Publication

Advance Selling and Advertising: A Newsvendor Framework

Wu, M., Zhu, S. X. & Teunter, R. H., 10-Jan-2020, In : Decision Sciences. 34 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Wu, M., Zhu, S. X., & Teunter, R. H. (2020). Advance Selling and Advertising: A Newsvendor Framework. Decision Sciences. https://doi.org/10.1111/deci.12423

Author

Wu, Meng ; Zhu, Stuart X. ; Teunter, Ruud H. / Advance Selling and Advertising : A Newsvendor Framework. In: Decision Sciences. 2020.

Harvard

Wu, M, Zhu, SX & Teunter, RH 2020, 'Advance Selling and Advertising: A Newsvendor Framework', Decision Sciences. https://doi.org/10.1111/deci.12423

Standard

Advance Selling and Advertising : A Newsvendor Framework. / Wu, Meng; Zhu, Stuart X.; Teunter, Ruud H.

In: Decision Sciences, 10.01.2020.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Wu M, Zhu SX, Teunter RH. Advance Selling and Advertising: A Newsvendor Framework. Decision Sciences. 2020 Jan 10. https://doi.org/10.1111/deci.12423


BibTeX

@article{681b73c69b4d4a0ba72cb6152b5f1b04,
title = "Advance Selling and Advertising: A Newsvendor Framework",
abstract = "Many firms offer consumers the opportunity to place advance orders at a discount when introducing a new product to the market. Doing so has two main advantages. First, it can increase total expected sales by exploiting valuation uncertainty of the consumers at the advance ordering stage. Second, total sales can be estimated more accurately based on the observed advance orders, reducing the need for safety stock and thereby obsolescence cost. In this research, we derive new insights into trading off these benefits against the loss in revenue from selling at a discount at the advance stage. In particular, we are the first to explore whether firms should advertise the advance ordering opportunity. We obtain several structural insights into the optimal policy, which we show is driven by two dimensions: the fraction of consumers who potentially buy in advance (i.e., strategic consumers) and the size of the discount needed to make them buy in advance. If the discount is below some threshold, then firms should sell in advance and they should advertise that option if the fraction of strategic consumers is sufficiently large. If the discount is above the threshold, then firms should not advertise and only sell in advance if the fraction of strategic consumers is sufficiently small. Graphical displays based on the two dimensions provide further insights.",
keywords = "Advance Selling, Advertising, Demand Forecast Accuracy Improvement, Newsvendor, Strategic Consumer, BOOKING DISCOUNT PROGRAMS, CONSUMERS, PRODUCTS, FUTURE, DECISIONS, SALES, MODEL",
author = "Meng Wu and Zhu, {Stuart X.} and Teunter, {Ruud H.}",
year = "2020",
month = jan,
day = "10",
doi = "10.1111/deci.12423",
language = "English",
journal = "Decision Sciences",
issn = "0011-7315",

}

RIS

TY - JOUR

T1 - Advance Selling and Advertising

T2 - A Newsvendor Framework

AU - Wu, Meng

AU - Zhu, Stuart X.

AU - Teunter, Ruud H.

PY - 2020/1/10

Y1 - 2020/1/10

N2 - Many firms offer consumers the opportunity to place advance orders at a discount when introducing a new product to the market. Doing so has two main advantages. First, it can increase total expected sales by exploiting valuation uncertainty of the consumers at the advance ordering stage. Second, total sales can be estimated more accurately based on the observed advance orders, reducing the need for safety stock and thereby obsolescence cost. In this research, we derive new insights into trading off these benefits against the loss in revenue from selling at a discount at the advance stage. In particular, we are the first to explore whether firms should advertise the advance ordering opportunity. We obtain several structural insights into the optimal policy, which we show is driven by two dimensions: the fraction of consumers who potentially buy in advance (i.e., strategic consumers) and the size of the discount needed to make them buy in advance. If the discount is below some threshold, then firms should sell in advance and they should advertise that option if the fraction of strategic consumers is sufficiently large. If the discount is above the threshold, then firms should not advertise and only sell in advance if the fraction of strategic consumers is sufficiently small. Graphical displays based on the two dimensions provide further insights.

AB - Many firms offer consumers the opportunity to place advance orders at a discount when introducing a new product to the market. Doing so has two main advantages. First, it can increase total expected sales by exploiting valuation uncertainty of the consumers at the advance ordering stage. Second, total sales can be estimated more accurately based on the observed advance orders, reducing the need for safety stock and thereby obsolescence cost. In this research, we derive new insights into trading off these benefits against the loss in revenue from selling at a discount at the advance stage. In particular, we are the first to explore whether firms should advertise the advance ordering opportunity. We obtain several structural insights into the optimal policy, which we show is driven by two dimensions: the fraction of consumers who potentially buy in advance (i.e., strategic consumers) and the size of the discount needed to make them buy in advance. If the discount is below some threshold, then firms should sell in advance and they should advertise that option if the fraction of strategic consumers is sufficiently large. If the discount is above the threshold, then firms should not advertise and only sell in advance if the fraction of strategic consumers is sufficiently small. Graphical displays based on the two dimensions provide further insights.

KW - Advance Selling

KW - Advertising

KW - Demand Forecast Accuracy Improvement

KW - Newsvendor

KW - Strategic Consumer

KW - BOOKING DISCOUNT PROGRAMS

KW - CONSUMERS

KW - PRODUCTS

KW - FUTURE

KW - DECISIONS

KW - SALES

KW - MODEL

U2 - 10.1111/deci.12423

DO - 10.1111/deci.12423

M3 - Article

JO - Decision Sciences

JF - Decision Sciences

SN - 0011-7315

ER -

ID: 108097864