Developing new smart services using integrated morphological analysis: integration of the market-pull and technology-push approach

Abstract

With the rise of smart services, new services are no longer generated via the traditional linear models of innovation. Rather, smart-service innovations require new frameworks to integrate the market-pull and technology-push models, which focus on both user-centric considerations and technological developments. However, current streams of research continue to merely suggest a conceptual framework. Therefore, it appears to be difficult to apply this framework into practice, due to a lack of systematic methodologies. In response, this study employs morphological analysis, a powerful tool for the systematic generation of ideas. Since the morphological analysis employs several dimensions for explaining new services and combines them to generate new ideas, it is easy to integrate the different approaches to innovations, such as market pull and technology push. A case study of smartphone application services is also conducted.

Data-Driven Understanding of Smart Service Systems Through Text Mining

“…Smart service systems incorporate technologies for sensing, communication, and control, among others (NSF 2016), to effectively and efficiently consider the needs and context of stakeholders . Other keywords describing smart service systems in the literature include cognition, sustainability (Spohrer and Demirkan 2015), self-reconfiguration, connection (Carrubbo et al 2015), wisdom, interaction (Barile and Polese 2010), people, real time (Gavrilova and Kokoulina 2015), user-centric (Geum et al 2016), dynamic experience , autonomy (Maglio 2017), and elasticity (Moldovan et al 2018). Different types of smart service systems, such as those found in homes (Alam et al 2012), healthcare (Raghupathi and Raghupathi 2014), buildings (Agarwal et al 2010), and transportation (Pelletier et al 2011), have been realized in various forms in smart cities (Abella et al 2017, Lim et al 2018d).…”

Multi-factor service design: identification and consideration of multiple factors of the service in its design process

“…The proposed MFSD method aims to complement existing studies and expand the service design literature by showing the utility of considering the multifactor nature in each hierarchical level. The morphological analysis, a well-known approach for structured system analysis and design, predefines key factors of the system in question and uses them for its analysis and design (Geum et al 2016). This approach has been applied to the service context recently (e.g., Meier and Boßlau 2013;Geum et al 2016).…”

“…The morphological analysis, a well-known approach for structured system analysis and design, predefines key factors of the system in question and uses them for its analysis and design (Geum et al 2016). This approach has been applied to the service context recently (e.g., Meier and Boßlau 2013;Geum et al 2016). However, how this approach can be used in the key tasks of service design process, such as customer understanding and service concept design, is not well known.…”

“…The multi-factor nature of service has been discussed in the service design literature frequently but implicitly, although the term ''multi-factor nature'' is not applied. For example, researchers have investigated multiple factors related to the experience-centric service design (Zomerdijk and Voss 2010; Ponsignon et al 2017), product-service system design Lim et al 2012), information-intensive service design (Lim et al 2018b), smart service design (Geum et al 2016;Maglio and Lim 2016), and service delivery process design (Bettencourt 2010;Lim and Kim 2014). This is attributed to that dividing blocks (factors) among the objects is useful to see certain functional work of the service (Osterwalder and Pigneur 2010;Lim et al 2018b).…”

“…Dijkman et al (2015) used these nine blocks to decompose existing service offerings systematically and to create a new service offering based on information from existing ones. Geum et al (2016) examined the five factors of service (the user, spatial, temporal, eventual, and value factors of service) and the three factors of technology (the input, process, and benefit factors of technology) to derive ideas of new smart service offerings. Lim et al (2018b) identified nine key factors that characterize information-intensive service offerings: (1) data source, (2) data collection, (3) data, (4) data analysis, (5) information on the data source, (6) information delivery, (7) customer (information user), (8) value in information use, and (9) provider network.…”