1 Introduction

Starting from the first half of the last century, the need for economic-managerial training of engineers has been addressed along two lines of development. The first one, according to a widespread approach variously adopted in the American and European contexts, was based on the ‘addition’ of economic-managerial training to engineering, with study courses aimed at graduates in engineering, often (and preferably) after a period of work experience, as in the case of Masters in Business Administration or Executive Masters in Business Administration. The second line was oriented to the “specialization”, i.e., the creation of new degrees or curricula in the field of engineering with the objective of training new professional figures with more or less in-depth skills in technology and business management. In line with this approach, a first example, also in terms of time, has been that of Industrial Engineering, whose first course of study, at the bachelor level, was established in 1909 at the Pennsylvania State University. After the Second World War, the new specialization in Engineering Management, also called Engineering and Technology Management, was introduced in some American engineering schools but also in Europe ed some countries of other continents (Japan, Australia).

Within the variegated path of contamination of the engineering and managerial disciplines, a different perspective has emerged over time, which has led to the birth and diffusion of new programs, different from those of Engineering Management, labeled as Management Engineering. The question was not purely formal as the expression Engineering Management has a different meaning from Management Engineering. Hence, Management Engineering can be defined as the engineering of management systems, with the application of engineering theories, methods, and tools to the area of management. In other words, Management Engineering is not management applied to engineering, but rather engineering applied to management.

Among the possible factors that fostered the evolution above described, in the broader framework of the economic-managerial training of engineers, two characterizing elements have to highlight. The first one is the contamination between cultural and scientific areas of different origins but interested in the issues of business management and technology (e.g., system science, operational research, plant engineering). The second element is the setting-up over time of a substantial nucleus of researchers dedicated to the disciplines characterizing the management area; starting from the first groups formed in the sixties and seventies, thanks also to the launch of the “research doctorate” and the opening of new research streams. The establishment of a strong nucleus of reference, capable of transferring the updated results of its research into the training activity, in a framework of growing collaboration with other disciplinary fields, contributed to defining the identity and effectiveness of the teaching activity, appropriate to the educational objectives. In this framework, management engineering courses must be updated, not only with respect to the evolution of the various disciplines, but also with respect to the need to train professionals who are even more aware of the role played in society as bearers of a systemic approach to innovation.

To sum up, Management Engineering deals with developing and transferring the knowledge necessary to design and manage complex organizational systems within the framework of the articulated relationships between technology, economics, and management. Management Engineering brings together the skills related to the integration of engineering culture with the economy and management of companies, organizations, and public and private institutions. These objectives are achieved through the fruitful interaction between teaching, research, and the valorisation of knowledge.

Management Engineering focuses on the processes of transformation, change and innovation, i.e. the complex interactions between technological and social variables, with the aim of understanding their economic implications, the impacts on organizations, territories and society and, consequently, the most appropriate strategic, managerial and policy choices. From this point of view, the issues of economics and management of technology, entrepreneurship, internationalization, digitization, ecological transition, and social innovation are central. In particular the discipline deals with the design and management of complex organizational systems such as global networks, supply chains, innovation ecosystems, cross-sector collaborations, studying their dynamics, managerial processes and choices aimed at generating value.

2 Background and Legacy

Management Engineering born on the base of a solid and sturdy Italian academic tradition. As early as the 1930s, many engineering faculties/schools included an economics course in the student’s curriculum. The aim was to combine the technical aspects with the economic feasibility. In this way engineering students received an initial cultural stimulus towards a professional activity that took into account both technical and economic issues. In this framework, attention to economic and organizational issues also has a long tradition at the Faculty of Engineering of the University of Naples Federico II. Already in the 60s it was founded and operated, under the presidency of the late prof. Luigi Tocchetti, the C.S.E.I. (Centre for economics applied to engineering). The C.S.E.I. was always attentive to the problems which, in those times, also emerged in other countries, both in the European and American continents, as well as in the countries of the Far East. The C.S.E.I. became a forge of young researchers who then held important positions in several universities, industries, and important public and private institutions. In the following years, under the guidance of various Deans and Department Directors, the Faculty/School of Engineering of the University of Naples Federico II increasingly strengthened its propensity towards economic and organizational issues. Propensity that led towards the mid-seventies to establish a teaching of economics and business organization, first entrusted to prof. Alfredo Del Monte and subsequently to prof. Mario Raffa. This first teaching represented the cultural nucleus of what would become management engineering in the Faculty of Engineering of the University of Naples Federico II. It was a single teaching offered as part of the training courses of the various traditional degree courses in engineering (aerospace, mechanical, electronics, chemistry, computer science, electrical, naval, etc.). This teaching introduced the engineering student to the topics of microeconomics, macroeconomics as well as to the study of industrial sectors and their significant managerial aspects (economics of small and medium-sized enterprises of the software industry, supply chain management of the aerospace and automotive industry, economics and management of the high-tech industry, product life cycle of different industries, innovation management, and project management, etc.). in the following years, according to the international trend, Naples also followed two parallel paths, that of more or less in-depth economic-managerial training, which is added to the basic training of engineers and that of specialization, with the creation of an ad hoc degree course in the field of engineering: It was the birth, thirty-two years ago of the management engineering degree course. The entry into the labor market of the management engineers of the University of Naples Federico II was rapid and with extremely flattering results judged satisfactory by the companies and by the various institutions in which, the graduates found employment. Currently, there are over a thousand graduates in Management Engineering. To these must be added the conferral (in October 1987) of the “Honorary degree” to prof. Franco Modigliani, former Nobel Prize winner for economics. Management Engineering graduates find ample employment opportunities both in manufacturing companies and in services, as well as in public administration. Currently about 5–7% work in small and medium-sized enterprises. Large companies (Italian and foreign) as well as multinational companies employ about 40–42% of graduates. 21–23% of management engineers carry out activities in the training sector, research, and public administration (schools, universities, research centers, local public bodies), while 30–32% carry out consultancy activities (both small and medium-sized enterprises and large companies and multinationals). This vast range of opportunities derives from the fact that management engineering is conceived with intersectoral characteristics and is therefore placed outside the logic of traditional specializations while aiming at the training of engineers culturally equipped to enter fields in which the technical variable and interact with economic, institutional, social and environmental ones. In this context, the management engineer does not lose his sincere identity as a technician oriented towards tackling problems concretely. In the confirmation of this pragmatic nature, his specific potentials are consolidated, always well distinct from those resulting from other areas of university studies.

On the base of these essential observations, the research activity in the sector of management engineering at the Department of Industrial Engineering of the University of Naples Federico II is strongly attentive to technology, since the latter has a significant influence on the change of production, economic and organizational processes. The research activity is characterized by a quantitative approach, without neglecting the qualitative variables which often assume crucial importance. Furthermore, it pays significant attention to the issue of complexity that increasingly characterizes companies, business systems, local systems, attention to sustainability (combined in terms of environmental, social, economic sustainability, etc.). The attention to the management aspects of complexity is the result of an activity aimed at developing a systemic culture inherited from the cultural areas that have contributed to the birth, growth, and development of management engineering.

3 Congresses

In relation with the various research streams, many national and international meetings and conferences has been sponsored and organized. Among these the most relevant are:

  • 21st annual IPSERA conference, Purchasing & Supply Management in a Changing World, Congress Centre, University of Naples, Federico II, April 1–4, 2012.

  • EWGLA and ISOLDE, XXI Meeting of European Working Group on Locational Analysis (EWGLA) and XIII Edition of the International Symposium on Locational Decision (ISOLDE), Naples and Capri, June 16–20, 2014.

  • XX SIGEF Congress, Harnessing Complexity through Fuzzy Logic, University of Naples Federico II. July 4–5, 2019.

  • XXXII AiIG Scientific Meeting, Rethinking Sustainability and Resilience after the Covid-19 pandemic. Developing research and education in Management Engineering, Naples, October 21–22, 2021.

  • 23rd ECKM Conference, European Conference on Knowledge Management (ECKM), Naples, September 1–2, 2022.

  • RENT XXXIV, Research in Entrepreneurship and Small Business Conference, Re-thinking entrepreneurship after the crisis, Congress Centre, University of Naples Federico II, November 17–18, 2022.

4 Main Research Programmes

The research activity of Management Engineering is organized into seven main research areas.

4.1 Complexity in Organizational and Innovation Management Studies

This research line has been devoted to building up a computational agent-based laboratory, named CLOD (Computational Laboratory for Organizational Design), to explore the advantages that agent-based approaches could offer to scholars and practitioners in organizational research, particularly in organizational design. The laboratory’s conceptual architecture is based on March’s organizational learning model, appropriately reframed in the light of Complex Adaptive Systems. It has a modular structure and has been used to perform generative experiments to explore, for example, the eventual benefits in terms of organizational performances obtained through informal coordination mechanisms based on natural language [1].

The Complexity theoretical and methodological perspectives have been also used outside the boundaries of individual firms, by studying organizational and innovation management issues in entrepreneurial networks [2], small firms’ clusters, and regional and national innovation systems. In most cases reported above, the research activity has been performed through agent-based platforms developed by the research group and made freely available in an open science perspective. A socio-computational approach is adopted to model business transactions and supply chain formation in Marshallian industrial districts. An agent-based model is presented and used as a virtual lab to test hypotheses concerning firms’ behavior in entrepreneurial clusters and the emergence of collaborative networks and specific structural properties at the system level. An agent-based modeling was also developed to support self-sustaining regional innovation systems (RISs). The model is the base of a computational laboratory, CARIS (Complex Adaptive Regional Innovation System), which aims at evaluating the self-sustainability of RISs and at investigating what are the resources, competencies, and mechanisms able to trigger powerful innovation and economic growth processes. Such a topic is particularly interesting for the so-called “lagging regions”, which, notwithstanding noticeable policy interventions, have been unable to significantly improve their innovation performances.

4.2 Empowering Academic Entrepreneurship in the Digital Age: Insights, Innovations, and Future Directions

One of the keyways universities can contribute to advance regional development and economic growth, is by nurturing entrepreneurial awareness among their students and fostering academic entrepreneurship (AE). By leveraging innovative educational models and digital tools, universities can empower students and academicians with entrepreneurial mindsets, ultimately driving economic growth and regional development. Within this context, the literature identifies four major research streams: Digital Technologies for Entrepreneurship Education, the ‘maker space movement’ for Academic Entrepreneurship, digital technologies for discovering entrepreneurial opportunities, and creating entrepreneurial competences in digital ‘university-based’ entrepreneurial ecosystems. Also, it reveals the need for further research and a more holistic understanding of the role of digital technologies in shaping entrepreneurial initiatives within academia [3].

Moreover, the role of digital technologies in entrepreneurship education centers is explored in a study analyzing Italian Contamination Labs (CLabs). The analysis reveals a limited adoption of digital technologies within CLabs, primarily utilized for promotional and communication purposes. In response to the challenges posed by the COVID-19 pandemic, researchers investigate the potential of digital technologies in promoting entrepreneurial self-efficacy and intention among engineering students. In [4], the authors reveal that an online-designed entrepreneurial course, leveraging digital technologies such as MOOCs and gamification, positively impacts students’ self-efficacy and intention to pursue entrepreneurial endeavors. The synthesis of these studies highlights the transformative potential of digital technologies in fostering student entrepreneurship and academic entrepreneurship. Building upon the research on AE, [5] focuses on exploring the factors that drive university engineering students to become entrepreneurs. Utilizing a configuration approach, this research investigates the entrepreneurial intentions and propensities of engineering students from various European countries. The findings reveal that entrepreneurial intention and propensity are influenced by a combination of factors rather than a single driver. Notably, the intensity of entrepreneurship education emerges as a crucial factor in shaping students’ entrepreneurial intentions. This innovative model aims to trigger transdisciplinary abilities in doctoral students, making them better prepared for entrepreneurial ventures. The study demonstrates that the T-shaped doctoral program positively influences students’ vertical skills and horizontal capabilities, enhancing their entrepreneurial readiness.

In [6] a comprehensive analysis of the current literature is performed to define the state of student entrepreneurship (SE) and identify potential research directions. The study involves an extensive review of 288 published articles from International Entrepreneurship and Management Journals, as well as journals in Education and Management Business Accounting subject areas. The results, structured into two macro sections, delve into corpus overview and bibliometrics, analyzing the evolution of SE-related articles over time, authorship trends, citation analysis, and the prominent journals in the field. This analysis highlights the growing significance of SE and the diverse approaches taken by researchers in exploring this area. A content analysis approach is performed to uncover the major themes and issues that emerge from the literature. An investigation of the most common theories used in SE research, the methodologies employed to gather data, and the mechanisms adopted by universities to promote and support SE among students provides valuable insights for researchers interested in exploring the different sub-fields within SE. This work not only contributes to the academic community but also offers valuable suggestions for management educators, business school administrators, and institutional leaders. By enhancing entrepreneurial activities and initiatives, universities can better support student entrepreneurs. Additionally, policymakers can rethink and redesign policies that encourage and foster entrepreneurship among students.

4.3 Links Between Open Innovation Strategies, Sustainability and Digitization of Companies

Adequate management of intellectual property (IP) is critical to sustaining competitive advantage and managing outbound OI, which describes the inside-out flows of knowledge and technology. In [7], it is presented an IP strategic framework comprising the following strategies: a ‘defensive’ strategy, aimed at avoiding knowledge spillovers and building barriers to competition; a ‘collaborative’ strategy, aimed at collaborating with other organizations and entering new markets; and an ‘impromptu’ strategy, which describes firms protecting their IP without a clear purpose. The authors investigate the relationships of such IP strategies with outbound OI and innovation performance in 158 Italian firms. The results show that not having any IP protection strategy can be a barrier to outbound OI and that firms with a defensive IP strategy embraced outbound OI more than those declaring a collaborative IP strategy. Finally, firms with collaborative IP strategies outperformed those with defensive strategies.

In [8], an exploratory analysis of 73 Italian manufacturing firms allowed identifying five intellectual property strategies: defensive, purposely defensive, collaborative, developing impromptu and impromptu. The article describes their differences in intellectual property protection mechanisms and outbound open innovation. Furthermore, a fuzzy-set qualitative comparative analysis identifies the optimal combination of formal, semiformal and informal intellectual property protection mechanisms to nurture outbound open innovation.

The challenges and complexities entailed by the OI should not be underestimated. Through a systematic bibliometric review of the literature on the causes of failure of OI, performed in order to analyze its evolution and to provide a framework to help managers understand and prevent OI failures, ten categories of causes of OI failure to be included in a seven-components framework have been identified. The latter adopts the perspective of the firm and investigates both internal and external causes of failure. In [9], the authors show that firms collaborating with a wider network of external partners to conduct their innovation activities are less likely to abandon them. The article also analyses how different categories of partners are associated with the risk of innovation abandonment. Finally, the results show that international collaborations are more likely associated with innovation abandonment than domestic ones. In [10], the motivations underlying COVID-related innovations, the role of inter-organizational collaboration, and their relationship with innovation novelty are explored. 18 Italian COVID-19-related innovations developed during the initial pandemic phase are studied, considering two industrial motivations based on the exploration-exploitation dichotomy and two institutional motivations (corporate social responsibility and marketing). Using the crisp set Qualitative Comparative Analysis, the authors found that institutional motivations have driven most radical and incremental innovation projects.

More recent literature suggests that OI can help companies also improve their Corporate Social Responsibility (CSR) performance. To this end, a theoretical framework to explain how companies can simultaneously improve OI and CSR through the management of relationships with stakeholders has been developed. Results show that the stakeholders’ theory can be used to explain the connection between OI and CSR performance and that companies can collaborate with different stakeholders’ categories to achieve a variety of CSR goals. The companies adopt a long-term perspective and explicitly include sustainability objectives in their open innovation strategy to enhance their position as reliable partners and elicit favorable responses from the environment. In [11], the authors suggests that the businesses’ collaborative relationships with external consultants or organizations can increase their competitive advantage, as external stakeholders could assist them in the development of sustainable innovations, diversification into different markets, and in the generation of new revenue streams. At the same time, they can support them in addressing numerous deficits in society. On the other hand, an organizational culture that promotes open innovation approaches could expose practitioners to risks and uncertainties, like revealing sensitive information to outsiders, among others.

4.4 Decision Support Systems for Supply Chain and Logistics Design and Management

Within the broad context of process innovation and optimization, a significant research field concerns the design and management of supply chains and logistic systems. In the following, the performed research activities and those still in progress are illustrated considering three main areas.

The first research area concerns Supply Chain (SC) design. SC consists in the definition and the organization of the different actors involved in the production, distribution and consumption of a given good or service (suppliers, producers, logistic providers, final customers). In this area, a fundamental problem is represented by the optimal location of the facilities along the entire chain (suppliers, production plants, distribution centres, warehouses). In this general framework, different real cases of location problems have been investigated, both in the private and the public sector, and general optimization models and methods have been developed, inspired by the so-called locational analysis methodologies. A specific stream is focused on the design of public service networks and, specifically, on the development of approaches able to produce long-term scenarios combining efficiency goals with the need to ensure adequate and equitable levels of user accessibility. The proposed models have been successfully used to solve various real problems in the different fields, e.g., healthcare [12] and reverse logistics [13]. The models have been generally solved by managing huge amounts of data, through the integration of optimization methods, Geographical Information Systems (GIS) and simulation tools. Another research stream concern the theoretical investigation of the location problems and, specifically, the definition of innovative models capable of taking into account the actual complexity of the systems; i.e., the presence of multiple facilities providing various type of services, the possibility of different interaction mechanisms among facilities (cooperative vs competitive), the stochastic nature of different elements of the problems, the adoption of multiple and conflicting performance indicators [14].

The second research area focuses on Last-mile logistic network organization. In general, last-mile concerns the delivery of parcels from the logistic distribution centres until the endpoints at which customers want the parcel to be delivered. In recent years, the striking diffusion of B2C and C2C e-commerce, also accelerated by the COVID-19 pandemic, is pushing logistic providers to reorganize their supply chains to reduce costs by satisfying increasing consumer requirements. As such, great emphasis is given to the optimization of this logistics’ phase. In this field, the main research activities concern the development of models and methods to support the optimal reorganization of urban infrastructure for last-mile logistics and the definition of novel delivery strategies [15]. Such activities have been carrying out within the framework of a research project funded by the National Italian National Resilience and Recovery Plan (NRRP), devoted to sustainable mobility (“Centro Nazionale per la Mobilità Sostenibile”, MUR CN00000023). In particular, two main classes of strategies have been exploring: (i) optimizing home delivery by leveraging novel technologies and shipping methods (electric vehicles, drones, crowd shipping) or by adopting novel logistic solutions; (ii) (partially) replacing home delivery by resorting to the so-called self-collection, which requires customers to autonomously go and collect parcels from manned or unmanned facilities (pick-up points and parcel lockers). To this end, we developed different models to support the location of pick-up points, aiming to maximize customers’ willingness to use self-collection and minimize logistic costs. Such models have been applied using real data to support the major Italian postal provider (Poste Italiane S.p.A) in the decision-making process concerning its self-collection network design.

Finally, the third research area is devoted to Re-engineering for Sustainable Processes and Supply Chains. It focuses on the re-design of inbound operations in order to combine productive efficiency with the reduction of environmental impacts. Activities have been stimulated by the participation to European and national projects: TrainERGY—Training for Energy Efficient Operations, 2015-1-PL01-KA203-016919, http://www.trainergy-project.eu/; PrESS—Promoting Environmentally Sustainable SMEs—-538851-LLP-1-2013-1-UK-ERASMUS-EQR, http://www.pressproject.eu/it/; METROPOLIS—METodologie RObuste per l’efficientamento dei Processi e l’Ottimizzazione Logistica nell’Industria Siderurgico-navale, funded by MISE—Ministero per lo Sviluppo Economico; 3A-ITALY, funded in the context of the National Recovery and Resilience Plan NRRP, MUR: PE00000004. In particular, more recently, we have been performing a complex industrial project in partnership with a medium enterprise of the shipbuilding sector, in which we are implementing an holistic approach for the optimization of production processes and their integration with inbound and outbound logistic operations [16]. The projects also aims at defining an appropriate set of KPIs, tailored on the specific production context, to describe the different dimensions of the production environment, and at re-engineering the critical processes to reduce the CO\({}_2\)-eq output.

4.5 Managing Digital and Sustainable Innovation in Individual Firms and Supply Chains

In the dynamic landscape of business, companies are actively embracing digital transformation to enhance and optimize their processes, including knowledge management (KM) processes. Consequently, knowledge management systems (KMSs) are becoming integral components of business operations. Successful KM requires a synergistic alignment between tools and practices to unlock the full potential of an organization’s assets. Efficiency and effectiveness in the adoption of KMSs for small and medium enterprises (SMEs) emerge as significant concerns [17]. We proposed a novel 3D-fuzzy logic methodology to examine the adoption of KMSs in supply firms related to the nature of knowledge and the KMSs used. The adoption of a decision support system assessing the alignment between tools and practices and suggesting strategies for KMSs adoption to improve KM alignment, the efficiency and the effectiveness performance of KMSs, resulted to be particularly valuable in bridging digital tools with managerial strategies.

While operational performance has long been a primary focus, incorporating sustainability performance metrics it has become mandatory. Global awareness prompts a thorough supply chain (SC) re-evaluation. In this context, logistics service providers (LSPs) play a vital role within SCs. The freight industry, including LSPs, is a major contributor to greenhouse gas and CO2 emissions. The growing influence of green practices and enabling technologies presents opportunities for emissions reduction and climate action. Our research effort has been focused on assessing and improving sustainable performance within the LSPs sector [18]. We proposed a taxonomy of green initiatives guiding LSPs in pursuing environmental sustainability performance. The taxonomy categorizes aims, practices, and technological tools, revealing discrepancies in the prioritization of certain sustainability aspects over others. The prevalence of technology adoption over green practices highlights the need to bridge gaps in technology, culture, and management to achieve comprehensive environmental sustainability.

The growing interest in sustainability objectives has driven our research to provide a comprehensive examination of established sustainability research streams within the SC. Considering the incredibly high number of papers in the literature on this topic, we adopted a novel tertiary-systematic review methodology to identify the most promising future research avenues to be further investigated [19]. Evaluating how reverse logistics and closed-loop SCs can be used to implement sustainable green SC practices and circular economy (CE) strategies, emerged as one of the most interesting future research directions to be further investigated. Consequently, a recent research trajectory has emerged, homing on CE, where emphasis is placed on technological and managerial aspects aimed at optimizing resource usage, minimizing waste, and increasing the value of products beyond their initial use. Central to this pursuit is a meticulous examination of the entire value chain, unlocking the potential to extend product lifecycles and elevate ecological consciousness. This pursuit encompasses a range of strategies, from waste reduction and recycling to other strategies. In this context, we started a multifaceted research stream that encompasses several pivotal dimensions. One of the most critical issues investigated in the current literature relates to the factors affecting the adoption of CE strategies. We investigated relationships between factors such as social pressure, environmental commitment, green incentives, supply chain management, and CE capabilities. The findings highlight the positive impact of commitment and incentives on supply chain management and sustainable design. This research underscores the need for strategic planning to facilitate CE transitions and integrate sustainability into supply chain management practices.

According to the current rules about commitment towards sustainability, businesses are poised to play a pivotal role in demonstrating their commitment towards sustainability through comprehensive accountability measures. Future forces companies to embrace holistic sustainable behaviours by analysing their lifecycle, in line with ISO standards, and leveraging technology. Our preliminary field analysis has been conducted in the agri-food industry, one of the most polluting industries due to the environmental impact of their operations [20]. Given the considerable resource consumption, waste generation, and emissions associated, companies in this industry are increasingly committed to integrate sustainable practices into their core operations, aligning with global efforts to address climate change and foster CE. To address these challenges, it is necessary to start with the assessments of the entire lifecycle of a product, from raw material extraction to disposal. Quantify its environmental impact through Life Cycle Assessment (LCA) according to ISO standards is imperative. Following the assessment phase, the improvement phase is performed. In this crucial stage, the focus shifts towards integrating CE practices to booster performance. The LCA analysis conducted in a food company uncovered key environmental hotspots within their SC, guiding our efforts towards areas that necessitated immediate attention. Strategies such as efficient packaging and sustainable procurement were strategically introduced, aligning with the company’s sustainability objectives and facilitating their transition towards CE.

As far as the knowledge diffusion process between companies is concerned, a hybrid model has been proposed which interprets the knowledge diffusion process within the triadic relationship between customer, first level supplier and second level supplier. The hybrid model is based on two main approaches suggested in the literature to address multi-criteria evaluation problems, the Analytic Hierarchy Process and the fuzzy set theory. The effective usability of the hybrid model is investigated through the sample of 20 supply chains. The hybrid model allowed to identify a taxonomy that highlights the role and the behaviour of first-tier suppliers within the supply chain. Four areas were highlighted: Hub supplier area, Source supplier area, Restrain supplier area, and Sponge supplier area. Taking cue from the proposed taxonomy, it was possible to identify implications for both customers and suppliers, as well as policy makers.

4.6 Organizational and Innovation Management in Healthcare

Health organizations are very fertile ground for management studies. Healthcare services are essential for sustaining and improving human well-being. These services require a strict interconnection among different people (i.e., doctors, nurses, healthcare professionals, managers) across different levels as macro (i.e., healthcare system), meso (i.e., hospital) and micro (i.e., process). Main research activities carried out in this context aimed at: 1) investigating how healthcare organizations transform their processes by introducing digital solutions and technologies, and 2) designing adequate methods to analyze and improve organizational and administrative processes.

Concerning the first line, the research has deepened aspects related to telemedicine, defined as the use of information technology to deliver medical services over distance to propose solutions to accessibility, quality, and costs of medical care. Adopting an explorative approach, we analyzed the implementation of four telemedicine projects located in the Southern Italy, a disadvantaged area in comparison to other Italian and European regions. The goal of this research was to shed light on the characterization of leverages and barriers, as well as the related managerial actions for change implemented in a context whereby the diffusion of telemedicine remains limited [21]. Another research, has investigated the acceptance of telemedicine by people through the analysis of the innovation journey of a firm, that designed and developed a telemedicine platform, collaborating with different actors – adopters (physicians, nurses, and patients) and health decision-makers. This case study allowed us to put in evidence an interwoven relationship between the Open Innovation approach adopted in the development of the telemedicine platform and the acceptance of the technology itself. Against this backdrop, Open Innovation is not only an enabler supporting knowledge exchanges, but also an enabler of Technology Acceptance [22]. Focusing on the use of digital solutions in healthcare organizations, we have investigated the factors affecting the clinicians’ behaviors towards the use of digital decision support systems in therapy appropriateness and deprescribing issue. This research carried out under a strong collaboration with a research group of LIUC University of Castellanza, uses a survey, combining traditional methods (i.e., regression) with Qualitative Comparative Analysis to analyze the results.

Concerning the improvement of organizational processes and studied the Triage, our research focused mainly on Emergency Department (ED). The Triage process regulates access to emergency care through the assignment of a priority level to each patient. An effective Triage process has an impact on ED’s quality and efficiency. The Triage code’s assignment is an example of a cognitive heuristic, where the decision-making process cannot be simply automatized, since it is affected in a complex manner by Individual, organizational, and contextual factors. In this vein, our research has developed methods and carried out analysis for assessing the impact of individual and organizational factors on individual decisions [23], for providing an analytical learning system to assess the quality of the Triage decision-making process and improve it [24]. Moving from Triage to healthcare processes in general, models based on Activity Based Costing and Social Network Analysis have been designed and experimented with in healthcare units with the aim to improve the processes coherently with a process management approach.

4.7 Project Management in World of Research, Public Administration and Business Start up

The research program is divided into three main areas addressing various perspectives related to project management.

The first area refers to Project Management in the Management of Research Projects. As part of this research, two main research projects were carried out.

The first project, carried out in collaboration with the National Research Council (CNR), was aimed at analyzing the diffusion of Project Management skills in a sample of 195 Principal Investigators from the various departments of the Institute. Through a self-assessment questionnaire, the Principal Investigators of the sample assessed their degree of oversight of the following types of skills: Process skills; Personal skills; Technical skills; Contextual and task related skills [25]. The survey results were processed through Partial Least Squares Path Modeling [26]. A model with theoretical constructs and latent variables is introduced to analyze the causal detection among different types of variables, including the activation of hard and soft PM skills of Principal Investigators.

The second project was carried out in collaboration with Wroclaw University of Science and Technology (Poland) [27]. The study aimed to investigate, in the light of the literature and through a cross-cultural study conducted in Italy and Poland, the relationship between soft skills (empowering leadership style, self-efficacy beliefs, and collective efficacy) of the principal researcher (PR) and the perceived success of research projects and satisfaction with the project, taking into account intercultural differences. A total of 67 PRs of complex projects in public universities (28 in Italy and 39 in Poland) participated in the study, completing a self-report questionnaire. Data were analyzed using descriptive and correlational analyses.

The second main research area focuses on Uncertainty and Risk in Project Management in Public Administration Organizations. As part of this research, two main projects were carried out. The first project, carried out in collaboration with the Ministry of Justice, was aimed to investigate whether the adoption of a risk-based approach that allows public managers to take into account the context and external not-controllable factors during goal setting may contribute to overcome unintended managerial side effects of performance management (PM) practices that hamper their success within public organizations. Explorative research was carried out on court officials of Italian public administration [28]. The second project aimed at assessing the uncertainty scope and types present in public projects, with uncertainty defined as a lack of knowledge, and to formulate recommendations for improving the success rate of public projects [29]. Apart from a literature review, a questionnaire was administered among 60 Italian and 40 Polish public-project managers. Questions about the level of knowledge of various project aspects in the project-planning phase were asked. It was found that, in their own opinion, knowledge of essential aspects of public projects in the planning stage was fairly low among public-project managers. On top of that, the results showed in which areas, and in which of the two countries, the uncertainty was mostly present. This type of research has not been identified in the literature. In both countries, an especially high uncertainty level characterized project stakeholders. The survey’s conclusions are juxtaposed with results from the literature: the negative influence of lack of knowledge (i.e., uncertainty) on project success, specific features of public projects and public-project managers, and the fact that certain negative phenomena influencing project success are significantly more present in the public than in the private sector. Our results indicate which aspects of public projects in both countries should be subject to deep changes—as far as information collecting and processing, in the project-defining and planning phase, is concerned. All this leads to recommendations of measures to be introduced in the public sector with respect to public-project management, e.g., the establishment of project management offices, project knowledge sharing, project management training—all focused on the identified uncertainty types in public projects, such as management of project stakeholders.

Finally, the last main research area concerns Project Management and Business Start Up. Here, a research project was carried out to explore the contribution of project management (PM) to business startups, presenting a PM-based interpretative framework predicated on the assumption that business startups can be interpreted as entrepreneurial projects [30]. The framework combines the evolutionary path of the business startup life cycle with PM approaches and methodologies to support startuppers in addressing the uncertainty of the entrepreneurial process. Focusing on the business startup project life cycle, the framework examines the critical issues in managing each stage, the most suitable PM approaches, and lastly the tools, techniques, and interpersonal skills that startuppers need to organize their activities. The findings demonstrate that managing flourishing business startup projects can be supported by balancing traditional and agile project management methodologies according to the level of uncertainty and complexity of the different stages of their launch and development. Implications for theory relate to the unconventional connection between the literature on PM and entrepreneurship; implications for practices include the adoption of the proposed framework as a roadmap to support nascent entrepreneurs in managing entrepreneurial projects.

5 Future

As far as Complexity in organizational and innovation management studies is concerned, the research will be devoted to designing and implementing an agent-based laboratory to jointly investigate the environmental, social, and economic impact of the introduction of innovative technology for green hydrogen in specific innovation value chains (e.g., high-quality bio-chemicals).

Regarding Empowering Academic Entrepreneurship in the Digital Age: Insights, Innovations, and Future Directions, future development of this research stream will investigate how digital technologies affect the university entrepreneurial ecosystem as to provide a comprehensive and up-to-date overview of digital academic entrepreneurship. The study will analyze the new opportunities created by digital technologies within the university entrepreneurial ecosystem, such as incubation and acceleration of new businesses, use of online platforms for communication and commerce, access to new markets and financing tools, and access to new digital knowledge and skills, are analyzed.

Concerning Links between open innovation strategies, sustainability, and digitization of companies, in the current landscape of business and innovation, there exists a profound interplay between open innovation strategies, sustainability practices, and the ongoing digitization of companies. This nexus forms the crux of future research, which aims to delve deep into the intricate connections between intellectual capital, the digitization journey, and the overarching domain of corporate sustainability. This exploration is set to unfurl a tapestry of insights, shedding light on the multifaceted relationships and their far-reaching implications. With meticulous attention to detail, our research aims to unravel the precise impacts of cutting-edge Industry 4.0 and the emerging Industry 5.0 technologies on the strategic paradigms adopted by businesses and their ensuing sustainable performance.

Regarding Decision support systems for supply chain and logistics design and management, we see various future research directions for each of the outlined areas of interest. For Supply chain design and Last-mile logistic network organization, we are keen to investigate more comprehensive indicators for accessibility evaluation, coupling geographical and digital dimensions, and novel models and methods for redesigning spatially distributed multi-level services. Finally, as concerns Re-engineering for sustainable processes and supply chains, leveraging the ongoing research experiences, our endeavor will be devoted to defining and implementing comprehensive Decision Support Systems involving optimization tools integrated with appropriate KPIs and relevant assessment methodologies for efficient and environmentally effective production planning.

As for Managing digital and sustainable innovation in individual firms and supply chains, future research will be devoted in supporting companies to identify inefficiencies and areas for enhancement, leading to more targeted strategies for sustainability improvement. Digital platforms based on blockchain protocols can enable transparency and traceability, fostering responsible sourcing practices and minimizing negative environmental and social impact of company’s operations. By unravelling the intricacies of CE strategies and evaluating their real-world impact, we advocate for a paradigm shift towards sustainability. Our research stands in the interplay between technological innovation, strategic management, and corporate social responsibility, towards resilient, sustainable, and responsible business models in the years to come.

Regarding Organizational and Innovation Management in Healthcare, future research will address to deepen this topic in a context in which balancing the trade-off among environmental, social, and economic sustainable actions becomes an urgent priority.

Finally, in terms of Project Management in World of Research, Public Administration and Business Start Up, a research project aimed at studying the factors that influence the results of the Digital Transformation in the Public Administration is being defined. The research is carried out in collaboration with Association of General Managers of Italian University Administrations (CoDAU) The purpose of the research is twofold: (i) evaluate to what extent the digitization projects influence the perception of student secretarial staff with respect to their work efficiency, relationships with students and colleagues (back office), job satisfaction; (ii) verify which factors influence (positively or negatively) the above perceptions.