Interorganizational collaboration in CBME: Perspective of SMEs

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UNIVERSITY OF EASTERN FINLAND Faculty of Social Sciences and Business Studies Business School

Interorganizational collaboration in CBME:

Perspective of SMEs

Master's Thesis, Innovation Management Tiiu Turunen, 306119

June 7, 2021

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Abstract

UNIVERSITY OF EASTERN FINLAND

Faculty

Faculty of Social Sciences and Business Studies

Department

Business School

Author

Tiiu Turunen

Supervisor

Ville-Veikko Piispanen

Title

Interorganizational collaboration in CBME: Perspective of SMEs

Major

Innovation management

Level

Master’s thesis

Date

7/6/2021

Number of pages

63 (2)

Abstract

The purpose of this study is to examine how SMEs are experimenting circular business models in collaboration with external partners. Finland’s government has committed Finland to be carbon neutral by 2035. Circular economy is perceived as the foundation to achieve this goal of carbon neutrality, strengthen the export-led economy and employment. In order to achieve carbon neutral circular economy, it is acknowledged needing a holistic change in societal decision making and planning. Although the prior voluntary implemented changes in company, household and consumer behaviours and attitudes have been recognized, more in-depth changes are still needed.

Regeneration of operational models and collaboration between various actors is emphasized to further circular economy.

Based on the conducted literature review, a research gap related to the need to redefine with who and how companies distribute value, and the changing role of network has been acknowledged. In this research, the prior literature of circular business models, circular business model experimentation and collaboration in circular economy is combined as the foundation for this work. Empirical research aims to gather information on the experiences of SMEs in testing circular economy business models in collaboration with partners, which aims to be integrated with previous research.

The qualitative research methodology approach is selected based on the research interest as there is noted to be relatively little amount prior research about the topic. The chosen research strategy is an extensive case study due its ability to describe complex business problems in practical and vivid format. The research is using semi-structured interview as a data collection method, which is chosen due its theory driven nature. Five in-depth interviews are conducted among Finnish SMEs operating on textile industry. By the set terms for the sampling, interviewed companies are identified to have sustainable value base based on their communication.

Based on the literature review, and conducted empirical research, circular business model experimentation in collaboration could be considered rather rare among SMEs. This research shows that experimenting companies are seen focusing on the feasibility and desirability of the circular business models. The circular economy business model experimentation is experienced to be about learning to tolerate uncertainty whereas social and cultural drivers are identified as supporting factors for circular business model experimentation. The results of this study show the conflict between the expected flexibility in circular business model experimentation in relations to the importance of contracting when working in collaboration relationship. The challenge of early adapter has been related, based on this research, to arisen motivation among CE actors to raise awareness among other actors and consumers to create more desirability for the proven models.

Key words

circular economy, circular business model, experimentation, SMEs, textile industry

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Tiivistelmä

ITÄ-SUOMEN YLIOPISTO

Tiedekunta

Yhteiskuntatieteiden ja kauppatieteiden tiedekunta

Yksikkö

Kauppatieteiden laitos

Tekijä

Tiiu Turunen

Ohjaaja

Ville-Veikko Piispanen

Työn nimi (suomeksi)

Organisaatioiden välinen yhteistyö kiertotalouden liiketoimintamallien testauksessa: Pk- yritysten näkökulma

Pääaine

Innovaatiojohtaminen

Työn laji

Pro gradu

Aika

7/6/2021

Sivuja

63 (2)

Tiivistelmä

Tämän tutkimuksen tarkoituksena on tutkia, kuinka pk-yritykset kokeilevat kiertotalousmalleja yhteistyössä ulkopuolisten kumppaniensa kanssa. Suomen nykyinen hallitus on sitoutunut Suomen olevan hiilineutraali vuoteen 2035 mennessä. Kiertotalouden koetaan olevan perusta hiilineutraaliustavoitteen saavuttamiselle, sekä vientivetoisen talouden ja työllisyyden vahvistamiselle. Hiilineutraalin kiertotalouden saavuttamiseksi tullaan tarvitsemaan kokonaisvaltaista muutosta yhteiskunnallisessa päätöksenteossa ja suunnittelussa. Vaikka aikaisemmat vapaaehtoiseesti toteutetut muutokset yritysten, kotitalouksien ja kuluttajien käyttäytymisessä ja asenteissa on tunnustettu, perusteellisempia muutoksia tarvitaan yhä. Toimintamallien uudistusta sekä eri toimijoiden välistä yhteistyötä korostetaan kiertotalouden edistämistä tukevina muutostoimina.

Kirjallisuuskatsauksen perusteella tutkimusaukon on havaittu liittyvän tarpeeseen määritellä uudelleen kenen kanssa ja miten yritykset jakavat arvoa, ja kuina verkon muuttuva rooli voidaan nykypäivänä käsittää. Tässä tutkimuksessa yhdistän aiemman kirjallisuuden kiertotalousmalleista, kiertotalousmallien kokeilusta ja yhteistyöstä kiertotaloudessa. Empiirinen tutkimuksen avulla pyritään keräämään tietoa pk-toimijoiden kokemuksista kiertotalouden liiketoimintamallien testaamisesta yhteistyössä kumppanien kanssa, joka pyritään yhdistämään aikaisempaan tutkimukseen.

Laadullinen tutkimusmenetelmä valittiin tutkimuksen aiheen perusteella, sillä aikaisempaa tutkimustietoa aiheesta on havaittu olevan suhteellisen vähän. Valittu tutkimusstrategia on laaja tapaustutkimus, sillä kyseisen strategian tiedetään voivan kuvata monimutkaisia liiketoimintaongelmia käytännöllisessä ja elävässä muodossa.

Tutkimuksessa käytettiin tiedonkeruumenetelmänä teemahaastattelua, joka valittiin sen teoriaohjaavan luonteen vuoksi. Viisi syvähaastattelua tehtiin suomalaisten tekstiiliteollisuudessa toimivien pk-yritysten keskuudessa.

Haastateltavat yritykset painottivat viestinnässään kestävää arvopohjaansa, jonka vuoksi ne valittiin tutkimuksen otantaan.

Kirjallisuuskatsauksen ja tehdyn empiirisen tutkimuksen perusteella kiertotalouden liiketoimintamallien kokeilua voidaan pitää pk-yritysten keskuudessa melko harvinaisena. Tutkimuksen perusteella kokeilevien yritysten havaittiin keskittyvän kiertotalouden liiketoimintamallien soveltuvuuteen sekä vetovoimaisuuteen. Kiertotalouden liiketoimintamallien koettiin käsittelevän epävarmuuden sietämistä, kun taas sosiaaliset ja kulttuuriset ajurit tunnistettiin yhteistä kokeilua tukeviksi tekijöiksi. Tutkimuksen tulokset osoittavat ristiriidan kiertotalouden liiketoimintamallien kokeilulta odotetun joustavuuden suhteessa sopimusten merkitykseen yhteistyösuhteessa.

Edelläkävijyyden haaste liitettiin tutkimuksen perusteella kiertotaloustoimijoiden lisääntyneeseen motivaatioon tietoisuuden lisäämisessä muiden toimijoiden ja kuluttajien keskuudessa, jonka havaittiin lisäävän kokeiltujen liiketoimintamallien houkuttelevuutta.

Avainsanat

kiertotalous, liiketoimintamalli, kokeilu, pk-yritys, tekstiiliteollisuus

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Until today, the linear “take, make, dispose” economic model has been the core of industrial development. Increased pressure on resource and supply chain risks have woken business leaders and policy makers to rethink the resource usage (Ellen MacArthur Foundation, 2015). Circular economy (CE) is aiming for finite resource using and defined as regenerative system which aim is to minimize the resource leakage by slowing, narrowing, and closing material loops (Ellen MacArthur Foundation, 2015; Geissdoerfer et al., 2017). CE thinking requires companies to make changes to their business models;

how they create and deliver value to their customers. These changes are known to be driving the companies from firm-centric to network-centric operational logic (Pieroni, McAloone &Pigosso, 2019).

Finland’s government has committed Finland to be carbon neutral by 2035. The commitment is a supportive act towards the European Commission's Green Deal-program.

By taking innovative actions towards the carbon neutrality, it is noted to raise the wellbeing if citizens, to increase employment situation as well as economic vitality. Finland is considered needing considerable investments to improve competitiveness, to enable export revenues from high technology and reduce emissions. Companies, municipalities, and citizen are known taking climate friendly actions towards the carbon neutrality, which supporting government has acknowledged important (Valtioneuvosto, 2020). CE is perceived as the foundation to achieve the goals of carbon neutrality, strengthen the export- led economy and employment. It is also noted to be reducing natural resource usage and environmental impact. In order to achieve carbon neutral CE, it is perceived to need a holistic change in societal decision making and planning. Although the voluntary implemented changes in company, household and consumer behaviours and attitudes have been recognized, more in-depth changes are still needed. Regeneration of operational models and collaboration between various actors is emphasized as a way to further CE (Valtioneuvosto, 2021).

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Generally, business experimentation is acknowledged to have an important role when accelerating the transition towards CE (Aminoff & Pihlajamaa, 2020; Bocken, Schuit &

Kraaijenhagen, 2018c; Konietzko et al., 2020a). The aim of business experimentation is to improve and learn about business model innovation with low risk and resources through connective learning with stakeholders (Bocken et al., 2018c). Research has shown experimentation to be able to improve the action and decision-making process towards sustainability (Bocken et al., 2018c; Konietzko et al., 2020a). It is thought to be iterative and collaboration with partners is known to be expediting the set-up process (Bocken et al., 2018c).

Business experimentation has grown interest in the management literature during the past decade. Business model experimentation (BME) is acknowledged in prior research to be beneficial to create radical innovations and societal, economic, and environmental impact.

Research has brought forward the positive impact the experimentation is having internally in the organization caused by the support towards the experimented business model (Bocken & Snihurc, 2019). BME creates external traction. In order to companies to transition towards circular business models (CBM), they need to reorganise their systems.

They need to redefine with who and how they distribute value, and their own changing role in network (Bocken & Antikainen, 2018). When experimented in collaboration with partners, societal stakeholders, and customers, it can be co-developed to respond the mutual objectives and interests (Bocken & Snihurc, 2019). Konietzko et al. (2020a) have stated based on their research on circular business model experimentation (CBME), the network’s impact on what is prioritized in the experimentation process. The reason behind this idea is that the already existing network is that the experimentation is actionable and is seen produce fast results (Konietzko et al., 2020a). The prior research has emphasized the need for further research on the role of network and stakeholders in the experimentation process of CE business models (Bocken & Antikainen, 2018; Bocken & Snihur, 2020; Bocken et al., 2019; Konietzko et al., 2020a).

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1.2 The purpose of the study

Circular business models are gaining attraction among SMEs to move towards sustainable and competitive economy. Despite the acknowledged benefits and attraction, the models have pointed out for being difficult to implement to practice. Financial resources and technical skills presented to be barriers to these actors (García‐Quevedo, Jové‐Llopis &

Martínez‐Ros, 2020). Prior research has noted how important the role of business experimentation is when accelerating the transition towards CE (Aminoff & Pihlajamaa, 2020; Bocken, Schuit & Kraaijenhagen, 2018c; Konietzko et al., 2020a). The aim of BME is to learn about business models with minor risks and low resources. Experimentation has been proved to improve the action and decision-making process towards sustainability through connective learning with stakeholders (Bocken et al., 2018c; Konietzko et al., 2020a). In order the companies to be able to transition towards circular business models, they need to reorganise their current systems to enable circular business models. Research has identified a need to redefine with who and how companies distribute value, and the changing role of network (Bocken & Antikainen, 2018).

In this research, I was examining how SMEs are experimenting CBMs in collaboration with external partners. The research was executed in order to gain understanding about the experiments and to connect already existing research literature. Theoretical framework pointed out the importance of shared values and motives when planning collaboration.

Prior research is noted to be lacking research on the CBME process itself to gain understanding about the content and types of participants. Research is also acknowledged lacking descriptions about the role of network and stakeholders in the experimentation process of CBMs (Bocken & Antikainen, 2018; Bocken & Snihurc, 2019; Bocken et al., 2019; Konietzko et al., 2020a). As value capturing from the stakeholder point of view has been pointed out, the collaborative experimentation has not been acknowledged in prior research. The purpose of this study is to contribute to the existing research on how SMEs experiment circular business models together with their external network.

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Based on the purpose and identified research gap the set research question for this work is:

“How are organizations experimenting circular business models with external partners?”

Two sub-questions were used to emphasize the important features emerged from the literature and to present more in-depth understanding of the topic:

“What factors have been seen supporting the collaboration in CBME?”

“How CBME has been experienced among SMEs?”

The intended contribution is to help the research field gain more understanding on how SMEs collaborate with external partners from the empirical perspective by gathering new knowledge about the CBME process, types of participants and the collaboration contracting. The findings are presenting a description how SMEs are experiencing the CBME in collaboration in the context of textile industry. More in-depth understanding of the joint experimentation process and value delivery is needed (Bocken & Antikainen, 2018).

To answer my research questions, I have conducted a literature review considering topics on CE, BME, CBME and organizational collaboration. There is a research gap in the existing literature for CBME in collaboration, topic delimitations have been made to unite the literature beneficial for this specific research. Methodology of qualitative research was selected based on the conducted literature review and research interests. The chosen research strategy was an extensive case study. Five in-depth interviews were performed to Finnish SMEs, which were identified to be operating with CE models in textile industry.

Based on collected data from the interviews, a qualitative content analysis was conducted.

1.3 Key concepts of the study

The key concepts gathered for this thesis are CE, CBM, CBME and interorganizational collaboration. The concepts and definitions are important to understand the entirety of this research and are thus described briefly below.

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CE is a concept, which aims to keep products and materials in use as long as possible (Lacy, Long, & Spindler, 2020). The alternatives for lifetime extension are reducing, reusing, recycling, and recovering materials in production, distribution, and consumption processes (Kirchherr, Reike & Hekkert, 2017). As the material reaches the end of use, it is recycled back into the system to create a loop. The system aims to continuous flow of materials by rethinking and redesigning the economy in a way which would create zero-waste (Lacy, Long, & Spindler, 2020).

Business model is a tool or a framework explaining the company’s core logic behind the system of activities, part of the strategy. Business model is framed around three components: customer value proposition, value creation and delivery, and value capture.

Customer value proposition describes how the value is provided to the customers. Value creation and delivery is describing how value is created and what is the competitive advantage of the company. Value capture describes the revenue and profit generating. The framework aims for value exchange relationship with customers (Richardson, 2008;

Spencer, 2013). CBM is described to be a sustainable business model, including both environmental and economic value creation. Business logic is generating profit from iterative flow of reused product and materials over time. The product value is aimed to keep high by slowing and closing the resource loops (Guldmann & Huulgaard, 2020).

BME is a small-scale and cost-effective way to test a theory or hypotheses. By experimenting the business model, the organization can reduce the risk of the uncertainty (Osterwalder et al., 2015; Ries, 2011). The results will reveal the new business model’s desirability, feasibility, and viability (Konietzko et al., 2020a).

Interorganizational collaboration involves two or more companies working together to accomplish mutual goal. Collaboration is enabling the participants to get access and develop their resources and markets. It can take many forms from informal to formal partnerships (Reuer, Matusik & Jones, 2019).

1.4 Structure of the thesis

Chapter 2 introduces the relevant literature related to CBM, the CBME and collaboration between external actors. The chapter is divided to five subchapters which are building up

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the theory based used for this thesis and introducing the reader to the theoretical concepts.

The theory is based on the concepts of CE, CBM, experimentation, CBME and finally, CBME in collaboration with external partners.

Chapter 3 presents and argues for the used methodological approach for this study. The chapter will introduce the chosen methodology of qualitative research design. The chosen semi-structured interviewing as a method for data collection and qualitative content analysis process is presented.

Chapter 4 present the findings made based on the empirical research. The chapter is introducing the findings based on the conducted qualitative content analysis in relations to the presented research questions. The chapter is explaining what type of CBME is currently taking place, supporting factors for the experimentation and how the experimentation has been experimented.

Chapter 5 discloses and introduced the conclusions of this study by bringing the empirical and theoretical discussion together. The chapter offers managerial implication, discusses the limitations of the study and provides outlook for future study.

1.5 The context of textile industry

This subchapter introduces textile industry as a CE actor and is validating the chosen industry connected to the research topic. The chapter is presenting some of the drivers and barriers of the industry in relations to transitioning towards CE.

Finland is calculated creating annually 71 million kilograms of textile waste (Dahlbo et al., 2015). At the same time, textile industry is known to be one of the most polluting industries in the world for years now (Angelova, 2020; Shirvanimoghaddam et all., 2020). In 2019, the textile and clothing industry’s turnover was announced to be 162 billion euros on European Union level (Figure 1) (EURATEX, 2020). Despite the corona, textile industry’s turnover was seen in 2020 to increase by 2,4 % in Finland (SVT, 2020). Industry acknowledged having negative impact on the environment due the consumption of large amount of resources, including water, chemicals, and natural and synthetic fibres. The large amounts of used resources have noted to be reflecting to huge amounts of the created waste

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annually. The industry is known having a great impact on global scale well, as the fibres can travel between continents before the final product is finished (Sillanpää & Ncibi, 2019).

Figure 1. Textile industries turnover shared per sector in 2019 (EURATEX, 2020, 14).

Due the high volumes of textile waste produced around the globe, reuse and recycle of the materials can be sustainable solution to reduce the produced waste, usage of virgin materials and consumption of energy (Shirvanimoghaddam et al., 2020). In March 2020, the European Commission adopted a new CE action plan, which includes an EU strategy for textiles. The action plan is seen driving innovation and new business models within the sector, as the strategy is supporting product-as-service model, circular material and production processes and international cooperation. European Commission has demanded textile waste collection to be mandatory latest by 2025 (European Commission, 2020b).

Industry is perceived to be facing technical, financial, and infrastructural barriers. CE is often seen as a way to recycle textiles. Recycling is considered as the worst way to recover the value of the textile and clothing products as the item being furthest from the use stage.

The recovery process of recycled items is pointed to be using more resources than reuse,

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refurbishing and other CE strategies. The recycling of mixed fibres, cotton, and polyester is still technically impossible which leads the lower quality and performance of the recycled material. Investment-vice the recycling and new technology needed is often seen risky. In addition, waste collection and sorting systems have noted not to be on the needed level to support the recycling processes efficiently. Other CE strategies as a solution is seen to enable the items not to end up to the recycling loop, but obtaining the quality by maintenance, reuse, redistribution, and refurbishment. These actions will need design and development of the products to fit to the cycle (Angelova, 2020).

As conducting a study on how standards for transitioning towards CE create interorganizational collaboration in context of textile industry, Fischer and Pascucci (2017) made the realization that companies experimenting in collaboration with interorganizational partners are not stating expected outputs for the project but rather set the goal for general material and process improvements towards CE. Researchers identified two pathways when transitioning to CE and managing the material flows: Status Quo arrangement (SQ) and Products as a Service arrangement (PAS). SQ contracts were acknowledged to aim for long lasting collaboration. The aim is to introduce new industry quality standards and up-cycling by collecting the post-consumer textiles, whereas the PAS contracts aimed for sharing the decision and property rights aiming for more independent collaboration turning the material flows to mutual metabolism between the buyers and suppliers by leasing the items (Fischer & Pascucci, 2017).

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2 THEORETICAL BACKGROUND

This chapter presents CE in BME context based on prior research. It is constructed based on the relevant themes related to the research question. The first subchapter introduces the concept of CE following by acknowledged circular business models. The chapter will proceed by introducing the BME research and finally focusing on academic research on the CBME and CBME in collaboration.

2.1 Circular economy

CE is known as an antonym for linear economy. The concept of linear economy is used to describe the natural resources flow into waste through production. It is seen to be diminishing the nature by removing and reducing natural capital and value (Murray, Skene

& Haynes, 2017). Geissdoerfer, et al. (2017) have defined the CE as regenerative system, which tends to minimize the resource leakage by slowing, closing, and narrowing material and energy loops. The resources are seen restored by design, maintenance, repair, reuse, remanufacturing, refurbishing, and recycling actions (Geissdoerfer, et al. 2017). The literature is emphasizing that the model is not only focusing on recycling of the resources but also redesigning the manufacturing and service supply. This is not done only to improve resource utilization but also to achieve more value (Kirchherr et al., 2017). The ambition of the concept is economic prosperity through environmental quality as the sustainable development is often seen secondary. Circularity is thought be achieved with novel business models and responsible consumers (Kirchherr et al., 2017).

CE is known to be operating in micro (company), meso (eco-industrial park) and macro (national) levels. China has been known as one of the first nations to implement the CE to their legislation as means of reducing, reusing, and recycling influencing all their business processes. Also, European Union and multiple NGO’s, such as Ellen Macarthur Foundation, have started to acknowledge and research the benefits of the CE (Kirchherr et al., 2017; Murray, Skene & Haynes, 2017). EU Green Deal published in March 2020 a new CE action plan where it was noted focusing on the production and consumer behaviour.

The plan is focusing to keep the used resources in EU economy as long as possible, which is seen emphasizing the CE (European Commission, 2020a).

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Research field has suggested that CE research should be focusing in future research on combining the latest ecological information to the naturalistic economical models (Murray et al., 2017). The further research from consumer perspective in relations to their contribution to CE has been emphasized (Kirchherr et al., 2017). CE has gained criticism about not including the social dimension to the model, whereas it is seen to be important part of the three pillars of sustainability (economic, environmental, and social). It has also been criticized for being over-simplistic and having unintended consequences. Due the risen critic, factors such as, ecological efficiency and reductionist thinking are noted to be important to take into consideration in the design process (Murray et al., 2017).

2.2 Circular business model

Simplistically the business model is a description how company is doing business. Business model framework can be defined based on three components, the value proposition, the value creation and delivery system, and value capture. The value proposition is describing what the company is offering to its customers and why the customers are ready to pay for it. The value creation and delivery system are explaining how and why the company is developing and delivering value to its customers. The value capturing defines how the company is regenerating revenue and profit (Doganova & Eyquem-Renault, 2009). Well- thought business model is considered to give defined and organized overall picture of the company and its operations. This is seen to help companies to execute the strategy (Richardson, 2008). From the design perspective, these three elements can be described as desirable, feasible and viable. Desirability is describing how desirable the value proposition is to the target users and investors. Feasibility is clarifying ways to organize the needed activities and resources to create and deliver value. Viability is declaring how the business model can regenerate revenue to sustain the value creation and delivery process. Konietzko et al. (2020a) have used these above-mentioned properties in their research work related to experimentation, as the elements can be tested and are thus suitable for research purposes (Konietzko et al., 2020a).

CBM is described to be a sustainable business model which includes both environmental and economic value creation. Business logic is shifted from traditional one-time sales of goods to generating profit from iterative flow of reused product and materials over time.

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Thus, the product value is aimed to keep as high as possible by slowing and closing the resource loops (Guldmann & Huulgaard, 2020). CBMs are argued to differ from conventional ones by needing more than one model (plural) to create value for business and the stakeholders (Pedersen, Earley & Andersen, 2019). Pedersen et al. (2019) have argued organizations struggle to create economically viable models. Virgin material prices being low and the inability to acknowledge the CE products’ recycling value are seen currently to be the main barriers for the CBMs to work.

Although the importance of circular business models has been acknowledged, the existing literature is known to lack clarity of the theoretical conceptualisation and position in economic and operation literature (Geissdoerfer et al. 2020). Research field has been seen presenting slightly differing definitions for circular business models. Frishammar and Parida (2019, 8) have defined the circular business model based on prior literature emphasizing the partnership aspect:

“…one in which a focal company, together with partners, uses innovation to create, capture, and deliver value to improve resource efficiency by

extending the lifespan of products and parts, thereby realizing environmental, social, and economic benefits.”

Whereas Geissdoerfer et al. (2020, 7) (Figure 2) have defined the circular business model based on the existing literature stressing the usage of resources:

“…business models which are cycling extending, intensifying, and/or dematerializing material and energy loops to reduce the resource inputs

into and the waste and the emission leakage out of an organizational system. This comprises recycling measures (cycling), use phase extensions (extending), a more intense use phase (intensifying), and the substitution of

products by service and software solutions (dematerializing).”

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Figure 2. The Circular economy (Geissdoerfer et al., 2020, 4).

To differentiate the linear from CE models, literature has utilized three different designs and business model strategies to describe the cycle of the resources: the slowing, closing, and narrowing resource loops (Figure 3). Slowing and narrowing loops aim both for resource reductions but whereas slowing flow is slowing the recycling of the resources, narrowing flow accepts the natural speed of flow. Narrowing flow is not including service loops, thus not seen as part of cycling systems. Closing loop tends to reuse the material through recycle (Bockent et al. 2016).

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Figure 3. Categorization of resource use by narrowing and closing the loop (Bocken et al., 2016, 309).

Design strategies for slowing the resource flow are extending the utilization period of the product, helping to reduce the need of resource usage. By designing long-life products, the organization pays attention to the durability, reliability, and timelessness of the products.

The other major design aspect is the product life extension. By designing product life extension, the organization takes notice on factors such as the maintenance, repairment, upgradability and standardization. The closed cycle is utilizing three different product design perspectives: biological cycle, technological cycle and design for disassembly and reassembly. Biological cycle products are designed for consumption and biodegrade to start a new cycle. Technical cycle is creating products which are recycling the materials for new products repeatedly, avoiding material flow through downcycling. Design for disassembly and reassembly is combining both technical and biological cycles to reassemble and recycle parts for another cycles (Bocken et al., 2016).

Bocken et al. (2016) have identified 4 CBM strategies for slowing and 2 for closing the loop based on prior research: The access and performance, extending product value, classic long-life model, and sufficiency models which are described to be slowing the loop, and the extending resource value and industrial symbiosis models which are closing the loop.

Based on Bocken et al.’s (2016) and Geissdoerfers et al.’s (2018) prior research,

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Geissdoerfer et al. (2020) have compressed the finding into four generic strategies for CBM: cycling, extending, intensifying, and dematerializing. Cycling means the reused, remanufactured, refurbished, and recycled materials and energy. It is extending the resource lifecycle as limiting the energy intake and waste output through technical cycle and is seen to be suitable for product-service systems. From the value proposition point of view the most important element is take-backs which needs collaboration in value chain and reverse manufacturing processes. Value is captured as the resources are turned into new forms of value, minimizing material acquisition costs, and creating additional revenues from the final products. Value is created and deliver through take-back systems and collaboration. Extending resource loops means ways to extend the product usage phase through design process. It aims for reducing the need for new product production. Value proposition is earned thought long-life products. The value is created and deliver by created services around the lifecycle of the product which are often related to long customer relationships (Geissdoerfer et al., 2020).

Intensifying means extending use phase of the product by utilizing share platforms as the value proposition. The strategy can lengthen the lifetime of the product through regular maintenance and updates of the products. Value is created by long lasting customer relationships and servitization. The environmental benefit is reducing waste and new product acquisitions. Dematerialization refers to product-service systems, product utility without ownership of the product through service and software solutions. Value is captured and delivered through slow and close loop capabilities and collaboration. The key elements for the value capturing are regular revenue streams, increased profit margins and new pricing mechanisms (Geissdoerfer et al., 2020). Internet of Things (IoT), remote locating and operating systems, is recognised to be supporting the servitization related CBMs’ by improving in-use and post-use products tracking as well as helping to monitor the maintenance needs or remaining lifetime of products. Companies are known to be currently facing implementation problems of Iot due the data management and adaptability problems considering the fast development phase of Iot technology (Ingemarsdotter, Jamsin &

Balkenende, 2020).

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Pedersen et al. (2019) have argued talking about CBM being misleading, as the CE solutions often demand collaboration between multiple parties with interconnected business models. They suggest future research to give more emphasis on different variations of business models in order to bring the CE more present. Geissdoerfer et al.

(2020) have highlighted in their research the nascent approach of ecosystem view in multi- stakeholder and network cases. Networks are generally considered to be more member stable and risky in literature. Networking is loose connection between the organizations to change information between the parties and described as a cooperation. Members can come and go without disturbing the linkages between the participants. Networks describe closer connection with more formal relationship and tend to have mutual goals and planning, thus comparable to coordination relationships. Network structures are often created by old competitors who joint their functions and goals. It relies strongly on its members and can be comparable with collaboration relationship (Brown & Keast, 2003). As multiple stakeholders join their forces as multi-business view, it leads to a value network. As value network and business model portfolio perspectives are combined, it can be described with ecosystem view. Ecosystem view can be seen to combine multi-stakeholder views into multi-business models. It could go beyond the regular corporate strategy thinking combined with industry analysis elements to collaborative and under investigated competitive elements (Geissdoerfer et al., 2020). Prior literature is not providing information how CBMs are experimented in collaboration based on the conducted literature review. With this study, I want to extend the understanding of how CBMs can be co-experimented and what is the value delivered to the participants as more in-depth understanding of the topic is acknowledged to be needed (Bocken & Antikainen, 2018).

2.3 Business model experimentation

BME is known to be a small-scale and cost-effective way for companies to test a theory or hypotheses. By experimenting the business model, the organization can reduce the risk of the uncertainty as it allows the investors and entrepreneurs to evaluate and commercialize the project without investing too much of the resources available (Bocken & Snihur, 2020;

Kerr et al., 2014; Osterwalder et al., 2015; Ries, 2011). It is also known to enhance stakeholder engagement and to promote collective learning (Bocken & Snihur, 2020). By

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experimenting with the novel business model’s companies can learn about the desirability, feasibility, and viability of the models (Konietzko et al., 2020a). Variation of published tools and methods have been created to help the experimentation process (Bocken et al., 2017).

Chesbrough (2010) has listed three key parts of the BME process: effective experimentation, effectuation, and change leadership. The participants should be provided with adequate resources, such as time and authority to advance the project. It is important for the organizations to select right people for the project from the skill and experience wise. BME is known for needing, on the organizational level, communication between different departments, such as operations, engineering, marketing, sales, and finance. The management is seen to be in key roles on BME as they hold credibility and decision-making power (Brown, Bocken & Balkenende, 2019).

Traditionally middle management, which is leading the functionalities on the organization, is acknowledged to have limited amount of decision-making power. This can make them in many cases unsuitable for the position to lead the experimentation. In many cases, in smaller companies, the CEO might be the right person to manage the change and the BME.

In these cases, something to consider is that the CEO might be too familiar and comfortable with the current business models to emphasize the experimenting. In larger organizations case, the general managers tend to have the authority needed for the decision making, but they are often rotated from position to another in every 2-3 years. This is not considered to be supporting a long-lasting experimenting process with the data interpretation and analysis processes. It is important to note that during the process, the organization needs to keep the normal operations running as well. The experimentation processes can be seen challenging for the organization, as they need to think the timing of resources shifting which can be seen to have career effects on the managerial positions as well. To ensure effective governance of the business model experimenting, the organization are been advised to address these leadership problems (Chesbrough, 2010; Bocken et al., 2017). When researched large organization’s BME, organizations have been noticed struggling from the team dynamics and stakeholder management perspective. Complex organization must use time for administrative duties and teams are seen struggling to control parallel project. The

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prior research has also made an observation that although the business models experimented would not be novel to the industry, it is acknowledged to take a major business model transformation to adopt the model for the focal company (Bocken et al., 2017).

Research has found the metrics setting important for the testing to keep the focus on the effort and intended outcome. Metrics can be qualitative as well as quantitative and should be chosen based on the novelty of the business model (Konietzko et al., 2020a). The empirical research has acknowledged that every experimentation case is different, thus the metrics should be chosen for the specific case in mind. As an example, Heikkilä et al.

(2015) have compiled repository of metrics including eight perspectives: customer value, service, technology, organization (internal/external), finance, value exchange, information exchange, and process alignment (internal/external). Each perspective is including separated themes such as created customer value or value exchange between partners. They have suggested the organizations to choose the metrics from each category to combine a comprehensive understanding of the experiment results. Based on the conducted research by choosing clear and assimilated metrics, management is seen to be able to keep the strategic focus during the experimenting process and to evaluate the success rate of the experimentation. Metrics are seen helping the viability and feasibility strategic planning during the BME (Heikkilä et al., 2015).

2.4 Circular business model experimentation

Whereas BME tends to test the value proposition, the CBME presents a clear environmental aspect to the hypothesis tested (Bocken & Antikainen, 2018). For experimentation to work in sustainable environment, research has emphasized the importance of the design of circular value proposition, reframing the meaning of resources, the mapping of minimum viable circular ecosystem, prototyping the circular ecosystem assets, test the minimum viable circular ecosystem, and gaining customer commitment (Konietzko, Bocken, & Hultink, 2020b). Organizations can be experimenting with four circular strategies; by slowing, closing, narrowing, or regenerating resource flows with their business activities (Bocken and Antikainen cited by Konietzko et al., 2020a;

Konietzko et al. as cited by Konietzko et al., 2020a). These are strategies which support

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the life extension and provide products which will last (slowing), will reduce the resource usage (narrowing), close material loops by utilizing recycling (closing) and use renewable energy, non-toxic materials etc. (regenerate) (Bocken & Antikainen, 2018; Konietzko et al. as cited in Konietzko et al., 2020a).

CBME is considered rather new topic in the literature. It is described to have fast-paced learning cycle and it is seen to be more iterative compared to piloting (Bocken &

Antikainen, 2018). Piloting is emphasized for forcing the organization to consider during the process all three aspects of the business model: desirability, feasibility and viability (Baldassarre et al., 2020). Experimentation process can be including tools such as A/B split tests, focus groups or paper versions of business models. These experimentation processes will be evaluating the possible business model transformation and are often followed by piloting process. Research has emphasized an optimal experimentation process to be evaluating the sustainability, circularity as well as customer and business values (Bocken

& Antikainen, 2018).

The existing approaches for CBME have found inspiration from science (Lean startup), intuitive experimentation (Effectuation), design (Design thinking) or business literature (Circular business experimentation cycle) (Bocken & Antikainen, 2018). The Lean Startup is currently known to be one of the most used approaches for BME (Felin et al., 2020). It is a collection of methods, which are allowing the entrepreneur to test their ventures in a cost-effective manner. The entrepreneurial goal is to make implicit assumptions on how the venture and market are working together. The assumptions are tested in a learning cycle called the build-measure-learn -loop (Harms, 2015). The experimentation process starts with value hypothesis where is meant to clarify whether the business model is creating value for the customer. Conducted growth hypothesis defines how the business model would be discovered by the customers (Ries, 2011, 61). By testing their assumptions, entrepreneur can find how the new venture would succeed on the market (Harms, 2015).

To start the build- phase, organization needs to create a minimum viable product (MVP).

MVP is created with minimum effort and development time. While entering the measurement phase, it is important to observe if the development work is leading to progress. Based on the measurement phase, organization can create innovation accounting

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and learning stones to complete the cycle. The final step of the cycle is called pivot, which means that organization must make decision whether to continue with their original hypothesis or change something in the experimentation process (Ries, 2011). The approach has drawn critique for being created as scientific approach without following the actual hypothesis development process and promoting incremental experimentation (Felin et al., 2020).

Effectuation is a theory of entrepreneurship describing a way the expert entrepreneurs develop successful projects. Based on the theory, entrepreneur starts with given set of means (bird-in-the hand principle): what they find important and, who and what they know.

Theory is suggesting entrepreneurs to follow four principles: to invest an amount of money that you are ready to lose (the affordable-loss principle), to seek strategic alliances to provide commitment (the crazy-quilt principle), value capturing from unexpected situations (the lemonade principle) and to build a protective network to secure the future (the pilot-in-the-plane principle). The first two principles are seen to follow the logic of The Lean Startup approach, as the goal is to launch the project with small direct payments, which are building systematically growing commitment to the business model. The ability to capture value from unexpected situations is seen describing the messy nature of the BME (Konietzko et al., 2020a; Sarasvathy, 2009).

Design thinking is described to have five core characteristics: a human-centred approach, a strong integration of experimenting with artefacts, collaboration in multidisciplinary teams, an integrative and holistic view on complex problems, and a characteristic six-step process. The six-step process includes the steps: understand, observe, define, ideate, prototype, and test (Geissdoerfer, Bocken & Hultink, 2016). The first step, understanding, refers to understanding customers and users’ mind-sets. The designer can identify possible issues customers run into by observing the users. As defining the problem or issue, the designer is identifying specific issues before starting to create the solutions in the ideating phase (Clarke, 2019). The prototyping is described as a low effort conceptualizing of the early idea of the experimented model (Geissdoerfer et al., 2016). The testing takes part with intended users to gain feedback (Clarke, 2019). The process is described to be iterative

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and aiming for rapid testing for multiple models to achieve the optimal solution. Method is created for developing innovative solutions (Geissdoerfer et al., 2016).

The Circular Business Experiment cycle includes six steps: purpose, value proposition experiment, value deliver experiment, value creation experiment, value capture experiment and field experiment. Compared to the Lean startup, Circular business experimentation cycle does not have to start from the value proposition. This process is also described to be iterative, and companies can go back and forth with the steps. The process is usually started by defining purpose or value proposition. After defining sustainable purpose, company can start to think about the societal and environmental value propositions. The value proposition experimentation is found to be reducing the risk of new ways to create revenue as approaching new target groups. Value delivery experiment is tested in relation to customers to see how they will accept the new business model. Value creation experiments are implemented with internal and external stakeholders to create joint consensus about the collaboration and resource usage. By joined experimentation the company can seek external validation and business model that works for all the parties. Value capture experiments are about beside cost and revenue creation, sustainable and environmental impact. Finally, the field experiments are combining the created assumptions and prior experiments. The prior research on the model has shown it to be considered as time and money consuming. The approach is also seen lacking ways to analyse the environmental and societal value creation (Bocken et al., 2018c).

These above mentioned most known approaches for CBME; Effectuation, Lean Startup, Design thinking and Circular business experimentation cycle, are not seen emphasizing the role of interorganizational collaboration. Lean Startup approach and Circular business experiment cycle are described to be structured guides for business as the other approaches are seen to be more unstructured (Bocken & Antikainen, 2018). Circular business model cycle is seen taking into consideration the value capturing from the stakeholder point of view, but it is not acknowledging the collaborative experimentation. The experimentation process is often described to be messy and dependent on the participants – entrepreneurs, managers, or designers – effectual logic and behaviour. This meaning, the participants tend to make decision what to test and conclude and how based on their prior knowledge on the

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subject, what they find important, and whom they know (Sarasvathy cited by Konietzko et al., 2020a). For the experimentation process, it is important for the participant to understand the leveraging factors on the process, such as the presumptions about the test and role of the people participating to the examination. By acknowledging the factors, participants can try to use these observations to compose stronger teams and prioritize the tested assumptions. In circular business model testing, this means the level of circular orientation and the network of supporting stakeholders (Konietzko et al., 2020a).

2.5 Interorganizational collaboration in CBME

To understand the collaborative relationship in experimentation, we must first understand some of the differences between different relationship types. The different types of relationships between organizations can be defined with Brown and Keast’s (2003) 3C model, which includes cooperation, coordination, and collaboration. In the model cooperation is described as short-term relationship where participants are sharing information, space or referrals but not forming mutual goals. Communication is often informal. Coordination is known to have higher level of commitment. It is including shared strategy, which requires information and resource sharing, and joint decision-making.

Coordination relationship is known to be needed and established when organizations need alignment. Collaboration is thought to be from these three relationships the most stable and long-term solution. To create this tight relationship, it needs planning and defined communication channels between multiple departments. Collaboration process is taking more time as the relationship needs high level of trust between the members. This type of relationship is often dealing with complex social dilemmas, it is important for the parties to have mutual goal and sense of working together (Brown and Keast, 2003). The above- mentioned relationship types are considered to be foundation to network relations. This thesis is focusing on the collaboration relationship due to its level of commitment and social dilemma dealing nature.

Why do organizations collaborate then? Research has presented the motivation and mind- set for CE as a key factor for collaboration. Shared values, such as sustainability and sense of responsibility, organization culture and capabilities are seen as supporting factors (Brown et al., 2019; Konietzko, Bocken, & Hultink, 2020b). Motives, intrinsic and

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extrinsic, for transitioning towards more sustainable business models are seen to arise from both personal and organizational levels and are perceived to be acting as triggers for collaboration. As the personal characteristics are seen important, also enthusiasm and persistency are emphasized as important factors for the experimentation (Brown et al., 2019). The identified motives for CBME collaboration are resource dependency, losing potential market share or competitiveness, finding suitable context to experiment and to operationalize circular business model (Aminoff, Valkokari & Kettunen, 2016; Brown et al., 2019). Research has also emphasized the importance of value creation experiments to create joint-consensus and to get pass prejudices when working together with stakeholders.

Experimentation with external stakeholders is known to intense the engagement with external and internal stakeholders and speeding up the start of the experimentation process (Bocken et al., 2018c). Early commitment and buy-ins from potential partners are considered important for the project proposal to be pursued further (Konietzko et al, 2020b).

Research has highlighted the importance of shared values when selecting possible partners for the collaboration as the lack of shared values is known to be causing conflicts between the participants, slowing down the progress and lower engagement level (Konietzko et al, 2020b). In addition, communication of the organization’s vision when engaging with external partners is been stressed. Alignment of individual and shared interests can help the partners to focus on the shared vision. In cases where collaboration parties have been able established a shared vision, the mutual goal and strategy setting have been noted to be easier to establish. To accomplish this, the collaboration often needs co-creative and organized processes (Brown et al., 2019; Konietzko et al, 2020b). Value creation experiments are perceived as a way to find joint consensus about the goal and to get pass possible prejudices when working together with stakeholders (Bocken et al., 2018c).

Trust is been emphasized as an essential part of the collaboration especially when talking about inter-organizational collaboration (Konietzko et al, 2020b). It is achieved by both formal and informal communication while created by fulfilling obligations, following expectations, and acting fairly. Due the multiple stakeholders, collaboration contracting is perceived challenging. The roles of the participants are important to define and possibly

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redefine during the project. Misunderstandings about the roles can lead to possible overlaps or conflicts. Clear roles have also been noted preventing misplaced expectations (Brown et al., 2019; Konietzko et al, 2020b). Thus, the collaboration relationship is often requiring governance structure. Partners are needed to be evaluated as equals’ co creating assets and cannot be disciplined by each other (Konietzko et al, 2020b).

To understand the collaborative activities between organizations it is important to understand the drivers and barriers of circular oriented innovation (COI) (Table 1). The drivers and barriers can be divided into soft and hard dimensions, where soft are considered as social/cultural and institutional/regional, whereas hard are technical and market dimensions. The hard dimensions have been recognised to be important for the innovation design process whereas the soft dimensions are needed for the collaboration with stakeholders to operationalize the CMB’s (Brown et al., 2019).

Table 1: Hard and soft dimensions of the drivers and barriers related to COI (Brown et al., 2019, 5).

Research has perceived the BME to require more intense collaboration as the competition is known simultaneously been increasing due the soft cultural barriers. Organizations are known to aim often for fast wins before they are willing to start to change their corporate culture align with their partners due the competition setup (Brown et al., 2019). Based on Muzafer Sherif ‘s (1966) Realistic conflict theory, groups tend to create conflicts when they need to compete for resources (Sherif 1966 cited by Helkama et al., 2020). This tends to decrease the open innovativeness as knowledge and economical rewards want to be protected (Brown et al., 2019). To keep the participants committed and deliver expected contribution, the project needs to ensure fair value capture between the actors.

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Commitment to cooperation is also seen to be ensured through early mutual gains (Konietzko et al, 2020b).

The figure below (Figure 4) has been conducted based on the literature review to describe the starting points for collaborative CBME. It is illustrating the collaborated literature and used as a foundation for this research.

Figure 4. Starting points for collaborative CBME based on prior literature (Bocken et al., 2018c, Brown et al., 2019 and Konietzko et al., 2020b).

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3 METHODOLOGY

3.1 Methodological approach

I have chosen for this thesis qualitative research methodology approach based on the research interests (Eriksson & Kovalainen, 2016; Taylor, Bogdan & DeVault, 2016).

Qualitative business research is acknowledged to give for the researcher the opportunity to focus on the complexity of the phenomena in its contexts (Eriksson & Kovalainen, 2016).

Due the modest preliterate of the research topic, instead of collecting data to evaluate hypotheses or theories as in quantitative research, this work aims for understand the patterns and insights from the industry point of view. As the research questions are approaching the topic from the perspective of experiences to gain a holistic view, the quantitative methodology was not seen suitable for this work (Eriksson & Kovalainen, 2016; Taylor, Bogdan & DeVault, 2016). In my research, I have been connecting theories of CE, BME and collaboration with external partners, which have not been connected, in earlier literature. The research philosophy of this study is focusing on interpretivism.

Interpretivism is reflected in the work through an interpretive view. The research findings are interpreted based on the interviewed target groups point of view (Sirén & Pekkarinen, 2017). A lot of the data analysis was conducted through used language and shared meaning (Eriksson&Kovalainen, 2016).

The chosen research strategy is extensive case study. Case study was chosen due its ability to describe complex business problems in practical and vivid format. The objective of this study is to extend the prior theory (Eriksson, 2016). Case study research allows the researcher to observe the situation in its context, in this case textile industry. Researcher can choose to use either single or multiple units of study. The method allows researcher to look in depth at the topic of interest (Farquhar, 2012). Case studies have gained criticism due the lack of scientific precision. Those have also been criticized to be aiming to help managers and decision makers to achieve higher operational control over the businesses (Eriksson, 2016). As Humphrey and Scapens (1996, as cited by Eriksson 2016) have noted, this case study research is implemented in order to gain a better picture of chancing business practices in their social context.

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3.2 Data collection

Interviewing as a data collecting method was chosen to gain information about interviewees’ experiences and attitudes about collaborative experimenting (Gubrium &

Holstein, 2001). The research was using semi-structured interview with closed and open- ended questions, which was chosen due their theory driven nature and to provide additional information on the subject (Eriksson & Kovalainen, 2016). The method is known helping researchers to address complex topics and to collect comparable data (Wilson, 2013).

The data for this research was collected by conducting five semi-structured interviews. I chose semi-structured interviewing for the data collecting to gather information on the interviewee’s experiences, attitudes, and values towards the CBME in collaboration.

Qualitative interviews are in-depth, and the collected data perceived to be more theory driven and collaborative (Gubrium & Holstein, 2001). Business research tends to use interviews as a method of data collection as it is a fast way to collect information about experiences that cannot be found in published form. Semi-structured interviews are noted having more flexible structure, compared to structured or unstructured interviews, which is leaned more on themes, topics, and issues. This allows the interviewer to vary the wording or the order of the questions (Eriksson & Kovalainen, 2016). The method is combining predefined questions to open-ended exploratory of the topic.

The goal is to gather answers to the core topics as the conversation is allowing new topics or issues emerge. Semi-structured interview method is allowing new topics or issues emerge in the conversation. It is often used when prior information about the subject under inspection is limited and additional information on the subject is still needed. The pros of the method are that those can help the researcher address complex topics, make sure interviews will collect comparable data and help to redirect the conversation if needed (Wilson, 2013). The recognized cons are that the comparability of the data depend a lot on the interviewees and what sort of topics they raise up during the interview (Eriksson &

Kovalainen, 2016). The themes for the interview were assembled based on prior literature and research. The interviews focused on current business strategy, experimentation, and collaboration and to the collected experiments. Themes were addressed with each

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interviewee as appropriate to their case taken account, but the order of the questions could vary depending on the informant.

I was using purposeful sampling as choosing companies for the interviews (Eriksson &

Kovalainen, 2016) in order to get homogeneous cases for the data collection. Case companies were selected from the textile industry, based on their stated sustainable vision.

By the set terms for the sampling contacted companies were supposed to be working in textile industry, SME and be able to be identified as sustainable actors based on their communication. The interview requests were sent by email to the participants to enforce the voluntary participation to the interview and informed why they were contacted regarding this research (Eriksson & Kovalainen, 2016). Overall, thirty-three companies were contacted with interview requests. Five of these companies accepted the interview request.

Interviews as a data collection method are known to include both ethical and moral issues.

The ethical issues are present throughout the whole interview process from the interview design to analysis/reporting stages. Ethical questions are often considering the consent of the interviewees, confidentiality, and consequences of the results (Brinkmann & Kvale, 2018). The participants were introduced to the document of consent before the interviews, to explain the purpose of the study, the roles and identities of the participants, agreed procedures and confidentiality (Brinkmann & Kvale, 2018; Eriksson & Kovalainen, 2016).

Companies were asked for consent to use the company name at the thesis.

The interviews were executed with Microsoft Teams communication platform due the ongoing COVID-19 pandemic. By using the virtual interviews, the safety of the participants was able to be secured and possible contaminations to be avoided. Participants received the Teams invitation and the preliminary questions before the interview to be able to familiarize themselves with covered subjects. The interview language was chosen to be Finnish, due it was the mother tongue of all the participants. Interviews were recorder to be transcribed and interviewees (Table 2) were offered possibility to read and commend on the transcripts of their own interviews if needed.

Interorganizational collaboration in CBME: Perspective of SMEs