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The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

This paper aims to examine the impact of the COVID-19 pandemic on the private label food products, specifically assessing the stability and changes in factors influencing purchasing decisions, and comparing pre-pandemic and post-pandemic datasets.

The study employs the Extra Tree Classifier method, a robust quantitative approach, to analyse data collected from questionnaires distributed among two distinct consumer samples. This methodological choice is explicitly adopted to provide a clear classification of factors influencing consumer preferences for private label products, surpassing conventional qualitative methods.

Despite the profound disruptions caused by the COVID-19 pandemic, this research underscores the persistent hierarchy of factors shaping consumer choices in the private label food market, showing an overall stability in consumer behaviour. At the same time, the analysis of individual variables highlights the positive increase in those related to product quality, health, taste, and communication.

The use of online surveys for data collection may introduce a self-selection bias, and the non-probabilistic sampling method could limit the generalizability of the results.

Practical implications suggest that managers in the private label industry should prioritize enhancing quality control, ensuring effective communication, and dynamically adapting strategies to meet evolving consumer preferences, with a particular emphasis on quality and health attributes.

This study contributes to the existing body of literature by providing insights into the profound transformations induced by the COVID-19 pandemic on consumer behaviour, specifically in relation to their preferences for private label food products.

A lack of suitably qualified Building Information Modelling (BIM) professionals is understood to be a major barrier towards higher uptakes of BIM in the Australian construction industry. In response, Australian universities have tried to integrate the teaching of BIM into construction-related curricula, but with limited success. The acknowledged impediment is the lingering mismatch between what universities offer and what industry actually needs. However, the exact nature of that mismatch has yet to be identified. This study addresses that knowledge gap. It assesses both the current status of BIM competencies among university graduates and explores how BIM education at Australian universities may be improved to deliver BIM work readiness, as required by the industry.

This paper employed a qualitative research approach, utilizing 17 semi-structured interviews with experts in the Australian BIM industry. The Person-Organization (PO) fit theory, which emphasizes the congruence between individual and organizational characteristics, was utilized as a theoretical framework to examine the compatibility between “demand” and “ability” perspectives. The resulting data were analysed using this theoretical framework to gain insights into the PO fit perspectives in relation to BIM industry practices.

Findings reveal that graduates are generally competent regarding the use of BIM software. However, employers require much more than software skills, and expect recruits to have the capability to implement BIM as a process according to information management standards. Specifically, graduates are significantly deficient in matters of BIM protocols, collaboration and coordination, information workflows as well as completion and handover procedures.

This study is the first of its kind that bridges the gap between industry expectations and university education, in the Australian context, moving beyond the common discourse in education literature, which is exclusively focused on assessing students’ perceptions about BIM.

The objectives of this study are twofold: firstly, to examine the effect of job variety on employee engagement and job burnout, and the effect of employee engagement and job burnout on employee happiness and job stress, respectively. Secondly, it examines the mediating role of employee engagement between job variety and employee happiness, as well as the mediating role of job burnout between job variety and job stress.

Data were collected from front-line nurses working in the health sector in Pakistan's major cities. A total of 169 samples were collected using online and face-to-face data collection approaches. The theoretical model was tested using the Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4.0.

The findings of this study highlight that job variety has a positive impact on employee engagement, which in turn leads to employee happiness among professional frontline nurses. Additionally, job variety as a demand increases employee burnout, which subsequently increases frontline nurses' job stress. The results also indicate that employee engagement mediates the relationship between job variety and employee happiness, while burnout mediates the relationship between job variety and job stress.

To date, there has been little research investigating the dual impact of job variety, leaving a significant gap in the existing literature. This study aims to address this gap and provide implications for both academics and HR managers by challenging the misconception that job variety is always a positive job resource.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

The built environment is taking enormous leaps towards its digitalization. Computer-aided tools such as building information modeling (BIM) are found in the forefront of this evolution, playing a critical role in creating the foundations for the upcoming development of smart low-carbon cities. However, the potential of BIM is still untapped – links will need to be created among the available and forthcoming methodologies under one integral operational system. The purpose of this paper is to present an integrated BIM-based life cycle-oriented framework for achieving sustainable constructions at the pre-construction phase. The developed framework represents an example of the approaches that the construction industry will need to adopt to integrate the different tools under an integrated smart city context.

The methodological approach follows the development of four same-volume different-configuration three-dimensional BIM designs, which are coupled with life cycle assessment (LCA) tools for establishing sustainable building design.

The results of this paper indicated that the choice of building design and shape can play a significant role in reducing the embodied energy and embodied carbon of buildings, achieving a reduction of up to 15% compared to a reference building of same volume and gross floor area.

The originality of this paper is found in its approach application by coupling three-dimensional BIM models with LCA data, the use of reinforcement detailing in an nD BIM study and the employment of country-specific LCA databases.