The questionnaire on productivity attributes (QPA)

• Published in: International journal of productivity and performance management 2018-07, Vol.67 (5), p.845-872
• Main Authors: Kamble, Raju Sheshrao, Wankhade, Lalit Narendra
• Format: Article
• Language: English
• Subjects: Confidence; Discriminant analysis; Employees; Engineers; Error analysis; Factor analysis; Goodness of fit; Human resource management; Identification; Job satisfaction; Literature reviews; Manufacturing; Optimization; Organizational aspects; Performance management; Productivity; Questionnaires; Researchers; Standard error; Variance analysis; Workers
• ISSN: 1741-0401; 1758-6658
• DOI: 10.1108/IJPPM-01-2017-0012

Purpose Although there are many studies investigating attributes affecting productivity, the research into measurement of those attributes has been incomplete. In an attempt to bridge this gap, the authors reviewed the productivity literature, identified and integrated previously described attributes, and developed a measure to estimate those attributes. The developed questionnaire – questionnaire on productivity attributes (QPA) – is based on a five-dimensional conceptual framework, which consisted of human resource management, management strategy, organizational culture, production methodology, and performance. A model that measures a way to construct a linear scale from ordinal data has also been introduced. The paper aims to discuss these issues. Design/methodology/approach Initially, a pilot survey among Indian academic and industrial experts as well as employees working in manufacturing industries was conducted to optimize clarity, readability, and construction of the QPA. After pilot-testing, the 45 QPA items were further field surveyed amongst a representative sample of 311 Indian engineers, managers, and workers from manufacturing industries. One-way analysis of variance is performed to examine whether there are differences among engineers, managers, and workers in the understandability or applicability of QPA. Exploratory factor analysis is used to confirm the five-dimensional conceptual framework. Also, infit and outfit measures have been used to check the QPA model fit. To increase confidence, all retained items are tested for goodness-of-fit test. Finally, the functioning of optimal response categorization of the QPA is demonstrated in terms of frequencies, average measures, and standard error. Findings A five-dimensional conceptual framework is identified. A generic short scale was constructed. Finally, the developed questionnaire provides new insights into how to avoid the trade-offs commonly observed in productivity research. Originality/value The newly designed QPA appears as a general measure for productivity attributes which can be used by scholars and practitioners to conduct basic research on productivity improvement in various industries.