Table 4

Factors affecting BDA adoption in SCP

FactorsDefinition and referenceExample and measuresReference
Technological
Relative advantage of BDAThe degree to which BDA is perceived as being better than the idea it supersedes to provide benefits such as cost reduction, operation improvement and marketing performance (Lai et al., 2018; Gunasekaran et al., 2017)Relative advantage***Maroufkhani et al. (2020) 
Improved decision making; Operational efficiencyRichey et al. (2016) 
Awareness of BDA benefitQueiroz and Telles (2018) 
Perceived benefit*Lai et al. (2018) 
Unclear business case or value; No need/not necessary/no benefitSchoenherr and Speier-Pero (2015) 
BDA technology complexityThe degree to which BDA can be regarded difficult to be understood and used for the organisation. (Lai et al., 2018; Roger, 1983)BDA complexity*Maroufkhani et al. (2020) 
Technology complexity***Lai et al. (2018) 
(challenge of) Data storage; (need of) Climbing the learning curve
One version of truth (single integrated system, usability);		Richey et al. (2016) 
Difficult to manage;
Inability to make sense of available data		Schoenherr and Speier-Pero (2015) 
Information (complexity) managementKache and Seuring (2017) 
BDA technology compatibilityThe degree to which BDA is perceived as being compatible to current information system and consistent with the existing values (Lai et al., 2018)BDA compatibility***Maroufkhani et al. (2020) 
Data scalabilityArunachalam et al. (2018) 
Lack of integration with current systemsSchoenherr and Speier-Pero (2015) 
BDA trialabilityThe degree to which BDA may be experimented with (Lai et al., 2018; Fosso Wamba et al., 2016)BDA trialabilityMaroufkhani et al. (2020) 
BDA observabilityThe degree to which the results of BDA are visible to the organisation (Lai et al., 2018; Fosso Wamba et al., 2016)BDA observabilityMaroufkhani et al. (2020) 
Big data qualityThe degree to which the data needed for BDA are accessible, consistent, and complete, and is integrated between the data collected (Lai et al., 2018; Rai et al., 2006)Data qualityArunachalam et al. (2018) 
Data quality**Lai et al. (2018) 
Lack of dataSchoenherr and Speier-Pero (2015) 
Data pools (data acquisition);
Validation tools		Sodero et al. (2019) 
Dealing with data growth and amount of accessible dataYudhistyra et al. (2020) 
BDA availability and stabilityThe degree to which BDA is stable and available (or already in use) both internally and externally (Baker, 2012; Oliveira and Martins, 2011)BDA uncertainty*Maroufkhani et al. (2020) 
Lack of techniques and proceduresArunachalam et al. (2018) 
Lack of appropriate solutions for SCM; Current applications unable to meet business needsSchoenherr and Speier-Pero (2015) 
Availability for real-time analysisYudhistyra et al. (2020) 
Organisational
Organisational readinessThe organisational preparedness for adopting the BDA change (Lai et al., 2018; Hameed and Arachchilage, 2016)Organisational culture and change management (e.g. data-driven culture, mindset of employee towards new system, transformational change management, culture change management, organisational resistance, entrepreneurial orientation)Arunachalam et al. (2018), Dubey et al. (2019), Dutta and Bose (2015), Kache and Seuring (2017), Lamba and Singh (2018), Schoenherr and Speier-Pero (2015), Yudhistyra et al. (2020), Dubey et al. (2020) 
Top management support*Lai et al. (2018), Maroufkhani et al. (2020) 
Top management support (or, top management commitment, top management involvement)Lamba and Singh (2018), Richey et al. (2016), Schoenherr and Speier-Pero (2015), Sodero et al. (2019) 
Financial readiness***Lai et al. (2018) 
Financial support and investmentKache and Seuring (2017), Lamba and Singh (2018), Queiroz and Telles (2018) 
Slack (human) resource (e.g. talent management and HR, Organisations' talented professionals, human capital)Kache and Seuring (2017), Queiroz and Telles (2018), Richey et al. (2016) 
Organisational competenceThe internal competence of the organisation in adopting the BDA change (Oliveira and Martins, 2011)Personnel level competence (e.g. human skill, lack of skill, technical knowledge business knowledge, relational knowledge, employees are inexperienced, technological capabilities)Arunachalam et al. (2018), Dubey et al. (2019), Mandal (2018), Schoenherr and Speier-Pero (2015), Sodero et al. (2019) 
Organisational-level competence (e.g. tangible resources, BDA skill and knowledge, company's IT tool unitization, data generation capability, data integration capability, advanced analytics capability, inability to identify most suitable data, IT capabilities and infrastructure)Dubey et al. (2019), Lamba and Singh (2018), Queiroz and Telles (2018), Arunachalam et al. (2018), Schoenherr and Speier-Pero (2015), Kache and Seuring (2017) 
IT infrastructure and capabilities***Lai et al. (2018) 
Organisation strategyThe business strategy at the organisational level that deal with the adoption of BDA technologyBusiness strategy and objectiveKache and Seuring (2017) 
Company's projects to use BDA in short term;
Company's BDA utilization in LSCM; Company's formal strategies to SCM innovation		Queiroz and Telles (2018) 
Organisational structureOrganisational structure intends for organisational size, stability, business scope, interconnectedness, presence of slack resources (Russel and Hoag, 2004; Baker, 2012)Organisational structureLamba and Singh (2018), Schoenherr and Speier-Pero (2015) 
Organisational complexitySodero et al. (2019) 
Supply chain structureThe possibility to gather and deliver information within organisations through some information technologies that facilitates the cooperation and coordination between supply chain members (Lai et al., 2018)SC integration (governance and compliance, integration and collaboration, SC connectivity, SC system integration, partner transparency, coordination)Kache and Seuring (2017), Lai et al. (2018), Richey et al. (2016), Sodero et al. (2019), Yu et al. (2018), Wamba et al. (2019), Fosso Wamba and Akter (2019) 
SC agility (e.g. SC agility, SC adaptability, responsiveness)Wamba et al. (2019), Yu et al. (2018) 
SC capability (e.g. SC management capability, SC technology capability, SC talent capability, SC analytics capability)Fosso Wamba and Akter (2019) 
Environmental
Security and privacy concerns on BDAThe degree to which organisations concern about privacy invasions and security risks in the use of BDA technology. (Accenture; Salleh et al., 2015) Privacy and security concern; privacy of the data; IT concern;
Risk and security governance; Information and cyber security;		Arunachalam et al. (2018), Yudhistyra et al. (2020); Kache and Seuring (2017), Queiroz and Telles (2018), Richey et al. (2016), Schoenherr and Speier-Pero (2015) 
BDA adoption of competitorsThe degree to which organisations perceive pressure from business competitors on using BDA technology to maintain competitive (Lai et al., 2018)BDA adoption of competitors*Lai et al. (2018) 
Competitive pressure***Maroufkhani et al. (2020) 
Regulatory environmentThe administrative and regulatory environment where the organisation operates, which can be both pressure or support in government policies (Lai et al., 2018; Baker, 2012; Oliveira and Martins, 2011)Government policy and regulation*Lai et al. (2018) 
High degree of regularity***Maroufkhani et al. (2020) 
Lack of policies and governance structureSchoenherr and Speier-Pero (2015) 
Presence of BDA service providersThe degree to which it presents BDA service providers and other third-party vendors in the market when most organisations are still unable to build and maintain the technology in-house (Baker, 2012)Market's talented professionalsQueiroz and Telles (2018) 
Cost of currently available solutionsSchoenherr and Speier-Pero (2015) 

Note(s): *indicate measures result as supported, **indicate measures result as supported by not significant, ***indicate measures result as not supported

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