The current state of window and blind design moves beyond evaluating a single function, such as energy consumption, to include a human perspective in architectural design approach to create value. A current thought among architects and design professionals is that the highest value outcomes can be obtained when any architectural design contributes to enhanced well-being. Previous studies show that an individual’s well-being is determined by five main life domain factors: health, economy, personality, demographic variables and behavior variables. However, the life domain factors health and economy show stronger and more positive correlations to well-being. At this point, value creation within architectural design context, including window and blind design, can be seen as an attempt to enhance well-being by improving health and providing economic benefits for clients. Clients can represent i) owners who own a built asset, ii) investors who commit capital and expect to obtain financial return, or iii) occupants who live or work in the building every day. In the context of owner-occupied buildings, the value creation process is mainly seen as an attempt to enhance well-being for one entity by improving health and providing economic benefits. When considering investment properties or assets held for sale, the value creation process is mainly translated into an attempt to enhance well-being for several entities by improving health for occupants and providing economic benefits for owners and/or investors.Selecting a window and blind design to enhance client well-being remains a challenging task due to three main difficulties. The first difficulty relates to the contradictory effects of windows and blinds on visual and thermal comfort, energy consumption and life cycle cost. The second difficulty is the availability of a variety of window and blind designs in different sizes, positions and forms, making the selection of windows and blinds an intricate decision challenge for architects and designers. The third difficulty involves decisions about the selection of windows and blinds that should include all criteria and their interactions simultaneously.To resolve the abovementioned difficulties, this research applied the analytical hierarchy process (AHP) as a multi-criteria decision-making method to select a window and blind design based on a trade-off between visual comfort, thermal comfort, energy consumption and life cycle cost. The analyses of results show the capability of AHP in resolving difficulties, however its application is mainly limited to a small number of designs. To overcome this limitation, a decision-making framework was developed based on integration between non-dominated sorting genetic algorithm-II (NSGA-II) as an optimization algorithm and AHP. The strength and limitations of the decision-making framework were later tested by employing it in window and blind design practice. To investigate further benefits from the implementation of the framework, it was expanded by evaluating additional building envelopes, i.e. windows as well as external walls, roof and floor constructions, which made it possible to select a trade-off construction solution. The analyses of results show the framework’s ability to resolve difficulties and locate a trade-off design in a relatively short period of time. However, the decision-making framework only allows the analysis of the objective criteria for evaluating visual comfort, thermal comfort, energy consumption and life cycle cost. This is because it is necessary to rely on the creativity of the architects and designers when designing windows and blinds in order to consider subjective issues. The decision-making framework can be used either by design teams or customer service experts in window manufacturing companies. A literature study was therefore conducted to extend the technology acceptance model and thereby investigate the determinants of framework user acceptance of the decision-making framework. The results showed that organizational, individual, technological and environmental characteristics were the most influential external variables when investigating determinants of framework user acceptance of the framework. Organizational characteristics included top management support, training, organizational culture, and organizational size, while individual characteristics included the users’ previous knowledge and experience. Technological characteristics embraced information quality and system quality, meanwhile environmental characteristics comprised fulfillment of regulations and competitiveness.

Earlier studies in the context of windows and blinds selection have mostly tried to increase the awareness regarding various effects of windows and blinds selection on subjective well-being, including their effect on visual comfort, thermal comfort, energy consumption and life cycle cost. However, the main problem is the potential conflicts between visual comfort, thermal comfort, energy consumption and life cycle cost. Increased awareness about the contradictory effect of windows and blinds selection on subjective well-being on one hand and lack of a feasible method in managing the conflicts on the other hand may bind individuals, as decision-makers, in a situation where they follow the immediate economic benefits rather than the long-term visual and thermal benefits. To solve the mentioned problem, this study analysed first the degree of the conflicts between average daylight illuminance and total energy consumption in Sweden. This decision was made due to large variation in solar elevation angle and solar intensity between summer and winter in Sweden, which has significant effects on daylight illuminance and total energy consumption. Analysing the conflicts was accomplished by developing two multivariate linear regression models for calculating average daylight illuminance and total energy consumption. Comparison and analysis of the multivariate linear regression models showed the existence of a high degree of conflicts, which makes window and blind selection a rather complex multidimensional problem. Specifying the degree of the conflicts formed a hypothesis as: “A multi criteria decision-making method increases the controllability and manages the conflicts in selecting windows and blinds”. The developed hypothesis was later tested by employing analytical hierarchy process, as widely used multi criteria decisionmaking method. The analytical hierarchy process prioritizes decision-maker’ preferences and introduces a desired trade-off solution. The results of employing analytical hierarchy process showed the capability of it in managing the conflicts among visual comfort, thermal comfort, energy consumption and life cycle cost. Finally, the application of the analytical hierarchy process was expanded by integrating it with nondominated sorting genetic algorithm-II, as an optimization algorithm. Through this integration, optimization algorithm combines windows’ and blinds’ design variables and analyses a large number of solutions, while analytical hierarchy process ranks the solutions based on decision-makers’ preferences and introduces a desired trade-off solution. The integration between analytical hierarchy process and the nondominated sorting genetic algorithm-II was presented later as a conceptual framework. The developed conceptual framework can be used for selecting windows and blinds II in both residential and commercial buildings. In selecting windows and blinds, the conceptual framework is a novel solution to the lack of a feasible method for increasing the controllability for decision-makers and obtaining a desired trade-off solution.

By covering interiors, such as walls, ceilings and floors, with wooden surfaces, one can change the quality of indoor environments and thereby affect both psychological and physiological responses. Psychological responses refer to individuals’ emotional reactions toward interiors, while physiological responses include changes in the activity of the brain, the autonomic nervous system, the endocrine system, and the immune system. The above-mentioned responses considered in this study are those caused by visual, auditory, olfactory and tactile stimulation from interior wooden surfaces. Although earlier studies have presented valuable information on this subject, questions remain about the material properties of wood which are associated with the stimulation. Specifying the material properties can support architects, designers and engineers who intend to use wood in interiors for improving psychological and physiological responses. A literature study therefore has been conducted to determine (i) the material properties of wood which are associated with sensory stimulation, and (ii) to specify relevant recommendations or requirements which should be fulfilled when covering interiors with wooden surfaces. The results show a lack of knowledge regarding the material properties of wood and the degree in which it affects sensory stimulation.

The selection of the most appropriate window and blind design is a challenging task due to the existence of potential conflicts between visual comfort, thermal comfort, energy consumption and life cycle cost. Resolving these conflicts relies on a trade-off window and blind design. This research applied a decision-making framework to select a trade-off window and blind design for an office room in Sweden. The decision-making framework was developed based on integrating the non-dominated sorting genetic algorithm-II and the analytical hierarchy process. The first step in the application of the framework was to generate a model of the office room using EnergyPlus. Six types of window and four types of blind; an internal venetian blind, an internal roller curtain, an external venetian blind and an external overhang panel, were modelled in EnergyPlus. The second step was to run an optimisation using non-dominated sorting genetic algorithm-II. For this purpose, various window and blind design variables were specified in modeFRONTIER platform. The third and last step in the application of the decision-making framework was to select a trade-off window and blind design using analytical hierarchy process. The results show the strength of the decision-making framework in selecting a trade-off design, and thereby the ability to resolve conflicts through intelligent use of simulation in analyzing big-data in built environment, energy and cost sectors. Since, the computation and processing power for performing simulations is constantly increasing, architects and designers can exploit the decision-making framework and locate a trade-off design in a relatively short period of time.

Swedish government adopted national targets to reduce total energy consumption and mitigate environmental impacts. At this point, detached houses play an important role, since they account for a large share of dwelling stock in this country. The majority of these buildings are affected by technical deteriorations in building envelopes and heating, ventilation and air condition systems. Accordingly, there is a need for a deep renovation strategy, which covers both energy efficiency measures and economic issues. Additionally, a deep renovation can improve indoor climate, which contributes to the enhanced health and wellbeing. Thus, the aim of this study is to compare the efficiency of eight different renovation packages in reducing energy consumption and providing economic benefits in a detached house in Sweden. The renovation packages include 1) improving the U-value of building envelopes; 2) adding a heat recovery for ventilation system; 3) installing a ground source heat pomp for supporting heat demand and domestic hot water; 4) combination of renovation package 1 and 2; 5) combination of renovation package 1 and 3; 6) combination of renovation package 2 and 3; 7) combination of renovation package 1, 2 and 3; and 8) combination of renovation package 1, 2, 3 along with installing photovoltaic cells for producing electricity. The reduction in energy consumption was calculated in kWh/m². year for each renovation package, while the economic benefit was obtained by calculating the payback period during a lifespan of 50 years and internal rate of return with interest rates of 1%, 3% and 6%. The results indicate that renovation package 8 has the highest potential in reducing total energy consumption, while renovation package 3 is the most profitable solution since it provides the shortest payback period with the highest internal rate of return. The results help to define and project efficient energy policies in Sweden.

European Energy Performance of Building Directive (EPBD) defined a target as all new constructed buildings within the EU region must be a zero-energy building by the end of 2020. Furthermore, all European countries must ensure the minimum comfort threshold in energy calculations. Reducing energy consumption and improving indoor comfort, including visual and thermal com-fort, can contribute to economic benefits. However, the main problem is the exi-tance of conflicts among visual comfort, thermal comfort, energy consumption and life cycle cost. To solve the abovementioned problem and to fulfil the EPBD’s target, this study aims to apply an integration between BIM, optimiza-tion and Analytical Hierarchy Process as a multi-criteria decision-making method on an office building in Sweden. Accordingly, 3 types of windows and 5 types of external wall, ground floor and external roof constructions were specified as op-timization variables. The combination between the optimization variables gener-ated 375 design alternatives. The performance of all 375 design alternatives were evaluated with respect to visual comfort, thermal comfort, energy consumption and life cycle cost. Later, AHP was used to find a trade-off design alternative. The results show that the combination between window type 1, external wall type 5, ground floor type 1 and external roof type 5 is the trade-off design alternative. Furthermore, the results show the integration enables to solve the abovemen-tioned conflicts and to fulfil the EPBD’s target.

Sweden has an ambitious target to attain 50% more efficient energy use by 2030. Improving the energy performance of buildings provides a great opportunity to achieve the above-mentioned target. At this point, windows play a substantial role in improving indoor environmental quality and reducing energy consumption and cost. A computer-based system was therefore developed, which allows selecting a suitable window design. The computer-based system was intended to be used in a large-sized window and door manufacturing company in Sweden. However, the benefits of implementing the computer-based system cannot be realized until users accept using it. Former literature employed the technology acceptance model to investigate the influence of external variables on cognitive beliefs and trace their effects on users’ intention and actual system use. A successful application of TAM relies on the specification of the external variable. Accordingly, this paper conducted a systematic literature review to determine the external variable, affecting users' acceptance, thereby extended TAM. The analyses of results showed that organizational, individual, technological and environmental characteristics were the most influential external variables when investigating determinants of users' acceptance toward a computer-based system. Organizational characteristics contained mainly top management support, training, organizational culture, and organizational size, while individual characteristics embraced users’ previous knowledge and experience. Technological characteristics comprised information quality and system quality, meanwhile environmental characteristics included fulfillment of regulations and competitiveness. The extended TAM overcomes limitations attributed to the unified theory of acceptance and use of technology model since it considers attitude as direct determinants of intentions. In addition, the extended TAM is advantageous when compared with technology, organization, environment framework, because it has clear constructs, which allows tracing the influence of external variables on cognitive beliefs, and thereby their effects on users’ intention and actual system use. The extended TAM will be used to investigate determinants of users’ acceptance of the computer-based system in the manufacturing company in Sweden and compare the effect of external variables on users' acceptance.

Window blinds have a substantial role in shaping the energy consumption and improving thermal comfort and visual comfort. However, difficulties in selecting a window blind remain, due to existence of potential conflicts between visual, thermal, energy and life cycle cost. To overcome this problem, this study evaluates the performance of interior blinds, including venetian with slat of 0° and 45°, roller and double pleated blinds with respect to visual, thermal, energy and life cycle cost. Later, the Analytical hierarchy method (AHP) is used for selecting the best blind based on trade-off among the visual, thermal, energy and life cycle cost. In using AHP, visual comfort is determined as most important objective with a weight of 52%. The results show that venetian blind with slat of 0° drawn 100% is the trade-off blind. Accomplishing the sensitivity analysis on blinds’ global weight shows that venetian blind with slat of 0° drawn 100% remains the trade-off blind until the weight of energy and life cycle cost is below 37% and 57% respectively and the weight of visual comfort is above 4%. However, changing thermal comfort weight has no impact on ranking of the blinds. This study shows the capability of AHP in managing the conflicts.

Windows and blinds play a significant role in both shaping energy consumption and enhancing indoor comfort. But there are still difficulties with selecting windows and blinds due to the existence of potential conflicts between visual comfort, thermal comfort, energy consumption and life cycle cost. A literature review was conducted with the purpose of developing a decision-making framework that resolves the conflicts, and allows selecting a window and blind design based on trade-off between visual comfort, thermal comfort, energy consumption and life cycle cost. The decision-making framework was developed by integrating non-dominated sorting genetic algorithm-II as an optimisation algorithm with analytical hierarchy process as a multi-criteria decision-making method. The optimisation algorithm considers different window and blind design variables and analyses multiple designs, while the multi-criteria decision-making method ranks the optimization results and selects a trade-off design. An operating package enabled the decision-making framework to be automated. The operating package was obtained by coupling EnergyPlus as a simulation tool and modeFRONTIER as an integration platform. The decision-making framework was developed to select a trade-off window and blind design through intelligent use of simulation in analysing big-data in built environment, energy and cost sectors. Application of the framework ensures the minimum visual and thermal comfort thresholds with the lowest energy demand and cost. Architects and designers can use the framework during the design or renovation phase of residential and commercial buildings.

Window design and the selection of glazing system have significant effect on daylight illuminance. Occupants’ productivity is highly dependent on daylight, as it associates with numerous health advantages. Hence conducting a systematic investigation considering the performance of various window designs and glazing systems is highly important at the early stage of design process. For this purpose, this study attempts to develop a multivariate linear regression model for estimating the average daylight illuminance. To perform the simulations, an office room prototype was modelled by COMFEN 5Beta software. The prototype is a hypothetical office room, as its size, HVAC system and envelopes construction are based on the common practice in construction in Sweden. Because average daylight illuminance is sensitive to window size, orientation, glazing system, design model and position, 544 simulations were performed based on thses variable to create an extensive dataset.  A multivariate linear regression model was developed based on 90% dataset, which was chosen randomly. The obtained R² value was exceeded 96%, which shows an excellent fit for the developed model. The interaction between variables was also studied. The remaining 10% of dataset was utilized for validating the developed model. The validity of the model was further compared with another multivariate linear regression model, developed based on 50% of the dataset.The results show the effectiveness of multivariate linear regression models in supporting architects and predicting average daylight illuminance in early stage of design analysis.

Windows as essential elements of buildings have a significant effect on total energy consumption, including heating and cooling demand in Sweden. A statistical reliable model for estimating the total energy consumption associated with various window designs and glazing systems helps architects and designers in the early stage of the design process. Most of the introduced models in literature utilized a mathematic sampling algorithm such as Monte Carlo to develop a simple linear regression model for estimating the total energy consumption. A simple linear regression model cannot describe the effect of different groups of a categorical variable. Hence this study considers four variables related to the window characteristics, including window size, design model, orientation, glazing system and develops a categorical multiple linear regression model for estimating the total energy consumption. 544 simulations were performed by COMFEN Beta5 software. The results were used as a database for developing a categorical multiple linear regression model. The accuracy of developed model was studied by the coefficient of determination, R- square value (R²). The obtained R² exceeded by 94%. Furthermore, the predicted total energy consumptions obtained by the developed regression model were compared with the simulated values by COMFEN software. Results show a strong linear relationship between predicted and simulated values.  Developed multivariate linear regression model can be utilized in early stage of design process for estimating the total energy consumption associated with various window designs and glazing systems.

The Swedish government aims to reduce total energy demand per heated building area by 50% until 2050.  A large number of residential buildings, built within the so-called “Million homes program” in Sweden, need major renovations, which offers an opportunity to implement energy efficiency measures and thereby, reduce total energy demand. The best way to encourage the implementation of a major renovation is to demonstrate a practical method which reduces energy demand and provides economic benefits. Hence, this study aims to determine the most cost-effective energy solution in renovating a multi-family residential building. Multiple energy renovation measures were simulated on a case study to reduce the space heating and domestic hot water by 50%.  The case study building was built within the “Million homes program” and is located in Växjö, Swedish climate zone 3. Design Builder software was used for analysing the pre-renovation energy performance of the building. The renovation measures comprised different insulation thicknesses of external walls, attic and ground floors, windows with different U-values, a mechanical ventilation with heat recovery system, and solar system for supporting space heating and domestic hot water. Later, a multi-objective optimization was accomplished for analysing every possible combination of renovation measures.  The most cost-effective energy solution was obtained by calculating the net present value in a lifetime of 30 and 50 years and discount rate of 1%, 3% and 5%. Comparing the implications of two different lifetimes on net present value with implications of three different discount rates on net present value shows that lifetime has more influence on net present value. Furthermore, the results show the capability of the multi-objective optimization method in analysing multiple renovation solution.

Sweden passed legislation to achieve a target of net zero greenhouse gas emissions by the end of 2045. The Energy Performance of Building Directive further obliged European countries to ensure zero-energy building codes and improve the quality of indoor environments when buildings are renovated, as approximately 40% of total greenhouse gas emissions in Sweden are produced while heating buildings. Windows currently play a significant role in improving the quality of indoor environments and cutting total energy consumption, thereby reducing greenhouse gas emissions and mitigating environmental impact. Selecting a suitable window design is a complicated task compounded by two main difficulties: i) the availability of multiple window designs, each with a different glazing system, size, form and position; and ii) conflict between visual comfort, thermal comfort and energy consumption. Previous studies have primarily analysed a limited selection of window designs; however, analysing a wide variety of glazing systems, sizes, forms and positions will help resolve the abovementioned difficulties, thereby ensuring zero-energy building codes while improving the quality of an indoor environment. A multi-objective optimization was therefore completed to analyse the performance of a wide variety of window design variables and select suitable designs for an office room in Sweden. The results show the potential of multi-objective optimisation to resolve the difficulties of selecting suitable window designs.

The majority of the single-family houses in Sweden are affected by deteriorations in building envelopes as well as heating, ventilation and air conditioning system. These dwellings are therefore in need of extensive renovation, which provides an excellent opportunity to install renewable energy supply systems to reduce the total energy consumption. The high investment costs of the renewable energy supply systems was previously distinguished as the main barrier in the installation of these systems in Sweden. House-owners should therefore compare the profitability of the energy supply systems and select the one, which will allow them to reduce their operational costs. This study analyses the profitability of a ground source heat pump, photovoltaic solar panels, and an integrated ground source heat pump with a PV system, as three energy supply systems for a single-family house in Sweden. The profitability of the supply systems was analysed by calculating the payback period (PBP) and internal rate of return (IRR) for these systems. Three different energy prices, three different interest rates, and two different lifespans were considered when calculating the IRR and PBP. In addition, the profitability of the supply systems was analysed for four Swedish climate zones. The analyses of results show that the ground source heat pump system was the most profitable energy supply system, since it provided a short PBP and high IRR in all climate zones when compared with the other energy supply systems. Furthermore, results show that increasing the energy price improved the profitability of the supply systems in all climate zones.

The majority of single-family houses in Sweden are affected by deteriorations in building envelopes as well as heating, ventilation and air conditioning systems, since they are about 30 years old. Theses house are therefore in need of extensive renovation, which provides an excellent opportunity to incorporate energy efficiency measures to reduce both the energy consumption and also operational. Although former studies analyzed the cost effectiveness of various renovation packages, they mainly excluded the evaluation of energy price implications on cost effectiveness of different renovation package in Sweden. Accordingly, this study considers three energy prices and quantifies the payback period (PBP) and internal rate of return (IRR) of the packages, when renovating a single-family house in Sweden. The renovation packages included three distinct energy supply systems, commonly installed when implementing energy renovations: ground source heat pump (GSHP), photovoltaic solar panels (PV), and an integrated GSHP and PV system. The analyses of results show that a the GSHP system provides higher IRR and the lowest PBP compared to the other two renovation packages, due to its high performance in reducing energy consumption and its relatively low investment cost. Furthermore, results show that raising the energy price can increase the IRR and reduce the PBP of the renovation packages and respectively. Moreover, increasing the interest rate adds on PBP of renovation packages, since it depreciates the cost for saved energy. 

Improving the energy performance of detached houses is expected to play an important role in achieving energy and climate targets in Sweden. The majority of detached houses require energy renovations due to technical deteriorations in heating, ventilation, and air conditioning systems approaching the ends of their lives. Renewable energy supply system implementation leads to total energy use reduction. No previous studies provided information regarding how possible climate futures could affect subsidies required to implement these systems. This study compared the performance of an air-to-water heat pump (ASHP), a ground-source heat pump (GSHP), and an integrated system of a ground-source heat pump and photovoltaic solar panels (GSHP-PV) in reducing the total energy use of a detached house, which was initially supplied by an electric boiler. The performances of the supply systems were analysed in regard to three different climate scenarios, following the Special Report of Emissions Scenarios, A2 storyline. The effects of three different interest rates and two different lifetimes on subsidies were also investigated for all three energy supply systems. The GSHP-PV system was the most efficient system, as it secured 97%–100% of the total energy consumption, followed by GSHP and AWHP. The analyses of the results showed that variations in future climate conditions changed the subsidies required to install the supply systems. Furthermore, the results showed that changes in lifetime had greater impact on subsidies than interest rate growth.

The Energy Performance of Building Directive obligated all European countries to reduce the energy requirements of buildings while simultaneously improving indoor environment quality. Any such improvements not only enhance the health of the occupants and their productivity, but also provide further economic benefits at the national level. Accomplishing this task requires a method that allows building professionals to resolve conflicts between visual and thermal comfort, energy demands, and life‐cycle costs. To overcome these conflicts, this study exploits the incorporation of building information modelling (BIM), the design of experiments as an optimization algorithm, and the analytical hierarchy process (AHP) into a multi‐criteria decision‐ making method. Any such incorporation can (i) create constructive communication between building professionals, such as architects, engineers, and energy experts; (ii) allow the analysis of the performance of multiple construction solutions with respect to visual and thermal comfort, energy demand, and life‐cycle costs; and (iii) help to select a trade‐off solution, thereby making a suitable decision. Three types of energy‐efficient windows, and five types of ground floors, roofs, and external wall constructions were considered as optimization variables. The incorporation of several methods allowed the analysis of the performance of 375 construction solutions based on a combination of optimization variables, and helped to select a trade‐off solution. The results showed the strength of incorporation for analyzing big‐data through the intelligent use of BIM and a simulation in the field of the built environment, energy, and costs. However, when applying AHP, the results are strongly contingent on pairwise comparisons

Ambitious targets were set in Sweden to increase the share of renewable energy resources and reduce greenhouse gas emissions. Renovating old detached houses can assist in achieving the abovementioned targets, since they make up a great share of the final energy consumption and carbon dioxide emissions in Sweden. Although, several attempts were taken to improve the energy performance of the detached houses, the implementation of energy efficient renovation is yet low due to mainly high investment cost. Former studies evaluated the cost effectiveness of various energy efficient renovations in renovating detached houses in Sweden, but they provided no information how possible climate futures affect the determination and adoption of energy efficiency policies, such as monetary instruments. Accordingly, this study considered three distinct energy renovation packages and analyzed the subsidies required for implementing renovation packages for given interest rates and lifetimes. Furthermore, three different climate scenarios were considered to analyze the effect of possible climate futures on subsidies required. The analyses of results show that increasing the lifetime have greater impact on required subsidies than increasing the interest rate. Furthermore, the results show that variation in future climate conditions changes the required subsidies when implementing energy efficiency renovations. Results can be used as an aid when adopting energy efficiency policies. 

Based on an online survey, this paper analyzes the attitude of house owners in Sweden towards future renovations and one-stop-shop (OSS) services for deep renovation of detached houses. With the aid of a house owners’ decision-making journey for renovation, personal and contextual variables have been analyzed to identify those house owners having renovation plans in the near future, what they are going to renovate, and which needs led them to that decision. Furthermore, we examine if there is an interest in OSS concept. Results suggest that deep renovation is not yet prioritized. The priority for house owners is to change specific components of their dwelling and follow a step-wise approach. Aesthetic renovations are high on the agenda, with some structural and energy-related renovations following them. House owners between 29- 49 years of age could be the customer segment to target for deep renovations. The OSS concept seems interesting to a number of house owners, who can form an early adopters segment that could develop the market. There is a need for a cost-efficient OSS concept for deep renovations, ensuring the quality of work, and the optimization of financial products and tax incentives to accelerate the deep renovation market.

Floor heating and radiators are two of the most common types of hydronic heating systemsused for space heating in single-family houses in cold climate regions. Notwithstanding, there are fewcomparative studies on indoor temperature distribution and system cost evaluations for radiatorsand floor heating. Furthermore, there are no aligned outcomes in terms of total heat supply fora single-family house with radiators or floor heating. In this study, the eect of building energyeciency level and construction type, including flooring material, on the supply heating demand andtransmission heat losses were studied for both radiator and floor heating systems. For this purpose,a single-family house located in Växjö, Sweden, was modeled as a case study. The heating demandwas supplied with a district heating system with a similar supply temperature at 45 C for both theradiator and floor heating system. A sensitivity analysis was also performed to assess the eect offlooring configurations on the annual supply heating demand for both conventional and passiveversions of the case-study building. The results showed that the radiator-integrated building had alower supply heating demand in comparison with the floor heating-integrated buildings. Based onthe sensitivity studies, the flooring material did not have a significant influence on the supply heatingdemand and on the transmission heat losses in the case of the radiators. The supply heating demandwas only reduced up to 3% if the flooring U-value was improved by 60%. The results also showedthat refurbishment in a standard conventional building with a radiator heating system based on thepassive criteria led to a 58% annual energy savings, while this amount for a building with a floorheating system was approximately 49%.