bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prime editing outperforms homology-directed repair as a tool for CRISPR-mediated variant knock-in in zebrafish
Authors: Vanhooydonck Michiel , De Neef Elyne , De Saffel Hanna , Boel Annekatrien , Willaert Andy , Callewaert Bert , Claes Kathleen BM 
Published: February 2025

ABSTRACTZebrafish serve as a valuable model organism for studying human genetic diseases. While generating knockout lines is relatively straightforward, introducing precise disease-specific genetic variants by knock-in (KI) remains challenging. KI lines, however, enable more accurate studies of molecular and physiological consequences of genetic diseases. Their generation is often hampered by low editing efficiencies (EE) and potential off-target effects. In this study, we optimized conventional CRISPR/Cas9-mediated homology-directed repair (HDR) strategies for precise KI of genetic variants in zebrafish and compared their efficacy with prime editing (PE), a recently developed technique that is not yet commonly used. Using next-generation sequencing (NGS), we determined KI EE by HDR for six unique base-pair substitutions in three different zebrafish genes. We assessed the effect of 1) varying Cas9 amounts, 2) HDR templates with chemical modifications to improve integration efficiency, 3) different micro-injection procedures, and 4) synonymous guide-blocking variants in the protospacer sequence. Increasing Cas9 amounts augmented KI EE, with optimal injected amounts of Cas9 between 200 and 800 pg. The use of Alt-R™ HDR templates (IDT) further increased KI EE, while guide-blocking modifications did not. Injecting components directly into the cell was not superior to injections into the yolk. PE, however, increased EE up to fourfold and expanded the F0 founder pool for four targets when compared to conventional HDR editing, with fewer off-target effects. Therefore, PE is a very promising methodology for improving the creation of precise genomic edits in zebrafish, facilitating the modeling of human diseases.
Examining generative AI user continuance intention based on the SOR model
Authors: Zhou Tao , Ma Xinjie 
Published: February 2025

PurposeThe purpose of this research is to examine generative artificial intelligence (AI) user continuance intention based on the stimulus-organism-response model.Design/methodology/approachWe adopted a mixed method of structural equation modeling and fuzzy-set qualitative comparative analysis to conduct data analysis.FindingsThe results found that generative AI content quality (perceived personalization, perceived accuracy and perceived credibility) and system quality (perceived interactivity, perceived anthropomorphism and perceived intelligence) affect sense of empowerment and satisfaction, both of which further determine continuance intention.Originality/valueExtant research has identified the effect of flow, trust and parasocial interaction on generative AI user continuance, but it has seldom disclosed the internal decisional process of generative AI user continuance intention. This research tries to fill this gap, and the results enrich the extant research on generative AI user continuance.
Developing calling to reduce turnover intention through mentoring: a contextualized study in China
Authors: Tan Xiao , Jiang Yangyang , Zhou Abby Jingzi , Zhou Steven Shijin , Wu Daoyou 
Published: February 2025

PurposeDrawing on social information processing theory and work-as-calling theory, this study explores the impact of mentoring within the Chinese context – which encompasses the roles of both mentors and senior mentees – on the calling and turnover intention of junior mentees in the hospitality industry.Design/methodology/approachSurvey questionnaires were administered to collect 222 valid responses from frontline hotel employees in China. Partial least squares structural equation modeling (PLS-SEM) was adopted to test the hypotheses. We further conducted several post hoc interviews to gain a deeper understanding of the relationships examined.FindingsChinese mentoring positively affects mentees’ perceiving and living a calling, which in turn reduces their turnover intention. Junior mentees’ liking of their senior mentees further amplifies the negative effect of living a calling on their turnover intention.Originality/valueThis study enriches the literature on calling by exploring the antecedents of perceiving a calling and the boundary conditions that enhance the effect of living a calling on turnover intention. Additionally, our study highlights the unique aspect of Chinese mentorship as resembling a family-like relationship, a characteristic shaped by the pervasive influence of Confucianism in China, which enriches the existing literature on mentorship studies.
Consumer wellbeing through fitness apps: a psychological ownership perspective
Authors: Gupta Shelleka 
Published: February 2025

Purpose
This study aims to undertake an examination of the determinants of psychological ownership (PO) in case of fitness apps and also attempt to understand the relationship between PO and consumer wellbeing (CWB). This relationship is also explored to understand the role of personal innovativeness (PI) and health consciousness (HC) as moderators.

Design/methodology/approach
The present study uses the PO theory as the base model for the study. The data was collected through face to face survey method and a total of 315 valid responses were received in a period of five months. All the hypothesized relationships were tested by using partial least square structural equation modeling.

Findings
This study confirms the significant relationship between PO and CWB. Control, investment of self and intimate knowledge of fitness apps are the significant factors that lead to the PO of these apps. The findings put forth HC as a significant and PI as an insignificant moderator.

Practical implications
This study gives important inputs to app developers for increasing the PO toward these fitness apps. The PO has a proven record for delivering positive behavioral outcomes for marketers but can also act as igniter to boost CWB. The findings suggest that marketers should target users with high HC who can turn out to be role models and significantly influence people around them.

Originality/value
This study is one of the few studies to examine the fitness apps by using the PO perspective. Further, this study demonstrates the role of PO in generating CWB and thus contributes to the knowledge of fitness app research by filling the gap in post-adoption studies of these apps.
Advancing information search through GenAI: the roles of search type, travel motive and GenAI customization level
Authors: Luo Xiaoyan , Xu Ding , Li Yuan (William) , Wan Lisa C. 
Published: February 2025

Purpose
The advancements in generative artificial intelligence (GenAI) encourage disruptive transformation in the hospitality industry. Previous discussions predominantly focused on the impact of AI-powered agents on the labor force. This research extends previous studies by investigating the feasibility of GenAI as an information search agent in comparison to the predominant role of search engines.

Design/methodology/approach
Based on the Tourist Online Information Search Behavior framework, the authors proposed that consumers’ GenAI adoption may vary upon search purpose (search type), individual differences (travel motive) and situational differences (GenAI task-oriented customization level). Four studies with a total number of 813 participants were conducted.

Findings
Taking GenAI over traditional search engines for pre-trip information search significantly increased with a non-decision-based (vs decision-based) purpose. To enhance the adoption of GenAI in its less effective but more important decision-based situations, the authors proposed and confirmed the incremental effect of utilitarian travel motives and task-oriented customization levels.

Practical implications
This study highlights GenAI’s potential as an information communication technology (ICT). This encourages tourism and hospitality businesses to consider integrating GenAI to strengthen ICT services. Moreover, search type, travel motive and task-oriented customization level are important in deploying GenAI for ICT improvement.

Originality/value
This study deepens the understanding of GenAI adoption in the tourism and hospitality sector by elaborating on the GenAI-as-ICT perspective and offers fresh insights into AI for pre-trip or pre-consumption information search.
Effect of top management knowledge value, knowledge-oriented culture and rewards on innovation performance and quality: the bridging contribution of knowledge-sharing process
Authors: Abdelwahed Nadia A. Abdelmegeed , Bano Safia , Al Doghan Mohammed A. , Soomro Bahadur Ali 
Published: February 2025

Purpose
Currently, innovation performance (IP) and innovation quality (IQ) are essential intertwined constructs that help small- and medium-sized enterprises (SMEs) thrive in a competitive business environment and achieve long-term success and sustainability. This paper aims to examine the effect of top management knowledge values (TMKVs), knowledge-oriented culture (KOC) and rewards on IP and IQ through knowledge sharing.

Design/methodology/approach
The authors used a deductive cross-sectional data approach and a standardized questionnaire adopted from the literature to obtain responses from the employees of Egyptian manufacturing SMEs. The authors based this study’s findings on 316 usable samples by applying the purposive sampling technique.

Findings
Using structural equation modeling (SEM) with path analysis using SmartPLS4, the findings of this study demonstrate that TMKV positively affects IP but not IQ. On the one hand, the KOC and knowledge-sharing process (KSP) are positive enablers of IP and IQ. On the other hand, knowledge-based reward (KBR) has an insignificant effect on IP and IQ. Moreover, while KSP mediates TMKV’s and KOC’s connections with IP and IQ, it does not mediate KBR’s relationship with IP and IQ.

Practical implications
This study’s findings will help policymakers and planners create strategies through knowledge management to improve employees’ vision, commitment and dedication, culminating in a favourable impact on IP and IQ. These findings highlight the need to foster a knowledge-based culture that promotes communication networks, establishes trust and enables individuals to make decisions to enhance organizational success, IP and IQ.

Originality/value
In the case of a developing country, this study helps to fill the gaps by offering an integrated framework that simultaneously explores knowledge management enablers, IP and IQ.
Mediating role of eWOM’s in green behavior interaction and corporate social responsibility: a stakeholder theory perspective
Authors: Saqib Zulkaif Ahmed , Ikram Muhammad , Qin Luo 
Published: February 2025

Purpose
This research aims to explore how policymakers manage the information and communication of green behavior on social platforms to support their growth in corporate social responsibility (CSR). Social platforms play a strategic and interactive role through electronic word-of-mouth (eWOM), which brings unprecedented green purchase opportunities.

Design/methodology/approach
Based on stakeholder theory, a conceptual framework is designed to investigate the influence of green behavior interactions (GBIs) on CSR under the mediating effects of eWOM subfactors (eWC = eWOM communication, eWIA = eWOM information adoption and eWSC = eWOM source credibility). Data from 414 regular stakeholders of logistics firms were analyzed via structural equation modeling.

Findings
The results reveal positive influences of the GBI on eWC, eWIA, eWSC and CSR, with path coefficients of 0.329, 0.713, 0.809 and 0.316, respectively. The mediating effects of eWC and eWSC from the GBI to CSR were discovered with path coefficients of 0.105 and 0.226, respectively. Coincidentally, the mediating role of eWIA was positive but not supported. The outcomes of this study indicate that the administration of GBI and eWOM from a green purchase perspective is essential for a firm. The CSR practices of green logistics firms can be successfully supported by the administration of the GBI and eWOM indicators.

Originality/value
This study develops a novel multidimensional framework that illustrates the impact of eWOM on reducing information asymmetry, enhancing credibility, supporting informed decision-making and improving green consumer behavior. By amplifying positive reviews, increasing engagement and establishing a feedback loop, this framework aims to provide comprehensive insights into the efficacy of eWOM for firms’ products and services.
Ensuring force sensing reliability for robot variable stiffness actuator by elastic deflection estimation
Authors: Xu Yapeng , Xin Tongshuai , Guo Kai , Ma Jun , Cao Yang , Li Xiaoke 
Published: February 2025

Purpose
This study aims to improve the force sensing performance of the robot joint for the safety and flexibility of physical human–robot interaction.

Design/methodology/approach
A force sensing mechanism (FSM) for an S-shaped spring of a robot variable stiffness actuator (VSA) was designed. The yield strength of the spring material, geometric and assembly structure constraints of the VSA are all considered for the actuator deflection limit design. The elastic deformation model is solved in reverse to obtain the local deformation limit profile of the S-spring at different spring angles. The deformation limit mechanism is manufactured by three-dimensional printing and assembled with S-springs. The force sensing function for the VSA is achieved by the input and output shaft encoders and stiffness model. The FSM is verified by torque-deflection experiments with variable stiffness.

Findings
The yield strength of the S-spring material is the strictest constraint for elastic deformation. Experimental results show that the external force can be quickly and reliably perceived. As the spring angle increases (stiffness increases), the hysteresis and nonlinear error decrease. Under the constraint of the FSM, the maximum deflection also decreases rapidly.

Originality/value
The designed FSM based on the deformation and stiffness model provides a comprehensive design reference in a VSA with nonlinear elastic mechanisms, which is ignored but important for exploring the VSAs potential.
Impact of environmental quality, renewable and non-renewable energy and governance quality on sustainable development: evidence from emerging economies
Authors: Mahmoodi Majid , Dahmardeh Ghaleno Nazar 
Published: February 2025

PurposeThe present study aims to examine the influence of environmental quality, renewable energy, non-renewable energy and quality of governance on sustainable development in two panels of 23 Asian and 8 European emerging countries during the 1996–2022 period.Design/methodology/approachThe present study employed second-generation methods of panel data analysis, which account for cross-sectional dependency and heterogeneity to achieve a more reliable conclusion.FindingsThe augmented mean group and common correlated effects mean group estimation findings exhibit the negative influence of environmental degradation and non-renewable energy on sustainable development, whereas the findings exhibit the positive effect of renewable energy and governance quality on sustainable development.Practical implicationsThe findings point out to policymakers and governments the importance of the adoption and implementation of policies to protect the environment, as well as promoting renewable energy incentive policies. Moreover, enhancing governance quality and striving towards good governance is essential for the successful adoption and implementation of energy and environment policies, as well as achieving sustainable development goals.Originality/valueThe present research contributes to the existing related literature in several ways. Adjusted net saving (ANS) is employed as a comprehensive indicator of sustainable development and ecological footprint (EFP) is employed as an exhaustive indicator of the environment’s quality rather than carbon dioxide emissions. In overall, this study is the first, to the best of our awareness, to simultaneously consider ANS, EFP and governance quality for examining the relationship among energy, environmental quality and sustainable development, especially in Asian and European emerging economies.
Early stage cost prediction model for Indian building construction projects using artificial neural networks
Authors: Padala S.P. Sreenivas , Goyal Anshul 
Published: February 2025

Purpose
This paper aims to enhance early-stage cost estimation in construction projects, a critical factor in project feasibility, funding, resource allocation and scheduling. Traditional cost estimation approaches suffer from limitations such as the absence of structured methodologies, assumptions of linear cost relationships, prolonged processes and expert judgment variations. To address these challenges, this study proposes a reliable cost prediction model based on artificial neural networks (ANNs) for building construction projects in India.

Design/methodology/approach
To develop cost prediction model, this study collected data from 377 building construction projects in India, encompassing 17 essential cost parameters. The methodology involves data preprocessing, constructing features and fine-tuning ANN hyperparameters meticulously to achieve optimal performance.

Findings
The research showcases effectiveness of cost prediction model, evident in significantly reduced mean square error values. ANN-based prediction model excels in handling nonlinear cost dependencies and diverse project complexities, making it a valuable tool for early-stage cost estimation.

Research limitations/implications
ANN-based cost prediction model is primarily designed for predicting costs associated with structural works of building projects.

Practical implications
The proposed solution offers stakeholders a robust data-driven decision-making tool during initial phases of construction projects. This can lead to more successful and economically viable outcomes.

Originality/value
This research examines the drawbacks of traditional cost estimation methods by presenting a data-driven approach leveraging machine learning. It significantly improves precision of early cost forecasts in construction projects while offering practical value to industry.
Practice Briefing: The inception and preliminary performance analysis of REITs in the Kingdom of Saudi Arabia
Authors: Marzuki Muhammad Jufri , Newell Graeme 
Published: February 2025

PurposeThe Saudi REIT market’s introduction in 2016 was part of the Kingdom of Saudi Arabia’s Vision 2030 master plan to diversify the country's sources of revenue and reform its financial sector. Despite the Saudi REIT market’s nascent state, it has experienced significant growth in a short period of time, being the largest REIT market in MENA. Saudi REITs are designed using well-established global REIT standards to facilitate efficient capital influx into commercial property investment opportunities in Saudi Arabia. The core aim of this paper is to highlight the development of Saudi REITs and empirically assess their performance over the period from December 2018 to December 2023.Design/methodology/approachUsing monthly total returns in local currency (SAR), the risk-adjusted performance and portfolio diversification attributes of Saudi REITs are assessed. A series of optimal portfolios are constructed to identify the potential added-value role of Saudi REITs in a multi-asset framework.FindingsWhilst Saudi REITs’ average annual return performance is lower than that of stocks, their annual returns are delivered with less volatility, thus giving a competitive overall risk-adjusted performance against other asset classes. This is a testament to Saudi REITs’ higher income return performance due to the fiscal-efficient framework. Further, when Saudi REITs are introduced in a stocks-bonds portfolio, they are able to improve the portfolio’s overall return whilst reducing the volatility, with their allocation in the asset mix observed to effectively scale throughout the portfolio risk-return spectrum.Practical implicationsSaudi REITs are an emerging investment opportunity for investors seeking exposure in a relatively stable and fast-growing MENA property market. As Saudi Arabia makes continuous reforms to improve the accessibility and transparency of its commercial property market, Saudi REITs are the most effective way to date for domestic and overseas investors to obtain exposure to the Kingdom’s property investment opportunities. Importantly, the encouraging preliminary results as identified in this paper provide valuable insight into the potential trajectory of Saudi REITs, given their significant contributing role to achieve the strategic objectives of Vision 2030.Originality/valueThis paper is the first empirical investigation that provides a preliminary performance validation of Saudi REITs as a listed pathway to commercial property exposure in Saudi Arabia. This study provides empirical evidence that enables more informed and practical decision-making in property investment, particularly in understanding the strategic importance of Saudi REITs within an investment portfolio.
Bibliometric analysis of artificial intelligence in high-to-room temperature superconductors: insights from the Scopus database
Authors: Pramono Andika Widya , Nurhakim Arif 
Published: February 2025

Purpose
This bibliometric analysis aims to comprehensively explore the intersection of artificial intelligence (AI) and high-to-room-temperature superconductors. Focusing on scientific literature, the study investigates trends, collaboration patterns and impactful publications in this interdisciplinary field.

Design/methodology/approach
The research employs an advanced search query in the Scopus database, targeting articles on the development of superconductors using artificial intelligence. Data collection involves executing the query, saving the results as a CSV file and analyzing it using R-Studio and VOSviewer. Statistical tools, T-tests, regression analysis and Python coding are utilized to enhance the depth of analysis.

Findings
The analysis spans various dimensions, including the overview of bibliometric characteristics, annual scientific production, average citations per year, sources of publications and source production over time. Noteworthy findings include a sustained growth in annual scientific production, a peak in average citations in specific years and the identification of influential journals shaping the field.

Research limitations/implications
While the analysis provides valuable insights, limitations include the potential influence of research biases and the exclusion of non-English articles. Further exploration is encouraged to address these limitations and gain a more nuanced understanding of the field.

Practical implications
Practically, this study aids researchers, practitioners and stakeholders in staying informed, identifying collaboration opportunities and contributing meaningfully to the ongoing growth and impact of high-to-room-temperature superconductors using artificial intelligence.

Social implications
Socially, the study underscores the collaborative and global nature of research in this field, emphasizing the shared endeavor worldwide to advance the understanding and application of superconductors through artificial intelligence.

Originality/value
This research contributes to the originality of the scientific landscape by offering a comprehensive analysis of the development of high-to-room-temperature superconductors with artificial intelligence. The utilization of advanced bibliometric techniques and the identification of key trends and sources enhance the understanding of this emerging and interdisciplinary research domain.