ObjectiveIn March 2025, a rare incident of acute group poisoning due to naphtha vapor inhalation occurred in Shandong, China. This study aimed to analyze the clinical data of patients exposed to mixed asphyxiating gases to enhance awareness of relevant personnel in industrial production and emergency medical staff.MethodsAn on-site investigation and laboratory testing were conducted to examine the poisoning incident. The clinical data of three patients poisoned by asphyxiating gases after inhaling naphtha vapor were retrospectively analyzed.ResultsPatients were primarily exposed to naphtha vapor through the respiratory tract. The main clinical manifestations were respiratory failure and neurological symptoms, such as impaired consciousness. Chest computed tomography and cranial magnetic resonance imaging revealed varying degrees of injury in all three patients, primarily characterized by hypoxic–ischemic brain lesions, pulmonary inflammation, and exudation. Laboratory tests showed arterial blood gas hypoxemia, abnormal white blood cell count, and an increased neutrophil ratio. After mechanical ventilation, glucocorticoid pulse therapy, and neurotrophic treatment, one patient recovered fully within 7 days, one exhibited persistent decorticate symptoms, and one continued to experience respiratory failure requiring mechanical ventilation. All three patients survived.ConclusionInhalation of naphtha vapor led to varying degrees of respiratory failure and neurological impairment in all three patients. Based on on - site sampling analysis and laboratory tests, it was determined that this incident was a poisoning incident caused by inhalation of a mixed gas mainly composed of hydrogen sulfide and alkane gases due to non - compliant operations. Early electrocardiogram monitoring combined with imaging evaluation played a crucial role in guiding clinical management and improving outcomes.
In response to the growing demand for eco-friendly materials and low-impact technologies, a study was conducted on the ultra-fine grinding of basalt in vibratory mills, with the basalt used for the experiments originating from the Targowica basalt quarry. Two types of basalt were used in the study: fine basalt consisting of particles with a size below 200 µm, agglomerated into lumps smaller than 100 mm, and aggregate with a particle size below 5 mm. The objective was to obtain a high proportion of the 0-10 µm particle size fraction, applicable in agriculture, construction, and environmental protection. Grinding tests were carried out for two types of feed material and different sets of grinding media. The best results were obtained using a mixture of steel grinding balls (Ø12 and 17.5 mm) with the addition of 0.4% polypropylene glycol, aimed at reducing agglomeration and improving grinding efficiency. In batch-mode operation, up to 70.5% of the 0-10 µm fraction was achieved. Although continuous grinding produced lower results (up to 44% of the 0-10 µm fraction), it demonstrated industrial implementation potential, especially after introducing chamber aeration and a modified material discharge method. The research confirmed the high industrial potential and effectiveness of vibratory grinding of basalt powder and indicated directions for further studies.
The widespread prevalence of opioids has prompted governments to implement targeted interventions aimed at reducing overdose mortality, with naloxone accessibility emerging as one of the most prominent policies. Naloxone, a potent opioid antagonist, is highly effective in reversing overdoses, yet its expanded availability introduces complex trade-offs, particularly in the presence of moral hazard. We develop a dynamic compartmental model that captures transitions between susceptible individuals and those with opioid use disorder, allowing us to evaluate the impact of naloxone accessibility on overdose mortality and to derive the optimal accessibility policy. We show that full naloxone accessibility is optimal in the absence of moral hazard or when its effect is small. However, when moral hazard is significant—where greater access to naloxone encourages riskier opioid use—expanded accessibility can paradoxically increase overdose deaths. Extending the model to incorporate peer-driven contagion in opioid misuse, we find that the structure of the optimal policy remains robust, preserving the bang–bang nature and the reversal induced by moral hazard. Two additional insights emerge under this interaction-based model. First, in epidemics primarily driven by prescription-induced opioid use, full accessibility remains optimal. In contrast, when opioid use spreads socially—especially as the effectiveness of naloxone declines due to potent synthetic opioids like carfentanil—limited accessibility may become preferable. Second, the relationship between naloxone accessibility and overdose mortality may become nonmonotonic, exhibiting an inverted U-shape in which moderate increases in accessibility can initially worsen outcomes. A calibrated case study based on U.S. data suggests that under current epidemic conditions, full accessibility remains optimal—a finding that aligns with existing regulatory policies. However, our results highlight that shifts in epidemic dynamics, such as increased opioid potency, may fundamentally alter this conclusion. These findings underscore the need for continuous reevaluation of naloxone distribution policies as the opioid crisis evolves.
In this paper, we explore the effectiveness of late penalties in reducing patient tardiness. Specifically, we evaluate two types of penalties: the last-place penalty (i.e., assigning late-arriving patients to the end of the queue) and the fixed-place penalty (i.e., moving late patients back by a fixed number of positions), under two conditions—absence of a time recommendation and presence of an explicit time recommendation. We conducted a randomized controlled trial involving 9,573 patient visits at a partner hospital in Asia. Our findings indicate that the fixed-place penalty has no significant impact on patient tardiness. In contrast, the last-place penalty significantly reduces patients’ late rate and encourages earlier arrival, particularly when no time recommendation is provided. When combined with a time recommendation, the last-place penalty continues to lower the late rate but does not further shift arrival times earlier. We also find that the last-place penalty is effective in increasing the patient’s compliance with the time recommendation. We further implemented the last-place penalty in the partner hospital across a broader dataset involving 61,829 visits, yielding consistent results.
Michael P Johnson, Samanthi Dijkstra-Silva, Tayo Fabusuyi
et al.
Diversity, equity, and inclusion (DEI) has received increasing attention as an organizing principle and rallying point for critical analysis and advocacy across many fields of study, embracing teaching, scholarship, organization design, and professional service. Within operations research (OR), operations management (OM), supply chain management (SCM), and related fields, DEI can provide a deeper understanding of the research enterprise: what research questions are asked, how the questions are answered through research design and analytic methods, and how the knowledge gained can influence scholarship and practice. However, the OR/OM/SCM literature on DEI is fragmented and a systematic review of where we stand is missing. In this paper, we adopt principles of systematic analysis to select and examine a wide range of peer-reviewed research in OR, OM, and SCM using qualitative and quantitative methods. We develop baseline metrics that represent the presence of DEI principles in published research and, through discussion of specific papers, identify opportunities for research to meaningfully engage with DEI principles and discuss specific ways that authors’ work reflects DEI principles. We develop principles for DEI and race- and social justice-aware research in OR/OM/SCM, provide guidance for institutions to support an enabling environment for DEI-aware research, discuss a range of research opportunities in DEI-infused OR/OM/SCM, and explain how critical theory can enhance DEI-aware research in decision science. Our analysis produces insights that can support researchers in OR/OM/SCM who wish to critically address DEI and related topics and integrate them into research programs.
Gila E Fruchter, Ashutosh Prasad, Thomas Reutterer
In a globalized economy, companies face a range of challenges and opportunities related to relocating production activities to a new country. Relocation can yield significant cost savings and other benefits, but there are also risks including potential damage to the brand image. Thus, firms need to carefully evaluate when to relocate and when to stop production in a particular location. We formulate an optimal control model and derive analytical as well as numerical results to provide insights into the optimal relocation timing and production stoppage decisions. We show that factors like higher relocation costs, higher production costs in the relocation country but high brand image in the country of origin, can postpone production relocation. Competitive effects alter relocation timing, particularly when the firm faces direct competition and asymmetric negative cross-image spillover effects with the rival brand in the home or relocation country. The paper discusses illustrative examples and derives implications for the timing of relocation and the duration of production in the relocation country.
Purpose – The objective of this study is to examine the impact of the dynamic environment on the relationship between intangible resources and sustainable competitive advantage in large and medium-sized manufacturing firms operating across various sectors.
Design/methodology/approach – The research sample was selected using cluster random sampling, which is based on company size, namely large and medium-sized companies only, totalling 257 companies as the unit of analysis. A questionnaire was utilized to collect data. While the study employed residual technique and the Hayes (2012) method for variable assessment, the primary method used was a causal analysis.
Findings – The findings indicate that the dynamic environment does not act as a moderating variable, implying that the sustainability of the organization is unaffected by the firm’s dynamic environment.
Research limitations/implications – Research findings can play a pivotal role in corporate strategy, enabling companies to reach a sustainable competitive advantage by closely monitoring environmental changes.
Practical implications – This research can assist companies in developing business strategies that are more adaptive to environmental changes, enabling them to actively monitor and identify emerging opportunities and threats. By doing so, companies can take appropriate steps to maintain their competitive advantage.
Originality/value – Previous researchers have rarely conducted this research, primarily due to a lack of understanding on how to effectively connect dynamic environments with intangible resources in order to achieve sustainable competitive advantage.
Production management. Operations management, Management. Industrial management
The coal industry is a high risk, high difficulty industry, and the annual global mine accident rate is high, so the safety of coal mine underground operations has been a concern. With the development of technology, the application of intelligent security technology in coal mine safety has broad prospects. In this paper, the research progress of vital signs monitoring and support equipment for underground personnel in coal mines is reviewed. The two main methods to ensure the safety of miners are discussed. They consist of directly monitoring human vital signs through portable devices such as smart helmets and smartwatches and indirectly monitoring underground environmental parameters. In addition, the application of information technology, sensor technology and artificial intelligence in vital signs monitoring is briefly discussed, and some future research directions are proposed. For example, through big data and artificial intelligence technology, vital signs data can be compared with historical data, individual health trends and potential risks can be analyzed, and we can provide personalized health management programs for miners. These technologies not only improve the safety of underground coal mine operation, but also provide an important guarantee for the realization of intelligent and safe coal mine production.
Background: To manage growth opportunities effectively and to make a significant impact on superior longterm performance, it is necessary to analyze firm value and diagnose its determinants. Increasing profit, providing prosperity to the company's stakeholders, and improving company value are the goals of every company's business. Purpose: The paper aims to build a model of the company's optimal value by assessing company performance based on financial statement analysis of European companies over the period 2015-2020. Study design/methodology/approach: The impact of financial indicators such as financial leverage, profitability, size, liquidity, growth, and asset tangibility on company value was thoroughly considered. The empirical research was founded on a sample of 158 Eastern and Western European companies, generating 948 observations. Panel regression analysis was conducted. Findings/conclusions: The obtained results revealed that debt-to-assets ratio, return on equity, and assets tangibility have a significant adverse effect on company value, whereas the return on assets and firm size have a significant favorable effect. The obtained conclusions should serve as a beneficial tool for the strategy of reaching the targeted market company's value and ensuring the company's future viability by the market. Hence, stakeholders could assess the perspective of the future company's development and strengthen the importance and influence of financial variables on the company's value. Limitations/future research: The research limitations, which are also opportunities for future research, are aimed at the investigation of company value indicators at the level of individual European economies or industries. One should look at the company's value factors before and after the Covid-19 pandemic and consider a longer time in the company's business. Other financial determinants that affect the value of the company could be considered, and the company value could be measured by some other indicators. Also, the influence of nonfinancial determinants on the company value could be researched.
Production management. Operations management, Personnel management. Employment management
Julian Senoner, Bernhard Kratzwald, Milan Kuzmanovic
et al.
To meet order fulfillment targets, manufacturers seek to optimize production schedules. Machine learning can support this objective by predicting throughput times on production lines given order specifications. However, this is challenging when manufacturers produce customized products because customization often leads to changes in the probability distribution of operational data—so‐called distributional shifts . Distributional shifts can harm the performance of predictive models when deployed to future customer orders with new specifications. The literature provides limited advice on how such distributional shifts can be addressed in operations management. Here, we propose a data‐driven approach based on adversarial learning, which allows us to account for distributional shifts in manufacturing settings with high degrees of product customization. We empirically validate our proposed approach using real‐world data from a job shop production that supplies large metal components to an oil platform construction yard. Across an extensive series of numerical experiments, we find that our adversarial learning approach outperforms common baselines. Overall, this paper shows how production managers can improve their decision making under distributional shifts.
Call centers are an increasingly important part of today's business world, employing millions of agents across the globe and serving as a primary customer‐facing channel for firms in many different industries. Call centers have been a fertile area for operations management researchers in several domains, including forecasting, capacity planning, queueing, and personnel scheduling. In addition, as telecommunications and information technology have advanced over the past several years, the operational challenges faced by call center managers have become more complicated. Issues associated with human resources management, sales, and marketing have also become increasingly relevant to call center operations and associated academic research. In this paper, we provide a survey of the recent literature on call center operations management. Along with traditional research areas, we pay special attention to new management challenges that have been caused by emerging technologies, to behavioral issues associated with both call center agents and customers, and to the interface between call center operations and sales and marketing. We identify a handful of broad themes for future investigation while also pointing out several very specific research opportunities.
[Significance]Autonomous and intelligent agricultural machinery, characterized by green intelligence, energy efficiency, and reduced emissions, as well as high intelligence and man-machine collaboration, will serve as the driving force behind global agricultural technology advancements and the transformation of production methods in the context of smart agriculture development. Agricultural robots, which utilize intelligent control and information technology, have the unique advantage of replacing manual labor. They occupy the strategic commanding heights and competitive focus of global agricultural equipment and are also one of the key development directions for accelerating the construction of China's agricultural power. World agricultural powers and China have incorporated the research, development, manufacturing, and promotion of agricultural robots into their national strategies, respectively strengthening the agricultural robot policy and planning layout based on their own agricultural development characteristics, thus driving the agricultural robot industry into a stable growth period.[Progress]This paper firstly delves into the concept and defining features of agricultural robots, alongside an exploration of the global agricultural robot development policy and strategic planning blueprint. Furthermore, sheds light on the growth and development of the global agricultural robotics industry; Then proceeds to analyze the industrial backdrop, cutting-edge advancements, developmental challenges, and crucial technology aspects of three representative agricultural robots, including farmland robots, orchard picking robots, and indoor vegetable production robots. Finally, summarizes the disparity between Chinese agricultural robots and their foreign counterparts in terms of advanced technologies. (1) An agricultural robot is a multi-degree-of-freedom autonomous operating equipment that possesses accurate perception, autonomous decision-making, intelligent control, and automatic execution capabilities specifically designed for agricultural environments. When combined with artificial intelligence, big data, cloud computing, and the Internet of Things, agricultural robots form an agricultural robot application system. This system has relatively mature applications in key processes such as field planting, fertilization, pest control, yield estimation, inspection, harvesting, grafting, pruning, inspection, harvesting, transportation, and livestock and poultry breeding feeding, inspection, disinfection, and milking. Globally, agricultural robots, represented by plant protection robots, have entered the industrial application phase and are gradually realizing commercialization with vast market potential. (2) Compared to traditional agricultural machinery and equipment, agricultural robots possess advantages in performing hazardous tasks, executing batch repetitive work, managing complex field operations, and livestock breeding. In contrast to industrial robots, agricultural robots face technical challenges in three aspects. Firstly, the complexity and unstructured nature of the operating environment. Secondly, the flexibility, mobility, and commoditization of the operation object. Thirdly, the high level of technology and investment required. (3) Given the increasing demand for unmanned and less manned operations in farmland production, China's agricultural robot research, development, and application have started late and progressed slowly. The existing agricultural operation equipment still has a significant gap from achieving precision operation, digital perception, intelligent management, and intelligent decision-making. The comprehensive performance of domestic products lags behind foreign advanced counterparts, indicating that there is still a long way to go for industrial development and application. Firstly, the current agricultural robots predominantly utilize single actuators and operate as single machines, with the development of multi-arm cooperative robots just emerging. Most of these robots primarily engage in rigid operations, exhibiting limited flexibility, adaptability, and functionality. Secondly, the perception of multi-source environments in agricultural settings, as well as the autonomous operation of agricultural robot equipment, relies heavily on human input. Thirdly, the progress of new teaching methods and technologies for human-computer natural interaction is rather slow. Lastly, the development of operational infrastructure is insufficient, resulting in a relatively low degree of "mechanization".[Conclusions and Prospects]The paper anticipates the opportunities that arise from the rapid growth of the agricultural robotics industry in response to the escalating global shortage of agricultural labor. It outlines the emerging trends in agricultural robot technology, including autonomous navigation, self-learning, real-time monitoring, and operation control. In the future, the path planning and navigation information perception of agricultural robot autonomy are expected to become more refined. Furthermore, improvements in autonomous learning and cross-scenario operation performance will be achieved. The development of real-time operation monitoring of agricultural robots through digital twinning will also progress. Additionally, cloud-based management and control of agricultural robots for comprehensive operations will experience significant growth. Steady advancements will be made in the innovation and integration of agricultural machinery and techniques.
Iuliana Ioana Merce, Ioana Anda Milin, Ramona Mariana Ciolac
Food quality and human health influences contemporary life. Today more than ever, quality products to be safe in terms of food to meet the needs and innocuity became major values for all producers, processors, distributors, especially for food consumers who are becoming more aware that their health depends on the quality of the food they consume. The paper recently a case study in a Romanian company in the dairy industry and the manufacture of dairy products, and all commercial operations the object of transaction milk and milk products, a small company that combines managed but we consider traditionalism ( the products we offer to the market ) modernism ( European requirements, quick marketing, producer - client relationship etc). This paper analyzes the emergence and development aspects of the company, implementing and upgrading production technology, issues related to the introduction of quality management, promotion and sale of products, customer relations, etc. We believe that SC HELVETICA MILK SRL, the constant concern of food safety, raw material procurement stage till marketing - customer satisfaction by offering quality products and thereby ensure customer loyalty. In conclusion, we believe the company is a successful example of business succces Romanian food industry.
Purpose – This research proposes an alternative method to solve completion delay issue and optimized the strategy using ISM technical method and Quality Cost Model application.
Design/methodology/approach – Data was acquired from 120 questions from company key persons that involved in project for last 5 years. The instruments processed using ISM analysis to measure the relationship among causes, then using Quality Cost Model to solve.
Findings – This research shows that factors of late payment from client, delays in bank credit processing, bad weather, and design changes by owners are the root causes of delays. Further analysis using the Theory of Constraint (TOC) shows that financial constraint issues influence the decreased throughput and increase operating cost. Further management use five sequential steps to improve the management and P-A-F models as one of strategic cost management tools applied to the root causes to determine the optimum cost strategy to solve the problem.
Research limitations/implications – This research was conducted using a case study method, and the conclusion related to problem and root cause may not be applied totally to other companies, but the framework may be applicable. Future research can investigate other issue using TOC framework, combine TOC with other models to conduct root cause analysis, and the COQ model implementation in shipyard management.
Practical implications – This research demonstrates that management can use Interpretative Structural Modelling (ISM) analysis to determine the root cause, then analyse and overcome the issues using TOC framework. COQ model approach to sharpening the decision, and prioritize the resources allocation.
Originality/value – This research combine ISM, TOC, and PAF Quality Cost Model approach for decision making which can be a management tool in strategic cost management.
Production management. Operations management, Management. Industrial management
Sustainable development and sustainability will be achieved if there is a balance between the human dimension and ecosystem. The purpose of this study is to evaluate the sustainability and resilience of forest ecosystems in the Totshami watershed, which seeks to maintain a balance between the human and ecosystem dimensions. Implementation of this model includes assessing the sustainability and determining the resilience of the basin. ArcGIS software was used to analyze and measure the sustainability of the IUCN method and after the final combination of indicators and criteria to produce the map. Identification of functions of the basin with 54 types of functions and was classified into four major services: provider, regulator, habitat and culture. Based on the research results, the final score was 35 for ecosystem dimensions and 50 for human dimensions. The two main objectives including maximizing the water production and minimizing the annual soil losses, along with responding to local demand, have been achieved in the process of optimizing the functions in this study. According to the projected watershed management operations in the basin, it is expected that the ecosystem sector will reach the desired level of sustainability, and in order for the basin to remain sustainable, the economic and social sections must also be considered, and it can be achieved by taking steps to improve people's living standards. Evaluation of the results of Totshami watershed resilience measurement during indicates low tolerance threshold and flexibility of Zagros forests and the result is a reduction in the resilience of these ecosystems to potential threats and disruptions.
Many manufacturing firms have become increasingly flexible in that they can rapidly idle and restart production in response to changing commodity prices. We study how operational flexibility alters both the timing and financing decisions in the firm. We perform this analysis in a dynamic model in which a firm has multiple debt issues and decisions are made to maximize shareholder value. We compare the decisions of a flexible firm, which can temporarily shut down to avoid operational losses, with those of a rigid firm which is not able to stop operating even in states where operational losses occur. On one hand, firms with operational flexibility can better exploit a larger tax shield by taking on more debt. On the other hand, taking on more debt may be less harmful for a rigid firm, since it increases the default threshold thereby reducing the region where operational losses are experienced due to inflexibility. We explore how the two forces trade off between the benefit of tax shield and the cost of default. We find that, even though bondholders charge a higher fair premium for debt issued by the inflexible firm, the rigid firm will utilize more debt. We also show that, all things being equal, firms with operational flexibility invest earlier and use less debt to finance the opportunity. Dynamic models that trade off tax shields with bankruptcy costs and ignore operational flexibility may result in theoretical leverage ratios being biased high.
We study production planning in a multi‐product setting, in which demand for each product depends on multiple financial assets (such as commodities, market indices, etc). In addition to the production quantity decision at the beginning of the planning horizon, there is also a real‐time hedging decision throughout the horizon; and we optimize both decisions jointly. With a mean–variance problem formulation, we first derive the optimal hedging strategy, given the production quantities. This leads to an explicit objective function with which bounds on optimal production quantities are identified. Thus, optimization of the production policies can be readily solved numerically as a static minimization problem. This way, we are able to give a complete characterization of the mean–variance efficient frontier, and quantify the contribution of the hedging strategy by the variance reduction it achieves. Furthermore, the model and results are extended to allow dynamic production control that tracks the demand rates.
Firms along a supply chain are exposed to risks that emanate from shocks that affect the supply of the commodity at the beginning of the chain, as well as shocks to the demand for the products and services that are produced at the end of the supply chain. These risk exposures tend to depend on production technologies as well as supply and demand elasticities. A key takeaway is that firms that use commodity inputs cannot in general rely on either the historical covariance between input prices and profits or industry practice to determine their strategies for hedging commodity price exposures.
Production planning is often challenging for small medium enterprises (SMEs) company. Most of the SMEs are having difficulty in determining the optimal level of the production output which can affect their business performance. Product mix optimization is one of the main key for production planning. Many company have used linear programming model in determining the optimal combination of various products that need to be produced in order to maximize profit. Thus, this study aims for profit maximization of a SME company in Malaysia by using linear programming model. The purposes of this study are to identify the current process in the production line and to formulate a linear programming model that would suggest a viable product mix to ensure optimum profitability for the company. ABC Sdn Bhd is selected as a case study company for product mix profit maximization study. Some conclusive observations have been drawn and recommendations have been suggested. This study will provide the company and other companies, particularly in Malaysia, an exposure of linear programming method in making decisions to determine the maximum profit for different product mix.
Production management. Operations management, Business
We study a horizontal merger in an oligopolistic market in which firms compete on production quantities. Each firm has its own in‐house manufacturing facility, and the production is subject to random yield. After the consolidation of two firms, the merged entity can use both manufacturing facilities that belong to the merging firms. It is well known that diversification can reduce the aggregate supply uncertainty of a firm, but this diversification benefit has not been explored in a merger analysis. We model the effects of reduced competition, cost synergy, and supply diversification from a merger and characterize their combined impact on firms’ production quantities and expected profits. Our analysis highlights the importance of yield correlation. In the postmerger model, although an increase in yield correlation intensifies end‐market competition and lowers the diversification benefit, it can increase the merged firm's expected profit. This is more likely to occur as the synergy effect increases, the number of competing firm increases, and the yield variance decreases. We also compare the premerger and postmerger equilibrium production quantity and expected profit of each firm. We show that there exists threshold levels of cost synergy above (or below) which the postmerger equilibrium profits or quantities exceed their premerger counterparts. We also show that, under yield uncertainty, firms may have an incentive to merge even without cost synergy due to the diversification benefit. With deterministic demand, cost synergy is necessary to justify a merger.