Stock Production Research Articles

Stock exchange operations as a tool for increase in the level of economic security of the enterprise

The problem of increasing the level of economic security of the enterprise is relevant for enterprises in market conditions of business, which are characterized by a high level of instability. However, in today's conditions of increased instability and increased threats, it is necessary to further deepen the study of the problem in order to find new effective tools for increasing the level of economic security of the enterprise. Exchange transactions are among such instruments. The main components of economic security, which can be positively affected by stock exchange operations, are financial, marketing and production. Prospects for the use of stock exchange operations to increase the level of financial security of the enterprise: operations on the commodity exchange, the purpose of which may be the purchase of production stocks and the sale of products of own production, will allow forecasting the level of expenses and the level of income both by cost and by the time of formation, which has a positive effect on the effectiveness of cash flow management, accordingly, has a positive effect on the level of solvency of the enterprise; operations on the stock market allow you to effectively attract financial resources to ensure the operation of the enterprise, and can also be used for the placement of equity securities of the enterprise and the effective search for co-owners; operations with futures and option contracts with a sufficient level of professional knowledge of the company's specialists will allow to provide the company with production resources and sell the company's products on the most favorable terms. The impact of stock exchange operations on marketing security: the stock market is an effective source of sales of products, within which it is possible to enter into contracts for future supply with a clearly established price level and terms of performance; due to the concentration of potential counterparties, it is possible to increase the volume of sales of the company's products; thanks to the desire to reach the level of the exchange standard, the tendency to increase the quality of products and their competitiveness is ensured; from the point of view of brand development, exchange transactions can have a negative impact, because during exchange trading, depersonalization of products and counterparties and maximum standardization are characteristic. The impact of stock exchange operations on production safety: an increase in the level of product quality to the level of the stock exchange standard, uninterrupted provision of the production process with raw materials and materials, thanks to which downtime can be reduced, the rhythm of production increased and the level of utilization of the production capacity of the enterprise. Therefore, the positive impact of stock exchange operations on the vast majority of functional components of the enterprise's economic security allows to increase its level and achieve the fulfillment of tasks related to increasing the level of competitiveness of the enterprise and ensuring the stability of business conditions.

Stock exchange operations in an anti-crisis management system of the enterprise

Today, in the process of building an effective system of anti-crisis management of the enterprise, more attention should be paid to such less common, but highly effective tools as stock transactions. Anti-crisis management is a certain set of strategic measures and tactical actions aimed at identifying, preventing and overcoming crisis phenomena in the company's activities, as well as impulses that potentially threaten the development of crisis phenomena in the future. The main directions of action are the following: development of the general anti-crisis strategy of the enterprise, ensuring the financial stability of the enterprise, implementation of the risk management system, restructuring of the enterprise and its business processes, personnel and communications management, increasing the efficiency of the marketing system, etc. Speaking about the place of stock exchange operations in the system of anti-crisis management of the enterprise, it should be noted that they can be considered as a tool in the middle of some of the above measures, namely optimization of business processes, improvement of the level of communications and activation of marketing. In all these aspects, the use of exchange operations can be effective. In our opinion, transactions with goods and derivative financial instruments require the main attention. Speaking about the optimization of business processes, the following advantages of cooperation with stock exchange institutions can be distinguished: guaranteed replenishment of production stocks with raw materials and materials of the required quality and quantity due to the conclusion of term exchange agreements for their supply, the forecast level of prices for raw materials and materials, which is fixed during the conclusion of exchange agreements , clearly defined conditions of supply. Access to the stock market also has a positive effect on the level of business communications, because it is the stock exchange that maximally concentrates all interested parties regarding specific types of goods, which contributes to the intensification of business activity. Exchange operations can also be considered as a highly effective tool for activating the marketing activities of the enterprise. In addition to the purchase of raw materials on the stock exchange for your activity, you can use the stock market for the sale of goods manufactured by the enterprise. In this way, the company can guarantee itself future sales in a certain forecasted price range, and accordingly, reasonable planning of the company's performance indicators, cash flows is possible, therefore, it becomes possible to manage insolvency, which is the main crisis impulse for the company.

Growth parameters of the clupeids Limnothrissa miodon and Stolothrissa tanganicae in northern Lake Tanganyika (Bujumbura sub-basin)

The analysis of growth parameters in fish stocks, such as the asymptotic length (L∞) and the curvature parameter (K), is crucial for the estimation of production rates and total mortality rates in fisheries management. Here, we estimated the growth parameters of the clupeids Limnothrissa miodon and Stolothrissa tanganicae in the northern part of Lake Tanganyika (Bujumbura sub-basin). Both species are important targets of pelagic fisheries, but the available estimates are based on scarce size frequency data, and rarely on size as a function of age data. We provide new estimates of L∞ and K based on size as a function of age data, with age being inferred from otolith weights. Furthermore, we reanalyze several existing length frequency datasets using advanced statistical procedures to test if growth parameters estimated by length frequency analysis are consistent with those obtained from size as a function of age. We found that length frequency analysis consistently underestimates L∞ and overestimates K as compared to length-at-age data. We recommend that length-at-age data are collected at a much broader spatial and temporal scale than currently available to advance our understanding of the growth dynamics of these two sardine species. This will improve the assessment of stock productivity of Lake Tanganyika’s pelagic fisheries and the conservation of these economically important fish species.

Maximizing the valorization potential of lignin through optimization of the Soda pulping conditions

The valorization potential of lignin is strongly dependent on the yield that can be obtained during the pulping process as well as its chemical structure. Both of these are determined by factors such as the biomass type, the selected extraction strategy and the employed conditions. Within this study, Miscanthus x giganteus biomass was subjected to systematically varying Soda pulping conditions, i.e., temperature (100 °C – 180 °C), OH– concentration (0.158 mol/L – 1.000 mol/L) and time (60 min – 360 min). These pulping conditions can be combined into a single factor, reflecting the processing severity, which in this work varied from approximately 1 to 5. The resulting black liquor, precipitated lignin, lignin stock solution (i.e., lignin dissolved in the solvent used in the subsequent depolymerization step) and product pool after mild reductive catalytic depolymerization (200 °C, 10 bar H2 initial, 4 h) were thoroughly characterized using a plethora of analysis techniques. Increasing the severity factor of the pulping was found to result in an enhancement of the delignification degree from 25.3 ± 2.6 % to 95.4 ± 9.9 %. However, beyond a severity factor of 3, fragmentation of native ether linkages and condensation reactions start to cause unfavourable changes in the chemical structure of the lignin and depolymerization product pool. Furthermore, these reactions significantly reduce the total mass yield from biomass to depolymerization product pool. An Adaboost model with quadratic base estimator was trained against the experimental data, and subsequently used to optimize the pulping conditions, aiming at a maximum total mass yield with minimal fragmentation and, hence, condensation, of the lignin. The optimum was experimentally validated, which resulted in a lignin with high β-O-4 content (42.7 ± 2.8 linkages per 100 aromatic units) and a total mass yield of 30.9 ± 3.4 wt% and a pulp with a residual lignin content of 8.25 ± 0.94 wt%.

Stormy sales: the influence of weather expectations on FMCG consumption

PurposeThis study aims to understand the impact of extreme weather events on fast-moving consumer goods (FMCG) consumption and to examine the role of anticipated product scarcity and FMCG types on such behavior.Design/methodology/approachThis paper conducted five studies, combining archival data analysis with behavioral experiments. The archival data included sales data from a supermarket chain and weather data from the National Weather Service. The experiments were designed to test the effect of extreme weather cues on consumption, the psychological mechanism behind this effect and moderators.FindingsThis research found that consumers’ anticipation of extreme weather events significantly increases their consumption of FMCGs. This research further discovered that these behaviors are driven by anticipated product scarcity and moderated by consumers’ altruisms and FMCG types.Research limitations/implicationsLimitations of the research include the reliance on reported sales data and self-reported measures, which could introduce biases. The authors also primarily focused on extreme weather events, leaving other types of disasters unexplored. Furthermore, cultural differences in disaster response might influence results, yet the studies do not fully address these nuances. Despite these limitations, the findings provide critical insights for FMCG retailers and policymakers, suggesting strategies for managing demand surges during disasters. Moreover, understanding consumer behavior under impending disasters could inform intervention strategies, potentially mitigating panic buying and helping ensure equitable resource distribution. Last, these findings encourage further exploration of environmental influences on consumer behavior.Practical implicationsThe findings have practical implications for products, brand managers and retailers in managing stock levels and product distribution during disasters. Furthermore, understanding the psychological mechanisms of these behaviors could inform policymakers’ designs of public interventions for equitable resource allocation during extreme weather events.Social implicationsThe research provides significant social implications by highlighting how extreme weather events impact FMCG consumption. This understanding can guide public policymakers in creating efficient disaster management plans. Specifically, anticipating surges in FMCG purchases can inform policies for maintaining price stability and preventing resource shortages, mitigating societal stress during crises. Moreover, these findings encourage public education around responsible purchasing during disasters, potentially reducing panic buying. By collaborating with FMCG manufacturers and retailers, governments can ensure a steady supply of essentials during extreme weather events. Thus, the research can play a crucial role in enhancing societal resilience in the face of impending disasters.Originality/valueTo the best of the authors’ knowledge, this is the first study to integrate the impact of extreme weather events on consumption behavior with the psychological theory of anticipated product scarcity. The unique focus on FMCGs offers a novel perspective on consumer behavior literature.

The implications of biomass and carbon sequestration of exclosure for climate change mitigation in arid areas, Sekota district, northern Ethiopia

Climate dynamics management plays a crucial role in safeguarding the environment from a global to local scale. Land degradation poses a significant threat to the livelihoods of millions of people living in drylands. Arid regions are particularly vulnerable when it comes to finding suitable habitats for ecological processes. Various global initiatives have been developed to restore degraded drylands. In addition, exclosures have important implications in arid areas for regulating environmental services. However, there is a lack of systematic studies on the biomass improvement and climate change mitigation effects of exclosures. A study was carried out in the Sekota district of northern Ethiopia to evaluate the impact of exclosures on biomass production and carbon stock. Three sites—Gateno, Jinqaba, and Mildam—were chosen for the pilot study. Data was collected from 27 quadrats, with different sizes used for sampling saplings, seedlings, litter, and soil. Soil samples were taken at depths of 0–20 cm and 0–40 cm. The data was analyzed using Excel and R Studio, and a linear mixed-effect model was used to determine the differences between land uses. The results indicated significant variations in above-ground biomass carbon, soil organic carbon, and total carbon stock between the two land uses. Furthermore, the observational perspective of exclosures in the Sekota district reveals a sustainable and suitable environment for interested parties. Exclosures prove to be effective in the restoration of degraded lands, as well as in enhancing biomass accumulation and carbon sequestration.

Fine-Grained Sentiment Classification Using Generative Pretrained Transformer

Social media platforms have seen a significant increase in the number of users and content in recent years. Owing to the increased usage of these platforms, incidents of teasing, provocation—both positive and negative—and harassment, and community attacks have increased tremendously. There is an urgent need to automatically identify such content or tweets that can hamper the well-being of an individual or society. Analyzing social media messages from Twitter and Facebook has become the focus of sentiment analysis in recent years, which formerly focused on online product evaluations. Sentiment analysis is used in a wide range of fields besides product reviews, including harassment, stock markets, elections, disasters, and software engineering. After the tweets have been preprocessed, the extracted features are categorized using classifiers like decision trees, logistic regression, multinomial nave Bayes, support vector machines, random forests, and Bernoulli nave Bayes, as well as deep learning techniques like recurrent neural network (RNN) models, long short-term memory (LSTM) models, bidirectional long short-term memory (BiLSTM) models, and convolutional neural network (CNN) model for sentiment analysis. In this paper, different techniques are compared to classify Twitter tweets into three categories: “positive,” “negative,” and “neutral.” We proposed a novel data-balancing technique for text classification. A text classification technique is proposed for analyzing textual data using the Generative Pretrained Transformer model owing to its contextual understanding and more realistic data generation capability. Comparative analysis of different Machine learning and Deep learning models are performed with and without data balancing. The experiments show that the accuracy and F1-measure of the Twitter sentiment classification classifier are improved. The proposed ensemble has outperformed and achieved an accuracy of 90%, precision of 88%, and 81% F1 score.

Plant species richness and legume presence increase microbial necromass carbon accumulation

Biodiversity control experiments have demonstrated that higher plant species richness increases plant production and soil organic carbon (SOC) stocks. However, although microbial necromass C constitutes a substantial and stable component of SOC, the effect of species richness on microbial necromass C accumulation remains unclear, especially concerning the presence or absence of legumes. We conducted an 8-year grassland biodiversity experiment to investigate how changes in plant diversity, with or without legumes, affect microbial necromass C and its proportion in SOC. Aboveground and root biomass increased by 254 % and 195 %, respectively, from monoculture plots to those with twelve species. SOC, total nitrogen (N), and microbial biomass C (MBC) all increased with plant species richness, independent of legume presence. The presence of legumes further increased the SOC, total N, MBC, and inorganic N compared to plots without legumes. Microbial necromass C increased by 48.3 % in twelve-species mixtures compared to monocultures; however, the ratio of microbial necromass C to SOC remained stable with increasing species diversity. Notably, the presence of legumes increased both the accumulation of microbial necromass C and its proportion in SOC compared to the absence of legumes at both high and low species diversity levels. This greater accumulation was primarily driven by increased plant productivity and microbial biomass, induced by legume-associated nitrogen fixation. Our findings highlight significant implications for ecosystem management: maintaining high levels of plant species diversity, particularly in conjunction with legumes, can increase microbial necromass C and enhance soil C sequestration.

Mise en place d’une antenne pharmaceutique de blocs opératoires dans un centre hospitalier universitaire

An operating room pharmaceutical unit centralizes medical devices and drugs for various surgical specialities. The aim of this work is to present the methodology used in our establishment to set up the operating room pharmaceutical unit. This approach involved the formation of multi-professional working groups. The needs of operating theatres were defined based on an analysis of healthcare product consumption and stock inventories. Material sheets were defined for each procedure. On the basis of simulations, material supply arrangements were selected, specifying material flows, equipment, workstations and information systems. Over 3200 healthcare product references were identified and 862 equipment files were created. Local stocks have been limited to medical trolleys for nursing staff. Emergency operating packs have been deployed for unforeseen operations. Cabinets have been dedicated to transporting re-sterilizable medical devices, and carts have been purchased for programmed operating packs. The equipment is made available by logistics agents and pharmacy assistants under pharmaceutical responsibility. This innovative approach is a model for facilities desiring to centralize and secure the logistics of healthcare products in the operating room. Ongoing adjustments will be required to meet new operating rooms needs.

Oil Demand and Stocks

Current data of world oil demand. This includes international bunkers and refinery fuel. Updated on a monthly basis.Current data of oil demand from counties such as Canada, the United States of America, Japan, OECD Europe, Belgium, France, Germany, Italy, Netherlands, Spain, Sweden, the United Kingdom, Australia, Mexico, Republic of Korea, and Turkey. Updated on a monthly basis.Current data for crude oil and refined product stocks in Canada, Chile, Mexico, the United States (Western Hemisphere), France, Germany, Italy, Netherlands, Spain, the United Kingdom and Other Europe (Europe), Japan, Republic of Korea, Other Pacific (Asia‐Pacific), and Total OECD (Table 12.1)Current data for refined product stocks in the OECD Western Hemisphere, OECD Europe, OECD Asia‐Pacific and Total OECD. Products include gasoline, diesel and gasoil, and heavy fuel oil. Updated on a monthly basis (Table 12.2).

UPDATE OF PETROPHYSICAL AND GEOLOGICAL MODEL OF MIDDLE JURASSIC DEPOSITS DURING WELL MONITORING

Tyumen deposits of the studied subsoil area of Western Siberia were put into operation from the middle of the last century, but active development of the YuS2 formation began not so long ago. Currently, the share of wells planned for the operation of this target in the coming years is growing. There are cases when the well performance does not meet the forecasts, which calls into question the correctness of the model used in the development of the target and the structure of the section itself.For high-quality planning of the production stock, it is necessary to prepare a reliable geological basis. The problem of updating the model and improving its reliability lies in the complex geological structure of the formation, which is characterized by high lateral and vertical heterogeneity, as well as in the absence of the basis for all geological models - seismic studies of the investigated subsoil area.The cross-section of the YuS2 reservoirs is complex for petrophysical and geological modeling and is characterized by low reservoir properties. The reservoirs are represented by thin interbeds of permeable interlayers and impermeable clay, carbonaceous and dense rocks.The article examines the specifics of building petrophysical models of YuS2 formations during development drilling using all available core and borehole data to detail the deposits of the Tyumen formation. The purpose of the work is to create own dependencies for interpretation of well geophysical survey data taking into account sedimentation conditions.To detail the Jurassic section, a comprehensive analysis of lithological and petrographic studies of core material from the point of view of geology and petrophysics was used.Facies analysis of the Tyumen deposits in the absence of seismic studies 3D acts as the main factor improving the quality of the predictive ability of geological models in support of development drilling. Adaptation of the petrophysical model to modern geological and technical conditions of well drilling is shown.An integrated approach to the study of the Tyumen formation deposits based on facies and petrophysical studies made it possible to improve the quality of the forecast of the distribution of the reservoir of formation YuS2 and obtain a detailed model. This will help optimize the placement of the production stock, as well as identify the prospects for the development of deposits in areas not covered by drilling.

Web-Based Inventory Management System Using First In First Out Algorithm

<p>PT. Agung Selaras Group is a property company that operates in the business of selling houses. With a good sales management system, the property company can support its work activities. The aim of this research is to develop a system that can simplify stock management and minimize the risk of loss in the sales process. The data source for this research was obtained from direct observation and interviews with PT. Agung Selaras Group. In this system the author will combine the First In First Out method in managing incoming and outgoing product stock. The results of this research are that the system that has been designed can make it easier for managers to collect data on incoming and outgoing goods so that the risk of managing product stock can be minimized, and with computerized reports it can provide more precise, accurate and fast information. From the results of black box testing, the percentage of this application system can run well.</p>

E-Commerce Information System Design Using SpringBoot Framework and PostgreSQL

Advances in information technology, especially in the field of information technology, have become an integral part of our daily lives. The increasing volume and complexity of data affects almost all aspects of our activities, including education, sales, transportation, banking, and others. In a world filled with advanced technology, people expect speed and convenience in everything. Therefore, businesses need to design and build effective and reliable e-commerce information systems to meet the demands of an increasingly connected and digitalized market. In this research, e-commerce information systems are faced with the demand to efficiently manage various aspects of business such as product management, stock, transactions, delivery, and payment. RESTful web services are used as a solution to facilitate data exchange between various systems effectively by using SpringBoot Framework, which is chosen as an easily configurable and efficient framework. In addition, security and flexibility in data management were in focus, with PostgreSQL chosen as a database capable of dealing with large data volumes and providing a good level of security. By combining SpringBoot-based RESTful web services and the use of PostgreSQL database, the e-commerce information system can provide high performance, integrated, and secure, improving the user's shopping experience and building customer trust in the e-commerce platform used. The research method used by researchers in the design of this information system is the System Development Life Cycle (SDLC) which includes planning, analysis, design and implementation.

The Plan Rancang Bangun Mesin Pemotong Adonan Kerupuk Rambak Tepung Guna Meningkatkan Kapasitas Produksi

In this era of progress in all sectors, which has an impact on the industrial sector in Indonesia, causing increasingly high competition. This research uses the Make to Order (MTO) and Make to Stock (MTS) production systems. The method used in this research contains stages that involve collecting data and information through interviews, observation, library studies. Based on the improvements that have been obtained, production capacity can also be increased, which was previously in line with demand. This happens because there is an automatic cracker dough cutting machine, so there is no excessive workload caused by manually cutting cracker dough.

Spawning history, fecundity, and potential sperm limitation of female blue crabs in Chesapeake Bay

The blue crab (Callinectes sapidus) is an ecologically and economically important species in estuaries of the Western Atlantic Ocean and Gulf of Mexico. Given the importance of reproductive output and spawner demography on population dynamics, blue crab management may be improved if individual-based changes in egg production are identified and incorporated into management advice. We determined the spawning history, batch fecundity, and stored sperm quantity of 126 ovigerous blue crabs in 2022 to estimate the reproductive potential of female blue crabs in Chesapeake Bay. Our mean estimate of fecundity, 2.17 million eggs/female, is similar to a fecundity estimate from 1986 (2.6 million eggs/female), but lower than an estimate from 1987 (4.0 million eggs/female). The 1987 estimate was likely biased high due to methodological differences. In 2022, size-specific fecundity did not differ from that in 1986. Size-specific fecundity was lower by 0.28 million eggs in multiparous females (i.e., those that produced at least one previous egg mass) compared with primiparous females (i.e., those producing their first egg mass). Size-specific fecundity was also greater in July and August than in June, however, females in June had a greater capacity for future reproductive potential because their average stored sperm quantity was three times greater than that of females in July and August. Most females in June were primiparous and would become multiparous females in July and August with higher size-specific fecundity. Our study is the first to pair individual fecundity, stored sperm quantity, and spawning history for blue crabs, which allows for a robust assessment of reproductive potential. Generally, the reproductive potential of individual female blue crabs was high at the individual level, such that sperm limitation is unlikely at the population level. Population-level production may be increased by protecting primiparous spawners as these crabs have the highest capacity to contribute offspring to the population. Furthermore, fisheries management may be improved by using our updated estimate of size-specific fecundity (Fecundity = 268,337 × exp(0.015 × Carapace Width)) and incorporating month or spawner history in models of stock production.

Manajemen Display Produk dan Stock Opname sebagai Strategi Peningkatan Efisiensi pada Batik Fajar Indah Solo

This research discusses the implementation of product display and stock taking management strategies as an effort to increase operational efficiency in the retail environment. The main focus is on the role of interns in applying product naming concepts to make things easier for customers and on the stock taking process carried out by employees during store closures. The research results show that effective product display management can shorten customer shopping time and increase their independence, while stock taking is key in maintaining store inventory accuracy. These findings contribute to the practical understanding of how management strategies can be implemented to improve customer experience and operational efficiency in the retail industry.

Product Market Competition and Stock Price Crash Risk: Evidence from China

Synopsis The research problem This study analyzes the relationship between product market competition (PMC) and stock price crash risk in China, especially for firms with weak corporate governance and a lower-quality information environment. Motivation Emerging capital markets like China have less-developed financial systems and institutions compared to developed capital markets like Europe and the United States, making them more susceptible to stock price crash risk. The impact of product market competition (PMC) on corporate decision-making has attracted considerable attention from scholars, especially given the increasingly intense and complex strategic competition in global markets and uncertainty in the world today. However, the effect of PMC on a firm’s stock price crash risk has not been thoroughly explored. Therefore, this study investigated how PMC affects managers’ tendency to hoard bad news and how this behavior contributes to the risk of stock price crashes. The test hypotheses We tested two competing hypotheses: PMC is negatively correlated with crash risk, and PMC is positively correlated with crash risk. Target population This study should be of interest to stakeholders, including firm managers, practitioners, regulatory authorities, policymakers, and investors. Adopted methodology This study employed ordinary least squares (OLS), difference-in-differences analysis (DID), and path analysis. Analysis Using a sample of Chinese A-share listed manufacturing firms from 2000 to 2021, this study found that competitive pressure from the product market encouraged managers to hide bad news, thereby increasing future stock price crash risk. Moreover, we performed additional tests to examine how PMC affected stock price crash risk. Findings We found robust evidence that PMC significantly increases stock price crash risk. Further tests showed that the effect of PMC on crash risk is more pronounced for firms with weak corporate governance and a lower-quality information environment. We also provide evidence that firms in highly competitive industries tend to disclose fewer negative words in the management discussion and analysis section of the annual report and fewer risk factors in the internal control report. Moreover, we show that operational risk is the underlying driver through which PMC affects crash risk.

Prediction of footwear demand using Prophet and SARIMA

In an increasingly globalized market, where world container traffic since 2000 has almost quadrupled, the prediction of demand is an element of great importance for the optimal business development of a company. This work focuses on demand forecasting in the fashion sector. It is a very volatile market, with some characteristics such as: seasonality, culture and fashion trends, that makes it difficult to estimate the inter-seasonal footwear demand. In recent years, many algorithms for the prediction of demand have been studied; they can be divided into three natures: statistical algorithms, artificial intelligence algorithms and hybrid algorithms, each of them with its own characteristics. AI-generated predictions provide business professionals with the ability to organize the purchase of materials, manage production processes and stock quantity. Therefore, the purpose of this work is to forecast the long-term sales of a highly seasonal footwear model based on its historical data, using the Prophet and SARIMA (Seasonal Autoregressive Integrated Moving Average) algorithms. This represents a novelty as sales predictions for footwear in the state of the art are not typically made over the long term or highly seasonal, and there is no model that clearly outperforms others. Additionally, a set of Key Performance Indicators has been established to evaluate the prediction outcomes, as the same indicators such as MAE, MAPE and RMSE are commonly used in the state of the art. Furthermore, a relational database structure has been proposed for the organized storage of future predictions. Finally, the results between Prophet and SARIMA have been compared to ascertain whether Prophet (a non-linear statistical algorithm) outperforms SARIMA (a linear statistical algorithm). In the model prediction Prophet obtains an accuracy of 98.8% and a 158.8 MAE, while SARIMA reaches an accuracy of 93% and a 83.9 MAE; all in all really positive results taking into account long-term prediction and high seasonality. It has been observed how Prophet provides better results when it comes to predicting results of annual quantities, for example, the number of shoes that are expected to be sold next year. However, SARIMA returns better results for those KPI that are calculated considering the monthly distribution of the prediction, as well as being 15 times faster in the mean prediction time.

Managerial myopia and corporate innovation strategy

We investigate the consequences of managerial myopia on both the quantity of innovation input and the quality of innovation outputs in China. Managerial myopia not only leads to a reduction in R&D investment but also results in a deterioration in the outputs, captured by the decrease in those substantive innovations and the degradation of patents’ knowledge breadth. Encouragingly, effective corporate governance mechanisms tend to mitigate the adverse effects of managerial myopia on innovation, but external pressures from stock market and product market may prompt myopic management to hastily engage in R&D efforts, but with further deterioration in innovation quality.

Computing Optimal Mitigation Plans for Force-Majeure Scenarios in Dynamic Manufacturing Chains

We consider force-majeure supply disruptions in a dynamic, multi-product manufacturing supply chain with time-dependent parameters. We present a linear programming model that captures a specific force-majeure scenario with respect to several objective functions that can be combined in a multi-objective framework, e.g., minimization of loss, maximization of shortage-free time, or prioritization of mitigation types. Solving this model yields an optimal mitigation plan that describes how to best (re-)allocate supply and production operations. Supported mitigation options include plant-side safety stock, supplier-side inventories, and additional production thus reflecting the manufacturing setting of a large-scale industrial player. We describe a workflow for increasing the resilience of supply chains based on risk profiles generated by our approach.