An empirical investigation of end-user query development: The effects of improved model expressiveness vs. complexity

Information Systems Research

Volumn 20, Issue 4, 2009, Pages 565-584

  Bowen, Paul L ^a   O'Farrell, Robert A ^b   Rohde, Fiona H ^b  

^a FLORIDA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

Expressiveness; Logical data models; Ontological clarity; Ontology; Parsimony; Scalability

Indexed keywords

ONTOLOGY; SCALABILITY;

BOUNDED RATIONALITY; CONCEPTUAL DATA MODELS; EMPIRICAL INVESTIGATION; EXPRESSIVENESS; LOGICAL DATA MODELS; MODELING EXPRESSIVENESS; ONTOLOGICAL CLARITY; PARSIMONY;

PROBLEM SOLVING;

EID: 77954266297     PISSN: 10477047     EISSN: 15265536     Source Type: Journal    
DOI: 10.1287/isre.1080.0181     Document Type: Article

References (53)

1. Akaike, H. 1974. A new look at the statistical model identification. IEEE Trans. Automatic Control 19 716-723.
2. Akiyama, F. 1971. An example of software system debugging. Inform. Processing 71 353-379.
3. Axelsen, M., A. F. Borthick, P. L. Bowen. 2001. A model for and the effects of information request ambiguity and end user query performance. Proc. Internat. Conf. Inform. Systems, New Orleans, LA, Association for Information Systems, Atlanta, 537-542.
4. Balzer, R. 1979. An implementation methodology for semantic data base models. Proc. Internat. Conf. Entity Relationship Approach to Systems Anal. Design, ACM-SIGMOD, Los Angeles, 433-444.
5. Batra, D. 1993. A framework for studying human error behavior in conceptual database modeling. Inform. Management 25 121-131.
6. Blackwell, D. 1953. Equivalent comparisons of experiments. Ann. Math. Statist. 24 265-73.
7. Bodart, F., M. Sim, A. Patel, R. Weber. 2001. Should optional properties be used in conceptual modelling? A theory and three empirical tests. Inform. Systems Res. 12(4) 384-405.
8. Borthick, A. F., P. L. Bowen, D. R. Jones, M. H. K. Tse. 2001a. The effects of information request ambiguity and construct incongruence on query development. Decision Support Systems 32(1) 3-25.
9. Borthick, A. F., P. L. Bowen, S. Liew, F. H. Rohde. 2001b. The effects of normalization on query developer query errors: An experimental evaluation. Internat. J. Accounting Inform. Systems 2(4) 195-223.
10. Bowen, P. L., R. A. O'Farrell, F. H. Rohde. 2006. Analysis of competing data structures: Does ontological clarity produce better end user query performance. J. Assoc. Inform. Systems 7(8) 514-544.
11. Bunge, M. 1977. Treatise on Basic Philosophy: Volume 3: Ontology I: The Furniture of the World. Reidel, Boston.
12. Burton-Jones, A., R. Weber. 1998. Understanding relationships with attributes in entity-relationship diagrams. Internat. Conf. Inform. Systems, Helsinki, Finland. Association for Information Systems, Atlanta, 214-228.
13. Campbell, D. J. 1988. Task complexity: A review and analysis. Acad. Management Rev. 13(1) 40-52.
14. Chan, H. C., K. K. Wei, K. L. Siau. 1993. User-database interface: The effect of abstraction level on query performance: A field experiment. MIS Quart. 17(4) 441-464.
15. Chan, H. C., B. C. Y. Tan, K. K. Wei. 1999. Three important determinants of user performance for database retrieval. Internat. J. Human Comput. Stud. 51(1) 895-918.
16. Chan, H. C., K. L. Siau, K. K. Wei. 2004. Effects of query complexity and learning on novice user query performance with conceptual and logical database interfaces. IEEE Trans. Systems, Man Cybernetics, Part A (Systems Humans) 34(2) 276-281.
17. Crossland, M. D., W. C. Perkins, B. E. Wynne. 1995. Spatial decision support systems: An overview of technology and a test of efficacy. Decision Support Systems 14 219-235.
18. Fenton, N. E., M. Neil. 1999. A critique of software defect prediction models. IEEE Trans. Software Engrg. 25(5) 675-689.
19. Gardner, W. B., M. Serra. 1997. An object-oriented layered approach to interfaces for hardware/software codesign of embedded systems. Thirty-First Annual Hawaii Internat. Conf. System Sci., Honolulu, 197-203.
20. Gemino, A. 1998. To be or may to be: An empirical comparison of mandatory and optional properties in conceptual modelling. Proc. Annual Conf. Admin. Sci. Assoc. Canada, Saskatoon, Saskatchewan, Canada. Administration Science Association: Information Systems Division, 33-44.
21. Gemino, A., Y. Wand. 2005. Complexity and clarity in conceptual modelling: Comparison of mandatory and optional properties. Data Knowledge Engrg. 55 301-326.
22. Green, P., M. Rosemann. 2004. Applying ontologies to business and systems modelling techniques and perspectives: Lessons learned. J. Database Management 15(2) 105-117.
23. Halstead, M. H. 1975. Elements of Software Science. Elsevier, North Holland, New York.
24. Hansen, M. H., B. Yu. 2001. Model selection and the principle of minimum description length. J. Amer. Statist. Assoc. 96(454) 746-774.
25. Hilton, R. W. 1979. The determinants of information system value: An illustrative analysis. J. Accounting Res. 17 411-35.
26. Hilton, R. W. 1980. Integrating normative and descriptive theories of information processing. J. Accounting Res. 18(2) 477-505.
27. Hoffer, J. A., J. F. George, J. S. Valacich. 2004. Modern Systems Analysis and Design, 4th ed. Addison Wesley Longman, Reading, MA.
28. Jih, K., D. Bradbard, C. Snyder, N. Thompson. 1989. The effects of relational and entity-relationship data models on query performance of query developers. Internat. J. Man-Machine Stud. 31(3) 257-267.
29. Khatri, V., S. Ram, R. T. Snodgrass. 2004. Augmenting a conceptual model with geospatio-temporal annotations. IEEE Trans. Knowledge Data Engrg. 16(11) 1324-1338.
30. Khatri, V., I. Vessey, S. Ram, V. Ramesh. 2006. Cognitive fit between conceptual schemas and internal problem representations: The case of geospatio-temporal conceptual schema comprehension. IEEE Trans. Professional Comm. 49(2) 109-127.
31. Knoblich, G., S. Ohlsson, H. Haider, D. Phenius. 1999. Constraint relaxation and chunk decomposition in insight problem solving. J. Experiment. Psych. Learn., Memory, Cognition 25 1534-1556.
32. Kottemann, J. E., W. E. Remus. 1989. A study of the relationship between decision model naturalness and performance. MIS Quart. 23(2) 171-181.
33. Lipow, M. 1982. Number of faults per line of code. IEEE Trans. Software Engrg. 8(4) 437-439.
34. March, J., H. A. Simon. 1958. Organizations. John Wiley, New York.
35. Mennecke, B. E., M. D. Crossland, B. L. Killingsworth. 2000. Is a map more than a picture? The role of SDSS technology, subject characteristics and problem complexity on map reading and problem solving. MIS Quart. 24(4) 601-629.
36. Ormerod, T. C., J. N. MacGregor, E. P. Chronicle. 2002. Dynamics and constraints in insight problem solving. J. Experiment. Psych. Learn., Memory, Cognition 28(4) 791-799.
37. Owei, V., S. B. Navathe, S. R. Hyeun. 2002. An abbreviated concept-based query language and its exploratory evaluation. J. Systems Software 63(1) 45-67.
38. Purao, S., V. C. Storey, T. Han. 2003. Improving analysis pattern reuse in conceptual design: Augmenting automated processes with supervised learning. Inform. Systems Res. 14(3) 269-290.
39. Rissanen, J. 1978. Modeling by shortest data description. Automatica 14 465-471.
40. Rho, S., S. T. March. 1997. An analysis of semantic overload in database access systems using multi-table query formulation. J. Database Management 8(2) 3-14.
41. Schwarz, G. 1978. Estimating the dimension of a model. Ann. Statist. 6 461-464.
42. Shoval, P., I. Frumermann. 1994. OO and EER conceptual schemas: A comparison of user comprehension. J. Database Management 5(4) 28-38.
43. Simon, H. A. 1957. Models of Man. John Wiley and Sons, New York.
44. Stabell, C. 1983. A Decision-Oriented Approach to Building DSS in Building Decision Support Systems. J. Bennett, ed. Addison-Wesley, Reading, MA.
45. Suh, K. S., A. M. Jenkins. 1992. A comparison of linear keyword and restricted natural language database interfaces for novice users. Inform. Systems Res. 3(3) 252-272.
46. Vessey, I. 1991. Cognitive fit: A theory-based analysis of graphs vs. tables literature. Decision Sci. 22(2) 219-240.
47. Wand, Y., R. Weber. 1993. On the ontological expressiveness of information system analysis and design grammars. J. Inform. Systems 4(4) 299-330.
48. Wand, Y., V. C. Storey, R. Weber. 1999. An ontological analysis of the relationship construct in conceptual modelling. ACM Trans. Database Systems 24 494-528.
49. Weber, R. 1997. Ontological Foundations of Information Systems. Coopers and Lybrand, Melbourne, Australia.
50. Weber, R. 2003. Conceptual modelling and ontology: Possibilities and pitfalls. J. Database Management 14(3) 1-20.
51. Wickens, C. D., C. M. Carswell. 1995. The proximity principle: Its psychological foundation and relevance to display design. Human Factors 37(3) 473-494.
52. Wood, R. E. 1986. Task complexity: Definition of the construct. Organ. Behav. Human Decision Processes 37 60-82.
53. Young, G. K., S. T. March. 1995. Comparing data modeling formalisms. Comm. ACM 38(6) 103-115.