The Effect of Lifestyle on Online Purchasing Decision for Electronic Services : The Jordanian Flying E-Tickets Case

This study aims to examine how Jordanian passenger’s lifestyle effects their buying decisions of online e-tickets by utilizing the AIO theory (Activities, Interests, and Opinions). A convenience sample of 473 passengers from the Jordanian airport was chosen as the population in order to verify the hypotheses and research framework. The results of the study show that the lifestyle of Jordanian passengers significantly influences their purchase of e-tickets. The analysis of the results indicates that each of the lifestyle dimensions: Activities, Interests, and Opinions, had a significant positive effect on the purchasing decision of the e-ticket Service.


Introduction
The internet is a key part of everyday life for both the young and the old.The most important use of the internet within business is E-marketing and businesses face many challenges due to the technological advances made this century (Murray, 2011).Furthermore, the methods of marketing have changed and improved.Consumers are becoming more open-minded due to internet and its multiple applications.Consequently, online purchasing decisions are a major task that consumers use the technology for.The consumer buying decision process is a systematic way of looking at how a consumer makes the decision to purchase a product or services.These basic psychological processes play an important role in understanding how consumers actually make their buying decisions (Luo & Bhattacharya, 2006).Smart companies try to fully understand the customers' buying decision-making process and their experiences in learning, choosing, using, and disposing of a product (Arnett et al, 2003).Research is needed to develop a clearer insight into how consumers will react to this type of marketing.
Every consumer behaves differently and there are many factors that affect behavior.Previous studies investigated factors such as social life, personality (Lars, 2010), lifestyle (Plummer, 1974), group reference, and education.Consumer behavior studies are one of the most important fields in business research.Lifestyle is a well-known approach that can be used to analyze consumer behavior.The Activities, Interests, and Opinions (AIO) theory is the most famous measurement of lifestyle (Plummer, 1974).Another method of is the value approach.However, values are broader in scope than attitudes or the types of variables contained in AIO.This study focuses on services and not goods because of the eight differences between them that make buying services more difficult than goods.Services are economic activities, which are offered by one party to another.Often time based, performances bring about the desired result for the recipients, objects, or other assets for which the purchases have responsibility, however, they do not normally take ownership of any of the physical elements involved (Lovelock & Wirtz, 2011, 37).
The airline electronic commerce market is one of the fast growing industries in the world.The airline industry's ticket distribution channel has changed to e-ticketing.This distribution channel enables customers to purchase e-tickets quickly and reduces costs for the company and the customer (Chen, 2009).While virtual distributors on the internet might be insecure and untrustworthy, they are still one of the most importance sales' channels for airlines.Jordan is a landlocked country with a territory of (89.342) sq.km with high potential demand in air transportation from its population of (9.5) million.According to the internet world stats and the Census Bureau, there are approximately (5.7) million internet users in Jordan in 2016, implying a penetration rate of (60) % (Yaseen et al, 2015).This concludes with Yaseen et al. (2015) that 95% of Jordanians own mobile phones and with 40% are smart phones with access to the internet.Many empirical studies have examined e-commerce customer's buying decisions in various countries.However, empirical research that examines the influence of lifestyle on buying decision of e-ticket is going so far in the e-commerce.
An Electronic Ticket (E-Ticket) is a paperless electronic document, which is particularly common in the airline industry (Kurniawan, 2010).Moreover, according to Alfawaer et al. (2011) defined E-Ticket as "a paperless electronic document used for ticketing travellers, mainly in the commercial airline industry".Another definition for the E-Ticket proposed by Sorooshian et al. (2013) as "a procedure of keeping record of sales, usage tracking and accounting for a passenger's transport with no requirement for a paper value document".Nowadays, all major airlines use the e-ticketing method to sell tickets.Previously, the airlines used to sell their tickets through a third party (Intermediaries).However, with the rabid development and expansion of web technologies the airlines started to eliminates this approach (disintermediation).Therefore, according to (turban) all major airlines sell their tickets online (Turban et al, 2017).When a customer buys or books airline tickets by telephone or the internet, the details of their reservation are stored in a computer.The benefit of e-ticketing is reducing expense of purchasing airline tickets by eliminating the need to print and post paper documents (Chen, 2009).Another advantage is that consumers can compare ticket costs easily online without a transaction fee.
According to Turban et al. (2017), numerous airlines like Cathay Pacific, Delta, and Qantas provide special service that affect the consumer behavior such as wireless services and advanced check-in.Moreover, most of the airlines nowadays use direct marketing by selling e-tickets over their own websites or through the so-called e-intermediaries.Moreover, some of the airline took a strategic step to enter alliances and consortia.With the rapid growth of social networks such as Facebook, YouTube, and twitter another field has emerged where consumers can get the latest offers from the Airlines companies, which we could name it as social travel networks.Moreover, it has been extended to mobile travel networks such as Trip Advisor Application and many other similar applications.Such applications allowed consumers to buy e-tickets either from a third party or from the airlines company's mobile applications.These mobile applications allowed the consumer to review reservation, book revenue flights, book award flights, seat map/assignment, and check in using mobile boarding pass.
Previous research indicates that consumer-purchasing decisions are effected by various elements, which form behavior in decision-making.To the researchers' knowledge, although many previous studies have researched the impact of consumer behavior on purchasing decisions there are very few, if any,(e.g.Emerald, Journal of Marketing, Jordan University e-library, and Google) that study the effect of lifestyle (AIO theory) on online purchasing decisions for electronic services with airline e-tickets as the case study.Kim et al. (2013) researched online retailer reputation and consumer response and examined cross-cultural differences.Mohamadou et al. (2005) studied US consumer-purchasing decisions and demand for apparel.Huang (Huang et al., 2011) studied decision making in online auctions.Andrews et al, (2012) linked the perceived value of mobile marketing with the experiential consumption of mobile phones.Persaud and Azhar explored innovative mobile marketing via smart phones Are consumers ready?(Persaud & Azhar, 2012).There are two studies, which are similar to this one; How Consumer Lifestyles Affect Purchasing Behavior: Evidence from Internet Shopping in Japan (Atchariyachanvanich & Okada, 2007) and A Lifestyles study on the Purchasing Behavior of Malaysian Online Consumers (Norzieiriani et al., 2014).However, this study focuses on electronic services and conducts an airline e-tickets case study.
The primary purpose of this research is to explain how lifestyle (using AIO theory) can affect online purchasing decisions for electronic services.Would Jordanian passengers like to pay for their tickets using online services?It is expected that this study of the passengers' lifestyles will be beneficial for marketers.It will enable them to develop and segment the market of e-service in accordance to their lifestyle, thus increasing sales.The research questions of this study relate to the influence of the Jordanian passengers' lifestyle on their decision to buy e-tickets.The specific questions to be examined are:  To what extent does the passengers' lifestyle influence their decision to buy e-tickets? Are there any differences among the passengers' lifestyles due to their demographic characteristics? Can we classify the buyers of e-tickets based on their lifestyle?

Literature Review
According to Plummer (1974), lifestyle measures people's activities in terms of how they spend their time, what they place importance on in their surroundings, their views of themselves and the world around them and some basic characteristics such as their stage in the lifecycle, income, education and where they live.Lifestyle is influenced by factors like demographics, social class, motives, personality, emotions, values, household lifecycle, culture and experiences.As an individual's lifestyle changes so, do their needs for different goods and services.This change in needs and attitudes results in changes to their purchase and consumption behavior.Lifestyle plays an important role in the purchase decisions of consumers.Consumers are motivated to buy products in order to maintain or pursue a certain lifestyle.Lifestyle segmentation is very important to research on consumer behavior and international marketing due to its large impact on the daily purchase decisions made by each individual (Horley et al., 1988, Hung, 2009;Li, 2009).
There are two approaches to conducting lifestyle studies.One focuses on the aspects of individual and household lifestyles that are most relevant to the products and services that firms produce.The other focuses on the general lifestyle patterns of a population.Thus, lifestyle measurements can be constructed with varying degrees of specificity at one extreme; measurements that are based on the more general lifestyle and at the other; measurements that are more product and activity specific.Therefore, this study is concerned with the variables of the general and specific lifestyle of passengers to understand their attitudes and prepare marketing strategies to deal with them accordingly (Atchariyachanvanich & Okada, 2007).Many other studies measured the lifestyles of consumers and established some parameters and estimates (Lee et al., 2009).Some of these conclusions are based on the prevailing values in different communities and others rely on the individual attributes and demographic characteristics of each population.Other studies concentrated on the socio economic conditions and tendencies of change, most of those studies measured the endogenous attributes of each community in order to measure their lifestyles and provide new results based on the activities, interests and opinions of the people (AIO).
Many studies have divided the market into sectors according to the general lifestyle.However, when we discuss a specific lifestyle we are referring to buying a specific product, which provides specific services.Purchasing attitudes have been studied in relation to specific lifestyles regarding food, housing, tourism, investment, medical services, and entertainment etc.In each case there is a different lifestyle; each product is related to a different subset of consumer lifestyles (Krishnan & Murugan, 2007).Guo & Barnes's (2011) study "Purchase behavior in virtual worlds: An empirical investigation in Second Life" developed and tested a conceptual model of purchase behavior in virtual worlds using a combination of existing and new constructs.They examined a kind of shopping behavior where in consumers spend a noticeable amount of money shopping on the internet.The factors in their model were external motivators like perceived value, instinct motivators like perceived happiness, social factors and consumers' habits.The results of the study indicate that one's habits, external factors and instinct motivators exert a powerful influence on their online shopping behavior.Hernández et al.'s (2011) study "Age, gender and income: do they really moderate online shopping behavior?"analyzed whether individuals' socioeconomic characteristics -age, gender and income -influence their online shopping behavior.The individuals analyzed were experienced e-shoppers i.e. individuals who often make purchases on the internet.The results of their research show that socioeconomic variables moderate neither the influence of the previous use of the internet nor the perceptions of e-commerce; in short, they do not condition the behavior of experienced e-shoppers.Chen's (2009) dissertation "Online consumer behavior: an empirical study based on theory of planned behavior" extends the theory of planned behavior (TPB) by including ten important antecedents as external beliefs to online consumer behavior.The results of the data analysis confirm that perceived ease of use (PEOU) and trust are essential antecedents in determining online consumer behavior through behavioral attitude and perceived behavioral control.The findings also indicate that cost reduction helps the consumer create a positive attitude towards the purchase.Further, the findings show the effects of two constructs, flow concentration and telepresence, on the consumers' attitude.Concentration is positively related to the attitude towards purchase; however, telepresence is negatively related to the consumers' attitude due to nervousness or concern about uncertainty in the online environment.Demangeot & Broderick's (2007) research "Conceptualizing consumer behavior in online shopping environments" adopted a holistic approach to consider how consumers perceive online shopping environments.
The conceptual model proposes that consumers perceive these environments in terms of their sense-making and exploratory potential, and it considers the influence of these factors on user involvement with the website, shopping value and intention to revisit.The findings indicate that sense-making and exploratory potential are distinct constructs; exploratory potential mediates the relationship between sense-making potential and involvement.Furthermore, involvement is essential in producing shopping value and intention to revisit.Ying's (2006) study "Essay on modelling consumer behavior in online shopping environments" examined online H01.There is no significant relationship between the passenger's lifestyle and their decision to buy e-tickets either taken together or separately.
H02.There are no significant differences among passenger's lifestyle based on their demographic variables (age, gender, income, and level of learning).

Research Methodology
To test the main hypothesis of this research, a survey was conducted.The questionnaire was adopted and combined from many similar researches and used to collect the required data in order to support or reject the hypotheses.The data for this research was collected through a self-administrated questionnaire with 473 respondents.The unit of the study is the passengers who buy e-tickets.According to the Airport International Group's (AIG) a monthly statistical report, the number of all passenger in August/ 2014 increased to 785,600 passengers (www.aig.aero).The 2014 Annual Report by the Royal Jordanian Airline reports more than 700,000 passengers.The convenience sampling method was used in this study.Krejcie & Morgan (1970) suggested that for a population exceeding 100,000 units, a minimum sample size of 384 respondents is required to test the hypotheses at the 95% confidence level (resulting in a 5% probability of error).The sample size that could be collected is 473.A total 500 questionnaires were distributed by hand and mail.The survey contained 81 questions.There were six questions regarding demographic characteristics: age, gender, income, level of learning and other questions.It also contained questions about independent variables.They were 22 questions about Activities, 17 about Interests, and 20 questions about Opinions.

Data Analysis Techniques
For the analysis, the collected data was coded into SPSS Version 21.The analysis consists of several different statistical analyses and tests.Regression, multiple regressions, and hierarchical regression were used to analyze the variables.The primary data was analyzed by a variety of statistical techniques, such as regression analysis.Cronbach's alpha was used to determine the reliability though measuring the data's internal consistency.The recommended minimum acceptable limit of reliability (alpha) for this measure is (0.60).The results showed a value of 0.932for all items which is a reasonable value and indicates that the data is reliable for the purposes of this study.The result showed a value of (0.932) for the all items as well as alpha for each variable is greater than accepted present 0.60, which is a reasonable value indicating the tool consistency that enhanced its use for the study.Multicollinearity between the independent variables is also checked using the Collinearity statistics: Tolerance and Variance Inflation Factor (VIF).Tolerance is the amount of variance in an independent variable that is not explained by other independent variables.VIF measures how much the variance of the regression coefficient is inflated by multicollinearity.The minimum acceptable cutoff value for tolerance is typically (0.10).The maximum acceptable cut-off value for the VIF is (10).In other words, to indicate no problem with multicollinearity tolerance value should not be less than (0.10) while VIF value should not be more than (10) (Belsley, et al. 2005).Table (2) shows the VIF values for each independent variable is less than 10, with tolerance ranges between (0.486-0.583).This means that there is no multicollinearity.

Profile of the Respondents
The unit analysis of this study is an online shopper who purchases products and/or services online.The majority (around 83%) of the respondents were young, falling into the 15 to 35 age group, followed by those in the 35 to 44 group, which made up approximately10% of the total.The next largest group was the 45 to 55 age group, with 4.7%, followed by those in the 55 and above group (1.1%).Within this sample, the female respondents (46.1% of the total) were slightly outnumbered by the male respondents.The majority of the respondents had received higher education and had a bachelor degree (65%) or higher (13%).The study shows that this category of people was more familiar with the use of a personal computer, the internet, and purchasing through cyberspace.There is a possibility that they may have used the computer or internet for work-related activities.

Descriptive Statistics
Means and Standard Deviations are used to describe the respondents' lifestyle based on their activities, interests, and opinion.

Activities
Table 4 shows that the respondents expressed a high level of agreement with the questions relating to activities since the means for all activities (individual or combined) were higher than three and their standard deviations were lower than one.Among the activities variables it is found that Q (1) "I enjoy spending time with family and friends and social gatherings" has the highest mean, whereas, Q (15) "I prefer action and violent movies and series" has the lowest mean.This result may indicate that the majority of the respondents are more family orientated.

Interest
Table 5 indicates that there are negative attitudes towards Q (4, 5) because their means are less than mean of the scale (3), however, there are positive attitudes toward the rest of questions because their means are above the mean of the scale (3).The grand mean also reflects that there are positive attitudes towards all the questions regarding this variable.In addition, it found that Q ( 16) "I care about having internet access in my house" has the highest mean, whereas, Q (4) "I pay attention to advertisements sent via Email" has the lowest mean.

Opinion
Table 6 indicates that there are negative attitudes toward Q (18) because its mean is less than mean of the scale (3), however, there are positive attitudes toward the rest of questions because their means are above the mean of the scale (3).The grand mean also reflects that there are positive attitudes toward all the questions of this variable.In addition, Q (1) "I see that it is important to develop the countryside" has the highest means, whereas, Q (18) "Online news is completely real" has the lowest mean.

Hypotheses Testing
This section presents a statistical examination of the study's hypotheses.The main purpose for these tests is to identify whether to accept the formulated hypotheses.The tests were run at the 95% significance level; therefore, if the probability of the observed data is smaller than the level of significance then the data suggests the hypothesis should be accepted.Table 7 summaries the results of the multiple regression analysis with the F-ratio test for the first hypothesis.The multiple regression analysis technique is used to examine the first hypothesis.
Hypothesis 01: There is no significant relationship between the passenger's lifestyle and their decision to buyer-tickets either taken together or separately Table 7 and 8 summaries the results of the multiple regression analysis with the F ratio test for the above hypothesis.The results indicate that each hypothesis has a significant correlation with the decision to buy e-tickets with R=.618 at the .000level of significance.Accordingly, it may be concluded that there is a significant relationship between the independent variables (Activities, Interests, and Opinions) and the decision to buy e-tickets either taken separately or together.In addition, 38.2% of the variance (R-Square) in the e-ticket buying decision is explained by the independent variables (Activities, Interests, Opinions) taken together.Hypothesis 02 : There is no significant relationship between the independent variables (Activities, Interests, Opinions) and online purchasing decision for electronic services due to demographic variables (age, gender, income, and level of education).Table 8 summarizes the regression results for the second hypothesis.It shows that the relationship the between independent variables (lifestyle) and dependent variable (buying decision of e-tickets) is significantly influenced by the income of the passengers but not the other demographic variables (i.e., age, gender and education).This result indicates that the income of the passengers plays an important role in their lifestyle when they buy e-tickets.

Conclusions
The result supports the first hypothesis.Thus, the lifestyle factors positively influence the passengers' decision to purchase e-tickets when taken together or separately.This result is consistent with the previous studies on the marketing literature that consumer lifestyle is an important potential factor which influences the future behavior of consumers (Kim et al., 2000;Atchariyachanvanich & Okada, 2007;Krishnan & Murugan, 2007;Lee et al., 2009).According to this study's results, demographic characteristics such as age, education and gender do not influences the passengers' lifestyle with regards to purchasing e-tickets, however, their income does.This result might indicate that income plays an important role in the respondent's e-ticket buying decision.The results also show that the majority respondents focus on their family in their lifestyle.The trust in buying e-tickets vary from one country to another due to many reasons such as Consumer awareness, E-commerce infrastructure, Lack of secure electronic transaction compliance, National strategic telecommunications planning, Financial services and infrastructure.Moreover, there are other factors related to Social and psychological drawbacks such as Trust, Resistance to change, Generation gap, Security and Language barrier and Legislations, policies and business ethics (El Gawady, 2005;Sweidan et al., 2012;Bisharat & Mukattash, 2016;Darawsheh & ALshaar, 2016;Ammari et al., 2017;Khwaldeh et al., 2017).
The researchers would like to note the importance some of the demographic characteristics such as age and education as it has some influence in the real life.The age or (the Generation Gap) is important factor where younger consumers tend to use the latest technologies and application when booking an e-ticket meanwhile older consumers tend to use the traditional ways in booking and buying airlines tickets in Jordan.Moreover, the education factor (consumer Awareness) plays an important role as well because the new curriculums tend to focus on using the new technologies in their academic life as well as personal life's.Meanwhile, older consumers tend not trust such technologies.The resistance to change is the result of above problems among the older consumers compared to the young consumers.According to El Gawady (2005) resistance to change is one of the main drawbacks in any attempt to bring about any attempt to technology specifically when it is related to buying online.
In Jordan, the government has addressed some of above-mentioned concerns by setting new laws and legislations that addresses cybercrimes starting from financial penalties to life sentence person (Yaseen et al, 2015).Despite that, the situation in Jordan lacks for a specific national Information technology Policy for both public and private sectors.Moreover, the Jordanian government should encourage these sectors to develop a clear coordinated set of rules and policies that meets with its legislations.Security is a major issue and Jordan was ranked at the ninth place among the Middle East countries in terms of terms of cybercrimes threats.This was due to low-level percentage in buying e-ticket and to the few online transactions in general.Moreover, Jordanian users tend to lack a proper security systems and solutions because they lack the needed knowledge in that area (Obeidat et al., 2016a;Almajali et al., 2017;Yassien et al., 2017).Another issue needs to be addressed is the trust issue, Jordanians are a cash oriented and are afraid to use their credit cards when it comes to buy e-tickets or to buy online in general due to the fact that they don't see faces or physical items compared to the paper ticket when they buy it from authorized agent and the airlines offices (Yaseen et al, 2015).Moreover, the language obstacle issue that hinders the expansion of buying e-tickets as most of the websites is in English and these results in a big obstacle for natives Arabic consumers.
Several researchers consider the information systems and in particular the information technology (IT) and its flexibility as an enabler to achieve the desired competitive advantages, and as a crucial support to operational and strategic business decisions (Al Azmi et al., 2012;Alkalha et al., 2012;Altamony et al., 2012;Al-Dmour et al., 2015;Hajir et al., 2015;Kateb et al., 2015;Maqableh & Karajeh, 2014;Obeidat et al., 2016b;Shannak et al., 2010;Vratskikh et al., 2016); thus further research is required to examine the role of such IT applications in enhancing the managerial decisions.In addition, scholars (e.g.Alshurideh & Alkurdi, 2012;Kannan & Gharibeh, 2013;Masa'deh, et al. 2015;Masa'deh, et al. 2017;Obeidat, et al., 2012Obeidat, et al., , 2014;;Tarhini, et al., 2015;Al-Dmour et al., 2016, 2017) emphasize the need for large firms to integrate their IT systems with their KM strategies in order to survive in their highly competitive business environments, which in turn could accelerate the managerial decisions as well.In conclusion, this study extends the prior research on behavioral buying decisions by including lifestyle factors and contributes to the existing body of knowledge on online purchasing decisions within online services.I hope that the results of this study will provide insights for future research in this area.
Table (1)shows the Cronbach Alpha for each item in the questionnaire.

Table 3 .
Demographic Data of Respondents

Table 4 .
Mean and Standard Deviation for the Construct of the Activities

Table 5 .
Mean and Standard Deviation for the Construct of Interests

Table 6 .
Mean and Standard Deviation for the Construct of Opinions

Table 7 .
Summary Results of Multiple Regression for Hypothesis H01 and H02

Table 8 .
Results of the Interaction Regression Test for Hypothesis Two