Next Article in Journal
Exploring the Global Innovation Systems Perspective by Applying Openness Index to National Systems of Innovation
Previous Article in Journal
Empirical Finding on the Determinants of Collective Consumption: Focused on Consumption Values, Trust, and Perceived Risk
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JOItmC
Volume 8
Issue 4
10.3390/joitmc8040180
JOItmC-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Readiness for Innovation of Emerging Grass-Based Businesses

by
Richard Orozco
1,2,* and
Philipp Grundmann
1,2
1
Department of Technology Assessment and Substance Cycles, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), 14469 Potsdam, Germany
2
Department of Agricultural Economics, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
*
Author to whom correspondence should be addressed.
J. Open Innov. Technol. Mark. Complex. 2022, 8(4), 180; https://doi.org/10.3390/joitmc8040180
Submission received: 10 August 2022 / Revised: 19 September 2022 / Accepted: 21 September 2022 / Published: 8 October 2022
Browse Figures
Review Reports Versions Notes

Abstract

:
New business opportunities based on grassland and green fodder present a promising avenue to realize the transition towards a circular and sustainable bio-based economy. Yet, such potential remains largely untapped and grass-based products and businesses remain a small niche in the global economy. To understand this phenomenon, this paper introduces and operationalizes a model to assess innovation readiness built around seven focus areas: technology, manufacturing, business, IPR, customer, team, and funding readiness with their own detailed “progress scales.” We employ necessary condition analysis (NCA) to identify limiting factors and bottlenecks in actual business situations. Our results reveal that lack of consumer awareness, infant conversion technologies and paucity of long-term investments that support emerging bio-based businesses are the most limiting conditions for the growth of emerging grass-based markets. The present study advances our understanding of the factors that limit complex innovations in grassland systems. Focusing on necessary conditions in a coordinated way between practitioners and policy makers by giving priority to fostering positive awareness of bioeconomy businesses, developing conversion technologies, and improving access to capital is a recommended approach to foster emerging grass-based innovations.

1. Introduction

The bioeconomy can be defined as the production, utilization, conservation, and regeneration of biological resources to provide sustainable solutions (information, products, processes and services) within and across all economic sectors and enable a transformation to a sustainable economy [1]. One of the most discussed aspects of the bioeconomy is the replacement of fossil-based products by renewable and plant derived resources [2]. Bioeconomy transitions have major implications for the structures and outcomes of the economy and offer a new dawn, in particular for rural regions, as new bio-based products and services enable a new take on skills, jobs, and provide mutual benefits for local economies and the environment [3,4]. This has been the main rationale for the political interest with strong focus on innovation through research and technology development represented in the European Green Deal, national bioeconomy strategies and global climate agreements, among others.
In the EU, approximately 17.5% of the surface area is covered by grasslands and green shrubs [5]. Grasslands not only provide food and income for herders, but also provide essential ecological services such as climate regulation, wind prevention, biodiversity conservation and carbon fixation [6] as well as cultural services such as aesthetics and recreation [7]. A large fraction of this area has traditionally been utilized as pasture for livestock. However, this practice has been declining substantially in the passing years [8]. Today these resources remain underutilized, being left to decay after mowing and thus causing costs and lost benefits for individuals and society. Utilizing the surplus material of otherwise unused grasslands can help valorize and maintain the biodiversity and ecosystem value of grasslands [6]. In the last few decades, varied technologies to enhance the treatment and valorization of grass biomass into high value-added products for emerging markets have been studied and developed [9,10,11,12]. However, the transfer of technologies and therewith commercialization of grass-based products into the market remains a difficult endeavor [13,14]. Despite the urgent need for harnessing local resources and developing innovative bio-based products, the full potential of grass biomass remains widely unlocked and alternative grass-based products remain relatively unknown and underused in Europe’s economy [15]. To fill this gap, this study addresses the question of which conditions limit the upscaling of emerging grass-based businesses? Further, we aim to assess if and to what degree these different conditions are of importance?
The intricacy of the bioeconomy starts at the system level by interfacing biotechnology and economy and involving industries, civil societies, governments, educational institutions, political and public organizations [16]. Emerging businesses are now dealing with systemic innovations [17,18] which encompass certain particularities into the larger transition towards a bio-based economy in a more dynamic context [19]. Firms in emerging markets typically suffer from the absence of an institutional infrastructure which includes access to capital and legal frameworks that would facilitate their business transactions [20]. Unlike other businesses, innovative bio-based businesses, have to deal with more and very specific legislative constraints, as well as the challenges posed by infant and non-adapted technology [21]. The unclear values and perceptions of consumers, ambiguous market signals and an embryonic competitive structure pose further difficulties [22]. As such, it has been recognized that grand societal challenges such as the depletion of natural resources cannot be solved by means of technological solutions alone [23,24]. To address the sustainability of future agriculture in this context, a holistic approach that considers the multidisciplinary nature of innovation processes is a fundamental milestone.
Literature on innovation indicates that transformation is a consequence of the interplay of activities at multiple levels [25,26]. The innovation process has been defined as the sum of all activities needed to develop, disseminate and commercially apply the innovative idea [27,28]. Organizations increasingly understand that meeting sustainability ambitions does not only require new and improved technologies, but innovation on the business model level [29]. In this context, several frameworks such as the Technology Innovation System (TIS) [30], the Business Model Canvas [31] and the Business Environment Framework [22] have helped with the conceptualization of a wide range of business models and business environments. Yet, methodologies for business and innovation research are complex and multifaceted, and unfortunately not as well developed as its conceptual aspects [32]. Contemporary methodological challenges for business and innovation research include, inter alia, deficient measures [33] and insufficient evidence about causal relations [34,35]. Despite considerable efforts, the current body of literature is still lacking a practically useful framework which enables the measurement of the wide variety of business processes and which considers their intricate relationships within the business setting [36,37]. Particularly, for emerging innovations enabling Bioeconomy transition [14,38].
Against this background, and taking advantage of more recent methodological developments, this investigation aims to make at least three contributions. Firstly, we present a practical framework synthesized from a number of different approaches as an instrument to assess the innovation readiness of emerging businesses. Secondly, we prescribe Necessary Condition Analysis (NCA) as a practical method to identify bottlenecks and critical determinants that are essential for upscaling innovative businesses based on grass and green fodder. Thirdly, we empirically test the NCA approach across eight grass-based cases with different “maturity” levels to gain understanding on the limiting factors for the development of emerging bio-based businesses, and grass-based businesses in particular. The empirical evidence provides key recommendations which could support firms and innovators to economize resources dedicated to the innovation process and translate into management tools for policy and planning.

2. Materials and Methods

2.1. Case Study Selection

We use case studies [39] due to the limited availability of businesses producing high value-added products from grass biomass. Limiting the study to one sector, namely the grass-based industry, allows in depth analysis of the conditions, ongoing activities and dynamics of sectors in transition towards more sustainability. Our sample comprises eight innovative grass-based businesses in Europe at different stages of the innovation process, i.e., from small-scale demonstration sites to more advanced self-sustaining businesses. The cases were selected using a combination of searches for innovative grass-based businesses in the web, expert’s forum and EU project network databases. The sampling criterion was based on the potential of the business models in terms of the use of grass as raw input material, the key activities to make use of the grass resources, the value propositions, the products and services provided different from traditional livestock and grass-based products (i.e., not milk, meat, cheese), as well as the customer segments, business channels, and revenue streams.

2.2. Case Study Description

Case 1: Small scale grass-refinery developed and operated by Aarhus University Center for Circular Economy (CBIO) in cooperation with the Food and BioCluster Denmark. The focus is on extracting protein from grass-clover, lucerne, organic grasses, and paludiculture crops from intensively managed grassland situated in nitrate sensitive areas. The biorefining process fractionates freshly harvested grass into a juice and a fibrous pulp. The pulp is ensiled and used for ruminant forages, while the juice is heated, to precipitate protein, and subsequently centrifuged to separate the protein concentrate. The organics in the residual liquid fraction (brown juice) is used for biogas production and the nutrients are recycled back to the soil as fertilizer.
Case 2: Digestion and fermentation to produce paper and carton products from road-side grass or fauna grass developed in collaboration with the Application Centre for Renewable Resources of Wageningen University and Research (ACCRES), Nordlike Fryske Walden and Schut Papier in the Netherlands. The raw material grass used is harvested from nature reserve areas and roadside areas. The digestate is separated into an aqueous fraction that is used as fertilizer and a solid fraction. From the solid phase the fibers are extracted and further refined to a quality that fits the applications for use of paper products. The company SCHUT uses grass fibers to manufacture egg-cartons and egg-trays.
Case 3: The local production of biochar uses grassland-cuttings from periodically wet grasslands located in the National Park Unteres Odertal, Germany. The harvested grass is mostly strongly lignified and with lower nutritional quality for animal feed. A Hydrothermal Carbonization process (HTC) is developed by the Leibniz-Institute for Agricultural Engineering and Bioeconomy (ATB) in cooperation with the Naturparkverein Unteres Odertal e.V. to produce grass-based biochar as supplement for soil improvement.
Case 4: The production of climate-friendly animal bedding from reed canary grass that has been heat treated and pressed is a development by Research Institutes of Sweden (RISE) and other local partners such as Glommers Miljöenergi and Vastakra Gard located in Sweden. The main technology to be applied is briquetting at local and small scale. The briquetting technology needs to be put in context with the other steps to create a new production chain.
Case 5: Re-engineering of grass unto biodegradable materials such as pulp molding, paper and packaging and fiberboards. The processes developed by Zelfo Technology located in Germany revitalizes a wide range of cellulosic and ligno-cellulosic sources. The processes impart new application capabilities to these materials, giving value to resources that had little to no value and encouraging the use of renewable and biodegradable materials as an alternative to plastic-based solutions. Current main applications are in pulp molding, paper and packaging and fiberboards.
Case 6: Sustainable use of resources in neglected or underutilized grasslands mainly through the production of biochar. The innovation is facilitated by the Hungarian Research Institute for Organic Agriculture (ÖMKI) to support organic agriculture production in Hungary. Building upon the experience of their nationwide on-farm experimentation network, ÖMKI aims to replicate grass-based business models in Hungary.
Case 7: Developing and replicating technical solutions and business models to valorize agricultural residues and grass material from marginal grasslands by the Romanian Association for Sustainable Agriculture (ARAD), a non-governmental organization focusing on the promotion of sustainable farming systems.
Case 8: Small scale circular systems based on grass and green fodder to provide new business opportunities for young entrepreneurs by the Galician Association of Agri-food Cooperatives (AGACA) in Spain. Drawing upon the practical experience of their 34,000 members, AGACA aims to replicate circular business models at a local level.

2.3. Variable Definition

To expedite an orderly and reproducible assessment of the innovation readiness process, a set of seven necessary conditions (or independent variables) for innovation were selected from the literature: Technology, Manufacturing, Business, IPR, Customer, Team and Funding Readiness. Our selection of the seven readiness areas was guided by the Innovation Readiness Level Framework (IRLF) developed by the Royal Institute of Technology in Stockholm, Sweden (KTH). The IRLF was inspired by the Technology Readiness Level (TRL) developed by the space industry in the 1970s. The other focus areas are not universally agreed. Yet, they have been included to support early-stage innovation development and have been empirically tested by KTH in multiple ventures for the past 20 years. Since our study targets the production of grass-based products, we extend the framework by including manufacturing readiness [40] and considering innovation readiness [41] as the outcome or dependent variable.
Within each focus area, a detailed readiness level scale from 1 to 9 is described with clear definitions of criteria, milestones, and activities that must be accomplished to move on to the next level (Appendix B). The scales provide a roadmap for guiding progress in every dimension of innovation development, from an idea unto its successful commercialization.

2.4. Data Collection

Data were gathered within the frame of the H2020 GO-GRASS project (www.go-grass.eu) between October 2019 and July 2022. Firstly, a questionnaire based on the Innovation Radar (Appendix A) was sent to eight business representatives of the cases to assess their current state and to understand their value propositions. These results were discussed in two stakeholder board meetings organized in the frame of the H2020 GO-GRASS project which took place in Denmark and Sweden in 2021. Focus group discussions [42] with entrepreneurs, researchers, technology developers, and agricultural producers took place with the aim of discussing opportunities and constraints for the upscaling processes of grass-based businesses.
The readiness levels of the business cases were assessed in an iterative process with experts, according to specific milestones and criteria (Appendix B). To evaluate the readiness levels for each case, we conducted self and external assessments [43]. Quality standards were ensured by assessing the diversity and the degree of consensus on the readiness levels in a series of dedicated meetings. Finally, based on the empirical findings, GO-GRASS project deliverables and consultations at project meetings, we derive upscaling strategies to accelerate the development of grass-based businesses.

2.5. Necessary Condition Analysis (NCA)

Conventional theories and methods generally operate on the logic that several factors contribute to the outcome and can compensate for each other (e.g., OLS and other types of multiple and multivariate regression, multilevel modeling and structural-equation modeling) [35]. Factors are usually interpreted as being sufficient causal factors that can help to produce the outcome. Yet, these methods are not able to identify necessary conditions in data sets [44].
In contrast to more traditional regression analysis that study variables in a probabilistic relation to each other, NCA is based on necessity causal logic and allows the study of variables which are necessary but do not guarantee a certain outcome [44]. For example, grass processing and conversion technologies are necessary but do not guarantee the success of businesses producing grass-based products. Indeed, a necessary condition will prevent an outcome from occurring. There will be “no Y without X” in the necessary condition logic. Thus, while a sufficient cause produces an outcome, without the necessary cause, the outcome will not exist despite other factors being present, at least to a necessary degree [45,46].
To spot critical determinants that constrain the upscaling of emerging grass-based businesses, we conducted a Necessary Condition Analysis (NCA) with the NCA package in R (Version 3.1.1). The advantage of using NCA is that the study and its theoretical reasoning can focus on single necessary concepts, which allows a clear storyline and an efficient data collection and analysis [47]. The method is developing rapidly and applied in a variety of research areas including business and management to provide effective decision support and managerial insights [48]. Examples of related studies that have used NCA include the role of contracts and trust in driving innovation [49], the link between specific firm capabilities and performance [50], and the necessity of top management support for successful implementation of lean manufacturing [51]. Identifying relationships of necessity is of key interest in the social sciences and beyond. It can provide actionable knowledge with “very powerful policy implications [52].” By understanding which variables are critical to what degree for a desired outcome, researchers and practitioners can gain a better understanding of the causal effects when examining a particular outcome.
The NCA analysis in R produces scatter plots in an XY plane and conducts a bivariate analysis. NCA draws borders lines called “ceiling lines” between the space without cases and the space with cases. NCA offers two default ceiling lines to choose from. The Ceiling Envelopment-Free Disposal Hull (CE-FDH) ceiling technique is a step function employed when using discrete (with few levels) necessary conditions. The Ceiling Regression-Free Disposal Hull (CR-FDH) ceiling technique is the default ceiling technique for discrete (with many levels) and continuous necessary conditions. In this study, we used nine levels for each condition; hence, we focus our analysis on the step function CE-FDH.
The size of the empty space above the ceiling line is an indication of the strength of the necessary condition (‘effect size’). In the following section, we report results of the NCA based on 10,000 permutations using the observed sample. The relative importance of the independent variables and the accuracy of the results were presented and discussed in two conferences among experts and practitioners.

3. Results

3.1. Readiness Levels

The results for the readiness levels of the cases in Table 1 show that the cases studied are very heterogeneous in terms of their readiness levels. Our sample comprises eight innovative grass-based businesses in different countries of Europe and at different stages of the innovation process, i.e., from small-scale demonstration sites to more advanced self-sustaining businesses.

3.2. Effect Sizes of the Seven Necessary Conditions

The results shown in Table 2 about the effects sizes for the seven conditions indicate that Customer Readiness has the biggest effect (0.619) for the development of the grass-based businesses tested. Thereafter, Technology Readiness (0.612), Funding Readiness and Team Readiness (0.571), Manufacturing Readiness (0.551), Business Readiness (0.518), and lastly IPR Readiness (0.268).
The effect size indicates to what extent a variable is necessary for an outcome. In other words, to what extent conditions constrain the outcome. The effect size d can range from 0 to 1. In applications of NCA, necessity effect sizes between 0 and 0.1 are usually considered small, from 0.1 to 0.3 medium, from 0.3 to 0.5 large and above 0.5 very large [47]. Yet, these are highly dependent on the research context and should be assessed accordingly.

3.3. Scatter Plots for Necessary Conditions

The NCA analysis in R produces x-y plots for each critical factor (X-axis) in relation to the levels of innovation readiness (Y-axis) with so called “ceiling lines”. Data analysis with NCA is always bivariate, meaning that each necessary condition is analyzed in isolation from the rest of the causal structure. Inspections of all figures (Figure 1, Figure 2, Figure 3, Figure 4, Figure 5, Figure 6 and Figure 7) show an empty space in the upper-left corner, indicating that all seven conditions are necessary to some extent for innovation readiness. The ceiling line represents the level of Y that can be reached with a certain level of X, or in other words, the level of X that is necessary for reaching a certain level of Y.
Figure 1 exemplifies the necessity of customers for innovation readiness. By observing the empty space in the upper left corner, we can formulate the hypothesis that to achieve a desired level of IRL 6, a level of at least CRL 6 is required. This means that the benefits of the product must be confirmed through partnerships or first customer testing in order to support the development and design of the product with a market driven business team.
Figure 2 exemplifies the necessity of technology for innovation readiness. By observing the empty space in the upper left corner, we can formulate the hypothesis that to achieve a desired level of IRL 4, a level of at least TRL 5 is required. In other words, to support project engineering development and design, the technology must be scaled from the laboratory unto a prototype demonstrated in an operational environment. To achieve an innovation readiness of 8, in which the capability to transition to full production and distribution is confirmed, the actual technology system must be completed and qualified through test and demonstration (TRL7). All other plots can be analyzed in the same way by using the detailed scales and descriptions provided in Appendix B.

4. Discussion

4.1. Customers

Our results indicate that customer readiness has the largest effect size or is the most critical condition for grass-based businesses to ascend the ladder of innovation. According to the expert group on R&D and innovation of the European Commission, enabling the market demand for innovative products is one of the key challenges for boosting productivity and competitiveness of Europe’s economy [53]. Recent studies stress a dismally low percentage of consumer awareness for bio-based products in several European countries [54,55].
Consumer’s purchasing preferences are essential for business as they signal the kind of products desired and enable companies to shape production decisions [56]. However, demand for bio-based products depends on the buyer’s perception of the product´s quality, usability and production method of the bio-based product [57]. This means that grass-based products must be perceived to be at least as good as their alternatives by the customers. Thus, a key challenge for entrepreneurs offering bio-based products is that potential customers often cannot make informed decisions related to the use of the offered new products and services provided by bioeconomy businesses [22]. In addition, geographically distant supply chains of resources have increased access to and human consumption of many goods, without consumers feeling accountable for or being aware of their environmental or social impacts [58].
The existence of strong environmental values in a certain region and the early formation of local markets for sustainable products and services may provide early testing grounds for wider development and diffusion [59]. At earlier stages, firms may enter an initial market with an early version of the product, learn from the experience, modify the product and marketing approach based on what has been learned [60]. Another recent study found that firms can nurture and manage customer relationships to acquire, share, and exploit customer knowledge for the benefit of the customers and the firm [61]. It should therefore be a top management priority to build and maintain the trust of consumers for bio-based products. Emerging grass-based businesses must identify the value proposition for its customers, which customers it tries to serve and identify the type of relations they want to create with their customer segments in the early stages of innovation [31]. Since novel green innovations are often systemic in nature and require changes in consumption behavior, end-user integration along the innovation process may be particularly relevant for the success of such products and services [62]. Finally, businesses emphasize the need to foster positive awareness of bioeconomy businesses and their products and services among consumers and public agents. As stated in a recent study, unless coupled with responsible consumptions patterns, sustainable production cannot contribute to the overall goals of sustainable development [63].

4.2. Technology

Our results indicate that technology readiness is the second most critical condition for grass-based businesses. Biotechnology is a key enabling technology for the discovery, development and manufacture of new products and materials [16,64]. Grass-biomass must be converted and manufactured into a product through a meaningful combination of different methods and processes (physical, chemical, biological and thermal). It is therefore necessary that biorefinery-based technologies are developed [65]. New technologies not only provide cleaner solutions for the future, but also help in avoiding and overcoming problems caused by the current technologies [66]. Furthermore, technological developments may encourage companies towards more circular systems of production [67].
Varied technologies to enhance the treatment and valorization of grass biomass unto high-value-added products for emerging markets have been studied and developed [10,12]. Yet, currently most of the technologies for utilizing the grassland biomass are developing at the lab scale and the further development, optimization and integration of the technologies into the existing industries or sectors are needed. However, technological advances do not necessarily result into marketable innovations able to change economic systems [18]. On one hand, new technologies often bring disruptive changes in value and supply chains and business behavior [24,68]. On the other hand, lacking technical skills creates challenges for identifying, assessing and implementing more advanced technical solutions [69]. In line with previous research, we highlight that technological developments which are not aligned to the needs of the stakeholders or to local conditions bear the risk of placing public money in the death-valley of innovation [70]. Information sharing platforms may support cooperation with stakeholders and enable better information transparency. Involving various kinds of social actors as assessors and discussants can support the decision process towards the most feasible and sustainable technologies to valorize grass resources and to facilitate the cascading use of grassland biomass unto a variety of bio-based products and services.

4.3. Funding

The agricultural economic literature on innovation clearly documents that innovations do not occur randomly, but rather that incentives and government policies affect the nature and the rate of innovation and adoption [28]. The public sector has played a major role in funding R&D activities that have led to new agricultural innovations. However, research has shown that emerging markets often suffer from the absence of access to capital [20]. This is especially true for emerging bio-based businesses which compete with the established economic system relying on fossil resources [15]. Such competition with the extant fossil-based industry is cost and risk intensive and thereby requires foresight and strategic management [2,71]. We found that attracting investors or securing access to credit at the early stage of a business is a major challenge. An explanation for this finding is that emerging bio-based companies are less attractive for traditional investors [22]. Previous studies show that bio-based businesses require greater investments in the short-term, whereas their results tend to materialize in the long term [72]. Our findings are in line with previous research which stated that due to the innovative nature of these businesses, public and private investors are not always familiar with the products and services provided by these companies [4]. Thereby resulting in difficulties to assess the opportunities and risks associated with investments in the bio-based sector.
Recent research on bioeconomy businesses demonstrated that interactions with various stakeholders such as research institutes and universities may enable emerging enterprises to create a consortium that makes it easier to apply for funding but also to understand the regulations for application and the obligations following the approval of financial resources [22]. To bring grass-based products to the market, emerging businesses require aligned funding mechanisms that incorporate and promote the specific benefits generated by grass-producing and grass-processing companies. The need to ensure a high level of funding readiness as an early prerequisite for innovation progress may also be a reason for the emergence of new forms of financing such as crowdfunding, prosumer models, Science-to-Business (S2B) and Business-to-Business (B2B) models [18,22].

4.4. Team

Entrepreneurs and entrepreneurial behaviors play an important role in the development of new business models [21,73]. However, individual entrepreneurial activity is not sufficient for a bioeconomy transformation [74]. Thus, securing the right skills and competencies and having a well-structured team emerges as a top priority for emerging grass-based businesses. As opportunities for new business fields emerge, the needed knowledge may exceed the competencies of traditional business models. New processes and technologies often require special skills and training. This triggers several challenges related to the development of the Bioeconomy and knowledge generation in converging industry fields [71].
New forms of cooperation both up-stream and downstream in the supply chain are of paramount importance to develop new bio-based value chains [75]. In line with previous research, we highlight the importance of investing in local relationships and networks [76,77]. Networks and collaborative structures may contribute to connecting and engaging farmers unto new practices required for the harvesting and collection of grass biomass. Furthermore, the involvement of stakeholders with multi-disciplinary skills, knowledge and expertise throughout the development of grass-based businesses might also support the identification and timely resolution of complex situations [74]. Identifying stakeholders to engage in the innovation process is important to collect diverse insights from stakeholders, to foster inclusion and diversity of perspectives, and even to shape collective expectations [78,79]. Finally, because the Bioeconomy is, by definition, a knowledge-based economy, academic research is particularly important for the groundwork of entrepreneurial activity and can facilitate knowledge transfer [80]. There is an urgent need for capacity development to develop a grass-based economy.

4.5. Manufacturing

The bio-based economy relies on sustainably produced biomass as raw materials for the production of various products [81]. The availability and quality of grass are the foundation of grass-based businesses. In order to achieve full-scale operations, businesses require sufficient biomass feedstocks with the right quality. Our results indicate that securing biological resources and critical infrastructure for production, have a large effect size for upscaling grass-based businesses. We found that single product approaches often struggle to create sufficient revenues to cover subsequent processing costs. As such, the viability of grass-based businesses depends on the range of suitable applications identified for the separate fractions. It has been demonstrated that a multiple-product approach, or cascading use of biomass can facilitate the efficient utilization of the whole plant and any process residues [82].
Grass as a raw material is a seasonally accruing material [83]. Hence, to ensure a predictable quality and a constant year-round supply of feedstock to a biorefinery facility, grass usually needs to be harvested and stored as silage [11]. The chemical composition of grass presented to the biorefinery determines the potential range of products that can be produced [10,11,12]. This means that grass must be harvested, preserved, pre-treated and stored in relation to certain parameters such as lignification level, moisture content and content of special ingredients such as fibers, proteins, polyphenols, ecdysone or other high-value components [84,85]. Specific management factors such as harvest date and nutrient management also have a significant impact on the yield and chemical composition of the feedstock [11]. The optimal stage for harvesting is determined by the particular grassland biomass use. For example, grass harvested at earlier growth stages may be more suitable for biogas production through anaerobic digestion [81], while grass harvested at later growth stages may be more suitable for technical fiber or combustion [83]. Hence, a key challenge for grassland farming is to develop management strategies in which the multiple ecosystem services of grasslands are sufficiently provided.
Recent research also shows that difficulties in mobilizing biomass is one of the main barriers that hamper the development of bio-based supply chains [15]. Therefore, logistics play an important role in the economic utilization of grass. An optimal design and operation of biomass supply chains are of critical importance for upscaling [86]. We found that emerging grass-based businesses seek to cultivate buyer-supplier relations and to secure a steady supply by experimenting with alternative sources of grass, including grass from roadsides, farmlands, nature conservation areas and municipal sources.

4.6. Business

In line with previous research, we found that the practical implementation of the bio-based businesses in general, and grass-based businesses in particular, is still lagging, and companies are struggling to develop effective business models in which revenue streams and economic feasibilities are clear [87]. A potential reason is that most grass-based products are targeted at very early-stage markets (e.g., grass biochar) or markets where the grass-based products compete with well-known alternative solutions (animal bedding, soybean protein or wood fibers). We found that innovative ideas based on grass biomass were fostered from observations of market inefficiencies and for valorizing underutilized biomass unto new products or services solutions. Starting a new industry, even in small scale, requires significant investments, reliable supply chains and time for new markets to form. Therefore, framework conditions are fundamental for the readiness of these businesses and affect each of the focus areas under study. Previous research has shown that the success or failure of organizations is not determined by the business model elements themselves, but rather through their complementarity, interrelations and alignment with the business environment [22,88]. Our findings highlight that national regulations, strategies and policies can stimulate demand in certain sectors (e.g., organic fertilizers), establish relevant infrastructure (e.g., biogas plants), and underpin investments that enable certain mechanisms to function unto the development of new value chains and markets. Finally, optimizing operations and reducing the risks of the business model, requires alignment with local conditions in which local needs are fulfilled.

4.7. IPR

We found that IPR has the least effect for upscaling innovative grass-based businesses. It seems logical that IPR might have a lower effect in comparison to the other conditions as not all businesses are interested in protecting intellectual property. Several stakeholders argued that IPR should not be considered in our innovation readiness framework as protecting IP might obstruct the efficient upscaling and replication of sustainable businesses in Europe. Yet, whether an organization has intellectual property rights (IPR) to protect or not, developing a strategy for assessing and developing IP protection might enhance the competitive advantage of the business and protect the benefits of investments. IPR might come in the form of patents for new inventions, trademarks for distinctive identification of products and services, registered designs for external appearance or trade secrets for valuable information not known to the public. Conducting a Freedom to Operate (FTO) analysis might be useful to have an overview of potential IPR in relation to the new products, services and business activities.

5. Conclusions

In competitive global environments, innovation is fundamental for ensuring that societies are able to produce more with fewer inputs, while simultaneously striving to ensure production is as sustainable as possible [89]. However, innovation is a broad concept covering innovation processes, structures, outcomes, antecedents, and behaviors at the organizational level in the private and public sectors as well as at the individual, national, and professional levels [19]. Therefore, it is becoming more evident that innovation can only be understood when viewed from various perspectives [90].

5.1. Theoretical Implication

We developed a framework to assess processes of innovation readiness and tested the operation in measure of seven focus areas: Technology, Manufacturing, Business, Customer, IPR, Team and Funding. With this, we contribute to a better understanding of the multidisciplinary nature of innovation processes and advance our understanding of the factors that limit complex innovations in grassland systems.

5.2. Practical Implication

One of the fundamental aims of the GOGRASS project, which served as a research platform for the current study, is to support the transition from demonstration cases financed by the EU, to self-sustaining businesses that can be replicated in Europe and beyond. In this study, our chosen sample ranges from demonstration to established grass-based businesses, with different levels of innovation readiness and different levels in the independent variables. Our aim was to identify which necessary conditions are critical at different stages of the upscaling process and to identify bottlenecks in emerging grass-based businesses. The results presented in this paper aim to foster real-world actions that increase sustainability and to provide further scientific knowledge on business research and innovation management.

5.3. Limits and Future Research Topics

The main challenge of multiple case study research involves issues of generalizability [39]. Our data were drawn from a small set of grass-based business models in Europe and the findings may or may not extend to other sectors and locations. At the same time, the surveyed enterprises function in various business environments and operate in various socio-economic conditions. Due to the complexity of socio-ecological systems and the interdisciplinary nature of sustainability sciences, no silver bullet exists that balances the benefits of situated knowledge with those of strong generalization [91,92]. Therefore, subsequent studies should focus on achieving a more holistic understanding of grassland systems and business conditions at the local level to help minimize trade-offs and maximize synergies between business and environmental wellbeing and lead to the attainment of Sustainable Development Goals (SDGs) [93].
We have presented NCA as an emerging approach capable of testing necessity. Yet, because NCA operates on a “necessary but not sufficient logic”, it can only be used to identify determinants whose absence would prevent an outcome from being achieved, but not determinants that will produce an outcome [94]. Accordingly, NCA represents a complement for, not a replacement of current analytical approaches such as, for example, OLS regression [52].
On the other hand, the constructs used in this study are derived from the literature and proven to be main focus areas in the innovation process. Yet, this is a simplification which does not consider the full complexity of highly interconnected and interdependent innovation processes and their networks of action situations [95,96]. In addition, the study focuses on the “internal” or “endogenous” processes of the cases and does not discuss fully their business environment [22], socio-ecological [97] nor spatio-temporal [98] specificities. While the use of “innovation” related indicators as the output of the innovation process provides a useful indicator on the success of innovation-related activities, it does not tell us how such output influences firm’s overall performance such as revenue growth and sustainability. For this literature to move forward, more comparative analysis of larger number of cases over a longer period of time as well as looking at the developments contributing to higher readiness levels are required.
As research on grass-based businesses and industries in sustainability transitions is quite recent [24], there is significant potential to intensify research at the intersection of business model innovations and Bioeconomy transitions [29]. Empirical analyses are indispensable for the advisory process in Bioeconomy transitions [99]. Future research could replicate the approach presented here and study necessary conditions in other regions, emerging industries or bio-based businesses. New readiness levels could also be incorporated in the analysis and suited to the specific research. Future research could use the NCA view of necessity thinking, for example, to understand what conditions are critical for agricultural producers to engage in new business activities related to the Bioeconomy. In tandem, contemplating the role of consumers seems to be especially promising to better understand entrepreneurial value creation and business models [4].
Finally, the value of the different ecosystem services needs to be taken into account for an appropriate use of grasslands as these are often in a trade-off relationship with each other [100,101]. We see a need for monitoring the effect of innovations and new business models which may compromise some ecosystem services provided by grasslands. In addition, we recommend that the socio-economic and institutional readiness of business environments be included in the assessment to ensure the promotion of rural communities, communication with relevant stakeholders and sustainable development [7]. In doing so, sustainability research must address the specifics of each case to avoid continuing the path of blueprint solutions [102]. We believe it is essential to address the multidisciplinary nature of innovation processes through collaborations with industry, governments and the public, as a basis for helping to build a comprehensive circular bio-based economy and for transforming the socioeconomic structure of contemporary society into a sustainable one.

Author Contributions

Conceptualization, R.O. and P.G.; methodology, R.O.; software, R.O.; formal analysis, R.O.; investigation, R.O.; resources, P.G.; data curation, R.O.; writing—original draft preparation, R.O.; writing—review and editing, R.O. and P.G.; visualization, R.O.; supervision, P.G.; project administration, P.G.; funding acquisition, P.G. All authors have read and agreed to the published version of the manuscript.

Funding

The research leading to the results of this article received funding from the European H2020 GO-GRASS project under the grant agreement (ID 862674). The publication of this article was funded by the Open Access Fund of the Leibniz Association.

Acknowledgments

We would like to thank all partners from the European H2020 GO-GRASS project for their contributions to data collection, in particular Gate2Growth (G2G), Research Institutes of Sweden (RISE), Institute for Food Studies & Agro-industrial Development (IFAU), Aarhus University (AU), Greenovate Europe (G!E), Hungarian Research Institute of Organic Agriculture (ÖMKI), Asociación Galega de Cooperativas Agrarias (AGACA), Stichting Wagenigen Research (ACRRES), Agro Business Park AS (ABP) and Noardlike Fryske Walden (NFW). We thank Jan Dul from Erasmus University Rotterdam for his valuable advice as well as the members of the NCA community for the exchange of ideas and experiences on the approach and methodology. We thank the three anonymous reviewers and the academic editor for their insightful comments and suggestions.

Conflicts of Interest

The authors declare no conflict of interest. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

Appendix A. Template of Innovation Radar Questionnaire

General Information
Organization name
Location
Goal(s) in GO-GRASS
Innovation Description
Innovation name
Innovation type (hardware, product, software, service, etc.)
Short innovation description
Innovation characterization
Current TRL (1–9) Choose from the list
Level of innovation Choose from the list
Market Description (if relevant)
Market sizeChoose from the listMarket trends
Targeted geography (country, region, etc.)
Targeted customer segments
Market maturity Choose from the list
Unique selling points (USPs), compared to existing solutions. (in short bullets)
Supply Chain/value chain (if relevant)
Grass (Input):
Have you identified how you will get enough raw materials for your production?		Yes ☐
No ☐		If yes, please elaborate
Grass (Input):
Do have indication of the price of the raw materials?		Yes ☐
No ☐		If yes, please elaborate
Product (Output):
Have you identified and/or been in contact with potential customers?		Yes ☐
No ☐		If yes, please elaborate
Product (Output):
(If yes above) are the customers willing to pay a premium for the new product (if needed)?		Yes ☐
No ☐
N/A ☐		If yes, please elaborate
Waste stream (Output):
Do you know what to do with the waste grass after production?		Yes ☐
No ☐		If yes, please elaborate
Financial Information (if relevant)
Additional funding needed to bring innovation to market.Choose from the listFounding sources
(choose as many as relevant)
Expected revenue from innovation at end of projectChoose from the listExpected revenue from innovation 5 years after end of project
Expected employment growth from innovation at end of project (FTE‡: full-time equivalent)Choose from the listExpected employment growth from innovation, 5 years after end of project
IPR (Intellectual Property Rights) & Standards (if relevant)
Status of IPR: Background (type and partner owner)
Status of IPR: Results/Foreground (type and partner owner)
Are there any IPR/Patents issues to be resolved with the consortium?Yes ☐
No ☐		If yes, please elaborate
Do you expect to be able to apply for patents during/after the project?Yes ☐
No ☐		If yes, please elaborate
Do you expect to be able to apply for trademarks or other IPR during/after the project?Yes ☐
No ☐		If yes, please elaborate
Standardization:
Describe whether there are any legal, normative or ethical requirements connected to the development of your product/Early requirements?		Yes ☐
No ☐		If yes, please elaborate

Appendix B. Definitions of Conditions and Outcome

Table
Table A1. Definition of Outcome- Innovation Readiness Level (https://www.esabic.no/wp-content/uploads/2018/12/a.-Innovation-Readiness-Level.pdf, accessed on 1 July 2022).
Table A1. Definition of Outcome- Innovation Readiness Level (https://www.esabic.no/wp-content/uploads/2018/12/a.-Innovation-Readiness-Level.pdf, accessed on 1 July 2022).
Innovation Readiness Level-IRLDefinition
1Inventor or team with a dreamLowest level of readiness where the intention surfaces to translate an idea, of a space system application or a space technology transfer, into a business venture.
2Paper studies producedOnce the basic ideas have been formulated, they are put down on paper in studies and analyses on the business opportunity.
3Experimental evidence of business opportunityActive research and development is initiated, including analytical/laboratory studies to validate predictions regarding the market, the competition and the technology.
4Capability to work limited-scope programs with project teamsBasic technological and business components are developed to establish that they will work together; an initial business plan is available.
5Capability to support project engineering development and design (no product, no revenues)The basic technological and business components are integrated with reasonably realistic supporting elements. The business plan is credible, but still needs to be validated against the final product characteristics.
6Capability to support development and design with a market-driven business team (product, no revenues)A representative prototype system is tested in a relevant environment. The business team is still incomplete and the venture not yet ready for commercialization. A full business plan including market, operational, technological and financial aspects is available
7Capability to support limited production; full business team in place (product and limited revenues)The business can run on a limited scale. The full team is in place.
8Capability to transition to full production and distribution (product and revenues)The technology has been proven to work and the venture structure has proven to be able to support growing market shares.
9Fully articulated business with appropriate infrastructure and staffing (growing market share)The offering incorporating the new technology has been used in operational conditions and the business is running with a growing market share.
Table
Table A2. Definition of seven necessary conditions (https://kthinnovationreadinesslevel.com/, accessed on 1 July 2022).
Table A2. Definition of seven necessary conditions (https://kthinnovationreadinesslevel.com/, accessed on 1 July 2022).
LevelTechnology ReadinessManufacturing Readiness Business
Readiness		Customer
Readiness		IPR ReadinessTeam
Readiness		Investment Readiness
1Basic principles observedConcept proposed with scientific validationHypothesizing on possible business concept (limited knowledge or insight int market and competition)Hypothesizing on possible needs in marketHypothesizing on possible IPR you might have (such as patents, software, copyright, design, trade secrets et al.)Little insights on the needs for a team (typically an individual). Lack of necessary competencies/resources.Initial business idea with vague description. No clear view on funding needs and funding options.
2Technology concept and/or application formulatedApplication and validity of concept validated or demonstratedFirst possible business concept described. Identified overall market and some competitors/alternativesIdentified specific needs in marketIdentified different forms of possible key IPR that you have. Ownership is clarified and you clearly own/control IPR.Insight and first idea on necessary competencies or external resources (e.g partners)Description of business concept (e.g., for NABC). Defined funding needs and funding options for initial milestones.
3Analytical and experimental proof of concept of critical function and/or characteristicsExperimental proof of concept completedDraft business model in canvas excluding revenues/costs. Described market potential and complete competitive overviewFirst market feedback establishedDetailed description of possible key IPR (e.g., invention or code). Initial search of technical field and existing iPR.A few necessary competencies/resources are present. Defined needed competencies/resources (and plans for finding).Well described business concept and initial verification plan. First small soft funding secured.
4Technology validation in laboratoryProduction validated in lab environmentFirst version of full business model in canvas (including revenues/costs). First projections to show economic viability and market potentialConfirmed problem/needs from several customers or usersConfirmed if protection is possible and for what (e.g., patentability). Decided why to protect certain IPR (business relevance)A champion is present. Several needed competencies in place. Initial plan for recruiting or securing additional key resources.Good pitch and short presentation of the business in place. Plan in place with different funding options over time.
5Technology validation in relevant environmentBasic capability demonstratedParts of business model tested on market and canvas updated. First version of revenue model including pricing hypothesis. Verified competitive position/uniqueness through market feedback.Established interest for product and relations with target customersDraft of IPR/patent strategy implemented and supporting business. Filed first complete patent application (or other IP registrations)Initial founding team with main needed competencies. Team agrees on ownership and roles and has aligned goals.Investor oriented presentation and supporting material tested. Applied for and secured additional larger funding (soft or other)
6Technology demonstration in a relevant environment Process optimized for production rate on production equipment Full business model including pricing verified on customers (by test sales) Benefits of the product confirmed through partnerships or first customer testing IPR/patent strategy implemented and supporting business. Positive response on filed applications. Initial assessment of freedom-to-operate (or landscape) Complementary, diverse and committed team with all necessary competencies/resources including both business and technology. Improved investor presentation in place including business(financials. Decided on seeking private investors and initial contacts taken.
7Technology prototype demonstration in an operational environment Capability and rate confirmed Product/market fit and customers payment willingness demonstrated. Attractive revenue v. cost projections (Validated by data and sales) Customers in extended product testing or first test sales All relevant IPR filled (e.g., additional patents). Patent entry into national/regional phase. Team and culture is fully in place and proactively developed. Updated plan for building necessary team on longer term. Team presents a solid investment case including business/financials. Decided on seeking private investors and initial contacts taken.
8Actual technology system completed and qualified through test and demonstration Full production process qualified for full range of parts Sales and metrics show business model holds and can scale. Business model is fine-tuned to explore more revenue options First products sold and increased structured sales efforts IPR management and IP management fully implemented. More complete assessment of freedom-to-operate. Management and CEO in place. Professional use of boards/advisors. Activated plan and recruitment for building long term team. There is corporate order and structure enabling investment. Team sheet discussions with interested investor(s).
9Actual technology system proven in operational environment Full production process qualified for full range of parts and full range of metrics achieved Business model is final and is scaling with growing recurring revenues that result in a profitable sustainable businessWidespread products sales that scale Strong IPR support and protection for business. Patent granted in relevant countries and maintained force.High performing, well-structured team and organization that is maintained and performs over time.Investment obtained. Additional investment needs and options continuously considered.

References

  1. Innovation in the Global Bioeconomy for Sustainable and Inclusive Transformation and Wellbeing. In Proceedings of the Global Bioeconomy Summit, Berlin, Germany, 19–21 April 2018; Available online: https://www.biooekonomierat.de/media/pdf/archiv/international-gbs-2018-communique.pdf?m=1637836879& (accessed on 1 July 2022).
  2. Aguilar, A.; Wohlgemuth, R.; Twardowski, T. Perspectives on Bioeconomy. New Biotechnol. 2018, 40, 181–184. [Google Scholar] [CrossRef] [PubMed]
  3. D’Amato, D.; Bartkowski, B.; Droste, N. Reviewing the Interface of Bioeconomy and Ecosystem Service Research. Ambio 2020, 49, 1878–1896. [Google Scholar] [CrossRef] [PubMed]
  4. Kuckertz, A.; Berger, E.S.C.; Brändle, L. Entrepreneurship and the Sustainable Bioeconomy Transformation. Environ. Innov. Soc. Transit. 2020, 37, 332–344. [Google Scholar] [CrossRef]
  5. Szarka, N.; Haufe, H.; Lange, N.; Schier, F.; Weimar, H.; Banse, M.; Sturm, V.; Dammer, L.; Piotrowski, S.; Thrän, D. Biomass Flow in Bioeconomy: Overview for Germany. Renew. Sustain. Energy Rev. 2021, 150, 111449. [Google Scholar] [CrossRef]
  6. Bengtsson, J.; Bullock, J.M.; Egoh, B.; Everson, C.; Everson, T.; O’Connor, T.; O’Farrell, P.J.; Smith, H.G.; Lindborg, R. Grasslands-More Important for Ecosystem Services than You Might Think. Ecosphere 2019, 10, e02582. [Google Scholar] [CrossRef]
  7. Pellaton, R.; Lellei-Kovács, E.; Báldi, A. Cultural ecosystem services in European grasslands: A systematic review of threats. Ambio 2022, 1–16. [Google Scholar] [CrossRef] [PubMed]
  8. Schils, R.L.M.; Bufe, C.; Rhymer, C.M.; Francksen, R.M.; Klaus, V.H.; Abdalla, M.; Milazzo, F.; Lellei-Kovács, E.; ten Berge, H.; Bertora, C.; et al. Permanent Grasslands in Europe: Land Use Change and Intensification Decrease Their Multifunctionality. Agric. Ecosyst. Environ. 2022, 330, 107891. [Google Scholar] [CrossRef]
  9. Ning, P.; Yang, G.; Hu, L.; Sun, J.; Shi, L.; Zhou, Y.; Wang, Z.; Yang, J. Recent Advances in the Valorization of Plant Biomass. Biotechnol. Biofuels 2021, 14, 102. [Google Scholar] [CrossRef] [PubMed]
  10. Ravindran, R.; Koopmans, S.; Sanders, J.P.M.; McMahon, H.; Gaffey, J. Production of Green Biorefinery Protein Concentrate Derived from Perennial Ryegrass as an Alternative Feed for Pigs. Clean Technol. 2021, 3, 656–669. [Google Scholar] [CrossRef]
  11. McEniy, J.; O’ Kiely, P. Developments in Grass-/Forage-Based Biorefineries. In Advances in Biorefineries; Elsevier: Amsterdam, The Netherlands, 2014; pp. 335–363. ISBN 978-0-85709-521-3. [Google Scholar]
  12. Patterson, T.; Massanet-Nicolau, J.; Jones, R.; Boldrin, A.; Valentino, F.; Dinsdale, R.; Guwy, A. Utilizing Grass for the Biological Production of Polyhydroxyalkanoates (PHAs) via Green Biorefining: Material and Energy Flows. J. Ind. Ecol. 2021, 25, 802–815. [Google Scholar] [CrossRef]
  13. Bröring, S.; Vanacker, A. Designing Business Models for the Bioeconomy: What Are the Major Challenges? EFB Bioecon. J. 2022, 2, 100032. [Google Scholar] [CrossRef]
  14. Golembiewski, B.; Sick, N.; Bröring, S. The Emerging Research Landscape on Bioeconomy: What Has Been Done so Far and What Is Essential from a Technology and Innovation Management Perspective? Innov. Food Sci. Emerg. Technol. 2015, 29, 308–317. [Google Scholar] [CrossRef]
  15. Orozco, R.; Mosquera-Losada, M.R.; Rodriguez, J.; Adamseged, M.E.; Grundmann, P. Supportive Business Environments to Develop Grass Bioeconomy in Europe. Sustainability 2021, 13, 12629. [Google Scholar] [CrossRef]
  16. Wohlgemuth, R.; Twardowski, T.; Aguilar, A. Bioeconomy Moving Forward Step by Step–A Global Journey. New Biotechnol. 2021, 61, 22–28. [Google Scholar] [CrossRef]
  17. Loorbach, D.; Wijsman, K. Business Transition Management: Exploring a New Role for Business in Sustainability Transitions. J. Clean. Prod. 2013, 45, 20–28. [Google Scholar] [CrossRef]
  18. Bröring, S.; Laibach, N.; Wustmans, M. Innovation Types in the Bioeconomy. J. Clean. Prod. 2020, 266, 121939. [Google Scholar] [CrossRef]
  19. Ghobakhloo, M.; Iranmanesh, M.; Grybauskas, A.; Vilkas, M.; Petraitė, M. Industry 4.0, Innovation, and Sustainable Development: A Systematic Review and a Roadmap to Sustainable Innovation. Bus. Strat. Environ. 2021, 30, 4237–4257. [Google Scholar] [CrossRef]
  20. Gao, C.; Zuzul, T.; Jones, G.; Khanna, T. Overcoming Institutional Voids: A Reputation-Based View of Long-Run Survival. Strat. Mgmt. J. 2017, 38, 2147–2167. [Google Scholar] [CrossRef] [Green Version]
  21. Moriggi, A. Exploring Enabling Resources for Place-Based Social Entrepreneurship: A Participatory Study of Green Care Practices in Finland. Sustain. Sci. 2020, 15, 437–453. [Google Scholar] [CrossRef] [Green Version]
  22. Adamseged, M.E.; Grundmann, P. Understanding Business Environments and Success Factors for Emerging Bioeconomy Enterprises through a Comprehensive Analytical Framework. Sustainability 2020, 12, 9018. [Google Scholar] [CrossRef]
  23. De Angelis, R. Circular Economy Business Models: A Repertoire of Theoretical Relationships and a Research Agenda. Circ. Econ. Sust. 2022, 2, 426–433. [Google Scholar] [CrossRef] [PubMed]
  24. Köhler, J.; Geels, F.W.; Kern, F.; Markard, J.; Onsongo, E.; Wieczorek, A.; Alkemade, F.; Avelino, F.; Bergek, A.; Boons, F.; et al. An Agenda for Sustainability Transitions Research: State of the Art and Future Directions. Environ. Innov. Soc. Transit. 2019, 31, 1–32. [Google Scholar] [CrossRef] [Green Version]
  25. Geels, F.W.; Schot, J. Typology of Sociotechnical Transition Pathways. Res. Policy 2007, 36, 399–417. [Google Scholar] [CrossRef]
  26. Ramcilovic-Suominen, S. Envisioning Just Transformations in and beyond the EU Bioeconomy: Inspirations from Decolonial Environmental Justice and Degrowth. Sustain. Sci. 2022, 17, 1139. [Google Scholar] [CrossRef]
  27. Dewangan, V.; Godse, M. Towards a Holistic Enterprise Innovation Performance Measurement System. Technovation 2014, 34, 536–545. [Google Scholar] [CrossRef]
  28. Sunding, D.; Zilberman, D. Chapter 4 The Agricultural Innovation Process: Research and Technology Adoption in a Changing Agricultural Sector. In Handbook of Agricultural Economics; Elsevier: Amsterdam, The Netherlands, 2001; Volume 1, pp. 207–261. ISBN 978-0-444-50728-0. [Google Scholar]
  29. Filser, M.; Kraus, S.; Breier, M.; Nenova, I.; Puumalainen, K. Business Model Innovation: Identifying Foundations and Trajectories. Bus. Strat. Environ. 2021, 30, 891–907. [Google Scholar] [CrossRef]
  30. Hellsmark, H.; Mossberg, J.; Söderholm, P.; Frishammar, J. Innovation System Strengths and Weaknesses in Progressing Sustainable Technology: The Case of Swedish Biorefinery Development. J. Clean. Prod. 2016, 131, 702–715. [Google Scholar] [CrossRef]
  31. Osterwalder, A.; Pigneur, Y.; Tucci, C.L. Clarifying Business Models: Origins, Present, and Future of the Concept. CAIS 2005, 16, 1–25. [Google Scholar] [CrossRef] [Green Version]
  32. Lewin, A.Y.; Volberda, H.W. The Future of Organization Studies: Beyond the Selection-Adaptation Debate. In The Oxford Handbook of Organization Theory; Oxford University Press: Oxford, UK, 2005; pp. 568–595. [Google Scholar] [CrossRef]
  33. van Loon-Steensma, J.M.; Goldsworthy, C. The Application of an Environmental Performance Framework for Climate Adaptation Innovations on Two Nature-Based Adaptations. Ambio 2022, 51, 569–585. [Google Scholar] [CrossRef]
  34. Wydra, S. Measuring Innovation in the Bioeconomy–Conceptual Discussion and Empirical Experiences. Technol. Soc. 2020, 61, 101242. [Google Scholar] [CrossRef]
  35. Aguinis, H.; Ramani, R.S.; Cascio, W.F. Methodological Practices in International Business Research: An after-Action Review of Challenges and Solutions. J. Int. Bus. Stud. 2020, 51, 1593–1608. [Google Scholar] [CrossRef]
  36. Giniuniene, J.; Jurksiene, L. Dynamic Capabilities, Innovation and Organizational Learning: Interrelations and Impact on Firm Performance. Procedia-Soc. Behav. Sci. 2015, 213, 985–991. [Google Scholar] [CrossRef] [Green Version]
  37. Hervas-Oliver, J.-L.; Boronat-Moll, C.; Sempere-Ripoll, F. On Process Innovation Capabilities in SMEs: A Taxonomy of Process-Oriented Innovative SMEs. J. Small Bus. Manag. 2016, 54, 113–134. [Google Scholar] [CrossRef]
  38. Piotrowski, S.; Carus, M.; Essel, R. Sustainable Biomass Supply and Demand:A Scenario Analysis. Open Agric. 2016, 1, 18–28. [Google Scholar] [CrossRef]
  39. Voss, C.; Tsikriktsis, N.; Frohlich, M. Case Research in Operations Management. Int. J. Oper. Prod. Manag. 2002, 22, 195–219. [Google Scholar] [CrossRef] [Green Version]
  40. Wheeler, D.; Ulsh, M. Manufacturing Readiness Assessment for Fuel Cell Stacks and Systems for the Back-up Power and Material Handling Equipment Emerging Markets 2009. Available online: https://www.nrel.gov/docs/fy10osti/45406.pdf (accessed on 1 July 2022).
  41. Evans, J.D.; Johnson, R.O. Tools for Managing Early-Stage Business Model Innovation. Res.-Technol. Manag. 2013, 56, 52–56. [Google Scholar] [CrossRef]
  42. Bitsch, V. Focus Group Discussions as a Research and Extension Method: The Case of Personnel Management Issues in Horticultural Businesses. Acta Hortic. 2004, 655, 461–469. [Google Scholar] [CrossRef]
  43. Ford, M.W.; Evans, J.R.; Matthews, C.H. Linking Self-assessment to the External Environment: An Exploratory Study. Int. J. Oper. Prod. Manag. 2004, 24, 1175–1187. [Google Scholar] [CrossRef]
  44. Dul, J. Necessary Condition Analysis (NCA): Logic and Methodology of “Necessary but Not Sufficient” Causality. Organ. Res. Methods 2016, 19, 10–52. [Google Scholar] [CrossRef]
  45. van der Valk, W.; Sumo, R.; Dul, J.; Schroeder, R.G. When Are Contracts and Trust Necessary for Innovation in Buyer-Supplier Relationships? A Necessary Condition Analysis. J. Purchasing Supply Manag. 2016, 22, 266–277. [Google Scholar] [CrossRef]
  46. Hauff, S. Analytical Strategies in HRM Systems Research: A Comparative Analysis and Some Recommendations. Int. J. Hum. Resour. Manag. 2021, 32, 1923–1952. [Google Scholar] [CrossRef]
  47. Dul, J.; Hak, T.; Goertz, G.; Voss, C. Necessary Condition Hypotheses in Operations Management. Int. J. Oper. Prod. Manag. 2010, 30, 1170–1190. [Google Scholar] [CrossRef] [Green Version]
  48. Knol, W.H.; Slomp, J.; Schouteten, R.L.J.; Lauche, K. Implementing Lean Practices in Manufacturing SMEs: Testing ‘Critical Success Factors’ Using Necessary Condition Analysis. Int. J. Prod. Res. 2018, 56, 3955–3973. [Google Scholar] [CrossRef] [Green Version]
  49. Tho, N.D. Firm Capabilities and Performance: A Necessary Condition Analysis. J. Manag. Dev. 2018, 37, 322–332. [Google Scholar] [CrossRef]
  50. Innovative Comparative Methods for Policy Analysis: Beyond the Quantitative-Qualitative Divide; Rihoux, B.; Grimm, H.M. (Eds.) Springer: New York, NY, USA, 2006; ISBN 978-0-387-28828-4. [Google Scholar]
  51. Salma, A.; Anas, C.; Mohammed, E.H. How Can Top Management Succeed in a Lean Manufacturing Implementation in the Small and Medium Sized Enterprises? In Proceedings of the 2018 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA), Tangier, Morocco, 26–27 April 2018; pp. 176–181. [Google Scholar]
  52. Vis, B.; Dul, J. Analyzing Relationships of Necessity Not Just in Kind But Also in Degree: Complementing FsQCA With NCA. Sociol. Methods Res. 2018, 47, 872–899. [Google Scholar] [CrossRef] [Green Version]
  53. Navrátilová, L.; Výbošťok, J.; Dobšinská, Z.; Šálka, J.; Pichlerová, M.; Pichler, V. Assessing the Potential of Bioeconomy in Slovakia Based on Public Perception of Renewable Materials in Contrast to Non-Renewable Materials. Ambio 2020, 49, 1912–1924. [Google Scholar] [CrossRef] [PubMed]
  54. Kurka, S.; Menrad, K.; Kurka, S.; Menrad, K. Biorefineries and Biobased Products from the Consumer’s Point of View. 2009. Available online: https://ageconsearch.umn.edu/record/91330/ (accessed on 1 July 2022). [CrossRef]
  55. Sijtsema, S.J.; Onwezen, M.C.; Reinders, M.J.; Dagevos, H.; Partanen, A.; Meeusen, M. Consumer Perception of Bio-Based Products—An Exploratory Study in 5 European Countries. NJAS Wagening. J. Life Sci. 2016, 77, 61–69. [Google Scholar] [CrossRef]
  56. Biggs, R.; Clements, H.; de Vos, A.; Folke, C.; Manyani, A.; Maciejewski, K.; Martín-López, B.; Preiser, R.; Selomane, O.; Schlüter, M. What Are Social-Ecological Systems and Social-Ecological Systems Research? In The Routledge Handbook of Research Methods for Social-Ecological Systems; Routledge: London, UK, 2021; pp. 3–26. ISBN 978-1-00-302133-9. [Google Scholar]
  57. Dewald, U.; Truffer, B. The Local Sources of Market Formation: Explaining Regional Growth Differentials in German Photovoltaic Markets. Eur. Plan. Stud. 2012, 20, 397–420. [Google Scholar] [CrossRef]
  58. Lynn, G.S.; Morone, J.G.; Paulson, A.S. Marketing and Discontinuous Innovation: The Probe and Learn Process. Calif. Manag. Rev. 1996, 38, 8–37. [Google Scholar] [CrossRef]
  59. Chaithanapat, P.; Punnakitikashem, P.; Khin Khin Oo, N.C.; Rakthin, S. Relationships among Knowledge-Oriented Leadership, Customer Knowledge Management, Innovation Quality and Firm Performance in SMEs. J. Innov. Knowl. 2022, 7, 100162. [Google Scholar] [CrossRef]
  60. Zimmerling, E.; Purtik, H.; Welpe, I.M. End-Users as Co-Developers for Novel Green Products and Services—An Exploratory Case Study Analysis of the Innovation Process in Incumbent Firms. J. Clean. Prod. 2017, 162, S51–S58. [Google Scholar] [CrossRef]
  61. Yildirim, S. The Consumer Role for Sustainable Development: How Consumers Contribute Sustainable Development Goals. In Advances in Marketing, Customer Relationship Management, and E-Services; Chkoniya, V., Madsen, A.O., Bukhrashvili, P., Eds.; IGI Global: Hershey, PA, USA, 2020; pp. 325–341. ISBN 978-1-79983-115-0. [Google Scholar]
  62. Venus, J.; Richter, K. Development of a Pilot Plant Facility for the Conversion of Renewables in Biotechnological Processes. Eng. Life Sci. 2007, 7, 395–402. [Google Scholar] [CrossRef]
  63. Ghisellini, P.; Cialani, C.; Ulgiati, S. A Review on Circular Economy: The Expected Transition to a Balanced Interplay of Environmental and Economic Systems. J. Clean. Prod. 2016, 114, 11–32. [Google Scholar] [CrossRef]
  64. Hinderer, S.; Kuckertz, A. The Bioeconomy Transformation as an External Enabler of Sustainable Entrepreneurship. Bus. Strat. Environ. 2022, 1–17. [Google Scholar] [CrossRef]
  65. Lacy, P.; Rutqvist, J. Waste to Wealth: The Circular Economy Advantage; Palgrave Macmillan: New York, NY, USA, 2015; ISBN 978-1-137-53068-4. [Google Scholar]
  66. Mulder, K.F. Innovation for Sustainable Development: From Environmental Design to Transition Management. Sustain. Sci. 2007, 2, 253–263. [Google Scholar] [CrossRef] [Green Version]
  67. Rizos, V.; Behrens, A.; van der Gaast, W.; Hofman, E.; Ioannou, A.; Kafyeke, T.; Flamos, A.; Rinaldi, R.; Papadelis, S.; Hirschnitz-Garbers, M.; et al. Implementation of Circular Economy Business Models by Small and Medium-Sized Enterprises (SMEs): Barriers and Enablers. Sustainability 2016, 8, 1212. [Google Scholar] [CrossRef] [Green Version]
  68. Bauer, F.; Coenen, L.; Hansen, T.; McCormick, K.; Palgan, Y.V. Technological Innovation Systems for Biorefineries: A Review of the Literature. Biofuels Bioprod. Bioref. 2017, 11, 534–548. [Google Scholar] [CrossRef] [Green Version]
  69. Borge, L.; Bröring, S. Exploring Effectiveness of Technology Transfer in Interdisciplinary Settings: The Case of the Bioeconomy. Creat. Innov. Manag. 2017, 26, 311–322. [Google Scholar] [CrossRef]
  70. Berrone, P.; Fosfuri, A.; Gelabert, L.; Gomez-Mejia, L.R. Necessity as the Mother of ‘Green’ Inventions: Institutional Pressures and Environmental Innovations. Strat. Mgmt. J. 2013, 34, 891–909. [Google Scholar] [CrossRef]
  71. Rönnlund, I.; Pursula, T.; Bröckl, M.; Hakala, L.; Luoma, P.; Aho, M.; Pathan, A.; Pallesen, B.E. Creating Value from Bioresources: Innovation in Nordic Bioeconomy; Nordic Innovation: Oslo, Norway, 2014; Available online: https://nordregio.org/wp-content/uploads/2014/11/Creating-value-from-bioresources.pdf (accessed on 1 July 2022).
  72. Kusa, R.; Duda, J.; Suder, M. Explaining SME Performance with FsQCA: The Role of Entrepreneurial Orientation, Entrepreneur Motivation, and Opportunity Perception. J. Innov. Knowl. 2021, 6, 234–245. [Google Scholar] [CrossRef]
  73. Paiva, T.; Ribeiro, M.; Coutinho, P. R&D Collaboration, Competitiveness Development, and Open Innovation in R&D. JOItmC 2020, 6, 116. [Google Scholar] [CrossRef]
  74. Musiolik, J.; Markard, J.; Hekkert, M. Networks and Network Resources in Technological Innovation Systems: Towards a Conceptual Framework for System Building. Technol. Forecast. Soc. Chang. 2012, 79, 1032–1048. [Google Scholar] [CrossRef] [Green Version]
  75. Tura, N.; Hanski, J.; Ahola, T.; Ståhle, M.; Piiparinen, S.; Valkokari, P. Unlocking Circular Business: A Framework of Barriers and Drivers. J. Clean. Prod. 2019, 212, 90–98. [Google Scholar] [CrossRef]
  76. Geels, F.W.; Verhees, B. Cultural Legitimacy and Framing Struggles in Innovation Journeys: A Cultural-Performative Perspective and a Case Study of Dutch Nuclear Energy (1945–1986). Technol. Forecast. Soc. Chang. 2011, 78, 910–930. [Google Scholar] [CrossRef]
  77. Konrad, K. Expectation Dynamics: Ups and Downs of Alternative Fuels. Nat. Energy 2016, 1, 16022. [Google Scholar] [CrossRef]
  78. Devaney, L.; Iles, A. Scales of Progress, Power and Potential in the US Bioeconomy. J. Clean. Prod. 2019, 233, 379–389. [Google Scholar] [CrossRef]
  79. Bugge, M.; Hansen, T.; Klitkou, A. What Is the Bioeconomy? A Review of the Literature. Sustainability 2016, 8, 691. [Google Scholar] [CrossRef] [Green Version]
  80. Agbor, V.; Carere, C.; Cicek, N.; Sparling, R.; Levin, D. Advances in Biorefineries: Biomass and Waste Supply Chain Exploitation; Waldron, K.W., Ed.; Woodhead Publishing Series in Energy; Elsevier/Woodhead Publishing: Amsterdam, The Netherlands, 2014; pp. 234–258. ISBN 978-0-85709-521-3. [Google Scholar]
  81. Prochnow, A.; Heiermann, M.; Plöchl, M.; Linke, B.; Idler, C.; Amon, T.; Hobbs, P.J. Bioenergy from Permanent Grassland–A Review: 1. Biogas. Bioresour.Technol. 2009, 100, 4931–4944. [Google Scholar] [CrossRef] [PubMed]
  82. Jarre, M.; Petit-Boix, A.; Priefer, C.; Meyer, R.; Leipold, S. Transforming the Bio-Based Sector towards a Circular Economy–What Can We Learn from Wood Cascading? Forest Policy Econ. 2020, 110, 101872. [Google Scholar] [CrossRef]
  83. Stefan, H.; Durksz, D.; Van der Weide, R. Review Paper on Traditional and Alternative Grassland Management Technologies. 2020. Available online: https://www.go-grass.eu/wp-content/uploads/2020/09/D2.1-Review-paper-on-traditional-and-alternative-grassland-management-technologies.pdf (accessed on 1 July 2022).
  84. Atashbar, N.Z.; Labadie, N.; Prins, C. Modeling and Optimization of Biomass Supply Chains: A Review and a Critical Look. IFAC-PapersOnLine 2016, 49, 604–615. [Google Scholar] [CrossRef]
  85. Reim, W.; Parida, V.; Sjödin, D.R. Circular Business Models for the Bio-Economy: A Review and New Directions for Future Research. Sustainability 2019, 11, 2558. [Google Scholar] [CrossRef] [Green Version]
  86. Ritter, T.; Lettl, C. The Wider Implications of Business-Model Research. Long Range Plan. 2018, 51, 1–8. [Google Scholar] [CrossRef]
  87. Samson, D.; Gloet, M. Innovation Capability in Australian Manufacturing Organisations: An Exploratory Study. Int. J. Prod. Res. 2014, 52, 6448–6466. [Google Scholar] [CrossRef]
  88. Alkemade, F.; Kleinschmidt, C.; Hekkert, M. Analysing Emerging Innovation Systems: A Functions Approach to Foresight. IJFIP 2007, 3, 139. [Google Scholar] [CrossRef]
  89. Fehrer, J.A.; Wieland, H. A Systemic Logic for Circular Business Models. J. Bus. Res. 2021, 125, 609–620. [Google Scholar] [CrossRef]
  90. Boda, C.S. Values, Science, and Competing Paradigms in Sustainability Research: Furthering the Conversation. Sustain. Sci. 2021, 16, 2157–2161. [Google Scholar] [CrossRef]
  91. Karlqvist, A. Going beyond Disciplines: The Meanings of Interdisciplinarity. Policy Sci. 1999, 32, 379–383. [Google Scholar] [CrossRef]
  92. Boval, M.; Angeon, V.; Rudel, T. Tropical Grasslands: A Pivotal Place for a More Multi-Functional Agriculture. Ambio 2017, 46, 48–56. [Google Scholar] [CrossRef]
  93. Xu, J.; Renaud, F.G.; Barrett, B. Modelling Land System Evolution and Dynamics of Terrestrial Carbon Stocks in the Luanhe River Basin, China: A Scenario Analysis of Trade-Offs and Synergies between Sustainable Development Goals. Sustain. Sci. 2021, 17, 1323–1345. [Google Scholar] [CrossRef]
  94. Stek, K.; Schiele, H. How to Train Supply Managers–Necessary and Sufficient Purchasing Skills Leading to Success. J. Purch. Supply Manag. 2021, 27, 100700. [Google Scholar] [CrossRef]
  95. Gatto, A. Polycentric and Resilient Perspectives for Governing the Commons: Strategic and Law and Economics Insights for Sustainable Development. Ambio 2022, 51, 1921–1932. [Google Scholar] [CrossRef] [PubMed]
  96. Kimmich, C.; Baldwin, E.; Kellner, E.; Oberlack, C.; Villamayor-Tomas, S. Networks of Action Situations: A Systematic Review of Empirical Research. Sustain. Sci. 2022, 1–16. [Google Scholar] [CrossRef]
  97. Pahl-Wostl, C. The Implications of Complexity for Integrated Resources Management. Environ. Model. Softw. 2007, 22, 561–569. [Google Scholar] [CrossRef] [Green Version]
  98. Smit, H.J.; Metzger, M.J.; Ewert, F. Spatial Distribution of Grassland Productivity and Land Use in Europe. Agric. Syst. 2008, 98, 208–219. [Google Scholar] [CrossRef]
  99. Kirchgässner, G. The Role of Homo Oeconomicus in the Political Economy of James Buchanan. Const. Polit. Econ. 2014, 25, 2–17. [Google Scholar] [CrossRef] [Green Version]
  100. Kennedy, S.; Fuchs, M.; Ingen, W.; Schoenmaker, D. A Resilience Approach to Corporate Biodiversity Impact Measurement. Bus. Strat. Environ. 2022, bse.3140. [Google Scholar] [CrossRef]
  101. Zhao, Y.; Liu, Z.; Wu, J. Grassland Ecosystem Services: A Systematic Review of Research Advances and Future Directions. Landsc. Ecol. 2020, 35, 793–814. [Google Scholar] [CrossRef]
  102. Eisenack, K.; Oberlack, C.; Sietz, D. Avenues of Archetype Analysis: Roots, Achievements, and next Steps in Sustainability Research. E&S 2021, 26, art31. [Google Scholar] [CrossRef]
Joitmc 08 00180 g001 550
Figure 1. Scatter Plot for Customer and Innovation Readiness.
Figure 1. Scatter Plot for Customer and Innovation Readiness.
Joitmc 08 00180 g001
Joitmc 08 00180 g002 550
Figure 2. Scatter Plot for Technology and Innovation Readiness.
Figure 2. Scatter Plot for Technology and Innovation Readiness.
Joitmc 08 00180 g002
Joitmc 08 00180 g003 550
Figure 3. Scatter Plot for Funding and Innovation Readiness.
Figure 3. Scatter Plot for Funding and Innovation Readiness.
Joitmc 08 00180 g003
Joitmc 08 00180 g004 550
Figure 4. Scatter Plot for Team and Innovation Readiness.
Figure 4. Scatter Plot for Team and Innovation Readiness.
Joitmc 08 00180 g004
Joitmc 08 00180 g005 550
Figure 5. Scatter Plot for Manufacturing and Innovation Readiness.
Figure 5. Scatter Plot for Manufacturing and Innovation Readiness.
Joitmc 08 00180 g005
Joitmc 08 00180 g006 550
Figure 6. Scatter Plot for Business and Innovation Readiness.
Figure 6. Scatter Plot for Business and Innovation Readiness.
Joitmc 08 00180 g006
Joitmc 08 00180 g007 550
Figure 7. Scatter Plot for IPR and Innovation Readiness.
Figure 7. Scatter Plot for IPR and Innovation Readiness.
Joitmc 08 00180 g007
Table
Table 1. Readiness levels assessment of grass-based businesses cases.
Table 1. Readiness levels assessment of grass-based businesses cases.
Case IDCountry TRLBRLCRLIPRFRLTMRLMRLIRL
1Denmark 77759888
2Netherlands74625556
3Germany 53413454
4Germany 99899899
5Sweden 77727577
6Hungary21211222
7Romania 43513323
8Spain 22511323
Table
Table 2. NCA parameters of the seven necessary conditions for upscaling grass-based businesses.
Table 2. NCA parameters of the seven necessary conditions for upscaling grass-based businesses.
Condition Method Effect Size (d)
Customer ReadinessCE-FDH0.619
Technology Readiness CE-FDH0.612
Funding ReadinessCE-FDH0.571
Team ReadinessCE-FDH0.571
Manufacturing ReadinessCE-FDH0.551
Business ReadinessCE-FDH0.518
IPR ReadinessCE-FDH0.268
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Orozco, R.; Grundmann, P. Readiness for Innovation of Emerging Grass-Based Businesses. J. Open Innov. Technol. Mark. Complex. 2022, 8, 180. https://doi.org/10.3390/joitmc8040180

AMA Style

Orozco R, Grundmann P. Readiness for Innovation of Emerging Grass-Based Businesses. Journal of Open Innovation: Technology, Market, and Complexity. 2022; 8(4):180. https://doi.org/10.3390/joitmc8040180

Chicago/Turabian Style

Orozco, Richard, and Philipp Grundmann. 2022. "Readiness for Innovation of Emerging Grass-Based Businesses" Journal of Open Innovation: Technology, Market, and Complexity 8, no. 4: 180. https://doi.org/10.3390/joitmc8040180

APA Style

Orozco, R., & Grundmann, P. (2022). Readiness for Innovation of Emerging Grass-Based Businesses. Journal of Open Innovation: Technology, Market, and Complexity, 8(4), 180. https://doi.org/10.3390/joitmc8040180

Article Metrics

Back to TopTop