This study evaluates the opportunities and challenges influencing the transition toward the established Pharma 4.0 paradigm within an emerging economy context. Contrasting empirical findings with the general manufacturing literature, it prioritizes the strategic factors necessary to optimize operations in the highly regulated pharmaceutical sector. Following a systematic literature review, a mixed-method approach was adopted, comprising 22 in-depth interviews with senior industry experts in Brazil. To ensure analytical rigor, the study introduces the Expert Judgment Reliability Protocol to validate qualitative data. Prioritization was performed using a hybrid Multi-Criteria Decision-Making (MCDM) model, integrating Information Entropy Weight (IEW) and TOPSIS. Results indicate that the primary opportunities for Pharma 4.0 involve advanced product traceability (Ci = 0.696), strategic market perception of modernity (Ci = 0.692), and quality improvement (Ci = 0.664). Conversely, implementation is hindered by critical structural challenges: specialized labor shortages (Ci = 0.177), the need for new management skills (Ci = 0.175), and insufficient government support (Ci = 0.167). This research fills a critical gap by providing empirical evidence of a technological plateau in emerging markets, where institutional voids and human capital scarcity limit advanced technology adoption. By linking MCDM rankings to an actionable Integrative Operations Framework, the study provides operations managers and policymakers with specific guidelines to foster digital maturity, thereby advancing Operations Management (OM) theory and practice.
Manufacturing companies face mounting pressure to adopt sustainable practices, yet a substantial gap persists between academic guidance and practical implementation. This study examines the perspective of pioneering manufacturers classified as innovators and early adopters of sustainable manufacturing (SM). This article seeks to answer the central question of how pioneers in the field successfully adopt SM measures and what implications arise for the wider industry. Building on a literature review of drivers and barriers, semi-structured expert interviews were conducted with ten sustainability and operations experts from eight German SM pioneers. Results reveal distinct barriers: bureaucratic delays, infrastructure deficits, and limited price premiums despite customer demand. They also highlight pioneer-specific drivers, including anticipation of future regulatory requirements and know-how accumulation through early innovation, which extend the current literature. Applying the diffusion-of-innovation framework, these findings explain the persistent adoption gap through unclear relative advantage, insufficient organizational compatibility, high complexity, and inadequate communication of outcomes. The twin transition shows potential synergies, whereby digital monitoring increases process transparency and supports the targeted implementation of sustainability measures. Decision makers are therefore encouraged to take indirect benefits into consideration, adopt digital monitoring systems, establish dedicated sustainability units, and nurture a transformation-supportive culture, thereby securing long-term competitiveness.
This study examines how integrating total quality management (TQM) and sustainable supply chain management (SSCM) drives circular economy implementation (CEI) in manufacturing firms. Integrating the Malcolm Baldrige National Quality Award (MBNQA) framework and the natural resource-based view (NRBV), the study applies structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) on data from 340 manufacturing firms. Our findings indicated a positive association between TQM and CEI, with SSCM acting as a partial mediating mechanism. Importance–performance map analysis revealed that SSCM delivers higher operational performance, while TQM holds greater strategic importance. Moreover, fsQCA further identified multiple configurational pathways leading to CEI. Overall, the present study contributes to the literature by clarifying how internal quality management capabilities translate into sustainability outcomes through supply chain mechanisms, particularly in a developing-economy context. Importantly, these findings provide actionable insights for managers seeking to align quality and sustainability initiatives to advance circular economy transitions.
Building supply chain resilience has become a strategic imperative in recent years due to pandemics, globalization, geopolitical pressures, and growing risk exposure. This study explores the adoption of digital twin technology to strengthen supply chain resilience in the U.S. manufacturing sector during COVID-19 pandemic crisis. Drawing on a grounded theory approach and 21 expert interviews, we identify key factors driving digital twin adoption in supply chains. We define digital twin adoption stages to strengthen supply chain resilience and propose a theoretical framework based on dynamic capability theory. Digital twin adoption follows four stages: (1) establishing the business case, (2) piloting and defining models, (3) digitizing supply chain processes, and (4) developing predictive and prescriptive capabilities. Through these stages, digital twin adoption enables real-time sensing, facilitates dynamic scenario planning, and automates decision-making, allowing faster and more effective disruption responses. The findings reveal that digital twin integration reinforces critical resilience dimensions: agility, reconfiguration, robustness, and collaboration. This study advances the emerging body of knowledge on digital twin adoption for supply chain resilience through the lens of dynamic capability theory. We present a comprehensive framework detailing the adoption process, from its antecedents to outcomes and maturity levels. Given the scarcity of empirical studies and holistic frameworks linking digital twin technology to supply chain resilience, this research offers a novel approach for researchers and practitioners to develop more resilient supply chains.
Supply chain (SC) actors may respond quickly to disruption yet struggle to coordinate their actions when planning cycles, decision windows, and interpretations of urgency differ. This paper examines that problem by introducing Temporal Agility (TA), a meta-coordination capability concerned with aligning the timing of interdependent adaptive activities. Drawing primarily on the dynamic capabilities view, complemented by temporal cognition and process theory, we explain how differences in temporal interpretation shape organizational pacing and cross-firm coordination. We develop a three-level framework and a recursive process model of temporal orchestration to explain how individually responsive actors can achieve coordinated adaptation. TA extends existing supply chain agility (SCA) research by identifying the temporal conditions under which distributed adaptive responses reinforce or interfere with one another. The framework also provides a basis for managerial interventions that address differences in planning horizons, response windows, and decision rhythms during disruption.
