Why Specialized Service Ecosystems Emerge—the Case of Smart Parking in Germany

Zimmermann, Sina et al. Article — Published Version Why Specialized Service Ecosystems Emerge—the Case of Smart Parking in Germany Information Systems Frontiers Provided in Cooperation with: Springer Nature Suggested Citation: Zimmermann, Sina et al. (2023) : Why Specialized Service Ecosystems Emerge— the Case of Smart Parking in Germany, Information Systems Frontiers, ISSN 1572-9419, Springer US, New York, NY, Vol. 27, Iss. 2, pp. 585-604, https://doi.org/10.1007/s10796-023-10453-y This Version is available at: https://hdl.handle.net/10419/323326 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Vol.:(0123456789) 1 3 Information Systems Frontiers (2025) 27:585–604 https://doi.org/10.1007/s10796-023-10453-y Why Specialized Service Ecosystems Emerge—the Case ofSmart Parking inGermany SinaZimmermann1 · ThomasSchulz1· AndreasHein2 · AlexanderFelixKaus1· HeikoGewald1 · HelmutKrcmar2 Accepted: 25 November 2023 / Published online: 16 December 2023 © The Author(s) 2023 Abstract Traffic caused by drivers searching for a free parking space has numerous negative effects, such as increased emissions and noise pollution. Innovative solutions can reduce these negative effects by providing car drivers with better information via a smart parking app. However, smart parking apps currently do not offer overarching solutions which support the entire parking process. Utilizing a service-dominant logic perspective, we examine why such overarching solutions do not emerge, whereas specialized ecosystems flourish. We follow a multiple case study approach and conduct qualitative interviews with three app providers and fourteen associated parking operators in Germany. Our results show how conflicting institutional arrangements at the micro, meso, and macro context levels lead to specialization. Our study deepens the understanding of how conflicting institutional arrangements affect the emergence of service ecosystems, drawing practical recommendations to overcome specialized smart parking apps in favor of overarching solutions. Keywords Smart parking· Service-dominant logic· Multiple case study· Institutional arrangements· Service ecosystems 1 Introduction The dominant use of private cars for mobility leads to numerous problems. Especially in cities, drivers waste valuable time waiting in traffic and searching for a free parking space. For example, INRIX (2017) shows that it costs car drivers around 41h per year to find free parking spaces in cities in Germany. This additional traffic caused by drivers searching for a free parking space is called “parking search traffic.” In addition to the loss of valuable time, parking search traffic has additional negative consequences, such as greenhouse gas emissions, noise pollution, and a financial burden for the driver due to the waste of fuel (e.g., Perković etal., 2020; Shin & Jun, 2014; Shoup, 2006). Although there are multiple approaches to reducing private car use, such as the provision of apps that make other mobility services such as public transport or bike-sharing more convenient (e.g., Schulz etal., 2023, 2021), it is not likely that private cars will lose its position as the most important means of transport in developed countries. Information technology (IT) offers opportunities to make private car use more efficient, for example, by providing drivers with information about accessible parking spaces. According to Watson etal., (2011, p. 59), a prerequisite for a change toward more sustainable behavior is providing the “right information at the right time.” In addition to whether a parking space is free, information such as the fastest route to parking spaces, the maximum parking time, and the parking fee is essential. Smartphone apps (hereafter apps) can provide this information through smart parking assistant services that rely on sensors, big data, open data, new ways of connectivity and exchange of information (e.g., Internet of Things, RFID, or NFC) as well as abilities to infer and reason” (Gretzel etal., 2015, p. 179). Through these smart parking assistants, cities can reduce parking search traffic and contribute to greater environmental, economic, and social sustainability. Overall, there is a large body of scientific literature on smart parking. Various studies focus on a technical perspective of smart parking, such as the development and comparison of different sensors, cameras, and radar sensors, to monitor whether a parking space is free (e.g., Al-Turjman * Sina Zimmermann sina.zimmer[email protected] 1 Center forResearch On Service Sciences, NeuUlm University ofApplied Sciences, Wileystraße 1, 89231Neu-Ulm, Germany 2 Krcmar Lab, Technical University ofMunich, Boltzmannstraße 3, 85748GarchingbeiMunich, Germany 586 Information Systems Frontiers (2025) 27:585–604 1 3 & Malekloo, 2019; Barriga etal., 2019; Idris etal., 2009; Perković etal., 2020), or the programming of a parking guidance algorithm (Shin & Jun, 2014). Other studies examine the potential economic and environmental impact of smart parking (e.g., Rodier & Shaheen, 2010). However, although research in various contexts has shown that the interplay of technical and social aspects is crucial for the implementation of information systems (IS) applications and the emergence of successful ecosystems (Sarker etal., 2019), research on smart parking that takes a non-technical but socio-technical perspective is still rare (Chovani & Jokonya, 2019). For instance, in the case of smart parking, socio-technical factors include the payment habits of potential users or the willingness to share personal data with smart parking providers. Although the technical prerequisites for smart parking might be given, these factors can hinder the emergence of overarching smart parking ecosystems, as users do not exploit the technical possibilities. Therefore, our research bridges important insights of interdisciplinary fields, such as IS, behavioral sciences, and economics to open up new perspectives on the topic of smart parking. An example for the socio-technical perspective are service ecosystem that represent an actor-to-actor network and is defined as “a relatively self-contained, self-adjusting system of mostly loosely coupled social and economic (resource-integrating) actors connected by shared institutional logics” (Lusch & Nambisan, 2015, p. 161). In a smart parking ecosystem, actors such as the app provider, end users, and cities, including public transportation companies, constitute a service ecosystem. Previous studies in this context examine why actors do not join a service ecosystem (Schulz etal., 2023) or the service platform (i.e., the app) used by the actors for service exchange has a limited functional range (Schulz etal., 2020). However, these studies do not provide insights into how different specialized service ecosystems emerge in specific areas, such as in the case of smart parking, to overcome specialization and provide more attractive, overarching solutions for (potential) users instead. Based on the institutional logics or institutional arrangements (Vargo & Lusch, 2017), actors in the ecosystem cocreate value. Institutional arrangements consist of interrelated institutions representing rules, norms, and beliefs (Vargo & Lusch, 2017). For smart parking ecosystems, institutional arrangements include, for example, rules about processing parking data or beliefs regarding the best business model of app providers for end users. Therefore, institutional arrangements are highly significant for understanding the emergence and design of service ecosystems. If, for example, the rules about processing parking data differ for an app provider and a parking provider, these parties will most likely not initiate cooperation (i.e., form an ecosystem). Scientific knowledge about institutional arrangements in general (Vargo & Lusch, 2017) and smart parking ecosystems, in particular, is still very limited. To fill this research gap, we analyze which institutional arrangements of the actors in a smart parking ecosystem lead to specialized rather than overarching ecosystems, posing the following research question: What factors lead to specialized rather than overarching smart parking ecosystems? We choose Germany as our context of the analysis because the impact and significance of institutional arrangements are particularly evident in smart parking ecosystems there. In Germany, app providers are still struggling to gain a foothold in cities due to the complexity of smart parking ecosystems. Consequently, only a few cities are currently cooperating with smart parking app providers. In addition, conflicting institutional arrangements in Germany lead to highly fragmented smart parking ecosystems that do not support the entire parking process, which includes the search for a free parking space, navigation to it, and digital payment (Hassoune etal., 2016; Idris etal., 2009). This focus of the apps on a specific phase of the parking process leads to specialized instead of overarching smart parking ecosystems, which makes them unattractive to potential users, as it requires the use of multiple apps for a single parking process. In our study, we take the service-dominant (S-D) logic perspective (Vargo & Lusch, 2004) on embedded institutional arrangements (Vargo & Lusch, 2017), follow a multiple case study approach and conduct qualitative interviews with three app providers and fourteen associated parking operators from Germany to reveal how specialized smart parking ecosystems emerge. The level of analysis is the smart parking ecosystem comprised of the smart parking app provider, the cooperating cities or companies, and the end users, with different underlying institutional arrangements. Based on a cross-case analysis, we reveal the impact of different institutional arrangements on the emergence of specialized ecosystems. With our research, we combine thorough theoretical analysis to tackle the practical problem of smart parking burdens in Germany, using insights from the scientific literature and interview data from smart parking industry specialists. Moreover, we combine these insights with a socio-technical lens to cover behavioral and technological perspectives in our research to explore multiple frontiers of the smart parking problem. We contribute to theory by providing insights into how conflicting institutional arrangements affect the emergence of overarching smart parking ecosystems (Vargo & Lusch, 2017). Our results show that especially political arrangements, end-user preferences, data provision and management, digital billing and payment options, and cooperation among app providers and cities/ companies lead to specialized ecosystems. Moreover, we shed light on the role of the concept of 'smartness' for our research and how it supplements former research on smart technologies and 587Information Systems Frontiers (2025) 27:585–604 1 3 smart cities (e.g., Alter, 2020; Kar etal., 2019; Sharma etal., 2023). Our practical contributions include recommendations on how to overcome specialized ecosystem structures to create overarching smart parking solutions. 2 Theoretical Background 2.1 Service‑Dominant Logic Perspective The service-dominant (S-D) logic perspective was introduced in marketing by Vargo and Lusch (2004) and has been applied by scholars from various academic fields (Vargo & Lusch, 2017), including IS (Brust etal., 2017; Haki etal., 2019; Lusch & Nambisan, 2015). The S-D logic perspective has been used in IS to analyze different research topics, such as customer relationship management, business models (Turetken etal., 2019), and service ecosystems (Breidbach & Maglio, 2016). Moreover, the S-D logic perspective has been applied to the area of smart mobility, for example, to analyze how digital innovation can be induced in the mobility market to optimize end-user experiences with IS (Turetken etal., 2019). The essence of the S-D logic perspective is captured by its three main concepts: (1) service ecosystem, (2) service platform, and (3) value co-creation (Lusch & Nambisan, 2015). A service ecosystem represents an actor-to-actor network and is defined as “a relatively self-contained, self-adjusting system of mostly loosely coupled social and economic (resource-integrating) actors connected by shared institutional logics and mutual value creation through service exchange” (Lusch & Nambisan, 2015, p. 161). Based on this definition, the different smart parking actors, such as the app provider and car-sharing and public transport companies, who use an app to provide users with information and access to multiple mobility services, constitute a service ecosystem (e.g., Schulz etal., 2023, 2021). One or more of these actors may be embedded in several service ecosystems at the same time (Akaka etal., 2013). Lusch and Nambisan (2015, p. 162) define a service platform as “a modular structure that consists of tangible [e.g., IT hardware] and intangible components (resources) and facilitates the interaction of actors and resources (or resource bundles).” Actors use service platforms to provide and access services more effectively (Lusch & Nambisan, 2015; Storbacka, 2019). Based on this explanation, smart parking apps and parking sensors can be regarded as service platforms. Value co-creation is based on service exchange among actors (Vargo & Lusch, 2017). A significant difference to the goods-dominant (G-D) logic perspective is that the customer is engaged in the service exchange (i.e., value cocreation) (Vargo etal., 2008). For example, rather than a car manufacturer attributing a specific value to a vehicle through its production, customers determine and create the value of the car by driving it. Value co-creation can also be identified through a positive change in the well-being of an actor (e.g., Chen etal., 2021; Schulz etal., 2021). In the situation above, for example, the value of the car is created when customers’ well-being is improved by driving it. In the IS research field, the concept of value co-creation has been adopted for different contexts. For instance, value co-creation mechanisms have been analyzed for business-to-business IT platforms (Schreieck etal., 2017) or in nascent digital platform ecosystems (Hodapp etal., 2019). However, our knowledge about value co-creation is still limited, especially in technologyenabled contexts, as analyzed in IS research (Breidbach & Maglio, 2016; Brust etal., 2017). Technological progress and breakthroughs (e.g., a camera-based, deep learning approach to detecting free parking spaces) and changes in industry logic continuously offer new opportunities for value co-creation worthy of exploration (Payne etal., 2008). In addition to these three main concepts of the S-D logic, we also consider institutional arrangements and different context levels in our study to analyze the emergence of specialized smart parking ecosystems. Institutional arrangements coordinate the actors and their service-for-service exchange within a service ecosystem. Institutional arrangements consist of interrelated institutions, including rules, norms, and beliefs (Vargo & Lusch, 2017), and conflicting institutional arrangements constrain the service exchange among actors of a service ecosystem (Schulz etal., 2020a). For example, German public transport companies often do not provide real-time timetable data and electronic tickets to app providers due to tendering and related price competition. Building on Koskela-Huotari etal. (2016, p. 2964) assertion that “breaking, making, and maintaining” institutional’ arrangements can facilitate service exchange among actors, we consider institutional arrangements highly significant for understanding the emergence of service ecosystems. To analyze institutional arrangements in more detail, different levels of context should be included. According to Chandler and Vargo (2011, p. 40), “a particular context [can be defined] as a set of unique actors with unique reciprocal links among them.” The authors distinguish three levels of context: (1) micro, (2) meso, and (3) macro (Chandler & Vargo, 2011). In the case of the micro-context level, a dyad is the unit of analysis, and the direct service exchange between the two actors, such as an app provider and a cooperating parking company, is examined. At the meso-context level, the focus is on a triad, for example, on an app-provider—parking company and a parking company—end-user relationship where indirect service exchange takes place. In contrast, the macro-context level focuses on complex ecosystems, examining how actors, dyads, and triads engage in direct and indirect service exchange. Since focusing solely 588 Information Systems Frontiers (2025) 27:585–604 1 3 on the macro-context level is insufficient to understand the value co-creation in a service ecosystem (Akaka & Vargo, 2015), we consider institutional arrangements at all three context levels to approach the emergence of smart parking ecosystems. Figure1 illustrates all the above-mentioned concepts and relationships of S-D logic for a smart parking ecosystem using an exemplary use case. Specifically, the figure depicts the different context levels, the value co-creation processes between the actors, and the institutional arrangements as the foundation of the value co-creation activities for each actor. In the following, we will analyze the institutional arrangements for each actor to understand how they lead to specialized instead of overarching service ecosystems in the case of smart parking in Germany. 2.2 Smart Parking The term smart parking can be anchored in the scientific literature in two ways. First, in the service and technology literature (e.g., Barile & Polese, 2010; Sharma etal., 2023; Wünderlich etal., 2015, p. 443), the addition of the term ‘smart’ highlights the emergence of a new service type “that is delivered to or, via an intelligent object, that is able to sense its own condition and its surroundings and thus allows for real-time data collection, continuous communication, and interactive feedback.” The concept of smartness includes different entities, such as devices, socio-technical systems, and automated systems (Alter, 2020), enabling different smart features, such as monitoring and optimization of services (Porter & Heppelmann, 2014). According to Sharma etal., (2023, p. 1293) such smart technologies can be characterized by three capabilities, namely”ubiquitous data, connectivity among objects, individuals, and organizations, and aggregation of information”, which leads to”exceptional engagement and intelligence, personalization, customization, contextual interaction, and automation”. Second, the term ‘smart parking’ can be attributed to the ‘smart city’ concept (Brauer etal., 2015). The smart city concept can be defined as a “[…] high-tech intensive and advanced city that connects people, information and city elements using new technologies […]” (Bakıcı etal., 2013, p. 139). Smart technologies in smart cities can then be applied to address cities' environmental, economic, and social challenges (Gupta etal., 2019), increasing the overall quality of life. The smart city concept enables different data-driven approaches, such as ‘smart mobility’, by deploying traffic data to optimize urban mobility (Kar etal., 2019). Moreover, smart mobility (e.g., availability of ICT infrastructure and innovative transport systems) Fig. 1 Exemplary smart parking ecosystem based on the concepts of the S-D logic 589Information Systems Frontiers (2025) 27:585–604 1 3 involves the use of an app and sensors placed on the parking spaces to provide information about their occupancy (Giffinger & Haindlmaier, 2010). Based on these concepts of smartness, smart parking is characterized in the literature as “[…] a way to help drivers find more efficiently satisfying parking spaces through information and communications technology […].” (Lin etal., 2017, p. 3229). Therefore, smart parking can be defined as a technology-driven approach aimed at optimizing the parking process through digital functionalities such as digital payment systems or real-time information on available parking spaces enabled by various sensors, all collectively contributing to behavioral shifts. Depending on the specific purpose of the smart parking system, different types of smart parking solutions can contain different systems and sets of functionalities (Diaz Ogás etal., 2020). However, a holistic approach, combining as many different functionalities as possible, is favorable to create overarching smart parking ecosystems. The ability to reserve a parking space and pay digitally is an important function of smart parking solutions (Hassoune etal., 2016; Idris etal., 2009). Access to a reserved parking space can be automated, for example, by using a camera-based solution that scans the vehicle’s license plate. According to Idris etal. (2009), smart payment systems are contactless (e.g., automated vehicle identification) or contact-based (e.g., credit card) solutions that do not require cash payment. In some cases, it is also possible to extend the parking time by smartphone, and dynamic prices are used as monetary incentives to use less popular parking spaces (Hassoune etal., 2016; Saharan etal., 2020). However, privacy and security concerns are two main hindrances to implementing smart payment systems (Al-Turjman & Malekloo, 2019; Idris etal., 2009). Furthermore, some studies analyze how the provision of smart parking solutions changes the behavior of car drivers regarding economic and environmental sustainability. For example, Rodier and Shaheen (2010) show how introducing a smart parking system can lower the drive-alone modal share, and Peng etal. (2017) and Mangiaracina etal. (2017) show that smart parking solutions contribute to the reduction of greenhouse gas emissions. Most relevant studies published beyond the IS field predominantly focus on the technical solutions that support a car driver during the different phases of the parking process. Numerous studies provide an overview of previous work or on specific technical solutions available in practice, such as Barriga etal. (2019), Hassoune etal. (2016), and Idris etal. (2009), who classify smart parking systems according to their functionalities, such as digital payment systems. The provision of information about free parking spaces is one of the essential functions of smart parking solutions, for which a variety of sensors, such as cameras, magnetometers, or radar sensors, can be used (e.g., Al-Turjman & Malekloo, 2019; Barriga etal., 2019; Idris etal., 2009; Perković etal., 2020). In summary, numerous smart parking studies take a technical perspective, and others focus on the behavioral changes caused by introducing a smart parking solution and related improvements in economic and environmental sustainability. Overall, there is a lack of studies examining socio-technical aspects, such as how the different actors (e.g., app providers, cities, and private parking operators) cooperate in practice. However, socio-technical aspects are crucial for IS implementations (Sarker etal., 2019), and a lack of understanding can hinder the emergence of overarching ecosystems as much as technical shortcomings. Our analysis of existing literature, therefore, shows that socio-technical factors leading to specialized ecosystems are so far not considered in the smart parking literature, although it is crucial to provide possible solutions to reach overarching smart parking ecosystems. To approach this question, we argue that the S-D logic perspective, with its embedded institutional arrangements on different context levels, is a suitable theoretical lens, as it enables an analysis of all services provided by the actors, their interrelationships, and the consequences for the emergence of specialized smart parking ecosystems. 3 Methodology 3.1 Case Study Research In this study, we chose a multiple-case design to gain insights into the factors that lead to specialized instead of overarching service ecosystems for smart parking (Yin, 2018). To get an overview of smart parking solutions in Germany, we first analyzed the smart parking app market using archival data. To gain a deeper understanding of institutional arrangements leading to specialized ecosystems, we then conducted 17 interviews with app providers and city and private parking operators from three different smart parking ecosystems. A case study research is defined as an analysis of “a phenomenon in its natural setting, employing multiple methods of data collection to gather information from one or a few entities (people, groups, or organizations)” (Benbasat etal., 1987, p. 370). In case study research, the boundaries of the phenomenon are not evident at the outset of the research, and no experimental control or manipulation is used. Our data collection methods include performing qualitative interviews and gathering data from archives (Eisenhardt, 1989). Case study research is considered appropriate when the research question is a ‘why’ or ‘how’ question, as in our study (Benbasat etal., 1987; Yin, 2018). In line with Benbasat etal. (1987), who argue that individuals, groups, and organizations are examples of cases, we define each service 590 Information Systems Frontiers (2025) 27:585–604 1 3 ecosystem as a case. The level of analysis is the app provider and the parking operators of a service ecosystem, as well as the institutional arrangements in which these actors are embedded. Based on these criteria, we decided to investigate service ecosystems whose actors want to realize smart parking in German cities: (1) Germany has an extensive parking infrastructure that is suitable for the installation of sensors to detect free parking spaces. (2) There are laws and high public pressure that aim to make people’s mobility behavior more sustainable. For example, due to the exceeding of legal limits for nitrogen oxides, it is forbidden to drive diesel cars in certain zones in some German cities like Berlin or Stuttgart (ADAC, 2019). (3) The results of previous studies (e.g., Schulz etal., 2023, 2021) show that the apps available on the market that support the switch from the private car to alternative mobility services still face numerous limitations in practice. For example, German public transport companies often do not generate real-time timetable data or operate a mobile ticketing system (Zimmermann etal., 2020). Smart parking apps, therefore, represent an important alternative to changing mobility behavior. 3.2 Overview ofSmart Parking Apps Table4 in the appendix provides an overview of the app providers that focus on realizing smart parking in German cities and their apps, which we identified based on an online search. Our analysis shows that the number of cities covered by the app varies widely. While the ParkPilot Köln app can only be used in Cologne, some other apps (e.g., mobilet.de, PayByPhone Parken) can be used in more than 300 German cities. However, it should be noted that an app usually cannot be used for all parking spaces and parking garages operated by a city. A function of some apps is that they help their users find an available parking space on the street, in parking garages, or in private and corporate parking spaces (e.g., Ampido, ParkHere Corporate). However, detecting free on-street parking spaces in real-time still seems to be a significant challenge due to the high number of parking spaces and, respectively, the high number of sensors that would be required. In some cities (e.g., Berlin, Hamburg), the ParkNow GmbH, therefore, uses a fleet of vehicles equipped with sensors to collect information about free parking spaces. However, most apps (e.g., PARCO) do not provide a comprehensive overview of available parking spaces in real-time, especially not on-street parking spaces. In contrast, the provision of that information represents a core function of the ParkPilot Köln and CityPilot apps. Some of the apps also offer navigation to a (free) parking space (e.g., EasyPark, ParkPilot Köln). In some cases, the user is forwarded to Google or Apple Maps, Android Auto, or Apple CarPlay for navigation (e.g., CityPilot app, PARCO app). A handful of apps (e.g., ParkHere Corporate, PARK NOW) also offer the option of storing the license plate number to automatically open the barrier of closed parking spaces and garages and/or start the recording of the parking time, although only for selected parking spaces. Digital payment of the parking fee is a core function of almost all apps. Several apps (e.g., Parkster, PARCO) offer the opportunity to purchase a parking ticket for a particular parking time and extend it if necessary. In some cities, however, a vignette or a handwritten note indicating the use of the app must be affixed to the vehicle to make it easier for inspectors to detect a possible parking violation. The Yellowbrick Germany app also offers users the opportunity to pay visitor parking fees. Invoicing of parking fees varies from immediately (e.g., PayByPhone Parken app) to weekly (Yellowbrick Germany app) or monthly (e.g., PARK NOW and PARCO app). App users usually have several payment options at their disposal, such as credit card, direct debit, and Paypal. This overview of the apps available for smart parking in German cities constitutes the basis for identifying suitable app providers for our data collection. 3.3 Data Collection Based on the overview of the app providers and their apps available for smart parking in German cities, we identified appropriate cases (i.e., service ecosystems) for our data collection. The overall aim of our data collection was to find appropriate interview partners to gain a deeper understanding of the institutional arrangements that lead to specialized instead of overarching smart parking ecosystems. In our selection, we also paid attention that the service ecosystems differed in terms of the number of cities included in the app, the number of app downloads (i.e., the number of users), and the core functions of the apps, especially whether the app focuses on displaying free parking spaces or on the payment of the parking fee. We requested interviews with the eight most appropriate app providers in terms of size and app functionalities. Our interview request was sent via email to the managing directors or, in one case, to the person responsible for business development. Three people responded positively and agreed to an interview. Further, we identified parking operators embedded in the respective service ecosystem through an online search (e.g., the website of the app providers). Our search revealed that some of the parking operators are members of the service ecosystem of more than one app provider. Based on a random choice, we selected 33 cities and private parking operators and conducted 14 interviews. On average, the 17 interviews lasted 26min each. All interviews were conducted by phone or via 591Information Systems Frontiers (2025) 27:585–604 1 3 computer software, such as Microsoft Teams and Zoom, from May to July 2021. All interviews were recorded and later transcribed. The interviews followed a semi-structured guideline. Semi-structured interviews offer a high degree of flexibility, which makes it possible to address issues that come to light during the interview (Flick, 2009; Myers & Newman, 2007). The questions asked of the experts of the cities and private parking operators were slightly different and included, among others, questions about the interviewee’s person, the city/company, and the cooperation with one or more app providers. In addition, we gathered secondary data (e.g., the city’s parking fee schedule and information about other payment options for parking fees) to supplement the interview data. Table1 provides an overview of the three cases and the actors analyzed. The app providers and the cities are abbreviated with AP and C. The private parking operators are an airport (AIR), a parking space service company (PSS), and a public transport organization (PTO). The cities (C1, C2, C6, and C7) marked with * are members of the service ecosystems of app providers 1 and 2. C8, which is marked with **, is embedded in the service ecosystems of app providers 1 and 3. 3.4 Data Analysis We analyzed the data collected using the software NVivo 12. The coding was done by one of the authors with several years of experience in qualitative research and data coding. The authors discussed the emerging coding structure and the preliminary results of the study in regular meetings. Such a common interpretation of the data material improves the reliability of the results (Miles etal., 2014). If the authors interpreted the data differently, discussions were held until a common understanding was reached. If necessary, the data material in question was re-analyzed. In addition, the data analysis includes the secondary data that we gathered, which enables us to verify and supplement the experts’ statements. Such data triangulation increases the quality of data analysis results (Flick, 2009; Miles etal., 2014). Because the S-D logic literature provides only limited knowledge of how institutional arrangements influence the emergence of service ecosystems (e.g., Schulz etal., 2020; Vargo & Lusch, 2017), we adopted a three-stage iterative coding approach (Strauss & Corbin, 1998). (1) In open coding, we identify the institutions and their rules, norms, and beliefs that enable or constrain the service exchange among actors (Schulz etal., 2020; Vargo & Lusch, 2017) and thus Table 1 Overview of cases and actors Case Actor Role of interviewee Number of inhabitants Number of parking garages Number of parking spaces Case 1 AP1 Managing Director C1* Smart City Manager ≤ 300,000 ≤ 20 n.a C2* Head of surveying department ≤ 150,000 ≤ 10 n.a C3 Head of economic development ≤ 100,000 ≤ 10 n.a C4 Traffic Planner ≤ 25,000 n.a n.a C5 Mobility Manager ≤ 25,000 n.a ≤ 2,000 C6* Business Unit Manager for Digitization ≤ 150,000 ≤ 10 ≤ 6,000 C7* Head of department for civil engineering ≤ 100,000 ≤ 20 n.a C8** Employee environmental office ≤ 100,000 n.a ≤ 4,000 Case 2 AP2 Managing Director C1* Smart City Manager ≤ 300,000 ≤ 20 n.a C2* Head of surveying department ≤ 150,000 ≤ 10 n.a C6* Business Unit Manager for Digitization ≤ 150,000 ≤ 10 ≤ 6,000 C7* Head of department for civil engineering ≤ 100,000 ≤ 20 n.a C9 Head of traffic control ≤ 25,000 ≤ 5 ≤ 2,000 C10 Head of public safety and order department ≤ 25,000 n.a ≤ 4,000 C11 Team leader for citizen services, registry office and public order office ≤ 25,000 n.a ≤ 2,000 Case 3 AP3 Employee Business Development C8** Employee environmental office ≤ 100,000 n.a ≤ 4,000 AIR Manager E-commerce / parking ≤ 5 ≥ 10,000 PSS Head of organization department n.a n.a PTO Employee bus transportation ≤ 5 ≤ 4,000 592 Information Systems Frontiers (2025) 27:585–604 1 3 influence the emergence of the service ecosystems for smart parking. (2) Our axial coding is based on the assumption of the S-D logic perspective that multiple interrelated institutions constitute an institutional arrangement (Vargo & Lusch, 2017). In other words, based on the open codes, we formed sub-categories depicting institutional arrangements that are in place in the service ecosystems (Vargo & Lusch, 2017), such as the use and management of data, and explain on a more detailed level why specialized service ecosystems emerge. (3) in selective coding, we used the sub-categories to create categories that cover the contextual levels – micro (dyad), meso (triad), and macro-level (Chandler & Vargo, 2011) – to which each institutional arrangement is linked. We then compared the coding for the three cases to gain insights into how different institutional arrangements lead to the emergence of specialized service ecosystems. 4 Results In the following, we first present institutional arrangements on different contextual levels (macro, meso, and micro) to explain the main reasons for the emergence of each specialized smart parking ecosystem separately. Afterward, we examine cross-case similarities and differences to form overarching insights into smart parking ecosystems in Germany. 4.1 Case 1 Our first case includes the ecosystem of AP1 and the cooperating cities C1-C8. AP1 is one of the biggest smart parking providers in Germany, and its app is available in many different cities, inside and outside of Germany. Their app provides functionalities to help users find available parking spaces on the street and in parking garages, and they offer digital payment functions. According to AP1, they aim for overarching solutions for end users. Moreover, they offer tailored cooperation models, depending on the requirements of their partners, such as different pricing models (e.g., for park-and-ride areas), and cooperation to promote public transportation is getting more popular. (AP1). At the macro level, we find institutional arrangements regarding politics, environment, and end-user preferences in Germany inhibiting an overarching integration of the smart parking ecosystem. In four cities (AP1, C1, C2, C4, C8) and in the interview with the app provider, the interviewees stated that political reasons inhibit a broader integration of smart parking systems. While for C1 the integration of private parking areas to enhance the parking search system is the most relevant factor, C4 stated, “The conversion [to a smart parking system] costs money. And there must be political will to spend the money.” Making city traffic more environmental-friendly is considered one of the reasons to implement a smart parking system in cities (AP1, C1, C4) because “Less parking search traffic improves not only air quality but also noise and safety as well” (C4). However, there are also concerns that “Making city center parking more attractive will ultimately hurt the transportation transition and the shift to public transit and bicycles” (C1), which can inhibit further expansion of smart parking initiatives. According to seven (C1-C3, C5-C8) representatives of the cities in this ecosystem, one of the main reasons (i.e., institutional arrangements) for the emergence of specialized smart parking ecosystems is conflicting end-user preferences in Germany. Most of the city representatives report that only a minor proportion of citizens, ranging from 2%-30% (C2, C3, C5, C7, C8), use the smart parking offers, and only C1 stated that “at the beginning, [the diffusion rate] was very slow, in the meantime, it should have spread much stronger.” There are two major drivers of the lack of acceptance: many people living in Germany prefer to pay by cash rather than digitally (AP1, C7), and especially elderly people living in Germany are not skilled in using a smartphone (C3 and C7), whereas “Younger generations, in particular, have a very high digital affinity” (C3). City representatives are conscious that “[…] we must not exclude older generations who may still find these topics a little difficult” (C3). At the meso level, we find that institutional arrangements regarding the billing process and data use foster overarching integration of the smart parking ecosystem, while data analysis inhibits overarching integration. Regarding digital billing, AP1 stated, “I think you can see this topic under the aspect of making it as easy as possible to [fun and] use [available parking spaces]. That’s where we try to help.” The easier billing process, again, is also an important aspect for the cooperating cities. As mentioned by C1, “The way we currently operate [smart parking], it is only a pure processing advantage” (C1, C2, C3, C4, C5, C6, C7). Moreover, many city representatives consider the current form of their cooperation a starting point to drive digitization forward, as stated by C3: “I think we are generally in a digitization process in C3, where we are trying to digitize all processes […], and therefore it is also necessary that you digitize such billing processes” (C3, C5, C7). The additional service regarding the billing process is not only relevant for the cities but is also extended to end users: “So basically, we see [payment via smartphone] as an additional service” (AP1). The cities also value this additional service for their citizens, especially considering the higher flexibility, as parking can be paid for “on the go” and not in advance for an estimated duration (AP1, C1, C2, C3, C6): “You can—depending on the provider—simply start the parking process to the minute and end it to the minute” (C2). Moreover, AP1 has integrated functionality for the 599Information Systems Frontiers (2025) 27:585–604 1 3 constitutes smart parking solutions (e.g., Hassoune etal., 2016; Saharan etal., 2020) that we find not fully evolved in our analyzed ecosystems. For instance, Hassoune etal. (2016) defined reserving parking spots and digital payment systems as important functionalities, or socio-technical systems, not embedded in all our analyzed ecosystems (Alter, 2020). Also, the ability to address environmental and social challenges with smart technologies is not fully exploited yet due to privacy and security concerns (AlTurjman & Malekloo, 2019; Gupta etal., 2019; Kar etal., 2019), as former literature show that comprehensive smart parking systems can lower the drive-alone modal share, therefore contributing to the reduction of greenhouse gas emissions (Mangiaracina etal., 2017; Peng etal., 2017). Overall, we conclude that the current smart parking ecosystems in Germany show promising approaches to exploit the potential stemming from smart devices, socio-technical systems, and automated systems but still lack crucial development steps to fully transform parking into smart parking processes in the sense of a smart city. 5.1 Theoretical Implications Our work has three main theoretical contributions. First, we complement the scientific literature on smart parking with an ecosystem perspective that focuses on factors that lead to the emergence of specialized ecosystems. While many papers take a predominantly technical perspective (e.g., Al-Turjman & Malekloo, 2019; Barriga etal., 2019; Idris etal., 2009; Perković etal., 2020), there is little research that examines how actors use the available technology. Based on our literature review, we also find that, with some exceptions (e.g., Chovani & Jokonya, 2019; Schulte etal., 2021), very few studies have been published in the IS field with a focus on smart parking – from either a technical or non-technical perspective. Accordingly, our study can be understood as a call for further research on this topic and its socio-technical aspects. Future research in IS can particularly build on the overview of the functions of the apps currently used for smart parking in German cities (Table4) to highlight the gap between technical feasibility and actual use in practice. Second, we contribute to the further development of the S-D logic perspective (Vargo & Lusch, 2004) by showing how institutional arrangements lead to the emergence of various specialized service ecosystems. The literature on the S-D logic perspective provides a limited understanding of how service ecosystems emerge and how actors, such as app providers, establish their position (Vargo & Lusch, 2017). However, it is assumed that “breaking, making, and maintaining” (Koskela-Huotari etal., 2016, p. 2964) institutional arrangements can facilitate value co-creation among actors, which in turn influences the emergence and design of service ecosystems. Although there is initial empirical evidence that conflicting institutional arrangements lead to actors not joining a service ecosystem (Schulz etal., 2023), it is still unknown how institutional arrangements lead to the emergence of different specialized service ecosystems as we observe them in practice in the field of smart parking. Third, in the present study, we addressed this research gap by taking a multiple case study approach and analyzing three ecosystems that each focus on specific aspects of the parking process (e.g., digital payment, data analysis). In line with the S-D logic literature, we argue that context is important to understanding the emergence of smart parking ecosystems. Our results show how the different levels of the context – defined as micro, meso, and macro (Chandler & Vargo, 2011) – and the respective institutional arrangements (e.g., the low acceptance rate of digital payment in Germany) contribute to the emergence of specialized service ecosystems. For example, the limited political support by municipalities or state-level governments leads to limited financial possibilities for many cooperating cities to integrate more than one app provider into their smart parking ecosystem. More specifically, we find that institutional arrangements at the macro-level (especially political arrangements and end-user preferences) often serve as a starting point for app providers, cities, and private parking companies for their targeted smart parking solution. For example, the low acceptance rate of digital payment in Germany leads to a specialization towards a data-driven business model for one of the app providers. This, in turn, influences the institutional arrangements at the micro and meso context level and leads to a lack of overarching smart parking solutions. Therefore, institutional arrangements at the macro level seem to be especially relevant for the degree of specialization of emerging smart parking ecosystems. 5.2 Practical Implications Our work provides two main practical contributions. First, we provide an overview of the apps available for smart parking in German cities, which practitioners can use to advance along the path toward smart cities. Our overview shows that despite technical progress (development of sensors, big data approaches, etc.), smart parking apps still lack important functionalities in practice. For example, real-time data on occupancy is provided for only a small number of parking spaces, and forecasts of availability at the calculated arrival time are still problematic. In addition, the overview can also be understood as a call to practitioners to better exploit the potential of digitalization to address urgent problems, such as reducing parking search traffic to reduce air and noise pollution and thus make cities more environmentally sustainable. 600 Information Systems Frontiers (2025) 27:585–604 1 3 Second, based on the interviews with cities and private parking operators, we can make recommendations to enhance smart parking solutions to promote their usage rates. Our results underscore the importance of matching app functionalities to user preferences from the customer's perspective. For example, in their study of the smart parking system in London, Peng etal. (2017) explain that public awareness, its usage, and user satisfaction are currently very low, which constrains the realization of its potential economic and environmental benefits. The user ratings for the apps that aim to enable smart parking in German cities also indicate a rather low level of user satisfaction (Table4). However, the use of apps is of great importance for the enhancement of smart parking as many data-related functions, such as navigation to free parking spots, are only possible via app usage. Our interviews with parking operators provide starting points for several potential improvements to smart parking solutions. Our results show that private parking operators (Case 3) better exploit data-related possibilities than most cities. The airport operator (AIR), for example, uses the possibility of dynamic prices to manage occupancy and increase turnover. One reason for this is certainly that cities are responsible for a much higher number of parking spaces, especially on-street parking spaces, which makes it time-consuming and expensive to equip the entire city area with sensors. Accordingly, one possibility to optimize smart parking solutions in cities would be to outsource the responsibility for the operation of parking spaces to private companies within a public–private partnership framework. Another reason is the non-digital mindset of many cities, which, for example, is evidenced by the need to affix a vignette or a handwritten note indicating the use of a smart parking app to the vehicle. Corresponding change management should be carried out in the cities to establish a suitable culture that focuses on the citizens and their growing interest in digitized solutions. An even higher orientation toward citizens' needs could be achieved if the data about parking occupancy were provided in overarching apps for cities that can also be used for other purposes, such as public transportation or to provide information about recreational facilities. 5.3 Limitations andFuture Research Our work has some limitations, which should be addressed in future research. First, we have limited our data collection to app providers and parking operators in Germany. As with residents of cities in many other countries, residents of German cities are negatively influenced by parking search traffic. The noise pollution and greenhouse gas emissions and other negative effects it causes negatively affect their well-being and health (Anenberg etal., 2019). From this perspective, our results are highly transferable. However, there are also some limitations to the transferability of our results. For example, people living in Germany have a lower level of acceptance of digital payment methods than people living in other European countries (EZB, 2021), which makes it difficult to reap the fruits of digitalization in general and smart parking in particular. To overcome this limitation, similar studies should be conducted in other countries to gain new insights into the emergence of specialized service ecosystems for smart parking through a cross-country analysis. Second, in our analysis of the service ecosystem, we collected data from the app providers and parking operators but not from end users. In line with the S-D logic perspective, we assume that end users, for example, by providing data with their smartphone, are engaged in value co-creation and thus contribute to the emergence of specialized smart parking ecosystems. Future research should examine value co-creation in customer-to-business relationships to obtain a complete picture of the service ecosystem. One possible approach would be to analyze data from smart parking app user reviews and ratings on app store websites. From a theoretical perspective, we have shown how institutional arrangements at the micro, meso, and macro context levels lead to the emergence of specialized service ecosystems for smart parking. Our study is grounded in recent S-D logic literature (e.g., Schulz etal., 2020; Vargo & Lusch, 2017), so we can assume that empirical evidence from the area of smart parking is sufficient to support the validity of our theoretical argumentation. Nevertheless, studies should also be conducted in other related areas, such as mobility ecosystems with public transportation and car-sharing providers, to examine the theoretical assumption about the effects of institutional arrangements on the emergence of specialized service ecosystems. 6 Conclusion The use of private cars leads to numerous problems that negatively affect the population. Especially in cities, drivers looking for a free parking space contribute significantly to traffic volumes, leading to greater frustration, wasted time, costs, energy consumption, and noise and air pollution. Smart parking is one approach to reducing parking search traffic and the problems it causes. However, despite the existing technical possibilities, smart parking is still in its infancy, and overarching solutions for end users are lacking. In this study, we take a S-D logic perspective to theorize how institutional arrangements at the micro, meso, and macro context 601Information Systems Frontiers (2025) 27:585–604 1 3 level result in smart parking apps being limited to certain functionalities (e.g., digital payment processes). To test our theoretical assumptions, we analyze empirical evidence collected in case studies with three service ecosystems aiming to enable smart parking in German cities and private parking areas. With our research, we use a theoretical analysis to tackle the practical problem of smart parking burdens in Germany, using insights from the scientific literature and practical insights smart parking industry specialists. By taking a socio-technical, and therefore interdisciplinary perspective, we unravel new insights including aspects from technical, behavioral, and economic research fields. Our results provide a theoretical foundation for the different factors leading to specialized service ecosystems. In addition, our results help practitioners to develop overarching smart parking solutions and advance along the path toward smart cities. Appendix Table4 Table 4 Overview of the app providers and their apps available for smart parking in German cities App provider name App name Number of cities the app can be used Number of app downloads User rating Core functions of the app Ampido GmbH Ampido n.a 100,000 + 4.6 Display of free parking spaces that are provided by private individuals, booking, digital payment, navigation Cleverciti Systems GmbH ParkPilot Köln 1 100 + n.a Display of free parking spaces, navigation, digital payment (by forwarding) EasyPark GmbH EasyPark > 2,200 cities in Europe 5,000,000 + 2.8 Option to extend the parking time, charging per minute, digital payment ParkHere GmbH ParkHere Corporate n.a 1,000 + 3.8 Reservation of a parking space in a company’s parking garage ParkNow GmbH PARK NOW 317 1,000,000 + 4.6 Charging per minute, digital payment at the end of month Parkster GmbH Parkster 344 1,000,000 + 4.4 Overview of parking spaces, option to extend the parking time, charging per minute, digital payment at the end of month Smart City System Parking Solutions GmbH CityPilot n.a 500 + 4.2 Display of free parking spaces Stadtraum GmbH mobilet.de 352 10,000 + 2.4 Option to extend the parking time, charging per minute, digital payment Sunhill Technologies GmbH PayByPhone Parken 355 500,000 + 4.0 Overview of parking spaces, option to extend the parking time, charging per minute, digital payment SWARCO TRAFFIC SYSTEMS GmbH PARCO 208 10,000 + 3.5 Overview of parking spaces, option to extend the parking time, charging per minute, digital payment at the end of month Yellowbrick GmbH Yellowbrick Germany 101 5,000 + 2.1 Charging per minute, payment of visitor parking fees, digital payment at the end of week 602 Information Systems Frontiers (2025) 27:585–604 1 3 Acknowledgements We would like thank the BayWISS Consortium Digitization for financially supporting Sina Zimmermann and Dr. Thomas Schulz. We would also like to thank the Bavarian State Ministry of Science and the Arts for funding Dr. Thomas Schulz. Authors' Contributions Each author made a significant contribution to the acquisition, analysis, and interpretation of the interview data and/ or to the conception of the manuscript. Funding Open Access funding enabled and organized by Projekt DEAL. Sina Zimmermann and Thomas Schulz received partial financial support by the BayWISS Consortium Digitization. Thomas Schulz is funded by the Bavarian State Ministry of Science and the Arts. Data Availability The interview data analyzed during the current study are not publicly available due to data privacy reasons but are available from the corresponding author on reasonable request. Declarations Ethics Approval and Consent to Participate Not applicable. Consent for Publication All authors consent to the manuscript being published by ISF. Competing Interests The authors retain full responsibility for the content of this publication and there are no competing interests. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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Sina Zimmermann (sina.zimmer[email protected]) is a PhD student at the Technical University of Munich (TUM),Munich, Germany, and works as a research associate at the Neu-Ulm University of Applied Sciences in Germany.She graduated in Management and Economics from Ulm University, Germany. Her research focus is on digitalnudging, sustainability and digital transformation in the mobility sector. Her work has been published in the Journalof Decision Systems, Technological Forecasting & Social Change, and in conference proceedings such as theEuropean Conference on Information Systems (ECIS) and the Pacific Asia Conference on Information Systems(PACIS). Thomas Schulz ([email protected]) holds a PhD of the Technical University of Munich (TUM), Germany inInformation Systems, and worked as a research associate at the Neu-Ulm University of Applied Sciences until 2022.He graduated in Management from University of Hohenheim, Germany. His research focus is on serviceecosystems, service platforms, and value co-creation in the mobility industry. His work has appeared, among others,in Business & Information Systems Engineering, Electronic Markets, Information Systems Frontiers, TechnologicalForecasting & Social Change, the International Conference on Information Systems (ICIS), and the EuropeanConference on Information Systems (ECIS). 604 Information Systems Frontiers (2025) 27:585–604 1 3 Andreas Hein ([email protected]) is a research group leader at the Chair for Information Systems, TechnicalUniversity of Munich (TUM), Munich, Germany. He holds a Master’s degree at TUM in Information Systems. Inaddition, Andreas has three years of experience as a Senior Strategy Consultant at IBM. His work has appeared injournals such as the Journal of Strategic Information Systems, Information Systems Journal, European Journal ofInformation Systems, Government Information Quarterly, Business & Information Systems Engineering, ElectronicMarkets and refereed conference proceedings such as ICIS, ECIS, PACIS, AMCIS, and HICSS. Andreas focuses hisresearch on digital platform ecosystems. Alexander Felix Kaus (alexander[email protected]) is a master student in IT projectand process-management atAugsburg University of Applied Sciences, Germany. He holds a bachelor’s degree in Information Systems fromUlm and Neu-Ulm University of Applied Sciences, Germany. In his Bachelor thesis he focused on ecosystems andsmart parking in Germany. Heiko Gewald (heiko.gew[email protected]) is a research professor of Information Management at Neu-UlmUniversity of Applied Sciences in Germany and Director of the Institute for Digital Innovation (IDI). He holds anMSc in Business Administration from University of Bamberg, an EMBSc from Heriot-Watt University Edinburghand a PhD in Information Systems from Goethe University Frankfurt. His research focuses on the use of digitalresources by the aging generation, HealthIT, and IT Management. His work has been published in the EuropeanJournal of Information Systems, Information & Organization, Information & Management, Communications of theACM, and presented on numerous international conferences.