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The paper aims to develop and validate an instrument to measure users’ perceptions of online personalized advertising.

First, we identified 12 different aspects of online personalized advertisement and formulated candidate items through a literature review. A card sorting study and expert review were conducted to generate the initial scale items. We then conducted one survey (n = 308) to create a reliable measurement instrument and another (n = 296) to validate the instrument. Finally, we tested how the dimensions of the OPAD-Perception Framework can be used to differentiate between different levels of ad sensitivity, control/no control over the ad personalization process, and different levels of granularity of ad explanation.

The resulting OPAD-Perception Framework contains 49 Likert-formatted questions measuring ten distinct dimensions of online personalized advertising: reliability, usefulness, transparency, interactivity, targeting accuracy, accountability, creepiness, willingness to rely on, self-actualization, and persuasion.

The OPAD-Perception Framework can serve as a powerful tool to measure users’ attitudes toward online personalized advertising. This will enable advertisers and social media platforms to better support users’ privacy expectations and provide user-friendly interfaces for controlling the ad personalization process.

The study aims to explore the factors that motivate social media (SM) users to abstain from sharing pictures on SM platforms through the lens of user resistance theory (URT).

The study adopts a mixed-method approach and utilizes the URT as a lens to explore user attitudes towards SM engagement. Insights were derived from consultations with ten domain experts possessing diverse professional backgrounds. To prioritize the identified resistance factors, the Fuzzy-OPA multi-criteria decision-making (MCDM) technique was employed.

The study identifies 13 factors influencing users' choices to abstain from sharing images on SM platforms, categorized into 2 primary groups: personal and platform-related factors. Personal factors include privacy concerns, fear of negative judgment and anxiety over self-presentation. In contrast, platform factors include perceived risks of sharing images without consent, lack of control over the privacy settings and the lack of trust in SM platforms, contributing to users' reluctance to share pictures on SM.

The study utilized ten experts' opinions to classify and prioritize factors, but results may vary with more experts from diverse backgrounds. Additionally, resistance factors may differ across SM platforms like Instagram, Snapchat, Facebook, etc. The study contributes to theory by identifying and classifying personal and platform barriers to SM non-use, filling a gap in existing literature. It offers a framework for future research on technology adoption and non-use, emphasizing the role of privacy, self-presentation and identity factors in user decision-making. This classification aids in designing measurement tools for further research.

The study contributes to theory by identifying and classifying personal and platform barriers to SM non-use, filling a gap in existing literature. It offers a framework for future research on technology adoption and non-use, emphasizing the role of privacy, self-presentation and identity factors in user decision-making. This classification aids in designing measurement tools for further research.

While most of the research on SM platforms has examined the drivers behind their adoption, reasons for non-adoption, remain relatively underexplored. The study fills this gap by investigating why users limit sharing content on SM platforms.