Search results

This study aims to understand the extent of privacy concerns regarding voice-activated personal assistants (VAPAs) on Twitter. It investigates three key areas: (1) the effect of privacy-related press coverage on public sentiment and discussion volume; (2) the comparative negativity of privacy-focused conversations versus general conversations; and (3) the specific privacy-related topics that arise most frequently and their impact on sentiment and discussion volume.

A dataset of 441,427 tweets mentioning Amazon Alexa, Google Assistant, and Apple Siri from July 1, 2019 to June 30, 2021 were collected. Privacy-related press coverage has also been monitored. Sentiment analysis was conducted using the dictionary-based software LIWC and VADER, whereas text mining packages in R were used to identify privacy-related issues.

Negative privacy-related news significantly increases both negativity and volume in Twitter conversations, whereas positive news only boosts volume. Privacy-related tweets were notably more negative than general tweets. Specific keywords were found to either increase or decrease the sentiment and discussion volume. Additionally, a temporal evolution in sentiment, with general attitudes toward VAPAs becoming more positive, but privacy-specific discussions becoming more negative was observed.

This research augments the existing online privacy literature by employing text mining methodologies to gauge consumer sentiments regarding privacy concerns linked to VAPAs, a topic currently underexplored. Furthermore, this research uniquely integrates established theories from privacy calculus and social contract theory to deepen our analysis.

The aim is to present a novel, empirical analysis of the competitive battle between retailer‐owned private labels (also known as store brands) and national brands (manufacturer‐owned) in the online retail market.

The authors investigate competition between private labels (PL) and national brands (NB) across online and offline retail channels using data supplied by a multichannel supermarket chain describing a full year's purchase records for 2,742 households in 36 product categories. They analyse competition between these two types of brands by estimating the following competition indicators: market share, loyalty and conquesting power (a measure of the ability of a brand to attract new customers).

The results indicate that, whereas both PL and NB increase their loyalty online (versus offline), only the PL increases market share and conquesting power online. Several specific category‐level effects are also found.

The analysis is restricted to a specific retailer and to grocery products.

Given the general improvement found for the PL in the online retail channel, together with the growing importance of online retailing, manufacturers should expect increasing retailer bargaining power. Since this improvement is not equal across categories, however, some manufacturers will have harder times than others.

To the best of the authors' knowledge, this is the first empirical paper to examine competition between PL and NB in the online channel. The database used is also highly unique in the sense that it is very unusual to obtain real purchase data for the same set of purchasers in both the offline and online retail channels.