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Orientador(es)
Resumo(s)
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.
Descrição
Palavras-chave
Product complexity Manufacturing operational performance Advanced manufacturing technology Procescomplexity Paper type Research paper
Contexto Educativo
Citação
THOMÉ, António Márcio Tavares; SOUSA, Rui; CARMO, Luiz Felipe Roris Rodriguez Scavarda do - Complexity as contingency in sales and operations planning. Industrial Management & Data Systems.ISSN 0263-5577. Vol. 114, N.º 5 (2014) p. 678-695
Editora
Emerald