Management Capabilities Research Articles

PSDM: A parametrized structural dynamic modeling method based on digital twin for performance prediction

Digital twin (DT) technology is a powerful tool that accurately represents physical entities and provides real-time monitoring and reliability analysis capabilities for decision-makers and managers. However, modeling complex systems in structural health monitoring using DTs can be repetitive and tedious with existing approaches. To address these issues, we propose a new approach called the Parametrized Structural Dynamic Modeling(PSDM) method. This approach effectively parametrizes dynamic systems in structural health monitoring by leveraging Proper Orthogonal Decomposition (POD) to represent and analyze complex structural behaviors. It also incorporates model reduction and kernel functions. By integrating physics-based insights and advanced modeling methodologies, the PSDM method aims to bridge the gap between the physical and digital domains, enabling accurate and efficient analysis of complex structural systems. To verify its accuracy and efficiency, we apply the PSDM method to two engineering cases: the wing cantilever beam and the telehandler boom. The results demonstrate that the online computational cost of the PSDM method is lower than Finite Element Methods (FEM), thereby improving the computational efficiency of DT modeling technology for complex-large structures. Thus, this research presents a feasible method for implementing structural reliability analysis for engineering equipment.

AI’s Bipolar Effect on Mitigating and Motivating Frauds

In the time of digital innovation, Artificial Intelligence (AI) stands at the forefront, signaling new capabilities in fraud management but also new vulnerabilities. This paper aims to dissect AI's paradoxical influence on fraud, portraying its roles in both promoting and mitigating fraudulent activities. The research seeks to bridge the gap in understanding the dual nature of AI, highlighting the need for ethical and regulatory frameworks to traverse the complications AI introduces into fraud detection and prevention. Utilising secondary data from Google News and academic databases with the keyword 'AI fraud,' this study adopts a keyword-based analysis to sift through the most relevant literature. The approach is designed to capture a comprehensive snapshot of the current discourse, underlining the bipolar impact of AI on fraud. The analysis reveals AI's significant potential in enhancing fraud detection systems through rapid data analysis and pattern recognition. However, AI technologies can be exploited to facilitate sophisticated fraud schemes. The study underscores an urgent need for evolving practices and policies that counteract AI's potential for misuse, weighing in the emerging concept of self-regulatory AI systems as a promising direction for future research. This paper contributes insights into the dualistic role of AI in fraud, adding depth to the discourse on its implications for security, ethical considerations, and regulatory challenges. It advocates for a balanced perspective on AI's capabilities.

Stakeholders’ participation in decreasing wildfire risk in the context of natural resource management in the Podpoľanie region of Slovakia

Key MessageAs the number and extent of wildfires are increasing due to climate change and human impacts, the demand for effective risk reduction strategies is growing. Due to limited resources or management capabilities in Slovakia, appropriate multistakeholder participation could help decrease the risk of wildfires while continuing to implement the principles of sustainable forest management. Thus, we recommend improving relationships with responsible stakeholders and increasing their knowledge.ContextAlthough the frequency of wildfires has declined in Slovakia, the total burned area per year and the average burned area per fire have increased rapidly, mainly due to traditional land management and increasing numbers of natural disasters resulting from climate change.AimThe objective of this study is to assess the participation and management of stakeholders in the region of Podpoľanie, which is the region of Slovakia that is most prone to wildfires. In particular, this study investigates the questions of who is accountable, in what networks, and with regard to what issues with the goal of enhancing efforts to combat wildfires.MethodsThis single-country case study features an exploratory sequential mixed-methods design. While stakeholders’ participation was explored via face-to-face interviews and interest-influence matrices, stakeholders’ prioritization was assessed via an online survey and the quantitative mapping of stakeholders’ involvement, power, interest, and knowledge.ResultsWe separately identified primary stakeholders (e.g., fire departments and state-owned forest enterprises) and secondary stakeholders (e.g., municipalities and community members). Tasks related to efforts to combat wildfires were largely in compliance with legal regulations and other mandates. Nonetheless, some stakeholders (e.g., governmental organizations involved in nature protection or nonstate forest owners and the associated enterprises) lacked the knowledge, experience, or responsibility necessary to perform these tasks.ConclusionThese stakeholders should be informed and monitored closely to achieve outcomes that can benefit a variety of stakeholders. We recommend a plan that involves improving the relationships among primary and secondary stakeholders, increasing their knowledge, and promoting effective participation to decrease the risk of wildfires in the region.

The managers' perspectives on service providing in women's harm reduction centers during the COVID-19 pandemic: mixed method study

BackgroundThe COVID-19 pandemic posed significant challenges for managers overseeing women's harm reduction centers. This study seeks to capture managers' perspectives on the service providing in women's harm reduction centers during the COVID-19 pandemic.MethodsThis convergent mixed-method study conducted in three provinces of Iran: Tehran, Khuzestan, and Kermanshah. The study was carried out between January and May 2023. In the quantitative part, the researchers utilized reports from 10 center managers. A researcher-designed questionnaire was employed to collect data on a wide range of services and referrals provided by the centers. The qualitative part of the research involved conventional content analysis and included 12 individual interviews. Two directors from the Ministry of Health and ten managers of women’s harm reduction centers participated in the interviews. During the interpretation phase, the researchers compared the quantitative and qualitative findings to obtain a comprehensive understanding of the topic.ResultsDuring the quantitative stage of the study, it was observed that all the managers were women, with an average age of 40.7 ± 7 years. More than half of the managers had obtained a postgraduate education (n = 6, 60%), and a majority of them were married (n = 7, 70%). Additionally, 40% of the managers (n = 4) were working as contractors. During the non-COVID-19 period, there were higher coverage by centers and residents, more referrals of non-injecting drug users and sex workers, and a higher number of group counseling sessions in all three provinces compared to the COVID-19 period. The qualitative analysis revealed two primary themes: "challenges" and "capabilities."ConclusionsDuring the COVID-19 pandemic, providing some services and client referrals decreased in the centers, and center managers faced increased challenges. Many of these challenges were in the communication, executive, management, structure, education, financial, civilization, facilities, and socio-cultural sectors. Managers used their skills to manage and control these challenges. It is important to focus on these challenges and managerial capabilities to effectively handle future crises.

Confined Crystallization Polyether-Based Flexible Phase Change Film for Thermal Management.

Phase change materials (PCMs) possess the potential to regulate temperature by utilizing their thermal properties to absorb and release heat. Nevertheless, the application of PCMs in thermal management is constrained by issues such as liquid leakage and limited flexibility. In this study, we propose a novel approach to address these challenges by incorporating a pore structure within nanofibers to confine the crystallization of phase change molecules, thereby enhancing the flexibility of the composite material. Additionally, inspired by the adaptive mechanisms observed in plants, we have developed a form stable PCM based on polyether, which effectively mitigates the issue of liquid leakage at higher temperatures. Despite being a solid-liquid PCM at its core, this material exhibits molecular-scale flow and macroscopic shape stability as a result of intermolecular forces. The composite film material possesses remarkable flexibility, efficient thermal management capabilities, adjustable phase transition temperature, and the ability to undergo repeated processing and utilization. Consequently, it holds promising potential for applications in personal thermal energy management.

Navigating COVID-19 Pandemic: Empowering Sustainable Supply Chains Performance through Leadership Capability, Knowledge Sharing Capability, and Strategic Management Capability amid COVID-19 Disruptions

Navigating COVID-19 Pandemic: Empowering Sustainable Supply Chains Performance through Leadership Capability, Knowledge Sharing Capability, and Strategic Management Capability amid COVID-19 Disruptions

The Impact Of Open Innovation And Knowledge Management On Sme Performance In Yogyakarta

This research examines the impact of knowledge management, open innovation, and innovation capabilities on the performance of SMEs in the Special Region of Yogyakarta. Although previous studies on open innovation in the Indonesian context have been conducted, specific results from this region still need to be included, and certain variables related to performance improvement in SMEs still need to be explored. Therefore, this study seeks to address these gaps, with 202 respondents contributing to the research. Data analysis was conducted using SPSS and PLS-SEM with the SmartPLS tool. The findings indicate that the variables of knowledge management, open innovation, and innovation capabilities have a positive impact on SME performance. This research aims to enrich the literature on open innovation and SME performance. The study also provides valuable insights for business practitioners and stakeholders on how to implement these variables to enhance business or company performance.

College Management System using Python & Django

The College Management System (CMS) is an advanced web-based application designed to streamline administrative and academic processes within educational institutions. Developed using the Django framework for backend functionalities and HTML, CSS, and JavaScript for frontend presentation, the CMS offers a comprehensive solution for managing various tasks efficiently. Leveraging SQLite as the databadminisratiase management system ensures robust data management capabilities, scalability, and ease of maintenance. The CMS provides a wide array of features to automate routine tasks and enhance collaboration among students, faculty, and administrators. Student admission and enrollment management, course scheduling, curriculum planning, and faculty assignment are seamlessly handled by the system, reducing manual workload and minimizing errors. Integrated messaging systems and announcement boards facilitate communication, fostering a collaborative learning environment. The examination management module automates the entire examination process, including exam scheduling, creation of question papers, venue allocation, and result processing. Online exam registration and automated grading streamline the process, ensuring accuracy and transparency while reducing administrative burden. Attendance tracking is simplified with the CMS, allowing faculty to record and monitor student attendance easily. Integration with biometric systems or RFID technology enhances accuracy and eliminates manual attendance taking. Comprehensive attendance reports provide insights into student progress and compliance with attendance policies. Resource management is optimized through the CMS, which enables efficient allocation and utilization of classrooms, laboratories, library resources, and equipment. Administrators can manage inventory, track asset availability, and schedule resource bookings to prevent conflicts and ensure optimal utilization. Reporting and analytics features empower administrators with real-time insights into various aspects of college operations. Customizable dashboards provide information on enrollment statistics, academic performance, financial data, and more, enabling informed decision-making and continuous improvement. In conclusion, the College Management System developed with Django, HTML/CSS/JS, and SQLite revolutionizes educational institution management. By combining advanced technology with intuitive design, the CMS enhances efficiency, transparency, and collaboration, ultimately contributing to the success and growth of the institution.

Multi-Shared-Task Self-Supervised CNN-LSTM for Monitoring Free-Body Movement UPDRS-III Using Wearable Sensors.

The Unified Parkinson's Disease Rating Scale (UPDRS) is used to recognize patients with Parkinson's disease (PD) and rate its severity. The rating is crucial for disease progression monitoring and treatment adjustment. This study aims to advance the capabilities of PD management by developing an innovative framework that integrates deep learning with wearable sensor technology to enhance the precision of UPDRS assessments. We introduce a series of deep learning models to estimate UPDRS Part III scores, utilizing motion data from wearable sensors. Our approach leverages a novel Multi-shared-task Self-supervised Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) framework that processes raw gyroscope signals and their spectrogram representations. This technique aims to refine the estimation accuracy of PD severity during naturalistic human activities. Utilizing 526 min of data from 24 PD patients engaged in everyday activities, our methodology demonstrates a strong correlation of 0.89 between estimated and clinically assessed UPDRS-III scores. This model outperforms the benchmark set by single and multichannel CNN, LSTM, and CNN-LSTM models and establishes a new standard in UPDRS-III score estimation for free-body movements compared to recent state-of-the-art methods. These results signify a substantial step forward in bioengineering applications for PD monitoring, providing a robust framework for reliable and continuous assessment of PD symptoms in daily living settings.

Estimation of overcharge-induced degradation state in lithium-ion cells using differential thermal voltammetry and distribution of relaxation times

Overcharge is recognized as a significant factor contributing to the degradation and potential thermal runaway of Li-ion cells. In this study, a novel approach is proposed to estimate the extent of overcharge-induced degradation in 18,650-type Li-ion cells with NCA cathodes and graphite anodes. Experimental results reveal abnormal heat generation and capacity loss due to overcharge-induced degradation. Using Differential Thermal Voltammetry (DTV) and Distribution of Relaxation Times (DRT) methods, ten degradation factors (DFs) that reflect the extent of degradation are identified. Through Pearson correlation analysis, the height of peak P1 in DTV and S2 in DRT are identified as the most indictive parameters to estimate degradation. Next, a predictive model based on Kriging deep learning method is developed using these parameters, which enables precise estimation. Validation results for the model demonstrate outstanding predictive accuracy, with a mean absolute percentage error (MAPE) of 3.25 % and a root mean square error (RMPE) of 3.62 %. The proposed methodology not only offers a robust approach to estimate overcharge-induced degradation of Li-ion cells, but also provides valuable insights for enhancing the monitoring and management capabilities of battery system.

Flexible phase change film based on lignin-derived porous carbon/Eicosane for wearable thermal management and microwave absorption

A flexible phase-change film with thermal management and microwave absorption capabilities was developed for use in wearable devices. The film was created using a solution casting method based on a porous carbon-loaded eicosane (LP33/EI) material. LP33 served as the porous encapsulation medium, while Eicosane (EI) acted as the phase change component. The flexible substrate was a blend of polyvinyl alcohol (PVA) and bacterial cellulose nanocellulose (BC). The ultrathin film had a thickness of 0.262 mm, and LP33/EI-4 exhibited exceptional mechanical strength of 188 MPa. Testing revealed that the phase transition process had melting and crystallization enthalpies of 134.71 J/g and 126.11 J/g, respectively. The encapsulation structure effectively prevented any leakage during the phase transition process. Under simulated solar irradiation of 200 mW/cm2, LP33/EI-4 achieved a photothermal conversion efficiency (η) of 89.46 %. Additionally, the porous LP33 structure and high dielectric loss contributed to remarkable microwave absorption capabilities of −42 dB in the X-band and − 52 dB in the Ku-band. Overall, LP33/EI films demonstrated exceptional performance in thermal management, energy storage, and microwave absorption, making them an ideal choice for a variety of applications in wearable devices.

Unveiling the path to green innovation: the interplay of green learning orientation, knowledge management capability and manufacturing firm’s capability to orchestrate resources

Purpose Amidst the increasing global emphasis on environmental sustainability, manufacturing firms seek to integrate eco-conscious practices into their innovation processes. This study aims to explore the intricate relationships between green learning orientation (GLO), knowledge management capability (KMC), resource orchestration capability (ROC) and two dimensions of green innovation (GI): green product innovation (GPDI) and green process innovation. Design/methodology/approach Partial least squares structural equation modelling (PLS-SEM) and moderated mediation techniques were used to investigate the relationships among the constructs using data gathered from a survey of 167 manufacturing firms in the United Arab Emirates. Findings This study indicates that GLO significantly influences GPDI and green process innovation. Although KMC mediates the relationship between GLO and process innovation, it does not mediate the GPDI relationship. Moreover, ROC significantly strengthens the links between GLO, KMC and both the aspects of GI. Practical implications This study emphasises the importance of fostering a green learning culture and integrating it into product development without complex knowledge management systems. This study also highlighted the role of effective resource allocation in maximising environmental learning benefits for sustainable innovation. Organisations can achieve environmental progress by integrating green knowledge into product and process development and by investing in sustainable practices. Originality/value By examining various mechanisms involving moderation and mediation, this study has made a notable contribution to advancing the field of knowledge-based view theory. This study also offers enhanced insights into the interconnections among GLO, knowledge management capability, ROC and a firm’s capacity for GI.

Strategic Alliances and Firm Innovation in Global Markets in Turkey

Purpose: The aim of the study was to investigate the strategic alliances and firm innovation in global markets in Turkey. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Strategic alliances significantly enhance firm innovation in global markets, particularly in Turkey. These partnerships enable firms to access resources and knowledge, driving innovation through joint R&D and technological advancements. In Turkey, alliances with multinational corporations and global partners accelerate technology adoption and best practices, boosting local firms' innovation capabilities and expanding market reach. Despite challenges like cultural differences and regulatory issues, effective alliance management can greatly benefit firms by improving competitiveness and innovation outcomes globally. Unique Contribution to Theory, Practice and Policy: Resource-based view (RBV) theory, transaction cost economics (TCE) theory & social network theory may be used to anchor future studies on strategic alliances and firm innovation in global markets in Turkey. Enhance organizational capabilities in alliance management through training programs and knowledge-sharing platforms that emphasize best practices in partner selection, negotiation, and collaborative innovation. Develop supportive regulatory frameworks that encourage cross-border alliances and facilitate intellectual property protection, thereby reducing legal uncertainties and enhancing trust among international partners.

Enhancing Operational Risk Management in the Mauritian Banking Sector: A Structured Approach

The purpose of this study aims to improve risk control, mitigation, and interbank risk comparison by advocating for Mauritian banks to adopt a standardised operational risk definition. The study suggests improving operational risk reduction or hedging, encouraging openness in risk management capabilities, and standardising risk assessment methods in accordance with Bank of Mauritius requirements. The study also recommends that banks create operational risk management committees to supervise risk control and mitigation initiatives. These committees should be composed of experienced personnel who are well-versed in the consequences of operational risk in the banking industry. Using a mixed-method approach, insights are obtained from various banks operating in Mauritius, with data acquired from a substantial sample of 150 participants. Targeting Mauritian bankers, questionnaires were distributed across reputable banks, and data were meticulously collected and analysed. The findings highlight contemporary concerns regarding economic well-being and the security of assets held by banks. It is recommended to implement changes on a modest scale initially, subject to close monitoring over a specified period, with the possibility of gradual expansion if successful outcomes ensue. In conclusion, this research is significant due to the limited exploration into operational risk management within the Mauritian context.

Human Resource Management Factors in Financial Analysis of Securities Companies

The outcomes of financial analysis serve as the basis for crucial decision-making in business operations. However, many small-scale securities companies tend to overlook this aspect. This study aims to investigate the relationship between financial analysis activities and business outcomes of small-scale securities companies in Vietnam. Data were collected from 92 respondents working in 27 small-scale securities companies (with owner equity of less than 250 billion Vietnamese Dong), holding positions such as management (directors, assistant directors, financial directors, chief accountants) and staff (financial and accounting personnel) involved in financial and accounting operations of Vietnamese securities companies. Sampling was conducted selectively from September 2023 to December 2023. Utilizing quantitative research, the Partial Least Squares Structural Equation Modeling (PLS-SEM) method was employed using SPSS 20 and AMOS 20 software. Results indicate that Financial Analysis Method (MAF) and Financial Analysis Content (variable FAC) positively influence financial analysis activities of small securities companies. Recommendations to enhance securities companies' business outcomes include (i) employing the EVA technique in financial analysis, (ii) improving management capabilities in financial report analysis, (iii) enhancing the skills of accounting and financial staff, and (iv) applying and operating professional ethical principles.

Configuring Technology Resources and Organizational Practices for Innovation Success

Overview: As novel technologies and organizational practices become available, innovation managers must identify and invest in those best suiting their needs. To ensure their firm’s innovativeness, innovation managers must integrate these new technologies and organizational practices into their resource portfolio and deploy them in combination with existing resources. In this article, we demonstrate the orchestration of technologies and practices that set the most innovative firms apart from less innovative. Using the fsQCA method, we found that high-performing firms configure their technological resources and organizational capabilities in bundles, whereas their less innovative counterparts are preoccupied with investing in technologies alone. Resource orchestration management is therefore a novel innovation management capability, which may accelerate a firm’s innovative capabilities. We offer practitioners managerial implications that emphasize the development of innovation managers’ resource orchestration capabilities.

The enhancement of water and energy conservation through condensed water reclamation for evaporative cooling towers

Although environmental groups have declaimed the application of greywater to alleviate water consumption, the progress of condensed water implementation for high-rise buildings was still sluggish. As greywater demands wastewater treatment before any application, the novelty of this study was to demonstrate the direct use of condensed water in an existing cooling water system without wastewater treatment. Considering there is barely any practical case study research to unveil the water-energy nexus in reclaiming condensed water for evaporative cooling tower systems, this research has signified that condensed water is a simple and low-budget application for water conservation and energy saving. Given that the condensed water possesses an intrinsic impurity-free property, the water-saving potentials have been amplified to the most tolerable total dissolved solids (TDS) of system water. Furthermore, it is beneficial that water quality control ameliorated the operating working conditions, the system performances were improved, and then less power was consumed. By getting rid of the wastewater treatment, consolidating the feasibility of practical direct-use application, and its sustainability for water and energy saving, this research may revive the attention of green building claimers to expedite its implementation and tie in the green building design. The condensed water derived from the electric ventilation system was reclaimed as an alternative water source for cooling without extra power consumption, which was ideal for concentration dilution and beneficial to descaling. An evaporative cooling system consumes tons of water, and the water losses are necessarily compensated by fresh water; this process occurs gradually over time and progressively escalates the TDS with time, which evocates water scale formations. Although the bleed-off (BO) that discharges the impurity-laden system water effectively lowers the TDS, it is not a water conservation measure, and the chemical effluent poses environmental hazards. The higher cycles of concentration (CoC) reduce the frequency of BO and sustain the full efficacy of antiscaling chemicals. Whenever water scales appear as a resistance of heat transfer deposit on the heat exchangers, the heat management capability is diminished and energy efficiency drops. The water and energy saving enhancement method was accomplished by reclaiming the condensed water and setting higher CoC.

One-Dimensional van der Waals Heterojunction Comprising Carbon Nanotube Half-Wrapped in Boron Nitride Nanotube: Deep Investigation of Thermal Rectification.

One-dimensional van der Waals (vdWs) heterostructures are celebrated for their exceptional thermal management capabilities, garnering significant research interest. Consequently, our research focused on the one-dimensional vdWs heterojunction comprising carbon nanotube half-wrapped in boron nitride nanotube (BNCNT), specifically their thermal rectification (TR) properties. We employed non-equilibrium molecular dynamics to explore the TR mechanism and assess the impacts of temperature, strain, and coupling strength on heat flux and TR ratio. Our findings reveal that the backward heat flux demonstrates greater atomic vibration instability, as indicated by mean square displacement (MSD), compared to forward heat flux. This instability leads to a higher concentration of localized phonons, thereby diminishing the backward heat flux and enhancing TR. Additionally, we utilized MSD to shed light on the negative differential thermal resistance phenomenon and the influence of stress on forward and backward heat fluxes. Remarkably, TR ratios reached 344% at 3% strain and 400% at -1% strain. Calculations of phonon density of states revealed a competitive mechanism between in-plane and out-of-plane phonons coupling in the inner carbon nanotube and an overlap degree of out-of-plane phonon spectra between the inner carbon nanotube and outer boron nitride nanotube. This accounts for the differing trends in forward and backward heat fluxes as coupling strength χ increases, with TR ratios exceeding 1000% at χ = 7.5. This study provides vital insights for advancing one-dimensional vdWs thermal rectifiers.

Regulative institutions, dynamic managerial capabilities, and strategic entrepreneurial performance

PurposeThis study examines firms' strategic entrepreneurial behaviors based on the interaction of regulatory institutions and entrepreneurs' cognition, human capital, and social capital capabilities.Design/methodology/approachData was collected from 450 exporting companies in Türkiye, which is a developing economy. Smart PLS 4.0 and SPSS 24.0 software were used to analyze the data. The data were examined using structural equation modeling, confirmatory factor analysis, average extracted variance, composite reliability, and Cronbach's alpha analyses.FindingsThe findings show that entrepreneurial cognition, social capital, and regulatory institutions influence each other, this relationship is not confirmed in managerial human capital. Moreover, while managerial cognition affects strategic entrepreneurship behavior, this effect was not supported for managerial human capital and managerial social capital. However, it was determined that only entrepreneurial cognition mediates the relationship between regulatory institutions and strategic entrepreneurial behavior.Originality/valueThis research enables entrepreneurs to understand, navigate, and appreciate the significance of the interactions between regulatory institutions and dynamic managerial capabilities in decision-making. Additionally, the study allows policymakers to develop evidence-based policy designs that equip entrepreneurs with the insights needed to succeed in a competitive and regulatory complex environment.

FROM NORMS TO NETWORKS: INVESTIGATING THE SYNERGY BETWEEN ORGANIZATIONAL CULTURE AND SOCIALIZATION IN IMPLEMENTING KNOWLEDGE MANAGEMENT PRACTICES IN SRI LANKA'S DOMESTIC SYSTEMATICALLY IMPORTANT BANKS

The ability to effectively manage and assess knowledge has become indispensable for business survival, making knowledge management capability a crucial asset in the banking industry. This close tie between knowledge management and organizational culture presents an opportunity to boost bank performance through socialization practices. Recognizing the importance of culture in implementing knowledge management through socialization, this study explores its impact within the Sri Lankan banking sector, specifically focusing on all four domestic systematically important banks. Utilizing an inductive approach within an interpretive framework, the research investigates cultural dimensions that contribute to knowledge diffusion. While acknowledging potential sample bias due to respondent selection methods and head office limitations, 20 executive-level staff, from November 2022 to February 2023, participated. A priori thematic analysis, guided by the SECI model's socialization aspects, revealed leadership, team dynamics, communication, and mentoring as key cultural dimensions influencing knowledge diffusion. The study concludes that the chosen banks' cultures encourage prioritizing socialization-based knowledge management practices for improved performance.