The bullwhip effect happens whenever the demand order fluctuations in the supply chain (SC) escalate as they are transferred up the SC. In fact, a small change in point-of-sale demand may be interpreted by SC participants as a much bigger variability in demand. This looks like a cracking a whip, where a small flick of the wrist may yield a large motion at the end of the whip. Misstate data from one side of a SC to the other part may yield substantial sloppiness. This includes increase in inventories, shortage of cash flow, weak customer satisfaction, etc. Enterprises may efficiently reduce the bullwhip effect by completely learning its root causes. This paper presents an overview on the concept and recent development of the bullwhip effect.

In this paper, we consider a multi-period integrated supplier selection and order lot
sizing problem where a single buyer plans to purchase a single product in multiple
periods from several qualified suppliers who are able to provide the required product
with the needed quality in a timely manner. Product price and order cost differs
among different suppliers. Buyer’s demand for the product is deterministic and varies
for different time periods. The problem is to determine how much product from which
supplier must be ordered in each period such that buyer’s demand is satisfied without
violating some side constraints. We have developed a mathematical programming
model to deal with this problem, and proposed a forward dynamic programming
approach to obtain optimal solutions in reasonable amount of time even for large scale
problems. Finally, a numerical example is conducted in which solutions obtained from
the proposed dynamic programming algorithm is compared with solutions from the
branch-and-bound algorithm. Through the numerical example we have shown the
efficiency of our algorithm.

This paper presents a new vendor-buyer system where there are different objectives for both sides. The proposed method of this paper is different from the other previously published works since it considers different objectives for both sides. In this paper, the vendor’s emphasis is on the crashing of the setup cost, which not only helps him compete in the market but also provides better services to his customers; and the buyer’s aim is to reduce the lead time, which not only facilitates the buyer to fulfill the customers’ demand on time but also enables him to earn a good reputation in the market or vice versa. In the light of the above stated facts, an integrated vendor-buyer stochastic inventory model is also developed. The propsed model considers two cases for demand during lead time: Case (i) Complete demand information, Case (ii) Partial demand information. The proposed model jointly optimizes the buyer’s ordered quantity and lead time along with vendor’s setup cost and the number of shipments. The results are demonstrated with the help of numerical examples.

:In this paper, we present a multi-objective possibilistic programming model to locate distribution centers (DCs) and allocate customers' demands in a supply chain network design (SCND) problem. The SCND problem deals with determining locations of facilities (DCs and/or plants), and also shipment quantities between each two consecutive tier of the supply chain. The primary objective of this study is to consider different risk factors which are involved in both locating DCs and shipping products as an objective function. The risk consists of various components: the risks related to each potential DC location, the risk associated with each arc connecting a plant to a DC and the risk of shipment from a DC to a customer. The proposed method of this paper considers the risk phenomenon in fuzzy forms to handle the uncertainties inherent in these factors. A possibilistic programming approach is proposed to solve the resulted multi-objective problem and a numerical example for three levels of possibility is conducted to analyze the model.

This paper identifies and analyzes barriers of customer relationship management (CRM) implementation in SMEs. Hence, based on a comprehensive review of the literature and gathering the viewpoint of experts, the influencing barriers are identified. In order to analyze the identified barriers, DEMATEL methodology is applied and a causal model of the relationships between barriers is developed. Furthermore, based on the DEMATEL results the barriers are also categorized into two groups of driver and dependent. The results of study show that inadequate budget, organization culture, obligation of major management to CRM and inadequate access to modern technical knowledge are among effective impediments and play important role in successful establishment of customer relationship management system.

Agile supply chain plays an important role on having efficient production planning. There are different factors affecting the efficiency of a supply chain and the attempt of this paper is to find the most important elements in agile supply chain. The proposed model of this paper gathers decision makers & apos; opinions and based on DEMATEL technique determines the most important items. The preliminary results of this survey indicate that we could divide the factors into four groups and two elements including automation and utilization of technical tools of relations and information play the most important roles among other factors.

Green supply chain management (GSCM) has emerged as a proactive approach for improving environmental performance of processes and products in accordance with the requirements of environmental regulations. The aim of this paper is to determine and model the drivers of GSCM to put environmental activities into practice. Thirty-four measurement items are developed on the basis of opinions from industrial experts and the literature and the necessary data are collected. To validate the measurement scales for GSCM, we perform a factor analysis. The results show that a six-factor measurement model (including internal environmental management, green purchasing, cleaner production, recovery, eco-design and pollution) fits the data acceptably. All of the measurement items significantly loaded on the constructs on which they were hypothesized to load. These results gave us confidence that the measures are indeed valid and reliable.

In recent decades, provision-chain management has been one of the major concepts. The main reason that attracts attention to the concept is the increase in competition and struggle for the survival. There are different ways to increase the competition in organizations such as increasing productivity by acquiring information technology.
In this paper, we present an integrated model with the balanced score card framework for supplier selection strategy. The proposed model of this paper gathers 161 important factors suggested in the literature and selects the six most important ones using different multi criteria techniques. We also propose a goal programming techniques with some hard constraints and implement the mathematical model for real-world case study of auto industry. The proposed model is solved in four different forms using TOPSIS, VIKOR and the combination of these 2 factors with factor analysis. The preliminary results indicate that a combination of VIKOR and factor analysis presented better results with 9% reduction in costs, 38% increase of quality, and 3.2% increase in acceptability.

The purpose of the present study is to introduce a model for competitiveness of suppliers in supply chain through game theory approach in one of the automobile companies of Iran. In this study, the game is based on price and non-price factors and this company is going to estimate the real profit obtained from collaboration with each of supply chain members. This happens by considering the governing competitive condition based on game theory before entering a bit for purchase of ? piece as spare part among 8 companies supplying this piece as the supply chain members. According to experts in this industry, the quality is the main non-price competitiveness factor after price. In the current research models, the model introduced by Lu and Tsao (2011) [Lu, J.C., Tsao, Y.C., & Charoensiriwath, C. (2011). Competition Under manufacturer Service and retail price. Economic Modeling, 28,1256-1264.] with two manufacturers- one distributer, being appropriate for the research data, has been considered as the basis and implemented for case study and then it has been extended to n-manufacturers-one common retailer. Following price elasticity of demand, potential size of market or maximum product demand, retailer price, production price, wholesale price, demand amount, manufacturer and retailer profit are estimated under three scenario of manufacturer Stackelberg, Retailer Sackelberg and Vertical Nash. Therefore, by comparing them, price balance points and optimum level of services are specified and the better optimum scenario can be determined. Sensitivity analysis is performed for new model and manufacturers are ranked based on manufacture profit, Retailer profit and customer satisfaction. Finally, in this research in addition to introducing-person game model, customer satisfaction, which has been presented in the previous models as a missed circle are analyzed.

In this paper, we address the optimization of an integrated line balancing process with workstation inventory management. While doing so, we have studied the interconnection between line balancing and its conversion process. Almost each and every moderate to large manufacturing industry depends on a long and integrated supply chain, consisting of inbound logistic, conversion process and outbound logistic. In this sense an approach addresses a very general problem of integrated line balancing. Research works reported in the literature so far mainly deals with minimization of cost for inbound and outbound logistic subsystems. In most of the cases conversion process has been ignored. We suggest a generic approach for linking the balancing of the line of production in the conversion area with the customers’ rate of demand in the market and for configuring the related stock chambers. Thus, the main aim of this paper is to translate the underlying problem in the form of mixed nonlinear programming problem and design the optimum supply chain so that the total inventory cost and the cost of balancing loss of the conversion process is jointly minimized and ideal cycle time of the production process is determined along with ideal sizes of the stock chambers. A numerical example has been added to demonstrate the suitability of our approach.