Business transformation in a distinctive institutional setting: A study of regional development banks in Indonesia

Thuda, Audy; Hamsal, Mohammad; Warganegara, Dezie Leonarda; Heriyati, Pantri Article Business transformation in a distinctive institutional setting: A study of regional development banks in Indonesia Administrative Sciences Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Thuda, Audy; Hamsal, Mohammad; Warganegara, Dezie Leonarda; Heriyati, Pantri (2024) : Business transformation in a distinctive institutional setting: A study of regional development banks in Indonesia, Administrative Sciences, ISSN 2076-3387, MDPI, Basel, Vol. 14, Iss. 11, pp. 1-27, https://doi.org/10.3390/admsci14110299 This Version is available at: https://hdl.handle.net/10419/321105 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Citation: Thuda, Audy, Mohammad Hamsal, Dezie Leonarda Warganegara, and Pantri Heriyati. 2024. Business Transformation in a Distinctive Institutional Setting: A Study of Regional Development Banks in Indonesia. Administrative Sciences 14: 299. https://doi.org/ 10.3390/admsci14110299 Received: 7 September 2024 Revised: 6 November 2024 Accepted: 6 November 2024 Published: 12 November 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Article Business Transformation in a Distinctive Institutional Setting: A Study of Regional Development Banks in Indonesia Audy Thuda * , Mohammad Hamsal, Dezie Leonarda Warganegara and Pantri Heriyati Management Department, BINUS Business School Doctor of Research in Management, Bina Nusantara University, Jakarta 11480, Indonesia; [email protected] (M.H.); [email protected] (D.L.W.); [email protected] (P.H.) *Correspondence: audy[email protected] Abstract: Limited research exists on business transformation strategy within the Indonesian banking sector, particularly regarding regional development banks, which play a crucial role in regional economic advancement. This study investigates the drivers of successful business transformation in Indonesian RDBs and their impact on organizational performance, examining the moderating role of regional government intervention. Employing structural equation modeling, the study analyzed data from 255 branch managers across 27 RDBs. Results reveal that talent development, transformational leadership, and digital adoption significantly drive successful business transformation, which in turn enhances organizational performance. Contrary to expectations, regional government intervention did not demonstrate a moderating effect. This study provides valuable insights for RDB managers and policymakers, emphasizing the imporace of talent development, leadership, and digital adoption as key pillars of successful transformation and highlighting the need for a nuanced understanding of institutional influences within this sector. Keywords: business transformation strategy; digital adoption; government intervention; transformational leadership; talent development 1. Introduction Based on Indonesian banking statistics per December 2023, the total banking assets reached IDR 11,765 trillion, underscoring the significant role of a robust banking sector in Indonesia’s economic growth. Within this landscape, regional development banks (RDBs) hold an asset portion of up to 8% of the total banking industry, demonstrating their importance in fostering regional economic advancement. RDBs have experienced an 8.9% growth in assets over the last three years, indicating their potential for further development. RDBs are present in almost every province in Indonesia, with the majority of company shares owned by regional governments. Banking authorities are urging RDBs to continue their business transformation efforts, encompassing all fundamental aspects of their operations (Kalisman 2019). However, RDBs face mounting pressure to adapt and evolve in response to rapid technological advancements, evolving market dynamics, and heightened competition within the financial services industry. These challenges necessitate implementing effective business transformation strategies to enhance organizational performance and ensure long-term sustainability. In formulating effective business transformation strategy, it is crucial to consider talent development (Montero Guerra et al. 2023), transformational leadership (Freihat 2020), and digital adoption (Bughin et al. 2021) as key determinants of success. Numerous studies have demonstrated the positive influence of these factors on regional banks’ efforts to transform and compete effectively in an increasingly competitive banking industry. The challenges the banking industry faces are further amplified by technological advancements and the emergence of new players, such as financial technology (fintech) companies. Amidst competition from large banks and fintech companies, RDBs are actively pursuing Adm. Sci. 2024,14, 299. https://doi.org/10.3390/admsci14110299 https://www.mdpi.com/journal/admsci Adm. Sci. 2024,14, 299 2 of 27 digitalizing their business processes, products, and services, recognizing the vital role of digital adoption in establishing a competitive advantage. However, as entities with majority ownership by regional governments, RDBs are also subject to government intervention. Akyuwen and Mangowal (2019) and Rachim et al. (2021) have suggested that regional government intervention can indirectly hinder RDB performance. Conversely, government intervention in specific contexts has been shown to have a positive impact (Zhao et al. 2021;Xu et al. 2022), highlighting the significant role of government intervention in either facilitating or hindering the success of business transformation strategies aimed at improving bank performance. Notably, no studies explore government intervention as a moderating variable to measure organizational performance in the banking sector, making this variable a novelty for this research. This approach is crucial as it differentiates the banking situation at regional and national levels, recognizing their distinct complexities. While RDBs may still lag behind national-scale banks, within the regional context, most RDBs possess assets that enable them to compete effectively with other commercial banks. This underlines the need to understand how government intervention, as a moderating factor, uniquely impacts RDB performance. Previous studies on organizational performance in the banking industry have identified both external factors (Wahyudi et al. 2021;Rachim et al. 2021) and internal factors (Berhe 2023;Quoc Trung 2022;Bhatia and Gulati 2021;Hossain 2021;Buchdadi et al. 2023; Rizani et al. 2022;Rumahorbo et al. 2021;Kamaludin and Nashsyah 2020) as key determinants. However, there remains a need to comprehensively understand the interplay of these factors in influencing organizational performance. This research examines the impact of business transformation strategies, focusing on talent development, transformational leadership, and digital adoption, on the performance of regional development banks (RDBs) in Indonesia. It further investigates the role of government intervention as a moderating variable to provide a nuanced understanding of how external factors influence organizational performance within a unique institutional setting. This research introduces government intervention as a novel moderating variable in the context of performance studies in the banking industry. The findings provide valuable insights for policymakers, banking authorities, and bank management, guiding effective transformation strategies and supporting regional growth. Additionally, this study offers a valuable reference for other regional banks in emerging markets facing similar challenges. The remainder of this paper is structured as follows. Section 2reviews the relevant literature and provides the theoretical background and hypothesis development. Section 3 details the research methodology, including the sampling technique, data collection process, and analytical methods used, and presents the results and analysis, followed by a discussion in Section 4that interprets the findings in light of existing literature and practical implications. Finally, Section 5concludes the study. 2. Literature Review and Hypothesis Development 2.1. Talent Development Talent development, encompassing organizational activities designed to cultivate and enhance employees’ skills, knowledge, and career trajectories, is crucial for achieving strategic alignment within organizations (Abiwu and Martins 2022). This concept can be understood from both micro and macro perspectives. From a micro perspective, talent development represents company initiatives aimed at individual employee growth. From a macro perspective, it encompasses a holistic process involving integrated planning, selection, and development across all aspects of human resource management (Nurfadilah et al. 2022). Further emphasizing the continuous nature of talent development, Dai and Speerschneider (2012) define it as a process of ongoing formal and informal learning and selfdevelopment. This process aims to cultivate a unique and responsible set of knowledge, skills, and character traits within individuals (Dalal and Akdere 2018). Garavan et al. (2012) position talent development within the broader framework of talent management, emphasizing its role in the strategic planning and implementation of talent-focused initiatives. Adm. Sci. 2024,14, 299 3 of 27 The positive impact of effective talent development on organizational outcomes is welldocumented. Anand (2011), through a case study, illustrated how talent pool management can significantly enhance employee engagement. This engagement, in turn, is essential for successful strategy implementation and the achievement of business goals. Anand further emphasizes that talent management is inherently strategic, as achieving organizational objectives hinges on attracting and retaining the best talent. This strategic importance is further accentuated by Sareen and Mishra (2016), who found a direct link between talent management practices and improved company performance. Their research highlights that organizations that effectively manage and strategically deploy talent are more likely to experience growth and profitability. Moreover, they emphasize the importance of retention strategies within talent development programs as a key driver of enhanced company performance. Finally, the increasing significance of talent development in the context of digital transformation is evident in recent studies. Montero Guerra et al. (2023) in Spain and Samih et al. (2022) in Egypt both found a positive correlation between talent development and successful digital transformation initiatives. Montero Guerra et al. propound that business transformation necessitates a shift in perspective, positioning “people” as a company’s most valuable strategic asset. Similarly, Samih et al. highlight the crucial role of top management support in optimizing talent to effectively implement business strategies, particularly within the context of digital transformation. Based on this body of research, we propose the following hypothesis: H1. Talent development has a positive effect on business transformation strategy. 2.2. Transformational Leadership Transformational leadership, characterized by a leader’s ability to inspire and motivate followers toward shared goals, plays a crucial role in organizational success. Radi Afsouran et al. (2022) defines transformational leadership as a process that elevates both leaders and employees to higher levels of morality and motivation, fostering a strong commitment to achieving organizational missions and goals. This leadership style is characterized by visionary thinking, innovative problem solving, and the ability to inspire and empower others. Greimel et al. (2023) further elaborate on this concept, describing transformational leadership as an approach that aligns followers with organizational goals and interests, ultimately driving improved performance. Saira et al. (2021) offers a more practical perspective, defining transformational leadership as the ability to enhance subordinate performance through motivation, empowerment, and recognition. Synthesizing these perspectives, transformational leadership can be understood as a leader’s capacity to elevate organizational performance by influencing, motivating, and valuing their subordinates. The influence of transformational leadership extends beyond individual and team performance, significantly impacting strategic design and implementation. Freihat’s (2020) study of health agency leaders in Jordan demonstrated a positive correlation between transformational leadership and effective marketing strategy implementation. This influence stems from the leader’s ability to garner support for and facilitate the reengineering of marketing strategies across all organizational levels. Similarly, in the technology manufacturing sector, Huang et al. (2021) found that green transformational leadership among top management predicted the adoption of proactive environmental strategies. This finding highlights the role of leadership in driving sustainability-focused strategic initiatives. The authors posit that transformational leaders, under their authority and influence, can effectively engage subordinates in the development and execution of such strategies. Özgül and Zehir (2023) further substantiate this link, revealing that green transformational leadership can positively influence financial performance through the mediating effect of environmental strategy implementation. This mediating role emphasizes top management’s importance in understanding strategic choices and priorities in driving sustainability and financial success. Adm. Sci. 2024,14, 299 4 of 27 The connection between transformational leadership and human resource strategy is also noteworthy. Ntlhanngoe and Chipunza (2021) found a strong association between transformational leadership behaviors and effective HR strategy implementation. Their research suggests that participative leadership and individual consideration are intertwined, with strategy serving as a mediating force that aligns leadership behaviors with employee needs to enhance organizational performance. Birasnav’s (2014) literature review reinforces this notion, indicating that top leaders exhibiting transformational leadership behaviors are likelier to achieve successful strategy implementation. Based on this evidence, we propose the following hypothesis: H2. Transformational leadership has a positive effect on business transformation strategy. 2.3. Digital Adoption and Organizational Performance Digital adoption, as the integration of information and communication technology into business operations, is crucial for organizations to thrive in today’s digital landscape. Waty et al. (2022) broadly define digital adoption as implementing digital technology in company activities. Lashitew (2023) provides a more nuanced perspective, particularly in the context of the COVID-19 pandemic, distinguishing between e-commerce adoption (utilizing technology for online sales) and remote work adoption (leveraging technology for remote work models). Finkelstein Shapiro and Mandelman (2021) further refine this definition, emphasizing the adoption of electronic devices, software, and hardware to streamline and enhance existing manual processes. In essence, digital adoption represents the strategic implementation of ICT to optimize business activities and generate value. The strategic implications of digital adoption are profound. Cuevas-Vargas et al. (2021) highlight the link between ICT adoption and marketing innovation as a driver of improved business performance. They emphasize the need for organizations to develop innovative advertising strategies that leverage technology to maintain a competitive edge. Van Zeebroeck et al. (2021) posit a dynamic relationship between technology and strategy, asserting that “strategy follows technology as much as technology adoption follows strategy”. While acknowledging that new technology adoption can drive strategic change, they caution that organizations must adapt to these changes, recognizing that more extensive technology adoption necessitates more significant strategic modifications. However, the relationship between digital adoption and organization strategies is not always straightforward. Oeij et al.’s (2022) study of logistics companies in the Netherlands revealed a relationship between employee innovation adoption and competitive strategy, but this relationship was not as strong as anticipated. The authors suggest this may be due to the lack of correlation between competitive strategy and employee involvement. This finding highlights the importance of aligning digital adoption strategies with employee engagement and empowerment to maximize their impact. Furthermore, the successful implementation of digital adoption strategies requires effective resource orchestration. Santos et al. (2023), in their study on entrepreneurial resilience during the COVID-19 pandemic, emphasize the role of digital technology in enhancing strategic resilience. On the other hand, Oeij et al. (2022), in their research on 123 logistics company managers in the Netherlands, found a relationship between employee innovation adoption and competition strategy. Oeij et al. explained that this relationship could have been stronger because, at the same time, competition strategy did not correlate with employee involvement. In a literature study examining the resilience of entrepreneurs during the COVID-19 pandemic, Santos et al. (2023) said that digital technology had a role in increasing the resilience of strategies carried out by entrepreneurs. Based on these findings, we proposed the following hypothesis: H3. Digital adoption has a positive effect on business transformation strategy. Adm. Sci. 2024,14, 299 5 of 27 Digital adoption is increasingly recognized as a critical driver of enhanced organizational performance, particularly in the rapidly evolving banking sector. Numerous studies confirm this positive correlation, highlighting the transformative impact of integrating digital technologies. For instance, research on e-banking adoption by Magboul and Abbad (2018) and Siddik et al. (2016) reveals a strong link between e-banking and improved organizational and financial performance. Similarly, Dwivedi et al. (2021) emphasize the significant role of fintech in enhancing competitiveness and performance by enabling banks to develop innovative products and services that attract and retain customers. The evidence consistently points to the positive influence of digital adoption on organizational performance. Studies by Adhitya and Sembel (2020) and Dadoukis et al. (2021) further underscore this connection, emphasizing the importance of strategic technology adoption for driving financial performance and enhancing resilience, particularly in times of disruption. These findings strongly support the following hypothesis: H4. Digital adoption has a positive effect on organizational performance. 2.4. Business Transformation Strategy and Organizational Performance With its focus on adapting and evolving to meet changing market demands, business transformation strategy plays a crucial role in driving organizational performance. While a universally accepted definition of business transformation remains elusive due to its broad scope, researchers like McKeown and Philip (2003) have identified key characteristics of successful transformations. These include discovering new strategies and processes, organization-wide involvement, cultural solid alignment, and integration into all management processes, encompassing performance evaluation, product development, and operations. This emphasizes the comprehensive and multifaceted nature of successful business transformation initiatives. As Andra and Andri s , an (2022) highlight, strategy is not static; it requires continuous adaptation to overcome challenges and achieve organizational goals. Empirical evidence further supports the positive impact of a well-defined business transformation strategy on organizational performance. Timotius’s (2023) research on MSMEs in Indonesia demonstrates the significant influence of business strategy on competitive advantage, particularly through innovation. Similarly, in the banking context, studies by Abu Khalaf and Alajani (2021) and Ivascu et al. (2023) confirm the positive relationship between strategic initiatives, such as product diversification, and organizational performance. Beyond direct effects, business transformation strategy also plays a mediating role in influencing organizational performance. Davidson’s (1999) stages of business transformation (vision, culture, and performance) suggest a sequential process where strategic changes lead to cultural shifts, ultimately driving performance improvements. This mediating role is further supported by research highlighting the positive impact of specific transformation strategies, such as digital transformation, on bank performance (Wang et al. 2020). These studies emphasize that successful transformation involves comprehensive changes across products, services, organizational structure, and business processes, ultimately leading to enhanced organizational performance. Therefore, a well-crafted and effectively executed business transformation strategy is a critical intermediary in achieving sustained organizational success. The complexity of developing business transformation in companies is relevant to the application of resource orchestration theory (ROT), which has high significance in strategy and places managers as elements that play an essential role in managing company resources (Sirmon et al. 2011). Based on these findings, we proposed the following hypotheses: H5. Business transformation strategy has a positive effect on organizational performance. H6. Business transformation strategy has a mediating role in organizational performance. Adm. Sci. 2024,14, 299 6 of 27 2.5. Regional Government Intervention As highly regulated institutions, banks operate within a complex ecosystem where government intervention is significant, especially for regional development banks with inherent government ownership stakes. This intervention can profoundly influence the relationship between a bank’s business transformation strategy and its overall performance. While some studies suggest potential drawbacks, such as hindering innovation stemming from board diversity (Luo et al. 2021), evidence suggests that government intervention can be a powerful force in shaping the effectiveness of business transformation initiatives. For instance, Xu et al. (2022) found that while regulatory interventions might initially hinder productivity, coupling them with financial support can yield positive outcomes. The study results show that local government intervention is like a “carrot and stick”; regulation is likened to the “stick” while the “carrot” is in the form of subsidies. This highlights the importance of considering the multifaceted nature of government actions and their strategic application in supporting transformation efforts. Furthermore, research indicates that regional government intervention can foster innovation, a critical aspect of successful business transformation. Zhao et al. (2021) demonstrated a positive correlation between regional government intervention and innovation, suggesting that targeted support can create an environment conducive to transformative change. Similarly, Kousar et al. (2017) highlighted how government instruments like taxes and subsidies can incentivize green innovation adoption, further strengthening the link between intervention and successful transformation towards sustainable practices. However, the context of RDBs presents unique challenges, particularly given that regional governments often hold significant ownership stakes. Research suggests a negative correlation between local government intervention and RDB profitability (Rachim et al. 2021). This inherent connection makes government intervention in RDBs practically unavoidable. While offering potential benefits, this intervention can also create pressure points that impact the relationship between business transformation strategy and organizational performance. As DiMaggio and Powell (1983) highlighted, governments act as “producers of norms,” wielding normative pressure to influence company actions. This pressure can manifest in various ways, including appointing government representatives to boards. Unfortunately, research suggests a negative correlation between increased government representation on RDB boards and profitability. This negative impact underscores the potential downsides of government intervention, particularly when it hinders RDBs’ ability to operate with the autonomy needed for successful business transformation. Furthermore, Akyuwen and Mangowal (2019) and Rachim et al. (2021) highlight the risks associated with close interactions between RDB management and regional leaders. While such interactions can facilitate collaboration, they can also create avenues for undue influence and corrupt behavior, potentially undermining the RDB’s profitability and capacity for successful transformation. Therefore, understanding the nuanced role of regional government intervention, particularly the balance between support and potential interference, is crucial for RDBs seeking to implement effective business transformation strategies. By promoting transparency, accountability, and a clear separation of interests, RDBs can mitigate the risks associated with government intervention while harnessing its potential benefits to drive organizational performance. Based on this review, we proposed the following hypothesis: H7. Regional government intervention influences the relationship between business transformation strategy and organizational performance. Regional government intervention plays a significant role in shaping the relationship between digital adoption and organizational performance within RDBs. As controlling shareholders, regional governments wield considerable influence over RDB operations and strategic direction, including decisions related to technology adoption. This influence can manifest in various ways, from setting technology-related policies to providing financial Adm. Sci. 2024,14, 299 7 of 27 incentives for digital transformation initiatives. Several studies have highlighted the impact of government intervention on technology adoption across different sectors (Alzadjali and Elbanna 2020;Chen et al. 2021;Muhamad et al. 2023), underlining its potential to either accelerate or hinder digital progress. While government intervention may not always directly dictate digital adoption within RDBs, it can indirectly influence organizational performance by shaping factors crucial for successful digital transformation. For instance, Waty et al. (2022) found that government intervention significantly impacts business agility and resilience, two key elements that enable organizations to adapt to technological advancements and leverage digital tools effectively. Therefore, by influencing these mediating factors, regional governments indirectly shape the relationship between digital adoption and organizational performance in RDBs. Based on this evidence, we propose the following hypothesis: H8. Regional government intervention influences the relationship between digital adoption and organizational performance. The conceptual model shown in Figure 1was built considering the hypotheses developed. Adm.Sci.2024,14,xFORPEERREVIEW7of26   Regionalgovernmentinterventionplaysasignificantroleinshapingtherelationship betweendigitaladoptionandorganizationalperformancewithinRDBs.Ascontrolling shareholders,regionalgovernmentswieldconsiderableinfluenceoverRDBoperations andstrategicdirection,includingdecisionsrelatedtotechnologyadoption.Thisinfluence canmanifestinvariousways,fromsettingtechnology-relatedpoliciestoprovidingfinancialincentivesfordigitaltransformationinitiatives.Severalstudieshavehighlightedthe impactofgovernmentinterventionontechnologyadoptionacrossdifferentsectors(AlzadjaliandElbanna2020;Chenetal.2021;Muhamadetal.2023),underliningitspotential toeitheraccelerateorhinderdigitalprogress.Whilegovernmentinterventionmaynot alwaysdirectlydictatedigitaladoptionwithinRDBs,itcanindirectlyinfluenceorganizationalperformancebyshapingfactorscrucialforsuccessfuldigitaltransformation.For instance,Watyetal.(2022)foundthatgovernmentinterventionsignificantlyimpactsbusinessagilityandresilience,twokeyelementsthatenableorganizationstoadapttotechnologicaladvancementsandleveragedigitaltoolseffectively.Therefore,byinfluencing thesemediatingfactors,regionalgovernmentsindirectlyshapetherelationshipbetween digitaladoptionandorganizationalperformanceinRDBs.Basedonthisevidence,weproposethefollowinghypothesis: H8.Regionalgovernmentinterventioninfluencestherelationshipbetweendigitaladoptionand organizationalperformance. TheconceptualmodelshowninFigure1wasbuiltconsideringthehypothesesdeveloped.  Figure1.ConceptualModel. 3.ResearchMethodology 3.1.ParticipantsandDataCollections Thestudypopulationcomprised576respondentsfromallRDB(TableA1)branch officesinIndonesia.UsingSlovin’sformulawitha5%marginoferror,theminimumrequiredsamplesizewasdeterminedtobe236respondents.Thisquantitativedatacollectionstrategyemployedatwo-partquestionnaireutilizinga6-pointLikert-typescale(1= stronglydisagree;6=stronglyagree).Thefirstpartcapturedrespondents’demographic profiles,includinggender,workexperience(yearsintheorganization),branchofficelocation,andtypeofbusiness.Thesecondpartfocusedongatheringinformationrelatedto theresearchvariables. Datawerecollectedthroughonlinesurveystargetingbranchmanagerswithinthe RDBbranchoffices.Thisstudyadoptsthebranchofficeasitsunitofanalysis,recognizing Figure 1. Conceptual Model. 3. Research Methodology 3.1. Participants and Data Collections The study population comprised 576 respondents from all RDB (Table A1) branch offices in Indonesia. Using Slovin’s formula with a 5% margin of error, the minimum required sample size was determined to be 236 respondents. This quantitative data collection strategy employed a two-part questionnaire utilizing a 6-point Likert-type scale ( 1 = strongly disagree; 6 = strongly agree). The first part captured respondents’ demographic profiles, including gender, work experience (years in the organization), branch office location, and type of business. The second part focused on gathering information related to the research variables. Data were collected through online surveys targeting branch managers within the RDB branch offices. This study adopts the branch office as its unit of analysis, recognizing its significance as a profit center and a key implementer of organizational strategy within the banking industry. Consequently, branch managers serve as the observation unit, reflecting their pivotal role in translating corporate grand strategy into actionable branchlevel strategies. This selection aligns with established practices in banking research. For instance, Kamaludin and Nashsyah (2020) focused on branch-level managers in their study on regional bank competitiveness, while Afshan et al. (2022) researched leadership within a leading Pakistani bank at the branch office level. Similarly, Al-Shari and Lokhande (2023) Adm. Sci. 2024,14, 299 8 of 27 utilized branch-level management as a data source to examine the relationship between fintech adoption and bank performance in Yemen. By gathering primary data directly from branch managers, this study ensures data authenticity and relevance to the chosen unit of analysis. 3.2. Data Analysis Data were analyzed using structural equation modeling with partial least squares estimation, employing SmartPLS software version 4.0.9.6. PLS-SEM is a multivariate data analysis technique particularly well-suited for examining complex models with latent constructs, such as the one proposed in this study (Hair et al. 2019). PLS-SEM is advantageous due to its ability to handle formative measurement models and provide robust estimations even with non-normal data distributions. This research aimed to explore the relationships and influences among variables through simultaneous analysis, testing the hypotheses statistically to determine data consistency (Byrne 2009). A two-stage approach, as described by Van Riel et al. (2017), was employed to examine the hypothesized relationships within this complex model. This approach is preferred for analyzing second-order constructs within PLS-SEM, offering advantages in handling potential multicollinearity and avoiding “double counting” of indicator variance. The first two-stage approach focuses on obtaining latent variable scores for the firstorder constructs, excluding the second-order constructs from this initial analysis. Indicator loadings are assessed for significance and relevance, while composite reliability values for each first-order construct are calculated and compared to recommended thresholds. Convergent and discriminant validity are evaluated using appropriate methods such as AVE and the Fornell–Larcker criterion. In the second stage, models incorporating the second-order constructs are estimated, utilizing the first-order construct scores from the previous stage as manifest variables. Path coefficients are assessed for significance and relevance, and R-square values for the endogenous constructs are calculated to determine the model’s explanatory power. Predictive relevance is also evaluated using the blindfolding technique, which assesses a construct model’s predictive relevance level. 3.3. Measurement of Variables This research employs a comprehensive model encompassing six variables, operationalized through 19 dimensions and 57 indicators (Table A2). The selection of dimensions and indicators for each variable is grounded in established literature, ensuring a robust measurement framework. Talent development dimensions and indicators are drawn from the research of Nurfadilah et al. (2022) and Panda and Sahoo (2015), building upon the foundational work of Abiwu and Martins (2022), Nurfadilah et al. (2022), and Dalal and Akdere (2018). Transformational leadership is measured using dimensions and indicators adapted from Siswanto and Yuliana (2022) and Bass et al. (2003), complementing the definitions provided by Radi Afsouran et al. (2022) and Greimel et al. (2023). Digital adoption is measured using three dimensions previously studied by CuevasVargas et al. (2021), aligning with the conceptualizations of Waty et al. (2022), Lashitew (2023), and Finkelstein Shapiro and Mandelman (2021). Business transformation strategy dimensions and indicators are adopted from the “business strategy” variable used by Wongsansukcharoen et al. (2015) and the “transformation strategy” variable employed by Wang et al. (2020), reflecting the definitions of “strategy” by Andra and Andri s , an (2022) and “transformation strategy” by Kalisman (2019). Regional government intervention relies on the work of Zhao et al. (2021), Xiao and Ma (2014), and Luo et al. (2021) to inform its measurement. Finally, organizational performance in the banking sector is measured using a balanced scorecard approach, with indicators derived from Al-Shari and Lokhande’s (2023) study, aligning with the framework established by Hajer and Anis (2018) and Kaplan and Norton (1992). This meticulous approach to variable measurement enhances the validity, reliability, and replicability of the research findings. Adm. Sci. 2024,14, 299 15 of 27 Table 5. Cont. Variables Dimensions Loading Factor AVE Organizational Performance (OP) Financial Perspective (FP) 0.851 0.540 Customer Perspective (CP) 0.876 Business Process Perspective (BPP) 0.745 Learning & Growth Perspective (LGP) 0.340 Table 6. Loading Factor and Average Variance Extracted (AVE) Second Stage. Variables Dimensions Loading Factor AVE Talent Development (TD) Training and Development (TAD) 0.786 0.695 Career Development (CD) 0.826 Creativity (CRV) 0.887 Transformational Leadership (TL) Inspirational Motivation (IM) 0.936 0.879 Intellectual Stimulation (IS) 0.956 Individualized Consideration (IC) 0.920 Digital Adoption (DA) Infrastructure (IFT) 0.902 0.843 Strategy Alignment (SA) 0.939 Individual Learning (IL) 0.914 Business Transformation Strategy (BTS) Strategy Selection (SS) 0.891 0.819 Changes in Value Creation (CVC) 0.913 Structural Changes (SC) 0.910 Regional Government Intervention (RGI) Financial Intervention (FI) 0.928 0.711 Regulation Intervention (RI) 0.748 Organizational Performance (OP) Financial Perspective (FP) 0.862 0.684 Customer Perspective (CP) 0.885 Business Process Perspective (BPP) 0.724 5. Discriminant Validity Test (Second Stage) The second stage of the discriminant validity assessment, using the Fornell–Larcker criterion, yielded positive results. As illustrated in Table 7, the square root of the AVE for each variable consistently exceeded its correlations with all other constructs in the model. This outcome confirms the discriminant validity of the measurement model, indicating that each construct is distinct and captures a unique aspect of the phenomenon being studied. Adm. Sci. 2024,14, 299 16 of 27 Table 7. Result of Fornell–Larcker Criterion Discriminant Validity Test (Second Stage). BTS DA OP RGI TD TL BTS 0.905 DA 0.751 0.918 OP 0.634 0.635 0.827 RGI 0.430 0.375 0.450 0.843 TD 0.667 0.729 0.543 0.348 0.834 TL 0.608 0.557 0.524 0.388 0.589 0.938 6. Reliability Test (Second Stage) The reliability of the measurement model was again confirmed in the second stage. Table 8reveals that both Cronbach’s alpha and composite reliability values for all variables exceeded the recommended threshold of 0.70. This finding, particularly the consistently high composite reliability values, strongly indicates that all variables demonstrate satisfactory internal consistency and reliability. Table 8. Result of Reliability Test. Variables Composite Reliability (rho_c) Talent Development (TD) 0.872 Transformational Leadership (TL) 0.956 Digital Adoption (DA) 0.942 Business Transformation Strategy (BTS) 0.931 Regional Government Intervention (RGI) 0.829 Organizational Performance (OP) 0.866 3.4.4. Structural Model Evaluation Results (Inner Model) 1. Path Coefficient The structural model evaluation commenced with assessing the significance of relationships between constructs, as indicated by path coefficients. Following Haryono’s (2016) guidelines, the focus was on the direction and significance of these path coefficients. A significant path coefficient, where the t-statistic exceeds 1.96 (p-value < 0.05), signifies a statistically significant relationship between the independent and dependent variables. Conversely, a non-significant path coefficient (t-statistic < 1.96, p-value > 0.05) suggests that the data do not support the hypothesized relationship. Table 9provides valuable information about the relationships between different factors in the study. The table shows the strength and significance of these relationships. The results support the initial hypotheses (H1 to H5) that Talent Development, Transformational Leadership, and Digital Adoption have a positive effect on Business Transformation Strategy, which, in turn, positively influences Organizational Performance. Further data analysis reveals that Business Transformation Strategy plays a crucial mediating role. This means that the positive effects of Talent Development, Transformational Leadership, and Digital Adoption on Organizational Performance are channeled through the implementation of effective Business Transformation Strategy (H6). However, the study did not support the moderating role of Regional Government Intervention (H7 and H8). This suggests that the influence of Talent Development, Transformational Leadership, and Digital Adoption on Organizational Performance, as mediated by Business Transformation Strategy, remains consistent regardless of the level of Regional Government Intervention. Adm. Sci. 2024,14, 299 17 of 27 Table 9. Result of Path Coefficient. Coefficient t-Statistics p-Values Result TD -> BTS 0.166 2.116 0.017 H1 Accepted TL -> BTS 0.231 3.497 0.000 H2 Accepted DA -> BTS 0.501 6.252 0.000 H3 Accepted DA -> OP 0.341 4.344 0.000 H4 Accepted BTS -> OP 0.275 3.114 0.001 H5 Accepted TD -> BTS -> OP 0.046 1.771 0.038 H6 Accepted TL -> BTS -> OP 0.064 2.024 0.021 DA -> BTS -> OP 0.138 2.658 0.004 RGI x BTS -> OP 0.083 1.077 0.141 H7 Rejected RGI x DA -> OP 0.031 0.434 0.332 H8 Rejected 2. R-square Test The R-square value measures the level of variation in changes in the independent variable compared to the dependent variable. The R-square results (Table 10) for endogenous latent variables in the structural model are 0.67 (strong), 0.33 (moderate), and 0.19 (weak) (Haryono 2016). Table 10. Result of R-square Test. R-Square R-Square Adjusted Business Transformation Strategy (BTS) 0.628 0.623 Organizational Performance (OP) 0.502 0.492 The R-square value represents the proportion of variance in the dependent variable explained by the independent variables. The model demonstrated moderate explanatory power, with an adjusted R-square value of 0.623 for Business Transformation Strategy and 0.492 for Organizational Performance. This indicates that the independent variables explain 62.3% of the variance in Business Transformation Strategy, and the combined effects of Digital Adoption, Business Transformation Strategy, and Regional Government Intervention explain 49.2% of the variance in Organizational Performance. While the model does not account for all the variance in the dependent variables, the moderate R-square values suggest that the chosen independent variables are meaningful predictors of Business Transformation Strategy and Organizational Performance within the studied context. 3. F-square Test The study utilized F-square values to determine the effect size of each predictor variable on the dependent variables. F-square values indicate the magnitude of a predictor’s influence, categorized as weak (0.02), moderate (0.15), or large (0.35) (Haryono 2016). The analysis (Table 11) revealed that Digital Adoption had a moderate influence on Business Transformation Strategy (F-square = 0.300). All other tested relationships demonstrated weak influence, with F-square values below 0.15. Specifically, Talent Development (Fsquare = 0.031) and Transformational Leadership (F-square = 0.089) had weak effects on Business Transformation Strategy. Similarly, Digital Adoption (F-square = 0.094) and Business Transformation Strategy (F-square = 0.057) had weak influences on Organizational Performance. Furthermore, the interaction effects of Regional Government Intervention with both Business Transformation Strategy (F-square = 0.009) and Digital Adoption (Fsquare = 0.002) on Organizational Performance were also weak. Adm. Sci. 2024,14, 299 18 of 27 Table 11. Result of F-square Test. Business Transformation Strategy (BTS) Organizational Performance (OP) Talent Development (TD) 0.031 Transformational Leadership (TL) 0.089 Digital Adoption (DA) 0.300 0.094 Business Transformation Strategy (BTS) 0.057 RGI x BTS 0.009 RGI x DA 0.002 4. Goodness of Fit Model Goodness of fit (GOF) validates the overall structural model. The GOF index is a single measure to validate the combined performance between the measurement model and the structural model, whether the GOF is low (0.1), moderate (0.25), or high (0.36) (Haryono 2016). The formula for calculating the GOF index is as follows: GOF value = √(average AVE ×average R-square) (1) GOF =√0.772 ×0.565 (2) GOF =0.660 Based on the calculation results (Table 12), the GOF value is 0.660, indicating that the combined performance of the outer and inner models in this study falls into the high GOF category. Table 12. Result of Goodness of Fit (GOF). Variables AVE R-Square Talent Development (TD) 0.695 Transformational Leadership (TL) 0.879 Digital Adoption (DA) 0.843 Regional Government Intervention (RGI) 0.711 Business Transformation Strategy (BTS) 0.819 0.628 Organizational Performance (OP) 0.684 0.502 Average 0.772 0.565 5. Prediction Relevance Test The study employed the Q2 predictive relevance test to assess the model’s predictive validity. A Q2 value greater than 0 indicates that the exogenous latent variables (predictors) effectively predict the endogenous latent variables (outcomes). The analysis yielded Q2 values of 0.505 for Business Transformation Strategy and 0.322 for Organizational Performance, both exceeding the 0 threshold. Results as shown in Table 13 suggest that the chosen predictor variables demonstrate good predictive validity for Business Transformation Strategy and Organizational Performance. Adm. Sci. 2024,14, 299 19 of 27 Table 13. Result of Prediction Relevance Test. SSO SSE Q2(=1 −SSE/SSO) Business Transformation Strategy (BTS) 765,000 378,798 0.505 Organizational Performance (OP) 765,000 518,403 0.322 Specifically, Talent Development, Transformational Leadership, and Digital Adoption are suitable predictors of Business Transformation Strategy. Similarly, Digital Adoption, Business Transformation Strategy, and their interaction with Regional Government Intervention effectively predict Organizational Performance. Another test in structural measurement is Q 2 predictive relevance, which functions to validate the model. The results of Q 2 predictive relevance are said to be good if the value is >0, which indicates that the exogenous latent variable is good (appropriate) as an explanatory variable that can predict its endogenous variable (Haryono 2016). 4. Discussion This study reveals several key findings regarding the factors influencing business transformation strategy and organizational performance in regional development banks. First, we found that Talent Development significantly influences Business Transformation Strategy (t= 2.116, p= 0.017). This result is in line with the research of Nurfadilah et al. (2022) regarding the effect of talent development on strategy. Other results from this research confirm the hypothesis that Transformational Leadership has a positive impact on Business Transformation Strategy (t= 3.497, p= 0.000). It aligns with the basic concept of transformational leadership (McKeown and Philip 2003;Radi Afsouran et al. 2022) and fortifies the findings of Wijaya Kusuma and Sudhartio (2020). These results show that leadership plays a more significant role in the local banking scale than employees. This study exhibited that Digital Adoption positively influenced Organizational Performance (t= 4.344, p= 0.000). Digital Adoption also influences Business Transformation Strategy positively (t= 6.252, p= 0.000). This finding aligns with the study of Alisjahbana et al. (2020), which suggests that digital adoption should replace the role of workers in business and non-business work units. Likewise, the studies by Cuevas-Vargas et al. (2021), Van Zeebroeck et al. (2021), and Oeij et al. (2022) on new technology are related to strategy formulation and even encourage strategy changes. This research shows that using technology as an organizational resource is more crucial than other resources in the banking industry on a local scale. Moreover, this research revealed that Business Transformation Strategy positively influenced Organizational Performance (t= 3.114, p= 0.001). This finding shows the importance of preparing a transformation strategy in an increasingly unstable business environment (Machani et al. 2015). In this way, RDBs need to transform their business to survive and compete with competitors (Nurfadilah et al. 2022). Furthermore, Business Transformation Strategy has proven to mediate Organizational Performance significantly. Additionally, it has been proven that Regional Government Intervention did not significantly have a moderation effect on the relationship between Business Transformation Strategy and Organizational Performance (t= 1.077, p= 0.141) or on the relationship between Digital Adoption and Organizational Performance (t= 0.434, p= 0.332). In previous studies, government intervention provides a moderating effect (Kousar et al. 2017). However, when applied to regional banking, the effect of regional government intervention does not have a significant impact. This study holds significant potential to advance resource orchestration theory by examining digital transformation in the context of Indonesian regional development banks. It can provide empirical support for ROT’s relevance in digital transformation by exploring how effectively orchestrating digital resources enables strategic renewal. By examining resource orchestration needs and approaches across different stages of transformation, drawing on Davidson’s (1999) framework (vision, culture, performance), the study can Adm. Sci. 2024,14, 299 20 of 27 offer a nuanced understanding of how orchestration evolves. Finally, by empirically testing the mediating role of business transformation strategy in linking resource orchestration to organizational performance, the study can further strengthen ROT’s core principles. Contrary to expectations derived from institutional theory, this study found that regional government intervention did not directly moderate the relationship between key drivers (business transformation strategy, digital adoption) and organizational performance in Indonesian regional development banks. While previous research often positions government intervention as a significant moderating force shaping organizational responses to institutional pressures (e.g., Kousar et al. 2017), our findings reveal a more nuanced dynamic within the Indonesian RDB context. This suggests that the influence of government intervention on RDB performance operates through alternative pathways, potentially stemming from the unique characteristics of these institutions. Their developmental mandates, regional resource dependencies, and close relationships with local authorities likely contribute to a distinct institutional logic that warrants further exploration. While this research provides valuable insights into the factors driving Business Transformation Strategy (f= 0.623) and Organizational Performance (f= 0.492) in Indonesian regional development banks, it is essential to acknowledge certain limitations. The results of this study show that Talent Development, Transformational Leadership, and Digital Adoption can explain Business Transformation Strategy as a variable. Therefore, future research can test other factors (37.7%) as antecedents of Business Transformation Strategy. Meanwhile, the combined effect of Digital Adoption, Business Transformation Strategy, and Local Government Intervention explains 49.2% of the variance in Organizational Performance. So, there is space for further research on the variables (50.8%) expected to affect Organizational Performance. In countries such as Japan and China, regional banks’ business strategies are no longer focused on business transformation but on improving performance through efficiency (Harimaya and Kondo 2016;Zhao et al. 2019). Meanwhile, in Germany, regional banks have shown better resilience during the financial crisis compared to large banks (Flögel and Gärtner 2020). Further investigation to compare these factors to the performances of neighboring countries can address new insight into RDBs’ performance and business transformation. The study’s geographical focus on Indonesia and the specific sample of branch managers might restrict the generalizability of findings to other contexts. Moreover, the reliance on a single data source and cross-sectional design limits broader comparisons and long-term insights. Future research could address these limitations by expanding the geographical scope and banking scale, incorporating multiple data sources and perspectives, and employing longitudinal designs to track the evolving dynamics of business transformation in the banking sector. Although focused on Indonesian regional development banks, this research offers valuable takeaways for managers across industries. Prioritizing digital transformation and employee upskilling, cultivating transformational leadership, fostering a culture of continuous learning and knowledge sharing, aligning business strategies with government policies, and adopting a people-centric approach to change management are crucial for navigating successful transformations in today’s rapidly evolving business landscape. Future studies could investigate additional factors influencing business transformation strategy and organizational performance within the digital economy, such as data-driven decision making, artificial intelligence, and financial technology partnerships. The findings underscore the importance of tailored government policies that support RDBs in their digital and organizational transformation efforts without imposing restrictive controls. For RDB management and organizational leaders, this study suggests a strategic focus on cultivating transformational leadership, fostering talent development, and accelerating digital adoption. Additionally, aligning business transformation efforts with local government initiatives and policies can help RDBs achieve more effective outcomes. Finally, banking authorities can significantly contribute to a thriving banking sector by Adm. Sci. 2024,14, 299 21 of 27 providing guidance on transformation strategies, facilitating collaboration and knowledge sharing, and fostering a supportive regulatory environment for digital adoption. 5. Conclusions This study examined the factors influencing business transformation strategy and organizational performance in Indonesian regional development banks, recognizing their crucial role in the nation’s financial landscape, as evidenced by their significant asset share and consistent growth within the banking sector. While regional development banks are vital for regional economic advancement, they face mounting pressures to adapt to technological advancements, evolving market dynamics, and heightened competition. This study confirmed the critical role of talent development, transformational leadership, and digital adoption as drivers of successful business transformation strategies and enhanced organizational performance in regional development banks. Importantly, our research revealed a unique finding: as entities with majority ownership by regional governments and subject to government intervention, regional government intervention controversially did not moderate the relationship between business transformation strategy and digital adoption with organizational performance in Indonesian RDBs. Notably, regional government intervention did not directly moderate the relationship between key drivers and organizational performance, suggesting a more nuanced influence on Indonesian RDBs that warrants further investigation. Future research could expand on this study by comparing the factors influencing business transformation and performance in regional banks across neighboring countries, enhancing generalizability and offering regional insights. Additionally, exploring factors within the digital economy could deepen understanding of digital transformation’s impact on organizational performance. This study advances resource orchestration theory by demonstrating the role of digital resource orchestration in strategic renewal. It challenges institutional theory by revealing nuanced effects of government intervention on performance, suggesting that unique institutional characteristics shape organizational outcomes differently than expected. This study highlights the importance of RDBs prioritizing digital transformation, talent development, and transformational leadership to enhance organizational performance. Finally, supportive government policies and collaborative efforts with banking authorities are essential for fostering a conducive environment that enables RDBs to navigate successful transformations. Author Contributions: Conceptualization, A.T. and M.H.; methodology, A.T., M.H., D.L.W. and P.H.; software, A.T.; validation, M.H., D.L.W. and P.H.; formal analysis, A.T.; writing—original draft preparation, A.T.; writing—review and editing, M.H. and A.T.; visualization, A.T.; supervision, M.H., D.L.W. and P.H.; project administration, A.T. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Doctor of Research in Management (DRM) Program BINUS Business School 098/HoP.DRM/IX/2024. Informed Consent Statement: Not applicable. Data Availability Statement: Data are contained within the article. Conflicts of Interest: The authors declare no conflicts of interest. Appendix A Table A1. List of Regional Development Banks. No. RDB 1 Bank Sulutgo Adm. Sci. 2024,14, 299 22 of 27 Table A1. Cont. No. RDB 2 Bank Aceh 3 Bank Sumut 4 Bank Riau Kepri 5 Bank Nagari 6 Bank Jambi 7 Bank Bengkulu 8 Bank Sumsel Babel 9 Bank Lampung 10 Bank BJB 11 Bank Banten 12 Bank DKI 13 Bank Jateng 14 Bank RDB DIY 15 Bank Jatim 16 Bank Kalbar 17 Bank Kalsel 18 Bankaltimtara 19 Bank Kalteng 20 Bank RDB Bali 21 Bank NTB Syariah 22 Bank NTT 23 Bank Sulselbar 24 Bank Sulteng 25 Bank Sultra 26 Bank Maluku Malut 27 Bank Papua Appendix B Table A2. Variables, Dimensions, and Indicators. Variables Dimensions Indicators Talent Development Training and Development The company’s training and development programs designed to develop skills that benefit in completing my works effectively in the long-term The company’s training and development programs has sharpened my characters to be more ethical, honest, and motivated Information and Technology (IT) training program has helped me in leveraging the use of digital technology Career Development The company has a career development plan to prepare the company for the future. The company has succession planning for each position. Employee promotions at the company prioritize achievement and then seniority. Adm. Sci. 2024,14, 299 23 of 27 Table A2. Cont. Variables Dimensions Indicators Talent Development Creativity The company encouraged their employee to take initiative The company open to new ideas The company has flexibility in procedures Transformational Leadership Inspirational Motivation My leader encourages me to see a problem as a learning opportunity My leader acknowledges my achievement My leader is a trusted person Intellectual Stimulation My leader appreciates every new idea to solve the problem that an organization faces My leader provides reasons to change my perspectives My leader gives me what I want in return for my support to him Individualized Consideration My leader wholeheartedly supports me when he/she feels that my idea is good for the company My leader knows what I want and helps me get it My leader compliments me if I perform well Digital Adoption Infrastructure The company develops and maintains their technology hardware & software The company provides staff to manage their information technology The company implements new technology applications Strategy Alignment The company aligns IT strategy with business strategy The company updating IT applications for business strategic goals The company deploying IT strategies for business processes Individual Learning The company provides IT-related training The company adapts employees to use IT applications The company develops employees’ IT knowledge and skills Business Transformation Strategy Strategy Selection The company implements a cost-efficiency strategy The company develops new product The company implements cost-efficiency and product development simultaneously Changes in Value Creation The company develops a more digital product display for customers The company prepares ways to create revenue from future business operations The company prepares their future business scope Structural Changes The company provides persons in charge of their digital transformation endeavor The company has a plan to integrate new operations into existing structures or create separate entities The company develops new competencies Regional Government Intervention Financial Intervention The regional government has an influence on investment decisions in my company The regional government has an influence on financing decisions in my company. The regional government really supports my company’s capital. Regulation Intervention Regional government policies have an influence on my company’s business. Regional government policies have an influence on my company’s operations. Regional government policies have an influence on customer services at my company. Adm. Sci. 2024,14, 299 24 of 27 Table A2. Cont. Variables Dimensions Indicators Regional Government Intervention Personnel Intervention The regional government has an influence on the selection of management in my company. The regional government has an influence on the selection of officials in my company. The regional government has an influence on the placement of employees in my company. Organizational Performance Financial Perspective Company transformation has increased market share. Company transformation has increased efficiency. Company transformation has increased profitability. 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