ABSTRACT This research aims to bring additional added value for the sustainable economic growth, namely how the past events and the neighbouring countries impact the worldwide economic dynamics and consequently the competitiveness conditions. Special emphasis was placed on tourism, given its global dynamics and its importance to the economy of some countries. To achieve these objectives, data from the World Bank was considered. The period analysed was from 2016 to 2023, considering data from 2015 to 2023 to calculate growth rates for employment and output (gross domestic product). This statistical information was assessed considering the developments associated with the Kaldor laws and the spatial autocorrelation approaches. The results highlight that the impacts of recent international events remain for the subsequent years and each country is influenced by the conjunctures of the neighbours. On the other hand, the tourism sector is of major importance to the world's economic sustainability, but its impact depends on the specifics of each circumstance and location. These are interesting insights to support policymakers in designing policies that are more adjusted to the current context, where the impacts of the past and of neighbouring countries cannot be ignored. On the other hand, the idea of tourism as an alternative driver of economic growth should be considered on a case‐by‐case basis. The originality of this study lies in the use of extended Keynesian cross‐section models with variables related to spatial effects and tourism to analyse the contexts associated with COVID‐19.

ABSTRACT This paper examines the drivers of radical green innovation (RGI) in Pakistan's textile manufacturing sector, with reference to environmental regulatory pressure (ERP), green market pressure (GMP), exploratory green learning (EGL), and big data analytics capability (BDAC). A quantitative research design was utilized, employing a self‐administered questionnaire to collect data from 313 employees across 20 textile manufacturing companies in Punjab, Pakistan. The descriptive statistics were done by SPSS 30.0, whereas structural equation modeling (SEM) was done by SmartPLS 4.1 to test the relationships between the key constructs. The analysis shows that GMP had a direct impact on EGL and RGI. ERP had no direct impact on EGL and RGI, indicating that regulatory compliance itself does not support radical green innovation. It is notable that BDAC had a negative moderating effect on the relationship between EGL and RGI, indicating that excessive use of data analytics may suppress the creative thinking required for radical green innovation. The study is the first to examine how the interaction of environmental regulatory pressure, green market pressure, exploratory green learning, and big data analytics capability affects radical green innovation within the textile industry of an emerging economy. To promote radical innovations, policymakers, managers, and decision‐makers should pay attention to the balance between data analytics and exploratory green learning. This balance can enable companies to be more aligned with market needs and regulatory conditions.

ABSTRACT Achieving sustainable economic growth in emerging economies remains challenging due to fragmented policy approaches linking circular economy practices, technological innovation, and renewable energy adoption. This study investigates the dynamic interactions among these sustainability pillars and their implications for long‐term economic development in five emerging Asian economies—Bangladesh, India, Vietnam, Indonesia, and the Philippines. Drawing on Ecological Modernization Theory and Endogenous Growth Theory, the study aims to examine both short‐run trade‐offs and long‐run complementarities among these variables. Using annual panel data from the World Development Indicators (1995–2024), the study employs a Generalized Method of Moments–Panel Vector Autoregression (GMM‐PVAR) framework to capture endogenous relationships, feedback effects, and dynamic adjustments. The findings reveal that technological innovation is the primary driver of sustainable economic growth and exhibits strong self‐reinforcing dynamics while also promoting circular economy development. In contrast, renewable energy adoption and economic growth initially exert negative effects on technological innovation, indicating short‐term trade‐offs; however, these effects transition into positive synergies over time. The circular economy demonstrates gradual and persistent influence across the system, although its short‐term effects remain limited. Furthermore, Granger causality results confirm that renewable energy adoption significantly predicts sustainable economic growth, while variance decomposition highlights the increasing long‐term contribution of circular economy practices and renewable energy. More importantly, the results underscore the importance of a phased and coordinated policy approach that balances short‐term trade‐offs with long‐term sustainability gains. The study contributes to the literature by providing a dynamic, system‐based understanding of sustainability transitions and offers practical insights for designing integrated policy frameworks in emerging economies.

ABSTRACT Cities and communities play important roles in sustainable development and climate change mitigation. This study presents a novel framework for developing carbon‐neutral visions for cities and communities. We established five “principles,” investigated options encompassing four parameters (management, goal setting, actions, and quantification), and introduced more detailed and technical “criteria” based on these principles. The five identified principles were that the framework should be universal, goal‐oriented, and implementable, and should have an appropriate spatial scale and encourage stakeholders. Then we draw recommendations based on the principles and criteria. We recommended, for example, not targeting consumption‐based emissions, that is, the Scope 3 emissions, because of limited information, differences in local government enforcement, and inconsistency across regions. However, resolving these issues can facilitate sustainable development in cities and communities. We applied the recommended method in Okuma Town, Fukushima Prefecture, Japan. Our study bridges the gap between the reality of local actions and the need to mitigate climate change at the global scale.

ABSTRACT Southeast Asia's coffee sector is a vital contributor to regional economies, sustaining rural livelihoods and accounting for a significant share of agricultural exports. This review analyses coffee communities in Vietnam, Indonesia, and the Philippines, focusing on the impacts of climate change and compounding stressors on production systems, as well as the adaptive strategies implemented by stakeholders. Rising temperatures, irregular rainfall patterns, and increased frequency of extreme weather events intensify risks for farmers, leading to reductions in both bean yields and overall quality. These challenges are compounded by structural vulnerabilities, including limited arable land, declining soil fertility, restricted financial resources, and reliance on outdated farming technologies, which undermine market competitiveness and impede long‐term community development. Despite these formidable challenges, Southeast Asia's coffee communities exhibit notable resilience through adaptive practices such as shade‐grown systems, intercropping, and improved farm management. The novelty of this review lies in identifying significant gaps in integrating long‐term climate adaptation strategies into national agricultural policies, which are essential for fostering resilience. Strengthening policy frameworks is critical for addressing climate‐related exposure while supporting sustainable coffee communities. Key recommendations include targeted policy interventions, broader adoption of sustainable agricultural practices, and enhanced value‐chain linkages. Furthermore, embedding climate adaptation within community‐based agricultural policies and expanding access to certification programmes will improve market opportunities for farmers. Overall, these findings underscore the importance of interdisciplinary research in informing these efforts, ensuring the sustainable development of the coffee sector, and addressing the specific risks faced by these communities while enhancing their resilience strategies.

ABSTRACT In the implementation of sustainable development goals (SDGs), researchers have greatly focused on factors such as human capital (HC), renewable energy (RE), economic growth (EG), and environmental preservation, which influence carbon (CO 2 ) emissions in South Asian countries, specifically Pakistan, India, and Bangladesh. This research uses secondary data points from 1990 to 2024 from World Development Indicators to investigate variable relationships in the airline sector of Pakistan, India, and Bangladesh. The collected data were analyzed by employing two analytical methods. First, it conducts stationarity tests through the Augmented Dickey‐Fuller to determine data stability. Second, the Autoregressive Distributed Lag (ARDL) model and System dynamic modeling (SD Modeling) via Python and Vensim software are used to analyze the impact of HC, RE, and EG on carbon emissions. The results reveal that both economic growth and renewable energy adoption, together with human capital investment, lead to diminished carbon emissions in South Asia. Research also demonstrates both the necessity of skilled personnel along with appropriate policy structures to achieve sustainable adoption of green technology that reduces airline sector CO 2 emissions. SD simulations determine that Pakistan, India, and Bangladesh require unified policies to integrate RE sources with enhanced education and climate management for sustainable airline growth. Thus, the work presents the systematic policy roadmap by which the governments in South Asia can operationalize SDG 7 and SDG 13 in the aviation industry by integrating clean energy transitions, institutional capacity building, and climate‐consistent regulatory reforms in sustainable aviation policies.

ABSTRACT As a nascent field, little is known about eco‐social policy, and to an even lesser extent, within emerging economies. This article examines how eco‐social policies are framed and practiced in this context using a Systematic Literature Review (SLR) of 20 peer‐reviewed articles, selected from an initial pool of 985 records following a multi‐stage screening and eligibility assessment process. The findings reveal that eco‐social policy in developing countries has evolved as a sub‐agenda within ongoing developmental expansion, operating alongside broader responses to structural complexities rooted in poverty, inequality, and labor informality. It is reflected in the central emphasis on preventive‐institutionalized measures (i.e., long‐term planning, community‐based resource governance, just transition strategies ), complemented by compensatory short‐term interventions (i.e., social assistance, job training, and climate‐related risk support ), aimed at realigning welfare regimes with environmental and social welfare objectives. Nevertheless, these policies are not conditioned to supporting industrial decarbonization, but instead function as risk reducers for the just transition and the climate crisis–particularly given widespread informality and (environmental‐related) structural vulnerability. Based on this pattern, the article argues that eco‐social policy in emerging economies most likely follows a green‐buffering rather than a production‐oriented, decarbonization‐driven trajectory characteristic of mature welfare states. The article concludes by outlining limitations and future research directions, calling for empirical testing and contextual refinement of the framework across diverse post‐colonial settings and emerging just transition coalitions.

ABSTRACT This study proposes a multidimensional framework to integrate Business Process Management (BPM) with the Sustainable Development Goals (SDGs), addressing gaps in research and practice. Through a bibliometric science mapping using keyword co‐occurrence network analysis in VOSviewer (Scopus 2015–2024), we identify five thematic clusters structuring the BPM–SDG interface. Beyond cluster identification, the analysis reveals structural imbalances, thematic fragmentation, and a predominant focus on SDGs 9 (Industry, Innovation and Infrastructure) and 12 (Responsible Consumption and Production), with comparatively limited integration of social dimensions. Combining quantitative co‐occurrence analysis with qualitative content review, we conduct an interpretive synthesis to derive a framework structured around four empirically grounded dimensions: Strategic, Operational, Social–Environmental, and Local–Global Scaling. Grounded in network‐derived evidence, the proposed model repositions sustainability as a multi‐level orchestration logic that extends BPM beyond efficiency optimization, integrating governance mechanisms, digital innovation, social equity, and cross‐scale coordination. The study advances BPM literature by reorganizing existing BPM constructs through a systemic SDG‐oriented lens, emphasizing the need for holistic approaches that balance economic, environmental, and social goals while providing actionable guidance for organizations and policymakers aligned with the 2030 Agenda.

ABSTRACT This study examines the influence of Environmental, Social, and Governance (ESG) performance, Green Innovation Practices (GIP), and Information Technology Capabilities (ITC) on Sustainable Business Performance (SBP) in the leather industry of Tamil Nadu, India. Using a hybrid methodological approach—combining Partial Least Squares Structural Equation Modeling (PLS‐SEM), SPSS, and Artificial Neural Networks (ANN)—the research captures both linear and complex non‐linear relationships among the variables. The results identify ESG performance as the most influential factor driving SBP, with GIP and ITC also contributing significantly. The study highlights the strategic importance of embedding strong ESG frameworks, fostering innovation through sustainable practices, and utilizing IT capabilities for operational efficiency and long‐term performance. It offers practical implications for industry leaders and policymakers aiming to enhance sustainability outcomes. While valuable, the study is limited by its regional and sector‐specific scope, reliance on cross‐sectional survey data, and the interpretability challenges of ANN. Future research should explore broader contexts and apply longitudinal approaches.

ABSTRACT The tourism sector faces pressing sustainability challenges, especially during crises. The rural communities reliant on ecotourism remain vulnerable, highlighting the need for responsible tourism. This study integrates social cognitive theory (SCT) and the elaboration likelihood model (ELM) to examine how self‐efficacy and outcome expectation influence attitude, intention, and ultimately responsible tourism behavior across economic, socio‐cultural, and environmental dimensions. Influencer credibility was proposed as a moderator of self‐efficacy‐attitude and outcome expectation‐attitude relationships. Using a survey of 383 ecotourists, data were analyzed through partial least squares structural equation modeling (PLS‐SEM), complemented by a post‐survey engagement for deeper insights. Results reveal that self‐efficacy and outcome expectation significantly influence attitude, which subsequently shapes intention and responsible tourism behavior. However, influencer credibility did not moderate the proposed relationships. This study advances SCT and ELM in responsible tourism and provides valuable guidance for policymakers and destination managers to promote sustainable practices.