41-45 of 45 Results  for:

  • Entrepreneurship x
Clear all

Article

Alexander Bolinger and Mark Bolinger

There is currently great enthusiasm for entrepreneurship education and the economic benefits that entrepreneurial activity can generate for individuals, organizations, and communities. Beyond economic outcomes, however, there is a variety of social and emotional costs and benefits of engaging in entrepreneurship that may not be evident to students nor emphasized in entrepreneurship courses. The socioemotional costs of entrepreneurship are consequential: on the one hand, entrepreneurs who pour their time and energy into new ventures can incur costs (e.g., ruptured personal and professional relationships, decreased life satisfaction and well-being, or strong negative reactions such as grief) that can often be as or more personally disruptive and enduring than economic costs. On the other hand, the social and emotional benefits of an entrepreneurial lifestyle are often cited as intrinsically satisfying and as primary motivations for initiating and sustaining entrepreneurial activity. The socioemotional aspects of entrepreneurship are often poorly understood by students, but highlighting these hidden dimensions of entrepreneurial activity can inform their understanding and actions as prospective entrepreneurs. For instance, entrepreneurial passion, the experience of positive emotions as a function of engaging in activities that fulfill one’s entrepreneurial identity, and social capital, whereby entrepreneurs build meaningful relationships with co-owners, customers, suppliers, and other stakeholders, are two specific socioemotional benefits of entrepreneurship. There are also several potential socioemotional costs of entrepreneurial activity. For instance, entrepreneurship can involve negative emotional responses such as grief and lost identity from failure. Even when an entrepreneur does not fail, the stress of entrepreneurial activity can lead to sleep deprivation and disruptions to both personal and professional connections. Then, entrepreneurs can identify so closely and feel so invested that they experience counterproductive forms of obsessive passion that consume their identities and impair their well-being.

Article

Briance Mascarenhas and Megan Mascarenhas

A strategic group is defined as a set of firms within an industry pursuing a similar strategy. The strategic group concept emerged with much promise over 40 years ago. Research on strategic groups over time in a broad variety of settings has sought to clarify their theoretical and empirical properties. These research findings are gradually being translated into practical managerial guidance, so that the strategic group concept can be understood, operationalized, and used productively by managers. Two main approaches exist for identifying strategic groups—a ground-up approach, using disaggregated data, and a top-down, using cognition. Once identified, managerial insights can be derived from clarifying a strategic group’s profile. Firm membership in a group helps to uncover immediate and more distant types of competitors. Group profitability differences reveal the more rewarding and less attractive areas within an industry, as well as identify the lower-return groups from where firm exits are likely to occur. Group dynamics reflect competitive and cooperative behavior within and between groups. Several promising areas for future research on strategic groups to improve understanding and practice of strategy.

Article

Sherry E. Sullivan and Shawn M. Carraher

The kaleidoscope career model (KCM) was developed by Mainiero and Sullivan in 2006 based on data from interviews, focus groups, and three surveys of over 3,000 professionals working in the United States. The metaphor of a kaleidoscope was used to describe how an individual’s career alters in response to alternating needs for authenticity, balance, and challenge within a changing internal and external life context. As a kaleidoscope produces changing patterns when its tube is rotated and its glass chips fall into new arrangements, the KCM describes how individuals change the pattern of their careers by rotating the varied aspects of their lives to arrange their work–nonwork roles and relationships in new ways. Individuals examine the choices and options available to create the best fit among various work demands, constraints, and opportunities given their personal values and interests. The ABCs of the KCM are authenticity, balance, and challenge. Authenticity is an individual’s need to make choices that reflect their true self. People seek alignment between their values and their behaviors. Balance is an individual’s need to achieve an equilibrium between the work and nonwork aspects of life. Nonwork life aspects are defined broadly to include not only spouse/partners and children but also parents, siblings, elderly relatives, friends, the community, personal interests, and hobbies. Challenge is an individual’s need for stimulating work that is high in responsibility, control, and/or autonomy. Challenge includes career advancement, often measured as intrinsic or extrinsic success. All three parameters are always active throughout the life span, and all influence decision-making. One parameter, however, usually takes priority; this parameter has greater influence in shaping an individual’s career decisions or transitions at that point in time. Over an individual’s life, the three parameters shift, with one parameter moving to the foreground and intensifying in strength as it takes priority at that time. The other two parameters will lessen in intensity, receding into the background, but they remain active.

Article

In the early 1990s business creation was receiving a great deal of attention after it was clear that new firms were a major source of job creation. There was not, however, reliable data on the prevalence of persons participating in firm creation, what they would do to implement new ventures, or the proportion of start-up efforts that became profitable businesses. This hiatus led to the development of longitudinal studies of the entrepreneurial process; 14 projects have now been implemented in 12 countries. The Panel Study of Entrepreneurial Dynamics (PSED) protocol was designed to provide estimates of the prevalence of individuals involved in business creation and the presence of pre-profit, start-up ventures; data on the major activities undertaken to implement a new firm; and track the proportion that completed the transition from start-up to profitable new firm. A number of challenges were involved in implementing the research program, including the development of efficient procedures for identifying representative samples of nascent entrepreneurs and criteria for determining the dates of entry into the start-up process, the transition to a profitable business, and disengagement from the initiative. Data collection is a three-stage process. The initial stage is identifying nascent entrepreneurs in a representative sample of adults. The second are detailed interviews on the start-up team and activity related to creating a new venture. The third stage is follow-up interviews completed to determine the outcome of the start-up efforts. A large number of scholars have been involved in development of the interviews and the PSED data sets have considerable information on the perspectives, activities, and strategies of those involved in the start-up process. Since the initial data sets were made available 15 years ago, there has been considerable research utilizing PSED data sets. One major finding, however, is that the firm creation process is much more diverse and complicated than had been expected. There are substantial research opportunities to be explored. A review of the major features of the PSED protocol and a summary of the existing data sets provides background that will facilitate additional analysis of the firm creation process. Four data sets (Australia, Sweden, and U.S. PSED I & II) are now in the public domain. Critical features of the start-up process have been consolidated and harmonized in a five-cohort, four country data set which is also available.

Article

For decades researchers have studied various aspects of the technology transfer and commercialization process in universities in hopes of discovering effective methods for enabling more research to leave the university as technologies that benefit society. However, this effort has fallen short, as only a very small percentage of applied research finds its way to the marketplace through licenses to large companies or to new ventures. Furthermore, the reasons for this failure have yet to be completely explained. In some respects, this appears to be an ontological problem. In their effort to understand the phenomenon of university commercialization, researchers tend to reduce the process into its component parts and study each part in isolation. The result is conclusions that ignore a host of variables that interact with the part being studied and frameworks that describe a linear process from invention to market rather than a complex system. To understand how individuals in the technology commercialization system make strategic choices around outcomes, studies have been successful in identifying some units of analysis (the tech transfer office, the laboratory, the investment community, the entrepreneurship community); but they have been less effective at integrating the commercialization process, contexts, behaviors, and potential outcomes to explain the forces and reciprocal interactions that might alter those outcomes. The technology commercialization process that leads to new technology products and entrepreneurial ventures needs to be viewed as a complex adaptive system that operates under conditions of risk and uncertainty with nonlinear inputs and outputs such that the system is in a constant state of change and reorganization. There is no overall project manager managing tasks and relationships; therefore, the individuals in the system act independently and codependently. No single individual is aware of what is going on in any other part of the system at any point in time, and each individual has a different agenda with different metrics on which their performance is judged. What this means is that a small number of decision makers in the university commercialization system can have a disproportionate impact on the effectiveness and success of the entire system and its research outcomes. Critics of reductionist research propose that understanding complex adaptive systems, such as university technology commercialization, requires a different mode of thinking—systems thinking—which looks at the interrelationships and dependencies among all the parts of the system. Combined with real options reasoning, which enables resilience in the system to mitigate uncertainty and improve decision-making, it may hold the key to better understanding the complexity of the university technology commercialization process and why it has not been as effective as it could be.