection compliance assessment: a privacy policy scoring approach and empirical evidence from thailand's smes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10597812/ https://www.ncbi.nlm.nih.gov/pubmed/37886776 http://dx.doi.org/10.1016/j.heliyon.2023.e20648 |
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