臺灣博碩士論文加值系統

　　本研究目的為探討使用者在使用LINE旅遊之後所產生確認程度，是否與使用之前的期望有所一致，參照Oliver (1980)提出的期望確認理論(Expectation-Confirmation Theory, ECT)作為研究模型的基礎理念，並且採用Bhattacherjee (2001)在修正期望確認理論(ECT)時，所提出之IS接受後持續使用模型(A Post-Acceptance Model of IS Continuance)來建置研究模型，以及使用DeLone & McLean (1992)提出的資訊系統成功模型(Information Systems Success Model, ISSM)，將知覺績效解釋成「知覺LINE旅遊品質特性(資訊品質、系統品質、服務品質)」。探討使用者在使用LINE旅遊時，所感受到的「確認程度」與「LINE旅遊使用者滿意度」，進一步瞭解使用者在使用LINE旅遊之後的「LINE旅遊持續使用意圖」。
　　本研究統計的有效問卷總共有520份，使用SmartPLS3.2.8套裝軟體所分析出來的結果顯示本研究的所有假說皆得到證實與成立。本研究的發現如下：(1)「知覺LINE旅遊品質特性(資訊品質、系統品質、服務品質)」對「確認程度」具有正向顯著的影響；(2)「知覺LINE旅遊品質特性(資訊品質、系統品質、服務品質)」對「LINE旅遊使用者滿意度」具有正向顯著的影響；(3)「確認程度」對「知覺LINE旅遊使用特性(知覺有用性、知覺易用性)」具有正向顯著的影響；(4)「知覺LINE旅遊使用特性(知覺有用性、知覺易用性)」對「LINE旅遊使用者滿意度」具有正向顯著的影響；(5)「確認程度」對「LINE旅遊使用者滿意度」具有正向顯著的影響；(6)「LINE旅遊使用者滿意度」對「LINE旅遊持續使用意圖」具有正向顯著的影響。

　　The purpose of this study is to explore whether confirmation generated by users after using LINE Travel is consistent with the expectations before use. Refer to Oliver (1980)'s Expectation-Confirmation Theory (ECT) as the basis of the research model, and using Bhattacherjee (2001) in the revision of the Expectation Confirmation Theory (ECT), the proposed IS Post-Acceptance Model of IS Continuance to build the research model. Exploring the "Confirmation" and "LINE Travel User Satisfaction" that users feel when using LINE Travel, to further understand the "LINE Travel Continuous Use Intention" after users use LINE Travel.
　　A total of 520 valid questionnaires were collected in this study. The results of the SmartPLS 3.2.8 software showed that all the hypotheses of this study were confirmed and established. The findings of this study are as follows: (1) "Perceived LINE Travel Quality Characteristics (information quality, system quality, service quality)" has a positive and significant impact on "Confirmation "; (2) "Perceived LINE Travel Quality Characteristics (information quality, system quality, service quality)" has a positive and significant impact on "LINE Travel User Satisfaction"; (3) "Confirmation" has a positive and significant impact on "Perceived LINE Travel Use Characteristics (perceived usefulness, perceived ease of use)"; (4) "Perceived LINE Travel Use Characteristics (perceived usefulness, perceived ease of use)" has a positive and significant impact on "LINE Travel User Satisfaction"; (5) "Confirmation" has a positive and significant impact on "LINE Travel User Satisfaction"; (6) "LINE Travel User Satisfaction" has a positive and significant impact on "LINE Travel Continuous Use Intention".

目錄
摘要 i
ABSTRACT ii
誌謝 iii
目錄 iv
圖目錄 vi
表目錄 vii
壹、緒論 1
1.1 研究背景 1
1.2 研究動機 3
1.3 研究目的 4
1.4 研究範圍 5
1.5 研究流程 5
貳、文獻探討 7
2.1 LINE旅遊 7
2.2 期望確認理論 8
2.3 資訊系統成功模型 12
2.3.1 資訊品質 14
2.3.2 系統品質 17
2.3.3 服務品質 20
2.4 知覺使用特性 23
2.4.1 知覺有用性 23
2.4.2 知覺易用性 23
2.5 使用者滿意度 24
2.6 持續使用意圖 24
參、研究方法 25
3.1 研究模型 25
3.2 研究假說 26
3.2.1 「知覺LINE旅遊品質特性」與「確認程度」之相關假說 26
3.2.2 「知覺LINE旅遊品質特性」與「使用者滿意度」之相關假說 27
3.2.3 「確認程度」與「知覺LINE旅遊使用特性」之相關假說 28
3.2.4 「知覺LINE旅遊使用特性」與「使用者滿意度」之相關假說 29
3.2.5 「確認程度」與「使用者滿意度」之相關假說 30
3.2.6 「使用者滿意度」與「持續使用意圖」之相關假說 31
3.3 研究變數之操作型定義 33
3.3.1 知覺LINE旅遊品質特性(資訊品質) 33
3.3.2 知覺LINE旅遊品質特性(系統品質) 34
3.3.3 知覺LINE旅遊品質特性(服務品質) 35
3.3.4 知覺LINE旅遊使用特性(知覺有用性) 36
3.3.5 知覺LINE旅遊使用特性(知覺易用性) 36
3.3.6 確認程度 37
3.3.7 LINE旅遊使用者滿意度 38
3.3.8 LINE旅遊持續使用意圖 38
3.4 研究設計 39
3.4.1 研究樣本 39
3.4.2 目標系統 39
3.4.3 樣本蒐集 40
3.4.4 資料分析方法與工具 40
3.4.5 問卷設計 40
3.4.6 前測 42
肆、資料分析 45
4.1 敘述性統計分析 45
4.1.1 有效問卷篩選 45
4.1.2 基本資料分析 45
4.1.3 受訪者行為分析 47
4.2 問卷量表之檢驗 49
4.2.1 信度分析 49
4.2.2 效度分析 52
4.3 研究模型驗證 55
4.4 研究假說驗證 56
4.5 中介效果驗證 57
伍、結論與建議 59
5.1 研究結論 59
5.2 研究貢獻 61
5.3 實務上的建議 62
5.4 研究限制 63
5.5 未來研究方向 63
參考文獻 65
附錄、研究問卷 80

圖目錄
圖1.1全球旅遊的銷售額 (資料來源：市場研究機構EMARKETER) 1
圖1.2各類型網站之使用人次 (資料來源：創市際雙週刊第114期) 2
圖1.3本研究流程 (資料來源：本研究整理) 6
圖2.1滿意度認知模型 (資料來源：OLIVER, 1980) 8
圖2.2期望確認理論模型 (資料來源：OLIVER, 1980) 9
圖2.3 IS接受後持續使用模型 (資料來源：BHATTACHERJEE, 2001) 11
圖2.4資訊系統成功模型 (資料來源：DELONE & MCLEAN, 1992) 12
圖2.5更新之後的資訊系統成功模型 (資料來源：DELONE & MCLEAN, 2003) 13
圖3.1研究模型 25
圖4.1研究模型之路徑係數圖 55

表目錄
表2.1「資訊品質」衡量指標 15
表2.2「系統品質」衡量指標 18
表2.3「服務品質」衡量指標 21
表3.1研究假說彙整表 32
表3.2「資訊品質」之操作型衡量問項 34
表3.3「系統品質」之操作型衡量問項 35
表3.4「服務品質」之操作型衡量問項 35
表3.5「知覺有用性」之操作型衡量問項 36
表3.6「知覺易用性」之操作型衡量問項 37
表3.7「確認程度」之操作型衡量問項 38
表3.8「LINE旅遊使用者滿意度」之操作型衡量問項 38
表3.9「LINE旅遊持續使用意圖」之操作型衡量問項 39
表3.10研究變數之操作型定義彙整表 41
表3.11前測問卷之信效度分析表 43
表4.1個人基本資料彙整表 45
表4.2行為分析彙整表 48
表4.3構面之信度彙整表 49
表4.4構面之權重值、平均數、標準差、變異數表 51
表4.5構面之收斂效度彙整表 53
表4.6構面之區別效度彙整表 54
表4.7研究假說驗證彙整表 56
表4.8中介效果驗證彙整表 58

中文文獻
[1] 許麗玲, 何晉滄, & 黃文楷. (2008). 探討 Blog 使用者持續採用行為之研究-以期望確認理論為基礎. 資訊管理學報, 15(4), 1-26.
[2] 許麗玲, 徐村和, 唐嘉偉, & 梁智勇. (2010). Blog 體驗價值對使用者持續使用意向之研究. 資訊管理學報, 17(4), 89-117.
[3] 許麗玲, 陳至柔, & 陳澔輝. (2013). 雲端 ERP 系統服務品質與持續使用意圖之研究. 電子商務學報, 15(2), 195-233.

英文文獻
[4] Abdullah, F., Ward, R., & Ahmed, E. (2016). Investigating the influence of the most commonly used external variables of TAM on students’ Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios. Computers in Human Behavior, 63, 75-90.
[5] Ahn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & management, 44(3), 263-275.
[6] Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11-39). Springer, Berlin, Heidelberg.
[7] Akter, S., D’Ambra, J., & Ray, P. (2010). Service quality of mHealth platforms: development and validation of a hierarchical model using PLS. Electronic Markets, 20(3-4), 209-227.
[8] Albert, R., Jeong, H., & Barabási, A. L. (2000). Error and attack tolerance of complex networks. nature, 406(6794), 378.
[9] Alkhattabi, M., Neagu, D., & Cullen, A. (2010). Information quality framework for e-learning systems. Knowledge Management & E-Learning, 2(4), 340.
[10] Bailey, J. E., & Pearson, S. W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management science, 29(5), 530-545.
[11] Barnes, S. J., & Vidgen, R. T. (2002). An integrative approach to the assessment of e-commerce quality. J. Electron. Commerce Res., 3(3), 114-127.
[12] Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology, 51(6), 1173.
[13] Baroudi, J. J., & Orlikowski, W. J. (1988). A short-form measure of user information satisfaction: a psychometric evaluation and notes on use. Journal of Management Information Systems, 4(4), 44-59.
[14] Barquin, R. C., & Edelstein, H. A. (1997). Building, using, and managing the data warehouse. Prentice-Hall, Inc..
[15] Basak, E., & Calisir, F. (2015). An empirical study on factors affecting continuance intention of using Facebook. Computers in Human Behavior, 48, 181-189.
[16] Belardo, S., Karwan, K. R., & Wallace, W. A. (1982, December). DSS component design through field experimentation: an application to emergency management. In Proceedings of the Third International Conference on Information Systems (Vol. 93).
[17] Bernroider, E. W. (2008). IT governance for enterprise resource planning supported by the DeLone–McLean model of information systems success. Information & Management, 45(5), 257-269.
[18] Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision support systems, 32(2), 201-214.
[19] Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS quarterly, 351-370.
[20] Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS quarterly, 229-254.
[21] Brown, I., & Jayakody, R. (2008). B2C e-commerce success: A test and validation of a revised conceptual model. The Electronic Journal Information Systems Evaluation, 11(3), 167-184.
[22] Cao, M., Zhang, Q., & Seydel, J. (2005). B2C e-commerce web site quality: an empirical examination. Industrial Management & Data Systems, 105(5), 645-661.
[23] Chen, L. Y., & Wu, W. N. (2017). AN EXPLORATION OF THE FACTORS AFFECTING USERS’SATISFACTION WITH MOBILE PAYMENTS. source: International Journal of Computer Science & Information Technology (IJCSIT), 9(3), 97-105.
[24] Cheng, M., & Yuen, A. H. K. (2018). Student continuance of learning management system use: A longitudinal exploration. Computers & Education, 120, 241-253.
[25] Chiou, J. S., & Droge, C. (2006). Service quality, trust, specific asset investment, and expertise: Direct and indirect effects in a satisfaction-loyalty framework. Journal of the academy of marketing science, 34(4), 613-627.
[26] Chiu, C. M., Hsu, M. H., Sun, S. Y., Lin, T. C., & Sun, P. C. (2005). Usability, quality, value and e-learning continuance decisions. Computers & education, 45(4), 399-416.
[27] Chong, A. Y. L. (2013). Mobile commerce usage activities: The roles of demographic and motivation variables. Technological Forecasting and Social Change, 80(7), 1350-1359.
[28] Chong, A. Y. L. (2013). Understanding mobile commerce continuance intentions: an empirical analysis of Chinese consumers. Journal of Computer Information Systems, 53(4), 22-30.
[29] Collier, J. E., & Bienstock, C. C. (2006). Measuring service quality in e-retailing. Journal of service research, 8(3), 260-275.
[30] Cronin Jr, J. J., & Taylor, S. A. (1992). Measuring service quality: a reexamination and extension. The journal of marketing, 55-68.
[31] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
[32] Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.
[33] de Melo Pereira, F. A., Ramos, A. S. M., Gouvêa, M. A., & da Costa, M. F. (2015). Satisfaction and continuous use intention of e-learning service in Brazilian public organizations. Computers in Human Behavior, 46, 139-148.
[34] DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information systems research, 3(1), 60-95.
[35] Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30.
[36] Delone, W. H., & Mclean, E. R. (2004). Measuring e-commerce success: Applying the DeLone & McLean information systems success model. International Journal of electronic commerce, 9(1), 31-47.
[37] Devaraj, S., Fan, M., & Kohli, R. (2002). Antecedents of B2C channel satisfaction and preference: validating e-commerce metrics. Information systems research, 13(3), 316-333.
[38] DeVillis, R. F. (1991). Scale development: Theory and applications.
[39] Dickinger, A., & Stangl, B. (2013). Website performance and behavioral consequences: A formative measurement approach. Journal of Business Research, 66(6), 771-777.
[40] Doll, W. J., & Torkzadeh, G. (1988). The measurement of end-user computing satisfaction. MIS quarterly, 259-274.
[41] Dong, T. P., Cheng, N. C., & Wu, Y. C. J. (2014). A study of the social networking website service in digital content industries: The Facebook case in Taiwan. Computers in Human Behavior, 30, 708-714.
[42] Edvardsson, B. (2005). Service quality: beyond cognitive assessment. Managing Service Quality: An International Journal, 15(2), 127-131.
[43] Eveleth, D. M., Baker-Eveleth, L. J., & Stone, R. W. (2015). Potential applicants’ expectation-confirmation and intentions. Computers in Human Behavior, 44, 183-190.
[44] F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.
[45] Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
[46] Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
[47] Fourie, C., & Lubbe, B. (2006). Determinants of selection of full-service airlines and low-cost carriers—A note on business travellers in South Africa. Journal of Air Transport Management, 12(2), 98-102.
[48] Franz, C. R., & Robey, D. (1986). Organizational context, user involvement, and the usefulness of information systems. Decision sciences, 17(3), 329-356.
[49] Fu, X. M., Zhang, J. H., & Chan, F. T. (2018). Determinants of loyalty to public transit: A model integrating Satisfaction-Loyalty Theory and Expectation-Confirmation Theory. Transportation Research Part A: Policy and Practice, 113, 476-490.
[50] Garcia-Smith, D., & Effken, J. A. (2013). Development and initial evaluation of the clinical information systems success model (CISSM). International journal of medical informatics, 82(6), 539-552.
[51] Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS quarterly, 213-236.
[52] Gorla, N., Somers, T. M., & Wong, B. (2010). Organizational impact of system quality, information quality, and service quality. The Journal of Strategic Information Systems, 19(3), 207-228.
[53] Gwebu, K. L., Wang, J., & Guo, L. (2014). Continued usage intention of multifunctional friend networking services: A test of a dual-process model using Facebook. Decision Support Systems, 67, 66-77.
[54] Halilovic, S., & Cicic, M. (2013). Antecedents of information systems user behaviour–extended expectation-confirmation model. Behaviour & Information Technology, 32(4), 359-370.
[55] Hamilton, S., & Chervany, N. L. (1981). Evaluating information system effectiveness-Part I: Comparing evaluation approaches. MIS quarterly, 55-69.
[56] Howard, J. A., & Sheth, J. N. (1969). The theory of buyer behavior. New York, 63.
[57] Hsiao, C. C., & Chiou, J. S. (2012). The impact of online community position on online game continuance intention: Do game knowledge and community size matter?. Information & management, 49(6), 292-300.
[58] Hsiao, C. H., Chang, J. J., & Tang, K. Y. (2016). Exploring the influential factors in continuance usage of mobile social Apps: Satisfaction, habit, and customer value perspectives. Telematics and Informatics, 33(2), 342-355.
[59] Hsu, C. L., Chang, K. C., & Chen, M. C. (2012). The impact of website quality on customer satisfaction and purchase intention: perceived playfulness and perceived flow as mediators. Information Systems and e-Business Management, 10(4), 549-570.
[60] Hsu, M. H., Chiu, C. M., & Ju, T. L. (2004). Determinants of continued use of the WWW: an integration of two theoretical models. Industrial management & data systems, 104(9), 766-775.
[61] Hsu, P. F., Yen, H. R., & Chung, J. C. (2015). Assessing ERP post-implementation success at the individual level: Revisiting the role of service quality. Information & Management, 52(8), 925-942.
[62] Iivari, J., & Ervasti, I. (1994). User information satisfaction: IS implementability and. Information & Management, 27, 205-220.
[63] Iivari, J., & Koskela, E. (1987). The PIOCO model for information systems design. Mis Quarterly, 401-419.
[64] Ives, B., Olson, M. H., & Baroudi, J. J. (1983). The measurement of user information satisfaction. Communications of the ACM, 26(10), 785-793.
[65] Joo, Y. J., Lim, K. Y., & Kim, E. K. (2011). Online university students' satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & education, 57(2), 1654-1664.
[66] Joo, Y. J., So, H. J., & Kim, N. H. (2018). Examination of relationships among students' self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122, 260-272.
[67] Kettinger, W. J., & Lee, C. C. (1994). Perceived service quality and user satisfaction with the information services function. Decision sciences, 25(5‐6), 737-766.
[68] Kim, S. E., Lee, K. Y., Shin, S. I., & Yang, S. B. (2017). Effects of tourism information quality in social media on destination image formation: The case of Sina Weibo. Information & Management, 54(6), 687-702.
[69] Kotler, P., & Armstrong, G. (2013). Principles of Marketing (16th Global Edition).
[70] Kuo, R. Z. (2018). EMRS Adoption: Exploring the effects of information security management awareness and perceived service quality. Health Policy and Technology, 7(4), 365-373.
[71] Larcker, D. F., & Lessig, V. P. (1980). Perceived usefulness of information: A psychometric examination. Decision Sciences, 11(1), 121-134.
[72] LaTour, S. A., & Peat, N. C. (1979). Conceptual and methodological issues in consumer satisfaction research. ACR North American Advances.
[73] Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers & Education, 54(2), 506-516.
[74] Lee, Y., & Kozar, K. A. (2006). Investigating the effect of website quality on e-business success: An analytic hierarchy process (AHP) approach. Decision support systems, 42(3), 1383-1401.
[75] Lee, Y., & Kwon, O. (2011). Intimacy, familiarity and continuance intention: An extended expectation–confirmation model in web-based services. Electronic Commerce Research and Applications, 10(3), 342-357.
[76] Lin, H. F. (2007). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications, 6(4), 433-442.
[77] Lin, H. F. (2010). An application of fuzzy AHP for evaluating course website quality. Computers & Education, 54(4), 877-888.
[78] Lin, J. C. C., & Lu, H. (2000). Towards an understanding of the behavioural intention to use a web site. International journal of information management, 20(3), 197-208.
[79] Lin, W. S., & Wang, C. H. (2012). Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Computers & Education, 58(1), 88-99.
[80] Liu, C., & Arnett, K. P. (2000). Exploring the factors associated with Web site success in the context of electronic commerce. Information & management, 38(1), 23-33.
[81] Loiacono, R. (2000). U.S. Patent No. 6,042,384. Washington, DC: U.S. Patent and Trademark Office.
[82] Lovelock, C. H., & Wright, L. K. (2007). Manajemen pemasaran jasa. Cetakan II. Indeks. Jakarta.
[83] Mahmood, M. A. (1987). System development methods-a comparative investigation. MIS Quarterly, 293-311.
[84] Mason, R. O. (1978). Measuring information output: A communication systems approach. Information & management, 1(4), 219-234.
[85] McClure, M. W. (2016). Investing in MOOCs:“Frenemy” risk and information quality. In Globalisation and Higher Education Reforms (pp. 77-94). Springer, Cham.
[86] McGill, T., Hobbs, V., & Klobas, J. (2003). User developed applications and information systems success: A test of DeLone and McLean's model. Information Resources Management Journal (IRMJ), 16(1), 24-45.
[87] McKinney, V., Yoon, K., & Zahedi, F. M. (2002). The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Information systems research, 13(3), 296-315.
[88] McKnight, D. H., Lankton, N. K., Nicolaou, A., & Price, J. (2017). Distinguishing the effects of B2B information quality, system quality, and service outcome quality on trust and distrust. The Journal of Strategic Information Systems, 26(2), 118-141.
[89] Miller, J., & Doyle, B. A. (1987). Measuring the effectiveness of computer-based information systems in the financial services sector. MIS quarterly, 107-124.
[90] Mouakket, S. (2015). Factors influencing continuance intention to use social network sites: The Facebook case. Computers in Human Behavior, 53, 102-110.
[91] Mouakket, S. (2018). The role of personality traits in motivating users' continuance intention towards Facebook: Gender differences. The Journal of High Technology Management Research, 29(1), 124-140.
[92] Nisar, T. M., & Prabhakar, G. (2017). What factors determine e-satisfaction and consumer spending in e-commerce retailing?. Journal of Retailing and Consumer Services, 39, 135-144.
[93] Noh, M. J., & Lee, K. T. (2016). An analysis of the relationship between quality and user acceptance in smartphone apps. Information Systems and e-Business Management, 14(2), 273-291.
[94] Oghuma, A. P., Libaque-Saenz, C. F., Wong, S. F., & Chang, Y. (2016). An expectation-confirmation model of continuance intention to use mobile instant messaging. Telematics and Informatics, 33(1), 34-47.
[95] Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of marketing research, 460-469.
[96] Oliver, R. L., & Linda, G. (1981). Effect of satisfaction and its antecedents on consumer preference and intention. ACR North American Advances.
[97] Olsen, S. O. (2002). Comparative evaluation and the relationship between quality, satisfaction, and repurchase loyalty. Journal of the academy of marketing science, 30(3), 240-249.
[98] Olson, M. H., & Lucas Jr, H. C. (1982). The impact of office automation on the organization: some implications for research and practice. Communications of the ACM, 25(11), 838-847.
[99] O'Reilly III, C. A. (1982). Variations in decision makers' use of information sources: The impact of quality and accessibility of information. Academy of Management journal, 25(4), 756-771.
[100] Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1991). Refinement and reassessment of the SERVQUAL scale. Journal of retailing, 67(4), 420.
[101] Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. the Journal of Marketing, 41-50.
[102] Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). Servqual: A multiple-item scale for measuring consumer perc. Journal of retailing, 64(1), 12.
[103] Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). ES-QUAL: A multiple-item scale for assessing electronic service quality. Journal of service research, 7(3), 213-233.
[104] Park, J., Kim, J., & Koh, J. (2010). Determinants of continuous usage intention in web analytics services. Electronic Commerce Research and Applications, 9(1), 61-72.
[105] Pattanagul, K., Chantatub, W., & Chaopanon, W. (2012). A Framework for Identifying and Managing Information Quality Metrics of Corporate Performance Management System. Journal of Modern Accounting and Auditing, 8(2), 185.
[106] Patterson, P. G., Johnson, L. W., & Spreng, R. A. (1996). Modeling the determinants of customer satisfaction for business-to-business professional services. Journal of the academy of marketing science, 25(1), 4-17.
[107] Petter, S., & Fruhling, A. (2011). Evaluating the success of an emergency response medical information system. International journal of medical informatics, 80(7), 480-489.
[108] Pitt, L. F., Watson, R. T., & Kavan, C. B. (1995). Service quality: a measure of information systems effectiveness. MIS quarterly, 173-187.
[109] Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information systems research, 13(1), 50-69.
[110] Regan, W. J. (1963). The service revolution. The Journal of Marketing, 57-62.
[111] Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of human-computer studies, 64(8), 683-696.
[112] Saarinen, T. (1996). An expanded instrument for evaluating information system success. Information & management, 31(2), 103-118.
[113] Saeed, K. A., Hwang, Y., & Mun, Y. Y. (2003). Toward an integrative framework for online consumer behavior research: a meta-analysis approach. Journal of Organizational and End User Computing (JOEUC), 15(4), 1-26.
[114] Saha, P., Nath, A. K., & Salehi-Sangari, E. (2012). Evaluation of government e-tax websites: an information quality and system quality approach. Transforming Government: People, Process and Policy, 6(3), 300-321.
[115] San Martín, S., López-Catalán, B., & Ramón-Jerónimo, M. A. (2012). Factors determining firms' perceived performance of mobile commerce. Industrial Management & Data Systems, 112(6), 946-963.
[116] Sarrab, M., Elbasir, M., & Alnaeli, S. (2016). Towards a quality model of technical aspects for mobile learning services: An empirical investigation. Computers in Human Behavior, 55, 100-112.
[117] Scott, M., DeLone, W. H., & Golden, W. (2011, June). IT quality and egovernment net benefits: a citizen perspective. In ECIS (p. 87).
[118] Sebetci, Ö., & Çetin, M. (2016). Developing, applying and measuring an e-Prescription Information Systems Success Model from the persperctives of physicians and pharmacists. Health Policy and Technology, 5(1), 84-93.
[119] Seddon, P., & Kiew, M. Y. (1996). A partial test and development of DeLone and McLean's model of IS success. Australasian Journal of Information Systems, 4(1).
[120] Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information systems research, 8(3), 240-253.
[121] Shannon, C. E., & Weaver, W. (1949). Themathematical theory of communication. Urbana: University of Illinois Press, 5.
[122] Sharma, S. K., & Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation. International Journal of Information Management, 44, 65-75.
[123] Sheikhtaheri, A., Kimiafar, K., & Sarbaz, M. (2014). Evaluation of system quality of hospital information system: a case study on nurses' experiences. In MIE (pp. 960-964).
[124] Siegmueller, C., & Narasimhaiah, R. (2010). Fatal 2, 4-dinitrophenol poisoning… coming to a hospital near you. Emergency Medicine Journal, emj-2009.
[125] Sobihah, M., Mohamad, M., Ali, N. A. M., & Ismail, W. Z. W. (2015). E-commerce service quality on customer satisfaction, belief and loyalty: a proposal. Mediterranean Journal of Social Sciences, 6(2), 260.
[126] Sohn, S. (2017). A contextual perspective on consumers' perceived usefulness: The case of mobile online shopping. Journal of Retailing and Consumer Services, 38, 22-33.
[127] Song, J., Kim, J., & Cho, K. (2018). Understanding users’ continuance intentions to use smart-connected sports products. Sport Management Review, 21(5), 477-490.
[128] Spreng, R. A., MacKenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the determinants of consumer satisfaction. Journal of marketing, 60(3), 15-32.
[129] Srinivasan, A. (1985). Alternative measures of system effectiveness: associations and implications. MIS quarterly, 243-253.
[130] Stefanovic, D., Marjanovic, U., Delić, M., Culibrk, D., & Lalic, B. (2016). Assessing the success of e-government systems: An employee perspective. Information & Management, 53(6), 717-726.
[131] Stickdorn, M. S., & Schneider, J. (2014). J.(2012) This is Service Design Thinking: Basics, Tools, Cases.
[132] Stone, R. W., & Baker-Eveleth, L. (2013). Students’ expectation, confirmation, and continuance intention to use electronic textbooks. Computers in Human Behavior, 29(3), 984-990.
[133] Tam, C., & Oliveira, T. (2016). Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective. Computers in Human Behavior, 61, 233-244.
[134] Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799-810.
[135] Udo, G. J., Bagchi, K. K., & Kirs, P. J. (2010). An assessment of customers’e-service quality perception, satisfaction and intention. International Journal of Information Management, 30(6), 481-492.
[136] Van der Heijden, H. (2003). Factors influencing the usage of websites: the case of a generic portal in The Netherlands. Information & management, 40(6), 541-549.
[137] Volonino, L., & Robinson, S. (1991). EIS experiences at Marine Midland Bank. Journal of Information Technology Management, 2(2), 33-38.
[138] Wang, Y. S., & Liao, Y. W. (2007). The conceptualization and measurement of m-commerce user satisfaction. Computers in human behavior, 23(1), 381-398.
[139] Wang, Y. S., & Liao, Y. W. (2008). Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Government Information Quarterly, 25(4), 717-733.
[140] Weng, G. S., Zailani, S., Iranmanesh, M., & Hyun, S. S. (2017). Mobile taxi booking application service’s continuance usage intention by users. Transportation Research Part D: Transport and Environment, 57, 207-216.
[141] Westbrook, R. A., & Reilly, M. D. (1983). Value-percept disparity: an alternative to the disconfirmation of expectations theory of consumer satisfaction. ACR North American Advances.
[142] Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information systems research, 16(1), 85-102.
[143] Wolfinbarger, M., & Gilly, M. C. (2003). eTailQ: dimensionalizing, measuring and predicting etail quality. Journal of retailing, 79(3), 183-198.
[144] Wu, J. H., & Wang, Y. M. (2006). Measuring KMS success: A respecification of the DeLone and McLean's model. Information & Management, 43(6), 728-739.
[145] Xu, J. D., Benbasat, I., & Cenfetelli, R. T. (2013). Integrating service quality with system and information quality: An empirical test in the e-service context. Mis Quarterly, 37(3).
[146] Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. The Journal of marketing, 2-22.
[147] Zeithaml, V. A., Parasuraman, A., & Malhotra, A. (2002). Service quality delivery through web sites: a critical review of extant knowledge. Journal of the academy of marketing science, 30(4), 362.
[148] Zeithaml, V.A. and Bitner, M.J. (2003) Services Marketing: Integrating Customer Focus across the Firm. 3rd Edition, Irwin McGraw-Hill, New York.
[149] Zha, X., Yang, H., Yan, Y., Liu, K., & Huang, C. (2018). Exploring the effect of social media information quality, source credibility and reputation on informational fit-to-task: Moderating role of focused immersion. Computers in Human Behavior, 79, 227-237.
[150] Zhang, M., Liu, Y., Yan, W., & Zhang, Y. (2017). Users’ continuance intention of virtual learning community services: the moderating role of usage experience. Interactive Learning Environments, 25(6), 685-703.
[151] Zheng, Y., Zhao, K., & Stylianou, A. (2013). The impacts of information quality and system quality on users' continuance intention in information-exchange virtual communities: An empirical investigation. Decision Support Systems, 56, 513-524.
[152] Zmud, R. W. (1978). An empirical investigation of the dimensionality of the concept of information. Decision sciences, 9(2), 187-195.
[153] Zviran, M., Pliskin, N., & Levin, R. (2005). Measuring user satisfaction and perceived usefulness in the ERP context. Journal of computer information systems, 45(3), 43-52.