Are managerial pressure, technological control and intrinsic motivation effective in improving data quality?

• Published in: Reliability engineering & system safety Vol. 119; pp. 26 - 34
• Main Authors: Molina, Roger, Unsworth, Kerrie, Hodkiewicz, Melinda, Adriasola, Elisa
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.11.2013; Elsevier
• Subjects: Accumulators; Applied sciences; Asset management; Biological and medical sciences; Collectors; Computer science; control theory; systems; Data acquisition; Data quality; Exact sciences and technology; Firm modelling; Fundamental and applied biological sciences. Psychology; Information systems. Data bases; Interactive; Managerial style; Manual data collection; Memory organisation. Data processing; Motivation; Motivation. Job satisfaction. Attitude; Occupational psychology; Operational research and scientific management; Operational research. Management science; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Reliability engineering; Reliability theory. Replacement problems; Safety; Software; Technological control; Water utilities; Managerial style; Technological control; Data quality; Asset management; Motivation; Manual data collection; Staff management; System reliability; Manager; Mixed method; Employee; Data integrity; Sequential method; Information quality; Concordance; Database; Self control; Quantitative analysis; Data gathering
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2013.04.009

Can data collectors be “pushed” into collecting high quality data or would being “pulled” be more effective? This paper finds that managers should be careful of the degree to which “push” factors, such as managerial pressure and technological input control, are relied upon. While they may be helpful for motivating those data collectors who are not intrinsically motivated, they are either not helpful or may discourage those data collectors who are intrinsically motivated. Instead, self-concordance may act as a longer-term, more stable approach to increasing the motivation of data collectors and thus increasing the quality of data that enter reliability systems. This study uses a sequential mixed-method approach involving interviews with 20 data collectors and a quantitative survey of 109 data collectors in a water utility. It examines the interactive effect of managerial pressure, technological input control and self-concordance on data collection performance.