Minimum Acceptable Price Research Articles

A dynamic strategy-proof algorithm for allocation and pricing of cloud services

In this paper, we present a dynamic strategy-proof algorithm for allocation and pricing. The algorithm relies on market history to forecast a benchmark price to ensure truthful valuation from the market participants. The algorithm also ensures that the utility is evenly distributed between buyer and seller. The utility is the difference between the buyer's maximum offer and the seller's minimum acceptable price. The results of the experimental studies carried out shows that: 1) the budget limits of the buyers with successful allocations were not exceeded; 2) only market participants with truthful offers and bids were allocated services; 3) the utility is higher when there is no strategy-proof for preventing overbid and that there is at least a 50% increase in price per unit when there is no strategy-proof to prevent overbid; 4) in terms of computational efficiency, the algorithm converges in polynomial time with a worst-case running time of O(n2).

Revenue management with minimax regret negotiations

We study the dynamic bilateral price negotiations from the perspective of a monopolist seller. We first study the classical static problem with an added uncertainty feature. Next, we review the dynamic negotiation problem, and propose a simple deterministic “fluid” analog. The main emphasis of the paper is in analyzing the relationship of the dynamic negotiation problem and the classical revenue management problems; and expanding the formulation to the case where both the buyer and seller have limited prior information on their counterparty valuation. Our first result shows that if both the seller and buyer are bidding so as to minimize their maximum regret, then it is optimal for them to bid as if the unknown valuation distributions were uniform. Building on this result and the fluid formulation of the dynamic negotiation problem, we characterize the seller’s minimum acceptable price at any given point in time.

The effects of a “no-haggle” channel on marketing strategies

As sellers increasingly turn to multi-channel retailing, the opportunity to implement different pricing policies has grown. With the advent of the internet, many traditionally bargained products such as automobiles, jewelry, watches, appliances and furniture are now being offered online at a fixed pre-determined price. We explore the strategy of simultaneously offering two pricing formats (fixed and bargained) via two different channels (online and brick and mortar) and find that in a market where there are two types of consumers—those with a high cost of haggling and others with a lower cost—a dual-pricing strategy is optimal only when there are enough high haggling-cost consumers, but not too many, and when the haggling costs between the two types of consumers are sufficiently different. We also find that it is optimal for the seller to specify a higher-than-cost minimum acceptable price as the price floor of bargaining. By doing so, the seller increases the bargained price by complementing the salesperson's bargaining ability, and also softens the internal competition between the two channels. Finally, we find that, surprisingly, the dual-pricing strategy may serve fewer customers while still being more profitable than a single price structure. The implications for consumer surplus are also explored.

The Effects of a 'No-Haggle' Channel on Marketing Strategies

As sellers increasingly turn to multi-channel retailing, the opportunity to implement different pricing policies has grown. With the advent of the internet, many traditionally bargained products such as automobiles, jewelry, watches, appliances and furniture are now being offered online at a fixed pre-determined price. We explore the strategy of simultaneously offering two pricing formats (fixed and bargained) via two different channels (online and brick and mortar) and find that in a market where there are two types of consumers — those with a high cost of haggling and others with a lower cost — a dual-pricing strategy is optimal only when there are enough high haggling-cost consumers, but not too many, and when the haggling costs between the two types of consumers are sufficiently different. We also find that it is optimal for the seller to specify a higher-than-cost minimum acceptable price as the price floor of bargaining. By doing so, the seller increases the bargained price by complementing the salesperson’s bargaining ability, and also softens the internal competition between the two channels. Finally, we find that, surprisingly, the dual-pricing strategy may serve fewer customers while still being more profitable than a single price structure. The implications for consumer surplus are also explored.

The Role of the Internal Reference Price in the Perception of the Sales Price

An understanding of how consumers perceive the objective signal of the sales price transmitted by firms through their communication strategies is fundamental in order for those firms to achieve their desire objectives, whether by way of prices, positioning, differentiation, etc. Within this process, a knowledge of the reference price used by consumers as a standard of comparison when evaluating the products/brands that exist in the market assumes a vital importance. The aim of this article is to analyse the nature of the past information used by consumers when forming their internal reference price, as well as the effects exerted both by this price and by the sales price to which these consumers react in their monetary perception. The results obtained demonstrate that the internal reference price can be inferred through direct measurements of the medium expected price, the maximum acceptable price and the minimum acceptable price. They further show that the two types of prices analysed, namely, the internal reference price and the sales price, exert positive and significant effects over the final monetary perception.

A brokered market with heterogeneous suppliers and consumers

We consider a brokered market with heterogeneous suppliers and consumers of identical items or services. Each supplier determines a minimum acceptable price for the items it supplies, based on its costs and target rate of return. The broker begins with a fixed set of items from the suppliers. Customers arrive periodically to the market and offer a bid for an item. If a customer wants more than one item, a set of bids is made. If the broker accepts a bid it must be assigned an item with minimum accceptable price less than or equal to the bid, and the price paid is the bid price. The broker has the option of rejecting a bid. The broker makes acceptance and assignment decisions to maximize the total expected discounted revenue. We show the optimal policy has a simple threshold structure where thresholds can be easily determined by finding the individually optimal policies subject to priorities.

A brokered market with heterogeneous suppliers and consumers

We consider a brokered market with heterogeneous suppliers and consumers of identical items or services. Each supplier determines a minimum acceptable price for the items it supplies, based on its costs and target rate of return. The broker begins with a fixed set of items from the suppliers. Customers arrive periodically to the market and offer a bid for an item. If a customer wants more than one item, a set of bids is made. If the broker accepts a bid it must be assigned an item with minimum accceptable price less than or equal to the bid, and the price paid is the bid price. The broker has the option of rejecting a bid. The broker makes acceptance and assignment decisions to maximize the total expected discounted revenue. We show the optimal policy has a simple threshold structure where thresholds can be easily determined by finding the individually optimal policies subject to priorities.

A brokered market with heterogeneous suppliers and consumers

We consider a brokered market with heterogeneous suppliers and consumers of identical items or services. Each supplier determines a minimum acceptable price for the items it supplies, based on its costs and target rate of return. The broker begins with a fixed set of items from the suppliers. Customers arrive periodically to the market and offer a bid for an item. If a customer wants more than one item, a set of bids is made. If the broker accepts a bid it must be assigned an item with minimum accceptable price less than or equal to the bid, and the price paid is the bid price. The broker has the option of rejecting a bid. The broker makes acceptance and assignment decisions to maximize the total expected discounted revenue. We show the optimal policy has a simple threshold structure where thresholds can be easily determined by finding the individually optimal policies subject to priorities.

Optimal Offer Strategies in Mergers and Acquisitions*

ABSTRACTThis paper models the corporate takeover process as a bargaining game under certainty. During the takeover process, an acquirer is generally uncertain about the minimum price the target shareholders will accept. Normally, a takeover is concluded after a sequence of offers have been made. This paper derives optimal offer strategies for the buyer at each stage of this bargaining game under uncertainty. Uncertainty about the target's minimum acceptable price is represented by a probability distribution. Optimal offer strategies depend on the probability distribution of the minimum acceptable price, which can change during the offer process.

Sensitivity Analysis of Construction Contract Prices Using Spreadsheets

“Bad profits” have been identified as the cause of more than one‐half of all business failures in construction. To improve the profitability of the construction contractors, the Fair and Reasonable Markup (FaRM) is defined as the smallest markup that satisfies the Required Rate of Return (RRR) of the contractor for the particular (or at least the general risk class of the) project at hand. The microcomputer‐based FaRM Pricing Model provides a systematic and efficient framework for analyzing the forecast cash‐flow stream of the project and for estimating the Minimum Acceptable Price (MAP). The model utilizes LOTUS 1‐2‐3 spreadsheet and can be implemented on most IBM or compatible microcomputers. The computerized model delivers speedy responses to a variety of what‐if questions investigating the sensitivity of FaRM and MAP to the billing policy and the Required Rate of Return (RRR) of the contractor and to the payments time lag and the retainage policy of the owner. Once the FaRM Pricing Model has been implemented, contractors should bid lower on projects which are more attractive; thereby, they should become more competitive. This should result in lower costs to owners while satisfying the RRR of the contractors. Conversely, contractors can maintain their RRR on the less attractive projects by submitting higher bid prices

Fair and Reasonable Markup (FaRM) Pricing Model

The Fair and Reasonable Markup (FaRM) is the smallest markup that satisfies the Required Rate of Return (RRR) of the contractor for the particular (or at least the general risk‐class of) project at hand. The model is based on reasonable and easily‐accessible information, and will result in a Minimum Acceptable Price (MAP). The firm cannot accept the project at a price below this MAP without diminishing the “equityholders' wealth.” A modified version of the FaRM Pricing Model for certain contracts under which home‐office overhead expenses must be recovered through FaRM is also presented. Once the FaRM Pricing Model has been implemented, contractors can make more intelligent pricing decisions. Instead of using a subjective markup, which may ignore the cash‐flow differences of various jobs, contractors using FaRM Pricing Model can bid lower on projects which are more attractive and become more competitive while satisfying their RRR. This should result in lower costs to owners. Conversely, by bidding higher on the less‐attractive jobs, contractors will still maintain their RRR should they obtain the contract.