List of tracks
- The entrepreneurial finance landscape in the era of digital technology
- The governance of higher education among systemic performances, new policies and institutional responses
- The role of digital technologies in design thinking: emerging issues for the organizations of the future
- Connected care: embracing value-based healthcare ecosystems through digital innovations
- Understanding and running complex systems: issues and methods
- Challenging the future of global production networks: the role of political changes, digital technologies and migrations
- Data science for innovation and the future of work
- Family companies at the edge of societal and technological change
- Public service innovation: challenges, risks and opportunities in a fast changing world
- Sharing economy and online multi-sided platforms: effects on traditional businesses
- Sustainable business models & circular economy
Track 1: The entrepreneurial finance landscape in the era of digital technology
Politecnico di Milano – Department of Management, Economics and Industrial Engeneering
Via Lambruschini 4b, 20156, Milano
Phone: +39 0223998040
Short description of the proposed track
Digital technologies such as artificial intelligence, data analytics, digital platforms, social media and blockchain are increasingly reshaping the financial services sector and the entrepreneurial finance ecosystem. Digitization has transformed dramatically entrepreneurs’ business models and their connection and interaction with traditional financial providers. At the same time, digitization has opened new channels, expanding the financing options available to start-ups and SMEs.
Different types of alternative financing mechanisms, such as crowdfunding, peer-to-peer lending, business incubators and accelerators, initial coin offerings (ICOs) have complemented traditional venture capitalists (VCs) and business angels (BAs) as providers of external capital to innovative companies. These new financing channels besides offering many advantages to both start-ups and established ventures, also bear new risks for investors and the efficiency of the financial ecosystem, including the risks of new speculation bubbles, frauds or even the development of new equity funding gaps. Indeed, the emergence of these new funding sources raise questions about their ultimate impact on financial markets and entrepreneurship, and on how policy makers can cope with them.
Indeed, new financing channels have increased the complexity of the entrepreneurial finance landscape, in particular they are continuously changing the relationship between the different actors of the financing ecosystem and start-ups’ financing pipeline. Research aimed at studying the interaction between two or more different financial mechanisms, both simultaneously (co-investments) and over time (sequential investments over different financing rounds) are warrant for understanding the long term impact of these forms of finance on the entrepreneurial ecosystem.
Finally, digital technologies saw the rise of a new type of entrepreneurial ventures active in banking and insurance sectors. These fintech or insurtech start-ups have already collected billions of dollars of investments around the world, yet there is little research about the specific role of these companies, their success drivers, their impact on other entrepreneurial companies or incumbents and their fundraising process.
Thus, the track aims at collecting and discussing original papers that will shed light on these recent issues in the entrepreneurial finance literature, especially considering how the digital technologies brought change to the entrepreneurial finance landscape. Possible topics include, but are not limited to:
- How is FinTech transforming start-up financing?
- How are FinTech start-ups different in terms of fundraising process?
- What is the role of alternative platform-based financial channels in the entrepreneurial finance ecosystem? For instance, what is the post-investment performance of crowdfunding campaigns?
- What role do social capital and the positioning of investors into a network play in securing investments from alternative financing providers?
- How do traditional and new investors interact?
- How do BAs and angel networks engage with other forms of financing? Are the relationships between VCs, BAs and crowdfunding characterized by complementarity or substitutability?
- How is the digital transformation influencing VCs’ and BAs’ investment process?
- Which are the new funding paths of start-ups characterized by an original combination of investors?
- What is the role of ICOs in the financing ecosystem?
- What is the impact of ICOs on the evolution of crowdfunding and other funding sources?
- What is the role of cultural and geographical distance in this new entrepreneurial finance landscape?
- What is the impact of digitization on regional equity gaps?
Venture Capital, Crowdfunding, Business Angel, Fintech
Track 2: “The Governance of Higher Education among Systemic Performances, New Policies and Institutional Responses: state of the art and future developments”
Cinzia Daraio, Department of Computer, Control and Management Engineering Antonio Ruberti, Sapienza University of Rome, e-mail: email@example.com, tel.(+39) 06 77274 068.
Short description of the proposed track
In spite of experiences in dealing with financial and economic crises, public spending in science and higher education as a counter-cyclic measure is far from being a reality in Europe, with the notable exception of Germany and the Nordic region. The challenges and opportunities for Europe are immense, independently if they are global, national or local. In this setup, an adequate policy framework not only helps mediating the interface between science, higher education and society, but also contributes to shaping systems, strategies and development patterns.
Higher education institutions play a crucial role for economy and society as they are not only producers of knowledge that is codified in scientific publications and embodied in university graduates, but they also contribute to economic growth and competitiveness by creating new opportunities that can be exploited commercially (e.g. Rothaermel et al. 2007; Perkmann and Walsh 2008; Bonaccorsi et al 2013).
Within this context, a relevant question is: Which types of public policies for science, technology and higher education for the coming decades, both for individual member states as well as the EU as a whole, are necessary?
This question can be further refined as follows: Which governance regimes are more conducive to the better performance of the higher education systems? Which characteristics of national policy dynamics (i.e. interactions among political, socioeconomic and ideational factors) determine specific choices in terms of governance regimes? Which institutional characteristics permit a coherent pursuit of the system’s principal systemic goals? What changes in the governance regimes have to be implemented to achieve better levels of competition, differentiation, institutional profiling and accountability of the higher education, science and technology systems? Which governance arrangements are associated to a better performance of the higher education system, and which, on the other hand, are ineffective in this respect?
What emerges from the current state of the art is the need for a systematic, multilevel, multi-methods analysis capable of taking into account the complexity of the phenomenon and its multifaceted (and often interconnected) dimensions.
Within this framework, the implementation of evaluation exercises play an important role.
New opportunities and challenges are offered by the availability of new data and new methods and approaches.
In the last few years, several initiatives at European level have been based on an intense production and use of new data. In the field of data on universities, the pioneering efforts of Aquameth (Daraio et al., 2011; Bonaccorsi and Daraio, 2007) and subsequently of Eumida (Bonaccorsi, 2014) have been transformed in an institutional initiative called ETER (European Tertiary Education Register), which has made publicly available microdata on universities in 2015 and will publish new data in 2016 and 2017. These efforts from Europe have a major counterpart on the other side of the Atlantic, where the STAR Metrics initiative (see https://www.starmetrics.nih.gov/) has promoted a federal and research institution collaboration to create a repository of data and tools that is producing extremely interesting results.
All these efforts, however, are based on the construction of new datasets, or the integration of existing datasets into new ones. They do not solve the issue of comparability and standardization of information and of inter-operability, updating and scalability of databases (Daraio and Glanzel, 2016) however, recent developments in engineering in computer science could be helpful and should be further explored to address these issues (Daraio, Lenzerini et al. 2016).
In the following we report some specific issues that could be helpful in understanding some of the mechanisms that influence the systemic performance and the impact of the higher education system and its interrelationships with science and innovation systems.
- Needs and emergence of new research, teaching and third mission assessment models and support tools.
- Opportunity and challenges for the assessment of the efficiency, effectiveness and impact of education in the Big Data era
- Mobility of EU students, researchers and citizens, including detailed analysis for STEM and emerging issues associated with the impact of immigration policies on science, technology and higher education.
- Emerging issues in industrial policy, innovation networks and growth through a multi-institutional framework, including the need to consider collective action of a quite large range of institutions and funding agencies.
- The unequal evolution of Higher Education and Research organizations in different EU regions/nations, including emerging governance structures for science, technology and education in Europe, including the changing nature of the state and policy advise, as well as the debunking of public and private myths.
- The impact of higher education institutions’ activities on local economic development.
- The multiple interactions between knowledge production and diffusion with urban dynamics and the need to foster smarter citizens and the continuous designing of cities for knowledge.
- The internationalization of HE and Research organizations, as a potential way to improve and leverage EU strategies for growth and social cohesion.
Higher education, governance, performance evaluation, multidisciplinary analysis, quantitative methods
Track 3: The role of Digital Technologies in Design Thinking: Emerging issues for the organizations of the future
Lorenzo Ardito, Università Campus Bio-Medico di Roma,06225419633, firstname.lastname@example.org, 06225419633
Stefano Magistretti, Politecnico di Milano stefano.magistretti.@polimi.it, 0223994093
Short description of the proposed track
Scholars and practitioners acknowledge the central role of design as a driver of innovation and change (Brown, 2008; Martin, 2009; Liedtka, 2015). In a way, the importance of design as a source of value creation has been scrutinized for decades (Peterson et al., 1986; Hirschman, 1986). Most of these investigations, however, have only considered design as the aesthetic and symbolic dimension of products, i.e., design as “form”, identity, and emotions, which underestimate the full role of design in the realm of management studies (Capaldo, 2007; Dell’Era and Verganti, 2010; Dell’Era et al., 2017). Indeed, the perspective on design is changing. Design is not only an aesthetic driver of innovation but a whole management practice that leads to a new set of processes, mindsets, capabilities, and organizational settings to meet organizational goals (Micheli et al., 2019), more recently referred to as design thinking (Brown, 2008; Martin, 2009).
Design Thinking is usually characterized by three traits: the human-centered perspective, where innovators build empathy with users; the leverage of creativity as a driver of innovation; and the intense use of visualization techniques and prototyping as rapid and effective sources of communication and learning among stakeholders (Brown, 2008; Lockwood, 2010). In this context, firms adopting new digital technologies develop more dynamic capabilities (Teece et al., 1997) that help them support such traits. Part of these dynamic capabilities, in fact, collapse with typical design thinking capabilities developed through design thinking, e.g., iterating, user-centricity, problem-solving in response to changing conditions, user engagement, and rapid prototyping. (Burdick & Holly, 2011). For example, in order to speed up the process of learning in iteration and prototyping, 3D printing solutions and Virtual Reality are permeating design thinking processes to boost learning throughout prototyping. Moreover, the advent of Big data opens up novel opportunities to gather a huge and wide variety of information about user needs/product-user interactions in a timely manner, and augmented reality may provide new tools for improved user engagement by relying on such big data. Finally, human-centered problem-solving abilities are nowadays more and more supported, or even delegated to Artificial Intelligence (AI) systems. Thus, the emerging presence of digital technologies in design thinking approaches can be recognized in the managerial practice but is still not adequately examined by academic studies.
Therefore, the track aims at reconnecting the design-based innovation methodologies with the challenges offered by digital technologies. In particular, the purpose is to critically reflect on the opportunities and limits that digital technologies provide to design thinking.
Theoretical and empirical contributions may address but are not limited to the following topics. Both qualitative and quantitative research approaches are welcomed to shed lights on the relation between digital technologies and design thinking.
Design thinking and digital transformation
- (How) Is design thinking changing/improving in light of digital transformation?
- How does digital transformation support design thinking?
- In which situations digital design thinking is more likely to be relevant (e.g., turbulent and uncertain situations)?
- How can digital technologies support and empower design thinking processes?
- Which theories (e.g., digital innovation, dynamic capabilities, creativity) should be considered/integrated to better explain the design thinking-digital technologies relationship?
The digital side of design thinking
- Which digital technologies are related to the diverse traits of design thinking? How?
- How the adoption of digital technologies can valorize design thinking?
- Which are the opportunities and threats that digital technologies offer to design thinking?
- (How) Does digital design thinking modify/affect a firm’s innovation process and outcomes?
- How are design-related methodologies integrated with digital technologies?
The organizational side of design thinking
- Which organizational performance (financial, creative, innovative, etc.) Are affected by digital design thinking? At what level of analysis (e.g., single individual, group, organization, supply chain)?
- What are the main individual and organizational barriers toward the integration of design thinking practices and digital technologies?
- Do organizational, team, or individual characteristics moderate or mediate the relationship between digital design thinking and performance?
The human side of design thinking
- Which individual competences, skills, and capabilities are required to support the adoption of digital technologies in design thinking practices?
- How the human side of design thinking is affected by digital technologies?
- What are the traits of digital “design thinker”?
Design Thinking, Digital Technologies, Digital Transformation.
Track 4. Connected Care: Embracing Value-based Healthcare Ecosystems through Digital Innovations
Luca Gastaldi, Politecnico of Milan
+39 02 2399 4046
+39 339484 7472
Short description of the proposed track
Healthcare is a paradigmatic example of a knowledge-intensive industry, characterized by salient and peculiar trends, and specific barriers to entry. The urgent needs of the healthcare systems and its decision makers are related to the recombination of consolidated knowledge assets, with the aims of (1) rethink needs, organizations and solutions, linking data with people; (2) creating better information and optimizing the delivery of services. The progressive availability of new sources of data, information and evidence – as well as the increased capability to elaborate them – is offering the unique opportunity of developing a huge ecosystem that might disrupt what we know about healthcare delivery.
Moving from these premises, digital innovations, have the potential to improve healthcare outcomes and reduce the related management costs, being useful to rethink the way in which the delivery of healthcare services could be guaranteed to citizens, and improving Value-base Healthcare principles, even in a condition of scarce resources, such as in the Italian public sector.
However, they often fail to produce the expected results due to the lack of a coherent innovation ecosystem able to support and complement the initiatives undertaken within single organization. In order to fully exploit their potential, digital innovations should be implemented through the orchestration of multiple actors (i.e., hospitals, general practitioners, community pharmacies, social-care providers, etc.), who operate at different levels in the services delivery (Dougherty and Dunne, 2011). Furthermore, in order to be effective, digital innovation should contaminate the whole healthcare chain, ranging from the adoption of innovative technologies (drugs, medical devices, diagnostic and clinical procedures/protocols, as well as clinical pathways), to the implementation of evidence-based approaches, capable of supporting the decision-making process (and, thus, being capable of measuring healthcare outcomes). Digital innovations also offer the possibility to use data for the development of healthcare management software that may be useful to decision makers.
This track aims triggering discussion on digital innovations to better understand the challenges in implementing new healthcare innovations, and to identify solutions as well as the needs and perspectives of various stakeholders, scholars and practitioners, across the whole healthcare sector. Moreover, it intends shedding light on how digital technologies may facilitate the cooperation among multiple actors in the delivery of cross-organizational healthcare services, and how they may impact the performance (in terms of efficiency, effectiveness, quality and organizational factors).
In order to narrow the present gap, this track invites scholars of different disciplines, such as healthcare management, operations management, innovation management, information science and evidence-based management, to share their latest research about exploration and exploitation in healthcare sector with respect to digital health and digital healthcare ecosystems. In particular, this track welcomes qualitative and quantitative contributions, both empirical and reviews, for deep understanding how healthcare organizations could leverage on digital health, pursuing multiple performance objectives.
In this regard, the proponents of this track aim collecting original, mature contributions to stimulate the debate among attendees, concerning the role that digital innovations might play in improving healthcare.
More specific, the following topics are welcome.
- Which is the current adoption level of digital technologies in the healthcare settings?
- How the adoption of digital technologies may improve the performance of healthcare services, both from an intra and inter-organizational perspective?
- Which is the current integration and digitalisation levels of the different actors (i.e., hospitals, general practitioners, community pharmacies, assurance’ institutions, etc.) involved in the delivery of complex healthcare-based, territorial services (e.g., clinical home support to people with chronic diseases)?
- How digital technologies might help designing value-for-money services about primary and secondary prevention? What about their role in facilitating the adoption of healthier lifestyles by citizens? What about healthy ageing through digital technologies?
- Which could be the levers (e.g., technological, policy-based, etc.) that can be used to accelerate the development of an effective digital innovation ecosystem in healthcare?
- Which new competencies should be developed by all actors in the healthcare arena? How should both patients and professionals be empowered through new competencies and fully exploit the value of digital technologies?
- How data-driven techniques may be used in order to analyse inter-organizational processes and evaluate the performance of an ecosystem of digital innovation in healthcare (in terms of both efficiency and effectiveness)?
- How performance could be measured and collected through digital technologies in the healthcare settings, to facilitate the generation of evidence-based policies and strategies?
- Does an evidence-based approach to management and organization facilitate the still difficult dialogue among different professionals in healthcare, as advocated by clinical governance principles?
- What about the emergence of digital health start-ups and new entrepreneurial digital ventures in healthcare? Which are the main barriers/enablers of their growth? How hospitals and other healthcare organizations might benefit from them, through the development and adoption of innovative open innovation strategies?
- Which are the most relevant experiences about the implementation of value-based healthcare strategies and initiatives through the use of digital technologies?
These topics are original and pave the way to enlarge existing research, being something that literature has not yet completely investigated, within the specific healthcare context. Expected contributions may deal with either methodological/theoretical issues or empirical investigations.
The proponents of this track are available to broaden its scope to other professional and knowledge-intensive contexts, where digital innovations are expected to play a key role in the improvement of healthcare.
Track 5: Understanding and running complex systems: issues and methods
Short description of the proposed track
This track deals with complexity of organizations and their environment, a common subject in management literature. Understanding the drivers of complexity and the general features characterizing complex systems has become a new imperative in economics and management research. Methods and tools of “complexity” can help identify future directions in organizational issues.
Complex systems of interdependent agents can be found everywhere at multiple scales, from the macro level, including industries, markets, and countries, to the micro level, involving firms and individuals. Therefore, modern organizations have to deal with a broad range of problems that present different configurations of complexity, such as: 1) diversity and heterogeneity of agents and their links, 2) interdependent structures among agents, 3) ambiguity of available information and 4) environmental dynamics.
One of the most important ingredients of complexity is network theory, which investigates structures and dynamics of interaction between social actors. It aims at revealing the principles that make networks more robust and efficient, considering a risk of failure, possibly induced by increasing interconnectedness.
Investigating economic complexity calls for dynamic approaches. They permit to model complex system behaviors, reproducing the internal dynamics of the entire system from the bottom, focusing on its micro attributes such as the agents, their attributes, actions, goals, and the network structure connecting them. In this regard, methodologies based on agent-based modeling, networks, system dynamics, evolutionary game theory, percolation theory are very suitable.
Also, the recent advent and spread availability of new technologies for massive data collection, e.g. wearable sensors, is offering the opportunity of measuring and evaluating complex network dynamics through data-driven methodologies. Providing automatic and more objective measurements of individual, team and firm behaviors, these tools can efficiently collect a very big amount of data in real time – increasing the data richness, quality, and reliability – and effectively support scholars in order to analyze complex systems.
The aim of this track is to attract empirical and theoretical contributions that use these approaches and address the topic of complexity. Particularly welcome are papers adopting innovative theoretical and empirical methodologies. We invite research which investigates: the drivers of complexity in business networks, such as supply chains and industrial clusters, as well as financial systems; the heterogeneity of actors’ behaviors, process coordination and link-formation mechanisms in different business domains; analyzing the relationship between complexity and resilience, fostering sustainability of the economy, innovative and unconventional policy and regulation measures.
Research which digs into the complexity of big data is also welcome. In particular, while text mining and network analysis have evolved into mature yet still quickly advancing fields, work at heir intersection lags behind in theoretical, empirical, and methodological foundations.
Track 6: Challenging the future of global production networks: the role of political changes, digital technologies and migrations
Politecnico di Milano
Short description of the proposed track
Production networks have been subject to a dramatic internationalization phase during the last decades, driven by the possibility to exploit location economies and to take advantage of new large and growing markets (such as India and China). This process involved not only manufacturing but also service industries and not only labour- but also knowledge-intensive activities. However, new trends are challenging the future of global production networks, such as the recent political changes, the mass-migrations and the raise of new technologies.
As regards the former, we refer to the recent rise of nationalisms and populisms, which are political movements that reject the elites and the status quo and that emphasize the role of the national (against the international) contexts. Some examples are the “America first” of U.S. President Trump, the Brexit affair in UK, and the predominance of nationalist parties in several European countries during the last European elections (e.g., Italy, France, Poland, Hungary etc.). Some consequences of this political change are the rise of protectionism (see e.g. the recent trade war between U.S. and China) and an increasing aversion towards globalization and the delocalization of manufacturing activities. This strong feeling is amplified by the increasing competition that European and U.S. firms are facing from emerging countries, which nowadays account for more than one third of cross border investments and which are increasingly acquiring firms in advanced countries to move from low- to high-value added activities across the value chain. In this regard, the cross-border M&As from China and India is also boosting the political and economic weight of these two countries in advanced economies. All these political issues are pushing policy makers to set-up policies that discourage investments of domestic firms in foreign countries and that re-attract manufacturing activities located abroad back to the home countries (i.e. back-reshoring). At the same time, firms are re-thinking their location choices, by moving from one country to another in search for better political and economic environments (i.e. further off-shoring).
A second challenge is arising from migrations, which involve about 250 millions of people moving across borders all over the world, who are driven in 90% of the cases by economic reasons and who are directed in almost two-thirds of the cases from developing to developed countries, where they often fill key occupational shortages. Despite being often perceived as a potential source of problems by public opinion, they can also represent an opportunity to boost international business. Indeed, they can act, first of all, as facilitators for their employers when the latter decide to undertake trade and FDI initiatives involving the migrants’ country of origin, as the latter can reduce transaction and information costs by providing valuable knowledge concerning their country of residence. Additionally, migrants can directly encourage foreign direct investment through referrals and personal business networks, and by reducing the cultural distance with respect to their country of origin. Finally, they can assist the country of origin development through remittances, return migration and “nostalgic trade”.
Finally, a third challenge arises from the so-called “Digital manufacturing revolution”, which is offering the possibility to increase productivity and decrease production costs (e.g. through additive manufacturing), to trace each face of the value chain (e.g. through the IOT), to globally outsource production to the final customer (e.g. through 3D printing) etc.. In this regard, digital technologies are expected to deeply influence several aspects of firms’ business models, processes, and value propositions in terms of, e.g., increased speed and customization, reduced labour intensity, stronger integration among the various business functions, increased R&D intensity of manufacturing activities, etc. As a consequence, the emergence of novel manufacturing technologies is both altering the relevance of the input factors and pushing firms to re-think whether manufacturing should be kept in-house or outsourced and offshored. Hence, new technologies will play a pivotal role in driving the future choices on where to locate firms’ value chain activities (i.e. the location choice) and how they to manage them (i.e. the entry mode choice). For instance, firms like Uber, AirB&B and Facebook, which are the biggest taxi, accommodation and media companies in the world, respectively, are already exploiting new technologies to globally outsource the taxi service, the accommodation provision and the media production, respectively, thus relying on a new business model where the core-activity is the platform rather than the service. At the same time, additive and smart manufacturing allow to substitute labour with capital, thus reducing the importance of location economies (e.g. in terms of low cost of labour) and offering the opportunity to undertake re-location choices such as back-reshoring and further offshoring.
Therefore, all the functional areas that are typically involved in cross-border investments are potentially affected by these new trends, from international business to international management, from international operation to global value chains, from international human resources to international marketing, from international finance to international entrepreneurship. However, researchers are often fragmented among different fields. As a consequence, research findings generated in a certain field/sub-field are not always known by scholars belonging to another one and cross-fertilization is not activated. Based on such evidence, the proponents are willing to organize a track offering the possibility to scholars coming from different academic communities to share their research regarding the firm’s internationalization process and, above all, how the aforementioned new trends are affecting the cross border investments. We are willing to adopt and to bridge multifaceted perspectives, which includes strategic, managerial, operation, global value chain, human resource, marketing, financial and entrepreneurship points of view, all sharing the focus on cross-border investments and all discussing how the new trends are affecting the main phenomena that are studied in each field. The proposed track is also based on the evidence that, within the AiIG community, there are several scholars belonging to the International Business, International Management and International Supply Chain and Operations fields.
political changes, migrations, digital technologies, international business and management, international supply chain and operations, global production networks and value chains
Track 7: Data Science for Innovation and the Future of Work
Università di Pisa
Short description of the proposed track
The information field has changed dramatically over the past years, affecting the economy, technology, culture and society. However, these changes have left an even stronger mark on business systems (Rai 2006, Jin 2015, Degryse 2016). Considering the mass of digital information produced in the past 10 years, companies have found themselves in a chaotic and constantly expanding digital universe. To innovate and stay competitive, companies must master methods and tools to prevent information overload, while gaining useful knowledge from the available data (Levitin 2014, Feng 2015).
The discipline of Data Science has emerged as a clear (although broad) field of research to solve data-related problems. Data science is an interdisciplinary field that uses scientific methods to extract knowledge and insights from structured and unstructured data. It attracts researchers and encompasses methodologies from wide-ranging fields such as statistics, mathematics, information science, computer science, data analysis, machine learning and communication and is therefore an ideal tool to bridge the gap between research, industry and society.
The objective of the present track is to collect works that use state-of-the-art Data Science tools and techniques to gather, transform, model and visualize data to gain valuable information relevant for firm innovation. The scope is to use publicly available data to obtain a clearer view of which information sources contain the most untapped value and which methods and tools can be used to uncover it.
The main contributions are expected to highlight:
1) Information relevant for different companies to build knowledge as a tool for innovation, in particular related to:
– data science for product innovation: e.g. data-driven product development, A/B testing, patents analysis, product success evaluation, machine learning for innovation.
– data science for competitive intelligence: e.g. brand analysis, competitors mapping, partners individuation, tools for knowledge visualization and communication.
– data science for open innovation & co-creation: e.g. papers mapping, open analytics, IP analysis, cloud computing.
– data science for new skills identification & mapping: e.g. curricula analysis, job vacancies identification, job creation, new skills for innovation.
We expect to see contributions coming from the usual sources (e.g. open databases, patents, papers, social media) but we especially welcome contributions from less-known sources.
2) Tools that can be used to extract valuable knowledge from the raw data. Since Data Science is broad, we expect to showcase a wide range of methodologies such as machine learning, deep learning, natural language processing, image analysis or tools for data visualization and communication, to name a few.
The track will include two different formats: (1) a classic paper presentation session and (2) an idea pitch session.
Seeing the broad intersect between the research field and practical needs of companies, the idea pitch session will be held in conjunction with scholars and representatives of industry, such as ErreQuadro, ADECCO, Fondazione Giacomo Brodolini, Fondazione Bruno Kessler. The idea pitch session will be focused on a specific track sub-topic – data science for new skills identification & mapping – and it will be orchestrated by prof. Gualtiero Fantoni, Università di Pisa.
Data science, innovation, machine learning, skills
Track 8. Family companies at the edge of societal and technological change
Associate Professor of Strategy and Family Business
Politecnico di Milano School of Management
+39 02 2399 9594
Short description of the proposed track
Family companies are highly prevalent across countries and industries, including the majority of private firms as well as a significant proportion of publicly traded companies. Research on family companies is important not only because of their economic dominance across the world, but also because they share distinctive features that influence key dimensions of management, including strategy, innovation and entrepreneurship. While commonly depicted as risk-adverse and reluctant to change and grow in order to avoid dilution of family control or loss of socio-emotional wealth, many of the world’s largest and most dynamic multinational companies are family companies, and they are often at the edge of societal and technological change.
We invite authors to submit high-quality research paper that address the key challenges and dilemmas that confront family companies in order to grow and succeed in today’s increasingly dynamic and competitive business world. We particularly encourage submissions that address the nexus between strategy, innovation and entrepreneurship in family companies, including (but not limited) to the following research areas and questions:
Strategy in family companies:
- How do family companies compete at the edge of societal and technological change?
- What are the major drivers of strategy in family companies? How are those drivers changing over time?
- How do family companies develop and sustain competitive advantage and superior performance?
- How do family companies manage the tensions between financial and non-financial goals in strategy making?
Innovation in family companies:
- Are family companies innovative? Do they innovate differently from non-family companies?
- How do family companies address major technological and societal changes with innovation?
- What role does family tradition and history play for family companies’ ability to innovate?
- Does generational succession favor or constrain family companies’ innovation capability? How and why?
Entrepreneurship in family companies:
- What is the role of families and family ties in new technological and non-technological ventures?
- How does family involvement in ownership and management influence corporate entrepreneurship in family companies?
- How do family companies venture in new technological domains?
- What drives entrepreneurial growth in family companies? How do those drivers differ from non-family companies?
Family companies, innovation, strategy, entrepreneurship
Track 9. Public service innovation: challenges, risks and opportunities in a fast changing world
Deborah Agostino, Politecnico di Milano
Short description of the proposed track
New technologies and the digital transformation pose several managerial and organizational challenges for public sector institutions operating in a variety of fields – such as culture, transportation, education, justice, health – and policy makers.
The first challenge is related to the relationship between the user (i.e. the citizen) and the public sector institution. User are no longer considered as passive recipients of services or information, but they are posed at the center of activities delivered by institutions, not lastly because of the possibility they have to access their own information and provide their perspective thanks to digital devices. Technologies are transforming the user-institution relationship from an authoritative to a more democratic approach, stimulating collaborative processes and practices, which can lead to co-production, co-design and co-creation.
The second challenge concerns data offered by new and digital technologies. Connected devices, social media and big data more in general are offering both users and the institution with a huge amount of data in a real time, opening new possibilities to improve the measurement of public services and public policies, while, at the same time, offering a better service to the final citizen. In this respect, data have a double role: enhancing the measurement systems adopted by public institutions, but also support institutions in delivering a service more aligned and personalized with users’ need.
Third, digital technologies are transforming internal processes and the organizational structure of public institutions. On the one hand, digital technologies have the potential to innovate the internal processes of public institutions as well as innovating the product offered by public institutions themselves. On the other hand, digital technologies can change the organizational configuration of public service delivery stimulating collaborative relationship between the public institutions and other actors involved in service delivery (private sector providers, users, research centers, local government..) in a network governance form.
These challenges offer several opportunities for improving service delivery, service performances, public policy assessment, but require also new managerial competences and novel managerial approaches. Given this context, this track intends to identify opportunities and risks of digital technologies for public sector institutions and for policy makers. Topics include, but are not limited to:
- The use of different innovative and digital technologies, such as big data or artificial intelligence in different phases of public policy processes or in public service delivery
- Risks and opportunities that digital technologies offer to the budgeting process, the performance management and reporting of public institutions
- The impact of new and digital technologies on public service delivery and policy making
- Adoption of innovative approaches to engage citizens in public service delivery, including, for example, co-creation processes.
Papers can be both theoretical or empirical. Policy and managerial implications must be derived from the results developed in the research work. Papers that deal with a broader concept of “public service innovation” are also welcome.
Public sector innovation, digital technologies, digital transformation, big data, administrative data, performance measurement, public policy
Track 10. Sharing economy and online multi-sided platforms: Effects on traditional businesses
Università degli Studi di Palermo
Short description of the proposed track
Online multi-sided platforms, namely online marketplaces where two or more distinct types of users (for instance buyers and sellers) can meet to exchange goods or services information, cover a wide range of activities including online e-commerce marketplaces, application stores embedded in mobile operating systems, social media, online advertising platforms, crowdfunding and crowdsourcing platforms, booking platforms, and search engines, among others1. They share key characteristics including the use of information and communication technologies to simplify interactions between users, the gathering and usage of data about these interactions, and the generation of network effects.
Over the last two decades, online platforms have introduced radical changes in the digital economy. They play a key role in the creation of “digital value” for enabling future economic growth in the European Union. They determine positive impacts at different levels, as well as risks to address. For example, the digitalization and the rise of online platforms have had positive impacts on the efficiency of the markets. However, some concerns on platform users, including businesses and consumers, can arise. This happens because their dependence on these platforms increases, and because of network effects though which online platforms can grow very fast, which means fast developments of algorithms through (data-driven) learning effects at the expenses of the users.
Accordingly, online platforms can achieve a dominant position with strong market power.
In this context, a particular type of online platforms has played a disruptive role in the society, namely Internet-enabled peer-to-peer platforms. Indeed, the technological developments in mobile communications and increasing social concerns about the (un)sustainability of a consumerist society have contributed to the rise of a new paradigm, namely the sharing economy (Sundararajan, 2016; Zervas et al., 2017; Jiang and Tian et al., 2018; Tian and Jiang, 2018). Within this paradigm, users collaboratively share and make use of underutilized resources on a massive scale upon payment (Jiang and Tian, 2018). The sharing economy paradigm has emphasized the concept of product or service accessibility and utilization, over the concept of ownership. At the same time, every consumer can become a product or service provider by exploiting the ownership of underutilized resources. As a consequence, sharing economy platforms have emerged as an alternative channel to access goods and services traditionally provided by long-established industries (Sundararajan, 2016).
From an industry point of view, the success of Airbnb and Uber, two peer-to-peer platforms in the contexts of hospitality and car transportation respectively, and currently two of the most valuable unicorns worldwide, has certainly contributed to the rapid growth of the phenomenon. In Europe, recent estimates suggest that the sharing economy will potentially soar up to €570 billion by 2025 compared with €28 billion in 2016 (PWC, 2016).
From an academic point of view, there is a growing interest in exploring the distinctive characteristics of these platforms compared to players in traditional industries as well as understanding how these characteristics can influence the competition between them. Some works have demonstrated that the business models of these platforms lead to a costs structure with much lower fixed and transaction costs and near-zero marginal costs as compared to players in traditional industries. This cost structure gives platforms the possibility to easily react when facing with high variability in customers’ demand and become a relevant threat for incumbents (Blal et al., 2018; Cusumano, 2015; Zervas et al., 2016). Some other studies focus on understanding the impact of sharing economy platforms on the market as a whole. In particular, some relevant aspects such as the impact on employment (Fang 2016; Sundararajan, 2016), regulation (Cohen and Sundararajan, 2015; Cannon and Summers, 2014) or environmental sustainability (Martin, 2016) have been recently studied.
Beside initial studies (see next state-of-the-art section for greater detail), much work needs to be done to fully understand the dynamics and the impact entailed by multi-sided platforms in general, and peer-to-peer platforms specifically. With this track, we aim at improving the understanding of the effects of the sharing economy, as well as that of online multi-sided platforms in general, on traditional industries across multiple aspects encompassing operational and strategic decisions, quality issues and environmental consequences, technological and business model innovation, provider and user behavior, inter-firm strategic interactions, organizational issues, profitability, welfare, and employment. Hence, we are interested in theoretical, conceptual and empirical works that provide new insights to open the black box of how these platforms are reshaping traditional industries, markets, and society as a whole across the above multiple aspects.
Sharing economy; online multi-sided platforms; peer-to-peer platforms.
Track 11: Sustainable Business Models & Circular Economy
Politecnico di Milano
Short description of the proposed track
Circular Economy has become increasingly debated at business and practitioners’ level, claiming for profound changes in managerial and organizational practices of firms in using energy, materials and resources, and reducing the environmental impacts of their activities. Circular Economy principles claims for firms to develop, manufacture, distribute but also retrieve products (Geng et al., 2013; Murray et al., 2015).
Most of literature contributions, also in managerial journals, so far discusses Circular Economy adopting a micro (i.e. people, e.g. in Mylan et al., 2016) or macro (i.e. policy makers, e.g. in Geng et al., 2009) approach. As a result, we have a number of guidelines and policies for guiding governments and policymakers to the benefits of Circular Economy, but we still lack consolidated managerial guidelines that push firms towards the implementation of this paradigm. In other words, a meso-approach that takes into account the firm as a unit of analysis still requires more theoretical and empirical effort. Moreover, the linkages between Circular Economy and Sustainability at company level requires a further investigation to understand whether and how these concepts overlap and where are the key point of distinction.
With this call for paper, we solicit members of AiIG to examine the role of Circular Economy in firms’ business models, by leveraging the different perspectives that characterize our community, i.e. business model design & innovation, sustainability, technology-based entrepreneurship, performance measurement, supply chain management.
Circular Economy, Sustainable Business Models, Circular Business Models, Sustainable Supply Chain, Circular Economy Indicators, Digital Technologies for Circular Economy, Circular Start-Ups.