## The Nexus of FinTech Adoption, HR Competency, Service Innovation, and Firm Growth in the Banking Sector: An Entropy-TOPSIS Approach### IntroductionIn the era of digital transformation, various industries, including banking, have embraced advancements in technology. The banking sector has leveraged innovative technologies like e-banking and service innovation to streamline operations, reduce costs, and expand services beyond traditional brick-and-mortar branches. The interplay of FinTech, human resource (HR) competency, service innovation, and firm growth demands systematic evaluation to unravel their impact on the performance and development of banking institutions. This study introduces a hybrid Multi-Criteria Decision-Making (MCDM) model that integrates the Entropy-Weighted Method (EWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approaches. The model facilitates the objective assessment and ranking of alternatives while considering multiple criteria, aiding decision-makers in selecting optimal strategies within the banking sector.### Literature ReviewThe rapid technological advancements have transformed the banking landscape, attracting academic interest and fostering innovative startups. Studies have analyzed FinTech financing in Indonesia's developing financial sector, highlighting the role of millennials and skilled professionals in driving its growth. HRM practices and employee retention have been examined, emphasizing the mediation of specialized knowledge, purpose similarity, and a cognitive approach to HRM. The importance of bankers' job satisfaction in India's banking sector has been explored, suggesting the need for performance-based reward systems and recognition. The impact of knowledge responsiveness on innovation and corporate financial performance has been investigated, emphasizing the role of an innovative environment.Moreover, research has explored the association between FinTech adoption and financial performance in the European banking system, indicating a positive correlation. The impact of digitalization on the technology acceptance model in Greek banking institutions has been assessed, underscoring the importance of employee receptiveness to new technologies for effective implementation. The utilization of big data technologies in the Indian banking sector has been highlighted, demonstrating its potential for improving security and fraud detection. The influence of FinTech on SME lending has been examined, suggesting that digital-first approaches can reduce loan availability. The integration of IT innovation and sustainable business performance has been analyzed, emphasizing the role of internal integration and agility.### MethodologyThis research employs a hybrid MCDM model to evaluate the significance of FinTech adoption, HR competence, service innovation, and firm growth in the banking sector. The model combines the Entropy-Weighted Method (EWM) for criterion importance determination and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for alternative ranking. The methodology consists of the following steps:1. **Identification of Criteria and Alternatives:** Based on a comprehensive literature review, a set of eleven relevant criteria and eight potential alternatives representing different banking institutions are identified.2. **Data Collection:** Data pertaining to each criterion and alternative is gathered from reliable sources, including financial reports, industry publications, and expert opinions.3. **Entropy-Weighted Method (EWM):** This method is utilized to determine the relative importance (weights) of the identified criteria. The entropy measure is calculated for each criterion, and the results are normalized to derive the weights.4. **TOPSIS Approach:** The TOPSIS approach is employed to rank the alternatives based on their closeness to an ideal solution and distance from a negative-ideal solution. The weighted normalized decision matrix is used to determine the performance of each alternative.5. **Alternative Ranking:** The TOPSIS scores are calculated for each alternative, and the alternatives are ranked in descending order based on their scores. The alternative with the highest score is considered the most effective and influential in enhancing the performance and growth of the banking sector.### ResultsThe application of the proposed MCDM model yielded comprehensive results that provide insights into the impact of FinTech adoption, HR competency, service innovation, and firm growth on the banking sector:1. **Criterion Importance:** The EWM analysis revealed that financial innovation, risk optimization, and credibility hold the highest weights, indicating their critical importance in determining the effectiveness of banking institutions.2. **Alternative Ranking:** The TOPSIS ranking identified Alternative A6 as the best-performing banking institution, followed by Alternative A8, A2, A5, A4, A1, A3, and A7. Alternative A6 demonstrated a balanced performance across all criteria, contributing to its higher ranking.### DiscussionThe findings of this study align with previous research highlighting the significance of FinTech adoption, HR competency, service innovation, and firm growth in the banking sector. The results indicate that banking institutions that effectively incorporate these elements into their strategies are better positioned to enhance their performance and competitiveness. The adoption of FinTech technologies, such as artificial intelligence, automation, and data analytics, enables banks to streamline operations, improve customer experience, and drive growth.The development of HR competency is crucial for banking professionals to embrace technological changes, drive innovation, and enhance service delivery. Continuous training and skill enhancements are essential to ensure that HR teams possess the necessary knowledge and capabilities to support the rapidly evolving banking landscape.Service innovation plays a vital role in differentiating banking institutions and attracting customers. The implementation of innovative services, such as mobile banking, digital wallets, and personalized financial advisory, enhances customer satisfaction and loyalty.Firm growth is the ultimate outcome of effective implementation of FinTech adoption, HR competency, and service innovation. Banks that consistently excel in these areas witness increased profitability, market share expansion, and customer base growth.### ConclusionThis research contributes to the understanding of the relationship between FinTech adoption, HR competency, service innovation, and firm growth in the banking sector. The proposed hybrid MCDM model offers a systematic and data-driven approach for evaluating and ranking alternative strategies, empowering decision-makers with valuable insights. The study highlights the importance of embracing advanced technologies, developing skilled HR teams, fostering innovation, and driving growth. Banks that prioritize these aspects are well-positioned to succeed in the evolving digital era.### Limitations and Future ResearchWhile this study provides valuable insights, certain limitations should be acknowledged:1. Data availability: The availability of data for some criteria and alternatives could have been limited, affecting the comprehensiveness of the analysis.2. Subjective judgments: The assignment of weights to criteria and the selection of alternatives involved subjective judgment, potentially influencing the results.Future research can address these limitations by expanding the dataset, incorporating additional criteria, and utilizing more sophisticated MCDM techniques to enhance the accuracy and reliability of the evaluation process.