CHAPTER 3 RESEARCH METHODOLOGY
3.1 Variables Operationalization
In the Pharmacy-UTAUT empirical research model, the definition, assumption and operationalization scale of core independent variables affecting the IT adoption are summarized in this paper, as shown in the table 3.1. It should be noted that considering the original measurement scale of the core independent variables is in English, to ensure the equality of the measurement content before and after translation, this research adopted the reverse translation method proposed by Brislin (1970). To put into practice, first, the author translated the English measurement scale into a Chinese version of measurement scale by himself, then a bilingual linguistics professor from Huai’an Institute of Technology was asked to translate the Chinese version back into English by himself. Finally, the author and the professor compared the two versions of the English measurement scale, analyzed if the second version of the English measurement scale expressed the same content as the original English version and correct the Chinese version accordingly.
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This study used Likert Scale of 7 levels to quantify the extent to which a subject agreed on a particular question, among which 1 stands for “Strongly Disagree”, 2 for
“Quite Disagree”, 3 for “Slightly Disagree”, 4 for “Neither Agree nor Disagree”, 5 for
“Slightly Agree”, 6 for “Quite Agree”, 7 for “Strongly Agree”.
The measurement of the actual use of the retail pharmacies’ IT is an indispensable process in the follow-up empirical research. In the literature review (Section 2.1) of the four major IT adoption models, two issues were found. First, TAM, TAM2 and UTAUT2 use the self-reporting form for the measurement of actual usage behavior. For instance, the actual use was defined by Venkatesh et al. (2012) as a comprehensive variable comprising type and frequency and designed as a question in a questionnaire.
Meanwhile, to reduce the influence of Common Method Variance (CMV), the measurement of the actual use behavior was carried out 4 months later than the first measurement of the behavior-affecting predictor. Second, UTAUT uses the form of System Log. In the empirical research on the adoption of IT in the context of medical health, the behavior measurement methods are divided into the above two categories as well. The first category is self-reporting, for instance, in the research of the IT adoption of CHC institutions staff members in Thailand, Kijsanayotin et al. (2009) divided the actual use behavior into four observation variables, namely frequency of use, care and reporting use, administrative use and communication use. The second category is system logs. For instance, Schaper and Pervan (2007) measured the actual usage behavior of IT using the track usage software Visual Time Analyzer (VTA).
In spite of the drawbacks of self-reporting, it is still an effective measurement of a variable given the limited investigation conditions. This study adopted the self-reporting form to measure the actual use behavior of Chinese retail pharmacies, based on the characteristics of Chinese retail pharmacies’ IT. The “actual use behavior”
variable was measured by an observable variable, namely “the frequency of IT usage”.
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“The frequency of IT usage” was measured using a 5-point scale. 1 means “use less than once a week”, 2 means “use once a week”, 3 means “use twice a week or more”, 4 means “use once a day” and 5 means “use twice or more a day”.
It should be noted that the measurement of the “actual use behavior” of the final variable in this study was not arranged a few months after then measurement of the core independent variable as it is in UTAUT, but was surveyed in the same time as the core independent variable in the same questionnaire. In fact, both interval and simultaneous measurements have their drawbacks. Simultaneous measurement can adopt the “visit concealment method”, “item meaning concealment method” and “reverse item design”
to reduce the impact of CMV (Peng et al., 2006). In this study, to investigate the actual use behavior, questions concerning “the frequency of IT usage” were put forward in the basic information part of the surveyed subject as the first part of the questionnaire, and the respondents were required to answer in order. By designing the structure of questionnaire in this the impact of CMV can be reduced.
41 Table 3.1 Pharmacy-UTAUT: Core Constructs, Definitions, and Scales
Core Constructs / Definitions Scales Source
Performance Expectancy
“The degree to which an individual believes that using the system will help him or her to attain gains in job performance.” (Venkatesh et al., 2003)
PE1: I find pharmacy IT useful in my job. Venkatesh et al. (2003)
PE2: Using pharmacy IT enables me to accomplish tasks more quickly.
PE3: Using pharmacy IT increases my productivity.
PE4: Using pharmacy IT increases my chances of getting a raise.
Effort Expectancy
“The degree of ease associated with the use of the system.” (Venkatesh et al., 2003)
EE1: My interaction with pharmacy IT is clear and understandable. Venkatesh et al. (2003) EE2: It is easy for me to become skillful at using pharmacy IT.
EE3: Learning how to use pharmacy IT is easy for me.
EE4: I find pharmacy IT easy to use.
Attitude
“An individual’s overall affective reaction to using a system.” (Venkatesh et al., 2003)
A1: People in the industry who are important to me think that I should use pharmacy IT. Venkatesh et al. (2003) A2: People in the industry who influence my behavior think that I should use pharmacy IT.
A3: The senior health administration has been helpful in the use of pharmacy IT.
A4: In general, the industry has supported the use of pharmacy IT.
Social Influence
“The degree to which an individual perceives that important others believe he or she should use the new system.” (Venkatesh et al., 2003)
SI1: People in the industry who are important to me think that I should use pharmacy IT. Venkatesh et al. (2003) Kijsanayotin et al. (2009) SI2: People in the industry who influence my behavior think that I should use pharmacy IT.
SI3: The senior health administration has been helpful in the use of pharmacy IT.
SI4: In general, the industry has supported the use of pharmacy IT.
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Core Constructs / Definitions Scales Source
Facilitating Conditions
“The degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system.” (Venkatesh et al., 2003)
FC1: I have the resources (e.g. fund, hardware facility) necessary to use pharmacy IT. Venkatesh et al. (2003) FC2: I have the knowledge (e.g. basic computer use) necessary to use pharmacy IT.
FC3: Pharmacy IT is compatible with other systems I use.
FC4: I can get help from others when I have difficulties using pharmacy IT.
Habit
“The extent to which people tend to perform behaviors automatically because of learning.”
(Limayem et al., 2007)
HA1: The use of pharmacy IT has become a habit for me. Venkatesh et al. (2012)
HA2: I am addicted to using pharmacy IT.
HA3: I must use pharmacy IT.
Behavioral Intention
“The strength to measure individual’s intention to take a particular action.” (Ajzen
& Fishbein, 1975)
BI1: I intend to use pharmacy IT in future work. Venkatesh et al. (2003)
BI2: I predict I would use pharmacy IT in future work.
BI3: I plan to use pharmacy IT in future work.
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