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A Novel Research on the Influence of Enterprise Culture on Internal Control in big Data and Internet of Things

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Abstract

The effective management of enterprise resources in internet of things is a growing research trend in modern era. The big data concept influences more opportunities to the researchers to exhibit their innovations in various application oriented fields. The academic and organizational researches suggested that big data provides more benefits on sustained basis for the committed resource management environment. The study shows positive and active enterprise culture is positively correlated to effective internal control. In the enhancement of these resource management initiatives, the dynamic capability of the data and its assumptions are considered. In the case of enterprise culture the implication of practical and business limitations and advantages are discussed in this article. The intellectual contributions and the poles of excellence on the field of big data is a common platform upon which several communication components in practice on every day use which are interfaced and interconnected. In general IoT reduces the distance between the real world and internet by incorporating and integrating different perspectives of technology such as pervasive computing, data communication, networking, sensor node communication etc.,

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References

  1. Batalla JM, Krawiec P (2014) Conception of ID layer performance at the network level for internet of things. Springer Pers Ubiquit Comput 18:465–480

  2. Wang H, Wang J (2014) November. An effective image represen- tation method using kernel classification. In: tools with artificial intelligence (ICTAI), 2014 I.E. 26th international conference on. IEEE, pp 853–858

  3. Khan Z, Anjum A, Kiani SL (2013) Cloud based big data analytics for future cities. In: Proc Conference on utility and cloud computing IEEE Computer Society, pp 381–386

  4. Guerrero-ibanez JA, Zeadally S, Castillo JC (2015) Integration challenges of intelligent transportation systems with connected vehicle, cloud computing, and internet of things technologies. IEEE Wirel Commun 22(6):122–128

  5. Mohamed N, Al-Jaroodi J, Real-time big data analytics: applications and challenges. High Performance Computing & Simulation (HPCS), 2014 International Conference on, 2: 305–310, 2014

  6. Gendreau AA, Moorman M (2016) Survey of intrusion detection systems towards an end to end secure internet of things. Proceedings of international conference on future internet of things and cloud

  7. Aloi G et al (2014) STEM-net: an evolutionary network architecture for smart and sustainable cities. Trans on Emerging Telecommunications Technologies 25(1):21–40

  8. Marie P, Lim L, Manzoor A, Chabridon S, Conan D, Desprats T (2014) QoC-aware context data distribution in the internet of things. In: Proceedings of the 1st ACM workshop on middleware for context-aware applications in the IoT, Bordeaux, France 2, pp 13–18

  9. Cárdenas AA, Manadhata PK, Rajan SP (2013) Big data analytics for security. IEEE Secur Priv 11(6):74–76

  10. Giannikos M, Kokoli K, Fotiou N, Marias GF, Polyzos GC (2013) Towards secure and context-aware information lookup for the internet of things. In: Proceedings of the 2013 international conference on computing, networking and communications (ICNC). San Diego, CA, USA, pp 28–31

  11. Mohamed N, Al-Jaroodi J, Real-time big data analytics: applications and challenges. High Performance Computing & Simulation (HPCS), 2014 International Conference on, 2: 305–310, 2014

  12. Bruno R, Nurchis M (2013) Robust and efficient data collection schemes for vehicularmultimedia sensor networks. In: Proceedings of the IEEE 14th international symposium and workshops on world of wireless, mobile and multimedia networks (WoWMoM). Spain, Madrid, pp 1–10

  13. Aazam M, Khan I, Alsaffar AA, Huh E-N (2014) Cloud of things: integrating internet of things and cloud computing and the issues involved. In: Proc. 11th Int. Bhurban Conf. Appl. Sci. Technol. (IBCAST), Islamabad, Pakistan, pp 414–419

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Acknowledgements

This paper is supported by the National Science and Technology Support Program: "R & D and application of key technology for high-end equipment manufacturing". (2012BAF12B08)

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Authors and Affiliations

  1. Faculty of Management &Economics, Dalian University of Technology, Dalian, China

    Haijun Liu & Xiaobing Liu

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  1. Haijun Liu
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  2. Xiaobing Liu
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Correspondence to Haijun Liu.

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Liu, H., Liu, X. A Novel Research on the Influence of Enterprise Culture on Internal Control in big Data and Internet of Things. Mobile Netw Appl 24, 365–374 (2019). https://doi.org/10.1007/s11036-017-0910-1

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