Fluctuations In Market Demand Research Articles

Green supply chain management through call option contract and revenue-sharing contract to cope with demand uncertainty

Green supply chain management (GSCM) could be applied to enhance environmental and economic goals simultaneously; nevertheless, according to The University of Chicago Booth report, the overwhelming impacts of the COVID-19 epidemic have caused high fluctuations in market demand. Hence, green supply chain (SC) managers have faced challenges in the decision-making process. Motivated by this issue, we investigate a two-echelon SC network containing one retailer and two suppliers (a non-green supplier and a green supplier). The non-green supplier produces a customary product and has a limited production capacity. Inspired by Coors Brewery Company, the green supplier produces a recyclable product with sufficient production capacity; the retailer faces demand uncertainty and is responsible for bringing back the end-of-life products to the green supplier for the recycling process. In this study, besides decentralized and centralized decision scenarios, we survey two kinds of contracts, i.e., a call option contract and a revenue-sharing contract, which the green supplier offers as risk-sharing policies to motivate the retailer to increase its order quantity. We found that the two parties could agree to coordinate the channel by negotiating the optimal terms of the recommended contracts (i.e., call option contract terms: option price and exercise price, revenue-sharing contract term: wholesale price). Furthermore, our results show that both proposed contracts create a win–win situation for each member and heighten the profitability of the entire SC. By comparing the two contracts, we notice that the green supplier would like to offer the call option contract, and the retailer desires to accept the revenue-sharing contract in return.

Could the E-Commerce Platform’s Big Data Analytics Ease the Channel Conflict From Manufacturer Encroachment? An Analysis Based on Information Sharing and Risk Preference

Big data technology and analytics makes the e-commerce platform obtain more accurate demand information from large-scale customer data. In this paper, we consider a dual-channel supply chain including a manufacturer with risk preference, a traditional retailer, and an e-commerce platform in which the manufacturer adopts an encroachment strategy, adding a direct channel through the e-commerce platform beside the ex-traditional channel. The game model approach is used to analyze the intention of the e-commerce platform's information sharing with the manufacturer and the impact of demand-information sharing on the channel conflict brought by manufacturer encroachment. The results show the manufacturer's encroachment strategy always creates channel conflict. The e-commerce platform is always glad to share its demand information with the online manufacturer, for the information value must be realized through the online transaction. More important, whether the demand information could ease the channel conflicts brought by manufacturer encroachment depends on the degree of the manufacturer's risk aversion, fluctuation of market demand, and the accuracy of the demand information. When the fluctuation of market demand is fixed, the demand information will ease the channel conflicts if the manufacturer is risk-neutral but increase the conflicts if the manufacturer is risk-averse. At the same time, we also find that the manufacturer's risk-aversion level can ease the channel conflicts. The higher the manufacturer's risk aversion, the more he relies on the traditional channel. When the manufacturer's risk aversion level reaches a certain point, manufacturer encroachment may even produce a “win-win” situation for the manufacturer and retailer in some conditions.

Data-Enabled Real-Time Modeling for Production Systems with Variable Cycle Time

Cycle time is one of the essential parameters that could lead to a significant improvement on the productivity of a manufacturing system. In the traditional manufacturing systems, cycle time for each station is recommended by the vendor and determined based on production line design and through repeated experiments and simulations. Once determined, the cycle time is typically unchangeable during the production operation. Nowadays, the development of smart manufacturing enables a flexible production operation, and the cycle time of each machine can be made changeable to quickly respond to market demand fluctuation and to further improve the system efficiency. To evaluate the performance of a serial production line with variable cycle time, a novel data-enabled manufacturing system model is developed, in which sensor data inputs are allowed and cycle times are modeled as input variables. In addition, an opportunity window concept, which has been studied in the previous study and has been treated as a real-time system status measurement, is extended to the variable cycle time scenario. Numerical case studies are presented to validate the fidelity of the data-enabled model and demonstrate the influence of variable cycle time of individual machines on the production line throughput and the opportunity windows.

МОДЕЛЬ ОПТИМАЛЬНОГО ПЛАНИРОВАНИЯ ПРОИЗВОДСТВАИ ДОСТАВКИ ПРОДУКЦИИ ПОТРЕБИТЕЛЯМ С УЧЕТОМ ЗАТРАТ ПРЕДПРИЯТИЯ НА МАРКЕТИНГ

The newtrendsoftheoryandpracticeoflogistics’ developmentarebasedonlogisticaloperatorsandmanagersofeach links of supply chainsaspirations to earn the maximal profit from integral paradigm of logistics application based on more close interaction between logistic and marketing strategies of firms or companies. At present, it is very actual the development and analysis of optimization models which are accounting simultaneously influence of marketing activity of companies and the logistics conception. In the article, on the basis of classical model of multi-nomenclature products optimal planning by an enterprise side by side the optimal planning of finished product transportation to consumers the economic-mathematical model has been developed and analyzed taking into account the marketing activity of enterprise. It is supposed that demand for finished products is a some increasing function of advertising costs. The concrete form of such dependence may be found in result of corresponding market’s analyses for previous period. In more simple case it may be the linear dependence. It is supposed also that expected demand without cost for advertising is known in result of market analyses. This optimization model allows us to findouttheoptimal joint production and transportationplansandoptimal advertising costs maximizing the total profit of enterprise. The experimental calculations show that interaction of marketing and logistics conceptions allows not only to increase the effectiveness of supply chain functioning as a whole but its every link, as well. The approach proposed may be applied for investigation of more general optimization models takingintoaccount the marketdemand fluctuation over the given planning horizon. The results obtained in the article show that above optimization model of integrated supply chain and its possible generalizations has thedefined perspective of further development in the framework of integral paradigm of logistics.Keywords: supply chain, optimization of the production and transportation plans, demand, marketing activity.

Lean manufacturing implementation and performance: the role of economic volatility in an emerging economy

PurposeThe purpose of this study is to explore the mediation effect of volatile economic conditions on performance benefits of successful kean manufacturing implementation (LMI). The mediating factor of economic volatility (EV) is constructed based on four macroeconomic dimensions – supplier uncertainty, market demand fluctuations, governmental policy changes and peer competition.Design/methodology/approachAn attempt is made to build an exhaustive list of the internal operational manifests grouped into one human and three technical input factors. Similarly the benefits accrued are collated under two performance measures – customer satisfaction (CS) and organizational goal satisfaction (OGS). Based on data from the Indian manufacturing sector, structural equation modelling (SEM) and ordinary least square (OLS) analyses are carried out to validate the proposed model.FindingsResults of the structural model validate the first six hypotheses posited in the model. Results of OLS further reveal the mediation effect of EV having negative impact on LMI–CS and LMI–OGS nexus.Practical implicationsThis research offers a fair understanding of the internal operational lean factors and the effect of volatile macroeconomic conditions on lean benefits. The structural model will aid the academicians and lean implementers comprehend the dimensional structure underlying the lean practices and beliefs. This work further helps to understand the moderation effect of environmental complexity on the output measures of LMI in the Indian manufacturing sector.Originality/valueThis work is one of the very first empirical analyses of lean performance under contingent economic conditions. The paper presents a valuable recommendation to practitioners for considering the dynamism of external economic environment instead of simply adopting standalone internal lean parameters, if satisfactory levels of performance in terms of CS and OGS are to be achieved.

China's Particle Therapy Equipment Market: Opportunities Outweigh Challenges.

Since 2019, China has been the second largest medical device market in the world. At present, high-end radiotherapy equipment such as particle therapy system has a huge market potential due to the grim situation of cancer prevention and control and the growth of people's wealth in China. However, China's MedTech industry, especially the particle therapy equipment field, still faces the influence of policy, fluctuation of market demand, strengthening of industry supervision, and even geopolitical realities. This paper reviews the market prospect of particle therapy medical devices from the perspective of China's medical device policy and demand information analysis, which is conducive to the research on the industrial layout of particle therapy medical physics, and also helps high-performance medical device manufacturers to expand their business visions. MedTech manufacturers should actively adjust their business strategy and implement scientific and technological innovation on the basis of compliance with industry regulatory requirements in order to seize opportunities from challenges and gain profits growth.

Benders’ decomposition for the balancing of assembly lines with stochastic demand

The quality of the balancing of mixed-model assembly lines is intimately related to the defined production sequence. The two problems are, however, incompatible in time, as balancing takes place when planning the line, while sequencing is an operational problem closely related to market demand fluctuations. In this paper, an exact procedure to solve the integrated balancing and sequencing problem with stochastic demand is presented. The searched balancing solution must be flexible enough to cope with different demand scenarios. A paced assembly line is considered and utility work is used as a recourse for station border violations. A Benders’ decomposition algorithm is developed along with valid inequalities and preprocessing as a solution procedure. Three datasets are proposed and used to test algorithm performance and the value of treating uncertainty in mixed-model assembly lines. The integration of the strategic balancing problem with the operational sequencing problem results in more robust assembly lines.

Carbon regulations, production capacity, and low-carbon technology level for new products with incomplete demand information

This study investigates the effects of two carbon regulations on manufacturers’ production capacity and low-carbon technology level for new products with incomplete demand information. As objective functions are not concave, we use the recursive method to solve the optimization problems with/without constraints. The optimal decision rules for production capacity and low-carbon technology level are derived. The theoretical results show that carbon regulations can encourage manufacturers to improve low-carbon technology level, but they limit the manufacturers’ production capacity. The benefits of carbon quotas and subsidies should be considered in conjunction with manufacturers’ planned capacity, as inappropriate trade or subsidy incentives may discourage firms from low-carbon innovation. The carbon cap-and-subsidy regulation increases the decision complexity. In contrast, under the carbon cap-and-trade regulation, policymakers can consider fewer elements. Numerical results show, when the carbon trading price is low, the carbon emissions under the carbon cap-and-subsidy regulation is reduced, but there may be a high subsidy cost for policymakers. However, when the carbon trading price is above a certain threshold, the carbon cap-and-trade regulation is more beneficial for policymakers. Moreover, under the carbon cap-and-trade regulation, manufacturers’ decisions and social welfare are less affected by fluctuations in market demand.

A clean global production network model considering hybrid facilities

The paper presents a cleaner production and distribution model for global facility network that offers reverse logistics services under the warranty period. Hybrid manufacturing and storage facilities with flexible capacity are considered to save the extra setup and maintenance cost linked with establishing new reverse logistics facilities. The carbon emissions are accounted for the various activities related to product manufacturing and return. The carbon cap and trade policy is considered for regulating emissions. The dynamic mixed-integer non-linear programming (MINLP) model discussed in the paper optimizes the total cost of the network including costs associated with reverse logistics. The model is analysed on two hypothetical data sets. The results for the smaller data set reveal that the inventory holding is a better alternative to capacity expansion to deal with fluctuations in market demand. However, for the bigger data set, capacity expansion is recommended to satisfy the increased demand instead of relying completely on inventory management. The results are further analysed for varying carbon price and it is observed that increase in carbon price initially causes an increase in the carbon emissions but later it starts decreasing. This indicates that the increase in carbon price does not provide quick results and is more effective in controlling the emissions in the longer run. Furthermore, the proposed model investigates how different trade policies viz. free trade agreement (FTA), FTA with cap, and an increase in tariff barriers influence the total carbon emissions and the total cost. The results indicate that the total cost and the total emissions are relatively less under FTA with cap, however, there is a slight increase in the emissions of one country.

Considering Random Factors in Modeling Complex Microeconomic Systems

Within the framework of a model describing real-functioning association of three enterprises, numerical calculations of economic dynamics parameters considering fluctuating market demand for the goods were performed. A methodology was suggested for approximated consideration of both seasonal and random demand fluctuations at the market of textile garments; the main steps of the suggested methodology were described. The main exogenous random factors within this model include, as stated above, the volume of market demand for the goods produced by the enterprises of the group. The basic volume of market demand is considered at the average actual level according to the results of the enterprises’ analysis, and additionally we take into account the influence of non-price factors, such as random changes in the consumers’ tastes, consumers’ income, and other random factors on the market demand. By volume of market demand, we consider the total amount of goods produced by the enterprises of the group that all consumers are willing and able to purchase at a specific price in a marketplace. The calculations were made based on actual values of external economic parameters, such as labor cost, product prices, etc. Influence of the market demand fluctuations on the companies’ activity has been illustrated both numerically and graphically, allowing the analysis of the impact of exogenous parameters on the companies output and profits. The suggested approach creates a basis for further analysis of the impact of random factors of a similar nature, i.e., stochastic shocks related to the level of interest rates, shifts and turnabouts in the social environment, as well as the market transformations due to annual/seasonal epidemics.

Dynamic Pricing of Ride-Hailing Platforms considering Service Quality and Supply Capacity under Demand Fluctuation

Increasing attention is being paid to the pricing decisions of ride-hailing platforms. These platforms usually face market demand fluctuation and reflect supply and demand imbalances. Unlike existing studies, we focus on the optimal dynamic pricing of the platforms under imbalance between supply and demand caused by market fluctuation. Dynamic models are constructed based on the state change of supply and demand by using optimal control theory, with the aim of maximizing the platform’s total profit. We obtain the optimal trajectories of price, supply, and demand under three ride demand situations. The effects of some key parameters on pricing decisions, such as coefficient of demand fluctuation, service quality, and fixed commission rate, are examined. We find the optimal dynamic price can improve the match of supply-demand in ride-hailing market and enhance the revenue of platform.

The Politics of Time in Colonial Bombay: Labor Patterns and Protest in Cotton Mills

Abstract This article examines the modes of time and work discipline that emerged through factory industry in colonial Bombay. Based on a wide range of archival sources, it shows that mechanized production did not invariably suggest a transition from task-based, irregular to clock-measured, rationally organized work patterns. Operating simultaneously within temporal orders constructed by the global economy, agriculture, family, and community, cotton mills combined new disciplinary practices with a flexible approach to labor. Gender, marital status, religion, skill, and position in the manufacturing chain influenced the pace and duration of work as well as subjective experiences of time at the factory. By maintaining the diversity and flexibility of time organization, mill owners could adjust production to fluctuations in market demand. At the same time, the strategy facilitated and obscured exploitation. As the industry grew, workers developed a language of resistance that emphasized the value of regular and standard work patterns defined with reference to clock hours and calendar days. In the factories of colonial Bombay, clocks were not just symbols of discipline and subjugation but also instruments of resistance and negotiation.

Research on the Maritime Logistics Pricing Model of Risk-Averse Retailer-Dominated Dual-Channel Supply Chain

Abstract Price decision is studied in a risk-averse retailer-dominated dual-channel supply chain, which consisting of one manufacturers and one retailer with both off-line and on-line channels. Firstly, two mean-variance models in centralized and decentralized supply chain are established. Secondly, the optimal solutions under the two decision modes are compared and analyzed. The results shows that the price of dual-channel of retailer decreased with the increase of retailers’ risk- aversion coefficient and the standard deviation of the fluctuation of market demand, while the wholesale price changes is on the contrary; in addition, when the market demand is greater than a certain value, the prices of dual channel are correspondingly higher in decentralized supply chain than in centralized supply chain, and vice versa. In addition, when the retailer’s risk aversion is in a certain interval, the expected utility of the whole supply chain is greater in centralized supply chain than in decentralized decision, and vice versa. Finally, a numerical example is given to verify the above conclusions.

Understanding reconfigurability of manufacturing systems: An empirical analysis

The need for more responsive manufacturing systems to deal with high product variety and large fluctuations in market demand requires new approaches that enable the system to react to changes quickly and efficiently. Reconfigurability is an ability that allows the addition, removal or rearrangement of manufacturing system components and functions to better cope with high product variety and significant fluctuations in market demand in a cost effective way. This paper empirically investigates the understanding of reconfigurability in industrial manufacturing companies and tests and validates its core characteristics using a questionnaire survey, which was carried out with Portuguese companies. Findings show the existence of five core characteristics of reconfigurability. The implications of these characteristics, concerning the implementation of Reconfigurable Manufacturing Systems, are also analysed and discussed.

Optimization of saving production cost in plastic jute sacks with dynamic programming

The plastic jute sack is one of the most popular rice packaging products in the market. One type of plastic jute sack used is LDPE type. The LDPE sacks used for rice packaging often-experiencing fluctuations in market demand. Fluctuating demand is a certain problem for companies in determining the number of production to meet the demand. It can be seen from the frequent over production companies and stock out at each period. Overproduction problem has an impact to increase production costs. Stock resulted in lost sales experienced adversely affected the company, especially from production cost. Based on the problems, the company must immediately performs an optimal production planning to handle various problems in the company. One method for saving the optimal cost production can be used is dynamic programming. This method aims to obtain the optimal number of production accordance to market demand. This research is done to reduce cost by optimizing number of production. Method that used to solve the problem is dynamic programming. By using this method, the company will obtain optimum production number with minimum production cost and considering total capacity available of the company. From the dynamic programming results obtained optimal production number with cost savings about 2.1%.

Methodical bases of fastplant-technologies for the fast production of niche cultures

Conceptual ideas and methodical approaches to the creation of fastplant-technologies for a rapid development and production of niche cultures are formulated in the article for the first time, specifics of their adaptation to the market conditions, adaptation to the conditions of implementation in the system of artificial modular productions placed on the scientific and production basis of cluster unions of the production of competitive niche products. The principles of selecting the components of the fastplant-system, the designation of elements of the modular design of co-production of niche cultures are given. The features of fastplant-technologies, their structure, methodical recommendations for scientific institutions, in relation to the formation of the commercial type technological proposals for introduction into innovative and investment-active segments of the niche market are determined. In this paper the terminology regarding to the concepts definitions of niche cultures, niche products, niche market, results of testing and analysis methods development and forecasting a niche cultures (products) market, creation of a production self-regulation that depends on commercial conditions, social needs state and society based on a market private partnership market system.
 The seasonal fluctuations of demand for niche crops are analyzed, in this connection the principles of creation a market-oriented technologies and mobile production complexes, which provide conditions for a rapid response to the market demand fluctuations and the deployment of production in the required volumes and quality in the short windows of the off-season, are proposed.
 It is proved that the main problem of the fastplant-technology creation is that the outgoing scientific developments, which are transforming into selection-technological and industrial innovations, have a low coefficient of a commercial ability. Scientific institutions mostly do not possess market-oriented process methods of creation and promotion competitive scientific and innovative products to consumers.
 Innovations developed by consulting companies are more adapted to the harsh market conditions, and therefore more understandable to agribusiness.
 The research presents methodical approaches and regulatory and organizational tools for the preparation of commercial proposals by scientific institutions, on the basis of which the fastplant-technology is created and projects of their use in the science-intensive niche business.

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

A novel formulation for combined scheduling and control of multi-product, continuous chemical processes is introduced in which nonlinear model predictive control (NMPC) and noncyclic continuous-time scheduling are efficiently combined. A decomposition into nonlinear programming (NLP) dynamic optimization problems and mixed-integer linear programming (MILP) problems, without iterative alternation, allows for computationally light solution. An iterative method is introduced to determine the number of production slots for a noncyclic schedule during a prediction horizon. A filter method is introduced to reduce the number of MILP problems required. The formulation’s closed-loop performance with both process disturbances and updated market conditions is demonstrated through multiple scenarios on a benchmark continuously stirred tank reactor (CSTR) application with fluctuations in market demand and price for multiple products. Economic performance surpasses cyclic scheduling in all scenarios presented. Computational performance is sufficiently light to enable online operation in a dual-loop feedback structure.

Practical Applications of ETF Transaction Costs Are Often Higher Than Investors Realize

The bid–ask spread alone does not tell the true cost of trading an exchange-traded fund (ETF). The market prices on most ETFs frequently deviate from their net asset value (NAV) because of fluctuations in market demand and supply. An investor needs to measure the true cost of an ETF trade as the difference between the fund9s current transaction price and its NAV at that point in time. Author James Angel , from Georgetown University , discusses his article, ETF Transaction Costs Are Often Higher Than Investors Realize , published in The Journal of Portfolio Management ’s Spring 2016 issue. In this article, Angel and co-authors Todd Broms of Broms Asset Management and Gary Gastineau of ETF Consultants.com offer their analysis of how and why ETF market prices deviate from their NAVs.

Optimization of line configuration and balancing for flexible machining lines

Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.

Integrated Moving Horizon-Based Dynamic Real-Time Optimization and Hybrid MPC-PID Control of a Direct Compaction Continuous Tablet Manufacturing Process

In this manuscript, a moving horizon-based real-time optimization (MH-RTO) has been integrated with a hybrid model predictive control (MPC) system for a continuous tablet manufacturing process for quality by design (QbD)-based efficient continuous manufacturing. In the proposed approach, the integrated MH-RTO provides the optimal operational set points for the tablet production rate in real time. The MH-RTO takes into consideration the capital and operating cost, the market fluctuations, the product inventory, the product quality assurance strategy, the regulatory constraints, and the product rejections. An advanced hybrid model predictive control system then ensures that the required production rate with desired quality is met with minimum resources and time. A robust optimization strategy and an efficient control system have been integrated to achieve the maximum profit. The MH-RTO integrated with a hybrid control strategy ensures the maximum possible profit irrespective of the market demand fluctuations. The basic advantage of the MH-RTO framework is that it takes into consideration the future demand and thus can lead to increased profit compared to a standard real-time optimization approach.