Abstract
This article discusses the results of a multi-industry and multi-country survey carried out to understand the needs, requirements, and use of big data and analytics by public and private organizations in decision-making, business processes and emerging business models. In particular, these issues are analyzed in specific industries where big data exploitation may have not only an economic value but also and an impact on social value dimensions such as, e.g., public and personal safety. Furthermore, the survey aims at questioning the characteristics of big data ecosystems in different and specific domains, thus identifying existing or potential barriers to the development of new data-driven industrial sectors along the big data information value chain. Finally, the authors have identified three key challenges (big data efficiency, effectiveness, and accessibility) to classify the survey results that showed low utilization rate of the data collected, lack of right tools and capabilities, the low rate of digital transformation of the companies as the key concerns for the respondents.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
The Economist: Big Data (2011)
The Economist: Data, data everywhere (2010)
IBM: What is big data? http://www-01.ibm.com/software/data/bigdata/
Kitchin, R., McArdle, G.: What makes big data, big data? Exploring the ontological characteristics of 26 datasets. Big Data Soc. 3, 2053951716631130 (2016)
Dumbill, E.: Making sense of big data (editorial). Big Data 1, 1–2 (2013)
Viscusi, G., Batini, C.: Digital information asset evaluation: characteristics and dimensions. In: Caporarello, L., Di Martino, B., Martinez, M. (eds.) Smart Organizations and Smart Artifacts. LNISO, vol. 7, pp. 77–86. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07040-7_9
Buhl, H.U., Röglinger, M., Moser, F., Heidemann, J.: big data - a fashionable topic with(out) sustainable relevance for research and practice? Bus. Inf. Syst. Eng. 5, 65–69 (2013)
Benington, J., Moore, M.H.: Public Value - Theory and Practice. Palgrave Macmillan, Basingstoke (2011)
Cordella, A., Bonina, C.M.: A public value perspective for ICT enabled public sector reforms: a theoretical reflection. Gov. Inf. Q. 29, 512–520 (2012)
Morris, S., Shin, H.: Social value of public information. Am. Econ. Rev. 92, 1521–1534 (2002)
Batini, C., Rula, A., Scannapieco, M., Viscusi, G.: From data quality to big data quality. J. Database Manag. 26, 60–82 (2015)
Viscusi, G., Castelli, M., Batini, C.: Assessing social value in open data initiatives: a framework. Futur. Internet 6, 498–517 (2014)
Abbasi, A., Sarker, S., Chiang, R.H.L.: Big data research in information systems: toward an inclusive research agenda. J. Assoc. Inf. Syst. 17, 3 (2016)
Oliveira, T., Martins, M.: Literature review of information technology adoption models at firm level. Electron. J. Inf. 14, 110–121 (2011)
Thong, J.Y.L.: An integrated model of information systems adoption in small businesses. J. Manag. Inf. Syst. 15, 187–214 (1999)
Oliveira, T., Thomas, M., Espadanal, M.: Assessing the determinants of cloud computing adoption: an analysis of the manufacturing and services sectors. Inf. Manag. 51, 497–510 (2014)
Davis, F.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13, 319–340 (1989)
Venkatesh, V., Bala, H.: Technology acceptance model 3 and a research agenda on interventions. Decis. Sci. 39, 273–315 (2008)
Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478 (2003)
DeLone, W.H., McLean, E.R.: Information system success: the quest for the dependent variable. Inf. Syst. Res. 3, 60–95 (1992)
DeLone, W.H., McLean, E.R.: The DeLone and McLean model of information systems success: a ten-year update. J. Manag. Inf. Syst. 19, 9–30 (2003)
Petter, S., DeLone, W., McLean, E.: Measuring information systems success: models, dimensions, measures, and interrelationships. Eur. J. Inf. Syst. 17, 236–263 (2008)
Ives, B., Olson, M.H., Baroudi, J.J.: The measurement of user information satisfaction. Commun. ACM 26, 785–793 (1983)
Baroudi, J., Orlikowski, W.: A short-form measure of user information satisfaction: a psychometric evaluation and notes on use. J. Manag. Inf. Syst. 4, 44–59 (1988)
Iivari, J., Ervasti, I.: User information satisfaction: IS implementability and effectiveness. Inf. Manag. 27, 205–220 (1994)
Wixom, B.H., Todd, P.A.: A theoretical integration of user satisfaction and technology acceptance. Inf. Syst. Res. 16, 85–102 (2005)
Ahituv, N.: A systematic approach towards assessing the value of an information system. MIS Q. 4, 61–75 (1980)
Ahituv, N.: Assessing the value of information: problems and approaches. In: DeGross, J.I., Henderson, J.C., Konsynski, B.R. (eds.) International Conference on Information Systems (ICIS 1989), pp. 315–325. Massachusetts, Boston (1989)
Viscusi, G., Spahiu, B., Maurino, A., Batini, C.: Compliance with open government data policies: an empirical assessment of Italian local public administrations. Inf. Polity. 19, 263–275 (2014)
Newsted, P.R., Huff, S.L., Munro, M.C.: Survey instruments in information systems. MIS Q. 22, 553 (1998)
Dillman, D.A., Smyth, J.D., Christian, L.M.: Internet, Mail, and Mixed-Mode Surveys: The Tailored Design Method. Wiley, Hoboken (2008)
AEGIS: Project At a Glance. https://www.aegis-bigdata.eu
Tsai, C.-W., Lai, C.-F., Chao, H.-C., Vasilakos, A.V.: Big data analytics: a survey. J. Big Data 2, 21 (2015)
Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mob. Netw. Appl. 19, 171–209 (2014)
Porter, M.E., Millar, V.E.: How information gives you competitive advantage. Harv. Bus. Rev. 63, 149–162 (1985)
Zillner, S., et al.: Big data-driven innovation in industrial sectors. In: Cavanillas, J.M., Curry, E., Wahlster, W. (eds.) New Horizons for a Data-Driven Economy, pp. 169–178. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-21569-3_9
Sambamurthy, V., Bharadwaj, A., Grover, V.: Shaping agility through digital options: reconceptualizing the role of information technology in contemporary firms. MIS Q. 27, 237–263 (2003)
Chen, D.Q., Preston, D.S., Swink, M.: How the use of big data analytics affects value creation in supply chain management. J. Manag. Inf. Syst. 32, 4–39 (2015)
Acknowledgements
This work was supported by the AEGIS project, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 732189. The document reflects only the author’s views and the Commission is not responsible for any use that may be made of information contained therein.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Rossi, E., Rubattino, C., Viscusi, G. (2019). For What It’s Worth: A Multi-industry Survey on Current and Expected Use of Big Data Technologies. In: Themistocleous, M., Rupino da Cunha, P. (eds) Information Systems. EMCIS 2018. Lecture Notes in Business Information Processing, vol 341. Springer, Cham. https://doi.org/10.1007/978-3-030-11395-7_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-11395-7_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-11394-0
Online ISBN: 978-3-030-11395-7
eBook Packages: Computer ScienceComputer Science (R0)