bluuebunny/crossref_metadata_2025_split huggingface dataset:
From pledge to action: integrating racial diversity into the supply chain
Authors: Kinney Yahzmine , Siegler Janaina , Fernhaber Stephanie A. 
Published: August 2024

PurposeOrganizations are increasingly making commitments and equity pledges to racially diversify their supply chain. While such commitments are commendable, historical attempts at reform have experienced limited success. This suggests that there is a need for organizations to understand the hurdles and complexity that might limit impact, and then be intentional when taking action.Design/methodology/approachIn this study, we conduct an inductive, qualitative investigation involving five organizations in Indianapolis USA. Three are corporations that had made a commitment to and are actively trying to racially diversify their supply chain. The other two are support organizations that serve as a link between suppliers and corporations.FindingsThe results identify three levels of interrelated management challenges associated with racially diversifying the supply chain at the industry, strategy, and operation levels.Originality/valueStrategies for overcoming the challenges when integrating racial diversity into the supply chain are discussed, and a set of directional questions are provided to help organizations with their quest to racially diversify their supply chains.
X-News dataset for online news categorization
Authors: Yousafzai Samia Nawaz , Shahbaz Hooria , Ali Armughan , Qamar Amreen , Nasir Inzamam Mashood , Tehsin Sara , Damaševičius Robertas 
Published: August 2024

PurposeThe objective is to develop a more effective model that simplifies and accelerates the news classification process using advanced text mining and deep learning (DL) techniques. A distributed framework utilizing Bidirectional Encoder Representations from Transformers (BERT) was developed to classify news headlines. This approach leverages various text mining and DL techniques on a distributed infrastructure, aiming to offer an alternative to traditional news classification methods.Design/methodology/approachThis study focuses on the classification of distinct types of news by analyzing tweets from various news channels. It addresses the limitations of using benchmark datasets for news classification, which often result in models that are impractical for real-world applications.FindingsThe framework’s effectiveness was evaluated on a newly proposed dataset and two additional benchmark datasets from the Kaggle repository, assessing the performance of each text mining and classification method across these datasets. The results of this study demonstrate that the proposed strategy significantly outperforms other approaches in terms of accuracy and execution time. This indicates that the distributed framework, coupled with the use of BERT for text analysis, provides a robust solution for analyzing large volumes of data efficiently. The findings also highlight the value of the newly released corpus for further research in news classification and emotion classification, suggesting its potential to facilitate advancements in these areas.Originality/valueThis research introduces an innovative distributed framework for news classification that addresses the shortcomings of models trained on benchmark datasets. By utilizing cutting-edge techniques and a novel dataset, the study offers significant improvements in accuracy and processing speed. The release of the corpus represents a valuable contribution to the field, enabling further exploration into news and emotion classification. This work sets a new standard for the analysis of news data, offering practical implications for the development of more effective and efficient news classification systems.
The influence of organizational commitment on employee green behavior: mediating role of work-related social media use
Authors: Bodhi Rahul , Chaturvedi Shakti , Purohit Sonal 
Published: August 2024

PurposeEmployee green behavior (EGB) is a type of pro-environment behavior at the workplace strategized by organizations to attain sustainable development goals. While organizations have prioritized eco-friendly practices to attain sustainability objectives, EGB has emerged as an essential area of research. Considering the need for sustained employee green behavior, it is important to understand what stimulates such behaviors in an organization. Therefore, we propose a theoretical model grounded in social exchange theory to assess the effect of organizational commitment on employee green behavior, work-related use of social media, social well-being and psychological well-being.Design/methodology/approachA questionnaire-based survey approach was used to collect data from 203 employees of Indian manufacturing and service industries. Partial least square structural equation modeling (PLS-SEM) analysis was applied to examine the proposed hypothesis.FindingsThe results revealed positive and significant effects of organizational commitment on psychological well-being, social well-being, work-related social media use and employee green behavior. Further, psychological well-being mediates the association between work-related social media use and employee green behavior.Originality/valueThis is one of the first studies to examine the effect of organizational commitment on employee green behavior to the best of our knowledge. Additionally, the findings empirically establish organizational commitment, work-related social media use and psychological well-being as antecedents to employee green behavior, thus offering novel insights and theoretically contributing to the employee green behavior, well-being and organizational literature.
Investigation on the lubrication performance of different carbon nanoparticles for titanium alloy
Authors: Yang Ye , Luan Hao , Tian Yaru , Si Lina , Yan Hongjuan , Liu Fengbin 
Published: August 2024

Purpose
This study aims to develop a high-performance nanofluid that can be used in titanium alloys machining. Titanium alloys are difficult-to-cut materials and difficult to be lubricated. This study explored the lubrication performance of various carbon nanoparticles in water-based lubricants for titanium alloys.

Design/methodology/approach
The lubricating and antiwear properties of the developed cutting fluid were tested by a tribo-tester. The lubricant performance was evaluated through friction coefficient, wear volume and surface quality. The lubrication mechanism was analyzed through surface morphology, wettability and bonding analysis.

Findings
The lubricating performance of four kinds of carbon nanoparticles on titanium alloys was tested and the results showed that single-layer graphene had the smallest COF and wear volume. The interaction between nanoparticles and debris was an important factor that influenced the lubrication performance of nanoparticles for titanium alloy. Moreover, the hybrid nanofluid with graphene and spherical graphite in a ratio of 1:2 achieved a balance between lubricating performance and price, making it the optimal choice.

Practical implications
The developed lubricant containing carbon nanoparticles that can lubricate titanium alloys effectively has great potential in machining titanium alloy as a high-performance cutting fluid in the future.

Originality/value
This paper fulfills an identified need for water-based lubricant for titanium alloys considering the bad tribological properties.

Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0124/
Diversity of digital media exposure, information verification and vaccination intention: an empirical study in China
Authors: Chen Hongliang , Chen Yueying , Xu Xiaowen , Atkin David 
Published: August 2024

PurposeDuring the COVID-19 pandemic, the public relied heavily on digital media to stay tuned for the latest update. Media preference could increase risk perceptions, although the influence of diverse media exposure remains unknown. Based on protection motivation theory, this study aims to investigate how digital media exposure diversity and information verification influence vaccination intention.Design/methodology/approachAnalyzing survey data from 837 respondents in China, this study examined the effects of digital media exposure on information verification, including their influences on the threat appraisal, coping appraisal, vaccine misinformation beliefs, subjective norms and trust in vaccines.FindingsResults indicate that diversity of digital media exposure increased threat appraisal (perceived severity) and coping appraisal (response efficacy and self-efficacy), while information verification increased only coping appraisal (response efficacy and self-efficacy). In addition, diversity of digital media exposure decreased vaccine misinformation beliefs. Furthermore, digital media exposure and information verification were linked to vaccination intention via the mediations of response efficacy, subjective norms and trust in vaccines.Originality/valueThis study is the first of its kind to investigate media exposure diversity in the context of vaccination and health crises. Our findings extended the PMT framework by exploring proactive information-related behaviors as antecedents of mediation processes. In addition, we examined misinformation beliefs, social norms and trust as societal influences. Theoretical and practical implications are also discussed.
Unleashing knowledge arbitrage potential: empowering startups through knowledge management
Authors: Nawaz Rabiya , Hina Maryam , Sharma Veenu , Srivastava Shalini , Farina Briamonte Massimiliano 
Published: August 2024

Purpose
Organizations increasingly use knowledge arbitrage to stimulate innovation and achieve competitive advantage. However, in knowledge management its use in startups is yet unexplored. This study aims to examine the utilization of knowledge arbitrage by startups, specifically during COVID-19.

Design/methodology/approach
This study employed an open-ended essay methodology to explore the drivers and barriers that startups face in utilizing knowledge arbitrage. We collected data from 40 participants to understand the role of knowledge arbitrage in startups’ knowledge management practices.

Findings
This study’s findings highlight the significance of knowledge arbitrage for startups. The benefits identified include organizational benefits such as building networks, innovating new products and achieving competitive advantage and financial benefits such as cost reduction and sales growth. The study also identifies several technological and organizational drivers and barriers that startups confront during knowledge arbitrage.

Originality/value
This study contributes to the existing literature on knowledge management by extending our understanding of knowledge arbitrage’s role in startups. Additionally, it sheds light on the importance of knowledge arbitrage for startups and the challenges they face, particularly in a disrupted environment reared by COVID-19. The study provides insights for the scholars and practitioners interested in effective knowledge management in startups.
How can companies handle paradoxes to enhance trust in artificial intelligence solutions? A qualitative research
Authors: Bakonyi Zoltán 
Published: August 2024

PurposeExploring trust's impact on AI project success. Companies can't leverage AI without employee trust. While analytics features like speed and precision can build trust, they may also lower it during implementation, leading to paradoxes. This study identifies these paradoxes and proposes strategies to manage them.Design/methodology/approachThis paper applies a grounded theory approach based on 35 interviews with senior managers, users, and implementers of analytics solutions of large European companies.FindingsIt identifies seven paradoxes, namely, knowledge substitution, task substitution, domain expert, time, error, reference, and experience paradoxes and provides some real-life examples of managing them.Research limitations/implicationsThe limitations of this paper include its focus on machine learning projects from the last two years, potentially overlooking longer-term trends. The study's micro-level perspective on implementation projects may limit broader insights, and the research primarily examines European contexts, potentially missing out on global perspectives. Additionally, the qualitative methodology used may limit the generalizability of findings. Finally, while the paper identifies trust paradoxes, it does not offer an exhaustive exploration of their dynamics or quantitative measurements of their strength.Practical implicationsSeveral tactics to tackle trust paradoxes in AI projects have been identified, including a change roadmap, data “load tests”, early expert involvement, model descriptions, piloting, plans for machine-human cooperation, learning time, and a backup system. Applying these can boost trust in AI, giving organizations an analytical edge.Social implicationsThe AI-driven digital transformation is inevitable; the only question is whether we will lead, participate, or fall behind. This paper explores how organizations can adapt to technological changes and how employees can leverage AI to enhance efficiency with minimal disruption.Originality/valueThis paper offers a theoretical overview of trust in analytics and analyses over 30 interviews from real-life analytics projects, contributing to a field typically dominated by statistical or anecdotal evidence. It provides practical insights with scientific rigour derived from the interviews and the author's nearly decade-long consulting career.
Promoting inclusivity: exploring Turkish language teacher identity and cognition in special education for students with visual impairments
Authors: Cinarbas Halil Ibrahim , Daloglu Aysegul 
Published: August 2024

Purpose
This case study aims to enrich research on language teacher identity and cognition by detailing the experiences of English language teachers instructing students with visual impairments in Türkiye, exploring the (re)formation of their identity and cognition within this context.

Design/methodology/approach
This study uses a qualitative approach, combining interviews, observations, field notes and legal document analysis. Hiver and Al-Hoorie's (2016) Complexity Theory guides data collection and analysis, supported by MAXQDA software.

Findings
The findings highlight the influences of personal, social, cultural and educational factors on language teacher identity and cognition, with a focus on interactions in preservice education, institutional requirements and instructional methods at the School for the Blind.

Originality/value
This case study provides practical and theoretical insights into language teacher identity and cognition within special education schools, contributing to the broader discourse on diversity in this field.
An efficient steel defect detection model based on multi-scale information extraction
Authors: Xu Wenshen , Zhang Yifan , Jiang Xinhang , Lian Jun , Lin Ye 
Published: August 2024

Purpose
In the field of steel defect detection, the existing detection algorithms struggle to achieve a satisfactory balance between detection accuracy, computational cost and inference speed due to the interference from complex background information, the variety of defect types and significant variations in defect morphology. To solve this problem, this paper aims to propose an efficient detector based on multi-scale information extraction (MSI-YOLO), which uses YOLOv8s as the baseline model.

Design/methodology/approach
First, the authors introduce an efficient multi-scale convolution with different-sized convolution kernels, which enables the feature extraction network to accommodate significant variations in defect morphology. Furthermore, the authors introduce the channel prior convolutional attention mechanism, which allows the network to focus on defect areas and ignore complex background interference. Considering the lightweight design and accuracy improvement, the authors introduce a more lightweight feature fusion network (Slim-neck) to improve the fusion effect of feature maps.

Findings
MSI-YOLO achieves 79.9% mean average precision on the public data set Northeastern University (NEU)-DET, with a model size of only 19.0 MB and an frames per second of 62.5. Compared with other state-of-the-art detectors, MSI-YOLO greatly improves the recognition accuracy and has significant advantages in computational cost and inference speed. Additionally, the strong generalization ability of MSI-YOLO is verified on the collected industrial site steel data set.

Originality/value
This paper proposes an efficient steel defect detector with high accuracy, low computational cost, excellent detection speed and strong generalization ability, which is more valuable for practical applications in resource-limited industrial production.
Can niche plasticity mediate species persistence under ocean acidification?
Authors: Cipriani Vittoria , Goldenberg Silvan U. , Connell Sean D. , Ravasi Timothy , Nagelkerken Ivan 
Published: August 2024

Abstract

Global change stressors can modify ecological niches of species, thereby altering ecological interactions within communities and food webs. Yet, some species might take advantage of a fast‐changing environment, allowing species with high niche plasticity to thrive under climate change.

We used natural CO2 vents to test the effects of ocean acidification on niche modifications of a temperate rocky reef fish assemblage. We quantified three ecological niche traits (overlap, shift and breadth) across three key niche dimensions (trophic, habitat and behavioural).

Only one species increased its niche width along multiple niche dimensions (trophic and behavioural), shifted its niche in the remaining (habitat) was the only species to experience a highly increased density (i.e. doubling) at vents. The other three species that showed slightly increased or declining densities at vents only displayed a niche width increase in one (habitat niche) out of seven niche metrics considered. This niche modification was likely in response to habitat simplification (transition to a system dominated by turf algae) under ocean acidification.

We further showed that, at the vents, the less abundant fishes had a negligible competitive impact on the most abundant and common species. This species appeared to expand its niche space, overlapping with other species, which likely led to lower abundances of the latter under elevated CO2.

We conclude that niche plasticity across multiple dimensions could be a potential adaptation in fishes to benefit from a changing environment in a high‐CO2 world.
Relational street‐level bureaucracy: Proximity policing and the construction of trust between citizens and municipal police officers in Nezahualcóyotl, Mexico
Authors: González‐Martínez Nashellit , Peeters Rik 
Published: August 2024

AbstractVarious studies have provided evidence that, especially in the Global South, relational street‐level bureaucracy can play a constructive role in bridging the gap between vulnerable population groups and a distant, formal bureaucracy that often fails to guarantee citizens’ rights and factual access to public services and benefits. However, studies have also highlighted street‐level bureaucracies’ vulnerability to practices of corruption, patrimonialism, and clientelism as they engage with citizens through more informal mechanisms. In this article, we contribute to understanding which institutional conditions can promote constructive citizen‐bureaucrat interactions by presenting findings from a qualitative study on proximity policing in a densely populated suburb of Mexico City with some of the highest crime levels in the entire metropolitan area. Sustained and managerially supported implementation of proximity policing has improved citizen‐police relations and facilitated learning processes by both officers and residents, while minimizing risks of clientelism. Although this model of municipal policing is no panacea for complex security issues, it does confirm existing evidence regarding the importance of relational street‐level bureaucracy for improving citizen trust and, moreover, highlights the importance of consistent managerial and citizen involvement as enabling factors.Points for practitioners
The traditional focus on bureaucratic control and capacities has often involuntarily ended up worsening public service provision in contexts with weak state institutions.
Relational street‐level bureaucracy can play a constructive role in bridging the gap between vulnerable population groups and a distant, formal bureaucracy.
Consistent managerial support, citizen involvement, and professional deliberation are crucial elements in mitigating the downsides of informality in street‐level interactions.
Variations in quality attributes of pulsed light‐treated table grape juice during refrigerated storage (4°C) and ambient conditions (25°C)
Authors: Basak Somnath , Parab Pooja , Chakraborty Snehasis 
Published: August 2024

AbstractPulsed light (PL) pasteurization is being explored as a substitute for the conventional thermal pasteurization of juices in recent times due to better retention of nutrients and overall quality. However, the long‐term stability of the PL‐pasteurized juice must be investigated to promote its application by the industry. The effect of PL treatment (effective fluence of 1.15 J·cm−2) and thermal treatment (90°C for 60 s) on microbial quality, enzyme activity, bioactive compounds, sensory acceptance, and color profile of table grape juice during storage at 4 and 25°C was investigated in this study. The PL pasteurization enhanced the microbial shelf‐life of the juice (<6 log10cfu·mL−1) from 5 to 35 days at 4°C. The PL and thermally‐pasteurized juice demonstrated a shelf‐life of only 10 days when stored at 25°C. The total soluble solids and titratable acidity did not alter significantly throughout the storage period. The peroxidase, polyphenol oxidase, and pectin methylesterase activities were below 10% for the PL and thermally‐treated beverage when stored at 4°C. The sensory acceptability of the PL‐pasteurized juice after 35 days of refrigerated storage (6.9 ± 0.3) was close to the untreated juice (7.2 ± 0.3) and greater than thermally‐treated juice (6.2 ± 0.2). After the 35th day of storage at 4°C, PL‐treated grape juice retained 55%, 12%, and 15.3% more phenolics, flavonoids, and antioxidant capacity, respectively, than the thermally‐pasteurized juice. Hence, PL pasteurization can effectively prolong the shelf‐life of table grape juice while achieving microbial and enzymatic stability, along with high sensory and nutritional appeal.Practical ApplicationExploring non‐thermal methods like pulsed light (PL) pasteurization as a substitute for conventional thermal methods is gaining recognition for its ability to retain nutrients and improve overall juice quality. However, the industry's adoption depends on understanding the shelf‐stability of PL‐pasteurized juice. This study specifically investigates the practical applications of PL treatment in comparison with conventional thermal treatment in enhancing microbial safety and enzymatic stability in table grape juice. The findings contribute insights into optimizing the shelf life of table grape juice and preserving its quality, supported by microbial, enzymatic, and sensory evaluations.