Since the introduction of the Doi Moi economic reform in 1986, the real estate market in Vietnam has witnessed a sharp increase in foreign investment inflows and a remarkable growth in the housing market, particularly for high-rise apartments in large cities. This study investigates the determinants of apartment prices in Ho Chi Minh City (HCMC) and Hanoi, the two most representative cities in Vietnam. The spatial distribution of apartments and their price determinants were addressed by the spatial analysis of Geographic Information System (GIS) and the hedonic model. The price determinants of both cities were closely associated with downtown-related factors; moreover, the externalities of urbanization affected each city. While HCMC was more related to the locational attributes of urban amenities and community density as well as programs because of unmanaged urbanization, Hanoi was more related to housing attributes, since the majority of apartment projects were developed under urban infrastructure development supported by the central government. Apartment cluster maps of each city clearly show the contrast of housing distribution. Our findings clarify the impact of government policies on housing price determinants and can be a reference for private- and public-sector stakeholders seeking to undertake economically and socially sustainable housing development projects in Vietnam.

We analyse the factors involved in the selection of a development site to secure the economic feasibility and profitability of a public development real estate project through a comparative analysis with private development projects. Logistic regression was used as the analysis method. In the case of public development projects, whether or not the investment screening passed was used as a dependent variable, and in the case of private development projects, the successful bid rate was used as a dependent variable. Independent variables were selected based on prior research on variables suitable for the purpose and situation of the project. The results show that the greater the total development costs of a public development project and the greater the size of a private development project, the greater the rate of approval and bidding success. For public projects, the rate of approval decreases when there are several subways, train stations, and supermarkets; however, this is not the case for private projects, owing to differences in development methods and project purposes. From a public standpoint, the balanced regional development, revitalisation of old city centres, and implementation of social overhead capital projects in neighbourhoods lacking infrastructure have a strong influence. From a private sector perspective, the mobile/resident population, modification in extra demand, and feasibility analysis have a strong influence. In sum, if the private sector avoids large-scale supermarket projects, they can be conducted as public development projects to enhance residents’ quality of life and revitalise the regional economy. Researchers should examine what could be benchmarked in the private sector in the operational stage and explore ways to maximise profitability and reduce financial burden.

This study investigates the integration of methods for real estate development planning and feasibility studies in the changing business environments of emerging big-data. It examines high-rise mixed-use development projects for the highest best use by combining fuzzy theory; thus, it identifies a big data-based innovative decision-making method for systemizing the various factors expected to influence real estate development. In this context, the study creates new evaluation fields and factors by integrating both conventional and big-data based high-rise mixed-use projects. The weight of each value was calibrated by relative significance and fuzzy measure using the Analytic Hierarchy Process (AHP) method. A measuring technique that applies analysis methodology to the evaluation areas was developed for more objective and clearer evaluation, and its application in the field was proposed. Evaluators can systematically assess the concerned evaluation areas during development project planning by examining the process. The findings also provided implications for the evaluation system’s operation by reflecting the variability of specific conditions of the varying projects in real estate and urban and land use planning.

This study identified the balanced development indicators that affected the results of the 2019 central investment review of local financial investment projects in South Korea. Factors with positive B values and categorized under the sectors of safety, health, and social welfare were given greater weight during the investment review. Based on the empirical analysis results and verification of the findings using sector-specific weights, this study proposed measures to improve investment reviews of local financial projects considering balanced regional development. We believe that our study makes a significant contribution to the literature because there is a lack of empirical studies on the topic, especially those using sector-specific weights based on investment review criteria. Further, we believe that this paper will be of interest to the readership of your journal because it addresses balanced regional development, which is considered a prerequisite for sustainable economic growth.

The study aims to prioritise investment projects of local Korean governments through priority analysis and provide basic data to secure sustainability by measuring the operational performances of these projects. We utilised the AHP technique to draw relative weight, followed by their correction, thereby deriving priorities across all 14 fields; the most important ones being social welfare (0.110), healthcare (0.108), fire prevention (0.097), environmental hygiene (0.092), and cultural tourism (0.088). Important areas prioritise balance and equity and their operational efficiency and productivity were based on statistical annual reports of 17 cities and provinces in Korea and Kosis data obtained from the National Statistical Office. For the measurement, we used six years of time series data from 2015 to 2020 and single point-in-time and annual trend analyses. The input factors were the amount of revenue and the number of public officials, and the output factors included the water and sewage supply rate, the number of tourists travelling for free, and the number of hospitals, welfare facilities, and rescue cases. These selections were appropriate to draw conclusions by analysing operational performance with detailed items in the priority field. Results revealed that the operating performance was excellent. However, to secure additional operational efficiency and productivity, technological innovation is needed.

This study identified, analysed, and prioritised significant factors for standardising the Korean smart city project evaluation system. We analysed the efficiency and productivity of companies currently providing smart city services, considering both policy and practical aspects. The prioritisation of smart city planning reflects the latest trends in South Korea, where urban planning is moving towards smart city planning. Furthermore, public–private and private–private partnership capacity-building highlights the importance of business scalability. This shows that smart city services are only stabilised when the private sector is involved in and leads the project, rather than focusing on public development. The feasibility of building intelligent facilities indicates that smart city projects should be implemented after securing cost–benefit feasibility. The results were used as the basis for an evaluation system, showing that, in smart city convergence alliances, small- and medium-sized enterprises achieved the highest efficiency by reducing inputs to 81% and 86% under the assumptions of constant and variable returns to scales, respectively. As the operational aspect is more problematic than the technical aspect, policy alternatives are necessary for smooth business progress, including increased flexibility of laws and institutions and the activation of policies that temporarily relieve regulations for smart city projects.