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Title: An Empirical Study and Model Assessment of Scheduling Performance Metrics in Automobile Industries
Authors: Yadav, Puneet
Supervisor: Bhullar, Supreet
Keywords: Scheduling performance;Partial least square-structural equation modeling;Executional Uncertainty;Environmental Uncertaity
Issue Date: 11-Aug-2016
Abstract: In today’s competitive business environment the planning and scheduling significantly influence the organizational performance, hence it is a quintessential aspect of the entire production system, though there is a limited literature on how an organization should organize and assess the planning process. The purpose of this thesis is to identify the factors on which scheduling performance can be measured in the automobile industries in the Northern India specifically. We extend planning and scheduling theory with a categorization of scheduling performance criteria, based on survey research design. In this research data from various automobile manufacturing industries in the northern India has been collected with the help of a questionnaire and analyzed using Statistical Package for the Social Sciences (SPSS) and Partial least square (PLS) has been used to develop the measurement and structural model for the study. Separate data have been collected planners and managers, hence separate models have also been prepared. Particularly, the results show that the scheduling process and product criteria have been significantly affecting the scheduling performance. The results revealed that executional uncertainty negatively affects the influential factors for both planner and the manager, while environmental uncertainty has a positive impact according to the manager and negative impact according to the planners and, hence study reports lack of coherence amongst the opinion of planner and manager. Therefore this research theoretically contributes to scheduling and performance measurement literature and practically supports managers and planner in developing scheduling performance measurement systems.
Appears in Collections:Masters Theses@MED

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