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The purpose of this paper is to obtain evidence concerning the basic dimensions included in cognitive prototypes pertaining to opportunity recognition and decision to launch a new venture; identifying the underlying dimensions of both prototypes – the cognitive frameworks current or nascent entrepreneurs employ in performing these important tasks.

The bi-dimensional models were tested in a sample of 284 founder entrepreneurs, using a 48-item questionnaire. It was used as structural equation confirmatory factor analysis to compare fit indices of uni-dimensional second-order and third-order bi-dimensional models of business opportunity and decision to launch a venture.

Results support the bi-dimensional models and offer support that both prototypes include two basic dimensions. For the business opportunity prototype these are viability and distinctiveness while for the decision to launch a new venture, the basic dimensions are feasibility and motivational aspects.

These results help to further clarify the nature of the cognitive frameworks individuals use to identify potential opportunities and reach an initial decision about whether to pursue their development. Uncovering the cognitive functioning of opportunity recognition and decision to exploit it, allow individuals to recognize opportunities easier and successfully; and to make more accurate and effective decisions.

Knowing the basic dimensions of opportunity and decision-making prototypes contributes to develop effective skills with respect to business opportunity recognition among students enrolled in entrepreneurship programs. These surveys can be used for self-assessment and also for investors, tutors, and entrepreneurship agents in order to help evaluate features of business opportunities and decision to launch a venture.

This study embraces a conceptual contribution, proposing a different model of the business opportunity and decision to exploit prototypes, and it extends Baron and Ensley (2006) previous work, to another important step in the entrepreneurial process – the decision to develop an identified opportunity through the launch of a new venture.

Projects have high stakes in how they are categorized. The final place of a project within a classification scheme depends on the inclusion or exclusion of certain classification criteria. So far, many researchers and organizations have used a variety classification criteria to construct different project classification schemes. However, most of these classification criteria have been taken for granted and the process of selecting them to categorize projects still remains a black box. The purpose of this paper is to open the black box of classification process and explain how it is reflected in picking the classification criteria.

Drawing on insights from cognitive psychology’s literature, the authors examine the main views of classification process to provide insight into the unknown or implicit reasons that one might have to pick particular attributes as project classification criteria.

The authors argue that classification occurs in the eye of the beholder; it is not only the project’s features per se but also the classifier’s “goals, ideal and preference” or “knowledge of causal relations” that are reflected in the classification criteria.

By elaborating the classification process, the authors brought the project context into the big picture of classification and provide a more rational, and coherent picture of how project classification works. This contributes to a theoretical blind spot, raised by prior researchers, related to the selection of project classification criteria.

Understanding classification processes will reduce the ambiguities, inconsistencies and multiple interpretations of project categories and help practitioners increase their projects’ visibility and legitimacy within an already established classification scheme. These implications help organizations in addressing some of the main obstacles to using categorization in project management practice.

The review of prior work in the category research literature and the insights from this paper will provide project management scholars with a useful toolbox for future research on project classification, which has long been understudied.

A recommendation system for an extended process of information retrieval in distributed information systems is proposed. This system is both a model of dynamic cognitive categorization processes and powerful real application useful for knowledge management. It utilizes an extension of fuzzy sets named evidence sets as the mathematical mechanisms to implement the categorization processes. It is a development of some aspects of Pask’s conversation theory. It is also an instance of the notion of linguistic‐based selected self‐organization here described, and as such it instantiates an open‐ended semiosis between distributed information systems and the communities of users they interact with. This means that the knowledge stored in distributed information resources adapts to the evolving semantic expectations of their users as these select the information they desire in conversation with the information resources. This way, this recommendation system establishes a mechanism for user‐driven knowledge self‐organization.

Entrepreneurial opportunity (EO) identification pertains to the core processes of entrepreneurship and innovation. The initial phase of this process starts with individual cognition, which is why cognition has been established as a critical theoretical perspective.

Knowledge and new information have been confirmed as essential cognitive impact factors. However, it is not understood well, how individuals apply those factors and how they actually identify innovative and economically viable EOs. To address the limitations of current research, this chapter investigates the current literature on underlying cognitive processes of opportunity identification.

The literature analysis demonstrates that there is not a single cognitive process but rather a magnitude of different micro-mechanisms that are necessary for the successful identification of EOs. The findings are grouped to four categories of cognitive processes and entail their micro-mechanisms: pattern recognition, information processing, and creative thinking. Furthermore, the analysis reveals that those micro-mechanisms have seldom been related to each other within the scope of opportunity identification. This chapter closes this gap by discussing and contrasting and the different process categories and respective micro-mechanisms and suggests an integrative theory development and avenues for future research.

We draw from psychological theories of leadership and literature on computer-mediated communication to challenge the received wisdom of the organization change literature about the need to match communication media richness to the equivocality of the task or change situation. We make the counter intuitive proposition that leaner forms of communication can be linked to higher perceptions of leadership charisma and effectiveness even in equivocal situations, and therefore can be more potent in effecting change than richer forms, under certain conditions. We discuss these conditions and the implications for organization change communications.

Scholars frequently address the dyadic relationships between leaders and followers without observing the simultaneity of leadership and followership roles, particularly evident in middle managers. Their implicit and explicit challenges are the foci of this paper.

Introducing technology at work presents a special challenge as learning is tightly integrated with workplace practices. Current design-based research (DBR) methods are focused on formal learning context and often questioned for a lack of yielding traceable research insights. This paper aims to propose a method that extends DBR by understanding tools as sociocultural artefacts, co-designing affordances and systematically studying their adoption in practice.

The iterative practice-centred method allows the co-design of cognitive tools in DBR, makes assumptions and design decisions traceable and builds convergent evidence by consistently analysing how affordances are appropriated. This is demonstrated in the context of health-care professionals’ informal learning, and how they make sense of their experiences. The authors report an 18-month DBR case study of using various prototypes and testing the designs with practitioners through various data collection means.

By considering the cognitive level in the analysis of appropriation, the authors came to an understanding of how professionals cope with pressure in the health-care domain (domain insight); a prototype with concrete design decisions (design insight); and an understanding of how memory and sensemaking processes interact when cognitive tools are used to elaborate representations of informal learning needs (theory insight).

The method is validated in one long-term and in-depth case study. While this was necessary to gain an understanding of stakeholder concerns, build trust and apply methods over several iterations, it also potentially limits this.

Besides generating traceable research insights, the proposed DBR method allows to design technology-enhanced learning support for working domains and practices. The method is applicable in other domains and in formal learning.

This conceptual paper explores a novel model explaining teachers' perceptions of their effective leader through the lens of implicit leadership theory (ILT), using the concepts of school principals' sense-making and cognitive complexity (CC).

The sense-making framework and CC theory were used to explain ILT, which focuses on individuals' perceptions of leaders' prototypical and anti-prototypical attributes.

The theoretical model suggests that school principals as sense-makers with high levels of CC will be perceived by teachers as effective in terms of leadership prototypes, whereas teachers' perceptions of principals with low levels of CC will be related to leadership anti-prototypes.

This paper suggests a model for a multidimensional understanding of the relationship between principals' sense-making and CC and their influence on teachers' perceptions of an effective leader.

Opening avenues for future research into employee perceptions of different leadership characteristics, this model emphasizes the cognitive aspects of school principals within implicit leadership theories. This theoretical model should be further examined empirically, and other types of CC, such as social and behavioral aspects, or affective complexity and self-complexity, should be considered.

Although the literature provides insights into the role of experiential learning based on prototypes in identification of latent customer need, it offers different views on the role of product prototypes in improving the efficacy of learning customer need, and also neglects the role of vicarious learning in prototype-based experiential learning. In a data-rich environment, market big data create new opportunities to learn from vicarious, digitalized experiences that are not observable with prototype-based learning. Therefore, the purpose of this study is to compare the effects of product prototype strategies – basic prototype strategy and enhanced prototype strategy – on identification of latent customer needs, and determine how each prototype strategy interacts with vicarious learning based on market big data to identify latent customer needs.

We collected data from 299 Chinese manufacturing firms via on-site surveys to explore our research question. All of our hypotheses were supported by the regression results.

This study finds that both the enhanced and basic prototype strategies (experiential learning from direct market experience based on prototyping) have positive effects on latent need identification, but the effect of enhanced prototypes is stronger. Furthermore, the enhanced and basic prototype strategies have different interaction effects with market big data (vicarious learning from indirect market experiences) on latent need identification.

This research extends the literature on prototype-based learning for latent need identification. It also contributes to the experiential prototype-based learning literature by exploring the role of vicarious learning based on market big data.

Brand effect is an important source of innovation performance, but rarely any study in the past has paid attention to explore the way firm innovation activities transform into brand effect. The purpose of this paper is to investigate how firm innovation activities transform into brand effect.

A set of hypothesis has been developed to show the relationships among firm innovation activities, brand prototype, brand preference and brand recommendation. The online survey method was used for data collection. In total, 546 valid questionnaires were retrieved. The study used confirmatory factor analysis and structural equation modeling technique to test the hypothesis.

Results indicate that brand prototype leads the process of cognitive processing from innovation activities’ perception to brand preference and recommendation. The consumer perception of process innovation, marketing innovation, product innovation and the store environment have direct impact on brand prototype that further influences product sophistication, brand preference and brand recommendation. But, the most powerful influence is on brand preference. Moreover, product sophistication–attribute-specific brand knowledge has direct impact on brand preference and indirect impact on the brand recommendation. The whole process from brand prototype to brand preference and brand recommendation mainly reflects the strength of the brand effect formation.

This study provides useful managerial insights so that firms can learn the way to maximize brand effect through the management of innovation perception and cultivation of innovation soft capability to enhance innovation performance.

This study unfolds the transformation of firm innovation activities into brand effect that provides a new theoretical explanation and a holistic framework for the source of innovation performance.