Digital Maturity Action Fields for SMES in Developing Economies

Abstract

Resource-dependent small and medium-sized enterprises (SMEs) in developing economies must keep up with large enterprises and self-sufficient SMEs, necessitating their digital transformation. Due to their usual lack of necessary resources such as digital skills and financial means, and their heavy reliance on external entities, many countries have established support systems to assist these resource-dependent SMEs in this undertaking. To ensure appropriate support, it is crucial to evaluate the digital maturity of such SMEs. Although there are numerous models and assessment tools available for assessing digital maturity, regrettably, none of these models adequately addresses the challenges faced by resource-dependent SMEs. This paper tackles the issue of assessing digital maturity specifically for resource-dependent SMEs, proposing a conceptual research framework for this purpose. In this study, the systematic Literature Review (SLR) encompassing comparative analysis methodology is employed to identify the dimensions of digital maturity in SMEs. The lens through which this analysis is conducted is the Resource Dependence Theory (RDT), which allows for the inclusion of the distinctive characteristics exhibited by resource-dependent SMEs. The paper concludes with the presentation of a theoretical conceptual framework that awaits the engagement of researchers to validate and test its propositions using empirical data.

Anomaly Detection In IoT Sensor Data Using Machine Learning Techniques For Predictive Maintenance In Smart Grids

“…Anomaly Detection in IoT Sensor Data: In the wake of digital transformation, anomaly detection has become a crucial component in the realm of the Internet of Things (IoT) and its widespread application in diverse industries [10,29]. In the context of smart grids, where IoT devices are extensively deployed to monitor and control various aspects of the electrical grid, anomaly detection plays a vital role in ensuring the reliability and efficiency of the system [2].…”

Organizational digital transformation: from evolution to future trends

“…Organizations are now harnessing advanced analytics and machine learning to anticipate customer needs, optimize supply chains, and provide highly tailored experiences (Attaran, 2020). This evolution has propelled us into an era where organizations are not merely adopting digital tools but are fundamentally redefining how they operate, compete, and create value (Omol et al, 2023). The digital transformation journey has become an integral part of organizational strategy, influencing every aspect of the modern business landscape.…”

“…and pioneer novel business models that were once considered inconceivable. These technological marvels provide the tools needed to navigate the digital landscape successfully, enabling organizations to thrive in an era of continuous innovation and transformation (Omol et al, 2023).…”

“…However, this voyage is far from straightforward. It requires a deep understanding of the intricate interplay between technology, culture, leadership, and strategy amongst other action fields (Omol et al, 2023). It necessitates the navigation of uncharted territories where innovation and disruption are intertwined.…”

Application Of K-Means Clustering For Customer Segmentation In Grocery Stores In Kenya

“…The retail industry is continuously evolving in the wake of digital transformation [1,30], and grocery stores play a pivotal role in meeting the daily needs of consumers. Understanding customer behavior and preferences is essential for these stores to optimize their marketing strategies, improve customer satisfaction, and enhance overall profitability [2].…”