Information Technology and
Market Transformation:
A Case Study of the Nigerian Emerging Innovation System
MSc Thesis International Development Studies
Graduate School of Social
carmel.shenkar@student.uva.nl
Information Technology and
Market Transformation:
A Case Study of the Nigerian Emerging Innovation System
MSc Thesis International Development Studies
Graduate School of Social Sciences
University of Amsterdam
December 10, 2016
By Carmel Shenkar
11128321
armel.shenkar@student.uva.nl
Information Technology and
Market Transformation:
1
Abstract
Models of economic development have historically focused on the question on diminishing returns and the change in means and methods of production. Innovation was recognized as the creation of new combinations of these means and methods that chances the norm of the economy. Nowadays, as production becomes less dependent on physical equipment and structures, and more on digital technology; new opportunities emerge for transforming markets. This research combines literature from diffusion of innovation and systems-of-innovation bodies of theory to examine the process of transformation in the Nigerian local market. It takes a different view as it applies innovation-systems analysis to a case of an emerging innovation system. The research is focused on Lagos, Nigeria. The findings and conclusions are drawn from in-depth and semi-structured interviews with local IT entrepreneurs and other stakeholders in the market, and on a survey of the activities of local start-ups. The research ultimately finds that interactions between local start-ups and other actors in the local emerging innovation system emphasize adoptability, scalability and business sustainability as the core principles of the preferences paradigm. These preferences shape the innovation activities of local start-ups and, consequently, affect how technology is used and infused in the local system: (1) local start-ups apply IT to common familiar consumer-market activities (re-inventing product placement in the local market), as they (2) engineer simplified locally-adjusted solutions to address easily-identified basic human and business needs (creating smart and locally-customized user interfaces for the local market), which can then (3) spread throughout the market in slow but continuous incremental growth trajectories (re-inventing business practices in the local market). The findings show that although it is still too early to make predictions, digital technology can potentially transform the Nigerian market. However, at this point the process is solely guided by market forces. Further research on emerging innovation systems and the role and power/influence of each of its players, is now more important than ever. Innovation systems are no longer the exclusive premise of industrialized developed countries. Innovation theory must therefore look beyond the narrow institutional view and adapt to new data and emerging realities.
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Table of Contents
CHAPTER 1: INTRODUCTION --- 3
1.1. Placing innovation in the context of development --- 3
1.2 Research location --- 5
1.3 The research rationale --- 6
1.4 Research structure --- 7
CHAPTER 2: THEORETICAL BACKGROUND AND CONCEPTUAL FRAMEWORK --- 8
2.1 Development and technology adoption: the importance of generating ‘demand’--- 8
2.2 technology infusion: Innovation activities of local start-ups --- 10
2.3 Interaction between Foreign tech firms and local start-ups --- 13
2.4 Interaction between venture capitalists and local start-ups --- 14
2.5 Interaction between leading entrepreneurial players and local start-ups:--- 15
2.6 summary, research question and conceptual scheme --- 17
2.7 Conclusions --- 19 CHAPTER 3: METHODOLOGY --- 20 3.1 Units of Analysis --- 20 3.2 Epistemological Stance --- 20 3.3 Sampling --- 20 3.4 Methods --- 21
3.5 Ethics and Limitations --- 22
3.6 Data Analysis --- 22
3.7 Conclusions --- 23
CHAPTER 4: THE NIGERIAN EMERGING INNOVATION SYSTEM --- 24
4.1 The growing sector of local IT start-ups --- 24
4.2 The challenge for IT: creating a local market --- 25
4.3 creating a market: interaction between actors in the local emerging innovation system --- 26
4.3.1INTERACTION WITH LEADING TELECOMS: THE PURSUIT OF ADOPTABLE SOLUTIONS --- 26
4.3.2INTERACTION WITH VENTURE CAPITALISTS: THE PURSUIT OF SCALABLE SOLUTIONS --- 29
4.3.3INTERACTION WITH ENTREPRENEURIAL PLAYERS: THE PURSUIT OF SUSTAINABLE SOLUTIONS ---- 32
4.4 Conclusions --- 36
CHAPTER 5: TECHNOLOGY INFUSION --- 37
5.1 The domain of technology: marketing innovation activities --- 38
5.2 The type of technological expertise: process innovation activities --- 40
5.3 The spread of technology: organizational innovation activities --- 42
5.4 Conclusions of the chapter --- 44
CHAPTER 6: CONCLUSIONS --- 46
6.1 Summary of key findings --- 46
6.2 the conection between innovation activities and market transformation --- 49
6.3 Policy recommendations and suggestions for further research --- 50
ANNEX 1: OPERATIONALIZATION OF KEY CONCEPTS --- 52
ANNEX 2: LIST OF (NON-ANONYMOUS) INTERVIEWEES --- 53
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Chapter 1: Introduction
Innovation is the successful exploitation of new ideas. This research places innovation in the context of development and examines the role that information and communication technology plays in the process of market transformation. It focuses on Lagos and specifically studies the activities of local IT start-ups in the Nigerian emerging innovation system. The study ultimately suggests that digital technology creates new opportunities that have not been possible in the past. Perhaps it is now time to re-think mainstream innovation theories and development avenues.
1.1. PLACING INNOVATION IN THE CONTEXT OF DEVELOPMENT
Models of economic development have historically focused on questions of diminishing returns and the changing nature of means and methods of production as a way to move forward (Solow 1956; Rostow 1960; Romer 1986; Mankiw, Romer and Weil 1992; Romer 1994; Sachs 2000; Easterly 2001). However, while the process of change in the nature of production was given a name - technological change, it was far more challenging to identify the fundamental input that drives this change (Romer 1994).
Schumpeter separated between the growth of the economy and economic development. He noted that while small changes “in the norm” are simply the adaptation of the economy to continuous incremental changes in data; the transition from one norm of the economic system to another in such a way that represents a break with the common understanding of a predictable and continuous change, signifies a move from growth to development (Schumpeter, Becker and Knudsen 2005). If growth is the increase of population or capital; development is the change of the norm of the economy (Ibid).
Schumpeter identified economic development as a process driven by the carrying out of new combinations of existing goods. In this process part of the goods existing in the static economy are withdrawn from the previous uses they commonly served and transform to be used in a different manner (Schumpeter, Becker and Knudsen 2002). Similarly, Weitzman (1998) suggested an idea-based growth model in which the production of new knowledge is a function of new re-combinations of old knowledge. The rate of expansion of new ideas based on previously untried combinatorics reconfigurations, he noted, is even more powerful than exponential growth, and is in fact only limited by the input of resources needed to process the number of potential new ideas into usable form (Weitzman 1998).
Innovation is the process of reconfiguration of new combinations that makes the previous predictable growth of the economy irrelevant. Digital technology represents such a case. It is not an incremental change that grows the economy; it is the fundamental reconfiguration that changes the norm of the economy and “represents a break with the common understanding of a predictable and continuous change” (Schumpeter, Becker and Knudsen 2005). Brynjolfsson and McAfee (2014) suggested that we have now entered into a time where what has come before is no longer a particularly reliable guide to what will happen next. As the reality of Moore’s Law progresses – as constraints in the digital world become looser and brilliant tinkering constantly finds ways to address the limitations imposed by physics – the resulting exponential growth makes it impossible to predict the implications of the doubling that is still to come, and leaves our intuition and experience behind (Brynjolfsson and McAfee 2014, pp.42-47). A unique role in this process of innovation is reserved to entrepreneurs. If disrupting the equilibrium state of an economy is a necessity for development; entrepreneurs, Schumpeter suggested, are the ones to identify the possible disruptions. He distinguished entrepreneurs from the masses not merely as those with the ability to identify new combinations; but more importantly, as those who act upon them. Even with a
4 wealth of ideas, many people do not act as they do not wish to pay for their ideas with their own economic existence (Schumpeter, Becker and Knudsen 2002, pp. 412-414). Entrepreneurship is associated with high risk; the distinctive factor, therefore, that separates entrepreneurs from the masses, is their willingness to “act” in the face of such risks.
Focusing on the problem of entrepreneurship in the face of high risk, Blank (2013) suggested that the pressures of rapid change and continual disruption make the ‘lean’ model more adequate to meet the challenges of the 21th century. The lean model is essentially a methodology designed to make the process of starting a new business less risky1; and ‘start-ups’ as a form of entrepreneurship are defined in this framework as “temporary organizations designed to search for a repeatable and scalable business models” (Blank 2013). This continuous searching and inventing of new business models, is what ultimately transforms markets. As modern production becomes less dependent on physical equipment and structures, and more on intellectual property, organizational capital, user-generated content, and human capital (Brynjolfsson and McAfee, p. 119); new opportunities for innovating and developing markets emerge. This study aims to explore how innovation in the age of digital technology can address questions of market transformation.
In this research, innovation is seen as a system of structure and process in which innovation emerges from a broad network of dynamically linked actors that operate within a specific institutional context (Foster and Heeks 2013, p. 336). However, in developing countries’ contexts not all building blocks of an innovation system have fully materialized. Particularly, the lack of local knowledge resources and adequate local financing opportunities in the supporting environment force local firms to rely much more on multinational corporations and foreign investors as providers of knowledge and capital. The consequences of the scarcity of good educational and research institutions, is that the quality of local knowledge providers is essentially below what entrepreneurs need in order to become high-end providers of goods and services in the global networks (Chaminade and Van 2008, p. 1688). Chaminade and Vang suggest that innovation systems in developing countries should be examined from an evolutionary perspective: as emerging innovation systems where some of the system’s building blocks are in place but the interaction among their elements is still in formation (Ibid).
This study focuses on local IT ups as innovation intermediaries in the local system. Local IT start-ups are a subsector of the general SMEs sector in Nigeria.2 This research refers to them as knowledge-based SMEs which, presumably, use the ‘lean’ methodology in search of repeatable and scalable business models. However, while they are part of the general SMEs sector; they also have a unique role within the emerging innovation system: they adopt new technologies into their business practices and infuse the
1 The “lean” model is largely based on three key principles: first, the business model canvas; where instead of writing an intricate business plan, founders summarize their hypotheses in a framework that defines how a company creates value for itself and its customers. Second, the customer development; as lean start-ups use a “get out of the building” approach to test their hypotheses and ask potential users, purchasers, and partners for feedback on all elements of the business model (including product features, pricing, distribution channels, and affordable customer acquisition strategies). Third, the agile development; which eliminates wasted time and resources by developing the product iteratively and incrementally (starting with MVPs) in response to customers’ feedback, as opposed to the typical yearlong product development cycles that presuppose knowledge of
customers’ problems and product needs (Blank 2013).
2 Nigerian authorities define SMEs based on a dual criteria of employment and assets (excluding land and buildings): micro enterprises are enterprises whose total assets are less than 5m Naira and their workforce does not exceed 10 employees; small enterprises are enterprises whose total assets are 5-50m Naira and a total workforce of 10-49 employees; and medium enterprises are enterprises with total assets of 50-500m Naira and a workforce of 50-199 employees (SMEDAN and NBS Collaborative Survey 2013).
5 technology throughout the local system via their operations. For purposes of clarity, this research simply labels them as “start-ups”, and uses the term “SMEs” to refer to the more general sector. It should be noted, however, that comprehensive real-time information on the actual proportion of start-ups within the sector of SMEs was unavailable. The research examines the different dynamics that define the interactions between local start-ups and other central actors in the emerging innovation system to show how these dynamics shape the preferences for certain innovation activities over others. These innovation activities, in turn, affect the ways technology is used and infused in the system, and can ultimately generate market transformation.
1.2 RESEARCH LOCATION:
The research takes place in Lagos, Nigeria. Nigeria is Africa’s most populous country and largest economy. However, despite some demonstrated strengths in the past decade, it seems that the country needs to adopt a new growth path. The economy is producing too few jobs. Unemployment rate has increased in recent years and stands at 13% as of 2016Q2.3 The poverty rate has declined only by 2%
between 2009 and 2012; and in some regions, has actually increased by 3.1% (EIU 2015, p. 5). The constant changes in oil prices have further underscored the need for sector diversification (Ibid). Regional disparities pose additional challenge to development, as the national average poverty rate varied from 16% in the Southwest to 50.2% in the Northeast (based on 2012/2013 figures) (Ibid, p. 16). SMEs have been pointed out as a potential driving force in the local economy, as they employ about 84% of the total Nigerian labor force and play a role in export, in local value addition and in technological advancement (SMEDAN and NBS Collaborative Survey 2013). Their ability to succeed is likely to bring a more sustainable growth, job creation and sector diversification.
Yet it seems that SMEs in Nigeria face great challenges. First, SMEs often need to maneuver an environment of inconsistent and unclear government regulations and policies. They are not sufficiently aware of existing government lending schemes or have clear information about funding opportunities and processes; they face complicated and time-consuming tax procedures and multiple taxation; they are overburdened by import regulations and the high costs associated, and their intellectual property is not sufficiently protected (EIU 2015; SMEDAN and NBS Collaborative Survey 2013).
Additionally, SMEs are struggling with poor infrastructure. Constant power shortages and other problems associated with inadequate basic infrastructure, such as access to roads and transportation, impede the successful growth of the sector. Overpopulated road network makes the distribution of goods costly and reduces the productivity of staff spending several hours a day commuting. Chronic power shortages are still a fact of everyday life, as less than half the population has access to electricity and those who can afford it tend to supplement the national grid with their own generators. Any substitute in the form of full solar systems or even small scale renewable solutions are still too expensive to be commonly used (EIU 2015; SMEDAN and NBS Collaborative Survey 2013).
Lastly, SMEs lack sufficient access to finance. They often finance themselves with savings and reinvested profits, or by capital from friends, family, private contacts or the limited available venture capital sources. Banks are somewhat reluctant to finance them. The fact that the majority of SMEs are not formally registered; the slowness of the judicial system, which impedes forecloses and seizing of assets; poor bookkeeping and financial accounting, and the lack of corporate structured management, typically make
6 banks adopt a rather conservative approach to loans (EIU 2015b; SMEDAN and NBS Collaborative Survey 2013).
ICT adoption can contribute greatly to the success and growth of SMEs in the local market. ICT penetration has been increasing rapidly in the past decade, and SMEs are benefiting from the falling costs of ICT, improved communication networks and the rising consumer class. There are about 140m mobile subscribers today and internet penetration is estimated at 50-60% and growing at an annual rate of 35% (EIU 2015, p. 13). Mobile networks make it easier for users to transfer money, pay bills, check and calculate prices, communicate with customers from any location with lower direct marketing costs, and leverage m‑payment technology and shopping apps; thereby easing physical infrastructure related challenges (Ibid). SMEs can now reach consumers more cheaply, moving away from the traditional and more expansive mediums. ICTs are practically creating entirely new markets for SMEs. Lastly, start-ups specifically benefit from fast internet and cloud computing, as it allows them to work remotely, thereby overcoming transport deficits and local skills shortages (Ibid, p. 14).
However, several problems still prevent SMEs from enjoying the full benefits of ICTs. First, network quality is inadequate, and broadband is still quite expensive (broadband penetration is currently estimated at only 4%-6%4). Second, insufficient internet security is a major concern, making cash-on-delivery still
the preferred payment method. The uncertainty of being paid for a product or service, threatens the survival of many small businesses. Finally, ICT infrastructure in rural regions is weaker than in urban areas, thus widening the urban-rural divide and increasing mass immigration to the cities. Challenging physical terrain, a lack of roads, access to power, vandalism and theft, are still a daily challenge for telecom companies (EIU 2015, pp. 15-16).
1.3 THE RESEARCH RATIONALE
ICT adoption is thus an imperative ingredient in Nigerian market transformation. The link between technology and development goes all the way back to the industrial revolution, but the current agenda of ICT for development is often being criticized as too technocratic top-down approach. Some have claimed it creates new forms of dependency, while others have argued against wasting funds on ICTs when other more fundamental needs are still pressing (Kleine & Unwin 2009; Kunst 2015; Foster and Heeks 2014). Interestingly, while common views accept that ICTs can generate employment and revenue in developing countries to some extent, it seems that so far it has rarely been a crucial factor in generating overall economic growth or actually contributed to the emergence of IT industries (Kunst 2015, p. 12).
If ICTs are means of development, then in order to have any practical impact they must not only be delivered, but also disseminated and their content communicated. Theories that explain adoption are therefore relevant. However, while the literature on ICT4D focuses on questions of access, it largely ignores the ‘demand’ part of adoption (Heffernan et al., 2012). This research reflects on how IT is used and infused in the local market. It shifts the focus from the question of access and adds the dimensions of dissemination and communication across the social system. In this way it contributes to the literature by departing from ‘access’ and explaining the creation of local demand.
This process is particularly interesting in the case of Nigeria. Local IT start-ups in Nigeria play a key role in ICTs dissemination and market transformation: they are the driving force of technology adoption. Employing a systems perspective to analyze local innovation and then focus on the choices of individual start-ups, provides a unique opportunity to understand how new technology is infused in the local
7 emerging system and how the market transforms. It is important to note at this point, however, that while this research indeed focuses on local start-ups; it does not aim to examine the effectiveness of the ‘lean’ model per se nor presumes to make any conclusions in this regard. The interest of this research in start-ups is restricted to their role as part of the emerging system that creates market innovation.
1.4 RESEARCH STRUCTURE
The research will proceed as follows: chapter 2 (“Theoretical Background and Conceptual Framework”) outlines the main theories and identifies the factors that form the conceptual framework of the study. Chapter 3 (“Methodology”) briefly presents some methodological issues and explains the choices that were made for this research. Chapter 4 (“The Nigerian Emerging Innovation System”) introduces the Nigerian local market for IT start-ups. It briefly presents the formation of the subsector and discusses some of the unique challenges it faces. It then proceeds to the main actors in the local system and describes their interactions and the resulting paradigm of preferences. Chapter 5 ("Technology Infusion") focuses on the activities of local IT start-ups and reviews how their choices and actions influence the way technology is infused in the local system. Finally, chapter 6 ("Conclusions") concludes with an overview that discusses the findings in light of the general propositions on adoption and development, and presents some policy recommendations and suggestions for further research.
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Chapter 2: Theoretical Background and Conceptual Framework
This chapter presents the theoretical framework of the study. Following the discussion on development and innovation in chapter one, this chapter starts with a review of the question of adoption and technology diffusion in social systems transformation. It sets forth diffusion-of-innovation and systems-of-innovation theories as the building blocks of the study (2.1), and identifies several attributes of innovation activities that affect technology infusion in local systems (2.2). The chapter then proceeds to present the main actors and dynamics of innovation systems in developing countries (2.3, 2.4, 2.5), and concludes with a conceptual scheme and the research questions (2.6).
2.1 DEVELOPMENT AND TECHNOLOGY ADOPTION: THE IMPORTANCE OF GENERATING ‘DEMAND’
The link between technology and development goes back to the industrial revolution: a period of unprecedented and fast technological change which brought improvements in life expectancy and per capita income. However, while common views accept that ICT can create employment opportunities and revenue in developing countries; it is debatable whether it has so far actually generated overall economic growth (Kunst 2015, p. 12). If development is to be achieved, the question should focus on how ICT creates market transformation. For ICTs to generate development, they need to be adopted and diffused in local social systems. Adoption and diffusion depend on questions of access and internet penetration, no doubt. However, access alone is not enough. Adoption and diffusion equally depend on the existence of demand. ‘Demand’ is not the same as 'need'; as ‘needs’ may exist without becoming 'demands' for a solution (Heffernan et al. 2012; Teubal 2002, p. 240). Adoption and successful transformation, however, will not take place where there is no demand.
In order to understand how ICTs transform social systems, then, we need to examine the process of technology infusion. The diffusion of innovation theory addresses the question of infusion from a sociological point of view. It explains technology adoption as closely related to the presence and strength of communication channels between individuals (Heffernan et al 2012). The process of diffusion is described as a process by which the innovation is communicated through certain channels over time among the members of a social system; and the four elements of diffusion are identified as the innovation itself, the communication channels used to diffuse the innovation within the system, the time it takes for the innovation to diffuse throughout the system, and the social system within which the innovation is diffused (Rogers 20155).
Diffusion-of-innovation theory, however, needs some adjustments to fit the context of developing countries. The theory usually refers to five distinct adopter groups existing within each social system (the innovators, early adopters, early majority, late majority, and the laggards), thereby in effect separating the innovators from the early adopters (Rogers 2015, p. 379). By separating these two groups, Rogers detaches those with an interest in new ideas that takes them out of the local circle of peer networks (the former), from those that are well integrated within the local social system (the latter) (Ibid). The former are presumed to be more risk-tolerant and have greater financial resources and complex technical knowledge; while the latter do not posses such capabilities, but hold a stronger position as opinion leaders within the social system and its communication networks (Ibid).
9 This sharp separation between innovators and early adopters is slightly inadequate for developing countries. As the rate of adoption of new ideas often depends on the degree to which they are perceived by the adopters as better and easier to understand and use than the ideas they supersede, easier to test with observable results, yet consistent with existing values, past experiences and adopters’ needs (Ibid, pp. 378-379); the role of local intermediaries (the early adopters, when referring to foreign technology) in developing countries often requires them to become themselves innovators.
In diffusion-of-innovation theory, the early adopters, with their direct linkages within the social system, are perceived only as passive presenters of external innovations. Their contribution to the process of diffusion is reduced to the function of decreasing uncertainties about the new ideas (often by simply adopting them and conveying a reliable evaluation of their quality), while the innovators are those that introduce innovation to the social system (Ibid, p. 379). The theory, thus, does not assign any active role to the early adopters of foreign technology, nor, on the other hand, foresees any direct link between innovators producers of foreign innovations and the local social system. Diffusion-of-innovation, therefore, while clearly addressing questions of generating ‘demand’, should be slightly expanded to take into account the unique nature of innovation in developing countries which essentially creates another group of innovators.
Foster and Heeks (2013) suggest the concept of “innovation intermediaries” for discussing the unique location of this new group of innovators. They note that a large portion of local innovative activity in low-income markets emerges from interactions between users and locally embedded intermediaries in non-traditional places where innovators create adaptive, incremental innovations to bridge an apparent mismatch between externally designed innovations and the particular environment of heterogeneous groups of low-income consumers (Foster and Heeks 2013, p. 337). This location deviates from traditional views of innovation, which typically adopt the Science-Technology-Innovation (STI) mode, and present the process as one based on basic R&D, experimentation (usually in labs), formalization, and codification of identified knowledge (Lundvall et al. 2009, p. 3). This picture however represents only one pillar of the innovation process (Oslo Manual 2005, p. 36). A broader view of innovation, more appropriate for low-income markets, the DUI mode (Doing-Using-Interacting), focuses on interactive learning through structures and relationships, and refers to learning-on-the-job when facing ongoing challenges or when interacting with external customers (Lundvall et all. 2009, p. 3).
The diffusion of new technologies in local social systems, thus, is largely guided by intermediate innovators who are in a better position (location-wise, openness to new ideas and links within the social system) to create innovations that are more likely to be adopted in the social system. They are generally more attentive to local nuances, have direct links to customers and can better respond to on-going challenges. However, if the process of diffusion is driven by local intermediary innovations, the interesting question is how it de facto works.
This question relates to the nature of relationships between different actors involved in the evolution of the local innovation system. Innovation and upgrading to higher value activities require the existence of a facilitating environment that supports interactive learning. Chaminade and Vang (2008) indicate that for SMEs in particular, the interaction best takes place with other firms and organizations co-located in the same geographic region. They note that innovation systems can be reduced to two types of actors and their interactions: the first, companies in the region’s main industrial clusters (including their customers and suppliers), and the second are institutions, agencies and organizations that back up the innovative performance of the first type (such as research and higher education institutions, financial institutions, business associations, vocational training agencies, etc.). Proximity facilitates the circulation of knowledge and information needed for innovation; and well-functioning innovation systems are
10 characterized by the intensity of interactions between the different building blocks (Chaminade and Vang 2008, p. 1686-7).
Systems-of-Innovation (SoI) as a body of theory provides a way to understand innovation as emerging from a network of dynamically linked actors operating within a specific institutional context (Foster and Heeks 2013, p. 336). It shifts the focus toward the interplay of institutions, whereby knowledge and technology are accumulated and developed through the transfer and diffusion of ideas, skills, knowledge, information and signals of many kinds between various actors (Oslo Manual 2005, pp. 32-33). Traditional SoI theories propose that different relationships between government, firms, research institutions, suppliers and consumers, influence the way new technologies are being created and infused throughout the industrial system (Breznitz 2007, p. 25). Individual enterprises are embedded in a set of institutions and non-firm organizations which determines both their behavior and outcome (Teubal 2002, p. 235); and innovation is seen as a path-dependent process in which factors such as market demand and opportunities for commercialization influence which products are developed and which technologies are successful (Oslo Manual 2005, pp. 32-33). Innovation systems in developing countries are usually characterized by weak interactive learning (Chaminade and Vang 2008, p. 1688). However, as firms and other actors accumulate the competences needed to engage in different forms of interactive learning, the system gradually evolves from an emerging to mature innovation system in which firms are engaged in continuous interactive learning with other firms, users, universities and other organizations (Ibid, p. 1689).
2.2 TECHNOLOGY INFUSION: INNOVATION ACTIVITIES OF LOCAL START-UPS
SoI theory presupposes that each innovation system adopts a specific paradigm that outlines its preferences for certain innovation activities over others (Breznitz 2007, p. 26). Innovation is the implementation of a new or significantly improved product (good or service), process, marketing method, or an organizational method in business practices, workplace organization or external relations; and it can be new either to the firm (at the very minimum), the market or the world (Oslo Manual 2005, p. 46). While traditional innovation theories are focused on basic R&D, it is important to note that innovation can include both R&D and non-R&D activities,6 and that the scope of actual R&D activities differs not
only by regions, but also by sectors (Ibid, p. 37).7
The Oslo Manual of 2005 identifies four types of innovations. Product (goods and services) innovations are the introduction of a good or service that is new or significantly improved with respect to its characteristics or intended uses. This includes significant improvements in technical specifications, components and materials, incorporated software, user friendliness or other functional characteristics (Ibid, p. 48). Process innovations are the implementation of a new or significantly improved production or delivery method. They include significant changes in techniques, equipment and/or software. Process
6 R&D activities usually point to basic research to acquire new knowledge for the creation of new inventions or the modification of existing techniques. Non-R&D activities are all activities aimed at implementing innovations that do not include R&D, for example identifying new concepts for products or processes; buying technical information and modifying the invention to the firm’s own needs; investing in intermediate inputs that embody the innovative work of others; reorganizing management systems; developing new methods for marketing, etc. (Oslo Manual 2005, p. 36).
7 While in high-tech sectors R&D plays a central role, other sectors typically rely on adoption of knowledge and technology. In low- and medium-tech sectors, innovations are generally more incremental, yet the process is often more complex than just a simple adoption of new technologies and in many cases involves the incorporation of high-tech products (Oslo Manual 2005, pp. 37-38).
11 innovations can be intended to decrease unit costs of production or delivery, to increase quality, or to produce or deliver new or significantly improved products (Ibid, p. 49).8
Marketing innovations are the implementation of a new marketing method involving significant changes in product design or packaging, product placement, product promotion or pricing, that are aimed at better addressing customer needs, opening up new markets, or newly positioning a firm’s product on the market, with the objective of increasing the firm’s sales (Ibid, pp. 49-50).9 Finally, organizational innovations are the implementation of a new organizational method in the firm’s business practices, workplace organization or external relations. They can be intended to increase a firm’s performance by reducing administrative costs or transaction costs, improving workplace satisfaction (and thus labor productivity), gaining access to non-tradable assets (such as non-codified external knowledge) or reducing costs of supplies (Ibid, p. 51).10
When firms innovate (in any of these four forms), they do so for a number of possible reasons. Their attempts to innovate may or may not succeed in achieving the intended objectives, and the attempts can sometimes result in completely different effects than the ones they intended (Ibid, p. 107).11 The Oslo
Manual highlights several factors as the objectives of firms to innovate, among them factors relating to competition, demand and market, such as short product life spans that necessitate the development of new products, the need to diversify product portfolio, or efforts to increase or avoid a decline in market share; factors relating to changes in production and delivery, whether they aim to improve quality, flexibility, or efficiency/cost reduction; and/or factors relating to workplace organization, whether they are aimed at customer relations, operational efficiency, or improving the capture and sharing of knowledge (Ibid, pp. 107).12
Objectives factors, the reasons why firms innovate, determine where they focus their innovation efforts. The definitions introduced by the Oslo Manual refer to specific activities of individual firms. In this research, however, these definitions will be used to describe the operations of the market in more general terms, as the aggregated activities of local start-ups. Chapter 5 uses the definitions of the Oslo Manual to explain the reconfiguration of means and methods of production that re-invent the operation of the local market: whether the activities of local start-ups create new products, new processes, new marketing methods or new organizational methods.
Innovations of various kinds require various types of technological expertise. The type of technological expertise available to start-ups determines what kind of needs they can address. Human needs are
8 Distinguishing between product and process innovations with respect to goods is easier. The difference between the two with respect to services is less clear, but process innovations generally involve new methods, equipment or skills to perform the service, and product innovations refer to new characteristics of the actual service offered (Oslo Manual 2005, p. 53).
9 Market innovations differ from process innovations, as the latter involve production and delivery methods aimed at decreasing unit costs or increasing product quality, while the former aim to increase sales volumes or market share through changes in product positioning or reputation (Oslo Manual 2005, p. 55).
10 Although both organizational innovations and process innovations aim to decrease costs through more efficient concepts of production and internal organization; process innovations deal mainly with implementing new equipment, software and specific techniques or procedures, and organizational innovations deal primarily with people and the organization of work (Oslo Manual 2005, p. 55).
11 While questions on both motives and effects provide valuable information on firms’ innovation activities, this research is focused on the motives.
12 The Oslo Manual provides a table listing specific factors relating to each category of objectives (Oslo Manual 2015, p. 108).
12 anything that human beings perceive as valuable. They rarely require technical breakthroughs, and solid engineering expertise is usually sufficient. Products aiming to address human needs do not require any particular domain expertise, and the common method of reaching appropriate solutions to human needs is by measuring the market response to the product. Business needs are anything that helps a business perform better in some sense, and usually they too do not require any technical breakthrough. But unlike human needs, a domain expert – a person who knows the industry well – is very well required here in order to provide appropriate solutions. A technical need is the need for some system or component to perform better. It can ultimately serve business or human needs, but its characteristics are different. Technical needs necessitate solutions of two separate categories: a technical solution that provides a capability that did not exist before; or a technical solution that provides a superior version of a product for which there is already an established market.13 The type of need and available technological expertise are
therefore inherently intertwined.
The four types are summarized in the following:
Table 1: The connection between types of needs and technological expertise
Type of need Key questions Lead person Technical
breakthrough human Is this a real need? Is the solution
solving the need?
None Not needed
business Is this a real need? Is the solution solving the need?
Business expert Not needed
Technical need in established markets
Can it be done? Scientist/inventor required
Technical need in new market
Can it be done? What will it be used for? Scientist/inventor, entrepreneurs, business expert required Source: http://readwrite.com/2015/12/01/4-types-of-startups/
Lastly, start-ups adopt certain business models that can generally be divided based on their potential market size and growth rates. High growth businesses typically feature novel technologies or business models that result in fast adoption. They focus on extreme scalability and they require very quick execution time. They thus depend on large sums of venture capital to fund rapid expansion. Whether externally or self-funded, high-growth start-ups are not designed to merely earn a living for their founders. Rather, in such businesses the founders usually want to create a significant equity position in a company that will eventually become publicly traded or get acquired.14 On the other hand, most
entrepreneurs are involved in what is typically described as traditional small businesses. This category refers to businesses that usually show a stable but slow growth profile. Most small businesses are not designed for extreme scale, as the founders often want to own their business and support their family. They are not excessively profitable, and their available capital source is most often savings and whatever
13 For further explanation, see: http://readwrite.com/2015/12/01/4-types-of-startups/
14 Self-funded high growth businesses aim for the same goal, but they do not dependent on external financing to get launched as the entrepreneur is able to launch with their own funds. They may seek external funding later on.
13 the founders can loan from their relatives and banks.15 The growth model ultimately determines the rate
and pattern of expansion and spread of an innovation.
Examining the objectives of start-ups to innovate, the needs they address and the growth model they typically adopt, facilitate better identifying how local start-ups use and infuse technology into the system: the business domains to which technology is applied, the type of technological expertise most prominent locally, and the way that technology spreads throughout the system. Assuming that preferences for certain innovation activities over others are linked to the dynamics and relationships between different actors, the next question should be how these interactions create the system’s preference paradigm.
2.3 INTERACTION BETWEEN FOREIGN TECH FIRMS AND LOCAL START-UPS
Multinational corporations (MNCs) are important actors in national innovation systems. Their activities transcend national boundaries and their R&D labs develop products on the technological cutting edge. The diffusion of their technologies and knowledge of the global market into local industrial systems can enrich the local industry in the host country with the capabilities needed for innovative products (Oslo Manual 2005, p. 39; Breznitz 2007, pp. 27-28). However, there is a range of activities that MNCs can operate in host countries, not all involve cutting edge technology. Host-country-related factors such as the level of development, size and growth of the domestic market, local amount of R&D, the extent of human capital development, and the cost of labor can explain differences in subsidiaries’ activities (Marin and Arza 2009, pp. 299-300). Corporate-related factors, such as corporate inertia that favors traditional R&D locations, for example, were found to determine subsidiaries’ activities as well (Cohen et al. 2009, p. 62). In addition to the type of activities MNCs choose to operate in a specific host country, there is a range of other possibilities for them to interact with the local tech community. Foster and Heeks (2014) identify two types of relationships between foreign producers and local users in low income markets: the market interaction, where highly intermediated networks serve as diffusion channels for lead producers; and the hierarchical interaction, where the relations are clearly defined by technical and managerial regulation of activities (Foster and Heeks 2014, p. 232). They note that while market interaction type of relations may limit potential knowledge flows; the formal and deliberate transfer of knowledge in hierarchical interaction can become too restrictive and lead to one-way top-down flows, thereby practically limiting the ability of local innovators to adequately adjust to local needs (Ibid, pp. 232-233).
Due to the highly asymmetric relations between MNCs and SMEs, both in terms of power and knowledge and in terms of incentives to collaborate (Chaminade and Vang 2008, p. 1688), MNCs’ activities in developing countries influence the opportunities open for local IT start-ups. The interaction can either generate technology-upgrading in the system and link local start-ups to foreign markets (through reverse knowledge flows, for example), or it can confine their opportunities by incentivizing products and business models that effectively limit the exposure of local start-ups in foreign markets.
Innovative-entrepreneurial subsidiaries, for example, can generate technology upgrading for the entire national system. As local start-ups often rely on MNCs as providers of knowledge and opportunity; subsidiaries in a particular host country are in a position to shape the growth model of local start-ups. For SMEs to develop high-end activities they need to continuously engage in learning with end-users, and to develop advanced technical capabilities and deep understanding of the business process of the client market (Chaminade and Vang 2008, p. 1691). Innovative subsidiaries that manage to achieve
15 For further explanation of different types of growth models see:
14 technological upgrading can re-focus on foreign markets and trade with other countries as well; thereby linking the local system with the global market (Marin and Arza 2009, p. 302; Breznitz 2007).
Chaminade and Vang (2008), however, demonstrate an opposite example. They found that only a small group of local firms in Bangalore has actually benefited from the interaction with MNCs: the growth model that most local SMEs have adopted in this case (i.e. export- and MNC-driven services) led to a fragmented industry with weak local linkages, in which most SMEs provided only standardized services with very low incentives for MNCs to create long-term arrangements (Chaminade and Vang 2008, p. 1691). Other examples show that the size of the local market plays a role as well; where in big countries, even the most innovative subsidiaries will tend to target the local market, as there is a bigger market to serve locally (Marin and Arza 2009, p. 302).
Marin and Arza suggest that the level of innovativeness adopted by individual subsidiaries differs depending on two factors: its interconnectedness to its own MNC or other international sources of knowledge, and on its local initiative and entrepreneurial attitude. Specifically they note that the more discretion the subsidiary has from its corporation to invest in technology and the more entrepreneurial it is, the more likely it is for the subsidiary to take initiative in developing new technological assets and encouraging local linkages. Subsidiaries that are mainly driven by decisions of their parent companies, on the other hand, are less likely to invest in technology in their host country (Marin and Arza 2009, pp. 291-293). The level of control, therefore, seems to play a crucial role.
The dynamics between MNCs and the local tech community therefore shape the customer-focus and growth models of local start-ups. MNCs in local innovation systems in developing countries, then, should not be seen solely as sources for knowledge and technology transfer. Their interaction with local start-ups clearly influences opportunities as well. These opportunities shape and determine the preferences paradigm of the local emerging innovation system.
2.4 INTERACTION BETWEEN VENTURE CAPITALISTS AND LOCAL START-UPS
Innovative entrepreneurship is not just a question of setting up a new business. It is setting up a new business in a way that introduces a new product, a new process, or a new market or organizational system for existing products and processes. Investors, which infuse the start-up with the necessary capital, become crucial actors. By supporting local start-ups, they in effect support the evolution of local innovation systems. The question is whether they also influence local preferences. Mazzucato points out that innovative entrepreneurship involves high levels of uncertainty, and profit maximizing investors will tend to invest in activities that have greater and more immediate returns (Mazzucato 2011, 134-135). SoI tradition suggests that the identities and preferences of financiers, particularly their origin and the financial gains they are looking for, shape the preferences of certain research and development activities in national innovation systems (Breznitz 2007).
Kohler and Baumann (2016) identify four dimensions on a market-hierarchical spectrum that classify different types of relations between ‘parent’ incubators and their incubated start-ups. These different types are based on the existing level of control in the ‘supporting-supported’ relationship. First, the ownership structure, ranging from programs where parent companies only take service fees from incubated start-ups, to those taking equity and, in the extreme venture-building version, programs in which the parent company holds control equity. Second, the adaptation mechanisms, ranging from programs where start-up founders make all decisions (throughout both the early- and growth-stage) independently, to centrally-controlled models where top management makes decisions for all supported start-ups. Third, the incentives regimes, ranging from full market-participation of start-up founders bearing all risks and
15 enjoying rewards, to models predominantly characterized by employee-superior relations where start-up founders receive salaries and are subjected to administrative control by the parent company. Lastly, the time horizons, ranging from models based on contractual well-defined fixed-term relations, to those featuring long-term employment-type contractual interactions (Kohler and Baumann 2016, pp. 6-8). While Kohler and Baumann discuss incubation programs specifically, the classification they present describes general power relations that characterize all relations between investors and their supported start-ups. The power relations spectrum ranges from investment models which are fundamentally independent and founder-run, all the way to the extreme hierarchical-type model: the factory-like venture-building company. Kohler and Baumann suggest that the extreme venture-venture-building company is more valuable in domains where execution matters more than creativity (Kohler and Baumann 2016, p. 24). By leveraging existing knowledge and know-how (mostly through centralized resource matching that alleviates early-stage distractions and management-orchestrated knowledge sharing among portfolio start-ups), this model is able to speed-up the process of venture building (Ibid, pp. 21-25). They propose that this model is more likely to attract risk-averse individuals who perform well within authority-based systems; while it will be less appealing to entrepreneurs with a drive for autonomy (Ibid, pp. 21-22). The centrally-controlled (hierarchical type) models appear to have blurred the boundaries between the traditional role of ‘investors’ and that of ‘MNCs’ in national innovation systems. In the venture-building model, the investor no longer invests in independent start-ups, but rather creates companies of its own. This type of interaction seems more like the type of relations between MNCs and their subsidiaries than the traditional relations of investors and portfolio companies. Relying on Foster and Heeks’ line of argumentation linking market v. hierarchical interaction to specific learning-patterns outcomes (Foster and Heeks 2014, pp. 232-233), it is here assumed that, on the one hand, centrally-controlled investment relationships (i.e. hierarchical interaction) facilitate greater knowledge transfer but are less flexible to local adaptations; and on the other hand, the founder-run investment model (i.e. market interaction) is less contributive to knowledge sharing but more open to bottom-up independent ideas.
Hierarchical centrally-controlled investment models better leverage existing knowledge and know-how, speed-up venture-building and reduce risks; but offer relatively low levels of entrepreneurial freedom and will probably lead to execution-driven type of activities. Market independent founder-fun models will allow more bottom-up entrepreneurial independence, but will face greater early-stage predicaments and will depend on experimentation. Developing markets pose higher risks for investors. It is therefore assumed that the greater the risk investors perceive the higher levels of control they will seek to retain over their supported start-ups. Higher levels of control translate to preferences for proven business models and an emphasis on execution and market performance innovation activities.
2.5 INTERACTION BETWEEN LEADING ENTREPRENEURIAL PLAYERS AND LOCAL START-UPS:
The mismatch between externally designed innovations and the particular environment of heterogeneous groups of low-income consumers (Foster and Heeks 2013, p. 337) opens opportunities for local start-ups in developing countries to create indigenous innovations. These opportunities outline their unique spaces for innovation. However, local technology-driven start-ups have to rely on themselves for building up stocks of technological knowledge (Global Innovation Index 2015, p. 84). SMEs depend on personal ways of transferring information more than they rely on the more codified modes of knowledge acquisition (Chaminade and Vang 2008, p. 1686). Therefore, the knowledge base and preferences of local
16 start-ups are shaped, to a large extent, by interactive learning with other like-minded start-ups and co-located entrepreneurial leading players.
Cohen and Levinthal (1990) propose that the capacity of a group to absorb external information (“absorptive capacity”) depends both on the expertise of its gatekeepers who monitor the environment and can translate the external information into understandable terms for the inside group, and the expertise of the members of the group who receive the information from the gatekeepers (Cohen and Levinthal 1990, pp. 132-133). Moreover, they suggest that a certain common ground of knowledge is essential to the ease of information flowing within a group of individuals with diverse expertise, as it increases the ability of the group as a whole to innovate (Ibid).
Thus, in order to innovate, a group needs to absorb information from different external sources and translate it to some common understanding, which can then be used in a range of expertise areas. However, as prior related knowledge of the group presumably affects its ability to recognize the value of new information (Cohen and Levinthal 1990, pp. 128-130); the past experiences of a group with external information sources, and the translating and framing thereof, necessarily shape the absorption and framing of new information as well. External sources of knowledge are not limited only to deliberate forms of technology transfers. They often include other channels as well, such as the movement of highly-skilled staff from MNCs subsidiaries into local firms; demonstration effects, where domestic firms observe and imitate the technology coming from subsidiaries; competition effects between companies, etc. (Marin and Arza 2009, p. 287).
Fressoli et al. (2014) suggest that when grassroots innovators interact with traditional innovation institutions, they can fit into existing spaces of innovation and adapt to the rules of dominant institutions, or they can resist the dominant regimes and try to transform the spaces (Fressoli et al. 2014, p. 281). However, Fressoli et al. note, the reaction to existing spaces of innovation is determined by the interpretation and framing of previous experiences (Ibid, pp. 287-288). It is important thus to examine how past experiences are framed within a group and how new information is absorbed and translated, in order to examine the orientation of knowledge creation within the group of innovators.
A special role is assigned to local leading firms, especially the ‘first winners’. The interaction between leading local firms and other local start-ups within the national innovation system is important for the evolution of the system. Most notably, leading local firms with global outreach can create linkages between other local firms and the global market or foreign investors (Breznitz 2007). However, their influence seems to depend on the type of interaction between the leading firm and the local system. Bernard et al. (2009) found that while in some cases the successful firm is in productive dialogue with a range of other actors in the national innovation system and takes on a leading role in the evolution of the system (the co-evolution model); in other cases, the firm is operating separately in parallel to the national system, and either disengages completely from the local context (the global enclave model), or develops its own resources locally within a single corporate entity (the internalization with a firm-level focus model) (Bernard et al. 2009, pp. 252-255). The interaction between leading local “first winners” and other local start-ups within the national system is thus more important for the evolution of the system than the success of the individual firm in the global market.
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2.6 SUMMARY, RESEARCH QUESTION AND CONCEPTUAL ACHEME
The theoretical framework is summarized in the following: Table 2: Theoretical framework summary
Preference paradigm Aspect of
innovation systems
Factor to be examined Possible outcomes Implications for creating preferences Interaction
between foreign tech firms and local start-ups
Type of interaction: market interaction vs. hierarchical interaction
Indirect knowledge flows, but more local flexibility (market interactions) vs. direct and deliberate knowledge transfer, but less local flexibility (hierarchical interactions)
What are the guiding principles that set preferences for certain innovation activities over others Interaction between venture capitalists and local start-ups
Type of investment model: from founder-run to centrally-controlled
no/indirect knowledge flows and more reliance on market experimentation, but greater local entrepreneurial freedom (founder-run models) vs. direct top-down knowledge flows and resources to reduce early-stage risks, but low levels of local entrepreneurial independence (centrally-controlled models)
Interaction between leading entrepreneurial players and local start-ups
Interactive learning: the leading “gatekeepers” and interpretation of external information
Knowledge creation depends on the expertise and experience of local gate-keeping agents and nodes
Technology infusion: Aspect of
technology infusion
Factor to be examined Possible outcomes Implications for how technology is infused Technology
domain
Type of activities where technology is inserted into the local market
Innovating activities for reasons related to competition, demand and market vs. for reasons related to production and delivery vs. for reasons related to workplace organization Technology is infused through product / process / marketing / organizational innovation of Technological expertise Technical manipulation required in order to
Technological and scientific
18 create products that will
infuse technology into the local market
the local market
Pattern of spread How technology is spread through the local market
Type of growth model (high growth big market size v. moderate growth limited market size)
This study aims to identify how the dynamics and relationships between different actors in the local innovation system influence the ways technology is infused. The main question of the research therefore is how does the preference paradigm of the Nigerian innovation system influence the way new technology is infused in the local market?
As SoI theory presupposes that each innovation system adopts a certain paradigm that creates preferences for certain innovation activities over others, and the preferences are directly linked to the nature of interactions between different actors in the local system, the research question is separated into three sub-questions based on key actors in the system:
I. How do interactions between foreign tech firms and local start-ups influence innovation activities in the local market?
II. How do interactions between venture capitalists and local start-ups influence innovations activities in the local market?
III. How do interactions between leading entrepreneurial players and local start-ups influence innovation activities in the local market?
Main hypothesis of the research: system-level interactions between foreign tech firms and local start-ups, venture capitalists and local start-ups and leading entrepreneurial players and local start-start-ups, emphasize specific principles that create preferences for certain local innovation activities. These principles affect the choices local start-ups make along three lines: the reasons why to innovate, the type of needs to address and the growth models to adopt. These choices guide the type of innovation activities they focus on, and in turn, outline how technology is used and infused in the local system.
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2.7 CONCLUSIONS
This chapter has provided the theoretical and conceptual framework of the study. It highlighted the importance of ‘demand’ for technology adoption and diffusion, and thus for market transformation and development. It then presented the diffusion-of-innovation and systems-of-innovation theories as the underlying frameworks for examining the process of technology infusion in local social systems, and identified the main dynamics and relationships at play in the context of developing countries. Lastly, it presented the research question and sub-questions of the study and outlined its main hypothesis. The next chapter will discuss the methodological issues.
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Chapter 3: Methodology
This chapter discusses the main methodological issues. It presents the central unit of analysis of the research, its epistemological stance, the choices for sampling, the different methods used, the main points concerning ethics and limitations, and briefly explains the methods used for data analysis. A table for operationalization of key concepts is added in Annex 1.
3.1 UNITS OF ANALYSIS
The research takes individual IT start-ups as the set unit of analysis. It specifically examines their products, business models, value propositions, growth models, and their interaction with other actors in the local innovation system.
3.2 EPISTEMOLOGICAL STANCE
This study assumes that there is one reality of dynamics that exist between different actors in innovation systems and those dynamics shape the way technology is infused. However, these dynamics can only be apprehended imperfectly (thus, a post-positivist perspective). The research aims to develop better understanding of such connections between system-level dynamics and technology adoption. In line with post-positivism, this study is based on several suppositions which have so far persisted and are therefore taken as probable facts, unless proven otherwise (Guba and Lincoln 1994). It accepts certain 'truths', as presented in the relevant literature, specifically about the kind of factors that guide economic behavior and preferences (for example, the most profitable business activities will be preferable over less profitable ones).
However, as a mixed-methods research, this study also draws on the ideas of pragmatism and “what works”. Accepting the existence of both objective and subjective knowledge (Cresswell and Clark 2011, p. 43), the research attempts not only to identify system-level dynamics and their influence; but also searches for the unique perspective of local IT start-ups on the matter, particularly how they interpret their role in the process. Additionally, borrowing from critical realism theories, this study acknowledges that social sciences are not ‘‘value-neutral", but rather they presuppose a commitment to human well-being (Gorski 2013, p. 669). Thus, while it does not presume to know the future, this study nevertheless provides some prudential suggestions for policy decisions.
3.3 SAMPLING
Two different types of groups have been approached in this research. The first group comprised of founders of local IT start-ups. Probabilistic sampling proved to be more difficult than initially expected; therefore non-probabilistic sampling was ultimately chosen for two reasons: first, this research examines only very specific cases representing certain characteristics which are disproportionate in relation to the larger population (Cresswell and Clark 2011, pp. 174-175); i.e. local founders of IT start-ups, as oppose to local founders of general SMEs which are more common in the larger population. Second, non-probabilistic sampling became unavoidable as I was only able to select individuals who were available and willing to participate.
The second group comprised of various individuals holding key positions in the local system. This group includes main influencers in the local system, VCs, representatives from subsidiaries of foreign firms,
21 individuals from academia and market research companies, government officials, new media influencers, etc. This group was approached for the purpose of conducting a qualitative analysis of the local innovation system, and thus individuals were chosen on the basis of purposeful sampling; i.e. those who have experienced the phenomenon or the key concept being explored in the study (Cresswell and Clark 2011, p. 173). The purpose was not to generalize from their experience, but rather to develop an in-depth understanding of the development of, and dynamics within, the local system. Maximal variation strategy was chosen is selecting these individuals, presuming that diversity of positions and experiences will generate different perspectives on the central phenomenon and reflect all the complexities involved (Cresswell and Clark 2011, p. 174). Finally, some individuals were approached as the study progressed, in order to shed light on particular points that emerged during the initial stage of data collection (Cresswell and Clark 2011, p. 174).
3.4 METHODS
Semi-structured in-depth interviews:
33 in-depth interviews have been conducted over a period of five months (April-August 2016).16
I. Interviews with IT start-up founders: 14 semi-constructed interviews (over a period of two months: mid-April to mid-June). The interviews were constructed around several main topics (entrepreneur’s background, motives for starting the business, business model and value proposition, funding the business, and main challenges); but were open enough to allow the interview to proceed in any direction which the entrepreneur chose to take it (stressing particular aspects which they found to be more significant than others). As some of these entrepreneurs have later also responded to the survey, the interviews were not counted for the analysis of the survey.
II. Context-related interviews: 19 in-depth interviews (over a period of 5 months: April-August 2016) with actors holding key positions within the local innovation system. The positions they hold allow them to provide a “bird-overview” over the history and evolution of the system as well as the current state of affairs. As some of these individuals are entrepreneurs themselves, they were additionally asked about their personal experiences as founders of local start-ups.
Survey:
An online survey has been conducted (July-August) among local IT entrepreneurs following, and based on impressions from, the field-research. The link was sent to a few local contacts which then sent it to their network of start-up founders. The purpose of the survey was to collect information on general topics: entrepreneurs’ backgrounds, kinds of businesses and value propositions, forms of collaboration and exchange of information between start-ups, motivations to innovate, hindering factors to innovation, sources of technology component and technology-related knowledge, means of funding the business, sources of business development-related knowledge and plans for scaling; in order to corroborate, refute and/or explore further possible directions. The survey was built with close-ended and open-ended questions. Overall, 31 entrepreneurs responded to the survey, representing different business-area application of information technology.
