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This study aims to propose a set of metrics in order to assess reactivity, dialogic communication and stakeholder engagement (popularity, commitment and virality): stakeholders' mood and social legitimacy on corporate Facebook pages. These metrics can offer a better understanding and measurability of this social media/social network/online communication management tool.

Three theories (dialogic, stakeholders and legitimacy) were considered in the development of these metrics. Empirical evidence was collected from a sample of 314 European companies. Then ten active companies were used to validate the proposed metrics on Facebook.

The constructed set of metrics was found to be valid and efficiently usable according to the principles of the applied theories. Moreover all the proposed metrics could be adapted for such sites as Google+.

Limitations can only be identified within the validation process as the metrics were only applied to ten representative companies from the Eurozone.

The proposed metrics will help users, marketing/PR/communication professionals and company managers to measure their and their competitors' popularity, commitment, virality (metrics which reflect stakeholder engagement), and the mood of stakeholders, and use content analysis in order to measure social legitimacy via CSR information disclosure on Facebook. Thus the online reputation of a company can be practically measured.

This paper is the first proposing metrics to assess stakeholder engagement and social legitimacy on a corporate Facebook page that can be used in both academic and professional circles to a gain a better understanding of corporate online communication via Facebook.

The purpose of this paper is to provide an introduction to the various web metrics tools that are available, and to indicate how these might be used in libraries.

The paper describes ways in which web metrics can be used to inform strategic decision making in libraries.

A framework of possible web metrics is provided that can be adapted for use as appropriate in libraries.

The paper offers assistance to any web site manager in planning new developments, given limited resources.

In this paper the authors aim to review the state-of-the-art literature on online review systems and their impacts on consumer behavior and retailers' performance with the aim of identifying research gaps related to different design features of review systems and developing future research agenda.

The authors conducted a systematic review based on PRISMA 2020 protocol, focusing on studies published in the domains of retailing and marketing. This procedure resulted in 48 selected papers investigating the design features of retailer online review systems.

The authors identify eight design features that are controllable by retailers in an online review system. The design features have been researched independently in previous literature, with some features receiving more attention. Most selected studies focus on the design features adapted metrics and review presentations, while other features are generally neglected (e.g. rating dimensions). Previous literature argues that design features affect consumer behaviors and retailers' performance. However, the interactions among the features are still neglected in the literature, creating a relevant gap for future research.

This paper distinguishes between different types of retailer online review systems based on how they are implemented. The authors summarize the state-of-the-art of relevant literature on design features of online review systems and their effects on consumer- and retailer-related outcome variables. This systematic literature review distinguishes between online reviews provided on websites controlled by retailers (internal systems) and third-party websites (external systems).

The purpose of this paper is to examine the impact of affiliate marketing strategies as a tool for increasing customers' engagement and vulnerability over financial services. This is attempted by examining the connection between affiliate marketing factors and customers' brand engagement and vulnerability metrics.

The authors developed a three-staged methodological context, based on the 7 most known centralized payment network (CPN) firms' website analytical data, which begins with linear regression analysis, followed by hybrid modeling (agent-based and dynamic models), so as to simulate brand engagement and vulnerability factors' variation in a 180-day period. The deployed context ends by applying the cognitive modeling method of producing heatmaps and facial analysis of CPN websites to the selected 47 vulnerable website customers, for gathering more insights into their brand engagement.

Throughout the simulation results of the study, it becomes clear that a higher number of backlinks and referral domains tend to increase CPN firms' brand-engaged and vulnerable customers.

From the simulation modeling process, the implication for backlinks and referral domains as factors that enhance website customers' brand engagement and vulnerability has been highlighted. A higher number of brand-engaged website customers could mean that vulnerable categories of customers would be impacted by CPNs' affiliate marketing. Improving those customers' knowledge of the financial services utility is of utmost importance.

The outcomes of the research indicate that online banking service providers can increase their customers' engagement with their brands by adopting affiliate marketing techniques. To avoid the increase in customers' vulnerability, marketers should aim to apply affiliate marketing strategies to domains relevant to the provided financial services.

The paper's outcomes provide a new approach to the literature, where the website customer's brand engagement comes out as a valuable metric for estimating online banking sector customers' vulnerability.

In the current digital era where online content is riddled with fabricated metrics and rankings, this research aims to investigate the underpinning mechanisms of the calculative practices which actors engage with to evaluate digital platform content in the absence of well-defined performance measures.

The paper focuses on the online, photo-sharing platform Instagram which is devoid of common performance measures such as rankings, ratings and reviews. The authors applied netnographic methods to capture users' actions and interactions at the Greek Instagram community. The authors adopt a practice lens as informed by Schatzki's ‘site ontology’ to capture actors' calculative practices as organised by rules, teleoaffective structures and general and practical understandings.

Platform actors engage in aesthetic and palpable evaluations of other user profiles and their posted content. They employ permissible (e.g., using third-party apps) and illicit (e.g., lobbying and procuring engagement) tactics to measure and manage digital platform performance, fabricate metrics and blur others' evaluations, in pursuit of prestige and material teleologies. Their calculative practices are conditioned by an implicit social etiquette, which permeates the platform both horizontally and vertically.

First, the paper captures and theorises the mechanisms which underpin actors' calculative practices for performance measurement in the absence of robust judgement devices. Second, it demonstrates how ambiguous assemblages of material and prestige teleologies, aesthetic and palpable evaluative regimes and implicit rules and practical expertise collectively invoke platform actors' calculative practices and the construction of performance measures. In doing so, it contributes to performance measurement literature via demonstrating how management accounting is implicated in the evaluation of digital platform outputs.

The paper provides insight on how platform actors fabricate performance metrics, what they perceive as ‘good’ online content and what constitutes an ‘impactful’ user account or a ‘successful’ social media campaign. Such findings are valuable to management accountants, entrepreneurs and practitioners who seek to evaluate digital platform performance.

Enterprise social networks (ESN) are increasingly used by companies to reinforce collaboration and knowledge sharing. While prior research has investigated ESN use practices, little is known about potential user roles emerging on these platforms. Against this backdrop, this paper develops an ESN knowledge actor role framework.

The framework is constructed based on a systematic review of literature covering knowledge worker role typologies, user roles identified in public online social spaces as well as findings from ESN research.

The ESN knowledge actor role framework distinguishes eight contributing and two reading roles. It describes the associated participation behaviours and establishes metrics to identify the roles.

Providing a notion of knowledge management-related roles in ESN, the framework enables a better understanding of knowledge processes and the involved actors. Moreover, the paper advances the field of ESN data analytics by designing a set of ESN metrics to characterise user behaviour.

Understanding ESN user roles, in particular regarding their knowledge contributions to the platform, can improve knowledge transparency in companies. The framework may usefully support the identification and management of critical knowledge resources and support decision-making in the areas of human resources management and knowledge management.

Providing a platform for knowledge-intensive interactions as well as record of user activities, ESN are well suited to observe and identify knowledge actor roles emerging in this context.

As existing studies show the accuracy of sampling methods depends heavily on the evaluation metric in web accessibility evaluation, the purpose of this paper is to propose a sampling method OPS-WAQM optimized for Web Accessibility Quantitative Metric (WAQM). Furthermore, to support quick accessibility evaluation or real-time website accessibility monitoring, the authors also provide online extension for the sampling method.

In the OPS-WAQM method, the authors propose a minimal sampling error model for WAQM and use a greedy algorithm to approximately solve the optimization problem to determine the sample numbers in different layers. To make OPS-WAQM online, the authors apply the sampling in crawling strategy.

The sampling method OPS-WAQM and its online extension can both achieve good sampling quality by choosing the optimal sample numbers in different layers. Moreover, the online extension can also support quick accessibility evaluation by sampling and evaluating the pages in crawling.

To the best of the authors’ knowledge, the sampling method OPS-WAQM in this paper is the first attempt to optimize for a specific evaluation metric. Meanwhile, the online extension not only greatly reduces the serious I/O issues in existing web accessibility evaluation, but also supports quick web accessibility evaluation by sampling in crawling.

The journalism profession has radically changed due to the digitisation and the development of new media. As content is moving online, rapidly evolving Internet technologies have affected basic journalistic work processes. In this context, changes in technology as well as audience engagement have greatly expanded the skills required to be a professional journalist nowadays. A number of studies have shown that search engines constitute an important source of the traffic to online news outlets around the world, identifying the significance of top rankings in search results. Concurrently, in the digital age, the interest in monitoring online activities as well as the significance of studying the traffic data has intensified. This chapter summarises the major findings of two studies regarding the use and impact of SEO and web analytics on news websites and journalism profession in Greece. Through examination of a sample of Greek journalists and several Greek news websites, it aims to provide new insights in the field of digital journalism.

Allocating budget optimally to marketing channels is an increasingly difficult venture. This difficulty is compounded by an increase in the number of marketing channels, a rise in siloed data between marketing technologies, and a decrease in individually identifiable data due to legislated privacy policies. The authors explore the rich attribution modeling literature and discuss the different model types and approaches previously used by practitioners and researchers. They also investigate the changing landscape of marketing attribution, discuss the advantages and disadvantages of different data handling approaches (i.e., aggregate vs. individualistic data), and present a research agenda for future attribution research.