Market Demand Uncertainty Research Articles

Construction of Ensemble Learning Model for Home Appliance Demand Forecasting

Given the increasing competition among household appliance enterprises, accurately predicting household appliance demand is crucial for enterprise supply chain management and marketing. This paper proposes a combined model integrating deep learning and ensemble learning—LSTM-RF-XGBoost—to assist enterprises in identifying customer demand, thereby addressing the complexity and uncertainty of the household appliance market demand. In this study, Long Short-Term Memory Network (LSTM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) models are established separately. Then, the three individual algorithms are used as the base models in the first layer, with the multiple linear regression (MLR) algorithm serving as the meta-model in the second layer, merging the demand prediction model based on the hybrid model into the overall demand prediction model. This study demonstrates that the accuracy and stability of demand prediction using the LSTM–RF–XGBoost model significantly outperform traditional single models, highlighting the significant advantages of using a combined model. This research offers practical and innovative solutions for enterprises seeking rational resource allocation through demand prediction.

Review on Location of Fresh Cold Chain Logistics Distribution Center

This paper reviews the research status, existing problems and challenges, and future research directions of the location of fresh cold chain logistics distribution centers. The research background is based on factors such as the development of the fresh product market, the technological progress of cold chain logistics, the requirements of environmental protection and sustainable development, and the intensification of market competition. The significance of site selection includes improving transportation efficiency, reducing costs, improving customer satisfaction, optimizing supply chain networks, and achieving environmental sustainability.The former focuses on low-carbon, demand uncertainty, and competitive distribution center location, while the latter focuses on the new retail environment and cold chain distribution. The review of relevant literature points out that some progress has been made in the research, but there are challenges such as market demand uncertainty, incomplete data and limited model applicability.Future research directions include the location model of cold chain logistics distribution center based on big data, the location model considering sustainable development factors, and the location method of cold chain logistics distribution center integrating multi-index evaluation.In the conclusion, it is pointed out that in the past, the time window and the overall logistics network were rarely used as research evaluation indicators in the site selection problems, and the cost of reverse logistics and closed-loop supply chain was rarely considered. In the prospect part, it is proposed that in the future, we should pay attention to the problems of reverse logistics and closed-loop supply chain in the distribution of fresh agricultural products, consider the multi-objective optimization of low-carbon cold chain logistics network in different policies and fields, and combine full simulation technology and optimization technology to realize the system optimization research.

An application of simultaneous stochastic optimisation on an open-pit copper mining complex with supply, recovery, and market uncertainties

ABSTRACT A mining complex is an integrated value chain that consists of multiple mines, stockpiles, processors, waste dumps, and tailing facilities, and where the in-situ materials mined are transformed into products sold to customers. Simultaneous stochastic optimisation provides a strategic mine planning framework that incorporates all components of a mining complex into a single mathematical representation, capitalising on the synergies between components while considering uncertainty. An application of this optimisation framework at a coper mining complex demonstrates that the incorporation of material supply, market demand, and processing recovery uncertainties into the modelling leads to production schedules that yield a higher NPV and metal recovery.

Integrated Model for Predicting Demand of Supersonic Transports Under Low-Boom Constraint

Commercial supersonic aircraft could return between 2035 and 2040 due to the desire for fast travel and advancements in technology that could reduce the cost of supersonic transport. Nevertheless, several challenges remain to make supersonic travel a reality. This paper presents an integrated model that ties the aircraft preliminary design process, the economics of aircraft development and operations, and passenger preferences to estimate worldwide demand for subsonic overland, Mach cutoff, and low-boom aircraft design concepts. This comprehensive and iterative methodology takes into account the uncertainty of market demand for supersonic travel and the complexities of supersonic network operations. Based on the study of four conceptual supersonic designs, we found that low-boom aircraft could attract 28% more demand worldwide compared to an optimized Mach cutoff design because of the additional time-saving benefits on overland routes. The results of this work offer valuable guidance to aircraft designers by explicitly tying the technical parameters of a design and the potential market demand. In addition, the integrated model developed may streamline the initial design development cycle by quantifying fleet size as part of an integrated modeling process.

Divesting or keeping overseas subsidiary production under rising production costs and uncertain market demands in host countries

This study examines whether overseas manufacturing subsidiaries are divested or kept under rising production costs and uncertain market demands in their host countries. We predict that even under increasing production costs, a subsidiary will not be divested but kept under high market demand uncertainty. A multinomial logit analysis of Korean overseas manufacturing subsidiaries finds that an overseas manufacturing subsidiary exposed to high labor cost growth in its host country is not divested but kept alive under high market demand uncertainty via cross-border production volume adjustments with other in-network subsidiaries in different countries. It also shows that the moderating impact of demand uncertainty on production shifts over divestment is pronounced more for the subsidiaries with low cross-country labor cost correlation, high product compatibility, and high ownership share. These findings imply that the longevity of subsidiary operations is shaped by geographic and organizational characteristics determining production shift conditions.

Risk Transmission in Low-Carbon Supply Chains Considering Corporate Risk Aversion

In order to study the impact of risk aversion characteristics of enterprises on supply chain risk transmission, the risk aversion utility function is introduced, and the risk elasticity coefficient is used to construct a supplier-dominated low-carbon supply chain risk transmission model. Simulation analysis is conducted to investigate the transmission of emission reduction and revenue risks caused by internal and external contingent risk factors. The study reveals that under conditions of market demand uncertainty, the risk transmission effect is unaffected by the risk aversion characteristics of members in the low-carbon supply chain. While the risk-aversion characteristics of suppliers can decrease their own profit risk, they have a negative effect on the profit risk of manufacturers and the emission reduction risk of supply chain nodes. There exists a critical threshold for the impact of the risk-aversion degree of suppliers on their own emission reduction risk transmission effect. When this threshold is exceeded, the emission reduction risk decreases with increasing risk aversion intensity of suppliers, and vice versa. The risk aversion characteristics of manufacturers can weaken the negative effect of supplier risk aversion on the fluctuation risk of manufacturer profits, but they exacerbate the emission reduction risk transmission effect of manufacturers under asymmetric information influence. The findings have important theoretical and practical implications for supply chain risk management.

Joint optimization of dynamic pricing, quality, and production quantity in the presence of online reviews: A distributionally robust optimization approach

This paper investigates the joint pricing, product quality, and production quantity decisions of a firm in a two-stage scenario, considering potential market demand uncertainty and the existence of online reviews. Two decision models are established based on whether the firm adjusts product quality and prices according to consumer feedback from reviews: a static model (as a baseline) and a dynamic model. In the static model, the firm decides product quality, prices, and production quantity in the first stage, while in the second stage, the firm does not enhance product quality, and prices remain unchanged. In the dynamic model, in the first stage, the firm decides initial product quality and pricing, then in the second stage, adjusts product quality based on consumer feedback and sets pricing accordingly. We propose a distributionally robust optimization (DRO) method to address this problem, obtaining a closed-form solution for the expected profit function under the worst distribution, making it easy to determine the optimal decision. Through numerical simulation analysis, we find that the firm implementing dynamic decisions always make higher profits compared to those using static decisions. This highlights the superiority of dynamic decisions in adapting to market changes and improving product quality. We also analyze the impact of expected and standard deviation of potential market demand, as well as consumer private assessment weight, on business decisions and profits. Our research provides effective support for firms with limited market information, enabling them to better formulate joint pricing, quality, and production decisions.

Reliability-based maintenance optimization of long-distance oil and gas transmission pipeline networks

This paper presents a maintenance model for optimal planning of pipeline network inspections subjected to corrosion and residual stress. The proposed model includes predictive degradation modeling, spatio-temporal reliability, and expected cost minimization. The pipeline networks are formed by linear segments and irregular zones such as elbows, weld joints, and flanges for putting pipes together and changing the direction of gas or liquid flow. The mean of Karhunen-Loève expansion is used to model space-variant corrosion, residual stress, and stochastic dependency in different exposure zones. Monte Carlo simulations are employed to compute the failure probability of individual components. Subsequently, a Bayesian network evaluates the failure probability of the complex pipeline network and identifies the most critical components. Depending on the objective or market demand uncertainties, a cost model is also proposed to optimize the inspection policy. The methodology is applied to a case study, and the results show that it can provide valuable insights to decision-makers to enhance complex systems' safety and reliability.

Complex dynamics of dual oligopoly demand uncertainty under carbon emission trading mechanism

The international community's growing focus on energy conservation and emission reduction has led businesses to prioritize low-carbon operations and the marketing of environmentally friendly products during their production processes. On the one hand, with the reform of carbon emissions trading, carbon emission trading has become a potential profit point for enterprises. On the contrary, the consumer market is influenced by the uncertain external environment. And consumers' environmental awareness increases the uncertainty of product demand. Therefore, the intricate dynamics of dual oligopoly demand uncertainty within the framework of a carbon emission trading mechanism are explored in this scholarly analysis. The best market Porter's generic strategies, including emission reduction investment and product pricing how can carbon quotas, uncertainty in market demand, and consumer environmental preferences improve expected profits? The results show that technology emission reduction costs, carbon emission trading prices and consumer preferences for low-carbon products. It is an important factor that affects the competitive strategy of the two enterprises. The different values of the above factors will change the relative intensity of emission reduction investment and the relative profitability of the two. Complete company statement in a balanced state. This article also investigates the complexity of adjusting the dynamic evolution path of competitive strategies between two organizations. Feedback controllers can effectively suppress unstable equilibrium states and provide effective references for their stable operation.

Sustainable agility of product development process based on a rough cloud technique: A case study on China's small and medium enterprises.

The importance of incorporating an agile approach into creating sustainable products has been widely discussed. This approach can enhance innovation integration, improve adaptability to changing development circumstances, and increase the efficiency and quality of the product development process. While many agile methods have originated in the software development context and have been formulated based on successful software projects, they often fail due to incorrect procedures and a lack of acceptance, preventing deep integration into the process. Additionally, decision-making for market evaluation is often hindered by unclear and subjective information. Therefore, this study introduces an extended TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method for sustainable product development. This method leverages the benefits of cloud model theory to address randomness and uncertainty (intrapersonal uncertainty) and the advantages of rough set theory to flexibly handle market demand uncertainty without requiring extra information. The study proposes an integrated weighting method that considers both subjective and objective weights to determine comprehensive criteria weights. It also presents a new framework, named Sustainable Agility of Product Development (SAPD), which aims to evaluate criteria for assessing sustainable product development. To validate the effectiveness of this proposed method, a case study is conducted on small and medium enterprises in China. The obtained results show that the company needs to conduct product structure research and development to realize new product functions.

An Investigation of Barriers to Adopt Green Innovation Among Manufacturing Organizations in Vietnam

This research aims to identify the main barriers to green innovation in Vietnam manufacturing organizations. This study began by reviewing the relevant literature and providing a solid theoretical framework to understand the determinants of green innovation for manufacturing firms in the global context. It also helps internal and external stakeholders figure out what influence and how to implement green innovation more efficiently by removing all impediments. Additionally, this article is considered a valuable and rational evidence for prioritizing and directing innovation policies in the manufacturing industry. Based on numerical data from 143 employees at middleand upper-level managers among manufacturing companies around Vietnam, the study found that deficiency of financial resources primarily significantly impacts green innovation adoption, followed by the uncertainty of market demand and lack of government support. However, with limited observations, the investigation did not observe the dynamic effect of green innovation over periods and only focused on the manufacturing sector instead of different industries for generalizing the research results. Moreover, the circumstances of green innovation would be diverse in other nations.
 Keywords: green innovation, manufacturing organizations, government supports, financial barriers, market barriers

The encroachment strategy under eco-innovation collaboration with delayed realized efficiency information

PurposeEco-innovation products, which means achieving more efficient and responsible use of resources and reducing the detrimental impact on the environment, can win a competitive advantage for the enterprises. But it is not easy to implement due to the high cost of eco-innovative technologies development, the uncertainty of market needs and return risk of investment. Many enterprises seek collaborations from their upstream suppliers to jointly carry out eco-innovation, such as Apple, IBM and Nike. A unique feature of collaboration is that efforts by one party enhance the marginal value of the other party's efforts. However, the collaboration will make the partner know the eco-innovation technology and prompt the partner to encroach the market to sell competitive products by herself. Motivated by this observation, this paper considers the optimal collaboration strategy on eco-innovation between upstream and downstream supply chain member and the optimal encroachment strategy of upstream supplier in a supply chain.Design/methodology/approachThis paper models a supply chain wherein a supplier provides products or materials for her manufacturer and cooperates with her manufacturer in eco-innovation. Also, the supplier could encroach on the market to sell similar products by herself. Then this paper uses game theory and mathematical modeling to do relative analysis.FindingsThe analysis reveals several interesting insights. First, eco-innovation collaboration makes supplier encroachment no longer only rely on the encroachment cost. The delayed realized eco-innovation efficiency information also plays a vital role. Second, different from previous research, the authors find the manufacturer's preference for supplier encroachment depends on the uncertainty of eco-innovation efficiency and potential market demand. Third, both partial and full encroachment strategies of the supplier can effectively improve the eco-innovation level.Originality/valueThe paper is the first to take the interplay between collaboration and encroachment into account in a supply chain. The results caution enterprises and policymakers to take vertical collaboration and delayed realized information into account in the competitive supply chain before making any operational decisions. Furthermore, the authors propose that governmental intervention aimed at stimulating supplier encroachment in appropriate circumstances can contribute to the improved environmental performance of products.

Estimation-based production control of manufacturing–remanufacturing systems with uncertain seasonal return and imprecise demand and inventory

Hybrid manufacturing systems utilising raw materials and returned end-of-life products for production are studied. The systems are failure-prone and subject to inventory, market demand and return uncertainties. Thanks to growing environmental and sustainability concerns, the manufacturing sector is currently experiencing a significant growth in the popularity of reverse logistics. However, the practical implementation of production control in such systems is challenging due to return flow uncertainty and variability. To address this challenge, an estimation-based control using the Kalman filter is proposed in this research. The demand and return models employed contain random and deterministic components, with the latter being time-invariant for demand and uncertain with seasonal variations for return. The processing steps used include the estimation of inventory levels and demand and return components, return forecasting allowing cost computation over a long horizon, and the determination of the production and disposal policies adapting to market variations and uncertainties. We classify the systems according to relationships between their production capacity, demand and return ranges. We then present an extensive numerical study of optimal policies for various system classes and show that adaptive policies outperform the conventional ones, thus proving the effectiveness of the proposed production control approach for complex industrially oriented systems.

Evaluasi Emergent Strategy Bisnis PLTS Atap PT X sehubungan dengan Ketidakpastian Strategis Permintaan Pasar

PT X is one of the developers of rooftop solar photovoltaic (PV) power plants in the commercial and industrial sectors in Indonesia. Over time, there has been a strategic uncertainty of market demand since 2022, mainly affected by the strong bargaining position of Wilayah Usaha's state-owned enterprise (Wilus SOE). Wilus SOE plays a significant role, is given priority in the provision of electricity for the public interest as stipulated in the regulation, and also has a dominant share (95 percent in 2020), making it a de facto monopoly in the electricity business in Indonesia. Wilus SOE has legitimacy as a power distributor and therefore has the authority to approve the capacity of rooftop solar PV power plants. Referring to this situation, this research aims to identify the intended strategy of PT X and the emergent strategy in dealing with the strategic uncertainty of market demand. PESTEL analysis (political, economic, sociocultural, technological, environmental, legal) and five-forces framework (competitive rivalry, new entrants, substitute products, suppliers, customers), as well as emergent strategy evaluation, were used as the framework of this research. To strengthen the analysis results, in-depth interviews were also conducted with the management team of PT X. Based on the series of analyses, it can be concluded that PT X's business is strongly influenced by legal factors while the competitive rivalry and customers' factor have very strong forces. On the other hand, PT X has implemented an emergent strategy well in dealing with the strategic uncertainty of market demand, as an effort to maintain the company's profitability. This research is expected to provide benefits for PT X and other rooftop solar PV power plant developers to understand the emergent strategy in order to remain competitive in its business implementation.

A comparative study on a firm’s optimal production decision considering risk aversion and carbon policies

To cope with global warming and achieve the goal of carbon emission reduction, various carbon policies have been implemented in many countries and regions. Some studies have indicated that with the popularity of low carbon, a small proportion of consumers show a green purchasing tendency. However, for firms, it is still difficult to predict the green purchase preferences of most consumers, and firms may face greater market demand uncertainty, which will bring profit risks. We assume that a firm’s decision is subject to its behavioral considerations, that is, its risk attitude. Considering the risk preferences of decision-makers and carbon emission policies, this paper addresses decision optimization in operations management. Our purpose is to analyze the optimal production decisions of risk-averse firms under carbon cap and carbon tax policies. Adopting the CVaR (conditional value-at-risk) criterion, we construct an optimization model with the constraints of carbon policies and obtain the analytic formula of optimal solutions. Then, we compare the optimal operational decisions for risk-averse firms and risk-neutral firms and further explore the impact of risk aversion on production and the parameters of carbon policy. Finally, some numerical studies are presented to analyze the carbon policies and risk aversion on firms’ operational decisions and give some managerial insights based on the analysis results.

Horizontal and vertical demand forecast information sharing in a distributive dual‐channel supply chain considering the manufacturer's product quality improvement

AbstractUnder the influence of market demand uncertainty, we discuss the issue of horizontal and vertical demand forecast information‐sharing in a distributive dual‐channel supply chain composed of a manufacturer, a traditional retailer and an online retailer in which both retailers obtain heterogeneous demand information through big data technology. We analyze vertical information‐sharing strategies in the condition that the manufacturer invests in product quality improvement under different horizontal information‐sharing scenarios. We also explore the value of horizontal information‐sharing across different channels through contrastive analysis. And the equilibrium information‐sharing states in different scenarios are conducted.

The Role of Retail Information Link in MNF's Coordination of Profit and Social Welfare via Procurement Outsourcing

“Retail Link” initially developed by Walmart enables the tier-1 supply chain partners to access the sales big data, and hence achieve demand information sharing. Doing so helps improve supplier relationships, but the supplier can make better wholesale price decisions based on accurate demand information, which might hurt the profit of the multinational firm (MNF) such as Walmart. Therefore, it is observed that some MNFs outsource both procurement and logistics functions to a logistics service provider (LSP) for the benefits of “one-stop-shopping,” and meanwhile, cut the information link with the supplier. This significantly changes their decision interactions and the resulted social welfare. In this article, we build a co-opetition model and study an MNF's two typical outsourcing strategies, where the MNF either outsources the logistics or the bundled functions of procurement and logistics to an LSP. We find that, when the market demand uncertainty is low, the MNF prefers bundled outsourcing given its significant brand image advantage. When the market demand uncertainty is high, the MNF prefers bundled outsourcing regardless of its brand image advantage. Interestingly, when market demand uncertainty is moderate, the MNF prefers bundled outsourcing when its brand image advantage is either not significant or very significant. We further compare the social welfare levels under two outsourcing strategies and find that win–win situations in the senses of the MNF's profit and social welfare can be identified.

Decision-Making of Cross-Border E-Commerce Platform Supply Chains Considering Information Sharing and Free Shipping

For cross-border e-commerce companies with high shipping costs, the existing retailer and the new entrant retailer on the platform are usually concerned with information sharing and free shipping due to the uncertainty of market demand. For this, by establishing a Stackelberg game model between two competing retailers, we analyze the strategy of retailers and explore the business strategies of the cross-border e-commerce platform. The study shows that regarding information-sharing strategies, retailer A’s willingness to share information is positively related to initial market potential and negatively related to market competition intensity. Moreover, retailer B is willing to spend higher information costs to purchase information when the necessity of the product is more elevated. As for a free shipping strategy, if the existing retailer offers free shipping, the new entrant retailer should also offer free shipping service to consumers when the initial market potential is larger. Conversely, when the initial market potential is smaller, the retailer’s willingness to offer free shipping decreases when the intensity of competition in the market increases. When the market tends to be perfectly competitive, the new entrant retailer will not choose a free shipping strategy, and the platform is most profitable when information sharing and free shipping occur simultaneously. However, when the carrier charges a higher shipping fee to customers, the existing retailer is more profitable when the new entrant does not offer free shipping. Therefore, in order to achieve a win-win situation for all parties, the platform needs to develop appropriate operational strategies to influence the decisions of retailers and carriers. Some numerical experiments are made to test the validity of the model and the effect of the parameters involved in the model.

Strategy Analysis for Retailer-Leading Supply Chain under Buyback Contract with Focus Theory of Choice

This paper investigates a retailer-leading two-tier supply chain with a buyback contract under market demand uncertainty, where the retailer first announces a potential maximal order quantity and the supplier then provides a unit wholesale price to influence the retailer’s order quantity. In recent years, an increasing number of experimental studies have reported that even in repeated multi-turn games, the decisions of suppliers viewed as newsvendors deviate significantly from the expectation-maximizing options. In light of this observation, we employ the focus theory of choice to characterize suppliers’ behavioral tendencies and theoretically derive optimal unit wholesale prices based on suppliers’ focus preferences. With these results, we further explore how suppliers’ foci may influence the interactions between the retailer and the supplier. We find that when the supplier takes the positive evaluation system as the decision criterion, optimism degree and confidence level have a negative effect on the wholesale price and a positive effect on the final order quantity, and the final order quantity must be located between the most possible market demand and the upper limit of the market demand. This paper provides a behavioral perspective to analyze suppliers’ optimal responses and their influences on retailers’ decision-making. Theoretical and numerical analyses gain managerial insights for retailers to make decisions when faced with suppliers with different focus preferences.

Collaborative financing and supply chain coordination for corporate social responsibility

Recent research in supply chain (SC) management shows that collaborative financing and coordination can separately improve the SC's corporate social responsibility (CSR). This article examines how reverse factoring (RF) and cost-sharing (CS) contracts initiated by sizable creditworthy retailers interact and can help SCs address various challenges posed by CSR, especially for small- and medium-sized suppliers with limited working capital. RF can simultaneously lead to greater CSR effort and higher profits for all SC members compared to traditional bank financing. We highlight, nevertheless, how some factors, such as market demand uncertainty, the interest rate premia charged by the respective banks, and the supplier's or retailer's bankruptcy risks, determine the adoption and the benefits of the financing devices. Our managerial implications indicate that combining collaborative financing and coordination can simultaneously be profitable for all members of the SC and incentivize the supplier to raise the CSR efforts. Specifically, a CS contract associated with an appropriate financing mechanism can help to improve CSR and the SC's profitability.