27 Journal of Business Models (2023), Vol. 11, No. 1, pp. 27-37 What Makes Your Business Model (Un)Investable? Mehdi Montakhabi1,2,3,4* Abstract This paper seeks to find out what makes a business model (un)investable. In particular, the study explores the reasons for venture capitalists’ rejection decisions on entrepreneurs’ proposals. The study digs into rejected cases in the American Shark Tank TV show as the source of secondary data. Data is transcribed, coded, synthesised, narratives are built, and storytelling techniques are applied to present the findings. The study deviates from the mainstream research on business models, based on primary data. In doing so, the study bridges between the business model research and communication sciences. Key words: Business model, venture capital, entrepreneur Please cite this paper as: Montakhabi, M. (2023), What Makes Your Business Model (Un)Investable?, Journal of Business Models, Vol. 11, No. 1, pp. 27-37 1 imec-SMIT, Vrije Universiteit Brussel, Pleinlaan 9, Brussels, 1050, Belgium 2 Garwood Center for Corporate Innovation, Haas School of Business, University of California, Berkeley, 2220 Piedmont Ave, Berkeley, CA 94720, United States 3 Imperial College Business School, Imperial College London, London SW7 2AZ, UK 4 Center of Energy Technologies (CET), Department of Business Development and Technology (BTECH), Aarhus University, Denmark *Correspondence: mehdi.montakhabi@vub.be ISSN: 2246-2465 DOI: https://doi.org/10.54337/jbm.v11i1.7166 Introduction Whether an innovation is likely to be successful is the holy grail of innovation management. Frequently, investors in early stages of an innovation make their judgements based on heuristics (Gigerenzer et al., 2011) based on a pitch: an idea that is brought forward by an entrepreneur (Sabaj et al., 2020). The success of an investment in this setting depends on how an investor filters out success or failure signals from the pitch. On the entrepreneurs’ side, the art of pitching well is bringing forward the necessary elements to convince investors. Therefore, idea evaluation based on a pitch is a communication process where an idea is sent from one side and interpreted by the other side. In communication studies, information theory suggests for the core message to be transferred suc- cessfully, any noise in the process needs to be filtered out (Pierce, 2012). Furthermore, the interpretation of the communication on the receivers’ side is prone to cognitive biases (Hilbert, 2012). Historically, innovation has been defined in very dif- ferent ways (Baregheh et al., 2009). In the last two decades the emphasis has been shifted to the role mailto:mehdi.montakhabi@vub.be https://doi.org/10.54337/jbm.v11i1.7166 Journal of Business Models (2023), Vol. 11, No. 1, pp. 27-37 2828 of the business model in capturing value from in- novation (cf., Chesbrough and Rosenbloom, 2002). In this view, the business model is considered one of the core success factors of an innovation. Follow- ing this approach, evaluation of an innovation from an investors’ point of view is tied to evaluation of the business model. Prior research has gone to great lengths to under- stand investment decisions to help investors im- prove the decision and entrepreneurs to generate more successful ideas. Authors have focused on how venture capitalists make investment decisions (Pence, 1982) and what kind of investments are more attractive for which groups of venture capi- talists (Klonowski, 2005). Others have investigated the criteria used by venture capitalists to evaluate proposals (MacMillan et al., 1985). A stream in the entrepreneurship literature has studied the entre- preneurs’ side of investment deals and investigat- ed “do and don’ts” in convincing potential investors (Clark, 2008). Some authors have explored the qual- ities of a successful pitch (Komulainen et al., 2020) as well as how to frame and sell an entrepreneurial idea (Dvouletỳ, 2017). Furthermore, the literature has studied how the selection is influenced by the quality of ideas (Boudreau et al., 2016), the use of portfolio approaches and stage gates (Brasil and Eggers, 2019), and several contextual factors—for example, the people pitching the ideas (Brooks et al., 2014), the evaluators of the ideas (Mueller et al., 2018), the presentation of ideas (Lu et al., 2019), the interplay between idea generation and selection (Harvey and Kou, 2013), past and current decisions (Helfat, 1994), and feedback (Wooten and Ulrich, 2017). One of the areas in idea evaluation that, de- spite its importance, has received less attention is evaluation of an innovation based on its business model. Scholars have contributed to the early development of business model research by considering the busi- ness model concept first (Massa et al., 2017) and then through business model innovation (Foss and Saebi, 2018) steadily progressing to open business models (Brenk, 2020; Montakhabi and Van Der Graaf, 2021). Business models have been studied through the lens of different theories such as transaction cost economics (Zott et al., 2010), dynamic capabilities (Leih et al., 2015), and the resource-based view of the firm (Mangematin et al., 2003), just to name a few. There has also been interest in the application of the business model per- spective in a variety of contexts such as innovation (Chesbrough and Rosenbloom, 2002), entrepreneur- ship (Foss and Saebi, 2016), and performance (Kim and Min, 2015). Despite the popularity of business model discussions in academia and practice (Fullenkamp et al., 2017) we observe little agreement not only on the foundations of business model research such as defi- nitions and construct clarity (Foss and Saebi, 2018), but also the criteria for evaluating (successful) busi- ness models. Regardless of the definition in use, the business model in itself is a cognitive tool that is used to communicate what an innovation is, rather than a recipe for success. Therefore, a business model is a form of discourse. This makes it difficult to define and consequently to evaluate. Evaluation of a business model requires knowledge from both the business and communication sides. Taken as a whole, previous work has generated im- portant insights into evaluation of ideas and invest- ment decisions on innovation projects. However, this overview of contemporary scholarship on idea evaluation reveals a number of fundamental gaps. First, in order to understand how investment deci- sions take place and what convinces investors, the storytelling function of business models as a com- munication tool and associated cognitive biases needs to be incorporated. Nevertheless, these as- pects are under-explored in business economics. A frequent approach in communication studies is to look at phenomena as stories, or even more broadly as constructs. In this view, as long as a construct has been talked about, it exists even though it may not be real. Second, at a theoretical level, the common practice in most previous studies focuses on success cases that consequently end in success-biased theory building. Therefore, data on failures are rarely used. A look at the existing venture capital databases supports this claim as there is no record of rejected ideas in most of the credible venture capital databases. Even though there are a few studies on exploring business model Journal of Business Models (2023), Vol. 11, No. 1, pp. 27-37 2929 changes based on false positives and false negatives (e.g., Chesbrough and Rosenbloom, (2002)’s study on Xerox PARC), there is still a considerable gap in the lit- erature on systematically identifying cognitive biases in investment decisions. Third, on a methodological level, when it comes to studying business models, most of the reasoning is inductive (Klauer and Phye, 2008) and studies are designed on single and multiple case studies. There- fore, many of the insights on business model evalu- ation remain somewhat context dependent and difficult to implement out of the studied context. Transferability and generalizability (Hellström, 2008) of findings in these kinds of studies are sometimes questionable as well. To bridge the aforementioned empirical, theoreti- cal, and methodological gaps, this study seeks to in- vestigate the criteria for predicting business model failure in investors’ evaluations of business models. To achieve this overarching aim, we systematically identify rejection criteria in evaluating innovations with an emphasis on business models. Not only will this study examine this very impor- tant question, but also use an ambitious theoreti- cal approach and methodology as well as a unique data set. The study deploys discourse analysis techniques from communication studies to use the American Shark Tank TV show as the second- ary source of data. A discourse analysis based on open coding is manually conducted on the content of the Shark Tank show. Even though the method is very well founded in communication sciences it is used less frequently in the management context. The data allow us to draw deductive-based conclu- sions. The remainder of this paper is structured as follows. First, the methodological approach of the study is explained. This is followed by the summary of find- ings. Findings are presented by applying the story- telling technique. Then, contributions and novelties of the study are explained. This is followed by the introduction of the limitations of the study. Finally, conclusion and opportunities for further research conclude the paper. Methodological Approach This is a qualitative study which utilises secondary data (Johnston, 2017). The American Shark Tank TV show is the source of data in this research. We focused on the cases which did not succeed to get investment in the show. Sharks represent venture capitalists who are investing their own money in their favorite busi- ness models pitched by entrepreneurs. This framing lets us have more than a thousand cases to study. In the majority of cases, there is no consensus be- tween sharks when it comes to successful busi- ness models. Even if one shark wants to invest, it is enough to make the case successful in attracting investment. However, for the rejected cases there is consensus among sharks. They may for different reasons but consensually reject a case. The study investigates the common features which are pointed out by venture capitalists as reasons for not investing in a business. In other words, a business model is uninvestable for venture capitalists if it suf- fers from the distilled rejection criteria. Neverthe- less, every business model which does not have the rejection symptomes gets venture capitalists’ money (for several reasons like each venture capitalist has its own interested areas to invest). Data is transcribed, coded, synthesised, narratives are built, and storytell- ing techniques are applied to present the findings. We studied four hundred and forty-three rejected pitches from the first twelve years of the show. We followed Gioia’s method, transcribed the data, and conducted a thematic analysis to code the data. This led to fifty-four codes in the first order of analysis. Each code represents the main reasons to reject a case. Subsequently, we conducted a second order of analysis and distilled fourteen secondary codes: four- teen things that appeared to turn off the investors. This is followed by building narratives for each sec- ondary code. We applied the storytelling technique (Boje and Jørgensen, 2020) to build the narratives to present our findings. Narratives are built by using quotes from the show. Each pitch is evaluated by six venture capitalists. In total twenty-nine venture capitalists were involved Journal of Business Models (2023), Vol. 11, No. 1, pp. 27-37 3030 in the show. We made our cases by assigning each rejected pitch to the applied code _reason for rejec- tion_ and the venture capitalist who used the code. Therefore a case is a combination of i) a venture capitalist, ii) a code, and iii) a pitch. This led to two thousand seven hundred and seventy-one cases. Table 1 shows the statistics of our analyzed data. Figure 1 shows the research design and the steps we followed in this research. The overarching focus of coding is on the busi- ness model (Massa et al., 2017) behind each pitch. A business model is considered as a means for value creation, delivery, and capturing (Teece, 2010). We distinguish entrepreneurs’ personalities (Chavez, 2016), venture capitalists’ preferences (Carter and Van Auken, 1994), and the quality of the pitch (Kunte et al., 2018) from the business model. Figure 2 distin- guishes the different elements in this study. Summary of Findings In the following the codes from our initial data analy- sis are presented. A narrative is built based on the relevant data for each code. For simplicity, we ex- cluded the direct quotes in the presentation of our findings. • At what stage is your business model? Al- though, it is assumed that businesses go for a venture capitalist at early stages but even in early stages of business there are differences between invention, proof of concept, and a run- ning business. The closer an idea is to a running business, the more trustable entrepreneurs’ visions are for a very simple reason; there are numbers to support entrepreneurs’ claims. A considerable part of investment is on the en- trepreneur and it is almost impossible to judge if the entrepreneur as a part of the idea is in- vestable. Table 1. Number of rejected pitches 442 Number of Sharks in each pitch 6 Total number of Sharks in the show 29 Number of codes in the first order of analysis 54 Number of codes in the second order of analysis 14 Total number of cases* 2771 * A case is a combination of a pitch, a shark, and a code from the first order of analysis Table 1: Statistics of the analyzed data Figure 1: Research design Journal of Business Models (2023), Vol. 11, No. 1, pp. 27-37 3131 • Ownership structure (Who owns how much?): for a venture capitalist it is important to know the ownership structure before and after own- ing a part of a business. If the ownership of a business is diluted before making a deal and entrepreneurs have lost control of their com- pany, or even if they still have control but will lose control as a result of a venture capitalist’s investment, most probably they are not a good option for a venture capitalist’s investment. Simply, if the entrepreneur is a part of invest- ment, how can someone invest in a business that has already lost the entrepreneur’s con- trol? • Is it a business or your hobby? The entrepre- neur believes it is a business and is doing it for a couple of years, not making money, and still continue doing, it is not a business, it is a hobby. No venture capitalist invests in hobbies, they invest in businesses. If the entrepreneurs are not all they will have a hard time finding a venture capitalist to invest. • Ownership profile (second job, conflict of in- terest, bankruptcy, debt, etc.)? Most times the idea of bringing in a venture capitalist is based on the fact: a slice of a watermelon is al- ways bigger than a grape. As much as the idea is important, the profiles of the owners are also important for venture capitalists. Some things like bankruptcy are dealt with like uranium by a venture capitalist. It implies there wouldn’t be any chance to access the banking system in the future. Having a second job as well im- plies that the entrepreneur will split the atten- tion between a venture capitalist’s investment and something else. Carrying a lot of debt also implies a venture capitalist should wait a long time to get the investment back. After all, there shouldn’t be a conflict of interest between what the entrepreneur does and what a venture cap- italist has invested in their portfolio. • Is the business scalable (licensing potential, franchising, etc.)? If a business is not scalable for any reason, it would be hard to find a venture capitalist to invest. The business should have the potential for growth in order to be able to feed two mouths, entrepreneur’s and venture capi- talist’s. Some signs signal scalability, amongst them are potential for licensing or franchising. • Is the business replicable? Does the business have any proprietary assets in its possession? If a business is easily replicable, why should a venture capitalist pay to buy a part of the busi- ness? A convincing answer in a venture capital- ist’s terminology is: the business has a design or utility patent, or at least has filed and is waiting for the patent. If being the first does not give a specific competitive advantage and there is nothing proprietary in the business, it implies the business will be copied at any time which is not a promising signal for a venture capitalist. • Does the business have a fat profit margin? From the moment a venture capitalist invests in a business, even before making the invest- ment, the question always is: how and when will the venture capitalists get their money back? The business should either increase the value of its shares or has a fat profit margin to be able to share money between shareholders. Having a fat profit margin tempts any venture capital- ist to get involved in the business. Figure 2: Positioning the study on business models rather than entrepreneur, venture capital, or the pitch Journal of Business Models (2023), Vol. 11, No. 1, pp. 27-37 3232 • Which one is the entrepreneur ready to give: royalty or equity? Although both seem like giv- ing up a right in a business for perpetuity, there is a huge difference between the two. Accept- ing to pay a royalty assures venture capitalists that they will get their money back but if paying the royalty stays for perpetuity it would look like a liability in case of an acquisition in the future. Paying a royalty especially when a business has a tiny profit margin will suck the blood out of the business. • Does the business have a realistic valuation? Even if everything is right, a wrong valuation might not let a deal with a venture capitalist to be made. It is not easy to value a business in early stages. On the one hand entrepreneurs do not want to sell their businesses for cheap, on the other hand no one wants to pay a premium for a promise in the future. Even if an entrepre- neur can sell a business at a high valuation, it is not good in the long run to have a high valuation because it will stop the businesses’ growth. • Do the entrepreneurs know their competi- tors? The entrepreneur should be the one who knows the competition better than anyone else and be able to convince venture capitalists that they have a comprehensive understanding of their competitors, either direct or indirect. Imagine a venture capitalist asking if there is a similar product or service in the market and the entrepreneur answers no and then suddenly a similar product shows up. • Is the entrepreneur decisive? It is also impor- tant to be able to process and make decisions fast. Entrepreneurs never have all the information they would like to have but they have to make de- cisions based on what they have. This is also true for the other side of the deal, it is what venture capitalists also do, they make investment deci- sions based on the limited information they have. The point is an entrepreneur can not sleep on a decision forever. If entrepreneurs want to play with sharks, and stay alive, they better be fast. • What is the growth strategy? There are differ- ent types of venture capitalists. There should be a strategic fit between the requested re- source, the business nature, and the growth strategy (retail, online, etc.) and the venture capitalists to whom an entrepreneur goes to. At the end of the day it is not just the venture capitalists who make the decision to choose a business to invest in, entrepreneurs should also select their venture capitalists. • Is the business seasonal? If a business makes money but it is not working all year round, it would not be an appealing investment for most venture capitalists. If the business has a prod- uct which can only be sold in a specific period of time, the business is also carrying a lot of risks; if the business losees that window during the year, it will lose any potential earnings for that year. • Does the business have a serious liability as- pect? No venture capitalist looks for liability nightmares. If a business entails health claims, especially if it still does not have scientific evi- dence, FDA approval, intervenes with the na- tional financial system, etc., then the business will be looked at as a liability nightmare in the venture capitalist’s investment portfolio. As long as a business is small, nobody cares about its li- abilities but the moment the business starts to grow, it will be visible on the radar. No venture capitalist wants to be the deepest pocket for the liabilities which a risky business carries. In presenting the findings we avoid using a prede- fined framework (e.g., Business Model Canvas or us- ing the three categories of value creation, delivery and capturing as framing devices) (Sort and Kristian- sen, 2021) for one main reason. Following a deduc- tive approach and analyzing an extensive number of cases lets us to capture elements that do not fit into the existing frameworks. For example, the Business Model Canvas does not capture seasonality nor the scalability aspects of a business. Hence, following a predefined model would have limited our findings to the boundaries of the selected model. Therefore, adhering the chosen methodology from the commu- nication sciences we opt for open coding without a predefined framework. Contribution and Novelty In answering the research question, the study ad- vances our understanding of the ways to better Journal of Business Models (2023), Vol. 11, No. 1, pp. 27-37 3333 evaluate and generate more successful ideas. This is achieveed by firstly deducing the reasons (related to the business models) of rejection of an idea from investors’ perspective that can also be examined failure cases in attracting venture capital invest- ment from the entrepreneurs’ perspective. To do so, the study deploys a novel approach in which the content of the American Shark Tank TV show is cre- atively used as the secondary source of data as well as the methods from communication studies that are applied to answer the question that mostly be- long in management research. In doing so, the study takes a risky and (arguably) novel approach that de- viates from mainstream research in management studies that rely on success cases in theory building. The novel theoretical, methodological, and empirical contributions of the study are: At the conceptual-theoretical level, the study con- tributes to the business model literature, which so far has mostly ignored investment decision-mak- ing and how errors one way or the other in funding a venture might lead to false conclusions on busi- ness model success factors and thus the merits of an innovation.  At a methodological level, the study bridges between business model research and communication sciences by deploying methods from media studies that are rarely used in manage- ment studies. Discourse analysis and open coding without following a predefined theoretical frame- work is a widely adopted approach in communica- tion sciences in general and in media studies in particular. Furthermore, such an approach has im- plications for future applications of this research to use Artificial Intelligence (AI) in order to evaluate crowdsourcing pitches over the Internet. In the me- dium term, this may allow us to employ AI for theory building in management studies.  At an empirical level, the study advances knowledge on generation and evaluation of more successful innovations. This can be used to build a screening tool based on the reasons for acceptance and rejection of investment decisions. This will help managers enhance their de- cisions regarding investments on innovations, i.e., “How to avoid bad deals?” and “How to identify good deals?” The tool will be a checklist consisting of the obvious and non-obvious reasons for rejecting or ac- cepting a proposal that we can distill. The tool can also be used by entrepreneurs to self-evaluate their investment proposals. Limitations and Remedies Several limitations pertain to using the show as the context of this study (e.g., the bridge between a TV show and real life, representativeness of ven- ture capitals as the sample, screenings to make the show attractive, etc.). Nevertheless, there are two main reasons to choose the American Shark Tank TV show as the context of this study. First, this is a very iconic phenomenon that has influenced busi- ness model thinking over one and a half decades and is now running in more than 20 countries, providing a uniquely rich amount of data on the breadth of in- novation evaluation by investors. Secondly, pitching business models for attracting investment is basi- cally an American format. Historically, Silicon Valley has been the place where pitching as a way of com- munication has been used to evaluate new ideas by investors. Therefore, there is no better way to inves- tigate this format than to look at how entrepreneurs pitch and how investors interpret those pitches. Using the content of a TV show in scientific studies is not new. For example “Card Sharks” (Gertner, 1993), “Jeopardy!” (Metrick, 1995), “Illinois Instant Riches” (Hersch and McDougall, 1997), “Lingo”, “Hoosier Mil- lionaire’’ (Fullenkamp et al., 2003), “Who Wants to be a Millionaire?” (Lanot et al., 2006), and “Deal or No Deal’’ (Post et al., 2008). Several studies have been conducted on the Shark Tank show (e.g., Lavanchy et al., 2022 and Sanchez-Ruiz et al., 2021). What has not been done before is focusing on the business model aspect of evaluations. Conclusions and Future Research This study presents common reasons for rejecting a pitch by venture capitalists based on the results of using the American Shark Tank TV show. By identify- ing the criteria of rejected business models the paper highlights what mistakes should be avoided in an en- trepreneur’s business model. To date, the literature on business models are mostly focused on single of multiple case studies based on primary data. Here a controversial method in communication science Journal of Business Models (2023), Vol. 11, No. 1, pp. 27-37 3434 is applied to use secondary data for business model studying. By building narratives based on codes and applying storytelling techniques, it elaborates what and why should be avoided in a business model to at- tract venture capitalists’ investment. Furthermore, the paper draws practical implications for venture capitalists to consider in their evaluation. The study uses the American Shark Tank TV show as the source of data. One interesting venue for future research is to conduct the same research on other available versions of the show (British, Australian, Mexican, and Indian shows to name a few) and com- pare the results (Hewitt-Taylor, 2001) to see if the findings are universally applicable or context de- pendent. In later stages of this research the findings can be used together with machine learning to evaluate the quality of a business model. This is similar to the credit evaluation systems in banks. A big enough sample size can provide the minimum required data for this purpose. Shark Tank is a unique setting which eliminates the contextual effects caused by researchers. Acknowledgements This work was supported in part by the Flemish Government through the FWO-SBO project SNIP- PET-S007619. I would like to thank Prof. Henry Ches- brough, Prof. Christopher Tucci, and Prof. Pieter Ballon for their insightful comments and support. I would also like to thank the proofreaders of the ar- ticle. Journal of Business Models (2023), Vol. 11, No. 1, pp. 27-37 3535 References Baregheh, A., Rowley, J., & Sambrook, S. (2009). Towards a multidisciplinary definition of innovation. Manage- ment Decision. Boje, D., & Jørgensen, K. M. (2020). A ‘storytelling science’approach making the eco-business modeling turn. Journal of Business Models, 8(3), 9-26. Boudreau, K. J., Guinan, E. C., Lakhani, K. R., & Riedl, C. (2016). 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