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Autonomous technologies represent an increasingly important, but at the same time controversial technological field with enormous potential. From a consumer perspective, however, the growing autonomy of technologies might result in a perceived loss of control, which can lead to consumer resistance. Given the practical and theoretical relevance, this research examines antecedents to consumer adoption of autonomous technologies in the context of self-driving cars.

This article looks through the lens of the technology acceptance model and conducts structural equation modeling.

The study validates the positive effect of perceived usefulness on behavioral intention to adopt self-driving cars. The results further suggest that individuals with a generally negative attitude toward technologies are afraid that they might not be capable of handling the new technology. Moreover, further mediation analyses reveal that perceived ease of use and perceived usefulness help us to explain the indirect effects of novelty seeking and technology anxiety on adoption intention.

The results imply that users' perceptions of an autonomous technology's usefulness are an important determinant of technology adoption. Adoption barriers could be overcome by emphasizing the usability of the new technology. On the other hand, individuals who enjoy using the old technology may be persuaded by arguments that focus on the usefulness of the new technology rather than its ease of use.

Self-driving automobiles will change our perception of mobility. It is important to understand the mechanisms that drive the adoption of such innovations.

This article reports the results from a panel discussion held at the 2019 European Conference on Information Systems (ECIS) on the use of technology-based autonomous agents in collaborative work.

The panelists (Drs Izak Benbasat, Paul Benjamin Lowry, Stefan Morana, and Stefan Seidel) presented ideas related to affective and cognitive implications of using autonomous technology-based agents in terms of (1) emotional connection with these agents, (2) decision-making, and (3) knowledge and learning in settings with autonomous agents. These ideas provided the basis for a moderated panel discussion (the moderators were Drs Isabella Seeber and Lena Waizenegger), during which the initial position statements were elaborated on and additional issues were raised.

Through the discussion, a set of additional issues were identified. These issues related to (1) the design of autonomous technology-based agents in terms of human–machine workplace configurations, as well as transparency and explainability, and (2) the unintended consequences of using autonomous technology-based agents in terms of de-evolution of social interaction, prioritization of machine teammates, psychological health, and biased algorithms.

Key issues related to the affective and cognitive implications of using autonomous technology-based agents, design issues, and unintended consequences highlight key contemporary research challenges that allow researchers in this area to leverage compelling questions that can guide further research in this field.

Decentralised autonomous organisations (DAOs) are internet-native self-governing enterprises where individual groups, communities, agencies, consumers and providers work together using blockchain-led smart contracts (SCs). This study aims to examine the role of DAO marketplaces in technology-led autonomous organisation design for enterprise technology sourcing industries, with algorithmic trust and governance.

The authors examined the importance of an enterprise marketplace governance platform for technology sourcing using DAO as a decentralised/democratised business model. A total of 98 DAO products/services are evaluated across 11 industries that envisage DAO as a strategic choice for the governance of decentralised marketplace platforms.

The research findings validate how a DAO-led enterprise marketplace governance platform can create a cohesive collaboration between consumers (enterprises) and providers (solution vendors) in a disintermediated way. The proposed novel layered solution for an autonomous governance-led enterprise marketplace promises algorithmic trust-led, self-governed tactical alternatives to a strategic plan.

The research targets multiple industry outlooks to understand decentralised autonomous marketplace governance and develop the theoretical foundation for research and extensive corporate suitability.

The research underpinnings boost the entrepreneurs’ ability to realise the practical potential of DAO between multiple parties using SCs and tokenise the entire product and service offerings over immutable ledger technologies.

To the best of the authors’ knowledge, this research is unique and the first of its kind to study the multi-industry role of algorithmic trust and governance in enterprise technology sourcing marketplaces driven by 98 decentralised and consensus-based DAO products across 11 industries.

Unprecedented endeavors have been made to take autonomous trucks to the open road. This study aims to provide relevant information on autonomous truck technology and to help logistics managers gain insight into assessing optimal shipment sizes for autonomous trucks.

Empirical data of estimated autonomous truck costs are collected to help revise classic, conceptual models of assessing optimal shipment sizes. Numerical experiments are conducted to illustrate the optimal shipment size when varying the autonomous truck technology cost and transportation lead time reduction.

Autonomous truck technology can cost as much as 70% of the price of a truck. Logistics managers using classic models that disregard the additional cost could underestimate the optimal shipment size for autonomous trucks. This study also predicts the possibility of inventory centralization in the supply chain network.

The findings are based on information collected from trade articles and academic journals in the domain of logistics management. Other technical or engineering discussions on autonomous trucks are not included in the literature review.

Logistics managers must consider the latest cost information when deciding on shipment sizes of road freight for autonomous trucks. When the economies of scale in autonomous technology prevail, the classic economic order quantity solution might again suffice as a good approximation for optimal shipment size.

This study shows that some models in the literature might no longer be applicable after the introduction of autonomous trucks. We also develop a new cost expression that is a function of the lead time reduction by adopting autonomous trucks.

The purpose of this paper is to inform researchers who are examining the adoption of autonomous vehicle technology and to provide marketing insights for developers and manufacturers of such vehicles and their ancillary technologies.

This study assesses consumer attitudes and behavioral intentions regarding autonomous vehicles (AV) by applying the consumer version of the unified theory of acceptance and use of technology (UTAUT2). We validate the model through a behavioral research study (n = 1,154).

The findings suggest that attitude toward AV is primarily formed through performance expectancy, effort expectancy, social influence and hedonic motivation. Furthermore, the level of autonomy has limited effects on attitude.

This is the first study to examine attitudes toward AV through the theoretical lens of UTAUT2. Additionally, this study provides insights into consumer perceptions and the corresponding effects on attitude by moderating the level of autonomy.

There are ethical, legal, social and economic arguments surrounding the subject of autonomous vehicles. This paper aims to discuss some of the arguments to communicate one of the current issues in the rising field of artificial intelligence.

Making use of widely available literature that the author has read and summarised showcasing her viewpoints, the author shows that technology is progressing every day. Artificial intelligence and machine learning are at the forefront of technological advancement today. The manufacture and innovation of new machines have revolutionised our lives and resulted in a world where we are becoming increasingly dependent on artificial intelligence.

Technology might appear to be getting out of hand, but it can be effectively used to transform lives and convenience.

From robotics to autonomous vehicles, countless technologies have and will continue to make the lives of individuals much easier. But, with these advancements also comes something called “future shock”.

Future shock is the state of being unable to keep up with rapid social or technological change. As a result, the topic of artificial intelligence, and thus autonomous cars, is highly debated.

The study will be of interest to researchers, academics and the public in general. It will encourage further thinking.

This is an original piece of writing informed by reading several current pieces. The study has not been submitted elsewhere.

This study, a research project, aims to examine the distinct characteristics of the Fourth Industrial Revolution (4IR), with a focus on construction. Following this examination, the paper presents a field study to evaluate the impact of the 4IR on the construction process.

The first half of this project is dedicated to defining the 4IR by reviewing existing literature. The other half of the project presents a case study to demonstrate the concept of the 4IR and measure the effect of its application. To validate the defined concept of the 4IR, the study focuses on the following: autonomous system for producing drawings and robotics in construction.

The intensive literature review revealed three unequivocal features of the 4IR: defined tasks, undefined tasks and improvement possibilities. The following case study showed that the incorporation of the three 4IR features resulted in improved productivity and efficiency during the construction of the podium for the Lotte World Tower. For example, the macro-based autonomous system achieved 5.52 shop drawings per hour, highlighting the potential impact of independent, autonomous machinery.

The originality of this project stems from its attempt to quantify the effectiveness of applying autonomous technologies to a practical project. While previous works in this field have focused on system development and improvement, this paper presents an autonomous system at work in an actual project, in which junior engineers were able to be entirely replaced. The system was successful in independently creating numerous required shop drawings. The value of this analysis is to generate scientific evidence to evaluate the efficacy of the adoption of 4IR-oriented technologies.

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.

The authors provide new quantitative evidence of the relationship between technologies and organizational design in the context of complex one-off products. The systems that produce complex, one-off products in mature, fragmented industries such as construction lack many of the typical organizational features that researchers have deemed critical to product development success (e.g., team familiarity, frequent communication, and strong leadership). In contrast, the complexity of these products requires a diverse knowledge base that is rarely found within a single firm. The one-off nature of construction’s products further requires improvization and development by a distributed network of highly specialized teams. And because the product is complex, significant innovations in the end product require systemic shifts in the product architecture. Riitta Katila, Raymond E. Levitt and Dana Sheffer use an original, hand-collected dataset of the design and construction of 112 energy-efficient “green” buildings in the United States, combined with in-depth fieldwork, to study these questions. A key conclusion is that the mature US construction industry, with its particularly fragmented supply chain, is not well suited to implementing “systemic innovations” that require coordination across trades or stages of the project. However, project integration across specialists with the highest levels of interdependence (i.e., craft, contract integration) mitigates the knowledge and coordination problems. There are implications for research on how technology shapes organizations (and particularly how organizations shape technology), and on the supply chain configuration strategies of firms in the construction industry as well as building owners who are seeking to build the best buildings possible within their budgets.