An-Najah National University Faculty of Graduate Studies THE SMART ENERGY CONSUMPTION MANAGEMENT IN BUILDINGS By Baraa A. Hakawati Supervisors Prof. Allam Mousa Dr. Fadi Draidi This Thesis is Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Engineering Management, Faculty of Graduate Studies, An-Najah National University, Nablus - Palestine. 2023 III Dedication I am infinitely grateful and extend my heartfelt thanks to all those who wished me success and provided their unwavering support. IV Acknowledgements First and foremost, I express my profound gratitude to the Almighty for bestowing upon me the strength, patience, and courage to successfully complete this thesis. I would like to extend my special appreciation to my esteemed supervisors, Prof. Allam Mousa and Dr. Fadi Draidi, for their unwavering guidance, continuous support, and invaluable comments and suggestions that greatly contributed to the success of this thesis. I am also deeply grateful to the examining committee for their diligent efforts in reviewing the thesis and providing valuable feedback for its improvement. My heartfelt thanks also go to my cherished family and friends for their unwavering motivation and support throughout this journey. Furthermore, I extend my sincere appreciation to all the participants from various Palestinian sectors who generously shared their answers and provided the necessary information, with special gratitude to Engineer M, T and Engineer Q, A, S. Lastly, I express my deepest thanks to all those who directly or indirectly contributed to my completion of this thesis. Your support has been invaluable and greatly appreciated. IX List of Contents Dedication ................................................................................................................................. III Acknowledgements .................................................................................................................. IV Declaration ............................................................................................................................. VIII List of Contents ........................................................................................................................... IX List of Tables ............................................................................................................................. XII List of Figures .......................................................................................................................... XIII List of Appendices ................................................................................................................... XIV Abstract ...................................................................................................................................... XII Chapter One: Introduction and Literature Review ........................................................................ 1 1.1 Chapter Overview.................................................................................................................. 1 1.2 General Background .............................................................................................................. 1 1.2.1 Problem Statement .............................................................................................................. 2 1.2.2 Research Questions ............................................................................................................. 3 1.2.3 The Significant of The Study .............................................................................................. 3 1.2.4 Research Objectives ............................................................................................................ 4 1.2.5 The Structure of The Thesis ................................................................................................ 5 1.3 Theoretical Background ........................................................................................................ 5 1.4 Conceptual Modeling and Hypothesis Generation ................................................................ 9 1.4.1 Conceptualization of The Proposed Model ......................................................................... 9 1.4.1.1 Knowledge ..................................................................................................................... 10 1.4.1.2 Tasks .............................................................................................................................. 10 1.4.1.3 Cost ................................................................................................................................ 15 1.4.1.4 Environmental Effect ..................................................................................................... 17 1.4.2 Hypothesis Development .................................................................................................. 19 Hypothesis 1 (H1): ...................................................................................................................... 20 Hypotheses 2 (H2) ...................................................................................................................... 20 Hypotheses 3 (H3) ...................................................................................................................... 20 Hypotheses 4 (H4) ...................................................................................................................... 20 Hypotheses 5 (H5) ...................................................................................................................... 21 Chapter Tow: Methodology ........................................................................................................ 22 2.1 Chapter Overview ................................................................................................................. 22 2.2 Research Type ....................................................................................................................... 22 2.3 Research Approach ............................................................................................................... 24 X 2.3.1 Quantitative Approach ....................................................................................................... 25 2.3.2 Qualitative Approach ......................................................................................................... 25 2.3.3 Mixed Approach ................................................................................................................ 26 2.4 Research Methodology ......................................................................................................... 26 2.5 Design of The Research ........................................................................................................ 29 2.6 Data Collection Analysis Tools ............................................................................................ 29 Chapter Three : Analysis And Results ......................................................................................... 31 3.1 Chapter Overview................................................................................................................ 31 3.2 Qualitative Analysis ............................................................................................................ 31 3.2.1 First Hypothesis, Knowledge -> Behavior ........................................................................ 32 3.2.2 Second Hypothesis, Knowledge -> Cost ........................................................................... 33 3.2.3 Third Hypothesis: Environmental Impact > Knowledge .................................................. 34 3.2.4 Fourth Hypothesis, Behavior -> Cost ................................................................................ 35 3.2.5 Fifth Hypothesis, Behavior -> Environmental Effect ....................................................... 36 3.3 Quantitative Analysis ........................................................................................................... 39 3.3.1 Assessment of the measurement model (Outer Model) ..................................................... 39 3.3.1.1 Convergent Validity ........................................................................................................ 39 3.3.1.2 Discriminant Validity ...................................................................................................... 43 3.3.2 Assessment Of Structural Model (Inner Model) ............................................................... 47 3.3.2.1 Testing Hypothesis .......................................................................................................... 48 3.3.2.2 Coefficient of determination (R-squared values) ............................................................ 51 3.3.2.3 Predictive Relevance (Q - squared values) ..................................................................... 51 3.3.2.4Effect Size (F-squared values) ......................................................................................... 53 3.3.2.5 Goodness of Fit index (GoF) ........................................................................................... 54 3.3.2.6 Mediation Analysis ......................................................................................................... 55 3.3.3 Descriptive Analysis .......................................................................................................... 57 3.3.4 Hidden Patterns Assessment .............................................................................................. 58 3.3.5 Analysis of the Numerical Data Collected from the Institutions ....................................... 61 Chapter Four: Discussion, Conclusion and Recommendations .................................................. 62 4.1 Chapter Overview ................................................................................................................. 62 4.2 Discussion ............................................................................................................................. 62 4.2.1 Discussion of Smart Energy Consumption Management in Buildings .............................. 62 4.2.2 Qualitative Analysis Discussion: ....................................................................................... 63 4.2.2.1 Knowledge as The Main Driver ...................................................................................... 63 4.2.2.2 The Dual Role of Behavior ............................................................................................. 64 XI 4.2.2.3 Environmental Stewardship ............................................................................................ 64 4.2.2.4 Contribute To a Sustainable Future ................................................................................. 64 4.2.3 Hypothesis Testing Discussion .......................................................................................... 65 4.3 Conclusion ............................................................................................................................ 68 4.4 Recommendations ................................................................................................................. 69 4.4.1 Diversifying Geographical Representation ........................................................................ 69 4.4.2 Fostering Industry Engagement ......................................................................................... 69 4.4.3 Incorporate Additional Stakeholders .................................................................................. 69 4.4.4 Evaluation of Implementation Strategies ........................................................................... 69 4.4.5 Explore technology integration .......................................................................................... 69 4.4.6 Assessment of long-term behavioral change ...................................................................... 70 4.4.7 Policy and Regulatory Frameworks ................................................................................... 70 4.4.8 Cross-Sector Collaboration ................................................................................................ 70 4.4. Case Studies and Best Practices .......................................................................................... 70 4.4.10 Campaigns for Public Awareness .................................................................................... 70 4.5 Study Limitations .................................................................................................................. 71 4.6 Future Research ..................................................................................................................... 71 List of Abbreviations .................................................................................................................. 73 References ................................................................................................................................... 74 Appendices .................................................................................................................................. 79 ب ........................................................................................................................................... الملخص XII List of Tables Table 1: Operationalization of Model Constructs ........................................................... 19 Table 2: Factor Loadings ................................................................................................ 40 Table 3: Construct Reliability and Validity. ................................................................... 42 Table 4: Latent Variable Correlation .............................................................................. 44 Table 5: Cross Loading ................................................................................................... 45 Table 6: Heterotrait-Monotrait (HTMT) Matrix ............................................................. 47 Table 7: Path Coefficient, STDEV, T values, and P-Values .......................................... 48 Table 8: Quality Criteria - R² and Q² .............................................................................. 53 Table 9: Effect Size (F²) ................................................................................................. 53 XIII List of Figures Figure 1: The Research Model and Proposed Hypotheses ............................................... 9 Figure 2: Research Cycle ................................................................................................ 23 Figure 3: Research Methodology .................................................................................... 28 Figure 4: Model Framework - PLS-SEM Algorithm ...................................................... 47 Figure 5: Model Framework - P-values .......................................................................... 49 Figure 6: Model Framework - T-Statistics ..................................................................... 49 Figure 7: Heat Map for The West Bank Provinces ......................................................... 57 Figure 8: Model Framework: PLS-SEM Algorithm After Adding the Exogenous Variable ........................................................................................................................ 59 Figure 9: Model Framework: Bootstrapping - P-Values After Adding the Exogenous Variable .......................................................................................................... 59 XIV List of Appendices Appendix A: Tables ........................................................................................................ 79 Table A.1: The Common Application of Research Design. ......................................... 79 Table A.2: Survey Questions (English) ........................................................................ 80 Table A.3: Survey Questions (Arabic) ......................................................................... 81 Table A.4: Interviews Uniformed Questions................................................................ 82 Table A.5: Qualitative Analysis Coding Table ............................................................ 83 Table A.6: Indirect Effects ........................................................................................... 86 Table A.7: Total Effects (Mediation) ........................................................................... 86 Table A.8: Confidence Intervals Bias Corrected .......................................................... 86 Table A.9: Questioner Summary .................................................................................. 87 Table A.10: Convergent Validity. ................................................................................ 87 Appendix B: Figures ....................................................................................................... 88 Figure B.1: Heterotrait-Monotrait Ratio ....................................................................... 88 Figure B.2: Coefficient of Determination (R2) ............................................................ 89 Figure B.3: Knowledge Levels for Residents ............................................................... 89 Figure B.4: Behavior Levels for Residents .................................................................. 90 XII THE SMART ENERGY CONSUMPTION MANAGEMENT IN BUILDINGS By Baraa A. Hakawati Supervisors Prof. Allam Mousa Dr. Fadi Draidi Abstract Smart energy consumption management, a novel technology that increases energy efficiency and lowers energy use in buildings, operates on IoT principles. The purpose of this study is to comprehend how household awareness of smart energy consumption management affects smart energy consumption management and its effects on user behavior, expenses, and environmental impact. A survey with 100 valid replies was used in the research model to assess the knowledge and consumption habits of building tenants in Palestine. However, Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Smart-PLS software were used to assess the research model. The study results clearly indicate that installing intelligent energy consumption management systems in residential buildings can lead to significant improvements in energy efficiency. Implementing these advanced energy management systems holds great promise for enhancing sustainability, particularly by reducing environmental impact. The critical revelation from this research is the necessity for initiatives focused on enhancing residents' familiarity with these systems. Education and awareness campaigns are essential to encourage energy conservation and the responsible use of energy-efficient equipment. In conclusion, this study underscores the transformative potential of smart energy consumption management in contributing to a more sustainable and energy-efficient future for residential buildings, but it emphasizes that knowledge dissemination and awareness-raising efforts are integral to realizing these benefits. Keyword: Environmental Impact; Smart Energy Consumption Management; User Behavior. 1 Chapter One Introduction and Literature Review 1.1 Chapter Overview This chapter provides an overview of the topic of the study and the underlying theory. The elements that are divided under this part include the overall context, problem statement, research questions, significance of the study, research goals, research hypotheses, and dissertation structure. A survey of the literature on the subject of the thesis is also provided in this chapter. This aims to provide a comprehensive understanding of energy efficiency and cost concepts with reference to smart energy consumption management and environmental impact. The chapter also tries to determine the inhabitants' awareness of smart energy consumption management in buildings and their patterns of energy consumption inside the building. It also examines the links between these variables and how they are evaluated in the context of the housing market in the West Bank. The proposed hypotheses were developed in order to investigate and confirm the projected correlations between the study variables based on the most recent research on these topics. 1.2 General Background The acceleration of countries’ industrial, economic and population growth is considered the most critical factors in increasing energy consumption. There should be more efforts to generate energy to comply with this growth. Consequently, we need to search for alternative sources of energy. Unfortunately, in addition to the high costs it causes, excessive power generation is also a negative factor in air quality. It is also possible, in many cases, that environmental and political problems may arise due to resource depletion, global warming, and acid rain Juaidi et al., (2016). In accordance with the elucidation provided earlier, it is reasonable to assert that we need to manage energy consumption more rationally, using modern methods that do not waste energy and make better use of it. Nowadays, smart techniques and technologies are enhanced to be adopted in our daily life. One of these technologies is the Internet of Things (IoT), sometimes called the internet of everything or the industrial internet. IoT is an emerging technology paradigm 2 that can be considered a global network of machines and devices that can interact through the internet Lee & Lee, (2020). As for Shrouf & Miragliotta, (2015), the paper suggested an interesting research methodology as it designed a public opinion survey that includes the technologies and benefits that the IoT offers in the factory sector. In this study, the Palestine market is considered to be the target for us, especially in West Bank, with no smart electric meters such as those covered in Shrouf & Miragliotta, (2015) According to the statistics provided by the Palestinian Energy Authority (PEA) in West Bank, the energy consumption in the construction and buildings sector adds up to about 60 % of the total consumption of energy, which is much larger percentage than that of the industrial sector (no more than 7%). Accordingly, our study aims to examine the readiness of the residential buildings sector of the West Bank to adopt smart energy consumption management systems in buildings to manage energy consumption and how can smart energy consumption management be effectively applied in residential buildings to reduce energy waste and improve energy efficiency, taking into account factors such as residents' behavior and knowledge of smart energy consumption management by collecting a number of residents' opinions to study their general knowledge of the smart systems used in buildings to verify that there is sufficient residential awareness of these systems, which may help reduce environmental damage and reduce rising costs in energy consumption. 1.2.1 Problem Statement The main problem that this study aimed to solve is the need for smart energy consumption control in residential sector in order to increase energy efficiency and decrease waste. The study identifies several facets of smart energy consumption management, taking into account energy use, using energy-efficient equipment, automating energy management, and changing resident behavior. The study also emphasizes the importance of educating residents about smart energy consumption management and its potential benefits for reducing energy consumption, costs, and environmental impact. Therefore, the research problem can be summarized as follows: How can the adoption of smart energy consumption management systems in residential buildings be promoted to increase energy efficiency, reduce energy waste, save costs, and contribute to environmental sustainability, particularly in the context of the West Bank? 3 1.2.2 Research Questions First Question: How can education and awareness efforts be effectively implemented to promote the adoption of smart energy consumption management systems in residential buildings, particularly in the West Bank, and what impact does this have on residents' energy-saving behaviors and environmental sustainability? Second Question: What are the key factors influencing the successful implementation of smart energy consumption management systems in residential sector, and how can these systems be optimized to achieve reduced energy consumption and cost savings? Third Question: To what extent do smart energy consumption management systems contribute to increased energy efficiency, reduced energy waste, and improved sustainability in the residential sector, and what are the specific benefits and challenges associated with the adoption of these systems, especially in the context of the West Bank? The findings of this research will provide policymakers and stakeholders with valuable insights into developing effective strategies to enhance energy efficiency and reduce the environmental impact of energy consumption in the residential sector in Palestine. Furthermore, through this research, it is possible to come up with many results, the most important of which is knowing the extent to which the resident's knowledge of smart energy consumption management systems inside homes and their general behavior inside it affects the smart energy consumption management costs and the environment as well. Moreover, studying the growth and spread of homes that use smart energy consumption management systems in the region over the past years. In addition to knowing the most used technology in the construction sector in the Palestinian market at West Bank. In conclusion, concern with this point of view alone, in isolation from the other dimensions of this topic, is wrong and will lead to completely inaccurate results. 1.2.3 The Significant of The Study The study of smart energy consumption management in buildings in the Palestinian residential sector is significant for several reasons. Firstly, it promotes environmental sustainability by reducing greenhouse gas emissions and energy consumption, contributing to a more sustainable future. Secondly, implementing smart energy consumption management systems can lead to economic benefits, such as cost savings 4 for residents and building owners through reduced energy consumption and lower utility bills. Thirdly, the study can have a positive social impact by providing residents with a comfortable and sustainable living environment. Fourthly, through developing and implementing smart energy consumption management technologies and systems in the Palestinian residential sector, the study can help progress green technology. Finally, the study can provide insights and recommendations for policymakers and government officials, potentially leading to the development of more effective and sustainable energy policies. 1.2.4 Research Objectives Research goals are mentioned below based on the importance of the study: • The study aims to explore and demonstrate the advantages of smart energy consumption management systems, particularly in residential buildings. It focuses on the potential benefits, such as reduced energy use, cost savings, and improved sustainability. • The study seeks to examine the impact of education and awareness efforts on residents' knowledge and behavior regarding smart energy consumption management. It aims to understand how knowledge dissemination can lead to more responsible energy use. • The study aims to identify and analyze the key factors influencing the successful implementation of smart energy management systems, including IoT technology, energy-efficient equipment, and resident behavior. It intends to explore the challenges and opportunities associated with these factors. • The study is conducted with a specific focus on the West Bank, and one of its objectives is to assess the feasibility and relevance of smart energy consumption management systems in this particular context. It aims to determine the potential for these systems to be adopted and effective in the region. • To provide building owners and decision-makers suggestions and guidance on how to support the adoption of intelligent energy consumption management systems in the Palestinian residential sector, which might ultimately lead to the development of more effective and sustainable energy policies. These objectives collectively aim to contribute to the understanding of how smart energy consumption management systems can be beneficial, and the factors that influence their adoption and effectiveness, with a specific emphasis on the West Bank. 5 1.2.5 The Structure of The Thesis The thesis is divided into four chapters, each of which examines a distinct aspect of the research. The introduction and background of the study, a description of the research problem, a list of research questions, a summary of the research's objectives, a discussion of the theoretical foundations, and a review of the pertinent literature on smart energy consumption management in buildings are all included in the first chapter. The chapter offers both the developed hypotheses and a conceptual framework for the inquiry. The research methodology is summarized in Chapter and includes the types and methodologies of study taken into consideration, data collecting and sampling strategies, as well as methods for measurement development and data analysis. The third chapter focuses on data analysis, including descriptive statistics and evaluation of the proposed model. The study hypotheses are tested and the results are categorized in the chapter sections. The fourth chapter is dedicated to discussing the obtained results and their implications. This section also includes the conclusion, recommendations, limitations, and future research directions. 1.3 Theoretical Background The buildings sector ranks as one of the world’s primary sources of energy consumption. Just to mentioned, Mataloto et al., (2019) emphasize that buildings consume electricity as the primary energy source to provide thermal comfort (cooling and heating systems), lighting systems, communication systems, entertainment etc. to their residents. The research of Zhao & Magoulès, (2012) pointed to the factors that give rise to energy consumption and performance in buildings by noting that there are many influencing factors such as the interior design of the building, external conditions, lighting, air conditioning switches, occupant-related activities, and other causes that lead to indiscriminate use of energy. Nowadays, smart technologies and techniques have been promoted and supported for adoption in our daily lives. During the past few years, science, techniques, and technology have developed fast and fascinatingly. For example, mobiles with higher capacities than computers have become relatively common Mataloto et al., (2019). The technological 6 development has also extended to the electrical installations of homes and buildings, dealing with all kinds of applications and fields, such as lighting, shutter control, heating, ventilation, and air conditioning, as well as security and energy consumption management. According to Abdullatif, (2021), construction and building automation found itself in a swift expansion in technologies and techniques to provide a fully advanced management and monitoring of the operational edges in the buildings and develop the equipment in houses for better energy consumption. According to Andrade et al.,(2022), energy consumption management technologies can be implemented using the IoT, thus ensuring user comfort, which is the primary goal of smart systems in leading technological features in buildings. The IoT plays a vital role in our daily tasks now and in the future, and this can be seen through the recent developments in the world of the Internet, which in turn provides efficiency and effectiveness to the system on which it is based, making these new systems a source of convenience and a standard way of living due to their time, energy and cost efficiency (Kashan Ali Shah & Mahmood, 2020). An understanding not far off, as for Andrade et al., (2022), smart home is a residence and building equipped with smart technologies specifically designed to provide customized services to users. The technological features are represented by the ability to obtain the information from the surrounding environment and interact with it accordingly Marikyan et al., (2021). As for Andrade et al., ( 2022), studies conducted on smart homes recommend different types of technologies and systems to monitor energy consumption and thus reduce the cost to the consumer through a unique feature of control and monitoring or even through the use of computational intelligence solutions to help improve energy consumption. The Energy Use Control (EUC) which is refers to the practice of managing and regulating energy consumption in order to reduce wasted energy, save costs, and reduce environmental impact, the Energy Performance Analysis (EPA) which is the assessment of the energy efficiency of the building., the Energy Consumption Monitoring (ECM) which aims to ensure and track the amount of energy that the building uses, the Energy Demand Forecasting (EDF) which is the process of predicting the amount of energy 7 needed to meet the demand in a building, and the optimization solutions applied to a building are some of the most functions that can be performed to manage energy use from Al-Ghaili et al., (2021) point of view. To mentioned, according to Hannan et al., (2018), Building-Energy-Management- Systems (BEMSs) is one of the tools and systems standards in smart buildings, it is a method that can control and monitor energy-related functions and tasks associated with a specific building; this method can contribute to the effective management of potential sustainable energy. The main objective of the BEMS is to balance two critical considerations which are occupants’ comfort, and the Building Energy Efficiency (BEE) which pointing to the design and construction of the buildings in a way that maximizes their energy performance while minimizing their impact on the environment(Al-Ghaili et al., 2021). An example of smart, innovative technologies is the Konnex Associations System (KNX). To keep things simple, KNX is defined as an open global standard for building and facility automation, both commercial and domestic Abdullatif, ( 2021). As in all BEMS’s, the components of the KNX system are the sensors, actuators, and system devices Abdullatif, (2021). This system is recommended for many reasons, first, the system is characterized by the control of energy consumption and the programming method used in it is much easier than other systems through a program called ETS. Moreover, it is common for many large companies to manufacture spare parts for this system, which is very important in installation and maintenance operations (Abdullatif, 2021). In addition, this system is prevalent in European and international markets and is constantly being developed. And just to mentioned, one of its interesting features is that it does not need to change parts if the various functions of the system are modified. In addition, it can easily overlap between functions and produce multiple scenarios, and the long-term system cost is lower than traditional control methods (Woo & Seung, 2009). The residential sector has been identified as one of the most energy-demanding sectors, and as a result, there is strong interest in exploiting smart, wirelessly connected devices with the goal of improving energy efficiency, user convenience, and overall life’s quality Berbakov et al., (2019). Referring to energy consumption standards in buildings, 8 Dell’Isola et al., (2019) proposed a simplified and detailed approach to estimate the energy consumption of a specific device, which can be simply implemented in an energy monitoring IoT application but this methodology requires knowledge of the household configuration and basic information about the device. Mataloto et al., (2019) indicates that energy management systems in buildings can operate using IoT principles, in order to provide device connectivity and automation input, thereby reducing energy costs at the building level, and improving energy efficiency through intelligent lighting control as an example as well as providing the necessary means to reduce wasted energy. Transforming the behavior of the general society towards more efficient practices in the use of energy and reducing its waste is an appropriate option to keep pace with the advanced acceleration in technology and population growth, which in turn will require an increase in energy production, which means increasing investments in energy production and distribution infrastructure (Berbakov et al., 2019). Marinakis & Doukas, (2018) research stated that smart energy consumption management in buildings can have a significant positive impact on the environment through the use of technology to improve energy use, reduce losses and promote sustainable practices, and then buildings can reduce carbon emissions and contribute to global efforts to combat climate change. The research of Marinakis & Doukas, (2018) adds that one way smart energy consumption management can have a positive impact by reducing the amount of energy buildings use. By using IoT-based automated sensors and systems to monitor and control lighting, heating, and cooling systems, buildings can avoid unnecessary energy consumption and reduce carbon emissions as mentioned earlier. Overall, smart management of energy consumption in buildings can play a vital role in reducing our impact on the environment, promoting sustainable development, and mitigating the effects of climate change. Finally, building upon the prior discourse, it becomes manifest that finding applications of smart technologies in buildings to achieve the goal of the lowest possible energy cost 9 without any environmental impact on the life cycle of the building is the ultimate goal for all energy engineers, planners, designers and researchers (Bhutta, 2017). 1.4 Conceptual Modeling and Hypothesis Generation The concepts of modeling and hypothesis creation or generation are two closely related terms in the field of scientific research. Generally, the term conceptual modeling is about developing a theoretical framework or model to explain a particular phenomenon or group of phenomena, meanwhile, hypothesis generation involves creating testable specific data based on the previously mentioned model (Larry B. Christensen, 2016). 1.4.1 Conceptualization of The Proposed Model At this particular phase, our primary objective is to establish a comprehensive understanding of the basic research model. This entails defining the scope and criteria of the model while also delving into the fundamental concepts and their interrelationships, drawing on insights from prior studies. In Figure 1, we present the proposed model, which comprises four distinct constructs. Among these constructs, two are focused on the residents, namely knowledge and behavior. The remaining constructs pertain to the costs associated with smart energy consumption management in buildings, as well as the environmental impact of implementing such systems. It is important to note that all four constructs are presumed to possess reflective indicators, which will aid in evaluating their respective attributes and characteristics. Figure 1 The Research Model and Proposed Hypotheses Knowledge Behavior Cost Environment 10 1.4.1.1 Knowledge As the residential sector has been identified as one of the most energy-demanding sectors, there is strong interest in exploiting smart, wirelessly connected devices with the aim of improving energy efficiency, user comfort, and overall quality of life Berbakov et al., (2019). Knowledge of smart energy consumption management systems in buildings helps to choose the appropriate system based on the characteristics of the building in which the system will be installed, and we are exploring the extent to which the Palestinian residents recognize these systems. Residential knowledge research is crucial in the context of smart energy consumption control in buildings for a variety of reasons. To begin, the residential sector, which consumes a big quantity of energy, accounts for a sizable portion of overall energy consumed by buildings. Understanding how to manage energy consumption at home may have a significant impact on total energy use and conservation. Second, because global energy and environmental challenges persist, optimizing building energy use is more important than ever. By lowering energy waste and greenhouse gas emissions in buildings, particularly in the residential sector, smart energy management may enable a more sustainable future. The adoption of energy-efficient techniques in the residential sector may be hampered by various obstacles and problems, which may be identified by researching residential knowledge in the context of smart energy consumption management in buildings. Policymakers and academics can create efficient policies and interventions to encourage energy-saving behavior and ease the transition to a more sustainable energy future by understanding these constraints. 1.4.1.2 Tasks Building energy management systems (EMS) are tools for managing and keeping track of the energy-related activities and duties connected to a certain structure Al-Ghaili et al., (2021). The EUC, EPA, ECM, and EDF are some of these systems' primary responsibilities in buildings, and their overall goals are to maximize energy efficiency, cut costs, and limit environmental effect. Buildings with smart energy consumption management systems are becoming more and more crucial as the globe struggles with energy and environmental issues. The development of effective and efficient systems that 11 may optimize energy usage in buildings depends on an understanding of the activities and functions performed by these systems. Smart energy consumption management systems can assist in lowering energy usage and expenses in households because the residential sector accounts for a significant portion of the total energy consumption in buildings Shakeri et al., (2017). By examining the functions of these systems, it is possible to spot any obstacles that can prevent their acceptance in the residential sector and to create efficient tactics to encourage adoption and assure their broad usage. Understanding how these systems work and how they affect the energy landscape is crucial for a more sustainable energy future since they have the capacity to drastically change it and make it more efficient and sustainable. 1.4.1.2.1 Effort By maximizing energy utilization and minimizing waste, smart energy consumption management in buildings has an impact on employee productivity inside the facility. Building occupants may experience less effort and stress in an atmosphere that is more efficient and pleasant thanks to intelligent energy management technologies. The amount of effort residents must do to regulate energy consumption inside the building can be reduced by researching their understanding about smart energy consumption management. This can be achieved by improving their awareness of energy usage patterns and habits, developing tailored solutions that align with their understanding and capacity, encouraging behavioral changes, and providing feedback mechanisms and incentives to reduce energy waste. By educating residents about the importance of energy conservation and providing them with the necessary tools and resources, they can be encouraged to adopt better energy management practices that ultimately lead to long-term behavioral changes and reduced effort in managing energy consumption. In the smart energy consumption management approach, the devices are controlled remotely through a wireless controller and through an intelligent energy management system. A remote control device can control several LED lights, for example, wired or wireless, by automatic dimming, turning them on or off, changing the warmth of their glow, which reduces kinetic effort inside the building (Bhutta, 2017). 12 1.4.1.2.2 Time Smart energy consumption management in buildings can reduce the time required for system installation and maintenance because intelligent energy management systems often use wireless technology and automated controls, which can simplify the installation process and reduce the need for physical wiring. Through intelligent systems, sufficient data can be obtained to identify shifts to distinguish between performance fluctuations across transitional time periods such as between day and night, working hours, etc., to report behavioral pattern changes and problems promptly and also to address inconsistencies in time series data from variation data sources to represent accurate overall energy usage pattern (Yang et al., 2017). Studying the residents' knowledge of smart energy consumption management can reduce the system installation and maintenance time inside the building. By understanding the residents' knowledge and behaviors, installers can identify the specific needs of the building and tailor the system accordingly, which saves time and resources during installation. When residents are knowledgeable about smart energy consumption, they can participate in the installation process, help with troubleshooting and maintenance, reducing the need for professional help. Moreover, residents can maintain the system themselves, reducing the need for regular maintenance checks, and decreasing the time spent on system maintenance. Therefore, studying the residents' knowledge of smart energy consumption management can provide valuable insights that optimize the installation and maintenance processes, resulting in less time and resources needed to maintain the system. 1.4.1.2.3 IoT principals Smart energy consumption management systems In building can be delivered using IoT principles, in order to provide device connectivity and automation inputs, thus reducing energy costs at the building level, improving energy efficiency through intelligent lighting control, as well as providing means to reduce wasted energy (Mataloto et al., 2019). In the context of Smart energy consumption management in buildings, IoT devices can be used to collect data on energy use, occupancy levels, and other relevant factors. This data can then be analyzed to identify patterns and trends, allowing occupants within buildings to make informed decisions about how to optimize energy consumption. The 13 importance of studying IoT principles in the context of Smart Energy Consumption Management in Residential Buildings, based on residents' knowledge and behavior, lies in enabling the development of effective strategies and technologies to optimize energy usage, promote energy conservation, and empower residents with knowledge and tools to actively participate in sustainable energy practices, ultimately leading to reduced energy costs, environmental impact, and enhanced energy efficiency in residential settings. In general, the use of IoT technology in Smart energy consumption management systems can help buildings become more efficient, sustainable and cost effective. 1.4.1.2.4 Behavior The acceleration of technological progress and quick population growth will undoubtedly require an increase in energy production, which in turn will require significant investments in energy production and distribution infrastructure. But we have the other option which is to shift the behavior of the general community towards more energy efficient and less wasteful practices (Berbakov et al., 2019). Understanding occupants' patterns and habits of energy consumption is critical for developing effective energy management strategies, finding possibilities for energy savings, and developing tailored solutions to encourage smart energy usage. By studying how people behave, it is possible to identify instances of energy waste, such as leaving lights on inadvertently or using energy-hungry equipment during peak hours. Addressing these concerns can help to reduce energy waste and promote more ecologically friendly energy usage. A culture of energy efficiency within the building may also be established by educating residents on the need of energy conservation and providing them with the tools and resources necessary to appropriately regulate their energy consumption. In the end, this might result in significant energy savings. 1.4.1.2.5 Lightning Smart lighting systems are particularly interesting because they go beyond conventional lighting control and introduce autonomous lighting control based on feedback from embedded sensors, user data, cloud services, and user input. This leads to a number of advantages like increased energy savings, improved functionality, and lighting that is more user-centered (Chew et al., 2017). 14 Smart energy consumption management in buildings requires careful examination of resident lighting habits. By understanding residents' behavior, building managers can identify opportunities to reduce energy consumption and personalize lighting solutions to meet specific needs and preferences. Additionally, identifying areas where residents need education or incentives can lead to behavior change, resulting in significant energy savings and reduced environmental impact. Optimizing lighting systems using sensors that detect occupancy or daylight can also reduce unnecessary energy consumption. Therefore, studying residents' behavior in lighting promotes energy savings, personalization, behavior change, and system optimization, creating more sustainable and efficient buildings while also promoting resident satisfaction and comfort. 1.4.1.2.6 Air-conditioning Within the scope of smart home networks, residential air conditioners should not be a major contributor to household electricity bills and loads on electrical grids. Instead, they must be energy efficient and respond to fluctuations in the grid to mitigate demand imbalances in the power supply. The existing demand response control strategies for residential air conditioners primarily target single-speed units and predominantly rely on adjusting the temperature set point in response to the electricity rates from the previous day on an hourly basis. By using the adaptability of single-speed air conditioners, these solutions seek to maximize energy usage and successfully control peak demand periods (Hu et al., 2019). To regulate energy usage in buildings intelligently, it is essential to examine how inhabitants use air conditioning. It's because energy consumption is significantly increased by air conditioning, especially in hotter regions. Understanding resident behavior may assist find areas for energy savings and allow temperature control systems to be tailored to fit particular requirements and preferences, increasing resident comfort and satisfaction while improving energy efficiency. Buildings may be made more sustainable and effective by improving air conditioning systems with sensors that detect occupancy or alter temperature in accordance with external circumstances. 1.4.1.2.7 Electric heaters A significant portion of home energy use goes into heating water, and several efforts have been made to integrate various domestic heating technologies to create hybrid heating 15 systems that are more adaptable, efficient, clever, and affordable (Wang et al., 2020). Understanding how inhabitants behave might assist find areas for energy savings because electric heaters are a large energy consumer, particularly in colder locations. Greater resident comfort and satisfaction can result from adapting temperature control options to fit particular requirements and preferences via the behavior of inhabitants. This can also increase energy efficiency. 1.4.1.3 Cost Given the recent advancements in fast internet, the Internet of Things is going to become increasingly important in our day-to-day activities. The system on which the IoT is built gains efficiency and effectiveness thanks to it. Due to their time, energy, and cost effectiveness, these modern technologies are sources of convenience and a norm for life (Mahmood & Kashan Ali Shah, 2020) There are several reasons why it is crucial to research the expenses involved with smart energy consumption management. First off, by locating locations where energy usage may be decreased, it can result in cost savings. This is important since energy prices may account for a sizable amount of the expenses for both families and enterprises. Second, by finding opportunities to utilize energy more effectively and lower carbon emissions, an awareness of the expenses associated with controlling energy use may also aid in reducing the environmental impact of energy usage. Thirdly, by identifying possible dangers and weaknesses in the energy system, research into the costs of smart energy consumption management may enhance energy security. Lastly, it can promote innovation and economic growth by supporting the development of new technologies in this growing field. Overall, a better understanding of the costs associated with smart energy consumption management is vital for achieving a more sustainable, efficient, and secure energy system that supports economic growth and environmental sustainability. 1.4.1.3.1 Energy consumption The IoT provides the feasibility and effectiveness of the system on which it is based so that these new technologies provide convenience and a standard way of living due to their time, energy and cost efficiency Kashan Ali Shah & Mahmood,( 2020). For example, intelligent energy management systems in buildings define an energy consumption profile and predict the amount of energy consumption in the future, which can then be compared 16 to the available energy in order to respond in a timely manner to deviations and reduce overall energy consumption (Bhutta, 2017). Studying the costs associated with smart energy consumption management can help reduce energy consumption in several ways. Firstly, by identifying areas where energy is being used inefficiently, households and businesses can take measures to reduce energy consumption, such as replacing outdated equipment with more energy-efficient models. Second, by identifying locations where energy is being used needlessly, smart energy consumption management systems enable real-time monitoring of energy usage, which can result in behavior changes and energy reduction. Studying the costs of energy management also encourages people and companies to minimize their energy usage by highlighting the financial savings that may be realized by doing so. To achieve a more sustainable energy system by lowering energy consumption and carbon emissions, it is crucial to evaluate the costs of smart energy consumption management. 1.4.1.3.2 Installing System The installation of energy management systems may be significantly impacted by researching the expenses related to smart energy consumption management. It tackles possible installation difficulties, aids in finding the most economical solutions, and promotes innovation in this expanding industry. Businesses and consumers may choose which energy management system would be the most effective and efficient for their needs by knowing the costs involved, taking into account elements like up-front installation expenses, continuing maintenance costs, and possible cost savings. By utilizing the findings from cost analysis, policymakers, companies, and investors may also collaborate to overcome adoption hurdles and encourage the use of energy management systems. Building size, the quantity of energy-consuming appliances, and the amount of automation needed are a few variables that might affect the price of establishing an intelligent energy management system in a building. Moreover, the cost of installing a smart IoT-based system in a building depends on the cost of the hardware included in the system and the software that works with it (Kashan Ali Shah & Mahmood, 2020). 17 1.4.1.3.3 System type The cost of a smart system in a building varies according to the type of system in terms of implementing functions related to it, which means that making the system fully control the building will cost more than the cost of the same system, but for specific tasks such as lighting and air conditioning, for example (Kashan Ali Shah & Mahmood, 2020). Studying the costs associated with smart energy consumption management can help in choosing the appropriate type of energy management system for a building. This includes determining whether a full system or a system designed to detect a specific function is more appropriate. By studying the costs of different system types, residents can identify the most cost-effective option for their needs and potential cost savings associated with different system types. 1.4.1.4 Environmental Effect Energy engineers, planners, designers, and researchers across the industry are actively seeking ways to incorporate smart technologies into buildings. Their ultimate objective is to achieve the ambitious goal of minimizing energy costs while ensuring a negligible environmental impact throughout the entire life cycle of a building. These professionals recognize the immense potential of smart technologies in optimizing energy efficiency, reducing wastage, and enhancing sustainability in building operations. By harnessing the power of innovative solutions, they aim to strike a balance between economic viability and environmental responsibility in the pursuit of sustainable development (Bhutta, 2017). 1.4.1.4.1 Sustainability Sustainability is a major consideration in designing and implementing an energy consumption management system in smart buildings because such a system is designed to optimize energy use and reduce losses, which not only helps reduce operating costs but also has a positive impact on the environment. To reach the future with sustainable green energy, this is done through the deployment of smart energy technologies through which traditional buildings can be transformed into smart energy buildings that lead to this through less energy consumption and better management of it (Bhutta, 2017). 18 1.4.1.4.2 Residential role Residents can play an important role in contributing to the success of the Smart energy consumption management System by adopting energy efficient behaviors and using the tools and resources provided by the system. Currently, most of the population chooses high-efficiency air conditioners and home appliances with an energy rating mark and few change their behavior. Residents are likely to save more energy if they are interested in changing their behavior in low-cost activities and minor modifications to the structure of the building. Understanding home energy conservation behaviors can contribute greatly to developing an effective energy policy that suits the needs of residents and encourages home energy savings (Jareemit & Limmeechokchai, 2017). 1.4.1.4.3 Governmental role The government can play a critical role in promoting and motivating the adoption of smart management of energy consumption in buildings by developing policies and regulations to encourage the adoption of energy saving technologies and providing financial incentives to support the implementation of smart energy consumption management systems. Understanding the needs of the population in relation to energy-saving activities and preferred behavioral changes can be used by the government in defining household energy-saving strategies and guidelines (Jareemit & Limmeechokchai, 2017). In this research model, various constructs related to smart energy consumption management in buildings are defined and operationalized. These constructs help to understand the different aspects of smart energy consumption management and its implications on energy efficiency, user behavior, and environmental impact. Each construct is associated with specific items and indicators to measure and analyze the relevant variables. The following table is a summarization of each construct and its indicators with the references cited from. 19 Table 1 Operationalization of Model Constructs Construct Item Indicator Reference Knowledge. K1 Task. (Al-Ghaili et al., 2021) K2 Time. (Yang et al., 2017) K3 Effort. (Bhutta, 2017) K4 IoT principals. (Mataloto et al., 2019) Behavior. B1 Lightening. (Chew et al., 2017) B2 Conditioners. (Hu et al., 2019) B3 Heaters. (Wang et al., 2020) Cost. SCMC1 Energy Consumption. (Kashan Ali Shah & Mahmood, 2020) (Bhutta, 2017) SCMC2 Installation. (Kashan Ali Shah & Mahmood, 2020) SCMC3 Type. (Kashan Ali Shah & Mahmood, 2020) Environmental Effect. EE1 Sustainability. (Bhutta, 2017) EE2 Residential role. (Jareemit & Limmeechokchai, 2017) EE3 Governmental role. (Jareemit & Limmeechokchai, 2017). 1.4.2 Hypothesis Development After examining pertinent previous research, a comprehensive understanding of the existing knowledge and deficiencies in the realm of smart energy consumption management in residential settings was gained. Through a thorough literature review, it was revealed that there is a notable research gap in Palestine regarding smart energy consumption management in the residential sector. This gap served as the foundation for formulating hypotheses to address the identified research gap. Developing a hypothesis involves formulating a research question and proposing a tentative explanation or prediction that can be tested through the empirical research we will do later. Hypothesis development is an important step in conducting this current research on smart energy consumption management in buildings, by formulating testable hypotheses. We can focus our investigations on specific questions and determine whether smart energy 20 consumption management systems are effective in achieving energy savings and promoting sustainability in the construction sector within the West Bank. Residents' knowledge of smart management technologies for energy consumption in buildings can be tested by questioning them about these technologies and their energy consumption and observing whether they modify their energy behavior to reduce consumption based on their knowledge. Therefore, we can assume: Hypothesis 1 (H1): “Residents with knowledge about smart energy consumption management in buildings will adopt more sustainable energy behaviors". Residential knowledge trade-offs between the financial dimensions of smart energy consumption management cost and the environmental impacts of smart energy consumption management systems in buildings. The main objective of all intelligent energy management systems is to obtain the best approach to managing energy consumption, at the lowest possible cost, with the least effect on the environment. Therefore, the effect of knowledge on the cost is denoted by (H2), and the impact of knowledge on the environment is denoted by (H3). Hypotheses (H2) and (H3) are drawn as follows: Hypotheses 2 (H2): “Residents' knowledge of smart energy consumption management systems in buildings helps positively reduce costs associated with smart energy consumption management systems in buildings”. Hypotheses 3 (H3): “Residents' knowledge of smart energy consumption management systems in buildings helps positively to reduce environmental damage”. The behavior of residents plays a major role in how energy is consumed in homes, for example, negligence in saving energy increases the costs needed to manage and regulate the negligence of residents by the smart system inside the building. Hence, the following fourth hypothesis is drawn: Hypotheses 4 (H4): “Good residents’ behavior inside buildings positively impacts the reduction of costs associated with smart energy consumption management systems in buildings”. 21 As mentioned earlier, the behavior of residents plays a major role in how energy is consumed in homes. Based on this, the behavior of the residents in the way they deal with energy consumption has repercussions on the environmental situation, hence the following fifth hypothesis: Hypotheses 5 (H5): “The good behavior of residents inside buildings has a positive impact on minimizing potential damage to the environment”. In addition, we can create a new hypothesis to examine the relationship between residents' knowledge and their possession of a smart system for managing the energy consumption of their buildings. According to the idea, there could be a connection between inhabitants' knowledge and their buildings' smart energy consumption control systems. While the alternative hypothesis contends that there is a link between these two variables, the null hypothesis contends that there is none. According to this theory, people who know more about energy management are more likely to have smart energy consumption management systems installed in their buildings than people who know less. This might be as a result of homeowners' increased awareness of the advantages of utilizing a smart energy consumption management system, such as lower energy costs and a smaller carbon impact. Derived from the aforementioned exposition, it is evident that: Hypothesis 6 (H6): “There is a significant positive relationship between the knowledge of the residents and their possession of a smart energy consumption management system in their buildings”. As in the case of knowledge, this hypothesis can be applied to behavior, so we can assume that: Hypothesis 7 (H7): “Residents who possess a smart system for managing the energy consumption of their buildings are more likely to engage in energy-saving behaviors compared to those who do not possess such a system”. 22 Chapter Two Methodology 2.1 Chapter Overview This chapter discusses the thesis' approach in detail. The description of the methodology flow chart is followed by an introduction to the various study kinds and methodologies. Additionally, the chapter elaborates on the data collection strategy, including instrument development and sampling techniques. Finally, the data analysis techniques are presented to examine the relationships between the model constructs. 2.2 Research Type Hair et al., (2011) characterized research as a "discerning pursuit of the truth" (p. 3), while Stragier et al., (2010) defined it as a methodical approach to gather, examine, and interpret data in order to improve our comprehension of a phenomenon that is significant or of interest. Stragier et al., (2010) propose that research is a cyclic process that commences with a problem or an unanswered question and culminates with interpreting the problem. Nevertheless, the confirmed or unconfirmed hypotheses may give rise to emerging issues. The complete concept of the cyclic process is illustrated in Figure 2 on page 7, as cited from (Stragier et al., 2010). According to Islamia, (2016), the type or design of research refers to the conceptual framework used to conduct research. In addition, the author suggests that a good research design should be grounded in theory, situational, feasible, redundant, and efficient. Research types can be broadly categorized into exploratory, descriptive, and causal designs. When there is little or stale material accessible on a given topic, exploratory research, sometimes referred to as formulative research, is helpful. Researchers who want to find novel links, patterns, and concepts, among other things, should do this kind of study. The literature review is regarded as the initial stage in comprehending the problem in exploratory research. Although qualitative research methods are frequently used, quantitative methods may also be used (Islamia, 2016; Hair et al., 2011). 23 Figure 2 Research Cycle Note: Refer to (Stragier et al., 2010) p. 7 Researchers frequently employ descriptive research or statistical research when they need to characterize a specific topic of interest, such as a community or social event. Structured data gathering techniques are used in this kind of study, including data observation, structured question interviews, and questionnaires. A confirmatory form of study, hypothesis testing is frequently employed in descriptive research Islamia, (2016) Hair et al., (2011). The two types of descriptive studies are cross-sectional and longitudinal. Cross-sectional studies provide a snapshot or description of a business issue at a particular time, while longitudinal studies describe events over time by collecting data about sample units at multiple times to pursue the business element Hair et al., (2011). On the other hand, causal research or explanatory research aims to interpret the relationship between two events. A causal relationship occurs when a change in one event (the cause) results in a change in the second event (the effect) (Islamia, 2016; Hair et al., 2011). In addition to the research designs previously discussed, Islamia, (2016) also describes experimental research design. This type of research is used to test causal relationships 24 under controlled conditions, meaning that the variables being studied are manipulated and conditions are kept constant throughout the experiment. According to (Islamia, 2016a). x A offers a table describing the typical uses of study designs. According to Hair et al., (2011), scholars frequently combine several forms of study into a single project. For instance, they could begin with qualitatively-based exploratory research before switching to quantitatively-based descriptive designs. The objectives and research questions will determine the best sort of study. Exploratory research is often utilized when the study topic aims to elucidate a problem. The descriptive approach is best suitable if the research question focuses on characterizing an instance, a sum, or a variable. The most effective method for determining how one variable affects another is causal research. However, exploratory research can be employed in descriptive research to develop a research instrument for the topic. In conclusion, the type of research questions and objectives will determine the study design. There is a noteworthy shortage of information accessible when it comes to researching the use of smart energy consumption management systems in buildings and their prospective use in the Palestinian residential building industry. According to Hair et al., (2011) recommendations, exploratory research would be the best type of research design for this study. This is because exploratory research, which may be carried out using either qualitative or quantitative research methodologies, can give a better understanding of business difficulties when there is little information available regarding an issue or problem. Literature research was also completed to help with the creation of the questionnaire that was utilized in this study to gather data and examine correlations. In conclusion, exploratory research was chosen for this study since it was thought to be the most appropriate style of research given the nature of the investigation. 2.3 Research Approach The research topic and the sort of data needed for the study, whether it be textual or quantitative, are often taken into when choosing which research technique to use. According to John & Creswell David, (2014)definition, the research approach encompasses all the steps involved in a study, from assumptions to data collection, analysis, and interpretation. Generally, there are three main research approaches: quantitative, qualitative, and mixed methods. A quantitative approach is typically selected 25 when the research question requires numerical data, whereas a qualitative approach is used when the research question requires textual data. Mixed methods, on the other hand, are employed when the research question necessitates both numerical and textual data (Marvasti, 2018). 2.3.1 Quantitative Approach The quantitative approach involves the collection of numerical data and the use of mathematical models for data analysis. According to Marvasti, (2018), researchers using this approach typically employ a deductive style and test objective theories by examining relationships among variables. The resulting research report usually includes an introduction, theory and literature review, methodology, results, and discussion. Marvasti, (2018) classified the quantitative approach into three categories: descriptive research, experimental research, and causal comparative research. Descriptive research methods include correlational research, development design, observational study, and survey research. Experimental research evaluates the outcomes of treatments, while causal comparative research analyzes cause and effect relationships between independent and dependent variables. John & Creswell David, (2014) focused on two designs of quantitative research: experimental research, which investigates the effects of treatments on outcomes, and survey research, which provides numerical descriptions of population trends, opinions, and attitudes using questionnaires or structured interviews. These designs can be applied through cross-sectional or longitudinal studies. 2.3.2 Qualitative Approach Qualitative research, as defined by John & Creswell David, (2014), relies on textual and visual data and is an approach that seeks to explore and understand the meanings that individuals or groups ascribe to social or human problems. This approach typically employs an inductive style, in which data is collected in the participant's setting, the general theme is derived from the particular setting, and data interpretation is provided. Marvasti, (2018) similarly noted that in a qualitative approach, social phenomena are investigated from the viewpoint of the participants, which is a distinguishing characteristic of this research approach. Qualitative research can be conducted using 26 various methods, including case study or idiographic research, which provides an in- depth analysis of a program, event, activity, process, or one or more individuals. Ethnography study is another method of qualitative research that focuses on the culture of a group, such as their behaviors and languages, over an extended period. Grounded theory study is a method in which the researcher derives a general, abstract theory of a process, action, or interaction grounded in the views of participants. Phenomenological study, on the other hand, is a method that aims to understand people's perceptions and perspectives regarding a particular situation, while content analysis study involves a detailed and systematic examination of the contents of a particular body of material to identify patterns, themes, or biases. 2.3.3 Mixed Approach According to Marvasti, (2018), the mixed method approach allows researchers to employ both quantitative and qualitative approaches in a single study, thereby collecting numerical and narrative data. For instance, researchers can collect numerical data through closed-ended questions and narrative data through interviews using open-ended questions, both of which are used to answer the research question. The main premise of using this approach is to gain a more comprehensive understanding of a research problem than can be achieved by using a single approach alone, as noted by John & Creswell David, (2014). This mixed research approach combines the strengths of both quantitative and qualitative methods to provide a more robust and nuanced understanding of the research problem. Several studies have been conducted in Palestine utilizing the mixed method approach. Al Qadi et al., (2018), for instance, applied this approach in assessing and choosing the most effective practices for energy consumption in the residential sector. Given that the current study also pertains to energy management in the Palestinian residential sector context, the mixed approach was deemed suitable based on the aforementioned study. 2.4 Research Methodology Stragier et al., (2010) define research methodology as the general approach adopted by a researcher to conduct their study, including the specific research strategy and mechanisms used to collect data. According to Hair et al., (2011), the research process consists of 27 three main phases: formulation, execution, and analytical. During the formulation phase, the research problem is identified, a comprehensive literature review is conducted, research questions and objectives are established, hypotheses are formulated, and the research design is determined. In the execution phase, the researcher selects a sampling method, designs the data collection tools, collects the data, and stores it. The analytical phase involves data analysis, interpretation, hypothesis testing, and drawing conclusions and recommendations based on the results. Figure 3 illustrates the research flow chart in this study. The methodology employed three general stages, commencing with defining the study problem, which centered on exploring the role of residents in sustainable performance concerning smart energy consumption management in Palestine, including the impact of residents' consumption behavior in this association. A literature review of essential concepts was conducted, and the research gap was identified. Based on the literature, hypotheses were formulated, and a mixed research approach was adopted. 28 Figure 3 Research Methodology The next stage commenced with designing interview questions to be administered to government and private institutions involved in the research subject, while simultaneously designing and assessing the questionnaire with the assistance of academic experts. The study population for this research consisted of a representative sample of 100 accurate responses from the West Bank. And to ensure randomness, the questionnaire was electronically distributed through social media platforms among various groups associated with the providences and it was made clear that the data we aim to collect will be treated at a high level of confidentiality and professionalism, and that its purpose is for research only. Once data was collected, the smart-PLS software was utilized to analyze the data and test the hypotheses, and the results, discussion, and recommendations were presented. Formulatio n phase • Research Problem Defining. • Conducting the Literature Review. • Hypotheses Development. • Formulating the Research Design and Methodology. Executio n • Questionnaire Development. • Selecting the Sample. • Data collection. Analytica l phase • Data Analyzing. • Hypotheses Testing. • Drawing the Results. • Limitations Identifying. 29 2.5 Design of The Research In this sub-phase, we will present the overall plan and strategy used to conduct our research study, including selection of research participants, data collection methods, and analysis techniques. This research is carefully designed to be research on duality in terms of type, in other words, it is research that bears the characteristics of research, both quantitative and qualitative. From a quantitative point of view, an online survey was designed to collect residential opinions for testing the hypotheses of the research model. The online survey was structured into five main sections. The initial section focused on gathering general information about the respondents' buildings, such as the province, building size, monthly electricity bill, and whether it had a traditional or smart system. The second section comprised questions pertaining to residents' awareness and understanding of smart energy consumption management in buildings. In the third section, general inquiries were made regarding residents' consumption behaviors within their homes. The fourth section aimed to gauge residents' opinions on the costs associated with implementing smart systems for energy management. Lastly, the fifth section examined the environmental impacts resulting from the implementation of these systems. The last four sections implemented a five-point Likert scale for rating responses. The questions were used to develop multi- item reflective measures for the four constructs of the research model. Regarding the qualitative approach to pickling, we have conducted a number of systematic interviews with the most important companies in the smart systems sector in the Palestinian market, namely (Al - Seder) and (Al-Takamul), in addition to our glow to one of the most important governmental institutions concerned in this field, which is the PEA. We had a full dialogue with these organizations about the aforementioned research hypotheses, in addition to some general information about the Palestinian market in this field. 2.6 Data Collection Analysis Tools To test the hypotheses, this study targeted the residents in the West Bank. Therefore, the survey was intended to collect data as a primary source for testing the hypotheses of the model's constructs. Although we aimed for a recommended sample size of 170 participants based on a 10-times rule of thumb, and unfortunately, we were only able to 30 collect only 100 valid responses, resulting in a response rate of 58.8%. Despite the smaller sample size, we can still proceed with analyzing our research model using Smart-PLS. This software utilizes partial least squares (PLS) analysis, which is particularly well- suited for smaller sample sizes compared to other techniques. PLS is renowned for its resilience, capacity to manage assumptions violations, and superior performance with lower sample sets. The Partial Least Squares-Structural Equation Modeling (PLS-SEM) statistical software technique was utilized in this study to evaluate the data and verify the validity of our hypotheses since it is good at examining sample sizes and efficient at evaluating intermediary variables and indirect correlations (Sarstedt et al., 2014). The suggested model's validity and dependability may also be directly tested using the Smart Partial Least Squares (Smart-PLS) program. It boasts an extremely user-friendly UI and excellent graphics. 31 Chapter Three Analysis And Results 3.1 Chapter Overview The results of analyzing the data collected from the people and organizations in charge of monitoring energy use are highlighted in this chapter. The Smart-PLS4 program was used to analyze the survey responses, evaluate the model's validity and reliability, and validate the assumptions. At this point, our goal is to evaluate and interpret the data gathered through research to find trends, correlations, and patterns that may be utilized to guide decision-making. Our goal is to assess research results in order to support judgments and decisions. Large volumes of quantitative and qualitative data are gathered, arranged, and interpreted during the analysis stage utilizing a variety of techniques such descriptive statistics, illustrations, and visualizations. 3.2 Qualitative Analysis We will now analyze the information gathered through open-ended questions, observations, and other non-numerical techniques used in the interviews with representatives of the aforementioned institutions, specifically the businesses "Al- Takamul" and "Seder" in addition to the Palestinian Energy Authority. In Palestine, a notable distributor of electrical supplies is Al-Takamul Engineering Company. They have established a solid reputation for their superior expertise, vast experience, and superb assistance in the field of electrical solutions thanks to a committed staff of highly experienced engineers and technicians. Al-Takamul is renowned as a dependable one-stop shop for Electrical Contractors, Utility Companies, and Big Calibre Projects and is one of the biggest participants in the sector. Their dedication to providing top-notch services has strengthened their standing in the industry and brought them considerable accolades. In order to oversee the energy industry in the Palestinian territories, the Oslo Accords led to the establishment of the Palestinian Energy Authority in 1994. Promoting openness, effectiveness, and sustainability in the energy industry are among its objectives. The authority is in charge of creating energy-related laws and regulations, promoting investment in renewable energy projects, and overseeing the electrical industry. 32 Additionally, it wants international collaboration in the energy sector and encounters difficulties including Israeli limitations and financial and technological barriers. Despite these obstacles, the authority is dedicated to developing the energy industry and attaining both economic and environmental sustainability. Since 1987, Seder, a privately held Palestinian company, has been doing business in Palestine. It was formally incorporated as a private firm in 2004 and works in a number of areas related to security and electricity in Palestine. Seder Company holds a prominent position as an electrical service contractor in the Palestinian market. It specializes in several sectors related to low voltage systems, including burglar alarm systems, fire alarm systems, satellite system installation (DTH, SMATV, CATV), CCTV systems, and Automatic Gates, among others. Additionally, Seder Company collaborates with the technical institute (PITTI) to offer training programs in these fields. These trainings aim to enhance technical skills and expertise in the industry. Qualitative data provided valuable insights into the hypotheses we put forward throughout this study, and we discuss each hypothesis from the point of view of the institutional representatives we interviewed. 3.2.1 First Hypothesis, Knowledge -> Behavior The project manager at Al-Takamul Engineering company Engineer M, T, emphasized that residents' knowledge of smart management of energy consumption can play an important role in enhancing energy efficiency and sustainability in buildings. By educating residents, providing feedback and offering incentives, in addition, the Electrical Engineer at the same company, Q, A, S, confirmed that decision makers can encourage residents to adopt behaviors that contribute to a more sustainable future. On the other hand, the engineer at the Palestinian Energy Authority, M, A, M pointed out some details about some aspect in the hypothesis, which are the knowledge of smart energy consumption management, education, feedback, and incentives. The engineer said during the interview that individuals who are knowledgeable about smart energy consumption management know how to efficiently control their energy use in buildings. It involves teaching locals on ways to save energy, such altering thermostat settings, utilizing energy- efficient equipment, upgrading lighting, and using less standby power. Residents in these locations may make wise judgments and take activities that result in lower energy use by 33 becoming more knowledgeable. While he noted that Palestinian leaders can play a significant role in informing the populace about wise energy usage management. This can be accomplished in a number of ways, including giving seminars, disseminating educational materials (pamphlets, notes, or internet resources), or planning awareness campaigns. The objective is to arm locals with the information and expertise they need to make decisions that are energy-efficient in their everyday lives. Additionally, it has been noted that resident feedback is crucial in shaping their behavior. Through energy monitoring devices or utility bills, decision-makers can regularly update people on their energy usage. Residents are more likely to be aware of their energy use and motivated to make good changes if information is provided about their energy consumption habits and suggestions for methods to increase efficiency. Residents may be inspired to adopt energy-saving habits via incentives. These inducements may take the shape of monetary awards, energy bill reductions, or other non-financial advantages. By recognizing and rewarding residents for their efforts to save energy, decision makers can reinforce positive behaviors and encourage long-term sustainable practices. In another interview with Engineer O, H, an Electrical Engineer at “Seder” Company, he emphasized that by implementing the strategies mentioned above, decision-makers can create a supportive environment that promotes energy efficiency and sustainability. The ultimate goal is to enable residents to actively participate in smart energy consumption practices, leading to less energy waste, a lower carbon footprint, and a more sustainable future. 3.2.2 Second Hypothesis, Knowledge -> Cost H2 states that the residents' knowledge of smart systems in buildings has an impact on the overall cost of smart management of energy consumption. Engineer M, T, confirmed that smart systems in buildings are designed to automate and improve energy use by monitoring and controlling various systems such as lighting, heating and cooling. While his colleague in the company Engineer Q, A, S pointed out that the effectiveness of these smart systems depends on the understanding and use of the building's occupants. If the residents have little or no knowledge about how these smart systems work, they may not take full advantage of the available features. 34 In our interview with the Palestinian Energy Authority, Engineer M, A, M a real-world example of what was previously mentioned, whereby residents who lack knowledge may not adjust thermostat settings to optimize energy use or forget to turn off lights and appliances. On the contrary, residents with a good knowledge of these systems can actively participate in reducing the building's total energy consumption. Engineer O. H. stressed that residents' understanding of smart systems is crucial for lowering the cost of smart management of energy consumption in a building. To maximize the efficiency of these systems in decreasing energy usage and attaining sustainability objectives, homeowners must be educated about their characteristics and advantages. When citizens are better educated, they can make more intelligent decisions and actively participate in energy conservation, which eventually reduces costs by controlling wise energy usage. 3.2.3 Third Hypothesis: Environmental Impact > Knowledge H3 claims that the environment is significantly impacted by the locals' understanding of smart systems. Engineer M. T. made the point that intelligent energy management systems in buildings have the power to cut energy consumption, which results in a more ecologically friendly and sustainable living environment. When inhabitants are aware of the smart technologies placed in their buildings and understand how to utilize them effectively, they may take practical efforts to cut energy consumption and carbon emissions, said engineer Q, A, and S. They may, for instance, utilize smart thermostats to customize the temperature in their houses to suit their requirements and prevent overheating or chilling. Residents may help to energy conservation and prevent energy waste by turning off lights and appliances when not in use. They may also utilize low- flow faucets and shower heads to save water, which is another crucial element of environmental sustainability. Engineer M, A, M said: “Through knowledge about the features and capabilities of smart systems, residents are empowered to make informed decisions and actively participate in sustainable living practices. Combined, their actions can have a significant impact in reducing energy consumption and mitigating the overall impact of climate change on the environment.” 35 Engineer O, H summarized what was reported by saying that residents' knowledge of smart energy consumption management systems in buildings plays an important role in promoting sustainable living practices and reducing the environmental footprint. By understanding and using these systems, residents can actively contribute to reducing energy consumption, adopting energy-efficient behaviors, and mitigating the negative effects of climate change. 3.2.4 Fourth Hypothesis, Behavior -> Cost H4 indicates that resident’s behavior has a significant impact on the energy consumption management cost of smart systems. Engineer M, T, claimed that the behavior of residents may undermine the effectiveness of these systems designed to improve energy use and reduce waste. For optimal energy use and waste reduction, it is imperative that residents are aware of the energy saving features of their smart systems and make effective use of them. This includes understanding how to operate and program smart thermostats, lighting controls, and other energy management devices for maximum efficiency. Engineer Q, A, S explained that residents should also avoid overriding system settings in a way that renders them ineffective. Setting temperature settings that are too high or too low, for example, can lead to excessive power consumption. It is important for residents to follow recommended guidelines and use system settings intelligently to ensure energy efficiency. Moreover, Engineer M, A, M added that residents should pay attention to turning off devices when not in use. Unnecessarily leaving appliances, lights, or other electrical devices on can waste energy. By developing habits of turning off appliances and making sure they are not left idle, residents can contribute significantly to reducing energy consumption and lowering associated costs. Engineer O, H concluded the discussion on this hypothesis that residents’ behavior plays an important role in determining the cost of energy consumption management for smart systems. By being aware of the energy saving features, using the system effectively, avoiding excesses, and practicing responsible energy use, residents can increase the efficiency of these systems and help reduce overall energy costs. Adopting energy-conscious behaviors is 36 essential for optimizing energy consumption and achieving cost savings in smart energy management. 3.2.5 Fifth Hypothesis, Behavior -> Environmental Effect H5 states that resident’s behavior directly affects the environment, resulting in both positive and negative effects. Engineer M, T stated that this hypothesis confirms the crucial role played by the behavior of individuals in determining the impact of smart systems in buildings on the environment. Engineer Q, A, S added that the hypothesis assumes that the behavior of residents is directly related to the effectiveness of smart systems in buildings and their general impact on the environment. Residents may significantly help reduce energy use, choose more sustainable activities, and ultimately improve the environment by making efficient use of these systems. Engineer M, A, and M analyzed some of the key issues surrounding this concept, including energy efficiency, smart systems' effects, environmental behavior and effects, and sustainability possibilities. The idea accepts that individual actions may directly affect the environment, the engineer continued. This covers both constructive actions that help preserve the environment, including energy efficiency and sustainable practices, and destructive actions that harm it. Additionally, he supported the theory that claims resident behavior influences how smart building technologies affect the environment. Smart systems can provide citizens the knowledge and resources they need to make better informed decisions and adopt sustainable habits. However, how the inhabitants utilize and engage with these tools will determine how beneficial they are. Furthermore, he said that smart technologies may make it possible for occupants to more effectively monitor and regulate the energy consumption within their properties. Residents may help reduce energy use and the environmental impact it has by adopting energy-saving behaviors including regulating thermostats, controlling lighting systems, and maximizing appliance use. 37 "The hypothesis highlighting that resident's behavior can be instrumental in promoting sustainable choices," the engineer said as she wrapped off the conversation. This can include options such as using renewable energy sources, recycling, reducing waste, and adopting environmentally friendly practices. By actively engaging in sustainable behaviors, residents can contribute to a healthier environment.” In conclusion of our last interview with Engineer O, H, he said: “In general, H5 recognizes the critical role of individual behavior in shaping the environmental impact of smart systems in buildings. It emphas