Complexity as contingency in sales and operations planning

Antônio Márcio Tavares Thomé*, Rui Soucasaux Sousa, Luiz Felipe Roris Rodriguez Scavarda Do Carmo

*Autor correspondente para este trabalho

Resultado de pesquisarevisão de pares

23 Citações (Scopus)

Resumo

Purpose - The purpose of this paper is to test whether complexity interacts with Sales and Operations Planning (S&OP) practices by positively moderating the impact of S&OP practices on manufacturing operational performance dimensions of quality, flexibility and delivery. Design/methodology/approach - Three hypotheses are developed on the relationships between S&OP practices, task complexity and process complexity and manufacturing operational performance. Scales are validated with structural equation modelling. The hypotheses are tested through a hierarchical regression analysis using data from a sample of 725 manufacturing plants from 21 countries. Findings - S&OP practices of organizational management, technological integration, measurement systems and integration of plans impact positively on manufacturing operational dimensions of quality, delivery and flexibility. Process complexity moderates the effect of S&OP practices, amplifying its impact upon all three performance dimensions. Product complexity moderates the effect on quality, but not on delivery and flexibility. Practical implications - S&OP practices of organizational and technological coordination of manufacturing and new product design; information technology to measure information sharing and planning; dedicated information systems do impact upon manufacturing operational performance. Results are amplified by process complexity. The more complex are the manufacturing processes the larger the gains of S&OP. Originality/value - This research applies contingency theory to S&OP and empirically demonstrates its impact on manufacturing operational performance and the moderator role of complexity.
Idioma originalEnglish
Número do artigo17112551
Páginas (de-até)678-695
Número de páginas18
RevistaIndustrial Management and Data Systems
Volume114
Número de emissão5
DOIs
Estado da publicaçãoPublicado - 2014

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