A M ODERATING EFFECT OF INTERRUPTION FACTOR BETWEEN … · applications. The marketers able to realize the effect of an interruption factor in intention to use smartphone applications

AMODERATING EFFECT OF INTERRUPTION FACTOR BETWEEN USER

ATTITUDE AND INTENTION TOWARDS SMARTPHONE APPLICATIONS

1Deepika R,

2Margaret Divya,

3Dr. Senthilkumar N

1,2Research Scholar, Department of Management Studies, Anna University, Chennai, India 3Associate Professor, Department of Management Studies, Anna University, Chennai,

India

[email protected]

ABSTRACT

Background /Objectives:Smartphone makes possible the latest potential adoption of

various applications. The objective of the research is to find out the influence of an interruption

factorbetween user attitude and intention to use smartphone applicationsand to evaluate that

increase in interruption factorwill have a significant effect on user intention to use shopping

applications.Method/ Statistical analysis:The authors measured user intention in the panel study

of 370 smartphone users. To find out the effect of interruption factor between attitude and

intention a stepwise multiple linear regression analysis is used.APearsoncorrelation analysis is

used to find out the overall association towards intention to use shopping applications.

Findings:The interruption factorhas a significant effect on user attitude and user intention

towards shopping applications. Thus the finding reveals that the increase in interruption factoras

a significant effect on user intention to use smartphone applicationsand most of the respondents

are younger generations are well known and not considering the effect of interruption

factor.Applications/Improvements:The paper necessitates the practical implications as well as

social implications. The paper classifies the effects of interruption factorin the usage of shopping

applications. The marketers able to realize the effect of an interruption factorin intention to use

smartphone applicationsso that necessity measures can be taken in order to retain the users.

Keywords:shopping, applications, smartphone, attitude, intention, interruption factor.

International Journal of Pure and Applied MathematicsVolume 118 No. 9 2018, 603-616ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu

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INTRODUCTION

The increasing mobility of the modern society, the number of smartphoneapplicationsas

increased. And this shopping application develops the mobile marketing and in retail business it

takes the greater strength. The most up-to-date generation of smartphones is ever more viewed

as handheld computer rather than phones. In today's application market, there are various

platforms available includes Android, Apple IOS, RIM Blackberry, Windows. More than half of

the world now lives with smartphones rather than traditional landline telephones (Thiam, 2013,

Adak 2014, et. al, 2014).In the last decade, smartphone creats a successful stories and it enables

the dramatic change in the user behavior of smartphone among citizens in India. In a short period

of time, smartphonehas infiltrated considerably into society, from innovators to laggads. These

kind of advancements has created an extended use of smartphone and thus it makes the user to

communicate frequently from anywhere. Active use of Social media and several applications has

made the individuals to use technology in their daily lives and applications make their choices on

their basis (Banerjee & Chua, 2016).The usage of smartphone as changed as global fashion

beyond the age, gender and socioeconomic status of mindsets of people (Aoki &Downes, 2003,

Katz, 1997; Turkle, 2011).

A previous research exhibitsconfirmation that there is extensive diversity in the way that

various people use smartphone apps (H.Falaki,D.Lymberopoulos et. al, 2010).Thus smartphone

smartphoneapplicationsare more effective than the traditional online websites. The relative

influence of online purchasing discovered that price exerted the major influence and extraversion

on purchase decisions as recurrence customers compared to potential customers (Hee – Woong

Kim, et.al, 2012).Marketers can augment the service’s perceived value by capitalize on

efficiency and effectiveness while curtailing the purchase price (Hsu and Lin, 2015). The user

interface quality of the application is considered to be important; the effects of circumstantial

colors and promotional incentives are also to be considered (Hsuan-Yi Chou, Shaojung Sharon

Wang, 2016). This paper begins with the outline of smartphones, smartphone applicationsandits

definition of each constructs.This paper will keep track through methods, data analysis and

discussion of results. The foremostobjective of this study is to determine and

identifywheatherincreases in interruption factor will have an effect on user intention in usage of

shopping applications.

Smartphone

Technolgy has evolved in recent years to determine the part of each human being. In most of the

the technology, the smartphone is the major one which placed in most of human being hands and

plays a crucial role (Duggan & Smith, 2013).

The smartphone arisen in the middle of 90th

century with so many features to meet its

demand in the market (Sagar, 2012)The smartphone consents users to exchange conversation,

text, surf the internet, shopping, payments and so on features available to others, all in one

communication device. The use of smartphone maturessuggestively and consumer behavior in

International Journal of Pure and Applied Mathematics Special Issue

604

information searches and interactive communicationdeviationshistrionically. Through

android/app store applications the usage of the smartphone has changed tremendously. As they

developed more reasonably pricedgadgets are being used by countless people. Thus,the

progresses in 3rd

generation and 4th

generation networks also driving applications in the

smartphone (kuo-LunHsaio, Chia- Chen Chen, 2016).

Shopping Applications

With the rapidlyemerging smartphone market, app services bring massive business

actions and changes users’ lives. Shopping is a inherent decision making system which keeps the

interaction and physical touch among the people to believe and observe about the particular

product (Wu & Wang, 2006). There is a much differences arises among the physical shopping

and the online shopping behavior. In online shopping too, the usage of certain websites and

applications are also differ (Changsu Kim, Robert D Galliers, et. al, 2012). There are two modes

in which individual can perform the shopping in mobile commerce transactions, either through

the standard mobile web browser or downloading and using specific applications. Most of the

smartphone applicationshave online websites and mobile applications too. In the current

scenario, through smartphone the applications become familiar and reaching the user earlier. For

this study, the smartphone applicationstaken into the study is Amazon, Flipkart, Snapdeal,

Gabon.

MATERIALS AND METHODS

To check research constructs and toprove the objectives, a questionnaire was directed

among smartphone users in Chennai, India. The sample study chosen for this study is a

metropolitan city, the innovators of younger generations will adapt to the new technology.The

structured questionnaire is distributed among smartphone users. The purposive sampling

method is used for data collection and the targeted respondents are individuals who have used

shopping applications. Sample sizes of 400 questionnaires were distributed among the

respondents in the context level of education and different age groups. Out of 400 only 370 is

completed and returned, yielding a response rate of 92.5 percent.

RESEARCH MODEL OF THE STUDY

This section discusses the conceptual research outline and consistent hypotheses based

on the objectives. This study uses Technology Acceptance Model as the base to determine the

constructs intention to use new technology. The conceptual frame work for the study in Figure

1.1 and hypothesis framed are listed below.


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Figure 1.1CONCEPTUAL FRAME WORK

Operational Definition of Variables

This section classifiesquite a fewdetermined variables, which put together the factors

regarding as the user intends to use shopping applications.

Perceived Usefulness

In the technology acceptance model, the perceived usefulness played a major role in

determining the acceptance of new technology. This construct reveals the technology usefulness

and it helps to reduce the workload of the user. Perceived usefulness is noteworthy factors

touchingrecognition of an information system or new technologies. Hence NH (Null Hypothesis)

in this study stated as

NH1: There is no significant relationship between Perceived usefulness and User attitude

towards shopping applications.

Perceived Ease of Use

Perceived ease of use is the another important construct in determining the usage of

specific technology. It helps the user for free of effort and the notch to which individual feels that

system is easy to access. Hence it is hypothesized as,

PERCEIVED USEFULNESS

PERCEIVED EASE OF USE

SOCIAL INFLUENCE

PERSONAL

INNOVATIVENESS

USER ATTITUDE

TOWARDS

SHOPPING

APPLICATIONS

INTENTION

TOWARDS

SHOPPING

APPLICATIONS

INTERRUPTION

FACTOR


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NH2: There is no significant relationship between Perceived ease of use and user attitude


Personal Innovativeness

The personal innovativeness is the additional constructs which adds the specific

information of personal differences of each individual and the intenion of human. The research

studies used personal innovativeness construct as a predictor for adoption intention of systems

and information technology.Hence it is hypothesis as

NH3: There is no significant relationship between personal innovativeness and attitude


Social Influences

Social influence is the major factor which determines the acceptance and

influence of person sourroundings which enable the user to use. Social influence is used in many

theories which explains positive effect on behviour intention to use particular technology. Hence

it is hypothesis as

NH4: There is no significant relationship between social influences and attitude towards


User Attitude and Intention

The user attitude and intention is the psychological tendency to the degree of which

positive feeling about the particular system.The attitude which explains the opinions and

expectation fo the user to keep his coginitive system in balance. These constructs are important

for the study to determine the user behavior towards shopping applications. The attitude which is

the successful factor for the adoption of broadband services (Thiagarajan G et.al 2010) and this

applies to the smartphone applications in the way attitude play an important role in determining

the intention to use.

NH5: There is no significant relationship between user attitude and user intention

towards shopping applications

Interruption factor

The Interruption factor reflects that level to which a personhave confidence in and

uncertainties about the probable trouble and ensuing loss triggered by the use of the particular

mobile applications. The Interruption factor can be treated as an activity that is malfunction,

interruption faced by the users in using a particular system or application, defined by Princeton

university wordNet 3.0. (Leppaniemi and Karjaluoto, 2005) Mobile spam such as hidden

transactions cost made by the service providers in the usage of mobile applications. (Wu and

Wang, 2005) any latent cost instigated by the use of the system. Since the construct of


607

interruption factors act as a moderating variable to support the theortical model. The m-

commerce applications are developed using web based technology and through internet based

technologies its acting. The security and privacy is most important to the web based applications.

(Siau and Shen, 2003)Customer trust effectsinterruption factor. (Ghosh and Swaminaha,

2001)defines interruption factors as a security and privacy risk of the user entitled during

transactions and payments. The built-in mobile applications can admittance all the data in the

mobile devices and there are no restrictions for anything. So using native applications for any

transactions the security and privacy will not be expected as much.Hence it is hypothesis as

NH6: There is increase in interruption factor will have no significant effect on user intention

behavior.

NH7: There is no significant association between userintentions to use smartphone shopping

applications.

RESULTS AND DISCUSSION

The study used cronbach’s coefficient to test the reliability of the structured questionnaire

items. From the result, it as shown 0.852 as per Table 1 is a highly reliable coefficient

Chart 1.1 Analysis of Product Which Respondents preferfor their Usage

From the study, there are many applications that can be run on smartphone and tablet. The

user can be attached to any of the product depends upon cost and affordability. Through this

research, it can reveal that smartphone user’s level is more than the tablet users. Some users are

using both smartphone and tablet for smartphone applicationsfor various reasons. The size of the

screen and usage feasibility is also an important factor in using the product. The smartphone

screen size can be up to 6inch and the tablet is more than that. The view of products in small

screen is very difficult comparing to large screen tablet. But smartphone size is handy than the

0

20

40

60

80

100

120

140

160

180

Smartphone Tablet Both

Product

Frequency


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tablet, so most of users are not considering the screen size and they compatibility plays the major

role in choosing the product.

Table1.1 Reliability Test

A Multiple Linear Regression Analysis between Independent Variables (Perceived Ease of

Use, Usefulness, Social influences, Personal Innovativeness) and Attitude:

The study used perceived usefulness, perceived ease of use, personal innovativenessis the

independent variables, whereas the user attitude is the dependent variable. Multiple linear

Regression is used to test the influences among the variables.

Table 1.2Analysis of Multiple Regressions for Attitude towards smartphone applications

Model R Value R Square Adjusted R

Square

Std Error of the Estimate

1 .887 .786 .784 2.30267

a. Predictors : (Constant ) PEOU, PI,SI

Table 1.3 Analysis of Multiple Regression Co-efficient Values for Attitudes towards

smartphone applications

Variables Unstandardized Co-efficient Standardized Coefficients T value P value

B Std. Error Beta

PU(Constant) 1.559 0.375 4.152 .001**

PEOU 0.364 0.109 0.364 3.349 .001**

PI 0.498 0.063 0.514 7.856 .001**

SI 1.702 0.135 1.695 12.584 .001**

a. Dependent Variable : ATT

Note : ** Denotes significant at 1% level.

Table 1.2 shows the R value 0.901 which is said to be good and indicates a strong level

of fit. The R2 value here is 0.887 which shows 88.7% of variance in the user attitude explained

by perceived usefulness, perceived ease of use, personal innovativeness and social influence. It

indicates that these factors are important to measure user attitude towards smartphone

applications.

Cronbach’s alpha No. of items

0.852 7


609

NH1: There is no significant relationship between perceived usefulness and user attitude towards


Table 1.3 shows that there is a statistically significant relationship between perceived

usefulness and user attitude. The co-efficient table shows P value for Perceived usefulness<0.05

which is significant at 1% level, hence concluding that the null hypothesis NH1 is rejected. Since

perceived usefulness has major impact on usage of shopping application, a thought to pay to

efficiency (Lee & Park, 2006). A technology that consents them to purchase outfitmore well and

acquire facts is going to be perceived as valued to the user.

NH2: There is no significant relationship between perceived ease of use (PEOU) and user

attitude (ATT) towards shopping applications.

Table 1.3 shows that there is a statistically significant relationship between perceived

ease of use (PEOU) and attitude (ATT). The co-efficient table shows P value for Perceived ease

of use<0.01 which is significant at 1% level, hence concluding that the null hypothesis NH2 is

rejected. The application user believes that smartphone applicationswill make them free of effort

from online websites and so on.

NH3: There is no significant relationship between personal innovativeness (PI) and user attitude

(ATT) towards shopping applications.

Table 1.3 shows that there is a statistically significant relationship between personal

innovativeness (PI) and attitude (ATT). The co-efficient table shows P value for Personal

innovativeness<0.01 which is significant at 1% level, hence concluding that alternative

hypothesis is accepted and NH3 null hypothesis is rejected.

NH4: There is no significant relationship between Social influences (SI) and user attitude (ATT)


Table 1.3 shows that there is a statistically significant relationship between social

influences (SI) and attitude (ATT). The co-efficient table shows P value for Social Influences

<0.05 which is significant at 1% level, hence concluding that alternative hypothesis is accepted

and NH4 null hypothesis is rejected.

Table 1.4 Analysis of Moderating Effect of Interruption factorCo - EfficientTowards

Smartphone Applications

Model Unstand. Coeff Stand. Co T Sig.

B Std. Beta

1 ATT 4.326 0.557 5.340 .001**

INT 0.156 0.038 0.209 4.099 .001**

2 ATT 2.667 0.846 4.971 .001**

INT 0.040 0.059 0.053 0.675 .001**


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DC 0.141 0.054 0.204 2.593 .001**

a. Dependent Variable : Intention to use

Note : ** Denotes significant at 1% level.

NH6: There is increase in interruption factorwill have no significant effect on user intention

behavior.

Table 1.4 represents construct of interruption factor can statistically support the influence

of attitude and intention towards shopping applications. Here in the co-efficient table, the P value

for interruption factor<0.01 hence alternative is accepted “There is increase in interruption

factorwill have a significant effect on user intention to useand the null hypothesis NH5 is

rejected. It clearly identifies the interrupton factor act as a negative moderator effect to the user

intention towards smartphone applicationsas stated in (Lai Chi Fai, 2011). The safekeeping and

concealment issues are for this category are more important than web-based applications. There

is some negative user effect on usage of smartphone applications(Lai Fai, 2011), but limited to

some extent and these not affected the usage of smartphone applications as mentioned in

previous research studies.

OVERALL ANALYSIS OF PEARSON CORRELATION BETWEEN USER

INTENTIONS TO USE SMARTPHONE SHOPPING APPLICATIONS

The Pearson correlation test is used to find the association between perceived usefulness,

perceived ease of use, personal innovativeness, social influence, and intention to use smartphone

shopping applications. The dependent variable User intention to use and the independent

variables such as Perceived ease of use (PEOU), Perceived Usefulness (PU), Social Influences

(SI), Personal Innovativeness (PI) is used to test the association between the variables.

Table 1.5 Overall analysis of Pearson Correlation towards Intention to use Smartphone

applications

PU PEOU PI SI ATT INT

PU Pearson correlation 1

Sig (2-tail)

PEOU Pearson correlation .895 1

Sig (2-tail) .000

PI Pearson correlation .755 .884 1

Sig (2-tail) .000 .000

SI Pearson correlation .859 .975 .925 1

Sig (2-tail) .000 .000 .000

ATT Pearson correlation .779 .851 .751 .881.

Sig (2-tail) .000 .000 .000 .000


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INT Pearson correlation .755 .884 1.000 .925 .751 1

Sig (2-tail) .000 .000 .000 .000 .000

According to the Table 1.5the pearson’s correlation test for perceived usefulness,

perceived ease of use, personal innovativeness, social influence, attitude and user intention

towards smartphone applicationsindicates that there is a strong association between them. The

analysis of this test clearly reveals that independent construct and attitude is re-counted as vital

and there is a positive relationship between user intentions as the P value is <0.001 at 1%

significant level. The analysis shows that NH7 hypothesis is rejected and alternative hypothesis is

accepted. There is an association between independent constructs and dependent constructs as

attitude between user intentions towards smartphone applications. The user has a positive impact

on using shopping applications, they feel comfortable and trustworthy.

CONCLUSIONS

An examination of research findings reveals that usage of smartphone applicationshave

some limitations but not affected that much as mentioned in previous research findings (Lai Chi

Fai, 2011) .Now a days the smartphone become the life of young generations and they not

considering any issues and giving importance to their activities. Thus the study establishes the

prominence ofinterruption factor such as memory space occupation, privacy, efficiency and

speed is rectified in smartphone applications, in this sense the usage will increase.The Google

play store software make available a exclusive platform for searching, downloading, purchasing

and so on. The interruption factorfactor can be rectified by encourages the users to leave

comments in the app page, feedbackfoms indicating to user , ratings be asked by the user of the

installed apps. Modestly through the particular app, the users search or select for different

applications according to the download reputation, overall rating attractiveness and user reviews.

Moreover all in one application such as shoppingapplicationsin the sense, Amazon, Flipkart,

Snapdeal, and more apps can be searched in single app. For example, the available application in

the android market is all in one shopping app. This contains 50 plus top shopping sites, deal of

the day form top sites.These kinds of applications reduces the occupation of memory space,

saves phone memory, users will come to know about all the offerings from the different retailers

in one place. This study contributes to the marketing online retailers to understand their pros and

cons of their particular application and what are factors which affecting the usage of their

particular retailer application. The findings of their study are important to online retailers to help

them come up with strategies to build online trust and efficiency in usage, which are essential for

them to succeed in e-business.

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Appendix A

Perceived Usefulness

1. Smartphone smartphone applicationssaves more time.

2. Smartphone smartphoneapplicationsthat makes easier for me to do shopping than

websites

3. Smartphone applications provide me prompt and efficiency services.

4. Smartphone applications provide systems to give appropriate feedback.

Perceived Ease of Use

1. Learning to use smartphone applications is easy for me

2. Instructions in the smartphone applications are easy to understand

3. Smartphone applications have more flexible ways to search for information.

4. It will be easy to purchase products through smartphone applications

Personal Innovativeness

1. When I hear about new technology I look for possibilities to experiment with it.

2. I am usually the first to try new information technology

3. I like to experiment with new information technology.

4. I am in the need to experiment with new technology.


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Social Influences

1. Social media (Eg: Facebook, Twitter, etc) do influences my decision on using shopping

applications.

2. Mass media (Eg: TV, Radio, Newspapers) do influences my decision on using shopping

applications.

3. Most people who are important to me think I should use shopping applications.

4. Now a day’s, using smartphone smartphoneapplicationsis current trend.

Attitude

1. Using mobile application for shopping makes me feel satisfied and happy.

2. Mobile application gives facility of easy price comparison.

3. I find mobile applications compatible with my life style.

4. Mobile applications offers discounts more than online websites.

Interruption factor

1. I worry about losing privacy data (such as location, phone number, etc) when installing

mobile application for shopping.

2. I worry about personal information (such as address, bank account, etc) when I use

mobile application for shopping.

3. Smartphone applications are not secure as the traditional online websites.

4. Smartphone applications are not convenient to view more products at a time.

Intention to Use

1. I intend to use smartphone smartphoneapplicationsservices in the future.

2. I intend to use smartphone applications for my shopping.

3. I do recommend that others to use the smartphone applications services.

4. Smartphone smartphoneapplicationsoffers discounts more than online websites.


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A M ODERATING EFFECT OF INTERRUPTION FACTOR BETWEEN … · applications. The marketers able to realize the effect of an interruption factor in intention to use smartphone applications