bluuebunny/crossref_metadata_2025_split huggingface dataset:
A poly(A) polymerase and oligo(dT)-dependent method for the purification of engineering circular RNAs that enhances protein expression in eukaryotic cells
Authors: Wei Lulu , Zhang Mengjuan , Zhang Haifeng , Zhao Haiyan , Mei Yingwu 
Published: December 2024

ABSTRACTCircular RNA (circRNA) has garnered significant attention as a promising therapeutic tool due to its remarkable stability and resistance to exonuclease degradation. However, the development of scalable and efficient purification methods remains a critical challenge. In this study, we propose and evaluate a novel purification strategy for engineered circular RNA (PAPdt), which leverages poly(A) polymerase and oligo(dT) affinity chromatography. Using poly(A) polymerase, we add poly(A) tails of over 200 nucleotides to the 3’-OH ends of all linear RNA impurities in a circular RNA preparation. These linear RNAs are then separated from the circular RNA via oligo(dT) affinity chromatography. The linear impurities, bearing longer poly(A) tails, exhibit extended retention on the oligo(dT) column, whereas the circular RNA, with a shorter poly(A) sequence, elutes more quickly. By stepwise elution with ultrapure water, we effectively separate the circular RNA from the linear contaminants. This method offers a fundamental solution to the purification of circular RNA, combining high efficiency, purity, and cost-effectiveness.
The nexus between teacher trainees’ digital literacy and online learning motivation
Authors: Ahmed Md. Meraz , Sultana Merine , Md. Rokonuzzaman  , Hossain Md. Kamal 
Published: December 2024

PurposeThis study examined the relationship between levels of digital literacy and the online learning motivation (OLM) of teacher trainees across various factors.Design/methodology/approachThis investigation utilized a quantitative research approach. The sample was selected through a purposive method and consisted of 485 teacher trainees from the School of Education at Bangladesh Open University (BOU). Participants' digital literacy and OLM were assessed using validated five-point Likert scale questionnaires, consisting of 17 items for digital literacy and six items for OLM. The collection of data was conducted via a cross-sectional survey. Descriptive analysis, Cronbach’s alpha, exploratory factor analysis, t-test and ANOVA were employed for the purpose of data analysis.FindingsThe findings demonstrated that teacher trainees possessed sufficient digital literacy and OLM concerning the specified variables. Furthermore, there was a significant correlation between digital literacy and OLM. BOU can evaluate all of these findings to make a rational decision regarding the development of its teacher education programs.Originality/valueThis exploratory study has yielded significant insights into the demographic characteristics, computer and internet skills, virtual learning skills and OLM of teacher trainees, thereby enhancing the existing body of knowledge in this field.
Consumers’ perceptions of regulatory food hygiene inspections of restaurants and takeaways
Authors: Flanagan Mark Andrew , Soon-Sinclair Jan Mei 
Published: December 2024

PurposeFoodborne illnesses are often attributed to food services such as restaurants and takeaways. This study aims to investigate consumers’ perceptions of regulatory food hygiene inspections of restaurants and takeaways in UK.Design/methodology/approachA cross-sectional online survey was conducted between November 2024 and March 2025, and 750 responses were received. Chi-square test was carried out to identify associations between demographic variables and checking of food hygiene rating or information. Ordered logistic regression was carried out to determine if demographics and eating out and/or takeaway consumption practices affect participants’ level of confidence in Local authorities (LA)’ (LAs) food hygiene inspections of restaurants and takeaways.FindingsFemales, individuals with food hypersensitivities, low-risk appetite, those who experienced food poisoning incidents and had reported food safety concerns to LA reported checking food hygiene rating or information more frequently. Our findings also revealed that participants who searched for food hygiene rating or information exhibited increased confidence in recent food hygiene inspections (less than a year).Practical implicationsLA should emphasise the importance of checking hygiene ratings or information before dining out or purchasing takeaways, especially for vulnerable groups. Although not mandatory, restaurants and takeaways in England and Scotland could make their hygiene ratings or information more visible and accessible to build public trust and encourage greater consumer engagement with food hygiene information. Additionally, public awareness on how food hygiene inspections are conducted and the factors influencing inspection schedules could further enhance consumer confidence in the inspection process.Originality/valueThis is the first study to explore the relationship between consumer perceptions of food hygiene inspection frequency and their confidence in LA’ inspection process. Our findings suggest that both perceived inspection frequency and food hygiene rating or information seeking behaviour can influence consumer confidence in LA’ food hygiene inspections.
Can FinTech alleviate the long-term use of short-term debts? Evidence from China
Authors: Yang Lianxing , Hong Yunzhe , Zhang Xiumin , Zhang Qing 
Published: December 2024

PurposeTo deepen the structural reform of the financial system on the supply side and mitigate associated risks in the economic and financial fields, with significant practical implications for FinTech development.Design/methodology/approachBased on microdata of listed companies, this paper constructs multi-level indicators of FinTech development. Robustness tests include alternative measures of the degree of long-term use of short-term debts, sample adjustments and heterogeneity in firm characteristics and regional differences.FindingsFinTech can significantly alleviate the long-term use of short-term corporate debt, although there are heterogeneous effects. The alleviation effect is more pronounced for state-owned enterprises, non-technology-intensive enterprises and other companies with lower levels of short-term debt maturity. Additionally, in regions with high capital mismatch and high levels of financial development, FinTech exhibits a significant suppressive effect on the long-term use of short-term corporate debt.Practical implicationsThe paper suggests promoting the diversification of FinTech products, emphasizing the importance of inclusive finance through FinTech, and driving China’s economic transformation and high-quality development.Originality/valueBy constructing a theoretical analysis framework of “FinTech—corporate investment and financing term mismatch,” this paper provides a multi-level estimation of the factors influencing FinTech’s impact on the long-term use of short-term corporate debt. This framework aids in developing a more dialectical and objective understanding of the economic effects of FinTech’s development.
Incorporating neurodiversity into international business research
Authors: Ott Dana L. , Moeller Miriam , Koveshnikov Alexei 
Published: December 2024

Purpose
The purpose of this viewpoint is to provide critical insights into the role of neurodiversity within the domain of International Business (IB) research. Neurodiversity is positioned as an opportunity for IB researchers to explore how differences in individual brain functioning and behavioral traits may impact on the practice of and research within IB through multiple lenses.

Design/methodology/approach
By critically reflecting on how to foster a more inclusive global business environment, the viewpoint increases researchers’ awareness about the role of neurodiversity within IB research and practice. It highlights distinct opportunities to incorporate neurodiversity and neurodivergent individuals at the center of IB research examinations.

Findings
Neurodiversity represents a paradigm shift in how neurological and cognitive differences have been perceived, valued and researched by challenging scholars to move beyond a model that views these differences as deficits or disorders to one that views them as strengths and opportunities. The authors identify a series of research questions to advance the study of neurodiversity in relation to global talent management; innovation and competitiveness; inclusive and equitable business practices and systems (human resource management, leadership and technology); stigmatization, biases and identity; and global organizations as change agents.

Originality/value
Considering that one in six people globally is neurodivergent, the viewpoint suggests directions to examine neurodiversity within the context of IB research and practice.
Cluster strength and regional resilience: the case of the USA in the Great Recession
Authors: Zárate-Mirón Viviana Elizabeth , Moreno Rosina 
Published: December 2024

Purpose
This paper aims to evaluate the role of cluster strength on regional resilience. Previous literature shows that the industrial composition of a region, measured with indicators of its specialization, diversity and related and unrelated variety, is a crucial determinant of resilience. In this paper, the authors aggregate cluster-level data into several indicators of regional cluster strength to proxy for different aspects of the cluster portfolio of a region.

Design/methodology/approach
In particular, the authors consider the role of the presence of strong clusters in a regional economy as well as the mix of clusters in which the region has main relevance. On the one hand, the authors assume that the agglomeration forces arising in regions specialized in certain clusters could mitigate the effect of recessions. However, these strong industrial linkages may increase the diffusion of the economic shock from one industry to the rest. To check which of these two forces dominates, the authors consider the resilience of the US states over the Great Recession period and use a cluster definition that classifies traded industries into 51 clusters.

Findings
This study’s findings suggest that the presence of a portfolio of strong clusters allows mitigating economic shocks.

Practical implications
Resilience mechanisms must be identified in the face of future economic shocks or pandemics like COVID-19.

Originality/value
Some research works have demonstrated that strong clusters help make other clusters resilient. However, the effects they can have on the entire region have not been analyzed, as in this study.
The power of customer-to-customer self-service technology in enhancing customer-to-customer interactions
Authors: Kim Hyun Sik , Choi Beomjoon 
Published: December 2024

Purpose
This research paper aims to examine the power of customer-to-customer (C2C) oriented self-service technology (SST) in enhancing customers’ perceived C2C interaction qualities in collectively interactive service settings where C2C interactions are crucial for value co-creation.

Design/methodology/approach
The authors collected survey data within a collectively interactive service setting (massively multiplayer online role-playing games, MMORPGs) to test hypotheses. The data were analyzed using partial least squares structural equation modeling (PLS-SEM).

Findings
The results reveal that C2CSST attributes (enjoyment, usefulness) significantly influence users’ perceived C2C interaction qualities (friend-, neighboring customer-, audience-interaction quality).

Research limitations/implications
The current research theoretically proposes and empirically validates new relational links from C2CSST attributes (enjoyment, usefulness) to each online C2C interaction quality in a collectively interactive service setting (MMORPG). However, future studies may need to explore further antecedents of each C2C interaction quality to help enhance the understanding of the model suggested.

Practical implications
The results of this study provide important guidance for designers looking to incorporate SST into collectively interactive services. Collectively interactive service providers should promote C2CSST attributes (enjoyment, usefulness) so that the users experience better C2C interactions, which may lead to customer-firm affection and loyalty.

Originality/value
Via the study, the present paper proposes a customized subcategory of self-service technology (C2CSST) and posits that the C2CSST attributes (enjoyment, usefulness) can be key managing targets for enhancing C2C interactions. To the best of the authors’ knowledge, this research is one of the first SST studies to explore the role of C2CSSTs as enablers of C2C interactions, extending the SST literature.
Machine learning-based fatigue life prediction of laser powder bed fusion additively manufactured Hastelloy X via nondestructively detected defects
Authors: Wang Haijie , Zhang Jianrui , Li Bo , Xuan Fuzhen 
Published: December 2024

PurposeBy incorporating the defect feature information, an ML-based linkage between defects and fatigue life unaffected by the time scale is developed, the primary focus is to quantitatively assess and elucidate the impact of different defect features on fatigue life.Design/methodology/approachA machine learning (ML) framework is proposed to predict the fatigue life of LPBF-built Hastelloy X utilizing microstructural defects identified through nondestructive detection prior to fatigue testing. The proposed method combines nondestructive micro-computerized tomography (micro-CT) technique to comprehensively analyze the size, location, morphology and distribution of the defects.FindingsIn the test set, SVM-based fatigue life prediction exhibits the highest accuracy. Regarding the defect information, the defect size significantly affects fatigue life, and the diameter of the circumscribed sphere of the largest defect has a critical effect on fatigue life.Originality/valueThis comprehensive approach provides valuable insights into the fatigue mechanism of structural materials in defective states, offering a novel perspective for better understanding the influence of defects on fatigue performance.
Investors’ pro-environmental attitude, spirituality and socially responsible investing: a mediating role of greenwashing practices
Authors: Shahid Ahmad Usman , Nagarajan Chitra Devi , Tufail Hafiza Sobia , Imran Muhammad 
Published: December 2024

Purpose
The objective of this study is to examine the influence of investors’ pro-environmental attitudes and spirituality on their intentions to invest in socially responsible investment projects in the context of India. This study also examines whether investors’ perceptions of firms’ greenwashing practices mediate the relationship between their pro-environmental attitude, spirituality and investing decisions.

Design/methodology/approach
The authors collected data from 337 investors registered at the National Stock Exchange of India. Additionally, data were analyzed, and hypotheses were tested using linear regression, zero-order correlation and mediation approaches in SPSS 28.

Findings
The findings of this study report that investors’ pro-environmental attitudes and spirituality have a significant positive impact on their intentions to invest in socially responsible investment projects. Additionally, their mediation analysis further shows that both manipulative and selective disclosures of greenwashing practices mediate the association between investors’ pro-environmental attitude, spirituality and their intentions to invest in socially responsible investment projects.

Practical implications
The findings of the study have important implications for regulators, policymakers, firms and researchers in understanding the impact of pro-environmental attitudes and firms’ greenwashing practices on investors’ socially responsible investing decisions.

Social implications
This study also has implications for regulators in creating awareness for tackling greenwashing practices and screening intentions to invest in socially responsible investment projects in developing countries.

Originality/value
This study stresses creating awareness for incorporating pro-environmental and spiritual mindset into addressing the challenges of socially responsible investing in the presence of greenwashing practices.
Does inflation or interest rate matter to Indonesian stock prices? An asymmetric approach
Authors: Sia Peck-Ching , Puah Chin-Hong , Leong Choi-Meng , Yii Kwang-Jing , Tang Maggie May-Jean 
Published: December 2024

PurposeThis paper examines the asymmetric effects of inflation and interest rate on stock prices in Indonesia.Design/methodology/approachVariables such as interest rate, inflation rate, gross domestic product (GDP), and exchange rate were tested using the time-series data fitted to the Nonlinear Autoregressive Distributed Lag (NARDL) model. The asymmetric effects of interest rate and inflation rate were estimated in two separate models, with data covering the period from 1997:Q1 to 2023:Q3.FindingsThe results indicated that interest rate exhibit asymmetric effects on stock prices in both the short and long run. Conversely, no asymmetric effect was identified for the inflation rate model. The NARDL result of the asymmetry interest rate model revealed that both positive and negative changes in interest rate have a negative impact on stock prices in Indonesia. Notably, stock prices were positively and significantly influenced by both economic growth and exchange rate. The results suggested that policymakers should respond more proactively by adjusting interest rate in line with stock price movements.Originality/valueThis study diverges from previous studies by employing a general equilibrium theoretic model to link output with stock returns and extending it to include macroeconomic variables relevant to stock price determination. This study uniquely examined the asymmetric effects of monetary policy variables in Indonesia, particularly by comparing the asymmetric effects of inflation and interest rate.
An evaluation of intellectual capital disclosure: evidence from Vietnamese firms
Authors: An Hoang Thi Thuy , Aly Doaa , Abdelqader Muath , J Melhem Muntaser , K Darwish Tamer , Al Tweijer Anas 
Published: December 2024

Purpose
This study aims to explore the extent of Intellectual Capital Disclosure (ICD) in the annual reports of the top 50 listed Vietnamese companies. It assesses the influence of firm characteristics and corporate governance structure on ICD practices.

Design/methodology/approach
ICD was measured using content analysis, specifically word count percentage. Panel data regression analysis was employed to examine the relationship between firm characteristics, governance structures and the level of ICD.

Findings
Results reveal that ICD levels among Vietnamese firms sampled are relatively low, averaging 17.43% of the overall annual report word count. Relational capital emerges as the most disclosed category of IC. Firm size, profitability, industry type, number of independent board members and CEO duality significantly impact the level of ICD. However, leverage, board size and the presence of an audit committee show no significant influence on ICD.

Practical implications
These findings offer insights into agency and signaling theories. They provide empirical evidence for stakeholders, academics and regulatory bodies to comprehend ICD practices and identify factors that could enhance ICD in emerging markets like Vietnam.

Originality/value
This study contributes to the literature by examining ICD practices in an emerging market context and identifying the impact of firm characteristics and governance structures on ICD levels, offering valuable implications for both theory and practice.
The impact of digital transformation practices in the recreation sector on digital behavior decision-making post-COVID-19
Authors: Yu Tai-Yi , Horng Jeou-Shyan , Liu Chih-Hsing , Chou Sheng-Fang , Huang Yung-Chuan , La Quoc Phong , Ng Yen-Ling 
Published: December 2024

Purpose
This study aims to explore post-COVID-19 tourism digital transformation, study innovative service delivery and provide insights for industry leaders and policy-makers to nurture robust sector growth amid evolving consumer demands.

Design/methodology/approach
This study used anonymous questionnaires and explored views on digital technology in sports centers and entertainment venues. Structural equation modeling explores latent variable interactions with respect to mediating and moderating effects.

Findings
Digital transformation practices influence decision-making indirectly through perceived behavior control, attitudes and service innovation, with differentiation strategies moderating this relationship.

Research limitations/implications
This study focuses on the recreation sector; future efforts should include insights, attitudes and actions from experts and government policy-makers.

Practical implications
This study enhances the literature on recreation professionals, offering guidance for navigating the evolving landscape of digital dynamics in the leisure and recreation sector.

Originality/value
The rise of digital technology highlights the importance of analyzing customer decisions influenced by digital behavior within the leisure and recreation industry.
Harnessing machine learning for money laundering detection: a criminological theory-centric approach
Authors: Ramadhan Syahril 
Published: December 2024

Purpose
The purpose of this study is to develop and evaluate the effectiveness of the criminology-centric machine learning (CCTML) framework in detecting money laundering activities by integrating criminological theories with machine learning techniques.

Design/methodology/approach
This study uses a mixed-methods approach, this research synthesizes qualitative insights from expert interviews and literature reviews with quantitative analysis using machine learning models. Criminology-centric features are engineered based on established theories to capture behaviors indicative of money laundering. Various machine learning algorithms, including Voting Ensemble, XGBoost, Random Forest and LightGBM, are evaluated for their effectiveness in detecting financial crimes.

Findings
The findings of the study demonstrate that the CCTML approach consistently outperforms common machine learning models in detecting money laundering activities across various evaluation metrics, including area under the curve, log loss, Matthews correlation coefficient, precision, recall and balanced accuracy. The integration of criminological insights into machine learning models significantly enhances their predictive accuracy and reliability.

Originality/value
This research synthesizes diverse criminological insights into a cohesive framework known as CCTML. This approach goes beyond common feature engineering by incorporating complex behavioral patterns and social dynamics, thereby enhancing the accuracy and transparency of money laundering detection systems. By leveraging state-of-the-art machine learning algorithms and explainable artificial intelligence (AI) techniques, CCTML not only improves predictive capabilities but also ensures that model decisions are interpretable and fair. Explainable AI helps CCTML reveal why certain transactions are flagged, aiding investigators in identifying key suspects. Furthermore, this study contributes a comprehensive anti-money laundering framework that integrates ethical considerations, promoting a more robust and just approach to combating financial crimes.