Sustainability Performance Research Articles

Unveiling the dynamic capabilities' influence on sustainable performance in MSMEs: a systematic literature review utilizing ADO-TCM analysis

Unveiling the dynamic capabilities' influence on sustainable performance in MSMEs: a systematic literature review utilizing ADO-TCM analysis

The Impact of Green Transformational Leadership on Sustainable Performance in Pakistan’s Manufacturing Sector: The Mediation Effect of Green Innovation

The Impact of Green Transformational Leadership on Sustainable Performance in Pakistan’s Manufacturing Sector: The Mediation Effect of Green Innovation

Does Environmental, Social and Governance Disclosure Practices Promote Customer Brand Perception? The Moderating Effect of Customers’ Sustainability Responsiveness

Environmental, social and governance (ESG) aspects have garnered considerable attention in corporate management on a global scale in recent times. As a result, researchers have paid notable attention to this subject. Though numerous studies have already explored various aspects of ESG in the context of emerging economies like Bangladesh, there is limited evidence on whether ESG practices promote customer brand perception (CBP). This study measures the impact of ESG on CBP deploying structural equation modeling in an emerging economy by analyzing the responses of 450 samples in accordance with the philosophies of triple bottom line theory and signaling theory. The results indicate that sustainability responsiveness, social and environmental disclosure practices, and CBP are positively impacted. Customers’ enhanced level of sustainability responsiveness strengthens the influence of governance disclosures in choosing a brand, while weakens the impact of environmental and social disclosures. However, the study concludes there is no significant effect of governance disclosures on CBP. The findings also reveal that social issues have the strongest impact on CBP among the ESG parameters. As sustainability concerns increase, customers either demand more sustainability performance from brands or their impression of the brands declines correspondingly. The study outlines a customer’s viewpoint on the requirements of ESG and sustainability concerns, which will contribute organizations to adopt appropriate ESG strategies and address sustainability challenges to win over customers and strengthen their brand image.

Sustainability Performance Reporting

Sustainability reporting is an essential tool for companies and organizations to assess and communicate their sustainability performance. Its importance derives from the need for transparency and accountability to stakeholders, including investors, customers, employees and local communities. The principles underlying an effective sustainability report include integrity, accuracy, comparability and clarity. The main purpose of the sustainability report is to provide a clear view of the economic, social and environmental impact of the organization’s activities, contributing to continuous performance improvement and alignment with international standards. The objective of our study is to analyze sustainability reporting and ESG (environment, social, governance) reporting, key steps and methods for measuring and reporting sustainability, and the sustainability policy criteria and reporting frameworks used internationally (GRI, IIRC, SASB, TCFD, ISO 26000, ISO 14016) in order to identify areas for further development to improve the relevance and effectiveness of sustainability reporting. The results obtained from our study enable a better understanding of how an organization reports its social, economic, and environmental impact, the differences in compliance with the international standards used, the main steps, and sustainability criteria followed. Our research highlights the necessary actions and steps through which sustainability reporting can become a more effective and relevant tool, contributing to real sustainable development and more responsible resource management. The usefulness of this report is reflected in many aspects: it facilitates informed decision making, enhances trust and reputation, helps identify risks and opportunities, and supports sustainable business strategies. The sustainability report is not only a means of reporting but also a catalyst for positive change, promoting responsible business practices and contributing to global sustainable development.

Responsible Environmental Management: Sustainable Strategy Models for the Future

The aim of this study is to explore the relationship between responsible en- vironmental management and business performance, emphasizing sustainable strategy models that enhance both environmental sustainability and profitability in modern organizations. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS, data were collected from 150 medium to large organizations across multiple industries, including manufacturing, retail, and energy sectors, all of which have implemented formal environmental man- agement initiatives. The findings reveal a statistically significant positive impact of responsible environmental management on both environmental sustainability (β = 0.72, p < 0.01) and business performance (β = 0.65, p < 0.01). Addi- tionally, environmental sustainability was found to positively influence business performance (β = 0.54, p < 0.01). These results validate the relevance of models such as the Triple Bottom Line and Circular Economy, providing action- able insights for companies aiming to enhance competitiveness while achieving sustainability goals. This study highlights the practical implications for busi- ness leaders and policymakers, particularly in fostering sustainable practices that align with both regulatory demands and long-term profitability. Future research is recommended to explore the longitudinal impacts of these strategies across different sectors and regulatory environments.

RETRACTION: The impact of sustainable development strategy on sustainable supply chain firm performance in the digital transformation era

RETRACTION: K. Nayal , R. D. Raut , V. S. Yadav , P. Priyadarshinee and B. E. Narkhede , “,” Business Strategy and the Environment 31, no. (2022): 845–859, https://onlinelibrary.wiley.com/doi/10.1002/bse.2921 The above article, published online on 26 October 2021 in Wiley Online Library (wileyonlinelibrary.com), and a corresponding Corrigendum, published on 21 April 2024 (https://doi.org/10.1002/bse.3783), has been retracted by agreement between the journal Editor‐in‐Chief, Richard Welford; ERP Environment; and John Wiley & Sons Ltd. The retraction has been agreed due to errors in the statistical analysis presented in Table 4. Despite the previously produced Corrigendum, errors are still evident. The authors provided an explanation; however, this was not regarded as satisfactory. As a result, the editors consider the results and conclusions in this article unreliable. The authors disagree with the retraction.

PROMOTING HANDICRAFT FAMILY BUSINESS THROUGH DIGITAL MARKETING TOWARDS SUSTAINABLE PERFORMANCE

The study aims to determine the dimensions of the adoption intention of digital marketing in handicraft family businesses towards business performance, as well as technological innovation applications in the family business for sustainable development. This study examines the theoretical insights and designs a conceptual framework based on previous studies of handicraft family businesses. In so doing, 290 survey data were collected from handicraft business owners and tourists by using face-to-face interviews through a structured questionnaire with 82.85% valid response rate. Moreover, structural equation modeling (SEM) was used to analyze data and find out the causal relationship among the constructs and hypothesis testing. As per the results of the study, among the 6 hypotheses paths all were supported along wit h 24 relationship path coefficients were noteworthy. The result shows that perceived ease of use, perceived risk, perceived usefulness, social norms, perceived behavioral control, and attitude radically influence to the adoption of digital marketing in han dicraft family businesses. The results of this study will assist the research scholars through theory and theoretical foundation for family business owners in understanding and comprehending the role of digital marketing in sustainable family business performance. Similarly, the legacy of family businesses in handicrafts or small businesses can be maintained and empowered through digital marketing to boost the economy. The study is the foremost one in discovering a sustainable business strategy through the success factors of digital marketing adoption in family businesses.

Promoting sustainable wastewater treatment operations: The role of lean practices and lean six sigma enablers

Promoting sustainable wastewater treatment operations: The role of lean practices and lean six sigma enablers

Theoretical design and synthesis of Co30Ni60/CC for high selective methanol oxidation assisted energy-saving hydrogen production

The integration of methanol oxidation reaction (MOR) with hydrogen evolution reaction (HER) represents an advanced approach to hydrogen production technology. Nonetheless, the rational design and synthesis of bifunctional catalysts for both MOR and HER with exceptional activity, stability and selectivity present formidable challenges. In this work, firstly, density functional theory (DFT) was utilized to design and evaluate material models with high performance for both MOR and HER. Secondly, guided by DFT, Co30Ni60/CC (CC, carbon cloth) composites with a leaf-like nanosheet structure were successfully fabricated via electrodeposition. In the MOR process, Ni acts as the predominant active center, while Co amplifies the electrochemically active surface area (ECSA) and enhances the selectivity of methanol oxidation. Conversely, in the HER process, Co serves as the primary active center, with Ni augmenting the charge transfer rate. The electrochemical results demonstrate that Co30Ni60/CC exhibits exceptional performance in both MOR and HER at a current density (j) of 10 mA cm−2, with peak potentials of 1.323 V and −95 mV, respectively. Additionally, it shows remarkable selectivity for the oxidiation of methanol to high value-added formic acid. Thirdly, following a 100 h chronopotentiometry (CP) test, the required potential demonstrates an increase of 4.9 % (MOR) and 8.1 % (HER), signifying the superior stability of Co30Ni60/CC compared to those reported in the literature. The exceptional performance of Co30Ni60/CC can be primarily attributed to that the leaf-like nanosheets structure not only exposes a plethora of active sites but also facilitates electrolyte diffusion, the monolithic structure prepared by electrodeposition enhances its stability, and the transfer of electrons from Co to Ni regulates its electronic structure, as corroborated by X-ray photoelectron spectroscopy (XPS) and density of states (DOS) analyses. Finally, at the same j, the voltage required by the Co30Ni60/CC||Co30Ni60/CC electrolytic cell, powered by an electrochemical workstation, is 198 mV lower than that required for alkaline water-splitting. Meanwhile, at higher j (100 mA cm−2), the electrolytic cell exhibits sustained and stable operation for 150 h, enabling high-efficiency hydrogen production and the synthesis of high value-added formic acid.

End-to-end AI pipeline optimization: Benchmarking and performance enhancement techniques for recommendation systems

End-to-end AI pipeline optimization is critical for improving the efficiency and performance of recommendation systems, which play a pivotal role in personalizing user experiences across various domains. This review explores benchmarking and performance enhancement techniques tailored to recommendation systems within AI pipelines. The objective is to streamline the processes involved in data ingestion, feature engineering, model training, and deployment to achieve optimal system performance and user satisfaction. Recommendation systems typically involve complex workflows that require continuous optimization. Benchmarking serves as a foundational step, enabling the identification of bottlenecks and inefficiencies within the pipeline. By establishing clear performance metrics, such as precision, recall, and latency, benchmarking allows for the comparative analysis of different algorithms, data processing methods, and system configurations. These metrics guide the selection of the most suitable models and techniques, thereby enhancing overall system effectiveness. Performance enhancement techniques are then applied to various stages of the AI pipeline. Advanced methods in feature engineering, such as automated feature selection and dimensionality reduction, can significantly improve model accuracy while reducing computational overhead. In the model training phase, techniques like hyperparameter tuning, gradient-based optimization, and distributed training are employed to accelerate convergence and improve model generalization. Additionally, optimization strategies at the deployment stage, including model compression, quantization, and the use of specialized hardware, are crucial for minimizing latency and resource consumption. This review also highlights the importance of continuous monitoring and feedback loops to maintain the effectiveness of recommendation systems in dynamic environments. By integrating real-time analytics and adaptive algorithms, systems can adjust to changing user behaviors and preferences, ensuring sustained performance improvements. In conclusion, optimizing end-to-end AI pipelines for recommendation systems involves a multifaceted approach that includes benchmarking, feature engineering, model training, and deployment enhancements. These efforts collectively contribute to more efficient, scalable, and accurate recommendation systems, ultimately leading to better user experiences and operational efficiencies. This paper will focus on optimizing AI pipelines for recommendation systems, covering the entire process from data extraction and feature engineering to model deployment and performance benchmarking. It will discuss techniques for identifying and mitigating performance bottlenecks in different computing environments, providing valuable insights for enhancing the efficiency of recommendation systems, which are crucial for various applications.

Exploring the Potential Synergies between Industry 5.0 and Green Lean Six Sigma for Sustainable Performance: A New Dimension of Operational Excellence

Today's companies are adopting a sustainable strategy, often in a reactive manner, to respond to customer demands, stakeholder concerns, and compliance with regulatory requirements, while seeking to proactively maintain a strong standing in the future market. This article explores the synergies between Industry 5.0 technologies and Green Lean Six Sigma (GLSS), highlighting how their integration can catalyse sustainable transformations in manufacturing. The study combines a literature review with empirical survey conducted across companies in various industrial sectors. The objective is to identify and examine potential synergies between Industry 5.0 technologies and Green Lean Six Sigma tools to improve the environmental impact of manufacturing companies. The results highlight the importance of Industry 5.0 technologies in boosting the efficiency of GLSS, thereby promoting more sustainable manufacturing practices. Key areas of synergy include sustainable process optimization, energy efficiency, sustainable personalization, data analytics for sustainability, and sustainable innovation. This article emphasizes the mutual benefits of integrating Industry 5.0 technologies with the Green Lean Six Sigma methodological framework. This combination reduces the consumption of materials and resources, improves energy efficiency, and stimulates innovation in favor of eco-responsible production. It calls for an integrated approach, considering technology, human resources, and processes, to enable manufacturing companies to achieve optimized operational performance while contributing to environmental sustainability.

Impact of regional investment on the sustainable development goals: A group analysis of economic and territorial development

AbstractThe European Green Deal aims at increasing the sustainability of European economic sectors to mitigate the effects of climate change. Complementing this initiative, the Next Generation EU (NGEU) program, whose budget will exceed 800 billion € by 2026, is not merely a recovery plan but also a catalyst for green technologies and sustainable activities. Within this framework, Italy stands as the largest beneficiary of funds. The present study explored the distribution to date of 194.4 billion € NGEU funds across Italian regions and the Sustainable Development Goals (SDGs) that have received the most significant attention as a result of this funding. Leveraging multiple comprehensive datasets, including one encompassing more than 306,706 measures and sub‐measures, the analysis revealed that 55.5 billion € was directed towards Italy's “Green Revolution and Ecological Transition,” with a further 104.1 billion € allocated towards (predominantly) SDGs 7 and 9. Moreover, 70.3 billion € was directed towards southern Italy (including the islands), while 81.0 billion € was allocated to the north. Although the population in the north is approximately one‐third larger than that of the south, on a per capita basis, the north received 2930 € while the south received a significantly greater sum of 3470 €. Thus, the NGEU has not significantly reduced the north–south divide in economic terms. Furthermore, some southern regions have shown satisfactory sustainability performance, despite receiving a relatively lower allocation of NGEU funds. The “Made in Italy” initiative may represent a strategic approach to increasing competitiveness in the global and digital markets and fostering fraternity among Italian regions. The present research offers valuable insights into the regional distribution of funds and their impact on sustainable development, suggesting that territorial gaps may be mitigated through a pragmatic, community‐based approach.

Remote Sensing, Artificial Intelligence and Smart Agriculture Technology Trends of the Future

The efficient and sustainable operation of the agricultural sector has become increasingly important in light of the transformations brought about by the third and fourth industrial revolutions. Population growth, increasing food demand, rising input costs, and environmental pressures necessitate innovative approaches not only to ensure food security but also to mitigate the effects of climate change. The European Union (EU) emphasizes the role of digital technologies in supporting agricultural productivity and resilience by promoting a bio-based economy. Strategies such as Farm to Fork (F2F) initiative aim to reduce pesticide and nutrient inputs, thus preserving biodiversity and supporting ecosystem health. Artificial intelligence (AI) and predictive analytics, along with connected sensors, offer opportunities to optimize water and nutrient usage and increase crop yields. By utilizing AI, combining remote sensing technologies, and monitoring changes in land use, it is possible to reduce environmental risks associated with agricultural practices. Although there are challenges such as high investment costs and data control for the integration of digital technologies, ongoing research and development efforts promise to overcome these obstacles. In conclusion, the integration of digital technologies into agriculture presents unique opportunities to address urgent issues and achieve sustainability goals. This review discusses the applicability of fundamental technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Precision Agriculture (PA), and Machine Learning (ML) in making agriculture more efficient and sustainable, by enabling the perception, monitoring, collection, analysis, and extraction of meaningful insights from agricultural data.

Sustainable Operation Strategy for Wet Flue Gas Desulfurization at a Coal-Fired Power Plant via an Improved Many-Objective Optimization

Coal-fired power plants account for a large share of the power generation market in China. The mainstream method of desulfurization employed in the coal-fired power generation sector now is wet flue gas desulfurization. This process is known to have a high cost and be energy-/materially intensive. Due to the complicated desulfurization mechanism, it is challenging to improve the overall sustainability profile involving energy-, cost-, and resource-relevant objectives via traditional mechanistic models. As such, the present study formulated a data-driven many-objective model for the sustainability of the desulfurization process. We preprocessed the actual operation data collected from the desulfurization tower in a domestic ultra-supercritical coal-fired power plant with a 600 MW unit. The extreme random forest algorithm was adopted to approximate the objective functions as prediction models for four objectives, namely, desulfurization efficiency, unit power consumption, limestone supply, and unit operation cost. Three metrics were utilized to evaluate the performance of prediction. Then, we incorporated differential evolution and non-dominated sorting genetic algorithm-III to optimize the multiple parameters and obtain the Pareto front. The results indicated that the correlation coefficient (R2) values of the prediction models were greater than 0.97. Compared with the original operation condition, the operation under optimized parameters could improve the desulfurization efficiency by 0.25% on average and reduce energy, cost, and slurry consumption significantly. This study would help develop operation strategies to improve the sustainability of coal-fired power plants.

CSR and Sustainable Environmental Performance: An Exploration of Mediating and Moderating Factors

Taking into consideration the moderating role of perceived organizational support within the framework of the natural resource-based view (RBV) theory, the purpose of this study is to investigate the connection between corporate social responsibility (CSR) and sustainable environmental performance. Specifically, this study focuses on the roles that green capability and green transformational leadership play as mediators in this relationship. Through the use of a survey questionnaire, information was collected from 420 employees working for small- and medium-sized enterprises (SMEs) in Bangladesh. The data were analyzed with the help of AMOS and SPSS. The findings indicate that the level of CSR has a significant impact on the performance of sustainable environmental practices. To a large extent, green capability and green transformational leadership serve as mediators in the relationship between CSR and sustainable environmental performance. Furthermore, perceived organizational support plays a significant role in moderating the relationship between CSR and sustainable environmental performance. The relationship between green transformational leadership and sustainable environmental performance is also significantly moderated by perceived organizational support. This is a significant contributor to the connection. This multidimensional corporate social responsibility model can be used to assess sustainable environmental performance in both industrialized and developing countries, and it can also be extended to other service sectors, according to the theoretical conclusion that can be drawn from the research. This research demonstrates that there is a direct connection between corporate social responsibility and sustainable environmental performance. As a result, practitioners are able to develop strategies that are effective in terms of corporate social responsibility. These findings should be taken into consideration by policymakers and managers who are dedicated to promoting equitable development of the country.

Modelling the Influence of Management Practices on Sustainable Market Performance in Serbian Enterprises

In the evolving global market, new business conditions necessitate that enterprises adapt and construct organizational structures grounded in new principles and the implementation of contemporary management methods. This is particularly crucial for enterprises in transitional economies, which need to be highly flexible and innovative to meet the increasing demands of users swiftly, employ modern management techniques, and gain a competitive edge. The modern business environment assumes that there are very few products, technologies, services, knowledge areas, or procedures unavailable to interested groups worldwide. This study examines the influence of modern management methods and techniques (MMMTs), human resource management (HRM), quality management (QM), and intellectual capital management (ICM) on the sustainable market performance (SMPC) of these enterprises. A structured survey was conducted among 146 managers from various Serbian industrial enterprises, and the data were analyzed using descriptive statistics, Pearson correlation analysis, linear regression, and multicollinearity tests. The results revealed significant positive correlations between MMMTs, HRM, QM, ICM, and SMPC, with quality management having the highest impact. These findings provide valuable insights for improving business competitiveness in Serbia’s industrial sector. The results also support the development of an integrated model for sustainable management practices in transitional economies.

Creating a Responsible Renewable Energy Investment Model for the MENA Region's Low-Carbon Transition

Addressing climate change presents specific challenges for the countries of the Middle East and North Africa (MENA), particularly concerning oil production and water scarcity, but it also offers opportunities for new paths toward sustainability. The transition to low-carbon energy raises significant concerns for oil and gas producers in the MENA region, especially regarding their dependence on hydrocarbon revenues. Without proper adjustments, this transition could worsen macroeconomic imbalances and potentially threaten existing social contracts. Policymakers are working to promote various renewable energy sources and implementation strategies to mitigate the adverse effects of climate change. As a result, the development of an index capable of accurately measuring and benchmarking a country's overall sustainability and economic performance becomes essential. This index should provide a comprehensive assessment of both the current and future state of renewable energy. Additionally, it must highlight key environmental, social, governance (ESG), and economic factors within the renewable energy sector. This proposal aims to establish a composite index, referred to as the Renewable Energy Responsible Investment Index (RERII), covering 19 countries and utilizing 22 distinct metrics. The RERII trend is calculated from 2010 to 2019. The proposed index can serve as a screening tool, decision-making aid, benchmarking instrument, and guide for sustainable development.

Debtholders' reaction to sustainability reporting regulations: International evidence

AbstractThis study investigates the impact of mandatory sustainability reporting on the affected firms' debt financing costs. Leveraging sustainability disclosure regulations enacted in 36 jurisdictions from 1998 to 2022 and using a staggered difference‐in‐differences empirical approach, we find that the regulation adoption firms experience a reduction in the debt financing cost subsequent to the mandate. Channel tests reveal that the benefit of a lower cost of debt is driven by greater transparency on sustainable practices and improved sustainability performance, which lead to a lower level of default risk stemming from sustainability‐related concerns. Cross‐sectional analyses further indicate that the debt financing cost reduction effect is more pronounced if the sustainability reporting regulations are issued by a government institution, on a full compliance basis, and with stronger enforcement. Our results provide policymakers with further evidence on the ongoing discussion about the effectiveness of sustainability disclosure mandates.

The Impact of Logistics Integration on Supply Chain Performance: The Moderating Role of Information Sharing

Purpose: The study aims to assess the influence of logistics integration on supply chain performance, as well as the function of information sharing plays in that connection among supply chain partners in a vital section of Ghana's economy (the Energy Sector). Methodology: The study employed quantitative approach and adopted the explanatory research designs in the investigation. The research population targets senior management staff of energy firms operating within the Greater Accra Region. The study used convenience sampling approach to select a total of 111 employees from the population. Structured survey questionnaire was used as a data collection instrument to gather primary data from respondents. Data technique used were descriptive and inferential analysis and structural equation modelling using IBM SPSS (version 26) and Amos version 23. Findings: The study found that: a) logistics integration has a significant and positive effect on supply chain performance; b) information sharing correlates positively and significantly with supply chain performance; c) information sharing does not have any influence of the relationship between supply chain performance and logistics integration. Unique Contribution to Theory, Policy, and Practice: The study recommends that, supply chain managers to utilize technology as part of the strategic objectives to attain supply chain performance across their operations and lastly, managers are encouraged to promote successful information flow across the chain using design for disassembly principles, source effective communication, and supplier need-to-know policies. The study concludes that future studies are urged to create a research model that takes into account the comprehensive definition of sustainability, including its economic, social, and environmental elements, in order to fill in gaps in the literature and fill them. Future research is also urged to take into account how industrial innovation mediates the link between sustainability and other important outcome variables including sustainability performance, cost performance, customer happiness, and environmental performance.

Reward exploitation or exploration? The effects of local government sustainability strategies and performance information on citizen evaluation

ABSTRACT Given the growing attention on citizen involvement in local sustainability, this study explores how citizens evaluate government sustainability performance stemming from exploitation (established policies) and exploration strategies (pioneering initiatives). Our survey experiment finds that positive sustainability performance resulting from exploitation achieves more favourable citizen evaluations compared to exploration. Negative sustainability performance does not moderate the associations between sustainability strategies and public assessments. Furthermore, Republicans, individuals with low climate beliefs, Hispanics, and low-income citizens prefer exploitation over exploration. As an early attempt to examine citizen preferences for organizational strategies, this study extends performance management research by linking organizational strategies with performance.