The impact of advanced technologies on healthcare supply chain performance in Sierra Leone: a structural equation modelling approach

The Covid-19 has wrought havoc on the supply chain across the world. During the global pandemic, supply chain managers were forced to rely on short-term solutions with little to no impact on their operations. This paper aims to assess the effect of collaboration, visibility, velocity, and flexibility on supply chain resilience. A total of 66 respondents constitutes the sample of the study, consisting of middle management employees across all depots nationwide. Eight research questions and eight hypotheses were generated and tested at 0.05 significance level using descriptive statistics and path analysis to quantify the relationships among multiple variables. Data were then analyzed through partial least squares - structural equation modeling. Results showed that collaboration, visibility, and flexibility have a significant impact on supply chain resilience. However, velocity did not have a significant impact on supply chain resilience. The research concludes that the supply chain capabilities play a crucial role in the supply chain resilience of the company and its supply chain partners. The key recommendations of the paper help enhance these capabilities to improve the resilience of its supply chain.

The COVID-19 pandemic has caused significant changes in almost all sectors, including disruptions in the global supply chain. Acceleration of supply chain recovery to create supply chain resilience and sustainability by implementing various strategies, including digitalization. Empirical evidence is still very limited in the literature, especially in studies involving supply chain actors from MSMES with different characteristics and locations. Therefore, this study aims to address this problem by analysis the role of digitalization in improving supply chain resilience and sustainability based on a case study of MSMES in Balikpapan City. Three hypotheses have been proposed to answer the research problem. This study uses the Structural Equation Modelling (SEM) approach with the help of IBM AMOS software version 22 for hypothesis testing. Questionnaires were distributed to 200 MSME actors with different characteristics in Balikpapan City. The results are: (1) the role of digitalization has a significant positive effect on supply chain resilience; (2) the role of digitalization has a positive effect on supply chain resilience; (3) supply chain resilience has a significant positive effect on supply chain sustainability. Despite the differences in characteristics of business models and business sectors, supply chain resilience and sustainability can be improved by using appropriate digital technology in each supply chain. The contributes of this study shows that there is a potential for good supply chain visibility that allows every actor along the supply chain to monitor, transfer, and improve the accuracy of decision making accurately and quickly, to handle any disruptions and improve supply chain sustainability.

The purpose of this paper is to investigate which of sustainability elements, in the context of triple bottom line (TBL), are used to build sustainable supply chain resilience. This paper presents a new body of knowledge and contribution to the literature by relating the triple bottom line (TBL) context to the building of sustainable supply chain resilience using structural equation modelling. The research were used to understand that individual sustainability factors matter and play a role in the context of supply chain resilience. A survey questionnaire was designed to collect this data from the research respondents. To statistical analysis was first Confirmatory Factor Analysis (CFA) conducted and used, then for the analysis and interpretation structural equation model. The findings indicate that individual sustainability factors matter and play a role in the context of supply chain resilience. A number of previous studies have developed broad catalogues of sustainability factors influencing supply chains, however, to date no convincing evidence has been presented as to which of the range of elements identified, and how they influence supply chain resilience building. Despite the large number of publications on sustainable supply chain and resilience building, there is still a gap and lack of proper consideration of TBL-related criteria as elements that can determine mechanisms for building supply chain resilience in the context of sustainable development. This paper operationalizes a using the structural research model to using a structural research model to investigate how and in which relationships the different elements of the triple bottom line influence the resilience of supply chains.

PurposeThis study aims to analyse whether the presence of supply chain complexity (SCC) influences firms to improve their supply chain (SC) resilience and SC robustness capability. This study also examines an important paradox: whether investing in both exploitation and exploration practices is conflicting or complementary to enabling SC resilience and robustness in the presence of SCC.Design/methodology/approachThe authors used a survey-based approach to collect 242 useful responses from SC professionals of Pakistani firms, an important emerging economy context. The data were analysed with covariance-based structural equation modelling to statistically validate the model.FindingsThe analysis reveals several key findings: the presence of SCC has a direct, positive influence on SC resilience and SC robustness; while exploitation practices only partially mediate the nexus between SCC and SC resilience, they fully mediate the relationship between SCC and SC robustness; while exploration practices partially mediate the nexus between SCC and SC resilience, they do not mediate the relationship between SCC and SC robustness and SCC has a significant influence on SC resilience and SC robustness sequentially through exploitation and exploration (i.e. one after the other).Practical implicationsThese findings help to reconcile the exploitation versus exploration paradox in cultivating SC resilience and SC robustness in the presence of SCC. The findings assist SC managers in determining how to deploy their limited resources most effectively to enhance SC resilience and SC robustness while facing SCC.Originality/valueThe authors devise and empirically validate a unique framework that demonstrates how the presence of SCC works as a stimulus to build SC resilience and SC robustness.

PurposeThis systematic literature review analyzes the academic literature to understand SC risk and resilience across different organizational sizes and industries. The academic literature has well discussed the causes of supply chain (SC) risk events, the impact of SC disruptions, and associated plans for SC resilience. However, the literature remains fragmented on the role of two fundamental elements in achieving SC resilience: the firm's size and the firm's industry as firms' contingent factors. Therefore, it is important to investigate and highlight SC resilience differences by size and industry type to establish more resilient firms.Design/methodology/approachBuilding upon the contingent resource-based view of the firm, the authors posit that organizational factors such as size and industry sector have important roles in developing organizational resilience capabilities. This systematic literature review and analysis is based on the structural and systematic analysis of high-ranked peer-reviewed journal papers from January 2000 to June 2021 collected through three global scientific databases (i.e. ProQuest, ScienceDirect, and Google Scholar) using relevant keywords.FindingsThis systematic literature review of 230 high-quality articles shows that SC risk events can be categorized into demand, supply, organizational, operational, environmental, and network/control risk events. This study suggests that the SC resilience plans developed by startups, small and mdium-sized enterprises (SMEs), and large organizations are not necessarily the same as those of large enterprises. While collaboration and networking and risk management are the most crucial resilience capabilities for all firms, applying lean and quality management principles and utilizing information technology are more crucial for SMEs. For large firms, knowledge management and contingency planning are more important.Originality/valueThis study provides a comprehensive review of the literature on SC resilience plans across different organizational sizes and industries, offering new insights into the nature and dynamics of startups', SMEs', and large enterprises' SC resilience in different industries. The study highlights the need for further investigation of SC risk and resilience for startups, SMEs, and different industries on a more detailed level using empirical data. This study’s findings have important implications for researchers and practitioners and guide the development of effective SC resilience strategies for different types of firms.

Building responsive and resilient supply chains: Lessons from the <scp>COVID</scp>‐19 disruption

The study explores the combined influence of AI technology, supply chain collaboration, and information sharing on supply chain resilience. An integrated study model was developed and tested via smartPLS using a purposive sample of 542 respondents across different industries, to understand how information sharing mediates the collective impact of AI technology and collaborative practices on supply chain resilience. The experimental results demonstrate that AI technology paves the way for timely information and insights generation, which develops collaborative relationships among supply chain partners, facilitates trust and transparency, and thereby, information sharing to exchange pertinent data and insights across the supply chain network. The data were collected by surveying 542 managers from various industries and analyzed using SmartPLS. Relationships among technology adoption, supply chain collaboration, information sharing, and supply chain resilience were investigated. Structural equation modeling (SEM) was employed to observe the direct and mediating effects of information sharing between technology adoption, supply chain collaboration, and supply chain resilience. This study implies that practical information-sharing activities are essential for achieving supply chain resilience amid unpredictability and disturbances in solid market environments. It presents how technology adoption and supply chain collaboration are crucial to supply chain resilience. Information sharing, however, is shown to be an essential mediator, as clear communication and knowledge exchange amongst supply chain partners are fundamentally important in achieving supply chain resilience. Organizations need to invest in AI-driven technologies and develop collaborative ties with their supply chains to be resilient. This paper constitutes a valuable study of the primary drivers of supply chain resilience. It offers implications that organizations can use to persist and grow in the current ambiguous business setting.

Enhancing global supply chain distribution resilience through digitalization: Insights from natural resource sector of China

Background Recent pandemics, epidemics and outbreaks continually underscore the critical importance of resilient supply chains in healthcare, particularly in clinical laboratories where timely access to supplies is essential for patient care. Supply chain disruptions, whether due to global crises or localized challenges, can significantly impact laboratory operations, leading to delayed diagnoses, compromised patient outcomes, and increased costs. It is estimated that 70%-80% of a patients’ EMR is clinical laboratory results. Despite this, supply chain resilience in clinical laboratories remains an under-addressed issue and remains a buzzword. Methods To evaluate the cost and importance of supply chain resilience in the clinical laboratory, we conducted a comprehensive review and interviews with 9 Healthcare Supply Chain experts analyzing the impact of supply chain disruptions on laboratory operations and patient care. Data was also collected from a diverse range of clinical laboratories, including hospitals, independent labs, and research institutions, spanning different geographic regions as well as a survey of 50 Laboratory experts with a 50% response rate. Key metrics assessed included: -Frequency and duration of supply chain disruptions. -Financial costs incurred due to disruptions, including expenses related to expedited shipping, alternative sourcing, and inventory management. -Impact on laboratory workflow, turnaround times, and patient care outcomes. -Strategies employed to mitigate supply chain risks and enhance resilience. Results Our review revealed findings regarding the cost and importance of supply chain resilience in the clinical laboratory: -Supply chain disruptions were frequent, with 85% of laboratories experiencing at least one significant disruption in the past year and 100% in experienced disruptions 2022. -The average duration of disruptions was 2-3 weeks, leading to substantial delays in test processing and patient care. -Financial costs associated with disruptions averaged $50,000 per laboratory per annum, including expenses for rush orders, and premium-priced alternatives. -Common strategies employed were increased inventory or safety stocks, multi-vendor sourcing, and supply chain mapping. Conclusions The findings of this study underscore the critical importance of supply chain resilience in the clinical laboratory. Supply chain disruptions are not just inconveniences; they pose significant risks to patient safety, operational efficiency, and financial sustainability. Investing in supply chain resilience is imperative for laboratories to fulfill their mission of delivering timely and accurate patient results. To continue to enhance supply chain resilience, laboratories must adopt a proactive approach, leveraging data-driven insights and collaborative partnerships. This includes diversifying supplier networks and fostering closer collaboration between laboratory and procurement teams.

PurposeThe aim of this paper is to investigate the role of the stakeholder's relationship with supply chain resilience (SCR) and organizational performance (OP) using the lens of stakeholder theory in the manufacturing and service industry. Investigating the supply chain community in Pakistan, this paper explores the relationship between SCR, OP and the stakeholder's relationship (including customers and suppliers).Design/methodology/approachA partial least square (PLS) – structural equation modeling (SEM) technique using SmartPLS 3.3.3 was used to test the hypotheses. Data were collected through a survey (questionnaire) completed by 202 supply chain representatives. All respondents were supply chain professionals working in different organizations in Pakistan.FindingsThe findings of the study revealed that supplier relationship (SR) and customer relationship (CR) have a positive and significant impact on SCR and a positive and significant relationship between SCR and OP. A positive and significant relationship between customer relationship and OP was also noted. The mediating role of SCR is also found positive and significant.Practical implicationsThe outcomes of the study will help managers to strengthen SCR through relationship management. The study is also helpful to increase OP through stakeholder management.Originality/valueThis study empirically tests an inclusive model with a PLS-SEM technique where SCR plays a mediating role in the mechanism, which is crucial since the supplier and customer (stakeholder) relationship has been never tested to gauge the OP by positioning SCR as a mediator while using the lens of stakeholder theory.

The aim of this research was to investigate factors that influence logistics firms’ supply chain agility and supply chain resilience. Therefore, an integrated research model based on strategic human resource management and artificial intelligence was developed to determine the agility and resilience of logistics firms. Empirical data were collected from 221 employees working in manufacturing firms in Saudi Arabia. For the data analysis, a structural equation modeling approach was used. The results indicated that joint leadership, employee skills, organizational culture, competitive intensity, human capital development, and artificial intelligence had substantial explained variance R2 of 80% for supply chain agility. Similarly, an importance performance analysis revealed that, within the integrated research model of supply chain agility, the factors of leadership, human capital development, and organizational flexibility had greater importance in determining supply chain resilience. Practically, this research shows that factors like leadership, employee skills, organizational culture, competitive intensity, human capital development, and artificial intelligence are positively associated with supply chain agility and, hence, require policymakers’ attention. The value of this research lies in its integration of artificial intelligence, organizational flexibility, and strategic human resource management to explore supply chain agility and its examination of the impact of these factors on supply chain resilience.

Purpose The rising global competition and uncertainty in business environment has led logistics firms to redesign supply chain strategies which boost disaster immunity. Therefore, the current study develops an integrated research framework that combines big data analytics capability, HR practices, resilience and resource reconfiguration to investigate logistic firm disaster immunity. In addition to that, the moderating effect of data-driven culture is tested between disaster immunity and supply chain performance. Design/methodology/approach The research design of this study is based on quantitative techniques and followed by positivist research paradigm. Data are collected through structured questionnaires. Overall, 219 managers have participated in this logistics research survey. Data are computed with structural equation modeling approach. Findings Statistical findings have revealed that collectively HR practices, innovation capability, proactive capability, reactive capability, resource configuration and supply chain resilience explained R2 71.5% variance in disaster immunity. Therefore, in the extended model, disaster immunity and data-driven culture have depicted R2 49.2% variance in manufacturing firm supply chain performance. Practical implications The integration of big data analytics capability factors with HR practices, supply chain resilience and resource configuration has enriched logistic literature in the disaster immunity setting. Practically, this study has concluded that factors such as data analytics capabilities, resource reconfiguration, supply chain resilience and HR practices need policymakers’ attention to boost disaster immunity and supply chain performance. Originality/value This research is original as it unveils three core factors of big data analytics capability, namely proactive, reactive and innovative capability, and examines firm disaster immunity. Similarly, research is unique as it combines capability factors with resilience, HR practices and resource reconfiguration and investigates logistic firm disaster immunity.

Supply chain resilience (SCRes) and performance have become increasingly important in the wake of the recent supply chain disruptions caused by subsequent pandemics and crisis. Besides, the context of digitalization, integration, and globalization of the supply chain has raised an increasing awareness of advanced information processing techniques such as Artificial Intelligence (AI) in building SCRes and improving supply chain performance (SCP). The present study investigates the direct and indirect effects of AI, SCRes, and SCP under a context of dynamism and uncertainty of the supply chain. In doing so, we have conceptualized the use of AI in the supply chain on the organizational information processing theory (OIPT). The developed framework was evaluated using a structural equation modeling (SEM) approach. Survey data was collected from 279 firms representing different sizes, operating in various sectors, and countries. Our findings suggest that while AI has a direct impact on SCP in the short-term, it is recommended to exploit its information processing capabilities to build SCRes for long-lasting SCP. This study is among the first to provide empirical evidence on maximizing the benefits of AI capabilities to generate sustained SCP. The study could be further extended using a longitudinal investigation to explore more facets of the phenomenon.

Building resilience or maintaining robustness: Insights from relational view and information processing perspective

With the acceleration of technological change and globalization, companies face increasing environmental uncertainty and complexity. The COVID-19 pandemic has severely damaged the global supply chain and aggravated the operational risks of supply chains. Industry and academia have conducted studies on the construction of resilient and integrated supply chains, and to date a bulk of empirical literature has already been accumulated. A notable feature of existing literature is the heterogeneity in the characterization of the relationship between supply chain resilience, supply chain integration, and supply chain performance. In this study meta-analysis and structural equation modeling (MASEM) methods are integrated to construct a theoretical framework of supply chain resilience, supply chain integration, and supply chain performance. 45 empirical studies (73 effect size data, 2092 samples) are selected from 10,623 papers published over the years 2013 to 2021 to explore the transmission mechanisms, the role of mediator variable, and boundary conditions of the relationship between supply chain resilience and supply chain performance. The results show that supply chain resilience can promote supply chain performance. Moreover, supply chain integration (supplier integration, internal integration, and customer integration) plays a partial mediating role for the impact of supply chain resilience on supply chain performance. Situations and measurement factors such as industry type, national culture (power distance), sampling area, and logistics performance have a certain impact on the relationship, and the usage of different indicators may lead to marked differences in conclusions regarding the relationship. By extracting the conclusions of existing empirical studies, this study proposes new insights into the mechanism of action of supply chain resilience, supply chain integration, and supply chain performance and provides specific suggestions for future supply chain management.