Examining the relationships between innovation, quality, productivity, and customer satisfaction in pure service companies

Author:

Rew Dongjun,Jung Joo,Lovett Steve

Abstract

PurposeThis study investigates the relationships between innovation, quality, productivity and customer satisfaction in pure service companies. Previous studies have shown a negative relationship between quality and productivity in services. However, we argue the two can be positively related when innovation is present.Design/methodology/approachThis paper develops and tests hypotheses using secondary data from COMPUSTAT, KLD STAT and the American Customer Satisfaction Index (ACSI). We test these hypotheses using ordinary least squares regression and conduct additional testing using path analysis.FindingsThe findings show that quality and productivity are positively related when innovation is present in pure service companies. The findings also reveal find that innovation is antecedent to both service quality and productivity which in turn positively affect customer satisfaction.Practical implicationsBoth companies and customers can increase their outcomes including higher levels of service quality, productivity and customer satisfaction. Managers should therefore design innovative systems that enable customers to participate in service production. Other innovative systems may help to increase capacity utilization by smoothing high and low demand times, thus increasing both service quality and productivity.Originality/valueThis study contributes to service research by identifying innovation as the key to simultaneously increasing service quality and productivity. The authors find empirical support for a model in which service quality and productivity have a complementary relationship leading to customer satisfaction with innovation as an antecedent, and we do so using a sample of pure service firms.

Publisher

Emerald

Subject

Strategy and Management,General Business, Management and Accounting,Business and International Management,General Decision Sciences

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