Concluding Remarks

  • Carlo Caserio
  • Sara Trucco
Part of the Contributions to Management Science book series (MANAGEMENT SC.)


This chapter discusses the results of the theoretical and empirical analysis presented in the previous chapters of the manuscript. The limitations and further developments of the research were also presented. In general, our results show that information overload is less perceived than information underload in all the comparisons performed in the research. The empirical results of our research concerning the relationship between ERP systems and information overload/underload show that ERP systems do not affect the perception of information overload/underload. However, the empirical results show that respondents who adopt ERP perceive higher data accuracy, system reliability and, in general, a higher information processing capacity than do respondents who do not adopt an ERP. Furthermore, our results show that respondents who adopt BI systems do not perceive a different level of information overload/underload compared with respondents who do not adopt. However, a more detailed analysis shows that managers of companies adopting BI systems perceive a higher data accuracy, a higher level of information processing capacity, and a more regular reporting system, based on more systematic frequency. Empirical evidence on the effects of the simultaneous adoption of ERP and BI on information overload/underload and on the features of information flow show that respondents adopting both an ERP and a BI system do not perceive higher or lower information overload or information underload than do the other respondents. Finally, our results confirm prior studies on information processing capacity and information quality and suggest that reporting is one of the drivers of information quality.



The authors gratefully acknowledge the anonymous reviewers for the insightful suggestions provided to enhance the quality of this manuscript.

The authors also acknowledge the assistant editor of this book series, Maria Cristina Acocella, along with the editorial staff of Springer for their professional and proficient involvement in the production of this book.

The authors also gratefully acknowledge the Università degli Studi Internazionali di Roma (UNINT), which has made this study possible by providing financial support.

This study is part of a larger project on accounting information systems.


  1. Agnew JR, Szykman LR (2005) Asset allocation and information overload: the influence of information display, asset choice, and investor experience. J Behav Finance 6:57–70CrossRefGoogle Scholar
  2. Al-Hakim L (2007) Information quality management: theory and applications. IGI GlobalGoogle Scholar
  3. Berthold H, Rösch P, Zöller S, et al (2010) An architecture for ad-hoc and collaborative business intelligence. In: Proceedings of the 2010 EDBT/ICDT workshops. ACM, p 13Google Scholar
  4. Bharadwaj AS (2000) A resource-based perspective on information technology capability and firm performance: an empirical investigation. MIS Q 169–196Google Scholar
  5. Bingi P, Sharma MK, Godla JK (1999) Critical issues affecting an ERP implementation. Manag 16:7–14Google Scholar
  6. Blanco S, Lesca H (1998) Business intelligence: integrating knowledge into the selection of early warning signals. In: Workshop on knowledge managementGoogle Scholar
  7. Bovee M, Srivastava RP, Mak B (2003) A conceptual framework and belief-function approach to assessing overall information quality. Int J Intell Syst 18:51–74CrossRefGoogle Scholar
  8. Boyer J, Frank B, Green B, et al (2010) Business intelligence strategy: a practical guide for achieving BI excellence. Mc PressGoogle Scholar
  9. Brien JA, Marakas GM (2009) Management information system. Galgotia Pubn L994 3Google Scholar
  10. Burkhard RA, Meier M (2005) Tube map visualization: evaluation of a novel knowledge visualization application for the transfer of knowledge in long-term projects. J UCS 11:473–494Google Scholar
  11. Burstein F, Holsapple C (2008) Handbook on decision support systems 2: variations. Springer Science & Business MediaGoogle Scholar
  12. Chandler JS (1982) A multiple criteria approach for evaluating information systems. MIS Q 61–74CrossRefGoogle Scholar
  13. Chapman CS, Kihn L-A (2009) Information system integration, enabling control and performance. Account Organ Soc 34:151–169. Scholar
  14. Corsi K, Trucco S (2016) The role of the CIOs on the IT management and firms’ performance: evidence in the Italian context. In: Strengthening information and control systems. Springer, pp 217–236Google Scholar
  15. da Costa RAG, Cugnasca CE (2010) Use of data warehouse to manage data from wireless sensors networks that monitor pollinators. In: 2010 Eleventh international conference on mobile data management (MDM). IEEE, pp 402–406Google Scholar
  16. Dell’Orco M, Giordano R (2003) Web community of agents for the integrated logistics of industrial districts. In: Proceedings of the 36th annual Hawaii international conference on system sciences, 2003. IEEE, p 10Google Scholar
  17. DeLone WH, McLean ER (1992) Information systems success: the quest for the dependent variable. Inf Syst Res 3:60–95CrossRefGoogle Scholar
  18. Eckerson WW (2005) The keys to enterprise business intelligence: critical success factors. TDWI RepGoogle Scholar
  19. Eppler MJ, Mengis J (2004) The concept of information overload: a review of literature from organization science, accounting, marketing, MIS, and related disciplines. Inf Soc 20:325–344CrossRefGoogle Scholar
  20. Evans JR, Lindsay WM (2002) The management and control of quality. South-Western, Cincinnati, OHGoogle Scholar
  21. Farhoomand AF, Drury DH (2002) OVERLOAD. Commun ACM 45:127CrossRefGoogle Scholar
  22. Foshay N, Kuziemsky C (2014) Towards an implementation framework for business intelligence in healthcare. Int J Inf Manag 34:20–27CrossRefGoogle Scholar
  23. Gottschalk P (1999) Strategic management of IS/IT functions: the role of the CIO in Norwegian organisations. Int J Inf Manag 19:389–399CrossRefGoogle Scholar
  24. Hitt LM, Wu DJ, Z X (2002) Investment in enterprise resource planning: Business impact and productivity measures. J Manag Inf Syst 19:71–98CrossRefGoogle Scholar
  25. Ho J, Tang R (2001) Towards an optimal resolution to information overload: an infomediary approach. In Proceedings of the 2001 international ACM SIGGROUP conference on supporting group work, September, pp 91–96Google Scholar
  26. Horvath L (2001) Collaboration: the key to value creation in supply chain management. Supply Chain Manag Int J 6:205–207CrossRefGoogle Scholar
  27. Imran M, Tanveer A (2015) Decision support systems: creating value for marketing decisions in the pharmaceutical industry. Eur J Bus Innov Res 3:46–65Google Scholar
  28. Juran JM (1992) Juran on quality by design: the new steps for planning quality into goods and services. Simon and SchusterGoogle Scholar
  29. Kahn BK, Strong DM, Wang RY (2002) Information quality benchmarks: product and service performance. Commun ACM 45:184–192CrossRefGoogle Scholar
  30. Karr-Wisniewski P, Lu Y (2010) When more is too much: operationalizing technology overload and exploring its impact on knowledge worker productivity. Comput Hum Behav 26:1061–1072CrossRefGoogle Scholar
  31. Kelly D (2005) Business Intelligence: the smart way to track academic collections. Educ Q 28:48Google Scholar
  32. Kock N (2000) Information overload and worker performance: a process-centered view. Knowl Process Manag 7:256CrossRefGoogle Scholar
  33. Lee AR, Son S-M, Kim KK (2016) Information and communication technology overload and social networking service fatigue: a stress perspective. Comput Hum Behav 55:51–61CrossRefGoogle Scholar
  34. Lee MR, Lan Y (2007) From Web 2.0 to conversational knowledge management: towards collaborative intelligence. J Entrep Res 2:47–62Google Scholar
  35. Lee YW, Strong DM, Kahn BK, Wang RY (2002) AIMQ: a methodology for information quality assessment. Inf Manag 40:133–146CrossRefGoogle Scholar
  36. Lee Z, Lee J (2000) An ERP implementation case study from a knowledge transfer perspective. J Inf Technol 15:281–288CrossRefGoogle Scholar
  37. Letsholo RG, Pretorius MP (2016) Investigating managerial practices for data and information overload in decision making. J Contemp Manag 13:767–792Google Scholar
  38. Li X, Qu H, Zhu Z, Han Y (2009) A systematic information collection method for business intelligence. In: International conference on electronic commerce and business intelligence, ECBI 2009. IEEE, pp 116–119Google Scholar
  39. Marchi L (1993) I sistemi informativi aziendali. GiuffrèGoogle Scholar
  40. Mauldin EG, Richtermeyer SB (2004) An analysis of ERP annual report disclosures. Int J Account Inf Syst 5:395–416. Scholar
  41. McClave JT, Benson PG, Sincich T (1998) A first course in business statisticsGoogle Scholar
  42. Melinat P, Kreuzkam T, Stamer D (2014) Information overload: a systematic literature review. In: International conference on business informatics research. Springer, pp 72–86Google Scholar
  43. Nelson RR, Todd PA, Wixom BH (2005) Antecedents of information and system quality: an empirical examination within the context of data warehousing. J Manag Inf Syst 21:199–235CrossRefGoogle Scholar
  44. Nita B (2015) Methodological issues of management reporting systems design. Res Pap Wroclaw Univ Econ Nauk Uniw Ekon We WroclawiuGoogle Scholar
  45. O’Brien JA, Marakas GM (2006) Management information systems. McGraw-Hill, IrwinGoogle Scholar
  46. O’Reilly CA (1980) Individuals and information overload in organizations: is more necessarily better? Acad Manage J 23:684–696CrossRefGoogle Scholar
  47. Piattini MG, Calero C, Genero MF (2012) Information and database quality. Springer Science & Business MediaGoogle Scholar
  48. Poston R, Grabski S (2001) Financial impacts of enterprise resource planning implementations. Int J Account Inf Syst 2:271–294. Scholar
  49. Ranjan J (2009) Business intelligence: concepts, components, techniques and benefits. J Theor Appl Inf Technol 9:60–70Google Scholar
  50. Reeves CA, Bednar DA (1994) Defining quality: alternatives and implications. Acad Manage Rev 19:419–445Google Scholar
  51. Robey D, Ross JW, Boudreau M-C (2002) Learning to implement enterprise systems: an exploratory study of the dialectics of change. J Manag Inf Syst 19:17–46CrossRefGoogle Scholar
  52. Sangster A, Leech SA, Grabski S (2009) ERP implementations and their impact upon management accountants. JISTEM-J Inf Syst Technol Manag 6:125–142Google Scholar
  53. Scapens RW, Jazayeri M (2003) ERP systems and management accounting change: opportunities or impacts? A research note. Eur Account Rev 12:201–233CrossRefGoogle Scholar
  54. Scheer A-W, Habermann F (2000) Enterprise resource planning: making ERP a success. Commun ACM 43:57–61CrossRefGoogle Scholar
  55. Shneiderman B (1996) The eyes have it: a task by data type taxonomy for information visualizations. In: Proceedings of IEEE symposium on visual languages, 1996. IEEE, pp 336–343Google Scholar
  56. Smith G, Ariyachandra T, Frolick M (2012) Business intelligence in the bayou: recovering costs in the wake. Organ Appl Bus Intell Manag Emerg Trends Emerg Trends 29Google Scholar
  57. Spira JB (2011) Overload! How too much information is hazardous to your organization. WileyGoogle Scholar
  58. Strong DM, Lee YW, Wang RY (1997) Data quality in context. Commun ACM 40:103–110CrossRefGoogle Scholar
  59. Stvilia B, Twidale MB, Smith LC, Gasser L (2005) Assessing information quality of a community-based encyclopedia. In: IQGoogle Scholar
  60. Swain MR, Haka SF (2000) Effects of information load on capital budgeting decisions. Behav Res Account 12:171Google Scholar
  61. Xu H, Horn Nord J, Brown N, Daryl Nord G (2002) Data quality issues in implementing an ERP. Ind Manag Data Syst 102:47–58CrossRefGoogle Scholar
  62. Yang X, Procopiuc CM, Srivastava D (2009) Summarizing relational databases. Proc VLDB Endow 2:634–645CrossRefGoogle Scholar
  63. Zeithaml VA, Parasuraman A, Berry LL (1990) Delivering quality services. N Y Free Press Career Dev 11:63–64Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of EconomicsUniversità degli Studi eCampusNovedrate (CO)Italy
  2. 2.Faculty of EconomicsUniversità degli Studi Internazionali di RomaRomeItaly

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