bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating the impact of employability skill training on the self-efficacy of disadvantaged adults
Authors: Mojtahedi Dara , Allen Rosie , Jess Ellie , Ioannou Maria , Synnott John 
Published: July 2024

Purpose
Employability skills training programmes are an effective means for reducing unemployment rates. Such programmes also have the potential to improve the general well-being (e.g. self-efficacy) of disadvantaged individuals, however, reliable longitudinal evaluations of the psychological benefits of such programmes are limited. The present study evaluated the impact of an employability programme offered to disadvantaged adults in North-West England on self-efficacy. Additionally, the study aimed to identify risk factors for programme disengagement to identify at-risk groups that require further support.

Design/methodology/approach
Secondary longitudinal data pertaining to the background characteristics, programme engagement and self-efficacy scores (repeatedly measured on a monthly basis) of 308 programme users were analysed.

Findings
Results demonstrated that employability programme engagement significantly increased self-efficacy scores. Additionally, the findings suggested that individuals with mental health and learning difficulties were more likely to disengage from the programme. The findings demonstrate that employability programmes can have a positive impact on the well-being of individuals from disadvantaged backgrounds, however, prolonged engagement is needed for which some individuals require further support with.

Originality/value
The present study analysed longitudinal data from a diverse sample of disadvantaged individuals to reliably evaluate psychological outcomes from employability training programmes.
What factors affect teacher professional learning: a qualitative meta-analysis based on the Onion model
Authors: Li Hanqiang 
Published: July 2024

Purpose
Current academic research on teacher learning is increasing in number and deepening in quality, but at the same time, the heterogeneity is growing significantly. Similar work is challenging to cross-check regarding conclusions due to the different research foci. This paper aims to provide a reliable theoretical framework and offers solid insights based on the existing research.

Design/methodology/approach
Based on the Onion model, 67 core literature in English and Chinese were coded through qualitative meta-analysis methods to explore environmental, behavioral, competence, belief, identity, mission and other factors that may impact teacher learning.

Findings
It was found that the quantitative structure of the current relevant studies was in an inverted triangular shape with three levels of steps, respectively, which can be summarized as structural environment, core behaviors and dominant mission. The heterogeneity between the findings mainly originated from two situations, oppositional and complementary and some structural adjustments were made to the Onion model according to the coding results to better represent the interaction of influences between the levels. It also analyzes current research trends and the centrality of learned behaviors based on the coding results.

Social implications
The design of teacher learning activities should combine theoretical, practical and inquiry learning to ensure that teachers are kept fresh and motivated by sustained and varied stimuli.

Originality/value
To the best of the authors’ knowledge, this study is the first to analyze teacher learning influences through qualitative meta-analysis and create node saturation to analyze the results, resulting in highly credible and valuable research findings.
An exploratory analysis of Early Adopters in education innovations
Authors: Basileo Lindsey Devers , Lyons Merewyn Elizabeth 
Published: July 2024

Purpose
The purpose of this study is to gain a better understanding of the conditions and motivations that influence teachers to adopt innovations.

Design/methodology/approach
Using Diffusion of Innovation theory (Rogers, 2003) and Self-Determination theory (Ryan and Deci, 2017), data from two surveys (n = 568; n = 108) and qualitative follow-up interviews of Early Adopter teachers (n = 16) were triangulated to discern relationships among their identification as Early Adopters, satisfaction of their basic psychological needs (BPN) and their implementation of an educational innovation.

Findings
Early Adopters had a positive and statistically significant relationship with the implementation of the innovation. Satisfaction of teachers’ BPN had the largest impact on innovation.

Research limitations/implications
The findings are preliminary and based on a small sample size of teachers. Reliability of the measure of BPN was not as high as the standard, but it did have the largest impact on implementation. Additional studies should explore the connections among Early Adopter teacher motivation, leadership and the satisfaction of their BPN.

Practical implications
School leaders should leverage the influence of Early Adopters to support innovation, and they should provide additional time, training and resources to supports teachers’ BPN.

Originality/value
This study examines how to identify and support Early Adopter teachers as enablers of change within schools. We know of no other studies that have used both Diffusion of Innovation theory and Self-Determination theory to understand the motivations of Early Adopter teachers.
Exploring association model across banks and fintechs in India
Authors: Roy Deepankar , Pramanik Himadri Sikhar , Bandyopadhyay Chayan , Datta Sayantan , Kirtania Manish 
Published: July 2024

Purpose
Bank–fintech associations are significant globally, establishing purposeful eco-systems towards extending and complementing capabilities, reach and customer experiences. This paper aims to explore 39 leading fintechs in India catering across payments, lending, wealth management, regulation, neo-banks and other banking functions. Alongside fintechs, the research studies 19 leading banks (public and private) to understand the nature of bank–fintech associations in the Indian context.

Design/methodology/approach
The research focuses on narratives from leading banks and top fintechs in India, captured from public disclosures and leadership interviews. The study leverages qualitative research techniques, including grounded theory approaches of inductive analysis, to codify interview and narrative observations to discover relevant objectives, scenarios, challenges and outcomes in India-centric bank–fintech associations.

Findings
Bank–fintech associations in India are increasingly focusing on financial services portfolio diversification and improvement in customer experience. Simultaneously, both banks and fintechs, differentiate with innovations and extend offerings to target underserved customer segments. The associations are beneficial for both banks and fintechs in transforming offerings and improving efficiency, scale across channels. Through codification of observations, review of existing literature and evaluation of best practices, alongside subject matter expertise, the study evolves a generalized “Association Model”. The model can steer meaningful bank–fintech associations in India and globally. The association model relates to observables like objectives, enablers of bank–fintech associations, challenges and association-driven value outcomes. Built from study of practices, the proposed model is relevant for strategic orientation in bank–fintech associations.

Originality/value
The findings reveal practices in bank–fintech associations in India with significant learning opportunity for organizational leaders globally. Understanding the nature of association is relevant for strategic interventions, particularly in scenarios of inter-organization collaborations. Central banks, policymakers, governments, investors, banks and fintechs can use the derived association model to establish, govern and steer purposeful value-driven associations.
An MS-TCN based spatiotemporal model with three-axis tactile for enhancing flexible printed circuit assembly
Authors: Kang Zengxin , Cui Jing , Wang Yijie , Hu Zhikai , Chu Zhongyi 
Published: July 2024

Purpose
Current flexible printed circuit (FPC) assembly relies heavily on manual labor, limiting capacity and increasing costs. Small FPC size makes automation challenging as terminals can be visually occluded. The purpose of this study is to use 3D tactile sensing to mimic human manual mating skills for enabling sensing offset between FPC terminals (FPC-t) and FPC mating slots (FPC-s) under visual occlusion.

Design/methodology/approach
The proposed model has three stages: spatial encoding, offset estimation and action strategy. The spatial encoder maps sparse 3D tactile data into a compact 1D feature capturing valid spatial assembly information to enable temporal processing. To compensate for low sensor resolution, consecutive spatial features are input to a multistage temporal convolutional network which estimates alignment offsets. The robot then performs alignment or mating actions based on the estimated offsets.

Findings
Experiments are conducted on a Redmi Note 4 smartphone assembly platform. Compared to other models, the proposed approach achieves superior offset estimation. Within limited trials, it successfully assembles FPCs under visual occlusion using three-axis tactile sensing.

Originality/value
A spatial encoder is designed to encode three-axis tactile data into feature maps, overcoming multistage temporal convolution network’s (MS-TCN) inability to directly process such input. Modifying the output to estimate assembly offsets with related motion semantics overcame MS-TCN’s segmentation points output, unable to meet assembly monitoring needs. Training and testing the improved MS-TCN on an FPC data set demonstrated accurate monitoring of the full process. An assembly platform verified performance on automated FPC assembly.
Design principles for MOOC platforms: a public sector perspective
Authors: Koddebusch Michael , Halsbenning Sebastian , Becker Jörg 
Published: July 2024

Purpose
One impediment of e-government implementation is the lack of e-(government) competences among public officials, especially because foundational education programs fail to teach them. Therefore, this study suggests massive open online course (MOOC)-based continuous education. This study aims to design and evaluate a MOOC and MOOC platform for acquiring e-competence in the public sector and principles for such platforms to capture their inherent design knowledge.

Design/methodology/approach
This study uses design science research incorporating qualitative and quantitative methods and draws on established patterns of formulating design principles (DPs).

Findings
The core results are a physically instantiated MOOC platform and six DPs: DP of 1) easy access and easy use, 2) professional exchange, 3) protected space, 4) domain focus, 5) cooperation with higher education institutions and 6) promotion from higher government level.

Research limitations/implications
This study contributes to e-government research by extending the design knowledge for the construction of domain-specific MOOC platforms. Moreover, the study contributes to platform economics by discussing existing theses and outlining new opportunities. The research also entails limitations, as the authors have solely considered MOOCs and neglected complimentary offers to sustain learning success.

Practical implications
This study provides practitioners with design principles they can use in their efforts to construct education platforms for the public sector. Moreover, the study presents a working MOOC platform instantiating these DPs, and thus provides an exemplary reference.

Social implications
Not fulfilling expectations regarding digital public services comes with a risk of decreasing trust in public organizations and the overall government. The results of this study contribute to enabling public officials fulfilling stakeholders’ expectations and generating public value.

Originality/value
By linking e-government competence education with MOOC platform design, this research approximates an important research gap. Scholars previously investigated e-competences and focused on alone-standing MOOCs to convey those. The results of this study offer the potential to construct platforms to centralize such fragmented solutions, maximizing their impact among public officials.
Are young adult consumers ready to be intelligent shoppers? The importance of perceived trust and the usefulness of AI-powered retail platforms in shaping purchase intention
Authors: ElSayad Ghada , Mamdouh Heba 
Published: July 2024

Purpose
The advancement of artificial intelligence (AI) has brought intelligent online shopping experiences to customers. AI-powered retail platforms deliver personalized shopping experiences through tailored recommendations, promotions and assistance. Given the increasing preference for online shopping, it is crucial to explore methods to optimize the adoption of AI-powered retail platforms. To address this, this study aims to examine the impact of technology readiness motivators (optimism and innovativeness) and inhibitors (discomfort and insecurity) on perceived trust, perceived usefulness and purchase intention toward AI-powered retail platforms.

Design/methodology/approach
Data were collected from 276 customers in Egypt, primarily from the millennial and Gen Z demographic segments. The collected data were then analyzed using the statistical package for social sciences (SPSS) and partial least squares structural equation modeling (PLS-SEM).

Findings
The findings revealed that optimism, innovativeness and discomfort significantly influence perceived trust, while optimism, insecurity and perceived trust significantly influence perceived usefulness. Both perceived trust and usefulness are significant predictors of purchase intention. Perceived trust mediates the effects of technology readiness motivators on perceived usefulness and purchase intention. Moreover, perceived usefulness mediates the effects of technology readiness motivators, insecurity and perceived trust on purchase intention.

Originality/value
To date, there are few investigations regarding the acceptance and adoption of AI-powered retail platforms in developing countries. Thus, this study offers valuable theoretical and practical implications in the context of smart retail technology adoption.
Discovery of a novel spotted fever group Rickettsia, “Candidatus Rickettsia kedanie,” in unfed larval chigger mites, Leptotrombidium scutellare
Authors: Ogawa Motohiko , Matsutani Minenosuke , Katayama Takashi , Takada Nobuhiro , Noda Shinichi , Takahashi Mamoru , Kageyama Daisuke , Hanaoka Nozomu , Ebihara Hideki 
Published: July 2024

AbstractSpotted fever group (SFG) rickettsia, the causative agent of SFG rickettsiosis, is predominantly carried by ticks, whereas Orientia tsutusgamushi, the causative agent of scrub typhus, is primarily transmitted by chigger mites in Japan. In this study, we attempted to isolate intracellular eubacteria from Leptotrombidium scutellare, a major vector of O. tsutsugamushi; moreover, we isolated an SFG rickettsia using a mosquito‐derived cell line. Draft genome sequences of this unique isolate, by applying criteria for species delimitation, classified this isolate as a novel strain, proposed as “Rickettsia kedanie.” Further genetic analysis identified conserved virulence factors, and the isolate successfully propagated in mammalian cells, suggesting its ability to cause diseases in humans. The presence of SFG rickettsia in unfed larvae implies potential dual‐pathogen carriage and reflects a symbiotic relationship similar to that between the mites and O. tsutsugamushi, indicating possibility of its transovarial transmission from female adults. Furthermore, conserved genomic similarity of the novel isolate to known SFG rickettsia suggests potential multiple hosts, including chiggers and ticks. In the natural environment, ticks, chigger mites, and wild animals may carry new isolates, complicating the infection cycle and increasing the transmission risks to humans. This discovery challenges the conventional association of SFG rickettsia with ticks, emphasizing its implications for research and disease control. However, this study was confined to a particular species of chigger mites and geographic area, underscoring the necessity for additional studies to comprehend the ecological dynamics, host interactions, and health implications linked to this newly identified SFG rickettsia.
Permanently on standby: Practitioner perspectives on the complexities of crisis planning
Authors: Chaudhri Vidhi , Armbrust Nina , Nguyen Sergül 
Published: July 2024

AbstractAlthough crisis planning (including both prevention and preparation) is well‐established as the 'alpha' of crisis management, businesses often find themselves caught off‐guard in the face of crises. What impedes business organizations from heeding scholarly advice to engage in crisis planning? Interviews with corporate communication professionals suggest that in a fast‐evolving digital landscape characterized by the ambiguity of what ‘qualifies’ as a crisis, the need for an organizational culture of preparedness and balancing structure with agility are the hallmarks of crisis planning. Even when interviewees acknowledge the importance of crisis planning, cultivating a culture of preparedness is contingent on an engaged leadership that recognizes and provides communication professionals a seat at the table, fosters internal coordination, and understands the importance of peacetime relationships with stakeholders. Our paper addresses the complexities and implications of crisis planning that is typically hidden from view.
Co‐working office spaces in Sydney: Spatiotemporal dynamics and industry patterns
Authors: Hsu Yi‐Ya , Han Hoon , Lee Jinwoo 
Published: July 2024

AbstractCo‐working spaces have emerged as cost‐effective office space management solutions for workers from diverse industries who share space, which generates cost savings and facilitates networking opportunities. Past studies have mainly focused on needs for and benefits of co‐working spaces and range in emphasis from design preferences to potential social and economic impacts. However, limited attention has been given to the temporal clustering and geographical distribution patterns of co‐working spaces. This study examines the spatial distribution patterns of co‐working spaces establishments in terms of building floor plans. We discern the subcategory of ‘co‐working office space’ from the floor space and employment survey data, spanning 2007, 2012, and 2017 as collected by the City of Sydney, a municipal government in Australia. Both co‐working offices offered by conventional enterprises and co‐working providers are identified, and the spatial associations between co‐working spaces and their relationships with industry composition are analysed. Using establishment analysis, three co‐working spaces are identified: (1) dedicated co‐working enterprises providing office service and well‐design spaces; (2) conventional office rental enterprises diversifying into co‐working style office; and (3) standard enterprises converting fixed office spaces to co‐working office configurations. The spatial analysis reveals an outward diffusion of co‐working spaces from the centre of Sydney CBD, which is of importance in geographical research focused on urban, social, and economic change.
Evaluation of fish meal freshness using a metal‐oxide semiconductor electronic nose combined with the long short‐term memory feature extraction method
Authors: Li Pei , Li Zhaopeng , Hu Yangting , Niu Zhiyou , Wang Zhenhe , Zhou Hua , Sun Xia 
Published: July 2024

AbstractTo improve the classification and regression performance of the total volatile basic nitrogen (TVB‐N) and acid value (AV) of different freshness fish meal samples detected by a metal‐oxide semiconductor electronic nose (MOS e‐nose), 402 original features, 62 manually extracted features, manually extracted and selected features by the RFRFE method, and the features extracted by the long short‐term memory (LSTM) network were used as inputs to identify the freshness. The classification performance of the freshness grades and the estimation performance of the TVB‐N and AV values of fish meal with different freshness were compared. According to the sensor response curve, preprocessing and feature extraction steps were first applied to the original data. Then, five classification algorithms and four regression algorithms were used for modeling. The results showed that a total of 30 features were extracted using the LSTM network, and the number of extracted features was significantly reduced. In the classification, the highest accuracy rate of 95.4% was obtained using the support vector machine method. In the regression, the least squares support vector regression method obtained the best root mean square error (RMSE). The coefficient of determination (R2), RMSE, and relative standard deviation (RSD) between the predicted value of TVBN and the actual value were 0.963, 11.01, and 7.9%, respectively. The R2, RMSE, and RSD between the predicted value of AV and the actual value were 0.972, 0.170, and 6.05%, respectively. The LSTM feature extraction method provided a new method and reference for feature extraction using an E‐nose to identify other animal‐derived material samples.
Benchmarking long‐read sequencing strategies for obtaining ASV‐resolved rRNA operons from environmental microeukaryotes
Authors: Overgaard Christina Karmisholt , Jamy Mahwash , Radutoiu Simona , Burki Fabien , Dueholm Morten Kam Dahl 
Published: July 2024

AbstractThe use of short‐read metabarcoding for classifying microeukaryotes is challenged by the lack of comprehensive 18S rRNA reference databases. While recent advances in high‐throughput long‐read sequencing provide the potential to greatly increase the phylogenetic coverage of these databases, the performance of different sequencing technologies and subsequent bioinformatics processing remain to be evaluated, primarily because of the absence of well‐defined eukaryotic mock communities. To address this challenge, we created a eukaryotic rRNA operon clone‐library and turned it into a precisely defined synthetic eukaryotic mock community. This mock community was then used to evaluate the performance of three long‐read sequencing strategies (PacBio circular consensus sequencing and two Nanopore approaches using unique molecular identifiers) and three tools for resolving amplicons sequence variants (ASVs) (USEARCH, VSEARCH, and DADA2). We investigated the sensitivity of the sequencing techniques based on the number of detected mock taxa, and the accuracy of the different ASV‐calling tools with a specific focus on the presence of chimera among the final rRNA operon ASVs. Based on our findings, we provide recommendations and best practice protocols for how to cost‐effectively obtain essentially error‐free rRNA operons in high‐throughput. An agricultural soil sample was used to demonstrate that the sequencing and bioinformatic results from the mock community also translates to highly diverse natural samples, which enables us to identify previously undescribed microeukaryotic lineages.