Search results

This paper aims to explain the factors shaping collective action within low-cost housing communities, focusing on parcel holders, through the utilisation of an expanded institutional analysis development (IAD) framework, which extends upon Ostrom’s foundational framework. Additionally, the paper explores four different property management approaches accessible to these communities.

The research employed a mixed-method approach comprising four sequential steps. Firstly, a quantitative inquiry entailed a questionnaire survey administered to 633 parcel holders across four low-cost housing schemes, aimed at discerning factors influencing collective action. Subsequently, a qualitative investigation involved face-to-face interviews with key stakeholders to elucidate the contributing factors of collective action, with a specific focus on Nursa Kurnia (a successful low-cost housing scheme comprising 200 units), accessible via Kuala Lumpur Middle Ring Road II. Thirdly, the study explored the social practice of “commoning the governance”. Lastly, the paper advocated for housing policy interventions, specifically proposing government subsidies for lower-income parcel holders.

Exemplified by the success of Nursa Kurnia, the research findings emphasised the importance of shifting local management’s mindset from a zero-sum approach to a win-win perspective. It highlighted the pivotal role of four factors (resource system, governance system, context and historical development) in shaping collective action and fostering improved property management practices. Moreover, the study highlighted the potential of “commoning the governance” as a new approach capable of addressing collective action challenges in low-cost housing management, presenting a promising avenue for future endeavours.

As more studies utilising the expanded IAD framework become available in the future, there is potential for further refinement and enhancement of the framework.

This study offers valuable insights for policymakers, property developers, local management and local communities, shedding light on challenges associated with the self-organisation of shared resources. Moreover, it highlights the potential of “commoning the governance” as a new property management approach to mitigate the impact of collective action problems.

The well-being of society’s most vulnerable segment is indicative of the overall societal health. This underscores the significance of addressing the interests and needs of these lower-income groups within the broader social context.

Exploring collective action within the context of self-organising low-cost housing, the study delves into an area marked by persistent challenges like free-riding tendencies and vandalism. Despite significant attention given to collective action issues in the past, the novel approach of “commoning the governance” remains unexamined in the realm of low-cost housing maintenance and management.

The COVID-19 pandemic has profoundly impacted the global economy, disrupting supply chains, causing job losses and altering consumer demand. In Malaysia, the real estate sector has been notably affected, with increased property impairments and overhang due to unprecedented uncertainty. Understanding these effects is crucial for policymakers and investors to prevent real estate and banking crises. This study aims to analyse the relationships between macroeconomic factors during the pandemic on property impairments and overhang, providing insights for maintaining macroeconomic stability. The findings will inform strategies for mitigating economic shocks, identifying opportunities, and guiding real estate policies in Malaysia and potentially globally.

This research article uses a time series ARDL regression analysis to examine pivotal macroeconomic factors including income, housing process, interest rates and unemployment on property loan impairments and property supply overhang in Malaysia. ARDL is effective to measure and analyse time series data, especially to understand the lagged impacts of macroeconomic factors. This can be seen by various economists in analysing macroeconomic factors affecting non-performing loans or the real estate finance using regression analyses both in Malaysia and other regions. The observations are gathered before, during and after the COVID-19 pandemic, spanning a five-year period with monthly frequency from 2018 to 2022.

The study emphasizes the critical importance of effectively managing unemployment and implementing policy interventions, such as moratoriums, to stabilize the economy and reduce the risk of loan impairments during crises like the COVID-19 pandemic. Additionally, this study highlights a significant inverse relationship between income per capita and loan impairments, underscoring the necessity for policies that promote economic growth and income equality. Initiatives targeting job creation, education and skills development can elevate income levels, thereby decreasing loan impairments. Lower lending interest rates during the pandemic also help mitigate the risk of loan impairments by facilitating borrowing, stimulating economic activity and enhancing financial well-being. Furthermore, the study suggests that while lower interest rates incentivize property developers and investors, understanding the intricate interaction between housing prices and supply is crucial for policymakers and stakeholders to effectively manage the housing market and ensure adequate housing supply, especially during crises.

This paper provides insight for policymakers, regulators, investors and property consultants into the dynamic effects of key macroeconomic factors amidst a global recession in how they impact the real estate market with regards specifically to all types of property loan impairments and property supply overhang. The observations are limited to the COVID-19 period, spanning five years with monthly data from 2018 to 2022. This understanding can facilitate the development of targeted strategic monetary policies and investment decisions in case of future recessions.

Policymakers should prioritize initiatives such as moratoriums and job creation programs to mitigate economic downturns. Additionally, financial institutions need to adjust lending practices in response to lower interest rates, while stakeholders in the housing market must understand the complex dynamics between housing prices and supply to ensure a balanced market. Overall, addressing underlying economic factors and implementing targeted policies are essential for building resilience and promoting sustainable economic growth amidst challenging circumstances.

Initiatives aimed at fostering income equality, creating employment opportunities and ensuring housing accessibility contribute to greater social cohesion and well-being. By promoting financial inclusion and building resilience to crises, societies can mitigate the adverse social impacts of economic challenges such as unemployment and housing affordability. Overall, addressing socioeconomic disparities and promoting inclusive growth are essential for fostering a more equitable and resilient society.

The originality and uniqueness of this study lie in its comprehensive analysis of the impact of COVID-19 on loan impairments and housing supply. While previous studies have focused on the pandemic’s effects on specific segments of the real estate market or property prices, this study provides a broad overview of its impact on property loan impairments and housing supply overhang. Finally, this study highlights the social and practical implications. Overall, this study offers a distinctive analysis of COVID-19’s impact on the real estate market and its implications for policymakers, real estate professionals and investors.

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.

To achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).

Results of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R² of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.

Therefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.

By adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

The purpose of this study is to investigate the effects of celebrity endorsers on consumer advocacy, customization and entertainment intentions based on the notion of the stimulus–organism–response (SOR) framework. In addition, this study aims to examine the mediating and moderating role of customization and entertainment intentions on the proposed relationships. The authors also intend to highlight the comparative effects between male and female young social media consumers on those proposed associations.

In the pursuit of comprehensive and rigorous data collection, this study adopted a quantitative methodology using a meticulously crafted questionnaire. The questionnaire survey was conducted in major cities of Malaysia using the convenience and snowball sampling techniques. A total of 576 responses were collected, even though 549 retorts were used for data analysis. In this investigation, the authors strategically used covariance-based structural equation modeling through the use of AMOS v. 24 as the primary data analysis tool. Augmenting the analytical depth, the authors also conducted a supplementary bootstrap analysis. The additional layers of examination were crucial for appraising the mediating and moderating effects inherent within the model, in which the PROCESS MACRO v.4.20 was used.

The results of this study revealed the significant direct positive effects of celebrity endorsers on consumer customization, entertainment and advocacy intentions. Consumer customization and entertainment intentions also found significant direct affirmative effects on consumer advocacy intention, along with the significant direct positive effects of consumer entertainment intention on consumer customization intention. The results further revealed that consumer customization and entertainment intentions cannot mediate the relationship between celebrity endorsers and advocacy intention. The entertainment intention also declined the mediating effects between celebrity endorsers and consumer customization intention. On the contrary, consumer customization intention significantly and positively, and entertainment intention also significantly but negatively, moderate the association between celebrity endorsers and consumer advocacy intention. This study also illustrates that the effects of those examined relationships differ between male and female young social media consumers.

This study investigates the impact of celebrity endorsers on consumer behavior, focusing on their customization, entertainment and advocacy intentions. It extends current SOR framework, enhances source credibility theory, fills gaps in the literature on social media brand engagement and underscores the significance of customization and entertainment intentions. The findings provide insights for managers aiming to harness consumer brand advocacy through celebrity endorsers effectively.

The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners.

Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses.

The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners’ intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners’ intentions to use IoT.

These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners’ intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field.

This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector.

The purpose of this paper is to develop a model considering synergy effect for prefabricated construction service combination selection.

This research defines prefabricated construction service as a service-led construction method that meets the specific requirements of clients. Based on network theory, the multi-dimensional collaborative relationships of the prefabricated construction inter-services are formulated. The synergy effect is quantitatively calculated through the linear weighting of the strengths of collaborative relationships. Further, a weighted synergy network (WSN) is developed, from which a service composition selection model considering the synergy effect is established. Then, a genetic algorithm is employed to implement the model.

The results showed that (1) when the number of prefabricated construction services is increased, the synergy effect of combination options is enhanced; (2) The finer-grained prefabricated construction services, the stronger the synergy effect of service combination; (3) Clients have heterogeneous preferences for collaborative relationships, and there are differences in the synergy effect of service combination.

The contribution of this research includes proposed a method to quantify the synergy effect from the perspective of collaborative relationships, explored the specific procedure for the prefabricated construction service combination selection under the service-led construction, and provided a reference for promoting the development in construction. Besides, the model proposed could be applied to prefabricated construction service composition selection with diverse research boundaries or client preferences by executing the same procedure.

Equitable risk allocation is important for the effective management of inevitable risks in International Construction Joint Venture (ICJV) projects. Previous studies have documented risks facing ICJV projects. However, there is a dearth of studies on the risk allocation preferences that take into consideration the opinions of both the local and foreign partners. This study aims to fill this gap by ascertaining the risk allocation preferences of the partners of ICJV projects for effective risk management.

Through a survey, data on risk allocation preferences were collected from both local and foreign partners of ICJV projects using a comprehensive register of 74 risks.

Following analysis, six risks were allocated to the local partner, 11 were allocated to the foreign partner, 51 risks were shared, four were allocated to a third party and two were to be negotiated based on the specific circumstances of the project. Practically, the study’s findings will help ICJV partners in drafting their ICJV contracts to adequately allocate risks and reduce contract negotiation time considerably.

The findings from this study will help partners in drafting their joint venture contract agreement and also reduce the period for contract negotiation. Knowledge of the preferred risk allocation is important in allocating risks in the contract agreement to the relevant partner for effective management.

This study, to the best knowledge of the authors, is one of the early studies to ascertain the risk allocation preferences of ICJV project partners in the Ghanaian construction industry – a departure from previous studies which focused on the identification and evaluation of risks. This study is also different from previous studies by considering the allocation preferences of both partners of the ICJV. The collection of data from both partners of the ICJV helped to consider their perceptions on risk allocation and evaluation, essentially leading to cross-cultural and optimal risk allocation preferences.

As the complex influencing factors for financing decisions and limited information at the early project stage often render inappropriate financing mode and scheme (FMS) selection in the large-scale urban rail transit (URT) field, this study aims to identify the multiple influencing factors and establish a revised case-based reasoning (CBR) model by drawing on experience in historical URT projects to provide support for effective FMS decisions.

Our research proposes a two-phase, five-step CBR model for FMS decisions. We first establish a case database containing 116 large-scale URT projects and a multi-attribute FMS indicator system. Meanwhile, grey relational analysis (GRA), the entropy-revised G1 method and the time decay function have been employed to precisely revise the simple CBR model for selecting high-similarity cases. Then, the revised CBR model is verified by nine large-scale URT projects and a demonstration project to prove its decision accuracy and effectiveness.

We construct a similarity case indicator system of large-scale URT projects with 11 indicators across three attributes, in which local government fiscal pressure is considered the most influential indicator for FMS decision-making. Through the verification with typical URT projects, the accuracy of our revised CBR model can reach 89%. The identified high-similarity cases have been confirmed to be effective for recommending appropriate financing schemes matched with a specific financing mode.

This is the first study employing the CBR model, an artificial intelligence approach that simulates human cognition by learning from similar past experiences and cases to enhance the accuracy and reliability of FMS decisions. Based on the characteristics of the URT projects, we revise the CBR model in the case retrieval process to achieve a higher accuracy. The revised CBR model utilizes expert experience and historical information to provide a valuable auxiliary tool for guiding the relevant government departments in making systematic decisions at the early project stage with limited and ambiguous project information.