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The purpose of the current study is to examine a social network site (SNS) users' overall satisfaction with SNS use in conjunction with their fan page visiting activities. We examined overall satisfaction with SNS usage from the lens of people's perceptions acquired from the use of sub-components of SNS.

The current study employed uncertainty reduction theory (URT) and general systems theory (GST) to examine antecedents affecting overall satisfaction with SNS use. Five constructs were adopted: interactive and passive uncertainty reduction strategies, perceived usefulness and continuance visiting behavior, satisfaction, and perceived functional benefits. Using a web-based survey, we analyzed 200 SNS users who follow at least one company's fan page, utilizing seemingly unrelated regression models to test hypotheses empirically.

Research findings reveal that uncertainty reduction strategies supported by URT are significantly associated with the perceived usefulness of a company's fan page. In turn, we found that perceived usefulness becomes a strong motivator to continuance visits to the fan page. The frequency of return visiting behaviors eventually accounts for overall satisfaction with SNS. Perceived functional benefits moderates the relationship between perceived usefulness and visiting behaviors significantly.

The current study contributes to information systems (IS), electronic communication, and their adjacent academic disciplines in providing evidence, including (1) the impact of uncertainty reduction strategies on continuance visiting behaviors in the SNS context, (2) SNS functionalities influencing the relationship between people's belief and behavior, and (3) theoretical significant perceptional link between a sub-component and a whole.

This study explores the benefits of accreditation from the Commission on Accreditation for Law Enforcement Agencies (CALEA), according to those who are engaged in the practice.

The authors collected data through open-ended, semi-structured telephone interviews. The authors analyzed the data using an inductive methodology.

The authors found that CALEA police accreditation enhances organizational learning through the development of knowledge brokers, the creation of communities of practice, support for knowledge repositories, support for knowledge managers and greater levels of transparency.

This qualitative study, which focuses on the perceptions and experiences of those involved in the CALEA process, provides a valuable complement to the quantitative literature on accreditation by shedding light on the organizational learning resulting from accreditation.

This paper aims to investigate the literacy corpus regarding the potential of big data to improve public decision-making processes and direct these processes toward the creation of public value. This paper presents a map of current knowledge in a sample of selected articles and explores the intersecting points between data from the private sector and the public dimension in relation to benefits for society.

A bibliometric analysis was performed to provide a retrospective review of published content in the past decade in the field of big data for the public interest. This paper describes citation patterns, key topics and publication trends.

The findings indicate a propensity in the current literature to deal with the issue of data value creation in the private dimension (data as input to improve business performance or customer relations). Research on data for the public good has so far been underestimated. Evidence shows that big data value creation is closely associated with a collective process in which multiple levels of interaction and data sharing develop between both private and public actors in data ecosystems that pose new challenges for accountability and legitimation processes.

The bibliometric method focuses on academic papers. This paper does not include conference proceedings, books or book chapters. Consequently, a part of the existing literature was excluded from the investigation and further empirical research is required to validate some of the proposed theoretical assumptions.

Although this paper presents the main contents of previous studies, it highlights the need to systematize data-driven private practices for public purposes. This paper offers insights to better understand these processes from a public management perspective.

Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media.

For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance.

The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts.

Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.

This paper aims to identify the mechanism through which consumer empowerment, created via the Facebook brand page (FBBP), is transformed into brand page stickiness. Specifically, a model examining the mediating role of FBBP experience and the moderating role of brand love is proposed and tested.

Data from 283 FBBP users were analyzed using structural equation modeling with partial least squares.

The findings reveal the positive effect of consumer empowerment and brand page experience on brand page stickiness. The mediating role of brand page experience and the moderating role of brand love were prominent in the consumer empowerment–brand page stickiness link.

This paper is novel in inaugurating the association between consumer empowerment and FBBP stickiness, which is mediated by brand experience and moderated with brand love. This paper enriches the understanding of how brand page stickiness can be enhanced in the social media context.

This paper guides managers to best utilize FBBP to create a pleasant experience and yield stickiness.

Green demarketing, which promotes anti-consumption as a more extreme sustainability tactic, could help consumers and societies move toward healthier consumption patterns while building strong, long-lasting relationships with consumers. As even the most committed brands find the need to oscillate between demarketing and conventional marketing for survival, this research tests how the congruency of the campaign shown on a brand's home page (owned media) and a following retargeting ad (paid media) could impact perceived congruency and further downstream effects. In doing so, this research proposes that the media context (i.e. news or shopping browsing context) in which the retargeting ad is embedded could determine how much congruency of the demarketing campaign across owned and paid media matters.

An experiment with a 2 (home page content: green vs. demarketing) × 2 (retargeting ad content: product vs. demarketing) × 2 (browsing context: shopping vs. news) between-subjects factorial design was employed with an online panel of 430 participants. The participants first saw the brand's home page content, then were assigned to a website browsing context where the retargeting ad of the brand was embedded.

In a news browsing context, users perceived higher congruency when product retargeting ads (vs. demarketing) were shown after a green home page exposure and when demarketing retargeting ads (vs. products) were delivered after a demarketing home page. The elevated perceived congruency successfully led to higher ad argument and ad attitude. These differences were not present in a shopping browsing context. These results showed that the congruency between the home page and the retargeting ad for demarketing campaigns mattered more in certain media contexts (i.e. news browsing context).

The study closes the empirical gap in demarketing brand activism campaigns by demonstrating when and how congruency between multiple owned and paid channels for demarketing campaigns impacts consumer responses. This study provides evidence of how the match of the demarketing campaign shown on a brand's home page and a following retargeting ad could impact perceived congruency and further downstream effects of ad argument and ad attitude while considering different browsing context effects.

This paper aims to demonstrate that Facebook likes affect outcomes in nonprofit settings. Specifically, Facebook likes influence affinity to nonprofits, which, in turn, affects fundraising outcomes.

The authors report three studies that establish that relationship. To examine social contagion, Study 1 – an auction field study – relies on selling artwork created by underprivileged youth. To isolate signaling, Study 2 manipulates the number of total Facebook likes on a page. To isolate commitment escalation, Study 3 manipulates whether a participant clicks a Facebook like.

The results show that Facebook likes increase willingness to contribute in nonprofit settings and that the process goes through affinity, as well as through Facebook impressions and bidding intensity. The total number of Facebook likes has a direct signaling effect and an indirect social contagion effect.

The effectiveness of the proposed mechanisms is limited to nonprofit settings and only applies to short-term effects.

Facebook likes serve as both a quality signal and a commitment mechanism. The magnitude of commitment escalation is larger, and the relationship is moderated by familiarity with the organization. Managers should target Facebook likes at those less familiar with the organization and should prioritize getting a potential donor to leave a like as a step leading to donation, in essence mapping a donor journey from prospective to active, where Facebook likes play an essential role in the journey. In a charity auction setting, the donor journey involves an additional step of bidder intensity.

The approach the authors study is shown effective in nonprofit settings but does not appear to extend to corporate social responsibility more broadly.

To the best of the authors’ knowledge, this study is the first investigation to map Facebook likes to a seller’s journey through signals and commitment, as well as the only investigation to map Facebook likes to charity auctions and show the effectiveness of this in the field.

This study aims to examine the correlation between the readability of financial statements and the likelihood of future stock price crashes in nonfinancial companies listed on the Egyptian Stock Exchange. It further explores the possible moderating effect of audit quality on this relationship.

The study uses ordinary least squares regression, generalized least squares estimation and two-stage least squares methodology to examine and validate the research hypotheses. The sample comprises 107 nonfinancial companies registered on the Egyptian Stock Exchange from 2016 to 2019.

The results reveal a significant negative association between the readability of financial statements and stock price crash risk. This suggests that companies with more complex financial statements tend to experience higher future crash risks. Additionally, the study identifies audit quality as a significant moderating factor. Higher audit quality, often indicated by engagements with Big-4 audit firms, strengthens the influence of financial statements readability on stock price crash risk. This implies that while high audit quality enhances investor confidence and market stability, it also accentuates the negative consequences of complex financial statements.

The findings of this paper have significant implications for regulators and standard-setting bodies in Egypt. They should consider refining and revising existing standards to emphasize the importance of enhancing the readability of financial reports. Additionally, auditing firms should actively engage in efforts to ensure clearer and more transparent financial reporting. These actions are vital for boosting investor confidence, strengthening Egypt’s capital market and mitigating potential risks associated with information opacity and complexity.

This study represents a pioneering endeavor within the Arab and Egyptian financial environments. To the best of the author’s knowledge, it is the first examination of the association between the readability of financial statements and stock price crash risk in these contexts. Furthermore, it explores factors such as audit quality that may influence this connection.

The purpose of this paper is to examine Robert Pagès' 1948 conception of “auto-document” as a possible forerunner to the neo-documentalist conception of “documentality” as offered in Bernd Frohmann’s 2012 article “The Documentality of Mme Briet’s Antelope.”

This paper is conceptual and historical.

Robert Pagès' concept of the “auto-document” in his 1948 article proposed an understanding of documents that depends on the “uniqueness” of a document. His article proposed a post-Otletian theory of documents similar to a discussion of documents by Bernd Frohmann in 2012 with the concept of “documentality.” Further attention to Pagès work and to Frohmann’s works could result in new understandings of Briet’s works, could illuminate other works and authors understood as belonging to neo-documentation and could yield new understandings of documents and information from the perspective of documentality as a new philosophy of information and documents.

Further attention to Pagès' work and to Frohmann’s works could yield new understandings of documents and the relation of documentary types across natural and sociocultural domains and bring renewed attention to documentality as a new philosophy of information and documents.

Attention to these issues could broaden the study of documents and documentation, increase the historical understanding of Suzanne Briet’s works and bring light to other works in neo-documentation, particularly in regard to the concept of documentality as a new philosophy of documentation and information.

Attention to these issues could broaden the study of documents and documentation to include more broadly animal and other natural entities and our relationships to them. The works cited also illuminate an empirical science understanding of documents, documentary evidence and information.

This is one of the first papers commenting on Robert Pagès’ works and brings renewed attention to Bernd Frohmann’s works, as well as to neo-documentation and its concept and philosophy of documentality, as a new philosophy of information and documents.

Purchase conversion prediction aims to improve user experience and convert visitors into real buyers to drive sales of firms; however, the total conversion rate is low, especially for e-retailers. To date, little is known about how e-retailers can scientifically detect users' intents within a purchase conversion funnel during their ongoing sessions and strategically optimize real-time marketing tactics corresponding to dynamic intent states. This study mainly aims to detect a real-time state of the conversion funnel based on graph theory, which refers to a five-class classification problem in the overt real-time choice decisions (RTCDs)—click, tag-to-wishlist, add-to-cart, remove-from-cart and purchase—during an ongoing session.

The authors propose a novel graph-theoretic framework to detect different states of the conversion funnel by identifying a user's unobserved mindset revealed from their navigation process graph, namely clickstream graph. First, the raw clickstream data are identified into individual sessions based on a 30-min time-out heuristic approach. Then, the authors convert each session into a sequence of temporal item-level clickstream graphs and conduct a temporal graph feature engineering according to the basic, single-, dyadic- and triadic-node and global characteristics. Furthermore, the synthetic minority oversampling technique is adopted to address with the problem of classifying imbalanced data. Finally, the authors train and test the proposed approach with several popular artificial intelligence algorithms.

The graph-theoretic approach validates that users' latent intent states within the conversion funnel can be interpreted as time-varying natures of their online graph footprints. In particular, the experimental results indicate that the graph-theoretic feature-oriented models achieve a substantial improvement of over 27% in line with the macro-average and micro-average area under the precision-recall curve, as compared to the conventional ones. In addition, the top five informative graph features for RTCDs are found to be Transitivity, Edge, Node, Degree and Reciprocity. In view of interpretability, the basic, single-, dyadic- and triadic-node and global characteristics of clickstream graphs have their specific advantages.

The findings suggest that the temporal graph-theoretic approach can form an efficient and powerful AI-based real-time intent detecting decision-support system. Different levels of graph features have their specific interpretability on RTCDs from the perspectives of consumer behavior and psychology, which provides a theoretical basis for the design of computer information systems and the optimization of the ongoing session intervention or recommendation in e-commerce.

To the best of the authors' knowledge, this is the first study to apply clickstream graphs and real-time decision choices in conversion prediction and detection. Most studies have only meditated on a binary classification problem, while this study applies a graph-theoretic approach in a five-class classification problem. In addition, this study constructs temporal item-level graphs to represent the original structure of clickstream session data based on graph theory. The time-varying characteristics of the proposed approach enhance the performance of purchase conversion detection during an ongoing session.