Information Technology and Management

, Volume 18, Issue 1, pp 55–82 | Cite as

Leveraging business-IT alignment through enterprise architecture—an empirical study to estimate the extents

  • Morteza Alaeddini
  • Hamed Asgari
  • Arash Gharibi
  • Mona Rashidi Rad


Achieving business-IT alignment (BITA) as a long-term and appraising management issue can be accomplished in a few ways, enterprise architecture (EA) being one of them. This paper attempts to give a critical understanding of the effects of performing EA on different aspects of BITA maturity through a global survey. A total of 236 respondents from 60 countries, a relatively large response for a survey, were selected. The main purpose of the research is to examine these impacts and to identify directions for innovative practices in the future, the unique contributions of this work. A questionnaire designed on the Luftman’s maturity model as well as various other statistical methods, including PLS path modeling, Wilcoxon matched-pairs signed-ranks test and Mann–Whitney U test, are applied to understand how the EA can deliver benefits. The implications of our findings in this study as well as its limitations are discussed from different viewpoints to enable both academics and practitioners to detect the flaws in the existing EA frameworks and propose improvements.


Enterprise architecture (EA) Business-IT alignment (BITA) Luftman’s maturity model Partial least squares (PLS) 



Special thanks are due to Prof. John Zachman for his valuable support and participation in this study. The authors also express their appreciation to Jan van Bon, Manager of LinkedIn group “TOGAF for Architecture,” for his time and assistance in the survey. The authors extend their thanks also to Reza Kaviani, Senior Manager at DIRECTV, for his feedback and pertinent help throughout this work. Further, the authors sincerely thank the three anonymous reviewers for their valuable comments.


  1. 1.
    Craig D, Kanakamedala K, Tinaikar R (2007) The next frontier in IT strategy: a McKinsey Survey. McKinsey Quarterly, SeattleGoogle Scholar
  2. 2.
    McGee MK (2008) IT and business alignment remains CIO’s top concern. InformationWeekGoogle Scholar
  3. 3.
    Reich BH, Benbasat I (2000) Factors that influence the social dimension of alignment between business and information technology objectives. MIS Q 24(1):81–113CrossRefGoogle Scholar
  4. 4.
    Valentine V (2011) IT management concerns changing rapidly. Information ManagementGoogle Scholar
  5. 5.
    Alaeddini M, Salekfard S (2013) Investigating the role of an enterprise architecture project in the business-IT alignment in Iran. Inf Syst Front 15(1):67–88CrossRefGoogle Scholar
  6. 6.
    Chen HM (2008) Towards service engineering: service orientation and business-IT alignment. In: 41st Hawaii international conference on system sciences (HICSS), Waikoloa, HI, p 114Google Scholar
  7. 7.
    Chen HM, Kazman R, Garg A (2005) BITAM: an engineering-principled method for managing misalignments between business and IT architectures. Sci Comput Program 57(1):5–26CrossRefGoogle Scholar
  8. 8.
    Gregor S, Hart D (2007) Enterprise architectures: enablers of business strategy and IS/IT alignment in government. Inf Technol People 20(2):96–120CrossRefGoogle Scholar
  9. 9.
    Lagerström R, Sommestad T, Buschle M, Ekstedt M (2011) Enterprise architecture management’s impact on information technology success. In: 44th Hawaii international conference on system sciences (HICSS), Kauai, HI, pp 1–10Google Scholar
  10. 10.
    Ross JW (2003) Creating a strategic IT architecture competency: learning in stages. MIS Q Exec 2(1):31–43Google Scholar
  11. 11.
    Versteeg G, Bouwman H (2006) Business architecture: a new paradigm to relate business strategy to ICT. Inf Syst Front 8(2):91–102CrossRefGoogle Scholar
  12. 12.
    Wegmann A, Balabko P, Le LS, Regev G, Rychkova I (2005) A method and tool for business-IT alignment in enterprise architecture. In: The 17th international conference on advanced information systems engineering (CAiSE), Porto, PortugalGoogle Scholar
  13. 13.
    Wilkinson M (2006) Designing an ‘adaptive’ enterprise. BT Technol J 24(4):81–92CrossRefGoogle Scholar
  14. 14.
    Bhattacharjya J, Chang V (2006) Evolving IT governance practices for IT and business alignment—a case study in an Australian Institution. In: 4th Annual conference on information science, technology and management (CISTM), Chandigarh, IndiaGoogle Scholar
  15. 15.
    Edwards BA (2000) Chief executive officer behavior: the catalyst for strategic alignment. Int J Value-Based Manag 13(1):47–54CrossRefGoogle Scholar
  16. 16.
    Vitantonio GD, Legh-Smith J, Millar W, Wilkinson M (2006) Meeting business objectives through adaptive information and communications technology. BT Technol J 24(4):113–120CrossRefGoogle Scholar
  17. 17.
    Henderson JC, Venkatraman N (1993) Strategic alignment: leveraging information technology for transforming organizations. IBM Syst J 32(1):472–484CrossRefGoogle Scholar
  18. 18.
    Luftman J, Lewis PR, Oldach SH (1993) Transforming the enterprise: the alignment of business and information technology strategies. IBM Syst J 32(1):198–221CrossRefGoogle Scholar
  19. 19.
    Rathnam RG, Johnsen J, Wen HJ (2005) Alignment of business strategy and IT strategy: a case study of a fortune 50 financial services company. J Comput Inf Syst 45(2):1–9Google Scholar
  20. 20.
    Silvius AJG (2008) The impact of national cultures on business & IT alignment. Commun IIMA 8(2):11–22Google Scholar
  21. 21.
    Wegmann A, Regev G, Rychkova I, Lê LS, de la Cruz JD (2007) Business and IT alignment with SEAM for enterprise architecture. In: 11th IEEE international enterprise distributed object computing conference (EDOC), Annapolis, MD, pp 111–121Google Scholar
  22. 22.
    Kang D, Lee J, Kim K (2010) Alignment of business enterprise architectures using fact-based ontologies. Expert Syst Appl 37(4):3274–3283CrossRefGoogle Scholar
  23. 23.
    van der Raadt B, Bonnet M, Schouten S, van Vliet H (2010) The relation between EA effectiveness and stakeholder satisfaction. J Syst Softw 83(10):1954–1969CrossRefGoogle Scholar
  24. 24.
    Elhari K, Bounabat B (2011) Platform for assessing strategic alignment using enterprise architecture: application to e-government process assessment. Int J Comput Sci Issues 8(1):1–8Google Scholar
  25. 25.
    Clark T, Barn B, Oussena S (2012) A method for enterprise architecture alignment. In: Proper E, Gaaloul K, Harmsen F, Wrycza S (eds) Practice-driven research on enterprise transformation, vol 120. Lecture notes in business information processing. Springer, Berlin, pp 48–76Google Scholar
  26. 26.
    Fritscher B, Pigneur Y (2011) Business IT alignment from Business model to enterprise architecture. In: Advanced information systems engineering workshops. Springer, Berlin, pp 4–15Google Scholar
  27. 27.
    Luftman J (2000) Assessing business-IT alignment Maturity. Commun Assoc Inf Syst 4(14):1–50Google Scholar
  28. 28.
    Derzsi Z, Gordijn J (2005) Value-based business-ICT alignment: a case study of the mobile industry. In: 12th research symposium on emerging electronic markets (RSEEM), Amsterdam, Netherlands, pp 83–95Google Scholar
  29. 29.
    Tapia RS (2007) Developing a maturity model for IT alignment in a cross-organizational environment. In: 2nd Dutch/Belgian conference on enterprise information systems (EIS), Groningen, NetherlandsGoogle Scholar
  30. 30.
    Shpilberg D, Berez S, Puryear R, Shah S (2007) Avoiding the alignment trap in IT. MIT Sloan Manag Rev 49(1):50–59Google Scholar
  31. 31.
    Cumps B, Viaene S, Dedene G, Vandenbulck J (2006) An empirical study on business/ICT alignment in European organisations. In: 39th Hawaii international conference on system sciences (HICSS), HI, p 195aGoogle Scholar
  32. 32.
    Camponovo G, Pigneur Y (2004) Information systems alignment in uncertain environments. In: IFIP international conference on decision support systems (DSS), Prato, Italy, pp 134–146Google Scholar
  33. 33.
    Baïna S, Ansias PY, Petit M, Castiaux A (2008) Strategic business/IT alignment using goal models. In: 3rd international workshop on business/IT alignment and interoperability (BUSITAL), Montpellier, France, pp 31–43Google Scholar
  34. 34.
    Bleistein SJ, Cox K, Verner J, Phalp KT (2006) B-SCP: a requirements analysis framework for validating strategic alignment of organizational IT based on strategy, context, and process. Inf Softw Technol 48(9):846–868CrossRefGoogle Scholar
  35. 35.
    Carvalho G, Sousa P (2008) Business and information systems MisAlignment model (BISMAM): an holistic model leveraged on misalignment and medical sciences approaches. In: 3rd international workshop on business/IT alignment and interoperability (BUSITAL), Montpellier, France, pp 104–119Google Scholar
  36. 36.
    Weiss JW, Anderson D (2004) Aligning technology and business strategy: issues & frameworks, a field study of 15 companies. In: 37th Hawaii international conference on system sciences (HICSS), Big Island, HI, pp 1–10Google Scholar
  37. 37.
    Leonard J, Seddon P (2012) A meta-model of alignment. Commun Assoc Inf Syst 31(1):231–259Google Scholar
  38. 38.
    Clarke R (1994) The path of development of strategic information systems theory.
  39. 39.
    Wegmann A (2002) The systemic enterprise architecture methodology business and IT alignment for competitiveness. In: EPFL, Lausanne, Switzerland, pp 1–8Google Scholar
  40. 40.
    Yetton PW, Johnston KD, Craig JF (1994) Computer-aided architects: a case study of it and strategic change. Sloan Manag Rev 35(4):57–67Google Scholar
  41. 41.
    van Eck P, Blanken H, Wieringa R (2004) Project GRAAL: towards operational architecture alignment. Int J Coop Inf Syst 13(3):235–255CrossRefGoogle Scholar
  42. 42.
    Baker J, Jones D, Cao Q, Song J (2011) Conceptualizing the dynamic strategic alignment competency. J Assoc Inf Syst 12(4):299–322Google Scholar
  43. 43.
    Chang HL, Hsiao HE, Lee YJ, Chang J (2009) Assessing IT-business alignment in service-oriented enterprises. In: PACIS, p 40Google Scholar
  44. 44.
    Gutierrez A, Orozco J, Serrano A (2006) Using tactical and operational factors to assess strategic alignment: an SME study. In: European and mediterranean conference on information systems (EMCIS), Costa Blanca, Alicante, Spain, pp 1–10Google Scholar
  45. 45.
    Papp R (2001) Introduction to strategic alignment. In: Papp R (ed) Strategic information technology: opportunities for competitive advantage. illustrated edn. IGI Glob, Hershey, PA, pp 1–24Google Scholar
  46. 46.
    Silva E, Plazaola L, Ekstedt M (2006) Strategic business and IT alignment: a prioritized theory diagram. In: PICMET, Istanbul, Turkey, pp 1–10Google Scholar
  47. 47.
    Tapia RS, Daneva M, van Eck P (2007) Validating adequacy and suitability of business-IT alignment criteria in an inter-enterprise maturity model. In: 11th IEEE international conference on enterprise distributed object computing (EDOC), Annapolis, MD, pp 202–213Google Scholar
  48. 48.
    Wang N, Xue Y, Liang H, Ge S (2011) The road to business-it alignment: a case study of two Chinese companies. Commun Assoc Inf Syst 28(1):416–436Google Scholar
  49. 49.
    Luftman J, Papp R, Brier T (1999) Enablers and Inhibitors of business-IT alignment. Commun Assoc Inf Syst 11(3):1–33Google Scholar
  50. 50.
    Luftman J (1996) Competing in the information age: strategic alignment in practice. Oxford University Press, New YorkGoogle Scholar
  51. 51.
    Weill P, Ross JW (2004) IT governance—how top performers manage IT decision rights for superior results. Harvard Business School Press, BostonGoogle Scholar
  52. 52.
    Weill P, Ross JW (2004) IT governance on one page. Massachusetts, CambridgeGoogle Scholar
  53. 53.
    Team CP (2010) CMMI® for development, version 1.3, Improving processes for developing better products and services. no CMU/SEI-2010-TR-033 Software Engineering InstituteGoogle Scholar
  54. 54.
    Giachetti RE (2010) Design of enterprise systems, theory, architecture, and methods. CRC Press, Boca RatonGoogle Scholar
  55. 55.
    Jahani B, Seyyed Javadein SR, Jafari HA (2010) Measurement of enterprise architecture readiness within organizations. Business Strategy Series 11(3):177–191CrossRefGoogle Scholar
  56. 56.
    Shah H, Kourdi ME (2007) Frameworks for enterprise architecture. IT Prof 9(5):36–41Google Scholar
  57. 57.
    Zachman JA (2002) The Zachman framework™ for enterprise architecture. Zachman International:79Google Scholar
  58. 58.
    CIO-Council (2001) A practical guide to federal enterprise architecture, version 1.0Google Scholar
  59. 59.
    Spewak S, Hill SC (1995) Enterprise architecture planning: developing a blueprint for data, applications, and technology. Wiley, New York CityGoogle Scholar
  60. 60.
    ITGI (2007) Control objectives for information and related technology (COBIT), Ver 4.1. IT Governance Institute (
  61. 61.
    The-Open-Group (2009) The Open group architecture framework (TOGAF), version 9.0Google Scholar
  62. 62.
    Pereira CM, Sousa P (2005) Enterprise architecture: business and IT alignment. In: ACM symposium on applied computing, Santa Fe, NM, USA, pp 1344-1345Google Scholar
  63. 63.
    Veasey PW (2001) Use of enterprise architectures in managing strategic change. Bus Process Manag 7(5):420–436CrossRefGoogle Scholar
  64. 64.
    Engelsman W, Quartel D, Jonkers H, van Sinderen M (2011) Extending enterprise architecture modelling with business goals and requirements. Enterp Inf Syst 5(1):9–36CrossRefGoogle Scholar
  65. 65.
    Xueying W, Feicheng M, Xiongwei Z (2008) Aligning business and IT using enterprise architecture. In: 4th international conference on wireless communications, networking and mobile computing (WiCOM), Dalian, pp 1–5Google Scholar
  66. 66.
    Tamm T, Seddon PB, Shanks G, Reynolds P (2011) How does enterprise architecture add value to organisations? Commun Assoc Inf Syst 28(1):141–168Google Scholar
  67. 67.
    Seigerroth U (2011) Enterprise modeling and enterprise architecture: the constituents of transformation and alignment of business and IT. Int J IT/Bus Align Gov (IJITBAG) 2(1):16–34CrossRefGoogle Scholar
  68. 68.
    Bradley RV, Pratt RME, Byrd TA, Simmons L (2011) The role of enterprise architecture in the quest for it value. MIS Q Exec 10(2):19–27Google Scholar
  69. 69.
    Bradley RV, Pratt RME, Byrd TA, Outlay CN, Wynn DE Jr (2012) Enterprise architecture, IT effectiveness and the mediating role of IT alignment in US hospitals. Inf Syst J 22(2):97–127CrossRefGoogle Scholar
  70. 70.
    Saat J, Franke U, Lagerström R, Ekstedt M (2010) Enterprise architecture meta models for IT/business alignment situations. In: 14th IEEE international conference on enterprise distributed object computing (EDOC), Vitoria, Brazil, pp 14–23Google Scholar
  71. 71.
    Varghese J, Kurien P (2004) IT imperatives beyond strategic alignment: enterprise architecture flexibility and IT delivery efficiency. Handb Bus Strategy 5(1):275–279CrossRefGoogle Scholar
  72. 72.
    Plazaola L, Flores J, Vargas N, Ekstedt M (2008) Strategic business and IT alignment assessment: a case study applying an enterprise architecture-based metamodel. In: 41st Hawaii international conference on system sciences, Waikoloa, HI, p 398Google Scholar
  73. 73.
    Wang X, Zhou X, Jiang L (2008) A method of business and IT alignment based on enterprise architecture. In: IEEE international conference on service operations and logistics, and informatics (IEEE/SOLI), Beijing, pp 740–745Google Scholar
  74. 74.
    Aier IS, Winter R (2009) Virtual decoupling for IT/business alignment–conceptual foundations, architecture design and implementation example. Bus Inf Syst Eng 1(2):150–163CrossRefGoogle Scholar
  75. 75.
    Haki MK, Forte MW (2010) Proposal of a service oriented architecture governance model to serve as a practical framework for business-IT alignment. In: 4th International conference on new trends in information science and service science (NISS), Gyeongju, pp 410–417Google Scholar
  76. 76.
    PMI (2008) A guide to the project management body of knowledge. Project Management Institute, Inc, PAGoogle Scholar
  77. 77.
    Foorthuis R, van Steenbergen M, Brinkkemper S, Bruls WA (2015) A theory building study of enterprise architecture practices and benefits. Inf Syst Front 1–24. doi: 10.1007/s10796-014-9542-1
  78. 78.
    Bahrami A, Sadowski D, Beahrami S (1998) Enterprise architecture for business process simulation. In: Winter simulation conference (WSC), Washington, DC, pp 1409–1413Google Scholar
  79. 79.
    Buckl S, Matthes F, Schweda CM (2009) Future research topics in enterprise architecture management—a knowledge management perspective. In: International conference on service-oriented computing (ICSOC), Stockholm, Sweden, pp 1–11Google Scholar
  80. 80.
    El Kourdi M, Shah H, Atkins A (2007) A proposed framework for knowledge discovery in enterprise architecture. In: Trends in enterprise architecture research (TEAR), St. Gallen, Switzerland, pp 41–49Google Scholar
  81. 81.
    Jafari M, Akhavan P, Nouranipour E (2009) Developing an architecture model for enterprise knowledge: an empirical study based on the Zachman framework in Iran. Manag Decis 47(5):730–759CrossRefGoogle Scholar
  82. 82.
    Ross J (2006) Enterprise architecture: driving business benefits from IT. 359, Massachusetts Institute of Technology. Center for Information Systems Research (CISR), Cambridge, MAGoogle Scholar
  83. 83.
    Vail E (2002) Knowledge management & enterprise architecture: an opportunity for synergy. White paper. Ptech Inc., Quincy, MassachusettsGoogle Scholar
  84. 84.
    Cotton LD, Haase GA, Havlicek JD, Thal AE (2009) Value driven enterprise architecture score (VDEAScore): A means of DoDAF architecture evaluation. In: 7th Annual conference on systems engineering research (CSER), Leicestershire, UKGoogle Scholar
  85. 85.
    Gustafsson P, Johnson P, Nordstrom L (2009) Enterprise architecture: A framework supporting organizational performance analysis. In: 20th International conference and exhibition on electricity distribution, Prague, Czech Republic, pp 1–4Google Scholar
  86. 86.
    Ostadzadeh SS, Habibi J, Ostadzadeh SA (2010) A framework for decision support systems based on Zachman framework. In: Elleithy K (ed) Advanced techniques in computing sciences and software engineering. Springer, Netherlands, pp 497–502CrossRefGoogle Scholar
  87. 87.
    Schelp J, Stutz M (2007) A Balanced Scorecard Approach to Measure the Value of Enterprise Architecture. Journal of Enterprise Architecture 3(4):8–14Google Scholar
  88. 88.
    Velitchkov I (2008) Integration of IT strategy and enterprise architecture models. Paper presented at the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing, Gabrovo, BulgariaGoogle Scholar
  89. 89.
    Lindstrom A, Johnson P, Johansson E, Ekstedt M, Simonsson M (2006) A survey on CIO concerns—do enterprise architecture frameworks support them? Inf Syst Front 8(2):81–90CrossRefGoogle Scholar
  90. 90.
    Molinaro LFR, Ramos KHC, Cotta Orlandi TR, Abdalla H (2010) Enterprise architecture to IT governance: an approach based on component business model and performance levels. In: Quintela Varajão JE, Cruz-Cunha MM, Putnik GD, Trigo A (eds) Enterprise information systems, vol 110. Communications in computer and information science. Springer, Berlin, pp 41–51Google Scholar
  91. 91.
    Nakakawa A, van Bommel P, Proper E (2010) Towards a theory on collaborative decision making in enterprise architecture. In: Winter R, Zhao J, Aier S (eds) Global perspectives on design science research, vol 6105. Lecture notes in computer science. Springer, Heidelberg, pp 538–541Google Scholar
  92. 92.
    Ireland V (2007) Enterprise architecture—a layer between portfolios and organisation strategy. In: 4th World project management week conference, SingaporeGoogle Scholar
  93. 93.
    Ross J, Weill P, Robertson DC (2006) Enterprise architecture as strategy: create a foundation for business execution. Harvard Business School Press, BostonGoogle Scholar
  94. 94.
    Fairhead N, Good J (2009) People-led enterprise architecture. In: Saha P (ed) Advances in government enterprise architecture. IGI Global, Pennsylvania, pp 285–306CrossRefGoogle Scholar
  95. 95.
    Coltman T, Devinney TM, Midgley DF, Venaik S (2008) Formative versus reflective measurement models: two applications of formative measurement. J Bus Res 61(12):1250–1262CrossRefGoogle Scholar
  96. 96.
    Diamantopoulos A, Siguaw JA (2006) Formative versus reflective indicators in organizational measure development: a comparison and empirical illustration. Br J Manag 17(4):263–282CrossRefGoogle Scholar
  97. 97.
    Jarvis CB, MacKenzie SB, Podsakoff PM (2003) A critical review of construct indicators and measurement model misspecification in marketing and consumer research. J Consum Res 30(2):199–218CrossRefGoogle Scholar
  98. 98.
    Sharp H, Rogers Y, Preece J (2002) Interaction design: beyond human-computer interaction. Wiley, HobokenGoogle Scholar
  99. 99.
    Presser S, Rothgeb JM, Couper MP, Lessler JT, Martin E, Martin J, Singer E (2004) Methods for testing and evaluating survey questionnaires. Wiley, HobokenCrossRefGoogle Scholar
  100. 100.
    Groves RM, Fowler FJ, Couper MP, Lepkowski JM, Singer E, Tourangeau R (2009) Survey methodology, 2nd edn. Wiley, HobokenGoogle Scholar
  101. 101.
    Bradburn NM, Sudman S, Wansink B (2004) Asking questions: the definitive guide to questionnaire design—for market research, political polls, and social and health questionnaires. WileyGoogle Scholar
  102. 102.
    Couper MP, Baker RP, Bethlehem J, Clark CZF, Martin J, Nicholls WL, O’Reilly JM (1998) Computer assisted survey information collection. Wiley, HobokenGoogle Scholar
  103. 103.
    Sandelowski M (1995) Sample size in qualitative research. Res Nurs Health 18(2):179–183CrossRefGoogle Scholar
  104. 104.
    Adcock R, Collier D (2001) Measurement validity: a shared standard for qualitative and quantitative research. Am Polit Sci Rev 95(3):529–546CrossRefGoogle Scholar
  105. 105.
    Chin WW, Newsted PR (1999) Structural equation modeling analysis with small samples using partial least squares. In: Hoyle RH (ed) Statistical strategies for small sample research. Sage, Thousand OaksGoogle Scholar
  106. 106.
    Fornell C (1987) A second generation of multivariate analysis: classification of methods and implications for marketing research. In: Houston MJ (ed) Review of marketing. American Marketing Association, ChicagoGoogle Scholar
  107. 107.
    Chen L (2010) Business–IT alignment maturity of companies in China. Inf Manag 47(1):9–16CrossRefGoogle Scholar
  108. 108.
    Sledgianowski D, Luftman J, Reilly RR (2006) Development and validation of an instrument to measure maturity of IT business strategic alignment mechanisms. Inf Resourc Manag J 19(3):18–33CrossRefGoogle Scholar
  109. 109.
    Carifio L, Perla R (2008) Resolving the 50-year debate around using and misusing Likert scales. Med Educ 42(12):1150–1152CrossRefGoogle Scholar
  110. 110.
    Norman G (2010) Likert scales, levels of measurement and the ‘‘laws’’ of statistics. Adv Health Sci Educ 15(5):625–632CrossRefGoogle Scholar
  111. 111.
    Sheskin DJ (2004) Handbook of parametric and nonparametric statistical procedures, 3rd edn. Chapman & Hall/CRC, Boca RatonGoogle Scholar
  112. 112.
    Anastasi A, Urbina S (1997) Psychological testing, 7th edn. Prentice-Hall, Upper Saddle RiverGoogle Scholar
  113. 113.
    DeVon HA, Block ME, Moyle-Wright P, Ernst DM (2007) A psychometric toolbox for testing validity and reliability. J Nurs Scholarsh 39(2):155–164CrossRefGoogle Scholar
  114. 114.
    Vaishnavi VK, Kuechler W (2008) Design science research methods and patterns—innovating information and communication technology. Auerbach Publications, NYGoogle Scholar
  115. 115.
    Chin WW (1995) Partial least squares is to LISREL as principal components analysis is to common factor analysis. Technol Stud 2(2):315–319Google Scholar
  116. 116.
    Rossiter JR (2002) The C-OAR-SE procedure for scale development in marketing. Int J Res Mark 19(4):305–335CrossRefGoogle Scholar
  117. 117.
    Petter S, Straub D, Rai A (2007) Specifying formative constructs in information systems research. MIS Q 31(4):623–656Google Scholar
  118. 118.
    Roberts N, Thatcher J (2009) Conceptualizing and testing formative constructs: tutorial and annotated example. ACM SIGMIS Database 40(3):9–39CrossRefGoogle Scholar
  119. 119.
    Henseler J, Ringle CM, Sinkovics RR (2009) The use of partial least squares path modeling in international marketing. Adv Int Mark (AIM) 20(1):277–320Google Scholar
  120. 120.
    Straub D, Boudreau M-C, Gefen D (2004) Validation guidelines for IS positivist research. Commun Assoc Inf Syst 13(1):63Google Scholar
  121. 121.
    Cohen J (1988) Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates, HillsdaleGoogle Scholar
  122. 122.
    Hair JF Jr, Hult GTM, Ringle C, Sarstedt M (2013) A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications, Thousand OaksGoogle Scholar
  123. 123.
    Hair JF, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis, 5th edn. Prentice Hall, Upper Saddle RiverGoogle Scholar
  124. 124.
    Woszczynski AB, Whitman ME (2004) The problem of common method variance in IS research. In: Whitman ME, Woszczynski AB (eds) The handbook of information systems research. IGI Glob, Hershey, PA, pp 66–77Google Scholar
  125. 125.
    Lindell MK, Whitney DJ (2001) Accounting for common method variance in cross-sectional research designs. J Appl Psychol 86(1):114CrossRefGoogle Scholar
  126. 126.
    Tenenhaus M, Esposito Vinzi V, Chatelin YM, Lauro C (2005) PLS path modeling. Comput Stat Data Anal 48(1):159–205CrossRefGoogle Scholar
  127. 127.
    Esposito Vinzi V, Trinchera L, Amato S (2010) PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement. In: Esposito Vinzi V, Chin WW, Henseler J, Wang H (eds) Handbook of partial least squares, vol 47–82. Springer, BerlinCrossRefGoogle Scholar
  128. 128.
    Brown TA (2006) Confirmatory factor analysis for applied research. Methodology in the social sciences. Guilford Publications Inc, New YorkGoogle Scholar
  129. 129.
    Hair JF, Ringle CM, Sarstedt M (2011) PLS-SEM: indeed a silver bullet. J Mark Theory Pract 9(2):139–151CrossRefGoogle Scholar
  130. 130.
    Wold H (1980) Factors affecting the outcome of economic sanctions: an application of soft modelling. Paper presented at the 4th World Congress of Econometric Society, Aix-en-provence, France, 1–3 MayGoogle Scholar
  131. 131.
    Falk RF, Miller NB (1992) A primer for soft modelling. University of Akron Press, AkronGoogle Scholar
  132. 132.
    Yeniay O, Göktaş A (2002) A Comparison of partial least squares regression with other prediction methods. Hacet J Math Stat 31(99):99–111Google Scholar
  133. 133.
    Howell RD, Breivik E, Wilcox JB (2007) Reconsidering formative measurement. Psychol Methods 12(2):205CrossRefGoogle Scholar
  134. 134.
    Chin WW, Marcolin BL, Newsted PR (1996) A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and voice mail emotion/adoption study. In: DeGross JI, Jarvenpaa S, Srinivasan A (eds) 17th International conference on information systems, Cleveland, OhioGoogle Scholar
  135. 135.
    Hulland J (1999) Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strateg Manag J 20(2):195–204CrossRefGoogle Scholar
  136. 136.
    Urbach N, Ahlemann F (2010) Structural equation modeling in information systems research using partial least squares. J Inf Technol Theory Appl 11(2):5–40Google Scholar
  137. 137.
    Efron B (1979) Bootstrap methods: another look at the jackknife. Ann Stat 7(1):1–26CrossRefGoogle Scholar
  138. 138.
    Efron B, Tibshirani RJ (1994) An introduction to the bootstrap, vol 57. CRC Press, Boca RatonGoogle Scholar
  139. 139.
    Chin WW (1998) Issues and opinion on structural equation modeling. MIS Q 22(1):5–9Google Scholar
  140. 140.
    Henseler J, Sarstedt M (2013) Goodness-of-fit indices for partial least squares path modeling. Comput Stat 28(2):565–580CrossRefGoogle Scholar
  141. 141.
    Geisser S (1974) A predictive approach to the random effect model. Biometrika 61(1):101–107CrossRefGoogle Scholar
  142. 142.
    Stone M (1974) Cross-validatory choice and assessment of statistical predictions. J R Stat Soc Ser B (Methodological) 36(2):111–147Google Scholar
  143. 143.
    Siegel S (1956) The Mann–Whitney U test. Nonparametric statistics for the behavioral sciences. McGraw-Hill, New York, NY, USGoogle Scholar
  144. 144.
    McKnight PE, Najab J (2010) Mann-Whitney U Test. In: Weiner IB, Craighead WE (eds) Corsini encyclopedia of psychology. Wiley, onlineGoogle Scholar
  145. 145.
    Moore DA, Tanlu L, Bazerman MH (2010) Conflict of interest and the intrusion of bias. Judgm Decis Mak 5(1):37–53Google Scholar
  146. 146.
    Urbaczewski L, Mrdalj S (2006) A comparison of enterprise architecture frameworks. Issues Inf Syst 7(2):18–23Google Scholar
  147. 147.
    Tang A, Han J, Chen P (2004) A comparative analysis of architecture frameworks. In: 11th Asia-Pacific software engineering conference. IEEE, pp 640–647Google Scholar
  148. 148.
    Sessions R (2007) Comparison of the top four enterprise architecture methodologies. ObjectWatch Inc.Google Scholar
  149. 149.
    Snijders CCP, Matzat U (2007) Reducing social desirability bias through indirect questioning in scenarios: When does it work in online surveys? Paper presented at the General Online Reseach, GOR07, Leipzig, March 26–28, 2007Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Computer Engineering and Information TechnologyAmirkabir University of TechnologyTehranIran
  2. 2.School of Progress EngineeringIran University of Science and TechnologyNarmakIran
  3. 3.Department of Geo-Informatics, School of Geo-Information Science and Earth ObservationUniversity of TwenteEnschedeThe Netherlands
  4. 4.Kent Business SchoolUniversity of KentCanterburyUK

Personalised recommendations