How smart technologies and big data affect systems’ lives? Conceptual reflections on the Smart City’ ecosystem

According to several managerial contributions the XXI century is the era of technology innovation, information sharing, and hyper connected societies (Castells, 1999; 2010; Shaw, 2002; Karakas, 2009; Webster, 2014; Barile et al., 2015). All the traditional social and economic rules are progressively changing as consequence of the fast evolutions in the challenging scenario in which we all everyday live (Van Dijk, 2012; Del Giudice et al., 2016). The emerging balances are showing an increasing relevance of technology and information as relevant drivers on which companies, organizations, and institutions should ‘act’ to improve their performances and opportunities for survival (Davenport, 2013; Evangelista et al., 2016). The information is the new ‘key resource’ for social and economic actors and the Information and Communication Technologies (ICTs) offer the instrument to better acquire, analyse, and use it (Lopez-Nicolas & Meroño-Cerdán, 2009). Building upon these reflections several managerial contributions have analysed the domain of information with the aim to better explain its dimensions (Miller, 1996; Garson, 2000; Siponen, 2001) and processes (Applegate et al., 2007; Alavi & Leidner, 2001; Davenport, 2013) and several researchers have highlighted the role of ICTs in supporting the information acquisition (Mansell, 1999; Roberts, 2000) and sharing (Hendriks, 1999; Steinmueller, 2000; Caputo et al., 2016b). By following this approach an increasing attention is emerging with reference to the topics of Smart Technology in terms of “self-operative and corrective system that requires little or no human intervention” (Haque et al., 2013: 22) and of Big Data as “high-volume, high-velocity, and/or high-variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization” (Chen & Zhang, 2014: 314-315). Despite the relevance of this topics, they define a perspective strictly focused on the technological and instrumental dimensions of society and really few attention is paid with reference to the role of actors involved in the information building and sharing (Cook & Das, 2004; Caputo et al., 2016a, 2016c). According to the several contributions offered with reference to the domains of Smart Technologies and Big Data all the society can be analysed and managed by building efficient digital platforms able to ensure better links among the several dimensions involved in social and economic processes. Unfortunately, the reality is more complicated than this. As underlined by Bijker et al. (2012), technologies can explain only a small part of the ‘social complexity’. In the same directions, Steinmueller (2000) underlines that information can only by partially decoding by using the technology because a large part of their meaning is embedded in human resources and they cannot be shared simple using a technological platform. More, Johannessen et al. (2001) outline that technologies is useful to improve the quality in management of more ‘tangible’ dimensions of human life but (for now) they are useless in understanding and managing cognitive and psicological variables. In accordance to all these contributions and embracing the interpretative perspective of social sciences a relevant research question required to be investigated: How smart technologies and big data affect our everyday life? With the aim to propose a possible answer to this question, the paper adopts the interpretative lens offered by the Systems Thinking and Service Logic in order to clarify the role of smart and digital environment in our life. Reflections herein are contextualized with reference to the domain of Smart City as relevant example of contamination among social and technological dimensions. Finally, implications, conclusions and future directions for research are presented. Theoretical and conceptual background The contributions of systems thinking in investigating smart technologies and big data The society could be defined as a complex of relationships based on the continuous sharing of resources and on the combination among several expectations finalized to the building of new value. All these elements make the society a domain that cannot be analysed simple by investigating its dimensions, they require to adopt interpretative lens able to outline in which ways different elements interact by building conditions of ‘reciprocal influence’ over the time (Bandura, 1978; Di Nauta et al., 2015). According to this, the society cannot be analysed in the light of mechanistic approach, it requires the adoption of a holistic perspective able to link all the involved elements and pathways in a common ‘interpretative picture’ (Odum & Barrett, 1971; Jackson, 2006; Hammond, 2010). Building upon this assumption, the systems thinking represents the better approach to understand in which way all the elements and relationships that found the society are linked and evolve over the time (Cutcliffe, 2000; Caputo, 2016). The systems thinking supports the shift from a reductionist and mechanistic approach direct to explain in which way elements are composed and related to a holistic a dynamic view in which the attention is also on the elements that affect the emergence and the evolution of the whole phenomenon (Barile et al., 2016). The systems thinking offers several relevant contributions to better understand in which ways an entity is able to organize itself (Maturana, 1975; Varela, 1984) by sharing resources with the ‘external’ environment (Espejo, 1990; Golinelli, 2010) in order to achieve conditions of survival (Beer, 1979; Barile, 2009a). Among the contributions offered by the systems thinking two research domains appear to propose relevant advancements in knowledge in understanding social dynamics: the Viable System Model (VSM) and the Viable Systems Approach (VSA). While the first one clarifies in which ways the elements involved in an organised entity are able to define conditions of reciprocal influence by building a shared balance (Beer, 1979, 1984, 1985; Espejo & Harnden, 1989; Espejo et al. 1996, Espejo & Reyes, 2011) the latter proposes a general representation of system based on its information variety useful to investigate any kind of organized entity aimed to survive in a specific environment (Barile 2009b; Barile & Saviano, 2010, 2011; Golinelli, 2010; Barile et al., 2012, 2014, 2016; Golinelli et al., 2012; Saviano et al., 2014). Specifically, the systems thinking – thanks to the contributions offered by the VSM and the VSA – enriches previous knowledge in managerial domains by underlining the relevance of cognitive dimensions in affecting system’s decision and behaviours (Barile et al., 2013). At same time, it highlights that it is not possible to define an objective view of reality because it is subjectively affected by the observers’ perspectives and need (Saviano & Caputo, 2013) and it defines useful guidelines to better represent the link among the elements that formed the system (Barile, 2013). As shown in the Figure 1, adopting the interpretative lens offered by the systems thinking, it emerges the relevant role of smart technologies in supporting the interaction among the different elements involved in a system by ensuring a fast reciprocal adaptation over the time (Streitz et al., 2005; Di Fatta et al., 2016) and the key role of big data as pathways to ensure the building of a strong feedback process able to increase the alignment between the linked systems (Wu et al., 2014). In such a perspective, the systems thinking offers the opportunities for define a shared conceptual framework in which technological and social dimensions are effectively linked (Polese et al., 2016; Saviano et al., 2016a). It underlines the need for enlarge the perspective both in technological and social studies in order to build better bridges among human resources and technical instruments (Barile et al., 2015; Saviano et al., 2016b). By adopting the systems perspective, it is possible to state that the advanced technologies are not smart theirself but they become smart only if they are aligned with users’ ability in use them to solve their needs. More, the automatized processes are suitable only in the case in which there is a shared expectation but they are useless in every case in which involved actors have different needs and/or perspectives. Finally, environment is subjectively built by the system therefore technologies can be produce effective, efficient, and suitable solutions only in the case in which they are based on an in depth study of variables and elements that address systems’ perceptions. The service perspective for big data and smart technologies Big data is being generated by everything around us at all times. Every digital process and social media exchange produces it. Systems, sensors and mobile devices transmit it. Big data is arriving from multiple sources at an alarming velocity, volume and variety. To extract meaningful value from big data, you need optimal processing power, analytics capabilities and skills. (https://www.ibm.com/big-data/us/en/) It is obvious in every single system we can find a lot of different procedures and processes that produce simple data all the time. This is common feature of all implementation of IT technology. It is necessary to underline that only this fact does not mean anything very marking. But the possibility of interconnecting among the devices we can use, huge number of combination enables us to create unique system, providing data and information to run other - following systems. We need to analyse the way how the big data are generated in Smart City. For this purpose we can use the platform, defined in paper “Bootstrapping Smart Cities through a Self-Sustainable Model Based on Big Data flows. Model, based mostly on technical point of view, is underlining the importance of open data. We can easily see the model of the Smart City is based on the services, that are dependent on open data. The model, presented above, is focusing to compare two variables - data flows and revenues coming from the work with those data flows. From the service perspective, reflecting the role of ICT, we cannot miss one more important aspect - and this is a value, co-created by the participating parties. To be absolutely clear, the value is not equal to revenue. Revenue is represented only by money transfer, but to explain the role of the big data in process of sustainability, we need to focus to the process of the value creation. In the beginning, the basic data are created - they are taken from smart sensors and similar devices. Those data are collected, processed and offered to customers via several applications, provided by different companies. Customers or in general all users of the application, are also sources of the data (feedbacks, data about their geographical position, searching data, data about their preferences, atc.). Those data are again added to the collection of the big data and together with actualized data from sensors are used to provide new level of the service. As shown in the following Figure 3, this cycle is potentially never ending - it ends only in the moment when it would not be able to provide a new value for the customer. The most important connection is no. 4 - it represents the will of customers to participate on service creation. On this critical factor depends if the service and whole environment will run and be continuously developed. The domain of Smart City among users, services, and technologies The Smart City is a term for a city that focuses basically on 2 main goals. One is a high living standard of its citizens and the second one is a sustainable development of the city. These main goals can be fulfilled by incorporating and evolving many services that support citizens' living standards on one hand and help to develop the city and prevent exhausting of sources on the other. There are many different papers contemplating about Smart City service domains. And there is still no shared agreement about them. For instance, here follows one of the latest definitions of Smart City using a distribution of service domains (Mattoni et al., 2015): - Community - Participation and Communication - Environment - Enhancement - Energy - Sustainability & Optimization - Mobility - Movement - Economy - Dynamism and Innovation In other words, a Smart City should support innovations, a use of a new technology, communication (people, services, private and public organizations from different city sectors), citizens' engagement and knowledge development, all to create a supportive synergistic environment. Technology perspective At the beginning of future cities research, there was the main focus on Technology perspective. More specifically, with the development of IT technologies and its common use in daily lives, there was an idea to use an advancement of this technology broadly in cities as well. This is how a concept of Digital city was born. Then this technology attitude was innovated and more oriented on services (e.g. Intelligent city, Ubiquitous city). Service perspective The shift to service point of view means using the technology not just for controlling and sharing information, but to provide better and usually more complex services as example, which is where a Smart City stands now. In recent years another advance appeared. The services themselves don't have a broader context and purpose in many cases. They are executed separately, which doesn't utilize a full potential of other services and cities in general. User perspective Users are able to use some services that a city government decided to implement, and it doesn't mean that these services are much worthy for citizens. There is now another shift arising now. It is a slow change from the service perspective to users (the citizens). Smart City Management Therefore, here we propose an attitude for developing Smart Cities in a complex manner. The idea is taken from a Management by Competencies (Plamínek & Fišer, 2005), the managerial approach that describes the approach to managing a vital company. Vitality in this context means that it is not just successful, but it is constantly successful. Exactly, the definition of the vitality is: attaining of current goals does not diminish the chance to achieve goals in the future It doesn’t drain its possibilities (resources) for a one-time achievement. It is successful in a long term. And the mean of success is its employees. Here is an analogy with Smart Cities, that aims to achieve sustainable development and focus on lowering energy consumption and renewable sources on one hand and on the other hand it aims to create a city with entertainment and work possibilities for its citizens. Basic idea is to realize the process and interconnections of the SC system. For that purpose, we can develop a duality model form MbC. Each city regardless whether it is smart or not has some requirements (goals) and possibilities (services). What should make Smart Cities different, is a way of assessing and reaching goals. Smart Cities' goals are oriented to their inhabitants (sustainable city development and high living standard) and can be fulfilled just by the active participation of their communities. By communities, we mean citizens and all the organizations and companies being part of the city. Thus, there are two main units with their possibilities and requirements. The first one is a Smart City itself which requirements are its goals and possibilities are city services. The second one is the communities in the city with their requirements - high living standard, and possibilities - human and financial capital. The whole system works like a cycle. As shown in the following Figure 4, Smart City goals are fulfilled by communities' possibilities and their requirements are conversely fulfilled by Smart City services (Fig. 5). Towards an ecosystem view of Smart City An ecosystem view of Smart City as Complex Adaptive Systems According to Lusch an ecosystem is “a spontaneously sensing and responding spatial and temporal structure of largely loosely coupled value proposing social and economic actors interacting through institutions and technology, to: (1) coproduce service offerings, (2) exchange service offerings and (3) cocreate value” (2011: 15). As presented, this definition seems to offer a clear representation of Smart City as proposed in the previous sections. Specifically, Smart City can be considered a complex of users, services, and technologies linked in order to ensure a shared satisfaction (Nam & Pardo, 2011). In such a perspective, a relevant role is played by smart technologies and big data in ensuring a shared satisfaction of all the involved actors by supporting the fast adaptation of the relationship on which the Smart City is based. Specifically, the Smart Technologies represents the instruments to improve the efficiency in the relationships between citizens and city infrastructures and services while Big Data ensures an effectively adaptation of city services to citizens’ expectations. According to this, Smart Technologies and Big Data can be considered the levers on which act to build a more efficient approach in the management of Smart City as Complex Adaptive System (CAS). As underlined by Holland, CAS is a system “that have a large numbers of components, often called agents, that interact and adapt or learn” (2006: 1). As shown in the Figure 5, by adopting the systems thinking the Smart Technologies and Big Data could support the emergence of Smart Cities aligned with the logic of CAS. More specifically, in the light of CAS the Smart City could shift to be considered an ex-ante planned technological city managed by some kind of supra entity to become a multi-dimensional interconnected domains adapt itself thanks to the support offered by the technologies (Smart Technologies) in order to respond to citizens’ behaviours and expectations (Big Data). In such a perspective the elements involved in Smart City can be considered agent in terms of “semi-autonomous units that seek to maximize their fitness by evolving over time [and able to] scan their environment and develop schema” (Dooley, 1996: 3). By adopting this interpretative perspective, it is possible highlights the high subjectivity that affect the Smart City and it is also possible to highlight that it is not possible to define an objective representation of Smart City because for each involved agent it acquires different meanings. In the light of CAS perspective, the Smart City is a relevant example of social phenomenon and its analysis, study, and representation requires to combine multiple perspective in a shared interpretative framework in order to show, by adopting a holistic approach, in which ways agents’ relationships affect its dynamics and evolutions over the time (Bowerman et al., 2000; Paskaleva, 2009; Cocchia, 2014). Conclusions and future directions for research As it was shown, the Smart City development depends on two main factors - continuously updated big data and smart technologies that are using them as one factor and customer willingness to cooperate on their development. Data and applications, used to produce more data that are used for the better utilization of the particular service and whole service environment. The process seems to be never ending, depending only on the fact and will of the al stakeholder to cooperate on its sustainable development. There are two basic streams for the future research: 1. What does exactly motivate customers to share their personal data to be used in service provision? 2. How to explain exact role of ICT in the Big Data analysis to provide higher level of the service? 3. How does the co-created value correspond with requirements - possibilities cycle, presented in this paper? Development of every system and its lifecycle needs to be analyze from those two perspectives - after that we will be able to explain the sustainable process in is whole perspective