Examining customer evaluations across different self-service technologies

Purpose – This study aims to examine the influence of different self-service technologies (SSTs) on customer satisfaction with and continued usage of SSTs. Specifically, it compares an interactive voice response (IVR) SST and an online SST from the same provider to assess how to manage these parallel SSTs.

Design/methodology/approach – A tracking study was used, beginning with a survey of n = 957 SST users to test a model pertaining to SST satisfaction across IVR and online SSTs. These SST users were then tracked over 12 months. The association between customer satisfaction with and continued usage of the SSTs was examined using behavioural data from the service provider.

Findings – While the overall model was found to be valid across both types of SSTs, perceptions of factors including ease of use, perceived control and reliability differed for IVR and online SSTs. Satisfaction with SSTs is linked with users’ continued use of SSTs, but is not a barrier to users’ adoption of newer SST forms.

Research limitations/implications – Highlighting the rapid developments in this field, a new SST was introduced by the provider to respondents during the 12-month tracking period, thus complicating the results. Further studies could include the customer purpose for using SSTs as a variable.

Practical implications – The findings offer support for organisations offering a suite of SSTs, even if they serve the same purpose. Customers evaluate SST types differently, and even satisfied SST users switch to different SSTs when they become available. Allowing customers to choose the SST that best suits them appears to be good practice.

Originality/value – This study develops a comprehensive model of customer SST satisfaction that is used to undertake a comparison of two different types of SSTs, which has been missing from prior research.

Recovering from other-customer-caused failure: the effect on focal customer complaining

In the high-contact restaurant context, customers frequently “overstay,” which negatively influences focal customers waiting for tables. We examine service recovery of this failure, otherwise termed an other-customer-caused failure (OCCF) by restaurants, and its influence on focal customer complaint intentions to the organization, namely vent and voice. OCCFs are commonplace and can have a damaging effect on service organizations, and thus need to be managed; yet empirical examination of their recovery is scarce. We address this by testing the effect of the recovery actions of wait comfort, service-worker effort, and apology on focal customers’ vent and voice complaint intentions. We found that these recovery actions interact complexly. Wait comfort is obligatory in reducing customer complaints, while effort and apology are substitutable when a comfortable wait is provided. This is an important contribution, as wait comfort has not previously been examined as a recovery action.

Crowdsourcing customer needs for product design using text analytics

In product design and engineering, identifying customer needs is the foundation for designing and producing a successful product. Traditionally, a range of techniques have been employed to elicit customer needs. A relatively new technique for identifying customer needs is ‘crowdsourcing’. An emerging area of research is the crowdsourcing of customer needs from online product review sites. This paper proposes a simple process for crowdsourcing customer needs for product design using text analytics. The analysis/visualization method is presented in detail. The text content of online customer reviews for a popular product is collected and processed using text analytics software. A published case study identifying expressed customer needs for the same generic product, collected via conventional means, is used to successfully validate the findings from the text analytics method.