Exploring the intention to continue using web-based self-service

Journal of Retailing and Consumer Services 24 (2015) 85–93

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Journal of Retailing and Consumer Services journal homepage: www.elsevier.com/locate/jretconser

Exploring the intention to continue using web-based self-service Shu-Mei Tseng Department of Information Management, I-Shou University, No. 1, Sec. 1, Syuecheng Rd., Dashu Township, Kaohsiung County 840, Taiwan

art ic l e i nf o

a b s t r a c t

Article history: Received 29 September 2014 Received in revised form 30 January 2015 Accepted 2 February 2015

The popularization of Internet and the development of cloud computing have not only changed our lifestyles, but have impacted the ways in which enterprises relate with their customers. For example, customers and enterprises can now directly interact through web-based self-services (e.g., Internet banking, online ticketing, online bookstores, and online reservations) that do not require face-to-face interactions. Web-based self-services (WBSS) allow enterprises to proactively initiate contacts with customers and respond to their needs. Customers can also quickly access the services they want online, at any time and place, thus enhancing overall service efficiency. However, a review of the previous literature shows that most related studies have used the Technology Acceptance Model, which examines perceived usefulness, perceived ease of use and attitude toward use, in order to investigate user behaviors when operating a WBSS. In contrast, there are few studies that examine the impact of perceived usefulness and perceived quality features on the continued intention to use a WBSS. Therefore, this study applied the questionnaire method and investigated the relationships among users’ perceived usage characteristics, quality characteristics, satisfaction and continued usage intention with regard to WBSS. Based on the results, specific recommendations are provided for enterprises to enhance the intention to continue using WBSS. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Web-based self-service Continued usage intention Satisfaction Information system success model Technology acceptance model

1. Introduction High labor costs have encouraged service firms to examine delivery options that enable customers to perform certain services for themselves (Dabholkar, 1996). This has been facilitated by the growing use of technology in services, which allows new ways of doing business and transforms the interactions between customers and firms (Ku and Chen, 2013). The development of the Internet and related technologies has revolutionized the service landscape, with many companies using web-based self-services (WBSS) to improve service operations and increase service efficiency for customers (Lin and Hsieh, 2007), allowing customers to access the services that they want at any time and place (Oh Jeong and Baloglu, 2013), leading to higher levels of customer satisfaction (Bitner et al., 2000; Curran and Meuter, 2005). However, even when customers can see the benefits of using WBSS, they may avoid it if they are not comfortable with or ready to use such a technology (Meuter et al., 2003). That is to say, customers apply WBSS will vary according to the personal characteristics of different individuals. Attitudes and behaviors related to the personal use of information technology (IT) have become a common research topic within the field of IT. For example, the Diffusion of Innovations E-mail address: [email protected] http://dx.doi.org/10.1016/j.jretconser.2015.02.001 0969-6989/& 2015 Elsevier Ltd. All rights reserved.

(DOI) approach is used to investigate how users adopt new technologies, concepts and gadgets (Rogers, 1995; Sanni et al., 2013); the Theory of Planned Behavior (TPB), which is used to predict behaviors, attitudes and intentions (Ajzen, 1991, 2002; ZamaniMiandashti et al., 2013); the Technology Acceptance Model (TAM), that explains and predicts the level acceptance of a specific IT (Davis 1989; Persico et al., 2014); and the Information System Success (ISS) model, which investigates the factors influencing user satisfaction with information system (de Lone and McLean, 1992). However, most previous studies were based on the TAM, and investigated the factors which determine the willingness to use IT and actual usage behaviors, in order to predict the levels of user acceptance in relation to a focal technology. There are few studies that simultaneously consider certain features, such as perceived usage and quality in order to investigate users’ intention to continue to use a WBSS (Eriksson and Nilsson, 2007). Therefore, this study is based on the TAM and the ISS model, and investigates user satisfaction and intention to continue using WBSS. Based on the results, it then proposes specific recommendations with regard to enhancing continued usage intention, and can thus serve as a reference for firms aiming to implement a WBSS. The paper is organized in the following manner. The theoretical background and hypotheses section introduces the key constructs of the study and develops the hypotheses. The methodology section explains the procedures used for data collection and validation of the measurement properties of the constructs, and the

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results section presents the results of this empirical study. A discussion of the results, along with the limitations of this work and recommendations for future research, are presented in the discussion section, which is then followed by the conclusion.

2. Theoretical background and hypotheses This study aims to investigate factors that influence users’ continued usage of a WBSS. first, an examination of how user perceptions of the usage and quality characteristics of WBSS influence their satisfaction and continued usage intention was conducted. then, the influence of user satisfaction on continued usage intention was investigated in order to better understand what factors influence this intention, and thus be able to provide specific recommendations for enterprises. the research model Is illustrated in Fig. 1, and each concept and research hypothesis Is elaborated on below. 2.1. Web-based self-services (WBSS) WBSS refer to when customers carry out certain services for themselves using online interfaces operated by the service provider (Rust and Lemon, 2001). Such service, like automated teller machines (ATMs), automated speech systems, an airport selfcheck-in kiosks, have the advantages of saving time and cost, being easy to monitor and use, and not requiring direct service employee involvement, all of which can increase service efficiency and lead to lower operating costs (Orel and Kara, 2014). Many such services are now based on the Internet, such as online shopping, package tracking, and ticket booking (Fitzsimmons, 2003), as well as the actual delivery of products, service support, and consumption of products and services (Liljander et al., 2006; Elliott et al., 2012; Oyedele and Simpson, 2007). 2.2. Web quality de Lone and McLean (1992) posited the Information System Success (ISS) Model, which proposes that information quality and system quality can affect the actual usage behaviors and level of user satisfaction that exist in relation to an information system. In 2003, de Lone and McLean revised the ISS Model by including service quality, a feature that was first proposed by Pitt et al.

(1995), and introducing the concept of net benefits, instead of individual and organizational impacts. In this revised ISS Model, information quality, system quality and service quality can all influence the users’ intention to use an information system, and thus their satisfaction with it. Whilst the use of an information system will impact user satisfaction and net benefits, user satisfaction will then impact the intention to use the system again. Finally, when the net benefits increase, both user satisfaction and the intention to use the system will increase. The ISS model has now been widely applied by many scholars. For example, Seddon and Kiew (1996) conducted a study on information quality and system quality to measure user satisfaction with an accounting information system, while de Lone and McLean (2004) applied the revised ISS Model to an e-commerce context, and examined the critical success factors of e-commerce websites. Kulkarni et al. (2006) and Wu and Wang (2006) applied the ISS model to assess the success of knowledge management systems. In recent years, many scholars have applied the ISS model to websites, and found that the information quality, system quality and service quality of a website are not only factors that affect user satisfaction, but can also be used as part of an index to measure the success of a website (Garrity et al., 2005; Ong et al., 2009). Lee and Yu (2012) used the revised ISS model to measure the project management information system success. Zheng et al. (2013) integrated IS post-adoption research and the ISS model, and proposed a research framework to investigate the continued intention of virtual community users from a quality perspective. 2.3. Technology acceptance model (TAM) Davis (1989), based on attitude theory along with the Theory of Reasoned Action (TRA), proposed by Fishbein and Ajzen (1975), developed the Technology Acceptance Model (TAM). TAM aims to provide a general explanation of the determinants of technology acceptance that is able to explain user behavior across a broad range of end user information technologies. TAM posits that perceived ease of use and perceived usefulness are two antecedents of the behavioral intention to use a technology, which then affects actual use behavior. Perceived usefulness refers to the users’ belief that using a system will allow them to enhance the level of work performance. While perceived ease of use refers to the users’ belief that using a system will not involve any significant efforts or frustrations.

Fig. 1. Research model and hypotheses.

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In addition, the external variables based on perceived usefulness and perceived ease of use can also indirectly influence users’ attitudes and intentions. Simultaneously, external variables will affect users’ beliefs and can help explain their attitudes and intentions. For example, Lin and Lu (2000) proposed that information system quality is the external variable of TAM that can be used to predict individual user acceptance of a website. Their study showed that information system quality has a significant influence on perceived usefulness and perceived ease of use. Saade and Bahli (2005) used TAM to predict the acceptance of online learning, using cognitive absorption as the external variable. The results showed that cognitive absorption has significant influences on perceived usefulness and perceived ease of use among online learners. Hjelt and Björk (2007) conducted a survey to find the key factors affecting the acceptance of an electronic document management system used with a construction project, based on the ISS model. Hsu et al., (2010) that perceived usefulness will be influenced by perceived ease of use, while perceived usefulness and perceived ease of use can also be influenced by other external variables, such as a user’s individual factors, environment, system characteristics, training, and so on. Based on this review of the literature, this study suggests that external variables, such as perceived WBSS quality characteristics (information, system and service qualities), would positively influence the perceived use characteristics. Therefore, this study proposes the following hypothesis: H1: Users’ perceived WBSS quality characteristics have positive influences on the perceived use characteristics.

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(2013) empirically proved that the perceived usefulness of a cloud enterprise resource planning system has a positive influence on user satisfaction. Based on these earlier studies, this work suggests that perceived ease of use and perceived usefulness have positive influences on satisfaction with a WBSS, and thus the following hypothesis is proposed: H2: Users’ perceived WBSS use characteristics have a positive influence on user satisfaction. Information refers to the descriptions of products or services that are provided by a website, and such information should be accurate, current, relevant, complete, and understandable (de Lone and McLean, 2003). Moreover, in order to be able to disseminate such information to users, a website should not only provide a system with the characteristics of reliability, responsiveness, and flexibility, but should also offer an easy to use interface with a quick response time, which will provide a good user experience (Chen and Yen, 2004). Finally, in addition to providing good quality information on a user-friendly system, a website should also be able to offer outstanding service quality in order to increase user satisfaction. This study thus believes that perceived WBSS quality plays an important role in user satisfaction, and, based on the studies reviewed above, that the perceived qualities of the information, system and services related to a WBSS have positive influences on user satisfaction. Hence, the following hypothesis is proposed: H3: Users’ perceived WBSS quality characteristics have a positive influence on user satisfaction. 2.5. WBSS continuous usage intention

2.4. WBSS satisfaction Based on the purposes of the focal technologies from a customer perspective, Meuter et al. (2000) classified the types of WBSS into customer service, transactions, and self-help. Some examples of customer service are package tracking and account information, which provide information and details of commodity flows. Retail purchasing and financial transactions are examples of transactions, and this type of WBSS should enable cash flows and logistics. Finally, distance learning and online information searches are examples of self-help WBSS. Due to the fact that the transactionsWBSS provide services with more content than customer serviceWBSS, user satisfaction with the former should be higher than with the latter. Put differently, transactions-WBSS put more emphases on security, transaction process, information quality, personnel service quality, incentives, and customized service, while customer service-WBSS usually place a greater focus on the information contents and convenience provided by the websites, and thus user satisfaction with transactions-WBSS will be higher than with customer service-WBBS (Barua et al., 2000; Doll and Torkzadeh 1988; Molla and Licker, 2001). Meuter et al. (2000) further posited three main factors that influence satisfaction with self-service technologies (SSTs), which are its ability to solve intensified needs, to provide better service than the alternative, and to do its job. Solving intensified needs means that SSTs can offer greater flexibility with regard to availability and hours of operation, thus providing immediate solutions to customer problems. Better than the alternative means that greater ease-of-use can be obtained through SSTs, by, for example, saving time and money, and gaining access to service at any time and place. Finally, the factor of doing its job refers to SSTs doing what they are supposed to. An empirical study conducted by Devaraj et al. (2002) showed that the customer perceived usefulness of a website has a significant effect on customer satisfaction with it, and thus on continued usage intention. Chiu et al. (2005) also showed that perceived usefulness influences e-learning user satisfaction. Hsu et al.

The phrase “behavioral intention” appears for the first time in the Theory of Reasoned Actions, proposed by Fishbein and Ajzen (1975). They concluded that individual behaviors are determined by individual behavioral intentions, with these intentions affected by subjective norms and attitude. Furthermore, they pointed out that behavioral intentions are one of the determinant factors of actual usage behavior. Similarly, Baker and Crompton (2000) stated that individual behaviors can be predicted by the related intention. Therefore, if it is possible to accurately measure a person’s intentions, then it is possible to predict their actual behaviors. Bhattacherjee (2001) empirically proved that when users can obtain an advantage or assistance through a certain behavior, then they are more willing to continue this behavior, finding that perceived usefulness has a positive influence on continued usage intention. Based on the expectation confirmation theory, Lin et al. (2005) investigated continued usage intention with regard to a website, and found that perceived usefulness and satisfaction were the main factors that determined this. Chiu et al. (2007) also found that the higher the satisfaction among students with regard to using an online learning system, the greater their intentions to continue to do so. Zhao et al. (2008) reported that customer satisfaction is positively linked to the behavioral intention to continue to use a self-service machine. Oh et al. (2013) focused on tourists’ adoption of SSTs at resort hotels, and found that perceived usefulness is positively related to intention to use. In addition, many other studies have provided evidence of the significant positive effect that perceived usefulness has on the behavioral intention to continue using something (e.g., Ku and Chen, 2013; Venkatesh and Morris, 2000; Pikkarainen et al., 2004), and that satisfaction can increase the technology/Internet-related behavioral intentions of customers (Collier and Sherrell, 2010; Liu, 2012; MacDonald and Smith, 2004). Applied WBSS makes it possible for customers to choose the level of service that they want and to interact with the staff to the degree that suits their individual preferences. Therefore, this study proposed that the higher user satisfaction is with a WBSS, the greater the continued

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usage intentions, as stated in the following hypotheses: H4: Users’ perceived WBSS use characteristics have a positive influence on users’ continued usage intention. H5: Users’ perceived WBSS quality characteristics have a positive influence on users’ continued usage intention. H6: WBSS satisfaction has a positive influence on users’ WBSS continued usage intention.

3. Methodology 3.1. Sampling This study applies the revised Information System Success (ISS) model and technology acceptance model (TAM) to explore WBSS satisfaction and continued usage intention. The integrity of research data can be affected if the respondents are reluctant to participate. Therefore, purposive sampling was used in order to ensure that respondents had high willingness to participate in the study, with the questionnaire aimed at individuals who had previously used WBSS. In order to increase the representativeness of the samples, the questionnaire was posted on popular online discussion forums and social network sites. There was a risk that the samples would be biased, as the respondents could include those who had only used a WBSS once or twice, and may never do so again. Therefore, following Bhattacherjee and Premkumar (2004), this study required that the respondents had used a WBSS for at least three months, in order to make sure that they were all continued users. A link to the online questionnaire was sent to the respondents at the beginning of June 2014, with 237 questionnaires returned by the end of July 2014. A total of 177 usable questionnaires were obtained, as 22 respondents had not used a WBSS yet, and 38 had no used one more at least three months. Table 1 shows the demographic breakdown of the sample, including details of their gender, age, marital status, occupation, educational level, frequency of WBSS usage, duration of WBSS usage, and monthly average WBSS usage. 3.2. Measures Instruments A structured questionnaire survey was adopted, because this is the most appropriate way to collect primary data. For the purposes of this study, an in-depth review of the literature on WBSS, continued usage intention, satisfaction, the ISS model, and TAM was conducted in order to clarify the research constructs. Based on the Table 1 Profile of the respondents (n¼ 177). (%) Gender Male Female Marital Status Single Married Others Occupation Student Military and government Others Age ≦19 years old ≧20 and ≦29 years old ≧30 and ≦39 years old ≧40 and ≦49 years old ≧50 years old

52 48 59.3 37.9 2.8 35 38.4 26.6 10.7 34.5 23.2 23.7 7.9

(%) Frequency of WBSS usage 1-9 times 10-39 times More than 40 times Duration of WBSS usage ≧3 months and ≦6 months ≧7 months and ≦14 months ≧15 months The monthly average of WBSS usage 1–5 times 6–10 times 11–20 times More than 20 times Education level Below high/vocational school University Graduate school and above

20.3 34.5 45.2 13.0 11.9 75.1 64.4 17.5 9.6 8.5 12.5 48 39.5

results of this, the various dimensions of each measure were identified to develop the draft questionnaire. Research constructs were operationalized by means of related studies, and these are summarized in Table 2. The final questionnaire includes five parts, on perceived WBSS quality characteristics, perceived WBSS use characteristics, satisfaction, continued usage intention, and the demographic details of the respondents. The language used in the questionnaire was simple Chinese that could be easily understood be the respondents. Some scholars and experts tested the draft questionnaire, which led to minor modifications to the wording, sequence, format and layout, question content and level of difficulty. After making sure that each item did not have any problems, the final questionnaire was sent to all respondents as an e-questionnaire. All of the items were measured on a seven-point Likerttype scale, ranging from “strongly disagree” to “strongly agree.” The final questionnaire items are shown in Table 2.

4. Results Partial Least Squares (PLS) aims to estimate parameters by minimizing the residual variances of all the dependent variables involved. The structural model describes the relationships among the latent variables posited by substantive theory, and the measurement model describes the relationships between the observed and latent variables. Compared to covariance-based SEM techniques, PLS is less stringent with regard to distributional assumptions, measurement scale type, and sample size requirement (Chin, 1998; Fornell and Cha, 1994), making it an appropriate technique for this study. The research model shown in Fig. 2 was thus analyzed using the Smart PLS program. 4.1. The measurement model Due to the fact that unidimensionality cannot be directly measured with PLS, but can be assessed using an exploratory factor analysis (EFA), this study applied EFA to establish whether the measurement items converge in the corresponding factor, whether each item loads with a high coefficient on only one factor, and whether this factor is the same for all items that are supposed to measure it. With regard to the items used to assess the perceived WBSS use characteristics and satisfaction, all met the related criteria, and thus none were removed from the data analysis. As for perceived WBSS quality characteristics, IQ1 for information quality, SYSQ1-3 and SYSQ 5 for system quality, and SQ6 for service quality, were thus omitted as their factor loadings were below 0.6, or the items not being classified into their own dimensions. As for continued usage intention, CUI2 was omitted as factor loading was below 0.6. The factor analysis results are shown in Table 3, and these indicate that the measurement model used in this study achieved good unidimensionality (Gefen and Straub, 2005). A null model was initially specified for the first-order latent variables, in which no structural relationships were included. To assess the reliability of the measures, the Cronbach’s alpha (CA), composite scale reliability (CR), and average variance extracted (AVE) were calculated. Table 3 shows that all the CR and Cronbach’s alphas exceed 0.740 (Nunnally and Bernstein, 1994), while the AVE of all measures exceeds the cut-off value of 0.50 (Chin 1998). Moreover, Table 4 shows that the square root of the AVE exceeds the intercorrelations of the construct with the other constructs in the model, thus showing good discriminant validity (Fornell and Larcker 1981). Additional support for discriminant validity comes from an inspection of the cross-loadings, which were not substantial in magnitude compared with the loadings (Chin 1998; Fornell and Larcker 1981). As shown in Tables 3 and 4,

Table 2 The operational definitions, questionnaire items and references sources. Research variables

Operational definition

Items

Perceived WBSS use characteristics Perceived usefulness The user subjectively perceives that using a WBSS can help PU1. WBSS can help me complete many tasks (e.g., online purchases, package them complete a specific task tracking, ticket reservations, online ordering, online registration, etc.) PU2. WBSS can help me to complete tasks better. PU 3. WBSS can help me complete tasks faster. PU 4. WBSS can help me complete tasks more effectively. Perceived ease of use The user subjectively perceives that the WBSS is easy to use PEU1. WBSS is easy for users to master. PEU 2. WBSS’ user interface suits my habits. PEU 3. WBSS’ user interface is very user-friendly. PEU 4. WBSS is easy to use.

System quality

Service quality

WBSS satisfaction

Continuous usage intention

IQ1. The information contents presented in the WBSS are quite extensive. IQ 2. The information contents presented in the WBSS are laid out in a clear that makes sense. IQ 3. The information contents presented in the WBSS are always updated. IQ 4. The information provided by the WBSS is correct. IQ 5. The WBSS provides the information I need. IQ 6. The WBSS can clearly display the information on the screen. IQ 7. The information contents provided by WBSS are the latest information that I am interested in. The cognitive belief of users towards the quality of the system provided SYSQ1. The layout of the WBSS does not require a lot of time to load. by the WBSS SYSQ 2. WBSS is reliable and system failures seldom occur. SYSQ 3. The different kinds of functions provided in the WBSS are convenient to use. SYSQ 4. WBSS provides layout design and information contents that I can revise and update at anytime. SYSQ 5. WBSS provides the right assistance and explanation in the right situation. SYSQ 6. I can interact with WBSS anytime I want. The cognitive belief of the users towards the additional services proSQ1. I can acquire the assistance that I need through the online cusvided by the WBSS, aside from the basic infrastructure tomer service. SQ 2. The service provided by the WBSS is reliable. SQ 3. WBSS is always happy to help me. SQ 4. WBSS can quickly respond to my demands. SQ 5. The FAQ in the WBSS is useful. SQ 6. WBSS can recommend products and services that fulfill my needs. The overall experience after using WBSS US1. I am satisfied with the information contents provided by the WBSS. US 2. I am satisfied with the WBSS system functions. US 3. I am satisfied with the service quality of WBSS. US 4. Overall, I am satisfied with using WBSS. The intention to continue to use WBSS in the future CUI1. I will keep using WBSS in the future. CUI 2. I will not use WBSS anymore in the future. CUI 3. Even though there is another WBSS, I will keep using the WBSS I am currently using. CUI 4. I am willing to recommend the WBSS I am using to my friends.

Davis (1989), Taylor and Todd (1995).

Davis (1989), Taylor and Todd (1995), Moore and Benbasat (1991).

Iivari and Koskela (1987), McKinney et al. (2002), Wixom and Todd (2005).

de Lone and McLean (1992), Wixom and Todd (2005).

Pitt et al. (1995), Parasuraman et al.(1988), Zhang and Prybutok (2005).

S.-M. Tseng / Journal of Retailing and Consumer Services 24 (2015) 85–93

Perceived WBSS quality characteristics Information quality The cognitive belief of users towards the information service provided by a WBSS

Reference sources

Bhattacherjee (2001).

Bhattacherjee (2001).

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90

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Fig. 2. The structural model.

the internal consistency reliability, indicator reliability, convergent validity, and discriminant validity were all good for the measurement scales used in this study (Urbach and Ahlemann 2010). Table 5 shows the CA, CR R2 and AVE of the measures in the second-order model, with all CA and CR being greater than 0.8, and all AVE greater than 0.5, thus indicating that the measures are reliable. All the loadings of the first-order latent variables on the second-order factors exceed 0.7, which provides support for the second-order model of perceived WBSS use and quality characteristics.

4.2. The structural model The structural model resulting from this analysis is presented in Fig. 2. R2 measures the relationship of a latent variable’s explained variance to its total variance. Values of approximately 0.670 are considered substantial, while those around 0.333 are considered average, and those around 0.190 are considered weak (Chin, 1998). Fig. 2 shows a substantial R2 of 0.767 for WBSS continued usage intention, a substantial level of 0.768 for WBSS satisfaction, and a moderate level of 0.441 for perceived WBSS use

Table 3 Psychometric properties in the null model for first-order constructs (n ¼177). Items

Loading

CA

CR

R2

AVE

PU1 PU2 PU3 PU4 PEU1 PEU2 PEU3 PEU4

0.956 0.936 0.964 0.950 0.897 0.929 0.942 0.931

0.965

0.975

0.850

0.905

0.944

0.959

0.860

0.856

IQ2 IQ3 IQ4 IQ5 IQ6 IQ7 SYSQ4 SYSQ6 SQ1 SQ2 SQ3 SQ4 SQ5

0.885 0.841 0.890 0.867 0.881 0.853 0.888 0.893 0.838 0.886 0.917 0.908 0.861

0.935

0.949

0.870

0.756

0.740

0.885

0.651

0.794

0.929

0.946

0.857

0.779

WBSS satisfaction

US1 US2 US3 US4

0.927 0.954 0.942 0.894

0.947

0.962

0.768

0.864

WBSS continued usage intention

CUI1 CUI3 CUI4

0.810 0.793 0.887

0.78

0.87

0.77

0.69

Construct Perceived WBSS use characteristics

Perceived usefulness

Perceived ease of use

Perceived WBSS quality characteristics

Information quality

System quality Service quality

†α¼ Cronbach’s alpha; CR¼ composite reliability; AVE ¼ average variance extracted

S.-M. Tseng / Journal of Retailing and Consumer Services 24 (2015) 85–93

Table 4 Mean, S.D., and intercorrelations of the latent variables for first-order constructs. Construct

Mean

S.D.

PU

PEU

IQ

SYSQ

PU PEU IQ SYSQ SQ WUS WCUI

6.172 5.590 5.324 5.170 4.985 5.263 5.369

0.975 1.054 1.049 1.102 1.183 1.133 1.013

0.952 0.711 0.568 0.438 0.391 0.493 0.566

0.925 0.691 0.555 0.602 0.643 0.625

0.870 0.660 0.748 0.765 0.759

0.891 0.721 0.707 0.707

SQ

WUS

0.883 0.868 0.771

0.930 0.853

Table 6 Testing the hypotheses in the structural model.

WCUI

0.831

†Square root of the AVE on the diagonal. † PU ¼ Perceived usefulness; PEU ¼ Perceived ease of use; IQ¼ Information quality; SYSQ¼ System quality; SQ ¼Service quality; WUS ¼ WBSS satisfaction; WCUI ¼ WBSS continued usage intention

91

Perceived WBSS use characteristics

WBSS satisfaction

WBSS continued usage intention

Perceived WBSS quality characteristics Perceived WBSS use characteristics WBSS satisfaction

H1:0.664***

H3:0.834***

H5:0.282**

H2:0.062

H4:0.136*

R2 Q2 (CV Redundancy)

0.441** 0.311

H3:0.520***

0.768*** 0.650

0.767*** 0.518

n

p o 0.05; po 0.01; nnn po 0.001. nn

Table 5 Assessing the second-order model characteristics.

of

perceived WBSS use

and quality

5. Discussion 5.1. Summary of results

Perceived WBSS use characteristics

Perceived usefulness Perceived ease of use

Loading

CA

CR

R2

AVE

0.922 0.928

0.953

0.961

0.441

0.753

Loading

CA

CR

AVE

0.932 0.807 0.926

0.953

0.958

0.640

Perceived WBSS quality characteristics

Information quality System quality Service quality n

p o 0.05;

nn

p o 0.01;

nnn

p o 0.001.

characteristics. More specifically, these variables explained 76.7% and 76.8% of the variation in the WBSS continued usage intention and satisfaction constructs, respectively, while the research model accounted for 44.1% of the variation in the perceived WBSS use characteristics construct. Another criterion for predictive validity of the model is to apply the Q2 test (also known as the cross-validated redundancy index) developed by Stone (1974) and Geisser (1975). A blindfolding procedure was performed to obtain the Q2 values. A Q2 value larger than 0 means that the model has predictive relevance (Barroso, Carrión, and Roldán, 2010). As can be seen from the results in Table 6, the proposed model had good predictive abilities. The significance of each path coefficient can also be seen from Fig. 2, showing the results of the standard path analysis, which indicates that perceived WBSS quality characteristics have a very significant and positive influence on perceived WBSS use characteristics, WBSS satisfaction, and WBSS continued usage intention, the standard path coefficients of which are 0.664, 0.834, and0.285, respectively. Perceived WBSS use characteristics do not have an influence on WBSS satisfaction, but do have a significantly positive influence on WBSS continued usage intention, with standard path coefficients of 0.062 and 0.136, respectively. WBSS satisfaction has a very significant positive influence on WBSS continued usage intention, with a standard path coefficient of 0.520. In summary, all the hypotheses are supported by the results of the empirical analysis (the t-values for all path coefficients are statistically significant at the α ¼ 0.05 level), apart from H2.

The results show that perceived WBSS quality characteristics (information quality, system quality, and service quality) has a very significant positive influence on perceived WBSS use characteristics (perceived usefulness and perceived ease of use), with a path coefficient of 0.664. Therefore, in order to enhance users’ perceived WBSS use characteristics, this study has the following suggestions. As for information quality, a WBSS should provide the correct information that customers need and are interested in, as well as clearly display this information on the user interface. As for service quality, a WBSS should quickly respond to customer demands and made users to feel that the WBSS is very kind to help their needs. As for system quality, a WBSS should aim to provide a personalized layout design and provide interactive functions so that users can revise, update and communicate with the WBSS at any time. Furthermore, these unique and interactive characteristics can lead to greater “stickiness”, this encouraging people to continue using the system. This study also suggests that a WBSS should provide a rich and enjoyable user interface so that users can have a pleasurable experience when using the system, as this will enhance both user satisfaction and willingness to continue using the WBSS. The results show that perceived WBSS quality characteristics has a very significant positive influence on WBSS satisfaction and WBSS continued usage intention (the path coefficients are 0.834 and 0.282), as found in several previous studies (Lee and Yu, 2012; Zheng et al., 2013). Hence, in order to enhance WBSS satisfaction and continued usage intention, this study suggests that a WBSS should be able to allow many users to carry out their tasks simultaneously, remaining stable and with a rapid loading time. In addition, when WBSS service failures occur, the system should be able to promptly recover and compensate users for any losses they may have suffered. The results show that perceived WBSS use characteristics do not have a significant influence on WBSS satisfaction (the path coefficient is 0.062). This is because satisfaction in this context is based on all the channels that users encounter when using a WBSS. For example, customers may use the Internet to search for information during the prepurchasing stage, and then visit a WBSS to make a final purchase decision (Eriksson and Nilsson, 2007). Therefore, if satisfaction is context-specific, then multichannel exchange situations must also be considered. In addition, compared with perceived usefulness and perceived ease of use, users may be more concerned about the degree of pleasure when using a WBSS, as well as the issues of transaction reliability, website

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interaction, convenience, and availability of personalized services, as these are the main drivers of satisfaction (Dabholkar, 1996; Globerson and Maggard, 1991; Meuter et al., 2000; Srinivasan et al., 2002; Szymanski and Hise, 2000; Xie et al., 1998). The results show that perceived WBSS use characteristics has a significant, positive influence on WBSS continued usage intention (the path coefficient is 0.136). That is, perceived WBSS use characteristics are a crucial determinant with regard to whether customers will continue their usage of a system or not. If the WBSS is perceived as being useful and easy to use, customers are thus more likely to continue to use it. A WBSS should thus be able to help customers quickly and efficiently complete their tasks, and do so via an easy to understand interface. The results show that WBSS satisfaction has a very significant, positive influence on WBSS continued usage intention (the path coefficient is 0.520). In other words, continued usage intention is mainly based on the level of user satisfaction. When the users are satisfied with a WBSS application, they not only will continue to use the system, but will also share their positive evaluations with their friends and family members, thus attracting more users. Therefore, in order to enhance WBSS continued usage intention, this study suggests that more efforts should be made to improve information quality, system quality, and service quality. In addition, the R2 of WBSS satisfaction is 0.768, which means that 76.8% of the variance can be predicted from the perceived WBSS quality and use characteristics. The R2 of WBSS continued usage intention is 0.767, which means that the model presented in this study can effectively predict and explain the WBSS continued usage intention. Moreover, the results of this work are consistent with those of previous studies in showing that WBSS satisfaction has a very significant, positive influence on WBSS continued usage intention (Bhattarcherjee, 2001; Chiu et al., 2005; Lin et al., 2005; Lin and Hsieh, 2007; Zheng et al., 2013). 5.2. Limitations and future research directions There are three main limitations of this study, as follows. First, while this study applied a purposive sampling method and obtained an adequate number of respondents, the results may include some bias. Therefore, it is suggested that future research should apply a random sampling method to collect more responses and increase the generalizability of the findings. Second, a significant number of the questionnaires that were returned were from people who had not used a WBSS for at least three months, and thus these responses were invalid and not included in the data analysis. In view of this, this study recommends that future researchers should think carefully about the target respondents, and work to ensure that the questionnaires are sent to people who have been using WBSS for a considerable period of time. Third, this study investigated the relationships among the perceived usage and quality features of WBSS, satisfaction and continued usage intention in a Chinese cultural context, subject to a specific set of societal, cultural and linguistic attitudes and behaviors. Therefore, future research could extend this study to other regions of the world.

6. Conclusions In order for a WBSS to succeed, it is essential to understand why consumers are willing to continue using such systems or not. This study thus reviewed the relevant literature to examine the influence of perceived use characteristics and quality characteristics on satisfaction and continued usage intentions with regard to WBSS. Three key results were identified by tests of the hypothesized model. First, the results show that user’s perceived

WBSS quality characteristics are an important driver of WBSS perceived usage characteristics, satisfaction and continued usage intentions. This means that the better the perceived WBSS quality characteristics, the better the usage characteristics, satisfaction and continued usage intentions will be. Second, the results show that perceived WBSS usage characteristics have a significant positive influence on continued usage intentions. Third, WBSS satisfaction also has a significant, positive influence on continued usage intentions. In addition, the greater the level of satisfaction with a WBSS, the more likely users is to both use it again and recommend it to others. The results of this study can serve as a reference when designing WBSS service interfaces and planning related marketing strategies.

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Shu-Mei Tseng is an associate professor at the Department of Information Management at I-Shou University, Taiwan. She received her Ph.D. at the Department of Industrial and Information Management at National Cheng Kung University, Taiwan. Her works have been published in the International Journal of Information Management, the International Journal of Production Economics, the Journal of Knowledge Management, Expert Systems with Applications, Industrial Management and Data Systems, the Journal of Enterprise Information Management, the International Journal of Quality and Service Sciences, the Journal of Retailing and Consumer Services, and the Management Research News. Her current research interests include knowledge management, information technology management, customer relationship management, and service quality.