How Heidi helps: designing for inspiration in digital travel assistants

Friedli, Jan; Dolata, Mateusz; Schwabe, Gerhard Article — Published Version How Heidi helps: designing for inspiration in digital travel assistants Information Technology & Tourism Provided in Cooperation with: Springer Nature Suggested Citation: Friedli, Jan; Dolata, Mateusz; Schwabe, Gerhard (2025) : How Heidi helps: designing for inspiration in digital travel assistants, Information Technology & Tourism, ISSN 1943-4294, Springer, Berlin, Heidelberg, Vol. 27, Iss. 4, pp. 1047-1080, https://doi.org/10.1007/s40558-025-00328-0 This Version is available at: https://hdl.handle.net/10419/330877 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. https://creativecommons.org/licenses/by/4.0/ ORIGINAL RESEARCH Information Technology & Tourism (2025) 27:1047–1080 https://doi.org/10.1007/s40558-025-00328-0 Abstract The emerging trend of inspirational Digital Travel Assistants (DTAs) is rapidly gaining prominence in the tourism industry yet remains underexplored in academic literature. This paper examines how inspirational DTAs can be designed to facilitate travel inspiration through autonomous and efficient co-creation at scale. Grounded in the literature on co-creation within the domain of travel planning (SchmidtRauch and Schwabe 2014) and the framework of customer inspiration (Thrash and Elliot 2003), this study employs a design science research (DSR) methodology to explore how to offer personalized travel inspiration through co-creation, catering to the evolving needs of modern travellers. We present an artefact of an inspirational DTA, named Heidi, as one example of how to facilitate this. Heidi was developed by Swiss International Airlines (part of the Lufthansa Group) in collaboration with Google. The evaluation was conducted via semi-structured interviews with three members of the HEIDI initiative and eleven users engaging with the design artefact. This research makes three contributions. First, we demonstrate a means–end relationship between co-creation (means) and inspiration (end) to conceptualise inspirational DTAs. Second, we propose actionable design principles for the development of inspirational DTAs. Lastly, this study extends the academic discourse on information systems in travel advice from IT-enabled human agent setups to IT-enabled virtual agent configurations, positioning inspirational DTAs as a novel paradigm in the evolving landscape of travel inspiration. Keywords Digital assistant · Travel inspiration · Co-creation · Travel planning Received: 24 November 2024 / Revised: 4 June 2025 / Accepted: 9 June 2025 / Published online: 2 July 2025 © The Author(s) 2025 How Heidi helps: designing for inspiration in digital travel assistants JanFriedli1· MateuszDolata1,2· GerhardSchwabe1 Extended author information available on the last page of the article 1 3 J. Friedli et al. 1 Introduction The rapid emergence of various Large Language Models (LLMs) has spurred the development of digital assistants, particularly in the tourism industry, where they are used to enhance travel inspiration and planning. Several organizations have capitalized on this opportunity by developing their own versions of inspirational Digital Travel Assistants (DTAs). For instance, Expedia introduced Romie, an inspirational DTA designed to assist customers in exploring a wide range of travel options. Likewise, Trip.com launched TripGenie, offering instant travel tips, inspiration, and itinerary suggestions. Startups such as Otto and Maya have also entered the market, utilizing generative AI technologies to provide similar services. The driving force behind this trend is the significant potential in travel inspiration and planning, as evidenced by Eurostat data showing that EU tourism reached a record 1.2 billion nights in the first half of 2024 (Eurostat 2024). As these emerging inspirational DTAs reshape digital retailing within the tourism industry, their influence is increasingly evident. The Lufthansa Group is a major global airline organisation, operating several prominent carriers including German Lufthansa, Swiss International Air Lines, Austrian Airlines, and Brussels Airlines. With a vast network spanning over 300 destinations across more than 100 countries, the Group connects key international hubs in Europe to major cities and regions worldwide, transporting over 120 million passengers per year. Given the prominent position of the Lufthansa Group in the travel sector, the growing trend towards inspirational DTAs is of critical importance for two reasons, which collectively, constitute as the ‘instance problem’. First, the Lufthansa Group faces an increasing risk of losing customers to rival inspirational DTAs due to evolving customer expectations within the inspirational phase of digital retailing. Second, the Lufthansa Group may also jeopardize its position in the premium market if it fails to effectively inspire customers on a large scale to build their personalized travel experiences. In collaboration with Google, a new initiative has been launched to create a public proof of concept (PoC) for an inspirational DTA artifact, called Heidi. Piloted by Swiss International Air Lines, this initiative aims to provide the Lufthansa Group with a winning position in the newly forming arena of inspirational DTAs. The overarching design objective for Heidi, serving as an inspirational DTA of the Lufthansa Group, is to facilitate travel inspiration through the autonomous and efficient cocreation at-scale (see Sect. 4.2). The aim of this paper — and the Heidi initiative — are to explore how inspirational DTAs can be designed to facilitate travel inspiration through the autonomous and efficient co-creation at scale. From a practical standpoint, this research could help to democratize personalized travel inspiration through co-creation in line with an emerging customer need. From a research standpoint, the broader trend of inspirational DTAs remains underexplored in academic literature, particularly within design research (see Sect. 2.4). While the rationale for this research on inspirational DTAs arises from the growing momentum within the travel industry, the abstract research problem is grounded in two identified gaps within the current body of research – both of which have been 1 3 1048 How Heidi helps: designing for inspiration in digital travel assistants validated with a structured literature review (see Sect. 3.2). First, there is a lack actionable and theoretically motivated guidance on how to achieve inspiration with DTAs. Such guidance would be valuable as it would allow users to (co-)shape their personalized travel plan in a collaborative experience, ensuring they feel both autonomous and supported, and therefore efficient. Second, we note that it remains open how co-creation and inspiration relate to each other, despite some research implying such a relationship. Considering these identified research gaps, we suggest that a theoretically motivated investigation of inspirational DTAs is promising, as they offer a radically new option to addressing co-creation challenges — positioning co-creation as a pathway to utility, specifically as a means for enabling inspiration (see Sect. 2.4). Further, the evaluation of the Heidi artefact is valuable because it uncovers the systematic design principles that can be shared for inspirational DTAs in the abstract, making this knowledge publicly accessible. Moreover, the evaluation reveals several design and knowledge gaps that Heidi fills in comparison to other systems, potentially setting new directions in the field of inspirational DTAs (see Sect. 6). Thus, this research objective holds significant relevance for both the academic research community and practical applications in the tourism industry. Given the emerging nature of inspirational DTAs, the Design Science Research (DSR) method was employed for this study. The core objective of DSR is the rigorous creation and evaluation of artifacts to generate new knowledge about specific, relevant problem classes and their solutions (Hevner and Chatterjee 2010). Empirical evidence was generated throughout the iterative development and evaluation the instance solution (Beck et al. 2013; Meth et al. 2015; Peffers et al. 2007), which was then abstracted into prescriptive design principles, as outlined in the schema presented by (Gregor et al. 2020) (see Sect. 3.1). The design principles are our theoretical contributions as they provide novel emerging design theory (Gregor 2006; Jones and Gregor 2007) on travel inspiration. The design principles are grounded in prior scientific behavioural theory and frameworks (Gregor et al. 2020; vom Brocke et al. 2020). The paper is structured as follows. First, it explores the related literature on CoCreation of Travel Advisory, then Customer Inspiration in Travel, followed by the emerging trend of inspirational DTAs. It then defines a clear theoretical point of departure. After outlining the methodology, the paper details how Heidi was designed. Subsequently, the paper presents the empirical evidence gathered through the evaluation of the artifact. Finally, the design principles are abstracted from this empirical data and their theoretical and practical contribution is highlighted. 2 Related work The following section outlines the related work that forms the foundation for the contribution of this paper. We begin by exploring the literature of Co-Creation of Travel Advisory. We include this as we propose value co-creation as a pathway to utility, specifically as a means of enabling travel inspiration. Thereafter, we highlight the literature of Customers Inspiration in Travel, including its relevance to the tourism industry. This discourse is relevant given the overarching design objective of these 1 3 1049 J. Friedli et al. emerging digital assistants — namely travel inspiration and its realisation. Finally, we provide an overview of the emerging trend of inspirational DTAs and define our theoretical point of departure. 2.1 Co-creation of travel advisory The advisory role in travel experiences, once the domain of brick-and-mortar travel agencies, has increasingly been taken over by online providers (Dilts and Prough 2003). Buhalis and Licata (2002) highlight the disintermediation that has transitioned traditional offline travel agencies into the online realm, leading to the emergence of new intermediaries, including the supplier organizations (e.g., airlines, hotels, etc.) or new entrants (e.g. startups). However, Novak and Schwabe (2009) contend that the core competence of these traditional travel agencies remains in their ability to offer expert, personalized counselling. This service of personalized travel counselling can be understood within ServiceDominant Logic (SDL) and contemporary service design theory. SDL posits that service value is co-created by multiple actors through the integration of resources and reciprocal service exchanges, rather than being unilaterally delivered by a provider (Vargo and Lusch 2004, 2008). Likewise, service design theories advocate creating socio-technical service systems and user-centric artifacts that facilitate resource integration and co-production of value; this approach aligns with SDL by treating service provision as a co-creation process instead of a one-way value transfer (Koskela-Huotari et al. 2016; Patrício et al. 2018). This rise of the co-creation process for personalized travel offers in the tourism industry can be attributed to three key factors, according to Neuhofer et al. (2012). Firstly, tourism firms have come to recognize the value of co-creation for both the business and the consumer. Secondly, customers increasingly seek empowerment and control over their holiday experiences. Finally, technological advancements enable tourism companies to facilitate greater consumer involvement. For the latter, digital technologies have empowered end-users to become active co-creators of rather than passive consumers (Von Hippel and Katz 2002; Bowman and Willis 2003; Reichwald et al. 2009), a shift to co-creation that can be particularly well observed in the travel advisory (Solakis et al. 2024). Novak and Schwabe (2009) argue the rise of co-creation is particularly significant in travel advisory due to the challenges in finding trustworthy information, the necessity for a personalized approach, and the customer experience that is ‘emotionally coloured’. Schmidt-Rauch and Schwabe (2014) further explore this concept by demonstrating how the “helping hand” of travel agents can be enhanced through practical value co-creation. They assert that travel planning encounters exemplify value cocreation services, as they require collaborative problem-solving and solution-finding between the travel agent and the customer. In general, such co-creation of travel planning is affected by several factors, including customers’ perceptions, attitudes, trust, social influence, and hedonic motivations (Solakis et al. 2024). In the specific discourse on IT-enabled travel advisory, it has been suggested that information systems should extend beyond their utilitarian functions to incorporate hedonic aspects, which enhance user enjoyment during 1 3 1050 How Heidi helps: designing for inspiration in digital travel assistants the process (Hassenzahl et al. 2002; Van Der Heijden 2004). According to SchmidtRauch and Schwabe (2014) there are several abstract challenges that may impede the co-creation efforts within the domain of IT-enabled travel advisory: 1. Insufficient solution-problem-space overlap. The problem space in the client’s mind and the solution space in the advisor’s mind may not always coincide. For example, a traveller generally knows her own travel needs, while a travel agent is the expert on available trips. To find a solution, both parties must work together to align the problem space of the customer with the solution space of the travel agent (Schmidt-Rauch and Schwabe 2014). Therein, limiting the dialogue (e.g., to just verbal communication with a human agent) can hinder traceability of information (Nussbaumer and Matter 2011) and thus impede the co-creation process. 2. Burden of choice. The solution space generally features a high number of choices. For example, a traveller might be overwhelmed by potential travel possibilities in South America alone. Due to the fragmented nature of internet information, even experienced travellers face significant challenges in efficiently finding dependable details, configuring highly personalized travel itineraries, and verifying the trustworthiness of sources (Novak and Schwabe 2009). Further, the extensive array of options and the resulting combinations for trip planning may be very complex (Schmidt-Rauch and Schwabe 2014). This may lead to burden-of choice (Schwartz 2005) and thus impede the co-creation process. 3. Stickiness of information needs. The definition of the problem space might often not be clear in the mind of the client. For example, a traveller might know that she wants a vacation but is uncertain about what exactly she wants, much less how to state it clearly and succinctly. This may include hidden needs, which are requirements not yet directly recognized (Goffin et al. 2010). Research has yet to indicate whether these ‘hidden needs’ may surface during the inspirational process. Additionally, tourists often struggle to articulate their demands clearly, typically conveying vague needs stemming from general emotions and desires (Prestipino et al. 2006; Novak and Schwabe 2009). The presence of sticky information impedes the co-creation process, while the presence of ‘hidden needs’ adds another level of complexity. Current research extensively explores the abstract challenges of co-creating travel planning, but it primarily focuses on scenarios involving humans, particularly travel agents. It remains unclear how these abstract challenges may be addressed when intelligent digital agents facilitate inspiration directly through autonomous and efficient co-creation (see Sect. 2.4). The co-creation of travel experience is relevant for tourism, with studies showing that the personal involvement of a traveller can significantly enrich the value of the experience (Prebensen et al. 2013). This is in line with Pencarelli (2020), who holds that digital technologies can enrich the traveller’s experience in the whole travel cycle including inspiration and planning. This technology-mediated co-creation process aims to provide customers with an interactive experience, where value is generated through their engagement (Prahalad and Ramaswamy 2004; Vargo and Lusch 2004; Wozniak et al. 2018). Recent literature demonstrates that these co-created digital tourism experiences can enhance outcomes like visitor satisfaction, memorability, and loyalty, as multiple actors (tourists, service providers, and even other customers) jointly contribute to the experience design (Campos et al. 2016; Dang and Nguyen 1 3 1051 J. Friedli et al. 2023). Recent research by Lin et al. (2024) examined antecedents of tourists’ value co-creation with robots across the hospitality and tourism sector during the service encounter (e.g. digital ordering in a restaurant). Key factors identified include robots’ anthropomorphism and perceived practical utility, both shown to influence co-creation by enhancing service experiences. However, this literature does not address the travel planning and also overlooks the role of inspiration in the co-creation process — an aspect our research aims to investigate. 2.2 Customer inspiration in travel Customer inspiration has been extensively conceptualized, particularly in the field of psychology and (digital) retailing. As for the psychology, Gollwitzer (1990) originally defined inspiration as a temporary state that bridges the gap between the deliberation phase and the implementation phase of a goal pursuit, effectively linking goal setting with goal striving. Thrash and Elliot (2003) expanded upon this by characterizing inspiration as a form of intrinsic motivation, which is unique in that it is evoked by an external source (i.e., stimulus) and connected to the realization of new ideas. They introduced the ‘tripartite conceptualization’ of inspiration, which consists of three core components: evocation, transcendence, and motivation. Evocation, the first component, refers to the idea that inspiration is triggered by a stimulus object, which sustains the inspirational experience. This stimulus object - or set of objects - is often external, acting as a catalyst that captures attention. Transcendence, the second component, relates to the individual’s vivid and concrete awareness of new possibilities, suggesting a cognitive shift that opens previously unrecognized opportunities. This shift is characterized by heightened clarity and receptivity to novel ideas, which can lead to new insights. Motivation, the third component, reflects the drive to actualize or express this newly envisioned potential. This motivational drive is often accompanied by a sense of urgency and enthusiasm, compelling individuals to take action on their inspired ideas. Building on their earlier work, Thrash and Elliot (2004) proposed a domaingeneral conceptualization of inspiration. They reframed their tripartite model into two overarching processes: a relatively passive process, termed ‘inspired by’, which encompasses evocation and transcendence, and a relatively active process, termed ‘inspired to’, which corresponds to motivation. This distinction emphasizes the dual nature of inspiration, where the initial, passive reception of ideas or awareness is followed by an active pursuit of these newly realized goals. There is widespread consensus that this psychological conceptualization of inspiration, at its core, can be observed across diverse manifestations. The discourse of customer inspiration within the digital retailing domain emphasizes the specific transition between the two states of ‘inspired by’ and ‘inspired to,’ as it is central to the purchasing decision. Böttger et al. (2017) introduce the concept of customer inspiration in the retailing domain as “a customer’s temporary motivational state that facilitates the transition from the reception of a marketing-induced idea to the intrinsic pursuit of a consumption-related goal” (p. 1). Therein, they maintain that customer inspiration is fundamentally about the transition from the state of ‘being 1 3 1052 How Heidi helps: designing for inspiration in digital travel assistants inspired by’ an external factor to the state of ‘being inspired to’ actualize a new idea. This perspective aligns with the broader discourse presented by Thrash et al. (2010) and Oleynick et al. (2014), who argue that under ideal conditions (i.e., an actionable idea and capacity for motivation), the process of being ‘inspired by’ naturally leads to the process of ‘inspired to.’ Böttger et al. (2017) emphasize that all three components of the tripartite model — evocation, transcendence, and motivation — are necessary for a ‘full episode of inspiration.’ Specifically, this could involve starting with evocation (e.g., introducing the idea of travel), progressing to transcendence (e.g., shifting customer awareness toward various travel possibilities), and ultimately leading to motivation (e.g., the intention to realize a travel itinerary by booking a ticket). As such, customer inspiration is emerging as a critical construct in digital retailing for understanding customer behaviour in general (Frasquet et al. 2024) and touristic behaviour in particular (Dai et al. 2022; Khoi et al. 2020; Kwon and Boger 2021). The relevance of travel inspiration to the tourism industry lies in its demonstrated influence on tourist decision-making. Dai et al. (2022) argue that inspiration can act as a cognitive shortcut, propelling prospective tourists from the initial inspirational phase directly to decision and booking. Leveraging the framework of customer inspiration (Thrash and Elliot 2004), they describe this process as a shift where new travel ideas generate motivational drive. Dai et al. (2022) further note that tourism represents a unique form of consumption, where the primary offering is the experience itself. Unlike consumption driven by rational problem-solving or utilitarian purposes, such experiential consumption focuses on the pursuit of “fantasies, feelings, and fun” (Holbrook and Hirschman 1982, p. 135). Building on the inspiration framework from Thrash and Elliot (2004), Fang et al. (2023) show how digital travel content—such as short-form videos on platforms like TikTok—can facilitate inspiration and influence destination choice. Similarly, Gretzel (2021) netnographic analysis of Pinterest illustrates how visual social media platforms facilitate the inspirational phase, often accelerating the transition from interest to action for tourists. Overall, travel inspiration not only prompts immediate booking behaviour but also fosters the emergence of new future travel ideas (Dai et al. 2022; Fang et al. 2023; Gretzel 2021), highlighting its relevance in the tourism domain. 2.3 Inspirational digital travel assistants (DTAs) Digital assistants that go beyond serving as agents and instead autonomously interact with users are increasingly emerging across various industries, such as finance, healthcare, and travel. They are being developed with diverse design objectives, tailored to the unique requirements and challenges of each sector. The research on such digital assistants is extensive. While introducing the concept of machines-asteammates, Seeber et al. (2020) hold that advancements in artificial intelligence will evolve collaboration technologies from mere tools to true teammates. Meanwhile, some researchers propose a partnership model with smart machines (Newman and Blanchard 2019; Seeber et al. 2020), whereas Schmidt and Loidolt (2023) propose a taxonomy of such interactions based on two factors: (1) whether the machine shares the goal with the human, and (2) whether the machine’s tasks are fully anticipated by the human. His research has been invigorated by significant developments in 1 3 1053 J. Friedli et al. generative artificial intelligence and the advent of various LLMs, particularly as of 2022, which has reached the tourism industry (Mich and Garigliano 2023). Recent literature increasingly emphasizes the collaborative aspect of interacting with digital agents, focusing on ‘acting together’ (Schmidt and Loidolt 2023). We observe that the first digital assistants are emerging with the design objective of facilitating inspiration, predominantly in the travel industry. These inspirational DTAs draw on the capabilities of LLMs to reach customers in the early stages of the digital retail user journey, specifically during the inspirational phase. For instance, Expedia has introduced Romie, Trip.com has launched TripGenie, and startups such as Otto and Maya are entering the market. They all appear to share the design objective of facilitating inspiration. 2.4 Abstract research problem To clarify the theoretical point of departure for the paper, this section outlines the lack of actionable and theoretically motivated guidance on how to achieve inspiration with DTAs, and the rationale for this research. Then, it notes that it remains open how co-creation and inspiration relate to each other, despite some research implying such relationship. Finally, it proposes that exploring inspirational DTAs is promising, because it presents a radical new approach to addressing co-creation challenges — specifically as a means for enabling inspiration. Despite the growing interest in experimenting with inspirational DTAs, it remains unclear how DTAs can be systematically designed to attain inspiration. Based on a structured literature review (see Sect. 3.2), we find a lack of actionable and theoretically motivated guidance on how to attain inspiration through DTAs. That said, the review identified several works that are relevant. First, Murugan et al. (2024) explore a chatbot-based travel planner that suggests itineraries using machine learning, though it does not employ LLMs. Further, the work adopts a purely functional perspective and lacks a theoretical grounding altogether. Second, Dai et al. (2022) situate travel inspiration in the customer journey, thus embedded inspiration in the tourism field. Yet, this study lacks a technological perspective, an artifact and a design-oriented methodology. Third, Trieu et al. (2024) explore a computer vision-based system that suggests domestic destinations with overseas-like appeal. While following design science research, their work is not informed by the framework of inspiration and does not explicitly aim to facilitate inspiration. The rationale for this research on inspirational DTAs, from a theoretical standpoint, arises from the growing momentum within the travel industry to develop proprietary versions of inspirational DTAs. Considering this trend, it is essential to understand what implications the deployment of such agents may have, and how to provide appropriate guidance for their future design and implementation so that positive effects can be achieved systematically and in a user-friendly manner, thereby maximizing their utility. While methodologies and frameworks from other digital agent domains — such as healthcare or finance — do exist, they are not readily transferable to the travel context. This is because the intended outcome— travel inspiration and its realisation — involves distinct psychological mechanisms and travel-specific 1 3 1054 How Heidi helps: designing for inspiration in digital travel assistants Second, Lufthansa Group may jeopardize its position in the premium market if it fails to effectively inspire customers on a large scale to build their personalized travel experiences. Central to digital retailing within the travel industry is the ability to clearly communicate the value proposition to prospective customers. This communication is a crucial prerequisite for conversion. Most airlines within the Lufthansa Group operate in the premium segment, offering ‘travel experiences’ that extend beyond mere ‘flight transportation.’ Communicating the value of such experiences becomes challenging when they are presented merely as a catalogue of generic options, which is currently the case. While human travel agents can create tailored and personalized value propositions, this approach is not scalable for the Lufthansa Group, which manages over 120 million passengers annually. Effective communication of the value proposition is crucial, as failing to convey this ‘premium promise’ could negatively impact customers’ willingness to pay. Conversely, inspiring customers to build their personalized travel experiences not only mitigates this risk but also fosters a closer emotional connection with the airlines. Furthermore, it effectively democratizes personalized travel inspiration in line with an emerging customer need. As such, Lufthansa Group intends to design an inspirational DTA with an efficient mechanism to build personalised travel experience with customers at scale (see Table 2). 4.2 Design objective As derived from the problem identification, the Lufthansa Group needs to (1) establish a presence during the inspiration stage by creating its own dedicated inspirational DTA and (2) develop an efficient mechanism to deliver personalized travel experiences to customers at scale. This dual need translates into an overarching design objective for Heidi, serving as an inspirational DTA of the Lufthansa Group. The design objective is to: facilitate travel inspiration through the autonomous and efficient co-creation at-scale. The overarching design objective was subject to specific design requirements that must be met. These requirements served as the developmental framework, wherein the artefact could be instantiated (see Table 3). First, the artefact requires a brand-compliant user interface. As the artefact is effectively an extension of the organisation’s digital presence, it is essential that it adheres to all visual branding guidelines, including the correct use of logos, colours, and other identity elements. Furthermore, the design must prioritize ease-of-use and Table 2 Problem identification 2 “The core is inspiring people to use and understand what we have to offer by providing insights on the various destinations we are flying to. Ultimately, the airline can get more revenue by having inspired people booking our destinations.”–Developer 1 “Our website presents destinations randomly and generic. Meanwhile, users trying to make sense of what would be best for them in terms of destinations. So, the need for inspiration comes from missing personalised information.”–Developer 1 “The online travel agencies and startups offer something very similar. We can only survive this competition if we play on our advantages in data. The airline data and customer data.”–Product Owner 2 1 3 1061 J. Friedli et al. accessibility, ensuring that a broad audience can interact with it effortlessly. The initial development should focus on incorporating rudimentary generative AI functionality (i.e. destination selection and itinerary creation via prompting) with a structure that allows for future expansion through additional ‘modules. Second, the artefact adheres to communication standards in accordance with corporate guidelines. As it acts as a representative of the organisation in both directions of interaction (i.e. input and output). On the input side, the artefact should not engage with inappropriate or illicit queries (e.g. block requests related to alcohol abuse). In terms of output, the artefact must maintain a professional and polished tone, always suggesting content that aligns with the ‘premium promise’ of the organisation’s offering and resulting customer base (e.g. generate itinerary with upscale activities). 4.3 Iterative development As part of the design approach (see Sect. 3.3), the PoC was delivered in two iterations. The first iteration provided the initial instantiation, adhering to the established design objectives and the developmental framework (see Sect. 4.2). The second iteration began with a series of customer interviews aimed at gathering initial feedback to assess whether the artifact met its intended objectives. While several smaller design elements were adjusted, a major feature change emerged from user testing. Initially, the first iteration of Heidi supported only “input-output,” where users could prompt the system and receive itineraries in response. User feedback indicated a need for “prompt guidance,” particularly for customers less familiar with interactive solutions using generative AI. To address this, two key modifications were implemented: first, the prompt field was pre-populated with a sample query to help users understand the structure of their input as they typed a new query; second, the initial screen was enhanced with three pre-prepared queries, allowing users to easily engage by clicking “try it” (e.g., planning a surf trip in South America). In addition to these changes, a further refinement was suggested by strategic partner Google. This involved expanding the itinerary feature with a ‘module’ showcasing major upcoming events at the destination (e.g., film festivals, Formula 1 races). See Fig. 4. This enhancement was aimed at providing users with more dynamic and engaging content, enhancing the overall value of the itinerary. Table 3 Design objective “When generative AI emerged, it was like giving us the scalable opportunity to put the user in the driver seat and help him or her create the travel experience with us.”–Product Owner 1 “The actual design was quite open. We started with the technology but wanted to make it easily accessible and to solve a specific problem. In our case: inspiration.”–Developer 1 “As a premium airline, instead of promoting things like McDonald’s on our itinerary, we should suggest elevated burger restaurants.”–Developer 1 “For the first step, it should be simple. Just an ‘input and output’, build in a modular way to be extended (…) Based on our corporate guidelines, there are clear Do’s and Don’ts in terms of what we want to see as input and as output.”–Product Owner 1 “If people are prompting: I want to get completely drunk in one of the sunny destinations. The system is not supposed to react.”–Developer 1 1 3 1062 How Heidi helps: designing for inspiration in digital travel assistants 4.4 Instantiated artefact The artefact, called Heidi, was developed and instantiated in line with the design objective. It has been made available online, clearly marked as a pilot initiative, and is accessible for public use. At the time of writing, the artefact is freely available at https://heidi.swiss.com/. Please refer to the below for an overview (see Figs. 1–4). Fig. 2 Curated Selection (Output 1) Fig. 1 Input Field (including Prompt Guidance) 1 3 1063 J. Friedli et al. Fig. 4 Suggested Events (Output 3) Fig. 3 Sample Itinerary (Output 2) 1 3 1064 How Heidi helps: designing for inspiration in digital travel assistants 5 Evaluation and results 5.1 Evaluation of initial proof of concept As per the overarching design objective for Heidi, the team set out to facilitate inspiration through autonomous and efficient co-creation at-scale. From a business perspective, the semi-structured interviews with members of the Heidi team revealed a consensus that the design objective of facilitating inspiration has been achieved (see Table 4). From a customer perspective, the empirical evidence validates that Heidi has facilitating inspiration through co-creation, sometimes even being referred to as a ‘sparring partner’. The semi-structured interviews further indicate that users found the artefact useful for co-shaping their personalized travel plans in a collaborative experience. They also noted that they felt both autonomous and supported in being ‘their own travel agents’. In this regard, the empirical evidence suggests that co-creation with Heid — which facilitated the inspiration — was both autonomous and efficient (see Table 5). In addition to the general assessment of users regarding the artefact, three themes were highlighted how Heidi — as an artefact of inspirational DTA — helped to facilitate travel inspiration through autonomous and efficient co-creation (see Table 6). First, users expressed support for how Heidi helps by placing the itinerary at the core of the planning process. Specifically, they note that it immediately organizes and structure their time in a new location which then helps in providing stimulating content that is up-to-date from the internet. Second, users highlighted how Heidi helps in defining the solution space. They emphasized Heidi’s role in filtering the overwhelming amount of information which then helps in providing “simplified points of exploration” that allow broadening the scope of possibilities. Third, users appreciated how Heidi helps in defining the problem space. They noted that Heidi clarified and articulated their vague needs which then helps in surfacing latent opportunities that “It’s a great option to simply avoid the confusion of navigating through all the different websites.”–Customer 4 “If I already have a destination in mind, I would use it as inspiration for specific activities in my travel itinerary to structure my time. That is valuable.”–Customer 11 Table 5 User perspective on initial proof of concept “I really like our first PoC. I particularly like the initial overview. You have the possibility to prompt and you with the three preloaded suggestions. (…) What I didn’t like is the filtering on the left side. It is a bit counterproductive as we want to do this all via prompting.”–Product Owner 1 “I’m happy with the proof of concept because it showcases really nicely what generative AI can do and how this could be used in our sector.”– Developer 1 “I really like the interface overall. It’s very clear, very structural. The prompt field is clear and has explanation. The resulting itinerary that is displayed is very well-designed.”–Product Owner 1 Table 4 Business perspective on initial proof of concept 1 3 1065 J. Friedli et al. had not been explicitly mentioned but were inferred. It is important to note that these three themes have been abstracted into design principles (see Sect. 6.1, Tables 6 and 14 in Appendix). 5.2 Suggestions for future iterations From a business perspective, there was agreement that the Heidi artefact has laid a solid foundation to be expanded upon. For future iterations, the imperative was identified to differentiate Heidi from other emerging inspirational DTAs in the industry. To better achieve the overarching design objective, several new requirements aimed at enhancing the artefact were proposed (see Table 7). First, the artefact must enrich its offering by integrating more company data. This involves connecting to the most relevant APIs, such as those providing average prices per destination (i.e., best price API) and incorporating profile data within the interaction (i.e., Travel ID) to identify customers and understand basic preferences (e.g., preference for continental Europe). Second, the artefact must be capable of understanding the customer’s position within the inspiration stage. This requires gathering input from the user to determine how far along they are in their planning process (e.g., whether they are exploring general Table 6 User perspective on initial proof of concept (continued) How Heidi helps with an itinerary “I would use the tool for inspiration, and I would also book through it. Even during the pandemic, I was my own travel agent and made my own itinerary. I can’t go back to the old way.”–Customer 3 “The inspiration already comes from either the internet or magazines when you’re interested in travel. There’s so much out there. That’s why I find this tool really stimulating.”–Customer 4 “I’m someone who likes everything to be visualized. I respond quickly to what I see, and I use that to decide whether something might be relevant to me or not.”–Customer 10 “I find that very useful. The itinerary for Vietnam, in my case, looks exciting. Now that I see it, I feel like I’d add a few more days at the beach.”–Customer 4 How Heidi helps with defining solution space “When you go to Google, you get a million different pieces of information for options, and in the end, you don’t know what to do.”–Customer 5 “I think I would use it to get inspiration for new destinations, very early in the process when I don’t know anything. I want to understand what is out there. It’s like a game to me.”–Customer 7 “Interesting to see all the other things I can do just because I entered ‘beach vacation’.”–Customer 1 “With so much information out there, this really helps me organize it better. More and more people are turning to this kind of inspiration again.”–Customer 3 How Heidi helps with defining problem space “I recommend the tool, especially when my friends are still undecided whether they want to go to the Eiffel Tower or the Louvre. They need such suggestions to help them decide and a sparring partner.”–Customer 4 “I am Brazilian and always thought I knew South America well, but Ecuador was never on my radar. A tool like this provides insights I would have never considered.”– Customer 11 “Yes, so far it’s super intuitive– and actually pretty cool that all the ideas are already built in. Now I just need to book the flight.”–Customer 4 “I just entered what you should do during three weeks in Australia, focusing on the highlights. Mainly to discover the must-sees I didn’t even know about. It created a great itinerary.”–Customer 9 1 3 1066 How Heidi helps: designing for inspiration in digital travel assistants options or searching for activities in a specific location). Third, the artefact must eventually facilitate strategic destination steering. This involves linking the system to the firm’s capacity management tools to promote destinations with high availability (e.g., seat load factors), ideally in real time, allowing customers to access potentially cheaper tickets while optimizing the company’s capacity management. From a customer perspective, the semi-structured interviews with users reveal a range of ideas for improving the artifact in alignment with the stated design objective (see Table 8). The suggested inclusion of price details, as proposed by the business perspective, was also repeatedly confirmed by the users. Further, a notion of introducing also places to stay in the itinerary was noted (i.e. hotel accommodations). From both a business and customer perspective, there was consensus on the future need for interactive personalisation (see Table 9). Therein, the artefact must adopt a hybrid approach combining visual imagery with chat-based interactions in the way it engages with the users. This was voiced by the product owners as a key guideline for Table 9 Joint perspective of future iteration “The key is to combine chat-based interaction with visual imagery. This creates the playroom. We cannot lose this aspect of gamification. Pure chats are everywhere, and people are used to it.”–Product Owner 1 “The tool didn’t ask what kind of traveller I am. Are these just generic suggestions for anyone going to Vietnam for this timeframe? I want to input my personality.”–Customer 6 “If we want personalisation, we need to learn more about the user. For example, we need to know what kind of traveller they are. This really makes the connection to the person.”–Product Owner 2 “Important will be that the system is intelligent enough to understand in which kind of inspiration or decision phase the customers is.”– Product Owner 1 “The conversation feels one-sided; I want to fine-tune the travel plan with the machine.”–Customer 1 “I’m wondering now. If I say I want to go to Croatia and input six days, maybe I need more or fewer days. There’s no challenge or feedback coming back.”– Customer 7 “I’m just thinking out loud. What if we focus first on the customer and gather their preferences before making suggestions? For example, preferences for sports or culture?”–Customer 8 “You could also add the travel dates, combine the preferences, and include a price overview. Then I would definitely need something like this.”–Customer 4 “I travel based on price, depending on the cheapest flight. With such a tool, I only know the most important thing at the end: the price.”–Customer 5 “I would see this as something that really combines all the elements together: activity, hotel, flight, and transport.”–Customer 2 Table 8 User perspective of future iteration ”It is a POC and therefore there is a lot of potential to improve”– Developer 1 “We have excellent data from the internet, but we like our own airline data. What are our prices? What is the flight schedule? We still lack depth.”–Product Owner 2 “If we want personalisation, we need to know what kind of traveller they are. This really makes the connection to the person.”– Product Owner 1 Table 7 Business perspective of future iteration 1 3 1067 J. Friedli et al. future iterations. Currently, the PoC has relatively basic generative AI functionality (i.e., destination selection and itinerary creation via prompting). However, as initially suggested by partner Google, there is potential to move toward a more interactive guidance approach. This was confirmed repeatedly via the user interviews. Indeed, the users wish to be guided through the inspirational process using a chat-based interface that solicits input (i.e., interaction), remembers the input (i.e., memory), and steers the conversation (i.e., guidance). This interaction should take place across the entire inspirational episode, enhancing user engagement and personalization. The mounting empirical evidence from both the user and business perspectives testified to the importance of interactive personalisation as another design principle for the future iteration of the Heidi artefact. Hence, it has been proposed as a nascent fourth design principle (see Sect. 6.1). 6 Discussion 6.1 Design principles of inspirational DTAs As discussed in Sect. 4.2, the design objective of inspirational DTAs is to facilitate travel inspiration through autonomous and efficient co-creation at scale. Historically, individuals have had two choices when engaging with travel inspiration: (1) navigating the process entirely on their own, which is autonomous but inefficient, or (2) seeking assistance through co-creation with a human travel agent, which may be efficient but not autonomous. With the advent of inspirational DTAs, a radically new option emerged for travel inspiration and its realisation — as exemplified by the Heidi artefact. The literature on Co-Creation of Travel Advisory (see Sect. 2.1) and the literature on Customer Inspiration in Travel (see Sect. 2.2) provide the theoretical grounding for the abstraction of the prescriptive Design Principles (DPs). Herein, we posit a means–end relationship between co-creation (means) and inspiration (end). In the context of inspirational DTAs, we conceptualize co-creation as a pathway to utility— specifically, as a means for enabling inspiration. More concretely, we suggest that inspirational DTAs can address the obstacles that hinder co-creation in the domain of travel advisory, thereby facilitating the achievement of the three components of an inspirational episode: evocation, transcendence, and motivation. We put forward three means-end relationships: First, it is useful to provide Solution–Problem Space Overlap as a means of achieving Evocation (DP1). Second, it is useful to reduce the Burden of Choice as a means of achieving Transcendence (DP2). Third, it is useful to mitigate the Stickiness of Information Needs as a means of achieving Motivation (DP3). Supported by empirical evidence from the user perspective of the initial POC (see Sect. 5.1), this led to three design principles: DP1, DP2, and DP3. This is in line with the methodological guidance of Gregor et al. (2020), who posit that central to design theory are the prescriptive design principles. These design principles strive for statements like, “If you want to achieve B, it is useful to try A.” Thus, 1 3 1068 How Heidi helps: designing for inspiration in digital travel assistants at the core, design provides a goal (“B”) and the means to achieve it (“A”) (Briggs and Schwabe 2011; Díaz Andrade et al. 2023; Kornwachs 2012). The fourth design principle, nascent in nature, was abstracted from converging empirical evidence on the future iteration of the Heidi artefact (see Sect. 5.2, Table 9). At the time of writing, these four design principle guide the development of Heidi. For additional details, please refer to Table 14 in Appendix. For a comprehensive overview of all design principles and their relation to the theoretical grounding, please refer to Illustration 1. In the following section, we examine all four design principle individually. Note that all design principles have been devised in the schema of Gregor et al. (2020), within the design theorizing framework of Lee et al. (2011). 6.2 DP1 - the principle of itinerary-based solution space In the domain of co-creation of travel advisory, Schmidt-Rauch and Schwabe (2014) state that the problem space in the client’s mind and the solution space in the advisor’s mind may not always overlap, yet ultimately require alignment. For example, while the traveller better understands their own needs, the agent has more expertise in the available options. In the inspirational framework, Evocation, the first component, refers to the idea that inspiration is triggered by a stimulus object, which sustains the inspirational experience (Thrash and Elliot 2003, 2004). In the literature of travel inspiration, this is the element that starts the trip-planning ‘dreaming’ (Dai et al. 2022). We propose that inspirational DTAs should be designed on their ability to “overlap” the Solution and the Problem space for the user. This means (1) creating a continuous stimulus object or set of objects and (2) maintaining a digital representation of this overlapped space continuously (see Table 10). The former can be achieved through a visually pleasing itinerary, which serves as the shared digital representation to ensure that both the user and the system are 1 3 1069 J. Friedli et al. working from the same information. This approach further ensures the traceability of information, as the co-creation process is no longer dependent on verbal dialogue with a human agent (Nussbaumer and Matter 2011). The latter naturally occurs as a byproduct as the suggested itinerary also serves as the source of continuous inspiration alongside its boundary object. As such, it is useful to provide Solution–Problem Space Overlap as a means of achieving Evocation. In practice, the inspirational DTA would provide the user with an itinerary suggestion for a 3-day trip to Barcelona. This itinerary would then be adjusted and refined (e.g. extending stay or adding a beach day) until it becomes the travel plan. 6.3 DP2 - the principle of simplified exploration In the domain of co-creation of travel advisory, the solution space typically involves numerous choices, making it challenging for travellers to efficiently create personalized itineraries. The overwhelming number of options can lead to a “burden of choice” (Schwartz 2005), which impedes the co-creation process (Novak and Schwabe 2009; Schmidt-Rauch and Schwabe 2014). In the inspirational framework, Transcendence, the second component, relates to the individual’s vivid and concrete awareness of new possibilities, suggesting a cognitive shift that opens previously unrecognized opportunities (Thrash and Elliot 2003, 2004). In the literature of travel inspiration, this encourages travel idea generation (e.g. destination or activity) (Dai et al. 2022). We propose that inspirational DTAs should be designed on their ability to reduce the Burden of Choice. This means (1) reducing the selection at every step of exploration to manageable simplicity (2) infusing this simplicity with clickable ‘points of exploration’ to rapidly acquire extended information (see Table 11). The former is achieved by priming the system to only present a manageable number of options for each query, based on general probabilities (e.g., activities or locations). The latter occurs naturally as a byproduct, as the tailored overview of curated travel options will inadvertently include some activities or destinations that are new to the user, thereby broadening the scope of possibilities. In line with customer expectations, this should Table 10 Description of the principle of inspirational DTAs according to (Gregor et al. 2020) Title Principle of itinerary-based solution space Aim, implementer, and user For designer (implementers) to achieve the Evocation, it is useful to “overlap” the Solution and the Problem space for the user. Context The user in the initial stages of the travel planning process. Mechanism Generally: This means (1) creating a continuous stimulus object or set of objects and (2) maintaining a digital representation of this overlapped space continuously. Technology: Employ Retrieval-Augmented Generation (RAG) to suggest the most likely itinerary for a selected destination in line with corporate guidelines and service offering Rationale Relationship: Providing Solution–Problem Space Overlap is a means of achieving Evocation, which is the first core component of an ‘episode of inspiration’ (Thrash and Elliot 2003). Empirical Evidence: Users see utility in how Heidi helps by placing the itinerary at the core of the planning process. Specifically, they note that it immediately organizes and structure their time in a new location which then helps in providing stimulating content that is up-to-date from the internet (see Sect. 5.1). 1 3 1070 How Heidi helps: designing for inspiration in digital travel assistants Author contributions J.F. wrote the main manuscript text. G.S. and M.D. contributed with valuable guidance throughout the study and the manuscript development. All authors reviewed the manuscript. Funding Open access funding provided by University of Zurich Data availability No datasets were generated or analysed during the current study. Declarations Competing interests The first author is a doctoral candidate at the University of Zurich in the Information Management Research Group. Concurrently, he holds a full-time position at the Lufthansa Group and is involved in the Heidi project, which serves as the focus of this study. The authors declare they have no financial interests in the publication of this manuscript. There was no funding received for this study.The views and opinions expressed in this paper are solely those of the primary author and do not necessarily reflect the official policy or position of the Lufthansa Group. The primary author has written this work in a personal capacity. 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