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IT infrastructure capabilities and IT project success: a development team perspective

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Abstract

In this research we investigate how IT infrastructure capabilities are related to IT project success from a development team perspective. We first conduct an extensive literature review and summarize the insights to suggest an IT infrastructure base model. Drawing upon several other bodies of literature, particularly the psychology literature, we then build upon the base model to propose an integrative research model for IT project success that considers both actual and perceived effects of IT infrastructure capabilities. This research model argues that (1) teamwork quality mediates the effect of technical and human IT infrastructure capabilities on IT project success, and (2) team perceptions of both IT infrastructure and team capabilities shape team perceived likelihood of project success, which subsequently affects team commitment that is crucial to IT project success. We also propose a direct-effect model that directly links all constructs to IT project success so that we can test the efficacy of our proposed research model by comparing all three models. We then collect empirical data (n = 91) through an online survey of CIO/CTOs and team leaders. All three models are evaluated and compared using the partial least squares method. The results show strong support for the proposed research model except for two IT infrastructure components. We discuss the practical and theoretical implications of the findings, and suggest several ways this research can be extended.

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References

  1. Ives B, Learmonth G (1984) The information systems as a competitive weapon. Commun ACM 27(12):1193–1201

    Article  Google Scholar 

  2. Powell T, Micallef A (1997) Information technology as competitive advantage: the role of human, business, and technology resources. Strategic Manage J 18(5):375–405

    Article  Google Scholar 

  3. Bourlakis M, Bourlakis C (2006) Integrating logistics and information technology strategies for sustainable competitive advantage. J Enterp Inform Manage 19(4):389–402

    Article  Google Scholar 

  4. Barua A, Kriebel C, Mukhopadhyay T (1991) An economic analysis of strategic information technology investments. MIS Quart 15(3):313–331

    Article  Google Scholar 

  5. Santos B (1991) Justifying investment in new information technologies. J of Manage Inform Syst 7(4):71–90

    Google Scholar 

  6. Davern M, Kauffman J (2000) Discovering potential and realizing value from information technology investments. J Manage Inform Syst 16(4):121–143

    Google Scholar 

  7. Scott JE, Vessey I (2002) Managing risks in enterprise systems implementations. Commun ACM 45(4):74–81

    Article  Google Scholar 

  8. Davies P (2002) When big projects go wrong. Chartered account J 14–20

  9. Goodwin B (2002) Failed projects cost users £8 M on average. Computer weekly. November, 4

  10. Zizzo T (2002) Capitalizing IT failure. Electronic Bus 28(11):23

    Google Scholar 

  11. Scott J (1999) The FoxMeyer drugs’ bankruptcy: was it a failure of ERP? Proc of the 5th Americas Conference on Inform Syst 223–225

  12. Hitt L, Wu D, Zhou X (2002) Investment in enterprise resource planning: business impact and productivity measures. J Manage Inform Syst 19(1):71–98

    Article  Google Scholar 

  13. Weill P, Broadbent B (1998) Leveraging the new infrastructure: how market leaders capitalize on information technology. Harvard Business School Press, Boston, MA

  14. Melville N, Kraemer K, Gurbaxani V (2004) Review: information technology and organizational performance: an integrative Model IT business value. MIS Quart 28(2):283–322

    Google Scholar 

  15. McKay D, Brockway D (1989) Building I/T infrastructure for the 1990 s. Stage by Stage 9(3):1–11

    Google Scholar 

  16. Broadbent M, Weill P, Clair D (1999) The implications of information technology infrastructure for business process redesign. MIS Quart 23(2):159–182

    Article  Google Scholar 

  17. Law CCH, Ngai EWT, Infrastructure IT (2007) Capabilities and business process improvement: association with IT governance characteristics. Inform Resour Manage J 20(4):25–47

    Google Scholar 

  18. Chung SH, Byrd TA, Lewis BR, Ford FN (2005) An empirical study of the relationship between IT infrastructure flexibility, mass customization, and business performance. The DATABASE for Advances in Inform Syst 36(3):26–44

    Google Scholar 

  19. Zhang M, Tansuhaj P (2007) Organizational culture, information technology capability, and performance: the case of born global firms. Multinatl Bus Rev 15(3):43–77

    Google Scholar 

  20. Morris SA, Strickland TH (2008/2009) Exploration of information system process improvements and firm performance. The J of Computer Inform Syst 49(2):86–91

    Google Scholar 

  21. Xia W (1998) Dynamic capabilities and organizational impact of IT infrastructure: a research framework and an empirical investigation. Dissertation, University of Pittsburgh

  22. Weill P, Olson M (1989) Managing investment in information technology: mini case examples and implications. MIS Quart 13(1):3–17

    Article  Google Scholar 

  23. Bacon C (1992) The use of decision criteria in selecting information systems/technology investments. MIS Quart 16(3):335–353

    Article  Google Scholar 

  24. Nash K (2003) 3 triumphs, 3 breakdowns. Baseline 14:22–23

    Google Scholar 

  25. Hoegl M, Gemuenden H (2001) Teamwork quality and the success of innovative projects: a theoretical concept and empirical evidence. Organization Sci 12(4):435–449

    Article  Google Scholar 

  26. Hoegl M, Parboteeah KP, Gemuenden HG (2003) When teamwork really matters: task innovativeness as a moderator of the teamwork-performance relationship in software development projects. J Engineering and Technol Manage 20(4):281–302

    Article  Google Scholar 

  27. The Standish Group (2004) The CHAOS report

  28. Ibbs CW, Kwak YH (2000) Assessing project management maturity. Proj Manage J 31(1):32–43

    Google Scholar 

  29. The Standish Group (1994) The CHAOS report

  30. Powers R, Dickson G, Project MIS (1973) Management: myths, opinions, and reality. California Manage Rev 15(3):147–156

    Google Scholar 

  31. Robey D, Farrow D (1982) User involvement in information systems development: a conflict model and empirical test. Manage Sci 28(1):73–85

    Article  Google Scholar 

  32. Robey D, Smith L, Vijayasarathy L (1993) Perceptions of conflict and success in information systems development projects. J Manage Inform Syst 10(1):123–139

    Google Scholar 

  33. Saarinen T (1990) System development methodology and project success. Inform & Manage 19:183–193

    Article  Google Scholar 

  34. DeLone W, McLean E (1992) Information systems success: the quest for the dependent variable. Inform Syst Res 3(1):60–95

    Article  Google Scholar 

  35. DeLone W, McLean E (2003) The DeLone and McLean model of information systems success: a ten-year update. J Manage Inform Syst 19(4):9–30

    Google Scholar 

  36. Aladwani A (2002) An integrated performance model of information systems projects. J Manage Inform Syst 19(1):185–210

    Google Scholar 

  37. The Standish Group (2001) Recipe for project success

  38. Hardy L, Chaudhuri T (2001) Designing an effective project management office. In: Tinnirello PC (ed) New directions in project management. Auerbach Publications, Philadelphia, pp 447–460

    Google Scholar 

  39. Hoffman T (2003) Value of project management offices questioned. Computerworld 37(29):7

    Google Scholar 

  40. Yardley D (2002) Successful IT project delivery: learning the lessons of project failure. Addison Wesley Professional

  41. Barki H, Hartwick J (1994) Measuring user participation, user involvement, and user attitude. MIS Quart 18(1):59–79

    Article  Google Scholar 

  42. Marble RP, System A (2003) Implementation study: management commitment to project management. Inform & Manage 41(1):111–123

    Article  Google Scholar 

  43. Wang ETG, Shih S-P, Jiang JJ, Klein G (2006) The relative influence of management control and user–is personnel interaction on project performance. Inform and Softw Technol 48(3):214–220

    Article  Google Scholar 

  44. Schneider K (2002) Non-technical factors are key to ensuring project. Computer weekly

  45. Chan CL, Jiang JJ, Klein G (2008) Team task skills as a facilitator for application and development skills. IEEE Trans Eng Manage 55(3):434–441

    Article  Google Scholar 

  46. Yen HR, Li EY, Niehoff BP (2008) Do organizational citizenship behaviors lead to information system success? testing the mediation effects of integration climate and project management. Inform & Manage 45(6):394–402

    Article  Google Scholar 

  47. Byrd TA, Turner D (2000) Measuring the flexibility of information technology infrastructure: exploratory analysis of a construct. J Manage Inform Syst 17(1):167–208

    Google Scholar 

  48. Fink L, Neumann S (2007) Gaining agility through IT personnel capabilities: the mediating role of IT infrastructure capabilities. J the Association for Inform Syst 8(8):440–462

    Google Scholar 

  49. Boh WF, Yellin D (2006) Using enterprise architecture standards in managing Information Technology. J Manage Inform Syst 23(3):163–207

    Google Scholar 

  50. Weill P (1993) The role and value of information technology infrastructure: some empirical observations. In: Banker R, Kauffman R, Mahmood MA (eds) Strategic information technology management: perspectives on organizational growth, competitive advantage. Idea Group Publishing, Hershey, PA, pp 547–573

    Google Scholar 

  51. Duncan N (1995) Capturing flexibility of information technology infrastructure: a study of resource characteristics and their measure. J Manage Inform Syst 12(2):37–57

    Google Scholar 

  52. Duncan N (1995) The invisible weapon: a study of information technology infrastructure as a strategic resource. Dissertation, Texas A&M University, Texas

  53. Broadbent M, Weill P, O’Brien T, Neo B (1996) Firm context and pattern of IT infrastructure capability. Proc of the 17th Int Conference on Inform Syst Cleveland, Ohio. 174–194

  54. Lewis B, Byrd T (2003) Development of a measure for information technology infrastructure construct. Eur J Inform Syst 12:93–109

    Article  Google Scholar 

  55. Byrd TA, Lewis BR, Bradley RV (2006) Is infrastructure: the influence of senior IT leadership and strategic information systems planning. J Computer Inform Syst 47(1):101–113

    Google Scholar 

  56. Langdon CS (2006) Designing information systems capabilities to create business value: a theoretical conceptualization of the role of flexibility and integration. J Database Manage 17(3):1–18

    Google Scholar 

  57. Zhang M, Sarker S, McCullough J (2008) Measuring information technology capability of export-focused small or medium sized enterprises in China: scale development and validation. J Global Inform Manage 16(3):1–25

    Google Scholar 

  58. Ray G, Muhanna WA, Barney JB (2005) Information technology and the performance of the customer service process: a resource-based analysis. MIS Quart 29(4):626–652

    Google Scholar 

  59. Ravichandran T, Lertwongsatien C (2005) Effect of information systems resources and capabilities on firm performance: a resource-based perspective. J Manage Inform Syst 21(4):237–276

    Google Scholar 

  60. Lai F, Li D, Wang Q, Zhao X (2008) The information technology capability of third-party logistics providers: a resource-based view and empirical evidence from China. J Supply Chain Manage 44(3):22–38

    Article  Google Scholar 

  61. Zhang C, Dhaliwal J (2009) An investigation of resource-based and institutional theoretic factors in technology adoption for operations and supply Chain management. Int J Prod Economics 120(1):252–269

    Article  Google Scholar 

  62. Banker R, Kauffman J (2004) The evolution of research on information systems: a fiftieth-year survey of the literature in management science. Manage Sci 50(3):281–298

    Article  Google Scholar 

  63. Tallon PP (2008) Inside the adaptive enterprise: an information technology capabilities perspective on business process agility. Inform Technol and Manage 9(1):21–36

    Article  Google Scholar 

  64. Bhatt GD, Grover V (2005) Types of information technology capabilities and their role in competitive advantage: an empirical study. J Manage Inform Syst 22(2):253–277

    Google Scholar 

  65. Chen JS, Tsou HT (2007) Information technology adoption for service innovation practices and competitive advantage: the case of financial firms. Inform Res-an Int Electronic J 12(3):23

    Google Scholar 

  66. Rai A, Patnayakuni R, Seth N (2006) Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quart 30(2):225–246

    Google Scholar 

  67. Zhang M, Sarker S, Sarker S (2008) Unpacking the effect of IT capability on the performance of export-focused SMEs: a report from china. Inform Syst J 18(4):357–380

    Article  Google Scholar 

  68. Cui L, Zhang C, Zhang CH, Huang LH (2008) Exploring IT adoption process in shanghai firms: an empirical study. J Global Inform Manage 16(2):1–17

    Google Scholar 

  69. Lee S, Kim KJ (2007) Factors affecting the implementation success of internet-based information systems. Computers in Hum Behav 23:1853–1880

    Article  Google Scholar 

  70. Webb BR, Schlemmer F (2008) Predicting web services performance from internet performance: an empirical study of resources and capabilities in E-business smes. J Knowl Manage 12(6):137–155

    Article  Google Scholar 

  71. Byrd TA, Pitts JP, Adrian AM, Davidson NW (2008) Examination of a path model relating information technology infrastructure with firm performance. J Bus Logistics 29(2):161–187

    Google Scholar 

  72. Sabherwal R, Sein M, Marakas G (2003) Escalating commitment to information systems projects: findings from two simulated experiments. Inform & Manage 40(8):781–798

    Article  Google Scholar 

  73. Vroom V (1964) Work and motivation. Wiley, London

  74. Fowler A, Walsh M (1999) Conflicting perceptions of success in an information systems project. Int J Proj Manage 17(1):1–10

    Article  Google Scholar 

  75. Jiang JJ, Klein G, Balloun JL, Crampton SM (1999) System analysts’ orientations and perceptions of system failure. Inform and Softw Technol 41:101–106

    Article  Google Scholar 

  76. Kearns GS, Sabherwal R (2007) Antecedents and consequences of information systems planning integration. IEEE Trans Eng Manage 54(4):628–643

    Article  Google Scholar 

  77. Ouadahi J, Qualitative A (2008) Analysis of factors associated with user acceptance and rejection of a new workplace information system in the public sector: a conceptual model. Canadian J Admin Sci 25(3):201–213

    Article  Google Scholar 

  78. Raghavan VV, Sakaguchi T, Mahaney RC (2008) Organizational justice perceptions and their influence on information systems development project outcomes. J Inform Technol Theory and Appl 9(2):27–43

    Google Scholar 

  79. Jiang JJ, Klein G, Wu SPJ, Liang TP (2009) The relation of requirements uncertainty and stakeholder perception gaps to project management performance. J Syst and Softw 82:801–808

    Article  Google Scholar 

  80. Arnold H, Test A (1981) Of the validity of the multiplicative hypothesis of expectancy-valence theories of work motivation. Academy of Manage J 24(1):128–141

    Article  Google Scholar 

  81. Remenyi D (1999) Stop IT project failure through risk management. Butterworth-Heinemann, Oxford

    Google Scholar 

  82. Ewusi-Mensah K (1997) Critical issues in abandoned information systems development projects. Commun ACM 40(9):74–80

    Article  Google Scholar 

  83. Lee C, Chen W (2007) Cross-functionality and charged behavior of the new product development teams in Taiwan’s information technology industries. Technovation 27:605–615

    Article  Google Scholar 

  84. Sundstrom E (1999) Supporting work team effectiveness: best management practices for fostering high performance. Jossey-Bass Publishers, San Francisco

    Google Scholar 

  85. Easley R, Devaraj S, Crant J (2003) Relating collaborative technology use to teamwork quality and performance: an empirical analysis. J Manage Inform Syst 19(4):247–268

    Google Scholar 

  86. Hoegl M, Parboteeah KP (2006) Autonomy and teamwork in innovative projects. Hum Resour Manage 45(1):67–79

    Article  Google Scholar 

  87. Hoegl M, Parboteeah KP (2007) Creativity in innovative projects: how teamwork matters. J Eng Technol Manage 24(1–2):148–166

    Article  Google Scholar 

  88. Hoegl M, Proserpio L (2004) Team member proximity and teamwork in innovative projects. Res Policy 33(8):1153–1165

    Article  Google Scholar 

  89. Hoegl M, Ernst H, Proserpio L (2007) How teamwork matters more as team member dispersion increases. J Product Innovation Manage 24(2):156–165

    Article  Google Scholar 

  90. Jude-York D (1998) Technology enhanced teamwork: aligning individual contributions for superior team performance. Organization Dev J 16(3):73–82

    Google Scholar 

  91. Richardson P, Denton DK (2007) Using the intranet to build teamwork. Team Perform Manage 13(5/6):184–188

    Article  Google Scholar 

  92. Biggs S (1978) Group participation in MIS project teams? let’s look at the contingencies first! MIS Quart. 2(1):19–26

  93. Kaiser K, Bostrom R (1982) Personality characteristics of MIS project teams: an empirical study and action-research design. MIS Quart 6(4):43–60

    Article  Google Scholar 

  94. White K, Project MIS (1984) Teams: an investigation of cognitive style implications. MIS Quart 8(2):95–101

    Article  Google Scholar 

  95. Ulloa BCR, Adams SG (2004) Attitude toward teamwork and effective teaming. Team Perform Manage 10(7/8):145–151

    Article  Google Scholar 

  96. Chatzoglou PD (1997) Factors affecting completion of the requirements capture stage of projects with different characteristics. Inform and Softw Technol 39:627–640

    Article  Google Scholar 

  97. Margerison C, McCann D (1984) High performing managerial teams. Lead and Organization Dev J 5(5):9–13

    Article  Google Scholar 

  98. Green T (2000) Keep the faith in motivation. Incentive 174(8):81–83

    Google Scholar 

  99. Rippin A (2002) Team working. Capstone Publishing, Oxford

    Google Scholar 

  100. McGrath JE (1964) A social psychological approach to the study of negotiation. Illinois University Press, Urbana

    Google Scholar 

  101. Hartono E, Santhanam R, Holsapple CW (2007) Factors that contribute to management support system success: an analysis of field studies. Decis Support Syst 43(1):256–268

    Article  Google Scholar 

  102. Lee MC (2009) Factors influencing the adoption of internet banking: an integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Res and Applications 8(3):130–141

    Article  Google Scholar 

  103. Locke E, Frederick E, Bobko P (1984) Effect of self-efficacy, goals, and tasks strategies on task performance. J Appl Psychology 69(2):241–251

    Article  Google Scholar 

  104. Renn R (2003) Moderation by goal commitment of the feedback-performance relationship: theoretical explanation and preliminary study. Hum Resour Manage Rev 13:561–580

    Article  Google Scholar 

  105. Hollenbeck J, Klein H (1987) Goal commitment and the goal-setting process: problems, prospects, and proposals for future research. J Appl Psychology 72(2):212–220

    Article  Google Scholar 

  106. Butler T (2005) Power conflict, commitment & the development of sales & marketing IS/IT infrastructures at digital devices, Inc. J Cases on Inform Technol 7(3):18–36

    Google Scholar 

  107. Chang K, Sheu TS, Klein G, Jiang JJ (2010) User commitment and collaboration: motivational antecedents and project performance. Inform and Softw Technol 52(6):672–679

    Article  Google Scholar 

  108. Ross TM, Jones EC, Adams SG (2008) Can team effectiveness be predicted? Team perform. Manage 14(5/6):248–268

    Google Scholar 

  109. Chau P (1996) An empirical assessment of a modified technology acceptance model. J Manage Inform Syst 13(2):185–204

    Google Scholar 

  110. Igbaria M, Zinatelli N, Cragg P, Cavaye A (1997) Personal computing acceptance factors in small firms: a structural equation model. MIS Quart 21(3):279–305

    Article  Google Scholar 

  111. R. Leifer, K. McGannon, (1986) Goal acceptance and goal commitment: their differential impact on goal setting theory. Paper presented at the annual meeting of the academy of manage, Chicago

  112. Renn R, Danehower C, Swiercz P, Icenogle M (1999) Further examination of the measurement properties of Leither & McGannon’s (1986) goal acceptance and goal commitment scales. J Occup Organ Psychol 72:107–113

    Article  Google Scholar 

  113. King WR, Flor PR (2008) The development of global IT infrastructure. Omega-Int J Manage Sci 36(3):486–504

    Article  Google Scholar 

  114. Armstrong J, Overton T (1977) Estimating non-response bias in mail surveys. J Marketing Res 14(8):396–402

    Article  Google Scholar 

  115. Compeau D, Higgins C (1995) Computer self-efficacy: development of a measure and initial test. MIS Quart 19(2):189–211

    Article  Google Scholar 

  116. Bollen KA (1989) Structural equations with latent variables. Wiley, New York

    Google Scholar 

  117. Sharma S (1996) Applied multivariate techniques. Wiley, London, pp 90–143

  118. Nunnally J (1978) Psychometric theory, 2nd edn. McGraw-Hill, New York

    Google Scholar 

  119. Igbaria M, Guimaraes T, Davis G (1995) Testing the determinants of micorcomputer usage via a structural equation model. J Manage Inform Syst 11(4):87–114

    Google Scholar 

  120. Thompson R, Higgins C, Howell J (1991) Personal computing: toward a conceptual model of utilization. MIS Quart 15(1):125–143

    Article  Google Scholar 

  121. Igbaria M, Parasuraman S, Badawy M (1994) Work experience, job involvement and quality of work life among information systems personnel. MIS Quart 18(2):175–202

    Article  Google Scholar 

  122. Wade M, Parent M (2001–2002) Relationships between job skills and performance: a study of webmasters. J of Manage Inform Syst 18(3):71–96

    Google Scholar 

  123. Teo H, Wei K, Benbasat I (2003) Predicting intention to adopt interorganizational linkages: an institutional perspective. MIS Quart 27(1):19–49

    Google Scholar 

  124. Marcoulides GA, Saunders C (2006) Editor’s comments—PLS: a silver bullet? MIS Quart 30(2):iii–ix

    Google Scholar 

  125. Chin W, Marcolin B (1995) The holistic approach to construct validation in is research: examples of the interplay between theory and measurement. In: IS proceedings in 23rd administrative science, vol 16, no 4. Association of Canada, Windsor, ON, Canada, pp 33–43

  126. Chin W (2001) PLS-Graph user’s guide version 3.0. Soft Modeling Inc

  127. Chin W (1998) The partial least squares approach for structural equation modeling. In: Marcoulides GA (ed) Modern methods for business research. Lawrence Erlbaum Associates, Hillsdale, pp 295–336

    Google Scholar 

  128. Keil M, Tan C, Wei K, Saarinen T, Tuunainen V, Wassenaar A (2000) A cross-cultural study on escalation of commitment behavior in software projects. MIS Quart 24(2):299–325

    Article  Google Scholar 

  129. Fornell C, Larcker DF (1981) Evaluating structural equation model with unobservable variables and measurement error. J Marketing Res 18(1):39–50

    Article  Google Scholar 

  130. Segars A, Grover V (1998) Strategic information systems planning success: an investigation of the construct and its measurement. MIS Quart 22(2):139–163

    Article  Google Scholar 

  131. Bagozzi R, Yi Y, Phillips L (1991) Assessing construct validity in organizational research. Admin Sci Quart 36(3):421–458

    Article  Google Scholar 

  132. Barclay D, Higgins C, Thompson R (1995) The partial least squares (PLS) approach to causal modeling: personal computer adoption and use as an illustration. Technol Stud 2(2):285–309

    Google Scholar 

  133. Tabachnick B, Fidell L (2000) Using multivariate statistics, 4th edn. Allyn and Bacon, Boston, MA

  134. Chin W (1995) Partial least squares is to LISREL as principal components analysis is to common factor analysis. Technol Stud 2(2):315–319

    Google Scholar 

  135. Baron RM, Kenny DA (1986) The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Personality and Soc Psychology 51(6):1173–1182

    Article  Google Scholar 

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Acknowledgments

We would like to thank the associate editor, Dr. Robert J. Kauffman, and three anonymous reviewers for their highly constructive comments. They have helped us make significant improvement to the manuscript.

Author information

Authors and Affiliations

  1. Department of Management Information Systems, School of Business and Management, American University of Sharjah, P.O. Box 26666, Sharjah, UAE

    Xiaobo Xu

  2. Department of Management, School of Business, Virginia Commonwealth University, 301 West Main Street, Richmond, VA, 23284-4000, USA

    Weiyong Zhang

  3. Department of Accounting and Information Systems, Pamplin College of Business, Virginia Tech, 3007 Pamplin Hall (0101), Blacksburg, VA, 24061-0101, USA

    Reza Barkhi

Authors
  1. Xiaobo Xu
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  3. Reza Barkhi
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Corresponding author

Correspondence to Xiaobo Xu.

Appendix: Questionnaire items

Appendix: Questionnaire items

1.1 First survey questionnaire

Functional efficiency of technical IT infrastructure components (ITREACH)

Approximately, what percentage of (0–100%):

  1. 1.

    All PCs in your organization are networked?

  2. 2.

    All business units/functions are connected through networks?

  3. 3.

    The computer platforms used by various units/functions are connected?

  4. 4.

    All transactions with your customer are electronically transmitted?

  5. 5.

    All transactions with your suppliers are electronically transmitted?

Flexibility of technical IT infrastructure components (ITFLEX)

Strongly disagree-1 Neutral-4 Strongly agree-7

  1. 1.

    Our networks can be easily updated with new technologies.

  2. 2.

    The various networks in our organization are compatible with each other.

  3. 3.

    Our data structure is flexible to support different users’ access needs.

  4. 4.

    The complexity of current application software seriously restricts our ability to develop new business applications.

  5. 5.

    Our computer platforms can be easily updated with new technologies.

Functional efficiency of human IT infrastructure components (ITRANGE)

Centralized IS function (centralized-1), the user units (decentralized-2), or external vendors (outsourced-3):

  1. 1.

    Develop business applications.

  2. 2.

    Maintain large-scale databases.

  3. 3.

    Perform IS project management.

  4. 4.

    Manage organization-wide data standards.

  5. 5.

    Provide technology advice and support services.

  6. 6.

    Identify and test new technology for business purposes.

  7. 7.

    Manage local area networks.

  8. 8.

    Implement security, disaster planning, and business recovery for applications and installations.

Functional efficiency of human IT infrastructure components (ITSTAND)

Your current IS standards/procedures adequately address (Strongly disagree-1 Neutral-4 Strongly agree-7):

  1. 1.

    Compatibility of computer platforms across user units.

  2. 2.

    Data consistent and integrity across systems.

  3. 3.

    Data security and privacy.

  4. 4.

    Data sharability across applications.

  5. 5.

    Application module reusability.

  6. 6.

    User interface commonality across applications.

  7. 7.

    Network connectivity across user units.

Flexibility of human IT infrastructure components (ITMGT)

Strongly disagree-1 Neutral-4 Strongly agree-7

  1. 1.

    The IS staff has good relationships with the users units.

  2. 2.

    The IS function is flexible in meeting changing user needs.

  3. 3.

    The IS staff is knowledge about our business activities.

  4. 4.

    The IS function is responsive to user service requests.

  5. 5.

    The services provided by the IS function are often unreliable.

  6. 6.

    We have a high regard for the technical expertise of the IS staff.

  7. 7.

    The IS function is able to identify and plan for future technology challenges.

IT project success (ITPERM)

Strongly disagree-1 Neutral-4 Strongly agree-7

  1. 1.

    The team produced large amounts of work.

  2. 2.

    The team produced high quality of work.

  3. 3.

    The team operated efficiently.

  4. 4.

    The team adhered to the budget.

  5. 5.

    The team adhered to the schedule.

  6. 6.

    Team members are satisfied with the interactions with people inside and outside of the team.

  7. 7.

    Team members are satisfied with their work done in the project.

1.2 Second survey questionnaire:

Teamwork quality (TWQ)

Strongly disagree-1 Neutral-4 Strongly agree-7

  1. 1.

    There was frequent communication within team.

  2. 2.

    Project-relevant information was shared openly by all team members.

  3. 3.

    The work done on subtasks within the project was closely harmonized.

  4. 4.

    The team recognized the specific potentials (strengths and weaknesses) of individual team members.

  5. 5.

    The team members helped and supported each other as best they could.

  6. 6.

    Every team member fully pushed the project.

  7. 7.

    It was important to the members of our team to be part of this project.

  8. 8.

    All members were fully integrated in our team.

Perceived IT infrastructure capabilities (PITIC)

I find our organization’s IT infrastructure resource (Strongly disagree-1 Neutral-4 Strongly agree-7):

  1. 1.

    useful to the project.

  2. 2.

    available to the project.

  3. 3.

    supportive to the project.

Perceived team capabilities (PTC)

I find our project team to have (Strongly disagree-1 Neutral-4 Strongly agree-7):

  1. 1.

    Cooperative members for the project.

  2. 2.

    Proper attitude for the project.

  3. 3.

    Necessary skills and knowledge for the project.

Perceived likelihood of project success (PLPS)

Please indicate the degree to which you agree or disagree with the following statements that describe for the most recently completed IT project before you started it as the project team leader (Strongly disagree-1 Neutral-4 Strongly agree-7):

  1. 1.

    The team will produce large amounts of work.

  2. 2.

    The team will produce high quality of work.

  3. 3.

    The team will operate efficiently.

  4. 4.

    The team will adhere to the budget.

  5. 5.

    The team will adhere to the schedule.

  6. 6.

    Team members will be satisfied with the interactions with people inside and outside of the team.

  7. 7.

    Team members will be satisfied with their work done in the project.

Team commitment (COMMIT)

In your honest opinion (Very low-1 Medium-4 Very high-7):

  1. 1.

    How hard did you try to achieve the project goal?

  2. 2.

    How persistent did you strive to attain the project goal?

  3. 3.

    How committed were you to achieving the project goal you were asked to try for?

  4. 4.

    How determined were you to reach your project goal?

  5. 5.

    How enthusiastic were you about attempting to achieve the project goal?

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Xu, X., Zhang, W. & Barkhi, R. IT infrastructure capabilities and IT project success: a development team perspective. Inf Technol Manag 11, 123–142 (2010). https://doi.org/10.1007/s10799-010-0072-3

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  • DOI: https://doi.org/10.1007/s10799-010-0072-3

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