A two-stage DEA-based target-setting framework for corporate performance: integrating accounting identities and managerial constraints

Purpose The purpose of this paper is to develop a novel two-stage data envelopment analysis (DEA) framework that addresses the critical gap between high-level financial targets and granular operational drivers. This research aims to provide a deterministic modeling approach to derive attainable and justifiable corporate performance targets. Design/methodology/approach Accounting identities are embedded into a two-stage DEA production framework to decompose a composite indicator into performance drivers, efficiency regulators (ER) and structural capacity drivers. Stage 1 identifies implementable input targets through radial contraction of ER and slack minimization. Stage 2 determines attainable output expansion and final target levels under variable returns to scale. Exogenous growth requirements (MGG) and efficiency guardrails (MGE) are incorporated as managerial parameters defining the feasible target region. The framework is applied to six Japanese automakers using FY2023 data. Findings The framework provides explicit benchmarking-based justification for allocating a composite-indicator target to decomposed financial components. The empirical results show that attainable target return on equity (ROE) as a function of the sales growth rate can exhibit a peak, implying the existence of an optimal growth rate that maximizes attainable target ROE. Higher growth does not necessarily increase attainable target ROE. The solution structure around the peak also helps clarify ROE improvement strategies, including the relative emphasis on growth versus efficiency improvement. Research limitations/implications The empirical analysis is limited to one industry and one fiscal year. Future research can extend the framework to multi-period settings, other industries and other composite financial indicators and examine robustness under alternative managerial parameter settings. Practical implications The framework improves the implement ability of numerical targets by linking accounting structure, benchmark peers and managerial conditions within an explicitly defined feasible set. It can support management control and governance by clarifying feasible improvement paths and the tradeoff between growth and efficiency. Originality/value This paper integrates accounting identities and exogenous managerial parameters into a two-stage DEA framework, moving beyond black-box benchmarking to produce attainable, decomposed and managerially interpretable targets.

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Publication Details

Journal
Journal of Modelling in Management
Published
2026-10-30
DOI
https://doi.org/10.1108/jm2-03-2026-0186
Primary Topic
Efficiency Analysis Using DEA
Type
article
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article

A two-stage DEA-based target-setting framework for corporate performance: integrating accounting identities and managerial constraints

Satoshi Kumagai
1 links
Journal of Modelling in Management
Efficiency Analysis Using DEA
article

A two-stage DEA-based target-setting framework for corporate performance: integrating accounting identities and managerial constraints

Satoshi Kumagai
article en

Abstract

Purpose The purpose of this paper is to develop a novel two-stage data envelopment analysis (DEA) framework that addresses the critical gap between high-level financial targets and granular operational drivers. This research aims to provide a deterministic modeling approach to derive attainable and justifiable corporate performance targets. Design/methodology/approach Accounting identities are embedded into a two-stage DEA production framework to decompose a composite indicator into performance drivers, efficiency regulators (ER) and structural capacity drivers. Stage 1 identifies implementable input targets through radial contraction of ER and slack minimization. Stage 2 determines attainable output expansion and final target levels under variable returns to scale. Exogenous growth requirements (MGG) and efficiency guardrails (MGE) are incorporated as managerial parameters defining the feasible target region. The framework is applied to six Japanese automakers using FY2023 data. Findings The framework provides explicit benchmarking-based justification for allocating a composite-indicator target to decomposed financial components. The empirical results show that attainable target return on equity (ROE) as a function of the sales growth rate can exhibit a peak, implying the existence of an optimal growth rate that maximizes attainable target ROE. Higher growth does not necessarily increase attainable target ROE. The solution structure around the peak also helps clarify ROE improvement strategies, including the relative emphasis on growth versus efficiency improvement. Research limitations/implications The empirical analysis is limited to one industry and one fiscal year. Future research can extend the framework to multi-period settings, other industries and other composite financial indicators and examine robustness under alternative managerial parameter settings. Practical implications The framework improves the implement ability of numerical targets by linking accounting structure, benchmark peers and managerial conditions within an explicitly defined feasible set. It can support management control and governance by clarifying feasible improvement paths and the tradeoff between growth and efficiency. Originality/value This paper integrates accounting identities and exogenous managerial parameters into a two-stage DEA framework, moving beyond black-box benchmarking to produce attainable, decomposed and managerially interpretable targets.

Journal of Modelling in Management
Aoyama Gakuin University (JP)
Openalex Percentile: Top 10%
Efficiency Analysis Using DEA
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