TY - JOUR
T1 - Exploring impact of production volume and product quality on manufacturers' profitability
T2 - analytical modeling and empirical validation
AU - Goswami, Mohit
AU - Ramkumar, M.
AU - Anthony, Jiju
AU - Jayaraman, Raja
AU - Cudney, Beth
AU - Chan, Felix T.S.
PY - 2025/2/24
Y1 - 2025/2/24
N2 - Purpose: This study aims to develop analytical models that consider product quality and production volume as essential drivers for profitability in the marketplace. It also considers product demand and price dynamics to understand related nuances backed by empirical validation. Design/methodology/approach: The pricing mechanism is influenced by production quality, while product demand is influenced by both price and quality. The study considers cost elements, including production cost and quality loss cost which in turn are influenced by production volume and product quality. It establishes analytical conditions for optimal product quality and applies them to numerical analyses considering four distinct industry settings. Findings: The study reveals that unique solutions exist for optimal product quality at each production level in four industry scenarios. The optimal production volume depends on product quality, and empirical research validates these findings from analytical models and numerical analysis. Originality/value: This study represents a pioneering effort to investigate operational strategies in both analytical and empirical contexts, thus contributing to the existing body of knowledge in this area.
AB - Purpose: This study aims to develop analytical models that consider product quality and production volume as essential drivers for profitability in the marketplace. It also considers product demand and price dynamics to understand related nuances backed by empirical validation. Design/methodology/approach: The pricing mechanism is influenced by production quality, while product demand is influenced by both price and quality. The study considers cost elements, including production cost and quality loss cost which in turn are influenced by production volume and product quality. It establishes analytical conditions for optimal product quality and applies them to numerical analyses considering four distinct industry settings. Findings: The study reveals that unique solutions exist for optimal product quality at each production level in four industry scenarios. The optimal production volume depends on product quality, and empirical research validates these findings from analytical models and numerical analysis. Originality/value: This study represents a pioneering effort to investigate operational strategies in both analytical and empirical contexts, thus contributing to the existing body of knowledge in this area.
KW - Empirical validation
KW - Operations strategy
KW - Optimization model
KW - Production economics
KW - Quality management
KW - Scenario analysis
UR - http://www.scopus.com/inward/record.url?scp=85217859378&partnerID=8YFLogxK
U2 - 10.1108/IMDS-05-2024-0429
DO - 10.1108/IMDS-05-2024-0429
M3 - Article
AN - SCOPUS:85217859378
SN - 0263-5577
VL - 125
SP - 1190
EP - 1219
JO - Industrial Management and Data Systems
JF - Industrial Management and Data Systems
IS - 3
ER -