Visual Thinking in Entrepreneurship

Master’s Thesis 15 credits Department of Business Studies Uppsala University Spring Semester of 2018

Date of Submission: 2018-08-08

Alisa Hayati Husen Muhammad Umer

Supervisor: Gundula Lucke

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Abstract

The aim of this thesis is to investigate potential links between components of visual

intelligence and visualization in entrepreneurship. The entrepreneurship literature in

literature review helped us to understand that the entrepreneurial activities rely heavily

on the visualization. Furthermore, the Research studies from the field of

neurocognitive science revealed to us a path to build our framework for investigating

the types and characteristics of visual thinking. Additionally, empirical studies on

visualization facilitated our investigation of visual ability in entrepreneurial visualization

activities. In order to fully utilize the theoretical background in our thesis, a quantitative

method with the help of limited quantifications was employed by conducting a web

survey including open-ended and multiple choice questions. Answers from twenty-four

entrepreneurs were analysed in light of findings from previous research on visual

intelligence in other fields of specializations. Thus, the findings of our research

indicated that the use of visuals by entrepreneurs was significantly common (75%).

Moreover, the use of visuals in idea generation, problem-solving and idea presentation

among entrepreneurs in relation with spatial visual intelligence in our study provided

the tenable argument for future work on this field. While it also indicated the gaps and

potential further studies under the subject of visual intelligence and entrepreneurship.

Keywords: Entrepreneurial visual thinking, Entrepreneurship, Visual intelligence,

Visual-spatial ability, Visual-object ability,

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Acknowledgement

We would like to thank our supervisor Gundula Lücke for her continuous support and

courage towards finishing this thesis. Through the discussions and your follow-up,

we were kept motivated. We also want to express our gratitude to Ivo Zander for

providing us the opportunity and the chance to be part of the entrepreneurship

program. His support throughout the program greatly helped us to increase our

knowledge in developing our future ideas. We would also like to thank our families

for their continuous support and patience.

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Table of Contents

Abstract 1

Acknowledgement 2

Introduction 5

Literature Review 7

Entrepreneurship and Entrepreneurs 7 Visualization and Entrepreneurship 8

Visualization in Idea Generation 9 Visualization in Idea Development: Problem-solving and Idea presentation 10 An External Means for Visualization: Whiteboard 11

Visual Intelligence 13 Visual-spatial Intelligence 14 Visual-object Intelligence 15 Visual Intelligence and Visualization in Different Fields of Study 16

Theoretical Framework 18

Methodology 19

Research Design 19 Sample Selection 20 Data Collection and Analysis 21

Filtration and Coding 22 Reliability and Validity 27

Findings 28

Interpretations of The Visuals 28 Kinematic Graphs 29 Artistic Paintings 30

Whiteboard Usage 32

Discussion 34

Conclusion 36

Future Research 37

Bibliography 38

Appendix 44

Question Bank 45 Table 1: Filtration Discerption 49

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Table 2: Filtration Discerption 50 Dataset of Web Survey 50

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Introduction

From the mainstream point of view in media and social networks, entrepreneurs are

referred to as smart individuals, especially the successful ones, but “are they?” or

“even if they are smart in what terms?” These questions were the first sparks in our

minds to start this thesis. Since studies in neurocognitive science have demonstrated

that the nature of the thinking process lies in the way information is visualized or

imagined in the brain (Blazhenkova, 2010; Plassmann, 2012), in this thesis work, we

sought to study the extent and the importance of visual intelligence in

entrepreneurship.

The components of visual intelligence and associated abilities to them have become

a centre of much of neurocognitive research (Blajenkova, 2006; Blazhenkova, 2010;

Kozhevnikov, 2007; Miller, 1986; Miller, 1996; Rosenberg, 1987; Gardner, 1983).

Additionally, Visualization as a form of a mental image of ideas and concepts is

associated with common entrepreneurial practices such as idea generation and

development (Roam, 2012; Osterwalder, 2010; Bresciani, 2013).

Interestingly, despite a large body of research on visual intelligence and visualization

(Eppler, 2007; Walny, 2011; Blazhenkova, 2010; Blajenkova, 2006; Stylianou, 2002),

we found that the influence of visual intelligence has not been substantially studied in

entrepreneurship. This potential new research area motivates us to design our

research with the aim of exploring in one of the least explored areas of study in

entrepreneurship.

Moreover, since the field of entrepreneurship is a relatively new field, there are many

concepts that remain to be explored (Shane, 2000), and the visual thinking process

by entrepreneurs is one of the concepts that remains to be investigated. The initial

questions in our research went through the following list:

• Can we characterize entrepreneurs by their visual abilities?

• How relevant is visual intelligence to entrepreneurship?

• Are there any links between entrepreneurs' visual intelligence and their

visualization practices?

Regardless of the reported broad use of visual intelligence, limited empirical work has

been done towards a better understanding of the processes of visualization and visual

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intelligence among entrepreneurs. Therefore, throughout our data collection and

analysis, we investigated the potential links between visual intelligence and

entrepreneurs’ visualization practices. For more details, we conducted a Web survey

with entrepreneurs from which we collected and analysed the responses. Moreover,

we investigated the visual intelligence of our participants based on their interpretations

of visual arts, graphs, and their whiteboard use. We also compared our findings with

the findings from previous studies of visual thinking abilities in other professions

(Blazhenkova, 2010; Walny, 2011).

Through this thesis, we intended to contribute with a deeper understanding of

entrepreneurs’ characteristics with the particular focus on their visual intelligence.

Such understanding will improve training of entrepreneurs based on their visual

thinking abilities and optimize the visualization techniques in entrepreneurial activities.

Ultimately, this thesis would signal further research in order to bring new perspectives

on entrepreneurship.

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Literature Review

Entrepreneurship and Entrepreneurs

Entrepreneurship with big names like Steve Jobs, Elon Musk, Bill Gates is associated

with big dreams, humble beginnings, and success in the face of doubters (Audia,

2005). Moreover, entrepreneurship is recognized as a set of activities toward the

creation of organizations (Gartner, 1988); However, in order to succeed in

entrepreneurship, entrepreneurs are heavily hinged upon their performances in their

roles and tasks that were undertaken through their job (Chen, 1998). This role and

task perspective of entrepreneurship is built upon three literature review sources.

Firstly, the theoretical economics view which defines entrepreneurship as a process

in which entrepreneurs are signified by their competence, capacities and skills in the

theme of the risk, creativity, opportunities, and managerial competence (Long, 1983).

Secondly, from the technology-based entrepreneurial point of view, the roles and tasks

for entrepreneurs are defined by the major problems in different stages of the growth

as if external relations (e.g., members, advisors), production, sales and marketing,

organizational systems, people(e.g., capable personal), and strategic positioning (e.g.,

new product development) (Kazanjian, 1988). Finally, the motivational pattern

perspective of entrepreneurs’ role can fall into the several components that

characterized the tasks involved in entrepreneur’s role such as self-achievement,

feedback of results, planning for future, personal innovation (Miner, 1993; Miner,

1990).

Furthermore, the interaction between entrepreneurs and their surroundings could also

state the role of an entrepreneur in terms of innovation in strategic management

practices (Gartner, 1988; Carland, 1984). The innovation in strategic practices can

represent itself in a number of forms like a new method of production, opening a new

market, a new good, or industrial reorganization, and so on (Carland, 1984). The idea

generation and idea development phases that clearly exist in all the forms were

mentioned in the process of the innovation management strategic practices; Indeed,

it is the first step of the creation of a venture (Bresciani, 2013; Gardner, 1983; Eppler,

2007). The phases of idea generation and development in entrepreneurship need to

be presented in order to be tangible and clear (Brown, 2010). For this reason, the

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information and knowledge of visualization can support the process of representation

and development of ideas within the venture creation and development process

(Bresciani, 2013).

Visualization and Entrepreneurship

Humans are predominately visual creatures, and most of the incoming information we

receive is visual (Koch, 2004) and entrepreneurs are not an exception. Visualization

is mostly identified as a tool of mental manipulation of spatial configuration which can

demonstrate itself in sets of graphical skills (Schroeder, 2004; Blazhenkova, 2010;

Roth, 1993). Visualization can be defined and differentiated by its formats such as

structure tables in conjunction with text, mental visualization and visual storytelling,

sketches, conceptual diagrams and maps, and graphics interactive environments

(Eppler, 2007; Horn, 1998). Furthermore, it has provided a substantial potential for the

creation of new ideas and enabled innovation at all levels from individual to group. The

knowledge of the visualization methods has also facilitated the propagation and

improvement of ideas (Eppler, 2007). Along with these applications and benefits of

visualization in the entrepreneurship, visualizations are thought to sustain the new

venture during its early vulnerable years (Reynolds, 1987; Star, 1981). Even though

entrepreneurs are fully living in the present, they envision what is to come. As leaders,

entrepreneurs utilize visuals to guide their organizations toward situations that do not

yet exist (Bird, 1989). Into contribution to the process of guiding an organization,

visualizations can be flexible and cost-efficient ways for entrepreneurial activities

(Bresciani, 2013). For instance, in the social entrepreneurship, a simple visualization

framework can demonstrate the visualization’s use in different stages of an

entrepreneurial project (Figure.1).

Idea Generation ------------------------- Idea Development -----------------------------

Figure 1: A sample of visualization framework in entrepreneurial project (Bresciani, 2013)

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Visualization in Idea Generation

Generally, entrepreneurs generate more ideas than opportunities since opportunities

are naturally based on the generation of many ideas (Foo, 2011). The idea generation

process is a critical aspect of innovation, product development, and advertising

(Toubia, 2016). There are several techniques and applications which can stimulate

and facilitate idea generation. Idea generation can break down into several parts such

as idea exchange and sharing which are important parts of group interaction

(Antoszkiewicz, 1992; Galegher, 1990). While the verbal information can make ideas

concrete and manageable, the visualization of ideas like sketching can generate

discussions and collaborations. Moreover, a visual concept of an idea can be led to

refinement and promotion of it (Bresciani, 2013).

In order to have a better understanding of the impact of visualization on the idea

generation process, we focused our review on one of the well-known idea generation

techniques “Brainstorming” which is a common way to generate new ideas in business

(Barringer, 2010). Brainstorming normally starts with freewheeling and a lively session

in which one person expresses an idea or issue then the rest of a group reacts and

responds to it. In such sessions, a flip chart or a whiteboard is used to record the ideas

and observe the session (Barringer, 2010). Adopting a cognitive view of idea

generation, the concept of brainstorming as a cognitive orientation is fundamentally

set to retrieve the associative memory (Wang, 2010; Toubia, 2016). Giving the

structure of memory, a network of interconnected concepts in memory could ease the

retrieving of related concepts (Figure.2). For example, a simple draw of ‘’sun’’ on the

whiteboard may activate a number of concepts such as “summer”, “hot”, and so on.

Therefore, the activation of a concept spreads through the memory network and sets

a cognitive stimulation effect (Nijstad, 2006; Raaijmakers, 1981). In other words, the

visual form of cognitive stimulation can transmit ideas from one participant to another

participant which may lead to novel associations or prime related concepts (Paulus,

2000; Eppler, 2007).

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Figure 2: Socio-cognitive processes of exchanging and expanding ideas with

conversationally retrieved pictures (Wang, 2010).

Visualization in Idea Development: Problem-solving and Idea presentation

The term of visualization used here refers to an action in which an individual

establishes a connection between an internal concept and its external representation

in order to communicate with others (Roth, 1993). Moreover, visualization can be

applied to some external medium such as paper, whiteboard visuals, digital forms of

presentations, etc. (Zazkis, 1996). Whether the format of the visualization involves in-

person contact or computer-based interactions, it can be used for communicating

complex knowledge and knowledge creation. Moreover, in the context of knowledge

management, visualization in basic forms as sketches can benefit problem-solving

potential (Eppler, 2007). An effective problem-solving solution requires a full exchange

of ideas between all group members (Janis, 1977). For instance, in a business

meeting, representatives from different areas or departments often aim to share

knowledge and perspectives to develop new products, directions, or solutions

(Dunbar, 1995; Sutton, 1996). However, corporations often encounter serious

problems in the effective sharing of knowledge between individuals or teams (Fisher,

1998; Tobin, 1998). Therefore, visualization in graphical forms can disseminate and

improve ideas with implicit aspects of the knowledge behind it (Polanyi, 1958; Eppler,

2007). The process of idea generation in a group with help of presentation aids like

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visualization ensures that the set of possible solutions can bridge the problem gap and

materialize decision-making (Söderlund, 2012).

In the realm of research, the arguments that were posed for the use of visual

representations in problem-solving have been backed by studies of cognitive science

(Blazhenkova, 2010; Coskun, 2000). Therefore, during the last decades, many studies

have emphasized the role of visual thinking in the problem-solving process

(Blazhenkova, 2010). This literature review suggests that the use of visual

representations can facilitate problem-solving (Stylianou, 2002). The studies suggest

that visual representations facilitate the problem-solvers’ tasks by extracting relevant

and pre-existing knowledge; moreover, it can facilitate the process of drawing

inferences from new information (Larkin, 1987; Eppler, 2007). However, it is not clear

how visual representations are used in fields like entrepreneurship, and there is not

enough information available about the interrelationship between visualization and

other strategies in the process of problem-solving (Stylianou, 2002).

An External Means for Visualization: Whiteboard

It is hardly possible to understand visual ability without evidence of its existence.

Usually, many external means like whiteboard are used to express ideas and thoughts.

Whiteboards are widely used as a means for transferring internal visualizations to

external visualizations. Indeed, whiteboards are a strong tool for data exploration due

to the fact that they are easy to draw visuals (Walny, 2011). However, studies have

shown that whiteboard users have different types of diagrams with different purposes

as the presentation of problems and idea sharing (Walny, 2011). Therefore, our

drawings and writing on the whiteboard may give indications on our visual thinking

process. Visualization on the whiteboard can be classified by different forms of

applications in visual thinking since the users have different reasons behind their

visualizations on the whiteboard (Zgraggen, 2014; Walny, 2011). Whiteboards as a

means for transferring internal visualization to external visualization is noteworthy for

several reasons (Walny, 2011; Bresciani, 2013; Eppler, 2007):

• Cognition platform for personal and collective purposes

• Group meeting uses for ideas exploitation and problem-solving

• Planning and organizational methods

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Furthermore, Dr. Walny’s research in 2011 investigated the types of visuals provided

a useful categorization of visualization on the whiteboard. The categorization of the

different forms of the visuals on the whiteboard including verbal, verbal and diagram,

diagram has set on distinctive purposes. Furthermore, the personal use or

communication purposes could change the use of visualizations (Walny, 2011). It has

also been argued that the ambiguity of sketches may act as a catalyst for idea

generation, and clarification of ideas (Buxton, 2007). Indeed, the use of visuals in the

form of sketches to diagrams, for knowledge creation and communication are

effectively linked to visual perception thinking (Arneheim, 1980; Eppler, 2007). In order

to form an entrepreneurial perspective of visualization, it was necessary to apply the

theories of visual intelligence to the practical daily performances that we can see in

different professions (Blazhenkova, 2009).

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Visual Intelligence

Overall, intelligence could be referred to as brain-based skills that allows one to bring

reason, plan, and identify solutions for carrying out tasks from which we can define it

as a mental capacity or ability (Gottfredson, 1997).Visual thinking can be defined as a

high level of information processing such as abstract representation and symbolic

deciphering of ideas and objects (Carpenter, 1990; Galton, 1880; Gardner, 1983;

Gottfredson, 1997; Snyderman, 1987). The visual ability can be defined as intelligence

when it plays a functional role on complex and multifunctional tasks in which it can be

stored and tracked (Gardner, 1999; Gottfredson, 1997; Lubinsky, 2004; Sternberg,

1985). Furthermore, having the distinguishable qualitative and quantitative

characteristics from the components of visual intelligence could draw a definition

supported by evidence from cognitive neurological studies (Gardner, 1999;

Blajenkova, 2006; Blazhenkova, 2009; Blazhenkova, 2010).

Cognitive neuroscience studies on the visual thinking process have provided evidence

for two visual thinking pathways: the object pathway and the spatial-related pathway.

The object pathway processes information about the visual pictorial appearances of

objects, and spatial pathway processes information about the spatial relations and

movements of objects (Kosslyn, 1992; Ungerleider, 1982; Blazhenkova, 2009). A

recent study has demonstrated qualitative differences in characteristics of the visual

imagery experiences among members of different professional groups. Most notably

pronounced differences have been identified between visual artists and scientists.

Also, humanities/social science professionals were shown to be more flexible than

scientists or visual artists in switching between spatial and object pathways of

information processing (Blajenkova, 2006; Blazhenkova, 2010). It is possible that

humanities and social science professionals’ imagery is mediated by verbal

processing which allows them a certain level of control and flexibility in image

manipulation (Blazhenkova, 2010) (see also (Vygotsky, 1986).To be more focused on

visual thinking, which is an integral part of our research, it is integral to articulate the

two different pathways of visual processing and their roles in different professions.

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Visual-spatial Intelligence

The characteristics of visual intelligence are mostly associated with the nature of

visual-spatial intelligence from general perspectives. Visual-spatial intelligence is

conceptualized based on imagining objects in a three-dimensional space or dealing

with orientation matters in the space (Carroll, 1993). For example, when the

information process over the movement of objects and the relationship between them

is associated with the visual-spatial ability. Previous studies have designated visual-

spatial intelligence to the dorsal part of the brain (Blazhenkova, 2010). It is also

commonly used as a subcomponent in measuring intelligence e.g. Wechsler

Intelligence Scale (Wechsler, 1997; Roid, 2003). Following the nature of spatial

intelligence, designing tests for evaluation of students based on their spatial ability

have shown that the level of spatial intelligence could be a significant predicting factor

for chances of success among students in a wide range of technical areas.

Furthermore, such tests can be used to predict performance among engineers,

mechanics, and physics (Ghiselli, 1973; Hegarty, 1989; Holliday, 1943; Kozhevnikov,

2006; Smith, 1964).

Previous researchers have stated that spatial ability tests can reflect visual-spatial

working memory capacity (Miyake, 1991; Shah, 1996). From this perspective, people

that have different levels of spatial abilities are also different in their ability to solve

problems that involve multiple spatial parameters (Kozhevnikov, 2007). Meeting the

criteria of the intelligence measurements requires ecological validity, abstract thinking

and distinctive qualitative and quantitative properties (Gardner, 1999; Gottfredson,

1997; Lubinsky, 2004; Sternberg, 1985). Individuals with high levels of spatial

intelligence are classified as the visual-spatial visualizer. The visual-spatial visualizers

are capable to use their imagery to transform and represent spatial relations

(Blazhenkova, 2010). The embodiments for this talent are an American theoretical

physicist Richard Phillips Feynman who was also a noble laureate in physics. In the

series of science lectures at the Cornell University under the title of ‘’Messenger

Lectures’’, he presented complicated concepts of physics using his visual-spatial

abilities to simplify very complex matters (Picture 1).

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Picture 1: Feynman is using visuals in context of physics

Visual-object Intelligence

Another component of visual intelligence is visual-object intelligence which represents

visual processing information of object properties. This aspect of intelligence is

associated with the ventral part of the brain (Motes, 2008). It involves processing

object properties and structure in terms of appearance, colour, shape, size, texture,

and brightness. In contrast, the spatial ability involves the movement of objects in

space. The character of highly visual-object intelligent individuals lies in their ability to

use imagery to construct accurate and clear images of the visual properties

(Kozhevnikov, 2002; Kozhevnikov, 2005)

In relation to different specializations, experimental studies have suggested that the

visual-object ability has its own unique ecological validity. In order to establish the

ecological validity for visual-object ability, Blazhenkova has published notable results

which indicates that the object ability has a specific relationship with different areas of

specializations (Figure 3) (Blazhenkova, 2010). The study examined 141 college

students from different majors. They were assessed for their visual-object and visual-

spatial abilities. The visual-object ability could explain the success in visual arts and

other fields that require a generation of high-resolution and vivid imagery.

U.S. DEPARTMENT OF ENERGY, WIKICOMMONS

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Figure 3: Relationship between object ability and specifc fields (Blazhenkova, 2010)

Figure 3 shows that visual art professionals have more distinguishable visual object

abilities based on three distinctive tests, namely: visual imagery questionnaires: The

VVIQ (Marks, 1973) is a frequently used self-report measure of the vividness of one’s

visual mental images., Degraded pictures test (DPT) (Blajenkova, 2006), This test was

designed to assess the ability to solve perceptual closure tasks that require identifying

objects obscured by noisy backgrounds., and Object-Spatial imagery questionnaire

,The OSIQ is a self-report questionnaire designed to assess individual preferences

towards, and abilities in, using visual- object versus visual-spatial imagery

(Blajenkova, 2006)

Visual Intelligence and Visualization in Different Fields of Study

Drawn upon recent studies (Blajenkova, 2006; Kozhevnikov, 2010; Blazhenkova,

2009) and inter-correlations of measurements through a varied set of data, it has been

found that visual-spatial ability and visual-object ability have different sets of

relationships with different areas of specializations. Growing number of evidence

supported by new research has demonstrated that the different professions have a

different portfolio of visual intelligence. Each of the two components of the visual ability

has its own volume of influence and role to play in certain professions (Blazhenkova,

2010; Miller, 1996; Kassels, 1991; Roe, 1975; Rosenberg, 1987; Winner, 1985). For

instance, visual artists set their imagery ability more in pictorial details that

demonstrate their visual-object ability. Whereas scientists are organizing their imagery

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based on abstract schematics that indicate their visual-spatial ability. In addition, the

humanities and social professional were more along with the line of imagery ability of

scientists than artists. Nonetheless, there are notable un-explored areas of

specializations as entrepreneurship in this area of research (Lindauer, 1983;

Blazhenkova, 2010; Blajenkova, 2006).

Furthermore, visualization plays a central role in conceptualization processes of major

discoveries such as Galileo’s laws of motion or Einstein’s theory of relativity, has found

extensive use of visual-spatial reasoning in these discoveries (Miller, 1986;

Nerssesian, 1995; Shepard, 1996). Scientists view their mental images as tools to be

used for effective problem-solving because they are easily accessed and discarded.

On the other hand, humanities/social science professionals have reported that they

generate uncontrolled object images when they are triggered by stimuli such as highly

descriptive text. However, in addition to text-triggered uncontrolled images, they also

generate controlled spatial images in order to solve or analyse problems that contain

complex verbal structures (Blazhenkova, 2010). Extending the scope of visualization’s

use in different areas of specialization, scientists more utilize visualization

transformation knowledge from the external world while artists use the graphic imagery

for communication along with the generation of concepts in the form of art (Roth,

1993). In contrast, entrepreneurs utilize visualization more in terms of knowledge

management as if representation and development of ideas, dissemination of

knowledge, and planning (Eppler, 2007; Bresciani, 2013).

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Theoretical Framework

Throughout our research’s theoretical framework, we studied that the innovation in

strategic management practices can state the role of entrepreneurs (Gartner, 1988).

Moreover, the idea generation and its development (problem-solving and idea

presentation) have undeniable roles in these practices which can be supported by

visualization (Brown, 2010; Bresciani, 2013). Visualization in entrepreneurial activities

can facilitate the process creation of new ideas and enable innovation through the

practices that are taken in entrepreneurial projects (Bresciani, 2013; Eppler, 2007).

Additionally, studies on the means of visualization like whiteboard showed an effect

link between visual perception thinking and visualization (Arneheim, 1980; Eppler,

2007; Walny, 2011; Buxton, 2007) From another angle, studying the visual intelligence

and its components gave us a better understanding of the conceptualization process

by visuals which can lead to the discovery of new ideas and the generation of solutions

for problems (Blazhenkova, 2010; Blazhenkova, 2009; Blajenkova, 2006). Therefore,

these standpoints and the knowledge we grasped from the literature review in our

thesis provided us a theoretical ground based on which we applied our aim of

analytical approaches and conducted the investigation for our findings as shown in the

figure below.

Figure 4: The theoretical framework of our thesis

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Methodology

In this section, we described our research design which provides us with a framework

for the collection and analysis of data. Furthermore, the techniques that were used to

analyse our data are presented in the data collection and analysis subsection, and in

the very end of this section, we described the steps to ensure reliability and validity of

our results.

Research Design

Given our study aim to find potential links between visual intelligence components and

entrepreneurship visualization usage, we decided to design our quantitative research

methodology based on two previous studies, hereafter named linked-studies, which

were conducted on visual intelligence and visualization on the whiteboard

(Blazhenkova, 2010; Walny, 2011). In this work, in order to collect data, we set a panel

of questions with a specific focus on entrepreneurs from different backgrounds. We

used quantitative methods to collect our data from the entrepreneurs around the globe

in a form of Web survey, and we employed quantitative methods techniques to analyse

our data.

Owing to the nature of visual intelligence as an internal process with external contents,

we set a panel of open-ended and multiple choice questions in our Web survey to

enable ourselves to analyse the quantitative differences among the responses that we

collected in the Web survey. However, limited-quantification were used for

demographic information about our participants and commonality in their behaviour.

During our data analysis , we laid out a set of filters and codes for our data collection

to analyse our data in conjunction with the results from the linked-studies. Further in

this section, in order to avoid unnecessary complexity, we defined our data collection

system in detail with a clear demonstration of the filtrations and codes that were

applied in our analysis. Moreover, the linked-studies have provided a valuable set of

analytical approaches from which we set our analysis (Blazhenkova, 2010; Walny,

2011). Additionally, it provided us the chance to have a vehicle for a new database

from which we could study the relation between visual intelligence and

entrepreneurship.

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Sample Selection

Since our aim was to collect data about the visual ability of entrepreneurs, we

implemented a purposive sampling strategy. Therefore, we based our sample

selection on LinkedIn profiles in order to identify potential respondents.

The following conditions were set to be met in order to send invitations (web-links) to

our respondents for the Web survey:

1. The current work status of participants should be related to entrepreneurship

2. The set of skills on participants’’ profiles should contain entrepreneurial skills

3. Their work experience should be related to entrepreneurship.

Applying the selection condition, eventually, we managed to conduct our Web survey

among 24 entrepreneurs from 31 invitations sent.

In the similar vein, we designed a question in our Web survey through which

participants had the chance to define themselves as entrepreneurs and those who are

likely to be called entrepreneurs (Figure 5 (A)).

Furthermore, in our study, a possible source for confounding was the educational

background of the participants since it has been shown that different professions have

different visual abilities (Blazhenkova, 2009; Blazhenkova, 2010). In order to

overcome the confounding effect within our sample selection, we did make sure that

our samples are from different backgrounds, and we are not just looking at one of the

backgrounds. We included a specific question in our Web survey to determine the

educational background of the entrepreneurs as it demonstrated in Figure 5 (B). Our

samples were from different backgrounds, and there was a minimum confounding

effect on our observations.

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Figure 5: (A) percentage of respondents who defined themselves as entrepreneurs or

potential entrepreneurs. (B) The educational backgrounds of the entrepreneur respondents.

Data Collection and Analysis

Our data collection is based on the questions that were answered by those who were

defined as entrepreneurs. Indeed, we applied specific modifications in our Web survey

to meet our goals in the thesis. In order to focus on entrepreneurs in our Web survey,

we designed our questions more related to the entrepreneurial environment with

respect to the origin of our questions in previous studies on the visual intelligence

(Walny, 2011; Blazhenkova, 2010). On this basis, our survey’s question panel

consisted of three sections:

1. Demographical questions (multiple choice questions)

In this section, we first provided a brief of what is the purpose of this survey and how

the participant can get through it. After an introduction to the survey, we wanted to

clarify the position of the respondents over the subject of entrepreneurship from their

professional viewpoints. We asked for their demographic information including their

age and their educational background, and this helped us to classify our data.

2. Visual intelligence questions (open-ended questions) In the second section of the survey, we led our respondents through a series of visual

questions obtained from the previous studies (Blazhenkova, 2010). The questions

Total number of participants: 24

A B

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were designed for the investigation of the components of visual intelligence through

simple tasks to follow. This section was further divided into two subsections:

• Evaluation of visual-spatial intelligence: the respondents were asked for their

interpretations of two kinematic graphs (double- index chart). The goal was to

understand their visual thinking about the motion of objects via schematic

presentation.

• Evaluation of visual-object intelligence: the respondents were asked to

elaborate on their personal interpretations of two paintings. From their

interpretations, we had the chance understand the entrepreneurs’ perspective

on the complexity of abstract arts.

3. Visualization questions (multiple choice and open-ended questions)

The last section of the survey focused on the interaction between the respondents and

the whiteboard to understand how they utilized their visual abilities on the whiteboard.

It was specifically designed for understanding to what extent they are interacting with

the whiteboard in terms of visualization and what are participants’ main purposes and

how responses can be related to their visual intelligence. Our questions were designed

for investigating visualization applications on the whiteboard and connect them to

visual intelligence components. Considering the ultimate goal of the thesis, the data

analysis phase has a close interdependent relationship with the linked-studies on

visual thinking. Our analysis in this thesis was drawn upon the filtration and the coding

structure referring to the linked-studies (Blazhenkova, 2010; Walny, 2011). The whole

structure of our assessment could be broken down into the following four tables. Each

of the tables was exclusively designed for analysing visual intelligence and

visualizations.

Filtration and Coding

The structure of our filtration and coding was designed to represent the criteria based

on which we carried out the analyses of our responses. It also indicates the bases of

our analysis structure and the assessment points which enabled us to discover the

findings of our thesis.

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Guiding table for spatial and object visual intelligence

This table is one of the key tools for investigating the links between the entrepreneurs’

visualization approaches and their visual abilities. Applying the components of this

table enabled us to investigate the entrepreneurs’ interpretations of interaction with

visuals and the entrepreneurs’ visualization usage.

Table 1: The filtrations and assessments of the responses are outlined below.

Visual intelligence components

Distinguishable active elements

Assessment structure Filtrations

Visual-Spatial Intelligence

• Spatial visualization

• Spatial relations

• Material present in space

• Orientation in space

• Ability to process object

in space

• Similarity between

visual interpretations

and distinguishable

elements of visual

components

• Similarity between

textual responses

and description of

the visual ability

• Context analysis with

peer group

1. Highly related

to visual-spatial

ability

2. Potentially

related to

visual-spatial

ability

3. Irrelevant to

visual-spatial

ability

Visual-Object Intelligence

• Visual appearance

process.

• Define pictorial

properties.

• Construct high-resolution

imagery images.

• Similarity between

visual interpretations

and distinguishable

elements of visual

components

• Similarity between

textual responses

and description of

the visual ability

• Context analysis with

peer group

1. Highly related

to visual-object

ability

2. Potentially

related to

visual-object

ability

3. Irrelevant to

visual-object

ability

24

Kinematic graphs

Two kinematic graphs in our Web survey were designed for examining the different

approaches among entrepreneurs towards a complex form of visual tasks. Our respondents’ interpretations about what is happening in the graphs and our

comparison of their responses with the intended meaning of the graphs allowed us to

have a better understand their visual ability.

Table 2: The filtrations and assessments of the responses are outlined below.

Graphs Original meaning Assessment structure Filtrations

A

Original chronological

description:

The object is initially

stationary. Then it

moves with constant

velocity and then it is

stationary again

• Similarity between

chronological

descriptions and the

original meaning.

• Context analysis in

conjunction with

Table 1

1. Pictorial

interpretation

2. Irrelevant

interpretation

3. Abstract

schematic

interpretation

B

Original chronological

description:

The object is moving

with constant

acceleration, then it

reaches constant

velocity, and finally, it

moves with constant de-

acceleration

• Similarity between

chronological

descriptions and the

original meaning.

• Context analysis in

conjunction with

Table 1

1. Pictorial

interpretation

2. Irrelevant

interpretation

3. Abstract

schematic

interpretation

25

Paintings

Table 2 was designed to help us assess the participants’ responses to the painting-

questions. It enabled us to examine their interpretations of abstract visual-object

information.

Table 3: The filtrations and assessments of the responses for the paintings are

outlined below.

Painting Original meaning Assessment structure

Filtrations

A

Artist:

L. Berryhill,

Name:

‘’Breakthrough’’

Represents the idea

of liberation through

adversity

• Similarity of

description to

the original

meaning

• Context analysis

in conjunction

with Table 1

1. Pictorial

interpretation

2. Irrelevant

interpretation

3. Abstract and

conceptual

interpretation

B

Artist:

W. Kandinsky

Name:

‘’Kleine Wekten’’

Represents the idea

of a plan for utopian

city and life within.

• Similarity

between

description to

the original

meaning

• Context analysis

in conjunction

with Table 1

1. Pictorial

interpretation

2. Irrelevant

interpretation

3. Abstract and

conceptual

interpretation

26

Visualization

This subsection of the filtration and coding was set to identify possible links between

entrepreneurs’ visualization interactions with whiteboards and the visual intelligence.

Therefore, we set 4 steps to investigate our respondents’ visualization behaviour with

whiteboards.

Table 4: The filtrations and assessments of the responses visual interaction with

whiteboard are outlined below.

Investigation steps

Description Assessment structure

Commonality This step focuses on how often

entrepreneurs use the whiteboard.

We analysed the frequency and commonality of the whiteboard usage by designing a multiple-choice question.

Purposes

The question inquiries about the

entrepreneurial purposes to use

visualization on the whiteboard

The choices of the open-ended question with

preferable choices was built upon the

entrepreneurial the concept of visualization from

literature body of our thesis, and further we

analysed the content of answers and its

frequency.

Type of visualization

This step was focused on investigating

which visual structure was the most

commonly used

Using the open-ended questions with preferable

choices helped us to link between the outcomes

of the purposes’ question and this question in

conjunction with Table 1.

The spectrum of word-diagram

we set a multiple choice question based

on previous studies on the whiteboard

and visual thinking (Walny, 2011). This

question represented the visuals on the

whiteboard form only textual to only

diagrams visuals in the form of a

diagram by representing 8 possible

models of word-diagram visuals.

We analysed The responses to the multiple

choice question based on the word-diagram

spectrum in our text-diagram question. the scale

structure of 1 to 8 from the only text visual to the

only diagram on the whiteboard gave us a tool to

investigate the content of the visuals in

visualization on the whiteboard among the

entrepreneurs in our study.

27

Reliability and Validity

In order to represent the trustworthiness of this research, prior to the Web survey, the

potential participants corresponded via mail and social network in order to certify that

their information is correct, and they have received the web link of our survey. This

verification structure allowed us to discuss the interpretation of the answers with more

certainty and reliability. In our data analysis, a cross-study comparison was used in

order to enhance the structure of the collected data. This configuration helped us to

improve the accuracy of our results which eventually led us to discover findings that

were hidden in the data.

28

Findings

Based on the structure of our data collection and analysis, the findings from our Web

survey can be divided into two main categories.

First, the findings from the analyses of responses to our graphs and paintings

questions from a group of entrepreneurs. Those questions were designed to

investigate the entrepreneurs’ visual intelligence ability. Furthermore, the results were

compared with other professionals that have been asked the same questions in a

previous study in the discussion section (Blazhenkova, 2010).

Second, the findings from our coding and filtration applied to our respondents’

visualization interaction with the whiteboard. The goal was to find potential links

between the respondents’ interactive behaviour with the whiteboard and their visual

intelligence.

Interpretations of The Visuals

In order to evaluate the visual thinking of entrepreneurs, we showed them two

kinematic graphs and two paintings. The abstract interpretation of the kinematic

graphs demonstrates what is happening in the graph in terms of spatial relations in

space which further classified as visual-spatial ability among participants. On the other

hand, the abstract interpretation of the paintings indicates the meaning of the paintings

and the conceptualization of the idea behind the painting. The reasons for showing

two graphs and two paintings were to confirm the answers and improve the reliability

of the findings. The participants were given space to express their opinion freely

without any limits to achieve unbiased results.

29

Kinematic Graphs

Kinematic graphs were used to demonstrate the properties of objects’ motion in space.

We analysed the responses to indicate the type of visual intelligence aspect that was

dominated in their interpretations (3.3.1.1). While describing the graph as merely going

down and up refers to a pictorial description of the graph, the description of the

movement of an object in space was associated with spatial descriptions. Noticeably,

the percentage of entrepreneurs that gave an abstract concept of the graphs was on

average twice more than those that gave a pictorial description (62.5% versus 31.2%)

(Figure 6). Three responses were categorized as irrelevant because either they had

not described their text sufficiently or their words were irrelevant.

Figure 6: Graph interpretation by entrepreneurs.

Some of the entrepreneurs provided abstract interpretations from the business point

of view. For instance, one described the graph as: “It can be about a reduction of

service quality and bad performance of support a marketing team for retention of

users. Also, at the same time growth of competitor can tend to be losing market

share.”. And another respondent related it to marketing by indicating “Marketing

campaign can show this growth (such as promotion). Or a good advantage to

comparison with competitors in a period of time”. The importance of making such

interpretations in the context of firm growth shows the high ability of entrepreneurs in

abstract thinking.

0%

10%

20%

30%

40%

50%

60%

70%

Abstract Pictorial Irrelevant

30

Artistic Paintings

Considering the structure of our abstract-art question, which was designed to

investigate the relation between the entrepreneurs’ interpretations of abstract

paintings and their visual intelligence. We showed our participants two paintings. First,

Painting ‘’A’’ from a collection of W. Kandinsky’s works of arts which represented the

idea of liberation through adversity. Second, Painting ‘’B’’ from L. Berryhill features the

idea of a plan for utopian city and life. In our Web survey, the entrepreneurs were

asked to decipher the meaning of the painting from their own perspectives and name

it. Additionally, throughout our analysis of the responses about painting “A”, we found

that the abstract thinking based on spatial intelligence ability possessed 58 percent of

our responses. On another hand, the object visual interpretation gained only 25

percent of the responses. an interesting observation was that some of our participants

tried to elaborate and describe the painting with spatial and abstract words related to

the entrepreneurship. For instance, one of the entrepreneurs described it as: ‘’the

entrepreneur as a kick-starter that use its wings to disrupts and breaks markets’’.

Figure 7: Entrepreneurs’ responses to the abstract art question about a painting by L. Berryhill.

31

In the second part of our abstract art question, our initial result from analysing the

respondents’ descriptions relativity with the original concept of Painting “B” indicated

a few noticeable outcomes. Firstly, only two distinct respondents mentioned that the

painting represents existing ideas in an abstract form by relating it to “life”. Secondly,

the same number of participants associated the painting to their feelings, and they

described it as ‘’cheerful mood’’ or “generation of positive emotions”, and both were

classified as object-visual thinkers. From another point of view, interestingly, three of

the respondents associated their description to their professional experiences.

Overall, the result of the analysis of the responses demonstrated that fifty-four

percentage of responses were classified as spatial-visual thinkers based on their

abstract interpretations of the painting. For instance one of respondent described that

“a busy mind with full of non-classified idea which like to go on a vacation to get

relaxing and do them later.” While the abstract interpretations in our study were more

focused on the meaning of the painting, the pictorial interpretations with 29% of total

responses in the study were more often focused on appearance features in the

painting rather than the concept behind it. However, a number of the spatial thinkers

in our entrepreneurial group have shown in-depth interpretations associated with their

entrepreneurial work environment. This finding inspired us to be more curious for

further investigations on this subject.

Figure 8: Entrepreneurs responses to the abstract art question about a painting by L. Berryhill.

32

Whiteboard Usage

In the whiteboard-usage questions, we aimed to investigate the relationship between

visualization on the whiteboard and visual intelligence. Therefore, we started our

investigation with the commonality of the whiteboard usage among the entrepreneurs,

and we found that the number of respondents who claimed that they use whiteboard

‘’always’’ or ‘’never’’ was the same number among respondents. In contrast, the

number of respondents who claimed that they were using whiteboard ‘’often’’ or

‘’sometimes’’ was around 75 percent of our responses.

After these findings, we sought for the purpose of whiteboard usage in our Web survey,

the number of respondents who stated that they were using the whiteboard for idea

generation as the main purpose was 62.5 percent of the responses. Moreover, the

second most common purpose of use among the entrepreneurs was designated for

problem-solving (58.3 percent of the answers). Finally, the third main purpose of the

whiteboard usage among our participants was “Idea Presentation” based on 45

percent of the responses.

In the next step, we analysed the responses to the particular open-ended and multiple

choice questions about the entrepreneurs’ perspectives of visualization on the

whiteboard. Interestingly, the results of the entrepreneurs’ responses in our Web

survey demonstrated that they most often used graph visualizations (mind-mapping)

by 54 percent which can be interpreted as an index of spatial thinking. With the help

from the guiding Table 1 shown in methodology section in conjunction with the

responses to the questions about the type of visuals and their visualization

preferences on the whiteboard, we found that entrepreneurs were more willing to

prioritize the spatial relations between concepts of their idea over visual appearances

in their visualizations. This pattern of behaviour in the majority of entrepreneurs (54%)

can be classified as spatial-visual thinking than object-visual thinking.

Furthermore, a specific question about the usage of words on the whiteboard enabled

us to estimate the respondents’ position on the spectrum of word-diagram visualization

schema. Thus, we found that only one of the participants claimed using only words on

the whiteboard, and none of our respondents were using non-word diagrams on the

whiteboard. Additionally, the results indicated that 62 percent of entrepreneurs use

33

integration of word and diagram on the whiteboard which was at 6th scale on the

spectrum of word-diagram shown in the figure below.

Figure 9: The Position of entrepreneurs’ responses on the spectrum of word-diagram

assessment.

Overall, the words and constructions of visuals in the entrepreneurs’ whiteboard

usage inspired us to introduce this hypothesis that the integration of the keywords

and spatial constructions of visualization can be classified as a visual-spatial ability

with textual stimuli. According to the result of our word-diagram scale based on the

responses of entrepreneurs to the word-diagram question in our Web survey, 62

percent of entrepreneurs stated that their visuals on the whiteboard have a

considerable portion of textual content. Indeed, it also raised this question about

how the verbal context was used as a trigger or a stimulus in the visualization

among entrepreneurs. Considering the most common types of visualizations

among entrepreneurs in our study, they more often were focused on elements

visualization that helped them to draw spatial connection instead of focused on

pictorial features; However, seemingly, texts are integral parts of their

visualizations.

1 2 3 4 5 6 7 8

34

Discussion

Despite the large body of knowledge about entrepreneurship, many of its aspects

remain to be explored. Here, we have borrowed the concept of visualization from the

entrepreneurship literature body in conjunction with neurocognitive science studies in

order to examine the possible links between visual intelligence and visualization in

entrepreneurship.

From our literature review, we learned that the innovative practices are integral parts

of the entrepreneurial activities (Carland, 1984; Gartner, 1988). Moreover,

visualization in the process of idea generation has a significant impact on the

innovation (Toubia, 2016). Therefore, the idea generation as an inseparable part of

these practices can benefit from visualization as an executive means (Bresciani,

2013). In the same way, our findings from the result of the whiteboard section in our

Web survey showed that 75 percent of entrepreneurs in our study used “often’’ or

“always” whiteboard as a visual platform for their work. Furthermore, the entrepreneurs

in our study also claimed that their first priority for using visualizations on the

whiteboard was the idea generation (62.5 percent).

From another angle, as it was reviewed in the literature body, the visualization even in

simple forms like sketch can lead to refinement and development of ideas (Bresciani,

2013). Indeed, the studies proposed that the visualization by extension of relevant

information and knowledge can facilitate the process of problem-solving (Larkin, 1987;

Eppler, 2007). Furthermore, the presentation of ideas and information in visual forms

can facilitate strategic practices such as problem-solving in entrepreneurship

(Stylianou, 2002). By the same token, the findings in our study on the intention of using

visualization on the whiteboard among entrepreneurs indicated that, in alignment with

the previous studies, the problem-solving and idea presentation are the second and

third most common purposes for using visualization among entrepreneurs. In more

details, 58.3 percent of entrepreneurs in our Web survey expressed that they use the

whiteboard for problem-solving as the second aim of visualization on the whiteboard,

and 45 percent of entrepreneurs in our study stated that the idea presentation as the

third aim of use.

In our studies on the visualization usage, we learnt that verbal and textual information

make ideas concrete and manageable. Additionally, different forms of visualization

35

can contain text for a verity of reason (Walny, 2011; Bresciani, 2013). From this

learning point of view, our findings from our Web survey in respect of the word-diagram

spectrum specified that the entrepreneurs largely used the visualization in conjunction

with words. Our findings indicated that the most common type of visualization among

entrepreneurs was mind-mapping by 54 percent which inherently included text in its

structure. Moreover, 62 percent of our participants stated that their visuals on the

whiteboard have a substantial portion of textual content. These findings in respect to

previous studies gave us a new perspective of integration of text and visualization in

entrepreneurial activities and enforce the concept of textual uses in the visualization

(Bresciani, 2013; Eppler, 2007).

In addition to visualization studies, we also applied another component to our

theoretical framework, the cognitive neuroscience studies on visual intelligence. The

studies on cognitive neuroscience in our literature review showed that different areas

of specializations have different visual abilities (Blazhenkova, 2010; Blajenkova,

2006). For instance, according to the previous study in this area, scientists organize

their imagery based on abstract schematics from which they were classified as spatial-

visual thinkers. On the contrary, artists are more likely to set the imagery in terms of

pictorial details from which they were classified as visual-object thinkers (Blazhenkova,

2010). From the visual intelligence point of view, our findings from the result of 4

questions in relation to visual intelligence indicated that 62.5 percent of entrepreneurs

widely responded to the complex form of visual tasks more closely to scientists as

spatial-visual intelligent. It showed that entrepreneurs in our study are more likely to

focus on spatial relation than pictorial features based on their responses to whiteboard

usage.

Moreover, in response to abstract art questions in our Web survey, on average 56

percent of entrepreneurs’ interpretations were classified as the abstract interpretation

which associated with spatial-visual thinking. Furthermore, following the dominate

spatial-visual thinking among entrepreneurs in our study, the finding from the analysis

on the responses in whiteboard questions in our survey revealed that entrepreneurs

are more focused on the spatial relations in their visualization on the whiteboard than

pictorial features. On the other hand, these findings indicated that entrepreneurs are

more relying on the spatial-visual intelligence than pictorial-visual intelligence;

36

However, it is still a question about how their visual intelligence can lead them to

certain interpretations.

Conclusion

Despite the large body of literature about visualization and visual intelligence, there is

little known about how visual intelligence can influence entrepreneurs’ performances.

In this thesis, we investigated the potential relationship between visual intelligence and

entrepreneurship with the help of the visualization on the whiteboard. Throughout our

study, we distinguished different components of visual intelligence along with the use

of visualization in entrepreneurship. This standpoint of visualization provided a broader

understanding of the entrepreneurs’ visual thinking process in relation to idea

generation and development in entrepreneurial activities. Our findings reinforced that

the idea generation and idea development in the form of problem-solving and

presentation of the ideas are most important purposes for using visuals among the

entrepreneurs. Furthermore, the analyses of the data were collected through the Web

survey in our study indicated that the components of visual intelligence have notable

roles in the entrepreneurs’ visual interpretations and their usage visualization. We

found that the spatial-visual thinking is more common than object-visual thinking

among entrepreneurs in their interaction with visuals. Moreover, the result of our study

on the visualization on the whiteboard demonstrated that spatial relations in the visuals

on the whiteboard are far more important than pictorial features of visual for the

entrepreneurs. Our findings demonstrated minimal resources with satisfactory results.

We believe that further work and studies on the relationship between visual

intelligence and entrepreneurial activities will produce a new perspective of

entrepreneurship.

37

Future Research

Due to the time constraints and the novelty of our research topic in the field of

entrepreneurship we had to prioritize our tasks and limited our investigation to certain

criteria and a number of entrepreneurs. Therefore, there are possibly many points that

could be improved in future research in this direction. Although we have taken

reliability measures but still obtaining answers from entrepreneurs in face-to-face

interviews or performing direct tests on the concept of visual thinking will provide

further evidence of the findings in this study. We also recommend further

investigations of the visual thinking process, particularly in the idea development.

38

Bibliography

Antoszkiewicz, J., 1992. Brainstorming: Experiences from two thousand teams. Organization Development Journal.

Arneheim, R., 1980. A plea for visual thinking. Critical Inquiry, p. 489–497.

Audia, P. a. R. C., 2005. A garage and an idea: what more does an entrepreneur need?.. California Management Review, Issue 48(1), pp. 6-28.

Baron, R. A., 2006. Opportunity Recognition as Pattern Recognition: How Entrepreneurs “Connect the Dots” to Identify New Business Opportunities. Academy of Management Perspectives, pp. 104-119.

Barringer, E. &. I. R. D., 2010. Successfully Launching New Ventures. s.l.:Pearson.

Bird, B., 1989. Implementing Entrepreneurial Ideas: The Case for Intention. The Academy of Management Review, 13(3 ), pp. 442-453.

Blajenkova, O. K. M. &. M. M. A., 2006. Object–spatial imagery: A new self-report imagery questionnaire. Applied Cognitive Psychology, p. 239–263.

Blazhenkova, O. &. K. M., 2009. The new object‐spatial‐verbal cognitive style model: Theory and measurement. Applied cognitive psychology, pp. 638-663.

Blazhenkova, O. &. K. M., 2010. Visual-object ability: A new dimension of non-verbal intelligence. Cognition. pp. 276-301.

Bresciani, S. a. E. M., 2013. Knowledge visualization for social entrepreneurs.. 17th International Conference IEEE, pp. 319-324.

Brown, T. a. W. J., 2010. Design thinking for social innovation. Stanford Social Innovation Review, Issue 8(1), pp. 30-35.

Buxton, B., 2007. Sketching user experiences: getting the design right and the right design. San Francisco, CA: Morgan Kaufmann.

Carland, J. W. .. H. F. .. B. W. R. &. C. J. C., 1984. Differentiating entrepreneurs from small business owners: A conceptualization. Academy of Management Review, Issue 9(2), pp. 354-359.

Carpenter, P. A. J. M. A. &. S. P., 1990. What one intelligence test measures: a theoretical account of the processing in the Raven Progressive Matrices Test. Psychological review, p. 404–431.

Carroll, J., 1993. Human cognitive abilities: A survey of factor-analytical studies. New York: Cambridge University Press.

Chen, C. G. P. a. C. A., 1998. Does entrepreneurial self-efficacy distinguish entrepreneurs from managers?. Journal of business venturing, Issue 13, pp. 295-316.

39

Coskun, H. P. P. B. V. a. S. J., 2000. Cognitive stimulation and problem presentation in idea-generating groups. Group Dynamics: Theory, Research, and Practice, Issue 4, p. 307.

Dunbar, K., 1995. How scientists really reason: Scientific reasoning in real-world laboratories. Cambridge, MA: MIT Press.

Eppler, M. a. B. R., 2007. Visual representations in knowledge management: framework and cases. Journal of knowledge management, Issue 11(4), pp. 112-122.

Fisher, K. &. F. M. D., 1998. The distributed mind. New York: Amacon.

Foo, M. D., 2011. Teams developing business ideas: how member characteristics and conflict affect member-rated team effectiveness. s.l.:Small Business Economics.

Galegher, J. K. R. a. E. C., 1990. Intellectual teamwork: Social and technical bases of collaborative work. s.l.:Lawrence Erlbaum Ass.

Galton, F., 1880. Statistics of mental imagery. Mind, 5(19), pp.301-318.

Gardner, H., 1983. Frames of mind: The theory of multiple intelligences. New York: Basic Books.

Gardner, H., 1999. Intelligence reframed: Multiple intelligences for the 21st century. New York: Basic Books.

Gartner, W., 1988. “Who is an entrepreneur?” is the wrong question. American journal of small business, Issue 12(4), pp. 11-32.

Ghiselli, E. E., 1973. The validity of aptitude tests in personnel selection. ersonnel Psychology, p. 461–477.

Gottfredson, L. S., 1997. Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography. Intelligence, p. 13–23.

Hegarty, M. &. J. M. A., 1989. Understanding machines from text and diagrams. In H. Mandl & J. Levin (Eds.), Knowledge acquisition from text and picture. Amsterdam: North Holland.

Holliday, F., 1943. The relation between psychological test scores and subsequent proficiency of apprentices in the engineering industry. Occupational Psychology, p. 168–185.

Horn, R., 1998. Visual Language: Global Communication for the 21st Century. Bainbridge Island, WA: MacroVU Press.

Janis, I. &. M. L., 1977. Decision making: A psychological analysis of conflict, choice, and commitment. New York: Free Press.

Kassels, S., 1991. Transforming imagery into art: A study of the life and work of Georgia O’Keeffe. In R. G. Kunzendorf (Ed.). Mental imagery, p. 45–52.

40

Kazanjian, R., 1988. Relation of dominant problems to stages of growth in technology-based new ventures. Academy of Management Journal, Issue 31, p. 257–279.

Koch, C., 2004. Quest for consciousness: A neurobiological approach. Englewood, CO: Roberts & Company Publishers.

Kosslyn, S. M. &. K. O., 1992. Wet mind: The new cognitive neuroscience. New York: Free Press.

Kozhevnikov, M. &. T. R., 2006. Real-time data display, spatial visualization ability, and learning force and motion concepts. Journal of Science Education and Technology, p. 113–134.

Kozhevnikov, M. B. O. &. B. M., 2010. Trade-off in object versus spatial visualization abilities: Restriction in the development of visual-processing resources. Psychonomic Bulletin & Review, p. 29–35.

Kozhevnikov, M. H. M. &. M. R. E., 2002. Revising the visualizer–verbalizer dimension: Evidence for two types of visualizers. Cognition & Instruction, p. 47–78.

Kozhevnikov, M. K. S. &. S. J., 2005. Spatial versus object visualizers: A new characterization of visual cognitive style. Memory & Cognition, p. 710–726.

Kozhevnikov, M. M. M. A. &. H. M., 2007. Spatial visualization in physics problem solving. Cognitive Science, pp. 549-579.

Larkin, J. a. S. H., 1987. Why a diagram is (sometimes) worth ten thousand words. Cognitive science, 11(1), pp. 65-100.

Lindauer, M. S., 1983. Imagery and the arts. In A. A. Sheihk (Ed.), Imagery: Current theory, research, and application. New York: Wiley.

Long, W., 1983. The meaning of entrepreneurship. American Journal of Small Business. American Journal of Small Business, Issue 8, p. 7–56.

Lubinsky, D., 2004. Introduction to the special section on cognitive abilities: 100 years after Spearman’s (1904) ’General Intelligence,’ objectively determined and measured. Journal of Personality and Social Psychology, p. 96–111.

Marks, D. F., 1973. Visual imagery differences in recall of pictures. British Journal of Psychology, Volume 64, p. 17.

McKelvie, S. J., 1995. The VVIQ as a psychometric test of individual differences in visual imagery vividness: A critical quantitative review and plea for direction. Journal of Mental Imagery, p. 1–106.

Miller, A. I., 1986. Imagery in Scientific Thought. Cambridge, MA: MIT Press.

Miller, A. I., 1996. Insights of genius imagery and creativity in science and art. Cambridge, MA: MIT Press.

41

Miner, J., 1990. Entrepreneurs, high-growth entrepreneurs, and managers: Contrasting and overlap- ping motivational patterns. Journal of Business Venturing, Issue 5, p. 221–234.

Miner, J., 1993. Role Motivation Theory. New York: Routledge.

Miyake, A. F. N. P. R. D. A. S. P. &. H. M., 1991. How are visuospatial working memory, executive functioning, and spatial abilities related? A latent-variable analysis.. ournal of Experimental Psychology: General, p. 621–640.

Motes, M. A. M. R. &. K. M., 2008. Object-processing neural efficiency differentiates object from spatial visualizers. NeuroReport, p. 1727–1731.

Nerssesian, N. J., 1995. Should physicists preach what they practice? Science & Education, Issue 4, p. 203–226.

Nijstad, B., 2006. owthegroup affects the mind: a cognitive model of idea generation in groups. Pers. and Social Psych. Review, pp. 186-213.

Osterwalder, A. &. P. Y., 2010. Business model generation: a handbook for visionaries, game changers, and challengers. New Jersey:ohn Wiley & Sons.

Paulus, P. a. Y. H., 2000. Idea generation in groups: A basis for creativity in organizations. Organizational behavior and human decision processes, 82(1), pp. 76-87.

Plassmann, H. R. T. Z. &. M. M., 2012. Branding the brain: A critical review and outlook. Journal of Consumer Psychology, pp. 1-36.

Polanyi, M., 1958. Personal Knowledge: Towards a Post-critical Philosophy. London: Routledge.

Raaijmakers, J., 1981. Searchof associative memory. Psych. Review, pp. 93-134.

Reynolds, P. D., 1987. New firms: Societal contribution ver- sus survival potential. Journal of Business Venturing, Issue 2, pp. 231-246.

Roam, D., 2012. The Back Of The Napkin. London:Marshall Cavendish Business An imprint of Marshall Cavendish International.

Rockey, E. H., 1986. Envisioning new business: How entre- preneurs perceive the benefits of visualization. Frontiers of Entrepreneurship Research, pp. 344-360.

Roe, A., 1975. Painters and painting. In I. A. Taylor & J. W. Getzels (Eds.), Perspectives in creativity. Chicago: Aldine: s.n.

Roid, G. H., 2003. Stanford binet intelligence scales 5th edition: Examiner’s manual. Itasca, IL: Riverside Publishing.

Rosenberg, H. S., 1987. Visual artists and imagery. Imagination, Cognition, and Personality, p. 77–93.

Roth, S., 1993. Visualization in Science and the Arts.

42

Söderlund, J. &. M. H., 2012. Project management scholarship: Relevance, impact and five integrative challenges for business and management schools. In: s.l.:International Journal of Project Management, pp. 217-359.

Schroeder, W. L. B. a. M. K., 2004. The visualization toolkit: an object-oriented approach to 3D graphics. Kitware.

Shah, P. &. M. A., 1996. he separability of working memory resources for spatial thinking and language processing: An individual differences approach.. Journal of Experimental Psychology: General, p. 4–27.

Shane, S. a. V. S., 2000. The promise of entrepreneurship as a field of research. Academy of management review, Issue 25(1), pp. 217-226.

Shepard, R. N., 1996. The science of imagery and the imagery of science. San Francisco, s.n.

Smith, I. M., 1964. Spatial ability: Its educational and social significance.. s.l.:s.n.

Snyderman, M. &. R. S., 1987. Survey of expert opinion on intelligence and aptitude testing. American Psychologist, p. 137–144.

Star, A. D. &. M. M. Z., 1981. urvival rates for retailers. Journal of Retailing, 57(2), pp. 87-97.

Sternberg, R. J., 1985. Beyond IQ: A triarchic theory of human intelligence. New York: Cambridge University Press.

Stylianou, D., 2002. On the interaction of visualization and analysis: the negotiation of a visual representation in expert problem solving. The Journal of Mathematical Behavior, 21(3), pp. 303-317.

Sutton, R. I. &. H. A., 1996. Brainstorming groups in context. Administrative Science Quarterly, Volume 41, pp. 658-718.

Tobin, D. R., 1998. The knowledge-enabled organization. New York: AMACON.

Toubia, O. a. N. O., 2016. Idea generation, creativity, and prototypicality. Marketing science, Issue 36(1), pp. 1-20.

Ungerleider, L. G. &. M. M., 1982. Two cortical visual systems. In D. J. Ingle, M. A. Goodale, & R. J. W. Mansfield (Eds.. Cambridge, MA: MIT Press.

Vygotsky, L. S., 1986. Thought and language. Cambridge, MA: MIT Press.

Walny, J., 2011. Visual thinking in action: Visualizations as used on whiteboards. Visual thinking in action: Visualizations as used on whiteboards, pp. 2508-2517.

Walny, J. L. B. J. P. R. N. a. C. S., 2012. Understanding pen and touch interaction for data exploration on interactive whiteboards.. IEEE Transactions on Visualization and Computer Graphics, Issue 18(12), pp. 2779-2788.

Wang, H. C. C. D. &. F. S. R., 2010. dea expander: supporting group brainstorming with conversationally triggered visual thinking stimuli, pp. 103-106.

43

Wechsler, D., 1997. Wechsler adult intelligence scale—3rd edition (WAIS- 3O). San Antonio, TX: Harcourt Assessment.

Winner, E. &. P. D., 1985. Giftedness in the visual arts. Items, p. 65–69.

Zazkis, R. D. E. &. D. J., 1996. Coordinating visual and analytic strategies: a study of students’ understanding.. Journal for Research in Mathematics Education, 27(4), p. 435–437.

Zgraggen, E. Z. R. a. D. S., 2014. Panoramicdata: Data analysis through pen & touch. IEEE transactions on visualization and computer graphics, Issue 20(12), pp. 2112-2121.

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Appendix

In this section, a more detailed description of the figures and tables which were

gathered from (Blazhenkova, 2010) and (Walny, 2011) are presented. It should be

noted that the following information are directly taken from the cited articles as well

as our data bank of the Web survey.

45

Question Bank

No.1

No.2

No.3

46

Interpretation of Visuals

No.4

No.5

47

No.6

No.7

48

Whiteboard usage

No.8

No.9

No.10

No.11

49

Table 1: Filtration Discerption

Filtrations Discerption

Pictorial interpretation

Respondents interpreted the graph

literally, in the form of a pictorial

illustration of a situation with

ordinate the graph, they illustrated

the literal shape of the graph

Abstract interpretation

Abstract interpretations, in which

participants interpreted the graph as

an imagery spatial representation of

movement over time

Irrelevant interpretation

participants interpreted the graph in

terms of irrelevant, not features of

the graph from pictorial views, and

their interpretations reflected not

sufficient of the information given in

the graph

50

Table 2: Filtration Discerption

Filtrations Discerption

Pictorial interpretation

Respondents who interpreted the

painting in terms of its appearance

features, as if colours or concrete

objects in the paintings, and

indicated superficial or lack of

emotion.

Abstract interpretation

Interpretations, in which is referred

to the paintings in terms of

conceptual and emotional content

that was not directly but also related

to the ideas of the painting

Irrelevant interpretation

Descriptions were irrelevant to the

painting’s appearance or emotional

content or missing entirely

Dataset of Web Survey

Answers from the respondents of our survey can be found at:

https://figshare.com/s/3979a57799ccc499b0f4