Does labor still lead to love in the presence of the Lean Startup Methodology? : the role of anticipated evaluation and customer feedback on overvaluation due to exertion of effort

Does labor still lead to love in the presence of the Lean Startup

Methodology?

The role of anticipated evaluation and customer feedback on overvaluation due to exertion of

effort.

Mather thesis author:

Under the supervision of:

MSc in Business Administration - Marketing Track

Statement of originality

This document is written by Julie Rogacki who declares to take full responsibility for the content of this document.

I declare that the test and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

Does labor still lead to love in the presence of the Lean Startup Methodology?

The role of anticipated evaluation and customer feedback on overvaluation due to exertion of effort.

Abstract

Most individuals persevere in bad ideas because they genuinely believe that the fruits of their labor is more valuable than others. This overvaluation due to the extension of effort has significant implications for organization as it leads them to dedicate energy and money in failing projects (Norton, Mochon, & Ariely, 2012). This thesis investigates within a Service-Dominant Logic (SD-Logic) framework how two aspects of the Lean Startup Methodology (LSM), namely anticipated evaluation and customer feedback, can have an impact on overvaluation due to exertion of effort. An experiment was conducted in which participants created paper snowflakes under four treatments varying these two aspects. The results demonstrate that customer feedback and anticipated feedback together lead for a higher willingness to pay for self-creation, decreased perceived market value and are unrelated to one’s overvaluation of willingness to pay for self-creation. This research is relevant to practice because it provides more practical content to the SD-logic and clarity on two underlying mechanisms of the LSM.

Table of Contents

Glossary: ... 5

Introduction ... 6

Literature Review ... 9

Service Dominant Logic (SD-Logic) ... 9

Co-creation ... 10

The IKEA-effect ... 11

The Lean Startup Methodology: ... 13

Feedback intervention... 15

Anticipated evaluation ... 16

Methodology ... 19

Experiment ... 19

Procedure ... 19

Measures ... 21

Result ... 25

General discussion ... 35

References ... 39

Appendices ... 42

A) Instructions used in the control group ... 42

B) Instructions used in the anticipated evaluation group ... 43

C) Instruction used in the customer feedback group ... 44

Glossary:

- FIT : Feedback Intervention Theory - GD-Logic: Good Dominant Logic - LSM: Lean Startup Methodology

- MVP: Minimum viable product is the smallest set of features and/or activities required to test a business model hypothesis and complete the “Build-Measure-Learn” cycle.

- SD-Logic: Service Dominant Logic - WTP - Willingness To Pay

Introduction

The 21st century is characterized by a shift in the traditional marketing model by its transition from a Good-Centered Model of Exchange to a Service-Centered Model of Exchange (Vargo and Lusch, 2004). As explained in their first study on Service-Dominant-Logic (SD-Logic; Vargo and Lusch 2004) we are moving toward a dynamic exchange relationships that suggests the exchange of services and/skills and processes are value co-created with the consumer. This transition in marketing is coupled with an interesting phenomena observed by the resurgence of the entrepreneurial spirit, where we see more entrepreneurial activity than ever in the 21st century. Instagram, Facebook, Uber and many others are the recent examples of entrepreneurial success stories. This increasing interest for entrepreneurship can easily be linked to the fundamental concept of co-creation described by the SD-Logic as more and more individuals desire to actively be co-creators of value for the market. Unfortunately, more than 90% of startups fail because of self-destruction rather by competition (Giardino,Wang, & Abrahamsson, 2014). Many startup founders realize too late they spent too much energy and money building a product nobody wants to buy (Eisenmann, Ries, & Dillard 2012). In response to this alarming rate of failure, Eric Ries (2011) introduced the LSM in order to guide entrepreneurs to minimize failure and uncertainty. Although originally developed for startups, this approach characterized by a customer centricity focus is also being used in established company. We observe its usage among some of the most outstanding companies such as Intuit or Dropbox (Silva, Calado, Silva, & Nascimento 2013). Individuals working under the LSM translate their ideas into falsifiable hypotheses, then test the hypotheses using a series of “minimum viable products” (MVP) each of which serve as the smallest set of activities/features required to thoroughly validate a concept. According to the test feedback, individuals must choose whether to proceed with their business model or to “pivot” by adapting some model elements or perish the experiment (Eisenmann et al, 2012). The LSM aims to alleviate cognitive biases that can otherwise lead to poor decisions (Eisenmann et al, 2012) by actively interacting with customer at the earliest stage of the value creation process via its

build-measure-learn feedback loop. The SD-Logic and LSM share an a mutual interest for value to be co-created by several actors including the beneficiary (Vargo and Lusch, 2004; Eisenmann et al, 2012). The SD-Logic is described by its authors as a mindset in which economic and social interaction phenomena but does not have a “worldview” position (2008); but little practical guidance is provided to its readers. The LSM can be seen as a response to needs outlined by the authors (Vargo and Lusch, 2008) for a market-centered perspective to provide more inputs on the concept of value creation and exchange. What make the LSM different from most of the other co-creation practices is its structured process and early contact with the customer aiming to “fail fast, Fail cheap” (Eisenmann et al, 2012). Still a lot of uncertainty is observed in regards of the full good practices and implications of co-creation in marketing research and practices (Payne, Storkbacka, and Frow, 2008).

Does labor still lead to love under the Lean Startup Methodology? This research aims to investigate the impact of anticipated evaluation and customer feedback on overvaluation due to the exertion of effort on value creation. In a previously conducted research by Norton, Mochon, and Ariely (2011) called the IKEA-effect the authors demonstrated that labor leads to overvaluation of self-creation when consumers are engaging in effort. The IKEA-effect is known a cognitive bias in which consumers hold a disproportionately higher value and liking for self-creations (Norton et al., 2011;2012); the primary purpose of this study was to replicate the formerly found IKEA-effect study and to investigation the impact of anticipated evaluation and customer feedback on employees. Anticipated evaluation is a core aspect of the LSM as individuals have to keep iterating their ideas until they find a product market-fit via its build-measure-learn feedback loop. We expect a Negative impact of on one’s evaluation as negativity enhancement is an underlying mechanisms of anticipated evaluations (Ofir and Simonson, 2001). Customer feedback is fundamental to the LSM as “build continuous feedback loop with the customer during the product development process’’ is the way how Mueller & Thoring (2010) characterized the LSM. This interest for customer centricity enables organizations to create a product customer want. Customer feedback is expected to have a positive impact on performance as the feedback appointing the right solution is positively correlated with an increase in performance (Kluger and DeNisi, 1996).

This study contributes to research by satisfying the call for further research made by Ofir and Simonson (2001) in regards of the impact of expecting to evaluate in different contexts as in the original study the concept was experiment on consumers. Moreover, still too little is known on how customers should engage in the co-creation of value (Payne et al. 2006) and the current research is relevant to practice as it provides more practical content to the SD-logic and clarity of the impact of two underlying mechanisms of the LSM. Lastly, this research addresses the need for a deeper understanding on how feedback intervention have or not a positive impact on performance (Kluger and DeNisi, 1996).

To answer the research question an experiment was executed. A literature review is presented in the subsequent section, covering Lean Startup and potential mechanisms underlying the SD-Logic leading towards the hypothesis of this thesis. Next, the methodology introducing the experiment in which the research set-up, data collection and conclusion are explained. Finally, a general discussion displaying the overall conclusion is presented, limitations and contribution to research and recommendations for future research.

Literature Review

Service Dominant Logic (SD-Logic)

This section explains the “Service Dominant Logic”. The SD-Logic was first introduced in 2004 in “Evolving to a New Dominant Logic for Marketing” by Vargo and Lusch and has since received a great deal of attention (Vargo and Lusch, 2008).

The foundational premises of Service-Dominant Logic are: ● Service is the fundamental basis of exchange

● Indirect exchange masks the fundamental basis of exchange ● Goods are a distribution mechanism for service provision

● Operant resources are the fundamental sources of competitive advantage ● All economies are services economies

● The customer is always a co-creator of value

● The enterprise cannot deliver value, but only offer value propositions ● A service-centered view in inherently customer oriented and relational ● All social and economic actors are resource integrators

● Value is always uniquely and phenomenologically determined by the beneficiary

The authors (Vargo and Lusch, 2004) explain that marketing thought has taken a new direction over the past several decades. They explain that marketing focus shifted from a Good Dominant Logic (GD- Logic) in which tangible output, and discrete transactions were fundamental, to a Service Dominant Logic (SD-Logic), in which intangibility, exchange process, and relationship are fundamental (Vargo and Lusch, 2004). The SD-Logic is described by the authors as a mindset characterised by an unified understanding of the role and characteristics of market, society and organization (Vargo and Lusch, 2008). The main premise of the SD-Logic is that all actors are

the prosperity of a party. In another word the authors explained that service is traded for service; that all firms are considered to be services firms; all market are about the exchange of services; and that the whole market is centered around service (Vargo and Lusch, 2004; 2008). This new orientation around service logic principles and theories represent this new marketing thought and practices (Vargo and Lusch, 2004; 2008). The SD-Logic is about the concepts of value-in-use and co-creation of value, and not about value-in-exchange and embedded concepts of the GD-logic (Vargo and Lusch, 2004; 2008). In this new logic firms are not longer the ones directing the market to customers; but firms have to interact with customers as partners to market alongside with others value-creation partners.

Co-creation

This section explains co-creation which is fundamental aspect of the SD-Logic as explained above. Under the SD-Logic the customer turn into a co-creator of value. This highlight the development of customer-supplier relationships via interaction and dialogue. Co-creation can be defined from different perspectives (Payne et al., 2006). The co-creation of value is a wanted goal as it helps company in displaying the customer's mentality and better the front-end process of spotting customers’ needs and wants (Lusch and Vargo, 2006). The use of co-creation by Vargo and Lusch’ (2006) is to some extend interrelated with the concept of GD-Logic. There are five ways in which the co-creation can be observed: i) the customer and the supplier exclusively engage in the important of the co-design of products; ii) self-service such as IKEA where there is a transmission of labor to the customers in important activity; ii) where the supplier offer an experience such as Disney Theme Parks and the customer is part of it; iv) the emotional engagement of customers via broadcasting; and lastly v) the self-selection of customer supplier’s recommended devices to clear up a precise problem (Payne et al., 2006). There is an evolution and transition of customers from “passive audiences” to “active players” (Prahalad and Ramaswamy., 2000). In the context of S-D logic, research on co-creation has emphasized their work on: fulfilling expectations (Olivier, 2006); co-creating the opinion

of the costumer (Jaworski and Kohli, 2006); marketing strategy effectiveness and operational efficiency (Kalaignanam and Varadarajan, 2006).

Three main processes: customer value-creating process, supplier value creating processes and encounter processes design the basis of the concept of co-creation (Payne et al., 2006). i)Customer value creating processes is explained as a business to consumer relationship; supplier value creating processes (Payne et al., 2006); ii) Supplier value creating processes is characterized by the resources and practices which the supplier handles its relationships with customer and other pertinent partners (Payne et al., 2006). iii) Encounter processes is seen as the practices and processes of interaction taking place within customer and supplier relationships that need to be monitored in order to expand a successful co-creation opportunities (Payne et al., 2006).

The IKEA-effect

As exposed by Payne et al., (2006) self-service is a type of co-creation where a transfer of labor to the customer is observed. The champion of this practice is the famous giant Swedish retailer IKEA who successfully find a way to actively engage with its customer. Despite the popularity of the co-creation phenomena, co-creation is also subject to biases such as the IKEA-effect. This part of the study has for objective to explain the IKEA-effect. The IKEA-effect is a cognitive bias in which consumer hold a disproportionately higher value and liking for self-creations (Norton et al., 2012). In four studies, Norton et al. (2012) demonstrated and explored the existence of the IKEA-effect. Participants were given IKEA boxes, folded origami and build sets of Legos, and when asked to estimate the value of their amateurish creations, they appraised them as identical in value to experts’ creations, and expected others to share their assumptions. The authors demonstrated that this increasing liking for self-creations only occurred when successful completion of tasks was observed. The IKEA-effect disappeared when participants had unbuilt their creations or if they failed to complete it (Norton et al., 2012). The forecast of success of one’s labor is essential for the IKEA-effect to appear. Based on an extensive body of literature, human have an intrinsic need for effectance (Norton, et al., 2011). Effectance is characterized as the capacity to successfully create desired outcome in one’s

environment by which individual achieve this ambition by gathering possessions and objects (Ahuvia, 2005; Belk, 1998: Dittmar, 1992, Furby, 1991). Research on efficacy indicated that the successful completion of tasks is one crucial mechanism by which individuals meet their objective to feel in control and competent, and it is an essential element for the link between liking and labor (White, 1959; Norton et al., 2012). We note that the use of hedonic and non customizable objects by the authors (Norton et al., 2012) enabled the generalization of the IKEA-effect; as well as the conclusion that the emergence of the IKEA-effect did not only emerge as a potential result of individual’s needs for adapting their creations to their preferences. Lastly, in their conclusions, the authors (Norton et al., 2011) stated that action demanding joint production leading to spread ownership across multiple parties have a negative impact on the contributor liking for its creation. This conclusion statement made by Norton et al., (2011) on the negative impact of spread ownership brings our interest towards the impact of the customer feedback and anticipated evaluation on one’s liking for self-creation.

H1 – Customer feedback and anticipated evaluation have a negative impact on one’s liking for self-creation

Several underlying psychological mechanisms were explored to assess what was driving this increasing in liking for self-assemble products. Previous research exhibits that individuals tend to like objects they have been endowed (Kahenman, Knetsch, & Thaler 1991; Langer, 1975) establishing the possibility that overvaluation may be a result of ownership of products and not due to exertion of effort. Researchers also proposed that the more time spent touching objects may be a reason for the observed value sensitivity of ownership and utility (Pecker & Shu, 2009). However, the result of the experiment conducted by Norton et al. (2011) were conflicting with an explanation around the endowment effect or touch. Aronson and Mills (1959) proposed that this increase in liking may be a result of the positive feelings of affectance that follow successful completion of tasks (Bandura, 1977). It is likely that creating products raise both attention about the positive aspect of that product (Ariely and Simonson, 2003; Carmon Wertenbroch and Zeelenberg, 2003; Dhar and Wertenbroch, 2000) and positive affect and emotional attachment to that product (McGraw, Tetlock, & Kritel, 2003)

both displayed to have the capability to influence. Despites some critics (Zwick, Bonsu, & Darmody, 2008) more and more companies are trying to associate consumers in the marketing, testing and design of their products (Bateson, 1985; Lengnick-Hall, 1996; Mills & Morros, 1986). This overvaluation observed by the IKEA-effect has significant implications for organizations, as the IKEA-effect may be resistant in any interventions, leading managers to devote energy and money to failing projects (Norton, Mochon, & Ariely, 2012). However, Bill Aulet (2014) in Discipline

entrepreneurship: 24 steps to a successful startup, cautions professionals to not let the IKEA-effect

blind companies on what the customers really want. This interest for customer centricity brings our attention towards to the Lean Startup Methodology known as a scientific drawn on a Learn-Build-Measure feedback loop aiming to minimize failure.

The Lean Startup Methodology:

The LSM is a hypothesis-driven methodology that was first proposed by Eric Ries (2011) in his book “The Lean Startup”. The book is often labeled as the Silicon Valley bible and it has its primary ideas borrowed from the web-based startups handling high degree of uncertainty (Ries, 2011). As explained by Eisenmann et al. (2012) the use of the lean startup method decrease uncertainty by using its feedback look constantly testing ideas in the market. It does not only ensure that the product development process is fast and iterative, but also ensure that you “fail fast, fail cheap” (Ries, 2011).

The method revolves around 7 Steps:

Step 1: Develop a Vision

Step 2: Translate the Vision into Hypothesis Step 3: Specify MVP Tests

Step 4: Prioritize Tests

Step 5: Learn from MVP Tests Step 6: Persevere, Pivot or Perish

The 7 steps explained above can be explained as follows: to start with the build-measure-learn loop it is important to first begin by investigating what the problem is and to set MVP to start learning. Entrepreneur have to start with an idea and presumptions that are not yet validated. As soon as this is created the MVP is tested with the customer and the decision of validating or rejecting the assumption is based on the feedback gathered (Eisenmann et al., 2012). The experimentation with a MVP through a continuous cycle of build-measure-learn individuals makes iterations until a viable business model has been established for the product (Eisenmann et al., 2012).

For the purpose of this research only one of these 7 steps displayed above will be emphasized- Step 6: Persevere, Pivot, Perish as we will explore the impact of customer feedback and anticipated evaluation. Persevere is explained as the MVP approve the business model hypothesis and other feedback does not lead to a change in direction. The entrepreneurs continues on his actual direction by either testing remaining hypothesis or- if all hypothesis have been approved by preparing to scale. (Eisenmann et al., 2012). Pivot: Pivoting is observed when the MVP test declines the proposed business model or hypothesis. Pivoting implies to adjust some business element while keeping others as greater opportunity are elsewhere (Eisenmann et al., 2012). Under the LSM pivoting is not considered as a goal or as something to be bypassed. Pivoting can be expensive and troublesome; but failing to pivot when assumptions are admitted to be improper can be highly catastrophic and damaging (Eisenmann et al., 2012). Perish: Perish is observed when entrepreneurs cannot establish a plausible pivot and the MVP test unquestionably dismiss an important business model hypothesis. This continuous iterations implies for individuals to anticipate continuous evaluation. We note that the lean principles have its roots in the Japanese manufacturing industry and was first mentioned by John Krafcik in 1988 in his article named the “The Triumph of the Lean Production System”. In that article lean is defined as a systematic method within a manufacturing system to reduce waste in which there is no sacrifice on the productivity. In the context of the LSM it means trying to lessen the use of resources of everything that does not increase customer value (Eisenmann et al., 2012). Nonetheless, there are some situations in which the LSM display lower advantages and where the entrepreneur should customized lean techniques or pursue another development. These situation can be illustrated

by when mistakes must be avoided; when uncertainty of demand is small or by when long product development cycle prevent launching early and often (Eisenmann et al., 2012).

Feedback intervention

Feedback is information collected from customers in regards of his or her past action (Annett, 1969). Taylor, Fisher and Ilgen (1984) propose that feedback is necessary for organizational effectiveness and not providing feedback can lead to anxiety, defective self-evaluations, and a deviation of effort toward feedback gathering activities. The dynamic between performance feedback and attitudinal outcomes and various behavioral are equivatenly complicated and still not completely understood. A key skill to develop sustainable competitive advantage for organization is defined as the capability to find out and fulfill customers’ needs and desires (Awuah, 2006). Customer feedbacks lead to the possibility of organizational learning on how to better employee-customer interactions resulting in a better service quality (Babbar and Koufteros, 2008; Madden et al., 2007; Tontini and Silveria, 2007). The first comprehensive theory of feedback was offered by Kluger and DeNisi (1996). Their Feedback Intervention Theory (FIT) relies on five main assumptions. i) goals or standards are formulated hierarchically between three levels of control: task-motivation, meta-task processes involving the self and task learning; ii) attention is normally conducted to a balance level of the hierarchy (attention is typically on task-motivation processes); iii) behavior is moderated by comparisons to standards or goals; iv) attention is finite and, therefore, only feedback-standard gaps that collect attention can actually regulate behavior; lastly v) feedback interventions has an impact on behavior by changing individuals' locus of attention. Alder (2007) explains that feedback effectiveness reduce as attention moves up toward the hierarchy closer to the self and away from the task. FIT propose that cues of the feedback message regulate the extent to which action regulation will or not gain the most consideration (Alder, 2007). Several cues may bring consideration away from the task toward other goals of the self such as meta-task processes and therefore have a negative impact on performance (Alder, 2007). These cues incorporate normative feedback, computer-mediated versus person feedback, feedback arranged to demoralize or encourage the recipient, and feedback aiming to

threaten the self. FIT exposed by Kluger and DeNisi's (1996) was the first major contribution on the feedback process. FIT assume that characteristics of feedback have an impact on the extent to which recipients focus on either task-motivation processes or meta-task processes and that level of attention moderates the feedback-performance relationship (Alder, 2007). Hence, we expect customer feedback and anticipated evaluation to have a positive impact on performance as Customer feedbacks as explained above can lead to the eventuality of a better service quality (Babbar and Koufteros, 2008; Madden et al., 2007; Tontini and Silveria, 2007).

H2- Customer feedback and anticipated evaluation have a positive impact on performance

Anticipated evaluation

The lean startup methodology as described above is a feedback loop in which individuals have to conduct experimentations with MVP through a continuous cycle of build-measure-learning; in which iterations are needed until a viable business model is established. The continuous cycle associated with iteration portray a continuous expectation of evaluation occurring throughout the entire hypothesis testing. Ofir and Simonson (2001) offered via a series of laboratory studies demonstrating that expecting evaluation lead individuals to evaluate less favorably the quality of product and to display lower satisfaction. The negative bias described by the authors was present even when the actual quality was either high or low (Ofir and Simonson, 2001). Vigilant processing and expecting evaluation were explored as exclusive ways but not necessarily mutual to interpret the valence of evaluation (Ofir and Simonson, 2001).

Vigilant processing suggests that expected evaluation lead to more accurate and rigorous evaluations; these evaluations are not observed to be more negative or positive (Ofir and Simonson, 2001). Greater attention to specific details in real time are observed when individuals know ahead about their responsibilities of evaluation; enabling the establishment of a more accurate assessment not based on evaluation from memory (Ofir and Simonson, 2001). Expected evaluation is derived from a gradual processing of attributes or individual element of the evaluated stimulus (Fiske and Pavelchak, 1996).

As anticipated evaluation’s underlying mechanisms is vigilant processing we expect customer feedback and anticipated evaluation to have an unrelated relationship with one’s overvaluation of willingness to pay for self-creation.

H3- Customer feedback and anticipated evaluation have an unrelated relationship with one’s overvaluation of willingness to pay for self-creation

Contrariwise, a request of evaluation following consumption may be assessed as an evaluation potentially based on its outcome. Satisfaction and quality evaluation can be made more precisely and more useful if individual know ahead that they will be inquire to provide evaluations. Individuals expecting to evaluate put more consideration in their evaluations, whereas individuals unexpecting evaluation may reckon on fuzzy memories.

Negativity enhancement is established on the notion that negative information is more pronounced and earn more attention than positive performance in the formation of judgements. Individuals pay more attention and emphasize negative aspects in a more pronounced way when expecting to provide evaluations as opposed to individuals unexpectedly asked to evaluate a service or product. This difference of attention between expected to evaluate and unexpected form the basis of the negativity enhancement. When expected to evaluate the negativity enhancement will change the manner in which individuals process and encode their experience leading to more negative evaluations (Ofir & Simonson, 2011). Intuitive prediction is inaccurate and expecting to evaluate leads to the production of a systematic bias in the form of overly negative and unrepresentative evaluations rather than in the form of improved accuracy. Hence, we expect that customer feedback and anticipated evaluation to have a negative impact on one’s willingness to pay for self-creation and perceived market value for self-creation as a result of the impact of the underlying mechanisms of negativity enhancement

H4 – Customer feedback and anticipated evaluation have a negative impact on one’s willingness to pay for self-creation

H5- Customer feedback and anticipated evaluation have a negative impact on perceived market value for self-creation

Methodology

For the purpose of testing the hypothesis one experiment was conducted. Under this experiment participants had to create paper snowflakes with the purpose of investigating if customer feedback and anticipated evaluation have or not an impact on individuals’ willingness to pay, perceived market value and likeability for self-creation. Following the experiment, an additional set of participants were asked to bid on our builder’s creations, establishing market value for each creation and a benchmark on how far above the market price our builders priced their own creations.

Experiment

The experiment used a 2 (customers feedback: yes or no) x 2 (evaluation expected: yes or no) between subject design. The aim of the experiment was to investigate if there were an effect of customer feedback and anticipated evaluation on participants’ self-creation in regards of their: willingness to pay, perceived market value, likeability, and overvaluation. In this experiment participants were asked to create a paper snowflake based on four different conditions and had to report their answers on the Qualtrics software.

Procedure

This experiment is a combination and variation of three studies previously conducted: the IKEA effect (Norton et al., 2011), In Search of Negative customer feedback: The Effect of Expecting to Evaluate

on Satisfaction Evaluations (Ofir & Simonson, 2001) and the Lean Startup (Ries, 2012). The current

experiment used a 2 (customers feedback: yes or no) x 2 (evaluation expected: yes or no) between subject design; an alternative to the study conducted by Ofir and Simonson (2001) in which participants were randomly assigned to one of four conditions in a 2 (evaluation expected: yes or no) x 2 (expectations stated: yes or no). The purpose of the current experiment was to investigate if customer feedback and anticipated evaluation have an impact on individuals’ self-creations in regards

IKEA-effect study (Norton et al., 2011) individuals had to disclose under the same procedure their willingness to pay and liking for self-creations; another set of participants were asked to bid on our builder’s creations enabling the assessment of how far above the market value our participants estimated their own creations. Lastly, the experiment attempted to set participants in an environment where they had to work under the Lean Startup methodology. Participants were told that there were a market need for paper snowflakes and that their objectives was to run a profitable business by creating and selling paper snowflake as display in the Appendix section. The choice of using paper snowflakes was inspired by an already existing workshop on the Lean Startup Methodology conducted by André Dhondt. Moreover, as the experiment was conducted in december the use of paper snowflake aimed to increase credibility as for the market need for paper snowflake in the market. Regardless, of the condition in which individuals were randomly allocated; participants had to both follow the paper instruction as illustrated in the appendix and customize their creations to what would be the perfect paper snowflake for the market according to them. The freedom and uncertainty provided by the possibility of one’s making its own assumption was voluntary as in the Lean Startup individuals have to translate their idea into falsifiable hypothesis in an uncertain environment (Ries, 2012).

Participants (N=104; 47 male, 57 female, Mage= 23.12, SD=5.12) at different universities in Amsterdam were receiving cookies for creating paper snowflakes in the first week of December 2017. Participants were told that that a market study revealed a high demand for paper snowflakes and they were the only ones knowing about it. One hundred and four participants were randomly assigned to one of four conditions in a 2 (customers feedback: yes or no) x 2 (evaluation expected: yes or no) between subject design. In all conditions participants were given a pair of scissors and an A4 piece of paper. One experimenter was sitting with the participant when creating the paper snowflake. The study was conducted in conjunction with Qualtrics software.

In the expected evaluation task, participants were informed that after creating the paper snowflake they would be contacted and informed about the reactions of individuals potentially interesting into purchasing their creations. In all conditions participants after the initial stage, participants were asked

the three following questions: (1) Please make a bid on your snowflake between 0 to 100 cents. A random number between 0 and 100 will be drawn ; if your number is equal or above that number, you will have to pay that amount and take your creation home, while if your bid is below the number we will keep your creation; (2) What do you think is the market value of your snowflake? (Between 0 to 100 cents); (3) How much do you like your creation? (1=not at all, 7=very much)

The last step of the experiment was conducted by another set of participants (N=4; 2 males, 2 females,

Mage= 26,75, SD=1,26) who were asked to provide a bid on the perceived market of each creation.

The value attributed by our participants’ willingness to pay was then subtracted to one attributed by our assessors.

Measures

Independent Variable

All independent variables were assessed on a categorical scale. Participants were randomly appointed to one of the four conditions where they were presented to a potential situation. The first condition, the control group, did not involve any manipulation of variable and served a base group. The second condition, included the manipulation of customer feedback. For the third condition, anticipated evaluation was manipulated. Lastly, for the fourth condition customer feedback and anticipated evaluation were manipulated together. The customer feedbacks were identical in the two groups (with and without the expected evaluation manipulation) in which this manipulation was enforced.

Customer Feedback: Participants working under this condition were working with an experimenter

acting as a customer to them. By acting as a factual customer the experimenter guided each participants with instructions aiming to express a factual customer opinion on the product being created. (Wu, Wei, Liu, & Au, 2010). As explained by the authors (Wu, et al.,2010) customer feedback is a combination of opinion and subjective logic modeling uncertainty from customers ; and a means for improvement of current practices (Fundin & Bergman., 2003). After several exchanges

with the original author of the Lean Startup Workshop, André Dhondt, and extensive research on paper snowflake best practices on internet a set list of feedbacks were created following the logic displayed by the authors mentioned earlier (Fundin & Bergman., 2003; Wu, & et al., 2010) . This created list of customer feedbacks was first pre-tested prior to the experiment on another sample (N=13) of participants. The pre-test had for goal to ensure that feedbacks provided during the experiment were formulated as a combination of opinion and subjective logic and as a means for participant to improve their creations. The instruction of customer feedbacks were as the following: At the beginning of the experiment participants were asked to fold more precisely the piece paper given to them to create the snowflake demanded. During the task creation participants were also instructed that making deep cuts would provide a better shape to their creations and would satisfy existing customer needs. Finally, when participants would claim to be done with their creations, they were asked to cut-out one extra piece.

Anticipated Evaluation: Participants were told at the beginning of the experiment that their creations

will be evaluated by a panel of individuals interested into potentially purchasing their creations; and that they will be contacted again to share these individuals reactions. This manipulation is a variation of the study conducted by Ofir and Simonson (2001) in which customers of a call centers were randomly assigned to one of four conditions in a 2 (evaluations expected: yes or no) x 2 ( expectation stated: yes or no) between-subjects design. In this previous study participants in the expected evaluation task were told that after receiving the service they would be approached again. Adding on Fishbein and Ajzen’s (1975) model of attitude formation, satisfaction judgment are characterized by the fact individuals have to expect to receive a formation of satisfaction; we note that this model of satisfaction are assumed to be built on the basis of disconfirmation levels on several attributes. This model do not propose any assumptions about the relative weights of negative or positive disconfirmation.

Customer Feedback and Anticipated Evaluation: In this condition participants were working under

Dependent Variable

Willingness to pay and perceived market value were measured on a discrete scale. Likeability was measured on a ordinal scale.

Willingness to pay: Identical measure as in the initial IKEA-effect study (Norton et al., 2011).

Participants were asked how much they will be willing to pay for their creations from 0 to 100 cents. They were told that a random price (from an unknown distribution) will be drawn and if their reservation was equal or higher to that random number, they will have to pay the amount and keep their creations. But if their reservation was below the random number draw, they will not be able to acquire their self-creation and we will keep their creations. This approach is an alternative of the Becker-DeGroot-Marschak (1964) and is perceive as suitable way to establish value elicitation.

Perceived Market Value: Participants were asked what they believe to be the market value of their

creation from 0 to 100 cents.

Likeability: Identical measure as in the initial IKEA-effect study (Norton et al., 2011). Participants

graded how much they liked their snowflake on a 7-point scale (1:not at all to 7: very much).

Performance: Identical measure as in the initial IKEA-effect study (Norton et al., 2011). Utility attributed by a the other set of participants on the paper snowflake made in the latter stage of the experiment. Participants were asked how much they will be willing to pay for other’s creations from 0 to 100 cents. They were told that a random price (from an unknown distribution) will be draw and if their reservation was equal or higher to that random number, they will have to pay the amount and keep their creations. But if their reservation was below the random number draw, they will not be able to acquire others’ creations and we will keep these creations. This approach is an alternative of the Becker-DeGroot-Marschak (1964) and is perceived as suitable way to establish value elicitation.

Overvaluation willingness to pay: The overvaluation of willingness to pay is the subtraction of the value attributed by the set of assessors on each individual's paper snowflakes minus the corresponding willingness to pay for self-creation revealed in the experiment.

The complete experimental procedure took 7 days. In the result section, the dependent variables were assessed one by one.

Result

Dependent Variable

Table 1: Correlation table

Likeability

A factorial analysis of variance (ANOVA) was conducted to evaluate the relationship between customer feedback and anticipated evaluation on likeability for self-creation. The result of the likeability in the four conditions are represented in tables 2.

N M SD No Customer Feedback; No Anticipated Evaluation 25 4,80 1,71 Customer Feedback; No Anticipated Evaluation 25 5,00 1,29 No Customer Feedback; Anticipated Evaluation 29 4,38 1,55

Customer Feedback and Anticipated Evaluation

25 5,52 0.96

SS DF MS F η2 Sig Customer feedback 11,635 1 11,635 5,845 ,055 ,017 Anticipated Evaluation ,064 1 ,064 ,032 ,000321 ,858 Customer feedback * Anticipated Evaluation 5,728 1 5,728 2,877 ,093 ,093 Error 199,068 100 1,991 Total 2718,000 104

Table 2.2: Likeability Factorial Anova table

There was a significant main effect of customer feedback on likeability for self-creation, F(1,100)=5,845, p=,017 partial η2=,055. Nonetheless, a non-significant main effect of anticipated evaluation on likeability for self-creation, F(1,100)=,858p=,006 partial η2=,000321 and a non-significant interaction effect between customer feedback and anticipated evaluation on likeability market value for self-creation F(1, 100) = 2,877, p =.093, η2 =,093 were detected.

These results do not support the hypothesis 1 stating that customer feedback and anticipated evaluation have a negative impact on one’s liking for self-creation. Anticipated evaluation does not have a significant impact on one’s liking for self-creation. However, as opposed to what Norton and al stated (2011) joint-contribution, represented in this experiment as customer feedback, did not have a negative impact on one’s liking for self-creation. Result from the factorial analysis revealed that regardless of anticipated evaluation, customer feedback have a positive impact on one’s liking for self-creation in comparison to when it is not present (M=5,26 versus M=4,59 ).

Performance

A factorial analysis of variance (ANOVA) was conducted to evaluate the relationship between customer feedback and anticipated evaluation on performance. The result of the performance in the four conditions are represented in tables 3.

N M SD No Customer Feedback; No Anticipated Evaluation 25 24,04 24,54 Customer Feedback; No Anticipated Evaluation 25 49,28 13,82 No Customer Feedback; Anticipated Evaluation 29 28,14 26,98

Customer Feedback and Anticipated Evaluation

25 56,72 17,93

Table 3.1: Mean of the Performance per condition

SS DF MS F η2 Sig Customer feedback 18751,705 1 18751,705 5,845 ,285 7,7677E-9 Anticipated Evaluation 861,739 1 861,739 ,032 ,018 ,179 Customer feedback * Anticipated Evaluation 72,302 1 72,302 2,877 ,002 ,696 Error 47130,488 100 471,305 Total 225681,000 104

There was a non-significant main effect of anticipated evaluation on performance for self-creation, F(1,100)=1,828p=,197 partial η2=,018. However, there was a significant main effect of customer feedback on performance for self-creation, F(1,100)=39,787 p= 7,7677E-9 partial η2=,285. Lastly, there was a non-significant interaction effect between customer feedback and anticipated evaluation on performance for self-creation F(1, 100) = ,153 p =,696, η2 =,002.

These results partially support the hypothesis 2 stating that customer feedback and anticipated evaluation have a positive impact on individual’s performance. Regardless of the anticipated evaluation, customer feedback had a main effect leading to an increase of 103 % in performance (M=26,10 versus M=53,00). The interaction demonstrated that when enforced jointly anticipated evaluation and customer feedback do not have a significant impact on individuals performance for self-creation. We note that anticipated evaluation does not have a significant main effect meaning on performance meaning that anticipated evaluation does not have a significant impact on performance.

Willingness to pay overvaluation

A factorial analysis of variance (ANOVA) was conducted to evaluate the relationship between customer feedback and anticipated evaluation on willingness to pay overvaluation. The result of the willingness to pay overvaluation in the four conditions are represented in tables 4.

N M SD No Customer Feedback; No Anticipated Evaluation 25 22,44 28,84 Customer Feedback; No Anticipated Evaluation 25 -15,56 25,24

No Customer Feedback; Anticipated Evaluation

29 -4,07 32,32

Customer Feedback and Anticipated Evaluation

25 -9,56 28,93

Table 4.1: Mean of the Willingness to pay overvaluation per condition

SS DF MS F η2 Sig Customer feedback 12243,891 1 12243,891 14,476 ,126 ,000245 Anticipated Evaluation 2722,748 1 2722,748 3,219 ,031 ,076 Customer feedback * Anticipated Evaluation 6841,105 1 6841,105 8,088 ,075 ,005 Error 84580,342 100 845,803 Total 105987,000 104

Table 4.2: Willingness to pay overvaluation Factorial Anova table

There was a significant main effect of customer feedback on willingness to pay overvaluation for self-creation, F(1,100)=14,476 p=,000245 partial η2=,126. However, anticipated evaluation had a non-significant effect on willingness to pay overvaluation for self-creation, F(1,100)=3,219 p=,076 partial η2=,126 was found. Lastly, a significant interaction effect between customer feedback and anticipated evaluation on willingness to pay overvaluation for self-creation F(1, 100) = 8,088 p =,005, η2 =,075 was found0111. Gabriel post-hoc tests revealed that participants working under the anticipating evaluation condition (p=,007), customer feedback (p=<,001) and both customer feedback and anticipated evaluation (p=,01) were significantly different from the control group.

These result support the hypothesis 3 stating that customer feedback and anticipated evaluate is unrelated to individual’s willingness to pay overvaluation. Regardless of anticipated evaluation, customer feedback has main effect on individual’s willingness to pay overvaluation leading to a significant decrease of 21% in individual’s willingness to pay overvaluation. The interaction effect revealed that anticipated evaluation and customer feedback lead to a decrease in willingness to pay overvaluation. Participants overvalued 26% more their own creations when there were no customer feedback and no anticipated evaluation as compared to when no customer feedback and anticipated evaluation were observed (M=22,44 versus M=-4,07). Interestingly, in the presence of customer feedback but no anticipated evaluation participants undervalued more their creation than when anticipated evaluation was present (M=-15,56 versus M=-9,56)

Willingness to pay

An analysis of variance (ANOVA) was conducted to evaluate the relationship between customer feedback and anticipated evaluation on the willingness to pay. The result of the willingness to pay in the four conditions are represented in tables 5.

N M SD No Customer Feedback; No Anticipated Evaluation 25 46,46 26,84 Customer Feedback; No Anticipated Evaluation 25 33,72 26,63 No Customer Feedback; Anticipated Evaluation 29 24,07 24,14

Customer Feedback and Anticipated Evaluation

25 47,16 30,84

SS DF MS F η2 Sig Customer feedback 690,888 1 690,888 ,936 ,009 ,336 Anticipated Evaluation 520,961 1 520,961 ,706 ,007 ,403 Customer feedback * Anticipated Evaluation 8320,001 1 8320,001 11,268 ,101 ,001 Error 73834,502 100 738,345 Total 228672 104

Table 5.2: Willingness to pay Factorial Anova table

There was a non significant main effect of customer feedback F(1,100)=,936, p=,336 partial η2=,009 and anticipated evaluation F(1,100)=,706, p=,403 partial η2=,007 on willingness to pay for self-creation. A significant interaction effect between customer feedback and anticipated evaluation was also found on the willingness to pay for self-creation F(1, 100) = 11,268, p =,001, η2 = ,101. Gabriel post-hoc tests revealed two significant differences between anticipated evaluation and customer feedback coupled with anticipated evaluation at p=,014; as well as a significant difference between anticipated evaluation with the control condition at p=,019.

These results partially support the hypothesis 4 stating that customer feedback and anticipated evaluation have a negative impact on one’s willingness to pay for self-creation. The experiment portrayed that when enforced separately customer feedbacks and anticipated evaluation do not have impact on individuals willingness to pay for self-creation. However, the result of the interaction effect revealed that working under both anticipated evaluation and customer feedback lead to a increase of willingness to pay for self-creation compared to individuals only working under anticipated evaluation (M=47,16 versus M=24,07). Moreover, when only customer feedback was observed participants were willing to pay 13 % less than when anticipated evaluation and customer feedback

were both not combined (M=33,72 versus M=46,48). Interestingly, when customer feedback and anticipated evaluation were observed together the willingness to pay for self-creation was slightly higher (0,68%) than when customer feedback and anticipated evaluation were both absent (M=46,48 versus M=47,16). These results portrayed that when observed separately customer feedbacks and anticipated evaluation do not have impact on individuals willingness to pay for self-creation. But interestingly when enforced together the interaction effect revealed that the willingness to pay for self-creation is actually slightly higher than when not combined.

Perceived Market Value

An analysis of variance (ANOVA) was conducted to evaluate the relationship between customer feedback and anticipated evaluation on the perceived market value for self-creation. The result of the willingness to pay in the four conditions are represented in table 6.

N M SD No Customer Feedback; No Anticipated Evaluation 25 41.64 32,09 Customer Feedback; No Anticipated Evaluation 25 28,64 25,58 No Customer Feedback; Anticipated Evaluation 29 17,79 17,92

Customer Feedback and Anticipated Evaluation

25 25,72 18,62

SS DF MS F η2 Sig Customer feedback 166,597 1 166,597 ,289 ,003 ,592 Anticipated Evaluation 4637,843 1 4637,843 8,032 ,074 ,006 Customer feedback * Anticipated Evaluation 2834,847 1 2834,847 4,909 ,047 ,029 Error 57745,319 100 577,453 Total 147318,000 104

Table 6.2 : Perceived Market Value Factorial Anova table

There was a non-significant main effect of customer feedback F(1,100)=,289, p=,592 partial η2=,003 on perceived market value for self-creation. However, a significant main effect of anticipated evaluation on perceived market value for self-creation F(1,100)=8,032, p=,006 partial η2=,074 was found. Lastly, a significant interaction effect between customer feedback and anticipated evaluation on perceived market value for self-creation was also observed F(1, 100) = 4,909, p =,029, η2 = ,047. Gabriel post-hoc tests revealed a significant difference between the anticipated evaluation condition and the anticipated evaluation with customer feedback at p=,014; as well as a significant difference between anticipated evaluation and the control condition at p=,019.

These results support hypothesis 5 stating that customer feedback and anticipated evaluation have a negative impact on perceived market value for self-creation. Regardless of customer feedback, the main effect revealed that anticipated evaluation itself have a negative impact of 38% on individuals’ perceived market value for self-creations (M=35,14 versus M=21,76). Based on the interaction effect it was found that when enforced jointly customer feedbacks and anticipated evaluation the perceived market value for self-creation was 57% higher compared to situation when only anticipated evaluation was applied (M=41,64 versus M=17,79). The lowest perceived market value for self-creation was

feedback was observed with or not anticipated evaluation the perceived market value the difference was only of 11,35% (M=25,72 versus M=28,64). Interestingly, when customer feedback and anticipated evaluation were observed together participants valued 62% less their creations than when no customer feedback and no anticipated evaluation were present (M=25,72 versus M=41,64).

General discussion

Does Labor still lead to love in the presence of the Lean Startup Methodology? This study had to goal to investigate the role of anticipated evaluation and co-creation on overvaluation due to exertion of effort. The current research showed that anticipated evaluation and customer feedbacks have an impact on customer willingness to pay for self-creation.

The results demonstrated that hypothesis 4 which stated that anticipated evaluation and customer feedback lead to a decrease in willingness to pay for self-creation was partially supported. In the presence of both anticipated evaluation and customer feedback participants were not willing to pay less for self-creation, but they were actually willing to pay more. The interaction effect of individuals willingness to pay revealed that in the presence of anticipated or anticipated evaluation participants were willing to pay less for self-creation. Nevertheless, the results found via the interaction effect support the hypothesis 5 which stated that anticipated evaluation and customer feedbacks have a negative impact on perceived market valuation. We also note that anticipated feedback alone display a negative main effect on individual perceived market value. Furthermore, the results do not support hypothesis 1 which stated that anticipated evaluation and customer feedbacks have a negative impact on one’s liking for self-creation. Anticipated evaluation did not have an impact on one’s liking for self-creation. However joint contribution, illustrated in this research by customer feedback, have a significant positive impact on one’s liking for self-creation. These findings are going against the statement made by Ariely et al. (2012) stating that joint contribution have a negative impact on one’s liking for self creation. Interestingly, customer feedback also displayed a positive impact on performance. These results partially support hypothesis 2 as anticipated evaluation did not have any impact on performance for self-creation. Lastly, the results supported hypothesis 3 which stated that anticipated feedback and customer evaluation were unrelated to willingness to pay overvaluation as in the presence of customer feedback and anticipated evaluation participants did not overvalue their self-creation. We also note that customer feedback alone has for main effect to decrease one’s willingness to pay overvaluation.

This study relates to previous work by replicating and adapting the IKEA-effect study conducted by Norton et al., (2011) on employees and looked at the impact of two additional variables: anticipated evaluation and customers feedback. It also relates to the study conducted by Ofir and Simonson (2001) on the impact of anticipated evaluation on consumers expect to evaluation; by investigating the role anticipated evaluation on other context such as its impact on produces. Lastly, it provides more practical guidance to managers on the core concept of co-creation in the SD-Logic and understanding of the impact of two important concepts of the Lean Startup. Previous studies demonstrated that engaging in effort to obtain an outcome have for effect an increase in willingness to pay and liking for self-creation. This has been labelled the IKEA-effect (Norton et al., 2011). In the original study of the IKEA-effect (Norton et al., 2011) participants were given IKEA boxes, folded origami and build sets of Legos and estimated their amateurish creations as identical in value to expert’s creations, and expected others to share their assumptions. However, in that initial study of Norton et al. (2011) participants were asked to create hedonic products for themselves and not for the purpose of serving someone’s needs. Research on anticipated evaluation conducted by Offir and Simonson (2001) was operated on customers’ evaluation of quality and satisfaction. The authors demonstrated that expecting to evaluate lead to lower satisfaction evaluation and reduced significantly one’s willingness to acquire and endorse the assessed services. However, the underlying mechanisms, vigilant processing and negativity enhancement, still remain the same as for when one’s have to anticipate evaluation regardless of whom is the receiver. Research should explore further the impact of expected to evaluate in other context and about the tasks characteristics on consumer’s evaluation on satisfaction and quality (Offir and Simonson, 2001); as well as the need for a greater understanding on how feedback intervention has or not a positive impact on performance (Kluger and DeNisi, 1996). This research contributes to the literature in several ways. First, this research addresses the literature gap in the effects of anticipated evaluation in other context and about the tasks characteristics by exploring the effect of anticipated evaluation on self-creation. One experiment was conducted to assess the effects of anticipated evaluation on five different variables: willingness to pay, perceived market valuation, liking, performance and willingness to pay overvaluation. Second, this research added two new variables, customer feedback and anticipated evaluation, to the initial study conducted

by Norton et al., (2011) named the IKEA-effect. It also investigated how creating a product for someone else need may impact the so-called IKEA effect. Further research may still be needed to assess further how the change of recipient for self-creation may or not have an impact on the IKEA-effect. Interestingly, results displayed contradicting finding to the statement made by the authors in their initial study (Norton et al., 2001). Joint-contribution, represented here under the form of customer feedback, had a positive impact on one’s liking for self-creation and not negative impact as expected. These findings could potentially also be explained by the fact that when participants were exposed to customer feedback they did not only like more their creations, but their performances were also part of the highest among all groups. As in the initial study we note that the increase of liking for self-creation is also interrelated with the feeling of competence (Norton et al., 2011). Moreover, in the current research participants were required to display some creativity, but also had to face some constraints under the form of customer feedback and with the instructions provided to create the paper snowflake. Dahl and Moreau (2007) proposed that having restriction on the level of creativity one’s have can lead to an increase in satisfaction with self-creation. Furthermore, the introduction of customer feedback led to not only increase in liking for self-creation; but also to the observation that this increase of liking was positively correlated with an increase in performance. In the current research the customer feedbacks were present in order to provide constructive insights and guidance to better improve self- creations represented here as paper snowflake. This increase in liking could also be explained as by what many study stated by proving the motivational benefits on assigning individuals tasks they can feel able to complete (Grant and Parker, 2009; Hackman and Oldman, 1976). However, the current research displayed that customer feedback had a negative main effect on willingness to pay overvaluation. These result provide greater clarification on the statement made by Norton et al. (2011) by proving by when one’s work under customer feedback its liking and performance for self-creation increase, but decrease one’s willingness to pay overvaluation. It would be interesting for future research to explore if this increase in performance and liking are the results of a correlation or a causality. Lastly, this research broaden the understanding of two underlying mechanisms of the lean startup mechanism known as customer feedbacks and anticipated evaluation;

getting more and more trendy however; for still too many individuals it is still too arduous to fully grasp the full impact of this popular new methodology and on how to successfully implement it. A deeper understanding of the impact of underlying mechanisms of the lean startup such as the customer feedback and anticipated evaluation on different variables provide great contribution to management practices. These results should enable manager to have a better understanding on what to watch out when instrumentalizing customer feedback and anticipated evaluation; these results also provide guidance about the impact of customer feedback and anticipated evaluation on different variable such as willingness to pay, liking, perceived market evaluation or overvaluation for self-creation which is crucial for company in order to avoid allocating resources in failing projects. The results proved that anticipated evaluation and customer feedback were unrelated to overvaluation and that customer feedback has for main effect to decrease one’s willingness to pay overvaluation. Finally, these findings were in contradiction with the statement made by Norton et al. (2012) in which they authors advocated that the IKEA-effect may be persistent to any intervention and that only the market may at time correct these flawed overvaluation. Nonetheless, the current research only explored two aspects of the lean startup methodology. Future research may want to investigate as well the impact of other underlying mechanisms of the lean startup such as the impact of iteration or pivoting.

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Appendices