This study explores the integration of data mining, customer relationship management (CRM), and strategic management to enhance the understanding of customer behavior and drive revenue growth. The main goal is the use of application of data mining techniques in customer analytics, focusing on the Extended RFM (Recency, Frequency, Monetary Value and count day) model within the context of online retailing. The Extended RFM model enhances traditional RFM analysis by incorporating customer demographics and psychographics to segment customers more effectively based on their purchasing patterns. The study further investigates the integration of the BCG (Boston Consulting Group) matrix with the Extended RFM model to provide a strategic view of customer purchase behavior in product portfolio management. By analyzing online retail customer data, this research identifies distinct customer segments and their preferences, which can inform targeted marketing strategies and personalized customer experiences. The integration of the BCG matrix allows for a nuanced understanding of which segments are inclined to purchase from different categories such as “stars” or “cash cows,” enabling businesses to align marketing efforts with customer tendencies. The findings suggest that leveraging the Extended RFM model in conjunction with the BCG matrix can lead to increased customer satisfaction, loyalty, and informed decision-making for product development and resource allocation, thereby driving growth in the competitive online retail sector. The findings are expected to contribute to the field of Infrastructure Finance by providing actionable insights for firms to refine their strategic policies in CRM.

Objective: As the scale and importance of official development assistance (ODA) continue to grow, the need to enhance the effectiveness of ODA policies has become more critical than ever before. In this context, it is essential to systematically classify recipient countries and establish tailored ODA policies based on these classifications. The objective of this study is to identify an appropriate methodology for categorizing developing countries using specific criteria, and to apply it to actual data, providing valuable insights for donor countries in formulating future ODA policies. Design/Methodology/Approach: The data used in this study are the basic statistics on the Sustainable Development Goals (SDGs) published annually in the SDGs Report. The analytical method employed is decision tree analysis. Results: The results indicate that the 167 countries analyzed were classified into 10 distinct nodes. The study further limited the scope to the five nodes representing the most disadvantaged developing countries and suggested future directions for aid policies for each of these nodes.

This study investigated the relationship between telecommunications development, trade openness and economic growth in South Africa. It determined explicitly if telecommunications development and trade openness directly impact economic growth or whether telecommunications strengthen or weaken the link between trade openness and economic growth using the ARDL bounds test methodology. The findings reveal that both telecommunications development indicators and trade openness significantly and positively impact South Africa’s GDP in the short and long terms. The study also found that control variables like internet usage and gross fixed capital formation significantly and positively influence GDP. Conversely, inflation was found to consistently affect GDP negatively and significantly. The findings from the ARDL cointegration analysis affirm a long-run economic relationship between the independent variables and GDP. The study also established that telecommunications development slightly distorts trade in the foreign trade-GDP nexus in South Africa. Despite this, the negative interaction effect is not substantial enough to overshadow the positive impact of trade openness on economic growth. From a policy perspective, the study recommends that South African policymakers prioritise enhancing local goods’ competitiveness in global markets and reducing trade barriers. It also advocates for improving the accessibility and affordability of telecommunications technologies to foster economic development.

Since the systematic approach of the processes and their interactions, the aim is to establish the configuration of a construction project for the housing of the Weenhayek indigenous people. Applied from the theoretical research of various authors on a group of methodologies, phases and tools for project management, through rational scientific methods, such as descriptive, analytical, comparative, analytical-synthetic, inductive-deductive, historical-logical, analogies, modeling, systemic-structural-functional, systematization; and empirical methods, such as interpretivism that involves inductive, qualitative, phenomenological and transversal research, and the interview technique; the way in which the implementation processes are organized, interacted and structured is established. This reveals an alternative for the detailed configuration of a construction project for Weenhayek houses, based on phases, activities, actions and work tasks with characteristics in accordance with the needs of the project.

This systematic literature review examines data saturation in qualitative research within the context of entrepreneurship studies from 2004 to 2024. Data saturation, a critical concept in ensuring the rigor of qualitative research, remains inadequately defined in terms of sample size and assessment criteria across various studies. This review synthesizes 11 empirical studies, focusing on strategies such as stopping criterion, code frequency counts, and comparative methods for determining saturation. It identifies sample sizes ranging from 7 to 39 interviews, with an average saturation occurring between 10 and 12 interviews. Furthermore, the study explores the influence of different sampling methods and homogeneity of study populations on saturation outcomes. Despite the reliability of existing methods, the findings underscore the need for greater transparency and consistency in reporting saturation criteria. The review offers valuable insights for entrepreneurial researchers aiming to design qualitative studies, emphasizing the importance of tailored saturation standards based on research objectives and methodologies. This research contributes to a clearer understanding of data saturation in entrepreneurial studies and highlights the necessity for further empirical investigation into saturation across diverse qualitative methods.