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The promotion of autonomous vehicles introduces privacy and security risks, underscoring the pressing need for responsible innovation implementation. To more effectively address the societal risks posed by autonomous vehicles, considering collaborative engagement of key stakeholders is essential. This study aims to provide insights into the governance of potential privacy and security issues in the innovation of autonomous driving technology by analyzing the micro-level decision-making processes of various stakeholders.

For this study, the authors use a nuanced approach, integrating key stakeholder theory, perceived value theory and prospect theory. The study constructs a model based on evolutionary game for the privacy and security governance mechanism of autonomous vehicles, involving enterprises, governments and consumers.

The governance of privacy and security in autonomous driving technology is influenced by key stakeholders’ decision-making behaviors and pivotal factors such as perceived value factors. The study finds that the governmental is influenced to a lesser extent by the decisions of other stakeholders, and factors such as risk preference coefficient, which contribute to perceived value, have a more significant influence than appearance factors like participation costs.

This study lacks an investigation into the risk sensitivity of various stakeholders in different scenarios.

The study delineates the roles and behaviors of key stakeholders and contributes valuable insights toward addressing pertinent risk concerns within the governance of autonomous vehicles. Through the study, the practical application of Responsible Innovation theory has been enriched, addressing the shortcomings in the analysis of micro-level processes within the framework of evolutionary game.

This study aims to explore the relationship between risk governance characteristics (chief risk officer [CRO], chief financial officer [CFO] and senior directors [SENIOR]) and regulatory adjustments (RAs) in Organization for Economic Cooperation and Development public commercial banks.

Using principal component analysis (PCA) and regression models, the research analyzes a representative data set of these banks.

A significant negative correlation between risk governance characteristics and RAs is found. Sensitivity analysis on the regulatory Tier 1 capital ratio and the total capital ratio indicates mixed outcomes, suggesting a complex relationship that warrants further exploration.

The study’s limited sample size calls for further research to confirm findings and explore risk governance’s impact on banks’ capital structures.

Enhanced risk governance could reduce RAs, influencing banking policy.

The study advocates for improved banking regulatory practices, potentially increasing sector stability and public trust.

This study contributes to understanding risk governance’s role in regulatory compliance, offering insights for policymaking in banking.

This paper analyzes two external costs often associated with port development, cost to fisheries from marine dredge disposal and damages from air pollution, using estimates of development and operation for a proposed (but since cancelled) container port as a case study. For dredge disposal, a bio-economic model was used to assess short- and long-term and indirect (joodweb) damages to fisheries from marine disposal of clean sediments. In the case of air pollution, estimates of annual activity levels and emission coefficients are used to estimate incremental annual emissions of three key pollutants (NOx, HC and CO) for trucks, trains, yard vehicles, and vessels. These estimates allow for phasing in of strict new air pollution regulations. For both external costs, sensitivity analyses are used to reflect uncertainty. Estimates of shadow values in year 2002 dollars amount from $0.094 per cubic yard to $0.169 per cubic yard of clean dredged material for the selected disposal site and from $0.0584 per mile (jor current control standards) to $ 0. 0023 per mile (after phasing in of new regulations) for air pollution from heavy trucks.

From the quantum game perspective, this paper aims to study a green product optimal pricing problem of the dual-channel supply chain under the cooperation of the retailer and manufacturer to reduce carbon emissions.

The decentralized and centralized decision-making optimal prices and profits are obtained by establishing the classical and quantum game models. Then the classical game and quantum game are compared.

When the quantum entanglement is greater than 0, the selling prices of the quantum model are higher than the classical model. Through theoretical research and numerical analysis results, centralized decision-making is more economical and efficient than decentralized decision-making. Publicity and education on carbon emission reduction for consumers will help consumers accept carbon emission reduction products with slightly higher prices. When the emission reduction increases too fast, the cost of emission reduction will form a significant burden and affect the profits of manufacturers and supply chain systems.

From the perspective of the quantum game, the author explores the optimal prices of green product and compares them with the classical game.

The main purpose of this study resides essentially in the development of a new tool to quantify the biomass in the bioreactor operating under steady state conditions.

Modeling is the most relevant tool for understanding the functioning of some complex processes such as biological wastewater treatment. A steady state model equation of activated sludge model 1 (ASM1) was developed, especially for autotrophic biomass (XBA) and for oxygen uptake rate (OUR). Furthermore, a respirometric measurement, under steady state and endogenous conditions, was used as a new tool for quantifying the viable biomass concentration in the bioreactor.

The developed steady state equations simplified the sensitivity analysis and allowed the autotrophic biomass (XBA) quantification. Indeed, the XBA concentration was approximately 212 mg COD/L and 454 mgCOD/L for SRT, equal to 20 and 40 d, respectively. Under the steady state condition, monitoring of endogenous OUR permitted biomass quantification in the bioreactor. Comparing XBA obtained by the steady state equation and respirometric tool indicated a percentage deviation of about 3 to 13%. Modeling bioreactor using GPS-X showed an excellent agreement between simulation and experimental measurements concerning the XBA evolution.

These results confirmed the importance of respirometric measurements as a simple and available tool for quantifying biomass.

To recover the growing deficit between American and near-peer mobile artillery ranges, the US Army is exploring the use of the M982 Excalibur munition, a family of long-range precision projectiles. This paper aims to analyze the effectiveness of the M982 in comparison to the M795 and M549A1 projectiles to further the understanding of what this new asset contributes.

Based upon doctrinal scenarios for target destruction, a statistical analysis is performed using Monte Carlo simulation to identify a likely probability of kill ratio for the M982. A values-based hierarchical modeling approach is then used to differentiate the M982 from similar-type projectiles quantitatively in terms of several different attributes. Finally, sensitivity analyzes are presented for each of the value attributes, to identify areas where measures may lack robustness in precision.

Based upon a set of seven value measures, such as maximum range, effective range, the expected number of rounds to destroy a target, and the unit cost of a munition, the M982 1a-2 was found to be best suited for engaging point and small area targets. It is noted, however, that the M795 and M549A1 projectiles are likely better munition options for large area targets. Hence, an integrated targeting plan may best optimize the force’s weapon systems against a near-peer adversary.

The findings provide initial evidence that doctrinal adjustments in how the Army uses its artillery systems may be beneficial in facing near-peer adversaries. In addition, the values-based modeling approach offered in this research provides a framework for which similar technological advances may be examined.

This paper aims to explore effective supply chain principles, through the theory of transaction cost economics, as measures to improve current contingency pharmaceutical item shortfalls in the Air Force Medical Service (AFMS) Contingency Pharmaceutical Programme.

In this research, AFMS contingency pharmaceutical data was collected from various databases, including the Joint Medical Asset Repository, Medical Contingency Requirements Workflow and the Medical Requirements List. Through the methodology of cost-benefit analysis, alternative sourcing and fulfilment practices are evaluated.

The findings of this research indicate that the application of centralized purchasing principles, in an effort to leverage prime vendor contract fill rates for shortage items, can lead to 12%–17% increases in pharmaceutical material availability across the programme.

This research clearly shows that consolidating demand for shortage items across Active Duty War Reserve Material assemblages, though applications of centralized purchasing principles that leverage prime vendor contract fill rates, can lead to substantial increases in material availability at costs that justify the calculated benefits.

The purpose of this paper is to explore the impact of supply capacity constraint, water delivery loss and fairness concern on the operational decisions/efficiency of the IBWT supply chain under the random precipitation.

Two game-theoretic decision models for the IBWT supply chain coordination considering water delivery loss without/with fairness concern under the supply capacity constraint and random precipitation are developed, analyzed and compared. On this basis, the corresponding numerical analyses are conducted and compared to derive the corresponding management insights and policy implications.

The research results indicate that the two-part tariff contract could effectively coordinate the IBWT supply chain and achieve operational performance improvement; the binding supply capacity constraint makes the water capacity to be allocated among IBWT distributors in accordance with fair shortage allocation rule and reduces the profit (or utility) of the IBWT supply chain and its members; the existence of fairness concern reduces the utility of the IBWT supply chain and its members; a lower precipitation utilization factor in the case with non-binding capacity constraint is beneficial for improving the profit/utility of the IBWT supply chain while a higher precipitation utilization factor in the case with binding capacity constraint is beneficial for improving the profit/utility of the IBWT supply chain; and reducing the water delivery loss rate, the mainline transfer cost, the branch-line transfer cost, the holding cost and the shortage cost and setting a higher retail price are beneficial for improving the profit/utility of the IBWT supply chain.

Two innovative coordination decision models under random precipitation are developed, analyzed and compared through game-theoretic approaches to investigate the impact of supply capacity constraint, water delivery loss and fairness concern on the operational decisions/efficiency of the IBWT supply chain, which have enhanced the optimization decision theory for the operations management of IBWT projects and provided a better decision support for the IBWT stakeholders to make better operations strategies.

Food supply chain (FSC) in Greece is dominated by small and medium-sized enterprises (SMEs), who face several challenges in adopting green practices. The purpose of this paper is to identify the key drivers and barriers influencing the environmental performance of SMEs within the Greek dairy supply chain (SC).

Descriptive research methodology attempts to prioritize the drivers and barriers for improving the environmental sustainability performance. Analytical hierarchy process and sensitivity analysis are used to understand the complex nature of the influencing factors.

The analysis identifies five barriers and six drivers for the implementation of green practices within the dairy SC. While external drivers significantly influence the market structure and logistics network, government, competitors and customers are the driving factors for improving environmental performance.

The study contributes to filling the literature gap on key factors influencing the implementation of green practices within the FSC. The identified influential factors will contribute toward building a framework for improving sustainability performance within the Greek dairy SC.

The study is expected to benefit the Greek and European SMEs by driving their environmental practices within the perishable SC network.

The paper provides directions for researchers, practitioners and policy makers in understanding the challenges for implementing green practices in the dairy SC. The holistic approach followed in this paper is a building block for a conceptual framework on implementing environmental sustainability within the FSC. Apart from contributing to the current literature by extending the research horizon to SMEs’ green adoption capability, this study also provides better understanding of the pivotal role of internal and external key factors in influencing sustainability performance.