Inter-Organizational Conflict (IOC) in Building Refurbishment Projects;an Exploratory Factor Analysis (EFA) approach

Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building refurbishment projects will lead to an increase in organizational interactions in the construction works as building refurbishment works involve interactions among many different organizations and it can cause Inter-Organizational conflict(IOC)among organizations involved in projects.This paper adopted an Exploratory Factor Analysis(EFA)approach to analyses IOC in building refurbishment projects.For this study,a fivepoint Likert Scale was adopted to ensure the instruments of the study are reliable.The researcher ultimately sent questionnaires as a web-link and email invitation to 1050 construction firms and 733 architectural firms.The questionnaire sent to managers and professionals from construction and architectural firms in Malaysia.Finally,one-hundred-seventy-nine(179)refurbishment projects formed a database for this paper.The finding of this paper shows the IOC factors that contribute to the improve the performance of building refurbishment project can be conflict during the construction stage,conflict between the client and the consultant,task expectations,basic responsibilities,final duration,project’s goals,conflict between the client and the contractor,final cost,final quality,standards of behaviors,conflict between the contractor and the consultant,interference and conflict during the design stage.

Modifying the Autism Spectrum Rating Scale(6–18 years)to a Chinese Context:An Exploratory Factor Analysis

The purpose of this study was to explore the psychometric properties of the Chinese version of the autism spectrum rating scale（ASRS）. We recruited 1,625community-based children and 211 autism spectrum disorder（ASD） cases from 4 sites, and the parents of all participants completed the Chinese version of the ASRS. A robust weighted least squares means and variance adjusted estimator was used for exploratory factor analysis. The3-factor structure included 59 items suitable for the current sample. The item reliability for the modi？ed Chinese version of the ASRS（MC-ASRS） was excellent. Moreover,with 60 as the cut-off point, receiver operating characteristic analysis showed that the MC-ASRS had excellent discriminate validity, comparable to that of the unmodi？ed Chinese version（UC-ASRS）, with area under the curve values of 0.952（95% CI： 0.936–0.967） and 0.948（95% CI：0.930–0.965）, respectively. Meanwhile, the con？rm factor analysis revealed that MC-ASRS had a better construct validity than UC-ASRS based on the above factor solution in another children sample. In conclusion, the MC-ASRS shows better ef？cacy in epidemiological screening for ASD in Chinese children.

Development of Elementary School Teachers＇ Self-Regulated Learning Exploratory Factor Scale

Self-regulated learning （SRL） is one of the precious ways in teachers＇ professional development, and its operation level includes different factors. With studies abroad and our preliminary investigation as base, this study developed a scale to test the factors SRL includes. According to the result of 905 teachers working in elementary school by exploratory factor analysis, the SRL for elementary teachers is consisted of its sociality （it included selecting leads and seeking for instructing）, its motivation（it included self-improvement and self-excelling）, its methods（it included strategy use and habitual behavior）, and its outcomes（it included extensive reading and teachers＇ professional development）. All the result indicated Teachers＇ SRL Scale had clear factor structure, good reliability and validity. It can be used to test the current operating situation of SRL for teachers working in elementary school.

Enhancing disaster management effectiveness: An integrated analysis of key factors and practical strategies through Structural Equation Modeling (SEM)and scopus data text mining

In the 21st century, the surge in natural and human-induced disasters necessitates robust disaster managementframeworks. This research addresses a critical gap, exploring dynamics in the successful implementation andperformance monitoring of disaster management. Focusing on eleven key elements like Vulnerability and RiskAssessment, Training, Disaster Preparedness, Communication, and Community Resilience, the study utilizesScopus Database for secondary data, employing Text Mining and MS-Excel for analysis and data management.IBM SPSS (26) and IBM AMOS (20) facilitate Exploratory Factor Analysis (EFA) and Structural Equation Modeling(SEM) for model evaluation.The research raises questions about crafting a comprehensive, adaptable model, understanding the interplaybetween vulnerability assessment, training, and disaster preparedness, and integrating effective communicationand collaboration. Findings offer actionable insights for policy, practice, and community resilience against disasters. By scrutinizing each factor's role and interactions, the research lays the groundwork for a flexible model.Ultimately, the study aspires to cultivate more resilient communities amid the escalating threats of an unpredictable world, fostering effective navigation and thriving.

Validation and adaptation of the Physical Activity Enjoyment Scale (PACES) in fitness group exercisers

Background:Recently,Mullen et al.(2011)presented an 8-item version of the Physical Activity Enjoyment Scale(PACES)that provides a valid instrument for assessing enjoyment in physical activity.The present paper investigated the psychometric properties of a Portuguese adaptation of PACES.Methods:After a process of back-to-back translation into Portuguese,395 members of fitness centers who ranged in age from 18 to 66 years(31.11§8.90,mean§SD)completed the translated version of the PACES.On average,participants had 3.2 years of experience in fitness group classes and practiced for approximately 3.3 times per week.Results:An initial exploratory factor analysis(n=139)revealed a unidimensional structure with factor loadings ranging from 0.79 to 0.89.Results also showed acceptable internal consistency.A confirmatory factor analysis in an independent sample(n=256)provided additional support for the unidimensional structure of the questionnaire.In addition,moderate positive correlations between enjoyment and intrinsic and identified regulation,and moderate negative correlations between enjoyment and external and amotivation,demonstrate the convergent validity of the instrument.Finally,measurement invariance between 2 independent samples was also found.Conclusion:The 8-item Portuguese version of PACES is a valid and reliable instrument for measuring enjoyment of physical activity in Portuguese adult fitness exercisers,and it is therefore suitable to use as a measure of affect in exercise adherence interventions studies.

Construction and structural Research of Organizational Ethical Climate Scales

Organizational ethical climate is an effective way to solve organizational ethical problems and dilemmas. Therefore study on our organizational ethical climate has the great significance to solve ethical problems and dilemmas faced by the organization and staff. Through semi-structured interview, structural interview and questionnaire survey and other methods this study gets to understand internal structural elements of organizational ethical climate under Chinese cultural background, and constructs organizational ethical climate questionnaire, which has good reliability and validity; carries out surveys in large scale by using the revised questionnaire, and recycles 709 valid questionnaires. The results of exploratory factor analysis and confirmatory factor analysis show that Chinese organizational ethical climate＇ s internal structure includes five factors： egoism, altruism, independence orientated, organizational system orientated, and law and code orientated.

A preliminary multicultural nursing competence instrument for assessing undergraduate student nurses

Purpose:To develop a multicultural nursing competence instrument for use in assessing undergraduate student nurses(SNs).Methods:This study enrolled 322 student nurses(SNs)employed at five hospitals in Hunan Province.The nurses were identified by the cluster sampling method.The items on the competence instrument were retained or deleted after analyzing their coefficient of variation,coefficient of correlation with the total score,t-test results.Reliability tests and correlation analysis were used to examine internal consistency,while exploratory factor analysis was used to determine construct validity.Results:After analyzing items,the final multicultural nursing competence instrument comprised a total of 49 items that evaluated five dimensions.The instrument showed good overall reliability(0.958),and the internal consistency of the five dimensions ranged from 0.884 to 0.952.Furthermore,the correlations among the five dimensions were statistically significant(P<0.01).An exploratory factor analysis of the five dimensions showed that five items incorporated aspects of cultural cognition(factor loading range,0.824-0.888),five items incorporated aspects of cultural attitude(factor loading range,0.629-0.815),twentytwo items involved cultural knowledge(factor loading range,0.587-0.792),seven items incorporated aspects of cultural skills(factor loading range,0.743-0.860),and 10 items involved cultural encounters(factor loading range,0.522-0.909).Conclusion:The multicultural nursing competence instrument for SNs demonstrated good reliability and validity,and can be utilized in nursing education programs and research.

Modeling parameters influencing city gas distribution sector based on factor analysis method

City gas distribution(CGD)sector is influenced by several factors like policy,infrastructure,health,safety etc.In order to understand this sector,an exploratory factor analysis is conducted.The Exploratory Factor Analysis(EFA)survey meticulously simplifies interconnected steps and examines the possible causal factor structure of a series of measured variables without hitting a predetermined result model.In this paper,the factor analysis is performed in three broad categories namely:managerial level,technical level and site workers to understand the most influencing factor of the sector.60 questionnaires were prepared to get feedback on parameters affecting CGD sector.The survey is performed by various means,like google form,email,phone calls,appointments with employees and personal meetings.It has been observed from the survey that the nine factors influences this sector and requires certain modifications for the development.Out of these nine factors,five were selected for the analysis which are infrastructure factor,policy factor,gas consumption factor,total energy demand factor and economy factor.The factor analysis has been performed in five major steps,namely factor analysis applicability,selection of factors,loading of factors,significance test of factors and factor loading matrix analysis.The results obtained from these exploratory factor analysis shows that variables like infrastructure,total energy demand and economy affects the CGD market most than the policy and gas consumption.

The Impact of State Policies on Investment Project Management in Polish Industrial Construction Sector

In this paper,we discuss the influence of economic,environmental and legal policies of the state on the management of investment projects in the area of industrial construction in Poland.Our empirical study relies on conducting a questionnaire survey.A total of 158 Polish companies dealing with industrial construction took part in the survey.Then,the collected questionnaires were subjected to a thorough analysis and interpretation,with the use of a method called the exploratory factor analysis(EFA).Our research reveals the key factors influencing successful investment project management in the Polish industrial construction sector.These factors have been identified as the“availability of technology in a stable political system”,“stability of the economic and tax systems”,“stable social system policy,stability and transparency of the legal system”and a“well-targeted environmental policy”.A key conclusion that can be drawn from our study is that an efficient management of investment projects in the industrial construction industry is significantly influenced by properly shaped and stable economic,environmental,and legal policies of the state.

Evaluation of ICUs and weight of quality control indicators:an exploratory study based on Chinese ICU quality data from 2015 to 2020

This study aimed to explore key quality control factors that affected the prognosis of intensive care unit(ICU)patients in Chinese mainland over six years(2015–2020).The data for this study were from 31 provincial and municipal hospitals(3425 hospital ICUs)and included 2110685 ICU patients,for a total of 27607376 ICU hospitalization days.We found that 15 initially established quality control indicators were good predictors of patient prognosis,including percentage of ICU patients out of all inpatients(%),percentage of ICU bed occupancy of total inpatient bed occupancy(%),percentage of all ICU inpatients with an APACHE II score≥15(%),three-hour(surviving sepsis campaign)SSC bundle compliance(%),six-hour SSC bundle compliance(%),rate of microbe detection before antibiotics(%),percentage of drug deep venous thrombosis(DVT)prophylaxis(%),percentage of unplanned endotracheal extubations(%),percentage of patients reintubated within 48 hours(%),unplanned transfers to the ICU(%),48-h ICU readmission rate(%),ventilator associated pneumonia(VAP)(per 1000 ventilator days),catheter related blood stream infection(CRBSI)(per 1000 catheter days),catheter-associated urinary tract infections(CAUTI)(per 1000 catheter days),in-hospital mortality(%).When exploratory factor analysis was applied,the 15 indicators were divided into 6 core elements that varied in weight regarding quality evaluation:nosocomial infection management(21.35%),compliance with the Surviving Sepsis Campaign guidelines(17.97%),ICU resources(17.46%),airway management(15.53%),prevention of deep-vein thrombosis(14.07%),and severity of patient condition(13.61%).Based on the different weights of the core elements associated with the 15 indicators,we developed an integrated quality scoring system defined as F score=21.35%xnosocomial infection management+17.97%xcompliance with SSC guidelines+17.46%×ICU resources+15.53%×airway management+14.07%×DVT prevention+13.61%×severity of patient condition.This evidence-based quality scoring system will help in assessing the key elements of quality management and establish a foundation for further optimization of the quality control indicator system.

Barriers and drivers for sustainable public transportation in Indian context

Rising negative externalities,including greenhouse gas emissions,climate change,and environmental pollution,shows the need for sustainable and environmentally friendly modes of transportation.Adopting zero-emission,environmentally friendly electric buses in public transportation systems can be an effective solution for both developing and developed countries,including India.While the Indian government is making numerous efforts to promote electric buses in commercial and public transportation systems,it faces several formidable obstacles.This research objective is to analyze and evaluate the primary factors influencing the adoption and usage of electric buses in the Indian public transportation system,within the limited available resources.A survey questionnaire is prepared with several perceptual subjects for the key perceived barriers.An empirical analysis using Structural Equation Modeling(SEM)is then performed to identify the critical barriers.The result of this study demonstrates that the infrastructural barriers substantially impact the adoption and utilization of electric buses.Further,the study provides critical insights and managerial implications for decision-makers.

Epidemiological-survey-based multidimensional modeling for understanding daily mobility during the COVID-19 pandemic across urban-rural gradient in the Chinese mainland

Human mobility survey data usually suffer from a lack of resources for validation.Epidemiological survey records,which are released to the public as a containment measure by local authorities,provide place visitation details validated by the authority.This study collected and analyzed the epidemiological survey reports published by local governments in the Chinese mainland,between January 2020 and November 2021.To reveal the mobility patterns during the COVID-19 pandemic across the urban-rural gradient in China’s mainland,we derived key mobility indicators from the epidemiological survey data from rural to megacities.We then applied exploratory factor analysis to identify latent factors that affected people’s mobility.We found that the pandemic poses varying impacts across the urban-rural gradient in the Chinese mainland,and the mobility patterns of middle and small cities are more influenced.Our results also showed that the pandemic did not enlarge gender gap in people’s mobility,as gender was not a significant driving factor for explaining people’s quantity of out-of-home activities as well as extent of life space,while age group and city levels were significant.Overall,we argue that the epidemiological survey data are valuable data sources for daily mobility modeling,especially for relevant studies to understand human mobility patterns during the pandemic.

Development and Initial Validation of the Novel Scale for Assessing Quality of Life of Prostate Cancer Patients Receiving Androgen Deprivation Therapy

Background：There has been no a specific scale to measure quality of life （QOL） for prostate cancer patients receiving androgen deprivation therapy （ADT） to date.This study aimed to develop and initially validate the scale to evaluate QOL for prostate cancer patients receiving ADT.Methods：The scale was developed following international recommendations.Moreover,the items were all generated through literature review and referenced questionnaires.After being reviewed by expert panelists,the revised scale was formed and then completed by a convenience sample of 200 prostate cancer patients from our hospital.Explore factor analysis （EFA） was applied to test the construct validity,then split-half reliability,Cronbach＆#39;s alpha,and test-retest reliability were applied to assess the reliability and stability of the scale.Results：The revised scale contained 22 items and a total of 200 participants had completed the scale.One hundred participants were randomly selected from the total 200 participants to perform EFA with varimax rotation on the revised scale,and ＆quot;hot flashes＆quot; item was deleted for low factor loading.We selected only 3 items from each factor,then,the final scale was formed with 18-items.We selected another 100 participants to perform the EFA again on the final scale.It was demonstrated that the structure with 6 factors explained 72.5% of total variance and factor loading value was above 0.40 in all items of the factors.Moreover,the split-half reliability coefficient,Cronbach＆#39;s alpha,and test-retest reliability coefficient were calculated to be 0.74,0.63,and 0.89,respectively,exhibiting good reliability on the whole.Conclusions：The scale was identified to be a valid and reliable instrument to measure QOL for prostate cancer patients receiving ADT.Moreover,further research is needed to overcome the potential drawbacks.

A Novel DBN-EFA-CFA-Based Dimensional Reduation for Credit Risk Measurement

Affected by the Federal Reserve's interest rate hike and the downward pressure on the domestic economy,the phenomenon of default is still prominent.The credit risk of the listed companies has become a growing concern of the community.In this paper we present a novel credit risk measurement method based on a dimensional reduation technique.The method first extracts the risk measure indexes from the basal financial data via dimensional reduation by using deep belief network(DBN),exploratory factor analysis(EFA)and confirmatory factor analysis(CFA)in turn.And then the credit risk is measured by a systemic structural equation model(SEM)and logistic distribution.To validate the proposed method,we employ the financial data of the listed companies from Q12019 to Q22022.The empirical results show its effectiveness on statistical evaluation,assessment on testing samples and credit risk forecasting.