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It seems that the Internet boom, which started at the end of the 1990s and finished with the spectacular collapse of the so-called dotcoms, is probably over. We are currently enjoying a period of fast and stable growth. This is manifested by the growing number of both Internet users and companies which – to an ever-increasing extent – use the Internet as a form of communication (both internal and external), promotion, sales etc. Expenditures on Internet advertising are growing continuously and now constitute more than 25% of all advertising expenditure. A natural consequence of this development is the need for the standardisation and organisation of the world of the Internet. These activities will result in a greater awareness of the benefits which this medium provides, increasing the possibilities of its use, and – most importantly – the opportunity to evaluate the return on investments made on the Internet. Nowadays, it is clear that many companies are striving to increase the quality of their activities on the Internet or to improve the effectiveness of such activities. As a consequence, the number of companies that look for indices which would enable the making of more precise and effective decisions in the scope of online operations is growing.

This chapter is dedicated to the phenomenon of the increasing role of the Internet in business, including the scale of its use by Polish and international companies. We present the most commonly used measures of marketing activities on the Internet and in social media. This group includes the indices which make it possible to determine whether a company actually needs a website. Other measures allow for the improvement in the effectiveness of the activity on the Internet, whereas others specify the costs of activities on the Internet and often serve as the basis for settlements between a company and advertising agencies or companies specialising in website design. It is worth emphasising that the Paid, Earned, Shared, Owned (PESO) model, worked out by Don Bartholomew,¹ is the basis for creation and description of indices concerning social media. This model has gained certain popularity in the social media industry. It does not, however, specify how individual indices should be named and calculated. It maps already existing indices and adapts them to specific levels of marketing communication measurement. All the measures indicated by the author of the model have been grouped into five major areas: exposure, engagement, brand awareness, action and recommendations. This model– similarly to all models of performance measurement – inspired by the sales funnel concept, adjusts certain standard indices and proposals of measurements for specific levels. Additionally, the measures are divided into four types, depending on who the owner of the content is: Paid (P) – refers to all forms of paid content; Owned (O) – all websites and web properties controlled by a company or brand; Earned (E) – the contents about a given brand created spontaneously by Internet users; and Shared (S) – the contents shared by Internet users.

This chapter presents results of a qualitative study among European champions in social media management. It aims to describe a strategic process and its implications for social media strategic management.

The chapter is based on four in-depth case studies involving both primary and secondary data analysis and interviews.

Social media management is governed by similar principles as corporate communication management. However, there is an important role of personal preferences of senior executives for an effectiveness of the strategic process.

The model allows describing the social media management in the multinational companies. Organizational learning process drawn in this chapter can be directly applied in the multinational companies from various industries.

Social media create an environment in which established actors need to learn how to communicate socially. Sophistication of the tools requires sophistication of the strategies and processes.

This chapter analyzes companies from various industries which are considered successful in social media strategic management. It creates a model which is applicable in various industries. It provides also insights into social media strategies from the research among social media global leaders.

This study examined social media, tax morale, and tax compliance behaviour. Partial Least Square-Structural Equation Modelling (PLS-SEM) was utilized to investigate the quantitative data gathered from 592 salaried and self-employed taxpayers in East Malaysia, comprising two regions – Sabah and Sarawak. The results showed that social media had no significant effect on tax compliance. There was, however, a significant and negative relationship between social media and tax morale. A significant and positive effect of tax morale on tax compliance was also discovered. The bootstrapping technique indicated that tax morale mediates the association between social media and tax compliance. This research is among the earliest in a developing country to investigate the effect of social media in enhancing tax compliance, thus, contributing to the tax literature with a broader focus.

Social media stage online patterns of social interaction that differ remarkably from ordinary forms of acting, talking and relating. To unravel these differences, we review the literature on micro-sociology and social psychology and derive a shorthand version of socially-embedded forms of interaction. We use that version as a yardstick for reconstructing and assessing the patterns of sociality social media promote. Our analysis shows that social media platforms stage highly stylized forms of social interaction such as liking, following, tagging, etc. that essentially serve the purpose of generating a calculable and machine-readable data footprint out of user platform participation. This online stylization of social interaction and the data it procures are, however, only the first steps of what we call the infrastructuring of social media. Social media use the data footprint that results from the stylization of social interaction to derive larger (and commercially relevant) social entities such as audiences, networks and groups that are constantly fed back to individuals and groups of users as personalized recommendations of one form or another. Social media infrastructure sociality as they provide the backstage operations and technological facilities out of which new habits and modes of social relatedness emerge and diffuse across the social fabric.

This chapter explores how audience research company Shareablee empowered marketers to look beyond ‘big numbers’ as social media was growing, and adjust their thinking towards a single, digestible source of meaningful measurement. As consumers spend more time online and on mobile devices, their attention continues to fragment across platforms, devices, and apps. This creates new challenges for marketers when it comes to reaching consumers meaningfully with content – and many challenges for researchers when it comes to measuring ROI. Shareablee believed that social media presented both a channel for connecting marketers with customers, and an unprecedented research opportunity to consider what billions of people care about, in real time. Innovating through a fast-changing and crowded digital environment means building quickly on partial information, iterating openly and forming strong but flexible opinions about what will benefit marketers most as the world changes around them.

This chapter draws on both theoretical and empirical literature on trust and discusses the role of trust in strategic communication. It also examines the importance of trust for organizational success, the dimensions of trust and distrust and discusses quantifiable proxies to measure trust and distrust on social media. The theoretically driven dimensions of trust and distrust served as a framework to examine how Boeing and Airbus use Twitter to communicate with their stakeholders and publics. 6,926 Twitter messages were examined in the process of content analysis. The following proxies of stakeholder and publics' trust in an organization were identified for Twitter: number of followers, friends and likes; frequency of online activities; length of messages; use of hashtags, links, exclamation and questions marks; and use of specific words and phrases in messages. Two separate lists of words and phrases were created, one for proxies of trust and one for proxies of distrust. In addition, the following trust building actions that organization can engage in on Twitter were identified: listening and engaging in dialogue by following users, mentioning users in messages, replying to enquiries, providing and encouraging feedback.