Big data and risk management in business processes: implications for corporate real estate

被引:26
作者
Battisti, Enrico [1 ]
Shams, S. M. Riad [2 ]
Sakka, Georgia [3 ,4 ]
Miglietta, Nicola [1 ]
机构
[1] Univ Turin, Dept Management, Turin, Italy
[2] Northumbria Univ, Newcastle Upon Tyne, Tyne & Wear, England
[3] Univ Nicosia, Nicosia, Cyprus
[4] UNICAF Univ, Larnax, Cyprus
关键词
Business process; Risk management; Business process management; Big data; Corporate real estate; Digital transformation; KNOWLEDGE MANAGEMENT; INTERNET; THINGS; INNOVATION; ANALYTICS; SYSTEMS; INTELLIGENCE; CHALLENGES; IMPACT; MODEL;
D O I
10.1108/BPMJ-03-2019-0125
中图分类号
F [经济];
学科分类号
02 ;
摘要
Purpose The purpose of this paper is to improve understanding of the integration between big data (BD) and risk management (RM) in business processes (BPs), with special reference to corporate real estate (CRE). Design/methodology/approach This conceptual study follows, methodologically, the structuring inter-textual coherence process - specifically, the synthesised coherence tactical approach. It draws heavily on theoretical evidence published, mainly, in the corporate finance and the business management literature. Findings A new conceptual framework is presented for CRE to proactively develop insights into the potential benefits of using BD as a business strategy/instrument. The approach was found to strengthen decision-making processes and encourage better RM - with significant consequences, in particular, for business process management (BPM). Specifically, by recognising the potential uses of BD, it is also possible to redefine the processes with advantages in terms of RM. Originality/value This study contributes to the literature in the fields of real estate, RM, BPM and digital transformation. To the best knowledge of authors, although the literature has examined the concepts of BD, RM and BP, no prior studies have comprehensively examined these three elements and their conjoint contribution to CRE. In particular, the study highlights how the automation of data-intensive activities and the analysis of such data (in both structured and unstructured forms), as a means of supporting decision making, can lead to better efficiency in RM and optimisation of processes.
引用
收藏
页码:1141 / 1155
页数:15
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