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Indoor positioning systems (IPS) have become increasingly important for several branches of the economy (eg, in shopping malls) but are relatively new to hospitals and underinvestigated in that context. This research analyzes the intention of actors within a hospital to use an IPS to address this gap.
To investigate the intentions of hospital visitors and employees (as the main actors in a hospital) to use an IPS in a hospital.
The reasoned action approach was used, according to which the behavior of an individual is caused by behavioral intentions that are affected by (1) a persuasion that represents the individual’s attitude toward the behavior, (2) perceived norms that describe the influence of other individuals, and (3) perceived norms that reflect the possibility of the individual influencing the behavior.
The survey responses of 323 hospital visitors and 304 hospital employees were examined separately using SmartPLS 3.3.3. Bootstrapping procedures with 5000 subsamples were used to test the models (one-tailed test with a significance level of .05). The results show that attitude (
This study has two major implications: (1) our extended reasoned action approach model, which takes into account spatial abilities and personal innovativeness, is appropriate for determining hospital visitors’ and employees’ intention to use an IPS; and (2) hospitals should invest in implementing IPS with a focus on (a) navigational services for hospital visitors and (b) asset tracking for hospital employees.
Hospitals are characterized by high levels of physical movement, with a constant stream of temporary visitors (patients and related visitors), personnel, and mobile technical equipment operating in different locations. While efficiency is a concern, it is also of the utmost importance to ensure high levels of hygiene to avoid contamination and the spread of disease, a necessity highlighted by the COVID-19 pandemic. Consequently, preventing the spread of disease by improving hygiene [
Until now, the market penetration for IPS in hospitals has been low because of high implementation costs—roughly US $10200 for approximately 9290 m² [
Research on the adoption of health care tracking apps has shown the importance of acceptance, notably in the context of COVID-19 [
To investigate the intention of actors in hospitals to use IPS, we adopted the well-established reasoned action approach (RAA) as a causal model to identify relevant influencing factors. The RAA identifies reasons for a specific behavior by considering behavioral, normative, and control beliefs [
Our results contribute to understanding which factors influence the intention of actors (ie, hospital visitors and employees) to use systems or applications (ie, IPS) in the health care management context. We show that the RAA, extended to include spatial abilities, can explain the intentions of two major stakeholder groups to use systems in the context of health care management. Hospitals wishing to improve hygiene can apply these insights to encourage IPS usage. This will help tackle a range of issues, from the threat of multiresistant germs to restrictions on hospital visitor numbers during a pandemic. Therefore, we recommend that hospitals invest in the implementation of IPS, taking stakeholder-specific requirements into account.
This article is organized as follows: the second and third sections clarify the theoretical background to the research and introduce the hypotheses and research model. The fourth section describes the materials and methods, and the fifth section presents the results, which are discussed in the sixth section. The final section concludes the research, clarifies its implications, and provides an outlook for further investigations.
An IPS determines the specific position of an individual or an asset [
Functional setup of an exemplary positioning system in a hospital [
Navigation applications allow the tracking of individuals by connecting localization data with personal data [
Model-driven approaches have been adopted in IPS research to account for the navigational requirements of users [
Within the hospital context, the only relevant study is that of Anagnostopoulos et al [
The RAA is a well-established psychological approach based on the theory of reasoned action [
An individual's attitude regarding a certain behavior is influenced by his or her beliefs concerning the characteristics and attributes related to the behavior. Thus, an attitude is affected by individual consequences that emerge through assessments of whether or not the behavior is desirable. Therefore, the individual is influenced by whether the behavior is endorsed or opposed by other individuals or groups (those who are most important to her or him in terms of the relevant behavior). The aggregation of motivation and perception assessments for all relevant referent groups is referred to as perceived norms [
Perceived behavioral control determines whether an individual is capable of or directly controls a specific behavior. It is defined by control beliefs that reflect the individual's key personal or situational aspects in relation to the behavior. Ultimately, performing a specific behavior involves the comparison and selection of attitudes, perceived norms, and perceived behavioral controls associated with each of the alternative behaviors in the choice set [
The reasoned action approach (RAA) according to Fishbein et al [
The RAA is a framework that has to be adjusted to a specific context [
First, behavioral beliefs are important for ascertaining the value that an individual perceives in using an IPS. These beliefs cover whether an IPS is perceived as helpful in finding the right location or tracking an object. The positive or negative feelings an individual has toward using an IPS in a hospital (the individual’s attitude) are rooted in those beliefs. For the purposes of this study, positive feelings are taken as how the individual feels, as it is the individual who determines whether an IPS is beneficial, satisfactory, relevant, and pleasant to use [
H1: The higher the behavioral beliefs concerning the use of an IPS in a hospital, the more positive an individual's attitude regarding the IPS.
H2: The more positive an individual's attitude concerning the use of an IPS in a hospital, the higher the intention to use the IPS.
Second, in line with RAA research, we represent the attitudes of other relevant individuals and groups as normative beliefs (subjective norms) [
H3: The higher the normative beliefs concerning the use of an IPS in a hospital, the more positive an individual’s perceived norms regarding the IPS.
H4: The more positive an individual’s perceived norms regarding the use of an IPS in a hospital, the higher the intention to use the IPS.
Third, it is necessary to investigate what facilitates or obstructs an individual’s use of an IPS in a hospital. Two of the most critical success factors in relation to information technology projects in hospitals considered are: (1) the complexity of the system and (2) the explanation of how to access it [
H5: The higher the control beliefs concerning an IPS in a hospital, the more positive the perceived behavioral control of an individual regarding the IPS.
H6: The higher the perceived behavioral control in terms of an IPS in a hospital, the higher the intention to use the IPS.
The navigational skills of the individuals have to be examined to determine confidence in the use of IPS in a hospital (in terms of perceived behavioral control) [
H7: The higher the spatial abilities, the higher the perceived behavioral control.
H8: The higher the spatial abilities, the lower the intention to use an IPS in a hospital.
For employees, we investigate their spatial abilities both for buildings that they know (the hospital where they work) and for large unfamiliar buildings, leading to the following hypotheses:
H9: The higher the spatial abilities for known buildings, the higher the perceived behavioral control.
H10: The higher the spatial abilities for large unknown buildings, the higher the perceived behavioral control.
H11: The higher the spatial abilities for known buildings, the lower the intention to use an IPS in a hospital.
H12: The higher the spatial abilities for unknown buildings, the lower the intention to use an IPS in a hospital.
The research model developed from these hypotheses is shown in
Research model.
We used a 7-point Likert scale for each item (from 1 “do not agree at all” to 7 “completely agree”). As Fishbein and Ajzen [
We included several control variables (ie, the size of the hospital and types of buildings, the employees’ work area, how long employees have been working at the hospital, when visitors or patients were present in the hospital, levels of personal innovativeness, and demographic data such as age and gender). The complete questionnaires can be found in A-1
The crowdworking platform Clickworker (similar to Amazon MTurk) was used to gather hospital visitors and employees in Germany in April and August 2020. The questionnaires for visitors and employees were separate. We included test questions at the beginning and end of the questionnaire to ensure that the self-reported status was correct. At the beginning of the process, participants also received a text that explained the main function of an IPS. Since the unsupervised online platform paid the participants for their responses, we followed the recommendations of Goodman et al [
Among the hospital visitors, the youngest participant was 18 years of age, and the oldest was 68 years. The mean age was 36.08 years (SD 11.73), with a variance of 137.48 years. A majority (250/323, 77.4%) were aged between 18 and 44 years, and 22.29% (72/323) were between 45 and 64 years.
For the hospital employees, the mean age was 33.67 years (SD 9.62), with a variance of 92.37 years. We asked the employees to state the main functional area in which they work. The most common area was nursing care (96/304, 31.58%), followed by hospital management (51/304, 16.78%), building services (37/304, 12.17%), diagnosis and therapy (26/304, 8.55%), research, teaching, and training (20/304, 6.58%), emergency medical services (19/304, 6.25%), pastoral care and social services (16/304, 5.26%), supply and waste management (12/304, 3.95%), integrated ambulant care (12/304, 3.95%), kindergarten for employees (11/304, 3.62%), hospice care (3/304, 0.97%), and patient accommodation (1/304, 0.33%).
A partial least squares approach to SEM was used to test the proposed models for hospital visitors and employees. Variance-based SEM is more suitable than covariance-based SEM in cases where the aim is to explain and predict the target construction in structural models or to identify key drivers [
First, composite reliability, used to examine internal consistency, was confirmed for both visitors and employees (A-5
The variance inflation factor was used to check for multicollinearity among the indicators for formative belief variables. For both groups, the values were in line with requirements (A-3
We also conducted several tests to ascertain the quality of our structural model. We used the standardized root mean square residual (SRMR) to determine the approximate fit for our composite factor and common factor models [
The descriptive statistics and correlations for both our samples are given in
The results of our analysis concerning the hospital visitors are presented in
For the visitors, strong empirical evidence was found in support of H1 (
Our investigation of H2 (
We found that perceived behavioral control is not a predictor of intention to use an IPS (
Descriptive statistics for the overall sample and correlations among variables for visitors (V) and employees (E).
Variablea | Mean (SD) | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
1 | Vb: 33.04 (11.2) E: 29.94 (11.63) | –c | V: .51*** E: .70** | V: .67*** E: .71** | V: .77*** E: .74** | V: .53*** E: .63** | V: .38*** E: .51** | V: –.21*** | E: –.04 | E: .20** | V: .70*** E: .70** |
2 | V: 23.75 (10.44) E: 27.35 (10.34) |
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– | V: .52*** E: .688** | V: .56*** E: .63** | V: .79*** E: .74** | V: .21*** E: .54** | V: .03 | E: .01 | E: .21** | V: .49*** E: .62** |
3 | V: 30.24 (11.27) E: 29.92 (11.84) |
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– | V: .67*** E: .67** | V: .58*** E: .65** | V: .28*** E: .50** | V: –.15** | E: –.08 | E: .19** | V: .71*** E: .70** |
4 | V: 5.55 (1.13) E : 5.39 (1.14) |
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– | V: .59*** E: .66** | V: .36*** E: .43** | V: –.16** | E: .05 | E: .11** | V: .74*** E: .65** |
5 | V: 4.64 (1.30) E: 4.84 (1.23) |
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– | V: .15** E: .39** | V: –.09 | E: .09 | E: .07 | V: .59*** E: .66** |
6 | V: 6.04 (0.94)E: 5.39 (1.24) |
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– | V: .10 | E: .03 | E: .24** | V: .31*** |
7 | V: 4.26 (1.25) |
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– | – | – | V: –.19** |
8 | E: 4.05 (1.50) |
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– | E: .43** | E: –.10 |
9 | E: 5.30 (1.08) |
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– | E: .04 |
10 | V: 5.34 (1.54) E: 5.24 (1.47) |
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aNumber assignment: 1=behavioral beliefs; 2=normative beliefs; 3=control beliefs; 4=attitude; 5=perceived norms; 6=perceived behavioral control; 7=spatial ability; 8=spatial ability large, unknown buildings; 9=spatial ability known buildings; 10=intention.
bV: n=323; E: n=304.
cNot applicable.
*
We found strong empirical evidence for H1 (
The results support H2 (
Research model results for hospital visitors. *
Research model results for hospital employees. *
As gender and age are important factors in spatial ability [
Post hoc analysis by gender and age.
No. | Group | Gender | Age, years | Correlation/( |
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1 | Visitors | Women | All | SAa>PBCb/(0.025) | .226 | .008 |
2 | Visitors | Men | All | SA>PBC | .061 | .188 |
3 | Visitors | Both | 34–68 | SA>PBC | .216 | .001 |
4 | Visitors | Both | 18–33 | SA>PBC | .058 | .235 |
5 | Visitors | Women | 34–68 | SA>PBC | .300 | .018 |
6 | Visitors | Women | 18–33 | SA>PBC | .172 | .098 |
7 | Visitors | Men | 34–68 | SA>PBC | .133 | .078 |
8 | Visitors | Men | 18–33 | SA>PBC | –.034 | .371 |
9 | Employees | Women | All | SA/KBc>PBC/(0.020) | .109 | .162 |
10 | Employees | Men | All | SA/KB>PBC | .172 | .018 |
11 | Employees | Both | 33–63 | SA/KB>PBC | .071 | .232 |
12 | Employees | Both | 18–32 | SA/KB>PBC | .177 | .025 |
13 | Employees | Women | 33–63 | SA/KB>PBC | .245 | .042 |
14 | Employees | Women | 18–32 | SA/KB>PBC | .353 | .002 |
15 | Employees | Men | 33–63 | SA/KB>PBC | .169 | .046 |
16 | Employees | Men | 18–32 | SA/KB>PBC | .141 | .138 |
17 | Employees | Women | All | SA/LUBd>Ie/(0.041) | –.154 | .008 |
18 | Employees | Men | All | SA/LUB>I | –.104 | .026 |
19 | Employees | Both | 33–63 | SA/LUB>I | –.212 | .000 |
20 | Employees | Both | 18–32 | SA/LUB>I | –.076 | .086 |
21 | Employees | Women | 33–63 | SA/LUB>I | –.078 | .161 |
22 | Employees | Women | 18–32 | SA/LUB>I | –.044 | .299 |
23 | Employees | Men | 33–63 | SA/LUB>I | –.161 | .019 |
24 | Employees | Men | 18–32 | SA/LUB>I | –.009 | .453 |
25 | Visitors | Women | All | PIf>Attg/(0.024) | .094 | .072 |
26 | Visitors | Men | All | PI>Att | .113 | .011 |
27 | Visitors | Both | 34–68 | PI>Att | .027 | .285 |
28 | Visitors | Both | 18–33 | PI>Att | .200 | .000 |
29 | Visitors | Women | 34–68 | PI>Att | –.060 | .239 |
30 | Visitors | Women | 18–33 | PI>Att | .223 | .006 |
31 | Visitors | Men | 34–68 | PI>Att | .087 | .103 |
32 | Visitors | Men | 18–33 | PI>Att | .119 | .043 |
33 | Visitors | Women | All | PI>PBC | .189 | .047 |
34 | Visitors | Men | All | PI>PBC | .119 | .045 |
35 | Visitors | Both | 34–68 | PI>PBC | .175 | .018 |
36 | Visitors | Both | 18–33 | PI>PBC | .100 | .138 |
37 | Visitors | Women | 34–68 | PI>PBC | .237 | .090 |
38 | Visitors | Women | 18–33 | PI>PBC | .181 | .153 |
39 | Visitors | Men | 34–68 | PI>PBC | .163 | .052 |
40 | Visitors | Men | 18–33 | PI>PBC | .047 | .337 |
41 | Employees | Women | All | PI>I/(0.168) | .248 | .001 |
42 | Employees | Men | All | PI>I | .319 | .000 |
43 | Employees | Both | 33–63 | PI>I | .243 | .000 |
44 | Employees | Both | 18–32 | PI>I | .315 | .000 |
45 | Employees | Women | 33–63 | PI>I | .186 | .040 |
46 | Employees | Women | 18–32 | PI>I | .201 | .039 |
47 | Employees | Men | 33–63 | PI>I | .238 | .003 |
48 | Employees | Men | 18–32 | PI>I | .440 | .000 |
aSA: spatial ability.
bPBC: perceived behavioral control.
cKB: known buildings.
dLUB: large unknown buildings.
eI: intention.
fPI: personal innovativeness.
gAtt: attitude.
In our investigation of intention to use an IPS in a hospital, we identified significant differences between visitors and employees. First, while perceived behavioral control is not significant in determining visitors’ intention to use (
Second, spatial abilities are significant for perceived behavioral control regarding hospital visitors (
For visitors, personal innovativeness is not significant for intention to use an IPS (
In current research on spatial abilities, the influence of gender is disputed; research that uses abstract measures, such as mental rotation, indicates that men are better than women at wayfinding [
The findings concerning the impact of the spatial abilities of employees for known buildings on perceived behavioral control align with the findings for visitors. However, it should be noted that the path is also significant for male employees aged 33-63 years (see
For unfamiliar environments, other aspects may be more relevant in determining the urgency of navigational assistance and thus intention to use an IPS, such as the complexity of the environment [
Hence, our results support the consensus in technology adoption research that there is a gender difference. Men’s decisions to adopt new technology are driven mainly by their attitude toward the technology, whereas women’s decisions are driven by subjective norms and perceived behavioral control [
To clarify the influence of the employees’ structural unit on their spatial abilities for known buildings, we post hoc analyzed our data set according to the functional areas in which the individuals are employed. Thus, we distinguished between employees who move through hospital buildings frequently because of their occupation (ie, those in nursing care, building services, and emergency medical services) and those who work mainly in the same place (all the other functional areas represented in our data; see “Data Collection And Participants”). We found that employees who work mainly in the same place are more confident in their spatial abilities in relation to known buildings (
Concerning the core model of the RAA, our investigation indicates that attitude and perceived norms are strong predictors of intention to use an IPS in a hospital. For hospital employees, the results are more differentiated; all the reflective variables of the RAA (attitude, perceived norms, and perceived behavioral control) are significant for intention to use, with perceived norms having the strongest influence. Attitude driven by behavioral beliefs is a major predictor of intention to use [
The descriptive statistics for spatial abilities show a mean of 4.18 (SD 1.56) for visitors, and for employers, a mean of 4.05 (SD 1.69) for large unknown buildings and a mean of 5.29 (SD 1.34) for known buildings. These results indicate that employees tend to navigate better through known buildings than through large unknown buildings, although no such tendency is found for visitors. For the influence of the personal innovativeness of employees on their intention to use an IPS, the mean value of 4.86 (SD 1.54) suggests that employees intend to use an IPS if they are personally innovative in terms of new technologies (see A-1
We analyzed the relevance of IPS in hospitals by considering the perspectives of the main actors, visitors, and employees. The explained variance indicates that intention to use is well predicted and that relevant aspects in the context are covered. This confirms that RAA is an appropriate approach for determining intention to use an IPS in a hospital. Furthermore, our results show that individual attitude and the social norms of relevant reference groups positively impact intention to use an IPS in a hospital. For employees, perceived behavioral control also positively influences intention to use an IPS. These results have many implications for theory, practice, and future research.
Our study design and findings contribute to the literature in several ways. First, we add to the knowledge of how systems or applications, specifically IPS, in the health care management context are accepted by actors in a hospital. Whereas related work regarding general health care tracking apps, including COVID-19-related apps [
Second, we integrate two major stakeholder groups into our analysis: general users, such as patients or visitors, and professional staff. As such, we demonstrate how health care management applications are perceived from a nonexpert perspective, thereby building on previous research, which has generally adopted an expert perspective [
Third, we introduce the RAA to analyze intention to use applications in the health care management context, thereby extending the theory conceptually and empirically into a context that considers spatial abilities and personal innovativeness. The high explained variance confirms that the theory is helpful for understanding the reasons for adoption intentions. This increased focus on analyzing the influence of different beliefs from a functional perspective extends other theories that have been applied in the context, such as uncertainty reduction theory [
Fourth, our extension of the RAA to cover spatial abilities and personal innovativeness contributes to the understanding of gender-related and age-related spatial ability. Hence, we demonstrate that demographics matter and should be considered when analyzing the acceptance of applications in a health care management context.
From a practical perspective, we recommend that hospitals invest in implementing IPS, as our results show that the potential user intention is high. Furthermore, IPS market research forecasts indicate that low-energy Bluetooth will be one of the most lucrative segments of the IPS market [
However, the IPS design requirements of hospital visitors and employees are different. From our finding that visitors’ attitudes and perceived norms are the most important predictors of their intention to use, it follows that the system needs to be simple and self-explanatory. The main focus of the application should be navigation to specific rooms or points of interest. If those services function properly, visitors are likely to recommend the system to reference groups that are important to them (eg, close friends and family), who will then assess and use the system accordingly.
For hospital employees, attitude and perceived norms are also relevant. However, the system needs a different functional focus for employees, whose intentions are determined by perceived behavioral control. Our research model shows that employees that work mainly in the same place are confident in their spatial abilities for known buildings. In other words, they do not need navigational services for specific rooms or points of interest in the hospital building in which they are employed. Asset tracking, in contrast, is more relevant, as this can facilitate daily work and help reduce redundant activity.
Our study is subject to some limitations that inform future research. First, we used the crowdworking platform Clickworker to gather our participants. This decision partly predetermined the personal innovativeness of our respondents, as individuals who use digital platforms are likely to be more personally innovative than those who respond to a pen and paper survey. Second, our study design involves convenience sampling, albeit with specific criteria for participation. Thus, we cannot claim that our sample is representative, and further research should focus on a defined target population. Third, our participants are from a single country, Germany. Future studies should cover different countries to identify additional relevant factors. Fourth, our research does not consider other settings, such as large hardware stores, that may be relevant to and interact with the hospital context. Therefore, future research should investigate general acceptance of IPS by, for example, determining the likelihood of using an IPS in a hardware store after using it in a hospital.
The Multimedia Appendix contains: the questionnaire (A-1), loadings of reflective variables (A-2), VIF values (A-3), loadings and weights of formative variables (A-4), composite reliability and AVE (A-5), HTMT- (A-6) and Stone-Geisser-values (A-7) of our study.
indoor positioning system
reasoned action approach
structural equation modeling
standardized root mean square residual
None declared.