Production Decisions Research Articles

A strategic optimizing carbon neutrality within profit and emission reduction efficiency: a stackelberg game analysis under a cap-and-trade scheme.

Carbon emissions (CO2e) are a main problem, and many countries are committed to reducing CO2e to attain carbon neutrality. To narrow this gap, this research considers green technology implementation (GTI) and CO2e quota in dual green gaming. The objective is to explore the integration of GTI and CO2e quotas into optimal production and pricing decisions in emission-generating companies (EGCs). To achieve this, a two-party simulation Stackelberg game model involving the CO2e strategy of EGCs and governments is proposed. We formulate a mathematical model and experimental methods to optimize EGCs' decision-making using neutral indicators. EGCs optimize production quantity, achieving CO2e reduction through ERE maximization. EGCs exhibit a strong commitment to ERE enhancement practices, enhancing profit and carbon-neutral goals. Our findings demonstrate the effectiveness of CO2e quotas and GTI as carbon-neutral indicators in EGCs, contributing to global CO2e reduction. Our research provides both literature and inspiration for global CO2e reduction efforts. Moreover, it aids governments in exploring optimal incentives and decisions for pricing and production. Last, this work enables EGCs to maximize profits and move toward a carbon-neutral environment.

Current constraints to reconcile tropical forest restoration and bioeconomy

AbstractLarge-scale forest restoration is vital for delivering a broad array of ecosystem services benefits to society. However, it is often perceived as an economically noncompetitive land use choice. Integrating economic opportunities into restoration aligns socioeconomic and environmental goals, reducing conflicts between forest production and conservation-oriented management decisions. Supply chains focusing on high-value goods can enhance the reach of forest restoration efforts and unite ecological and economic benefits in a multifunctional manner. The bioeconomy has emerged as a potential but critical driver for attracting investments in restoration. We outline the challenges and solutions to reconcile forest restoration and bioeconomy, specifically about (i) native timber production, (ii) non-timber forest products, (iii) biotechnological products, and (iv) intangible ecosystem services. This requires collaborative and multidisciplinary efforts to improve investment in large-scale projects. The intricacies of these issues intersect with research development, market dynamics, legal frameworks, and regulatory paradigms, underscoring the necessity for nuanced and tailored public policy interventions. These integrated approaches should enable tropical countries to lead the global forest-based economy and usher in a new era of forest restoration. Graphical abstract

Mitochondria and Alcohol-Associated Liver Disease: Pathogenic Role and Target for Therapy.

Alcohol-associated liver disease (ALD) is one of the leading causes of chronic liver disease and a major cause of liver-related death. ALD is a multifactorial disease triggered by the oxidative metabolism of alcohol which leads to the activation of multiple factors that promote the progression from steatosis to more advanced stages like alcohol-associated steatohepatitis (AH) that culminate in alcohol-associated cirrhosis and hepatocellular carcinoma. Poor understanding of the complex heterogeneous pathology of ALD has limited drug development for this disease. Alterations in mitochondrial performance are considered a crucial event in paving the progression of ALD due to the crucial role of mitochondria in energy production, intermediate metabolism, calcium homeostasis, and cell fate decisions. Therefore, understanding the role of mitochondria in eliciting steatosis and progression toward AH may open the door to new opportunities for treatment. In this review, we will cover the physiological function of mitochondria, its contribution to ALD in experimental models and human disease, and explore whether targeting mitochondria may represent a game changer in the treatment of ALD.

Impacts of agricultural production decisions on the safe and just operating space: A systematic literature review

Impacts of agricultural production decisions on the safe and just operating space: A systematic literature review

Shareholder primacy or stakeholder governance?

Externalities happen largely in the private sector and cannot be fully separated from production decisions. Decision-making in companies thus co-determines the degree of sustainability of an economy. Advances in impact valuation allow us to express the stakeholder interests in finance and valuation terms. We can thus compare investment decisions and payout decisions for three types of models: the shareholder value model, the shareholder welfare model, and the stakeholder model. Our results show that stakeholder-driven companies are better able to pursue a sustainable economy. Corporate governance should be adjusted accordingly.

A Study on the Production-Inventory Problem with Omni-Channel and Advance Sales Based on the Brand Owner’s Perspective

This study explores a supply chain product-inventory problem with advance sales under the omni-channel strategies (physical and online sales channels) based on the brand owner’s business model and develops corresponding models that have not been proposed in previous studies. In addition, because the brand owner is a member of the supply chain, and has different handling methods for defective products or products returned by customers in various retail channels, defective products or returned products are included in the supply chain models to comply with actual operating conditions and fill the research gap in the handling of defective/returned products. Regarding the mathematical model’s development, we first clarify the definition of model parameters and relevant data collection, and then establish the production-inventory models with omni-channel strategies and advance sales. The primary objective is to determine the optimal production, delivery, and replenishment decisions of the manufacturer, physical agent, and online e-commerce company in order to maximize the joint total profits of the entire supply chain system. Further, this study takes the supply chain system of mobile game steering wheel products as an example, uses data consistent with the actual situation to demonstrate the optimal solutions of the models, and conducts sensitivity analysis for the proposed model. The findings reveal that increased demand shortens the replenishment cycle and raises order quantity and shipment frequency in the physical channel, similar to the online channel during normal sales. However, during the online pre-order period, higher demand reduces order quantity and cycle length but still increases shipment frequency. Rising ordering or fixed shipping costs lead to higher order quantity and cycle length in both channels, but variable shipping costs in the online channel reduce them. Market price increases boost order quantity and frequency in the online channel, while customer return rates significantly impact inventory decisions.

Estimation of district-level spring barley yield in southern Sweden using multi-source satellite data and random forest approach

Remote sensing observations and artificial intelligence algorithms have emerged as key components for crop yield estimation at various scales during the past decades. However, the utilization of multi-source satellite data and machine learning for estimating aggregated crop yield at the regional level in Europe has been only scarcely explored. Our study aims to bridge this research gap by focusing on the district-level spring barley yield estimation in southern Sweden from 2017 to 2022. We developed an estimation method with the random forest (RF) approach using four satellite-derived products along with two climate variables. These variables were used individually and in combinations as inputs for the RF approach. The results showed that vegetation indices (VIs) outperformed solar-induced chlorophyll fluorescence (SIF) in barley yield estimation, while combining VIs and SIF variables achieved the highest model performance (R2 = 0.77, RMSE = 488 kg/ha). The inclusion of climate variables generally had little added contributions to the model performance. Importantly, barley yield prediction could be achieved two months prior to harvest, using monthly VIs and SIF data from April and May. Our study demonstrated the feasibility of using freely accessible satellite data and the machine learning approach for estimating crop yield at the pan-European regional level. We expect that our proposed methodology can be extended to different crop types and regional-scale crop yield estimation in Europe, benefiting national and local authorities in making agricultural productivity decisions.

Opera “Ruslan and Lyudmila” by M. Glinka: pages of history and modern times

The article, based on the works of musicologists, literary critics and music critics, examines the history of Glinka's fateful acquaintance with Pushkin, the birth of the opera Ruslan and Lyudmila, the reasons for the failure of its first production and modern directorial decisions of the play. The magical national poem-tale by A. Pushkin “Ruslan and Lyudmila”, despite the attacks of critics, enjoyed great success among contemporaries. Pushkin’s plot attracted Glinka because it opened up a wide scope for his melodic talent. Glinka listened to Pushkin's wishes and created a vivid performance with dance episodes, original stage solutions, lyrical line and emphasized originality of Russian images of Pushkin’s poem. At the same time, Glinka rejected Pushkin's irony, which permeates the poem, and composed a magical work dominated by music. We have a Pushkin plot in the absence of the Pushkin word. Ruslan and Lyudmila have been arguing about the opera for almost 200 years, there are several editions of the music.

Integrating Money Cycle Dynamics and Economocracy for Optimal Resource Allocation and Economic Stability

This paper integrates two theoretical frameworks to explore optimal resource allocation and the dynamics of the money cycle in a hypothetical economy. It examined the theoretical background of the problems of choice. The first framework considers an economy governed by an omniscient authority responsible for production and distribution decisions, focusing on the logic of choice and efficient resource allocation. The second framework introduces the concept of the new economic system of Economocracy, emphasizing the role of the Money Cycle theory in economic management and governance. By combining these frameworks, the paper provides a comprehensive understanding of productive and distributive efficiency and examines the impact of the money cycle on economic stability and growth. A mathematical modeling of the money cycle is presented to highlight the relationship between money distribution, economic capacity, and overall economic health. The integrated approach offers valuable insights for optimizing resource allocation and enhancing economic resilience.

Two-agent proportionate flowshop scheduling with deadlines: polynomial-time optimization algorithms

AbstractVolatility in the supply chain of critical products, notably the vaccine shortage during the pandemic, influences livelihoods and may lead to significant delays and long waiting times. Considering the capital- and time-intensive nature of capacity expansion plans, strategic operational production decisions are required best to address the supply-demand mismatches given the limited production resources. This research article investigates the production scenarios where the demand of one agent must be completed within a specified due date, hereinafter referred to as the deadline, while minimizing the maximum or total completion time of another agent's demand. For this purpose, the Two-Agent Proportionate Flowshop Scheduling Problem with deadlines is introduced. Two polynomial-time optimization algorithms are developed to solve these optimization problems. This study will serve as a basis for further developing this practical yet understudied scheduling problem.

Challenges to Empowerment of Women through Value Chains: The Need to Move from Individual to Relational Empowerment

ABSTRACTThis article examines the prevailing assumption by donors that connecting smallholder women to value chains will close the gender gap and empower women. Based on a case study of a programme that seeks to empower women through their integration into value chains in Vietnam, the article assesses women's empowerment across four dimensions: economic, psychological, social and political. The authors argue that women's engagement in value chains does not always financially benefit and empower women because patriarchal power structures within families, communities and businesses make it challenging for women to gain authority over production decisions in higher‐value crops. Women in the study gained more autonomy over ‘women's crops’ which yielded small incomes, while men had control over production that was seen as ‘men's work’, and in large‐scale and more lucrative production. Gendered power relations affect women's access to economic opportunities: in this context, development agencies should reconsider their approaches to women's economic empowerment by focusing on relational rather than individual empowerment. This means that women's economic empowerment programmes should involve both men and women, with targeted interventions ensuring women are empowered within the household and in their connections with the community, local authorities and businesses.

Farmers as prosumers: Evidence from cadmium‐contaminated rice in China

AbstractWe study farmer responses in rice production and consumption to China's cadmium‐contaminated rice (CCR) event in 2013. We show that the CCR event reduced both rice production and consumption but did not significantly affect the quantity and price of rice sold by farmers in areas affected by cadmium pollution. Households with young children reduced their rice production and consumption by a larger amount than others, whereas the responses are reversed for households with elderly people. The decrease in rice production was mainly driven by the decrease in farmers' consumption of self‐produced rice instead of through price or income channels, indicating that farmers are prosumers who make production decisions not purely to maximize profit but also to satisfy their own consumption needs. Farmers being prosumers helped promote production side responses to new information about food safety.

The evolution of two‐stage production and order equilibrium in a random yield supply chain with demand information updating

AbstractThe mismatch between production, order, and demand seriously affects supply chain performance. However, most research focus on the mismatch between the retailer's order and customer's demand, which ignores the influence of the supplier's random yield on supply chain members' decision‐making. This paper investigates a two‐stage optimization problem within a two‐echelon supply chain, featuring a supplier with random yield and a retailer updating demand information in real‐time. Faced with a long production lead time, the retailer can either place advance orders at the production season's onset (first‐stage advance order) or opt for instant orders at the beginning of the sales season (second‐stage instant order). To ensure timely order fulfillment, the supplier initially employs a cost‐effective regular production mode with random yield during the production season. If yields are insufficient during sales, a pricier emergency production mode with guaranteed output becomes available. Utilizing a dynamic programming approach, we formulate the two‐stage optimization problem to derive optimal production and order decisions. Our analysis uncovers how realized random yield and stochastic market signals influence emergency production and instant order quantities in the second stage. We compare expected profits in scenarios with perfect and imperfect market signals, probing the members' preferences regarding order strategies. An intriguing finding emerges: as instant wholesale prices rising, the supplier's preferred order strategy diverges from the retailer. By strategic adjustments to the instant wholesale price, we demonstrate the potential for unanimous agreement on preferred order strategies among supply chain members — a quality enhancing the chain's flexibility and performance. Moreover, we extend the model to hybrid order strategies and identify conditions for unanimous preference among the three strategies. To bolster our theoretical findings, we provide numerical examples, lending practical support to our study.

A choice-based approach to dynamic capacitated multi-item lot sizing with demand uncertainty

With the purpose of planning and implementing pricing decisions on a tactical level as well as production decisions on an operational level, we consider – in an integrated form – the capacitated multi-item lot sizing problem with uncertain item demands and price-dependent discrete choice demand. The model is embedded into an overarching rolling horizon procedure allowing for adaptations to changes in demand and cost parameters. We first formulate the static problem version as a nonlinear mathematical program with underlying multinomial logit demand and subsequently linearize it to make it viable for mathematical programming solvers. Uncertainty of demands is taken into account by Monte Carlo simulation. More specifically, we generate random demand scenarios and utilize them as input data for the sample average approximation problem version. We further endow the problem setting with possibilities to incorporate pricing policy requirements such as restricting the number of price adaptations or defining periods without price adaptations. Overall, the developed approach yields a powerful tool for balancing item demands via pricing in a way favorable for adhering to available production capacities and thereby striking a balance between revenues and costs. Computational results confirm that adapting prices to time-dependent demand and cost parameters is exploited effectively to maintain a deliberately controlled production environment. Moreover, the integrated pricing and production setting allows to study the effect of pricing policy restrictions and demand uncertainties upon attainable profits.

Reducing Phosphorus Loss in Short-Cycle Horticultural Production Using Activated Aluminum-Amended Substrates and Modified Fertigation Practices.

To support growth, short-cycle horticultural crops require readily available nutrients. However, this often leads to nutrient leaching. Implementing best management practices in production decisions like incorporating fertilizer retaining amendments to substrates or modifying fertilization programs can mitigate nutrient losses to the environment and associated costs. This study examined using an activated aluminum (AA) material as a substrate amendment to retain phosphorus (P) within containers while also assessing methods to reduce P fertilization in Tagetes production over a six-week production cycle. A commercial peat moss substrate (PL) pre-loaded with nutrients was amended with AA, enabling comparisons between substrates with and without AA. Enhanced fertilizer practices involved supplementing the initial nutrients by applying a weekly fertigation solution including nitrogen and potassium over the six weeks, but P for either 0, 2, 4, or 6 weeks. The incorporation of AA significantly reduced P leaching losses by 89.5-97.7%, compared to the PL substrates receiving P the entire six weeks. Regardless of substrate or fertilizer management, all Tagetes had equivalent sizes (growth index) and aboveground biomass. The results indicate that amending substrates with AA and/or reducing additional P inputs are effective strategies to minimize P leaching without compromising Tagetes quality.

Financing options for logistics firms considering product quality loss

Purpose This paper aims to investigate the impact of quality loss in transit on e-commerce supply chain pricing, production and financing decisions. Design/methodology/approach The authors consider a Stackelberg game model with a supplier, logistics firm and e-commerce platform. The logistics firm is capital-constrained and obtains funding from the e-commerce platform by debt financing or equity financing. Through backward induction, this paper first solves the equilibrium results under the two financing schemes and then reveals the financing preferences of all parties. Findings The results demonstrate that equity financing reduces financing costs and promotes production significantly. However, it may also lead to overproduction, particularly in markets with poor profitability and high cost factors. When the percentage of product quality loss is large, equity financing is preferable. With the increasing of transportation level, the benefits of debt finance are steadily growing. In addition, equity financing is the Pareto dominant scheme for all firms under certain circumstances. The extensions consider hybrid financing and another quality loss type. Practical implications The paper derives the equilibrium solutions and financing preferences, then specifies the threshold for applying financing schemes. Provide guidance for logistics firms’ finance model innovation and core enterprise involvement in the logistics industry. Originality/value The paper investigates how logistics firms’ financing strategies are impacted by product quality loss.

A MILP-based approach to address the production and distribution planning of large industrial gas supply chains

This paper focuses on addressing the Production Routing Problem (PRP) of industrial gas supply chains (SC). The work introduces a Mixed-Integer Linear Programming (MILP) based approach to effectively tackle this challenging problem. The proposed framework aims to increase company profits by optimizing both production and distribution activities simultaneously. For the distribution part, a route generation algorithm is employed to initially generate a set of feasible routes, ensuring that only routes with practical significance are considered. Subsequently, the mathematical model is developed considering only the set of routes generated. The formulation includes decisions associated with plants production levels, plant selection to supply the different consumers, clients to be visited per trip and day, quantity to be delivered and routes to be used. As part of the problem, it is considered that trucks can make several trips per day, as well as trips of several days. To take into account the last feature, the approach accounts for the explicit effect of the lead time on production and distribution decisions. In this way, the work allows for different delivery times for customers included in the same route, according to their inventories and usage levels. The model considers fleet unavailability until they return to the plants after finishing a trip. Finally, two case studies, one motivating and the other industrial size, are presented and solved. The results obtained demonstrate the effectiveness of the proposed approach to solve the case studies in reasonable CPU times.

Multi-agent platform to support trading decisions in the FOREX market

Trading decisions often encounter risk and uncertainty complexities, significantly influencing their overall performance. Recognizing the intricacies of this challenge, computational models within information systems have become essential to support and augment trading decisions. The paper introduces the concepts of trading software agents, investment strategies, and evaluation functions that automate the selection of the most suitable strategy in near real-time, offering the potential to enhance trading effectiveness. This approach holds the promise of significantly increasing the effectiveness of investments. The research also seeks to discern how changing market conditions influence the performance of these strategies, emphasizing that no single agent or strategy universally outperforms the rest. In summary, the overarching objective of this research is to contribute to the realm of financial decision-making by introducing a pragmatic platform and strategies tailored for traders, investors, and market participants in the FOREX market. Ultimately, this endeavor aims to empower people with more informed and productive trading decisions. The contributions of this work extend beyond the theoretical realm, demonstrating a commitment to address the practical challenges faced by traders and investors in real-time decision-making within the financial markets. This multidimensional approach to financial decision support promises to enhance investment effectiveness and contribute to the broader field of algorithmic trading.

Theoretical and methodological aspects of the analysis of the introduction of digital technologies into the practice of regional manufacturers

In the context of innovative transformations, information is a particularly valuable resource. And it is the need associated with obtaining reliable sources for the research base and making effective management decisions in production that has become the basis for the development of digital spheres of the economy. The purpose of this article is to consider issues related to evaluating the effectiveness of the introduction of digital technologies into modern production. The importance of considering the topic is due to the fact that many technological solutions are developed and implemented annually in all spheres of life. These innovations make it possible to radically change the conduct of business by automating some business processes, which, as a rule, helps to increase profits and reduce costs in the company.

Electrolyte jet tomography: Three-dimensional microstructure mapping with an electrochemical machine tool and an optical microscope

There is a general separation between the manufacturing processes that add value to materials on the factory floor and the techniques engineers use in the laboratory to evaluate the microstructures and the surface integrity that results. These techniques are often destructive or require a vacuum and are incompatible with production lines. However, this information has intrinsic value and could be exploited to inform production decisions during manufacture. In this study, a novel approach to acquire this information is presented that is underpinned by electrolyte jet machine tool coupled with optical microscopy, which can allow the extraction of both grain-wise partial orientation and morphological information, and crystallographic macro textures in three dimensions. Here, iterative sections are precisely machined into the near surface of a commercially pure titanium alloy using an electrochemical jet and subsequently imaged, allowing the reconstruction of high-fidelity microstructure models rapidly and under ambient conditions. In doing so, new insights into the specific orientation-dependent dissolution mechanisms are offered, and the acquisition of appropriate conditions that result in nanoscale roughness surfaces (avoiding the dominance of pitting and preferential grain removal) is firstly explored. Building on prior work, a piecewise approach is presented to analyse the acquired image stacks to map partial crystal orientations, while different approaches are proposed to account for jet-specific surface artefacts and waviness. This is repeated over 20 layers in an individual specimen and layer-wise orientation maps are used to construct volumetric models of the specimen. These data sets are then explored from the perspective of materials/manufacturing engineers, who may use to this information to effect advancements to materials processing technologies.