2016/09/30

«Typologies of Ecopreneurs. Harnessing Innovative Potential of Ecopreneurs»



Thaddeus McEwen. «Ecopreneurship as a Solution to Environmental Problems: Implications for College Level Entrepreneurship Education». International Journal of Academic Research in Business and Social Sciences, vol. 3, n.º 5, May 2013. See the references in the original publication of this article.






«Typologies of Ecopreneurs

»Most researchers agree that there are two categories of environmental entrepreneurs –those who have a profit or economic orientation and those who have the sustainability orientation and want to help change or improve the environment (Taylor & Walley, 2003; Isaak, 2002; Koester, 2011). Schnick, Marxen & Freiman, (2002) refer to the categories as the two ends of the ecological orientation continuum. At one end are ecopreneurs who constantly adopt environmentally-friendly practices and at the other end are entrepreneurs who give no ecological consideration to the businesses at all. In other words, environmental entrepreneurs are either starting green businesses or making their businesses green (OECD, 2011). Table 2 presents the different types of ecopreneurs related to each category.

»One criticism of the ecopreneurship typologies is that they do not account for the changes that might occur among entrepreneurs, e.g., could ecopreneurs move between different typologies, and which drivers mainly guide their behavior (deBruin & Lewis, 2005 cited in Gibbs, 2007). In response, Isaak (1998) argued that the various types of ecopreneurs are not pure forms, but represent reference points for broad changes within businesses. The process theory of entrepreneurship supports Isaak’s “viewpoint, which emphasizes the fact that “you can’t pin people down to one type, because entrepreneurs are always in the process of ‘becoming’” (Steyaert, 2004, p. 6).

»[...]




»Harnessing Innovative Potential of Ecopreneurs

»Given the growth of ecopreneurship, the question now is, how do we harness the innovative potential of ecopreneurs to exploit the opportunities within environmental degradation? In other words, how do we foster the development of new entrepreneurial firms that will create the innovations necessary to solve environmental problems?

»According to Shane and Venkataraman (2000), “entrepreneurial action is created at the nexus of two phenomena: the presence of enterprising individuals and the presence of lucrative opportunities” (p. 218). Ecopreneurs are the enterprising individuals. Some are motivated by profit and start businesses that happen to be green, while others have a sustainability orientation and are motivated by environmental needs. Their businesses are founded on the principle of sustainability and they seek to combine environmental awareness with conventional entrepreneurship (Schnick, et al. 2002). Lucrative entrepreneurial opportunities exist within the environmental degradation e.g. the problems of climate change, pollution, energy, etc.

»According to Shane (2003), the nexus is the place where the entrepreneur interacts with the environment, e.g. environmental degradation, to identify opportunities. How they interact and whether opportunity recognition and exploitation takes place depends on the resources the entrepreneur has at his or her disposal and the resources available in the environment (pg.8). Given that the entrepreneur-environment interaction is so critical to creating entrepreneurial action necessary for developing environmental innovations, what should be done to stimulate ecopreneurship?


»1. Provide high quality and reliable information to ecopreneurs.

»Lack of quality information is a major barrier to ecopreneurship. Because environmental innovations involve highly technical operations very little can be accomplished without reliable information about the nature and extent of the problems, the range of solutions available, the costs, and how to minimize them (Banks & Heaton, 1995). According to Cohen and Levinthal (1990), successful ecopreneurs recognize opportunities that others do not see because they have better access to information about the existence of the opportunities.

»Hermann (2011) also states that information availability and management help the entrepreneur or ecopreneur get closer to the opportunity i.e., where the market changes are and what is needed to access them. Clearly, the provision of reliable information directly to the potential business founders is a key factor in helping them make the decision to invest in an eco-innovation startup (Schnick, et al. 2002).


»2. Facilitate collaboration and networking among ecopreneurs and innovation intermediaries.

»“An innovation intermediary is an organization or body, which acts as an agent or broker in any aspect of the innovation process between two or more parties.” (Howells 2006, p. 172). They help the ecopreneur acquire knowledge outside their own organizational boundaries (Clarke & Roome, 1999), an as such the ecopreneur gain access to and exchange relevant ecology and sustainability-related information. Some of the different types of intermediaries are government and local authorities, NGOs, universities, industry associations and consultants.

»Collaboration between ecopreneurs and innovation intermediaries also provide access to direct assistance, e.g., advice on funding sources, advice on business operations, identification of potential collaborators, etc., which supplement the ecopreneurs resources and can lead to a startup involved with eco-innovations (Klewitz, Zeyen & Hansen (2012).


»3. Refocus the publicly funded environmental technologies (Research & Development)

»First, attracting more private sector funds for environmental technologies should be an important policy. In doing so, efforts should be made to reduce the risk for the private investors, while making sure that public money is used effectively and does not crowd out private initiatives (OECD, 2008).

»Secondly, publicly funded environmental technologies needs to be refocused. Presently, most of the funding are allocated to agencies that have very little to do with environmental technology (Department of Energy 44%, National Aeronautics and Space Association 23% and Department of Defense 11%), while a small percentage is directed to technologies that improve the environment, e.g. Department of commerce 6.2% and the Environmental Protection Agency 2% (Banks and Heaton, 1995). According to an OECD report, over 100 billion dollars are spent annually to support and conduct R&D in twenty-two agencies, but six agencies control 95 percent of the funds (OECD, 2008).

»If we are serious about attracting the innovative potential of entrepreneurs to develop environmental technologies, we need to refocus publicly funded R&D. This could be done by including improved environmental performance as a criterion for current R&D programs and also making environmentally relevant R&D a subcomponent of current programs (Banks & Heaton, 1995, p. 4).


»4. Increase the speed of commercialization of environmental technologies

»Many available environmental technologies have not been successfully introduced into the market because of market, infrastructure, production and consumption obstacles (OECD, 2009). One way to accelerate the commercialization of new technologies and the development of startups that will create clean technologies and green jobs is to establish a business incubator, e.g., cleantech business incubator. The incubator will offer flexible ready-to-go office space, lab facilities, and a supportive environment, where starting teams can share ideas with other entrepreneurs and fuel innovators. It will also give each startup the chance to work with a dedicated mentor, as well as access to a growing network of cleantech and business experts and introductions to prospective investors (Walti, 2011).

»Another way to speed up commercialization of new environmental technologies is technology certifications or validations. Quasi public bodies e.g. standards institutes will evaluate the effectiveness of the new technology and certifies its compliance with the standards. It is a one time scientific and technical performance evaluation, as well as a regulatory certification of environmental technology.

»This certification will reduce uncertainty around the new technologies and increase their acceptance, by offering third party information on technologies, which is critical to the EPA, other government agencies, and purchasers of innovative environmental technologies. Certifications and validations are other effective ways to foster diffusion and therefore speed up commercialization (Banks & Heaton, 1995: OECD, 2008).


»5. Increase access to financing

»Availability of funding and other incentives are critical for environmental innovation. Access to funding is necessary to help ecopreneurs meet the cost of technical development and to win recognition of new products and services (Schick, et al. 2002).

»Access to financing is extremely difficult for entrepreneurs in green innovation because of the immaturity of the market, the difficulty associated with accurately pricing the relative risk of the investment and the lack of history or track record of success. All of these make it more difficult for new entrants to innovation to obtain reasonable costs financing, than it is for established firms (OECD, 2011).

»To harness the innovative potential of entrepreneurs for environmental technologies, there is need to improve access to financing through strengthening financial support with loan guarantees, grants, revolving loan funds, tax credits, etc., developing relationships with the early-stage investment community, and provide information on the various financial incentives, subsidies, tax credits and grants available to encourage investments in environmental technologies (OECD, 2008; OECD, 2011).


»6. Improve access to markets

»A strong demand for new products, processes and services is the most important driver of environmental innovation. Strengthening demand could be done through regulatory policies that reward new technologies and greater use of economic incentives (Banks & Heaton, 1995).

»Regulatory signals that are strong, predictable and clear will spur environmental innovation. It is essential that the regulations discriminate in favor of new technologies rather than prolong the status quo. For example, reducing the reliance on available technology as the measure by which pollution control standards are set and looking instead to improve future capabilities (Banks & Heaton, 1995, p. 3).

»Greater use of economic and financial incentives will also stimulate demand. Presently, incentives, such as, tradable credits and charges have been used only in the context of air pollution. There is need to expand these incentives to other areas, such as, water pollution and beyond to strengthen demand and stimulate innovation (Banks & Heaton, 1995, pg.3).


»7. Establish clear policy on government procurement of green products

»The biggest challenge green businesses face is going from research to production and distribution, and government can help companies make this transition successfully by procuring green products (p. 12). Government, at all levels, must play a more important role in terms of purchasing green products and services and in showing other consumers the benefits of purchasing green products.

»Through the introduction of sustainability criteria into public procurement decisions, the government can stimulate the development and use of more environmentally-friendly technologies. The strategy should address responsibilities, resources and monitoring and evaluation procedures. The key goal should be to develop standards and create momentum towards significantly increasing the amount of green produts and services purchase by the government. (Ambachtsheer, Charest, Ksowski, Mitschele, & Nielson, 2007).


»8. Provide incentives for customers

»Consumers also have an important role to play in fostering green innovation. They account for more than 60% of the final consumption in the OECD area. The purchasing decisions that they make therefore have major impact on the extent to which markets can work to provide innovation in green growth.

»Providing incentives to consumers will stimulate the market and encourage investment in environmental R&D and environmental technologies. This is vital, because the development of environmental technologies depends on having a strong local market that allows entrepreneurs to successfully get off the ground (OECD, 2011).

»Consumers form a significant part of the market, offering incentives to encourage greener purchases will be beneficial to the cleantech sector. Although some incentives such as rebates through the Energy Star Program are currently offered to consumers, more still needs to be done to create a solid market for green products. Also, there is need to simplify and centralize existing incentives by developing a website that lists the incentives and eligible products by region and jurisdiction (Ambachtsheer, et al. 2007).

»Subsidies, such as reduced taxes or tax credits have been used to increase the attractiveness of more fuel efficient vehicles. In addition to taxes, governments can also use grants and subsidies to influence consumer behavior and to protect the environment, while at the same time creating opportunities for environmental innovation, investment, employment and green growth. The Japanese “ecoprint” system aimed at rewarding purchases of energy-saving home appliances and vehicles is a case in point (OECD, 2010).


»9. Promote flexible labor market policies and support worker skills training programs

»The transition towards a low carbon economy requires workers with new competencies to exploit the potential of the new technologies. Labor markets and training policies can play a key role in facilitating the adjustment necessary for the transition to green growth (OECD, 2010).

»The government and economic development agencies should promote and support flexible labor market policies to facilitate the movement of workers and resources from declining to innovative firms and regions. Too much rigidity in labor markets has been shown to reduce innovations (Cotis, Serres, and Duval, 2010). Having the right people is a driver for innovation, but it requires relevant education as well as the development of skills to complement the formal education (OECD, 2011).»





Innovation Typologies
Thematic Readings

2016/09/29

«Innovation typology comparisons»



Rosanna Garcia y Roger Calantone. «A Critical Look at Technological Innovation Typology and Innovativeness Terminology: A Literature Review». Journal of Product Innovation Management, vol. 19, n.º 2, March 2002. See references in the original publication of this text.




«Innovation typology comparisons

»There is no question that not all innovations are the same. Accordingly, they are frequently classified into typologies as a means of identifying their innovative characteristics or degree of innovativeness. It has been theorized and empirically tested that the varying degrees of newness and the discontinuities resulting from highly innovative innovations will change the important factors in the NPD process [18, 47,54]. This contingency approach to the NPD process has resulted in researchers devising ad hoc typologies to label degrees of innovativeness. A review of the literature reveals the following categorizations:

»_ eight categories–reformulated/new parts/remerchan- dising/new improvements/new products/new user/ new market/new customers [29]; Y five categories–systematic/major/minor/incremental/ unrecorded [18];

»_ tetra-categorization –incremental/modular/architec- tural/radical [27], niche creation/architectural/regular/ revolutionary [1], incremental/evolutionary market/ evolutionary technical/radical [42], incremental/ market breakthrough/technological breakthrough/ radical [7], incremental/architectural/fusion/ breakthrough [57];

»_ triadic categorization–low innovativeness/moderate innovativeness/high innovativeness [31], incremental/ new generation/radically new [62] and,

»_ dichotomous categorization–discontinuous/continu- ous [3,47], instrumental/ultimate [23], variations/re- orientations [43], true/adoption [37], original/refor- mulated [64], innovations/reinnovations [49], radical/ routine [38], evolutionary/revolutionary [59], sustaining/disruptive [9], really new/incremental [50, 54], breakthrough/incremental [46], and radical/incre- mental [5,18,4,30,35,52,56].


»This abundance of typologies has resulted in the same name being used for different types of innovations and the same innovation being classified under different typologies. The following review of four different classifications by four groups of researchers will demonstrate this point.

»Utterback [59] provides the following definition of a discontinuous or radical innovation: “By discontinuous change or radical innovation, I mean change that sweeps away much of a firm’s existing investment in technical skills and knowledge, designs, production technique, plant and equipment” [p. 200]. From Utterback’s perspective, dislocation or discontinuity at the firm level or in the industry accompanies the introduction of radical innovations. Continuous (incremental) innovations give way to standardization and status quo within the firm or industry.

»Rothwell and Gardiner [49] focus on technological discontinuity, by emphasizing ‘reinnovations’ or improvements on existing innovations. Their dichotomy of ‘innovations’ and ‘reinnovations’ leads to several subcategories. ‘Innovations’ are radically new inventions establishing landmark new products, and as such, create new industries. ‘Reinnovations’ dominate much of the contemporary “real” industrial world. They result in existing technology improving upon existing product design (incremental), new technology improving existing products (generational), existing technology creating new products (new mark products), improved materials improving existing products (improvements), and new technology improving subsystems of existing products (minor details).

»Another viewpoint, Kleinschmidt and Cooper’s [31] study of 195 new products, leads to a triad categorization. Klein- schmidt and Cooper’s typology distinguishes between ‘high’, ‘moderate’, and ‘low’ innovativeness. Highly innovative prod- ucts include new to the world products and new to the firm lines, which are also new to the market. Moderately innovative products consist of less innovative new lines to the firm and new products to the existing product line. Low innovative products include modifications, cost reductions, and repositioning.

»A fourth perspective, Abernathy and Clark’s [1] matrix categorization focuses on competitive significance by mapping technology competence against market environments. The four resulting categories for innovations are ‘niche creation’, ‘architectural’, ‘regular’ and ‘revolutionary’.In niche creations, stable and wellspecified existing technology is refined, improved, or changed to support a new market position. These refinements build on established technical competence and improve product applicability in emerging market segments. Architectural innovations forge new market linkages with new technology through the creation of new industries or the reformation of existing ones. They set the future architecture of the industry. Regular innovations build on established technical and production competences targeted to existing markets and customers. They often involve incremental improvements in process technology. Revolutionary innovations disrupt and obsolete technical and production competence but target existing markets and customers.

»A couple of examples will demonstrate how just these four different classification approaches can lead to different labeling of the same innovation. A classic example is the typewriter. Utterback [59] writes, “Discontinuities were observed between the periods of the manual typewriter, electrics, dedicated work processors, and personal computers. Of the large manual type- writer firms of the early twentieth century, none were successful in jumping onto the bandwagon of the electric typewriter; it was IBM, an outsider that developed both the product and its market” [p. 201]. Based on this scenario, Utterback would designate the electric typewriter as a radical innovation because the new technology brought about industrial discontinuity and new competitors.

»The Rothwell and Gardiner typology identified an ‘incremental’ design as adding radical new features to improve upon an existing innovation. Thus, Rothwell and Gardiner would label the electrical technology advancement from manual to electric typewriters as an incremental innovation. Kleinschmidt and Cooper would label the typewriter technology evolution a moderate innovation and Abernathy and Clark would call it a revolutionary innovation.

»Another example is the Canon laser photocopier which produced digital signals that could be electronically digitally processed, stored or transmitted simultaneously to a number of distant slave printers. The analog system of its conventional predecessors were unable to network. The new technology was the application of a laser and electronic information processing step inserted between the original optical and print systems. The digital processing subsystem allowed the production of a technologically new laser digital copier. Utterback would label the movement from analog to digital technology a market broadening, competence enhancing, radical innovation. Yet for Rothwell and Gardiner, radical technology embedded in a reinnovation does not constitute a radical innovation, instead just a redesign on an ‘innovation’. Thus, they would label this innovation an incremental innovation with a subassembly change. Kleinschmidt and Cooper would label it a moderate innovation, and to Abernathy and Clark the copier technology evolution is a regular innovation.

»As these two examples demonstrate, the same innovation can be labeled on either ends of the scale of innovativeness depending on the researcher. This ambiguity in classification schema makes it impractical, if not impossible, to accurately compare research studies. With these types of terminology irregularities, it is impossible to accumulate knowledge regarding innovation types and how their varying degrees of newness alter the NPD process. The next section will review how inconsistencies also plague the operationalization of product innovativeness in empirical literature.»





Innovation Typologies
Thematic Readings

2016/09/27

«From Disruptive Technology to Disruptive Business Model Innovation: In Need for an Integrated Conceptual Framework»



Solomon R. Habtay and Magnus Holmén. School of Economic and Business Sciences, Faculty of Commerce, Law and Management, University of Witwatersrand, 2012. Paper. See references in the original publication of this text.




«Discussions and Conclusions

»This study modelled the evolutionary development of disruptive business model innovation by proposing two hierarchically linked phases. Consistent with previous research, the result of this paper suggests that latent disruptive innovation is negatively related to incumbent’s managers’ mainstream customer orientation at initial stage (Govindarajan et. al., 2011; Adner, 2002; Christensen, 1997). This negative relationship should define a potentially disruptive innovation, and should distinguish at the most basic level between disruptive and sustaining innovations. In addition, it should also distinguish disruptive kinds of innovations from other types of discontinuous innovations, e.g. radical innovations that are positively related to incumbent’s managers’ mainstream market orientation (Govindarajan et al., 2011).

»In the long run, however, incumbents’ mainstream customer orientation can be positively associated with the emergence of a potentially disruptive niche market. This suggests that beyond the disruptive innovation’s endogenous characteristics, exogenous asymmetric cognition orientations between the innovator and incumbent can inform the disparate trajectories.

»This insight provides theoretical reasoning to consider ex ante incumbents’ customer orientation as one of the precursors of a potentially disruptive niche market. This negative (incumbents) customer orientation towards disruptive innovation arises because neither the new business model’s disruptiveness potential nor its trajectory is perceptible ex ante (Danneels, 2004; Gilbert, 2003; Nightingale, 2004) in niche markets that emerge outside of incumbents radar (Christensen and Raynor, 2003). While the flood of new firms in a niche market can increase the threat of disruption, incumbents’ absence or possibly misguided responses to disruptive firms during the niche market phase may also increase the disruptiveness potential of the niche market. We find support in Christensen’s (1997) argument that established firms are likely to flee the niche market in order to concentrate on profitable markets, consequently providing new firms a competitive free space and momentum to grow the niche market.

»The incumbent’s part of the disruptive innovation model hypothesized that a potentially disruptive niche market business model innovation can be transformed into disruptive innovation, if conditions amplify asymmetric capabilities and incentives and associated incumbents’ managerial dilemma. Studies on technological change have argued that technical competencies mismatch can cause incumbents misfortune in face of discontinuous innovation (Henderson, 2006; Henderson and Clark, 1990; Tushman and Anderson, 1986). But our findings suggest the notion of capabilities misfit may not be present in disruptive innovation phenomena.

»Confirming to Christensen’s (1997) argument, our result suggests that incumbents may be disrupted, despite mastering radical, competence-destroying or architectural innovation capabilities. There are two possible explanations. First, some disruptive business model innovations, such as no-frills low-cost airlines, insurance and banking models may create misfits in downstream capabilities such as in distribution and sales, but they do not significantly depart from established upstream technical activities. When conditions allow, incumbents can leverage accumulated capabilities and thus respond successfully. Second, although some technologically sophisticated disruptive innovations entail downstream and upstream capabilities misfit, resource endowed firms may either hire skills and technologies or acquire disruptive firms to develop disruptive capabilities.

»This study confirms that disruptive innovation is the function of asymmetric incentive systems and managerial dilemma. The economic asymmetric explanation depicts disruptive innovation as a process outcome when entrants pursue competition through low-cost high volume business models against differentiated business models in the mainstream market. This creates a dilemma for incumbents which in turn may trigger disruption.


»Theoretical and managerial implications

»Our study makes several key contributions to theory and practice. First, most business model innovation studies adopt entrants’ entrepreneurial perspectives in examining new business model development. Conversely, extant disruptive innovation research begins when these studies “end” and adopt incumbents perspectives in exploring firms impediments to adaptive efforts. This study systematically links both perspectives together and explores disruptive business model innovation. Second, disruptive innovation theory attributes to technological change or asymmetric economic motivations for the departure of disruptive paradigm. Beyond these explanations, this study shows how asymmetric cognitive orientations can inform the disparities between the disruptive and sustaining business models trajectories.

»Third, this study systematically unpacks the differential effects of capabilities, incentive systems and managerial cognition as underlying mechanisms of disruptive innovation. While asymmetric incentives and cognition orientations can explain disruptive innovation, asymmetric technical capabilities have no effect on disruptive innovation. The study further breaks down the cognitive explanation into incumbents’ customer orientation and incumbents managerial dilemma. Incumbents’ customer orientation refers to ex ante difficulties in identification of latent or emerging disruptive niche market. On the other hand, incumbents dilemma is an ex post construct that explains the difficulties incumbents’ managers encounter in responding to disruptive innovation when the incumbent confronts disruptive innovation.


»Limitations and Future Research

»First, although the business model literature has offered a number of important theoretical frameworks of business model concept, strategic management research has yet to offer psychometrically reliable, valid and widely agreed upon definition with operational constructs of the concept that can assist for innovation research on the topic of disruptive business model innovation (Markides, 2008). Since the business model concept is evolutionary, complex, dynamic and multidimensional that considers all aspects of business activities over development period, this study focused only on few aspects. Other important explanatory constructs could have been excluded from our analysis.

»Second, we tested the conceptual model on aggregated data from five industries. However this attempt to generalize the findings across industries makes data interpretation problematic. Disruptive innovation is relative, “not an absolute phenomenon” (Christensen, 2006: 42). In other words, disruptiveness can only be defined in relation to a certain incumbent’s business model in a specific context. If each disruptive innovation is investigated separately across the five industries, each could have drawn alternative explanations. Study on disruptive business model innovation heterogeneity across industries could thus shed further knowledge.

»Third, our results show that a potentially disruptive niche market business model does not have inherent disruptive capacity on its own. Although a latent disruptive innovation can initially create a niche market, some business models functioning as “tickets to entry” may fail (Brink and Holmén, 2009), while others may remain isolated in niche markets. Still in other circumstances some may progress over time through a disparate performance trajectory to spark an era of disruption. But this situation appears unpredictable and difficult to make theoretical connections ex post.

»The challenge of identifying early signals of latent disruptive innovation remains unsolved. Further research could investigate the inherent features of latent disruptive business model innovation in order to distinguish from other types of low-cost business models that do not materialize disruptive threats. Furthermore, little is known of incumbents competitive behaviour before disruption unfolds. Our conclusion that incumbents’ customer orientation leads to absence is a necessary generalization and considers incumbents as homogenous. A future study on the heterogeneity of incumbents’ reactions during a potentially disruptive niche market evolution period could be an interesting topic to explore.»





Innovation Typologies
Thematic Readings

2016/09/26

«Paradigm Shift in Pre-Service Teacher Education: Implications for Innovation and Practice»



Yin Cheong Cheng. Innovative Practices in Pre-Service Teacher Education. An Asia-Pacific Perspective, Cher Ping Lim, Kenneth Cock, Graeme Lock and Christopher Brook (Eds.), Rotterdam, Sense Publishers, 2009.




«The three waves of education reforms in different parts of the Asia-Pacific Region and beyond entail different types of teacher effectiveness: internal effectiveness, interface effectiveness and future effectiveness, which are based on completely different paradigms in education. Correspondingly, the major characteristics of three waves of pre-service teacher education and their innovations are different.

»The first wave of education reform emphasizes internal improvement and effectiveness of schools. Therefore, the paradigm of pre-service teacher education conceptualizes teacher effectiveness mainly as the internal effectiveness of teaching and work to achieve the planned school goals. The innovations in teacher education are often short-term, relating to improvement in delivery of planned professional knowledge, skills and attitudes to prospective teachers. There is a lack of systematic application of ICT.

»The second wave of education reform focuses on the interface between the school and the community. The concept of teacher interface effectiveness is to provide education services that satisfy the needs of stakeholders and are accountable to their schools and the public. Innovations in the second wave of teacher education focus mainly on enhancement of satisfaction of stakeholders such as policymakers, teacher employers, prospective teachers and community leaders.

»The third wave of education reform represents a paradigm shift towards school future effectiveness, which is relevant to the future needs and sustainable developments of individuals and the society. Therefore, the focus of teacher future effectiveness is on ensuring the relevance of aims, content, practices, and outcomes of teacher work to the multiple and sustainable developments for the future. The third wave of pre-service teacher education uses a future model with emphasis on CMI and triplization, aiming at creating unlimited opportunities for teachers’ continuous life-long learning and development with the support of networked human and ICT environment.

»As opposed to the first and second waves, the third wave pre-service teacher education in the Asia-Pacific region should have extensive innovations with the application of ICT in building up a networked environment for teachers’ individualized, localized and globalized professional learning and CMI development. Innovation with ICT plays a key role in ensuring the paradigm shift in pre-service teacher education.

»Although teachers’ internal effectiveness, interface effectiveness, and future effectiveness are based on different paradigms and they have different strengths and focuses, all of them can co-exist and, arguably, can still make a contribution to the practice of pre-service teacher education in the new century. They can be mutually supplementary to each other, taking internal improvement, interface satisfaction and accountability, and future relevance into consideration. I believe that preservice teacher education should facilitate prospective teachers to perform internal effectiveness, interface effectiveness, and future effectiveness for their schools.

»This would provide the new generation of teachers total teacher effectiveness. I hope that the analysis in this chapter provides a new comprehensive framework for local and international educators, researchers, and policy-makers to develop new teachers and conduct innovations in pre-service teacher education for the future.»





Innovation Typologies
Thematic Readings

2016/09/23

«A Business Model Innovation Typology»



Yariv Taran, Harry Boer and Peter Lindgren. Decision Sciences, vol. 46, n. 2, April 2015. See the references in the original publication of this text.



«CONTRIBUTION AND FURTHER RESEARCH


»Theoretical Contribution

»Business model innovation matters, but business model innovation theory is scarce and lacks an intellectual home (Teece, 2010). We used notions from innovation, organization, strategy, and business model theory to inform a multiple case study aimed at developing a typology of business model innovations, a first yet necessary step in the building of theory, and a powerful tool for strategic decision makers.

»This article contributes to innovation theory, which has largely neglected the phenomenon of business model innovation, and to the business model community, which has put little effort into theory development.

»The study suggests that the success of the innovation depends on, among others, the company’s appreciation of the new business model’s innovativeness and the extent to which the company achieves fit between the innovativeness (radicality, reach, complexity), strategic context (proactiveness), and organizational setting (openness) of the innovation.

»These factors define four types of business model innovation. The case studies showed that three of these types present ideal types, that is, effective forms of business model innovation, but did not provide enough evidence to conclude the same about a fourth type. The four types are essentially different in the way they were triggered (strategic context), the locus of the process (organization setting), the innovativeness of the business models pursued and the risk involved, as well as the consequences of failure. A company’s risk appetite and mitigation seem to be major factors explaining the existence of the four types. The association between fit among the innovativeness, strategic context, and organization setting of a business model innovation on the one hand, and success, on the other, together with our arguments for the central role of risk (appetite and mitigation), led us to develop three propositions for further research.


»Limitations and Further Research

»Given the highly explorative nature of this study, as well as its small sample, the typology, its explanation and the propositions should be considered as tentative theory. Several approaches are possible to extend and test the typology proposed, including more case studies to shed additional qualitative light on the findings presented here. Two issues deserve specific attention.

»First, both companies are analyzers, large (in EU terms), active in the electronics industry, and located in Northwest Europe. Further, preferably surveybased, research is needed to test whether the typology and the propositions hold beyond these limitations.

»Important inputs to the development of that survey are related to the second limitation. It is not unlikely that we overlooked important descriptors of each of the four types. For example, we identified the role of risk and the potential effects of failure, but there may well be other aspects in which business model innovations differ. Research into technological, product and, to some extent, organizational and administrative innovation has identified a range of issues including, but not limited to, success factors (Project SAPPHO – Rothwell and his colleagues, starting with Rothwell et al. (1974) and Rothwell, 1977; Project NewProd – Cooper and his colleagues (e.g., Cooper, 1980; Cooper & Kleinschmidt, 1995), the roles of key individuals in innovation processes (e.g., Sch¨on, 1963; Frohman, 1978; Maidique, 1980; Roberts & Fusfeld, 1981; Boer & During, 2001) and also insight into the organizational context (Burns & Stalker, 1961; Hage & Aiken, 1970; Zaltman, Duncan,&Holbek, 1973; Pierce&Delbecq, 1977; Daft, 1978) and, more recently, the process of innovation (Cooper, 1983;Van deVen&Poole, 1990; Roussel, Saad, & Erickson, 1991; Van de Ven, 1992; Boer & During, 2001).

»With reference to Cooper and Kleinschmidt (1995), whose five categories of success factors encompasses all of these issues, we have limited insight into the influence of process (except for the impact of market understanding or, rather, lack thereof) and lack data about culture and (senior management and organizational) commitment. Furthermore, our insight into the role of strategy and organization is limited to two aspects, proactiveness and openness, respectively. For example, we lack data on the role of key individuals. There is a wealth of theory on (mostly product) innovation, organization, and strategy, in addition to the authors referred to above, which may help in developing propositions on the influence of each of these five categories on the success of business model innovation, which can be operationalized and tested through the survey suggested above.


»(Potential) Managerial Contribution

»Should it appear that further research enriches, but does not essentially alter, the business model innovation typology and, particularly, the influence of consistency on success, the typology presents a powerful decision-making tool. First, it helps managers to identify, estimate, and seek consistency between the key drivers of business model innovation success, including innovativeness, strategic context, and organizational setting, and possibly also the factors categorized by Cooper and Kleinschmidt (1995). Second, the typology as is includes key pointers to be considered, particularly the importance of risk appetite and mitigation. Hopefully, further research as indicated above will produce more pointers.


»Cross-Case Analysis – Toward a Business Model Innovation Typology

»Table 3 combines the characteristics identified and discussed above and suggests four types of business model innovation, three of which are successful and can be regarded as ideal. For reasons of convenience, we labeled the four types using the descriptors of strategic context (i.e., proactive vs. reactive) and organizational setting (i.e., open vs. closed). We identified examples of each of the four types.

»We will first present these types, and then discuss the effects of fit between the innovativeness, strategic context, and organizational setting of a business model innovation on the success of the innovation.

»Four main types of business model innovations

»Open/proactive: Cases D and F were highly successful open/proactive business model innovations. This type has many potential advantages but also disadvantages, particularly the risks involved (e.g., Lieberman & Montgomery, 1988, 1998) in aiming for a radically new to the industry (case F) or even the world (case D) innovation. Company Alpha reduced those risks by limiting the complexity of the innovations to four building blocks (target customers, core competences, partner network, and profit formula). Rather than developing entirely new core competences, the company acquired and enhanced existing competences. Furthermore, company Alpha conducted and deployed these innovations through a joint venture, which allowed it to share the risks involved, while keeping its existing business and the necessary competences intact.

»Closed/proactive: Cases A, 1, and, depending on perspective (see below), also case 3 were closed/proactive business model innovations. Case A was aimed at developing an entirely new business in addition to company Alpha’s existing activities. Case 1 involved a major overhaul of company Beta’s existing business. Both innovations involved a significant departure from the companies’ current activities (high radicality), offering new-to-the-industry products (high reach), requiring changes in all (case 1), or most (all except new competence development or acquisition, case A) building blocks (high complexity). The risks involved in this type of innovation are high, in particular if it is aimed at replacing the company’s entire business model, as in case 1. Obviously, developing an additional business as in case A is also risky, but in that case the company still has its existing business to fall back to. Cases A and 1 were highly successful and worth the risks involved.

»Open/reactive: Cases E and 2were open/reactive business model innovations, but had radically opposite characteristics in terms of their innovativeness. Aimed at offering new-to-the-industry products (high reach), case E marked a next step in company Alpha’s strategy in that it involved an improvement (low radicality) of relatively few of the building blocks (low complexity) of the company’s already highly unique business model. Due to these characteristics, this was a relatively low-risk innovation, whose (financial) risks were further reduced through the establishment of a joint venture with a venture fund. Case 2was an acquisition, which did not change the industry, let alone the world (low reach), but gave company Beta access to a very different industry (high radicality). After a major redesign (high complexity), the acquired company was expected to continue as an independent business. Cases E and 2 were very successful.

»(Partly) closed/reactive: This last group is problematic. Case B is a closed/reactive innovation. Cases C and G are partly closed/reactive innovations. Both cases involved an attempt to outsource some of company Alpha’s activities to a partner, marketing and sales (case C) and manufacturing (case G), respectively. Through case 3, company Beta attempted to push a radically new product into the marketplace. Although it had all the innovativeness characteristics of a closed/reactive business model innovation (low radicality, low reach, high complexity), content-wise case 3 involved a closed/proactive innovation. Innovations in this group are largely governed and handled internally, although there may be some partner interaction (e.g., the outsourcing attempts in cases C and G). The outcome of this type of innovation is a range of incremental (low radicality) changes in all or most of the company’s business model building blocks (high complexity), which are, however, at best new to the company. In effect, the risks involved were low and the consequences of failure limited.


»The effect of fit on success

»Except for open/reactive innovations, there appears to be fit between the innovativeness, strategic context, and organizational setting of the business model innovation.

»Open/proactive business model innovations are associated with high levels of radicality and reach, and a low level of complexity (cases D, F). Closed/proactive innovations score high on all three innovativeness characteristics (cases A, 1, and, depending on perspective, 3). Business model innovations taking place in a (partly) closed/reactive context are lowin radicality and reach, but high in complexity (cases B, C, G, and, again, depending on perspective, 3). As to the open/reactive innovations, the picture is less straightforward: cases E and 2 have radically opposite characteristics – low-high-low and high-low-high, respectively. Through case E, company Alpha tried to use its existing competences to go beyond its current market and reach out to the rest of the industry, with a partner, in the form of a joint venture. Case 2 involved the acquisition of an existing company, which left company Beta’s internal organization largely intact, but enabled it to access new markets with new products. The implication of this finding is that we should distinguish between two open/reactive subtypes (see Table 3).

»Three of the ten business model innovation attempts failed (shown in brackets in Table 3); one was a partial success. All these cases fall into the (partly) closed/reactive group.



»IDEAL TYPES: IDENTIFICATION AND TENTATIVE EXPLANATION


»Ideal Types

»The differences between the success and (partial) failure cases suggest that fit among innovativeness, strategic context, and organizational setting affects the likelihood of success. The finding that fit plays an important role is concurrent with various bodies of theory, including manufacturing strategy (e.g., Hayes & Wheelwright, 1984; Skinner, 1985), organization theory (e.g., Mintzberg, 1979), and innovation theory (e.g., Boer & During, 2001).

»On the aggregate innovativeness scale combining radicality, reach, and complexity, all successful cases, A, D, E, F, 1, and 2, were more innovative than the partially successful case B and the failures C, G, and 3. All successful cases were high in reach, except case 2, and highly radical, except case E. In contrast, cases B, C, G, and 3 were low in radicality, low in reach, and high in complexity.

»A deeper look into the failure cases suggests a pattern. First, complexity hardly seems to explain the difference between success and failure, but radicality and reach do. Case C involved the establishment of a new business unit offering incremental improvements to existing products, combined with outsourcing of marketing and sales to a partner. Case G concerned outsourcing of manufacturing to a partner, which, however, failed to result in a competitive product. Company Alpha is, indeed, a highly competent design company, accustomed to pushing new products into the marketplace and with a successful history of technology development collaborations. However, the company may have underestimated the complexities involved in establishing a successful operational collaboration through outsourcing. Case 3 failed because company Beta tried to push a new product into the market – they improved (low radicality) many of the building blocks (high complexity) to develop a new product for (mostly) existing market segments (low reach), without, however, having any idea of how customers would respond. In other words, the innovativeness characteristics are associated with a (partly) closed/reactive innovation, rather than the closed/proactive innovation it actually is.

»Accepting the organization theory notion (e.g., Doty et al., 1993) that effective configuration implies ideal type, the open/proactive configuration, the two forms of closed/proactive configuration, and the open/reactive configurations represent ideal types. The closed/reactive configuration may also be an ideal type, but we do not have sufficient evidence for that, as the three failures are examples of business model innovations that fall between the (other) ideal types; they are either not entirely closed, or represent some mix of proactive and reactive behavior.


»Tentative Explanation and Propositions

»Risk appetite (e.g., HM Treasury, 2006; KPMG, 2008) and mitigation, that is, dealing with the potential effects of failure, seem to explain most of the associations between the innovativeness, proactiveness, and openness of business model innovations.

»Successful high radicality, high reach, and low complexity business model innovations are associated with an open, proactive approach. High radicality and reach are clearly associated with proactiveness. Companies mitigate the risk involved by keeping the innovation outside their existing core business. They reduce the risk and effects of failure further by focusing on a limited number of building blocks. Based on this, we propose:


»Proposition 1

»Companies pursuing a proactive, that is, high radicality and high reach, business model innovation, best adopt an open approach aimed at establishing a new business outside their existing core business or some form of external collaboration, with a limited number of new building blocks.

»A proactive company pursuing a highly complex business model innovation takes serious risks and the consequences of failure may be disastrous, especially if it adopts a closed approach. The company should be prepared to take and actively manage the risks involved in innovating its entire core business. We propose:


»Proposition 2

»Successful companies pursuing a proactive, that is, high radicality and high reach, as well as high complexity business model innovation, and adopting a closed approach, take and actively manage the risks involved in innovating their entire core business.

»Acompany pursuing an open, reactive business model innovation is cautious. In variant A (Table 3), the company reaches out to the world but stays close to home at the same time, by only pursuing incremental innovation of a limited number of building blocks. Alternatively, in variant B (Table 3), the company may, for example, acquire an existing company in a different industry, which provides it with several radically different buildings blocks that the company may further develop based on its own experiences. The result, however, is a mostly “new to the company” business model. The risk level is low (variant A) to medium (variant B) and the effects of failure are limited as the company’s existing business is not affected.


»Proposition 3

»Companies pursuing an open, reactive business model innovation are cautious, keep the risk involved relatively low, and go for low radicality, high reach, and low complexity or, alternatively, high radicality, low reach, and high complexity, which, in both cases leads to limited effects, should the innovation fail.

»Closed, reactive business model innovations are associated with low radicality, low reach, and high complexity, low to medium risk and limited failure effects. As our research did not provide evidence of successful cases of this type, further research is needed to investigate if closed, reactive business model innovations can be successful.»





Innovation Typologies
Thematic Readings

2016/09/22

«A Typology of Reverse Innovation»



Max von Zedtwitz, Simone Corsi, Peder Veng Søberg, and Romeo Frega. Journal of Product Innovation Management, n. 32(1), June 2014. See the references in the original publication of this text.













«Discussion

»Strengths and Merits of the Typology


»“Reverse innovation” is just one of many recent additions to the jungle of innovation terms that have come to be used in the context of developing countries and emerging markets. Concepts such as frugal innovation, cost innovation, innovation for the bottom of the pyramid, etc. (see Table 1) often have overlapping characteristics and create terminology confusion. Common to all of them is that they describe innovation in developing countries, from developing countries, and sometimes even for developing countries.

»The proposed model provides clarity at least with respect to reverse innovation. Building on Rogers’s (1962) concept of a flow of innovation and Vernon’s (1966) four main phases of international innovation, it distinguishes between advanced and developing countries both as markets and creators of global innovation flows. The global innovation model has expanded the notion of reverse innovation beyond a reintroduction of products successful in developing countries to markets in advanced countries. Knowledge is created, codified, and embodied in new products and services before launch, and the model captures the innovative value added in developing economies (e.g., Christensen et al., 2010; Hang, Chen, and Subramanian, 2010).

»This model appears to be one of very few to explicitly differentiate along the geographical locus of innovation; most international models of innovation map a flow between headquarter and subsidiaries (e.g., Ghoshal and Bartlett, 1988). For instance, reverse innovation and reverse knowledge transfer differ also in the sense that reverse knowledge transfer is simply knowledge flow back to the headquarters (Buckley et al., 2003).

»Previous research has assumed that innovation activities are ideally colocated; even Vernon’s hypothesis builds on the premise that the advanced country inventor is physically close to available technology, customers, and expressed needs. While the differentiation into only two location categories may be crude, it enables a clearer organization of future analysis along previously established patterns of research.

»Research that has emphasized the organizational locus of innovation—for example, offshoring, collaborative product development, reverse knowledge transfer, and outsourcing—can now be recast with potentially new insights.

»The definition of a “reversed” vis-à-vis a “normal” flow of innovation might raise concerns of ethnocentrism. Innovation is not a new concept for developing countries, even though they may not have the industrial sophistication of high-tech innovation found in advanced countries, and their innovations are generally diffused only within geographically limited regions, in contrast to the international innovation flows from advanced countries.

»For this purpose, the term “reverse” is no more than a tool for describing an empirical phenomenon seen against the current paradigm. Moreover, the reverse direction of the flow of innovation is not defined by any particular country (e.g., from a Chinese point of view, any innovation first launched somewhere else before it is launched in China could rightfully be considered a reverse innovation); it is the classification of the involved countries at the time of the flow that determines whether the innovation is reverse or not. For instance, a thousand years ago, Europe’s economy would have been classified as developing, whereas China’s and the Middle East’s would have been classified as advanced.

»The model thus also challenges our understanding of temporal continuity in innovation. Even though the model seems to impose a strict sequential straightjacket on innovation, it does not designate how much time may elapse in each phase or, equally important, between two phases. How much delay can there be in a process of innovation before it is no longer identifiable as a flow? How long can the innovation process be suspended?

»Rogers (1962) puts no upper limit on the time innovation may take to disseminate to new adopters. Related questions to resolve in this context involve the definition of the origin of an innovation (an identifiable source of a new idea or technology) and the extent to which the innovation can be internalized.

»Finally, the new model also introduces six new innovation flows that have not yet been identified as reverse flows in the literature. On the basis of the earlier marketbased definition, only xxDA flows (i.e., AADA, ADDA, DADA, and DDDA) have been recognized as reverse innovations. On the basis of the new model, six more innovation flows are reverse: ADAA, ADAD, DAAA, DAAD, DDAA, and DDAD. Two of these are reverse innovations in the strong sense.



»Weaknesses and Implications for Future Research

»While the relative simplicity of the model is useful for creating a cogent conceptual framework, the phases of an innovation flow may not always be as clearly delineated as the model would suggest, neither across time as part of a continuous flow nor across a multicountry geography. Any shortcomings of the model’s applicability need to be addressed in future research.

»With four distinct phases, the innovation flow is linear and gives the impression of being deterministic. The model, which follows the four generic phases of Vernon’s product life-cycle theory, could be expanded beyond primary and secondary markets (the final two innovation phases) toward tertiary markets, for instance when an innovation is first introduced in China as the home country, and next in other BRIC countries, before the company is sufficiently confident or resourceful to enter markets in advanced countries. Simultaneous market launches, especially those that immediately target both advanced and developing markets, also stretch the model.

»The notion of flow could also be more refined for the earlier innovation phases, but this would not fundamentally change the sequential logic of concept and product creation. This issue is more pronounced in mixedinnovation use of the model. For instance, it is often difficult, and sometimes impossible, to separate product from technology development. Is the Tata Nano a DDDx or an ADDx innovation? The case for DDDx is that the product was conceived in India; the case forADDx is that the automobile concept, on the basis of which the Tata Nano was later developed, was developed in the West.

»Drawing a clear boundary is also difficult when we have research-intensive products such as medicines (Oncovin, for example) where the first innovation phase is science rather than product focused. If the model is used for technology innovation, then questions about transitioning ownership and temporal distance between phases are likely to arise; if the model is used for product innovation, these issues are less acute.

»More research on innovation conducted concurrently in different countries is also necessary. This was hardly an issue during Vernon’s time, but with the arrival of modern telecommunication and information technologies and more lateral business structures, innovation is increasingly performed simultaneously in multiple locations. Most new product development projects are still conducted in one location or in one country only (Li and Vanhaverbeke, 2009), and even when several countries are involved, the leadership and the lion’s share of the work usually reside in one location. Still, there are always a few cases of innovation that are truly multinational in nature and that may be more difficult to map with the present simplified scheme. Given the multilateral collaboration in such innovation projects, we suspect they would not qualify as reverse innovations.

»It may be worthwhile to note that an innovation can only be called reverse after a reversal of the flow has actually occurred. What exactly triggers those reversals, that is, the antecedents of reverse innovation, remains largely unexplored, and would require a reclassification of push and pull factors in global R&D and innovation literature.

»Another expansion of the model concerns the relatively simple distinction between “advanced” and “developing” economies. A more nuanced model could include fast-follower countries such as China, India, and Turkey; least-developed countries, which make up the majority of “markets at the bottom of the pyramid” (Prahalad, 2004); and newly industrialized countries. Such countries are aggregated in the model under the term “developing country”; future research should utilize the categorization scheme best suited to the chosen reference framework and intended application.

»The model allows researchers to conceptualize, capture, and analyze areas of global innovation thus far neglected because of few actual observed innovation cases (e.g., a DADAflow of innovation) but of potentially important future application and theoretical interest. The model also seems to map a generational timeline from the top (AAAA) to the bottom (DDDD), implying that, historically, the majority of global innovation flows first took place in ways identified by Vernon (AAAA or AAAD) but gradually started to include flow types located immediately below, such as those that targeted developing countries as primary markets, as well as flow types emerging later, such as those that describe product development in developing countries.



»Research Propositions

»While the majority of global innovation still seems to be of Vernon’s original type, future innovation flows will likely be more evenly distributed among the types outlined here. As described earlier, there is a trend, driven in part by the global ascendency of MNCs [multinational companies] from developing countries, in part by MNCs worldwide, and especially by advanced countries, to locate R&D centers in developing countries while continuing to serve markets in their home countries. Thus:


»Proposition 1: In the future, there will be more reverse innovation of both weak and strong types.

»MNCs aim to leverage local advantages in global innovation, although these advantages may differ between advanced and developing countries. Reverse innovations in the strong sense are originating mostly from developing countries, according to the model, while weak reverse innovation originates from advanced countries.

»Six of the 10 reverse innovation flows, and four of the five strong reverse innovation flows, have their earliest ideation stage in a developing country, and only one (weak) reverse innovation flow does not pass through a developing country in either concept development or new product development. Hence:


»Proposition 2: Developing country MNCs will engage more in strong reverse innovation than will advanced country MNCs, and advanced country MNCs will engage more in weak reverse innovation.

»Failing to leverage local home country advantages would be as damaging as failing to exploit market opportunities abroad. Several cases of reverse innovation reported in this paper were motivated by the failure to successfully innovate the original technology along traditional global innovation flows.

»Competing firms who master the art of leveraging countries as sources of both know-how and markets, wherever they may be and at whatever level of development, will have an advantage over those firms that stagnate in their global innovation capability (Chen, Huang, and Lin, 2012). Therefore:


»Proposition 3: MNCs that engage in reverse innovation will improve their overall innovation productivity.

»Access to host country advantages has been a strong driver for globalization of innovation (von Zedtwitz and Gassmann, 2002). Findlay (1978) argues that countries with large development differences have a stronger need to catch up, while Cohen and Levinthal (1990) suggest that countries with lowcognitive and institutional distance find it easier to do so.

»Intellectual property regimes are of particular importance in this context, as they have positive bearing on both foreign inbound direct investment and overall domestic innovative capacity and stock of knowledge, improving overall conditions for innovation in a country (D’Agostino and Santangelo, 2010). Thus:


»Proposition 4: In the future, there will be more reverse innovation (both weak and strong) from developing countries with improved institutional frameworks.»





Innovation Typologies
Thematic Readings

«A Business Model Innovation Typology»

Yariv Taran, Harry Boer and Peter Lindgren. Decision Sciences, , vol. 46, n. 2, April 2015. See the references in the original publication of this text.



« »





Innovation Typologies
Thematic Readings

2016/09/21

«Stakeholder analysis to support inclusivity of innovation processes in farming and food systems»



Margareta Amy Lelea, Guyo Malicha Roba , Anja Christinck and Brigitte Kaufmann. «“All relevant stakeholders”: a literature review of stakeholder analysis to support inclusivity of innovation processes in farming and food systems». 12th European International Farming Systems Association Symposium, At Harper Adams University, United Kingdom. See the references in the original publication of this text.



«Recent decades have witnessed a growing application of different forms of stakeholder identification and analysis in research fields such as public policy, international development, agriculture and environmental sciences. Particularly with transdisciplinary research, stakeholder involvement is necessary for knowledge integration and innovation co-creation. A stakeholder analysis is a way of identifying who is a stakeholder related to a specific issue or problem situation, and serves at making their interests, objectives, power dynamics and relationships explicit.

»Christopher Weible, working on marine resource management, emphasises that stakeholder analysis needs “to address a set of questions: who are the stakeholders to include in the analysis; what are the stakeholders' interests and beliefs; who controls critical resources; with whom do stakeholders form coalitions; and what strategies and venues do stakeholders use to achieve their objectives” (2006: 96).

»The first step of a stakeholder analysis is identification. However, stakeholder analysis must be done iteratively, in particular because the joint problem definition and the identification of stakeholders are circularly linked. This means the joint problem definition is influenced by the stakeholders contributing to it, and the way how the problematic situation is defined again influences which stakeholders are affected or can be affected by it. The emphasis on iterative stakeholder analysis is described by scholars from policy (Varvasovszky and Brugha, 2000) environmental sciences (Reed, 2009) and development (Zimmermann and Maennling, 2007).


»Problem definition

»In food and farming systems, those who describe a problem have bearing on what actors are regarded as within the system boundaries, and subsequently which of these actors will be thought to have a legitimate ‘stake’.

»Researchers typically describe a problem from the outset of research (usually during proposal writing); such problems may be deemed relevant in the scientific discourse of the researcher’s discipline or stated as a priority area for interventions in donor policies. However, researchers from other disciplines, as well as non-academic actors working at different scales, may have different perspectives on the same problem or issue. This is why transdisciplinary research strives to address real world problems that are important in the societal discourse, and to take the integration of various perspectives of the problem or issue addressed as a starting point for the research.

»In transdisciplinary research, the joint problem definition is, therefore, established as distinct phase in the research design and includes knowledge integration for problem identification and problem structuring (Hirsch Hadorn et al., 2008). Methods with which to achieve a common understanding of a problem can include creating system maps with stakeholders (Angelstam et al., 2013) and also problem and solution trees (Snowdon et al., 2008).


»Identification of stakeholders from multiple actors

»In transdisciplinary research multiple stakeholders belonging to a diverse set of actor categories need to be integrated, since their different perceptions, knowledge and relationships will contribute to finding solutions to the problem situation (Hirsch Hadorn et al., 2008). In such a situation, it is unlikely that there is one person who can oversee which actors need to be included (Müller et al., 2012). This is an additional reason why “identification of relevant stakeholders is not straightforward” (Cuppen 2009: 33).To overcome this difficulty, a stakeholder analysis can be done by a team because “a team can compensate for and neutralize individual biases and question untested assumptions” (Varvasovszky and Brugha, 2000: 340). In some cases these teams are composed of researchers or other related professionals. An example that initially used experts to generate a list, became participatory because each of the named stakeholders were contacted, “asking them for their opinion and allowing them to add or delete one or more stakeholders” (Stanghellini, 2010: 685).

»To start a participatory identification process, first a group of potential stakeholders can be identified by researchers either from literature, media, explorative research or other sources depending on the context and focus. For example, individuals and organizations active in an area or on a topic might be identified in secondary literature including reports from other organizations. Meetings could then be set up with organizations that might have lists of individuals that are active in the issue or area of focus. Typically, agricultural extension officers and other non-profit staff are approached. However, this might run the risk of reproducing information from the same people who are frequently put forward because they are considered ‘model’ farmers and therefore often called upon to act as representatives.

»Identification can also come from observation in places where people are active, such as in farmers’ markets, auction houses, community meetings and other places. From these observations, researchers can identify some of the people who are active in relation to an issue. Once a few people are interviewed, then a snowball approach can be used to ask for recommendations of other people to approach.

»Participatory stakeholder analysis can include sharing of decision-making regarding identification of actors, determination which of them are stakeholders, and selection of individuals to participate. Participatory actor maps can be used to facilitate identification using Venn diagrams or other communication tools (Lelea et al., 2014).


»Diversity of actors

»The multiple and diverse entry points described above can generate a more complete identification of who has a ‘stake’ and hence should be involved. In some cases, there are many individuals identified which can be grouped to create actor categories (and later stakeholder categories). However, it is more common that researchers or others doing a stakeholder analysis will start with an actor category such as ‘farmers’ or ‘traders’ and look for individuals that belong to this category. This bears the risk that one is not accounting for internal heterogeneity. Forming categories is used to reduce complexity.

»However, the criteria with which grouping is organized will have consequence on who is ultimately involved. For example, to what extent might the category of ‘farmer’ need to be broken down into subcategories to offer the needed diversity of perspectives? Determining the criteria for categorization should become an issue of discussion with stakeholders. Applying methods to critically analyze internal heterogeneity within actor categories lends itself towards crafting greater inclusivity by recognizing important differences. When regarding the social landscape, what is the “difference which makes a difference” (Bateson, 1972: 459) in a given context? Rather than assuming what differences matter based on pre-determined categories, create spaces in which participants can draw their own conclusions about which differences matter most in a particular time and place. As Sara Ahmed has written, we must “trace how the differences that matter between us, matter in some places more than [in] others” (1998: 197).

»Information about actor heterogeneity can be obtained though both individual interviews and group discussions. The transcribed text can later be coded for themes about important differences in the ‘actor landscape’. An important contribution regarding recognition of stakeholder heterogeneity has come from an example with biomass in the Netherlands where Q methodology was applied (Cuppen, 2010).

»In a stakeholder analysis, heterogeneity within a group needs to be acknowledged until the point at which differentiation no longer brings new perspectives. The questions are: To what extent is this heterogeneity important for the objective? What will be the implication of ignoring this aspect? For the sake of stakeholder analysis which enables inclusive innovation processes to move forward, there must be a willingness to reflect on this complexity and to make adjustments as feasible.


»Marginalized groups

»Marginalized groups are often understood as communities in society to whom full access to certain rights, opportunities or resources is systematically denied by members of other groups (e.g. Silver, 1994). In a broader sense, marginalization may also include that the contributions and needs of certain groups in relation to a problem or issue addressed are less visible compared to those of others. In agriculture, this might manifest as invisibility of marginalized groups who perform labor, such as in the case of migrant workers picking strawberries in California (Mitchell, 2003). Inclusion of marginalized groups can be difficult because their identification hinges on the ability of those involved to recognize inter-connections and on their efforts to intentionally seek out marginalized groups (Table1).


»There is convergence among these authors that seeking inclusion of marginalised and hard to reach stakeholders is both necessary and challenging. However, the necessity of including marginalized groups as stakeholders in research projects depends mainly on the project goals. ‘Inclusive innovation’ refers to the development of innovations for and by those who tend to be excluded by the general ‘mainstream’ of business or development initiatives (Heeks et al., 2013).

»These authors identify two key aspects in defining inclusive innovation: (1) A clarification as to which marginalized, excluded group is to be the focus of attention for an innovation; and (2) which aspect of innovation must the excluded group be included in (and in order to achieve what). The second aspect refers to the fact that an inclusive innovation may refer to the marginalized group as being innovator or as being ‘impacted’ by innovation; in other words, an innovation can be inclusive with regard to the process, or the outcomes, or both. Furthermore, the desired outcomes can be defined in many different ways. Inclusive innovation can mean that a marginalized group has participated in a project and benefited from it, for example, with regard to networks, capacity building and new insights. On the other hand, it could also mean that previously existing inequalities have been reduced as a result of the project, e.g. that the income of poor people has increased and inequality has been reduced (Johnson & Anderson, 2012). The latter would require a more systematic way of addressing inequalities beyond just ensuring participation. Richard Heeks and co-authors (2013), therefore, suggest a range of different levels of inclusion, each of which requires different steps to be taken in the course of the innovation process.


»Who represents?

»The concept of ‘representation’ arises because stakeholder categorization is used to create smaller groups for participatory processes. As discussed above, stakeholder categories such as ‘farmer’, ‘trader’, or ‘retailer’ cannot be assumed to have internal homogeneity. Furthermore, such categories do not immediately translate into people to collaborate with in transdisciplinary agricultural research. From operations and systems management, Matthias Müller and co-authors write, “in the context of collaborative research into societal problem situations, this difference [between abstract categories and individuals] is crucial, as the purpose of collaboration is to enlarge the epistemic base by using real persons…to represent the perspectives of abstract categories of actors” (Müller et al, 2012: 496).

»For this reason, we suggest acknowledgement of the implications of individuals’ positionality within the recognized internal heterogeneity of an actor category. As is emphasised in literature on situated knowledge (Haraway, 1988), relevance systems (Schutz and Luckmann, 1973), and emphasised in transdisciplinary approaches (Hirsch Hadorn et al., 2008), all individuals only every have a partial view.»





Innovation Typologies
Thematic Readings

2016/09/20

Nicholas D. Evans (@NicholasDEvans): «The future of innovation management software»



Computerworld (@Computerworld)




«If you're involved in managing innovation for your organization, you're likely working with some form of enterprise innovation management software, or you're in the process of selecting a solution that can best support your needs.

»To help you think about future needs with regard to managing innovation, I have identified five areas where I believe today's innovation management software needs to evolve to support the ever-expanding needs of the business with regard to digital transformation.

»Before we explore how the software needs to evolve, it's worth noting that the first step for any organization is to define a program that addresses the five critical pillars of innovation management capability and then to fine-tune and adjust this program for the needs of digital transformation.

»Clearly, the overall program goals and objectives should drive software decisions and not vice versa. If you're in the process of selecting software, be sure to evaluate according to your overall program needs -- and look well beyond the table stakes of idea management.

»With this in mind, here are the five areas where I believe today's innovation management software needs to evolve over the next few years.


»From incremental, value-chain focus to disruptive, ecosystem focus (strategy)

»Despite all the attention on disruptive innovation, organizations still tend to focus 90% of their efforts on incremental innovation in products and services (i.e., core and adjacent initiatives) and only 10% of their efforts on truly disruptive innovation (i.e., transformational initiatives).

»While innovation management software supports both types of innovation today, it also needs to embrace the more recent changes occurring in platform business models. This is an important shift, with IDC predicting that, by 2018, more than 50% of large enterprises -- and more than 80% of enterprises with advanced digital transformation strategies -- will create and/or partner with industry platforms.

»As companies move toward platform business models as an emerging go-to-market approach, innovation software needs to incorporate new features and functions that will support this ecosystem-centric approach.

»In “Digital business ecosystems and platforms: 5 new rules for innovators,” I highlighted some of the new rules for innovators as organizations move further toward this model as a key part of their corporate strategy. As an example, if you're pursuing an industrial internet model similar to GE's Predix business model, your innovation processes will need to change to support and foster intra-ecosystem innovation for continuous and collaborative innovation with ecosystem partners. You can perhaps think of this as “open innovation” on steroids.


»From 80% “ideate” to 80% “explore and scale” (people)

»When we look at the work effort related to innovation management, we see that an organization today can spend something like 80% of its time on the heavy lifting related to idea management. This involves not just coming up with ideas, but managing them through the innovation pipeline to find the most promising ideas for subsequent execution.

»While ideas themselves are often generated rapidly, it takes considerable time to rationalize the ideas and develop the most promising into a vision board, business model canvas or similar form of initial business case that the organization can then review in more depth and decide how to proceed.

»Today's innovation management software does a good job of supporting idea management, but needs to expand to help companies focus their innovation teams more on deciding “where to play” and “how to scale” their big bets. If we can automate the idea-management function as much as possible -- for example, with intelligent automation to streamline processes and with analytics to aid decision making -- we can help free up resources to spend more time on the critical front-end and back-end components of the innovation life cycle.



»From ideation focus to end-to-end focus (process)

»From a process perspective, innovation management software typically scores well on detailed definition and execution of the process steps underlying idea management. It scores less well in connecting the innovation process to the upstream strategy and downstream execution processes of the typical enterprise.

»If we look at the overall marketplace today, the market for innovation management software is highly fragmented and centered on the “ideate” (i.e., idea management) portion of the innovation life cycle with, for the most part, limited vendor differentiation. In the future, innovation management software needs to provide more connectivity into the adjacent corporate processes of strategy and execution so that strategy can help to guide innovation, innovation can help to inform strategy and innovations can be successfully launched at speed and at scale.


»From tactical enablers to next-generation enablers (technology)

»When we look at the technology enablers used to support innovation processes, there's excellent use of social, mobile, analytics and cloud technologies to support idea management, but this needs to expand to employ the next generation of technology enablers.

»Today, there's plenty of use of social sharing capabilities, mobile application access and as-a-service software. Over the past 10 years, these enablers, while still highly valuable, have become table stakes, and we now need additional enablers which can further automate innovation processes and accelerate decision-making.

»As an example, intelligent automation may be able to improve idea management functions with artificial intelligence-enabled idea consolidation to suggest which ideas might be worthy of combining. Intelligent automation may also be able to support “where to play” decisions in terms of robo-market intelligence software to aid manual market research and emerging technology tracking functions.


»From internal platforms to ecosystem platforms (platform)

»Finally, innovation management software needs to evolve from an internal platform approach to more of an ecosystem platform approach where there's a focus on continuous and collaborative innovation with customers and partners. This ecosystem approach is already available for targeted areas such as matchmaking between seekers and solvers for various innovation challenges, but needs to expand further to address all life-cycle elements from insights to ideas to impact.

»Some of the leading players in the innovation management software arena are already embarking on this journey with a number of new capabilities as well as planned future enhancements in their product road maps. With continuous digital transformation being key to corporate survival, tapping into a new breed of innovation management software will be a valuable way to maximize your chances for success.»





Innovation Typologies
Thematic Readings