Destination management organisations used to be primarily viewed as marketing organisations for destinations [13]. The main focus was to increase competitiveness and continuously improve the tourist experience, which in turn was expected to lead to increased visitor numbers and income [14]. This one-sided view has undergone a shift in recent years due to external dynamic challenges and internal demands on the tourism industry. Among other things, the external factors include an increased importance of sustainability [15] and the rapid development of information and communication technologies (ICTs) [16]. One of the internal factors that DMOs have to take into consideration is the importance of integrating residents and their support for tourism in order to have well-functioning and sustainable destination development [17]. In recent times, the need to react appropriately to different crises and to be resilient [18] has caused destinations to redefine their roles. To effectively accommodate these more complex destination demands, it is no longer sufficient to simply work on destination marketing. Contemporaneous DMOs are, therefore, shifting away from destination marketing and management, through destination governance, and to destination leadership, taking up place-making embedded in an actor network [19]. Therefore, there is a growing need for DMOs to adopt new organisational concepts in destination governance. To face future challenges, and to reach individual and collective goals, building networks seems to be a promising approach [10]. As DMOs have specific roles as coordinators, communicators, and networkers [20], they can be regarded as stewards of such networks, which try to balance the needs of all destination stakeholders through a participatory approach [21]. In addition, innovation, leadership, and social and human capital are important characteristics of a modern DMO, especially when it comes to integrating technological infrastructure for a successful smart destination development [22]. In our context, the consideration and use of information and communication technologies, as well as the collection and evaluation of tourism-related data, are prerequisites for the development of smart tourism destinations. Thus, DMO structures need to be fundamentally changed so they can incorporate the benefits of the digitalisation that will provide the best possible tourist experience at the destination [16,23]. To address these challenges, the new fundamental functions of smart DMOs are discussed [24]. Among others things, the installation of a smart tourism infrastructure is one solution that could improve smart tourist experiences.

Smart destinations can be defined as “places utilising the available technological tools and techniques to enable demand and supply to co-create value, pleasure, and experiences for the tourist and wealth, profit, and benefits for the organisations and the destination” [25] (p. 394). Smart solutions and technologies include, for example, ubiquitous public Wi-Fi, big data analytics tools, advanced DMO websites, blogs, apps, QR codes and geotags [26], social media, augmented and virtual reality [26,27], sensor technology, and near-field communication technology [27,28]. These technological components can be transformed into digital services that can enhance the real-life experience of tourists. Examples of this are automated check-in processes and digital payment.

These smart technologies can play a crucial role in optimising strategies aimed at avoiding the negative effects of tourism caused by overtourism [29]. They can be viewed as enablers in developing and implementing such strategies. Many popular cities that struggling with overtourism are now using smart digital solutions to implement mitigation strategies [27].

Camatti et al. [29] distinguished three steps for the application of digital solutions to overcome overtourism issues. The first was to calculate the tourism carrying capacity and set its limits. The second involved controlling and gathering data through the use of information and communication technologies and monitoring systems, such as GPS-based tracking, artificial intelligence (AI)-based systems, geotagging, movement data, and big-data analytics tools. The third step was to define and initiate actions and policies for mitigating the overtourism issues, such as demarketing and creating alternative offers [27,29].

The information gathered in the second step can be used for dispersing tourists by informing them about the number of spaces available at an attraction and suggesting alternatives [36]. Strategies for demarketing, managing new attractions, and regulating activities can be implemented through, for example, social network marketing, mobile apps or tourist cards for use at attractions. Other examples include the use of measurement tools and smart technologies to efficiently manage traffic, or the use of augmented and virtual reality to create new tourist experiences [27,36].

Several approaches can be used for changing visitor behaviour through digital visitor management systems [37]. These intended behavioural changes must be considered when designing ways of transmitting information to visitors. Nudging is considered to be one of these approaches. It stems from both social psychology and behavioural economics [38,39], and is defined as “an intervention on the choice architecture that is predictably behaviour-steering, but preserves the choice-set and is (at least) substantially non-controlling, and does not significantly change the economic incentives” [40] (p. 343). In digital choice environments, influencing people’s behaviour with the help of user-interface design elements is known as digital nudging [41]. Meske and Potthoff [42] substantiate the definition by adding the essential elements of respecting the freedom of choice without changing the choice options as well as the subtle character of nudging strategies. Furthermore, according to them not only the user-interfaces, but also the way of giving information can be a nudge [42].

In contrast to other approaches aiming at changing visitor behaviour—such as persuasion strategies—nudging can be considered a rather soft paternalism approach. Paternalism is defined as “the interference of a state or an individual with another person, against their will, and defended or motivated by a claim that the person interfered with will be better off or protected from harm” [43]. Nudges are often considered in the context of libertarian paternalism. This liberty-preserving soft paternalism approach aims at steering people towards a decision that increases their wellbeing while preserving freedom of choice [44,45]. Thus, such soft paternalism is considered less intrusive and less manipulative [44,46] than stronger forms of paternalism. It must also be noted that the recipient’s wellbeing is a subjective matter [47]. Furthermore, a nudge can also lead to a decision that promotes a different nudging goal, for example, improving the common good [48].

In research, different categorizations and types of (digital) nudges have been proposed by several authors, e.g., [42,48,49,50]. These and other authors agree that nudges in a digital visitor management system can, for example:

• Simplify the information and reduce the distraction while maintaining the same choice options;
• Present the information in a specific way with the help of framing mechanisms and highlight specific choice options;
• Rank the choice options in a chosen order;
• (Constantly) remind people which activity they might want or should do;
• Utilize social norms and social influence to show people what others have chosen to do since people often act according to the behaviour of others;
• Use direct and personal recommendations that point out the targeted activity and promote the targeted decision.

The decision of which nudge will be used to influence the behaviour of the visitors should be made with regard to the desired outcome as well as the information behaviour of the visitors [48] and the underlying psychological theories [49]. Therefore, Karlsen and Andersen [48] propose the following several steps to decide on the right nudge: (1) Define the goal; (2) Understand the users; (3) Understand the situation; (4) Select the targeted activity; (5) Select relevant information; and (6) Design the nudge [48]. Afterwards, the nudge needs to be presented and its success needs to be evaluated.

The listed nudging measures respect the freedom of choice of the recipients while also trying to guide them towards a decision that benefits their wellbeing. In the hedonistic tourism context, factors such as pleasure and relaxation should be considered part of the recipient’s wellbeing [51]. On top of that, nudges in digital visitor management decision can, at the same time, benefit the destination and promote a more sustainable behaviour. With regard to tourism, the nudging approach is, therefore, considered to be a useful tool for sustainable development [39] in destination management [52]. This is because customer centricity is a deeply inherent value in tourism, and is particularly practised in the field of hospitality management. Therefore, for a DMO it is important to consider the following two conditions: “no reduction in the quality of the vacation experience for the tourist, and no increase in cost for the business implementing the intervention” [51] (p. 9) when implementing a nudge-based digital visitor management.

Recommender systems can be defined as “software applications that help users to find items of interest in situations of information overload” [53] (p. 105). Against the backdrop of the rapid development of ICT, combined with the increased use of machine-learning methods, recommender systems are increasingly being used in tourism. In a tourism context, recommender systems, usually displayed via smartphone apps [8], websites [54], chatbots [55] or other mobile applications, can help to provide (personalised) information on tourist destinations, activities, and points of interest, or can help to reduce disinformation. Smart solutions are needed to mitigate negative crowding effects at tourist destinations (see Section 2.2) and to balance tourist flows at tourist destinations. In the context of digital visitor management, digital recommender systems can provide both forecasts of the future occupancy of a specific location and alternative destinations in addition to visit/do-not-visit recommendations.

When it comes to trip planning, tourists require a vast amount of information [56]. Compared to classic route recommendations using digital tools (e.g., Google Maps), oriented towards pure time and cost assessments, the personal preferences of tourists have to be considered when dealing with tourist activities, such as city tours or hiking trails [54]. Consequently, recommender systems, which are hyper-personalised in terms of communicating with their users (e.g., via WhatsApp), are promising because they are rated much better than passive applications [57].

Web applications for trip planning were already being employed when recommender systems began to be used in tourism [54], and recommender solutions are now being used in trip planning [58]. However, recommender solutions can generally be used in all types of tourism, including urban tourism [59] and cultural tourism [60], and in every phase of the trip, with the tourists’ need for a personalized service (e.g., transport, attractions) being high [61]. However, efficient tourist recommender systems have to consider the context they are being applied to, and should be designed accordingly. Tan et al. [62] used the acronym “TILES” (i.e., temporal, identity, location, environment, and social) to describe the categories of tourists’ most important information needs and requirements [62].

However, despite the elaboration of theoretical frameworks for such systems [56,63], there are currently no acceptable solutions that work in practice [8,36]. Although there are already systems that can guide the user through graphical interaction, such as smartphone apps, or give passive support, as seen in route planners, these do not reflect the idea of a recommendation system for digital visitor management. In particular, there is no AI recommender that can provide information on how frequented certain POIs are, based on sensor data, that could practically tackle overtourism issues. Nonetheless, empirical evidence shows that it is possible to use recommender systems in tourism to guide tourists to less visited places that have been recommended by a DMO without exacerbating the tourist experience [57].