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Problem 1 of the International Workshops for Eddy Current Code Comparison is a hollow cylinder with axis perpendicular to a uniform field. A total of 17 solutions are described and compared with experimental results. Many kinds of codes, both two‐ and three‐dimensional, were found to give satisfactory solutions.

The nature of technologies that are recognised as Artificial Intelligence (AI) has continually changed over time to be something more advanced than other technologies. Despite the fluidity of understanding of AI, the most common theme that has stuck with AI is ‘human-like decision making’. Advancements in processing power, coupled with big data technologies, gave rise to highly accurate prediction algorithms. Analytical techniques which use multi-layered neural networks such as machine learning and deep learning have emerged as the drivers of these AI-based applications. Due to easy access and growing information workforce, these algorithms are extensively used in a plethora of industries ranging from healthcare, transportation, finance, legal systems, to even military. AI-tools have the potential to transform industries and societies through automation. Conversely, the undesirable or negative consequences of AI-tools have harmed their respective organisations in social, financial and legal spheres. As the use of these algorithms propagates in the industry, the AI-based decisions have the potential to affect large portions of the population, sometimes involving vulnerable groups in society. This chapter presents an overview of AI’s use in organisations by discussing the following: first, it discusses the core components of AI. Second, the chapter discusses common goals organisations can achieve with AI. Third, it examines different types of AI. Fourth, it discusses unintended consequences that may take place in organisations due to the use of AI. Fifth, it discusses vulnerabilities that may arise from AI systems. Lastly, this chapter offers some recommendations for industries to consider regarding the development and implementation of AI systems.

The aim of the paper is to investigate the impacts of simplifications of a reduced-order simulation model of squirrel cage induction machines (SCIMs) by numerical experiments.

Design of setups to isolate the main influences on the results of the reduced-order model of SCIMs. Results of time-stepping finite element calculations are used as benchmark.

Whereas neglecting eddy current effects and the assumption of a sinusoidal rotor current distribution leads to acceptable deviations in regular inverter operation, the sampling and interpolation of the machine parameters in a two-axis coordinate system considerably deteriorate the model accuracy. Using a polar coordinate system for this purpose is expected to significantly improve the model quality.

Preparing the ground for a successful, both fast and accurate simulation model of SCIMs as parts of electrified drivetrains.

While the phenomenon of technostress has received significant attention from researchers in recent years, empirical findings concerning the consequences of specific forms of techno-stressors have remained scattered and contradictory. The authors aim to integrate the conclusions of previous studies to understand the effects of specific techno-stressors on strain and job performance.

This study employs meta-analytic techniques to calibrate the findings of 67 studies investigating more than 63,100 employees.

In general, not all techno-stressors have adverse effects. In particular, techno-uncertainty does not impact job performance. In addition, relative weight analyses reveal the relative importance of techno-complexity and techno-insecurity as predictors of both strain and job performance. Finally, this study finds that the effects of specific techno-stressors on job performance vary depending on research participants' gender, educational attainment and employment status.

First, this study provides a more nuanced view of the effects of specific techno-stressors. Second, this research clarifies the relative importance of specific techno-stressors as predictors of strain and job performance. Finally, this study reveals the moderating effects of demographic variables on the relationships between specific techno-stressors and job performance.

This study focuses on unintended negative consequences of IT, called technostress. Given that employees are recognized as a major information security threat, it makes sense to investigate how technostress resulting from employees' constant interaction with IT influences the likelihood of security incidents. Although past research studied the concept of security-related technostress, the effect of IT use itself on employees’ extra-role activities such as security-related behaviors is unanswered. Thus, this paper aims to provide an understanding of the negative impact of technostress on employee information security policy (ISP) compliance.

Drawing on technostress literature, this research develops a research model that investigates the effect of technostress on employee intention to violate ISPs. It also extends the dimensionality of technostress construct by adding a new dimension called “techno-unreliability” that shows promising results. The authors use online survey data from a sample of 356 employees who have technology-based professions. We apply the structural equation modeling technique to evaluate the proposed research model.

Findings showed that IT use imposes high-level perceptions of a set of technostress creators, which makes users rationalize their ISP violations and engage in non-compliant behaviors. Further analysis of each dimension of technostress showed that techno-complexity, techno-invasion and techno-insecurity account for higher ISP non-compliant behaviors.

This study provides a new understanding of technostress to the context of information security and emphasizes on its negative impact on employee ISP compliance behaviors.

Since the emergence of the Internet in the twentieth century and the rapid growth of different types of information technologies (IT), our lives, either personal or professional, have become digitised. Adoption and diffusion of IT enhance individuals and organisational performance, yet scholars discovered a dual nature of IT in which IT usage may have negative aspects too. First, the inability to cope with IT in a healthy manner creates stress in users, termed technostress. Second, digitisation and adoption of new technologies (e.g. IoT and multi-cloud environments) have increased vulnerabilities to information security (InfoSec) threats. Although organisations utilise counteraction strategies (e.g., security systems, security policies), end-users remain the top source of security incidents. Existing behavioural research has approached technostress and InfoSec independently. However, it is not clear how technology-stressors influence employees’ security-related behaviours. This chapter reviews the interaction effect of these concepts in detail by proposing a conceptual model that explains that technostress is the main reason for employees’ non-compliance with security policies in which users with high-level perceptions of technostress are more likely to violate InfoSec policies. Counteraction strategies to mitigate technostress and security threats are also discussed.

The authors argue that the current studies about malicious insiders confuse the fact that malicious attacks belong to two different categories, namely, those that launch instrumental attacks and expressive attacks. The authors collect malicious insider data from publicly available sources and use text-mining techniques to analyze the association between malicious insiders’ characteristics and the different types of attack.

The authors investigated the relationship between personality characteristics and different types of malicious attacks. For the personality characteristics, the authors use the same method as Liang et al. (2016), which extracted these characteristics based on a keyword-characteristic dictionary. For different types of malicious attacks, two raters rated each case based on criteria modified from criminology research to determine the degree of expressiveness and instrumentality.

The results show that malicious insiders who are manipulative or seeking personal gain tend to carry out instrumental attacks. Malicious insiders who are arrogant tend to conduct expressive attacks.

This study uses third party articles to identify the personality characteristics of known malicious insiders. As such, not all personality characteristics may have been reported. Data availability was an issue.

Understanding if different personality characteristics lead different types of attacks can help managers identify employees who exhibit them and mitigate an attack before it occurs.

Malicious insider attacks can have devastating results on businesses and employees. Help to identify potential malicious insiders before they act, may prevent undue harm.

This study used 132 cases of none malicious insiders to examine their attack objectives. No other study that the authors know of used that many cases.

The study of deception and the theories, which have been developed have relied heavily on laboratory experiments in controlled environments, using American college students participating in mock scenarios. The purpose of this paper is to validate previous deception detection research in a real-world, high stakes environment where the unit of analysis is the question–response pair.

The study used previously confirmed linguistic and paralinguistic speech cues and the constructs of deception in an attempt to validate a leading deception theory, interpersonal deception theory (IDT). A combination of descriptive and predictive analysis was conducted to best understand the relationship between speech cues and changes in the subjects’ behavior.

The result validates IDT with mixed results on individual measures and their constructs. However, there is clear evidence across the 711 question-response pairs that not only was it possible to differentiate truth from deceptive behavior but also patterns of behavior can be seen over time.

Because of the real-world nature of the study, it is difficult to generalize the results to a larger population. However, one implication for future research is the development of methods to capture, process and prepare raw speech into data ready for analysis.

This paper attempts to fill the gap between the controlled mock scenarios and the harsh reality of real-world deception.

The purpose of this paper is to investigate the work practices of network security professionals and to propose a new and robust work practices model of these professionals.

The proposed work practices model is composed by combining the findings of ten notable empirical studies performed so far this century. The proposed model was then validated by an online survey of 125 network security professionals with a wide demographic spread.

The empirical data collected from the survey of network security professionals strongly validate the proposed work practices model. The results also highlight interesting trends for different groups of network security professionals, with respect to performing different security-related activities.

Further studies could investigate more closely the links and dependencies between the different activities of the proposed work practices model and tools used by network security professionals to perform these activities.

A robust work practices model of network security professionals could hugely assist tool developers in designing usable tools for network security management.

This paper proposes a new work practices model of network security professionals, which is built by consolidating existing empirical evidence and validated by conducting a survey of network security professionals. The findings enhance the understanding of tool developers about the day-to-day activities of network security professionals, consequently assisting developers in designing better tools for network security management.

The purpose of this study is to demystify the authenticity dimensions of wine experience with the locally guided tour in the meal-sharing economy, drawing on travellers' online reviews at Withlocals for French locally guided wine tours.

The qualitative research approach was performed through the thematic analysis of 940 online reviews from Withlocals. The coding phase was completed based on a three-step coding process (i.e. open, axial and selective coding), as all reviews that were gathered were related to locally guided wine tours rather than only wine-sharing activities.

The findings of this study demonstrated four interrelated authenticity dimensions: the taste of terroir, local atmosphere, oenological knowledge and local insight. The results of this study also notably showed that all reviews were primarily positive; travellers expressed their satisfaction with wine tours at Withlocals and often mentioned their re-purchase intentions as well as advising wine tours in the meal-sharing economy.

Several worthy theoretical and practical implications were discussed for local tour guides to improve their tour quality more authentically. The results also demonstrate that locally guided wine tours in the meal-sharing economy were regarded as a multidimensional activity that provides a better discovery of a wine destination.

Despite the large volume of generic meal-sharing economy experience studies, the authenticity experience of the locally guided wine tours has been surprisingly omitted by scholars. Therefore, this study contributes to the sharing economy literature through wine experience by addressing the authenticity dimensions of the locally guided wine tours in the meal-sharing economy.