Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6, 8281-8293 2024 Publisher: Learning Gate DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate © 2024 by the authors; licensee Learning Gate * Correspondence: sri.dewi@email.unikom.ac.id Building the success of culinary SMEs in food processing: Perspectives on business ecosystem analysis and digital transformation in West Java, Indonesia Deden Abdul Wahab1, Sri Dewi Anggadini2*, Dedi Sulistiyo Soegoto3, Rio Yunanto4 1,3Master of Management, Universitas Komputer Indonesia, Indonesia; wahab@email.unikom.ac.id (D.A.W.) dedi@email.unikom.ac.id (D.S.S.). 2Department of Accounting, Universitas Komputer Indonesia, Indonesia; sri.dewi@email.unikom.ac.id (S.D.A.). 4Department of Computerized Accounting, Universitas Komputer Indonesia, Indonesia; rio.yunanto@email.unikom.ac.id (R.Y.). Abstract: This study seeks to analyze the role and impact of the business environment and digital transformation on the development of small culinary firms focused on processed foods. While a business ecosystem and digitalization generally impact various business kinds, research particularly addressing small culinary operations is few. This study used a descriptive and verification-based methodology, focusing on West Java, Indonesia, as the case study. The unit of analysis comprises small culinary firms that focus on processed meals, whereas the units of observation are the business actors involved. Observations and surveys were performed over nearly a year, from January 2022 to November 2023, with primary data evaluated by Structural Equation Modeling (SEM) and supplemented by a literature study to validate the findings. The results demonstrate that the business environment and digital transformation enhance the success of small culinary firms focused on processed goods. An effective business ecosystem and suitable digital transformation can greatly influence corporate success. Consequently, business stakeholders are urged to capitalize on prevailing business ecosystem conditions and enhance digital transformation in decision-making processes to attain company success. Keywords: Business ecosystem, Business success, Digital transformation. 1. Introduction Small culinary enterprises specializing in processed foods play a significant role in supporting economic resilience in communities and their function in social stability (Disperindag, West Java, 2022). The role of Micro, Small, and Medium Enterprises (MSMEs), particularly in Indonesia, has demonstrated substantial contributions to the economy, especially in creating job opportunities, thereby reducing unemployment. Generally, MSMEs in developing countries, including Indonesia, encompass a wide variety of businesses and characteristics, with a large number of enterprises spread across regions. MSMEs are also positioned as key players in economic activities across various sectors and are often recognized as drivers of local economic development and community empowerment, creating new markets and serving as sources of innovation. Moreover, during times of economic and financial crises in Indonesia, MSMEs have significantly contributed to maintaining the macroeconomic balance of payments. Many of their products are in high demand in broader markets through export activities, whether as raw materials, finished goods, or semi- finished goods (Benjamin et al., 2019). It is undeniable that MSMEs remain one of the sectors with competitive advantages, supporting Indonesia's economy by utilizing abundant domestic raw materials and offering unique and distinctive product variations. The development of small culinary enterprises specializing in processed foods within MSMEs in West Java can be observed in Table 1, which shows an increasing number of businesses from 2017 to 2021. This growth indicates that processed culinary products are widely consumed by people from various segments of society. The rising demand for these 8282 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate products presents significant opportunities for business actors. However, improvements across interconnected sectors still face challenges. These challenges stem from several factors, including existing business ecosystem constraints, internal managerial issues, and changes in consumer preferences for culinary products, ranging from presentation to packaging and services. Table 1. The number of processed culinary food MSMEs in West Java. No Year Processed culinary foods 1 2017 1,761,095 2 2018 1,870,058 3 2019 1,985,763 4 2020 2,108,627 5 2021 2,239,092 Source: West Java Cooperative and Small Business Office (2023). Looking deeper, particularly in aspects related to marketing challenges, MSME products often face competitive pressures. This includes competition in the domestic market from similar products produced by large enterprises and imports from other countries, as well as challenges in the export market. Furthermore, MSMEs frequently suffer from limited access to information, including transportation challenges in distributing their products. This is often due to the businesses being located in areas with underdeveloped infrastructure. Additionally, the products they produce often struggle to meet standards, particularly international production and trade standards. Given these issues, research in this area is urgent, as the success of small-scale culinary businesses often falters when faced with business changes (Bacq et al., 2022). On the other hand, the rapid advancements in information technology and the digitization of business systems required by organizations are not easily adapted by small business owners. The business ecosystem, which should function as a synergistic force for organizations to build partnerships and deliver value to end users or customers, often does not support small businesses, jeopardizing their survival. Moreover, while the business ecosystem and digital transformation offer opportunities for small businesses through technological advancements, they also pose significant threats. The inability of business owners to adapt and establish networks with suppliers, distributors, customers, or even competitors often leads to regression or bankruptcy. Specifically, small-scale culinary businesses are one of the most common types of MSMEs, particularly in West Java, where they play a vital role in supporting economic resilience and contributing to social stability. According to West Java's Department of Industry and Trade (2022), the prospects for the food and beverage industry continue to show positive development and contribute significantly to national economic growth. However, despite the vast number of small-scale culinary businesses and the widespread consumption of their products, their growth is not accompanied by strong resilience to sustain their operations. Many even face bankruptcy. This stagnation often stems from classic problems such as limited market access, financing, management, the ability to utilize technological advancements, and building business networks within the current digitalized ecosystem (Ilmafa'ati, 2021). The issues identified in this context include: 1) The inability of small-scale culinary businesses to establish relationships and synergize with other companies in building strategic partnerships to deliver value to end users or customers, which poses a significant challenge. 2) The inability to adapt to a business ecosystem where businesses complement each other, supply products to one another, combine products or services to create added value, or find better channels to reach larger target markets, potentially leading to the failure to sustain or enhance their success. 3) Weaknesses in utilizing advancements in information technology in line with current digitalization trends, resulting in weak competitiveness and subsequently low chances of sustaining their operations. Based on the points mentioned above, this research aims to examine small-scale culinary businesses in West Java to enhance their success. This is achieved through the process of identifying, studying, and 8283 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate analyzing the business ecosystem as a determining factor and digital transformation as a technological change that can be utilized. The research approach refers to theories related to business ecosystems and the readiness of small businesses to adapt to technological advancements through effective digitalization practices. In this context, the business ecosystem refers to a complex network of relationships among companies, customers, partners, competitors, regulators, and other elements that influence business performance and success. The existence of this ecosystem requires active interaction among stakeholders to create sustainable added value and mutual benefits. This interaction includes mutually beneficial collaboration processes, resource sharing, and building trust within a dynamic business environment. A fundamental attribute of the business ecosystem is interconnectedness and the capacity for evolution among firms, institutions, and customers in generating and leveraging economic value. A corporation may depend significantly on suppliers for raw materials or finished goods, while business partners can enhance market share and operational efficiency (Dentoni et al., 2021). These connections foster a symbiotic relationship that allows organizations to expand and compete in a dynamic market. Moreover, the business ecosystem includes customers as the primary source of revenue. Therefore, understanding customer needs, preferences, and behaviors is crucial for businesses to offer relevant and high-quality products or services. This approach requires integrating customer data to predict market trends and develop product innovations that align better with consumer demands. Innovation within the business ecosystem requires a holistic and well-coordinated strategy, considering the interactions between various actors and factors involved in value creation and utilization. This innovation process includes developing adaptive business models, applying the latest technologies, and strengthening managerial capacities to maintain competitiveness in a continuously evolving ecosystem (Bouncken & Kraus, 2022). Several aspects of the business ecosystem surrounding MSMEs have been examined, but many challenges remain. Existing studies have only scratched the surface, leaving ample room for further research to map, model, and explore components and drivers of the business ecosystem and digital readiness. This includes people, organizations, culture, and the digital environment. Previous studies have primarily focused on specific digital technologies, such as e-commerce, social media, online transportation, and online stores. However, a broader understanding of the ecosystem can help businesses identify opportunities, anticipate challenges, and develop effective strategies to achieve their goals by enhancing entrepreneurial capabilities (Coda et al., 2018). Conversely, digitalization involves the transformation of information from analog to digital formats, facilitating its processing by computers. This transformation involves a comprehensive change in the operational, communicative, and value delivery methods of businesses and organizations, facilitated by digital technologies that are customized to their specific processes (Hitpass et al., 2019). Jafari et al. (2021) contend that digital transformation facilitates firms in enhancing operations, developing new products and services, and engaging more efficiently with customers. Digitalization sometimes serves as the preliminary stage in the digital transformation process. Data acquired through digitalization provides critical insights and information necessary for effective digital transformation. Collaboration and co-creation with customers, employees, and partners are vital for effective digital transformation programs, enabling firms to develop solutions that meet the changing needs of stakeholders (Manser et al., 2021). According to Reis et al. (2018), several factors drive digitalization, including technology, customer needs, market competition, globalization, lifestyle changes, environmental pressures, and government regulations. Government support is also critical to help small businesses "go digital" and "go global" (Bacqet al., 2022). Given the diversity of culinary businesses in West Java, which produce unique local specialties, this research is conducted across a broad geographic area to generalize findings to a larger and more representative population. This approach aligns with the ongoing digitalization and transformation of MSMEs, providing valuable insights for the development of these businesses in the region. 8284 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate 2. Literature Review The concept of a business ecosystem is influenced by cross-industry operations and is often compared to a biological ecosystem (Bachri & Setiani, 2017). A business ecosystem can be understood and analogized as an economic community formed by organizations and individuals that interact to create valuable goods and services. According to Garousi et al. (2022), a business ecosystem can be simply defined as a dynamic condition consisting of several economic players who are largely independent but can collectively create products or services, forming an integrated solution. Herrera (2016) highlights two key characteristics of a business ecosystem: first, the loosely connected network among member elements within an interconnected environment, and second, the strength of the network due to extensive connections, enabling it to develop and sustain itself while enhancing the performance of its elements or participants (Ilmafa'ati, 2021). The presence of various organizations involved in a business ecosystem necessitates the implementation of a collaborative approach across the value network to ensure synergy among stakeholders. One of the primary goals of a business ecosystem is to create and capture value through innovation, which can enhance competitiveness in the global market (Höllen et al., 2020). A business ecosystem is characterized by its dynamic nature, network-oriented focus, and external orientation that extends beyond individual companies, enabling cross-industry integration. Collaborative and competitive relationships serve as key drivers within the business ecosystem, creating a supportive environment that fosters continuous innovation. No single member holds full control or sole ownership within the ecosystem, making its success dependent on the contributions and cooperation of all its members. This implies that businesses must develop and deploy various new capabilities to coordinate and enhance value creation (Damayanti et al., 2023). Business ecosystems also provide a collaborative environment and shared infrastructure that fosters trust among members (Fellnhofer, 2017), thereby encouraging resource and information exchange. Advancements in information technology, supported by internet infrastructure, have undeniably transformed many aspects of human life, including business operations. Today’s business activities are deeply intertwined with technological progress, spanning production, marketing, and distribution processes. These technological advancements offer both significant benefits and challenges that all stakeholders must navigate. Digital technology has played a critical role in connecting value-creation processes. Numerous studies demonstrate that the strategic adoption of digital technology can lead to improved competitiveness, productivity, and performance (Barkhatov et al., 2016). For MSMEs, adopting digital technology enables them to perform a wide range of activities in response to potential problems, unexpected events, or challenges beyond their immediate control. As such, digital transformation is essential amid the rapid, unpredictable, and uncertain changes in today’s environment, particularly for MSMEs, including small-scale culinary businesses. In today's rapidly changing environment, businesses of all sizes face intense competition and numerous challenges. To sustain growth in a volatile, uncertain, complex, and ambiguous world, companies must innovate, remain flexible, adopt cutting-edge technologies, and respond quickly to these challenges to stay competitive and thrive (El Hilali, El Manouar, & Idrissi, 2019; Marhraoui & El Manouar, 2018). For MSMEs, adopting digital technology to ensure business continuity requires a strategic rethinking of their business processes, as its implementation impacts various activities, organizational structures, and performance. Isahak et al. (2017) define digital transformation as a process designed to improve an entity by instigating substantial alterations in its characteristics through the amalgamation of information, computer, communication, and networking technologies. Digital transformation is not limited to large enterprises; it also provides chances for MSMEs to enhance their operations via digitization (Dewi Anggadini et al., 2023). According to Hardilawati et al. (2019), there are strong motives for leveraging rapidly evolving technology, such as cost reduction, increased efficiency, and improved customer relationships and satisfaction. However, many companies across various industries struggle to adapt to the digital era. Research findings indicate that digitalization creates opportunities for innovative business models and serves as a powerful transformative force, reshaping business processes, corporate capabilities, products, services, and key relationships (D.J. Teece, 2016). To capitalize on digitalization, 8285 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate businesses must work diligently to integrate digital technologies into their operations (Husin & Haron, 2020). While many large corporations struggle to adapt to or leverage digitalization, it poses even greater challenges for small and medium-sized enterprises (Harel et al., 2021). Digital technology has fundamentally changed how we communicate with others. Digitalization plays a vital role in driving economic growth by promoting inclusivity through interconnectivity among businesses, facilitating international trade, and addressing informational barriers (Street & Street, 2020). Currently, digitalization and organizational sustainability are top priorities influencing the business world (Marhraoui & El Manouar, 2018; Miceli et al., 2021). Thus, research into the relationship between business sustainability and digitalization is crucial. Many researchers and practitioners emphasize the importance of digital transformation as the application of the latest technologies and innovations to enhance process efficiency, ensuring that products add value and contribute to an organization's sustainable economic growth (Chandola, 2016). Nowadays, businesses must undergo digital transformation in order to push themselves beyond their comfort zones, adapt, and compete in a world driven by technology breakthroughs. One of the top three strategic initiatives for companies and organizations has been determined to be digital transformation (Gartner, 2017; Mentsiev et al., 2020). Scholars frequently consider digital transformation to be a "continuous process" that involves both the government and corporate sectors, rather than just a project (Herrera, 2016). El Hilali, El Manouar, and Idrissi (2019) identify digitalization as the first stage of an organization's digital transformation process. Barkhatov et al. (2016) define digitalization as the use of digital technology to change conventional corporate operations, processes, goods, and services (Dewi Anggadini, 2023). This approach commonly makes use of a variety of technologies, including cloud computing, data analytics, artificial intelligence, and the Internet of Things (IoT) (Isahak et al., 2017). According to El Hilali, El Manouar, and Idrissi (2019), digitalization is the initial stage of a fully integrated digital business. In order to generate new revenue streams and creative business models, digital transformation is then positioned as the next stage, with an emphasis on rethinking and continuously refining the use of technology, data, human resources, and processes to shape digital organizations (Street & Street, 2020). Accordingly, digital transformation includes significant changes and transformations propelled by a strong technological base in addition to being just about technology (Garousi et al., 2022). 3. Methodology The research method used in this study is both descriptive and verificative. The adopted approach is explanatory or causal research, aiming to determine how one variable affects changes in another (Sekaran, Uma & Bougie, Roger, 2020). The study begins by identifying and examining the components of the business ecosystem, key factors influencing it, readiness for digitalization or digital transformation, including its driving factors, and the success of small-scale culinary businesses in a descriptive manner. Subsequently, the contribution of the business ecosystem in determining digital transformation readiness, which impacts the success of small-scale culinary businesses, is measured quantitatively. The study employs three main techniques: 1) conducting a review and analysis of various relevant reference sources to support the theoretical foundation and research framework, 2) conducting a structured discussion involving a group of participants to explore their views, opinions, and experiences on the research topic (FGD), and 3) collecting data through direct interaction with respondents using structured questions or direct observation to obtain relevant information on the research topic. Qualitative and quantitative data are processed in this study, including data analysis from interviews, observations, and group discussions to gain in-depth understanding, as well as survey data processing to obtain an accurate quantitative overview. The research activities are carried out through several stages: designing the study, developing instruments, determining samples, collecting field data, tabulating data, filtering and classifying data, analyzing data, interpreting results, formulating recommendations, and compiling the final report. The sampling includes both business actors and representatives from relevant government agencies, considering data accuracy and representation in the food processing sector. The sample population consists of 200 small-scale businesses under the guidance of the Cooperative and Small Business Office 8286 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate of West Java Province, selected using a probability sampling method. Initially, cluster sampling is conducted across selected districts/cities, and the unit of observation is the small business actors themselves. Once the data is collected, it undergoes tabulation, organization, and selection to ensure that the data used for analysis is accurate and relevant. The selection process aligns with the type and level of importance of the required information. This ensures valid and accurate data, which is critical to achieving the objectives of this study. The SEM process begins with data tabulation from questionnaire responses, followed by analysis through several stages: 1) Specification, 2) Identification, 3) Estimation, 4) Validity and reliability testing, 5) Goodness-of-fit testing, 6) Model respecification. The SEM procedural steps are illustrated in Figure 1, which depicts the workflow for the analysis process. Figure 1. Overall research variable analysis structure. 4. Results and Discussion The study employed a measurement tool that included a range of quantitative analyses in accordance with the research objectives. The investigation utilized the data analysis technique of Structural Equation Modeling (SEM), comprising two primary models: the measurement model (outer model) and the structural model (inner model). The study included three underlying variables: Business Ecosystem (X1), Digital Transformation (X2), and Business Success (Y), comprising a total of 18 observable variables. There are eight manifest variables associated with the Business Ecosystem, six related to Digital Transformation, and four pertaining to Business Success. The measurement model in SEM guarantees that the observed variables precisely represent the latent variables under investigation. This is achieved using Confirmatory Factor Analysis (CFA), which assesses the model's fit, validity, and reliability. In SEM, the coefficients of manifest variables reveal the extent of correlation between these variables and their associated latent variables, illustrating the robustness of these connections. The loading factor stands out as a vital measure in this analysis, reflecting the correlation between an indicator and its underlying construct. Indicators that exhibit high loading factors play a crucial role in elucidating the latent variable, whereas those with low loading factors exert a lesser influence. Numerous studies suggest that a minimum loading factor of 0.50 is essential for ensuring strong 8287 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate validity (Hair et al., 2010; Ghozali, 2008). Nonetheless, additional sources, including Sharma (1996) and Ferdinand (2000), indicate that values as low as 0.40 can still be deemed acceptable. The coefficient values span from -1 to 1. A positive value signifies that the manifest and latent variables are aligned in their movement, whereas a negative value denotes that they are moving in opposing directions. Table 2 presents the contributions of each manifest variable to the latent variable Business Ecosystem (X1). The analysis reveals that ecosystem complexity and industry diversity have the lowest contributions to shaping the business ecosystem. Manifest variables with moderate contributions include value exchange forms, types of relationships, participant engagement, and ecosystem strategies. Technology and openness level record the highest contributions in explaining the Business Ecosystem latent variable, emphasizing their critical role in creating an effective and competitive business ecosystem. These findings highlight the varying strengths of manifest variables in explaining the latent constructs, providing valuable insights into the most influential factors within the business ecosystem. Table 2. The contribution of each manifest variable to the latent variable in the business ecosystem. No Variable manifest Coefficient loading factor 1. X1.1 (Ecosystem strategy) 0.65 2. X1.2 (Degree of openness) 0.89 3. X1.3 (Engagement of diverse participants) 0.64 4. X1.4 (Types of relationship) 0.63 5. X1.5 (Form of value exchange) 0.58 6. X1.6 (Diversity of industries) 0.44 7. X1.7 (Complexity of multiple ecosystem) 0.46 8. X1.8 (Technologies) 0.75 The analysis of the manifest variables for the Business Ecosystem indicates that all variables have acceptable and valid loading factors, suggesting their reliability in measuring the latent construct. These finding highlights that the variables are meaningful contributors to the model, albeit with varying levels of influence. For the latent variable Digital Transformation, the contributions of its manifest variables are outlined in Table 3. The variables Customer, Culture, and Data show relatively lower contributions to Digital Transformation, while Operation, Strategy, and Technology have stronger contributions. This suggests that operational practices, strategic focus, and technological adoption play a more critical role in driving digital transformation compared to customer orientation, cultural aspects, and data management. Table 3. The contribution of each manifest variable to the latent variable in digital transformation No Variable manifest Coefficient loading factor 1. X2.1 (Customer) 0.43 2. X2.2 (Strategy) 0.74 3. X2.3 (Culture) 0.47 4. X2.4 (Technology) 0.78 5. X2.5 (Operation) 0.71 6. X2.6 (Date) 0.55 Similarly, Table 4 examines the manifest variables for the latent variable Business Success, emphasizing the contribution of each indicator to this construct. The results underscore the importance of understanding the varying impacts of manifest variables to accurately capture the essence of the latent variables. The acceptance and validity of the loading factors across all variables confirm the robustness of the model, allowing for a nuanced analysis of the relationships between business 8288 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate ecosystems, digital transformation, and business success. These insights can guide businesses in prioritizing key areas for improvement to enhance performance and competitiveness. Table 4. The contribution of each manifest variable to the latent variable in business success. No Variable manifest Coefficient loading factor 7. Y1.1 (Profitability) 0.68 8. Y1.2 (Business expansion) 0.66 9. Y1.3 (Market extent) 0.99 10. Y1.4 (Product quality) 0.92 The R² number, or coefficient of determination, quantifies the proportion of variance in the dependent variable that is elucidated by the independent variables in the model. The range is from 0 to 1 (0 ≤ R² < 1), with elevated values signifying more explanatory power of the model. This number is essential for evaluating the model's overall suitability and predictive power, as it underscores the efficacy of the proposed relationships between variables. Furthermore, Figure 2 visually illustrates the links between manifest and latent variables, loading factor analysis, and the R² values using a path map, offering an extensive overview of the structural relationships and the contributions of each variable to the entire model. This image aids in recognizing essential pathways and corroborating the model's assumptions. Figure 2. Path diagram of the correlation between manifest variables and latent variables. The measurement method assesses the structural model, known as the inner model test, which encompasses the R-square (R²) value, path coefficients, and T-statistic tests. The R² value, or coefficient of determination, quantifies the degree to which the proposed exogenous variables in the equation account for the variance in the endogenous variable. To enhance comprehension of the relationship between the Business Ecosystem (X1) and Digital Transformation (X2) and their impact on Business Success (Y), please consult Figure 3 presented below: 8289 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate Figure 3. Path diagram of the influence and correlation between latent variables. The relationship between the Business Ecosystem and Digital Transformation has a coefficient of 0.32, indicating a significant positive relationship. This concept illustrates that the business ecosystem drives digital transformation in enhancing and advancing small-scale culinary businesses. Conversely, it also means that digital transformation supports the development and progress of the business ecosystem within small-scale culinary enterprises in West Java. For further details, refer to Table 5, as well as Figures 2 and 3, as presented above. Table 5. The influence of exogenous latent variables on endogenous latent variables. Structural path coefficient R-square. value Effect with exogenous latent variables Sig. (%) X1 X2 Business ecosystem (X1): Business success (Y) 0.42 (0.42)² x100 =17.64% 4.83% 22.47% Digital transformation (X2): Business success (Y) 0.36 (0.36)² x100 =12.96% 4.83% 17.79% Total 40.26% Based on Table 5, the Business Ecosystem (X1) contributes 22.47% to Business Success (Y), consisting of a direct effect of 17.64% and an indirect effect of 4.83% through Digital Transformation (X2). This indicates that a strong network of business partners, supplier support, and favorable policies not only directly enhance business performance but also facilitate the adoption of digital technologies, further strengthening overall business success. Meanwhile, Digital Transformation (X2) has a total impact of 17.79% on Business Success (Y), comprising a direct effect of 12.96% and an indirect effect of 4.83% through the Business Ecosystem (X1). This suggests that implementing digital technologies such as system integration, data analytics, and business process automation not only directly improves operational efficiency but also strengthens the business ecosystem by streamlining collaboration and communication among stakeholders. Thus, the reciprocal relationship between the Business Ecosystem and Digital Transformation demonstrates that both factors complement each other, creating a synergistic effect that amplifies their positive impact on business success. The direct effect reflects the immediate impact of each variable, 8290 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate while the indirect effect highlights how one variable reinforces the other, generating a mutually supportive cycle of growth. 4.1. Path Coefficient Analysis The path coefficient represents the standardized regression coefficient (Z-standard), illustrating the influence of exogenous variables on endogenous variables as structured in the path diagram. The calculated path coefficients are presented in Table 6. Table 6. Path coefficient test results. Business success (Y) Business ecosystem (X1) 0.42 Digital transformation (X2) 0.36 Based on the results of the path coefficient test shown in Table 6, the variable business ecosystem has a coefficient value of 0.42 in relation to business success, indicating a positive relationship with an influence of 42%. Similarly, the variable digital transformation has a coefficient value of 0.36 in relation to business success, showing a positive impact of 36%. The remaining 22% is attributed to external factors or other variables not discussed in this study. 4.2. T-Statistic Test The T-Statistic test is conducted to evaluate partial hypotheses and establish the relationships between the variables business ecosystem, digital transformation, and business success, as detailed in Table 7. Table 7. Statistical t-test results. Path coefficient P values T table T statistics Decision Conclusion Business ecosystem (X1) →Business success (Y) 0.42 0.00001 2.030 3.28 H0 rejected Significant Digital transformation (X2) →Business success (Y) 0.36 0.00001 2.030 3.52 H0 rejected Significant The results from Table 7 demonstrate that the business ecosystem significantly influences business success, as evidenced by a T-statistic of 3.28, which surpasses the T-critical value of 2.03. The rejection of the null hypothesis (H0) indicates that elements such as partnerships, supplier networks, and regulatory support within the business ecosystem significantly contribute to business success. Digital transformation significantly impacts business success, evidenced by a T-statistic value of 3.52, exceeding the T-critical value of 2.03. The rejection of H0 in this test indicates that the adoption of digital technologies, including process automation, data analytics, and digital integration, directly enhances operational efficiency and market competitiveness. The integration of a strong business ecosystem with efficient digital transformation is a fundamental factor in promoting business growth and sustainability. 5. Discussion Successful companies do not operate as isolated entities within a defined national industry but rather resemble organisms within a natural ecosystem. They collaborate and compete with other organizations while developing capabilities, each fulfilling specific roles within the ecosystem. This interdependence enables them to innovate, develop new products and services, and better meet customer needs. However, much like natural ecosystems, business ecosystems are vulnerable to collapse if they fail to adapt or respond swiftly to external changes. Consequently, the long-term performance of individual 8291 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate companies—their success or decline—is significantly influenced by the adaptive actions of the ecosystem (J.F. Moore, 1993; E. Anggraeni, E. Den Harthigh, and M. Zegveld, 2007). Research by Christens (2012) highlights that business ecosystems drive ongoing innovation and product iterations to meet evolving consumer demands, undergoing cycles of creation, expansion, and eventual extinction. Digital transformation has profoundly impacted industries and business activities globally, albeit with varying challenges across business segments and regions. Digital transformation facilitates the delivery of structured information to customers via the internet, bridging the informational gap between companies and clients. This increased market transparency empowers consumers with stronger bargaining power and access to lower prices. However, regional differences in digital sophistication may influence these outcomes. Digital transformation represents a fundamental shift for many companies, enabling them to reshape their business models and access new client bases (Grab et al., 2018b). According to Mentsievet al. (2020), market dynamics evolve alongside digitalization, as companies, industries, and nations strive to keep pace with its accelerating importance for success and progress. Chandola (2016) further emphasizes the significant impact of digital transformation on organizational sustainability, citing benefits such as improved process efficiency, faster decision-making, enhanced supply chain management and tracking, regulatory compliance, and increased workforce productivity. Together, these insights demonstrate that both business ecosystems and digital transformation play critical roles in driving business success. 6. Conclusion And Recommendation The study demonstrates that the business ecosystem has a positive and significant impact on the success of small-scale culinary businesses in West Java. A well-functioning business ecosystem contributes to greater business success; however, challenges such as industry diversity within the culinary sector, the complexity of ecosystem elements (e.g., customers, suppliers, government policies, and competitors), and gaps in collaboration remain prevalent. These challenges highlight areas for improvement within the ecosystem. Additionally, digital transformation significantly influences business success, with key challenges identified in customer engagement and the cultural adaptability of business owners. Effective digital transformation relies on customers' ability to understand and utilize digital tools, as well as on fostering a culture that embraces technological advancements. Together, a robust business ecosystem and successful digital transformation strengthen core business outcomes, including profitability, market expansion, customer reach, and product quality, ensuring sustainable growth in an increasingly competitive environment. Acknowledgments: This research was completed on schedule due to the motivation and support from multiple stakeholders. We thank the Directorate General of Higher Education, Research, and Technology, Ministry of Education, Culture, Research, and Technology of the Republic of Indonesia, for the funding that facilitated the publication of this article in a Scopus-indexed international journal. Copyright: © 2024 by the authors. 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/). References [1] Bachri, A. S., & Setiani, A. (2017). The Influence of Creativity and Learning Innovation on Entrepreneurial Mentality and its Implications for Learning Outcomes. Dinamika Pendidikan, 12(2), 148-158. [2] Bacq, Sophie, and Ruth V. Aguilera. (2022). Stakeholder governance for responsible innovation: A theory of value creation, appropriation, and distribution. Journal of management studies 59.1: 29-60. (a). [3] Barkhatov, V., Pletnev, D., & Campa, A. (2016). Key success factors and barriers for small businesses: Comparative analysis. Procedia-Social and Behavioral Sciences, 221, 29-38. [4] Benjamin Grab, Marieta Olaru, Roxana Maria Gavril. (2019). The Impact Of Digital Transformation On Strategic Business Management.ecoforum. Issue XXX. [5] Bouncken, R. B., & Kraus, S. (2022). Entrepreneurial ecosystems in an interconnected world: emergence, governance and digitalization. Review of Managerial Science, 16(1), 1-14. https://creativecommons.org/licenses/by/4.0/ 8292 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate [6] Chandola, V. (2016). Digital Transformation and Sustainability. Harvard University, Extension Studies in candidacy for the degree of Master of Liberal Arts (ALM) in Sustainability. Cambridge, Massachusetts:https://www.researchgate.net/publication/292983072. [7] Christens, B.D. (2012). Toward relational empowerment. Am. J. Community Psychol., 50, 114–128. [CrossRef] [PubMed] [8] Coda, Roberto, Patrícia Viveiros de Castro Krakauer, and Davi de França Berne. (2018). Are small business owners entrepreneurs? Exploring small business manager behavioral profiles in the São Paulo Metropolitan region. RAUSP Management Journal 53.2 : 152-163. [9] D. J. Teece. (2016). The Palgrave Encyclopedia Of Strategic Management. Business Ecosystem. London: Palgrave Macmillan. [10] Damayanti, F. N., Dewi Anggadini, S., & Aldila, A. (2023). Affecting Factors Success of Accounting Information System (AIS). Journal of Engineering Science and Technology, 18(5). [11] Dentoni, D., Pinkse, J., & Lubberink, R. (2021). Linking sustainable business models to socio-ecological resilience through cross-sector partnerships: A complex adaptive systems view. Business & Society, 60(5), 1216-1252. [12] Dewi Anggadini, S., A Wahab, D., Sulistiyo Soegoto, D., Yunanto, R., & Rosyad, A. (2023). Designing An MSMES Integrated Information System Model Through Zakat Management. Journal of Engineering Science and Technology, 18(2). [13] Dewi Anggadini, S., Luckyardi, S., & Lnu, S. (2023). Development of Micro Small-Medium Business in Asian Countries (Indonesia, Malaysia, Philippines, and Thailand): A comparison in accounting behavior. Journal of Eastern European and Central Asian Research, 10(3). [14] E. Anggraeni, E. Den Harthigh and M. Zegveld, (2007). Business Ecosystem As A Perspective For Studying The Relations Between Firms And Their Business Networks. Delft, [15] El Hilali, W., El Manouar, A., & Idrissi, M. A. (2019). Reaching sustainability during a digital transformation: a PLS approach. International Journal of Innovation Science, 12(1), 52-79. [16] Fellnhofer, K. (2017). Drivers of innovation success in sustainable businesses. Journal of Cleaner Production, 167, 1534-1545 [17] Ferdinand, A. (2000). Structural equation modelling dalam penelitian manajemen. Badan Penerbit Universitas Diponegoro. Semarang. [18] Garousi Mokhtarzadedeh, N., Jafarpanah, I., & Zamani Babgohari, A. (2022). Knowledge management capability, entrepreneurial creativity, entrepreneurial intensity and firm performance: the mediating role of ambidexterity. British Food Journal, 124(7), 2179-2208. [19] Gartner. (2017). Gartner, October 02,2017 The Gartner 2018 CIO Agenda Industry Insights l Gartner, Inc. Gartner, Inc [20] Ghozali, Imam. (2008). Structural Equation Modelling, Edisi II, Universitas Diponegoro, Semarang. [21] Grab, B., Bumbac, R., Gavril, R., Ilie, C., (2018). The winner takes it all - business model innovation in the tourism industry, BASIQ Conference in Heidelberg 2018, 4th BASIQ International Conference on New Trends in Sustainable Business and Consumption Proceedings, ISSN: 2457-483X, 11 -13 June 2018 [22] Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate Data Analysis: A Global Perspective. In Multivariate Data Analysis: A Global Perspective (Vol. 7). [23] Hardilawati, W. L., Sandri, S. H., & Binangkit, I. D. (2019, December). The Role of Innovation and E-Commerce in Small Business. In International Conference of CELSciTech 2019-Social Sciences and Humanities track (ICCELST- SS 2019) (pp. 18-22). Atlantis Press. [24] Harel, R., Schwartz, D., & Kaufmann, D. (2021). The relationship between innovation promotion processes and small business success: the role of managers’ dominance. Review of Managerial Science, 15, 1937-1960. [25] Harvie, C., Narjoko, D., & Oum, S. (2013). Small and Medium Enterprises access to finance: evidence from selected Asian economies. ERIA Discussion Paper Series, 23 [26] Herrera, M. E. B. (2016). Innovation for impact: Business innovation for inclusive growth. Journal of Business Research, 69(5), 1725-1730. [27] Hitpass, Bernhard, and Hernán Astudillo. (2019). Industry 4.0 challenges for business process management and electronic-commerce. Journal of theoretical and applied electronic commerce research 14.1 : I-III. (a). [28] Höllen, M., Lengfeld, C., & Konrad, E. D. (2020). Business Success for Creative and Cultural Entrepreneurs: Influences of Individual-and Firm-Related Factors on Revenue and Satisfaction. International Journal of Arts Management, 22(2). [29] Husin, MM, & Haron, R. (2020). Micro, small and medium enterprises' competitiveness and micro-tak?ful adoption. ISRA International Journal of Islamic Finance. DOI: https://doi.org/10.1108/IJIF-03-2019-0038 [30] Ilmafa'ati, R. (2021). The influence of entrepreneurship, creativity and business location on business success. Innovation Research Journal, 2(1), 51-64. [31] Isahak, M., Loh, MY, Susilowati, IH, Kaewboonchoo, O., Harncharoen, K., Mohd Amin, N., & Ratanasiripong, P. (2017). The association of workplace exposures on quality of life in small and medium enterprise workers: a cross- sectional study in four ASEAN countries. Asia Pacific Journal of Public Health, 29 (4), 315- 327. https://doi.org/10.1177/1010539517699060 DOI: https://doi.org/10.1177/1010539517699060 [32] J. F. Moore, (1993). Predators And Prey. A New Ecology OfCompetition in Harvard Business Review, pp. 75 – 86, https://doi.org/10.1108/IJIF-03-2019-0038 https://doi.org/10.1177/1010539517699060 https://doi.org/10.1177/1010539517699060 8293 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8281-8293, 2024 DOI: 10.55214/25768484.v8i6.3791 © 2024 by the authors; licensee Learning Gate [33] Jafari-Sadeghi, V., Garcia-Perez, A., Candelo, E., & Couturier, J. (2021). Exploring the impact of digital transformation on technology entrepreneurship and technological market expansion: The role of technology readiness, exploration and exploitation. Journal of Business Research, 124, 100-111. [34] Manser Payne, E. H., Dahl, A. J., & Peltier, J. (2021). Digital servitization value co-creation framework for AI services: a research agenda for digital transformation in financial service ecosystems. Journal of Research in Interactive Marketing, 15(2), 200-222. [35] Marhraoui, M. A., & El Manouar, A. (2018). IT Innovation and Firm‟s Sustainable Performance: The Intermediary Role of Organizational Agility – An Empirical Study. I.J. Information Engineering and Electronic Business, 3, 1-7 [36] Mentsiev, A. U., Engel, M. V., Tsamaev, A. M., Abubakarov, M. V., & Yushaeva, R. S.-E. (2020). The Concept of Digitalization and Its Impact on the Modern Economy. International Scientific Conference "Far East Con" (ISCFEC 2020) (pp. 2960-2964). Atlantis Press SARL [37] Miceli, A., Hagen, B., Riccardi, M., Sotti, F., & Settembre-Blundo, D. (2021). Thriving, Not Just Surviving in Changing Times: How Sustainability, Agility and Digitalization Intertwine with Organizational Resilience. Sustainability, 13, 1-17. [38] Reis, J., Amorim, M., Melão, N., & Matos, P. (2018). Digital transformation: a literature review and guidelines for future research. Trends and Advances in Information Systems and Technologies: Volume 1 6, 411-421. [39] Sekaran, Uma & Bougie, (2020). Roger. Research Methods For Business : A Skill Building Approach (8th ed. (Asia Edition). Hoboken: Wiley. [40] Sharma, S. (1996) Applied Multivariate Techniques. John Wiley and Sons Inc., New York, 512 p. [41] Street, K., & Street, K. (2020). The Concept of Digitalization and Its Impact on the Modern Economy. 128(Iscfec), 2960–2964.