55 Chapter IV Result and Analysis This chapter entails results as well as a discussion based on the research methodology conveyed in the previous chapters. It attempts to evaluate in a thorough and detailed manner the outcome of analytic findings based primarily on identification, assessment, and prioritization under risk conditions in Indonesia Pharmaceutical Supply Chains (PSCs). This chapter, using an integrated Delphi- AHP-System Modeling framework, analyses the calculated weights of risk factors and their relationships, thus providing insights into the vulnerabilities and complexities of Indonesia's PSCs. Through an in-depth analysis of expert interviews, literature reviews, and causal loop diagrams, this chapter will address the risk picture impacting the pharmaceutical sector. Indeed, as discussed in this section, it further addresses the main supply chain interdependencies and provides the most essential intervention areas to improve resilience and sustainability in the future. The later sections then provide analyses of these discussions and their contributions towards a wider discourse to minimize supply chain risks and enhance stability in the Indonesian pharmaceutical industry. IV.1 Introduction Risk identification is crucial for mitigating potential disruptions in Pharmaceutical Supply Chains (PSCs) and supporting sustainability practices within the industry. With systematic risk identification, organizations can proactively strategize on how to address their vulnerabilities, ensuring continuity in the supply of essential medicines. Effective identification of risks allows companies to foresee disruptions and take precautionary actions before the issue escalates, according to Mishra et al. (2019). In an industry where quality and timely delivery of products are indispensable, procurement, production, and distribution-related risk identification would help minimize waste and shortages and ensure compliance with regulations in the pharmaceutical sector (Sharma et al., 2023). 56 Risk identification paves an avenue toward advanced changing technology that is supposed to improve visibility in the supply chain as well as enhance data analytics. On the other hand, complete risk identification would yield a wealth of information that could not have been complemented with advanced technology. Additionally, a comprehensive risk map allows prioritization of the most critical risk factors, such as supplier reliability, geopolitical issues, and regulatory change that are not possible to cover completely through technological tools (Giannakis & Papadopoulos, 2016). Identification and prioritization of risks enable firms to allocate resources optimally to high-impact areas along the supply chain (Zuo et al., 2022; Price & MacNicoll, 2015). Therefore, this strategy will ensure mitigation measures are applied to possible threats in order to decrease importance and thus strengthen resilience. Furthermore, understanding the interrelations between identified risks is equally critical. Interdependencies among risks, such as the interplay between regulatory hurdles and supplier reliability, can amplify their combined impact if not addressed holistically. Analyzing these interconnections provides a more comprehensive risk map, aiding decision-makers in evaluating cascading effects and prioritizing interventions (Diaz-Gallo et al., 2021). This system-thinking approach strengthens the decision-making process, enabling PSCs to adopt more sustainable, adaptive, and resilient strategies in the face of dynamic challenges. The findings of this research reveal that the dependency on imported raw material medicine is a significant challenge impacting the resilience and sustainability of Indonesia's pharmaceutical supply chain. This dependency not only exposes the sector to global disruptions but also limits the development of domestic capabilities. Delving into the analysis in each sub-chapter will provide a robust and comprehensive examination of the contributing factors, including supply chain risks, policy gaps, and infrastructure challenges. Furthermore, the sub-chapters will discuss potential strategies to mitigate this dependency, focusing on enhancing local production, improving resource allocation, and fostering innovation. This detailed analysis is expected to offer actionable insights, leading to recommendations for 57 strengthening policy implementation and reducing import reliance to support a more self-reliant pharmaceutical industry in Indonesia. IV.2 Result of the Delphi Method Following the execution of an extensive and thorough review of the existing body of literature, an initial framework for research was meticulously formulated, which is visually represented and elaborated upon in Chapter 2 of the study (Figure II.2). The intricate composition of various factors and sub-factors predominantly corresponds with findings and analyses presented in previous scholarly investigations about PSCs, thereby reinforcing the relevance and applicability of this research framework within the broader academic discourse. This constructed framework was then adeptly employed to enhance the process of identifying risk factors, utilizing the Delphi method aimed at addressing the critical risk factors that are inherently associated with the reliance on imported raw materials within the context of Indonesia's pharmaceutical industry. The Delphi process, known for its iterative nature, was structured to include two cycles of interviews to ensure comprehensive and reliable insights. This engaged highly qualified subjects who were specialists in the pharmaceutical industry for more than 15 years. The background of the experts is shown in Table IV.1. Table IV.1. Experts’ background Group Institution Position Experience Finished Product Manufacture Pharmaceutical Industry AAA General Manager >25 years Trader & Distributor Trader BBB Independent Comissaris >40 years Government Ministry of Health Director >30 years Finished Product Manufacture Pharmaceutical Industry CCC Vice President >30 years Trader & Distributor Distributor DDD Chief Executive Officer >30 years Raw Material Manufacture Raw Material Industry EEE President Director >30 years Raw Material Manufacture Raw Material Industry FFF Sales Manager >20 years Finished Product Manufacture Pharmaceutical Industry GGG Department Head >20 years 58 During the first phase, these experts provided an evaluation of the factors and sub- factors listed. They were only required to express their agreement or disagreement with the relevance of these factors and sub-factors to dependence on imported raw materials in Indonesia. The findings from the first phase showed that some of the sub-factors were not considered relevant by the experts. Furthermore, the experts suggested additional recommendations for other sub-factors that were more relevant to the import dependency of raw material medicine in Indonesia. To guarantee that the Delphi process reached a consensus among the experts, modifications were implemented to the compilation of factors and sub-factors in light of the feedback from Cycle 1. Subsequently, a second round of interviews was initiated. In Cycle 2, the experts were prompted to reassess the amended compilation and evaluate the significance level of each sub-factor in a quantifying manner. The score of assessment is based on five scales from one (very not important) to five (very important). This quantification procedure was pivotal in securing a mutual accord among the experts, as it confirmed that no additional alterations were required for the compilation of factors and sub-factors. The iterative characteristics of the Delphi methodology, coupled with its systematic framework, facilitated the enhancement and confirmation of the results. According to Cheng (2001), the study adopts a modified Delphi method to analyze the questionnaire results using specific selection criteria. A mean value threshold of 3.5 is applied, as this represents the midpoint between a moderate and important scale, with scores above 3.5 indicating importance. Additionally, a standard deviation threshold of 1 is utilized to assess the level of consensus based on the assumption of a normal distribution of the questionnaire data. The criteria are defined as follows: • If the mean value exceeds 3.5 and the standard deviation is below 1, the criterion is deemed "important," indicating that consensus has been reached among the experts. Such criteria are included for further discussion in the second-stage questionnaire or the AHP (Analytical Hierarchy Process) phase. 59 • Conversely, if the mean value falls below 3.5 or if the standard deviation exceeds 1, the criterion is considered "not important," suggesting a lack of agreement among the experts. These criteria are excluded from the second- stage questionnaire or the AHP process. The results of this modified Delphi method serve to refine the list of criteria, ensuring that only those deemed important and agreed upon are carried forward for further analysis.