Table Of ContentContributions to Management Science
Carlo Caserio · Sara Trucco
Enterprise Resource
Planning and
Business Intelligence
Systems for
Information Quality
An Empirical Analysis in the Italian
Setting
Contributions to Management Science
More information about this series at http://www.springer.com/series/1505
Carlo Caserio Sara Trucco
(cid:129)
Enterprise Resource Planning
and Business Intelligence
Systems for Information
Quality
An Empirical Analysis in the Italian Setting
123
CarloCaserio SaraTrucco
Faculty of Economics Faculty of Economics
Universitàdegli Studi eCampus Universitàdegli Studi Internazionali
Novedrate diRoma
Italy Rome
Italy
ISSN 1431-1941 ISSN 2197-716X (electronic)
Contributions toManagement Science
ISBN978-3-319-77678-1 ISBN978-3-319-77679-8 (eBook)
https://doi.org/10.1007/978-3-319-77679-8
LibraryofCongressControlNumber:2018936625
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To my family
Carlo Caserio
To my Mom and Dad
Sara Trucco
Preface
Nowadays, Information Technology (IT) innovations, the advent of the Internet,
and the ease offinding and sharing information are all elements that contribute to
obtaining overwhelming amounts of data and information. On the one hand,
managers can now easily find and store information, and on the other hand, this
hyper-amount of data does not allow us to distinguish between “good” and “bad”
information. Furthermore, the data and information stored in enterprise databases
maybeobsolete,inaccurate,irrelevant,orpartial.Inotherwords,companiesdonot
finditdifficulttoacquireandstoreahuge“quantity”ofdataandinformation.Their
probleminsteadistoobtainanadequatelevelof“quality”ofdataandinformation.
The point is that the increased volume of data and information can undermine the
capacityofcompaniestodiscernqualityfromnon-qualitydataandinformation,and
this difficulty is even more crucial when we consider that we are living in an
information economy where data, information, and knowledge become extremely
strategic for companies. Therefore, the quality of information deserves particular
attention.
Although IT has played a key role in bringing about information overload and
underload, possible solutions to these phenomena are still being sought in the IT
field. Integrated systems, data management systems, data warehousing, data min-
ing, and knowledge discovery tools are some examples of IT solutions that com-
panies are adopting to deal with information overload/underload. One of the most
effectivesolutionsseemstobetheimplementationofEnterpriseResourcePlanning
(ERP) systems, which improve data quality, data integrity, and system integration.
Inadditiontoimprovingdataqualityandsystemintegration,companiesalsoaim
atimprovingtheircapacitytoperformdataanalysis.Asamatteroffact,inorderto
pursue the objective of improving the quality of information, companies need to
pay attention both to the quality of incoming data and to the capacity to analyze it
anddelivertheresultinginformationtotherightperson,attherighttime.Therefore,
Business Intelligence (BI) systems are another important solution that companies
usetoimprovetheirdata analysis andprocessingcapabilities andtorecognizeand
select relevant data for a more effective decision-making process.
vii
viii Preface
Thismanuscriptwillexamine,throughanempiricalanalysis,theroleplayedby
ERP and BI systems in reducing or managing information overload/underload and
thus in improving the information quality perceived by the Italian manager. The
research is based on the idea that the improvement of information systems,
achievablebymeansofERPandBIsystems,may reduceoreliminateinformation
overload/underload. We also investigate whether the combined adoption of ERP
and BI systems is more effective in dealing with information overload/underload
thanwouldbethesingleadoptionofERPorBIsystems.Furthermore,theresearch
presented in this book examines the influence that ERP and BI systems may have
on the features of information flow—such as information processing capacity,
communication and reporting, the frequency of meetings, and information sharing
—and, in turn, the influence of information flow features on information quality.
Theresearchwas made possible bythe financialsupportoftheUniversità degli
Studi Internazionali di Roma (UNINT).
This study is part of a larger project on accounting information systems.
Novedrate, Italy Carlo Caserio
Rome, Italy Sara Trucco
Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 A Brief Overview of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Theoretical Contributions of the Present Work . . . . . . . . . . . . . . . 3
1.3 Managerial Implications of the Present Work. . . . . . . . . . . . . . . . 5
1.4 Structure of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2 Enterprise Resource Planning Systems . . . . . . . . . . . . . . . . . . . . . . . 13
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2 The Evolution of ERP Systems. . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3 Information Quality and ERP . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3.1 Information Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3.2 ERP System for Information Quality. . . . . . . . . . . . . . . . . 21
2.4 Critical Success Factor for ERP Implementation. . . . . . . . . . . . . . 23
2.5 Critical Success Factors for ERP Post-implementation . . . . . . . . . 26
2.6 Advantages and Disadvantages of ERPs . . . . . . . . . . . . . . . . . . . 27
2.6.1 Potential Benefits of ERP Adoption . . . . . . . . . . . . . . . . . 27
2.6.2 A Framework for Classifying the Benefits of ERP
Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.6.3 Potential Disadvantages of ERP Adoption. . . . . . . . . . . . . 31
2.7 ERP as a Driver of Alignment Between Management
Accounting Information and Financial Accounting
Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.8 The Managerial Role of the Chief Information Officer . . . . . . . . . 33
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3 Business Intelligence Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.2 Business Intelligence and Companies Needs. . . . . . . . . . . . . . . . . 44
3.3 BI for Management Information Systems Needs. . . . . . . . . . . . . . 48
ix
x Contents
3.3.1 Alignment to Group Logics . . . . . . . . . . . . . . . . . . . . . . . 48
3.3.2 Coordination and Technical-Organizational
Integration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.3.3 Improvement of Data Management and Decision
Support Information. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.3.4 Improvement in Communications . . . . . . . . . . . . . . . . . . . 53
3.4 BI for Strategic Planning Needs . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.4.1 Monitoring of Environmental Signals . . . . . . . . . . . . . . . . 55
3.4.2 Planning and Control Requirements . . . . . . . . . . . . . . . . . 57
3.4.3 Innovative BI Tools for the Adaptation
to Environmental Conditions . . . . . . . . . . . . . . . . . . . . . . 59
3.5 BI for Marketing Needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.6 BI for Regulations and Fraud Detection Needs. . . . . . . . . . . . . . . 61
3.7 Critical Success Factors of BI Implementation and Adoption . . . . 62
3.8 BI Maturity Models and Lifecycle. . . . . . . . . . . . . . . . . . . . . . . . 65
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
4 ERP and BI as Tools to Improve Information Quality
in the Italian Setting: The Research Design . . . . . . . . . . . . . . . . . . . 75
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.2 Literature Review Supporting the Research Design. . . . . . . . . . . . 76
4.2.1 Literature Review on Information Overload
and Information Underload. . . . . . . . . . . . . . . . . . . . . . . . 76
4.2.2 Links Between Information Overload/Underload
and ERP Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
4.2.3 Links Between Features of Information Flow
and ERP Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
4.2.4 Links Between Information Overload/Underload
and Business Intelligence Systems . . . . . . . . . . . . . . . . . . 80
4.2.5 Links Between Features of Information Flow and
Business Intelligence Systems . . . . . . . . . . . . . . . . . . . . . 82
4.2.6 The Combined Use of ERP and Business Intelligence:
Information Overload/Underload and Features
of Information Flow. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.2.7 Literature Review on Information Quality . . . . . . . . . . . . . 84
4.2.8 Links between Features of Information Flow and
Information Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
4.3 Sample Selection and Data Collection . . . . . . . . . . . . . . . . . . . . . 89
4.4 Variable Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
4.4.1 Research Variable Measurement. . . . . . . . . . . . . . . . . . . . 90
4.4.2 Variable Measurement: Control Variables . . . . . . . . . . . . . 94
4.5 Factor Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
