THE LESSON LEARNT FROM Childers. 1986. Assessment of the psychometric properties of an opinion leadership scale

In this paper, the author revised the King and Summers' (1970) scale for opinion leadership. As many researchers have found, they argued that the opinion leaders were more likely to be product innovators and high in consumer creativity; were more likely to be risk preference and non-dogmatism; and were full of personal knowledge in certain products.
However, by using the KS scale (7-point response), each Alpha of the opinion leaders' personality was low (about 0.66). By using the same scale, the author could barely get high correlation between the result of KS scale and that which again got from KS scale. Thus, the validity of KS scale was doubted.
To improve this point, they utilized a 5-point scale and modified some KS scales (under the item-to-total correlation, they deleted the inappropriate items), in Table 2. In the end, the Alpha increased and the correlation between opinion leadership with creativity and ownership of the product was confirmed.
Also, to test the validity of the revised scale, different users of cable television (different in their degree of adoption of cable TV services) were analyzed. And, they found that, under Turkey HSD test of means, the average opinion leadership scores for premium subscribers and basic-only subscribers were significantly greater than the score for the group that had refused to subscribe to cable TV. Thus, the people who are familiar to TV services will found high in opinion leadership.

THE LESSON LEARNT FROM Chan & Misra. 1990. Characteristics of the opinion leader: A new dimension

In this paper, the authors analyzed the characteristics of opinion leaders (or givers). Historically, the opinion leaders were considered as important part in new-product adoption and diffusion, and venture business. In their personality, they tend to be less dogmatic, more innovative, more venturesome, likely to be confident in their appraisal of the product category, and more socially active. By analyzing 262 students and using Stepwise discriminant analysis, they found that contrary to previous findings, risk preference, dogmatism, and exposure to print media were not found to be significant discriminating characteristics of opinion leaders. But the product familiarity, personal involvement, and public individuation were significant in distinguishing opinion leaders from nonleaders (p. 57). The relationship between public individuation and opinion leadership is reasonable (p. 54).

THE LESSON LEARNT FROM Elfring & Hulsink, 2003. Networks in entrepreneurship: The case of high-technology firms

In this paper, the authors, using the theory of contingency, argued how strong and weak ties influenced the performance of high-tech start-ups in releasing incremental and radical innovations. They demonstrated that although strong and weak ties are both beneficial to venture businesses in terms of opportunity recognition, resource assembling, and legitimacy; their value is different when facing with different innovation types.
Thus, they proposed that a mix of strong and weal ties are crucial to the high-tech start-ups.
Towards discovery of opportunity, they demonstrated that networks could provide not only source of information bur help entrepreneurs evaluate the opportunities and potential markets. Here, the weak ties could provide more new and broad information whereas strong ties could be of importance of helping evaluating opportunities in greater detail.
Towards securing resources, strong ties provided privileged rights to help gather venture capital and work-forces. Also at the circumstance of legitimacy, the strong ties contributed in convincing potential market and existing industry to believe the innovative products.
In the end, the authors proposed that

1. For pursuing incremental innovations, weak ties are more likely to discover opportunities.
2. For pursuing radical innovations, the mix of strong and weak ties are more likely to discover opportunities.
3. Strong ties enable trusted feedback and exchange of tacit knowledge on the nature of the opportunity.
4. For pursuing incremental and radical innovations, strong ties are more likely to help secure resources.
5. Strong ties enable the exchange of tacit knowledge in the development of resources.
6. For pursuing incremental innovations, strong ties help ventures gain more legitimacy.
7. For pursuing radical innovations, the mix of strong and weak ties are more likely to gain legitimacy (cognitive ones and socio-political ones).
8. Weak ties are more important for radical innovations, as endorsement by outsiders is important in gaining legitimacy.

THE LESSON LEARNT FROM Freeman, L. 1978. Centrality in social networks: Conceptual clarification

First introduced by Bavelas in 1948, the idea of centrality in human community has been recognized. The centrality was related to group efficiency in problem solving, perception of leadership, and the personal satisfaction of participants. And, before arguing centrality, the graph-theory is necessary, where the words: "adjacent, degree of point, path, cycle, connected, distance, geodesics" have their unique meaning. 

In the terms of point centrality, "a point that falls on the communication paths between other points exhibits a potential for control of their communication." And, a central position is one that is not dependent upon others as intermediaries or relayers of messages. Short distances mean fewer message transmissions, shorter times, and lower costs. Especially, concern with communication activity will suggest a degree-based measure, interest in control of communication requires a measure-based upon betweenness; and concern with either independence or efficiency leads to the choice of a measure based upon closeness. 

The LESSON LEARNT FROM Borgatti, S. 1995. Centrality and AIDS

"Centrality measures are commonly described as indices of prestige, prominence, importance, and power - the four Ps." There are usually four measures, which were developed by Freeman (1979) and Bonacich (1972), being used in network analysis: degree, closeness, betweenness, and eigenvector centrality. "Degree centrality may be defined as the number of ties that a given node has." When all else is equal, we could describe degree centrality as measuring the risk (or opportunity) of receiving whatever is flowing through the network. Furthermore, in eigenvector centrality, it was demonstrated that "it wasn't just how many people a person knew that counted, but how many people the people that they knew knew." That's to say, an actor that is connected to many actors who are themselves well-connected is assigned a high score, but an actor who is connected only to near isolates is not. "Closeness centrality may be defined as the total graph-theoretic distance of a given node from all other nodes." "Betweenness centrality is defined as the number of times that a node needs a given node to reach another node." Thus, also according to Granovetter's (1973) definition, actors with many weak ties are more important than others because removing those actors would do the most damage to transmission possibilities throughout the network.

THE LESSON LEARNT FROM Shane. 2000. Prior knowledge and the discovery of entrepreneurial opportunities

Here, the author followed the logic that entrepreneurial opportunity discovery is a function of the distribution of information in society. For the information asymmetry and different experience, people usually discover different opportunities in a given technological change.

Thus, through investigating eight different new venture businesses based on the invention of 3DP, the author showed that " (1) any given technological change will generate a range of entrepreneurial opportunities that are not obvious to all potential entrepreneurs;" (2) entrepreneurs can and will discover these opportunities without searching for them; and (3) any given entrepreneur will discover only those opportunities related to his or her prior knowledge (p. 449).

Different from Neoclassical equilibrium theories and Psychological theories of entrepreneurship where the fundamental attributes of people were considered to determine who becomes an entrepreneur, Austrian theories which the author clearly followed emphasized that the information about opportunity was crucial. As the result of this difference, the Austrian theories showed a different explanation of the discovery, exploitation, and organization of entrepreneurial opportunities: (1) they did not view the process of opportunity discovery as mechanical; (2) the possession of information leads to opportunity discovery; and (3) opportunity exploitation is endogenous to opportunity discovery.

Basing on the same technological invention, since "each person's idiosyncratic prior knowledge creates a 'knowledge corridor'," people would discovery and exploit the opportunity in different ways. First, their prior knowledge about markets will influence people's discovery of which markets to enter to exploit a new technology; second, their prior knowledge about how to serve markets will influence the discovery of how to use a new technology to serve a market; third, their prior knowledge of customer problems will influence the discovery of products and services to exploit a new technology. Namely, the prior knowledge people got from work places or education and from roles of user or supplier, moderates (1) the relationship between technological invention and opportunity recognition and (2) the relationship between recognized opportunity and the approach of exploiting it.

It is important to notice that neither a technological change nor the search of opportunities will directly lead to the opportunity discovery, people's prior knowledge in market and recognition helps discover the opportunities (p. 465). "A large amount of technological change might generate a small amount of economic output, because it generates a small number of entrepreneurial opportunities" (p. 466). None of the new venture businesses were started by the inventor of 3DP.

THE LESSON LEARNT FROM Casson & Wadeson. 2007. The discovery of opportunities: Extending the economic theory of the entrepreneur

The entrepreneurship is considered as the choice under conditions of scarcity and entrepreneurs were the people who specialized in making choices that require intensive use of judgement. In this paper, the authors demonstrated that an entrepreneurial opportunity is best conceived as a potentially profitable but hitherto unexploited project. The reason why people did not notice the project could be rooted in the costs of discovery, since the information is often costly for potential entrepreneurs to obtain.

Entrepreneurs are the people who believe they have lower information costs than other people, believe that they had better theories, and advantage in collecting and processing information. The ends pursued by entrepreneurs might be non-materialistic or purely financial rewards.

As the result of changes in the environment and the opportunity recognition stimulated by the prospect of profit, entrepreneurs will search different opportunities. And, the success or failure is decided by their search strategy.

On the set of projects, entrepreneurship is objective and exogenous whilst on the set of opportunities, it is often subjective and endogenous. Much of the confusion over opportunity has arisen because of the failure to distinguish properly between the project set and the opportunity set (p. 290). By subjective, it is because it reflects individual entrepreneurs' perceptions of prospective profits; by endogenous, it is because some of the unexplored projects which formed the basis for the opportunity set since entrepreneurs decided not to exploit them previously.

To make this transparent, the authors illustrated three stages involved in a project: discovery, investment, and operation.

At the first stage, Coordination in a project-based economy is necessary to understand entrepreneurial opportunity. In a volatile economy, the project portfolio needs to be continually updated; and there is always the competition with each project for scarce resources. Also, existing projects are competing with new projects to retain the resources already under their control (p. 290). Thus, there are always Complements and substitutes between projects. It is reasonable to allocate resources to the most promising projects. When there is conflicting projects, the provision that only one project could be undertaken is the most direct solution. Then, Infrastructure and knowledge is necessary to any type of project. The knowledge spill-overs could bring the opportunity in the future.

At the second stage, since Evaluating new projects is costly, it is important to find a strategy for economizing on the costs of entrepreneurial discovery. Here are two stages: one is to locate the fields where entrepreneurs intend to focus his search; and two is to examine a set of potential projects. The characteristics of each project would be the "symptoms of the projects' underlying profitability" (p. 293), since at this stage how profitable the project will be is unknown to anyone (p. 296). When evaluating, there are two approaches to do this. One is An inward-looking approach, where it focuses on the preferences and capabilities of the entrepreneur such as the lifestyle. Another is An outward-looking approach where the change in the trends in the long run were taken into entrepreneurs' consideration, such as technological change. Also in this approach, the performance of current projects will also be treated as the criteria for opportunity evaluation. Here, more projects of the best performing types will remained; or the projects whose significance was not appreciated by the previous investments will be emphasized.

At the third stage, different entrepreneurs might look different part of an opportunity and they tend to have different pools of information. This makes the Sequential screening different from each other. Essentially, the project which is felt uncertain would be put "on hold." Owing to their limited information and resources, entrepreneurs will carry one project at one time and terminate the project ASAP so that he can proceed to investigate others. Entrepreneurs are not working along, but they will have to take account of the choices of the field made by other entrepreneurs. Sophisticated entrepreneurs may be able to gain further advantage through the strategic exploitation of the social processes such as starting a rumor.

THE LESSON LEARNT FROM Klevorick et al., 1995. On the sources and significance of interindustry differences in technological opportunities

In this paper, the authors argued why the R&D intensity is high in some industries and low in others. In previous researches, it was demonstrated that (1) firm size and market structure or (2) market size and growth in demand is the reason. But here, they argued that the technological opportunity and the ability to appropriate returns from new developments are crucial reasons.

By technological opportunities, they comprise the set of possibilities for technological advance which could be measured in terms of the distribution of values of improved production-function or production-attribute parameters, or of the distribution of returns to R&D (p. 188). These opportunities illustrated that the R&D at the level of the firm or industry is subject to diminishing returns. "As resources are devoted to R&D and projects are completed, technological opportunities are depleted and the pool of opportunities can be exhausted" (p. 188). Thus, an industry which was thought rich in technological opportunities was the one where high R&D intensities and high rates of technical advance tend to be sustained over time.

Basing on this logic, the authors thought there were 3 types of sources of technological opportunities: (1) the advance of scientific understanding; (2) technological advances originating outside the industry; and (3) feedbacks from technology.

First, it was believed that significant technological breakthroughs can be traced directly to advances in basic general scientific understanding that occurred just prior to the breakthrough (p. 189). After facing the need or an object, the science will be employed from the mind of the researcher. Thus, scientific advantage generated offsets to diminishing returns to R&D. Meanwhile, the scientific and engineering disciplines could provide and help facilitate technical progress of various kinds. These basic researches could be applied in various industries.

Second, here the party at the upstream or downstream of the supply chain could be important to industry R&D efforts. Third, the technology and research of today might only provide new starting points for future technology, which was called "compulsive sequences" or "natural trajectories." The logic of this feedbacks also suggested that although they could partially offset the tendency of R&D to deplete prevailing opportunities, in the long run they cannot totally offset that tendency (p. 192).

By using the data from Yale Survey, the above proposition was verified. Among the industries, the industry like drugs and semiconductors appear close to science; while motors, generators, industry controls, motor vehicle parts, and accessories are relatively distant from science. Universities and labs are often important to new sciences, but the basic sciences, compared with applied science and engineering fields, did not show high relevance to industry R&D (p. 197).

Material suppliers, production equipment suppliers, research equipment suppliers, and users were found important sources of technological knowledge. Namely, the sources with vertical linkages were important. About the natural trajectories, changes in scale of production, mechanization/automation, improving process yield, improving input material, and from batch to continuous process are found important resources.

Accordingly, the authors could distinguish industries that are rich in technological opportunities from those that are not (p. 201). Also among high opportunity sectors, different sources of opportunities impacted differently on R&D/sales, process innovation, and product innovation. The R&D intensity was correlated with (1) the connections with several of the fields of science; (2) the contributions made by university and government labs; (3) the work of equipment suppliers.

THE LESSON LEARNT FROM Alvarez & Barney. 2005. How do entrepreneurs organize firms under conditions of uncertainty?

In this paper, the authors separated the risk from uncertainty. This separations was treated as the criteria of deciding who is entrepreneur or non-entrepreneur. Under the conditions of uncertainty, entrepreneurs solve the problem of firms' decision rights and of residual claims so that they could organize a firm to facilitate the assembly and coordination of the resources needed to exploit a market opportunity (p. 777).

Even though managers or many people could use various ways to increase the certainty of the outcomes associated with making their decision, such as using the data on consumer preferences, "it will often the case that - even after all that can be done - the outcomes of decisions will often not be certain" (p. 778).

Thus, when exploiting a market opportunity, there often have two types: First, the risky investments. Furthermore, there were two conditions existed: (1) "when all possible future outcomes of exploiting that market opportunity are known at the time the decision is made; and (2) when the probability of each of these outcomes occurring is also known at the time a decision is made. The outcomes of these decisions are governed by well-defined probability distributions" (p. 778). Also, under these conditions, "as long as the discounted present value of the cash flows generated by making a risky investment in a market opportunity is positive, those seeking to maximize their economic wealth will have an incentive to make this investment" (p. 778).

Second, the uncertain investments. This is the situation where "the decision to invest in a market opportunity is uncertain when the possible outcomes of this decision and the probability of those outcomes are not known when a decision is made" (778). People are often so overconfident about themselves' anticipation to the result of decision that they underestimate the level of uncertainty in their environments.

All in all, when the outcomes of a decision are not certain, they are either risky or uncertain.

Under the conditions of uncertainty, the two currently dominate discussions of how firms are organized - that is, transactions cost economics and incomplete contract theory - could hardly work. In transactions cost economics, since there is a cost associated with using markets to govern certain economic exchanges, the hierarchical governance could address this issue by bringing a problematic exchange within the boundaries of a firm where a manager can monitor and control the behavior of all parties to that exchange. This process of reducing the treat of opportunism is known as "managerial fiat" (p. 780).

The reason why this hierarchy could work is based on the assumption that managerial fiat had sufficient information to manage an exchange in ways that are acceptable to all parties to that exchange. However, when the value of each party is unknown and the outcomes is unknown, such government to exploit opportunities might be ineffective.

In incomplete contract theory, it was suggested that "it is frequently not possible to write and enforce detailed and complete contracts to manage economic exchanges when those exchanges are initially conceived. In such settings, a firm emerges as an institutional framework where the rights to make specific decisions in an exchange are assigned to different parties to that exchange. The key decision rights are 'residual rights of control'" (p. 781).

However, when the information of who might benefit the most from an exchange is not known at the time when a firm is being organized under uncertainty, the people in the company cannot know who should control residual rights in that exchange.

To solve foregoing problem at the conditions of uncertainty, the authors argued several typologies:

First, Clan-based entrepreneurial firms. To make transaction-specific investments under uncertainty, the decision making in this firm would not be hierarchical, rather decision making would be more "democratic and consistent" with searching for a consensus among all those who have made specific investments in the firm. It should be emphasized that (1) the value of both productivity and value of an exchange may not be known, ex ante; and (2) an exchange only becomes possible if a clan already exists. People in clan-based entrepreneurial firms share all decision rights and residual claims, so that everyone is creating the value of firms and trusted by others. This process would bring decision-making leadership among all essential firm employees.

Second, Expert-based entrepreneurial firms. The decision of whether participating in the market opportunity exploitation is not dependent on the value pf people' opportunity, but on how they can use the assets they control in other economic settings. Thus, although the probability distribution of outcomes associated with making a specific investment may not be known, by examining the total value of the opportunity costs of parties to an exchange, it will be possible to identify who in an exchange has the strongest incentive to maximize the value of that exchange and who in an exchange should have the decision-making rights in that exchange (p. 785).

It should be emphasized that: (1) if the party have opportunity costs that are approximately equal in value, then these individuals will have difficult problems organizing a firm under uncertainty; and (2) the person with the most valuable opportunity costs should have decision-making rights of control in any firm that is organized - that is, they should be the "expert" in this expert-based entrepreneurial firm (p. 785).

Third, Charisma-based entrepreneurial firms. It is a sense that some individuals have of themselves of their vision of the future and of the inevitable success of their cause. Charismatic individuals can sometimes gather others around them in a form of hierarchical organization. In the extreme, the values, beliefs, and logic of subordinates are replaced by the vision of the charismatic leader. Thus, the firm will also be hierarchical.

In sum, basing on the distinction between risk and uncertainty, current transactions cost and incomplete contract theories apply quite well under conditions of risk; they must be extended and modified under conditions of uncertainty. Furthermore, these arguments help distinguish between entrepreneurial and non-entrepreneurial firms: entrepreneurial firms are organized under uncertainty, whose "primary purpose" is to solve transaction difficulties associated with the inability to know the value of an exchange at the time that exchange is commenced; non-entrepreneurial firms are organized under conditions of risk. The typology developed here showed that entrepreneurial firms could vary in some systematic ways.

Without these entrepreneurial firms, uncertainty is not likely to evolve into risk because there would be no coordinated resources brought together to try to exploit market opportunities. Without this initial coordination of resources, information about the probability distribution of outcomes associated with an exchange may not become known.

In the case where entrepreneurial firms could not transform themselves into non-entrepreneurial firms, the costs of renegotiating decision rights and residual claims may simply be too great to enable the exchanges around which a firm is organized to continue.

THE LESSON LEARNT FROM Busenitz. 1996. Research on entrepreneurial alertness

This is the re-test of Kaish & Gilad (1991)'s test of entrepreneurial alertness. While the gathering and interpreting of information is central to the entrepreneurial activity, "entrepreneurs are inclined to explore opportunities that are not obvious, and they identify these opportunities by linking different pieces of information in new ways" (p. 37).

Two hypotheses were tested: first, entrepreneurs exhibit more general alertness than do managers by spending more non-business time "searching" for opportunities and ideas (alertness); then, entrepreneurs are less likely than managers to rely on conventional economic analysis in appraising an opportunity and more likely to value their own subjective impressions (information cues).

All in all, Busenitz found that Kaish & Gilad tried to answer "How do entrepreneurs position themselves to encounter these opportunities?" and "When entrepreneurs look for new opportunities, what kind of information will get them interested immediately?"

THE LESSON LEARNT FROM Eckhardt & Shane. 2003. Opportunities and entrepreneurship

In this paper, authors reviewed the existing ideas about entrepreneurial opportunities. First of all they indicated several problems in the dominant theories in entrepreneurship. It was found that these theories "have sought to explain entrepreneurship as a function of types of people engaged in entrepreneurial activity and, as a result, have largely overlooked the role of opportunities" (p. 334). In particular, the authors demonstrated four "strict constrains" within equilibrium model of entrepreneur theory (p. 335).

Following Venkataraman (1997), they define entrepreneurship as the discovery, evaluation, and exploitation of future goods and services (p. 336). About entrepreneurial opportunities, they defined it as situations in which new goods, services, raw materials, markets and organizing methods can be introduced through the formation of new means, ends, or means-ends relationships. Entrepreneurs are different from non-entrepreneurs in that they created or identified the new ends and means previously undetected by market participants.

Towards entrepreneurial opportunities, they further argued why prices are incomplete indicators. First, it is because entrepreneurs had to believe the price of their resources would have value in the future rather than at a given point in time. "Prices fail to provide all of the necessary information to make all decisions about resources" (p. 337). Second, "in the absence of futures markets for goods and services, there is no way to use current prices to determine if there would be an opportunity to serve a market that is not yet in existence" (p. 337). The similar situation would repeat at the introduction of different innovations.

Thus, entrepreneurial profit and loss lies not in the information by the price change, but in the entrepreneurial conjecture as to the cause of that information. In these situations, individuals must make decisions based on information not incorporated in prices, and do so through mechanisms other than optimization. "Entrepreneurs bring new means-ends decision making frameworks into the price system by forming perceptions and beliefs about how to allocate resources better than they are currently allocated" (p. 338). And formulating a profitable conjecture about an opportunity is far from the trivial exercise of optimizing within existing means-ends frameworks since it requires forming expectations about the prices at which goods and services that do not yet exist will sell (p. 339). The individual must conjecture that a positive probability exists that the future price of the item will exceed its costs and that future demand will exist. Predicting such things with certainty is not possible, as it requires individuals to possess information that does not yet exist at the time of individual discovery. The only reliable confirmation that a previously unseen or unknown valuable opportunity does in fact exist occurs when a market has been created for the new item.

After the opportunity has been discovered, the entrepreneurial profit that opportunity generated is likely to be transient due to external and internal factors (e.g., competition). So, there needs to be certain mechanisms to make opportunity life longer (e.g., patent).

Entrepreneurial opportunities manifest themselves in a variety of different ways. First and foremost, they can occur as a result of changes in a variety of parts of the value chain. Opportunities also vary as to their resources: in prior research there are four important ways of categorizing opportunities by sources:

1. information asymmetry vs. exogenous shocks. Here, Kirzner and Schumpeter disagreed over where exogenous shocks of information are the primary catalyst of entrepreneurship.

2. the state of research on exogenous shift-based opportunities. There are usually several different types of exogenous shift exist - say, shifts in social demographics; the creation of new knowledge; and the shift in the properties of technology regimes (opportunity conditions, appropriability conditions, cumulative conditions, and the nature of the knowledge).

3. supply vs. demand side changes. "In general, the entrepreneurship literature implicitly focuses on supply side changes. [...] But changes in demand alone can generate opportunities. Customer preferences influence the allocation of resources because producers need to respond to the preferences and purchasing habits of customers" (p. 343).

4. productivity-enhancing vs. rent-seeking opportunities. As economics are made more efficient owing to the entrepreneurial activity, most researchers thought that entrepreneurship is productive entrepreneurship. However, it is also possible to think that entrepreneurial actions as private rent-seeking. It means that the opportunity generate personal value but no social value.

5. initiator of the change. Most studies focused on the technological opportunities which included two sets of actors: specialized knowledge creating agencies and firms within the industrial chain.

In the end, the authors emphasized that the study of opportunity-based perspective should use the tools like the longitudinal process studies, experiments, simulation models, and historical studies. This is because the dynamic processes that occur over time is crucial to the opportunity discovery.

THE LESSON LEARNT FROM Ronstadt. 1988. The corridor principle

"The Corridor Principle states that the mere act of starting a venture enables entrepreneurs to see other venture opportunities they could neither see nor take advantage of until they had started their initial venture" (p. 31).Previously, there is a single venture myopia among researchers and practitioners: it is assumed "a venture has a prestart-up period, a start-up phase, followed by poststart-up phase that may, or may not include the founding entrepreneur(s)" (p. 32) . Example of this linear model are Ken Olsen of DEC and Ray Kroc of McDonald's.

In former multiple venture research, Lamont (1972) mentioned that "Learning is a property of almost all business activity. Applied to technological entrepreneurship it means that experienced entrepreneurs exhibit substantial learning when they form a second technology based enterprise." So, the key point for this principle is that the knowledge and opportunities revealed most often after one gets into business (p. 34).

In this study, author abstracted data from 1537 respondents, and separated entrepreneurs into practicing entrepreneurs and ex-entrepreneurs. He found that (1) a positive relationship appears to exist between finding at least a second venture and realizing a longer entrepreneurial career; (2) significant shares of entrepreneurs are creating their second venture very early in their entrepreneurial careers; (3) relatively young career starts that are anticipated may allow future entrepreneurs to exploit the phenomenon of the Corridor Principle and enjoy longer lives as entrepreneurs; (4) many entrepreneurs are not visualizing their initial venture as a stepping stone to their second venture.

The reason why people from one entrepreneurial corridor to another may relate to: the need of the entrepreneur to do something new and different; the need to expand, or realize changing goals by starting a more promising venture; the need to bolster a declining initial venture by starting a second, third, etc. venture (p. 38).

THE LESSON LEARNT FROM Pavia. 1991. The early stage of new product development in entrepreneurial high-tech firms

The new product process is often divided into seven basic steps: new product strategy development, idea generation, screening, business analysis, development, testing, and commercialization. In this paper, the first three of these stages were argued. By making use of 118 high-tech manufacturing firms and software development firms, the author answered 4 questions: what are most valuable methods for identifying new products? what screening criteria did firms use? are idea generation and screening approaches associate with success? are the answers to these questions related to the educational background of decision makers?

When identifying potential new products, it was found that only about a third of the firms systematically gather potential new products ideas from customers (p. 23). Informal discussions and inter-departmental meetings are quite important activities for new product development. Similarly, although firms try to incorporate a discussion of new products in their annual strategic plans, only about a third of all the firms find this to be a very important activity; entrepreneurial high-tech firms still rely heavily on customer input for new product direction and utilize informal methods to identify new products. Firms that utilize informal identification methods may use either internal or external sources; but firms with formal methods would only use internal resources while rating annual strategic plan and market research as important parts (p. 25). With respect to screening, firms without formal procedures are more likely to use phrases like "ad hoc" and "gut feel" to describe their methods, and smaller number of them agreed that they use a consistent set of criteria for evaluation. The decision maker with business training has little effect on the aspects of idea generation but they may lead firms to rely more on short-term financial screening hurdles.

Finally, this study strongly suggests that the annual strategic plan has the potential for being an effective new product identification tool; and the information that would accrue through the use of environmental scanning and a database of potential new products. This is to say, the entrepreneurial high-tech firms with formal new product development process and plans are more favorable.

THE LESSON LEARNT FROM Ardichvili, A., et al. 2003. A theory of entrepreneurial opportunity identification and development

The entrepreneurial activity is not one time thing. The creation of successful businesses follows a successful opportunity development process which is cyclical and iterative (p. 106). In this paper, the authors discusses how entrepreneur's personality traits, social networks, and prior knowledge as antecedents of entrepreneurial alertness to business opportunity; and entrepreneurial alertness is the condition for the success of the opportunity identification triad: recognition, development, and evaluation.

What is opportunity? It appears as an "imprecisely-defined market need" or so-called value thought, or "un- or under-employed resources or capabilities" or so-called value creation capability (p. 108). The latter may include basic technologies, inventions, or ideas for products and services.

As this opportunity progresses from its elemental form and a business concept begins to emerge, the core notions of how the market need might be served or the resources deployed will be contained. And, as this more precise and differentiated business concept matures, it grows into a business model, which juxtaposes market needs and resources. A complete business model will also include a financial model. Finally, as an opportunity develops into its most elaborated form, the business concept will ultimately metamorphose into a full business plan.

What is opportunity development and recognition? They include perception, discovery, and creation - not simply "recognition." Business concept creation involves redirecting or recombining sources in order to create and deliver value superior to that currently available.

What is opportunity evaluation? Opportunities are evaluated at each stage of their development, although the evaluation might be informal or even unarticulated. If a business concept has yet to be developed, a feasibility analysis can specify it; or the "stage-gate" procedure can explicitly call for evaluation at each of several levels of development. As the result, the number of opportunity perceived will greatly exceed the number of successful businesses formed.

There are six major factors influencing this opportunity development process. First, entrepreneurial alertness or awareness, which might be high or low (p. 114); Second, information asymmetry and prior knowledge, which included two domain (special interest and industry knowledge); Third, accidental discovery versus systematic search, where accidental discovery may result from heightened entrepreneurial alertness while the entrepreneur is in a mode of "passive search" (p. 115); Fourth, social networks where casual acquaintance is more likely to provide unique information than are close friends because most people have more weak ties; Fifth, personality traits (optimism and creativity); Sixth, types of opportunities including four types which accord to different level of value sought and value creation capability (p. 117).

This theory was expected to hold in the domain of new business creation and development, both as independent businesses and as new businesses created within existing corporations.

THE LESSON LEARNT FROM Parker, S. C. 2005. The economics of entrepreneurship: What we know and what we don't

"Economics brings a large set of versatile and powerful theories and methods to the study of entrepreneurship. They are usually but not always quantitative, are often based on models of optimizing behavior under uncertainty, and utilize empirical approaches founded on the econometric analysis of large and representative data samples" (pp. 2-3). Also, "it seems fair to acknowledge that the economics approach focuses on a few aspects of entrepreneurship rather than the totality of this complex phenomenon" (p. 4).

There are many building blocks for thinking the research questions that have been raised by economics of entrepreneurship:

(1) occupational choice under uncertainty, (2) credit rationing that have shaped the understanding of small business lending as well as the potential role of governments to intervene in credit markets to assist entrepreneurial start-ups, (3) innovation.

In innovation, there are two theoretical models have been particularly influential (p. 12). One is that entrepreneurs learn from a series of stochastic draws that come in from the market. Based on constantly arriving new information, entrepreneurs adjust their beliefs and their market strategies (Jovanovis, 1982). Second, it is the product life cycle and the evolution of industries in which different types of innovation are performed at different stages of firm maturity (Klepper, 1996).

Following Schumpeter's insights on innovation and entrepreneurship, literature on "patent races" has emerged that pits established firms against each other in the drive to discover new innovations that yield monopoly profits. Also, growth is enhanced through individual entrepreneurs exploiting knowledge by creating new ventures even though they are not contributing to the production of knowledge (p. 13).

The above argument provided the theoretical models, whereas in the following the canonical empirical models would be summarized.

Economics distrust individuals' declared intentions and forces them to undertake the harder but more objective task of inferring their preferences from their actual behavior. Or, economics often apply advanced and innovative statistical techniques to overcome thorny empirical problems., like sample selection bias, unobserved heterogeneity, endogeneity, and non-stationarity.

In particular, there are models: (1) discrete choice models to analyze people's participation and survival in entrepreneurship, (2) sample selection models to analyze entrepreneur's profit, (3) hazard models to analyze how long people will remain in entrepreneurship and survive in the market, (4) cointegration estimators for time series entrepreneurship data to analyze how multiple aggregate variables covary over time, (5) decomposition techniques to analyze how entrepreneurial outcomes differed between socio-economic groups, and (6) earnings functions to analyze how schooling and other human capitals influence the earnings of entrepreneurs.

THE LESSON LEARNT FROM Garcia & Calantone. 2002. A critical look at technological innovation typology and innovativeness terminology: A literature rev

The author reviewed no less than 15 constructs and at least 51 distinct scale items by using 21 empirical studies in the new product development (NPD) literature. These studies did not use the same terminology as the research being undertaken, which leads to "new" findings that are in fact rehashes of previous work.

About "innovation," it is "an iterative process initiated by the perception of a new market and/or new service opportunity for a technology-based invention which leads to development, production, and marketing tasks striving for the commercial success of the invention. [...] This iterative process implies varying degrees of innovativeness and thus, necessitates a typology to describe different types of innovations. [...] It is important to elucidate that an invention does not become an innovation until it has processed through production and marketing tasks and is diffused into the marketplace. [...] Thus, an innovation differs from an invention in that it provides economic value and is diffused to other parties beyond the discoverers" (p. 112).

About "innovativeness," it is a "measure of the potential discontinuity a product (process or service) can generate in the marketing and/or technological process" (p. 113). This discontinuity could be broken into two frameworks: "(a) macro level where the concern is measuring how the characteristics of product innovation is new to the world, the market, or an industry; and (b) a micro level where product innovativeness is identified as new to the firm or the customer.

Basing on these levels (macro/micro) and S-curves (marketing/technology/both), the author categorized the innovation into three kinds: (1) radical innovations, which are innovations that cause marketing and technological discontinuities on both a macro and micro level; (2) incremental innovations, which occur only at a micro level and cause either a marketing or technological discontinuity but not both; and (3) really new innovations, which cover the combinations in between these two extremes (p. 120).

Radical innovations often do not address a recognized demand but instead created a demand previously unrecognized by the consumer. A radical innovation can be identified by the initiation of a new technology and new marketing S-curve (p. 122). Really new innovations are easily identifiable by the criteria that a discontinuity must occur on either a marketing or technological macro basis in combination with a micro level discontinuity. They can evolve into new product lines, product line extensions with new technology, or new market with existing technology. "Incremental innovations will not result in macro discontinuities which are only seen in radical or really new innovations" (p. 123). Because of the iterative nature, imitative products are frequently new to the firms, but not new to the market. All in all, if the market discontinuity is low or the technological discontinuity is low, this leads to low product innovativeness. On the contrary, high discontinuity in both factors leads to high product innovativeness (p. 124).

PS: the distinction between the marketplace and an industry is that the industry is comprised of several different markets. If an innovation is new to the industry, it is new to the marketplace (p. 124). New to the world implies new to the industry and new to the firm.

To use the customer's perspective for identifying products would be liken as letting the customer drive the innovative process of the firm (p. 125).

THE LESSON LEARNT FROM Piller et al. 2005. Overcoming mass confusion: Collaborative customer co-design in online communities

When participating in a community, users often faced (1) burden of choice of finding the right option from a large number of customization options; (2) the difficulty of addressing individual needs and of transferring them into a concrete product specification; and (3) uncertainties (based on missing information) about the behavior of the product. These problems were named as "mass confusion." To solve the confusion, the author emphasized that traditional mass customization for transaction is not an appropriate way but the collaborate customer co-design would work.

In contrast, the community for collaborative customer co-design is different. It brings (1) a better starting configuration to users, (2) the fostering joint creativity and problem solving, and (3) the building of trust and the reduction of the perception of risk (p. 13). In this community, all customers can be members of the community instead of just some lead users as in the case of innovation community; and it often fosters aesthetic creativity instead of the joint solving of technical problems (p. 12). "Customization with regard to aesthetic design is often influenced by peers and the taste of a group rather than by the individual taste of a single person" (ibid).Of course, to solve the same confusion, the community for transaction, as a business community, could be improved by developing appropriate toolkits for cus

tomer co-design and building strong customization brands. However, this is the network between users and their suppliers, where the users often have less motivation to participate.

Compared with each other:

First, often, firms just offer a standard product as pre-configuration. Instead of focusing on automatic filtering processes in which a single customer does not get in contact with other customers, the community setting for customer co-design empowers an individual design process by sharing knowledge, providing a better fitting pre-configuration. Hence, within the community "affinity groups (Peppers & Rogers, 1997)" were formed and customers would receive recommendations for future purchases without the need to look at a broad range of products (pp. 14-15).

Second, communities for co-design reflect expert knowledge of customer groups with interact not only with one company, but importantly also with each other. This can

foster creativity and stimulate better solutions due to the effect of intrinsic motivation on innovation-related activities (self reward and exchange of information).

Third, a customized solution that is jointly developed by a group of users is often more robust. Communities where users can interact with each other can help in generating trusted recommendations. Communities of co-design could further enhance trust building and reduce the perceived risk of (potential) buyers of a customized product by building word-of-mouth communication.

"Customers participated in the community because they can directly benefit from a customized product variant, but also due to factors of intrinsic motivation as well as the peer recognition and reputation. [...] From a customer perspective, contributing to an anonymous information pool via the toolkit would remain a simple customer-supplier-interaction, most certainly lacking users' motivation" (p. 19).

All in all, form the mass customization, the customers could get the returns - (1) the value of a customized product and (2) rewards from the design process such as flow experience; but had to incur the costs - (1) the premium paid for the individualized product compared to a standard offering and (2) the drawbacks of the customers' active participation in value creation during the configuration process.

To analyze the above ideas, authors made use of Adidas and Lego as descriptive research, and utilized the cases of My Virtual Model, Usertool, American Eagle, and Swatch Via Della Spiga, as exploratory.

THE LESSON LEARNT FROM Baldwin & von Hippel. 2009. Modeling a paradigm shift: From producer innovation to user and open collaborative innovation

In this paper, the author demonstrated a paradigm shift in innovation. In producer innovation paradigm, it was assumed that "a producer serving many customers can afford to invest more in an innovation design than any single user" (p. 2); and there are four reasons contributing to this preeminence of mass-produced products in economy: (1) computational resources were scarce, (2) there was a close tie between design of items and the mass-production technologies, (3) modular design methods were not well understood, and (4) cheep and rapid communication was not technologically possible.

Here, from the factors of design cost and communication cost, the feasibility of each innovation model was argued. Adopting Chandler's logic, they expected a particular organizational form to be prevalent when its technologically determined cost are low and to be ascendent when its costs are declining relative to the costs of other forms (p. 8). They do not believe that producer innovation will disappear but they do expect it to become less pervasive and ubiquitous than was the case during most of the 20th century. Examples of producer innovators are: (1) a firm or individual that patents an invention and licenses it to others; (2) a firm that develops a new process machine to sell to its customers; (3) a firm that develops an enhanced service to offer its

A given mode of innovation is viable with respect to a particular innovation opportunity if the innovator finds it worthwhile to incur the requisite costs to gain the anticipated value of the innovation (p. 9). Innovation opportunity has four generic costs: design cost, communication cost, production cost, and transaction cost. To make the argument as clear as possible, the author first focus on the communication and design cost, holding production and transaction costs constant. clients. With respect to an open collaborative innovation project are: (1) the participants are not rivals to the innovation design and (2) they do not individually or collectively plan to sell products or services, such as an open source software project.

In the circumstance of single user innovation, the effort of innovation is worthwhile if the value is greater than the user's design cost: d[s]

In the circumstance of producer innovation, producers can economically justify undertaking larger designs than can single users, because they expect to spread their design costs over many purchasers. Here, producers were assumed to know their customers' willing-to-pay for innovative products: Expected profit = p*Q*-d[p]-c[p]. Here the design costs are higher than the value of the innovation to a single user. And, when the communication cost is low so that the sum of design and communication costs fall below the producer's bound, the producer could

innovate. (1) The size of the potential market, and (2) the need to communicate are affecting the viability of producer innovation.

The bounds of open collaborative innovation are the communication cost of user i is lower than his expected benefit from communicating (the probability that member j will respond; the fraction of remaining design that member j can provide; and the value that user i may obtain). When working together and contributing his or her own part, the total design investment will be the sum of their individual design costs. Thus, OCI operating within a task-divisible and modular architecture can pursue much larger innovation opportunities than single user innovators acting alone.

About the production cost, the author emphasized that there were differences between information products and physical products. There is a contrast between mass production and mass customization. Sometimes, the product-specific production systems make the producer innovation model dominate. About the transaction cost, the free reveal activity of users made the cost decrease but alike to classic transaction costs in patent and secrecy, there would be cost of enforcing GPL. The regulation may also bring costs to OCI.

THE LESSON LEARNT FROM Parhankangas & Arenius. 2003. From a corporate venture to an independent company: A base for a taxonomy for corporate spin-off

By using the data on 50 technology-related spin-off firms from large Finnish corporations, the authors categorized the corporate spin-offs into 3 types: spin-off developing new technologies, spin-offs serving new markets, and restructuring spin-offs.

They perceived that "the decision to form a spin-off firm is deeply rooted in the nature of interaction between the venture to be spun-off and its parent firm" (p. 464). The study focuses on new business formation based on the business ideas developed within the parent firm being taken into a self-standing firm (p. 464). They utilized two perspectives: resource-based approach and resource-dependent approach. The former is fundamentally concerned with the internal accumulation of assets; while the latter pays close attention to the behavior of organizations and individuals in a resource exchange relationship. In sum, the RBA seeks to explain the outcome of the resource sharing relationship, and the RDA is more concerned with motivations driving the behavior of the parties.

From these perspectives, they proposed that (1) before spin-off, relatedness enhances competence development in a new venture; (2) spin-off decisions are associated with reduced resource fit between the parent firm and the venture; and (3) spin-off ventures with intensive resource sharing linkages with the parent firm are less likely to diversify away from their original competence base than spin-off firms with less intensive resource sharing linkages.

Then, they conducted cluster analysis. In Cluster 1, the new technology group, all the spin-off ventures are engaged in developing leading-edge, new-to-market technologies. The idea fro technology development came from outside the parent firm. There were no resource linkages between parent and venture but rather is collaboration with university or research institutes. The spin-off-triggering factor was mostly the restructuring programs undertaken by the parent firm. In Cluster 2, the new market group, the parent and venture essentially had the same technology base, but the impetus for the ventures within the parent firm was either to support the core businesses of the parent; or to exploit the possibilities of core technologies to the fullest. As the spin-off firm introduced new product applications of the technology, the linkages tended to weaken. In Cluster 3, the restructuring group, the ventures were old established business units of parent firms. The technological competencies being developed were rather mature. At the earlier stages of the venture evolution, these ventures had shared technology, production, marketing- and distribution- related resources with other business units of the parent firm. This will continue until the ventures established its position in the markets.

THE LESSON LEARNT FROM von Hippel. 1976. The dominant role of users in the scientific instrument innovation process

From 80% of 111 cases of scientific instruments, von Hippel found that the firms comprising the industry are not in themselves necessarily innovative but rather only provide the product engineering and manufacturing function for instrument users (e.g., scientists).

He analysed three kinds of innovations - basic innovations, major improvement, and minor improvement - according to the degree of the increase in functional utility. What makes an innovation major one is dependent on the point of view of the instrument user (p. 218). Only the first commercial introduction of an innovation is included in the sample; and is included only if it is commercially successful. By commercial success, it means that the invention is being offered for sale, by at least one commercializing company, from the time of innovation until the present day (p. 217).

Manufacturers may perform engineering work, but this work typically affects only the engineering embodiment of the user's invention, not its operating principles. Furthermore, nine of the ten profitable commercialized products were the result of user-dominated innovation processes. Users often have to take considerable initiative to bring a company to enter a product line new to it; and manufacturers who accepted the idea would often introduce a new instrument type to its established customer base (p. 223). The precommercial diffusion of significant user inventions via "homebuilt" replications of the inventor's prototype design by other users. This enshrines relatively minor activities within the manufacturer as the "innovation process" and relegates major activities by the user to the status of "input" to that process (p. 230).

Nevertheless, von Hippel, also hasten to add that "at this point we by no means wish to suggest that the patterns which we will describe are in any sense 'pure types' or represent an exhaustive listing of possible innovation patterns" (p. 231). The user invented because some needed the invention as a day-in, day-out functional tool for their work; and others were motivated to invent and reduce the invention to practice because how it performed was a useful means of testing and deepening their understanding of the principles underlying this operation (p. 235). A firm should not make use and would not find all the information from the users' invention useful or novel.

THE LESSON LEARNT FROM von Hippel. 1986. Lead users: A source of novel product concepts

Lead user and usage patterns

This is a paper which is telling us how and why to introduce lead users into the process of innovation. By lead users, they are different from the manufacturers or typical users in that (1) they face unique needs; and (2) they derive net benefits from the solution to their needs. "By industrial and consumer products, they are only components in larger usage patterns which may involve many products. Since a change in one component can change perceptions of and needs for some or all other products in that pattern, users must first identify their existing multiproduct usage patterns in which the new product might play a role" (p. 792). In traditional marketing research such as similarity-dissimilarity method, there is a problem that "neither method contains an effective mechanism to encourage this outcome (new attributes of a product)" (p. 793).

Although people who are more familiar with one usage pattern of a product may not sense the new pattern of that product - say, "the familiarity with existing product attributes and users interferes with an individuals' ability to conceive of novel attributes and users" (p. 792). But on the other hand, von Hippel emphasized that "the constraint of users to the familiar does not lessen the ability of marketing research to evaluate needs for new products by analyzing typical users" since "the 'new' is reasonably familiar to the users" (p. 796). In particular, users able to obtain the highest net benefit from the solution will be the ones who have devoted the most resources to understanding it. And it follows that these users would have the richest real-world understanding of the need to share with inquiring market researchers (p.797).

Lead user and innovation

Since problem-solving activity has been motivated by expectations of economic benefit, and since lead users have been defined in part as users positioned to obtain high net benefit from a solution to their needs, it is reasonable that lead users may have made some investment in solving the need at issue" (p. 800).

Lead users' innovation and general market

With respect to users of industrial products, they "typically measure the value of proposed new industrial products in economic terms, so important underlying trends related to product value are often inescapably clear to those in the industry" (p. 798). But with respect to users of consumer products, there is often no underlying stable basis for comparison, so the accurate trend identification is often more difficult. Thus, in the instance of industrial goods, the translation of lead users' innovation to general market is not a serious problem while in the instance of consumer goods, a test of the applicability might be needed in the translation. "