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Purpose: This study aims to demonstrate the importance of the requisite trust for the processes of digitalization of business, the state and society in general. Design/methodology/approach: The work is built "from particular to general". The analysis of many cases of digitalization projects leads to some higher-level principles useful for description most of them – trust, umwelt and complexity. Findings: Based on the analysis of empirical material, the principle of requisite trust is introduced based on the definition of trust through a "relevant umwelt". In addition, the article examines many aspects of society digitalization processes using cybernetic concepts. It is shown that (1) in the core of digitalization process is the export of the umwelt from human head to a computer (digital umwelt), (2) models used in the digital platforms are not only a reflection of social processes, but have a significant impact on them, like the observers of cybernetics of the second order and (3) umwelt concept is closely related to a social reality concept, meanings are relative and are carried by the communication systems. Research limitations/implications: The paper summarized practical and theoretical experience in the field of digital projects and introduced The Law of Requisite Trust. In the future, this principle should be studied more formally in quantitative terms. Originality/value: The principle of requisite trust, as well as the definition of trust through the relevant umwelt is original. The promotion of trust in organizations and also digital organizations using such instruments as standard of social responsibility (ISO 26000) has high practical value. [ABSTRACT FROM AUTHOR]

Purpose: India has the biggest number of active users on social media platforms, particularly Twitter. The purpose of this paper is to examine public sentiment on COVID-19 vaccines and COVID Appropriate Behaviour (CAB) by text mining (topic modeling) and network analysis supported by thematic modeling. Design/methodology/approach: A sample dataset of 115,000 tweets from the Twitter platform was used to examine the perception of the COVID-19 vaccination and CAB from January 2021 to August 2021. The research applied a machine-learning algorithm and network analysis to extract hidden and latent patterns in unstructured data to identify the most prevalent themes. The COVID-19 Vaccine Hesitancy Amplification Model was formulated, which included five key topics based on sample big data from social media. Findings: The identified themes are Social Media Adaptivity, Lack of Knowledge Providing Mechanism, Perception of Vaccine Safety Measures, Health Care Infrastructure Capabilities and Fear of Coronavirus (Coronaphobia). The study implication assists communication strategists and stakeholders design effective communication strategies using digital platforms. The study reveals CAB themes as with Mask Wearing Issues and Employment Issues as relevant themes discussed on digital channels. Research limitations/implications: The themes extracted in the present study provide a roadmap for policy-makers and communication experts to utilize social media platforms for communicating and understanding the perception of preventive measures of vaccination and CAB. As evidenced by the increased engagement on social media platforms during the COVID-19-induced lockdown, digital platforms are indeed valuable from the communication perspective to be proactive in the event of a similar situation. Moreover, significant themes, including social media adaptivity, absence of knowledge-providing mechanism and perception of safety measures of the vaccine, are the critical parameters leading to an amplified effect on vaccine hesitancy. Practical implications: The COVID-19 Vaccine Hesitancy Amplification Themes (CVHAT) equips stakeholders and government strategists with a preconfigured paradigm to tackle dedicated communication campaigns and assess digital community behavior during health emergencies COVID-19. Social implications: The increased acceptance of vaccines and the following of CAB decrease the advocacy of mutation of the virus and promote the healthy being of the people. As CAB has been mentioned as a preventive strategy against the COVID-19 pandemic, the research preposition promotes communication intervention which helps to mitigate future such pandemics. As developing, economies require effective communication strategies for vaccine acceptance and CAB, this study contributes to filling the gap using a digital environment. Originality/value: Chan et al. (2020) recommended using social media platforms for public knowledge dissemination. The study observed that the value of a communication strategy is increased when communication happens using highly trusted and accessible channels such as Twitter and Facebook. With the preceding context, the present study is a novel approach to contribute toward digital communication strategies related to vaccination and CAB. [ABSTRACT FROM AUTHOR]

Purpose: There is a growing worry about people possibly isolating themselves in online bubbles and avoiding contact with ideas that differ from their beliefs, creating a scenario of ideological polarization. To investigate into this matter, this work aims for a reflection about the contingency of communication in social media. Does social media make the experience of communication in the digital space more contingent (providing it with more possibilities, with people accessing different contents and ideas) or less contingent (reducing the available possibilities, making people isolate themselves)? Design/methodology/approach: This is a theoretical work, constructed through bibliographical reviews. To reflect about the question that are posed, the author selected Niklas Luhmann's social systems theory to approach the concept of contingency. In addition to that, the author presented the main arguments of the debates about echo chambers and online bubbles. In the end, the author combined the two reviews together using elements of the Luhmannian theory and drew some conclusions about the initial question. Findings: The study concluded that social media have an ambivalent potential regarding contingency in the digital space: it can both expand or reduce the available possibilities of communication, depending on criteria like topic, potential of diffusion and focus of attention. There is no one-side effect. Research limitations/implications: The approach at echo chambers does not reflect "the" form of contingency in social media, but "a" form. Therefore, the study cannot provide any general conclusions about the relation between contingency and social media. The digital space is a large one, and more studies are required to achieve more substantial propositions. Originality/value: The research has an originality value both for systems theory and social media studies. First, because, as far as the author knows, no other system-theoretical argument has taken the connection between contingency and social media as a primary analysis object. Second, because of a theoretical interpretation effort, the studies of echo chambers indicate mixed results about the phenomenon of online isolation, but no attempt was made to make sense of these mixed results from a specific sociological theory. The author did that by using Luhmann's theoretical framework, which proved to be a good tool for explaining and unifying these different results on a more abstract level. [ABSTRACT FROM AUTHOR]

Purpose ? This paper considers correction aspects of computer communication networks modelling with emphasis on their performance evaluation. In general, the problem is to achieve the highest possible performance given constraints on the system. Design/methodology/approach ? The paper reviews the application of the analytical methods, based on the queueing theory, to the computer communication systems and makes an extension of theory to the improvement of the developed analytical models. In this sense the paper describes the derivation of a correction factor for analytical models to study more precise their basic parameters (end-to-end delay, performance, etc.). Finding ? The contribution is in incorporating the derived correction factor to account for the real non-exponential nature of the input to the transmission channels of computer communication systems. The produced results by corrected analytical model are compared with results previously reported in the literature to estimate the magnitude of improvement. Practical implications ? The improved analytical models were tested under various ranges of parameters, which influence the architecture of the computer communication networks and which are important for practical use. Research limitations/implications ? The rapid rate of growth of computer-based communication systems (e.g. distributed computer networks, mobile data networks) has resulted in a renewed and intensive interest in this area. Efficient design of their service facilities leads to the sharing of resources among users. Such public shared networks are largely oversubscribed by independent users, which make random demands on the network resources. The optimal resource allocation to satisfy such demands and the proper settlement of contention when demands exceed the capacity of the resources, constitute the problem of being able to understand and to predict system behaviour. Originality/value ? To behaviour analysis we can use both analytical and simulation methods. Modelling and simulation are methods, which are commonly used by performance analysts to represent constraints and optimise performance. Principally the application of analytical queuing theory results belongs to the preferred method in comparison to the simulation method, because of their ability to analyse also very large networks. [ABSTRACT FROM AUTHOR]