Track 1: Service science in a smart society: design research on smart working
|Eleonora, Veglianti||Université Catholique de Lille, Francefirstname.lastname@example.org|
|Dina, Sidani||Saint-Joseph University of Beirut – Business School, Lebanonemail@example.com|
|Lapo, Mola||SKEMA Business School Université Cote Azure (GREDEG), Francefirstname.lastname@example.org|
The service science as an emerging multidisciplinary field can give an important contribution in several research areas. As Spohrer (2021) suggested the acceleration of the technologies and the policy changes attempts toward the so-called Service Innovation Roadmaps (SIRs) of responsible entities. Therefore, individuals, companies and governments should change in a better version with a focus on value co-creation and knowledge-intensive interactions.
This scenario is influenced by the COVID-19 widespread that requires different players to rethink their strategies with new and innovative elements. Among them, the concept of smart society in general and of smart working in particular are growing requiring further attention. New challenges and concerns related to smart working at the national as well as at the international level brings researchers and experts from both academia and industry to recognize the importance of smart working from different perspectives.
This track is interdisciplinary, and it covers various fields. The articles of this track aim at identifying the role of smart working in the field service science, which could allow, through the informational intelligence of service, to connect together the intelligence of living together – Human Sciences-, the intelligence of solutions – Natural Sciences- and the intelligence of the artificial – Sciences of Engineering, including the Digital (Leonard, 2021). With the spread of smart working in this
pandemic context, Service Science and Information Technology tend to strengthen in order to reinforce a cognitive continuum between pillars related to all the cocreators of the services, with concerned logic to different skills, competencies and eservices science activities (Leonard and Deagoicea, 2021)
Topics include but are not limited to:
– Changes in service sector due to smart working
– Value cocreation in a smart working setting
– ICT as “enabler” of smart working
– Digital transformation and smart working
– Effects of smart working on the organizational structure
– Management smart working in different sectors
– Development and implementation of smart working strategies
- Spohrer J. Service innovation roadmaps and responsible entities learning. ITM Web
of Conferences 38(4):01001 (2021)
- P.P. Maglio, C. Breidbach, A Service Science Perspective on the Role of ICT in
Service Innovation Conference: European Conference on Information Systems
- Léonard, M. (2020). Informational Lights from Service Science for the progression
of Society. 10.1051/978-2-7598-2467-0.
- Leonard, M. Deagoicea, M (2021) – Responsible Service Logic – ITM Web Conf. 38 DOI: 10.1051/itmconf/20213803003
Track 2: Decision analytics ecosystems for public health management, emergency preparedness and response
|Nabil Georges Badr||St Joseph University, Lebanonemail@example.com|
|F. Jordan Srour||Lebanese American University, Lebanonfirstname.lastname@example.org|
With a foundation in service engineering and service management, service science combines principles of systems theory, operations research, management science, marketing science, advanced computing and communication technology, network theory, social computing, and analytics (Qiu, 2014). Service ecosystems co-create value through the reconfiguration of resources (human and other) using service science for a systematic innovation of the services to adapt to the changing constraints, disruption and value propositions. The goal is to apply scientific understanding to advance our ability to design, improve, and scale service ecosystems (Maglio and Spohrer, 2008). This requires the transition from goods dominant logic to service dominant logic in the assessment of the value in the outcome of a service.
This track looks at emergency preparedness and response as a fundamental service in public health. When emergency event of public health occurs, it is difficult to get the needed data, for analysis and quick decision making, in a short time, to inform effective action. Reactive systems, using spatial computing (Guo et al, 2018) for example, that are exploited for the visualization of large, multi-dimensional data have become an important component of the system of response to health emergencies (Wang et al, 2017). However, these resources are reactive and may not establish a roadmap for learning for the resilience of the public health ecosystem, in improving the outcome of the next emergency. It is time for the public health service ecosystems to develop service innovation roadmaps that exploit learning ecosystems while defining specific action plans and templates for the readiness cycle for emergencies including the stages of awareness, investment, preparedness and response (Spohrer, J. (2021). Decision analytics systems have the potential for advancing the learning cycle after each emergency in a feedback loop and patterns, proven to help the mostly laborious approaches that are in effect (Ramadi and Srinivasan).
This track invites papers that highlight use cases in service innovations based on decision analytics ecosystems for public health management, emergency preparedness and response. These learning ecosystems can be decision systems that capture information from multiple agents in the public health ecosystem and transform that information into action to promote awareness, suggest investments, inform models for preparedness and build the capabilities required for effective response and recovery.
List of research topics of the track
– Service innovations based on decision analytics ecosystems for public health management
– Transformation of emergency response services via decision analytics ecosystems
– Predictive systems integration in response ecosystems for resource allocation
– Decision analytics ecosystems for disaster risk reduction in public health
– Value co-creation and systematic innovation in decision analytics ecosystems for emergency services through the frameworks of service science
- Guo, Danhuai, Yingqiu Zhu, and Wenwu Yin. “OSCAR: a framework to integrate spatial computing ability and data aggregation for emergency management of public health.” GeoInformatica 22.2 (2018): 383-410.
- Maglio, P.P., Spohrer, J. Fundamentals of service science. J. of the Acad. Mark. Sci. 36, 18–20 (2008). https://doi.org/10.1007/s11747-007-0058-9
- Qiu, R. G. (2014). Service science: The foundations of service engineering and management. John Wiley & Sons.
- Ramadi, Khalil B., and Shriya S. Srinivasan. “Pre-emptive Innovation Infrastructure for Medical Emergencies: Accelerating Healthcare Innovation in the Wake of a Global Pandemic.” Frontiers in Digital Health 3 (2021): 36.
- Spohrer, J. (2021). Service innovation roadmaps and responsible entities learning. In ITM Web of Conferences (Vol. 38, p. 01001). EDP Sciences.
- Wang, Deqiang, Danhuai Guo, and Hui Zhang. “Spatial temporal data visualization in emergency management: a view from data-driven decision.” Proceedings of the 3rd ACM SIGSPATIAL Workshop on Emergency Management using. 2017.
Track 3: Smart Services’ Innovation Design
|Leonard Walletzký||Masaryk University, Brno, Czech Republiemail@example.com|
|Luca Carrubbo||University of Salerno, Italyfirstname.lastname@example.org|
Smart Services become a significant part of our lives. They define how we use smart devices, like smartphones, computers, or tablets, in our daily lives. Especially in the last two years of the COVID-19 pandemic, the Innovation and the development of Smart Services contributed to how the whole society survived the lockdowns. It also revealed their potential to contribute to the current challenges of developing service environments like Smart Cities or bring new solutions to improve the resilience of the service receivers. The track’s goal is to explore the journey of Smart Service Innovation in the near past and present the possible roadmap for their development in the future.
• Design Innovation of smart services
• Multicontextual environment of smart services
• The resilience of smart services
• Sustainable design of smart services
• User involvement to smart service design
• Structure of smart services
• Smart Service Systems viability
List of references
• M. Drăgoicea et al., “Service Design for Resilience: A Multi-Contextual Modeling Perspective,” in IEEE Access, vol. 8, pp. 185526-185543, 2020, doi: 10.1109/ACCESS.2020.3029320.
• Walletzky L., Buhnova B., Carrubbo L. (2018) Value-Driven Conceptualization of Services in the Smart City: A Layered Approach. In: Barile S., Pellicano M., Polese F. (eds) Social Dynamics in a Systems Perspective. New Economic Windows. Springer, Cham. https://doi.org/10.1007/978-3-319-61967-5_5
• Walletzký L., Carrubbo L., Toli A.M., Ge M., Romanovská F. (2020) Multi-contextual View to Smart City Architecture. In: Spohrer J., Leitner C. (eds) Advances in the Human Side of Service Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1208. Springer, Cham. https://doi.org/10.1007/978-3-030-51057-2_42
• I. F. M. I.B.M, Succeeding through Service Innovation: A Service Perspective for Education, Research, Business and Government, Cambridge: University of Cambridge Institute for Manufacturing, 2008.
• P. P. Maglio, S. Srinivasan, J. T. Kreulen and J. Spohrer, “Service systems, service scientists, SSME, and innovation”,” in Communications of the ACM, Vols. Vols. 49, n.7, 2006, p. 81–85.
• J. Spohrer, “Working together to build a Smart Planet,” in ICSOC, Service-Oriented Computing, San Francisco, 2010.
• F. Polese, S. Barile, V. Loia and L. Carrubbo, “The demolition of Service Scientists’ cultural-boundaries”,” in Handbook of Service Science, II ed., Springer, 2018, p. 773–784.
• S. Barile and F. Polese, “Smart service systems and viable service systems: Applying systems theory to service science,” Service Science, vol. 2, p. 21–40, 2010.
• L. D. Peters, S. Nenonen, F. Polese, P. Frow and A. Payne, “Viability mechanisms in market systems: prerequisites for market shaping”,” Journal of Business & Industrial Marketing, p. 1–10, 2020.
• S. Barile, R. Lusch, J. Reynoso, M. Saviano and J. Spohrer, “Systems, networks, and ecosystems in service research,” J. Serv. Manag, vol. 27 4, p. 652–674, 2016.
• C. Mele, J. Pels and F. Polese, “A Brief Review of Systems Theories and Their Managerial Applications”,” Service Science, vol. 1, p. 126–135, 2010.
Track 4: Digital innovation through smart services
|Thang Le Dinh||Université du Québec à Trois-Rivières, Canadaemail@example.com|
|Jolita Ralyte||University of Geneva, Switzerlandfirstname.lastname@example.org|
|Thanh Thoa Pham Thi||TU Dublin College of Business, Irelandemail@example.com|
Nowadays, the digital disruption and the fourth industrial revolution change fundamentally the way enterprises do business. Enterprises need to innovate to create unique and exceptional competitive advantages. Digital innovation means innovating products, processes, or business models using digital technology platforms as a means to an end within and across organizations. This track aims at expanding our knowledge regarding the adoption of smart services in today’s business landscape to promote the digital innovation. Smart services, which are built based on knowledge-based and intelligent systems and services, have the capacity of self-detecting and self-adaptation to users’ needs without their explicit requests. Big data, business analytics, the Internet of Things and cloud computing provide a huge source of knowledge that allows to determine user contexts and then to enable intelligence capabilities of smart services.
Based on the service science perspective, this track aims at exchanging research ideas and best practices related to new business strategies and models, applications and management of smart services within the context of digital innovation. We are open to all types of research methods and welcome both theoretical and empirical studies on the following (but not limited to) research topics:
- Innovation roadmaps for smart services
- Smart service ecosystem and Responsible Entities Learning
- Theory, approaches and applications for design, development and deployment of knowledge-intensive smart services
- Smart services for industry 4.0
- Enabling smart services with knowledge management
- Predicting user intentions
- Self-detecting, geolocation-based services
- User knowledge management, user context in knowledge-intensive smart services
- Enabling smart services with Big data, Cloud computing and the Internet of Things
- Smart service innovation, evolution and adaptation
- Smart services, smart service systems and value co-creation networks
- Information systems for a smart world, smart cities and smart communities
- Smart services for crisis management
- Nambisan, S., Lyytinen, K., Majchrzak, A., & Song, M. (2017). Digital Innovation Management: Reinventing innovation management research in a digital world. MIS quarterly, 41(1).
- Ciriello, R. F., Richter, A., & Schwabe, G. (2018). Digital innovation. Business & Information Systems Engineering, 60(6), 563-569.
- Wiesböck, F., & Hess, T. (2020). Digital innovations. Electronic Markets, 30(1), 75-86.
- Lusch, R. F., & Nambisan, S. (2015). Service innovation. MIS quarterly, 39(1), 155-176.
- Barrett, M., Davidson, E., Prabhu, J., & Vargo, S. L. (2015). Service innovation in the digital age. MIS quarterly, 39(1), 135-154.
- Beverungen D, Müller O, Matzner M, Mendling J, Vom Brocke J. (2019). Conceptualizing smart service systems. Electronic Markets. 29(1):7-18.
- Léonard, M. (2020). Informational Lights from Service Science for the progression of Society. 10.1051/978-2-7598-2467-0.
- Le Dinh, T., Pham Thi TT, Pham-Nguyen, C. (2020) Towards a Context-Aware Knowledge Model for Smart Service Systems. In International Conference on Computational Collective Intelligence, pp. 767-778, Springer, Cham.
- Troisi O, Visvizi A, Grimaldi M. (2021). The different shades of innovation emergence in smart service systems: the case of Italian cluster for aerospace technology. Journal of Business & Industrial Marketing.
- Demirkan H, Bess C, Spohrer J, Rayes A, Allen D, Moghaddam Y. (2015). Innovations with smart service systems: analytics, big data, cognitive assistance, and the internet of everything. Communications of the association for Information Systems, 37(1):35.
Track 5: Business Model Canvas of Services
|Jim Spohrer||International Society of Service Innovation Professionals (ISSIP.org), USAfirstname.lastname@example.org|
|Monica Dragoicea||University Politehnica of Bucharest, Romaniaemail@example.com|
|Michel Léonard||University of Geneva, Switzerlandfirstname.lastname@example.org|
The Business Model Canvas (BMC ) demonstrated the importance for firms to have accurate, concise, visual business models. Furthermore, this importance is not dissolved because of a lot of activities of a firm are conducted through or from digitalized services. The purpose of this track is to delve deeper the BMC approach by considering digitalized services in the center of BMC design and by providing sustainable efficient support to establish Services Innovation Roadmaps (SIRs) .
Several proposals claim to improve the first BMC  to establish a better concordance between BMC and Service Science , notably with the Service Science Canvas constructed from the 10 main concepts of Service Science , with the Smart Service Model Canvas (SSModC) for the purposes of resilient Society , with the Service Logic Business Model Canvas grounded on the Service Dominant Logic .
A huge research exploration is open to delve deeper the role of BMCs in establishing SIRs, with considering, for instance,
- the gap between goods dominant logic and service dominant logic,
- the mandatory links between SIRs and Responsible Entities Learning,
- the interwoven activities to create, design, establish SIRs, BMCs, or service systems,
- all of these activities in an agile perspective to support the continuous improvements,
- digital supports for all these activities.
 Osterwalder, A. & Pigneur, Y. (2010). Business model generation: a handbook for visionaries, game changers, and challengers. New York, Wiley.
 Spohrer, J. (2021). Service innovation roadmaps and responsible entities learning. In ITM Web of Conferences (Vol. 38, p. 01001). EDP Sciences.
 O.V. Pavlov, F. Hoy, Toward the Service Science of Education, in Handbook of Service Science, Volume II, P.P. Maglio, C.A. Kieliszewski, J.C. Spohrer, K. Lyons, L. Patricio, Y. Sawatani, Y. (Eds.) (Springer International Publishing, 2019) 545-566
 Polese, P., Dragoicea M., Carrubo L., Walletzky L (2021). Why Service Science matters in approaching a “resilient” Society? In ITM Web of Conferences (Vol.38, p 02001), EDP Sciences, Conference IESS 2.1, Geneva March 2021.
 Jukka Ojasalo, Katri Ojasalo, (2018) “Service Logic Business Model Canvas”, Journal of Research in Marketing and Entrepreneurship, https://doi.org/10.1108/JRME-06-2016-0015
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Track 6 : Innovative digital approaches in the academic world
|Giovanna Di Marzo Serugendo||University of Geneva, Switzerland||Giovanna.DiMarzo@unige.ch|
|Pierre-Yves Burgi||University of Geneva, Switzerland||Pierre-Yves.Burgi@unige.ch|
|Lamia Friha||University of Geneva, Switzerland||Lamia.Friha@unige.ch|
|Laurent Moccozet||University of Geneva, Switzerland||Laurent.Moccozet@unige.ch|
|Jean-Henry Morin||University of Geneva, Switzerland||Jean-Henry.Morin@unige.ch|
The academic field is an extraordinary place for developing and experimenting, supporting, and even deploying digital innovation. Research, teaching, learning, and the provision of efficient services for a whole academic community are core business activities of Universities. Students, researchers, teachers and all the university members need services to fulfill their duties, to support their projects and ideas in an optimal manner.
Developing and experimenting innovation is a central aspect of research and scientific activities, in particular digital innovation for research related to information systems, computer science or more generally to service science. This activity generates various digital artefacts, ranging from novel methods, paradigms, proof-of-concepts up to intangible designs.
Supporting innovation concerns any member of an academic organization, from students and researchers wishing to further develop ideas or projects into actual effective entrepreneurial activities or social innovations with an impact, to University staff interested in exploring the academic institution activities, including digital novelties to facilitate everyday work.
This track aims at bringing together academics and practitioners for sharing breakthroughs related to the creation or leverage of innovative services. Topics include but are not limited to:
• How can we strengthen students’ partnership in the academic field to experiment, innovate and anticipate the much needed pedagogical reform ?
• How can we provide a personalized response to the needs of student/teacher/researcher/staff and civil society needs during their studies/activities ?
• How to provide student/teacher/researcher/staff and members of civil society with new, personalized responses that enable them to achieve self-fulfillment throughout their studies, their activities, and their lives.
• How can we leverage technologies such as AI, blockchain, VR/AR/MR to improve higher education services ?
• How to be a stakeholder while co-animating and co-creating new valuable services together?
• Ideas, explorations, experimentations, assessments of the role of fabrication along the three missions of a University (teaching, research and service to the society).
Research topics and their relationship to the conference theme:
• Smart Digital services in the academic world;
• Personalized services to a better student/teacher/staff experience
• Agile and participative construction;
• Advanced technologies such AI, blockchain, VR/AR/MR to leverage new services.
• The role of fabrication at large (tangible and intangible)
 Giovanna Di Marzo Serugendo, Lamia Friha, Digital innovation process in the academic sector – The case of the University of Geneva, in Proc. of the International Conference on Exploring Services Science (IESS 2021) (EDP Sciences, 2021)
ITM Web Conf. 38 03004 (2021) DOI: 10.1051/itmconf/20213803004
 Leopoldo Angrisani et al, Evolution of the academic FabLab at University of Naples Federico II, 2018 J. Phys.: Conf. Ser. 1065 022013
 L. Angeli, F. Fiore, A. Montresor, and M. Marchese, “Designing a Hands-on Learning Space for the New Generation,” in Proceedings of the FabLearn Europe 2019 Conference, New York, NY, USA, May 2019, pp. 1–3. doi: 10.1145/3335055.3335060.
 J.H. Morin, L. Moccozet, Build to think, build to learn: what can fabrication and creativity bring to rethink (higher) education? in Proc. of the International Conference on Exploring Services Science (IESS 2021) (EDP Sciences, 2021). ITM Web Conf. 38 03004 (2021) DOI: 10.1051/itmconf/20213802004
 M. Pande, S. V. Bharathi, Theoretical foundations of design thinking – A constructivism learning approach to design thinking, Thinking Skills and Creativity, Volume 36, 2020, 100637, ISSN 1871-1871, https://doi.org/10.1016/j.tsc.2020.100637.