Big Data as a Management Decision-Making Tool in Digital Business Environments

Author(s):  
Tatyana Y. Salutina ◽  
Elena Y. Klesareva ◽  
Galina P. Platunina
2019 ◽  
Vol 36 (1) ◽  
pp. 25-39 ◽  
Author(s):  
David Egan ◽  
Natalie Claire Haynes

PurposeThe purpose of this paper is to investigate the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing decisions.Design/methodology/approachA three-stage iterative thematic analysis technique based on the approaches of Braun and Clarke (2006) and Nowell et al. (2017) and using different research instruments to collect and analyse qualitative data at each stage was used to develop an explanatory framework.FindingsWhilst big data-driven automated revenue systems are technically capable of making pricing and inventory decisions without user input, the findings here show that the reality is that managers still interact with every stage of the revenue and pricing process from data collection to the implementation of price changes. They believe that their personal insights are as valid as big data in increasing the reliability of the decision-making process. This is driven primarily by a lack of trust on the behalf of managers in the ability of the big data systems to understand and interpret local market and customer dynamics.Practical implicationsThe less a manager believes in the ability of those systems to interpret these data, the more they perceive gut instinct to increase the reliability of their decision making and the less they conduct an analysis of the statistical data provided by the systems. This provides a clear message that there appears to be a need for automated revenue systems to be flexible enough for managers to import the local data, information and knowledge that they believe leads to revenue growth.Originality/valueThere is currently little research explicitly investigating the role of big data in decision making within hotel revenue management and certainly even less focussing on decision making at property level and the perceptions of managers of the value of big data in increasing the reliability of revenue and pricing decision making.


2018 ◽  
Vol 17 (2) ◽  
pp. 55-65 ◽  
Author(s):  
Michael Tekieli ◽  
Marion Festing ◽  
Xavier Baeten

Abstract. Based on responses from 158 reward managers located at the headquarters or subsidiaries of multinational enterprises, the present study examines the relationship between the centralization of reward management decision making and its perceived effectiveness in multinational enterprises. Our results show that headquarters managers perceive a centralized approach as being more effective, while for subsidiary managers this relationship is moderated by the manager’s role identity. Referring to social identity theory, the present study enriches the standardization versus localization debate through a new perspective focusing on psychological processes, thereby indicating the importance of in-group favoritism in headquarters and the influence of subsidiary managers’ role identities on reward management decision making.


2006 ◽  
Author(s):  
Leigh A. Baumgart ◽  
Ellen J. Bass ◽  
Brenda Philips ◽  
Kevin Kloesel

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