Background: In order to optimize positioning and associated drug price for both payer and investor, it is for a company essential to forecast the potential market access attractiveness for the new drug for different indications at the early onset of the clinical development program. This analysis must include the constraints from the perspective of the payer, but also the biotech companies, who require a minimum drug price to satisfy their investors. This paper aims to provide an Integrated Valuation Model for payer and investor, bridging concepts from health economics and economic valuation reflecting the perspectives of the payer and the investor for a drug in early clinical development phase. The concept is illustrated for a new hypothetical drug (Product X) in advanced breast cancer in 1-line, 2-line, and 3-line position. Methods: The Integrated Valuation Model includes the outcomes of the budget impact model, pricing matrix model, and cost-effectiveness model reflecting the payer's perspective. These models are interacted and linked with a discounted cash flow model in order to reflect also the economic value from the investor's perspective. Results: The maximum price in 1-line position is €269.7 for the payer and the minimum price is €14.7 for the investor, which are unit prices per administration corresponding with treatment regimens for the comparative treatments. In 2-line position, the maximum price is €274.1 for the payer and the minimum price for the investor increases to €184.5 for the investor because of the smaller market size in 2-line position, which leads to a smaller pricing corridor to satisfy both payer and investor. Consequently, Product X has market access attractiveness for both payer and investor in 1-line and 2-line position. However, the minimum price €942.7 in 3-line position for the investor is higher than the maximum price €283.3 for the payer, which means there is no market potential. Conclusion: The practical strategic application of the Integrated Valuation Model is optimization of positioning and price of Product X. Hence, it can be a transparent tool in early-stage development of a compound based on upfront assessment of market access attractiveness for the payer and the investor.
Production scheduling has a long history of research but still presents open challenges, when considering production systems with uncertainty. The digitization, and in particular Digital Twins, may play a role in progressing the research field. The paper proposes a framework to exploit the Digital Twin synchronization with the field to include health assessment models into the simulation-based optimization of the production system scheduling. The health assessment is based on a modelling of failure modes and monitoring signals to connect the physical production resources to health and operating states in order to have a more accurate prediction of the makespan with respect to the actual makespan of the production system. The scheduling framework is validated through a laboratory application in the Industry 4.0 Lab at the School of Management of Politecnico di Milano.
Servant leadership is a form of moral-based leadership where leaders tend to prioritize the fulfillment of the needs of followers, namely employees, customers and other stakeholders, rather than satisfying their personal needs. Although the concept is not new among both academics and practitioners, it has received growing consideration in the last decade, due to the fact that it can positively affect a series of individual and organizational outcomes, such as job satisfaction and organizational commitment. In particular, the latest trend in literature has focused on the identification of the antecedents, mediating and moderating mechanisms at the basis of this relationship, as well as on the development of a common scale to measure the construct across diverse economic and cultural contexts. The purpose of this paper is to depict the evolution of the scientific literature that has developed on the concept, to identify the main criticalities and provide avenues for future research. A dynamic methodology called “Systematic Literature Network Analysis” has been applied, combining the Systematic Literature Review approach with the analysis of bibliographic networks.
Discontinuation of antimicrobial stewardship programs (ASPs) and increased antibiotic use were described during SARS-CoV-2 pandemic. In order to measure COVID-19 impact on ASPs in a setting of high multidrug resistance organisms (MDRO) prevalence, a qualitative survey was designed. In July 2021, eighteen ID Units were asked to answer a questionnaire about their hospital characteristics, ASPs implementation status before the pandemic and impact of SARS-CoV-2 pandemic on ASPs after the 1st and 2nd pandemic waves in Italy. Nine ID centres (50%) reported a reduction of ASPs and in 7 cases (38.9%) these were suspended. After the early pandemic waves, the proportion of centres that restarted their ASPs was higher among the ID centres where antimicrobial stewardship was formally identified as a priority objective (9/11, 82%, vs 2/7, 28%). SARS-CoV-2 pandemic had a severe impact in ASPs in a region highly affected by COVID-19 and antimicrobial resistance but weaknesses related to the pre-existent ASPs might have played a role.
Abstract—In this paper we propose a fuzzy logic-based approach to analyze NHS public administrative data related to pre- and post-pandemic claims filed by patients, analyzing the legal and ethical issues connected to the use of Artificial Intelligence systems, including our own, to take critical decisions having a significant impact on patients, such as employing computational intelligence to justify the management choices related to ICU bed allocation. Differently from previous papers, in this work we follow an unsupervised approach and, specifically, we perform an analysis of UK hospitals by means of a computational intelligence algorithm integrating Fuzzy C- Means and swarm intelligence. The dataset that we analyse allows us to compare pre- and post- pandemic data, to analyze the ethical and legal challenges of the use of computational intelligence for critical decision-making in the health care field. Index Terms—Computational Intelligence, AI and Law, AI Ethics, Health Care, Covid-19, Fuzzy Logic
Background This article investigates the hospital costs related to the management of COVID-19 positive patients, requiring a hospitalization (from the positivity confirmation to discharge, including rehabilitation activities). Methods A time-driven activity-based costing analysis, grounding on administrative and accounting flows provided by the management control, was implemented to define costs related to the hospital management of COVID-19 positive patients, according to real-word data, derived from six public Italian Hospitals, in 2020. Results Results reported that the higher the complexity of care, the higher the hospitalization cost per day (low-complexity = €475.86; medium-complexity = €700.20; high-complexity = €1,401.65). Focusing on the entire clinical pathway, the overall resources absorption, with the inclusion of rehabilitation costs, ranged from 6,198.02€ to 32,141.20€, dependent from the patient’s clinical condition. Conclusions Data could represent the baseline cost for COVID-19 hospital management, thus being useful for the further development of proper reimbursement tariffs devoted to hospitalized infected patients.
Introduction: The objective of the analysis is to investigate whether there is a correlation between deaths occurred within nursing homes in Lombardy Region and those related to the whole elderly population residing in the municipalities of their location at the beginning of the COVID-19 pandemic. Methods: The analysis considered a sample of 17 nursing homes belonging to the same legal entity (with a total of 2,197 beds). The changes occurred in the trend of deaths in 2020 between January the 1st and February the 20th, and between February the 21st and April the 4th, compared with the average number of deaths occurred in the same time intervals of the previous three-year period (2017-2019) were investigated. To verify the presence of a correlation between deaths occurring within nursing homes and those related to the whole elderly population residing in the municipalities of their respective locations, Pearson correlation index was calculated, distinguishing between elderly over 65 years of age and elderly over 85 years of age. Results: A statistically significant correlation was identified between the number of deaths among the overall population and the number of deaths among nursing homes residents between February the 21st and April the 20th, while no correlations were identified between January the 1st and February the 20th. Conclusions: The number of deaths occurred in the nursing homes of the sample considered shows similar trends to those of the elderly population of the municipalities in which they are located.
The movie industry is a highly differentiated context where production studios compete in non-price product attributes, which influences the box office results of a motion picture. Because of the short life cycle and the constant entrance of new competitive products, temporal decisions play a crucial role. Time series of the number of movies on release and the sum of the box office results of the ten top motion pictures (ranked by box office result for that week) present a counterphased seasonality in the US movie market. We suggest that a possible reason is a risk sensitivity adaptation in the behaviour of the movie’s distributors. This paper provides a model supporting this hypothesis. We developed an agent-based model of a movie market, and we simulated it for 15 years. A comparable global behaviour exists when producers schedule the movies according to given risk-sensitive strategies. This research improves the knowledge of the US motion picture market, analyzing a real-world scenario and providing insight into the behaviour of existing firms in a complex environment.
Residents' relatives are regularly solicited to evaluate the hotel, social- and health-care services that nursing homes provide to the aged in order to preserve their residual cognitive, physical, and social capabilities. In this study we argue that, due to the services' different technical and functional elements, residents' relatives find it easier to assess the quality of the hotel services instead of the other types of services. Based on 2012 responses from residents' relatives in 38 nursing homes in the Northern part of Italy, our results show that satisfaction with hotel services partially mediates the impact of satisfaction with social- and health-care services, above and beyond their direct effect on the overall satisfaction with all services. We conclude by discussing theoretical contributions and managerial implications.
Firm performance is an important output that managers should control. Of the several perspectives taken to analyse performance within companies, innovation performance and economic performance are especially relevant. Joint patents are an important but overlooked strategy that firms can use to improve their performance. In this paper, an agent-based model and simulator (PABIM) is developed to investigate the impact of noncopatenting and copatenting strategies on economic and innovation performance. Economic performance is evaluated by observing turnover, whereas innovation performance is evaluated using the Innovation Patent Index (IPI). IPI is based on five patent features, each of them defined using machine learning algorithms. The results show that, depending on the innovation intensity of the sector, both noncopatenting and copatenting strategies can be effective to improve both the economic and innovation performance.
(1) Background: Patent foramen ovale (PFO) is a congenital abnormality present in up to 25% of the general population, and it is a relevant cause of cryptogenic stroke. We applied the hospital-based HTA model (AdHopHTA) to conduct a multidimensional assessment of NobleStitch EL, an innovative suture-mediated PFO closure device. We compared it to Amplatzer PFO Occluder (APO) to provide evidence to inform technologies’ governance in hospital settings. (2) Methods: For each AdHopHTA dimension we: systematically retrieved available evidence from the literature applying the PRISMA guidelines and then analyzed original clinical and cost data of a NobleStitch EL device at San Raffaele research hospital in Milan (Italy). The economic dimension was analyzed through activity-based costing and a cost analysis. We conducted semi-structured interviews with selected healthcare professionals to explore the organizational, legal, social, and ethical impact. (3) Results: A single study was included for the NobleStitch EL, with 10 for APO. Both literature data and original data showed comparable safety. Efficacy data analysis found that the PFO closure was at 89% for NobleStitch EL vs. 89–97% for APO. APO has a better impact on the budget and minor process costs. Consulted experts reported that the organizational impact of NobleStitch EL in the short and the long run as null, albeit a better impact under the social and the ethical aspects. (4) Conclusion: We suggest that there is inadequate evidence to conclude the relative efficacy of NobleStitch EL as compared to APO. Nevertheless, this report shows a good safety profile and higher costs for NobleStitch EL, with no organizational or legal impact. Further studies in selected population are recommended.
The growth of the enterprise blockchain research supporting supply chain management calls for investigations of their impact and mindfulness of their design, use cases, and pilots. With a blockchain design for the Proof of Delivery (PoD) process management, this paper contributes to learning about performance measurement and the transaction costs implications during the development and application of smart contracts. An experimental design science approach is applied to develop an open-source blockchain to explore ways to make the delivery processes more efficient, the proof of delivery more reliable, and the performance measurements more accurate. The theory of Transaction Costs is applied to evaluate the cost implications of the adoption of smart contracts in the management of the PoD. The findings show that smart contracts make the delivery processes more efficient and proof of delivery more reliable. Yet, the methods and metrics are too complex and qualitative, limiting the smart contract's capability to measure performance. Our findings indicate potential transaction costs reduction by implementing a blockchain-based performance measurement. The complexities of the delivery process and proof of delivery call for pre-contractual steps to identify the processes and performance metrics to design blockchains. Smart contracts need further development and digital aids to handle qualitative inspections and proof of delivery generation during the delivery process. The blockchain requires the system's capacity to record off-chain transactions, such as in case of disputes resolutions. The authors extended blockchain research beyond the theoretical level, designing an open-source blockchain for supply chain management within the use case, pilot design, and case study.
The circular economy (CE) has been lauded as a path enabling more environmentally sustainable economic growth for diverse industrial companies, requiring them to design and implement circular business models (CBMs). A CE widens a company's perspective to include supply chains when adopting and implementing a CBM; however, the intersection of CBMs and circular supply chain management (CSCM) research has been under-studied. Although considerable CBM research has been carried out, the role of supply chain collaboration in companies' CBMs has been neglected. To address this research gap, in the present study we integrate knowledge from CBM and CSCM literature and conduct a qualitative multiple case study of six Italian and Finnish companies in order to analyze how their supply chain collaborations enable implementation of CBMs. The results allow us to develop a new conceptual framework, a synthesis of how supply chain collaborations support companies' CBM design and implementation, and a research agenda comprising seven thematic management aspects at micro, meso, and macro-levels. The framework, synthesis, and agenda provide conceptual guidance and structure for researchers and pragmatic guidance for managers.
To anticipate, adapt and respond to, and recover from disruptions, firms need to enhance supply chain (SC) resilience. The spread of the COVID-19 pandemic in 2020 represented a unique opportunity to investigate it empirically. This study focuses on the exploration of the resilience strategies adopted to deepen their temporal characteristics and contribute to developing the current understanding of proactivity and reactivity, something that needs to be further investigated. Multiple-case study research was conducted considering 21 Italian companies in the grocery industry. Results show that with the outbreak of the pandemic, companies adopted a set of 21 strategies that spanned five resilience categories: redundancy, flexibility, agility, collaboration, and innovation. To explain the temporal characteristics of the identified resilience strategies we propose an original taxonomy that elaborates the previous theory by introducing two new dimensions related to the strategies’ timing (“when?” and “how long?”). Each dimension can be complemented with other sub-dimensions that explain the design and activation of resilience strategies, and their utilisation and availability. The proposed taxonomy broadens the narrow view offered by existing research on the temporal dimension of resilience, as multiple layers are needed to disentangle the temporal characteristics of different strategies. It also provides an original viewpoint on interpreting the strategies’ proactivity or reactivity as their boundary is increasingly blurred. Lastly, the study opens up to future investigations of the antecedents of the design and utilisation/activation of resilience strategies, as companies could rethink their managerial decisions based on the continuous evolution of their operating environment.
Objectives In scenarios of vaccine scarcity or contexts of organizational complexity, it is necessary to define prioritization strategies for allocating vaccine doses in compliance with the criterion of equity and efficiency of health resources. In this context, the COVIDIAGNOSTIX project, based on the health technology assessment (HTA), assessed the role of SARS-CoV-2 serological tests as a companion diagnostic in the definition of the vaccination strategies for the vaccine administration. To guarantee evidence support for health policy choices, two different vaccine strategies were analyzed, one based on administering the vaccine booster dose to the entire population (VACCINE strategy) and the other based on allocation criteria (TEST&VACCINE strategy). Methods The decision-oriented HTA (DoHTA) method, integrated with specific modeling and simulation techniques, helped define the perimeter to make health policy choices. Results The processing of the scores attributed to the key performance indicators concerning all the evaluation domains shows a performance of 94.34% for the TEST&VACCINE strategy and 83.87% for the VACCINE strategy. Conclusions TEST&VACCINE strategy can be the most advantageous in various scenarios due to greater speed from an operational and an economic point of view. The assessment schemes defined by COVIDIAGNOSTIX (i.e., technologies/intended use/settings) can easily and quickly be exported and adapted to respond to similar health “policy questions”.
Background and Aims: INTERCheckWEB is one of the most outstanding digital technologies, that could be implemented at the hospital level, supporting the clinicians in the evaluation of the therapy appropriateness, reducing the potentially inappropriate prescriptions, for the improvement of the clinical decision‐making process. The paper aims at investigating the relationship between clinicians' behaviors towards digital decision support system in therapy appropriateness for elderly patients in polytherapy in medical departments, defining the factors that could influence clinicians to use INTERCheckWEB, for supporting drugs' prescription. Methods: A questionnaire was administered to 70 clinicians referring to Internal Medicine wards, of four Italian hospitals. The authors assessed how perceived usefulness, perceived ease of use, image, and output quality, would affect INTERCheckWeb intention to use. Inferential statistics, by means of a regression analysis, were conducted to define the main aspects useful to understand the factors impacting on such digital technology adoption in clinical practice. Results: The regression analysis reported that image, perceived ease of use and perceived usefulness, as well as the moderator effect of the voluntary use between the perceived usefulness and the intention to use, are the factors that most influence the use of INTERCheckWEB (adjusted R2 = 0.870). Conclusions: Results demonstrated that clinicians would use INTERCheckWEB, when available, to identify all the information on situations that could be dangerous for the patients, thus limiting the drug–drug interactions, optimizing the overall patient's clinical pathway. Furthermore, the implementation of INTERCheckWEB could also contribute to the proper management of COVID‐19 patients, since both hospitalized and symptomatic COVID‐19 patients are frequently older, with comorbidities.
Collaboration between research and industry is fundamental for technology innovation. Most existing research in this domain has focused on the drivers or enabling factors that lead to the success of such collaboration. On the contrary, the lack of information about collaboration failures in research-industry settings still represents one of the main obstacles to studying this topic. In this paper, we argue that management scholars should deepen inquiry on unsuccessful research-industry collaborations, as these occurrences may also have major repercussions in terms of business failures. Accordingly, we take stock of research on unsuccessful collaborations in the Big Science context, a special open innovation environment characterised by unexplored cases of research-industry collaboration failures. To address the need to investigate the drivers of failure in this context, we leverage a multiple case study analysis with a retrospective approach of a polar sample type of six case studies of collaborations between CERN – the biggest fundamental research organisation in the world – and supplier companies: three collaborations that have been recognised as successful, and three that have been recognised as failures. By doing so, we aim to provide a framework highlighting the main drivers that lead to failures of collaborations in this peculiar open innovation context and to shed light on the reasons why research-industry collaborations may fail in the Big Science context.
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