Identifying lessons from sports is relatively common in the business world. While this practice has come under scrutiny in academic journals, we believe it is possible to derive valuable business insights from sporting events and the training, preparation, and competition that come with particular sports. Unfortunately, most attempts to do this use metaphors to make comparisons (“X is like Y”) when they should be using analogies (“X works like Y”) to explain the internal functioning of a relatively unobservable phenomenon through a better-known mechanism that does not imply perfect synergy or similarity.
Mixing metaphors and analogies as tools of scientific inquiry can be dangerous. Neuropsychology fell into this trap in the 1980s. It started with a metaphor, “The brain is a computer,” but then mistook it for an analogy. The functioning of computers was well known, being devised by humans, and thus their processes could be grasped (and used as an analogy for the brain). Soon after, neuropsychologists were discussing issues like “programming” cognitive processes, or “encoding information” in a “memory store,” implying that the brain actually did work on the same principles as computing machines. It took about two decades to understand that this metaphor—a more poetic rendering of the brain’s function—was being misused as analogy. That is, it was taken to be an exact explanation of how reality was structured. This misuse thus impeded discoveries about the way in which the human brain operates, as the functioning of the brain happens through radically different mechanisms than those of a home computer.
The business world should avoid this trap. Instead of deploying metaphors when seeking insights from sporting competitions, it should use analogies to examine workable parallels between sports and markets. Sports are a domain where:
- Industry structures are given and known to all.
- Competitors are obliged to follow a strict set of rules and compete exclusively on performance.
- Physical resources are usually spread relatively homogenously (especially when speaking of top athletes).
Exceptions to this last point may arise, such as when a combination of unique physical attributes (like height, endurance, speed, or flexibility) and personal commitment to develop talent makes an athlete completely dominant throughout their careers—like in the cases of Michael Phelps, Sergey Bubka, or Usain Bolt.
Yet more often in every sport there are a dozen or so top athletes more or less equally gifted, with the result that competition is defined by the ways they develop their resources to ensure maximum performance. For example, the difference in results between the number one and number three spot in the women’s long jump in 2022 was 0.98 per cent (a wind-aided 7.13 m took the top distance while the third place for the year was 7.06 m), while in the men’s decathlon the difference was closer to only 0.79 per cent (marks of 8867 versus 8797), and in the men’s 5000-metres, a mere 0.16 per cent separated the times of the first- and third-place finishers (12:45.71 versus 12:46.96, according to worldathletics.org).
It is difficult to argue that this dynamic, if replicated in the marketplace, would sound attractive to a business manager. It represents a case of “red ocean competition”—the type of market rivalry when, according to W. Chan Kim and Renée Mauborgne (the authors of the book outlining these concepts, Blue Ocean Strategy), “industry boundaries are defined and accepted, and the competitive rules of the game are known,” and when “companies try to outperform their rivals. . . . As the market space gets crowded, prospects for profits and growth are reduced.”
Red ocean competition is a situation that the modern strategic literature advises against at any cost, considering it imperative for firms to find their way into the “blue oceans” of new market creation and avoid head-to-head competition.
Interestingly, since the introduction of the divide between red and blue ocean strategies by Kim and Mauborgne in 2004, virtually no literature has emerged on the why and how of competing in the “red ocean” for firms that actually do it. The only reason for firms to remain in a red ocean strategy, in the words of the authors, could be the “mental traps” of unimaginative business managers—that is, mental blocks that prevent ways of creating or finding new markets.
Yet red oceans are a fact of life for many businesses in the world. Grocery retailing is a perfect example: most of the turnover is generated by a limited set of products, and nearly all of them are available to all retailers to resell. Prices are determined by the volume of business, creating a positive feedback loop that would strengthen bigger players and weaken smaller ones. The only advantage that a firm could leverage is a more convenient location.
Paradoxically, the age of digital platforms (often hailed as effective explorers of blue oceans) has made this competition ever more intense, as it has become truly global, de-emphasizing the importance of location, the traditional unique resource of smaller businesses. Consider such an example from Amazon.com, the world’s marketplace: The U.S. version of the website lists 10,000 items in the category “female casual dress,” 7,000 items in “blankets and throws,” and over 10,000 results in “bakeware.” Surely there cannot be such stark differentiation here as a blue ocean strategy would suggest.
Given the red ocean nature of digital platforms or business ecosystems such as Amazon, AliExpress, Uber, or App Store, why do businesses participate in them? The issue of participation in digital platforms is largely overlooked in business studies, which tend to focus on the leaders or owners of platforms rather than the strategic nature of the choice.
Chasing the answer to this question, two of the authors of this article crafted an exploratory project that involved a series of interviews and case studies; this work revealed that the owners and managers of firms that participate in third-party platforms are far from being “un-strategic” and merely following established business routines in the hopes of earning enough for firm survival. Instead, the use of these platforms implies a search for instruments that could help them shape their future in competitive markets.
While this finding may not be earth-shattering, a chance encounter and casual conversation suggested a new way to conceptualize this issue. Alexander Golovin, a professional sport coach, shared with the authors some cases of the successes of his trainees that appeared structurally very similar to the stories of digital platform contributors. Joint discussions of the experiences of sportspeople and businesspeople (methodologically a peculiar combination of hard data analysis, active research, and exploratory qualitative study) brought us to a concept that reconciled our empirical observations with the existing theoretical literature and offered new insights into effective practical responses to the challenges of red ocean competition. In the present article, we take the analogy approach, arguing that some sport disciplines demonstrate essentially the same mechanisms of competition as red ocean markets, where firms use homogenously distributed resources to create products with no major opportunities for changing the rules of the game. The analogy can be useful for both theoreticians and practitioners of business because in sports the idea of head-to-head competition is taken as an imperative, with the consistent marshalling of intellectual resources into finding more effective ways of responding to the challenge. Performance transparency (which business studies can only envy) allows athletes and coaches to not only conceptualize red ocean strategies but constantly put them to rigorous empirical testing, with hard data used as feedback.
Most sports disciplines offer interesting material for analyses that can lead to valuable insights into the problems of competition. In particular, red ocean business is highly comparable to ultramarathon running. Technically, an ultramarathon is any race beyond the standard Olympic marathon distance of 42.2 kilometres. This definition includes a wide range of distances—from a slightly longer marathon of 50 km to multi-day races (of which the six-day Marathon des Sables in the Sahara Desert is probably the most famous). Yet one class of events stands apart: 200+ km non-stop races, which require over a day of running. They pose a significant challenge for training and require peculiar techniques, different from classic marathon preparation.
It takes months of full commitment to exhaustive training to even finish in races like Milan–San Remo (285 km), the Spartathlon (246 km), or the “mere” 217 km of Badwater, which is deliberately placed on the statistically hottest day of the year. Taking a prize or winning looks to be a superhuman feat, requiring a speed of 10 km per hour and running virtually non-stop for more than a day. Every athlete on the starting line is to expect competition from dozens of contenders who are as physically gifted, as committed to preparation, and as motivated to win.
The foundations of the modern approach to Olympic marathon training were generally formed in the early 1950s by Jim Peters, who was the first to break two hours and 20 minutes over this distance. He practiced twice a day, running over 160 km a week. In 1967, Derek Clayton from Australia ran a time of two hours and 10 minutes with an extensive training program that involved up to 320 km of weekly running and three daily training sessions. Since then, intensity has been introduced into the training process with the trend towards more moderate weekly mileage: elite athletes run in the range of 160–220 km, and out of them approximately 20 per cent involve high-intensity running. The modern “formula” for successful marathon training includes a total weekly volume of running four to five times more than the target distance, weekly running in parts for the target distance and at the target speed, and running once a week for the full target distance but at a lower speed. This means running 70–120 per cent of the target distance every day in two to three sessions.
This formula allows for, among other things, predicting the results of an athlete in a race with high precision, and this understanding of expected results for every stage of the race allows a runner to use competitive tactics and craft a racing strategy. While an athlete does not know all of the capabilities of other contestants, they are well aware of their own potential, comparing it with the current pace of the race and deciding whether it would be beneficial to speed up or keep behind the leaders, saving a bit of effort.
Applying this approach to ultramarathon running is impossible due to the radically different proportion between the target distance and feasible daily training distance. Take the example of the leading ultra-runner, Aleksandr Sorokin from Lithuania, the World and European Champion in day running and world-record holder for races of 24 hours, 100 km, and 100 miles. His training data is publicly available and used by many sportsmen and coaches as a benchmark for their personal programs. Sorokin is a professional sportsman (i.e., he has no other bread-winning activity) and trains three times a day, running up to 380 km per week, twice as much as modern marathoners. His “return on investment” in terms of running performance is impressive. He covered 242 km in 24 hours in 2015 and 279 km over the same time in 2019, setting the world record; he then surpassed it with 309 km in 2021 and 319 km in 2022, an increase of 31.8 per cent. Yet even with these volumes of training—unachievable for athletes who have to support themselves through other professional activities—he covers daily no more than 20 per cent of the distance of the ultra-races mentioned above. Ultramarathoners with a focus on 200+ km races never actually run their target distance in the course of training, not even half of it. This is the equivalent of developing a product that would never be assembled unless a sale is made. No matter how sure a firm is about the quality of the parts, there is enough of a possibility that something will go wrong when they are put together. This applies to ultramarathoners as well.
Additional complexities may emerge during ultramarathon races. While classic marathons are scheduled for periods of mild weather and designed to use well-paved roads and avoid significant inclines, the most famous ultras include crossing mountain ridges (the cumulative ascent is over 1 km in Spartathlon and over 4 km in Badwater), overcoming mountain slopes where running is impossible in principle (Spartathlon), and exposure to extreme heat (Badwater). Though these conditions affect all competitors, the peculiarities of individual reactions to them provide for complex tactics planning by athletes and coaches.
Interestingly, this complexity makes ultramarathons more inclusive in terms of participation, making it one of the few remaining sports disciplines without an official division between professionals and amateurs. While each race has strict qualification requirements, they do not require participants to have professional status (unlike official marathons, where amateurs compete in separate leagues). The “openness” of the sport helps to attract new competitors; the list of top-25 performers changes by as much as 60–80 per cent a year. Indeed, some amateurs achieve impressive results despite significant handicaps versus professionals in training time, which is theoretically the key resource for achieving top performance in running: each year, amateurs comprise between 60 per cent and 68 per cent of the top 25 athletes in 24-hour running, and on average, amateurs tend to consistently show higher results than professionals.
Such a turnover rate is comparable to the estimates of attrition of new businesses in red ocean markets. Yet it also does not mean that it is impossible to sustain a position among the top ultramarathoners; despite the shuffling at the top, there have been several athletes who stayed in the top 25 for four years or more during the past decade, with their performance generally above the average level of the top 25 in general. However, such a grueling competitive environment means that performing at such a high level for a long period of time is difficult, and athletes who remain in the top 25 for seven years or more tend to score in the bottom half of the top echelon. This observation may have a direct analogy in business, as it is not necessarily the best performers who can effectively sustain competitive pressure over time but sometimes the most consistent.
Moreover, the constant stream of new entrants pushes up performance standards; in the past 10 years, the average distance run by global top-25 ultramarathoners increased by 5.7 per cent. The classic theory of competition would predict that such growth should lead to a smaller number of new entries (as expected, chances of becoming a recognized athlete are diminishing as performance improves). Yet this does not happen, and the correlation between the turnover rate in the top 25 and the average result achieved in the previous year is positive (0.25). This resembles the constant growth of the number of participants in online marketplaces, which happens despite the fact that new entrants are aware of tough competition and its pressure on prices.
A striking example of amateur success is the case of Sergey Ionov, who finished third in Badwater in 2021. For him, preparing for an ultramarathon on a competitive level seemed to be an over-ambitious target, as his job as a managing director of a London City investment bank kept him busy for 60 to 70 hours a week. Not only did it severely limit his weekly training time (leaving about 15 hours a week versus 25+ for professional athletes), it also made training unevenly spread across days, with approximately 70 per cent of the workload falling on weekends. Despite these limitations, Ionov attempted Badwater in 2018, finishing 13th, with a time of 32:24:52. He sought to improve this result in 2020, but the COVID-19 pandemic led to the cancellation of races across the world. His new target was Badwater 2021. The limitations on his training time required a radically different approach, with more intensive exercises. One of the “hacks” invented by his coach was prolonged jumping and recursive downhill running, creating more stress on the athlete’s legs and preparing them to meet the challenge of exercise-induced muscle damage (EIMD), the key contributor to fatigue in ultramarathons. The result was impressive: Ionov finished third after semi-professional Harvey Lewis (Badwater 2014 winner) and amateur Igor Gotsuliak with a time of 26:49:06, an improvement of almost six hours versus 2018.
One of the consequences of the impossibility of test-running an ultramarathon is the exclusion of benchmarking competitive tactics: an athlete does not have reasonable expectations about target times during the race and thus does not know if they have any “unused” potential. Instead, they run with the pace pre-set to more or less guarantee finishing in the hope that the result will measure up against competitors. Ultramarathoners are strictly instructed by coaches to ignore all other competitors during the race and resist the temptation to engage in personal “duels.”
The case of Ivan Zaborsky is instructive in this regard, as he is an ambitious amateur working full time as a manager in a retail network but who also finished first in the Milan–San Remo in 2018, setting the course record. He first ran Spartathlon in September 2017, setting a personal target of keeping up with professionals Aleksandr Sorokin and Joao Oliveira. He obtained second position in the race after the first 42.2 km, yet he did not manage to keep this pace and finished 35th, six and a half hours behind the winner (Sorokin). He was set to run the Milan–San Remo race in April 2018 and sought ways of quickly improving his performance, with his coach focusing on race tactics. The target pace was set from the start to be five and a half minutes per km, which was significantly below his initial tempo at Spartathlon (4.5 min/km). In the first third of the race, Zaborsky was behind the top 10 racers, while by the middle he had moved up to third and after 200 km he took the lead, overtaking key professional competitor Joao Oliveira, three-time winner and the record holder of the race. Even with a more economical pace, Zaborsky could run consistently for “only” 245 km and for the last 40 km he had to rest by walking. Despite this, he was the first athlete to cover the distance in less than 30 hours (29 hours 46 minutes), setting a new record and taking first place. Oliveira finished second, more than an hour behind.
Ultramarathons also add an important aspect of structural complexity: energy consumption. An athlete consumes roughly 1 kcal per 1 kg of weight per 1 km of distance, which is very significant for a human. Importantly, there is no feasible way to deliver energy to an organism at a comparable rate, so running (unlike walking) will inevitably consume energy stored in an organism. The human body can extract energy from either fats or carbohydrates with the help of oxygen. Fats are stored in sufficient quantities in a healthy body, yet carbohydrates are approximately 6 per cent more energy efficient per 1 litre of oxygen consumption. Unfortunately, a normal human organism has carbohydrates only for about two hours of running—about the time of a professional marathon. Ultras, which last over 20 hours, require extensive restructuring of an athlete’s metabolism; the process is known as “gut training,” which refers to developing the enzymes that allow more effective extraction of energy from nutrition, considering the idiosyncrasies of an individual’s biochemistry.
The power of the technique is illustrated by the example of Dmitry Nedoshitov, who moved from 13th to seventh in global rankings at age 51. Nedoshitov is a devoted amateur runner from a regional Russian town whose financial means preclude participation in commercial ultra-races like Spartatlon or Badwater. Instead, he has concentrated on 24-hour running, and has for a long time been a self-taught athlete. He had no significant limitation of training time and developed a personal approach based on research from the Internet that allowed him to take the 31st position in the global rankings in 2021. Correcting for his age (Nedoshitov turned 50 that year), his result would have put him in 13th place, quite a respectable achievement. Looking to improve his position, Nedoshitov turned to professional coaches, who noted that increasing the training workload was neither necessary nor advisable in the context of winter in a regional town that allowed only outdoor running through poorly managed snow-clad roads. Gut training was instead applied, as Nedoshitov reported problems with nutrition that led to a significant loss of pace with time. Improved metabolism and corrections in race tactics allowed him to overcome this obstacle: in May 2022, he ran the All-Russia 24-hour championship with an almost 7 per cent improvement in his result, bringing him to 18th in global rankings (seventh overall when corrected for age).
Business Lessons from Ultramarathons
The experience of ultramarathons and, especially, ultramarathoners provides an apt working analogy for competition in red ocean markets, as the leading events—like Spartathlon, Badwater, or the individually run (but globally comparable) 24-hour races—are akin to international digital marketplaces. They are all open to competitors from across the globe and provide them with equal opportunities, one goal, and a unified set of rules (similar to the four functions of digital platforms, which are matchmaking, setting rules and standards, providing instruments, and ensuring audience building, according to Moazed and Johnson).
Within this set of rules, athletes and firms can vary individual tactics yet produce essentially the same “product,” competing solely on their performance within the race (similar to a firm providing “value for money” in business in a field of many competitors). Indeed, the one-to-many competitions of ultramarathons (as well as many other sports disciplines) are closer to the realities of business than the series of duels that happen in various team sports, which have been frequently used as material for resource-based analyses in business literature.
The ambitions, motivation, and training processes of ultramarathoners also parallel our research on participants of digital marketplaces. The experiences of our interviewees in competing in the digital marketplace appear to coalesce around launching a business based on one’s own personal experience in consumption coupled with the ambition to both achieve competitive results and enjoy a psychologically rewarding activity. The awareness of strong international competition happens to be a psychological motivator, rather than a barrier, for our interviewees, as people eagerly dive into the red ocean in understanding that the key to success is the effectiveness of every aspect of operations. They seek to achieve this effectiveness through the commitment of all available resources, but also seek more creative means of their application in the hopes of achieving a stronger competitive position.
One of the most interesting similarities between ultramarathoners and entrepreneurs in the digital space is their bifurcated attitude toward competition. On the one hand, ultramarathoners are perfectly aware of the existence of strong competitors, whose numbers are growing as a fact of life. On the other hand, this awareness does not translate into fear or even interest in the affairs of competitors, with ultramarathoners admonished by coaches and trainers to focus on their own performance and generate improvement from within. A similar disdain for explicit competitive analysis was noted by Jim Collins in his book Good to Great, and has become a mainstay of the management literature; however, business researchers have thus far not focused on the situation where competitive analysis may be detrimental even as a firm is trying to beat as many competitors as possible.
Can the ultramarathon approach then lead to success in business? When applied to companies, any answer would necessarily be speculative due to the lack of data on the performance of firms in a given market segment. Our analogy with a particular sport, however, should provide some clues: the cases outlined above demonstrate how athletes have been able to strengthen their competitive position through the improvement of various aspects of their performance. Contrary to the conventional logic that would predict that more physically gifted and longer trained ultramarathoners will take higher positions in races, we see that strategies and tactics exist that allow success even in the context of certain deficiencies of resources (such as age or time to train). While the idea that red ocean competition requires total optimization of every operational aspect sounds banal, the sports analogy allows us to demonstrate that this approach actually works.
It is here that we must raise the imitability issue, which lies at the core of the argument against performance-based competition. In theory, every athlete has access to the same set of training techniques or race tactics. While certain programs are kept secret by marathoners and their coaches, they are based on publicly available scientific findings related to physiology, anatomy, biology, etc. Yet the structural complexity of ultramarathoning precludes competitors using all available instruments to their full potential. Here, in our opinion, lies the key to reconciling theory and practice, as the potential homogeneity of resources in the market—which, as Barney demonstrated over 30 years ago, leaves no room for competitive advantage—does not necessarily translate into actual homogeneity. In markets with enough structural complexity, individual actors may be incapable of maximizing performance across all possible dimensions; this creates what can be labelled dynamic micro-heterogeneity, which allows the more persistent or creative players to improve their competitive position—though this improvement will never allow market domination. In less structurally complex domains, like a classic marathon, there are indeed fewer possibilities of beating more resourceful players. It is quite possible that in real business there is no binary opposition of “red” and “blue” oceans, but rather a continuum of markets, defined by the relative structural complexity of the operations of individual actors.
What do these observations mean for business practitioners across the world? Most important is that there is life in the red oceans. Performance-based competition against multiple players with weakly differentiated products can be a strategic choice and not a result of falling into a “mental trap.” While traditional management theory emphasizes differentiation and new market creation as the “true” strategic response to competitive pressure, our analogy suggests that focused improvement of various components of business operations may also be a promising strategy; we see no reason why it should be considered inferior in any aspect. This understanding can at least provide psychological relief. Indeed, we have observed quite a few businesses that had a true inferiority complex due to their inability to effectively differentiate their business, even though their core operations had a strong competitive position and generated impressive financial returns. The idea of micro-heterogeneity gives strategic guidance for red ocean competition, allowing firms to optimize performance simultaneously across several functions while switching between them to get higher marginal returns—the way athletes who cannot increase their running load apply gut training and develop better race tactics. Many businesses who sell through online marketplaces follow intuitively this approach, switching skillfully between periods of price cuts, heavier investment in advertising, and “milking,” which refers to earning higher profits with somewhat lower volumes (akin to periods of resting through walking in ultramarathons races).
The neglect of red ocean competition by the extant management literature creates a major gap in business theory, which especially affects its applicability to the real-life situations of small and medium-sized enterprises. Participation in digital marketplaces, which are quickly conquering global retail markets, is one particular domain that remains largely uncovered, empirically and conceptually. We believe that when red oceans of performance-based competition are researched and conceptualized as thoroughly as the blue oceans of new market creation, business practitioners will be faced with more informed strategic choices. We hope that this brief introduction attracts more attention to various aspects of red ocean competition, further legitimizing it as a business strategy.
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