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2022 ◽  
Vol 30 (7) ◽  
pp. 0-0

At present, most risk management work mainly relies on manpower, and manpower relies on the professional knowledge of relevant skilled workers to discover hidden safety risks in production activities. This article combines relevant big data theories and 4V characteristics to analyze and investigate safety production and big data, study data structure, data source and data type. Using 5W1H scientific big data and applications, this analysis method analyzes the theoretical basis, applications and beneficiaries of big data related to safety production, some of which are application links and important theoretical issues. Secondly, it studies the security risk management model based on big data, proposes a risk management model based on big data, the technical basis of big data and the idea of a three-dimensional model, and applies the systematic space method, which is reflected in three aspects of risk management. In the end, a risk identification model based on big data, a risk assessment classification model, and a risk early warning and pre-control model are defined.

2022 ◽  
Vol 22 (2) ◽  
pp. 1-28
Stephanie Lunn ◽  
Monique Ross ◽  
Zahra Hazari ◽  
Mark Allen Weiss ◽  
Michael Georgiopoulos ◽  

Despite increasing demands for skilled workers within the technological domain, there is still a deficit in the number of graduates in computing fields (computer science, information technology, and computer engineering). Understanding the factors that contribute to students’ motivation and persistence is critical to helping educators, administrators, and industry professionals better focus efforts to improve academic outcomes and job placement. This article examines how experiences contribute to a student’s computing identity, which we define by their interest, recognition, sense of belonging, and competence/performance beliefs. In particular, we consider groups underrepresented in these disciplines, women and minoritized racial/ethnic groups (Black/African American and Hispanic/Latinx). To delve into these relationships, a survey of more than 1,600 students in computing fields was conducted at three metropolitan public universities in Florida. Regression was used to elucidate which experiences predict computing identity and how social identification (i.e., as female, Black/African American, and/or Hispanic/Latinx) may interact with these experiences. Our results suggest that several types of experiences positively predict a student’s computing identity, such as mentoring others, having a job, or having friends in computing. Moreover, certain experiences have a different effect on computing identity for female and Hispanic/Latinx students. More specifically, receiving academic advice from teaching assistants was more positive for female students, receiving advice from industry professionals was more negative for Hispanic/Latinx students, and receiving help on classwork from students in their class was more positive for Hispanic/Latinx students. Other experiences, while having the same effect on computing identity across students, were experienced at significantly different rates by females, Black/African American students, and Hispanic/Latinx students. The findings highlight experiential ways in which computing programs can foster computing identity development, particularly for underrepresented and marginalized groups in computing.

Buildings ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 43
Funmilayo Ebun Rotimi ◽  
Firas Majthoub Almughrabi ◽  
Don Amila Sajeevan Samarasinghe ◽  
Chathurani Silva

Skill availability is an important component in the uptake of prefabrication and plays a crucial role in housing supply. However, the challenge is that the demand for housing has outgrown the availability of specifically trained workers. This challenge is not unique to New Zealand; many developed countries worldwide are facing similar issues. Therefore, the purpose of this study is to determine relevant skills in the prefabricated residential construction sector in New Zealand (NZ) and suggest improvement measures from the standpoint of industry stakeholders. The study adopted a semi-structured online survey and administered it to multiple construction industry practitioners. The study found the training of the construction workforce as one significant area of focus. In addition, external sourcing of international prefabrication-specific skilled workers could improve the issues of skill shortages in the residential prefabrication sector. Furthermore, the study revealed that the barriers to healthier prefabrication uptake are closely linked to shortages in management, digital architecture and design, and vocational skills related to residential construction. The study has contributed to the current pool of knowledge by identifying skill issues in NZ’s prefabricated residential construction sector, classifying the major restraints limiting prefabrication implementation, and determining measures for increasing industry uptake. It is anticipated that this will help construction organizations and the wider industry develop strategic goals and a roadmap for meeting the skill requirements in NZ. Training policies and programmes can be developed with focus on crucial prefabrication skill requirements at governmental level. Curriculum reviews are recommended for uptake by academic and vocational institutions.

2021 ◽  
Vol 6 (01) ◽  
pp. 12-20
Rajendra Bahadur Shrestha

Engagement of employers in the Technical Vocational Education and Training (TVET) system is needed not only to increase the training capacity but to ensure the TVET is demand-driven, quality oriented, future focused and provides the economy with the skilled workers it needs. Employer engagement in TVET system covers a spectrum of cooperation and involves small participation to build the trust required to develop more robust long-term engagement strategies. Developing engagements with employer and employer’s associations at all levels of the training programmes life cycle facilitate the development of workable solutions for training-to-work transitions. The employer has a crucial role to play in the delivery of training programmes. Engagement of employer is an essential component of overall training programmes and leads to developing responsive labour market skill needs, supporting priority economic sectors, training design and development, training delivery and post training support to develop ongoing dialogue with employer and employer associations. The need to increase the engagement of employers in TVET programmes has been known for many years in the country, however, employer engagement in training delivery of TVET programme is under-explored in Nepal. This article addresses the existing situation, explores issues, and share some practicable initiations of employer engagement in the TVET programme.

2021 ◽  
pp. 103530462110669
Yu Cheng Lai ◽  
Santanu Sarkar

This paper builds an estimation model to test whether improved labour standards necessarily lead firms to send work offshore to countries with lower wages and fewer employment protections; or improved labour standards influence the labour market, where with time, firms attract more skilled workers, which help deter outward foreign direct investment (FDI). When more firms comply with improved labour standards, the industrial relations climate also improves as non-compliance usually causes labour unrest. Using a model built on pooled cross-sectional time-series data from 2008–17, we studied the role of changes in labour unrest and the percentage of skilled workers in the labour force in predicting outward FDI in Taiwan. Per our estimation model, we found the percentage of skilled workers steadily increased as Taiwan maintained improved labour standards. The increase in skilled workers also increased labour costs making it challenging for firms to stay onshore. However, skilled workers helped firms improve productivity, which justified increased labour costs. As a result, firms in Taiwan that complied with labour standards found it less challenging to pay higher wages and stayed onshore. JEL Code: J28, J38, F66

2021 ◽  
Vol 12 ◽  
Virginia Barba-Sánchez ◽  
Luis Orozco-Barbosa ◽  
Enrique Arias-Antúnez

Smart City initiatives across the globe have spurred increasing demand for high-skilled workers. The digital transformation, one of the main building blocks of the Smart City movement, is calling for a workforce prepared to develop novel business processes. Problem-solving, critical and analytical thinking are now the essential skills being looked at by employees. The development of the so-called STEM curriculum, Science, Technology, Engineering, and Mathematics is being given a lot of attention by educational boards in response to preparing young generations for the Smart City work market. Based on the IMD Smart City Index, PISA, and World Bank reports, we develop a model for assessing the impact of the IT secondary school capacities on Smart-City business developments. The model reveals the relationship between the technological capacity of the secondary-school, and the business activity of a Smart City. Moreover, the study shows the existence of a positive relationship between the IT capacity of secondary schools and the resulting entrepreneurial activity of the city. Our results are of interest to decision-makers and stakeholders responsible for designing educational policies and agents involved in the digital transformation and development of Smart Cities initiatives.

2021 ◽  
Vol 28 (56) ◽  
pp. 37-56
Alexis S. Esposto ◽  
Luis Federico Giménez

Over the last three decades the labor market of most developed countries have experienced a sustained period of upskilling. This means an overall increase in the skill requirement of jobs determined by the demand for skilled labor. This suggests that their labor demand has become more skill intensive, shifting towards skilled workers relatively to unskilled workers. An analysis of job growth of the Argentine labor market between 1997 and 2009 using data from the EPH, evidences a process of deskilling over this period, with serious implications in terms of competitiveness and about issues related to increasing social and economic inequality.

2021 ◽  
Lee Tedstone

Abstract The energy sector is facing more challenges than ever before – from the impacts of the pandemic on already low margins, to Environmental, Social and Governance pressures mounting to gain investment and attract skilled workers in a competitive market. Over past year, the oil and gas sector has accelerated a critical path to digital transformation, paving its way to a more agile, greener future. Data-sharing and collaboration enabled through the Digital Twin helps companies drive efficiency, which in turn creates opportunities to improve sustainability performance, even on legacy assets. This presentation will demonstrate how moving to Digital Twin technology is a viable brownfield solution to many of the industries pressing challenges today. It will also make the business case for how digitalization and digital twin connectivity are not only possible on a brownfield asset but also, why it is critical to meet the needs of the plant of the future.

2021 ◽  
pp. 103530462110424
Arnd Kölling

This study analyses firms’ labour demand when employers have at least some monopsony power. It is argued that without taking into account (quasi-)monopsonistic structures of the labour market, wrong predictions are made about the effects of minimum wages. Using switching fractional panel probit regressions with German establishment data, I find that slightly more than 80% of establishments exercise some degree of monopsony power in their demand for low-skilled workers. The outcome suggests that a 1% increase in payments for low-skilled workers would, in these firms, increase employment for this group by 1.12%, while firms without monopsony power reduce the number of low-skilled, by about 1.63% for the same increase in remuneration. The study can probably also be used to explain the limited employment effects of the introduction of a statutory minimum wage in Germany and thus leads to a better understanding of the labour market for low-skilled workers. JEL Codes: J23, J42, C23, D24

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