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With the continuous development of the wind power industry, wind power plant (WPP) has become the focus of resource development within the industry. Site selection, as the initial stage of WPP development, is directly related to the feasibility of construction and the future revenue of WPP. Therefore, the purpose of this paper is to study the siting of WPP and establish a framework for siting decision-making.

Firstly, a site selection evaluation index system is constructed from four aspects of economy, geography, environment and society using the literature review method and the Delphi method, and the weights of each index are comprehensively determined by combining the Decision-making Trial and Evaluation Laboratory (DEMATEL) and the entropy weight method (EW). Then, prospect theory and the multi-criteria compromise solution ranking method (VIKOR) are introduced to rank the potential options and determine the best site.

China is used as a case study, and the robustness and reliability of the methodology are demonstrated through sensitivity analysis, comparative analysis and ablation experiment analysis. This paper aims to provide a useful reference for WPP siting research.

In this paper, DEMATEL and EW are used to determine the weights of indicators, which overcome the disadvantage of single assignment. Prospect theory and VIKOR are combined to construct a decision model, which also considers the attitude of the decision-maker and the compromise solution of the decision result. For the first time, this framework is applied to WPP siting research.

The widespread family businesses play an important role in the national economy of developed countries in Europe and North America, or of developing countries in East Asia. However, family business succession is a worldwide difficult problem. The innovative family business succession practices of Robert Bosch GmbH, the German family company which has a history of 130 years (1886-2016), basically follow the trend of evolving from family businesses to social enterprises after further socialization. However, it has its own innovation and uniqueness which is worthy of reference by Chinese family businesses.

The purpose of this chapter is to cover banking efficiency using the concept of the Meta frontier function and to study group and subgroup differences in the production technology. This study estimates the technical efficiency (TE) and technology gap ratios (TGRs) for banks in Islamic countries. Using the assumption of the convex hull of the Meta frontier production set using the virtual Meta frontier within the nonparametric approach as presented by Battese and Rao (2002), Battese et al. (2004), and O'Donnell et al. (2007, 2008) and after relaxing this assumption, the study investigates if there is a significant difference between these two methods. To overcome the deterministic criterion addressed to nonparametric approach, the bootstrapping technique has been applied. The first part of this chapter covers the analytical framework necessary for the definition of a Meta frontier function and its estimation using nonparametric data envelopment analysis (DEA) in the case where we impose the assumption of the convex production set and follows in the case of relaxation of this assumption. Then we estimated the TE and the TGR in concave and nonconcave Meta frontier cases by applying the Bootstrap-DEA approach. The empirical part will be reserved for highlighting these methods on data bank to study the technical and technological performance level and prove if there is a difference between the two methods. Three groups of banks namely commercial, investment, and Islamic banks in 17 Islamic countries over a period of 16 years between 1996 and 2011 are used.

The workforce management model conceptualised for the effective management of the construction workforce was subjected to expert scrutiny to determine the suitability and applicability of the identified practices and their attributed variables to the construction industry. In achieving this, a Delphi approach was adopted using experts from construction organisations in South Africa. These experts comprised workforce management personnel and construction professionals in senior management positions. The data were analysed using appropriate statistical tools such as interquartile deviation, Kendell’s coefficient of concordance, and chi square to determine consensus among these experts. After a two-round Delphi, the seven constructs proposed in the conceptualised workforce management model were adjudged to be important and worthy of adoption by construction organisations seeking to improve workforce management in the current fourth industrial revolution era.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

The variance between the winning bid and the owner's estimated cost (OEC) is one of the construction management risks in the pre-tendering phase. The study aims to enhance the quality of the owner's estimation for predicting precisely the contract cost at the pre-tendering phase and avoiding future issues that arise through the construction phase.

This paper integrated artificial neural networks (ANN), deep neural networks (DNN) and time series (TS) techniques to estimate the ratio of a low bid to the OEC (R) for different size contracts and three types of contracts (building, electric and mechanic) accurately based on 94 contracts from King Saud University. The ANN and DNN models were evaluated using mean absolute percentage error (MAPE), mean sum square error (MSSE) and root mean sums square error (RMSSE).

The main finding is that the ANN provides high accuracy with MAPE, MSSE and RMSSE a 2.94%, 0.0015 and 0.039, respectively. The DNN's precision was high, with an RMSSE of 0.15 on average.

The owner and consultant are expected to use the study's findings to create more accuracy of the owner's estimate and decrease the difference between the owner's estimate and the lowest submitted offer for better decision-making.

This study fills the knowledge gap by developing an ANN model to handle missing TS data and forecasting the difference between a low bid and an OEC at the pre-tendering phase.

Financial inclusion in Peru has been addressed through coverage, quality of financial services, movement of transactions, and service points. The purpose of this chapter is to evaluate for the department of Ancash, Peru, the link between financial inclusion and its socioeconomic factors. Socioeconomic variables and financial inclusion of the Ancash department of the National Household Survey are taken as indicators, later contrasted through the logit model, with the financial inclusion variable being the explained variable.

There is evidence of positive and negative relationships between financial inclusion and socioeconomic variables; these are important components for planning financial inclusion. Raising the levels of formal employment, the educational level and considering the area of residence would be a strategy to generate a dynamic of inclusion in the department of Ancash.

Purpose: A psychiatric illness called burnout is caused by emotional tiredness, cynicism, and a decreased sense of personal accomplishment. For police officers to handle and adjust to difficult, stressful, and sometimes traumatic events, resilience or recovery during downtime are considered critical capacities. The study aims to investigate the association between resilience or recovery experiences and job burnout among police officers and to ascertain if recovery experiences during off-job time can lessen the harmful impacts of burnout.

Design/methodology: The data were gathered from police officers in the South zone of Kerala state using a structured questionnaire. The police force may have favourable effects on economic development if it embraces resilience-building concepts and develops into a more resilient enterprise. The study used convenience sampling, and the researchers received 300 responses. Karl Pearson correlation and simple regression analysis are used to test hypotheses.

Findings: Findings suggest an association between burnout and resilience or recovery experience measures during off-job time among police officers in Kerala. It is found that recovery experiences can buffer the adverse effects of job stress and burnout.

Practical implications: The results of this study could guide the design of initiatives and programmes that enhance police officers’ performance and satisfaction while also encouraging their general well-being. To further reduce police burnout, implement a programme that aims to improve occupational stress recovery at the organisational level.

Originality/value: It is crucial to evaluate police officers’ burnout and its relationship to resiliency or recovery in their spare time. This study offers unique insights into certain off-the-job behaviours or activities that link to lower levels of burnout; this information could guide programmes or interventions intended to help police personnel.

Social engineering is crucial in today’s digital landscape. As technology advances, malicious individuals exploit human judgment and trust. This study explores how age, education and occupation affect individuals’ awareness, skills and perceptions of social engineering.

A quantitative research approach was used to survey a diverse demographic of Egyptian society. The survey was conducted in February 2023, and the participants were sourced from various Egyptian social media pages covering different topics. The collected data was analyzed using descriptive and inferential statistics, including independent samples t-test and ANOVA, to compare awareness and skills across different groups.

The study revealed that younger individuals and those with higher education tend to research social engineering more frequently. Males display a higher level of awareness but score lower in terms of social and psychological consequences as well as types of attacks when compared to females. The type of attack cannot be predicted based on age. Higher education is linked to greater awareness and ability to defend against attacks. Different occupations have varying levels of awareness, skills, and psychosocial consequences. The study emphasizes the importance of increasing awareness, education and implementing cybersecurity measures.

This study’s originality lies in its focus on diverse Egyptian demographics, innovative recruitment via social media, comprehensive exploration of variables, statistical rigor, practical insights for cybersecurity education and diversity in educational and occupational backgrounds.

This paper aims to investigate the effect of physical vapor deposition (PVD)-coated stencil wall aperture on the life span of fine-pitch stencil printing.

The fine-pitch stencil used in this work is fabricated by electroform process and subsequently nano-coated using the PVD process. Stencil printing process was then performed to print the solder paste onto the printed circuit board (PCB) pad. The solder paste release was observed by solder paste inspection (SPI) and analyzed qualitatively and quantitatively. The printing cycle of up to 80,000 cycles was used to investigate the life span of stencil printing.

The finding shows that the performance of stencil printing in terms of solder printing quality is highly dependent on the surface roughness of the stencil aperture. PVD-coated stencil aperture can prolong the life span of stencil printing with an acceptable performance rate of about 60%.

Stencil printing is one of the important processes in surface mount technology to apply solder paste on the PCB. The stencil’s life span greatly depends on the type of solder paste, stencil printing cycles involved and stencil conditions such as the shape of the aperture, size and thickness of the stencil. This study will provide valuable insight into the relationship between the coated stencil wall aperture via PVD process on the life span of fine-pitch stencil printing.