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Увеличение прибыльности с помощью повышения лояльности потребителя в низкомаржинальном секторе услуг по прокату: применение к индустрии российского велошеринга

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Работа доступна по лицензии Creative Commons:«Attribution» 4.0
Шестаков Станислав Владимирович
Бесплатно
Работа доступна по лицензии Creative Commons:«Attribution» 4.0

Работа посвящена изучению влияния лояльности потребителей на прибыльность в российском велошэринге. Задачами работы являются анализ существующей литературы в сфере лояльности потребителей и ее влияние на прибыльность предприятия, анализ бизнес-модели российского велошэринга, количественное измерение лояльности российских пользователей к велошэрингу и измерение влияния повышенной лояльности на выручку и прибыль российских велошэринговых компаний. Основным результатом работы является разработка модели влияния лояльности потребителей на прибыльность и определение основных факторов лояльности, которые имеют наибольшее влияние на рост выручки и прибыли в российском велошэринге.

Background
Bike-sharing service has recently become one of the most innovative sharing models. The system is, though, not novel, and the very first bike-sharing product was created in 1965 in Amsterdam when the government attempted to find an innovative solution to the traffic problem. Later on, the bike-sharing industry evolved within three generations, which included a free-bikes system, coin-deposit system, and advanced technologies generation. (Shaheen, Guzman, & Zhang, 2010)
The first two generations took place mostly in Europe. In the free-bikes phase, the initiatives appeared, on the one hand, extremely successful in France, and, on the other hand, resulted in a failure in the United Kingdom. The launch of “Bycyken” in Denmark in 1995 triggered the second generation of bike-sharing, which featured distinguishable bicycles, designated docking stations and small coin deposits to unlock the bikes, and became extremely successful and widespread across Europe. The third generation of bike-sharing incorporated advanced technologies for bicycle reservations, pick-up, drop-off, and information tracking and involved not only the European region but also Asia and America. (Shaheen et al., 2010) The market took its explosive growth in 2007, and by 2014 more than 855 cities had introduced their bike-sharing systems. (Richter, 2015) (Appendix 1) China appears to be the global leader in the bike-sharing market with 70 cycle sharing brands, 16 million bikes and over 130 million users. (“Simply Put,” 2017) According to Roland Berger, the global bike-sharing market is expected to grow at GAGR of 20% and to reach EUR3.6 to EUR5.3bn by 2020. (Schönberg, Dyskin, & Markewitz, 2016)
The bike-sharing phenomenon is relatively new for Russia. It appeared first in 2013 with the launch of VeloBike and Veli’k companies in Moscow and Kazan. (“Shared Cycling Booms in Russia,” 2014) Later on, a company with a similar business model was launched in Saint Petersburg and is currently operating under the brand “Velogorod”. Overall, two major companies – VeloBike and Velogorod – currently represent the Russian bike-sharing industry and, therefore, its market size can be estimated by the revenue produced by both companies, which totaled in more than RUR301m. (“За Честный Бизнес АО ‘СИТИБАЙК,’” 2018; “За Честный Бизнес ООО ‘ВЕЛОГОРОД,’” 2018)
Recently, the first and largest dockless bike-sharing provider Ofo announced its expansion into the Russian market. (“В России появится китайская система велопроката Ofo,” 2017) Ofo, as well as the other 40 Chinese bike-sharing companies, implement the practice of charging their customers deposits of $30 to $40 before the user’s first ride. The Russian bike-sharing platforms, in turn, do not require the consumer deposits yet. Moreover, the system in Russia supports only station-based bicycles, whereas the Chinese players are mostly operating dockess bikes.
Therefore, the following work investigates the opportunities to increase the customer loyalty to station-based bike-sharing in Russia. The paper elaborates on the key factors, which affect the consumers’ willingness to use shared bikes and provides recommendations on how to increase the customers’ loyalty within the bike sharing customers industry in Russia.
Research problem, question, and tasks
The current research problem is shaped by the two most relevant issues associated with the launch of a rental business in Russia.
The first issue is academic and related to two main problems. On the one hand, the researchers fail two generate a universal definition of customer loyalty. Some of them refer to the feeling of attachment of a customer to a product. Others name loyalty as repeated purchase behavior, which results from the psychological decision-making process. There are researchers who also include the marketing efforts of potential rivals into the definition of loyalty. (Akın 2012) The following work investigates this issue and creates a definition of customer loyalty suitable to the current topic.
On the other hand, researchers found various ways, in which customer loyalty may affect profits. Therefore, there is a problem of finding a customer loyalty model, which might be suitable for the Russian bike sharing.
The second issue implies that the returns of the Russian bike sharing companies are not stable and they are usually operating at low or negative margins. For instance, the Saint Petersburg’s Velogorod has been operating at negative margins and decreasing returns for the past two years. (“ООО ‘ВЕЛОГОРОД,’” n.d.) Moscow’s Velobike revenue, in turn, is increasing, however, the company’s returns are fluctuating. The previous year, Velobike’s profit margin was about 2%. (“АО ‘СИТИБАЙК,’” n.d.)
Thus, the problem that the current research needs to solve is shaped by the two following issues: finding customer loyalty profit model suitable for the Russian bike sharing and unstable returns with fluctuating revenue of the current players. This implies that in order to increase their financial health, the Russian bike sharing companies need to increase either the wider spectrum of customers or intensify the usage of their services. As, theoretically, the on-time increase in the customers loyalty has a positive impact on a company’s profits, (Reinartz & Kumar, 2002) the companies are in need to increase the Russian customers’ loyalty to bike-sharing.
The current work will be of special interest to the bike-sharing companies in Russia and of those who intend to enter the Russian bike-sharing market.
Goal:
Therefore, the goal of the research is to identify the key factors, which will increase the customers’ loyalty to bike-sharing in Russia.
Furthermore, the research attempts to answer the following question:
• What are the key factors which will increase the customer loyalty to bike sharing in terms of usage frequency?
• What is the feasible effect of the increased customer loyalty on profits in the Russian bike-sharing?
Research tasks:
• Identify what bike sharing is and classify it according to its history and business models
• Identify the business model of the Russian bike-sharing
• Find the definition of customers loyalty to a product and elicit the main factors which affect it
• Find the most important metrics for measuring customers loyalty
• Create the framework of customer loyalty effect on profitability in the Russian bike-sharing
• Conduct a survey on customers loyalty among the current bike-sharing users in Russia
• Come up with the most suitable tools to increase the customer loyalty
Theoretical background and the research gap
Since the bike sharing is relatively to the Russian market, there is no vivid approach to identifying the phenomenon in the Russian literature. (Mamraeva & Tashenova, 2016) identify bike-sharing as a rental system, usually created on a non-commercial basis, which allows customers to rent a bicycle at one of the automated stations, make a trip and return the bike to any rental point in the same city.
However, substantial work has already been done on identifying the bike-sharing as a phenomenon and investigating the strategic side of this topic by the foreign researchers. (Martin, Cohen, Botha, & Shaheen, 2016) identify bike-sharing as a system provides shared bicycles for use by the general public. (Shaheen et al., 2010) also introduce the definition of bike-sharing not only as a system but also as a strategy for combating the current transportation problems in modern cities. Prior to their work, (DeMaio, 2009) created a classification of bike-sharing based on the history of its development and introduced the three-generation framework to the phenomenon, where the last generation is integrated with IT-infrastructure and computing power.
Some researchers also view bike sharing as a part of the sharing evolution and suggest approaching this phenomenon within the large scope of the sharing economy. (郭, 2017) Fang found that dynamic rather than static pricing is more common for the sharing economies. (Fang, Huang, & Wierman, 2017) Kung and Zhong further presented a game theoretical study, which concluded that two features of membership-based pricing outperform the other pricing strategies by two basic features: earliness of collecting money and maximizing the price-sensitive order frequency. (Kung & Zhong, 2017) However, the scholars are still struggling to find common ground on the topic of sharing economy. Botsman identifies sharing economy as ‘an economic system based on sharing underused assets or services, for free or for a fee, directly from individuals’. (Botsman, 2015) Other scholars, though, regard sharing economy as “the growing ecosystem of providers and consumers of temporary access to products and services.” (Santana & Parigi, 2015) Therefore, disputes whether bike sharing is related to the sharing economy still exists among scholars.
Also substantial work has been done on the economical side of the topic. Waserhole and Jost developed a pricing strategy to capture the part of the demand leading to the best behavior for the system. (Waserhole & Jost, 2012) Rousseau in collaboration with other scholars concluded that the future demands in bikes for each station is perfectly known over a short-term horizon. (Contardo, Morency, & Rousseau, 2012)
Customers’ loyalty in bike-sharing is a topic which has not got yet sufficient attention from scholars. There are a number of approaches to the definition of loyalty. According to the definition of Shevchenko, loyalty is the adherence of buyers to a brand, motivated by a firmly rooted habit of buying the same product or using the same service.(“Словарь основных маркетинговых терминов,” n.d.) In turn, customer loyalty can be defined as a positive attitude of the buyer to a particular product, brand, store, service, etc., which, although a consequence of factors significant to the buyer, lies more in the emotional sphere. (Сысоева & Нейман, n.d.) Russian marketer Dymshits argues that “consumer loyalty is based on direct consumer characteristics of the product or services that form the preference for this brand when buying in a product group, as well as the attitude towards it.” (Дымшиц, 2007) Thus, it is the accumulated experience of consumption that forms the relation to the commodity.
Rare works can be found on customers’ loyalty in bike-sharing. However, (Kalina, 2016) introduced her attempt on finding the key factors which might affect the customers’ loyalty in the different customers’ segments in bike-sharing. In 2017 the French Deloitte also created research on customer loyalty in bike-sharing and identified that for 64% of respondents the key factor of switching for shared bikes is a “good value for money,” which implies availability and the quality of the bikes. (Turner & MacMillan, 2017)
Even though a substantial literature has been done on the bike sharing pricing, it is mostly related to the station-based bike sharing. Consumer deposits with the third-generation bike-sharing is an extremely new phenomenon, therefore, little research has been yet done on that pricing strategy for station-free bike sharing. Therefore, due to the novelty of the topic deposits strategy of bike sharing services remains unexplored.

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