Using Sector-Index Data to Model Demand Allocation for Capacity and Production Planning

Shu-Jung Yang; Yingying Huang; Teck-Yong Eng

doi:10.1109/TEM.2024.3411149

Using Sector-Index Data to Model Demand Allocation for Capacity and Production Planning

Shu-Jung Yang, Yingying Huang^*, Teck-Yong Eng

^*Corresponding author for this work

Management

Research output: Contribution to journal › Article › peer-review

Abstract

Demand allocation (DA) is a market mechanism that a firm needs to consider in its sales and operations planning (SOP) because the market falls far short of perfect competition. The current analytics challenge in jointly evaluating demand planning (DP) and capacity and production planning (CPP) to realize a firm's SOP process in such a market is to successfully identify a suitable DA mechanism that shows how to split total industry demand among competing firms in the same sector. We develop a sector-index approach to DA using aggregated financial data to predict the firm-level DP. With this novel analytics approach, we develop a data-driven operations model of CPP to derive the optimal data-dependent capacity-expansion and production decisions. We demonstrate the practical value in a case study of the semiconductor sector and find significant linkages between capacity expansion and sector-index share. We show that a firm's sector index increases its capacity-expansion size, thereby decreasing its sector-index share. Our findings suggest that a high-index-share firm proactively expands more capacity than low-index-share firms, but its expansion may not increase its market value if the lead time is neither short nor long.

Original language	English
Number of pages	15
Journal	IEEE Transactions on Engineering Management
DOIs	https://doi.org/10.1109/TEM.2024.3411149
Publication status	E-pub ahead of print - 7 Jun 2024

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10.1109/TEM.2024.3411149

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title = "Using Sector-Index Data to Model Demand Allocation for Capacity and Production Planning",

abstract = "Demand allocation (DA) is a market mechanism that a firm needs to consider in its sales and operations planning (SOP) because the market falls far short of perfect competition. The current analytics challenge in jointly evaluating demand planning (DP) and capacity and production planning (CPP) to realize a firm's SOP process in such a market is to successfully identify a suitable DA mechanism that shows how to split total industry demand among competing firms in the same sector. We develop a sector-index approach to DA using aggregated financial data to predict the firm-level DP. With this novel analytics approach, we develop a data-driven operations model of CPP to derive the optimal data-dependent capacity-expansion and production decisions. We demonstrate the practical value in a case study of the semiconductor sector and find significant linkages between capacity expansion and sector-index share. We show that a firm's sector index increases its capacity-expansion size, thereby decreasing its sector-index share. Our findings suggest that a high-index-share firm proactively expands more capacity than low-index-share firms, but its expansion may not increase its market value if the lead time is neither short nor long.",

author = "Shu-Jung Yang and Yingying Huang and Teck-Yong Eng",

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N2 - Demand allocation (DA) is a market mechanism that a firm needs to consider in its sales and operations planning (SOP) because the market falls far short of perfect competition. The current analytics challenge in jointly evaluating demand planning (DP) and capacity and production planning (CPP) to realize a firm's SOP process in such a market is to successfully identify a suitable DA mechanism that shows how to split total industry demand among competing firms in the same sector. We develop a sector-index approach to DA using aggregated financial data to predict the firm-level DP. With this novel analytics approach, we develop a data-driven operations model of CPP to derive the optimal data-dependent capacity-expansion and production decisions. We demonstrate the practical value in a case study of the semiconductor sector and find significant linkages between capacity expansion and sector-index share. We show that a firm's sector index increases its capacity-expansion size, thereby decreasing its sector-index share. Our findings suggest that a high-index-share firm proactively expands more capacity than low-index-share firms, but its expansion may not increase its market value if the lead time is neither short nor long.

AB - Demand allocation (DA) is a market mechanism that a firm needs to consider in its sales and operations planning (SOP) because the market falls far short of perfect competition. The current analytics challenge in jointly evaluating demand planning (DP) and capacity and production planning (CPP) to realize a firm's SOP process in such a market is to successfully identify a suitable DA mechanism that shows how to split total industry demand among competing firms in the same sector. We develop a sector-index approach to DA using aggregated financial data to predict the firm-level DP. With this novel analytics approach, we develop a data-driven operations model of CPP to derive the optimal data-dependent capacity-expansion and production decisions. We demonstrate the practical value in a case study of the semiconductor sector and find significant linkages between capacity expansion and sector-index share. We show that a firm's sector index increases its capacity-expansion size, thereby decreasing its sector-index share. Our findings suggest that a high-index-share firm proactively expands more capacity than low-index-share firms, but its expansion may not increase its market value if the lead time is neither short nor long.

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