Showing papers by "Shib Sankar Sana published in 2018"

Optimal Pricing of competing retailers under uncertain demand-a two layer supply chain model

Abstract: The paper studies a two-echelon supply chain comprising of one manufacturer and two competing retailers with sales price dependent demand and random arrival of the customers. The manufacturer acts as the supplier who specifies wholesale price for the retailers and the retailers compete with each other announcing different sales prices. We analyse a single-period newsvendor type model to determine the optimal order quantity, considering the competing retailers’ strategies.The unsold items at the retailers are buyback to the manufacturer at less price than the sales prices.On the other hand, the retailers face shortages as the demand is uncertain in nature. The profit functions of manufacturer and two retailers are analyzed and compared following Stakelberg, Bertrand, Cournot–Bertrand and integrated approaches. Moreover, distribution-free model is analyzed for integrated profit of the chain. A numerical example is given to illustrate the theoretical results developed in each case. Computational results show that it is always beneficial in integrated system for the members of the chain.

Managing green house gas emission cost and pricing policies in a two-echelon supply chain

Abstract: Reduction of green house gas (GHG) emission is becoming a vital issue to protect our environment. In this point of view, industrial firms’ managers have to consider the cost of emissions trading in their policies to control GHG emission as almost all developed and developing countries of the world are now implementing some norms and penalty for GHG emission. The present article deals with a manufacturer–retailer supply chain model where cost of GHG emission during manufacturing process is taken into account. The profit functions of decentralized and centralized models are analyzed and compared considering emissions trading schemes. This study suggests to the manager of manufacturing firm who may apply two policies, shortages and adjustment of wholesale price, to reduce GHG emission. Although both policies are beneficial for GHG trading, the manufacturer prefers to allow shortages while the retailer prefers the other. Revenue sharing contract and asymmetric Nash bargaining strategy are used to resolve channel conflict and to share surplus profit between the channel members. Finally, a numerical example is presented to validate the proposed model.

Managing a retailer’s dual-channel supply chain under price- and delivery time-sensitive demand

Abstract: This paper aims to explore optimal pricing policies and characteristics of a two-level dual-channel supply chain under price- and delivery time-sensitive demand. Besides price of the product, the delivery lead time is also a crucial factor in customers’ purchase decisions. A longer delivery lead time would diminish customers’ acceptance and faithfulness on the online channel, while a shorter delivery lead time would lead to incorporation of a substantial amount of logistics costs. In formulation of mathematical model, the effects of delivery lead time on the manufacturer and the retailer’s pricing strategies and profits in cooperative and non-cooperative dual-channel supply chain are explained analytically.,The analytical models are formed for both non-cooperative and cooperative scenarios under inconsistent and consistent pricing. The authors examine whether revenue sharing (RS) contract or delivery cost sharing contract can solely coordinate the dual-channel supply chain. If a single contract fails, then the combination of RS contract with delivery cost sharing to achieve channel coordination is discussed.,It is found that the RS or delivery cost sharing contract cannot coordinate the channel individually but revenue and delivery cost sharing contract jointly coordinate the channel. All analytical results are illustrated numerically, along with sensitivity analysis.,There are many correlated issues that need to be further investigated. First, one good extension to this research may include the consideration of the channel structure with competitive retailers. It will be interesting to analyze the performance of coordination mechanisms by considering the retailer as a Stackelberg leader in retailing.,The findings and subsequent methodological discussions aim to provide practical guidance to retailers who are allowing customers to choose how, when and where they interact and purchase by offering a combination of websites (fully functional and mobile-enabled), catalogs and stores with increasing convergence of channels.

The ( p , q , r , l ) model for stochastic demand under Intuitionistic fuzzy aggregation with Bonferroni mean

Abstract: This paper investigates a hill type economic production-inventory quantity (EPIQ) model with variable lead-time, order size and reorder point for uncertain demand. The average expected cost function is formulated by trading off costs of lead-time, inventory, lost sale and partial backordering. Due to the nature of the demand function, the frequent peak (maximum) and valley (minimum) of the expected cost function occur within a specific range of lead time. The aim of this paper is to search the lowest valley of all the valley points (minimum objective values) under fuzzy stochastic demand rate. We consider Intuitionistic fuzzy sets for the parameters and used Intuitionistic Fuzzy Aggregation Bonferroni mean for the defuzzification of the hill type EPIQ model. Finally, numerical examples and graphical illustrations are made to justify the model.

Joint economic lot sizing model with stochastic demand and controllable lead-time by reducing ordering cost and setup cost

Abstract: This paper derives a mathematical integrated production inventory model of single vendor and buyer to investigate the effects of capital investment in setup cost of the vendor and order processing cost of the buyer on the decision variables of the model. Main purpose of this study is to minimize the integrated total cost of the vendor and buyer by optimizing the delivery lot size, lead-time, setup and order processing cost and number of deliveries per order simultaneously while lead-time demand follows normal distribution and unknown distribution, i.e., distribution free case. This model is analyzed by calculus method and justified with appropriate numerical illustrations. Numerical results show that significant savings can be achieved at optimal investments in reducing lead time, ordering cost and setup cost. Finally, sensitivity analysis of the key parameters is carried out and some managerial implications are also included.

Hybrid improved cuckoo search algorithm and genetic algorithm for solving Markov-modulated demand

Abstract: One of the fundamental problems in supply chain management is to design the effective inventory control policies for models with stochastic demands because efficient inventory management can both maintain a high customers’ service level and reduce unnecessary over and under-stock expenses which are significant key factors of profit or loss of an organization. In this study, a new formulation of an inventory system is analyzed under discrete Markov-modulated demand. We employ simulation-based optimization that combines simulated annealing pattern search and ranking selection (SAPS&RS) methods to approximate near-optimal solutions of this problem. After determining the values of demand, we employ novel approach to achieve minimum cost of total SCM (Supply Chain Management) network. In our proposed approach, hybrid improved cuckoo search algorithm (ICS) and genetic algorithm (GA) are presented as main platform to solve this problem. The computational results demonstrate the effectiveness and applicability of the proposed approach.

A system dynamics model of financial flow in supply chains: a case study

Abstract: The article discusses the operational and financial relationships among the channel members of a supply chain comprising of a manufacturing company and a distributor. This research simulates the financial system that enables a more accurate diagnosis of disaggregated metrics “Cash to Cash”, considering different interactions between material flow and the financial flow of the two links, manufacturer and distributor. This model considers the feedback loops between material flow models and financial models without which some interactions are lost during simulation. The proposed diagnostic method which incorporates an eclectic process re-engineering practices and state of the art of dynamic simulation with the implementation of advanced techniques of sensitivity and dynamic optimization models those are applied on the concept of stocks and flows. This methodology is used in order to analyze and improve business strategies by generating policies which help to improve cash flow of the company. To validate our model, a case study illustrating the improvement of different metrics of the supply chain is considered here. The results show that the companies have to invest in technology in order to generated strategic decision to enhance their financial metrics.

An inventory model of three-layer supply chain of wood and furniture industry in the Caribbean region of Colombia

Abstract: This article deals with a mathematical model for multi-item inventory system under a collaborative scheme in a three-level supply chain consisting of multiple raw material suppliers, multiple manuf...

A Hesitant Fuzzy Set Theory Based Approach for Project Portfolio Selection with Interactions under Uncertainty.

Abstract: This paper proposes a new practical model for project portfolio selection focusing on two issues; the first issue relates to managing uncertainty provoked by hesitant situations and the second issue relates to the interaction effect of projects on final value of portfolio. Based on the above issues, the hesitant fuzzy weighted averaging (HFWA) operator is applied to aggregate the hesitant fuzzy information corresponding to each project and its interactions. A linear programming model is proposed to optimize project portfolio selection problem considering interactive project sets and its dependency unlike the previously literature. Finally, the effectiveness of the proposed technique is illustrated by means of a practical example.

Supply chain coordination with random yield and demand uncertainty

Abstract: Uncertainty is a major challenging factor in the marketing strategies of the players in a supply chain. In this study, the random yield for both the supplier and manufacturer is investigated to find the optimal decisions in the environment of demand uncertainty. To meet the effect of random yield in the supplier’s production, the manufacturer places a flexible ordering policy in a range with conditions imposed thereupon. It is also assumed that the manufacturer faces both the under-stocking and over-stocking risk. In the over-stock situation, the model is developed with the chance factor of holding and selling with salvage value for the extra products. The behavior of the model under a centralized, vertical Nash approach is analysed. A manufacturer-Stackelberg and revenue sharing contract with penalty and sharing are also discussed. The sensitivity of the key parameters is examined to test the feasibility of the model. Finally, a numerical example with graphical illustrations is provided to invest...

Two-layer supply chain model for Cauchy-type stochastic demand under fuzzy environment

Abstract: Purpose The purpose of this paper is to deal with profit maximization problem of two-layer supply chain (SC) under fuzzy stochastic demand having finite mean and unknown variance. Buyback policy is employed from the retailer to supplier. The profit of the supplier solely depends on the order size of the retailers. However, the loss of shortage items is related to loss of profit and goodwill dependent. The authors develop the profit function separately for both the retailer and supplier, first, for a decentralized system and, second, joining them, the authors get a centralized system (CS) of decision making, in which one is giving more profit to both of them. The problem is solved analytically first, then the authors fuzzify the model and solve by fuzzy Hausdorff distance method. Design/methodology/approach The analytical models are formed for both centralized and decentralized systems under non-cooperative and cooperative environment with suitable constraints. A significant assumption on density function, namely Cauchy-type density function, is introduced for demand rate because of its wider range of the retailers’ satisfactions. Fuzzy Hausdorff metric is incorporated within the fuzzy components of the fuzzy sets itself. Using this method, the authors find out closure values of both centralized and decentralized policies, which is an essential part of any cooperative and non-cooperative two-layer SC models. Moreover, the authors take care of the profit values with corresponding ambiguities for both the systems explicitly. Findings It is found that the centralize policy of SC could only be able to maximize the profit of both the retailers and suppliers. All analytical results are illustrated numerically along with sensitivity analysis and side by side comparative studies between Hausdorff and Euclidean distance measure are done exclusively. Research limitations/implications The main focus of attention of the proposed model is given to usefulness of Hausdorff distance. Unlike other distances, Hausdorff distance can take special care on the similarity measures of different fuzzy sets. Researchers have been engaged to use Hausdorff distance on the different fuzzy sets but, in this study, the authors have used it within the components of a same fuzzy set to gain more closure values than other methods. Originality/value The use of this Hausdorff distance approach is totally new as per literature survey suggested yet. However, the Cauchy-type density function has not been introduced anywhere in SC management problems by modern researchers still now. In crisp model, the sensitivity on goodwill measures really provides a special attention also.

A game theoretic approach to optimal pricing of flights and passengers at congested airports

Abstract: Purpose This paper aims to embark a mathematical model based on investigation and comparison of airport pricing policies under various types of competition, considering both per-passenger and per-flight charges at congested airports. Design/methodology/approach In this model, four-game theoretic strategies are assessed and closed-form formulas have been proved for each of the mentioned strategies. Numerical examples and graphical representations of the optimal solutions are provided to illustrate the models. Findings The rectitude of the presented formulas is evaluated with sensitivity analysis and numerical examples have been put forward. Finally, managerial implications are suggested by means of the proposed analysis. Research limitations/implications The represented model is inherently limited to investigate all the available and influential factors in the field of congestion pricing. With this regard, several studies can be implemented as the future research of this study. The applications of other game theoretic approaches such as Cartel games and its combination with the four mentioned games seem to be worthwhile. Moreover, it is recommended to investigate the effectiveness of the proposed model and formulations with a large-scale database. Originality/value The authors formulate a novel strategy that put forwards a four-game theoretic strategy, which helps managers to select the best suitable ones for their specific airline and/or air traveling companies. The authors find that by means of the proposed model, the application of Stackelberg–Bertrand behavior in the field of airport congestion pricing will rebound to a more profitable strategy in contrast with the other three represented methods.

Application of rough set and netnography in tourism marketing analysis

Abstract: Social media has given customers more power over sharing their knowledge, opinions and experiences with each other. Tourists as customers of destinations are also using text ads on social media and websites to share their experiences. The purpose of this study is to find out the factors which have affect on the decisions of tourists towards the most popular destinations in Tehran, Isfahan and Shiraz of Iran.,Netnography methodology has been applied to 2,852 comments showing travelers’ experiences through TripAdvisor.com. As a result, ten major factors have been discovered. According to these factors, a questionnaire has been designed and distributed among 449 tourists. In the second step, the collected data are used by rough set theory to discover the rules of destination recommendation based on the factors discovered before. Finally, eight main rules are determined to further analysis.,The findings confirm that beauty, cultural attractions, safety, welfare, costs and dealing with passengers are more important than other observed dimensions.,In this study, first the factors affecting consumer behavior in the tourism industry have been investigated. Based on this, the comments of tourists who have traveled to one of the cities Shiraz, Isfahan or Teheran and shared their experiences on TripAdvisor.com are studied. Further, the rules are discovered based on the rough set theory, and owing to the large number of objects (449 customer), the Rosetta software has been used.

ABC analysis of the customers using axiomatic design and incomplete rough set

Abstract: Customer’s recognition, classification, and selecting the target market are the most important success factors of a marketing system. ABC classification of the customers based on axiomatic design exposes the behavior of the customer in a logical way in each class. Quite often, missing data is a common occurrence and can have a significant effect on the decision- making problems. In this context, this proposed article determines the customer’s behavioral rule by incomplete rough set theory. Based on the proposed axiomatic design, the managers of a firm can map the rules on designed structures. This study demonstrates to identify the customers, determine their characteristics, and facilitate the development of a marketing strategy.

Integrated supply chain of supplier and retailer for stochastic demand

Abstract: This article deals with a two-stage supply chain comprising of the retailer and the supplier in which demand of the end customers follows news-vendor type demand. The setup costs, purchasing and procurement costs are dependent on lot sizes. The mathematical models for continuous and discrete variables of the chain are analyzed mathematically to maximize the expected average profits of individual and the collaborating systems. As our study suggests that collaborating system is always better than the decentralized system for known distribution cases, we also optimize the joint profit of the retailer and the supplier for a distribution free case which is implemented for unknown distribution. Finally, numerical examples of the demand patterns are illustrated to justify the proposed model. The punctual research directions from the proposed model are also provided in the conclusion section.

Attracting and Retaining Customers by Axiomatic Design and Incomplete Rough-Set Theory

Abstract: Customer is the most important source of added value in the company. So attracting and retaining the customers is vital in the competitive market. Identifying the effective factors on customer’s loyalty can help managers to make decisions related to maintaining and creating loyal customers. Customer’s behavioral structure designing based on axiomatic design technique reveals the logical actions and reactions between customers and the business environment. In this paper, customer’s behavior is designed based on axiomatic design technique in light of the rapid growth of data sets. The incomplete rough set theory is used in order to deal with missing data which may occur eventually in big data set. Thus customer’s behavioral rules are explored applying incomplete rough-set theory in data set of mobile phones. As a result, managers of a mobile phone companies can find out the appropriate strategies by mapping incomplete rough-set theory with axiomatic designed structure in order to attract and retain the customers.

Coverage Reduction: A Mathematical Model

Abstract: This paper deals with a mathematical model for reduction of the lack of coverage (LC) involving multiple coverage in presence of partial covering. The model proposes a new structure of assignment o...