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The research provides new strategies for enhancing resilience in pharmaceutical manufacturing by addressing the dynamic nature of digital technology within the challenging framework of a VUCA (volatility, uncertainty, complexity and ambiguity) world, focusing on the concept of digital twins (DTs). This paper aims to emphasize the pivotal role of resilience in navigating disruptions and propose future research directions to contribute to the industry’s effective adaptation to uncertainties and dynamic challenges.

This research uses a qualitative approach, drawing insights from an extensive literature review on pharmaceutical manufacturing resilience and the integration of digital technologies. Methodologically, it synthesizes information from scholarly articles, empirical studies and industry reports to construct a comprehensive understanding. This design facilitates a thorough examination of the subject, providing valuable insights for practitioners, researchers and policymakers in the pharmaceutical industry.

This paper illustrates the practical application of DTs in vaccine production, emphasizing their critical role in ensuring quality, safety and adaptability. It adopts the “seizing, sensing and transforming” framework, showcasing the strategic integration of Industry 4.0 technologies to address dynamic challenges. Key insights include the significance of human elements alongside technological advancements, the need for real-time monitoring using Internet of Things (IoT) and artificial intelligence (AI) and the transformative potential of sustainability practices, diversified supply chains and collaborative ecosystems.

This paper highlights the integration of human and digital elements, emphasizing IoT, AI and DTs for resilience. It underscores sustainable practices, supply chain diversification and collaboration as key strategies for addressing pharmaceutical industry challenges.

This paper offers practical insights for pharmaceutical manufacturing, emphasizing the need for robust cybersecurity measures, strategic investments in digital technologies and proactive regulatory compliance. Managers are encouraged to allocate budgets for digital integration, prioritize change management for technology adoption and invest in a skilled workforce. The adoption and management of DTs are highlighted to enhance resilience. Overall, the paper guides pharmaceutical organizations in navigating the complexities of the VUCA environment, ensuring the quality and safety of products through a multifaceted approach that combines advanced technologies with sustainability practices, supply chain diversification and collaborative ecosystems.

The research addresses VUCA challenges, including volatility, uncertainty, complexity and ambiguity in pharmaceutical manufacturing. It emphasizes societal benefits such as uninterrupted drug supply, environmental responsibility through sustainable practices and enhanced collaboration among stakeholders. By leveraging digital technologies and resilience strategies, the study highlights the pharmaceutical sector’s pivotal role in managing health crises and ensuring patient safety.

This paper offers substantial originality and value by presenting a comprehensive framework for bolstering resilience in pharmaceutical manufacturing within the VUCA environment. The integration of advanced digital technologies, notably DTs, is explored in-depth, providing novel insights into their practical application. The “seizing, sensing and transforming” concept contributes a nuanced approach, considering both technological and human dimensions. This paper addresses the gaps in current literature by combining diverse elements such as Industry 4.0, risk assessment, sustainability practices and collaborative ecosystems. Its practical implications for managers and detailed exploration of research directions add tangible value, guiding future endeavors in enhancing pharmaceutical industry resilience.

The purpose of this study is to comprehensively explore the impact of digitalization on healthcare supply chains (HcSCs). It seeks to understand how digital technologies enhance efficiency, transparency and responsiveness within these complex logistical systems. The study aims to provide a holistic view of the transformative potential of digitalization in the healthcare sector, with a particular focus on improving patient care and streamlining operational processes.

This research employs a systematic review methodology, carefully curating a selection of 45 relevant articles from 66 articles rigorously screened using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to provide a holistic view. It follows established systematic review protocols, incorporating a meticulous search strategy and precise keyword selection. The chosen research design enables a comprehensive examination of the existing body of knowledge concerning digital platforms, real-time tracking technologies, transparency and responsiveness in the context of HcSCs.

The findings of this study emphasize the pivotal role of digital technologies in reshaping HcSCs. Digital platforms, real-time tracking systems and technological integrations substantially enhance efficiency, transparency and responsiveness. Data-driven decision-making, improved communication and agile responses to dynamic demands are key aspects. These findings underscore the transformative impact of digitalization on healthcare logistics, emphasizing the potential for streamlined operations, enhanced patient care and more efficient resource allocation.

Despite the systematic methodology, this study is subject to certain limitations. It relies on existing literature, which may not cover the most recent developments in the rapidly evolving field of digital HcSCs. Furthermore, the study may be influenced by publication bias. The implications suggest the need for continued research to explore emerging digital technologies and their effects on healthcare logistics, ensuring that supply chains remain agile and responsive.

The practical implications of this research are significant for HcSC managers with insights into digital technologies to enhance transparency and collaboration and improve resource visibility. The integration of data analytics can lead to more effective inventory management and demand forecasting. Blockchain (BC) technology can ensure transparent and secure transactions, fostering trust among stakeholders. For practitioners, this research offers actionable guidance for navigating the digital age, promoting operational efficiency and ensuring a consistent supply of essential medical products. Researchers can use these insights as a foundation for further exploration into the potential of digitalization in HcSCs.

The social implications of digitalization in HcSCs are far-reaching. They encompass improved patient care, as digital technologies enhance the efficiency, transparency and responsiveness of supply chains. This translates to better access to critical medical supplies, potentially reducing healthcare disparities and benefiting underserved populations. Enhanced patient safety is a significant social outcome, as transparent and secure transactions enabled by technologies like BC mitigate the risks associated with counterfeit medications. Furthermore, digitalization builds trust among stakeholders, promotes accountability and fosters resilient healthcare systems, which are capable of responding effectively to crises. It also has the potential to make healthcare more affordable, contributing to increased healthcare access and transparency in decision-making.

The originality and value of this study lie in its comprehensive synthesis of diverse findings related to digitalization in HcSCs. While prior studies have examined isolated facets of digital technology adoption, this research provides a comprehensive overview. It contributes to a deeper understanding of the transformative potential of digitalization within the healthcare sector, offering practical approaches to enhance patient care and streamline operations.

This paper aims to study the various developments taking place in the field of gas sensors made from polyaniline (PANI) nanocomposites, which leads to the development of high-performance electrical and gas sensing materials operating at room temperature.

PANI/ferrite nanocomposites exhibit good electrical properties with lower dielectric losses. There are numerous reports on PANI and ferrite nanomaterial-based gas sensors which have good sensing response, feasible to operate at room temperature, requires less power and cost-effective.

This paper provides an overview of electrical and gas sensing properties of PANI/ferrite nanocomposites having improved selectivity, long-term stability and other sensing performance of sensors at room temperature.

The main purpose of this review paper is to focus on PANI/ferrite nanocomposite-based gas sensors operating at room temperature.

To predict the influence of inherent microfabrication and operating environmental influences on the performance of capacitive type sensors and actuators so that one can tune the performance and carry out more realistic designs.

When the sensors and actuators are micromachined or microfabricated, they are subjected to special problems that are characteristic to microdimensions. The important concerns are the influence of microfabrication process on the material properties and influence of operating environment on the system behavior. Hence, this paper proposed a way of quantifying and modeling the influence of inherent limitations of microfabrication and operating environment for the better design of micromachined capacitive type sensors and actuators. The methodology applies the modeling the variation of the elastic property of the system due to above influences through elastic stiffening and weakening concepts. The approach includes the application of boundary conditioning concept through Rayleigh energy method.

The microfabrication process and electrostatic field can alter significantly both static and dynamic behavior of the device. The performance of the device could also be tuned through these influences.

As the displacement of the sensors is expected to be small, linear approach is applied. The sensitivity, output range, operating limits and natural frequencies of the sensor can be easily controlled by varying the process and operating environmental influences.

Improved and more realistic design of microfabricated capacitive type sensors and actuators for many applications, such as, pressure sensors, microphones, microspeakers, etc.

A simple and easy way of modeling and quantifying the influence of process and operating environment was proposed for the betterment of design. The proposed design method can be applied for any micromachined or microfabricated capacitive type sensors and actuators so that varying sensitivities, output ranges and natural frequencies could be obtained. Over the last few years, newly emerging micro‐electro‐mechanical‐systems (MEMS) technology and micro‐fabrication techniques have gained popularity and importance in the miniaturization of a variety of sensors and actuators. The proposed technique is very useful in making the field of MEMS more matured as it attempts to model the problems that are unique to MEMS environment.

The purpose of this study is to explore the latest approaches in integrating artificial intelligence and analytics (AIA) in energy smart grid projects. Empirical results are synthesized to highlight their relevance from a technology and project management standpoint, identifying several lessons learned that can be used for planning highly integrated and automated smart grid projects.

A systematic literature review leads to selecting 108 research articles dealing with smart grids and AIA applications. Keywords are based on the following research questions: What is the growth trend in Smart Grid projects using intelligent systems and data analytics? What business value is offered when AI-based methods are applied? How do applications of intelligent systems combine with data analytics? What lessons can be learned for Smart Grid and AIA projects?

The 108 selected articles are classified according to the following four research issues in smart grids project management: AIA integrated applications; AI-focused technologies; analytics-focused technologies; architecture and design methods. A broad set of smart grid functionality is reviewed, seeking to find commonality among several applications, including as follows: dynamic energy management; automation of extract, transform and load for Supervisory Control And Data Acquisition (SCADA) systems data; multi-level representations of data; the relationship between the standard three-phase transforms and modern data analytics; real-time or short-time voltage stability assessment; smart city architecture; home energy management system; building energy consumption; automated fault and disturbance analysis; and power quality control.

Given the diversity of issues reviewed, a more capability-focused research agenda is needed to further synthesize empirical findings for AI-based smart grids. Research may converge toward more focus on business rules systems, that may best support smart grid design, proof development, governance and effectiveness. These AIA technologies must be further integrated with smart grid project management methodologies and enable a greater diversity of renewable and non-renewable production sources.

A new cutting tool is always well-defined and sharp at the onset of the metal cutting process and gradually losses these properties as the machining process advances. Similarly, at the beginning of the machining process, amplitude of tool vibrations is considerably low and it increases gradually and peaks at the end of the service period of the cutting tool while machining. It is significant to provide a corresponding real-time varying damping to control this chatter, which directly influences accuracy and quality of productivity. This paper aims to review the literature related to the application of smart fluid to control vibration in metal cutting and also focused on the challenges involved in the implementation of active control system during machining process.

Smart dampers, which are used as semi-active and active dampers in metal cutting, were reviewed and the research studies carried out in the field of the magnetorheological (MR) damper were concentrated. In smart materials, MR fluids possess some disadvantages because of their sedimentation of iron particles, leakage and slow response time. To overcome these drawbacks, new MR materials such as MR foam, MR elastomers, MR gels and MR plastomers have been recommended and suggested. This review intents to throw light into available literature which exclusively deals with controlling chatter in metal cutting with the help of MR damping methods.

Using an MR damper popularly known for its semi-active damping characteristics is very adaptable and flexible in controlling chatter by providing damping to real-time amplitudes of tool vibration. In the past, many researchers have attempted to implement MR damper in metal cutting to control vibration and were successful. Various methods with the help of MR fluid are illustrated.

A new cutting tool is always well-defined and sharp at the onset of metal cutting process and gradually losses these properties as the machining process advances. Similarly, at the beginning of the machining process, amplitude of tool vibrations is considerably low and it increases gradually and peaks at the end of service period of cutting tool while machining. Application of MR damper along with the working methodology in metal cutting is presented, challenges met are analyzed and a scope for development is reviewed.

This study provides corresponding real-time varying damping to control tool vibration which directly influences accuracy and quality of productivity. Using an MR damper popularly known for its semi-active damping characteristics is very adaptable and flexible in controlling chatter by providing damping to real-time amplitudes of tool vibration.

This study attempts to implement smart damper in metal cutting to control vibrations.

It is significant to provide corresponding real-time varying damping to control tool vibration which directly influences accuracy and quality of productivity.

The purpose of this paper is to determine the level of technical efficiency of the main oil countries worldwide during the period 2010–2017.

The use of the network data envelopment analysis model (NDM) is proposed, in which the technical efficiency of each node is calculated. For the development of the model, three main nodes were identified: exploration and production, industrial transformation and commercialization. Finally, NDM for the international oil industry will be structured, and efficiency will be calculated at the global level and at each node.

The analysis of the results of the application of the NDM raised that the most efficient node was exploration and production, whereas the efficient oil countries were the USA, France, the United Arab Emirates and Angola.

The limitation presented in this investigation was the availability of data.

The practical implications of this type of study are that, through the results obtained, proposals can be made in the oil industry to improve each of the nodes or areas in which efficiency was not reached, as well as make better use of the resources available to this industry in each country.

The social implications of this study are the basis for developing energy policies in the oil industry to help improve the quality of life of users.

The value and originality of this study is based on the joint implementation of the NDM methodology.

The rapid growth of e-commerce has encouraged online retailers to adapt to the purchase behaviour of Generation Y consumers. For this purchase, the purpose of this paper is to investigate Generation Y online consumer repurchase intention in Thai context based on Stimuli-Organism-Response (SOR) model.

Data were used to test the hypotheses that Generation Y consumer online response is influenced by online environment cues and organism. In total, 401 questionnaires were collected in Bangkok through judgemental sampling and convenient sampling. SPSS 24 was used to analyse Generation Y consumers’ demographic information and reliability test. Amos 24 was utilized to examine measurement model and structural equation model.

The findings finally revealed that website security presents the strongest influence on Generation Y consumers trust. Also, online promotion possesses the weakest association with Generation Y consumers trust. More importantly, Generation Y consumer online repurchase intention is positively influenced by the degree of trust they have towards websites. The implications of the findings for marketers are discussed.

The empirical data are limited to generate findings from a limited number of Generation Y consumers in Bangkok only. Also, the study limits itself to explore only inter-relationship in the scope of SOR.

It is suggested that in order to draw attention from and retain Generation Y consumers, online retailers should aim at strengthening trust-building in the online buyer–seller context as well as a dynamic promotional campaign. Moreover, a constellation of relevant marketing strategies is recommended.

Since there is a lack of implementation of SOR model based on the Thai context, this paper fills the gap by illustrating how SOR works in Thailand with updating findings.

The purpose of this paper is to develop a framework for benchmarking the service quality of amusement parks.

A hybrid approach, which is a combination of AHP (analytic hierarchy process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), is applied for service quality benchmarking.

Amusement parks are centers of attraction at various tourist destinations across the world. Their service quality is constituted by the attainment of certain quality attributes that varies with different parks. For sustaining in the industry, the managers of the parks need to have a good overview of the practices followed by them and their competitors that necessitate benchmarking of the service quality.

The developed framework using the hybrid methodology of AHP and TOPSIS can be applied for comparing different amusement parks based on quality attributes, which will help the organizers in improving their service quality.

The paper identifies various service quality attributes of amusement parks and an evaluation scheme for those attributes had been developed. Based on these, a framework had been developed for benchmarking of service quality of different amusement parks.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.