รายงานการประชุมระดับนานาชาติ RTBEC2021

The 6th RMUTT Global Business and Economics International Conference 2021 (RTBEC 2021)

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The 6th RMUTT Global Business and Economics International Conference 2021 (RTBEC 2021)

Guidelines of Training Curriculum Development for New Skill
Requirements of Flight Attendants after Covid-19 Pandemic Impact

Nattaya Srisupha1
Natesiri Ruangariyapuk2
Krit Witthawassamrankul3

Abstract
Covid-19 pandemic impacted vastly on the global aviation industry, particularly, the national
Thai airline which is currently facing economic and business challenges. The major change affected the
huge reduction of human resources, particularly operators, who were not allowed to fly during covid-
19. Many flight attendants, who were in crisis, found unsecured in their operation position. At the same
time, the organization planned to develop the training curriculum for new skill requirement for the flight
attendants after covid-19 pandemic impact. The new training curriculum to be developed will help the
flight attendants be much skillful in order to cope with the work situation after covid-19 pandemic
impact. This research aimed to study the guidelines for training curriculum development for new skill
requirements for flight attendants after covid-19 pandemic impact. The researcher interviewed the needs
of new skills and the guidelines for training development from the 30 key persons divided into 15 flight
attendants and 15 cabin crews in charge, who were personally different in terms of age, work
experience, position and income per month. The results of the study found that the flight attendants
should study more variety of work, rather than in-flight service, programming and computers, such as
Amadeus, reservation. In addition, the flight attendants should gain more knowledge on service during
pandemic crisis. The guidelines for training curriculum development included 1) immigration rules and
regulation and third language improvement 2) attitude and positive thinking and 3) entrepreneurship
and business. The recommendation are 1) the study should include more external specialists in the
airline business and 2) the study should include some quantitative research instrument such as
questionnaires and tests for evaluation and measurement. For the policy and managerial implication,
the results should be transferred to the related department in order to develop the required skills and
search more instructors for the aforementioned training. This could help more human resource
development in the organization.

Keywords: Guidelines, Airline, Training Curriculum Development

1 Lecturer at Aviation Personnel Development Institute, Kasem Bundit University, 60 Romklao Road, Meenburi, Bangkok, Thailand.
E-mail: [email protected]
2 Lecturer at Aviation Personnel Development Institute, Kasem Bundit University, 60 Romklao Road, Meenburi, Bangkok, Thailand.
E-mail: [email protected]
3 Lecturer at Aviation Personnel Development Institute, Kasem Bundit University, 60 Romklao Road, Meenburi, Bangkok, Thailand.
Corresponding author: [email protected]

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Introduction
Human resources is the most important factors for organization development, particularly

airline service, which needs competent human resources in numbers of works, such as operational works
such as flight attendants and ground staff. (Anantaphong &Proyrungroj, 2020). Numbers of potential
employees in airline business were demanded in 2018 due to the high growth of aviation industry,
especially from Thai tourism and international product delivery (CAAT, 2019). Numbers of school,
therefore, aimed to produce qualified graduates and students to meet the demands of specific position
based on airline. However, there is little consideration on technology, innovation and crisis impact.
When the airline is facing the Covid-19 pandemic crisis, it found that the operators, particularly flight
attendants could not adjust themselves to the change. Many lost their jobs and found that their abilities
were not enough for the other positions in their airlines. Therefore, this research aimed to explore what
the new skills requirement for the flight attendants in the National Thai airline and what guidelines for
the training development for new skills after covid-19 pandemic crisis for these flight attendants should
be. The significances of the study were not only for the flight attendants’ coping with the pandemic
crisis, but also for the coming challenges they have to face. In 2018, it found that Thai national airlines
faced the challenges of its business operation. The accumulated loss has consecutively risen (Thai
Airways International Public Company, 2020). The company had to sell out the assets and reduced
numbers of employees, particularly flight attendants. The challenges were big in 2019 and bigger in
2020 when the covid-19 pandemic spread and respreads, such as flight cancellation, air navigation
service provider inconvenience, reduced aircraft use and international flight disagreement (ICAO,
2021). More and more flight attendants felt unsecured when their job and skills were not stable
(Thongtip, 2020). They need to be much flexible and competent in their work, vertically and
horizontally. Therefore, the training curriculum development for new skills should be provided for the
flight attendants.

Research Objectives
1. To study the guidelines for training curriculum development for new skill requirements for

flight attendants after covid-19 pandemic impact.
2. To explore the opinion of the flight attendants and cabin crews in charge.

Review of Literature
This section describes the materials and equipment used in the research, explain how the

samples were gathered, any randomization techniques and how the samples were prepared, explain how
the measurements were made and what calculations were performed upon the raw data and describe the
statistical techniques used upon the data. This study included the review literatures of training and its
curriculum development, airline training, change management, and related research as:

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The 6th RMUTT Global Business and Economics International Conference 2021 (RTBEC 2021)

Training is one of techniques to provide the knowledge. It is important for operational work
such as service and operational workers. Training could be prepared or off-the-job-training and
immediate training or on-the-job training, based on appropriateness of time, cost and effectiveness
(Duangsong & Suttichote, 2019). Good training should include the important factors such as trainers,
equipment, media, environment and trainees (Ford, Henderson & O’Hare, 2014). Well-organized
training should be constructed based on appropriateness of timing, lesson preparation with objectives,
and measurement and evaluation process. Then, after experienced training, the trainers can develop its
curriculum to meet the demands and suits for the trainers. Good curriculum development comes from
understanding the knowledge and skill requirement with objective and assessment.

Training in airline service, especially for flight attendants is unique. Some reasons makes the
training for flight attendants different is the type of airline. Flight attendants in premium airlines
normally need more skills to learn, including both working skills and interpersonal skills in order to
provide excellent service for first class and business classes. Training for the flight attendants are service
and serving skills, communicational skills, problem-solving skills, etc. (Fariduddin, Hum, Halim &
Jaafar, 2020). The ones who provide training for flight attendants, therefore, are the experienced flight
attendants who can transfer the knowledge with arts. Since the flight attendants work is dynamic due to
numbers of factor changes, such as technological and innovation change, rule and regulation change,
environmental changes; flight attendant training has to be revised and recurrent training, particularly,
safety and security training is compulsory for the flight attendants. (Salameh, 2016) Hence, the
curriculum development has to be considered for the situational changes, particularly innovation and
technology and pandemic.

Curriculum development for new skills of the flight attendants has been into the considered
issues since 2018 when the national airline encountered financial risks from the business operation
(Asian aviation staff, 2021). The problem was even worse when the airline faced covid-19 pandemic
problem. Reduction in numbers of flights limits numbers of flight attendants. Numbers of the flight
attendants could not find other job in different position. Many faced the challenges due to their
familiarity with the work pattern. Restructure and downsizing in the national Thai airline exposed the
risks to the flight attendants. Therefore, the curriculum development for new skills of the flight
attendants will help them to stay with the organization firmly and usefully. Generally, curriculum
development for flight attendants suit one period of time. When the situational change, new skills must
be provided for the flight attendants. It is possible that the flight attendants may have to learn new skills
beyond their work in order to stay in the airline (Limwirat, Promsawat & Klaisuwan, 2018).

A curriculum comprises numbers of courses with the notions of ‘must’ and ‘should’ (Liu and
Zhu, 2016). Therefore, to develop a new curriculum, it requires the guidelines to develop the
curriculum. The guidelines for curriculum development include understanding the situation, necessities
of the courses, adjustment of the previous courses and potentials of the new curriculum. Hence, to
discover the guidelines for curriculum development should be the first step in the process of the

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curriculum development. It has come before find the courses and writing the course descriptions.
Traditionally, airline curriculum development includes the requirement of rules and regulation of the
well-known international organization such as ICAO or The International Civil Aviation Organization,
especially rules and regulations for aviation safety and security, or CATT (The Civil Aviation Authority
of Thailand), the requirement of the airline service such as serving, interpersonal skills, problem-solving
skills, and the requirement of the competency such as knowledge, skills, attributes. The competency is
however, changed based on numbers of factors such as technology, innovation and economic. Human
resources in airline business need to update their competencies; otherwise, they will not be able to work
in dynamic change (Garcia, Pongkrapan, Sacares & Surinta, 2018).

Research Methodology
This research is qualitative and used the interview to study the guidelines for curriculum

development for the new skill requirements for flight attendants after covid-19 pandemic. The reason
of using the interview method was to gather more clarification the curriculum development, which
needs the explanation and the knowledge is rather tacit. The researcher gathered the data from the 30
key informants who were divided into 15 flight attendants and 15 cabin crew in charge (CIC). Both
flight attendants and cabin crews in charge provided the guidelines for the curriculum development for
the new skill requirement for flight attendants after covid-19 pandemic since the flight attendants were
the one who used the curriculum and could inform their needs for the curriculum development
guidelines. The cabin crews in charge were the one who provided the training and experienced the in-
fight service work, they could provide the guidelines for the curriculum development guidelines.

Therefore, the key informants were 15 flight attendants and 15 cabin crews in charge in the
Thai national airline, segmented by their personal factors in the below table (table 1). The data collection
obtained from the key informants was from March 10 –April 10, 2021. The selection criterion for every
key informant is the work experience of at least more than 1 year and they must work in this national
airline. Therefore, they know the organization background and culture.

The data analysis was divided into 2 parts. For the interview method, the answers from the key
informants gathered were used content analysis. For the questionnaire, the results were analyzed by
descriptive statistics as frequency and percentage. The quality of the interview questions had been
validated by 3 experts, who are Ph.D. instructors in the Aviation Institute and the questionnaires were
approved its content validity of more than 0.70 and reliability of 0.81.

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Table 1 Key Informants (n = 30)

Profile Factors Variables f %
6 20.00
Gender Male 24 80.00
5 16.67
Female 8 26.67
14 46.67
Age 23-32 years 3 10.00
3 10.00
33-42 years 10 33.44
14 46.67
43-52 years 3 10.00
15 50.00
53 and Above 15 50.00

Work Experience Less than 3 years *

3-10 years

10-20 years

21 and Above

Position Cabin Crew in Charge

Flight Attendants

*less than 3 years is the contractual period of work.

Research Results
The research results from the key informants has been divided into 2 parts as 1) the opinions of

the flight attendants (from the 4 questions) and 2) the guidelines for curriculum development for new
skill requirement of the flight attendants in Thai national airline.

The opinions of the flight attendants:
1. What are the environmental factors which the curriculum development?
The key informants informed that covid-19 pandemic was the most impactful factor which the
curriculum development should be considered. They recommended that the covid-19 pandemic exposed
many notions of training such as on-line training; off-the-job training, media for training should be
varied such as DVD and online because some physical locations of training were prohibited and some
flight attendants were quarantined of 14 days after flying. Covid-19 pandemic also forced the flight
attendants to be aware of the knowledge and the training of safety and security. The flight attendants
told that the curriculum should provide more knowledge on service performance during covid-19
pandemic with standard and measurement. Also, covid-19 pandemic drives the technological and
innovation movement. The flight attendants informed that they need to learn more technology and
innovation. During their work as flight attendants, they physically operated and rather used familiarity
in work. They should have more time to learn technology and new equipment, such as programming.
2. What are the organizational factors for the curriculum development?
The key informants informed that downsizing and restructuring in the organization is the factor
which should be considered for the curriculum development. There were 2 reasons of the downsizing
and restructuring as economic and business management. The organization used traditional

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management and functional structure. Therefore, the flight attendants only know their own jobs and
tend to work repeatedly since they found there is no need to improve their skills. When they work for
long time, they have to no step to go up or new career path. They felt loss and would like to upgrade
themselves. However, it is quite difficult for them to change when being old. To this, the flight
attendants recommended that the curriculum development should offer more and variety of courses,
related with airline functions for them such as Amadeus, cargo packing, reservation. This will be helpful
when moving to the new positions. Some of job rotation and job enlargement could help them as well
as training from the curriculum development. This program has been implemented in the airline for
years.

3. Do you have any suggestion for the curriculum development?
The curriculum development for new skills of flight attendants should not be scoped for the
flight attendants’ functions only. It is rather based on the competencies and aimed to increase
competencies of the flight attendants. In the future, it is likely that flight attendants have shorter working
duration such as contractual restriction. Technology and innovation can replace some job of flight
attendants. In addition, the curriculum development should provide some psychological lessons, such
as stress management, consultation, etc. and business lessons such business excel, entrepreneurship,
marketing and management. Some flight attendants who do not want to work more in-flight can switch
to training and management positions. And lastly, the curriculum development should concern
sustainability by learning. Due to the limitation of physical work, the flight attendants may not work
for a long time. There should be the courses for long-life learning and the work-related. This will help
the succession plan for the position.
The Guidelines of Curriculum Development for New Skills of Flight Attendants after covid-19
Pandemic
Based on the study, the guideline of curriculum development for new skills of flight attendants
after covid-19 pandemic should include 1) the knowledge and skills for the work after covid-19 and
during covid-19 such as safety and security, rules and regulations such as immigration rules and
regulations, updated aviation laws 2) attitude and positive thinking. Some psychological lessons should
be provided for the flight attendants who coped with stress and there should be some lessons for positive
thinking and 3) entrepreneurship and marketing and management for the flight attendants in case that
they will perform other functions in the organization. In addition, the third language and business soft
skills should be added.

Discussion and Conclusions
In conclusion, the flight attendants will need more variety of skills and tends to be job

enlargement, rather than job enrichment. This was the same as other operation works, such as hotels or
other functional works (Musili, 2010). The curriculum development for new skills for the flight
attendants after covid-19 should include the technology and innovation courses like other service in

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intense competition by technology and innovation era (Park, Lee & Nicolau, 2020). Human resources
in service industry like other industry cannot avoid the competition from technology and innovation.
Also, to develop the curriculum has to consider the organization changes, such as downsizing and
restructuring. Outsourcing and offshoring are also a factor for competition. In addition, the curriculum
development should be based on the competencies, rather than the functional work. Since service works
in the future will be much diversified, competencies to work in different areas in the companies are
important (Gibbs, Slevitch & Washburn, 2017) and lastly, to be sustainable, the flight attendants should
have life-long learning. They should learn from everywhere and every time, either during quarantine
from covid-19 pandemic or when they are alone. Last, the flight attendants should have some
entrepreneurship and marketing and management skills. This will benefit them and the business work
in the future. To the results of the study, it showed that after covid-19 pandemic impact, it is likely that
the airline human resources must be flexible and work in the diverse assignments. They have to change
their work based on functions but into the personal competencies. The human resource development
also has to adapt itself to the new management for the situation after Covid-19 and business
management change. It needs to improve more training and manage the needs of training based on
competencies. Cross training and small group training, which meets the personal development, should
be organized for both business and cost reduction purposes. The recommendation for the research are1)
the study should include more specialists in the airline business, rather inside cabin crews in charge in
the airline in order to see how competitor and industry practice and 2) the study should include some
quantitative research instrument such as questionnaires and tests; therefore, the results will be much
accurate, specific and measurable. For the policy and managerial implication, the results should be
transferred to the related department in order to develop the required skills and find more instructors
who possess the qualification to conduct the aforementioned training. This could help more human
resource development.

References
Anantaphong, W. & Proyrungroj, R. (2020). Flight attendants’s self-adjustment working for foreign

airlines. The Journal of Development Administration Research, 10(3), 15-21.
Asian Aviation Staff. (2021, March, 3). Thai Airways will shed workers, downsize planes in operation

in major restructuring to survive. Retrieved From https://asianaviation.com/thai-airways-will-
shed-workers-downsize-planes-in-operation-in-major-restructuring/
Civil Aviation Authority of Thailand. (2019, December, 31). State of Thai aviation industry 2019.
Retrieved From https://www.caat.or.th/wp-content/uploads/2020/06/STATE-OF-THAI-
AVIATION- INDUSTRY-2019.pdf
Duangsong, S. & Suttichote, S. (2019). Comparing training environments safety management systems
of C-Learning and E-Learning that results in the satisfaction of flight attendants: Thai Lion
Air. (Master Thesis, Kasem Bundit University, Bangkok, Thailand).

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Fariduddin, M.N., Hum, W.L., Halim, L. & Jaafar, M.J. (2020). Basic-Sim train-the-trainer: a
resuscitation training module for cabin crew in Malaya. Songklanakarin Journal Sciences and
Technology, 42(1), 73-80.

Ford, J., Handerson, R. & O’Hare, D. (2014). The effects of crew resource management (CRM)
training on flight attendants' safety attitudes. Journal of Safety Research, 48, 49-56.

Garcia, R.C., Pongkrapan, W., Sacares, R.T. & Surinta, N. (2018). Human Resource availability
situation of airline companies in Thailand. SSRN Electronic Journal, 1-16,
DOI:10.2139/ssrn.3308092.

Gibbs, L, Slevitch, L., & Washburn, I. (2017). Competency-based training in aviation: The impact on
flight attendant performance and passenger satisfaction. The Journal of Aviation/Aerospace
Education and Research, 26(2), 55-80.

International Civil Aviation Organization. (2021, March, 31). Economic Aspects of COVID-19 on
Civil Aviation. Retrieved From https://www.icao.int/sustainability/Pages/Economic-Impacts-
of-COVID-19.aspx

Limwirat, N., Promsawat, P. & Klaisuwan, R. (2018). The factors relating with personal development
case study of flight attendant, Thai Airway International Public Company Limited. Suan Dusit
Graduate School Academic Journal, 14(1), 31-42.

Liu, X.Q. & Zhu, W.Z. (2016). Towards an integrated approach to cabin service English curriculum
design: A case study of China Southern Airlines’ cabin service English training course.
Higher Education Studies, 6(2), 30-37.

Musli, A. (2010). Perceived effectiveness of training and development on performance of in-flight
attendants in Kenya Airways Limited. [Master thesis, University of Nairobi]. University of
Nairobi Research Archive.

Park, S., Lee, S.J., & Nicolau, J.L. (2020). Understanding the dynamics of the quality of airline
service attributes: Satisfiers and dissatisfiers. Tourism Management, 81, 1-15.

Salameh, Z. (2016). Perceptions of safety knowledge and skills in vocational training. International
Education Studies, 9(5), 133-146.

Thai Airways International Public Company. (2019). Annual Report. Retrieved from
https://thai.listedcompany.com/misc/ar/20200420-thai-ar2019-en.pdf on 18 May 2021

Thongtip, B. (2020). Coronavirus disease 2019 (Covid-19) problems and leadership potential for new
normal organization development. Journal of Social Science and Buddhistic Anthropology,
5(11), 434-447.

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Work-Stress, Coping and the Needs of Airline Customer Service Agents
during Covid-19 Pandemic Spread

Nutchirathorn Naulsom1
Krit Witthawassamrankul2

Abstract
This research aimed to study the work-stress, coping and the needs of airline customer service
agents during covid-19 pandemic spread. This researcher applied mixed method using both
questionnaire instrument and interview method. The researcher distributed the questionnaires
instrument to 400 airline customer service agents and interviewed 10 customer service agents during
15 October to 15 September, 2020 at Suvarnabhumi Airport. The statistical analysis for the
questionnaire was frequency, percentage, mean, S.D., t-test and One-way ANOVA and the content
analysis for the interview method. The results founded that the highest job stress during covid-19 came
from role ambiguities (mean = 4.41), then interpersonal problems (mean = 4.35) and economic
problems and role conflicts (mean = 4.27), respectively. The hypothesis testing results showed that only
different ages affected different stress of airline customer service agents. The interview results showed
that the airline customer service agents coped with the stress by compromising. They were flexible and
adjusted themselves with the situation during covid-19 pandemic. Their work-stress did not come from
the work-stress itself; however, it stemmed from the uncertainty of the environment and policy. They
needed more clarity and clarification of the updated policy. Therefore, information was the most useful
they needed. In addition, the unstable compensation caused their work-stresses.

Keywords: Stress, Airline, Customer Service Agent

1 Lecturer at Aviation Personnel Development Institute, Kasem Bundit University, 60 Romklao Road, Meenburi, Bangkok, Thailand
E-mail: [email protected]
2 Lecturer at Aviation Personnel Development Institute, Kasem Bundit University, 60 Romklao Road, Meenburi, Bangkok, Thailand
Corresponding author: [email protected]

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Introduction
Airline is one of the major parts in tourism and hospitality business bringing a large portion of

incomes to Thailand. The airline business includes both passenger and delivery service. Based on the
report in the last decade, the Thai airline business rapidly grows in numbers and qualities. Many low-
cost airlines opened its businesses to serve the demand of regional flying and neighbor and closed
countries, such as Vietnam, Malaysia, Singapore, China, Korea, Japan, etc. Therefore, it expands the
market and jobs as airline customer service agents, who are working with process and people with time
constraints (Civil Aviation Authority of Thailand, 2019).

Airline customer service agents are persons who assist the customers with itinerary changes,
flight reservations and questions about customer loyalty programs. They provide flight information,
issuing tickets, check-in service, checking boarding passes, solving ticket problems and checking
baggage for passengers. The airline customer service agent can upgrade the seats and reissue seats for
the passengers when no seats are available in the flight. They can work in many places based on their
functions, as call center for information and assistance, front desk of an airport, etc. Four types of airline
customer service agents are 1) Customer Service Representative: the one who is responsible for solving
the complaints and questions of the customer. 2) Airport Manager: the one who is responsible for the
smooth functioning of all the activities at the airport. 3) Retail Sales Associate: the one who is
responsible for assisting consumers in the collection and purchasing of products. 4) Flight
Attendant: the one who is responsible for ensuring the safety and security of the passengers during the
flight. Since each type has different functions and works, the stress is different. In general, work-stresses
of airline customer service agents were from people and process constraints. The more problems came
when they face the covid-19 pandemic in their work (Law, 2018; Burapharat, 2018).

Covid-19 pandemic has spread to Thailand since March, 2021. The pandemic caused changes
in service industry, particularly airline business due to the spread of virus from saliva. For the acceptable
case, the airline is allowed to operate. However, the airline customer service agents have to follow the
rules and regulation from the health unit and aviation organization. When the problem is not easy to
control, the airline customer service agents have to stop their works from flight cancellation, reduction
of workers in shift. This caused the problems of not enough compensation for the airline customer
service agents. Moreover, the operational process during covid-19 pandemic was longer (Maneenop &
Kotcharin, 2020). The passengers may be unsatisfied and affected by the stresses of the airline customer
service agents. Therefore, this research was conducted in order to study the work-stress, coping and the
needs of airline customer service agents during covid-19 pandemic spread (International Civil Aviation
Organization, 2021).

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Research Objectives
1. To study work stresses of airline customer service agents during covid-19 pandemic.
2. To discover coping and managing work stress of airline customer service agents during

covid-19 pandemic.
3. To explore the needs of airline customer service agents during covid-19 pandemic.

Review of Literature
Work-stress can be defined as a work related psychological pressure and a worker’s ability to

respond and grip the specific situation at workplace skillfully (Chen & Silverthorne, 2008), as the
experience of unpleasant negative emotions such as tension, anxiety, frustration, anger and depression
resulting from aspects of work (Salami, 2010) and as a series of physiological, psychological and
behavioral responses due to the continuing effects of one or more stressor on individuals in an organization
(Yan & Xie, 2016). Therefore, the work-stress included both mental and physical reaction from the works
and related to the work to the stressors who work in the organization. The stressors may experience
stresses from the works itself and showing their mentally and physically unpleasant reacts such as anxiety,
fear, anger, depression, etc. Working in airline business caused numbers of work-stresses due to the job
characteristics such as pressure from passengers, uncertainty of atmosphere and environments, or
expectation of the persons (Boonkao, 2015; Soo & Liew, 2020; Pi, Chiu & Lin, 2016). Factors affecting
work stresses could be from the work-related stressors such as task demand, role ambiguities, role
conflicts, ethical dilemmas, interpersonal problems, career development, and physical setting and personal
stressors such as family problems, economic problems and behavior symptoms. Since the work as airline
customer service agents is in service industry, the stressors face the stressors from service characteristics.

Research Methodology

The researcher used mixed methods in this study. The researcher distributed 400 questionnaires

as research instruments and interview 10 key informants as the research method. The questionnaire

consisted of 2 parts as 1) personal factors or demographic profiles and 2) factors affecting job stress

which includes work-related stressors and personal stressors. the obtained data from the questionnaires

were analyzed by using descriptive statistics as frequency, percentage, mean, standard deviation and
inferential statistics as t-test, One-Way ANOVA. The Likert’s Scale was used to measure the level of

stresses (10 factors of stresses). It indicated 5 ranges as 1 as lowest and 5 as highest. The interval in

each range was 0.80. The meaning was:

4.21 - 5.00 = Highest

3.41 - 4.20 = High

2.61 - 3.40 = Moderate

1.81 - 2.60 = Low

1.00 - 1.80 = Lowest

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The questionnaire has been approved its content validity by IOC of more than 0.72 and the
reliability by 10% tryout was 0.89. The researcher interviewed 10 key informants, who are the airline
customer service agents. The questions for interview were:

1. What are the stresses of airline customer service agents during covid-19 pandemic?
2. What are the coping and managing stresses of airline customer service agents during
covid-19 pandemic?
3. What are the needs of airline customer service agents during covid-19 pandemic?

Research Results

The questionnaire results of the factors affecting work stresses were divided into personal

factors or the respondents, factors affecting work-stress and the hypothesis testing for genders as:

Table 1 Respondents (n = 200)

Profile Factors Variables F%

Gender Male 200 50.00

Female 200 50.00

Age 18-25 years 40 10.00

26-30 years 171 42.75

31-35 years 149 37.25

36 and Above 40 10.00

Marital Status Single 199 49.75

Married 128 32.00

Separated 17 4.25

Others 56 14.00

Position Flight Service 95 23.75

Ground Service 87 21.75

Others 182 45.50

Work Experience 1-5 years 42 10.50

6-10 years 90 22.50

11-15 years 164 41.00

More than 15 years 146 36.50

Income per Month (Average) Less than 10,000 27 6.75

10,001-20,000 155 38.75

20,001-30,000 40 10.00

More than 30,000 178 44.50

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According to the Table 1, the results showed that male (200 respondents at 50%) and female
(200 respondents at 50%) equally responded the questionnaires. In terms of age, the highest age range
was 26-30 years (171 respondents at 42.75%) and followed by age between 31-35 years
(149 respondents at 37.25%). The highest marital status was single (199 respondents at 49.75%) and
the second one was married status (128 respondents at 32%). In the meantime, the highest numbers of
position was others (182 respondents at 45.50%) and second number of position was flight service
(95 respondents at 23.75%). The highest work experience was 11-15 years (164 respondents at 41%)
and the second rank of work experience was more than 15 years (146 respondents at 36.50%). The
highest income per month was more than 30,000 (178 respondents at 44.50%) and the second one was
10,000-20,000 (155 respondents at 38.75%).

Table 2 Factors affecting work stress

Personal Factors Mean S.D Meaning

1. Family problems 4.26 0.540 Highest

2. Economic problems 4.27 0.525 Highest

3. Behavior symptoms 4.21 0.519 Highest

4. Task demand 4.17 0.516 High

5. Role ambiguities 4.41 0.540 Highest

6. Role conflicts 4.27 0.546 Highest

7. Ethical dilemmas 4.21 0.546 Highest

8. Interpersonal problems 4.35 0.540 Highest

9. Career Development 4.26 0.525 Highest

10. Physical setting 4.26 0.545 Highest

According to Table 2, all factors affecting work stress were rated at a highest level, except task

demand (mean = 4.17). Out of 10 factors, role ambiguity was rated the first highest rank (mean = 4.41);

meanwhile, the second highest position was interpersonal problems (mean = 4.35).

Table 3 Hypothesis testing of different genders affected factors affecting work stresses

Factors affecting work stresses. Male Female T p-value

̅ S.D ̅ S.D 0.281
0.328
1. Family problems 3.45 0.76 3.56 0.77 1.081 0.446
0.330
2. Economic problems 3.45 1.14 3.55 0.74 0.981 0.137
0.249
3. Behavior symptoms 3.85 0.86 3.77 0.83 -0.764

4. Task demand 3.34 0.71 3.46 0.94 0.975

5. Role ambiguities 3.37 0.76 3.52 0.82 1.492

6. Role conflicts 3.42 0.76 3.53 0.75 1.157

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Table 3 Hypothesis testing of different genders affected factors affecting work stresses (Cont.)

Factors affecting work stresses. Male Female T p-value

̅ S.D ̅ S.D

7. Ethical dilemmas 3.20 0.94 3.34 0.75 1.489 0.138

8. Interpersonal problems 3.35 0.82 3.56 0.86 1.841 0.067

9. Career Development 3.30 0.74 3.28 0.91 -0.133 0.895

10. Physical setting 3.26 0.76 3.41 0.89 1.323 0.187

According to Table 3, hypothesis testing revealed that different genders have no difference in

each factor (for 10 factors) at a statistical significance level of 0.05 because every p-value was more

than 0.05. In addition, the other personal variables such as age, and marital status were not explored

here in this paper like genders since they had no difference in the beginning at 0.12, 0.41 and 0.27

respectively.

The interview results showed that:
1. What are the stresses of airline customer service agents during covid-19 pandemic?
The flight attendants informed that the causes of stress were from 1) work-related stressors and

2) personal factors. The work-related stressors of the flight attendants were from role ambiguities, long-
hour flying, and working with colleagues from different cultural backgrounds and attitudes. The
problems were from miscommunication. In addition, the flight attendants mentioned their stresses from
evaluation and promotion. They have to continue their working contract after monthly flight
monitoring. The expectation causes them stressful. The customer service agents informed that their
stress was from time pressure and flight schedule. The delay incurred cost and being rush caused
mistakes. Their problem was from not enough compensation, particularly in covid-19 spread, they had
to reduce their work hours and therefore, the compensation was less. Some customer service agents
informed the unclear job description problem caused confusion with work and job sharing. They wasted
time discussing their jobs with colleagues.

2. What is the coping and management of stresses of airline customer service agents during
covid-19 pandemic?

The airline customer service agents tended to compromise and manage themselves in the
situation. They check the situation more often and adapt themselves, instead. The flight attendants
tended to ask their colleagues, rather than purser for helps them when having problems. To customer
service representatives, they faced the problems by themselves and may ask helps from their supervisors
and colleagues. However, from the study, it showed that the flight attendants were less stressful when
coping with the situation since their works were based on flights. Once they finished their in-flight
service, they reported the cases and then they could move on the new flight and new experiences. In
opposite to the customer service representatives, they could not change their work atmosphere and their

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supervisor. They had to solve their continuous problems. During covid-19 pandemic, the coping and
managing stress for the two positions were different. The flight attendants had more standard and
measures to cope with the problems. For minor re-spread covid-19 problems, they were asked to follow
the rules of regulations of the aviation organization and for the big re-spread covid-19, the flights
attendants were not allowed to fly and may have to be quarantined for 14 days after flying with risks.
However, the customer service representatives had less standard and measures for coping and managing
stresses with covid-19, based on the different service provision and contact. They have to be aware and
update the information and judge by themselves for some cases, which is complicate and new.

3. What are the needs of airline customer service agents during covid-19 pandemic?
The customer service representatives needed more updated information to manage their work.
They found it was difficult to manage the problem when getting the information immediately before
their work, particularly some positions which requires the time for preparation and guidance such as
supervisor. The Thai airline personnel also informed their needs regarding their compensation and
stability of their work. They have to prepare for their family. For the flight attendants, they are riskier
than the customer service agents due to their nature of work. Most of income was from per diem, which
is variable cost. In case of no flight, it means the flight attendants had very low compensation, in
opposite to the customer service agents, who have large proportion of permanent income. However,
both need welfares and benefits.

Discussion and Conclusions
Based on the demographic factors, it showed that there were equally 200 customer service

agents (= 50%) and 200 flight attendants (= 50%). Most respondents were females (= 53.50%) and
males (= 46.50%). The highest age range was around 26-29 years old (= 42.75%) and then the age range
around 31-35 years old (37.25%). The highest marital status was single (= 49.75%) and then married
(= 32%). The bachelor degree level were highest (= 45%) and they work with flight service (= 23.75%)
and ground service (= 21.75). The highest work experience was around 11-15 years (= 41%) and then
around 6-10 years (22.50%), the average income per month was more than 30,000 baht (44.50%) and
then 10,000-20,000 baht per month (= 38.75%), respectively.

Overall factors affecting the stress of airline customer service agents was at a highest level
(mean = 4.46). Based on the 10 factors of stresses of airline service agents, role ambiguities was highest
(mean = 4.41), then interpersonal problems (mean = 4.35) and economic problems and role conflicts
(mean = 4.27), respectively.

The research found that airline customer service agents have almost highest stresses for every
factor during covid-19 pandemic. To work-related stress, they stressed much on their role ambiguity.
To this, it was possible that at the time there is unclear role. The airline customer service agents may
found lack of clarity, certainty and/or predictability. Role ambiguity may be from unclear job
description and/or uncertain organizational objectives. This can create burnout from the airline

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customer service agents (McCormack & Cotter, 2013). Some airline customer service agents stressed
much on economic and work environment due to changed compensation from the work and instability
of work. However, the stresses of airline customer service agents were different from the positions and
works. The study also showed that job characteristics, role of employee participation, progression of
careers, relationship in the workplace, organization structure and climate were related with the level of
stress among ground service agent (Amornpipat, 2020). The research also showed that flight attendants
expected more on their career advancement and therefore, they may face stress easier if they could not
balance their satisfaction and self-fulfillment, particularly younger flight attendants (Majali and Shana,
2019). For the managerial recommendation, the management persons should identify clear job
description and roles since role ambiguity and unclear job description was at a highest level. Regarding
issues of covid-19 impact, the management persons should reduce the economic and work environment
impact from covid-19. The plan for compensation in each step should be announced in order that the
airline customer service agents could prepare and adjust in each step. The future research should be
focusing on role ambiguity because this is the highest stress found in the study. The study should be
exploring on job description, responsibility and assignment.

References
Amornpipat, I. (2020). Stress of employees working in the aviation industry: A study of Bangkok

Airways Limited ground service agents. International Journal of Scientific and Research
Publications, 10(8), 441-445.
Boonkao, A. (2015). Factors relating to stress at work of flight attendants. Journal of Pacific Institute
of Management Science, 1(1), 31-40.
Burapharat, Y. (2018). The relationship between positive psychological capital and job burnout: A
study of Thai Airways Internal flight attendants. (Master Independent Study, Kasem Bundit
University, Bangkok, Thailand).
Chen, J. & Silverthorne, C. (2008). The impact of locus of control on job stress, job performance and
job satisfaction in Taiwan. Leadership & Organization Development Journal, 29(7), 572-582.
Civil Aviation Authority of Thailand. (2019, December, 31). State of Thai aviation industry 2019.
Retrieved from https://www.caat.or.th/wp-content/uploads/2020/06/STATE-OF-THAI-
AVIATION-INDUSTRY-2019.pdf
International Civil Aviation Organization. (2021, March, 31). Economic Aspects of COVID-19 on
Civil Aviation. Retrieved from https://www.icao.int/sustainability/Pages/Economic-Impacts-
of-COVID-19.aspx
Law, C.C. (2018). A Practical Guide to Airline Customer Service: From Airline Operations to
Passenger Services. California: Brown Walker Press.
Majali, S.A. & Shana, Z. (2019). Sources of stress and coping strategies among flight crew
Psychology and behavioral science international journal, 12(3), 1-9.

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Maneenop, S. & Kotcharin, S. (2020). The impact of Covid-19 on the global airline industry: an event
study approach. Journal of Air Transport Management, 89, 101-120.

McCormack, N. & Cotter, C. (2013). Managing burnout in the workplace. London: Chandos
Publishing.

Pi, C.T., Chiu, S.K. & Lin, J.Y. (2016). Effect of employee work stress, work satisfaction and work
values on organizational commitment. Business & Entrepreneurship Journal, 5(1), 1-3.

Salami, S.O. (2010). Mentoring and work attitudes among nurses: the moderator roles of gender and
social support. Europe’s Journal of Psychology, 6(1), 102-126.

Soo, H.S. & Liew, S.A. (2020). Airline employee’s health and stress in Malaysia. European Journal
of Molecular & Clinical Medicine, 7(6), 2248-2254.

Yan, H. & Xie, S. (2016). How does auditors, work stress affect audit quality? Empirical evidence
from the Chinese stock market. China Journal of Accounting Research, 9(4), 304-319.

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Influence of e-Commerce Marketing Mix and Technology Acceptance on
Loyalty in Online Application “Shopee”

Vincent Didiek Wiet Aryanto1
Darin Portangtam2

Noppawan Musicabutr3
Wisit Rittiboonchai4
Abstract

The objective of this research is to study the influence of e-commerce marketing mix on loyalty
in online application “Shopee”. The research samples were 571 Thais and Indonesians. Data were
analyzed with percentages, confirmatory factor analysis, path analysis, and structural equation model
(SEM). The results indicated that e-commerce marketing mix affected the loyalty of the product through
“Shopee” application with no statistical significance (DE = 0.043), but there was statistical significance
(IE = 0.691) for the indirect influence. In conclusion, e-commerce marketing mix would not affect the
loyalty if it was not transmitted through technology acceptance.
Keywords: Technology Acceptance, Loyalty, Online Application, E-commerce Marketing Mix

1 Professor of International Marketing, Digital Marketing, Universitas Dian Nuswantoro, University Semarang, Indonesia,
E-mail: yang diverifikasi di dsn.dinus.ac.id
2 Faculty of Management Nakhon Pathom Rajabhat University, Thailand. E-mail: [email protected]
3 Independent scholars. E-mail: [email protected]
4 Faculty of Management, Nakhon Pathom Rajabhat University, Thailand
Corresponding author: [email protected]

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Introduction
The digital world plays a huge role in everyday life; therefore, it affects the business, in which

buyers and sellers can contact each other easily, resulting in efficiency in speed and cost reduction in
various aspects of consumers' purchasing decisions. The e-commerce market in Thailand continues to
expand continuously (Vapeevuttikorn & Changchenkit, 2021) and it is driving the new generation to
become entrepreneurs. There are accessible marketing channels and inexpensive public relations that
can be easily use through mobile applications. According to National Statistical Office Thailand survey
(2021), the number of smartphone users age 6 and older has continuously been increased from 5 million
Thais to 31.7 million Thais since 2012. From the survey, most smartphone users’ activities were social
networking (91.5%), downloading movies and music (88.0%), uploading data (55.9%), and followed
by the news (46.5%). The study of the growing online market could be useful and revealed the
purchasing behavior of modern consumers (Ruenrom, 2018). Online shops on Shopee application are
gaining immense popularity with consumers. The application was launched in Singapore in 2015 with
target consumers in Southeast Asia and Taiwan. It offers fully functions social marketplace on mobile
phone which users can buy and sell from anywhere at any time. In addition, it provides logistics support
and payment platform to facilitate safety trade for users (Phewlhueng, 2015). Shopee also differentiates
itself by having "Shopee Guarantee", a system that ensures the safety and confidence for online trades
as the payments will be hold and made to the sellers when the buyers receive their orders. Business
model of Shopee mainly started with consumer-to-consumer (C2C), then over period of time has
become business-to-consumer (B2C) and now is a hybrid model which is considered to be an advantage
for Shopee users compared to its competitors (Sanook, 2016).

In conclusion, the modern online business must gain a competitive advantage by building long-
term relationships with customers in order to achieve confidence, satisfaction and loyalty which will
increase the return to the company sustainably (Fatemeh & Ahmad, 2013, Aka, Kehinde & Ogunnaike,
2016). Therefore, e-commerce marketing mix and technology acceptance are required in order to
generate online ordering via website or application. These could affect the consumer purchasing
decision process, resulting in the value of investment, and creating competitive advantage. The
decision-making process must be developed to create customer loyalty to the point where it can convert
customers to partners who are ready to generate a wide spread of word of mouth on social networks.
This research focuses on customers with purchasing experiences through “Shopee” website or
application in Thailand and Indonesia. The research results will be useful for the stakeholders and can
be used to develop marketing strategies in the online social era to the fullest.

Research Objective
To study the influence of e-commerce marketing mix on loyalty in online application “Shopee”.

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Literature Review
For the literature review, this research focuses on key variables including:

Electronic Commerce Marketing Mix
The concepts of online marketing mix that consists of 6Ps are:
1. Product refers to things - can be both tangible and intangible - that are offered and sold to

customers in different ways to meet the needs of customers. Online trading has to be very transparent
with one another as it is done without seeing or touching product or service, therefore the quality of
product or service should be guaranteed, and shipping process has to be done with great supervision in
order to build trust among customers. In case of any errors or misunderstandings happen, complaints
may arise and lead to a negative image and may affect other customers relationships especially in the
digital age where Word of Mouth (WOM) and negative information or experiences travel fast to society
(Isabelle, Lova & Line, 2016).

2. Price refers to things that defines the value of a product in monetary terms or is its acceptable
value in exchange. Price is another important factor affecting consumers' purchasing decisions as they
usually compare the price with the value of the product.

3. Place refers to the process of moving products from the manufacturer to the customer via
online trading, websites, and social networks. Place factors with technology acceptance theory include
structure and layout design for quick and easy operation, ease of access to information, straightforward
ordering processes and systems, and convenience way to contact the seller. In addition, dissemination
and public relations provides opportunities for customers to recommend and express which helping
online stores to improve and develop products or services to meet customer needs more efficiently
(Morgan & Hunt, 1994, Yadav & Singh, 2014).

4. Promotion refers to the communication between seller and buyer or target groups with
important objectives to inform or influence product demand and purchase decisions through marketing
activities.

5. Privacy refers to policies set by traders or organizations to protect personal information and
build credibility as consumers are required to disclose various personal information such as name,
address, telephone number, e-mail, or credit card number. Therefore, maintaining customer privacy and
the stability of the system are important factors affecting customer trust which will lead to purchasing
decisions.

6. Personalization refers to interactive services between traders and individual customer to
deliver what customer needs. as the technology evolves, online channels are constantly evolving. Due
to the development of online technology, traders can provide a personalized services to customer where
the sellers can interact directly with their customer (Wongnitchakul, 2012, Pogorelova, Yakhneeva,
Agafonova & Prokubovskaya, 2016).

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Technology Acceptance
Technology acceptance can be considered a social behavior because each person has different

levels of technology acceptance. Human technological readiness will be driven by two factors: positive
factors that support a more inclusive society and negative factors that hinder technological readiness.
Positive factors include the social environment that contributes to the optimism of technology, such as
improving human livelihoods, creating more benefits, etc., and the atmosphere that interested in and
likes to experiment with new technologies. Utilizing technology and innovation that lead to sustainable
development, traders have to understand nature and social behavior in order to provide strategies for
building confidence, willingness, and motivation to make it more common for users to be ready and
confidence to accept technology and innovation (Tantayanon, 2017).

Technology acceptance has important elements including
1. Perceived Usefulness is the degrees of belief that the use of information technology can
increase efficiency and productivity. In technology acceptance theory, benefit perception is a key factor
indicating the level of adoption or technology usage because perceived benefits have a direct influence
on acceptance behavior and indirect influence on usage through acceptance behavior (Venkatesh, 1999).
The main factor contributing to the high value and rapid growth of Internet-based trading is consumers
awareness of the benefits of online trading such as time saving when purchasing products also being
able to reach consumers better than offline stores (Vijayasarathy, 2002), variety of products and prices
to meet customer needs (Gupta, Su & Walter, 2004) because customer can instantly compare prices
(Verhoef & Langerak, 2001) with amount of information or description about the product, ease of use
and convenience on product selection throughout websites.
2. Perceived Ease of Use is the degree of perception that technology should be user friendly –
easy and effortless to use. The perception has direct influence on the use of the system and indirectly
influence the use of the system through the perceived benefit (Davis, Bagozzi & Warshaw, 1989;
Venkatesh, 1999). The online store website, therefore, should have a user-friendly design, reliable, and
suitable for every user.
3. Intention to Use occurs when (1) users accept persuasive behavior due to rewarded or non-
punitive expectations (2) users accept social influences on satisfaction relationships with others and (3)
users appreciate the inner values when accept social influences as that influence is worthy of the value
it deserves.
4. Perceived Risk is when uncertainty in finance, product quality, social psychology, and
physical. It can be referred to the uncertainty over the time a customer spends on online transactions.
As Forsythe and Shi (2003) defined the meaning of risk perception to the user's beliefs about gaining
or losing when deciding to accept technology which are the important variables to users behavior when
users decide to embrace the technology if they believe the technology is at low risk. Thom (2000)
proposed that online stores have disadvantages and risks when it comes to payments and refunds which
also include customer services and the cancelling orders. Customers feel insecure about their security

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and privacy when shopping through an online store. Customers feel insecure about their safety and
privacy when making purchases through online stores because they feel that online payments do not
have sufficient security systems as much as offline stores.

5. Attitude toward Using is psychological inclination expressed by assessing the degree of
technology liking or dislike (Eagly & Chaiken, 1993). Attitudes usually affect the use of technology
and also influence the intentions of technology acceptance.

6. Actual Use refers to the intention to be used and accepted in the technology. Turner et al.
(2010) suggested that technology implementation is the destination of technology acceptance. However,
it is usually validated by using a measure of behavioral intention to use rather than actual usage.

Loyalty
Customer loyalty refers to customer positive feelings, attitudes, and impressions on online

stores. These sensations appear from self-processing which develop from having a good relationship
with the stores which could be result in repurchasing rom the stores and recommend to others (Lin,
2013, Wong, Lo & Ramayah, 2014).

From literature review, customer loyalty, especially electronic loyalty, could be summarized as follows:
1. Repurchasing: is a key component of measuring customer loyalty. When customers
intentionally and repeatedly repurchasing, it shows the loyalty to the brand or the stores and the
confidence that have
2. Centrality: which create brand loyalty arises from consumer's belief with the brand and
finally creates positive word-of-mouth to encourage family, friends, acquaintances to purchase from the
brand. Nowadays, technology has made it possible for word-of-mouth to be online rather than offline
such as writing and posting reviews on social media platforms, and others share the link until it becomes
a viral (Wong, Lo & Ramayah, 2014).
3. Accessibility: the electronic loyalty website differs from other loyalty as it can be measured by the
number of memberships on the website. Loyal customers would fill out their personal information because
they would like to make frequent purchases and feel to be part of the brand (Lin, 2013).

From reviewing the literature, the conceptual framework can be defined as follows:

Figure 1 Conceptual Framework

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Research Methodology
The researchers collected online questionnaires from 571 Thais and Indonesians customers who

have purchased products online from “Shopee” application, using Hair et al. (2010) sample size
criterion, 20 -50 samples were defined per observable variable. This research has 15 observable
variables and 38 samples per observable variable therefore the sample would be at least 570 samples,
derived by convenience sampling. The questionnaire passed the content validity test from 3 experts.
Research results

Most of the respondents were female (73.56%), aged 25-35 (54.47%), and mostly were
company employees (37.13%), with moderate numbers of Thai and Indonesian nationalities (50.86
percent and 49.04 percent, respectively). For path analysis results, the influence of e-commerce
marketing mix and technology acceptance on the loyalty of online shopping through “Shopee”
application can be presented as follows:

Figure 2 Influence of e-commerce marketing mix and technology acceptance on loyalty in online
application “shopee” (before model adjust)

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Figure 3 Influence of e-commerce marketing mix and technology acceptance on loyalty in online
application “shopee” (after model adjust)

Table 1 Verification of conformity with the empirical data

Indicator criterion Before adjust The result of After adjust The result of

consideration consideration

χ2/df < 5 7.177 × 2.143 √

RMSEA 0.03-0.08 0.104 × 0.045 √

NFI > 0.90 0.909 √ 0.978 √

CFI > 0.90 0.920 √ 0.988 √

GFI >0.90 0.865 × 0.967 √

SRMR < 0.05 0.0525 × 0.0274 √

Note: √ Refers to pass the index test result criteria used to verify the conformity and consistency of the

model to the empirical data.

The results of the analysis of indices used to verify the conformity and harmony of the model

to the empirical data. New component analysis the results of the harmonization assessment of the model
showed that χ2 = 147.87, df = 69, χ2/df = 2.143, RMSEA = 0.045, NFI = 0.978, CFI = 0.988,

GFI =0.967, SRMR = 0.0274 The new model has better empirical consistency because it is consistent

with sufficient empirical data. Analysis results can be explained from internal latent variables. To the

internal observable variable and from external latent variables go to the externally observed variables

from Table 2-3

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Table 2 Path analysis

Technology acceptance Loyalty online shopping

R2=0.519 R2=0.954

DE IE TE DE IE TE

Electronic commerce marketing mix 0.713 - 0.713 0.043 0.691 0.734

0.044 0.044 0.091 0.051 0.046

16.300 16.300 1.25 13.530 14.250

Technology acceptance 0.969 - 0.969

0.052 0.052

18.781 18.781

Note** EP = Estimation parameter, SE = Standard error, t-value

DE=Direct effect / IE = Indirect effect/ TE = Total effect

Loyalty on purchasing via “Shopee” was driven by the collective influence of technology

acceptance (TE = 0.969) and e-commerce marketing mix (TE = 0.734) with statistical significance and

a predictive power of 51.90%.

For the direct influence, e-commerce marketing mix affected the loyalty of the product through
“Shopee” with no statistical significance (DE = 0.043), but there was statistical significance (IE=0.691)

for the indirect influence. In conclusion, e-commerce marketing mix would not be affected by the
loyalty through “Shopee” if it was not transmitted through the technology acceptance

Table 3 Confirmatory factor analysis λ t-value R2
Matrix LAMDA - X
Electronic commerce marketing mix 0.648 20.876** 0.653
Product :PRD 0.705 19.691** 0.597
Price :PRI 0.713 14.060** 0.338
Place :PLA 0.649 12.021** 0.270
Promotion :PRM 0.665 20.115** 0.591
Personalization :PER 0.868 19.656** 0.876
Privacy :PRV
Technology acceptance 0.750 - 0.729
Perceived usefulness: PU 0.779 35.708** 0.780
Perceived ease of use: PEU 0.784 27.287** 0.756
Intention to use: IU 0.744 26.571** 0.737
Perceived risk: PR 0.806 26.158** 0.717
Attitude toward using: ATU 0.663 21.202** 0.562
Actual use: ACU

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Table 3 Confirmatory factor analysis (Cont.) λ t-value R2
Matrix LAMDA - X

Loyalty online shopping

Confidence: CONF 0.727 - 0.590

Centrality: CENT 0.831 24.892** 0.739

Accessibility: ACC 0.768 20.231** 0.647

* Significance level < .05 ** Significance level< .01

The results based on weight factors indicated that centrality had the most weight factor on the
loyalty on trading through “Shopee” and confidence had the least weight factor on repurchasing. For

technology acceptance, attitude toward using had the most weight factor while actual use had the least.

For e-commerce marketing mix, factor loading in order was privacy, place, and price respectively.

Summary and Discussion
1. Loyalty through “Shopee” application had overall influence on technology acceptance and

e-commerce marketing mix with statistically significant indicated that these two factors played a vital
role on online transaction. This finding was consistent with Vapeevuttikorn and Changchenkit (2021)
and Phumpri, Pongsittikanchana and Rittiboonchai (2017) which showed that creating digital marketing
communications awareness through e-commerce required an internet search engine, digital media for
public relations, advertising banner, social media marketing, and word-of-mouth to influence
consumers decisions and loyalty.

2. When considering only direct influence, the result revealed that e-commerce marketing mix
did not have a statistically significant effect on loyalty on “Shopee” application. This finding was not
consistent with Kitiyanan et.al. (2019) which suggested that marketing mix factors had an influence on
purchasing via e-commerce. This might be due to the different of the samples as the prior research were
college students and this research were working people.

3. E-commerce marketing mix had a statistically significant impact on loyalty through
technology acceptance. This finding was consistent with Chaimuang, Saefung and Kongkerd (2020)
that said the application of e-commerce technology should be used integrated with marketing strategy
to create customer confidence and long-term relationships that eventually lead to loyalty.

Suggestions from Research
1. This research affirmed that e-commerce marketing mix would generate customers loyalty for

“Shopee” application through technology acceptance. Therefore, the integration between the marketing
mix and the technology acceptance is something that entrepreneurs need to develop in order to create
an appropriate marketing strategy.

2. The results on weight factors found that “Shopee” application has the strengths on privacy,
distribution channel, and pricing strategy. The areas that need to be improved were the uniqueness of

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the product when compared with competitors. Entrepreneurs need to study and develop marketing
strategy to meet customers’ needs.

3. For loyalty, “Shopee” has the strength in centrality – able to get into consumer heart. Brand
loyalty happened when it was linked to consumers belief and make consumers appreciate the brand.
But for confidence, it needs to be developed to encourage repurchasing.

Suggestions for Further Research
1. This research targeted on Thais and Indonesians customers only. Further study may focus on

ASEAN customers and study on other shopping applications.
2. This research focused only on quantitative research. Further study may expand by conducting

additional qualitative research.
3. The research collected data from consumers perspective only. Further study may study on

the entrepreneurial side.

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Heuristic-based Multiple-criteria Analysis for Medical Technology
Recruitment Problem with Weighted Average Competency Gap

Rachasak Somyanonthanakul1
Jiraporn Gatedee2

Abstract
Medical technologists play a fundamental role in the diagnosis of disease in patients. A
recruiting of a medical technologist for vacant job positions, most hospitals or medical laboratories
consider the congruence between new medical technologies and jobs (or positions) since it is known to
contribute to the hospital’s or medical laboratory productivity and service efficiency. For each job,
important core, technical, and behavioral competencies are defined and their minimum required levels
are set. It is then the purpose of the hospital’s or medical laboratory to assign new medical technologist
to these jobs such that the maximum person-job fit is achieved. In this paper, we formulate the medical
technologist recruitment problem as the multiple-criteria employee-job assignment problem. Its
objective is to assign a new medical technologist to the vacant jobs so as to minimize the total weighted
average competency gap. We develop a heuristic-based multiple-criteria analysis for solving a new
medical technologist recruitment problem. A numerical example is given to demonstrate the
computation procedure and its result. The assignment results obtained from the optimization model and
the heuristic-based multiple-criteria analysis are also compared.

Keywords: Human Resource Development, Medical Technologist, Multi-Criteria Analysis.

1 Lecturer at College of Digital Innovation Technology, Rangsit University, Pathum Thani, Thailand.
2 Assistant Professor at Faculty of Medical Technology, Rangsit University, Pathum Thani, Thailand.
E-mail: [email protected]
Corresponding author: [email protected]

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Introduction
Achieving the optimal level of service efficiency is the goal of healthcare organization. The

financial well-being of the organization and competitiveness in global markets are strongly influenced
by its ability to reach such optimal level with its limited resources, reputation, materials, equipment,
energy and staff. With today’s fast changing market trend and customer demands, introductions of new
services, and innovations in healthcare operations, every organization has to continuously improve its
efficiency through more effective and efficient use of its limited resources. (According to John Storey
(2016), “effective” means that an organization produces the right quality and quantity of services for
the society, while “efficient” means that an organization uses the minimum amount of resources needed
to produce its services.) Among them, the human resource is perhaps the most difficult one to manage
since it is the least flexible component of the service system and efficient a medical technologist is
scarce.

As such, it is essential that the hospital or medical laboratory have to recruit the right medical
technologist and assign them to the right jobs so as to ensure not only an increase in work efficiency
and job satisfaction, but also a decrease in management cost. Through human resource management
(HRM), the productive contribution of individual a medical technologist can be improved in ways that
are strategically, ethically, and socially responsible (John Storey, 1996). To achieve this purpose, the
organization has to obtain, develop, utilize, evaluate, maintain and retain its efficient a medical
technology. Improving their knowledge, skills, and abilities is also one of the responsibilities of HRM.
This issue has always been essential since high work efficiency also leads to high productivity.

To prevent a mismatch between newly recruited a medical technologist and jobs, an employee-
job assignment that maximizes person-job (P-J) fit to help to increase their work efficiency and enhance
their job satisfaction is needed. Many researchers have studied P-J fit by considering various measures
and found that proper matching between a medical technologist and jobs leads to more positive
outcomes than negative ones. Berisha and Lajçi (2020) used a person-environment fit conceptual model
based on the degree of compatibility between individuals and situational characteristics. The results
from the model imply that any misfit in person and environmental components could lead to lower job
satisfaction, lower performance, and higher occupational strain. Kalayathankal et al. (2021) applied a
fuzzy number approach to select the better candidates under various evaluation criteria among available
personnel and jobs in an industrial environment. Nanu (2020) measured the person-organization fit and
used it as a predictor of the medical technology attitude toward the organization. Kolawole et al (2020)
conducted a survey to determine decision factors used in the industry to assign project managers to
projects. They developed a matching model in which the important inputs are the specific requirements
of the particular projects and the skills and capabilities of the potential candidates. Wang et al. (2020)
identified the leadership styles of personnel to be a critical factor to fit with the requirements in
employment modes. A perfect congruence between them would lead to an effective utilization of human
capital.

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In many hospitals, the assignment of a medical technologist to jobs is based on the subjective
opinion of a designated person or team. A lack of quantitative measures and an appropriate decision-
making tool contributes to the common use of subjective judgment to decide who will be assigned to
which job. Savino et al. (2020) formulated the employee-job assignment problem (EJAP) as three linear
programming models and used two person-job (P-J) fits, competency- based (C-based) and preference-
based (P-based) that are quantitative measures of the levels of work efficiency and job satisfaction,
respectively, as objective criteria. When solving EJAP to optimality, only one solution (the optimal
solution), which may or may not be usable, will be generated. From the sensitivity analysis, it was found
that the optimal employee-job competency gap is more sensitive to the weight of the core competency
category than that of the functional competency category.

In this paper, we consider the medical technology recruitment problem as the multiple-criteria
employee-job assignment problem. Its objective is to assign a medical technology to vacant jobs so as
to minimize the total weighted average competency gap. A heuristic-based multiple-criteria analysis is
proposed for solving large-sized a medical technology recruitment problem. After describing the
algorithm, we provide a numerical example to demonstrate the computation procedure and its result.
The assignment results obtained from the optimization model and the heuristic-based multiple-criteria
analysis are also compared.

Person-job fit
Person-job fit (P-J fit) can be conceptualized as the degree to which an individual’s preferences,

knowledge, skills, abilities, needs, and values match job requirements (van Hooft et al 2020). Studies
have shown that P-J fit is associated with job performance (Kaur, 2020), job satisfaction, and career
success (Aydin Kucuk, 2020). Savino et al. (2020) developed two quantitative P-J fits to represent the
degree of compatibility between a person and a job based on competency and job satisfaction,
respectively. When viewing the compatibility measure based on the competency, such P-J fit is called
“competency-based P-J fit.” When the assignment is considered according to the job preference of a
medical technology (meaning that a medical technology is allowed to choose a list of jobs to which they
would like to be assigned), P-J fit is then called “preference-based P-J fit.”.

Valdez (2010) have been defined the competency as “the ability to perform the activities within
an occupation or function to the standard expected in employment”. The term “competency” thus
embodies attributes such as knowledge, skills, abilities and attitudes required in professional practice.
Competency may be core, general or task-specific. Examples of core competencies are literacy,
numeracy, reliability, communication skills and ability to work in teams. General competencies refer to
competencies for the particular profession, as in the case of the Medical Technology profession i.e.,
general competencies of medical technologists or medical laboratory scientists. In contrast, task-
specific competencies refer to individual disciplines in the practice of the profession (e.g. hematology,
microbiology, etc. for Medical Laboratory Science or Medical Technology profession).

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Medical technologist combines the challenges of medicine with scientific knowledge. Medical
technologists also called clinical laboratory scientists perform in the laboratory a wide range of tests
that play a vital role in the detection and treatment of diseases and disorders. Laboratory tests can be
simple or complex usually requiring the use of microscopes, state-of-the-art instruments and computers.

In a clinical setting, medical technologists perform and/or supervise the performance of
analytical testing of blood, body fluids, and other types of biological specimens. They identify the
presence of bacteria, fungi or parasites or prepare blood units for purposes of transfusion. Typical areas
in the clinical hospital setting are hematology, chemistry, immunology, blood bank, and microbiology.
Medical technologists are trained to use skills in critical thinking, problem solving and situational
analysis that arise in the clinical laboratory. Using their technical skills and knowledge of disease status,
medical technologists are an integral staff for patient diagnosis and treatment. Careers in medical
technology are available in hospital laboratories, forensic laboratories, reference laboratories, molecular
diagnostics, veterinary offices, doctor ’s offices, management, industry, pharmaceutical and cosmetics
industries, medical sales, and educational and research institutions. The most marketable skill of an
entry-level medical laboratory technologist is the application of principles learned in the educational
program for use in a broad spectrum of laboratory activities in the work environment. Over the past few
years there was concern for how well the “syllabus approach” met the needs of programs preparing
entry-level medical laboratory technologists for a workplace that is rapidly changing due to new
technology in the health care system.

According to Harris et al. (1995), competency-based education is structured around competent
performance by learners, where competence is defined in terms of achievement of the level of work
standards. The quality of education is more readily measured. Since the performance levels are
described by standards of consistency of expected performance between programs and schools. This is
more easily determined.

Competency-based curriculum refers to an organized set of learning experiences based on
knowledge, skills and abilities as demonstrated by the learner derived from expectations explicit in the
stated desired mastery levels. The competency-based curriculum dwells on competencies (knowledge,
skills, abilities) demonstrated by the learner (1) as derived from industry-identified skill standards; (2)
stated so as to make possible assessment of learner behavior in relation to expected levels of mastery
under specified conditions; (3) based and in harmony with specified competencies and, (4) made public
in advance. Assessment of the student competencies is based on (1) their performance as the primary
source of evidence; (2) performance is measured against a competency standard and one that strives for
objectivity (Harris et al., 1995).

In the past, the Research and Development Committee and the Board of Governors of the ASCP
Board Registry initiated a study to identify the professional competencies for the medical laboratory
technologist certification examinations. Six general competencies were identified, namely (1) technical
skills; (2) judgement and analytical decision making; (3) knowledge base; (4) communication; (5)

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teaching and training; and (6) supervision and management. Specific responsibilities were identified
and validated under the six general competencies. Then, The Canadian Society for Medical Laboratory
Science (CSMLS) has identified on the six competency categories namely: (1) safe work practices; (2)
data gathering and specimen procurement or receipt; (3) analysis of specimen and validation of results;
(4) analytical techniques; (5) interpretation and reporting of results; and (6) quality management. Each
competency category has its own competency indicators where points or marks are being assigned when
used in assessing an entry-level medical technologist.

Here we define competency as the medical technologist’s attribute or the job characteristic
determined by the international standard that is relevant to employee-job assignment (EJA). The
competence level can be assessed quantitatively (based on test scores) or qualitatively (based on the
supervisor’s opinion). A competency must be carefully defined so that it can truly reflect job
performance. In modern organizations where work efficiency is an essential issue, competency plays
an important role in the career development and promotion. It is reasonable to say that a medical
technologist who is more competent has a greater opportunity to be promoted to a higher rank/position
than the one who is less competent. Generally, competency can be divided into two categories, namely,
core competency and functional competency. The latter can be further divided into technical and
behavioral competencies.

Core competencies can be viewed as an organization’s basic requirements that a medical
technologist must satisfy. Core competencies are rather general and should represent the minimum
requirement level. There is no standard set of core competencies that are common for all organizations.
For each core competency, the minimum competence level should be set and used as the screening
level. Examples of core competencies are adaptation to technical skills, judgement and analytical
decision making, knowledge base, communication, teaching and training, and supervision and
management, changes, teamwork, problem-solving skill, decision-making skill, leadership, systematic
thinking, and inter-personnel communication skill.

Functional competencies are more specific than core competencies since they can be viewed as
job requirements. Individual jobs are likely to have different sets of functional competencies.
Preferably, any medical technology who will be assigned to a certain job has to possess all functional
competencies that the job requires, with individual competence levels meeting or exceeding the
minimum requirements. Functional competencies can be further divided into technical and behavioral
competencies. It is not unusual for any given job to have specific technical requirements. Such technical
requirements are based on the operation process to accomplish the desired job objective. Examples of
technical competencies include safe work practices, data gathering and specimen procurement or
receipt, Analysis of specimen and validation of results, analytical techniques, interpretation and
reporting of results, and quality management.

Once again, for each technical competency, a minimum level of competence needs to be defined
to assist in the job screening process. Another set of job requirement that any given job normally

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requires could include attitude, human relations, creativity, honesty, self-responsibility, credibility, etc.
These job requirements are largely called behavioral competencies. For example, an accounting job
usually requires a medical technology who is not only technically knowledgeable but also honest and
trustworthy to handle the flow of funds.

Savino et al (2020) referred to the set of competencies and their competence levels that a
medical technology possesses as the “a medical technologist profile,” and those required by a job (job
specifications) as the “job profile”. When any pair of employee-job is being evaluated, it is important
that only the core, technical, and behavioral competencies that are included in both a medical technology
and job profiles are considered. It is not reasonable to consider the competencies (in any category) that
a medical technology has, but that are not required by the job that he/she is being considered for.

The competence level may be assessed using a numerical scale from 1 to 10, where 1 represents
the lowest competence level and 10 represents the highest competence level. The difference in
competence levels of a given competency between a medical technology and job profiles is called the
“competency gap”. Note that the competency gap can be either zero or a positive value.

 If the competence level of a given competency in a medical technology profile is equal
to or higher than the level required (for the same competency) by the job profile, it shows that a medical
technology is well qualified (or overqualified) to handle that job. Thus, the competency gap is zero.

 If the competence level of a given competency in a medical technology profile is lower
than the level required (for the same competency) by the job profile, the competency gap is indicated
by the absolute difference between them.

Within the same competency category (core, technical, or behavioral), it is assumed that all
competencies are equally important. Thus, an “average competency gap” will be determined for each
competency category. Next, an “a medical technologist competency gap” is calculated from the three
average competency gaps. Since it is likely that each hospital may have different viewpoints about how
the three competency categories should be weighed, different importance weights can be assigned and
a medical technology competency gap is basically a weighted average value. Note that a medical
technologist competency gap indicates how fit the employee-job assignment is for a particular
employee-job pair. The smaller the gap, the better the P-J fit is.

When several a medical technologist are to be assigned, their medical technologist competency
gaps are summed together to yield a “total competency gap.” Since the total competency gap tends to
increase with the number of medical technologies, the assignment solution that involves several medical
technologies are likely to yield a larger total competency gap than the solution involving fewer medical
technologist. Therefore, it is necessary to normalize the total competency gap by the number of a
medical technologist who are reassigned. The ratio of the total competency gap to the number of a
medical technology is called “EJA competency gap” since it reflects the overall P-J fit of the EJA
solution (Savino et al., 2020).

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Mathematical Model
Assumptions

1. The number of medical technologists to be assigned is equal to the number of jobs that are
available.

2. All medical technologists can be assigned to any job that is available.
3. Each medical technologist can be assigned to only one job.
4. Each job required only one medical technologist.
Notation
n number of medical technologist or jobs being considered, persons or jobs
ecik competence level of core competency k of medical technologist i
jcjk competence level of core competency k required by job j
etik competence level of technical competency k of medical technologist i
jtjk competence level of technical competency k required by job j
ebik competence level of behavioral competency k of medical technologist i
jbjk competence level of behavioral competency k required by job j
Scj, Stj, Sbj set of cores, technical, and behavioral competencies, respectively, required by job j
Gcijk gap of core competency k between medical technologist i and job j
Gtijk gap of technical competency k between medical technologist i and job j
Gbijk gap of behavioral competency k between medical technologist i and job j
ncj, ntj, nbj number of cores, technical, and behavioral competencies, respectively, required by job j
wc, wf, wt, wb importance weight of core, functional, technical, and behavioral competency

category, respectively
G EJA competency gap
xij binary variable representing employee-job assignment, {0,1}
1 if employee i is assigned to job j; 0 otherwise.
Model
To optimize competency-based P-J fit, the EJA competency gap must be minimized. As seen in
Eq. (1), the EJA competency gap (G) is defined as the average competency gap that is
determined from all assigned medical technologists and is based on all competencies that those jobs
require. Two functional constraints are formulated.
Eq. (2) states that each employee can be assigned to only one job.
Eq. (3) specifies that each job requires only one employee.
Eq. (4) is decision variable constraint.
This section describes the materials and equipment used in the research, explain how the
samples were gathered, any randomization techniques and how the samples were prepared, explain how
the measurements were made and what calculations were performed upon the raw data and describe the
statistical techniques used upon the data.

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     
   G n     xij 
Minimize 1  n wc  Gcijk  wt  Gtijk  Gbijk    (1)
where n     wf    wb    
  i1  kSc j    kSt j  kSb j  
     
j1  nc j nt j nb j


Gcijk  0 if jc jk  ecik
 if jc jk  ecik
 jc jk ecik

Gtijk  0 if jt jk  etik
 if jt jk  etik
 jt jk etik

Gbijk  0 if jbjk  ebik
 if jbjk  ebik
 jbjk  pbik

subject to

n = 1 i = 1, 2, …, n (2)
(3)
 xij = 1 j = 1, 2, …, n (4)
= {0, 1} i = 1, 2, …, n; j = 1, 2, …, n
j 1
n

 xij

i 1

xij

Heuristic-based Multiple-criteria Analysis
A heuristic-based Multiple-criteria Analysis to assign new medical technologist to jobs so as to

minimize the EJA competency gap is proposed. The algorithm consists of two phases. In the first phase,
an initial employee-job assignment solution that minimizes the average core competency gap is
determined. Then, in the second phase, the EJA competency gap is improved (reduced) through an
iterative procedure. The EJA heuristic-based multiple-criteria analysis can be described as follows.
Phase I: Finding an Initial Solution
Step 1: Construct a table consisting of n rows and n columns where row i represents medical

technologist i and column j represents job j.
Step 2: In any cell (i, j) for all i's and j's, enter the average core competency gap determined when

assigning medical technologist i to job j ( Gcij ).
Step 3: For each row i (where i = 1,…, n), arrange Gcij in ascending order.

Step 4: In the first column, find the row that has a smallest Gcij . Then, assign medical technologist i
to job j and exclude job j from further consideration. If there are ties, select any medical
technologist i arbitrarily.

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Step 5: Find the row that has the next smallest Gcij where job j has not been excluded yet. Continue
assigning medical technologists to jobs in this manner until no jobs are available. Then,
proceed to the next column.

Step 6: Repeat Steps 4 and 5 until all medical technologist have been assigned to jobs. Then, stop.
The resulting new employee-job assignment solution is an initial solution.

Step 7: Determine the EJA competency gap of the initial solution G0 using Eq. 1
Phase II: Improving the Initial Solution
Step 1: For each resulting pair of employee-job in the initial solution, determine a weighted average

competency gap (WGij).
Step 2: Find the employee-job pair that has the largest weighted average competency gap.
Step 3: Consider the chosen employee-job pair (in Step 2) and each of the remaining employee-job

pairs at a time. Compute the sum of the two weighted average competency gaps.
Step 4: Exchange the employee's job (in Step 2) and that in the other pair and re-compute the revised

sum of the weighted average competency gaps (after exchanging the jobs).
Step 5: Compute the difference between the sums in Steps 3 and 4.
Step 6: Repeat Steps 3-5 until all possible pairs have been considered.
Step 7: Select the two employee-job pairs with the largest positive difference. If all differences are

negative, proceed to Step 10. Otherwise, exchange the jobs between the two selected pairs
and proceed to Step 8.
Step 8: Re-determine the EJA competency gap of the new employee-job assignment solution using Eq. 1.
Step 9: Repeat Steps 1-8.
Step 10: In case that all differences are negative, the chosen employee-job pair (in Step 2) is non-
exchangeable. Exclude that employee-job pair from further consideration.
Step 11: Re-determine the EJA competency gap of the reduced new employee-job assignment
solution using Eq. 1.
Step 12: Repeat Steps 1-11 until all employee-job pairs have been excluded.
Step 13: The final new employee-job assignment solution is determined from all of those excluded
employee-job pairs.

Numerical Example
Consider a hospital that has seven vacant job positions (J1, J2, …, J7). Based on the company

policy, the Human Resource (HR) Department has defined five core competencies (C1, C2, …, C5),
five technical competencies (T1, T2, …, T5), and five behavioral competencies (B1, B2, …, B5), with
the importance weights of the competency categories being as follows:

 Core competency category – weight = 0.70
 Functional competency category – weight = 0.30

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- Technical competency sub-category – weight = 0.50
- Behavioral competency sub-category – weight = 0.50
Depending on its nature, not every core competency, technical competency, and behavioral
competency is required by each job. Table 1 shows the job profiles of the available seven jobs. The
competency score ranges from 1 to 10, when 10 is the highest.
The HR Department received several application letters for the seven job vacancies. After pre-
screening the applicants, seven potential candidates (E1, E2, …, E7) were invited for a written test and
oral interview. All seven candidates agreed to be considered for other job positions in addition to the
one that each person applied to. The candidates were evaluated according to all core, technical, and
behavioral competencies. Unlike the job profiles, every core competency, technical competency, and
behavioral competency is assessed for individual candidates. Table 2 shows the candidate profiles of
the seven candidates.
Since all seven job positions are considered to be equally important, there is no special
preference as to which job must be filled with the best candidate. As a result, this new employee-job
assignment problem is concerned with the maximum overall productivity. It is common to assume that
if the best person-job fit is achieved, the maximum productivity can be obtained. In other words, the
seven candidates will be assigned to the seven vacant jobs so as to minimize the total weighted average
competency gap.

Table 1 Job profiles (based on the fifteen cores, technical, and behavioral competencies)
Core Competency Technical Competency Behavioral Competency

Job
C1 C2 C3 C4 C5 T1 T2 T3 T4 T5 B1 B2 B3 B4 B5

J1 6 8 - - 10 5 - - 8 7 - 8 9 - 9
J2 - - - 6 7 6 8 5 6 10 9 - - - 10
J3 - 10 5 5 - 10 9 - 7 10 - - - 9 8
J4 5 5 9 9 - 10 9 - 8 9 8 - - 9 10
J5 9 5 - 5 10 5 10 - - - - 10 9 8 -
J6 6 - - 8 - 5 6 8 - 6 - - - - 6
J7 - - 9 9 - 9 7 7 6 - - - - 8 6
Note: “-” means that the competency is not required by the job.

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Table 2 Candidate profiles (based on the fifteen cores, technical, and behavioral competencies)

Candidate Core Competency Technical Competency Behavioral Competency
C1 C2 C3 C4 C5 T1 T2 T3 T4 T5 B1 B2 B3 B4 B5

E1 1 6 1 2 8 2 8 8 2 9 10 5 9 2 1

E2 10 8 5 1 3 6 1 8 10 4 2 8 8 3 2

E3 7 6 5 7 10 8 6 3 2 3 4 10 8 10 10

E4 7 6 8 5 7 2 7 10 7 7 7 4 1 7 10

E5 4 9 3 7 9 1 1 1 1 3 1 6 7 10 4

E6 2 3 2 3 7 2 10 9 4 5 3 1 6 10 4

E7 5 1 7 4 3 8 8 10 1 8 6 1 9 9 4

The above-mentioned new employee-job assignment problem is solved using the optimization

model given in Section 3.3 by a Microsoft Excel Solver program. The optimal solution is obtained as

shown below. (E1 – J5)
Candidate 1 – Job 5 (E2 – J1)
Candidate 2 – Job 1 (E3 – J6)
Candidate 3 – Job 6 (E4 – J4)
Candidate 4 – Job 4 (E5 – J3)
Candidate 5 – Job 3 (E6 – J2)
Candidate 6 – Job 2 (E7 – J7)
Candidate 7 – Job 7

The resulting minimum EJA competency gap is 2.11.

Next, the heuristic-based multiple-criteria analysis is utilized to determine the EJA solution.

Firstly, an initial solution is determined. The computation procedure can be briefly explained as follows.

In Phase I, the average core competency gaps for all possible new employee-job pairs are initially

computed (see Table 3). Next, for each candidate, the average core competency gaps are re-arranged in

ascending order (see Table 4). Then, starting at the first column, find the row (candidate) with a smallest

average core competency gap, and assign the job corresponding to the smallest gap to that candidate.

Steps 4-6 in Phase I are repeatedly performed to assign new employees to jobs.

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Table 3 Average core competency gaps

Candidate Job
J1 J2 J3 J4 J5 J6 J7

E1 2.10 1.40 2.57 3.33 2.28 3.85 5.25

E2 1.63 3.15 1.40 2.10 1.93 2.45 4.20

E3 0.47 0.00 0.93 1.05 0.35 0.35 2.10

E4 1.17 0.35 0.93 0.88 0.88 1.05 1.75

E5 0.70 0.00 0.70 1.58 1.05 1.05 2.80

E6 2.80 1.05 2.80 3.15 2.45 3.15 4.55

E7 3.50 2.10 2.33 1.93 2.80 1.75 2.45

Table 4 Ordered average core competency gaps

Candidate Average Core Competency Gap

E1 1.40 2.10 2.28 2.57 3.33 3.85 5.25

E2 1.40 1.63 1.93 2.10 2.45 3.15 4.20

E3 0.00 0.35 0.35 0.47 0.93 1.05 2.10

E4 0.35 0.88 0.88 0.93 1.05 1.17 1.75

E5 0.00 0.70 0.70 1.05 1.05 1.58 2.80

E6 1.05 2.45 2.80 2.80 3.15 3.15 4.55

E7 1.75 1.93 2.10 2.33 2.45 2.80 3.50

The initial EJA solution (which is based on the average core competency gap) is summarized

as shown below. Additionally, the weighted average competency gaps of the seven employee-job

pairs and the EJA competency gap are computed

Candidate 1 – Job 7 (E1 – J7) WG17 = 6.49

Candidate 2 – Job 3 (E2 – J3) WG23 = 2.98

Candidate 3 – Job 2 (E3 – J2) WG32 = 0.83

Candidate 4 – Job 4 (E4 – J4) WG44 = 1.51

Candidate 5 – Job 1 (E5 – J1) WG51 = 1.90

Candidate 6 – Job 5 (E6 – J5) WG65 = 3.28

Candidate 7 – Job 6 (E7 – J6) WG76 = 2.05

The initial EJA competency gap G0 is 2.72.

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Table 5 shows the weighted competency gaps of all possible combinations of employees and

jobs which will be used in the following iterative procedure.

Table 5 Weighted competency gaps (WGij)

Candidate Job
J1 J2 J3 J4 J5 J6 J7

E1 3.10 2.35 4.18 4.69 3.20 4.71 6.49

E2 2.18 4.67 2.98 3.74 3.00 3.31 5.21

E3 1.02 0.83 1.57 1.89 0.70 0.65 2.48

E4 1.97 0.74 1.57 1.51 2.08 1.16 2.09

E5 1.90 1.89 2.13 3.35 2.33 2.06 3.89

E6 4.00 2.28 3.70 4.30 3.28 3.60 5.04

E7 4.45 2.99 3.05 2.74 3.40 2.05 2.83

In Phase II, an iterative improvement procedure is applied to reduce the EJA competency gap.

In any iteration, the job in the employee-job pair with a largest weighted competency gap is exchanged

with the job in other pairs. The exchange that results in a largest difference in the sum of weighted

competency gaps is chosen and the two jobs are exchanged. Then, the new employee-job pair with the

largest weighted competency gap is selected. The procedure continues until none of the exchanges has

a positive difference. The employee-job pair with the current largest weighted competency gap is thus

non-exchangeable and excluded from further consideration. The above iterative procedure is

summarized below.

Iteration 1:

The selected employee-job pair: E1 – J7

1st exchange: E1 – J7 and E2 – J3  E1 – J3 and E2 – J7

Difference: (6.49 + 2.98) – (4.18 + 5.21) = 0.08

2nd exchange: E1 – J7 and E3 – J2  E1 – J2 and E3 – J7

Difference: (6.49 + 0.83) – (2.35 + 2.48) = 2.49

3rd exchange: E1 – J7 and E4 – J4  E1 – J4 and E4 – J7

Difference: (6.49 + 1.51) – (4.69 + 2.09) = 1.22

4th exchange: E1 – J7 and E5 – J1  E1 – J1 and E5 – J7

Difference: (6.49 + 1.90) – (3.10 + 3.89) = 1.40

5th exchange: E1 – J7 and E6 – J5  E1 – J5 and E6 – J7

Difference: (6.49 + 3.28) – (3.20 + 5.04) = 1.53

6th exchange: E1 – J7 and E7 – J6  E1 – J6 and E7 – J7

Difference: (6.49 + 2.05) – (4.71 + 2.83) = 1.00

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The largest positive difference is 2.49. Thus, the resulting exchange in this iteration is E1 – J2

and E3 – J7. The improved EJA solution is shown below.

Candidate 1 – Job 2 (E1 – J2) WG12 = 2.35

Candidate 2 – Job 3 (E2 – J3) WG23 = 2.98

Candidate 3 – Job 7 (E3 – J7) WG32 = 2.48

Candidate 4 – Job 4 (E4 – J4) WG44 = 1.51

Candidate 5 – Job 1 (E5 – J1) WG51 = 1.90

Candidate 6 – Job 5 (E6 – J5) WG65 = 3.28

Candidate 7 – Job 6 (E7 – J6) WG76 = 2.05

The improved EJA competency gap G1 is 2.36.

Iteration 2:

The selected employee-job pair: E6 – J5

1st exchange: E6 – J5 and E1 – J2  E6 – J2 and E1 – J5

Difference: (3.28 + 2.35) – (2.28 + 3.20) = 0.15

2nd exchange: E6 – J5 and E2 – J3  E6 – J3 and E2 – J5

Difference: (3.28 + 2.98) – (3.70 + 3.00) = -0.44

3rd exchange: E6 – J5 and E3 – J7  E6 – J7 and E3 – J5

Difference: (3.28 + 2.48) – (5.04 + 0.70) = 0.02

4th exchange: E6 – J5 and E4 – J4  E6 – J4 and E4 – J5

Difference: (3.28 + 1.51) – (4.30 + 2.08) = -1.59

5th exchange: E6 – J5 and E5 – J1  E6 – J1 and E5 – J5

Difference: (3.28 + 1.90) – (4.00 + 2.33) = -1.15

6th exchange: E6 – J5 and E7 – J6  E6 – J6 and E7 – J5

Difference: (3.28 + 2.05) – (3.60 + 3.40) = -1.67

The largest positive difference is 0.15. Thus, the resulting exchange in this iteration is E6 – J2

and E1 – J5. The improved EJA solution is shown below.

Candidate 1 – Job 5 (E1 – J5) WG15 = 3.20

Candidate 2 – Job 3 (E2 – J3) WG23 = 2.98

Candidate 3 – Job 7 (E3 – J7) WG32 = 2.48

Candidate 4 – Job 4 (E4 – J4) WG44 = 1.51

Candidate 5 – Job 1 (E5 – J1) WG51 = 1.90

Candidate 6 – Job 2 (E6 – J2) WG62 = 2.28

Candidate 7 – Job 6 (E7 – J6) WG76 = 2.05

The improved EJA competency gap G2 is 2.34.

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Iteration 3:
The selected employee-job pair: E1 – J5

1st exchange: E1 – J5 and E2 – J3  E1 – J3 and E2 – J5

Difference: (3.20 + 2.98) – (4.18 + 3.00) = -1.00

2nd exchange: E1 – J5 and E3 – J7  E1 – J7 and E3 – J5

Difference: (3.20 + 2.48) – (6.49 + 0.70) = -1.51

3rd exchange: E1 – J5 and E4 – J4  E1 – J4 and E4 – J5

Difference: (3.20 + 1.51) – (4.69 + 2.08) = -2.06

4th exchange: E1 – J5 and E5 – J1  E1 – J1 and E5 – J5

Difference: (3.20 + 1.90) – (3.10 + 2.33) = -0.33

5th exchange: E1 – J5 and E6 – J2  E1 – J2 and E6 – J5

Difference: (3.20 + 2.28) – (2.35 + 3.28) = -0.15

6th exchange: E1 – J5 and E7 – J6  E1 – J6 and E7 – J5

Difference: (3.20 + 2.05) – (4.71 + 3.40) = -2.86

Since all differences are negative, the E1 – J5 pair is non-exchangeable and therefore excluded

from further consideration. Thus, the remaining six employee-job pairs are:

Candidate 2 – Job 3 (E2 – J3) WG23 = 2.98
Candidate 3 – Job 7 (E3 – J7) WG32 = 2.48
Candidate 4 – Job 4 (E4 – J4) WG44 = 1.51
Candidate 5 – Job 1 (E5 – J1) WG51 = 1.90
Candidate 6 – Job 2 (E6 – J2) WG62 = 2.28
Candidate 7 – Job 6 (E7 – J6) WG76 = 2.05

The revised EJA competency gap is 1.89.

The iterative procedure is then repeated with only six employee-job pairs to be considered. A

list of employee-job pairs that are non-exchangeable (in the order of exclusion) is as follows:

1st exclusion: E1 – J5

2nd exclusion: E7 – J7

3rd exclusion: E6 – J2

4th exclusion: E2 – J1

5th exclusion: E5 – J3

6th exclusion: E3 – J6

The 6th exclusion then leaves E4 – J4 as the last employee-job pair.

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In summary, the heuristic-based multiple-criteria analysis yields the following new employee-

job assignment solution. (E1 – J5)
Candidate 1 – Job 5 (E2 – J1)
Candidate 2 – Job 1 (E3 – J6)
Candidate 3 – Job 6 (E4 – J4)
Candidate 4 – Job 4 (E5 – J3)
Candidate 5 – Job 3 (E6 – J2)
Candidate 6 – Job 2 (E7 – J7)
Candidate 7 – Job 7

The final EJA competency gap is 2.11.

(Readers should note that the above new employee-job assignment solution is identical to the

optimal solution presented earlier.)

Conclusion
In this paper, a heuristic-based multiple-criteria analysis based on competency-based person-

job fit that measures the level of productivity for the new employee-job assignment problem is
proposed. An EJA competency gap is used as a quantitative index representing competency-based
person-job fit. It is calculated from the weighted average of the gaps (differences) of core, technical,
and behavioral competencies between the person and job profiles. A mathematical programming model
that is developed to find a new employee-job assignment solution that minimizes the EJA competency
gap is also presented. The resulting solution consequently maximizes the total productivity. While the
mathematical model is suitable for solving small new employee-job assignment problems, it is not
practical for large-sized problems.

The heuristic-based multiple-criteria analysis consists of two phases. In the first phase, an initial
new employee-job assignment solution is determined using only the average core competency gap
between the persons and jobs. In the second phase, an iterative procedure is developed to improve the
EJA competency gap by exchanging the jobs between the employee-job pair having a largest weighted
average competency gap and the pair that yields the largest positive difference in the sum of weighted
average competency gaps.

From the illustrative example, the results clearly demonstrate the simplicity and effectiveness
of the proposed heuristic-based multiple-criteria analysis in generating the new employee-job
assignment solution. Readers can see that the computation procedure of the proposed algorithm is
logical and systematic. Both properties help to reduce the computation time and enable the construction
of computer codes to computerize the computation steps. Although the new employee-job assignment
solutions derived from the heuristic-based multiple-criteria analysis and from the mathematical model
are identical. We will not be too optimistic to claim that our algorithm is as effective as the optimization

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approach. However, owing to its logical and systematic nature, we believe that as the size of the problem
increases, our algorithm will be more efficient than the optimization approach.

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