Purpose: Few well-documented studies have explained the importance of researching firms' marketing analytics capability (FMAC). In spite of its significance, there is scant attention to conceptualising and empirically investigating FMAC and its consequences in a data-driven business context. Thus, this study aims to develop and test a conceptual model that relates FMAC and its repercussions in the data-rich business environment.Design/methodology/approach: This study analysed the data from 250 managers amongst large and medium-sized manufacturing and service-intensive firms. Furthermore, this research performed an empirical study by using operationalised questionnaire survey method to verify the hypotheses and reach its theoretical and managerial implications. Structural equation modelling with maximum-likelihood estimation method was applied to verify the validity of the proposed research model.Findings: Multivariate analysis results show that FMAC significantly influences firms' competitive marketing performance (FCMP) with the presence of holistic marketing decision-making (HMDM) as a mediator. Moreover, adoption of artificial intelligence (AAI) enhances the relationship of FMAC-HMDM and FMAC-FCMP linkages.Practical implications: This study analyses how FMAC can enhance FCMP and contributes to resource-based views and technological capability theories. From a managerial perspective, guidelines are provided for marketers to adopt advance technologies, such as AI, to optimise FMAC and HMDM to achieve competitive marketing performance.Originality/value: Believing that “how to be competitive in marketing performance under data-rich-environment”, this research is the first to use the data of a firm manager to facilitate the understanding of FMAC, which provides a new direction for improving marketing performance. In addition, HMDM and AAI are also proposed for firms to optimise FCMP.

Purpose: This paper aims to review the critical challenges and factors influencing the successful adoption of electronic learning (e-learning) systems in higher educational institutions before and during the current propagation of the coronavirus disease 2019 (COVID-19) pandemic.Design/methodology/approach: This study undertook a literature review concerning the in-depth revision of previous studies published in 2020 and 2021. A total of 100 out of 170 selected research papers were adopted to identify and recognise the factors restricting the application of e-learning systems.Findings: The findings determine and illuminate the most challenging factors that impact the successful application of online learning, particularly during the wide propagation of the COVID-19 pandemic. The review of the literature provides evidence that technological, organisational and behavioural issues constitute significant drivers that frontier the facilitation of the e-learning process in higher educational institutions.Practical implications: The current paper suggests a guide for managers and scholars in educational institutions and acts as a roadmap for practitioners and academics in the educational field and policymakers as this research spotlights the significant factors challenging the e-learning process before and during the pandemic crisis.Originality/value: The provided in-depth literature review in this research will support the researchers and system designers with a comprehensive review and recent studies conducted before and during the COVID-19 pandemic considering the factors limiting the e-learning process. This paper formulates a valuable contribution to the body of knowledge that will assist the stakeholders in the higher educational institutions' context.Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2022-0085.