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Implementing Adaptive Strategies of Decision Support Systems During Crises

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Global Business Strategies in Crisis

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

Abstract

A typical Decision Support System requires data access, a model enhanced with proper machine learning algorithms and a user interface. So, thanks to the development of fast machine learning algorithms and big data, Decision Support Systems may be used as Executive Information Systems in practice to support the decisions of executives. With the improvement of science and technology, it has become more feasible to store large amounts of data both on local and remote databases. New and robust machine learning algorithms are available to process this data and extract information to support decision makers and decision-making processes like future risk management, investment plans, predicting opportunities in the sector, long-term recruitment plans, and employee training programs. In this chapter, decision support systems have been presented in general. Additionally, some details have been given about how to use decision support systems and for what business purposes they may be exploited by the top management.

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References

  • Alemany MME, Ortiz A, Boza A, Fuertes-Miquel VS (2015) A model-driven decision support system for reallocation of supply to orders under uncertainty in ceramic companies. Technol Econ Dev Econ 21(4):596–625

    Article  Google Scholar 

  • Apoteker T, Barthélémy S (2005) Predicting financial crises in emerging markets using a composite non-parametric model. Emerg Mark Rev 6(4):363–375

    Article  Google Scholar 

  • Asadi R, Ghatee M (2015) A rule-based decision support system in intelligent Hazmat transportation system. IEEE Trans Intell Transp Syst 16(5):2756–2764

    Article  Google Scholar 

  • Babecký J, Havranek T, Mateju J, Rusnák M, Smidkova K, Vasicek B (2012) Leading indicators of crisis incidence: evidence from developed countries

    Google Scholar 

  • Beraldi P, Violi A, De Simone F (2011) A decision support system for strategic asset allocation. Decis Support Syst 51(3):549–561

    Article  Google Scholar 

  • Brucker P (1988) An efficient algorithm for the job-shop problem with two jobs. Computing 40(4):353–359

    Article  Google Scholar 

  • Christopher JJ, Nehemiah HK, Kannan A (2015) A clinical decision support system for diagnosis of Allergic Rhinitis based on intradermal skin tests. Comput Biol Med 65:76–84

    Article  Google Scholar 

  • Daniel J (2002) Decision support systems: concepts and resources for managers. Greenwood Publishing Group, New York

    Google Scholar 

  • Dios M, Molina-Pariente JM, Fernandez-Viagas V, Andrade-Pineda JL, Framinan JM (2015) A decision support system for operating room scheduling. Comput Ind Eng 88:430–443

    Article  Google Scholar 

  • Dutta G, Gupta N, Fourer R (2011) An optimization-based decision support system for strategic planning in a process industry: the case of aluminium company in India. J Oper Res Soc 62(4):616–626

    Article  Google Scholar 

  • Fanti MP, Iacobellis G, Ukovich W, Boschian V, Georgoulas G, Stylios C (2015) A simulation based Decision Support System for logistics management. J Comput Sci 10:86–96

    Article  Google Scholar 

  • Fazi S, Fransoo JC, Van Woensel T (2015) A decision support system tool for the transportation by barge of import containers: a case study. Decis Support Syst 79:33–45

    Article  Google Scholar 

  • Inmon WH, Hackathorn RD (1994) Using the data warehouse. Wiley-QED Publishing, Somerset, NJ

    Google Scholar 

  • Jaakkola T, Jordan MI, Singh SP (1994) On the convergence of stochastic iterative dynamic programming algorithms. Neural Comput 6(6):1185–1201

    Article  Google Scholar 

  • Kirkpatrick S (1984) Optimization by simulated annealing: quantitative studies. J Stat Phys 34(5–6):975–986

    Article  Google Scholar 

  • Lin C, Hsieh PJ (2004) A fuzzy decision support system for strategic portfolio management. Decis Support Syst 38(3):383–398

    Article  Google Scholar 

  • Lin S, Kernighan BW (1973) An effective heuristic algorithm for the traveling-salesman problem. Oper Res 21(2):498–516

    Article  Google Scholar 

  • Liu S, Young RI, Ding L (2011) An integrated decision support system for global manufacturing co-ordination in the automotive industry. Int J Comput Integr Manuf 24(4):285–301

    Article  Google Scholar 

  • Marakas GM (2003) Decision support systems in the 21st century, vol 134. Prentice Hall, Upper Saddle River, NJ

    Google Scholar 

  • Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21(6):1087–1092

    Article  Google Scholar 

  • Neoh SC, Srisukkham W, Zhang L, Todryk S, Greystoke B, Lim CP, et al (2015) An intelligent decision support system for leukaemia diagnosis using microscopic blood images. Scientific Reports, 5

    Google Scholar 

  • Perrot N, Baudrit C, Brousset JM, Abbal P, Guillemin H, Perret B, et al (2015) A decision support system coupling fuzzy logic and probabilistic graphical approaches for the agri-food industry: prediction of grape berry maturity. PloS One 10(7):e0134373

    Google Scholar 

  • Ruiz AB, Sindhya K, Miettinen K, Ruiz F, Luque M (2015) E-NAUTILUS: a decision support system for complex multiobjective optimization problems based on the NAUTILUS method. Eur J Oper Res 246(1):218–231

    Article  Google Scholar 

  • Scott J, Ho W, Dey PK, Talluri S (2015) A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments. Int J Prod Econ 166:226–237

    Article  Google Scholar 

  • Sharda R, Delen D, Turban E, Aronson J, Liang TP (2014) Business intelligence and analytics: systems for decision support-(required). Prentice Hall

    Google Scholar 

  • Siddiqui MF, Reza AW, Kanesan J (2015) An automated and intelligent medical decision support system for brain MRI scans classification. PLoS One 10(8), e0135875

    Article  Google Scholar 

  • Sjöberg L (2003) Intuitive vs. analytical decision making: which is preferred? Scand J Manag 19(1):17–29

    Article  Google Scholar 

  • Vallerio M, Hufkens J, Van Impe J, Logist F (2015) An interactive decision-support system for multi-objective optimization of nonlinear dynamic processes with uncertainty. Expert Syst Appl 42(21):7710–7731

    Article  Google Scholar 

  • Vardarlier P, Silahtaroglu G (2016) Gossip management at universities using big data warehouse model integrated with a decision support system. Int J Res Bus Social Sci 5(1):1–14, 2147-4478

    Article  Google Scholar 

  • Zhao BW, Chen YM, Jiang SS, Zhou ZW, Li YF (2015) Lymph node metastasis, a unique independent prognostic factor in early gastric cancer. PLoS One 10(7):e0129531

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Management Information Systems, School of Business, Istanbul Medipol University, Kavacik Campus, Beykoz, 34810, Istanbul, Turkey

    Gökhan Silahtaroğlu

Authors
  1. Gökhan Silahtaroğlu
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Correspondence to Gökhan Silahtaroğlu .

Editor information

Editors and Affiliations

  1. Istanbul Medipol University, Beylikduzu, Istanbul, Turkey

    Ümit Hacioğlu

  2. Istanbul Medipol University , Eyup, Istanbul, Turkey

    Hasan Dinçer

  3. Istanbul Medipol University , Zeytinburnu, Istanbul, Turkey

    Nihat Alayoğlu

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Silahtaroğlu, G. (2017). Implementing Adaptive Strategies of Decision Support Systems During Crises. In: Hacioğlu, Ü., Dinçer, H., Alayoğlu, N. (eds) Global Business Strategies in Crisis. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-319-44591-5_20

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