Volume 40(1) p.37-52 Received: March 16, 2022 Revision received: December 19, 2022 Accepted: January 6, 2023 https://doi.org/10.54155/jbs.40.1.37-51 Business Model Innovation through Open Innovation: Empirical Evidence from the Automotive Industry Benedict Seiferlein a, Dominik K. Kanbach b a HHL Leipzig Graduate School of Management, Leipzig, Germany. benedict.seiferlein@hhl.de (Corresponding Author). b HHL Leipzig Graduate School of Management, Leipzig, Germany. dominik.kanbach@hhl.de. Abstract Although open innovation (OI) has been characterized as one key driver for business model innovation (BMI), the literature lacks an in-depth understanding of how OI influences the business models (BM) of new ventures. However, such an understanding is crucial for improving the value creation and value capture for technological innovations in inbound OI settings. Based upon a unique data set of 19 new ventures from 7 countries, which participated in Europe’s largest OI platform, this study finds that OI leads to an expansion in the customer segment, a greater focus in the value proposition, a shorter (but deeper) value chain, and challenges to the revenue model. The paper highlights important theoretical contributions for the BMI and OI literature, and derives tangible managerial guidance for entering OI partnerships. Keywords Business model innovation, Open innovation, Automotive industry, New ventures 1. Introduction Business model innovation (BMI), defined by Casadesus-Masanell and Zhu (2013, p. 464) as “the search for new logics of the firm and new ways to create and capture value,” has become in- creasingly decisive for commercializing technolo- gies, gaining sustainable competitive advantages, shaping industries, and increasing firm perfor- mance (Seiferlein et al., 2023). The elaboration of these new value creation and value capture logics into a consistent business model (BM), in which the customer segment, value proposition, value chain, and revenue model are coherently de- fined, is thereby of key strategic importance to en- trepreneurs and a source for innovation in and of itself (Zott & Amit, 2010). However, despite two decades of research, the academic understanding of how BMI is achieved, and how this affects the el- ements of a BM, remains limited—particularly for new ventures (Foss & Saebi, 2017). One of the foremost suggestions for purposefully enabling BMI can be found in the open innova- tion (OI) literature, which argues that BMI is fa- cilitated by deliberately integrating external part- ners into the development of new BMs (Foss & Saebi, 2017). Following this reasoning, companies This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. © 2023 The authors. https://doi.org/10.54155/jbs.40.1.37-51 benedict.seiferlein@hhl.de dominik.kanbach@hhl.de Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 38 should use OI to validate assumptions about the customer segment, value proposition, value chain, and revenue model and innovate these BM ele- ments based on feedback from external partners (Ibarra et al., 2020). However, thus far, this recom- mendation has been primarily derived from anec- dotal evidence or purely conceptual works (e.g., Chesbrough & Rosenbloom, 2002; Saebi & Foss, 2015). Accordingly, Foss and Saebi (2018) con- cluded that the impact of OI on BMI requires fur- ther academic scrutiny. We argue that the need to understand the con- sequences of OI on BMI is especially critical for new ventures due to the increased flexibility of their BMs, smaller companies’ greater reliance on OI to overcome their liabilities of size, the fact that new ventures’ perspectives on OI are under- researched, and the collaboration between incum- bents as stimuli for new ventures’ BMI needs fur- ther scholarly attention (Albats et al., 2021; Sp- ithoven et al., 2013; Urbaniec & Żur, 2021). Given thisstartingpoint, newventuresmightparticularly benefit from previously identified benefits of OI, such as increased creativity, more successful tech- nology exploitation, and improved market access, to advance their BMI (Chesbrough & Appleyard, 2007; Chesbrough&Schwartz, 2007; Marulloetal., 2018). Therefore, we ask the research question: How does OI influence BMI in new ventures? We answer this by applying a qualitative research approach, based on a sample of new ventures that participated in Europe’s largest OI platform between 2016—2022. Building upon a rich and unique data set, including interviews with founders, CEOs, and key personnel of 19 new ventures from 7 countries, we provide empirical evidence of how OI impacts BMI alongside the BM components customer segment, value propo- sition, value chain, and revenue model. In so doing, we provide three main contributions: First, we heighten the understanding of how BMI is fostered—which is among the most frequently- cited gaps in the BMI literature (Seiferlein et al., 2023). Second, by studying how OI influences BMI as a context-specificfactor, weanswertherequestsfor further research on an issue expressed in recent BMI and OI literature reviews (e.g., Foss & Saebi, 2017; Spender et al., 2017). Third, we provide valuable managerial lessons for entrepreneurs and corporate managers engaging in OI, especially since BMI and strategic manage- ment are inherently linked (Casadesus-Masanell & Ricart, 2010). The remainder of the paper is structured as fol- lows. Section 2 provides the theoretical back- ground on BM and BMI, OI and open BM, and the connections between them. Once done, we in- troduce our methodological approach, before pre- senting our findings and integrating them into the ongoing academic and managerial discussion. 2. Theoretical Background Business Models and Business Model Innovation BMs have been defined as “management’s hypoth- esis about what customers want, how they want it, and how the enterprise can organize to best meet those needs, get paid for doing so, and make a profit” (Teece, 2010, p. 172). Hence, they serve to define the economic boundaries for con- verting technological inventions into viable inno- vations, and link the company-internal technologi- cal sphere with the market (Chesbrough & Rosen- bloom, 2002). With this architecture of operations, BMs influ- ence the diffusion of novel technologies and speed of market penetration, for which an inno- vative BM itself could well be a decisive factor (Urbinati et al., 2019). Moreover, BMI represents an additional opportunity to differentiate from the competition (Chesbrough, 2007a). However, conducting BMI is often characterized as a challenging, multifaceted, and interwoven strategic activity, for which new ventures routinely lack the requisite knowledge (García-Gutiérrez & Martínez-Borreguero, 2016; Kraus et al., 2022). Moreover, the existing literature offers new ven- tures only limited empirical guidance (Snihur & Zott, 2020). Indeed, it tends to only offer instruc- tion on conducting experiments with BM config- urations and integrating company-external feed- back to reduce a BM’s technological and market Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 39 uncertainties (Micheli et al., 2020). Similarly, Trimi and Berbegal-Mirabent (2012) and Ibarra et al. (2020) have advocated for integrating customers for pursuing BMI to validate hypothe- ses and achieve consistency between a new ven- ture’s offerings and customer expectations. How- ever, Hossain (2017) concluded in his BMI litera- ture review that there is still a significant scarcity of knowledge on customer integration for BMI. Among those gaps is how customers influence the outcome of BMI in detail (Micheli et al., 2020). From a theoretical lens, these recommendations resonate with OI, which is frequently-mentioned in the BMI context, but rarely explicitly discussed (Saebi & Foss, 2015). Thus, recent BMI literature reviews call for more empirical studies on the in- tersection of BMI and OI (e.g., Foss & Saebi, 2017). Open Innovation Chesbrough and Bogers (2014, p. 3) defined OI as a “distributed innovation process based on purposively managed knowledge flows across organizational boundaries, using pecuniary and non-pecuniary mechanisms in line with the or- ganization’s BM.” The literature differentiates be- tween inbound OI, which is concerned with cre- ating value through integrating external inputs (e.g., ideas, know-how), and outbound OI, which uses external paths to a market for commercial- izing excess assets (e.g., patents). OI is thus a potential strategy with which to increase firms’ creativity, gain access to new markets, reduce costs and risks, and ultimately improve profitabil- ity (Chesbrough & Appleyard, 2007; Chesbrough & Schwartz, 2007). In a recent study of 251 European companies, Teplov et al. (2019, p. 26) found that inbound OI is more prevalent than outbound OI, while highlight- ing that only “free revealing, scanning for exter- nal technologies, subcontracting R&D, customer co-creation in R&D projects, and idea and start-up competitions” were commonly acknowledged as OI practices by the participants. Their results ac- corded with Spieth and Meissner’s (2018) observa- tion that the academic discussion of OI is primar- ily concerned with advancing technological inno- vations from an R&D perspective. However, in environments with increasing R&D costs and shrinking product life cycles, Ches- brough (2007b) proposed applying OI not only in R&D, but also following an open business models logic. Open Business Models According to Weiblen (2014, p. 57), “an open busi- ness model describes the design or architecture of the value creation and value capturing of a fo- cal firm, in which collaborative relationships with the ecosystem are central to explaining the over- all logic”. Hence, the interactions between cus- tomers and suppliers in an open BM transcend straightforward selling and sourcing transactions in that they also involve a deeper integration of value creation and capture (Weiblen, 2014). For instance, this is typically the case for car manufac- turers, where suppliers account for approximately 75% of the created value and profoundly influence their partners (Seiferlein et al., 2023). Frankenberger et al. (2014) argued that inconsis- tencies in a BM, the pressure to find a new BM for value creation and value capture, collaboration ex- perience, imitation of open BM patterns, and the blurring of industry boundaries are conducive for open BMs. However, empirical evidence still lacks details on how this openness influences BMs (Holm et al., 2013). Saebi and Foss (2015) argued that the economic benefits of OI for BMI are determined by BM configuration, as well as the breadth and depth of the applied OI strategy. Their purely conceptual work suggested that new ventures with radical innovations should design their BM through intensive collaboration with key partners, which is also in line with Pynnönen et al.’s (2012, p. 11) recommendation to integrate customers into the BMI “from the very beginning”. In the same vein, Marullo et al.’s (2018) cross- sectional study of start-ups identified a positive correlation between the integration of external knowledge and successful technology exploita- tion. However, neither of these studies have pro- vided empirical insights into exactly how firms do this, nor how this affects the BM in detail. This disparity is in line with the knowledge gap on Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 40 how BMI arises in new ventures, as well as which role the integration of customers or other firm- external actors play in BMI (Andreini et al., 2021; Hossain, 2017; Snihur & Zott, 2020). Consequently, Spender et al.’s (2017) literature re- view on startups and OI concluded with a call to investigate new ventures’ BMI using qualitative re- search methods based upon original data. Accord- ingly, we seek to narrow this research gap with the present study. 3. Methodology Research Design Case-based research is particularly well-suited to studying the dynamics of complex processes with limited pre-existing theoretical foundations, ex- ploring relationships between interrelated con- cepts, and advancing theory building based on the examined cases (Gehman et al., 2018). Since all of these aspects apply to our research question, we opted to apply a qualitative research approach (Andreini et al., 2021). Next, we chose a research context likely to allow for replication between the studied new ventures (Eisenhardt, 1989). Thus, we focusedourattention on the automotive industry, which is especially ap- propriate for studying the effects of OI on BMI for four reasons: First, the industry is traditionally highly col- laborative with long-standing experience in co- developing innovations in a tier structure of manu- facturers (Jacobides et al., 2016). These structures include: Tier 1, system suppliers; Tier 2, parts sup- pliers; and Tier 3, raw material suppliers. Second, the industry is confronted with increas- ing cost pressure and shrinking product life cy- cles, as well as market pressure to develop more autonomous, connected, and sustainable mobility options, thereby further emphasizing the need for BMI and OI (Ili et al., 2010; Leemann et al., 2021; Seiferlein et al., 2022). Third, the industry is increasingly following Ches- brough’s (2007b) recommendations to use OI to create and capture value with BMI (Spieth & Meiss- ner, 2018). Fourth, the automotive industry commonly uti- lizes Startup Autobahn—Europe’s largest OI plat- form as measured by the number of partners and implemented projects (Daimler AG, 2021; Startup Autobahn, 2020). Since its inception in July 2016, the platform has grown to include 29 corporate partners, and 289 new ventures from 43 countries have developed 380 prototypes, of which every fourth has achieved commercialization following the experimentation phase (Schwarze, 2021). Drawing our sample from this well-established program allowed us to control for potential in- fluencing factors, such as differences in program design, cross-check inferences between multiple participants of the same program, and benefit from a large variety of interview partners. More- over, Startup Autobahn is a stage-agnostic pro- gram for new ventures, thereby enabling us to gain in-depth insights into OI’s influence on BMI ir- respective of the maturation of new ventures. Ac- cordingly, this served to increase the generalizabil- ity of our findings. Finally, the program connects new ventures with incumbents from the automotive industry, includ- ing such car manufacturers as Mercedes-Benz, Hyundai, and Porsche, and automotive suppliers like BASF, Bosch, Schaeffler, and ZF—who can be- come potential customers for a commercial pilot R&D project with the new venture. As such, these collaborations between new ventures and firmly- established corporates fit the OI archetype from a practitioners’ perspective, thus increasing our study’s practical relevance (Teplov et al., 2019). Data Collection Following Gioia et al. (2012), we collected exten- sive primary and secondary data through various means. First, we conducted 19 semi-structured inter- views with founders and C-level representatives of emerging firms headquartered in Austria, Bul- garia, Finland, Israel, Germany, Slovakia, and the United States, all of whom had participated in Startup Autobahn since its inception. The partic- ipants were randomly selected and approached either in-person, via social media, or through the snowballing technique (Biernacki & Waldorf, 1981). We conducted the interviews in either Ger- Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 41 man or English, and transcribed them within 48 hours of the interview. Our interviews included questions about the BM before their participation in Startup Autobahn, the introduction of changes during and due to the program, and the lessons they had drawn from their participation. More- over, we also asked individual follow-up ques- tions. Second, we conducted in-person field visits to Startup Autobahn’s OI events in Stuttgart, Ger- many, and attended virtual community meet ups to engage in an informal exchange with represen- tatives of new ventures, such as CEOs, CFOs, and members of the founding team. Third, we also attended IAA Mobility 2021 (the world’s largest mobility fair) in Munich, Germany, in order to meet Startup Autobahn alumni in an industry-specific setting and learn more about the venture’s development. Collectively, the field notes and meeting memos gathered for the pri- mary data greatly enhanced our understanding. Moreover, we extensively collected secondary data from such sources as podcasts, public inter- views with the founders and collaboration part- ners of the new ventures, and Startup Auto- bahn’s own publications (e.g., video recordings of pitches and community events). Additionally, we searched for academic and lay publications about the program with search engines, such as EBSCO Host, Google Search, and Google Scholar, to trian- gulate our findings. Having completed the above steps, we collected and analyzed the data iteratively until we reached theoretical saturation, as suggested and defined by Thornberg and Charmaz (2014). Data Analysis We followed Gioia et al.’s (2012) guidelines for the data analysis, which included coding the tran- scribed primary and secondary data in MAXQDA, and built a data structure to categorize our find- ings. Hence, we formed informant-centric first- order concepts, data-driven conceptual second- order themes, and connected them with estab- lished aggregated dimensions in the BMI liter- ature. Consequently, we related each of our twelve second-order themes to one of the four BM components customer segment, value propo- sition, value chain, and revenue model as found in Frankenberger et al. (2013). This final abduc- tive aggregation enabled cross-fertilization within the BMI research domain, contributed to consoli- dation within the BMI literature, and allowed us to follow an approach applied in other BMI papers (e.g., Daood et al., 2021). The result of the data analysis is illustrated in Figure 1a and 1b, while ad- ditional supporting quotes can be found in Table 2 in the appendix. 4. Findings Our findings indicate that OI influences every com- ponent of the BM in three distinctive aspects. We explain these results in the following section. Customer Segment A BM’s customer segment defines the target group for a company’s offering (Frankenberger et al., 2013). Our data reveals that OI is con- ducive for extending the customer base, regard- less of whether a new venture has previously been exposed to the specific industry. As such, OI can pave the way for getting in contact with key decision-makers in potential clients and secur- ing their commitments more rapidly than in more closed business settings, thus easing entry into a new industry. One interviewed partner put this rather succinctly: From our point of view, they [Startup Autobahn] opened us a network in the automotive industry that otherwise would have taken me, as a busi- ness developer, a very long time to reach the right contact. The opportunity to talk to a Porsche inno- vation manager at Startup Autobahn that knows the exact relevant contact and can open that door or make that reference is really, really helpful. Interestingly, many of our interview part- ners—who strategically used OI to enter the au- tomotive industry—strongly discouraged other new ventures from engaging in OI as early as possible, regardless of whether they may have been accepted to an OI program. Instead, they shared their experiences that being close to hav- ingaproductready, andreachingthetippingpoint between an explorative and exploitative mode, is Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 42 Fig ure 1a: Da taS tru ctu re Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 43 Fig ure 1b: Da taS tru ctu re Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 44 Table 1: Interview List # Position Country of ventures’ headquarters 1 CEO & Co-founder Austria2 CEO & Co-founder Bulgaria3 Sales Director Finland4 CEO & Co-founder Finland5 CEO Finland6 CEO & Co-founder Germany7 Head of Business Development Germany8 Head of Marketing Germany9 CEO & Co-founder Germany10 CEO & Co-founder Germany11 CEO & Co-founder Germany12 CEO & Co-founder Germany13 CEO Germany14 General Manager Israel15 General Manager Israel16 Vice President Israel17 Head of Business Development Slovakia18 Sales Director United States19 Head of Business Development United States the optimal moment to use OI. Indeed, the CEO of a new venture explained: It is crazy and not recommended to participate [in OI] at the beginning of the company, but at that point when you have a product, once you have market maturity, once you want to commu- nicate directly and everything is scalable for the OEM, once you know what the customers want, and you know “we just have to make some little adjustments and then let’s go.” That’s the moment when such a program makes sense. An executive of another new venture similarly ar- gued that detailed preparation is pivotal before OI makes sense, due to the thorough checks that even stage-agnostic programs entail for the BMs of new ventures: My advice to startups coming to Startup Autobahn is don’t come before you don’t have all your an- swers ready. You really need to invest time, effort, and money in building that information brief that has all the answers that the industry is going to require. [...] You need to understand that you will be asked a lot of hard questions, and the an- swer cannot be, “We don’t know,” or, “We need to check.” You really need to be ready. For companies with a prior initial track record in the industry, OI influences the customer segment by significantly easing expansion within the indus- try. This is initiated by intentionally making the collaboration visible to the public and the collabo- ration partner’s organization. One interviewee ex- plained: We produced one video for Mercedes and one for Porsche, wrote an article, and, of course, did several posts on LinkedIn. [...] This helped us get a good level of positive internal communica- tion within the respective firms [...]. What we achieved, thanks to this, is that our product is cur- rently rolled out to further Mercedes-Benz plants, and we’re in talks with Porsche on further expand- ing there, too. This openness also smooths expansion into addi- tional application areas. The new ventures can thus utilize their innovative achievements in one industry alongside their public exposure to ven- ture into areas. One interviewee summarized this thusly: One could see that we were able to expand the types of customers we are able to target [with our solution] since we moved from a pure sales and Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 45 automotive retail solution to one that’s also suit- able for automotive engineering applications. Interestingly, the positive benefits of OI for ad- vancing the customer segment are not limited to industry boundaries. Instead, they inspire new ventures to seek additional potential markets, and cross-fertilize business development in adjacent and distant industries, such as aerospace, archi- tecture, pharmaceuticals, and system and ma- chine construction. Additionally, according to our primary data, they provide a signaling effect to stakeholders beyond the initial industry. One in- terviewee exemplified this point: Startup Autobahn has been a boost for the entire company, even for customers who have nothing to do with automotives. Also, the communication of our project has been a boost for investors and sales in the architecture area. It helped us unques- tionably to elevate the entire company to a higher level. These extensions in the customer segment ulti- mately also lead to significant changes in the value proposition. Value Proposition The value proposition of a BM specifies which value-adding products and services are offered to the customer segment (Frankenberger et al., 2013). We found empirical evidence that—thanks to OI—new ventures meticulously reflect on their value proposition, gain an increased level of focus, and ultimately calibrate their offerings to estab- lished industry requirements. An interviewee ex- plained: From the technological solution point of view, it also gives more understanding of what kind of physical interfaces we really need to create, mean- ing the hardware interfaces and software inter- faces, and what kind of standards and certifica- tions we need to take care of and study in the long run. A Co-CEO and co-founder added: What helped us was to get a sort of a benchmark of what other business models are out there for engineering tools [like ours and] learn from the customer first-hand: What gets billed? What are the specific collaboration modes? What are the service levels, etc.? This led to an itemization of requirements. Furthermore, this mix of in-depth and informal ex- changes with a variety of industry experts enables new ventures to validate the demand for their so- lutions, as well as to identify in which areas they have a competitive advantage that should become the focus for their future value proposition. An in- terview partner exemplified this by stating: Eventually, we decided to focus only on providing the foil for our automotive segment by ourselves, and not the electric controller [...] We just had to realize: We cannot offer an entire system, but we have to specialize ourselves onto the core technol- ogy. Finally, OI supports new ventures in transform- ing their value proposition into modular offerings, from which customers have higher sourcing flexi- bility. Furthermore, OI motivates them to proac- tively decrease evaluation barriers from a cus- tomer perspective so as to attract additional cus- tomers in the future. One interviewee illustrated: We were confirmed through [our participation in] Startup Autobahn that it’s important to offer com- ponents which you can bundle easily [...] If you have industry partners, which have different busi- ness models, products, etc., they ask, “What can this startup contribute?” And therefore, I have to make it easy for them and offer a box, where I can say: “This is a working system, just try it out, you can adapt it easily to your needs.” [...] This of- fering approach is something which has been en- couraged by Startup Autobahn, and which we now offer. All of these value proposition changes also impact the value chain. Value Chain The value chain details how organizations create and deliver the value proposition through orches- trating activities and processes (Frankenberger et al., 2013). According to Porter (2004, p. 46), it consists of the primary activities “inbound and outbound logistics,” “operations,” “marketing and sales,” and “service,” as well as the support ac- tivities “procurement,” “technology development,” “human resources management,” and such “firm Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 46 infrastructures” as finance and general manage- ment. Our data reveals that new ventures capital- ize upon OI to integrate their activities in the indus- try’s value network, which leads to a shorter and deeper value chain within the new ventures. One co-founder summarized this through stating: On the value creation side, a change occurred in the way we develop, which led us to open our ecosystem and purposefully decide to locate parts of the value chain in a partner. The increased concentration of the value chain along the specialization in key activities facilitates a standardization for all of its remaining parts. Accordingly, new ventures heavily engage in the implementation of industry-specific certifications, such as ISO and DIN-compliances, and manage the professionalization of internal workflows in suchawayastoimprovecollaborationwithclients and the manufacturability of their solution. An in- terviewee explained: The tricky thing is to rig up the collaboration man- agement from a startup perspective in such a way that innovation management, product manage- ment, etc., is professionalized very quickly. How- ever, this is challenging for firms, because within the Startup Autobahn [program] it’s hectic, much is done in an “on request” fashion, and all this has to be transferred into a standard operation mode. Finally, new ventures take OI as a vehicle for mak- ing significant adjustments to their value chain in terms of strengthening their marketing pres- ence. In particular, they generate brand aware- ness and build up reference cases so as to fuel fur- ther growth: We’re in an industry where you don’t have to ask, “Is there a non-disclosure agreement?” but “how many non-disclosure agreements are there?” [...] Therefore, it’s always difficult for startups to get visible, and what helps is that such open innova- tion projects are, by definition, made accessible to a closing panel, a community, or, in the best case, even the press. And that is always very good be- cause then you do have a reference case. All of these changes in customer segment, value proposition, and value chain also impact the rev- enue model. Revenue Model The revenue model outlines a BM’s financial as- pects, and details the cost and revenue mecha- nisms through which a company intends to gen- erate profits (Frankenberger et al., 2013). Our data suggest that new ventures strategically employ OI to evaluate how much value their inno- vative solutions generate for customers—which is essential information for improving their prof- itability and own value capturing mechanisms. For example, one interviewee characterized this as fol- lows: What we have learned through DXC was that we were able to quantify how much savings in terms of money we can bring the customer. [...] So we learned a bit about how we need to price one of our solutions. Concerning the pricing of OI projects, multiple ventures also made the thought-provoking discov- ery that increasing the price for OI collaboration serves to heighten the chances of a successful col- laboration, since a higher price increases the visi- bility of the project within the corporate and guar- antees management attention. One CEO elabo- rated upon this in detail: We have a higher probability that the customer supports and actively works with us whenever we charge a substantial amount for such [OI] projects. Indeed, the projects that performed worse were those we did for free. These projects go on and on, lack the management attention because the senior management doesn’t know what the front- line employees do, and therefore, the vice presi- dent doesn’t know what the team leader does with us, etc. It all boils down to the question of how high-level the project is anchored. And this corre- lates directly with the project price. That’s a ques- tion of commitment and a question of “Who’s au- thorized to approve budgets?” And the more we charge, the higher the project goes in the hierar- chy, and the more closely the project gets moni- tored, and the better the work that gets done at the bottom of the organization. However, according to our data, after establishing an initial OI collaboration between the new ven- ture and a corporate partner, the latter may in- crease the pressure on the cost and margins of Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 47 the former. This is done through applying their market power and in-depth industry know-how in estimating prices through the entire value chain. Therefore, corporate partners may impose their billing terms on new ventures, for instance, for ex- tending due dates, and undertake thorough due diligence to uncover any potential for decreasing the cost of the new venture’s solution from a cus- tomer’s perspective. One interviewee described it thusly: We had to decrease our overall costs considerably and display the pricing structure for the product very, very transparently to the OEM, but also to the Tier-1, and as a result, our revenue per square meter shrunk substantially. Based upon the shared understanding that the in- dustry prefers lower unit prices over lasting ex- clusivity rights for commercializing the new ven- ture’s solution in their end product, OI leads to in- creased sales volumes, which is mutually benefi- cial for both parties. An interviewee explained: The automotive industry is not so eager to have a kind of exclusivity because even Porsche said to us, “You can talk to Daimler, you can talk to other car makers,” because they understood that if [our solution] comes exclusively, then the price point will jump. And I think they have learned these kinds of lessons that it’s better to be able to scale it to the huge volumes because, at the end of the day, it comes cheaper to them as well. But obvi- ously, they want to have a certain advantage, per- haps, let’s say, one or two years in advance so that they can be the first company to launch it to the marketplace. In conclusion, our findings underline that OI also influences the revenue model. In the following section, we summarize and discuss our findings in the light of the ongoing academic debate. 5. Discussion This study examines how OI influences BMI in new ventures (Figure 2). To explore this issue, we ap- plied a qualitative research approach based upon 19 new ventures which participated in Europe’s largest OI platform. Through clustering our find- ings into customer segment, value proposition, value chain, and revenue model—as per Franken- berger et al.’s (2013) BM framework—we were able to empirically underline how new ventures achieve consistency within their BMs through pur- suing OI with incumbents as their customers. We provide empirical evidence of how OI leads to an expansion in the customer segment and en- ables new ventures to enter new industries, accel- erate growth in entered industries, and leverage their experience in one sector to prepare for an expansion into others. Thus, we confirm previous findings that OI can enable new ventures to iden- tify industries where their solutions can create value (e.g., Chesbrough & Schwartz, 2007). How- ever, our results contradict the preeminent notion in the BMI and OI literature that a very early en- gagement in OI is advantageous (e.g., Pynnönen et al., 2012). Indeed, the experts in our sample con- sistently stressed the importance of thoroughly preparing the engagement in an OI platform in or- der to be ready to capitalize on the momentum for scaling the BM. Thus, based on our data, we argue that, if new ventures wait to commence OI until they are abundantly prepared, it will increase the odds that OI becomes the tipping point for a new venture to shift from an explorative to an ex- ploitative mode. Hence, our data suggest that the managerial recommendation for BMI should not be to integrate customers “from the very begin- ning” (Pynnönen et al., 2012, p. 11), but instead at a point where the new venture is prepared to engage in a meaningful exchange with potential partners. Forthevalueproposition, weconfirmMoschneret al.’s (2019) finding that OI is conducive for develop- ing a value proposition from a new venture’s per- spective, andextendtheliteraturebydetailingOI’s impact on the value proposition. Moreover, we found evidence to suggest that OI might increase the creative potential of what is offered to the cus- tomer (cf. Chesbrough & Appleyard, 2007). How- ever, we have also demonstrated that the mar- ket pressure to comply with, and adjust to, es- tablished industry practices works against the cre- ative push often associated with OI when viewed from a new ventures’ perspective. Therefore, we argue that, in order to maintain the initial creative momentum, new ventures must balance their de- Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 48 Figure 2: OI Influence on BM Components sire to receive early market feedback with the ben- efits of developing a solution detached from the direct influence of conformity with the dominant design. In line with Chesbrough and Appleyard (2007), we have demonstrated that new venture’s value chains become complementary to those already present in the industry. Given the predominance of open BMs in the automotive sector, this leads to a comprehensive integration of the new ventures into a global value network. Consequently, their value chain becomes both shorter and deeper due tospecializationandstandardization, thuslimiting the creative potential for applying unusual prac- tices for value creation in a so highly-regulated and standardized domain as the automotive in- dustry. Thus, our data again underline that a pre- matureengagementinOImighthamperthedevel- opment of unusual approaches to create value. Finally, we have stressed OI’s influence on the revenue model and confirmed previous research emphasizing the cost reductions which can be realized through OI (cf. Chesbrough & Schwartz, 2007). However, our data also accentuates that—contrary to previous understandings in the literature—this does not improve profitability per se (e.g., Ili et al., 2010). Instead, new ventures’ mar- gins are challenged in an OI partnership between new ventures and corporates, thereby reflecting the unevenly distributed market power of the part- ners. This flipside of OI has been underempha- sized in the literature, which could possibly be cor- related with the lack of research on new ventures’ perspectives. Thus, in light of these findings and the persistent need to improve the academic and managerial un- derstanding of OI’s influences on BMI, this study encourages a careful reflection on the two follow- ing aspects. First, the findings underline the importance of identifying the optimal point in time to engage in OI. As demonstrated, this is vital to offset certain disadvantages of OI, such as pressure on margins or loss of creative potential due to premature OI engagement. Second, we stress that the gains for one OI partner can come at a price for the other. Consequently, we argue that taking the firm’s individual perspec- tive into consideration—for instance, concerning experience with industry requirements—is a criti- cal managerial task before pursuing BMI through OI. 6. Limitations and Future Research We conducted our study with high theoretical and methodological rigor. Nevertheless, we acknowl- Seiferlein & Kanbach / Journal of Business Strategies (2023) 40:37-52 49 edge that our research is not free from limitations, which themselves may inspire future research. We studied the effects of OI on BMI in an in- bound OI setting in one industry. Accordingly, we here acknowledge that the effects may well dif- fer between inbound and outbound OI, as well between industries (Spender et al., 2017). How- ever, we mitigated the potential disadvantages of this research setting by examining the most rele- vant form of OI from a practitioner’s perspective (Teplov et al., 2019). Moreover, we focused on an industry for which research calls for OI have been expressed, the need for BMI is preeminent, and which hosts Europe’s largest innovation platform (Ili et al., 2010; Seiferlein et al., 2022; Startup Auto- bahn, 2020). Moreover, our application of a qualitative re- search method may have limited the generaliz- ability of our findings compared to other meth- ods. However, we would argue that our adop- tion of this research method is well-justified given the sparse existing theoretical underpinnings. Fur- thermore, by studying 19 new ventures from 7 countries which participated in Startup Auto- bahn at different points in time during the last 6 years—and by following Gioia et al.’s (2012) guide- lines to yield empirical results based on rigor—we believe that our findings are valuable and trans- ferable for entrepreneurs and executives in sim- ilar settings. Nonetheless, we would value addi- tional quantitative studies to further deepen the understanding of how OI influences BMI. These studies could build upon the identified relation- ships, quantify the individual impact of the first- order and second-order themes, and test our hy- pothesis with a larger sample size. Moreover, fur- therstudiescouldmeasuretheimpactofpotential mediators on the OI-BMI relationship, such as the absorptive capacity, dynamic capabilities, strate- gic agility or the previous OI and BMI experience of the studied new ventures, to name but a few (cf. Foss & Saebi, 2017; Zhang et al., 2021). Finally, our explicit consideration of the perspec- tive of new ventures for examining OI’s effects on BMI was due to persistent calls in the litera- ture. Notwithstanding, we acknowledge that fu- ture studies with an inverse corporate perspective could complement our research and draw useful comparisons with our findings, as suggested re- cently by Milei (2022). References Albats, E., Podmetina, D., & Vanhaverbeke, W. (2021). Open innovation in SMEs: A process view towards business model innovation. Journal of Small Business Management, 1–42. https://doi.org/10. 1080/00472778.2021.1913595 Andreini, D., Bettinelli, C., Foss, N. J., & Mismetti, M. (2021). 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