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Page 1 of 8 ANZMAC 2009 Antecedents and Consequences of Customer Satisfaction with Interactive Voice Response Nichola Robertson, Deakin University, Heath McDonald, Deakin
Page 1 of 8 ANZMAC 2009 Antecedents and Consequences of Customer Satisfaction with Interactive Voice Response Nichola Robertson, Deakin University, Heath McDonald, Deakin University, Abstract The aim of this study was to empirically test a model of antecedents and consequences of customers satisfaction with interactive voice response (IVR). IVR is a commonplace selfservice technology, yet it has seldom been the focus of academic research. As customers frustration with IVR is apparent, understanding how customers evaluate IVR and their subsequent behavioural intentions is important. Findings of a study of Australian Football League members who were users of its IVR system indicated that customer satisfaction resulted when it was easy to use, offered fast service and provided customers with feelings of control. Overall satisfaction with the IVR system was related to customers intentions to reuse it and their trust in the AFL. Managerial implications of the findings are discussed. Keywords: Interactive voice response (IVR), self-service technology, customer satisfaction, antecedents and consequences. ANZMAC 2009 Page 2 of 8 Antecedents and Consequences of Customer Satisfaction with Interactive Voice Response Background Self-service technologies, or machine-assisted and electronic services, are diverse in terms of variety (Anitsal et al., 2002; Ostrom et al., 2002). Therefore, prominent researchers in the field of SST study have advocated distinguishing between the different types of SSTs (Dabholkar, 1994; Meuter et al., 2000). In classifying SSTs, a key categorisation variable applied is the type of technology. This includes Internet, interactive kiosk and interactive voice response (IVR) (Meuter et al., 2000). Previous SST studies have been broadly conducted across SST technology types (i.e., data were aggregated without regard for specific types of SSTs) (see, for example, Meuter et al., 2000; Robertson and Shaw, 2009), or have been skewed toward Internet-based SSTs (Evanschitzky et al., 2004; Yen and Gwinner, 2003), with some focus on kiosks (Dabholkar and Bagozzi, 2002; Oyedele and Simpson, 2007; Simon and Usunier, 2007). Conversely, there is a lack of research on IVR (see, for exception, Dean, 2008; McCartan-Quinn et al., 2004). As differences in consumer behavior have been demonstrated between the distinct types of technologies (Curran and Meuter, 2005), the current study focuses on IVR that has been provided the least attention in the SST literature. IVR is defined as an automated telephony technology that uses a recorded human voice to offer customers a menu of options and prompts them for spoken responses. Customers responses are read by IVR technology to provide service to customers (Dean, 2008). IVR enables customers to generate benefits for themselves, without the presence of the organisation s personnel (Meuter et al., 2000). For example, customers can use IVR to book a taxi service, obtain flight information, pay a credit card bill, or lay a wager. However, despite the prominence of IVR in a range of service industries, it has seldom been the focus of academic research. We were able to locate only two academic studies in the marketing literature that focused solely on IVR (see Dean, 2008; McCartan-Quinn et al., 2004), and two additional studies that included it in a comparison of SSTs (Curran and Meuter, 2005; 2007). The Dean (2008) and McCartan-Quinn et al. (2004) studies were exploratory in nature and were concerned with customers frustrations with IVR. These studies findings suggested that customers were generally dissatisfied with IVR. This is similarly echoed in the trade literature and, in the authors experience, is representative of social chitchat related to IVR. It is common to hear customers complaining about their negative experiences with IVR (McCartan-Quinn et al., 2004). In the light of this, the current study empirically tests a model of antecedents and consequences of customer satisfaction with an IVR SST. This is important because customer satisfaction will influence the success of IVR and of the organisations that employ it. The Proposed Model and Hypotheses Development The model proposed and resulting hypotheses (see Figure 1) is grounded in the SST and information systems (IS) literature. As IVR is considered a type of SST, we propose that the antecedents that have been found to influence customers evaluation of other types of SSTs (e.g., Internet-based SSTs), may be relevant in the context of IVR. These included reliability (Dabholkar et al., 2003), ease of use (Curran and Meuter, 2005; Dabholkar et al., 2003), Page 3 of 8 ANZMAC 2009 enjoyment (Dabholkar et al., 2003), perceived control (Dabholkar et al., 2003; Lee and Allaway, 2002) and perceived speed (Dabholkar et al., 2003). However, the distinct characteristics of IVR, such as it being an audio technology, bring into question the applicability of such antecedents, which need to be confirmed by empirical research. The outcome variables of customers satisfaction with IVR that were included in this study are customers intentions to reuse the IVR system and customers trust in the service provider. SST providers rely on both initial adopters and continued users (Eriksson and Nilsson, 2007). Customer satisfaction with IVR is expected to influence customers intentions to continue to use it, influencing its survival. In respect to the construct of trust in the service provider, SST research has demonstrated that customers develop attitudes toward many distinct elements in an SST encounter, including the service provider in general (Reinders et al., 2008). Reliability H 1 Ease of use H 2 (+ve) 0.41*** H 6 (+ve) 0.46*** Trust in provider Enjoyment H 3 (+ve) 0.07 H 4 (+ve) 0.28*** Overall satisfaction H 7 (+ve) 0.83*** Perceived control H 5 (+ve) 0.29*** Reuse intentions Speed Figure 1: Hypothesised Model of IVR Satisfaction Research Method Research Method The Australia Football League (AFL) offers season ticket passes at both club level and at the broader sport level. AFL members hold the broader level season tickets. They are the focus of this study. In 2009, over 49,000 AFL memberships were sold. In 2008, two new SSTs were introduced to service AFL members. The first was an IVR system that allows members to undertake tasks such as renewing their memberships and retrieving match day information. The second was an online membership service that allows members to carry out activities like booking reserved seats and dining at matches, renewing memberships and updating personal details. Data were collected on the use of both SSTs by AFL members, but only the IVR data is reported in this paper. A complete list of all AFL members who had provided the AFL with an address and permission to be contacted was obtained from the AFL. The list ANZMAC 2009 Page 4 of 8 contained the contact details of 28,147 members (57 per cent of the total membership). All members were contacted via and were invited to complete an online questionnaire. The survey was open for two weeks, and one reminder was sent after seven days to nonrespondents. By the close of the survey, 6,010 members had responded (21 per cent of the sample, 12 per cent of the population). Tests for non-response bias were conducted by comparing early and late respondents on three key questions, and by comparing respondent demographics to known population data, and no evidence of bias was found. As part of a larger questionnaire, respondents were asked if they had used the new SSTs adopted by the AFL. Those who had used either or both of the SSTs were asked to complete a series of items pertaining to their SST experience. Existing items that were sourced from past studies, and adapted to the IVR context, were employed to measure each of the constructs of interest (speed; three items (Dabholkar, 1996), ease of use; four items (Dabholkar, 1996), reliability; four items (Dabholkar, 1996), enjoyment; three items (Dabholkar, 1996), perceived control; three items (Dabholkar, 1996), overall IVR satisfaction; two items (Lin and Hsieh, 2007), intentions to reuse the IVR; four items (Turel et al., 2008) and trust in the provider; four items (Gefen et al., 2003)). All of the measures utilised a seven-point scale. Of the 6010 AFL members who completed the survey, 958 reported having used the new SSTs. For IVR, 250 respondents (4 per cent) reported having used it. This figure is consistent with data collected by the IVR system in respect to usage levels. The analysis presented in this paper concerns only those AFL members who reported using the IVR system. Following the removal of seven multivariate outliers, 243 usable responses remained. The data were analysed using the two-step approach to structural equation modelling. The measurement model was found to fit the data adequately (see Table 1) following the deletion of several items based on the diagnostics provided by AMOS 17.0 and that could be justified theoretically (McDonald, Ho, and Ho, 2002). All of the constructs were confirmed to be unidimensional, as per the literature. Composite reliability (see Table 1) and average variance extracted (see Table 2) were calculated per construct, all of which were found to be above the 0.5 level recommended (Fornell and Larcker, 1981). In order to demonstrate discriminant validity, the researchers took the square root of each of the AVE values as in Table 2 (Hulland, 1999). These were compared to the correlations in the corresponding rows and columns. To show discriminant validity for each of the constructs, the magnitude of the square root of the AVE value needs to be greater than the magnitude of the correlations in the equivalent rows and columns. Table 2 indicates that there is acceptable discriminant validity for each construct in the study, with the exception of reliability that was subsequently removed from further analysis. Once the measurement model was shown to be satisfactory, the structural model was tested. With the exception of chi-square, the fit statistics indicated a good fit of the model to the data (chi-square = [df = 140], p = 0.00, NF1 = 0.96, CFI = 0.98, and RMSEA = 0.05). All of the hypotheses were supported (see the standardised estimates in Figure 1), with the exception of H 3, i.e., IVR enjoyment was not found to be related to overall satisfaction. The relationship between reliability of the IVR and overall satisfaction was not tested (see Figure 1) due to the problematic discriminant validity of the reliability construct. The model explained 69 per cent of the variance in reuse intentions and 31 per cent of customers trust in the AFL. Page 5 of 8 ANZMAC 2009 Table 1: Final Measurement Model Results Model Fit Chi-square df NFI CFI RMSEA Variable Mean Standard Standardised CR Deviation Loading Reliability The IVR works well Using the IVR results in faultless service The IVR delivers what it promises Ease of use Using the IVR is effortless The IVR is user-friendly The IVR is easy to use Enjoyment The IVR is entertaining to use The IVR is fun to use Perceived control I have complete control when using the IVR I feel in charge when using the IVR Speed The IVR allows me to get fast service The IVR provides me with efficient service The IVR reduces the waiting time for the service Overall satisfaction Overall, I am satisfied with the IVR offered by the AFL The IVR offered by the AFL is close to my ideal IVR Reuse intentions Assuming I had another need for service, similar to this one, I intend to use the IVR Given that I had another need for service, similar to this one, I predict that I would use the IVR I intend to use the IVR for service as often as needed Trust in provider AFL membership is honest AFL membership care about its customers AFL membership provide good service AFL membership can be relied on to keep its promises ANZMAC 2009 Page 6 of 8 Table 2: Correlation Matrix and AVE Statistics Construct Construct Reliability Speed 0.88** Ease of use 0.92** 0.87** Perceived control 0.71** 0.68** 0.69** Enjoyment 0.67** 0.65** 0.65** 0.77** Overall satisfaction 0.89** 0.85** 0.87** 0.79** 0.72** Reuse intentions 0.76** 0.71** 0.73** 0.68** 0.63** 0.79** Trust in provider 0.52** 0.49** 0.49** 0.40** 0.37** 0.52** 0.51** 0.91 Note: Diagonal elements shown in bold are square roots of the AVE values of the constructs. Discussion, Managerial Recommendations and Limitations The aim of this study was to test a model of antecedents and consequences of customers satisfaction with IVR. The results suggest that the antecedents of customers satisfaction with the AFL s IVR system generally correspond to those found in previous SST satisfaction research, which has often been conducted in the online context. Firstly, ease of use of the IVR system was found to be the strongest predictor of customers overall satisfaction with it. Customers use of IVR should be effortless and, therefore, IVR s automated voice needs to be clear and its menus should be simple. Secondly, perceived control was found to be weakly related to customers satisfaction with IVR. Customers are more likely to positively evaluate SSTs that offer them a sense of control (Lee and Allaway, 2002). If customers feel trapped inside the IVR system, described as IVR hell (Dulude 2002, p. 172), their perceived control is diminished, as is their overall satisfaction with the system. Thirdly, customers perceived speed of the IVR system was weakly and positively related to customers overall satisfaction with it. This is supportive of Dean s (2008) exploratory work on IVR. A major source of satisfaction for customers of SSTs is timesaving (Meuter et al., 2000). This finding reiterates the importance of short menus and the accuracy of speech recognition. This will avoid delays associated with customers being required to listen to lengthy menus and repeat information. Finally, enjoyment was not found to be related to customers satisfaction with IVR. This could be explained by the fact that the telephone has been a major part of our lives for a long time and, therefore, is not associated with the fun of using a more novel SST, such as retail self-scanning. In respect to the outcomes of customers satisfaction with IVR, both customers intentions to reuse the IVR system and their trust in the provider, i.e., the AFL, were positively associated with customer satisfaction with the system. As it has been suggested that IVR systems are often market rather than customer driven (Dean, 2008), this study highlights the importance of customer satisfaction with IVR in encouraging customers to reuse the technology and spilling over to their global perceptions of trust in the provider. The implications of this study are tempered by several limitations. These include the questionable accuracy of self-reports, the small number of items that remained to measure some of the constructs and the use of a single service context and type of IVR system, e.g., oral versus using a telephone keypad. Therefore, extending the current study to other service contexts and testing the model across IVR types is encouraged. Future research also needs to consider the effects of other IVR distinctive antecedents of IVR satisfaction, e.g., voice quality, and additional consequences, such as positive word of mouth. Page 7 of 8 ANZMAC 2009 References Anitsal, I., Moon, M.A., Anitsal, M.M., Technology-based self service: Issues for retail management and research. Developments in Marketing Science 25 [no issue number provided], Curran, J.M. and Meuter, M.L., Self-service technology adoption: Comparing three technologies. Journal of Services Marketing 19 (2), Curran, J.M. and Meuter, M.L., Encouraging existing to switch to self-service technologies: Put a little fun in their lives. Journal of Marketing Theory and Practice 15 (4), Dabholkar, P.A., Technology-based service delivery: A classification scheme for developing marketing strategies. Advances in Services Marketing and Management 3 [no issue number provided] Dabholkar, P.A Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality. International Journal of Research in Marketing 13 (1), Dabholkar, P. A. and Bagozzi, R.P An attitudinal model of technology-based selfservice: Moderating effects of consumer traits and situational factors. Journal of the Academy of Marketing Science 30 (3), Dabholkar, P.A., Bobbit, L.M., Lee, E.J Understanding consumer motivation and behavior related to self-scanning in retailing: Implications for strategy and research on technology-based self-service. International Journal of Service Industry Management 14 (1), Dean, D. (2008). What s wrong with IVR self-service. Managing Service Quality 18 (6), Dulude, L Automated telephone answering systems and aging. Behaviour and Information Technology 21 (3), Eriksson, K., Nilsson, D Determinants of the continued use of self-service technology: The case of Internet banking. Technovation 27 (4), Evanschitzky, H., Iyer, G.R., Hesse, J., Ahlert, D E-satisfaction: A re-examination. Journal of Retailing 80 (3), Fornell, C. and Larcker, D.F Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18 (February), Gefen, D., Karahann, E., Straub, D.W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27 (1), Hulland, J Use of partial least squares in strategic management research: A review of four recent studies. Strategic Management Journal 20 (2), ANZMAC 2009 Page 8 of 8 Lee, J. and Allaway, A Effects of personal control on adoption of self-service technology innovations. Journal of Services Marketing 16 (6), Lin, C. Hsieh, P.L The influence of technology readiness on satisfaction and behavioural intentions toward self-service technologies. Computers in Human Behaviour 23 [no issue number provided], McCartan-Quinn, D., Durkin, M., O'Donnell, A Exploring the application of IVR: Lessons from retail banking. The Service Industries Journal 24 (3), McDonald, R.P., Ho, R., Ho, M Principles and practice in reporting structural equation analyses. Psychological Methods 7 (1), Meuter, M.L., A.L. Ostrom, Roundtree, R.I., Bitner, M.J Self-service technologies: Understanding customer satisfaction with technology-based service encounters. Journal of Marketing 64 (3), Oyedele, A, Simpson, P.M An empirical investigation of consumer control factors on intention to use selected self-service technologies. International Journal of Service Industry Management 18 (3), Ostrom, A.L., Bitner, M.J., Meuter, M.L Self-service technologies. In: Rust, R.T., Kannan, K.T. (Eds.), e-service: New Directions in Theory and Practice. M.E. Sharpe, NY, pp Reinders, M.J., Dabholkar, P.A., Frambach, R.T Consequences of forcing consumers to use technology-based self-service. Journal of Service Research 11 (2), Robertson, N. and Shaw, R.N. (2009) Predicting the likelihood of voiced complaints in the self-service technology context. Journal of Service Research 12 (1), Simon, F., Usunier, J.C. (2007) Cognitive, demographic, and situational determinants of service customer preference for personnel-in-contact over self-service technology. International Journal of Research in Marketing 24 (2), Turel, O., Yuan, Y., Connelly, C.E In justice we trust: Predicting user acceptance of e- customer services. Journal of Management Information Systems. 24 (4), Yen, H.R. and Gwinner, K.P., Internet retail customer loyalty: The mediating role of relational benefits. International Journal of Service Industry Management 14 (5),
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