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Sanjay L. Ahire

Researcher at University of South Carolina

Publications -  40
Citations -  4677

Sanjay L. Ahire is an academic researcher from University of South Carolina. The author has contributed to research in topics: Total quality management & Quality management. The author has an hindex of 21, co-authored 38 publications receiving 4477 citations. Previous affiliations of Sanjay L. Ahire include Western Michigan University & University of Dayton.

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Development and Validation of TQM Implementation Constructs

TL;DR: Through a detailed analysis of the literature, this research identifies 12 constructs of integrated QM strategies and using a survey of 371 manufacturing firms, the constructs are empirically tested and validated.
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The impact of design management and process management on quality: an empirical investigation

TL;DR: In this article, the authors established a framework for identifying the synergistic linkages of design and process management to the operational quality outcomes during the manufacturing process (internal quality) and upon the field usage of the products (external quality).
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The role of top management commitment in quality management: an empirical analysis of the auto parts industry

TL;DR: In this article, the authors examined the associations between ten integrated quality management constructs and the resulting product quality, and concluded that firms with high top management commitment produce high quality products despite variations in individual constructs.
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Total quality management: a literature review and an agenda for future research

TL;DR: A review, classification, and analysis of the research in TQM spanning the last two decades is presented in this paper, where a total of 226 articles are identified from 44 refereed management journals published from 1970 to 1993 and these articles are then classified and analyzed using the following two-dimensional scheme: (1) article orientation (conceptual, case study, empirical, analytical, simulation, and overview) and (2) article focus using the Malcolm Baldrige National Quality Award criteria.
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An empirical comparison of statistical construct validation approaches

TL;DR: The Hybrid Approach performs well not only in terms of the statistical validity of constructs, but also incorporates the feature to recognize patterns suggested by exploratory methods, and is recommended for refining and validating measurement instruments in relatively unexplored research domains as well as in matured research domains.