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As sustainable performance has a central role in the small and medium enterprises (SMEs) performance literature, this study aims to examine the influence of networking capabilities in enhancing sustainable performance through knowledge workers’ productivity and digital innovation. It also examines the sequential mediating role of knowledge workers’ productivity and digital innovation on networking capabilities and SMEs’ sustainable performance relationship.

Data were collected from 308 knowledge workers in the information technology sector and analyzed using the Hayes Process Macro bootstrapping method to test the proposed hypotheses.

Results indicate that knowledge workers’ productivity and digital innovation individually and sequentially mediate the relationship between networking capabilities and SME’s sustainable (economic and environmental) performance, surprisingly, they do not act as a mediator between networking capability and SME’s social performance. SMEs should prioritize investments in the professional development of their knowledge workers through training and skill enhancement programs. This investment equips knowledge workers with the tools to effectively use the knowledge and resources acquired through networking. Thus, knowledge workers may improve performance by using these resources to tackle challenges.

Although this research focused on this specific context, it is prudent to acknowledge that additional factors may also exert influence on sustainable performance within SMEs, factors that managers may consider when making decisions. Methodologically, the cross-sectional design of this research poses a potential limitation, as it does not allow for the complete elimination of endogeneity concerns. However, it is worth noting that scholars have endorsed the use of cross-sectional data in cases where management researchers aim to expand beyond well-documented and longitudinal data sets.

This research offers practical recommendations for SMEs to improve their sustainable performance through networking. SMEs should seek partnerships with complementary knowledge to improve operations and for other performance-oriented benefits.

This study adds significantly to the literature on sustainable SME performance by studying the interdependent effects of networking capabilities. It also represents the individual and sequential mediation mechanism that links networking capabilities to SME success through knowledge worker productivity and digital innovation.

Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a trade-off between financial and environmental aspects of these decisions, this paper aims to determine an optimal location, among candidate locations, of a new logistics center, its capacity, as well as optimal network flows for an existing distribution network, while concurrently minimizing the total logistics cost and gas emission. In addition, uncertainty in transportation and warehousing costs are considered.

The problem is formulated as a fuzzy multiobjective mathematical model. The effectiveness of this model is demonstrated using an industrial case study. The problem instance is a four-echelon distribution network with 22 products and a planning horizon of 20 periods. The model is solved by using the min–max and augmented ε-constraint methods with CPLEX as the solver. In addition to illustrating model’s applicability, the effect of choosing a new warehouse in the model is investigated through a scenario analysis.

For the applicability of the model, the results indicate that the augmented ε-constraint approach provides a set of Pareto solutions, which represents the ideal trade-off between the total logistics cost and gas emission. Through a case study problem instance, the augmented ε-constraint approach is recommended for similar network design problems. From a scenario analysis, when the operational cost of the new warehouse is within a specific fraction of the warehousing cost of third-party warehouses, the solution with the new warehouse outperforms that without the new warehouse with respective to financial and environmental objectives.

The proposed model is an effective decision support tool for management, who would like to assess the impact of network planning decisions on the performance of their supply chains with respect to both financial and environmental aspects under uncertainty.

An emerging body of literature has pinpointed the role of supply chain structure in influencing the extent to which supply chain members disclose information about their internal practices and performance. Nevertheless, empirical research investigating the effects of firm-level relational embeddedness on network-level transparency still lags. Drawing on social network analysis, this research examines the effect of relational embeddedness on supply chain transparency and the contingent role of digitalization in the context of environmental, social and governance (ESG) information disclosure.

In their empirical analysis, the authors collected secondary data from the Bloomberg database about 2,229 firms and 14,007 ties organized in 107 extended supply chains. The authors employed supplier and customer concentration metrics to measure relational embeddedness and performed multiple econometric models to test the hypothesis.

The authors found a positive effect of supplier concentration on supply chain transparency, but the effect of customer concentration was not significant. Additionally, the digitalization of focal firms reinforced the impact of supplier concentration on supply chain transparency.

The study findings contribute by underscoring the critical effect of relational embeddedness on supply chain transparency, extending prior literature on social network analysis, providing compelling evidence for the intersection of digitalization and supply chain management, and drawing important implications for practices.

Introduction: Sustainable marketing practices foster a company and its stakeholders’ environmental, social, and economic well-being while promoting products and services. An integrated approach to sustainability recognises these three interdependent pillars, seeking to unite together. Investing in renewable energy has triple-bottom-line benefits – reducing greenhouse gas emissions, creating jobs, and promoting economic growth. Sustainable marketing practices can be a win-win for companies and the environment.

Need of the Study: Studying and understanding the sustainable development goals (SDGs) are crucial for India and worldwide. Sustainable marketing is becoming increasingly important for companies as they seek to meet the growing demand for sustainable products and services. Sustainable marketing practices can help businesses reduce environmental impact, promoting eco-friendly products and services.

Purpose of the Study: The study focused on achieving the SDGs requires addressing all three pillars of sustainability together. The study explored the different sustainable marketing practices that companies adopt worldwide, how they contribute to environmental, social and economic stability, the benefits of such practices, and the challenges companies face in implementing them.

Methodology: The study is based on secondary data – 10 companies, out of which 5 brands are among the top 10 brands (Souromi, 2023) and 5 are within the top 20 international sustainable brands (Fashinza, 2020) belonging to the textile industry worldwide, were chosen and their sustainable marketing practices were identified and analysed.

Findings: The study highlights standard sustainable marketing practices adopted by different companies worldwide in the textile industry, exploring the contribution of sustainable marketing practices in achieving SDGs.

The purpose of this study is to propose a research model based on the stimulus–organism–response (S–O–R) model to examine whether network externality, personalization and sociability as environmental feature antecedents to learners’ learning engagement (LE) can influence their learning persistence (LP) in massive open online courses (MOOCs).

Sample data for this study were collected from learners who had experience in taking MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 371 usable questionnaires were analyzed using structural equation modeling in this study.

This study proved that learners’ perceived network externality, personalization and sociability in MOOCs positively affected their cognitive LE, psychological LE and social LE elicited by MOOCs, which jointly led to their LP in MOOCs. The results support all proposed hypotheses, and the research model accounts for 76.2% of the variance in learners’ LP in MOOCs.

This study uses the S–O–R model as a theoretical base to construct learners’ LP in MOOCs as a series of the inner process, which is affected by network externality, personalization and sociability. It is worth noting that three psychological constructs including cognitive LE, psychological LE and social LE are used to represent learners’ organismic states of MOOCs usage. To date, hedonic/utilitarian concepts are more often adopted as organisms in previous studies using the S–O–R model, and psychological constructs have received lesser attention. Hence, this study’ contribution on the application of capturing psychological constructs for completely expounding three types of environmental features as antecedents to learners’ LP in MOOCs is well documented.

Introduction: This study investigates the COVID-19 pandemic’s effects on the sustainability of the supply chain. It investigates how modern supply networks and procedures were equipped for such a catastrophe, and the pandemic’s effects on the environment, highlighting the significance of studying resilience and sustainability concurrently.

Purpose: The study acknowledges the importance of environmental sustainability for businesses and the need to examine trends in organisational, customer, policy, and distribution networks.

Need for the Study: The COVID-19 pandemic has significantly impacted supply chains. This study aims to provide insight into the long-term repercussions of the crisis and the importance of incorporating environmental considerations.

Methodology: The study uses a mixed-methods approach to evaluate the effects of the COVID-19 pandemic on supply networks and environmental sustainability indices. Data from industry reports, governmental publications, polls, and qualitative research techniques have been gathered.

Findings: The results of this study advance our understanding of how to preserve supply chains in the wake of the COVID-19 pandemic. It highlights the need for enhanced resilience and sustainability measures, expose the flaws and weaknesses of contemporary supply networks, and uncover developing patterns and tactics in customer behaviour, policy frameworks, distribution networks, and supply chain management.

Practical Implications: The COVID-19 pandemic has provided businesses, decision makers, and researchers with guidance on handling its potential and challenges – increasing the supply chain’s resistance to future interruptions, incorporating environmentally friendly practises, developing policies to support resilient and sustainable supply chains, adapting to changing consumer tastes, increasing effectiveness, and minimising the environmental impact of distribution networks.

This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

With technological innovation elements and the competitive market environment becoming increasingly complex, numerous firms utilize network embeddedness to achieve and sustain innovation. However, empirical research has not conclusively established which form of network embeddedness more effectively facilitates corporate innovation. Drawing on the heterogeneous network resources perspective, this study explores the impact of market network embeddedness, technology network embeddedness and their synergy on the green innovation performance of manufacturing small and medium-sized enterprises (SMEs). Furthermore, it investigates the moderating role of resource orchestration capability in these relationships.

Through an online questionnaire survey of Chinese manufacturing SMEs, 293 sample data were collected, and the hierarchical regression analysis was conducted to test the hypothesis.

The results indicate that market and technology network embeddedness significantly enhance green innovation performance, with the former exerting a more significant impact. Furthermore, the synergy between market and technology network embeddedness positively influences green innovation performance. Additionally, resource orchestration capability strengthens the positive effects of both market and technology network embeddedness on green innovation performance, while the moderating effect of resource orchestration capability on the relationship between the synergy of the two and green innovation performance was insignificant.

The study faced many limitations, such as collecting primary data, which relied on a questionnaire only, using cross-sectional data and examining only manufacturing SMEs.

Based on the heterogeneous network resources perspective and integrating social network theory and resource orchestration theory, this study explores the impact of network embeddedness on the green innovation performance of manufacturing SMEs, which sheds new light on the network embeddedness research framework and also enriches the antecedents of green innovation. In addition, this study provides implications on how manufacturing SMEs effectively utilize network embeddedness and resource orchestration capability to enhance green innovation performance.

In this article, the authors analyse a complex social process affecting historic public paths in rural areas in southern Spain. Despite the fact that urban populations are demanding the enhancement of this type of natural heritage for tourism, sports and recreational use, some parts of the network have been abandoned or usurped.

The study is multidisciplinary, comprising three interlinked studies. The cartographic study comprises an inventory of public paths in rural areas based on administrative sources. The legal study analyses local, regional and national regulations governing agricultural, environmental, heritage, sports and tourism uses of the infrastructure. The sociological study analyses social discourses on the uses of public paths, and identifies conflicts between farmers, landowners, environmentalists, sportspeople and tourists.

The preliminary results identified an important public paths network in Andalusia, approximately 160,000 km. The legal study found that there are laws regulating use, although local authorities do not monitor compliance or provide solutions to enhance management. The sociological study determined the attribution of environmental, cultural and economic value to public paths, but also the existence of conflicts between rural and urban populations.

Given that this is ongoing research, only state of the art and some preliminary albeit sufficiently consistent results are presented.

The results could help to guide public policy and governance of public paths.

Public paths promote rural development and a green/sustainable economy.

The research results and conclusions are original.

Green practices are essential for sustainability. However, it is challenging due to the socioeconomic and environmental concerns. Similarly, after the induced SDG-12 and SDG-13 by United Nations, the pressure groups forced manufacturers to consider sustainability. Therefore, this research aims to examine the sustainability through multifaceted green functions in manufacturing is examined.

Data were collected from 293 supply chain professionals of manufacturers from a developing economy. Hypotheses were tested through a quantitative method using partial least squares-structural equation modeling with the help of SmartPLS version 4 to validate the measurement model.

The findings revealed that all six direct hypotheses were supported. However, out of four hypotheses of mediation, one was not supported. Besides, a sequential mediation of green supply chain environmental cooperation and green human resource management was supported. The findings illustrated that green supply chain practices positively influence all used variables.

This research provides practical insight to practitioners to implement green practices in their supply chain networks for social, economic and environmental sustainability and compliance with SDG-12 and SDG-13. The sustainability was validated in a higher-order construct (HOC) (formative), including sequential mediation in the model with the support of resource dependency theory. Therefore, this study adds substantial literature to the existing body of knowledge.

This research provides an interdisciplinary framework by adding knowledge to the Resource Dependency Theory to address Sustainable Development Goals-12 (SDGs) and SDG-13. Likewise, this research provides an extension towards the body of knowledge on the issue, which can be used in future research and critical examinations for cleaner and sustainable production. So far, in Pakistan, no research has looked at the function of these integrated variables in the manufacturing industry with a diligent focus on sustainability as it was validated in a higher-order construct (formative) with one sequential mediation, which makes this research unique.