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Business Analytics for Managers

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Business Analytics for Professionals

Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

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Abstract

Humans are decision-makers. Career and lifestyle decisions such as starting a business, purchasing a product, and investing in the future are all personalized decisions. Managers also in businesses make many decisions every day. If there is one truth that may be agreed upon about all managers, it is that they are overwhelmed by the burden of decisions. In today's business environment companies use data and analytics to gain competitive advantage by taking the most accurate strategic and operational decisions. Companies can vastly enhance their business operations through the use of business analytics, such as sophisticated data analysis, optimization and machine learning. The goal of business analytics is to help organizations improve their decision making with faster, better analysis.

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References

  1. Delen D, Demirkan H (2013) Data, information and analytics as services. Decis Support Syst 55(1):359–363. https://doi.org/10.1016/j.dss.2012.05.044

    Article  Google Scholar 

  2. S, Mathew SK (2018) Business analytics and business value: a comparative case study. Inf Manage 55(5):643–666. https://doi.org/10.1016/j.im.2018.01.005

  3. Whitelock V (2018) Business analytics and firm performance: role of structured financial statement data. J Bus Anal 1(2):81–92. https://doi.org/10.1080/2573234X.2018.1557020

    Article  Google Scholar 

  4. Bayrak T (2015) A review of business analytics: a business enabler or another passing fad. Procedia Soc Behav Sci 195:230–239. https://doi.org/10.1016/j.sbspro.2015.06.354

    Article  Google Scholar 

  5. Poornima S, Pushpalatha M (2020) A survey on various applications of prescriptive analytics. Int J Intell Netw 1(July):76–84. https://doi.org/10.1016/j.ijin.2020.07.001

    Article  Google Scholar 

  6. Hindle G, Kunc M, Mortensen M, Oztekin A, Vidgen R (2020) Business analytics: defining the field and identifying a research agenda. Eur J Oper Res 281(3):483–490. https://doi.org/10.1016/j.ejor.2019.10.001

    Article  MATH  Google Scholar 

  7. Holsapple C, Lee-Post A, Pakath R (2014) A unified foundation for business analytics. Decis Support Syst 64:130–141. https://doi.org/10.1016/j.dss.2014.05.013

    Article  Google Scholar 

  8. Lepenioti K, Bousdekis A, Apostolou D, Mentzas G (2020) Prescriptive analytics: Literature review and research challenges. Int J Inf Manage 50:57–70.https://doi.org/10.1016/j.ijinfomgt.2019.04.003

  9. Griva A, Bardaki C, Pramatari K, Papakiriakopoulos D (2018) Retail business analytics: customer visit segmentation using market basket data. Expert Syst Appl 100:1–16. https://doi.org/10.1016/j.eswa.2018.01.029

    Article  Google Scholar 

  10. Delen D, Ram S (2018) Research challenges and opportunities in business analytics. J Bus Anal 1(1):2–12. https://doi.org/10.1080/2573234X.2018.1507324

    Article  Google Scholar 

  11. Vidgen R, Shaw S, Grant DB (2017) Management challenges in creating value from business analytics. Eur J Oper Res 261(2):626–639. https://doi.org/10.1016/j.ejor.2017.02.023

    Article  Google Scholar 

  12. Montgomery H (1983) Decision rules and the search for a dominance structure: towards a process model of decision making. Adv Psychol 14:343–369. https://doi.org/10.1016/S0166-4115(08)62243-8

    Article  Google Scholar 

  13. Barthélemy JP, Bisdorff R, Coppin G (2002) Human centered processes and decision support systems. Eur J Oper Res 136(2):233–252. https://doi.org/10.1016/S0377-2217(01)00112-6

    Article  MATH  Google Scholar 

  14. Zhu K, Kraemer KL, Xu S (2006) The process of innovation assimilation by firms in different countries: a technology diffusion perspective on e-business. Manage Sci 52:1557–1576. https://doi.org/10.1287/mnsc.1050.0487

    Article  Google Scholar 

  15. Simon HA (1960) The new science of management decision. In: Harper Brothers, New York.https://doi.org/10.1037/13978-000

  16. Lee SM, Eom HB (1990) Multiple-criteria decision support systems: the powerful tool for attacking complex, unstructured decisions. Syst Pract 3(1):51–65. https://doi.org/10.1007/BF01062821

    Article  Google Scholar 

  17. Bernroider EWN, Schmöllerl P (2013) A technological, organisational, and environmental analysis of decision making methodologies and satisfaction in the context of IT induced business transformations. Eur J Oper Res 224(1):141–153. https://doi.org/10.1016/j.ejor.2012.07.025

    Article  Google Scholar 

  18. Trakadas P, Simoens P, Gkonis P, Sarakis L, Angelopoulos A, Ramallo-González AP, Skarmeta A, Trochoutsos C, Calvo D, Pariente T, Chintamani K, Fernandez I, Irigaray AA, Parreira JX, Petrali P, Leligou N, Karkazis P (2020) An artificial intelligence-based collaboration approach in industrial iot manufacturing: Key concepts, architectural extensions and potential applications. Sensors (Switzerland) 20(19):5480. https://doi.org/10.3390/s20195480

    Article  Google Scholar 

  19. Negulescu OH (2014) Using a decision-making process model in strategic management. Rev General Manage 19(1):111–123

    Google Scholar 

  20. Azvine B, Nauck D, Ho C (2003) Intelligent business analytics—a tool to build decision-support systems for eBusinesses. BT Technol J 21(4):65–71. https://doi.org/10.1023/A:1027379403688

    Article  Google Scholar 

  21. Sharma R, Mithas S, Kankanhalli A (2014) Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations. Eur J Inf Syst 23:433–441. https://doi.org/10.1057/ejis.2014.17

    Article  Google Scholar 

  22. Jalal-Karim A (2013) Evaluating the impact of information security on enhancing the business decision-making process. World J Entrepreneurship Manage Sustain Dev 9(1):55–64. https://doi.org/10.1108/20425961311315719

    Article  Google Scholar 

  23. Seddon PB, Constantinidis D, Tamm T, Dod H (2017) How does business analytics contribute to business value? Inf Syst J 27:237–269. https://doi.org/10.1111/isj.12101

    Article  Google Scholar 

  24. Purvis RL, Sambamurthy V, Zmud RW (2001) The assimilation of knowledge platforms in organizations: an empirical investigation. Organ Sci 12:117–135. https://doi.org/10.1287/orsc.12.2.117.10115

    Article  Google Scholar 

  25. Kowalczyk M, Buxmann P (2014) Big data and information processing in organizational decision processes: a multiple case study. Bus Inf Syst Eng 6(5):267–278. https://doi.org/10.1007/s12599-014-0341-5

    Article  Google Scholar 

  26. Chen H, Chiang RHL, Storey VC (2012) Business intelligence and analytics: from big data to big impact. MIS Q Manage Inf Syst 36(4):1165–1188. https://doi.org/10.2307/41703503

    Article  Google Scholar 

  27. Akter S, Wamba SF, Gunasekaran A, Dubey R, Childe SJ (2016) How to improve firm performance using big data analytics capability and business strategy alignment? Int J Prod Econ 182:113–131. https://doi.org/10.1016/j.ijpe.2016.08.018

    Article  Google Scholar 

  28. Kohli R, Kettinger WJ (2004) Informating the clan: controlling physicians’ costs and outcomes. MIS Q Manage Inf Syst 28(3):363–394. https://doi.org/10.2307/25148644

    Article  Google Scholar 

  29. Akter S, Michael K, Uddin MR, McCarthy G, Rahman M (2020) Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics. Ann Oper Res, 1–33.https://doi.org/10.1007/s10479-020-03620-w

  30. Rongqiang S, Yan C, Chang D, Qingyue G (2020) Research on promoting the application of disease prediction system based on machine learning. In: Proceedings of the 2020 international symposium on artificial intelligence in medical sciences, pp 45–50. https://doi.org/10.1145/3429889.3429898

  31. Dremel C, Herterich MM, Wulf J, Waizmann JC, Brenner W (2017) How AUDI AG established big data analytics in its digital transformation. MIS Q Exec 16(2):81–100

    Google Scholar 

  32. Davenport TH, Ronanki R (2018) Artificial intelligence for the real world. Harv Bus Rev 96(1):108–116

    Google Scholar 

  33. Hildebrand C, Efthymiou F, Busquet F, Hampton WH, Hoffman DL, Novak TP (2020) Voice analytics in business research: conceptual foundations, acoustic feature extraction, and applications. J Bus Res 121:364–374. https://doi.org/10.1016/j.jbusres.2020.09.020

    Article  Google Scholar 

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Authors and Affiliations

  1. Industrial Engineering Department, Management Faculty, Istanbul Technical University, 34367 Macka, Istanbul, Turkey

    Yakup Turgut, Yildiz Kose, Alp Ustundag & Emre Cevikcan

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  1. Yakup Turgut
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  2. Yildiz Kose
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  3. Alp Ustundag
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  4. Emre Cevikcan
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Correspondence to Alp Ustundag .

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Editors and Affiliations

  1. Isletme Fakultesi, Istanbul Technical University, Istanbul, Turkey

    Alp Ustundag

  2. Isletme Fakultesi, Istanbul Technical University, Istanbul, Turkey

    Emre Cevikcan

  3. Isletme Fakultesi, Istanbul Technical University, Istanbul, Turkey

    Omer Faruk Beyca

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Turgut, Y., Kose, Y., Ustundag, A., Cevikcan, E. (2022). Business Analytics for Managers. In: Ustundag, A., Cevikcan, E., Beyca, O.F. (eds) Business Analytics for Professionals. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-030-93823-9_1

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  • DOI: https://doi.org/10.1007/978-3-030-93823-9_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-93822-2

  • Online ISBN: 978-3-030-93823-9

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