Yun Fah Chang, Wei Cheng Choong, Sing Yan Looi, Wei Yeing Pan and Hong Lip Goh
The purpose of this paper is to analyse and predict the housing prices in Petaling district, Malaysia and its six sub-regions with a set of housing attributes using functional…
Abstract
Purpose
The purpose of this paper is to analyse and predict the housing prices in Petaling district, Malaysia and its six sub-regions with a set of housing attributes using functional relationship model.
Design/methodology/approach
A new multiple unreplicated linear functional relationship model with both the response and explanatory variables are subject to errors is proposed. A total of 41,750 housing transacted records from November 2008 to February 2016 were used in this study. These data were divided into 70% training and 30% testing sets for each of the selected sub-regions. Individual housing price was regressed on nine housing attributes.
Findings
The results showed the proposed model has better fitting ability and prediction accuracy as compared to the hedonic model or multiple linear regression. The proposed model achieved at least 20% and 40% of predictions that have less than 5% and 10% deviations from the actual transacted housing prices, respectively. House buyers in these sub-regions showed similar preferences on most of the housing attributes, except for residents in Shah Alam who preferred to stay far away from shopping malls, and leasehold houses in Sri Kembangan are more valuable. From the h-nearest houses indicator, it is concluded that the housing market in Sungai Buloh is the most volatile in Petaling District.
Research limitations/implications
As the data used are the actual housing transaction records in Petaling District, it represents only a segment of Malaysian urban population. The result will not be generalized to the entire Malaysian population.
Practical implications
This study is expected to provide insights to policymakers, property developers and investors to understand the volatility of the housing market and the influence of determinants in different sub-regions. The potential house buyers could also use the model to determine if a house is overpriced.
Originality/value
This study introduces measurement errors into the housing attributes to provide a more reliable analysis tool for the housing market. This study is the first housing research in Malaysia that used a large number of actual housing transaction records. Previous studies relied on small survey samples.
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Behrooz Nazemi and Mohsen Rafiean
The purpose of this paper is to use Group Method of Data Handling (GMDH)-type artificial neural network to model the affecting factors of housing price in Isfahan city housing…
Abstract
Purpose
The purpose of this paper is to use Group Method of Data Handling (GMDH)-type artificial neural network to model the affecting factors of housing price in Isfahan city housing market.
Design/methodology/approach
This paper presents an accurate model based on GMDH approach to describing connection between housing price and considered affecting factors in case study of Isfahan city based on trusted data that have been collected from 1995 to 2017 for every six months. The accuracy of the model has been evaluated by mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) in this case.
Findings
Due to the obtained value of MAPE, RMSE and MAE and also their interpretation, accuracy of modelling the factors affecting housing price in Isfahan city housing market using GMDH-type artificial neural network that has been conducted in this paper, is acceptable.
Research limitations/implications
Due to limitation of reliable data availability about affecting factors, selected period is from 1995 to 2017. Accessing to longer periods of reliable data can improve the accuracy of the model.
Originality/value
The key point of this research is reaching to a mathematical formula that accurately shows the relationships between housing price in Isfahan city and effective factors. The simplified formula can help users to use it easily for analysing and describing the status of housing market in Isfahan city of Iran.
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Sadith Chinthaka Vithanage, Michael Sing, Peter Davis and Manikam Pillay
Off-site manufacturing (OSM) has emerged as a method of modern construction that provides several benefits including achieving lower costs, a quicker schedule and environmentally…
Abstract
Purpose
Off-site manufacturing (OSM) has emerged as a method of modern construction that provides several benefits including achieving lower costs, a quicker schedule and environmentally friendly solutions. Although numerous researches are available that advocate the adoption of OSM, the devotion towards OSM safety is somewhat limited. However, OSM invariably generates safety risks, including dynamics and uncertainty in safety management. There is a unique call to have an investigation on the identification of OSM safety risks.
Design/methodology/approach
To provide a full picture on the OSM safety, a systematic literature review was adopted based on interpretivist philosophical stance. The literature search was conducted in key electronic databases to identify OSM safety-focused publications. Bibliometric analysis was adopted to identify co-occurrences of keywords and collaboration among authors in OSM safety-related research publications. Content analysis was conducted to provide a taxonomy of OSM safety risks. The identified studies were critically analysed to determine the focus of OSM safety research and provide future research directions.
Findings
The results demonstrated frequently appeared OSM safety aspects while highlighting the limitedness of collaborative research outputs in common authorships. Content analysis subsequently unveiled safety risks in OSM under human, organisational and work environmental factors. A critical analysis of extant literature revealed seven research classifications of OSM safety. Directions were offered to enhance OSM safety by applying principles of targeted safety management concepts, technology-driven safety measures and bespoke training programs.
Originality/value
This study provides a comprehensive review on the identification of safety risks throughout OSM while presenting the avenues useful for the development of OSM safety management strategies.
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Sidhartha Sahoo, Shriram Pandey and Sanjaya Mishra
The purpose of this study is to identify seminal research works on distance and online learning that have had significant impact on the domain.
Abstract
Purpose
The purpose of this study is to identify seminal research works on distance and online learning that have had significant impact on the domain.
Design/methodology/approach
The authors used the SCOPUS database for this study as the data source, and a well-defined search strategy retrieved the items for analysis. First, the authors identified the h-index (n = 207) of the discipline to determine the threshold for listing the top works. The authors critically analysed these classic publications using several bibliometric parameters to present the analysis. To understand the primary focus of the classic research works, the authors also carried out a keyword cluster analysis using VOSviewer.
Findings
While the USA produced maximum classic research, authors from Canada have maximum research visibility in terms of citations (n = 474.06). Canada also received the highest value of RCI (1.30), followed by Taiwan and Australia. The majority of the classics are published in 67 scientific journals. Of these, Computers and Education published the highest number with a quarter of the total citations (n = 19,403). Although e-learning was the nucleus of the research theme, the authors observed that students, learning systems, online learning, blended learning, learning management systems and computer-aided instructions dominated their influence in the research cluster.
Originality/value
To the best of the authors’ knowledge, this is the first of its kind work in the field of distance and online learning. Findings of this study would be useful to faculty, researchers and students in the discipline to focus on the seminal works and understand their implications better in the context of the growing significance of the discipline.