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Degree apprenticeships in the UK have grown exponentially since they were introduced. While claims and speculations about their impact have been made by high-profile politicians, lobbyists and training providers, the evidence base for these claims has never been systematically scrutinised. The purpose of this paper is to analyse and present up-to-date peer-reviewed evidence on the impact of degree apprenticeships on social mobility and productivity and their influence on future policy.

The authors critically and systematically review over 4,000 data points from relevant sources and synthesise the results qualitatively and quantitatively with a combined method approach. Quantitative evidence has been aggregated where possible and tested for statistical significance. Qualitative evidence has been critically reviewed and comparatively analysed.

The analysis reveals that there is a shortage of depth and breadth of concrete and peer-reviewed evidence on the impact of degree apprenticeships. Nevertheless, existing data demonstrate that degree apprenticeships are meeting their intended purpose of contributing positively to the UK Government’s high-level goals for productivity and social mobility. They are an alternative route into higher education and serve as a vital talent pipeline providing opportunities for young people, existing employees and learners from diverse backgrounds.

This paper provides the first systematic and peer-reviewed synthesis of the impact of degree apprenticeships. It brings together existing evidence and statistically validates outcomes to inform researchers, educators, training providers, policymakers and other stakeholders in their recommendations moving forward.

The serious wear problem of heavy-haul freight vehicle wheels affects the safety and economy of vehicle operation. This paper aims to study wheel wear evolution law and the influence of line parameters on wheel wear of heavy-haul freight, and provide the basis for operation and line maintenance.

The wheel wear test data of heavy-haul freight vehicles were analyzed. Then a heavy-haul freight vehicle dynamic model was established. The line parameters influencing wheel wear in heavy-haul freight vehicles were also analyzed by the Jendel wear model, and the effects of rail cant, rail gauge, rail profile and line ramp on wheel wear were analyzed.

A rail cant of 1:40 results in less wheel wear; an increase in the rail gauge can reduce wheel wear; and when matched with the CHN60 rail, the wear depth is relatively small. A decrease of 9.21% in wheel wear depth when matched with the CHN60 rail profile. The ramp of the heavy-haul line is necessary to consider for calculating wheel wear. When the ramp is considered, the wear depth increases by 8.47%. The larger the ramp, the greater the braking force and therefore, the greater of the wheel wear.

This paper first summarizes the wear characteristics of wheels in heavy-haul freight vehicles and then systematically analyzes the effect of line parameters on wheel wear. In particular, this study researched the effects of rail cant, rail gauge, rail profile and line ramp on wheel wear.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0038/

With the development of regional economy, innovation network plays an increasingly prominent role in reducing regional innovation cost and enabling information, knowledge and capital flow and diffusion. Building an efficient innovation network has become a feasible way to improve regional innovation capabilities and performance. Thus, under the background of Chinese special triple helix structure, the specific mechanism of innovation network characteristics on regional innovation performance is still an issue that needs to be studied urgently.

This study conducts a multi-level regression analysis regional innovation panel data of China from the past four years to explore how the three dimensions of innovation network characteristics (i.e. network density, openness and strength) affect regional innovation performance.

The results show that there is an inverted-U relationship exists between network density and regional innovation performance. The network openness and regional innovation performance show a significantly positive relationship and a U-shaped relationship exists between network strength and regional innovation performance.

First, this study examines the relationship between network density, openness, strength and innovation ability in the network variable structure. However, this study does not analyze how absorptive capacity impacts the network structure and innovation performance of regional innovators. Second, innovation network intensity largely varies according to different types of enterprises or industries. Therefore, future studies can attempt to analyze the relationship between innovation network and innovation performance on the basis of the industry or the enterprise itself. Fourth, this study does not consider the change in the influence of innovation network structure on innovation ability.

The results of this study provide insights for the formulation of the regional innovation policy. First, enterprises must maintain good contact with research institutes, universities and technology intermediaries and promote resource, information and money flow between networks through formal and informal interactions. Enterprises can currently only interact with a limited number of innovative subjects due to their limited resources. Therefore, we should continue implementing the open policy of foreign capital utilization and absorb the technology, knowledge, management, ideas, talent and other resource advantages in the world. The investment environment in the central and western regions should be improved as soon as possible to guide foreign direct investments to the middle and the west part of China, thereby promoting the coordinated development of regional innovation ability and economy.

In 2015, the Chinese Government proposed “public entrepreneurship and innovation,” including technological, institutional, management and mode innovations. This study suggests that innovation subjects in the region should establish an interactive and dynamic innovation network among innovators.

The innovation of this study lies in the analysis of the characteristics of innovation network that significantly affect regional innovation performance, the exploration of different stages of innovation network construction path and provide theoretical guidance for the construction of innovation network.

This paper aims to anticipate the possible development direction of WAAM. For large-scale and complex components, the material loss and cycle time of wire arc additive manufacturing (WAAM) are lower than those of conventional manufacturing. However, the high-precision WAAM currently requires longer cycle times for correcting dimensional errors. Therefore, new technologies need to be developed to achieve high-precision and high-efficiency WAAM.

This paper analyses the innovations in high-precision WAAM in the past five years from a mechanistic point of view.

Controlling heat to improve precision is an effective method. Methods of heat control include reducing the amount of heat entering the deposited interlayer or transferring the accumulated heat out of the interlayer in time. Based on this, an effective and highly precise WAAM is achievable in combination with multi-scale sensors and a complete expert system.

Therefore, a development direction for intelligent WAAM is proposed. Using the optimised process parameters based on machine learning, adjusting the parameters according to the sensors’ in-process feedback, achieving heat control and high precision manufacturing.

The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities.

Using Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis.

Comparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency.

First, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances.

The results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers.

The results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies.

The research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.

The purpose of this study is to explore the role skepticism plays among adolescents’ online information literacy skills.

The authors provide the conceptual grounding to operationalize and measure the notion of skepticism in an online information literacy context. Inspired by an existing measure known as the Skepticism Scale (Hurtt, 2010), the authors made substantial revisions to the scale to target middle school and high school students’ skepticism in six distinct, but related factors: questioning mind; search for knowledge; suspension of judgment; self-esteem; interpersonal understanding; and autonomy. The authors provide preliminary evidence of validity and reliability of the revised Skepticism Scale using Exploratory Factor Analysis and performed multiple linear regression using the Skepticism Scale measures to predict an adolescents’ online information literacy skills.

The Skepticism Scale was found to produce internally consistent constructs for all six measures. Three of the six measures were related to online information literacy skills, including the search for knowledge, interpersonal understanding and questioning mind.

This paper attempts to examine the potentially positive role of skepticism in information literacy skills among adolescents.

The construction industries at present are focusing on designing sustainable concrete with less carbon footprint. Considering this aspect, a Fibre-Reinforced Geopolymer Concrete (FGC) was developed with 8 and 10 molarities (M). At elevated temperatures, concrete experiences deterioration of its mechanical properties which is in some cases associated with spalling, leading to the building collapse.

In this study, six geopolymer-based mix proportions are prepared with crimped steel fibre (SF), polypropylene fibre (PF), basalt fibre (BF), a hybrid mixture consisting of (SF + PF), a hybrid mixture with (SF + BF), and a reference specimen (without fibres). After temperature exposure, ultrasonic pulse velocity, physical characteristics of damaged concrete, loss of compressive strength (CS), split tensile strength (TS), and flexural strength (FS) of concrete are assessed. A polynomial relationship is developed between residual strength properties of concrete, and it showed a good agreement.

The test results concluded that concrete with BF showed a lower loss in CS after 925 °C (i.e. 60 min of heating) temperature exposure. In the case of TS, and FS, the concrete with SF had lesser loss in strength. After 986 °C and 1029 °C exposure, concrete with the hybrid combination (SF + BF) showed lower strength deterioration in CS, TS, and FS as compared to concrete with PF and SF + PF. The rate of reduction in strength is similar to that of GC-BF in CS, GC-SF in TS and FS.

Performance evaluation under fire exposure is necessary for FGC. In this study, we provided the mechanical behaviour and physical properties of SF, PF, and BF-based geopolymer concrete exposed to high temperatures, which were evaluated according to ISO standards. In addition, micro-structural behaviour and linear polynomials are observed.

The explosion of data due to the sophistication of information and communication technology makes it simple for prospective tourists to learn about previous hotel guests' experiences. They prioritize the rating score when selecting a hotel. However, rating scores are less reliable for suggesting a personalized preference for each aspect, especially when they are in a limited number. This study aims to recommend ratings and personalized preference hotels using cross-domain and aspect-based features.

We propose an aspect-based cross-domain personalized recommendation (AsCDPR), a novel framework for rating prediction and personalized customer preference recommendations. We incorporate a cross-domain personalized approach and aspect-based features of items from the review text. We extracted aspect-based feature vectors from two domains using bidirectional long short-term memory and then mapped them by a multilayer perceptron (MLP). The cross-domain recommendation module trains MLP to analyze sentiment and predict item ratings and the polarities of the aspect based on user preferences.

Expanded by its synonyms, aspect-based features significantly improve the performance of sentiment analysis on accuracy and the F1-score matrix. With relatively low mean absolute error and root mean square error values, AsCDPR outperforms matrix factorization, collaborative matrix factorization, EMCDPR and Personalized transfer of user preferences for cross-domain recommendation. These values are 1.3657 and 1.6682, respectively.

This study assists users in recommending hotels based on their priority preferences. Users do not need to read other people's reviews to capture the key aspects of items. This model could enhance system reliability in the hospitality industry by providing personalized recommendations.

This study introduces a new approach that embeds aspect-based features of items in a cross-domain personalized recommendation. AsCDPR predicts ratings and provides recommendations based on priority aspects of each user's preferences.

Mobile location-based service (m-LBS) seems like a new class of personalized service due to location positioning technologies. This work aims to investigate consumer readiness (RED) toward m-LBS based on integrating pull effect- and push effect-related factors into the technology acceptance model (TAM).

An online survey collected data from 423 participants, and the research framework was analyzed using structural equation modeling (SEM).

The results divulge that consumer RED is determined by TAM antecedents, including usefulness (USE) and ease of use (EOU). EOU motivates USE in m-LBS. Regarding pull effect-related factors, absorptive capacity (ABC) is the strongest positive factor influencing consumer RED to use m-LBS, followed by technology willingness (TWI) and innovativeness (INN). Moreover, INN, trust (TRU) and perceived risk (RIS) significantly influence USE and EOU.

This work endeavors to explicate customer RED toward m-LBS by incorporating some meaningful pull effect-related dimensions (i.e. ABC, TWI and INN) and pushing effect-related dimensions (i.e. RIS) into crucial antecedents rooted in TAM. Thus, the findings assist practitioners in developing marketing strategies by boosting pull effects and controlling push effects on customer engagement in m-LBS.