Skip to main content
SpringerLink
Log in

Information and data quality in business networking: a key concept for enterprises in its early stages of development

  • Position Paper
  • Published:
Electronic Markets Aims and scope Submit manuscript

Abstract

Information and data of high quality are critical for successful business performance in general and Business Networking in particular. As the trend toward sharing information between business partners and value networks is still increasing, the position paper aims at providing a comprehensive perspective on the state of research with regard to information and data quality in Business Networking. The paper shows that much has been achieved, but that fundamental aspects still remain unaddressed. Based on the results of a literature review, the paper identifies consequential areas of research and makes six propositions for future research. In doing so, the position paper aims at offering novel perspectives and at introducing new areas of research in a field of particularly high relevance in the networked business and electronic markets domain.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. See http://ejournals.ebsco.com/home.asp.

  2. See http://www.emeraldinsight.com/.

  3. See http://aisel.aisnet.org/.

  4. Available under: http://mitiq.mit.edu/iciq/iqproceedings.aspx.

  5. See http://www.avox.info/.

  6. See http://www.bvdinfo.com.

  7. See http://www.dnb.com.

  8. See http://www.gs1.org/.

References

  • Allemang, D. (2010). SemanticWeb and the linked data enterprise. In D. Wood (Ed.), Linking enterprise data (pp. 3–23). Berlin: Springer. doi:10.1007/978-1-4419-7665-9_1.

    Chapter  Google Scholar 

  • Alt, R., & Fleisch, E. (2000). Business networking systems: characteristics and lessons learned. International Journal of Electronic Commerce, 5(2), 7–27.

    Google Scholar 

  • Alt, R., & Klein, S. (2011). Twenty years of electronic markets research—looking backwards towards the future. Electronic Markets, 21(1), 41–51. doi:10.1007/s12525-011-0057-z

    Google Scholar 

  • Alt, R., Fleisch, E., & Werle, O. (2000). The concept of networkability—how to make companies competitive in business networks. Paper presented at the 8th European Conference on Information Systems (ECIS 2000), Vienna (Austria).

  • Alt, R., Fleisch, E., & Österle, H. (2001). Introduction—chances and challenges in business networking. In H. Österle, E. Fleisch, & R. Alt (Eds.), Business networking—shaping collaboration between enterprises (2nd ed., pp. 1–14). Berlin: Springer.

    Google Scholar 

  • Applegate, L. M. (2001). Emerging Networked Business Models: Lessons from the Field, Working report No. 9-801-172, Harvard Business School.

  • Atkinson, K., & McGaughey, R. (2006). Accounting for data: a shortcoming in accounting for intangible assets. Academy of Accounting and Financial Studies Journal, 10(2), 85–95.

    Google Scholar 

  • Auramo, J., Kauremaa, J., & Tanskanen, K. (2005). Benefits of IT in supply chain management: an explorative study of progressive companies. International Journal of Physical Distribution & Logistics Management, 35(2), 82–100. doi:10.1108/09600030510590282.

    Google Scholar 

  • Barnes, S. J., & Vidgen, R. (2003). Measuring web site quality improvements: a case study of the forum on strategic management knowledge exchange. Industrial Management & Data Systems, 103(5), 297–309. doi:10.1108/02635570310477352.

    Google Scholar 

  • Batini, C., & Scannapieco, M. (2006). Data quality. Concepts, methodologies and techniques. Berlin: Springer.

    Google Scholar 

  • Batini, C., Cappiello, C., Francalanci, C., & Maurino, A. (2009). Methodologies for data quality assessment and improvement. ACM Computing Surveys, 41(3), 1–52. doi:10.1145/1541880.1541883.

    Google Scholar 

  • Ben Hassine-Guetari, S. (2009). Data quality evaluation in an E-Business environment: A survey. Paper presented at the 14th International Conference on Information Quality, Potsdam (Germany).

  • Berti-Équille, L. (2007). Tracing data pollution in large business applications. Paper presented at the 13th International Conference on Information Quality, Cambridge, MA (USA).

  • Caballero, I., Caro, A., Calero, C., & Piattini, M. (2008). IQM3: information quality management maturity model. Journal of Universal Computer Science, 14(22), 3658–3685.

    Google Scholar 

  • Cappiello, C., & Pernici, B. (2008). Quality-aware design of repairable processes. Paper presented at the 13th International Conference on Information Quality, Cambridge, MA (USA).

  • Chung, W. Y., Fisher, C., & Wang, R. (2002). What skillls matter in data quality? Paper presented at the 7th International Conference on Information Quality, Cambridge, MA (USA).

  • Claassen, M. J. T., van Weele, A. J., & van Raaij, E. M. (2008). Performance outcomes and success factors of vendor managed inventory (VMI). Supply Chain Management: An International Journal, 13(6), 406–414. doi:10.1108/13598540810905660.

    Google Scholar 

  • Cullen, A. J., & Taylor, M. (2009). Critical success factors for B2B e-commerce use within the UK NHS pharmaceutical supply chain. International Journal of Operations & Production Management, 29(11), 1156–1185. doi:10.1108/01443570911000177.

    Google Scholar 

  • Davenport, T. H. (1998). Putting the enterprise into the enterprise system. Harvard Business Review, 76(4), 121–131.

    Google Scholar 

  • Davenport, T. H., & Short, J. E. (1990). The new industrial engineering: information technology and business process redesign. Sloan Management Review, 31(4), 11–27.

    Google Scholar 

  • Dayal, U., Hsu, M., & Ladin, R. (2001). Business process coordination: State of the art, trends, and open issues. Paper presented at the 27th VLDB Conference, Rome (Italy).

  • DeLone, W. H., & McLean, E. R. (1992). Information systems success: the quest for the dependent variable. Information Systems Research, 3(1), 60–95. doi:10.1287/isre.3.1.60.

    Google Scholar 

  • Dholakia, N., & Firat, A. F. (2006). Global business beyond modernity. Critical Perspectives on International Business, 2(2), 147–162.

    Google Scholar 

  • Diemers, D. (2000). A sociological framework for information quality in virtual knowledge communities. Paper presented at the 5th International Conference on Information Quality, Cambridge, MA (USA).

  • Dreibelbis, A., Hechler, E., Milman, I., Oberhofer, M., van Run, P., & Wolfson, D. (2008). Enterprise master data management: an SOA approach to managing core information. Upper Saddle River: IBM.

    Google Scholar 

  • English, L. P. (1999). Improving data warehouse and business information quality (1st ed.). New York, NY (USA): Wiley.

    Google Scholar 

  • Eppler, M. J. (2001). A generic framework for information quality in knowledge-intensive processes. Paper presented at the 6th International Conference on Information Quality, Cambridge, MA (USA).

  • Eppler, M. J., & Helfert, M. (2004). A framework for the classification of data quality costs and an analysis of their progression. Paper presented at the International Conference on Information Quality 2004, Cambridge, MA (USA).

  • Fairchild, A. (2006). Decision management: role and effect of using an intelligent intermediary to aid in information sharing. Information Technology and Management, 7(4), 249–258. doi:10.1007/s10799-006-0275-9.

    Google Scholar 

  • Fedorowicz, J., Gogan, J. L., & Culnan, M. J. (2010). Barriers to interorganizational information sharing in e-government: a stakeholder analysis. The Information Society: An International Journal, 26(5), 315–329. doi:10.1080/01972243.2010.511556.

    Google Scholar 

  • FInES Cluster (2011). Position paper on orientations for FP8: A European innovation partnership for catalysing the competitiveness of European enterprises. European Commsion, Future Internet Enterprise Systems (FInES) Cluster, Brussels (Belgium).

  • Fleisch, E., & Österle, H. (2000). Business networking: A process-oriented framework. In H. Österle, E. Fleisch, & R. Alt (Eds.), Business networking—shaping enterprise relationships on the internet (pp. 55–91). Berlin: Springer.

    Google Scholar 

  • Forslund, H., & Jonsson, P. (2007). The impact of forecast information quality on supply chain performance. International Journal of Operations & Production Management, 27(1), 90–107. doi:10.1108/01443570710714556.

    Google Scholar 

  • Global Commerce Initiative, Capgemini, SAP, HP (2008) 2018: The Future Value Chain.

  • Gregor, S. (2006). The nature of theory in information systems. MIS Quarterly, 30(3), 611–642.

    Google Scholar 

  • Guimaraes, T., Armstrong, C, & Jones, B. (2006). Evolving a comprehensive measure for system quality. Paper presented at the 11th International Conference on Information Quality, Cambridge, MA (USA).

  • Helfert, M., & Radon, R. (2000). An approach for information quality measurement in data warehousing. Paper presented at the 5th International Conference on Information Quality, Cambridge, MA (USA).

  • Horne, N. W. (1995). Information as an asset: the board agenda. Computer Audit Update 1995 (9):5–11.

  • Kagermann, H., Osterle, H., & Jordan, J. M. (2010). IT-Driven business models: Global case studies in transformation. Hoboken, NJ (USA): Wiley.

    Google Scholar 

  • Kathri, V., & Brown, C. V. (2010). Designing data governance. Communications of the ACM, 53(1), 148–152. doi:10.1145/1629175.1629210.

    Google Scholar 

  • Kitchenham, B., Mendes, E., & Travassos, G. H. (2006). A systematic review of cross- vs. within-company cost estimation studies. Paper presented at the 10th International Conference on Evaluation and Assessment in Software Engineering, Staffordshire (UK).

  • Kodate, A., Hario, D., Kawagishi, H., Tanaka, Y., Baba, T., & Seki, S., et al. (2005). Requirements of new emerging services in the ubiquitous networking society based on IQ analysis. Paper presented at the 10th International Conference on Information Quality, Cambridge, MA (USA).

  • Lee, Y. W. (2004). Crafting rules: context-reflective data quality problem solving. Journal of Management Information Systems, 20(3), 93–119.

    Google Scholar 

  • Lee, Y. W., Strong, D. M., Kahn, B. K., & Wang, R. Y. (2002). AIMQ: a methodology for information quality assessment. Information Management, 40, 133–146.

    Google Scholar 

  • Legner, C., & Lebreton, B. (2007). Preface to the focus theme section: ‘Business interoperability’ business interoperability research: present achievements and upcoming challenges. Electronic Markets, 17(3), 176–186. doihttps://doi.org/10.1080/10196780701503054.

    Google Scholar 

  • Legner, C., & Wende, K. (2006). Towards an Excellence Framework for Business Interoperability. Paper presented at the 19th Bled eConference, Bled (Slovenia).

  • Lin, H.-F. (2007). The role of online and offline features in sustaining virtual communities: an empirical study. Internet Research, 17(2), 119–138. doi:10.1108/10662240710736997.

    Google Scholar 

  • Lin, C.-T. (2010). Examining e-travel sites: an empirical study in Taiwan. Online Information Review, 34(2), 205–288. doi:10.1108/14684521011036954.

    Google Scholar 

  • Liu, X., He, M., Gao, F., & Xie, P. (2008). An empirical study of online shopping customer satisfaction in China: a holistic perspective. International Journal of Retail & Distribution Management, 36(11), 919–940. doi:10.1108/09590550810911683.

    Google Scholar 

  • Loonam, M., & O’Loghlin, D. (2008). Exploring e-service quality: a study of Irish online banking. Marketing Intelligence & Planning, 26(7), 759–780. doi:10.1108/02634500810916708.

    Google Scholar 

  • Loshin, D. (2001). Enterprise knowledge management: The data quality approach. San Diego, CA (USA): Morgan Kaufmann.

    Google Scholar 

  • Maditinos, D. I., & Theodoridis, K. (2010). Satisfaction determinants in the Greek online shopping context. Information Technology & People, 23(4), 312–329. doi:10.1108/09593841011087789.

    Google Scholar 

  • Madnick, S., Wang, R., Dravis, F., & Chen, X. (2001). Improving the quality of corporate household data: Current practices and research directions. Paper presented at the 6th International Conference on Information Quality, Cambridge, MA (USA).

  • Madnick, S, Wang, R., Lee, Y. W., & Zhu, H. (2009). Overview and Framework for Data and Information Quality Research. ACM Journal of Data and Information Quality, Vol. 1, No. 1, Article 2. doi:10.1145/1515693.1516680.

  • Malone, T. W., & Crowston, K. (1994). The interdisciplinary study of coordination. ACM Computing Surveys, 26(1), 87–119.

    Google Scholar 

  • MGB. (2010). Kult-Ice-Tea der Migros jetzt auch im PET. In U. P. Naef (Ed.), Press Release. Zürich (SUI): Migros-Genossenschafts-Bund.

  • Melkas, H. (2004). Analyzing information quality in virtual service networks with qualitative interview data. Paper presented at the 9th International Conference on Information Quality, Cambridge, MA (USA).

  • Miles, R. E., & Snow, C. C. (1992). Causes of failure in network organizations. California Management Review, 34(4), 53–72.

    Google Scholar 

  • Moebius, M. (2002). Reasons for rejecting extranet technology in channel relationships: A study of white goods retailers in Germany. Paper presented at the 10th European Conference on Information Systems (ECIS 2002), Gdańsk (Poland), 2002-06-06.

  • Moore, J. F. (1996). The death of competition: Leadership & strategy in the age of business ecosystems. New York: Harper.

    Google Scholar 

  • Najjar, L., & Bishu, R. (2005). Information quality in the banking industries. Paper presented at the 11th Americas Conference on Information Systems (AMCIS 2005), Omaha, NE (USA).

  • Nakatani, K., Chuang. T.-T., & Zhou, D. (2006). Data synchronization technology: Standards, business values and implications. Communications of the AIS, 17(1):Art. 44.

    Google Scholar 

  • Nath, T., & Standing, C. (2010). Drivers of information technology use in the supply chain. Journal of Systems and Information Technology, 12(1), 70–84. doi:10.1108/13287261011032661.

    Google Scholar 

  • Oliveira, P., Rodrigues, F., & Henriques, P. (2006). An ontology-based approach for data cleansing. Paper presented at the 11th International Conference on Information Quality, Cambridge, MA (USA).

  • Österle, H. (1996). Business engineering: Transition to the networked enterprise. Electronic Markets, 6(2), 14–16.

    Google Scholar 

  • Österle, H., & Winter, R. (2003). Business engineering. In H. Österle & R. Winter (Eds.), Business engineering (Vol. 2, pp. 3–18). Berlin (Germany): Springer.

    Google Scholar 

  • Österle, H., Fleisch, E., & Alt, R. (1999). Business networking. Shaping enterprise relationships on the internet. Berlin (Germany): Springer.

    Google Scholar 

  • Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. Hoboken, NJ (USA): Wiley.

    Google Scholar 

  • Otto, B. (2011). Quality management of corporate data assets. In C.-P. Praeg & D. Spath (Eds.), Quality management for IT services: Perspectives on business and process performance (pp. 193–209). Hershey, PA (USA): IGI Global.

    Google Scholar 

  • Otto, B., & Ofner, M. (2010). Towards a process reference model for information supply chain management. Paper presented at the 18th European Conference on Information Systems (ECIS 2010), Pretoria (South Africa).

  • Otto, B., & Schmidt, A. (2010). Enterprise master data architecture: Design decisions and options. Paper presented at the Proceedings of the 15th International Conference on Information Quality, Little Rock, AR (USA).

  • Otto, B., Wende, K., Schmidt, A., & Osl, P. (2007). Towards a framework for corporate data quality management. Paper presented at the 18th Australasian Conference on Information Systems, Toowoomba (Australia).

  • Park, C.-H., & Kim, Y.-G. (2003). Identifying key factors affecting consumer purchase behavior in an online shopping context. International Journal of Retail & Distribution Management, 31(1), 16–29. doi:10.1108/09590550310457818.

    Google Scholar 

  • Pokorny, L. R. (2006). Determining the cost and effectiveness of enhancing data in the U.S. Defense Logistics Agency supply chain. Paper presented at the 11th International Conference on Information Quality, Cambridge, MA (USA).

  • Redman, T. C. (1995). Improve data quality for competitive advantage. Sloan Management Review, 36(2), 99–107.

    Google Scholar 

  • Redman, T. C. (2001). Data quality. The field guide. Boston: Digital Press.

    Google Scholar 

  • Riemer, K., & Klein, S. (2006). Network management framework. In S. Klein & A. Poulymenakou (Eds.), Managing dynamic networks (pp. 17–66). Berlin (Germany): Springer.

    Google Scholar 

  • Rotchanakitumnuai, S., & Speece, M. (2009). Modeling electronic service acceptance of an e-securities trading system. Industrial Management & Data Systems, 109(8), 1069–1084. doi:10.1108/02635570910991300.

    Google Scholar 

  • Sarkis, J., & Sundarraj, R. P. (2000). Quality and process standards for electronic commerce. Paper presented at the 5th International Conference on Information Quality, Cambridge, MA (USA).

  • Sarner, A., Drakos, N., & Prentice, S. (2008). The Business Impact of Social Computing. Stamford, CT (USA): Gartner, Inc.

    Google Scholar 

  • Sarsfield. (2009). The data governance imperative: A business strategy for corporate data. Cambridgeshire (UK): IT Governance Publishing.

    Google Scholar 

  • Seethamraju, R. (2005). Relative importance of web quality dimensions. Paper presented at the 11th Americas Conference on Information Systems (AMCIS 2005), Omaha, NE (USA).

  • Shankaranarayan, G., Wang, R. Y., & Ziad, M. (2000). IP-MAP: Representing the manufacture of an information product. Paper presented at the 2000 Conference on Information Quality, Cambridge, MA (USA).

  • Shankaranarayanan, G., & Cai, Y. (2006). Supporting data quality management in decision-making. Decision Support Systems, 42(1), 302–317. doi:10.1016/j.dss.2004.12.006.

    Google Scholar 

  • Shannon, C. E. (1949). Communication in the presence of noise. Proceedings of the IRE, 37, 10–21.

    Google Scholar 

  • Stvilia, B., Gasser, L., Twidale, M. B., Shreeves, S. L., & Cole, T. W. (2004). Metadata quality for federated collections. Paper presented at the 9th International Conference on Information Quality, Cambridge, MA (USA).

  • Su, Q., Li, Z., Y-T, S., & Chen, T. (2008). Conceptualizing consumers’ perceptions of e-commerce quality. International Journal of Retail & Distribution Management, 36(5), 360–374. doi:10.1108/09590550810870094.

    Google Scholar 

  • Swaid, S. I., & Wigand, R. T. (2007). Key dimensions of e-commerce service quality and its relationships to satisfaction and loyalty. Paper presented at the Bled eConference 2007, Bled (Slovenia),

  • Tapia, R. S. (2006). What is a networked business? University of Twente, Department of Computer Science, Enschede (The Netherlands).

  • Timmers, P. (1999). Business models for electronic markets. Electronic Markets, 8(2), 3–8.

    Google Scholar 

  • Van den Hoven, J. (1999). Information resource management: stewards of data. Information Systems Management, 16(1), 88–91.

    Google Scholar 

  • Wang, R. Y. (1998). A product perspective on total data quality management. Communications of the ACM, 41(2), 58–65.

    Google Scholar 

  • Wang, R. Y., & Strong, D. (1996). Beyond accuracy: what data quality means to data consumers. Journal of Management Information Systems, 12(4), 5–34.

    Google Scholar 

  • Wang, R. Y., Storey, V. C., & Firth, C. P. (1995). A framework for analysis of data quality research. IEEE Transactions on Knowledge and Data Engineering, 7(4), 623–640.

    Google Scholar 

  • Wang, R. Y., Lee, Y. W., Pipino, L. L., & Strong, D. M. (1998). Manage your information as a product. Sloan Management Review, 39(4), 95–105.

    Google Scholar 

  • Webb, H. W., & Webb, L. A. (2004). SiteQual: an integrated measure of Web site quality. The Journal of Enterprise Information Management, 17(6), 430–440. doi:10.1108/17410390410566724.

    Google Scholar 

  • Weber, K., Otto, B., & Österle, H. (2009). One Size Does Not Fit All – A Contingency Approach to Data Governance. ACM Journal of Data and Information Quality, Vol. 1, No. 1, Article 4. doi:10.1145/1515693.1515696.

  • Wigand, R. T., Wood, J., & Yiliyasi, Y. (2009). Information quality issues in the mortgage banking industry. Paper presented at the 14th International Conference on Information Quality, Potsdam (Germany).

  • Williamson, O. E. (1979). Transaction-cost economics: the governance of contractual relations. Journal of Law and Economics, 22(2), 233–261.

    Google Scholar 

  • Wilson, R. M. S., & Stenson, J. A. (2008). Valuation of information assets on the balance sheet: the recognition and approaches to the valuation of intangible assets. Business Information Review, 25(3), 167–182.

    Google Scholar 

  • Winter, R. (2008). Design science research in Europe. European Journal of Information Systems, 17(5), 470–475. doi:10.1057/ejis.2008.44.

    Google Scholar 

  • Yao, Y., & Murphy, L. (2007). Remote electronic voting systems: an exploration of voters’ perception and intention to use. European Journal of Information Systems, 16(2), 106–120. doi:10.1057/palgrave.ejis.3000672.

    Google Scholar 

  • Zhou, T., Li, H., & Liu, Y. (2010). The effect of flow experience on mobile SNS users’ loyalty. Industrial Management & Data Systems, 110(6), 930–946. doi:10.1108/02635571011055126.

    Google Scholar 

  • Zhu, H., & Fu, L. (2009a). Towards quality of data standards: Empirical findings from XBRL. Paper presented at the International Conference on Information Systems (ICIS 2009), Phoenix, AZ (USA).

  • Zhu, H., & Wu, H. (2009b). Sloppy Tags and Metacrap? Quality of User Contributed Tags in Collaborative Social Tagging Systems. Paper presented at the 15th Americas Conference on Information Systems (AMCIS 2009), San Francisco, CA (USA).

Download references

Author information

Authors and Affiliations

  1. Institute of Information Management, University of St. Gallen, Müller-Friedberg-Strasse 8, 9000, St. Gallen, Switzerland

    Boris Otto

  2. Information, Operations and Analysis Group, Northeastern University, 214 Hayden Hall, 360 Huntington Avenue, Boston, MA, 02115, USA

    Yang W. Lee

  3. Department of Information Technologies and Systems, University of Castilla-La Mancha, Paseo de la Universidad 4, 13071, Ciudad Real, Spain

    Ismael Caballero

Authors
  1. Boris Otto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yang W. Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ismael Caballero
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Boris Otto.

Additional information

Responsible editor: Hubert Österle

Appendix

Appendix

Table 5 Coverage of business networking concepts
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Otto, B., Lee, Y.W. & Caballero, I. Information and data quality in business networking: a key concept for enterprises in its early stages of development. Electron Markets 21, 83–97 (2011). https://doi.org/10.1007/s12525-011-0063-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12525-011-0063-1

Keywords

JEL classification

Search

Navigation