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University of Amsterdam

Customer loyalty through

online communities

THE CASE OF

KLM Club China

Master Thesis

Master in Business Studies

Student:

Tom Stevens

Student number:

5626536

Supervisor:

Prof. Dr. J.H.J.P. Tettero

2

nd

Supervisor:

Drs. Ing. A.C.J. Meulemans

Supervisor KLM:

Stuart Makosi

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ACKNOWLEDGEMENTS

I am very happy to present this thesis about the effect of the introduction of KLM Club China on flying behavior. In February 2007 my seven months of internship at KLM started. Inspired by this internship, I decided to finish my master thesis in line of my internship.

I would like to thank several people who contributed to the success of this thesis and to the success of finishing my Bachelor and Master studies at the Universities of Groningen and Amsterdam. First of all I would like thank my supervisor Prof. Dr. J.H.J.P. Tettero for his guidance and advice, which helped me to improve the structure and quality of this thesis. Next to that, I am very grateful to all people at KLM who supported and motivated me during my internship and the period of finishing this thesis. A special thanks goes to my manager Stuart Makosi and to Charles Hageman for their help and inspiration. I would also like to make use of this opportunity to deeply thank my parents for giving me the freedom to study and to enjoy my period of studying both at home and abroad. Furthermore I would like to thank my grilfriend Carmen for her contribution to this thesis and even more for her contribution to a wonderful period of studying. I am really looking forward to celebrate our graduation in Mexico! Finally, I would like to thank my biggest source of inspiration and extremely appreciated friend; my grandfather, I am more than happy to make you proud with my graduation.

For more than six years I very much enjoyed my life as a college student. Now I feel ready for a new phase in life.

Tom Stevens

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ABSTRACT

The airline industry is a marginal and highly competitive business. The effects of the worldwide economic slump, high fuel prices and the aftermath of September 11th attacks, have impacted airline economics and viability (Boland, Morrison and O’Neil, 2002). Besides reducing internal and external costs, airlines start realizing that customers cannot be ignored (Boland, Morrison and O’Neil, 2002). A successful implemented CRM program is responsible for building and maintaining relations with selected customers. In building and maintaining these relationships, using the rights touchpoints is evident in enlarging customer loyalty. In order to ultimately sell extra tickets to potential and existing customers, KLM started up a new touchpoint for a specific chosen target group; the online community KLM Club China. The introduction of KLM Club China has led to the following research question:

‘What is the effect of the introduction of KLM Club China on flying behavior at KLM?’ In order to answer this question two different empirical studies are performed; a flying behavior study and a quantitative online survey. According to the flying behavior study, the conclusion can be drawn that KLM Club China members do not significantly increase their flying behavior towards China after becoming member of the community. No evidence of a positive contribution of KLM Club China on flying behavior has been recognized. Results from the online survey show that in general members of KLM Club China do not rate the community very highly and that the expectations members had before joining the club have only somewhat been met. In evaluating the community, four key criteria of successful communities have been analyzed. Both the technical factors and activity rate of members can be considered as positive. The (live)contact possibilities with fellow members and especially the clearness of the communities’ ultimate goal can be considered as less positive. Next to that, a fifth key factor is of influence on a communities’ success in this particular KLM Club China case. The extent to which people are already involved with the owner of the community is of significant influence on the appreciation of the community. From this evaluation, the conclusion can be drawn that all five key factors together influence the appreciation and thus success of the community. The missing or insufficiency of one or more key factors, in this case understanding the communities’ ultimate goal, strongly negatively influences the overall appreciation and thus the success of the community.

However, different ratings from different groups can be distinguished. Active members, who can be considered as the largest group within the community, members with a lower Flying Blue level (ivory) and members who visit the KLM Club China live events, are more

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satisfied about the community than others. Especially among these groups members state that their membership of KLM Club China does positively influence their appreciation towards KLM, involvement with KLM and interest in flying with KLM in general and to China.

This research shows that the introduction of KLM Club China does not contribute to increasing flying behavior in the first place, but that by attracting more new members and members of lower Flying Blue levels to the Club, consolidating members’ activity rate, clearly communicating the communities’ goal and organizing and promoting KLM Club China live events, success can be achieved.

Keywords: customer relationship management, airline industry, customer loyalty, online communities.

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TABLE OF CONTENTS

ACKNOWLEDGEMENTS ... 2

ABSTRACT ... 3

TABLE OF CONTENTS ... 5

1. INTRODUCTION ... 7

1.1 KLM Royal Dutch Airlines ... 7

1.2 KLM Club China ... 9

1.2.1 KLM Club China – Website and features ...10

1.2.2 KLM Club China – Members ...11

1.2.3 KLM Club China – Competitors ...13

2. PROBLEM STATEMENT ... 14

2.1 Sub-questions...14

2.2 Scientific relevance ...15

2.3 Data gathering and analyzing ...15

2.4 Research model ...15

3. LITERATURE STUDY ... 17

3.1 Customer Relationship Management ...17

3.1.1 Customer Relationship Management - History ...17

3.1.2 Customer Relationship Management - Definition ...18

3.1.3 Impact of CRM implementations in the airline industry ...19

3.1.4 Pitfalls and critical success factors in CRM implementation ...21

3.1.5 Sub-conclusion 1 ...23

3.2 Customer loyalty ...23

3.2.1 The concept of customer loyalty ...24

3.2.2 Profitability of customer loyalty ...24

3.2.3 Principles of profitable customer loyalty ...25

3.2.4 Sub-conclusion 2 ...26

3.3 Online communities ...26

3.3.1 The concept of online communities ...27

3.3.2 Value creation through online communities ...28

3.3.3 Success factors of online communities...29

3.3.4 Sub-conclusion 3 ...30

3.4 Conceptual model...30

4. METHODOLOGY ... 33

4.1 Study 1: Flying behavior ...33

4.2 Study 2: Online survey ...34

4.2.1 Questionnaire design ...34

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5. RESULTS ... 36

5.1 Study 1: Flying behavior ...36

5.1.1 Members and non-members May 2006 ...38

5.1.2 Members and non-members August 2006 ...39

5.2 Study 2: Online survey ...41

5.2.1 Profile and background respondents ...42

5.2.2 Appreciation KLM Club China ...45

5.2.3 Added value KLM Club China for members ...50

5.2.4 Added value KLM Club China for KLM ...51

5.3 Discussion and interpretation of results ...56

6. CONCLUSION, LIMITATIONS AND RECOMMENDATIONS ... 60

6.1 Conclusion...60

6.2 Limitations ...63

6.3 Recommendations ...64

REFERENCES ... 65

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1. INTRODUCTION

The airline industry is a marginal and highly competitive business. The game is played around 3 major aspects which are price, schedule and loyalty programme (Ritter, 2007). The effects of the worldwide economic slump, high fuel prices and the aftermath of September 11th attacks, have impacted airline economics and viability (Boland, Morrison, O’Neill, 2002). In order to reduce costs, many airlines worldwide have focused on operational improvements. Besides reducing internal and external (e.g. travel agent commissions) costs, airlines start realizing that the customer cannot be ignored (Boland, Morrison, O’Neill, 2002). Therefore Boland, Morrison and O’Neill (2001, p.1) concluded that ‘as airlines struggle to gain market share and sustain profitability in today’s fiercely competitive and economically demanding environment, they must develop new ways to manage their customer relationships to optimize customer loyalty and revenues.’

The places where the relationship between an airline and a customer is built are the customer contact points (touchpoints) (Beckmann and Sindemann, 2006). Technological developments have highly impacted the characteristics of the current customer contact points. Nowadays, company’s customer contact points can include the Internet, e-mail, sales, direct mail, telemarketing operations, call centres, advertising, stores and so on (Chen and Popovich, 2003). Specified to the airline industry, touchpoints can be distinguished into five categories according to Beckmann and Sindermann (2006):

1. Pre-flight (incl. website, ticket office, sales force and call center) 2. Departure airport (incl. check-in, lounge and gate)

3. Inflight (incl. cabin crew and inflight entertainment) 4. Arrival airport (incl. baggage claim and arrival lounge) 5. Post-flight (incl. website and call center)

Positioned by the company itself as the innovative airline, KLM is continuously seeking for new customer contact points.

Strengthened by the current consumer trend - the changing role of the customer from consuming to experiencing (Ritter, 2007) - KLM started to see travellers more as permanent customers than periodical travellers. Therefore the company expanded the pre- and post-flight touchpoints with an online community; KLM Club China.

1.1 KLM Royal Dutch Airlines

KLM Royal Dutch Airlines is an international airline operating worldwide, within the Air France KLM Group. The Air France KLM Group was formed in 2004 and is member of SkyTeam Alliance, a global alliance in which several important European, American and Asian airlines have joined forces to make their passengers’ travel experience seamless

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and convenient across allied carriers. KLM’s home base is Amsterdam Airport Schiphol. As part of Air France KLM, KLM has 3 core activities:

→ Passenger transport (nearly 22 million passengers in 2006/2007) → Cargo transport (620,000 tons of cargo in 2006/2007)

→ Engineering & Maintenance (provided services to more than 100 airlines in 2006/2007)

In fiscal year 2007/2008, Air France KLM passenger business carried 73,5 million passengers and reported an operating income of €1,07 billion on €18,37 billion revenue. KLM has a workforce of more than 30,000, of whom almost 27,000 are employed in the Netherlands.

KLM’ s mission statement: By striving to attain excellence as an airline and by participating in the world's most successful airline alliance, KLM intends to generate value for its customers, employees and shareholders.

KLM Club China is part of the CRM department of KLM, which is part of the Marketing & Brand section of the Commercial Division.

Figure 1.1, KLM’s Commercial Division

Within the passenger business, KLM is split into the Commercial division, Inflight Services, Flight Operations, Ground Services, Network, KLM Cityhopper, and Operations

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control & Fleet Services. Marketing & Brand is positioned within the commercial division, being responsible for:

→ The specification of KLM’s product & services

→ KLM’s brand, brand positioning, corporate identity and marketing communication → The Air France / KLM loyalty program Flying Blue

→ KLM’s CRM strategy and execution, including Customer research and Customer Care.

Figure 1.2, KLM’s Marketing & Brand Organization

1.2 KLM Club China

May 2006, KLM Club China was introduced together with the launch of flights to Chengdu, as the first online Business Community developed by KLM. KLM Club China can be considered as an expansion of the companies’ CRM program. Membership of KLM’s frequent flyer program Flying Blue is required in order to become member of KLM Club China. According to the business case ‘KLM Club China aims at expanding KLM’s core passenger travel business with a value added service.’ With the introduction of KLM Club China, KLM starts seeing passengers more as permanent customers than frequent flyers. The airline has specifically chosen for Club ‘China’. ‘China is a fast growing economy but still difficult to penetrate because of culture and language differences. Through KLM’s

Introduction: May 2006

Objective: Generate direct and indirect revenue. Direct revenue is supposed to

be generated by capitalizing on the customer database and advertising income from partners and sponsors. Indirect revenue is expected from increased customer loyalty, resulting in increase number and value per boarding (Business Case KLM Club China, 2006)

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strong core position in China, the airline will be able to help customers bridge the difficulties’ (Business Case KLM Club China, 2006).

KLM’s traditional circle of contact reflects the interaction between KLM and the customer, as required from an operational perspective of consuming KLM’s service. In terms of consuming experience, the traditional circle of contact covers the purchasing experience and the consumption experience, as described by Caru and Cova (2006). Through Club China, KLM enlarges its circle of contact towards customers, covering more experience phases of the customer and therewith bringing KLM closer to the customer, ultimately resulting in improved customer intimacy (Ritter, 2007).

Figure 1.3, KLM’s circle of contact

1.2.1 KLM Club China – Website and features

KLM Club China offers Business people doing business in and with China, an online platform which can help them in their success in doing business in and with China. In average, 3400 unique visitors1 and 6000 visitors2 visit the website of KLM Club China each month.

1 A unique visitor is a statistic describing a unit of traffic to a Website, counting each visitor only once in the time frame of the report.

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Members of KLM Club China are able to share information about themselves and their companies on the website. More than 95% of all active members added additional information about themselves and their professions to their profiles. Members can provide each other from useful (business)information, via contributing tips, experiences, calendar items and classifieds. Next to that, the Club China team and third parties regularly contribute relevant and interesting information about doing business in China to the website. The message center enables KLM Club China members to directly communicate with each other. Each day members send each other 122 messages in average. The message center can be considered as a tool to maintain business contacts and enlarge members’ networks. Members contact each other for business or pleasure reasons. Via offline events organized by KLM Club China, the community shifts from online to offline. Several partners of KLM Club China offer the Club members premium services and discounts. In the current situation membership of KLM Club China is free of charge. Within a limited period of time, the KLM Club China team will introduce different levels of membership. This will go hand in hand with the introduction of a paid membership.

1.2.2 KLM Club China – Members

August 2007, 4300 members living in 102 countries joined KLM Club China. The large amount of Dutch members can be explained through the focus of KLM Club China on its home-market; The Netherlands. All events except one have been held in the Netherlands and promotional activities are often organized at Schiphol airport.

43%

31% 14%

12%

The Netherlands Other Great Britain China Figure 1.4, KLM Club China members by country – August 2007

In order to become KLM Club China member, membership of the Flying Blue program is required. KLM distinguishes 4 levels of Flying Blue membership; platinum, gold, silver

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and ivory, whereby platinum can be considered as the highest level in membership. Taken all KLM Club China members into account, the following division can be made.

29%

24% 17%

30%

Platinum Gold Silver Ivory

Figure 1.5, KLM Club China members sorted by Flying Blue membership – August 2007.

The target group of the network consists of all business people doing business in and with China. The general opinion within KLM is that the community seems to be more interesting for Small & Medium Enterprises than Multinationals, who have in general more sources to find the most relevant (business)information.

25% 25% 20% 13% 17% 1 t/m 10 10 t/m 100 100 t/m 1000 1000 t/m 10.000 > 10.000

Figure 1.6, KLM Club China members specified by company size – August 2007

In 2005, 18 KLM airplanes per week flew to China. With an average capacity of 370 passengers and load factor of 87% (www.klm.com), over 300.000 passengers travelled

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with KLM to China in 2005. With the increasing number of flights and destinations3, the number of passengers travelling from or to China with KLM will be much bigger in 2007. Mentioning this, the percentage of the target group who actually became member in the past 16 months is relative low.

1.2.3 KLM Club China – Competitors

The concept of KLM Club China is unique. Not one competitor is offering a similar service. Obviously, competition can be noticed in different kind of China minded communities / networks. Via search engines as Google (key words: China business Club, China community, Club China) and the business case of KLM Club China, several competitors have been recognized. Most of the China oriented business clubs are specifically focused on networking (China clubs in Xing, Stanford Greater China Club, China Business Club, China table of the Industrieele Groote Club). Above business clubs organize lectures, informal drinks and other ‘get-togethers’. Other China oriented business clubs have a more informative character (China Business Directory, Geledraak.nl, EVD, Business-China.com). Members and in some cases non-members of these clubs can gain information about doing business in China, such as Chinese regulations, market-information and market-information about ethics and etiquettes. None of these services combines the networking and informative characteristics (Business Case KLM Club China, 2006).

3 Details are described in chapter 5.

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2. PROBLEM STATEMENT

Both market and technological trends influence the development of innovations within KLM and the overall airline industry. KLM Club China can be noticed as a pioneer in the field of implementing Web 2.0 opportunities in a frequent flyer program. All major airlines implement and exploit frequent flyer programs to stimulate customer loyalty. However, KLM is the first airline that attempts to enlarge the circle of contact by introducing an online community. Prior to developing and implementing new communities, it is absolutely necessary to measure the impact of these new services. Therefore the key question of this research can be defined as follows:

‘What is the effect of the introduction of KLM Club China on flying behavior at KLM?’ In this thesis, flying behavior can be considered as the frequency of flights towards China.

2.1 Sub-questions

In order to be able to answer the key question of this research, both a literature study and empirical study are performed. The following sub-questions are formulated for the literature study:

→ What is Customer Relationship Management? → What is the impact of CRM in the airline industry?

→ What are the pitfalls and critical success factors in CRM implementation? → What is customer loyalty?

→ Is customer loyalty profitable?

→ What are the principles of profitable customer loyalty? → What is an online community?

→ How can online communities create value?

→ What are the success factors of online communities?

The following sub-questions are formulated for the empirical study: → How many flights and destinations does KLM offer to China?

→ How many flights to China do KLM Club China members make per year? → How many flights to China do non-KLM Club China members make per year? → Is a difference in flying behavior towards China notable between KLM Club China

members and non-KLM Club China members?

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→ How do KLM Club China members appreciate KLM Club China? → What is the added value of KLM Club China for members? → What is the added value of KLM Club China for KLM?

2.2 Scientific relevance

The scientific relevance of this research is to contribute insight in the combination of CRM, customer loyalty and online communities. What is the impact of such a community on customer loyalty? How can those communities create value? Both questions are able to add important value to the already existing theory.

With the results of this research managers at KLM should be able to consider a strategy in the development of both coming and existing communities.

2.3 Data gathering and analyzing

In order to find an answer to the main question, two different empirical studies are performed:

1. The flying behavior (frequency of flights) towards China of in total 842 KLM Club China members is investigated. In order to notice a possible difference through KLM Club China in flying behavior, the frequency of flights during membership is compared with the frequency of flights in the same period a year before membership. These results are compared with a control group of in total 753 travellers who joined KLM Club China in a later stage in order to identify a possible difference.

2. A quantitative online survey conducted by 3900 KLM Club China members (return rate of 27,8%; 1086 participants) gives insight in the appreciation, usability and success of the community.

Through connecting both studies, the effect of membership of KLM Club China on flying behavior is measured.

Data collected out of the online survey and the itinerary database will both be analyzed via the statistical program SPSS and presented in chapter 5 and the appendices.

2.4 Research model

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Figure 2.1, Research model

The research model shows the structure which will be followed in this thesis. After introducing the current market situation, company, KLM Club China and problem statement (chapter 1 & 2), chapter 3 covers the literature study. The topics of CRM (3.1), customer loyalty (3.2) and online communities (3.3) form together with the concept of KLM Club China the conceptual model (3.4). Sub-questions defined in chapter 2, are answered in the different paragraphs of chapter 3.

Chapter 4 provides the reader insight in the methods of research, data collection and sampling and questionnaire design. A schematic representation of the KLM Club China study has been given in paragraph 4.3.

Results of both researches are presented and interpreted in chapter 5. In Chapter 6, the conclusion, limitations and ultimately recommendations for further research are given.

Research model Chapter 6. Conclusion, limitations & recommen-dations Chapter 4. Methodo-logy Chapter 5. Research results and interpre-tations 3.1 CRM 3.2 Customer loyalty 3.3 Online communities 3.4 Conceptual model 5.1 Study 1: Flying behavior 5.2 Study 2: Online survey 5.3 Interpre-tation of the results Chapter 3. Literature study Chapter 1&2 Introduction and problem statement

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3. LITERATURE STUDY

The basis of each scientific study lies in the study of recent literature that is related to the subject of study. In this chapter a theoretical framework is developed and a conceptual model is presented. The conceptual model form the basis for this study.

3.1 Customer Relationship Management

In order to be able to answer the sub-questions related to CRM - What is Customer Relationship Management? What is the impact of CRM in the airline industry? What are the pitfalls and critical success factors in CRM implementation? – literature concerning this topic is investigated and defined in this chapter.

3.1.1 Customer Relationship Management - History

The origins of Customer Relations Management (CRM) can be traced back to the Management Concept of Relations Marketing (RM). In the 1980’s, several scholars and managers recognized the benefits of managing relations (Jackson, 1985 and Webster, 1992). Levitt (1983), and Dwyer, Schurr and Oh (1987) were pioneers in proposing a systematic approach for the development of the buyer-seller relationships. Together with the influence of several information system concepts as Computer Aided Selling (CAS) and Sales Force Automation (SFA), Relations Marketing merged towards integrated CRM systems (Gebert, Geib, Kolbe and Riempp, 2003).

The airline industry started in the 1980’s to look at using CRM tools to understand their customers better (Darby and Simone, 2006) and increase loyalty (Binggeli, Gupta and de Pommes, 2002). Nowadays CRM programs are used in a wide variety of industries to identify and retain valuable customers, stimulate the indecisive ones to spend more, and to cut cost of serving those who are less valuable (Binggeli, Gupta and de Pommes, 2002).

Organizations focused on long-term relations with their customers, have more chance to survive and to develop in profitable organizations (Peelen, 1999). As a result, the former focus on single transactions shifted to a focus on long-term relations (Peelen, 1999). Dwyer et al. (1987) recognized the shift from transaction-marketing to relation-marketing in the 1980’s. Developments in the environment of the organizations and technology improvements stimulated this process. Willenborg and Leeflang (1996) explained the revaluation of the long-term relation concept through external developments. According to them, these external developments are:

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→ Increased knowledge and power of consumers

→ A bigger but less differentiated offer of products in the maturity phase of the product-life-cycle

→ Internationalizing and globalizing of markets → Developments in the information technology

→ Increased power of retailers, decreased power of manufacturers. → Privatizing of organizations

Because of these external developments, suppliers faced difficulties in distinguishing themselves from their competitors. Long-term relationships with consumers help organizations in strengthening their market position (Willenborg and Leeflang, 1996). Through the evolution form product or brand management to customer management (Sheth, 2005) and from product portfolio management to customer portfolio management (Johnson and Selnes, 2004), there was an explosion of customer data in the 1980’s and 1990’s (Boulding, Staelin, Ehret and Johnston, 2005). ICT developments such as the introduction of the Internet, enabled marketers to directly communicate with consumers (one-to-one marketing, direct marketing), to store and analyze customer information (database marketing) and to set up learning relations with individual customers (relationship marketing). Using these data and analyses, organizations began to focus on acquiring new customers, retaining current customers and ‘enhancing these relationships through such activities as customized communications, cross-selling and the segmentation of firms, depending on their value to the firm’ (Boulding, Staelin, Ehret and Johnston, p. 156, 2005).

3.1.2 Customer Relationship Management - Definition

Customer Relationships Management is such a broad and developing concept that it is difficult to find one all-embracing definition. Many scholars have defined the concept of CRM over the last decades.

Peelen (2003) looks at CRM from an ICT perspective. According to Peelen, CRM is the automation of horizontally integrated business processes involving front office customer contact points via multiple, interconnected delivery channels.

Verhoef and Langerak (2002) integrate both the marketing and ICT perspective in defining CRM. According to them CRM is a process that primarily focus on the development and maintenance of relationships with individual customers in such a way that for both parties value is created. Customer databases, statistical decision support tools and interactive communication techniques (internet, call centers) assist firms in developing and maintaining the relationships.

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Chen and Popovich (p. 672, 2003) emphasize the combination of people, processes and technology in their definition of CRM: ‘Customer relationship management is a combination of people, processes and technology that seeks to understand a company’s customer. It is an integrated approach to managing relationships by focusing on customer retention and relationship development.’

Payne and Frow approach CRM from the management perspective. As others scholars, they emphasize the combination of building and maintaining a relationship and technology. Therefore Payne and Frows’ definition of CRM is most comprehensive and covers essential elements found in various definitions about CRM:

‘CRM is a management approach that seeks to create, develop and enhance relationships with carefully targeted customers in order to maximize customer value, corporate profitability and thus shareholder value. CRM is primarily concerned with utilizing information technology to implement relationship marketing strategies’ (Payne and Frow, 2000, p.2).

3.1.3 Impact of CRM implementations in the airline industry

For full-services airlines, CRM is essential in their strategy (Boland, Morrison, O’Neill, 2002). Through differentiating themselves from competitors in the eyes of customers, airlines can create competitive advantage (Boland, Morrison, O’Neill, 2002). CRM applications help organizations in the airline industry assess customer loyalty and profitability on measures and customer information (Chen and Popovich, 2003). Recent advances in information technology (IT) have enabled airlines to turn customer information into customer insight. Information about customers can be selected via several ways, for instance via the website (surf and click behavior) and fill-in forms (to join a frequent flyer program, during flights etc.). Understanding customer behavior is important to adjusting business strategies and finding new opportunities. Frequent-flyer programs and data warehousing have provided a possibility to gain additional insight into the traveller’s behavior and preferences. Such insights can provide useful information which can be acted upon during interactions with the customer (Boland, Morrison, O’Neill, 2002).

The effects of the worldwide economic slump, high fuel prices and the aftermath of September 11th attacks, have impacted airline economics and viability (Boland, Morrison, O’Neill, 2002). Besides reducing internal and external (e.g. travel agent commissions) costs, many airlines are turning customer relationship management as a tool for managing customer relationships (Boland, Morrison, O’Neill, 2002).

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Research conducted by Bingelli, Gupta and de Pommes (2002) emphasize the impact and value of well implemented CRM programs in the airline industry. According to their research a well implemented CRM program can increase an airline’s revenue by as much as 2,4% a year, representing an annual impact of $100 million – $250 million for a large carrier (2002, Table 3.1.). According to their research, a well implemented CRM program increase revenues through ‘reduced churn (0,5-1,1%), growth in wallet share (0,3-1,2%) and new customers (0,05%) (Bingelli, Gupta and de Pommes, 2002, p.2). Revenue from reduced (through elimination of waste through targeting unprofitable customers and reduce of marginal flights costs due to increased business) and increased costs (CRM implementation costs) cancels each other.

Scope of airline Possible impact

Large Airline (RPK4 = 76 million – 200 million)

$100 million - $250 million Midsize Airline (RPK = 21 million – 76

million)

$25 million - $60 million Small Airline (RPK = 5 million – 21

million)

$15 million - $50 million

Table 3.1, The impact of a well implemented CRM program for airlines (Bingelli, Gupta and de Pommes (2002)).

Next to these numbers, Boland, Morrison and O’Neill (2002) figured out that 3,5% of the customers is responsible for 16% of the revenue (figure 3.1.). Bingelli, Gupta and de Pommes (2002) believe that it is over-simplified to allocate elite frequent flyers as the top 3,5% customers. According to them, a significant number of customers in the lower tiers of the frequent flyer program could be of greater value than passengers in the upper tiers. Regular travellers who pay full fare prices can be of greater value than frequent flyers who receive several discounts. ‘By assessing customers’ value to the company, and their key needs, the business can determine which customers it should retain and how it can migrate lower-value customers to higher-value segments’ (Boland, Morrison, O’Neill, p. 5, 2002).

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Figure 3.1, Airline customer value segmentation by revenue (Boland, Morrison and O’Neill (2002)) Supported by these figures and research conducted by The Economist Intelligence Unit (2007), which considers customer engagement as the base for creating crucial competitive advantage, the impact of having a good relationship with frequent customers is clear. The places where the relationship between an airline and a customer are built are the customer contact points; touchpoints (Beckmann and Sindemann, 2006). ‘Often these touchpoints are controlled by separate information systems. CRM integrates touchpoints around a common view of the customer’ (Chen and Popovich, p. 673, 2003). Collecting and integrating information from different touchpoints is a perfect tool in allocating revenues and costs to customers (Beckmann and Sindemann, 2006). Through the transaction database, an understanding of historic customer profitability based on transactions will be created. Through mixing the historic data with information received from other touchpoints (complaint behavior, lost luggage information etc.) customer’s development potential and customers’ future value can be predicted. Through creating an overview of costs and revenues per customer or per target group, underinvestment can be eliminated and overinvestment reduced (Beckmann and Sindemann, 2006).

3.1.4 Pitfalls and critical success factors in CRM implementation

‘Companies that successfully implement CRM will reap the rewards in customer loyalty and long run profitability’ (Chen and Popovich, p.672, 2003). Unfortunately, the vast majority of CRM implementations fail (Lovelock and Wirtz, 2004). CRM implementation failure rate is as high as approximately 65% (Apicella, Mitchell and Dugan, 1999). ‘If CRM is implemented in a way that leads consumers to believe that they are worse off, firms can put themselves at substantial risk. Information reciprocity can break down, and consumers may ultimately choose to opt out of relationships’ (Boulding, Staelin, Ehret

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and Johnston, p. 159, 2005). Therefore, it is extremely important to understand the pitfalls and success factors in CRM implementation.

An important aspect in a random CRM implementation is the collection of data. Sometimes a firm can collect information about the customer during the transaction, other times companies must rely on the customers’ readiness providing this information (Boulding, Staelin, Ehret and Johnston, 2005). In today’s Internet environment customers often are skeptical about sharing personal information with regard to privacy reasons. Therefore, ‘if customers lose trust in firms and believe that their data are used by firms for purposes of exploiting them, consumers will attempt to keep their data private or to distort the data. This has led and could continue to lead, to both individually based efforts to keep data private or collectively based efforts that lead to privacy regulations’ (Boulding, Staelin, Ehret and Johnston, p. 160, 2005). In conclusion, a successful implementation of CRM requires that firms carefully treat privacy norms and regulations and respect consumers trust.

Companies and customers meet each other via the different touchpoints, the places where the relationship between both parties is built. Companies often pay more attention on the quantity of touchpoints than the quality of touchpoints. Reinartz, Krafft and Hoyer (2004) believe that it is not true that building more relationships is better than building the right type of relationship, which they consider as critical factor. Therefore, Beckmann and Sindemann (2006) advise companies to develop an understanding of which touchpoints are most efficient to roll out CRM treatments. ‘Key criteria in such a touchpoint prioritization are the value added by a particular touchpoint (e.g. driven by the number of contacts and the variable costs per treatment) and the fixed costs to install treatments at this touchpoint (e.g. driven by IT development and employee training)’ (Beckmann and Sindemann, p. 9, 2006).

One of the key components of CRM is a good measurement process (Payne and Frow, 2005). Most CRM systems are measured via outcome measures, such as acquisition, retention, cross-selling, up-selling, customer lifetime value and customer migration (Boulding, Staelin, Ehret and Johnston, 2005), which are necessary and important. ‘However, they may not be directly linked to the value-dual creation process, which is the core concept of CRM. Thus it is essential that the firm also develop measures that are directly connected with this value-dual creation process, enabling the firm to understand the drivers of value and thus to ensure long-term success’ (Boulding, Staelin, Ehret and Johnston, p. 160, 2005). In order to enhance a firm’s innovation activities and keep the firm competitive, some of the measures have to connect to both the current and future

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value creation process (Boulding, Staelin, Ehret and Johnston, 2005). Focused on the airline industry, Binggeli, Gupta and de Pommes (2002) conclude that only very little airlines are able to identify their most valuable customers. ‘By taking steps to implement a truly consumer-centric approach to relationship management, an airline will be better positioned to acquire, develop and retain high-value customers’ (Boland, Morrison, O’Neill, p. 1, 2002). Through implementing customer analytics and decision support technologies, airlines will be able to use information about customers not only to differentiate service levels based on customer value, but also to drive important operational decisions (Boland, Morrison, O’Neill, 2002).

The role of employees in implementing a successful CRM strategy is often under-appreciated. According to Boot and Welsem (2002) the human factor is an important factor for the success of CRM. Satisfied, involved and motivated employees will transfer this feeling to customers. Reitz (2005) discussed how a particular airline went from worst to first in customer satisfaction. He emphasized the importance of having people issues under control before investing in expensive CRM technologies. According to Reitz, the difference between successful and unsuccessful CRM implementations can be made by employees. Zwan (2003) agrees with this statement but emphasizes the role of the management itself. In order to implement a successful CRM strategy, the top-management of an organization has to show commitment to the implemented CRM strategy.

Finally, patience is an important success factor in CRM implementation. Implementation of CRM is a time consuming activity and requires endurance (Peelen, 2003).

3.1.5 Sub-conclusion 1

3.2 Customer loyalty

In order to be able to answer the sub questions related to customer loyalty - What is customer loyalty? Is customer loyalty profitable? What are the principles of profitable customer loyalty? – literature concerning this topic is investigated and defined in this chapter.

CRM is focused on building and maintaining relationships wit targeted customers in order to create value. A well implemented CRM program can increase an airline’s revenue with 2.4%. Therefore the impact of having a good relationship with customers is clear. Key factors for implementing a successful CRM program are the collection of data, quality of the touchpoints, the measurement process, the role of the employees and management and having patience.

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3.2.1 The concept of customer loyalty

Since several decades the word ‘loyalty’ is discussed in the marketing literature. In general, consumers relate loyalty towards brands, services, stores, activities and product categories.

The marketing literature believes that customer loyalty can be defined in two distinct ways; loyalty as an attitude and loyalty as a behavior (Jacoby and Kyner, 1973). The behavioral view of loyalty is comparable with loyalty as defined in other scientific areas as the service management literature (Hallowell, 1996).

Many scholars relate the concept of customer loyalty to profitability and repeat purchasing behavior. Mittal and Lasser (1998) recognize customer loyalty as a path to long-term business profitability. Srinivasan, Anderson and Ponnavolu (2002) define loyalty as a customer’s favourable attitude towards a company that results in repeat buying behavior and positive word-of-mouth behavior. Oliver (1997: cited Yi and Jeon, 2003, p. 231) emphasizes the commitment of loyal customer towards their favourable product, service or brand.

In this thesis a combination of different definitions is used in defining customer loyalty: ‘Customer loyalty is a deeply held commitment to repurchase a preferred product or service consistently in the future and to provide new referrals through positive word of mouth.’

3.2.2 Profitability of customer loyalty

In the Marketing literature there is no universal agreement about the profitability of customer loyalty. Advocates and adversaries of the link between customer loyalty and profitability only agree about the positive impact of word-of-mouth behavior due to customer loyalty.

Gronroos (1984, 1991) performed research on the impact and value of customer loyalty. His findings support the theory that customer satisfaction is related to customer loyalty, which is positive related to profitability (Hallowell, 1995). Lovelock, Vandermerwe and Lewis (1999) believe that customer loyalty drives profitability and growth.

Some business analysts have suggested that the cost of recruiting new customers is five times higher than the costs of retaining existing customers (Mittal and Lasser, 1998). Subsequent research by consultants such as Bain & Company supports the suggestion

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that loyal customers are more profitable to a firm. This profitability is thought to be generated by the following elements:

Element Scholar

Reduced recruitment/operating costs (e.g. costs of advertising, costs of personal selling pitch to new prospects, costs of explaining business procedures to new clients).

→ Dowling and Uncles (1997) → Mittal and Lasser (1998) → Lovelock and Wirtz (2004)

Increased spending behavior/increased purchases

→ Dowling and Uncles (1997) → Berry and Parasuraman (1991) → Lovelock and Wirtz (2004) Less price sensitivity and competitive

pressures/profit from price premium

→ Dowling and Uncles (1997) → Dick and Basu (1994) → Lovelock and Wirtz (2004)

Word of mouth benefits → Dowling and Uncles (1997)

→ Jones and Sasser (1995) → Lovelock and Wirtz (2004) Table 3.2, Profitability through Customer Loyalty

Despite of all the positive critics about the importance and value of customer loyalty, some scholars are more critical towards this premise. Reinartz and Kumar (2002; p.12) believe that ‘no company should ever take for granted the idea that managing customers for loyalty is the same as managing them for profitability. The only way to strengthen the link between profits and loyalty is to manage both at the same time.’ Reinartz and Kumar (2002) also consider that the relationship between customer loyalty and profitability is much weaker than advocates suggest. Next to that Lovelock and Wirtz (2004) emphasize that it would be a mistake to assume that loyal customers are always more profitable than those making one-time transactions.

3.2.3 Principles of profitable customer loyalty

Inspired by Reinartz and Kumar’s (2002) conclusion that managing customer for loyalty should go hand in hand with managing them for profitability, it is necessary to investigate how companies could be able to do so.

Reinartz and Kumar believe that the link between loyalty and profits is weaker than expected. However, they do not believe that investments in loyalty are doomed. ‘The

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reason the link between loyalty and profits is weak has a lot to do with the crudeness of the methods most companies currently use to decide whether or not to maintain their customer relationships’ (Reinartz and Kumar, p. 7, 2002). Many companies currently use methods in measuring profitability that are focussed on recency and frequency of purchase. A problem hereby is that these methods do not distinguish frequently and infrequently bought goods. Developments in technology is allowing companies to already record the often complex behavior of their customers (Kumar and Reinartz, 2002). Through implementing these technologies in their organizations, the link between profits and loyalty will be strengthened (Kumar and Reinartz, 2002).

Verhoef (2003) did research to the effect of customer loyalty on customer retention and customer share development. He believes that customer loyalty positively effects profitability. In his research Verhoef emphasizes the importance of a differentiated loyalty program. ‘It is difficult to increase loyalty above the market norms with an easy-to-replicate ‘add on’ customer loyalty program’ (Verhoef, p. 42, 2003).

Research conducted by Dowling and Uncles (1997) accentuates that customer loyalty programs only have potential to be successful and thus profitable if the program directly enhances the product or service value proposition. Without adding value to the companies’ offered product or service, loyalty programs are useless and can even devalue the brand. ‘In this respect, probably the least useful rewards for customer loyalty are free gifts, these are nice to receive, but they tend to be only short-term tactical froth which can devalue the brand’ (Dowling and Uncles, p. 16, 1997).

3.2.4 Sub-conclusion 2

3.3 Online communities

In order to be able to answer the sub questions related to online communities - What is an online community? How can online communities create value? What are the success factors of online communities? – literature concerning this topic is investigated and defined in this chapter.

Companies manage loyal customers in order to gain more profitability. In the Marketing literature there is no universal agreement about the profitability of customer loyalty. Adversaries of the link between customer loyalty and profitability believe that managing customer for loyalty should go hand in hand with managing them for profitability. Principles of profitable customer loyalty are the quality of measuring tools, differentiation of the loyalty program and the added value of the loyalty program towards the companies’ product/service.

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3.3.1 The concept of online communities

The rapid growth of number of Internet users worldwide influences the opportunities of communicating with customers. Providing an online community can be an effective way to retain existing customers and attract potential customers (Armstrong and Hagel III, 1996).

The origins of the online community can be traced back to the 1970’s. From this starting point, rapid technology developments elaborated the scope and possibilities of online communities (Balasubramanian and Mahajan, 2000). In general, communities set up in an early stage are non-commercial. Communication, entertainment and sharing information were their reasons of existence (Armstrong and Hagel III, 1995). Due to the further integration of Internet possibilities in people’s daily lives (e.g. nowadays financial transactions via the Internet are already a feature of life online), commercial communities have emerged in the last decade. In the nineties, Armstrong and Hagel III (1995) already predicted differences between commercial and non-commercial communities. According to them, commercial communities integrate communication (chat, e-mail, bulletin boards), information (directories, content, advertising), entertainment (books, magazines, games) and transactions more effectively than non-commercial communities. Because of financial resources, content of non-commercial communities is often more complete and up-to-date in comparison with content of non-commercial communities (Armstrong and Hagel III, 1995).

Armstrong and Hagel III (1996) were pioneers in combining companies and online communities. In their definition an online community must fulfil five criteria:

1. Distinctive focus through membership

2. Integration of communication within the community and content 3. Emphasis on member related content

4. Choice among competing vendors 5. Commercially motivated organizers

In the literature, many scholars underline the human and relationship aspect within online communities. Franz and Wolkinger (2002) consider human feelings and personal relationships within a community as key factors. Dyson (1997) defines a community as the unit in which people live, work and play.

In defining online communities in this thesis, a combination of two definitions will be followed:

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An online community is an union between individuals that share a common value or interests using new information technology to communicate within a space accessible for members only (Schubert, 2000; Balasubramanian and Mahajan, 2000).

3.3.2 Value creation through online communities

Together with the rapid growth of number of Internet users (350 million users in 2005), an increasing number of companies started building online communities. In order to understand the possibilities and value of those communities, several scholars did research on the impact of online communities. Moon and Sproull (2001) used the case of e.g. LEGO’s LUGNET in order to describe the value of communities, while Kim, Lee and Hiemstra (2004) based their study on members of a Korean travel community. Even though both studies differ in amount and objective, the main result of both studies is highly comparable: successful communities can lead to an increase of customer loyalty. Loyalty through online communities is driven through several aspects. Hagel III and Armstrong (1997) believe that a communities strength is the ability for the community owner to develop an one-on-one relationship with customers and the possibility to develop a two-way sharing of information. Next to that, vendors can take advantage of communities ‘not only to improve their understanding of individual key customers, but also to build a track record of good service and responsiveness to their needs. The loyalty they create in this way will be based on performance, not brand, but it will serve to build up the brand’ (Hagel III and Armstrong, p. 150, 1997).

Franz and Wolkinger (2002) distinguish two different aspects of economic interest in a community. The community as a stand-alone business that is financially self supportive through revenue from advertisements, membership fees and commerce revenues (Timmers, 1998) and the community as add-on in a diversified business model like content or commerce platforms in order to build customer loyalty and customer feedback. In practical, a combination between both aspects is not unthinkable (Franz and Wolkinger, 2002). Through its link with customer loyalty, in this research the focus will be on the community as add-on in a diversified business model.

In the early nineties, community experts Armstrong and Hagel III (1995, 1997) already foresaw the twofold goal of online communities; creating value through direct benefits as membership fee, advertisements etcetera, and increasing customer loyalty. ‘If loyalty is defined in terms of repeat purchases, or ‘coming back for more’, communities are a tremendous vehicle for increasing loyalty to a vendor’s products’ (Hagel III and Armstrong, p. 149, 1997). Moon and Sproull (2001) believe that the increase of customer loyalty is caused by active participation in the online community, which results in a more favourable evaluation of the firm and its brand, ‘thereby increasing the firm’s brand

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equity’ (Moon and Sproull, p. 21, 2001). Kim, Lee and Hiemstra (2004) consider that through stimulating participation and members’ interest, customer loyalty of community members will be increased.

Furthermore, Moon and Sproull (2001; p.21) emphasize the importance of positive word of mouth through online communities: ‘Because enthusiasm for the product or service is a precondition for membership in a customer community, members can communicate powerful positive product testimonials that are untainted by commercial endorsements. These testimonials are more credible when they are encountered on volunteer electronic communities rather than on corporate web pages. Positive word of mouth generated by these customers can result in potential increases in market share for the firm with minimal marketing effort by the company’.

Without even realizing it, members of online communities provide firms with useful information about customer needs through interaction within the community (Moon and Sproull, 2001). Besides that, through interaction between the community owner and its members, members can be a source of product innovations and improvements (Moon and Sproull, 2001). In general members are very motivated to participate in product development efforts. Increasing reputation within the community through participation in product development programs can be considered as a main reason here for (Franz and Wolkinger, 2002). LEGO continuously monitors the LUGNET newsgroups to collect information about trends and interests of customers. As a result, an obvious correlation between LEGO’s product lines and trends and interests discussed at the LUGNET newsgroups can be noticed (Moon and Sproull, 2001). Besides LEGO, also software companies as Microsoft make grateful use of information shared at different platforms users are using. Customers report bugs and even provide Microsoft with information of how to fix them (Moon and Sproull, 2001).

3.3.3 Success factors of online communities

The potential value of online communities is recognized by scholars. Besides success stories, lots of communities do not meet the expectations (Walden, 2000).

Armstrong and Hagel III (1995) emphasize that technical factors fulfil an important role in organizing a successful community. The fields of marketing, customer service, product development and information systems have to present in the community organization. McDermott (2001) supports the technical challenge. According to him community owners have to make easy to connect, contribute to and access the community.

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Next to that, McDermott underlines the impact of (live) contact possibilities. ‘Live contact is the key to building a sense of commonality, enthusiasm and trust. In addition to individual meetings and web connections, create opportunities for the community as a group to share ideas’ (McDermott, p. 9, 2001).

‘A community cannot be sustained if most of its members are fleeting participants who quickly lose interest in participating. People will not continue to visit a community if they do not find high quality information there; they will not continue to contribute if they perceive that there is no value in the interaction’ (Moon and Sproull, p. 16, 2001). Dutch community expert Marco Derksen (2006) agrees with this statement. He believes that at least 10% of all members need to be active in order to keep the community lively and interesting for its members. The definition of being active depends on the topic and purpose of the community and needs to be designed by the community owner (Derksen, 2006).

Finally, the ultimate goal and strategy of an online community must be clear and touchable (Armstrong and Hagel III, 1995). What does the community owner wants to achieve with the community and how does the community owner wants to achieve this goal?

3.3.4 Sub-conclusion 3

3.4 Conceptual model

In conclusion of the theory and previous research conducted by scholars, the following conceptual model has been developed.

An online community is an union between individuals that share a common value or interests using new information technology to communicate within a space accessible for members only. Successful communities can lead to an increase of customer loyalty, positive word-of-mouth behavior and can act as a source of product innovations and improvements. Key factors in creating successful online communities are technical factors, (live)contact possibilities, activity rate of members and the clearness of the communities’ ultimate goal and strategy.

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Figure 3.2, Conceptual model

As Franz and Wolkinger (2002) mentioned, profitability through online communities can be created in different ways. In the case of KLM Club China, profitability flows from both direct and indirect revenues. Profits from direct revenues, such as advertisements, partners, membership fee etcetera, are mentioned in this research, but are not treated as a key element of this study.

All connections in this conceptual model are discussed separately.

→ Existing members Frequent Flyer Program & new members Frequent Flyer Program

KLM Club China

While membership of KLM’s Flying Blue program is obliged in order to become member of KLM Club China, the introduction of KLM Club China attracts both existing and new members of the Flying Blue program to the Club.

→ KLM Club China

Expansion of CRM / Frequent Flyer Program

For the existing Flying Blue members, KLM Club China elaborates the program and forms a new touchpoint.

→ KLM Club China

Customer loyalty

Expansion of CRM / Frequent Flyer

Program

Customer Loyalty

Direct revenue

KLM Club China Profitability Existing members Frequent Flyer Program New members Frequent Flyer Program Increase Flying behavior -Technical factors -(live)contact possibilities -Activity rate members -Clearness of the communities’ ultimate goal

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KLM’s online community has been introduced in order to increase customer loyalty. According to the relevant literature, successful online communities lead to an increase of customer loyalty and positive word of mouth behavior.

→ Customer loyalty

Increased flying behavior

If the principles of profitable customer loyalty are followed, increasing customer loyalty will lead to increasing flying behavior of KLM Club China members.

→ Increased flying behavior

Profitability

Increased flying behavior of KLM Club China members will eventually lead to profitability. If the profits from extra transactions of KLM Club China members are bigger than the costs of managing and organizing the community, profitability will be generated.

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4. METHODOLOGY

In order to measure the impact of KLM Club China on flying behavior of its members in comparison with flying behavior of non-KLM Club China members, a study based on flying data of both KLM Club China members and Flying Blue members who joined KLM Club China in a later stage is performed. Together with this study, a quantitative online survey conducted by 1086 KLM Club China members gives insight in the background of members, members’ appreciation of the Club and the added value of the Club for both members and KLM. Results of both studies are analyzed in chapter 5.

4.1 Study 1: Flying behavior Phase 1:

During the introduction of the community in May 2006, 300 Flying Blue members joined KLM Club China. These travellers were, together with other Flying Blue members, invited to join KLM Club China via a Flying Blue e-mail (this e-mail was sent to travellers who made six or more boardings in 2005 to China), billboards at Schiphol airport or folders in flights to and from China.

In the performed study, the number of flights to China in the period May 1. 2006 – October 31. 2006 of this selected group, are compared with their flying frequency to China in the period May 1. 2005 – October 31. 2005. Next to this, a control group of 753 Flying Blue members who did not join KLM Club China before November 2006, is selected. Also their flying behavior in the period May 1. 2006 – October 31. 2006 is compared with the number of flights this selected control group made in the period May 1. 2005 – October 31. 2005. The control group is of such a size that a reliability of 95% is created (Baarda & de Goede, 2001).

Phase 2:

In addition to phase 1, an extra research is conducted to create more reliability. In August 2006, 542 Flying Blue members joined KLM Club China. Their flying frequency to China in the period August 1. 2006 – October 31. 2006 is measured and compared with their flying frequency in the same period in 2005. Results from these data are compared with the results from the data of the control group of 753 Flying Blue members as mentioned above.

Seasonal effects:

The research is not influenced by seasonal effects, due to the fact that the same months in two years are compared.

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Trend effects:

As trend effects are similar for members as well as non-members, the research is not influenced by trend effects.

Number of weekly flights offered by KLM:

The number of weekly flights to and from China offered by KLM changed in the period 2005-2006. Compared to the same period a year before the number of flights increased in 2006. During the analysed period, the number of flights to and from China offered by KLM were not constant. Since this is equal for members and non-members (control group) the research is not influenced by the changing number of weekly flights offered by KLM.

4.2 Study 2: Online survey

The second study is based on an online survey of KLM Club China members. Via an online survey, KLM Club China members are asked to share their feelings, expectations and overall appreciation towards the Club. Through analyzing these results and connecting them with outcomes of the flying behavior research (as presented in paragraph 4.1), conclusions concerning the relation between the appreciation of KLM Club China and the differences in flying behavior are drawn in chapter 5.

Using an online survey as research method reduces costs, time and geographical limitations (Dillman, 2000). KLM Club China is an international community and accommodates members of more than 90 different countries. Besides reducing the mentioned limitations, members of online communities appreciate using online research methods probably more than traditional surveys (Kim, 2004).

Members’ email addresses have been collected from the database of KLM Club China. Members without a (valid) Flying Blue number and members who just subscribed to the community have been filtered out of the mailing list. To stimulate response, a bonus of 250 Flying Blue miles has been awarded to participants of the research. The online survey has been sent to 3900 members. A 32,4% response rate was obtained from the survey. Among the return 1086 questionnaires were usable, representing an effective response rate of 27,8%.

4.2.1 Questionnaire design

The overall objective of the online survey is to gain information about KLM Club China members, their appreciation of the community and the added value of KLM Club China for members and for KLM. The questionnaire consisted of a total of 39 questions, of which 22 questions were asked in order to fulfil this research. The other 17 questions were attached by order of KLM and included general questions about KLM or were used

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to introduce other questions. In appendix 1, only questions relevant for this particular research are included.

In the online survey, 8 questions were formulated to gain background information, 5 questions were used to gain insight in members’ appreciation for KLM Club China, 8 questions were designed to measure the value of KLM Club China for KLM and 1 question was used to measure the value of KLM Club China for its members.

The questionnaire consists of both open and multiple-choice questions. Results from the questionnaire are discussed in chapter 5.

4.3 Research model

A schematic representation of the KLM Club China study is given in figure 4.1 below.

Figure 4.1, Research Model KLM Club China Study

KLM Club China Study

Analysis Flying behavior selected Club China members Online survey → Select target group and control group for flying behavior research. → Design question-naire. → Select targetgroup question-naire → Collect flying data out of the Flying Blue database → Specify KLM destinations and frequency → Send questionnaire to selected target group. → Analyze and combine results Preparation / Research Design

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5. RESULTS

Both conducted studies are discussed separately. Paragraph 5.1 shows the results of the flying behavior study and paragraph 5.2 discusses the results from the online survey. In paragraph 5.3 the interpretation of the results is given. Appendices 2 and 3 give an overview of the results of both researches analyzed with the statistical program SPSS.

5.1 Study 1: Flying behavior

In this study, two groups have been selected:

1. Members who joined KLM Club China May 1. 2006 (group 1) 2. Members who joined KLM Club China August 1. 2006 (group 2)

Through analyzing flying behavior of two different groups instead of one single group, reliability of the research is improved. The number of transactions towards China (note: 1 transaction is 1 boarding) of both groups has been investigated. Transaction data from May 1. 2006 – October 1. 2006 (period 1b) has been analyzed for group 1 and transaction data from August 1. 2006 – October 1. 2006 (period 2b) has been analyzed for group 2. These data are coming from the Flying Blue database. In order to notice a difference in flying behavior through membership of KLM Club China, the transactions made by both groups are compared with the transactions both groups made in the same period in 2005 (period 1a for group 1 and 2a for group 2). Next to this, flying data of two control groups (one for group 1 and one for group 2) have been investigated. In order to notice a significant difference in flying behavior through membership of KLM Club China, all data are analyzed with the statistical program SPSS. Figure 5.1 illustrates the selection of the groups.

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1a 1b 0 200 400 600 800 1000 1200 1400 1600 1800 2000 April 2 005 May 2 005 June 2005 July 2 005 Augu st 20 05 Sept embe r 200 5 Octo ber 2 005 Nove mber 2005 Dece mber 200 5 Janu ary 200 6 Febr uary 2006 Marc h 200 6 April 2 006 May 2 006 June 2006 July 2 006 Augu st 20 06 Sept embe r 200 6 Octo ber 2 006 Nove mber 2006 Dece mber 200 6 Janu ary 200 7 Febr uary 2007 Marc h 200 7

KLM Club China members non-KLM Club China members Figure 5.1, Selection of groups study flying behavior.

During the research period the number of weekly flights offered by KLM to China is not constant.

Figure 5.2, Number of weekly KLM flights to China April 2005 – March 2007.

2a 2b 0 5 10 15 20 25 30 April 200 5 May 2 005 June 200 5 July 2 005 Augu st 200 5 Sept embe r 200 5 Octo ber 2 005 Nove mbe r 200 5 Dece mbe r 200 5 Janu ary 2 006 Febr uary 200 6 March 200 6 April 200 6 May 2 006 June 200 6 July 2 006 Augu st 200 6 Sept embe r 200 6 Octo ber 2 006 Nove mbe r 200 6 Dece mbe r 200 6 Janu ary 2 007 Febr uary 200 7 March 200 7

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Compared to the same period a year before, the number of flights increased. However, this is equal for members and non-members. In comparing these groups, the change in number of weekly flights offered by KLM to China has no influence. In analyzing transaction data from 2006 with transaction data from 2005, the increase in number of flights is considered.

5.1.1 Members and non-members May 2006

300 Flying Blue members joined KLM Club China during the introduction date, May 1 2006. A group of 753 Flying Blue members did join KLM Club China in a later stage, but not before November 2006 (see figure 5.3). This group is used as the control group. From the Flying Blue database, the number of transactions towards China made by both groups in the periods May 1. 2006 – October 31. 2006 and May 1. 2005 – October 31. 2005 has been analyzed and compared. By doing so, the effect of membership of KLM Club China on flying behavior towards China can be noticed.

0 200 400 600 800 1000 1200 1400 1600 1800 2000 April 2 005 May 2 005 June 2005 July 2 005 Augu st 20 05 Sept embe r 200 5 Octo ber 2 005 Nove mber 2005 Dece mber 200 5 Janu ary 200 6 Febr uary 2006 Marc h 200 6 April 2 006 May 2 006 June 2006 July 2 006 Augu st 20 06 Sept embe r 200 6 Octo ber 2 006 Nove mber 2006 Dece mber 200 6 Janu ary 200 7 Febr uary 2007 Marc h 200 7

KLM Club China members non-KLM Club China members

Figure 5.3, Selection of groups study flying behavior phase 1.

With in average 1,13 boardings per month to China in the period May 1. 2005 – October 31. 2005, the members who joined KLM Club China during its introduction date can be considered as heavy users. Through the large number of miles they flew with KLM to China in 2005, the heavy users can be considered as platinum or gold members. ‘The composition of the first group of KLM Club China members can be explained through analyzing the invitation procedure. Besides billboards at Schiphol airport and folders in

Control

group

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