IDEAS home Printed from https://ideas.repec.org/a/spr/binfse/v6y2014i5p267-278.html
   My bibliography  Save this article

Big Data and Information Processing in Organizational Decision Processes

Author

Listed:
  • Martin Kowalczyk
  • Peter Buxmann

Abstract

Data-centric approaches such as big data and related approaches from business intelligence and analytics (BI&A) have recently attracted major attention due to their promises of huge improvements in organizational performance based on new business insights and improved decision making. Incorporating data-centric approaches into organizational decision processes is challenging, even more so with big data, and it is not self-evident that the expected benefits will be realized. Previous studies have identified the lack of a research focus on the context of decision processes in data-centric approaches. By using a multiple case study approach, the paper investigates different types of BI&A-supported decision processes, and makes three major contributions. First, it shows how different facets of big data and information processing mechanism compositions are utilized in different types of BI&A-supported decision processes. Second, the paper contributes to information processing theory by providing new insights about organizational information processing mechanisms and their complementary relationship to data-centric mechanisms. Third, it demonstrates how information processing theory can be applied to assess the dynamics of mechanism composition across different types of decisions. Finally, the study’s implications for theory and practice are discussed. Copyright Springer Fachmedien Wiesbaden 2014

Suggested Citation

  • Martin Kowalczyk & Peter Buxmann, 2014. "Big Data and Information Processing in Organizational Decision Processes," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(5), pages 267-278, October.
    • Handle: RePEc:spr:binfse:v:6:y:2014:i:5:p:267-278
    DOI: 10.1007/s12599-014-0341-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s12599-014-0341-5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s12599-014-0341-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Richard L. Daft & Robert H. Lengel, 1986. "Organizational Information Requirements, Media Richness and Structural Design," Management Science, INFORMS, vol. 32(5), pages 554-571, May.
    2. Jay R. Galbraith, 1974. "Organization Design: An Information Processing View," Interfaces, INFORMS, vol. 4(3), pages 28-36, May.
    3. Paul C. Nutt, 2008. "Investigating the Success of Decision Making Processes," Journal of Management Studies, Wiley Blackwell, vol. 45(2), pages 425-455, March.
    4. Hasso Plattner & Alexander Zeier, 2011. "In-Memory Data Management," Springer Books, Springer, number 978-3-642-19363-7, September.
    5. Said Elbanna & John Child, 2007. "Influences on strategic decision effectiveness: Development and test of an integrative model," Strategic Management Journal, Wiley Blackwell, vol. 28(4), pages 431-453, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    2. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.
    3. Božič, Katerina & Dimovski, Vlado, 2019. "Business intelligence and analytics for value creation: The role of absorptive capacity," International Journal of Information Management, Elsevier, vol. 46(C), pages 93-103.
    4. Emmanuel P. Paulino, 2022. "Amplifying organizational performance from business intelligence: Business analytics implementation in the retail industry," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 18(2), pages 69-104.
    5. Swapnajit Chakraborti & Shubhamoy Dey, 2019. "Analysis of Competitor Intelligence in the Era of Big Data: An Integrated System Using Text Summarization Based on Global Optimization," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 345-355, June.
    6. Marin FOTACHE & IonuÈ› HRUBARU, 2017. "Performance Analysis Of Two Big Data Technologies On A Cloud Distributed Architecture. Results For Non-Aggregate Queries On Medium-Sized Data," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 63(3), pages 21-50, January.
    7. Julian Krumeich & Dirk Werth & Peter Loos, 2016. "Prescriptive Control of Business Processes," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 58(4), pages 261-280, August.
    8. Christoph Keding, 2021. "Understanding the interplay of artificial intelligence and strategic management: four decades of research in review," Management Review Quarterly, Springer, vol. 71(1), pages 91-134, February.
    9. Fotache Marin & Hrubaru Ionuț, 2016. "Performance Analysis of Two Big Data Technologies on a Cloud Distributed Architecture. Results for Non-Aggregate Queries on Medium-Sized Data," Scientific Annals of Economics and Business, Sciendo, vol. 63(s1), pages 21-50, December.
    10. Ninja Soeffker & Marlin W. Ulmer & Dirk C. Mattfeld, 2019. "Adaptive State Space Partitioning for Dynamic Decision Processes," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 261-275, June.
    11. Ossi Ylijoki & Jari Porras, 2016. "Conceptualizing Big Data: Analysis of Case Studies," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(4), pages 295-310, October.
    12. Ionut HRUBARU & Marin FOTACHE, 2017. "On the Performance of Three In-Memory Data Systems for On Line Analytical Processing," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 21(1), pages 5-15.
    13. Awan, Usama & Shamim, Saqib & Khan, Zaheer & Zia, Najam Ul & Shariq, Syed Muhammad & Khan, Muhammad Naveed, 2021. "Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance," Technological Forecasting and Social Change, Elsevier, vol. 168(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    2. Ahmed Hamdi & Tarik Saikouk & Bouchaib Bahli, 2020. "Facing supply chain disruptions: enhancers of supply chain resiliency," Economics Bulletin, AccessEcon, vol. 40(4), pages 2943-2958.
    3. Starling David Hunter & Henrik Bentzen & Jan Taug, 2020. "On the “missing link” between formal organization and informal social structure," Journal of Organization Design, Springer;Organizational Design Community, vol. 9(1), pages 1-20, December.
    4. Goh, Shao Hung & Eldridge, Stephen, 2019. "Sales and Operations Planning: The effect of coordination mechanisms on supply chain performance," International Journal of Production Economics, Elsevier, vol. 214(C), pages 80-94.
    5. Xinwei Li & Wenjuan Zeng & Mao Xu, 2022. "The Moderating Role of IT Capability on Green Innovation and Ambidexterity: Towards a Corporate Sustainable Development," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    6. Roger Moser & Srinath Rengarajan & Gopalakrishnan Narayanamurthy, 2021. "Decision Intelligence: Creating a Fit between Intelligence Requirements and Intelligence Processing Capacities," IIM Kozhikode Society & Management Review, , vol. 10(2), pages 160-177, July.
    7. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    8. Johann Piet Hausberg & Peter S. H. Leeflang, 2019. "Absorbing Integration: Empirical Evidence On The Mediating Role Of Absorptive Capacity Between Functional-/Cross-Functional Integration And Innovation Performance," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 23(06), pages 1-37, August.
    9. Jahangir Karimi & Toni M. Somers & Yash P. Gupta, 2004. "Impact of Environmental Uncertainty and Task Characteristics on User Satisfaction with Data," Information Systems Research, INFORMS, vol. 15(2), pages 175-193, June.
    10. Ágnes Szukits, 2022. "The illusion of data-driven decision making – The mediating effect of digital orientation and controllers’ added value in explaining organizational implications of advanced analytics," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 33(3), pages 403-446, September.
    11. Stephan M. Liozu & Sven Feurer & Andreas Hinterhuber & Arch Woodside, 2021. "Configurational theory and practices of firms employing multiple pricing policies: assessing effective and ineffective pricing recipes in multiple firm contexts," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(4), pages 420-435, August.
    12. Iben Duvald, 2019. "Exploring reasons for the weekend effect in a hospital emergency department: an information processing perspective," Journal of Organization Design, Springer;Organizational Design Community, vol. 8(1), pages 1-27, December.
    13. Cao, Guangming & Duan, Yanqing & Cadden, Trevor, 2019. "The link between information processing capability and competitive advantage mediated through decision-making effectiveness," International Journal of Information Management, Elsevier, vol. 44(C), pages 121-131.
    14. Leena Pekkinen & Kirsi Aaltonen & Jaakko Kujala & Janne Härkönen, 2015. "Evaluating Sources of Risks in Large Engineering Projects: The Roles of Equivocality and Uncertainty," International Journal of Management, Knowledge and Learning, International School for Social and Business Studies, Celje, Slovenia, vol. 4(2), pages 163-180.
    15. Moser, Roger & Kuklinski, Christian Paul Jian-Wei & Srivastava, Mohit, 2017. "Information processing fit in the context of emerging markets: An analysis of foreign SBUs in China," Journal of Business Research, Elsevier, vol. 70(C), pages 234-247.
    16. Gu, Minhao & Yang, Lu & Huo, Baofeng, 2021. "The impact of information technology usage on supply chain resilience and performance: An ambidexterous view," International Journal of Production Economics, Elsevier, vol. 232(C).
    17. Rengarajan, Srinath & Moser, Roger & Narayanamurthy, Gopalakrishnan, 2021. "Strategy tools in dynamic environments – An expert-panel study," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    18. David C. Hall & Tracy D. Johnson-Hall, 2021. "The value of downstream traceability in food safety management systems: an empirical examination of product recalls," Operations Management Research, Springer, vol. 14(1), pages 61-77, June.
    19. Petrou, Andreas P. & Hadjielias, Elias & Thanos, Ioannis C. & Dimitratos, Pavlos, 2020. "Strategic decision-making processes, international environmental munificence and the accelerated internationalization of SMEs," International Business Review, Elsevier, vol. 29(5).
    20. Jeremy Galbreath & Chia‐Yang Chang & Daniel Tisch, 2023. "The impact of a proactive environmental strategy on environmentally sustainable practices in service firms: The moderating effect of information use value," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 5420-5434, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:binfse:v:6:y:2014:i:5:p:267-278. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.