Product Price, Quality, and Service Decisions Under Consumer Choice Models

2021 ◽  
Author(s):  
Ruxian Wang ◽  
Chenxu Ke ◽  
Shiliang Cui
Keyword(s):  
Logit Model ◽  
Market Competition ◽  
Service Differentiation ◽  
Problem Definition ◽  
Mixed Integer ◽  
Quality Level ◽  
Service Cost ◽  
Product Price ◽  
Substitutable Products ◽  
Service Duration

Problem definition: In this paper, we develop an integrated framework to study a firm’s joint decisions on product price, quality, and service duration in a variety of monopolistic and competitive scenarios. Academic/practical relevance: Product price, quality, and ancillary service (such as maintenance and factory warranty) are arguably among the most important factors consumers consider when making a purchase decision. Meanwhile, they are also seen as effective instruments for firms to achieve market segmentation. We consider a cost structure for a firm in which the service cost depends on the product quality level. In particular, if quality is associated with product reliability (respectively, complexity), the service cost would decrease (increase) in the quality level. Methodology: We adopt the widely used multinomial logit model and the nested logit model to study consumers’ choice behavior and employ mixed-integer optimization and game theory to conduct analyses. Results: We find that with multiple substitutable products being offered, it is sufficient for a firm to provide only two maximally differentiated service durations at optimality. The quality of each product should be set at a level such that the marginal utility to consumers equals the marginal cost to the firm, independent of the decisions on other products, whereas the pricing decision should take into account all products. In addition, consumer surplus increases when the firm can make more decisions. Managerial implications: Regardless of product substitution and market competition, the optimal quality level and service duration for each product can be determined independently of other products. Moreover, service differentiation can benefit consumers and improve the firm’s profitability at the same time.

Estimating Lost Sales for Substitutable Products with Uncertain On-Shelf Availability

2021 ◽  
Author(s):  
Daniel Steeneck ◽  
Fredrik Eng-Larsson ◽  
Francisco Jauffred
Keyword(s):  
Inventory Management ◽  
Product Category ◽  
Problem Definition ◽  
Lost Sales ◽  
Negative Consequences ◽  
Demand Model ◽  
Data Set ◽  
Probabilistic Choice ◽  
Substitutable Products ◽  
Choice Sets

Problem definition: We address the problem of how to estimate lost sales for substitutable products when there is no reliable on-shelf availability (OSA) information. Academic/practical relevance: We develop a novel approach to estimating lost sales using only sales data, a market share estimate, and an estimate of overall availability. We use the method to illustrate the negative consequences of using potentially inaccurate inventory records as indicators of availability. Methodology: We suggest a partially hidden Markov model of OSA to generate probabilistic choice sets and incorporate these probabilistic choice sets into the estimation of a multinomial logit demand model using a nested expectation-maximization algorithm. We highlight the importance of considering inventory reliability problems first through simulation and then by applying the procedure to a data set from a major U.S. retailer. Results: The simulations show that the method converges in seconds and produces estimates with similar or lower bias than state-of-the-art benchmarks. For the product category under consideration at the retailer, our procedure finds lost sales of around 3.0% compared with 0.2% when relying on the inventory record as an indicator of availability. Managerial implications: The method efficiently computes estimates that can be used to improve inventory management and guide managers on how to use their scarce resources to improve stocking execution. The research also shows that ignoring inventory record inaccuracies when estimating lost sales can produce substantially inaccurate estimates, which leads to incorrect parameters in supply chain planning.

scholarly journals Web-Based Smart Market Applications as a Preference Transition during COVID-19 Pandemic

2021 ◽  
Vol 328 ◽  
pp. 04015
Author(s):  
Ika Oktavia Suzanti ◽  
Fifin Ayu Mufarroha ◽  
Imamah Jauhari
Keyword(s):  
Web Application ◽  
Raw Materials ◽  
Market Competition ◽  
Market Price ◽  
Black Box ◽  
Product Price ◽  
Web Based ◽  
The Public ◽  
Traditional Markets ◽  
Analysis Design

The Smart Market application is a web application that useful for making easier of traders and consumers to carry out buying and selling activities in the midst of the COVID-19 pandemic. In advances technology, it is very relevant to implement website-based buying and selling which is quite easy to reach. Hence these activities become more practical and efficient by online without leave the house and it can be seen by the wider community. Another advantage is that the public can see product price updates so that they can find out the price and prevent the market price of raw materials which tends to fluctuate and become a big government homework that never ends. With the increasingly competitive market competition, the Smart Market system was built to maintain the existence of traditional markets and retain customers who tend to like to shop online. The system has been built by proposing research methodologies including, analysis, design, implementation, and testing. The system has been tested to see the ability using black box techniques and it is found that all features have been running well in accordance with the expected results.

scholarly journals Strategic Management in Local Hospital Markets: Service Duplication or Service Differentiation

2020 ◽  
Author(s):  
Hanh Q. Trinh
Keyword(s):  
Market Structure ◽  
Market Competition ◽  
The United States ◽  
Service Differentiation ◽  
Strategic Decision ◽  
High Tech ◽  
Local Market ◽  
Dyadic Relationship ◽  
American Hospital ◽  
Size Asymmetry

Abstract Background: The purpose of this study is to assess the influences of market structure on hospitals’ strategic decision to duplicate or differentiate services and to assess the relationship of duplication and differentiation to hospital performance. This study is different from previous research because it examines how a hospital decides which services to be duplicated or differentiated in a dyadic relationship embedded in a complex competitive network. Methods: We use Linear Structural Equations (LISREL) to simultaneously estimate the relationships among market structure, duplicated and differentiated services, and performance. All non-federal, general acute hospitals in urban counties in the United States with more than one hospital are included in the sample (n=1726). Forty-two high-tech services are selected for the study. Data are compiled from the American Hospital Association Annual Survey of Hospitals, Area Resource File, and CMS cost report files. State data from HealthLeaders-InterStudy for 2015 are also used.Results: The findings provide support that hospitals duplicate and differentiate services relative to rivals in a local market. Size asymmetry between hospitals is related to both service duplication (negatively) and service differentiation (positively). With greater size asymmetry, a hospital utilizes its valuable resources for its own advantage to thwart competition from rivals by differentiating more high-tech services and reducing service duplication. Geographic distance is positively related to service duplication, with duplication increasing as distance between hospitals increases. Market competition is associated with lower service duplication. Both service differentiation and service duplication are associated with lower market share, higher costs, and lower profits. Conclusions: The findings underscore the role of market structure as a check and balance on the provision of high-tech services. Hospital management should consider cutting back some services that are oversupplied and/or unprofitable and analyze the supply and demand in the market to avoid overdoing both service duplication and service differentiation.

A reliable location-inventory-routing three-echelon supply chain network under disruption risks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ehsan Mohebban-Azad ◽  
Amir-Reza Abtahi ◽  
Reza Yousefi-Zenouz
Keyword(s):  
Supply Chain ◽  
Objective Function ◽  
Problem Definition ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Inventory Routing ◽  
Content Type ◽  
Proposed Model ◽  
Disruption Risk ◽  
Disruption Risks

Purpose This study aims to design a reliable multi-level, multi-product and multi-period location-inventory-routing three-echelon supply chain network, which considers disruption risks and uncertainty in the inventory system. Design/methodology/approach A robust optimization approach is used to deal with the effects of uncertainty, and a mixed-integer nonlinear programming multi-objective model is proposed. The first objective function seeks to minimize inventory costs, such as ordering costs, holding costs and carrying costs. It also helps to choose one of the two modes of bearing the expenses of shortage or using the excess capacity to produce at the expense of each. The second objective function seeks to minimize the risk of disruption in distribution centers and suppliers, thereby increasing supply chain reliability. As the proposed model is an non-deterministic polynomial-time-hard model, the Lagrangian relaxation algorithm is used to solve it. Findings The proposed model is applied to a real supply chain in the aftermarket automotive service industry. The results of the model and the current status of the company under study are compared, and suggestions are made to improve the supply chain performance. Using the proposed model, companies are expected to manage the risk of supply chain disruptions and pay the lowest possible costs in the event of a shortage. They can also use reverse logistics to minimize environmental damage and use recycled goods. Originality/value In this paper, the problem definition is based on a real case; it is about the deficiencies in the after-sale services in the automobile industry. It considers the disruption risk at the first level of the supply chain, selects the supplier considering the parameters of price and disruption risk and examines surplus capacity over distributors’ nominal capacity.

scholarly journals Design and Optimization of Capacitated Supply Chain Networks Including Quality Measures

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Krystel K. Castillo-Villar ◽  
Neale R. Smith ◽  
José F. Herbert-Acero
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Optimization Methods ◽  
Mixed Integer ◽  
Computational Time ◽  
Quality Level ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Quality Costs ◽  
Business Entities

This paper presents (1) a novel capacitated model for supply chain network design which considers manufacturing, distribution, and quality costs (named SCND-COQ model) and (2) five combinatorial optimization methods, based on nonlinear optimization, heuristic, and metaheuristic approaches, which are used to solve realistic instances of practical size. The SCND-COQ model is a mixed-integer nonlinear problem which can be used at a strategic planning level to design a supply chain network that maximizes the total profit subject to meeting an overall quality level of the final product at minimum costs. The SCND-COQ model computes the quality-related costs for the whole supply chain network considering the interdependencies among business entities. The effectiveness of the proposed solution approaches is shown using numerical experiments. These methods allow solving more realistic (capacitated) supply chain network design problems including quality-related costs (inspections, rework, opportunity costs, and others) within a reasonable computational time.

scholarly journals Detecting Customer Trends for Optimal Promotion Targeting

2020 ◽  
Author(s):  
Lennart Baardman ◽  
Setareh Borjian Boroujeni ◽  
Tamar Cohen-Hillel ◽  
Kiran Panchamgam ◽  
Georgia Perakis
Keyword(s):  
Optimization Model ◽  
Problem Definition ◽  
Customer Relationships ◽  
Mixed Integer ◽  
Percentage Error ◽  
Integer Optimization ◽  
Demand Model ◽  
Support Tool ◽  
Demand Models ◽  
Transactional Data

Problem definition: Retailers have become increasingly interested in personalizing their products and services such as promotions. For this, we need new personalized demand models. Unfortunately, social data are not available to many retailers because of cost and privacy issues. Thus, we focus on the problem of detecting customer relationships from transactional data and using them to target promotions to the right customers. Academic/practical relevance: From an academic point of view, this paper solves the novel problem of jointly detecting customer trends and using them for optimal promotion targeting. Notably, we estimate the causal customer-to-customer trend effect solely from transactional data and target promotions for multiple items and time periods. In practice, we provide a new tool for Oracle Retail clients that personalizes promotions. Methodology: We develop a novel customer trend demand model distinguishing between a base purchase probability, capturing factors such as price and seasonality, and a customer trend probability, capturing customer-to-customer trend effects. The estimation procedure is based on regularized bounded variables least squares and instrumental variable methods. The resulting customer trend estimates feed into the dynamic promotion targeting optimization problem, formulated as a nonlinear mixed-integer optimization model. Though it is nondeterministic polynomial-time hard, we propose a greedy algorithm. Results: We prove that our customer-to-customer trend estimates are statistically consistent and that the greedy optimization algorithm is provably good. Having access to Oracle Retail fashion client data, we show that our demand model reduces the weighted-mean absolute percentage error by 11% on average. Also, we provide evidence of the causality of our estimates. Finally, we demonstrate that the optimal policy increases profits by 3%–11%. Managerial implications: The demand model with customer trend and the optimization model for targeted promotions form a decision-support tool for promotion planning. Next to general planning, it also helps to find important customers and target them to generate additional sales.

scholarly journals Optimizing Day-Ahead Electricity Market Prices: Increasing the Total Surplus for Energy Exchange Istanbul

2020 ◽  
Vol 22 (4) ◽  
pp. 700-716 ◽  
Author(s):  
Kursad Derinkuyu ◽  
Fehmi Tanrisever ◽  
Nermin Kurt ◽  
Gokhan Ceyhan
Keyword(s):  
Genetic Algorithms ◽  
Tabu Search ◽  
Social Welfare ◽  
Electricity Market ◽  
Energy Exchange ◽  
Heuristic Algorithms ◽  
Optimization Techniques ◽  
Problem Definition ◽  
Combinatorial Auction ◽  
Mixed Integer

Problem definition: We design a combinatorial auction to clear the Turkish day-ahead electricity market, and we develop effective tabu search and genetic algorithms to solve the problem of matching bidders and maximizing social welfare within a reasonable amount of time for practical purposes. Academic/practical relevance: A double-sided blind combinatorial auction is used to determine electricity prices for day-ahead markets in Europe. Considering the integer requirements associated with market participants’ bids and the nonlinear social welfare objective, a complicated problem arises. In Turkey, the total number of bids reaches 15,000, and this large problem needs to be solved within minutes every day. Given the practical time limit, solving this problem with standard optimization packages is not guaranteed, and therefore, heuristic algorithms are needed to quickly obtain a high-quality solution. Methodology: We use nonlinear mixed-integer programming and tabu search and genetic algorithms. We analyze the performance of our algorithms by comparing them with solutions commercially available to the market operator. Results: We provide structural results to reduce the problem size and then develop customized heuristics by exploiting the problem structure in the day-ahead market. Our algorithms are guaranteed to generate a feasible solution, and Energy Exchange Istanbul has been using them since June 2016, increasing its surplus by 448,418 Turkish liras (US$128,119) per day and 163,672,570 Turkish liras (US$46,763,591) per year, on average. We also establish that genetic algorithms work better than tabu search for the Turkish day-ahead market. Managerial implications: We deliver a practical tool using innovative optimization techniques to clear the Turkish day-ahead electricity market. We also modify our model to handle similar European day-ahead markets and show that performances of our heuristics are robust under different auction designs.

scholarly journals Advantages and disadvantages from enforcing emission restrictions within emission control areas

2016 ◽  
Vol 1 (2) ◽  
pp. 107-132 ◽  
Author(s):  
Maxim A. Dulebenets
Keyword(s):  
Numerical Experiments ◽  
Liner Shipping ◽  
Mixed Integer ◽  
Approximation Procedure ◽  
Service Cost ◽  
Content Type ◽  
Shipping Company ◽  
Advantages And Disadvantages ◽  
Mathematical Programs ◽  
Linearization Techniques

Purpose Emissions produced by oceangoing vessels not only negatively affect the environment but also may deteriorate health of living organisms. Several regulations were released by the International Maritime Organization (IMO) to alleviate negative externalities from maritime transportation. Certain polluted areas were designated as “Emission Control Areas” (ECAs). However, IMO did not enforce any restrictions on the actual quantity of emissions that could be produced within ECAs. This paper aims to perform a comprehensive assessment of advantages and disadvantages from introducing restrictions on the emissions produced within ECAs. Two mixed-integer non-linear mathematical programs are presented to model the existing IMO regulations and an alternative policy, which along with the established IMO requirements also enforces restrictions on the quantity of emissions produced within ECAs. A set of linearization techniques are applied to linearize both models, which are further solved using the dynamic secant approximation procedure. Numerical experiments demonstrate that introduction of emission restrictions within ECAs can significantly reduce pollution levels but may incur increasing route service cost for the liner shipping company. Design/methodology/approach Two mixed-integer non-linear mathematical programs are presented to model the existing IMO regulations and an alternative policy, which along with the established IMO requirements also enforces restrictions on the quantity of emissions produced within ECAs. A set of linearization techniques are applied to linearize both models, which are further solved using the dynamic secant approximation procedure. Findings Numerical experiments were conducted for the French Asia Line 3 route, served by CMA CGM liner shipping company and passing through ECAs with sulfur oxide control. It was found that introduction of emission restrictions reduced the quantity of sulfur dioxide emissions produced by 40.4 per cent. In the meantime, emission restrictions required the liner shipping company to decrease the vessel sailing speed not only at voyage legs within ECAs but also at the adjacent voyage legs, which increased the total vessel turnaround time and in turn increased the total route service cost by 7.8 per cent. Research limitations/implications This study does not capture uncertainty in liner shipping operations. Practical implications The developed mathematical model can serve as an efficient practical tool for liner shipping companies in developing green vessel schedules, enhancing energy efficiency and improving environmental sustainability. Originality/value Researchers and practitioners seek for new mathematical models and environmental policies that may alleviate pollution from oceangoing vessels and improve energy efficiency. This study proposes two novel mathematical models for the green vessel scheduling problem in a liner shipping route with ECAs. The first model is based on the existing IMO regulations, whereas the second one along with the established IMO requirements enforces emission restrictions within ECAs. Extensive numerical experiments are performed to assess advantages and disadvantages from introducing emission restrictions within ECAs.

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