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This study aims to provide an overview of the past two decades of lifelong learning (LLL) policies for enhancing employability and reduce social exclusion in young people of European countries through the development of the so-called LLL key-competences.

Built on a quasi-systematic review, this contribution explores traditional and new methods for promoting the LLL transition, and then employability, in young adults (e.g. apprenticeship, vocational training, e-learning, etc.).

It argues the need to identify all the possible approaches able to support policymakers, as they can differently impact key-competence development.

Finally, based on the consolidated EU policy experience, we propose a strategy of implementation of the LLL programmes that facilitates the institutions’ decision processes for policy-making through the use of decisional support system.

The game plan firms must navigate in the quest of competitive advantage which is changing quickly. More and more firms acknowledge that future prosperity depends on achieving the joint goals of economic, environmental and social sustainability. This understanding has resulted in both firms and actors on the financial markets enhancing their focus on environmental, social and governance dimensions in their respective decision-making processes. In this chapter, the focus is on one key component of the changing game plan, the European Union’s (EU) Sustainable Finance Platform that envisions investors as a key driver of firms’ sustainability transformation. Based on survey data from Swedish listed firms, we discuss implications and outcomes of the Platform. Our results show that investors play an important role in setting the rules of the gameplan for firms. However, not to the extent that it meets the ambitions of the policymakers. This suggests either that the Platform will fail to meet its aims or that firms should expect further significant changes to the gameplan in the future.

To combat climate change, protect biodiversity, maintain water quality, facilitate a just transition for workers and engage citizens and communities, a diversity of stakeholders across multiple levels work together and collaborate to co-create mutually beneficial solutions. This paper aims to illustrate how a 7.5-year collaboration between local communities, researchers, academics, companies, state agencies and policymakers is contributing to the reframing of industrial harvested peatlands to regenerative ecosystems and carbon sinks with impacts on ecological, economic, social and cultural systems.

The European Union LIFE Integrated Project, Peatlands and People, responding to Ireland’s Climate Action Plan, represents Europe’s largest rehabilitation of industrially harvested peatlands. It makes extensive use of marketing research for reframing strategies and actions by partners, collaborators and communities in the evolving context of a just transition to a carbon-neutral future.

The results highlight the ecological, economic, social and cultural reframing of peatlands from fossil fuel and waste lands to regenerative ecosystems bursting with biodiversity and climate solution opportunities. Reframing impacts requires muddling through the ebbs and flows of planned, possible and unanticipated change that can deliver benefits for peatlands and people over time.

At 3 of 7.5 years into a project, the authors are muddling through how ecological reframing impacts economic and social/cultural reframing. Further impacts, planned and unplanned, can be expected.

This paper shows how an impact planning canvas tool and impact taxonomy can be applied for social and systems change. The tools can be used throughout a project to understand, respond to and manage for unplanned events. There is constant learning, constantly going back to the impact planning canvas and checking where we are, what is needed. There is action and reaction to each other and to the diversity of stakeholders affected and being affected by the reframing work.

This paper considers how systemic change through ecological, economic, social and cultural reframing is a perfectly imperfect process of muddling through which holds the promise of environmental, economic, technological, political, social and educational impacts to benefit nature, individuals, communities, organisations and society.

This paper aims to conceptualize the digital behavior of startups and investigate the emerging behaviors about digital strategies of the Italian startup firms enrolled in the Startup Act policy initiative. Digital technologies were divided into intra- and inter-organizational digital infrastructures, and this categorization offers startups the opportunity to identify a set of enabling technologies that could be used to improve their digital strategies.

An empirical analysis has been conducted to investigate the degree of adoption of digital intra- and inter-organizational digital infrastructures in the entire population of 6,178 Italian firms listed in the Register of Innovative Startups.

The paper proposes a taxonomy bringing together four startup behaviors for adopting digital technologies: digital follower, technical influencer, social influencer and digital leader. From the perspective of policy makers, considering the financial efforts that public authorities are supporting in the last decade, implications are mainly concerned with policy measures aimed both to reinforce the overall adoption of digital technologies and to develop a balanced adoption of intra- and inter-organizational digital infrastructures.

Measures addressed to support female and foreign entrepreneurship could be useful to support a more dynamic and well-balanced cultural and racial contamination, thus improving the adoption of digital tools.

This study investigates the impact of large-scale teaching in higher education on students’ preparedness for the workforce within the context of evolving labour market demands, the expansion of higher education and the application of high-impact teaching strategies. It synthesizes perspectives on employer work readiness, the challenges and opportunities of large-scale teaching and strategies for fostering a dynamic academia-industry feedback loop. This multifaceted approach ensures the relevance of curricula and graduates’ preparedness while addressing the skills gap through practical recommendations for aligning teaching methodologies with employer expectations.

The research methodically examines the multifaceted challenges and opportunities inherent in large-scale teaching. It focuses on sustaining student engagement, maintaining educational quality, personalizing learning experiences and cultivating essential soft skills in extensive student cohorts.

This study highlights the critical role of transversal skills in work readiness. It also uncovers that despite its challenges, large-scale teaching presents unique opportunities. The diversity of large student groups mirrors modern workplace complexities, and technological tools aid in personalizing learning experiences. Approaches like peer networking, innovative teaching methods, real-world simulations and collaborative resource utilization enrich education. The importance of experiential learning for augmenting large-scale teaching in honing soft skills is emphasized.

This manuscript contributes to the discourse on large-scale teaching, aligning it with employer expectations and the dynamic requirements of the job market. It offers a nuanced perspective on the challenges and opportunities this educational approach presents, providing insights for crafting engaging and effective learning experiences in large cohorts. The study uniquely integrates experiential learning, co-creation in education and industry-academia feedback loops, underscoring their importance in enhancing student work readiness in large-scale teaching.

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

The purpose of this research is two-fold: first, the researchers will create a reliable and valid hospitality senior exit survey by conducting a Delphi panel of experts and second, the researchers will pilot-test the instrument with students from a four-year university. The data will be (a) assessed to determine the retention of knowledge by four-year students, (b) used by academicians to make changes to course material and (c) used to help with the accreditation assessment process.

A Delphi panel of hospitality educators was used to validate the items, and graduating hospitality students were used to calculate reliability.

By embracing the hospitality exit survey (HES), institutions can effectively evaluate and enhance their programs. With its ability to gauge students' knowledge retention, the study findings serve as a powerful tool for shaping the future of hospitality education.

The study's findings might be somewhat limited in representing a broader range of perspectives within hospitality programs. Another limitation stems from the structure of the survey itself. The survey included numerous items requiring two inputs for each item. This format has the potential to introduce certain biases among participants.

In a positive statement, organizations can use this information to discover why employees stay and then continue to develop goals/strategies to ensure this process stays up to date. Academia is no different. Academia also wants to produce the best product, and since the students are to become the next set of leaders, these programs need to know what is successful and what needs to be adjusted.

A strategic exit interview program should 1)Uncover issues relating to human resources/students; 2) understand employees'/students' perception of the work; 3) managers'/directors' leadership style and effectiveness; 4) human resource/college/departments benchmarks and 5) improve the organization.

This research holds significant importance as it focuses on developing the senior HES and its potential utilization within hospitality programs. The HES serves as a valuable tool for these programs to evaluate the knowledge levels of their graduating students and collect data necessary for assessment and accreditation purposes.

Transportation infrastructure asset management has long been an active but challenging problem for agencies, which urges to maintain a good state of their assets but faces budgetary limitations. Managing a network of transportation infrastructure assets, especially when the number is large, is a multifaceted challenge. This paper aims to develop a life-cycle cost analysis (LCCA) based transportation infrastructure asset management analytical framework to study the impacts of a few key parameters/factors on deterioration and life-cycle cost. Using the bridge as an example infrastructure type, the framework incorporates an optimization model for optimizing maintenance, repair, rehabilitation (MR&R) and replacement decisions in a finite planning horizon.

The analytical framework is further developed through a series of model variations, scenario and sensitivity analysis, simulation processes and numerical experiments to show the impacts of various parameters/factors and draw managerial insights. One notable analysis is to explicitly model the epistemic uncertainties of infrastructure deterioration models, which have been overlooked in previous research. The proposed methodology can be adapted to different types of assets for solving general asset management and capital planning problems.

The experiments and case studies revealed several findings. First, the authors showed the importance of the deterioration model parameter (i.e. Markov transition probability). Inaccurate information of p will lead to suboptimal solutions and results in excessive total cost. Second, both agency cost and user cost of a single facility will have significant impacts on the system cost and correlation between them also influences the system cost. Third, the optimal budget can be found and the system cost is tolerant to budge variations within a certain range. Four, the model minimizes the total cost by optimizing the allocation of funds to bridges weighing the trade-off between user and agency costs.

On the path forward to develop the next generation of bridge management systems methodologies, the authors make an exploration of incorporating the epistemic uncertainties of the stochastic deterioration models into bridge MR&R capital planning and decision-making. The authors propose an optimization approach that does not only incorporate the inherent stochasticity of bridge deterioration but also considers the epistemic uncertainties and variances of the model parameters of Markovian transition probabilities due to data errors or modeling processes.

Site supervision features largely influence the productivity status of construction operational processes. This study aims to use a case study containing mixed methods to test the site supervisory traits in applying mathematical theories to construction operations for directing supervisory capabilities under various operational characteristics.

A total of 62 construction site supervisors were trained as part of a new apprenticeship programme. Through literature reviews and expert consultations, grading criteria were designed with various degrees of descriptions and score ratings. The supervisory attributes were evaluated under seven competency element characteristics mapped with the relevant learning domains.

The results demonstrate a detailed sectional view of performance ratings of supervisors under different characteristics of competency factors with the validity, reliability, applicability and generalisability assurance of the research findings using relevant statistical tests and expert evaluations.

Though the research applications were engaged directly with the construction industry in the Sri Lankan setting, other developing countries and emerging industries can also employ equivalent tactics to attain similar outcomes in their industry-based operations.

The research findings have led to producing a new guide that makes significant impacts on deciding the capability levels in construction supervisory attributes while executing problem-solving applications in construction planning and operational processes. Accordingly, the findings push to open a gate to intake advanced cognitive attributes towards addressing the industry's knowledge gap on how the problem-solving-based apprenticeship protocols need to be linked with the supervision features.

The purpose of this study is to conduct a systematic literature review that illuminates the current state of knowledge regarding the specific approaches by which multinational corporations (MNCs) implement corporate social responsibility (CSR) on the subsidiary level in developing countries.

Even though substantial scholarly work has been made to outline MNCs' activities in developing countries, this literature remains fragmented. To support the field in its theoretical as well as empirical advancements, this study conducts a systematic review of this body of literature and content analysis of relevant articles using insights from strategic marketing literature (market driving/proactive and market-driven/reactive approaches).

The authors synthesize our findings by presenting a taxonomy of proactive/reactive CSR approaches in developing markets along with propositions that can guide future research in this area.

Among the key contributions of this study's literature review is the development of a taxonomy of proactive/reactive CSR, bringing together different and fragmented streams of research and viewing them from strategic marketing (“proactive/reactive”) perspective. The taxonomy and the two ensuing propositions can advance future CSR-related studies with MNCs in focus by providing both theoretical and empirical guidance.