scholarly journals Dynamic Pricing in a Multi-Period Newsvendor Under Stochastic Price-Dependent Demand

Mathematics ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 520 ◽  
Author(s):  
Mehran Ullah ◽  
Irfanullah Khan ◽  
Biswajit Sarkar
Keyword(s):  
Dynamic Pricing ◽  
Demand Uncertainty ◽  
New Technologies ◽  
Rapid Development ◽  
Life Cycles ◽  
Selling Price ◽  
Market Demand ◽  
Newsvendor Model ◽  
Pricing Policy ◽  
Dependent Demand

The faster growth of technology stipulates the rapid development of new products; with the spread of new technologies old ones are outdated and their market demand declines sharply. The combined impact of demand uncertainty and short life-cycles complicate ordering and pricing decision of retailers that leads to a decrease in the profit. This study deals with the joint inventory and dynamic pricing policy for such products considering stochastic price-dependent demand. The aim is to develop a discount policy that enables the retailer to order more at the start of the selling season thus increase the profit and market share of the retailer. A multi-period newsvendor model is developed under the distribution-free approach and the optimal stocking quantities, unit selling price, and the discount percentage are obtained. The results show that the proposed discount policy increases the expected profit of the system. Additionally, the stocking quantity and the unit selling price also increases in the proposed discount policy. The robustness of the proposed model is illustrated with numerical examples and sensitivity analysis. Managerial insights are given to extract significant insights for the newsvendor model with discount policy.

scholarly journals Dynamic Pricing Policy Using Preservation Technology with Stock and Price Sensitive Demand

2020 ◽  
Vol 26 (3) ◽  
pp. 266-274
Author(s):  
Uttam Kumar Khedlekar ◽  
Priyanka Singh ◽  
Neelesh Gupta
Keyword(s):  
Dynamic Pricing ◽  
Policy Decision ◽  
Pricing Strategy ◽  
Selling Price ◽  
Market Demand ◽  
Pricing Policy ◽  
Preservation Technology ◽  
Proposed Model ◽  
Stock Policy ◽  
Dependent Demand

This paper aims to develop a dynamic pricing policy for deteriorating items with price and stock dependent demand. In declining market demand of items decreases with respect to time and also after a duration items get outdated. In this situation it needs a pricing policy to sale the items before end season. The proposed dynamic pricing policy is applicable for a limited period to clease the stock. Policy decision regarding the selling price could aggressively attracts the costumers. Objectives are to maximize the prot/revenue, pricing strategy and economic order level for such a stock dependent and price sensitive items. We are giving numerical example and simulation to illustrate the proposed model.

scholarly journals Retailer’s Optimal Procurement Strategy under Supply Disruption and Stochastic Demand: Backup Sourcing or Simultaneous Sourcing

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Feng Lin ◽  
Jinzhao Shi ◽  
Peng Wu ◽  
Xingxuan Zhuo
Keyword(s):  
Demand Uncertainty ◽  
Wholesale Price ◽  
Stochastic Demand ◽  
Selling Price ◽  
Market Demand ◽  
Supply Disruption ◽  
Sourcing Strategies ◽  
Sourcing Strategy ◽  
Major Disruption ◽  
Better Than

Practically, supply disruption may lead production process to entirely halt (completely disrupted) or the output to differ in the order size (partially disrupted), which makes it more difficult for the retailer to satisfy stochastic market demand. Under the circumstance, the retailer is likely to procure products from two suppliers to effectively alleviate the demand-supply mismatches. Thus, under supply disruption and stochastic demand, this paper develops both backup sourcing and simultaneous sourcing (SS) strategies to analyze the retailer’s performance, where backup sourcing includes wholesale price priority (WPP) and supply reliability priority (SRP). Specifically, (1) under WPP, when the selling price is relatively lower (higher), the retailer is suggested to activate the reliable backup supplier after the realization of supply disruption (demand uncertainty). (2) Under SRP, two scenarios including minor disruption and major disruption can be identified, where the retailer’s order quantity from the reliable (unreliable) supplier under minor disruption scenario is more (less) than that under major. (3) Finally, this paper systematically compares the retailer’s preferences among WPP, SRP, and SS via theoretical results and numerical examples. That is, when the unreliable supplier is more likely to work normally or shortage cost (selling price) is relatively lower, the retailer prefers SPR regarding the unreliable supplier as backup sourcing due to its lower wholesale price and acceptable supply disruption. Otherwise, the retailer is inclined to WPP regarding the reliable supplier as backup sourcing for ensuring all market demand to be satisfied. In addition, unless the emergency prices of two suppliers are extremely higher, backup sourcing strategies could perform better than simultaneous sourcing strategy.

scholarly journals The Impact of Cost Information Sharing on Procurement Contract Design

2020 ◽  
Vol 4 (2) ◽  
pp. 34
Author(s):  
Dong Chao ◽  
Yankang Chen
Keyword(s):  
Private Information ◽  
Demand Uncertainty ◽  
Original Problem ◽  
Contract Design ◽  
Model Parameters ◽  
Selling Price ◽  
Optimal Contract ◽  
Market Demand ◽  
Cost Information ◽  
The Impact

In this paper, we provides contract design mechanisms and analysis for manufacturers to manage decentralized supply chain. Suppose the manufacturer’s final product consists of components, each produced by a different supplier, and the manufacturer first purchases components from suppliers, then assembles them into final product and meet demands aftermarket realization. While supply chain’s internal cooperation always benefits both, suppliers are often reluctant to proactively share their own production cost structure, otherwise manufacturers may depress purchase prices, which may reduce supplier’s profit. Manufacturers on the other hand, prefers to be informed of true cost information in order to gain greater revenues. We takes manufacturer’s perspective and design the optimal contract menu for suppliers, both to enable suppliers to disclose private cost information and to maximize the benefits. We start by modeling the original problem and find that the original problem is a complex multidimensional optimization problem. We then examine the nature of the original problem solving and devise the solution algorithm to arrive at the optimal contract menu. This algorithm reduces the complexity of the original question from o(2 n ) to o(n). We further investigate the influence mechanism of model parameters on the results and find that when market demand increases or the selling price of the final product increases, value of private information increases significantly. However, if market demand uncertainty increases, the value of information may increase or decrease for both sides.

Centralized Decisions for a Two-Stage Supply Chain with Price-Discount Dependent Demand

2018 ◽  
Vol 6 (3) ◽  
pp. 249-259
Author(s):  
Xiyang Hou ◽  
Yongjiang Guo
Keyword(s):  
Supply Chain ◽  
Demand Uncertainty ◽  
Production Capacity ◽  
Selling Price ◽  
Price Discount ◽  
Two Stage ◽  
Demand Information ◽  
Historic Data ◽  
Stage 1 ◽  
Dependent Demand

Abstract In this paper, we study a centralized supply chain for a two-stage with selling price discount. This supply chain consists of a supplier and a retailer. Based on the feature that the product’s selling season is short and the supply chain faces great demand uncertainty. We consider a two-stage scenario where, at the beginning of stage 1, the supplier reserves production capacity based on historic data in advance, stage 2 comes to us after some leadtime, both the supplier and the retailer update the demand information, the retailer then places an order not exceeding the reserved capacity based on the selling-pricing discount dependent demand. We make optimal decisions on the reserved capacity in stage 1, selling price discount and order quantity in stage 2. In this supply chain, the pattern in stage 2 is figured out first, and then stage 1 is cleared as well. Then we present a numerical example to give some insights. Finally we get some conclusions.

SIMULATION OF INVENTORY POLICY FOR PRODUCT WITH PRICE AND TIME-DEPENDENT DEMAND FOR DETERIORATING ITEM

2012 ◽  
Vol 03 (01) ◽  
pp. 1150001 ◽  
Author(s):  
D. SHUKLA ◽  
U. K. KHEDLEKAR ◽  
R. P. S. CHANDEL ◽  
S. BHAGWAT
Keyword(s):  
Inventory Management ◽  
Dynamic Pricing ◽  
Optimal Number ◽  
Pricing Policy ◽  
Data Set ◽  
Maximum Profit ◽  
Net Profit ◽  
Recurrence Method ◽  
Theoretical Results ◽  
Dependent Demand

In a declining market for goods, we optimize the net profit in business when inventory management allows change in the selling prices n times over time horizon. We are computing optimal number of changes in prices, respective optimal prices, and optimal profit in each of the cycle for a deteriorating product. This paper theoretically proves that for any business setup there exists an optimal number of price settings for obtaining maximum profit. Theoretical results are supported by numerical examples for different setups (data set) and it is found that for every setup the dynamic pricing policy outperforms the static pricing policy. In our model, the deterioration factor has been taken into consideration. The deteriorated units are determined by the recurrence method. Also we studied the effect of different parameters on optimal policy with simulation. For managerial purposes, we have provided some "suggested intervals" for choosing parameters depending upon initial demand, which help to predict the best prices and arrival of customers (demand).

The Synergy between CRISPR and Chemical Engineering

2019 ◽  
Vol 19 (3) ◽  
pp. 147-171
Author(s):  
Cia-Hin Lau ◽  
Chung Tin
Keyword(s):  
Viral Vectors ◽  
Chemical Engineering ◽  
Target Genes ◽  
New Technologies ◽  
Rapid Development ◽  
Genetic Circuits ◽  
Viral Packaging ◽  
Conditional Control ◽  
Logic Operations

Gene therapy and transgenic research have advanced quickly in recent years due to the development of CRISPR technology. The rapid development of CRISPR technology has been largely benefited by chemical engineering. Firstly, chemical or synthetic substance enables spatiotemporal and conditional control of Cas9 or dCas9 activities. It prevents the leaky expression of CRISPR components, as well as minimizes toxicity and off-target effects. Multi-input logic operations and complex genetic circuits can also be implemented via multiplexed and orthogonal regulation of target genes. Secondly, rational chemical modifications to the sgRNA enhance gene editing efficiency and specificity by improving sgRNA stability and binding affinity to on-target genomic loci, and hence reducing off-target mismatches and systemic immunogenicity. Chemically-modified Cas9 mRNA is also more active and less immunogenic than the native mRNA. Thirdly, nonviral vehicles can circumvent the challenges associated with viral packaging and production through the delivery of Cas9-sgRNA ribonucleoprotein complex or large Cas9 expression plasmids. Multi-functional nanovectors enhance genome editing in vivo by overcoming multiple physiological barriers, enabling ligand-targeted cellular uptake, and blood-brain barrier crossing. Chemical engineering can also facilitate viral-based delivery by improving vector internalization, allowing tissue-specific transgene expression, and preventing inactivation of the viral vectors in vivo. This review aims to discuss how chemical engineering has helped improve existing CRISPR applications and enable new technologies for biomedical research. The usefulness, advantages, and molecular action for each chemical engineering approach are also highlighted.

scholarly journals Coping with Loss Aversion in the Newsvendor Model

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jianwu Sun ◽  
Xinsheng Xu
Keyword(s):  
Expected Utility ◽  
Loss Aversion ◽  
Confidence Level ◽  
Profit Maximization ◽  
Optimal Order ◽  
Market Demand ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Decision Bias ◽  
Optimal Order Quantity

We introduce loss aversion into the decision framework of the newsvendor model. By introducing the loss aversion coefficientλ, we propose a novel utility function for the loss-averse newsvendor. First, we obtain the optimal order quantity to maximize the expected utility for the loss-averse newsvendor who is risk-neutral. It is found that this optimal order quantity is smaller than the expected profit maximization order quantity in the classical newsvendor model, which may help to explain the decision bias in the classical newsvendor model. Then, to reduce the risk which originates from the fluctuation in the market demand, we achieve the optimal order quantity to maximize CVaR about utility for the loss-averse newsvendor who is risk-averse. We find that this optimal order quantity is smaller than the optimal order quantity to maximize the expected utility above and is decreasing in the confidence levelα. Further, it is proved that the expected utility under this optimal order quantity is decreasing in the confidence levelα, which verifies that low risk implies low return. Finally, a numerical example is given to illustrate the obtained results and some management insights are suggested for the loss-averse newsvendor model.

scholarly journals Metagenomics, gene discovery and the ideal biocatalyst

2004 ◽  
Vol 32 (2) ◽  
pp. 298-302 ◽  
Author(s):  
D.A. Cowan ◽  
A. Arslanoglu ◽  
S.G. Burton ◽  
G.C. Baker ◽  
R.A. Cameron ◽  
...  
Keyword(s):  
New Technologies ◽  
Rapid Development ◽  
Gene Discovery ◽  
Metagenomic Library ◽  
Metagenomic Sequencing ◽  
Optimum Conditions ◽  
Enzyme Screening ◽  
Specific Amplification ◽  
The Ideal

With the rapid development of powerful protein evolution and enzyme-screening technologies, there is a growing belief that optimum conditions for biotransformation processes can be established without the constraints of the properties of the biocatalyst. These technologies can then be applied to find the ‘ideal biocatalyst’ for the process. In identifying the ideal biocatalyst, the processes of gene discovery and enzyme evolution play major roles. However, in order to expand the pool genes for in vitro evolution, new technologies, which circumvent the limitations of microbial culturability, must be applied. These technologies, which currently include metagenomic library screening, gene-specific amplification methods and even full metagenomic sequencing, provide access to a volume of ‘sequence space’ that is not addressed by traditional screening.

scholarly journals A Comprehensive Survey on Cyber-Physical Smart Grid Testbed Architectures: Requirements and Challenges

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1043
Author(s):  
Abdallah A. Smadi ◽  
Babatunde Tobi Ajao ◽  
Brian K. Johnson ◽  
Hangtian Lei ◽  
Yacine Chakhchoukh ◽  
...  
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Smart Grids ◽  
Data Exchange ◽  
Information Technologies ◽  
New Technologies ◽  
Rapid Development ◽  
Environmental Benefits ◽  
Future Research ◽  
Time Data

The integration of improved control techniques with advanced information technologies enables the rapid development of smart grids. The necessity of having an efficient, reliable, and flexible communication infrastructure is achieved by enabling real-time data exchange between numerous intelligent and traditional electrical grid elements. The performance and efficiency of the power grid are enhanced with the incorporation of communication networks, intelligent automation, advanced sensors, and information technologies. Although smart grid technologies bring about valuable economic, social, and environmental benefits, testing the combination of heterogeneous and co-existing Cyber-Physical-Smart Grids (CP-SGs) with conventional technologies presents many challenges. The examination for both hardware and software components of the Smart Grid (SG) system is essential prior to the deployment in real-time systems. This can take place by developing a prototype to mimic the real operational circumstances with adequate configurations and precision. Therefore, it is essential to summarize state-of-the-art technologies of industrial control system testbeds and evaluate new technologies and vulnerabilities with the motivation of stimulating discoveries and designs. In this paper, a comprehensive review of the advancement of CP-SGs with their corresponding testbeds including diverse testing paradigms has been performed. In particular, we broadly discuss CP-SG testbed architectures along with the associated functions and main vulnerabilities. The testbed requirements, constraints, and applications are also discussed. Finally, the trends and future research directions are highlighted and specified.

Digital Transformation of the Service Sector

2021 ◽  
pp. 41-54
Author(s):  
D. Shevchenko ◽  
V. Mihaylov
Keyword(s):  
Business Model ◽  
Service Sector ◽  
New Technologies ◽  
Rapid Development ◽  
Digital Transformation ◽  
Services Sector ◽  
Remote Maintenance ◽  
New Business ◽  
The Difference ◽  
Cloud Technologies

The article is devoted to the problems of digital transformation of companies in the service sector. The article describes the concepts of "digitization", "digitalization", "digital transformation", "automation". The analysis of the main sectors of the public services sector, the processes of transformation into a new business model of their development is carried out. Specific examples show the role of digital technologies implemented by individual companies, the leaders of their industry: "Internet of Things" (IoT); virtual diagnostics of the service; mobile applications and portals; artificial intelligence and machine learning (AI / ML); remote maintenance; UX design; virtual reality; cloud technologies; online services and others. The authors proceed from understanding the difference between automation and digitalization, the strategic goal of which is to create a new digital business model that creates new value. The result of digital transformation is the reconfiguration of processes that change the business logic of the company and the process of creating value. The article concludes that the rapid development of new technologies leads to the fact that companies face not only a dilemma when choosing the most suitable technologies for investment, but also the problem of staffing and finding an adequate organizational structure to create and maintain a new business model of the company.

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