Real Estate Brokerage Research Articles

The Impact of Digital Transformation on Service Models and Employee Skill Requirements in Taiwan's Real Estate Brokerage Industry

This paper investigates how digital transformation impacts service delivery models and employee skill requirements in Taiwan's real estate brokerage industry. Through a multiple-case comparison approach, data was collected from 200 participants across real estate firms to examine organizational adaptation to technological change. The research employed structural equation modeling and hierarchical linear modeling to analyze relationships between compensation satisfaction (β = 0.45, p < 0.001), digital competency levels, and internal case circulation patterns. Results demonstrate that digital technologies significantly reshape brokerage operations, with digitalized companies achieving 32% higher client acquisition rates and 45% reduction in transaction processing time. Analysis reveals that employee digital literacy accounts for 28% of performance variance, while organizational support systems explain 23% of technology adoption rates. The findings extend service innovation literature by establishing empirical links between compensation systems and digital transformation success, providing a practical framework for technology integration in Taiwan's real estate sector. This research offers evidence-based recommendations for firms implementing digitalization strategies and developing employee capabilities in response to industry evolution.

AI in Vocational Training: A Qualitative Interview Study of Early-Stage Practitioners in the Real Estate Brokerage Industry in China

This study aims to unveil the individual and sectoral factors influencing the integration and utilization of artificial intelligence (AI) in vocational training among early-stage practitioners in China's real estate brokerage industry. The study involved in-depth interviews with 33 participants, each possessing less than two years of industry experience and demonstrating either experience with or a keen interest in AI applications. Rooted in the transformative potential of AI in vocational training, thematic analysis was employed to reveal the intricate interplay of individual factors—motivation, attitude, self-efficacy, and digital literacy—alongside sectoral elements such as policies, practices, and organizational culture. The findings illuminate the significant impact of these factors on the acceptance and utilization of AI, underscoring the complexity of participant attitudes, shaped by perceived usefulness and ease of use. Diverse levels of self-efficacy and digital literacy among participants regarding AI adoption were also evident. On the sectoral front, policies play a dual role, either providing support or imposing restrictions on AI adoption, while practices and organizational culture wield substantial influence over the opportunities and challenges associated with AI use. These empirical insights and best practices offer stakeholders valuable guidance to enhance employability and productivity in this ever-evolving industry. Importantly, this study advocates for a more inclusive approach in future research, addressing limitations in sample representativeness and recommending the integration of quantitative methodologies. This approach is crucial for fostering a comprehensive understanding of AI utilization in vocational training, ensuring robust insights for future advancements in the industry.

A Study on the Application of Monthly and Jeonse Conversion Ratio in the Calculation of Real Estate Brokerage Fees

A Study on the Application of Monthly and Jeonse Conversion Ratio in the Calculation of Real Estate Brokerage Fees

A Study on the Application of Monthly and Jeonse Conversion Ratio in the Calculation of Real Estate Brokerage Fees

A Study on the Application of Monthly and Jeonse Conversion Ratio in the Calculation of Real Estate Brokerage Fees

Assessing Organizational Culture in Real Estate Brokerages: Links to Real Estate Agent Success

Real estate agents interested in maximizing their sales commissions may consider the impact of their brokerage firm’s organizational culture on their incomes. They may also seek to understand whether the size and age of their brokerage firms correspond to four popular organizational culture types: clan, hierarchical, market, and adhocracy. A survey distributed to United States real estate agents was analyzed to examine these relationships. The results supported hypotheses indicating that clan cultures were dominant in small firms with 20 or fewer employees and in younger firms under six years, while market cultures prevailed in larger and older firms. Additionally, market and adhocracy cultures correlated positively with brokerage firm size, and adhocracy cultures were more prevalent in younger firms. Real estate commissions were highest in companies with market culture features, followed by clan, adhocracy, and hierarchical cultures. Linear regressions and bootstrapping further supported a negative relationship between hierarchical cultures and real estate commissions and a negative relationship between adhocracy cultures and the age of firms. Theoretical and practical implications are discussed.

The Analysis on Public Opinion on the Real Estate Brokerage Commission System

The Analysis on Public Opinion on the Real Estate Brokerage Commission System

The role of gained trust: effects on intrinsic motivation, person-job fit and turnover intentions among real estate brokers

PurposeThe purpose of this paper is to analyze if gained trust is intrinsically motivating and whether it is correlated to subjective person-job fit and occupational turnover intentions among Swedish real estate brokers.Design/methodology/approachThe empirical data was gathered via a survey targeting all real estate brokers in Sweden and analyzed using structural equation modeling.FindingsThe results indicated that brokers are motivated by gained trust from their sellers and that gained trust is a vital part of person-job fit among brokers. In addition, the results show that higher levels of person-job fit reduce the occupational turnover intentions among brokers.Research limitations/implicationsBeing a real estate broker in Sweden might differ from being a broker in many other otherwise comparable countries. Another limitation is the lack of measurements of job satisfaction and/or intrinsic motivation connected to other job characteristics besides customer relations and gained trust. The high mean values of person-job fit, and intrinsic motivation connected to gained trust from customers are contributing to a more nuanced description of brokerage.Practical implicationsThis study gives insights about intrinsic motivation and its connection to person-job fit. Awareness of what drives brokes can be used by both workers and managers to reduce occupational turnover.Originality/valueThis study is interesting from a person-job fit theory advancement perspective since the focus is given to the connection between specific situational work characteristics and person-job fit.

Making the hard sale: Migrant sales agents and the precarious labours of Philippine real estate brokerage

In recent years, scholars have taken interest in the significant remittance contributions of Filipinos living and working abroad to what some have called the Philippine ‘real estate boom’. In the case of real estate property as investment, however, much remains unknown with regards to how major Philippine real estate developers capture, facilitate and ensure the continuous flow of migrant investments into condominium units in the Philippines. This article examines how Philippine real estate developers make use of a particular kind of sales labour to reach various Overseas Filipino Worker (OFW) populations. It argues that most major developers rely on a hierarchical, networked and transnationalized labour arrangement, composed mainly of licensed and unlicensed sales agents. Drawing from interviews with sales agents working in and between the cities of Metro Manila and Dubai, it then complicates dominant depictions of real estate sales agents by demonstrating the precarious conditions they work under as well as how this flexible labour arrangement often works in two ways. First, this article demonstrates that through their sales labour, specific Filipino migrant community dynamics such as community leadership, charity and other migrant ‘life projects’ such as investments, side hustles and debt get absorbed into the very circuitry of real estate accumulation. Second, through sales agents’ recruitment of OFW ‘marketing partners’, Philippine real estate developers are able to enter and expand into spaces of migrant advocacy and of migrant in/formal work to enrol OFWs either as potential investors, as labour or both.

Impact of the COVID-19 pandemic on commercial housing demand in Vietnam

Purpose The study aimed to determine the impact rate of the COVID-19 pandemic on Vietnam’s commercial housing demand as compared to other factors and proposes several policies to increase housing demand as a result of the pandemic. Design/methodology/approach The study randomly investigated 400 homebuyers during the COVID-19 pandemic. The structural equation model, SPSS20.0 and AMOS24.0 software were used to determine the impact of factor groups on housing demand. Findings The COVID-19 pandemic has a second impact after housing prices on commercial housing demand, followed by 10 other factors. The impact rates of factors range from 3.45% to 15.74%. Research limitations/implications The study has only determined the extent of the impact of the COVID-19 pandemic on housing demand in Hanoi city, so it is necessary to continue to study this issue in other provinces and cities of Vietnam. The proposed research method would be consulted when it is necessary to determine the factors affecting housing demand in other countries around the world. Practical implications The study proposes some implications related to commercial housing demand in the context of the COVID-19 pandemic such as fighting the epidemic, supporting housing investors; reducing loan interest rates; increasing the time to pay for housing; supporting enterprises to stabilize production; strengthening real estate brokerage and carrying out administrative procedures online. Social implications Investors and the State can use the implications to make the right housing decisions to provide housing for people and maintain social stability. Originality/value To the best of the authors’ knowledge, this paper presents for the first time a method to determine the impact of the COVID-19 pandemic on commercial housing demand in Vietnam. The paper also points out some specific factors affecting commercial housing demand that are different from those shown in previous research.

부동산 중개업 조직 구성에 관한 연구

The domestic real estate market and brokerage market are gradually weakening their competitiveness due to the market structure centered on individuals and small businesses. Accordingly, in order to actively respond to changes in domestic and foreign conditions, expand services in the brokerage industry, and strengthen the competitiveness of the brokerage industry, the government is inducing the incorporation and enlargement of the real estate brokerage industry. In this study, it was revealed that incorporation and enlargement cannot be a solution to the organization of licensed real estate agents to promote the professionalism of brokers and improve brokerage services to the public while overcoming the smallness of private licensed real estate agents, and derived brokerage cooperatives as an alternative as a practical alternative. Currently, the legal conflicts between the “Licensed Real Estate Agents Act” and the “Framework Act on Cooperatives” can be resolved through the revision of the “Licensed Real Estate Agents Act”. In addition, under the current legal system, it is necessary to operate a cooperative focusing on supporting the brokerage business, such as strengthening the capabilities of “Licensed Real Estate Agents Act”, under the current legal system, which is one of the best ways to organize and operate immediately.

거시경제 및 인구특성의 변화가 수도권 및 비수도권 주택 매매시장에 미치는 영향에 관한 연구

This study attempted to compare and derive the impact on the housing sales market in the metropolitan area and local cities and to present implications in terms of the real estate brokerage market. The Vector Error Correction Model was used as the analysis method in consideration of the time series characteristics and cointegration relationship of the used macroeconomic and demographic variables. The analysis results and implications are summarized as follows. In the case of the metropolitan area model, interest rates, consumer price indices, population growth rates, and fertility rates were the main factors influencing the housing sales market. The five metropolitan city models are the main factors influencing interest rates, economic growth rates, and consumer price indices, while the explanatory power of the fertility rate is very low. Considering these results, housing can be classified as an investment product in the metropolitan area, and local cities can be classified as a housing sales market with strong characteristics as a consumer product. Long-term housing sales are not expected to increase significantly due to the recent decline in investment and real demand due to the stabilization of housing prices due to high-interest rates. The housing brokerage market needs to be developed into a convergence field by combining highly relevant management and consulting.

해외 이주 한인 대상 부동산 중개 서비스 디자인

해외 이주 한인 대상 부동산 중개 서비스 디자인

Evaluating the effects of supervised consumption sites on housing prices in Montreal, Canada using interrupted time series and hedonic price models

BackgroundIn 2017, three brick and mortar supervised consumption sites (SCS) opened in Montreal, Canada. Opponents argued the sites would attract people who use drugs and reduce local real estate prices. MethodsWe used interrupted time series and hedonic price models to evaluate the effects of Montreal’s SCS on local real estate prices. We linked the Quebec Professional Association of Real Estate Brokers’ housing sales data provided by Centris Inc. with census tract data and gentrification scores. Homes sold within 200m of the SCS locations between 1 January 2014 and 31 December 2021 were included. We adjusted for internal (e.g., number of bed/bathrooms, unit size) and external attributes (e.g., neighbourhood demographics), and included a spatio-temporal lag to account for correlation between sales. For sensitivity analysis we used site-specific dummy variables to better account for unmeasured neighbourhood differences, and repeated analyses using 500m and 1000m radii. ResultsWe observed a price shock after the opening of the first two SCS in June 2017 (level effect: −10.5%, 95% CI: −19.1%, −1.1%) but prices rose faster month-to-month (trend effect: 1.1%, 95% CI: 0.7%, 1.6%) after implementation. Following the implementation of the third site in November 2017 there was no immediate impact (level effect: 2.4%, 95% CI: −10.4%, 17.0%) but once more prices roses faster (0.9%, 95% CI: 0.4%, 1.5%) thereafter. When we replaced neighbourhood attributes with a site-specific dummy variable, we observed the same pattern. Sales’ prices dropped (level effect: −9.6%, 95% CI: −15.0%, −3.8%) but rose faster month-to-month (trend effect: 0.9%, 95% CI: 0.6%, 1.2%) following June 2017’s SCS implementations, with no level effect (4.9%, 95% CI: −7.3%, 18.6%) and a positive trend (0.9%, 95% CI: 0.5%, 1.3%) after November 2017’s SCS opening. In most 500m and 1000m radii models, there were no immediate shocks following SCS opening, however, positive trend effects persisted in all models. ConclusionOur models suggest homes sold near SCS may experience a price shock immediately post-implementation, with evidence of market recovery in the months that follow.

Strategic team design for sustainable effectiveness: A data-driven analytical perspective and its implications

Teams are building blocks of organizations and essential inputs of organizational success. This article studies a data-driven analytical approach that exploits the rich data accumulated in organizations in the digital era to design teams, including prescribing team composition and formation decisions. We propose to evaluate a team regarding its performance and temporal stability, referred to as sustainable effectiveness (SE). Our approach estimates the team's performance and stability using machine learning models. It then optimizes an integrated objective of the team's performance and stability through mixed-integer programming models formulated according to predictive models. Consequently, this approach mines meaningful team compositions from historical data and guides strategic team formation accordingly. We conduct empirical studies using authentic data from our partner company in the real estate brokerage industry. The findings reveal that teams that adhere to our model's recommendations achieve an average percentage improvement of 153.1% to 156.5% higher than the benchmark teams, particularly when recruiting one or two members in their actual SE during the post-formation period. We further disclose the mechanism underlying this improvement from the perspective of changes in team compositions. Our study provides a decision support tool for team design and ensuing team dynamic management.

공인중개사의 자아탄력성이 행복감에 미치는 영향관계 연구

The purpose of this study is to investigate the relationship between ego resilience and happiness of licensed real estate agents. In order to achieve the purpose of this study, the ego resilience factors of real estate agents were derived and their impact on happiness was statistically analyzed for 226 real estate agents in Seoul and Gyeonggi region. As a result, positivity and emotional control were found to have a significant influence on the ego resilience of real estate agents. However, diversity was found to have no effect on happiness. Therefore, in order to increase happiness through the ego resilience of real estate agents, positivity and emotion regulation factors must be improved. To achieve this, first, a real estate agent must believe that good things will happen in the future and have the mindset to overcome difficulties with prospects, hopes, and goals for the future. Second, it is necessary for real estate agents to control their emotions and engage in real estate brokerage work with composure, anger control, patience, and a calm mind.

부동산 중개사고 예방을 위한 실증연구

This study aims to recognize the seriousness of real estate brokerage accidents that may occur in real estate leasing contracts and to identify important factors that can be prioritized to prevent them. To prevent this from happening, let's take a look at the types of real estate brokerage accidents and how they occur, as well as the current state of lease damage. Then, based on the factors selected from government policies, reports, papers, and 1:1 in-depth interviews with experts, we prioritized the factors that are important to prevent real estate brokerage accidents in real estate lease contracts through the Analytical Hierarchy Process (AHP). The results of the analysis showed that the following steps were taken: researching and verifying the seniority of the security deposit and the date of occupancy for multifamily housing units, checking the seniority rights, checking and notifying the availability of a return guarantee for the security deposit, verifying the owner (trust property, registered owner), and checking the status of the property with public records (also checking the status of the building). The results of this study will be used as a basis for preventing real estate brokerage accidents when signing real estate leases to establish transaction order in the real estate market.

Broker's Role and Responsibility in Commercial Brokering Contracts in Saudi Law

As trade and economic activities expand and spread in this era, the brokerage contract plays an important role in wealth trading and the exchange of goods and services in various trade, industrial, and other fields. A professional acquires the status of a merchant for this work, whether a natural person or a legal entity. The need for brokers and intermediaries continues to increase constantly due to their skills and expertise in bridging views and narrowing the gap between contractors, facilitating the conclusion of transactions. This underscores the impact of the broker's role on commercial and economic life and the necessity to develop laws governing their business, especially given the ambiguity in regulating this topic. From this perspective, the present research examines the broker's role and responsibility by adopting a comparative and analytical descriptive approach. The research is structured into three chapters, aiming to investigate the broker's role and responsibility in performing the functions of the brokerage contract, preserving documents, ensuring implementation, and refraining from prohibited practices. The goal is to draw the most important findings and recommendations, which include recommending the standardization of brokering and real estate brokering procedures, harmonization between the business transaction system project and the real estate brokerage system, recommending the establishment of a private center for trade brokerage with independence and legal person status, and suggesting the addition of some important provisions.

부동산 중개플랫폼 정보사용자의 만족도에 관한 연구

This study examines how user expectation influence satisfaction on real estate brokerage platforms applying the expectancy-disconfirmation theory. It operationalized and measured variables such as user expectations, perceived performance, expectancy-discrepancy, satisfaction, and subsequent behavioral intentions based on prior research. Hypotheses were developed for empirical analysis, and data from 272 responses collected via a 5-point likert scale survey were analyzed. Structural equation modeling(SEM) was employed to validate relationships among variables and analyze direct and indirect effects. The results indicate that user expectations significantly affect performance but not expectancy-discrepancy or satisfaction directly. However, expectations indirectly impact satisfaction through expectancydiscrepancy, acting as a criterion for satisfaction before direct user experience. Performance influences expectancy-discrepancy but not satisfaction directly. Expectancy-discrepancy positively influences satisfaction, leading to subsequent behavioral intentions like revisiting or recommending the platform. In summary, although user expectations do not directly influence satisfaction, their indirect effect through expectancy-discrepancy underscores the dynamic interplay between expectations and satisfaction.

Does Personal Financial Distress Affect Workers’ Performance? Evidence From Real Estate Agents

This study examines how personal financial distress affects workers’ performance. Using the real estate brokerage industry as a setting and personal bankruptcy filing as a proxy for personal financial distress, we find that sale prices of agent-represented houses are lower in the year when agents are financially distressed than the non-distressed year, relative to the control group. We also find that the less desirable sales’ outcomes induced by distressed agents spill over to homeowners’ future buying activities. These owners subsequently buy houses with higher loan-to-value (LTV) ratios in lower-quality neighborhoods.

House Price Prediction Based on Joint Clustering and Linear Regression

The corona virus disease (COVID-19) epidemic has a great impact on the real estate industry. The epidemic has caused a downward trend in housing values. It is essential for those who want to buy property during this period of economic recovery to understand the key factors influencing house pricing. In order to identify the factors that influence real estate prices and make house price prediction, this study uses a mathematical model called linear regression to analyze the data. The model is further improved and streamlined by focusing on essential elements. The study successfully pinpoints the most critical factors affecting home prices and makes relatively accurate house price prediction. Notably, the house's number of levels and bedrooms are essential determinants for house price prediction. Understanding these variables enables real estate agencies to concentrate on particular areas for improvement, thereby optimizing the total housing market, which gives buyers a clearer idea of the types of homes they can pick. Real estate brokers can work more productively, increase their competitive edge, and guarantee long-term success in the post-pandemic recovery phase. Furthermore, by building homes with more logical conditions for buyers, brokers may protect their brand identity and nurture client loyalty.