Cognitive Map Method Research Articles

Triangular Fuzzy Cognitive Maps Method for Modelling Interrelation between Causal and Trigger Factors Towards Students' Mathematics Problem-Solving Ability

The purpose of this study is to model the interrelation between causal and trigger factors towards students' mathematics problem-solving ability by using the triangular fuzzy cognitive maps (TrFCM) method. Selection weaknesses and limitations in the method of relational analysis cause the interrelation and influence between variables not to be visualised and do not reveal the characteristics of the actual interaction. As a result, this study demonstrates TrFCM as a more effective way of analysing the relationship between variables based on the complexity that happens in analysing causal factors and triggers for students' problem-solving abilities in mathematics. The results of the influential relations map (IRM) demonstrate that emotion and metacognition are the triggers for problem-solving ability. While executive function is the main cause of success in completing mathematics problems, it is also influenced by additional factors such as motivation, attention, and working memory. These causal and triggering factors also mobilise parts of students' cognitive and behavioural performance to improve the process of solving mathematics problems. Based on the outcomes of this study, computational intelligence methods like fuzzy systems give useful procedures for analysing data from expert surveys. The TrFCM method offers a more accurate relational analysis procedure in modelling interrelation between human factors.

Феномен релокации (Модели экономического поведения российских мигрантов после февраля 2022 г.)

The events of February 2022 became the starting point of a new wave of Russian emigration. On the one hand, this phenomenon can be considered within a series of previous migration waves, on the other hand, the modern context leaves its imprint on the current migration process, making it very special from the economic and sociocultural perspectives. The article presents an attempt to analyze this specificity with an emphasis on the characteristics of the economic behavior of emigrants. Empirically, the study is based on a series of in-depth interviews with people who left Russia after February 2022. On the basis of these interviews, the authors built idealized cognitive models of possible options for the economic behavior of migrants. The authors considered a total of four models: relocation, which involves searching for a job in the host country; relocation, which involves remote work for a Russian company; relocation, which involves creating or moving one’s own business; relocation to a branch of a Russian company. Since the economic strategies of migrants are influenced by signals broadcast by the Russian government structures, the article analyzed the statements of representatives of these structures using the method of network cognitive mapping, which made it possible to reveal two types of official discourse in relation to those who left Russia, which differed in the extent of their criticism towards them. In general, the study showed that migrants of the latest wave are internally heterogeneous and fall into several groups that differ markedly in their motivation and patterns of economic behavior. At the same time, a significant part of them continues to cooperate with Russia in one way or another and, in principle, is ready to return to Russia. For them, migration is driven largely by security and/or economic reasons. Only a minority of emigrants left the country due to their disagreement with the current political course and consider the possibility of coming back only if the political course changes radically.

Cognitive mapping of the economy of trust

The concept of trust has been extensively explored by governments, researchers, and academic communities focusing on public authorities and the financial system, albeit in separate contexts. Trust plays a vital role in both sectors, influencing various aspects of governance, economic stability, and societal well-being. However, the relationship and interdependencies between trust in the government and trust in the financial system remain relatively unexplored. In addressing this gap, this study aims to improve the understanding of the role of trust in the socio-economic system and provide a framework for analysing the complex causal mechanisms between developments in the financial and public sectors using trust concepts. To achieve this, the study adopts the Fuzzy Cognitive Mapping (FCM) method in combination with the fuzzy Delphi method (FDM) as the methodological approach. The results highlight that even a small decline in trust can have severe repercussions on the stability of the financial system, deposit levels, exchange rate stability, and the prevalence of non-performing loans. Additionally, violations of trust in the financial sector also impact the development of the public sector, resulting in decreased trust in the government, fiscal stability, tax revenues, and government bond purchases. The study also demonstrated that when trust in both the financial sector and the government is eroded simultaneously, the complexities and the extent of negative consequences are amplified. These findings emphasize the interconnected nature of trust dynamics in both sectors and underscore the importance of a comprehensive approach to addressing trust-related challenges.

Investigating customer behavior on Instagram to enhance online sale: modeling the effect of content types and broadcasting tools

Purpose This study aims to examine the role of various Instagram contents on customer behavior. The studied case is associated with herbal teas sold on active Instagram pages. Design/methodology/approach A structured questionnaire is exploited to collect data from customers. The integration of two entropy weight methods and weighted sum method are used to evaluate the priority of contents. In addition, model development is illustrated through which Instagram broadcasting tools are prioritized benefiting from fuzzy cognitive map method. Findings The results illustrate that customer behavior is moderated by content types, which empirically enhances the profitability of the business. The results of this study reveal that educational live, show other ones experience at live as well as motivational lives are the most effective contents. This study is a pioneering one to practically assess the construct of social media engagement through the effects of content types on the Instagram platform. Originality/value The effects of various contents, including motivational content, other customers’ experiences, products, educational content and purchase bill, on customer behavior are studied.

Multiple-Input–Multiple-Output Randomized Fuzzy Cognitive Map Method for High-Dimensional Time Series Forecasting

Multiple-Input–Multiple-Output Randomized Fuzzy Cognitive Map Method for High-Dimensional Time Series Forecasting

An analysis of challenges to the low-carbon energy transition toward sustainable energy development using an IFCM-TOPSIS approach: A case study

As countries worldwide grapple with the urgent need to mitigate climate change, adopting low-carbon energy sources has become a top global priority. This priority is particularly emphasized in the European Union (EU), with various initiatives, policies, and regulations to promote renewable energy sources and reduce carbon emissions. Despite these efforts, the transition to a low-carbon energy future has faced several challenges, such as the high cost of renewable energy technologies, land use, and technical issues. These challenges require decision-makers to consider and address various factors to ensure sustainable and low-carbon energy development. In this context, the present study identified challenges to the low-carbon energy transition through a literature review from 2013 to 2023. The study then set out a novel intuitionistic fuzzy cognitive map method to map the interactions of identified challenges and analyze the case study performance in dealing with the challenges under three scenarios: people first, technology first, and duet. Subsequently, the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) method was applied to find the best scenario according to performance analysis. The results indicated that the most significant challenge is investment, followed by short-termism, and reformation, out of seventeen identified challenges. Results also indicated that the duet scenario was the best, and broad conclusions and policy implementations were provided according to the obtained results.

A method based on q-rung orthopair fuzzy cognitive map and TOPSIS method for failure mode and effect analysis considering risk causal relationships

As a preventive maintenance technique, failure mode and effect analysis (FMEA) is widely applied to determine and eradicate possible failures. In recent years, many FMEA methods have been developed to address the limitations of traditional FMEA methods in failure mode (FM) assessment, weight calculation, and FM prioritization in complex uncertain environments. However, due to the complexity of equipment, systems, services, etc., there is an inevitable influence on causal relationships between FMs, which is rarely considered by existing methods. Therefore, a novel FMEA method, which integrates the technique for order preference by similarity to the ideal solution (TOPSIS) of q-rung orthopair fuzzy set (q-ROFS) and q-rung orthopair fuzzy cognitive map (q-ROFCM), is proposed for reasoning the relationships between FMs. The design of the novel method, named q-ROFCM FMEA, involves three stages. The q-ROFS is applied to evaluate the risk factors for capturing more ambiguous information in the first stage. The q-ROFCM is proposed and the causal relationship between FMs is integrated to describe the impact of the relationships on the evaluation results through the dynamic behavior of FMs in the second stage. In the third stage, the TOPSIS method is applied to determine the priority ranking of FMs based on more reliable similarity measurement results of the projection measure. The proposed new method is applied to the FM risk assessment of power units in the railway turnout system. The competitiveness and effectiveness of the proposed method have been demonstrated by comparison with other classic methods and sensitivity analysis.

Fuzzy cognitive map and mean square method in empirical modeling: Application in economics

This article offers a Fuzzy Cognitive Map (FCM) - based method of empirical modeling which can be considered as an alternative to multivariate regression analysis for the input–output relationship extraction from experimental data. Vertices of the FCM graph are interpreted as input–output variables of the empirical model, and the weights of arcs are unknown parameters that are estimated in two stages. The first stage consists of the arcs weights estimating based on the proximity of the columns’ values in the input–output observation data table. At the second stage, the observation table is used for the offline weights adjustment using the least squares method and the optimization procedure by genetic algorithm. The method is illustrated by the example of the World Bank data testing the relations between Gross Domestic Product per Capita vs demographic, educational, economic, technological and other factors. The novelty of the method in comparison to the Soft Regression technique lies in the utilization of the FCM arcs weights adjustment according to the least squares criterion.

A Study on the Lexical Evolution of Yuzhong Dialect Based on Cognitive Mapping and Its Pragmatic Mechanisms

Abstract Based on the method of cognitive mapping, this paper systematically organizes the evolution of Yuzhong dialect vocabulary in different historical stages, revealing its important role in the evolution of the Chinese language. The global statistical information of the corpus is utilized to train the word vectors, which are input into the recurrent neural network as feature vectors to enhance the model’s ability to learn long-distance information. Perplexity is defined as a metric for evaluating the performance of a language model, the inverse of the geometric mean probability assigned to each word by the model given a known sequence of words in the test set. Subsequently, based on this metric, a corresponding model was built to comprehensively evaluate the performance of the language model, which provides insights into the functions and expressions of Yuzhong dialect words in communication. Among them, the number of unsubstituted nouns, such as weather, is 41, and the color of the sky is 67, showing the rhyme and stability of Yuzhong dialect vocabulary in specific domains.

Exploring Dynamics of Water, Energy, and Food Systems in Agricultural Landscapes Using Mental Modeling: A Case of Varamin Plain, Iran.

This study applies the mental model and cognitive mapping method to involve stakeholders in delineating the mutual relations between sources of water, energy, and food (WEF) production in the Varamin Plain (VP). Through involving farmers and managerial experts, the approach facilitates the deployment of community communication patterns to recognize and comprehend problems and move from single-loop learning to double-loop learning. The dynamic model was driven from the final mental model of the participants to reflect changes in the systems over time. The system dynamic (SD) model incorporates three scenarios for enhancing irrigation efficiency, managing groundwater extraction, and satisfying environmental needs. The results uncovered that the surface and underground water resources of the VP will gradually decrease within the next two decades in the range of 158 and 2700 million cubic meters (MCM) per year. Also, the plain suffers from water insecurity and a 162 MCM shortage. Consequently, focusing on understanding the nexus and nexus governance can enhance resource management and achieve sustainable development goals. Essentially, promoting collaborative governance, such as creating cooperative organizations and implementing double-loop learning, and instituting a water market, regulatory governance, and monitoring laws can improve the state of Varamin Plain's resources. These results carry important policy implications for using mental models to consider dynamics for discussions on participatory management of the WEF system nexus and environmental management.

New Hybrid MCDM Approach for an Optimal Selection of Maintenance Strategies: Results of a Case Study

Summary Industrial systems are becoming more sophisticated, and their failure can result in significant losses for the company in terms of production loss, maintenance costs, fines, image loss, etc. Conventional approaches to modeling and evaluating the failure mechanisms of these systems do not consider certain important aspects, such as the interdependencies between failure modes (FMs) with information and data containing uncertainties as they are generally collected from experts’ judgments. These restrictions may lead to improper decision-making. The use of more advanced techniques to model and assess the interdependencies among components’ failures under uncertainties seems to be more than necessary to overcome these deficiencies. It is in this context that the proposed approach fits. It consists of proposing a hybrid multicriteria decision-aking (MCDM) approach that combines several techniques for a better selection of maintenance strategies. Using the failure mode and effects analysis (FMEA) technique, the potential FMs of components, along with their causes and effects, are identified. The relative importance (or weight) of these FMs is determined using the fuzzy simple additive weighing (FSAW) method based on how they affect the system’s goals. The causal relationships between FMs and their final weights are determined by the fuzzy cognitive maps (FCM) method and the nonlinear Hebbian learning and differential evolution (NHL-DE) algorithm. Finally, based on the final FM weights provided by the FCM, the simple additive weighing (SAW) method is used to select the optimal maintenance strategies. The results of applying the proposed approach to an operating compressor lubrication and sealing oil system demonstrate its importance and usefulness in assisting system operators to efficiently allocate the optimal maintenance strategies, considering the strong correlation between FMs and their effects on system performance while accounting for the uncertainties associated with experts’ judgments. These correlation effects have led to changes in the assigned weights of the selected FMs. Specifically, the FM related to the low output of the lube/seal oil pump, which was initially assigned a lower priority, and with the correlation effects has become the first critical FM. This shift in prioritization emphasizes the need to address this particular FM promptly. By focusing on addressing these high-priority FMs, maintenance efforts can be optimized to prevent or mitigate more severe consequences. Among the various maintenance strategies evaluated, it was determined that the combination of condition-based maintenance (CBM) and precision maintenance (PrM) yields the most favorable outcome in terms of mitigating the impact of accidental failures and undesired events on the selected system.

The effects of the aesthetics and composition of hotels’ digital photo images on online booking decisions

Photographic images help customers perceive product information more accurately and clearly. A customer’s perception of a particular product also influences their decision to purchase it. In the context of a hotel, guests evaluate digital hotel photos online during their booking decision process. While a large body of research has contributed to the understanding of how hotel online digital images shape hotel customer behaviour, little is known about the aesthetics, content, and composition of hotel images and their effects on booking decisions. In addition, previous research has routinely been criticised for having methodological limitations. These studies have routinely used surveys and experiments to explore how hotel pictures affect customer perception of the hotel and his/her booking intentions. Unlike prior studies, this research scopes a determination of the ‘selling’ properties pertinent to the hotel’s digital images placed online on the hotel-themed websites with the application of the latest technologies pursuant to visual data mining, processing and analysis. This study employed Google’s Inception v3 neural network as an AI solution for embedding and classifying hotel photo images with the further application of logistic regression and fuzzy cognitive mapping method. The results of the present study determined the hotel picture properties that may engender positive customer perception of the hotel and sequentially can precipitate hotel booking. The revealed ‘selling’ hotel image properties comprise (a) light and time of the photo shooting, (b) image colour scheme, (c) human presence, and (d) shooting angle. This study suggests a set of practical recommendations to hotel marketers to develop ‘selling’ photo images that generate hotel bookings online. The completed research is one of the first in the nascent literature stream in AI-powered computer vision solutions studies to determine the effects of photo aesthetics on online hotel bookings.

Euro-Atlantic perspective on the concept of multipolarity in the context of degradation of Western values

The concept of multipolarity implies a geopolitical situation in which several power centres balance each other. Devising solutions of international development should be implemented in parity conditions. Russian’s approach to multilateralism was fi rst articulated by former Russian prime minister Yevgeny Primakov in the late 1990s under which Russia's interaction with multilateral institutions is based on steadfast observance of international law. The article briefl y analyzes Western understanding of the concept of multipolarity in light of the deterioration in the international situation and attempts to introduce a «mental quarantine» and outright segregation in relation to the Russian world by Washington and its satellites. For the analysis, the method of cognitive mapping was used. We have to admit that Russophobia in the West is an artificially implanted trend in the spirit of the new time, proclaiming a total rejection of traditional values. It can be concluded that global shifts provoked from the outside are just as destructive and vicious an experiment with unpredictable consequences as a rethinking of the role and significance of the family, the experience of previous generations and, in general, the foundations of human existence.

Islamic finance in Kazakhstan: the view of experts

PurposeOver the past decades, Islamic finance has expanded its presence to many countries including post-Soviet region. The purpose of this paper is to empirically investigate this phenomenon in Kazakhstan by adopting qualitative sociological approach. The study also aims to provide vital information and propose recommendations for market participants to contribute to the development of Islamic finance industry in Kazakhstan.Design/methodology/approachPrimary data were gathered using the qualitative method of in-depth expert interviews with nine Islamic finance professionals representing Islamic banks, ijarah companies, funds and development institutions in Kazakhstan who occupy senior positions (directors, managers, heads of departments, etc.). Furthermore, the primary data of interviews were analyzed and processed using another qualitative method of cognitive mapping, the essence of which is to graphically display the concepts that are most often used by informants.FindingsThe study has shown that first there is a demand for Islamic finance among Kazakh business and population. At the same time, Muslims are not the only consumers of Islamic financial services; therefore, it is affordability rather than religiosity that is an important criterion for choosing Islamic finance. Second, murabaha and ijarah are the two most popular Islamic financial products in Kazakhstan, while equity-based instruments are hardly ever used. Third, Kazakhstan government policy toward Islamic finance received controversial assessments of experts: the state support is declared, but specific actions required by the market participants are not taken. Fourth, key factors that significantly limit the development of the Islamic finance market in Kazakhstan include a shortage of supply, which, in turn, is strongly associated with the second factor – limited funding of local Islamic finance institutions, the absence of insurance (or guaranteeing) system of investment accounts of the local Islamic banks, insufficient economy of scale, lack of convenient service and weak marketing policy of the existing Islamic banks and, finally, lack of educational programs.Practical implicationsThe study reveals the potential development of Islamic finance in Kazakhstan which is a rarely studied topic. The findings and recommendations of this study can be used by the regulators, market players and policymakers of Islamic finance industry in Kazakhstan, post-Soviet and other Islamic finance-oriented countries.Originality/valueThis study offers new insights on the future of Islamic finance in Kazakhstan: in long term, the development will be determined by new financial technologies – Islamic FinTech, but in short term – by Islamic windows (currently not allowed by Central Bank) that will help to significantly expand the audience, increase awareness and demand for Islamic finance among local businesses and public. The current study is original, important and up-to-date, as it uses an approach that sources primary data in the form of experts’ point of view instead of relying on literature or document analysis. It is not a mere theoretical study of the literature but an empirical investigation of the problem. Moreover, it seeks to contribute to the Islamic finance literature in the post-Soviet region, particularly from the experts’ perspective.

ОБЩЕСТВЕННОЕ УЧАСТИЕ В ДЕЯТЕЛЬНОСТИ ВЛАСТИ: ОБЩЕСТВЕННОЕ И ПАРТИСИПАТОРНОЕ БЮДЖЕТИРОВАНИЕ И СОУЧАСТВУЮЩЕЕ ПРОЕКТИРОВАНИЕ НА УРОВНЕ МУНИЦИПАЛИТЕТОВ САНКТ-ПЕТЕРБУРГА

The article discusses the global and Russian experience in the development of various approaches for the influence of society on the budgetary process. These are the participation of public organizations in the discussion of the regional or city budget (public budgeting) and the distribution of a small share of the budget by the boards of residents (participatory budgeting). The experience of the project “A budget that can be understood and influenced”, implemented by the St. Petersburg Humanitarian and Political Science Center “Strategy”, is briefly presented in the article. The foreign and domestic experience of another related approach for the civic participation in the activities of the authorities - the participatory design of urban space - is analyzed. In case of municipal formations of St. Petersburg, the authors analyze the reasons why municipal deputies choose not participatory budgeting, but participatory design while seeking ways of civic inclusion in decision-making. Expert interviews were conducted with deputies of four municipalities of St. Petersburg, and the cognitive mapping method was used to analyze the texts of the interviews. The reasons for deputies to make such a choice appeared to be the vagueness of the normative support for participatory budgeting, which increased the risk of intervention of the prosecutor's office, disagreements among deputies in municipal councils, as well as obstacles with the availability of expert support. The article discusses the problems of developing an ecosystem of public participation in the government activities.

Comprehensive risk assessment and analysis of blockchain technology implementation using fuzzy cognitive mapping

Identifying and assessing potential risks of implementing new technologies is critical for organizations to respond to them efficiently during the technology life cycle. Blockchain has been introduced as one of the emerging and disruptive technology in the field of information technology in recent years, which system developers have noted. In this study, a comprehensive set of risks have been identified and categorized based on the literature findings to identify the risks of blockchain implementation. Critical risks are defined by performing a two-stage fuzzy Delphi method based on the experts' opinions. Then, possible causal relationships between considered risks are identified and analyzed using the fuzzy cognitive mapping method. Finally, the most important risks are ranked based on the degree of prominence and the relationships between them. Industry enterprise resource planning system based on blockchain technology has been studied as a case study. The obtained results indicate that the technology's immaturity has the most impact, the high investment cost is the most impressive risk, and privacy has a critical role in risks relationships. In addition, the high investment cost has the highest priority among other risks and the privacy and issues with contract law are ranked second and third, respectively.

How to ‘measure’ ideas. Introducing the method of cognitive mapping to the domain of ideational policy studies

ABSTRACT Decades of study have greatly improved our understanding of the role of ideas in policy-making. General knowledge accumulation, however, has been slow, which may be caused by the limited availability of methods designed to study ideas. This article introduces the method of cognitive mapping (CM) and argues its value for ideational policy sciences. It starts with an overview of the methodological debate in the literature and methods in use, culminating in five requirements a method to analyze ideas should fulfil. Subsequently, the CM technique is introduced. Using a map of the Dutch Prime Minister Rutte and Central Bank Governor Knot, the article shows CM to fulfil four of the requirements as it helps to distinguish different forms of beliefs separately from their impact on policy and other relevant variables. Finally, a probability probe shows that CM-based expectations match Dutch governmental policies quite accurately, attesting to the validity of the method.

Unsociability and Psychological and School Adjustment in Chinese Children: The Moderating Effects of Peer Group Cultural Orientations

This study examined the moderating effects of cultural orientations of peer groups on the relations between unsociability and psychological and school adjustment in Chinese children. Participants included 1,092 students (527 boys, M age = 12.21 years) in the sixth grade in elementary schools. Data on individualistic and collectivistic cultural orientations, unsociability, and adjustment were obtained from multiple sources including peer nominations, teacher ratings, self-reports, and school records. Using the Social Cognitive Map method, 193 peer groups were identified. Among the results, unsociability was negatively associated with peer preference and academic achievement in groups low on individualistic orientation but not in groups high on individualistic orientation. Unsociability was also negatively associated with peer preference more strongly in groups with higher scores of collectivistic orientation. The results suggested that, in general, unsociable children performed better in social and academical areas in more individualistically oriented groups and less collectivistically oriented groups. The cultural context of peer groups may play a significant role in shaping social and school adjustment of unsociable children.

A new lens to the understanding and reduction of household food waste: A fuzzy cognitive map approach

Food waste generated at the household level is known to be the main contributor to total food waste, particularly in developed regions. Reducing household food waste (HFW), however, is an extremely compelling task as there are many complex and interacting factors behind the HFW behavior. This study aims to address the factors behind the complexity by applying the Fuzzy Cognitive Map (FCM) method. FCM represents a new approach that enables the use of multiple resources, consideration of outnumbered factors, handling of linguistic ambiguities, and scenario analysis. Through FCM, this study aims to develop a more complete model of the complex HFW drivers' system and identify the most influential HFW drivers addressing which is key while designing HFW-reducing interventions. The current study employs a three-stage methodology that utilizes content analysis of scholarly published academic articles and exploits expert opinion to construct an FCM. In the final stage, through scenario analysis, the study tests and reports the effects of each HFW driver and evaluates them based on their potential to reduce HFW. The findings of this research reveal that system concepts A12 (fail to consume what is in the fridge), A2 (excessive purchasing), and A9 (cooking and serving too much) are the most influential practices concerning HFW. While the study suggests innovative approaches that would enable people not to give up their normality to cope with A12 , tackling A9 requires challenging the normality, and addressing A2 requires changing food store-related infrastructural elements. Moreover, the study draws attention to the concept C2 (food safety and health concerns) due to its potential to be a disincentive to FW reduction efforts as well as to the concept G1 (lack of knowledge/skill/awareness) which requires special attention to maximize its potential. Finally, the paper offers specific recommendations to practitioners and policymakers and provides future research directions.

Analyzing critical barriers of smart energy city in Turkey based on two-dimensional uncertainty by hesitant z-fuzzy linguistic terms

Successful implementation of smart energy cities in Turkey is essential to optimize urban energy systems. Turkey faces several barriers on its way to establishing smart energy cities. Since assessment of these barriers must be handled by considering many different perspectives, assessment of the critical barriers for SEC can be considered as a multi-criteria decision-making (MCDM) problem. This study aims to identify possible critical barriers hindering Turkey from becoming an SEC and prioritize these barriers based on an integrated MCDM methodology. This methodology consists of fuzzy Decision Making Trail and Evaluating Laboratory (DEMATEL) and cognitive mapping methods. The integrated methodology has been constructed with hesitant fuzzy Z-numbers, which allows not only to state the impreciseness of the evaluations but also to consider the hesitancy of the decision-makers to evaluate barriers concerning SEC implementation in Turkey. While the relations between the barriers have been determined via the hesitant fuzzy Z-DEMATEL method, their weights have been obtained through the hesitant fuzzy Z-cognitive mapping method. For Turkey, policy, economic, and social barriers are determined as the essential main barriers, respectively. Besides, the following five sub-barriers: the lack of successful past experiences/projects, social/political conflicts, inadequate regulatory framework, lack of regulatory norms, policies/directions, the lack of technical knowledge among planners, and information on new technology are deserved to be more attention since they have high weights. The research should help policymakers and businesses better understand the barriers to smart energy city projects in order to improve effective action and policy interventions that lead to more successful projects.