Theme & Track Topics

TRACK 1: 1. Education in times of shocks, crises and uncertainty

Under conditions of protracted uncertainty, education – and so education systems – around the world have been implicitly endowed with the role of anchors/stabilizers of social, political and economic order, domestically and internationally. Amidst uncertainty and change, education and education systems continue to equip the student with basic and common foundational knowledge and skills. In this way, they contribute to stability. However, education systems are also expected to equip students with the knowledge, understanding and skills necessary to face the challenges of the future. This prompts several questions:
• How can we ensure that students learn more, more efficiently, in line with a set of foundational liberal norms and values, while at the same time allowing the faculty to conduct research?
• How can the acquisition of digital skills by students be facilitated? What are the drivers of a smart use of technologies for teaching and learning? How can digital skills foster social change and lead to bridging the digital divide? How and to what extent does technology-enhanced learning reframe the interaction between users and the devices, and how can new ways of delivering an education service/ creating knowledge and a new culture of learning be co-developed?
• How can students’ and teachers’ acceptance of technology and digital skills (the psychological dimension) be fostered, and the digital divide and barriers to technology be reduced and the inclusion and democratization of technology (the social dimension) enhanced?
• What set of policy-tools, strategies and policies are needed to address the challenges and opportunities that education and education systems can deliver on?

TRACK 2:Smart cities and communities

While the debate on smart cities gains in momentum, it is necessary to examine smart cities, and so also the debate, through the lens of shocks and crises. Notably, our understanding of what smart cities are, what they are for and how to attain this, should and will be driven by the implications of prolonged uncertainty, be it economic, political, social, environmental, and other. In this context, several questions emerge:
• How will smart cities and the related political agenda behind their development adapt to these circumstances and face the challenges?
• How can the cul-de-sac of conceiving of smart cities only in terms of what is technologically possible be avoided? Which are the dimensions of smartness in the smart city context?
• How can they be accounted for? How can they be measured ?
• How can smart city performance be accounted for?
• How can such concepts as sustainability, liveability, well-being, resilience, innovation, etc. in the smart city context be reconciled?
• How can Industry 5.0. and Innovation 5.0. in the smart city context be conceived?

Track 3: Big data, business and society: Managing the distributed risks and opportunities

While big data embodies paradigmatic shift in the way data can be gathered, organized and processed, and consequently information can be produced, it also remains a vague and a misunderstood concept. The imperative that the research community needs to undertake is to ensure that the salience of the big data paradigm is translated into tangible benefits, including applications, processes, and solutions, for society at large. From a different angle, considering the scope of the challenges to our societies, including the business sector and the economy (local, regional, global) that we face today, it is equally important to query the specific mechanisms behind the opportunities that big data may generate, e.g. the benefits of a data-driven approach for businesses and organizations and the potential threats inherent in big data. In this context, the key questions that need to be addressed include:
• What dynamic capabilities are required to address complexity, to challenge technological evolution and foster the adoption of data-driven orientation in organizations (public and private)?
• How can security and privacy risks be managed?
• What is the connection between big-data-driven strategies and business model innovation (BMI)?
• How can the vulnerabilities of databases be reduced to improve data security?
• What kind of skills are necessary to support the process?

TRACK 4: Management: Rethinking management in times of profound change

Over the past two years, the global health emergency, natural disasters, the climate emergency, the war in Ukraine and the subsequent economic, political, and social and societal crises have been threatening the business sector. The recovery from these shocks and disrupting events, which can bring rupture and relating risks, can present many challenges. However, these events can also offer companies multiple opportunities for growth, development, and possibly expansion. In this context, smart and digital technology may serve as the key levers for the co-development of innovative and sustainable ways of navigating the variety of challenges that business should face. Companies that adopt smart technologies can be reread as complex ecosystems and smart service systems in which multiple relationships between different actors are established to provide various kinds of services through constantly technology-mediated interactions. Hence, contemporary research on management should investigate the most efficient strategies designed and adopted by companies to exploit the opportunities offered from contemporary crises. Studies on business’ ability to overcome crisis and to prosper after recovery can address a variety of multi-disciplinary questions.
• How can contemporary businesses and organizations develop readiness to change and adopt a proactive attitude to attain continuous improvement and develop resilience?
• In which ways the service ecosystems perspective may be helpful in pre-empting risks and mitigating the implications of crises?
• In which ways do digital transformation and the relating smart and digital technologies contribute to the effort to address the challenges of global and local scales? Is technology an instrument, an enabler or a multiplier of value?
• How can business models be redesigned to increase sustainability in VUCA times?
• How can technological ecosystems reframe operations, and value chain and supply chain management to improve flexibility and business transformation?
• How can digital technologies support decision-making, policy-making and governance in the complex process of recovery from shocks in companies, institutions and cities?
• Can digital technologies improve value and knowledge creation in smart service systems and ecosystems and enable innovation?
• How can economic recovery be balanced with social needs to pursue sustainability and enhance social inclusion, well-being and resilience?

TRACK 5: Innovation, entrepreneurship, and innovation management in the era of Industry 5.0.

Innovation is key in the challenge inherent in a period of crisis and transformation such as the one we are facing. Rapidly changing technology, business models and social behavior are essential to overcoming the multifaceted implication of the Covid-19 pandemic, of the war in Ukraine and of the mounting energy crisis. The discipline of innovation management, traditionally associated with the management of structured processes in large firms, has recently developed to overlap with the discipline of entrepreneurship. That is, large firms and start-ups are increasingly seen as actors that collaborate and compete through emerging and traditional industries. It has recently been highlighted that an excessive focus on technology can be counterproductive and that, instead, aspects related to the human being must always remain central. With this in mind, we talk more and more often about Innovation 5.0.

Consequently, the key questions that need to be addressed include:
• How can resilient, human-centered innovation ecosystems be built?
• How can the fields of Entrepreneurship and Innovation Management contribute to a better understanding of innovation ecosystems?
• How do innovation processes change in these times of crisis, and how can they help overcome them?
• How does technology interact with individual, organizational and social aspects to shape the so-called “new normal”?
• How can the connection between innovation, Innovation 5.0. and business model innovation be conceptualised?
• How can innovation help overcome the energy crisis?
• What are the differences between the Innovation 5.0 paradigm and previous approaches?
• Is there a dark side of innovation? How can its negative effects be prevented?

TRACK 6: ICT and the medicine and healthcare cluster

At the heart of the Industry 5.0. paradigm, lies the recognition that (digital) innovation and its application in the form of services, products, and processes need to serve the triple imperative of being sustainable, human-centric and geared toward resilience of industry, the economy and society. The transition to the broadly defined Industry 5.0. paradigm is accompanied by groundbreaking developments and ideational shifts in several branches/subsectors of industry, including the medicine and healthcare cluster. The impact of digital technologies on this broad and highly diversified cluster is profound and spans areas ranging from (big) data management, through new diagnostic opportunities, new approaches to treatment, to novel ways of managing the healthcare system.

While research addressing each specific aspect of this (in fact, digital transformation of the medicine and healthcare sectors flourishes), many of these interconnected topics are discussed separately from each other, while at the same time the dialogue between practitioners and academics remains vague. What follows is that the exploratory and explanatory potential inherent in current research and practice remains under-utilized, effectively undermining the possibility of attaining the imperatives related to the Industry 5.0. paradigm in the medicine and healthcare cluster.

Recognizing the expertise and the ideas of medicine and healthcare practitioners, as well as the needs of patients, the objective of this track is to encourage dialogue between the research community engaged with the topics at the centre of current ICT development of ICT (big data, artificial intelligence (AI), machine learning (ML), quantum computing, cognitive computing and others) and their application in the medicine and healthcare sector (including big data-driven diagnostics, AI-based predictive models, and others) and practitioners engaged in day-to-day work with patients. Ideally, the encounter of these two communities will allow us to take a holistic and multi-disciplinary view of the question of how to ensure that the patient receives the full benefit of the profound developments taking place at the intersection of ICT, medicine and healthcare. While several topics in the so- defined domain will remain highly specialized and will be discipline- and field-specific, a great number of topics exist that require a conversation and, indeed, research involving experts and practitioners from diverse fields and disciplines. The objective of this track is to enable that to happen.

Researchers and practitioners interested in joining the Rii Forum 2023, to engage in conversation on these topics, may consider the following items/discussion points:
• big data-supported diagnosis, prediction and treatment of patients with diverse illnesses and conditions;
• data-mining for patients’ extended history and diagnosis;
• data-supported prognostics and identification of the most efficient treatment, including customized pharmaceutical care;
• ICT-enhanced patient-centred tools and instruments, including customized apps, wearables, and others, for efficient treatment of specific illnesses and conditions;
• ICT-enhanced tools in the context of care of the elderly;
• good and bad practices in diagnostics and patients’ care
• transcranial magnetic stimulation (TMS)
• the challenge of privacy, data protection, cyber-security: issues, problems, ways of addressing them;
• business and managerial considerations;
• regulatory approaches and public policy tools in the domain of the medicine and healthcare cluster.

TRACK 7: Data-driven approaches & human resource management in the era of digitalization

In the era of digitalization, organizations adopt data-driven decision-making in various aspects of business, while big data is now commonly used in day-to-day activities. The same applies to human resource (HR) departments. HR management must therefore evolve into a true autonomous decision science in order to guide, analyze and improve decisions inherent in the workforce. Indeed, given the harsh competition in the marketplace, organizations need to invest wisely in their human capital to build and maintain their competitive advantage. This also means that the need to align their HR strategies with the overall business strategy. In fact, organizations have at their disposal plenty of information related to their workforce that, when combined with external resources, can be treated as big data. As such, if approached with an open mind and appropriate analytical tools, it can offer useful information for business-driven decision-making.

In this sense, HR analytics, i.e. the use of data, analytics and systemic reasoning in relation to the people involved and/or connected to the organization, is an emerging discipline that can enable the HR department to fulfill the promise of becoming a true strategic partner for organizations. Indeed, the use of HR analytics is a powerful means at the disposal of the HR function to understand the impact of HR practices on organizational performance and to create value for the organization, enabling the HR department to increase its influence on business decisions and future corporate strategy.

However, as a relatively new practice, HR analytics is often only superficially understood by organizations, especially in terms of the benefits it can provide and the impact on business outcomes it can produce. In addition, the academic literature regarding the practice is still underdeveloped and still presents significant discrepancies in reference to approaches, definitions, outcomes, and potential issues that may arise. There is still no agreement regarding the meaning of HR analytics, as well as the processes, competencies, and skills needed for HR analytics to improve HR strategy, workforce decisions, and individual and organizational performance.

In this sense, some of the key questions to be answered are:
• What capabilities and skills are required for the successful implementation of HR data driven approach within organizations?
• What are the main obstacles to the successful implementation of a data driven approach within organizations?
• How does HR analytics impact organizational performance variables?
• Which synergies need to be created both within and outside organizations to expand the impact of HR analytics?
• What are the privacy and ethical implications of the usage of HR data?
• What is the perception of different stakeholders (internal and external to the companies) of a data driven approach with regard to people and human behaviors, and how to improve it?

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