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.

Graphene oxide can be referred to as oxidized graphene. Similar to graphene, oxidized graphene possesses remarkable structural features, advantageous properties, and technical applications. Among polymeric matrices, conducting polymers have been categorized for p conjugated backbone and semiconducting features. In this context, doping, or nano-additive inclusion, has been found to enhance the electrical conduction features of conjugated polymers. Like other carbon nanostructures (fullerene, carbon nanotube, etc.), graphene has been used to reinforce the conjugated matrices. Graphene can be further modified into several derived forms, including graphene oxide, reduced graphene oxide, and functionalized graphene. Among these, graphene oxide has been identified as an important graphene derivative and nanofiller for conducting matrices. This overview covers essential aspects and progressions in the sector of conjugated polymers and graphene oxide derived nanomaterials. Since the importance of graphene oxide derived nanocomposites, this overview has been developed aiming at conductive polymer/graphene oxide nanocomposites. The novelty of this article relies on the originality and design of the outline, the review framework, and recent literature gathering compared with previous literature reviews. To the best of our knowledge, such an all-inclusive overview of conducting polymer/graphene oxide focusing on fundamentals and essential technical developments has not been seen in the literature before. Due to advantageous structural, morphological, conducting, and other specific properties, conductive polymer/graphene oxide nanomaterials have been applied for a range of technical applications such as supercapacitors, photovoltaics, corrosion resistance, etc. Future research on these high-performance nanocomposites may overcome the design and performance-related challenges facing industrial utilization.

 This study explores the primary drivers influencing sustainable project management (SPM) practices in the construction industry. This research study seeks to determine whether firms are primarily motivated by external pressures or internal values when embracing SPM practices. In doing so, this study contributes to the ongoing discourse on SPM drivers by considering coercive pressures (CP), ethical responsibility (ER), and green transformational leadership (GTL) as critical enablers facilitating a firm’s adoption of SPM practices. Based on data from 196 project management practitioners in Pakistan, structural equation modeling (PLS-SEM) was employed to test the hypothesized relationships. Results highlight that CP influences the management of sustainability practices in construction projects, signifying firms’ concern for securing legitimacy from various institutional actors. As an ‘intrinsic value’, ER emerges as a significant motivator for ecological stewardship, driven by a genuine commitment to promoting sustainable development. This study also unveils the significant moderating effect of GTL on the association among CP, ER, and SPM. Lastly, the results of IMPA reveal that ER slightly performs better than CP as it helps firms internalize the essence of sustainability. This research study expands our understanding of SPM drivers in construction projects by exploring the differential impact of external pressures and the firm’s intrinsic values. These findings provide valuable insights for policymakers and practitioners, aiding them in promoting SPM to attain sustainable development goals.

Nanocomposites are high performance materials which reveal rare properties. Nanocomposites have an estimated annual growth rate of 25% and fastest demand to be in engineering plastics and elastomers. Their prospective is so prominent that they are valuable in numerous areas ranging from packaging to biomedical applications. In this review, the various types of matrix nanocomposites are discussed highlighting the need for these materials, their processing approaches and some recent results on structure, properties and potential applications. Perspectives include need for such future materials and other interesting applications. Being environmentally friendly, applications of nanocomposites propose new technology and business opportunities for several sectors of the aerospace, automotive, electronics and biotechnology industries.

A novel composite material based on polymers (polyvinyl alcohol, polyvinyl butyral) and liquid crystal (4-n-pentyl-4’-cyanobiphenyl) has been developed and studied. Configuration transformations of point defects in nematic droplets under the influence of an electric field, caused by localized changes in the concentration of NLC within the polymer matrix, have been discovered and analyzed. The boundary conditions necessary for achieving a nematic structure with homogeneous alignment of the director both within the droplet and at its surface have been established, optimizing the anisotropy of light transmission in polymer-dispersed liquid crystal (PDLC) films. Additionally, polarization effects inside nematic droplets under the application of an electric field have been identified.

Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.