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Full-Text Articles in Business
Of Promoting Networking And Protecting Privacy: Effects Of Defaults And Regulatory Focus On Social Media Users’ Preference Settings, Hichang Cho, Sungjong Roh, Byungho Park
Of Promoting Networking And Protecting Privacy: Effects Of Defaults And Regulatory Focus On Social Media Users’ Preference Settings, Hichang Cho, Sungjong Roh, Byungho Park
Research Collection Lee Kong Chian School Of Business
Privacy research has debated whether privacy decision-making is determined by users' stable preferences (i.e., individual traits), privacy calculus (i.e., cost-benefit analysis), or “responses on the spot” that vary across contexts. This study focuses on two factors—default setting as a contextual factor and regulatory focus as an individual difference factor—and examines the degree to which these factors affect social media users' decision-making when using privacy preference settings in a fictitious social networking site. The results, based on two experimental studies (study 1, n = 414; study 2, n = 213), show that default settings significantly affect users' privacy preferences, such that …
Authentic Leadership In The Digital Age, Richard R. Smith
Authentic Leadership In The Digital Age, Richard R. Smith
Research Collection Lee Kong Chian School Of Business
Artificial intelligence algorithms are actively assessing our personality and behaviour based on our social media footprint with amazing accuracy – even after we have retired or died.
Evolution Of Corporate Reputation During An Evolving Controversy, Siyoung Chung, Mark Chong, Jie Sheng Chua, Ji Cheon Na
Evolution Of Corporate Reputation During An Evolving Controversy, Siyoung Chung, Mark Chong, Jie Sheng Chua, Ji Cheon Na
Research Collection Lee Kong Chian School Of Business
Purpose: The purpose of this paper is to investigate the evolution of online sentiments toward a company (i.e. Chipotle) during a crisis, and the effects of corporate apology on those sentiments. Design/methodology/approach: Using a very large data set of tweets (i.e. over 2.6m) about Company A’s food poisoning case (2015–2016). This case was selected because it is widely known, drew attention from various stakeholders and had many dynamics (e.g. multiple outbreaks, and across different locations). This study employed a supervised machine learning approach. Its sentiment polarity classification and relevance classification consisted of five steps: sampling, labeling, tokenization, augmentation of semantic …