Pub Date : 2023-07-17DOI: 10.1108/jerer-02-2023-0008
Marcelo Cajias, Joseph-Alexander Zeitler
PurposeThe paper employs a unique online user-generated housing search dataset and introduces a novel measure for housing demand, namely “contacts per listing” as explained by hedonic, geographic and socioeconomic variables. Design/methodology/approachThe authors explore housing demand by employing an extensive Internet search dataset from a German housing market platform. The authors apply state-of-the-art artificial intelligence, the eXtreme Gradient Boosting, to quantify factors that lead an apartment to be in demand.FindingsThe authors compare the results to alternative parametric models and find evidence of the superiority of the nonparametric model. The authors use eXplainable artificial intelligence (XAI) techniques to show economic meanings and inferences of the results. The results suggest that hedonic, socioeconomic and spatial aspects influence search intensity. The authors further find differences in temporal dynamics and geographical variations.Originality/valueTo the best of the authors’ knowledge, it is the first study of its kind. The statistical model of housing search draws on insights from decision theory, AI and qualitative studies on housing search. The econometric approach employed is new as it considers standard regression models and an eXtreme Gradient Boosting (XGB or XGBoost) approach followed by a model-agnostic interpretation of the underlying effects.
{"title":"Quantifying the drivers of residential housing demand – an interpretable machine learning approach","authors":"Marcelo Cajias, Joseph-Alexander Zeitler","doi":"10.1108/jerer-02-2023-0008","DOIUrl":"https://doi.org/10.1108/jerer-02-2023-0008","url":null,"abstract":"PurposeThe paper employs a unique online user-generated housing search dataset and introduces a novel measure for housing demand, namely “contacts per listing” as explained by hedonic, geographic and socioeconomic variables. Design/methodology/approachThe authors explore housing demand by employing an extensive Internet search dataset from a German housing market platform. The authors apply state-of-the-art artificial intelligence, the eXtreme Gradient Boosting, to quantify factors that lead an apartment to be in demand.FindingsThe authors compare the results to alternative parametric models and find evidence of the superiority of the nonparametric model. The authors use eXplainable artificial intelligence (XAI) techniques to show economic meanings and inferences of the results. The results suggest that hedonic, socioeconomic and spatial aspects influence search intensity. The authors further find differences in temporal dynamics and geographical variations.Originality/valueTo the best of the authors’ knowledge, it is the first study of its kind. The statistical model of housing search draws on insights from decision theory, AI and qualitative studies on housing search. The econometric approach employed is new as it considers standard regression models and an eXtreme Gradient Boosting (XGB or XGBoost) approach followed by a model-agnostic interpretation of the underlying effects.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72748823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-11DOI: 10.1108/jerer-01-2023-0002
G. Wiejak-Roy, Gavin Hunter
PurposeMany town centres in England exhibit high retail property vacancies and require regeneration. Several alternatives for the replacement of town centre retail (TCR) have been suggested, one of which is healthcare. The healthcare sector in England is in distress, with the National Health Service (NHS) tackling extensive patient waiting lists, whilst operating from an ageing estate. This paper is an introductory study that uses seven carefully selected personalised surveys to raise academic awareness of the importance and potential of integrating healthcare into town centres and calls for large-scale research to establish the statistical validity of the reported observations.Design/methodology/approachThis study is developed from an interpretative standpoint. Through semi-structured interviews with key stakeholders specific to retail-to-healthcare conversions, this study reports stakeholders' perspectives on opportunities and limitations for such conversions to give direction for large statistical research in the future.FindingsAll participants support the integration of healthcare into town centres and agreed that diagnostic services, mental health support and primary care services are appropriate for provision within town centres. The participants advocate large-scale change in town centres in England, with integrated healthcare co-located with complementary services to fit with wider regeneration plans. Participants prefer adaptation of existing buildings where technically feasible and emphasise the importance of obtaining the buy-in of other stakeholders whilst expressing concerns about the uncertainty of capital funding availability.Originality/valueThis is the first study to analyse the practice of retail-to-healthcare conversions in town centres. These are still rare in England and projects are complex. The market experience is limited, and thus, the literature is scarce. This study fills this void and provides a starting point for future quantitative research in this area and informs the new town-planning policies.
{"title":"Recycling English town centres – from retail to healthcare: surveys, views and next steps","authors":"G. Wiejak-Roy, Gavin Hunter","doi":"10.1108/jerer-01-2023-0002","DOIUrl":"https://doi.org/10.1108/jerer-01-2023-0002","url":null,"abstract":"PurposeMany town centres in England exhibit high retail property vacancies and require regeneration. Several alternatives for the replacement of town centre retail (TCR) have been suggested, one of which is healthcare. The healthcare sector in England is in distress, with the National Health Service (NHS) tackling extensive patient waiting lists, whilst operating from an ageing estate. This paper is an introductory study that uses seven carefully selected personalised surveys to raise academic awareness of the importance and potential of integrating healthcare into town centres and calls for large-scale research to establish the statistical validity of the reported observations.Design/methodology/approachThis study is developed from an interpretative standpoint. Through semi-structured interviews with key stakeholders specific to retail-to-healthcare conversions, this study reports stakeholders' perspectives on opportunities and limitations for such conversions to give direction for large statistical research in the future.FindingsAll participants support the integration of healthcare into town centres and agreed that diagnostic services, mental health support and primary care services are appropriate for provision within town centres. The participants advocate large-scale change in town centres in England, with integrated healthcare co-located with complementary services to fit with wider regeneration plans. Participants prefer adaptation of existing buildings where technically feasible and emphasise the importance of obtaining the buy-in of other stakeholders whilst expressing concerns about the uncertainty of capital funding availability.Originality/valueThis is the first study to analyse the practice of retail-to-healthcare conversions in town centres. These are still rare in England and projects are complex. The market experience is limited, and thus, the literature is scarce. This study fills this void and provides a starting point for future quantitative research in this area and informs the new town-planning policies.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85277245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-11DOI: 10.1108/jerer-11-2022-0036
Miroslav Despotovic, David Koch, Eric Stumpe, Wolfgang A. Brunauer, M. Zeppelzauer
PurposeIn this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.Design/methodology/approachThe authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.FindingsThe results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.Originality/valueTo the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.
{"title":"Leveraging supplementary modalities in automated real estate valuation using comparative judgments and deep learning","authors":"Miroslav Despotovic, David Koch, Eric Stumpe, Wolfgang A. Brunauer, M. Zeppelzauer","doi":"10.1108/jerer-11-2022-0036","DOIUrl":"https://doi.org/10.1108/jerer-11-2022-0036","url":null,"abstract":"PurposeIn this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.Design/methodology/approachThe authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.FindingsThe results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.Originality/valueTo the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90568126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-26DOI: 10.1108/jerer-10-2022-0031
Alona Shmygel, Martin Hoesli
Purpose The purpose of this paper is to present a framework for the assessment of the fundamental value of house prices in the largest Ukrainian cities, as well as to identify the thresholds, the breach of which would signal a bubble. Design/methodology/approach House price bubbles are detected using two approaches: ratios and regression analysis. Two variants of each method are considered. The authors calculate the price-to-rent and price-to-income ratios that can identify a possible overvaluation or undervaluation of house prices. Then, the authors perform regression analyses by considering individual multi-factor models for each city and by using a within regression model with one-way (individual) effects on panel data. Findings The only pronounced and prolonged period of a house price bubble is the one that coincides with the Global Financial Crisis. The bubble signals produced by these methods are, on average, simultaneous and in accordance with economic sense. Research limitations/implications The framework described in this paper can serve as a model for the implementation of a tool for detecting house price bubbles in other countries with emerging, small and open economies, due to adjustments for high inflation and significant dependence on reserve currencies that it incorporates. Practical implications A tool for measuring fundamental house prices and a bubble indicator for housing markets will be used to monitor the systemic risks stemming from the real estate market. Thus, it will help the National Bank of Ukraine maintain financial stability. Social implications The framework presented in this research will contribute to the enhancement of the systemic risk analysis toolkit of the National Bank of Ukraine. Therefore, it will help to prevent or mitigate risks that might originate in the real estate market. Originality/value The authors show how to implement an instrument for detecting house price bubbles in Ukraine. This will become important in the context of the after-war reconstruction of Ukraine, with mortgages potentially becoming the main tool for the financing of the rebuilding/renovation of the residential real estate stock.
本文的目的是为评估乌克兰最大城市房价的基本价值提供一个框架，并确定阈值，违反该阈值将标志着泡沫。设计/方法/方法房价泡沫检测使用两种方法:比率和回归分析。考虑了每种方法的两种变体。作者计算了房价租金比和房价收入比，可以确定房价可能被高估或低估。然后，作者通过考虑每个城市的单个多因素模型和使用单向(个体)影响面板数据的内部回归模型进行回归分析。唯一明显且持续时间长的房价泡沫时期是与全球金融危机同时出现的时期。平均而言，这些方法产生的泡沫信号是同步的，并且符合经济意义。本文中描述的框架可以作为一个模型，用于在其他新兴、小型和开放的经济体中检测房价泡沫的工具的实施，因为它包含了对高通货膨胀和对储备货币的严重依赖的调整。房地产市场的系统性风险将被用于监测房地产市场的系统性风险，并将使用衡量基本房价的工具和房地产市场泡沫指标。因此，它将帮助乌克兰国家银行(National Bank of Ukraine)维持金融稳定。本研究提出的框架将有助于增强乌克兰国家银行的系统性风险分析工具包。因此，这将有助于防止或减轻房地产市场可能产生的风险。原创性/价值作者展示了如何实现一种检测乌克兰房价泡沫的工具。在乌克兰战后重建的背景下，这将变得非常重要，抵押贷款可能成为住宅房地产存量重建/翻新融资的主要工具。
{"title":"House price bubble detection in Ukraine","authors":"Alona Shmygel, Martin Hoesli","doi":"10.1108/jerer-10-2022-0031","DOIUrl":"https://doi.org/10.1108/jerer-10-2022-0031","url":null,"abstract":"Purpose The purpose of this paper is to present a framework for the assessment of the fundamental value of house prices in the largest Ukrainian cities, as well as to identify the thresholds, the breach of which would signal a bubble. Design/methodology/approach House price bubbles are detected using two approaches: ratios and regression analysis. Two variants of each method are considered. The authors calculate the price-to-rent and price-to-income ratios that can identify a possible overvaluation or undervaluation of house prices. Then, the authors perform regression analyses by considering individual multi-factor models for each city and by using a within regression model with one-way (individual) effects on panel data. Findings The only pronounced and prolonged period of a house price bubble is the one that coincides with the Global Financial Crisis. The bubble signals produced by these methods are, on average, simultaneous and in accordance with economic sense. Research limitations/implications The framework described in this paper can serve as a model for the implementation of a tool for detecting house price bubbles in other countries with emerging, small and open economies, due to adjustments for high inflation and significant dependence on reserve currencies that it incorporates. Practical implications A tool for measuring fundamental house prices and a bubble indicator for housing markets will be used to monitor the systemic risks stemming from the real estate market. Thus, it will help the National Bank of Ukraine maintain financial stability. Social implications The framework presented in this research will contribute to the enhancement of the systemic risk analysis toolkit of the National Bank of Ukraine. Therefore, it will help to prevent or mitigate risks that might originate in the real estate market. Originality/value The authors show how to implement an instrument for detecting house price bubbles in Ukraine. This will become important in the context of the after-war reconstruction of Ukraine, with mortgages potentially becoming the main tool for the financing of the rebuilding/renovation of the residential real estate stock.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135996186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-22DOI: 10.1108/jerer-09-2022-0026
Peter Palm, Helena Bohman
PurposeReal estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. The purpose of this paper is to investigate how real estate firms use big four auditors to signal quality.Design/methodology/approachThe authors use Swedish firm level data containing all limited liability real estate companies in the country to determine the determinants of big four auditors. The data set consists of 34,306 observations and is analyzed through logit regressions.FindingsThe results show that big four companies are primarily contracted by large and mature companies, rather than new firms or firms with volatile financial records, although the latter could be expected to have a large need to signal quality. The authors also find that firms listed on the stock market and firms targeting public use real estate are more inclined to use big four companies.Originality/valueReal estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. No prior study of this area has been detected.
{"title":"Auditor choice in real estate firms: a quality signal?","authors":"Peter Palm, Helena Bohman","doi":"10.1108/jerer-09-2022-0026","DOIUrl":"https://doi.org/10.1108/jerer-09-2022-0026","url":null,"abstract":"PurposeReal estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. The purpose of this paper is to investigate how real estate firms use big four auditors to signal quality.Design/methodology/approachThe authors use Swedish firm level data containing all limited liability real estate companies in the country to determine the determinants of big four auditors. The data set consists of 34,306 observations and is analyzed through logit regressions.FindingsThe results show that big four companies are primarily contracted by large and mature companies, rather than new firms or firms with volatile financial records, although the latter could be expected to have a large need to signal quality. The authors also find that firms listed on the stock market and firms targeting public use real estate are more inclined to use big four companies.Originality/valueReal estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. No prior study of this area has been detected.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84133374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-11DOI: 10.1108/jerer-05-2023-070
P. Taltavull
The real estate market is constantly evolving, influenced by a variety of factors, both global and local. Recent events such as an increase in inflation and global unrest have had significant impacts on the real estate market, affecting everything from residential access to changes in office usage and investment strategies. To better understand these shocks and identify new patterns of behavior, it is essential to analyze historical data and conduct innovative research. In Volume 16(1), a collection of papers shed light on some of the most pressing issues facing the real estate market today. For example, Rubinacci, Marzano and Piselli present a historical perspective on price cycles and residential transactions in Italy. Their analysis highlights the importance of credit cycles in shaping the market and demonstrates how this phenomenon is consistent across different countries. Other papers in this volume explore various aspects of real estate investment decisionmaking. Autio, Pulkka and Junnila examine how corporate investment strategies are changing in response to market competition, while Fadeyi, McGreal, McCord and Berry investigate the impact of long-term perspectives on investment decisions in the London office market. Another critical change in the real estate market is the concept of the workplace. Tsolacos, Lee and Tse explore the rise of co-working and how this new form of office space usage is affecting decision-making. With tenants placing more value on flexibility and well-being, companies are evaluating offices not just on their physical characteristics and location but also on their ability to provide services. Two papers in this volume examine the role of real estate brokers in the market. WiejakRoy analyzes how vendor due diligence affects values and real estate transactions, while Ahlenius and K agstr€om investigate the role of rewards in job satisfaction among Swedish brokers. Finally, Maier and Reyman analyze the institutional factors affecting real estate development in SilesianMetropolitan Areas, while Oladiran, Sunmoni, Ajayi, Abbas and Guo explore the attributes of university students’ accommodation in online searches. Through these studies, it becomes clear that real estate is intimately connected to many other aspects of politics and the economy. As such, it is essential to stay informed and conduct innovative research to better understand the market’s complexities and plan for the future. I hope you enjoy reading this issue.
{"title":"Editorial: Real estate investment and corporate decisions","authors":"P. Taltavull","doi":"10.1108/jerer-05-2023-070","DOIUrl":"https://doi.org/10.1108/jerer-05-2023-070","url":null,"abstract":"The real estate market is constantly evolving, influenced by a variety of factors, both global and local. Recent events such as an increase in inflation and global unrest have had significant impacts on the real estate market, affecting everything from residential access to changes in office usage and investment strategies. To better understand these shocks and identify new patterns of behavior, it is essential to analyze historical data and conduct innovative research. In Volume 16(1), a collection of papers shed light on some of the most pressing issues facing the real estate market today. For example, Rubinacci, Marzano and Piselli present a historical perspective on price cycles and residential transactions in Italy. Their analysis highlights the importance of credit cycles in shaping the market and demonstrates how this phenomenon is consistent across different countries. Other papers in this volume explore various aspects of real estate investment decisionmaking. Autio, Pulkka and Junnila examine how corporate investment strategies are changing in response to market competition, while Fadeyi, McGreal, McCord and Berry investigate the impact of long-term perspectives on investment decisions in the London office market. Another critical change in the real estate market is the concept of the workplace. Tsolacos, Lee and Tse explore the rise of co-working and how this new form of office space usage is affecting decision-making. With tenants placing more value on flexibility and well-being, companies are evaluating offices not just on their physical characteristics and location but also on their ability to provide services. Two papers in this volume examine the role of real estate brokers in the market. WiejakRoy analyzes how vendor due diligence affects values and real estate transactions, while Ahlenius and K agstr€om investigate the role of rewards in job satisfaction among Swedish brokers. Finally, Maier and Reyman analyze the institutional factors affecting real estate development in SilesianMetropolitan Areas, while Oladiran, Sunmoni, Ajayi, Abbas and Guo explore the attributes of university students’ accommodation in online searches. Through these studies, it becomes clear that real estate is intimately connected to many other aspects of politics and the economy. As such, it is essential to stay informed and conduct innovative research to better understand the market’s complexities and plan for the future. I hope you enjoy reading this issue.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82772653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1108/jerer-10-2021-0049
S. Tsolacos, Stephen Lee, H. Tse
PurposeThis study aims to examine the impact of “space-as-a-service” (SAAS) provision on office rents in the UK and quantify premia to office rents.Design/methodology/approachUsing hedonic modelling techniques the authors are able to quantify the impact of a number of SAAS features on office rents in the City of London using CoStar data. The authors control for the quality of the buildings by focussing on five-star buildings, rated by CoStar, as these buildings are more likely to incorporate SAAS features.FindingsUsing data on 317 transactions in 37 City of London Office buildings over the period 1 November 2004–15 July 2020, the authors find that tenant exclusive mobile applications (MAPPS) and a public terrace or rooftop command a rent premium of around £13 and £6.5 per sq. ft per annum, respectively. However, other SAAS features such as conferencing facilities, on-site fitness centre and touch down space have no significant impact on office rents. The impact of exclusive MAPPS varies with size of net lettable area.Research limitations/implicationsThe SAAS real estate model is an emerging trend in the office market. As it grows in importance more research questions will have to be investigated. The present study raises awareness of the need to specify SAAS features and form a rating system that will facilitate future research on the subject.Practical implicationsThe conclusion from the present investigation is that only two SAAS features have a positive impact on office (tenant exclusive mobile apps and a public terrace or rooftop), which suggest that these two features may form the basis of any future SAAS rating system. These two SAAS components should carry more weight in valuations and pricing.Originality/valueTo the best of the authors’ knowledge, this is the first study that attempts to quantify the impact of SAAS features on office rents.
{"title":"‘Space-as-a-service’: A premium to office rents?","authors":"S. Tsolacos, Stephen Lee, H. Tse","doi":"10.1108/jerer-10-2021-0049","DOIUrl":"https://doi.org/10.1108/jerer-10-2021-0049","url":null,"abstract":"PurposeThis study aims to examine the impact of “space-as-a-service” (SAAS) provision on office rents in the UK and quantify premia to office rents.Design/methodology/approachUsing hedonic modelling techniques the authors are able to quantify the impact of a number of SAAS features on office rents in the City of London using CoStar data. The authors control for the quality of the buildings by focussing on five-star buildings, rated by CoStar, as these buildings are more likely to incorporate SAAS features.FindingsUsing data on 317 transactions in 37 City of London Office buildings over the period 1 November 2004–15 July 2020, the authors find that tenant exclusive mobile applications (MAPPS) and a public terrace or rooftop command a rent premium of around £13 and £6.5 per sq. ft per annum, respectively. However, other SAAS features such as conferencing facilities, on-site fitness centre and touch down space have no significant impact on office rents. The impact of exclusive MAPPS varies with size of net lettable area.Research limitations/implicationsThe SAAS real estate model is an emerging trend in the office market. As it grows in importance more research questions will have to be investigated. The present study raises awareness of the need to specify SAAS features and form a rating system that will facilitate future research on the subject.Practical implicationsThe conclusion from the present investigation is that only two SAAS features have a positive impact on office (tenant exclusive mobile apps and a public terrace or rooftop), which suggest that these two features may form the basis of any future SAAS rating system. These two SAAS components should carry more weight in valuations and pricing.Originality/valueTo the best of the authors’ knowledge, this is the first study that attempts to quantify the impact of SAAS features on office rents.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89854624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-14DOI: 10.1108/jerer-09-2022-0024
Martin Ahlenius, Jon Kågström
Purpose Intrinsic motivation affects job satisfaction and turnover intention. Still, previous motivational studies among real estate brokers (brokers) have primarily focused on extrinsic rewards, leaving intrinsic rewards/motivation practically unexplored. The purpose of this study is therefore to evaluate the role of both satisfaction with intrinsic rewards (SIR) and satisfaction with extrinsic rewards (SER) on job satisfaction and turnover intention among Swedish brokers. Design/methodology/approach This article is a replication, more precisely an empirical generalization and extension, of Mosquera et al .’s (2020) study conducted among brokers in Portugal. Using a sample of 910 Swedish brokers, the study analyzes a conceptual framework and tests hypotheses by using partial least squares (PLS). Findings Results indicate that SIR has a very strong impact on job satisfaction, which is not the case in the Portuguese sample. On the other hand, SER does not have an impact on job satisfaction, which is the case in the Portuguese sample. SIR does not have an impact on turnover intention in the Swedish sample, whereas SER does. Job satisfaction has twice the positive impact on turnover intention in the Swedish sample compared to the Portuguese. Furthermore, job satisfaction mediates the relationship between SIR/SER and turnover intention. Research limitations/implications Findings of this study extend the existing literature of satisfaction with extrinsic and in particular intrinsic rewards on job satisfaction and turnover intention in the context of the brokerage industry. The most interesting difference between the samples is that Swedish brokers display much higher levels of satisfaction with intrinsic rewards. On the other hand, Swedish brokers appear to be less driven by extrinsic rewards, which is not in line with prior studies within brokerage. Practical implications Both managers and students planning to become brokers should consider that SIR has a stronger impact on job satisfaction than SER. What are perceived as intrinsic rewards, however, is highly subjective, which is troublesome from a managerial perspective, even more so as SIR is much harder to influence than SER. Given that intrinsic motivation is primarily a consequence of needs fulfillment, screening of applicants for person-job fit ought to increase job satisfaction and reduce turnover given its focus on the congruence between job demands and worker’s needs, respectively, what a job provides and the worker’s needs. Originality/value This study contributes to the brokerage research field by indicating that being a broker differs substantially between countries and that intrinsic rewards matter for Swedish brokers.
{"title":"Fat cats or sociable wolves? Swedish real estate brokers and intrinsic rewards\u0000 - A quantitative empirical generalization","authors":"Martin Ahlenius, Jon Kågström","doi":"10.1108/jerer-09-2022-0024","DOIUrl":"https://doi.org/10.1108/jerer-09-2022-0024","url":null,"abstract":"\u0000 Purpose\u0000 Intrinsic motivation affects job satisfaction and turnover intention. Still, previous motivational studies among real estate brokers (brokers) have primarily focused on extrinsic rewards, leaving intrinsic rewards/motivation practically unexplored. The purpose of this study is therefore to evaluate the role of both satisfaction with intrinsic rewards (SIR) and satisfaction with extrinsic rewards (SER) on job satisfaction and turnover intention among Swedish brokers.\u0000 \u0000 \u0000 Design/methodology/approach\u0000 This article is a replication, more precisely an empirical generalization and extension, of Mosquera\u0000 et al\u0000 .’s (2020) study conducted among brokers in Portugal. Using a sample of 910 Swedish brokers, the study analyzes a conceptual framework and tests hypotheses by using partial least squares (PLS).\u0000 \u0000 \u0000 Findings\u0000 Results indicate that SIR has a very strong impact on job satisfaction, which is not the case in the Portuguese sample. On the other hand, SER does not have an impact on job satisfaction, which is the case in the Portuguese sample. SIR does not have an impact on turnover intention in the Swedish sample, whereas SER does. Job satisfaction has twice the positive impact on turnover intention in the Swedish sample compared to the Portuguese. Furthermore, job satisfaction mediates the relationship between SIR/SER and turnover intention.\u0000 \u0000 \u0000 Research limitations/implications\u0000 Findings of this study extend the existing literature of satisfaction with extrinsic and in particular intrinsic rewards on job satisfaction and turnover intention in the context of the brokerage industry. The most interesting difference between the samples is that Swedish brokers display much higher levels of satisfaction with intrinsic rewards. On the other hand, Swedish brokers appear to be less driven by extrinsic rewards, which is not in line with prior studies within brokerage.\u0000 \u0000 \u0000 Practical implications\u0000 Both managers and students planning to become brokers should consider that SIR has a stronger impact on job satisfaction than SER. What are perceived as intrinsic rewards, however, is highly subjective, which is troublesome from a managerial perspective, even more so as SIR is much harder to influence than SER. Given that intrinsic motivation is primarily a consequence of needs fulfillment, screening of applicants for person-job fit ought to increase job satisfaction and reduce turnover given its focus on the congruence between job demands and worker’s needs, respectively, what a job provides and the worker’s needs.\u0000 \u0000 \u0000 Originality/value\u0000 This study contributes to the brokerage research field by indicating that being a broker differs substantially between countries and that intrinsic rewards matter for Swedish brokers.\u0000","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91292187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-10DOI: 10.1108/jerer-09-2022-0027
Pauli Autio, Lauri Pulkka, S. Junnila
PurposeThe aim of this paper is to introduce a framework that helps to identify strategic themes on which real estate investors form their strategies. A holistic approach to strategic management in real estate management has enjoyed popularity in corporate real estate research, while similar research has been lacking from the investor-based real estate management.Design/methodology/approachThe research design consists of two main parts: 1) formulating propositions based on existing literature and 2) attempting to validate the propositions through a qualitative interview study with major real estate owners in Finland.FindingsThe main finding is that the current real estate investors reflect the transient nature of competitive advantages and assess their strategies accordingly. The companies consider the traditional profitability and revenue growth aspects of their business but also a more long-term future growth dimension. As an outcome, the investors base their strategies on eight strategic themes which are “Innovation”, “ESG”, “Marketing and sales”, “Financial management”, “Leasing management and tenant satisfaction”, “Competitive environment and portfolio management”, “Outsourcing and strategic partnerships” and “Cost and operation optimization”.Research limitations/implicationsThis paper opens opportunities for future research concerning different strategies in real estate investment business and their impacts.Practical implicationsThe presented framework provides support for real estate investors to create real estate management strategy or to evaluate their current strategy and to recognize operational actions and decisions that are relevant for their strategy.Originality/valueThis paper provides an extension to corporate real estate (CRE) literature by showing that the CRE theories are adaptable to real estate investment and provide value for their strategic management. This paper also contributes to real estate investment literature by providing a well-founded and empirically contested strategic management framework, the IREM framework, for identifying strategic themes on which real estate investors form their strategies.
{"title":"Creating a strategy framework for investor real estate management","authors":"Pauli Autio, Lauri Pulkka, S. Junnila","doi":"10.1108/jerer-09-2022-0027","DOIUrl":"https://doi.org/10.1108/jerer-09-2022-0027","url":null,"abstract":"PurposeThe aim of this paper is to introduce a framework that helps to identify strategic themes on which real estate investors form their strategies. A holistic approach to strategic management in real estate management has enjoyed popularity in corporate real estate research, while similar research has been lacking from the investor-based real estate management.Design/methodology/approachThe research design consists of two main parts: 1) formulating propositions based on existing literature and 2) attempting to validate the propositions through a qualitative interview study with major real estate owners in Finland.FindingsThe main finding is that the current real estate investors reflect the transient nature of competitive advantages and assess their strategies accordingly. The companies consider the traditional profitability and revenue growth aspects of their business but also a more long-term future growth dimension. As an outcome, the investors base their strategies on eight strategic themes which are “Innovation”, “ESG”, “Marketing and sales”, “Financial management”, “Leasing management and tenant satisfaction”, “Competitive environment and portfolio management”, “Outsourcing and strategic partnerships” and “Cost and operation optimization”.Research limitations/implicationsThis paper opens opportunities for future research concerning different strategies in real estate investment business and their impacts.Practical implicationsThe presented framework provides support for real estate investors to create real estate management strategy or to evaluate their current strategy and to recognize operational actions and decisions that are relevant for their strategy.Originality/valueThis paper provides an extension to corporate real estate (CRE) literature by showing that the CRE theories are adaptable to real estate investment and provide value for their strategic management. This paper also contributes to real estate investment literature by providing a well-founded and empirically contested strategic management framework, the IREM framework, for identifying strategic themes on which real estate investors form their strategies.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89008356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-17DOI: 10.1108/jerer-11-2022-069
P. Taltavull
The post-pandemic effect on the economy is affecting real estate markets. The rise in inflation and disruption to supply channels, in addition to the increase in risk due to the Ukrainian war, are changing the way in which markets work and reach equilibrium. In this issue, some of the mechanisms to understand real estate market performance are analysed, particularly focussing on real estate prices. The new evidence contained in the manuscripts can be grouped into three categories. The first one contains research with a more macro perspective. The second category contains new evidence of how transactions are related to brokerage features, while in the third, research using spatial econometric tools, an increasingly used method in real estate, appear. The first group has a more macro focus on the general trends affecting real estate markets.
{"title":"Editorial: From macro to micro analysis: new findings from real estate markets in Europe","authors":"P. Taltavull","doi":"10.1108/jerer-11-2022-069","DOIUrl":"https://doi.org/10.1108/jerer-11-2022-069","url":null,"abstract":"The post-pandemic effect on the economy is affecting real estate markets. The rise in inflation and disruption to supply channels, in addition to the increase in risk due to the Ukrainian war, are changing the way in which markets work and reach equilibrium. In this issue, some of the mechanisms to understand real estate market performance are analysed, particularly focussing on real estate prices. The new evidence contained in the manuscripts can be grouped into three categories. The first one contains research with a more macro perspective. The second category contains new evidence of how transactions are related to brokerage features, while in the third, research using spatial econometric tools, an increasingly used method in real estate, appear. The first group has a more macro focus on the general trends affecting real estate markets.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74594004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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