What is the impact of user preferences on the design of the hospital online registration system: An integrated approach

An ecient enable and them to go and when their turn This study, based on means-end chain (MEC) theory and the Kano model, aims to: 1) understand user preferences toward using a hospital online registration system by constructing the Kano–MEC hierarchical value map, and 2) deduce and formulate effective system planning and promotion strategies. Methodology/approach Mixed methods research was employed to collect data. A total of 16 hospital registration websites were examined and 34 in-depth interviews were conducted. All the interview transcripts were analyzed, and 16 attribute, 13 consequence, and 4 value variables were obtained for a nal questionnaire design. A total of 376 valid samples were collected from a questionnaire survey to construct a Kano–MEC hierarchical value map.


Means-end Chain (MEC) Theory
Gutman [4] proposed the MEC model to depict the relationship between consumption behavior and personal value. Reynolds and Gutman [8] adopted the laddering technique originally developed by Hinkle [9] to uncover the implicit meanings in each MEC. The basic idea of MEC is that a product's attributes are the means through which consumers obtain consequences/feelings after consuming such attributes to achieve consumers' desired end state of being [10,11,12,13]. Therefore, each MEC contains three major components: attribute (A), consequence (C), and values (V). Each MEC includes three levels of abstractness.
At the lowest level are attributes, which can be abstract, such as atmosphere and style, or concrete such as price and weight. At the next level are functional and psychosocial consequences. At the highest level are values, which could be instrumental or terminal. Aggregating individual MECs from customers enables researchers to form a tree diagram, namely, an HVM, which visualizes customers' innermost thinking toward a particular product or service. Today, MECs have become a representative theory to reveal consumers' innermost cognitive structure of a particular product/service [14]. In practice, MEC theory has been widely used to deal with issues in the retail, communication, tourism, and healthcare industries [13,15,16,17].

Kano Model
Rooted in motivation-hygiene theory [18], the two-dimensional model, which maps customer satisfaction and product development, was proposed by Kano et al. [19]. The Kano model classi es customer preference into ve categories: must-be quality, one-dimensional quality, attractive quality, indifferent quality, and reverse quality. In a quality evaluation, attributes in the must-be category can be viewed as the essential requirements that a product or service must possess to meet customer demands. If such attributes are well done, then customers take this for granted and their satisfaction level will not rise at all. However, if such attributes are missing or not well done, customers would view this product or service as incomplete and will be dissatis ed. In the one-dimensional category, customers will be satis ed if these attributes are ful lled, but they will be dissatis ed if these attributes are not ful lled. Attributes classi ed as indifferent quality will neither result in customer satisfaction or dissatisfaction nor in uence customers' quality evaluation of the product or the service. In the attractive category, attributes are not normally expected by customers. Put another way, these attributes provide satisfaction if they are ful lled, but do not cause dissatisfaction if they are not ful lled. Moreover, a product or service that has particular attributes in the reverse category may lead to customer dissatisfaction. In practice, the Kano model is applied not only in quality control but also in the elds of product development, services, information, and healthcare [20,21,22,23,24,25].

Research Framework and Procedure
This study adopted MEC theory to examine the preferences and cognitive appraisals of users toward the hospital online registration system and then utilized the Kano model to classify the attributes or features of the online registration system into Kano's ve categories (i.e., one-dimensional, must-be, indifferent, attractive, and reverse quality). Through the use of the HVM derived from MEC theory and Kano's quality appraisal, the ndings of this study can provide hospital managers with insightful information to formulate effective strategies with regard to system planning, webpage copywriting and design, and function design. Figure 1 illustrates the research framework of this study.

Samples, Variables, Questionnaire Design, and Data Collection
This study adopted one-on-one in-depth interviews to collect data for an MEC analysis. Thirty-four participants with experience using the hospital online registration system were recruited. Male and female participants were evenly split. Most of the participants were aged between 25 and 34 years old and are heavy Internet users in Taiwan [26]; this is also the main group that is familiar with the hospital online registration system. Each interview took roughly 45 minutes. The following are the main questions asked in each interview: 1. Please recall the hospital online registration system that you have used before. What are the names of the hospitals? Please provide detailed information for the one that impressed you the most and why.
2. Which attributes/features of the online registration system do you prefer the most? Why are they important to you? Please provide more information.
3. What consequences or feelings do you have when the online registration system offers such attributes?
What would you feel if such attributes are not provided and why?
4. Which values can you achieve after using this system?
All interviews were audio recorded, transcribed, and conducted with permission from the participants. To ensure accuracy, the interview transcripts were content analyzed by using the terms identi ed in Table 1 and con rmed by each respondent. The extracted phrases from the transcripts were then coded into the appropriate categories of MEC as A, C, and V variables, as shown in Table 2. Thirty-three variables were gathered, including 16 attribute, 13 consequence, and 4 value variables. The percentage agreement and the reliability coe cient agreement among the three coders are 94.7% and 98.2%, respectively, thereby indicating that the content analysis results are reliable [27].  With the use of the 33 variables from the 34 in-depth interviews, an MEC dot connection questionnaire was designed by arranging all the attribute, consequence, and value variables into three columns from the left to the right. All respondents were asked to choose which attributes in the rst column were important to them and then draw a line to connect the dots from the attributes to the dots in the consequence and value columns to form their A-C-V chains for HVM construction. For Kano analysis, the functional/dysfunctional questions were designed by asking "How do you feel if this attribute (i.e., functional menu layout [A1], Q&A [A2], …, and App [A16]) is provided/not provided by the hospital online registration system?" All respondents were required to choose one of the following ve levels: delighted, must-be, neutral, live with, and dislike.
Therefore, the nal questionnaire was designed to include one conditional question and four parts. The conditional question was used to validate that the respondent had used the online registration system before. The rst part of the designed dot connection questionnaire was for the MEC analysis, and the second and third parts were the ve-level Kano questionnaire, including functional and dysfunctional questions. The last part was designed to collect the respondents' demographic information, such as gender, age, and monthly income.
In this study, data were gathered via a paper-based questionnaire survey over three months in the summer of 2018. With ineffective or missing data eliminated from 500 collected questionnaires, a total of 376 valid samples with an effective recovery rate of 75.2% were used for further analysis.

MEC and Kano Analyses
For MEC analysis, data collected from the dot connection-type questions that represent the A-C and C-V linkages and frequencies from 376 valid samples were tabulated into the summary implication matrix. In this work, 16 attribute, 13 consequence, and 4 value variables formed 260 (16 × 13 + 13 × 4) active cells in the summary implication matrix, and the total number of linkages was 4,092. Displaying 4,092 A-C and C-V linkages in a single HVM is impossible because doing so would make the HVM too complex to read.
Consequently, setting a cut-off value is essential before constructing the HVM. The basic idea for the cut-off value determination is the use of a relatively small number of cells in the summary implication matrix to represent a large portion of the total number of linkages [5,11,14,28,29]. A detailed discussion of cut-off point determination and related criteria was provided in Pieters et al. [28]. High linkage frequencies correspond to high importance of these linkages [14]. Therefore, for HVM construction, this study set the cutoff values at 22, 50, and 71 to represent weak, middle, and strong linkages, respectively. As shown in Table 3,  For the Kano analysis, this study adopted the ve-level Kano questionnaire (i.e., delighted, must-be, neutral, live-with, and dislike) and used the Kano evaluation table (Table 4) proposed by Matzler and Hinterhuber [30] to classify 16 attributes of the online registration system into one-dimensional, must-be, attractive, indifferent, and reverse quality. Furthermore, this study used customer satisfaction coe cient (see formulas 1 and 2) to evaluate which attributes can in uence the satisfaction of online registration system users.

Sample Description
Among 376 valid samples (see Table 5

HVM of the Hospital Online Registration System
In Fig. 2, the dotted line (weak linkage) indicates that a cut-off value of 22 was set for an HVM construction by using A-C and C-V linkage frequencies of 22 or higher in the summary implication matrix. For example, "app (A16)" provides users with "useful (C12)" feelings after using the online registration system, yielding "a sense of satisfaction (V3)," that is, hospital online registration system managers should promote that their app is useful and meets the satisfaction of users. Given that a high linkage frequency represents the high importance of the linkage, this study mainly focused on the discussion of those important (strong) linkages.
The bold lines (see Fig. 2) with a cut-off value of 71 represent that these A-C-V linkages are perceived as important by 376 respondents. "Functional menu layout (A1)," for instance, causes users to perceive that the system is "e cient (C1)" and leads to their "sense of security (V1)." In addition, users prefer "right-clicking the registration by department tab (A5)" and "modifying or canceling one's appointment (A6)" provided by the hospital's online system, because these attributes can produce a "convenience (C3)" bene t, achieving their psychological state of "security (V1)," "enjoyment (V2)," and "satisfaction (V3)." If a hospital's registration system has the "downloading doctor's schedule (A7)" attribute, then this attribute can make users perceive the "convenience (C3)" and "availability (C7)" of the system and thereby achieve "security (V1)," "enjoyment (V2)," and "satisfaction (V3)." Moreover, "doctor's introduction (A8)" causes users to perceive that the system is "informative (C10)" and further leads to their "sense of satisfaction (V3)." "Rightclicking the registration by symptom of a disease (A13)" makes patients feel "not embarrassed (C8)" to register online and thus arouses the users' "sense of satisfaction (V3)." Furthermore, the "instant messaging (A15)" attribute provided by the hospital online registration system not only provides users with "time-saving (C2)" and "easy-to-use (C13)" bene ts but also gives users "a sense of security (V1)" and "a sense of enjoyment (V4)." Hospital managers should focus on "functional menu layout (A1)," "right-clicking the registration by department tab (A5)," "modifying or canceling one's appointment (A6)," "downloading doctor's schedule (A7)," "doctor's introduction (A8)," "right-clicking the registration by symptom of a disease (A13)," and "instant messaging (A15)" in creating an online registration system, because these attributes are the most important features that encourage patients to make an appointment with doctors online.

Kano Classi cation of User's Perceptions toward Hospital Online Registration System
Kano analysis Witell and Löfgren [31] empirically con rmed that the ve-level Kano questionnaire is the most effective measurement for the classi cation of quality attributes. In this study, attribute data gathered from ve-level Kano questionnaire were statistically analyzed and summarized in Table 6. The percentages of each row represent the results of the quality appraisals from 376 respondents. The highest percentage indicates the particular attribute belonging to that particular Kano classi cation, termed the rst-priority attributes of Kano's quality classi cation. The second highest percentage attribute is named the second-priority attributes of Kano's quality classi cation. First-priority attributes of Kano's quality classi cation 1. One-dimensional quality (OQ) For users, the attributes of an online registration system are classi ed as one-dimensional quality, which represents that user satisfaction will increase if the quality performance is good. By contrast, bad performance decreases satisfaction. As shown in the rst-priority column with the symbol OQ, "right-clicking the registration by department tab (A5) (51.2%)," "modifying or canceling one's appointment (A6) (45.6%)," "downloading doctor's schedule (A7) (48.5%)," "doctor introduction (A8) (33.6%)," "right-clicking the registration by doctor's name (A13) (46.0%)," and "instant messaging (A15) (54.1%)" are classi ed as onedimensional quality. Thus, the managers of hospital registration systems should pay more attention to the improvement of these attributes.

Must-be quality (MQ)
None of the 16 attributes was classi ed as must-be quality in the rst-priority Kano classi cation, which indicates that users believe the hospital online registration system must have these attributes. User satisfaction will not increase because the system provides these must-be attributes. However, user satisfaction will decrease dramatically if these attributes are not provided.

Attractive quality (AQ)
None of the 16 attributes fell under attractive quality. If the system does not have such attributes, users will not feel dissatis ed or disappointed [32].

Reverse quality (RQ)
Attributes in the reverse category may lead to user dissatisfaction if the system provides such attributes. In this study, none of the 16 attributes was classi ed under reverse quality.

Second-priority attributes of Kano's quality classi cation
In the rst-priority Kano's quality classi cation, 10 out of 16 attributes were in the indifferent category, showing that user satisfaction would not be in uenced by these 10 attributes. Therefore, this study further examined the second highest percentage in each row to nd the second-priority attribute quality classi cation of each attribute. As shown in the last column (second-priority quality classi cation) of Table   6, a total of 9, 2, and 5 items of attributes were grouped in the must-be, attractive, and one-dimensional categories, respectively.

Kano's Customer Satisfaction Coe cient
To understand the relation between online registration system users' satisfaction/dissatisfaction if their requirements are met/unmet and the priority of these requirements in the Kano model, this study adopted Kano's customer satisfaction coe cient to reveal the most important quality element for increasing satisfaction. As shown in Table 7, "instant messaging (A15) (0.678)," "right-clicking the registration by department tab (A5) (0.590)," and "right-clicking the registration by symptom of a disease (A3) (0.588)" are the top three most important quality attributes for increasing satisfaction. Notably, A15, A5, and A3 are classi ed as one-dimensional quality, thereby indicating that a high satisfaction index (SI) corresponds to the high in uence of the satisfaction level. With regard to the extent of dissatisfaction indices (DSIs), the negative sign represents a negative impact on user satisfaction if these attributes are unmet. Table 7 shows that "downloading doctor's schedule (A7) (-0.844)," "right-clicking the registration by department tab (A5) (-0.827)," and "modifying or canceling one's appointment (A6) (-0.776)" are the top three quality attributes for decreasing the dissatisfaction level. Similarly, A7, A5, and A6 are also grouped under one-dimensional quality, thereby indicating that a high absolute value of the DSI corresponds to high dissatisfaction if the attribute does not meet the requirement of users. Interestingly, "right-clicking the registration by department tab (A5)" has high SI and DSI, thereby indicating that this attribute should be viewed as the core component that can effectively satisfy system users if its performance is met.  Figure 3 illustrates the impact on overall satisfaction with quality de ned by the SI value on the x-axis and the absolute DSI value on the y-axis. Referring to Yao et al. [20], when the attribute quality is far from the origin point (0, 0), such an attribute has a greater in uence on satisfaction. As shown in Part I of Fig. 3 (both SI and absolute DSI values greater than 0.5), "right-clicking the registration by department tab (A5)," "modifying or canceling one's appointment (A6)," "downloading doctor's schedule (A7)," "right-clicking the registration by doctor's name (A13)," and "instant messaging (A15)" are classi ed as one-dimensional attributes that can improve users' satisfaction and reduce their dissatisfaction by increasing quality ful llment. In Part II of Fig. 3 (SI value greater than 0.5 but absolute DSI value less than 0.5), "app (A16)" is the only attribute located in this section. If the quality of "app (A16)" is met, then it would have a greater in uence on user satisfaction improvement but less in uence on dissatisfaction decrease. By contrast, "functional menu layout (A1)," "doctor introduction (A8)," "hospital oor layout (A11)," and "right-clicking the registration by doctor's name (A14)" are attributes in Part III of Fig. 3 (absolute DSI value greater than 0.5 but SI value less than 0.5) that would have greater impact on reducing user dissatisfaction but less impact on increasing user satisfaction if quality ful llment increases. The rest of the attributes (A2, A3, A4, A9, A10, and A12) in Part IV of Fig. 3 (SI and absolute DSI values less than 0.5) have little impact on user satisfaction and dissatisfaction. Thus, improving the quality of these attributes might not be necessary.

Discussion
This study integrated the MEC and Kano models to reveal users' preferences and perceptions toward the online registration system of hospitals. Through the integration of these two models, researchers can not only understand the implications of each A-C-V linkage of MEC but also further gain insight into the Kano's quality classi cation of each attribute to provide hospital managers with insightful information for formulating effective system design and promotion strategies.
User preferences for online registration system design  Figure 4 (i.e., A5, A6, A7, A8, A13, and A15) should evidently be the focus of online registration system design. The use of attributes can yield "time-saving (C2)," "convenience (C3)," "availability (C7)," "not embarrassed (C8)," "informative (C10)," and "easy to use (C13)" feelings and lead to the achievement of "a sense of security (V1), "a sense of enjoyment (V4)," and "a sense of satisfaction (V3)." Attribute quality classi cation and user cognitive structure On the left-hand side of Figure 4, each attribute is classi ed as indifferent, attractive, one-dimensional, or must-be quality by the respondents' rst or second priority order. First and second priorities represent that at least 33% and 12% of respondents have the same point of view and classi ed the attribute into its related Kano's quality classi cation, respectively. In Figure 4, six attributes (A1, A2, A3, A10, A11, and A16) are listed as rst priority and classi ed as indifferent quality, but four of them (A1, A3, A10 and A16) listed as second priority were classi ed as one-dimensional quality, that is, system designers still need to pay attention to "functional menu layout (A1)," site map (A3)," "department and clinic code (A10)," and "app (A16)" attributes, given that the performance of these attributes is highly related to customer satisfaction. Notably, "Q&A (A2)" in the second priority was grouped under attractive quality, representing that this attribute may produce additional satisfaction to users. "Hospital oor layout (A11)" in the second priority was classi ed as must-be quality, showing that at least 12% of respondents recognize this attribute as an essential feature of a registration system; without this attribute, they will feel the system is incomplete.

Conclusion
System planning This study found that "right-clicking the registration by department tab (A5)," "modifying or canceling one's appointment (A6)," "downloading doctor's schedule (A7)," "doctor introduction (A8)," "right-clicking the registration by doctor's name (A13)," and "instant messaging (A15)" are classi ed as one-dimensional quality in the rst priority and as must-be quality in the second priority, which means that they are important for registration system design. Given that at least 33% of respondents viewed these attributes as onedimensional quality, the high performance of these attributes corresponds to increased user satisfaction, and vice versa. These attributes were also classi ed under must-be quality, which means that if such attributes are missing, then users will be dissatis ed. Evidently, managers should focus on these attributes (A5, A6, A7, A8, A13, and A15) to formulate their system planning for enhancing the functions of their online registration system and increasing user satisfaction.

Promotion strategy
On the basis of the Kano-MEC hierarchical map (Figure 4), "e cient (C1)," "time-saving (C2)," "convenience (C3)," "availability (C7)," "not embarrassed (C8)," "informative (C10)," and "easy to use (C13)" are important consequences/bene ts that users perceived upon utilizing the attributes of the registration system. Such consequences or bene ts strongly link to "a sense of security (V1)," "a sense of enjoyment (V4)," and "a sense of satisfaction (V3)," showing that users' values can be achieved via the consequences/bene ts of using the attributes. As a result, hospitals can promote these bene ts of using an online registration system to reduce the personal costs of hospital registration. Authors' contributions (YC examined and interpreted the data that were collected and analyzed by LS. CF summarized the results and constructed the gures. CS wrote the manuscript. All authors have read and approved the nal manuscript.)   Satisfaction impact