Professional Barriers in Energy Efficiency Retrofits—A Solution Based on Information Flow Modeling
Abstract
1. Introduction
2. Materials and Methods
2.1. Literature Retrieval
2.2. Trend Analysis of Literature
3. Results
3.1. Visual Analysis of Key Literature
3.2. Process Design
3.3. Transformation Decisions
3.4. Cooperative Work
3.5. Risk Analysis
4. Discussion
4.1. Common Issues
4.2. Information Flow Model
4.3. Summary and Outlook
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
AI | artificial intelligence |
AR | augmented reality |
BEM | building energy model |
BIM | building information model |
DFD | data flow diagram |
DSM | design structure matrix |
EEMs | energy efficiency measures |
EPC | energy performance contracting |
IDEF0 | integration definition for function modeling |
IDSS | intelligent decision support system |
nZEBs | Near-zero-carbon buildings |
PERT | program evaluation and review technique |
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Types of Barriers | Main Barriers | Research References to Barriers | Bibliography |
---|---|---|---|
Technical Barriers | The implementation of energy efficiency retrofits involves technologies of great professional complexity and there are large gaps in professional competence between different professionals (energy efficiency retrofits are too complex) | Lack of technical knowledge and expertise is a significant barrier, leading to poor remodeling results. | [26] |
A lack of technical awareness among professionals can significantly reduce the outcome of a final remodel. | [27] | ||
Lack of knowledge about building retrofitting and the constraints of the current state of the art. | [28] | ||
Lack of knowledge leads to a limited understanding of the available technologies in energy efficiency retrofits and limited knowledge of building conditions to efficiently select implementation options (inadequate building audits) | Lack of complete information can be a huge deterrent to choosing to invest in energy-efficient technologies. | [29] | |
Asymmetric information among the involved parties and a lack of common goals lead to information gaps during the course of the project. | [30] | ||
Limited knowledge of the aging properties of building materials. | [31] | ||
Lack of proper understanding of the performance of older buildings. | [32] | ||
Lack of adequate documentation of proven sustainable retrofitting techniques for old buildings. | [33] | ||
Unclear information about the needs of the building of energy efficiency retrofits process and not knowing which organizations need to share information (unclear information needs) | Lack of important meter data can have a huge impact on energy efficiency estimates. | [34] | |
Lack of knowledge of current energy efficiency processes and what data are needed for the audits. | [35] | ||
Insufficient knowledge of material parameters in the same building series can lead to large errors in assessments. | [36] | ||
Limited knowledge of the sources and properties of sustainable materials for building retrofits. | [37] | ||
Economic Barriers | Lack of detailed and accurate energy use data and forecasts of retrofit effects, while the flow of multidisciplinary information in actual retrofits is restricted, and energy audits and payback calculations are not accurately assessed (poor integration of cost–benefit-related information leads to uncertainty in energy audits and payback periods) | Lack of information is a significant barrier to energy efficiency estimations in energy efficiency retrofits, and incorrect energy efficiency estimates can lead to errors in the final evaluation of the program. | [38] |
The methodology for calculating the payback time for energy efficiency measures is based on self-defined formulae, and some retrofitters do not really know yet how to calculate the payback time for energy efficiency measures. | [30] | ||
Investors are not clear about the payment calculation method, the actual retrofit effect, and the potential benefits that largely affect the motivation of energy efficiency retrofits. | [39] | ||
Lack of energy audits can address information and uncertainty issues that concern a variety of cross-disciplinary information, with the explicit mentioning of the lack of information as one of the more significant barriers. | [29] | ||
Information barriers are one of the major issues in energy efficiency retrofits, including cognitive, managerial, and technical aspects, further increasing the economic uncertainty. | [26] | ||
Some energy audits give less consideration to the cost. | [40] | ||
Life cycle costing remains a challenging task, and the lack of interdisciplinary cooperation has resulted in the lack of a coordinated approach to the task. | [41] | ||
The security of the payback period of energy efficiency retrofit projects is limited by the inaccurate assessment of the calculation of the project’s cost–benefit. | [42] | ||
Lack of information sharing and advice, limited resources and knowledge, and the risk of not realizing expected energy efficiencies. | [43] | ||
Often, when the initial investment is too large, there is no option to change to a less costly program, but rather to try to convince the investor (the initial investment is too large) | The problem of the excessive initial investment can be effectively dealt with through programmatic changes, of which the identification of programmatic and financing instruments prior to the start of a project is a major obstacle. | [26] | |
The initial availability of funds is the most decisive factor for district-scale renovation and directly determines most of the renovation approaches. | [44] | ||
High up-front costs, insufficient and unstable funding, and insufficient financial instruments available to support the reasonable costs of the benefits are major problems for the economy. | [31] | ||
Related to local government finances, fiscal incentives, tax grounds, grants, and direct subsidies from different regional governments lack real-world considerations (the lack of government incentives) | Government financial subsidies can promote institutional and individual incentives for retrofitting, while there is a lack of credible information on energy efficiency. | [27] | |
In China, a complex and effective financing policy has not yet been developed. Without financial incentives, residents, heating companies, and ESCOs have no incentive to move forward. Long-term incentive mechanisms or subsidy policies should be implemented immediately. | [45] | ||
Economic interventions (subsidies) can work to some extent. | [40] | ||
Environmental Barriers | Lack of a standardized quantitative framework for carbon emissions from building renovations and subsequent operations (the lack of a standardized carbon accounting framework) | Limited interdisciplinary knowledge transfer in building retrofitting has been identified as a major barrier. A key issue among these challenges is the lack of standardized assessment tools for environmental aspects. | [41] |
Accounting for gaps in building performance, invisible carbon emissions and carbon offsets in the carbon framework are major barriers. | [46] | ||
Evaluating the environmental impact from the perspective of a software engineer, design-oriented and interdisciplinary connections, data transparency, and incentives were identified as the most important aspects. | [47] | ||
Other Barriers | Complex interest disputes between stakeholders | Information asymmetry among stakeholders makes the willingness to transform inconsistent and even backward-looking among parties. | [48] |
Information asymmetry between the public and experts/government | When energy efficiency retrofits are undertaken, the participants’ awareness of energy efficiency and knowledge of the benefits can contribute greatly to energy efficiency retrofits. | [29] |
Stages Involved | Content | Year | Bibliography | |||||
---|---|---|---|---|---|---|---|---|
Design | Construction | Full Process | Retrofitting Decisions | Cooperative Work | Process Design | Risk Analysis | ||
× | × | 2025 | [50] | |||||
× | × | 2024 | [51] | |||||
× | × | 2024 | [52] | |||||
× | × | 2024 | [53] | |||||
× | × | 2023 | [54] | |||||
× | × | 2023 | [55] | |||||
× | × | 2023 | [56] | |||||
× | 2023 | [57] | ||||||
× | × | 2023 | [58] | |||||
× | × | 2022 | [59] | |||||
× | 2021 | [60] | ||||||
× | × | 2021 | [61] | |||||
× | × | 2021 | [62] | |||||
× | × | 2021 | [63] | |||||
× | × | 2021 | [64] | |||||
× | 2021 | [65] | ||||||
× | × | 2021 | [66] | |||||
× | × | 2020 | [67] | |||||
× | × | 2020 | [68] | |||||
× | × | 2020 | [69] | |||||
× | × | 2019 | [70] | |||||
× | × | 2019 | [71] | |||||
× | 2019 | [72] | ||||||
× | × | 2019 | [73] | |||||
× | × | 2018 | [74] | |||||
× | × | 2018 | [75] | |||||
× | × | 2017 | [76] | |||||
× | × | 2017 | [77] | |||||
× | × | 2017 | [78] | |||||
× | × | 2017 | [79] | |||||
× | × | 2017 | [80] | |||||
× | × | 2016 | [81] | |||||
× | × | 2016 | [82] | |||||
× | × | × | 2015 | [83] | ||||
× | × | 2015 | [84] | |||||
× | × | 2015 | [85] | |||||
× | × | 2015 | [86] | |||||
× | × | × | 2014 | [87] | ||||
× | × | 2014 | [88] | |||||
× | 2014 | [89] | ||||||
32 | 3 | 5 | 26 | 5 | 2 | 4 | Number of relevant studies |
Research Location | Total Number of Risks | Number of Risks of Inappropriate Coordination | Percentage Share of Total Number | Weighting | Bibliography |
---|---|---|---|---|---|
China—Hong Kong | 18 | 10 | 55.6% | / | [96] |
China | 21 | 9 | 42.8% | / | [97] |
China—Southern Region | 8 | 5 | 62.5% | / | [98] |
Russia | 22 | 10 | 45.4% | 36.3% | [99] |
China | 11 | 6 | 54.5% | 53.6% | [100] |
Modeling Technology Name | Disadvantages of Information Modeling | Bibliography |
---|---|---|
Program Evaluation and Review Technique (PERT) | Insufficient flexibility and over-reliance on predetermined activity grids and duration estimates make it difficult to track task follow-up. Inability to provide a detailed account of the information flow, only predicting the elapsed time of events, and not taking into account the impact of the uncertainties involved. Probabilistic, using probabilistic estimates to measure the project elapsed time. | [108] |
IDEF Modeling Methodology | The system is highly complex, with a huge upfront investment, requiring knowledge of the entire event process, for the input, output, mechanism, and control information requires the full cooperation of personnel from multiple departments. Highly integrated information, high requirements for personnel, requiring the participation of personnel with a high level of specialized knowledge. Expandability: for new technology, new processes can be based on the original model to establish a new IDEF0 model. Substitutable modularity: the IDEF0 model consists of modules, and any module can be replaced by a new module under the condition of ensuring correct information flow. Modeling normalization: the symbols and rules used in the IDEF0 modeling are unified and recognized by various industries. Process normalization: the IDEF0 modeling establishes processes with sequential logic that can be used to guide the design or implementation of processes. Hierarchical: the IDEF0 modeling is based on task decomposition (WBS), with multiple levels of task hierarchy. | [109,110] |
Petri Net | The system has a large amount of computation and is prone to data explosion; when the nodes and tokens are increased, the data on the original basis increase exponentially, leading to difficulty in verification. Flexibility: the logic of complex or dynamic behavior of the system can be processed by adding or subtracting nodes, and has a strong processing capacity. Lack of time dimension: the ability to express event time dimension information is weak. | [111,112] |
Data Flow Diagram (DFD) | Inadequate representation of information dependencies and inability to characterize the complex dependencies and interactions between parts of the information. Intuitive: graphical representation and easy to understand. Statelessness: DFD does not focus on the state changes in the system, only on the processing and flow of data. Different perspectives and understanding of processes by each person make it difficult to standardize the same system, and require the intervention of people who are more familiar with the processes. | [113,114,115] |
Design Structure Matrix (DSM) | Ease of operation through the matrix form to represent the structure and dependence of the system; easy to analyze and optimize. Collaborative decoupling, which can be based on matrix iteration, and with a strong collaborative decoupling effect for negative feedback information. Versatility: can be used for system design and also for project management and schedule control. | [116,117] |
System Dynamics Model | Quantifiable: capable of quantitative analysis and numerical simulation to assess the performance of the system. Fuzzy transfer of information, with only positive and negative feedback, as well as cause and effect relationships. | [118,119] |
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Share and Cite
Liao, X.; Wang, C.; Li, B.; Li, B.; Du, C. Professional Barriers in Energy Efficiency Retrofits—A Solution Based on Information Flow Modeling. Buildings 2025, 15, 280. https://doi.org/10.3390/buildings15020280
Liao X, Wang C, Li B, Li B, Du C. Professional Barriers in Energy Efficiency Retrofits—A Solution Based on Information Flow Modeling. Buildings. 2025; 15(2):280. https://doi.org/10.3390/buildings15020280
Chicago/Turabian StyleLiao, Xilong, Chun Wang, Baiyi Li, Baizhan Li, and Chenqiu Du. 2025. "Professional Barriers in Energy Efficiency Retrofits—A Solution Based on Information Flow Modeling" Buildings 15, no. 2: 280. https://doi.org/10.3390/buildings15020280
APA StyleLiao, X., Wang, C., Li, B., Li, B., & Du, C. (2025). Professional Barriers in Energy Efficiency Retrofits—A Solution Based on Information Flow Modeling. Buildings, 15(2), 280. https://doi.org/10.3390/buildings15020280