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Journal of the Knowledge Economy

, Volume 10, Issue 1, pp 104–125 | Cite as

Mind the Information Expectation Gap

  • Tomi RajalaEmail author
Article

Abstract

Information is valuable to decision makers in both public and private sectors. The New Public Management (NPM) reform in the public sector has stressed the importance of performance information to politicians, public managers, and citizens. Information economics has acknowledged the meaning of information as a market determinant. However, as a discipline, information economics has not developed a cost concept that describes the negative value of an incorrect decision caused by the non-use or misuse of information. A systematic theoretical approach describing the factors causing such non-use or misuse is also currently missing in information economics. This article aims to fill these two research gaps. It defines infonomic costs (ICs) as the negative value of information non-use or misuse, denoting the benefits lost by the decision maker. By conducting an exploratory literature review, another new concept called the information expectation gap (IEG) is created to depict why the non-use or misuse leading to ICs occurs. The IEG also explains how information and knowledge asymmetries come into existence. The conceptual work presented here offers novel understanding and terminology to both academics and practitioners. Practitioners can utilize the IEG concept in information system management because it displays several dysfunctions that they may face in their information systems. For academics, this research opens up new theoretical conversations about the different types of information system dysfunctions that cause market errors and adverse policy decisions.

Keywords

Infonomic costs Information expectation gap Information asymmetry Knowledge transfer Knowledge-sharing barrier 

References

  1. Adaval, R., & Wyer, R. S. (1998). The role of narratives in consumer information processing. Journal of Consumer Psychology, 7, 207–245.CrossRefGoogle Scholar
  2. Adelman, I. (1999). Fallacies in development theory and their implications for policy. In G. Meier & J. Stiglitz (Eds.), Frontiers of development economics. Washington: World Bank and Oxford University Press.Google Scholar
  3. Ahmad, N., Lodhi, M. S., Zaman, K., & Naseem, I. (2015). Knowledge management: a gateway for organizational performance. Journal of the Knowledge Economy, 7, 1–18.Google Scholar
  4. Akerlof, G. (1995). The market for “lemons”: quality uncertainty and the market mechanism. In S. Estrins’s & A. Marin’s (Eds.), Essential readings in economics (pp. 175–188). New York: St. Martin’s Press.CrossRefGoogle Scholar
  5. Asch, S. E. (1956). Studies of independence and conformity: I. A minority of one against a unanimous majority. Psychological monographs: general and applied, 70, 1–70.CrossRefGoogle Scholar
  6. Axelrod, R., & Cohen, M. (2008). Harnessing complexity: organizational implications of a scientific frontier. New York: Basic Books.Google Scholar
  7. Baumard, P. (1999). Tacit knowledge in organizations. London: SAGE Publications Ltd.Google Scholar
  8. Bonjour, L. (2010). Epistemology: classic problems and contemporary responses. Lanham: Rowman & Littlefield.Google Scholar
  9. Borgida, E., & Nisbett, R. E. (1977). The differential impact of abstract vs. concrete information on decisions. Journal of Applied Social Psychology, 7, 258–271.CrossRefGoogle Scholar
  10. Boulding, W., Morgan, R., & Staelin, R. (1997). Pulling the plug to stop the new product drain. Journal of Marketing Research, 34, 164–176.Google Scholar
  11. Campbell, M. C., & Kirmani, A. (2000). Consumers’ use of persuasion knowledge: the effects of accessibility and cognitive capacity on perceptions of an influence agent. Journal of Consumer Research, 27, 69–83.CrossRefGoogle Scholar
  12. Casey, C. J., Jr. (1980). Variation in accounting information load: the effect on loan officers’ predictions of bankruptcy. Accounting Review, 55, 36–49.Google Scholar
  13. Chang, K. H., & Gotcher, D. F. (2010). Conflict-coordination learning in marketing channel relationships: the distributor view. Industrial Marketing Management, 39, 287–297.CrossRefGoogle Scholar
  14. Chatman, J. A. (1989). Matching people and organizations: selection and socialization in public accounting firms. Administrative Science Quarterly, 36, 459–484.CrossRefGoogle Scholar
  15. Chewning, E. G., & Harrell, A. M. (1990). The effect of information load on decision makers’ cue utilization levels and decision quality in a financial distress decision task. Accounting, Organizations and Society, 15, 527–542.CrossRefGoogle Scholar
  16. Colarelli, S. M., Hechanova-Alampay, R., & Canali, K. G. (2002). Letters of recommendation: an evolutionary psychological perspective. Human Relations, 55, 315–344.CrossRefGoogle Scholar
  17. Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, 95–120.CrossRefGoogle Scholar
  18. Crowther, M. S., Keller, C. C., & Waddoups, G. L. (2004). Improving the quality and effectiveness of computer‐mediated instruction through usability evaluations. British Journal of Educational Technology, 35, 289–303.CrossRefGoogle Scholar
  19. Deary, I. J., Johnson, W., & Houlihan, L. M. (2009). Genetic foundations of human intelligence. Human Genetics, 126(1), 215–232.CrossRefGoogle Scholar
  20. Dermer, J. D. (1973). Cognitive characteristics and the perceived importance of information. Accounting Review, 48, 511–519.Google Scholar
  21. Diener, E. (2000). Subjective well-being. Social Indicators Research Series, 37, 11–58.CrossRefGoogle Scholar
  22. Dweck, C. S. (1999). Self-theories: their role in motivation, personality, and development. Philadelphia: Psychology Press.Google Scholar
  23. Elster, J. (1987). Solomonic judgments: against the best interest of the child. The University of Chicago Law Review, 54, 1–45.CrossRefGoogle Scholar
  24. Festinger, L. (1957). A theory of cognitive dissonance. Evanston: Row, Peterson.Google Scholar
  25. Fischer, G. (2012). Context-aware systems: the ‘right’ information, at the ‘right’ time, in the ‘right’ place, in the ‘right’ way, to the ‘right’ person. In Proceedings of the International Working Conference on Advanced Visual Interfaces in Capri Island (Naples), Italy (pp. 287–294).Google Scholar
  26. Fumagalli, R. (2013). The futile search for true utility. Economics and Philosophy, 29, 325–347.CrossRefGoogle Scholar
  27. Garrett, J. J. (2011). The elements of user experience: user-centered design for the web and beyond. Berkeley: New Riders.Google Scholar
  28. Girle, R. (2009). Modal logics and philosophy. Durham: Acumen.Google Scholar
  29. Goodwin, N. C. (1987). Functionality and usability. Communications of the ACM, 30, 229–233.CrossRefGoogle Scholar
  30. Greenwald, B. C., & Stiglitz, J. E. (1986). Externalities in economies with imperfect information and incomplete markets. The Quarterly Journal of Economics, 101, 229–264.CrossRefGoogle Scholar
  31. Guba, E. G., & Lincoln, Y. S. (1998). Competing paradigms in qualitative research. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (3rd ed., pp. 191–215). Thousand Oaks: Sage Publications.Google Scholar
  32. Hahn, M., Lawson, R., & Lee, Y. G. (1992). The effects of time pressure and information load on decision quality. Psychology & Marketing, 9, 365–378.CrossRefGoogle Scholar
  33. Hart, S. G. (1986). Theory and measurement of human workload. In J. Zeidner (Ed.), Human productivity enhancement: training and human factors in system design (pp. 396–456). New York: Praeger.Google Scholar
  34. Hayek, F. A. V. (1967). Studies in philosophy, politics and economics. London: Routledge & K. Paul.CrossRefGoogle Scholar
  35. Herr, P. M., Kardes, F. R., & Kim, J. (1991). Effects of word-of-mouth and product-attribute information on persuasion: an accessibility-diagnosticity perspective. Journal of Consumer Research, 17, 454–462.CrossRefGoogle Scholar
  36. Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart, exercise your heart: exercise effects on brain and cognition. Nature Reviews Neuroscience, 9, 58–65.CrossRefGoogle Scholar
  37. Hood, C. (2010). The blame game: spin, bureaucracy, and self-preservation in government. Princeton: Princeton University Press.CrossRefGoogle Scholar
  38. International Accounting Standards Board (IASB). (2008). An improved conceptual framework for financial reporting. London: International Accounting Standards Committee Foundation (IASCF).Google Scholar
  39. IASB. (2010). The conceptual framework for financial reporting 2010. London: IASCF.Google Scholar
  40. Iselin, E. R. (1988). The effects of information load and information diversity on decision quality in a structured decision task. Accounting, Organizations and Society, 13, 147–164.CrossRefGoogle Scholar
  41. Jaffe, A. B., Newell, R. G., & Stavins, R. N. (2005). A tale of two market failures: technology and environmental policy. Ecological Economics, 54, 164–174.CrossRefGoogle Scholar
  42. Janicot, C., Mignon, S., & Walliser, E. (2016). Information process and value creation: an experimental study. Journal of the Knowledge Economy, 7(1), 276–291.CrossRefGoogle Scholar
  43. Jansen, E. P. (2008). New public management: perspectives on performance and the use of performance information. Financial Accountability & Management, 24(2), 169–191.CrossRefGoogle Scholar
  44. Joos, I. M. (2000). Computers in small bytes: a workbook for healthcare professionals. Boston: Jones and Bartlett.Google Scholar
  45. Jung, W., Olfman, L., Ryan, T., & Park, Y. (2005). An experimental study of the effects of representational data quality on decision performance. In Proceedings of the American Conference on Information Systems (AMCIS) 2005 Conference in Omaha.Google Scholar
  46. Kirk, N. (2006). Perceptions of the true and fair view concept: an empirical investigation. Abacus, 42(2), 205–235.CrossRefGoogle Scholar
  47. Klein, P. (1998). Foundationalism and the infinite regress of reasons. Philosophy and Phenomenological Research, 58, 919–925.CrossRefGoogle Scholar
  48. Koivunen, H. (1997). Hiljainen tieto. Helsinki: Otava.Google Scholar
  49. Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: how difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77, 30–46.Google Scholar
  50. Levin, I. P., & Gaeth, G. J. (1988). How consumers are affected by the framing of attribute information before and after consuming the product. Journal of Consumer Research, 15, 374–378.CrossRefGoogle Scholar
  51. Lindblom, C. E. (1959). The science of “muddling through”. Public Administration Review, 19, 79–88.CrossRefGoogle Scholar
  52. Lindblom, C. E., & Cohen, D. K. (1979). Usable knowledge: social science and social problem solving. New Haven: Yale University Press.Google Scholar
  53. Macintosh, G., & Gentry, J. W. (1999). Decision making in personal selling: testing the “KISS principle”. Psychology & Marketing, 16(5), 393–408.CrossRefGoogle Scholar
  54. Maker, J. K., & Hu, M. (2003). The priming of material values on consumer information processing of print advertisements. Journal of Current Issues & Research in Advertising, 25, 21–30.CrossRefGoogle Scholar
  55. Malhotra, N. K. (1982). Information load and consumer decision making. Journal of Consumer Research, 8, 419–430.CrossRefGoogle Scholar
  56. Malhotra, N. K., Jain, A. K., & Lagakos, S. W. (1982). The information overload controversy: an alternative viewpoint. The Journal of Marketing, 46, 27–37.CrossRefGoogle Scholar
  57. March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2, 71–87.CrossRefGoogle Scholar
  58. Markie, P. (2004). Rationalism vs. empiricism. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Summer 2015th ed.). http://plato.stanford.edu/archives/sum2015/entries/rationalism-empiricism/.20.12.2016.Google Scholar
  59. Milgrom, P., & Roberts, J. (1986). Price and advertising signals of product quality. The Journal of Political Economy, 4, 796–821.CrossRefGoogle Scholar
  60. Miller, H. (1996). The multiple dimensions of information quality. Information Systems Management, 13, 79–82.CrossRefGoogle Scholar
  61. Mishkin, F. S. (2004). Can central bank transparency go too far? (No. w10829). In C. Kent & S. Guttmann (Eds.), The future of inflation targeting Reserve Bank of Australia. Sydney: J.S. McMillan Printing Group.Google Scholar
  62. Moore, R. F. (1996). Caring for identified versus statistical lives: an evolutionary view of medical distributive justice. Ethology and Sociobiology, 17, 379–401.CrossRefGoogle Scholar
  63. Morgan, G., & Smircich, L. (1980). The case for qualitative research. Academy of Management Review, 5, 491–500.CrossRefGoogle Scholar
  64. Mortimer, J. T., & Lorence, J. (1979). Work experience and occupational value socialization: a longitudinal study. American Journal of Sociology, 84, 1361–1385.CrossRefGoogle Scholar
  65. Naciri, A. (2009). Internal and external aspects of corporate governance. New York: Routledge.CrossRefGoogle Scholar
  66. Neisser, U., Boodoo, G., Bouchard, T. J., Jr., Boykin, A. W., Brody, N., Ceci, S. J., & Sternberg, R. J. (1996). Intelligence: knowns and unknowns. American Psychologist, 51, 77–101.CrossRefGoogle Scholar
  67. Nelson, P. (1970). Information and consumer behavior. Journal of Political Economy, 78, 311–329.CrossRefGoogle Scholar
  68. Nielsen, J. (1993). Usability engineering. Boston: Academic.CrossRefGoogle Scholar
  69. Niiniluoto, I. (1996). Informaatio, tieto ja yhteiskunta: Filosofinen käsiteanalyysi. Helsinki: Edita.Google Scholar
  70. Nordin, S., Heiskanen, J., & Niiniluoto, I. (1999). Filosofian historia: Länsimaisen järjen seikkailut thaleesta postmodernismiin. Oulu: Pohjoinen.Google Scholar
  71. Nyhan, B., & Reifler, J. (2010). When corrections fail: the persistence of political misperceptions. Political Behavior, 32, 303–330.CrossRefGoogle Scholar
  72. Obeso, M., & Sarabia, M. (2016). Knowledge and enterprises in developing countries: evidences from Chile. Journal of the Knowledge Economy. doi: 10.1007/s13132-016-0374-8.
  73. O’Reilly, C. A. (1980). Individuals-and-information overload in organizations: is more necessarily better? Academy of Management Journal, 23, 684–696.CrossRefGoogle Scholar
  74. O’Reilly, C. A. (1982). Variations in decision makers’ use of information sources: the impact of quality and accessibility of information. Academy of Management Journal, 25, 756–771.Google Scholar
  75. Peirce, C. S. (1877). The fixation of belief. Popular Science Monthly, 12, 1–15.Google Scholar
  76. Peirce, C. S. (1998). The essential peirce: selected philosophical writings. Bloomington: Indiana University Press.Google Scholar
  77. Plomin, R., & Spinath, F. M. (2004). Intelligence: genetics, genes, and genomics. Journal of Personality and Social Psychology, 86, 112–129.CrossRefGoogle Scholar
  78. Polanyi, M. (2009). The tacit dimension. Chicago: University of Chicago Press.Google Scholar
  79. Powell, W. W., & Snellman, K. (2004). The knowledge economy. Annual Review of Sociology, 30, 199–220.CrossRefGoogle Scholar
  80. Roto, V., Law, E., Vermeeren, A., & Hoonhout, J. (2011). User experience white paper. Bringing clarity to the concept of user experience. Leibniz: Schloss Dagstuhl.Google Scholar
  81. Schick, A. G., Gordon, L. A., & Haka, S. (1990). Information overload: a temporal approach. Accounting, Organizations and Society, 15, 199–220.CrossRefGoogle Scholar
  82. Schul, Y., Mayo, R., & Burnstein, E. (2004). Encoding under trust and distrust: the spontaneous activation of incongruent cognitions. Journal of Personality and Social Psychology, 86, 668–679.CrossRefGoogle Scholar
  83. Schwartz, B. (2004). The paradox of choice: why more is less. New York: Ecco.Google Scholar
  84. Shields, M. D. (1980). Some effects of information load on search patterns used to analyze performance reports. Accounting, Organizations and Society, 5(4), 429–442.CrossRefGoogle Scholar
  85. Speier, C., Valacich, J. S., & Vessey, I. (1999). The influence of task interruption on individual decision making: an information overload perspective. Decision Sciences, 30, 337–360.CrossRefGoogle Scholar
  86. Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87, 355–374.CrossRefGoogle Scholar
  87. Stacey, R. D. (1996). Complexity and creativity in organizations. San Francisco: Berrett-Koehler Publishers.Google Scholar
  88. Sternberg, R. J. (2012). Intelligence. Wiley Interdisciplinary Reviews: Cognitive Science, 3, 501–511.Google Scholar
  89. Stigler, G. J. (1961). The economics of information. The Journal of Political Economy, 69, 213–225.CrossRefGoogle Scholar
  90. Stiglitz, J. E. (1975). The theory of “screening”, education, and the distribution of income. The American Economic Review, 65(3), 283–300.Google Scholar
  91. Stiglitz, J. E. (2002). Information and the change in the paradigm in economics. The American Economic Review, 92(3), 460–501.CrossRefGoogle Scholar
  92. Stone, P. (2014). Non-reasoned decision-making. Economics and Philosophy, 30, 195–214.CrossRefGoogle Scholar
  93. Taber, C. S., & Lodge, M. (2006). Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science, 50(3), 755–769.CrossRefGoogle Scholar
  94. Taylor, R. N., & Dunnette, M. D. (1974). Influence of dogmatism, risk-taking propensity, and intelligence on decision-making strategies for a sample of industrial managers. Journal of Applied Psychology, 59, 420–423.CrossRefGoogle Scholar
  95. Terano, T. (2008). Beyond the KISS principle for agent-based social simulation. Journal of Socio-informatics, 1(1), 175–187.Google Scholar
  96. Terhune, K. W., & Kennedy, J. L. (1963). Exploratory analysis of a research and development game. Princeton: Princeton University Press.CrossRefGoogle Scholar
  97. Tsoukas, H. (2004). Complex knowledge: studies in organizational epistemology. Oxford: Oxford University Press.Google Scholar
  98. Van Dooren, W., & Van In, W. S. (2008). Performance information in the public sector: how it is used. Basingstoke: Palgrave Macmillan.CrossRefGoogle Scholar
  99. Van Maanen, J., & Schein, E. H. (1979). Toward a theory of organizational socialization. Cambridge: MIT Press.Google Scholar
  100. Vessey, I. (1991). Cognitive fit: a theory-based analysis of the graphs versus tables literature. Decision Sciences, 22, 219–240.CrossRefGoogle Scholar
  101. Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: what data quality means to data consumers. Journal of Management Information Systems, 12, 5–33.CrossRefGoogle Scholar
  102. Wu, X. Y., & Wang, P. (2015). Measuring network user psychological experience quality. In K. Chan (Ed.), Proceedings of the 2015 International Conference on Testing and Measurement: Techniques and Applications (TMTA2015). (TMTA2015), 16–17 January 2015, Phuket Island, Thailand.Google Scholar

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© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.School of Management (JKK)University of TampereTampereFinland

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