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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Integration, uncertainty and information: how do they affect planning performance?

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Author(s):
Sagawa, Juliana Keiko [1] ; Nagano, Marcelo Seido [2]
Total Authors: 2
Affiliation:
[1] Univ Fed Sao Carlos, Ctr Ciencias Exatas & Tecnol, Engn Prod, Sao Carlos - Brazil
[2] Univ Fed Sao Carlos, Escola Engn Sao Carlos, Engn Prod, Sao Carlos - Brazil
Total Affiliations: 2
Document type: Journal article
Source: REGE-REVISTA DE GESTAO; JAN 2021.
Web of Science Citations: 0
Abstract

Purpose-Effective planning requires the participation of different functions and may be hampered by lack of integration and information quality (IQ). This paper aims to investigate the relationships among integration, uncertainty, IQ and performance, in the context of the production planning and control function. The literature lacks in-depth studies that consider these factors altogether, showing how they interact and how they contribute to improve business performance. Design/methodology/approach-The authors introduce the variable of planning performance, which represents the quality of the production plans/planning process and is related to the frequency and causes of modifications to these plans. The relationships among the mentioned constructs are investigated by means of multiple case studies. Findings-The results illustrate that integration is positively related to planning performance, and this relationship is mediated by IQ and moderated by uncertainty. Originality/value-The presented analysis may help practitioners to foster interfunctional integration, better cope with uncertainty and improve information management, aiming to achieve better planning performance. The managers can choose integration and IQ improvement mechanisms that better fit to their environment/reality, using the four different cases as a benchmark. Moreover, this research contributes to the literature exploring this contingency perspective by means of in-depth case studies, considering that most of the existing research adopting this perspective is survey-based. (AU)

FAPESP's process: 19/12023-1 - Dynamic models for the control of job shop production systems
Grantee:Juliana Keiko Sagawa
Support type: Regular Research Grants