Purpose The purpose of this study is to evaluate how manufacturers today face mounting demands from stakeholders to adopt innovative manufacturing systems that mitigate the negative societal and environmental effects of their operations. Consequently, manufacturing processes are constantly evolving. Open innovation (OI) systems present a promising avenue for manufacturers to develop dynamic capabilities (DCs), thereby enhancing their long-term performance. However, despite its potential significance, empirical research linking OI, DC and sustainable manufacturing performance (SMP) remains relatively scarce, especially concerning the simultaneous minimization of environmental impact, economic viability and social acceptability. Design/methodology/approach This study rigorously investigates the intricate relationship between various OI systems (namely outbound, inbound and coupled) and their impact on SMP through the mediating influence of DC within the context of large-scale manufacturing enterprises. Using a robust quantitative research design, the authors surveyed 346 employees from prominent Malaysian manufacturers. Data collection utilized a 5-point Likert scale questionnaire drawn from established literature. The authors then used partial least squares structural equation modelling (PLS-SEM) for comprehensive data analysis, resulting in the validation of 11 out of 12 research hypotheses. Findings The findings reveal that both inbound innovation and coupled OI exert direct, positive influences on the social, economic and environmental facets of manufacturing performance. Conversely, outbound innovation predominantly affects economic and environmental performance. A key insight from this study is the mediating role played by DC in shaping the relationship between OI and SMP. This underscores the critical importance for manufacturers to invest in developing DC to maximize the positive impact of OI on SMP. Practical implications The study emphasizes the importance of fostering DC to leverage the potential benefits of OI for SMP improvement. The findings can guide manufacturers in adopting strategies that simultaneously address environmental concerns, economic sustainability and social responsibility. Originality/value Unlike prior studies that treat OI as a unitary construct or assert DC’s mediating role by citation alone, this study disaggregates OI into inbound, outbound and coupled forms, and grounds DC’s mediating function in its sensing, seizing and transforming microfoundations, showing that mediation strength scales systematically with each OI mode’s knowledge-integration demands (variation accounted for [VAF] ranging from 22.34% to 68.67%). This mechanism-level, differentiated account rather than a uniform DC–OI–SMP relationship is the study’s central conceptual contribution.
Purpose This study aims to explore possible futures for the sustainable fashion industry in Iran by examining the relationship between material culture and social awareness. It aims to identify the key drivers and underlying forces shaping sustainability transitions in the context of environmental, social, economic and cultural challenges. Design/methodology/approach This study adopts a qualitative approach based on causal layered analysis (CLA). Data were collected through semistructured interviews with nine experts in the fashion and apparel industry. Initial themes were identified through thematic analysis and subsequently organized across the four CLA layers: litany, social and structural causes, worldview/discourse and myth/metaphor. Findings The findings reveal that the future of sustainable fashion is shaped by a complex interplay of socio-cultural, economic, technological, environmental and institutional factors. At the litany level, issues such as conspicuous consumption, lifestyle patterns, market-driven production and cultural innovation are particularly prominent. At the level of social and structural causes, factors including media influence, the behavioral patterns of elites and policymakers, challenges in domestic production and consumer agency play critical roles. At the worldview/discourse level, values such as social responsibility, support for domestic production, conscious consumption and environmental sustainability are emphasized. At the deepest layer, cultural metaphors and narratives related to authenticity, responsibility and the balance between tradition and modernity shape both perceptions and practices. Research limitations/implications This study is based on qualitative data from a limited number of experts; therefore, future research could expand the sample size or incorporate quantitative approaches to enhance generalizability. Practical implications The findings offer valuable insights for policymakers, industry stakeholders and cultural actors seeking to align production systems with social awareness, ethical governance and sustainable practices. Social implications The study highlights the importance of strengthening social awareness, responsible consumption, cultural identity and collective responsibility to support more sustainable and ethical fashion practices in Iran. Originality/value This study applies a futures-oriented methodology (CLA) to the fashion industry in Iran, providing a multilayered understanding of sustainability challenges and offering pathways for long-term transformation.
Purpose This study aims to examine how the convergence of positive psychology and educational technology evolved between 2007 and 2025, based on publications identified through a systematic search covering 2005–2025. It maps key trends, thematic developments, collaboration patterns and emerging signals relevant to the future development of this interdisciplinary field. Design/methodology/approach A bibliometric analysis of 101 peer-reviewed publications indexed in Scopus and Web of Science was conducted using the Bibliometrix R package. Performance analysis, science mapping and network visualization examined thematic evolution, intellectual structures and international collaboration across three developmental phases: conceptual exploration (2007–2015), methodological expansion (2016–2020) and integrative empirical consolidation (2021–2025). Findings Findings reveal increasing integration of motivational and well-being theories, particularly engagement, psychological adaptability and self-determination, with adaptive and AI-enhanced learning technologies. Emerging themes, including gamification, AI-driven personalization and digital well-being interventions, signal growing attention to learner-centered and psychologically informed digital learning. Despite this growth, the field remains fragmented, with limited cross-national collaboration and underrepresentation of non-Western perspectives. From a foresight perspective, these patterns provide early signals of potential trajectories toward adaptive, well-being–oriented and ethically governed learning environments. By combining bibliometric mapping with a futures-oriented lens, the study provides anticipatory insights to inform research priorities, educational technology design and strategic decision-making toward inclusive, context-sensitive and sustainable educational futures. Research limitations/implications This study is limited to English-language publications indexed in Scopus and Web of Science, which may underrepresent regional and non-English scholarship. Future research should incorporate additional databases and multilingual sources to provide a more comprehensive view of the field. Practical implications The study provides guidance for educational institutions, EdTech developers and policymakers. Findings support the adoption of adaptive learning systems, learner well-being analytics, strengths-based digital interventions and culturally responsive educational resources. The results also highlight the importance of ethical AI governance, transparency, privacy protection and equitable access in the design and implementation of technology-enhanced learning environments. Social implications This study highlights how the integration of positive psychology and educational technology can support learner well-being, resilience, engagement and lifelong learning. The findings emphasize the importance of digital equity, cultural inclusivity and ethical AI governance to ensure that emerging educational technologies contribute to individual flourishing and broader societal well-being rather than reinforcing existing inequalities. Originality/value The study underscores the need for inclusive, interdisciplinary and ethically grounded innovation, emphasizing data responsibility, contextual sensitivity and equitable access. By integrating bibliometric mapping with a futures-oriented lens, this study provides anticipatory insights into the evolution of digital learning and well-being research, supporting the design of sustainable, human-centered and globally relevant educational ecosystems.
Purpose Artificial intelligence (AI) is transforming social structures, value systems and collective knowledge practices in ways comparable to transformative experiences, which fundamentally alter preferences and perspectives. This paper aims to examine how the conceptual framework of transformative experiences can inform societal responses to AI-driven change. It asks: how can the theory of transformative experiences guide collective decision-making and governance under conditions of epistemic uncertainty and value transformation associated with AI? The aim is to develop a conceptual framework for understanding AI as a collective transformative experience and for supporting more rational, foresight-oriented societal engagement with its impacts. Design/methodology/approach This study adopts a multidisciplinary conceptual approach, integrating insights from transformative experience theory, social epistemology, futures studies and AI governance literature. Firstly, key governance challenges (uncertainty, opacity and value instability) are identified through a focused analytical review. Secondly, structural analogies between individual transformative experiences and societal encounters with AI are developed. Thirdly, strategies for rational engagement with transformative experiences are translated into a phased governance framework comprising preparation, evaluation, implementation and reflection, with explicit alignment to established foresight methods and tools. Findings AI-induced societal change shares core features with transformative experiences, including deep epistemic uncertainty, limited ex ante evaluation and the potential for preference and value transformation. The analysis argues that, under these conditions, governance is likely to depend on collective epistemic processes rather than purely technical optimisation. On this basis, the paper proposes – as a conceptual contribution to be tested empirically – a four-phase governance model (preparation, evaluation, implementation and reflection) organising a representative and extensible taxonomy of 11 strategies, rather than a closed or exhaustive set, to support adaptive, participatory and learning-oriented governance. Integrating social epistemology foregrounds the potential importance of epistemic diversity, institutional learning and structured collective deliberation for managing AI-related transformation. The framework is stated in falsifiable terms, and its own operationalisation is offered for empirical scrutiny. Research limitations/implications The proposed framework is conceptual and requires empirical validation. This paper specifies explicit conditions under which the framework would be disconfirmed and identifies concrete empirical tests. Future research should test and refine the model through case-based studies of AI deployment in domains such as health care, public administration or autonomous systems. Empirical work is also needed to examine how epistemic institutions and participatory mechanisms influence collective learning under transformative technological conditions. Practical implications The framework offers guidance for policymakers and organisations seeking to structure decision processes under deep uncertainty. Recommended practices include anticipatory governance, experimental regulatory environments, multi-stakeholder deliberation, iterative evaluation and foresight-based learning mechanisms to support adaptive institutional responses. Social implications Viewing AI as a collective transformative experience emphasises the need for inclusive and reflexive governance that addresses value change, distributional effects and power asymmetries. Such an approach may help align AI development with evolving societal priorities related to fairness, accountability and human well-being. Originality/value This paper reconceptualises AI governance through the lens of collective transformative experience and integrates this perspective with social epistemology. By developing a phased model organising a representative taxonomy of strategies grounded in epistemic theory and aligned with foresight practices, it offers a novel socio-epistemic framework that extends beyond risk management and technical ethics towards adaptive, learning-oriented and futures-aware governance. The framework is presented reflexively and in testable form, inviting empirical evaluation of both its prescriptions and its own operationalisation.
Purpose Considering the importance and the long-standing role of Public Libraries (PLs) and the ever-increasing rate and intensity of socio-political, cultural and above all else technological changes, the future of PLs should be reimagined and their function and mission re-conceptualized. Although the alternative futures of PLs in the Global South could bear points of resemblance to those of the Global North, due to global mega-trends, relative socio-political homogeneity and technological convergence, local particularities could lead to divergent eventualities. This study aims to meet this objective. Design/methodology/approach Participatory action research and future-oriented action research (FAR) were deployed as our theoretical lenses. As for the method, Schwartzian steps of scenario-building were followed. A combination of social, technological, economic, environmental, political, value technique for horizon and environmental scanning; strengths, weaknesses, opportunities and threats (SWOT) analysis, foresight workshops, surveys and semistructured interviews was used to conduct this research. Findings In this research, the authors provide four scenarios of the future of PLs in Iran – as a case study in the Global South – in 2030. Participatory. The two key drivers of the future of PLs in Iran were chosen to be the conceptualization of PLs (service provider vs rhizome) and the essence of knowledge (consumptive vs experiential) which resulted in four scenarios: Co-LABoscope, Hubrary, Imitarium and Discoveria. Scenarios were quantified using speculations to provide a better comparison among these alternative scenarios and some strategic/tactical recommendations were made based on the initial SWOT analysis. Originality/value First, the multimethod case-studies using FAR are rare and this can be considered as one of the contributions of this research to the literature. Also, neologisms offered by the final scenarios can deconstruct and reconstruct how the future of PLs, in general, and education, in particular should be approached.
