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In the aftermath of the COVID-19 pandemic, supply chains have become important policy tools to ensure the security and resilience of regional trading blocs of major economies. The US government’s focus on supply chains for selected strategic industries and the EU Commission’s renewed efforts to strengthen its supply chains using ‘sustainability standards’ coincides with the global trend in the shift towards digital and low-carbon economies. Furthermore, the rising tensions between the US and China, with no signs of reconciliation over key issues of contention, have emphasized the need for more credibility and trust in global supply chains. However, such policies also have the potential to serve as new barriers to participation in supply chains by less-developed economies which are not yet prepared to meet the high-level sustainability criteria which aim for higher protection of the environment and labor rights. There also seems to be an apparent shift in paradigm supporting the interventionist role of government that emphasize the need for more discretion for policy objectives that pursue societal and democratic values, not to mention national security interests. The current rules of international trade, however, do not sufficiently address these new issues and need to be realigned in order to meet the new demands. The current ‘rules of the game’ need to be reinforced in order to accommodate the rising need of countries for increased consideration of issues of sustainability and competitiveness.

The purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.

The network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.

The selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions.

This study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.

This concluding chapter summarizes the critical insights that changemakers ought to consider in their attempt to lead and manage cocreation processes and enhance their impact. The chapter also addresses three crucial challenges to the advent of a sustainable future: the need to rethink the assumptions of mainstream economics, the need to secure political stability in times of rapid societal change; and the demand for the deepening democracy. Finally, the chapter argues that local efforts to build a sustainable future will only succeed if key economic, political, and democratic challenges are effectively dealt with at the global and national levels.

In an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance. Our study delves into this complex backdrop, focusing on the intricate interplay the between traditional and emerging energy sectors.

This study analyzes the interconnections among green financial assets, renewable energy markets, the geopolitical risk index and cryptocurrency carbon emissions from December 19, 2017 to February 15, 2023. We investigate these relationships using a novel time-frequency connectedness approach and machine learning methodology.

Our findings reveal that green energy stocks, except the PBW, exhibit the highest net transmission of volatility, followed by COAL. In contrast, CARBON emerges as the primary net recipient of volatility, followed by fuel energy assets. The frequency decomposition results also indicate that the long-term components serve as the primary source of directional volatility spillover, suggesting that volatility transmission among green stocks and energy assets tends to occur over a more extended period. The SHapley additive exPlanations (SHAP) results show that the green and fuel energy markets are negatively connected with geopolitical risks (GPRs). The results obtained through the SHAP analysis confirm the novel time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness findings. The CARBON and PBW markets consistently experience spillover shocks from other markets in short and long-term horizons. The role of crude oil as a receiver or transmitter of shocks varies over time.

Green financial assets and clean energy play significant roles in the financial markets and reduce geopolitical risk. Our study employs a time-frequency connectedness approach to assess the interconnections among four markets' families: fuel, renewable energy, green stocks and carbon markets. We utilize the novel TVP-VAR approach, which allows for flexibility and enables us to measure net pairwise connectedness in both short and long-term horizons.

The purpose of this paper is to open up new lines of research into the engagement of corporations during humanitarian crises. The paper provides an introduction to core concepts in the delivery of humanitarian assistance, as well as a comprehensive overview of when, why, how, and to what effect corporations engage in humanitarian action.

Building on extant literature and policy reports, the paper synthesizes concepts and insights to map the interdisciplinary field of research on corporate engagement in humanitarian action.

The paper systematically reviews and describes different dimensions of corporate engagement for delivering humanitarian action and explains key complications that inspire new research questions. In particular, the paper highlights challenges associated with getting corporations to engage in humanitarian action; challenges associated with ensuring effective corporate engagement; and challenges associated with ensuring ethical engagement.

By raising new questions about corporate engagement in humanitarian action, this paper develops an original and positive research agenda for international business, management research, and related fields.

The paper aims to propose a new mathematical model for allocation and scheduling of vessels at multiple marine container terminals of the same port, considering the access channel depth variations by time of day.

This paper proposes a new mathematical model for allocation and scheduling of vessels at multiple marine container terminals of the same port, considering the access channel depth variations by time of day. The access channel serves as a gate for vessels entering or leaving the port. During low-depth tidal periods the vessels with deep drafts have to wait until the depth of the access channel reaches the required depth.

A number of numerical experiments are performed using the operational data collected from Port of Bandar Abbas (Iran). Results demonstrate that the suggested methodology is able to improve the existing port operations and significantly decrease delayed vessel departures.

The contribution of this study to the state of the art is a novel mathematical model for allocation and scheduling of vessels at multiple terminals of the same port, taking into consideration channel depth variations by time of day. To the best of the authors’ knowledge, this is the first continuous berth scheduling linear model that addresses the tidal effects on berth scheduling (both in terms of vessel arrival and departure at/from the berth) at multiple marine container terminals.