SATISFACTION AND NEGATIVE-WORD-OF MOUTH
4.4 Research Methodology
H5c In a service recovery situation, customer-initiated voice has higher effect on negative word-of-mouth intention than no voice.
which was slightly more expensive than that for the card without the accidental insurance coverage. At this point, the customer has detected a service mistake.
There are three experimental conditions regarding customer complaint, namely, firm-initiated voice, customer-initiated voice and no voice. In the firm- initiated voice condition, after the transaction was done, another staff person came to ask whether the transaction was processed correctly and if the customer were satisfied with the service. The customer then complained that he/she did not intend to apply for the card with insurance for which the annual fee was more expensive. The staff apologized and offered that if the customer wanted the chance to change to the normal card, she (the staff) could arrange it. The customer decided to change, and the staff proceeded accordingly.
In the customer-initiated voice condition, when the transaction was complete, the customer decided to go back to the staff and complain that he/she had not intended to apply for the card with insurance for which the annual fee was more expensive. The staff apologized and inquired if the customer wanted to change to the normal card, and if so, the staff could arrange it. The customer decided to change, and the staff completed the change accordingly.
Lastly, the no voice condition describes that after the transaction was complete, the staff came to the customer to inform him of the error and apologize for it. In this iteration, the staff has corrected and changed the card type for customer. All conditions are recovered by the same service recovery; that is, the card has been changed to normal type and a refund was made back to the customer.
4.4.3 Measurement of Variables
The scales used to measure the constructs were adapted from previous studies.
The four items of distributive justice, the four items of interactional justice, and the three items of satisfaction were adapted from Maxham and Netemeyer (2002).
Procedural justice was measured using seven items adapted from Karande et al. (2007).
Finally, negative word-of-mouth intentions were measured on three items adapted from Blodgett et al. (1997). (Blodgett et al., 1997). All justice items and negative word-of-mouth intentions were measured on a seven-point scale, anchored by “1 =
strongly disagree” to “7 = strongly agree”. Satisfaction items were measured on a seven-point scale ranging from “1 = not at all satisfied” to “7 = very satisfied”.
As the measurement items were originally developed in English, this study uses collaborative translation technique to assure the conceptual equivalence (Douglas
& Craig, 2007). First, the authors and a professional translator simultaneously and independently translated the scale items into Thai. Then, another researcher fluent in both Thai and English used a back-to-back translation technique to evaluate whether the two translated scales maintained the meaning of the original measurement scales.
A pretest was conducted with 25 respondents; the scales were then modified and finalized based on the feedback received.
4.4.4 Manipulation and Realism Checks
To check whether the experimental manipulations worked as intended, the participants were asked to report the perceptions of the scenarios. The manipulation check items were measured using a seven-point scale anchored by “ 1 = strongly disagree” to “7 = strongly agree”. The realism of the scenario was checked by asking the participants the extent to which they thought the situation described in the scenario could happen in real life. The realism was measured on a seven-point scale ranging from “1 = not at all realistic” to “7 = very realistic”.
4.4.5 Participants
The sample consists of 258 undergraduate students (39% men, aged 20-29 years) from two universities in Thailand. Using undergraduate students as subjects is consistent with the previous research in service recovery (Bonifield & Cole, 2007;
Grewal et al., 2008; Prasongsukarn & Patterson, 2012; Lastner et al., 2016).
Furthermore, a student sample is appropriate for this study as students are familiar with the service domain. Among them, 100% were currently bank customers, 85.74%
had heard about service failure, and 15.70% had encountered a similar type of failure.
4.4.6 Procedures
Data collection was conducted in a classroom setting. The experimenters first greeted and gave information and instructions for the experiment. Then, each participant was randomly assigned one of the three scenarios. The participants were asked to imagine they were the customers in the scenario and answer a series of questions about their responses to the scenario, the manipulation check, and demographic information.
4.4.7 Control Variables
Attitudes toward complaining, external blame attribution, gender, and past experience were included as control variables of the analysis as they were indicated influence evaluation of service recovery in previous studies. External blame attribution was measured for three items adopted from Gelbrich (2010). Participants were asked to measure on a seven-point scale, anchored by “1 = not at all” to “7 = very much”. Attitudes toward complaining was measured by four items adopted from Bodey and Grace (2006), and these measurement items were assessed on seven-point scale ranging from “1 = strongly disagree” to “7 = strongly agree”. Gender and past experience with service failure were measured by a single item.
4.4.8 Common Method Bias
This study collected the data using a self-reporting questionnaire for which independent and dependent variables were collected from the same source; this may lead to a common method variance problem. As suggested by Podsakoff et al. (2003), this study used both procedural and statistical remedies to control the common method bias. For procedural remedies, the participants were assured of anonymity and were assured that there were no right or wrong answers. Additionally, the order of measurement of independent and dependent variables were counterbalanced to control for priming effects. In the statistical control stage, Harman’s single factor test was conducted to identify the presence of common method variance. The exploratory factor analysis result reports that the largest variance explained by a single factor was 29.49%, indicating that the study was not compromised by common method bias issue.