Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review

Abstract

In the current market landscape, enterprises face tremendous pressure to remain competitive and innovative to extend their businesses globally. Thus, a need exists for a new data analysis technique and a tool known as Big Data Analytics (BDA), which refers to massive data sets in light of their volume, velocity, variety, and veracity. Small and Medium Enterprises (SMEs) face challenges in obtaining and utilizing the knowledge derived from big data to make informed decisions regarding market selection and adopting appropriate internationalization strategies. These enterprises encounter resource limitations that hinder their ability to effectively acquire and implement big data insights for strategic decision-making in these areas. This systematic literature review aims to investigate the state of research on adopting big data analytics in SMEs. The study focuses on identifying key factors that influence the adoption of BDA. The study extracted 13 significant factors that are the highest influencers for BDA in SMEs. Those factors are top management support, training, relative advantage, it infrastructure, security, compatibility, complexity, adaptability, government it policies, competency, collaboration, digital transformation tools, and decision quality. The findings of this review are useful for practitioners, researchers, and decision-makers in understanding the factors that influence the adoption of big data analytics and the potential benefits and challenges associated with its implementation. Findings will shed light on the interplay between data governance and other factors influencing adoption, providing valuable insights for organizations seeking to establish robust data governance frameworks that support successful BDA initiatives.

The Critical Success Factors Influencing the Use of Mobile Learning and its Perceived Impacts in Students’ Education: A Systematic Literature Review

“…"Mobile learning and students", S5= "Mobile learning in education" S1= "399", S2= "53", S3= "39", S4= "6", S5= "10" The detailed methodology of this study is not just a procedural backbone but a critical element that directly shapes the credibility, specificity, and applicability of our findings and conclusions. This kind of study allows us to confidently assert that the identified critical success factors are key influencers in the effective implementation and perceived impacts [32] of mobile learning in students' education. The following sub-sections explain the SLR steps in detail.…”

“…This study adopted the SLR based on a comprehensive and systematic method for identifying and analyzing the studies [31][32][33] in M-learning adoption among students of higher education institutions. The steps taken towards carrying out the SLR are presented in the following Fig.…”

“…Several conditions exist for defining a research question: clarity, relevance, specificity, importance, feasibility, testability, and novelty [34]. In other words, the question needs to be developed to allow the determination of its answer within the study scope, and it needs to explain the knowledge gap and contribute to the phenomenon being examined [32,34]. The question must also be feasible and achievable within available resources and be innovative, original, and present viewpoints to the study field [35].…”

“…In the case of a well-thought-out search procedure, the execution of the resources at hand is required to determine the relevant studies that meet the research conditions [32,35]. This determination using SLR is core to searching the relevant sources and maintaining SLR standards.…”

“…The study selection process was categorized into different phases in the initial review -this entailed reviewing the titles of the articles based on the inclusion and exclusion criteria [16,32]. The papers that were not cut were dropped, while the remaining ones were filtered by reviewing their abstracts and findings.…”