The potential threats of exposing personal data associated with online services have been a reason for concern, and individuals as customers may decline to disclose their data due to trust issues. Literature has shown evidence that greater transparency in the types and purposes of data requested encourages individuals to disclose personal data. This evidence indicates a need to examine the characteristics of personal information practices. Furthermore, current data privacy regulations recognize the presence of different data characteristics such as location-specific, health-specific, and financial-specific. Yet, current legislations are formed to identify personal data as a singular category regardless of the requirements, including the specification of processed personal data to be relevant and limited to what is necessary for enabling service functions. Without categorization, measuring “relevant” and “necessary” can be ambiguous. Several pieces of researches have explored the impact of personal information type and sensitivity level on privacy concern and disclosure; however, most of them lacked an in-depth examination of data categorization with systematic validation. Our study aims to fill this gap, and additionally further look into how contextual demographic factors influence the perception on information privacy concern and disclosure of different personal data categories from a Malaysian perspective. Our study provides new evidence of validated personal data categories and their significant differences in perceived information privacy concern and disclosure intention. Our research finding also discovers that Age, Gender, and Working Industry, as demographic factors, have significant effects on disclosure intention associated with Tracking, Finance, Authenticating, and Medical-health information.

暴露与在线服务相关的个人数据的潜在威胁一直是令人担忧的一个原因，作为客户的个人可能会因信任问题而拒绝披露他们的数据。有证据表明，所请求数据的类型和目的的更大透明度鼓励个人披露个人数据。这一证据表明需要检查个人信息实践的特征。此外，当前的数据隐私法规承认存在不同的数据特​​征，例如特定于位置的、特定于健康的和特定于财务的。然而，目前的立法是为了将个人数据识别为单一类别，而不管要求如何，包括将处理的个人数据指定为相关且仅限于启用服务功能所需的内容。如果没有分类，衡量“相关”和“必要”可能会产生歧义。多项研究探讨了个人信息类型和敏感程度对隐私关注和披露的影响；然而，他们中的大多数缺乏对数据分类的系统验证的深入检查。我们的研究旨在填补这一空白，并进一步研究背景人口因素如何从马来西亚的角度影响对信息隐私关注和不同个人数据类别披露的看法。我们的研究为经过验证的个人数据类别及其在感知信息隐私问题和披露意图方面的显着差异提供了新证据。我们的研究结果还发现，年龄、性别和工作行业作为人口统计因素，对与跟踪、财务、身份验证和医疗健康信息相关的披露意愿有显着影响。