Innovation in business model as a response to the sharing economy

Espinosa Sáez, Daniel; Delgado-Ballester, Elena; Munuera-Alemán, José Luis Article Innovation in business model as a response to the sharing economy European Journal of Management and Business Economics (EJM&BE) Provided in Cooperation with: European Academy of Management and Business Economics (AEDEM), Vigo (Pontevedra) Suggested Citation: Espinosa Sáez, Daniel; Delgado-Ballester, Elena; Munuera-Alemán, José Luis (2023) : Innovation in business model as a response to the sharing economy, European Journal of Management and Business Economics (EJM&BE), ISSN 2444-8451, Emerald, Leeds, Vol. 32, Iss. 5, pp. 602-619, https://doi.org/10.1108/EJMBE-06-2022-0187 This Version is available at: https://hdl.handle.net/10419/325553 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Innovation in business model as a response to the sharing economy Daniel Espinosa S aez, Elena Delgado-Ballester and Jos e Luis Munuera-Alem an Department of Marketing, University of Murcia, Murcia, Spain Abstract Purpose –The sharing economy (SE) is significantly affecting traditional companies, which have felt a need to adapt their business model. The aim of this study is to identify the different types of adaptation developed by companies within a SE context, and to examine how they relate to their characteristics. Design/methodology/approach –A content analysis involving 149 real-world adaptation cases was carried out, after which a Kruskal–Wallis test and a multiple correspondence analysis were used to explore the relationships between the types of adaptation identified, the business characteristics and the strategic decisions taken for these adaptations. Findings –Through the analyses proposed in the study, the main conclusions suggest that the way companies adapt to SE is related to business characteristics and the strategic decisions taken for these actions, demonstrating throughout the article what types of adaptations are made depending on variables such as sector of activity or business orientation. Originality/value –This study is the first to examine the variables affecting the decisions among traditional companies in response to the SE. In addition, this work explores the SE from the business point of view, shedding light on the participation in SE by traditional companies. Keywords Sharing economy, Business model innovation, Content analysis, Acquisition, Internal development, Partnership Paper type Research paper 1. Introduction In recent years, there has been a tremendous growth in the number of sharing economy (SE) platforms aimed at renting or selling second-hand goods that has profoundly modified consumer behavior and business activities (Agarwal and Steinmetz, 2019). This trend has given rise to the development of an alternative form of consumption that advocates a sustainable economic system through a more efficient exploitation of resources and products (Hamari et al., 2016;Jiang et al., 2016). As a result, the SE has had important socioeconomic and business implications, including the elimination of intermediary companies in operations, direct connection between consumers or the lengthening of the useful life of products. The SE was first seen as a threat to the manufacturers of durable goods and traditional service providers because of its negative influence on industries like hospitality, transportation, fashion, finance and even distribution channels (Keko et al.,2018). EJMBE 32,5 602 © Daniel Espinosa S aez, Elena Delgado-Ballester and Jos e Luis Munuera-Alem an. Published in European Journal of Management and Business Economics. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode The authors are indebted to the editor and the special issue editor for their thoughtful and very helpful comments on earlier version of this study. This research has been supported by a research grant from the financial institution CajaMurcia, the University of Murcia, and the Murcia Innovation Ecosystem: EMURI. The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/2444-8494.htm Received 21 June 2022 Revised 6 April 2023 Accepted 2 May 2023 European Journal of Management and Business Economics Vol. 32 No. 5, 2023 pp. 602-619 Emerald Publishing Limited e-ISSN: 2444-8494 p-ISSN: 2444-8451 DOI 10.1108/EJMBE-06-2022-0187 However, it has recently come to be seen as an opportunity for established business models to create and offer greater value for existing customers (Garud et al., 2022), to acquire new customers, to reduce internal costs through resource and energy efficiency (Chien, 2022;Hsu, 2023), to achieve sustainable development goals (Sadiq et al., 2023) and, for organizations, to expand their reputation by positioning themselves in the market as “sustainable” organizations (Ciulli and Kolk, 2019). As such, traditional companies have started to adapt their business models to SE principles through alternatives such as business model innovation or vertical integration (Chen and Wang, 2019) taking into account that the efficient use of network externalities and external contributions in innovation efforts toward the SE can create competitive advantages (Belezas and Daniel, 2022). However, so far, few studies have examined this area (Zervas et al., 2017), and our study attempts to deepen the SE literature by (1) analyzing if there are differences in the types of adaptation used according to the characteristics of the company itself and their strategic decisions taken for these adaptations (Zervas et al., 2017), (2) identifying what characteristics and strategic decisions are more related to different types of adaptations toward SE (Ciulli and Kolk, 2019), (3) broadening the overall understanding of the SE phenomenon through qualitative analysis (Rojanakit et al., 2022) of real business cases (Agarwal and Steinmetz, 2019) and (4) explaining how business model innovation can play an important role in providing alternatives through SE (Eckhardt et al., 2019). In an effort to address the research gaps mentioned above, we conducted a Kruskal–Wallis test and a multiple correspondence analysis (MCA) among 149 cases of firm adaptations toward SE, and in doing so, identifying important theoretical and practical implications. From a theoretical point of view, the main implications are (1) the extension of the development and explanation of the different forms of adaptation to the SE and their illustration through examples, (2) the enrichment of the existing academic literature on the SE with an approximate distribution of the relationship between the different forms of adaptation carried out by firms to the SE and the characteristics of the firms, (3) the linking of the SE literature with existing literature on business model innovation and (4) the exploratory association of the strategic decisions that each type of adaptation implies for the firm. The ideas provided will open up new lines of research for future studies. From a practical point of view, the main implications are (1) the relationship of concrete examples of adaptation with the adaptation options developed in the literature on SE, giving ideas for company managers, (2) at the same time provides ideas about the consequences that these adaptations will imply for companies, thus helping marketing and innovation professionals from traditional companies to take decisions on how to adapt or react to changes in the market related to SE and (3) explanation for emerging platforms on the distribution of business characteristics that may be most closely related to the different types of adaptation, yielding indications about future threats or opportunities. 2. Theoretical framework Recently, there have been major changes affecting markets in terms of production, marketing, corporate governance and business models (Edelman et al., 2017). Among the changes deserving to be highlighted are the technological advances that have enabled an extensive development of information technologies and important advances in online and mobile communications (Battisti and Brem, 2021), the awareness of climate change and the repercussions that consumer behavior may have on the environment (Hamari et al., 2016). These changes are causing, among other things, a shift away from product ownership in favor of temporary product sharing, resulting into the development of “SE platforms” (Kumar et al., 2018) that affect traditional companies in multiple ways, as described in section 2.1. Innovation in sharing economy 603 2.1 Impact of the sharing economy on traditional markets The emergence and growth of SE, a scalable socioeconomic system that employs technologyenabled platforms to provide users with temporary access to tangible and intangible resources (Eckhardt et al., 2019), have a significant effect on traditional durable goods manufacturers and service providers. Not only does it alter consumer (purchasing and usage) behavior, it also affects the mode of operation of manufacturers (Li et al., 2020), their market share and the role played by consumers (Matzler et al., 2015). From the point of view of people’s purchasing behavior, and according to the European Commision (2018), at a European level, only 33% of collaborative platform users claim that they will continue to use products/services through traditional business models in the same quantities as before accessing these platforms. By contrast, 32% of them affirm to have replaced to some degree the services they used through traditional channels with services offered through collaborative platforms. This shows that the effects of the SE on consumption patterns in established markets are a worrying reality for traditional companies. From a business perspective, all sectors and industries are being affected to a greater or lesser extent by the SE (Keko et al., 2018). SE poses a threat to established companies as it cannibalizes purchases and reduce prices (Richard and Cleveland, 2016) by promoting the replacement of individual property acquisition by shared ownership (Sanasi et al., 2020)or even by short-term renting (Belk, 2014). This can be clearly seen in hospitality and transportation, which are the sectors that have been most affected (Gerwe and Silva, 2020). For example, Zervas et al. (2017) found that a 1% increase in Airbnb listings leads to a reduction of 0.05% in quarterly hotel revenues, which is in line with recent research by Hossain (2020). Additionally, Airbnb’s entry makes the hotel industry more heterogeneous, forcing high-quality hotels to reposition themselves at the higher end of the market, while lower quality accommodations move to compete on price with Airbnb (Chang and Sokol, 2022). In the transportation sector, Kim et al. (2018) demonstrated that mobility markets such as cabs have significantly reduced their number of trips in relation to the growth of Uber. Mouratidis et al. (2021) argued that the average number of vehicles owned per household has significantly reduced when using the SE, and that for every vehicle used in shared mobility the number of vehicles in circulation has proportionally been reduced. In addition, the SE has also led to significant changes in distribution channels because the sales force of the B2B2C sector has been replaced by these service providers (Kumar et al., 2018). As such, the SE challenges traditional marketing channels and supply chains. The concepts of ownership and its transfer are deeply embedded in the roles of traditional channel members, while in the SE, consumers see access as an accepted way to obtain resources that were previously acquired through traditional channels (Ferrell et al., 2017). To cope with the negative consequences described above, companies have begun to adapt to the SE as it is described in section 2.2. 2.2 Business model innovation in the face of the SE The shift toward the new modes of consumption that characterize the SE may offer new options for companies to innovate (Ciulli and Kolk, 2019), to continue serving their customers (Sanasi et al., 2020), or to design new business models and value propositions to better adapt themselves to the new demand logics (Massi et al., 2021). In this way, traditional companies can leverage their experience and the strength of their brands to adapt to SE (Richard and Cleveland, 2016) or give their product a new form of use (Klotz, 2018). To take advantage of these opportunities, some companies have already begun to adapt their business models to the principles of SE (Chen and Wang, 2019), and earlier studies have identified different forms of adaptation (see Table 1). EJMBE 32,5 604 Belk (2014) and Matzler et al. (2015) were the first to suggest some classifications of adaptation options, on the basis of which new forms of adaptation were later proposed such as extending the brand to peer-to-peer rental services (Richard and Cleveland, 2016), adding product rental to the service offering of companies (Klotz, 2018), developing or using collective shipping services through agreements (Kang et al., 2019) or cooperating with SE platforms (Li et al., 2020). Other authors, such as Chen and Wang (2019), explore already established options like acquisition or companies creating their own platforms. More recently, Ciulli and Kolk (2019) have proposed a new classification of adaptive actions that distinguish between internal development, partnership and acquisition. At the same time, we observe a lack of research that has examined whether these alternative optionsofadaptationdependonacompany’s specific characteristics (Ciulli and Kolk, 2019), especially within a B2B context (Agarwal and Steinmetz, 2019), where academic studies have analyzed the main barriers for industrial companies to enter the SE (Govindan et al., 2020), and the challenges they face to develop sharing-based business models (Melander and Arvidsson, 2021). To shed light on this issue, the next section describes the methodology used to analyze, in a B2B context, whether the adaptation options observed in the market are related to the business characteristics of the companies involved. 3. Methodology Given that business reality is, in some cases, ahead of academic studies in terms of the development and analysis of new business models (Bocken et al., 2014), an exhaustive study of real cases of adaptation has been carried out following a procedure similar to the one developed by Ciulli and Kolk (2019) and Urbinati et al. (2017). For the identification of the cases, we followed a process divided into five sequential steps, which took place between July 2021 and January 2022. First, we identified the economic sectors with the greatest presence of SE, and which are the most important exchange platforms in each sector based on the information provided by consulting firms like PwC (2015,2018) or organizations like the European Commision (2016, 2018). This resulted in the following list of sectors: accommodations, automotive, financial, machinery/industrial equipment, fashion, labor service, catering, and retail and logistics. Belk (2014) Offering free content while providing other sources of income Acquire a collaborative platform Create a collaborative platform Matzler et al. (2015) Sell the use of the product Support customers in their desire to resell goods Exploit unused resources and capabilities Provide repair and maintenance services Expanding into new markets with collaborative consumption Develop new business models through the SE Richard and Cleveland (2016) Extending the brand to peer-to-peer rental services Klotz (2018) Add product rental services Chen and Wang (2019) Acquire a collaborative platform Create a collaborative platform Kang et al. (2019) Develop/use a collective mailing service Ciulli and Kolk (2019) Internal development Partnership Acquisition Li et al. (2020) Cooperating with collaborative platforms Source(s): Table by the authors Table 1. Types of business adaptation to the SE Innovation in sharing economy 605 Second, we focused on identifying specific cases of companies that are active in the sectors we identified and that have innovated to adapt to the SE. Using Google Chrome browser, we consulted both general and news section results by adding the term “SE”to each of the sectors. Because it was a general keyword search, millions of results were obtained. Third, to reduce the enormous number of results we obtained in the previous step, new, more refined and specific search keywords were used for each sector to obtain more precise results. Table 2 contains the keywords/headlines used to perform the searches. Accommodation Hotel SE Hotel sharing Hotel adapt to SE Automotive Cars SE Mobility SE Geely Holding Group SE Daimler SE Group Volkswagen SE Toyota Motor Corporation SE Nissan SE Volvo SE Hyundai Company SE Tesla Motors SE Groupe Peugeot Soci et e Anonyme (PSA) SE Renault SE Kia Motors SE Financial Bank SE Finance SE Industrial machinery/equipment Machinery SE Construction SE Equipment SE B2B SE Sharing machinery Fashion Fashion SE Collaborative fashion Fashion companies subscription Fashion clothing rental Rental services in fashion H&M SE Nike SE Levi’sSE Labor services Corporations SE Manufacturer SE Corporations crowd work Shared economy in labor services Shared economy in labor insurance Restoration Catering SE Delivery sharing service Retail and logistics Logistics SE Shared transportation Retail SE Supermarket SE Department store SE Retailers SE Wholesalers SE Source(s): Table by the authors Table 2. Sectors and search keywords EJMBE 32,5 606 In the fourth stage of the process, more specific information was collected for each of the identified cases to generate a more complete description. To this end, the website of the exchange platform and/or company related to the specific example was visited and press releases on the innovation of the business model developed by the actors involved were consulted. In turn, this search made it possible to identify alternative keywords, resulting in the identification of new cases. In addition, for each registered company, an exhaustive search was carried out for information on business characteristics such as turnover, age, sector of activity and commercial orientation. The entire process of identification, information collection and analysis described above resulted in a total sample of 149 adaptation cases [1]. Finally, the information obtained for each case was recorded and coded using content analysis, and different variables were defined to characterize each individual case. As a result, a database of 10 variables describing the identified business cases was formed. 3.1 Content variables and coding The variables used to characterize the adaptation cases are described in Table 3. Some of them characterize the companies themselves and others have to do with the decisions made to adapt to the SE. As far as the commercial orientation of companies is concerned, we distinguished three options: a consumer orientation (B2C), a business orientation (B2B) or a mixed (B2B and B2C) orientation. The size of the companies was defined according to the 2019 turnover in millions of euros (MMV). Because most companies are large, we opted in favor of classifying them in terms of their size relative to each other. The variables “the type of adaptation”and “the part of the business model adapted”were codified following Ciulli and Kolk (2019). Specifically, three categories were used to describe the “types of adaptation.”“Internal development”encompasses companies that have used Sector Size Business orientation Age 15Industry 15<2 252–10 3510–50 45>50 15B2C 25B2B 35B2B and B2C 15<10 2510–50 3550–100 45>100 25Transportation and storage 35Construction 45Trade 55Hospitality and tourism services 65Other services Type of adaptation Adapted business model part Brand decision 15Internal development 25Acquisition 35Partnership 15Value proposition 25Customer interface 35Business infrastructure 45Entire new business model 15New brand 25Extension Consumption change Duration (years) Country 15App 25Rent 35No 150–1 251–5 35>5 15China 25EEUU 35Spain 45Japan 55United Kingdom 65Europe 75Asia 85America 95World Source(s): Table by the authors Table 3. Variables structure and coding Innovation in sharing economy 607 their own resources to adjust their business to SE. Within the category of “partnership”are identified those companies that have modified their business models through collaboration agreements with other institutions. By contrast the category “acquistion”includes the total or partial purchase of other companies or platforms as a way to adapt. The variable “adapted business model part”has four categories. The “value proposition” one encompasses those cases whose change action involved the addition of a new product/ service offered to existing customers. An example of this would be a new home delivery service offered by a supermarket. The “customer interface”option represents those adaptation actions that involved offering a new or existing product/service to a new segment of consumers. An example would be the development by an insurance company of a special insurance for users of shared mobility, which is a segment hitherto unexploited by the company. The “business infrastructure”category refers to adaptation options that involve changes in the way the company’s resources (e.g. labor, equipment, machinery or tools) are managed. This is the case with the joint creation among several companies of an innovation ecosystem to cooperate in the use of resources or hiring of labor. Finally, the creation of a complete “new business model”frames cases of adaptation that involve the creation of an entirely new business model for the company. An example of this would be the offering of shared mobility services by car companies. Additionally, we also looked at whether the modification or creation of new business models involves a “brand decision.”This variable classifies cases of adaptation into two categories depending on whether the change implies the creation of a new brand related to the created/adapted business model (“new brand”category), or it only involves the integration of these business model changes within the firm’s existing brand portfolio (“brand extension” category). Whether these adaptation options involve some type of “consumption change”when purchasing goods or services was also analyzed and different categories were identified. The “app”category implies the use mobile applications to interact with the company. The “rent” option involves not acquiring ownership of the product but entering into temporary rental contracts with the companies. The “no”category means that the modes of consumption did not change at all. 3.2 Sample description Table 4 shows the characteristics of the companies involved. The most prominent sector is industry (56%), followed by other services (22%) and commerce (11%), while they are mostly very large companies, 49% of them with a turnover over V50 M, and 26% between V10 M and V50 M. In addition, most of the companies operate in both B2B and B2C contexts (77%) and have significant experience in the market, with 67% of them having been in business for more than 50 years. The type of adaptation most frequently developed is partnership (63%) and the least common form is acquisition (16%). Regarding the adapted business model, the most frequent options are the adaptation of the customer interface (33%) and the creation of a new business model (31%). In terms of brand decision, in most cases (71%) companies kept using their current brand (brand extension), while a minority of 29% preferred to create a new brand. Most of the adaptation cases did not directly involve changes in the form of consumption (51%), while some others (39%) opted to use an application to offer products. Finally, the geographical profile of the adaptation actions developed is centered on three categories: worldwide (28%), Europe in general (25%) and the USA (23%). The duration of these adaptations varies between 1 and 5 years (59%). EJMBE 32,5 608 4. Analysis and results 4.1 The Kruskal–Wallis test First, for data analysis, the Kruskal–Wallis test was performed using SPSS software. The Kruskal–Wallis test is a non-parametric (one-factor) test that analyzes the variances of categorical variables and compares differences between three or more groups (Tuff ery, 2011). This test has been used by recent studies (see Chang et al.,2019;Rita et al., 2021) with similar aims to the present study, that is, to explore the relationships between qualitative variables. In the context of our study, this test will help to understand how firm characteristics (e.g. sector, size, business orientation and age), and the strategic decisions taken for these adaptations (part of the adapted business model, brand decision, consumption change, country and duration) are related to the different types of adaptation carried out by firms to the SE. More specifically, the test will allow us, through the use of the Kruskal–Wallis chi-square, to test the null hypothesis that: H0. There are no significant differences in the dependent variable (i.e. that there are no differences in the use of the different type of adaptation) between the groups of independent variables (firm characteristics and strategic decisions). As shown in Table 5, the Kruskal–Wallis chi-square p-value is <0.1 in several cases, and in others even <0.01 so that we can reject the null hypothesis at this level of significance. More specifically, Table 5 shows how, with respect to the characteristics of the companies, there are significant differences in the types of adaptation used according to the business sector. This indicates that not all companies engage in the same adaptation activities toward the SE, but that, depending on the sector in which they operate, they are oriented toward one type of action or another. This is also the case for business orientation, although with a lower significance (p< 0.1), which shows that there are significant differences in the implementation of the types of adaptation according to the business orientation of the company. However, there are no significant differences in the use of adaptation options according to the size or age of the enterprise, indicating that it cannot be claimed that companies, large or small, old or new, adapt in different ways. Sector % Size % Age % Business orientation % Industry 56 <2 11 <10 2B2C 20 Other services 22 2–10 14 10–50 31 B2B 3 Trade 11 10–50 26 50–100 47 B2C and B2B 77 Hospitality and tourism services 9 >50 49 >100 20 Transport and storage 2 Adapted business model part % Type of adaptation % Country % Duration % Entire new business model 31 Acquisition 16 World 28 <1 18 Business infrastructure 7 Partnership 63 Europe 25 1–560 Customer interface 33 Internal development 21 EEUU 23 >5 22 Value proposition 29 Spain 6 China 4 Brand decision % Consumption change % United Kingdom 4 Extension 71 App 39 America 4 New brand 29 Rent 10 Asia 3 No 51 Japan 3 Source(s): Table by the authors Table 4. Business and actions characteristics of SE adaptation Innovation in sharing economy 609 making it difficult to draw conclusions about smaller companies. As such, future research can also include smaller companies, and see what the similarities and differences are when looking at the size of a company. Note 1. The complete list of companies, sectors and types of adaptation can be requested from the authors. References Adner, R. (2006), “Match your innovation strategy to your innovation ecosystem”,Harvard Business Review, Vol. 84 No. 4, p. 98. Agarwal, N. and Steinmetz, R. (2019), “Sharing economy: a systematic literature review”,International Journal of Innovation and Technology Management, Vol. 16 No. 06, 1930002. Arimond, G. and Elfessi, A. (2016), “A clustering method for categorical data in tourism market segmentation research”,Journal of Travel Research, Vol. 39 No. 4, pp. 391-397. Battisti, S. and Brem, A. (2021), “Digital entrepreneurs in technology-based spinoffs: an analysis of hybrid value creation in retail public–private partnerships to tackle showrooming”,Journal of Business and Industrial Marketing, Vol. 36 No. 10, pp. 1780-1792. Belezas, F. and Daniel, A.D. (2022), “Innovation in the sharing economy: a systematic literature review and research framework”,Technovation, Vol. 122, 102509. Belk, R. (2014), “You are what you can access: sharing and collaborative consumption online”,Journal of Business Research, Vol. 67 No. 8, pp. 1595-1600. Bocken, N.M.P., Short, S.W., Rana, P. and Evans, S. (2014), “A literature and practice review to develop sustainable business model archetypes”,Journal of Cleaner Production, Vol. 65, pp. 42-56. Cant u, C.L., Schepis, D., Minunno, R. and Morrison, G. (2021), “The role of relational governance in innovation platform growth: the context of living labs”,Journal of Business and Industrial Marketing, Vol. 36 No. 13, pp. 236-249. Carlborg, P.J., Hasche, N. and Kask, J. (2021), “Overcoming the business model transformation dilemma: exploring market shaping and stabilizing strategies in incumbent firms”,Journal of Business and Industrial Marketing, Vol. 36 No. 13, pp. 66-77. Chang, H.H. and Sokol, D.D. (2022), “How incumbents respond to competition from innovative disruptors in the sharing economy—the impact of Airbnb on hotel performance”,Strategic Management Journal, Vol. 43 No. 3, pp. 425-446. Chang, H.C., Wang, C.Y. and Hawamdeh, S. (2019), “Emerging trends in data analytics and knowledge management job market: extending KSA framework”,Journal of Knowledge Management, Vol. 23 No. 4, pp. 664-686. Chen, Y. and Wang, L. (2019), “Commentary: marketing and the sharing economy: digital economy and emerging market challenges”,Journal of Marketing, Vol. 83 No. 5, pp. 28-31. Chien, F.S. (2022), “The mediating role of energy efficiency on the relationship between sharing economy benefits and sustainable development goals (Case of China)”,Journal of Innovation and Knowledge, Vol. 7 No. 4, 100270. Child, J., Faulkner, D. and Pitkethly, R. (2001), The Management of International Acquisitions, Oxford University Press, New York. Ciulli, F. and Kolk, A. (2019), “Incumbents and business model innovation for the sharing economy: implications for sustainability”,Journal of Cleaner Production, Vol. 214, pp. 995-1010. Coombes, P. (2022), “A review of business model research: what next for industrial marketing scholarship?”,Journal of Business and Industrial Marketing, Vol. 38 No. 3, pp. 520-532. Das, S., Avelar, R., Dixon, K. and Sun, X. (2018), “Investigation on the wrong way driving crash patterns using multiple correspondence analysis”,Accident Analysis and Prevention, Vol. 111, pp. 43-55. EJMBE 32,5 616 Eckhardt, G.M., Houston, M.B., Jiang, B., Lamberton, C., Rindfleisch, A. and Zervas, G. (2019), “Marketing in the sharing economy”,Journal of Marketing, Vol. 83 No. 5, pp. 5-27. Edelman, B., Luca, M. and Svirsky, D. (2017), “Racial discrimination in the sharing economy: evidence from a field experiment”,American Economic Journal: Applied Economics, Vol. 9 No. 2, pp. 1-22. European Commision (2018), “The use of the collaborative economy (issue october)”. European Commision (2016), “The use of collaborative platforms”,Flash Eurobarometer, Vol. 438, available at: http://ec.europa.eu/commfrontoffice/publicopinion/index.cfm/ResultDoc/download/ DocumentKy/72885 Ferrell, O.C., Ferrell, L. and Huggins, K. (2017), “Seismic shifts in the sharing economy: shaking up marketing channels and supply chains”,Journal of Marketing Channels, Vol. 24, pp. 3-12. Francis, J. and Smith, A. (1995), “Agency costs and innovation some empirical evidence”,Journal of Accounting and Economics, Vol. 19 Nos 2-3, pp. 383-409. Garud, R., Kumaraswamy, A., Roberts, A. and Xu, L. (2022), “Liminal movement by digital platformbased sharing economy ventures: the case of Uber Technologies”,Strategic Management Journal, Vol. 43 No. 3, pp. 447-475. Gerwe, O. and Silva, R. (2020), “Clarifying the sharing economy: conceptualization, typology, antecedents, and effects”,Academy of Management Perspectives, Vol. 34 No. 1, pp. 65-96. Govindan, K., Shankar, K. and Kannan, D. (2020), “Achieving sustainable development goals through identifying and analyzing barriers to industrial sharing economy: a framework development”, International Journal of Production Economics, Vol. 227, 107575. Hamari, J., Sj€ oklint, M. and Ukkonen, A. (2016), “The sharing economy: why people participate in collaborative consumption”,Journal of the Association for Information Science and Technology, Vol. 67 No. 9, pp. 2047-2059. Hossain, M. (2020), “Sharing economy: a comprehensive literature review”,International Journal of Hospitality Management, Vol. 87, 102470. Hsu, C.C. (2023), “The role of the core competence and core resource features of a sharing economy on the achievement of SDGs 2030”,Journal of Innovation and Knowledge, Vol. 8 No. 1, 100283. Jiang, B., Tian, L., Xu, Y. and Zhang, F. (2016), “To share or not to share: demand forecast sharing in a distribution channel”,Marketing Science, Vol. 35 No. 5, pp. 800-809. Jord~ ao, R.V.D., Souza, A. ^ O.A. and Avelar, E.A. (2014), “Organizational culture and post-acquisition changes in management control systems: an analysis of a successful Brazilian case”,Journal of Business Research, Vol. 67 No. 4, pp. 542-549. Joseph, D., Windham-Bannister, S. and Mangold, M. (2021), “What corporates can do to help an innovation ecosystem thrive–and why they should do it”,Journal of Commercial Biotechnology, Vol. 26 No. 1, pp. 3-12. Kang, Y., Lee, S. and Chung, B.D. (2019), “Learning-based logistics planning and scheduling for crowdsourced parcel delivery”,Computers and Industrial Engineering, Vol. 132 No. 2019, pp. 271-279. Kanter, R.M. (1994), “Collaborative advantage”,Harvard Business Review, Vol. 72 No. 4, pp. 96-108. Karim, S. and Mitchell, W. (2004), “Innovating through acquisition and internal development: a quarter-century of boundary evolution at Johnson & Johnson”,Long Range Planning, Vol. 37 No. 6, pp. 525-547. Keko, E., Prevo, G.J. and Stremersch, S. (2018), “The what, who and how of innovation generation”,in Golder, P.N. and Mitra, D. (Eds), Handbook of Research on New Product Development, Edward Elgar Publishing, pp. 37-59. Kim, K., Baek, C. and Lee, J.D. (2018), “Creative destruction of the sharing economy in action: the case of Uber”,Transportation Research Part A: Policy and Practice, Vol. 110, pp. 118-127. Klotz, F. (2018), “Manufacturers can also win in the sharing economy”,MIT Sloan Management Review, Vol. 49 No. 2, pp. 1-5. Innovation in sharing economy 617 Konietzko, J., Bocken, N. and Hultink, E.J. (2020), “Circular ecosystem innovation: an initial set of principles”,Journal of Cleaner Production, Vol. 253, 119942. Kumar, V., Lahiri, A. and Dogan, O.B. (2018), “A strategic framework for a profitable business model in the sharing economy”,Industrial Marketing Management, Vol. 69, pp. 147-160. Lee, G.K. and Lieberman, M.B. (2010), “Acquisition vs internal development as modes of market entry”,Strategic Management Journal, Vol. 31 No. 2, pp. 140-158. Li, Y., Bai, X. and Xue, K. (2020), “Business modes in the sharing economy: how does the OEM cooperate with third-party sharing platforms?”,International Journal of Production Economics, Vol. 221, 117467. Mai, E.S. and Ketron, S. (2022), “How retailer ownership of vs collaboration with sharing economy apps affects anticipated service quality and value co-creation”,Journal of Business Research, Vol. 140, pp. 684-692. Massi, M., Rod, M. and Corsaro, D. (2021), “Is co-created value the only legitimate value? An institutional-theory perspective on business interaction in B2B-marketing systems”,Journal of Business and Industrial Marketing, Vol. 36 No. 2, pp. 337-354. Matzler, K., Veider, V. and Kathan, W. (2015), “Adapting to the sharing economy”,MIT Sloan Management Review, Vol. 56 No. 2, pp. 71-77. Melander, L. and Arvidsson, A. (2021), “Introducing sharing-focused business models in the B2B context: comparing interaction and environmental sustainability for selling, renting and sharing on industrial markets”,Journal of Business and Industrial Marketing, Vol. 36 No. 10, pp. 1864-1875. Moreau, C.P., Franke, N. and von Hippel, E. (2018), “The paradigm shift from producer to consumer innovation: implications for consumer research”, in Golder, P.N. and Mitra, D. (Eds), Handbook of Research on New Product Development, Edward Elgar Publishing, pp. 81-99. Mouratidis, K., Peters, S. and van Wee, B. (2021), “Transportation technologies, sharing economy, and teleactivities: implications for built environment and travel”,Transportation Research Part D: Transport and Environment, Vol. 92, 102716. Parchomenko, A., Nelen, D., Gillabel, J. and Rechberger, H. (2019), “Measuring the circular economy - a multiple correspondence analysis of 63 metrics”,Journal of Cleaner Production, Vol. 210, pp. 200-216. PwC (2015), “The sharing economy - consumer intelligence series”, available at: https://www.pwc.com/ us/en/industry/entertainment-media/publications/consumer-intelligence-series/assets/pwc-cissharing-economy.pdf PwC (2018), “Share economy 2017. The new business model”, available at: https://www.pwc.de/de/ digitale-transformation/share-economy-report-2017.pdf Richard, B. and Cleveland, S. (2016), “The future of hotel chains: branded marketplaces driven by the sharing economy”,Journal of Vacation Marketing, Vol. 22 No. 3, pp. 239-248. Rita, P., Ramos, R.F., Moro, S., Mealha, M. and Radu, L. (2021), “Online dating apps as a marketing channel: a generational approach”,European Journal of Management and Business Economics, Vol. 30 No. 1, pp. 1-17. Rojanakit, P., Torres de Oliveira, R. and Dulleck, U. (2022), “The sharing economy: a critical review and research agenda”,Journal of Business Research, Vol. 139, pp. 1317-1334. Sadiq, M., Moslehpour, M., Qiu, R., Hieu, V.M., Duong, K.D. and Ngo, T.Q. (2023), “Sharing economy benefits and sustainable development goals: empirical evidence from the transportation industry of Vietnam”,Journal of Innovation and Knowledge, Vol. 8 No. 1, 100290. Sanasi, S., Ghezzi, A., Cavallo, A. and Rangone, A. (2020), “Making sense of the sharing economy: a business model innovation perspective”,Technology Analysis and Strategic Management, Vol. 32 No. 8, pp. 895-909. Thomas, L.D. and Ritala, P. (2022), “Ecosystem legitimacy emergence: a collective action view”, Journal of Management, Vol. 48 No. 3, pp. 515-541. EJMBE 32,5 618 Tuff ery, S. (2011), Data Mining and Statistics for Decision Making, John Wiley & Sons, Chichester. Urbinati, A., Chiaroni, D. and Chiesa, V. (2017), “Towards a new taxonomy of circular economy business models”,Journal of Cleaner Production, Vol. 168, pp. 487-498. Xie, X. and Wang, H. (2020), “How can open innovation ecosystem modes push product innovation forward? An fsQCA analysis”,Journal of Business Research, Vol. 108, pp. 29-41. Zervas, G., Proserpio, D. and Byers, J.W. (2017), “The rise of the sharing economy: estimating the impact of Airbnb on the hotel industry”,Journal of Marketing Research, Vol. 54 No. 5, pp. 687-705. Zhang, J., Yu, B. and Lu, C. (2021), “Exploring the effects of innovation ecosystem models on innovative performances of start-ups: the contingent role of open innovation”,Entrepreneurship Research Journal, 20200529. Corresponding author Daniel Espinosa S aez can be contacted at: [email protected] For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: [email protected] Innovation in sharing economy 619