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The digital divide usually refers to access or usage, but some studies have identified two other divides: awareness and demand (want). Given that the hierarchical stages of the innovation adoption process of a customer are interrelated, it is necessary and meaningful to analyze the digital divide in eHealth services through three main stages, namely, awareness, want, and adoption.
By following the three main integrated stages of the innovation diffusion theory, from the customer segment viewpoint, this study aimed to propose a new matrix analysis of the digital divide using the awareness, want, and adoption gap ratio (AWAG). I compared the digital divide among different groups. Furthermore, I conducted an empirical study on eHealth services to present the practicability of the proposed methodology.
Through a review and discussion of the literature, I proposed hypotheses and a new matrix analysis. To test the proposed method, 3074 Taiwanese respondents, aged 15 years and older, were surveyed by telephone. I used the stratified simple random sampling method, with sample size allocation proportioned by the population distribution of 23 cities and counties (strata).
This study proposed the AWAG segment matrix to analyze the digital divide in eHealth services. First, awareness and want rates were divided into two levels at the middle point of 50%, and then the 2-dimensional cross of the awareness and want segment matrix was divided into four categories: opened group, desire-deficiency group, perception-deficiency group, and closed group. Second, according to the degrees of awareness and want, each category was further divided into four subcategories. I also defined four possible strategies, namely, hold, improve, evaluate, and leave, for different regions in the proposed matrix. An empirical test on two recently promoted eHealth services, the digital medical service (DMS) and the digital home care service (DHCS), was conducted. Results showed that for both eHealth services, the digital divides of awareness, want, and adoption existed across demographic variables, as well as between computer owners and nonowners, and between Internet users and nonusers. With respect to the analysis of the AWAG segment matrix for DMS, most of the segments, except for people with marriage status of Other or without computers, were positioned in the opened group. With respect to DHCS, segments were separately positioned in the opened, perception-deficiency, and closed groups.
Adoption does not closely follow people’s awareness or want, and a huge digital divide in adoption exists in DHS and DHCS. Thus, a strategy to promote adoption should be used for most demographic segments.
Health care organizations are beginning to use the Internet in reaching a large part of the population in a cost-effective manner [
eHealth services have improved access to health care in rural [
In the last 10 years, researchers have begun discussing customer acceptance of eHealth services using the technology acceptance model [
The digital divide relates not only to Internet access but also to the existence of a gap between people who can effectively use new information and communication tools, such as the Internet, and those who cannot [
More differentiated use of the Internet across varying segments of a given population may result in the digital divide [
The availability of a home computer is another factor used to predict an individual’s ability to access the Internet [
Previous studies have shown that certain demographic variables and computer and Internet access are factors causing the digital divide, and that such a divide usually entails access or usage. Some studies have also identified two other divides: awareness [
H1: There exists an awareness divide in eHealth services across certain demographic variables, computer ownership, and Internet access.
H2: There exists a want divide in eHealth services across certain demographic variables, computer ownership, and Internet access.
H3: There exists an adoption divide in eHealth services across certain demographic variables, computer ownership, and Internet access.
The earliest and most well-known consumer purchasing decision process is attention–interest–desire–action, first proposed in the late 1800s and early 1900s [
Some studies have mentioned that probabilities can be associated with the stages of the hierarchical models to show the ultimate behavioral impact of promotion [
H4: The adoption rate of a given eHealth service is bound to consumers’ corresponding awareness rate.
H5: The adoption rate of a given eHealth service is bound to consumers’ corresponding want rate.
From the end user’s viewpoint, Dixon [
In a pull health care system, the patient requests the product and pulls it through the delivery channel [
H6: The want rate for a given eHealth service is not necessarily bound to consumers’ corresponding awareness rate.
H6-1: The want rate for a given eHealth service is bound to consumers’ corresponding awareness rate.
H6-2: The want rate for new and innovative e-services may be greater than consumers’ corresponding awareness rate.
Generally speaking, there is no adoption if there is no awareness. Higher awareness may bring higher want rates, but the intention of using some eHealth services will be low if there is a shortage of want. However, people having the potential need for an eHealth service will easily pay attention to the promotion and receive the information and, as such, may have a higher awareness rate than those who are not in need of the service. Thus, the following three hypotheses were proposed:
H7: Want rate, given awareness for each consumer segment, is higher than want rate with unawareness.
H8: Adoption rate, given want for each consumer segment, is higher than adoption rate without want.
H9: Awareness rate, given want for each consumer segment, is higher than awareness rate without want.
According to H4 to H9, awareness and want have interactive influences on adoption rate. Therefore, when evaluating the digital divide in some e-services, the corresponding awareness and want rates should be considered separately. Based on the technology adoption lifecycle (bell curve), with a combination of innovators and early majority stages, the four types of adopters are segmented by three slightly adjusting adoption life cycle cumulative rates of 15%, 50%, and 85% [
First, awareness and want rates were divided into two levels at the middle point of 50%, and then the 2-dimensional cross of the AWAG segment matrix was divided into four categories: opened group, desire-deficiency group, perception-deficiency group, and closed group. Second, using the cumulative rate of 15% or 85%, each category was further divided into four subcategories. In the awareness–want segment matrix (
People categorized under the opened group are open to innovation. They are keen on seeking new information and are always on the lookout for something new and innovative. On the other hand, those who are categorized under the closed group are closed minded when it comes to innovation, and they lag behind in receiving new information. They are not interested in innovation and, as such, they usually resist trying something new. People categorized under the desire-deficiency group lack desire for innovation. Although they receive new information early, they are usually not interested in innovation and may resist trying something new. Meanwhile, those under the perception-deficiency group lack perception for innovation. Although they lag behind in receiving new information, they are still interested in innovation and always intend to try something new and innovative.
Each of the above four groups was further divided into four subgroups, according to the degrees of awareness and want, and based on a cumulative rate of 15% or 85%. For the opened group and closed group, the subgroups were strong, awareness-bias, want-bias, and generic. For the desire-deficiency group and perception-deficiency group, the subgroups were strong, generic, and want-bias or awareness-bias. The strong subgroup is the most open, closed, perception-deficient, or desire-deficient group. The generic subgroup is the least open, closed, perception-deficient, or desire-deficient group. There is some room to raise awareness for the awareness-bias subgroup and some room to raise want for the want-bias subgroup.
In the AWAG segment matrix, awareness and want are on the same level for four groups: strong opened group, generic opened group, generic closed group, and strong closed group. In these four groups, the awareness rate corresponds to the want rate. However, the opened degree for innovation decreases from left-up to right-down. For example, people under the strong opened group are innovators with the most open minds. Most of them already know about some innovations or new services, and they are full of want. On the opposite side, people under the strong closed group are laggards with the most closed minds. Most of them do not know or care about innovation or new services, and they are lacking in want.
Groups located on the left-down side of the downward-sloping 45° line have awareness rates greater than want rates. The groups located on the opposite side have inversed characteristics. The larger the distance beyond the 45° line, the greater the bias between awareness and want. For example, the group in the farthest left-down area is the strong desire-deficiency group. People belonging to the strong desire-deficiency group may not be the target of innovation. Although they have high awareness, they are short of want. Thus, any innovation promotion will not drive them to do something, and any promotion budget allocated to this group may be wasted. People belonging to the strong perception-deficiency group located at the farthest right-up, although high in want of innovation, are seriously ignored or may not have the capability to get information. Thus, they do not receive enough information on innovation. This group should be prioritized first, and more promotion efforts should be exerted on them.
The present study defined four possible strategies: hold, improve, evaluate, and leave [
Prescriptions of the awareness, want, and adoption gap ratio (AWAG) segment matrix
Category | Subcategory | Strategy | Action | Current target |
Opened group | Strong | Hold | Keep up the good work. | Primary |
Awareness-bias | Hold and improve (raise) | Keep up the good work and keep raising the awareness. | Secondary | |
Want-bias | Hold and improve (raise) | Keep up the good work and keep raising the want. | Tertiary | |
Generic | Hold and improve (raise) | Keep up the good work and keep raising the awareness and want. | Tertiary | |
Closed group | Strong | Evaluate then leave or evaluate then improve (spread and create) | Evaluate the potential of the segment then choose an action between “maintain status quo” and “keep spreading the awareness or creating the want.” | Nontarget |
Awareness-bias | Evaluate then leave or evaluate then improve (spread) | Evaluate the potential of the segment then choose an action between “maintain status quo” and “keep spreading the awareness.” | Nontarget | |
Want-bias | Evaluate then leave or evaluate then improve (create) | Evaluate the potential of the segment then choose an action between “maintain status quo” and “keep creating the want.” | Nontarget | |
Generic | Evaluate then leave or evaluate then improve (raise) | Evaluate the potential of the segment then choose an action between “maintain status quo” and “keep raising the awareness or want.” | Nontarget | |
Desire-deficient group | Strong | Evaluate then leave or evaluate then improve (create) | Evaluate the potential of the segment then choose an action between “maintain status quo” and “keep creating the want.” | Nontarget |
Want-bias | Evaluate then leave or evaluate then improve (create) | Evaluate the potential of the segment then choose an action between “maintain status quo” and “keep creating the want.” | Nontarget | |
Generic | Improve (create) | Keep creating the want. | Nontarget | |
Perception-deficient group | Strong | Improve (spread) | Keep spreading the awareness. | Potential target |
Awareness-bias | Improve (spread) | Keep spreading the awareness. | Potential target | |
Generic | Improve (spread) | Keep spreading the awareness. | Potential target |
In using the AWAG segment matrix, managers should first re-evaluate the awareness and then the wants of some segments. If a segment is found to have low awareness, some promotion activities should be carried out, and follow-up should be conducted to raise the want. The e-services at the bottom right area should be pulled to the top left area, step by step, if possible or necessary. The suggested improvement direction for each group is shown in
Awareness, want, and adoption gap ratio (AWAG) segment matrix.
Improving directions for each region in the awareness, want, and adoption gap ratio (AWAG) segment matrix. Ab = awareness-bias; G = generic; S = strong; Wb = want-bias.
Based on H4, H5, and H6, the adoption rate of a product or service is highly related to the corresponding awareness and want rates of consumers. However, even if consumers are aware of a new service or product, it does not follow that they will choose or use it. Therefore, the adoption rate is bound to the awareness and want rates. Under this situation, it is not proper to compare the adoption rates of products or services directly because they are under different levels of awareness and want (ie, the room for adoption promotion should be limited under current awareness and want). Therefore, Liang [
The adoption gap ratio is the proportion of the adoption rate for a product or service thatcan be promoted under the current awareness or want rates. The range of the adoption gap ratio is from 0% to 100%. Among those who are already aware of or in want of an eHealth service, the adoption gate rate represents the percentage of people who have never used the service. The gate rate is 0% when the adoption rate is equal to the minimum value of the awareness and want rates. The gate rate is close to 100% when almost no one currently uses the product or service. Using the proposed adoption gap ratio, we can thus evaluate the effectiveness of adoption promotion more accurately. Several studies have found that perceived ease of use, perceived usefulness, and self-efficacy have direct effects on user attitude [
Equation for calculating the adoption gap ratio for service x.
In 2002, 62.6% of hospitals in Taiwan had developed their own websites. Most of these hospitals agreed that applying Internet technology could improve service quality and work efficiency and that the Internet would have a huge influence on the delivery of medical websites [
According to statistics compiled by the Ministry of the Interior in Taiwan, there were 1,490,801 elderly people in December 1996, representing 7.10% of Taiwan’s total population. This figure met the criteria of an old-age society set by the United Nations [
To compare the digital divide on awareness, demand, and adoption of eHealth services in the different technological life cycles, the DMS and DHCS were selected as empirical subjects.
A telephone survey was conducted to evaluate the awareness of, want for, and use of DMS and DHCS. The survey method and questionnaire are presented in
In all, 3074 Taiwanese respondents aged 15 years and older were interviewed by telephone. The demographic, computer ownership, and Internet access profile of the respondents is shown in
Profile of respondents: Demographic variables, computer ownership, and Internet access
Demographics | n | % | ||
Total | 3074 | 100.0 | ||
|
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Male | 1518 | 49.38 | ||
Female | 1556 | 50.62 | ||
|
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15−24 | 509 | 16.6 | ||
25−34 | 621 | 20.2 | ||
35−44 | 568 | 18.5 | ||
45−54 | 565 | 18.4 | ||
55−64 | 367 | 11.9 | ||
≥65 | 444 | 14.4 | ||
|
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Below primary school | 384 | 12.5 | ||
Junior high school | 249 | 8.1 | ||
Senior high school | 1014 | 32.99 | ||
Junior college | 434 | 14.1 | ||
University | 847 | 27.6 | ||
Graduate and above | 146 | 4.8 | ||
|
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Single | 1065 | 34.65 | ||
Married or cohabiting | 1876 | 61.03 | ||
Othera | 133 | 4.3 | ||
|
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Northern Area | 974 | 31.7 | ||
Central Area | 753 | 24.5 | ||
Southern Area | 663 | 21.6 | ||
Eastern Area | 87 | 3 | ||
Taipei City | 365 | 11.9 | ||
Kaohsiung City | 232 | 7.5 | ||
|
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≤450 | 651 | 21.2 | ||
451–650 | 211 | 6.9 | ||
651–950 | 501 | 16.3 | ||
951–1250 | 433 | 14.1 | ||
1251–1550 | 279 | 9.1 | ||
1551–2250 | 219 | 7.1 | ||
≥2251 | 140 | 4.6 | ||
Don’t know/no answer | 641 | 20.8 | ||
|
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No income or unstable | 104 | 3.4 | ||
≤650 | 156 | 5.1 | ||
651–1250 | 478 | 15.5 | ||
1251–1850 | 561 | 18.3 | ||
1851–2450 | 445 | 14.5 | ||
2451–3050 | 316 | 10.3 | ||
3051–4650 | 295 | 9.6 | ||
≥4651 | 155 | 5.0 | ||
Don’t know/no answer | 563 | 18.3 | ||
|
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|
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Yes | 2787 | 90.66 | ||
No | 286 | 9.3 | ||
|
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Yes | 2154 | 70.07 | ||
No | 919 | 29.9 |
a Divorced, separated, or widowed.
The awareness, want, and adoption rates of each demographic group for DMS and DHCS are shown in
Rates of awareness, want, and adoption by demographics and the corresponding regions in the awareness, want, and adoption gap ratio (AWAG) segment matrix for the digital medical service
Stage | Region in |
|||||||||
Awareness | Want | Adoption | Adoption gap ratio | |||||||
Variable | IDb | Item | n | % | n | % | n | % | % | |
Total | T | 2667 | 86.8 | 2390 | 77.8 | 1370 | 44.6 | 42.7 | O_Wb | |
Gender | G1 | Male | 1323 | 87.1 | 1179 | 77.7 | 649 | 42.8 | 44.9 | O_Wb |
G2 | Female | 1344 | 86.4 | 1211 | 77.9 | 721 | 46.3 | 40.5 | O_Wb | |
Age range (years) | A1 | 15−24 | 402 | 78.9 | 399 | 78.4 | 189 | 37.0 | 52.8 | O_G |
A2 | 25−34 | 579 | 93.2 | 524 | 84.4 | 343 | 55.2 | 34.5 | O_Wb | |
A3 | 35−44 | 539 | 94.9 | 470 | 82.8 | 282 | 49.6 | 40.1 | O_Wb | |
A4 | 45−54 | 510 | 90.3 | 454 | 80.3 | 245 | 43.3 | 46.0 | O_Wb | |
A5 | 55−64 | 321 | 87.5 | 280 | 76.4 | 143 | 39.0 | 49.0 | O_Wb | |
A6 | ≥65 | 315 | 71.1 | 263 | 59.3 | 169 | 38.0 | 35.9 | O_G | |
Education level | E1 | Below primary school | 257 | 66.9 | 221 | 57.7 | 124 | 32.4 | 43.8 | O_G |
E2 | Junior high school | 187 | 75.1 | 174 | 69.7 | 72 | 29.0 | 58.4 | O_G | |
E3 | Senior high school | 886 | 87.5 | 764 | 75.4 | 385 | 38.0 | 49.6 | O_Wb | |
E4 | Junior college | 410 | 94.5 | 372 | 85.9 | 223 | 51.4 | 40.1 | O_S | |
E5 | University | 784 | 92.6 | 720 | 84.9 | 469 | 55.3 | 34.9 | O_Wb | |
E6 | Graduate and above | 142 | 97.2 | 139 | 95.2 | 97 | 66.1 | 30.6 | O_S | |
Marital status | M1 | Single | 918 | 86.2 | 863 | 81.1 | 466 | 43.8 | 46.0 | O_Wb |
M2 | Married or cohabiting | 1685 | 89.9 | 1473 | 78.5 | 886 | 47.2 | 39.8 | O_Wb | |
M3 | Otherc | 63 | 47.2 | 54 | 40.7 | 17 | 13.1 | 68.0 | C_G | |
Geographic area | L1 | Northern Area | 868 | 89.2 | 775 | 79.6 | 442 | 45.4 | 43.0 | O_Wb |
L2 | Central Area | 646 | 85.7 | 573 | 76.1 | 310 | 41.1 | 46.0 | O_Wb | |
L3 | Southern Area | 568 | 85.6 | 515 | 77.7 | 305 | 46.1 | 40.7 | O_Wb | |
L4 | Eastern Area | 76 | 86.9 | 74 | 84.6 | 37 | 41.9 | 50.5 | O_Wb | |
L5 | Taipei City | 341 | 93.5 | 304 | 83.4 | 194 | 53.3 | 36.1 | O_Wb | |
L6 | Kaohsiung City | 168 | 72.4 | 148 | 64.0 | 82 | 35.4 | 44.7 | O_G | |
Personal monthly income (US $) | P1 | ≤450 | 520 | 79.9 | 474 | 72.9 | 265 | 40.7 | 44.2 | O_G |
P2 | 451–650 | 181 | 85.7 | 161 | 76.3 | 90 | 42.9 | 43.7 | O_Wb | |
P3 | 651–950 | 460 | 91.9 | 414 | 82.7 | 240 | 47.8 | 42.2 | O_Wb | |
P4 | 951–1250 | 413 | 95.4 | 369 | 85.1 | 219 | 50.5 | 40.7 | O_S | |
P5 | 1251–1550 | 261 | 93.6 | 237 | 85.2 | 149 | 53.5 | 37.2 | O_S | |
P6 | 1551–2250 | 216 | 98.6 | 192 | 88.0 | 150 | 68.6 | 22.0 | O_S | |
P7 | ≥2251 | 137 | 97.8 | 124 | 88.5 | 62 | 44.4 | 49.9 | O_S | |
P8 | Don’t know/no answer | 479 | 74.8 | 419 | 65.3 | 195 | 30.4 | 53.5 | O_G | |
Family monthly income (US $) | F1 | No income or unstable | 88 | 84.9 | 70 | 67.1 | 39 | 37.8 | 43.7 | O_G |
F2 | ≤650 | 120 | 76.9 | 106 | 67.8 | 53 | 33.8 | 50.1 | O_G | |
F3 | 651–1250 | 398 | 83.2 | 347 | 72.6 | 178 | 37.3 | 48.6 | O_G | |
F4 | 1251–1850 | 501 | 89.2 | 462 | 82.3 | 257 | 45.8 | 44.3 | O_Wb | |
F5 | 1851–2450 | 412 | 92.6 | 379 | 85.1 | 239 | 53.6 | 37.0 | O_S | |
F6 | 2451–3050 | 296 | 93.5 | 274 | 86.9 | 176 | 55.6 | 36.0 | O_S | |
F7 | 3051–4650 | 280 | 94.8 | 253 | 85.9 | 164 | 55.8 | 35.1 | O_S | |
F8 | ≥4651 | 147 | 94.8 | 135 | 86.9 | 89 | 57.5 | 33.8 | O_S | |
F9 | Don’t know/no answer | 425 | 75.5 | 364 | 64.6 | 174 | 30.9 | 52.2 | O_G | |
Computer ownership | C1 | Yes | 2496 | 89.6 | 2259 | 81.0 | 1305 | 46.8 | 42.2 | O_Wb |
C2 | No | 170 | 59.5 | 132 | 46.0 | 65 | 22.7 | 50.8 | D_G | |
Internet access | I1 | Yes | 1965 | 91.2 | 1816 | 84.3 | 1114 | 51.7 | 38.6 | O_Wb |
I2 | No | 701 | 76.3 | 574 | 62.5 | 255 | 27.8 | 55.5 | O_G |
a Groups are opened (O), desire-deficiency (D), perception-deficiency (P), and closed (C); regions are strong (S), generic (G), awareness-bias (Ab), and want-bias (Wb).
b Item identifier.
c Divorced, separated, or widowed.
Rates of awareness, want, and adoption by demographics and the corresponding regions in the awareness, want, and adoption gap ratio (AWAG) segment matrix for the digital home care service
Stage | Region in |
|||||||||
Awareness | Want | Adoption | Adoption gap ratio | |||||||
Variable | IDb | Item | n | % | n | % | n | % | % | |
Total | T | 1563 | 50.9 | 2139 | 69.6 | 150 | 4.9 | 93.0 | O_G | |
Gender | G1 | Male | 806 | 53.1 | 1055 | 69.5 | 84 | 5.5 | 92.1 | O_G |
G2 | Female | 757 | 48.7 | 1084 | 69.7 | 66 | 4.3 | 93.9 | P_G | |
Age range (years) | A1 | 15−24 | 250 | 49.1 | 366 | 71.9 | 31 | 6.1 | 91.5 | P_G |
A2 | 25−34 | 318 | 51.2 | 440 | 70.8 | 32 | 5.1 | 92.8 | O_G | |
A3 | 35−44 | 315 | 55.5 | 415 | 73.1 | 23 | 4.0 | 94.5 | O_G | |
A4 | 45−54 | 334 | 59.2 | 432 | 76.5 | 23 | 4.1 | 94.6 | O_G | |
A5 | 55−64 | 173 | 47.2 | 246 | 67.1 | 15 | 4.1 | 93.9 | P_G | |
A6 | ≥65 | 173 | 39.0 | 239 | 53.9 | 27 | 6.0 | 88.9 | P_G | |
Education level | E1 | Below primary school | 120 | 31.3 | 196 | 51.2 | 15 | 4.0 | 92.3 | P_G |
E2 | Junior high school | 114 | 45.7 | 154 | 61.5 | 8 | 3.1 | 95.0 | P_G | |
E3 | Senior high school | 520 | 51.3 | 711 | 70.1 | 44 | 4.4 | 93.8 | O_G | |
E4 | Junior college | 262 | 60.4 | 330 | 76.1 | 20 | 4.5 | 94.0 | O_G | |
E5 | University | 451 | 53.3 | 636 | 75.1 | 55 | 6.4 | 91.4 | O_G | |
E6 | Graduate and above | 96 | 65.8 | 113 | 77.5 | 8 | 5.7 | 92.6 | O_G | |
Marital status | M1 | Single | 541 | 50.8 | 765 | 71.8 | 62 | 5.8 | 92.0 | O_G |
M2 | Married or cohabiting | 989 | 52.7 | 1325 | 70.6 | 86 | 4.6 | 93.5 | O_G | |
M3 | Otherc | 34 | 25.1 | 49 | 37.0 | 2 | 1.7 | 95.3 | C_G | |
Geographic area | L1 | Northern Area | 502 | 51.5 | 689 | 70.8 | 53 | 5.4 | 92.4 | O_G |
L2 | Central Area | 410 | 54.4 | 536 | 71.2 | 44 | 5.8 | 91.8 | O_G | |
L3 | Southern Area | 323 | 48.8 | 443 | 66.7 | 29 | 4.4 | 93.5 | P_G | |
L4 | Eastern Area | 46 | 52.2 | 70 | 80.6 | 3 | 3.4 | 95.7 | O_G | |
L5 | Taipei City | 192 | 52.6 | 270 | 74.1 | 10 | 2.6 | 96.4 | O_G | |
L6 | Kaohsiung City | 91 | 39.4 | 131 | 56.5 | 12 | 5.1 | 91.0 | P_G | |
Personal monthly income (US $) | P1 | <450 | 277 | 42.6 | 422 | 64.8 | 33 | 5.1 | 92.1 | P_G |
P2 | 451–650 | 117 | 55.6 | 146 | 69.0 | 13 | 6.2 | 91.0 | O_G | |
P3 | 651–950 | 258 | 51.5 | 358 | 71.4 | 24 | 4.8 | 93.3 | O_G | |
P4 | 951–1250 | 228 | 52.7 | 332 | 76.7 | 23 | 5.4 | 93.0 | O_G | |
P5 | 1251–1550 | 174 | 62.6 | 206 | 74.0 | 15 | 5.3 | 92.9 | O_G | |
P6 | 1551–2250 | 135 | 61.5 | 178 | 81.2 | 14 | 6.2 | 92.4 | O_G | |
P7 | ≥2251 | 93 | 66.6 | 112 | 79.6 | 12 | 8.7 | 89.0 | O_G | |
P8 | Don’t know/no answer | 280 | 43.7 | 387 | 60.4 | 16 | 2.5 | 95.8 | P_G | |
Family monthly income (US $) | F1 | No income or unstable | 40 | 38.3 | 60 | 57.7 | 1 | 0.6 | 99.0 | P_G |
F2 | ≤650 | 71 | 45.3 | 92 | 58.7 | 5 | 3.2 | 94.6 | P_G | |
F3 | 651–1250 | 210 | 44.0 | 330 | 69.2 | 24 | 5.0 | 92.8 | P_G | |
F4 | 1251–1850 | 320 | 57.0 | 416 | 74.1 | 26 | 4.7 | 93.7 | O_G | |
F5 | 1851–2450 | 246 | 55.3 | 325 | 73.0 | 29 | 6.4 | 91.2 | O_G | |
F6 | 2451–3050 | 171 | 54.2 | 237 | 74.9 | 17 | 5.5 | 92.7 | O_G | |
F7 | 3051–4650 | 182 | 61.8 | 232 | 78.7 | 22 | 7.6 | 90.4 | O_G | |
F8 | ≥4,651 | 87 | 56.2 | 113 | 72.8 | 12 | 8.0 | 89.1 | O_G | |
F9 | Don’t know/no answer | 236 | 41.9 | 334 | 59.3 | 14 | 2.4 | 95.9 | P_G | |
Computer ownership | C1 | Yes | 1473 | 52.9 | 2026 | 72.7 | 143 | 5.1 | 92.9 | O_G |
C2 | No | 90 | 31.4 | 114 | 39.7 | 6 | 2.3 | 94.3 | C_G | |
Internet access | I1 | Yes | 1192 | 55.3 | 1615 | 75.0 | 125 | 5.8 | 92.3 | O_G |
I2 | No | 371 | 40.4 | 524 | 57.0 | 25 | 2.7 | 95.3 | P_G |
a Groups are opened (O), desire-deficiency (D), perception-deficiency (P), and closed (C); regions are strong (S), generic (G), awareness-bias (Ab), and want-bias (Wb).
b Item identifier.
c Divorced, separated, or widowed.
With respect to the digital divide in DHCS, except for gender, the
In the paired proportion test between adoption and awareness or want rates for the demographic groups, there are significant differences between adoption and awareness or want rates across the demographic groups (
In the paired proportion test between awareness and want rates for the demographic groups, there are significant differences between awareness and want rates for most demographic groups (
In the independent proportion test of want rates between unawareness and awareness for DMS and DHCS, there are significant differences for most demographic groups (
With respect to the analysis of the AWAG segment matrix for DMS, most of the segments, except for people without a computer or with marriage status of divorced, separated, or widowed, are positioned under the opened group. This is not surprising given that DMS was already well established in Taiwan. However, although most of the segments belong to the opened group, their degrees of openness are different. In general, individuals with high levels of personal and family monthly incomes, as well as those with education levels of graduate and above, belong to the strong opened group, whereas those who are either younger or older, have low education and family monthly income levels, are living in Kaohsiung City, or have no computer or Internet access belong to the generic opened group. Those without a computer belong to the generic desire-deficiency group with relatively low want, indicating that they may have high awareness of DMS, but their needs may not be identified. People with a marriage status of divorced, separated, or widowed belong to the generic closed group. With relatively low DMS awareness, they may be encountering some barriers in obtaining information (
The adoption gap ratios of segments for DMS range from 22.0% to 68.0%. All segments still have room to promote adoption. Among people with a marriage status of Other, 68% of those who were aware or in want of DMS did not adopt the service. The adoption gap ratios are near or above 50% among people aged between 25 and 34 or between 55 and 64 years; having education levels of junior high school or senior high school; having marriage status of Other; living in the eastern area; having personal monthly incomes above US $2251 and family monthly incomes less than 1250, or did not know or refused to answer questions on personal or family monthly income; and had no computer or Internet access. These findings indicate a huge potential area where DMS adoption can be promoted.
With respect to analysis of the AWAG segment matrix for DHCS, segments are separately positioned in the opened, perception-deficiency, and closed groups. Segments of females; aged between 15 and 24, 55 and 64, and above 65 years; having education levels below primary school or junior school; living in the southern area or Kaohsiung City; having personal monthly incomes of less than US $450, or did not know or refused to answer questions on personal income; having minimal family monthly incomes that were unstable or less than US $1250, or did not know or refused to answer questions on family income; or had no Internet access are positioned in the generic perception-deficiency group. This indicates that the awareness of DHCS for those segments is relatively low. People with marital status of divorced, separated, or widowed, as well as those without a computer, belong to the generic closed group. Both their awareness and want rates are relatively low. Other segments not mentioned above all belong to the generic opened group (
Awareness, want, and adoption gap ratio (AWAG) segment matrix for the digital medical service (DMS) and digital home care service (DHCS).
Awareness, want, and adoption gap ratio (AWAG) segment matrix by age (A; years) for the digital medical service (DMS) and digital home care service (DHCS).
Awareness, want, and adoption gap ratio (AWAG) segment matrix by educational level (E) for the digital medical service (DMS) and digital home care service (DHCS).
Awareness, want, and adoption gap ratio (AWAG) segment matrix by marital status (M) for the digital medical service (DMS) and digital home care service (DHCS).
Awareness, want, and adoption gap ratio (AWAG) segment matrix by geographic area (L) for the digital medical service (DMS) and digital home care service (DHCS).
Awareness, want, and adoption gap ratio (AWAG) segment matrix by personal monthly income (P) for the digital medical service (DMS) and digital home care service (DHCS).
Awareness, want, and adoption gap ratio (AWAG) segment matrix by family monthly income (F) for the digital medical service (DMS) and digital home care service (DHCS). DK = don't know; RA = refused to answer.
Awareness, want, and adoption gap ratio (AWAG) segment matrix by computer ownership (C) and Internet access (I) for the digital medical service (DMS) and digital home care service (DHCS).
The results of this study show that digital divides in DMS and DHCS exist across certain demographic variables. In addition, the study has proven that the want rate is not always bound to the awareness rate. The want rate is usually bound to the awareness rate for existing services, such as DMS. However, DHCS is an innovative e-service in Taiwan; thus, for this service, the want rate is higher than the awareness rate. This study has also proven that awareness and want have reciprocal effects. Adoption may be pulled with rising awareness and want. A higher awareness rate may result in a higher want rate, and people in need of some eHealth services have a higher awareness rate than those who are not in need of the service. Therefore, the innovation diffusion process should start from awareness, followed by want, and awareness and want will gradually rise through the cycle of technology push and consumer pull, and pull adoption.
Using AWAG segment matrix analysis led to several conclusions. With respect to DMS, most segments belong to the opened group. Based on the adoption gap ratio analysis, all the gap values are higher than 22%, signifying that there is room for raising strategies for DMS adoption.
For DMS, segments with high levels of personal and family monthly incomes, as well as segments with education levels of graduate and above, all belong to the strong opened group and are the primary target markets. The marketing strategy of “hold” and the action of “keep up the good work” are suggested. Compared with other segments, the adoption gap ratio for those with personal monthly incomes above US $2251 is the highest and is near 50%. This segment should be ranked first in terms of adoption promotion strategies.
Segments with members who are either younger or older, have low education levels, have low family monthly income levels, live in Kaohsiung City, and have no Internet access belong to the generic opened group for DMS. For these, the “hold and improve strategy” and the action of “keep up the good work and keep raising the awareness and want” are recommended. These segments constitute the third target market for DMS. Other segments, except for people without a computer and with marriage status of Other, constitute the secondary target market for DMS. Thus, the “hold and improve strategy” with the action of “keep up the good work and keep raising the awareness” is suggested.
People without computers belong to the generic desire-deficiency group and are nontarget markets for DMS. The marketing strategy of “improve (create)” and the action of “keep creating the want” are suggested. The adoption gap ratio for this segment is 50.8%; in this segment, half of those who do not adopt DMS are in want of DMS. Thus, the adoption promotion strategy should also be used at once. People with marriage status of Other belong to the generic closed group. The adoption gap ratio for this group is the highest; in this segment, 68% of those who do not adopt DMS are in want of DMS. Thus, the “evaluate then improve (raise)” strategy and the actions of “evaluate the potential of the segment then keep raising the awareness or want” and “promote the adoption” are suggested.
With respect to DHCS, half of the segments belong to the opened group, and one-third of the segments belong to the perception-deficiency group. According to the adoption gap ratio analysis, because DHCS is a new eHealth service in Taiwan, all the gap values are higher than or near 90%, indicating that there is a huge room for raising DHCS adoption.
Segments with members who are female, young, late-middle aged, or elderly; have low education levels; live in the southern area or Kaohsiung City; have low or unstable personal or family incomes or refuse to answer questions on income; or without Internet access belong to the generic perception-deficiency group for DHCS. These segments are potential target markets for DHCS, and the marketing strategy “improve (spread)” and the action of “keep spreading the awareness” are suggested.
People who are divorced, separated, or widowed, or without computers belong to the generic closed group for DHCS. These two segments are nontarget markets for DHCS, and the “evaluate then leave or evaluate then improve (raise)” strategy and the action of “evaluate the potential of the segment then choose an action between “maintain status quo” and “keep raising the awareness or want” should be used. Other segments for DHCS all belong to the generic opened group. These constitute the third target market for DHCS. The “hold and improve strategy” and the action of “keep up the good work” and “keep raising the awareness and want” are thus suggested.
This study has proposed the AWAG segment matrix analysis and analyzed the digital divides in DMS and DHCS across different demographic groups. From the results of this study, the digital divide in awareness and want across different demographic groups can be easily observed by cross-segmenting the awareness and want rates. Marketing strategies have also been clearly established. The adoption gap ratio between adoption and awareness or want rates is large for DMS and even larger for DHCS. These indicate that adoption does not closely follow peoples’ awareness or want, and that a huge digital divide in adoption exists in DHS and DHCS. Adoption education and promotion programs should therefore be used.
For marketing managers in business, government, or other related institutions, the AWAG segment matrix provides a simple and clear method for analyzing the digital divides and differentiating between target and nontarget markets. Moreover, it helps managers adjust their market strategies and allocate their budget more effectively from an objective and customer-oriented viewpoint.
For further research, the AWAG segment matrix can be revised by adding “satisfaction with eHealth service” into the analysis. The AWAG segment matrix can also be extended to analyze differential concerns on information security among the different segments mentioned in this study.
Survey methodology and questionnaire.
Tables 5-11.
awareness, want, and adoption gap ratio
digital home care service
digital medical service
information technology adoption model
None declared.