Search results

Recent developments in the psychometric assessment of youth psychopathic traits suggest that the inclusion of a conduct disorder (CD) factor to the traditional three factors of the psychopathy construct may improve the incremental validity of these measures. The purpose of the current study is to examine whether the addition of a CD factor incrementally improves the ability of the Youth Psychopathic Traits Inventory Short version (YPI-S) to predict criminal recidivism.

A longitudinal quantitative research design was used with a sample detained male youth (N = 214, M_age = 16.4 years, SD_age = 1.3 years).

Results using the area under the curve analysis suggest that the inclusion of a CD factor slightly improves the capacity of the YPI-S to predict one-year general criminal recidivism, but it does not significantly increase its capacity to predict violent criminal recidivism. Results also indicate that a CD scale outperforms the YPI-S, even with an additional CD factor included, in terms of predicting one-year general and violent recidivism.

Self-reported youth psychopathic trait measures, even those that include a CD factor as a fourth factor, should be used with caution when the aim is to predict youth criminal recidivism.

To the best of the authors’ knowledge, this is the first study using a self-reported youth psychopathic traits measure with a CD factor to examine youth criminal recidivism.

Despite the fact that shame is recognized as a significant factor in clinical encounters, it is under-recognized, under-researched and under-theorized in health prevention, assessment and cross-cultural contexts. Thus, this study aims to investigate the psychometric properties of the most widely used scale, the “Other as Shamer Scale” (OAS), to assess the risk and proclivities of external shame in adults. As in health care, there is a barrier between what is known through research in one culture and what is acceptable in practice in another culture.

The Urdu version was prepared using the standard back-translation method, and the study was conducted from June 2021 to January 2022. The translation and adaptation were completed in four steps: forward translation, adaptation and translation, back translation, committee approach and cross-language validation. The sample, selected through the purposive sampling method, is comprised of 200 adults (men = 100 and women = 100), with an age range of 18–60 years (M = 28, SD = 5.5), spanning all stages of life. The Cronbach's alpha reliability and factorial validity of the OAS were assessed through confirmatory factor analysis and Pearson correlation analyses. Internal consistency and test–retest reliability (at a two-week interval) were used to evaluate the reliability. Statistical analyses were performed using Statistical Package for Social Sciences (version 22) software.

Preliminary analysis revealed that the overall instrument had good internal consistency (Urdu OAS a = 0.91; English OAS a = 0.92) as well as test–retest correlation coefficients for 15 days (r = 0.88). The factor loading of all items ranged from 0.69 to 0.9, which explained the significant level and indicated the model's overall goodness of fit.

Findings suggest that this scale has significant psychometric properties and the potential to be used as a valid, reliable and cost-effective clinical and research instrument. This study contributes to scientific knowledge and helps to develop and test indigenous cross-cultural instruments that can be used to examine external shame in Pakistani people.

Limited use of Internet of Things (IoT) technology on construction sites has restricted its value in the construction industry. To propel its widespread application, this paper explores the influencing factors and action paths of construction companies' IoT technology adoption behavior.

First, literature research, technology adoption theories, and semi-structured expert interviews were employed to build the adoption model. Second, a questionnaire survey was conducted among Chinese construction contractors to collect empirical data. Third, the structural equation model method and regression analysis were used to test the adoption model. Finally, the findings were further validated with interviews, case studies, and field observations.

External environmental pressure (EEP), perceived benefit (PB), top management support (TMS), company resource readiness (CRR), adoption intention (AI), and perceived compatibility (PCA) have a direct positive impact on adoption behavior (AB). In contrast, perceived cost (PC) and perceived complexity (PCL) exert a direct negative impact on AB. The EEP, PB, and PC are critical factors affecting AB, whereas AI is strongly affected by CRR and TMS. Besides, AI plays a part mediating role in the relationship between seven factors and AB. Company size and nature positively moderate AI's positive effect on AB.

This paper contributes to the knowledge of IoT technology adoption behavior in the construction sector by applying the technology adoption theories. Exploring the implementation barriers and drivers of IoT technology in construction sites from the perspective of organizational technology adoption behavior and introducing moderating variables to explain adoption behavior are innovations of this paper. The findings can help professionals better understand the IoT technology adoption barriers and enhance construction companies' adoption awareness, demand, and ability. This work also provides a reference for understanding the impact mechanism of the adoption behavior of other innovative technologies in construction.

The influx of expatriates to the Gulf Cooperation Council (GCC) countries has led to labor imbalance inducing these countries to initiate workforce nationalization policies. However, despite the policies' emphasis on increasing the presence of nationals in all sectors, employing nationals in the private sector is still a critical challenge for policymakers. This paper explores local job seekers' and employees' perceptions of employment choices in the private and public sectors.

Adopting a qualitative approach, data were collected through in-depth interviews with 28 local job seekers, either not currently employed or employed but seeking another job.

The data revealed a contextualized understanding of positive and negative connotations pertaining to employment in the private and public sectors in Qatar.

Understanding nationals' negative preconceived notions against working in the private sector and the perceived benefits of public sector employment lays the groundwork for developing measures to help policymakers to create labor market-oriented policies that stimulate mobility between the public and private sectors.

This study contributes to the workforce nationalization literature in the GCC countries by examining local job seekers' perceptions associated with employment in the private sector and the public sector. A closer examination of why nationals are hesitant to enter the private sector can propel the pendulum towards higher success rates of workforce nationalization.

Monetary policy has major impacts on macroeconomic indicators of the country. Accordingly, uncertainty regarding monetary policy shifts can cause challenges and risks for businesses, financial markets and investors. Thus, the purpose of this study is to investigate how real estate market volatility responds to monetary policy uncertainty.

The GARCH-MIDAS model is applied in this study to investigate the nexus between monetary policy uncertainty and real estate market volatility. This model was fundamentally instituted to accommodate low-frequency variables.

The results of this study reveal that increased monetary policy uncertainty highly affects the volatility in real estate market during the peak period of COVID-19 as compared to full sample period and COVID-19 recovery period; hence, a significant decline is evident in real estate market volatility during crisis.

This study is particularly focused on peak and recovery period of COVID-19 considering the geographical region of Greece, Japan and the USA. This study provides a complete perspective on the nexus between monetary policy uncertainty and real estate markets volatility in three distinct economic views.

Based on the research of free trade agreements on alleviating service trade policy heterogeneity and its impact on manufacturing exports, this article aims to not only provide a basis for China's strategy of promoting regional economic integration, but also provide a policy reference for the manufacturing industry to expand the export market space.

This study uses the two principles of “answering” and “scoring” to quantify the indicators of service trade policy heterogeneity to test the relationship between heterogeneity of service trade policy, free trade agreement and manufacturing export.

According to empirical study, the export of Chinese manufacturing firms is severely hampered by the variety of service trade regulations, and the bigger the enterprise, the more hampered it is. In comparison to communications, transport and commerce, the financial industry's policy heterogeneity has a greater negative impact on certain industries. The major methods used to reduce the impact of service trade policy heterogeneity on manufacturing exports are product price increases and product quantity reductions. Also, by reducing the heterogeneity of service trade regulations and fostering industrial exports, the free trade agreement that China has signed can be quite successful. The open commitment in the area of national treatment, however, can reduce policy heterogeneity and advance manufacturing.

In the area of market access, the effect of export is superior to the open promise. Thus, in order to effectively support the stabilization of international trade, China should actively encourage the negotiation and signing of higher-quality and mutually beneficial free trade agreements.

In recent decades, human resource management (HRM) in health organizations has faced several problems associated with employees' efficiency and happiness, which has been particularly exacerbated after the pandemic crisis. In this scenario, this study seeks to analyze nurses' turnover intention by comparing Portuguese public and private healthcare organizations. As determining factors, transformational leadership, perceived organizational support and organizational commitment were considered.

A survey was digitally applied to 277 nurses from Portuguese public and private healthcare organizations.

Results suggested that there are differences in nurses' turnover intentions: there is a greater likelihood of nurses in the private sector planning to leave the healthcare organizations the nurses work for when compared to public hospital nurses. Furthermore, nurses in public hospitals perceive lower levels of transformational leadership, organizational support and organizational commitment than those in the private sector. The underlying cause as to the intention of leaving the public sector resides in normative commitment. On the other hand, lower affective commitment explains the intention to abandon the private sector.

This study is relevant for human resource managers and administrators in public and private hospitals since it enables a diagnosis of the situation, as well as a definition of the most appropriate policies for each of the sectors as a strategy to attract and retain health professionals.

This study is significant as the study provides a better understanding of the reasons which lead nurses to consider leaving the organization where the nurses work and the difference between nursing professionals in public and private hospitals.

Considering the swift adoption of innovative sustainability practices in businesses to accomplish sustainable development goals (SDGs), research on corporate sustainability has increased significantly over the years. This research intends to analyze the published literature, emphasizing the existing, emerging and future research directions on achieving the SDGs through corporate sustainability.

This research analyzed the growing trends in corporate sustainability by incorporating 2,038 Scopus articles published between 1999 and 2022 using latent Dirichlet allocation (LDA) topic modeling, bibliometrics and qualitative content analysis techniques. The bibliometric data were analyzed using performance and science mapping. Thereafter, topic modeling and content analysis uncovered the topics included under the corporate sustainability umbrella.

The findings indicate that investigation into corporate sustainability has considerably increased from 2015 to date. Additionally, the majority of studies on corporate sustainability are from the United States of America, the United Kingdom and Germany. Besides, the USA has the most collaboration in terms of co-authorship. S. Schaltegger was considered the most productive author. However, P. Bansal was ranked as the top author based on a co-citation analysis of authors. Further, bibliometric data were evaluated to analyze leading publications, journals and institutions. Besides, keyword co-occurrence analysis, topic modeling and content analysis highlighted the theoretical underpinnings and new patterns and provided directions for further research.

This study demonstrates various existing and emerging themes in corporate sustainability, which have various repercussions for academicians and organizations. This research also examines the lagging themes in the current domain.

Amidst the complicated nature of the UAE’s facilities management (FM) industry, the need to recalibrate the existing performance measurement (PM) system measures and criteria has been resonating to ensure their ability to capture the FM industry trends and dynamics, thus enhancing organizational excellence. Therefore, this research aimed to propose a specific PM tool to the country’s FM industry to accurately assess performance and establish strategic enhancements.

The study reviewed literature on the available PM systems to gather the available measures, which were presented to a focus group of seven participants, who were purposively selected based on their expertise in FM and PM implementation in the UAE to adjust them and add ones relevant to the UAE’s FM industry.

The focus group conducted various changes, from retaining certain measures and criteria, renaming them to simplify or make them more representative of the industry, ranking them based on their importance to limit their numbers, to finally categorizing them as enablers or results. Consequently, the final proposed tool was composed of nine dimensions with 51 measures as performance enablers and three dimensions with 11 measures as performance results. Seven measures were added by the experts, who highlighted their increasing popularity in the UAE’s FM industry.

Through addressing the critical void in literature, this paper develops a specific PM tool aligning with the intricacy of the UAE’s FM industry, thus providing proactive contribution to the industry’s effective and sustainable growth.

This paper aims to emphasize economic complexity, tourism, information and communication technology (ICT), renewable energy consumption and foreign direct investment (FDI) as the determinants of carbon emissions.

These economies rely on the tourism sector, and Asian countries rank among the top tourism economies worldwide in terms of tourism receipts. This study uses a series of empirical estimators, i.e. cross-sectional augmented auto-regression distributive lag and panel cointegration, to validate the main hypotheses.

The econometric results confirm an inverted U-shaped association between economic complexity and carbon emissions, validating the economic complexity index induced environment Kuznets curve hypothesis for the selected Asian economies.

Finally, the empirical results admit articulating some imperative policy suggestions to attain a sustainable environment on behalf of outcomes.

Furthermore, ICT and renewable energy consumption are environment-friendly indicators, while FDI and the international tourism industry increase environmental pressure in selected countries. In addition, this study also explores the interaction between renewable energy and ICT with FDI and their effects on carbon emissions. Interestingly, both interaction terms positively respond to the environmental correction process.

Because ICT with FDI may not reduce environmental pollution unless the energy used in FDI projects is greener. Moreover, in Asian economies, industrial and other sectors could increase environmental quality via the role of ICT in FDI.

修正亚洲前 8 大经济体的旅游环境库兹涅茨曲线假设：ict 和可再生能源消耗的作用

这些经济体依赖旅游业, 就旅游收入而言, 亚洲国家在全球旅游经济体中名列前茅。本研究使用一系列经验估计量, 即 CS-ARDL 和面板协整来验证我们的主要假设。

本文强调经济复杂性、旅游、信息和通信技术 (ICT)、可再生能源消费和外国直接投资 (FDI) 作为碳排放的决定因素

计量经济学结果证实了经济复杂性与碳排放之间的倒 U 型关联, 验证了 ECI 对选定亚洲经济体的环境库兹涅茨曲线 (EKC) 假设。

最后, 实证结果承认阐明了一些必要的政策建议, 以代表结果实现可持续环境。

此外, 信息通信技术和可再生能源消耗是环境友好型指标, 而外国直接投资和国际旅游业增加了选定国家的环境压力。此外, 本研究还探讨了可再生能源和 ICT 与外国直接投资之间的相互作用及其对碳排放的影响。有趣的是, 这两个交互项都对环境校正过程做出了积极响应。

ICT 与 FDI 可能不会减少环境污染, 除非 FDI 项目中的能源使用更环保。此外, 在亚洲经济体中, 工业和其他部门可以通过 ICT 在 FDI 中的作用提高环境质量。

环境库兹涅茨曲线; 外商直接投资;信息和通信技术; 可再生能源;旅游;亚洲主要旅游经济体

文章类型： 研究型论文