中文部分:
1.黃芳銘 (2002)。結構方程模式理論與應用。台北:五南。
2.周子敬 (2004)。以統計檢定力檢測結構方程模式運用在商管研究的正確性。中原學報,32(4),619-633。3.梁定澎、戚樹誠、陳世哲、洪世章、邱志聖、林丙輝、陳振明、李賢得、
盧瑞芬、王泰昌、顧宜錚 (2004)。管理一及管理二學門國際學術期刊分級及排序專案計畫。行政院國家科學委員會專題研究計畫成果報告。
4.戚樹誠、洪世章、廖苑君、陳彥君 (2004)。臺灣管理學術單位在組織與管理領域之國際學術期刊上發表狀況研究。臺灣管理學刊,4(1),1-24。5.陳世哲、李昇暾、林修葳、洪世章、張錦特、葉仕國、盧瑞芬、謝依靜、曹瓊文、吳淑鈴 (2005)。國內管理學專業期刊評比排序之研究。中山管理評論,13(1),15-48。6.周子敬 (2006)。結構方程模式(SEM)-精通LISREL。台北:全華圖書。
7.周子敬 (2006)。國內TSSCI心理學門期刊結構方程模式應用概況及評鑑。
2006年健康與管理學術研討會,新竹:元培科技大學。
8.彭台光、高月慈、林鉦棽 (2006)。管理研究中的共同方法變異:問題本質、影響、測試與補救。管理學報,23(1),77-98。9.吳明隆 (2009)。結構方程模式-AMOS的操作與應用。台北:五南。取自https://www.dropbox.com/s/jj7qsriie0uc07p/%E5%90%B3%E6%98%8E%E9%9A%86AMOS_%E7%B5%84%E5%90%88%E4%BF%A1%E5%BA%A6and%E5%B9%B3%E5%9D%87%E8%AE%8A%E7%95%B0%E6%95%B8%E6%8A%BD%E5%8F%96%E9%87%8F_%E5%9F%B7%E8%A1%8C%E6%AA%94.rar。
10.鄧夢婷 (2010)。以社會影響觀點探討Web 2.0應用服務之持續使用意圖。私立大同大學資訊經營研究所碩士論文。11.賴香菊、黃三益、梁定澎、洪新原、吳祥麟 (2011)。台灣資訊管理學術單位學術期刊論文發狀況。資訊管理學報,18(3),175-196。12.張偉豪 (2011)。SEM論文寫作不求人。台北:鼎茂圖書。
13.邱皓政 (2011)。當PLS遇上SEM:議題與對話。量化研究學刊,3(1),20-53。
14.張偉豪、鄭時宜 (2012)。與結構方程模式共舞-曙光初現。新北市:前程文化。
英文部分:
1.Ajzen, I., &; Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. New Jersy, NJ: Prentice-Hall.
2.Anderson, J., &; Gerbing, D. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
3.Andersson, L. M., &; Bateman, T. S. (1997). Cynicism in the work place: Some causes andeffects. Journal of Organizational Behavior, 18, 449-469.
4.Aulakh, P. S., &; Gencturk, E. F. (2000). International principal–agent relationships– control, governanceand performance. Industrial Marketing Management, 29, 521-538.
5.Avolio, B., Yammarino, F. J., &; Bass, B. M. (1991). Identifying common methods variance with data collected from a single source: An UnresolvedSticky Issue. Journal of Management, 17(3), 571-587.
6.Babin, B. J., Hair, J. F., &; Boles, J. S. (2008). Publishing Research in Marketing Journals Using Structural Equations Modeling. Journal of Marketing Theory and Practice, 16 (4), 279-285.
7.Bagozzi, R. P., &; Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16(2), 74-94.
8.Bagozzi, R. P., &; Yi, Y. (1990). Assessing method variance in multitrait-multimethod matrices: The case of self-reported affect and perceptions at work. Journal of Applied Psychology, 75, 547-560.
9.Bagozzi, R. P., &; Yi, Y. (1991). Multitrait-multimethodmatrices in consumer research. Journal of ConsumerResearch, 17, 426-439.
10.Baron, R. M., &; Kenney, D. A. (1986). The Moderator-Mediator Variable Distinction in SocialPsychological Research: Conceptual, Strategic,and Statistical Considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
11.Bentler, P. M. (1980). Multivariate analysis with latent variables: Causal modeling. Annual Review of Psychology, 31, 419-456.
12.Bentler, P. M., &; Bonett, D. G. (1980). Significance tests and goodness-of-fit in theanalysis of covariance structures. Psychological Bulletin, 88(3), 588-606.
13.Biktimirov, E. N., &; Nilson, L. B. (2003). Mapping your course: designing a graphic syllabus for introductory finance. Journal of Education for Business, 78(6), 308-312.
14.Bollen, K. A., &; Lennox, R. (1991). Coventional wisdom on measurement: Astructural equation perspective. Psychological Bulletin, 110(2), 305-314.
15.Bollen, K. A., &; Long, S. L. (1993). Testing Structural Equation Modeling. Newbury. UK: Sage Publication.
16.Bollen, K. A., &; Stine, R. A. (1992). Bootstrapping goodness-of-fit measures in structural equation models. Sociological Methods and Research, 21, 205-229.
17.Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
18.Boulding, K. E. (1956). General systems theory: The skeleton of science. Management Science, 2(3), 197-208.
19.Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.
20.Browne, M.W., &; Cudeck, R. (1989). Single sample cross-validation indices forovariance structures. Multivariate Behavioral Research, 24(4), 445-455.
21.Byrne, B. M. (2001). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Mahwah, NJ: Erlbaum
22.Campbell, D. T., &; Fiske, D. W. (1959). Convergent and discriminant validation by themultitrait-multi-method Matrix. Psychological Bulletin, 56(2), 81-105.
23.Cardozo, R. N. (1965). An experimental study of customer effort, expectation, and satisfaction. Journal of Marketing Research, 2(3), 244-249.
24.Chen, S. C., Yen, D. C., &; Hwang, M. I. (2012). Factors influencing the continuance intention to the usage of Web 2.0:An empirical study. Computers in Human Behavior, 28, 933-941.
25.Cunningham, E. G., &; Wang, W. C. (2005). Using AMOS graphics to enhance the understanding and communication of multiple regression. IASE / ISI Satellite.
26.Cureton, E. E. (1957). The upper and lower twenty-seven per cent rule. Psychometrika, 22(3), 293-296.
27.D'Agostino, R. B., &; Cureton, E. E. (1975). The 27 percent rule revisited. Educational and Psychological Measurement, 35, 47-50.
28.DeVellis, R. F. (2003). Scale Development: Theory and Applications (2nded.). Thousand Oaks, CA: Sage Publications.
29.Fishbein, M. &; Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
30.Fornell, C. (1984). A second generation of multivariate analysis: Classification of methods and implications for marketing researc, working paper, University of Michigan.
31.Fornell, C., &; Larcker, D. F. (1981). Evaluating Structural Equation Models with UnobservableVariables and Measurement Error. Journal of Marketing Research, 18(1), 39-50.
32.Greene, C. N., &; Organ, D. W. (1973). An evaluation of causal models linking the received role with jobsatisfaction. Administrative Science Quarterly, 18, 95-103.
33.Hair, J. F., Anderson, R. E., Tatham, R. L., &; Black, W. C. (2009). Multivariate Data Analysis (7th ed.). Prentice Hall International: UK.
34.Hair, J. F., Anderson, R. E., Tatham, R. L., &; Black, W. C. (1998). Multivariate Data Analysis(5th ed.). Prentice Hall International: UK.
35.Harris, C. (2008). Ranking the management journals. Journal of Scholarly Publishing, 39, 373-409.
36.Hershberger, S. L. (2003). The growth of structural equation modeling: 1994-2001. Structural Equation Modeling, 10, 35-46.
37.Hoffman, D. L., &; Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60, 50-68.
38.Hoyle, R. H., &; Panter, A. T. (1995). Writing about structural equation models. In R. H. Hoyle (Eds.). Structural equationmodeling: concepts, issues, and applications. Thousand Oaks,CA: Sage.
39.Kelley, T. L. (1939). The selection of upperand lower groups for the validation of testItems. Educational Psychology, 30, 17-24.
40.Kelloway, E. K. (1996). Common practice in structural equation modeling.In C. L. Copper &; I. Robertson (Eds.). International review of industrial and orginazitional psychology (pp. 141-180). Chichester, UK: John Wiley and Sons.
41.Kelloway, E. K. (1998). Using LISREL for structural equation modeling-A researcher’s guide. Thounsand Oaks, CA: Sage Publication.
42.Kemery, E. R., &; Dunlap, W. P. (1986). Partialling factor scores does not control method variance: A replyto podsakoff and todor. Journal of Management, 12(4), 525-544.
43.Kerlinger, F. N., &; Lee, H. B. (1999). Foundations of behavioural research (4th ed.). Fort Worth: Harcourt.
44.Kline, R. B. (2005). Principles and Practice of Structural Equation Modeling: Methodology in the Social Sciences (2rded.)., New York: Guilford Press.
45.Kline, R. B. (1998). Software programs for structural equation models: AMOS, EQS, and LISREL. Journal of Psychoeducational Assessment, 16, 343-364.
46.Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling: Methodology in the Social Sciences (3rded.)., New York:Guilford Press.
47.Mackinnon, D. P., Fritz, M. S., Williams, J., &; Lockwood, C. M. (2007). Distribution of the product confidence limits for the indirect effect: Program PRODCLIN. Behavior Research Methods, 39(3), 384-389.
48.Mallard, A. G. C., &; Lance, C. E. (1998). Development and evaluation of a parent-employee interrole conflict scale. Social Indicators Research, 45, 343-370.
49.Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis withapplications. Biometrika, 57(3), 519-530.
50.Maruyama, G. M. (1997). Basics of structural equation modeling. Thousand Oaks, CA: Sage.
51.McDonald, R. P., &; Ho, M. R. (2002). Principles and practice in reporting structural equation analysis. Psychological Methods, 7, 64-82.
52.McQuitty, S. (2004). Statistical power and structural equation modeling in business research. Journal of Business Research, 57, 175-183.
53.Mueller, R. O. (1997). Structural equation modeling: Back to basics. Structural Equation Modeling, 4, 353-369.
54.Oliver, P., Marwell, G., &; Teixeira, R. (1985). A theory of the critical mass:
Interdependence, group heterogeneity, and the production of collective action. American Journal of Sociology, 91(3), 522-556.
55.Podsakfoff, P. M., MacKenzie, S. B., Lee, J. Y., &; Podsakoff, N. P. (2003). Common method biases in behavioral research:A critical review of the literature andrecommended remedies. Journal of Applied Psychology, 88(5), 879-903.
56.Podsakoff, P. M., &; Organ, D. W. (1986). Self-Reports inOrganizational Research: Problems and Prospects. Journal of Management, 12(4), 531-544.
57.Schriesheim, C. (1979). Thesimilarity of individual directed and group directed leader behavior descriptions. Academy of Management Journal, 22(2), 345-355.
58.Schriesheim, J. F. (1980). The social context of leader-subordinate relations: An investigation of the effects of group cohesion. Journal of Applied Psychology, 65(2), 183-194.
59.Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structuralequation models. Sociological Methodology, 13, 290-312.
60.Soper, D. S. (2009). Sobel Test Calculator for the Significance of Mediation (Online Software), Retrieved from http://www.danielsoper.com/statcalc3.
61.Stafford, T. (2011). Special research commentary series on advanced methodological thinking for quantitative research (Editorial introduction). MIS Quarterly, 35(2), xv-xvi.
62.Steensma, H. K., Tihanyi, L., Lyles, M. A., &; Dhanaraj, C. (2005). The evolving value of foreign partnerships in transitioning economies. Academy of Management Journal, 48(2), 213-235.
63.Steiger, J. H. (2001). Driving fast in reverse:The relationship between software development, theory, and education in structural equation modeling. Journal of the American Statistical Association, 96, 331-338.
64.Stevens, J. P. (1990). Intermediate statistics: A modern approach. Hillsdale, NJ: Erlbaum.
65.Erlbaum Stevens, J. (1996). Applied multivariate statistics for the social sciences. Mahwah, NJ: Lawrence Erlbaum Associates.
66.Tanaka, J. S. (1993). Multifaceted conceptions of fit in structural equation models. In: K. A. Bollen &; J. S. Long, Editors (Eds.).Testing structural equation models (pp. 10-40). Newbury Park, CA: Sage.
67.Thompson, B. (2000). Ten commandments of structural equation modeling. In L. G. Grimm &; P. R. Yarnold (Eds.). Reading and understanding more multivariate statistics (pp. 261-283). Washington, DC: APA.
68.Tomarken, A. J., &; Waller, N. G. (2005). Structural equation modeling: Strengths, limitations, and misconceptions. Annual Review of Clinical Psychology, 1, 31-65.
69.Torkzadeh, G., Koufteros, X., &; Pflughoeft, K. (2003). Confirmatory analysis of computer selfefficacy. Structural Equation Modeling, 10(2), 263-275.
70.Williams, L. J., &; Anderson, S. E. (1994). An alternative approach to method effects by usinglatent-variable models: Applications in organizational research. Journal of Applied Psychology, 79, 323-331.