Search results

Employability skills training programmes are an effective means for reducing unemployment rates. Such programmes also have the potential to improve the general well-being (e.g. self-efficacy) of disadvantaged individuals, however, reliable longitudinal evaluations of the psychological benefits of such programmes are limited. The present study evaluated the impact of an employability programme offered to disadvantaged adults in North-West England on self-efficacy. Additionally, the study aimed to identify risk factors for programme disengagement to identify at-risk groups that require further support.

Secondary longitudinal data pertaining to the background characteristics, programme engagement and self-efficacy scores (repeatedly measured on a monthly basis) of 308 programme users were analysed.

Results demonstrated that employability programme engagement significantly increased self-efficacy scores. Additionally, the findings suggested that individuals with mental health and learning difficulties were more likely to disengage from the programme. The findings demonstrate that employability programmes can have a positive impact on the well-being of individuals from disadvantaged backgrounds, however, prolonged engagement is needed for which some individuals require further support with.

The present study analysed longitudinal data from a diverse sample of disadvantaged individuals to reliably evaluate psychological outcomes from employability training programmes.

The purpose of this paper is to realize the lightweight of connecting rod and meet the requirements of low energy consumption and vibration. Based on the structural design of the original connecting rod, the finite element analysis was conducted to reduce the weight and increase the natural frequencies, so as to reduce materials consumption and improve the energy efficiency of internal combustion engine.

The finite element analysis, structural optimization design and topology optimization of the connecting rod are applied. Efficient hybrid method is deployed: static and modal analysis; and structure re-design of the connecting rod based on topology optimization.

After the optimization of the connecting rod, the weight is reduced from 1.7907 to 1.4875 kg, with a reduction of 16.93%. The maximum equivalent stress of the optimized connecting rod is 183.97 MPa and that of the original structure is 217.18 MPa, with the reduction of 15.62%. The first, second and third natural frequencies of the optimized connecting rod are increased by 8.89%, 8.85% and 11.09%, respectively. Through the finite element analysis and based on the lightweight, the maximum equivalent stress is reduced and the low-order natural frequency is increased.

This paper presents an optimization method on the connecting rod structure. Based on the statics and modal analysis of the connecting rod and combined with the topology optimization, the size of the connecting rod is improved, and the static and dynamic characteristics of the optimized connecting rod are improved.

The purpose of this paper is to explore how process management (PM) can support small- and medium-sized enterprises (SMEs) in pursuing sustained competitive advantage. For this purpose, a dynamic capabilities (DC) lens was used.

A narrative literature review and a multiple case study with an action research approach at two road freight transport companies were used.

PM provides structure and system thinking to support the development of competitive advantage. Concerning PM, management of knowledge, management style and process orientation are key factors for the generation of competitive advantage for SMEs.

This study contributes to PM literature by studying its support for and implementation at SMEs. Furthermore, the study contributes to the literature on DC by providing concrete examples of activities linked to such capabilities.

This study contributes to practitioners by providing examples of implementing PM and identifying competitive advantage, connected with PM elements.

This study has social and environmental implications for the quality of life of the Swedish people.

This paper contributes to clarifying the connection between the research fields of quality management and DC to explore how PM can support SMEs in pursuing sustained competitive advantage.

The health, well-being and productivity (i.e. WELL) of office building occupants are vulnerable to poor office environments. Therefore, this study aims to identify new features and concepts of office buildings in supporting occupants’ WELL. To achieve that aim, this study: explores new WELL features for office buildings, develops new WELL concepts for office buildings and examines the influence of the newly developed WELL concepts on existing WELL building standard (WELL v2) concepts.

The first phase involved ten experts to assign weightage for health, well-being and productivity. In the second phase, 206 questionnaire survey data were collected from office building occupants throughout Malaysia. Exploratory factor analysis established new WELL concepts for office buildings. Partial least-squares structural equation modelling examined the influence of the newly developed WELL concepts on the existing WELL v2 concepts.

Two new WELL concepts were developed: “space and services”, consisting of sufficient space, workstation privacy, office layouts, building automation systems, cleanliness and information technology (IT) infrastructure, and “building security”, consisting of security systems and safety at parking lots. Here, “space and services” influences all existing WELL v2 concepts, and “building security” influences the water, nourishment, mind and community concepts of WELL v2.

This study uncovers holistic WELL building concepts to support occupants’ health, well-being and productivity with additional new features and concepts for construction industry policymakers to establish holistic building assessment tools.

Relying on the effort-recovery model, this study aimed to test how and when a good night’s sleep increases in daily physical health. The authors hypothesized that when individuals have a good night’s sleep, it helps them to recover their self-regulatory resources, and, in turn, these cognitive resources improve their physical health experienced at work. Furthermore, the authors argue that this will be different depending on the individuals’ levels of neuroticism; that is, the indirect relationship between sleep duration and physical health through self-regulatory resources will be stronger for individuals who score lower on neuroticism, and in contrast, the relationship will be buffered for those who score higher on neuroticism.

To test the hypothesized model, the authors conducted a three-wave longitudinal study with working adults (N = 262). The authors used multilevel modelling to test if neuroticism moderated the indirect relationship between sleep duration and physical health through self-regulatory resources, at both between and within-person levels.

The multilevel results showed that a good night’s sleep recovered self-regulatory resources needed to promote physical health; however, this indirect relationship was buffered for those who scored higher on neuroticism (versus lower levels of neuroticism).

Hence, the role of neuroticism as a potentially harming condition for employees’ physical health is pointed out.

The findings highlight the relevance of sleep as a recovery activity for both cognitive and physical resources experienced during the working day. However, this appears to be attenuated for employees with higher levels of neuroticism.

The current research aims to investigate the impact of coronavirus 2019 (COVID-19) evolution, government stringency measures and economic resilience on stock market volatility in the Middle East and North African (MENA) emerging markets. Other macroeconomic factors were also taken into account.

Based on financial data from 10 selected MENA countries, we tested an integrated framework that has not yet been explored in prior research. The exponential generalized autoregressive conditional heteroskedasticity (E-GARCH) was adopted to analyze data from March 2020 to February 2022.

Our research illustrates the direct and indirect effects of the virus outbreak on stock market stability and reports that economic resilience could alleviate the volatility shock. This finding is robust across the various proxies of economic resilience used in this study. We also argue that the negative impact of the pandemic on equity market variation gets more pronounced in countries with higher level of stringency scores.

Policymakers ought to strengthen their economic structures and reinforce the economic governance at the national level to gain existing and potential investors’ trust and ensure lower stock market volatilities in times of crisis. Our study also recommends some key economic factors to consider while establishing efficient policies to tackle unexpected shocks and prevent financial meltdowns.

Our findings add to the evolving literature on the reaction of economic and financial markets to the sanitary crisis, particularly in developing countries where research is still scarce. This study is the first of its kind to investigate the stock market reaction to stringency measures in the understudied MENA region.

Augmented reality (AR) and virtual reality (VR) are increasingly recognized among technologies potentially driving the digital innovation of small and medium-sized enterprises (SMEs). Nevertheless, the implications of AR/VR adoption in innovation processes have yet to receive much attention to date, with the need to explore the issues facilitating a systematic implementation in the SME context. This study aims to investigate the possible innovation paths of SMEs as a result of AR/VR adoption.

The authors performed a multiple case study research involving six Italian SMEs in manufacturing and service sectors that are investing in AR and/or VR solutions and are digitally innovating thanks to these technologies.

AR/VR solutions lead to different types of innovation in SMEs, i.e. for innovating product or service offerings, business processes or even the business model, when AR/VR extends to the company business logic. SMEs demonstrate being able to leverage internal sources with the essential commitment of top management and low resistance of employees in all kinds of AR/VR-enabled innovations. Conversely, they involve different external innovation sources according to the type of innovation pursued. Organizational issues emerged as more relevant than technological issues.

Results contribute to the literature on digital transformation of SMEs and provide managerial guidance on innovation sources and organizational issues to be considered to effectively deploy AR/VR solutions into specific innovation paths.

This study explores the impact of emergent technologies in the innovation process along with multiple perspectives, degree of complexity, and strategic importance in the SME context.

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

This study was conducted to investigate the impact of indoor environmental quality (IEQ) and internal design on the performance of students in university dormitories in Tehran and North Cyprus.

Using a survey questionnaire, 298 students living in student dormitories in Tehran and North Cyprus were surveyed for data collection.

Research has shown that the academic performance and well-being of students are heavily impacted by factors related to IEQ and internal design. The study conducted in Tehran and North Cyprus has identified the most effective components of IEQ and internal design for student dormitories. The study suggests that proper ventilation, furniture design, temperature control and lighting design are key factors that significantly affect IEQ and internal design. Control and lighting design are key factors that significantly affect IEQ and internal design.

Originality: The study utilizes a comparative study designed to analyze the differences and similarities between the two locations.

The purpose of this paper is to emphasize the risks involved in modeling inflation volatility in the context of macroeconomic policy. For countries like Ghana that are always battling economic problems, accurate models are necessary in any modeling endeavor. We estimate volatility taking into account the heteroscedasticity of the model parameters.

The estimations considered the quasi-maximum likelihood-based GARCH, stochastic and Bayesian inference models in estimating the parameters of the inflation volatility.

A comparison of the stochastic volatility and Bayesian inference models reveals that the latter is better at tracking the evolution of month-on-month inflation volatility, thus following closely the data during the period under review.

The paper looks at the effect of parameter uncertainty of inflation volatility alone while considering the effects of other key variables like interest and exchange rates that affect inflation.

Economists have battled with accurate modeling and tracking of inflation volatility in Ghana. Where the data is not well-behaved, for example, in developing economies, the stochastic nature of the parameter estimates should be incorporated in the model estimation.

Estimating the parameters of inflation volatility models is not enough in a perpetually gyrating economy. The risks of these parameters are needed to completely describe the evolution of volatility especially in developing economies like Ghana.

This work is one of the first to draw the attention of policymakers in Ghana towards the nature of inflation data generated in the economy and the appropriate model for capturing the uncertainty of the model parameters.