bluuebunny/crossref_metadata_2025_split huggingface dataset:
How SMEs’ supply chain specific investment impacts supply chain financing performance: insights from signaling theory
Authors: Lu Qiang , Wang Yangyang , Yang Yudong 
Published: January 2025

Purpose
This study aims to investigate how small and medium-sized enterprises (SMEs’) supply chain specific investment (SCSIs) affects supply chain financing performance (SCFP) in the innovative industrial finance model, and further analyze the internal mechanisms and important contextual factors.

Design/methodology/approach
Based on signaling theory, this study constructs a mediating and moderating model to examine the influencing mechanisms of SMEs’ SCSIs on SCFP, including the mediating effect of opportunism and the moderating effect of digital technology deployment (DTD). A multiple regression analysis is conducted to verify the theoretical hypotheses, using questionnaire data collected from 288 SMEs in China.

Findings
The empirical findings indicate that both SMEs’ supply chain asset-specific and relationship-specific investments can significantly promote SCFP. Also, SMEs’ SCSIs can improve SCFP by reducing the occurrence of opportunism perceived by supply chain partners. The breadth of DTD positively moderates the relationship between the two types of SCSIs and SCFP, while the depth of DTD has no significant moderating effect on the relationship between SCSIs and SCFP.

Originality/value
This study has discussed the important and novel issue of how financially distressed SMEs can send effective signals to financial institutions by increasing their SCSIs in supply chain finance mode. By revealing the influencing mechanisms of SMEs’ SCSIs on SCFP, this study contributes to expanding the research on the antecedents of SCFP from the dimension of interorganizational transactions. This study also enriches the perspectives of signaling theory by exploring the interaction between signal sender and signal intermediary.
Social ties as dynamic managerial capabilities and SME performance: unraveling the role of industrial boundary conditions
Authors: Uzkurt Cevahir , Ceyhan Semih , Ekmekcioglu Emre Burak 
Published: January 2025

Purpose
As a contribution to the social ties and dynamic capabilities literature, the purpose of this study is to examine the boundary role of the industrial factors (competitive intensity, dependence on suppliers and demand uncertainty) on the relationship between small and medium-sized enterprises (SMEs) social ties (business ties and political ties) and firm performance.

Design/methodology/approach
Data were collected from 1,077 SME top-level managers in Turkiye. The proposed model is analyzed using partial least squares (PLS) path modeling in SmartPLS 4.0 software.

Findings
The results elucidate how demand uncertainty serve to moderate the influence exerted by both business and political ties upon the performance of SMEs. However, the moderating effects of competitive intensity and dependence on suppliers, although initially hypothesized, were not found to have a significant impact on the relationships.

Practical implications
The relevance of social ties of SMEs may depend on the industrial factor. Although both political and business ties are effective on the customer side, these ties may become irrelevant when it comes to competition and supplier relations. In competitive SME settings, where businesses are vying for similar markets, the effectiveness of ties might be questionable. In such cases, SMEs might invest in building in-house capabilities and competencies, rather than relying on their relational networks.

Originality/value
This study contributes to the understanding of how relational networks, which are considered as dynamic managerial capabilities, impact SMEs performance. It also fills an important gap by testing the boundary role of industrial factors on this relationship. The empirical data is collected from the Turkish context, which is also an original aspect of the study, considering most of the social ties literature has a limited focus on a few contexts. The results also indicate new areas for discussion and exploration, indicating potential avenues for further research.
Exploring ChatGPT literacy as predictor and moderator in enhancing informal digital learning of English (IDLE): a partial least square analysis
Authors: Li Xiaomeng , Thien Lei Mee 
Published: January 2025

Purpose
This study aims to explore the role of ChatGPT literacy within the technology acceptance model (TAM) framework and its potential for learners of English as a foreign language (EFL), whereby ChatGPT is integrated into their informal digital learning of English activities.

Design/methodology/approach
Data from 543 Chinese EFL learners were collected using a cross-sectional quantitative method. The relationships between six factors, namely, ChatGPT literacy, perceived ease of use, perceived usefulness, attitude, behavioral intention and actual use, were conceptualized and tested based on the TAM framework. The conceptualized model was verified using partial least squares structural equation modeling.

Findings
The findings indicated that ChatGPT literacy is a significant predictor of perceived ease of use and perceived usefulness, which were the two core variables with a significant impact on attitude. Perceived ease of use positively influenced perceived usefulness, indicating the mediating role of perceived usefulness in this path. Attitude significantly and positively influenced behavioral intention, which positively predicted actual use. Moreover, ChatGPT literacy moderated the relationship between behavioral intention and actual use.

Originality/value
This study extends the TAM framework by incorporating ChatGPT literacy as a predictor and moderator between behavioral intention and actual use. Empirical evidence is further offered for including ChatGPT as a language-learning instrument with great potential for EFL learners in extramural EFL learner settings.
Managing difficult conversations on new technology integration: the case of generative AI
Authors: Eapen Tojin Thomas , Finkenstadt Daniel J. 
Published: January 2025

Purpose
Managing difficult conversations about new technology integration is crucial for businesses that must adopt disruptive innovations while maintaining organizational integrity. This article explores the “technology integrity” challenge, which involves preserving identity, operational, and relational aspects of business integrity during the new technological integration process. Using Generative AI as an illustrative case, the article provides a six-stage conversation framework, covering authenticity, direction, unification, scalability, transparency, and ethics, to guide organizations in conducting empathetic, inclusive dialogues with internal and external stakeholders.

Design/methodology/approach
This is a conceptual paper for a practitioner audience.

Findings
The article provides a six-stage conversation framework, covering authenticity, direction, unification, scalability, transparency, and ethics to guide organizations in conducting empathetic, inclusive dialogues with internal and external stakeholders.

Originality/value
This article explores the “technology integrity” challenge, which involves preserving identity, operational, and relational aspects of business integrity during the new technological integration process. This is particularly critical for organizations integrating AI technologies.
Critical success factors for students’ knowledge-sharing behaviors: a comparison between undergraduate, graduate and professional course students
Authors: Evangelista Edmund , Mustapha S.M.F.D Syed , Marir Farhi 
Published: January 2025

Purpose
The purpose of the research was to explore the critical success factors (CSFs) that enable knowledge-sharing behaviors (KSB) among students and to determine if there are differences in the CSFs that enable KSB among undergraduate, graduate or professional course students.

Design/methodology/approach
The study is based on primary data collection, surveying 281 students using a multiple-choice Likert-style scale.

Findings
Researchers found that factors such as knowledge culture (KC), perceived rewards (PR), quality of technology (QT), trust, networking ties (NT) and competitiveness were critical for KSB. In contrast, collective culture, subjective norms (SN) and the ability to share did not significantly impact KSB. The CSFs common among students at different educational levels were KC, PR, trust and competitiveness. KC was more important for undergraduates and professional course students but less significant for graduate students. Additionally, NT and the QT did not impact KSB among undergraduates.

Originality/value
While several studies have explored CSFs for knowledge-sharing behaviors among students at specific educational levels, there is a lack of comparative empirical research examining KSB and the CSFs affecting students at different educational stages. This study fills a gap in the literature by adopting a comparative approach and presenting common success factors for knowledge sharing among students at various educational levels.
COSST: A tool to facilitate seed provenancing for climate‐smart ecosystem restoration
Authors: Silva Mateus C. , Moonlight Peter , Oliveira Rafael S. , Rowland Lucy , Pennington R. Toby 
Published: January 2025

Abstract

Selecting the best seed sources is a key step in ecological restoration planning especially under climate change. Seed‐provenancing strategies include composite, aiming to reproduce natural gene flow; predictive, focusing on future climate adaptation; and climate‐adjusted, a combination of composite and predictive. Yet, implementing different seed‐provenancing principles remains a challenge.

To fill this methodological gap, we developed the Climate‐Oriented Seed‐Sourcing Tool (COSST), a tool built in R capable of suggesting priority areas for seed sourcing according to composite, predictive, or climate‐adjusted strategies, as well as the restoration site and focal species.

The tool derives its inputs from species distribution models, which require occurrence and climate data only. COSST accommodates multiple climatic variables, weights the variables according to species‐specific sensitivities, and accounts for uncertainties between climate forecasts.

We demonstrated the flexibility of COSST using Caryocar brasiliense (pequi), a tree native to the Brazilian Cerrado, as a case study. The tool identified optimal areas for collecting C. brasiliense seeds and estimated the proportion of seeds to be sourced from various suppliers. We made available an R code for running COSST along with a Shiny application for data visualization.

Synthesis and applications. Our tool can guide where to source seeds for species lacking range‐wide information on genetic structure, which is the case for a substantial proportion of the tropical flora, where ecosystem restoration is of paramount importance.
The role of occupational therapy in providing vocational rehabilitation for people living with inflammatory arthritis: A scoping review
Authors: Somerville Susan , Codd Yvonne , Gowran Rosemary J. 
Published: January 2025

AbstractIntroductionInflammatory arthritis significantly impacts work participation resulting in cost to individuals, employers, and society. Vocational rehabilitation seeks to address this need, but its pathways, interventions, and efficacy continue to be under investigation. Contributing variables are complex, identifying the need for a conceptual framework to guide practice. Occupational therapy addresses this complexity, providing theoretical frameworks such as the Person‐Environment‐Occupation‐Performance (PEOP) model to understand the occupation of work supporting well‐being and design interventions. The aim of this scoping review is to map the role of occupational therapy in providing vocational rehabilitation for people living with inflammatory arthritis.MethodsA scoping review following Arksey and O'Malley's (2005) stages was completed. Major databases and grey literature were systematically searched, and hand‐searches completed. Descriptive and thematic analysis mapped the findings to the PEOP model framework.Consumer and Community InvolvementThere was no consumer or community involvement in this review.ResultsFourteen studies were included. Major themes aligned to the PEOP model with further analysis synthesised in subthemes. A majority of person‐related interventions to support work performance was observed. This framework identifies the domains of focus in vocational rehabilitation and current gaps. Work instability, employment retention, and self‐efficacy were used to measure effectiveness.ConclusionThis scoping review presents the evidence regarding vocational rehabilitation for the inflammatory arthritis population in the context of occupational therapy theory to provide a framework for clinical practice. A current focus on person‐focused interventions was identified. The PEOP model provides a clear framework to understand the complexity and nuances of vocational rehabilitation across the domains. Outcome measures for vocational rehabilitation are heterogenous and require further exploration as capturing the intricacy of achieving balance with work participation remains unclear. Further research into vocational rehabilitation programs incorporating all domains of the PEOP model is needed. Consideration of work performance measurements to inform effectiveness and the resulting impact on a person's well‐being is required.
Mechanisms and strategic prospects of cannabinoids use: Potential applications in antimicrobial food packaging—A review
Authors: Dey Moumita , Bera Sharmita , Tyagi Preeti , Pal Lokendra 
Published: January 2025

AbstractThis review focuses on antimicrobial packaging for food safety, critically examining the activity and efficacy of cannabinoids against commonly found microorganisms and exploring their antimicrobial mechanisms. Specifically, the review considers cannabinoids derived from industrial hemp plants, which are characterized by low levels of psychoactive components. It also outlines viable strategies to control the sustained release of cannabinoids from the packaging, enabling extended storage and enhanced safety of food products. Research demonstrates that cannabinoids are effective against both foodborne bacteria and fungi, with their antimicrobial action primarily attributed to microbial membrane instability. Cannabinoids can be utilized to prepare effective antimicrobial films and edible coatings; however, the number of studies in this area remains limited. The potential of cannabinoids to contribute to intelligent packaging systems is also discussed, with an emphasis on the regulatory aspects and challenges associated with incorporating cannabinoids into food packaging. Finally, the review identifies future research directions to address current limitations and advance hemp‐based antimicrobial food packaging solutions.
Automating egg damage detection for improved quality control in the food industry using deep learning
Authors: Cengel Talha Alperen , Gencturk Bunyamin , Yasin Elham Tahsin , Yildiz Muslume Beyza , Cinar Ilkay , Koklu Murat 
Published: January 2025

AbstractThe detection and classification of damage to eggs within the egg industry are of paramount importance for the production of healthy eggs. This study focuses on the automatic identification of cracks and surface damage in chicken eggs using deep learning algorithms. The goal is to enhance egg quality control in the food industry by accurately identifying eggs with physical damage, such as cracks, fractures, or other surface defects, which could compromise their quality. A total of 794 egg images were used in the study, comprising two different classes: damaged and not damaged (intact) eggs. Four different deep learning models based on convolutional neural networks were employed: GoogLeNet, Visual Geometry Group (VGG)‐19, MobileNet‐v2, and residual network (ResNet)‐50. GoogLeNet achieved a classification accuracy of 98.73%, VGG‐19 achieved 97.45%, MobileNet‐v2 achieved 97.47%, and ResNet‐50 achieved 96.84%. According to the results, the GoogLeNet model performed the damage detection with the highest accuracy rate (98.73%). This study encompasses artificial intelligence and deep learning techniques for the automatic detection of egg damage. The early detection of egg damage and accurate interventions highlights the significant importance of using these technologies in the food industry. This approach provides producers with the ability to detect damaged eggs more quickly and accurately, thereby minimizing product losses through timely intervention. Additionally, the use of these technologies offers a more efficient means of classifying and identifying damaged eggs compared to traditional methods.
Children With Sydenham Chorea and Psychiatric Disorders Had Variable Long‐Term Outcomes and Required Multidisciplinary Management
Authors: Mushet Nadine , Morton Michael , Minnis Helen , Gillberg Christopher 
Published: January 2025

ABSTRACTAimSydenham chorea (SC) is a globally significant, post‐streptococcal, childhood neuropsychiatric condition that is rare in western Europe. This retrospective single‐centre study focused on children with neuropsychiatric features of SC.MethodsParticipants were recruited from neuropsychiatry referrals to a regional paediatric neurology department in Glasgow, Scotland, from 2009 to 2012. Interviews established the course of SC and the children's medical and family histories. Semi‐structured psychiatric interviews explored current and past episodes of psychopathology.ResultsWe studied 12 children (seven girls) with a mean age of 13 (range 10–15) years, and an average of six (range 4–10) years after their SC symptoms began. Before they displayed symptoms, seven children had been suspected or diagnosed neurodevelopmental problems and four had separation anxiety. Their physical symptoms were often debilitating. Psychopathology was most severe during their first episode and SC diagnoses were sometimes delayed. Educational problems were frequent. Multiple psychiatric conditions were diagnosed in 11 children and anxiety and attention deficit hyperactivity disorder were the most common. Relapses occurred in nine cases. Additional services that were accessed included cardiology, rheumatology, physiotherapy, occupational therapy and speech therapy. Medication included prophylactic penicillin and symptomatic treatment.ConclusionChildren with SC and psychiatric disorders had variable long‐term outcomes and required multidisciplinary management.
The neonate respiratory microbiome
Authors: Pirr Sabine , Willers Maike , Viemann Dorothee 
Published: January 2025

AbstractOver the past two decades, it has become clear that against earlier assumptions, the respiratory tract is regularly populated by a variety of microbiota even down to the lowest parts of the lungs. New methods and technologies revealed distinct microbiome compositions and developmental trajectories in the differing parts of the respiratory tract of neonates and infants. In this review, we describe the current understanding of respiratory microbiota development in human neonates and highlight multiple factors that have been identified to impact human respiratory microbiome development including gestational age, mode of delivery, diet, antibiotic treatment, and early infections. Moreover, we discuss to date revealed respiratory microbiome–disease associations in infants and children that may indicate a potentially imprinting cross talk between microbial communities and the host immune system in the respiratory tract. It becomes obvious how insufficient our knowledge still is regarding the exact mechanisms underlying such cross talk in humans. Lastly, we highlight strong findings that emphasize the important role of the gut–lung axis in educating and driving pulmonary immunity. Further research is needed to better understand the host – respiratory microbiome interaction in order to enable the translation into microbiome‐based strategies to protect and improve human respiratory health from early childhood.
Deeds speak louder than words: Employees' responses to supervisors' word‐oriented and deed‐oriented voice endorsement
Authors: Ni Dan , Zhang Yihua , Wu Wen , Peng Xianting , Zheng Michelle Xue 
Published: January 2025

AbstractIntegrating the voice endorsement literature and behavioral integrity theory, this research first advances the constructs and develops the scales for supervisors' word‐oriented and deed‐oriented voice endorsement in Study 1. In Study 2, we examine how supervisors' word‐oriented and deed‐oriented voice endorsement influence employee voice behavior. Results from a four‐wave field study demonstrate that supervisors' word‐oriented voice endorsement is negatively related to perceived supervisor behavioral integrity, whereas supervisors' deed‐oriented voice endorsement is positively related to perceived supervisor behavioral integrity. Perceived supervisor behavioral integrity enhances employees' willingness to discuss ideas and ultimately promotes their voice behavior. In addition, a higher (versus lower) level of explanation providing weakens the negative impact of supervisors' word‐oriented voice endorsement and strengthens the positive impact of supervisors' deed‐oriented voice endorsement on perceived supervisor behavioral integrity. Theoretical and practical implications are discussed.
Your needs or mine? The role of allies' needs and their perceptions of disadvantaged groups' needs in motivating solidarity‐based actions
Authors: Sağlamöz Ahmed Faruk , Kutlaca Maja , Leite Ana C. 
Published: January 2025

AbstractWe propose a new motivational model that integrates self‐determination theory (with a focus on basic needs) with social‐psychological research on allyship and solidarity to better understand when and why allies may engage in different actions to address social injustice. We theorize that normative (e.g., donations and protesting) and non‐normative (e.g., blocking highways and disrupting events) solidarity‐based actions are motivated by allies' basic needs (measured at the individual and group levels) as well as their perception of disadvantaged groups' basic needs (measured at the individual and group levels). We tested the model in two cross‐sectional studies using two different contexts: English citizens' solidarity (i.e., allies from a high‐status group) with Ukrainian refugees and students' solidarity (i.e., allies from a low‐status group) with the striking university employees in the United Kingdom (Ntotal = 1232). In both studies, we found that the more allies' needs were satisfied, the more likely they were to engage in normative solidarity actions. In contrast, intentions to engage in non‐normative solidarity actions were predicted by frustration of allies' needs. Perceptions of disadvantaged group's needs predicted engagement in both normative and non‐normative actions. Notably, high‐status allies' solidarity was driven by both individual and group‐level needs, whilst low‐status allies were only motivated by group‐level needs.