Big Data is Power: Business Value from a Process Oriented Analytics Capability

Rogier Van de Wetering; Patrick Mikalef; John Krogstie

doi:10.1007/978-3-030-04849-5

Big Data is Power: Business Value from a Process Oriented Analytics Capability

Rogier Van de Wetering, Patrick Mikalef, John Krogstie

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Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

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Abstract

Big data analytics (BDA) has the potential to provide firms with competitive benefits. Despite its massive potential, the conditions and required complementary resources and capabilities through which firms can gain business value, are by no means clear. Firms cannot ignore the influx of data, mostly unstructured, and will need to invest in BDA increasingly. By doing so, they will have to, e.g., necessitate new specialist competencies, privacy, and regulatory issues as well as other structural and cost considerations. Past research contributions argued for the development of idiosyncratic and difficult to imitate firm capabilities. This study builds upon resources synchronization theories and examines the process to obtain business value from BDA. In this study, we use data from 27 cases studies from different types of industries. Through the coding analyses of interview transcripts, we identify the contingent resources that drive, moderate and condition the value of a BDA capability throughout different phases of adoption. Our results contribute to a better understanding of the importance of BDA resources and the process and working mechanisms through which to leverage them toward business value. We conclude that our synthesized configurational model for BDA capabilities is a useful basis for future research.

Original language	English
Title of host publication	Business Information Systems Workshops
Subtitle of host publication	BIS 2018 International Workshops, Berlin, Germany, July 18–20, 2018, Revised Papers
Editors	Witold Abramowicz, Adrian Paschke
Place of Publication	Cham
Publisher	Springer International Publishing AG
Chapter	41
Pages	468-480
Number of pages	13
Edition	1
ISBN (Electronic)	9783030048495
ISBN (Print)	9783030048488
DOIs	https://doi.org/10.1007/978-3-030-04849-5
Publication status	Published - 2019
Event	21st International Conference, Business Information Systems: BIS 2018 - Berlin, Germany Duration: 18 Jul 2018 → 20 Jul 2018 http://bis.ue.poznan.pl/bis2018/

Publication series

Series	Lecture Notes in Business Information Processing
Volume	339

Conference

Conference	21st International Conference, Business Information Systems
Country/Territory	Germany
City	Berlin
Period	18/07/18 → 20/07/18
Internet address	http://bis.ue.poznan.pl/bis2018/

Keywords

Big Data
Process stages
Qualitative coding
RESOURCE-BASED VIEW
big data analytics capabilities

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10.1007/978-3-030-04849-5

Big_data_is_power_Business_valueFinal published version, 558 KBLicence: Taverne

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Van de Wetering, R., Mikalef, P., & Krogstie, J. (2019). Big Data is Power: Business Value from a Process Oriented Analytics Capability. In W. Abramowicz, & A. Paschke (Eds.), Business Information Systems Workshops: BIS 2018 International Workshops, Berlin, Germany, July 18–20, 2018, Revised Papers (1 ed., pp. 468-480). Springer International Publishing AG. https://doi.org/10.1007/978-3-030-04849-5

Van de Wetering, Rogier ; Mikalef, Patrick ; Krogstie, John. / Big Data is Power : Business Value from a Process Oriented Analytics Capability. Business Information Systems Workshops: BIS 2018 International Workshops, Berlin, Germany, July 18–20, 2018, Revised Papers. editor / Witold Abramowicz ; Adrian Paschke. 1. ed. Cham : Springer International Publishing AG, 2019. pp. 468-480 (Lecture Notes in Business Information Processing, Vol. 339).

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abstract = "Big data analytics (BDA) has the potential to provide firms with competitive benefits. Despite its massive potential, the conditions and required complementary resources and capabilities through which firms can gain business value, are by no means clear. Firms cannot ignore the influx of data, mostly unstructured, and will need to invest in BDA increasingly. By doing so, they will have to, e.g., necessitate new specialist competencies, privacy, and regulatory issues as well as other structural and cost considerations. Past research contributions argued for the development of idiosyncratic and difficult to imitate firm capabilities. This study builds upon resources synchronization theories and examines the process to obtain business value from BDA. In this study, we use data from 27 cases studies from different types of industries. Through the coding analyses of interview transcripts, we identify the contingent resources that drive, moderate and condition the value of a BDA capability throughout different phases of adoption. Our results contribute to a better understanding of the importance of BDA resources and the process and working mechanisms through which to leverage them toward business value. We conclude that our synthesized configurational model for BDA capabilities is a useful basis for future research.",

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Van de Wetering, R, Mikalef, P & Krogstie, J 2019, Big Data is Power: Business Value from a Process Oriented Analytics Capability. in W Abramowicz & A Paschke (eds), Business Information Systems Workshops: BIS 2018 International Workshops, Berlin, Germany, July 18–20, 2018, Revised Papers. 1 edn, Springer International Publishing AG, Cham, Lecture Notes in Business Information Processing, vol. 339, pp. 468-480, 21st International Conference, Business Information Systems, Berlin, Berlin, Germany, 18/07/18. https://doi.org/10.1007/978-3-030-04849-5

Big Data is Power: Business Value from a Process Oriented Analytics Capability. / Van de Wetering, Rogier; Mikalef, Patrick; Krogstie, John.
Business Information Systems Workshops: BIS 2018 International Workshops, Berlin, Germany, July 18–20, 2018, Revised Papers. ed. / Witold Abramowicz; Adrian Paschke. 1. ed. Cham: Springer International Publishing AG, 2019. p. 468-480 (Lecture Notes in Business Information Processing, Vol. 339).

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

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N2 - Big data analytics (BDA) has the potential to provide firms with competitive benefits. Despite its massive potential, the conditions and required complementary resources and capabilities through which firms can gain business value, are by no means clear. Firms cannot ignore the influx of data, mostly unstructured, and will need to invest in BDA increasingly. By doing so, they will have to, e.g., necessitate new specialist competencies, privacy, and regulatory issues as well as other structural and cost considerations. Past research contributions argued for the development of idiosyncratic and difficult to imitate firm capabilities. This study builds upon resources synchronization theories and examines the process to obtain business value from BDA. In this study, we use data from 27 cases studies from different types of industries. Through the coding analyses of interview transcripts, we identify the contingent resources that drive, moderate and condition the value of a BDA capability throughout different phases of adoption. Our results contribute to a better understanding of the importance of BDA resources and the process and working mechanisms through which to leverage them toward business value. We conclude that our synthesized configurational model for BDA capabilities is a useful basis for future research.

AB - Big data analytics (BDA) has the potential to provide firms with competitive benefits. Despite its massive potential, the conditions and required complementary resources and capabilities through which firms can gain business value, are by no means clear. Firms cannot ignore the influx of data, mostly unstructured, and will need to invest in BDA increasingly. By doing so, they will have to, e.g., necessitate new specialist competencies, privacy, and regulatory issues as well as other structural and cost considerations. Past research contributions argued for the development of idiosyncratic and difficult to imitate firm capabilities. This study builds upon resources synchronization theories and examines the process to obtain business value from BDA. In this study, we use data from 27 cases studies from different types of industries. Through the coding analyses of interview transcripts, we identify the contingent resources that drive, moderate and condition the value of a BDA capability throughout different phases of adoption. Our results contribute to a better understanding of the importance of BDA resources and the process and working mechanisms through which to leverage them toward business value. We conclude that our synthesized configurational model for BDA capabilities is a useful basis for future research.

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ER -

Van de Wetering R, Mikalef P, Krogstie J. Big Data is Power: Business Value from a Process Oriented Analytics Capability. In Abramowicz W, Paschke A, editors, Business Information Systems Workshops: BIS 2018 International Workshops, Berlin, Germany, July 18–20, 2018, Revised Papers. 1 ed. Cham: Springer International Publishing AG. 2019. p. 468-480. (Lecture Notes in Business Information Processing, Vol. 339). doi: 10.1007/978-3-030-04849-5

Big Data is Power: Business Value from a Process Oriented Analytics Capability

Abstract

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Keywords

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