Modeling the demand and supply in a new B2B-upstream market using a knowledge updating process

Trichy Krishnan, Shanfei Feng, Tony Beebe

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

Business-to-Business (B2B) services companies invest heavily in acquiring very expensive assets that they hire out to serve their clients (e.g. UPS buys huge warehouses and hires them out to companies), and hence they engage in careful long-term planning and forecasting, especially when it concerns a new market. It is interesting to note that the client-firms, on the other hand, decide to hire those assets based mostly on the prevailing short-term market forces. Hence, it is important for the companies which provide the assets for hire to also build the prevailing short-term market trends into their long-term forecasting and planning. In this paper, we develop a model for tracking these two simultaneously evolving and interacting patterns, namely the asset-availability (i.e. supply) and utilization (i.e. demand) patterns, in order to better understand the underlying processes, and thereby provide a basis for better forecasting. We test our models using three sets of data collected from the oil drilling industry, and find the proposed model to provide a good fit and forecasting efficiency.
Original languageEnglish
Pages (from-to)1160 - 1177
Number of pages18
JournalInternational Journal of Forecasting
Volume27
Issue number4
DOIs
Publication statusPublished - 2011

Cite this

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title = "Modeling the demand and supply in a new B2B-upstream market using a knowledge updating process",
abstract = "Business-to-Business (B2B) services companies invest heavily in acquiring very expensive assets that they hire out to serve their clients (e.g. UPS buys huge warehouses and hires them out to companies), and hence they engage in careful long-term planning and forecasting, especially when it concerns a new market. It is interesting to note that the client-firms, on the other hand, decide to hire those assets based mostly on the prevailing short-term market forces. Hence, it is important for the companies which provide the assets for hire to also build the prevailing short-term market trends into their long-term forecasting and planning. In this paper, we develop a model for tracking these two simultaneously evolving and interacting patterns, namely the asset-availability (i.e. supply) and utilization (i.e. demand) patterns, in order to better understand the underlying processes, and thereby provide a basis for better forecasting. We test our models using three sets of data collected from the oil drilling industry, and find the proposed model to provide a good fit and forecasting efficiency.",
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Modeling the demand and supply in a new B2B-upstream market using a knowledge updating process. / Krishnan, Trichy; Feng, Shanfei; Beebe, Tony.

In: International Journal of Forecasting, Vol. 27, No. 4, 2011, p. 1160 - 1177.

Research output: Contribution to journalArticleResearchpeer-review

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AB - Business-to-Business (B2B) services companies invest heavily in acquiring very expensive assets that they hire out to serve their clients (e.g. UPS buys huge warehouses and hires them out to companies), and hence they engage in careful long-term planning and forecasting, especially when it concerns a new market. It is interesting to note that the client-firms, on the other hand, decide to hire those assets based mostly on the prevailing short-term market forces. Hence, it is important for the companies which provide the assets for hire to also build the prevailing short-term market trends into their long-term forecasting and planning. In this paper, we develop a model for tracking these two simultaneously evolving and interacting patterns, namely the asset-availability (i.e. supply) and utilization (i.e. demand) patterns, in order to better understand the underlying processes, and thereby provide a basis for better forecasting. We test our models using three sets of data collected from the oil drilling industry, and find the proposed model to provide a good fit and forecasting efficiency.

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