Modeling the Decision-making of Real Estate Developers in the Building Energy Efficiency (BEE) Market- A Game Theoretical Model from Transaction Costs Perspective

2011 ◽  
Author(s):  
Queena K. Qian ◽  
Edwin H. W. Chan
Keyword(s):  
Decision Making ◽  
Energy Efficiency ◽  
Theoretical Model ◽  
Real Estate ◽  
Transaction Costs ◽  
Building Energy ◽  
Building Energy Efficiency ◽  
Game Theoretical Model ◽  
Real Estate Developers

REAL ESTATE DEVELOPERS' CONCERNS ABOUT UNCERTAINTY IN BUILDING ENERGY EFFICIENCY (BEE) INVESTMENT—A TRANSACTION COSTS (TCS) PERSPECTIVE

2012 ◽  
Vol 7 (4) ◽  
pp. 116-129 ◽  
Author(s):  
Queena K. Qian ◽  
Edwin H.W. Chan ◽  
Lennon HT Choy
Keyword(s):  
Energy Efficiency ◽  
Real Estate ◽  
Transaction Costs ◽  
Large Scale ◽  
Energy Use ◽  
Transaction Cost Economics ◽  
Building Energy ◽  
Building Energy Efficiency ◽  
Economic Market ◽  
Real Estate Developers

Buildings account for 40% of global energy consumption and nearly one-third of global CO2emissions; and the resulting carbon footprint significantly exceeds that of all forms of transportation combined. Attractive opportunities exist to reduce buildings' energy use at lower costs and higher returns than in other sectors. This paper analyzes the concerns of uncertainty, in terms of transaction costs, to the real estate developers when they make decisions about investing in Building Energy Efficiency (BEE). To solicit views of developers regarding BEE investment, in-depth interviews were conducted with 15 executives and architects who work in big real estate development firms covering 80% of real estate activities in Hong Kong. This research applies transaction cost economics (TCE) to study the underlying reasons resulting from uncertainty that cause market reluctance to accept BEE by choice. It provides a detailed analysis of the current situation and future prospects for BEE adoption through studying the impacts from three aspects: economic, market and policy uncertainties. It delineates the market and suggests possible policy solutions to overcome the uncertainties and to attain the large-scale deployment of energy-efficient building techniques. The findings establish the groundwork for future studies on how to choose a particular policy package and what roles government should play to solve the existing problems in BEE development.

Drivers of Investment in Commercial Real Estate Sustainability: 2006–2018

2019 ◽  
Vol 11 (1) ◽  
pp. 130-155
Author(s):  
Michael Brooks ◽  
J.J. McArthur
Keyword(s):  
Energy Efficiency ◽  
Real Estate ◽  
Public Relations ◽  
Building Energy ◽  
Business Case ◽  
Commercial Real Estate ◽  
Building Energy Efficiency ◽  
Number Of Factors ◽  
Near Future ◽  
Asset Managers

We investigate the factors (“drivers”) that motivated investment in energy efficiency in commercial real estate office buildings over the 2006–2011 and 2012–2017 period, and looking forward from 2018 in the context of growing concern over carbon emissions around the world. These insights were collected from large Canadian asset managers through interviews conducted in 2017 and 2018. Key findings were that (1) organizations noted an increasing number of factors driving investment decisions over the three periods; (2) cost drivers (payback period and anticipated financial returns) were the top two drivers in 2006–2017; (3) public relations factors became significantly more important looking forward, with brand (reputational impact) as the top-ranked driver and tenant attraction tied for third place; and (4) mitigation against risks such as resilience and anticipated compliance consistently increased in importance. This study contributes to a comprehensive understanding of past, present, and near-future sustainable real estate investment priorities, changing owner behaviors, and the perceived business case for building energy efficiency investments.

scholarly journals A GP-Based Hierarchical Objectives Decision-Making Method for Building Energy Efficiency Optimization

Buildings ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 52
Author(s):  
Xiang Li ◽  
Sha Liu ◽  
Yichao Sun
Keyword(s):  
Decision Making ◽  
Energy Efficiency ◽  
Optimization Method ◽  
Building Energy ◽  
Energy Performance ◽  
Decision Makers ◽  
Building Energy Efficiency ◽  
Simulation Engine ◽  
Goal Programming Model ◽  
Building Designs

Building energy efficiency, which is critical in reducing environmental impact, has become one of the most important objectives of building designs. In order to precisely express the goals of building designs, and help decision makers estimate the ultimate performance of design schemes in advance when searching for the optimal building design, the Goal Programming Model (GPM) is introduced in this study to provide a solution for explicit design objective delivery and multi-stakeholder involved decision-making support. In this proposed method, EnergyPlusTM works as a simulation engine to search for the relationship between design parameter combinations and building energy consumption. Simultaneously, Genetic Algorithm (GA) is used to improve the efficiency of overall building energy performance optimization by processing multiple iterations. A case study with five possible design scenarios was dedicated in this study to implement the proposed optimization method, and the optimization results verified the capacity of the established GP-based optimization method to satisfy various design requirements for decision makers and/or stakeholders, especially in facing the hierarchical objectives with different priorities. In this case, the envelope-related variables, including the exterior wall and window, serve as optimization objectives. The optimization is carried out under the ideal air conditioning system, considering different energy usage patterns. Meanwhile, comparing with the vague and restricted expression of objectives in multi-objective optimization, the proposed GP-based optimization method provides explicit trade-off relationships among various objectives for designers, which improves the practical value of the optimized designs, so as to ensure the project success and facilitate the development of green buildings.

scholarly journals A Conceptual Benefits Realization Model for Minimization of Transaction Costs in Building Energy Efficiency (BEE) Affordable Housing Delivery

2019 ◽  
Vol 266 ◽  
pp. 03013
Author(s):  
Abdulazeez U. Raji
Keyword(s):  
Energy Efficiency ◽  
Transaction Costs ◽  
Affordable Housing ◽  
Building Energy ◽  
Project Team ◽  
Building Energy Efficiency ◽  
Housing Projects ◽  
Specific Investment ◽  
Benefits Realization ◽  
Key Dimensions

Energy efficiency is fundamental to enhancing homes affordability. There are several unique challenges to affordable housing that owner-developers need to address in order for energy efficiency to make significant economic sense. Issues such as Transaction Costs (TCs) plays a significant role in achieving building energy efficiency (BEE) for affordable housing delivery. It is evident that split incentives, information asymmetry, institutional transition, opportunistic behavior, and ill-informed users incur different levels of TCs and affect stakeholder’s willingness to take part in BEE for affordable housing. A better understanding of the nature and structure of TCs is indispensable to enhance the market-drive and investment for BEE affordable housing. Uncertainty, specific investment, frequency, and bounded rationality seen as the key dimensions of TCs. The research focuses on how to minimize TCs involve in BEE affordable housing delivery. It was found in the literature that, the level of TCs for building energy efficiency estimated at 20.5% of total project costs. A conceptual competency-driven benefits realization model is proposed for minimizing TCs taking into consideration the peculiarities of the current housing projects delivery. This research aims to establish the significance of leveraging on BEE project team-competency and commitment organized within a strategic Benefits Realization Management framework to optimize client‘s benefits regarding minimizing TCs. The focus is on the aspect of a developer’s competencies and their project team commitment concerning minimizing TCs that structured within a Benefits Realization Management (BRM) practice. This model is proposed as a pro-active enabler tool to achieve Value for Money in BEE affordable housing projects. This paper is part of a series of publications.

Picture fuzzy multi-criteria group decision-making method to hotel building energy efficiency retrofit project selection

2020 ◽  
Vol 54 (1) ◽  
pp. 211-229 ◽  
Author(s):  
Le Wang ◽  
Hong-Yu Zhang ◽  
Jian-Qiang Wang ◽  
Guo-Fang Wu
Keyword(s):  
Decision Making ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Building Energy ◽  
Project Selection ◽  
Building Energy Efficiency ◽  
Average Operator

Building energy consumption accounts for a considerable proportion on energy consumption. To reduce building energy consumption, building energy efficiency retrofitting (BEER) based on Energy Performance Contracting mechanism is the most feasible and cost-effective method. With the increase number of BEER projects, BEER project selection has become an essential problem for energy service companies. In this paper, a multi-criteria group decision-making (MCGDM) method is proposed to deal with BEER project selection problem. First, picture fuzzy sets are employed to describe the evaluation information under the complex and uncertain environment. Subsequently, picture fuzzy weighted average operator and Laplace distribution-picture fuzzy order weighted average operator are proposed based on convex combination to aggregate individual evaluations into the overall evaluations. Furthermore, picture fuzzy TOPSIS-based QUALIFLEX method is developed to identify the optimal ranking of alternatives. Moreover, the practicality, effectiveness and advantages of the proposed MCGDM method are illustrated using a case study of hotel BEER project selection and comparative analysis. Finally, conclusions about primary contributions, and future discussions of the proposed method are demonstrated.

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