Competitive supply behavior when price information is fuzzy

2008

This paper addresses the problem of determining the sale price and the production quantity under supply uncertainty. The problem is commonly observed in the agricultural industry. We consider a firm that initially leases farm space in order to grow fruit. The realized amount of fruit supply fluctuates due to weather conditions, diseases, etc. At the end of the growing season, the firm makes two production decisions: the amount of realized supply to be converted to finished product and the amount of additional supply to purchase from other growers. However, the second opportunity to purchase from other growers occurs at a unit cost that depends on the realized supply. This is defined as the yield-dependent purchasing cost. Specifically, the lower the realized supply, the higher the unit purchasing cost. Two modeling approaches are presented for the price-setting behavior. In the Early Pricing model, the sale price is determined when the leasing agreement is made, and in the Postponed Pricing model, it is set after observing the realized supply. The presence of the yield-dependent purchasing cost differentiates this work from studies that feature price-setting behavior under supply uncertainty. In traditional models where the unit purchasing cost is a constant, the firm experiences either the case of "complete backlogging" (all demand is satisfied) or "lost sales" (some of the demand is not satisfied), but not both. The yield-dependent cost, however, forces the firm to experience both cases simultaneously in this problem. The paper first identifies the optimal sale price and production decisions for the two variants of the problem with complete backlogging and lost sales, and later shows how these decisions differ when the firm utilizes the purchasing alternative with the yield-dependent cost. In the Early Pricing model, it proves that 1) the optimal stocking level is greater than or equal to its equivalent developed for the complete backlogging and lost sales variants, 2) the optimal sale price is greater than or equal to that of the lost sales variant, and is less than or equal to that of the complete backlogging variant, and 3) the purchasing alternative does not always reduce the firm's initial investment in the leased farm space. In the Postponed Pricing model, it shows that the optimal amount of farm space to be leased can be uniquely determined and that the contribution of the purchasing alternative is always positive.

The main aim of the book is to outline some of the regular effects which price uncertainty has upon production and profit and, in so doing, to indicate the benefits which flow from relating economic theories, especially theories of economic behavior, to more general and abstract theories.

The Annals of the University of Oradea. Economic Sciences

In inventory and production decision problems, decision makers are interested to identify the optimal inventory and production level. In a certain decision environment, the optimal inventory level could be determined through traditional inventory methods and the optimal ptoduction level could be determined through linear programming algorithms. In an uncertain decision environment, the traditional methods and algorithms can not provide efficient and relevant solutions for these levels, due to the vague and changing parameters. In this case it is neccesary to develop new methods and models that can deal with vague variables and provide optimal levels. In this paper, the optimal inventory and production levels are determined through a single model that uses fuzzy linear programming. This new model is Fuzzy Optimistic-Reasonable-Pessimistic Inventory Model. It has three scenario: optimistic, reasonable and pessimistic, that are defined through triangular fuzzy numbers. In this way, dec...

2005

This paper deals with traditional pricing models under uncertainties. A fuzzy model is applied to the classical economical approach in order to calculate the possibilities of economical indices such as profits and losses. A realistic case study is included to illustrate a typical application of the fuzzy model to the pricing issue.

Soft Computing, 2020

In online direct selling, three effective elements, namely price, refund and quality, affect the increment (or decrement) of demand and product return. This paper considers forward and backward (i.e., return) pricing decisions under uncertainty and develops a fuzzy mathematical model based on the Stackelberg game approach utilizing the proper action and reaction between a manufacturer and a retailer. Moreover, media advertising and manufacturer's desire for accepting massive payments made us take into account the advertising as another factor influencing the demand. By an agreement between the manufacturer and the retailer, the costs of advertising and raising the level of the product quality are shared by two agreed rates. Two numerical examples are considered and the associated results are analyzed under fuzzy and crisp conditions when customers are sensitive or insensitive to the quality of the product. It is found that incorporation of the quality factor under a fuzzy environment has a better performance compared with the case of ignoring the quality and uncertainty in the parameters.

Journal of Agricultural and Resource Economics, 2020

Theory of the firm suggests that optimal production levels decrease as output price becomes random. Firms operating in industries with long production lags are also exposed to input price uncertainty. This paper provides a novel decision theoretic model in the presence of both input and output price uncertainty and uses U.S. beef sector data to test theoretical propositions concerning firm behavior. Our findings confirm that, in a two-stage production, the introduction of input price uncertainty leads to increased use of the input and an increased level of output in stage one and a decreased level of output in stage two.

Mult-objectives in a Fuzzy Environment. The paper incorporates four constraints such as warehouse space and the constraint, investment amount constraint, percentage of utilization of volume of the ware house space and the shortage level constraint by allowing shortages. The previous researchers had analyzed different models on this relevant topic without shortages. But this paper mainly focuses on model with shortages and above mentioned constraints.

THE THEORY OF PRICE UNCERTAINTY, PRODUCTION AND PROFIT , 1968

The purpose of this chapter is to consider a limited number of theories of decision-making and human behavior. The theories under consideration will be sufficiently general to cover behavior under uncertainty, for behavior under these conditions is our main concern. A study of these abstract theories will enable us to appreciate their applicability to production decisions under price uncertainty.

Jurnal sistem teknik industri, 2023

Fuzzy set theory, or fuzzy logic, has been in use in inventory systems since the 1980s, with vaguely defined, ill-defined, or imprecise values, or decisions based on individual subjective beliefs. Provides a framework for describing the parameters that can be passed. There are many uncertainties in inventory management that can arise due to many things, such as: Order Changes, Random Supplier Capabilities, or Unexpected Events. Fuzzy logic as a method of inventory control that provides a framework by considering parameters that are vague or poorly defined, or whose values are imprecise and determined based on individual subjective beliefs make it available. The purpose of this white paper is to review previous studies using fuzzy logic in inventory management to see the uncertainty variables used. The method used is a thematic analysis of articles on the application of fuzzy logic in various industries. The results of the review show that variables like fuzzy logic make it easy to obtain results from uncertainty variables that can be applied to industrial activities to enable manufacturing activities to be carried out effectively and efficiently increase.

2012

This paper tackles the question of the anticipation of the supply chain partner's decisional behaviour under uncertain criteria. In other words, we propose a model to support sequential decisions under uncertainty where the decision maker has to make hypothesis about the decision criteria. For example, Hurwicz criterion weights extreme optimism and pessimism positions and a classic criticism of this criterion consisting in the difficulty of the weight assessment and the involving decision instability. To achieve this, we present a method based on fuzzy representation of weight vision. Finally, the model allows sequential decision of a Decision Tree to be compute thanks a pignistic probabilities treatment of the fuzzy representation of the decision maker optimism-pessimism index. This approach is illustrated through an industrial case study.