DO BUSINESS ANGELS REACT TO NONVERBAL CUES?

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DO BUSINESS ANGELS REACT TO NONVERBAL CUES?

TO WHAT EXTENT DOES NONVERBAL COMMUNICATION INFLUENCE BUSINESS ANGEL

DECISION-MAKING?

Small Business and Entrepreneurship Master’s thesis

Jan R. Schomaker (S3182142) June 20th, 2017

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Author: Jan R. Schomaker

Title of thesis: Do Business Angels React to Nonverbal Cues? Degree: Master of Science (Business Administration)

Degree program: Small Business and Entrepreneurship Thesis advisor: dr. Andreas J. Rauch

Thesis co-assessor: dr. Samuele Murtinu Year: 2017 Pages: 58 Words: 13,238 Abstract

PURPOSE OF THE STUDY

The objective of this study is to generate new evidence and approach the partly deficient theories of business angel decision-making. The study investigates this matter by examining the investment behavior based on the influence of nonverbal communication cues and discovering whether the research stream of nonverbal behavior complements the findings of traditional business angel decision-making research. The thesis emphasizes on the pitch presentations, wherein entrepreneurs attempt to sell their ventures and equity in exchange for financing to business angels.

DATA

The characteristic hand-coded data on business angels is sourced from a German TV show named “Die Höhle der Löwen”. By analyzing the latest production season, the author was capable of witnessing the decision-making process of five business angels, of which one is female. The absolute number of examined pitch meetings accounts for 52, which consisted of 26 accepted pitch presentations and 26 declined ones.

RESULTS

The results propose that nonverbal communication at least moderately influences the decision-making of business angels. The effects of nonverbal communication additionally seem to affect the essentials of the agency theory conflicts some for the better and some for the worse. Overall, visual nonverbal cues appear to have a more significant impact on investment behavior than auditory nonverbal cues.

Keywords: Business angels, Investment decision-making, Nonverbal communication,

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LIST OF TABLES

TABLE1. NONVERBALCUESANDILLUSTRATIONSINTHEDIAGNOSTIC

FUNCTIONFORLIEDETECTION ... 19 TABLE2. INFORMATIONABOUTTHEBUSINESSANGELS ... 25

TABLE3. DESCRIPTIVESTATISTICS,INCL.MEAN,S.D.ANDNOFNONVERBAL

CUESANDINVESTMENTOFFERS ... 31 TABLE4. INTER-CORRELATIONSAMONGNONVERBALCUESANDINVESTMENT

OFFERS ... 31 TABLE5. MULTIPLELINEARREGRESSIONSRESULTSOFNONVERBALCUESON

INVESTMENTOFFERS ... 32 TABLE6.MULTIPLELINEARREGRESSIONSOFVISUALNONVERBALCUESON

INVESTMENTOFFERS ... 33 TABLE7.MULTIPLELINEARREGRESSIONSOFAUDITORYNONVERBALCUESON

INVESTMENTOFFERS ... 34 TABLE8. DISTRIBUTIONSOFBUSINESSANGELREJECTIONCRITERIAAMONG

THEBUSINESSANGELS ... 38

LIST OF FIGURES

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DO BUSINESS ANGELS REACT TO NONVERBAL CUES?

TO WHAT EXTENT DOES NONVERBAL COMMUNICATION INFLUENCE BUSINESS ANGEL

DECISION-MAKING?

1. INTRODUCTION

In the 1970s and beginning of the 1980s, Albert Mehrabian, Professor at the University of California, L.A. found evidence of the fact that more than 90 % of our communication reaches the receiver through human body language, including gestures, facial expressions (55 %) and voice (38 %). Only 7 % of the communication contains verbal content (Mehrabian, 1971; 1981). During a conversation, therefore, people are sending nonverbal signals to the receivers that are not only measurable through the spoken word. How words are expressed and supported through physical movements can reveal a lot more information about the actual value of the spoken word. In business situations, consequently, gestures, facial expressions, and voice can lead to trust and belief in the sender, indicating behavioral trust dimensions and thereby showing whether or not a person is trustworthy, capable, trusting and communicative (Maxwell & Levesque, 2014). Whether or not the receiver can detect suspicious cues when the sender is trying to deceit the receiver can make a huge difference in the financial success of business individuals. Situations of deceit can be contract and price negotiations, job interviews, or investment decisions based on a personal connection to the founder.

This study will focus on the latter, particularly on the pitch situation, in which entrepreneurs present their product or service idea to a group of business angels hoping they will invest in their venture with the preferred amount of money for a particular percentage of shares in their company.

1.1. BACKGROUND AND MOTIVATION

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business angels cannot conceivably evaluate each investment opportunity versus all these criteria.

To show which kind of research already exists, the author will shortly show two very opposing types of studies regarding business angel decision-making. The first one by Jeffrey et al. (2016) focuses on the financial and professional factors such as experience and education of the founders, the market potential of the business model, product adoption, patents, product status and their significance for the investment decision of business angels. This study has an empirical character as they analyze real-time data of a TV-show from Canada called „Dragon’s Den", in which they evaluate 166 successful pitches that received an investment. The second one, examined by Clark (2008), assesses the effect of entrepreneurs' verbal ‘pitch' presentation abilities using factors like clarity and structure of the presentation. Clark (2008) is providing a different view of how business angel investment decisions might be affected by more subjective dimensions and therefore going away from the opinion of an investment decision as a ‘hard evidence'-oriented ‘substance'-based process. However, this research has a clear case study character, as Clark (2008) is regarding three pitches and analyzes how the investors at a UK angel investor forum evaluated the pitches concerning presentational skills.

A greater variance of research regarding business angel decision-making will follow in the Literature Review to adequately show the theoretical and managerial importance for this thesis. As will be explained in the following, no research exists about the influence of nonverbal behavior on the investment decision of business angels. The author will analyze pitch cases of the German TV show “Die Höhle der Löwen” and measure the occurrence of nonverbal cues based on a framework by Vrij et al. (2000) to find out if the business angels react more significantly to subconscious influences than previous literature has shown.

1.2. RESEARCH QUESTIONS

Based on the literature gap as identified above and the goals of this research, the author has formulated two research questions. The lack of empirical evidence with regards to the effect of entrepreneurs’ nonverbal behavior on the investment decision of business angels, leads to the first research question:

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implications it will be of great importance to differentiate between these two opposing consequences. Hence, the second research question asks:

2. Are there nonverbal cues that directly enhance or decrease the investment probability of business angels?

1.3. CONTRIBUTION TO THE LITERATURE

By addressing this research gap, the author aims to contribute to the literature of investment decision-making in several ways. First, the author wants to find out if nonverbal behavior as a whole has a direct influence on business angel decision-making. Second, the author aspires to discover nonverbal cues that will improve the investment probability. Third, the author aspires to find nonverbal cues that will decrease the investment probability. This will, in the author’s point of view, be precious to future researchers and practitioners. It is the particular interest of the author to take a look at both successful and unsuccessful pitches to find the cues that improve as well as decrease the investment probability. The results will allow nascent entrepreneurs to prepare themselves better before pitching their businesses in front of business angels and conceivably increase the number of ventures that receive funding.

1.4. RESULTS

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auditory nonverbal influences (speech rate and speech disturbances), at least, within this study and with this sample size, have no direct effect on business angels’ investment decision. The results of this research, nonetheless, specify that there is much more to discover in the practices of business transactions, e.g. business angel investment, that reveals areas, which researchers have not studied to a greater extent. More essentially, it was the first step towards complementing business angel decision-making models with the literature stream of nonverbal behavior.

1.5. LIMITATIONS OF THE STUDY

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biased. To manage these problems, the author has taken sufficient time per episode to collect the data with adequate care and documented the observations as accurately as possible.

1.6. STRUCTURE OF THE STUDY

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2. LITERATURE REVIEW

This chapter emphasizes the most noteworthy literature from the research of business angel decision-making and nonverbal behavior. The goal is to start closing an existing gap between these two rather large literature streams and find out on an empirical basis whether or not nonverbal communication influences business angel decision-making during an investor-entrepreneur pitch situation. Therefore both research streams have to be presented appropriately.

To firstly understand their investment behavior it is crucial to provide definitions for business angels and explain their decision processes. The first section provides a short overview of business angels and their general investment behavior. The second section underlines the importance of agency theory as a backbone of business angel decision-making. The third section revises empirical research streams that have been examined so far regarding business angel decision-making, separated into previous survey and questionnaire studies and more recently real-time studies.

To secondly understand the effects of body language it is crucial to provide definitions for different kind of body language characteristics and cues for detecting deceit, which function as variables for the empirical analysis. In the first section, the author provides the reader an overview of the existing literature on nonverbal behavior. In the second section, the author presents research streams that explain indicators for deceit/deception during an interview situation, which then will analyze the investor-entrepreneur pitch situation.

2.1. INTRODUCTION TO BUSINESS ANGELS

Business angels are frequently described as high-net-worth personalities who use their wealth to support businesses seeking for capital (Feeney et al., 1999; Van Osnabrugge, 2000; Mason, 2007). Friends and family usually disqualify from this classification (Mason, 2007; Riding, 2008). In comparison to the highly formal venture capital investors, business angels are relatively informal investors (Wetzel, 1983). As a result, business angel and venture capital investment can compete but indeed rather complement each other, e.g. with regards to the investment stage or the amount of capital they are providing (Freear & Wetzel, 1990).

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Business angels consequently are the most valuable source of finance for small businesses (Feeney et al., 1999), which is crucial for society. Small businesses generate the majority of jobs and participate considerably on economic growth (Sudek, 2006).

In the UK, a traditional business angel investment is equal to GBP 100.000 and below (Mason & Harrison, 2002). Researchers have proven that business angels assign only up to 20 % of their portfolio to private firms (Mason & Harrison, 2002; Stedler & Peters, 2003; Mason, 2007). Thus it appears that they are not contingent on the triumph of their private investments (Mason & Harrison, 1996a; Prowse, 1998). In Germany, the average business angel held on up to five investments and completed up to two agreements per year (Stedler & Peters, 2003).

On top of that, business angels favor ventures located close from home (Prowse, 1998; Paul et al., 2007), because they can more easily source and monitor the supported companies. Proximity is of particular importance due to arising agency disequilibria and asymmetrical information. Monitoring companies close from home tends to be more efficient and less expensive (Mason & Harrison, 2002).

Nowadays, business angels aim to co-invest as a group with additional business angels (Prowse, 1998; Feeney et al., 1999; Paul et al., 2007). These syndicates create the possibility for individual investors to invest in additional and larger deals (Mason, 2007). A network of business angels makes investment less uncertain, because evaluation and due diligence improve. In comparison to venture capitalists due diligence processes of business angels are assumed to be less systematic, less extensive and more subjective (Van Osnabrugge, 2000; Morrissette, 2007). Due to the shortage of resources business angels typically, need to rely profoundly on gut feeling and personal valuation of the entrepreneur (Mason & Stark, 2004; Van Osnabrugge, 2000). In Germany, on average, 16 % of the applications business angels observed gained an investment (Stedler & Peters, 2003); in Canada, it is only 6 %, in the UK it is 8 %. Business angels make modest common stock investments. Hence, the price and the equity stake need to please each party to reach an agreement (Mason 2007; Paul et al. 2007). As these small startups usually have relatively small commercial or operative history and limited tangible assets, business angels favor simple rules of thumb estimations or gut feeling to formal valuation heuristics (Prowse, 1998).

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after keeping the investment typically between five and eight years (Feeney et al., 1999). In direct comparison to venture capitalists business angels usually have more significant non-financial motivations (Morrissette, 2007). For business angels, fun and excitement in helping and working with exciting startups play a vital role and can act as a type of physical compensation (Mason & Harrison, 2002; Mason & Stark, 2004).

2.2. AGENCY THEORY AS THE THEORETICAL BACKBONE

To describe the relationship and successive approximation between entrepreneurs and business angels, the author deploys the agency theory as the theoretical foundation. As outlined in the following, business angels place a higher emphasis on informal criteria when investing. Contrary to venture capitalists, they decide for the deal first and then arrange contracts ex-post. Therefore they need more carefully evaluate individual characteristics of the entrepreneurs to minimize the risks of mutual ex-post disagreement. Nonverbal communication plays a significant part. How important its role is, the reader can acknowledge in the last two chapters. In the following, the author will present the core aspects of agency theory with special regards to the business angel investment process.

Concerning decision-making of institutional venture capital fund manager, considerable research exists. Anyhow, research still lacks understanding of informal business angel investment (Paul et al., 2007). In the article of Van Osnabrugge, (2000), finance literature has been used to characterize the disparities among venture capital and business angel decision-making. To this date, this is the single theoretical contribution deployed to business angel decision-making.

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Van Osnabrugge (2000) differentiates two methods to reduce probable agency conflicts amongst the agent and the principal. These can be distinguished by their emphasis on different stages, not with risk reduction as they both value this quite strongly. The principal-agent approach needs to define the ideal contract amongst both parties (Jensen & Meckling, 1976). Screening and due diligence of the company ex-ante the investment decision enable the creation of a perfect contract (Van Osnabrugge, 2000). The better the contract ex-ante, the fewer discrepancies of information among the parties. The incomplete contracts approach explains that no optimal contracts exist and therefore it supports the post-investment allocation of control, which has found more important than ex-ante screening and contract writing considered by the first approach. Van Osnabrugge (2000) discovered that business angels focus more on reducing agency risks ex-post the investment (incomplete contracts approach), whereas venture capitalists strain actions ex-ante the investment (principal-agent approach).

Venture capital portfolio managers are paid employees who steer substantial funds of investor capital; business angels devote their money, and due to this they also face the consequences personally. Therefore they are well advised to diminish the possible agency conflicts by their active involvement and use a hands-on approach with the businesses, in which they participate. (Van Osnabrugge, 2000).

On the question whether business angels mainly invests in the product/market or entrepreneur, Van Osnabrugge (2000) concludes that business angels focus more on the entrepreneur and venture capitalists on the product/market. This shows that research on nonverbal behavior fits better with a focus on business angels than on venture capitalists, as these are more concerned about the object/goal than interested in the person itself. For instance, venture capitalists strongly consider that start-up teams can easily be replaced (Mason & Harrison, 1996a) whereas business angels, such as Carsten Maschmeyer, on the other hand, believe only in strong entrepreneurs, not in strong startups or ideas (see TV show “DHDL”).

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corporations with comparatively small equity stake owned by the management (Kelly & Hay, 2003).

As a result, scholars have recognized the urge to employ also other principles to business angel decision-making (Kelly & Hay, 2003; Mason, 2007). With this thesis, the author aims to mitigate the existing research gap using an empirical psychological approach based on the nonverbal behavior that the founders (agents) send and the business angels (principals) receive.

2.3. BUSINESS ANGEL DECISION-MAKING RESEARCH

The denial rates of novice investment proposals are relatively high, as mentioned in the introduction to business angels (Stedler & Peters, 2003; Mason & Harrison, 1995). Hence, it is crucial to comprehend both the investment and rejection criteria applied in business angel decision-making. Knowing these criteria can support entrepreneurs to expand their chances of receiving finance from business angels. In this section, the author will focus on the evolution of the business angel decision-making literature, concentrating on the investment and rejection criteria drawing from earlier survey and interview analyses as well as more recent research with a focus towards real-time analyses focusing primarily on the business pitch.

2.3.1. REVIEW OF QUESTIONNAIRE AND INTERVIEW STUDIES

Haar et al. (1988) seem to be the first authors to study investment criteria of business angels. The sample finally contained 121 business angels from the U.S. East Coast with a small response percentage of 4.3 %. Their survey demanded respondents to order the importance of their investment criteria. Next, to that, they required the respondents to rank critical flaws in the investment proposals that would disqualify their investment. Business angels supported solely two criteria: Firstly, management unmistakably proves capability to run the business and secondly, the proven demand for the solution. Other fewer important criteria were the founders' track record and a massive commercial product potential. Core disqualifiers were the direct opposite of the two mainly supported investment criteria – management’s incompetence to thrive and unsatisfactory market outlook.

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that business angels feel much more reliant on the individuals they invest in compared to other sorts of investors; placing much emphasis on the founders and the management team. In his research, another important investment criterion is the business outlook for the company. Also, the investor's familiarity with the industry is critical. (Landström, 1998)

Therefore, if entrepreneurs nonverbally behave inadequate, so that they appear to be unable to succeed, business angels have a reason for rejection. By using nonverbal cues, which create negative impressions, such as insecurity or lack of authenticity, business angels might evaluate the entrepreneurs as incapable (Mason & Stark, 2004).

With regards to deal-specific studies, Mason & Harrison (1996b) firstly studied why business angels decline investment proposals. They analyzed a sample of 35 declined investment proposals of the UK based business angel syndicate “Metrogroup" from taped interviews. The business angels rejected most of the possibilities due to a single deal killer. The most prominent deal killer were incapable entrepreneurs, unlike VCs that see them as easily replaceable. The second most prominent motive was a gap between market or marketing-related criteria and financial concerns. The primarily financial deal killer was unrealistic or inconsistent financial projections. Hence, in addition to Haar et al. (1988), Mason & Harrison (1996b) deliver a reason that measuring nonverbal behavior particularly on business angels is more reasonable than on venture capitalists.

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valuable. Credibility can be achieved through the use of certain nonverbal cues, as the reader will find out in the upcoming sections.

The main goal of Stedler & Peters (2003) research was to find evidence on business angels in Germany. Their main emphasis was on the motives and motivations of business angels for investing. Based on 232 questionnaires that represent 46 % of the response rate they found out that business angel investment criteria include management, product, financial, market and investment characteristics. The most important aspects were the entrepreneur and the management, sales and market and product or service. In the entrepreneur category, the most critical criteria were the personal impression, power of persuasion and ability to motivate (Stedler & Peters, 2003). The evaluation of these criteria can be influenced if the entrepreneur uses the correct nonverbal behavior. It is a different question whether business angels make their decision based on these cues; the analysis will give some indication.

2.3.2. A REVIEW OF REAL-TIME STUDIES

Clark (2008) demonstrated that one way in which entrepreneurs can acquire financing for their venture is by holding a pitch presentation. During the sales pitch, the entrepreneur is aiming to sell shares of their company to business angels. In return, they receive capital from the angels, and occasionally even their knowledge and contacts. Business angel networks more and more ask entrepreneurs to perform these pitches at their societal events (Mason & Harrison, 2003; Mason, 2007; Clark, 2008). The pitches mostly take place before the first screening period, before the business angels have even taken a look at the business plan or eventually met with the founders in person (Clark, 2008). These pitches typically last around 15 minutes (Mason & Harrison, 2003), but can likewise be elevator pitches that take only some minutes (Clark, 2008). As Mason & Rogers (1997) have proven that the average time that investors need to decide for or against an opportunity is solely 6 minutes, the value of such these pitch performances is not questionable. One of Clarks (2008) main finding was that understandability and structure, as well as the entrepreneurs’ characteristics and their competency to promote themselves and their investment proposal, are key for a successful pitch. Expanding the gained results of Clark’s study, the author will provide details on which kind of nonverbal presentational skills are specifically necessary based on the results of the analysis.

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Their opinions, impressions, and feedback were saved, and after the pitch, they were demanded if they felt intrigued to follow the proposition further. Moreover, they were asked to deliver a brief analysis for their decision. The preponderance of the respondent would reject the proposition due to the following reasons: poor presentation, lack of understanding, imperfect information, poor presentation and investor fit deliberations. The dominant issues for rejection were presentation-related matters such as not linking with the audience and losing their attention, in addition to not provided presupposed knowledge. The second most dominant factors for rejection were relating to market issues, e.g. failed provided information on value, market size, competition, potential customers, and segmentation. Finally, the third most dominant factors for rejection were product-related issues. The entrepreneur itself has received negative critics for not selling their proposition well enough. The results of the study by Mason & Harrison (2003) show that entrepreneurs have to improve their persuasion abilities so that they can electrify the business angels in pitch meetings. The use of correct body cues can diminish a lack of connection and understanding. If they are for business angels, the reader can investigate in the analysis.

Maxwell et al. (2011) studied business angel decision-making at an early stage using 150 pitch performances between entrepreneurs and prospective investors. In contrast to most of the previous studies that suggest that business angels use an entirely compensatory decision model, investors rather use a shortcut decision-making heuristic identified as elimination-by-aspects to diminish the actual investment proposals to a better, controllable size. The investment opportunities, therefore, are rejected if they are diagnosed with only one fatal flaw; if not, they do proceed beyond that stage. Elimination-by-aspects is anyhow not used by business angels as a decision-making heuristic in the final decision of whether to fund an opportunity. At subsequent stages, more compensatory and subjective models of decision-making are used (Maxwell et al., 2011). This means, that, to make a final decision, more subjective influence plays an important role, which opens the way also for the analysis of nonverbal behavior.

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(e.g. agency theory and trust). Using successful nonverbal cues can convince business angels to invest despite the risks of adverse selection and moral hazard.

Maxwell & Levesque (2014) ran another real-time research to gather behavioral information from real interactions to test hypotheses regarding the building, damaging or violation of trust and how the investor’s trust level can impact the decision to propose an investment. The outcomes indicate that founders who get investment offers show a greater amount of trust-building communication during the initial meeting and a lesser amount of unintended trust-damaging communication than founders who do not obtain an offer and present limited deliberate trust-violating communication. Entrepreneurs who violate or damage trust can anyhow obtain investment offers; given that the investors deploy a control mechanism prior the investment is taking place. They thereby explain the investor-entrepreneur relationship with reciprocal trusting and trustworthy behaviors. They are testing the trust dimensions: trustworthy, capable, trusting and communicative (Maxwell & Levesque, 2014). Nonverbal behavior can influence these criteria to some extent. During this study, the reader will receive information whether the influence is significant, independent to the verbal content of the pitch.

2.4. MODALITIES OF NONVERBAL BEHAVIOR

Nonverbal communication is feeling not only a burst of interest but also a rapidly growing importance in the scientific community. One part of the significance and enthusiasm over nonverbal communication originates from the renaissance of interest in non-conscious activities. Another reason for the renewed attention is psychology’s evolution from seeing humans as “cold” (rational, information-processing) to “hot” (driven, passionate, not always rational) in their consideration and behavior. New coherences of theory and methodology can establish entirely new grounds of endeavor. (Hall & Knapp, 2013)

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over-studied, and moreover, nonverbal behavior is, of course, fascinating and important in the real world. (Hall & Knapp, 2013)

Therefore, by the findings of this study, business angels could check for nonverbal cues before investing in a founder and founders could absolve a course in how to avoid damaging or how to use enhancing nonverbal cues to receive funding. Next, to build a foundation for the hypotheses section, the modalities of nonverbal communication will be introduced. Starting with facial behavior, followed by vocal behavior, gesture, and body movement, eye behavior, and proxemics.

2.4.1. GESTURE AND BODY MOVEMENT

During this section, the author introduces the reader into the area of gestures and body movement in interpersonal behavior. As modern research shows, concerning syntax, vocal stress and meaning, gesture is closely synchronized with speech (Bull, 2012). Furthermore, it is important in transferring feelings and interactive attitudes. Also, scholars suggest that gesture is essentially subordinate to speech, basically intensifying and elaborating the articulated word. Anyhow, compared to speech, gesture as a modality of communication has remarkably different characteristics. The core elements are that gesture is visual, quiet, and comprises a sequence of physical actions. Moreover, it is greatly visible, and there are also differentiations in visibility between different kinds of gesture (Bull, 1994). Consequently, specific communicative actions can be preceded more directly via gesture than via speech, which significantly influences social interaction. The scientific attention to gesture has a long past, but only during the last years, it has become the focus of systematic examination (Bull, 2002). Microanalytic research of gesture has helped to emphasize its significance as a part of nonverbal behavior. In modern psychological science, the expression gesture can be described as a visible body movement, which transmits a message; gesture can arise both in combinations with, and in the lack of, speech (Kendon, 2004).

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regarding syntax, vocal stress, and meaning; it is furthermore essential in sharing emotions and interactive attitudes (Bull 1994; 2012).

Microanalytic findings have revealed that an individual's body activity is tightly aligned with their speech, a phenomenon frequently mentioned as self-synchrony (e.g., Condon & Ogston, 1967; Dittmann, 1972). Woodall & Burgoon (1981) examined the properties of nonverbal synchronization on the processing and approval of a message by the listener. Alignment between gesture and speech improved the processing of information for the listener, and therefore the capability to recall information afterward. Moreover, participants perceived aligned messages to be much more intriguing than those in either with restricted gesture or unsynchronized circumstances. Additionally, speakers in the unsynchronized circumstance were seen as less trustworthy than those in the synchronized circumstance. Analogously, McNeill et al., (1994) discovered that a mismatch between an individual's speech and gesture generated communicative challenges for the listener. As said by Kendon (1972, 1980, 1988), there is a pattern of body movements that interrelate with speech. Hostetter (2011) conducted a meta-analysis of 38 studies investigating the impact of gesture on the understanding of an oral message throughout conversation. The study especially focused on listeners’ comprehension across firstly speech only and secondly speech with gesture. In the end, he derived these conclusions: Gesture that portrays motoric activities transfers more information than that planned to transport abstract ideas. Gesture is more communicative when it delivers information not articulated in the associated speech than when it is made redundant by the spoken dialogue.

2.4.2. FACIAL BEHAVIOR

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Ekman recharged the awareness in Darwin and possibly formed and guided how we reflect on emotion and nonverbal behavior. Nowadays, this is recognized as the neurocultural theory, which assumes that there is a fixed relation among few basic emotions and numerous other mechanisms, containing patterned physiological motivation. Key, however, to what is observed as basic emotions, is the prototypical expressive patterns – particularly facial expressive patterns (Ekman & Cordaro, 2011).

The neurocultural theory has two modules – the spontaneous expression of emotion and the regulation of expression – a subsequent development. This opinion can be demonstrated most evidently by “felt” and “false” smiles. Consistent with Ekman and colleagues (Ekman & Friesen, 1982; Ekman et al., 1980), one should differentiate amongst smiles that happen spontaneously in combination with a positive affect and those that are voluntarily put on the face to conceal or cover a negative emotion.

An outcome of the academic frame of reference of a clear separation of genuine and controlled expressions interests the concept of leakage via “micro-expressions” which is significant for the study of deception (e.g. Vrij et al., 2010). Surely, this has developed to the most dynamic part of Ekman’s study and has even arrived in TV crime shows such as CSI (Levenson & Ekman, 2006). Thus, the popularity of these methods and this framework has not only influenced scientists, but also nonprofessionals alike (Levine et al., 2010).

Ekman & Friesen (1969, 1974) argued that the face be more controllable than the body (i.e., hands, legs, and feet). The face can send a large number of messages at a fast rate. Senders are more aware of their facial expressions than of their body movements. Several studies from outside the field of deception provide evidence consistent with the view of the body as a leaky channel and the face as a controlled channel (DePaulo & Fisher, 1981; DePaulo et al., 1984). It is less likely to give away deception. Therefore, during this study, the author focuses mainly on the body, only considering smiles and head movements; excluding other emotional facial expressions.

2.4.3. VOCAL BEHAVIOR

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of the particular state of the speaker (aside from more stable traits and dispositions), which serve as important context information for the listener, such as speech disturbances. In contrast to the visual look and articulation of the person, always visible, vocalization can be turned on and off. As speech is one of the best-controlled human actions, the availability of nonverbal vocal signs of information managing, affect and assertiveness, which continuously convoy vocalization, is substantially determined by consciously measured speech activity. It is this binary coding of all vocal behavior, mostly unintentional physiological events impacting the vocal organs and greatly coordinated verbal motion utilizing symbolic coding, which make the research of vocal behavior a multilayered and challenging undertaking. Consequently, the author, of this study, analyzes merely objective characteristics such as speech rate, speech hesitations and speech errors.

2.4.4. EYE BEHAVIOR

In discovering mental and emotional conditions of others, for humans, the eyes are specifically useful. The two eye activities, receiving the greatest empirical and academic attention in research, include eye gaze, and pupil dilation/constriction. Eye gaze carries remarkable social information and function. Modern eye behavior studies have benefited from progress in eye tracking knowledge, allowing for specific dimensions of seeing behavior with high time-based resolution. Since looking behavior, and also visual attention, are so closely connected – eye activities usually follow concealed attentive shifts (Deubel & Schneider, 1996) – we can conclude the place of one’s visual attentiveness from changes in gaze (Deubel & Schneider, 1996; Hoffman & Subramaniam, 1995). The analysis will exclude eye behavior for two reasons: first, the video material is filmed from one side and therefore it would be highly speculative whether or not the entrepreneur is looking directly at the business angels’ eyes. Second, there are five business angels and sometimes more than one entrepreneur in the room. Hence, it would be challenging to receive a high rate of accuracy.

2.5. DETECTING DECEPTION LITERATURE

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Researchers, focusing on the fields of educational psychology, diagnostics or forensic, habitually endorsed the psychological literature stream of lie detection (Feldman, 1976; Maier, 1966; Raskin & Hare, 1978; Trovillo, 1939). Lie detection functioned as an exemplar of the psychology of emotions (Krauss et al., 1981; Scherer, 1986). The nonverbal behavior method to lie detection rests on the premise that cognitive exertion or emotional reactions accompanied with lies are displayed in vocal or body signs past the individual’s voluntary power. Even though people try to hide certain feelings and information, nonverbal cues give more details about a person’s actual state of mind than what the person aims to show.

TABLE 1

Nonverbal Cues and Illustrations in the Diagnostic Function for Lie Detection

While the existing empirical validation proves that this is occasionally the situation, meta-analyses demonstrate that also the most valid nonverbal signals assume only weak relationships with the truth criterion (Zuckerman et al., 1981). Regarding the process of truthfulness assessment, most conventional methods share an implicit concept of lie detection as a decoding process. The cognitive or affective stress linked with lying cannot be completely hidden. Therefore, the outflow of unchecked expressions in the rush of communication can eventually be deciphered and used by experienced lie detectors. The actual cues that leak through the nonverbal or autonomic channel during the process of lie production are presumed to be employed in the individual course of lie detection. One refers

Nonverbal Cue Illustration

Illustrators Illustrators are hand and arm movements that support and complement a person’s speech. People that accompany their speech with many illustrators are perceived as more knowledgeable and competent. During lying, the frequency of illustrators decreases.

Adaptors: Self-adaptors are hand movements such that a hand touches the other hand or part of the body or the face. Induced are hand and finger movements like pressing, rubbing, holding, scratching, and playing. During lying, the rate of self-adaptors increases.

Smiling: When people lie, they often show a kind of incomplete smiling that appears camouflaged and artificial. Natural, cheerful, and complete smiling is reduced, however.

Hand and finger movements:

During lying, people show a lower frequency of hand and finger movement as they are trying to hide the fact that they are lying.

Leg and foot movements:

Leg and foot movement seems to be the most accurate indicator for lying because these body parts are the ones that humans can cover the worst.

Lack of head movements:

People show reduced head movements when lying. Head movements are less pronounced and less vigorous; that is, lying people have their head fixed.

Reduced speech rate and pause fillers:

Lying people often show delays and disfluencies in their speech. There are two possibilities of how such dysfluencies can appear. First, the rate of speech decreases. Second, pause fillers word repetitions appear increasingly.

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to these cues as authentic cues as they are accurate reflections of the process of lie production. The corresponding decoding assessment has numerous testable effects. First, the leakage of cues is of global occurrence. Second, authentic cues can be examined by human lie detectors, which are sensorily ready and cognitively adjusted to identify them. Third, human lie detectors have the ability to learn how authentic cues are connected to the criterion of truth. In

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3. HYPOTHESES

Based on the previously introduced lie detection literature, the author will motivate and posit hypotheses and bring them into the context and setup of a start-up pitch situation. The agency theory, which is greatly important for business angels to find trust in the person they invest in, implies that business angels should not receive signals from entrepreneurs that deliver any uncertainty, lack of authenticity or general psychological issues like unhappiness. This is why the author has drawn the literature of lie detection, as it provides a framework of tendencies on which nonverbal behavior business angels perceive as deceptive behavior and therefore as actions that create distrust and diminish the desire to cooperate closely with the founders to grow their venture, which business angels enjoy doing. Hypotheses 1 – 6 focus on the visual nonverbal cues, such as illustrators, adaptors, smiling, hand and finger movement, leg and foot movement and head nodding, whereas Hypotheses 7 – 8 particularly investigate auditory nonverbal cues, such as speech disturbances and speech rate.

3.1. VISUAL NONVERBAL CUES Illustrators

Illustrators, as mentioned in Chapter 3, help to understand and recall information provided better during a presentation. In the literature of lie detection, liars use fewer illustrators as they are trying to stay as neutral as possible. On top of that, by using them, speakers can influence how others perceive their character. For instance, Maricchiolo et al. (2009) discovered that listeners see individuals who accompany speech with gestures as more cool-headed and knowledgeable than non-gesturers. Kelly & Goldsmith (2004) again found that listeners preferred speakers who use gesture than those who did not use gestures. Hence, the author hypothesizes:

Hypothesis 1. The influence of illustrators on investment offers will be positive. Adaptors

Hand movements such that the hand touches the other hand or parts of the body or the face are called self-adaptors. They appear in different forms of hand and finger movements such as pressing, rubbing, holding, scratching and playing. While lying, the frequency of self-adaptors increases (Vrij et al., 2000). During a pitch situation, entrepreneurs should try to avoid the use of adaptors, as it may imply that the entrepreneurs hide information from the business angels or are not convinced of their business itself. Hence, the author concludes:

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Smiling

Smiling, in general, has a positive effect on others as it creates an atmosphere of relaxedness, happiness and sometimes even passion. Anyhow, as discussed in Chapter 3, academics differentiate between “felt” and “false” smiles. Therefore, consistent with Ekman and associates (Ekman & Friesen 1982; Ekman et al., 1980), one should separate between smiles that occur naturally in conjunction with a positive affect (felt smile) and those that are willingly expressed to hide a negative reaction (false/disguised smile). As the differentiation between these felt and false smiles is a highly scientific process, the author decided to focus on smiles in general. Business angels want to enjoy their cooperation with the supported entrepreneurs and therefore are interested in investing their wealth in suitable individuals. When the entrepreneur’s reaction contains natural smiles while pitching his idea, the business angels will think that the founder is passionate and happy with his idea. Thus, the author hypothesizes:

Hypothesis 3. The influence of smiles on investment offers will be positive. Hand and finger movement

In particular, Vrij et al. (2000) found out that liars show fewer hand and finger movements. Therefore, in a pitch situation, a high frequency of hands and fingers without arm movement should be regarded as a sign of being comfortable and not trying to control or hide the situation. Hence,

Hypothesis 4. The influence of hand and finger movements on investment offers will be

positive.

Leg and foot movement

With regards to leg and foot movement, Pease (2011) discovered in their studies with executives that “managers by lying, regardless of gender, unconsciously much more move their legs. Most of the staff had a hacker’s facial expressions, they by lying tried to control their hands, but almost no one knew what his or her feet are doing. These results were confirmed by the psychologist Paul Ekman, who found, that by lying are increasing the lower body movements, and observers better expose the lies when they see a liar's body. This explains why business leaders feel more comfortable hiding at desks with a solid front. Glass surface, and tables are causing more stress than massive tables, because you can see the human legs, then it is difficult to control yourself completely". Accordingly, the legs are the human body part that lies the least. Therefore, the author hypothesizes,

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Head nodding

Buller & Aune (1987) hypothesized in their research that deceivers (liars) might exhibit more nonverbal behaviors intended to protect their persona than truth tellers with special regards to head nodding. This was firstly suggested by DePaulo et al. (1985). During this study, the author will dedicate further investigation towards this hypothesis regarding the investment decisions of business angels. Therefore, head nodding can be subconsciously seen as a tool to hide something from the investors. The author suggests,

Hypothesis 6. The influence of head nodding on investment offers will be negative.

3.2. AUDITORY NONVERBAL CUES Speech disturbances

According to a study about lie detection by Vrij et al. (2000), deceivers reveal more ‘ah’ or ‘non-ah’ disturbances in their speech, because these actions are referred to thinking hard (Burgoon et al., 1989; Vrij, 1998; Goldman-Eisler, 1968; Köhnken, 1989). Thinking hard could, of course, be a sign that the founders are passionate about their ideas. During a pitch situation though, business angel are looking for competent managers for their business investment. As there will be multiple occasions, where the founders have to present themselves and their venture in public scenarios, business angels should be eager to invest in the ones that persuade others for their idea to grow their venture. Speech disturbances, such as speech hesitations (‘ah’ or ‘mm’ between words) or speech errors (word/sentence repetition, change, incompletion, slips of the tongue) will in most cases lead to the opposite of persuasion and therefore show unprofessionalism and insecurity. Multiple authors demonstrated that increasing speech errors and speech hesitations caused lower credibility scores, while the effect seems greater for dynamism and competence than for trustworthiness (Lay & Burron, 1968; McCroskey & Mehrley, 1969; Miller & Hewgill, 1964; Sereno & Hawkins, 1967). Thus, the author concludes:

Hypothesis 7. The influence of speech disturbances on investment offers will be negative. Speech rate

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average rate created higher scores of the speaker’s affection (Brown et al., 1973; Brown et al., 1974; Smith et al., 1975) and general success (Apple et al., 1979). Therefore, the author can imply that a normal to fast speech rate might have a positive impact on the investment decision-making on business angels. Hence,

Hypothesis 8. The influence of speech rate on investment offers will be positive. FIGURE 1

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4. METHODOLOGY & DATA

This chapter familiarizes the reader with the methods and data operated in this thesis. The particular data used is obtained from a German TV show entitled “Die Höhle der Löwen”. In the first section, the author will concisely present the concept and guidelines of “Die Höhle der Löwen”. In the second section, the author will explain the methodologies employed, including the measurement of dependent and independent variables and address potential validity concerns.

4.1. INTRODUCTION TO THE TV SHOW “DIE HÖHLE DER LÖWEN” “Die Höhle der Löwen” (DHDL) is the German spin-off of the globally syndicated reality TV-show Dragons’ Den. In the show, entrepreneurs present their ventures and ideas in front of a board of five business angels (“Löwen”; German for lions) to receive a direct equity investment, starting at € 10.000. The lions are informal investors, who are prepared to bring in their own capital in exchange for a share of the proposed business ventures (DHDL, 2017). To evaluate the investment proposals, there are constantly five business angels present at the “Höhle” (German for cave). Four of them are male; one of them is female. TABLE 2 provides

general personal information of each participating business angel.

TABLE 2

Information about the Business Angels

Name Birth year Net worth Entrepreneur Education Industry experience

Jochen Schweizer 1957 n/a Serial - Travel

Frank Thelen 1975 > €10 m Serial - Tech - Startups

Ralf Dümmel 1966 n/a Yes - Retail

Judith Williams 1972 n/a Yes University Teleshopping

Carsten Maschmeyer 1959 €1.050 m Serial - Insurance

* This data is obtained from the business angels’ web pages and the TV show. Net worth values are retrieved from Wikipedia and are shown for illustrative reasons.

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have requested at the initiation of the pitch. Otherwise, they leave empty-handed. If a lion proposes less than the entire amount, the entrepreneur has to gain an additional investment from at least one of the residual lions to reach the full amount. At maximum, five investors can be involved. The founder can moreover negotiate for a higher valuation of the share than he/she originally demanded. The lions can freely decide on the amount of their investment. If the entrepreneur believes that the investor is not suitable for them or if the two parties cannot find an agreement, the entrepreneur has the right to reject the investment offer. A deal made in the cave is legally not directly binding for both parties. After due diligence checks and mutual integrity to process the transaction, both parties can still refrain from their unwritten agreement. The production company remains impartial to the business relationship of the business angel and the entrepreneurs.

During this study, the author solely observes the business pitch, to provide the highest standard of objectivity and comparability between the varieties of pitches, as the Q&A session and the negotiations after can contain various subjects and issues, based on the information provided or not provided during the pitch.

4.2. SAMPLE AND DATA COLLECTION

The entrepreneurs, appearing in these pitches, were selected to present their businesses on television through an online application process initiated by the production company Sony. For the 3rd season, which aired in 2016, the screening processes chose 67 companies that were called to the studio, where their interaction was recorded and produced in 11 episodes of each 120 minutes (DHDL, 2017). 52 business pitch presentations from the first nine episodes were used for the data collection process. In order to examine the interactions among the business angels and entrepreneurs, the author used the edited for television versions, which are available through the TV channels online database, which gave the chance to observe and reconsider interactions but also involves limitations that are discussed in Chapter 1.4. and 4.2.3.

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4.2.1. DEPENDENT VARIABLE

The number of investment offers represents this study’s dependent variable. Investment offers are offers that entrepreneurs receive from business angels that, when accepted by the entrepreneurs, eventually turn into investments. As this study is aiming to describe the effectiveness of nonverbal communication on the success of business pitches, investment offers seem to be the only valuable and stable variable, being solely dependent on the business angels’ decision-making. Actual investments would also incorporate the responsive decision-making process of entrepreneurs, which is not considered in this research. The number of investment offers varies between 0 and 5, as business angels in the TV show can decide not to invest, to invest solely or to invest syndicated with up to four other investors.

4.2.2. INDEPENDENT VARIABLES

One observer measured the independent variables of the entrepreneurs during their venture pitch, including the nine measures listed below. Meanwhile, the observer was not informed about whether the pitches led to a deal and if, how many investors proposed an offer. First, the observer watched the video on mute. This way the verbal content could not interfere with the observers’ examination of the frequency of visual cues. Second, the observer watched the sequence with sound to detect speech disturbances, collected the amount of words used during the pitch to calculate the speech rate and gather information of how many investment offers (0 – 5) have been proposed by the business angels. At first, the author aspired to divide measured frequencies by the number of entrepreneurial team members. However, during the observation process, it was rapidly clear that the camera predominantly followed the entrepreneur that was leading the presentation at this particular moment. Therefore, the author decided only to measure the nonverbal cues of talking entrepreneurs. This is why the collected data was not divided by the number of entrepreneurs that presented the pitch; even though many entrepreneurs were in the room, this research considered them as one.

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variables have been coded and how they were counted. These are the nonverbal cues observed during the real-time video examination based on a coding system developed by Vrij et al. (2000) and Buller & Aune (1987):

Illustrators. Illustrators were measured by the frequency of arm and hand movements

that are intended to adjust and/or complement what is being said orally (Ekman & Friesen, 1969); an illustrator was counted as one event when the arm and hand movement had started, had been used for the support or modification of the verbal content, and then finally arrived back at their starting position (Vrij et al., 2000).

Adaptors. Adaptors were collected by the frequency of scratching the wrists, body,

head, and so forth (Vrij et al., 2000). Rubbing one's hands together was not implied as adaptor but as hand and finger movement (Friesen et al., 1979); as soon as the hands were back at the starting point, a possible next adaptor could be measured.

Smiling. Smiling was measured by the frequency of smiles and laughs the

entrepreneurs expressed during their pitch situation. Each smile and laugh was counted separately and measured as one event. (Vrij et al., 2000)

Frequency of hand and finger movements. Movements of hands or fingers in the

absence of moving the arms were measured based on the framework of Vrij et al. (2000).

Frequency of leg and foot movements. Movements of legs and feet were only

measured when the entrepreneurs were standing and not clearly walking to present a product or change their position. Coinciding movements of feet and legs were coded as one movement. (Vrij et al., 2000)

Head Nodding. Frequency of moving the head in a way of agreeing with the other

person, e.g. head nodding. One fully completed nod was measured as one head nodding. (Buller & Aune, 1987)

Speech hesitations. Speech hesitations were measured by the frequency of saying "ah"

or "mm" between words. Each hesitation was counted as one event. (Vrij et al., 2000)

Speech errors. Speech errors were measured by the frequency of word and/or sentence

replication, sentence adjustments, and sentence incompletion. Each of the actions mentioned above was counted as one single event. (Vrij et al., 2000)

Speech rate. To calculate the speech rate, first, the number of words used during the

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Due to the occurrence of different pitch durations, the author will adjust the measured events and set the frequencies in relation to the length of the pitching time to establish a necessary amount of comparability. The resulting data that was used for gathering the results is accessible in the APPENDIX II – DATA SET.

4.2.3. VALIDITY CONCERNS

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5. RESULTS

First, to test Hypotheses 1–8 made in Chapter 3, the author conducts a multiple linear regression (MLR) including all independent and dependent variables of the model. In a subsection, the author describes the descriptive statistics and inter-correlations of the model. Then the MLR is being processed. After that, in a second step, the author runs two separate MLRs, one with visual nonverbal cues and another with auditory nonverbal cues; both with investment offers as the dependent variable.

5.1. DESCRIPTIVE STATISTICS AND INTER-CORRELATIONS

As a first step, the author analyzes the descriptive statistics (TABLE 3) and the

inter-correlations (TABLE 4) of the data sample. The sample size of the conducted bivariate

correlation is N=52, consisting of 52 companies that proposed their business ventures to the investors. As the first variable of the visual nonverbal cues, illustrators have a mean of 6.51 and a standard deviation of 3.26, which shows that there is a moderate variation in the use of illustrators by the entrepreneurs. Adaptors have a mean of 0.32 per minute and a standard deviation of 0.55, stating that the standard deviation is almost twice as high as the mean, which declares that there is a significant variation of the use of adaptors among the entrepreneurs. On average there are 0.6 smiles per minute with an equally high standard deviation. The frequency of hand and finger movement is with a mean of 0.27 relatively low but has similarly as adaptors a twice as high standard deviation, which shows that there is a relatively higher difference in the frequency of hand and finger movement among the entrepreneurs. The frequency of leg and foot movement is twice the frequency of hand and finger movement with a standard deviation of 0.80. On average, each entrepreneur nods his/her head 1.44 times per minute, with a standard deviation of 1.18 explaining a great dissimilarity among the entrepreneurs’ head movements.

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TABLE 3

Descriptive Statistics, incl. Mean, S.D. and N of Nonverbal Cues and Investment Offers

Variable Mean S.D. N

Illustrators (IL) 6.513 3.263 52 Adaptors (AD) 0.323 0.547 52 Smiling (SM) 0.602 0.602 52 Hand and finger movement (HF) 0.272 0.609 52 Leg and foot movement (LF) 0.595 0.797 52 Head nodding (HN) 1.444 1.180 52 Speech hesitations (SH) 1.053 1.319 52 Speech errors (SE) 0.326 0.419 52 Speech rate in words/min (SR) 127.904 28.133 52 Investment offers (IO) 1,06 1,145 52

Next, to that, a two-tailed partial Pearson’s correlation was conducted to find out whether inter-correlations (TABLE 4) exist between the ten independent and dependent

variables. The following correlation matrix ensures that the analysis is not biased by an unequal distribution of the total sample (N=52):

TABLE 4

Inter-correlations among Nonverbal Cues and Investment Offers

Variable IL AD SM HF LF HN SH SE SR IO

Illustrators (IL) 1.00 Adaptors (AD) -0.02 1.00 Smiling (SM) -0,05 -0.25 1.00

Hand and finger movement (HF) -.28** 0.01 0.05 1.00 Leg and foot movement (LF) 0.03 0.19 -0.26 0.20 1.00 Head nodding (HN) 0.08 -0.08 .36*** 0.01 -0.16 1.00 Speech hesitations (SH) 0.04 -0.01 -0.26 0.15 -0.04 -0.16 1.00 Speech errors (SE) -0.20 -0.05 -0.06 .48*** 0.16 -0.26 0.12 1.00 Speech rate in words/min (SR) 0.00 0.20 0.00 0.02 0.08 -0.06 -0.04 0.06 1.00 Investment offers (IO) -0.12 -0.01 .25* -0,17 -.23 -0.16 -0.15 -0.11 0.08 1.00 Notes: Pearson correlations are reported.

* Correlation is significant at the 0.10 level (2-tailed). ** Correlation is significant at the 0.05 level (2-tailed). *** Correlation is significant at the 0.01 level (2-tailed).

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the 0.10 level. Therefore there is only one relatively high important inter-correlation between speech errors (SE) and hand and finger movements (HF).

5.2. MULTIPLE LINEAR REGRESSION – NONVERBAL CUES ON INVESTMENT OFFERS

In the following, the author computes a MLR including all variables of the model. The MLR model has an R of 0.474 and an R2 of 0.225, which shows that the dependent variable cannot be precisely predicted by the proportion of the variance in the independent variables. Anyhow, the Durbin-Watson test indicates with a measure of 2.275 that there is almost no autocorrelation in the model.

TABLE 5

Multiple Linear Regressions Results of Nonverbal Cues on Investment Offers

Model Summaryb

Model R R2 Adj. R2 SE of the _Estimate Durbin-_Watson

1 0.474 0.225 0.058 1.111 2.275 ANOVAa Sum of Squares df Mean square F Sig.

Model Sum of Squares df Mean square F Sig.

1 Regression 15.012 9 1.668 1.352 .241b Residual 51.815 42 1.234

Total 66.826 51 a. Dependent Variable: Investment Offers

b. Predictors: (Constant), Speech rate in words/min, Smiling, Hand and finger movement, Illustrators, Speech hesitations, Adaptors, Head nodding, Leg and foot movement, Speech errors

Coefficientsa

Unstandardized

Coefficients Standardized Coefficients

Model B S.E. Beta t Sig.

1 (Constant) 1.424 0.870 1.636 0.109 Illustrators (IL) -0.041 0.051 -0.118 -0.820 0.417 Adaptors (AD) 0.112 0.305 0.054 0.369 0.714 Smiling (SM) 0.557 0.303 0.293 1.834 0.074 Hand and finger movement (HF) -0.207 0.313 -0.110 -0.662 0.512 Leg and foot movement (LF) -0.253 0.214 -0.176 -1.180 0.245 Head nodding (HN) -0.304 0.149 -0.313 -2.041 0.048 Speech hesitations (SH) -0.082 0.127 -0.094 -0.644 0.523 Speech errors (SE) -0.306 0.448 -0.112 -0.682 0.499 Speech rate in words/min (SR) 0.003 0.006 0.070 0.500 0.620 a. Dependent Variable: Investment offers

As shown in TABLE 5, the F-test of the MLR model is, with a significance level of 0.241, too

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5.3. POST HOC ANALYSES

In this section, the author separates the nonverbal cues and conducts two different MLRs to raise the chances of obtaining a significant F value.

5.3.1. MULTIPLE LINEAR REGRESSION – VNC ON INVESTMENT OFFERS

The first of these two MLRs includes visual nonverbal cues (VNC), with the variables “illustrators”, “adaptors”, “smiling”, “hand and finger movement”, “leg and foot movement”, and “head nodding”. The second regression consists of the auditory nonverbal cues (ANC), incorporating the variables “speech hesitations”, “speech errors” and “speech rate”. The aim of the author here is to find out whether or not there will be a significant relationship between VNC and investment offers and/or ANC and investment offers.

TABLE 6

Multiple Linear Regressions of Visual Nonverbal Cues on Investment Offers

Model Summaryb

Model R R2 _{Adj. R}2 SE of the

Estimate Durbin-Watson 1 .452a 0.204 0.098 1.087 2.312 ANOVAa Sum of Squares df Mean square F Sig.

Model Sum of Squares df Mean square F Sig.

1 Regression 13.635 6 2.273 1.923 .098b Residual 53.192 45 1.182

Total 66.827 51

a. Dependent Variable: Investment Offers

b. Predictors: (Constant), Head nodding, Hand and finger movement, Adaptors, Illustrators, Leg and foot movement, Smiling

Coefficientsa

Unstandardized

Coefficients Standardized Coefficients

Model B S.E. Beta t Sig.

1 (Constant) 1.524 0.458 3.328 0.002

Illustrators (IL) -0.042 0.049 -0.119 -0.853 0.398

Adaptors (AD) 0.176 0.290 0.084 0.605 0.548

Smiling (SM) 0.621 0.286 .326** 2.175 0.035

Hand and finger movement (HF) -0.343 0.268 -0.182 -1.279 0.208

Leg and foot movement (LF) -0.233 0.206 -0.162 -1.127 0.266

Head nodding (HN) -0.272 0.139 -.280* -1.949 0.058

a. Dependent Variable: Investment offers

* Correlation is significant at the 0.10 level (2-tailed). ** Correlation is significant at the 0.05 level (2-tailed). *** Correlation is significant at the 0.01 level (2-tailed).

The multiple linear regression model (TABLE 6) for visual nonverbal cues has an R of

DO BUSINESS ANGELS REACT TO NONVERBAL CUES?

DO BUSINESS ANGELS REACT TO NONVERBAL CUES?

TABLE OF CONTENTS

LIST OF TABLES

LIST OF FIGURES

DO BUSINESS ANGELS REACT TO NONVERBAL CUES?

1. INTRODUCTION

2. LITERATURE REVIEW

3. HYPOTHESES

4. METHODOLOGY & DATA

5. RESULTS