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Despite the wide use of quantitative assessment to identify the relationship between green logistics (GL) practices and the sustainability performance (SP) of firms, results of these studies are inconsistent. A lack of theoretical foundation has been cited as a potential reason for these contradictory findings. This study aims to explore the relationship between GL practices and SP qualitatively and to provide a theoretical foundation for this link.

Following a multi-methodology approach, the authors used the grounded theory method (GTM) to investigate perceived relationships through qualitative analysis and adopted the system thinking (ST) approach to identify causal relationships using causal loop diagrams (CLDs).

The authors identified different sustainability practices under three major categories: logistics capabilities, resource-related practices and people-related practices. This analysis showed the relationships among these practices are non-linear. Based on the results, the authors developed three propositions and introduced a theoretical foundation for the relationship between GL practices and SP.

Managerial personnel can use the theoretical foundation provided by this study when making decisions on GL practices adoption. This theoretical foundation suggests applying a holistic approach that can help optimize SP by selecting suitable practices. On the other hand, researchers can use a multi-methodology approach suggested by this study to explore complex social issues.

This study contributes to the knowledge from a methodology perspective as no previous studies have been conducted to identifying the relationship between GL practices and SP by combining GTM and ST approaches. This combination can be extended to build system dynamics models for sustainable logistics impacts bringing novelty to the research field of sustainable logistics.

Emerging from the COVID-19 pandemic, the Philippines has undergone the “new normal” transition, creating a strategic recovery effort to reinvigorate the industry. In tourism, these transitions aim to safeguard employees' and guests' health and safety, ensure continuity of business operations, boost tourism confidence leading to satisfaction, and establish a resilient and sustainable tourism industry in the postpandemic era. Hence, this chapter employs a system thinking leveraging a causal loop diagram (CLD) to construct a comprehensive roadmap for Philippine tourism's postpandemic resurgence through the system thinking lens. The CLD visually illustrates the inter-related factors influencing the recovery process, encompassing collaborative engagements, innovations, economic revitalization, and health and safety protocols. By analyzing the causal relationships among these variables, this chapter explicates the dynamic and interconnected nature of the postpandemic recovery leading to the recovery of the Philippine tourism industry, especially in the context of thinking small. Through this chapter, thinking small could involve a shift toward localized solutions and community-focused initiatives that allow them to foster local economies, build resilience, and create a more inclusive and sustainable postpandemic recovery.

This study is conducted to understand an emerging public health problem in the garb of polycystic ovarian syndrome (PCOS) that affects about 6–21% of women in reproductive age from a systems perspective.

The research is conducted in two phases. In phase 1, 15 women suffering from PCOS were interviewed to generate a knowledge map using an interpretive phenomenological research approach. The emerging themes were divided into four categories, namely individual, familial, societal, organizational, medical and systemic. In phase 2, five workshops were conducted with six invited actors to generate a causal loop diagram (CLD) of PCOS. The Standards for Reporting Qualitative Research (SRQR) are used in this study.

A CLD from an individual's perspective with implications on organizational, societal and system levels.

Awareness of “lifestyle diseases” is increasing, and this research shall help future studies put PCOS in the larger psychosocial context. The geographical location of respondents can be a limitation, as the causal linkages could only be true for the research site.

The CLD provides a comprehensive understanding of complex emerging phenomenon of PCOS.

The paper draws attention to factors such as frequently changing doctors, withdrawal from work, medication fatigue, inclination to adopt due to infertility, etc.

This is the first such paper laying out the causal relationships between factors at the individual levels and connecting them to societal, organizational and system levels. This mapping can be useful for policymakers and industry leaders to empathize with PCOS sufferers so that their working conditions can be managed better.

The ripple effect (i.e. disruption propagation in networks) belongs to one of the central pillars in supply chain resilience and viability research, constituting a type of systemic disruption. A considerable body of knowledge has been developed for the last two decades to examine the ripple effect triggered by instantaneous disruptions, e.g. earthquakes or factory fires. In contrast, far less research has been devoted to study the ripple effect under long-term disruptions, such as in the wake of the COVID-19 pandemic.

This study qualitatively analyses secondary data on the ripple effects incurred in automotive and electronics supply chains. Through the analysis of five distinct case studies illustrating operational practices used by companies to cope with the ripple effect, we uncover a disruption propagation mechanism through the supply chains during the semiconductor shortage in 2020–2022.

Applying a theory elaboration approach, we sequence the triggers for the ripple effects induced by the semiconductor shortage. Second, the measures to mitigate the ripple effect employed by automotive and electronics companies are delineated with a cost-effectiveness analysis. Finally, the results are summarised and generalised into a causal loop diagram providing a more complete conceptualisation of long-term disruption propagation.

The results add to the academic discourse on appropriate mitigation strategies. They can help build scenarios for simulation and analytical models to inform decision-making as well as incorporate systemic risks from ripple effects into a normal operations mode. In addition, the findings provide practical recommendations for implementing short- and long-term measures during long-term disruptions.

Electrification is a promising solution for decarbonising the road freight transport system, but it is challenging to understand its impact on the system. The purpose of this research is to provide a system-level understanding of how electrification impacts the road freight transport system. The goal is to develop a model that illustrates the system and its dynamics, emphasising the importance of understanding these dynamics in order to comprehend the effects of electrification.

The main methodological contribution of the study is the combination of the multi-layer model with system dynamics methodology. A mixed methods approach is used, including group model building, impact analysis, and literature analysis.

The study presents a conceptual multi-layer dynamic model, illustrating the complex causal relationships between variables in the different layers and how electrification impacts the system. It distinguishes between direct and induced impacts, along with potential policy interventions. Moreover, two causal loop diagrams (CLDs) provide practical insights: one explores factors influencing electric truck attractiveness, and the other illustrates the trade-off between battery size and fast charging infrastructure for electric trucks.

The study provides stakeholders, particularly policymakers, with a system-level understanding of the different impacts of electrification and their ripple effects. This understanding is crucial for making strategic decisions and steering the transition towards a sustainable road freight transport system.

This paper studies digitalization projects aiming to increase the share of regional food in the hospitality sector and communal catering. The focus is set on influencing factors and underlying feedback structures that arise through the digitalization of regional food supplies. The results can guide stakeholders to get a better understanding of key influencing factors and complexities from a holistic perspective.

A systems thinking approach is employed to model regional food networks. The influencing factors were found in the literature and in two model regions. Feedback loops and underlying structures were explained and validated through semi-structured interviews. Findings are visualized in causal loop diagrams (CLDs) and are used for theory development.

The presentation in CLDs helps understanding the influence of digital logistics platforms on the entire system of regional food supply and not just on isolated parts. Among others, cooperation, trust and digital solutions were identified as key success factors when aiming to increase the share of regional food in the hospitality sector and communal catering.

The work focused on the underlying feedback structures occurring in regional food supply in two, rural Bavarian regions in Germany with their unique geographical settings. Findings may, consequently, not be entirely transferable to other regions with varying characteristics. Further research needs to be done to see how much these regional parameters influence digital logistics platforms.

The paper contributes to the existing scientific literature by showing the impact coming from digital logistics platforms on regional food supply systems. Developing CLDs provides a basis for future work and facilitates discussion for researchers and practitioners to support future real-world implementations.