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Customer-Based Corporate Valuation : = Modeling with Missing, Aggregated Data Summaries.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Customer-Based Corporate Valuation :/
其他題名:	Modeling with Missing, Aggregated Data Summaries.
作者:	McCarthy, Daniel M.
面頁冊數:	1 online resource (142 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Contained By:	Dissertation Abstracts International78-12B(E).
標題:	Statistics. -
電子資源:	click for full text (PQDT)
ISBN:	9780355110142

Customer-Based Corporate Valuation : = Modeling with Missing, Aggregated Data Summaries.
McCarthy, Daniel M.

Customer-Based Corporate Valuation :Modeling with Missing, Aggregated Data Summaries. - 1 online resource (142 pages)

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.

Thesis (Ph.D.)--University of Pennsylvania, 2017.

Includes bibliographical references

There is growing interest in "customer-based corporate valuation," explicitly tying the value of a firm's customer base to its financial valuation. This dissertation studies the theory and application of customer-based corporate valuation. The dissertation is comprised of three essays, each of which studies a different aspect of the topic. In the first essay, we develop a general customer-based corporate valuation framework. In doing so, we enumerate the determinants of corporate value and how predictions of customer base activity can be used to inform these determinants. In the second essay, we develop a customer-based corporate valuation model that is specifically suited to contractual (or subscription-based) businesses. We apply this model to publicly-disclosed data from two companies, DISH Network and Sirius XM Holdings. In the third essay, we develop a customer-based corporate valuation model for non-contractual (or non-subscription-based) businesses. This is a more challenging problem, because non-contractual businesses have more complex transactional patterns---they are characterized by latent attrition instead of observable churn behavior, and often have irregular purchase timing and spend amounts. We apply this methodology to data from a large business unit of an e-commerce retailer, valuing the business unit as a whole, decomposing this valuation into existing and yet-to-be-acquired customers, and analyzing customer profitability. In both essays two and three, we assume that the modeler is an external stakeholder, and thus only has the ability to observe a very limited, possibly incomplete, periodically disclosed collection of customer data summaries, unlike a situation in which the granular data is observed. We conclude with a short chapter which describes areas for future research.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355110142Subjects--Topical Terms:

556824
Statistics.
Index Terms--Genre/Form:

554714
Electronic books.

Customer-Based Corporate Valuation : = Modeling with Missing, Aggregated Data Summaries.
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502 $a Thesis (Ph.D.)--University of Pennsylvania, 2017.
504 $a Includes bibliographical references
520 $a There is growing interest in "customer-based corporate valuation," explicitly tying the value of a firm's customer base to its financial valuation. This dissertation studies the theory and application of customer-based corporate valuation. The dissertation is comprised of three essays, each of which studies a different aspect of the topic. In the first essay, we develop a general customer-based corporate valuation framework. In doing so, we enumerate the determinants of corporate value and how predictions of customer base activity can be used to inform these determinants. In the second essay, we develop a customer-based corporate valuation model that is specifically suited to contractual (or subscription-based) businesses. We apply this model to publicly-disclosed data from two companies, DISH Network and Sirius XM Holdings. In the third essay, we develop a customer-based corporate valuation model for non-contractual (or non-subscription-based) businesses. This is a more challenging problem, because non-contractual businesses have more complex transactional patterns---they are characterized by latent attrition instead of observable churn behavior, and often have irregular purchase timing and spend amounts. We apply this methodology to data from a large business unit of an e-commerce retailer, valuing the business unit as a whole, decomposing this valuation into existing and yet-to-be-acquired customers, and analyzing customer profitability. In both essays two and three, we assume that the modeler is an external stakeholder, and thus only has the ability to observe a very limited, possibly incomplete, periodically disclosed collection of customer data summaries, unlike a situation in which the granular data is observed. We conclude with a short chapter which describes areas for future research.
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