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Entrepreneurial and strategic actions are crucial for wealth creation, and the business opportunity is a critical factor in this process. The purpose of this paper is to explore the role of the firm’s strategic posture in the relationship between individual alertness and opportunity identification within an existing firm. This approach contributes to entrepreneurship theory building through a multilevel study.

The quantitative research focuses on understanding the mediating role of an organization’s strategic posture in the opportunity identification process. Using a sample of 276 firms, this study tests a two-level model to explain opportunity identification.

The findings provide empirical evidence that a firm’s strategic posture mediates the relationship between individual alertness and opportunity identification. Furthermore, this study finds differences in the mediating role of a firm’s strategic posture through which entrepreneurs and managers affect opportunity identification. Years after the creation of startup, the entrepreneurs still exhibit entrepreneurial characteristics that affect opportunity identification. The findings provide evidence that entrepreneurs foster an internal culture and set of values that are more favorable to radical innovation, compared to managers who favor incremental and less risky projects.

The findings suggest the possibility for new theory building that can improve the fields of entrepreneurship and management research. Moreover, the proposed model constitutes a new approach to analyze the mediating role of an organization’s strategic posture in the opportunity identification process.

This paper provides an original approach to literature in exploring the relationship between entrepreneurial alertness and firm’s strategic posture in explaining the opportunity identification process. This work will help expand the theory building that explores differences between managers and entrepreneurs in organizations.

The purpose of this paper is to propose an integrated theory to explain the effect of regional culture on high-technology micro and small (HTMS) firm outcomes. The integrated culture-social capital outcomes (CSCO) model examines the impact of culture on performance and evolution of HTMS firms through the mediating effect of intra-firm and inter-firm social capital.

Theoretical insights from social capital and culture are combined with the results of previous empirical observations to explain cross-cultural differences in the performance of HTMS firms. The authors then propose the CSCO model as a means to integrate and advance theory building.

The CSCO model explains the impact of culture on performance and evolution of HTMS firms through intra-firm and inter-firm social capital networks. Cultural context affects the performance of high-tech micro and small firms through the nature and structure of the networks involved in building and exploiting inter-firm and intra-firm social capital. Moreover, regional culture indirectly influences the balance between positive and negative effects of social capital on firm performance. These observations explain inconsistent findings from past empirical research and contribute to understanding the “embeddedness paradox” of social capital.

The present model is not comprehensive. It does not account for many contextual factors identified in organizational network and cluster literature that contribute to the development of HTMS firms. Future research should consider the relationships between the three dimensions of social capital and seek to test the model with rigorous data collection and analysis.

While past studies focus on the direct relationship between regional culture and firm performance, this paper proposes the mediating effect of internal and external social capital between cultural context and firm performance. This proposal contributes to social capital and entrepreneurship literature and provides a potential explanation for inconsistent findings in past empirical research.

The purpose of this paper is to investigate the influence of temporal construal theory on entrepreneurial intention models using a three-country study. Inclusion of temporal construal theory in intent models would suggest path dependent influence on intent, and more specifically, that intent may be subdivided into temporally based categories, broadly codified as short-term and long-term intent.

A quasi-experimental study of 1,046 university students in business and engineering from the USA, Mexico, and Spain was conducted. A temporal construal model of intent is proposed, including measures of short-term and long-term intent. Entrepreneurial self-efficacy (ESE), part of the perceived behavioral control in the theory of planned behavior, is utilized to structure the model antecedents.

The results suggest the existence of differences in individual entrepreneurial intent measures depending on the individual’s perception of when the entrepreneurial event is anticipated to occur in their lives. Utilizing an ESE construct, the authors demonstrated that short-term entrepreneurial intent significantly mediates the effect of ESE on long-term entrepreneurial intent. Furthermore, the results identify a mediating model that does not depend on regional country differences, thus supporting the generalizability of the findings.

The paper bridges temporal construal theory and entrepreneurial intentions to qualify the path dependent effects of this psychological phenomena and its impact on identifying nascent entrepreneurs. The multi-country results indicate the ability to generalize the findings into a more complete theoretical model of entrepreneurial intention and suggests potential improvements in predictive models that currently use single or averaged measures of entrepreneurial intent.

This chapter opens the second part of the Volume, focusing on the small farms' role and dynamics within the evolving food system. Assessing small farmers' actual and potential contribution to the change towards a sustainable food and nutrition security requires a deep understanding of their strategic decision-making processes. These processes take place in a context highly conditioned by internal and external conditions, including the complex relations between farm and household, which are mapped and described. Building on an adaptation of Porter's model (Porter, 1990), the chapter investigates how farmers, given those conditions, define their strategies (in particular their innovation strategies) aimed at economic and financial sustainability through a multidisciplinary analysis of scientific literature. Internal conditions are identified in the light of the Agricultural Household Model (Singh & Subramanian, 1986) which emphasizes how family farming strategies aim at combining business-related objectives, and family welfare. Then, a comprehensive set of external conditions is identified and then grouped within eight categories: ‘Factors’, ‘Demand’, ‘Finance and Risk’, ‘Regulation and Policy’, ‘Technological’, ‘Ecological’, ‘Socio-institutional’ and ‘Socio-demographic’. Similarly, six types of strategies are identified: ‘Agro-industrial competitiveness’, ‘Blurring farm borders’, ‘Rural development’, ‘Risk management’, ‘Political support’ and ‘Coping with farming decline’.

Starting from a critical analysis of the main criteria currently used to identify marginal areas, this paper aims to propose a new classification model of such territories by leveraging knowledge discovery approaches and knowledge visualization techniques, which represent a fundamental pillar in the knowledge-based urban development process.

The methodology adopted in this study relies on the design science research, which includes five steps: problem identification, objective definition, solution design and development, demonstration and evaluation.

Results demonstrate how to exploit knowledge discovery and visualization to obtain multiple mappings of inner areas, in the aim to identify good practices and optimize resources to set up more effective territorial development strategies and plans. The proposed approach overcomes the traditional way adopted to map inner areas that uses a single indicator (i.e. the distance between a municipality and the nearest pole where it is possible to access to education, health and transportation services) and leverages seven groups of indicators that represent the distinguishing features of territories (territorial capital, social costs, citizenship, geo-demography, economy, innovation and sustainable development).

The proposed model could be enriched by new variables, whose value can be collected by official sources and stakeholders engaged to provide both structured and unstructured data. Also, another enhancement could be the development of a cross-algorithms comparison that may reveal useful to suggest which algorithm can better suit the needs of policy makers or practitioners.

This study sets the ground for proposing a decision support tool that policy makers can use to classify in a new way the inner areas, thus overcoming the current approach and leveraging the distinguishing features of territories.

This study shows how the availability of distributed knowledge sources, the modern knowledge management techniques and the emerging digital technologies can provide new opportunities for the governance of a city or territory, thus revitalizing the domain of knowledge-based urban development.

The paper aims to propose a knowledge visualization approach and algorithm to support public decision makers to define the inner areas, which represents a strategic topic in the European debate about territorial inequality and development.

The study has been developed by following the design science research, which includes six steps: problem identification and motivation; identification of the objectives for a solution; design and development; demonstration; evaluation; and communication. As for the design and development step, the proposed approach and algorithm ground on association mining to discover hidden relationships existing among municipalities. They have been applied to analyse the 97 municipalities of the Lecce province, and each municipality has been described through 30 multi-domain indicators organized into seven categories, whose data have been collected from institutional datasets, local sources or web-scraping process.

A set of complementary analyses has been generated through the construction of dynamic and interactive knowledge maps that show “similar” municipalities according to the indicators selected.

The approach and algorithm proposed allow discovering similarities existing among distinct municipalities, based on the analysis of a set of multi-domain indicators. The approach may complement or completely substitute the existing ones used to define inner areas, thus overcoming both the methodological limits of the “top-down” line imposed by the central legislator, and the “bottom-up” paradox consisting in the illusion that single (and often small) towns have the economic and cognitive resources necessary to implement effective territorial mapping and development strategies. In such a way, policy makers can be aware on similarities existing among distinct towns and can thus share cognitive and financial resources to define a common plan and a set of practices for territorial development.

In their authoritative literature review, Breen and Jonsson (2005) claim that ‘one of the most significant trends in the study of inequalities in educational attainment in the past decade has been the resurgence of rational-choice models focusing on educational decision making’. The starting point of the present contribution is that these models have largely ignored the explanatory relevance of social interactions. To remedy this shortcoming, this paper introduces a micro-founded formal model of the macro-level structure of educational inequality, which frames educational choices as the result of both subjective ability/benefit evaluations and peer-group pressures. As acknowledged by Durlauf (2002, 2006) and Akerlof (1997), however, while the social psychology and ethnographic literature provides abundant empirical evidence of the explanatory relevance of social interactions, statistical evidence on their causal effect is still flawed by identification and selection bias problems. To assess the relative explanatory contribution of the micro-level and network-based mechanisms hypothesised, the paper opts for agent-based computational simulations. In particular, the technique is used to deduce the macro-level consequences of each mechanism (sequentially introduced) and to test these consequences against French aggregate individual-level survey data. The paper's main result is that ability and subjective perceptions of education benefits, no matter how intensely differentiated across agent groups, are not sufficient on their own to generate the actual stratification of educational choices across educational backgrounds existing in France at the beginning of the twenty-first century. By computational counterfactual manipulations, the paper proves that network-based interdependencies among educational choices are instead necessary, and that they contribute, over and above the differentiation of ability and of benefit perceptions, to the genesis of educational stratification by amplifying the segregation of the educational choices that agents make on the basis of purely private ability/benefit calculations.