Multidimensional drivers of change - A transformation process of real estate business models: Empirical evidence from the German real estate industry

2018 ◽  
Author(s):  
Andreas Pfnür ◽  
Benjamin Wagner
Keyword(s):  
Real Estate ◽  
Empirical Evidence ◽  
Business Models ◽  
Transformation Process ◽  
Real Estate Industry ◽  
Drivers Of Change

scholarly journals STRATEGIC BUSINESS MODEL TYPOLOGIES EVIDENT IN THE CHINESE REAL-ESTATE INDUSTRY

2018 ◽  
Vol 22 (6) ◽  
pp. 501-515 ◽  
Author(s):  
Guiwen Liu ◽  
Kaijian Li ◽  
Asheem Shrestha ◽  
Igor Martek ◽  
Yang Zhou
Keyword(s):  
Real Estate ◽  
Asset Management ◽  
Value Chain ◽  
Business Models ◽  
Core Competency ◽  
Real Estate Industry ◽  
High Turnover ◽  
Commercial Property ◽  
The Real Estate ◽  
Work Done

The Chinese real estate industry has emerged over recent decades as one of the key drivers of Chinese economic growth and attracted thousands of players nationwide. Yet, despite the continuing importance of the real-estate industry in China, there has not been any work done to identify nor describe the strategic business models used by enterprises within the sector. This study fills this gap in the literature. This paper begins by building a framework for studying the strategic business models used within the Chinese real-estate industry, and then goes on to identify the generic models that exist in the industry. A two-step cluster analysis of 117 Chinese real-estate companies was carried out over seven parameters identified in the literature as impacting business models: 1) clients, 2) products offered, 3) market locale, 4) financial structure, 5) value chain embeddedness, 6) core competency, and, 7) revenue source. Five generic strategic business models that characterize the Chinese real-estate industry were identified: 1) commercial property model, 2) government servicing model, 3) cost efficiency model, 4) asset management model, and, 5) high-turnover model. The findings will assist industry practitioners in evaluating and informing their own competitive positions within the Chinese real-estate industry.

scholarly journals Transformation of the real estate and construction industry: empirical findings from Germany

2020 ◽  
Vol 90 (7) ◽  
pp. 975-1019 ◽  
Author(s):  
Andreas Pfnür ◽  
Benjamin Wagner
Keyword(s):  
Real Estate ◽  
Construction Industry ◽  
Value Creation ◽  
Business Models ◽  
Service Providers ◽  
Adaptation Strategies ◽  
Real Estate Industry ◽  
The Real ◽  
The Real Estate ◽  
The Impact

Abstract The German real estate and construction industry is facing a transformation, triggered by fundamental changes in technology, the economy and society. The purpose of this paper is to explore how these changes exert pressure to adapt on existing business models, while also offering opportunities for their further development. A model that attributes the transformation of the real estate industry to megatrends, specific structural change drivers, business models and the interaction of the groups of players in the value creation system is developed. The model is tested empirically by a survey. Structural equation modelling is used to measure the impact of various determinants of transformation and the relevance of adaptation strategies to the different groups of players. As a result, the study explains three impact mechanisms of the transformation in the real estate industry. The transformation originates from the occupiers, who need more flexible space and are focusing on holistic solutions that are not provided by the real estate industry. Service providers are striving to increase the efficiency of their traditional processes, rather than evolving new business models or services. The investors recognise the increasing importance of the occupiers but they are rarely pursuing the resulting strategies. Property developers recognise these requirements: their adaptation strategies most strongly question their previous business. For practitioners, the results point out the opportunities and risks of transformation and help to illustrate the need for change. For academicians, the results indicate a way to explain and measure the transformation of a value creation system.

scholarly journals INTEGRATING BIG DATA INTO DECISION-MAKING IN REAL ESTATE INDUSTRY

2020 ◽  
Vol Vol. 36 (No. 2) ◽  
pp. 25-33
Author(s):  
Beyza Ali ◽  
Nikolai Siniak
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Real Estate ◽  
Value Creation ◽  
Business Models ◽  
New Technologies ◽  
Smart Devices ◽  
Data Generation ◽  
Real Estate Industry ◽  
Business World

With the developments in technology everything we use became smarter which resulted in an outbreak in data generation, which in turn demanded innovations in technology. The new technologies did not only affect the social life but also changed the dynamics in the way businesses are conducted. Compared to before, today people have platforms where they can state their opinions publicly. As positive opinions can increase the reliability of a product, person, brand or etc. negative opinions can decrease the reliability. The increase in the use of such platforms and smart devices resulted in an unprecedented increase in data generation. Hereby a new phenomenon, called Big Data, emerged. In parallel with these developments, business world came to a point where traditional business models and strategies run short to challenge the requirements of clients. At this point it is important to realize that the only way to stay in the game is to accept the paper the meaning and the importance of the Big Data phenomena is discussed through its effect on value-creation and decision-making. The process of integrating Big -making processes is investigated with an emphasis on the importance of value-creation from Big Data. As a result of the conducted literature review, success factors for a successful integration process are suggested. One of the industries that has mostly affected from the emergence of Big Data is real estate industry. A case study on the owner occupation rates in Europe was conducted using the annual report for 2019 of European Mortgage Federation (EMF) with the aim to point out to the advantages of using Big Data and analysis over the traditional methods and to emphasize the significance of adopting data analytics technologies.

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