**Abstract:** The survival of companies in globalized and highly competitive markets, heavily depends on their ability to innovate through the creation of new products and/or services, supported by sustainable processes to prevent business failure. There are many factors regarding the interface company/stakeholders/market at all hierarchical levels, which have a major contribution to sustain innovation in processes regarding the creation of new products and services. A holistic approach of all these factors, as a whole, has not been a subject of scientific research conducting to the necessity of creating a proposal of a framework that can be integrated and systemic. Thus, this paper aims to propose a functional holistic model, which integrates the strategic, organizational and operational levels regarding market business and company interaction, as well as the set of factors to take into account to guarantee assurance that innovative processes are sustained, when new products and/or services are created or improved. Conducted through an investigation of the state of the art, by literature review, a comprehensive and integrated conceptual model was built in a deductive-inductive way. Then, the conceptual model was validated through four case studies. Finally, it was found that the conceptual framework became functional, because its applicability has been successfully tested in a business environment. As a result, the tool developed here, can be useful to measure and evaluate projects dedicated to companies that innovate in a sustainable way.

**Keywords:** sustainability; innovation; new products; functional framework; SIFSNPIP; case studies

#### **1. Introduction**

Competitive new products and services are the output of sustainable innovative processes that companies manage in a systematic way, challenged by demanding and dynamic business markets [1]. According to [2], sustainable innovative processes are crucial for the survival of competitive companies, being a major factor for business success [3]. Also, firms should undertake their ideas about sustainable innovative products and services, and bring it to market as quickly that they can, to be competitive in nowadays global markets [4]. But the sustainability of innovative processes that support new product creation is not an easy process, and therefore a project can fail even when it was initially estimated to succeed. So, the innovative processes developed to create new sustainable products, involves considerable and various risks due to the uncertainty associated to business markets, according to [5]. Thus, risk is a strong obstacle to be transposed in business market characterizes by uncertainty, complexity and turbulence, according to [2,6]. So, the shortening of the available time to manage

projects with both efficiently and effectively, is a very important issue to be taken in account by managers, especially when they concern relating to products and services of radical innovative nature [7]. According to [6], companies should manage their projects in a proactive, structured and sustainable way, to survive and succeed in such competitive markets, and for that, sharing knowledge through collaborative networks is crucial [8], taking in account all possible variables and parameters that have influence in the strategic, organizational and operational hierarchical levels of companies [9]. This finding is extremely important regarding new products and services that emerge of innovative projects and their sustainable implementation, which requires an increasing rational and holistic approach [10]. It is extremely challenging for companies the development of successful sustainable innovative processes to create new products or services, and for that the path that involves generation of new ideas is crucial. New idea generation occurs normally in the beginning of sustainable innovation processes to generate new products and services. So, this point is especially important, since it determines companies potential to undertake promising new product and service ideas at reasonable costs. In contexts where resources are constrained, creativity seems to be extremely contributive to problem-solving processes [11].

During literature review, was found a lack of holistic approaches or frameworks that could encompass the strategic, organizational and operational hierarchical levels of companies, in order to create new products and services through sustainable innovative projects, aiming the minimization of the risks of business failure inherent to its implementation. To serve these needs, it's proposed in this paper a "Systemic and Integrated Framework for Sustainability of New Product Innovation Processes"—SIFSNPIP. Thus, an extensive literature review supporting the construction of conceptual version of SIFSNPIP was carried out and it's presented on Section 2 of this paper. In Section 3, the key phases regarding the research methodology approached in this paper are presented. Section 4 presents and describes the case studies that were carried out to validate conceptual SIFSNPIP model and shows the aspects that were found which allowed to transform the model from conceptual to functional. In Section 5 the full framework of SIFSNPIP it's presented. Finally, the main of this investigation conclusions are presented in Section 6.

#### **2. Literature Review**

In order to design a theoretical framework, that determines the sustainability of innovative processes in the creation of new products or services, it was needed to find the most relevant set of variables and parameters that comprise strategic, corporative and operational business levels, as well as the way they interact with each other.

Firstly the approach of the strategic level was needed in order to understand which aspects embrace the company/market interactions and its ways of articulation. Secondly was found that the organizational level can be decomposed into two sub-levels with the same importance to a company: the corporate culture with a structural nature and the management principles that normally respond with market situations. Thirdly, the operational level was approached, as well as its inherent processual variables. So, the developed literature review was organized in this sequence, as Figure 1 illustrates. In there, the arrows between all levels, show the way of the relationship that the three levels have among themselves.

**Figure 1.** General framework of the approach of the Systemic and Integrated Framework for Sustainability of New Product Innovation Processes (SIFSNPIP) (authors' own elaboration).

#### *2.1. Systemic and Strategic Environment in Sustainability of Innovative Processes that Support New Products (SIPSNP)*

In the strategic level of the SIPSNP, is crucial for managers to take in account the relationship between: sustainable strategic innovation; source of new product or service creation; and the concept of business strategy. Sustainable strategic innovation in a highly competitive environment, embodies industries regarding both disruptive and incremental nature. The first one exists in markets without competitors, designated by "blue ocean strategy" (BOS), and the second exists whenever there is competition, designated by "red ocean strategy" (ROS) [12].

BOS is especially important when companies and businesses need to grow fast, and rather than compete with existing rivals as happens in ROS, BOS allows the creation of unique offerings for the emerging new markets [12].

Despite the above mentioned, is normal that hybrid strategies to be very common in business markets in which firms develop sustainable new products and services that emanate from innovation that embraces both radical and gradual processes, and in this context, hybrid strategies are called "purple ocean strategy" (POS) [13]. POS strategy corresponds to disruptive products and services with no competition at the beginning and while the possibility to remain like that exists. At the same time, other products regarding incremental innovation faces the existent competition. Beyond these strategies, companies have more challenges involving other factors of strategic nature that must be also considered, thus they require accurate analysis of correspondent trade-offs involved, namely facts concerning various risks and their interaction [14]. In a competitive environment along with high complexity of production processes risks of business failure must be analyzed in a systematic way, which means, with a continuous analysis of trade-offs involving the various risk factors of SIPSNP, especially those regarding quality, time and costs [15].

Independently of the SIPSNP strategies being radical, incremental or mixed, companies can't ignore the risks which they are exposed and must to be aware at the dynamics of competition through the implementation of systematic benchmarking practices [16]. For companies achieve the best performances of SIPSNP business, [17] concluded that teamwork, multidisciplinary and collaborative attitude have a huge impact in benchmarking practices efficiency and effectiveness, which should integrate the corporate culture of firms. According to [18], the globalization of markets and businesses is a trend that will remain strong in long term. Therefore an unavoidable aspect of globalization has been outsourcing practices, especially the knowledge-based services, such as the development of SIPSNP. Companies all over the world need to reduce costs, but the question is not the need of a particular practice of outsourcing or working abroad, but when and how it will be done to achieve greater competitive advantage in the market [18]. One special fact that arises in a particular process of outsourcing and/or offshoring is the "intellectual property" (IP) jointly developed. According to [18], exploitation and defense of IP, when generating both incremental and radical innovation, have impact on the strategic management of the focal company. Globalization and internationalization of business regarding SIPSNP projects, often correspond to engineering and management complex systems involving R&D and information highly reserved [19]. The strategic options pointed out are associated to risks of opportunistic expropriation of knowledge and related monitoring costs of the subcontracted partners, which sometimes are not only distant in geography but also in culture [19]. The focal company must have enough responsibility, knowledge and skills to ensure control over the processes regarding, onshore/offshore, third-party option (third-party logistics 3pl) decisions to guarantee that the final product or service fulfils the customer's needs. Therefore, all stakeholders involved in a business must integrate a network of synergies, to ensure the articulation of all processes regarding SIPSNP projects, but this fact increases complexity to the whole system and the concomitant risk that can emerge from the failure of each element. That's why the risks must be predicted so they can be avoided when trade-offs are considered [20].

A way of prevent the risks of business failure is the systematic relationship between companies and the market, meeting and even anticipating the customers' needs [21]. Therefore, the marketing performs an important point of articulation between a company and its customers, through the establishment of a systematic interaction between them promoting to companies the perception and understanding of the "voice of the customer" [22]. To this purpose, [22–24] point out some three important aspects: (1) a permanent interaction between the company and the customer to provide exchange of information, namely suggestions from the customer and a validation-built step by step between the designer and the customer, concerning the phases of products or services design; (2) in cases of products or services customization, it is crucial to considerate that the solution was obtained after experiments validated by the customer; (3) the existence of suppliers involvement with the company to ensure the sustainability the design of new products or services from the beginning.

In SIPSNP projects it is very important to consider, in strategic terms, if innovation requires the marketing function, because the role played by it in the whole new products or services design also depends on the level of innovation required, in order to obtain a positive trade-off regarding marketing/quality/cost/time [25].

From a general perspective, obtained from the literature review on the most relevant factors that comprise a strategic vision in SIPSNP environment described above, is presented in Figure 2 with a thereof summary of SIPSNP.

#### *2.2. Organizational Parameters*

From literature review it was found that several parameters have influence in firms that develop new products with sustainable innovative processes, in a structural way, and that they reported to the corporate culture; and the ones of a conjunctural order were derivate from management principles. It was also enlighten by the existing literature that each type of parameters is associated to specific factors, which will be covered in the following two sections.

#### 2.2.1. Corporate Culture

In strategic management, the organizational parameters are considered part of the corporate culture. And one of the most relevant is the ability to function in the development of sustainable innovative projects with cross-functional teams perfectly connected in a systematic way. Therefore, many authors advise multidisciplinary, multifunctional and/or cross-functional organization type [1,26–29]. Such connections pass through the formation of collaborative teams, which should include at least employees

of the organization, suppliers and customers. So, it is crucial to have a reliable information flow that ensure visibility and transparency in connecting people, processes and technologies.

The organizational strategy of working in multidisciplinary integrated teams (cross-functional) is increasingly suitable to companies that develop new products and services, due to markets globalization, existing together in partnerships and collaborative alliances with inter-organizational information sharing skills and sustainable innovation [30]. That is, a whole innovation capacity, radical and incremental, in organizations that work on network and that encompass collaboration with customers and suppliers [31].

Another way to characterize the sustainable innovative processes concerns to open innovation, in which resources move easily at the border or interface company/market [32]. Whenever open innovation must be shared as a partnership or strategic alliance, it assumes the designation of co-innovation [33]. This shared innovation, benefits the value chain to the customer, called a win-win relationship, and is of a major importance for companies to create value in the market. According to [34], with co-innovation different internal and external sources are integrated into a platform in order to turn the company more competitive and able to satisfy the customer's voice that means the existence of co-creation, co-design and joint development [35].

It follows that the corporate culture should incorporate another common inter-organizational factor: the competitiveness. That is, to incorporate in the company a competitive spirit associated with the effectiveness and success of sustainable new products and services available to the market [36].

#### 2.2.2. Management Principles

Regarding the principles of management, the main organizational parameters that allow companies to respond to the market situations, are the following: compliance with legislation of the product inherent to each of the specific markets regarding new products or services development, manufacturing and commercialization [37]; product standardization that permits conformity with international rules and internal flexibility, facilitating modularization processes [38,39]; certification [39]; the agility of performance [40], connected with lean thinking [41,42] in the search for maximum efficiency, effectiveness and productivity [43].

In order to embody the paradigm of optimal productivity is needed to combine lean practices with flexibility and agility, especially when companies need to manufacture various types of products simultaneously [44,45]. Concluded about the importance to associate lean and agile concepts, so they proposed the term "leagility" aiming to integrate them in the paradigm of Supply Chain Management (SCM) in response to market's needs. Likewise, the terms flexibility and proactive flexibility were combined into the term "adaptability" according to [46]. On Figure 3, it's summarized the relevant factors of SIPSNP integrated at the organizational level.

**Figure 3.** Organizational parameters. Framework Approach (authors' own elaboration).

#### *2.3. Process Variables*

According to literature review, are considered as relevant the following process variables: undertaking an idea of the product or service through a process of innovation management [47]; the organization and management of the project [19]; the quality and control of a project [22] and the engineering and technological capabilities [48,49].

Sustainable innovation management is a methodical process of new ideas generation that allows companies to create value in a proactive way [47], and that can be done in so many ways, therefore that's why each innovation process is unique [50]. From product and service perspective, innovation in a sustainable way to prevent and minimize risks of failure, is therefore a process of creation something new (a product, a service, a process, etc.) yet unknown by the market, and that is due mainly to creative capacity and the technologies available to undertake it. So, it is not a casual situation, but an overall process extending over time [51]. The generation of ideas is a fundamental part of an innovation process that can be convergent or divergent: it is convergent when the idea is the result of a systematic collective process based on trial and error; and it is divergent when a "flash of genius" of some bright and creative collaborator occurs. According to [52], an innovative value chain consists of three main phases: generation of ideas; sorting of ideas and their development; and its dissemination through organization to the market. If it is decided to undertake an innovative idea into a new product or service, the next step will be the project management of SIPSNP.

Many authors as [29,53], present classic models that are examples of "organizational architectures" that group, compose and arrange sub-teams, their inter-relationships and hierarchies. Information flows and "architecture of processes" allow to properly delegate the work to be carried out through the hierarchical levels of companies, as well and the respective flow-related information those levels, aiming to achieve projects goals [20]. Present a model regarding iterative project management, or spiral model, in which flexible changing of work specifications are possible, avoiding the need of restart the whole project from the beginning, modifying only the necessary steps when market changes occur. There are other kind of proposed managing models for SIPSNP projects that are more flexible and agile, widely used by companies worldwide and scientifically known, like simultaneous or concurrent engineering [54–57], and Stage–Gate® [58–60].

Another process variable to have in account in SIPSNP projects is the quality of products and services which are inherent to them [60]. And Taguchi (1986) method is a very important tool used by managers, because of its importance to achieve sufficiently robust outputs with high quality levels [25].

SIPSNP implementation also implies to know and to control engineering and technological capabilities [48,49,61]. Conclude about the importance of prototyping whenever it is needed, and since engineering, technology, quality and reliability are very important issues in those kind of processes, teamwork and collaboration across all hierarchical levels, are crucial for its success. Figure 4 illustrates the most relevant process variables approached by literature review.

**Figure 4.** Operational level variables. Framework Approach (authors' own elaboration).

#### *2.4. Problems and Innovative Solutions*

Markets are increasingly demanding for sustainable and innovative products and services, additionally more information is required by customers, about the environmental impact of products and services provided by companies. Modern management must use sophisticated tools to meet such expectations, so it can be possible to improve monitoring processes of products and services impact, in order to understand how they can be made more sustainable. Regarding products and services lifecycle, which impact is not caused only by the industrial processes or even the usage of

products and services, but also by natural methods of extraction and exploitation of raw materials and others, the transport and storage processes, etc. Therefore, a key factor for a successful sustainability management concerns to the availability and sharing of relevant data and knowledge that must be wisely shared and used along all logistic chain regarding to developed projects [62].

The tools and methodologies available to serve problem solving regarding SIPSNP, are one of the most important issues of a project [63,64]. Conducted a survey of about three dozen tools and techniques obtained through an extensive literature review and realization of several case studies on Taiwanese companies, as well as interviews with experts in the field. Based on [63,64] work, a sample of the most important tools for SIPSNP projects is presented in Table 1.

**Survey of Tools to Support SIPSNP Grouping Tools and Methodologies** Creative and Innovative Solutions TRIZ; DOE; DFX; Pugh analysis; Creative Design; Axiomatic Design Focus on Quality Function QFD (e.g.: Kano Model; Ishikawa diagram; DFMEA; Pareto law) Focus on Precision Manufacturing DFSS (DMAIC cycle and it's variants) Focus on Involvement of Suppliers SDI Design Support Robust Design; **Modular** Design; CE Decision Support AHP; CBR; DEA; Delphi Panel; Fuzzy logics; Neuronal Networks

**Table 1.** Systemic and Strategic Environment in Sustainability of Innovative Processes that Support New Products (SIPSNP) tools and methodologies (authors' own elaboration).

Acronyms: TRIZ (Theory of Inventive Problem Solving); DOE (Design of Experiments); DFX (Design for Excellence); QFD (Quality Function Development); DFMEA (Design Failure Model and Effect Analysis); DFSS (Design for Six Sigma); DMAIC (Define-Measure-Analyze-Improve-Control); CE (Concurrent Engineering); AHP (Analytical Hierarchy Process); CBR (Case Based Reasoning); DEA (Data Envelopment Analysis).

Due to the fact that in the literature was found a general confusion about the application of the terms "tools" and "methodologies", for this paper they were grouped putting its focus on their use. Therefore, they were grated as follows: "Creative and Innovative Solutions"; "Quality Function"; "Precision Manufacturing"; "Involvement of Suppliers"; "Design Support" and "Decision Support". Also there was considerate that if similar problems occur, is not guaranteed that they will have similar solutions, because markets are dynamic, and along with that uncertainties can emerge [65]. Uncertainly can be reduced by if the company has an adequate portfolio of problems and respective solutions, and for that the methodology "Case-Based Reasoning" (CBR) can be extremely useful [66]. When a problem is new, there won't be any solutions to solve it obtained from the above mentioned portfolio, so it is necessary to use any of the available methodologies and presented in Table 1. But, if there are several solutions available in such portfolio, it is necessary to determine a ranking of solutions in order to adopt the more suitable one to the existent problem. And for that, one of the most commonly used method is the Analytical Hierarchy Process (AHP). According to [67,68], AHP is very useful to rank the various possible alternatives to support the decision making process. The different ways to achieve a solution to an existing problem, regarding SIPSNP projects, is illustrated in Figure 5.

**Figure 5.** Problems and innovative solutions. Framework Approach (authors' own elaboration).

#### **3. Research Methodology**

As already mentioned, the objective of this investigation is to build a holistic model, which can become a support tool for the sustainable development of innovative processes for creating products and/or services (both incremental and radical), that is, a model that can serve as a roadmap for companies working in this area.

The literature review resulted in a survey, as exhaustive as possible, in a deductive way of the current state of the art and of the set of existing or proposed models for relevant but partial issues of this theme, as long as its methods and tools. The theoretical investigation was conducted in an exploratory way through a deductive-inductive strategy, given that the topic in question adapts to strategic management issues, whose problems and their solutions always involve so many aspects and perspectives, which vary with the changes that constantly occur in the markets that are currently globalized, hampering decision-making processes. It is intended that the main added value of this investigation is evidenced by the difference in the level of science in question between the situation of a possible pulverization of partial models and the construction of the holistic, comprehensive and integrated model, which is intended to be achieved with the work developed.

The proposed model was initially conceptual, as it was obtained thanks to the inductive jump performed after deduction in a qualitative type investigation, having been empirically tested at a later stage, with its external empirical validation through a set of case studies on sustainability innovative processes for creating products and/or services in a national and international industrial environment (in case studies involving projects with partners worldwide). The purpose of this validation was not to generate theory, but only to test, validate and improve it. And so, the conceptual model obtained became functional, because it was shown that it actually works in an industrial environment.

Therefore, it was decided from the beginning on a deductive-inductive structure research, through literature review that it was possible to achieve the conceptual model SIFSNPIP, and there was the need for its empirical validation. Then, for the validation of the model case studies in industrial environment were performed, since most issues to validate were questions of "how" and "why" type, in their qualitative and explanatory variant, as recommended by [69]. In accordance with this work goals, the research was generally regarded as descriptive, due to the fact that it aims to accurately describe the phenomena of reality studied and hence did not require the use of techniques and statistical methods. The methodologies used to validate models regarding exact sciences are often quantitative, while approaching social sciences they are often qualitative, given its high flexibility [69,70].

In the real meaning of the case studies, the case's target to be analyzed is called "unit of analysis" [71]. According to this definition, the units of analysis regarding this investigation are composed of innovative products and services, whose purpose was to test the proposed conceptual model. Since the case studies were performed though interviews complemented with guided tours of companies' manufacturing facilities (that were only possible to perform in Portugal), an interview script (protocol) was elaborated, according to the guidelines pointed out by [71]: interviews (recorded or not) at the place of analysis; telephone conversations; mail contacts; collection of written documents

or computer data; collection of information from "key informants" (only one or a panel), that should be trustworthy people with the right technical and scientific knowledge, from the inside of the organization. Still according to [71], an important aspect to be agreed by both parts in each case study, is the confidentiality of data or information collected and the hypothesis of firm choose to remain anonymous. A final aspect pointed out by this author, refers to the importance of obtaining a formal authorization from the organization boards and provide to their representatives, as well as the "key informants", to review the material provided.

The criterion used in choosing the case studies presented in this article was based on the fact that its scope covers the objectives stipulated in the investigation. In other words, verify and validate all aspects inherent to the proposed conceptual model for the four product/service/incremental/radical combinations, as much as possible, in the perspectives of the national and international industry. The validation of the proposed model through case studies aims to assess its functionality in a business environment and to verify the need of its improvement, so that it can constitute, in the best possible way, a roadmap to be followed by of companies wishing to create new products and/or services in a sustainable manner in the business markets in which they operate. Figure 6 illustrates the key stages involving the research methodology followed in this paper.

**Figure 6.** Key stages involving the research methodology (authors' own elaboration).

#### **4. Case Studies**

Four case studies were preformed, regarding products and services, which proved to be sufficient to validate the various parts of the developed model developed, based on literature review, and according to a specific protocol adopted, described by [72]. First, it was validated in the business field the proposed conceptual SIFSNPIP and, secondly, its usefulness was evidenced by demonstrating that it can successfully applied in the assessment of companies that design and develop sustainable new products, allowing to punctuate the evolutionary state of all their strategic, organizational and operational aspects and also its range of innovative products to market.

The ccompanies that collaborated to carry out the presented case studies, were the international business group Instituto de Soldadura e Qualidade (ISQ) and a Portuguese company of metalworking industry, which preferred to remain anonymous.

Of the four explanatory cases studied in industrial environment, two were related to products and were called by "HVAC" and "WJ-LASER" while the other two, were related to services and called by "NaturalHy" and "Brazing".

The case studies were carried out through meetings with work teams of the companies analyzed, belonging to the three levels of decision making: strategic; organizational and operational. For this, three meetings were carried out for each one of the four cases, with a total contribution of 12 work teams. To pursue this end, an interview script was elaborated, composed by questions inherent to each item covered in the model, which was made in accordance with [71,72].

The constitutive meetings of the case studies were aimed at obtaining answers to the questions in the interview script, in order to verify the extent to which all aspects evidenced in the model were performed by the company. The cases are described in Sections 4.1–4.4. Results regarding scores related to the degree of accomplishment by firms of each item of the model, using the Likert scale presented below, are presented in Table 2. Then, complementary open questions of type "how" and "why", made to better understand the extent to which the answers fit this scale to explain the scores obtained, also helped to present the description of the cases and to perform de discussion of the results presented in Section 4.5.

In order to define the scores attributed to each item of the model, the following Likert scale was used:

The interview script open questions were designed to address the following aspects in a systemic way:

Figure 7 shows that the four case studies were chosen to cover the four possibilities, regarding their application in products and services vs. incremental and radical innovation.

**Figure 7.** Selection criteria for the case studies presented: Application vs. innovation type (authors' own elaboration).

#### *4.1. HVAC Case*

"HVAC" (Heating, Ventilating and Air Conditioning) case regards to the metalworking industry in which a Small-Medium Enterprise (SME) manufactures a high range of HVAC equipment to be commercialized in the market. This business activity requires a considerable capacity of innovation relating to the manufacture processes of its products, which are mainly: SPIRO® system; heat exchangers; silencers; air handling units (AHUs); rectangular, circular and oval ducts - those ones with

Ethylene-Propylene-Diene-Methylene (EPDM) sealing gasket; chilled beams; fan units; chilled water and storage heat tanks grilles and diffusers and CADvent software (for calculus and dimensioning of air duct installations). To guarantee the sustainability of its products in th metalworking industry e market the firm performs continuous improvement of the products, but because mostly all of them contain a huge number of components, as the AHUs. Therefore, the company can use its resources both to manufacturing and improvement processes, working in ROS to promote its customers satisfaction, and trough marketing, expanding itself in the market.

#### *4.2. WJ-LASER Case*

"WJ-LASER" case regards the use of both cutting processes water jet (WJ) and (light amplification by stimulated emission of radiation (LASER) on several kinds of materials to promote the manufacturing of customized products, that means, products defined by the customers. The use of this cutting technologies requires the tool Creative Design. The customers that requires this kind of technologies from the firm, are mainly from rehabilitation of ancient artifacts (oil paintings, pottery, papyri, etc.), art and advertising industries. Through the adjustment of cutting parameters in non-metal materials, this two technologies can be used on waste removal of high precision, without damaging the object material. When the firm uses this technologies in the cutting sector, due to the extreme flexibility of its equipment, the innovation level of the products obtained is radical, because all kind of geometries can be designed with high accuracy. Water jet and laser cutting technologies are suitable for small batches or even single parts, but not for mass production.

#### *4.3. NaturalHy Case*

NaturalHy case regards to a radical service provided by an international business group that focuses strongly on Research & Development (R&D).

The denomination "NaturalHy" defines a project that was recently concluded on which the group participated as part of the executive/steering committee. The project goal is the distribution and use of natural gas with hydrogen addition, so the chemical mix can be used across all Europe, with high level of safety and environmental sustainability through infrastructures designed and built for its distribution. The radical innovation of this case is inherent to the addition of hydrogen to natural gas with a combustion reaction, generating gaseous chemical reaction products with very low amount of carbon dioxide. The project also involved the building of pipelines and storage tanks to distribute and store this new gaseous product, and the distribution network can be used by both domestic and industrial fields, and beyond that, the project also covers permanent monitoring and tracing processes, to ensure its sustainability. The development of this project occurred between years 2004 to 2009, with the collaboration of over 38 business partners, involving a huge investment dimension. The amount invested in the project was about EUR 11 million (granted by the European Commission), having exceeded a profit of about EUR 17 million. Still during the period above mentioned, the project expanded to the Middle East, having participation in the building and operation of the Research Centre of the Petroleum Institute in Abu Dhabi laboratories. This case study was unique to the model purposed in this paper, because allowed it to pass to a functional level with the introduction of exportation policies as a factor not pointed out by literature review on strategic management, as one of the strategic inherent classical issues normally approached.

#### *4.4. Brazing Case*

Brazing case regards to the use of brazing technology in polymeric materials without lead alloys, as a service with incremental innovation, since this technology was already used worldwide in metal materials. Working with alternative chemical alloys rather than lead, in brazing of polymeric materials (that are the material basis of electronic circuit boards) allows to guarantee health and environmental sustainability. The company offers a testing service using this technology to serve projects regarding the manufacture of electronic and electrical components for several kinds of industries, namely audio visual, aerospatiale, appliances and electronics firms and business groups, in partnership with: Research & Development (R&D) institutions; airlines; governmental agencies and armed forces. From these business partners are highlighted: Crane-NSWC; American Air Force; Boeing; BAESystems; ITB Inc.; NASA; Texas Instruments; Northrop Grummam and Portuguese Association of Electrical and Electronics Industries (PAEEI). A disadvantage of using this technology is the difficulty on welding in polymeric materials using elements with high melting points, like tin to work with this type of circuits, and for this reason, it is crucial to conduct a high number of tests. When the risk of failure of an electronic board leads to catastrophic results, in the case of aircraft and military armament, lead alloys can be used again, so experiments are extremely important to make a decision about which alloy material can be used with a minimum risk of failure. Since testing is one the most important phase of high risk projects, DFSS, DOE, DFX, among others, are the support methodologies and tools to test performing with the highest accuracy possible.

#### *4.5. Discussion of Results*

In "HVAC" case it was found that the "systemic and strategic environment" level almost factor scores were of 1 and 2. This is an acceptable fact, because the firm works in ROS. In the factor levels of both "corporate culture" and "management principles", scores incidence occurred were of 1 and 3.

This was an expectable fact, because firm works with compliance by the rules and obligations to the market. Regarding "process variables" level, the scores were almost all between 1 and 2, due to the fact that the firm works with the same range of products aiming to make the best use of its resources and with a specific technological and engineering know-how. And from the panel of tools available in Table 1, the use of modular and tolerance design reached the score 4, because all production is composed of modular products, in which assembling processes need to obey to specific tolerances.

In "WJ-LASER" case, when rating the "systemic and strategic environment" level, almost factor scores were in 4, but not the one regarded to ROS vs. BOS that correspond to score 2, and the one regarded outsourcing with score 0. In the factor levels of both "corporate culture" and "management principles", scores incidence occurred were on 4. The factors regarding involvement of suppliers and customers scored in 2 or 3 respectively, because concerns to a radical innovation. In level "process variables", all scores obtained were equal to 4, because it is a project that must highly obey to all that issues to be extremely profitable. But relating Stage-gate® projects the score was 0, because this management tool is not applicable on water jet and laser technologies. It was found a large application of creative project methodology combined with modular design. And almost all other methodologies and tools referred in Table 1 were pointy used, except the TRIZ and DFSS, because there were no contradictions to be solved through TRIZ methodology, and DFSS has no application in individual parts or small batches of products concerning this case.

In "NaturalHy" case it was found that the "systemic and strategic environment" level, factors scores were of 4, except the one concerning the ROS, because it is the innovation is radical. This case showed up that exportation issue was not contemplated in the conceptual model so, it was a gap not found in the literature review, that when included on the "systemic and strategic environment" level of the conceptual model, turned it into functional. In the literature review about strategic management was found a single paper on this subject—the work of [73] - regarding business expansion and perspectives. Regarding levels of both "corporate culture" and "management principles" most of its factors were scored with 4, but not the ones concerning offshoring, outsourcing, and the need for low cost solutions. Regarding the level "process variables", its factors were scored between 1 and 4, because it is about a project regarding a huge amount of issues to take in account, and ones are more demanding than others. Regarding methodologies and tools presented on Table 1, the business group it was found that almost all of them were applicate in the project.

In "Brazing" case it was found that the "systemic and strategic environment" level, factors scores were practically all on 4. Regarding levels of both "corporate culture" and "management principles" almost all of them were scored with 4, and the same happened to level "process variables". Regarding

methodologies and tools presented on Table 1, it was found that the company uses almost all of them, sometimes separately and other times combining the ones that are complementary. For example, the business group uses DFSS many times, because the level of accuracy required on the manufacturing of electronic circuit boards is a very accurate process.

All scores that were obtained using the already mentioned Likert scale on the application of all SIFSNPIP items, with the four case study carried out, are presented in Table 2.

**Table 2.** Summary of the scores of the factors measured by SIFSNPIP (authors' own elaboration).

The four cases studies regarding both incremental and radical products and services, carried out on firms and business group's facilities, were found to be enough regarding the measurement of all issues that integrate its levels, because the results obtained fit into the analyzed realities. And conceptual model SIFSNPIP, built based on the literature review, became conceptual after its validation in industrial field through the described cases studies.

#### **5. Proposal of a Conceptual**/**Functional Model**

SIFSNPIP functional model was finally obtained, by putting Figures 1–5 altogether along with its interactions, as illustrated on Figure 8.

**Figure 8.** Functional model of SIFSNPIP (authors' own elaboration).

It is important to highlight that the item "export policy" integrates the "systemic and strategic environment" level of SIPSNP model, and also that this fact was the differentiator factor between the conceptual and functional model.

#### **6. Conclusions**

The research on literature review, was based on a deductive-inductive pathway, in order to construct a comprehensive and integrated conceptual model to support Sustainability of New Product Innovation Processes—the SIFSNPIP model. It was empirically validated, in the industrial environment through four explanatory case studies, referring to the implementation of sustainable new products and services, both incremental and disruptive. From the literature review it wasn't detect, until now, any holistic models to support sustainability of new product innovation processes, regarding this phenomenon as a whole appropriate for cases of enterprises or industries models, but only partial approaches. This fact justified the purpose of this investigation, and for all that was exposed in this paper, it was concluded that this goal was successfully achieved. The SIFSNPIP model that was initially conceptual, became functional after its external validation in industrial field through the performance of four case studies, regarding both incremental and radical products and services. So, functional SIFSNPIP model can be used as a diagnostic tool or roadmap for measurement of projects carried out by firms that innovate, design and develop new products with a sustainable way of management.

According to the initial objectives, model SIFSNPIP should allow at least two different uses:

It seems clear that would be desirable that model SIFSNPIP could be better tested with a dozen or more case studies, with several business organizations that design new products, both incremental and radical, sustainably. Such applications could have, for organizations, a measurement and improvement of their own processes, in addition to any specific adaptations of the model, as well as data collection that would allowed a statistical treatment of the incidence and influence of the model factors on competitiveness of the national and international innovative industry itself.

**Author Contributions:** Conceptualization, A.S.M.E.D. and A.A.; methodology, A.S.M.E.D., A.A., H.V.G.N. and R.S.; validation, A.S.M.E.D., H.V.G.N. and R.S.; formal analysis, A.S.M.E.D. and A.A.; investigation, A.S.M.E.D., A.A., H.V.G.N. and R.S.; resources, A.S.M.E.D. and A.A.; data curation, A.S.M.E.D. and A.A.; writing—original draft preparation, A.S.M.E.D. and A.A.; writing—review and editing, A.S.M.E.D. and R.S.; visualization, A.S.M.E.D. and R.S.; supervision, A.S.M.E.D. and R.S.; project administration, A.S.M.E.D. and A.A. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** The authors of this paper wish to thank the Sustainability Journal for the opportunity to submit this paper to its Special Issue "Innovation Ecosystems: A Sustainability Perspective", a fact that gave inspired motivation to carry out this work. It is also intended to express gratitude to all of the members of the scientific community who, in the past, have written R&D works that served as references for the literature review done in this research work in particular. A "thank you" is sent to the companies that collaborated to carry out the presented case studies (international business group Instituto de Soldadura e Qualidade—ISQ and a Portuguese company of the metalworking industry that preferred to remain anonymous), which contributed to increase the knowledge about the subject in question. Lastly, the authors also wish to acknowledge the Fundação para a Ciência e a Tecnologia (FCT—MCTES) for its contact support that helped to carry out the case studies presented in this paper via the project UIDB/00667/2020 (UNIDEMI).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

## **The Role of Territorially Embedded Innovation Ecosystems Accelerating Sustainability Transformations: A Case Study of the Transformation to Organic Wine Production in Tuscany (Italy)**

#### **Cristina Chaminade <sup>1</sup> and Filippo Randelli 2,\***

Received: 21 April 2020; Accepted: 3 June 2020; Published: 5 June 2020

**Abstract:** Over the last few years, there has been a growing concern among academics and practitioners about the slow pace in which sustainability transformations unfold. While most socio-technical transformations tend to happen over extended periods, research shows that unless some dramatic changes are introduced, we are risking damaging the critical earth systems that sustain human life. In this context, understanding why and how transformations happen at a much faster pace in certain places than in others is of crucial importance. This paper investigates the rapid transformation of Panzano, from traditional wine production to organically produced wine. Using a combination of document analysis, participant observation, and face to face interviews in Panzano in 2019, this article examines the role of the territorially embedded innovation ecosystems facilitating this fast transformation. The study looks at place based-structural preconditions and different forms of agency at different stages in the transformation. Our findings illustrate that a place-based agency is paramount for accelerating sustainability transformations.

**Keywords:** innovation; ecosystem; organic wine; Tuscany

#### **1. Introduction**

In November 2018, the UN IPCC report indicated that profound transformations are needed before 2030 if we want to avert catastrophic environmental consequences, including the total loss of all coral reefs and a significant reduction of island communities [1]. A couple of months later, in April 2019, the UN launched the most comprehensive report on the state of world biodiversity and ecosystem services since the seminal Millennium Ecosystem Assessment [2]. The results of the three-year research project directly involving 150 scientists around the world were devastating. According to the report, two in five amphibian species are at risk of extinction, as one-third of reef-forming corals, and close to one-third of other marine species. In economic terms, the losses are jaw-dropping. Pollinator loss has put up to \$577bn (£440bn) of crop output at risk, while land degradation has reduced the productivity of 23% of global land [2]. With slightly more than ten years to go to the IPCC deadline, the need for accelerated system transformations has come to the forefront of political and academic debates [3–8].

However, we still know very little about if and how system transformations might be accelerated [9]. In fact, in the real world, long-term incremental system changes are the norm, partly due to the systemic nature of innovation. On the one hand, systems are path-dependent. Prior investments in technologies and the related human capital, infrastructure, institutional frameworks, and other sunk costs can lock-in the system and prevent it from responding to radical changes [10]. On the other hand, science,

technology, and innovation policies tend to focus on addressing failures in existing systems rather than changing them, thus perpetuating gradual change [8].

In contrast with the structuralist perspective, the literature on the governance of sustainability transformations has focused on the role of agency on the speed [11] and the directionality of the transformations [12]. According to this literature, the existence of protected spaces for experimentation or the role of intermediaries [13] can create new opportunities for transformation and affect the direction and speed of transformations. The literature has significantly contributed to our understanding of enabling factors supporting transformations and the role of agency. However, it has also received critiques, particularly from economic geographers, on the lack of attention to how innovative ecosystems embedded in particular territories, shape the speed and direction of transformations [14–16].

This paper aims to address this gap by looking at the role of territorially embedded innovation ecosystems (TEIE) in accelerated sustainability transformations. TEIEs belong to what Boyer (in this same special issue) calls the regional/local ecosystem approach, which highlights the territorial dynamics of the innovation process [17]. TEIE is an embracing concept that might include innovative clusters, industrial districts, or regional innovation systems. A more in-depth look into the role of structural preconditions and agency in the transformation of specific TEIE is essential for several reasons. On the one hand, structural preconditions differ significantly between different TEIEs. The economic structure of a region, its knowledge specialization, or its institutional frameworks are the results of historical processes of knowledge accumulation. The existence of shared institutional frameworks, strong networks, and a sense of place enable interactive learning and continuous innovation in TEIEs [18]. TEIEs are constructed relationally, through social capital and networks supporting the creation and exchange of knowledge [19]. It is in this respect that evolutionary economic geographers argue that history matters in regional transformations. In other words, the opportunities for transformation of particular TEIE are path-dependent [20].

On the other hand, the transformation capacity of particular territories can be shaped by particular forms of agency. Grillitch and Sotarauta suggest that different forms of agency can shape the opportunity space for transformation: entrepreneurial, institutional, and place-based. Regarding the latter, a strong sense of place [14] place frames [15] or place leadership [21] as a shared understanding of the identity of a place, and a shared vision of what that place might become, is crucial for transformations. Ecosystems, understood through this place-making lens, could potentially be a powerful mechanism for accelerating transformations.

While promising, this recent literature on agency and regional transformations remains at a rather general and theoretical level. It focuses on regional transformations in general, without paying specific attention to sustainability transformations as one specific transformation with a clear directionality [12]. Furthermore, for the current paper, there is a lack of studies analyzing how structural preconditions and agency in TEIEs affect the speed of transformation.

This paper aims at contributing to this gap in the literature. It investigates the role of the local innovation ecosystem in the rapid transformation of Panzano from traditional wine production to organically produced wine. Panzano is a county in Tuscany where the transition to organic wine has almost reached 100% of the territory in barely 25 years. This article investigates the role of place-based structural preconditions and different forms of agency in the transformation of the TEIE over time. The analysis allows us to identify which factors appear to be more significant at different stages in the transformation, from the incept to the acceleration and the consolidation. For instance, while structural preconditions and entrepreneurial agency are essential at the beginning of the transformation, it is place-based leadership that significantly contributes to the acceleration.

The paper is structured as follows. Section 2 discusses the concept of sustainability transformations and the determinants of its speed. We pay particular attention to the role of the specific territorial context in which these transformations emerge and deploy in shaping the speed and direction of transformations. Section 3 provides an overview of the methodology used for data gathering and analysis. Section 4 expands the study of Panzano, investigating the drivers behind its fast transformations, and Section 5 concludes.

#### **2. Literature Review**

#### *2.1. Sustainability Transformations*

Over the last few years, there has been a growing concern among academics and practitioners about the slow pace in which sustainability transformations unfold [22]. Research shows that unless some dramatic changes are introduced in the following decade, we are risking damaging the critical earth systems in which human life on this planet is sustained [23,24]. In this context, understanding why and how transformations happen at a much faster pace in certain places than in others is of crucial importance.

In the context of this paper, we follow Roggema et al. [25] definition of sustainability transformations. Transformation is seen as a change towards a future that is fundamentally different from the current situation [3]. Incremental change, on the other hand, is seen as a slow process, with imperceptible changes, and a transition is seen as a fluent change towards an improved version of the current status, but where the current system is not fundamentally changed [26]. In this respect, only the term "transformation" would capture the radical and non-linear nature of system change [27]. The latter is also referred to in the literature as deep transitions [8,27]. The current paper adopts this later understanding of sustainability transformations as embracing substantial change from the previous situation, including changes in practices, routines, beliefs, and policies.

A key characteristic of sustainability transformations of the radical and deep kind discussed above is that they take time. System transformations require structural changes in current economic, social, political, and technological regimes and meta-regimes [28], implying profound transformations of the dominant techno-economic paradigm [29] and the reconfigurations of actors, their relationships [30], and the formal and informal institutions that influence their behavior. The structuralist approaches to sustainability transformations see them as path-dependent. Prior investments in technologies and the related human capital, infrastructure, institutional frameworks, and other sunk costs prevent systems from responding to radical changes [10]. Economic actors set up routines to reduce the uncertainty driven by their bounded rationality. Due to their tacit and cumulative nature, routines are not easy to change, and very difficult to imitate for other firms [31]. In other words, firms are subject to cognitive constraints [31] that hinder the process of change. At the same time, science, technology, and innovation policies tend to focus on addressing failures in existing systems rather than changing them, thus perpetuating gradual change [8]. As a result of these structural constraints, it is argued that transformations will take decades and even centuries to complete.

It is only recently that the role of agency in sustainability transformations has come explicitly to the forefront of academic discussions [8,11,32]. Within this emerging stream of literature, researchers look at the capacity of individuals and organizations to act independently and to make their own free choices [32–34] and create opportunities for change [35]. The main finding is that understanding agency, which is how different actors might strategically join forces in networks to achieve particular goals, is key to overcoming the structural system inertia to incremental change and realizing transformations [11].

Both structural preconditions and agency vary significantly between different territories, and economic geographers have criticized the current literature on sustainability transformations for their lip service to the analysis on how innovative ecosystems embedded in particular territories shape the speed and direction of transformations [16–18]. TEIEs matter because regions have accumulated different skills and knowledge, relations, and institutional frameworks over time. But also, as place-based leadership is paramount for sustainability transformations [35]. In other words, both structural preconditions and agency are related to, and embedded, in particular territorial innovation ecosystems, creating a particular sense of place. The extent to which TEISs are important for understanding sustainability transformations will be discussed next.

#### *2.2. Territorially Embedded Innovation Ecosystems and Sustainability Transformations*

Economic geographers have long acknowledged the impact of territorially embedded ecosystems for innovation [36,37]. Firms and organizations closely located share network relations of (mainly) tacit and informal nature that are crucial for knowledge exchange. Geographical proximity also facilitates interaction between diverse and complementary capabilities [38,39] and a spatial neighbor effect conveyed through social interaction and visibility [40]. Firms can derive localized competitive advantages due to the joint and collective cumulative path of learning and coordination and close face to face interaction [41,42]. At the same time, informal control mechanisms, such as those exerted by social communities, are also powerful mechanisms to avoid free-riding [38].

In other words, innovation ecosystems are constructed relationally [19]. Moreover, those relations tend to happen with other organizations nearby. Place-making relations influence, and are influenced by, formal and informal institutions that are embedded in the territory [43]. Together, actors, relations, and institutions are the basis of a territorially embedded ecosystem.

It follows that the development of a particular ecosystem is path-dependent. The same relations, institutions, and actor configurations in the territory can act both as a promoter or deterrent of change. Similarly, the variety of knowledge present in one particular region affects the possibilities for path creation in that same region. Knowledge accumulates over time, and regions portray particular knowledge specializations. Thus, history matters in the transformative capacity of a particular TEIE, since it shapes the actors, network, and institutions of particular territories, as well as the knowledge base in which the innovation capacity of that particular territory is based.

While acknowledging the structural preconditions for the change of particular TEIEs, Grillitsch and Sotarauta [35] suggest that different forms of place-based agency can shape the capacity of a TEIE to transform. The authors propose to distinguish between three types of agency: Schumpeterian innovative entrepreneurship, institutional entrepreneurship, and place-leadership. Schumpeterian innovative entrepreneurship refers to attempts to break with existing growth paths through processes of Schumpeterian creative destruction, and it is observable through new ventures and new processes. Institutional entrepreneurship refers to individual and organizational attempts to change existing institutions, molding the rules of the game so that the Schumpeterian entrepreneurs can surface and succeed. Institutional entrepreneurship is observable through changes in rules and regulations. Finally, place leadership refers to "social processes involved in making things happen" [35]. Place leadership is the most difficult to observe due to its embeddedness in informal institutions. In the words of Sotarauta et al. [21] (p. 128), investigating place-based leadership is about revealing the types of social processes involved in "making things happen" and in "getting things done, more often than not, in an indirect manner". How different forms of agency and structural preconditions shape the capacity of a TEIE to start, speed up, and consolidate sustainability transformations remains to be studied.

Identifying small-scale accelerated transformations and analyzing them could be a first step in understanding how sustainability transformations can be accelerated. We do so by looking at the fast transformation of a region in Tuscany–Panzano, from conventional to organic wine production at a much faster pace than the neighboring regions. In particular, we look at how the combination of structural characteristics and agency influences the speed of change.

#### **3. Research Design**

This paper uses case study research, which is suitable for the holistic, in-depth exploration and understanding of complex issues, such as sustainability transformations [44]. This approach will help to explain both the process and outcome of human-institution-forest interactions, through the observation, reconstruction, and analysis of the case study outlined below.

#### *3.1. Selection of Case Study: Organic Wine Production in Panzano*

The case was selected following a purposive sample procedure. Purposive sampling is recommended when the aim is to focus on particular characteristics that enable one to explain the research questions [45], in this case, how the innovation ecosystem enabled the fast transition of Panzano to organic wine production. The case was selected because of its extreme characteristics; that is, the fact that the sustainability transformation has taken place at a much more accelerated pace than in the overall region.

Panzano is located in the municipality of Greve in Chianti within the Tuscany region (Italy), between the two cities of Firenze and Siena (see Figure 1). The municipality of Greve in Chianti is included in the Chianti Classico region, which covers 71,800 hectares (177,500 acres) of territory, of which 10,000 hectares are devoted to wine production. The Chianti Classico region also includes the entire territories of the municipalities of Castellina in Chianti, Gaiole in Chianti and Radda in Chianti and parts of those of Barberino Tavarnelle, Castelnuovo Berardenga, Poggibonsi, and San Casciano Val di Pesa.

**Figure 1.** The location of Panzano in Chianti (the borders are the municipality of Greve in Chianti), within Tuscany and Italy (small frame with Tuscan municipality borders). (Source: self-elaboration with the use of Quantum GIS and Open Street Map).

Rows of vines alternating with olive orchards are a characteristic feature of the Chianti Classico landscape. About 7200 hectares (17,290 acres) of vineyards are part of the DOCG (Denominazione di Origine Controllata e Garantita), for the production of Chianti Classico, one of the most famous red wine in Italy and the world, as 80% of the production is exported worldwide. The Chianti Classico region has multiple sub-zones, some of which have formed unions or associations to promote their wines. Panzano is a sub-zone in the municipality of Greve in Chianti, and it represents 10% of the entire Chianti Classico territory.

The Chianti Classico organic production has since the year 2000 and now represents approximately 35% of the total wine production in the region. What differentiates Panzano from the regional trends towards organic production is twofold: the percentage of organic production vis à vis conventional production and the speed of the transformation to organic production. The latter is the particular focus of this paper.

#### *3.2. Data Collection and Analysis*

For the data collection and analysis, we use innovation biographies (IBs). IBs are a "valuable methodology to reflect the evolutionary character of the dynamics of the social initiatives' and innovation processes in deepening the understanding of development paths, knowledge trajectories, and stakeholder interactions at the micro-level" [46] (p. 15). They are particularly useful for analyzing complex, emergent and non-linear events involving many actors across different levels [47].

In IBs, it is of paramount importance to use a combination of data collection techniques and sources to triangulate information, combining data from the individual and contextual level. Interviews constitute the individual level, as they reflect personal perspectives. Desk research using document analysis and participant observation enriches the biographic picture at the contextual level.

Primary data was collected through face to face semi-structured interviews conducted in 2018 to some wine producers in Panzano by both authors of this paper. The interviews were with the owners of the wineries and the local agronomist. The interviewees included all the key actors mentioned in all documents as paramount for the transformation of Panzano into organic wine production (five in total), which had been engaged in the transformation from the start. This provided depth of data rather than breadth, which was considered to be more suitable for the development of the IB. Moreover, an additional two interviews and a small survey were conducted with wineries in the Chianti Classico area for triangulation. The interviews were recorded. The interview guide was divided into four main blocks that enquired about the drivers and process of transformation, the role of networks, the sources of knowledge and the impact of the transformation on the economic, social and environmental sustainability of the firm to capture different aspects of the role of the innovation ecosystem in the transformation of Panzano.

The interviews took place either on the production field, where the interviewees could explain how much organic wine productions differed from conventional production or in their office. The notes taken during these field visits are part of the participant observation.

Writing and analyzing the IB "is a process of telling a real, detailed, and "thick" story covering all relevant aspects" [46] (p. 38). The use of IBs implies (i) the development of a biographical time-space path with the major milestones or events identified (sequence of events). (ii) For each event, information is collected on the actors involved, their relation (actors), and their location; (iii) the knowledge that they provided and if there was any conflict (barriers in the innovation process) [48]. The result is a chronological observation of the transformation of Panzano and the actors, networks, and institutions that enabled the transformation.

#### **4. The Role of the Territorially Embedded Innovation Ecosystem in the Accelerated Transition of Panzano to Organic Wine Production**

The transition towards organic agriculture in Panzano was not a linear process. Several key events can allow us to trace the historical process that brought Panzano to full organic wine production. The entire process is explained through three different phases.

#### *4.1. Phase 1. Emergence—1992–2000*

Organic production in Panzano can be traced back to the early nineties when a traditional wine producer in the area started experimenting with organic wine production in a small plot of his land (Interview 4). At that time, there was no sense of community in the region. Instead, each of the producers was fencing for itself (Interview 4).

The territory was just emerging from a profound crisis, which had forced producers to reduce the yield significantly to prevent the prices from sinking [49]. According to one of the interviewees, the region was making too much wine and of inferior quality. The wines were very light and not capable of age for a long time and, thus, not competitive in the international market.

Because of the crisis, many producers sold their farms. The new entrants did not come exclusively from the territory, but from other parts of Italy and from abroad. In other places in Tuscany and Chianti, foreign people bought farms as an investment or for exploitation (Interview 2). Instead, those that acquired the farms in Panzano moved with their families to Panzano, reflecting a life-choice.

The latter might be one of the reasons why the newcomers were committed almost from the start to the production of organic wine. They had a strong sense of responsibility to the environment and their family (Interviews 1, 3 and 4).

To revert to methods of production that were not chemical-intensive, the producers turned to the older employees of their farm that had worked in the vineyards before the fifties (Interviews 1 and 4), their agronomists (Interview 3) and old books (Interview 4), in search of the required knowledge. They also started to share their experience and visit other neighboring farms, to get to know how others were experimenting with organic productions, thus creating the first seeds of social capital in the region. Cognitive proximity and social proximity facilitated knowledge sharing. Regarding cognitive proximity, all newcomers had higher education, although not necessarily as oenologist or agronomists. Concerning social proximity, most of the newcomers were of the same age, share a similar philosophy of life (Interviews 1, 3–5), and were open-minded (Interview 3).

Furthermore, newcomers almost immediately developed a strong sense of place. Place identity reflects how the producers talk about the wine—they wanted a wine that could "reflect the sense of place" (Interview 1)—something more "subtle and reflective of the place".

Most of the wine producers were also part of a formal association of the wine producers of Panzano (Unione Viticoltori di Panzano in Chianti), which had been created in 1995 and agglutinated 20 out of the 35 Panzano producers. However, the association focused on the promotion of the local wine through a wine festival, rather than on creating a shared vision of the territory. It was not until the beginning of the year 2000 that the association started to play a different role, as discussed next.

#### *4.2. Phase 2. Acceleration—2000–2016*

A trigger event in the acceleration of the transformation to organic wines happened in 2000 when the Italian Ministry for Agriculture and Forestry forced all wine producers to use chemicals to fight an insect vector of the Golden Flavescence ("Scaphoideus titanus") a disease that causes enormous damages to the vineyards. The disease can be transmitted from plant to plant if geographically close together. So, the Ministry made mandatory two specific strategies to fight it: a regular spray of pesticide on all the vineyards, attacked or not, and uprooting of all the infected plants.

The Tuscany region had historically few attacks of Scaphoideus titanus since it prefers humid habitats, and therefore the insect was not well known by the winemakers. To prepare a strategy that would allow limiting the use of pesticides, the Winemakers Association of Panzano in Chianti reacted as a group and asked for the support of a local agronomist (Interviewee 5). Together, they decided to propose a monitor program to understand the real danger of the pest in the area. The region reacted positively and changed the decree from the obligation to spree to the obligation to monitor and control. The monitoring was carried out with the scientific support of the CRA (Consiglio per la Ricerca in Agricoltura e l'Analisil'Analisi dell "Economia Agraria) of Florence and the University of Pisa, and the Tuscany region approved it. The monitoring exercise showed that there was no presence of the insect in the region, and the use of pesticides was avoided.

The wine producers understood very clearly that, as an association, they had a strong influence and very tangible gains (Interview 4). The monitoring system based on the use of traps to identify the presence of insects was offered for free for the Panzano wineries. Therefore, the plague was a significant event in the transformation of Panzano, as they saw the value of being associated and acting together (Interviews 1–5). All the producers resisted using insecticides.

The success of the monitoring system strengthened the links among producers. It also allowed local producers to put their trust in the local agronomist (Interview 5), which is one of the pioneers of organic wines in Italy and on his approach to grape growing, which is rooted in two different levels of defense against pathogens: direct and indirect. The direct defense acts on the harmful agent, trying to neutralize it only in case of its presence in the vineyards. The direct approach makes use of copper and sulfur-based compounds to stop the pathogen agent. Under the present legislation, organic agriculture can also use a direct approach of defense: synthesized chemicals are limited but not banned, and any winemaker can decide to spray copper and sulfur-based compounds once the risk is high. It follows that monitoring is crucial to reduce the use of them.

Indirect defense views the outbreak of pathology as a result of a two parts interaction: the pathogen agent and the plant. Therefore, it is reductive to focus only on the chemical elimination of the harmful agent. Instead, it is more efficient (and less impactful on the environment) to prevent detrimental outbreaks by focusing on the natural defense that every plant has. This approach is based on prevention, with the use of chemical compounds just for extraordinary attacks of pathogens.

The implementation of the monitoring system enabled the establishment of connections outside Panzano, with the CRA of Florence and with the universities of Florence and Pisa. Since 2000, the monitoring project never stopped, and the Ministry for Agriculture and Forestry revoked the obligation of regular treatments with pesticides, and the monitoring system was officially included in the allowed strategies to fight the "Scaphoideus titanus".

In other words, the need for prevention against the "Scaphoideus titanus" was a challenge transformed into an opportunity. It is only due to the monitoring strategy success that the agronomist could start supporting some of the local winemakers in the transition to organic production (Interview 5).

A further step in the acceleration towards organic wines in Panzano happened in 2005, with the opening of SPEVIS (Stazione Sperimentale per la Viticoltura Sostenibile). SPEVIS is an experimental agronomical center for the development of sustainable wine production and the "Sustainable Panzano" strategy (Panzano Sostenibile) (Interviews 1, 3–5). SPEVIS was founded by the local agronomist in collaboration with local producers and research institutes, and it could be considered as a natural outcome of already existing informal collaborations. A unique characteristic of SPEVIS was that, although it was funded by only a handful of wine producers in the area, it provided advice and support to any local producer interested in shifting to organic wine production practices for free. The collective action taken around SPEVIS is another example of new place leadership involved in making things happen.

Nevertheless, the disruptive innovation of SPEVIS was not only the leadership per se but rather the way information was shared. In the case of SPEVIS, the goal was not only supporting their clients in the transition to organic wine production but rather to widespread as much and soon as possible the organic agriculture in the area. As a matter of fact, over time, SPEVIS published various types of booklets and researches studies online and for free. In 2008, SPEVIS presented its vision of sustainable viticulture, which became a "manual on organic wine production" the following year. Then, in 2011, they published a research-based manual, a yearbook for winemakers, a complete book with the description of Panzano's methodology and philosophy (updated in 2014 in a new edition), and a combination of books and cd-roms on grape diseases.

Therefore, it is clear how any case study on Panzano wine cluster cannot leave behind this free flow of knowledge, available for not only the Winemakers Association's members or the SPEVIS' clients. The place leadership of SPEVIS was functioning as a meta-actor, and the free flow of knowledge on organic viticulture was nurturing the Panzano innovation ecosystem.

After the introduction of SPEVIS, the conditions for the acceleration of the transition toward organic winemaking were set. Panzano reached 50% of vineyards under organic production exceptionally soon. Part of this excellent result was due to the initial excitement. Some producers were already interested in organic agriculture, and the interaction between SPEVIS and the local Winemakers association opened up the way to a radical change. Since 2000, it has taken 12 years to reach 75% of organic vineyards and 16 to reach 95%, which is an incredible result and represents a strong example in the Italian scenario (see Table 1). The types of actors can partly explain the dramatic acceleration of the last years. If initially, it was only the small and medium-size producers that changed to organic; in the past few years, the large producers have finally adopted 100% organic agriculture (Interview 4).

**Table 1.** The role of the territorially embedded innovation ecosystem in the three stages.

Source: Own elaboration based on the interviews.

#### *4.3. Phase 3. Stabilization and Scaling Up—2016 Onwards*

Thanks to the propulsive thrust of SPEVIS, to the commitment of the AIAB (Associazione Italiana Agricoltura Biologica), and the will of the mayor of Greve in Chianti, on September 27, 2016, the Bio-district of Greve in Chianti was officially established [50]. According to one of the interviewees (Interview 3), the success of the joint response to the "Scaphoideus titanus" crisis triggered the idea of the bio-district. The bio-district aims to bridge the gap between farmers and citizens and enable spaces for the dialogue between policymakers, producers, consumers, and citizens to build shared visions about what the region could be (Interview 4). The latter is entirely in line with the sense-of-place discussed earlier [14].

Similar bio-districts soon followed the Bio-District of Greve in Chianti in Gaiole in Chianti, and more recently, the entire Chianti Classico became a bio-district (Interview 4). The latter refers to the entire DOCG Chianti Classico wine production area, and it has the goal to support the transition to organic agriculture of the entire area of Chianti Classico. Further structuration of the change is taking place in the forms of new laws. According to one of the interviewees (Interview 4), the Italian government is discussing a new law regarding organic agriculture, and one of the chapters in the law will be about bio-districts.

The success of Panzano is now widespread in the entire wine region, and today, 35% of agricultural land in the Chianti Classico area is organic [50]. Interestingly, not all the wine producers of Panzano identify themselves with the bio-district as strongly as they do with the Association of Panzano wine producers (Interview 1). In this sense, the regional bio-district does not trigger as strong a sense of place as the Panzano area does.

The transition to organic was not only influenced by place, but it also influenced place. Physically, the transformation to organic was also visible from the outside. In the words of one of the interviewees (Interview 1), it changed the landscape. For example, in particularly rocky places, the stones were not visible after a while, because the soil was so fertile that the rocks would not separate from it. Going back to more traditional production techniques also reinforced the linkages with the place.

#### **5. Discussion**

This paper analyzes a wine region in which the sustainability transformation towards organic wine production took place much faster than in the neighborhood regions. Our point of departure was trying to understand why this was the case. We used innovation biographies to capture the trajectory within the innovation ecosystem: we build a timeline, identifying the stages in the transformation (emergence, acceleration, and stabilization) and the triggering events that supported the transformation from one stage to the other. We focus on how the whole transformation could be achieved at a much faster pace than in surrounding localities. We look at actors and formal and informal networks and their embeddedness in the territory and how they influence institutional change at the regional and national levels.

The main contribution of this paper is to bring the role of the territorially embedded ecosystem to the discussion on the speed of sustainability transformations. In doing so, we look at both place-based structural preconditions and well as the place-based agency.

Our findings suggest that structural preconditions and place-based agency are essential for sustainability transformations, but not at the same stages in the transformation. Structural preconditions are paramount in the early stages of the transformation, together with the entrepreneurial agency. However, the place-based agency, and to a lesser extent, institutional agency, and becomes paramount in the acceleration phase.

In the case of Panzano, sharing knowledge about the transition to organic agriculture was crucial for the speed of the transformation. Both pioneers' farmers and SPEVIS, in collaboration with universities, were working as a source of knowledge for the conventional farmers that found it easy and convenient to shift to organic agriculture. The social and geographical proximity fostered the share of knowledge, and the result confirms that innovation ecosystems are constructed relationally [17] on a strong sense of place [14].

The role of a local leader and intermediary–SPEVIS- was crucial. The local leader reduced the gap between the farm and the market, supporting the farmers in the transition to organic viticulture. A unique characteristic of SPEVIS was that it provided free advice and support to any local producer interested in shifting to organic wine production practices. The success of SPEVIS may suggest that supporting the access to knowledge through the action of local meta-actors cooperating with the local firms is crucial for sustainability transformations. Furthermore, conventional farmers consider the first step towards organic as the most "expensive" due to the need for new skills, materials, and suppliers. In this perspective, the free advice and support received from SPEVIS was paramount to convince conventional wine producers to move towards organic production. In other words, the institutional agency is essential in the acceleration phase, but it should be intertwined with the place-based agency that only local leaders can guarantee.

Interestingly, the regional bio-district in Chianti is not transiting to organic at the same fast pace, because it does not trigger the strong sense of place as the Panzano area did. This insight of our research opens up a relevant field for future research: how to reproduce at a larger territorial scale the sense of place and the social capital, due to the density of relations that might accelerate the transition? Is it better to refer to a larger region for a transformative change or to a mosaic of small territorially embedded innovation ecosystems?

These findings may have important policy implications. Policies tend to look at sustainability transformations, either at the macro-level of the market or the micro-level of firms, neglecting the role of the territory (meso level). A territorial approach to policy-making could illuminate the discussion on how to accelerate sustainability transformations. Our findings show that a strong sense of place facilitates a dense network of relations, which in turn fosters knowledge development and diffusion, a vital function of an innovation ecosystem. The pace of the transition can be accelerated by an effect of neighboring, which fosters social interaction and visibility [40].

Our study also reveals that the transition towards sustainability is not a linear process. Structural preconditions and different forms of agency play a different role at different stages in the transformation and thus require different policies over time, but also over space. For instance, while in some regions, it is still crucial to enhance better structural preconditions, in some others, fostering the cooperation among actors to widen the existing knowledge is paramount.

The case of Panzano highlights the importance of place-based approaches to the study of sustainability transformations [14,15]. Innovation ecosystems, understood through this place-making lens, could potentially be a powerful mechanism for accelerating transformations. While promising, our research is based only on a single case study. The observed mechanisms that facilitated an accelerated transformation to organic agriculture in Panzano may also operate in other regions or sectors but remain to be studied. For that, a systematic comparative analysis of different accelerated regional transformations is needed.

**Author Contributions:** Conceptualization, C.C. and F.R.; methodology, C.C and F.R.; validation, C.C. and F.R.; formal analysis, C.C. and F.R.; investigation, C.C. and F.R..; resources, C.C. and F.R.; data curation, C.C. and F.R.; writing—original draft preparation, C.C. and F.R.; writing—review and editing, C.C. and F.R.; visualization, C.C. and F.R.; supervision, C.C. and F.R.; funding acquisition, C.C.. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was partly supported by the EU-RISE project Makers (Smart Manufacturing for EU Growth and Prosperity). H2020 Marie Skłodowska-Curie Actions (Grant number 691192).

**Acknowledgments:** Cristina Chaminade would like to thank Marco Bellandi at the University of Florence and Fondazione per la Ricerca e L'Innovazione (Florence), for hosting her in Florence for half a year and supporting the research on regional sustainability transformations. Both authors would like to thank the interviewees for the richness of their insights and their generosity with their time. We thank the three anonymous reviewers for their careful reading of our manuscript and their many insightful comments and suggestions.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

van Vuuren, D., Eds.; Report prepared by The World in 2050 Initiative; International Institute for Applied Systems Analysis (IIASA): Laxenburg, Austria, 2018.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Article* **A Framework for Risk Assessment in Collaborative Networks to Promote Sustainable Systems in Innovation Ecosystems**

**Ricardo Santos 1,2,\*, António Abreu 1,3, Ana Dias 1,4, João M.F. Calado 1,5, Vitor Anes 1,5 and José Soares <sup>6</sup>**

Received: 16 July 2020; Accepted: 31 July 2020; Published: 2 August 2020

**Abstract:** Nowadays—and due to an increasingly competitive world—organizations need to collaborate in an open innovation context to be efficient and effective by achieving high levels of innovation with their products and services. However, the existing resources—as well as the innovation achieved from the diversity of partners involved—brings challenges to the management; in particularly with risk management. To fulfill such needs, risk management frameworks have been created to support managers, on preventing threats with systems development, although without properly account the influence of each system component, on the entire system, as well as the subjectivity within human perception. To account for these issues, a framework supported by fuzzy logic is presented in this work, to evaluate the risk level on system development in open innovation environment. The approach robustness is assessed by using a case study, where the challenges and benefits found are discussed.

**Keywords:** collaborative networks; virtual enterprise; open innovation; risk management; fuzzy logic; systems engineering

#### **1. Introduction**

Nowadays, small and medium-sized enterprises (SMEs) plays a crucial role on most economies in the world, by creating jobs that reduces the unemployment, besides the contribution for the gross domestic product (GDP) of each country. In most countries, its presence, is expressed by more than 87 percent of all existed enterprises [1].

Furthermore, the unpredictability around the economic context and the highly competitiveness of the actual marketplace, have forced organizations into a position where its crucial to find forms of survivance in such context. From the literature, there is a consensus that innovation should being part on new product/system development to organizations, reach competitive advantage in highly competitive markets or even in new markets to be explored [2–4].

In this context, the innovation ecosystems, and in particular, virtual enterprises (VEs) allows to share the necessary competencies and resources, to develop products/systems to better respond to the market opportunities, by operating in a collaborative network context [5].

Furthermore—and based on the existed studies from the literature—one-way to promote sustainability on innovation ecosystems (IE), is by identifying and assessing the risks involved in such environments, namely on the VE, created, with the purpose of having a collaborative environment, where knowledge, competences and risk are shared between the partners involved.

However, the development and the innovation on new systems, it is not easy to be managed especially for VEs [6,7], since that the system or the product to be developed, is normally associated with several risks, regarding the different system components involved. Which are developed by the different partners of the collaborative network.

Furthermore, there is a certain subjectivity degree on risk assessment, related with human perception, which increases with the number of risk managers, as well as with the number of partners involved [8]. This becomes even more difficult, by knowing that the responsibility on each system component, is shared by more than one partner/actor of the same network [9].

Thus, the selection of the right partner, in order to minimize the risk on each system component and then, to minimize the global risk of the system development, assumes one of the main reasons to develop models that allows the risk management in such context.

Additionally, companies are relatively vulnerable to external events, such as political, economic, technical and financial, among others.

In this sense, risk management, could help VEs to mitigate unwanted risks that could avoid the success with its system development. Without managing the risks properly, VEs could face severe consequences, such as losing clients, negative environmental impact—and even financial bankruptcy [4].

To do this, risk management (RM), act as a process to identify, assess, monitor and report the risks involved, in terms of their impacts and probabilities of occurrence [5]. The identification and evaluation allow of such risks, allows the elaboration of a set of actions to minimize any negative effects that may occur [6].

There are several methods that can be found on literature (e.g., decision trees, Delphi analysis, failure modes and effects analysis (FMEA), risk matrix, among others), which can be used to identify and analyze the risks involved. However, there is a lack of approaches to manage risk on VEs that simultaneously analyses the influence between each system component and the final system or product to be developed, as well as to include human perception on classifying each risk according to its impact and probability of occurrence [7].

Furthermore, the subjectivity around risk assessment, referred before, it is not included in most existent models found on literature, which brings the necessity to be included into an integrated approach, in order to deal with the human perception on risk assessment.

Therefore, we have considered a set of risks adopted here, on behalf of VE, by considering the design of each system component as an innovative project itself, with a set of risks involved.

The innovation, reached on system component, contributes to the innovation of the final product or system, developed on behalf of the VE created for that purpose.

The VE as well as the system/product to be developed, can have multiple risks categories related to each system domain (SD), whose relationship with each risk from each system component, should be accounted.

Thus, in this study, it will be presented an approach to incorporate the issues referred above, namely, the inclusion of a possible influence from each system component risk on the system/product domains, as well as the subjectivity around human perception on risk assessment, by using fuzzy systems.

The model developed here, will also be tested, by using a case study based on a developed system to produce "green" energy, in order to identify the challenges to be accounted on future research, as well as the benefits achieved, such as the prioritization of each risk, regarding each system component, in order to define the actions to mitigate such risks in an open innovation context.

Therefore, Section 2 describes a literature review, followed by Section 3, in which the research method is described, while Section 4 describes the case study used to validate the proposed approach through the achieved results. Section 5 ends this study, with some concluding remarks and future work.

#### **2. Literature Review**

#### *2.1. Open Innovation Ecosystems*

The open innovation (OI) and its impacts on economic, social and even political markets, are widely valued among several stakeholders (which naturally includes the policymakers), since it is an important key factor to achieve competitiveness. Several authors have recently increased the literature production, regarding the importance of innovation into our societies [7]. The innovation concept has become an important issue to be considered in the political and public discourse, with bringing therefore, an important impact on several scientific fields. Several definitions of this concept can be found on literature. An important definition, refers innovation, has a phenomenon that occurs when an invention is introduced in the market [8,9], although a formally definition, can be found by Chesbrough [10], broking therefore, with the classical linear approach, related with the closed innovation paradigm and by introducing new challenges within the innovation process.

The same author [10] claims that the closed innovation model type is no longer sustainable, from the economic point of view and organizations should engage into an open innovation approaches to be more competitive, by being a new way to create value to a company or other organization [10]. In essence, these OI models, can be defined by having two different types of knowledge flow and resources [10]. The first one, regards to the outside-in knowledge flow, i.e., it occurs when a company brings knowledge from the exterior, as well as resources from its partners, customers, scientific centers, universities, among other stakeholders involved, in order to improve its performance in terms of innovation, which allows to reduce costs and even time through the acquisition or borrow of the resources that they need to achieve its goals.

The second one, regards, the inside-out knowledge flow, where the companies search for solutions to share knowledge, already available from each partner, and/or other resources within the exterior environment in order to add value to the organization. An example of this, is the transfers of rights and the out-licensing.

With regards to OI, there are on literature, some approaches that can be found, namely the works of [11,12], with two of them, being very used among the managers of OI projects.

An OI model, is the InnoCentive [12], which was created in 2001. This model, runs in a software platform, available on web and it is based on six steps, which starts to identify the ideas and problems, followed by the challenge formulation, the intellectual property agreement specification, the challenge publication, the solution assessment and finishing with a price regarding the intellectual property transfer. The other model, widely used by organizations, is the one designed by Procter & Gamble (P&G), named "Connect + Develop", which allows to work in an inwards and outwards approach, by including issues such as the marketing for engineering, as well as the commercial services for product design.

Although an open innovation approach could release positive achievements, it also brings risk to the organizations, which leads them, to design a proper strategy to protect innovation, in order to produce boundaries and to turn the same outcomes measurable [13,14]. Furthermore and in an OI context, organizations should also consider the risks involved, to be aware of the greater ones involved, to maintain their competitive performance.

Based on the OI concept, an OI ecosystem, can be referred as an innovation ecosystem (IE) with a number of supported activities, being classified as an open innovation actions [15].

Regarding the IE, some works has explored the types of stakeholders involved in OI ecosystems, as well as the relation between the focal firms and the partners involved, with their influences on innovation, by recurring to different IE perspectives.

An example of such perspective is the one from [15], which has stated that a IE, is an aligned framework, formed by a set of multilateral partners, with the aim of interacting with each other, to achieve a certain (and focal) value. Another perspective can be given by [16], where they consider IE, as a business ecosystem with a high level of interaction among the different key partners, namely customers, universities, suppliers and competitors and suppliers.

Additionally—and based on works from [17]—it seems to exist the evidence that the product/ system innovation of nowadays, has increasingly depended on the interaction between the organizations that participates in the IE.

Other studies seem to reinforce this interdependence in terms of collaboration, between the innovation actors involved (e.g., [18,19]), although there is a lack of research that explores the interdependences between the actors with regards to a particular innovation ecosystem ([17]).

Usually, most of the literature, only focus on situations with a single mode of interaction, such as the cooperation between the university and industry (e.g., [16–19]), while other works claims for more integration of IE modes to accelerate firm innovation, which brings the need to explore more the OI ecosystem modes in order to provide a more comprehensive analytical framework for understanding OI ecosystems. Authors such as [18] have done this work, by determining that an IE is formed by a multilateral set of partners, which needs to interact to get a focal value.

Other authors, such as [19], referred the fact that IEs are more than just a typical OI with an outside-in flow—or even an inside-out flow—between the partners of the network, being more an interrelated actors to achieve and sustain an IE, to create multidisciplinary knowledge and achieve high levels of innovation with a product/system.

#### *2.2. Risk Assessment*

Apart from the development of innovation management approaches, organizations also tries to predict the changes (and also responding to them) that may occur with the development of a systems/product before and after its launch in the market, in order to be more competitive, effective and efficient. Such attempts have been performed, despite the lack of practical approaches, to support their risk management attempts [20].

The uncertainty, related with the innovative processes, is bonded not only to the inherent failure risk, but also to inherent success possibility, which brings the need to adequately manage the risk management within an innovative process/activity [20].

Therefore, and since that the aim of a risk management model is to facilitate process innovation, instead of stifle the same innovation—organizations require a strategy that allows to perform early risk diagnosis and also the management [20] of the risks involved.

From the literature, we can identify several risk assessment approaches, widely used by organizations, such as the balanced scorecard (BSC) [21], the failure mode effects analysis (FMEA), analytic hierarchy process (AHP) [22], Fault Tree analysis (FTA) [23] and the risk diagnosing methodology (RDM) [24].

The analytic hierarchy process (AHP) could be considered as a multivariate analysis method with the purpose to reduce the randomness, related to the subjective evaluations, by taking into consideration several and different objectives, based on different criteria [23]. This method is mostly used on selection of scenarios [24]. Another risk evaluation approach referred here, is RDM approach, which has the main purpose of providing strategies to support (and even improve) the possibility of a given project to be succeeded, through the identification and management of their (potential) risks [23,24]. The RDM approach, is also implemented to assist the systematic diagnosis of organizations, by accounting issues like the consumer acceptance, the commercial viability, the organization competitive answers, the external responses, the product and manufacturing technology process, in which the evaluation of

the project risk is defined not only by the risk probability of occurrence and its correspondent effects, but also defined by the organizations' capability to influence the destiny of the actions, regarding each risk.

#### **3. Research Methodology**

#### *3.1. Proposed Approach*

Based on what was stated before, a virtual enterprise (VE), commonly arises to develop specific products/systems, by joining different competences and resources from a set of partners, to achieve high levels of innovation at a low-cost level, when compared to a "traditional enterprise" that must acquire from the market, the same resources and competencies.

Therefore, and based on the importance of VE on having a framework to assess the risk in such context—in this work it will be presented an approach to evaluate the existence of a possible relationship between the individual risk from a given system component *n* (*Scn*) (which will be assessed according to a set of different domains or risk categories) and the risk, regarding each domain of the virtual enterprise, represented here by the product/system to be developed.

Thus—and based on [25,26]—the different risks involved can be categorized based on the taxonomy adopted in this work, which is organized according to the 2 hierarchical risk levels considered here, namely; the system risk (SR) and the system component risk (Scn) (Figures 1 and 2).

**Figure 1.** Risk taxonomy adopted (adapted from [21]).

By bearing in mind that a system component (Sc), can be considered (and managed) as a project, the completion of such project, even with or without success, could bring an impact on the various VE domains through its system to be developed, given the expected changes that may be occur with the development of each Sc itself.

Instead of VE domains, we have system domains (SD).

Therefore, each system component *n* (*Scn*) of the system to be develop, has a development project involved, which have a risk associated with it that can be managed on behalf of project risk management (PRM) techniques. Each risk, associated with the *Scn*, can be considered, as part of the systems' risk management (SRM), managed by the VE management board, which is responsible for the entire system to be developed (Figure 2).

Furthermore, the risk regarding to a given system component *n* (*ScRScn*), can be achieved by accounting the risk, obtained in several domains or risk categories, namely; performance (*P*), quality (Q), cost (*C*), time (*T*), among others [25,26].

Apart from the risk, associated with the system component (*ScRScn*), there is the risk associated with the system to be developed (*SR*), where and according to the risk taxonomy presented on Figure 1, it can be assessed on behalf of the following risk categories strategy (S), operations (O), finance (F), marketing (M), information systems (IS), environment (E), among others.

The possible existence of a relationship between the two risks referred before, namely *ScRScn* and *SR*, as well as its domains or risk categories involved, are described on Figure 2.

Thus, the risk regarding each system component (*ScRScn*), can influence the risk value of the system risk (SR), on its different domains, which in this study we have considered the following system domains (SD), namely; strategy (S), operations (O) and marketing (M).

**Figure 2.** Relationship between the *ScRScn* and system risk (SR).

The need to define and quantify such influence, allows to predict the effect that a risk, regarding to a given system component *n* (*ScRScn*) can originate in the overall system risk (SR), with the transition from a current stage into another (and future) one, reached through its deployment ([2]).

The system component risk (ScR), regarding its domains, namely "time", "performance" and "cost", are presented and discussed on [26–28], as a set of risk categories considered on behalf of project risk management, according to some studies found on literature.

Therefore, and based on [25–31]—the ScR was categorized, as it follows:

Regarding the system risk domains, it was considered the following ones:

• Strategy (S)—resulting from the errors in strategy (e.g., by developing a technology regarding a component that cannot work with other technologies from other product components or even a product technology that cannot meet the consumer needs) [27];

Even the SR domains, as well as the ScR domains, could be expanded into additional and other risk categories apart from the ones presented before.

#### *3.2. Model Architecture*

The approach presented in this work, is based on the concept of system development (Figure 2) and it consists into an integrated approach that includes fuzzy logic to incorporate the uncertainty and ambiguity, regarding the human perception on risk evaluation with regards to system development.

Therefore, and based on the relationship shown on Figure 2—the approach presented in this work, resorts to fuzzy logic to make a qualitative and quantitative analysis of product risk evaluation in an open innovation context, by integrating two hierarchical risk levels, namely; system component and system development as a whole.

The approach, it is presented on Figure 3.

**Figure 3.** Proposed model.

The system component level, has the aim of evaluating the system component risk (*ScRScn*), by taking into consideration a given system component (Sc) *n*. On the other hand, the second one, evaluates the system risk level (SR), by including the existence of a possible influence (*InfSRScn*), regarding each system component *n* (*Scn*) on the entire system risk (SR) (Figure 3).

For each risk category, regarding each system component (Figure 1), namely performance (P), cost (C) and time (T), there is an individual risk (<sup>−</sup>*RScn*), which results from the combination of each

(expected) impact (−*IScn*) and the correspondent probability of occurrence (−*PScn*) considered here (Figure 3), i.e.,:

$$TR\_{\rm Scn} = TP\_{\rm Scn}.TI\_{\rm Scn} \tag{1}$$

$$PR\_{\rm Scn} = PP\_{\rm Scn}.PI\_{\rm Scn} \tag{2}$$

$$\mathbb{C}R\_{\text{Scn}} = \mathbb{C}P\_{\text{Scn}}.\mathrm{CI}\_{\text{Scn}}\tag{3}$$

Based on Figures 2 and 3, the risk category, regarding each system component *n* (*ScRScn*), can be achieved by combining all the individual risk category considered, i.e.,:

$$\text{CscR}\_{\text{Scn}} = TR\_{\text{Scn}}.\omega\_{\text{TRn}} + PR\_{\text{Scn}}.\omega\_{\text{PRn}} + \text{CR}\_{\text{Scn}}.\omega\_{\text{CRn}} \tag{4}$$

With the weights (ω−*Rn*), corresponding each one, to a risk category, regarding a system component *n*, namely cost (C), time (T) and performance (P). These weights, should satisfy the following condition:

$$1 = \omega\_{\text{TRn}} + \omega\_{\text{PRn}} + \omega\_{\text{CRn}} \tag{5}$$

The existence of a (possible) influence, regarding the risk with a given System component *n* (*ScRScn*), over each system development domain (SD) considered here, is also included in this approach, by taking the correspondent (and expected) impact variable (<sup>−</sup>*IScn* <sup>→</sup> *SD*), which will affect one (or even more) domains of the system development (SD).

In this work, it was considered three domains, regarding to the system, developed on behalf of the VE created, namely, marketing (M), operations (O) and strategy (S).

Through the risk categories time (T), performance (P) and cost (C), related to a system component *n* (*Scn*), it was achieved a set of expected impact values (−*IScn* → *SD*), regarding to each system development domain considered. Then and for each system domain (SD) considered here, only one value of <sup>−</sup>*IScn* → *SD* is selected (Figure 3), between the different values. Such a process is preformed based on the risk manager perception.

Furthermore and based on each SD considered here, fuzzy logic is then deployed, by using a set of linguistic variables and inference rules, to obtain the correspondent impact value of <sup>−</sup>*IScn* → *SD*.

Regarding the indirect influence, resulted from the system component *n* (*Ind\_InfScn*) on each SD, it is achieved, by accounting the maximum value of the three corresponding (and expected) impact values (<sup>−</sup>*IScn* <sup>→</sup>*SD*) related to each system domain, achieved before, i.e.,:

$$\text{Ind\\_Inf}\_{\text{Scn}} = \max \{ \text{S} l\_{\text{Scn} \to \text{S} \prime}, P l\_{\text{Scn} \to \text{S} \prime}, \text{Cl}\_{\text{Scn} \to \text{S} \prime}, \dots, S l\_{\text{Scn} \to \text{O} \prime}, P l\_{\text{Scn} \to \text{O} \prime}, \text{Cl}\_{\text{Scn} \to \text{O}} \} \tag{6}$$

The existence of a (possible) direct influence, from each system component and through its different domains, is also considered here, since that the resources used on each system component, can affect resource availability in terms of the system development context.

Thus, the Sc domain with more impact, allows to estimate the direct influence (*Dir\_InfScn*) of a given Scn, which is obtained, by achieving the maximum value of the three <sup>−</sup>*IScn* → *SD* values, mentioned before, i.e.,:

$$\text{Dir\\_Inf}\_{\text{Scn}} = \max \{ \text{PI}\_{\text{Scn}\prime} \text{TI}\_{\text{Scn}\prime} \text{CI}\_{\text{Scn}} \} \tag{7}$$

Therefore, the total influence (*In f SRScn*) from a given Sc*n* on system development, will be resulted by adding the *Dir*\_*InfScn* with *Ind*\_*InfScn*, i.e.,:

$$\text{InfPR}\_{\text{Scn}} = \text{Ind\\_Inf}\_{\text{Scn}} \alpha\_{\text{Ind}.n} + \text{Dir\\_Inf}\_{\text{Scn}} \alpha\_{\text{Dir}.n} \tag{8}$$

The existence of the weights ωDir.n and ωInd.n, intends to define the relative importance, given by the risk manager to the direct and indirect influences achieved before, with both parameters, satisfying the following condition, i.e.,:

$$1 = \omega\_{\text{Ind.u}} + \omega\_{\text{Dir.u}} \tag{9}$$

Therefore, the system development risk (*SRScn*), resulted from each Sc*n*, is achieved by combining the probability of occurrence of the event (*PSR* <sup>→</sup> *SD*), the external impact on each system domain (SD) (*ISR* <sup>→</sup> *SD*) and the influence from each *Scn* on system risk (*In f SRScn*), i.e.,:

$$SR\_{\text{Scu}} = P\_{\text{SR} \to SD}.I\_{\text{SR} \to SD}.InfSR\_{\text{Scu}} \tag{10}$$

The values of *ISR* <sup>→</sup> *SD* and *PSR* <sup>→</sup> *SD*, are achieved, by selecting the maximum value of product, between *ISR* <sup>→</sup> *SD* and *PSR* <sup>→</sup> *SD*, both considered for each system domain (SD), namely marketing (M), operations (O) and strategy (S), i.e.,:

$$\langle I\_{\rm SR\rightarrow SD\cdot} P\_{\rm SR\rightarrow SD} \rangle = \max \{ I\_{\rm SR\rightarrow M} \times P\_{\rm SR\rightarrow M\cdot} I\_{\rm SR\rightarrow O} \times P\_{\rm SR\rightarrow O\prime} I\_{\rm SR\rightarrow S} \times P\_{\rm SR\rightarrow S} \} \tag{11}$$

The system risk (SR) is therefore resulted from the contribution of each *SRScn*, related to the correspondent *Scn* considered and based on its relative importance (ωScn), i.e.,:

$$SR = \omega\_{\rm Sc1} \mathcal{S} \mathcal{R}\_{\rm Sc1} + \omega\_{\rm Sc2} \mathcal{S} \mathcal{R}\_{\rm Sc2} + a \upmu\_{\rm Scn} \mathcal{S} \mathcal{R}\_{\rm Scn} \tag{12}$$

where ωSc1, ωSc2 and ωScn, are the weights, respectively regarded to the relative importance given to each system component *n* (*Scn*).

#### *3.3. Fuzzy Implementation*

The levels of risk, related to *ScRScn* and SR values, were obtained from each correspondent fuzzy inference system (FIS) (Figure 3) and they were based on a set of inference rules from the type of "If-And-Then" and according to the risk category.

According to Figure 3 and regarding the system component level, the FIS "F1", is based on the expressions (1–3), regarding the inputs (<sup>−</sup>*PScn*) and (<sup>−</sup>*IScn*), i.e.,:

$$\rm{^-R}\_{\rm Scu} = \rm{^-P}\_{\rm Scu} \cap \rm{^-I}\_{\rm -Scu} \tag{13}$$

Thus, the inference rules, regarding F1 system (Figures 3 and 4), can be formulated as: "IF probability (-PPrn) is P AND impact (-IPrn) is I, THEN the process risk is R.

The same approach can be achieved for the impact <sup>−</sup>*IScn* → *SD*, which allows to obtain the indirect influence *Ind\_InfScn*, defined on (6). Therefore, and based on 13, the impact *IScn* → *SD*, is achieved through the following expressions:

$$I\_{\rm Scn\to\-S} = T I\_{\rm Scn\to\-S} \cap PI\_{\rm Scn\to\-S} \cap CI\_{\rm Scn\to\-S} \tag{14}$$

$$I\_{\rm Scn \to M} = T I\_{\rm Scn \to M} \cap P I\_{\rm Scn \to M} \cap C I\_{\rm Scn \to M} \tag{15}$$

$$I\_{\rm Scn \to O} = T I\_{\rm Scn \to O} \cap PI\_{\rm Scn \to O} \cap CI\_{\rm Scn \to O} \tag{16}$$

The possible influence of the risk, regarding the system component *n*, related to each system domain (SD), can also be considered by using the FIS F2 (Figures 3 and 4), which is based on a set of linguistic rules and variables, which can be formulated as "If impact (*TIScn* → *SD*) is it and the impact (*TIScn* → *SD*) is Ip and the impact (*TIScn* → *SD*) is Ic, Then the average impact of the system component *n*, on each SD is <sup>−</sup>*IScn* → *SD*.

Similar approach can be proposed, regarding the system risk level (*SRScn*), where, based on (10)—and by considering the influence from Sc*n* on system risk development (*In f SRScn*)—*SRScn* is obtained by using the following expression:

$$SR\_{\text{Scu}} = P\_{\text{SR} \to SD} \cap I\_{\text{SR} \to SD} \cap InfSR\_{\text{Scu}} \tag{17}$$

Thus, the inference rules regarding the FIS F3 (Figures 3 and 4), is defined as "If probability (*PScn* <sup>→</sup> *SD*) is P, impact (*ISR* <sup>→</sup> *SD*) is I and Scn influence on system risk (*InfSRScn*) is Inf. Then the system risk level (*SRScn*) is SR.

#### *3.4. Definition of Linguistic Variables: Values and Pertinence Functions*

Regarding the linguistic variables—and according to some works existing on the literature ([25,26])—it is normally recommended that the number of levels shouldn't be more than nine levels, since that a bigger value, surpass human perception limits, when it concerns to value discrimination.

Therefore, and based on these recommendations—five levels were adopted for each of the linguistic variables considered in this work. The definition of the five levels, as well as the correspondent pertinence functions, are described on Tables 1–3. Regarding each pertinence function, it was used the triangular type function, whose parameters a, b and c, were also described on the same tables.

**Table 1.** Values regarding the linguistic variable type "probability of occurrence (P)" and pertinence functions.

Thus—and with regards to all off the domains of the Sc probability of occurrence (<sup>−</sup>*PScn*), i.e., cost (C), time (T) and performance (P)—it was defined the pertinence functions and linguistic variables, which are presented on Table 1.

Same approach, was also deployed to define the probability of occurrence, regarding the system risk (*PSR*→*SD*), by also using Table 1, with SD, being the system domain considered here, i.e., strategy (S), operations (O) and marketing (M).

Regarding the linguistic variables, related to the expected impact, considered for each Sc*n* (−*IScn*) and on behalf of the three Sc domains considered here (cost (C), time (T) and performance (P)), on Table 2 are described the correspondent linguistic values, as well as the pertinence functions, used to define the same variables.

**Table 2.** Values regarding the linguistic variable type "expected impact (I)" and pertinence functions.

Similar approach was conducted for the variable—*IScn* <sup>→</sup> *SD*, regarding the correspondent expected impact value of each Sc domain on each system domain (SD) considered here, namely, marketing (M), operations (O) and strategy (S), with Table 2, also being applied in this case, given the same criteria, established for *-IScn* variable.

With regards to the Sc risk (−*RScn*)—and on behalf of its Sc domains (cost (C), time (T) and performance (P))—the correspondent linguistic variable, is defined on Table 3, through its pertinence functions and correspondent triangular parameters (a, b, c). A similar approach was also deployed to define the linguistic variable regarding the system risk, related to the *SRScn* variable.

**Table 3.** Values regarding the linguistic variable type "risk level (R)" and pertinence functions.

In addition to the parameters, presented on Tables 1–3, it is possible to correspond the linguistic values into numeric ones, based on a set of intervals (Table 4), which will help to analyze the final results obtained, regarding the risks with system components, as well as the overall system development risk.

**Table 4.** Variable types used: linguistic values and the correspondent numeric ones.

#### *3.5. Fuzzy Deployment*

Based on the model, presented on Figure 3, each one of the fuzzy inference system (FIS), was implemented by recurring to Matlab fuzzy Logic ToolboxTM (version R2017a) (Figure 4), which is integrated on MATLAB® software platform. Thus, the definition of the membership functions, as well as the inference rules, was based on Tables 1–3—and also made by recurring to the same toolbox—which was also used to analyze the behavior of each FIS considered.

As it referred before, in all of the FIS considered here, it was used triangular functions, whose parameters were taken from Tables 1–3, as well as the membership functions, whose inference rules were implemented by using Mamdani inference mechanism (Figure 4), due to its intuitive approach, well-suited to human input and widespread acceptance on literature [32,33].

With regards to the system component (Sc) level, the FIS F1, has on its inputs the linguistic variables "Probability of occurrence (−*PScn*)", as well as the correspondent expected Impact value ( <sup>−</sup>*IScn*), while the respective output, is the Sc risk level (<sup>−</sup>*RScn*), which is related to each one of the Sc domains considered in this work.

The implementation of FIS F2 (influence of a given Sc*n* on each system domain), has on its inputs, the linguistic variables, *TIScn* → *SD*, *PIScn* → *SD* and *CIScn* → *SD*, with the output variable of F2 having the Sc*n* average impact, on each system domain (SD), i.e., <sup>−</sup>*IScn* → *SD*.

**Figure 4.** MATLAB implementation, regarding each fuzzy inference system (FIS) considered.

The FIS F3, has on its inputs the linguistic variables *PScn* <sup>→</sup> *SD*, *IScn* → *SD* and *InfSRScn*, while the output is consistent with the linguistic variable *SRScn*.

With regards to the defuzzification method used in all FIS deployment, it was used the centroid approach, given its widely use in works from the literature ([26]).

In Figure 5, it is presented the surfaces, resulted from several simulations to assess the behavior of FIS 1, with concerns to each risk category (domain) considered here, regarding the Sc risk level.

**Figure 5.** FIS surfaces, regarding FIS F1 and related to (**a**) time (T), (**b**) performance (P) and (**c**) cost (C).

Based on the three obtained surfaces, presented on Figure 5, it can be noticed some differences, regarding the three graphics, which are mainly associated with the difference regarding the inference rules adopted for each one of the Sc domains considered in this work, allowing therefore, to obtain different combinations of the output, for the same pair of inputs.

#### **4. Case Study, Results & Discussion**

The model robustness was evaluated by recurring to a case study, which was based on a virtual enterprise (VE). This VE, was established to develop an integrated and sustainable approach, to supply an industry, by producing its own energy through the integration of hydrogen with photovoltaic system.

The purpose of this system is to become a typical integrated product, to be further sold (and deployed) to the small industries, with a nominal electric power, ranging between 40–60 kW.

On these conditions, the system is designed so that the load to be fed, does not depend on the public electricity network, which makes the installation, self-sufficient in terms of electric energy.

The diagram presented on Figure 6, shows the developed system, with all of its components.

In order to ensure the total independence of the industry from the electric grid, the system produces electric energy during the day, by the photovoltaic and fuel cell systems, with the remained energy, being stored by using hydrogen as an energy carrier. This is preformed, by converting the same energy into the correspondent amount of hydrogen to be stored. The hydrogen stored, is then converted into electric energy by the fuel cell, during the night.

Based on Figure 6b, the system developed here, is composed by a series of components, which includes the photovoltaic system (PV panels and the converter), the electrolyzer to convert electric energy into hydrogen, the fuel cell to convert hydrogen into electric energy, the fuel tanks, the control system of the flow of air/oxygen (to control the purity of the O2 consumed by the fuel cell), the remain power converters, the management system, as well as other auxiliar systems (e.g., electric valves, tubes, cables, electric bombs, among other components).

**Figure 6.** System developed (views). (**a**) Conceptual; (**b**) schematic.

Each system component is developed/manufactured by a set of partners (with indirect/direct involvement), through the open innovation network (OIN), created on behalf of the virtual enterprise (VE), established to develop the system presented on Figure 6.

This virtual enterprise, is formed by 13 partners (Figure 7), originated from different industries and sectors, including two Research & Development (R & D) centers from two universities.

**Figure 7.** Virtual enterprise and diversity of processes involved [10].

In order to model the resources and the different competences involved here, shared among OIN partners, it was adopted the open innovation model, developed from the work of [10], which allows to manage the innovation (and the partner contribution) on behalf of the system/product do be developed (Figure 7).

The VE, shares different competences and resources between the partners involved, resulting therefore, into a set of innovations around the product development.