bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting and analysing initiator crime environments based on machine learning for improving urban safety
Authors: Hwang Yoonjae , Jung Sungwon , Park Eun Joo 
Published: February 2024

PurposeInitiator crimes, also known as near-repeat crimes, occur in places with known risk factors and vulnerabilities based on prior crime-related experiences or information. Consequently, the environment in which initiator crimes occur might be different from more general crime environments. This study aimed to analyse the differences between the environments of initiator crimes and general crimes, confirming the need for predicting initiator crimes.Design/methodology/approachWe compared predictive models using data corresponding to initiator crimes and all residential burglaries without considering repetitive crime patterns as dependent variables. Using random forest and gradient boosting, representative ensemble models and predictive models were compared utilising various environmental factor data. Subsequently, we evaluated the performance of each predictive model to derive feature importance and partial dependence based on a highly predictive model.FindingsBy analysing environmental factors affecting overall residential burglary and initiator crimes, we observed notable differences in high-importance variables. Further analysis of the partial dependence of total residential burglary and initiator crimes based on these variables revealed distinct impacts on each crime. Moreover, initiator crimes took place in environments consistent with well-known theories in the field of environmental criminology.Originality/valueOur findings indicate the possibility that results that do not appear through the existing theft crime prediction method will be identified in the initiator crime prediction model. Emphasising the importance of investigating the environments in which initiator crimes occur, this study underscores the potential of artificial intelligence (AI)-based approaches in creating a safe urban environment. By effectively preventing potential crimes, AI-driven prediction of initiator crimes can significantly contribute to enhancing urban safety.
Benchmarking design-thinking as a tool for education: a systematic review and future research agenda
Authors: Bathla Arushi , Chawla Ginni , Gupta Ashish 
Published: February 2024

PurposeDesign-thinking (DT) in education has attracted significant interest from practitioners and academics, as it proffers new-age thinking to transform learning processes. This paper synthesises extant literature and identifies the current intellectual frontiers.Design/methodology/approachFirst, a systematic-literature-review was undertaken employing a robust process of selecting papers (from 1986 to 2022) by reading titles, abstracts and keywords based on a required criterion, backward–forward chaining and strict quality evaluations. Next, a bibliometric analysis was undertaken using VOSviewer. Finally, text analysis using RStudio was done to trace the implications of past work and future directions.FindingsAt first, we identify and explain 12 clusters through bibliometric coupling that include “interdisciplinary-area”, “futuristic-learning”, “design-process” and “design-education”, amongst others. We explain each of these clusters later in the text. Science, Technology, Engineering, Arts and Mathematics (STEAM), management education, design and change, teacher training, entrepreneurship education and technology, digital learning, gifted education and course development) Secondly, through co-word-analysis, we identify and explain four additional clusters that include “business education and pedagogy”, “content and learning environment”, “participants and outcome” and finally, “thinking-processes”. Based on this finding, we believe that the future holds a very positive presence sentiment for design thinking and education (DT&E) in changing the 21st century learning.Research limitations/implicationsFor investigating many contemporary challenges related to DT&E, like virtual reality experiential learning, sustainability education, organisational learning and management training, etc. have been outlined.Practical implicationsAcademics may come up with new or improved courses for the implementation of DT in educational settings and policymakers may inculcate design labs in the curricula to fortify academic excellence. Managers who would employ DT in their training, development and policy design, amongst others, could end up gaining a competitive advantage in the marketplace.Originality/valueThis study conducted a comprehensive review of the field, which to our limited knowledge, no prior studies have been done so far. Besides, the study also outlines interesting research questions for future research.
Key performance indicators for hospital planning and construction: a systematic review and meta-analysis
Authors: Liu Wenque , Chan Albert P.C. , Chan Man Wai , Darko Amos , Oppong Goodenough D. 
Published: February 2024

PurposeThe successful implementation of hospital projects (HPs) tends to confront sundry challenges in the planning and construction (P&C) phases due to their complexity and particularity. Employing key performance indicators (KPIs) facilitates the monitoring of HPs to advance their successful delivery. This study aims to comprehensively investigate the KPIs for hospital planning and construction (HPC).Design/methodology/approachThe KPIs for HPC were identified through a systematic review. Then a comprehensive assessment of these KPIs was performed utilizing a meta-analysis method. In this process, basic statistical analysis, subgroup analysis, sensitive analysis and publication bias analysis were performed.FindingsResults indicate that all 27 KPIs identified from the literature are significant for executing HPs in P&C phases. Also, some unconventional performance indicators are crucial for implementing HPs, such as “Project monitoring effectiveness” and “Industry innovation and synergy,” as their high significance is reflected in this study. Despite the fact that the findings of meta-analysis are more trustworthy than those of individual studies, a high heterogeneity still exists in the findings. It highlights the inherent uncertainty in the construction industry. Hence, this study applied subgroup analysis to explore the underlying factors causing the high level of heterogeneity and used sensitive analysis to assess the robustness of the findings.Originality/valueThere is no consensus among the prior studies on KPIs for HPC specifically and their degree of significance. Additionally, few reviews in this field have focused on the reliability of the results. This study comprehensively assesses the KPIs for HPC and explores the variability and robustness of the results, which provides a multi-dimensional perspective for practitioners and the research community to investigate the performance of HPs during the P&C stages.
Digital writing with AI platforms: the role of fun with/in generative AI
Authors: Stornaiuolo Amy , Higgs Jennifer , Jawale Opal , Martin Rhianne Mae 
Published: February 2024

Purpose
With the rapid advancement of generative artificial intelligence (AI), it is important to consider how young people are making sense of these tools in their everyday lives. Drawing on critical postdigital approaches to learning and literacy, this study aims to center the experiences and perspectives of young people who encounter and experiment with generative AI in their daily writing practices.

Design/methodology/approach
This critical case study of one digital platform – Character.ai – brings together an adolescent and adult authorship team to inquire about the intertwining of young people’s playful and critical perspectives when writing on/with digital platforms. Drawing on critical walkthrough methodology (Light et al., 2018), the authors engage digital methods to study how the creative and “fun” uses of AI in youths’ writing lives are situated in broader platform ecologies.

Findings
The findings suggest experimentation and pleasure are key aspects of young people’s engagement with generative AI. The authors demonstrate how one platform works to capitalize on these dimensions, even as youth users engage critically and artfully with the platform and develop their digital writing practices.

Practical implications
This study highlights how playful experimentation with generative AI can engage young people both in pleasurable digital writing and in exploration and contemplation of platforms dynamics and structures that shape their and others’ literate activities. Educators can consider young people’s creative uses of these evolving technologies as potential opportunities to develop a critical awareness of how commercial platforms seek to benefit from their users.

Originality/value
This study contributes to the development of a critical and humanist research agenda around generative AI by centering the experiences, perspectives and practices of young people who are underrepresented in the burgeoning research devoted to AI and literacies.
Unpacking the effects of performance feedback on strategic change: the moderating role of industry conditions
Authors: Alnahedh Mishari , Alrashdan Abdullatif 
Published: February 2024

Purpose
This paper aims to integrate insights from the behavioral theory of the firm and the dynamic capabilities perspective to explain how the historical and social attainment discrepancies motivate firms to change. Specifically, this paper proposes that a negative historical attainment discrepancy encourages the firm to engage in strategic change to solve its performance problems. In contrast, this paper advanced that a positive social attainment discrepancy motivates strategic change as a mechanism to bolster the firm’s position within the industry. Further, this paper integrated the moderating effects of industry dynamism and industry munificence.

Design/methodology/approach
This paper tests hypotheses using panel data on 2,435 US public firms over the years from 1996 to 2018. This paper uses a fixed-effects regression model to empirically test these hypotheses.

Findings
This paper finds empirical support for the effects of both the negative historical attainment discrepancy and the positive social attainment discrepancy on the firm’s tendency to engage in strategic change. As for the hypothesized moderating effects, this paper finds that industry munificence accentuated the effects of both attainment discrepancies on the firm’s tendency to engage in strategic change. However, the results do not support the hypothesized moderating effect of industry dynamism on either of these attainment discrepancies.

Originality/value
This paper contributes to the research on the separate effects of historical and social comparisons within the context of strategic change. Further, the paper bolsters our understanding of how performance feedback increases the firm’s tendency to change. Finally, the paper integrates theoretical views from the behavioral theory of the firm and the dynamic capabilities perspective on how socially high-performing firms may build and sustain their competitive advantage through organizational change.
Harnessing of carboxy containing starch nanoparticles as an adsorbent for Cd (II) ions and methylene blue from waste water effluent: synthesis, metrological characterization and properties
Authors: Mostafa Khaled , El-Sanabary Azza 
Published: February 2024

Purpose
The novelty addressed here is undertaken by using tailor-made and fully characterized starch nanoparticles (SNPs) having a particle size ranging from 80 to 100 nm with a larger surface area, biodegradability and high reactivity as a starting substrate for cadmium ions and basic dye removal from wastewater effluent. This was done via carboxylation of SNPs with citric acid via esterification reaction using the dry preparation technique, in which a simple, energy-safe and sustainable process concerning a small amount of water, energy and toxic chemicals was used. The obtained adsorbent is designated as cross-linked esterified starch nanoparticles (CESNPs).

Design/methodology/approach
The batch technique was used to determine the CESNPs adsorption capacity, whereas atomic adsorption spectrometry was used to determine the residual cadmium ions concentration in the filtrate before and after adsorption. Different factors affecting adsorption were examined concerning pH, contact time, adsorbent dose and degree of carboxylation. Besides, to validate the esterification reaction and existence of carboxylic groups in the adsorbent, CESNPs were characterized metrologically via analytical tools for carboxyl content estimation and instrumental tools using Fourier-transform infrared spectroscopy (FTIR) spectra and scanning electron microscopy (SEM) morphological analysis.

Findings
The overall adsorption potential of CESNPs was found to be 136 mg/g when a 0.1 g adsorbent dose having 190.8 meq/100 g sample carboxyl content at pH 5 for 60 min contact time was used. Besides, increasing the degree of carboxylation of the CESNPs expressed as carboxyl content would lead to the higher adsorption capacity of cadmium ions. FTIR spectroscopy analysis elucidates the esterification reaction with the appearance of a new intense peak C=O ester at 1,700 cm−1, whereas SEM observations reveal some atomic/molecules disorder after esterification.

Originality/value
The innovation addressed here is undertaken by studying the consequence of altering the extent of carboxylation reaction expressed as carboxyl contents on the prepared CESNPs via a simple dry technique with a small amount of water, energy and toxic chemicals that were used as a sustainable bio nano polymer for cadmium ions and basic dye removal from wastewater effluent in comparison with other counterparts published in the literature.
Hidden truncation model with heteroskedasticity: S&P 500 index returns reexamined
Authors: Belhachemi Rachid 
Published: February 2024

Purpose
This paper aims to introduce a heteroskedastic hidden truncation normal (HTN) model that allows for conditional volatilities, skewness and kurtosis, which evolve over time and are linked to economic dynamics and have economic interpretations.

Design/methodology/approach
The model consists of the HTN distribution introduced by Arnold et al. (1993) coupled with the NGARCH type (Engle and Ng, 1993). The HTN distribution nests two well-known distributions: the skew-normal family (Azzalini, 1985) and the normal distributions. The HTN family of distributions depends on a hidden truncation and has four parameters having economic interpretations in terms of conditional volatilities, kurtosis and correlations between the observed variable and the hidden truncated variable.

Findings
The model parameters are estimated using the maximum likelihood estimator. An empirical application to market data indicates the HTN-NGARCH model captures stylized facts manifested in financial market data, specifically volatility clustering, leverage effect, conditional skewness and kurtosis. The authors also compare the performance of the HTN-NGARCH model to the mixed normal (MN) heteroskedastic MN-NGARCH model.

Originality/value
The paper presents a structure dynamic, allowing us to explore the volatility spillover between the observed and the hidden truncated variable. The conditional volatilities and skewness have the ability at modeling persistence in volatilities and the leverage effects as well as conditional kurtosis of the S&P 500 index.
The effects of celebrity endorser on consumer advocacy behavior through the customization and entertainment intention – A multivariate analysis
Authors: Kalam Abul , Goi Chai Lee , Tiong Ying Ying 
Published: February 2024

Purpose
The purpose of this study is to investigate the effects of celebrity endorsers on consumer advocacy, customization and entertainment intentions based on the notion of the stimulus–organism–response (SOR) framework. In addition, this study aims to examine the mediating and moderating role of customization and entertainment intentions on the proposed relationships. The authors also intend to highlight the comparative effects between male and female young social media consumers on those proposed associations.

Design/methodology/approach
In the pursuit of comprehensive and rigorous data collection, this study adopted a quantitative methodology using a meticulously crafted questionnaire. The questionnaire survey was conducted in major cities of Malaysia using the convenience and snowball sampling techniques. A total of 576 responses were collected, even though 549 retorts were used for data analysis. In this investigation, the authors strategically used covariance-based structural equation modeling through the use of AMOS v. 24 as the primary data analysis tool. Augmenting the analytical depth, the authors also conducted a supplementary bootstrap analysis. The additional layers of examination were crucial for appraising the mediating and moderating effects inherent within the model, in which the PROCESS MACRO v.4.20 was used.

Findings
The results of this study revealed the significant direct positive effects of celebrity endorsers on consumer customization, entertainment and advocacy intentions. Consumer customization and entertainment intentions also found significant direct affirmative effects on consumer advocacy intention, along with the significant direct positive effects of consumer entertainment intention on consumer customization intention. The results further revealed that consumer customization and entertainment intentions cannot mediate the relationship between celebrity endorsers and advocacy intention. The entertainment intention also declined the mediating effects between celebrity endorsers and consumer customization intention. On the contrary, consumer customization intention significantly and positively, and entertainment intention also significantly but negatively, moderate the association between celebrity endorsers and consumer advocacy intention. This study also illustrates that the effects of those examined relationships differ between male and female young social media consumers.

Originality/value
This study investigates the impact of celebrity endorsers on consumer behavior, focusing on their customization, entertainment and advocacy intentions. It extends current SOR framework, enhances source credibility theory, fills gaps in the literature on social media brand engagement and underscores the significance of customization and entertainment intentions. The findings provide insights for managers aiming to harness consumer brand advocacy through celebrity endorsers effectively.
Rapid quantitative detection system for measles virus‐neutralizing antibodies using HiBiT‐tagged virus‐like particles
Authors: Okura Takashi , Miyakawa Kei , Tahara Maino , Someya Kenji , Seki Fumio , Nishi Mayuko , Otsuki Noriyuki , Ryo Akihide 
Published: February 2024

AbstractImmunological testing to detect neutralizing antibodies (NAbs) is important in measles (MV) infection control. Currently, the plaque reduction neutralization test is the only credible method for measuring actual virus NAbs; however, its feasibility is hampered by drawbacks, such as long turnaround times, low throughput, and the need for laboratory biosafety equipment. To solve these problems, we developed a simple and rapid MV‐NAb detection system using lentivirus‐based virus‐like particles incorporated with the NanoLuc fragment peptide HiBiT comprising the MV fusion protein and hemagglutinin on their exterior surface. Overall, this simple, safe, and rapid method could be used to detect MV NAbs.
Geese migrating over the Pacific Ocean select altitudes coinciding with offshore wind turbine blades
Authors: Weiser Emily L. , Overton Cory T. , Douglas David C. , Casazza Michael L. , Flint Paul L. 
Published: February 2024

Abstract

Renewable energy facilities are a key part of mitigating climate change, but can pose threats to wild birds and bats, most often through collisions with infrastructure. Understanding collision risk and the factors affecting it can help minimize impacts on wild populations. For wind turbines, flight altitude is a major factor influencing collision risk, and altitude‐selection analyses can evaluate when and why animals fly at certain altitudes under certain conditions.

We used GPS tags to track Pacific Flyway geese (Pacific greater white‐fronted goose, tule greater white‐fronted goose and lesser snow goose) on transoceanic migrations between Alaska and the Pacific Coast of the contiguous United States, an area where offshore windfarm development is beginning. We evaluated how geographic and environmental covariates affected (1) whether birds were at rest on the water versus in flight (binomial model) and (2) altitude selection when in flight (similar to a step‐selection framework). We then used a Monte Carlo simulation to predict the probability of flying at each altitude under various conditions, considering both the fly/rest decision and altitude selection.

In both spring and fall, geese showed strong selection for altitudes within the expected rotor‐swept zone (20–200 m asl), with 56% of locations expected to be within the rotor‐swept zone under mean daylight conditions and 28% at night. This indicates a high possibility that migrating geese may be at risk of collision when passing through windfarms. Although there was some variation across subspecies, geese were most likely to be within the rotor‐swept zone with little wind or light tailwinds, low clouds, little to no precipitation and moderate to cool air temperatures. Geese were unlikely to be in the rotor‐swept zone at night, when most individuals were at rest on the water.

Synthesis and applications. These results could be used to inform windfarm management, including decisions to shut down turbines when collision risk is high. The altitude‐selection framework we demonstrate could facilitate further study of other bird species to develop a holistic view of how windfarms in this area could affect the migratory bird community as a whole.