Valuing young companies. A member-based approach

Table of Contents

1 Introduction

1.2 Course of analysis

1.3 Research motivation

1.4 Research aims and objective

1.5 Possible application

1.6 Methodology

1.6.1 Research approach

1.6.2 Data collection

1.6.3 Case study methodology

1.6.4 Choosing between single and multiple case study approach

1.6.5 Data analysis

2 Common valuation methods

2.1 Traditional valuation approach

2.1.1 Asset value approach

2.1.2 Market value approach

2.1.3 Discounted cash flow

2.2 Real option pricing

2.3 Reconsiderations

3 Network effect models and Customer Valuation

3.1 Network theory

3.2 Literature review in regard to the Customer Valuation

3.3 Customer Valuation

3.3.1 DCF Customer Equity Model

3.3.2 Real Option Customer Equity Model

3.3.3 Binominal scenario tree technique developed by Krafft et al. (2005)

3.4 Reconsideration

4 Case studies

4.1 Investigation into the network effect of social media-based recruiting companies

4.2 LinkedIn case study

4.2.1 LinkedIn – introduction and core products

4.2.2 LinkedIn – PESTLE analysis

4.2.3 LinkedIn - SWOT analysis

4.2.4 LinkedIn – financial statement

4.2.5 LinkedIn – historical stock price

4.2.6 LinkedIn – traditional valuation

4.2.7 LinkedIn – intrinsic valuation

4.2.8 LinkedIn – relative valuation

4.2.9 LinkedIn – investigation into the customer base

4.2.10 Members, page visits and activity

4.2.11 Network effect (Small World)

4.2.12 Network geographically and further considerations

4.2.13 The new model Krafft et al. (2005) - member valuation approach

4.2.14 Comparison of the different methods

4.2.15 Outcome limitations and reconsiderations

4.3 Xing case study

4.3.1 Xing – introduction and core products

4.3.2 Xing – PESTLE analysis

4.3.3 Xing - SWOT analysis

4.3.4 Xing – financial statement

4.3.5 Xing – historical stock price

4.3.6 Xing – traditional valuation

4.3.7 Xing – intrinsic valuation

4.3.8 Xing – relative valuation

4.3.9 Xing – investigation into the customer base

4.3.10 Members, page visits and activity

4.3.11 Network effect (Small World)

4.3.12 The Krafft et al. (2005) model

4.3.13 Comparison of the different methods

4.3.14 Outcome limitations and reconsiderations

4.4 Viadeo case study

4.4.1 Viadeo – introduction and core products

4.4.2 Viadeo – PESTLE analysis

4.4.3 Viadeo – SWOT analysis

4.4.4 Viadeo – traditional valuation

4.4.5 Viadeo – multiple valuation

4.4.6 Viadeo – investigation into the customer base

4.4.7 Members, page visits and activity

4.4.8 The Krafft et al. (2005) model

4.4.9 Comparison of the different methods

4.4.10 Sensitivity analysis

4.4.11 Outcome limitations and reconsiderations

4.5 Cross-case study reconsiderations

5 Findings

6 Conclusions

Objectives and Research Themes

This dissertation aims to improve the valuation process for young, high-growth companies that benefit significantly from network effects. By analyzing the relationship between an organization's customer base and its market value, the study seeks to develop a more accurate predictive model for investment purposes, thereby reducing investment risk and fostering innovation.

• Evaluation of traditional company valuation methods and their limitations for start-ups.
• Investigation of network effects and their impact on customer-based valuation.
• Application of the Krafft et al. (2005) model through comparative case studies.
• Analysis of LinkedIn, Xing, and Viadeo to test member-based valuation accuracy.
• Comparison of quantitative models with historical market performance.

Excerpt from the Book

Summary of Chapters

1 Introduction: This chapter identifies the research gap regarding the valuation of young companies and establishes the motivation, objectives, and methodological approach of the study.

2 Common valuation methods: This section reviews traditional investment valuation techniques, highlighting their limitations for early-stage companies, and discusses the theory-practice gap.

3 Network effect models and Customer Valuation: This chapter explores network theory and examines specific customer-based valuation models, including the DCF Customer Equity and the Krafft et al. (2005) model.

4 Case studies: This chapter applies the proposed member-based valuation method to LinkedIn, Xing, and Viadeo, comparing the results against traditional metrics and historical stock performance.

5 Findings: This chapter synthesizes the research results, confirming that traditional methods are insufficient for young, network-dependent companies and demonstrating the higher accuracy of the member-based approach.

6 Conclusions: The final chapter summarizes the research, acknowledges limitations, and recommends future work in the field of member-based company valuation.

Keywords

Xing, LinkedIn, Viadeo, valuation, investment, seed company, young company, start-up, customer valuation, member prediction, network effect

Frequently Asked Questions

What is the core focus of this research?

The research focuses on improving the valuation of young, high-growth companies, particularly those in the social media and software sector, by integrating the network effect and customer base into the valuation process.

Which sectors are analyzed in this dissertation?

The dissertation primarily examines social media-based recruiting companies, using LinkedIn, Xing, and Viadeo as primary case studies.

What is the main objective of the study?

The objective is to find a more reliable valuation method for young companies that gain significant value from their customer network, which current traditional methods fail to capture accurately.

Which research methods are employed?

The study uses a mixed-method approach, combining a literature review, expert interviews, and three detailed case studies utilizing quantitative and qualitative data.

What does the main body of the work cover?

The main body covers a critique of traditional valuation methods, an exploration of network theories, and the application of the Krafft et al. (2005) model to evaluate how member growth correlates with company value.

What are the primary keywords characterizing this work?

Key terms include valuation, start-up, network effect, customer lifetime value, and the specific companies LinkedIn, Xing, and Viadeo.

How does the Krafft et al. (2005) model differ from traditional methods?

Unlike traditional methods that rely heavily on historical revenue or cash flow data—which are often lacking in start-ups—this model focuses on customer growth and network effects as a basis for valuation.

What were the major conclusions regarding the accuracy of the proposed model?

The case studies indicated that the member-based valuation model showed a higher correlation to historical market prices than traditional DCF models, suggesting it is a more accurate tool for this specific category of companies.