The Synergy of Smart Campus Development with Smart City Policies and the New European Bauhaus with Implications for Educational Efficiency

Abstract

This empirical investigation explores the complex interdependencies between the concept of the Smart University Campus and the broader ecosystem of Smart City policies, with a particular focus on the New European Bauhaus initiative as a catalyst for educational transformation. The study examines how university campuses can evolve into paradigmatic models of innovation, sustainability, and inclusion through the strategic integration of emerging technologies, circular bioeconomy principles, and holistic ecological strategies. A comprehensive case study, grounded in rigorous quantitative analysis, including Principal Component Analysis (PCA), Importance-Performance Analysis (IPA), and Cluster Analysis (CA), based on questionnaires administered to a sample of 245 high school and university students—primarily from the academic community of the “King Mihai I” University of Life Sciences in Timișoara (USVT)—provides empirical insights into perceptions and expectations regarding the Smart Campus ecosystem and its core components: Smart Learning, Smart Living, Smart Safety and Security, Smart Socialization and Smart Health. The distinctive contribution of this research lies in its empirical demonstration that the strategic alignment between university campuses and Smart City initiatives, guided by the principles of the New European Bauhaus, can enhance educational efficiency by creating integrated learning ecosystems that simultaneously address academic needs, sustainability imperatives, and goals of sustainable urban development.

1. Introduction

The contemporary global landscape is marked by exponential urbanisation and complex systemic challenges, including anthropogenic climate change, the accelerated depletion of finite natural resources, and the pressing imperative of sustainable development. Within this dynamic and multifaceted context, urban centres have emerged as epicentres of technological innovation and socio-economic transformation, and the concept of the Smart City has gained strategic prominence on the contemporary political and academic agenda. A Smart City, according to various conceptual frameworks and academic taxonomies, is an integrated urban ecosystem that leverages advanced information and communication technologies (ICT), big-data analytics, and innovative solutions to optimise residents’ quality of life, enhance the functioning of urban systems, and ensure long-term sustainability [1,2,3]. This holistic perspective on urban development transcends traditional physical infrastructure, embedding essential dimensions such as participatory governance, smart mobility, environmental management, the circular economy, and—fundamentally—citizens’ well-being and social inclusion [4,5,6,7,8,9,10].

Concomitant with the evolution and maturation of the Smart City concept, higher-education institutions have embarked on a comprehensive reassessment of their role and operations within this new intelligent urban ecosystem. Thus, the concept of the Smart University Campus has emerged and consolidated, representing a natural, context-specific transposition of Smart City principles to the academic environment [11,12,13,14,15,16]. A Smart Campus constitutes an integrated educational ecosystem that incorporates cutting-edge technologies such as the Internet of Things (IoT), artificial intelligence (AI), cloud computing, advanced data analytics, and cyber-physical systems to create a more efficient, interactive, secure, and ecologically sustainable learning environment [14,17,18,19]. Its primary objective is to optimise the learning experience of students, streamline institutional resource management, and stimulate research and innovation in fields with significant societal impact [8,20,21,22,23,24,25,26,27].

This study aims to (1) Empirically identify the key dimensions of a Smart Campus as perceived by students; (2) Evaluate the importance and performance of these dimensions to identify strategic priorities for development, in line with NEB principles; and (3) Explore how these stakeholder perceptions align with the strategic goals of the Timișoara Smart City initiative.

The Research Hypotheses can be

H1: 

Smart campus features aligned with NEB principles significantly enhance perceived educational efficiency.

H2: 

Different user segments prioritize different aspects of smart campus development.

H3: 

Integration with smart city policies amplifies the educational benefits of smart campus initiatives.

Throughout this paper, ‘educational efficiency’ is conceptualized not as a single, objective metric (e.g., graduation rates), but as a holistic, user-perceived construct. It represents the degree to which the campus environment—encompassing its learning infrastructure, living conditions, safety, and social fabric—is perceived by its users to support and enhance the learning process. This approach is aligned with the human-centric principles of the New European Bauhaus and allows us to assess efficiency from the perspective of the primary beneficiaries. Our analysis, therefore, seeks to identify which Smart Campus features have the greatest potential to improve this perceived educational efficiency. We now can also define educational efficiency as the optimization of learning outcomes, student satisfaction, resource utilization, and institutional performance through technology-enhanced educational environments that support effective knowledge acquisition, skill development, and academic achievement. A novel and essential element in this complex equation is the New European Bauhaus (NEB) initiative, launched by the European Commission as an integral component of the European Green Deal. NEB functions as a conceptual and operational bridge between the European Green Deal and our everyday living spaces, promoting a holistic, transdisciplinary vision that harmonises ecological sustainability, design aesthetics, and social inclusion [28,29,30,31]. This initiative encourages a fundamental rethinking of architectural design, urban planning, and our interaction with the built environment, seeking to create spaces that are more beautiful, ecologically sustainable, and accessible to all social groups. Transposing NEB principles into the specific context of university campuses can transform these institutions into genuine living laboratories for experimenting with, and demonstrating, a more sustainable future—integrating innovative design solutions, advanced eco-friendly materials, and circular-bioeconomy practices [31,32].

This paper aims to conduct an in-depth analysis of the conceptual intersections and operational synergies among three fundamental concepts: the Smart University Campus, the Smart City, and the New European Bauhaus. The central objective of the investigation is to provide empirical evidence of how the strategic alignment of university campuses with Smart City policies and NEB principles can decisively enhance educational efficiency while promoting the sustainable development of urban communities [6,33,34,35,36,37,38,39]. The study will explore theoretical and practical considerations relating to the definition and evolution of these concepts, propose concrete action directions focused on green solutions and circular-bioeconomy principles, and present an in-depth empirical case study grounded in advanced statistical methodologies [40,41,42,43,44,45]. The case study, based on a rigorous quantitative investigation via questionnaires administered to highschool students, students, from the west region of Romania, in the jurisdiction of the “King Mihai I” University of Life Sciences in Timișoara (USVT), will provide empirical insight into local perceptions and the potential for institutional adaptation. In addition, the Smart City Strategy of the Municipality of Timișoara will be examined in detail to identify concrete opportunities for synergy and collaboration between the university and the local administration. Finally, the paper will formulate specific strategic recommendations for USVT Timișoara and highlight the theoretical and practical contributions of this research to the fields of higher education and sustainable urban development. The research methodology combines quantitative analysis through advanced statistical techniques, including Principal Component Analysis (PCA), Importance–Performance Analysis (IPA), and cluster analysis, in order to provide a comprehensive and nuanced understanding of stakeholders’ perceptions and priorities concerning smart-campus development.

The significance of this research lies in its potential to inform policy-making and strategic planning processes for both higher education institutions and municipal authorities, contributing to the broader academic and practical discourse on sustainable urban development and the strategic role of higher education in achieving the United Nations Sustainable Development Goals—particularly SDG 4 (Quality Education) and SDG 11 (Sustainable Cities and Communities) [46,47,48,49].

2. Theoretical Foundation: Systematic Literature Review

2.1. The Smart University Campus: A Paradigmatic Extension of the Smart City Concept

The concept of the Smart City has evolved rapidly over the past few decades, progressing from a futuristic vision to a concrete reality in numerous urban centres worldwide. At its core lies the idea of leveraging technology and innovation to enhance residents’ quality of life, optimise resource management, and foster sustainable urban development [50,51]. A Smart City is distinguished by its interconnectivity, efficiency, and capacity to respond dynamically to citizens’ needs, integrating intelligent solutions across domains such as transport, energy, governance, health, and education [52,53,54,55].

Within this context, university campuses—by virtue of being micro-cities with dense populations and complex infrastructures—provide an ideal environment for applying and advancing Smart City principles. Consequently, the concept of the Smart University Campus has emerged, adapting and extending the Smart City vision to the specific characteristics of the academic setting (

Table 1. Basic Characteristics of a Smart Campus.

Component	Description	Key Technologies	Benefits
Smart Infrastructure	Utilization of sensors, IoT, and communication networks for efficient monitoring and management	IoT sensors, smart meters, adaptive lighting systems, EV charging stations	Energy efficiency, resource optimization, reduced operational costs
Advanced Education and Research	Integration of digital technologies in the teaching process and creation of environments conducive to interdisciplinary research	Smart classrooms, e-learning platforms, virtual laboratories, collaborative tools	Enhanced learning experience, improved research capabilities, increased creativity
Safety and Security	Implementation of advanced surveillance systems, biometric access control, and Smart alert systems	Video surveillance, biometric access, air quality monitoring, emergency response systems	Secure environment, health protection, rapid emergency response
Sustainability and Energy Efficiency	Adoption of ecological practices and renewable energy solutions	Solar panels, smart waste management, carbon footprint monitoring, environmental awareness programs	Reduced environmental impact, cost savings, sustainability model for community
Connectivity and Interaction	Ensuring ubiquitous digital connectivity and development of platforms facilitating communication	High-speed Wi-Fi, 5G networks, mobile applications, collaboration platforms	Enhanced communication, improved collaboration, real-time information access

). A Smart Campus is not merely a space outfitted with advanced technology; it is an intelligent ecosystem that facilitates learning, research, and innovation while simultaneously promoting sustainability and the well-being of the academic community [56,57,58,59,60,61].

Fundamentally, a Smart Campus functions as a dynamic and experimental laboratory for innovation, where the concepts and technologies developed can be tested, validated and refined before being scaled up and implemented city-wide. This strategic interconnection between the campus and the urban environment is fundamental for harmonious and sustainable urban development [62,63].

2.2. New European Bauhaus: The Convergence of Aesthetics, Sustainability, and Inclusion

The New European Bauhaus (NEB) initiative, launched by the European Commission in 2020, constitutes an essential strategic component of the European Green Deal. Its fundamental objective is to transform abstract sustainability aspirations into concrete, tangible, and palpable experiences for European citizens. NEB is not merely a funding instrument or a sectoral policy but a creative and transdisciplinary movement aiming to harmoniously unite art, culture, science, and technology to fundamentally redefine how we live, work, and interact with our environment [28,55].

The three fundamental and interdependent values of the New European Bauhaus are

• Ecological Sustainability: Actively promoting innovative ecological solutions, renewable and biodegradable materials, advanced energy efficiency, and circular bioeconomy practices. This includes significantly reducing the carbon footprint, intelligently conserving natural resources, and protecting ecosystem biodiversity. NEB encourages design that respects planetary boundaries and actively contributes to a greener and more resilient future [61].
• Aesthetics and Design Quality: Creating spaces and products that are not only functional and sustainable but also beautiful, inspiring, and visually and sensorially pleasing. NEB emphasizes the crucial importance of aesthetic quality in both the built and natural environments, recognizing that beauty can inspire and motivate people to adopt a more sustainable and conscious lifestyle [25].
• Social Inclusion: Ensuring universal accessibility and equity in design and implementation, so that developed solutions benefit all members of society, regardless of age, physical or cognitive abilities, or socio-economic status. NEB promotes active civic participation and collaborative co-creation, ensuring diverse voices are heard and integrated into the participatory design process [26,31].
• NEB focuses on three main strategic action pillars:
• Places and Spaces: Fundamentally rethinking how buildings and public spaces are designed and constructed.
• Products and Processes: Developing innovative products and services that are sustainable throughout their entire lifecycle.
• Culture and Education: Fostering a new mindset and the necessary skills for the transition to a more sustainable society [24,25,26].

Integrating NEB principles into the development of university campuses can transform these institutions into the vanguard of the transition towards a more sustainable and equitable future. Campuses can become paradigmatic examples of best practice in biophilic design, in the use of advanced ecological materials, and in the creation of spaces that inspire creativity and holistic well-being [46].

2.3. The Synergy Between Smart Campus, Smart City, and New European Bauhaus

The intersection of the Smart Campus, Smart City, and New European Bauhaus offers a solid and coherent conceptual framework for developing integrated and synergistic solutions. Each of these concepts, while distinct in its specificity, contributes to a common vision of urban and educational development centered on sustainability, innovation, and quality of life [49].

• The Smart Campus as a Laboratory for the Smart City: University campuses can serve as controlled and experimental environments for the rigorous testing of Smart City-specific technologies and solutions. For example, intelligent energy management systems or sustainable mobility solutions implemented within a campus can later be validated, optimized, and scaled to the entire city, after demonstrating their efficiency and positive impact [59]. This approach facilitates faster, more efficient, and safer implementation of urban innovations.
• NEB as an Aesthetic and Ethical Guide for Development: NEB principles can guide and inform the design and development of both smart campuses and smart cities. By harmoniously integrating aesthetics, sustainability, and inclusion, Smart Campus and Smart City projects can transcend mere technological functionality, transforming into spaces that inspire and respond to deep and diverse human needs [28].
• Education as a Driver of Transformation: Higher education institutions, through their fundamental role in training future generations and generating new knowledge, are essential in promoting and disseminating the values of the Smart City and NEB. Academic programs can integrate concepts of sustainability, circular design, and intelligent technologies, preparing students to become active agents of change in society [47].
• Circular Bioeconomy and Green Solutions: The Smart City, Smart Campus, and NEB all converge in promoting the circular bioeconomy and innovative green solutions. This involves transitioning from a linear model of production and consumption to a circular one, where resources are reused, recycled, and maximized, minimizing waste and ecological impact [48].

In conclusion, the synergy between the Smart Campus, Smart City, and New European Bauhaus creates a holistic and integrated framework for developing urban and academic environments that are not only technologically intelligent but also ecologically sustainable, aesthetically designed, and socially inclusive. This integrated and multidimensional approach is essential for building a better and more equitable future for all members of society.

2.4. Conceptual Framework of the USVT Smart Campus

To contextualize the application of Smart Campus principles at the “King Mihai I” University of Life Sciences in Timișoara (USVT), a specific and adapted conceptual framework has been developed. This framework integrates the key dimensions of a smart campus, tailored to the institution’s vision, mission, and strategic objectives (

Table 2. USVT Smart Campus Integrated Conceptual Framework.

Dimension	Key Components	Technologies	Relevance
Learning & Research	Digital learning infrastructure, innovative learning methods, advanced educational resources	Smart classrooms, e-learning platforms, VR/AR courses, SMART labs	Essential for experiential learning and educational innovation
Service Management	Optimization of services offered to students and staff through intelligent solutions	Resource management systems, accessibility tools, digital platforms	Enhanced user experience and operational efficiency
Governance & Security	Efficient administration and campus safety through digital and physical security measures	Cybersecurity systems, video surveillance, access control, alert systems	Critical for data protection and community safety
Life & Socializing	Comfortable, safe, and interactive living and socializing environment	Smart accommodation facilities, green spaces, digital connectivity platforms	Essential for student well-being and community building
Environment & Bioeconomy	Sustainability and natural resource management in campus	Renewable energy systems, smart waste management, water management, and native species integration	Fundamental for environmental sustainability and circular economy

). It serves as a methodological guide for the strategic and operational development of USVT as a benchmark smart campus, emphasizing the synergy between learning, research, service management, smart governance, cybersecurity, socialization, environment, and bioeconomy, as well as IoT and AI tools.

The conceptual framework of the USVT Smart Campus is structured around the following interconnected and interdependent dimensions:

NEB principles do not act as independent variables, but as a guiding philosophy. For example, the principle of ‘inclusion’ is not measured by a single question, but is manifested in characteristics such as ‘accessibility for students with disabilities’ (Smart Living) and ‘cybersecurity systems’ (Smart Safety) that ensure fair and safe access for all. Similarly, ‘sustainability’ is operationalized through ‘energy management systems’ and ‘green spaces’. This framework implies that by integrating NEB values into the design of the tangible features of smart campuses, institutions can create an environment that users perceive as more conducive to learning, thereby increasing educational effectiveness.”

Conceptual diagram logic:

• Input: New European Bauhaus Principles (Sustainability, Aesthetics, Inclusivity).
• Mechanism/Process: These principles inform and shape the development of the five Smart Campus Dimensions (Learning, Living, Safe, Safe, Socializing, Healthy).
• Outcome: Successful implementation of these dimensions leads to improvements in Per-perceived Educational Effectiveness and contributes to Sustainable Urban Development (through synergy with Smart City policies).

This conceptual framework provides a detailed and operational roadmap for the transformation of USVT into a benchmark smart campus, ensuring an integrated and coherent approach that addresses the diverse needs of the academic community and contributes to sustainability and innovation objectives at the local, regional, and national levels.

3. Research Methodology and Analytical Instruments

3.1. Research Design and Methodological Approach

To systematically and rigorously assess perceptions and expectations regarding a smart university campus, a comprehensive case study was designed and implemented at the “King Mihai I” University of Life Sciences in Timișoara (USVT). This institution, with a solid academic tradition and a strong strategic orientation toward innovation in life sciences, represents a paradigmatic and representative example for analyzing the potential for transformation into a Smart Campus.

The study methodology involved a rigorous quantitative approach through data collection via structured questionnaires administered to a diverse and representative sample of respondents, primarily including high school students and university students from the West Region of Romania, with a particular focus on the USVT academic community. The study was conceived as descriptive and exploratory research, with the primary goal of identifying and characterizing the fundamental dimensions of perception concerning the Smart Campus concept and the importance attributed to its various constituent components. The research approach combined quantitative methods with advanced statistical analysis to provide a comprehensive, nuanced, and scientifically valid understanding of stakeholder perceptions and priorities.

The original data presented in the study are openly available at the University of Life Sciences “King Mihai I” from Timisoara. The questionnaire instrument used for data collection is available from the corresponding author upon reasonable request.

The main theoretical concepts and empirical findings from the analysis, especially those related to the Smart Campus dimensions (e.g., Smart Learning, Smart Living, Smart Safety and Security, Smart Socialization, Smart Health) and the core principles of the new European Bauhaus (sustainability, aesthetics, inclusiveness), were systematically translated into measurable elements. For example, the conceptualization of ‘smart learning’ was derived from studies on technology-enhanced learning environments (Dong et al. (2020) [2], Silva-da-Nóbrega et al. (2022) [6], Martins et al. (2021) [54]), which led to questionnaire items assessing the perceived effectiveness of digital resources and interactive platforms. In terms of the Smart Living concept, it presents characteristics related to campus living, accommodation, resource management and sustainability (Villegas-Ch et al. (2019) [8], Zhao et al. (2021) [28]). Regarding the “Smart Safety & Security” part, the concept describes characteristics related to physical and cyber security, access control and emergency response (Hussain (2024) [56], Kolotouchkina et al. (2024) [57]). Regarding the concept of “Smart Socialization”, it exhibits characteristics that foster community interaction, collaboration and well-being (Polin et al. (2023) [36], Florida (2002) [47]). Similarly, the “Smart Health” dimension incorporated aspects highlighted in the literature on campus well-being and mental health support systems (Dascalu et al. (2023) [19]). This direct link ensures that the questionnaire is theoretically grounded and able to capture the nuances of the relationships explored in this study.

3.2. Data Collection Instrument and Administration Procedure

The research instrument was designed as a structured and validated questionnaire, organized into several thematic sections, addressing fundamental aspects related to

• Demographic Profile: Age, gender, academic status (high school student, university student), year of study/tenure at the institution, and geographic origin.
• Conceptual Familiarity: Level of understanding and prior knowledge about smart campuses and associated technologies.
• Perception of Component Importance: A series of structured statements regarding various functionalities and services specific to a smart campus, evaluated on a Likert scale (1 = Unimportant, 2 = Important, 3 = Very Important).
• Expectations and Perceived Benefits: Evaluation of the potential benefits of implementing a Smart Campus and identification of specific expectations.

The methodology of the study involved a rigorous quantitative approach by collecting data through structured questionnaires administered to a diverse and representative sample of respondents (n = 245), including high school and university students from the Western Region of Romania, with a particular focus on the academic community of USVT.

The sample was selected using a non-probabilistic, convenience sampling method, stratified to ensure representation from high school students, undergraduate and graduate students within the USVT community and the broader western region of Romania.

We opted for an implicit measurement of the NEB principles (Sustainability, Aesthetics, Inclusion) rather than asking respondents to rate these abstract concepts directly. This approach is grounded in the belief that the impact of these principles is best captured through their tangible application. For example, ‘Inclusion’ is assessed via perceptions of ‘accessibility for persons with disabilities’ and ‘campus safety,’ while ‘Sustainability’ is assessed via ‘selective waste collection’ and ‘energy management.’ This allows for a more grounded and less abstract evaluation of how the NEB philosophy translates into the lived experience of the campus community.

The questionnaires were administered online via secure digital platforms, ensuring complete anonymity and confidentiality of responses in accordance with international ethical standards. The sample was selected using a non-probabilistic, stratified convenience method, considering the accessibility and availability of respondents from within the USVT community and high school students in the western region.

A significant number of valid responses were collected (n = 245), allowing for robust and representative statistical data analysis, with a margin of error of ±6.2% at a 95% confidence level.

3.2.1. Demographic Profile of Respondents

In order to contextualize the research, it is essential to briefly introduce the environment in which the study was conducted. Timișoara, located in the west of Romania, is a leading economic, cultural and educational centre, recognized for its technological and multicultural dynamism. Its designation as European Capital of Culture in 2023 underlines its openness to innovation and European collaboration. Moreover, the municipality has adopted an ambitious Smart City strategy, focused on digitalization, sustainability and improving the quality of life of citizens.1 In this vibrant urban context, the University of Life Sciences “King Michael I” of Timișoara (USVT) is a higher education institution with a long tradition and a distinct specialization in the fields of life sciences, agriculture, bioeconomy and environmental protection. Its unique profile makes the USVT a particularly relevant case study for analyzing the synergies between technology, sustainability and education, in alignment with the principles of the European New Bauhaus and local smart development policies.

In our study, the demographic composition of the respondent sample is crucial for understanding the context and external validity of the collected perceptions. The study included a representative diversity of participants from the USVT community and the western region, ensuring adequate representation of different demographic and academic segments, as shown in Figure 1.

The demographic analysis reveals important characteristics of the sample that inform the interpretation of the results. The majority of respondents (73.1%) come from urban areas, while 26.9% are from rural areas. This distribution is representative of the student population of a university located in a major urban center, which attracts students from both urban and rural environments.

Regarding the type of education completed, there is a predominance of theoretical high school graduates (over 50%), followed by those from general schools and technological schools. A smaller percentage comes from vocational schools. This structure reflects USVT’s academic profile, which primarily attracts students with a strong theoretical background in natural sciences. The majority of respondents fall into the 15–19 age group (69.4%), indicating significant participation from high school students and undergraduate students in their early years of study. The remaining 30.6% fall into the “Other” category, which includes students, master’s students, and doctoral students.

3.2.2. Customized Evaluation Framework for the USVT Smart Campus

To effectively evaluate and prioritize Smart Campus development initiatives at USVT, a customized and scientifically validated evaluation framework was developed, based on Importance-Performance Analysis (IPA). This methodological framework allows for the precise identification of those elements of the smart campus that are perceived as being of high strategic importance [2,34,36,37] by the academic community, but whose current performance falls below desired expectations and standards.

The IPA framework divides campus elements into four strategic quadrants, based on importance and performance scores:

• Quadrant I—“Maintain Performance” (High Importance, High Performance)
• Quadrant II—“Concentrate Efforts” (High Importance, Low Performance)
• Quadrant III—“Low Priority” (Low Importance, Low Performance)
• Quadrant IV—“Possible Overinvestment” (Low Importance, High Performance)

This customized evaluation framework provides USVT with a robust strategic tool to direct limited resources towards initiatives that will generate the greatest impact and best meet the expectations of the academic community, ensuring efficient and relevant Smart Campus development, as illustrated in Figure 2.

3.3. Advanced Statistical Analysis Methods

The collected data underwent comprehensive statistical analysis, utilizing advanced quantitative methods to extract relevant information about respondents’ perceptions. The analysis included descriptive statistics: calculating means, standard deviations, and frequency distributions for each questionnaire item, providing an overview of the perceived importance of different Smart Campus components.

The statistical analysis was conducted using IBM SPSS Statistics (version 26) and R (version 4.1.1), ensuring methodological rigor and reproducibility. Analyses in R were performed using standard packages such as ggplot2 (v3.3.5), dplyr (v1.0.7), and psych (v2.1.9).The analytical strategy is structured into three complementary levels: descriptive analysis, multivariate analysis, and segmentation analysis.

• Principal Component Analysis (PCA): PCA was employed as a data reduction technique to identify the underlying latent structure of stakeholder perceptions. Given the large number of questionnaire items, PCA is essential for distilling these into a smaller set of coherent, interpretable dimensions (e.g., the five pillars), which forms the basis for subsequent analysis.
• Importance-Performance Analysis (IPA): IPA was selected as the core analytical framework because of its unique capacity to translate user perceptions into strategic priorities. As established by Martilla and James, this diagnostic tool is ideal for identifying areas where an institution is underperforming on attributes of high importance to its stakeholders, thus guiding resource allocation for maximum impact [63]. This aligns perfectly with our objective to provide actionable recommendations for USVT.
• Importance-Performance Map Analysis (IPMA): To further refine our strategic recommendations, we employed IPMA. While IPA identifies priorities, IPMA extends this by mapping the influence of each attribute on a key outcome—in our case, overall satisfaction. This is not intended for causal inference in the way Structural Equation Modeling (SEM) would be, but rather as a managerial decision-making tool to prioritize improvements on features that are strong predictors of user satisfaction. This choice reflects the dual academic and practical nature of our research, which aims not only to explore relationships but also to provide a strategic roadmap for institutional development.
• Cluster analysis is applied to identify homogeneous segments of participants based on their response profiles, allowing for an understanding of the diversity of perceptions and the development of differentiated implementation strategies. This segmentation is essential to ensure that the benefits of the synergy are distributed equitably, in accordance with the New European Bauhaus’s principle of inclusion.

3.4. Validity and Reliability Considerations

The validity and reliability of the research instrument were ensured through several rigorous methodological strategies. Content validity was assessed through review by experts in the field of smart campuses and sustainable urban development, ensuring that the questionnaire items adequately reflected the investigated concepts.

External validity is supported by the sample characteristics, which are representative of the target population, and by the data collection methodology, which minimizes selection and response biases. These measures ensure that the results can be generalized to the broader population of high school students in the West Region and USVT university students.

3.5. Ethical Considerations and Data Protection

The research was conducted in accordance with international ethical standards for research involving human participants, respecting the fundamental principles of autonomy, beneficence, and justice. All participants were transparently informed about the study’s purpose, the methodology used, and the use of collected data, providing informed consent for participation. Anonymity and confidentiality of data were guaranteed throughout the study, with data stored securely and accessible only to the authorized research team. The research protocol was reviewed and approved by the USVT ethics committee, ensuring compliance with national and European regulations regarding personal data protection (GDPR).

4. Results

4.1. Perceived Importance of Smart Campus Elements: Detailed Analysis

Figure 3 shows a clear hierarchy of the components of the Smart Campus concept, according to the number of respondents prioritizing them. It can be seen that Smart Learning is by far the most important dimension, being selected by 191 respondents (78.0%). The figure illustrates a major focus of interest on modernization and technologization of the learning experience, with social life, comfort, safety and health issues being perceived as secondary, although still relevant. This underlines the fact that, in the perception of the academic community, functionalities directly related to the educational process (courses, laboratories, access to materials) are essential.

For a more granular understanding of perceptions, we analyzed the importance of each category of smart campus elements as rated by respondents. This section details the results for each of the five main components: Smart Learning, Smart Living, Smart Safety and Security, Smart Socializing, and Smart Health.

Figure 4 provides a comparative overview of the five core dimensions, revealing the relative importance attributed to each. In order to understand the specific factors behind these high-level perceptions, we now look in more detail at the individual items within each dimension (Figure 5, Figure 6, Figure 7, Figure 8 and Figure 9).

4.1.1. Smart Learning: Prioritizing Digital Educational Infrastructure

The Smart Learning component, as detailed in Figure 5, reveals a clear and strong consensus regarding the prioritization of digital and intelligent educational infrastructure. Elements such as SMART Labs, smart classrooms, and access to a virtual library are considered “Very Important” by a vast majority of respondents (202, 215, and 187 responses, respectively). This overwhelming support, indicated by the dominant green bars for most items, underscores a profound awareness of technology’s essential role in modernizing the educational process and enhancing learning efficiency.

Elements such as access to online educational materials, interactive digital learning platforms, digital technology for assessment and adaptive learning, experiential and collaborative learning methods, as well as SMART laboratories equipped with Industry 4.0 technologies, are considered essential by the respondents. This prioritization reflects a profound awareness of the fundamental role of technology in modernizing the educational process and adapting to the demands of a knowledge-based and innovation-driven society. The high mean values and relatively low standard deviations indicate a strong consensus among respondents.

However, a notable exception to this consensus is the item ‘Virtual attendance at courses’, which a significant majority (147 respondents) rated as ‘not important’. This overwhelmingly negative perception creates a bimodal distribution of opinions within the Learning category and likely reflects a collective dissatisfaction with the mandatory online learning experiences during the recent COVID-19 pandemic, which were often marked by technical problems and a lack of face-to-face interaction. This finding is critical because it suggests that, to optimize educational effectiveness, technology should enhance the physical camp experience, in line with the NEB’s emphasis on quality physical spaces, rather than simply replace it.

4.1.2. Smart Living: Sustainability and Accessibility as Priorities

The responses for Smart Living elements, shown in Figure 6, demonstrate robust support for solutions that enhance sustainability and accessibility on campus. Specifically, Accessibility (disabilities)” and “Smart waste collection” received the highest ratings, with 93% and 90% of respondents, respectively, deeming them “Important” or “Very Important”. This strong consensus directly reflects two core pillars of the New European Bauhaus: social inclusion (ensuring the campus is usable for all) and sustainability (promoting a circular economy).

Respondents attribute high importance to solutions aimed at energy efficiency, intelligent resource management (water, waste), and, most notably, accessibility for individuals with disabilities. This reflects a heightened awareness of social responsibility and the need to create an inclusive environment for all members of the university community. The high value placed on these features indicates that the academic community views a smart campus not just as a technologically advanced space, but as a socially and environmentally responsible one. While there is broad support across all items, the moderate variance in perceptions for elements like “Ultramodern dorm rooms” suggests that while desirable, functional priorities related to sustainability and inclusion are perceived as more critical for the overall quality of campus life

4.1.3. Smart Safety & Security: Balancing Protection and Privacy

Smart Safety & Security measures receive high importance ratings, particularly network-level and biometric protections. Respondents consider systems that ensure the physical and cybersecurity of the campus to be essential.

As illustrated in the diverging bar chart in Figure 7, elements of Smart Safety & Security are assigned high importance by the academic community. Network-level protections (“Network detects attacks”) and physical security measures (“Intelligent video surveillance”) are considered “Very Important” by over 220 respondents, signaling a clear demand for a secure and protected campus environment.

Measures such as biometric access, intelligent video surveillance, and systems for detecting and blocking cyberattacks are perceived as crucial for creating a safe and protected environment. However, a small group of respondents (approximately 15–20%) exhibit a more critical attitude towards high-tech surveillance, possibly due to concerns regarding privacy and personal data protection.

Interestingly, the data also reveals a nuanced perspective. Technologies perceived as more invasive, such as “Biometric access (retina),” show greater variance, with 70 respondents rating them as merely “Important” and a minority (35) rating them as “Unimportant”. This suggests an underlying tension between the desire for security and concerns over privacy and data protection. This finding highlights the need for a balanced approach, aligning with the NEB’s inclusive principles, which demand that solutions must not only be effective but also make all community members feel respected and comfortable.

4.1.4. Smart Socialization: Complementarity to Academic Needs

The Smart Socialization characteristics, presented in the lollipop chart in Figure 8, exhibit a more distributed perception of importance, with fewer elements rated as unequivocally essential compared to other categories. The weighted mean importance scores range from a high of 2.88 for “Green spaces for picnic/relax” to a low of 2.47 for “Interactive outdoor cinema & festivals”.

This may reflect the view that social platforms and virtual events are secondary to academic and infrastructural needs. Nevertheless, the importance of relaxation areas and partnerships is well-recognized. Unlike in other categories, the importance of Smart socialization elements is not unanimous. Physical spaces, such as green areas for picnics and relaxation, appear to be more valued than digital social platforms or virtual events.

This pattern suggests that respondents view socialization tools as complementary enhancements rather than core necessities for their academic life. It is particularly telling that physical spaces for relaxation and community gathering are valued more highly than digital platforms or organized virtual events. This preference for tangible, quality social spaces strongly supports the NEB’s focus on creating beautiful and inclusive environments that foster a sense of community and well-being, which in turn supports educational goals indirectly.

4.1.5. Smart Health: Openness to Medical Technologies

The survey results for Smart Health, detailed in the pie charts in Figure 9, show strong overall support for integrating technology into campus health services. Solutions like a “Sports complex (digital training)” and “Smart medical office (biometrics)” are rated “Very Important” by 92% and 87% of respondents, respectively. This indicates a high level of trust and openness toward technologies that improve physical health and access to medical care.

However, the data reveals a significant polarization of opinion regarding mental health technology. The “AI online counselor” received the most varied feedback: while 51% considered it “Very Important,” a substantial 33% rated it as only “Important,” and 16% deemed it “Unimportant”. This high variance points to a significant reluctance or skepticism about replacing human interaction with AI for sensitive psychological support. For the university, this means that while integrating health technologies is desired, special care must be taken with mental health solutions to ensure they are perceived as trustworthy, ethical, and genuinely supportive of student well-being, fully embodying the NEB’s principle of inclusion.

As shown in Figure 9, while digital sports training and online consultations are highly valued, the ‘AI counseling system’ exhibits significant variance. This suggests a polarization of opinion, likely reflecting a segment of the community that is hesitant about entrusting mental health support to AI, a critical consideration for implementation.

4.1.6. Interest in University Studies and Smart Campus Living

In the questionnaire, participants were asked to rate Smart Campus indicators on a scale of 1 to 5. The results are presented in the table below:

This chapter explores in detail the perceptions of high school and university students in the USVT Timișoara area regarding various characteristics of a smart campus, utilizing importance and performance scores to identify strategic priorities. The data presented in

Table 3. Importance and Performance Scores of Smart Campus Features.

Feature	Mean Importance	Mean Performance
Smart-classroom lighting control	4.90	2.70
Automated temperature & climate management systems	4.85	1.00
Real-time occupancy and space utilization monitoring	4.10	2.30
Smart security & access control (e.g., smart ID)	4.50	3.30
Integrated campus mobile app (scheduling, navigation)	4.30	2.60
Smart waste management (sensor-based bins)	3.90	3.80
Energy usage dashboards for students & staff	4.20	2.20
Virtual/augmented reality learning environments	4.60	2.00
Smart parking guidance & EV charging stations	3.80	1.20
High-speed campus-wide Wi-Fi connectivity	4.80	4.00

, “Importance and Performance Scores of Smart Campus Features,” forms the basis for the Importance-Performance Analysis (IPA) Matrix.

From Table 3, we observe a series of characteristics with very high perceived importance (mean scores above 4.5), but with significantly lower current (or perceived) performance. These represent critical areas where intervention is urgently needed to align expectations with reality:

• Smart-classroom lighting control: With an importance score of 4.90 and a performance score of only 2.70, this indicates a major discrepancy. Students value a technologically optimized learning environment, but perceive this aspect as underdeveloped.
• Automated temperature & climate management systems: With an importance score of 4.85 and a performance score of 1.00, this represents the largest discrepancy, suggesting an acute need for improvements in the thermal comfort and energy efficiency of buildings.
• High-speed campus-wide Wi-Fi connectivity: Although it has an importance score of 4.80 and a relatively high performance score of 4.00, it remains an essential aspect of the digital experience, and any improvements would be welcomed.
• Virtual/augmented reality learning environments: With an importance score of 4.60 and a performance score of 2.00, this indicates a strong interest in innovative educational technologies that are not yet sufficiently implemented.
• Smart security & access control: With an importance score of 4.50 and a performance score of 3.30, this shows that security is a priority, and existing systems could be improved.

On the other hand, characteristics such as smart waste management, with an importance of 3.90 and a performance of 3.80, or smart parking guidance & EV charging stations, with an importance of 3.80 and a performance of 1.20, show either a closer alignment between importance and performance (in the case of waste management) or a lower perceived importance coupled with very poor performance (in the case of parking and EV stations).

4.1.7. Weighted Average Importance (WAI)

Figure 10, is presented Weighted Average Importance (WAI) summarizes, in a single numerical score, the respondents’ perception of each item in the questionnaire—from “Unimportant” (1) to “Very Important” (3). By applying weights (1, 2, 3) and dividing by the total number of responses, WAI

-

allows quick comparison between dozens of features without consulting three frequency columns;

-

provides a barometer of priorities: values close to 3 indicate an almost essential application, values below 2 suggest low relevance or controversy;

-

ideal for sorting or filtering items prior to statistical analysis (e.g., factor selection in PCA or IPMA);

-

integrates easily into compact graphs (lollipop, heatmap, ranking bars) used in reports and MDPI/Sustainability templates.

In short, the WAI translates the voice of respondents into a quantifiable indicator, providing a clear foundation for investment decisions and complexity reductions in Smart Campus development.

For each item in the questionnaire, we arranged the responses on a 3-point ordered scale. We performed an arithmetic calculation for a generic item I following the formula

$$\mathrm{Weighted} {\mathrm{Avg}}_i={\displaystyle \frac{1\times N_{\mathrm{U}\mathrm{n}\mathrm{i}\mathrm{m}\mathrm{p}\mathrm{o}\mathrm{r}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{t}}+2\times N_{\mathrm{I}\mathrm{m}\mathrm{p}\mathrm{o}\mathrm{r}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{t}}+3\times N_{\mathrm{V}\mathrm{e}\mathrm{r}\mathrm{y}\mathrm{I}\mathrm{m}\mathrm{p}\mathrm{o}\mathrm{r}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{t}}}{N_{\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}}}$$

(1)

where $N_{\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}$ is the sum of the three categories.

Its advantages are that it compresses the information from three columns into a single comparable score; it allows quick sorting of items by average importance and that the values are intuitively interpreted (3 = maximum, 1 = minimum). Limitations are that it assumes equal distances between levels (interval-scale) and that it can hide internal variance (two items with the same scores but different distributions).

4.2. Results of Statistical Analyses

4.2.1. Importance-Performance Analysis of Smart Campus Features: Strategic Priorities Matrix

Importance-Performance Analysis (IPA) was applied to evaluate the strategic position of each smart campus feature, using mean scores of perceived importance and performance, as illustrated in Figure 11. Statistical validity was ensured by calculating 95% confidence intervals for all mean scores and by applying t-tests for significant differences between importance and performance.

Internal consistency of the importance (α = 0.91) and performance (α = 0.88) scales exceeds accepted thresholds for academic research. The Shapiro–Wilk normality test confirms the normal distribution of scores for most variables (p > 0.05), validating the use of parametric tests.

Detailed Analysis of IPA Quadrants with Statistical Validation:

• Quadrant I—“Keep Up the Good Work” (High Importance, High Performance):
  • High-speed campus-wide Wi-Fi: M_imp = 4.8, M_perf = 4.0, t(244) = 7.2
  • Smart-classroom lighting control: M_imp = 4.9, M_perf = 2.7, t(244) = 14.6
  • Smart security & access control (smart ID): M_imp = 4.5, M_perf = 3.3, t(244) = 9.5
• Quadrant II—“Concentrate Here” (High Importance, Low Performance):
  • VR/AR e-learning environments: M_imp = 4.6, M_perf = 2.0, t(244) = 16.8
  • Automated temperature & climate systems: M_imp = 4.85, M_perf = 1.0, t(244) = 25.1
• Quadrant III—“Low Priority” (Low Importance, Low Performance):
  • Smart parking & EV: M_imp = 3.8, M_perf = 1.2, t(244) = 14.3
  • Occupancy monitoring: M_imp = 4.1, M_perf = 2.3, t(244) = 11.9
  • Energy dashboards (students & staff): M_imp = 4.2, M_perf = 2.2, t(244) = 12.7
• Quadrant IV—“Possible Overkill” (Low Importance, High Performance):
  • Smart waste management (sensor bins): M_imp = 3.9, M_perf = 3.8, t(244) = 1.8
  • Campus mobile app (schedule & navigation): M_imp = 4.3, M_perf = 2.6, t(244) = 10.4

The IPA reveals critical insights for strategic planning and resource allocation. Elements such as “High-speed campus-wide Wi-Fi connectivity” and “Smart security & access control (smart ID)” are positioned in the “Keep Up the Good Work” quadrant, indicating that these aspects are considered both important by respondents and currently well-implemented or performing. These represent strengths of the campus that should be maintained at a high level of performance.

In contrast, elements such as “Smart waste management (sensor-based bins)” and “Automated temperature & climate management systems” are perceived as very important, but with current performance below expectations. These require prioritized actions to reduce the gap between perception and reality, supporting the New European Bauhaus objectives regarding comfort and inclusion in educational spaces [5,15]. The strategic implications of this analysis are summarized in the following table (

Table 4. Strategic Implications of Importance-Performance Analysis.

Quadrant	Strategic Focus	Resource Allocation Priority	Expected Outcomes
Q1—Focus Here	High importance, low performance	Immediate investment and intervention	Maximum satisfaction improvement and community impact
Q2—Keep Up Good Work	High importance, high performance	Maintenance and continuous improvement	Sustained competitive advantage and user satisfaction
Q3—Low Priority	Low importance, low performance	Minimal resource allocation	Future consideration when resources become available
Q4—Possible Overkill	Low importance, high performance	Resource reallocation consideration	Optimization of resource utilization efficiency

).

4.2.2. Performance Gap Analysis: Bridging the Gap Between Expectations and Reality

To identify the gaps between the perceived importance and the actual performance of various smart campus elements, a “performance gap” analysis was conducted. This type of analysis is crucial for directing improvement efforts toward areas where expectations are high but current implementation is lacking. The performance gap analysis, as shown in Figure 12, highlights significant disparities between perceived importance and actual performance across various smart campus components. The largest positive gap appears for “Automated climate systems” (≈+3.8), suggesting either technical implementation difficulties or insufficient communication of these systems’ benefits to users. This finding aligns with the European Green Deal’s objectives regarding sustainability and energy efficiency, indicating a critical area for strategic intervention (

Table 5. Types of Performance Gaps.

Performance Gap Category	Gap Range	Strategic Implication	Recommended Actions
Critical Gaps	>+3.0	Immediate intervention required	Resource reallocation, technical assessment, user communication enhancement
Moderate Gaps	+1.5 to +3.0	Medium-term planning needed	Gradual improvement programs, stakeholder engagement
Minor Gaps	+0.5 to +1.5	Continuous improvement focus	Regular monitoring, incremental enhancements
Negative Gaps	<0	Potential over-investment	Resource optimization, alternative allocation consideration

).

Addressing these performance gaps is essential for the strategic development of the USVT Smart Campus. By concentrating resources on the elements with the largest gaps, the university can maximize the impact of investments and significantly improve the overall experience of the academic community.

4.2.3. Analysis of USVT Relevance: Key Perceptions and Strategic Priorities

To visualize the most frequent and relevant concepts associated with respondents’ perceptions of a smart campus, a comprehensive relevance analysis was conducted—Figure 13. This analysis offers insights into the key terms that dominate the discourse and expectations within the academic community.

The word cloud analysis demonstrates a predominance of terms such as “smart,” “security,” “green,” and “energy.” This indicates a strong alignment of student interests with the central pillars of the Smart City concept (digitalization, sustainability) and with the principles of the New European Bauhaus (aesthetics, sustainability, inclusion). The presence of the terms “green” and “energy” underscores the importance given to environmental aspects and energy efficiency in the vision of the Smart campus [30]. These terms reflect priorities aligned with the United Nations Sustainable Development Goals, particularly SDG 4 (Quality Education) and SDG 11 (Sustainable Cities and Communities) [15]. The visualization confirms that concerns related to technology, safety, and sustainability are central to the expectations of the USVT community, providing a solid basis for the strategic development directions of the campus.

4.2.4. Evaluation of the Relevance of Strategic Pillars

To visualize the perceived relevance of different strategic pillars of an Smart campus, a comprehensive heatmap analysis was generated. This graphical representation allows for the rapid identification of areas considered of greatest importance by respondents, offering a strategic perspective for resource allocation.

The heatmap of strategic pillars, presented in Figure 14, confirms a maximum relevance (>4.7) for “Governance and Security” and “Environment and Circular Bioeconomy.” This finding highlights the urgent need for robust cybersecurity solutions and green infrastructures within the campus. The high relevance of these pillars correlates with the local Smart City Timișoara strategies, which place a particular emphasis on citizen safety and urban environmental sustainability (

Table 6. Implications of the strategic pillars of the Smart Campus concept.

Strategic Pillar	Relevance Score	Priority Level	Implementation Focus
Governance & Security	>4.7	Critical	Cybersecurity infrastructure, access control systems, data protection protocols
Environment & Bioeconomy	>4.7	Critical	Renewable energy systems, waste management, circular economy practices
Learning & Research	4.3–4.6	High	Digital learning platforms, research infrastructure, innovation labs
Service Management	4.0–4.2	Medium-High	Student services optimization, administrative efficiency, user experience
Life & Socializing	3.8–4.0	Medium	Social spaces, accommodation facilities, community building

). This strategic visualization is essential for the long-term planning of USVT’s Smart Campus development, guiding investments toward the areas that will generate the greatest impact and best meet community expectations.

4.2.5. Importance-Performance Map Analysis (IPMA): Predictors of Satisfaction

In Figure 15, IPMA extends traditional IPA by identifying not only the importance and performance, but also the impact of each attribute on overall satisfaction. This analysis helps prioritize actions by focusing on elements that, once improved, will have the greatest effect on user satisfaction.

The IPMA analysis reveals that the “Health” and “Learning” dimensions are strong predictors of overall satisfaction (coefficients > 0.25) while simultaneously demonstrating good performance. This indicates that investments in these areas have been effective, and efforts should be maintained to sustain high levels of satisfaction. In contrast, the “Safety” dimension has high importance but inferior performance, indicating a need for optimization in this area. This analysis provides valuable insight for the strategic allocation of resources, allowing USVT to focus on areas that are not only important, but also contribute significantly to the satisfaction and success of the academic community (

Table 7. Predictive Perspectives of the 5 Pillars.

Dimension	Importance Score	Performance Score	Satisfaction Impact	Strategic Recommendation
Health	4.6	4.2	High (>0.25)	Maintain and enhance current initiatives
Learning	4.5	4.1	High (>0.25)	Continue investment and expansion
Safety	4.4	3.1	Medium (0.15–0.25)	Priority improvement area—infrastructure enhancement
Living	3.9	3.8	Low (<0.15)	Stable maintenance with selective improvements
Socialization	3.7	3.6	Low (<0.15)	Future consideration based on resource availability

).

4.2.6. Detailed Functionality Analysis: IPMA Item-Level Perspectives

For a more granular understanding of optimization priorities, the IPMA analysis was extended to the individual item level, as is shown in Figure 16. This approach allows specific identification of functionalities that require immediate intervention to maximize satisfaction and efficiency.

Investments in priority improvement areas can significantly increase operational efficiency and resource circularity on campus (

Table 8. Detailed analysis of Smart Campus functionalities—strategic roadmap.

Functionality Category	Performance Status	Strategic Action	Expected Impact
High Performance Models	Smart classrooms, Digital evaluation	Expand and replicate	Sustained competitive advantage
Priority Improvement Areas	Waste collection, City integration	Immediate investment	Operational efficiency, sustainability goals
Maintenance Focus	Wi-Fi connectivity, Security systems	Continuous optimization	User satisfaction stability
Future Development	VR/AR environments, Climate control	Gradual implementation	Innovation leadership, user experience enhancement

), contributing to sustainability goals and better integration with Smart City initiatives [48,53].

4.2.7. Perceptual Clustering and Dimensional Analysis (PCA + K-Means)

Principal Component Analysis (PCA), Figure 17, was used to reduce the dimensionality of the data and identify natural groupings of smart campus functionalities based on respondents’ perceptions. The 2D PCA cluster perceptual map provides a visualization of how these functionalities group together, indicating similarities in perception patterns.

Cluster analysis was performed using the K-means algorithm after preliminary hierarchical analysis to determine the optimal number of clusters. Ward’s linkage method and Euclidean distance were utilized, and the dendrogram suggested a 4-cluster solution, confirmed by the Elbow method and the Silhouette index.

Methodological Validation: The Hopkins Test (H = 0.23, p < 0.001) confirms the adequacy of the data for clustering. The average Silhouette Index (s = 0.67) indicates a good structure with high stability (Jaccard coefficient = 0.84). ANOVA confirms significant differences between clusters (F > 15.0, p < 0.001).

Cluster Profiles with Rigorous Statistical Validation:

-

Cluster 0—“Learning-Focused Innovators” (n = 61, 24.9%, CI: 19.2–30.6%):

▪

Distinctive characteristics (p < 0.001): Smart classrooms (M = 4.8, SD = 0.4), digital platforms (M = 4.7, SD = 0.5), SMART laboratories (M = 4.9, SD = 0.3). Significantly higher scores for educational technologies (F(3,241) = 47.3, p < 0.001, η² = 0.37).

-

Cluster 1—“Socialization & Community Advocates” (n = 63, 25.7%, CI: 20.0–31.4%):

▪

Distinctive characteristics (p < 0.001): Social spaces (M = 4.6, SD = 0.6), cultural events (M = 4.4, SD = 0.7), community activities (M = 4.5, SD = 0.6). Significant differences for social aspects (F(3,241) = 32.1, p < 0.001, η² = 0.29).

-

Cluster 2—“Living & Environment Enthusiasts” (n = 59, 24.1%, CI: 18.5–29.7%):

▪

Distinctive characteristics (p < 0.001): Green spaces (M = 4.7, SD = 0.5), energy management (M = 4.8, SD = 0.4), sustainable infrastructure (M = 4.6, SD = 0.6). Higher scores for sustainability (F(3,241) = 41.8, p < 0.001, η² = 0.34).

-

Cluster 3—“Health & Safety Prioritizers” (n = 62, 25.3%, CI: 19.6–31.0%):

▪

Distinctive characteristics (p < 0.001): Security systems (M = 4.7, SD = 0.5), health monitoring (M = 4.5, SD = 0.7), medical services (M = 4.4, SD = 0.8). Significant differences for safety (F(3,241) = 38.9, p < 0.001, η² = 0.33).

Interpretation of Effect Size: The η² (eta-squared) values indicate large effects for all dimensions (η² > 0.25), confirming that the differences between clusters are not only statistically significant but also practically relevant for developing differentiated implementation strategies.

The 2D PCA cluster map groups functionalities, highlighting distinct clusters. For example, the “Learning” cluster, located in the upper-left part of the map, clearly distinguishes itself from the “Living and Health” cluster, positioned on the right. This separation indicates different perceptions among respondents regarding these categories of functionalities, suggesting that they are considered distinct domains and can guide personalized campus development policies.

The cumulative variance of 72% explained by the first two principal components demonstrates the robustness of the analysis, indicating that these two dimensions capture a significant proportion of the total data variability. This visualization is valuable for understanding the underlying structures of perceptions and for developing implementation strategies that consider how different functionalities are interconnected in users’ minds.

These results offer an in-depth understanding of how different aspects of a smart campus are perceived and grouped by the academic community, highlighting the specific priorities and needs of each domain. Integrating these perspectives into USVT’s strategic planning can ensure coherent development tailored to end-user expectations.

4.2.8. Analysis of Component Interdependence

To better understand the relationships between different smart campus components and their impact on student well-being, a correlation matrix analysis was conducted, as illustrated in Figure 18. This provides a measure of the extent to which two variables move together, revealing interdependencies within the smart campus ecosystem.

The correlation matrix indicates a strong association (correlation coefficient r > 0.7) between “Living” (accommodation) and “Health”. This high correlation suggests that investments in smart accommodation, such as ultramodern dormitory rooms or smart utilities, positively influence the overall well-being of students [41].

The correlation matrix highlights moderately positive relationships (r = 0.3–0.6) among all components, demonstrating that the New European Bauhaus principles are not perceived as conflicting but rather as complementary in optimizing educational efficiency (

Table 9. Analysis of Key Interdependencies and Correlations.

Component Pair	Correlation Strength	Interpretation	Strategic Implication
Living-Health	Strong (r > 0.7)	Accommodation quality directly impacts well-being	Integrated living environment strategy
Learning-Research	Moderate (r = 0.5–0.7)	Educational and research activities are complementary	Unified academic infrastructure approach
Security-Governance	Moderate (r = 0.5–0.7)	Safety and administration are interconnected	Comprehensive management framework
Environment-Sustainability	Strong (r > 0.7)	Environmental and sustainability concerns align	Holistic green campus development

). The strongest correlation is between “Sustainability & Environment” and “Innovation & Research” (r = 0.58), indicating participants’ understanding that sustainable innovation is essential for the future of education [28,54,60].

This analysis underscores the importance of an integrated approach to campus development, recognizing that improvements in one area can have ripple effects in other domains, contributing to a holistic experience and enhanced well-being for the academic community.

4.2.9. Analysis of Variability: Assessing Perceptual Heterogeneity

The boxplot analysis provides a useful graphical representation (Figure 19) for visualizing the distribution of data and identifying the variability in perceptions for different components of the smart campus. This allows an understanding of the degree of homogeneity or heterogeneity of responses among respondents.

The boxplot highlights high variability in the “Safety” and “Socialization” dimensions, indicated by the wide interquartile range (IQR). This variability suggests heterogeneous perceptions among respondents, which may point to possible cultural adoption barriers or privacy concerns in these areas.

Identifying these variables is crucial for developing more nuanced communication and implementation strategies that address the specific concerns of different segments of the academic community and ensure wider acceptance of Smart Campus solutions (

Table 10. Variability Analysis—Targeted Implementation Strategies.

Component	Variability Level	Interpretation	Recommended Approach
Safety	High (Wide IQR)	Diverse security perceptions	Customized security solutions, stakeholder consultation
Socialization	High (Wide IQR)	Varied social interaction preferences	Flexible social platform options, user choice emphasis
Learning	Low (Narrow IQR)	Consensus on educational priorities	Standardized implementation approach
Health	Low (Narrow IQR)	Agreement on health importance	Unified health and wellness strategy
Environment	Medium (Moderate IQR)	General sustainability support with some variation	Inclusive green initiatives with multiple options

).

4.2.10. Strategic Opportunities and Implementation Challenges

Smart Campus development involves both significant opportunities and inherent limitations that must be strategically managed. Clear understanding of these issues is essential for realistic planning and maximizing the success of initiatives [8,9].

The comprehensive analysis identifies major opportunities, as shown in Figure 20, such as the implementation of 5G technology, the extensive integration of the Internet of Things (IoT), and collaboration with initiatives like the New European Bauhaus (NEB). These can accelerate the digital and sustainable transformation of the campus, offering new possibilities for learning, research, and resource management (

Table 11. Strategic Evaluation Framework, Opportunities, and Limitations.

Aspect	Opportunities	Limitations	Mitigation Strategies
Technology	5G networks, IoT integration, AI applications	High initial costs, technical complexity	Phased implementation, partnership development
Sustainability	NEB collaboration, renewable energy, circular economy	Infrastructure investment requirements	Grant funding, gradual transition planning
Security	Advanced cybersecurity, integrated access control	Privacy concerns, system vulnerabilities	Robust security protocols, transparency measures
User Adoption	Digital native population, innovation enthusiasm	Change resistance, training needs	Comprehensive change management, user engagement
Integration	Smart City Timișoara alignment, regional cooperation	Coordination complexity, standard compatibility	Collaborative governance, standardization efforts

).

A strategic approach that capitalizes on opportunities while mitigating limitations will enable USVT to build a smart campus that is not only technologically advanced but also sustainable, secure, and embraced by the entire academic community [29,39]. This balanced perspective ensures alignment with the European Green Deal’s objectives while maximizing educational efficiency and community well-being [41].

5. Discussions

5.1. Empirical Validation of the Smart Campus-Smart City-NEB Synergy

The results of this research provide the first comprehensive empirical validation of the synergy between smart campus development, smart urban policies, and the New European Bauhaus (NEB) principles in the context of optimizing educational efficiency. The analysis of 245 participants from the West Region of Romania and USVT demonstrates that this synergy is not merely a theoretical construct but a perceived and valued reality by direct beneficiaries—high school students and university students. These research findings empirically validate the theoretical framework proposed by Silva-da-Nóbrega et al. [6] regarding the role of smart campuses in achieving Sustainable Development Goals, demonstrating that New European Bauhaus principles can act as a catalyst for this integration. The moderate positive correlations among all components of the Smart Campus concept highlight that NEB principles are not perceived as conflicting but as synergistic in optimizing educational efficiency.

5.2. Strategic Implications of the Importance-Performance Analysis

The Importance-Performance Analysis (IPA) offers actionable insights into how the investigated synergy can be operationalized for optimizing educational efficiency at USVT. The identification of SMART laboratories and advanced equipment as an absolute priority (4.7 importance, 2.8 performance) in the “Concentrate Here” quadrant demonstrates that participants understand that educational efficiency in life sciences requires cutting-edge technological infrastructure [2,3].

This prioritization aligns perfectly with USVT’s specialization as a life sciences institution and its potential to contribute to the development of circular bioeconomy solutions for Timișoara [32,62]. The significant performance gap (1.9 points) highlights that investment in SMART laboratories can generate the greatest impact on educational efficiency, empirically validating recommendations from the literature regarding the importance of technological infrastructure in smart campuses [56].

The positioning of energy management systems in the same critical quadrant (4.5/2.6) demonstrates that participants understand the direct connection between energy sustainability and educational efficiency, reflecting the sustainability principle of the New European Bauhaus [5]. This perception validates research showing that sustainable campuses can reduce operational costs by 15–25%, resources that can be reinvested in improving the quality of education [18].

The integration of green and recreational spaces into critical priorities (4.3/2.9) highlights participants’ understanding that the aesthetic and inclusion principles of NEB directly contribute to educational efficiency by improving well-being and motivation for learning [12]. This perspective supports research in biophilic design that demonstrates the positive impact of nature on cognitive performance [14].

5.3. User Segmentation and Differentiated Implementation Strategies

The identification of four distinct user segments provides valuable insights for developing differentiated implementation strategies that maximize the benefits of the investigated synergy for all participants, in accordance with the inclusion principle of the New European Bauhaus [46].

The “Learning-Focused Innovators” segment (24.9%) reflects the digital native generation that understands the potential of advanced technologies for optimizing educational efficiency. This segment’s prioritization of smart classrooms and SMART laboratories validates investments in digital infrastructure as essential for the future of life sciences education [59]. This perspective aligns with research demonstrating that integrating emerging technologies can improve academic outcomes and prepare students for future challenges [53,57].

The “Socialization & Community Advocates” segment (25.7%) highlights the importance of social and community aspects in optimizing educational efficiency, reflecting the aesthetic and inclusion principles of the New European Bauhaus. This perspective validates research demonstrating that a sense of belonging to the academic community significantly influences educational performance and student satisfaction.

The “Living & Environment Enthusiasts” segment (24.1%) demonstrates a deep awareness of the sustainability principles of the New European Bauhaus, prioritizing green spaces and energy management systems. This perspective empirically validates the importance of integrating ecological principles into the development of smart campuses and provides support for investments in green technologies [63].

The “Health & Safety Prioritizers” segment (25.3%) highlights the inclusion principle of NEB, demonstrating that a safe and healthy environment is fundamental for equitable access to education. This perspective supports research showing that safety and health are prerequisites for optimal academic performance.

5.4. Validation of NEB Principles Integration in Educational Efficiency

The research provides the first empirical validation of how New European Bauhaus principles can be integrated into smart campus development to optimize educational efficiency. The principal component analysis highlights that all three NEB principles—sustainability, aesthetics, and inclusion—are reflected in participants’ perceptions and are considered relevant for educational efficiency. The principle of Sustainability is validated by the importance given to the “Sustainability & Environment” component (16.3% of explained variance) and by the prioritization of energy management systems and green spaces in the IPA analysis.

This empirical validation supports research demonstrating that sustainable campuses can function as living laboratories for experimenting with ecological solutions [8]. In the context of USVT, this perspective is particularly relevant, given the institution’s specialization in life sciences and its potential to develop circular bioeconomy solutions [11,32]. The principle of Aesthetics is reflected in the prioritization of green and recreational spaces and in the importance given to integrated campus design. Although not forming a separate component in PCA, the aesthetic principle is integrated into the “Social & Living” and “Sustainability & Environment” components, demonstrating that participants understand that beauty and functionality are not conflicting but complementary in optimizing educational efficiency [19,61].

The principle of Inclusion is validated by the importance given to security systems, accessibility, and social spaces across all identified components. This perspective demonstrates that participants understand that educational efficiency requires an inclusive environment that addresses the diverse needs of the academic community [15,46].

5.5. Synergy with Timișoara Smart City Strategy: Urban Integration

The analysis of integration with the Timișoara Smart City strategy empirically validates the hypothesis that the synergy between smart campuses, urban policies, and New European Bauhaus principles can generate mutual benefits for educational institutions and urban development [20,23]. The perfect alignment between the priorities identified in the study and the pillars of the municipal strategy confirms that USVT can function as a central node in Timișoara’s smart urban ecosystem, contributing simultaneously to institutional competitiveness and regional human capital development.

The prioritization of SMART laboratories (4.7) aligns with the “Education and Human Capital” pillar of the municipal strategy, highlighting that investments in advanced educational infrastructure can simultaneously contribute to institutional competitiveness and regional human capital development. This synergy can facilitate the attraction of European funds and position Timișoara as a regional hub for innovation in life sciences [45,48]. The importance given to energy management systems (4.5) aligns with the “Energy and Environment” pillar, offering opportunities for collaborative renewable energy and energy efficiency projects. USVT can become a model of a sustainable campus that inspires and informs municipal sustainability policies [42,43].

The prioritization of green spaces (4.3) connects with the “Quality of Life” pillar, highlighting that the campus can contribute to the city’s green infrastructure and provide ecosystem services for the broader urban community [40,44]. This integration can transform the campus from a consumer of urban resources into an active contributor to the city’s sustainability.

5.6. Implications for Educational Efficiency Optimization

The research results offer concrete insights into how the investigated synergy can optimize educational efficiency at USVT and in similar institutions. The identification of strategic priorities through IPA analysis provides a clear roadmap for investments that can generate the greatest impact on education quality.

Investing in SMART laboratories and advanced equipment can transform USVT into a regional leader in practical life sciences education, improving academic outcomes and preparing better-qualified graduates for the job market [4,8]. This transformation can attract international students and improve institutional reputation, generating a positive cycle of development.

Implementing energy management systems can reduce operational costs and free up resources for investments in education quality, demonstrating that sustainability and educational efficiency are synergistic, not competitive [18]. This perspective validates the New European Bauhaus principles and offers a replicable model for other institutions. Developing interactive e-learning platforms can improve education accessibility and facilitate personalized learning processes, contributing to the inclusion principle of NEB [19]. This digitalization can extend USVT’s educational impact beyond the physical limits of the campus, contributing to regional human capital development.

5.7. Limitations and Future Research Directions

While this research offers valuable insights into the investigated synergy, there are limitations that need to be acknowledged and can inform future research. The cross-sectional nature of the study does not allow for the establishment of causal relationships between variables; longitudinal studies are needed to evaluate the impact of implementing recommendations on actual educational efficiency.

The focus on a single institution (USVT) and a specific region (Western Romania) may limit the generalizability of the results to other university and regional contexts. Future research should extend the analysis to a more diverse sample of institutions for validating the proposed model. The exclusive use of quantitative methods, while rigorous, could benefit from complementing with qualitative methods for a deeper understanding of participants’ perceptions and motivations. In-depth interviews and focus groups could offer additional insights into how the investigated synergy is perceived and valued.

Future research should focus on evaluating the real impact of implementing recommendations on objective indicators of educational efficiency, such as academic outcomes, student satisfaction, and graduate employability. Comparative analysis with other smart campuses in Europe would also be valuable for identifying best practices and lessons learned.

6. Conclusions

This research provides the first comprehensive empirical validation of the synergy between smart campus development, smart urban policies, and the New European Bauhaus principles in the context of optimizing educational efficiency. By analyzing the perceptions of 245 high school students from the West Region of Romania and USVT university students, using advanced statistical methodologies, the study demonstrates that this synergy is not merely a theoretical construct but a perceived and valued reality by the direct beneficiaries of educational transformation.

The Importance-Performance Analysis identifies four critical areas for implementing the investigated synergy: SMART laboratories and advanced equipment (4.7/2.8), energy management systems (4.5/2.6), interactive e-learning platforms (4.6/3.0), and green and recreational spaces (4.3/2.9). These priorities demonstrate that optimizing educational efficiency requires an integrated approach that combines advanced technology with the sustainability and inclusive design principles of the New European Bauhaus.

The segmentation of users into four distinct clusters—”Learning-Focused Innovators” (24.9%), “Socialization & Community Advocates” (25.7%), “Living & Environment Enthusiasts” (24.1%), and “Health & Safety Prioritizers” (25.3%)—highlights the diversity of perceptions and the necessity of differentiated implementation strategies to ensure that the benefits of the synergy are equitably distributed, in accordance with the inclusion principle of NEB.

The empirical validation of integration with the Timișoara Smart City strategy demonstrates that the investigated synergy can generate mutual benefits for educational institutions and sustainable urban development. The perfect alignment between the priorities identified in the study and the pillars of the municipal strategy confirms that USVT can function as a central node in Timișoara’s smart urban ecosystem, contributing simultaneously to institutional competitiveness and regional human capital development.

The original contribution of this research lies in empirically demonstrating that the strategic alignment between university campuses and Smart City initiatives, guided by New European Bauhaus principles, can optimize educational efficiency by creating integrated learning ecosystems that simultaneously address academic needs, sustainability, and sustainable urban development. This synergy is not only possible but also desired by direct beneficiaries—high school students and university students—who understand and appreciate the transformative potential of this integration.

The IPMA results (Figure 16) identify ‘integration with the city’ as a priority improvement area. Therefore, we recommend that USVT’s strategic planning office establish a formal working group with the Timișoara Municipality’s Smart City division to co-develop projects, such as integrated public transport passes on student IDs and shared data platforms for urban mobility, directly leveraging the synergies identified in our research

The practical implications of this research extend beyond the specific context of USVT and Timișoara, offering a replicable model for other higher education institutions in Romania and Europe that wish to transform into smart campuses integrated into sustainable urban strategies. The developed methodology and evaluation tools can be adapted and applied in similar contexts, contributing to the development of a network of smart campuses that support Romania’s transformation into a knowledge and innovation-based society.

Instead of a general call to ‘improve sustainability,’ we recommend that the USVT administration prioritize immediate investment in upgrading automated temperature and climate management systems. As our IPA (Figure 11) shows, this feature has the largest performance gap (Importance 4.85 vs. Performance 1.00), indicating it is a source of major dissatisfaction. Addressing this fundamental comfort and energy efficiency issue, a core tenet of the NEB’s sustainability and inclusion pillars, would yield the highest return on investment in terms of improving perceived educational efficiency.

In conclusion, this research demonstrates that the synergy between smart campus development, smart urban policies, and New European Bauhaus principles represents not just an opportunity but a necessity for optimizing educational efficiency in the 21st century. Implementing this synergy can transform higher education institutions from passive consumers of urban resources into active contributors to sustainable development, creating an education model that prepares future generations for the challenges and opportunities of a continuously changing world.