The elderly (senior) is a unique generation with specific housing preferences. This study aims to provide an overview on the elderly housing preferences of the Malaysian generations. The objectives of this study are: (i) To define elderly; (ii) To identify the elderly housing preferences features; and (iii) To determine the elderly housing preferences by different age group (generations). The study adopts mixed-method strategy and revealed; (i) Health; (ii) Safety; (iii) Convenience; (iv) Amenity; and (v) Community as the preferred elderly housing features. This study provides guidance to the main actors of property development on the preferred elderly housing features.Keywords: Elderly (Senior) Housing; Aging-in-Place; The Residential Environment Preferences; GenerationseISSN: 2398-4287 © 2020. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.DOI: https://doi.org/10.21834/e-bpj.v5i13.2102

The elderly generation is distinctive, and this reflects their housing preferences. This study aims to offer an outline of the Malaysian generational elderly housing preferences. The main objectives of this study; (i) To define elderly; (ii) To classify the features of elderly housing preferences; and (iii) To ascertain the elderly housing preferences by generations. This study applies mixed-method strategy and shown; (i) Health; (ii) Safety; (iii) Convenience; (iv) Community; and (v) Amenity as the preferred elderly housing features. This study guides the main actors of property development on the preferred elderly housing by the Malaysian generations.Keywords: Ageing in Place; Generations, Elderly (Senior) housing; Residential Environment PreferenceseISSN 2398-4295 ©2020 The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.DOI: http://dx.doi.org/10.21834/ajbes.v5i18.185

Monte Carlo Simulation is a mathematical technique that generates random variables for modelling risk. This technique is suitable and benefits to the various client such as public and private sector to evaluate the costing prepared by the Quantity Surveyor. The methodology used is a qualitative approach consisting of a case study and document analysis. The result shows through Monte Carlo simulation, can predict the worst return from the accuracy of the estimation and given absolute confidence for project development. Keywords: Monte Carlo, Risk Analysis, Cost Prediction, Qualitative Approach eISSN 2398-4279 ©2020 The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.
DOI: https://doi.org/10.21834/ajqol.v5i18.204

As the world’s population ages, more attention is being given to the issue of the supply of Retirement Villages. Retirement Villages is a type of elderly housin

Low-bid selection can significantly impact construction delivery, leading to delays, substandard quality, and cost overruns if pricing risks are not considered. This research, however, provides a solution that empowers Quantity Surveyors (QS) to act. They can implement BIM to ensure the accuracy of the prepared pre-tender estimate. Furthermore, the application of Monte Carlo (MC) simulation, using probability distribution, can provide a range of tender prices that can be accepted by the client, thereby mitigating the risk of pricing error by the contractor. As demonstrated in this research, the combination of BIM and MC simulation offers a powerful tool for the construction industry. A case study method through document analysis has been chosen to investigate the patterns of tender prices the bidders offer for a bridge construction project. Then, using a pre-tender estimate as a starting point, MC simulates thousands of probable tender prices in a random sequence based on normal distribution. The outcomes indicate that the clients could avoid the high risk of choosing a contractor based on the lowest tender price in a construction project by using Monte Carlo. Therefore, the research shows that applications of Building Information Modelling and Monte Carlo simulation are not just beneficial but crucial for judgment for clients in the construction industry, and it is up to the stakeholders to implement these findings.