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2021 | OriginalPaper | Buchkapitel

Emerging Interactions of ERP Systems, Big Data and Automotive Industry

verfasst von : Florie Bandara, Uchitha Jayawickrama

Erschienen in: Advances in Software Engineering, Education, and e-Learning

Verlag: Springer International Publishing

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Abstract

Interactions of enterprise resource planning systems and big data are crucial for the automotive industry in the process of quick and reliable decision-making with the use of large chunks of data collected by each department of the organization. Similarly, unstructured data collected by sensor systems need proper control of data to put out the best results combined with automation. This study adopts a systematic literature review conducted mainly under three phases in order to give a robust combination between the three areas, i.e. ERP systems, big data and automotive industry. The three phases are determining the combination between the enterprise resource planning systems and big data and individually explaining their interaction with the automotive industry. This study has been able to identify the strict influence of large chunks of data on the automotive industry such as data management issues, trust issues and complexity in the responsiveness of enterprise resource planning systems. It is recognized that the main reasons for the emergence of complexity in the responsiveness of enterprise resource planning systems are the unstructured data collected by sensors of emerging concepts such as connected cars and the eventual automation of automobile functions. The study depicts the major influence of an enterprise resource planning system in order to centralize the entire organization whilst a large amount of structured and unstructured data collected.

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Literatur
1.
Zurück zum Zitat U. Jayawickrama, S. Liu, M. Hudson, Empirical evidence of an integrative knowledge competence framework for ERP systems implementation in UK industries. Comput. Ind. 82, 205–223 (2016)CrossRef U. Jayawickrama, S. Liu, M. Hudson, Empirical evidence of an integrative knowledge competence framework for ERP systems implementation in UK industries. Comput. Ind. 82, 205–223 (2016)CrossRef
3.
Zurück zum Zitat U. Jayawickrama, S. Yapa, Factors affecting ERP implementations: Client and consultant perspectives. J. Enterp. Resour. Plan. Stud. 2013 (2013) U. Jayawickrama, S. Yapa, Factors affecting ERP implementations: Client and consultant perspectives. J. Enterp. Resour. Plan. Stud. 2013 (2013)
4.
Zurück zum Zitat C. Wickman, J. Orlovska, R. Soderberg, Big data usage can be a solution for user behavior evaluation: An automotive industry example. Procedia CIRP 72, 117–122 (2018)CrossRef C. Wickman, J. Orlovska, R. Soderberg, Big data usage can be a solution for user behavior evaluation: An automotive industry example. Procedia CIRP 72, 117–122 (2018)CrossRef
5.
Zurück zum Zitat Deloitte LLP, Big data and analytics in the automotive industry: Automotive analytics thought piece Contents, p. 16, 2015 Deloitte LLP, Big data and analytics in the automotive industry: Automotive analytics thought piece Contents, p. 16, 2015
7.
Zurück zum Zitat U. Jayawickrama, S. Liu, M.H. Smith, P. Akhtar, M. Al Bashir, Knowledge retention in ERP implementations: The context of UK SMEs. Prod. Plan. Control 30(10–12), 1032–1047 (2019)CrossRef U. Jayawickrama, S. Liu, M.H. Smith, P. Akhtar, M. Al Bashir, Knowledge retention in ERP implementations: The context of UK SMEs. Prod. Plan. Control 30(10–12), 1032–1047 (2019)CrossRef
8.
Zurück zum Zitat K. Saxena, The future of erp with big data businesses systems and impacting. Int. J. Adv. Electron. Comput. Sci. 3(9), 25–27 (2016) K. Saxena, The future of erp with big data businesses systems and impacting. Int. J. Adv. Electron. Comput. Sci. 3(9), 25–27 (2016)
9.
Zurück zum Zitat T.H. Davenport, Putting the enterprise into the enterprise system. Harv. Bus. Rev., 121–132 (1998) T.H. Davenport, Putting the enterprise into the enterprise system. Harv. Bus. Rev., 121–132 (1998)
10.
Zurück zum Zitat H.M. Al-Sabri, M. Al-Mashari, A. Chikh, A comparative study and evaluation of ERP reference models in the context of ERP IT-driven. Bus. Process. Manag. J. 24(4), 943–964 (2018)CrossRef H.M. Al-Sabri, M. Al-Mashari, A. Chikh, A comparative study and evaluation of ERP reference models in the context of ERP IT-driven. Bus. Process. Manag. J. 24(4), 943–964 (2018)CrossRef
12.
Zurück zum Zitat M. Ali, L. Miller, ERP system implementation in large enterprises – A systematic literature review. J. Enterp. Inf. Manag. 30(4), 666–692 (2017)CrossRef M. Ali, L. Miller, ERP system implementation in large enterprises – A systematic literature review. J. Enterp. Inf. Manag. 30(4), 666–692 (2017)CrossRef
14.
Zurück zum Zitat A. Lorenc, Customer logistic service in the automotive industry with the use of the SAP ERP system, 2015 4th Int. Conf. Adv. Logist. Transp., pp. 18–23, 2015 A. Lorenc, Customer logistic service in the automotive industry with the use of the SAP ERP system, 2015 4th Int. Conf. Adv. Logist. Transp., pp. 18–23, 2015
15.
Zurück zum Zitat W. Tsai, P. Lee, Y. Shen, H. Lin, A comprehensive study of the relationship between enterprise resource planning selection criteria and enterprise resource planning system success. Inf. Manag. 49(1), 36–46 (2012)CrossRef W. Tsai, P. Lee, Y. Shen, H. Lin, A comprehensive study of the relationship between enterprise resource planning selection criteria and enterprise resource planning system success. Inf. Manag. 49(1), 36–46 (2012)CrossRef
17.
Zurück zum Zitat J. Kim, H. Hwangbo, S. Kim, An empirical study on real-time data analytics for connected cars: Sensor-based applications for smart cars. Int. J. Distrib. Sens. Netw. 14(1) (2018) J. Kim, H. Hwangbo, S. Kim, An empirical study on real-time data analytics for connected cars: Sensor-based applications for smart cars. Int. J. Distrib. Sens. Netw. 14(1) (2018)
19.
Zurück zum Zitat I.A.T. Hashem, I. Yaqoob, N.B. Anuar, S. Mokhtar, A. Gani, S. Ullah Khan, The rise of ‘big data’ on cloud computing: Review and open research issues. Inf. Syst. 47, 98–115 (2015)CrossRef I.A.T. Hashem, I. Yaqoob, N.B. Anuar, S. Mokhtar, A. Gani, S. Ullah Khan, The rise of ‘big data’ on cloud computing: Review and open research issues. Inf. Syst. 47, 98–115 (2015)CrossRef
20.
Zurück zum Zitat Z. Shi, G. Wang, Integration of big-data ERP and business analytics (BA). J. High Technol. Manag. Res. 29(2), 141–150 (2018)CrossRef Z. Shi, G. Wang, Integration of big-data ERP and business analytics (BA). J. High Technol. Manag. Res. 29(2), 141–150 (2018)CrossRef
21.
Zurück zum Zitat Z. Khan, U. Jayawickrama, P. Akhtar, S.Y. Tarba, The Internet of Things, dynamic data and information processing capabilities and operational agility. Technol. Forecast. Soc. Change, 1–32 (2017) Z. Khan, U. Jayawickrama, P. Akhtar, S.Y. Tarba, The Internet of Things, dynamic data and information processing capabilities and operational agility. Technol. Forecast. Soc. Change, 1–32 (2017)
26.
Zurück zum Zitat J. Kim, H. Hwangbo, S. Kim, An empirical study on real-time data analytics for connected cars: Sensor-based applications for smart cars. Int. J. Distrib. Sens. Netw 14(1) (2018) J. Kim, H. Hwangbo, S. Kim, An empirical study on real-time data analytics for connected cars: Sensor-based applications for smart cars. Int. J. Distrib. Sens. Netw 14(1) (2018)
28.
Zurück zum Zitat W.-H. Lin, H. Liu, H.K. Lo, Guest editorial : Big data for driver, vehicle, and system control in ITS. IEEE Trans. Intell. Transp. Syst. 17(6), 1663–1665 (2016)CrossRef W.-H. Lin, H. Liu, H.K. Lo, Guest editorial : Big data for driver, vehicle, and system control in ITS. IEEE Trans. Intell. Transp. Syst. 17(6), 1663–1665 (2016)CrossRef
29.
Zurück zum Zitat A. Elragal, ERP and Big Data: The Inept Couple. Procedia Technol. 16(February), 242–249 (2015) A. Elragal, ERP and Big Data: The Inept Couple. Procedia Technol. 16(February), 242–249 (2015)
31.
Zurück zum Zitat M. Voigt, C. Bennison, M. Hammerschmidt, Gaining traction Big Data in the automotive industry. Bus. Transform. J. 10, 1–2 (2016) M. Voigt, C. Bennison, M. Hammerschmidt, Gaining traction Big Data in the automotive industry. Bus. Transform. J. 10, 1–2 (2016)
32.
Zurück zum Zitat S. Gill, Big Data, the Internet of Things, and how ERP can make good on the promise of real-time actionable intelligence, 2017 S. Gill, Big Data, the Internet of Things, and how ERP can make good on the promise of real-time actionable intelligence, 2017
33.
Zurück zum Zitat J. S. Apte et al., High-resolution air pollution mapping with Google street view cars: Exploiting Big Data, Environ. Sci. Technol., 2017 J. S. Apte et al., High-resolution air pollution mapping with Google street view cars: Exploiting Big Data, Environ. Sci. Technol., 2017
34.
Zurück zum Zitat A. Mylonas, V. Meletiadis, L. Mitrou, D. Gritzalis, Smartphone sensor data as digital evidence. Comput. Secur. 38(2012), 51–75 (2013)CrossRef A. Mylonas, V. Meletiadis, L. Mitrou, D. Gritzalis, Smartphone sensor data as digital evidence. Comput. Secur. 38(2012), 51–75 (2013)CrossRef
35.
Zurück zum Zitat T. Orosz, & I. Orosz, Company level big data management, in SACI 2014 - 9th IEEE Int. Symp. Appl. Comput. Intell. Informatics, Proc., pp. 299–303, 2014 T. Orosz, & I. Orosz, Company level big data management, in SACI 2014 - 9th IEEE Int. Symp. Appl. Comput. Intell. Informatics, Proc., pp. 299–303, 2014
37.
Zurück zum Zitat I. Bin Aris, R.K.Z. Sahbusdin, A.F.M. Amin, Impacts of IoT and big data to automotive industry, in 2015 10th Asian Control Conf. Emerg. Control Tech. a Sustain. World, ASCC 2015, (2015), pp. 1–5 I. Bin Aris, R.K.Z. Sahbusdin, A.F.M. Amin, Impacts of IoT and big data to automotive industry, in 2015 10th Asian Control Conf. Emerg. Control Tech. a Sustain. World, ASCC 2015, (2015), pp. 1–5
38.
Zurück zum Zitat D. Levinson and P. Investigator, “The Transportation Future s Project: Planning for Technology Change,” 2016. D. Levinson and P. Investigator, “The Transportation Future s Project: Planning for Technology Change,” 2016.
39.
Zurück zum Zitat U. Jayawickrama, S. Liu, and M. H. Smith, “Knowledge prioritisation for ERP implementation success,” Ind. Manag. Data Syst., 2017 U. Jayawickrama, S. Liu, and M. H. Smith, “Knowledge prioritisation for ERP implementation success,” Ind. Manag. Data Syst., 2017
40.
Zurück zum Zitat S. Accelerometers, U. Deep, Estimating Vehicle Movement Direction from Smartphone Accelerometers Using Deep Neural Networks (Senmsors, 2018) S. Accelerometers, U. Deep, Estimating Vehicle Movement Direction from Smartphone Accelerometers Using Deep Neural Networks (Senmsors, 2018)
Metadaten
Titel
Emerging Interactions of ERP Systems, Big Data and Automotive Industry
verfasst von
Florie Bandara
Uchitha Jayawickrama
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-030-70873-3_62

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