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Waiting for service: modelling the effectiveness of service interventions

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  • Ken Butcher
  • Asad Kayani

Abstract

Most service businesses tend to experience unwelcome delays in service delivery that often generate strong negative impacts from customers. In response, managers develop and implement service intervention strategies, such as providing length and reason of a delay, both of which have been reported to have positive impacts on customers. However, the results from studies investigating such interventions are mixed. Accordingly, it is hypothesised that these effects may be contingent upon certain situations. This research project has investigated the wait situation using an experimental design. A 2 × 2 × 2 factorial design was first created using a restaurant scenario for the stimulus material and an online web site was used to collect data from 130 respondents. Our findings indicate a significant moderating effect of level of service use and degree of goal attractiveness on the effectiveness of providing duration and cause information. More importantly, we found that under certain conditions a service intervention may be counterproductive to the intended strategy. This finding suggests that managers need to be wary of developing and executing expensive service recovery strategies without due regard to the customer segment being targeted. Copyright Springer-Verlag 2008

Suggested Citation

  • Ken Butcher & Asad Kayani, 2008. "Waiting for service: modelling the effectiveness of service interventions," Service Business, Springer;Pan-Pacific Business Association, vol. 2(2), pages 153-165, June.
    • Handle: RePEc:spr:svcbiz:v:2:y:2008:i:2:p:153-165
    DOI: 10.1007/s11628-007-0030-2
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    References listed on IDEAS

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    1. Hui, Michael K & Thakor, Mrugank V & Gill, Ravi, 1998. "The Effect of Delay Type and Service Stage on Consumers' Reactions to Waiting," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 24(4), pages 469-479, March.
    2. Piyush Kumar & Manohar U. Kalwani & Maqbool Dada, 1997. "The Impact of Waiting Time Guarantees on Customers' Waiting Experiences," Marketing Science, INFORMS, vol. 16(4), pages 295-314.
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    Cited by:

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    2. Changhee Kim & Hongsuk Yang & Soo Wook Kim, 2018. "Optimal baggage sorting rule to reduce waiting time in baggage claim," Service Business, Springer;Pan-Pacific Business Association, vol. 12(2), pages 435-451, June.
    3. Paul MUKUCHA & Divaries Cosmas JARAVAZA & Forbes MAKUDZA, 2022. "Towards Gender-Based Market Segmentation: The Differential Influence of Gender on Dining Experiences in the University Cafeteria Industry," Management and Economics Review, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 7(2), pages 182-200, June.
    4. Yan Han & Wanying Li & Shanshan Wei & Tiantian Zhang, 2018. "Research on Passenger’s Travel Mode Choice Behavior Waiting at Bus Station Based on SEM-Logit Integration Model," Sustainability, MDPI, vol. 10(6), pages 1-23, June.
    5. Chanho Song & Sungha Jang & Jennifer Wiggins & Edward Nowlin, 2019. "Does haste always make waste? Service quantity, service quality, and incentives in speed-intensive service firms," Service Business, Springer;Pan-Pacific Business Association, vol. 13(2), pages 289-304, June.
    6. Don Jeng & Sky Kuo, 2012. "Internal service quality within the different Chinese subcultures: a comparison between Taiwan, China, and Singapore," Service Business, Springer;Pan-Pacific Business Association, vol. 6(4), pages 425-458, December.
    7. Fabian Schéele & Darek M. Haftor & Natallia Pashkevich, 2022. "Predicting delays in service operations," Service Business, Springer;Pan-Pacific Business Association, vol. 16(2), pages 211-226, June.

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