Multidisciplinary Engineering Science Open

Barriers to Implementing Sustainable Engineering Solutions in Multidisciplinary Contexts: A Qualitative Study of Engineering Professionals in Tehran

Navid Sadeghi ^*

This study aimed to explore the major barriers that hinder the implementation of sustainable engineering solutions in multidisciplinary project contexts from the perspectives of engineering professionals, project managers, sustainability consultants, and public-sector technical experts in Tehran. A qualitative descriptive design was adopted. Data were collected through semi-structured interviews with 24 participants selected through purposive maximum-variation sampling from engineering consulting firms, construction and infrastructure companies, environmental advisory units, energy-related organizations, and municipal technical bodies in Tehran. Participants had direct experience in designing, managing, evaluating, or implementing sustainable engineering solutions across multidisciplinary projects. Interviews continued until theoretical saturation was reached, which occurred after the twenty-first interview; three additional interviews were conducted to confirm conceptual adequacy. Interviews were audio-recorded with permission, transcribed verbatim, anonymized, and analyzed using thematic analysis. NVivo software was used to organize transcripts, develop initial codes, compare patterns across participant groups, and construct final categories. Analysis generated five main categories of implementation barriers: fragmented disciplinary logics and weak cross-functional communication; economic and procurement constraints; regulatory ambiguity and institutional inertia; limited sustainability knowledge, data, and lifecycle assessment capacity; and stakeholder misalignment, risk perception, and weak accountability. Participants emphasized that sustainable engineering solutions often fail not because of technical impossibility, but because engineering, financial, managerial, legal, and social actors evaluate project success through different criteria. High initial costs, short-term budgeting, uncertain incentives, fragmented approval procedures, limited access to reliable lifecycle data, and insufficient client demand weakened implementation. Sustainable engineering implementation in multidisciplinary contexts requires more than technical design competence. It depends on integrated governance, lifecycle-based evaluation, interdisciplinary communication, supportive regulations, financial incentives, stakeholder engagement, and organizational accountability. The findings suggest that sustainable engineering should be embedded into project planning, procurement, education, and performance evaluation systems rather than treated as an optional design feature.

Exploring the Integration of Artificial Intelligence into Multidisciplinary Engineering Workflows

Maryam Al Zadjali ^* , Tariq Al Riyami , Salma Al Busaidi

This study aimed to explore how artificial intelligence is being integrated into multidisciplinary engineering workflows and how engineers perceive its effects on collaboration, design decision-making, professional roles, and organizational readiness. A qualitative descriptive design was employed using semi-structured interviews with 24 engineering professionals working in multidisciplinary engineering organizations in Muscat, Oman. Participants included civil, mechanical, electrical, software, systems, and project engineers, as well as engineering managers with direct experience of AI-supported tools in design, simulation, project coordination, documentation, quality assurance, or decision support. Participants were recruited purposively to capture variation in engineering discipline, professional experience, and organizational role. Data collection continued until theoretical saturation was reached. Interviews were audio-recorded, transcribed verbatim, anonymized, and analyzed using thematic analysis. NVivo software was used to organize transcripts, code interview data, compare patterns across disciplinary groups, and develop final themes. Four main categories emerged from the analysis: AI as a boundary-spanning coordination mechanism, AI-enabled acceleration of design exploration and technical decision-making, human oversight and trust in AI-generated outputs, and organizational readiness for sustainable AI integration. Participants described AI as useful for connecting fragmented disciplinary knowledge, reducing repetitive documentation work, supporting early-stage design alternatives, improving simulation preparation, and facilitating cross-functional communication. However, they also emphasized concerns regarding data quality, model explainability, accountability for engineering decisions, software interoperability, and uneven AI literacy across teams. The integration of AI into multidisciplinary engineering workflows is not merely a technical transition but a socio-technical transformation that reshapes collaboration, professional judgment, and organizational learning. Sustainable AI adoption requires high-quality engineering data, transparent governance, domain-specific validation, continuous professional training, and human-centered workflow redesign.

A Qualitative Exploration of Knowledge Sharing in Multidisciplinary Engineering Research Teams

Ahmed Al Harthy , Fatima Al Balushi ^* , Said Al Khabouri

This study aimed to explore how knowledge is shared, interpreted, and transformed among members of multidisciplinary engineering research teams in Muscat, Oman. A qualitative exploratory design was employed to examine the lived and practice-based experiences of researchers, engineers, project coordinators, and technical specialists working in multidisciplinary engineering research teams. Twenty-five participants were recruited through purposive sampling from university-based laboratories, research centers, and industry-linked engineering projects in Muscat. Data were collected exclusively through semi-structured interviews lasting 45–75 minutes. Interviews focused on participants’ experiences of sharing technical knowledge, coordinating expertise, managing disciplinary differences, using digital platforms, and overcoming barriers to collaboration. Sampling continued until theoretical saturation was reached after 22 interviews, followed by three confirmatory interviews. All interviews were audio-recorded with consent, transcribed verbatim, anonymized, and analyzed using thematic analysis supported by NVivo software. The analysis generated five main categories: boundary translation and shared technical language, relational trust and psychological safety, digital and informal knowledge infrastructures, leadership-enabled expertise coordination, and tensions created by time pressure, ownership, and institutional silos. Participants described knowledge sharing as more than information exchange; it involved translating assumptions, negotiating meanings, clarifying dependencies, and developing shared problem representations. Effective knowledge sharing occurred when teams created psychologically safe spaces, used visual and digital artifacts, recognized distributed expertise, and established routines for cross-disciplinary sensemaking. Barriers included disciplinary jargon, publication competition, fragmented documentation, uneven participation, and insufficient time for reflective integration. Knowledge sharing in multidisciplinary engineering research teams is a socially embedded, technically mediated, and leadership-dependent process. The findings suggest that successful collaboration requires shared language, trust, documentation discipline, boundary-spanning leadership, and institutional incentives that reward collective knowledge creation. Strengthening these conditions can improve research integration, innovation quality, and team learning in engineering research environments.

Understanding Stakeholder Engagement in Large-Scale Engineering Projects: A Qualitative Study

Bence Varga , Anna Kovacs ^* , Gabor Toth

This study aimed to explore how professionals involved in large-scale engineering projects understand, organize, and sustain stakeholder engagement across complex project environments in Hungary. A qualitative research design was adopted to obtain an in-depth understanding of stakeholder engagement practices from the perspectives of professionals directly involved in large-scale engineering projects. Data were collected through semi-structured interviews with 24 participants from Hungary, including project managers, engineering leads, procurement specialists, public-sector representatives, environmental and social impact experts, and community liaison officers. Participants were selected through purposive sampling to ensure variation in role, sector, and professional experience. Interviews continued until theoretical saturation was reached, with no substantially new codes emerging after the twenty-first interview and three additional interviews conducted to confirm saturation. Interviews were audio-recorded with consent, transcribed verbatim, anonymized, and analyzed using thematic analysis. NVivo software was used to organize transcripts, support systematic coding, compare categories, and develop higher-order themes. The analysis generated four main categories: dynamic stakeholder identification and prioritization, communication as a mechanism of alignment, trust and legitimacy in contested project environments, and institutional-contractual constraints on engagement. Participants described stakeholder engagement as a continuous and adaptive process rather than a fixed procedural requirement. Effective engagement depended on early mapping of formal and informal actors, transparent communication, responsiveness to local concerns, and the ability to negotiate competing expectations among government bodies, contractors, communities, consultants, and end users. However, fragmented governance, political pressure, rigid contractual arrangements, and delayed communication often reduced the quality of engagement. Stakeholder engagement in large-scale engineering projects is best understood as a relational, political, and iterative process embedded in technical, institutional, and social complexity. The findings suggest that successful engagement requires more than compliance-based consultation; it requires continuous stakeholder intelligence, credible communication, trust-building, and flexible governance mechanisms that allow project teams to respond to emerging concerns throughout the project life cycle.

Exploring Collaboration Between Engineers, Data Scientists, and Environmental Specialists in Sustainable Technology Development

Lucas Silva , Mariana Costa ^* , Rafael Oliveira

This qualitative study aimed to explore how engineers, data scientists, and environmental specialists collaborate in the development of sustainable technologies in Brazilian organizational and project contexts. A qualitative descriptive design was used to examine professional experiences of interdisciplinary collaboration in sustainable technology development. Data were collected through semi-structured interviews with 27 participants from Brazil, including engineers, data scientists, and environmental specialists involved in renewable energy, circular economy, water management, environmental monitoring, smart-city, and climate-analytics projects. Participants were selected purposively to ensure disciplinary diversity and direct experience in collaborative sustainability-oriented technology projects. Interviews were conducted online and face-to-face, lasted between 45 and 75 minutes, and continued until theoretical saturation was reached at the twenty-fourth interview, followed by three confirmatory interviews. Audio recordings were transcribed verbatim and analyzed using thematic analysis supported by NVivo software. Five main categories were identified: shared sustainability problem framing, translation across disciplinary languages, data-mediated integration, negotiation of technical-environmental trade-offs, and organizational conditions for collaborative innovation. Participants described collaboration as most effective when teams moved beyond sequential expert contribution and developed shared problem definitions, common indicators, and iterative feedback loops. Data dashboards, environmental impact models, prototypes, and regulatory matrices functioned as boundary objects that helped professionals coordinate without eliminating disciplinary differences. However, collaboration was constrained by incompatible timelines, different evidentiary standards, fragmented data ownership, and tensions between engineering feasibility, algorithmic performance, environmental integrity, and commercial pressure. Sustainable technology development depends not only on advanced technical expertise but also on structured interdisciplinary collaboration. The findings suggest that engineers, data scientists, and environmental specialists need shared evaluative frameworks, translational routines, participatory data governance, and organizational support to integrate environmental knowledge into technology design. Strengthening these collaborative capabilities can improve the relevance, legitimacy, and sustainability performance of emerging technologies.

Exploring Engineers’ Experiences of Interdisciplinary Collaboration in Multidisciplinary Engineering Projects: A Qualitative Study

Pouya Nouri ^* , Yalda Asadi

This study aimed to explore engineers’ lived experiences of interdisciplinary collaboration in multidisciplinary engineering projects and to identify the relational, communicative, organizational, and learning processes that shape effective cross-disciplinary work. This qualitative study was conducted using a conventional thematic analysis approach. Participants were 24 engineers working in multidisciplinary engineering projects in Tehran, Iran. They were selected through purposive sampling to ensure variation in engineering discipline, professional experience, organizational role, and project type. Data were collected exclusively through semi-structured interviews, each lasting approximately 45–75 minutes. Interviews focused on participants’ experiences of working with engineers and professionals from other disciplines, perceived facilitators and barriers to collaboration, communication practices, conflict management, leadership support, and learning outcomes. Data collection continued until theoretical saturation was achieved. All interviews were audio-recorded with participants’ consent, transcribed verbatim, and analyzed using NVivo software. The analysis followed iterative coding, category development, constant comparison, memo writing, and theme refinement. Five main categories emerged from the analysis: negotiating disciplinary languages and mental models; coordination through boundary objects and integrative routines; relational trust and psychological safety; leadership and project governance as collaboration scaffolds; and interdisciplinary learning and professional identity development. Participants described interdisciplinary collaboration as both necessary and challenging. While disciplinary diversity improved problem-solving and project innovation, it also created misunderstandings, delays, jargon-related confusion, and conflicts over priorities. Effective collaboration depended on shared project goals, early clarification of roles, structured coordination meetings, use of common design documents, respectful communication, and leaders who actively mediated disciplinary boundaries. The findings suggest that interdisciplinary collaboration in engineering projects is not merely a technical process but a socially negotiated practice requiring communication competence, trust, boundary-crossing capacity, integrative leadership, and reflective learning. Multidisciplinary projects benefit when organizations create formal and informal structures that enable engineers to translate disciplinary knowledge, manage conflict constructively, and develop shared ownership of complex project outcomes.

Engineers’ Perceptions of Sustainable Design Practices in Complex Engineering Systems

Narges Yeganeh ^*

This study aimed to explore how engineers working in Tehran perceive, interpret, and implement sustainable design practices in complex engineering systems. A qualitative research design was employed to examine engineers’ lived professional experiences of sustainable design in multidisciplinary engineering contexts. Twenty engineers from Tehran were recruited through purposive and snowball sampling. Participants had professional experience in civil, mechanical, electrical, industrial, software/systems, chemical, environmental, and infrastructure-related engineering fields. Data were collected exclusively through semi-structured interviews, each lasting approximately 45–75 minutes. Interview questions focused on participants’ understanding of sustainability, design decision-making, trade-off management, organizational constraints, stakeholder expectations, use of sustainability tools, and perceived barriers to sustainable engineering practice. Interviews continued until theoretical saturation was reached. All interviews were transcribed verbatim and analyzed using thematic analysis with the support of NVivo software. Analysis generated five main categories: life-cycle and systems thinking, sustainability as a technical design criterion, trade-off management under complexity, organizational and project-level enablers, and tool/data limitations in sustainable engineering practice. Engineers generally perceived sustainable design as more than environmental protection, emphasizing long-term performance, resource efficiency, maintainability, risk reduction, social responsibility, and economic feasibility. However, participants reported that sustainability was often weakened by cost pressure, fragmented project governance, limited client commitment, insufficient local data, and late-stage integration into design processes. Sustainable design was most feasible when sustainability requirements were embedded early, supported by multidisciplinary collaboration, and translated into measurable engineering criteria. The findings suggest that engineers recognize sustainable design as a necessary professional responsibility in complex engineering systems, but its implementation depends on early systems-level integration, organizational support, credible assessment tools, and alignment between technical, economic, environmental, and social objectives.

A Qualitative Exploration of Decision-Making Processes in Multidisciplinary Engineering Innovation

Sina Rahimi ^* , Pegah Kamali

This study aimed to explore how multidisciplinary engineering teams make innovation-related decisions under conditions of technical uncertainty, disciplinary diversity, organizational constraint, and market-oriented pressure. This qualitative study was conducted using semi-structured interviews with 24 participants from Tehran-based engineering and technology-oriented organizations. Participants included senior engineers, project managers, R&D specialists, product development experts, innovation managers, and technical consultants who had direct experience in multidisciplinary engineering innovation projects. Purposeful sampling was used to recruit information-rich participants, and data collection continued until theoretical saturation was achieved after the twenty-first interview, followed by three additional interviews to confirm thematic stability. Interviews were conducted face-to-face or online, lasted 45–75 minutes, and focused on participants’ experiences of innovation decision-making, cross-disciplinary coordination, technical evaluation, conflict resolution, risk assessment, and implementation choices. Audio-recorded interviews were transcribed verbatim and analyzed using thematic analysis with the support of NVivo software. Analysis produced five main categories: shared problem framing across disciplinary boundaries, evidence-based negotiation under uncertainty, distributed authority and decision ownership, iterative experimentation and risk balancing, and organizational alignment with innovation value. The findings showed that multidisciplinary engineering decisions were rarely linear or purely technical. Instead, participants described decision-making as an interactive process shaped by translation between disciplinary logics, negotiation over evidence, informal influence, prototype-based learning, and organizational expectations regarding cost, feasibility, timing, and market relevance. The study concludes that effective decision-making in multidisciplinary engineering innovation depends on the team’s ability to create shared interpretive spaces, combine analytical and experiential knowledge, clarify decision authority, tolerate controlled experimentation, and align technical novelty with organizational value. These findings contribute to engineering innovation literature by showing how decision-making operates as a socio-technical and negotiated practice rather than a purely rational selection process.

Multidisciplinary Engineering Science Open

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Exploring Engineers’ Experiences of Interdisciplinary Collaboration in Multidisciplinary Engineering Projects: A Qualitative Study

Engineers’ Perceptions of Sustainable Design Practices in Complex Engineering Systems

A Qualitative Exploration of Decision-Making Processes in Multidisciplinary Engineering Innovation

Challenges of Communication Across Engineering Disciplines: A Qualitative Inquiry

Exploring Professional Identity Formation Among Engineers Working in Multidisciplinary Environments

Engineers’ Perspectives on Ethical Challenges in Emerging Multidisciplinary Technologies: A Qualitative Study

A Qualitative Investigation of Innovation Management in Multidisciplinary Engineering Organizations

Barriers to Implementing Sustainable Engineering Solutions in Multidisciplinary Contexts: A Qualitative Study of Engineering Professionals in Tehran

Exploring the Integration of Artificial Intelligence into Multidisciplinary Engineering Workflows

A Qualitative Exploration of Knowledge Sharing in Multidisciplinary Engineering Research Teams

Understanding Stakeholder Engagement in Large-Scale Engineering Projects: A Qualitative Study

Exploring Collaboration Between Engineers, Data Scientists, and Environmental Specialists in Sustainable Technology Development

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Barriers to Implementing Sustainable Engineering Solutions in Multidisciplinary Contexts: A Qualitative Study of Engineering Professionals in Tehran

Exploring the Integration of Artificial Intelligence into Multidisciplinary Engineering Workflows

A Qualitative Exploration of Knowledge Sharing in Multidisciplinary Engineering Research Teams

Understanding Stakeholder Engagement in Large-Scale Engineering Projects: A Qualitative Study

Exploring Collaboration Between Engineers, Data Scientists, and Environmental Specialists in Sustainable Technology Development

Exploring Engineers’ Experiences of Interdisciplinary Collaboration in Multidisciplinary Engineering Projects: A Qualitative Study

Engineers’ Perceptions of Sustainable Design Practices in Complex Engineering Systems

A Qualitative Exploration of Decision-Making Processes in Multidisciplinary Engineering Innovation