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Article
Publication date: 19 March 2024

Nikodem Szumilo and Thomas Wiegelmann

This paper aims to provide a comprehensive analysis of the transformative impact of Artificial Intelligence (AI) and Large Language Models (LLMs), such as GPT-4, on the real…

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Abstract

Purpose

This paper aims to provide a comprehensive analysis of the transformative impact of Artificial Intelligence (AI) and Large Language Models (LLMs), such as GPT-4, on the real estate industry. It explores how these technologies are reshaping various aspects of the sector, from market analysis and valuation to customer interactions and evaluates the balance between technological efficiency and the preservation of human elements in business.

Design/methodology/approach

The study is based on an analysis of the strengths and weaknesses of AI as a technology in applications for real estate. It uses this framework to assess the potential of this technology in different use cases. This is supplemented by an emerging literature on the topic, practical insights and industry expert opinions to provide a balanced perspective on the subject.

Findings

The paper reveals that AI and LLMs offer significant benefits in real estate, including enhanced data-driven decision-making, predictive analytics and operational efficiency. However, it also uncovers critical challenges, such as potential biases in AI algorithms and the risk of depersonalising customer interactions.

Practical implications

The paper advocates for a balanced approach to adopting AI, emphasising the importance of understanding its strengths and limitations while ensuring ethical usage in the diverse and complex landscape of real estate.

Originality/value

This work stands out for its balanced examination of both the advantages and limitations of AI in real estate. It introduces the novel concept of the “jagged technological frontier” in real estate, providing a unique framework for understanding the interplay between AI and human expertise in the industry.

Details

Journal of Property Investment & Finance, vol. 42 no. 2
Type: Research Article
ISSN: 1463-578X

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Article
Publication date: 5 February 2018

Nikodem Szumilo, Thomas Wiegelmann, Edyta Łaszkiewicz, Michal Bernard Pietrzak and Adam P. Balcerzak

The purpose of this paper is to evaluate how real estate returns behaved over the last two decades in relation to the other two asset types. This allows a direct evaluation of how…

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Abstract

Purpose

The purpose of this paper is to evaluate how real estate returns behaved over the last two decades in relation to the other two asset types. This allows a direct evaluation of how investors make allocation choices and perceive risks and rewards offered by properties in the context of changing market conditions.

Design/methodology/approach

A de-smoothed MSCI index is used to reflect direct property returns and control for both income and capital returns within it. Indirect property returns are approximated by the RX Real Estate index. By supplementing this data with an analysis of trends in both space and capital markets it is possible to relate investor behavior to events affecting other assets.

Findings

It is possible to identify three distinctive periods characterized by different correlation of returns and behavior of investors: before the crisis of 2008, the crisis period between 2008 and 2012 and recovery afterwards. These appear to have corresponded to different stages of the economic cycle. Interestingly, performance of asset classes has also differed over that period suggesting that at different points in the cycle asset allocation decisions may have been made differently.

Practical implications

It appears that as investments over the last 15 years real assets in Germany behaved similarly to bonds. It is possible that this phenomenon was driven by an aversion to the stock market and its associated risk which became a concern after the financial crisis of 2008. Over the downturn that followed the market shock investors appear to have turned to assets with simpler risk profiles like direct real estate and government debt. On the other hand, the correlation between direct property investment index and stock returns has been found to be small but negative. This shows not only that the two asset classes were often driven by different factors but also suggests that diversification was, at least theoretically, possible.

Originality/value

Direct real estate investment returns have repeatedly been found to exhibit characteristics similar to those found in bond as well as equity markets (Eichholtz and Hartzell, 1996; Clayton and MacKinnon, 2003) but little research examines the correlation between returns offered by those asset classes in a mature financial and property market. In addition, the recent financial crisis provided a dynamically changing investment which is ideal for investigating structural relationships between assets.

Details

Journal of Property Investment & Finance, vol. 36 no. 1
Type: Research Article
ISSN: 1463-578X

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Article
Publication date: 1 August 2016

Sergey Trofimov, Nikodem Szumilo and Thomas Wiegelmann

– The purpose of this paper is to examine state of the art data storage methods of real estate investment data.

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Abstract

Purpose

The purpose of this paper is to examine state of the art data storage methods of real estate investment data.

Design/methodology/approach

It analyses the process of real estate investment in order to classify and characterize the data it generates. Appropriate literature review is provided.

Findings

The results show that a relational database is the most appropriate database management system type for real estate related data.

Practical implications

Appropriately structured and modelled data flow can improve the design of the real estate investment process. It is also concluded that adopting an optimal design of IT-solutions could improve informational and operational efficiency of the industry.

Originality/value

The subject of this paper lacks sufficient coverage. Popular database management systems are presented and analysed in the context of their suitability for the real estate industry.

Details

Journal of Property Investment & Finance, vol. 34 no. 5
Type: Research Article
ISSN: 1463-578X

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