Abstract The objective of this thesis is to contribute to the understanding of drivers of customer loyalty by exploring the dynamics of customer‐brand relationships and the role they play for the creation and management of customer loyalty in the airline industry. The particular relevance of the research objective arises from the intensification of competition in the airline industry and the extensive consolidation that is expected to accompany it. These market challenges make the retention of valuable customers an essential prerequisite for the achievement of a sustainable competitive advantage and, hence, the airline’s overall success. Relevant literature from related fields, such as relationship and service marketing, form the foundation for the development of the conceptual airline customer loyalty (ACL) model. Centered on the concept of relational benefits, this model depicts important antecedents to customer loyalty in the airline industry. Relational benefits are thereby defined as benefits customers receive as a result of their engagement in customer‐brand relationships. In the course of this study, three types of relational benefits are identified as bearing relevance for the airline industry: social, psychological, and functional benefits. The ACL model is empirically tested employing structural equation modeling on primary data collected from an online survey with 276 participants. The results reveal that three distinct paths to airline customer loyalty can be distinguished with each being characterized by one of the observed relational benefits. Accordingly, they are defined as the social, the psychological, and the functional path to airline customer loyalty. Each path originates from distinct brand performance characteristics, moves along the respective type of relational benefits, and results in customer loyalty either directly and/or mediated by the dimensions of relationship quality – customer satisfaction and relationship commitment. Managerial implications on how to manage airline customer loyalty are inferred along these three paths, accentuating the particular relevance of social‐psychological aspects of customer‐brand relationships for the management of airline customer loyalty. By combining important brand‐ and relationship‐related concepts, this thesis provides a holistic perspective on the management of customer loyalty in the airline industry that has to date been missing.
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Abstract
The objective of this thesis is to contribute to the understanding of drivers of customer
loyalty by exploring the dynamics of customer‐brand relationships and the role they play for
the creation and management of customer loyalty in the airline industry.
The particular relevance of the research objective arises from the intensification of
competition in the airline industry and the extensive consolidation that is expected to
accompany it. These market challenges make the retention of valuable customers an
essential prerequisite for the achievement of a sustainable competitive advantage and,
hence, the airline’s overall success.
Relevant literature from related fields, such as relationship and service marketing, form the
foundation for the development of the conceptual airline customer loyalty (ACL) model.
Centered on the concept of relational benefits, this model depicts important antecedents to
customer loyalty in the airline industry. Relational benefits are thereby defined as benefits
customers receive as a result of their engagement in customer‐brand relationships. In the
course of this study, three types of relational benefits are identified as bearing relevance for
the airline industry: social, psychological, and functional benefits.
The ACL model is empirically tested employing structural equation modeling on primary data
collected from an online survey with 276 participants. The results reveal that three distinct
paths to airline customer loyalty can be distinguished with each being characterized by one
of the observed relational benefits. Accordingly, they are defined as the social, the
psychological, and the functional path to airline customer loyalty. Each path originates from
distinct brand performance characteristics, moves along the respective type of relational
benefits, and results in customer loyalty either directly and/or mediated by the dimensions
of relationship quality – customer satisfaction and relationship commitment. Managerial
implications on how to manage airline customer loyalty are inferred along these three paths,
accentuating the particular relevance of social‐psychological aspects of customer‐brand
relationships for the management of airline customer loyalty. By combining important
brand‐ and relationship‐related concepts, this thesis provides a holistic perspective on the
management of customer loyalty in the airline industry that has to date been missing.
Table of contents
I
Table of contents
List of figures ................................................................................................. IV
List of tables ................................................................................................... V
List of appendices......................................................................................... VII
List of abbreviations .................................................................................... VIII
4 Conceptual and theoretical foundation for the development of the airline customer loyalty model ................................................................ 17
4.1 The concept of customer loyalty ............................................................................... 18
4.1.1 The influence of customer loyalty on a firm’s profitability ................................ 18
4.1.3 Customer loyalty through relationship marketing ............................................. 22
4.2 Customer loyalty through relationships between customers and airline brands ..... 23
4.2.1 The service‐dominant logic of marketing in the airline industry ........................ 23
Table of contents
II
4.2.2 The service brand as a relationship partner ....................................................... 26
4.2.3 Relational benefits as a basis of airline customer loyalty ................................... 27
4.2.4 Relationship quality as mediator between relational benefits and customer loyalty.................................................................................................. 31
4.3 Chapter summary – identification of concepts to be included in the ACL model .... 33
5 The airline customer loyalty model ......................................................... 35
5.1 The influence of airline brand performance characteristics on relational benefits . 35
5.1.1 The influence of social brand performance on relational benefits .................... 36
5.1.2 The influence of airline image on relational benefits ......................................... 37
5.1.3 The influence of brand‐self congruence on relational benefits ......................... 39
5.1.4 The influence of trustworthiness on relational benefits .................................... 40
5.1.5 The influence of service quality on relational benefits ...................................... 42
5.1.6 The influence of perceived value on relational benefits .................................... 43
5.1.7 The influence of co‐creation of value on relational benefits.............................. 44
5.1.8 The influence of the airline’s country of origin on relational benefits ............... 45
5.1.9 The influence of FFP attractiveness on relational benefits ................................ 46
5.2 Consequences of relational benefits ......................................................................... 47
5.2.1 Consequences of social benefits ......................................................................... 47
5.2.2 Consequences of psychological benefits ............................................................ 49
5.2.3 Consequences of functional benefits.................................................................. 51
5.3 The influence of relationship quality on customer loyalty ........................................ 52
5.3.1 The influence of customer satisfaction on commitment and customer loyalty 52
5.3.2 The influence of relationship commitment on customer loyalty ....................... 53
5.4 Graphical illustration of the proposed ACL model .................................................... 54
6 Empirical testing of the proposed airline customer loyalty model ........... 54
6.1 PLS as research method ............................................................................................. 54
6.1.1 Selection of PLS as research method .................................................................. 54
6.1.2 Application of PLS ............................................................................................... 55
6.2 Data collection ........................................................................................................... 56
6.2.1 Internet survey as data collection method ......................................................... 57
1 Introduction Running airlines profitable has always been a great challenge (cf. Doganis, 2006). In addition
to intense competition diminishing airlines’ profits, airlines are exposed to market volatility,
legal regulations restricting operations, and a disadvantageous cost structure with high fixed
costs (Delfmann, 2005, p. 12; Shaw, 2007, p. 54). The ongoing deregulation and liberalization
of the industry over the past years, which has, inter alia, resulted in the removal of fare
restrictions, have further altered the competitive landscape by encouraging the entry of new
competitors in the market. In particular, low‐cost carriers have become a driving force in this
competitive landscape. In contrast to traditional network carriers1, which typically pursue a
service differentiation strategy, low‐cost carriers focus primarily on keeping their operating
costs low, thus taking over cost leadership. These developments have had extensive
repercussions on the European airline industry’s market structure, resulting in increased
price competition. In an industry that has always been marked by marginal profitability
(Doganis, 2006), this competition on price has led to further profit decline. Today, numerous
airlines in Europe are struggling to make profits or are facing bankruptcy, implying that
extensive consolidation activities are forecast for the European market. At the same time,
the relentless price competition, especially in the short‐haul segment, puts airlines’ service
at risk to be perceived by customers as a rather generic offering.
In such a highly competitive environment, customer loyalty has become an increasingly
effective means for securing a firm’s profitability (e.g. Reichheld & Sasser, 1990; Reinartz &
Kumar, 2002). Customer loyalty refers to a customer’s repeated same‐brand purchase within
a given category, based on a favorable attitude toward and preference for the particular
brand. Empirical findings have revealed that increased market share and decreasing price
sensitivity among customers are particular contributions of customer loyalty to a firm’s
profitability (Chaudhuri & Holbrook, 2001). The establishment and maintenance of a loyal
customer base should, therefore, be (and in many cases already is) a key objective for
airlines, since it promotes a sustainable competitive position in the market place.
Consequently, the retention of valuable customers is an important objective and requires
airline management to understand the underlying factors that reinforce airline customers’
loyalty toward a given airline brand.
1 These carriers are often also referred to as legacy or flag carriers as they were formerly state‐owned. For a detailed description, please refer to Chapter 3.2.
2
Customer loyalty rests in particular on the brand, which plays an important role in customer
retention. A brand can be described as a “cluster of functional and emotional values that
promises a unique and welcome experience” (de Chernatony et al., 2006, p. 819) for its
customers. By creating unique associations and feelings among customers that are directly
and exclusively connected to the given airline, the brand helps airlines differentiate
themselves from their competitors. In addition to its differentiation function, the brand
serves as a potential relationship partner for the customer. The customer‐brand relationship
can evolve and develop through continuous positive interactions between the customer and
the brand (e.g. Grönroos, 2007, p. 331) and provides airlines with the opportunity to offer
their customers benefits that go beyond the core air transport service (cf. Hennig‐Thurau et
al., 2002, p. 234). In such relationships, customers perceive the airline brand as a legitimate
partner in the relationship dyad (Sweeney & Chew, 2000; cf. Fournier, 1998). Customers
construct relationships with brands so that they provide and add meaning and value to their
lives (Sweeney & Chew, 2000; Fournier & Yao, 1997). This value is generated by the
relational benefits resulting from the relationship with the brand as perceived by the
customer (cf. Aaker, 2002, p. 95; Hennig‐Thurau et al., 2002, p. 234). Ultimately, the
customer decides whether the relationship with a given brand generates value or not.
Hence, it is fundamental for the establishment of customer loyalty to understand what
potential and existing customers expect from their relationship with an airline brand.
However, since customers’ personalities and lifestyles differ, as does their evaluation of the
relationship with the brand, customer characteristics must also be taken into account.
With the objective of fostering customer loyalty, airlines introduced loyalty schemes in the
1980s and 1990s. These so‐called frequent flyer programs award customers for flights taken
with the given airline. While these programs attract a great number of airline customers,
skepticism has been expressed whether such programs in fact lead to true customer loyalty
based on a positive attitude toward and preference for the brand. Critics assert that the
reason why customers repurchase a ticket to travel with the given airline rests alone on the
rational and economic benefits the airline’s frequent flyer program offers (cf. Plimmer, 2006;
Dowling & Uncles, 1997). Given frequent flyer programs’ questionable effect with reference
to the creation of customer loyalty, other drivers of customer loyalty in the commercial
airline industry must be considered. Several studies on the antecedents of customer loyalty
in the airline industry have been carried out (e.g. Ostrowski et al., 1993; Park et al., 2006;
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Zins, 2001). This thesis, however, takes a different approach and argues that the
consideration of the dynamics that result from customer‐brand relationships can generate
new knowledge about how customer loyalty can be created and maintained in the airline
industry.
1.1 Research question
Based on the previous discussion, this thesis’ research objective is to gain insights into the
dynamics of customer‐brand relationships in the airline industry and the effect these can
have on customer loyalty. To achieve the stated objective, the research focuses on the
identification of important drivers of airline customer loyalty. This further establishes a more
profound understanding of customers’ appraisal of specific airline brand characteristics.
Further consideration of customers’ influential role in relational exchanges elicits the need
to pay special attention to those characteristics that differentiate airline customers from one
another. The knowledge gained from this research study provides a foundation on which
recommendations directed at airline managers can be built. Consequently, this thesis
approaches the research question from a managerial perspective.
In consideration of the previously formulated research objective, the overarching research
question of this thesis is:
What kind of benefits do customers seek when they engage in relationships with airline
brands, and how can these relationships strengthen airline customer loyalty?
4
1.2 Sub‐questions
Based on this overall research question, the following sub‐questions (SQ) to be answered
are:
1.3 Definitions
The most important concepts mentioned in the research question and the sub‐questions are
briefly defined below. More detailed definitions are provided in the following chapters.
First, the interchangeable use of the terms airline, airline brand, and airline/brand image in
this thesis must be addressed. The term airline in general relates to the company that
provides the actual air transport service. However, this thesis concentrates on the
relationship between a given airline and its customers. Customers primarily perceive airlines
as brands, i.e., in terms of the benefits the airline provides them. The brand, on the other
hand, cannot be created by the airline per se, but is built by the customer (Grönroos, 2007,
p. 331). Brand image thus relates to the associations a customer links to a particular airline.
In this context, customer loyalty is defined as a customer’s repeated same‐brand purchase
within a given category, based on a favorable attitude toward and preference for the specific
brand. A more elaborate definition of customer loyalty is presented in Chapter 4.1.2. It is
worth mentioning that several different descriptions of loyalty are discussed in the
literature, e.g., customer loyalty, brand loyalty, or service loyalty. Here, the term customer
loyalty was explicitly chosen to emphasize that this research study focuses on the loyalty
customers exhibit toward a specific airline brand.
SQ1: How do relational benefits affect customer loyalty toward a specific airline brand?
SQ2: How do fundamental airline brand performance characteristics influence the
relational benefits perceived by airline customers?
SQ3: How do differences in airline customer characteristics moderate the airline customer
loyalty model?
SQ4: What managerial implications can be inferred from the results of this study?
5
The relational benefit approach assumes that both the customer and the service provider
must benefit from the relationship if it is to persist in the long run. From the customer’s
perspective, the maintenance of this relationship depends primarily on the existence of
relational benefits. These refer to benefits that go beyond the basic services offered by the
service provider. This thesis distinguishes between three different types of relational
benefits: social, psychological, and functional benefits.
It should further be noted that, whenever it is referred to the customer, female and male
customers are considered. However, for simplicity and easiness to read, only ‘he’ and ‘him’
will be used.
2 Methodology This chapter discusses the methodological orientation applied in this thesis to answer the
research question. Furthermore, the role of theory within this context is assessed. Finally,
the outline and demarcation of the thesis are presented.
2.1 Methodological orientation and research approach
With regard to the overall research question and the proposed sub‐questions, this thesis’
objectives are (1) to gain new insights into the effect customer‐brand relationships can have
on airline customer loyalty. These findings are arrived at by reviewing and exploring relevant
literature on customer loyalty, relationship and service marketing, and brand management.
By synthesizing the most important concepts identified in the different fields of research, (2)
a conceptual model is developed which depicts the causal relationships between the
identified concepts and their influence on airline customer loyalty. (3) This model is then
empirically tested.
To meet the objectives described above, this thesis adopts a positivist research philosophy;
relevant literature is reviewed to establish a suitable conceptual framework, including the
construction of hypotheses (cf. Saunders et al., 2007, p. 103). Hypotheses refer to ideas or
propositions about the relationship between two or more concepts that can be tested using
statistical analysis (cf. Saunders et al., 2007, p. 117; Collis & Hussey, 2003, p. 55). The
hypotheses formulated and subsequently tested here concern the proposition of causal
relationships between different concepts that lead to airline customer loyalty. Consequently,
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the first part of the study, which aims to understand the relevant concepts and constructs of
customer loyalty, relationship marketing, and service marketing in literature, is exploratory
(cf. Malhotra & Birks, 2007, p. 70). The purpose is to deduce hypotheses from the existing
literature and from previous studies (cf. Ghauri & Grønhaug, 2005, p. 15; Gill & Johnson,
2002, p. 34). The second part of the study is explanatory, with its focus on testing the
postulated hypotheses and examining the causal relationships between the concepts (cf.
Malhotra & Birks, 2007, p. 70; Saunders et al., 2007, p. 134), to be able to infer managerial
implications from the empirical results obtained.
Since the main objective of this study is to explore the underlying causal relationships
between variables that result in airline customer loyalty, a deductive research approach is
employed. That is, hypotheses on the causal relationships are deduced from existing
knowledge (literature), subjected to empirical scrutiny (testing), and, based on the findings
are either accepted or rejected (Ghauri & Grønhaug, 2005, p. 15). Saunders et al. (2007,
pp. 117‐118) draw attention to several important characteristics of the deductive approach.
First, resulting from the formulation of hypotheses that need to be tested, deduction is
usually associated with the collection of quantitative data which lend themselves to
statistical analysis (Saunders et al., 2007, p. 104). Because measurement is an essential
element of the analysis of quantitative data, it must be conducted with precision to ensure
the measurement’s accuracy (Collis & Hussey, 2005, p. 7). In order to ensure objective data
collection, the researcher should be impartial to the subject matter being measured
(Saunders et al., 2007, p. 118). Furthermore, to make the measuring of the concepts
possible, they have to be presented in operational terms (Ghauri & Grønhaug, 2005, p. 15;
Saunders et al., 2007, p. 118).
Finally, this research study takes a managerial perspective. The objective is to understand
the underlying reasons for why customers remain loyal to a specific airline brand. The
insights gained can be transformed into distinctive initiatives by airline managers, which
contribute to the strengthening of airline customers’ loyalty. Hence, this thesis’ goal is to
propose recommendations for airline managers on how to intensify the bonds between the
customers and the airline brand.
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2.2 Overall research design
While deduction describes the general approach applied here to answer the research
question, the research design details the necessary procedures to obtain the information to
answer it. It further specifies the role of theory and the unit of analysis.
The employment of a deductive research approach requires the collection of a considerable
amount of representative quantitative data. Consequently, a survey is the most suitable
research strategy for this study, since the collection of a large amount of standardized and
structured data is thereby possible, which, in turn, allows for a quantitative analysis
(Saunders et al., 2007, p. 138; Malhotra & Birks, 2007, p. 266). A detailed discussion of the
type of survey conducted and the data analysis process is presented in Chapter 6.
This thesis’ main research question necessitates profound knowledge on what kinds of
benefits customers seek in a relationship with a select airline brand. In the conceptual part
of this thesis, theory, i.e., a system for organizing concepts in a way that produces
understanding and insights (Zaltman et al., 1977 in: Ghauri & Grønhaug, 2005, p. 39) is
applied to identify the framework’s key dependent and independent variables. In addition,
theory provides guidance on the operationalization of the key variables identified. In the
analytical part of this thesis, the theory on which the airline customer loyalty model is built
guides the data analysis strategy and the interpretation of results. Furthermore, the findings
arrived at are interpreted on the basis of the literature reviewed and previous research and
are integrated in the existing body of knowledge (cf. Malhotra & Birks, 2007, p. 51).
Concentrating on customers’ particular attitudes and behavior toward airline brands, the
research question clearly identifies airline customers as the designated unit of analysis. For
reasons of generalization, this study aims to cover a heterogeneous consumer base. Airline
customers in general, therefore, constitute the unit of analysis.
2.3 Thesis outline and demarcation
This section briefly introduces the contents of each of the individual chapters. It also depicts
this thesis’ limitations.
Chapter Three provides a brief introduction to the airline industry, its current challenges,
and its two most prominent business models: network carriers and low‐cost carriers. In
8
addition, dimensions for customer segmentation are discussed. Furthermore, frequent flyer
programs (FFPs), a loyalty scheme specific to the airline industry, are introduced, and their
advantages and disadvantages highlighted. It must be noted here that the chapter focuses
on airline industry specificities and forecasts that were made prior to the outbreak of the
financial and economic crisis. What effect the current developments will have on the
industry in the long‐term is difficult to assess and beyond the scope of this thesis.
Chapter Four concentrates on the review of existing literature in the fields of customer
loyalty, relationship and service marketing. With reference to customer loyalty, various
definitions discussed in academic literature are presented, and the different components for
defining true loyalty are assessed. As the focus of this study is on the identification of factors
that influence customer loyalty rather than on the analysis of customer loyalty as such, an in‐
depth analysis of different levels of loyalty or a comprehensive discussion of loyalty’s
influence on a company’s profitability is beyond the scope of this thesis. By considering
relationship marketing’s primary objective, namely building and strengthening relationships
with customers, this study intends to contribute to the current understanding of the drivers
of customer loyalty. To further contemplate the nature of services and the specificities of
service marketing, analyzing customer‐brand relationships is a feasible approach. Here,
special attention is given to the relevance of relational benefits and relationship quality in
the long‐term maintenance and enhancement of such relationships. By processing and
evaluating existing knowledge and synthesizing it, the focus of the research is refined and
concepts for inclusion in the conceptual model are determined.
Based on the insights gained from the literature review and the results from studies
previously conducted in the fields of relationship marketing and customer loyalty, the airline
customer loyalty (ACL) model is conceptualized in Chapter Five. Hypotheses on causal
relationships that exist between the different constructs of the model are postulated for
subsequent empirical testing.
Chapter Six focuses on the empirical testing of the airline customer loyalty model. The
analytical approach is introduced, and details on the data collection procedure are provided.
Furthermore, the operationalization of the constructs is described. Following the validation
of the model, the results of the empirical study are presented. The chapter concludes with a
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discussion on the empirical findings based on the inferences arrived at by answering sub‐
questions one, two, and three.
Chapter Seven combines the theoretical insights gained from the literature review with the
empirical findings based on the conclusions to sub‐questions one, two, and three to
deliberate managerial implications. Thus, sub‐question four is addressed.
Chapter Eight presents final conclusions and suggests directions for future research.
3 The airline industry This chapter provides a brief overview on the specificities of the passenger airline industry.
First, an outline of historical, legal, and economic factors is presented before the industry’s
two dominant business models, network carriers and low‐cost carriers, are introduced. The
chapter further addresses marketing‐related aspects that characterize the airline industry
such as dimensions for customer segmentation and frequent flyer programs. The chapter
concludes with a concise future outlook of the industry.
3.1 Airline industry specificities
Until the mid‐1980s, the highly‐regulated airline industry was dominated by international
airlines which were fully‐, or at least majority‐owned by their national governments. This
was primarily because governments realized that air transport would be of major
significance for economic and social development, as well as for trade (Doganis, 2006,
p. 223). To promote their country’s power, status, and prestige (Hanlon, 2007, p. 7), each
state designated one airline, the country’s ‘flag carrier’, to operate flights on bilateral routes
between those countries with which air traffic rights had been exchanged (Doganis, 2006,
p. 223). Since the mid‐1980s, the successive liberalization of traffic rights and regulations has
facilitated the privatization of state‐owned airlines. Today, most are either fully or partially
privatized, or are in the process of being privatized (Doganis, 2006, p. 225; Hanlon, 2007,
p. 15). However, a large number of formerly state‐owned carriers continue to commemorate
their historical heritage in their names and in the colors of their corporate design (e.g.,
British Airways, Air France). While liberalization initially spurred the privatization of airlines,
it also triggered the entry of new carriers in the market. Faced with increasing competition
and, simultaneously, decreasing government subsidies traditional carriers were forced to
10
abandon old market practices and become more competitive and customer‐oriented
(Doganis, 2006, p. 224). At the end of the 1990s, traditional flag carriers faced new
challenges from the emergence of low‐cost, low‐fare carriers2 entering the market and
altering the competitive landscape. Again, traditional carriers had to rethink their strategies
and increase their flexibility in order to adapt to the changes in the marketplace.
The airline industry has been characterized by heavy regulations which limit airlines’ room
for maneuver. While other industries have paved the way for companies to transform into
global players, the principle that airlines should be ‘substantially owned and effectively
controlled’ by nationals from the given state in which the airline is registered, has prevented
airlines from becoming truly global businesses by obstructing cross‐border merger and
acquisition activities (Hanlon, 2007, p. 9; Doganis, 2006, p. 54; Shaw, 2007, p. 53). To
overcome the restrictions imposed by this nationality rule, airlines formed global alliances as
a means to secure some of the benefits a larger size and scope offer (e.g. greater purchasing
power, better distribution of maintenance costs, etc). While the 1990s witnessed an outright
alliance‐building frenzy, three major alliances, namely Star Alliance, oneworld, and
SkyTeam3, now dominate the competitive landscape (cf. Doganis, 2006, p. 85, 99). Shaw
(2007, p. 110) asserts that the formation of alliances was not a means in itself; rather, it was
an indispensable ‘detour’, since cross‐border consolidation activities continue to be
restricted by regulations. Moreover, Hanlon (2007, p. 10) argues that the existing airline
alliances may prove to be precursors to actual cross‐border mergers, considering that
government‐imposed constraints and regulations on foreign ownership are progressively
being relaxed.
The cyclical nature of the airline industry, with its growth cycles closely linked to changes in
the world economy, is one of its major economic idiosyncrasies (Doganis, 2006, p. 4; Mason,
2005, p. 19; Shaw, 2007, p. 64). However, this direct relationship between economic growth
and air travel demand seems to have weakened, mainly as a result of low‐cost airlines that
offer lower fares and thus stimulate demand irrespective of the economic situation
2 Low‐cost carriers are primarily characterized by their low operational costs, enabling them to offer low‐fare tickets.
3 Star Alliance has 19 member airlines. Among them are Air Canada, Air China, Lufthansa, Scandinavian Airlines, Singapore Airlines, Thai, and United (Star Alliance, 2009). oneworld has 10 member airlines, including American Airlines, British Airways, Cathay Pacific, JAL, and Quantas (oneworld, 2009). SkyTeam has 11 member airlines, including Air France, Alitalia, Southern China Airlines, Delta Air Lines, KLM, and Northwest Airlines (SkyTeam, 2009).
11
(Doganis, 2006, p. 18). Airlines furthermore have to cope with marginal profitability
(Doganis, 2006, p. 4; Hanlon, 2007, p. 5). The airline industry’s cost structure with high fixed
costs relative to variable costs makes volume a crucial factor for securing profits (Taneja,
2003 in: Tiernan et al., 2008, p. 213). While the constant emergence of new competitors and
the simultaneous pullout or failure of others intensify the industry’s dynamics, additional
pressure is exerted by the customer, who is gaining power in an increasingly transparent
market made possible by the easily accessible information on the Internet on prices,
conditions, and consumer rights (Mason & Alamdari, 2007, p. 303; Delfmann et al., 2005,
p. 12).
3.2 Key business models in the airline industry
In general, four fairly generic business models can be identified in the airline industry: (1)
network airlines, (2) low‐cost airlines, (3) charter airlines, and (4) regional airlines
(Bieger & Agosti, 2005, p. 50). Since network airlines and low‐cost carriers represent the
dominant business models in the international airline industry, only these two models will be
further elaborated on.
Network carriers are ‐ first and foremost ‐ characterized by an extensive international route
network with a complex hub‐and‐spoke system that includes short‐ and long‐haul
connections (e.g. Doganis, 2006, p. 149; Franke, 2004, p. 15; Tiernan et al., 2008, p. 214). In
most cases, network carriers evolved from formerly state‐owned flag carriers. Traditionally,
they have pursued a full service differentiation strategy. Different seating classes and
corresponding pre‐flight, in‐flight, and post‐flight services function as a means for
differentiation and further facilitate the targeting of multiple customer segments
(Pompl et al., 2003, p. 6; Tiernan et al., 2008, p. 214). Offering loyalty schemes such as
frequent flyer programs and belonging to one of the three major airline alliances (Star
Alliance, oneworld, and SkyTeam) complement network carriers’ differentiation strategy (cf.
Tiernan et al., 2008, p. 214). Yet network carriers’ profitability on short‐haul operations has
been heavily undermined by the expansion of low‐cost carriers and their impact on pricing.
Airline business experts (e.g. Mason & Alamdari, 2007, p. 306;4 Doganis, 2006, p. 266) argue
that the future business model of major network carriers will be based on an extensive long‐
4 Mason and Alamdari (2007) conducted a Delphi study with 26 air transport experts in order to detect future trends considering EU network carriers, low‐cost carriers, and consumer behavior.
12
haul network backed by alliances to provide a global spread, and supported by a short‐haul
and domestic network reduced significantly in size and importance.
In contrast to network carriers’ business model, which is based on service differentiation,
low‐cost carriers pursue a strategy of cost leadership. The traditional low cost model
concentrates on maximum aircraft utilization, the operation of a single aircraft type only,
and keeping to short turnaround times at secondary or less congested airports with lower
fees (e.g. Bieger & Agosti, 2005, p. 53; Doganis, 2006, pp. 147; Hanlon, 2007, pp. 58). An
overview of the most important operation and product features distinguishing low‐cost
carriers from network carriers is provided in Table 1.
Operation/ product feature Low-cost carriers Network carriers Airports Secondary, less congested (by and
large) 15-20 minute turnarounds
Primary (hubs) Higher turnaround times due to congestion and labor regulations
Aircraft Single aircraft type (e.g. Boeing 737, Airbus A320) High utilization (over 11 hours/day)
Multiple aircraft types Moderate utilization
Connection Point-to-point No interlining No baggage transfer
Hub-and-spoke Interlining Code share, global alliance
Distribution Mostly direct via Internet booking Travel agents Internet Call center
Fares Low Simple structure
Complex structure
In-flight Single class No seat assignment Pay for amenities, onboard selling
Multiple class Seat assignment Complimentary amenities In-flight entertainment
FFP No (by and large) Yes Target group Leisure, price sensitive business
travelers Leisure and business
Table 1: Comparison of low‐cost carriers vs. network carriers5
Owing to their significantly lower cost base, low‐cost carriers are able to offer point‐to‐point
services at substantially lower fares than network carriers. This introduction of low‐fare
services on European routes has brought about an increase in leisure travel, a higher traffic
volume, and a loss of market shares for both network carriers and charter airlines (Mason,
indicate that low‐cost carriers have been successful in increasing their number of business
5 Own illustration based on: Wensveen and Leick (2009, p. 6); Doganis (2006, p. 157); Hanlon (2007, pp. 58).
13
travelers in Europe as well (Mason & Alamdari, 2007, p. 302). Though Europe experienced a
virtual low‐cost boom in 2002/2003 with over a dozen new airlines entering the market
(Doganis, 2006, p. 161), several of them had to pull out of the market soon thereafter, since
they could not operate profitably or were taken over by competitors (Anonymous, 2006,
p. 19). Thus far, it seems that the low‐cost carrier business model is only successful on short‐
haul routes. Though several carriers have tried to adopt the low‐cost business model to long‐
haul international routes, such attempts have to date been unsuccessful (cf. Simon, 2008).
3.3 Customer segmentation
In order to define distinct target groups, customers are typically segmented along
demographic, psychographic, and/or behavioral dimensions (cf. Peter & Olson, 2008,
pp. 370; Solomon et al., 2006, p. 9). Shaw (2007, p. 24) specifies three variables along which
passengers in the airline market are traditionally segmented: (1) passengers’ journey
purpose (reason for travel), (2) the length of their journey, and (3) their country or culture of
origin. Oyewole & Choudhury (2006), on the other hand, contend that purchase situation
factors also represent useful segmentation dimensions. Accordingly, they differentiate
between reason for travel, frequency of travel, class of travel, and type of airline used.6 Since
the reason for travel constitutes the most traditional dimension along which customers are
segmented in the airline industry (cf. Teichert et al., 2008, p. 229), it is described in more
detail in the following section.
Airline customers can essentially be divided into business and leisure travelers. While there
may be some exceptions to these two dimensions (e.g. pilgrimage, medical transport) most
of the trips taken by airline passengers fit into one of these two categories (Shaw, 2007,
p. 24). Business travelers have long been the most important customer segment for airlines
due to their relative price inelasticity (Hanlon, 2007, p. 35). While business travelers in the
past gave emphasis to flexibility and service over price and, therefore, generally purchased
first and business class tickets, a large proportion of this customer segment seems to now be
giving preference to price over service, and seems willing to sacrifice flexibility and frills in
return for lower fares (Mason & Alamdari, 2007, p. 302). This development is corroborated
by recent studies which reveal that – in parallel to the decrease of business travelers who fly
6 In their study, Oyewole & Choudhury (2006) analyze the influence the four different purchase situations can have on the importance consumers attach to services in the airline industry.
14
business class on short‐haul routes – the proportion of passengers who choose low‐cost
carriers for business travel rose to 71% in 2004/2005 from only 28% in 1998/1999 (Company
Barclaycard in: Mason & Alamdari, 2007, p. 302). Indicators used in these studies show that
business travel continues to expand, but that the expenditures for business travel are under
increasing scrutiny (Barclaycard Business, 2008, p. 3). In 2007/2008, 55% percent of UK
business travelers stated that they fly economy class most often (cf. Figure 1) as compared
to 46% in 2006/2007. While 41% of the business travelers participating in the Barclaycard
survey cited business class as being their main class of travel in 2001, their number
decreased to only 11% in 2007 (Barclaycard Business, 2008, p. 5).
Figure 1: Most‐travelled seating class by UK business travelers in
20077
IATA’s (2007) ‘Corporate Air Travel Survey’ found that the key determinants for business
travelers’ airline choice for short‐haul flights included frequent flyer programs, convenient
departure and arrival times, as well as punctuality of flights. On long‐haul flights, the main
factors influencing business travelers’ airline choice were frequent flyer programs, non‐stop
flights, and seat comfort.
Air travel demand in the leisure travel segment is primarily influenced by ticket price,
travelers’ disposable income, and their available free time (Graham, 2006, p. 16), where the
amount of disposable income is principally determined by economic wealth. Graham (2006,
p. 16) points out that greater job pressure and concerns over job security actually deters
employees from taking leave for extended periods, which has contributed to the trend
toward shorter vacations. Lower fares, on the other hand, imply that frequent shorter trips
7 Own illustration adapted from: Barclaycard Business (2008, p. 5).
55%
15% 14%11%
5%
0%
10%
20%
30%
40%
50%
60%
Economy Premium economy
Low cost First/business Not stated
15
are not necessarily more expensive than the traditional annual leave (Mason, 2005, p. 303),
which has led to an increase in the frequency of shorter trips taken by leisure travelers
(Graham, 2006, p. 16). In recent years, the leisure travel market has grown more rapidly than
the business travel market (Hanlon, 2007, p. 35; Dresner, 2006, p. 30). Hanlon (2007, p. 35)
estimates that the current breakdown of the worldwide demand for air travel between
leisure and business lies at approximately 80/20.
3.4 Loyalty programs
Considering this highly competitive landscape, airlines need to undertake great efforts to
retain their profitable customers. Shaw (2007, p. 241) suggests that relationship marketing,
i.e., putting equal or greater emphasis on the maintenance and strengthening of
relationships with existing customers than on the acquisition of new customers, is an
effective concept to be pursued in order to retain customers. Loyalty programs that center
on passengers whose air travel demands are generally less price elastic (e.g. business
travelers) (Hanlon, 2007, p. 85) and expected to be so in the long‐term, constitute an
important customer relationship management tool (Liu & Yang, 2009, p. 104).
Liu and Yang (2009, p. 94) define loyalty programs as “long‐term‐oriented programs that
allow consumers to accumulate some form of program currency, which can be redeemed
later for free rewards.” Frequent flyer programs (FFPs) represent loyalty programs typical of
the airline industry. Consumers accumulate frequent flyer points for each purchased flight,
with the number of points awarded usually equaling the distance of the flight (Lederman,
2007, p. 1137). These accumulated points can eventually be redeemed for rewards, the most
common of which is a free flight or a free upgrade with the given airline or one of its alliance
partners (IATA, 2007, p. 73; Lederman, 2007, p. 1137; Carlsson & Löfgren, 2006, p. 1470).
Due to the award scheme’s nonlinear design, customers have even more incentives to stick
to one particular airline (Carlsson & Löfgren, 2006, p. 1470). Furthermore, airlines seek to
make their competitors appear more expensive by emphasizing the opportunity costs of
forgone loyalty rewards (Palmer, 2005, p. 161). Hence, frequent flyer programs constitute an
important economic switching barrier (Hanlon, 2007, p. 85; Dowling & Uncles, 1997).
Serious doubts, however, have been raised about the success of frequent flyer programs and
their contribution to true customer loyalty. Dowling and Uncles (1997), for example, claim
16
that customers end up associating their loyalty to a particular rewards program rather than
to the actual airline brand. Furthermore, Doganis (2006, p. 277) argues that frequent flyers,
who often are high‐yield passengers, tend to be members of several airlines’ FFPs.
Accordingly, FFPs’ relevance in terms of securing customer loyalty for a particular airline is
diminishing. A recent study conducted by Liu and Yang (2009) analyzed the success of
competing loyalty programs in the airline industry and found that loyalty programs did not
always lead to beneficial outcomes, and that only airlines with high market shares enjoyed
sales increases on account of their loyalty programs.
3.5 Industry outlook
Considering the downward trend in airline yields, primarily owing to airline deregulation and
liberalization, increased competition, excess capacity, downgrading activity, and the advance
of low‐cost carriers (cf. Mason, 2005, p. 19; A.T. Kearney, 2003, p. 8), industry experts
predict that consolidation activities in the airline business will increase (Doganis, 2006, p. 20;
A.T. Kearney, 2003, p. 8). Such activities may include mergers and acquisitions and will most
likely translate into strong airlines acquiring their weak or failing competitors (Doganis, 2006,
p. 21). Such a scenario will result in a market that is characterized by a small number of very
large network carriers (Mason & Alamdari, 2007, p. 310). Consolidation, however, is not
predicted to remain limited to network carriers alone. Rather, the trend toward
consolidation will affect all sectors of the industry, including low‐cost airlines (Doganis, 2006,
p. 21; Mason & Alamdari, 2007, p. 310). The challenges network carriers face in the
competition with low‐cost airlines on short‐haul routes have already been mentioned in
Chapter 3.1. Since the network carriers’ business model precludes the achievement of cost
structures similar to those of low‐cost carriers (e.g. complex hub‐and‐spoke system, labor
issues, unions), network carriers are expected to increasingly shift their focus to long‐haul
routes which will deliver sustainable profit streams (Mason & Alamdari, 2007). The current
trend among business travelers, who are increasingly becoming price‐sensitive, is further
forecast to lead to the termination of business class service on short‐haul routes, while more
leisure travelers will take advantage of low fares to travel more frequently both within the
EU and abroad (Mason & Alamdari, 2007, p. 310).
17
3.6 Chapter summary
The airline industry, which historically was state‐subsidized to demonstrate and sustain a
country’s status and power, has undergone extensive transitions since the mid‐1980s. These
changes were initiated in particular by gradual liberalization and deregulation. The
emergence of low‐cost carriers, the increasing power of customers, as well as a general
economic downturn applied pressure on airline managers to rethink their business strategies
yet again. Forecasts predict that the network carrier model will only remain sustainable on
international routes, while continental and short‐haul routes will increasingly be dominated
by a small number of large low‐cost carriers and a few niche carriers. With regard to airline‐
specific customer segments, a key differentiator between business and leisure travelers has
long been the higher price elasticity for leisure travelers (cf. Hanlon, 2007, p. 35; Dresner,
2006, p. 29). However, the introduction of low fare tickets by low‐cost carriers has weakened
the direct relationship between economic growth and air travel demand. Especially with
respect to network carriers, experts advise airline managers to focus on individual
customer’s needs, brand distinction, and the differentiation of services (Lufthansa
Consulting, 2008, p. 9). Only those airlines that find ways to attract and retain customers by
offering a differentiated service concept vis‐à‐vis competitors will succeed to operate
profitable on the grounds of a valuable customer base. The strengthening of customer
loyalty, therefore, is an important objective for achieving profitability through the retention
of valuable customers.
4 Conceptual and theoretical foundation for the development of
the airline customer loyalty model The previous chapter focused on current challenges in the airline industry and emphasized
the importance of a loyal customer base. This chapter sets the theoretical framework for the
development of the airline customer loyalty (ACL) model. Introducing customer loyalty as an
effective means for the achievement of a company’s overall objectives of profitability and
differentiation, this chapter first discusses different notions of customer loyalty to establish
a general understanding of the concept. Second, it is argued that the building of customer
loyalty is closely linked to the establishment and maintenance of relationships between the
customer and the firm, i.e., to relationship marketing. Furthermore, considering the
specificities of the service industry, special attention is given to the management of
18
customer‐brand relationships and the meaning of relational benefits and relationship
quality. The chapter concludes with a synthesis of the theories reviewed and the
identification of concepts to be ACL model.
4.1 The concept of customer loyalty
This chapter explains how customer loyalty can influence a firm’s profitability, introduces
definitions of customer loyalty as depicted in the literature, and discusses the prerequisites
for the establishment of true loyalty. It furthermore advocates the consideration of
relationship marketing to better understand the drivers of customer loyalty.
4.1.1 The influence of customer loyalty on a firm’s profitability
Several authors contend that a direct relationship exists between a firm’s loyal customer
base and its profitability (Reichheld & Sasser, 1990; Heskett et al., 2008; Reinartz & Kumar,
1991; Zeithaml et al., 1996). In addition, a loyal customer base can lead to decreased costs
(Reichheld, 1993; Berry, 1995), since it costs less to provide services to loyal and satisfied
customers (Reichheld, 1996) and because sales, marketing, and set‐up costs can be
amortized over an extended period, i.e., throughout the customer lifetime (Clark & Payne,
1994). Customer loyalty is furthermore essential, as it represents an important basis for
developing a sustainable competitive advantage (Dick & Basu, 1994, p. 99) over competing
brands in inter‐ and intra‐market competition.
19
4.1.2 Defining customer loyalty
Customer loyalty and its advantages for the firm have been extensively discussed in
marketing literature. The result is a plethora of definitions. Table 2 provides an overview of
definitions that are frequently cited in the literature.
Author(s) Definition Cunningham (1956) Single-brand loyalty is the proportion of total purchases represented
by the largest single brand used. Dual-brand loyalty is the proportion of total purchases represented by the two largest single brands used.
Day (1969) “There is more to brand loyalty than just consistent buying of the same brand – attitudes, for instance” (p. 29)
Jacoby & Kyner (1973) Brand loyalty is “(1) the biased (i.e., nonrandom), (2) behavioral response (i.e., purchase), (3) expressed over time, (4) by some decision-making unit, (5) with respect to one or more alternative brands out of a set of such brands, and (6) is a function of psychological (decision-making, evaluative) processes.” (p. 2)
Dick & Basu (1994) Customer loyalty is the strength of the relationship between an individual’s relative attitude and repeat patronage, mediated by social norms and situational factors.
Oliver (1999) “a deeply held commitment to rebuy or repatronize a preferred product/service consistently in the future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational influences and marketing efforts having the potential to cause switching behavior” (p. 34)
Table 2: Overview of definitions of customer loyalty
As the comparison of the different definitions of customer loyalty illustrates, two key
dimensions exist: a behavioral (cf. Cunningham, 1956) and an attitudinal (cf. Day, 1969)
dimension. Both are described below in more detail and an equal consideration of both
dimensions is advocated, if true loyalty is to be achieved.
Behavioral loyalty refers to the customer’s actual behavior of repurchasing a specific brand
within a given category over time (e.g., Day, 1969; Chaudhuri & Holbrook, 2002). Kumar and
Shah (2004, p. 318) describe behavioral loyalty as “loyalty of a customer as observed from
the customer’s purchase behavior.” This explicitly means that the customer repeatedly
chooses the same brand when he needs a specific product or service. This behavior may be a
result of a true preference for the brand. However, repeat purchases of the same brand may
also be attributable to mere convenience, habit, or because the barriers to change (i.e. the
switching barriers) are too high. While proponents of the one‐dimensional construct of
customer loyalty argue that attitude is irrelevant in determining loyalty toward a brand and
consider the debate on the notion of ‘true’ loyalty a “waste of time” (Sharp et al., 2002)
opponents claim that behavioral definitions of customer loyalty are inadequate for
20
explaining how and why customers are loyal to a specific brand, and call for an analysis of
the “individual’s dispositional basis for repeated purchase” (Dick & Basu, 1994, p. 100). Zins
(2001, p. 270) further criticizes that the observation of behavioral loyalty alone does not
leave room to draw any substantiated conclusions about customers’ future actions. Only
measuring behavioral loyalty actually overestimates the share of true loyalty, since it does
not account for those customers who buy a brand simply because no other alternative is
available or because a particular brand is offering a special promotion (Day, 1969).
Considering the deficiency of behavioral loyalty to provide insights into the underlying
motives and processes that lead to customer loyalty, researchers promote the inclusion of
attitude, in addition to behavior, to adequately define customer loyalty. Day (1969, cf. Table
2) was perhaps the first to recognize and articulate this necessity (Bandyopadhyay & Martell,
2007, p. 37). A customer’s attitude basically performs an object appraisal function. Keller
(2003, p. 392) refers to brand attitude as the overall evaluation of the brand in terms of its
quality and the satisfaction it generates. Dick and Basu (1994) assert that the attitude
toward a brand has to be measured in relation to other brands that are perceived by
consumers as being relevant in a specific consumption context. Only when a particular brand
is associated with a strong attitude and is clearly differentiated from other brands in the
customer’s mind does the given brand exhibit a high relative attitude vis‐à‐vis other brands
in the consumption context. Jacoby and Chestnut (1978) refer to attitudinal loyalty as the
consumer’s predisposition toward a brand as a function of decision‐making and evaluative
processes. Based on a strong preference for the given brand relative to other brands in the
category, attitudinal loyalty helps companies build an invisible exit barrier for their
customers, especially in non‐contractual situations where switching costs and barriers are
In this section, hypotheses about the causal relationships between relational benefits and
customer loyalty are formulated. As has been argued in Chapter 4.2.4, relationship quality
mediates the relationship between relational benefits and customer loyalty. Accordingly, the
influence of relational benefits on the two relationship dimensions, customer satisfaction
and relationship commitment, are proposed here as well.
5.2.1 Consequences of social benefits
Social benefits refer to the feeling of belonging and familiarity perceived by the customer as
a result of the long‐term relationship with the given airline brand. In a broader sense, social
benefits also relate to customers’ perceptions of how the brand can enhance their standing
in their social environments (see Chapter 4.2.3.1).
Several researchers have suggested that social benefits are positively related to the
customer’s commitment to the relationship (Goodwin, 1996; Goodwin & Gremler, 1996 in:
Hennig‐Thurau et al., 2002, p. 235). Berry (1995) claims that social bonds between
48
customers and service employees lead to higher levels of customer commitment to the given
company. Moreover, as argued in Chapter 4.2.2, relationships do not only exist between two
persons, they can also evolve between a person and a brand. On the premise that customers
only maintain a relationship with a brand if they benefit from it, positive experiences as
social benefits over time will lead to commitment on the customer’s part to maintain the
relationship in the future.
Differing results have been obtained on the effect of social benefits on satisfaction. While
Gwinner et al. (1998, p. 111) found a strong link between social benefits and customer
satisfaction, Hennig‐Thurau et al.’s study (2002) revealed that the relation between social
benefits and customer satisfaction was insignificant.
Reynolds and Beatty (1999, p. 14 referring to Crosby et al., 1990) argue that the interaction
between the customer and the service provider within a relationship is crucial for
satisfaction. Further support for this proposition is provided by Gremler and Gwinner (2000)
whose analysis on customer‐employee rapport13 suggests that such interaction plays a
significant role in the degree of satisfaction with the service provider. Social benefits,
however, do not only comprise the direct social interaction with the brand but also the
extent to which the brand reinforces its customers’ status within their social environments.
Since customer satisfaction is related to the degree to which customer expectations are met,
it can be said that the customer’s level of satisfaction in the interaction with the brand
increases in response to rising social benefits associated with the relationship.
Next to these indirect influences, a direct influence of social benefits on customer loyalty can
be proposed. Empirical evidence for this hypothesis has been established by several studies
on customer loyalty (Chang & Chen, 2007; Hennig‐Thurau et al., 2002; Price & Arnould,
1999, Reynolds & Beatty, 1999). Researchers contend that a strong link exists between the
social aspects of the customer‐provider relationship and customer loyalty. For example,
Berry (1995) suggests that social bonds between customers and employees can be used to
foster customer loyalty. Similarly, Oliver (1999) suggests that customers who are part of a
social organization (which may include both other customers and employees) are more
13 The concept of rapport is closely related to the concept of social benefits as defined here. Gremler and Gwinner (2000, p. 91) denominate positive interactions and personal connections as two common and important facets of rapport.
49
motivated to remain loyal to the given company. Social relationship concepts such as
fondness, tolerance, respect, and rapport (Gremler & Gwinner, 2000) have been found to be
influential in the development of service loyalty (Goodwin & Gremler, 1996). The effect of
social benefits on customer loyalty in the airline industry, moreover, has been substantiated
in a study among Taiwanese airline passengers (Chang & Chen, 2007). In their study
analyzing the relationship between relational benefits and customer loyalty in three classes
of service firms, Hennig‐Thurau et al. (2002) found that social benefits have a significant
influence on commitment and customer loyalty.
Correspondingly, the following hypotheses are formulated:
H10a: Social benefits positively influence customer satisfaction.
H10b: Social benefits positively influence relationship commitment.
H10c: Social benefits positively influence customer loyalty.
5.2.2 Consequences of psychological benefits
Psychological benefits refer to the positive feelings and emotions customers develop from
their relationship with the brand. Confidence in the positive outcomes of the relationship
results in less anxiety and a feeling of safety and comfort when interacting with the brand.
Customers further develop a feeling of trust, that is, a “willingness to rely on an exchange
partner in whom one has confidence” (Moorman et al., 1992, p. 315).
As Berry (1995, p. 242) suggests, “customers who develop trust in service suppliers based on
their experience with them […] have good reasons to remain in these relationships”. Trust is
seen to reduce consumer uncertainty and vulnerability in service relationships (cf. Beatson
et al., 2008, p. 215; Berry, 1995, p. 242). These benefits can create relationship efficiency for
the customer (e.g. through decreased transaction costs) which, in turn, fosters commitment
to the relationship (Garbarino and Johnson, 1999; Hennig‐Thurau et al., 2002; Morgan and
Hunt, 1994; Beatson et al., 2008, p. 215). If customers feel comfortable with the service
brand, they are more likely to develop a positive attachment to the brand. Through the
ongoing relationship, customers know what to expect from the brand and perceived risk and
anxiety decrease. All of these factors affect a customer’s willingness to remain in and refine
the relationship with the brand in the future, that is, psychological benefits are also
proposed to positively influence relationship commitment.
50
Less anxiety about the relationship can also have a positive impact on satisfaction (cf.
Hennig‐Thurau et al., 2002; Beatson et al., 2008, p. 215; Anderson & Narus, 1990). Beatson
et al. (2008, p. 215) propose that customers’ confidence in the honesty and integrity of a
brand are likely to result in increased customer satisfaction with the brand and its
performance. Psychological benefits relate to customers’ knowledge about what to expect
from the airline brand. Based on the confirmation/disconfirmation paradigm, it can be
argued that when the brand meets the customer’s expectation, perceived psychological
benefits lead to customer satisfaction.
Turning again to Berry’s (1995, p. 242) proposition that customers who trust the service
provider will remain in the relationship, it can further be proposed that psychological
benefits have a positive influence on customer loyalty. Accordingly, Chang and Chen (2007)
found that confidence benefits have a positive and significant influence on customer loyalty.
As described in Chapter 4.1.3, a relationship between the customer and the brand develops
through several encounters and interactions over time. The customer’s experience of the
brand as a relationship partner that can be trusted motivates him to continue the interaction
with the brand and, hence, remain in the relationship.
Hennig‐Thurau et al. (2002) emphasize the significance of the link between confidence
benefits and customer satisfaction, as well as between confidence benefits and customer
loyalty. However, in their study, confidence benefits only have an insignificant influence on
commitment. In the business‐to‐business context, on the other hand, Sweeney and Webb
(2007) found the link between psychological benefits and relationship commitment to be
crucial. Beatson et al. (2008), in a study on relationship quality in cross‐sea passenger
transportation, determined that relationship trust affects satisfaction, commitment, and
behavioral intentions.
Correspondingly, the following hypotheses are formulated:
14 As argued in Chapter 4.2.3.3, the conceptualization of functional benefits in this thesis partly relate to the conceptualization of special treatment benefits as conceptualized by Gwinner et al., 1998 and Hennig‐Thurau et al., 2002.
52
5.3 The influence of relationship quality on customer loyalty
Relationship quality has been described as a concept that mediates the influence of
relational benefits on customer loyalty (see Chapter 4.2.4). In the following section, the
interrelationship between customer satisfaction and relationship commitment, and the
effects of both concepts on customer loyalty are hypothesized.
5.3.1 The influence of customer satisfaction on commitment and customer loyalty
Customer satisfaction here refers to the affective state determined by the evaluation of the
brand’s performance (cf. Zins, 2001, p. 276). It is a judgment of the service brand’s capability
to provide “a pleasurable level of consumption‐related fulfillment, including levels of under
or overfulfillment” (Oliver, 1997, p. 13). Customers are satisfied if the performance meets or
exceeds their expectations prior to consumption. Likewise, they are dissatisfied if the brand
does not meet their expectations.
Customer satisfaction is theoretically and empirically considered to be one of the most
important factors influencing customer loyalty (Garbarino & Johnson, 1999; Heskett et al.,
2008). Customers choose brands that they think can satisfy their needs. If customers
evaluate an airline brand as being capable of meeting the expectations they have raised
prior to consumption, it is presumed that customers are satisfied with the brand. Once
satisfied, customers will choose the same airline for subsequent travels. In line with this
argumentation, Beatson et al. (2008) found that customer satisfaction positively influences
behavioral intentions such as willingness to recommend the brand, positive word‐of‐mouth,
and repurchase intention, i.e. customer loyalty. Park et al. (2006) determined that customer
satisfaction directly influences behavioral intentions, which were measured as the
customer’s willingness to recommend the airline to others and their repurchase intention.
Gwinner et al. (1998) showed that satisfaction with the service provider positively impacts
customer retention. Reynolds and Beatty (1999) demonstrated that satisfaction with a
company was positively linked to loyalty to the company. Hennig‐Thurau et al. (2002) found
that of all constructs hypothesized to influence customer loyalty, satisfaction had the
strongest impact.
Customer satisfaction is further assumed to positively influence customers’ commitment to
their relationship with the airline brand. A high level of satisfaction resulting from the
53
interaction with the airline brand provides repeated positive reinforcement, thereby
creating positive emotional commitment bonds with the brand (cf. Beatson et al., 2008, p.
215; Hennig‐Thurau et al., 2002, p. 237; Hennig‐Thurau & Klee, 1997, p. 753).
Correspondingly, the following hypotheses are formulated:
5.4 Graphical illustration of the proposed ACL model
Summarizing the formulated hypotheses, Figure 5 provides a graphical illustration of the ACL
model.
Figure 5: The ACL model
6 Empirical testing of the proposed airline customer loyalty model This chapter describes the empirical testing of the ACL model. The analysis approach, the
data collection method, the operationalization of the model’s constructs, as well as the
analytical results are presented.
6.1 PLS as research method
6.1.1 Selection of PLS as research method
To empirically validate the ACL model developed in the previous chapter for its
transferability to reality, a research method needs to be chosen that is able to accurately
test the model. The method, therefore, needs to be able to analyze logically and
theoretically derived causal relationships between latent (i.e. unobservable) variables.
According to Malhotra and Birks (2007, p. 406) structural equation modeling (SEM), a
statistical technique based on multiple regression and factor analysis, is suitable to test
Social benefits
Psychological benefits
Functional benefits
Customer satisfaction
Country-of-origin
Co-creation of value
Service quality
Perceived value
Trust-worthiness
FFP attractiveness
Brand-self congruence
Social brand performance
Relationship commitment
Customer loyalty
Airline image
55
interrelationships among a set of variables (see also: Pallant, 2001, pp. 91‐92; Haenlein &
Kaplan, 2004, p. 285).
In general, there are two approaches to SEM which can be differentiated according to their
underlying estimation algorithms: covariance‐based approaches (e.g., LISREL, AMOS) and
variance‐based approaches (e.g., PLS) (Jahn, 2007, p. 1; Haenlein & Kaplan, 2004, p. 285).
Based on the differentiation of both approaches according to Jahn (2007; see also: Haenlein
& Kaplan, 2004), the variance‐based PLS approach proves to be the more appropriate
approach for the present analysis: first, besides constructs that are reflectively
operationalized, the ACL model established in Chapter 5 also includes one construct (i.e.
service quality) that is formatively operationalized.15 While PLS basically supports a
formative operationalization of latent variables and therefore can be used for models with
reflective and formative types of indicators (Fornell & Bookstein, 1982, p. 442), covariance‐
based approaches do not accept formative variables (Blunch, 2008, p. 155). Second, in
comparison to covariance‐based approaches, PLS is insensitive to skewed distributions; a
normal distribution of the empirical data is therefore not imperatively required (Fornell &
Bookstein, 1982, p. 443; Huber et al., 2007, p. 10). Third, as previously stated, the present
analysis pursues a managerial perspective and is thus strongly practice‐orientated. Especially
for this reason the variance‐based approach PLS is preferred in this study, since it is
demonstrably the approach with the highest predictive accuracy and, hence, the highest
practical explication (cf. Huber et al., 2007, p. 13; Jahn, 2007, p. 16).
6.1.2 Application of PLS
The partial least squares (PLS) estimation basically consists of three parts. (1) The structural
model (inner model) reflects the relationships between the latent variables (Haenlein &
Kaplan, 2004, p. 290). While latent variables are characterized by abstract, not directly
measurable content, each latent variable needs to be defined by a set of indicators (cf.
Huber et al., 2007, p. 3). (2) The measurement model (outer model) describes how the latent
variables and their manifest indicators (i.e., measurement variables) are connected
(Haenlein & Kaplan, 2004, p. 290; Blunch, 2008, p. 5). (3) Weight relations, which link the
15 See Edwards and Bagozzi (2000) for a more elaborate differentiation between reflective and formative variables.
56
indicators to their respective unobservable variables, are further used to estimate case
values for the latent variables (Chin & Newsted, 1999 in: Haenlein & Kaplan, 2004, p. 290).
In general, indicators can be divided into two groups – reflective and formative variables.
Their differentiation is based on the direction of the relationship between the latent variable
and its respective indicators (Edwards & Bagozzi, 2000, p. 155). Reflective variables mirror
the latent variable (cf. Edwards & Bagozzi, 2000, p. 155). They are caused by the latent
variables and are indirectly affected by exogenous influences on the latent variable (Bollen,
1989 in: Diamantopoulos, 1994, p. 445; Zinnbauer & Eberl, 2004, p. 4). Formative variables,
on the other hand, form the construct (Edwards & Bagozzi, 2000, p. 15), and constitute
conceptual elements of the latent variable (Huber et al., 2007, p. 18). In comparison to
reflective variables, changes in the latent variables are, therefore, caused by their formative
indicators (Haenlein & Kaplan, 2004, p. 288).
Based on the differentiation between the structural model and the measurement model as
well as the two types of indicators, different quality criteria need to be tested in order to
validate the model. Hulland (1999, p. 198) suggests that a PLS model should be analyzed and
interpreted sequentially in two stages: (1) the assessment of the reliability and validity of the
measurement model; and (2) the assessment of the structural model. Appendix 1 discusses
the quality criteria that need to be fulfilled for both stages, respectively.
Compared to covariance‐based structural equation models, there is no overall goodness‐of‐
fit measure for the PLS model. However, based on a summarized validation of the
previously‐mentioned quality criteria, an overall evaluation of the model’s informational
value is possible (cf. Fornell & Bookstein, 1982, p. 450; Huber et al., 2007, p. 43).
6.2 Data collection
While general methodological considerations have been dealt with in Chapter 2, the
following section addresses the particular data collection method chosen. It further
introduces the questionnaire design before providing information about the course of the
data collection and descriptive data of the sample.
57
6.2.1 Internet survey as data collection method
To collect the primary data needed to test the transferability of the hypothesized ACL model
to reality, a self‐administered Internet survey was chosen as the data collection method. This
choice is primarily based on the Internet survey’s inherent advantages compared to other
survey methods such as personal interviewing, telephone interviewing, or mail interviewing
(cf. Malhotra & Birks, 2007, pp. 273‐274). Internet surveys present a cost efficient method to
collect a great amount of data in a relatively short time frame. Furthermore, comparing data
reliability for telephone and Internet‐based surveys, Braunsberger et al. (2007) found that
web panels display higher levels of data reliability than telephone surveys. This effect can be
ascribed to the removed interviewer bias (Malhotra & Birks, 2007, p. 274) for self‐
administered surveys. The lack of an interviewer affords more privacy to the respondents
(Braunsberger et al., 2007, p. 763), which may lead respondents to answer questions more
truthfully. The software‐controlled collection of data further decreases the risk of wrong or
incomplete data. Respondents can be advised of uncompleted questions, for example.
Thereby, the quality of the data is increased (Malhotra & Birks, 2007, p. 274). As data is
already stored in electronic format, the electronic processing of the data is more efficient
and less prone to transmission error (cf. Saunders et al., 2007, p. 358).
The most important limitations to Internet surveys are probably sample representativeness
and issues of sample control and diversification (cf. Prophis, 2002 in: McConkey et al., 2003,
p. 78; Malhotra & Birks, 2007, p. 275). As Internet use has, however, been growing in all
societal segments in the last years, it is already evident that the total population is
increasingly well represented in the community of Internet users (cf. Lütters, 2004, pp. 15).
6.2.2 Questionnaire design
The questionnaire is divided into four parts. First, respondents are introduced to the survey
and informed about its purpose and background. In the context of the introduction,
respondents are advised of the anonymity of their information and instructed that it is their
personal perceptions and opinions that are to be the basis of their answers. Furthermore,
survey participants are advised that they have the opportunity to take part in a drawing for
an iPod nano by providing their email address at the end of the questionnaire. Second,
participants are asked to choose an airline about which they will answer the stated
questions. They are advised to choose an airline they have preferably flown with more than
58
once within the last three years. The self‐selection of the airline was chosen to make sure
that respondents have sufficient knowledge about the airline to answer the survey
questions. The third and major part of the questionnaire addresses questions related to the
concepts in the ACL model. Participants are asked to specify to which degree they agree or
disagree with each statement in a series about the concepts in the model (for the
operationalization of the concepts, see Chapter 6.3). A 7‐point Likert scale was chosen as the
rating scale, ranging from ‘strongly agree’ to ‘strongly disagree’. It was chosen in order to
give respondents a wide enough range, on the one hand, but to not overwhelm respondents
with too many answer possibilities, on the other hand (cf. Saunders et al., 2007, p. 372).
Fourth, respondents were asked to provide information about their general travel habits
with respect to air transport and some information on their socio‐demographic background.
The questionnaire designed for the study is available in Appendix 2.
6.2.3 Course of data collection and descriptive data of sample
To make sure that the questionnaire was easy to understand and fill in, a pretest was
conducted in the period from January 30 to February 03, 2009. In total, 8 people
participated in the pre‐test with most of the participants aged between 20 and 35 years. To
ensure that the questionnaire was also easy to fill in for older respondents, 2 persons older
than 60 years were asked to take part in the pre‐test. Furthermore, half of the testers were
chosen because of their regular flying habits, while the other half were fairly inexperienced
with regard to the airline industry in general. The selection of pre‐testers was made in order
to cover a wide variety of respondents, which was anticipated in the actual sample.
The sampling for the survey took place as a combination of targeted emails and a snowball
procedure (cf. Malhotra, 2007, p. 414). The link including a short introduction and the
request to participate was posted on several online platforms and was also sent via email. In
the field time, between February 15, 2009 and February 20, 2009, a total of 276 respondents
participated in the survey. An overview of the socio‐demographic distribution of the
respondents and their particular travel habits is provided in Appendix 3.
The sample indicates an almost even distribution between female (51.1%) and male (48.9%)
respondents. Two thirds of the survey participants belonged to the age range between 20
and 29 years, indicating an overrepresentation of young participants. Corresponding to the
age distribution, 43.1% indicated that they were students while 27.9% were company
59
employees. With respect to the information regarding travel habits, 72.8% claimed that they
primarily travelled on leisure while 27.2% stated that their primary reason for air travel was
business. These numbers almost correspond to Hanlon’s (2007, p. 35) 80/20 breakdown
between leisure and business airline passengers (see Chapter 3.3). Interestingly, 80% of
respondents indicated that they traveled by air at least once every 6 months (52.9% travel
by air at least once every 3 months), which emphasizes that respondents had profound
knowledge of and experience with airline travel.
In summary, it can be concluded that the sample indicates an overrepresentation of young
participants and students. Due to the high level of the overall sample quality, it should not
be overvalued, but must be kept in mind when interpreting the findings.
6.3 Operationalization of constructs and validation of measurement model
In the following, the operationalization of the constructs included in the ACL model is
described. A number of studies previously conducted by other authors have been reviewed
in order to compile measurement scales that suit the measurement of the integrated
constructs. These items were either directly adopted or adapted to the present study. If no
measurement items could be found to accurately measure the respective construct, new
indicators were created. A compilation of the measurement scales reviewed is provided in
Appendix 4.
Prior to the estimation of the ACL model with smartPLS, an exploratory factor analysis was
conducted in SPSS. The results are briefly discussed in Chapter 6.3.1 before the
operationalization of the constructs and the validity of the measurement model is analyzed
in Chapters 6.3.2 to 6.3.6.
6.3.1 Exploratory factor analysis
An exploratory factor analysis was conducted to examine to what extent the formulated
questionnaire items are related to the latent constructs of the ACL model (cf. Byrne, 1998,
p. 6). Factor analysis can only be conducted for reflective variables (cf. Fornell & Bookstein,
1982, p. 441). As service quality is defined by formative indicators, it is left out of the
exploratory factor analysis. Aside from the items measuring airline image, social brand
performance, and functional benefits, all other questionnaire items could be allocated to the
construct they were intended to measure. A list of the measurement items is provided in
60
Appendix 5. A summary of the results from the exploratory factor analysis can be found in
Appendix 6.
Resulting from the findings of the exploratory factor analysis, the constructs airline image
and social brand performance were merged and entitled airline reputation. The
measurement items for airline reputation consist of all items originally asked with reference
to airline image plus items one, two, and five that were asked for social brand performance.
Items three and four measuring social brand performance were excluded from the analysis.
Furthermore, concerning functional benefits, items one and two were deleted, leaving only
As reported in Chapter 6.3.1, the exploratory factor analysis resulted in merging the
construct airline image and social brand performance. Interpreting the questionnaire items
constituting the newly created construct, this construct was entitled airline reputation. In
contrast to airline image, airline reputation alludes to associations and opinions of society,
not just of individual customers.
Measurement items
Factor loadings T-values
1 I have always had a good impression of this airline. 0.738 22.5432 I believe this airline has a better image than its competitors. 0.816 31.9723 In my opinion, this airline has a good image in the minds of
passengers. 0.870 56.415
4 I think that this airline has a good reputation in society. 0.849 39.5965 Most people who are important to me like this airline. 0.711 19.7946 My friends and family highly value this airline. 0.744 23.9967 I think that a lot of people have a high opinion about this airline. 0.832 35.377Discriminant validity: Fornell-Larcker-Criterion: fulfilled
Measurement items one, two, and three are adopted from Park et al. (2006, based on: Nha
& Gaston, 2001). Item four widens the concept of airline image, including the airline’s
reputation in society. Statements five and six, which originally measured subjective norm,
are based on Chang (1998). Statement 7 is adapted from Martensen and Grønholdt (2004)
focusing on social approval as part of emotional brand evaluation.
61
Brand‐self congruence
The scale for testing brand‐self congruence was adopted from a survey on brand‐consumer
relationships conducted at LMU, Munich. While the original scale was in German, the scale
was translated into English and checked for meaning and grammar by a native speaker (cf.
Saunders et al., 2007, p. 377).
Measurement items
Factor loadings T-values
1 The brand image and how I see myself are very similar. 0.887 57.5932 The brand says a lot about who I am and who I want to be. 0.905 68.5933 I can identify with the brand. 0.925 85.7094 The brand and I have very much in common. 0.929 52.5065 I think there is a similarity between what the brand stands for
and me. 0.925 56.046
6 The brand suits me. 0.863 40.892Discriminant validity: Fornell-Larcker-Criterion: fulfilled
Table 4: Operationalization of brand‐self congruence
Trustworthiness
Measuring trustworthiness, items one, two, and three have been adapted from Söderlund
and Julander (2003), while items four and five have been adapted from Martensen &
Grønholdt (2004).
Measurement items
Factor loadings T-values
1 This airline is upright and sincere. 0.855 34.3132 This airline cares about my needs. 0.862 33.2693 This airline is concerned about my well-being. 0.845 28.1684 This airline is trustworthy and credible. 0.890 66.2265 This airline communicates openly and honestly. 0.828 28.603Discriminant validity: Fornell-Larcker-Criterion: fulfilled
Several scales can be found for testing the service quality of airlines. While a great number
of authors concentrate on testing service quality in its own right, the scales are usually quite
extensive. For this study, a scale from Park et al. (2006) was adopted. Resulting from in‐
depth interviews and focus group discussions with airline staff and passengers, the authors
identified three dimensions of service quality characteristic for airline services, namely
62
‘reliability and customer service’, ‘in‐flight service’, and ‘convenience and accessibility’. The 3
measurement items with the highest values within each dimension have been selected to
measure airline service quality in the present survey.
Measurement items Weights T-values 1 The employees of this airline are willing to help passengers. 0.181 1.8292 The employees of this airline are able to answer passengers’
questions in a satisfactory way. 0.152 1.765
3 The employees of this airline give passengers personal attention.
0.125 1.315
4 This airline offers high seating comfort. 0.143 1.4525 This airline offers great meal service. 0.259 2.6186 This airline offers great in-flight entertainment. 0.001 0.0117 The reservation and ticketing is prompt and accurate. 0.277 2.8138 The check-in service of this airline is very good. 0.086 0.8219 This airline offers a convenient flight schedule. 0.190 2.725Discriminant validity: Composite correlation < 0.9: fulfilled
Rajah et al. (2008) argue that, while the idea of value co‐creation has been conceptually
discussed by a number of authors, their study is the first to support it empirically. Of the
three measurement items proposed by the authors, only item one was adopted from their
study. Items two to seven have been developed for this study. They relate to the
understanding of value co‐creation as has been elaborated in Chapter 4.2.1.
63
Measurement items
Factor loadings T-values
1 If necessary, this airline really goes out of its way to react to my needs.
0.827 33.116
2 If there is a problem, this airline is interested in what I have to say.
0.872 46.813
3 This airline tailors its service to my needs. 0.876 57.1724 I find it easy to contact this airline. 0.664 14.4625 I feel that my comments and concerns are highly valued by this
airline. 0.877 53.380
6 This airline is responsive to my needs. 0.894 63.3537 I have experienced this airline offering non-standardized levels
Table 9: Operationalization of airline country of origin
FFP attractiveness
The measurement items for FFP attractiveness are loosely based on a study by Long et al.
(2006) in which the authors analyzed important aspects of frequent flyer programs for
business and leisure travelers. While the authors identified four factors relating to airlines’
FFPs, namely ‘keeping score’, ‘program benefits’, ‘flight treatment’, and ‘administrative
issues’, only items from program benefits (see items one, two, three, and four) and
treatment (see items five and six) are included to measure FFP attractiveness in this analysis.
64
Measurement items
Factor loadings T-values
1 This airline’s frequent flyer program is very attractive. 0.811 18.6192 This airline’s frequent flyer program offers desirable benefits. 0.855 22.7583 It is easy to redeem benefits earned from this airline’s frequent
flyer program. 0.803 19.614
4 This airline’s frequent flyer program helps me reduce the cost of air travel.
0.713 12.835
5 This airline’s frequent flyer program treats members better than other travelers who do not belong to the program.
0.754 11.981
6 Being a member of this airline’s frequent flyer program makes me feel special.
Table 10: Operationalization of FFP attractiveness
6.3.3 Operationalizing relational benefits
Social benefits
As previously discussed in Chapter 4.2.3.1, in this study social benefits are considered to
have a much broader meaning compared to Gwinner et al.’s (1998) original description.
While measurement item one is adapted from LaBahn’s definition of social rapport as “the
client’s perception that the personal relationships have the right chemistry and are
enjoyable“, the remaining measurement items of social benefits have been developed for
this study based on the definition of social benefits predominant in this thesis.
Measurement items
Factor loadings T-values
1 The interaction with this airline and its employees is enjoyable. 0.698 19.0812 Dealing with this airline’s employees gives me a sense of
harmony. 0.817 37.497
3 Traveling with this airline, I perceive a feeling of familiarity. 0.796 28.4134 This airline emphasizes my role in society. 0.884 63.2955 This airline complements my social status. 0.858 48.8886 This airline supports my lifestyle. 0.792 28.947Discriminant validity: Fornell-Larcker-Criterion: fulfilled
As mentioned in Chapter 4.2.3.2, psychological benefits relate to the customers’ positive
feelings and emotions derived from the relationship with the brand. Since these include the
confidence benefits defined by Gwinner et al. (1998), some of the measurement items are
adopted from confidence benefit measurements adopted in related studies. For example,
65
measurement items one, two, and three are adopted from Chang and Chen (2007) who
analyzed the influence of confidence benefits on switching barriers and customer loyalty
among airline customers in Taiwan. Measurement items one and two have similarly been
used to measure psychological benefits in the B2B context by Sweeney and Webb (2007).
Measurement items four, five and six are adapted from Gwinner et al.’s (1998) confidence
benefit measurements, where item five has also been used by Sweeney and Webb (2007) to
measure psychological benefits. Item seven has been added to place more emphasis on the
feeling of security and comfort that characterizes the definition of psychological benefits in
this thesis.
Measurement items
Factor loadings T-values
1 I feel I can trust this airline. 0.803 23.7012 I am less worried when I fly with this airline. 0.879 51.2903 I am confident that the service will be performed correctly by
this airline. 0.829 33.936
4 I believe there is less risk that something will go wrong. 0.873 45.2285 I know what to expect from this airline. 0.724 13.5346 I have less anxiety when I buy a ticket for this airline. 0.801 27.7147 I feel secure and comfortable with this airline. 0.887 50.962Discriminant validity: Fornell-Larcker-Criterion: fulfilled
Table 13: Operationalization of functional benefits
66
6.3.4 Operationalizing relationship quality
Customer satisfaction
Customer satisfaction is measured adapting Hennig‐Thurau et al.’s (2002) measurement
items to the airline context (items one to four). Additional items measuring customers’
satisfaction in relation to their previous expectations (item five) (cf. Han et al., 2008, p. 39)
and in comparison to the airline’s competitors (item six) (cf. Zhang & Bloemer, 2008) have
further been included.
Measurement items
Factor loadings T-values
1 Overall, I am very satisfied with this airline. 0.821 30.9402 I am always delighted with this airline’s service. 0.819 31.6463 It is wise of me to fly with this airline. 0.807 31.5054 I think I do the right thing when I decide to use this airline. 0.840 36.6085 My experiences with this airline exceed my expectations. 0.784 26.8296 In comparison to other airlines, I am very satisfied with this
Table 14: Operationalization of customer satisfaction
Relationship commitment
All of the items measuring customers’ relationship commitment have been adopted from
Hennig‐Thurau et al.’s (2002) study.
Measurement items
Factor loadings T-values
1 I am very committed to my relationship to this airline. 0.863 52.3652 My relationship to this airline is very important to me. 0.963 181.0343 I really care about my relationship to this airline. 0.953 126.9734 My relationship to this airline deserves my maximum effort to
Table 15: Operationalization of relationship commitment
6.3.5 Operationalizing customer loyalty
To give consideration to both the attitudinal and the behavioral aspect of customer loyalty,
the measurement items for customer loyalty include both dimensions. Items one and two
relate to positive word‐of‐mouth and willingness to recommend the brand. Items three and
four measure the customers’ repurchase intention (i.e. the customers’ intention to utilize
the service of the airline again). All items are adapted from Nadiri et al. (2008). In addition,
67
measurement item five is included to measure the customer’s overall loyalty towards the
airline.
Measurement items
Factors loadings T-values
1 I say positive things about this airline to others. 0.866 44.3402 I recommend this airline to others. 0.871 47.9433 I consider this airline the first choice for air transport. 0.857 43.5914 I will consider this airline for air transport in the next few years. 0.759 25.6565 I consider myself to be loyal to this airline. 0.813 35.731Discriminant validity: Fornell-Larcker-Criterion: fulfilled
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Table 21: Summary of survey participants’ situational characteristics
Appendices
118
Appendix 4: Measurement scales reviewed for operationalization of constructs
Overview of consulted studies Martensen & Grønholdt (2004)
Development of a customer-based brand equity model linking brand associations and brand evaluations to customer-brand relationships
Chang (1998) Study comparing the validity of theory of reasoned action and theory of planned behavior with respect to their ability to predict unethical behavior
Zins (2001) Study investigating the role of relative attitude and commitment in customer loyalty models. Using insights gained from a study in the commercial airline industry
Park et al. (2006) Study investigating the impact of service quality and other marketing variables on airline passengers’ future behavioral intentions
Ostrowski et al. (1993) Study investigating the relationship between service quality and retained preferences as a measure of customer loyalty
Nadiri et al. (2008) Survey investigating the impact of developed industry-specific service quality dimensions on customer loyalty toward the national airline of Northern Cyprus
Andreassen & Lindestad (1998)
Study investigating the impact of corporate image on quality, customer satisfaction and loyalty in the Norwegian packaged tour industry
Esch et al. (2006) Study investigating the influence of brand knowledge and brand relationships on current and future purchases
Grzeskowiak & Sirgy (2008)
Study investigating the influence of self-image congruence, customer loyalty, brand-community, and consumption regency on customer well-being
Han et al. (2008) Study investigating determinants of service loyalty across various service contexts among Chinese consumers
Söderlund & Julander (2003)
Study examining the role of trust in customers‘ satisfaction responses to poor and good services
Rajah et al. (2008) Study exploring the role of co-creation of value for the strengthening of the customer-marketer relationship
Long et al. (2006) Study examining the influence frequent flyer programs have on loyalty to the service provider
Gwinner et al. (1998) Studies investigating the benefits customers receive as a result of engaging in long-term relational exchanges with service firms
Sweeney & Webb (2007) Study examining the influence of functional, psychological, and social relationship benefits on individual and firm commitment to the relationship in a B2B context
Hennig-Thurau et al. (2002)
Study investigating the influence of relational benefits and relationship quality on relationship marketing outcomes in different service contexts
Chang & Chen (2007) Study examining the influence of relational benefits on switching barriers and customer loyalty among Taiwanese airline customers
Paul et al. (2009) Testing theory about repeat purchase drivers for consumer services Reynolds & Beatty (1999) Study investigating the influence of relational benefits on satisfaction,
loyalty, word of mouth, and purchases in retailing Zhang & Bloemer (2008) Study examining the impact of value congruence on consumer-service
brand relationships among consumers of clothing stores and banks in the Netherlands.
Beatson et al. (2008) Study examining the impact of employee behavior and relationship quality on customers in the cross-sea passenger transport context
Table 22: Overview of consulted studies
Appendices
119
Social brand performance Martensen & Grønholdt (2004) -> social approval as part of emotional evaluation
Brand X is a lifestyle more than a product. I really identify with people who use brand X. I am proud to use brand X.
Chang (1998) subjective norm Most people who are important to me think I should buy this brand. My friends and family’s opinion about the airline (washing powder) I use is. important to me Making my choice, I am concerned about other people’s opinion.
Table 23: Studies consulted with respect to ‘social brand performance’
Airline image Zins (2001) This airline is competent.
This airline offers great quality Park et al. (2006) based on: Nha & Gaston (2001)
I have always had a good impression of this airline I believe this airline has a better image than its competitors In my opinion, this airline has a good image in the minds of passengers
Ostrowski et al. (1993) Carrier image Please choose the airline that is best for each of the following: - convenient schedules - low fares - frequent flyer program - quality of customer service - airline reputation - on-time performance Note: the names of major carriers were listed and respondents were to check their one choice for each criteria
Nadiri et al. (2008, p. 270) Availability of low price ticket offerings Consistency of ticket prices with given service Image of the airline company
Andreassen & Lindestad (1998, p. 16)
Overall opinion of the company Opinion of the company’s contribution to society Liking of the company
Esch et al. (2006, p. 101) based on: Low & Lamb (2000)
Overall attitude towards the brand Perceived quality of the brand The brand’s overall affect
Table 24: Studies consulted with respect to ‘airline image’
Appendices
120
Brand-self congruence Grzeskowiak & Sirgy (2008, p. 302)
self-image congruence, adapted from direct measures of self-congruity (Sirgy et al. 1997)
Do the typical people who buy this brand of coffee match how you see yourself? 1. I can identify myself with the people who buy this brand of coffee. 2. The typical person who buys this brand of coffee matches how I see myself 3. The image of this coffee brand is highly inconsistent with my self-image Do the typical people who shop at this coffee store match how you see yourself? 1. I can identify myself with the people who shop at this store 2. The typical person who comes to this store matches how I see myself. 3. The image of this store is highly inconsistent with my self-image Do the typical people who work at this coffee store match how you see yourself? 1. I can identify myself with the people who work at this store. 2. The typical person who works at this store matches how I see myself. 3. The image of this store’s personnel is highly inconsistent with my self-image.
Bruner et al. (2001, p. 513) based on: Sirgy et al. (1997)
Take a moment to think about…. Think about the kind of person who typically uses …. Imagine this person in your mind and then describe this person using one or more personal adjectives such as stylish, classy, masculine, sexy, old, athletic, or whatever personal adjectives you can use to describe the typical user of …. Once you’ve done this, indicate your agreement or disagreement to the following statements. … is consistent with how I see myself … reflects who I am People similar to me fly (wear) … … is very much like me … is a mirror image of me
Survey about brand relationships at LMU University Munich
Das Markenimage und mein Selbstbild sind in vielen Dingen sehr ähnlich. (The brand and how I see myself are very similar) Die Marke sagt viel darüber aus, wer ich bin und sein will. (The brand says a lot about who I am and who I want to be) Ich kann mich mit der Marke identifizieren. (I can identify with the brand) Die Marke hat mit mir viel gemein. (The brand and I have very much in common) Die Marke passt zu mir. (The brand suits me) Ich sehe Ähnlichkeiten zwischen dem, wofür die Marke steht und meiner Person. (I think there is a similarity between what the brand stands for and me)
Table 25: Studies consulted with respect to ‘brand‐self congruence’
Appendices
121
Trustworthiness Martensen & Groenholdt (2004) Trust and credibility
Brand X is trustworthy and credible Brand X communicates openly and honestly I have great faith in brand X
Han et al. (2008, p. 39) Trust This hotel is trustworthy because it is concerned with the customer’s interests. This hotel treats customers with honesty. This hotel has the ability to provide for my needs. I trust and am willing to depend on this hotel.
Söderlund & Julander (2003) based on: Anderson et al. (1994); Ganesan, (1994); Garbarino & Johnson (1999); Morgan & Hunt (1994)
X keeps its promise to me X does really care for me I feel I can trust X X is concerned about my well-being I feel confidence with regards to X
Table 26: Studies consulted with respect to ‘trustworthiness’
Service quality Zins (2001) In-flight comfort
- leg-room - chair width Personal service - friendliness - service on board Catering - variety - quality
Park et al. (2006) Reliability and customer service - courtesy of employees - employees who are willing to help passengers - employees who have the knowledge to answer passengers' questions - give passengers personal attention - neat appearance of employee - safety of flying - sincere interest in solving problems - on-time performance Convenience and accessibility - convenience of reservation and ticketing - Promptness and accuracy of reservation and ticketing - Check-in service - Frequent flyer program - Promptness and accuracy of baggage delivery - availability of non-stop flight - Convenient flight schedule - seat allocation - amount imposed for overweight baggage In-flight service (Park et al., 2006) - seating comfort - seat space and legroom - meal service - in-flight entertainment services - up-to-date aircraft and in-flight facilities
Martensen & Grønholdt (2004) The employees are competent The employees give me individual attention The employees are courteous and forthcoming
Appendices
122
Han et al. (2008) Service reliability (very unreliable/very reliable) Service individuation (very standard/very individualized) Service professionalism (very unprofessional/very professional) Service speed (very slow/very fast) Service facilities (very dated/very advanced) Staff appearance and manner (very inappropriate/very appropriate) Staff interest and caring (very little/very much) Overall service quality (poor/excellent)
Table 27: Studies consulted with respect to ‘service quality’
Perceived value Park et al. (2006) Considering the services that the airline offers, are they worth
what you paid for them? The ticket price of this airline is reasonable
Martensen & Groenholdt (2004) brand value as dimension of rational evaluation
Brand X provides good value for money Brand X lives up to my expectations It makes sense to buy brand X instead of any other brand, even if they are the same
Andreassen & Lindestad (1998, p. 15)
Quality given price Price given quality
Table 28: Studies consulted with respect to ‘perceived value’
Co-creation of value Rajah et al. (2008) The company really went out of its way to work with the
customer. The final purchase solution was arrived at mainly through the joint effort of the company and the customer. I would describe the situation described as a very high level of purchasing co-creation.
Table 29: Study consulted with respect to ‘co‐creation of value’
FFP attractiveness Long et al. (2006) Keeping score
Program benefits Flight treatment Administrative issues
Table 30: Study consulted with respect to ‘FFP attractiveness’
Appendices
123
Social benefits Gwinner et al. (1998) I am recognized by certain employees
I am familiar with the employee(s) who perform(s) the service I have developed a friendship with the service provider They know my name I enjoy certain social aspects of the relationship
Sweeney & Webb (2007) We have more than a formal business relationship with them We have a real friendship with them We work on things together We share information
Hennig-Thurau et al. (2002) I am recognized by certain employees. I enjoy certain social aspects of the relationship. I have developed a friendship with the service provider. I am familiar with the employee(s) that perform(s) the service. They know my name.
Chang & Chen (2007) I enjoy certain social aspects of the relationship Some airline employees know my name I have developed friendships with certain airline employees
Paul et al. (2009) Affiliation: …it creates a feeling of attachment to the airline or other people there. Altruism: …it allows me to do something good for the airline or others Communication: …it allows me to have enjoyable interactions with the employees or other customers Community: …it helps to ensure that I can live in a thriving community
Table 31: Studies consulted with respect to ‘social benefits’
I feel I can trust this airline I am not worried when I fly on this airline I am confident that the service will be performed correctly by this airline
Sweeney & Webb (2007) B2B context
We have peace of mind in dealing with them We trust them We know what to expect of/from them If they give us their word, we know that whatever it is, it will be done There's a real sense of understanding between us
Gwinner et al. (1998) confidence benefits
I believe there is less risk that something will go wrong I feel I can trust this airline (service provider) I have more confidence the service will be performed correctly I have less anxiety when I buy the service I know what to expect when I buy a ticket for this airline (go in) I get the airline's (provider's) highest level of service
Paul et al. (2009) That airline [brand company] [most important attribute] is important to me, because Autonomy: …it allows me to decide and act on my own Comfort: …it helps me to feel less stress then when there … Confidence: …it helps me to trust Privilege: …it makes me feel like a preferred customer Welcomeness: …it makes me feel welcome as a customer
Table 32: Studies consulted with respect to ‘psychological benefits’
Appendices
124
Functional benefits Reynolds & Beatty (1999) I value the convenience benefits my airline (sales associate)
provides me very highly. I value the time saving benefits my airline (sales associate) provides me very highly. I benefit from the advice my sales associate gives me. I make better purchase decisions because of my sales associate.
Chang & Chen (2007) special treatment benefits
I can get faster service if necessary I am placed higher on the stand-by lost when the flight is full This airline will manage to give me a seat when the flight is full This airline will upgrade my seat when possible
Gwinner et al. (1998) special treatment benefits
I get discounts or special deals that most customers do not get I get better prices than most customers They do services for me that they do not do for most customers I am placed higher on the priority list when there is a line I get faster service than most customers.
Paul et al. (2009) That airline [brand company] [most important attribute] is important to me, because Convenience: …it helps me to save time and effort Knowledge: …it allows me to feel informed Money savings: …it helps me to save money
Table 33: Studies consulted with respect to ‘functional benefits’
Customer satisfaction Park et al. (2006) based on: Oliver (1980)
Overall, how satisfied are you with the airline's service quality? My choice to use this airline was a wise one I think that I did the right thing when I decided to use this airline
Hennig-Thurau et al. (2002) My choice to use this airline (company) was a wise one. I am always delighted with this airline's (firm’s) service. Overall, I am satisfied with this airline (organization). I think I did the right thing when I decided to use this airline (firm).
Compared to other airlines (banks), I am very satisfied with X Based on all my experience with X, I am very satisfied My experiences at X have always been pleasant Overall, I am satisfied with X
Martensen & Groenholdt (2004) satisfaction as dimension of rational evaluation
Overall, how satisfied are you with brand X? How well does brand X meet your expectations? When thinking of your ideal brand, how well does brand X compare?
Andreassen & Lindestad (1998, p. 16)
Overall satisfaction Comparison with an ideal package tour company Congruence with expectations
Han et al. (2008, p. 39) I am satisfied with my experiences in this hotel. I have had pleasurable stays in this hotel. I am satisfied with this hotel overall. My experiences at this hotel have exceeded my expectations.It was wise of me to stay at this hotel.
Table 34: Studies consulted with respect to ‘customer satisfaction’
Appendices
125
Relationship commitment Hennig-Thurau et al. (2002) My relationship to this specific airline (service provider) . . .
- is something that I am very committed to. - is very important to me. - is something I really care about. - deserves my maximum effort to maintain.
Beatson et al. (2008) I am loyal to [firm name]. I am committed to my relationship with [firm name] because I like being associated with them I feel strongly attached to [firm name]. I would like to develop a long term relationship with [firm name]. I feel a sense of belonging to [firm name].
Table 35: Studies consulted with respect to ‘relationship commitment’
Repurchase intention Nadiri et al. (2008) I consider this airline company first choice for air
transportation. I will consider this airline company more for air transport in the next few years.
Chang & Chen (2007) I will continue patronizing this airline. Zhang & Bloemer (2008) adapted from: Lam et al. (2004); Zeithaml et al. (1996)
I consider X as my first choice for airlines (banks). I will do more business with X in the next few years. If I had to do it over again, I would make the same choice.
Positive word-of-mouth Nadiri et al. (2008) I say positive things about this airline company to other
people. I recommend this airline company to someone who seeks my advice. I encourage my friends and relatives to fly with this airline company.
Chang & Chen (2007) I say positive things about this airline to others. I recommend this airline to others.
Hennig-Thurau et al. (2002) I often recommend this airline (service provider) to others. Zhang & Bloemer (2008) adapted from: Fullerton (2003); Zeithaml et al. (1996)
I say positive things about X to other people. I recommend X to people who seek my advice. I encourage friends and relatives to do business with X.
Willingness to interact Martensen & Groenholdt (2004) engagement
I am very interested in brand X.
Willingness to pay more Zhang & Bloemer (2008) I am willing to continue to do business with X, even if its
prices increase. I am willing to pay a higher price than other airlines (banks) charge for the benefits I currently receive from X.
Table 36: Studies consulted with respect to ‘customer loyalty’
Appendices
126
Appendix 5: Measurement items included in questionnaire
Model constructs Measurement items
Soc
ial b
rand
pe
rform
ance
1. Most people who are important to me like this airline. 2. My friends and family highly value this airline. 3. I am proud to fly with this airline. 4. This airline represents a specific lifestyle. 5. I think that a lot of people have a high opinion about this airline.
Airl
ine
imag
e
1. I have always had a good impression of this airline. 2. I believe this airline has a better image than its competitors. 3. In my opinion, this airline has a good image in the minds of passengers. 4. I think that this airline has a good reputation in society.
Bra
nd-s
elf
cong
ruen
ce
1. The brand image and how I see myself are very similar. 2. The brand says a lot about who I am and who I want to be. 3. I can identify with the brand. 4. The brand and I have very much in common. 5. I think there is a similarity between what the brand stands for and me. 6. The brand suits me.
Trus
t-w
orth
ines
s
1. This airline is upright and sincere. 2. This airline cares about my needs. 3. This airline is concerned about my well-being. 4. This airline is trustworthy and credible. 5. This airline communicates openly and honestly.
Ser
vice
qua
lity
1. The employees of this airline are willing to help passengers. 2. The employees of this airline are able to answer passengers’ questions in a
satisfactory way. 3. The employees of this airline give passengers personal attention. 4. This airline offers high seating comfort. 5. This airline offers great meal service. 6. This airline offers great in-flight entertainment. 7. The reservation and ticketing is prompt and accurate. 8. The check-in service of this airline is very good. 9. This airline offers a convenient flight schedule.
Perceived value
1. Considering the services that this airline offers, they are worth what I pay for them. 2. The ticket price of this airline is reasonable.
Co-
crea
tion
of
valu
e
1. If necessary, this airline really goes out of its way to react to my need. 2. If there is a problem, this airline is interested in what I have to say. 3. This airline tailors its service to my needs. 4. I find it easy to contact this airline. 5. I feel that my comments and concerns are highly valued by this airline. 6. This airline is responsive to me needs. 7. I have experienced this airline offering non-standardized levels of service to me.
Cou
ntry
-of
-Orig
in 1. I have a favorable opinion about the country this airline originates from.
2. I really like this airline’s country-of-origin. 3. I have a very good impression about this airline’s country-of-origin. 4. I feel comfortable about this airline’s country-of-origin.
Appendices
127
FFP
attr
activ
enes
s 1. This airline’s frequent flyer program is very attractive. 2. This airline’s frequent flyer program offers desirable benefits.
3. It is easy to redeem benefits earned from this airline’s frequent flyer program. 4. This airline’s frequent flyer program helps me reduce the cost of air travel. 5. This airline’s frequent flyer program treats members better than other travelers who
do not belong to the program. 6. Being a member of this airline’s frequent flyer program makes me feel special.
Soc
ial b
enef
its 1. The interaction with this airline and its employees is enjoyable.
2. Dealing with this airline’s employees gives me a sense of harmony. 3. Traveling with this airline, I perceive a feeling of familiarity. 4. This airline emphasizes my role in society. 5. This airline complements my social status. 6. This airline supports my lifestyle.
Psy
chol
ogic
al
bene
fits
1. I feel I can trust this airline. 2. I am less worried when I fly with this airline. 3. I am confident that the service will be performed correctly by this airline. 4. I believe there is less risk that something will go wrong. 5. I know what to expect from this airline. 6. I have less anxiety when I buy a ticket for this airline. 7. I feel secure and comfortable with this airline.
Func
tiona
l be
nefit
s
1. This airline saves me time and effort. 2. I feel confident in my purchase decision when I buy a ticket for this airline. 3. Compared to other airlines, I have the feeling to save money when I buy a ticket for
this airline. 4. It is easy and convenient to use this airline.
Cus
tom
er
satis
fact
ion
1. Overall, I am very satisfied with this airline. 2. I am always delighted with this airline’s service. 3. It is wise of me to fly with this airline. 4. I think I do the right thing when I decide to use this airline. 5. My experiences with this airline exceed my expectations. 6. In comparison to other airlines, I am very satisfied with this airline.
Rel
atio
nshi
p co
mm
itmen
t 1. I am very committed to my relationship to this airline.
2. My relationship to this airline is very important to me. 3. I really care about my relationship to this airline.
4. My relationship to this airline deserves my maximum effort to maintain.
Loya
lty
1. I say positive things about this airline to others. 2. I recommend this airline to others. 3. I consider this airline the first choice for air transport. 4. I will consider this airline for air transport in the next few years. 5. I consider myself to be loyal to this airline.
Table 37: Measurement items included in questionnaire
Appendices
128
Appendix 6: Results of exploratory factor analysis
KMO- und Bartlett’s Test Kaiser-Meyer-Olkin measure of sampling adequacy
,920Bartlett’s Test of Sphericity Approx. Chi-sq. 9439,231 df 741
Sig. ,000Table 38: KMO‐ and Bartlett‐test for constructs of brand performance characteristics
Table 49: Coefficients of determination (R²) for endogenous constructs
Calculation of VIF for social benefits Regression on Adjusted R² VIF = 1/1-R²AirRep 0,391 1,642Bsc 0,303 1,435Servq 0,516 2,066Perv 0,109 1,122CoV 0,464 1,866
Calculation of VIF for psychological benefits Regression on Adjusted R² VIF = 1/1-R²AirRep 0,443 1,795Bsc 0,336 1,506Trustw 0,536 2,155Servq 0,53 2,128CoV 0,479 1,919CoO 0,116 1,131
Calculation of VIF for functional benefits Regression on Adjusted R² VIF = 1/1-R²Trustw 0,437 1,776Servq 0,424 1,736Perv 0,135 1,156CoO 0,102 1,114FFP 0,053 1,056
Appendices
132
Calculation of VIF for satisfaction Regression on Adjusted R² VIF= 1/1-R² SocBen 0,26 1,351PsyBen 0,264 1,359FunBen 0,054 1,057
Calculation of VIF for commitment Regression on Adjusted R² VIF= 1/1-R² SocBen 0,377 1,605PsyBen 0,425 1,739FunBen 0,177 1,215Sat 0,567 2,309
Calculation of VIF for loyalty Regression on Adjusted R² VIF= 1/1-R² SocBen 0,47 1,887PsyBen 0,44 1,786FunBen 0,174 1,211Sat 0,567 2,309Comm 0,36 1,563Note: Highest VIF for each construct is marked in bold
Table 50: Calculation of variance inflation factors (VIF) for structural model
Endogenous construct Stone-Geisser Q²
Social benefit 0,427Psychological benefit 0,405Functional benefit 0,244Satisfaction 0,435Commitment 0,316Loyalty 0,437
Table 51: Stone‐Geisser Q² for endogenous constructs
Appendices
133
Figure 10: The structural ACL model
Soci
al
bene
fits
Psyc
holo
gica
l be
nefit
s
Func
tiona
l be
nefit
s
Cus
tom
er
satis
fact
ion
Serv
ice
qual
ity
Perc
eive
d va
lue
Co-
crea
tion
of
valu
e
FFP
attra
ctiv
enes
s
Cou
ntry
-of-
orig
in
Trus
t-w
orth
ines
s
Bran
d-se
lf co
ngru
ence
Airli
ne
repu
tatio
n
Rel
atio
nshi
p co
mm
itmen
t
Cus
tom
er
loya
lty
0.40
(8.8
6)0.
4(8
.80)
0.15
(2.8
1)
-0.0
1(0
.23)
0.04
(0.5
9)
R²=
0.6
6
R²=
0.5
96
R²=
0.3
77
R²=
0.6
5
R²=
0.3
91
R²=
0.6
45
NOTE: N
umbe
rs are path coefficients. Num
bers in
brackets are t‐values.
Dotted lines indicate nonsignificant
paths. R² ind
icates the am
ount of
variance
explained.
Appendices
134
Appendix 9: Sub‐group comparison
Combination Group comparison Combination 1 The hypothesis is rejected for both sub-groups. Hence, there is no
significant difference between the sub-groups. Combination 2 The assessed values for the evaluated hypothesis are identical for both
sub-groups. Hence, there is no significant difference between the sub-groups.
Combination 3 The hypothesis is accepted for one sub-group but rejected for the other. Hence, there is a significant difference between the sub-groups.
Combination 4 The hypothesis is accepted for both sub-groups. By means of a t-test it has to be evaluated whether the difference is significant. The difference between the sub-groups is significant for a calculated t-value > 1.66 (α=10%) or > 1.98 (α=5%). According to Chin (2002):
n Size of sub-group 1 m Size of sub-group 2
; Estimate of the original sample with regard to the model association of interest in both sub-groups
); Standard error of the generated bootstrap sample Table 52: Criteria for the evaluation of significant differences between sub‐groups18