Abstract
The hospitality industry is growing at a faster pace across the world which results in accumulating a huge amount of data in terms of employee details, property details, purchase details, vendor details and so on so forth. The industry is yet to fully benefit from these big data and the data has not been investigated to all extent for decision making or revenue/budget forecasting. Chae et al., 2014 has proposed in his paper to have descriptive, predictive and prescriptive data analysis as a good tool to analyze the big data collected in such means. In this paper, the author has tried to explore the data and produce some useful visual reports which is beneficial for the top management that give extra information about the inventoried data. The visual representation is limited to descriptive and predictive data analysis due to the time constraints. The author has used mainly R studio for the visual reporting. The author’s vision is to do an extended study by further investigation with the information gathered for prediction and decision making.
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References
Wang, G., Gunasekaran, A., Ngai, E., Papadopoulos, T.: Big data analytics in logistics and supply chain management: certain investigations for research and applications. Int. J. Prod. Econ. 176, 98–110 (2016)
Varela Rozados, I., Tjahjono, B.: Big data analytics in supply chain management: trends and related research. In: International Conference on Operations and Supply Chain Management, vol. 6, no. 1 (2014)
Albano, G., Antellini Russo, F., Castaldi, G., Zampino, R.: Evaluating small businesses’ performance in public e-Procurement: evidence from the Italian government’s e-marketplace. J. Small Bus. Manag. 53, 229–250 (2015)
Croom, S., Brandon-Jones, A.: Impact of e-procurement: experiences from implementation in the UK public sector. J. Purchasing Supply Manag. 13(4), 294–303 (2007)
Johnson, M.: A study of e-market adoption barriers in the local government sector. J. Enterp. Inf. Manag. 25(6), 509–536 (2012)
Kothari, T., Hu, C., Roehl, W.: Adopting e-Procurement technology in a chain hotel: an exploratory case study. Int. J. Hospitality Manag. 26(4), 886–898 (2007). https://doi.org/10.1016/j.ijhm.2006.01.005
Kothari, T., Hu, C., Roehl, W.: Adopting e-Procurement technology in a chain hotel: An exploratory case study (2018). Accessed 4 June 2018
Piluso, J., Leimer, M., Zhang, K.: Empowered by analytics: procurement in 2025. EY: Building a better world, vol. 11, no. 14 (2016)
Shi, X., Liao, Z.: Managing supply chain relationships in the hospitality services: an empirical study of hotels and restaurants. Int. J. Hospitality Manag. 35, 112–121 (2013)
Teo, T., Lin, S., Lai, K.: Adopters and non-adopters of e-procurement in Singapore: an empirical study. Omega 37(5), 972–987 (2009)
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Mathew, E. (2019). Big Data Analytics in E-procurement of a Chain Hotel. In: Barolli, L., Xhafa, F., Khan, Z., Odhabi, H. (eds) Advances in Internet, Data and Web Technologies. EIDWT 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-030-12839-5_27
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DOI: https://doi.org/10.1007/978-3-030-12839-5_27
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