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Use of RFID Technology for Automatic Job Costing

Author

Listed:
  • Jeremy C. Bellah

    (Sam Houston State University, Huntsville, TX, USA)

  • Kunpeng Li

    (Utah State University, Logan, UT, USA)

  • Pamela J. Zelbst

    (Sam Houston State University, Huntsville, TX, USA)

  • Qiannong Gu

    (Ball State University, Muncie, IN, USA)

Abstract

Radio frequency identification (RFID) technology has been used to collect information for use in information systems that support knowledge-based business decisions. Most applications involve using the technology for automatic identification and tracking within facilities and supply chains. However, there are a number of other uses for the technology in the context of supporting knowledge-based decisions. By describing an innovative use of RFID technology, this study contributes to research and practice in the area of knowledge-based tools. Specifically, the process created in this study uses RFID technology to automatically and accurately calculate job costing information for fixed-position projects. By implementing the methods described in this process, business professionals can reap important benefits from the knowledge generated by the system.

Suggested Citation

  • Jeremy C. Bellah & Kunpeng Li & Pamela J. Zelbst & Qiannong Gu, 2014. "Use of RFID Technology for Automatic Job Costing," International Journal of Information Systems and Social Change (IJISSC), IGI Global, vol. 5(2), pages 53-68, April.
    • Handle: RePEc:igg:jissc0:v:5:y:2014:i:2:p:53-68
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    Cited by:

    1. Murray, Portia & Orehounig, Kristina & Grosspietsch, David & Carmeliet, Jan, 2018. "A comparison of storage systems in neighbourhood decentralized energy system applications from 2015 to 2050," Applied Energy, Elsevier, vol. 231(C), pages 1285-1306.
    2. Thacker, Kendall S. & Barger, K. McCall & Mattson, Christopher A., 2017. "Balancing technical and user objectives in the redesign of a peruvian cookstove," Development Engineering, Elsevier, vol. 2(C), pages 12-19.
    3. Ogbomo, Osarumen O. & Amalu, Emeka H. & Ekere, N.N. & Olagbegi, P.O., 2017. "A review of photovoltaic module technologies for increased performance in tropical climate," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1225-1238.
    4. Antonelli, Marco & Barsali, Stefano & Desideri, Umberto & Giglioli, Romano & Paganucci, Fabrizio & Pasini, Gianluca, 2017. "Liquid air energy storage: Potential and challenges of hybrid power plants," Applied Energy, Elsevier, vol. 194(C), pages 522-529.
    5. Zhang, Ke & Hao, Lei & Du, Miao & Mi, Jing & Wang, Ji-Ning & Meng, Jian-ping, 2017. "A review on thermal stability and high temperature induced ageing mechanisms of solar absorber coatings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1282-1299.
    6. Helms, Thorsten & Loock, Moritz & Bohnsack, René, 2016. "Timing-based business models for flexibility creation in the electric power sector," Energy Policy, Elsevier, vol. 92(C), pages 348-358.
    7. Duscha, Vicki & Fougeyrollas, Arnaud & Nathani, Carsten & Pfaff, Matthias & Ragwitz, Mario & Resch, Gustav & Schade, Wolfgang & Breitschopf, Barbara & Walz, Rainer, 2016. "Renewable energy deployment in Europe up to 2030 and the aim of a triple dividend," Energy Policy, Elsevier, vol. 95(C), pages 314-323.
    8. Ferreira, Agmar & Kunh, Sheila S. & Fagnani, Kátia C. & De Souza, Tiago A. & Tonezer, Camila & Dos Santos, Geocris Rodrigues & Coimbra-Araújo, Carlos H., 2018. "Economic overview of the use and production of photovoltaic solar energy in brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 181-191.

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