Demand Amplification Research Articles

Enhance Productivity In The Garment Industry Through A Modified Value Stream Mapping Approach

The objective of this study is to overcome problems that occur in the garment industry, the company has tried to develop an agile system to increase productivity in this industry. The garment company that focusses on the production of woven bottoms and outerwear, noted that women's woven bottoms products have the highest demand throughout 2022. However, the company was unable to meet Brand demand of 3.5%. Production data shows defects in products, low quality raw materials, and unstable production processes. A modified Value Stream Mapping (VSM) methodology is use to consider all aspects of production. The results of traditional VSM and Value Stream Analysis Tools (VALSAT) analysis include current state and future state, identification of value added and non-value-added elements during the production process, as well as setting priorities to reduce waste in the production process, especially in inventory (19%), defective parts (17%), and transportation (15%). Based on the VALSAT matrix, Process Activity Mapping (33.5%), Supply Chain Response Matrix (21.6%), and Demand Amplification Mapping (15.3%) were obtained. The findings of this research are Pilot Run, which succeeded in becoming an agile and reliable system during the production process. Through the application of the methodology combined with VSM the results have improved compared to the traditional VSM method. This proves that this method is effective in overcoming takt time, cycle time, man power, and value-added ratio. Limitations of this research were also discussed, including that this research only focused on women's woven bottom products only on the production workflow. Kata Kunci: Agile System, Enhance Productivity, Garment Manufacturing, Lean Manufacturing, Value Stream Mapping.

Trend Conformity Behavior of Luxury Fashion Products for Chinese Consumers in the Social Media Age: Drivers and Underlying Mechanisms.

When a bandwagon consumption trend of luxury fashion products appears, potential consumers tend to conform to the trend. The conformity behavior is enhanced by social media because it makes bandwagon trends more visible. However, no research has explored the drivers of fashion trend conformity in the social media age and the underlying mechanisms. Our empirical research demonstrates that fashion trend conformity is a socially directed type of behavior driven by trend perception and reference group pressure, which represent the informational and normative social influence stimuli, respectively. In addition to the direct impact, we also examine the mediating roles of demand amplification and the urge to buy impulsively (UBI). Demand amplification and UBI, respectively, reflect the rational cognitive reaction and irrational emotional reaction to stimuli of fashion bandwagon consumption. However, our results show that only the cognitive reaction path works, but the emotional reaction path does not. Put simply, trend conformity behavior is largely the result of consumers' rational reactions rather than irrational reactions to the social influence stimuli of bandwagon consumption. Our study contributes to the research on luxury fashion consumption by introducing three new concepts, i.e., fashion trend conformity, trend perception, and demand amplification, to describe and theorize the characteristics of consumer behavioral patterns for luxury fashion products and new drivers and novel underlying mechanisms of consumer behaviors in the social media age. Our findings offer practical insights for retailers and manufacturers to promote fashion trend conformity behavior.

Retailer access pricing and supplier relations in the agency model

AbstractIn vertical relations where a retailer enters into agency contracts with multiple heterogenous suppliers of unrelated products, I show the retailer can turn the products into complements or substitutes by charging or subsidizing consumers for access. The optimal access price depends critically on the revenue share that the retailer takes from each supplier, and the retailer's cross‐price elasticity with respect to each supplier's price. When firms price simultaneously, the retailer optimally subsidizes consumer access if and only if the aggregate of these two factors across all suppliers exceeds 1. When the retailer prices before suppliers, it benefits from an additional demand amplification effect: The retailer can use the access price to manipulate suppliers' best responses such that they always lead to demand surges across the whole network of suppliers, which then benefits the retailer through revenue sharing. Under different circumstances, the retailer may achieve this through either further raising a positive access price, or further reducing a negative access price.

PEMETAAN PENCIPTAAN NILAI PADA AKTIVITAS PENGADAAN DAN PENJUALAN SKRAP LOGAM KALENG MENGGUNAKAN VALUE STREAM MAPPING UNTUK MENGURANGI WASTE DI PT ANISA JAYA UTAMA

Industrialization is an alternative development model needed by the country to spur economic processes. Apart from accelerating the economy, the development of industrialization also has impacts that need to be watched out for, including the presence of a waste industry. One of the companies that manages the waste, namely PT. AJU is also a service company for the procurement and sale of metal waste (metal scrap) in Karawang. The metal scrap studied is canned metal scrap, which is wasteful in the procurement and sales process. So that efforts are made to minimize the waste that occurs. This research uses the Value Stream Mapping method with VALSAT analysis. Based on the research results, the most common types of waste are waiting (28%), inventory (24%), and movement (20%). Then the mapping tools that will be used based on the results of converting the questionnaire scores into the VALSAT matrix are Process Activity Mapping (33%), Supply Chain Response Matrix (20%), and Demand Amplification Mapping (17%). The Value Added Ratio (VAR) before the repair has a value proportion of 3%, while after the repair analysis the VAR value becomes 9%.

Reserve Accumulation, Macroeconomic Stabilization, and Sovereign Risk

Abstract In the past three decades, governments in emerging markets have accumulated large amounts of international reserves, especially those with fixed exchange rates. This article proposes a theory of reserve accumulation that can account for these facts. Using a model of endogenous sovereign default with nominal rigidities, we argue that the interaction between sovereign risk and aggregate demand amplification generates a macroeconomic-stabilization hedging role for international reserves. We show that issuing debt to purchase reserves during good times allows the government to stabilize aggregate demand when sovereign spreads rise and rolling over the debt becomes more expensive. We provide empirical evidence consistent with the model’s predictions.

Seismic demand amplification of steel frames with SMAs induced by earthquake sequences

This paper investigates the inelastic seismic demands of steel frames equipped with shape memory alloys (SMAs) subjected to mainshock-aftershock earthquake sequences. Based on the multiple nonlinear stages of steel frames equipped with SMAs, a trilinear self-centring hysteretic model is introduced and validated first. Then, inelastic spectral analyses of steel frames equipped with SMAs subjected to mainshock-aftershock earthquake sequences are conducted. In particular, the energy modification factors of the corresponding single-degree-of-freedom (SDOF) under single mainshocks and mainshock-aftershock earthquake sequences are examined and compared. The results show that the energy modification factor of steel frames equipped with SMAs under mainshock-aftershock earthquake sequences is higher than that under single mainshocks, and the energy modification factor shows sensitivity to trilinear self-centring hysteretic parameters. Last, an amplification coefficient is developed and estimated for quantifying the amplification effect of recorded mainshock-aftershock earthquake sequences on the energy modification factor. Specifically, several machine learning (ML) algorithms are implemented and compared for estimation and interpretation. The results indicate that the XGBoost model performs best in predicting the amplification coefficient with the highest coefficient of determination of 0.9845. Besides, the interpretable ML approaches including partial dependence plot (PDP) and shapely additive explanations (SHAP) are proved helpful in explaining the trained ML model.

Seismic response of slender MDOF structures with self‐centering base shear and moment mechanisms

AbstractAs the amplification of seismic force demands due to higher‐mode effects on tall buildings is increasingly recognized as a design challenge, a number of high‐performance systems have been proposed to limit such effects through combined base shear‐limiting and moment‐limiting dual mechanisms. To better understand the influence of these dual base systems on the overall seismic behavior of tall buildings, this paper presents a study on the seismic response of Multi‐Degree‐of‐Freedom (MDOF) systems incorporating combined base shear‐limiting and moment‐limiting mechanisms. For an MDOF system with a given initial period and base strength level, the base shear‐limiting mechanism is defined by a shear strength factor, an inelastic stiffness parameter, and an energy‐dissipation parameter, while the base moment‐limiting mechanism is defined by a moment strength factor. To determine the influence of these parameters on the overall seismic responses of MDOF structures, a comprehensive parametric study was conducted, and the results were presented and discussed in terms of base displacement and rotation demands, seismic force demand amplification at the base and along the height, peak floor acceleration, peak roof drift, and absorbed energy. The numerical modeling methodology used in the parametric study was validated against 200 small‐scale shaking table tests of a scaled MDOF specimen with a base shear and moment dual‐mechanism system and was used to model MDOF structures that are representative of tall buildings with initial periods ranging from 1.0 to 10 s and having various base‐mechanism properties. The parametric study was then conducted using an ensemble of 20 Ground Motions (GM) scaled to three code‐specified seismic hazard levels for Los Angeles, California. The results of this study can be used to facilitate the design of base shear and moment dual‐mechanism systems for mitigating higher‐mode effects and enhancing the seismic resilience of tall buildings.

Analysis of Sub-Optimization Impact on Partner Selection in VMI

Different combinations of elements will lead to different system functions, so a supply chain composed of enterprises with different characteristics will lead to differences in the system performance. In this study, a vendor-managed inventory (VMI) model is built; the model takes into consideration the factors of demand amplification, order and inventory cost change. Then, the change in the revenue of the supply chain and its members—due to VMI—are represented, and the influence of the different production parameters on this change is analyzed. On the basis of proving the distinctive feature of the Kaldor–Hicks improvement possessed by VMI, the profit fluctuations of enterprises in a supply chain that is composed of members with different characteristics using VMI are calculated by a numerical experiment. The conclusions of this paper indicate why enterprises prefer to choose VMI partners, and the results confirm the sub-optimal characteristic of this tendency. In addition, the results also reveal the inherent contradiction of VMI between supply chain efficiency improvement and coordination among the supply chain’s members. If an enterprise chooses VMI partners solely to maximize its own interests, the possibility of Pareto improvement in the supply chain will be maximized. However, at this time, a more effective supply chain system cannot be organized.

Mitigating bullwhip effect in an agent-based supply chain through a fuzzy reverse ultimatum game negotiation module

Supply Chain Management is frequently regarded as a distributed system whose productivity is mainly influenced by healthy interaction and cooperation among members. Examples of such inefficiencies can be seen in “Demand amplification” referring to asymmetric increase of demands among supply echelons due to both operational and behavioral causes. This paper addresses defective loops of non-cooperation as well as absence of information to manage the dynamics of demand amplification in a four-echelon supply chain; a new agent-based structure is suggested to facilitate the cooperation and coordination among major components and provide a structured context for interactive information sharing. Adequate motivation to share the required information is derived from an automated negotiation between retailer and manufacturer echelons in a four-echelon serial supply model. In doing so, the retailer agent would be encouraged to share customer demand information using Token-Based ordering policy, through a Reverse Ultimatum Game negotiation module. A novel fuzzy approach is suggested in order to cope with ambiguities involved in this negotiation; Numerical experiments prove that the proposed fuzzy negotiation mechanism can warrant the agreement among negotiating parties in nearly half the number of RUG iterations with 30% agreement share. This success in bringing the negotiation parties to an agreement results in the bullwhip effect decreasing by 30% in a four-echelon agent-based supply system.The proposed agent-based supply model which is designed to facilitate this cooperative decision-making process includes some unique innovative features: the knowledge base of the proposed system is able to retrieve and reuse the previous negotiation outcomes, through a gradual learning module. A combination of Case-Based Reasoning and Rule-Based inference mechanisms are applied to facilitate this, so prior cases will be stored in a Frame-Based structure. Eventually, the integrity of the proposed agent-based system is examined through combining Top-Down and Subsets integration approaches and some numerical experiments are provided to confirm the efficiency of the proposed agent-based structure in bullwhip effect management.

Monetary Policy and Inequality under Labor Market Frictions and Capital-Skill Complementarity

We provide a new channel through which monetary policy has distributional consequences at business cycle frequencies. We show that an unexpected monetary easing increases labor income inequality between high-skilled and less-skilled workers. To rationalize these findings, we build a New Keynesian DSGE model with asymmetric search-and-matching (SAM) frictions and capital-skill complementarity (CSC) in production. We show that CSC on its own introduces a dynamic demand amplification mechanism: the increase in high-skilled employment after a monetary expansion makes complementary capital more productive, encouraging a further rise in investment demand and creating a multiplier effect. SAM asymmetries magnify this channel. (JEL E32, E52, E24, E12, E25, J63)

A Model of Asset Price Spirals and Aggregate Demand Amplification of a 'COVID-19' Shock

In this paper we: (i) provide a model of the endogenous risk intolerance and severe asset price and aggregate demand contractions following an adverse real (non-financial) shock; and (ii) demonstrate the effectiveness of Large Scale Asset Purchases (LSAPs) in addressing these contractions. The key mechanism stems from heterogeneous risk tolerance: as a recessionary shock hits the economy and brings down asset prices, risk-tolerant agents' wealth share declines and their leverage rises endogenously. This reduces the market's risk tolerance and generates downward pressure on asset prices and aggregate demand. When monetary policy is unconstrained, it can offset the decline in risk tolerance with an interest rate cut that boosts the market's Sharpe ratio. However, if the interest rate policy is constrained, new contractionary feedbacks arise: recessionary shocks lead to further asset price and output drops, which feed the risk-off episode and trigger a downward loop. In this context, LSAPs improve asset prices and aggregate demand by transferring risk to the government's balance sheet, which reduces the market's required Sharpe ratio and reverses the contractionary feedbacks. Quantitatively, we show that aggregate shocks and LSAPs have large impacts on asset prices when the model is calibrated to fit the inelastic demand for aggregate assets uncovered in recent literature. We also show that heterogeneity in risk tolerance explains part of the demand inelasticity in normal times, and further reduces the elasticity after a recessionary shock. The COVID-19 shock and the large response by all major central banks provide a vivid illustration of the environment we seek to capture.

Multi-objective optimisation framework of genetic programming for investigation of bullwhip effect and net stock amplification for three-stage supply chain systems

In this work a multi-objective optimisation framework of genetic programming (GP) in the modelling of bullwhip effect and NSA for centralised and decentralised supply chain systems has been proposed. The individual and interactive effect of these four input factors has been investigated on bullwhip effect and NSA by adapting the parametric and sensitivity approach on the formulated models. The appropriate settings of dominant input factors (batch ordering and demand signal processing for a decentralised chain, demand signal processing and rationing shortage gaming for a centralised chain) are suggested to optimise the bullwhip effect and NSA of three-stage supply chain simultaneously. The implications and advantages of proposed optimisation framework will be useful for business practitioners to monitor and supervise the sudden demand amplification that generally faced by them in the supply chains.

Time-of-use pricing model based on power supply chain for user-side microgrid

The user-side microgrid offers great potential for improving energy efficiency. This flexible and small-scale power system is characterized by multiple types of clean power supplies. The power supply chain can reveal the supply-demand relationships in the series of steps from power generation to consumption. However, electricity prices tend to vary and can significantly affect the actual energy costs to end-users and other entities in the power supply chain. In this study, we propose an optimization model of time-of-use pricing for the user-side microgrid from the perspective of power supply chain management. The objective of this model is to minimize the total cost of the power supply chain and optimize the charging-discharging behaviors of end-users. First, to reduce the impact of demand amplification and variation, we investigated the bullwhip effect of the power supply chain. Then, we considered distributed energy storage as an important component of the user-side microgrid and how electric power companies can utilize pricing strategies to optimize the charging-discharging behaviors of end-users. We performed experiments based on two scenarios that assumed end-users with and without distributed energy storage devices. A comparative analysis of the modelling results indicates that optimal time-of-use pricing can support the charging-discharging behaviors of residential users and reduce the cost of the entire electric power supply chain. The optimized time-of-use price is important for stability, flexibility, and efficiency improvement in both the user-side microgrid and the entire power supply chain.

Ductility demands and residual displacements of pinching hysteretic timber structures subjected to seismic sequences

Building structures constructed of timber components are characterized by a pinching-type hysteresis that indicates degraded stiffness and strength. Owing to the significant effect of their loading history, these types of structures may be more prone to failure when subjected to sequential seismic excitations. This study investigates the effect of seismic ground motion sequences on the ductility demands and residual displacements of building structures with pinching hysteretic models. A single-degree-of-freedom (SDOF) structure is considered, and is modeled with the hysteretic model consisting of a slip element and a bilinear element. The seismic ground motion sequences are simulated by repeating ground motion records with differing intensities. Through dynamic time history analysis, the effect of the seismic intensity, ductility level, hysteretic parameters, and site conditions are investigated. The results indicate that the seismic sequences amplify the ductility demands of pinching hysteretic structures, and this effect is more significant for short period structures. The pinching hysteretic structures have ductility amplification factors that are higher than those of bilinear hysteretic structures. The residual displacement shows a relatively strong correlation to the maximum displacement, and the ratio of residual displacement to maximum displacement approximately obeys an exponential probability distribution. Based on the numerical results, empirical formulas for estimating the ductility demand amplification and the probability density distribution of the residual displacement are proposed.

Game—The Online Wood Supply Game

This paper describes the Wood Supply Game (WSG), a prize-winning e-learning tool that is freely available for players all over the world. The game effectively helps students and managers realize the challenges in managing demand and supply in wood supply chains, and gain insight into the types of measures required to make these divergent chains effective. The WSG is an adaptation of the Beer game, a popular didactic tool used to empirically demonstrate demand amplification in a simple and generic context. The supply chain modeled by the Beer game does not involve co-products, and thus is very different from the wood supply chain, which is divergent by nature. The WSG presented in this paper models a supply network with one point of divergence and demand for two products. This preserves the simplicity of the game but enables it to offer a base for supply network simulation in a large number of industrial sectors with divergent processes. We describe an online version of the WSG, discuss our experiences playing it with students and managers, and provide hints to the instructor.

Sensitivity analysis of pounding between adjacent structures

SummaryThis article deals with sensitivity of the response of pounding buildings with respect to structural and earthquake excitation parameters. A comprehensive sensitivity analysis is carried out by means of Monte Carlo simulations of adjacent single degree of freedom impacting oscillators. This sensitivity analysis, based on Sobol's method, computes sensitivity indexes which provide a consistent measure of the relative importance of parameters such as the dimensionless main excitation frequency, the mass and frequency ratios of the structures, and the coefficient of restitution. Moreover, the influence of nonlinear behavior of the impacting structures is also considered. The consequences of pounding on the structures themselves are analyzed in terms of maximum force and nonlinear demand amplification compared with the case without pounding. As for the influence of pounding on the floor response spectra, the quantity of interest is the maximum impact impulse. The overall conclusions of this analysis are that the frequency ratio is the most important parameter as far as the maximum force and nonlinear demand are concerned. Regarding the maximum impact impulse, the mass and frequency ratios are, in general, the most influential parameters, the mass ratio being predominant for low frequencies of the oscillator of interest.

Influential Structural Parameters of Pounding between Buildings during Earthquakes

This article studies the sensitivity of the response of pounding buildings with respect to structural and earthquake excitation parameters. A comprehensive sensitivity analysis is carried out by means of Monte Carlo simulations of adjacent single degree of freedom impacting oscillators. This sensitivity analysis, performed with Sobol”s method, computes sensitivity indexes which provide a consistent measure of the relative importance of parameters such as the dimensionless main excitation frequency, the mass and frequency ratios of the structures and the coefficient of restitution. Moreover, the influence of nonlinear behaviour of the impacting structures is also considered. The consequences of pounding, on the structures themselves, are analyzed in terms of maximum force and nonlinear demand amplification compared to the case without pounding.

Fuzzy knowledge-based token-ordering policies for bullwhip effect management in supply chains

The "Bullwhip Effect" is a well-known example of supply chain inefficiencies and refers to demand amplification as moving up toward upstream echelons in a supply chain. This paper concentrates on representing a robust token-based ordering policy to facilitate information sharing in supply chains in order to manage the bullwhip effect. Takagi---Sugeno---Kang and hybrid multiple-input single-output fuzzy models are proposed to model the mechanism of token ordering in the token-based ordering policy. The main advantage of proposed fuzzy models is that they eliminate the exogenous and constant variables from the procedure of obtaining the optimal amount of tokens which should be ordered in every period. These fuzzy approaches model the mentioned mechanism through a push---pull policy. A four-echelon SC with fuzzy lead time and unlimited production capacity and inventory is considered to survey the outcomes. Numerical experiments confirm the effectiveness of proposed policies in alleviating BWE, inventory costs and variations.

A simulation model of a coordinated decentralized supply chain

AbstractThis paper presents a simulation‐based study of a coordinated, decentralized linear supply chain (SC) system. In the proposed model, any supply tier considers its successors as part of its inventory system and generates replenishment orders on the basis of its partners’ operational information. We show that the proposed coordinated decision‐making process creates a reduction in information distortion along an SC compared with a traditional, noncoordinated strategy. A novel result is that we show how a coordinated SC can avoid the detrimental consequences of demand amplification in terms of penalty costs due to the stockout phenomenon in upstream stages.

Information management strategies and supply chain performance under demand disruptions

The operations management literature presents inadequate comprehensive understanding on information management strategies of mitigating supply chain disruption risks. By using control theory modelling and simulation, this study compares the disruption mitigation effects of three information management strategies. From the aspect of stability, the existing stability boundaries are revised by a new method in a two-echelon case. It shows that supply chains (SC) with popular information management strategies are not evidently more stable than traditional ones. From the aspect of disruption recovery time, an innovative two-echelon swiftest response problem under these information management strategies is formulated and solved. Results show that a collaborative planning, forecasting and replenishment (CPFR) SC with complete SC information performs the best. However, in a later operational risk mitigation test, an information sharing (IS) SC with partial information has the smallest bullwhip effect. From the aspect of demand amplification and frequency response, an innovative frequency–response plot of order amplification is proposed in a time-continuous SC with moving average forecasts. It implies the best frequency response for concurrently mitigating both operational and disruption risks coming from a CPFR SC. But for a certain SC structure there is still a balance between mitigating bullwhip effect and quick response. Moreover, it also implies that anti-bullwhip should exist in a certain condition, as realised in our numerical experiments.