Final Version
The impacts of employee motivation on e-service quality – An empirical study about hospitality industry in the Netherlands
Student Name: Xuan Zhu Student Number: 11641738 1st Supervisor: Erik Dirksen MSc. 2nd Supervisor: Prof. Dr. H. P. Borgman
Track: Master Business Administration – Digital Business
Statement of originality
This document is written by Student Xuan Zhu who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
As the literature gap stated, for e-service quality, most research focused only on its identification of detailed elements or on the interaction between customers and the website, missing the other potentially significant independent variables such as employee motivation. This thesis carried out an empirical study and investigated the impacts of employee motivation on e-service quality in the hospitality industry in Amsterdam, Netherlands.
The main research questions are: 1) What are the impacts of employee motivation on e-service quality in hospitality industry in the Netherlands? and 2) What is the most important element of e-service quality in the hospitality industry in the Netherlands? Through a secondary research of literature reviews of 48 academic articles, the complete theoretical framework and relevant hypotheses are developed. Next to that, the primary research, which is consisted of 2 questionnaire surveys, is conducted from May 30, 2018 to June 13, 2018, in three five-star hotels in Amsterdam: Pestana Amsterdam Riverside, Bilderberg Garden Hotel, and Renaissance Amsterdam Hotel. After analyzing the data, the positive influences of employee motivation on the e-service quality is confirmed, and the most important element of e-service quality in the hospitality industry in the Netherlands is Fulfillment.
Table of contents
INTRODUCTION ... 5
LITERATURE REVIEW ... 7
2.1TRADITIONAL SERVICE QUALITY ... 7
2.2E-SERVICE QUALITY ... 9
2.3EMPLOYEE MOTIVATION ... 11
2.4CONCEPTUAL FRAMEWORK AND HYPOTHESIS ... 15
METHODOLOGY ... 19
3.1SECONDARY RESEARCH ... 19
3.2PRIMARY RESEARCH... 22
3.2.1SURVEY 1 WITH QUESTIONNAIRE A ... 24
3.2.2SURVEY 2 WITH QUESTIONNAIRE B ... 32
3.2.3SAMPLE AND PROCEDURE ... 34
3.2.4MEASUREMENT OF VARIABLES ... 35
FINDINGS………...37
4.1INTRODUCTION... 37
4.2RELIABILITY CHECK ... 38
4.3SURVEY 1:E-SERVICE QUALITY ... 38
4.3.1FORMULAS ... 38
4.3.2RESULTS ... 39
4.4SURVEY 2:EMPLOYEE MOTIVATION ... 44
4.5RELATIONSHIP BETWEEN VARIABLES ... 48
4.5.1E-SERVICE QUALITY AND EMPLOYEE MOTIVATION... 49
4.5.2E-SERVICE QUALITY AND CUSTOMER SATISFACTION ... 51
4.6SUMMARY ... 52
CONCLUSION AND RECOMMENDATION ... 54
5.1CONCLUSION ... 54
5.2RECOMMENDATION ... 58
5.2.1ESTABLISH AN EFFECTIVE AND INCENTIVE REMUNERATION SYSTEM ... 59
5.2.2STRENGTHEN INTERNAL COMMUNICATION AND CREATE A RELAXED AND OPEN WORKING ENVIRONMENT ... 60
5.2.3PROVIDE CONTINUOUS TRAINING AND FAIR PROMOTION SYSTEM ... 60
REFERENCE ... 61
CHAPTER 1 Introduction
The rapid popularization of the Internet and online commerce have greatly facilitated people’s accessibility to get information in online shopping, such as the price comparison, brands overview, company disclosure, etc. In terms of the hospitality industry, hotels have quickly and effectively set up their own online websites, expecting to increase their visibility and improve brand images. According to a new survey from Hitwise, the number of online bookings accounts for about 30.56% of the total hotel booking volume from may 2016 to May 2017 in the United States (Schaal, 2017), showing the significance and urgency for hotels to build online channels.
Moreover, the instant price comparisons on the websites make non-price competitiveness, such as e-service quality, more vital than ever (Yang & Jun, 2002). According to Parasuraman, Zeithaml, and Malhotra (2005), e-service quality is defined as the extent to which a website facilitates efficient and effective shopping, purchasing, and delivery. Subsequently, e-service quality has two major components: namely Core Service Scale (E-S-QUAL) and Recovery Service Scale (E-RecS-(E-S-QUAL). E-S-QUAL includes Efficiency, System availability, Fulfillment, and Privacy, while E-RecS-QUAL contains Responsiveness, Compensation, and Contact (Parasuraman, Zeithaml, & Malhotra, 2005). Notice that E-RecS-QUAL is only salient when customers have non-routine interaction with the websites (Hsin, Wang, & Yang, 2009), for example, they have problems and need to consult the employees.
As prior literature mainly focused on the identification of e-service quality elements and (or) the interaction between customers and the website, this thesis aims to find the impacts of
employee motivation when hospitality industry attempts to increase e-service quality, as employees are the ones who are responsible for both E-S-QUAL elements (designing un-direct website service) and E-RecS-QUAL (offering un-direct interaction service), and employee motivation is the key for them to convey superior service quality continuously.
In Chapter 2 Literature Review, the author would present literature reviews, introducing relevant theories about traditional service quality and e-service quality, and addressing the literature gap in terms of the topic of the thesis: the relationship between employee motivation and e-service quality. The research questions, theoretical framework, and some hypotheses will be proposed at the end. In Chapter 3 Methodology, main methodologies of the dissertation are explained. In Chapter 4 Findings, the data from our applied methodologies will be analyzed and some insights will be discussed. In Chapter 5 Conclusion and Recommendation, the whole thesis is summarized and some recommendations for hotels are put forward.
CHAPTER 2 Literature Review
Whether for the tangible products or the intangible commodities, the service quality has been a trump card for enterprises to win the market competition. Over the years, the object of previous studies has shifted from traditional service quality to e-service quality slowly. As numerous papers have focused on traditional service quality and its relationship with other different variables (such as customer satisfaction, consumer behavior, customer loyalty, purchase intention, etc.), the attempts to study e-service quality are still limited in identifying and measuring e-service quality. Based on prior literature, this review would emphasize on the following steps: (1) introduce relevant theories about traditional service quality; (2) list acknowledged e-service quality identifications; (3) provide information about employee motivation and its connection with e-service quality. The research questions, theoretical framework, and some hypotheses will be proposed at the end.
2.1 Traditional service quality
The study of traditional service quality began in the late 1970s, and there are several recognized definitions about this term. Grönroos (1984) puts forward that the service quality is composed of the results’ quality (what kind of service the customers get) and process’ quality (how customers are served). On the basis of Grönroos’ concept, Rust and Oliver (1993) add the third composition: where customers receive the service. More over, Parasuraman, Zeithaml and Berry (1985) further develop Grönroos’ concept by defining service quality as the gap between customer expectation and customer perception. They systematically divide the service quality into five elements: Tangible, Reliability, Responsiveness, Assurance and Empathy. Tangible refers to service facilities, personnel and
other physical contacts with customers; reliability means the capability of this company to accurately fulfill its guaranteed service for customers; responsiveness indicates the ability of service employees to actively provide services; assurance is termed when employees are able to establish consumers trust and confidence; empathy is known as the care and concern for customers from the entity (Parasuraman, Zeithaml & Berry, 1985).
In addition, there is a wide range of measurement models for traditional service quality, including SERVQUAL (Parasuraman, Zeithaml & Berry, 1988), LODGSERV (Knutson et al., 1990), SERVPERF (Cronin & Taylor, 1994), DINESERY (Hasan & Subhani, 2011), HOLSERV (Wong, Dean, & White, 1999), etc., among which SERVQUAL is the most famous and the most recognized one. According to Parasuraman, Zeithaml and Berry (1988), by using a seven-point Likert scale ranging from ‘‘Strongly Agree’’ (7 points) to ‘‘Strongly Disagree’’ (1 point), SERVQUAL measures the Expectation Score and Perception Score of consumers, thus quantifying the service quality and giving managers insights about future improvements. Each Score part has the same 22 statements to measure all the five elements (Tangible, Reliability, Responsiveness, Assurance and Empathy), and five average sub service quality scores (the gaps between sub Expectation Score and sub Perception Score) will be gained at last. The smaller the score is, the better customer perception fits customer expectation, and the higher the service quality will be.
The significance of traditional service quality seems to be agreed by all the scholars. Up to now, a number of empirical researches have proved that traditional service quality increases consumer satisfaction, customer loyalty, future purchase intention, Word of Mouth, brand image and other competitive attributes in many industries including banking, hospitals, telecom, food, retailing, etc. (Suryani & Hendryadi, 2015; Meesala & Paul, 2016; Tang & To,
2015; Liu & Tsai, 2010; Chinomona, 2013). As the topic and theories have become gradually complete and perfected, more researchers notice the e-service quality when faced with the fast-growing e-commerce and the dramatic increase of online consumer base.
2.2 E-service quality
With the popularization of the internet commerce and online retailing, instant price comparisons on the website make non-price competitiveness, such as e-service quality, more vital than ever (Yang & Jun, 2002). Santo (2003) describes e-service quality as the overall customer evaluations and judgements about the excellence and quality of e-service delivery in the virtual markets. Parasuraman, Zeithaml, and Malhotra (2005) define e-service quality as the extent to which a website contributes to effective and efficient shopping, purchase, and delivery.
In addition to the basic definition of e-service quality, the exact identification of e-service quality elements has received much attention from the academia, and currently there is no commonly agreed measurement model for e-service quality (Schuster, 2015). Santo (2003) claims that e-service quality is made up of Incubative and Active parts. Incubative part consists of Ease of use, Appearance, Linkage, Structure, Layout and Content; while Active parts contains Reliability, Efficiency, Support, Communication, Security, and Incentives (Santos, 2003). Parasuraman, Zeithaml, and Malhotra (2005) create a basic scale named E-S-QUAL and a subscale called E-RecS-E-S-QUAL. On the one hand, E-S-E-S-QUAL will measure the e-service quality delivered by the website, including four elements: Efficiency, Fulfillment, System availability, and Privacy. On the other hand, E-RecS-QUAL will assess other three elements which are salient only when online customers have non-routine encounters with the website: Responsiveness, Compensation, and Contact. On the basis of E-S-QUAL (process
quality) and E-RecS-QUAL (recovery quality), Collier and Bienstock (2006) argue that an outcome quality should be added. In the meanwhile, Fassnacht and Koese (2006) perform a qualitative study and develop a broadly applicable and hierarchical model for e-service quality, containing environment quality, service delivery quality, and service product. Afterwards, Ding, Hu, and Sheng (2011) bring forward another measuring scale called E-SELFQUAL and separate e-service quality into perceived control, service convenience, customer service, and service fulfillment.
The benefits of e-service quality have also been studied. For instance, Lee and Lin (2005) confirm that the e-service quality affects customer satisfaction and in turn influences customer purchase intention. It is verified that improved e-service quality enhances customer satisfaction, behavioral intentions, website revisits, Word-Of-Mouth communication, trust building and repeated purchase (Gounaris, Dimitriadis, & Stathakopoulos, 2010; Kalia, Arora, & Kumalo, 2016; Yin & Ho, 2016).
Since this study concentrates on the e-service quality in the hospitality industry in the Netherlands, the author decides to choose the measurement scale of Parasuraman, Zeithaml, and Malhotra (2005). The reason behind the decision lies in that E-S-QUAL and E-RecS-QUAL clearly divide the e-service quality into website delivered and human delivered. In terms of E-S-QUAL, Efficiency means the convenience and ease to enter and use the website; Fulfillment signifies how the website’s promises about product availability and order delivery are fulfilled; System availability involves the technical performance of the site; Privacy connotes whether the website protect customers’ privacy and avoid information leak. In terms of E-RecS-QUAL, Responsiveness represents that customers’ issues can be handled and responded in time; Compensation suggests that the company or the website will compensate
customers for the problems they encounter; Contact stands for that the consumers can seek for assistance through phones, emails, or other online channels.
As it can be seen from above, so far, most research in e-service quality has mainly focused on the identification of e-service quality elements and the interaction between customers and the website (Schuster, 2015; Collier & Bienstock, 2006). However, no matter traditional service quality or e-service quality, the customer service employees are the bridge between the company and the customers. From the perspective of E-S-QUAL and E-RecS-QUAL, employees are the ones who design, support and maintain enterprise website, and who deliver recovery service quality such as communication and compensation.
2.3 Employee motivation
Although few studies have specifically and officially emphasized on the employees when discussing e-service quality, at least some insights can be gained from previous literatures. For example, Hennig-Thurau (2004) probes into the importance of service personnel in online shopping, revealing that employees’ characteristics including technical skills, social skills, and decision-making power, are a main determinant of service firms’ success. Similarly, Yee, Yeung, and Cheng (2010) found out the positive link between employee motivation and online service quality by doing a survey of 210 high-contact service shops in Hong Kong. Also, Lin and Hsieh (2011) raise that customer-employee interaction is vital, and employee motivation enhances customer perception of service quality when firms apply technology into its communication with customers. Besides, some papers verify that employee encouragement and motivation (includes employee appraisal, rewards, and recognition) is a crucial component to achieve high service quality and business excellence,
especially in service industries (Talib, et al. 2011; Mustak, Jaakkola, & Halinen, 2013; Talib, Rahman, & Qureshi, 2016; Slåtten, & Mehmetoglu, 2011).
As such, this study will focus on the employee motivation, since it has been proved that if employees have a clear vision of the importance of service to the companies and are motivated to deliver that quality, superior service quality will be achieved (Bowen, 1986; Hays, & Hill, 2001; Liao et al., 2009). At the same time, Aleven (2017) mentions that there is
a difference in perceptions of satisfaction and customer retention between the managers and the customers, because employees as the intermediary do not perfectly play their roles and communicate with the two parties, which in turns will lower the e-service quality. To solve this issue, it is necessary for managers to pay attention to the cultivation of high employee motivation in the online customer journey.
It is widely accepted that motivation is involved in start, direction, intensity and continuity of human behaviors, and enhanced employee motivation can be developed as a strategy to promote organizational performance (Ramlall, 2004). Given the large efforts to develop a strategy in big enterprise, it is rational to explore and understand basic motivation theories and the types of motivation. Well-known traditional and classic motivation theories include Maslow's Hierarchy of Needs, Herzberg's Hygiene-Motivational Factors, McClellan's achievements Theory, Douglas McGregor’s Theory X and Theory Y, etc. While there are five core theoretical and modern theories mainly focusing on the work motivation of employees: expectancy motivation, equity theory, goal-setting theory, job design, and self-determination theory (Grant & Shin, 2011).
For the types of employee motivation, here the thesis would adopt the formerly established employee motivation model, which parts employee motivation into six contributions: Achievement motivation, Affiliation motivation, Competence motivation, Power motivation, Incentive motivation, and Attitude motivation (Wiley, 1997; Sokolowski, et al. 2000; Ramlall, 2004).
Achievement motivation means the the willingness of an employee to seek career development and success. Individuals will satisfy their needs for success or the attainment of excellent through different methods, motivating by both internal and external reasons (Rabideau, 2005). The significance of achievement motivation is reflected in the expectancy motivation theory as well. According to expectancy motivation, workers choose to invest efforts by weighing their probabilities of achieving desired results (Grant & Shin, 2011), which is determined by three functions: expectancy, instrumentality, and valence. Higher the expectancy of their achievement needs is, more motivated employee will be and better results might be obtained. Also, Owusu-Yeboah (2012) proposes that, people with high achievement scores prefer to work independently and have a better promotion performance inside the organization or entrepreneurial development, since they are continuously seeking for self-breakthroughs and personal development.
Affiliation motivation denotes the ability of employees to work within social networks. When working in a group, a person always has the need to be included, involved, supported and to have a sense of belongings (Hill, 2009). Affiliation motivation is also highlighted as relatedness (feeling connected and belonged to others) out of three psychological needs to motivate employees in the self determination theory (Gagné & Deci, 2005). Also, in a study
of Liao et al., (2009), it is easier for employees with high affiliation motivation to establish long lasting relations with customers and retain returning customers.
Competence motivation refers to the competences or strengths of an employee to be far ahead in some activities. The mechanism behind competence motivation is that, when a person successfully manages an assignment, he or she will be further encouraged and more confident to finish another task (Elliot & Dweck, 2013). The goal setting theory analyzes competence motivation from a more contextual and realistic angle, and it believes that people who have achieved specific goals, especially moderately difficult ones, will aim to be more competitive in other fields and motivate high performance in the future (Locke & Latham, 2002). Competences can be built up through external factors such as learning and training, which provides an insight for modern companies who expect to meet the competence needs of employees (Sarkis, Gonzalez-Torre, & Adenso-Diaz, 2010).
Power motivation indicates the desire to gain power or to risk for power. The first concept of power motivation was identified by David McClelland in 1961, stating as a desire to control other people and seek for agreement and compliance (McClelland, 1979). The empirical researches of Xu, et al. (2012) and Maner & Mead (2010) confirmed the individuals with high power motivation have more possibility to become a leader in the teamwork.
Incentive motivation means that the consequences of activities will influence personal behaviors. This kind of motivation emerged during the 19th century, and proposes that people are pulled towards behaviors which brings rewards but are pushed away from actions which lead to negative results, such as punishment, fines, and dismissal. In simple words, the individuals are encouraged by rewards and will shrink back at bad outcomes. According to
equity theory (Adams & Freedman, 1976), employees are motivated when their inputs (e.g., efforts, skills, knowledge) are equal to outcomes (e.g., salaries, welfare, benefits). In addition, Herzberg (2008) also agreed with the positive influences of incentive motivation, and suggests that the enterprises can provide some extrinsic incentives to enhance employees’ enthusiasm.
Attitude motivation describes the influence of the attitudes on the person. The attitude may appear in the form as how people think and feel about themselves, lives, the working conditions, the job designs, etc. For example, in the Job design theory, Grant & Shin (2011) claim that job characteristic model contains three psychological stages: experienced meaningfulness, responsibility for outcomes, and knowledge of results. Consequently, people will have different emotions when they work on different jobs, thus the motivation degree differs too.
2.4 Conceptual Framework and Hypotheses
As stated above, the literature gap lies in that, for e-service quality, most research focused only on its identification of detailed elements or on the interaction between customers and the website, missing the other potentially significant independent variables such as employee motivation. This thesis would aim to carry out an empirical study and further investigate the impacts of employee motivation when companies try to extend online business and attempt to improve the e-service quality. The author will select hospitality industry as the research field, as hotels, whose business is much dependent on excellent service quality, are trying hard to adopt electronic platforms and conduct digital transformation to propaganda themselves during the Internet age. Accordingly, the research questions are listed as follows:
1) What are the impacts of employee motivation on e-service quality in hospitality industry in the Netherlands?
2) What is the most important element of e-service quality in the hospitality industry in the Netherlands?
To answer these questions, the following conceptual model is formulated and the hypothesis development will be explained below the model.
Conceptual Model
As discussed before, the definition and division of Parasuraman, Zeithaml, and Malhotra (2005) about e-service quality are adopted here. E-service quality is the extent to which a website contributes to effective and efficient shopping, purchase, and delivery, and consists of a basic scale named E-S-QUAL (Efficiency, Fulfillment, System availability, and Privacy) and a subscale called E-RecS-QUAL (Responsiveness, Compensation, and Contact). When it
comes to employee motivation, some insights about its positive influences on the e-service quality can be drew from or supported by previous literatures (Hennig-Thurau, 2004; Yee, Yeung, & Cheng, 2010; Lin & Hsieh, 2011). Therefore, H1 and H2 can be formulated as the positive relationships caused by employee motivation. Besides, this study also expects to compare the two scales on how they are affected by the employee motivation, thus H3a and H3b are proposed accordingly.
H1: Employee motivation improves the Core Service Scale (E-S-QUAL) of e-service quality. H2: Employee motivation improves the Recovery Service Scale (E-RecS-QUAL) of e-service quality.
H3a: Employee motivation has more influences on the Core Service Scale (E-S-QUAL) than on the Recovery Service Scale (E-RecS-QUAL).
H3b: Employee motivation has more influences on the Recovery Service Scale (E-RecS-QUAL) than on the Core Service Scale (E-S-(E-RecS-QUAL).
In addition, the benefits of e-service quality have provoked a heated discussion in academia. In this case, due to the limited time of a questionnaire survey, customer satisfaction is selected to be the index that measures the first impression and short-term happiness of the customers who visit the website shortly, evaluate the e-service quality quickly, and rate the degree to which the e-service meets their expectation. At the end of the questionnaire, participants will be required to express his or her satisfaction towards the website on a score from 1 to 10. Since many scholars agree with the idea that excellent e-service quality enhances customer satisfaction (Lee & Lin, 2005; Gounaris, Dimitriadis, & Stathakopoulos, 2010; Kalia, Arora, & Kumalo, 2016; Yin & Ho, 2016), this thesis assumes that:
H4: High Core Service (E-S-QUAL) scores lead to high customer satisfaction.
Furthermore, one of the research questions is to find out what are the most important elements of e-service quality in the hospitality industry in the Netherlands. For related literatures, Bauer, Falk and Hammerschimidt (2006) did a number of semi-structured interviews with customers who frequently shop online, and proposed that, from a marketing management point of view, the responsiveness should be paid a lot of attention to due to its utmost significance in predicting customers’ perceived value and customer satisfaction. According to Yang and Tsai (2007), they also operate an online survey to examine and validate the effectiveness of e-service quality, and reveal that fulfillment, efficiency, responsiveness and contact are the most important elements in influencing satisfaction and loyalty. However, as the industry differs, the focus of e-service quality might also be different. With a quantitative study, Collier and Bienstock (2006) argue that the recovery service scale, including Responsiveness, Compensation, and Contact, can contribute most to the design of e-service experience, thus increasing customer satisfaction. In the research of Zaverah et al. (2012), in the Internet Banking Services industry, it claims that only three elements of e-service quality are statistically significant and have great impacts on customer satisfaction: Privacy, System availability, and Efficiency. As the critical element of every industry might vary, this thesis aims to find the most vital component of e-service quality in the hospitality industry in the Netherlands. Therefore, following hypotheses are developed:
H6a: Efficiency is the most important element in improving customer satisfaction. H6b: Fulfillment is the most important element in improving customer satisfaction.
H6c: System availability is the most important element in improving customer satisfaction. H6d: Privacy is the most important element in improving customer satisfaction.
H6e: Responsiveness is the most important element in improving customer satisfaction. H6f: Compensation is the most important element in improving customer satisfaction.
H6g: Contact is the most important element in improving customer satisfaction. CHAPTER 3
Methodology
Aiming to find an optimized method to research the topic, this thesis combines secondary research and primary research. Through secondary research, the author collected a total number of 48 articles based on many criteria, and reviewed them to identify research questions and develop hypothesis. Based on the solid theoretical foundation set up by secondary research, a primary research which takes the form of questionnaire surveys and uses the quantitative analysis is designed subsequently.
3.1 Secondary research
Secondary research refers to the type of research that describes, discusses, interprets, analyzes, evaluates, summarizes the information of other people (Stewart, & Kamins, 1993). Since specific institutions and agencies in many countries have recorded and studied important national or regional statistics over years (Widaman, et al., 2011), the secondary research has been increasingly valued and adopted by many scholars in academic fields.
There are several reasons to use secondary research. Firstly, it is an ideal choice for scholars who expect to conduct comparative research, especially in chronological order (Kiecolt & Nathan, 1985). The data obtained by respected institutions usually cover a wide range of information, such as different times and places, and have become valuable evidences for researchers’ studies. Secondly, the secondary research offers researchers plentiful insights, such as how to replicate an empirical research, how to improve the validity of measurement tools, how to improve the the number of samples and the generalizability of the research, etc. Thirdly, it is economical to use secondary research. The practical large-scale investigation
often costs a large amount of money, manpower, and material resources, while the desk research can save the costs to a large extent (Kiecolt & Nathan, 1985).
Yet, there are several limitations of the secondary research. Above all, the data used in the secondary research is not completely collected for the same research subject as the user is studying, so the degree of relevance with the current research subject should be seriously considered (Cook, 1974). Posteriorly, sometimes the target data is not easy to obtain, and the researchers also need to pay a certain amount of money (Lefever, Dal, & Matthiasdottir, 2007). Lastly, some parts of the data might be incomplete and false, therefore affecting the validity of the whole study (Lefever, Dal, & Matthiasdottir, 2007).
For this thesis, the authors selected a certain number of previous papers, so as to gain some background information and research design insights. Utilized during the process, Table 1 shows the criteria the author adopted when choosing related journal articles.
Table 1. The Criteria for Choosing Secondary Data (Articles)
Criteria Details
Dependability Is the article published on respected academic journals or trusted websites? Currency Is the article up-to-date (ideally published within a decade)?
If not, did the article propose classical concepts, theories, or models?
Key words Service quality, e-service quality, employee motivation, customer satisfaction, hospitality industry, hotels, Netherlands, Core Service Scale (E-S-QUAL), Recovery Service Scale (E-RecS-QUAL), e-service quality measurement, employee motivation measurement, customer satisfaction measurement, e-service quality survey, etc.
Relevance Is the research question of the article similar to the research questions of this thesis?
Do the mentioned concepts mean the same with those of this thesis? Are the units of measurement the same with those of this thesis?
Accuracy Does the article contain errors in research design, sampling, data collection, analysis, and discussion?
Are the results reasonable and logical? Cost Is the cost of data acquisition worth it?
Following Table 1, a total number of 48 articles were collected and referred to, and they are already discussed in Chapter 2. Literature Review. After evaluating dependability, currency, key words, relevance, accuracy, and cost, the author identified what are the research gap and research questions, how the study will be developed, and what methodology should be applied. As a result, upon the solid foundation set up by the secondary research, a primary research completely fitting with the thesis is designed subsequently.
3.2 Primary research
While the secondary research indicates the interpretation of other people’s data, such as biographies, newspapers, and journal articles, primary research is crucial in presenting the opinions or information through the firsthand investigation of the author himself or herself (Glass, 1976). In most cases, in primary research, the author needs to conduct a survey or an experiment to obtain data for his or her own research project, thus gaining more accurate and evident findings. In other words, the data of a primary research do not exist in readymade written form, but only will be created by people. Example of primary resources can be census data, interviews, questionnaires, audio and video records, opinion polls, experiments, speeches, pieces of creative writing, historical and legal documents, internet communications, etc. (De Lusignan, & Van Weel, 2005).
When collecting primary data, researchers can collect specifically for their own needs, can define the scope of their own data, and can exclude the impact of certain unrelated factors. Here, the primary research method for this thesis is questionnaire surveys, and quantitative analysis will be applied to cope with the data. There are several reasons why the questionnaire surveys are chosen. Firstly, the results of a questionnaire are easy to quantify if the design is good, which is convenient for statistical processing and analysis (Ilieva, Baron, & Healey, 2002). Currently, a large number of related statistical analysis software can help to do data analysis, and some of them can even directly help to design the questionnaire, which facilitates data mining to a great degree. Secondly, it is impossible for any individual, either a researcher or an investigator, to put subjective prejudice and biases into the study, because the form, order, and type of answers of the investigation question in a structured survey are all fixed (Church, & Waclawski, 2017). Thirdly, the electronic questionnaire nowadays
overcomes the barriers of time and space, leading to more flexible information collection process. Besides, electronic questionnaire has lower cost and large scale, can be sent out and retrieved via websites and email, is easier for adjustment and modification, and can be directly coded as data in the back end (Wright, 2005).
Whereas, there are also some limitations for the questionnaire survey. Primarily, the design of questionnaires, without doubts, is difficult. The quality of the main content of the questionnaire will directly affect the value of the entire survey. For example, different people might have different interpretations for the same question, and controlling the reliability and validity of a questionnaire requires the researcher to have rich experience in designing survey materials (Gillham, 2008). Next to that, the results of a survey tend to be broad but shallow (Ganassali, 2008). As questionnaire is a way to use text to communicate with people, the respondents will be upset of there are too many questions or the questions are hard to understand. Therefore, the general questionnaires are relatively brief, making it impossible to further investigate a certain topic with the audience. Subsequently, questionnaire surveys are usually done by the users themselves, so the quality of survey results is not guaranteed (Wright, 2005). For instance, the researchers have no idea about whether is the real target group filling in the survey (often some people pretend to be the target group because they want to get rewards for participating in the survey), if is there any person influencing the participant’s response (the participant might discuss with someone to fill out the form), or whether is the participant scribbling with the questionnaire, etc. Last but not least, sometimes the response rate is very low, especially when the researcher chooses to do an online survey (Shih, & Fan, 2008). The author must have a certain number of valid questionnaires, otherwise the representation of the data will be a problem. The response rate is influenced by
factors such as the length of questionnaire, the degree of difficulty of the questions, whether privacy issues are involved, how much the reward the respondents will get, and so on.
To resolve the dispute, a pilot study will be conducted after the first-version questionnaire comes out and before the formal large-scale survey starts (Schade, 2015). The pilot study is a small experiment which usually consists of a sample of 20 to 30 people, and would reveal the deficiencies in the proposed designs or procedures. In this thesis, the pilot study will point out how the questions should be modified, how can the confusing and misleading language of the text be revised, what is the expected response rate, and in what ways can people more positively respond to the survey.
3.2.1 Survey 1 with Questionnaire A
Combining the characteristics of the hospitality industry and the original E-S-QUAL assessment model developed by Parasuraman, Zeithaml, and Malhotra in 2005, the Survey 1 is designed to measure the scores of seven e-service quality elements (Efficiency, System availability, Fulfillment, Privacy, Responsiveness, Compensation, and Contact). The primary research objects include three five-star hotels in Amsterdam: Pestana Amsterdam Riverside, Bilderberg Garden Hotel, and Renaissance Amsterdam Hotel. These three hotels are recognized places on travel and trip websites, and all have their own websites for better service.
In Questionnaire A, respondents are going to review the three hotels’ websites. For each hotel, there are 20 statements evaluating 7 e-service quality elements, and 1 separate question asking about the overall customer satisfaction score at the end. On the one hand, for each statement, the respondents can rate the hotel’s e-service quality in 3 scores: Expected Score,
Perception Score, and Degree of Importance. Expected Score means how good the respondent expects the e-service quality to be before visiting the website; Perception Score indicates that how good the respondent feels about the e-service quality after visiting the website; Degree of Importance is termed as to what the extent does the statement matter to the respondent. The three scores will be gained through a use of a Likert score scale, ranging from Very Low (1), Low (2), Medium (3), High (4), Very High (5). On the other hand, for the separate question, the respondent will also use the Likert score scale to give an overall customer satisfaction score towards the website. At the end of the Questionnaire A, for each hotel, 1 average Customer Satisfaction Score, 7 average Expectation Scores, 7 average Perception Scores, and 7 average Degree of Importance Scores will be collected.
Table 2 is about Efficiency, which means the convenience and ease to enter and use the website (Parasuraman, Zeithaml, & Malhotra, 2005). For each hotel, there are 3 statements adapted from 8 original ones: EFF1. Information at this site is well-organized and I can easily find what I need; EFF2. This site is well organized and simple to use, and I can get anywhere on the site; EFF3. I can load the pages fast and finish whatever I want to do quickly.
Table 2: Statements for the Element ‘Efficiency’
Item Original Statement Item (New) Questionnaire A Statement EFF1 This site makes it easy to
find what I need.
EFF1 Information at this site is well-organized and I can easily find what I need.
EFF4 Information at this site is well organized.
EFF2 It makes it easy to get anywhere on the site.
EFF2 This site is well organized and simple to use, and I can get anywhere on the site. EFF6 This site is simple to use.
EFF8 This site is well organized. EFF3 It enables me to complete a
transaction quickly.
EFF3 I can load the pages fast and finish whatever I want to do quickly. EFF5 It loads its pages fast.
EFF7 This site enables me to get on to it quickly.
Source: Parasuraman, Zeithaml, & Malhotra (2005)
Table 3 is about System Availability, which stands for the technical performance of the site (Parasuraman, Zeithaml, & Malhotra, 2005). Here it is assessed by 3 statements as well: SYS1. This site is always available for business and services; SYS2. This site launches and runs right away; SYS3. This site does not crash even if I enter some information.
Table 3: Statements for the Element ‘System Availability’
Item Original Statement Item (New) Questionnaire A Statement SYS1 This site is always available
for business.
SYS1 This site is always available for business and services.
SYS2 This site launches and runs right away.
SYS2 This site launches and runs right away.
SYS3 This site does not crash. SYS3 This site does not crash even if I enter some information.
SYS4 Pages at this site do not freeze after I enter my order information.
Source: Parasuraman, Zeithaml, & Malhotra (2005)
Table 4 is about Fulfillment, which signifies how the website’s promises about product availability and order delivery are fulfilled (Parasuraman, Zeithaml, & Malhotra, 2005). Customers will get the following 3 criteria: FUL1. This site offers truthful services as it promises; FUL2. The site gives feedbacks very quickly; FUL3. The services are always successfully delivered (e.g. booking a room).
Table 4: Statements for the Element ‘Fulfillment’
Item Original Statement Item (New) Questionnaire A Statement FUL1 It delivers orders when
promised.
FUL1 This site offers truthful services as it promises.
FUL6 It is truthful about its offerings.
FUL7 It makes accurate promises about delivery of products. FUL2 This site makes items
available for delivery within a suitable time frame.
FUL2 The site gives feedbacks very quickly.
FUL3 It quickly delivers what I order.
FUL4 It sends out the items ordered. FUL3 The services are always successfully delivered (e.g. booking a room). FUL5 It has in stock the items the
company claims to have.
Source: Parasuraman, Zeithaml, & Malhotra (2005)
Table 5 is about Privacy, which connotes whether the website protect customers’ privacy and avoid information leak (Parasuraman, Zeithaml, & Malhotra, 2005). Currently there are 3 assessment standards: PRI1. This site protects information about my web-shopping behavior;
PRI2. This site will not leak my personal information to others; PRI3. The online transaction at this site is safe.
Table 5: Statements for the Element ‘Privacy’
Item Original Statement Item (New) Questionnaire A Statement PRI1 It protects information about
my Web-shopping behavior.
PRI1 This site protects information about my web-shopping behavior.
PRI2 It does not share my personal information with
other sites.
PRI2 This site will not leak my personal information to others.
PRI3 This site protects information about my credit card.
PRI3 The online transaction at this site is safe.
Source: Parasuraman, Zeithaml, & Malhotra (2005)
Table 6 is about Responsiveness, which represents that customers’ issues can be handled and responded in time (Parasuraman, Zeithaml, & Malhotra, 2005). It can be measured by 3 parts: RES1. This site provides return services and convenient return options; RES2. This site offers a meaningful guarantee for consumers’ interests and rights; RES3. This site responds to problems promptly and gives clear instructions upon issues.
Table 6: Statements for the Element ‘Responsiveness’
Item Original Statement Item (New) Questionnaire A Statement RES1 It provides me with convenient
options for returning items.
RES1 This site provides return services and convenient return options.
RES2 This site handles product returns well.
RES3 This site offers a meaningful guarantee.
RES2 This site offers a meaningful guarantee for consumers’ interests and rights. RES4 It tells me what to do if my
transaction is not processed.
RES3 This site responds to problems promptly and gives clear instructions upon issues. RES5 It takes care of problems
promptly.
Source: Parasuraman, Zeithaml, & Malhotra (2005)
Table 7 is about Compensation, which suggests that the company or the website will compensate customers for the problems they encounter (Parasuraman, Zeithaml, & Malhotra, 2005). Compensation contains only 2 sections: COM1 This site compensates me for problems it creates (e.g. wrong information post, order cancelation, overlapping reservation, etc.); COM2. This site compensates me when the hotel price drops sharply in a short period of time.
Table 7: Statements for the Element ‘Compensation’
Item Original Statement Item (New) Questionnaire A Statement COM1 This site compensates me for
problems it creates.
COM1 This site compensates me for problems it creates (e.g. wrong information post, order cancelation, overlapping
reservation, etc.) COM2 It compensates me when what
I ordered doesn’t arrive on time.
COM2 This site compensates me when the hotel price drops sharply in a short period of time.
COM3 It picks up items I want to return from my home or business.
N/A N/A
Source: Parasuraman, Zeithaml, & Malhotra (2005)
Table 8 is about Contact, which refers to that the consumers can seek for assistance through phones, emails, or other online channels (Parasuraman, Zeithaml, & Malhotra, 2005). Contact has three attributes: CON1 This site provides various channels for customers to communicate with the company; CON2. This site or its channels have customer service representatives available online; CON3. This site offers the ability to speak to a live person if there is a problem.
Table 8: Statements for the Element ‘Contact’
Item Original Statement Item (New) Questionnaire A Statement CON1 This site provides a telephone
number to reach the company.
CON1 This site provides various channels for customers to communicate with the company.
CON2 This site has customer service representatives
available online.
CON2 This site or its channels have customer service representatives available online.
CON3 It offers the ability to speak to a live person if there
is a problem.
CON3 This site offers the ability to speak to a live person if there is a problem.
Source: Parasuraman, Zeithaml, & Malhotra (2005)
3.2.2 Survey 2 with Questionnaire B
While Survey 1 focuses on the customer side, Survey 2 emphasizes on the employees’ angle. The Questionnaire B is made up of another group of judgmental statements, and will measure six motivation scores of the website customer service employees of the three five-star hotels we mentioned in Amsterdam: Pestana Amsterdam Riverside, Bilderberg Garden Hotel, and Renaissance Amsterdam Hotel.
In Questionnaire B, for employees in each hotel, they will measure 15 items covering 6 types of employee motivation (Achievement motivation, Affiliation motivation, Competence motivation, Power motivation, Incentive motivation, and Attitude motivation). For each item, they need to come to two scores: Motivation Degree and Satisfaction Degree. Motivation Degree means how the item motivates the employee, while Satisfaction Degree means how the employee is truly motivated by this item in this hotel. The same Likert score scale is utilized here as well, ranging from Very Low (1), Low (2), Medium (3), High (4), Very High (5). At last, for each hotel, 6 elements’ Motivation Degree scores and Satisfaction Degree scores will be gained.
In detail, the Achievement motivation (the willingness of an employee to seek career development and success) is measured by 3 items: (1) Clear career identification and great career prospects; (2) The possibility of inspiring individual potential and encouraging better performance; (3) The sense of fulfillment after finishing tasks and making certain contributions. The Power motivation (the desire to gain power or to risk for power) is appraised by (4) A reasonable staff promotion system which enables achievable equal promotion chances; (5) A certain degree of decision-making power; (6) The power of leading and influencing others and even the company. The Competence motivation (the competences or strengths of an employee to be far ahead in some activities) is gauged by (7) Available training programs provided by the organization to develop more skills and (8) High ranks in performance assessment. The Affiliation motivation (the ability of employees to work within social networks) is judged by (9) Good communication and relationships with colleagues and superiors; (10) Comfortable and relaxed working atmosphere; (11) Respects, praises and recognition from others (colleagues, superiors, clients, etc.) Incentive motivation (the rewards
that influences personal behaviors) is assessed by (12) Competitive and fair salaries the hotel provides and (13) Extra bonuses and welfare benefits the hotel offers. Attitude motivation (the influence of the attitudes on the person) is valued by (14) Resonance with the corporate culture and (15) Pleasure in the job itself.
3.2.3 Sample and procedure
The surveys of this thesis will be conducted in three five-star hotels in Amsterdam: Pestana Amsterdam Riverside, Bilderberg Garden Hotel, and Renaissance Amsterdam Hotel. As for the sampling technique, non-probability sampling is chosen for this thesis, so the author can draw a sample based on his or her own convenience or subjective judgment (Vehovar, Toepoel, & Steinmetz, 2016). Due to the fact that these two surveys would take much time, the author will choose the Snowball sampling method. For Survey 1 with Questionnaire A, a number of people with the required characteristics (such as the Master students at UvA) will be surveyed to evaluate the e-service quality of these hotel websites firstly, and then they can recommend other qualified respondents to participate in the study as well. For Survey 2 with Questionnaire B, the author would contact the online service employees of these hotels, and they can persuade other colleagues into participating in the study further.
The expected sample size is 180 for Survey 1 with Questionnaire A, and 45 for Survey 2 with Questionnaire B. A pilot study which contains 11 persons was conducted at the beginning to predict potential response rate and to correct some mistakes and misunderstandings in the questionnaires. After that, the formal surveys were started to collect related data for the analysis part. From May 30, 2018 to June 13, 2018, for Survey 1, 612 pieces of Questionnaire A were sent out to UvA master students, the authors’ acquaintances and alumnus in both Netherlands and China, and some online forums. At the end, 167 valid questionnaires were
recovered, and the response rate is 27.29%. For Survey 2, 89 pieces of Questionnaire B were sent to employees who work in the three object hotels through Facebook, LinkedIn, Instagram, Hotel contact lines and email. Eventually, 36 pieces of questionnaire B were received, and the response rate is 40.45%.
3.2.4 Measurement of variables
In Survey 1, for each hotel, 1 average Customer Satisfaction Score, 7 average Expectation Scores, 7 average Perception Scores, and 7 average Degree of Importance Scores will be gained. Notice that E-service quality Score is the difference between Perception Score and Expectation Score. The detailed statistics format will be shown in Table 9.
Table 9: Variables in Survey 1 Elements Expectation Score Perception Score E-service quality Score Importance Score Efficiency System availability Fulfillment Privacy Responsiveness Compensation Contact Customer Satisfaction Score
In Survey 2, similarly, for each hotel, there are 6 average Motivation Degrees and 6 average Satisfaction Degrees. The detailed statistics format will be shown in Table 10.
Table 10: Variables in Survey 2
Elements Motivation Score Satisfaction Score
Achievement motivation Affiliation motivation Competence motivation Power motivation Incentive motivation Attitude motivation
Once the author gets the whole dataset, data analysis can be conducted to find whether there is an obvious relationship between e-service quality and employee motivation. Besides, the most important element of e-service quality for hospitality industry in Amsterdam will be found out. Eventually, the thesis will propose recommendations to these hotels, indicating which part of employee motivation can be improved in the future to contribute to higher e-service quality.
Chapter 4 Findings 4.1 Introduction
As described in the Methodology Chapter, the two separate surveys were conducted from May 30, 2018 to June 13, 2018. Three luxurious hotels in Amsterdam are chosen: Pestana Amsterdam Riverside, Bilderberg Garden Hotel, and Renaissance Amsterdam Hotel. On the one hand, Survey 1 with Questionnaire A invited people to evaluate and rank different items which actually represent e-service quality elements by the use of a five-score Likert scale, and asked them to give a final customer satisfaction score on the basis of how good the customer experience that they perceived is. On the other hand, Survey 2 with Questionnaire B contacted the online service employees of these three hotels through Facebook, LinkedIn, Instagram, hotel contact lines and email. In the end, for Survey 1, 612 pieces of Questionnaire A were sent out to UvA master students, the authors’ acquaintances and alumnus in both Netherlands and China, and some online forums. 167 valid questionnaires were recovered, and the response rate is 27.29%. For Survey 2, 89 pieces of Questionnaire B were sent to employees who work in the three object hotels through Facebook, LinkedIn, Instagram, Hotel contact lines and email. Eventually, 36 pieces of questionnaire B were
received (13 from Pestana Amsterdam Riverside, 11 from Bilderberg Garden Hotel, and 12 from Renaissance Amsterdam Hotel), and the response rate is 40.45%.
This chapter aims to explore the data that were obtained from the surveys. Firstly, the author will perform the reliability check, and calculate the Cronbach’s alpha of the data in SPSS. Secondly, Quantitative analysis is applied to proceed the statistics, such as scatterplots, linear regression and correlation coefficients. Finally, as more features of the data reveal, our hypotheses can be accepted or rejected, contributing to the next chapter: discussion and conclusion.
4.2 Reliability check
A reliability test is conducted to examine the consistency of measurements. In this thesis, the reliability test was performed for our six variables: Expectation Score, Perception Score, Importance Score, Customer Satisfaction Score, Motivation Degree, and Satisfaction Degree. Luckily, the results from those two surveys showed that all the variables have a high level of internal consistency (Cronbach’s alpha > 0.7).
4.3 Survey 1: E-service quality 4.3.1 Formulas
This section analyzes the data from 167 questionnaires from Survey 1. Based on the original E-S-QUAL assessment model developed by Parasuraman, Zeithaml, and Malhotra in 2005, questionnaire A collects the scores for 7 elements of e-service quality in 3 hotels: Efficiency (measured by Item 1, 2, 3), System availability (measured by Item 4, 5, 6), Fulfillment (measured by Item 7, 8, 9), Privacy (measured by Item 10, 11, 12), Responsiveness (measured by Item 13, 14, 15), Compensation (measured by Item 16, 17), and Contact
(measured by Item 18, 19, 20). For convenience, Pestana Amsterdam Riverside, Bilderberg Garden Hotel, and Renaissance Amsterdam Hotel here are referred to Hotel 1, Hotel 2 and Hotel 3.
According to Parasuraman, et al. (1985), the difference between Perception Score and Expectation Score is the value of service quality. Therefore, the formula below shows how the e-service quality is calculated in this thesis:
ESQ = PS - ES
Next to that, the Degree of Importance of each element can be gained by the following equation. Here, ‘n’ denotes the serial number of the seven elements. If n equals 1, 𝐷𝐷𝐷𝐷1 represents the Degree of Importance of the first element – Efficiency; if n equals 2, 𝐷𝐷𝐷𝐷2 stands for the Degree of Importance of System availability; and so forth. Besides, ‘i’ refers to the item number and ‘xn’ means that how many items are measured for this element.
𝑫𝑫𝑫𝑫𝒏𝒏=𝒙𝒙𝒏𝒏𝟏𝟏 ∑ 𝑫𝑫𝑫𝑫𝒊𝒊
4.3.2 Results
At the beginning of the survey 1, participants are required to write down their expectations (ES) for each item for a five-star hotel in Amsterdam. Then, compared to the expectation standards, they begin to assess the websites of Hotel 1, Hotel 2 and Hotel 3, and rate those items for each hotel by their perception (PS). At the end, participants also give the degree of how important each item is (DI).
A key concept about the e-service quality value should be noticed. The goodness or badness of the variable can only be judged when comparing customer perception and customer
expectation. As a result, 0 is the critical value that distinguishes positive and negative e-service quality. A positive score indicates good e-e-service quality, while a negative score indicates a poor one. Furthermore, bigger the value of importance score is, more important of the element will be. Applying the formulas mentioned above, results in the three hotels are displayed in tables.
Table 11. E-service quality in Hotel 1 (Pestana Amsterdam Riverside) Elements Expectation Score Perception Score E-service quality Score Importance Score Efficiency 4.39 4.45 0.06 4.24 System availability 4.19 4.29 0.10 4.39 Fulfillment 4.18 4.36 0.18 4.69 Privacy 4.27 4.22 -0.05 4.44 Responsiveness 4.40 4.25 -0.15 4.48 Compensation 4.22 4.01 -0.21 4.07 Contact 4.16 4.16 0 4.32 Average 4.26 4.25 -0.01 4.38 Customer Satisfaction Score 4.66
The Expectation Score and the Importance Score of the survey are fixed. The elements, which customers expect hotels to have a good performance most, are ranked as
Responsiveness, Efficiency, Privacy, Compensation, System availability, Fulfillment, and Contact. Nevertheless, the importance rank is not the same as the expectation rank. Customers view Fulfillment, Responsiveness, and Privacy most significant, and the followings are System availability, Contact, Efficiency, and Compensation. One reason behind this difference lies in that, people tend to adjust their expectations based on their real-life experience. For example, because of privacy leak risk, they expect the hotel to protect their privacy more. The other reason is that people are also inclined to have a preference for elements that contribute to a smooth purchasing process, when they have great purchase intent. For instance, they expect the efficiency of the website to be very good when purchasing, but rank this element as not so important when compared to other parts of the process. As a consequence, we can conclude that four elements, including Fulfillment, Responsiveness, Privacy, and Efficiency are critical when enhancing a hotel’s e-service quality.
As demonstrated in Table 11, the overall e-service quality score of Hotel 1 is -0.01, signifying that the customers’ experience on the website just fits what they expected before. Hotel 1 achieves positive results in Efficiency, System Availability, and Fulfillment; negative results in Privacy, Responsiveness, and Compensation; and neutral result in Contact. Hotel 1’s customer satisfaction score is high: 4.66 out of 5.
Table 12. E-service quality in Hotel 2 (Bilderberg Garden Hotel)
Elements Expectation Score Perception Score E-service quality Score Importance Score Efficiency 4.39 4.03 -0.36 4.24 System availability 4.19 3.92 -0.27 4.39
Fulfillment 4.18 4.34 0.16 4.69 Privacy 4.27 4.16 -0.11 4.44 Responsiveness 4.40 4.12 -0.28 4.48 Compensation 4.22 3.98 -0.24 4.07 Contact 4.16 4.04 -0.12 4.32 Average 4.26 4.08 -0.18 4.38 Customer Satisfaction Score 4.15
Different from Hotel 1, Hotel 2 got a negative score finally: -0.18. It only does well in the element Fulfillment, while all the e-service quality scores of other elements are negative. As a consequence, the customer satisfaction score is also lower than the previous one: only 4.15 out of 5. From the negative metrics, it can also be inferred that the Hotel 2 should urgently strengthen or improve elements like Efficiency, System availability, Responsiveness, and Compensation.
Table 13. E-service quality in Hotel 3 (Renaissance Amsterdam Hotel)
Elements Expectation Score Perception Score E-service quality Score Importance Score Efficiency 4.39 4.20 -0.19 4.24 System availability 4.19 4.01 -0.18 4.39 Fulfillment 4.18 4.15 -0.03 4.69 Privacy 4.27 4.21 -0.06 4.44 Responsiveness 4.40 4.56 0.16 4.48
Compensation 4.22 4.09 -0.13 4.07 Contact 4.16 3.98 -0.18 4.32 Average 4.26 4.17 -0.09 4.38 Customer Satisfaction Score 4.39
The e-service quality of Hotel 3 is between Hotel 1 and Hotel 2. It gained -0.09, with only positive result in Responsiveness. The customer satisfaction score is also ranked the second place: 4.39 out of 5. From the negative figures, the most urgent weaknesses of Hotel 3 should be Efficiency, System availability and Contact. Combining all the statistics in three hotels, the averaged e-service quality can be gained. Notice that in the Questionnaire A, 7 Expectation Scores and 7 Importance Scores were only asked once so they are always the same. While for Perception Scores, we choose the average one. For example, the final Perception Score Efficiency (PSE) = (PES Hotel 1 + PES Hotel 2 + PES Hotel 3)/3.
Table 14. Averaged E-service Quality
Elements Expectation Score Perception Score E-service quality Score Importance Score Efficiency 4.39 4.23 -0.16 4.24 System availability 4.19 4.07 -0.12 4.39 Fulfillment 4.18 4.28 0.10 4.69 Privacy 4.27 4.20 -0.07 4.44 Responsiveness 4.40 4.31 -0.09 4.48 Compensation 4.22 4.03 -0.16 4.07 Contact 4.16 4.06 -0.10 4.32
Average 4.26 4.17 -0.09 4.38 Customer
Satisfaction Score
4.40
As we said before, on the whole, the four elements (Responsiveness, Efficiency, Privacy, and Fulfillment) are very important to hotels if they want to improve the e-service quality results. From the averaged figures, the luxurious hotels in Amsterdam only have positive E-service quality score for Fulfillment, basically meeting the customer expectation. Hence, they need to emphasize more on the Efficiency, Privacy and Responsiveness parts.
4.4 Survey 2: Employee motivation
This section analyzes the data from 36 questionnaires from Survey 2 (13 from Hotel 1, 11 from Hotel 2, and 12 from Hotel 3). Questionnaire B collects the scores for 6 types of employee motivation in 3 hotels: Achievement motivation (measured by Item 1, 2, 3), Power motivation (measured by Item 4, 5, 6), Competence motivation (measured by Item 7, 8), Affiliation motivation (measured by Item 9, 10, 11), Incentive motivation (measured by Item 12, 13), and Attitude motivation (measured by Item 14, 15).
With the five-point Likert measurement scale, employees in those three hotels can fill any of the five digits in the Motivation Degree column and the Satisfaction Degree column. The results are exhibited in the Table 15, 16, 17 respectively.
Table 15. Employee Motivation in Hotel 1 (Pestana Amsterdam Riverside) Motivation Degree Satisfaction Degree
Power motivation 4.46 4.17 Competence motivation 4.23 4.32 Affiliation motivation 4.37 4.04 Incentive motivation 4.54 3.98 Attitude motivation 3.92 4.21 Average 4.35 4.14
As can be seen from the table, for motivation degree, employees in Hotel 1 attach most importance to Achievement motivation, Incentive motivation and Power motivation. Yet, what they actually felt within the hotel is not what they imagined. From the satisfaction degree, employees are satisfied by Competence motivation, Attitude motivation, and Power motivation. In a deeper level, Hotel 1 does not provide enough career development opportunities and rich material incentives, but indeed creates a competitive working environment for employees. This issue should be addressed otherwise there will be conflicts in the long run.
Table 16. Employee Motivation in Hotel 2 (Bilderberg Garden Hotel) Motivation Degree Satisfaction Degree
Achievement motivation 4.22 4.05 Power motivation 4.54 4.02 Competence motivation 3.94 4.24 Affiliation motivation 4.25 3.84 Incentive motivation 4.63 3.69 Attitude motivation 3.38 4.20 Average 4.16 4.01
For Hotel 2, employees there claim that they can be most motivated by Incentive motivation, Power motivation and Affiliation motivation. The gap between expectation and reality is also big. In fact, they are satisfied most with the Competence motivation and Attitude motivation, while what motivations they think highly of all have lowest scores in the satisfaction rank: Incentive motivation (3.69), Power motivation (4.02), and Affiliation motivation (3.84). Hence, it is deduced that Hotel 2 does not pay a satisfactory amount of wage, does not own a fair and achievable promotion system which will maximize power motivation, and does not possess a very harmonious and cheerful working condition.
Table 17. Employee Motivation in Hotel 3 (Renaissance Amsterdam Hotel) Motivation Degree Satisfaction Degree
Achievement motivation 4.43 3.95 Power motivation 4.19 3.82 Competence motivation 4.08 4.50 Affiliation motivation 4.31 4.47 Incentive motivation 4.42 3.78 Attitude motivation 3.89 4.14 Average 4.22 4.11
When it comes to Hotel 3, employees are inspired by Achievement motivation, Incentive motivation and Affiliation motivation. Apart from Affiliation motivation, Hotel 3 fails in the other two motivations. It also does a good job in fulfilling Competence motivation and
Attitude motivation. Thus the main problem of this hotel should be the lack of career development opportunities and rich material incentives.
Table 18. Averaged Employee Motivation Motivation Degree Satisfaction Degree Difference Achievement motivation 4.41 4.04 -0.37 Power motivation 4.40 4.00 -0.40 Competence motivation 4.08 4.35 0.27 Affiliation motivation 4.31 4.12 -0.19 Incentive motivation 4.53 3.82 -0.71 Attitude motivation 3.73 4.18 0.45 Average 4.24 4.09 -0.15
Taken those scores in Table 15, Table 16 and Table 17 together, we get the averaged employee motivation scores for all the hotels. It can be noticed that personnel in these three
luxurious hotels think a great deal of Incentive motivation, Achievement motivation, Power motivation, and Affiliation motivation, and pay less attention to Competence motivation and Attitude motivation. However, when compared to what extent are they truly urged by these four motivations, the results are all negative. From the difference figures, Incentive motivation, Power motivation, and Achievement motivation should be the priority issues that hotels need to address.
4.5 Relationship between variables
After discussing the e-service quality and employee motivation respectively, the author combined the averaged values of different variables in the following table.
Table 19. Variables in the survey
Hotel 1 Hotel 2 Hotel 3
E-Service Quality -0.01 -0.18 -0.09 E-S-QUAL 0.07 -0.15 -0.12 E-RecS-QUAL -0.12 -0.21 -0.05 Employee Motivation (Satisfaction Degree) 4.14 4.01 4.11 Customer Satisfaction 4.66 4.15 4.39
As Hypothesis assumes many relationships, some scatterplots are developed to shown the possible relationships between different variables.
4.5.1 E-service quality and employee motivation
Figure 1. E-Service Quality and Employee Motivation (Satisfaction Degree)
Figure 2. E-S-QUAL and Employee Motivation (Satisfaction Degree)
Figure 3. E-RecS-QUAL and Employee Motivation (Satisfaction Degree)
y = 1,205x - 5,0179 R² = 0,9302 -0,20 -0,18 -0,16 -0,14 -0,12 -0,10 -0,08 -0,06 -0,04 -0,02 0,00 4 4,02 4,04 4,06 4,08 4,1 4,12 4,14 4,16 E-se rv ice Q ua lit y Employee Motivation y = 1,3417x - 5,5499 R² = 0,586 -0,2 -0,15 -0,1 -0,05 0 0,05 0,1 4 4,02 4,04 4,06 4,08 4,1 4,12 4,14 4,16 E- S-Q UA L Employee Motivation
As can be seen clearly from Figure 1, Figure 2, and Figure 3, e-service quality, including its two components E-S-QUAL and E-RecS-QUAL, is verified to have a positive linear relationship with employee motivation. The higher employee motivation the hotel has, the higher e-service quality, E-S-QUAL, and E-RecS-QUAL should be. The three points in each figure are Hotel 1, Hotel 2, and Hotel 3. Among these three hotels, Hotel 1 has the biggest employee motivation, e-service quality, and E-S-QUAL, but does not get the highest E-RecS-QUAL because of the small sample’s data deviation. The conclusion also shows great consistency with the study results in literature review – greater employee motivation contributes to higher e-service quality, including both E-S-QUAL and E-RecS-QUAL.
Moreover, as the trend lines show the linear functions and R-square of each relationship. In general, the higher the R-squared, the better the model fits your data. For E-Service Quality and Employee Motivation, the function is written as ‘y=1.205x-5.0179’, and R-square=0.93. When employee motivation increases by 1 unit, the e-service quality will also improve by 1.205 units, and the function can explain 93% of all the variability of the response data around its mean. Similarly, for E-S-QUAL and Employee Motivation, the function is written
y = 0,9209x - 3,8899 R² = 0,6107 -0,25 -0,2 -0,15 -0,1 -0,05 0 4 4,02 4,04 4,06 4,08 4,1 4,12 4,14 4,16 E-Re cS -Q UA L Employee Motivation
