Circular Economy in Supply Chains

Introduction

This chapter aims to introduce the audience to the study, analysed in this dissertation. In the very first of this chapter, a brief introduction of the context of this research will be described (i.e. the current challenge of the manufacturing supply chain and how CE principles could contribute to supply chain sustainability and competitiveness). Then, it goes on with an exploration of the research gaps. In the end, this section defines the aims and objectives that are effective for addressing, also provides a guide to the subsequent chapter.

Theoretical Background of Research

Supply chain management (SCM) is defined as management of upstream and downstream relationships, where in the number of network entireties (i.e. supplier, carrier, manufacturer and retailer) collaborates to contribute to low-cost supply chain and superior customer service (Beamon, 1998; Lemay et al., 2017). Contradictorily, In modern days business, the management of business process has shifted in the context of SCM where the entities compete for inter-network rather than as members of supply chain network (Lambert and Enz, 2017). This contradiction is due to that, the challenge of resource scarcity caused by rising consumption of natural resources, consequent resource price volatility (Lieder and Rashid, 2015), shortened product life cycle, and growing manufacturing cost (Beamon, 1998). Analysis of literature indicates that, the manufacturing system, based on the linear supply chain is unquestionably unsustainable (Korhonen, Honkasalo and Seppälä, 2018; Reike, Vermeulen and Witjes, 2018). In the linear supply chain, virgin raw materials are extracted from mining companies and subsequently processed into final products, which are ultimately disposed into landfill, mostly with little or no recovery process of the products, components and embedded materials. For this supply chain model, the demand for raw material is continuously increasing as the increasing population. Since the dawn of industrialisation, the consumption of non-renewable resource is 1.7 times more than what earth can generate (Rathinamoorthy, 2018). If companies still operate in this economic model, the natural resource will be exhausted at some point of the future (Kirchherr, Reike and Hekkert, 2017). However, the linear production paradigm is not caused material scarcity. The most urgent problem is the negative environmental impact like the destruction of natural habitats and climate change (Ward, 2018). Thus, in more recently, companies are encouraged to optimise the value of in all aspects of "Triple bottom line". This encouragement comes from stricter legislation, increasing costs on waste disposal, raising customer awareness on environmental issues and deficient use of resources (Difrancesco and Huchzermeier 2016). Therefore, it is imperative to develop supply chains that are sustainable and profitable by taking the values of environments, societies and companies into consideration (Olugu and Wong, 2012). The concept of CE appears to provide opportunities to resolve the problems that existed in the linear supply chain. For two decades ago, academic researchers have already started to focus on the interrelationships between the environment and economy. The introduction of CE has attracted almost all attention of different parties, including society, government, industry and academia (Stahel and Reday-Mulvey, 1976). The term CE in the supply chain context is defined as an economic-industrial system, that utilises the 6Rs to reduces, repair, reuses, redesign, recovery, and recycles the wastes in the production and consumption process, and it operates at three levels, which are Macro level (nation) Meso level (eco-industrial-park) and micro-level(from companies to consumers). The CE is a method to improve the environment and economy and social equity simultaneously and sustainably (Kirchherr, Reike and Hekkert, 2017). The concept of CE is increasingly relevant to reverse logistics and closed-loop supply chain, which aims at reducing the environmental footprint and leaving disposal scarcely by optimising the value of disposed products (Govindan et al., 2016). The concept of CE is worthwhile satisfying the different value propositions of societies, environments and companies toward a prosperous and sustainable eco-economic system (Lieder and Rashid, 2015). Three groups' benefits will be satisfied by adopting the CE to address the mismatch between environment development and consequent environmental influence. For the companies, the CE can bring economic and competitive advantages through a particular pathway to grasp innovations and to eliminate the obstacles to sustainability (Ziegler, 2019); For example, the main CE innovation is mainly the material flow of reuse refurbish and recycling of disposed products, which respond to the increasing risks of price volatility, increasing challenges of production efficiency that are driven by returning products and increasing wastes caused by complexity of return products. Eventually, the prices of the product can be decreased, which in turn facilitates the consumption (Korhonen, Honkasalo and Seppala, 2017). For the societies, the implementation of CE can bring employment opportunities in the sectors of the reverse supply chain (Burger et al., 2019). For the environment, in the concept of CE, the biological wastes and substance wastes can be not only utilised as the maximum of its value within closed-loop industrial cycles but also re-entered back to nature without any harms (Baldassarre, 2019). Therefore, the concept of CE is supported by governmental bodies and industrial unions to achieve industrial symbiosis and industrial ecology (Domenech and Bahn-Walkowiak, 2019).

CE in the UK manufacturing sector

Vacho and Klassen (2010) suggested that, to infuse supply chain with CE practice will enhance the level of integration of supply chains including both reverse and forward supply chains. Beamon (1998) described that a supply chain is defined as an integrated manufacturing process that is formed by a series of distinct functional manufacturing processes. the reformation of supply chain concept is made up of some certain changes in manufacturing environment. Although there are many supply chains models like Lean supply chain model to guide the waste elimination. There are still plenty of wastes created by the manufacturing sector (González Chávez, C. A. et al, 2019). A research indicated that the manufacturing sector in the UK created approximately 15 million tonnes wastes between 2010 to 2017 (GOV, 2019). These wastes create huge amount of losses to companies (Agnolucci and Arvantiopoulos, 2019). The appearance of CE seems a method to fundamentally minimise the wastes and improve the sustainability of companies. A research indicated that, in the EU, the CE will generate £ 1.8 trillion and reduce 39% of CO2 emission until 2030. Both the UK government and EU are Actively promoting the implementation of CE among the manufacturing sectors (MacArthur, Zumwinkel and Stuchtey, 2015). However, the progress of CE has been limited among the practitioners due to variety of CE barriers (Julian et al., 2018). The Barriers are from variety of circles such as lack of the customer awareness and the immaturity of the available technology (Korhonen et al., 2018). Therefore, this paper will make a research of an in-depth study by synthesising different factors and views from literature and practitioners who stand for different position of the UK manufacturing sectors to identify the application of CE in the manufacturing sector of the UK.

Aim and Objectives

This research choses the UK as reginal focus as scholars have paid insufficient attention on the empirical literature about CE in UK manufacturing sector (Julian et al., 2018; Jesus, 2018). Thus, the aim of this research is to “critically analyse the drivers, enablers and barriers of implementing CE concept for the UK manufacturing industry” so that factors are identified, and the UK manufacturing industry is able to get deeper insight of where the value is, how to achieve this value and what challenges need to be overcome. Therefore, the UK manufacturers are capable of grasp the opportunities and strive to make a significant breakthrough toward CE within the particular context of the UK. Thus, this section aims to review the previous literature to conceptualize drivers, enablers and barriers of CE in the manufacturing sector. Then to identify the undefined field in order to conduct further research regarding the CE in the manufacturing sector in the UK.

Research question with an aim requires satisfying a set of objectives that are listed below:

Explore the drivers, enablers, and barriers towards CE in the UK manufacturing sector.

Define the concept of CE and the implementation of CE from the perspective of the most notable scholars including three aspects of social, environmental and economic sustainability.

Develop a theoretical framework that detail the main drivers, enablers and barriers of transition toward CE by considering business performance, competitiveness, and sustainability.

Refine and validate the framework above from the perspective of companies in order to get a n in-depth understanding of how the companies considering the drivers, enablers, and barriers of CE and its practice relating to the 6Rs within the UK manufacturing context and their impact on business performance, competitiveness, and sustainability

The basic idea of this research is to identify the viewpoints of manufacturing industry towards CE in the UK. Therefore, this paper will progressively narrow the content down to only investigate the drivers, enablers and barriers from the perspective of practitioners in the UK manufacturing sector. In another word, this paper will start with data collection regardless of its region and standpoint, then the data will be validated only reflects the viewpoint of manufacturing companies in the UK context.

Structure of this project

This research incorporates six chapters as shown in figure 1.1. Chapter 1 provides a brief introduction into the CE in the supply chain of manufacturing sector. It illustrates the problems of current linear supply chain and introduces the opportunities that CE can provide to the linear supply chain in terms of sustainability and competitiveness of supply chain, and optimisation of social, environmental and economic value. This chapter also introduces the aim and objectives of this research, and subsequently provides the structure for the whole dissertation. Chapter 2 provides an in-depth review of literature on drivers, enablers and barriers of CE relating to business performance, sustainable performance and business competitiveness. Also, this chapter describes the implementation of CE based on the principle of 6Rs. At the end of this chapter, which provides a conceptual framework which is summarisation of the drivers, enablers and barriers of CE in order to verify these finding in the UK manufacturing sector. Chapter 3 is the methodology chapter, which justifies the methodological choices used for this qualitative research. This chapter critically analysed the research philosophy, research strategy, data collection and data analysis methods. Chapter 4 is the presentation of data collected from interview and questionnaire. Chapter 5 is the analysis of finding from this empirical research in chapter 4 by synthesizing the finding with literature review analysed in the chapter 2 to find similarities and difference, also this chapter concludes the whole research. It also suggests areas for further research and admits the limitation of this paper.

Literature Review

Introduction

The aim of this chapter is to collect the fragmented findings regarding the scope of “drivers, enablers and barriers of Circular Economy in the UK manufacturing industry” through a systematic review of existing literature (Armstrong, 2011). Hereby, this chapter includes the scoping review of existing literature qualitatively and quantitatively in order to identify a more specific research question in the manufacturing context within the UK. The literature was done by using the University’s library website and google scholar and the key words used are: Circular Economy, economic and ecological Sustainability, product-life extension activities (3Rs, 6Rs), closed-loop supply chain, cradle to cradle approaches, industrial ecology, business performance, sustainability performance, and competitiveness. This section is divided into five parts. Firstly, this paper explores the drivers of CE and the principles to guide the implementation of CE in the manufacturing sector. Secondly, this paper identifies the critical enablers of CE in the manufacturing sector. Thirdly, the barriers for CE in the manufacturing sector are discussed as well. Moreover, the current condition of CE in the UK manufacturing sector is analysed. In the end, this paper summarizes all the findings above to create a conceptual framework in order to assist in future research.

Definition of CE

The philosophy of CE advocates to create an economic system in which the assumption of limited resource is supplied within a closed system. Moreover, the primary goal of CE is to satisfy the current demands without harming the future generations’ ability to satisfy their needs (Geissdoerfer et ai., 2018) CE is defined as a circular flow of materials in order to use the biological energy and materials as circulation as possible through multiple phases (Yuan etal, 2006). Kirchherr, Reike and Hekkert（2017b) defined CE as an social-economic system to achieve a sustainable development of environment, society and economy at three levels including macro-level (nation), meso level (regional) and micro level (product). CE requires a transformation of business rationales and economic structures. The macro-level of CE concerns the structure of entire economy and the industrial composition. While the meso level of CE concerns the regional systems where its emphases on the eco-industrial park. At this level, the primary goal is to collaborate with local community to reduce the waste in order to achieve not only sustainable development but also improving the social, economic and environmental benefits. Meanwhile, the micro system concerns the production system and how the individual enterprise to achieve its circularity (Abreu and Ceglia, 2018).

Drivers of Circular Economy

When the companies encounter challenges are related to sustainability and profitability, the companies usually are forced to develop a more sustainable business model by internal and external drivers (Gusmerotti et al., 2019). The traditional linear production system creates wastes in the material and energy flow through processes of extracting & producing-consuming-dumping (Winans, Kendall and Deng, 2017; Abreu and Ceglia, 2018). Consequently, the mismatching between the economic development and consequent environmental effects cause unsustainable economic performances (Lieder and Rashid, 2016; Shi and Yu, 2014). Hence, both organisations and governments are seeking a framework to boost a mutual beneficial relationship compatible with companies’ benefits (input cost reduction), social benefits, and environmental predictability and sustainability (de Jesus and Mendonça, 2018; WEF, 2014). Furthermore, the linear supply chain model also weakens organisations' competitive advantages, such as the resource-related risks, where manufacturing industry faces fierce competition in access to critical resources especially those with high price volatility level (Lieder and Rashid, 2016). Therefore, the factors mentioned above lead to various degree of motivations that are driven by different stakeholders internally and externally to encourage the CE transformation. Externally, most of the studies have highlighted that the governments of developed countries and policymakers are the most activists to push the transition of CE by which the material wastes can be back into the industry through closing the material loop. The CE transformation could benefit to societies in term of the further growth of population and job creation (cheng, 2007; Morone and Navia, 2016; Govindan and Hasanagic, 2018). Besides, The environmental disruption (emissions pollutants, resource scarcity, solid waste generation and landfill waste) and resource scarcity cause the most international organisations encourage and force the manufacturing companies to maximize environmental benefits through the promotion of CE concepts (Wysokińska, 2018; Clark et al., 2016; Govindan and Hasanagic, 2018); Therefore, the companies are forced to abide by the regulations of waste management in order to prevent the regulative penalties (Kumar et al., 2019). For example, most EU governments legislate their taxation systems on the basis of whether the resources are renewable (Stahel, 2013); also, the governments invest in costly infrastructures can be regarded as an economic driver (Morone and Navia, 2016). Hence, the external drivers of CE for companies are that the rebalance of environment and economy system (de Jesus and Mendonça, 2018), risk mitigation of resource scarcity (Georgesçu-Roegen's, 1971), improvement of industrial eco-system and symbiosis system ((Rashid et al., 2013), enhancement of material efficiency (allwood, 2014; Rashid et al., 2013; allwood, 2014), creation of jobs and sustainable social development (cheng, 2007; Morone and Navia, 2016; Govindan and Hasanagic, 2018), government supports in relation to preferential policy and infrastructure (Wysokińska, 2018; Clark et al., 2016; Govindan and Hasanagic, 2018), industrial trends toward innovation and sustainability (de Jesus and Mendonça, 2018). Although, most of the researches analyse the CE done mainly from the environmental aspect. However, the environmental drivers are not the primary consideration of business transforming to CE model (Gusmerotti et al., 2019; EMF, 2018). Internally, the CE is regarded as a way to be innovation (Pomponi and Moncaster, 2017); for example, international organisations, EU and UN advocate the CE as a strategic framework. Moreover, non-governmental organisations such as World Economic Forum (WEF) also treat the transformation of CE as a driver of innovation and sustainability (de Jesus and Mendonça, 2018).

Moreover, Testa, Boiral and Iraldo (2018) pointed out that, internally, the economic benefits are the necessary drivers of companies selecting environmental practices (Testa, Boiral and Iraldo, 2018). The transformation of the CE supply chain model provides new opportunities to companies. Lieder and Rashid (2016) pointed out that, companies need to find a way to gain economic benefits profitably and sustainably by creating a new value stream through utilisation of by-products and waste. As shown in figure 2.1, Kumar et al. (2019) and Gusmerotti et al. (2019) found that, the organisations which perform poorly about CE principles that had the worst economic performance. Contrarily, the organisations which implement CE supply chain principles had the best economic performance. Besides, the authors highlighted that there was no significant evidence to prove other drivers concerning non-economic initiatives such as regulatory drivers and resource scarcity risks. Therefore, the economic drivers were the most effective at attracting organizations in implementing more CE principles.

Besides, in the manufacturing sector, the competitiveness of companies is directly affected by its resource availability and price volatility (Wysokińska, 2018). Therefore, the companies adopt CE practice in order to reduce the risks aforementioned and stay sustainable through managing discarded products as resources (Batista et al., 2018). Therefore, the speed of wastes generation and resource depletion are slowed down (Boiral and Iraldo, 2018). Sperling (2017) pointed out that, companies has various of motivations to upgrade their technological capacity such as reduction of costs through material recovery technology. Thus, the transformation of CE is also driven by technology factors. There are also drivers which are attributed as both internal and external drivers. The structural social-technique changes of CE have stolen the limelight from academia and practitioners in diverse ways (de Jesus and Mendonça, 2018). Historically, Georgesçu-Roegen's (1971) criticised the fundamental drawbacks of linear economic system in regard of resource scarcity. Pearce and Turner (1990) advocated that, the application of CE principles are associated with industrial eco-system and industries symbiosis system to production system, which will not only improve the efficiency of natural eco-system but also boosts the material efficiency. In the age of twenty-first century, the concept of CE has been penetrated completely to the field of supply chain, including extension of product life cycle and material efficiency (Rashid et al., 2013; allwood, 2014), cradle to cradle principles (McDonough and Braungart, 2007), closed-loop supply chain (Pomponi and Moncaster, 2017). Nowadays, the industrial pressures also cause companies to implement CE activities (Sehnem and Pereira, 2018). Such pressures come from two perspectives. Firstly, Jakhar, S. K. et al. (2019) pointed out that, the fierce competition caused companies to pay more attention on the material efficiency and customer satisfaction. The CE is a principle to maximise the value of products. Through the realisation of 6Rs, the products, components and materials can be reused, reassembled, and remanufactured as far as possible (Zeng, H. et al., 2017). By doing so, the customers will have multiple choices and production efficiency will be optimised (Lanz, M. et al., 2019). Therefore, the supply chain model is more sustainable and competitive that those linear supply chain. Secondly, the environmental certificates are regarded as essential requirements to enter the most of markets and industries such as ISO 14001 (Mesa, Esparragoza and Maury, 2018). Therefore, companies implement CE activities in order to serve satisfy basis requirement of industries and markets （EM Foundation, 2014). However, most current literature focus on the contribution of CE to the rebalance of environment and economy system (de Jesus and Mendonça, 2018), where, the sustainable supply chain development for companies are the green economy. Figure 2.2 illustrated the interrelationship and interdependence of three drivers, which are "Environmental Impact", "economic benefit" and "Resource scarcity". However, the economic driver is examined as the significant factors that drive business toward the CE model (Lieder and Rashid, 2016). Evidently, the economic benefits of CE are indirect and more complex to achieve than the environmental benefits (EM Foundation, 2014). Therefore, the most current literatures about CE are largely down from environmental impacts and resource scarcity, also leave the manufacturing sectors in general (Lieder and Rashid, 2016). However, the achievement of economic benefit requires a multifaceted approach to design business models, supply chain models and products by total involvement and commitment of all relevant stakeholders (Gusmerotti et al. 2019). For example, the resource availability is fundamental for business to earn economic benefits. In turn, price volatility can impact on economic benefits directly. Meanwhile, government will also restrict the industrial activity in order to prevent environmental disruption. Therefore, all the drivers are interrelated and pushed by different stakeholders that force companies to design a CE framework by considering more broader stakeholders.

In summary, based on the discussed literature, there are many broader factors push the transformation of CE and will be considered in this research as shown in table 2.3. Each of the factors are interrelated and interacted. To illustrate, there are three stakeholders, all possess different motivations to push the transformation of CE. The governmental bodies and societies aim to protect the planet earth that they are living (de Jesus and Mendonça, 2018) regarding to environmental wastes and resource scarcity. Thus, the governments set policies, and provide incentives and costly infrastructure to push CE initiatives amongst companies. Bilaterally, the companies are concerned with their performance relating to sustainability, profitability and competitiveness. Coincidentally, the CE provides the blueprint for both parties, it shifts business model, supply chain model to a more sustainable and competitive status. The CE enables companies to reduce the risks of resource scarcity and associated price volatility. Moreover, the material efficiency can be increased, which causes the reduction of raw material input and reduces the environment impacts. Furthermore, through implementation of CE, business could achieve personalization which will enhance the competitiveness of business by providing diverse products in low operational wastes.

There are not the most important drivers, and the importance and intercalations of each driver depend on the context of the supply chain and country background that the companies located in (Sperling, 2017). Thus, this research will mainly consider the factors related to businesses and examine the importance and intercalations of each element.

Principles of CE

Public institutions and industries possess inverse motivations toward CE. To be precise, governments call for the collective awareness of environmental protection and social benefits. Contrarily, companies focus on economic benefits and growth primarily (Winans, Kendall and Deng, 2017). Therefore, the implementation of CE concepts requires the total engagement between national institutions from up-bottom and companies from bottom-up concurrently, as shown in figure 2.3 (Winans, Kendall and Deng, 2017). The concept of CE converges and compromises the interests of both the public institutions and the industrial actors together through the achievement of a productive economy that is environmentally and regeneratively. Therefore, the inverse motives of both national and company can be converged and aligned, where both the parties should primarily focus on the CE goals rather than prioritisation of economic benefit at the cost of environment and vice versa (Winans, Kendall and Deng, 2017).

The core ideology of CE is underpinned by 3Rs, which are the acronym of Reduction, Reuse and Recycling (Manickam and Duraisamy, 2019). The rationale of 3Rs is to design the products that keep material in a closed-loop. Hence the raw materials and energies can be used in multiple phases, and less production of the material will be required (European Commission,2019). The definitions and aims of CE are shown in figure 2.4. Geng et al. (2012) cited in Frodermann (2018) that, the leading principle of 3Rs is “Reduction” where the industry should primarily focus on reducing the consumption of resources and wastes generated in increased production efficiency (Geng et al., 2012). The principle of “Reuse” means that, the products should be employed as the maximum of its capability, and the lifecycle should be extended via reselling disposed items or even reassembled into a new manufacturing process without modification (Manickam and Duraisamy, 2019). The "Recycling" stands for the residual value of the products such as biodegradable materials and energy should be fully extracted for further utilisation （Frodermann, 2018).

Besides, Batista (2018) advocated the adoption of 6Rs (listed below) in the supply chain archetype which includes a number of recovery streams enabling different recovery flow as depicted in figure 2.5. In detail, the circular supply chain model involves a broader design of ecosystem to the material recovery systems (Guide and Van Wassenhove, 2009). As figure 2.5 illustrated, the 6Rs can be embedded into distinct material flows correspondingly with various purpose. On the one hand, the direction of material flow is extended, the closed-loop supply chain boundaries are extended to include the open-loops (other manufactures) as alternative supply chain in order to optimise the value of wastes. In term of the optimisation of wastes, circular supply chain not only recovers the end of life returns but also transforms the recovered and secondary materials to by-products through synergy effect between two or more companies (Eskandarpour et al. 2015; Batista, 2018; Green et al., 2012)). On the other hand, Batista (2018) stated that, the scope of the supply chain is extended to include the different streams in order to achieve the purposes of 6Rs distinctively. However, the achievement of 6Rs of CE is enabled through the purposeful design of functional process of material recovery and specific management of supplier relationships.

Reusing: products can be reused after the exhaustion of its initial purpose.

Repairing: fix the product for reuse.

Reconditioning: making adjustment to the components of a product. therefore, the components can be sent back to processing order;

Refurbishing: remoulding product to a nearly new state but with no improvement in functionality.

Remanufacturing: bring product in nearly new condition with functional improvement through a set of manufacturing activities for the end-of-life product or parts.

Recycling: processing products into raw material for the production of new products.

The concept of CE is tightly linked with waste management, which aims at eliminating material waste and improving resource efficiency. Stahel (1994) distinguished CE concepts into two types of resource efficiency that guide the CE (figure 2.6). The first concept is " product-specific loop" which emphasise on the extension of product life and the reuse of the products (loop 1). The second concept calls "material-specific loop" which is based on the material recycling where post used waste (supply)and production-input (resources) are the closed within a cyclic loop (loop 2).

As figure 2.7 illustrates, Stahel (2013) also mentioned four loops, are, reuse, repair, reconditioning and recycling. Moreover, reconditioning stresses on refurbishing used products as a new one. The effectiveness of this spiral loop is greatly influenced by the inner circles in which the innermost circle creates the most significant saving environmentally and economically in term of capital, material, energy and workforce.

Besides, McDonough and Braungart (2013) proposed the principle of "Gradle to Gradle" to encourage designers toward sustainability. The concept mentioned that when the products reach the end of its life, which will be differentiated to " biological nutrient" or "technical nutrient" as depicted in figure 2.8 (Rathinam, 2018). Rarhinam (2018) illustrated that, in the Biological cycle, the consumption is high, so the substances are designed to reflow back into the system through different processes such as compositing (McDonough and Braungart, 2013). Therefore, this system regenerates renewable resources for the existing system and the economy. The material through Technique cycle are reused, recycled and remanufactured (Rathinam, 2018). Namely, the products and components are recovered and restored in the technique cycle.

To combine the figure 2.7 and figure 2.8, Ellen MacArthur Foundation provides the most prominent concept of CE, as shown in figure 2.9 (Eva Guldmann, 2016). The axis is the process of linear production. The marked curves around the axis are the possibilities of CE. As figure 2.9 presented, the ultimate goal of CE is to eliminate the waste in the last stage of the linear economy. Also, the closer to innermost, the more benefits are obtained concerning the environment, society and organisational economies. the principles above can be summarised into three principles (Towards the Circular Economy, 2019)

Principle 1: preserve natural resources by balancing renewable resource flows.

Principle 2: maximise the value of the resources through the ideology, either biological or technique cycle.

Principle 3: design the product and process from the point of CE.

However, the concept of CE is far more comprehensive than waste management stressed. Ghidellini et al. (2011) pointed out that, it requires the design of solutions by looking at general aspects synchronously including the interaction between the society, environment and the production process where it is embedded. Next section will critically explore the critical enablers of the circular economy. The implementation of the circular economy happens in three scales: Macro (e.g., regional), Meso (e.g., eco-industrial park) and Micro (products, consumers) (Kirchherr, Reike and Hekkert, 2017b; de Mattos and de Albuquerque, 2018). It starts from the micro level, such as eco-design of product, then the macro level should be embedded in order to achieve a systemic approach (Kumar et al., 2019). In summary, the circular supply chain is designed in line with the 6Rs principles (table 2.2) where, the materials and wastes are flow through the closed-loop (inside of supply chain) and open-loop (other supply chain). The 6Rs stresses that, the fundamental the supply chain should be changed to deliver service and functionality to customer rather than selling products to customers (Kortmann and Piller, 2016). Hence, the customer will be willing to support the flow of each function of 6Rs smoothly. This research will be based on the 6Rs as a starting point to examine the in-depth drivers, enablers and barriers of CE in the UK manufacturing sector.

Enablers of Circular Economy

This section aims to discuss the essential enablers of CE in the manufacturing sector. The achievement of recovery materials require the involvement of wide range of stakeholders to collaboratively enable the various recovery flow (Wysokińska, 2018; de Jesus and Mendonça, 2018). Rahimifard and Clegg (2007) pointed out that, the more sustainable supply chain model depends on the stakeholders amongst supply chain from its suppliers to end consumers all around the world. Internally, the transformation of CE requires a “system shifting” of business model which advocates a fundamental shift rather than accumulative modification of the status of the current supply chain (Jackson, Lederwasch and Giurco, 2014). Externally, Lieder and Rashid (2016) advocated that, the CE requires the transformation of the supply chain, which should include not only the new production and distribution process but also consumption processes and other companies’ supply chain. Joseph Nye (2006) and Mendonca (2014) stated two kinds of enablers which are hard and soft enablers. The hard enabler refers to a capability to push an innovation such as technical and financial/economic/market support; for example , the environmental protection equipment and environmental design technology can bring benefit to a long-lasting profit of the company as well as the improvement of the business image in a long run (Ma, Song and Zhou, 2018). While the soft enablers regard to the ability to drive a system change, in which the organisational and the social cultures are essential to affect the performance of CE; for example, adopting environmentally friendly operations could establish the ethical image of a company. This image will attract more customers who have environmentally conscious (Ma, Song and Zhou, 2018). So that, the companies are enabled to operate in a culture that facilitate the CE operations. Apparently, the hard enablers are more emphasis on technological and economic foundations. Whereas the soft enabler is more related to regulatory and culture aspects. de Jesus and Mendonça (2018) recommended that, both hard and soft enablers are interacted, and all enablers are not mutually exclusive to facilitate the CE. Thus, the importance of the factors and their interactions are depending on the context that companies operate. For the soft enablers, Leadership is crucial to facilitate a higher level of collaborations and common initiatives among supply chain players (Batista, 2018). The supportive activities to supply chain players such as training and technology support would enhance the collective ability to provide continuous flow of recovery process (Jackson, Lederwasch and Giurco, 2014). in addition, the promotion of consumer responsibility toward CE mindset is vital and the most central for CE (Lewandowski, 2016; Gallaud and Laperche, 2016). Moreover, Rizos et al. (2016) conducted a sample of 52 manufacturing SMEs case studies in order to identify the enablers of CE transformation. The authorities prioritised various enablers of CE, as shown in figure 2.10. The "company's culture" is the most reported factor that most of the companies stated that the managers', employees' and suppliers’ mindset and commitment toward CE are the essential factors in enabling the transformation of CE. Moreover, "Networking" is the second most mentioned enabler, third of companies states that the company should join a "network" including like-minded suppliers or customers to support sustainability collaboratively. De Mattos and de Albuquerque (2018) supplemented that, the "geographical proximity” often happens in manufacturing level, it can boost symbiotic industrial practices with collaboration. An efficient industrial symbiosis and the maximum value of resources always happen within a particular area that firms are located. Therefore, the success of industrial symbiosis depends on the collaboration of companies collectively with the mutual purpose of environmental and economic sustainability. Furthermore, a research shows that the manufactures are generally forced to implement CE practice by industrial pressures. Ma, Song and Zhou (2018) pointed out that environmental regulations and policies are the most critical enablers to support companies to internalise the proactive environmental practice; for example, ISO 14001 and EMAS standards are the certifiable management system, where this system not only guides companies to internalise their environmental practice but also increase their corporate legitimacy in view of external stakeholders (Testa, Boiral and Iraldo, 2018).

The companies need an external recognition in term of financial and reputational “incentives” or Government Preferential Policies. Testa, Boiral and Iraldo (2018) pointed out that providing companies with incentives can enable the actual internalisation of CE, where companies will have motives to encourage each level of supply chain members to abide by the CE principles. such incentives can accelerate the implementation of CE step forward. In addition, Ma, Song and Zhou (2018) analysed classified three aspects of enablers as shown Figure 2.11, which are economic, social, and environmental prospects. In reality, all enablers are interrelated. Notably, the enabler of “Corporate Social Responsibility” (CSR) is a critical factor to provide the driver for other enablers and motivations of CE. The CSR initiative provides a systematic logic of how environmentally friendly operations can facilitate economic benefit (Carroll, 1979).

For the hard enablers, “technology” is vital in enabling CE (Szutowski et al., 2017). Firstly, Eco-innovation (EI) is a critical pathway as a transformative process to achieve CE. The EI is a new social-technique system that offers a problem-solving tool to enable a holistic transformation of CE (Szutowski et al., 2017). Not only the companies can be benefit from EI in term of the improvement of efficiency and competitiveness what are enabled by green technologies, but also the society and environment can gain positive effects (Szutowski et al., 2017). Secondly, Moreno et al. (2018) pointed out that, the digital technology as a supporting system is indispensable to enable the smart factory (The Manufacture, 2019), and the visibility of communications, and close collaborations between all parties that is from inside manufacture plant to outside customer service. Thirdly, the company should have its “IT infrastructure” to connect different partners to not only understand the current system but also identify the opportunities and risks. In addition, Rizos et al. (2016) and Rizos et al. (2016) stated that, Environmental design technology can directly have influence on the living environment and improve the environmental protection awareness of all parties including society, which in turn upgrade the performance of CE. Mattos and de Albuquerque (2018) stated that, the companies should have special funds to reduce the risks of the investment, such funds can be from start-up financing or governmental subsidization. Thus, the “Financially attractive” is also an important enabler; for example, several international banks and financial institutions evaluate companies’ financial risk by taking CE activities into consideration. Moreover The “reverse supply chain” is also important. The implementation of CE requires joint efforts from upstream suppliers to adopt environmentally friendly inputs to downstream partners to carry out CE practice in term of 6Rs (de Jesus and Mendonça, 2018). Therefore, it is vital to design a circular supply chain that enables the product to be re-entered into the supply chain as a production input. Finally, (Masi, Day and Godsell, 2017) pointed out that, CE represents a closed bounded supply chain that material flows are circulated within a closed loop. Thus, the recovering material requires a comprehensive “environmental protection infrastructure” to support the reverse logistic (Genovese, A. et al., 2017). An effective circular supply chain is achieved by sharing infrastructures with partner firms in order to close the resource flow by overall circulation of wastes (Hu et al., 2010). In summary, table 2.3 summarises all the enablers of circular economy that will be investigated in this research. However, this chapter collected a lot of enablers from diverse backgrounds. the achievement of one enabler may elicit the necessity of other enablers. For example, The CSR initiatives could be an underlining philosophy for CE implementation, which may necessitate a upgrade for environmental equipment and green technology (Rizos et al., 2016). The enablers of CE, and their interrelations and importance are undiscovered in the UK manufacturing sectors. Thus, this research will identify all factors in this specific area.

Barriers to Circular Economy

Although the level of awareness among organisations against CE is improved gradually, there is still a lack of clear awareness in term of CE and relevant principles (Winans et al., 2017). This is due to the lack of sense of participation among the public (Benton et al., 2015). Therefore, there is a need for extensive public education through different channels. Geng and Doberstein (2008) suggested that, the enhancement of social awareness can be achieved through media and publicity work, and government policies. However, Su et al. (2013) argued that the social institutions and governments are not capable enough to facilitate the social awareness, which is due to the lack of qualified personnel and weak institutional and human capabilities. Research indicates that consumers are mostly unwilling to buy a product that is manufactured from scrap (Moncaster,2017). Thus, it makes organisations hard to promote CE initiatives due to low customer acceptance. furthermore, the CE concept requires a continuous closed-loop supply chain. To achieve this, customers would have to sign a contract with limited usage of their product in order to ensure the ongoing return of inputs (Zhang, 2010). Nevertheless, many consumers are willing to use the product beyond the contract, which leads to the unsmooth flow of materials, and therefore interrupt the CE activities (Bicket, 2014). On the other hand, trends of government policy have a significant influence on the business strategy (EMF, 2013). Due to the factor that there are many countries with the fragmented regulatory system, which cause an inadequate legal and policy system, and unclear assignment of responsibility of CE. This causes their local governments and institutions are not accountable to support the implementation of CE (Naustdalslid, J. 2014). Also, the policymakers are unable to lead the formulation of the standard system, causing the lack of clear vision, mission, objectives and indicators for award and punishment of CE performance (Pan et al.,2015). Therefore, organizations are afraid of taking risks and go for existing strategies. As a result, the spread of CE is restricted. Besides, Nausrdalsid (2014) noted that, in most regions, the current tax regulations do not facilitate the implementation of CE. Technical factors are regarded as a most critical barrier to the CE implementation (Johnson and Suskewicz, 2009), the availability of technology enables the standardised product quality and durability. Also, the technique solutions are essential for the design of product-life extension (Geng et al., 2014). The technique barriers are not only concerning the appropriate technologies (Watkins et al., 2013), but also considering the technology gaps such as the gap between the products development and processes (Kaenzig and Wüstenhagen, 2010). Economic barriers are also severe in the manufacturing sector (Kumar et al., 2019). The financial benefit of CE is unverified, and the upfront investment for CE is considerable (Liu and Bai, 2014). Therefore, the managers are hesitated to invest in CE activities because of the long-term and unknown economic return. Also, as mentioned above, companies avoid to adopt CE practice even they are willing to transforming, which is due to the lack of tax incentives and financial support mechanisms from banks and government's budgetary system (Kumar et al., 2019). The transformation of CE is costly and except large enterprise. Therefore, the government must positively facilitate a favourable environment for the promotion of CE. The lack of reliable information also obstructs the implementation of CE as it requires the regular flow of material and tightly collaboration between all stakeholders within a closed-loop (Pomponi and Moncaster, 2017). Additionally, the lack of reliable information combined with the high cost relating to the establishment of eco-industry chains, cause the company are unable to build up an instant-feedback-mechanism (Liu and Bai, 2014). As a result, these uncertainties embedded within CE lead to companies avoided to invest in the remanufacturing process. There are also several environmental barriers. Geng et al. (2012) reported that, the government bodies and environmental institutions pay fewer efforts on environmental management projects and infrastructures, which cause the existing environmental protection system dysfunction. Even more, the companies are unsatisfied with the current incentives of promoting greener activities. Furthermore, the large environment losses are due to the lack of proper technology on the landfilling and incineration activities (Gregson et al., 2015). For a reason, that much of Governments do not provide the incentives for the waste recovery. Therefore, for the existing remanufacturing companies, the materials recovered are incapable of satisfying the current demand, which leads to these companies have to adopt virgin material. In summary, table 2.4 summarised all the barriers, that will be considered in this research. There are only two barriers that are attributed as internal barriers, which are technical and economic/financial factors. However, government have ability to support companies to overcome these barriers. Nevertheless, all the external barriers are somehow related to roles of the government including the social awareness of CE principles, regulatory factors and environmental infrastructures. Therefore, this research will examine all these factors within UK manufacturing sector.

Circular Economy and its relationship with Business performance, Sustainability Performance, and Business Competitiveness

The CE brings various public and social opportunities to the company (Gusmerotti et al., 2019). It includes the consumers/users in the supply chain (Horikx and Beqiri, 2017). Firstly, the CE improves the business competitiveness, the company can retain customers by better understanding of the customers' needs. Hence, the companies can design and manufacture the product accordingly (Ion and Mihaela, 2018). By doing so, the companies can attract more customers by satisfying their requirements (Ion and Mihaela, 2018). Also, The CE encourages rental models in all nodes of the supply chain (EMF, 2013). This enables the companies to get a deep insight into their customers and provides the customers with products that are more personalised and cheaper (Stahel, 2016). Therefore, the whole societies are benefited by circular economy where not only the consumers are more conscious about environmentally friendly products, but also companies have a qualitative leap and are more profitable, sustainable and competitive than its competitors. Hence, the CE protects and improves businesses to attain their desired market share (Chiaroni and Chiesa, 2017). The CE improves the business sustainability, the achievement of CE is far more beyond the legal requirement (Kama, 2015). The CE enables business to comply with environmental standards. Therefore, CE enables organisational legitimacy and reduce the pressure from societies and governmental bodies (Johan and Hervé, 2012). Moreover, the CE enables the supply chain to reduce wastes in the operational process. The companies are capable of turning waste into wealth, which brings the companies additional money. Besides, CE provides the potential for companies to improve the resource efficiency (Alfonso, 2019). The wastes can be produced to raw material and sale to other companies, so that, the cost of raw material can be decreased, and the price volatility can be mitigated as well as the reduction of supply risks (Alfonso, 2019). Furthermore, the CE improves the relationship with the community or stakeholders, it strengthens the real connection between industry and society. Inside the closed-loop, all participants understand the business strategies due to an extended collaboration (Tolio, 2017). The products' life cycle does not end up with consumers as it should be regained as inputs of production (Geissdoerfer et al., 2018). This aligns companies with customers in a strong and enduring relationships (Geissdoerfer, De Carvalho and Evans, 2018). The CE also improves the work environments. By developing environmental science and technologies, the CE practices offer supply chain resilience where the companies are not only capable of controlling the number of changes but also building capacity for adoption and learning (Ponis and Koronis, 2012). Therefore, the new markets are more comfortable to be penetrated (Park et al., 2010), and the new profit pools are built. As a result, business performance and competitive advantages are enhanced. Additionally, through the reworking and recycling of materials, the productivity and life cycles of which are increased, and the requirement for landfill is decreased (Brenner et al., 2018. Much more interesting, the Circular activities can present companies with opportunities for diversification of other products, the companies benefit from more resilient economy through the enhanced innovation capabilities (Brown, 2018), and the employees' skill is improved to support mass customisation (Chiaroni and Chiesa, 2017). The CE improves the business performance, the improvement of efficiency and operational performance can be achieved by CE transformation. The benefit of CE includes lower costs as well as increase profitability (Gusmerotti et al., 2019). It reduces cost through remanufacturing management and sustainable supply chain, which enables a lower cost of inputs and reduces risks of environmental penalty (Kama, 2015). The companies are capable of turning waste into wealth, which brings the companies additional money. in other words, the revenue channel is created through the closed-loop, which adds competitive advantage to companies over their rivals (Abu-Ghunmi et al., 2016). Also, the disposed materials can be sold through an opened-loop system. Therefore, the market share of companies is enabled to growth through the CE transformation. In reality, in China, the wastes such as metal and plastic can be sold to salvage station by municipalities that companies collect it lower than market price in order to turn it as an input of production (Geng et al., 2013). By doing so, both the public and companies can benefit from CE. As a result, a financially mutual-beneficial relationship is generated.

Circular Economy in the UK manufacturing Industry

In recent decades, the UK economy has been transforming from manufacturing to servicing (Peace, 2019). The manufacturing output of the UK is ranked ninth globally. The acceptance of CE brings considerable benefits to the UK economy, which account for 19% of the UK economy (Mesa, Esparragoza and Maury, 2018). Research shows that there are annually £23 billion earning by UK companies through CE activities. The manufacturing sector has been the second largest consumers of energy in the UK (The Manufacturer, 2019). Also, it is the most energy consumption sector (Wrap.org.uk, 2019). The manufacturing sector is gloomier partially due to the government decisions on Brexit, and some companies paused their investment in the UK (e.g. Nissan). Nevertheless, the manufacturers' strategic planning focus on risk in order to react to the chaos. As mentioned in section 2, the digital technology is an essential enabler of CE and supply chain resilience, and it can not only reduce the cost of the operation but also ensures more flexible customer service in line with the continuous process. Research shows that 74% of UK manufacturers agree that the needs of applying digital technology. However, there are only 1% of UK companies applied digital technology successfully (The Manufacturer, 2019). The lack of enough funding due to the uncertainty of Brexit, lack of clear digital strategies and successful pioneer are reasons for that companies are hesitated to implement digital technology (The Manufacturer, 2019). Thereby, Thornton, Henneberg and Naudé (2013) suggested that, the current manufacturing sectors need to disrupt their existing business models through clear leadership to promote the desired culture. According to CE principles (3Rs), the UK manufacturing industry has been adopted the principles of CE, and advocates to comply with UK waste hierarchy, as shown in figure 2.10.

Research shows that the R&D spending relating to CE activities has been increased by 8.3% between 2016 and 2017(SMMT, 2018). Firstly, car components are designed with modularity and upgradeability in mind, so which can be easily replaced when brake. Secondly, the car sharing users are growing annually, the circular manufacture offering car-sharing services to the consumer by tackling the current rock-bottom utilization rate. Thirdly, the UK manufacturing sector has invested in CE operations where car component gets reintroduced in the production process. As a result, 9.4% down of CO2 produced by per vehicle (The Manufacturer, 2019), production energy use has dropped by 3.7% from 2016 to 2017(SMMT, 2018). Water uses per complete vehicle has decreased by 27% since 2016. Today 95% of the vehicle is reused and recycled. moreover, the vehicles' life is extended by the replacement or remanufactured parts. Most interestingly, the turnover of the UK automotive industry rose 5.3% in 2017(SMMT, 2018). In short, Figure 2.11 shows the UK automotive manufacturing performance in term of CE in 2017.

Besides, the automotive industry also positively invest in disruptive technologies in order to be closer to CE ideology (The Manufacturer, 2019); For example, The disruptive technology enables companies to maximise the value of the waste. Since 2017, the Vauxhall launched the allowance scheme where customers can get ￡2,000 off on any brand new Vauxhall when trading in any scraped car (SMMT, 2018). Therefore, Vauxhall can recycle the components from the scrapped vehicle to extract more economic benefits. By doing so, both customers and Vauxhall are benefited from CE. Therefore, the embedding of CE within the manufacturing sector facilitates competitiveness and sustainability.

Research Gap and Conceptual framework of this research

Section one has listed the overall aim of this paper. Both drivers, enablers and barriers of CE in the manufacturing sector of the UK are reviewed. The relationship between variables of CE is complicated. This section aims at conceptualising this field to build the theory (Weick, 1995). This framework will be classified by five sub-sections as listed below.

Drivers for the adoption of economy principles

Enablers for implementation of Circular economy principles

Barriers for implementation of Circular economy principles

6RS

Business performance, Sustainability performance, and competitiveness

Drivers for the adoption of Circular Economy

The enablers of CE are presented in figure 2.12. This section summarises the initiatives and external pressures caused by various stakeholders. there are internal and external enablers. The external drivers are pushed by nations, government bodies and social institutions, and the internal drivers are motivated by organisations themselves. The Internal drivers include “Economic Benefits” and “Innovations” (Kumar et al., 2019; Korhonen, Honkasalo and Seppälä, 2018; Reike, Vermeulen and Witjes, 2018; Winans, Kendall and Deng, 2017; Abreu and Ceglia, 2018). The external drivers contain “reduce environment impact” (Lieder and Rashid, 2016), “job creation” and “ Infrastructures provided by governments” and “ environmental protection policies” (Testa, Boiral and Iraldo, 2018; Kumar et al., 2019; Batista et al., 2018; de Jesus and Mendonça, 2018; cheng, 2007). Furthermore, the “ resource scarity” (McDonough and (Braungart, 2007), “material efficiency” (Shi and Yu, 2014), “ Sustainability” (EMF, 2018) are factors that considered by both internal and external stakeholders

Enablers for implementation of Circular principles

In this conceptual framework, there are two kinds of enablers which are hard and soft enablers respectively as sown in figure 2.13 (Joseph Nye, 2006; Mendonca, 2014). Hard enablers refer to technical and financial factors, and soft enablers refers to organisational and social culture. The soft enablers include “Leadership”, “consumer responsibility”, “company’s culture”, “Corporate Social Responsibility” “policy/regulation” “Networking”, “incentives” (Jackson, Lederwasch and Giurco, 2014; Lewandowski, 2016; Gallaud and Laperche, 2016; Rizos et al.,2016; Ma, Song and Zhou, 2018; Carroll, 1979). While hard enablers include “environmental protection infrastructure”, “technology”, “financial attractiveness”, “Reverse logistic supply chain” and “Geographical proximity” (Moreno et al., 2018; Joseph Nye,2006; Mendonca, 2014; Jesus and Mendonça,2018; Szutowski et al., 2017; The Manufacture, 2019). However, none of the factors can support CE independently, and all factors are interacted and interplayed to enable the continuous smooth flow of circular supply chain. Thus, the Organisation, Society and Government are stakeholders to collaboratively enable the hard and soft practice of CE.

Barriers for implementation of Circular concept

The barriers existed in companies that have either implemented CE or not (Benton et al., 2015; Gregson et al., 2015). There are internal and external barriers as shown figure 2.14. Internally, "uncertainty of return on investment", "lack of proper technology" and "lack of reliable information" lead to the companies avoid investing in CE (Pomponi and Moncaster, 2017; Kumar et al., 2019; Liu and Bai, 2014; Pan et al.,2015). Externally, the barriers include “poor Public awareness” (Winans et al., 2017). “lack of public participation” (Winans et al., 2017; (Winans et al., 2017; Geng and Doberstein, 2008; Winans et al., 2017; Geng and Doberstein, 2008), “incapability of government and social institution” (Su et al., 2013), “variability of user habit” (Moncaster,2017; Zhang, 2010), “inefficient legal and policy system” (Naustdalslid, J. 2014; EMF, 2013; Pan et al.,2015), “high upfront investment” and "incomplete environmental infrastructure"(Liu and Bai, 2014; Geng et al.,2012; Gregson et al., 2015). Particularly, “Technical barriers” and “Financial factors” are both internal and external barriers, which are key to stop the progress of CE (Gregson et al., 2015; Kaenzig and Wüstenhagen, 2010; Watkins et al., 2013; Geng et al., 2014; Johnson and Suskewicz, 2009).

6Rs

The circular supply chain incorporates various circular flows to enable recovery flow of materials and wastes. Companies adopt 6Rs to build their supply network in order to make diverse loop material flows work. As figure 2.5 illustrated the 6Rs support restorative flows not only in a closed-loop (within supply chain of company itself) but in an open-loop (across supply chain). Moreover, the wastes are minimised, and product-life are extended through the efficient management of Biological materials and technical materials as shown figure 2.9. However, the loop differentiations are vital to determine the levels of efficiency of material Use (Stahel, 2013). Table 2.6 summarises the key characteristics of circular supply chain and corresponding 6Rs principles.

Business Performance, Business Sustainability and Business competitiveness

The CE requires a disruptive transformation of the traditional linear supply chain. The attributes of circular supply chain could bring significant competitive advantages to companies where the real connection between industry and society are strengthened (Tolio, 2017). This brings a radical change of business models (Gusmerotti et al., 2019), the competitive priority of companies and supply chains are reshaped (Masi, Day and Godsell, 2017). For the business performance, the risks related to resource scarcity and price volatility are reduced significantly, which impact positively on “companies’ profitability” (Ponis and Koronis, 2012). Also, the CE contributes to the “improvement of efficiency and operational performance” as the value of resources are designed to be utilised as maximum as possible during ever stages of the production process (Kama, 2015). Furthermore, the disposed materials can be sold to other manufactures, which can improve the “companies’ market share” (Stahel, 2016). For the business sustainability. The CE contributes to “waste reduction in operational process” (Alfonso, 2019), “growth of resource efficiency” (Alfonso, 2019), “improvement of compliance with environmental standard” (Johan and Hervé, 2012), “improvement of relationship with community or stakeholders” (Tolio, 2017), “improvement of work environment” (Ponis and Koronis, 2012) and “improvement of living quality of surrounding community” (Brenner et al., 2018). For the business competitiveness. the CE contributes to the “growth of customer satisfaction” (EMF, 2013), “adding value for customers”, “customer retention” (Ion and Mihaela, 2018), “attraction of new customers” (Ion and Mihaela, 2018), “attaining desired growth” and “securing desired market share” (Chiaroni and Chiesa, 2017).

Research Gap of Circular Economy

Many researches have exploited the drivers, enablers and barriers of CE as well as the CE impact on business performance in general sense, and the field of UK is neglected, especially for the manufacturing sectors. Moreover, some of the findings may not be suitable for the UK industries such as aforementioned that the barriers of lack of technological infrastructure as a barrier to implementing CE. However, the UK has the world most advanced technological infrastructure for business to develop CE (SMMT, 2018). Therefore, this research will specify the drivers, enablers and barriers of CE and the performance of its 6Rs activities, the compares their relationship with business performance, business sustainability and business competitiveness in the UK manufacturing sector. (Gusmerotti et al., 2019). Business performance, Sustainability performance, and competitiveness. The conceptual framework of this research as explained above its presented in Figure 2.15.

Conclusion

This chapter looked at the previous study of Circular economy in the manufacturing sector within the UK. Also, this chapter critically analysed the drive for adoption of CE and how it is implemented, which are summarized in section 3.71. Section 3.72 and 3.73 summarised the enablers and barriers of CE in manufacturing sector respectively. According to section 3,7, the author found that, the implementation of CE in the UK manufacturing sector is flourishing. However, the full range of resources has been reviewed by the author, including technical reports, government reports, academic books, journal articles, conference papers, and magazines. The data are found from EBSCO, Statista, ScienceDirect. However, as section 3.74 stated, many fields are unexplored, and this dissertation will research on that.

Research Methodology

Introduction

This chapter discusses the methodological choices used for this empirical research. Below justifies the underlying research philosophies and research methods that this paper will adopt for collecting and analysing primary data. This research aims to conceptualise a research context that is the most appropriate for investigating the drivers, enablers and barriers of circular supply chains in the UK manufacturing sector and their relationships with business performance, business sustainability and business competitiveness. Firstly, this chapter analysed the research philosophies and identified Epistemology that underpins this methodology. Secondly, this chapter clarified the qualitative methods as an only research approach to collect primary data. It then preceded with discussion of the logic behind this research. Moreover, this chapter adopted questionnaire that is most proper for collecting qualitative data (Wilson and Sapsford, 2006). Finally, the process of data collection, and data analysis were discussed.

Research Philosophies

Before getting into the data collection, the research philosophy illustrates the researcher’s position of research strategy and methods (Welman et al, 2005). Saunders (2015) pointed out two categories of research philosophy which are ontology and epistemology. Ontology concerns assumption about the nature of reality (Kumar, 2019), and epistemology emphasizes how to examine the reality (Kumar, 2019). To more precisely. The intrinsic elements of epistemology include Positivism, Realism, Interpretivism and the intrinsic element of Ontology includes subjectivism and objectivism (Saunders, 2015). For the Epistemology, The positivism refers to the stance of the natural scientist, it advocates that reality is uninfluenced by human bias and can be measured by adopting the objective measurement (Hair et al., 2016) where the qualitative method is appropriate to test the hypotheses by using statistical techniques. Whereas, the interpretivism criticises positivism that tries to discover universal law, the Interpretivism emphases the stance of the social science. The interpretivism advocates that the reality is interpreted through the richer context of human actors who experience different circumstances within organisational and social worlds (Yin, 2011). Therefore, the qualitative method is appropriate to understand the collaboratively meaningful reality. Moreover, the realism emphasises to use scientific approach to form the theories and hypotheses about the independent existence from human mind. However, the realism distinguishes between the critical realism and direct realism (Bryman and Bell, 2015). The critical realism highlights that the reality is independent but not directly accessible via the researchers’ knowledge of it and observation, which should be uncovered by exploring underlining causes (Harreveld, 2016). Whereas, the direct realism refers to the reality is what we see. Therefore, the critical realism suits for qualitative research such as using interviews and case studies. And direct realism suits for using participant observation (Creswell and Creswell, 2017). Ontologically, there are two extreme philosophies called objectivism and subjectivism. the objectivism emphasises that there is single or multiple truth excepting the existence of social actors. Therefore, the quantitative method or mixed method is appropriate. Whereas, the subjectivism believes that the truth/truths are interpreted due to the actions of social actors (Creswell and Creswell, 2017). Therefore, the qualitative method is appropriate in order to understand insights about a situation from ill-defined data sources (Saunders, 2015). Based on the afore-discussion. This research attempts to understand the CE and its relative variables in the UK manufacturing sectors. Therefore, the perception of industrial players is important. Thus, the epistemology approach will be conducted, because it is used to understand the sources of knowledge within a particular area (Welman et al, 2005). More precisely, the positivism approach is most proper for this research. The reason is that the purpose of this research is to define the CE in the UK manufacturing industry, thus the finding should be generalized to expose the overall context of all kind of the manufacturing companies in the UK (Eisenhardt,1989). Thus, because of this paper has its limited time bar, the positivism philosophy is the best approach to follow. Therefore, this research will be conducted through quantitative method which will be discussed later.

Research Approach

This section focusses on designing the research method which will provide the logical of exploring new knowledge for the researcher and help to discover the research questions in different methods. There are two most popular research methods which are inductive method and deductive method (Saunders, 2015). The inductive approach refers to observe the factors based on the aim and objectives that are proposed during the research process. Then gives the general role based on what has been observed (Hair et al., 2016). In this approach, the phenomenon is explored based on the data collection. Therefore, this method is used to generate the theory. The deductive approach is a logical process flows the process of setting hypotheses based on the theories that are generally assumed to be true, testing the hypotheses, and confirming or rejecting the hypotheses (Hair et al., 2016). Therefore, in a deducted research, the hypotheses should be gathered through identifying the factors from literature review, then test the factors from the data analysis. Because this is a new area of research in the UK manufacturing sectors (Kirchherr, Reike and Hekkert, 2017). Therefore, the deductive approach is more appropriate to understand the concept under study in detail (Goddard and Goddard, 2014). This research will start from literature review in order to find the factors relating to the research aim and objectives of this research and then analyse the reliability of these factors in the UK manufacturing sector (Eisenhardt,1989).

Research Strategies

Saunders (2015) summarised the processes when designing a methodology. As figure 3.1 shown, this chapter mainly follows the procedures of the ‘research onion’ to develop a research design from peripheral to centre in order to identify the research design that is more appropriate for the research. The most popular research strategies are listed below including survey, case study, grounded theory and experiments (Yin, 2011).

Survey: surveys involve collecting data through questionnaire, the data should be standardised and easy to be compared (Kirchherr, Reike and Hekkert, 2017). The benefits of conducting surveys are that it allows a large amount of data to be collected in an economical method (Yin, 2011). Therefore, it can be used to understand the relationship between the analysable number of variables. Conversely, survey research encounters inflexibility and validity as respondents can only answer the particular questions without any further explanations. Therefore, the more complex reasons cannot be detected (Nardi,2018).

Experiment: the aim of the experiment is to find the causal links that independent variables have an impact on relevant dependent variables. However, there is less control over variables that lead to confounding results which is due to experimenters’ preferences (Yin, 2011).

Grounded theory: grounded theory is underpinned by the induction approach where it starts with the data collection without the constraint of a theoretical framework, then the theoretical endpoint is grounded, based on the data. The benefit of Grounded theory is that it avoids making pre-assumption and identifies what actually happen. Contrarily, this method requires large amounts of data, which are difficult to be managed and categorised (Bryant and Charmaz, 2007).

Case study: it is a method to investigate the contemporary phenomenon within its real organisational context. the advantage of conducting case study is that the research concerns dynamic populations which are difficult to follow up. The disadvantage is that the case study may be subject to selection bias (Bryant and Charmaz, 2007).

The choice of research strategy is depending on the research aim because this will be the tool of data collection. However, there is lack of attention that academia paid on CE in the UK manufacturing sectors (Kirchherr, Reike and Hekkert, 2017). According to the research aim, this paper aims to uncover the appropriate factors that enable, drive and limit the implementation of CE in the UK manufacturing sector and their relationships with business performance, business competitiveness and business sustainability. Therefore, it is essential to conduct a research based on the rationale of deduction method. This research uses survey as an appropriate tool to investigate the suitability and interactions of the various variables that were discussed in the literature review section (Welman et al, 2005). The data will be gathered through large-scale questionnaire from respondents in the UK manufacturing sector with the purpose to justify the accurate meaning and experiences associated with the phenomena (Welman, 2005).

Research Method

This section focusses on the method of data collection which is a process to discover the answers of research problem and hypotheses by collecting information from relevant sources (Yin, 2011). This research focuses on the quantitative data collection methods. The feature of this method is that, the data will be collected through questionnaire with closed-ended questions, and the data will be analysed through various mathematical calculations depending on type of expectations of the research aim and objectives. Because of this, research is based on the deductive approach where the data collection is based on theories that have been generated (Hair et al., 2016). Therefore, this research adopts quantitative methods where the questionnaire will be conducted in order to screen the finding that is appropriate for the UK manufacturing sector (Hair et al, 2010). Besides, the time horizons for this research is cross-sectional by which the data will be collected efficiently (Saunders, 2015). Quantitative data refers to the numerical data which is used to collect data that are pre-defined. Therefore, the researcher is able to define the rationale based on the emergence of findings that is from the literature review (Saunders, 2015). The reason to choose quantitative method is because that there is lack of research about the implementation of CE within the UK context. Therefore, this research aims to use a statistical model to count and classify features of CE in the UK manufacturing sector to verify insights based on the general finding from literature review. For the purpose of this research the quantitative data will be collected through 5 scale Likert questionnaires (Welman, 2005). This paper will use linear regression method via SPSS software to analyse the quantitative data collected for this research.

Sampling Process

The sampling process has three steps including identifying the target groups, choosing a proper sampling technique, and defining size of target groups (Malhotra et al, 2006). The target group is defined as the populations within the UK manufacturing sector. There are two types of sampling techniques, which are probability sampling and non-probability sampling(Bell and Harly, 2018). The former means that, the samples of the population is known and can answer the research questions. Conversely, the latter, the samples of the population that can answer the questions are unknown. In this research. In this research, the probability sampling techniques are only method to obtain the samples in which the stratified random sampling techniques will be applied due to the characteristics of sampling frames that have relevant strata and contain period patterns. The benefit of probability sampling is that it has higher level of reliability and no sampling bias (Bell and Harly, 2018). The survey questionnaire will be generated through the Qualtrics platform. The questionnaire is shared to the email of businesses in the manufacturing industry. Due to the fact that, the data is collected from a single researcher in a finite time. There is a need for adopting adequate sampling techniques to screen populations that are most capable of answering the questions. The ideal population of this research is the manufacturing sector within the UK. The questionnaire is the first approach of data collection, and this research is designed to use a minimum of 80 questionnaires where the confidence level of the samples is designed to reach the 95% with 5% margin of error. Since the data is analysed. Questionnaire design The design of questionnaire aims to obtain drivers, enablers and barriers of circular economy in the UK manufacturing sector. Kirchherr, Reike and Hekkert (2017) and Kumar et al. (2019) suggested that, the layout of questionnaire follows a structured sequence and gives instructions to respondents on question answering in order to get the data that meets the research objectives. The sequence of the questionnaire is organised by using funnel method that starts from the general knowledges to more deeper ones of CE. The questionnaire consists of 5 blocks in order to test following variables: Knowledge and level of Circular Economy Principles, Circular economy principles (6Rs), Drivers Enablers and Barriers of Circular Economy, Business Performance, sustainability and competitiveness of CE and Demographics. The measures are measured on a 5-point Likert scales (Welman, 2015). Table 3.1 below illustrates the questions for each block and its measures. The whole online questionnaire is in appendix 1. The link for the online questionnaire is: https://warwickwmg.eu.qualtrics.com/jfe/form/SV_5mPSzpqBXrpJ9aZ

Table 1. questionnaire questions, measures and their sources

Data Analysis methods

In quantitative data analysis, the raw numbers will be screened into meaningful data by critical thinking (Saunders, 2015). The data will be developed as hypotheses and analysed through linear regression method by SPSS. The quantitative data analysis includes frequencies, means of variables and the relationships of variable will be analysed trough the linear analysis. The output can be in the forms of graphs, charts and statistics, which are depending on where it is best to represent the context. The process of quantitative data analysis is shown below (Hair et al., 2016).

Data collection；preparation of data, input of data into SPSS

Data reduction；organising simplifying the data in a way that is meaningful data analysis: Using the most appropriate statistics to analyse the data, and analyse the relationships of the data.

Data display；organising the data and finding the links between findings and existing theories, then using the appropriate table/diagrams to display data according to research aim and objectives

Research Ethics

Research ethics are the regulations that the researcher must observe it during the entire process of designing, processing and illustrating the finding. Furthermore, the researcher must respect the intended and real participants' rights regarding privacy. This report follows four principles of research ethics

Avoid the risk of harm to participants

The first principle that the researcher must be considering is to avoid harms. Namely, the researcher should assess the harms and benefits that would have adverse impact on any of the participants during the designing stage of the study. Furthermore, the researcher must modify the study to prevent unanticipated harmful impacts during the designing stage of the study.

Respect confidentiality and privacy

The researcher should respect and protect the participants’ privacy and confidentiality. The researcher should also understand the requirements that are required by participants before making contact. Also, the researcher will discuss the limits of confidentiality with participants and give detail about how to detail the data is required from participants and how to use their data. Moreover, the researcher should protect the participants' privacy regardless of whether or not there is a requirement of anonymity.

Conclusion

This chapter provided a framework for the research method. It started from the research philosophy to underpin the rationale of whole research and narrowed down to the data analysis to collate the outcome of the research. In the end, the several ethical issues were highlighted in order to ensure the ethical integrity during the whole period of dissertation.

Data Analysis

Introduction

This chapter implements the descriptive data analysis method and scale development process to reveal the theoretical variables that were collected from literature review chapter and were not directly observable (Guest and Namey, 2015). Firstly, the data reduction and missing value analysis will be conducted, and the descriptive analysis is carried out in order to present an entire profile of the sample. Secondly the characteristics of all samples will be described by comparing their frequencies. Thirdly, the reliability assessment will be used to test the reliability of the data collected. Next is the assessment of one-way ANOVA. Moreover, validity assessment will be conducted. The last is linear regression analysis.

Missing Value Analysis and Reverse coded items

In the data cleaning stage, the data sets are processed for analysis. There were total 106 responses received, in which 83 participants answered all questions and 23 responses were cleaned due to a lot of missing values (more than 90% unanswered questions). Thus, sample size of 83 is adopted for the analysis. Moreover, there were no reverse coded items in the measure as all code items are positively worded. Variables of the questionnaire are coded, abbreviations for each variable are shown table 4.1. Therefore, the data is enabled to be processing for further analysis in IBM SPSS Statistics 25 software package. The Abbreviations for each of variables are listed in table below

Sample Characteristics

In this initial stage, it is important to generate a statistical impression concerning the characteristics of the main samples. In this descriptive statistic, the very first stage is to illustrate characteristics of sample populations. Due to this research adopted the stratified sampling method, where samples were drawn randomly from manufacturing sector in the UK. Therefore, this chapter mainly divided into two categories to identify the characteristics of individual and organisation. The organisational characteristics include the data set of that Sector that company belongs to (SCB), Corporate Age of Companies (CAC) and level of Adoption of circular economy (LD). On the other hand, the individual (respondents) characteristics include the data set of that Working Age of Respondents (WAR). The reason for analysing aforementioned characteristics is to determine factors than may impact the choice of answer of respondents. and also, the performance of 6Rs and the Drivers, Enablers and Barriers may vary in term of aforementioned characteristics. This stage will test the frequency for each of variables in their data set. The analysis of sample characteristics includes the test for means, frequency, maximum and minimum value, and standard deviation.

Sector of Companies (SCB)

The sector of company refers to type of area that companies are located in manufacturing industry. As illustrated in figure 4.1, there were out of 83 participants respondents given 9 options. They are widely spread to various sectors in the manufacturing industry. The majority of respondents chose ‘other manufacturing’ option i.e. 31.33 %. The Food and Beverage sectors account for the second largest proportion at 21.69 %. Automotive industry represents 18.07%, while construction and building products account for 10.84%. Moreover, chemical, aerospace and defence, and oil and gas refining represent 7.23%, 6.02% and 2.41% respectively. Finally, cleaning technologies and packaging account for the least proportion of respondents at just 1.2% equally. The mean is 4.87 and standard deviation is 3.279.

Corporate Age of company (CAC)

The company’s age is a variable of this research. As seen from figure 4.2, it is obvious that the majority of companies have been active between 1-5 years. The second largest proportion of companies have been around more than 10 years and account for 25.3%. Moreover, 22.89 % of companies have been operated for less than one years. Lastly, the least percentage of companies aged between 5 and 10 years. The mean is 2.47 and standard deviation is 1.108.

Level of adoption of CE (LD)

Figure 4.3 illustrates the level of adoption of CE principles in respondents’ companies. The largest proportion of companies have limited adoption of CE, which account for 34.94 % of total respondents. Nearly 30% of participants adopt some degree of CE principles. The rest of slices account for quarter of total participants in where 14.46 % of respondents answered that they have high adoption of CE, this conversely 15.66% of companies do not adopt CE practices. However, 4.82% of companies which account for the lowest percentage adopt CE to a great extent. The mean is 2.58 and the standard deviation is 1.072, which means the data is closely clustered around the mean.

Working Age of Respondents

As far as the working age of respondents is considered as it is displayed in figure 4.4. Coincidentally, the respondents that have been hired less than one years and between 1-2 years account for the same and largest proportionately i.e. 33.73%. Whereas, only a very limited percentage of respondents have been standing between 1-5 years i.e. 13.25% and while 19.28% of respondents chose more than 5 years. The mean is 2.18 and the standard deviation is 1.106.

Measure Development Procedures

A clear ‘psychometric properties’ of scale can guide researcher to have clear methodology to ensure the reliable and valid data to be analysed (Despoudi, 2016). Therefore, this sector identifies and eliminates the data that are poorly performed. figure 5 describes the procedures, which are conducted in this data analysis chapter.

Reliability Assessment

Statistically, the term reliability refers to reproducibility as a measuring procedure to test the accuracy to robustness (Cleophas and Zwinderman, 2019). There are various methods to test the reliability i.e. test-retest reliability and internal consistency. The term internal consistency can be applied to test multiple items that have same construct and intercorrelate with others. Lee et al. (2008) pointed out that, all the multiple items need to be tested in or der to ensure their reliability. In this section, there are 9 multiple items as listed in table 4.1 1 i.e. RD, RUMR, RC, DOCE, EOCE, BOCE, BP, SB, BP2. Here applied Cronbach’s Alpha to test the scale reliability of multiple items, which is because it is best to identify the reliability of multiple Likert questions (Churchill, 1979). The Cronbach’s Alpha provides indicators on whether the model’s constructs conform to the aim of the researcher and guides which items should be delated from the construct. For each item, If the indicator of Cronbach’s Alpha is greater and equal to 0.70, which means the measure is reliable. Also, the average Cronbach’s Alpha of all items should be better greater than 0.8. As table 1 shown, the Cronbach’s Alpha of each of items are greater than 0.8. Therefore, here conclude that all the multi-item measures are tested as highly reliable. Thus, the further analysis can be carried out.

Sample Features (mean)

The aim of this section is to critically analyse the mean and standard deviation of each data set in order to measure the average distance and the degree of dispersion of the data in their data set. This section allocates all variables into four dimensions where each variable has comparable attributes within their dimensions as listed below. The analysis includes standard deviation, means, maximum and minimum value of variables.

Dimension one: DOCE, EOCE, BOCE

Dimension two: RLCE, LD

Dimension three: RD, RUMP, RC

Dimension four: BP, SB, BP2

The first dimension aims to test the average level of DOCE, EOCE, BOCE respectively, and to justify the most and least influential factors that have impact on drivers, enablers and barriers correspondingly. The second-dimension testes level of the respondents’ knowledge about CE and level of adoption of CE in their business operations. The third dimension identifies the level of efficiency regarding to the implementation of 6Rs which is divided in to three activities including RD, RUMP and RC. The last dimension compares the average score of BP, SB and BP2 in order to prioritize the contribution of CE toward business performance and sustainability. In addition, the last dimension also compares the sub-categories of each BP, SB and BP2 to identify the most and least contribution toward BP, SB and BP2 correspondingly.

Mean and Standard Deviation of DOCE, EOCE and BOCE

This section compares the average level of responders’ attitude towards Drivers, Enablers and Barriers of CE. As table 2 displayed, the column of question number indicates the sub-questions of DOCE, EOCE and BOCE correspondingly as referring to appendices 1. The column of mean indicates the total participants that answered this question. The mean refers to the average score of each data set. The standard deviation indicates the level of fluctuation around the mean. In this analysis, all the standard deviations are around the 1, which indicates that the most data are close to average. For the DOCE, the Q5_13 and the Q5_18 are the highest mean i.e. 4.16, which indicates that the primary drivers of CE are ‘achieving long term sustainability’ and ‘industry pressure’. Whereas, the Q5_3 is the lowest mean (3.64) but the gap with the highest mean is not big, which however indicates that ‘reduce operational costs’ is the least important driver of CE. Nevertheless, the mean of DOCE (overall mean of all the DOCE) is 3.967, which indicates that, all the drivers seem to be important and there is no significant difference indicated by measure of mean.

For the EOCE, there are not significant gaps between all variables as their means are closely similar. The largest mean is 3.46 which is occupied by Q6_10 (Part of Corporate social responsibility strategy) and Q6_13 (incentives for the efforts of environmentally friendly practice). Whereas, the smallest mean is 3.22. which is possessed by Q6_12 (Inclusion of customer). Furthermore, the overall mean of EOCE is 3.5439.

For the BOCE, the grand average for is 3.3226. The Q7_8 account for the largest mean i.e. 3.66, where the most of respondent’s regard ‘high upfront investment’ as primary barriers of CE. Contrarily, Q7_4 represents the smallest mean i.e. 3.11 where ‘non-supportive governmental and social institutions’ is treated as a barrier with the smallest influence.

Mean and Standard deviation of RLCE and LD

As seen from Table 4.6, respondents have moderate understanding toward CE as the mean of RLCE is 2.53 and standard deviation is 0.915, which means the most of scores are not spread out from mean. Similarly, companies are only adopted some level of circular economy principles in business operation as the mean of LD is 2.58 with low standard deviation (1.072)

Mean and Standard deviation of RD, RUMR and RC

This dimension analyses the means for RD, RUMP, RC. For the RD, the mean of Q17_1 is larger than Q17_2. Therefore, respondents tended to use resource in an efficient way than use renewable inputs. For the RUMR, the largest mean is possessed by Q18_1 which is 2.71, which indicates that most proportion of respondents identify ways to reintroduce end-of-life products into their or other supply chains. However, the smallest mean is 2.61 (Q18_4), which means that the least of respondents chose to refurbish products. For the RC, the mean of Q19_1 is higher than Q19_2. Therefore, the most respondents prefer to process products into new material to produce new products rather than to collect products from customers for recycling. However, the grand mean of RD is greater than others. Therefore, RD is more preferred by respondents in their business operation.

Mean and Standard deviation of BP, SBM BP2

In general, Participants estimated that the extent to which the CE contributed to neutral business performance regarding to BP, SB, BP2. In order to analyse from grand mean, the contribution of CE to BP is greater than SB and BP2. For the BP, the Q8_1 account for the largest mean (3.39). Therefore, the CE improved the efficiency and operational performance most. The mean of Q8_2 (sales growth) is regarded as the smallest number of BP but it is extremally close to the largest mean of BP. For the SB, Q9_05 is the largest mean i.e. 3.30 where ‘improvement of work environment’ gained the highest score. In contrast, Q9_4 (improvement of relationship with community) gained the lowest mean i.e. 3.16. For the SB, the highest mean is 3.46 (Q10_3), where the CE practice has contributed to ‘customer retention’ the most. Whereas, the lowest mean is 3.25 (Q10_5), which indicates that the CE contribute little to attain desired growth over the last two years.

Validity Assessment

Validity assessment is used to test the degree to which whether a scale-measure can represent what it claims to measure (Carmines and Zeller, 2008). Here adopts internal consistency reliability in which it adopts the Alpha (α) coefficient to test the validity of the questionnaire. This sector is divided into two parts, the first will critically analyse the correlation coefficient between DOCE, EOCE and BOCE. The second will analyse the correlation coefficient between RD、RUMR, RC, BP and LD. Table 4.9 indicates the correlation between DOCE, EOCE and BOCE. As a result, all their P-values are less than 0.05. Therefore, there are statistically significant positive correlations between all three variables. In addition, if the P-value is less than 0.1, the correlations are statistically highly significant. Thus, here concludes that the correlations of all variables are statistically highly significant.

As table 4.10 displayed. Based on the correlation analysis between RC and BP, the correlation coefficient is 0.255* where the significance level is 0.2 (greater than 0.1 and less than 0.5). Therefore, there is statistically significant between the correlations of RC and BP. Other than that, all the other P-values of RD、RUMR, RC, BP and LD are less than 0.01. Therefore, the correlations of all the other variables are statistically positively significant.

Hypothesis highlight

This section highlights the finding from literature review sector in order to propose hypothesis for justification.

Hypothesis 1 (H1): When there is effect of the drivers of circular economy (DOCE) that is positive and Business performance (BP), business sustainability (SB) and business competitiveness (BP2) will be negative against the tendency of drivers of circular economy.

Hypothesis 2 (H2): When there is effect of the Enablers of circular economy (EOCE) that is positive then Business performance, business sustainability and business competitiveness will be positive too.

Hypothesis 3 (H3): When there is effect of barriers of circular economy (BOCE)that is positive then Business performance, business sustainability and business competitiveness will be negative against the tendency of barriers of circular economy.

Hypothesis 4 (H4): When there is relative success of reduce (RD), which is due to the positive increase in Business performance, business sustainability and business competitiveness .

Hypothesis 5 (H5): When there is relative success of Reuse, Re-Manufacturing, Refurbish (RUMP)，which is due to the positive increase in Business performance, business sustainability and business competitiveness .

Hypothesis 6 (H6): When there is relative success of recycle (RC), which is due to the positive increase in Business performance, business sustainability and business competitiveness.

Linear Regression

The linear regression method is used to test whether there are statistically significant relationships between one dependent variable and several independent variables. More precisely, whether the predictor variables (independent variables) can statistically significantly predict the outcome variable (dependent variable). There are three steps to justify the hypothesis progressively. The first step is to test the value of R2, which is an indicator about the percentage of the variance in dependent variables that independent variables can describe collectively (Macinnes, 2017). The second step is to test the overall predictive capability of independent variables which indicate the variability in response to the corresponding dependent variable. The p-value and the F ratio are used to test the overall strength of association between a dependent variable and several independent variables. If the P-value is less than alpha 0 .5, the overall regression modal is significant, and vice versa (Coolican, 2014). After the P value is justified, the F ratio is used to indicate the degree of freedom, a large F ration shows the large variation between the means of dependent variable and independent variables. The last step uses P-value in Coefficients table to read the particular size of effect that one independent variable has on the dependent variable. If the P-value is less than alpha value of 0.5, relationship between two particular variables are statistically significant (Macinnes, 2017). Then the beta value is used to indicate the direction (positive and negative) and size of the effect in which when an independent variable increase or decrease by one the dependent variable will be expected to increase or decrease by the beta value (Macinnes, 2017). The aim of the linear regression method is to identify the degree to which there are relationships between one dependent variable with one or more independent variables. This chapter is divided into two sections in order to test the statistic relationship between a dependent variable and its relative independent variables. the second section (hypothesis 1,2,3) tests the statistical significance between the dependent variables of DOCE, EOCE, BOCE and the independent variables of BP, SB, BP2. The last section includes the hypothesis 4, 5, 6, the statistical relationship between independent variables of SB, BP, BP2 and dependent variables of RD, RUMP, RC will be tested. The SPSS output of ANOVA table and Model summary table will be displayed in appendices.

Test of H1, H2, H3

H1(Appendix 3)

This section tests the relationship between independent variables of BP, BP2 and SB dependent variable of DOCE. The R2 is 0.281 in which 28% of total variation can be explained by independent variables. The Coefficients table indicates that the P-value of each BP, SB and BP2 is greater than 0.05. Therefore, there is not statistically significant relationship between the Dependent variable of DOCE and independent variables of BP, BP2 and SB Thus, the hypothesis 1 is rejected as drivers of CE does not relate to the business performance.

H2 (Appendix 4)

This section sets EOCE as dependent variables and BP, BP2 and SB as independent variables. There are 43.1% of variability (R2=0.431) can be described by independent variables. Moreover, the overall regression model is significant as the P-value (0.00) of ANOVA table indicates that there is at least one relationship between the dependent variable and the independent variables that is statistically significant. The table of Coefficients (table 4.12) describes which relationship is statistically significant. Firstly, the relationship between EOCE and SB is statistically significant (P-value = 0.015) where each additional positive 1-unit increase in SB will lead to EOCE to increase by 1.157 beta value. Whereas, the beta value of BP and BP2 are greater than 0.05. Thus, there are not statistically significant relationship between dependent variable of EOCE and independent variables of BP and BP2. As a result, the Hypothesis 2 are rejected in which only the relationship between SB and EOCE satisfied the assumption.

H3 (Appendix 5).

This section sets BOCE as dependent variable and BP2, BP and SB as independent variables. The R2 indicates that There are 28.4% of total variation can be explained by independent variables. Also, the overall regression model is significant as the ANOVA tale indicates the P-value is 0.00, which is less than 0.5. As seen from the table 4.13, the P-value of SB is less than 0.05 which indicates that there is statistically significant relationship between SB and BOCE. Moreover, the beta value of SB shows a positive effect. Therefore, here concludes that the Hypothesis 3 is rejected as there are not obvious relationship between BP-BOCE and BP2-BOCE. Also, there is a positive relationship between SB and BOCE, which is against the Hypothesis 3.

Hypothesis 4, 5 and 6

H4 Appendix 6

The aim of this section is to identify whether the positive change in independent variables that are SB, BP and BP2 can cause positive effect on RD that is dependent variable. The R2 indicates that the 16.2% of variation is RD can be explained by SB, BP and BP2. The P-value in ANOVA table indicates that the overall regression model is statistically significant. However, the Coefficients table reveals the relationships between each individual variables and dependent variable. As table 4.14 indicates the P-value of each BP, SB and BP2 is greater than 0.05. Thus, the hypothesis 4 can be rejected as there is not statistically significant.

H5 Appendix 7

For the hypothesis 5, the dependent variable is RUMR, and the independent variables are BP, SB, BP2. The R2 is 0.202, which describes that, there are 20.2% of variations in RUMP can be explained by SB, BP and BP2. Moreover, there is at least one independent variable can have statistically significant effect on dependent variables as the P-value in ANOVA table is 0.00. Thus, moving on to the Coefficients table (table 4.15), the P-value of SB is 0.02 which is less than 0.05, and the beta value of SB also shows a positive trend (0.412). Therefore, the every 1-unit increase in SB will cause the RUMR increased by the 0.412 that is beta value of SB. However, the P-value of each BP and SB does not statistically significant. Therefore, the hypothesis 5 is rejected as only the relationship between SB and RD conforms to hypothesis, but the other two do not.

H6 Appendix 8

The section sims to verify the hypothesis that ‘When there is positive effect of RC, the SB, BP and BP2 will be positive too’. This section sets the SB, BP and BP2 as independent variable, the RC as dependent variable. The R2 indicates that, there are nicely 49.9% of variations in RUMR can be explained by BP, SB and BP2. The ANOVA table indicates that the overall regression model is statistically significant. For the coefficient table, only the P-value of SB is less than 0.05 and the beta value of SB is 0. 412, which is positive. Thus, the SB have statistically positive effect on RUMP. Here occludes that the hypothesis 6 is rejected, which is because the BP and BP2 failed to prove the positive effect of relationship.

conclusion

So far, all the hypotheses have been tested regarding the effect of business performance, business competitiveness and sustainability on drivers, enablers, barriers of CE. There are three hypotheses that are set for verifying their relationships, which are H1, H2 and H3, and the hypothesis testing was that, all the hypotheses were rejected as shown in table 4.17. For the H1, the result indicates that the Drivers of CE is irrelevant with business performance, business competitiveness and business sustainability. For the H2, the result shows that business sustainability and business competitiveness have positive effect on the enablers of CE. However, the business performance is irrelevant with the enablers of CE. For the H3, the result indicates that the barriers of CE are irrelevant with business performance and business competitiveness. And there is a result that demonstrates an opposite-result to H3 that is when the when companies’ capability of sustainability is increased, then the barriers of CE are consequently increased too. The last goal stated by objective 4 is to verify the effect of business performance, business sustainability and business competitiveness on the performance of reduce, RUMR (Reuse, Repairing, Re-Manufacturing, Refurbish) and recycle. There are three hypotheses, which are H4, H5 and H6. The results are shown below. The H4 is rejected due to the performance of BP, SB and BP2 are irrelevant with the performance of reduce. The result of H5 indicates that the business performance and business competitiveness are irrelevant with the performance of RUMR. However, the business sustainability has the positive relationship with RUMR, which reflect that when the business performance of sustainability is increased, which will lead to the performance of RUMR increase as well. The result of H6 indicates that the performances of business competitiveness, business sustainability and business performance are irrelevant with recycle.

Discussion, conclusion, limitation and further research

Introduction

The aim of this chapter is to interpret the significance of the research finding regarding the research aim and research objectives of this dissertation. Precisely, this chapter will conclude the entire research finding by discussing the results from the data analysis chapter, draw implication for the finding from literature review, and reflect on a set of practical implications on the context of the research. Firstly, the results of this research are presented by comparing with the literature finding. Secondly, having hypothesis confirmed or rejected, the theoretical and practical contribution of this research are discussed critically.

Research summary

The aim of this section is to interpret and explain the key result that the researcher has been found. In recently four decades, the concept of CE and its drivers, enablers and barriers has received an increasingly number of attentions because of its issues related to the economic benefits (sustainable revenue generation), the resource scarcity (eliminating the risk of price volatility) and the environmental impact (solid waste, landfill, emissions) etc. (Lieder and Rashid, 2016). The realisation of the CE is reflected in the achievement of 6RS. The principle of 6Rs is embedded into distinct material flows correspondingly with their particular purpose, which will help to optimise the value of waste by creating a closed material flow through both internal and external supply chain loops. Thus, the concept of CE is closely related to the terms competitive advantage, business performance and sustainability (Tolio, 2017). However, many authors possessed different view about the CE in a general sense and the field of UK need to be examined (Gusmerotti et al., 2019). Therefore, this section will go step by step to highlight main finding about the drivers, enablers and barriers toward CE, and their relationships with competitive advantage, business performance and sustainability.

Drivers, Barriers and Barriers in the UK Manufacturing Sector

Following a systematic design, this dissertation adopted a questionnaire to collect data and achieved the objectives. the out of 83 questionnaires were analysed and assessed. Table 2 indicates all the key elements of this research and their relationships within the conceptual framework. the Figure 1 (research objectives) demonstrated a systematic research design of this thesis. As objective 4 indicates that, the first step is to define the drivers, enablers and barriers in the UK manufacturing sector. Different studies have stressed various drivers about the CE. the result of this study (table 5.1) indicated that, the primary drivers in the UK manufacturing sector are the industrial pressure forces the implementation of environment standard（EM Foundation, 2014), achieving long term sustainability (Batista et al., 2018), improving brand reputation (Govindan and Hasanagic, 2018), improvement of business competitiveness (e.g. through product-life extension) (cheng, 2007), Avoiding regulative costs of environmental pollution and waste (Kumar et al., 2019), Improving material / resource efficiency (Rashid et al., 2013), and New value stream through utilisation of by-products and waste (Lieder and Rashid, 2016). Therefore, the result of this research is supported by the current literature that advocated the primary drivers of the CE are irrelevant with environmental aspects from Testa, Boiral and Iraldo (2018), Lieder and Rashid (2016), Kumar et al. (2019), Gusmerotti et al. (2019). For the other drivers that have been summarised in the literature review sector, that are being irrelevant in this chapter as the respondents held neutral attitudes toward them. the finding of this research is opposite to current researches that emphasized on that the drivers of the CE are relating to the resource scarcity (Georgesçu-Roegen's, 1971), creation of jobs and sustainable social development (cheng, 2007; Morone and Navia, 2016; Govindan and Hasanagic, 2018), government supports in relation to preferential policy and infrastructure (Wysokińska, 2018; Clark et al., 2016; Govindan and Hasanagic, 2018), Environmental impacts (Wysokińska, 2018), New value stream through utilisation of by-products and waste (Lieder and Rashid, 2016), CE related Infrastructures (de Jesus and Mendonça, 2018), avoidance of regulative costs (Kumar et al., 2019).

For the enablers of the CE, there is no obvious answer indicates the most important enablers in the UK manufacturing sector as the respondents held neutral attitude toward all the enablers that were collected from literature review chapter and all the enablers are account for the same importance. this research finding is supported by the current literature from Winans, Kendall and Deng (2017), Rahimifard and Clegg (2007), Lieder and Rashid (2016), Lieder and Rashid (2016) and Jesus and Mendonça (2018) who pointed out that there are no most important enablers of CE and all enablers are mutually interacted to facilitate the CE, the success of CE requires a total effort between national institutions from up-bottom and companies from bottom-up concurrently to achieve a system shifting of business model. Therefore, the success of CE requires the collaboration between both public institutions and the industrial actors to achieve a productive economy that is environmentally and regeneratively. However, there are two enablers that gained the highest vote in this research. The first is that The CE practices of company should be motivated by governments and societies in term of the financial and reputational incentives (Testa, Boiral and Iraldo, 2018). Also, the most of respondents agree that the CSR is critical factor to enable the implantation of CE as it provides a systematic logic of the connection between environmentally friendly practice and business profit (Carroll, 1979). Furthermore, it is worthy to highlight that the other enablers are also critical to enable the implementation of CE; such as the leadership to facilitate the higher level of collaboration (Batista, 2018), the culture of the CE mindset (Batista, 2018), the Networking with like-minded players to support collaboration (Rizos et al., 2016), the geographical proximity (i.e. maximum value of resources always happen in a functional distance) (Rizos et al., 2016), the supportive policy and regulations (Rizos et al., 2016), the consumer responsibility (Gallaud and Laperche, 2016 ), Environmental protection infrastructure (Ma, Song and Zhou, 2018), the green technology (Joseph Nye,2006), and the reverse supply chain (de Jesus and Mendonça, 2018).

For the barriers of the CE, there are no significant differences between the importance of all barriers. In another word. There is no fatal barrier to obstacle the implementation of CE in the UK manufacturing sector as all responses are toward the moderate attitude. The ‘economic barriers’ is examined as the most the biggest obstacle that business faced. Liu and Bai (2014) pointed out that, the companies in manufacturing sector are afraid to invest in the CE practices due to the unverified financial benefits and a high upfront investment. Moreover, the lack of public awareness (Winans et al., 2017), lack of governmental attention for environmental protection (government provides unfavourable legal and policy system for CE) (Naustdalslid, J. 2014) and the technology challenges are verified as important barriers of the CE practice (Gregson et al., 2015).

the result of this research indicated that the business performance, business sustainability and business competitiveness do not have significant relationship with the driver of CE and barriers of CE (table 4.17). the result indicates that the changing business performance (operational performance, sales growth and market share), performance of sustainability ( operational efficiency, reduction of wastes and improvement of living quality of community) and competitiveness of business ( achieving customer satisfaction and securing desired market share) do not influence on the drivers and barriers of CE. This result is against the current literature that advocated the drivers of CE is relating to the business performance, business sustainability and business competitiveness from Gusmerotti et al., (2019), Winans, Kendall and Deng (2017), Abreu and Ceglia (2018), Lieder and Rashid (2016), Shi and Yu (2014), de Jesus and Mendonça (2018), WEF (2014), Pomponi and Moncaster, (2017), Testa, Boiral and Iraldo (2018), Kumar et al. (2019), Wysokińska (2018), Sperling (2017). Moreover, the result of this research is also against with the current literature that advocated the barriers of CE have negative relationship with business performance, business competitiveness and business competitiveness from Moncaster (2017), Su et al. (2013), Zhang (2010), Bicket (2014), EMF (2013), Pan et al. (2015), Nausrdalsid (2014), Geng et al. (2014), Johnson and Suskewicz (2009), Watkins et al. (2013), Kaenzig and Wüstenhagen (2010), Liu and Bai (2014), Kumar et al. (2019), The result also indicates that the business performance and business competitiveness are irrelevant with enablers of CE. this result is opposite to the current literature that stressed the positive relationship between enablers of CE and business performance, business competitiveness from Wysokińska (2018), de Jesus and Mendonça (2018), Jackson, Lederwasch and Giurco (2014), Joseph Nye (2006), Mendonca (2014), Ma, Song and Zhou (2018), Ma, Song and Zhou (2018), Batista (2018), Rizos et al. (2016), Testa, Boiral and Iraldo (2018), Carroll (1979), Szutowski et al. (2017), Szutowski et al. (2017), Genovese, A. et al. (2017) and Hu et al. (2010). However, this research justified that the business sustainability has significant positive effect on the enablers of CE, as if there is positive increase in the sustainability performance of business, enablers of CE will be satisfied significantly. Therefore, this research adds to current literature about the positive relationship between enablers of CE and business sustainability (Joseph Nye, 2006; Mendonca,2014; de Jesus and Mendonça, 2018; Jackson, Lederwasch and Giurco, 2014; Jackson, Lederwasch and Giurco, 2014; Kama, 2015; Gusmerotti et al., 2019; Gusmerotti et al., 2019; Ion and Mihaela, 2018; Alfonso, 2019; Alfonso, 2019) by saying that if there is improvement business sustainability, there will be improvement in relation to the enablers of CE. The business performance, business sustainability and business competitiveness are irrelevant with the performance of 6Rs except from the effect of business sustainability on RUMP. This result is conflicting with the current literature that stressed the significant positive relationship between business performance, business sustainability, business competitiveness with activities of 6Rs expect for the relationship between business performance and RUMP from Manickam and Duraisamy (2019), Frodermann (2018), Geng et al. (2012), Guide and Van Wassenhove (2009), Stahel (2013), McDonough and Braungart (2013), Towards the Circular Economy (2019), Ghidellini et al. (2011). However, this research confirms that the activities of RUMP (Reuse, Repairing, Re-manufacturing, Refurbish) are positively closely bound up with business sustainability. Therefore, the manufacturing companies should consider improving their performance of RUMP activities in their supply chain if they want to improve their sustainability performance. Therefore, this finding adds to the current literature about the positive relationship between business sustainability and RUMP activities (Ghidellini et al., 2011; Towards the Circular Economy, 2019; Ghidellini et al., 2011; Ghidellini et al., 2011) by saying if there is positive effect of business sustainability, there is an improvement in RUMP activities. Apparently, as the philosophy of CE is to preserve the energy/ resource for satisfying the future generations’ demand while satisfying the current demand (Geissdoerfer et ai., 2018). Indeed, the definition of CE is to achieve a long-lasting sustainable development of environment, society and economy. Also, the most of respondents chose the CSR as a most important enablers of implementing CE, which emphasize the role of the company that is social and environment accountable. Therefore, it is evident that the concept of CE is more emphases on the sustainability rather than short term profitability (EMF, 2018). Hence, it is reasonable that the main drivers of CE are improving brand image and achieving long term sustainability. Finally, it is clear that for the reason of that there is no significant enablers and barriers of CE is due to that the benefit of CE is unverified (Liu and Bai, 2014), and the complexity of CE makes the enablers and barriers of CE are difficult to be exposed in the real practice.

Thus, based on the afore-analysis of this chapter, the author summarised a CE pyramid that is dedicated for the UK manufacturing sector (Figure 5.1). This pyramid is summarised based on the enablers of CE and RUMP activities which have positive effect on the business sustainability. This pyramid is a bottom-up approach including three levels which are Micro level (supply chain level), Meso level (social institution and society) and Macro level (regional) , the very bottom is micro level and the basic and most essential for the manufacturing companies to achieve the CE. Liu and Bai (2014) pointed out that the primary barrier of business to implement CE is the high-upfront investment and unverified financial benefits. In addition, the CSR is voted as the prior enabler of CE. Therefore, for the implementation of CE activities, the profit must come first. Namely, the manufacturing companies must ensure their business to be profitable that is only channel to collaborate with and benefit to long term sustainable social, environment and economic benefits (Carroll, 1979). In order to achieve a profitable CE model, there are three factors are essential in order to build up a supply chain, that is validated for RUMP activities (Reuse, Repairing, Re-manufacturing, Refurbish). The first is the collaboration with like-minded supply chain plyers to ensure the commitment and collaboration towards CE (Rizos et al., 2016). The second is leadership, the manufacturing companies should have clear leadership to promote the desired culture among their supply chain (Rahimifard and Clegg, 2007). The last is that company should ensure the technology is workable to facilitate the CE activities (Mendonca, 2014). Having a capability to generate profit through CE activities, then the second layer is meso level. there is a need for collaboration between manufacturing companies and social institutions (Naustdalslid, 2014), which is because of the principle of CE that requires to change the consumption behaviour of customers from the ownership of the product to the user of the product (Moncaster,2017). Therefore, the social institution is critical to promote the CE through diverse way such as media and publicity work to ensure the disposed products can be flow back to supply chain on time (Winans et al., 2017). The top layer is the macro level, the business should be social and environmental accountability to improve the performance of CE continuously (Chiaroni and Chiesa, 2017). Therefore, the business can continue contribute to society to gain the high reputation which is regarded as an irreproducible competitive advantage (Chiaroni and Chiesa, 2017).

Theoretical and Practical Contribution

Contribution to the circular supply chain framework in the UK manufacturing context

As in all studies about CE, all the researches are limited to the reginoal comtext and there is no generalised reseach finding about the CE in the UK manufacturing secor (Batista, 2018). This research provides the first comprehensive the current application of CE in the UK manufacturing sector and the particular drivers, enablers and barriers that are only fitting to the UK context. Furthermore, this research analysed the effect of business performance, business sustainability and business competitiveness on the drivers, enablers, barriers and 6Rs in the UK manufacturing sector, which is also unverified by the current literatures.

Practical contribution to the CE practitioners

The CE is a method to drive business towards a long-lasting sustainable development through a mutual development of economic, social and environmental values. Therefore, the practice of CE will bring business with unique competitive advantages that is admired by wide range of stakeholders (societies, governmental bodies, industrial institutions). Although the business performance and business competitiveness cannot be linked to the performance of CE in a short period of time. The concept of CE brings business towards a next level of sustainability and which is difficult to be overtaken (Abu-Ghunmi et al., 2016) A set of managerial recommendations are offered by this research, concerning the managerial philosophy (CSR), design of supply chain, leadership, collaborations which can boost the implementation of CE by manufacturing business in the UK. For example, this research highlighted the importance of CSR as a backup enabler to help managers developing the strategies underpin their company’s CE objectives. Also, this research pointed out the importance of leadership and collaboration with like-minded industrial players that can facilitate the efficiency of CE in their supply chain. The sustainability performance of business will be improved in line with improvement of some of the CE (6Rs) activities such as reuse, repairing, re-manufacturing and refurbish. Such activities will contribute to not only resource efficiency across the processes but also the improvement of relationship with the stakeholders (Eskandarpour et al. 2015).

Limitation and further suggestion

The author admits that, there are few limitations of this research, since the limited amount of data were collected from wide range of companies in the UK manufacturing sector. The below will explain the limitation and further suggestions about this research.

Measure of CE and its Elements

Several elements of CE in the manufacturing sector were analysed and discovered in this study. This research provides a foundation for future research into the CE from various perspectives for example drivers, enablers, barriers, 6Rs and their interrelations with business performance, business competitiveness, business sustainability. In addition, the result of this research shows the generalized finding of CE in the UK manufacturing sector. Therefore, the further researches are encouraged to explore the application of CE in other industrial or regional context. Furthermore, due to that the data were collected from the limited populations, and there are some findings, which are against some of the current literature such as the business performance and business competitiveness are irrelevant with the principles of CE. Thus, there is a need for the further justification of the research finding of this thesis in the context of the UK manufacturing sector.

Limitations of methodology

There are several limitations of the research methodology. Firstly, the research only adopted survey questionnaire to collect data through various sectors in the UK manufacturing industry. Therefore, the future researchers could conduct research by collecting more data in few manufacturing sectors in order to increase the accuracy of the result for some particular sector. Moreover, this research only adopted the quantitative method to screen the finding to most appropriate for the UK manufacturing context. the future research could use more research methods to identify the in-depth view of this research topic regarding the drivers, enablers and barriers of CE and their contributions to the business performance, business sustainability and business competitiveness. The research methods can include the experiment, interview and archival analysis. Furthermore, this research used the linear regression to test the hypotheses. Thus, the future researches can assess the non-linear relationship between the business performance, business sustainability, business competitiveness and drivers, enablers, barriers. Or the non-linear relationship between business performance, business sustainability, business competitiveness and 6Rs

Conclusion

In order to conclude, this research contributes to the drivers, enablers and barriers of CE in the UK manufacturing industry in both practical and theoretical sense. Also, this research identifies the relationships between derivers, enablers, barriers of CE and business performance, business sustainability, business competitiveness. Moreover, the relationships between 6Rs and business performance, business competitiveness, business sustainability are also analysed too. The section 5.21 presents the results of drivers, enablers and barriers of CE in the UK manufacturing sector as shown table 5.1, 5.2 and 5.3. Also, there are 6 hypotheses were tested, and the result indicated that the business performance and business competitiveness have a significant positive with the enablers of CE. Furthermore, the business sustainability has significant positive relationship with performance of Reuse, Repairing, Re-Manufacturing, Refurbish. The result of these hypotheses is shown in table 5.4. In short, this thesis indicates that the success of CE cannot achieved through overcoming the technical barriers (technology factors and CE infrastructures). The relationship with society and industrial partners should be taken into consideration too. Thus, the future researches are supposed to identify the more complex context of CE in the area of CE in the UK manufacturing sector.

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