Aviation Environment in Greece: A case study of Aegean Airlines and Olympic Airways
Aegean Airlines and Olympic Airways are two airlines based in Athens, Greece - Aviation Environment in Greece: A case study of Aegean Airlines and Olympic Airways introduction. Strong market conditions are found in the Airlines. The purpose of this case study is find out the environment in Aegean Airlines and Olympic Airways in terms of effects of commitment of Aegean Airlines and Olympic Airways management to satisfy customers necessary for high service quality. The level of satisfaction or dissatisfaction among customers was analyzed with the help of different variables such as: l) perception of customers about the quality of service provided at the Aegean Airlines, 2) the suitability present between the external communication and the quality of service provided at the Aegean Airlines and Olympic Airways, and 3) the situational variable. It was found that the situational variable played a significant role in the differentiation of extent of satisfaction or dissatisfaction among the customers using Aegean Airlines and Olympic Airways it is found that the Aegean Airlines and Olympic Airways’ environment regarding service quality and customer satisfaction is lacking in internal and technical perspectives. It is recommended that the Aegean Airlines and Olympic Airways should utilize their resources for the fulfillment of other organizational objectives.
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Chapter One: Introduction
The service industry plays a great role in the development of a nation through a unique phenomenon. The environment of aviation is consisted of several factors and customer satisfaction is one of them. The quality of interactions between the customers and the concerned personnel measure the level of customers’ satisfaction about the service industry. Emphasis is now made on the quality of service provided to the customers. If quality of service provided by an airline is satisfactory then the airline may survive in the competitive environment. Two airlines are studied in this research namely Aegean Airlines and Olympic Airways. Both the airlines are highly successful in their market. But it is found that both the airlines are lacking in the commitment of the management of these airlines to satisfy their customers’ needs and wishes.
Purpose of the Study
The present study has following purposes:
· Studying the effects of customers’ perceptions on service quality to the customer satisfaction level.
· Studying the effects of conformity between service quality and external communication on the customer satisfaction level.
· Studying the variables for differentiating the levels of customers’ satisfactions or dissatisfactions.
· Studying whether the customers (from segments of business, holidays, or visiting friends and relatives) have differences in, expressing their satisfactions or dissatisfactions.
· Studying the effects of management commitment and level of employee’s work/job satisfaction on the customers’ perceptions about service quality and level of customers’ satisfaction.
Importance of the Study
According to the model of customers’ satisfaction by Zeithaml and Bitner (1996b), quality service is the focus of assessments reflecting the customers’ perceptions on the five specific dimensions of services, namely: 1) empathy, 2) reliability, 3) responsiveness, 4) tangibility, and 5) assurance. On the other hand, the concept of satisfaction is more inclusive than the concept of quality service. Customer satisfaction is influenced by five variables, namely: 1) service quality, 2) product quality, 3) price, 4) situation, and 5) personality.
In this research, we made several modifications to the Zeithaml and Bitner model (1996b). First, combining the variables of product quality and service quality into variable of service quality (in this research, the term used is “customers’ perception of service quality”, as the customers have already compared their expectations and the delivered service). Besides, combining the variables of product quality, service quality is also based on the nature of the airline service product itself, where it is difficult to differentiate product from service. Second, differentiating the variables of situation differentiated by delay in departure and non-delay. Third, differentiating the variables of customers’ personality by:
a) Segments of travel destination: business, holidays, and visiting friends,
c) Passenger class,
e) Educational level,
g) Income per month, and
h) Previous experiences in flying with the respective airline company.
The fourth modification is differentiating the variable of price, namely differentiating the customers by the amount they pay for their tickets, discounted, or non-discounted (normal price). The fifth modification is, adding the variable of conformity between service quality and external communication as the variable that influences the level of customer satisfaction.
Two variables will be analysed from the service provider side, namely, management commitment and employee’s job satisfaction. Management commitment is whether the service provider (airline company) had already considered the customers’ expectations. Employees’ job satisfaction refers to measuring the personnel’s satisfaction regarding the job as a whole: salary, acquired facilities, colleagues, superiors, and relationship with the customers.
Overview of Remaining Chapters
Rest of the study is organized as follows: Chapter Two provides review of related literature. Chapter Three provides the research hypotheses. Chapter Four provides research methodology. Chapter Five provides research results and discussions. Chapter Six provides theoretical implications and applications and chapter Seven provides conclusion and recommendations.
Chapter Two: Review of Related Literature
Role of Culture in Satisfaction of Customers and Perceived Service Quality
Customers’ evaluations of service quality and their expressions of satisfaction are critical inputs to the development of marketing strategies (Ofir and Simonson 2001). Customer satisfaction undeniably has come to be an important cornerstone of customer-oriented business practices for firms that operate in diverse industries and global markets (Szymanski and Henard 2001). Satisfaction ratings are viewed as means to strategic ends, such as repurchase behavior and customer retention (Mittal and Kamakura 2001), that directly affect a firm’s profits and overall performance. However, even though most companies recognize that satisfying customers’ needs and wants is critical to their success, developing the understanding to achieve that goal is becoming increasingly difficult in today’s global arena (Darling and Taylor 1996). Verhage, Yavas, and Green (1990,p. 302) warn that “global marketers need to be very cautious in accepting theories or techniques that are proven to be successful in their home markets.” As firms reach over national borders, they are challenged to establish a marketing orientation effectively across a complex of national cultures (Nakata and Sivakumar 2001). Most satisfaction research has used U.S. subjects to develop and test satisfaction theory (Spreng and Chiou 2002); thus, such measures of quality and satisfaction may be less applicable and less meaningful in other countries, thereby leading to less-than-optimal results. This is no less true for services than for products; the service sector is taking on increasing importance in the global economy, particularly in most advanced countries, such as those in the European Union as well as Canada, Japan, and the United States. Services have replaced goods as the building blocks of employment and gross national product in the economically developed world (Bowen and Hallowell 2002).
Despite increasing evidence that points to the emergence of a global consumer culture–that is, a horizontal segment of consumer groups with similar values, norms, and behaviors across cultures and national boundaries–the vast majority of consumers worldwide are not (yet) members of that segment (Alden, Steenkamp, and Batra 1999). Thus, cultural differences must be taken into account in any successful marketing effort, including the measurement of service quality and satisfaction. The four distinguishing characteristics of services (inseparability, variability, intangibility, and perishability; Kotler 2003) pose formidable obstacles for globalization. Depending on the context of the service consumption experience, the cultural characteristics of consumers are likely to interact with one or more of the four dynamic characteristics of service-dominated products. In testimony to this notion, the quest for universally applicable dimensions of service quality (applicable to all cultures and markets) has eluded researchers and thus remains ongoing (Bolton and Myers 2003).
Antecedents of Customer Satisfaction: Expectations and Perceived Service Quality
Perceived service quality has proved among the most important, yet debatable, constructs in recent marketing literature. It has been shown to be an input to both customer satisfaction and value (Oliver 1996), which in turn have a direct impact on customer loyalty to the service organization (Zeithaml, Berry, and Parasuraman 1996). Before the actual consumption experience, it is posited that consumers hold a set of expectations (based on previous or similar experiences or primed by communications, including word of mouth and/or advertising) that serve as a benchmark for quality interpretations of the service encounter. Customers who have salient expectations are likely to perceive deviations from their recollections with respect to the particular service episode.
Simply stated, perceived service quality reflects how well the service delivery matches or exceeds a customer’s expectations. Nonetheless, the elusiveness of this construct has been referred to by Brady and Cronin (2001) and by Parasuraman, Zeithaml, and Berry (1985), to name a few. Much research has focused on how service quality perceptions should be measured (Brady and Cronin 2001; Cronin and Taylor 1992; Parasuraman, Zeithaml, and Berry 1985, 1988). Most research stems from Parasuraman, Zeithaml, and Berry’s (1985) work in which they applied gap analysis to the area of services and derived the idea of “perception gaps,” or gaps that occur between the service firm’s perception of quality provided and the customer’s perception of quality received. This gap model is based on the disconfirmation paradigm that was originally used in the product literature (Churchill and Surprenant 1982) and that resulted in the well-known, highly debated SERVQUAL model (Parasuraman, Zeithaml, and Berry 1988). The SERVQUAL model has been used to assess quality in many types of service situations; some scholars (Weekes, Scott, and Tidwell 1996) believe that its adaptability is its main strength, provided that a generic base adequate to measure process and industry-specific outcomes can be added.
Brady, Cronin, and Brand’s (2002) study provides an interesting alternative to the disconfirmation paradigm and the SERVQUAL measure of perceived service quality by replicating and extending the work of Cronin and Taylor (1992), who offer theoretical justification for discarding the expectations section of SERVQUAL and focusing on performance only. Brady, Cronin, and Brand use SERVPERF to measure performance only and find it to be superior to the gap-based SERVQUAL scale in measuring perceived service quality, which they find to be properly modeled as an antecedent of satisfaction.
Customer satisfaction is the paramount marketing outcome (Patterson 1993); it is a function of the expectations that the consumer brings to the service encounter (Zeithaml, Berry, and Parasuraman 1996) and of his or her subsequent evaluations of service quality (Oliver 1996). Satisfaction levels are a convenient means for identifying and segmenting consumers in markets, given that “repeat purchases, rather than trial purchases, dominate sales of existing services” (Bolton and Myers 2003, p. 110). Thus, in international contexts, it is crucial to grasp how culture influences the level of satisfaction. The answer to this question has critical implications for how global service providers allocate resources in different cultures and different countries.
Services are both intangible and variable, which forces consumers to rely on extrinsic cues, such as the person providing the service or the appearance of the service facility, to evaluate the service encounter. Furthermore, the quality of the interpersonal interaction (which reflects the service characteristic of “inseparability”) between the customer and the contact employee often influences customer satisfaction (Bitner 1992). Garbarino and Johnson (1999) find that for low-relational customers, satisfaction is the primary mediating construct, whereas for high-relational customers, trust and commitment are the mediators between component attitudes and future intentions. This implies that when there is trust and commitment between the customer and the service provider, there will be less dissatisfaction expressed, and the customer will be less likely to leave a service provider as a result of a single poor performance. This implication could be particularly important to the Asian or Japanese service setting, in which trust and commitment are considered prerequisites of any good service-provider relationship.
Although many of the causes of satisfaction and dissatisfaction with products and services are universal (e.g., poor quality), variation exists according to cultural context (Schütte and Ciarlante 1998), particularly for Asian consumers. Lee (1990) proposes a modified Fishbein (1967) behavioral intention model to account for the two most important social influences in a Confucian culture such as Japan: group conformity pressure and the concept of face. Thus, Asian consumers can be expected to express dissatisfaction less often because of a need to maintain group harmony and a desire to shield the service provider from “losing face.” However, Asia is fundamentally a service culture, so a low level of expressed consumer dissatisfaction should not be considered equal to a high level of consumer satisfaction. Thus, we consider cultural context and restrict satisfaction to transaction-specific judgments (Cronin and Taylor 1992) that have both affective and cognitive components (Oliver 1996).
Culture and Consumer Behaviour
Culture can be defined as the sum of learned beliefs, values, and customs that create behavioural norms for a given society (Yau 1994, p. 49). Culture is to society what memory is to individuals (Kluckholn 1954). Hofstede (1991,p. 4) defines culture as “the collective programming of the mind.” Culture is everything that people have, think, and do as members of their society (Ferraro 2002), and it often manifests in consumer decisions, which are driven by individual values that members of a culture hold. Cultural values are considered the basic motivators in life and are the prescriptions for behaviour (Rokeach 1973), including consumer behaviour. Culture’s influence on marketing activities continues to increase in today’s global marketplace (Peñaloza and Gilly 1999). Indeed, the influence of culture has been demonstrated in nearly all facets of marketing efforts, including advertising (Laroche et al. 2001), market entry mode (Brouthers and Brouthers 2001), retailer practices (Bello and Dahringer 1985), Internet usage (Quelch and Klein 1996), shopping practices (Ackerman and Tellis 2001), multinational marketing teams (Salk and Brannen 2000), and the marketing environments themselves (Doran 2002).
The influence of culture is our focus because perceptions are filtered through the lens of culture, and perceived performance has been demonstrated to affect satisfaction and perceived service quality directly (Halstead, Hartman, and Schmidt 1994). Attitudes and beliefs, which are integral parts of any culture, are included in the affective component, which many scholars (see Szymanski and Henard 2001) believe has an impact on satisfaction levels beyond classical expectancy-disconfirmation effects. Furthermore, different cultures vary with respect to behavioral norms. Therefore, from culture to culture, customers are apt to evaluate services differently and to hold different expectations about optimal and adequate encounters (Bolton and Myers 2003). We research the influence of culture with respect to both perceived service quality and expressed satisfaction, because it has been demonstrated that they are distinct but related constructs (Fournier and Mick 1999).
The Dimensions of National Culture and Consumer Behaviour
National culture has been defined as patterns of thinking, feeling, and acting that are rooted in common values and societal conventions (Nakata and Sivakumar 2001). National cultures have been classified in many ways, but Hall’s (1976) context paradigm and Hofstede’s (1980) and Hofstede and Bond’s (1988) cultural dimensions are the most widely accepted cultural theories among marketing and international business scholars. In this study, we examine three national cultures (United States, Canada, and Japan) in terms of Hall’s context paradigm and Hofstede’s cultural dimensions. Culture has been shown to influence marketing efforts to these three groups for product choice (Hulland 1999), product usage (Ferley, Lea, and Watson 1999), and consumption patterns (Kim, Laroche, and Joy 1990), to name a few. Japanese and U.S. consumers have different reactions to marketing efforts of industrial services (Money, Gilly, and Graham 1998) and different attitudes toward direct marketing (Maynard and Taylor 1996), movies and television programs (Corliss 1999), and advertising (Taylor, Miracle, and Chang 1994).
Contextual variation occurs along a continuum, on which Japan is at the extreme of the high-context countries, and Germany and Switzerland are at the extreme of the low-context countries. Canada and the United States are relatively low-context countries (Hall 1976). In high-context cultures, the building of relationships and trust comes before business, whereas the opposite is true in low-context cultures. In low-context cultures, meaning is taken from words (i.e., explicit meaning). In high-context cultures, more meaning comes from the context in which something is said, including the setting and the status of the people involved; nonverbal communication and visual cues take on additional meaning and importance. In low-context cultures, individual achievement and individual welfare are of prime importance; in high-context cultures, the welfare of the group and the maintaining of group harmony are top priorities. In addition, cooperation, reasonableness, and understanding of others are the most admired virtues (Gannon 2001). People often suppress their true feelings for the good of the group or a relationship. From a marketing perspective, this suggests that customer loyalty is greater in a high-context country such as Japan, because customers do not want to disturb the harmony of the relationship that they have established with the seller. The high-context nature of Asian cultures has been attributed to Confucian influences. Because national character is said to be formed by history and embedded in culture (Chow et al. 1997), the two main national characteristics of Japan (“groupism” and vertical relationships) are believed to stem from the Tokugawa era, Japan’s 250-year period of self-imposed isolation from the rest of the world. Rather than confrontation, the notions of seriousness, self-sacrifice, self-control, discipline, and harmony were ingrained in the culture.
Hofstede (1980) and Hofstede and Bond (1988) derive five main distinguishing aspects of countries’ national cultures: individualism, uncertainty avoidance, masculinity, power distance, and long-term orientation. The first dimension closely resembles that of Hall’s (1976) context paradigm and lies along a continuum (on which individualism and collectivism form endpoints) that captures people’s social behavior toward the group. Loose ties between people characterize individualist (and low-context) cultures, whereas strong, cohesive ties between group members characterize collectivist (and high-context) cultures. Fatalism (i.e., the tendency for a person to submit to his or own fate) is also characteristic of collectivist cultures, whereas members of individualist cultures are more apt to seek control over their own fate. A high-context communication style is a feature of collectivist cultures, whereas low-context communication figures in individualist cultures. Bolton and Myers (2003,p. 114) posit that in collectivist cultures, relationships between service providers and their customers are “stronger, more intimate, and (thus) more loyal” than such relationships in individualist cultures. Inherent to individualist cultures is the notion of self-responsibility: From a services perspective, this implies that, compared with collectivist customers, individualist customers are apt to be less tolerant of service delays and failures (Furrer, Liu, and Sudharshan 2000). According to this perspective, the United States and Canada are highly individualist cultures, whereas Japan is relatively collectivist (Hofstede 1980).
Uncertainty avoidance “indicates the extent to which a society feels threatened by uncertain and ambiguous situations” (Hofstede 1980, p. 45). Cultures that score high on uncertainty avoidance attempt to minimize the possibility of such situations by adhering to strict laws and measures. Furrer, Liu, and Sudharshan (2000,p. 360) conjecture that, particularly in cultures of high uncertainty avoidance, there is an important distinction between frequent (e.g., supermarket) and infrequent (e.g., dental clinic) service contexts: In the latter, “uncertainty and ambiguity from the unknown situation has to be reduced by a close relationship with the service provider.” Although Japan scores high on the uncertainty avoidance index, both the United States and Canada are quite tolerant of uncertainty. The continuum of masculinity/ femininity expresses “the extent to which the dominant values in society are ‘masculine’–that is, assertiveness, the acquisition of money and things, and not caring for others, the quality of life, or people” (Hofstede 1980, p. 46). In general, masculine societies are aggressive and competitive; feminine societies tend to be more modest and nurturing. More than any other culture surveyed, Japan is the most masculine; Canada and, to a lesser extent, the United States fall toward the midpoint on the continuum. Power distance “indicates the extent to which a society accepts the fact that power in institutions and organizations is distributed unequally” (Hofstede 1980, p. 45). It is along this cultural dimension only that the three countries exhibit convergence; all three national cultures have relatively low power distance. The final dimension, long-term orientation, distinguishes sharply between Japan and the two North American countries. Japan is characterized as long-term (future) oriented, whereas the United States and Canada are characterized as relatively short-term (present and past) oriented. Cultures that have a long-term orientation expect long-term and close relationships with service providers; aspects of service quality that are likely to be important in such cultures include reliability, responsiveness, and empathy (Furrer, Liu, and Sudharshan 2000). Donthu and Yoo (1998) and Furrer, Liu, and Sudharshan have found support for this notion.
Why measure customer satisfaction?
In the ‘new economy’ (Arthur, 1996; Drucker, 1993; Schneider, 1996) knowledge is a resource as well as, increasingly, a product: with tangible goods becoming globally standardized and best practices travelling fast, companies gain competitive advantages through constant innovation, better targeting of customers and additional services. Those strategies cannot be applied to the arm’s length type of customer relations. The higher the innovative and service component, the more the customer becomes part of the performance equation. Customer relations then constitute an important asset that should be monitored just like physical assets. Most emerging approaches to the measurement of intellectual capital agree on the importance of customer capital, as expressed in sales, satisfaction and reputation (Edvinsson & Malone, 1997; Kaplan & Norton, 1996; Schneider, 1996; Sveiby, 1997). Accordingly, those approaches distinguish between reference customers (reputation), new customers or first trial customers (new sales) and repeated customers (satisfaction, sales). Independently of approaches to the measurement of intellectual capital, marketing literature has suggested a wide array of industry-specific models to monitor customer satisfaction (for an overview see Bearden et al., 1996, also Hayes, 1992).
We can therefore conclude that management and marketing theorists as well as practitioners agree on the importance of customer relations for a business’s success. In order for that vision not to remain pure rhetoric, it is important to put into operation the concept of customer relations so that it can be monitored and managed. Most pundits would agree on that. But that is where unanimity stops. When confronted with the task to define the vision of ‘understanding customer relations’, management theorists will supply different answers depending on contradicting predispositions of different paradigms.
Different epistemological approaches and their consequences on measuring customer relations
We shall now discuss two management concepts and argue that measurement is more important to one of them. We shall keep our discussion short as this is not the context to discuss deeply different ways of knowing. Classical management theory is grounded in the hypothesis of rational decision-making. It is assumed that decision-making improves with the quantity of information available to a decision-maker. Decision-makers are supposed to use their own and third party knowledge according to purpose, without preferences. It is equally assumed that decision-makers can learn from surrogates, that is, acquire the qualifying context together with codified data. Based on those assumptions, management theory advises managers to accumulate data, to extend human information processing capacity by hardware and software and to mine data and texts available from operating procedures for hidden patterns that could improve future decision-making. Classical theory-based approaches hold if there are linear causal relationships that can be generalized for different contexts, that is, if people behave in a predictable manner that is stable over time. Behaviour need not be deterministic, as long as we can find a distribution that delivers good approximations, such as normal distribution that is assumed in many data mining procedures.
If, on the other hand, we let go of some assumptions of classical theory, as they seem unrealistic, we have to deal with causal loops (interdependencies), microdiversity that is not necessarily normally distributed, with path dependency and partial irreversibility of processes. CAS (Complex Adaptive Systems) theory accounts for those premises and can, in addition, allow for behavioural specificities, such as worse decision-making with increasing knowledge, subjective preferences for sources and presentational forms of information, conscious and unconscious manipulation of data, and others. Partial path dependency (current decisions of a consumer are influenced but not determined by his/her experiences with past decisions) and partial irreversibility (money spent on one item cannot be spent on another) contribute to non-average outcome (Wollin, 1999). Non-average outcomes are no problem to statisticians as long as they do not affect macrostability, that is, the behaviour of an overall system in observation. This is the case if they smooth each other out and follow a predictable pattern. To assume smoothing out and predictability is not, however, suitable if numbers are small (such as with few dominant customers, quite common in business-to-business relations), if elements of an entity are isolated or only loosely coupled in terms of space, time or common domains (such as for culturally different customers or groups that are not exposed to the Internet and television), if there is irreversibility (such as in buying products that require learning and would lead to sunk costs, if abandoned) and if we account for purposeful breaking of patterns as acts of innovation (cf. Wollin, 1999). In the latter cases seemingly random aberrations in a system (such as street kids wearing rugs) can become triggers around which new patterns emerge (in the example above, wearing rug-type cloths could turn into fashion).
Even if we maintain the rather narrow assumptions of classical theory we run into some problems of empirical research in social sciences that are as well known, and constantly ignored. Those are representations on the one hand (are customers ready to be interviewed on the phone a valid or biased selection of all customers in question?) and measurement procedures as well as interpretation of results on the other: Which indicators do we use, how stable are those indicators over time and with regard to measurement intervention and how do they interrelate? How can we observe without bias in a world of unlimited stimuli? Does it make sense to generalize all customers for all categories of products and services under all types of situational conditions. Of course, those questions are not new. We do not claim that they are. What is amazing, however, is that they are not taken seriously. In economics we usually argue as follows. Let us assume my grandma has four tyres. She can thus be defined to be a bus. As she is defined to be a bus, she will run on petrol. Therefore let us feed her petrol. This metaphor of course exaggerates, usually we do not die from conclusions drawn from economic theory. Still, we would like to see more discussions of the question what value of information we can gain from measurement. Usually this question is treated as technical. The expectation is that humankind will develop ever better methods to deal with them. But, what if they were undecidable in principle and what if we did harm in the meantime, like to poor grandma in the metaphor? Then, the ultimate argument, supplied by traditional science, that although what we have is Unsatisfactory, we do not have an alternative would not be very valid anymore.
All our studies are necessarily burdened with severe caveats as to the samples (access to data), reductions and isolations included in the method. The original authors diligently dedicate a section of their papers to those caveats but they seem to be lost in the process of diffusion of knowledge within the scientific community and, even more so, in the practical field. Feeble hypotheses thus gain the force of powerful truths and are acted upon. This may even produce empirical evidence–in the form of self-fulfilling prophecies. To conclude, it is not so much the theoretical weaknesses of our models that measure ‘reality’ that constitute the problem, but rather our tendency to forget those weaknesses and treat results as true images of reality.
From a practical point of view the collection of ever more data produces the following problems:
· Human beings, as the sources of many of those data (especially on attitudes, opinions, future plans) will become increasingly unwilling to bear the transaction costs of providing them. Customers have started to feed back that they feel molested by questionnaires (especially as they only get standardized reactions to very idiosyncratic responses). Some companies have made it a policy no longer to react to the myriads of questionnaires received from PhD students. From a game theory perspective, free riding on the information produced by surveys is the alternative with the highest payoff, while co-operation does not produce an easy-to-quantify benefit, if any at all.
· The more sophisticated the procedures to collect and process data, the higher the danger that data collecting and processing become ends to themselves. This constitutes ‘controlling-bias’ (Schneider, 1998).
We can conclude this paragraph by stating that measuring customer satisfaction inserts itself into the classical paradigm of management and is exposed–even within this simplifying paradigm–to a number of difficulties. As this issue is about the measurement of customer satisfaction, we will concentrate on measurement in the following section. But a warning seems appropriate that the whole measurement endeavour, which has become so popular under the headline of intellectual capital, might end up like the efforts to measure organizational concepts in contingency theory. After millions had been spent, researchers came home not with the Holy Grail but with a broken teapot (Kieser-Kubicek, 1992, p. 4).
We therefore formulate the following cautious proposition: paradigm shifts in management theory have led us to account for system thinking and more realistic assumptions on behaviour. Although idiosyncrasies are probably exaggerated in societies that develop common and habitual patterns of expectations through a number of media (cf. Luhmann, 1996), we have to distinguish systems with average outcomes from systems with non-average outcomes. While we can apply measuring according to standardized statistical procedures to the former, they are meaningless to the latter. Table 1 contrasts two basic epistemological paradigms in a black-and-white manner to enlighten their differences and implications for research.
What do we measure?
Roughly spoken, the chain of argument in management theory is the following. Finding out about customer preferences will allow one to provide customized products and superior service to current customers which will entail further sales as well as a boost in image so that new customers can be gained. Customer feedback helps continuously to improve performance. In particular, it can inspire employees to increase their efforts (Fig. 4).
A corresponding research design will usually contain three major constructs, namely service quality as expressed by several indicators, customer satisfaction, another construct that can only be measured by using indicators and a third construct, namely success, again to be defined by indicators. On all three categories of indicators there is no general consensus but rather competing ideas, resulting in competing theories and consultancy products.
Depending on the product and channel of distribution, several models have been developed for the constructs of product and satisfaction. Characteristics and prices of products, speed of delivery, friendliness and competence of personnel involved, and time of recovery are indicators used frequently for the first construct, while satisfaction is measured in emotional/attitudinal dimensions (such as feeling esteem) and in action-oriented dimensions (such as readiness to repurchase; see Bearden et al., 1996). New technologies make it a lot easier for all parties involved to do research on a continuous basis. “Driving the customer focus is a new breed of technology, including database tools that let companies gather information about their customers like never before, sales force applications that let them deliver service and Web technologies that let them establish more personalized relationships with customers …” (Information Week, compiled by Creemers, 1999). But new technologies do not eliminate the critical aspects of the basic research design. We are insecure about the relationship between constructs: Satisfaction, for instance, may not always lead to returns. In turn, returns do not automatically mean success (some customers simply are not profitable as better costing would show; see Information Week, compiled by Creemers, 1999). Moreover, we are insecure about the relationship between indicators and constructs. Figure 2 shows a general research design.
Thirdly, we cannot fully control the situation in which a survey takes place. To take verbal reactions as a proxy for the attitudes and (planned) actions of respondents may be wrong, as polls before elections have shown. Therefore, despite all the effort invested in valid testing instruments construct validity will remain an unsolved issue. Without entering into detail we could sum up that in order to obtain higher construct validity, frequent and very sophisticated testing is needed. To maintain a positive relationship of costs and benefits while measuring intangibles, on the other hand, asks for simple procedures. This refers us to the second part of our paper: Will measuring intangibles pay off?
The model presented above could be amplified by an additional construct relating employee satisfaction to product/service quality, as has been suggested by various sources. As said before, there is a trade-off between different research criteria: the more factors we include, the less tractable the model becomes, especially if we account for polynomic functions, or even ‘worse’ for exponential functions. Translated back into a marketing context the model works best if customers, or groups of target customers, behave in a similar manner. This can be assumed if they are either influenced by the same type of cultural formation as well as commercial advertising and/or if they depend on their mutual behaviour. Both assumptions were plausible in a mass production society; the latter continues to be so as best purchasing practices are diffused by literature, conferences and consultants. On the other hand, the Internet provides business as well as end-customers with opportunities to innovate, so that small numbers and sudden shifts in behaviour cannot be excluded.
Which model should we underlie our idea of monitoring intangible assets under the considerations given above? This depends on the advice required for future action. If, for instance, the Swiss in general and on average are 97% satisfied with their medical treatment (cf. Bruhn & Grund, 1999), this can mean different things: those reached on the phone and ready to devote time, who may be biased toward the more harmony-seeking part of a population, either claim to be satisfied vis-a-vis a research authority or are really satisfied. Can we know for sure that Swiss doctors are better than US doctors where the average satisfaction rate is much lower? Maybe. But, we could also find an explanation referring to the different organization of healthcare in both countries or in relation to a more indirect culture in Switzerland that would not express discontent right away (cf. Hall & Hall, 1990). As we see, the advice that can be gained from such expensive endeavours as national customer satisfaction indices is not very specific. As long as different groups can be held responsible there is not much hope for consequential action and if there is no consequential action, what should the effort be good for? On the other hand, let us assume people are asked more specifically and reveal they are not wholly satisfied with their encounters with doctors. We would then still not know whether this was due to a perceived lack in competence, to waiting time or not enough time devoted or to the doctor not giving any explanations. The more detailed the study would be, the more probable that it really delivers information but also that only a biased minority will be ready to answer a phone interview and that the whole study will become more cost-intensive. We would concede that, in principle, a national index may trigger action by the legislator, by professional federations, by the educational system, by doctors themselves or by patients seeking treatment elsewhere. But given the pluri-responsibility, the biased and vague type of information and insecurity as to the quality of higher scores in other countries, this is highly improbable. Feedback on customer satisfaction, as we see it, makes more sense at an industry or company level. At an overall level it raises some serious questions with regard to costs, liability and general accessibility, which will be discussed later.
Criteria for measurement in a business context
i. Efficiency and manageability
In a business–as compared to a pure research context–efficiency becomes an important criterion beyond validity, reliability and objectivity. As a general rule, measurement makes sense as long as its cost are outweighed by the benefits generated by the ‘information added’ through the gathering and processing of data. The problem is, companies can hardly determine the costs of measurement and, even less so, its benefits. In general, better information should lead to better decisions, and thus to better success. Apart from decisions not always been implemented as planned, behavioural theory shows us that there is no linear relationship between the quantity of information and the quality of decision-making (Dorner, 1989; Schneider, 1990)
Furthermore, due to the information paradox, companies must bear the costs to develop a measurement system before they can evaluate its benefits. They can alleviate the paradox by letting competitors be the pioneers and then imitate them (benchmarking). But this would mean to lag behind. Despite there being no precise answer to the requirement of efficiency, we can nevertheless formulate some heuristics: the measurement of intangibles should be organized in a way that ‘minimizes’ its costs and ‘maximizes’ its use.
To minimize costs, simple and standardized procedures are recommended. They should mainly rely on data gathered for other purposes (synergy). The latter should be gathered and documented as a by-product of operations so that no additional staff are needed. To maximize use, however, requires other recommendations. Management must ensure that information reaches the ‘right’ decision-makers in the ‘right’ time, is interpreted ‘correctly’ and translated into action. This is usually not considered an issue of measurement, but of the further use of measures taken.
If we bear the context of use in mind while designing new instruments to measure intangibles, we must consider some empirical evidence that refers to behaviours other than purely ‘rational’ in the context of business organizations.
ii. Organizational context
Following the broader discourse on measuring not only customer satisfaction but also other intangibles, we assume in this paragraph that measures are generated internally and provided for reasons of internal rather than external reporting. We shall discuss some possibly harmful implications of the simple fact that measures are compiled by those to be measured (although it will not be the same persons within an organization who do and control). Observations of how (top) managers decide supply a very strong argument for translating narratives into financial codes. It is Peter Drucker’s observation that managers only understand the language of numbers: what is not measured will consequently not be managed (Drucker, 1993, p. 44).
On the other hand, Brown has found that managers cannot digest more than a few chunks of quantitative information. Five to seven codes that should be defined clearly and simply are acceptable, more sophisticated measures will be rejected (Brown, 1997, pp. 15-20).
Organizational behaviour literature supplies the following observation. Companies do not establish departments and divisions because they grow, but grow in numbers of people employed because they establish departments and divisions. As mentioned before, a new function, ‘controlling of intangibles’, would elicit its specialists to prove their indispensability and importance, probably by developing ever more sophisticated measurement systems. Owing to the results mentioned above, those reports would be widely ignored and therefore wasteful (Schreyogg, 1996, p. 180).
A fourth category of studies we should consider here is related to the coupling of single measures with appraisal systems and incentive schemes. Although it seems quite reasonable at first sight, the use of codes as ‘carrots’ implies some dangers: appraisees will tend to manipulate the measurements (as to the timing of measurement or the exposure of the behaviour in question only at the moment of measurement). Alternatively, they will tend to focus on the code ‘to the letter’ and thus possibly counteract its substantial meaning or its interaction with other criteria which are difficult to put into operation. We could talk here of the tendency of the quantifiably suppressing quality. Measures used within appraisal and incentive systems are submitted to the same contradictory requirements as measures for intangibles in general: to be valid they should be differentiated, sophisticated and only used as a set of interdependent factors; to be manageable, however, they must be ‘simple and stupid’.
Another dialogue within the emerging community of people interested in measuring intangibles centres around the issue of standardized versus customized instruments. Standardized measures seem suited for external reporting. They allow for comparability. They can be developed by public or private experts and acquired either as a public good or at much lower costs than customized instruments.
Reliability and objectivity can be more easily guaranteed. Standardized measures produce the portability of all knowledge related to their use as an externality. But standards could also be defined as the minimal common denominator, as the outcome of compromise. They might be defined too vaguely to inspire action or be too formalized to be more than an exercise in documentation and an argument to be used in marketing.
Standardized measures may entail the danger of form overruling content, certification of a quality becoming more important than its generation. The criticism of the ISO certification procedure as a bureaucratic, backward-oriented, innovation-preventing routine points to this danger and should be kept in mind if we talk about a European Customer Satisfaction Index.
Customized instruments, on the other hand, could be designed in a way that reflects special aspects of a business (its strategic uniqueness) and thus be more valid than standardized measures. They could thus inspire bench-breaking rather than benchmarking, innovation rather than collusion. Their disadvantages are that development costs must be internalized, that they are less appropriate for external reporting and possibly more open to self-delusion.
To capture the advantages of both procedures we will probably have to develop measures that are standardized for special groups (defined by industry, size, stage within industry cycle, etc.).
A third dialogue focuses on the question of financial versus non-financial measures. Non-financial measures can be qualitative indicators (so-called ‘soft facts’) which are believed to translate into financial measures in future periods. A narrow focus on financial measures has been criticized as being backward-oriented, to miss tracing key success factors and supporting unhealthy short-term orientation (Edvinsson & Malone, 1997, 8ff). To express intangibles by non-financial measures is thus regarded as a necessary counterweight against ‘bean-counters’ with a lack in entrepreneurial attitudes.
This argument has its merits. Without qualitative measures of human skills or customer relations their long-term building might always fall short of the expectation of immediate financial returns. On the other hand, there is no reason to ‘maximize’ R&D expenditure, training hours or customer contact and satisfaction per se if they do not result in higher earnings (cash flows) or higher company value. At the end of the day, qualitative measures need to be correlated with financial results, while time lags between cause and effects should be accounted for.
To conclude, we can state requirements for the measurement of intangibles in general, and customer satisfaction in particular. Table 6 summarizes our argument.
We can state that research and business-context criteria are partially contradictory and require trade-offs. Efficiency may counteract validity as well as reliability, manageability may require concessions as to representability, motivation for action may ask for inappropriate generalizations or exaggerations of measures. Trade-offs must be guided by the purpose of measurement, which can only be decided by an organization’s strategists (Table 7).
iii. Cost, liability, accessibility
Many projects in the realm of measuring intangibles are shared endeavours between the practical field and research institutions (cf. OECD, 1999, Technical Meeting, June): public money is provided to kick-off the basic idea of developing new measures and to learn about the viability of tools. Does this constitute a necessary contribution to fundamental research or a market-distorting subsidy? What about liability for information? In most cases it is impossible to establish a clear causal link between a certain piece of information and harm done to its recipients. Therefore, we do not have liability legislation for research results (imagine a world in which researchers were as liable as plumbers or pharmacists), but liability would become an issue if information was sold by private providers. It is also an issue for boards in relation to their investors. This constitutes one of the reasons for their reluctance to accept mandatory external reporting on insecure intangibles. Knowledge is an enabling not an enforcing factor. Owing to its more or less tacit components it is open to interpretation that makes its regulation difficult. Still, we will need some rules to prevent us from fraud and insider trading. Accessibility of information is closely linked to the question of who bears the cost to generate it. If funding is public, we should rather assume that a public good has been produced. Information, as a common good, does not usually constitute competitive advantage. Furthermore, evaluation procedures within bureaucratic and scientific communities are generally inappropriate to deal with cost-efficiency. Therefore, the idea of establishing markets to allocate costs and benefits of information generation is appealing. Companies, groups of companies, could arrange and pay for external measurement or internalize the endeavour. They will do so if they perceive higher benefit than costs. But, as said before, costs and benefits are insecure, spread over time and influenced by the fact, that ‘ceteris is never paribus’ in real-life management. This adds up to the trivial observation that whoever develops measurement tools will and can only do so if there is a consensual belief that tools will pay off, if not now than in the future when all current problems will be solved: Do we capture the right information rightly, is this information used properly? Again, we are confronted with a question of quasi-religious nature which cannot be decided scientifically.
iv. A whole variety of research methods
We have used surveys as a blueprint for our critical discussion of measurement methods because they are most common in customer satisfaction research (cf. Bearden et al., 1996). Meanwhile, we are well aware that various techniques have been developed to render verbal reactions to eliciting questions more valid: the critical incident technique and various checks to elicit (in) consistent answers to similar questions can detect obvious lies but not a person’s cultural and social ‘distortions’, or his or her self-deception. Interviews over the phone, as used for national customer satisfaction indices, will even miss non-verbal clues and need to be restricted to unambiguous simple statements. Those statements deliver information that is not very valid economically because it is too general to create much value. Our main argument against aggregate information from questionnaire-type instruments stems, though, from its underlying assumptions of macrostability and average outcomes. It could well be that the ‘post X’, net-oriented generation produces non-average outcomes more often than not. It has also been said that this generation neither takes the burden to argue nor to develop opinions (OE1, 18 August 1999, results of youth study, cf. Sennett, 1998). They will vote with their feet, or keyboards, rather then get involved. Furthermore, any kind of interview constitutes unavoidably an intervention into an ongoing relationship. We understand the price of any non-standardized good, such as a service, to be an expression of an ongoing relationship rather then a fixed datum. To ask for a customer’s satisfaction and preferences changes this relationship and could well be used to direct his/her attention towards those dimensions a company (or an industry) is good at. Measurement changes its function completely if understood as a marketing, i.e. communication, tool. All the shortcomings discussed above will weigh much less then, as we do not measure any existing reality but a reality that is co-created by our endeavour.
Validity of measures: A knowledge perspective
If we want to discuss validity in a broader epistemological context we can refer to Polanyi’s concept of tacit knowledge (Polanyi, 1967) or Boisot’s distinction between codified and unmodified knowledge (Boisot, 1984).
Tacit knowledge (or implicit knowledge in the notation by Nonaka & Takeuchi, 1995) is not the opposite of explicit knowledge as many knowledge management theorists wrongly perceive (Davenport & Prusak, 1998; Edvinsson & Malone, 1997; Schmitz & Zucker, 1996), but its qualifying context; so to say the hidden part of the iceberg. To make explicit means to divest the tip of the iceberg of its foot for the sake of economizing the process of diffusion of knowledge. Explicit knowledge can be passed on as a structure of ‘essentials’, but without its qualifying context. The ultimate explicit form is codification. To understand the difference, let us consider a face-to-face situation of a salesperson and a customer. This situation is completely uncodified. It contains the complexity and richness of all the clues present in the environment and the person of the customer. Most certainly the salesperson will not be able to deal with this complexity, and miss many of the clues. If he/she is given a form to capture part of those clues, which are then codified, his/her colleagues will receive quite a different type of information. Customer X might be described as ‘1-3-2-3’, where 1 stands for female, 3 for age group over 50, 2 for first time customer and 3 for her overall ranking of satisfaction on a five-point Likert scale.
We can see quite clearly that recipients of such codes can hardly reconstitute the complexity and information-richness of the original situation of measurement. Codes do not function like holograms. They are valid only if recipients/users have a shared understanding (pointing to a degree of homogeneity which is harmful to innovation of any business) and if they apply to a context that is very similar to their original context. This, of course, is a general problem of modern society. We trade off richness of information against its diffusability and work on the grounds of the assumption that the basic structure, transported by the code, is sufficient for any further use of the knowledge in question.
As mentioned earlier, from the perspective of interpretative theories and complex-adaptive theory this assumption is questionable. This is no argument against measurement, but it is an argument against confusing the map with the territory and against allocating the majority of attention, actions taken and financial means to the restricted information we can gain from such measurement.
What could be done?
Firstly, we should see that the procedure of measurement in the case of customer satisfaction is no neutral act, but an intervention. Whenever we design a method to learn about customer relations, we should do it with the alterations in mind that we would like to happen. We thus do not just want to know how we performed in the past, we want to create the future. As we cannot not influence our customers,while we survey them, we should rather influence them according to our vision and business strategy.
Secondly, we should never forget the core task to create intangibles over the effort to control them. If educational reform leads to teachers being distracted from their core task, namely to inspire young people to learn, by the need to document and legitimate each step they take (as is perceived by teachers in the UK), the quality of the core task may even deteriorate. Managing customer relations must therefore first and foremost mean to design and cherish those relations, not just to measure and document them.
Thirdly, we should be prudent and use our measures as sticks and carrots in incentive systems designed according to a simplistic stimulus-response-based theory of behaviour. If we consider all the caveats that are especially related to validity, we cannot take responsibility for such use. However, measures can be useful yardsticks within learning processes.
Finally, we should keep in mind that the starting point of all statistical procedures is the endless repetition of the same event. In a simultaneous setting this endless repetition must be substituted by the sameness of behaviour of a large number of elements. In order to make those methods applicable, we need standardization and homogenization. This seems to be quite the opposite of what is recommended to businesses and individuals in a new economy?
The service paradox
Before dwelling on the literature on service quality, a terse elucidation on the necessity and rationale for the separate handling of services would not be out of place here.
Both the organizational behaviour literature and the marketing literature have recognized the differences in organizational dynamics that exist between the management of services and goods (Schneider & Bowen, 1985). In the organizational behaviour literature as explained by Schneider and Bowen (1985), the accent has been on streamlining organizations for the delivery of the prototypical service that varied from the prototypical good in many different ways. On the other hand, understanding how these defining features of services may warrant diverse strategies for marketing services has been the dominant interest of the marketing people.
Thus, the need and the logic for an independent treatment of services marketing centre on the subsistence of diverse attributes of services which are repeatedly cited in the literature: intangibility, inseparability of production and consumption, heterogeneity and perishability (Zeithaml et al., 1985). An analysis of these attributes is presented one by one.
Services are intangible when compared to physical goods (Levitt, 1981). Bateson (1977) explained that there are two distinct characteristics of services, viz. ‘palpable’ intangibility, i.e. they cannot be touched; and ‘mental’ intangibility, i.e. it is hard to anticipate exactly the outcome of a particular service. Bateson (1979) argued that intangibility is the precise goods-services differentiation on which all other differences are based. Products are tangible objects that exist in both time and space, while services consist of social acts or interactions and exist in time only (Berry, 1980). Inseparability of production and consumption stems from the concurrent creation and consumption that delineates the majority of services (Carmen & Langeard, 1980; Gronroos, 1978; Zeithaml et al., 1985). Goods are first produced, inventoried, sold, then consumed; services are usually sold first, then produced and consumed simultaneously because they cannot be inventoried (Berry, 1980; Maister, 1982). Variability of service expectations is the hallmark of all services, especially those with a very high labour content (Parasuraman et al., 1985). The characteristic and the sum and substance of a service (e.g. medical examination, car rental and restaurant service) can vary from producer to producer, from customer to customer and from day to day (Zeithaml et al., 1985). Services are perishable, i.e. they cannot be saved and used later in times of need or emergency (Bessom & Jackson, 1975; Thomas, 1978). As services are performances that cannot be inventoried, service organizations are frequently in trouble in terms of matching supply and demand (Zeithaml et al., 1985). Most services actually consist of acts and interactions, which are typically social events. The control and management of social events calls for certain special skills and techniques (Stebbing, 1993). Mills and Moberg (1982) highlighted that in service transactions, the raw material to be converted to service output depends, to a great extent, on the facts and information furnished by the customer. Also, clients play a crucial role in influencing the outcome of the transformation process as well.
Bowen and Schneider (1988) summarized that, fundamentally, services vary on a continua not only from goods but also from each other. Although the different models offered by various researchers differ in the weights they assign to the several discriminating features of services such as intangibility, simultaneity of production and consumption, variability of service expectations, perishability and participatory role of consumers, they all converge to one issue, i.e. if the prototypical service differs from the prototypical good, then the systems by which these goods and services are produced and marketed will also vary.
The background literature on service quality
The credit for heralding the service quality research goes to Parasuraman, Zeithaml and Berry (see Parasuraman et al., 1985, 1988; Zeithaml et al., 1985, 1990). The authors, based on qualitative research, formulated a measure of service quality derived from data on a number of services, instead of counting on earlier dimensions of goods quality in the manufacturing sector. The initial results, based on some focus group findings, yielded 10 dimensions of service quality that included tangibles, reliability, responsiveness, competence, courtesy, credibility, security, access, communication and understanding the customer. Further empirical scrutiny (Parasuraman et al., 1988) resulted in a 22-item scale, called ‘SERVQUAL’, which measures service quality based on five dimensions, viz. tangibles, reliability, responsiveness, assurance and empathy. The entire approach was formulated on the tenet that customers entertain expectations of performances on the service dimensions, observe performance and later form performance perceptions. The authors defined service quality as the degree of discrepancy between customers’ normative expectations for the service and their perceptions of the service performance. Rust and Oliver (1994) noted that the SERVQUAL instrument captured the crux of what service quality might mean, i.e. a comparison to excellence in service by the customer.
In their empirical work, Cronin and Taylor (1992) controverted the framework of Parasuraman et al. (1988) with respect to conceptualization and measurement of service quality, and propounded a performance-based measure of service quality called ‘SERVPERF’ by illustrating that service quality is a form of consumer attitude. They argued that the performance-based measure was an enhanced means of measuring the service quality construct.
In another empirical work, Teas (1993) investigated conceptual and operational issues associated with a ‘perceptions-minus-expectations (P-E)’ service quality model. The author developed alternative models of perceived service quality based on evaluated performance (EP) and normated quality (NQ). It was concluded that the EP model could overcome some of the problems associated with the P-E gap conceptualization of service quality.
Parasuraman et al. (1994a) responded to the concerns of Cronin and Taylor (1992) and Teas (1993) by demonstrating that the validity and alleged severity of many of those concerns were questionable. Parasuraman et al. (1994a) elaborated that though their approach for conceptualizing service quality could and should be revised, relinquishing it altogether in preference of the alternate approaches proclaimed by Cronin and Taylor and Teas did not seem warranted. This triggered an interesting controversy in service quality research.
In another empirical work, Parasuraman et al. (1994b) revamped SERVQUAL’s structure to embody not only the discordance between perceived service and desired service (labelled as measure of service superiority, or MSS), but also the discrepancy between perceived service and adequate service (labelled as measure of service adequacy, or MSA).
Several other works have also criticized the operationalization, conceptualization, measurement and applications of SERVQUAL across different industrial settings (for a detailed discussion, see Buttle, 1996).
The critical dimensions of service quality
From the foregoing discussions, it is palpable that the SERVQUAL instrument has in fact generated bounteous interest in service quality measurement. Antithetically, critics of SERVQUAL have also disputed the logic and requirement behind the measurement of expectations (Cronin & Taylor, 1992, 1994), the decipherment and operationalization of expectations (Teas, 1993, 1994), the reliability and validity of SERVQUAL’s difference-score formulation (Babakus & Boller, 1992; Brown et al., 1993) and SERVQUAL’s dimensionality across various service scenes (Carman, 1990; Finn & Lamb, 1991).
The point worth debating here is that the comprehensiveness of the 22-item scale proposed by Parasuraman et al. (1988) in addressing the critical dimensions of service quality is in question, for the simple reason that a careful examination of the scale items divulges that the items at large focus on the human aspects of service delivery and the remaining on the tangibles of service (like the effect of atmospherics, design and decor elements, appearance of equipment, employee dress, etc.).
The notability of the element of human interaction/intervention in the service delivery has been, without an iota of scepticism, acclaimed and reiterated by various other researchers as well (e.g. Harber et al., 1993a, b; Mills & Morris, 1986; Norman, 1991; Schneider & Bowen, 1985, 1992, 1993, 1995; Schneider et al., 1994, 1996a, b; Stebbing, 1993). Of the five SERVQUAL dimensions, four, namely, reliability, responsiveness, assurance and empathy, relate to this aspect.
The fifth one, i.e. the tangibles, pertains to the effect of physical facility, equipment, personnel and communication materials on customers. The effect of this atmospherics, popularly known as ‘servicescapes’ (Bitner, 1992), does affect customers in myriad manners. Bitner (1992) elucidated how these servicescapes influence both employees and customers in physiological, psychological, sociological, cognitive and emotional ways. Various authors have also dealt with in detail the impact of these tangibles on the service perceptions by customers and their effect on employees (Baker et al., 1988; Berry & Clark, 1986; Sundstrom & Altman, 1989; Upah & Fulton, 1985; Zeithaml et al., 1985). But, while accentuating the significance and germaneness of these two momentous dimensions, one should also admit as apodictic that the highly subjective concept of service quality not only confines to the realms of these elements, but also encompasses other critical factors, such as:
(1) The service product or the core service.
(2) Systematization/standardization of service delivery (the non-human element). (3) The social responsibility of the service organization.
A discussion on each of these factors along with the justification of the choice of these elements are adduced next.
The service product or core service
The core service portrays the ‘CONTENT’ of a service. What is delivered is as substantial as how it is delivered. Schneider and Bowen (1995) clarified that many a time managers become so involved with all the procedures, processes and contexts for service, that they tend to overlook that there is also something called the ‘core service’. Rust and Oliver (1994) defined that the service product is whatever service ‘features’ are offered. Schneider and Bowen (1995) also argued that fancy facilities, modern equipment, stylish uniforms and terrific signs can never countervail for bad/mediocre food, poor financial advice, an inappropriate will, or lousy music. Hauser and Clausing (1988) also demonstrated the influence of diverse product (or service) attributes on customers’ perceptions.
To quote an example, a bank’s loan disbursal service with an associated credit terms and repayment modalities is a service product. The features that make up any service execute a powerful influence on the quality perceptions of customers. No matter how affable, amiable and courteous a bank’s personnel are to the customers, if the bank fails to offer a broad range of services/or more features in every service it provides, the customer may not attach a very high value to the quality of service it offers. Even if a doctor is on time and sympathetic and understanding to his patients, the patients may not perceive his service quality as high if the doctor lacks competence in diagnosing the diseases or administering the drugs. Even though the passengers on an aeroplane are treated well by the aircrew and the hostesses, people would feel hesitant and frightened to travel on the airline if they perceived that the flight provided by it was unsafe.
To put everything in a nutshell, the core service itself has discernible, tangible and multidimensional quality features that could discriminate services and could preponderate over other issues such as delivery. The quality of this core service largely influences and sometimes may be the ultimate determinant of the overall service quality from the viewpoint of the customers (Schneider & Bowen, 1995).
Systematization of service delivery (non-human element)
The service delivery represents the ‘HOW’ of a service. It has two distinct and disparate features:
(1) Human element of service delivery, which has been effectively addressed by the SERVQUAL.
(2) The processes, procedures, systems and technology that would make a service a seamlessness one.
The second aspect is as crucial as the first one. Customers would always like and expect the service delivery processes to be perfectly standardized, streamlined and simplified so that they could receive the service without any hassles, hiccups or undesired/inordinate questioning by the service providers. Zemke and Schaaf (1990) quoted a study of 1500 consumers by Cambridge Reports, a Massachusetts-based research firm, which found that 44% of the respondents indicated that ‘ease of doing business with’ was the fundamental reason for choosing a financial firm.
Milakovich (1995) noted that process improvement has become the prime focus of the service quality revolution, as he observed that the key to total quality service (TQS) depends on understanding the process, as a mechanism to transmute knowledge and respond to customers faster than the competitors. Ahire et al. (1995) explained that the overall quality of the products or services could be made better by improving the quality of the processes either directly or indirectly. Spenley (1994) posited that the basic business processes go a long way to substantiating the quality of an organization’s products or services. Enhancement of technological capability (e.g. computerization, networking of operations, etc.) plays a crucial role in establishing the seamlessness in service delivery.
In addition to abetting as a potential market signal, social responsibility helps an organization to lead as a corporate citizen in encouraging ethical behaviour in everything it does. This critical factor has seldom found a place in the quality management literature, even though it does come into picture in the Malcolm Baldrige National Quality Award Criteria (Malcolm Baldrige National Quality Award Guidelines, 1998) under the heading ‘Company responsibility and citizenship’. A study conducted by ‘Consumer Reports’ on customers of non-banking financials (Zemke & Schaaf, 1990) found that one of the predominant consumer concern on service quality was: “Equal treatment tempered by pragmatism, stemming from the belief that everyone, big or small, should be treated the same”. They were also concerned about getting good service at a reasonable price, but not at the expense of quality.
The point which merits articulating here is that an organization cannot count only on financial performance to survive in this ever-changing scenario of global competition, but also has a responsibility to the society in which it exists. Albeit this feature sounds highly abstract and intangible, it does contribute to the formation of the quality perceptions by customers. For example, a hospital that gives free treatment to the economically downtrodden, an educational institution that grants scholarships for the poor, or a financial institution that provides loans to needy ones with less rigid loan conditions, would certainly be adored and appreciated by the customers. These subtle, but nevertheless forceful, elements send strong signals towards improving the organization’s image and goodwill and consequently influencing the customers’ overall evaluation of service quality and their loyalty to the organization.
In essence, it is postulated that service quality is based essentially on five dimensions (see Fig. 1.), namely:
(1) Core service or service product.
(2) Human element of service delivery.
(3) Systematization of service delivery–non-human element.
(4) Tangibles of service (servicescapes).
(5) Social responsibility.
Chapter Three: Research Hypotheses
This research tests the following propositions:
1. The higher the customers’ perception of service quality, the higher the level of customer satisfaction.
2. The higher the conformity between the service quality and external communications, the higher the level of customer satisfaction.
3. The level of customers’ satisfaction or dissatisfaction is differentiable by variables of:
a) Customers’ perception of service quality,
e) Conformity between service quality and external communications.
4. a) Variable of situation (on-time departure) is the variable to differentiate the level of satisfaction or dissatisfaction of customers in the business segment.
b) Variable of price (discounts) is the variable differentiating the level of satisfaction or dissatisfaction of customers from the segments of tourism and family visits.
5. The higher the management commitment and level of employee’s job satisfaction, the higher the customers’ perception of service quality, and the higher the level of customer satisfaction.
Chapter Four: Research Methodology
Research Design and Implementation
The methodology used in this research is the survey method. As this research is to explain the causal relationship among the variables through hypothetical testing, this study is an explanatory research by nature.
“Population” in this research refers to the services provided by airline companies; in this case, it is focused on customers and employees of airline companies, namely Aegean Airlines and Olympic Airways.
Samples and Sample Size
1) Samples of customers
The samples comprised customers from the two airline companies (Aegean Airlines and Olympic Airways). The respondents were passengers of the airline companies who were waiting to board at the departure lounges at each terminal of the companies in Athens, Greece. The respondents were requested to fill in the questionnaire in accordance to their previous experiences (no longer than the past three months) of using the airline company’s services.
2) Samples of Service Providers
a) Sampling of decision-makers: Individuals representing the group of directors and managers (head office).
b) Sampling of front liners: Individuals representing the personnel directly relating with the customers, namely cabin crew, reservation officers, personnel at ticketing, check-in counters, boarding gates (greeting service), delivery baggage staff, and lost and found personnel.
Data Analysis Technique
To decide on the statistical analysis method for use, a normality test was conducted. Results of statistical analyses using the Kolmogorof Smirnof Test indicated a value of p > 0.05 for all the variables of sample data. This means that the samples have normal distribution.
Based on results of the normality test, statistical analyses were carried out using parametric statistics. The statistical analyses used the Regression Analysis, Factor Analysis, Discriminant Analysis, and Path Analysis. Analysis of research data used the level of significance α = 0.05.
Chapter Five: Research Results and Discussion
Effects of Customers’ Perceptions of Service Quality on the Level of Customers’ Satisfaction
To test the effects of the variable of customers’ perceptions of service quality on the variable of level of customers’ satisfaction, the researcher used the regression analysis.
Results of the regression analysis indicated that the customers’ perceptions of service quality have significant effects on the level of customers’ satisfaction (p < 0.05). In several marketing projects, the concept of service quality is often interchangeable with the concept of customer satisfaction. However, Zeithaml and Bitner (1996b) in their book Services Marketing stated that the concept of service quality is different from the concept of customer satisfaction. According to Zeithaml and Bitner, service quality is only one of the variables determining customer satisfaction. Besides service quality, there are other variables affecting the level of customer satisfaction, namely: price, situation, and personal factors. The findings of this research support the theory of Zeithaml and Bitner. The low value of R⊃2 (53.2 per cent) for the two concepts often considered as interchangeable, indicated the effects of the other variables (besides service quality) on the level of customer satisfaction.
Effects of Customers’ Perceptions of Service Quality on the Level of Customer Satisfaction, Measured by Servqual Dimensions
The measurement of the variable of customers’ perceptions of service quality comprised of five Servqual dimensions, namely tangibility, reliability, responsiveness, assurance, and empathy.
Results of the regression analysis on the five Servqual dimensions on the level of customer satisfaction indicated that four out of the five Servqual dimensions have significant effects on the level of customer satisfaction (all have p < 0.05). The only dimension not significantly affecting the level of customer satisfaction is responsiveness.
Besides, the other conclusion drawn from the regression analysis results is the dominant effect of the dimension of assurance compared to effects of the other Servqual dimensions. The dimension of assurance measured the service security on the level of skills and knowledge needed to enable the provision of good services. Good services include courteousness, respect, attention, friendliness, professionalism, and honesty of the service provider to convince the customers to trust the offered services. The five items covered in this dimension are: flight safety, encouraging airline staff behaviours, airline company image, respect and friendliness shown by the airline staff, as well as the capability of the airline staff to answer questions. The dominance of the dimension of assurance over the other Servqual dimensions is shown by the largest regression coefficient of the assurance dimension compared to the regression coefficient of the other Servqual dimensions, namely 0.725.
Effects of Customers’ Perceptions of Service Quality on the Customer Satisfaction Level by Airline Companies
Results of regression analysis indicated that the customers’ perceptions of service quality on the two airlines (Aegean Airlines and Olympic Airways) have significant effects on the customer satisfaction level (all with p < 0.05). Worth noting is the result of regression analysis for Aegean Airlines. Out of the two airline companies, it turns out that the customers’ perceptions’ of service quality of Aegean Airlines have dominant effects on the level of customer satisfaction for Aegean Airlines, compared to the another airline. This is shown by the regression coefficient for Aegean Airlines being largest compared to the regression coefficients of another airline, namely 0.8.
Table 3 presents the mean and standard deviation of the customer satisfaction level by the respective airline companies. The Olympic Airways customers exhibited the highest level of customer satisfaction (83.13) compared to the Aegean Airlines. Besides, the standard deviation of the satisfaction level of Olympic Airways customers is also showing the smallest figure (10.84).
Effects of Conformity between External Communication and Service Quality on the Customer Satisfaction Level
Table 4 presents the regression analysis results conducted on the variable of conformity between external communication and the service quality and of the variable of customer satisfaction level.
Results of the analysis indicate that the conformity between external communications and service quality has significant effects on the customer satisfaction level (p < 0.05). Up to the present time, marketing researchers have never conducted a research that tested the relationship between service quality and external communications on the customer satisfaction level. However, several researchers have mentioned the importance of fulfilling one’s promises to the customers. Gronroos (1990) stated that the strong base for keeping good relationships with the customers is to fulfill the promises made by the company. For the company side, this relates to the three important activities in the company. They are, namely: 1) making realistic promises to customers, 2) fulfilling the promises while serving the customers, and 3) enabling the front liners and serving system to fulfill these promises. Kotler (1994) had discussed the three marketing activities using terms of external marketing, interactive marketing, and internal marketing.
Effects of Conformity between External Communications and Service Quality on the Customer Satisfaction Level by Airline Companies
Results indicated that conformity between service quality and external communications conducted by the two airline companies (Aegean Airlines and Olympic Airways) have significant effects on the customers’ level of satisfaction (all values of p < 0.05). The effects of conformity between service quality and external communications on the customer satisfaction level were of highest priority on Olympic Airways (7.958) followed by Aegean Airlines (7.311).
Differentiating Factors of the Customers’ Satisfaction Level on the Whole
According to Zeithaml and Bitner (1996), there are four variables (personality, situation, price, and customers’ perceptions of service quality) affecting customers’ satisfaction. However, it turns out that, in general, the variables of price and personality are not the differentiating factors for the level of satisfaction and dissatisfaction of customers of airlines. On the other hand, the customers’ perceptions on service quality and situation (on time departure) have proven to be the main factors differentiating the level of satisfaction or dissatisfaction of customers. Another finding which deviates from the concept proposed by Zeithaml and Bitner (1996b) is that the fulfillment of airline company’s promises turns out to be the differentiating factor for the customers’ level of satisfaction or dissatisfaction. These promises, as contained in the promotional brochures and other forms of external communications, proved to have a great effect on the satisfaction level, expressed in a larger canonical discriminant F coefficient of the variable of situation (0.529). Results of discriminant analysis on all the differentiating variables on customer satisfaction level, using the stepwise method, indicate significant effects with a p value of < 0.05.
Results of factor and discriminant analyses indicate that the variable of price turns out not as the differentiating variables for the customers’ level of satisfaction or dissatisfaction. The customers’ satisfaction or dissatisfaction may be due to three reasons. First, the airfare for a certain route tends to be similar among the airlines. Second, of all the domestic passengers, 74 per cent of them were flying for official or business purposes, thus their fares were paid by companies. This fact had made price not a differentiating factor for the level of customers’ satisfaction or dissatisfaction. Third, self-paying passengers were, in general, European with high income.
Factors Differentiating the Customers’ Satisfaction Level by Segments
Furthermore, discriminant analysis was carried out to identify the factors differentiating the customer satisfaction levels by segments of customer flight destinations, namely business, vacation or tourism, and visiting friends and relatives. Results of analyses on the three segments of customer flight destination indicated similarities of factors differentiating the levels of customers’ satisfaction or dissatisfaction on service quality and conformity between service quality and external communications (promotion). Out of the two factors, the customers’ perceptions on service quality is the more dominant factor differentiating the level of customers’ satisfaction compared to conformity between service quality and external communications on the segments of business and vacation. Meanwhile, the conformity between service quality and external communications was more dominant compared to the customers’ perception on service quality on the segment of visiting friends and relatives. These findings are shown by the canonical discriminant function coefficient for the respective segments.
The discriminant analysis for customers of the business segment proved that the variable of situation (on time performance) is the factor differentiating the level of customers’ satisfaction with a quite high level of significance (0.17). Besides, the data showed that the mean value of the satisfaction level of customers of the business segment experiencing no delays (80.18) is higher than the mean value of satisfaction level of customers of the same segment experiencing delays (75.25). Apart from that, the standard deviation of customers’ satisfaction level of customers experiencing delays is showing a lower value (11.2) compared to the satisfaction level of customers not experiencing any delays. We may conclude that there is a difference in the level of customers’ satisfaction when there is a delay.
Effects of Management Commitments, Front liners’ Job Satisfaction, and Customers’ Perception of Service Quality on the Customer Satisfaction Level
Based on results of path analysis shown in Figure 3, we conclude that management commitment has a direct negative effect (-0.361) on the customer satisfaction level. Besides, management commitments had positive indirect effects on customers’ satisfaction through customers’ perception of service quality (0.359). Of all the available paths, the path of customers’ perception of service quality and customers’ satisfaction had the greatest effects among the other path (1.021). Furthermore, after considering the direct effects of management commitments and front liners’ job satisfaction, the total indirect effect was greatest in the indirect path between management commitments and customers’ perception of service quality. The total indirect effect on the level of customer satisfaction was -0.052. This total effect is greater than the total effect of the path between the front liners’ job satisfaction, customers’ perception of service quality, on the level of customer satisfaction (namely -0.265).
Another conclusion drawn from the path analysis results is that the front liners’ job satisfaction had negative effects on the customers’ perception of service quality and the customer satisfaction level. The customers’ perception of service quality, which is the customers’ evaluation on the airline’s performances, is not reflected by the front liners’ job satisfaction. In other words, the customers give positive evaluations of the service quality and customer satisfaction as there is the effects of management commitments of the airline company, and not because of the front liners’ job satisfaction. The research results indicate that most of the customers of airline companies (64.8 per cent) were not satisfied with the services they received. The customers’ dissatisfactions were due to the interactions taking place between the customers and the front liners, and not because the customers felt that the company did not have commitments for service quality.
This finding contradicts the results of earlier researches. Schneider and Bowen (1985) and Gronroos (1993) concluded that “if managers treat their employees well, the employees will treat their customers well.”
Chapter Six: Theoretical Implications and Applications
The findings in this research indicate that management commitment on service quality have positive indirect effects on the customer satisfaction level, through customers’ perception of service quality. Besides, the front liners’ job satisfaction turns out to have no positive effects on the customers’ perception of service quality and level of customer satisfaction. In other words, the customers give positive evaluations on service quality and are satisfied due to the effects of management commitments to service quality, not the effects of the front liners’ job satisfaction. To increase customers’ satisfaction, the management should continuously enhance their commitments on service quality, so that through the leadership mechanism, the decision-makers at the airline companies could enhance their employees’ job satisfaction. On the other side, the internal marketing activities (especially the training of front liners) should be enhanced their effectiveness, as the evaluation on service quality will be determined by the interactions taking place between customers and the front liners.
Management commitment is found to be highest at the Aegean Airlines. Nevertheless, however, customers of the airline companies consider the best quality service was provided by Olympics Airways, causing the highest satisfaction level of Olympics Airways customers. We conclude that the corporate environment (in this research, the management commitment to service quality) is the factor determining the satisfaction level of customers of airline companies.
Chapter Seven: Conclusions and Recommendations
This study concludes that:
1. The majority of customers of airline companies (64.8 peter cent) were not satisfied with the services they received. This was due to the airline companies lacking customer orientations, their orientations were on products.
2. Customers’ perception of service quality has positive effects on the level of customer satisfaction. Out of the five dimensions of service quality, the dimension of assurance has greatest effects on the level of customer satisfaction. Assurance of flight-safety, airline company image, professionalism of personnel, and friendliness of the front liners, are the additional values influencing the level of customer satisfaction.
3. Fulfilling the company’s promises (conformity between service quality and external communications) has significant effects on the level of customer satisfaction. Exaggerated promotional themes (not in conformity with the services provided) could lead to customers’ dissatisfaction for the services provided by the domestic airline companies.
4. On the whole, the level of satisfaction or dissatisfaction of customers of airline companies is not differentiated by the variables of price (discounts) and personality. However, the differentiating variables are the variables of a) customers’ perception of service quality; b) conformity between service quality and promotion; and c) situation (on time performance). The price competition strategy adopted so far by some domestic airline companies proved to have no differentiating effects on the level of customers’ satisfaction or dissatisfaction.
5. The variable of situation (on time performance) proved to be the differentiating variable for the level of satisfaction or dissatisfaction of customers of the business segment. The variable of price (discounts) did not prove to be the differentiating variable for the level of satisfaction or dissatisfaction of customers of the segments of tourism or holidays and visiting friends or relatives. On incidents of delays, the time of announcing the delay was the differentiating variable for the level of satisfaction or dissatisfaction of customers of the segment of visiting friends and relatives.
6. Management commitments to service quality have positive indirect effects on the level of customer satisfaction, through the customers’ perception of service quality. On the contrary, the front liners’ job satisfaction did not prove to have positive effects on the customers’ perception of service quality and customers’ satisfaction.
The findings of this research proved that management commitments could enhance customers’ satisfaction through improving customers’ perception of service quality.
1. To enhance customers’ satisfaction, the airline companies should enhance the quality of the services they provide to the customers. Improvement of service quality should be conducted on the five Servqual dimensions, especially the dimensions of assurance and tangibility.
2. The airline companies should better be more careful in making service promises through external communications (promotional activities). Exaggerated and less realistic promotional themes could influence customers’ satisfaction.
3. Management commitment to service quality should be enhanced through the mechanism of leadership. The managers already on a high position of work dimension should better promote the people dimension. On the other hand, the managers already on a high position of people dimension should better promote the work dimension.
4. It is necessary for the company to promote internal marketing activities through training programmes, especially for customer-contact service employees, as the customers’ evaluation on service quality will depend on the interactions taking place between customers and front liners.
5. An integrative research, involving the service providers and users as respondents, should be conducted on other kinds of services as well. This is to test the relationships made as hypotheses in this research, especially the relationship between management commitments and employees’ job satisfaction and its effects on the customers’ perception of service quality and on the level of customer satisfaction.
6. Future research is necessary to study the internal aspects of service quality and management of customer-contact service employees or the front liners. The topics worth considering are, among others, leadership and internal marketing strategies (training).
Table 1: Planned and Realised Sample Size of Customers by Airlines
Legend for Chart:
A – No
B – Company
C – Average number of passengers/day
D – Planned Sample Size
E – Obtained Number of Samples
A B C D E
Airline 951 460 419
Airways 1,195 420 647
7,921 798 956
Number of samples
used in data analysis 887
Note: The plan for sample size is at least 10 per cent of the average number of passengers leaving Athens Airport per day.
Table 2: Sample Size of Decision-makers by Companies
Legend for Chart:
A – No
B – Company
C – Population
D – Obtained Samples Number
E – Obtained Samples Percentage
A B C D E
Airline 45 43 56.7
Airways 46 23 43.3
Total 91 66 100.0
Table 3: Mean and Standard Deviation of Satisfaction Level of Customers of Domestic Airlines by Airline Companies, August 2006
Legend for Chart:
A – No
B – Company
C – Customer Satisfaction Level Mean
D – Customer Satisfaction Level Standard Deviation
A B C D
Airline 79.51 13.48
Airways 83.13 10.84
Average scores of
two companies 78.11 12.19
(n = 887)
Table 4: Regression Analysis Results: Effects of Conformity between External Communications and Service Quality on Customer Satisfaction Level for all Two Airline Companies, August 2006
Legend for Chart:
A – Equation
B – R²
C – t Constant
D – t Regression Coef.
E – F
F – P
A B C D E F
Y = 47.506 + 8.310 X 0.425 38.4 25.6 654.1 0.001 (b)
(n = 887)
Legend: R² = Coefficient of determination
p = level of significance
b = significant
Y = level of customer satisfaction
X = Conformity of external communications and service quality
Table 5. Epistemological approaches and measurement
Approaches Understanding ‘reality’
Classical science Basic assumptions:
(positivistic, Popperian) Phenomena are given
a ‘whole’ can best be understood
by dividing it into isolated parts
and by adding the knowledge on
ù describe the phenomena to be
studied as accurately as
ù formalize (the more maths the
ù design methods of objectivated
perception (measurement) to
exclude subjective bias
ù synthesize your findings
Interpretative, constructivist Basic assumptions:
(constructionist) approaches Phenomena are not given, but
socially constructed A ‘whole’ can
best be understood by experiencing
it as such, thus by intuition and
ù Do not focus on isolated
elements but on their
ù Invest effort in the
construction of phenomena,
experiment with different
ù Recognize pattern rather than
achieving accuracy in isolated
details (fuzzy rather than
Table 6. Criteria to measure intangibles
Legend for chart:
A1=Ease of fulfilling
A2=Absenteeism as a measure of employee dissatisfaction
A3=Double problem of construct validity and indicator validity; never 100%
A4=Customer survey used by different affiliates at different points in time
A5=’Ceteris is rarely paribus’ complex, real-time situations are no laboratories
A6=Intelligence tests designed and validated by ‘scientific’ procedure
A7=To be interest-free is logically impossible but can be brought into line by sound methodology
A8=Skills measured as formal qualifications versus assessment in a 6-month trainee period
A9=Easier for singular measures drawn from existing accounts and statistics; increasingly easy for secondary research (Internet); often in contradiction to validity and strategic relevance
B1=Managers give more feedback after a survey showing a corresponding deficit
B2=Simplicity, plausibility, understandability, ease to access
B3=Innovativeness measured as new products-to-sales ratio
B4=Often driven out by the easy to quantify and a ‘squirrel’ mentality of accumulating details
Criteria Definition B5 A1
Classical Validity A measure captures A2 A3
research what we want to know,
criteria what it pretends to
Reliability Stability of measurement A4 A5
Objectivity Distant and interest-free A6 A7
perspective of an
Business Efficiency Benefits of measure A8 A9
context outweigh costs of their
Usability Measures are paid B1 B2
attention, interpreted in
an intended way and
translated into action
Strategic Measures are important B3 B4
relevance to monitor strategy and
inspire the development
of new strategy
Table 7. Trade-offs in measuring Intellectual Capital (IC)
Legend for chart:
A2=Standardized measures, by-product of traditional accounting/controlling procedures
A3=Simple, few and clear measures, correlation to financial measures
A4=Sophisticated procedures, rather customized than standardized; qualitative, non-financial measures
Criterion A1 A5
Cost of establishment and administration ?? A2
Usability of information, value added by ?? A3
Validity ?? A4
Figure 1: Research Conceptual Framework
Figure 2: Research Operational Framework
Figure 3: Effects of Management Commitments, Front liners’ Job Satisfaction, and Customers’ Perception of Service Quality on Satisfaction Level
Figure 4: Basic Research Design to Measure Customer Satisfaction
Figure 5: Enlarged Model of Influence Factors on Consumer Satisfaction
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