Examining Factors Affect Passenger's Satisfaction ...

Examining Factors Affect Passenger’s Satisfaction and Loyalty: A comparative Analysis from Jordan Airport Abbas Al-Refaie, Rami H. Fouad Diana Eteiwi

Examining Factors Affect Passenger’s Satisfaction and Loyalty: A comparative Analysis from Jordan Airport Abbas Al-Refaie1, Rami H. Fouad 2* Diana Eteiwi3 1,3Department of Industrial Engineering, University of Jordan, Amman 11942, Jordan [email protected] 2*Department of Industrial Engineering, Hashemite University, 13133, Zarqa, Jordan [email protected]

Abstract This paper investigates the relationships between service quality, perceived value, and corporate image on passengers’ satisfaction and loyalty from the perspective of national (NA) and international (IA) airlines passengers in Jordan airport. Two models were established for this purpose. The results revealed that: (1) NA and IA passengers ensure that service quality is directly and significantly enhances passenger satisfaction which also influences service loyalty. Moreover, they believe that perceived value is positively related to passenger satisfaction, (2) NA and IA passengers emphasize the positive relationship between perceived value and passenger satisfaction, whereas they show a partial effect of perceived value on service loyalty, (3) NA passengers indicate a positive effect of perceived value on cognitive loyalty. However, AI passengers strongly relate perceived value with cognitive loyalty, (4) NA passengers relates strongly corporate image with passenger satisfaction and perceived value. However, IA passengers indicate a slight effect of corporate image on PS and perceived value and (5) NA and IA passengers reveal an indirect relationship between corporate image and cognitive loyalty. In conclusion, service quality and perceived values are found the key factors which affect passenger satisfaction and consequently passengers’ loyalty. Considering these findings in planning and improvement activities enable airlines to improve their performance as well as compete in today’s harsh competition.

Key word: Passenger Satisfaction, Loyalty, Perceived Value, Corporate Image 1. Introduction Air travel, driven by liberalization and globalization, remains the fastest-growing market. Delivering high quality service to passengers is the core competitive advantage for an airline’s profitability and sustained development. Moreover, increasing customer retention is a major key to the ability of a service provider to generate profits [1]. Hence, it is important to understand the determinants affecting a passenger’s loyalty. Park [2] suggested that the key variables considered in airlines include service quality, passenger’s satisfaction, perceived value, and corporate image, satisfaction with e-service, behavioral loyalty, attitudinal loyalty and cognitive loyalty. Chen [3] suggested that the measurement of passenger satisfaction should be used in conjunction with the measurement of perceived value. Mostert, et al. [4] investigated the effect of service failures and an airline’s service recovery efforts on their customer relationships and future patronage of the airline. Data were collected from passengers flying with South African domestic passenger airlines departing from Tambo International Airport. The findings indicate that customer satisfaction with an airline’s service recovery efforts significantly influences their relationship with the airline as well as their future patronage of the airline. In practice, it is easier and considerably less expensive to retain a customer than to continuously attempt to acquire new customers [5-7]. Therefore, airlines should establish relationships with their customers and retain them to increase profitability over the longer term. That is, airlines have to constantly deliver their services more satisfactorily than those of their competitors [8]. Several research efforts examined the effect of service quality, satisfaction, and loyalty on behavioral intention [9-13]. In Jordan, however, little research efforts have been directed toward investigating the factors that affect passenger satisfaction and loyalty. Therefore, this research aims at investigating the factors that affect passenger satisfaction and loyalty from the perspective of passengers flying via national airline (NA) and international airlines (IA). Two models will be constructed for this purpose. The first one studies

Advances in information Sciences and Service Sciences(AISS) Volume5, Number3, Feb 2013 doi: 10.4156/AISS.vol5.issue3.75

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the effects of service quality on overall satisfaction and loyalty. Moreover, it investigates the relationships between these factors. While, the second model examines the factors affect cognitive loyalty. The remaining of this research is outlined in the following sequence. Section two presents the conceptual framework. Section three conducts data collection and analysis of the two models using structural equation modeling. Section four summarizes research results. Finally, conclusions are made in section five.

2. Conceptual Framework 2.1 Model I: Overall Satisfaction Model and Loyalty This model investigates the relationships between passenger satisfaction, service quality, and loyalty. 2.1.1 Passenger Satisfaction Customer Satisfaction (CS) is a key factor in business success in today’s sharp competition [14-17]. Satisfaction is an overall effective response to a perceived discrepancy between prior expectation and perceived performance after consumption. Customer satisfaction is defined as a judgment made on the basis of a specific service encounter [18]. Passenger’s satisfaction is a feeling based on the service experience of a passenger’s most recent flight. Increasing customer satisfaction can lead to improved profits, and positive word of mouth communication. It can be a significant determinant of passengers’ buying behavior and crucial to the long time survival of an airline. 2.1.2 Service Quality Service quality is the consumers overall impression of the relative inferiority/superiority of the organization and its services [19]. In the airline industry, delivering high quality service to passengers is essential for airlines survival, as well as it is a significant driver of passenger’s satisfaction, passenger loyalty, and passenger’s choice of airline. An airline’s service quality [20-21] can be measured by: i. In-flight service quality (IFSQ), which aims at improving safety, quality and cost effectiveness of in-flight services for the benefit of member airlines, partners, and passengers. ii. Reservation and ticketing (R&T), which enables people to pre-schedule flights for use at a later time. Reserving airline tickets gets passengers a good price and guarantees a seat on the flight one needs. Advance ticketing is required on almost all flights unless one wants to pay a higher price. iii. Airport services (AS), which develop and maintain standards and procedures for the handling of passengers at airports, including all forms and regulations. iv. Employee services (ES), which aims at establishing employee friendly policies and management practices; foster a healthy, productive rewarding work environment and offer administrative and consulting services to departments and employees. v. Reliability (RE), which means the ability of a person or system to perform and maintain its functions in routine circumstances, as well as hostile and unexpected circumstances. vi. Customer satisfaction with the web site and e-services (CSWS). The pervasive use of Internet in the airline business has created a digitalized market that improves the processes dealing with acquisition, management, and maintenance of passengers. Valuable customer knowledge and market information obtained through the Internet presents the potential for improving customer relationships for airlines. Conceptually, higher quality service leads to higher passenger satisfaction. Consequently, the following hypotheses are developed: H 1: IFSQ has a positive effect on PS. H 2: R&T, AS, and ES are positively related with PS. H 3: CSWS has a positive effect on PS. H 4: RE has a positive effect on PS.

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2.1.3 Service Loyalty There are three main streams in service loyalty (SL) including behavioral, altitudinal, and cognitive loyalty [22]. SL is determined by the degree to which a customer exhibits repeat purchasing behavior from a service provider, possesses a positive attitudinal disposition toward the provider and considers using only this provider when a need for this service arises. Various measures in terms of behavioral, attitudinal and cognitive attribute are used as measures of service loyalty including: (a) repeat purchase behavior by showing continuance commitment on an entity, (b) word of mouth, which means recommending others to purchase through any common means. It is believed that loyal customers are likely to give positive feedback to the service company, (c) period of usage, which represents the time interval in which the customer is keeping consumption from a particular service provider continuously, (d) repeat purchase intention; which basically is referred as the extent of repeat purchase intention from the same service provider with affective commitment, (e) preference, which is the typical measure for the attitudinal dimension of service loyalty attained when the customer expressed strong positive preference as well as high repeat patronage on an entity, (f) choice reduction behavior; which is a definite resultant behavior of loyalty, as customers with a strong strength of loyalty would appear to reduce the search motivation, and hence eventually forgo the choice of other alternatives and reduce the competitive efforts on decision making, and (g) first-in-mind, where extremely loyal passengers will be ideally limited to only one choice that should be the first choice in their minds. It is believed that higher passenger satisfaction results in stronger service loyalty including attitudinal and behavioral. Therefore, it is hypothesized that: H 5: Higher level of PS will lead to higher level of SL. H 6: PS has a positive effect on AL. H7: PS has a positive effect on BL. Based on the developed seven hypotheses, the structural model is built as shown in Fig. 1.

IFSQ AL

H1 R&T, AS, ES

H6 H2 PS

H5

SL

H3 CSWS H7 H4

BL

RE Fig. 1. The proposed Model I.

2.2 Model II: Cognitive Loyalty This model considers the relationships between SQ measures, PS, cognitive loyalty (CL), SL, corporate image (CI), and perceived value (PV). From the constructs of Model I, the following hypotheses are considered: H 1-3: Service quality (IFSQ and R&T, AS and ES, and RE) has positive effect on PS. H 4: Higher level of PS of the service will lead to higher level of SL. H 5: PS has a positive effect on CL.

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2.2.1 Perceived Value Perceived value (PV) is the consumer overall assessment of the utility of a product (or service) based on perceptions of what is received and what is provided. More specifically, perceived value can be summarized as a trade-off between perceived benefits and perceived costs. PV is an important variable of customer satisfaction and buying behavior. Value added services are ways in which an airline company can gain competitive advantages, such as, frequent flyer programs increase the long term value of the relationship with the airline, offering greater benefits to repeat passengers than to occasional users. Typically, perceived value positively affects customer satisfaction [23-24]. Several studies examined the relationships among service quality, perceived value and customer satisfaction [25]. They supported the positive impact of quality service on perceived value and customer satisfaction. Thus, the following hypotheses are established: H 6-8: Service quality (IFSQ and R&T, AS and ES, and RE) has positive effect on PV. H9: PV has a significant positive effect on PS. H10: Higher level of PV of the service will lead to higher level of SL. H11: PV has a significant positive effect on CL. 2.2.2 Corporate Image Corporate image (CI) can be defined as perceptions of an organization reflected in the associations held in consumer memory. The purpose of CI in airlines is to reflect a distinctive competence in comparison with their competitors to allow the airline name, symbol, or identity to mean something distinctive and with a corresponding appeal. A favorable CI leads to a preferred choice among their choice set when passengers contemplate air travel. Hence, the perception of SQ directly affects the perception of CI. Further, CI plays an important role in creating customer satisfaction [26]. Barich and Kotler [27] described CI as the overall impression made on the minds of the public about an organization. It is believed that CI has a significant direct effect on SL and CL. Aydin and Ozer [28] indicated that the perception of service quality directly affects the perception of corporate image. In addition, a positive image helps customers experience pleasurable social and emotional benefits and hence enhances perceived value. As a result, the following hypotheses are proposed: H12: CI has a significant positive effect on PS. H13: CI of the service will lead to higher level of PV. H14: CI has a significant positive effect on CL. Based on the above hypotheses, the Model II constructs are related as shown in Fig. 2.

H1-3

SQ

H4

PS

SL

H5

H6-8

H9

H12

H10

Image H13

PV

CL H11

H14 Fig. 2. The proposed Model II.

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3. Data Collection and Analysis 3.1 Data Collection The data is collected via a questionnaire composed of two parts; the first part contains item measures for the constructs of Model I and II. The scale that used is a seven-point Likert scale [2] ranging from 1: strongly disagree to 7: strongly agree, whereas the second part consists of passenger’s demographic parameters. The design of the questionnaire was based on multiple item measurement scale. Tables 1 and 2 displays the number of item measures for each construct and demographic parameters, respectively. Table 1. Measurement items for all variables Construct

SQ

Measure IFSQ

Items 6

R&T AS ES CSWS

2 4 6 6

RE

7 3 2 4 3 3 2 2

PS AL BL Service recovery Image Value Cognitive loyalty

Table 2. Demographic parameters. Parameter Gender

Age Occupation Education Nationality Class of travel Airline of travel Frequent flyer member

Item Male Female 15-30 31-45 46-60 60+ This was specified according to the passenger Primary school Secondary University degree Other and please specify type This was specified according to the passenger Business Economy This was specified according to the passenger Yes No

3.1 Data Collection A pilot study is conducted to see if any of the statements were difficult for subjects to understand and to check for the appropriateness of the items used in this thesis. A number of samples of international as well national passengers, who have recent experience of travel, were consulted. In

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addition, the questionnaire was first reviewed by airline experts and airline staff. Based on their opinions, experts and passengers the final questionnaire is designed then distributed. Sample survey is the method of collecting and gathering information from a part of the population by using a structured questionnaire. In this model simple random sampling is used, which gives a known and equal nonzero chance of selection to each member of the population. A random sample is usually a representative sample. Therefore, in this research the passengers at Jordan airport are chosen for collecting data.

3.2 Data Analysis Four hundred surveys are distributed and 263 are returned, which incurs a response rate of 66 %. The number of the national airlines (NA) respondents is 127, whereas the number of the international airlines (IA) respondents is 136.

3.2.1 Demographic Profile of the respondents The profile of the respondents is looked upon in terms of age, gender, educational attainment. The results show that:  For age, 68% of the respondents were 15-30 years old, 20 % were between 31-45 years old; 5 % were between 46-60 years old, and 7 % were above 60 years old.  For the distribution of respondent by gender; 48% and 51% of the respondents were female and male, respectively.  For educational attainment, it is found that 79% of the respondents were university graduates.

3.2.2

Analysis of Model I and II

(a) Multicollinearity test Multicollinearity measures the degree by which items measure the same entity and a value of 0.9 or above for the inter-item correlations indicate the possibility that two or more items measure the same entity [29]. To investigate multicollinearity, the inter-item correlation coefficients for the measured items are calculated for Models I and II for the data from NA and IA passengers. Table 3 displays the summary of item statistics for NA and FA passengers in Model I, respectively. It is noted that the maximum inter-item correlations are 0.684 and 0.690 for NA and IA passengers, respectively. Similarly, Table 3 also shows the summary of item statistics for NA and IA passengers in Model II, respectively, where for NA and IA passengers, the maximum of the inter-item correlations do not exceed the threshold value. Hence, it is concluded that the multicollinearity problem is not apparent in both models. Table 3. Summary of item statistics for NA passengers (Model I). Model I II

Passenger NA IA NA IA

Mean 0.236 0.334 0.237 0.320

Minimum -0.250 -0.110 -0.270 -0.017

Maximum 0.684 0.690 0.673 0.644

Range 0.935 0.799 0.943 0.661

Variance 0.035 0.018 0.035 0.015

(b) Test of Reliability To assess reliability, internal consistency methods are widely used and generally Cronbach’s alpha, α, is used to assess internal consistency. The α is the average of all possible split half coefficients resulting from different items and a value of 0.6 or less generally indicates unsatisfactory consistency [29]. Tables 4 and 5 display the α values for the constructs of Model I and II, respectively. Apparently, the α values exceed the threshold value and thus indicate the internal consistency in both models. Table 4. The α values for the constructs of Model I.

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Variable

NA

IFSQ R&T, AS, and ES CSWS RE PS AL BL Overall alpha

0.619 0.717 0.728 0.634 0.692 0.768 0.641 0.917

IA 0.763 0.820 0.846 0.828 0.783 0.837 0.731 0.947

Table 5. The α values for the constructs of Model II. Variable IFSQ and R&T AS and ES RE PS PV CI CL Overall alpha

NA 0.661 0.674 0.634 0.692 0.598 0.641 0.623 0.836

IA 0.795 0.801 0.828 0.783 0.698 0.783 0.483 0.938

(c) Confirmatory factor analysis Confirmatory factor analysis (CFA) is used to test the validity of the measurement model [31]. In general, if the ratio between the Chi square goodness of fit measure and the degrees of freedom is less than 5, the model is accepted. The other goodness of fit indices include the root mean square error of approximation (RMSEA), where the recommended maximum RMSEA is 0.09. Further, the Minimum should be achieved with a probability less than p