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The purpose of this research is to achieve multi-task autonomous driving by adjusting the network architecture of the model. Meanwhile, after achieving multi-task autonomous driving, the authors found that the trained neural network model performs poorly in untrained scenarios. Therefore, the authors proposed to improve the transfer efficiency of the model for new scenarios through transfer learning.

First, the authors achieved multi-task autonomous driving by training a model combining convolutional neural network and different structured long short-term memory (LSTM) layers. Second, the authors achieved fast transfer of neural network models in new scenarios by cross-model transfer learning. Finally, the authors combined data collection and data labeling to improve the efficiency of deep learning. Furthermore, the authors verified that the model has good robustness through light and shadow test.

This research achieved road tracking, real-time acceleration–deceleration, obstacle avoidance and left/right sign recognition. The model proposed by the authors (UniBiCLSTM) outperforms the existing models tested with model cars in terms of autonomous driving performance. Furthermore, the CMTL-UniBiCL-RL model trained by the authors through cross-model transfer learning improves the efficiency of model adaptation to new scenarios. Meanwhile, this research proposed an automatic data annotation method, which can save 1/4 of the time for deep learning.

This research provided novel solutions in the achievement of multi-task autonomous driving and neural network model scenario for transfer learning. The experiment was achieved on a single camera with an embedded chip and a scale model car, which is expected to simplify the hardware for autonomous driving.

Until recently, only relatively few Northern European companies had organized their operations by use of autonomous work groups, although the first literature on this subject stems from the 1950s. Yet this seems to be changing. From recent publications and the author′s experience it appears that the diffusion of autonomous work groups is increasing relatively suddenly. A survey among eight cases in six companies (two Dutch, four Swedish) shows that recent changes in the marketplace and in available technology are the main reasons why this increase has taken place and why, according to the companies, this is the very moment to start using autonomous work groups. On the one hand these changes enable the companies to introduce autonomous work groups, while on the other these changes force companies to do so.

We examine how input- (vs. output-) based performance evaluation and incentive intensity impact employees’ autonomous motivation, thereby influence their proactive work behaviors.

We collected survey responses from 309 employees of different firms. Multi-group Structural Equation Modeling analyses were used to analyze the data.

Input-based evaluation had a positive effect on autonomous motivation and proactive work behaviors when task uncertainty was high, but a negative effect when it was low. Autonomous motivation had a positive effect on proactive work behaviors.

Our results on the moderating effect of task uncertainty provide insights into inconsistencies in earlier studies. Moreover, applying self-determination theory of motivation to incentive research can provide some insights into why sometimes, incentives can negatively affect performance.

The study of proactive work behaviors is important because despite their necessity in the fast-changing business environment, they are relatively unexplored in the incentive literature. Proactivity is especially important for tasks that are high in uncertainty because the exact tasks to achieve those goals are hard to specify.

We investigate the effect of performance management system on proactive work behaviors, mediated by autonomous motivation and moderated by task uncertainty.

This paper is dedicated to the topic of the emerging challenges of traditional criminal law as posed by the development of modern technology. In certain parts of the world, the automotive industry has already implemented a new generation of autonomous self-driving vehicles. Moreover, there have been incidents where such vehicles have been involved in traffic accidents with deadly consequences. The use of autonomous intelligence is also emerging in other important sectors, such as in medicine and the military.

The issue of the legal liability of autonomous machines has been the subject of numerous philosophical debates and approached from the perspective of tort law. The question of criminal liability, however, has still not been debated more comprehensively. In this text, I will analyze the scope and limits of criminal liability of humans for criminal offenses “committed” by autonomous systems. Firstly, I will describe potential crimes of AI in context of intent and negligence. Secondly, I will propose the new concept of (shared) criminal liability, the concept I will name the Division of Labor theory.

The purpose of this research paper is to recover the autonomous flight performance of a mini unmanned aerial vehicle (UAV) via stochastically optimizing the wing over certain parameters (i.e. wing taper ratio and wing aspect ratio) while there are lower and upper constraints on these redesign parameters.

A mini UAV is produced in the Iskenderun Technical University (ISTE) Unmanned Aerial Vehicle Laboratory. Its complete wing can vary passively before the flight with respect to the result of the stochastic redesign of the wing while maximizing autonomous flight performance. Flight control system (FCS) parameters (i.e. gains of longitudinal and lateral proportional-integral-derivative controllers) and wing redesign parameters mentioned before are simultaneously designed to maximize autonomous flight performance index using a certain stochastic optimization strategy named as simultaneous perturbation stochastic approximation (SPSA). Found results are used while composing UAV flight simulations.

Using stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV over previously mentioned wing parameters and FCS, it obtained a maximum UAV autonomous flight performance.

Permission of the directorate general of civil aviation in the Republic of Türkiye is essential for real-time UAV autonomous flights.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach is very useful for improving any mini UAV autonomous flight performance cost index.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach succeeds confidence, highly improved autonomous flight performance cost index and easy service demands of mini UAV operators.

Creating a new approach to recover autonomous flight performance cost index (e.g. satisfying less settling time and less rise time, less overshoot during flight trajectory tracking) of a mini UAV and composing a novel procedure performing simultaneous mini UAV having passively morphing wing over certain parameters while there are upper and lower constraints and FCS design idea.

Connecting autonomous drones to ground operations and services is a prerequisite for the adoption of scalable and sustainable drone services in the built environment. Despite the rapid advance in the field of autonomous drones, the development of ground infrastructure has received less attention. Contemporary airport design offers potential solutions for the infrastructure serving autonomous drone services. To that end, this paper aims to construct a framework for connecting air and ground operations for autonomous drone services. Furthermore, the paper defines the minimum facilities needed to support unmanned aerial vehicles for autonomous logistics and the collection of aerial data.

The paper reviews the state-of-the-art in airport design literature as the basis for analysing the guidelines of manned aviation applicable to the development of ground infrastructure for autonomous drone services. Socio-technical system analysis was used for identifying the service needs of drones.

The key findings are functional modularity based on the principles of airport design applies to micro-airports and modular service functions can be connected efficiently with an autonomous ground handling system in a sustainable manner addressing the concerns on maintenance, reliability and lifecycle.

As the study was limited to the airport design literature findings, the evolution of solutions may provide features supporting deviating approaches. The role of autonomy and cloud-based service processes are quintessentially different from the conventional airport design and are likely to impact real-life solutions as the area of future research.

The findings of this study provided a framework for establishing the connection between the airside and the landside for the operations of autonomous aerial services. The lack of such framework and ground infrastructure has hindered the large-scale adoption and easy-to-use solutions for sustainable logistics and aerial data collection for decision-making in the built environment.

The evolution of future autonomous aerial services should be accessible to all users, “democratising” the use of drones. The data collected by drones should comply with the privacy-preserving use of the data. The proposed ground infrastructure can contribute to offloading, storing and handling aerial data to support drone services’ acceptability.

To the best of the authors’ knowledge, the paper describes the first design framework for creating a design concept for a modular and autonomous micro-airport system for unmanned aviation based on the applied functions of full-size conventional airports.

Drawing on organismic integration theory, we aim to examine whether the reasons independent contractors choose contract work are related to their on-the-job motivation and job satisfaction and whether their perceived support enhances positive (or buffers negative) effects.

We collected data at three separate time points from 241 adjunct instructors to test a moderated mediation model using bootstrapping analyses.

The positive relationship between pull factors (e.g. autonomy) and job satisfaction is fully mediated by the autonomous motivation contractors experienced at work. The inverse relationship between push factors (e.g. inability to secure desired work role) and job satisfaction is not mediated by autonomous nor controlled motivation experienced at work. Contractors' perceived organizational support does not moderate the relationship between either push or pull factors and autonomous motivation. Post hoc analysis shows a moderating effect of perceived supervisor support on the nonlinear relationship between push factors and autonomous motivation.

Recruiting individuals drawn to the benefits of contract work may have important implications for worker motivation, job satisfaction and potentially beyond. Moreover, organizations may consider whether existing support resources and infrastructure are appropriate for contractors.

Despite the abundance of evidence demonstrating the benefits of organizational and supervisor support among traditional employee populations, such support may be of limited value to those drawn to contract work.

Today, business model innovations leverage digital technologies to gain a competitive advantage and transform business processes. Blockchain is still gaining attention in specific fields and bringing value to business models. There is a dearth of research on how blockchain decentralized autonomous organizations impact organization business model innovations. This study attempts to contribute the body of knowledge based on a review of decentralized autonomous organizations and the business model innovation literature using the integrative and generative approach.

The paper offers an analysis of decentralized autonomous organizations based on digital business models built on the well-established work by Osterwalder and Pigneur (2010). The practical multilayered decentralized autonomous organizations architectural implementation model design is achieved using practical archetypes depicted in the proposed decentralized autonomous organizations business model. The paper evaluates a marketplace comprising 13 decentralized autonomous organizations led platforms with core functionalities.

The paper delivers decentralized autonomous organizations led digital business model canvas elements to explain decentralized autonomous organization business model innovations. It presents the underlying multilayered decentralized autonomous organizations architectural implementation model required to conceptualize a practical business model with an enterprise-ready target operating model.

The paper contributes directly to the practical decentralized autonomous organizations business model canvas, exemplifying the nine elements of decentralized autonomous organizations’ characteristics for any organizational transformation. The tools and accelerators (business model, layered architecture, target operating model and product mapping) developed in the paper address the managerial challenges of redesigning the decentralized business models.

The proposed decentralized autonomous organizations smart contract powered business model provide a digital platform to adhere to rules, follow policies, preserve principles and develop consensus without human interventions. The paper shapes the first of its kind decentralized autonomous organizations marketplace evaluation while mapping it to decentralized autonomous organizations layered architecture product requirement considering business model dimension to adopt actionable target operating model.

The purpose of this research is to examine the relationship between spiritual leadership and employee innovative behavior by testing the mediating role of autonomous motivation and the moderating role of employee power distance orientation.

The author predicted an indirect relationship between spiritual leadership and employee innovative behavior via autonomous motivation. Also, the author predicted the positive effect of spiritual leadership on employee innovative behavior will be stronger when employee power distance orientation is high. Hypotheses are tested with data gathered from 174 participants.

Results showed that spiritual leadership was positively related to employee innovative behavior via autonomous motivation. And, the positive relationship between spiritual leadership and autonomous motivation was stronger when employee power distance orientation was high. Furthermore, the indirect effect of autonomous motivation was stronger when employee power distance orientation was high.

This study provides a new theoretical perspective – self-determination theory – to test how and when spiritual leadership enhances employee innovative behavior by suggesting autonomous motivation as a mediator and employee power distance orientation as a boundary condition.

The results of this research provide suggestions for leaders to adopt spiritual leadership as well as enhance interactions between them and employees to increase employee innovative behavior.

This study highlights the moderating role of employee power distance orientation and uses self-determination theory to examine how and when spiritual leadership plays a positive role.

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.