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In this chapter, the authors explore collective entrepreneurship through the lens of how public entrepreneurship boosts collective action towards a common good. The role of public entrepreneurs and the collaborative nature of innovation community members evidence a collective action that pursues a socio-political change. Through a case study contextualized during the COVID-19 pandemic crisis in Spain, the authors explore how a public entrepreneur triggered a collective action that led to the creation of the innovation community: The Coronavirus makers. This collaborative network groups more than 20,000 researchers, developers, and engineers. They altruistically put their knowledge and resources at the service of the community to provide solutions for one of the healthcare system’s main problems at that time – the shortage of medical supplies to cope with the increasing number of COVID-19 cases. The collective action of the Coronavirus makers has impacted the health and wellbeing fields, the community and the values that should define social change and allow the construction of a more open, equitable and sustainable society. Potentially, our findings confirm that collective entrepreneurship derives from a function of collective action.

The objective of this systematic literature review (SLR) is to explore the current state of research in the field of household finance (HF). This study aims to summarize the existing research to highlight the importance of household finance in a nation’s economy. By exploring all conceptual and applied implications of HF, this study projects directions for future research to develop a comprehensive understanding of the subject.

This SLR is based on 112 articles published in peer-reviewed journals between 2006 and 2020 (Table 3). The methodology comprises five steps, namely, formulation of research questions, identification of studies, their selection and evaluation, analyses and syntheses and presentation of results.

The findings of this study show that studies on HF are gradually increasing worldwide with the USA registering the highest number of published research on the topic during the period under scrutiny. Notwithstanding the increasing attention and research on HF, empirical research in emerging economies is lagging. Additionally, this study finds that HF structure presents a perfect setting to understand how households compose their financial portfolio, make financial decisions and what factors influence their decisions.

This study is an SLR – an accurate and accepted method of reviewing available literature on a selected subject. However, the selection of inclusion and exclusion criteria depends on the researchers’ rationale which might lead to research bias. This should be considered an inherent limitation of SLR.

By synthesizing the contents of extant literature, this study presents important insights into HF. This study underlines the most discussed topics in the domain and identifies potential investigation areas. This study gives the knowledge of leading articles, authors and journals and informs scholars and academicians about the areas that need further investigation by portraying the complete picture of the subject in a systematic manner. Further, this study highlights that households make suboptimal financial decisions that affect their financial well-being. To reduce the adverse impacts of these decisions, policymakers and financial institutions must take steps to improve households’ use of formal financial markets. Household decisions can be reformed by enhancing consumers’ knowledge about financial products and services. Furthermore, households can be served better by offering customization in traditional financial products.

This study synthesizes the main findings of selected literature on HF. The expansion of studies on HF has generated the need to review the existing literature in a systematic manner. To the researchers’ best knowledge, this SLR is the first thorough study of available articles in the HF domain. This study presents the scope of future research by highlighting numerous aspects and functions of HF.

The purpose of this article is to treat the nonlinear optimal control problem in EV traction systems which are based on 5-phase induction motors. Five-phase permanent magnet synchronous motors and five-phase asynchronous induction motors (IMs) are among the types of multiphase motors one can consider for the traction system of electric vehicles (EVs). By distributing the required power in a large number of phases, the power load of each individual phase is reduced. The cumulative rates of power in multiphase machines can be raised without stressing the connected converters. Multiphase motors are also fault tolerant because such machines remain functional even if failures affect certain phases.

A novel nonlinear optimal control approach has been developed for five-phase IMs. The dynamic model of the five-phase IM undergoes approximate linearization using Taylor series expansion and the computation of the associated Jacobian matrices. The linearization takes place at each sampling instance. For the linearized model of the motor, an H-infinity feedback controller is designed. This controller achieves the solution of the optimal control problem under model uncertainty and disturbances.

To select the feedback gains of the nonlinear optimal (H-infinity) controller, an algebraic Riccati equation has to be solved repetitively at each time-step of the control method. The global stability properties of the control loop are demonstrated through Lyapunov analysis. Under moderate conditions, the global asymptotic stability properties of the control scheme are proven. The proposed nonlinear optimal control method achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs.

Comparing to other nonlinear control methods that one could have considered for five-phase IMs, the presented nonlinear optimal (H-infinity) control approach avoids complicated state-space model transformations, is of proven global stability and its use does not require the model of the motor to be brought into a specific state-space form. The nonlinear optimal control method has clear implementation stages and moderate computational effort.

In the transportation sector, there is progressive transition to EVs. The use of five-phase IMs in EVs exhibits specific advantages, by achieving a more balanced distribution of power in the multiple phases of the motor and by providing fault tolerance. The study’s nonlinear optimal control method for five-phase IMs enables high performance for such motors and their efficient use in the traction system of EVs.

Nonlinear optimal control for five-phase IMs supports the deployment of their use in EVs. Therefore, it contributes to the net-zero objective that aims at eliminating the emission of harmful exhaust gases coming from human activities. Most known manufacturers of vehicles have shifted to the production of all-electric cars. The study’s findings can optimize the traction system of EVs thus also contributing to the growth of the EV industry.

The proposed nonlinear optimal control method is novel comparing to past attempts for solving the optimal control problem for nonlinear dynamical systems. It uses a novel approach for selecting the linearization points and a new Riccati equation for computing the feedback gains of the controller. The nonlinear optimal control method is applicable to a wider class of dynamical systems than approaches based on the solution of state-dependent Riccati equations.

The purpose of this paper is to prevent the destruction of other parts of a wind energy conversion system because of faults, the diagnosis of insulated-gate bipolar transistor (IGBT) faults has become an essential topic of study. Demand for sustainable energy sources has been prompted by rising environmental pollution and energy requirements. Renewable energy has been identified as a viable substitute for conventional fossil fuel energy generation. Because of its rapid installation time and adaptable expenditure for construction scale, wind energy has emerged as a great energy resource. Power converter failure is particularly significant for the reliable operation of wind power conversion systems because it not only has a high yearly fault rate but also a prolonged downtime. The power converters will continue to operate even after the failure, especially the open-circuit fault, endangering their other parts and impairing their functionality.

The most widely used signal processing methods for locating open-switch faults in power devices are the short-time Fourier transform and wavelet transform (WT) – based on time–frequency analysis. To increase their effectiveness, these methods necessitate the intensive use of computational resources. This study suggests a fault detection technique using empirical mode decomposition (EMD) that examines the phase currents from a power inverter. Furthermore, the intrinsic mode function’s relative energy entropy (REE) and simple logical operations are used to locate IGBT open switch failures.

The presented scheme successfully locates and detects 21 various classes of IGBT faults that could arise in a two-level three-phase voltage source inverter (VSI). To verify the efficacy of the proposed fault diagnosis (FD) scheme, the test is performed under various operating conditions of the power converter and induction motor load. The proposed method outperforms existing FD schemes in the literature in terms of fault coverage and robustness.

This study introduces an EMD–IMF–REE-based FD method for VSIs in wind turbine systems, which enhances the effectiveness and robustness of the FD method.

This study examines how professional technicians' teaching styles and students' learning readiness affect cooking skills performance in culinary inheritance.

This study constructed a learning performance model from the situated cognition perspective using a sample of students at universities and vocational colleges on a professional technician course. A total of 4,000 questionnaires were mailed to students, of which 2,018 were returned.

Students regard technical professors as teaching experts and expect them to care for their learning, while professional technicians' knowledge sharing significantly increases students' learning performance. The findings provide insight into professional technicians' teaching styles for academics.

This study focuses on the situated cognition perspective and its correlation with students' learning performance and discusses professional technicians' knowledge sharing as an important influencing factor.

Five-level rectifiers have received widespread attention because of their excellent performance in high-voltage and high-power applications. Taking a five-level rectifier with only four-IGBT for this study, a sliding mode predictive control (SMPC) algorithm is proposed to solve the problem of poor dynamic performance and poor anti-disturbance ability under the traditional model predictive control with the PI outer loop.

First, mathematical models under the two-phase stationary coordinate system and two-phase synchronous rotating coordinate system are established. Then, the design of the outer-loop sliding mode controller is completed by establishing the sliding mode surface and design approach rate. The design of the inner-loop model predictive controller was completed by discretizing the mathematical model equations. The modulation part uses a space vector modulation technique to generate the PWM wave.

The sliding mode predictive control strategy is compared with the control strategy with a PI outer loop and a model predictive inner loop. The proposed control strategy has a faster dynamic response and stronger anti-interference ability.

For the five-level rectifier, the advantages of fast dynamic influence and parameter insensitivity of sliding mode control are used in the voltage outer loop to replace the traditional PI control, and which is integrated with the model predictive control used in the current inner loop to form a novel control strategy with a faster dynamic response and stronger immunity to disturbances. This novel strategy is called sliding mode predictive control (SMC).

COVID-19 has accelerated the shift to remote work. Enabling knowledge workers to do their jobs from home or elsewhere brings benefits by increasing labour participation, avoiding unproductive commuting time (thus reducing the carbon footprint), and reducing the gender gap by enabling a partner with domestic care responsibilities to work. Not all jobs are suitable for remote work, but far more remote work is feasible than has been typical to date. The post-pandemic new normal is sure to differ both from the pre-pandemic normal and from current arrangements. Hybrid arrangements where part of the week is spent at the office, and a part at home, might well become the norm. Employers, workers, trade unions, and governments will need to adapt to the new normal.

In this paper, I explore what shapes the identities of digital nomads (DNs), a class of remote workers who travel and work concurrently. Through extensive fieldwork and interviews with 50 digital nomads conducted in seven coworking hostels in Mexico in 2022, I construct a theory of DN identity. I base this upon the frequent transformations they undergo in their Circumstances, which regularly change their worker identity.

DNs relinquish traditional social determinants of identity, such as nationality and religion. They define their personal identities by their passions and interests, which are influenced by the people they meet. DNs exist in inherently transitive social spaces and, without rigid social roles to fulfil, they represent themselves authentically. They form close relationships with other long-term travellers to combat loneliness and homesickness. Digital nomads define their worker identities around their location independence. This study shows that DNs value their nomadic lifestyle above promotions and financial gain. They define themselves by productivity and professionalism to ensure the sustainability of their lifestyle. Furthermore, digital nomad coworking hubs serve focused, individual work, leaving workplace politics and strict ‘office image’ norms behind. Without fixed social and professional roles to play, digital nomads define themselves personally according to their ever-evolving passions and the sustainability of their nomadic life. Based on these findings, I present a cyclical framework for DN identity evolution which demonstrates how relational, logistical, and socio-personal flux evolves DN’s worker identities.

Positive experiences with working from home (WFH) during the Corona pandemic (COVID-19) have motivated many employees to continue WFH after the pandemic. However, factors influencing employees' WFH intentions against the backdrop of experiences during pandemic-induced enforced working from home (EWFH) are heterogeneous. This study investigates factors linked to information technology (IT) professionals' WFH intentions.

This mixed-methods study with 92 IT professionals examines the effects of seven predictors for IT professionals' WFH intentions. The predictors are categorized according to the trichotomy of (1) characteristics of the worker, (2) characteristics of the workspace and (3) the work context. Structural equation modeling is used to analyze the quantitative survey data. In addition, IT professionals' responses to six open questions in which they reflect on past experiences and envision future work are examined.

Quantitative results suggest that characteristics of the worker, such as segmentation preference, are influencing WFH intentions stronger than characteristics of the workspace or the work context. Furthermore, perceived productivity during EWFH and gender significantly predict WFH intentions. Contextualizing these quantitative insights, the qualitative data provides a rich yet heterogeneous list of factors why IT professionals prefer (not) to work from home.

Reasons influencing WFH intentions vary due to individual preferences and constraints. Therefore, a differentiated organizational approach is recommended for designing future work arrangements. In addition, the findings suggest that team contracts to formalize working patterns, e.g. to agree on the needed number of physical meetings, can be helpful levers to reduce the complexity of future work that is most likely a mix of WFH and office arrangements.

This study extends literature reflecting on COVID-19-induced changes, specifically the emerging debate about why employees want to continue WFH. It is crucial for researchers and practitioners to understand which factors influence IT professionals' WFH intentions and how they impact the design and implementation of future hybrid work arrangements.

The authors analyzed the evolution of working from home (WFH) within industries in 12 European countries in the period 2008–2017 and studied its relationship with information and communication technologies (ICT).

The authors used data from the European Union Labour Force Survey (EU-LFS) to document the trends and levels of WFH within industries in 12 European countries. The authors further used the EU-KLEMS database and a difference-in-difference approach to study whether the fall in prices of ICT is associated with a higher share of employees who work from home in industries that depend more on ICT relative to industries that depend less.

The authors show that WFH has increased almost everywhere and that there is significant heterogeneity across industries. The authors provide evidence that the fall in prices of ICT is associated with a higher share of employees who work from home in industries that depend more on ICT relative to industries that depend less. This result also holds within age, gender and occupation groups. While the authors find no significant differences among gender and occupation groups, the positive association between the fall in ICT prices and WFH increases with age.

This paper has two main contributions: First, it reports that WFH has increased in European countries in the period 2008–2017. Second, it provides new explorations about the relationship between ICT and WFH by using the price variation of ICT.