Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain

By Rameshwar Dubey, Angappa Gunasekaran, Stephen J. Childe, David Roubaud, Samuel Fosso Wamba, Mihalis Giannakis, Cyril R. H. Foropon. International Journal of Production Economics, 2019

381 citations recorded by the source corpus.

Abstract The main objective of the study is to understand how big data analytics capability (BDAC) as an organizational culture can enhance trust and collaborative performance between civil and military organizations engaged in disaster relief operations. The theoretical framework is grounded in organizational information processing theory (OIPT). We have conceptualized an original theoretical model to show, using the competing value model (CVM), how BDAC, under a moderating influence of organizational culture, affects swift trust (ST) and collaborative performance (CP). We used WarpPLS 6.0 to test the proposed research hypotheses using multi-respondent data gathered through an email questionnaire sent to managers working in 373 organizations, including the military forces of different countries, government aid agencies, UN specialized agencies, international non-government organizations (NGOs), service providers, and contractors. The results offer four important implications. First, BDAC has a positive, significant effect on ST and CP. Second, flexible orientation (FO) and controlled orientation (CO) have no significant influence on building ST. Third, FO has a positive and significant moderating effect on the path joining BDAC and CP. Finally, CO has negative and significant moderating effect on the path joining BDAC and CP. The control variables: temporal orientation (TO) and interdependency (I) have significant effects on ST and CP. These results extend OIPT to create a better understanding of the application of information processing capabilities to build swift trust and improve collaborative performance. Furthermore, managers can derive multiple insights from this theoretically-grounded study to understand how BDAC can be exploited to gain insights in contexts of different management styles and cultures. We have also outlined the study limitations and provided numerous future research directions.

Subfields: Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/03ceee62c15b79f8160c9132e71edcedef1096bb

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Citations in the corpus

Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting (2020, methodology): “…of organisational information processing theory (OIPT) (see Gattiker and Goodhue 2004; Haußmann et al. 2012; Srinivasan and Swink 2015, 2018; Dubey et al. 2019a, 2019c) and relational view (RV) (Dyer and Singh 1998), because neither perspective can, on its own, explain the direct or…”
Disruption risks in supply chain management: a literature review based on bibliometric analysis (2020, methodology): “…to combine different methodologies, such as quantitative modelling (Fahimnia et al. 2015), simulations (Ivanov 2018, 2019), and empirical studies (Dubey et al. 2019a, 2019b; Ambulkar, Blackhurst, and Grawe 2015; Mishra et al. 2016), to mutually justify the correctness of the proposed managerial…”
Evaluating the factors that influence blockchain adoption in the freight logistics industry (2020, background): “Organizational culture affects how firms respond to external pressures and makes strategic business decisions (Dubey et al, 2019).”