This investigation extends into the intricate fabric of customer-based corporate reputation within the banking industry, applying advanced analytics to decipher the nuances of customer perceptions. By integrating structural equation modeling, particularly through SmartPLS4, we thoroughly examine the interrelations of perceived quality, competence, likeability, and trust, and how they culminate in customer satisfaction and loyalty. Our comprehensive dataset is drawn from a varied demographic of banking consumers, ensuring a holistic view of the sector’s reputation dynamics. The research reveals the profound influence of these constructs on customer decision-making, with likeability emerging as a critical driver of satisfaction and allegiance to the bank. We also rigorously test our model’s internal consistency and convergent validity, establishing its reliability and robustness. While the direct involvement of Business Intelligence (BI) tools in the research design may not be overtly articulated, the analytical techniques and data-driven approach at the core of our methodology are synonymous with BI’s capabilities. The insights garnered from our analysis have direct implications for data-driven decision-making in banking. They inform strategies that could include enhancing service personalization, refining reputation management, and improving customer retention efforts. We acknowledge the need to more explicitly detail the role of BI within the research process. BI’s latent presence is inherent in the analytical processes employed to interpret complex data and generate actionable insights, which are crucial for crafting targeted marketing strategies. In summary, our research not only contributes to academic discourse on marketing and customer perception but also implicitly demonstrates the value that BI methodologies bring to understanding and influencing consumer behavior in the banking sector. It is this blend of analytics and marketing intelligence that equips banks with the strategic leverage necessary to thrive in today’s competitive financial landscape.

Firms, recognizing their Corporate Social Responsibility (CSR), are becoming catalysts for societal change by integrating Environmental, Social and Governance (ESG) criteria into their activities. The fashion industry exemplifies this effort, with an increasing number of companies embracing sustainability and ethical practices. In this context, our purpose is to provide a clear and comprehensive picture of the link between sustainability and business performance in the fashion industry. This work presents a Multivariate Regression Analysis, scrutinizing both external perspectives through stock prices and internal perspectives via profitability indices. Our aim is to discern the intricate relationship between sustainability practices and financial performance within the fashion industry, aligning ESG criteria with long-term economic success. Our regression analysis reveals a significant positive correlation between ESG scores and stock prices, indicating investor recognition of ESG performance as a crucial investment criterion. However, when focusing internally on profitability, the ESG score does not exhibit statistical significance, suggesting a yet-to-be-established connection between ESG policies and corporate profitability. This study underscores the evolving role of companies as sustainability promoters, emphasizing the crucial role of ESG performance in shaping investor perceptions. Nevertheless, it also highlights the need for further exploration into the intricate relationship between sustainable policies and corporate profitability. As businesses increasingly embrace sustainability, in fact, it could become paramount for informed decision-making and fostering ethical societal and environmental progress.

The United Nations General Assembly declared 2023 the “International Year of Millets” in order to promote millet cultivation, consumption, and conservation. Millets play an important role in food security, livelihoods, and biodiversity. Despite its numerous benefits, millet cultivation and consumption in Uttarakhand have declined due to a variety of constraints. This paper examines the effects of regiocentrism and materialism on intention towards Uttarakhand’s regional food products (millets). It employs PLS-SEM to investigate relationships between latent variables and generate results on a sample of 460 participants. This study elucidates the intricate interplay between materialism, regiocentrism, and intention towards regional food products in the Himalayan region, enriching the theory of planned behavior (TPB) with a nuanced understanding of personal values and regional identity. It reveals materialism’s positive association with attitudes towards regional food products, suggesting materialistic individuals may view these products as status symbols, thus affecting behavioral intentions. Additionally, the research highlights regiocentrism’s dual influence—enhancing attitudes yet deterring purchase intentions—underscoring the complexity of regional pride in consumer decision-making. These findings advance TPB by integrating broader value systems and cultural context, offering significant theoretical and practical insights for promoting sustainable consumption patterns.

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.

This article aims to analyze the role of the Medan City Religious Harmony Forum (FKUB) in shaping harmony in digital literacy-based virtual communities. FKUB has a central role as an institution that ensures that the aspirations and interests of religious communities can be accommodated effectively. In addition to making real improvements, FKUB also initiated its moderating role through the digital realm. This research adopts a qualitative method using a phenomenological approach. Primary data was obtained through interactions with key informants, while secondary data sources involved articles, books, reportage related to the context of the research theme. Data collection was conducted through interview, observation, and documentation techniques. Data analysis used the Miles and Huberman analysis model with the steps of data coding, data presentation, and conclusion drawing. The results showed that FKUB initiated digital literacy-based religious moderation through two development communication models. The first model is a linear model where FKUB acts as a community educator. The second model is a participatory model that is usually uploaded on Instagram, FaceBook and Youtube social media. This model allows the community to comment and have two-way communication with the FKUB. Both models are oriented towards creating collective intelligence as an indicator of building virtual harmony. Through digital literacy-based development communication, FKUB can be a mediator in meeting the Sustainable Development Goals (SDG’s), namely: Peace, justice and strong institutions, as well as promoting equality and reducing inequality.

This cross-sectional study examines the knowledge, perception, and practice of health professions students and academics in Jordan concerning halal pharmaceuticals. Health professions students and academics from various universities in Jordan were surveyed using a structured questionnaire. Data analysis included descriptive statistics and inferential tests to identify factors affecting knowledge, perception, and practice. Participants had a high level of awareness regarding general halal and haram concepts, but there was relatively lower awareness of the term “halal pharmaceuticals” and detailed information about non-halal ingredients. Knowledge scores varied between students and academics, with academics scoring higher. Participants exhibited positive perceptions, acknowledging the importance of knowledge about halal pharmaceuticals and patients’ rights to inquire about medication sources and ingredients. Concerns were raised about the potential controversy surrounding the topic. This research contributes to understanding the role of halal pharmaceuticals in healthcare, particularly in predominantly Muslim countries. The findings highlight the importance of integrating education on halal pharmaceuticals into healthcare curricula, emphasizing patient-centered care, and addressing cultural and religious sensitivity. There is a need for tailored educational approaches and sensitivity training to bridge the gap between knowledge and practice.

Amidst an upsurge in the quantity of delinquent loans, the financial industry is experiencing a fundamental transformation in the approaches utilised for debt recovery. The debt collection process is presently undergoing automation and improvement through the utilisation of Artificial Intelligence (AI), an emergent technology that holds the potential to revolutionise this sector. By leveraging machine learning, natural language processing, and predictive analytics, automated debt recovery systems analyse vast quantities of data, generate forecasts regarding the likelihood of recovery, and streamline operational processes. Debt collection systems powered by AI are anticipated to be compliant, precise, and effective. On the other hand, conventional approaches are linked to increasing expenditures and inefficiencies in operations. These solutions facilitate efficient resource allocation, customised communication, and rapid data analysis, all while minimising the need for human intervention. Significant progress has been made in data analytics, predictive modelling, and decision-making through the application of artificial intelligence (AI) in debt recovery; this has the potential to revolutionize the financial sector’s approach to debt management. The findings of the research underscore the criticality of artificial intelligence (AI) in attaining efficacy and precision, in addition to the imperative of a data-centric framework to fundamentally reshape approaches to debt collection. In conclusion, artificial intelligence possesses the capacity to profoundly transform the existing approaches utilized in debt management, thereby guaranteeing financial institutions’ sustained profitability and efficacy. The application of machine learning methodologies, including predictive modelling and logistic regression, signifies the potential of the system.

The trilateral defense and security pact between Australia, the United Kingdom, and the United States has strong impact to the security dynamics in the Indo-Pacific area. This agreement entails a strengthened alliance between Australia and enhanced military collaboration with the United States and the United Kingdom resulting in regional volatility. This paper aims to examine the AUKUS (Australia–United Kingdom–United States Partnership) agreement and the resulting ensuing instability in the Indo-Pacific region, specifically from Indonesia’s perspective. The focus of the research is on the interplay between Indonesia’s diplomacy capability and the military functions of the Indonesian Navy as security policy. This study employs a qualitative approach to delve into in-depth insights into the evolution of AUKUS in the Indo-Pacific region, which triggered a series of responses from many countries subsequent to the announcement of the establishment of the AUKUS Defense Pact. The AUKUS establishment simply reinforces the notion that geopolitical tensions are pulling the area apart. The influence of the AUKUS-China war can jeopardize regional stability since the US and China continuously demonstrate the supremacy of their armaments in order to dissuade one another. The AUKUS-China contest has had a highly adverse impact on Indonesia. This article argues that the Indonesian Navy’s diplomatic prowess is crucial because it has the potential to play a big influence in the Indo-Pacific region’s international political dynamics concerning the South China Sea. Furthermore, the Indonesian Navy must proactively prepare for potential armed conflicts in Indonesian territorial seas by developing a comprehensive maritime policy during times of peace, leveraging its geographical advantages.