Consumers' ethical perceptions of social media analytics practices: Risks, benefits and potential outcomes

Michaelidou, Nina; Micevski, Milena

doi:10.1016/j.jbusres.2018.12.008

Cited by 24 publications

(15 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The current study revealed that perceived risk significantly mediates the relationship between perceived ethicality of social media analytics and marketing discomfort and consumer self-disclosure. These outcomes are consistent with previous studies (Michaelidou & Micevski, 2019). Michaelidou & Micevski (2019) penned down that unfavorable social media analytics practices lead to an increase in the perceived risk of the consumer and eventually impact the consumer willingness to disclose about themselves.…”

Section: Discussionsupporting

confidence: 92%

“…These outcomes are consistent with previous studies (Michaelidou & Micevski, 2019). Michaelidou & Micevski (2019) penned down that unfavorable social media analytics practices lead to an increase in the perceived risk of the consumer and eventually impact the consumer willingness to disclose about themselves. Similarly, (Jacobson et al, 2020) highlighted that consumers usually evaluate the risk and benefits of sharing information on social media.…”

Section: Discussionsupporting

confidence: 92%

“…On the other hand, justice in organizations holds a significant place as it is regarded as a tool through which organizations function with fairness and ethicality. Hence, any organization's critical structural foundation must be fair and ethical in interacting with consumers (Michaelidou & Micevski, 2019). Similarly, (Wan et al, 2021) have associated justice with ethicality by focusing on fairness and the organization's morality.…”

Section: Justice Theory and Social Media Analyticsmentioning

confidence: 99%

“…(Smith et al, 2012). (Michaelidou & Micevski, 2019) highlighted that SMA context's organizational practices raise psychological concern on the individuals who feel that their privacy concerns have been surpassing by the organization for their material gains.…”

Section: Justice Theory and Social Media Analyticsmentioning

confidence: 99%

See 3 more Smart Citations

Social Media Analytics Lens: A Study on Consumer Perceived Risk to Share Information on Social Media Networks

Majeed

Mahmood

Molnár

et al. 2021

HSSR

View full text Add to dashboard Cite

Purpose of the study: This study focuses on understanding the potential unfavourable social media analytics practices (SMA) and how they may lead to the negative perception of consumer self-disclosure on social media sites and causing market discomfort for people. We also examined a framework regarding the SMA practices, and their impact on the customer’s trust to use social media networks. Methodology: Data were collected from 527 social media users with the help of an online questionnaire. Partial Least Squares Structural equation modeling—PLS-SEM was used using SmartPLS to validate the questionnaire and measure the hypothesized relationships between the constructs. Main Findings: The results show that perceived risk mediates the relationship between the perceived ethicality of social media analytics and the marketing discomfort of the consumers. Moreover, we also found that the negatively perceived ethicality of social media analytics leads to marketing discomfort of the consumers. This negative attitude impacts the consumer’s intention to purchase, interest in the product, and intention to be vulnerable toward the company. Applications of this study: These findings have practical utility for all types of organizations that use social media. This study is general for all social media sites. This study also provides direction for future research, such as managing the personal information of the social media users from being used by the organizations without consumer permission and developing ethical standards to use the consumer information for the marketing strategies. Novelty/Originality of this study: Social media analytics (SMA) gathered data from the social media platforms such as Twitter, Instagram, and blogs, representing a massive room to utilize public data, and these lead towards the ethical concerns of the consumers. For this problem, we studied a complete framework to identify the major outcomes of the PESMA on the consumers' self-disclosure and marketing comfort.

show abstract

Section: Discussionsupporting

confidence: 92%

Section: Discussionsupporting

confidence: 92%

Section: Justice Theory and Social Media Analyticsmentioning

confidence: 99%

Section: Justice Theory and Social Media Analyticsmentioning

confidence: 99%

See 2 more Smart Citations

Social Media Analytics Lens: A Study on Consumer Perceived Risk to Share Information on Social Media Networks

Majeed

Mahmood

Molnár

et al. 2021

HSSR

View full text Add to dashboard Cite

show abstract

“…Past research has shown the importance of social media analytics to understand the perception and to identify the events/factors influencing a brand or product performance (Park et al, 2016;Kaplan and Haenlein, 2010). However, most research are focused toward the customer's perception toward the brand or product (Michaelidou and Micevski, 2019;Rose et al, 2019). Very few studies on social media analytics are focused toward the startup ecosystem.…”

Section: Literature Reviewmentioning

confidence: 99%

Analyzing the startup ecosystem of India: a Twitter analytics perspective

Singh

Chauhan

Dhir

2019

JAMR

View full text Add to dashboard Cite

Purpose The purpose of this paper is to use Twitter analytics for analyzing the startup ecosystem of India. Design/methodology/approach The paper uses descriptive analysis and content analytics techniques of social media analytics to examine 53,115 tweets from 15 Indian startups across different industries. The study also employs techniques such as Naïve Bayes Algorithm for sentiment analysis and Latent Dirichlet allocation algorithm for topic modeling of Twitter feeds to generate insights for the startup ecosystem in India. Findings The Indian startup ecosystem is inclined toward digital technologies, concerned with people, planet and profit, with resource availability and information as the key to success. The study categorizes the emotions of tweets as positive, neutral and negative. It was found that the Indian startup ecosystem has more positive sentiments than negative sentiments. Topic modeling enables the categorization of the identified keywords into clusters. Also, the study concludes on the note that the future of the Indian startup ecosystem is Digital India. Research limitations/implications The analysis provides a methodology that future researchers can use to extract relevant information from Twitter to investigate any issue. Originality/value Any attempt to analyze the startup ecosystem of India through social media analysis is limited. This research aims to bridge such a gap and tries to analyze the startup ecosystem of India from the lens of social media platforms like Twitter.

show abstract