PurposeBusiness intelligence (BI) systems (i.e. technology and procedures that transform raw data into useful information for managers to enable them to make better and faster decisions) have enormous potential to improve organisational efficiency. However, given the high expenditure involved in the deployment of these systems, the factors that will enable their successful integration should be thoroughly considered and assessed before these systems are adopted. Absorptive capacity (ACAP) is the ability of organisations to gather, absorb and strategically influence new external information, and as such, there is a strong theoretical connection between ACAP and BI systems. This research aims to empirically investigate the relationship between the dimensions underpinning ACAP (i.e. acquisition, assimilation, transformation and exploitation) and whether and how they affect the efficiency of BI systems, which, in turn, can enhance organisational efficiency.Design/methodology/approachThis study formulates five hypotheses addressing the effect of ACAP dimensions on BI systems efficiency and the effect of BI systems efficiency on organisational efficiency. It synthesises previous qualitative work and current research to derive sets of measures for each of the key constructs of the study. It follows a quantitative methodology, which involves the collection of survey data from senior managers in the telecommunications industry and the analysis of the data using partial least squares – structural equation modelling (PLS-SEM).FindingsThe results of the analysis confirmed the validity of the constructs and proposed measures and supported all five hypotheses suggesting a strong positive relationship between the ACAP dimensions, acquisition, assimilation, transformation and exploitation and the efficiency of BI systems and a strong effect of BI systems efficiency on organisational efficiency.Practical implicationsThe study offers a comprehensive model of ACAP and BI systems efficiency. The set of measures that underpin these constructs could help researchers understand how ACAP dimensions are practically implemented and could contribute to their efforts to develop ACAP measurement instruments. At the same time, the model can help managers assess the readiness of their firms to adopt BI systems and identify which areas should be further developed, before committing to the substantial financial investment associated with BI systems. It also provides a set of practical solutions that could be implemented to enable a more robust ACAP and support a better integration of BI systems.Originality/valueFollowing an empirical approach, this study refines one’s theoretical and practical understanding of ACAP as an organisational dynamic capability and its dimensions; it provides an account on how each dimension affects different aspects of BI systems efficiency, which, in turn, may contribute to the improvement of organisational efficiency. Moreover, the study reframes ACAP measures as a set of requirements that can be practically assessed and followed before attempting to purchase BI systems.
Grounded theory methodology (GTM) is an extensive research methodology that is immensely active in numerous social science research fields. It is by far one of the most popular techniques applied in qualitative research. The challenge in using such methods might appear in their complexity. Several steps of coding and analysis in GTM can be fuzzy and multifaceted for novice researchers specialised in Information Systems (IS) fields, knowledge management, and broad applications of IS. The current study suggests a design framework for novices in qualitative research that presents GTM as a set of techniques characterised graphically, allowing the extraction of grounded results and a set of pragmatic analysed data classifications rather than only concentrating on implementing a grounded “theory”. Hence, the research stresses using the term “grounded techniques”, permitting the creation of grounded categories to strengthen qualitative research results' rigour. The proposed framework meticulously exemplifies how an organised set of phases in a research design can enlighten the novice researcher while conducting a study in knowledge absorptive capacity using a comprehensive GTM process to enforce the understanding of GTM techniques.
This study technically analyses one of the online exam supervision technologies, namely the Artificial Intelligence-based Auto Proctoring (AiAP). This technology has been heavily presented to the academic sectors around the globe. Proctoring technologies are developed to provide oversight and analysis of students’ behavior in online exams using AI, and sometimes with the supervision of human proctors to maintain academic integrity in a blended format. Manual Testing methodology was used to do a software testing on AiAP for verification of any possible incorrect red flags or detections. The study took place in a Middle Eastern university by conducting online exams for 14 different courses, with a total of 244 students. Afterward, five human proctors were assigned to verify the data obtained by the AiAP software. The results were then compared in terms of monitoring measurements: screen violation, sound of speech, different faces, multiple faces, and eyes movement detection. The proctoring decision was computed by averaging all monitoring measurements and then compared between the human proctors’ and the AiAP decisions, to ultimately set the AiAP against a benchmark (human proctoring) and hence to be viable for use. The decision represented the number of violations to the exam conditions, and the result showed a significant difference between Human Decision (average 25.95%) and AiAP Decision (average 35.61%), and the total number of incorrect decisions made by AiAP was 74 out of 244 exam attempts, concluding that AiAP needed some improvements and updates to meet the human level. The researchers provided some technical limitations, privacy concerns, and recommendations to carefully review before deploying and governing such proctoring technologies at institutional level. This paper contributes to the field of educational technology by providing an evidence-based accuracy test on an automatic proctoring software, and the results demand institutional provision to better establish an appropriate online exam experience for higher educational institutions.
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