Understanding the formation of software-as-a-service (SaaS) satisfaction from the perspective of service quality
Introduction
The development of on-demand software delivery service models such as software-as-a-service (SaaS), aiming to provide firms with Internet-based access to resources or applications related to a firm's complete virtual value chain [3], [28], has raised an important question: How to improve a client firm's satisfaction. The reason for attracting a client firm is to avoid high installation cost and uncertainty pervading tradition IT initiatives, but reduced capital investments of the client usually cause its low dedication to the relationship with its service provider (SP) [17], [25]. Satisfaction plays a key role in avoiding a client's switch to a new vendor and increasing its positive word of mouth and long-term continuation of relationships with the SP [16]. However, studies on SaaS [4] show that clients' unsatisfying rate is high and the formation of satisfaction is inconclusive, slowing the advances of SaaS. This present study focuses on the determinants of satisfaction in SaaS, because they help SPs understand how to improve their service quality and clients choose the SP which is beneficial to them to avoid costs involved in switching SPs including termination costs and redeployment costs [11].
While the promising opportunities for the successful use of SaaS and its software revenues, are forecasted to grow by 19.4% overall between 2008 and 2013, not everyone is optimistic about the future of SaaS [4]. Some studies are skeptical about SaaS's viability in markets of enterprise application software such as ERP and have identified that the top three reasons for dissatisfying client firms are unfulfilled technical requirements, information security and privacy concerns, and lack of flexibility for performing the outsourced task such as changing contractual or functional aspects [3], [4]. Others have pointed out that inspiring trust and loyalty in an online and on-demand service model may not be easy [6], [24].
Due to these inconsistent views, researchers on SaaS have struggled to develop research models by identifying the key drivers of client satisfaction. They have suggested that a socio-technical perspective should be used by combining individual, technological, organizational, and service-related factors [3], [4]. Accordingly, some studies have examined various antecedents of satisfaction, including individual characteristics (e.g. perceptions on SPs' performance and competence, trust), contextual factors (e.g. gender, experience, and shared values) and service quality (e.g. interaction and outcome quality, perceived benefits) [10], [16], [28]. However, less attention has been paid to the unique features of SaaS and a systematic and empirical investigation on the formation of SaaS satisfaction remains scant. Without the minimal level of satisfaction, users are unlikely to continue using SaaS and the investment in SaaS is unable to recover, emphasizing the importance of understanding satisfaction. To deliver satisfied services, SaaS vendors have to earn their customers' trust and to provide high quality service from which the trust can be created [4], [11]. Responding to their calls and attempting to fill the gap in understanding about how SaaS customers' satisfaction is formed, this study raises the following research questions.
RQ1: How does trust in SaaS vendors' competence and goodwill affect customers' satisfaction? How do relational norms moderate the above relationships?
RQ2: How does vendors' service quality affect trust?
This study builds on theories in several domains to deepen our understanding about how satisfaction is formed, including social capital, social exchange theory, and service marketing [13], [16], [30]. The underlying premise of our work is that client satisfaction is most likely to be affected by whether an SP is perceived to possess characteristics that support the SaaS-based software delivery arrangements. In particular, this study draws from the dedication–constraint framework [2] by integrating two distinct mechanisms of trust—competence-based (CBT) and openness-based (OBT) trust. We emphasize the role of trust as an intervening variable linking the causal relationship between SP service quality and client satisfaction. Besides, we also examine how trust interacts with relational norms to influence satisfaction. This study contributes to the research of on-demand and online service by accounting for the influence of dedication–constraint mechanisms on shaping post-adoption phenomena.
Section snippets
Satisfaction and SaaS
Extant research on outsourcing has considered user satisfaction as one of the most important measures of IS success in general and outsourcing in particular [8], [26]. Satisfaction with new service reflects users' cognition-based and emotion-based evaluation on it and plays a key role in their post-adoption behavior (e.g., word-of-mouth and continuance) [16], [29], [30]. Understanding the formation of satisfaction is critical to a new business model such as SaaS, because in the early
Hypotheses
Fig. 1 lists the model of this study, including the base relationships between service quality, trust, and satisfaction (H1–3), and the moderating effect of relational norms on the relationships between trust and satisfaction (H4).
Survey administration and sample characteristics
In order to test the proposed hypotheses, this study used a survey method to collect empirical data. With the help of “Market Intelligence & Consulting” department of “Institute for Information Industry” in Taiwan and some SaaS online forums such as “McAfee”, we identify those firms that are most likely to have experiences with SaaS. Senior IT managers were chosen as the key informants because of their experience in outsourcing and SaaS. We mailed the questionnaire to them along with a letter
Analysis and results
This study used partial least squares (PLS) analysis to examine the measurement model empirically [7]. Compared to other methods, PLS does not require data to have large sample size and multivariate normal distribution. Moreover, PLS is able to test interaction terms. PLS conducts an iterative set of factor analysis and a bootstrap approach to evaluate the significance (t-value) of the paths based on ordinary least squares by PLS's estimation technique. This study employed SmartPLS 2.0 with
Discussion
To the best of our knowledge, this is the first empirical research to investigate the relationships between service quality of SaaS, trust, and satisfaction and consider the moderating effect of relational norms on the formation of satisfaction.
First, the influence of trust on satisfaction shows that the predictive power of competence-based trust is similar to that of openness-based trust, implying that clients' satisfaction with vendors is influenced by both clients' emotion and rational
Shih-Wei Chou is a professor in the department of MIS (Management of Information Systems) at National Kaohsiung First University of Science of Technology in Taiwan where he teaches knowledge management, software engineering, object-oriented information systems, and management of information systems. He received his doctorate in computer science (CS) from Illinois Institute of Technology, and he holds a master degree in CS from Mississippi State University. Prior to getting his doctorate, he
References (30)
- et al.
Customers' motivations for maintaining relationships with service providers
Journal of Retailing
(1997) - et al.
Opportunities and risks of software-as-a-service: findings from a survey of IT executives
Decision Support Systems
(2011) - et al.
Facilitating relational governance through service level agreements in IT outsourcing: an application of the commitment–trust theory
Decision Support Systems
(2008) - et al.
An investigation of factors that influence the duration of IT outsourcing relationships
Decision Support Systems
(2007) - et al.
Exploring information technology outsourcing relationships: theory and practice
The Journal of Strategic Information Systems
(2000) - et al.
Are there contagion effects in information technology and business process outsourcing?
Decision Support Systems
(2011) - et al.
The evolution of Web-based optimization: from ASP to e-services
Decision Support Systems
(2007) - et al.
Assessing the effects of service quality and justice on customer satisfaction and the continuance intention of mobile value-added services: an empirical test of a multidimensional model
Decision Support Systems
(2012) - et al.
An interdisciplinary perspective on IT services management and service science
Journal of MIS
(2010) - et al.
Service quality in software-as-a-service: developing the SaaS-Qual measure and examining its role in usage continuance
Journal of MIS
(2012)
Microprocess and macrostructure
Factors affecting bloggers' knowledge sharing: an investigation across gender
Journal of MIS
A partial least squares latent variable modeling approach for measuring interaction effects—results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study
Information Systems Research
The DeLone and McLean model of information systems success: a ten-year update
Journal of MIS
Structural equation models with unobservable variables and measurement errors
Journal of Marketing Research
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Shih-Wei Chou is a professor in the department of MIS (Management of Information Systems) at National Kaohsiung First University of Science of Technology in Taiwan where he teaches knowledge management, software engineering, object-oriented information systems, and management of information systems. He received his doctorate in computer science (CS) from Illinois Institute of Technology, and he holds a master degree in CS from Mississippi State University. Prior to getting his doctorate, he spent two years working in the telecommunication industry. His research interests include outsourcing and service science, IS usage and behavior, and electronic commerce. His work has appeared in the Decision Support Systems, Information Systems Journal, Journal of Information Science, Computers and Education, Journal of Computer-aided Learning, and International Journal of Human-computer Studies among others, and has been presented at the PACIS, and HICSS, and other international conferences.
Chun-Hsiung Chiang is currently a Ph.D. student in MIS of National Kaohsiung First University of Science of Technology. His research interests include outsourcing, IT usage and behavior, electronic commerce, and service science.