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The Service Industries Journal
ISSN: 0264-2069 (Print) 1743-9507 (Online) Journal homepage: http://www.tandfonline.com/loi/fsij20
An innovative service quality evaluation and
improvement model
Li-Fei Chen, Szu-Chi Chen & Chao-Ton Su
To cite this article: Li-Fei Chen, Szu-Chi Chen & Chao-Ton Su (2017): An innovative
service quality evaluation and improvement model, The Service Industries Journal, DOI:
10.1080/02642069.2017.1389907
To link to this article: http://dx.doi.org/10.1080/02642069.2017.1389907
Published online: 23 Oct 2017.
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Date: 25 October 2017, At: 02:35
THE SERVICE INDUSTRIES JOURNAL, 2017
https://doi.org/10.1080/02642069.2017.1389907
An innovative service quality evaluation and improvement
model
創新的服務品質衡量與改善模型
Li-Fei Chena, Szu-Chi Chenb and Chao-Ton Suc
a
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Department of Business Administration, Fu Jen Catholic University, New Taipei City, Taiwan, Republic of
China; bMBA Program in International Management, Fu Jen Catholic University, New Taipei City, Taiwan,
Republic of China; cDepartment of Industrial Engineering and Engineering Management, National Tsing Hua
University, Hsinchu, Taiwan, Republic of China
ABSTRACT
ARTICLE HISTORY
Importance-performance analysis (IPA) is a popular approach used
by firms to focus resources on crucial attributes, reduce
expenditure on non-critical ones and develop improvement and
innovation strategies accordingly. However, IPA develops quality
improvement plans based on inaccurate assumptions about the
independence between importance and performance and lacks
clear measurement standards, which may lead to inappropriate
recommendations. IPA also does not account for desired versus
adequate service. Therefore, this study proposes an innovative
framework that integrates the advantages of IPA, the zone of
tolerance concept, and Kano’s model. A case study conducted in a
wealth management department in the banking industry
demonstrates the effectiveness of the proposed methodology.
The results indicate that the proposed approach recommends
optimal service strategies to managers and outperforms
traditional IPA.
Received 30 March 2017
Accepted 1 October 2017
KEYWORDS
Importance-performance
analysis (IPA); zone of
tolerance (ZOT); Kano’s
model; service quality
关键词
重要性-績效分析; 容忍區
間; 狩野品質模式; 服務品
質
摘要
重要性-績效分析法 (importance-performance analysis, IPA) 可協助
企業將資源有效集中於顧客在意的關鍵屬性,減少非必要的支
出,並據以發展相關的改善與創新策略。此方法簡單易用,因此
受到業界廣泛的使用。然而,IPA 法的設計假設有部分並不適
當,如:此法假設重要性與績效是彼此獨立無關的,這並不符合
常理;它也缺乏清楚的指標衡量標準,因而可能導致錯誤的決
策。此外,IPA 法也未考慮顧客期待的服務水準與至少應符合的
服務水準。因此,本研究整合 IPA 法、容忍區間法 (zone of
tolerance, ZOT),以及狩野品質模式 (Kano’s model) 的優點,提
出一個創新的服務品質衡量模式,並利用某銀行的財富管理部門
的實際案例,以驗證本研究所提出方法之有效性。研究結果顯示
本方法能較傳統的 IPA 法提供更適當的服務改善方向與策略。
1. Introduction
The importance of service quality has been widely noted in the literature; its strategic
advantages in contributing to market share and returns on investment have been
CONTACT Li-Fei Chen
075033@mail.fju.edu.tw
Department of Business Administration, Fu Jen Catholic University,
No. 510, Zhongzheng Rd., Xinzhung Dist., New Taipei City 24205, Taiwan, Republic of China
© 2017 Informa UK Limited, trading as Taylor & Francis Group
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2
L.-F. CHEN ET AL.
demonstrated in Anderson and Zeithaml (1984), Cui, Lewis, and Park (2003), and Phillips,
Chang, and Buzzell (1983). Because of the rise in consumer awareness in recent years, customer demand has become more varied; today, fulfilling customer demands is a considerable challenge for every organization (Chen, Wen, & Yang, 2014; Gelbrich, Gäthke, &
Grégoire, 2015; Hsiao, Chen, Chang, & Chiu, 2016). Although all companies exert effort
to improve their products or services to increase customer satisfaction, determining
how to allocate limited resources is also essential for achieving optimal levels of customer
satisfaction (Chang, Liang, Chu, & Chou, 2012; Chen, 2012). Furthermore, not all attributes
hold the same weight in satisfying customer needs. Identifying the critical factors that
determine satisfaction is critical to the sustained success of any organization (Chang
et al., 2012; Chen, 2014, 2015).
To help firms provide efficient services to customers with optimally allocated resources,
Martilla and James (1977) propose the importance-performance analysis (IPA), which is
considered an economical, simple, and effective approach for prioritizing items (Arbore
& Busacca, 2011). However, despite its simplicity, IPA has shortcomings such as the
absence of a clear standard for measuring attribute importance and performance, and
inherently inaccurate assumptions about the independence and linearity relationship of
importance and performance. Therefore, companies may adopt inappropriate quality
improvement strategies when prioritizing attributes by using IPA (Azzopardi & Nash,
2013; L. F. Chen, 2014; Garver, 2003; Lai & Hitchcock, 2015; Lo, Wang, Chien, & Hung, 2012).
Service quality can be used to measure the suitability of the match between the service
levels perceived by customers and customer expectations (Grönroos, 1984; Lewis &
Booms, 1983). Parasuraman, Zeithaml, and Berry (1985) identify two levels of customer
expectations: desired service (DS) and adequate service (AS). DS is the ideal service that
a customer would like, and AS is the poorest service that a customer can accept. The
zone of tolerance (ZOT) is the difference between DS and AS (Berry & Parasuraman,
1991; Parasuraman, Zeithaml, & Berry, 1991; Zeithaml, Berry, & Parasuraman, 1993).
According to Parasuraman (2004), if the perceived service level falls within the zone, customers are satisfied; if the perceived service exceeds their DS level, customers are
delighted; and if the service falls below the AS, customers will be dissatisfied. The ZOT
concept provides additional valuable information that enables companies to measure customer feelings toward every service item (Johnston, 1995).
Kano, Seraku, Takahashi, and Tsuji (1984) posit that attribute performance exerts asymmetric effects on satisfaction and dissatisfaction, and propose the two-dimensional quality
model, which assumes that the invisible requirements regarding quality can be identified
(Berger et al., 1993). The model reveals these requirements and classifies the quality attributes into five categories: ‘indifferent,’ ‘attractive,’ ‘one-dimensional,’ ‘must-be,’ and
‘reverse.’ Each category provides a specific strategy for improving a firm’s service quality
based on its characteristics. Researchers have indicated that it is crucial to consider
Kano’s quality categories when using IPA to avoid misinterpretations (Arbore & Busacca,
2011; L. F. Chen, 2014; Tontini & Picolo, 2010).
The aim of this study is to present an innovative model for measuring service quality,
called the Kano-ZIPA model, by integrating the advantages of IPA, the ZOT, and Kano’s
model. The Kano-ZIPA model can enable organizations to identify improvement opportunities, so that specific quality improvement strategies can be planned accordingly. A case
study of a wealth management department in the banking industry is explored to
THE SERVICE INDUSTRIES JOURNAL
3
demonstrate the effectiveness of this proposed model. Moreover, the performance of the
proposed approach is compared with that of traditional IPA.
2. Literature review
IPA was developed by Martilla and James (1977), and is the conventional method for prioritizing improvements to service quality. It involves two dimensions and four quadrants
(Figure 1) that measure the performance and importance of the service attributes. According to their positions on the matrix, the following improvement strategies can be recommended: (a) keep up the good work: attributes in this quadrant matter to customers
and customers are currently satisfied with them; therefore, the performance level
should be maintained; (b) concentrate here: the performance of these attributes does
not reach the level of their value to customers; therefore, immediate improvement is
required; (c) low priority: the attributes in this quadrant are not considered crucial, nor
are they performing well; therefore, these attributes are not prioritized when managers
make improvement plans; and (d) possible overkill: customers do not particularly value
the attributes in this quadrant, but the performance of these attributes is high; therefore,
the company may be allocating too many resources to these attributes.
Using IPA, managers can consider the costs of various improvements and develop an
action plan accordingly (Bacon, 2003). The main strengths of IPA are its low cost, ease
of use, and well-focused strategy suggestions; thus, IPA is considered an effective way
to prioritize items (Sampson & Showalter, 1999). IPA has been applied in numerous industries such as tourism and hospitality (Albayrak, 2015; Chu & Guo, 2015), health care (Cohen,
Coleman, & Kangethe, 2016; Rau et al., 2017), education (O’neill & Palmer, 2004), banking
(Matzler, Sauerwein, & Heischmidt, 2003), and manufacturing (Murali, Pugazhendhi, &
Muralidharan, 2016).
Despite the simplicity of this model, it has the following shortcomings: (a) the discontinuity in the four quadrants means that a slight change in an attribute’s position may
Quadrant II
High
Importance
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2.1 Importance-performance analysis
Low
Quadrant I
Concentrate here
Keep up the good work
Quadrant III
Quadrant IV
Low priority
Possible overkill
Low
High
Performance
Figure 1. Traditional IPA matrix (Martilla & James, 1977).
4
L.-F. CHEN ET AL.
trigger a contradictory strategy because of the changed priority (Bacon, 2003); (b) it
ignores the relationship between a firm’s performance and the expectations of its customers; (c) it only considers a firm’s own performance without comparing it to competitors
(Keyt, Yavas, & Riecken, 1994); (d) no clear standard for the range of the horizontal and
vertical axes, measurement scale, and placement of the crosshairs exists; and (e) several
authors have proposed that performance is related, linearly or nonlinearly, to overall satisfaction with service attributes (Chen, 2014). It is clear that managerial improvement
directions derived from traditional IPA can be potentially misleading.
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2.2 Service quality and ZOT
Service quality refers to the gap between customers’ perceived and expected levels of
service. When the expected level is higher than the perceived level, customers are dissatisfied (Lewis & Mitchell, 1990; Parasuraman et al., 1985). Parasuraman et al. (1985) outline
the five gaps model of service quality. These gaps are: (1) managers’ lack of knowledge
about customer expectations; (2) managers being unable to meet customer expectations
because the expectations are too high or resources are too limited; (3) suppliers being
unable to reach the standards set by managers; (4) firms giving an impression that
creates expectations in customers that they cannot meet; and (5) customers having
service expectations because of the company’s reputation and their own past experience
and personal demands, but finding the perceived service level below their original expectations. Notably, the fifth gap is influenced by the other four gaps. This model indicates
that if companies aim to satisfy customers with their services, they must decrease the
fifth gap.
Parasuraman et al. (1985) also distinguish the fifth gap from the others. Consequently, the ZOT concept (Figure 2) was developed, pointing out that customer satisfaction can be classified under two levels, DS and AS. DS refers to a customer’s
preconceived ideas of excellent service, AS is the minimum level that a customer will
tolerate, and the ZOT is the difference between DS and AS (Berry & Parasuraman,
1991; Parasuraman et al., 1991; Zeithaml et al., 1993). The ZOT concept has received substantial academic attention, with several researchers advocating the ZOT model to
enhance performance-based models (e.g. Nadiri, Kandampully, & Hussain, 2009; Teas
& DeCarlo, 2004; Voss, Parasuraman, & Grewal, 1998; Walker & Baker, 2000). Walker
and Baker (2000) identify the importance of service quality by examining expectation
levels and zone widths, and Teas and DeCarlo (2004) investigate the increased predictive power of a measure considering the ZOT. More recently, Chang et al. (2012)
develop a systematic algorithm to prioritize which service attributes should be
improved, based on a fuzzy ZOT. K.-Y. Chen (2014) proposes the analytical framework
of the competitive ZOT service-quality-based IPA (CZIPA), which evaluates service
quality based on a competitive ZOT; in that study, competitors are benchmarked in
the hot spring hotel industry. The CZIPA eliminates measurement bias and the
problem of crosshair placement, and adds up the standard for the range of the horizontal and vertical axes and measurement scale. Although the concepts adopted into IPA
could improve the issue of measuring performance, they still involve improper assumptions about the independence and linearity relationships of importance and performance, and can result in inappropriate decisions by companies.
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THE SERVICE INDUSTRIES JOURNAL
5
Figure 2. Nature and determinants of customer expectations of service (Zeithaml et al., 1993).
2.3 Kano’s model
Kano et al. (1984) propose the concept of a two-dimensional quality model (Figure 3) by
exploring the nonlinear and asymmetrical effects of attribute performance on customer
satisfaction. They classify quality attributes into the following categories: (a) one-dimensional, (b) must-be, (c) attractive, (d) indifferent, and (e) reverse elements. The concept
is outlined as follows:
(a) One-dimensional quality elements (O): When these elements are sufficient, the customer feels satisfied, and the more sufficient the elements are, the more the customer
enjoys them; however, when they are insufficient, the quality is unacceptable.
(b) Must-be quality elements (M): If these elements are sufficient, the customer believes
things must be this way or the situation would be unacceptable.
6
L.-F. CHEN ET AL.
Satisfied
Attractive quality
One-dimensional quality
Indifferent quality
Not fulfilled
Fulfilled
Reverse quality
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Must-be quality
Dissatisfied
Figure 3. Kano’s two-dimensional quality model (Kano et al., 1984).
(c) Attractive quality elements (A): When these elements are sufficient, the customer is
satisfied, and the more sufficient the elements are, the greater the enjoyment
(which can exceed the excitement for the one-dimensional elements). Notably,
even when they are insufficient, the customer still finds the quality acceptable.
(d) Indifferent quality elements (I): Whether or not these elements are sufficient, customer
satisfaction remains the same.
(e) Reverse quality elements (R): When these elements are sufficient, the customer feels
dissatisfied; when they are insufficient, he/she feels satisfied.
Kano et al. (1984) also designed a functional/dysfunctional questionnaire to classify
these quality elements. Respondents are asked how they would feel if a particular attribute
were present or fulfilled, and they select one of the following answers: (1) satisfied, (2) it
should be that way, (3) I am indifferent, (4) I can live with it, or (5) dissatisfied. Subsequently, they are asked how they would feel if that attribute were absent or unfulfilled,
and select one of the abovementioned responses. By combining the two answers, each
attribute can be classified according to Kano’s evaluation table (Table 1).
3. Methodology
This study proposes a Kano-ZIPA model that combines the advantages of IPA, the ZOT, and
Kano’s model to enable managers to identify a strategic position and develop a service
Table 1. Evaluation table for classifying quality attributes using the Kano questionnaire.
Attribute is not fulfilled
Attribute is fulfilled
Satisfied
It should be that way
I am indifferent
I can live with it
Dissatisfied
Satisfied
It should be that way
I am indifferent
I can live with it
Dissatisfied
R
R
R
R
I
I
I
R
I
I
I
R
I
I
I
R
M
M
M
Q
Notes: M: must-be, O: one-dimensional, A: attractive, I: indifferent, R: reverse, Q: questionable.
THE SERVICE INDUSTRIES JOURNAL
7
improvement plan for each service attribute. The proposed Kano-ZIPA model comprises
the following six stages: (1) defining service attributes and collecting customer data, (2)
identifying Kano’s quality categories for each attribute, (3) evaluating AI and AP based
on the ZOT concept, (4) discriminating between high and low groups for both AI and
AP, (5) establishing the ZIPA matrix, and (6) constructing a Kano-ZIPA portfolio and planning quality improvement strategies for each attribute according to the position on the
Kano-ZIPA matrix. The model concept is shown in Figure 4, and its stages are detailed
as follows:
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3.1. Stage 1: Define service attributes and collect customer data
After domain experts are consulted and the service attributes defined, customer data are
collected using a two-part questionnaire. The first part is Kano’s functional/dysfunctional
questionnaire. The customers describe their feelings concerning whether each attribute is
functional or dysfunctional by selecting from the provided descriptive options: ‘I like it this
way,’ ‘It must be this way,’ ‘I am neutral,’ ‘I can live with it this way,’ or ‘I dislike it this way.’
For the second part, respondents rate their feelings about DS, PS, and AS levels for each
attribute on a Likert scale, with values ranging from 1 (extremely dissatisfied) to 5 (extremely
satisfied).
3.2. Stage 2: Define Kano’s quality categories for each attribute
Using the data collected in the first questionnaire in Stage 1, each service attribute is categorized into one of five elements based on Kano’s evaluation table: (a) one-dimensional
quality elements, (b) must-be quality elements, (c) attractive quality elements, (d) indifferent quality elements, or (e) reverse quality elements. Because the reverse quality element
refers to a high degree of achievement resulting in dissatisfaction, and vice versa, a low
degree of achievement resulting in satisfaction, it does not represent legitimate customer
need in real-world practice (Chen, 2012). Therefore, this study focuses on a discussion of
the first four quality elements: one-dimensional, must-be, attractive, and indifferent
elements.
3.3. Stage 3: Evaluate attribute importance and performance based on the ZOT
concept
Expanding on the ZOT concept as proposed by Parasuraman et al. (1991), Campos and
Nóbrega (2009) analyze the relationship between the importance of attributes and the
ZOT of each. They determine that, when attributes have a higher importance, the customer has a narrower ZOT. Therefore, a measure of importance called ZAI is developed in the
present study by considering the ZOT concept. To measure the ZAI of attributes, the following formula is proposed:
n
n
ZAIj =
DSij /n
(DSij − ZOTij ) /n
i=1
i=1
(1)
n
n
=
DSij /n
ASij /n = DSj × ASj , j = 1, . . . , k,
i=1
i=1
L.-F. CHEN ET AL.
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8
Figure 4. Kano-ZIPA research framework.
where i is the ith customer, n is the total number of customers, j is the jth attribute, k is the
total number of service attributes, ZAIj is the importance level of the jth attribute according
to the ZOT concept, DSij is the DS rated by the ith customer regarding the jth attribute,
ZOTij is the ZOT of the ith customer regarding the jth attribute, ASij is the AS rated by
the ith customer regarding the jth attribute, DSj is the average of all customers’ DS regarding the jth attribute, and ASj is the average of all customers’ AS regarding the jth attribute.
ZAIj is then used to measure importance, and its value ranges between 1 and 5. A greater
value of ZAIj indicates that the attribute has greater importance.
THE SERVICE INDUSTRIES JOURNAL
9
To determine how favorably the company has performed regarding these items,
the ZAP is defined to measure performance according to the ZOT concept as
follows:
ZAPj =
n
n
n
n
PS
/n
/
(DS
−
ZOT
)/n
=
PS
/n
/
AS
/n
ij
ij
ij
ij
ij
i=1
i=1
i=1
i=1
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= PSj /ASj ,
(2)
where ZAPj is the performance level of the jth attribute according to the ZOT
concept, PSij is the PS rated by the ith customer regarding the jth attribute, and
PSj is the average of all customers’ PS regarding the jth attribute. The formula is
used to calculate ZAPj , which indicates how suitable an item is. The range of ZAPj
is usually 0 , ZAPj ≤ 5. Therefore, a value closer to 5 indicates more favorable
performance.
3.4. Stage 4: Discriminate between high and low ZAI and ZAP groups
The average value of all ZAIj , denoted by AVEZAI, is used to classify high and low ZAI
groups as follows:
k
ZAI
/k.
(3)
AVEZAI =
j
j=1
An attribute is considered to have high importance if ZAIj is greater thanAVEZAI; otherwise, it is considered of low importance. Notably, when ZAPj . 1, then PSj . ASj , which
indicates that the attribute is performing at or more favorably than the level that customers can accept. However, when ZAPj , 1, then PSj , ASj , which indicates that the attribute is performing below the acceptable level and the conditions should be improved.
Therefore, 1 is used as a threshold to classify a high or low performance. An attribute
with ZAPj . 1 indicates a tolerable performance and an attribute with ZAPj , 1 indicates
an intolerable performance.
3.5. Stage 5: Establish the ZIPA matrix
Similar to the traditional IPA matrix, the ZIPA matrix comprises two dimensions and four
quadrants based on the measured ZAI and ZAP of items (Figure 5). The ZIPA matrix is completed by mapping attributes into the four quadrants according to the data collected in
Stage 1.
3.6. Stage 6: Construct the Kano-ZIPA matrix and plan quality improvement
strategies
By combining the concepts of ZIPA and Kano’s model, a 4 × 4 Kano-ZIPA matrix can be
constructed (Table 2), and the results obtained in Stages 2 and 5 used to assign each attribute to a space in the grid. According to the locations of the attributes in the Kano-IPA
matrix, fundamental improvement guidelines can be suggested (Table 3). These are
detailed in the following paragraphs.
10
L.-F. CHEN ET AL.
Zone II
Importance (ZAI)
High
Zone I
High ZAI & Low ZAP
High ZAI & High ZAP
AVEZAI
Zone III
Low
Zone IV
Low ZAI & High ZAP
Low ZAI & Low ZAP
Intolerable
1
Tolerable
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Performance (ZAP)
Figure 5. Proposed ZIPA matrix.
Table 2. Kano-ZIPA portfolio matrix.
ZIPA
ZAI
ZAP
High
Kano’s categories
Zone
Must-be factor
One-dimensional factor
Attractive factor
Indifferent factor
Tolerable
(I)
(1) Minor strength
(5) Major strength
(9) Major strength
High
Intolerable
(II)
(2) Major weakness
(6) Major weakness
(10) Potential strength
Low
Low
Intolerable
Tolerable
(III)
(IV)
(3) Minor weakness
(4) Surplus
(7) Minor weakness
(8) Minor strength
(11) Minor weakness
(12) Minor strength
(13) Possible
opportunity
(14) Possible
opportunity
(15) Non-critical
(16) Redundancy
(a) Must-be quality factors
(P1) Minor Strength: A must-be factor with high importance is also expected to be
high in performance. However, the level of fulfillment should not be too high,
because satisfaction cannot be improved with and already better-than-adequate performance. Thus, an attribute assigned to cell P1 is considered a minor strength for a
company. Managers should focus on improving efficiency based on cost control concerns, and develop an appropriate plan (e.g. for simplifying the process of delivering
the service).
(P2) Major Weakness: A high-importance must-be factor indicates something that must
be adequately fulfilled. Intolerably low performance is considered a major weakness
because it can result in unavoidable dissatisfaction. An action plan to fulfill these items
adequately should be implemented as a top priority.
(P3) Minor Weakness: A low-importance must-be factor with intolerably low performance can induce some customer dissatisfaction; thus, it is considered a minor weakness.
A conservative improvement plan can be adopted for efficient fulfillment.
(P4) Surplus: A low-importance must-be factor with a high performance generates a
surplus for firms. The amount invested in such items should be reduced until a satisfactory,
but not excessive, level is reached.
THE SERVICE INDUSTRIES JOURNAL
11
Table 3. Segmented quality improvement plan of the proposed Kano-ZIPA model.
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ZIPA
Kano’s categories
Zone
Must-be factor
One-dimensional
factor
ZAI
ZAP
Attractive factor
Indifferent factor
High
Tolerable
(I)
(P1) Minor Strength
A proper plan is
developed to
improve
efficiency.
(P5) Major Strength
A reasonably
aggressive
strategy is
provided to exploit
customer
satisfaction.
(P9) Major Strength
To distinguish a
company from
competitors, a
leverage strategy
should be planned.
High
Intolerable
(II)
(P6) Major Weakness
To reduce
dissatisfaction, an
aggressive
improvement plan
should be
implemented
immediately.
(P10) Potential
Strength
An active
improvement
strategy should be
adopted when
resources are
available.
Low
Intolerable
(III)
(P2) Major
Weakness
To fulfill
adequately, a
corrective and
preventive action
plan should be
implemented
immediately.
(P3) Minor
Weakness
Budget cuts can
be implemented
here.
(P13) Possible
Opportunity
To attain potential
customers’
satisfaction and
transform the items
into attractive
factors, these
factors can be
investigated.
(P14) Possible
Opportunity
To prevent
dissatisfaction, an
observation plan
can be
implemented.
(P7) Minor Weakness
Budget cuts can be
implemented here.
Low
Tolerable
(IV)
(P4) Surplus
The amount
invested should
be reduced until
it reaches an
adequate level.
(P8) Minor Strength
Item quality to
date should be
ensured, but
attention should
be reduced.
(P11) Minor
Weakness
To attain potential
customers’
satisfaction,
managers should
further investigate
this factor.
(P12) Minor Strength
To distinguish a
company from
competitors,
strategy to
enhance its
importance to
customers can be
implemented.
(P15) Non-critical
Managers should
not focus on this
item.
(P16) Redundancy
The amount
invested on items
should be reduced
to eliminate waste.
(b) One-dimensional quality factors
(P5) Major Strength: A high-importance one-dimensional factor is expected to have
high performance because it can generate high satisfaction. Hence, a high-importance
one-dimensional factor with high performance is considered a major strength. To
enhance customer satisfaction, a reasonably aggressive strategy to continue this performance is recommended.
(P6) Major Weakness: A high-importance one-dimensional factor with intolerably low
performance can lead to serious dissatisfaction. Implementing an improvement plan
should be a top priority, as indicated in P2.
(P7) Minor Weakness: A low-importance one-dimensional factor with intolerable performance is considered a minor weakness because it can result in some dissatisfaction,
although not enough to be a major concern. A conservative improvement plan can be
adopted to increase the level of satisfaction.
12
L.-F. CHEN ET AL.
(P8) Minor Strength: A low-importance one-dimensional factor with high performance
is a minor strength for firms. Managers can pay less attention to these factors, although
they should ensure that they maintain a decent performance level.
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(c) Attractive quality factors
(P9) Major Strength: A high-importance attractive factor with a high performance can
generate more satisfaction than a one-dimensional factor can. Therefore, to distinguish
a company from competitors, a leverage strategy should be planned.
(P10) Potential Strength: A high-importance attractive factor can potentially become a
strength, generating unexpectedly high satisfaction if fulfilled. Therefore, managers should
pay more attention to improving the fulfillment of high-importance attractive factors with
low performance. An active improvement strategy can be adopted when resources are
available.
(P11) Potential Weakness: A low-importance attractive factor with low performance
induces little dissatisfaction; however, if ignored, companies may lose an opportunity to
generate high satisfaction. Therefore, managers should further investigate this factor.
(P12) Minor Strength: A low-importance attractive factor with high performance is a
minor strength because of the low contribution to satisfaction. To distinguish a
company from competitors, however, a strategy to enhance its importance to customers
can be implemented.
(d) Indifferent quality factors
(P13) Possible Opportunity: A high-importance indifferent factor with high performance
can potentially become attractive. Managers should investigate the item and exploit it if it
appears to be transforming into an attractive factor. However, in the absence of signs that
this item could become attractive in the long run, managers should consider reducing
resources spent on it.
(P14) Possible Opportunity: A high-importance indifferent factor can potentially
become attractive in the future. Managers should monitor this item and improve its performance in the presence of signs that it is becoming attractive.
(P15) Noncritical: A low-importance indifferent factor with low performance is noncritical because it can produce neither satisfaction nor dissatisfaction. Managers should not
focus on this item.
(P16) Redundancy: A low-importance indifferent factor with high performance can
produce only negligible satisfaction. Investments in this factor are wasteful and should
be reduced.
4. Case study
4.1. The case
The case study examines a company active in the banking industry, with more than 100
branches in Taiwan as well as several overseas subsidiaries, foreign branches, and a
foreign representative office. According to SINGFIN’s report of ‘wealth management in
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Taiwan’ (SINGFIN, 2017), Taiwan’s wealth management market is one of the most competitive in the world. Taiwan has approximately 130,000 high net worth individuals (those with
assets of at least $1million USD) as of 2016, and the number is expected to increase stably
over the upcoming years. In addition, banks in Taiwan have crowded the market, and
wealth management services are not limited to the financial domain. Therefore, managers
in the case study company should develop service strategies that enhance their competitiveness in the market.
4.1.1. Defining service attributes and collecting customer data
The questionnaire to understand the customers is based on SERVQUAL (a framework
adapted from Parasuraman et al., 1991) and its five dimensions: (a) tangibles, (b) reliability,
(c) responsiveness, (d) assurance, and (e) empathy. To fit the realistic operations of the case
company, a discussion with two managers is also conducted to modify the questions. The
questionnaire consists of two parts. The first of which is used to evaluate each customer’s
DS, AS, and PS level rating according to a Likert scale that ranged from 1 (extremely dissatisfied) to 5 (extremely satisfied). The second part is Kano’s functional/dysfunctional questionnaire. The respondents are asked to choose one of the following answers: (a)
satisfied, (b) it should be that way, (c) I am indifferent, (d) I can live with it, or (e) dissatisfied
under the situations if they feel a particular attribute were fulfilled and if they feel a particular attribute were not fulfilled. A pretest was administered at two branches of the
company in Taipei, and the respondents were 13 sales coordinators who were the first
Table 4. Service attributes.
Items
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
X11
X12
X13
X14
X15
X16
X17
X18
X19
X20
X21
X22
X23
X24
X25
Description
The branches of the bank provide complete and timely financial information (e.g. currency rate and interest rate).
The branches of the bank provide services in a safe and private environment (e.g. an exclusive office).
When services are provided, information is managed promptly and smoothly with equipment.
The appearance of the financial consultants is clean and conveys professionalism.
The bank provides a market research report on areas and countries.
The bank provides a banking application on mobile devices.
The financial consultants can explain the information of services, responsibility, and financial situation.
The financial consultants understand customers’ financial needs.
The bank provides tax and real estate planning services, and professionals are available for consultation with
individual customers.
The bank provides insurance consulting services, including explanations for policy terms, applications for insurance
claims consultations, collection services, progress concerning claims notices, and so on.
The financial consultants are active in providing services and care to customers.
The financial consultants understand customers’ needs and protect their privacy and rights.
The bank provides VIP priority when VIP members are at the service counter.
The bank informs customers of sudden events, new information, and new product information.
The bank provides additional high-level services, such as the reservation of local or overseas hotels and restaurants.
The bank provides pick-up services from international airports several times per year as well as high-speed train
tickets and airport VIP room reservations.
The financial consultants keep their promises.
The brand and reputation of the bank are reliable.
The financial consultants offer recommendations based on individual needs and do not focus on selling goods
because of commissions.
The financial consultants explain the risks of goods in details.
The financial consultants check financial conditions periodically.
The financial consultants provide information on goods as well as investment performance (through visits, phone
calls, and messages).
The financial consultants inform customers of the fee required for every service.
The financial consultants respond to customer complaints or suggestions effectively and in a short period.
The overall service quality which the customers perceive from the bank.
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L.-F. CHEN ET AL.
line to deal with customers to ensure the wording was clear. A total of 24 service attributes
and overall service qualities were investigated in this study. Please see Table 4 for these
attributes.
In February and March 2014, convenience sampling was used to recruit customers in
the two branch banks and that agreed to take part in the research. By checking carefully
with the respondents face-to-face, a total of 243 effected questionnaires were collected.
Cronbach’s α coefficient is .924 for the customer PS level, .972 for the DS level, .956 for
the AS level, and .752 for Kano’s questionnaire. All of these values are above the benchmark value of .70 recommended by Nunnally (1978) and Churchill (1979), confirming
that the survey results show solid internal consistency and reliability.
Table 5 presents a summary of the demographics and consumption patterns of the
respondents. Moreover, it shows that most of the respondents are women (53.5%),
married (80.9%), and have college degrees (53.1%). Nearly half are over 51 years of age
(43.8%). Additionally, 21.7% of the respondents have worked in the service industry,
and 19.5% are retired. Most of the respondents had been using the company’s services
for 2–10 years (67.6%); the majority had also been receiving VIP service for 2–5 years
(54.0%) or 6–10 years (33.6%). The type of VIP status is dependent on the amount respondents have invested in the company. The highest level is VIPC, followed by VIPB, and then
by VIPA; nearly half of the respondents here are VIPB members (48.7%), which reveals that
the largest proportion of customers were provided with mid-level service. New members
of the wealth management service (less than 1 year) account for 10.6% of the respondents.
Furthermore, the primary way that they had learned about this service was through the
bank itself (55.5%). Approximately half of the respondents (47.8%) visit this bank twice
every month.
4.1.2. Analysis of Kano-ZIPA model
After collecting the DS, PS, and AS data, the ZAI and ZAP for each attribute can be derived.
Table 6 shows the statistical results of the ZIPA model. Notably, the average ZAI value, 3.89,
is used to classify the attribute importance into high and low groups, while 1.00 is used to
classify the attribute performance into tolerable and intolerable groups. Each attribute is
then assigned to one of the four zones in the ZIPA matrix (see Figure 6). In total,
58.33%, 8.33%, 12.50%, and 20.83% of the attributes are located in zones I, II, III, and IV,
respectively. First, 14 attributes including X1, X2, X3, X4, X7, X11, X12, X13, X17, X18,
X20, X22, X23, and X24 with the high level of importance and tolerable performance
are located in zone I. The managers should ‘keep up the good work’ on these attributes.
Next, managers should try their best to ‘concentrate’ on attributes X19 and X21 which
located in zone II because these attributes are very important to customers but their
current performance is intolerable. Third, although the performance of attributes X6,
X15, and X16 located in zone III is intolerable, managers can set ‘low priority’ to
improve them due to their low level of importance to customers. Finally, attributes X5,
X8, X9, X10, and X14 located in zone IV are ‘possible overkill.’ Although their performance
is tolerable, allocate resource on these attributes may not bring value to customers due to
their low-importance level.
From the data collected through Kano’s functional/dysfunctional questionnaire, Kano’s
categories are identified for each attribute. Combining these results and the position in the
THE SERVICE INDUSTRIES JOURNAL
15
Table 5. Demographics and consumption pattern of the respondents.
Items
Demographics
1. Gender
2. Marital status
3. Age
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4. Educational status
5. Occupation
Consumption pattern
1. How many years have you been provided service in this
bank?
2. How many years have been provided with the wealth
management service (VIP service) in this bank?
3. Which channels were you informed about the wealth
management service (VIP service) in this bank in the
beginning? (Multiple choices)
4. How often do you come to this bank every month for
the wealth management service (VIP service)?
5. Which type of VIP service do you receipt?
Categories
Male
Female
Married
Single
Below 20 years old
21–30 years old
31–40 years old
41–50 years old
Above 51 years old
Junior high school and below
Senior high school/senior high
vocational school
College
Graduate school and above
Prefer not to answer
Student
Housekeeper
Military officer/ government
official/educational personnel
Financial industry
Manufacturing industry
Freelance
Service industry
Retirement
Others
Less than 1 year
2–5 years
6–10 years
11–15 years
16–20 years
21–25 years
26–30 years
Above 31 years
Less than 1 year
2–5 years
6–10 years
11–15 years
From relatives/ friends
From the company
Official website
TV
Newspaper/ magazine
Others
Less than Once
Twice
3 times
4 times
5 times
VIPA
VIPB
VIPC
Frequency
Percentage
105
121
183
41
1
11
51
64
99
7
38
46.5
53.5
80.9
18.1
0.4
4.9
22.6
28.3
43.8
3.1
16.8
120
31
30
3
33
23
53.1
13.7
13.3
1.3
14.3
10.2
29
34
10
49
44
1
12.8
15.0
4.4
21.7
19.5
0.4
4
76
77
38
23
5
2
1
24
122
76
5
71
146
6
23
17
0
59
108
37
11
11
91
110
25
1.8
33.6
34.1
16.8
10.2
2.2
0.9
0.4
10.6
54.0
33.6
2.2
27.0
55.5
2.3
8.7
6.5
0.0
26.1
47.8
16.4
4.9
4.9
40.3
48.7
11.1
ZIPA matrix, the Kano-ZIPA model is then analyzed, as noted in Tables 7 and 8. Practical
service strategies are recommended as follows:
First, two crucial must-be factors with unacceptable performance (X19 and X21) are
considered to be major weaknesses causing widespread customer dissatisfaction. Managers should consider these attributes top priority and adopt a corrective action plan to
16
L.-F. CHEN ET AL.
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Table 6. Statistical results of the proposed ZIPA model.
No.
DS
PS
AS
ZAI
ZAI level
ZAP
ZAP level
ZIPA zone
Improvement guidelines
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
X11
X12
X13
X14
X15
X16
X17
X18
X19
X20
X21
X22
X23
X24
Ave
4.32
4.43
4.26
4.48
3.78
3.21
4.33
3.63
3.94
4.13
4.64
4.42
4.33
3.99
3.73
3.94
4.64
4.53
4.51
4.39
4.24
4.25
4.35
4.56
4.21
3.96
4.2
3.85
4.33
3.53
2.8
3.82
3.29
3.42
3.61
4.1
3.87
4.13
3.44
3.09
3.22
4.07
4.22
3.72
3.81
3.6
3.69
3.86
3.89
3.73
3.56
3.76
3.68
3.84
3.32
2.95
3.65
3.18
3.39
3.49
3.98
3.73
3.66
3.41
3.2
3.29
3.9
3.98
3.8
3.79
3.62
3.6
3.82
3.85
3.60
3.92
4.08
3.96
4.15
3.54
3.08
3.98
3.40
3.65
3.80
4.30
4.06
3.98
3.69
3.45
3.60
4.25
4.25
4.14
4.08
3.92
3.91
4.08
4.19
3.89
High
High
High
High
Low
Low
High
Low
Low
Low
High
High
High
Low
Low
Low
High
High
High
High
High
High
High
High
1.11
1.12
1.05
1.13
1.06
0.95
1.05
1.03
1.01
1.03
1.03
1.04
1.13
1.01
0.97
0.98
1.04
1.06
0.98
1.01
0.99
1.03
1.01
1.01
1.03
Tolerable
Tolerable
Tolerable
Tolerable
Tolerable
Intolerable
Tolerable
Tolerable
Tolerable
Tolerable
Tolerable
Tolerable
Tolerable
Tolerable
Intolerable
Intolerable
Tolerable
Tolerable
Intolerable
Tolerable
Intolerable
Tolerable
Tolerable
Tolerable
(I)
(I)
(I)
(I)
(IV)
(III)
(I)
(IV)
(IV)
(IV)
(I)
(I)
(I)
(IV)
(III)
(III)
(I)
(I)
(II)
(I)
(II)
(I)
(I)
(I)
Keep up the good work
Keep up the good work
Keep up the good work
Keep up the good work
Possible overkill
Low priority
Keep up the good work
Possible overkill
Possible overkill
Possible overkill
Keep up the good work
Keep up the good work
Keep up the good work
Possible overkill
Low priority
Low priority
Keep up the good work
Keep up the good work
Concentrate here
Keep up the good work
Concentrate here
Keep up the good work
Keep up the good work
Keep up the good work
Figure 6. Analysis of collected data using the ZIPA matrix.
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Table 7. Statistical results of the proposed Kano-ZIPA model.
No.
ZAI level
ZAP level
ZIPA Zone
Kano quality category
Kano-ZIPA position
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
X11
X12
X13
X14
X15
X16
X17
X18
X19
X20
X21
X22
X23
X24
High
High
High
High
Low
Low
High
Low
Low
Low
High
High
High
Low
Low
Low
High
High
High
High
High
High
High
High
High
High
High
High
High
Low
High
High
High
High
High
High
High
High
Low
Low
High
High
Low
High
Low
High
High
High
(I)
(I)
(I)
(I)
(IV)
(III)
(I)
(IV)
(IV)
(IV)
(I)
(I)
(I)
(IV)
(III)
(III)
(I)
(I)
(II)
(I)
(II)
(I)
(I)
(I)
Must-be
One-dimensional
Indifferent
Indifferent
Indifferent
Indifferent
Must-be
Indifferent
Indifferent
Must-be
Must-be
Must-be
Attractive
Indifferent
Attractive
Attractive
Must-be
Must-be
Must-be
Must-be
Must-be
Must-be
Must-be
Must-be
P1
P5
P13
P13
P16
P15
P1
P16
P16
P4
P1
P1
P9
P16
P11
P11
P1
P1
P2
P1
P2
P1
P1
P1
Table 8. Segmented quality improvement plan of Kano-ZIPA.
Kano’s categories
ZIPA
zone
I
II
III
IV
One-dimensional
factor
Attractive factor
(P1) Minor strength
X1, X7, X11, X12, X17, X18, X20, X22,
X23, and X24
(P2) Major weakness
X19 and X21
(P3) Minor weakness
(P5) Major strength
X2
(P9) Major strength
X13
(P6) Major
weakness
(P7) Minor
weakness
(P4) Surplus
X10
(P8) Minor strength
(P10) Potential
strength
(P11) Minor
weakness
X15 and X16
(P12) Minor
strength
Must-be factor
Indifferent factor
(P13) Possible
opportunity
X3 and X4
(P14) Possible
opportunity
(P15) Non-critical
X6
(P16) Redundance
X5, X8, X9, and X14
fulfill them immediately. Second, two minor weaknesses (X15 and X16) are examined.
These two attractive factors might generate satisfaction if addressed adequately;
however, in this case, they are currently ignored. The managers should observe them.
Third, two attributes (X2 and X13) of both high importance and high performance are considered major strengths. X2 is a one-dimensional factor, requiring an aggressive strategy to
generate customer satisfaction; this is contrasted by X13, which has the highest ZAP value
but is an attractive factor. A leveraging strategy exploiting X13 could distinguish the firm
from its competitors. Fourth, 10 highly critical must-be attributes with high performance
(X1, X7, X11, X12, X17, X18, X20, X22, X23, and X24) are considered minor strengths,
where the service level must be maintained to prevent dissatisfaction. However, a highperformance level for these must-be factors does not increase customer satisfaction,
and the managers should develop a plan to improve efficiency. Furthermore, two attributes (X3 and X4) are considered potential opportunities; managers can formulate
18
L.-F. CHEN ET AL.
improvement plans to enhance these attributes, and transform them into attractive
factors. Finally, four indifferent attributes of low importance (X5, X8, X9, and X14) with
high performance are classified as redundant items, and one must-be attribute of low
importance (X10) is classified as a surplus item. Attribute X6, which has the lowest ZAP,
is noncritical because it is an indifferent factor of low importance and the low performance
of this item neither affects customer satisfaction nor dissatisfaction. To optimize resource
use, the firm should consider reducing investments in these attributes. However, X10
should be preserved at an adequate level.
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4.2. Comparison and discussion
To compare the proposed Kano-ZIPA approach with traditional IPA, the importance of
each attribute is derived using standardized regression coefficients, by conducting multivariate linear regressions of the AP ratings on overall customer satisfaction. The derived
importance is adopted for comparison because it is the most commonly used indirect
importance measure in IPA studies. The adjusted R 2 is .567, and the significance value
(P) is .000 for the regression model. Table 9 presents an outline of the results of traditional
IPA and the Kano-ZIPA model.
Traditional IPA and the Kano-ZIPA model offer opposing suggestions for 41.67% (10/24)
of the attributes (X5, X9, X12, X13, X14, X16, X17, X20, X22, and X23). Traditional IPA
suggests that X5, X9, and X14 be addressed using a ‘concentrate here’ strategy,
whereas the Kano-ZIPA model offers recommendations for ‘redundancy.’ Because these
are indifferent factors, they should not receive additional effort and should even be deemphasized. Problematically, the strategies proposed by traditional IPA can result in wasted
resources because of the incompleteness of the analysis. For example, traditional IPA
assigns X12, X13, X17, X20, and X23 to the ‘possible overkill’ group, yet according to the
Kano-ZIPA model, the attributes are a strength. Thus, a position in the ‘possible overkill’
group may result in a loss of strength if these factors are eliminated. Additionally, X16 is
deemed ‘low priority’ according to traditional IPA, but a ‘minor weakness’ requiring
immediate improvement according to the model proposed herein. Traditional IPA also
places X22 in the ‘concentrate here’ quadrant; however, X22 is a must-be factor according
to the Kano-ZIPA model, and thus we recommend that managers pay sufficient attention
to this factor but focus on cost control.
Although similar strategies are recommended to address some attributes, the KanoZIPA model offers more strategy details than does traditional IPA. Traditional IPA recommended addressing X15, X19, and X21 by using a ‘concentrate here’ strategy,
whereas the Kano-ZIPA model defined them as ‘weaknesses.’ Unlike the Kano-ZIPA
model, traditional IPA reminded managers to ‘concentrate here’ without providing a
precise recommendation to direct the improvements. Traditional IPA provides directions
to ‘keep up the good work’ regarding X1, X7, X11, X18, and X24, which is consistent
with the Kano-ZIPA model categorizing these factors as a ‘minor strength.’ This recommendation means that the work should be maintained; however, these factors are also ‘mustbe’ factors, and traditional IPA does not discuss the cost control concern that Kano-ZIPA
raises. Moreover, traditional IPA considers X3 and X4 ‘overkill,’ and hence, unlike the
Kano-ZIPA model, fails to identify potential opportunities.
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Table 9. Comparison of the proposed Kano-ZIPA model and traditional IPA.
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Traditional IPA
Kano-ZIPA
No.
AP
score
Standardized regression
coefficients
AP
level
AI
level
X1
3.96
.076
High
High
X2
4.20
.086
High
High
X3
3.85
.113
High
X4
4.33
.014
X5
X6
X7
3.53
2.80
3.82
X8
X9
X10
X11
Kano’s quality
categories
Zone
Decision
M
(I)
O
(I)
Low
Keep up the good
work
Keep up the good
work
Possible overkill
I
(I)
High
Low
Possible overkill
I
(I)
.048
−.056
.154**
Low
Low
High
High
Low
High
I
I
M
(IV)
(III)
(I)
3.29
3.42
3.61
4.10
−.262***
.294***
−.238***
.088
Low
Low
Low
High
Low
High
Low
High
I
I
M
M
(IV)
(IV)
(IV)
(I)
X12
3.87
−.154**
High
Low
Concentrate here
Low priority
Keep up the good
work
Low priority
Concentrate here
Low priority
Keep up the good
work
Possible overkill
M
(I)
X13
4.13
.018
High
Low
Possible overkill
A
(I)
X14
X15
3.44
3.09
.130*
.076
Low
Low
High
High
Concentrate here
Concentrate here
I
A
(IV)
(III)
X16
3.22
−.084
Low
Low
Low priority
A
(III)
X17
4.07
−.181**
High
Low
Possible overkill
M
(I)
X18
4.22
.265***
High
High
M
(I)
X19
3.72
.096
Low
High
Keep up the good
work
Concentrate here
M
(II)
X20
3.81
−.104
High
Low
Possible overkill
M
(I)
X21
3.60
.101
Low
High
Concentrate here
M
(II)
X22
3.69
.119
Low
High
Concentrate here
M
(I)
X23
3.86
−.012
High
Low
Possible overkill
M
(I)
X24
3.89
High
High
Keep up the good
work
M
(I)
(P1) Minor
strength
(P5) Major
strength
(P13) Possible
opportunity
(P13) Possible
opportunity
(P16) Redundancy
(P15) Non-critical
(P1) Minor
strength
(P16) Redundancy
(P16) Redundancy
(P4) Surplus
(P1) Minor
strength
(P1) Minor
strength
(P9) Major
strength
(P16) Redundancy
(P11) Minor
weakness
(P11) Minor
weakness
(P1) Minor
strength
(P1) Minor
strength
(P2) Major
weakness
(P1) Minor
strength
(P2) Major
weakness
(P1) Minor
strength
(P1) Minor
strength
(P1) Minor
strength
.388***
Decision
Ave 3.73
.041
Notes: 1. *P < .1; **P < .05; ***P < .01. 2. M: must-be, O: one-dimensional, A: attractive, and I: indifferent.
The comparison shows that the proposed Kano-ZIPA outperforms traditional IPA for the
following reasons. First, Kano-ZIPA provides a clear standard for the range of the horizontal
and vertical axes, the measurement scale, and the placement of the crosshairs. Second,
Kano-ZIPA adds additional concepts, such as the gap between the PS and AS, and
solves the problem of misleading strategy suggestions that are triggered by slight
changes in an attribute’s position. Third, Kano-ZIPA overcomes the shortcomings of traditional IPA and enhances its advantages with Kano’s quality categories. Finally, firms
can easily conduct further investigations to improve service quality by interviewing
more respondents or performing statistical analyses.
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L.-F. CHEN ET AL.
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5. Conclusion
To maintain their position in the market and use limited resources efficiently, firms must
understand their customers’ needs. Moreover, they should examine their performance to
identify service attributes and classify them appropriately.
In this study, the advantages of IPA and the ZOT are combined to provide a simple and
efficient tool for firms. In addition, the proposed Kano-ZIPA model, which integrates the
ZIPA matrix with Kano’s categories, enables firms to devise suitable action plans. The
case study of a wealth management department in the banking industry establishes the
effectiveness of the proposed methodology: Based on the results, the department
should conduct more in-depth investigations, such as statistical analysis on different customer segmentation to identify customer needs, and plan substantially stronger strategies
accordingly. Furthermore, the proposed IPA matrix is demonstrably easy to implement
after collecting data from the two-part questionnaire.
This study proposes an effective approach, and implements it with objectivity and accuracy, despite some limitations in personnel, time, and external factors. For example, the
questionnaires were administered in an active company in the banking industry. The
respondents were all VIP customers in the wealth management department, and the services they receive require a certain degree of privacy. Therefore, the data were collected by
several well-trained company staff, which facilitated the protection of the customers’ personal information; however, the company might also have distorted the real situation. We
thus recommend a follow-up survey to be conducted by external staff to reduce this conflict of interest. In addition, the questionnaires were filled out and returned in one session.
Factors such as limited time and participants’ emotions or distractions may have influenced the results. Because the analysis is based on the collected data and suggestions provided accordingly, a future survey with the full cooperation of the respondents is
recommended.
Other suggestions for future study are as follows. First, this study analyzes customer
expectations for each service attribute by combining the strong points of IPA, ZOT, and
Kano’s model; however, the results only reveal customers’ points of view, without considering the resources (money and others) spent on the service attributes, and how these might
be affected through the suggested quality improvement strategies. Given that these strategies may bring about substantial change, future research is recommended to consider
more viewpoints, such as those of human resources and financial departments. Second,
to avoid a tediously long questionnaire that would inconvenience respondents, a consideration of service attributes was omitted in this survey. More service attributes can be examined in the future. Finally, the proposed approach should be tested in additional industries
to confirm its validity and compare the differences that would affect the generalization.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work was partially supported by Grants from Ministry of Science and Technology, Taiwan [MOST
105-2410-H-030 -033 -MY2].
THE SERVICE INDUSTRIES JOURNAL
21
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