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The main purpose of this study is to detect homogeneous housing market areas among 196 districts of 5 major cities of Turkey in terms of house sale price indices. The second purpose is to forecast these 196 house sale price indices.

In this paper, the authors use the monthly house sale price indices of 196 districts of 5 major cities of Turkey. The authors propose an autoregressive (AR) model-based fuzzy clustering approach to detect homogeneous housing market areas and to forecast house price indices.

The AR model-based fuzzy clustering approach detects three numbers of homogenous property market areas among 196 districts of 5 major cities of Turkey where house sale price moves together (or with similar house sales dynamic). This approach also provides better forecasting results compared to standard AR models by higher data efficiency and lower model validation and maintenance effort.

In this study, the authors could not use any district-based socioeconomic and consumption behavioral indicators and any discrete geographical and property characteristics because of the data limitation.

The finding of this study would help property investors for establishing more effective property management strategies by taking different geographical location conditions into account.

From the government side, knowing future rises, falls and turning points of property prices in different locations can allow the government to monitor the property price changes and control the speculation activities that cause a dramatic change in the market.

There is no previous research paper focusing on neighborhood-based clusters and forecasting house sale price indices in Turkey. At this point, it is the first academic study.

It is important to forecast index series to identify future rises, falls, and turning points in the property market. From the point of this necessity and importance, the main purpose of this paper is to forecast the future trends in Dubai housing market.

This paper uses the monthly time series of Reidin.com Dubai Residential Property Price Index (DRPPI) data. In order to forecast the future trends in Dubai housing market, Box‐Jenkins autoregressive integrated moving average (ARIMA) forecasting method is utilized.

The results of the ARIMA modeling clearly indicate that average monthly percentage increase in the Reidin.com DRPPI will be 0.23 percent during the period January 2011‐December 2011. That is a 2.44 percent increase in the index for the same period.

Reidin.com residential property price index is a crucial tool to measure Dubai's real estate market. Based on the current index values or past trend, real estate investors (i.e. developers and constructors) decide to start new projects. Attempts have also been made in the past to forecast index series to identify future rises, falls, and turning points in the property market. The results of this paper would also help government and property investors for creating more effective property management strategies in Dubai.

There is no previous study analyzing the future trends in Dubai housing market. At this point, the paper is the first academic study that identifies this relationship.

This research aims to determine the contribution of publications in the context of Türkiye to the international entrepreneurship literature between 2005 and 2022. We examined 471 articles published in international journals in the Web of Science (WoS) Core Collection database using bibliometric analysis techniques. We analyzed the data with the software Biblioshiny+Bibliometrix, SciMAT, and VOSViewer. We used performance, theme and evolution, co-authorship, and document analysis in data analysis. Performance analysis findings show that the most publications were made in 2021, the journal with the most publications was sustainability, and the author with the most publications was Bakır, C. Theme and evolution analysis revealed that the motor themes were corporate entrepreneurship, gender and entrepreneurial intentions in the first period (2005–2014), while institutional entrepreneurship stood out as the niche theme. In the second period (2015–2022), “corporate entrepreneurship” and “performance” emerged as the motor themes, while the niche themes in this period were “Syrian refugees” and “entrepreneurial intentions.” Document analysis findings show that the most studied entrepreneurship types are gender, family, corporate, social, and small business, respectively. In addition, immigrant/refugee entrepreneurship is emerging as a new topic, while indigenous entrepreneurship, informal entrepreneurship, sustainable entrepreneurship, and religion entrepreneurship are the most minor studied topics in entrepreneurship. Evidence-based decision-making inputs were obtained for those holding the resource allocation authority in Türkiye. Policymakers and funders, as well as individuals and institutions that want to design the future in terms of resources, can benefit from the findings and analysis of this chapter. Türkiye, which ranks 26th in the world regarding entrepreneurship, must develop a policy based on data.