Search results

Work-Based Learning (WBL) is a form of practical learning that is still rare, yet upcoming in academic education. It differs mainly from classical approaches because work experience forms a key curriculum element. To enable WBL, a cultural change in academic landscape seems required, which depends on views and support of academic staff.

The authors carried out a case study, in which the authors interviewed 20 Dutch science professors to examine their vision on the master track Science, Business and Policy (SBP), a WBL program offered for over 15 years.

Generally professors are positive about its added value and recommend the track, especially for students with career ambitions outside academia. WBL is perceived to have a positive contribution to academic level. Professors indicated that for academic skills development, compared with a traditional master's program, SBP is evaluated neutral to positive.

Altogether the current climate at the university of Groningen towards WBL seems predominantly positive. The educational change towards a solid inclusion of WBL in the regular curriculum seems supported by one of the key players, the professors. This track could thereby be an example for other WBL programs worldwide.

This study aims to identify the publication phase, performance and scientific contributions of research papers related to enterprise risk management (ERM) and to visualise the emerging themes in addressing volatility, uncertainty, complexity and ambiguity (VUCA).

The biblioshiny technique based on the bibliometrix R package was used to draw journal papers’ performance and scientific contributions by displaying distinctive features from the bibliometric method used in prior studies. The data was extracted from the Web of Science (WOS) and Scopus databases.

Since the 1990s, ERM publication has gained momentum, and it is generally categorised into four main themes. Studies by Miller (1992) and Bromiley et al. (2015) scored the highest in global and local citations, respectively. However, the Economic Outlook ranked first in quality of publications while the Journal of Risk and Insurance topped in quantity of publications. Collaborative research mainly exists between two authors, and the dynamic number of collaborative networks is evident in the USA.

This study is limited by the filtered keywords used to generate the search on journal papers’ in WOS and Scopus. It is imperative to have more comprehensive and rigorous analytics on ERM research to enable a direction for future research. Finally, ERM implementation better equips firms to mitigate risk in a VUCA environment.

This study attempts to fill a vacuum of ERM literature, specifically in business economics, in addressing VUCA. Moreover, it covers a comprehensive predetermined period of from its inception in 1983 until 2022.

The purposes of this paper are to examine the factors persuasive in building competitive advantage strategies for the co-living and co-working service operators and study the sustainability of the business model for co-living and co-working space.

In this research, a structured literature review of journals, articles, reports, conference proceedings, websites published in recent times and e-newspapers has been conducted. The first step of the research included identifying the relevant literature. For this step, multiple keywords were used in searching for literature on Google.com, Google Scholar, Proquest, Taylor & Francis, Emerald, Elsevier. Upon literature identification, the procured reports were divided into the following three parts: co-living reports, co-working report and others. More than 250 content reports were analyzed, and finally, 105 relevant literature reports from various sources were recorded for further analysis. Focus group discussion and semi-structured interviews were also conducted.

This study concluded after analyzing the literature, focus group discussion and semi-structured interviews that co-working and co-living space would be sustainable business if proper competitive strategies were leveraged, in accordance with the increase in demand over time. This study also serves as a wakeup call for the operators in the co-living and co-working sphere to work on their competitive advantages and differentiate themselves to tap business opportunities. The sustainability of the model by identifying the factors was also emphasized in this study. Further studies of co-living and co-working models should be conducted in the Indian context to analyze the multifarious potential that this new trend of shared accommodation can open up.

This study is based on content analysis, focus group discussion and semi-structured interview analysis. More content and literature were found to be evidenced mostly in Western literature. This is a limitation to the study. This study also had a limitation in including bigger sample of focus groups discussion and interviews; however, the analysis effectively set out a landscape of co-living and co-working space in India.

It is an original research work based on an existing concept and services. As co-living and co-working service operators are cropping up in major cities, enticing the target potential with a platter of services primarily linked with many of the beneficial factors, the researchers in this work attempt to examine the factors persuasive in building the competitive advantage strategies for the co-living and co-working space and the sustainability of these two business models. A ripe market with multifarious possibilities waiting to be tapped with the right plan of action is the need of the hour.

The purpose of this paper is to develop an appropriate machine learning model for predicting soil compaction degree while also examining the contribution rates of three influential factors: moisture content, electrical conductivity and temperature, towards the prediction of soil compaction degree.

Taking fine-grained soil A and B as the research object, this paper utilized the laboratory test data, including compaction parameter (moisture content), electrical parameter (electrical conductivity) and temperature, to predict soil degree of compaction based on five types of commonly used machine learning models (19 models in total). According to the prediction results, these models were preliminarily compared and further evaluated.

The Gaussian process regression model has a good effect on the prediction of degree of compaction of the two kinds of soils: the error rates of the prediction of degree of compaction for fine-grained soil A and B are within 6 and 8%, respectively. As per the order, the contribution rates manifest as: moisture content > electrical conductivity >> temperature.

By using moisture content, electrical conductivity, temperature to predict the compaction degree directly, the predicted value of the compaction degree can be obtained with higher accuracy and the detection efficiency of the compaction degree can be improved.

Automatic modulation recognition (AMR) is a challenging problem in intelligent communication systems and has wide application prospects. At present, although many AMR methods based on deep learning have been proposed, the methods proposed by these works cannot be directly applied to the actual wireless communication scenario, because there are usually two kinds of dilemmas when recognizing the real modulated signal, namely, long sequence and noise. This paper aims to effectively process in-phase quadrature (IQ) sequences of very long signals interfered by noise.

This paper proposes a general model for a modulation classifier based on a two-layer nested structure of long short-term memory (LSTM) networks, called a two-layer nested structure (TLN)-LSTM, which exploits the time sensitivity of LSTM and the ability of the nested network structure to extract more features, and can achieve effective processing of ultra-long signal IQ sequences collected from real wireless communication scenarios that are interfered by noise.

Experimental results show that our proposed model has higher recognition accuracy for five types of modulation signals, including amplitude modulation, frequency modulation, gaussian minimum shift keying, quadrature phase shift keying and differential quadrature phase shift keying, collected from real wireless communication scenarios. The overall classification accuracy of the proposed model for these signals can reach 73.11%, compared with 40.84% for the baseline model. Moreover, this model can also achieve high classification performance for analog signals with the same modulation method in the public data set HKDD_AMC36.

At present, although many AMR methods based on deep learning have been proposed, these works are based on the model’s classification results of various modulated signals in the AMR public data set to evaluate the signal recognition performance of the proposed method rather than collecting real modulated signals for identification in actual wireless communication scenarios. The methods proposed in these works cannot be directly applied to actual wireless communication scenarios. Therefore, this paper proposes a new AMR method, dedicated to the effective processing of the collected ultra-long signal IQ sequences that are interfered by noise.

The academic–practitioner gap has been a widely discussed and well-established issue. Despite numerous studies conducted in this area, empirical evidence reveals that the gap is widening and also emphasizes the exigency to bridge this gap. Hence, the purpose of this study is to propose an acceptable solution that will fill this lacuna.

The study adopts the qualitative research methodology and was based on the system theory (ST) and the institutional theory (IT). Interviews, based on a semi-structured questionnaire, were conducted, focusing on three categories, namely individuals with solely academic experience, individuals with both academic and industrial exposure and business leaders. The unit of analysis was the individual.

The study, which unearthed some rich and challenging evidence from the respondents, reveals that gaining industrial exposure and working on continuous professional development are vital for academics to narrow or even close this gap. In addition, serving as apex members at board level or in professional bodies, serving global organizations as lead consultants and working on research collaborations are other important dimensions for academics.

This study introduces an emerging model named the “Pentagon Model” and develops a corporate index (C-index) for academics to earn, similar to the h-index. The study also explains the operationalization of the C-index based on the proposed algorithm. Hence, it is the envisaged that this study will change the landscape of the academic sphere in practical terms.

This study was carried out with the sole intention of bridging the gap between academics and practitioners. The proposed model and the index, which were developed by the author purely based on the outcome of this study, pave the way for many future research studies, not only to further improve the C-index but also to minimize disparities in transdisciplinary work between academics and practitioners.

This study explores how problem-based learning (PBL) programs can address Sustainable Development Goals (SDGs) via the higher education (HE) curriculum, teaching materials and relevant assessments, supporting learning at scale for HE institutions.

Employing SDGs and their indicators as the coding framework, our two-phase study evaluates the curriculum and teaching materials of seven PBL programs at a leading higher education institution (HEI). The first phase involved a content analysis to assess the degree of sustainability integration in 156 relevant courses. The second phase applied a semi-automated mapping protocol to analyze learning and teaching materials in 120 relevant courses.

The school aligns with 17 SDGs (100%), covering 94 indicators (55.62%). On average, each program within the school addresses over ten of these goals and incorporates more than 24 associated indicators. However, the study reveals an imbalance in the incorporation of SDGs, with some goals not yet deeply and comprehensively embedded in the curriculum. While there is a substantial focus on sustainability theories, the practical implications of SDGs in emerging countries, particularly through case studies and assessments, require significant enhancement.

Mapping SDGs allows HEIs to identify strengths and gaps in SDG integration, thereby improving the PBL approach to enhance student work readiness in sustainability-focused careers.

Through the lens of transformative learning theory, this study provides evidence of SDG integration into PBL curricula. It highlights a mapping methodology that enables HEIs to evaluate their sustainability readiness in curriculum, teaching materials and relevant assessments.

The construction industry is widely recognized as one of the most hazardous sectors in the world. Despite extensive research on safety management, a critical issue remains that insufficient attention is devoted to safety practices in rural areas. Notably, accidents frequently occur during the construction of rural self-built houses (RSH) in China. Safety management tends to be overlooked due to the perceived simplicity of the construction process. Furthermore, it is essential to acknowledge that China currently lacks comprehensive laws and regulations governing safety management in RSH construction. This paper aims to analyze the behavior of key stakeholders (including households, workmen, rural village committee and the government) and propose recommendations to mitigate safety risks associated with RSH construction.

This paper applies evolutionary game theory to analyze the symbiotic evolution among households, workmen and rural village committee, in situations with or without government participation. Additionally, numerical simulation is utilized to examine the outcomes of various strategies implemented by the government.

Without government participation, households, workmen, and rural village committee tend to prioritize maximizing apparent benefits, often overlooking the potential safety risks. Numerical simulations reveal that while government involvement can guide these parties towards safer decisions, achieving the desired outcomes necessitates the adoption of reasonable and effective strategies. Thus, the government needs to offer targeted subsidies to these stakeholders.

Considering that during the construction phase, stakeholders are the main administrators accountable for safety management. However, there exists insufficient research examining the impact of stakeholder behavior on RSH construction safety. This study aims to analyze the behavior of stakeholders about how to reduce the safety risks in building RSH. Thus, the authors intend to contribute to knowledge in this area by establishing evolutionary game model. Firstly, this study carried out a theoretical by using tripartite evolutionary game to reveal the reasons for the high safety risk during building RSH. Practically, this research points out the important role of households, workmen and rural village committee in improving safety management in rural areas. Besides, some suggestions are proposed to the government about how to reduce construction safety risks in rural areas.

Introduction: Work-based learning (WBL) bridges the gap between academic theory and exposure to real-life situations where students’ knowledge is filtered and applied to relevant workplace environments.

Purpose: This study aims to examine students’ and employers’ voices on their perspectives of WBL. It focuses on students reading for an undergraduate degree in Bachelor’s in Commerce in two majors, with a specialisation in Public Policy at the University of Malta.

Methodology: Questionnaires were sent to students to obtain their views on the experience and benefits of WBL. This was followed by structured interviews conducted with employers and undergraduate students to provide an overview of their respective work-based experiences. WBL providers were asked to draw up reports on the students’ performance. The feedback which emerged from the structured interviews on the nature of these experiences was analysed. These tools helped to calibrate and refine the nature of these practices.

Findings: The study’s findings show that WBL experiences help students increase technical knowledge, improve their soft skills, and learn new tools, sought after by employers. Feedback emanating from employers’ perspectives serves to temper the University course curriculum to ensure that it is relevant to the requirements of modern-day society.

Sources highlight that lack of systematic labour training components results in low performance and productivity of labour, which leads the construction industry of many countries to face various challenges. This study aims to quantify the variations in the performance and productivity levels of labour in building construction projects through the applications of effective work-based training components.

A comprehensive literature review and a series of experts’ discussions with action-oriented communication approaches were conducted to develop a set of practices related to labour training, performance assessment and productivity measurements within a framework. The developed practices were applied to around 100 labourers working on nine building construction projects through a construction supervisory training programme.

The study presents the detailed patterns of the significant changes in labour performance and productivity levels. The majority of trained labourers have grown to perform the work process with some relevant theoretical and operational knowledge and skills. The overall results spotlight the significant behavioural changes that can be observed in workforce operations by improving labour performance, which resulted in implementing effective labour-rewarding practices within a framework.

Although the study findings were limited to the Sri Lankan context, the proposed practices can be applied to the industry practices of the construction sector of other developing countries and the other developing industries in similar ways/scenarios.

The study outcomes contribute to uplifting the work qualities of labourers with life-long learning opportunities and unlocking the potential barriers for expanding the local labour supply while controlling the excessive inclination of the local firms towards foreign labour. This paper describes further implications and future scopes of the study elaborately.

The study provides generalised mechanisms and practices that transform the labour characteristics and add new attributes for strengthening the values of construction supervision practices to obtain well-improved work outputs. The study outcomes reinforce the chain relationships among the training elements, labour performance and productivity levels, leading to upgrading current planning and operational management practices, especially adding constructive mechanisms in resource levelling and productivity benchmarking practices.