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The purpose of this paper is to show that building stock is currently one of the largest energy consumers. It is thus imperative that buildings are optimally planned, constructed, and used from both the environmental and the economic point of view. Cost models are relevant tools for achieving this objective as they can be used to estimate the occupancy costs in early project phases including energy costs.

In the paper a regression model for predicting the energy consumption and energy costs of office buildings is developed based on the results of a survey conducted in 80 Swiss office properties.

The proposed energy cost model shows good agreement with the observed field data. The mean absolute percentage error resulted in 12 per cent. Validation tests using five properties not used for the model development revealed percentage errors ranging between −17 per cent and 7 per cent. The proposed concept and the presented cost model can be used as a basis for future studies.

The energy consumption and energy cost model can be improved as the database for developing them is further extended (including properties from different owners with different strategies, for example energy contracting, outsourcing, and maintenance strategies).

The objective of the study was to develop and validate a predictive model to facilitate the estimation of occupancy costs in early project phases. A procedure is presented on how quantitative energy consumption and cost models can be developed. Provided that sufficient empirical data are available, this proecdure can be used in further studies as a suitable and practicable concept to advance occupancy cost models.

Maintenance and running costs contribute significantly to the total cost of running facilities. Almost half of the energy consumed in the UK is used in buildings. Energy consumption can be attributed to many factors. Describes the fundamentals associated with modelling running costs in leisure centres and then investigates 19 sport centres in the city of Liverpool, using data elicited from the Liverpool Leisure Services Directorate. The energy operating costs were analysed using statistical techniques and artificial intelligence methods. Three types of modelling, linear/non‐linear regression, neural networks and neurofuzzy were developed to predict energy cost. Testing and validation of the results showed that neural network models outperformed both regression and neurofuzzy techniques. However, all the models showed a high level of accuracy. The models would be of use to professionals involved in feasibility studies.

The purpose of this study is to examine the application of sustainable building design and operation within a university setting to determine its economic efficacy and potential for further university investment.

This study incorporated a life cycle cost analysis (LCCA), simple payback period and discounted payback period calculations to determine the return on investment, including a sensitivity analysis when comparing the energy use and financial benefits of the sustainable design of a multi-use facility at Toronto Metropolitan University with buildings of similar size and use-type.

It was found that there is a positive business argument for Canadian Universities to consider the use of sustainable design to reduce energy use and greenhouse gas (GHG) emissions. A reasonable payback period and net present value within an institutional context were determined using a life-cycle cost assessment approach.

This study was limited to the measure of only a single location. Certain assumptions regarding energy pricing and interest rates and the related sensitivities were anchored on a single year of time, and the results of this study may be subject to change should those prices or rates become significantly different over time. Considerations for future research include a longitudinal approach combined with a more detailed analysis of the effect of use-type on the variables discussed.

For university administrators, the results of this study may encourage institutions such as universities to approach new building projects through the lens of energy efficiency and environmental sustainability.

GHG emissions are a well-proven contributor to global climate change, and buildings remain a significant source of GHG emissions in Canada due to their winter heating and summer cooling loads. As a result, sustainable building design on university campuses can mitigate this impact by optimizing and reducing energy consumption.

Research related to the economic evaluation of sustainable building design on university campuses is generally limited, and this study represents the first of its kind in regard to an LCCA of a sustainably designed building on a Canadian University campus.

This study aims to examine the effects of policy incentives and cost on the choice and use of renewable energy in North-Central Nigeria.

The data for this study are collected from a sample of 290 respondents drawn from across 6 states in North-Central Nigeria, including the Federal Capital Territory. This study uses descriptive statistics and multinomial logistic regression to analyze the data.

The findings reveal that there is a huge potential demand for renewable energy sources (particularly solar photovoltaic) in the rural communities in Nigeria. It also indicates a positive and highly significant relationship between the level of awareness, availability and income and the use (consumption) of renewable energy sources among the rural communities. Furthermore, the cost of installation and maintenance of renewable energy, its reliability and availability are significant determinants of renewable energy choices among rural inhabitants in Nigeria.

The authors submit that inefficient policy strategies, high cost of installation and lack of awareness remain the major hindrances to the use of more efficient renewable energy sources. From a policy point of view, a viable strategy for effective use of renewable energy sources is the involvement of government, development partners and agencies for the funding of renewable energy technology in the rural sector of the country. The usage of modern renewable energy would increase if policy incentives are aimed at covering parts of the maintenance and installation cost of renewable energy users. The authors recommend that apart from creating awareness on the benefits of renewable energy, policymakers should provide a desirable policy environment for private energy firms to supply renewable energy at an affordable cost to the rural communities in Nigeria.

A majority of the rural households in Nigeria, as shown in this article, are poor and therefore use firewood as their main source of cooking energy because of the cost of renewable energy.

Despite the abundance of renewable energy sources and government effort at improving renewable energy use, more than 15 million people live without access to electricity and 54 million are without modern energy services for cooking and lightening in Nigeria. A total of 61% of these people live in rural areas. Therefore, this study is novel in providing energy policy insights for rural communities in North-Central Nigeria.

Decarbonising the housing stock is one of the largest challenges in the built environment today, which is getting the attention not only from policymakers but also from social housing corporations, financial organisations and users. In line with the international Paris-Climate-Change-Conference 2015, Dutch cities and housing associations have embraced this challenge with the ambitions to become carbon neutral in 2050. To reach such goals, both the rate and depth of renovation need to increase. Several technical solutions to eliminate the energy demand in dwelling have been developed and tested. Nevertheless, the intake rate of deep retrofitting is low. Despite recent developments, there are still significant barriers related to financing, lack of information and user acceptance. To address those barriers, the purpose of this paper is to investigate the relationship between energy efficiency upgrades and the cost of living.

Focusing on walk-up apartments in the Netherlands, a framework of refurbishment measures that affect the energy efficiency was identified, and their performance was calculated. Furthermore, the rental price adjustment was estimated, taking into account the refurbishment investment and the exploitation cost of the renovated dwellings.

The comparison of the energy use and rental price for the different options demonstrated how the different renovation measures affect the energy cost, the energy use, rent and cost of living. The tenants are more likely to accept the solutions that take into account the total cost of living and sustainability benefits. The study gives a holistic standpoint to the issue of energy upgrades, by quantifying the effect of the potential measures for the whole exploitation period. It has shown the potential of the different interventions to improve the performance and living conditions, without necessarily increasing the total cost of living.

Such results aim at supporting the decision making between the stakeholders, primarily housing associations and tenants.

The importance of the study is that it gives a holistic standpoint to the issue of energy upgrades, by quantifying the effect of the potential measures for the whole exploitation period. The cost, as a key, if not the more most decisive, issue, is put into perspective in relation to the benefit, in order to give a direction to the renovation design and arguments for the stakeholders’ dialogue. The approach of the study goes beyond cost-optimality of measures and investigated the relation between energy upgrades and cost, as a way to evaluate design variation and address the lack of information barrier in renovations. Moreover, it also proves that deep renovation is feasible without increasing in the total cost of living, which is a principal argument to promote renovations.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

The purpose of this paper is to use basic economic theory to examine the relation between the demanded data traffic and the network costs for several network deployment scenarios and find the most preferable deployment strategy subject to specific constraints in near future (2015-2020).

The paper identifies the cost structure of radio access networks and explicitly models the network costs as a function of data traffic, both in the short-run (current network) and in the long-run (future capacity expansion scenarios). In the short-run model, the operating cost of the current network is calculated, highlighting the energy cost and its dynamics. In the long-run model, assuming unchanged site infrastructure, the cost analysis provides information for decision-making on network evolution.

The results show that the operating cost does not differ significantly from short- to long-run, and the energy cost constitutes a small but remarkable share (around 7 per cent) of total network operating cost. In addition, the paper concludes that the best strategy is not the most cost-efficient strategy but the one which meet the coverage requirements imposed by the regulator when the spectrum is allocated to operators. Finally, the speed of investments in urban regions is driven by the traffic growth, whereas in suburban and rural regions, it is driven by the regulator’s intervention.

The paper contributes to the improvement of cost modeling for techno-economics by using economic theory and analyzing the energy consumption. In addition, the paper investigates real cases for mobile operators, and provides useful information for decision-making in network evolution.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

To support ongoing industry efforts to reduce the cost of energy (CoE) of offshore wind compared to other types of energy sources, researchers are applying scientific models and thought processes to identify potential areas of improvement and optimization. This paper aims to introduce a conceptual framework from a supply chain management (SCM) perspective, aimed at promoting the reduction of CoE in the offshore wind energy industry.

Using conceptual arguments from current academic literature in SCM, a comprehensive framework is presented that clarifies how SCM practices can be used by offshore wind energy industry to reduce CoE.

The offshore wind energy sector is a young industry that must reduce CoE to compete with other forms of energy. Applying a supply chain perspective in the offshore wind industry has hitherto been limited to the academic community. This paper offers a SCM framework that includes three interdependent aspects of reducing CoE – innovation, industrialization and supplier partnering – to guide the industry towards sources to reduce CoE.

SCM is a broad research area; thus, the presented framework to reduce the CoE is open for further development.

The paper provides insights into how the CoE can be reduced through innovation, industrialization and partnering in the offshore wind energy supply chain.

The paper offers a seminal contribution by introducing a SCM framework to understand sources and approaches to reduce CoE in the offshore wind energy industry.

The purpose of this paper is to exam the financial impact on the owner/lessor who is considering a partial energy upgrade to an existing medical office building. The owner who leases the building using a triple net lease does the upgrade prior to leasing the building, with the expectation of earning higher rents. How much should the owner who leases the property spend for a given rent per square foot increase?

The empirical study highlights the impact of key financial variables on the dependent variable medical office construction spending put in place in the USA. The independent variables prime interest rate, cost of natural gas per therm and electricity cost per KWH, resale building prices are significant variables when predicting medical office construction spending. A case study using a cost-benefit model is developed. It inputs corporate income tax rates, incorporates a debt service coverage ratio, prime interest rate, analyzes investment tax credit (ITC) and rebate scenarios and varies the level of rental income and energy savings. The case study results provide insight into which factors are enabling higher net construction spending when considering a green energy retrofit project. Both the regression model and the case study model focussed on the owner of a building who rents medical office space to tenants using a triple net lease. The owner/lessor paradigm analyzes revenue enhancements, the tax implications of having these savings and benefits associated with borrowing when financing the green retrofit. The availability of low cost borrowing, increases in the ITC percent and rebates and increases in rent per square foot have an impact on potential energy upgrade spending.

The empirical model finds the independent variables to be significant. Utility cost, resale value of office buildings, the prime interest rate, business bankruptcy court filings and unemployment rate fluctuations adequately explain movements in medical office building spending for the years 2000 through 2015 yielding a R2 of 73.8 percent. The feasibility case study indicates that the energy saving levels and ITCs not income tax rates are the primary drivers for a partial energy retrofit.

Market incentives are a function of the cost of energy. If the cost of energy drops, then the profit incentive to conserve energy becomes less important. The role of tax credits, rebates, property tax reductions and government directives, then become primary incentives for installing energy upgrades. The owner of an empty building assumes all of the operating costs normally paid by a tenant under a triple net lease. This possibility was not included in the replacement cost-benefit model used in this paper.

The feasibility of doing an energy upgrade to an existing building requires that a cost-benefit analysis be undertaken. The independent variables that are significant when doing a regression model or proxies for these variables are incorporated into a present value model. The results in Table V can be used as an initial template for determining how much to spend per square foot when doing an energy upgrade. The square foot amounts can be applied to different size office buildings. The corporate income tax rate or a personal income tax rate has minimal impact on energy construction upgrade spending.

More energy efficient office buildings reduce the amount of greenhouse gases released into the atmosphere. Energy efficient buildings also conserve on scarce fuel reserves. ITCs and rebates limit the role of government in directing decisions to do energy upgrades. The market mechanism to some degree can help encourage energy conservation through asset upgrades.

The paper incorporates an empirical model which is a form of technical analysis to examine independent variables that explain medical office building spending with a case study structured on expected revenues and costs which takes a fundamental approach to understanding the relationship between the dependent variable and its independent variables. The regression model combines factors that impact the demand for energy efficient medical buildings from an owner/lessor perspective which includes resale values of existing buildings, business bankruptcy filings and unemployment rates. Supply independent variables include the prime interest rate and electricity per KWH and natural gas per therm. The regression model found these variables to be significant. The case study uses the same independent variables or close proxy variables to determine the maximum financially feasible per square foot spending that can be invested in energy upgrades.