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Article
Publication date: 14 April 2023

Zihao Ye, Georgios Kapogiannis, Shu Tang, Zhiang Zhang, Carlos Jimenez-Bescos and Tianlun Yang

Built asset management processes require a long transition period to collect, edit and update asset conditions information from existing data sets. This paper aims to explore and…

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Abstract

Purpose

Built asset management processes require a long transition period to collect, edit and update asset conditions information from existing data sets. This paper aims to explore and explain whether and how digital technologies, including asset information model (AIM), Internet of Things (IoT) and blockchain, can enhance asset conditions assessment and lead to better asset management.

Design/methodology/approach

Mixed methods are applied to achieve the research objective with a focus in universities. The questionnaire aims to test whether the integration of AIM, IoT and blockchain can enhance asset condition assessment (ACA). Descriptive statistical analysis was applied to the quantitative data. The mean, median, mode, standard deviation, variance, skewness and range of the data group were calculated. Semi-structured interviews were designed to answer how the integration of AIM, IoT and blockchain can enhance the ACA. Quantitative data was analysed to define and explain the essential factors for each sub-hypothesis. Meanwhile, to strengthen the evaluation of the research hypothesis, the researcher also obtained secondary data from the literature review.

Findings

The research shows that the integration of AIM, IoT and blockchain strongly influences asset conditions assessment. The integration of AIM, IoT and blockchain can improve the asset monitoring and diagnostics through its life cycle and in different aspects, including financial, physical, functional and sustainability. Moreover, the integration of AIM, IoT and blockchain can enhance cross-functional collaboration to avoid misunderstandings, various barriers and enhance trust, communication and collaboration between the team members. Finally, costs and risk could be reduced, and performance could be increased during the ACA.

Practical implications

The contribution of this study indicated that the integration of AIM, IoT and blockchain application in asset assessment could increase the efficiency, accuracy, stability and flexibility of asset assessment to ensure the reliability of assets and lead to a high-efficiency working environment. More importantly, a key performance indicator for ACA based on the asset information, technology and people experience could be developed gradually.

Originality/value

This study can break the gap between transdisciplinary knowledge to improve the integration of people, technology (AIM, IoT and blockchain) and process value-based ACA in built asset management within universities.

Details

Construction Innovation , vol. 25 no. 2
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 1 January 2025

Nektarios Gavrilakis and Christos Floros

We investigate herding behavior and explore how risk aversion interacts with herding in a sample of selected sustainability indices. Furthermore, we evaluate volatility…

67

Abstract

Purpose

We investigate herding behavior and explore how risk aversion interacts with herding in a sample of selected sustainability indices. Furthermore, we evaluate volatility co-movements and dynamic and time-varying correlations of two notable indicators: the cross-sectional absolute deviation of returns (CSAD) and the risk aversion index (RAI). Moreover, we explore a spillover mechanism (in the short and long run) of risk aversion to sustainable investing.

Design/methodology/approach

Our study uses daily prices from 01/06/2012 to 15/07/2022 obtained from S&P Dow Jones Indices. We use autoregressive - Glosten, Jagannathan, and Runkle generalized autoregressive conditional heteroscedastic (AR(1)-GJR GARCH) methodologies to measure the impact of cross-sectional absolute deviation of returns (CSAD) and risk aversion (RAI) indicators on the conditional variance of selected sustainability indices. Furthermore, we employ dynamic conditional correlation with generalized autoregressive conditional heteroscedasticity, generalized autoregressive conditional heteroscedasticity generalized autoregressive conditional heteroscedasticity mixed data sampling and dynamic conditional correlation with mixed data sampling models to examine any dynamic correlation, spillover volatility effects and the predictability stance of the CSAD and the RAI factors on sustainable investing.

Findings

Our empirical outcomes capture no-herding behavior but display herding on the risk aversion indicator. The cross-sectional dispersion of returns positively affects the conditional variance of all selected sustainable markets, besides emerging markets, while the risk aversion factor negatively influences the conditional variance for Europe and the USA. We have identified long-term contagion effects relating to the variability of returns in our sample, with the exception of emerging markets.

Practical implications

The dispersion of returns can predict the swings of long-term volatilities of Nordic and Europe markets, while the risk aversion factor can predict the long-run volatilities of sustainable markets except Nordic.

Originality/value

The current study presents, for the first time in the sustainable finance literature, an empirical analysis of herding and risk aversion in sustainable investment returns over time. Our findings offer valuable insights to fund managers, finance professionals and investors, providing them with an opportunity to proactively manage their portfolios and reduce financial risk by understanding the volatility behavior of sustainable investing. Furthermore, it is crucial to explore and understand how the dispersion of returns and risk aversion interact with sustainable markets for the construction of optimal portfolios.

Details

EuroMed Journal of Business, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1450-2194

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Article
Publication date: 15 November 2023

Junaidi Junaidi

This study examines the role of ethical leadership in building employee trust, knowledge sharing (KS), job satisfaction and then influencing employee engagement in the workplace.

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Abstract

Purpose

This study examines the role of ethical leadership in building employee trust, knowledge sharing (KS), job satisfaction and then influencing employee engagement in the workplace.

Design/methodology/approach

The sample included 610 employees of Indonesia Islamic Bank, obtained through an online survey. Structural equation modelling was used to test the research hypotheses.

Findings

Ethical leadership actively contributes to the growth of employee trust, exchange knowledge frequent and job satisfaction and then become key points to enhance employees’ engagement.

Research limitations/implications

Future research is required to validate across regions and organisations to in light of the findings of the topic study.

Practical implications

Organisational leaders and employees obtain a better understanding of ethics and organisation management field, hence employees and leaders must encourage ethical values as code of conduct in the workplace.

Originality/value

This study demonstrated the extent of the Khan concept for a combination of employee engagement, ethical leadership and KS. It also incorporates employee job satisfaction and the organisational engagement among employees.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0218

Details

International Journal of Social Economics, vol. 51 no. 7
Type: Research Article
ISSN: 0306-8293

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