Novelty-knowledge alignment: A theory of design convergence in systems development

Journal of Management Information Systems

Volumn 29, Issue 1, 2012, Pages 15-52

  Tiwana, Amrit ^a  

^a UNIVERSITY OF GEORGIA   (United States)

Author keywords

design convergence; iteration; novelty; oscillations; peripheral knowledge; systems development

Indexed keywords

DESIGN CONVERGENCE; ITERATION; NOVELTY; OSCILLATIONS; PERIPHERAL KNOWLEDGE; SYSTEMS DEVELOPMENT;

ALIGNMENT; DESIGN;

INFORMATION TECHNOLOGY;

EID: 84867300900     PISSN: 07421222     EISSN: None     Source Type: Journal    
DOI: 10.2753/MIS0742-1222290101     Document Type: Article

References (58)

1. Adelson, B., and Soloway, E. The role of domain experience in software design. IEEE Transactions on Software Engineering, 11, 11 (1985), 1351-1360
2. Adler, P.S. Interdepartmental interdependence and coordination-The case of the design/manufacturing interface. Organization Science, 6, 2 (1995), 147-167
3. Armstrong, J., and Overton, T. Estimating non-response bias in mail surveys. Journal of Marketing Research, 14, 3 (1977), 396-402
4. Baron, R., and Kenny, D. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 6 (1986), 1173-1182
5. Bassellier, G., and Benbasat, I. Business competence of information technology professionals: Conceptual development and influence on IT-business partnerships. MIS Quarterly, 28, 4 (2004), 673-694
6. Bassellier, G.; Benbasat, I.; and Reich, B. The influence of business managers' IT competence on championing IT. Information Systems Research, 14, 4 (2003), 317-336
7. Boehm, B. Software Cost Estimation with Cocomo II. Upper Saddle River, NJ: Prentice Hall, 2000
8. Bucciarelli, L. Designing Engineers. Cambridge: MIT Press, 1994
9. Carlile, P. A pragmatic view of knowledge and boundaries: Boundary objects in new product development. Organization Science, 13, 4 (2002), 442-455
10. Cerveny, R.P.; Garrity, E.J.; and Sanders, G.L. A problem-solving perspective on systems development. Journal of Management Information Systems, 6, 4 (Spring 1990), 103-122
11. Cramton, C. The mutual knowledge problem and its consequences for dispersed collaboration. Organization Science, 12, 3 (2001), 346-371
12. Curtis, B.; Krasner, H.; and Iscoe, N. A field study of the software design process for large systems. Communications of the ACM, 31, 11 (1988), 1268-1287
13. De Luca, L., and Atuahene-Gima, K. Market knowledge dimensions and cross-functional collaboration: Examining the different routes to product innovation performance. Journal of Marketing, 71, 1 (2007), 95-112
14. Deephouse, C.; Mukhopadhyay, T.; Goldenson, D.R.; and Kellner, M.I. Software processes and project performance. Journal of Management Information Systems, 12, 3 (Winter 1995-96), 187-205
15. Faraj, S., and Xiao, Y. Coordination in fast response organizations. Management Science, 52, 8 (2006), 1155-1169
16. Goodhue, D.; Lewis, W.; and Thompson, R. Statistical power in analyzing interaction effects: Questioning the advantage of PLS with product indicators. Information Systems Research, 18, 2 (2007), 211-227
17. Hansen, M. Knowledge networks: Explaining effective knowledge sharing in multiunit companies. Organization Science, 13, 3 (2002), 232-248
18. Hibbs, C.; Jewett, S.; and Sullivan, M. The Art of Lean Software Development. Sebastopol, CA: O'Reilly, 2009
19. Hoetker, G. Do modular products lead to modular organizations? Strategic Management Journal, 27, 6 (2006), 501-518
20. Hoopes, D., and Postrel, S. Shared knowledge, "glitches," and product development performance. Strategic Management Journal, 20, 9 (1999), 837-865
21. Hunt, A., and Thomas, D. The Pragmatic Programmer. Boston: Addison-Wesley, 2000
22. Iacobucci, D. Mediation Analysis. Los Angeles: Sage, 2008
23. Jaccard, J., and Turrisi, R. Interaction Effects in Multiple Regression, 2d ed. Thousand Oaks, CA: Sage, 2003
24. Kenny, D.; Kashy, D.; and Bolger, N. Data analysis in social psychology. In D. Gilbert, S. Fiske, and G. Lindzey (eds.), The Handbook of Social Psychology. Boston: McGraw-Hill, 1998, pp. 233-265
25. Kim, Y.R., and Stohr, E.A. Software reuse: Survey and research directions. Journal of Management Information Systems, 14, 4 (Spring 1998), 113-149
26. Kirsch, L.J.; Sambamurthy, V.; Ko, D.-G.; and Purvis, R.L. Controlling information systems development projects: The view from the client. Management Science, 48, 4 (2002), 484-498
27. Kraut, R., and Streeter, L. Coordination in software development. Communications of the ACM, 38, 3 (1995), 69-81
28. Leonard-Barton, D. Implementation as mutual adaptation of technology and organization. Research Policy, 17, 5 (1988), 251-267
29. Lindell, M., and Whitney, D. Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology, 86, 1 (2001), 114-121
30. Marengo, L.; Dosi, G.; Legrenzi, P.; and Pasquali, C. The structure of problem-solving knowledge and the structure of organizations. Industrial and Corporate Change, 9, 4 (2000), 757-788
31. Mathieu, J. The influence of shared mental models on team process and performance. Journal of Applied Psychology, 85, 2 (2000), 273-283
32. McCarthy, J., and McCarthy, M. Dynamics of Software Development. Redmond, WA: Microsoft Press, 2006
33. Messerschmitt, D., and Szyperski, C. Software Ecosystem. Cambridge: MIT Press, 2003
34. Mihm, J.; Loch, C.; and Huchzermeier, A. Problem-solving oscillations in complex projects. Management Science, 49, 6 (2003), 733-750
35. Nelson, K.M., and Cooprider, J.G. The contribution of shared knowledge to IS group performance. MIS Quarterly, 20, 4 (1996), 409-429
36. Nickerson, J., and Zenger, T. A knowledge-based theory of the firm-The problem-solving perspective. Organization Science, 15, 6 (2004), 617-632
37. Nidumolu, S. The effect of coordination and uncertainty on software project performance: Residual performance risk as an intervening variable. Information Systems Research, 6, 3 (1995), 191-219
38. Nonaka, I. A dynamic theory of organizational knowledge creation. Organization Science, 5, 1 (1994), 14-37
39. Ouchi, W. A conceptual framework for the design of organizational control mechanisms. Management Science, 25, 9 (1979), 833-848
40. Postrel, S. Islands of shared knowledge: Specialization and mutual understanding in problem solving teams. Organization Science, 13, 3 (2002), 303-320
41. Rowen, R. Software project management under incomplete and ambiguous specifications. IEEE Transactions on Engineering Management, 37, 1 (1990), 10-21
42. Sawyer, P.; Rayson, P.; and Cosh, K. Shallow knowledge as an aid to deep understanding in early-phase requirements engineering. IEEE Transactions on Software Engineering, 31, 11 (2005), 969-981
43. Shaft, T.M., and Vessey, I. The relevance of application domain knowledge: Characterizing the computer program comprehension process. Journal of Management Information Systems, 15, 1 (Summer 1998), 51-78
44. Shenhar, A., and Dvir, D. Reinventing Project Management. Boston: Harvard Business School Press, 2007
45. Simon, H. The Sciences of the Artificial, 2d ed. Cambridge: MIT Press, 1981
46. Smith, R., and Eppinger, S. Identifying controlling features of engineering design iteration. Management Science, 43, 3 (1997), 276-293
47. Smith, R., and Eppinger, S. A predictive model of sequential iteration in engineering design. Management Science, 43, 8 (1997), 1104-1120
48. Takeishi, A. Knowledge partitioning in the interfirm division of labor: The case of automotive product development. Organization Science, 13, 3 (2002), 321-338
49. Terwiesch, C., and Loch, C. Collaborative prototyping and the pricing of custom-designed products. Management Science, 50, 2 (2004), 145-158
50. Tiwana, A. Governance-knowledge fit in systems development projects. Information Systems Research, 20, 2 (2009), 180-197
51. Tiwana, A., and Keil, M. Does peripheral knowledge complement control? An empirical test in technology outsourcing alliances. Strategic Management Journal, 28, 6 (2007), 623-634
52. Van de Ven, A. Engaged Scholarship: A Guide for Organizational and Social Research. Oxford: Oxford University Press, 2007
53. Venkatraman, N. The concept of fit in strategy research: Toward verbal and statistical correspondence. Academy of Management Review, 14, 3 (1989), 423-444
54. Vessey, I., and Conger, S. Learning to specify information requirements: The relationship between application and methodology. Journal of Management Information Systems, 10, 2 (Fall 1993), 177-201
55. Volkema, R. Problem formulation in planning and design. Management Science, 29, 6 (1983), 639-652
56. von Hippel, E. Sticky information and the locus of problem solving: Implications for innovation. Management Science, 40, 4 (1994), 429-439
57. Wallace, L.; Keil, M.; and Rai, A. How software project risk affects project performance: An investigation of the dimensions of risk and an exploratory model. Decision Sciences, 35, 2 (2004), 289-322
58. Xu, P., and Ramesh, B. Software process tailoring: An empirical investigation. Journal of Management Information Systems, 24, 2 (Fall 2007), 293-328