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Drawing on the work of Niklas Luhmann, the paper argues that technology can be viewed as a self-referential system which is autonomous from both human beings and other function systems of society. The paper aims to develop a philosophy of technology from the work of Niklas Luhmann. To achieve this aim, it draws upon the systems-theory work of Jacques Ellul, a philosopher of technology who focuses on the autonomous potential of technological evolution.

The paper draws on the work of Niklas Luhmann and Jacques Ellul to explore the theme of autonomous technology and what this means for our thinking about technological issues in the twenty-first century. Insights from these two thinkers and researchers working in the Luhmannian sociological tradition are applied to remote work.

The sociological approach of Luhmann, coupled with Ellul's insights into the autonomous nature of technology, can help us develop a systems theory of technology which takes seriously its irreducibility to human functions.

The paper contributes to the growing sociological literature that thematizes the Luhmannian approach to technology, helping us better understand this phenomenon and think in new ways about what technological autonomy means.

The paper brings together the work of Luhmann, Ellul and contemporary researchers to advance a new understanding of technology and technological communication.

Digital transformation (DT) projects are complex and often unsuccessful. While researchers have suggested many guidelines and best practices on how to successfully roll out DT projects and how they are spread among a large number of scientific papers. The aim of this paper is to synthesize these guidelines into clear overviews.

A systematic literature review was conducted on both Scopus and Web of Science to search for papers suggesting DT guidelines or best practices. In total, 150 papers dealing with DT and guidelines were fully analyzed.

Eight main DT guidelines were found and each one was expanded with several best practices on how to implement these. The results are eight tables giving an overview of the commonly agreed-upon best practices for each DT guideline.

These overviews are useful for both researchers and practitioners, to guide future work and to be inspired respectively. This paper calls for more research on how these guidelines are followed in practice, how these differ per industry and what their impact is on the overall success of DT projects.

The synthesis of DT guidelines organized into an accessible format has not yet been conducted before, and can serve as a seminal pinpoint for future research.

Four reputed leaders for the coming years in the field of special education for individuals with emotional and behavioral disorders (EBD) each with a slightly different perspective on the field were asked to respond independently to a prompt asking what does special education mean for students with EBD and what is being done and how do we maintain tradition? The contributors' responses to the prompt are presented and then summarized across the essays. A remarkable consistency emerges across the independent essays. In addition to the tradition of providing a free and appropriate education in the least restrictive environment, the contributors identify needs to support teachers serving this population. Needs in teacher training and the expertise required to meet the needs of individuals with EBD are outlined as well as potential contributions of technology to carry out specific tasks. We conclude with a call for increased advocacy for use of the knowledge that we currently possess and that which will soon be discovered to support students with EBD as well as their teachers. We also note that the contributors' names are listed alphabetically to acknowledge the equality of each person to the final product.

Reservation of travel and leisure services through the digital environment has gained a growing role in society, influencing the revolution of the sector. It needs to be noted that there is a considerable lack of formal approaches to the identification of factors for the positive reception and use of these digital tools. For this reason, it is necessary to establish the main factors influencing the adoption and use of digital travel and restaurant platforms (TRPs), adding to the theoretical model two new factors: trust and word-of-mouth (WOM). This paper aims to discuss the aforementioned ideas.

A theoretical model has been proposed, based on the extended unified theory of acceptance and use of technology (UTAUT2). Data collection was conducted through an online survey, in which 331 responses were compiled. Data obtained were analysed using structural equation modelling (SEM) with AMOS v27 software.

The results show that performance expectancy and WOM have a significant impact on the adoption of TRPs. However, it was found that effort expectancy, social influence, facilitating conditions, trust and price/value are not significant variables.

This research confirms that WOM communication positively influences the use of TRPs, facilitating various aspects for restaurant customers, including reducing wait times, streamlining the ordering process for allergic and intolerant customers, enhancing loyalty programs, order management and the opportunity to provide a personalised experience.

This study is the first to incorporate WOM variable into the extended UTAUT2 model applied to TRPs. Through a literature review, it has paved the way for significant future research directions that have not been adequately addressed by the scientific community, including the adoption and usage of food delivery platforms and online review platforms, as well as the behaviour of disabled customers towards these platforms.

This chapter conceptualises a link between Industrial Revolution 4.0 (IR 4.0), big data, data science and sustainable tourism.

The author adopts a grounded theory and conceptual approach to endeavour in this exploratory research.

The outcome shows a significant rise of big data in the tourism sector under three major dimensions, i.e. business, governance and research. And, some exemplary evidence of institutions promoting the use of big data and data science for sustainable tourism has been discussed.

The conceptualised interlinkage of concepts like IR 4.0, big data, data science and sustainable development provides a valuable knowledge resource to policy-makers, researchers, businesses and students.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.