PLEASURABLE IN-FLIGHT MEAL SERVICES DESIGN
BASED ON PASSENG
ER’S PERSONALITY TRAITS USING
HYBRID
KANSEI
ENGINEERING
HETY HANDAYANI HIDAYAT
GRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY BOGOR
DECLARATION OF ORIGINALITY
AND COPYRIGHT TRANSFER*
Hereby, I declare that the thesis entitled Pleasurable In-flight Meal Services
Design Based on Passenger’s Personality Traits Using Hybrid Kansei Engineering is my own work under supervision of Dr Eng Taufik Djatna, STP, MSi and Dr Ir Hartrisari Hardjomidjojo, DEA. It has never previously been published in any university. All of incorporated originated references from other published as well as unpublished papers are stated clearly in the text as well as in the references.
Hereby, I delegate that the copyright to this paper is transferred to Bogor Agricultural University.
Bogor, November 2015
Hety Handayani Hidayat
SUMMARY
HETY HANDAYANI HIDAYAT. Pleasurable In-flight Meal Services Design
Based on Passenger’s Personality Traits Using Hybrid Kansei Engineering. Supervised by TAUFIK DJATNA and HARTRISARI HARDJOMIDJOJO.
In-flight meal service is one of the important point to judge an airline as favorite to the passengers in the long trip. It is crucial to improved in-flight meal services design that focused on pleasurable needs that highly was influenced by psychological index. This index is known as personality traits. Hence, it should be include passenger’s personality traits in designing services as pleasurable. Thus, this work concentrated on formulating a pleasurable in-flight meal services design by using hybrid Kansei engineering approach which combines Kansei engineering and service system engineering. Kansei engineering used to excavated Kansei
word that related with in-flight meal service, whereas the service system engineering contribute to identified and designed of costumized in-flight meal service by using information technology.
This reseach done aims to identify the passenger’s personality traits, to design in-flight meal service for each of the personality traits, and to evaluate the model performances. Passengers Identification are carried by firstly collect Kansei
word from selected panelist interviewing, search Kansei word synonym by using thesaurus dictionary and then have information retrieval of twitter and clustering them by using Pillar K-means algorithm. To design an appropriate in-flight meal service, it is neccesary to determine the design elements, collect the sample and
evaluation passenger’s preferences by questionnaire. They later became the basis for the formulations synthesize the design by using quantification theory type 1 (QTT1). To assure that systems are implemented, the model performance will be evaluated by t test.
The passenger’s personality traits identified from their tweet abaout in-flight mela service on particular type namely neophobia, variety seeking selective, and variety seeking. Variants formulation for each personality traits were designed for different categories such as menu variant, menu information, appearances, cordiality, originality, ordering method, and serving condition. In order to simplify the user deployment, as result of pleasurable design corresponding to each personality traits and presented in the dashboards. The evaluation by t test, be discovered that the models have represented a real word. Requirement the implementation of this model, it is required an integration fully with the current booking and information costumer system that running online. As result obtained the recommended design for user deployment to provide in-flight meal sevice that
corresponding to passenger’s personality traits.
RINGKASAN
HETY HANDAYANI HIDAYAT. Desain Pelayanan Makanan yang Menyenangkan dalam Pesawat Berdasarkan Kepribadian Penumpang Menggunakan Hybrid Kansei Engineering. Di bawah bimbingan TAUFIK DJATNA dan HARTRISARI HARDJOMIDJOJO.
Pelayanan makanan dalam pesawat adalah salah satu faktor penting bagi penumpang dalam memilih maskapai yang disukai terutama untuk perjalanan yang panjang. Hal ini menjadi penting untuk melakukan perubahan dalam desain pelayanan makanan yang berfokus pada kebutuhan yang menyenangkan (pleasurable) yang mayoritas dipengaruhi oleh indeks psikologis penumpang. Indeks ini dikenal dengan istilah kepribadian. Oleh karena itu kepribadian perlu dipertimbangkan dalam mendesain pelayanan tersebut. Formulasi desain pada penelitian ini menggunakan Hybrid Kansei engineering yang mengkombinasikan
Kansei engineering dan service system engineering. Pendekatan Kansei engineering digunakan untuk menggali kata-kata Kansei terkait pelayanan makanan dalam pesawat, sedangkan service system engineering berkontribusi dalam mengidentifikasi dan mendesain pelayanan makanan menggunakan teknologi informasi.
Tujuan dari penelitian ini adalah mengidentifikasi kepribadian penumpang, mendesaian pelayanan makanan yang sesuai, dan mengevaluasi performansi model yang dihasilkan. Identifikasi penumpang dilakukan dengan terlebih wawancara panelis yang terpilih untuk mengumpulkan kata Kansei, selanjutnya adalah mencari sinonim kata Kansei dengan menggunakan Thesaurus
kamus online, serta melakukan pengambilan data dari Twitter dan klusterisasi dengan agoritma Pillar K means. Untuk mendesain pelayanan yang sesuai, maka dilakukan penetapan elemen desain, menggumpulkan sampel dan melakukan evaluasi dengan menyebarkan kuesioner. Data ini kemudian menjadi dasar dalam mensintetis model formulasi desain dengan menggunakan Quantification Theory Type 1 (QTT1). Untuk memastikan bahwa sistem dalam diimplementasikan, maka dilakukan evaluasi kinerja model dengan uji t untuk menguji realibilitas model.
© Copyright 2015 by IPB
All Rights Reserved
No Part or all of this thesis may be excerpted without or mentioning the sources. Excerption only for research and education use, writing for scientific papers, reporting, critical writing or reviewing of a problem. Excerption does not inflict a financial loss in the paper interest of IPB.
Thesis
as partial fulfillment of the requirements for the degree of Master of Science in the Agroindustrial Technology Study Program
PLEASURABLE IN-FLIGHT MEAL SERVICES DESIGN
BASED ON PASSENG
ER’S PERSONALITY TRAITS USING
HYBRID
KANSEI
ENGINEERING
GRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY BOGOR
2015
PREFACE
I would like to thank Allah Subhanahu Wa Ta’ala for all His gifts and favour to make research is successfully completed. The research is conducted since July 2014, with the title of Pleasurable In-flight Meal Services Design Based
on Passenger’s Personality Traits Using Hybrid Kansei Engineering.
I would like to express my sincere gratitude to Dr Eng Taufik Djatna as Chair of Advisory Committee for his support and encouragement during my study in Bogor Agricultural University. I am very grateful to Dr.Ir.Hartrisari Hardjomidjojo, DEA as Member of Advisory Committee for her advice and supervision during the thesis work. I am very grateful to Prof Hanny Wijaya, Dr Aji Hermawan, Prof Khaswar Syamsu, Ms Miranda Yasella and Ms Salma Ibrahim as selected panelists who have given a lot of advices. I would like to thank to my beloved family Sarif Hidayat (father) and Musilah (mother), Erny Mulayasari Hidayat (sister), and Atep Nuryana Hidayat (brother) for their true and endless love, for never failing patience and encouragement.
I would like to thank all lectures and staff of Agro-industrial Technology Department, all of colleagues, especially my best friend in Laboratory Computer of Agro-industrial Technology Department namely Novi Purnama Sari, Aditya Ginantaka, IB Dharma Yoga, Rahmawati, Elfa Susanti, Elfira Febriyani, Nina Hairiyah, M. Zaki Hadi, Azri Firwan, Rohmah, Wenny, Fajar Munichputranto, Yudhis, Ikhsan, Imam and Denny, colleageus in Computer Sciences Department namely Husnul, Riva, Puspa, Luki, Peter, Yudha, Siti, Heti and Ela), colleageues in Dahlia namely Shierly, Dini, Iga, Maya, Anti, Rima, Mita, Nindya, Nana, Agnes, and Fatma, colleagues in Agro-industrial comunity namely Ika Rezvani, Dora Vitra Meizar, Priska Wisudawati, Ika Purwaning, Riri Mardaweni, Mustika Zelvi, Felga Zulfia Rasdiana, Yosra Adi Putra Rully, Lely, Zulfa, Gilang, Wina and to all of colleagues in Agro-industrial Technology 2013.
Last but not least, I would like to thank Directorate General of Highes Education, The Ministry of Education and Culture (DIKTI) for BPPDN (Beasiswa Pendidikan Pascasarjana Dalam Negeri) scholarship given.
I hope this research meet the requirement for Master Degree achievement and its will be useful for the society.
Bogor, November 2015
TABLE OF CONTENT
TABLE LIST vii
FIGURE LIST vii
APPENDIX LIST viii
1 INTRODUCTION 1
Background 1
Problem Statement 2
Objective 2
Benefit 3
Boundaries 3
2 RELATED WORK 3
3 METHODOLOGY 4
Research Period and Location 3
Research Framework 3
Data Analysis 5
Identification Passenger’s Personality Traits 5
Formulation In-flight Meal Services Model Design Based on
Passenger's Personality Traits 7
Evaluation of Model Design 9
4 RESULT AND DISCUSSION 10
Passenger’s Personality Trait Identity 10
PleasurableIn-flight Meal Services Model Based on Passenger's Personality
Traits 15
Model Performances 27
Implementation Plan 28
Advantages and Disadvantages 29
5 CONCLUSION AND RECOMMENDATION 30
Conclusion 30
Recommendation 31
REFERENCES 31
APPENDIX 34
GLOSSARY 53
TABLE LIST
1 Kansei word from experts and literature review 11
2 Synonym of Kansei word 12
3 Data term frequency and tweet’s personality traits 13
4 Design elements 17
5 Sample identification 19
6 The evaluation passenger’s preferences 21
7 Design formulation for each personality traits 22
8 Top 3 design elements for each personality traits 23
9 Recommended design for each personality traits 27
10 Result of t test 27
11 Requirement data 28
FIGURE LIST
1 Research Framework 4
2 Optimized centroid algorithm 7
3 Examples of in-flight meal service 8
4 The example behaviour of personality traits 10 5 The best combination λand β in silhouette score 14 6 Distribution of tweet’s personality traits 15
7 Categories of Passenger's requirement 16
8 Histogram of Partial Corellation Coefficients 23 9 Selected dashboard as result of QTT1 analysis model for Neophobia (N) 24 10 Selected dashboard as result of QTT1 analysis model for Variety Seeking
Selective (VSS) 25
11 Selected dashboard as result of QTT1 analysis model for Variety Seeking
(VS) 26
APPENDIX LIST
1 List of questions to collecting Kansei words 34
2 Kansei word synonyms and symbols 37
3 Data acquisitions (data retrieve and cleaning data) 44
4 Clustering Pillar K-means Result 45
5 Passenger’s preference designs questionnaire 46
6 Respondent Profile 48
7 Passenger’s preference in-flight meal service designs questionnaire
(Neophobia Personality trait) 50
8 Passenger’s preference in-flight meal service designs questionnaire (Variety
Seeking Selective Personality trait) 51
9 Passenger’s preference in-flight meal service designs questionnaire (Variety
1
INTRODUCTION
Background
Recent studies show that as air transportation industries rises significantly, airlines have the main obligation to bring passengers from one place to their destinations. However, along with the competitive climate growth, airlines are also required to provide good quality services to their passengers starting from before the flight, during the flight, and after the flight (Upadhyaya 2012). The services provided are covering the ease of information and ticketing, the boarding pass checking, the baggage provisions, the accuracy of schedule, comfort and safety flight (Suki 2014; Jager and Zyl 2013; Archana and Subha 2012; Bahreini
et al. 2013; ACRP 2013; Jia EA, et al. 2012). For fulfilling the passenger’s requirement, airlines also completing their services with a set aside food which is known as in-flight meal (Jones 2004). In-flight meal services is one of the factors
on passenger’s list for choosing an airline which is covering food (i.e quality, volume, menu variation, and appearance), pricing, cordiality of crew, getting information, ordering method, and punctually.
Efforts to obtain optimum consumer satisfaction, each airlines is challenged to fulfill passenger’s requirement. However, their requirement may be unlimited. On the other hand, airlines have limited resources, especially budget. Therefore, airlines should had examined passenger’s requirements deeply before they designed excellent services. Referring to Jordan (2000) that the design of a service or a product must consider functionality, usability and pleasurable aspects. But according to ACRP (2013) in the case of in-flight meal services, functionality and usability aspects had been met the current airline Standard Operational Procedure (SOP). However, to improve customer satisfaction, airlines focus on pleasurable
aspect. In more details, pleasurable will be reviewed deeply of the passenger’s
psychological side (Jordan 2000). This psychological assessment becomes important in designing favorable in-flight meal services. So, it becomes scope of this research.
Designing service model is currently potentially performed with hybrid
Kansei engineering approach which combine the field of Kansei engineering and service sciences. In contrast to other technique designs, Kansei engineering able to
deeply explore the explicit and the implicit factors of costumer’s want. Customer’s psychological indexes are arrested as Kansei words (Nagamachi & Lokman 2015). On the other hand, it is declared by Lopes and Ricardo (2013), Service System Engineering (SSE) is a systems approach (consumer oriented services) between the various stakeholders and resources that involved to design customize and personalize services according to consumer’s requirement. SSE contribute to deepen the design elements as well as information retrieval as a basic
2
personality traits. Therefore, it becomes challenge for this research to be able to design in-flight meal service corresponding for each personality traits.
Kansei is defined as feelings and desires of each personality traits. In the technological developments era, identifying personality traits are possible to done through online and real time without having to ask directly to the person concerned. One way is to use data from social media (Safko & Brake 2009). Almost everyone have an account at the social media either Twitter, Facebook, Google +, Path, Instagram, etc. In this study, the identification of passenger’s personality traits be analyze based on their tweet (a opinion on twitter) in real time. The related word frequency will be the basis for clustering. Twitter was chosen as example because it has 284 million monthly active users, and 500 million tweets sent per day and then supports 35 languages with more than 40 million users (Duggan & Brenner 2013).
In order to enhance effectiveness, it is necessary to know the relationship between personality traits and the design elements. This was conducted by the use of Quantification Theory Type 1 (QTT1). According to Lai et al. (2006) QTT1 is more effective and efficient. This QTT1 produce mathematical equation. The resulting models are necessary to verify that the generated models are reliable. Since the models are linear regression, they should be verify by t test (Pauole et al. 2000). Based on the problems and challenges, the aims of this study is to identify the passenger’s personality traits, to design in-flight meal service for each of the personality traits, and to evaluate the model performances.
Problems Statement
It is great challenge for designers to formulate the service that fulfill the passenger requirement and preference. In order to assist service designer, Hybrid
Kansei engineering was chosen as a method to design the costumized service. Moreover passenger’s personality traits were involved to pursue the pleasurable design which reflecting their own personality. Thus, there were several problems related to in-flight meal service design based on Hybrid Kansei engineering based on passenger’s personality trait, as follows:
1. How to identify passenger’s personality traits?
2. How to design pleasurable in-flight meal service for each of the passenger’s personality traits?
3. How to evaluate the performances of proposed model?
Objectives
Based on described proposed problem above, there are three main objectives formulated in this research as follows:
1. To identify the passenger’s personality traits
2. To formulate pleasurable in-flight meal service model for each of the
passenger’s personality traits
3
Benefits
The research is expected to give three benefits which consist of to provide the information about new service design concept generation, service design element which relevant to design concept, and quantification model of in-flight meal service design. Advanced, the result of this research is expected to give the recommendation about the best in-flight meal service that corresponding to each
passenger’s personality trait.
Boundaries
In order to concentrate for solution, following are the boundaries in this research:
1. Meals were chosen as object of this research (except snack and beverages) 2. The design elements was focused on pleasurable needs of pasenggers
3. The input for identification of pasenger’s personality trait were data from social media in text form. In this case, twitter was chosen as case study
4. The quantification model of in-flight meal service were generated from QTT1 analysis by using survey data
2
RELATED WORK
Study related to in-flight meal service was conducted since 2004. Jones (2004) was studied about the operational of in-flight meal service and its differences with food services. After 2004 until 2014, customer satisfaction has been studied on the airline performance, included the in-flight meal service quality. For example, Upadhyaya (2012) was studied about the customer satisfaction measurement on the various airline at Arab Saudi. He postulate that there was a gap between the costumer satisfaction and costumer need in many parameter involved in-flight meal service. Also, Jia et al. (2012) was studied on Malaysia Airline, then the service quality was studied on Indian Airline Archana and Subha (2012). Then, Jager and Zyl (2013) studied in Malaysia and South
Africa Airline specially international passenger’s expectation. Bahreini et al.(2013) was analysed the defferences performance between several airline. On the otherhand, Suki (2014) was built the calculating model for service quality.
Kansei Engineering research are mostly used to designing product. But Hartono (2011) was due to designing hotel service for Indonesian tourist. Then, the end of 2014, Djatna and Hidayat (2014) was designed the in-flight meal service by used real time key element but does not consider yet the pleasurable needs and kansei of passengers.
4
3
METHOD
Research Period and Location
This research was conducted from July 2014 to April 2015. The samples of in-flight meal services were collected in depth literature review. The survey activities and data analysis were conducted at Computer Laboratory of Agro-industrial Technology, Bogor Agricultural University, Bogor.
Research Framework
The methodology was designed to solve the research problem. The research framework detail was represented in Figure 1. In this research, generally, based on interview and discussion with selected panelist, the Kansei word were obtained. Its became an database to preprocess the posting content related to in-flight meal service to identify the passengger’s preferences. Meanwhile in order to formulate the pleasurable in-flight meal service model, the questionnaires were used to acquire the data related to passenger’s preferences. Then, this models were evalute by using t test.
Start
Collect the Kansei word [experts & literature review
1st Questionner]
Search for synonims of Kansei word [Thesaurus dictionary online]
Collect the samples [Market survey]
Identify of design elements in the samples
Data samples
Analyze correlation by QTT1 in R languange programming
Evaluate passenger’s peferences
[2nd Questionnaire]
Kansei word
Solution flow for 1st
Objective Solution flow for 2nd
Objective Solution flow for 3rd
Objective
Define Personality traits [literature review]
Retrieve data in R languange programming
[twitter]
Term frequency per tweet
Identify Personality Traits by Pillar K-mean Tweet’s Personality Traits clusters Categories value & PCC [Dashboard design] Valid design Calculate T value element
designs in R
Determine T table [significant level=5%]
T values
T tabel
T values > T table?
Finish Preprocessing data
5
Referring to Neil and Noor (2011) that in-flight meal service given by an airline differed between Low Cost Carrier (LCC) with legacy airlines. In this research, in-flight meal service design devoted to legacy airline. Indefinitely that the price attribute is unconsidered.
On the legacy airline, in-flight meal service given also distinguished by class flight namely the economic, business and executive. Any of a class have their own SOP. To be more specific on the sample collection and respondents, this case focused on designing pleasurable in-flight meal service for economic class. Economy class chosen as object class because the economy class has a more seat portions, such as GA (Garuda Indonesia Airline) which has a total seats 96 consist of the economic seats as many as 84 seats and the business ones only 12 seat (GA 2012).
Data Analysis
Identification of Passenger’s Personality Traits
There were several stages to identify passenger’s personality trait. Initially, to define personality traits. Followed by, collecting the Kansei word related to in-flight meal services by interviewing selected panelist and literature review. Then, search the synonym of Kansei word by using Thesaurus dictionary online. Thereafter, information retrieval from social media then data preprocessing. Finally, clustering using Pillar K-means (Barakbah & Kiyoki 2009).
Definition of Personality traits
Personality traits needs to be defined to ease in understanding, identify and clustering the data. A definition that will be used in this research are based on the several literature review of previous research. Personality traits closely related to someone’s psychological to response the problem that indicated with his or her behaviour as early response. In this case only be limited to interest someone would new foods
Collection of Kansei words
In this stage, Kansei words will collect by interviewing selected panelist. The selected panelist were people who often enjoy various type of in-flight meal service from various airline as well as having their interest against and understand about him or his personality traits and the trends in choosing certain foods. To further ease the selected panelist in collecting Kansei words, then used the questionnaire on Appendix 1. This questionnaire contains the questions for exploring the experiences, hopes and insights of selected panelists.
Searching synonyms of Kansei words
To be more effective in the next process, it is crucial to search the synonyms of Kansei words. Searching synonyms aims to enrich database Kansei
6
it is one of the best online dictionary that containing synonym and antonym based on the concept of meaning and rigorous with the other words (Caplan 2011). Information retrieval from social media
Passenger’s personality traits were determined by using data or comment from social media. Owing to the fact that, social media has become more popular for people to express their ideology to public (Djatna & Hidayat 2014). Firstly, determines the conditions of the data collection. Next, the data obtained need to cleared redundancy and retweet to make sure there no duplication.
The major challenge in text mining is converting unstructured text into the structured model. This must be done prior to doing any advanced analytics. The possible steps of text preprocessing are the same for all text mining tasks, though which processing steps are chosen depends on the task. The basic steps are as follows (Miner et al. 2012):
1. Scope of the text to be processed was be choosen (documents, paragraphs, etc.). 2. Tokenize: Break text into discrete words called tokens.
3. Filter: Remove stopwords (“stopping”) or take wordlist.
4. Stem: Remove prefixes and suffixes to normalize words 5. sentence boundaries detection: Mark the ends of sentences.
6. Normalize case: Convert the text to either all lower or all upper case.
Clustering tweet personality trait by using Pillar K-means
In this purposed system, in order to cluster tweets apply Pillar K-means. In pillar algorithm the distribution of dataset is similar to pillar of a building. The initial centroid is located as furthers possible distance from the other. (Barakbah & Kiyoki 2009). In other word, those k furthest object selected as initial centroid, where k refer to cluster number to be observed.
In other word, those k furthest object selected as initial centroid, where k
refer to cluster number to be observed. Let T
t ii| 1,..,n
be dataset, k be number of clusters, C
c ii| 1,...,k
be initial centroids,STT be identification for T which already selected in the sequence of process, DM
t ii| 1,..,n
be accumulated distance metrics for each iteration and m be grand mean of X. The proposed algorithm is described on Figure 2 (Barakbah & Kiyoki 2009).After obtained the best initial centroid, the next step are following to K-means algorithm. K-K-means algorithm is an iterative technique that is used to portion documents into K cluster. The basic algorithm are input kis the number of clusters to get a set data of kclusters. The K-means steps are following:
a. knumbers of clusters were choosen to be determined b. Cfrom pillar solution as initial centroid was choosen
7
d. Step 2 and 3 were repeated until convergence is attained Set C ,ST ,and DM
Calculate Ddis T m
,
Set number of neighbors nmin .n
k
Assign dmaxarg max
DSet neighbors ndis. maxd
Set i1as counter to determine the ith initial centroids
DM DMD
Select xarg maxDM as the candidate for the ith initial centroids
ST ST
Set D as the distance metric between T to Set no number of data points fulfilling Dnbdis
Assign DM
0 If nonminAssign D ST( )0
CCU
1
i i
Ifik, go back to step 7
Finish in which Cis the solution as optimized initial centroid Figure 2. Optimized centroid algorithm
Formulation of Pleasurable In-flight Meal Services Model Based on Personality Traits
After discovered passenger’s personality traits,it is crucial to consider them in designing in-flight meal services. To design pleasurable in-flight meal services using hybrid Kansei engineering, there were several stage. Frist, collect the in-flight meal services sample. Next, determine design elements based on service science perspective. Then, evaluate passenger’s preferences. And the last is synthesis design formulation using QTT1.
The following steps are quantification theory type 1 (Lai et al. 2006) processes on how to:
1. The in-flight meal services attributes were determined (Xn) (n=1,2,...,7) 2. the categories i of in-flight meal services attributes (Xni) are defined. For
example, in this case for menu variant there are 2 categories i.e 2 options (X11) and vegetarian, moslem, and kosher (X12)
3. The samples are classified based on their attribute categories 4. The passenger’s preferences are evaluated about samples
8
Collecting in-flight meal services design samples
In-flight meal services design samples will obtain by market survey from domestics and international flight with all of classes (economics, business, and executive classes). Figure 3 below described in-flight meal service samples.
Figure 3. Example of in-flight meal service
Determining the design elements
Design elements should determine to identifying samples and to focusing formulation in-flight meal service design .The identification of design elements and their own types will be done by literature review on pleasurable needs. The design elements were seen based on the service system engineering perspective in hybrid Kansei engineering.
Evaluating the passenger’s preferences
In this stage, the evaluation created passenger’s preferences conducted by survey. Hence, the selected respondent will answer the questionnaire. The questionnaire was consist of in-flight meal samples. The preferences levels were 5-point Linkert scale, started from 1 that refer to “strong dislike” and 5 that mean
to “strong like”. The samples obtained from previous stage. The questionnaire is
presented in Appendix 5. The questionnaire was divided into two main parts is the first part to know the number of respondents enjoyed the experience of in-flight service meal service and his or her personality trait.
Synthesizing model formulation by Quantification Theory Type 1 (QTT1) Formulating model design was adopted on the application of Kansei
Engineering to determine the relationship between design concept and design elements by using Quantification Theory Type 1 (QTT1) method (Schütte et al.
9
Kansei engineering and standard Kansei engineering are in determining the design concept.
Referring to Hui et al. (2009), the QTT1 define as a method of qualitative and categorical multiple regression analysis allowed inclusion of independent variables that are categorical. By using QTT1 synthesis of service will be more powerful. The model formulation as follows (Lai et al. 2006):
^
. 1 1
i
k E C
i j ijs s
i j
y x
(2)Where ^k
s
y is the predicted value of standard variable for the sthproduct sample {s1, s2, ..,s15},ion the kth personality traits {k1, k2, k3},iis design elements index, E is number of design elements, jis categories index,Ciis the number of category of the ith design element {i=1,2,..,7}, is stochastic variable whose
expectation value E( )=0,xi j. is the category score of the jth style within the ith
design element, and ijsis dummy variable coefficient.
Evaluation of Model Performance
Evaluation means to ensure that the model has been represented in the real world. In this research, the model was verified the reliability with t test. There were several stages to evaluate model performance. Firstly, calculate t value. Next stage is determine t table. Then compare t value and t table. Here is more detail to evaluate the model performances:
Calculating t value
The model performance was verified the reliability with t test of PCC (Partial Correlation Coefficient) values from the result of Quantification Theory Type 1. The following questions detailed for calculating t value as follows (Hui et al. 2009):
2 1 (3) 1 value s E t r r
Where tvalueis reliability result,
r
is Partial Correlation Coefficient (PCC) value,sis ordinal number of sample, Eis ordinal number of design elements. Determining t table
10
Comparing t value and t table
After discovering t, in this stage, t value will be compare with t table. Design element declared as reliable, if:
(4) value
t t
4
RESULT AND DISSCUSSION
Passenger’s Personality Trait Identity
From our results we discovered that personality traits are psychological factors influencing consumption patterns. This factor leads to passenger characteristics that influence their consumption behavior. Kittler and Sucher (2008) mentioned that there is a close relationship between food and the personality traits. This includes the food selection, the presentation, the equipment used to how to eat it. This is in accordance with the terms that are familiar in the
world i.e. “You are what you eat.” Personality traits is one of the things that affects consumer wishes and judgment about food service.
The personality traits were divided into theree namely (a) neophobia, (b) variety seeking selective, and (c) variety seeking as seen in Figure 4. According to Mak et al. (2012), they postulate 2 types of personality traits are neophobia and variety seeking. In they studied, define (a) neophobia as a people who are reluctant to try new foods. Secondly, (b) variety seeking tends affect a personal food choices. Variety seeking is the term used for the personality of the person who likes looking for something that is diverse (diversity) and different as a good choice in service or food. This type has the flexibility to adopt the food they consume. In the development, it has been added by Djatna and Hidayat (2014), for a consideration of some groups of people who have an interest but they were constrained in certain allergies or limit certain types of food. The group is called as variety seeking selective (c).
11
(c)
Figure 4. The example behaviour of personality traits
(a) Neophobia, (b) Variety Seeking Selective, and (c) Variety Seeking Therefore, in this case their psychological captured from the words spoken in their opinion on Twitter (tweet). The research began by interviewing 5 selected panelist and literature review for collecting Kansei words. Selected panelist are people who have often enjoy in-flight meal services of various international airlines, has an interest about in-flight meal service and understand about food personality traits. To assist selected panelist in collecting Kansei words, in addition to interview, they also asked to fill the questionnaires on Appendix 1. As a result, 57 Kansei words about in-flight meal services are obtained, as seen in Table 1 below.
Table 1 Kansei word from experts and literature review
Personality traits Kansei word
Neophobia (N) difficult, common, familiar, reject ,definite, colorless, local, satisfying, popular, single, old, tasty, same, similar, traditional Variety Seeking
Selective (VSS)
acceptable, agreable, healthy, homesuitable, delicious, deluxe, fresh, juicy, friendly, kindly, halal, helpful, intelligent, nutricious, skill, thoyib, clean, selection, vegetarian, perfect Variety Seeking
(VS)
choices,colorful, attractive, new, cheap, expensive, difficult, flavorful, different, delectable, unique, brave, flexible, greeting, impressive, interest, unfamiliar, unpopular, special, option, memorable, extraordinary, modern
Source: Experts survey (2014); Martin (2001); Mak et al. (2012); Ratner & Kann (2002)
The Kansei words on Table 1 become the word identifier in filtering and
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Table 2 Synonym of Kansei words Words
Synonyms limited, customary, disesteemed, remarkable, challenging, demanding, laborious, painful, formidable, galling, gargantuan, hard-won, herculean, immense, intricate, irritating, labored, operose, prohibitive, frequent, ..., coincident, concurrent, contempt, restored (Thesaurus.com)
Having Kansei word synonyms, next steps is data retrieval by using query condition in R language. Tweet were taken that containing the words inflight catering, inflight dining, inflight food, flight meal, airline meal, airline catering”
as condition with a sample of 1474 tweets updated with English language during in the years of January 2014 to April 2015. The keywords election are based on the other terms that often used to refer in in-flight meal services. It is number of tweet which reflect of 1% of allowable access from total tweets in the worlds that fulfill the conditions. This access is free of charge and legal from twitter users who have API key .The API key is code unique which will be needed to synchronizing blog or a web by social network account belonging to the user.
The basic assumption of which are applied in the taking of the tweets is all the tweets that fulfilling a condition that has been set will come from passengers or people who have been enjoying in-flight meal services from the certain airline. Because account user that posting the tweet must have certain interest against in-flight meal services. In addition, the tweets taken is not limited by an airline and regions.
Tweets that have been taken then be removed the data redundancy and spam. It turns out there were only 1065 of 1474 tweets that capable to process. More detail about information retrieval was shown in Appendix 3. The amount of data obtained for seventh the keyword are different. This indicates the level of popularity keyword as a term used to denote in-flight meal service. Then the data did preprocessing that includes tokenizing, filtering the Kansei word synonyms that has been accumulated and stemming to find basic words. The Kansei word synonym and notation are shown on Appendix 2. Synonym words should be notated, to ensure the number of synonyms and to ease column labeling in output produced. Output from this data preprocessing is term frequency matrix. There are 1113 synonyms of Kansei words which denoted as Kw1113 as a representation that data term frequency matrix there will be consist of 1113 column.
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Table 3 Data term frequency and tweet’s personality traits No
Tweet
Kansei words synonyms Personality traits
Kw1 Kw2 Kw3 Kw4 Kw1113
1 0 0 0 0 . 0 VSS
2 0 0 0 0 . 0 VSS
3 0 0 0 0 . 0 VS
4 0 0 0 0 . 0 VSS
5 0 0 0 0 . 0 N
6 0 0 0 0 . 0 VS
7 0 0 0 0 . 0 VS
8 0 0 0 1 . 0 VS
9 0 0 0 0 . 0 VSS
10 0 0 0 0 . 0 VS
11 0 0 0 0 . 0 VS
12 0 0 0 0 . 0 VSS
13 0 1 0 0 . 0 VS
. . . .
. . . .
1067 0 0 1 0 . 0 VS
Data term frequency on Table 3, the Kansei word synonym (the notation were shown on Appendix 2) calculation only consist of zero (0) and one (1). The meaning of zero (0) are refer to that tweet does not content the Kansei word. Otherwise, one (1) refer to Kansei word in tweet content only spoken once. Table 3 above were be an input in the clustering process by using Pillar K-means and personality traits is the output produced. The clustering process are used the algorithm that shown on Figure 2.
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Figure 5. The best combination λ and β in silhouette score
Before the centroid of each clusters are determined, the optimal value of α and β must be determined by trial and error. The values of λand β play significant
role in silhouette score. Silhouette function was to understand how good an object is placed in a cluster (Barakbah and Kiyoki 2009).
The β (beta) value shows the gap or distance between centroid clusters and λ (lamda) value refer to the range or radius each cluster. Hence, the basic principles in Pillar K-mean to optimize initial centroid is to maximize beta value and minimize alpha value. Based on calculation, the best cluster solution were λ = 0.1
and β = 0.2 because it had the highest silhouette score (s = 0.833938272).
To recap, the type of passenger’s personality traits is identified from a tweet posting that related with in-flight meal service. From observed dataset, it is found
the passenger’s personality traits distribution as shown in Figure 6. lamda: 0.1
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Figure 6. Distribution tweet’s personality traits
From Figure 6 above, known that the majority distribution of the tweets personality trait is variety seeking with 71% or consist of 755 tweet posting. Then, distribution of neophobia and variety seeking selective nearly the same namely 15 % or 154 tweet posting and 14 % or 153 tweet posting.
Pleasurable In-flight Meal Service Model Based on Personality Traits
In-flight meal service is an additional services provided by an airline to passenger with set aside food during their journey, in-flight meal service is meant to increase of overall passenger satisfaction. Lupiyoadi and Hamdani (2008) stated that service in an activity that have occurred from interaction with a person or a machine that which produces customer satisfaction .Although services are intangible things, but basically just as product, services also respond to its consumer acceptance. Hence to design the excellent in-flight meal services, the
airlines should to know the specific of passenger’s requirement.
According to Jordan (2000) that passenger’s requirement dirived into three hierarchy level needs that namely level 1 is functionality needs, level 2 is usability needs and level 3 is pleasurable needs. Then, Figure 7 below shown categories of
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Figure 7. Categories of passenger’s requirement (Adopted from Jordan 2000 and Perone et al. 2005)
Clearly, in the figure 7 shown the categories of pasenger’s requirement about in-flight meal service. The service will be useless if it does not contain appropriate functionality. In-flight meal service cannot be usable if it does not contain the functions necessary to perform the tasks for which it is intended. If in-flight meal service does not have the right functionality, set aside food with fast and accurate, will cause dissatisfaction.
Having appropriate functionality is a prerequisite of usability, but it does not guarantee usability. The usablity of in-flight meal service is comitement and consistency services; providing the food safety; and acceptable costing. In other words, passenger want to have in-flight meal service that provide the nutritious and healthy food, with enough volume that serve in the right time when they hungry.
Having become used to usable services included in-flight meal service, it seems inevitable that people will soon want services that make passangers feel good about who they are; services that bring not only functional benefits but also emotional ones. In pleasurable needs, passenger want an in-flight meal service that costumize, impress, memorable and enjoyable. Its level related to Kansei concept that consider the psychological aspect to designing services. In addition, based on ACRP document (2013) discovered that in airline’s current SOP (Standard Operational Procedure) only fulfilling the level of functionality needs and usability needs. But the third hierarchy level, pleasurable needs, are has not been fulfilled. Hence, in this work focused on pleasurable needs.
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Table 4 Design elements
Type Menu Variant Menu
Information Appearance Cordiality Originality
Ordering method
Serving Condition (i) (X1) (X2) (X3) (X4) (X5) (X6) (X7)
1 2 Options Limited Unique Greeting Origin
Departure Package
Hot or Warm
2
Kosher, Muslim, And Vegetable Menu
Oral Standard More
Information Destination
Buy On Board (Bob) Cool
3 Written Not Specified Prebooking
4 Determine Their
Own
BoB& Prebooking
Not only about meals but also about how these meals are served. The attributes about meals are including:
a. Menu variant (X1)
Menu variant (X1) is how much an option granted to passengers in choosing the food. It has 2 categories which usual be on the market that is 2 options (X1.1) such as rendang or fried rices; Kosher, Moslem, and vegetable (X1.2). Kosher refer to food for person that have interdiction. Moslem that meals non alcohols and insurable as halal food; and vegetable is meals non an animal protein.
b.Appearances (X3)
Presentation of our meals with appetite for its consumption. So, airline business must pay attention about appearance. This attribute have 2 categories namely unique (X3.1) such as using banana’s leaf or another materials that refer to local wisdom; and standard (X3.2) such as using the dishes standard.
c.Originality (X5)
In this case, originality that mean place where are the meals come from. Based on point of departure, originality only derived as 4 categories namely origin depature (X5.1), destination (X5.2), not specified or random (X5.3), and determine their own (X5.4).
The attributes about service are consist of: a.Menu Information (X2)
Menu information is how airlines explain menu choices offered . Its design elemen derived as limited (X2.1) that mean only list of menu; oral (X2.2) is the steward give more detail about menu such as the material, processes, etc; and written (X2.3) is there are information detail in list of menu.
b.Cordiality (X4)
In this case, cordiality attributte about attitude of flight stewardess when they offer the menu. They only greeting (X4.1) or they give more information (X4.2).
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Ordering method derived into 4 type. Package (X6.1) mean that the meal are included in ticket and passengers does limited to choice the menu. Buy On Board or BOB (X6.2) is the method that the passengers determine their menu during the flight. Prebooking (X6.3) mean that the passengers should be select their menu when they reservesed the ticket. Prebooking and BOB (X6.4), this is more flexible because the passengers can selected the menu before flight or during the flight.
d. Serving condition (X7)
Serving condition showing how conditions food when served to passengers.This design elemen derived as 2 categories, namely hot or warm condition (X7.1) and cool condition (X7.2).
After determine the elemen designs, the next stage is to collect the in-flight meal service samples. From the results of the market survey, there were 15 samples of in-flight meal services. The selected sampels are in-flight meal services type that provided from the airline in the world that were consist of domestic and international flights. In this case, there were several airline that was chosen as the samples both their domestic and international flights.
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Table 5 Samples identification No In-flight
Type Menu Variant
Menu
Information Appearance Cordiality Originality Ordering Method
Serving Condition
1 Domestic 2 Options Limited Standard Greeting Not Specified Package Cool
1 1 2 1 3 1 2
2 International
Kosher, Muslim, And
Vegetable Menu Oral Unique
More Information
Origin
Departure Bob Hot or Warm
2 2 1 2 1 2 1
3 International
Kosher, Muslim, And
Vegetable Menu Limited Standard Greeting
Determine
Their Own Bob&Prebooking Cool
2 1 2 1 4 4 2
4 International
Kosher, Muslim, And
Vegetable Menu Limited Standard Greeting
Origin
Departure Bob&Prebooking Cool
2 1 2 1 2 4 2
5 International
Kosher, Muslim, And
Vegetable Menu Written Unique
More Information
Origin
Departure Prebooking Cool
2 3 1 2 1 3 2
6 International
Kosher, Muslim, And
Vegetable Menu Written Standard
More
Information Destination Bob&Prebooking Hot or Warm
2 3 2 2 2 4 1
7 International
Kosher, Muslim, And
Vegetable Menu Limited Unique
More Information
Determine
Their Own Bob&Prebooking Hot or Warm
2 1 1 2 4 4 1
8 Domestic 2 Options Limited Unique Greeting Not Specified Package Hot or Warm
1 1 1 1 3 1 1
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Table 5 Samples identification (continued) No In-flight
Type Menu Variant
Menu
Information Appearance Cordiality Originality Ordering Method
Serving Condition 9 International
Kosher, Muslim, And
Vegetable Menu Oral Standard
More
Information Not Specified Prebooking Cool
2 2 2 2 3 3 2
10 International
Kosher, Muslim, And
Vegetable Menu Limited Unique Greeting
Determine
Their Own Bob&Prebooking Hot or Warm
2 1 1 1 4 4 1
11 Domestic 2 Options Oral Unique Greeting Not Specified Package Hot or Warm
1 2 1 1 3 1 1
12 International
Kosher, Muslim, And
Vegetable Menu Limited Unique Greeting Not Specified Prebooking Hot or Warm
2 1 1 1 3 3 1
13 Domestic 2 Options Oral Unique Greeting Not Specified Bob&Prebooking Cool
1 2 1 1 3 4 2
14 Domestic 2 Options Limited Unique Greeting Destination Prebooking Hot or Warm
1 1 1 1 2 3 1
15 International
Kosher, Muslim, And
Vegetable Menu Oral Unique
More Information
Origin
Departure Bob Cool
2 2 1 2 1 2 2
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The samples were then evaluated through a questionnaire of passenger's preferences with Linkert scale with level 5 scale, where level 1 indicates “strong
dislike”, 2 refer to “dislike”, 3 indicates “abstain”, 4 refer to “like”, and level 5 which shows “stronglike”. The evaluation was conducted to 50 respondents that were selected by purposive or judgement sampling.
Respondents were person who have had the experience of enjoying in-flight meal service. Another thing considered in selection respondents were frequency and duration flight .This relates to the passenger’s needs and type of in-flight meal services that given. Besides duration and frequency flight, on Appendix 5 that contains respondent profil, known that the majority of respondents are students.
[image:39.595.131.498.302.556.2]In addition, in questioner (Appendix 6) also asked few questions to determine the type of respondent’s personality traits. Results of sample identification and evaluation of passenger's preferences for each personality traits are described in the Table 6.
Table 6 Evaluation of passenger’s preferences
No sample Passenger’s Preferences
Neophobia Variety Seeking Selective Variety Seeking
1 1,727 1,789 2,150
2 3,181 3,842 3,600
3 2,910 3,000 2,850
4 3,000 2,947 3,100
5 3,455 2,947 4,050
6 1,727 3,000 3,800
7 3,818 3,211 3,350
8 1,727 3,211 2,150
9 1,727 2,895 3,600
10 3,091 3,263 2,150
11 2,727 2,947 3,600
12 1,727 3,842 2,850
13 2,727 1,789 3,100
14 2,910 3,844 2,150
15 1,727 2,895 2,850
As results of the field survey, 50 respondents that selected to be observed are consisting of neophobia are 11 peoples, selective seeking variety are 19 peoples, and variety seeking are 20 peoples. The preferences for each personality traits are shown on Appendix 7, 8, and 9. The value of preference in Table 4 above are indicated the average preference value for each personality trait.
The data were then calculated by Eq.2, where design elements were the independent variables and personality traits were the dependent variable. The calculation results shown in Table 7. PCC (Partial Correlation Coefficient) is the relationship between design elements and personality traits. The type of each selected design element as follow which ordered by ^k
s
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Table 7 Design formulation for each personality traits Design Element of
Inflight meal services
neophobia vss vs
PCC PCC PCC
X1 0,84 0,769 0,779
X2 0,962 0,748 0,909
X3 0,776 0,746 0,765
X4 0,63 0,661 0,617
X5 0,982 0,761 0,635
X6 0,977 0,761 0,7
X7 0,965 0,807 0,84
Constant Multiple R2 0,982 0,977 0,965 0,962 0,84 0,776 0,63 Nephobia Variety seeking selective variety seeking
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Figure 8. Histogram of Partial Correlation Coefficients Table 8 Top 3 design elements for each personality traits
Personality traits 1st 2nd 3rd
Neophobia Originality Ordering Method Serving Condition Variety Seeking
Selective Serving Condition Menu Variant Ordering Method Variety Seeking Menu Information Menu Variant Serving Condition
To simplify user deployments, the design models were displayed in a dashboard. The dashboards are a simple way to organize together and manage multiple charts that share the same underlying data. Its contain various components, such as charts, gauges, and dials, that are bound to data sources. The components (Juice 2009). Display the data in a compact and visual manner. In this case, dashboard were adopted Herzberg chart. Where in Herzberg chart there are two opposite side (Hong & Waheed 2011). The positive side showed design elements that increases passenger’s preferences. While the negative side refeer tahta the factors affect the dispreferences of passengers.
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Categories value
Design element categories on infight meal service that affecting neophobia (N) preferences
Design element categories on the inflight meal service that led to extreme
dispreferences
Design element categories on the inflight meal service that led to extreme
[image:42.595.117.524.121.601.2]preferences
Figure 9. Selected dashboard as Result of QTT1 analysis model for Neophobia (N)
From the selected dashboard on Figure 9 shown that neophobia type was eiger to combination model that has “2 options” menu varian (X1), menu information (X2) by “oral”, has “standard” appeareance (X3), cordiality (X4) as
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Design element categories on infight meal service that affecting variety seeking selective (VSS) preferences
Design element categories on the inflight meal service that led to extreme dispreferences
Design element categories on the inflight meal service that led to extreme preferences
[image:43.595.125.548.117.592.2]Categories value
Figure 10. Selected dashboard as Result of QTT1 analysis model for Variety Seeking Selective (VSS)
The Herzberg chat on Figure 10 was selected for variety seeking selective. The meaning of model is the variety seeking type was prefer the combination model that has option “Kosher, Muslim, and Vegetable menu” menu varian (X1),
does not problem with “limited” menu information (X2), “unique” appeareance (X3), cordiality (X4) as “greeting” from crew, menu come from (X5) “destination”, ordering method (X6) is “Buy on Board (BoB)”, and then served (X7) in “hot or
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Design element categories on infight meal service that affecting variety seeking (VS) preferences
Design element categories on the inflight meal service that led to extreme dispreferences
Design element categories on the inflight meal service that led to extreme preferences
[image:44.595.121.480.118.587.2]Categories value
Figure 11. Selected dashboard as Result of QTT1 analysis model for Variety Seeking (VS)
The selected dashboard in Figure 11, it was shown that variety seeking
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[image:45.595.95.509.57.820.2]The dashboards for neophobia, variety seeking, and variety seeking selective are the output that a system that shows the design of the services corresponding to each personality traits. Output this is a constant and unaffected by time. Recommended in-flight meal services design for every personality traits seen in Table 9.
Table 9 Recommended design for each personality traits
Personality
traits X1 X2 X3 X4 X5 X6 X7
Neophobia 2 options Oral Standard Greeting Origin
departure Prebooking Hot or warm variety
seeking selective
Kosher, Muslim,
and Vegetable menu Limited Unique Greeting Destination BoB
* Hot or warm
variety seeking
Kosher, Muslim,
and Vegetable menu Oral Standard Greeting
Origin
departure Package Hot or warm
*BoB= Buy on Board
Model Performance
Evaluation eventually was conducted to ensure the models presented the real world. As result, model of QTT1 was in form of regression equation, hence this study conducted reliability test by using t test. Reliability testing was done for every design elements. Significance level used in this study was 0.05. In other words, 95% of the decision to reject the false hypothesis was true. The t0,05was 1.860 obtained by using Table t, with degrees of freedom was 8 (i.e. 15 samples, 7 design elements). Further calculation by formula Eq.3, using the data in the Table 5, PCC then obtained t value for each design element is shown in Table 9.
Table 10 Result of t test Design
Element
Neophobia Variety
Seeking Selective Variety Seeking
t value Result t value Result t value Result x1 4,102 Reliable 3,182 Reliable 3,292 Reliable x2 9,266 Reliable 2,983 Reliable 5,754 Reliable x3 3,259 Reliable 2,968 Reliable 3,145 Reliable x4 2,147 Reliable 2,330 Reliable 2,072 Reliable x5 13,565 Reliable 3,106 Reliable 2,172 Reliable x6 12,211 Reliable 3,107 Reliable 2,590 Reliable x7 9,695 Reliable 3,619 Reliable 4,100 Reliable
After the t value was known, then the t value is compared witht0,05. Referring to the Eq.4, the design element was declared unreliable if the value t
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Implementation Plan
[image:46.595.95.495.154.816.2]The implementation of a system can be done by integrating this system with a ticket reservation system that was applied. However, this implementation need to be supported by other stakeholders besides designers to fulfilling the requirement data. Hence, in the implementation plan of this system has previously identify the requirement data and stakeholders as PIC. The requirement data were shown in Table 11 below.
Table 11 Requirement data
INPUT STAKEHOLDER OUTPUT
Type of in-flight meal services
1. Categories of menu variant
2. Categories of menu information
3. Categories of appearances
4. Categories of cordiality 5. Categories of originality 6. Categories of ordering
method
7. Categories of serving condition
Posting content about in-flight meal /In-flight catering/In-flight dining/ In-flight food/ Flight meal/ Airline meal/ Airline catering
Passenger’s preferences (in
text format) In-flight code
1. Airline name 2. In-flight code
3. Departure-Destination 4. Time Passengers Identity 1. Name 2. Age 3. Email
4. ID social media
Designer
Passenger
Airline
Airline & passenger
Passenger’s personality trait 1. Neophobia
2. Variety Seeking Selective 3. Variety Seeking
In-flight meal service corresponding with passenger’s personality trait
1. Neophobia
2. Variety Seeking Selective 3. Variety Seeking
Based on the Table 11, known that the input of a systems are follow: 1. Type of in-flight meal services
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2. Posting content about in-flight meal
Passengers are hoped to posting in social media about their preferences on in-flight meal service in a format text. Next, this posting would be an input in
determining passenger’s personality traits
3. In-flight code
In-flight code will be given by Airline to passengers when they has booked the ticket. In-flight this code represent the Airline’s name, the flight number, origin and destination.
4. Passenger’s identity
The passenger’s identity is important thing to know the name of passengers and his or her name in social media accounts .This identity was obtained from reservation process.
To ensure that the required data will be collected, when passengers booked on tickets, they should be answer a question for knowing passenger’s preferences on the in-flight meal services. For example, “How is the in-flight meal service that you expect and prefer? Please write down your comments by post in your social media accounts with the format: Your preferences on in-flight meal services #inin-flightmeals #inin-flightcode”. For example, “I want fresh food and diverse and served in warm condition#inflightmeals#AOA137”. The posting will be extracted and classified based on code flight online.
Advantage and Disadvantage
Althought, model required to integrate as a application system, but best in-flight meal service models that coressponding to each personality trait were operated on real time mode. Then, the result was represented as dashbord to easier for understanding the model. Identified advantages that have been recognized of this system are:
1. Kansei words were derived from depth interview with selected panelists dan literature review.
2. Selected samples
a. Samples were selected based on mileage that has been adjusted for the transportation law that in-flight meal service should be provided for flight duration more than 1 hour 59 minutes.
b. Samples have accommodate domestic and international flights. 3. Data for identification of personality traits devided from social media, not
only teitter but also another social media such as intagram, facebook and path.
4. The information retrieval from social media was be done in online and real time mode.
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6. The selection of respondents have been considered on their profile namely experience in-flight meal service, frequency flight per 6 month, the average duration of flight, occupation and age.
7. The generated model performance were reliables.
Nevertheless, the implementation of model have some restrictions and draw backs as follows:
1. Object
Object in this research was limited on in-flight meal services which given by legacy airline in economy flight class. Also, the model generated only be implemented on the particular type of the airlines and flight class.
2. Input
The design limited by input type, its only consider Kansei word as an input of psychological index. Only posting text content as input systems, whereas to better understand personality traits using non verbal data of social media such as image and photo.
In addition, system only be operating if posting were contained one or more 1113 words that have been stored in a database earlier (Kansei word synonyms on appendix 6). If does not containing the words, hence the pasengger’s personality traits were unidentified.
3. Design elements
Design elements in this system only seen from seven (7) elements namely menu variant, menu information, appearance, cordiality, originality, ordering method, and serving condition. In fact there are still many design other elements in in-flight meal service such as equipment and music facilities
In addition, in type of design an element of are still severely limited .Such as in design elements variant menu , type 2 option (X1.1) dan Kosher, Muslim, And Vegetable (X1.2). But, in the reality, there were the another types of menu variant such as for healthy diet (For example, less sugar diet)
4. Input to generated model
In this case, the data used only limited come from survey data that was be done by using 100 selected respondents. Respondents were selected by purposive or judgement sampling where the technique is not paying attention to the value of probabilistic.
5
CONCLUSION AND RECOMMENDATION
Conclusion
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% and variety seeking selective is 14 %. An in-flight service model has been built by using Quantification Theory Type 1 for each personality trait to analyze the relationship between personality traits and design elements. As result, the best in-flight meal service models to each personality trait were different combination of seventh design elements namely menu variant, menu information, appearance, cordiality, originality, ordering method, and serving condition. The models were presented as dashboard to easier the user deployment. Then, the model already implemented because based on t test, known that models have realiable. In general, the result showed that in-flight meal service models were specific for each personality traits and it have represented the real world problem.
Recommendation
In the future, it is expected to further research by considered Kansei non verbal expression. In addition, to make system more powerful, it required to integrate as familiar user interface system in to easier for implementation with their current booking and membership information systems.
REFERENCES
[ACRP]. Airport Cooperative Research Program. 2013. How airline measure costumer service performance. Washington (US): ACRP.
Archana R, Subha M V. 2012. A study on service quality and passenger satisfaction on Indian airlines. Int J Multidiscip Res
