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Early information technology scholarship centered on the internet’s potential to be a democratizing force was often framed using an equalization/normalization lens arguing that either the internet was going to be an equalizing force bringing power to the masses, or it was going to be normalized into the existing power structure. The purpose of this paper is to argue that considered over time the equalization/normalization lens still sheds light on our understanding of how social media (SM) strategy can shape electoral success asking if SM are an equalizing force balancing the resource gap between candidates or are being normalized into the modern campaign.

SM metrics and electoral data were collected for US congressional candidates in 2012 and 2016. A series of additive and interactive models are employed to test whether the effects of SM reach on electoral success are conditional on levels of campaign spending.

The results suggest that those candidates who spend more actually get more utility for their SM campaign than those who spend less in 2012. However, by 2016, spending inversely correlates with SM campaign utility.

The findings indicate that SM appeared to be normalizing into the modern congressional campaign in 2012. However, with higher rates of penetration and greater levels of usage in 2016, the SM campaign utility was not a result of higher spending. SM may be a greater equalizing force now.

Campaigns that initially integrate digital and traditional strategies increase the effectiveness of the SM campaign because the non-digital strategy both complements and draws attention to the SM campaign. However, by 2016 the SM campaign was not driven by its relation to traditional campaign spending.

This is the first large N study to examine the interactive effects of SM reach and campaign spending on electoral success.

The purpose of this paper is to examine the impact of microblogging word of mouth (MWOM) through twitter on value co-destruction for Athens, as a tourism destination facing a sustained crisis. The study demonstrates the sentiment and sharing evolution of tweets, illustrating the value co-destruction of a tourism destination. Overall, the study expands understanding on the online footprints of MWOM in the field of tourism.

It uses social media focused data mining and sentiment analysis, to analyze more than 90,000 tweets posted by top twitter influencers between 2013 and 2015. The methodology that the authors have adopted follows seven steps: first, identification of the top-5 twitter influencers who use the hashtag #Athens, based on their klout score; second, collection of tweets from the top-5 twitter influencers, for the period from January 2013 until June 2015; third, collection of the retweets metadata of the above tweets and of the corresponding retweeter accounts (i.e. user id, name, screen name), together with the frequency of retweeting per tweet; fourth, collection of user metadata (i.e. location and number of followers) from the retweeter accounts; fifth, influence computation of retweetwers using their klout score; sixth, tweets classification based on the klout score of their retweeters; and seventh, sentiment analysis of the collected tweets.

The findings show the high potential of value co-destruction in virtual environments, through negative MWOM related to tourism destinations in crisis, and shared among highly influencing users, that disseminate negative stories through microblogging. The findings also reveal the existence of negativity bias that can reduce the risks of visiting a new destination facing a crisis and, at the same time, significantly destroy the destination’s value.

This is the first study to examine the impact of MWOM through twitter on a tourism destination facing a sustained crisis, such as Athens. This study uses social media focused data mining and sentiment analysis, to analyze more than 90,000 tweets posted by top twitter influencers between 2013 and 2015. The findings reveal the existence of negativity bias that can reduce the risks of visiting a new destination facing a crisis and, at the same time, significantly destroy the destination’s value.

The purpose of this paper is to analyze the moderating effects of the social influence of the blogger and the extent to which the reader has experience of that blogger, on loyalty toward the blogger, via two variables: blogger interactive practices (BIPs) and blogger credibility.

A quantitative empirical study was undertaken to estimate the research model. Structural equations were employed.

The results show that blogger social influence moderates the relationships between BIPs and intention to recommend the blogger and blogger credibility; and between credibility and intention (to recommend the blogger and to follow their suggestions). Meanwhile, the extent of the reader’s experience of the blogger moderates the relationships between BIPs and intention.

The present work offers criteria that may be of value to bloggers and firms in assessing the extent to which the blogger’s activities are effective in terms of achieving reader loyalty. The proposed variables are measured objectively online, using the Klout Index of social influence and the extent of the reader’s experience of the blogger (inferred from the number of bloggers followed by the reader).

Blogs are considered a mechanism to manage information overload in social media, and they are recognized for their influence on the reader’s decision-making process. The study contributes to the knowledge-base by proposing two moderating variables of loyalty-formation: blogger social influence and the extent of the reader’s experience of the blogger.

This paper aims to provide a social network site influence (SNSI) profile of early adopters. This study explores the relationship between personality traits of early adopters of social network sites (SNS), their propensity to share information and rumors and their general SNSI.

An online survey was sent to the first users of Twitter (n = 200) and Google+ (n = 130) to assess their personality traits. Answers of each respondent were matched to their SNSI scores from Klout and PeerIndex, the industry standard for measuring SNSI.

Early adopters of SNS, in comparison to market mavens, are more likely to exert influence on one particular topic related to their profession: technology and the internet. Their levels of extraversion, openness and conscientiousness have a positive and significant impact on information sharing, and a negative impact on rumor sharing. Both, information sharing and rumor sharing have a positive and significant impact on the general SNSI of early adopters.

Firms struggle to decide whether to invest early in the life of newly created SNS as they are unsure about the characteristics of early adopters of such networks, and, more importantly, whether these sites are effective initial vectors for word-of-mouth. The findings demonstrate that early adopters’ influence (SNSI score) is on par with that of the rest of SNS users, suggesting their influence may be somewhat limited. The study also shows that the opinion leadership impact of the more influential early adopters is monomorphic in nature, being mainly confined to the related technology and internet domains.

The diffusion of social media among public administrations has significantly grown in the last years. This phenomenon has created a field of research that seeks to understand the adoption and impact of social media in the public sector. The purpose of this paper is to identify the factors that make social media successful in Spanish local governments.

The paper is based on an adapted version of a neo-institutional model: Enacting Electronic Government Success (EEGS). The data have been collected through three main sources: primary data from a questionnaire designed and conducted by the authors, secondary data of statistical sources, and tertiary data collected through Klout Score.

The results from a survey and statistical analysis provide preliminary validation of the model and show a direct relationship between organizational, institutional, and environmental factors with the successful use of social media in local public administrations. The data analysis shows that ten variables jointly explain 54.6 percent (adjusted R²=0.546) of the variability observed in the dependent variable.

First, the analysis model used represents a limited sample size to carry out a complex quantitative analysis. Second, the use of Klout Scores can offer some bias. Finally, certain variables complicate the comparative potential of the study.

This study provides original primary data and contributes to the growing field of study related to social technologies in public administrations. This research also confirms in an exploratory way the validity of the EEGS model.

Misinformation can have lasting impacts in the management and control of a public emergency. The purpose of this paper is to demonstrate how misinformation flows and how user characteristics can shape such flows in the context of a violent riot in Singapore.

The authors apply the two-step flow theory and discuss the mixed methods approach involving wrangling Twitter data and descriptive analysis to develop and analyse two corpuses of misinformation related to the riot.

The findings are mostly consistent with the two-step flow theory, in that misinformation flows to the masses from opinion leaders (as indicated by higher measures such as online social influence and followers/following ratio). In the presence of misinformation, tweets opposing such misinformation may not always come from opinion leaders.

The authors work furthers knowledge about how misinformation goes viral, which provides practical implications to help policymakers and scholars in understanding and managing the dynamics and pitfalls of misinformation during an emergency.

This paper tackles the problem of misinformation in public emergencies using a mixed methods approach and contributes to ongoing theoretical work on managing online misinformation especially in public emergencies and crises.

Central to the celebrity creation process is mass media communication and impression management (IM) behaviors of social actors. The emergence of social network sites (SNSs) such as Twitter offers a platform for social actors to engage both of these means in efforts to manage their celebrity. The purpose of this paper is to contribute to the understanding of how celebrity athletes manage their celebrity status by investigating IM tactics employed by National Basketball Association (NBA) celebrities on Twitter.

A content analytic design was employed to examine the Twitter posts of the top ten most popular and influential NBA celebrity athletes (past and present) at the time of tweet acquisition.

The findings revealed the celebrity athletes used a variety of IM tactics to manage their celebrity. Defensive IM tactics (i.e. reactive measures taken) were used sparingly when compared to offensive IM tactics (i.e. proactive measures taken). Also, consistent with extant IM literature, the celebrity athletes utilized IM tactics in isolation as well as in combination.

The extant literature suggests that celebrities cultivate their relationships with the various media outlets with the potential to create (or even damage) one’s celebrity. This study offers celebrity athletes and their managers with useful insight on celebrity management.

This study is the first to examine IM in a sport business context, particularly the use of IM of athletes on SNSs.

Digital transformation allows organisations to increase the efficiency of their operations, respond faster and make more accurate decisions, adapt quickly to a new reality, and improve the customer experience; however, many companies still face several obstacles and challenges on its path to digital transformation, including organisational culture, a lack of IT resources and management, a lack of a clear budget for digital transformation, a challenge with digital security and artificial intelligence (AI). This chapter concludes the edited book focusing on management and information technology in the digital era. We acknowledge there are still many areas that need to be explored regarding technological adoption. However, we hope we have captured some theoretical insights that are available at this point. We hope readers will find the chapters in this book both enriching and thought-provoking and that the insights provided in the collection of research materials will enhance the understanding in this area, inspire further interest in management and information technology in the digital era, and provide a basis for sound management decisions and stimulate new ideas for future research.

Industry platforms can alter relations among exchange partners in such a way that the industry structure is changed. The focus of much industry platform research has been on how platform creation and leadership offers advantages to the most central firms, but platforms can also be advantageous for small specialist firms that compete with the most central firms. We examine book publishing as an example of an industry in which the central players – large publishing firms – are losing power to self-publishing authors because the distributor Amazon has a powerful platform for customers to communicate independently, and the non-publishing platform Twitter also serves as a medium for readers to discuss and review books. Our empirical analysis is based on downloaded sales statistics for Amazon Ebooks, matched with Amazon reviews of the same books and tweets that refer to the book or the author. We analyze how Ebook sales are a function of publisher, Amazon reviews, and tweets, and we are able to assess the importance of each factor in the sale of book titles. The main finding is that Amazon reviews are powerful drivers of book sales, and have greater effect on the sales of books that are not backed by publishers. Twitter also affects book sales, but less strongly than Amazon reviews.