bluuebunny/crossref_metadata_2025_split huggingface dataset:
What drives the real estate market? Could behavioral indicators be useful in house pricing models?
Authors: Vasileiou Evangelos , Hadad Elroi , Melekos Georgios 
Published: April 2024

PurposeThe objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.Design/methodology/approachIn our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.FindingsOur findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.Practical implicationsThe results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.Originality/valueThis is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.
A clothing pattern generating framework based on scanned human body model
Authors: Xiao Boxiang , Liu Zhengdong , Shi Jia , Wang Yuanxia 
Published: April 2024

PurposeAccurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.Design/methodology/approachPhysics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.FindingsThe results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.Originality/valueThe main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.
Corporate–NGO collaboration and CSR disclosure – the moderating role of corporate profitability
Authors: Ali Waris , Frynas J. George , Wilson Jeffrey 
Published: April 2024

Purpose This research investigates the influence of corporate–NGO collaborations on corporate social responsibility (CSR) disclosure measured in three different ways (i.e. extent, level and quality) in low-income developing economies. Additionally, it examines the moderating effect of corporate profitability in the relationship between corporate–NGO collaborations and CSR disclosure.Design/methodology/approach This research uses multivariate regression analysis based on data collected from 201 non-financial firms listed on the Pakistan Stock Exchange (PSE).Findings The findings reveal that corporations with NGO partnerships are more likely to disclose CSR information and provide high-quality information regarding workers, the environment and community-related issues. Further, corporate profitability positively moderates the corporate–NGO collaborations and CSR disclosure relationship.Research limitations/implications Research limitations are presented in the conclusion section.Practical implications The findings underline the crucial significance of NGOs and their associated normative isomorphism logics for CSR disclosure in low-income countries with weak law enforcement and relatively ineffective state institutions, which were previously believed to lack such institutions.Originality/value While some research has suggested that companies in developing countries perceive significant pressure from NGOs to adopt social disclosure, no study has specifically explored how internally driven corporate–NGO collaboration (as opposed to external NGO activist pressures) promotes CSR disclosure specifically in developing economies.
Effectiveness of internal auditing from the lens of internal audit factors: empirical findings from the banking sector of Bangladesh
Authors: Khanam Zobaida 
Published: April 2024

Purpose
This study aims to assess the impact of determinants on the effectiveness of internal audit (IA) within the banking industry of Bangladesh.

Design/methodology/approach
The data was obtained through 152 survey questionnaires from a total of 43 privately owned and six state-owned commercial banks in Bangladesh. The analysis was conducted using structural equation modeling.

Findings
The findings demonstrate that the independence of internal auditors and the quality of IA substantially impact enhancing the efficiency of IA. On the other hand, the competence of internal auditors and management support in IA functions do not significantly impact the effectiveness of IA.

Practical implications
The study’s findings may have significant policy implications for the government, regulators, internal auditors, management committees and other stakeholders in establishing programmes to enhance the efficacy of IA as a component of banking audit management reforms.

Originality/value
This study makes three distinct contributions to the existing literature. Firstly, previous literature focused on the determinants affecting the external audit efficiency of the public companies and banking sectors in Bangladesh (Hasan, 2018; M. M. U. Reza, 2021). In this study, the author enhances the research by presenting empirical findings on the IA effectiveness of banks. Secondly, the author expands the research by incorporating both private and state-owned commercial banks as samples. Thirdly, the study is unique given that it investigates the effectiveness of IA in response to the recent financial scandals in the banking industry of Bangladesh (The Daily Star, 2023).
CSR perceptions and practices in small hotels in urban cities
Authors: Khodaviren Maryam , Dhar-Bhattacharjee Sunrita 
Published: April 2024

PurposeThis study aims to examine the perception and practices related to Corporate Social Responsibility (CSR) implemented in Small and Medium-sized Enterprises (SMEs), focussing on small hotels in London.Design/methodology/approachA qualitative research design comprising detailed semi-structured interviews was employed with 12 small hotel owner-managers in central London and its outskirts. The study adopts a social constructionist approach to explore CSR perspectives and practices, along with a social capital framework to investigate how CSR is perceived at the individual level and consequently manifested into CSR practices.FindingsThe findings indicate that a small hotel’s implementation of CSR is influenced by long-term versus short-term considerations, as well as socio-economic and socio-political conditions. Individual-level factors, like hoteliers’ CSR conceptualisation and personal and business values, affect CSR adoption in small hotels. Lastly, institutional-level factors, such as ineffective institutional participation and the hotelier’s cultural background against the cosmopolitan context of a big city, have contributed to a muted response to socially responsible issues.Research limitations/implicationsThis study was conducted with a limited sample of 12 participants from small hotels in London and its outskirts, which may limit the generalisability of the findings. Future research could enhance these findings by involving a larger and more diverse group of participants from various urban areas, potentially employing a quantitative research approach for broader applicability. This study’s insights can guide policymakers in educating small business owners on CSR benefits and implementation. It also proposes how governments could encourage sustainable practices among small hotels seeking to enhance their reputation. Moreover, these findings enable small businesses to develop their stakeholder strategies for greater CSR initiatives.Originality/valueThis study integrates social capital theory into investigating CSR in small hotels in London, broadening the literature on CSR perception and integration, particularly in SMEs and the hospitality sector.
An ontology-driven model for hospital equipment maintenance management: a case study
Authors: Titah Mawloud , Bouchaala Mohammed Abdelghani 
Published: April 2024

Purpose This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.Design/methodology/approach The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.Findings Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.Originality/value An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.
Why and when is frequent supervisory negative feedback undesirable? The role of trust in supervisor and attribution of supervisor motives
Authors: Guo Wenjing , Jiang Yuan , Zhang Wei , Wang Haizhen 
Published: April 2024

PurposeResearch on the effects of feedback frequency has reported mixed findings. To tackle this problem, the current study focuses on specific feedback signs (i.e. negative feedback). By integrating the face management theory and attribution theory, this study examined the mediating effect of trust in supervisors and the moderating effect of employee-attributed performance promotion motives for negative feedback.Design/methodology/approachA field study with 176 participants and two supplemental experiments with 143 and 100 participants, respectively, were conducted to test the theoretical model.FindingsResults revealed that the frequency of supervisory negative feedback negatively influenced employees’ trust in supervisors, which in turn influenced employees’ perceptions of feedback utility and learning performance. These indirect effects can be alleviated when employees have high degrees of performance promotion attribution for supervisor motives.Originality/valueThis research extends feedback research by integrating feedback frequency with a specific sign of feedback and revealing a moderated mediation effect of the negative feedback frequency.
An advanced netnographic framework for analyzing brand community overlap conflicts in the phygital brand community (PBC) environment
Authors: Levy Yann , Sabri Ouidade 
Published: April 2024

Purpose
This study aims to introduce and define the concept of phygital brand community (PBC). It discusses the potential conflicts that can arise from engaging in multiple PBCs and propose an enriched netnographic methodological approach to explore the role of PBC engagement overlap and its influence on the phygital experience.

Design/methodology/approach
Following a critical analysis of the inherent limitations of netnographic methodological approaches in the context of PBCs, this study develops an enriched netnographic research protocol that accounts for the challenges of engagement overlap among PBCs.

Findings
This study proposes two methods of analysis, namely, “participatory netnography” and “witness netnography,” which are derived from a mixed-methodology approach that integrates elements of netnography.

Research limitations/implications
The findings of this study underscore the requisite methodological refinements imperative for enhancing netnographic analysis, particularly in its application for a better comprehension of individual behaviors within the realm of PBCs. In pursuit of this objective, the identified adjustments encompass ethical considerations, evaluation methods and their application in a digital milieu, where intricate mechanics and technologies frequently elude conventional methodologies.

Originality/value
In this study, the authors present a novel conceptualization of PBCs, highlighting their role and development, as well as the challenges they pose. To adequately capture the impact of PBC engagement overlap, the authors propose the need for an enriched mixed-methodological approach.
A case of Schnitzler syndrome with unusual immunoglobulin A gammopathy exacerbated by COVID‐19 infection
Authors: Ikuno Yasuaki , Takahashi Toshifumi , Sugiura Shuji , Hayami Takuma , Yamaguchi Akihiko , Fujimoto Noriki 
Published: April 2024

AbstractSchnitzler syndrome (SchS) is a rare autoinflammatory disease characterized by chronic urticarial rash and monoclonal immunoglobulin M (IgM) or IgG gammopathy. Viruses, including COVID‐19, activate the innate immune system, therefore SchS, in which the innate immune system is improperly activated, is hypothesized to be exacerbated by viral infection. However, there were no reported SchS cases exacerbated by any viral infection. Here, we report a SchS case with an unusual IgA gammopathy manifested and exacerbated by COVID‐19 infection. This report advocates the need for recognizing unusual cases of SchS with monoclonal IgA, and following up on paraprotein like IgA even when it is initially undetectable in cases with SchS symptoms. We also hypothesize that existing autoinflammatory diseases may be exacerbated by COVID‐19 infection in the case of a combination of these diseases.
Telling mutualistic and antagonistic ecological networks apart by learning their multiscale structure
Authors: Pichon Benoît , Le Goff Rémy , Morlon Hélène , Perez‐Lamarque Benoît 
Published: April 2024

Abstract

Characterizing and understanding the processes that shape the structure of ecological networks, which represent who interacts with whom in a community, has many implications in ecology, evolutionary biology and conservation. A highly debated question is whether and how the structure of a bipartite ecological network differs between antagonistic (e.g. herbivory) and mutualistic (e.g. pollination) interaction types.

Here, we tackle this question by using a multiscale characterization of network structure, machine learning tools, and a large database of empirical and simulated bipartite networks.

Contrary to previous studies focusing on global structural metrics, such as nestedness and modularity, which concluded that antagonistic and mutualistic networks cannot be told apart from only their structure, we find that they can be told apart by combining a meso‐scale characterization of their structure and supervised machine learning. Motif frequencies appear particularly informative, with an over‐representation of densely connected motifs in antagonistic networks and of motifs with asymmetrical specialization in mutualistic networks. These structural properties can be used to predict the type of interaction with relatively good confidence. Beyond this classical mutualism/antagonism dichotomy, we also find significant structural uniqueness linked to specific ecologies (e.g. pollination, parasitism).

Our results clarify structural differences between antagonistic and mutualistic networks and suggest the investigation of the structural uniqueness of specific ecologies as a promising approach for characterizing interactions beyond the coarse antagonistic/mutualistic dichotomy.
Epithelial–mesenchymal transition dysregulation in prostate cancer: Insights from molecular unraveling and epidemiological analyses in Tunisia, North Africa
Authors: Said Rahma , Hernández‐Losa Javier , Haro Rosa Somoza Lopez de , Moline Teresa , Zouari Skander , Blel Ahlem , Rammeh Soumaya , Derouiche Amine , Ouerhani Slah 
Published: April 2024

AbstractIntroductionThe progression of prostate cancer (PCa) has been linked worldwide, including in African populations, to the dysregulation of the epithelial–mesenchymal transition (EMT).MethodsTo clarify the connection among EMT markers, clinicopathological parameters, and epidemiological factors, we analyzed 35 PCa specimens from patients in Tunisia, a country in North Africa, arranged by stages. We also carried out extensive molecular and epidemiological analyses.ResultsSignificant dysregulation of EMT genes was found, with an overexpression of ZEB‐1, Twist, Snail‐1, and Vimentin (p < 0.05) and underexpression of E‐cadherin and β‐catenin (p < 0.05). Positive correlations were observed between transcription factors and the mesenchymal marker Vimentin (p < 0.001, r = 0.574; p = 0.029, r = 0.411; and p < 0.001; r = 0.506) according to Spearman correlation analyses, whereas negative correlations were found between epithelial markers (E‐cadherin, β‐catenin) and Vimentin (p < 0.05; r < 0). Higher PSA, Gleason scores, and metastasis were all correlated with the dysregulation of EMT (p < 0.05). Notably, there was a positive correlation between higher consumption of tobacco (≥20 Packets per year) and Vimentin expression (p < 0.001, r = 0.854), suggesting a relationship between smoking and EMT activation in the Tunisian population. Moreover, Twist showed a positive correlation with diabetes (p < 0.001, r = 0.385), whereas no significant correlations were found between EMT markers and comorbidities such as hypertension and coronary insufficiency. These results demonstrate the intricate connection between molecular changes, epidemiological factors, and disease progression, and they emphasize the crucial role that EMT plays in promoting PCa aggressiveness in African populations, particularly in Tunisia.ConclusionIn summary, understanding these correlations could help develop focused treatment plans and enhance patient outcomes for PCa management in African settings.
Ultrasound and clinical factors predicting central lymph node metastases in patients with unilateral multifocal papillary thyroid carcinoma
Authors: Liang Zhenwei , Zhang Jixin , Chen Lei , Liu Jinghua , Wang Fumin , Shao Yuhong , Sun Xiuming , Chen Luzeng 
Published: April 2024

AbstractObjectiveThis retrospective study involving a large dataset of unilateral multifocal papillary thyroid carcinoma (UM‐PTC) sought to identify factors that predict central lymph node metastases (CLNM) in patients.MethodsWe identified a cohort of 158 patients who underwent cervical ultrasonography followed by UM‐PTC diagnosis based on postoperative pathology. The relationship between CLNM and UM‐PTC clinical ultrasound features was evaluated using univariate and multivariate analyses. Receiver operating characteristic (ROC) curve analysis was used to determine the ability of total tumor diameter (TTD) to predict CLNM.ResultsAmong the 158 UM‐PTC patients, the incidence of CLNM was 29.7% (47/158). Univariate and multivariate analyses revealed that a number of similarity of sonographic features (NSSF) ≥4 (odds ratio [OR] = 11.335, 95% confidence interval [CI]: 3.95–32.50,p = 0.000), microcalcifications (OR = 3.54, 95% CI: 1.30–9.70,p = 0.014), a TTD of ≥2 cm (OR = 4.48, 95% CI: 1.62–12.34,p = 0.004), number of nodules ≥3 (OR = 13.17, 95% CI: 3.24–53.52,p = 0.000), and Lateral cervical lymph node metastasis (LLNM) (OR = 5.57, 95% CI: 1.59–19.48,p = 0.007) were independently associated with CLNM in UM‐PTC. ROC curve analysis revealed that the TTD cut‐off of 1.795 cm had a sensitivity of 0.723 and a specificity of 0.676 for predicting CLNM.ConclusionsPatients with UM‐PTC are at high risk of CLNM. NSSF ≥4, microcalcifications, TTD of ≥2 cm, LLNM, and a number of nodules ≥3 were independently associated with CLNM. Our data show that ultrasound may guide surgical decisions in the treatment of UM‐PTC.