Pricing and lead time decisions for make-to-order firms with contingent orders

Easton, Fred F.; Moodie, Douglas R.

doi:10.1016/s0377-2217(98)00101-5

Cited by 107 publications

(49 citation statements)

References 39 publications

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“…Since it usually takes some time for a potential sale to materialize, the collection of sales representatives' information as to the number of customers interested in a product (such as the number of outstanding sales vouchers) can generate an indication about the future sales of that product, hence it constitutes imperfect ADI. In connection with this example, Easton and Moodie [6] discuss how ''outstanding bids'' (that is, pending proposals at prospective customers) can be employed in quoting the lead time and contract price for a new bid in a single resource production environment.…”

Section: Introduction and Related Literaturementioning

confidence: 99%

Modelling imperfect advance demand information and analysis of optimal inventory policies

Tan

Güllü

Erkip

2007

European Journal of Operational Research

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We consider an inventory control problem where it is possible to collect some imperfect information on future demand. We refer to such information as imperfect Advance Demand Information (ADI), which may occur in different forms of applications. A simple example is a company that uses sales representatives to market its products, in which case the collection of sales representatives' information as to the number of customers interested in a product can generate an indication about the future sales of that product, hence it constitutes imperfect ADI. Other applications include internet retailing, Vendor Managed Inventory (VMI) applications and Collaborative Planning, Forecasting, and Replenishment (CPFR) environments. We develop a model that incorporates imperfect ADI with ordering decisions. Under our system settings, we show that the optimal policy is of order-up-to type, where the order level is a function of imperfect ADI. We also provide some characterizations of the optimal solution. We develop an expression for the expected cost benefits of imperfect ADI for the myopic problem. Our analytical and empirical findings reveal the conditions under which imperfect ADI is more valuable.

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Section: Introduction and Related Literaturementioning

confidence: 99%

Modelling imperfect advance demand information and analysis of optimal inventory policies

Tan

Güllü

Erkip

2007

European Journal of Operational Research

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“…iii) Acceptance probability (Aor) s : To calculate the probability of customer accepting a quotation submitted by the company, Easton and Moodie (1999) and Cakravastia and Takahashi (2003) have used an S-shaped logit model. This model was constructed without utilizing any information on contingent order.…”

Section: Limit Levelmentioning

confidence: 99%

“…This complicates matters for company that have to prepare quote for new order. Easton and Moodie (1999) is the first paper to explicitly coin the effect of contingent orders on quotation. The paper dealt with this problem in a single resource and single job production environment.…”

Section: Introductionmentioning

confidence: 99%

Dealing with customers enquiries simultaneously under contingent situation

Piya¹

2015

10.5267/j.ijiec

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This paper proposes a method to quote the due date and the price of incoming orders to multiple customers simultaneously when the contingent orders exist. The proposed method utilizes probabilistic information on contingent orders and incorporates some negotiation theories to generate quotations. Rather than improving the acceptance probability of quotation for single customer, the method improves the overall acceptance probability of quotations being submitted to the multiple customers. This helps increase the total expected contribution of company and acceptance probability of entire new orders rather than increasing these measures only for a single customer. Numerical analysis is conducted to demonstrate the working mechanism of proposed method and its effectiveness in contrast to sequential method of quotation.

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“…Duenyas (1995) and Duenyas and Hopp (1995) use semi-Markov decision processes to solve the problem of quoting optimal lead times to customers when the probability of a customer placing an order depends on the lead time quoted to him. Easton and Moodie (1999) develop a probabilistic model in order to determine optimal pricing and due date setting decisions and Watanapa and Techanitisawad (2005) extend Easton and Moodie's model. Kapuscinski and Tayur (2000) are able to determine the structure of an optimal due date setting policy for a revenue management problem at a make-to-order company.…”

Section: Literature Reviewmentioning

confidence: 99%

Revenue management for manufacturing companies

Pekgün

2012

J Revenue Pricing Manag

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Pricing and lead time decisions for make-to-order firms with contingent orders

Cited by 107 publications

References 39 publications

Modelling imperfect advance demand information and analysis of optimal inventory policies

Modelling imperfect advance demand information and analysis of optimal inventory policies

Dealing with customers enquiries simultaneously under contingent situation

Revenue management for manufacturing companies

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