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The paper aims to provide a critical review of how variations in the conceptualization and contextualization of hate crime across US cities might impact how their individual law enforcement agencies collect hate crime data. Media reports and political discourses present hate crime as a prevalent problem in the USA. However, this representation of hate crime in the public sphere is not reflected in the relatively low national numbers of hate crimes published annually by the Federal Bureau of Investigation.

Drawing primarily on the national hate crime data for the period 2008–2018, this author conducted a secondary research study of the concept, context, extent and law enforcement collection of hate crime data in five cities in the USA.

This paper is a product of some of the findings of the study, which include the definition of hate crime at the federal, state and city levels and the contextualization of hate crimes at these levels. The findings show inconsistencies in how the five cities and associated law enforcement agencies conceptualize hate crime and in how they collect and report hate crime data at local and national levels.

Through its analysis of how five US cities and the associated law enforcement agencies interpret and respond to hate crime data collection, with recommendations of best practices for hate crime data collection by law enforcement agencies, the paper contributes to the academic and nonacademic debate on hate crime.

This study aims to examine the effectiveness of individual dynamic capabilities (DC) constructs and whether they had comparable effects on a company’s competitiveness in market turbulence (MT). This study used quantitative methods to determine how the DC elements, sensing, learning, integrating and coordinating, influenced competitiveness, with the moderating role of MT during a real-time crisis.

Survey data was gathered from 426 tourism small and medium-sized enterprises (TSMEs) in the United Arab Emirates and analyzed quantitatively.

The study found that not all DC constructs were equally important in promoting competitiveness. TSMEs’ survival depended more on sensing and integrating capabilities than learning and coordinating capabilities, and on how these capabilities were used by managers or owners of TSMEs. The study found no moderation effect of MT.

The generalizability of the results was hindered by the study’s focus on TSMEs in a single geographic location. The reasons for lack of proper mobilization of DCs constructs were not explored, but the data on the relative efficacy of DC constructs during a crisis significantly contributed to the literature.

This study emphasized ways that companies could improve firm competitiveness during a crisis by deploying DCs to optimize operations. The implications for research, practical aspects and limitations are presented and discussed.

The purpose of this paper is to introduce a double-stator switched reluctance machine (DS-SRM) for electric vehicles (EVs) and to propose multi-mode operations for this machine.

Analysis of flux linkage distributions and torque characteristics using finite element method (FEM). Building a dynamic simulation model based on electromagnetic characteristics, mathematical equations and mechanical motion equations of the DS-SRM drive system. The paper proposes multi-mode operations (inner-stator excitation mode, outer-stator excitation mode and double-stator excitation mode) based on motor working regions. It also conducts simulation and experimental results to verify the effectiveness of the proposed multi-mode operations strategies and control schemes.

There is almost no electromagnetic coupling between the inner and outer stators due to the specially designed rotor structure and optimized windings polarity configuration. Analysis of flux linkage distributions and torque characteristics verified the independence of inner and outer stators. Proposal of multi-mode operations and corresponding control rules achieved the smooth switching between different modes.

The paper introduced the DS-SRM for EVs and proposed multi-mode operations, along with control rules, to optimize its performance. The specially designed rotor structure, optimized winding polarity configuration, and the proposed multi-mode operations contribute to the originality of the research.

The integration of digital technologies into education has brought about a profound transformation, fundamentally reshaping the learning landscape. The purpose of this study is to underscore the importance of investigating the factors influencing students’ engagement (SE) in this evolving digital era, particularly within formal digital learning environments. To address this need, the study is grounded in self-determination theory (SDT) and presents a comprehensive model comprising interconnected elements: digital competence (DC), smartphone use (SPU), perceived autonomy (PA), digital formal learning (DFL) and SE.

The research conducted an investigation within Saudi Arabian universities, collecting a robust data set of 392 cases. This data set underwent rigorous analysis to validate the proposed model. To untangle the intricate relationships within the framework, the study used partial least squares structural equation modelling. Given the distinct dimensions of the two constructs under study, the researcher used a disjoint two-stage approach to establish reflective-formative higher-order constructs (HOC).

The findings revealed that digital literacy and digital skills (DS) constitute the foundational constituents of DC. Simultaneously, the study identified facilitation, distraction and connectedness as integral components of SPU. Importantly, the study established that DC, SPU, PA and DFL significantly influence SE. Furthermore, the research illuminated the mediating roles played by SPU, PA and DFL in the complex relationship between DC and SE.

This study advances the literature by delineating the dynamic interplay between DC, SPU and SE in digital learning. It extends SDT within educational contexts, emphasizing the role of internal motivations and DS. Methodologically, it innovates through reflective-formative HOCs, deepening the analysis of complex educational constructs. Managerially, it guides institutions in enhancing DC and integrating smartphones effectively into learning, advocating for tailored strategies to foster engaging and autonomous digital learning environments, thereby enriching both theoretical understanding and practical application in education.

With the emergence of big data analytics and the importance of analytics-driven decisions, the travel industry is swiftly jumping on and adopting the bandwagon. However, research in this domain is limited. Accordingly, the present research seeks to understand how big data analytics capabilities (BDAC) add value to tourism supply chains (TSCs) and can dynamic capabilities (DC) improve the triple bottom line.

Data from 218 valid responses were collected from different Indian tourism industry units. Confirmatory factor analysis (CFA) was applied to confirm the constructs, followed by partial least squares structural equation modelling (PLS-SEM) to check the mediating effect of DC on TSCs performance.

The findings show that BDAC significantly influence the performance of TSCs and that DC plays a critical role in strengthening the impact of BDAC on TSCs' economic performance. These results corroborate that DC plays a key moderating role.

This study contributes significantly to the tourism sector in India, where tourism is a key contributor to the country's gross domestic product. Theoretically, this study contributes to the resource-based view (RBV) and practically encourages professionals in the tourism sector to promote the use of BDAC to enhance the performance of TSCs.

The originality of the study is that it has tried to comprehend the moderating role of dynamic capabilities which impact BDAC to improve TSC performance.

The purpose of this study is to investigate the structural, surface roughness and corrosion properties of the zirconium oxide thin films deposited onto SS304 substrates using the direct current (DC) magnetron sputtering technique.

DC sputtering at different powers – 80, 100 and 120 W – was used to deposit ZrO₂ thin films onto different substrates (Si/SS304) without annealing of the substrate. Atomic force microscope (AFM), energy-dispersive X-ray spectroscopy (EDS), Tafel extrapolation and contact angle techniques were applied to investigate the surface roughness, chemical compositions, corrosion behavior and hydrophobicity of these films.

Results showed that the thickness of the deposited film increased with power increase, while the corrosion current decreased with power increase. AFM images indicated that the surface roughness decreased with an increase in DC power. EDS analysis showed that the thin film has a stoichiometric ZrO₂ (Zr:O 1:2) composition with basic uniformity. Water contact angle measurements indicated that the hydrophobicity of the synthesized films decreased with an increase in surface roughness.

DC magnetron sputtering technique is infrequently used to deposition thin films. The obtained thin films showed good hydrophobic and anticorrosion properties. Finally, results are compared with other deposition techniques.

This study aims to assess the effectiveness of a scale measuring artificial intelligence capabilities by using the resource-based theory. It seeks to examine the impact of these capabilities on the organizational-level resources of dynamic capabilities and organizational creativity, ultimately influencing the overall performance of government organizations.

The calibration of artificial intelligence capabilities scale was conducted using a combination of qualitative and quantitative analysis tools. A set of 26 initial items was formed in the qualitative study. In the quantitative study, self-reported data obtained from 344 public managers was used for the purposes of refining and validating the scale. Hypothesis testing is carried out to examine the relationship between theoretical constructs for the purpose of nomological testing.

Results provide empirical evidence that the presence of artificial intelligence capabilities positively and significantly impacts dynamic capabilities, organizational creativity and performance. Dynamic capabilities also found to partially mediate artificial intelligence capabilities relationship with organizational creativity and performance, and organizational creativity partially mediates dynamic capabilities – organizational creativity link.

The application of artificial intelligence holds promise for improving decision-making and problem-solving processes, thereby increasing the perceived value of public service. This can be achieved through the implementation of regulatory frameworks that serve as a blueprint for enhancing value and performance.

There are a limited number of studies on artificial intelligence capabilities conducted in the government sector, and these studies often present conflicting and inconclusive findings. Moreover, these studies indicate literature has not adequately explored the significance of organizational-level complementarity resources in facilitating the development of unique capabilities within government organizations. This paper presents a framework that can be used by government organizations to assess their artificial intelligence capabilities-organizational performance relation, drawing on the resource-based theory.

The purpose of this paper is to implement a closed loop regulated bidirectional DC to DC converter for an application in the electric power system of more electric aircraft. To provide a consistent power supply to all of the electronic loads in an aircraft at the desired voltage level, good efficiency and desired transient and steady-state response, a smart and affordable DC to DC converter architecture in closed loop mode is being designed and implemented.

The aircraft electric power system (EPS) uses a bidirectional half-bridge DC to DC converter to facilitate the electric power flow from the primary power source – an AC generator installed on the aircraft engine’s shaft – to the load as well as from the secondary power source – a lithium ion battery – to the load. Rechargeable lithium ion batteries are used because they allow the primary power source to continue recharging them whenever the aircraft engine is running smoothly and because, in the event that the aircraft engine becomes overloaded during takeoff or turbulence, the charged secondary power source can step in and supply the load.

A novel nonsingular terminal sliding mode voltage controller based on exponential reaching law is used to keep the load voltage constant under any of the aforementioned circumstances, and its performance is contrasted with a tuned PI controller on the basis of their respective transient and steady-state responses. The former gives a faster and better transient and steady-state response as compared to the latter.

This research gives a novel control scheme for incorporating an auxiliary power source, i.e. rechargeable battery, in more electric aircraft EPS. The battery is so implemented that it can get regeneratively charged when primary power supply is capable of handling an additional load, i.e. the battery. The charging and discharging of the battery is carried out in closed loop mode to ensure constant battery terminal voltage, constant battery current and constant load voltage as per the requirement. A novel sliding mode controller is used to improve transient and steady-state response of the system.

This study examines how dynamic capabilities (DCs) impact global value chain (GVC) upgrading and assesses the mediating role of innovation.

The study uses a quantitative research method. The data are collected using an online questionnaire administered to respondents working in Chinese automobile manufacturers in China and Laos. The data are analyzed using structural equation modeling (SEM) and related software.

The results show that DCs and innovation capabilities (ICs) positively affect GVC upgrading and that ICs plays a mediating role between DC and GVC upgrading. Dynamic capabilities evolution (CE) mediates the relationship between DCs, ICs and GVC upgrading. Finally, differences exist in the effects of the three dimensions of DCs on ICs and GVC upgrading.

Focusing on the absorption and transformation of knowledge, enterprises could experience a clear enhancement of IC and CE and be more likely to obtain higher marginal returns. The study provides insights for emerging market firms to gain higher added value in internationalization.

This study demonstrates that different dimensions of DCs have different effects on GVC upgrading. In terms of theory, the impact of IC is considered in terms of the mediating effect of CE on IC. Differences are highlighted concerning the impact of learning capability, integrating and coordinating capability and sensing capability on the mediated relationships.

The research on supply chain resilience (SCRES) has gained momentum after organizations have experienced more frequent and severe disruptions, especially with COVID-19 and the Russia/Ukraine conflict. Due to its potential for new practices and capability building, SCRES requires dynamic capabilities (DC) to enable an organization to prepare for, counter, and recuperate from disruptions leading to performance improvements and competitive advantage.

The present literature study seeks to enrich the theoretical debate on DC in SCRES, contributing to an advanced understanding of SCRES. Therefore, a meta-review of 83 peer-reviewed literature reviews has been conducted. Based on qualitative content analysis and abductive reasoning, relevant constructs are synthesized to facilitate theory-building for SCRES DC into a comprehensive framework.

The analysis reveals that SCRES has developed into an independent research area. Thus, resilience capabilities must be considered bundles of practices, evolving from different areas beyond supply chain risk management (SCRM). Most recent literature reviews on SCRES address more than one practice bundle applying SCRES DC as antecedents of new DC when organizational structures become more mature, leading to path dependencies when building business capabilities.

Aggregating extant literature on SCRES into a theoretical framework, the study contributes to a better understanding of the relationships between DC and SCRES practices while offering potential avenues for future research. It enriches DC theory by extending its microfoundations towards a holding/buffering dimension, which particularly accounts for the stability-based view of SCRES.