Despite the efforts of governments and firms, the construction industry is trailing other industries in labour productivity. Construction companies are interested in increasing their labour productivity, particularly when demand grows and construction firms cope with labour shortages. Off-site construction has proved to be a favourable policy to increase labour productivity. However, a complete understanding of the factors affecting construction labour productivity is lacking, and it is unclear which factors are influenced by off-site construction. This study developed a conceptual model describing how 15 factors influence the construction process and make a difference in labour productivity between off-site and on-site construction. The conceptual model shows that all 15 factors affect labour productivity in three ways: through direct effects, indirect effects and causal loops. The model is a starting point for further research to determine the impact of off-site construction on labour productivity.
MULTIFILE
In this article, we calculate the economic impact of pilgrimage to Santiago de Compostela in the NUTS 2 region Galicia (Spain) in 2010. This economic impact is relevant to policymakers and other stakeholders dealing with religious tourism in Galicia. The analysis is based on the Input-Output model. Location Quotient formulas are used to derive the regional Input-Output table from the national Input-Output table of Spain. Both the Simple Location Quotient formula and Flegg's Location Quotient formula are applied. Furthermore, a sensitivity analysis is carried out. We found that pilgrimage expenditures in 2010 created between 59.750 million and 99.575 million in Gross Value Added and between 1, 362 and 2, 162 jobs. Most of the impact is generated within the 'Retail and Travel Services' industry, but also the 'Industry and Manufacturing', 'Services' and 'Financial and Real Estate Services' industries benefit from pilgrimage expenditures. This research indicates that in even in the most conservative scenario, the impact of pilgrimage is significant on the local economy of Galicia.
MULTIFILE
This study explored the dimensionality and measurement invariance of a multidimensional measure for evaluating teachers’ perceptions of the quality of their relationships with principals at the dyadic level. Participants were 630 teachers (85.9% female) from 220 primary and 204 secondary schools across the Netherlands. Teachers completed the 10-item Principal–Teacher Relationship Scale (PTRS) for their principals. Confirmatory factor analyses (CFA) provided evidence for a two-factor model, including a relational Closeness and Conflict dimension. Additionally, multigroup CFA results indicated strong invariance of the PTRS across school type, teacher gender, and teaching experience. Last, secondary school teachers and highly experienced teachers reported lower levels of Closeness and higher levels of Conflict in the relationship with their principal compared to primary school teachers and colleagues with less experience. Accordingly, the PTRS can be considered a valid and reliable measure that adds to the methodological repertoire of educational leadership research by focusing on both positive and negative aspects of dyadic principal–teacher relationships.
Size measurement plays an essential role for micro-/nanoparticle characterization and property evaluation. Due to high costs, complex operation or resolution limit, conventional characterization techniques cannot satisfy the growing demand of routine size measurements in various industry sectors and research departments, e.g., pharmaceuticals, nanomaterials and food industry etc. Together with start-up SeeNano and other partners, we will develop a portable compact device to measure particle size based on particle-impact electrochemical sensing technology. The main task in this project is to extend the measurement range for particles with diameters ranging from 20 nm to 20 um and to validate this technology with realistic samples from various application areas. In this project a new electrode chip will be designed and fabricated. It will result in a workable prototype including new UMEs (ultra-micro electrode), showing that particle sizing can be achieved on a compact portable device with full measuring range. Following experimental testing with calibrated particles, a reliable calibration model will be built up for full range measurement. In a further step, samples from partners or potential customers will be tested on the device to evaluate the application feasibility. The results will be validated by high-resolution and mainstream sizing techniques such as scanning electron microscopy (SEM), dynamic light scattering (DLS) and Coulter counter.
In order to achieve much-needed transitions in energy and health, systemic changes are required that are firmly based on the principles of regard for others and community values, while at the same time operating in market conditions. Social entrepreneurship and community entrepreneurship (SCE) hold the promise to catalyze such transitions, as they combine bottom-up social initiatives with a focus on financially viable business models. SCE requires a facilitating ecosystem in order to be able to fully realize its potential. As yet it is unclear in which way the entrepreneurial ecosystem for social and community entrepreneurship facilitates or hinders the flourishing and scaling of such entrepreneurship. It is also unclear how exactly entrepreneurs and stakeholders influence their ecosystem to become more facilitative. This research programme addresses these questions. Conceptually it integrates entrepreneurial ecosystem frameworks with upcoming theories on civic wealth creation, collaborative governance, participative learning and collective action frameworks.This multidisciplinary research project capitalizes on a unique consortium: the Dutch City Deal ‘Impact Ondernemen’. In this collaborative research, we enhance and expand current data collection efforts and adopt a living-lab setting centered on nine local and regional cases for collaborative learning through experimenting with innovative financial and business models. We develop meaningful, participatory design and evaluation methods and state-of-the-art digital tools to increase the effectiveness of impact measurement and management. Educational modules for professionals are developed to boost the abovementioned transition. The project’s learnings on mechanisms and processes can easily be adapted and translated to a broad range of impact areas.
Despite the benefits of the widespread deployment of diverse Internet-enabled devices such as IP cameras and smart home appliances - the so-called Internet of Things (IoT) has amplified the attack surface that is being leveraged by cyber criminals. While manufacturers and vendors keep deploying new products, infected devices can be counted in the millions and spreading at an alarming rate all over consumer and business networks. The objective of this project is twofold: (i) to explain the causes behind these infections and the inherent insecurity of the IoT paradigm by exploring innovative data analytics as applied to raw cyber security data; and (ii) to promote effective remediation mechanisms that mitigate the threat of the currently vulnerable and infected IoT devices. By performing large-scale passive and active measurements, this project will allow the characterization and attribution of compromise IoT devices. Understanding the type of devices that are getting compromised and the reasons behind the attacker’s intention is essential to design effective countermeasures. This project will build on the state of the art in information theoretic data mining (e.g., using the minimum description length and maximum entropy principles), statistical pattern mining, and interactive data exploration and analytics to create a casual model that allows explaining the attacker’s tactics and techniques. The project will research formal correlation methods rooted in stochastic data assemblies between IoT-relevant measurements and IoT malware binaries as captured by an IoT-specific honeypot to aid in the attribution and thus the remediation objective. Research outcomes of this project will benefit society in addressing important IoT security problems before manufacturers saturate the market with ostensibly useful and innovative gadgets that lack sufficient security features, thus being vulnerable to attacks and malware infestations, which can turn them into rogue agents. However, the insights gained will not be limited to the attacker behavior and attribution, but also to the remediation of the infected devices. Based on a casual model and output of the correlation analyses, this project will follow an innovative approach to understand the remediation impact of malware notifications by conducting a longitudinal quasi-experimental analysis. The quasi-experimental analyses will examine remediation rates of infected/vulnerable IoT devices in order to make better inferences about the impact of the characteristics of the notification and infected user’s reaction. The research will provide new perspectives, information, insights, and approaches to vulnerability and malware notifications that differ from the previous reliance on models calibrated with cross-sectional analysis. This project will enable more robust use of longitudinal estimates based on documented remediation change. Project results and methods will enhance the capacity of Internet intermediaries (e.g., ISPs and hosting providers) to better handle abuse/vulnerability reporting which in turn will serve as a preemptive countermeasure. The data and methods will allow to investigate the behavior of infected individuals and firms at a microscopic scale and reveal the causal relations among infections, human factor and remediation.
