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Computers in Human Behavior 35 (2014) 75–84
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Computers in Human Behavior
journal homepage: www.elsevier .com/locate /comphumbeh
Discovering determinants of users perception of mobile devicefunctionality fit
http://dx.doi.org/10.1016/j.chb.2014.02.0200747-5632/� 2014 Elsevier Ltd. All rights reserved.
⇑ Corresponding author. Address: College of Business, University of North Texas,1155 Union Circle #311160, Denton, TX 76203-5017, USA. Tel.: +1 (940) 594 1822.
E-mail addresses: [email protected] (A. Negahban), [email protected] (C.-H. Chung).
Arash Negahban a,⇑, Chih-Hung Chung b
a College of Business, University of North Texas, 1155 Union Circle #311160, Denton, TX 76203, USAb College of Information, University of North Texas, 1155 Union Circle #311068, Denton, TX 76203, USA
a r t i c l e i n f o
Article history:Available online 18 March 2014
Keywords:Perceived mobile device-functionality fitMultifunctional useMultifunctionalityMobile deviceSmartphones
a b s t r a c t
In recent years, there has been an explosive growth in the use of mobile devices. The ubiquitous and mul-tifunctional nature of these devices with internet connectivity and personalization features make them aunique context to investigate what factors shape mobile users perception of their mobile device function-ality fit with their needs. In order to answer this question, we proposed a research model in which weintroduced multifunctional use and perceived device-functionality fit as two new constructs. The resultsof our study show that a significant portion of individuals’ perceived device-functionality fit can beexplained by their perceived enjoyment, perceived ease of use, perceived usefulness, and symbolic valueof the device. In terms of the theoretical contribution, our research suggests revamping the concept ofdevice-functionality fit when it comes to mobile devices by accounting for both hedonic and utilitarianaspects of mobile devices. In terms of practical implications, our study highlights the importance ofthe social image that mobile devices create in the society for their users as well as the importance oflook-and-feel aspects of mobile devices in shaping users perception of fit between functionalities of theirmobile devices and their needs.
� 2014 Elsevier Ltd. All rights reserved.
1. Introduction
Today, mobile phone is an essential device in our daily lives. Thepropagation of mobile devices along with omnipresent internet ac-cess has significantly changed our lives by changing the essence ofmobile phones from simple voice and messaging devices to highlyflexible and multifunctional devices that can be used almost any-time and anywhere for a wide range of purposes, ranging fromfully utilitarian to fully hedonic. Mobile technology has dramati-cally changed not only the way many businesses worked, but alsothe way we live and communicate with each other. It has reshapedour social habits, behaviors and our relationships with others. Ithas brought new needs to our lives that we never had before.
Mobile devices, such as smartphones, support for internet con-nectivity, GPS, digital camera, and multimedia has nurtured theproliferation of myriad mobile applications that combine these ser-vices to enrich the functionalities of these devices. It is no longereasy to list all the functionalities that a mobile device provides. It
seems that the scope of functionalities that mobile devices providethese days is ever growing.
The ubiquitous and multifunctional essence of these devicesalong with their personalization features allows mobile users toadd different applications to their mobile devices and customizethem based on preferences as well as use them to address their he-donic or utilitarian needs. This makes the context of ubiquitouscomputing and mobile technology a unique area of study for aca-demics and a boundless opportunity for the practitioners.
Previous studies have shown two broad emerging factors affectacceptance of mobile phones: Interface characteristics and net-work capabilities (Sarker & Wells, 2003). However, in this study,we investigate how the concept of fit between users’ requirementsand device functionalities can be applied into the context of mobiledevices and how their unique characteristics can affect user’s per-ception of their mobile device-functionality fit.
The remainder of the paper is structured as follows. After thisintroduction, we will provide a brief overview of the relevant liter-ature and develop our research model for mobile device function-ality fit. We will then discuss our research methodology, results,key findings and contributions, followed by limitations, directionsfor future research, and conclusion.
76 A. Negahban, C.-H. Chung / Computers in Human Behavior 35 (2014) 75–84
2. Theoretical background
In this section, we present an overview of the widely used the-ories that have been applied within the context of adoption anduse of mobile technology in order to build a foundation for our re-search model and introduce the concepts of perceived mobile devicefunctionality fit and multifunctional use.
2.1. Adoption and use of information technology
Technology acceptance model (TAM) (Davis, 1989) has beenwidely used to explain users’ acceptance and use of mobile tech-nology (Kim & Garrison, 2009; Kim, Park, & Morrison, 2008;Negahban, 2012; Oi, Li, Li, & Shu, 2009; Son, Park, Kim, & Chou,2012) and various mobile services including mobile internet(Chong, Darmawan, Ooi, & Lin, 2010; Chong, Zhang, Lai, & Nie,2012; Kuo & Yen, 2009; Lee, Noh, & Kim, 2012; López-Nicolás,Molina-Castillo, & Bouwman, 2008), mobile games (Liu & Li,2011), financial mobile services (Chen, 2008; Hsu, Wang, & Lin,2011; Jaradat & Twaissi, 2010; Kim, Mirusmonov, & Lee, 2010;Liu, Wang, & Wang, 2011; Luarn & Lin, 2005; Teo, Tan, Cheah,Ooi, & Yew, 2012), mobile health-care services (Lin, 2011), mobileTV (Jung, Perez-Mira, & Wiley-Patton, 2009), and mobile text alertsystems (Lee, Chung, & Kim, 2013). TAM posits that perceived use-fulness (PU) and perceived ease of use (PEOU) are the determinantsof behavioral intention to use (BI). Perceived usefulness is definedas ‘‘the degree to which a person believes that using a particularsystem would enhance his or her job performance’’ (Davis, 1989,p. 320). Perceived ease of use is defined as ‘‘the degree to which aperson believes that using a particular system would be free of ef-fort’’ (Davis, 1989, p. 320). Despite its widely use, TAM has somelimitations in explaining acceptance and use of mobile technology(López-Nicolás et al., 2008); which were later on addressed byother complementary theories.
The united theory of acceptance and use of technology(UTAUT) developed by Venkatesh, Morris, Davis, and Davis(2003) was used to evaluate the probability of success for newtechnology overviews. Moreover, in order to design interven-tions for users that may be less inclined to adopt and use newsystems, it also supports them to understand the drivers ofacceptance. UTAUT incorporated TAM, Theory of planned behav-ior (TPB), innovation diffusion theory (IDT), motivation model,social cognitive theory to develop a unified theory for technol-ogy acceptance. In addition, it tested independent variables,such as, performance expectancy, effort expectancy, social influ-ence, facilitating conditions, to use of technology, controlling forgender, age, experience, and voluntariness of use. UTAUT alsoaccounts for internal and external motivations. However,although the UTAUT provides a more detailed model for accep-tance and use of technology, it was still has certain limitations.Therefore, Venkatesh, Thong, and Xu (2012) developed UTAUT2and added hedonic motivation, price value, and habit to explainthe model of acceptance and use of technology. UTAUT2 pro-vides an integrated model of acceptance and use of technology,which improves TAM. UTAUT and UTAU2 provide a more de-tailed conceptions about the relationships between external,internal motivations, and acceptance and use of mobile technol-ogy. These two models hold that social influence (symbolic va-lue) influences perceived usefulness. They have been used inprevious research to investigate acceptance of various mobileservices such as online mobile games (Chen & Kuan, 2012), mo-bile banking (Tan, Chong, Loh, & Lin, 2010), and other mobileservices (Han, Mustonen, Seppanen, & Kallio, 2006; Rao Hill &Troshani, 2010).
2.2. Hedonic aspects of information systems
Information systems (IS) can have both hedonic and utilitarianpurposes. Utilitarian information systems aim to provide instru-mental value to users while hedonic information systems aim toprovide self-fulfilling value to users (Heijden, 2004; Sun & ZhanG,2006). However, the utilitarian-hedonic aspects of systems aretask-dependent. This can blur the boundary between hedonicand utilitarian aspects, especially for mixed systems that can beused for either purposes (Sun & ZhanG, 2006). For example, inter-net can be used both for finding a job (utilitarian use) and forwatching movies (hedonic use).
Previous studies have found that perceived enjoyment is a dom-inant predictor for hedonic aspects of information systems andperceived usefulness is strong predictor for utilitarian aspects ofIS (Heijden, 2004). Perceived enjoyment is defined as the qualitythat using technology is perceived to be enjoyable by its own,regardless of performance expectations (Davis, Bagozzi, & War-shaw, 1992).
Perceived enjoyment and perceived usefulness are importantfactors that influence users’ acceptance and use of technology(Hong & Tam, 2006; Lee & Chang, 2011; Liao, Tsou, & Huang,2007; Thong, Hong, & Tam, 2006). Attitudinal beliefs, includingperceive usability, perceive ease of use, and perceived enjoymentalso significantly affect user’s hedonic attitude (Hong, Thong,Moon, & Tam, 2008). Enjoyment is also identified as a value driverof hedonic digital artifacts (Turel, Serenko, & Bontis, 2010).
2.3. Device multifunctionality
Today, mobile devices are no longer a mere communication de-vice for voice calling and text messaging, but they also provide var-ious functionalities and services to their users such as multimedia,games, digital camera, mobile internet, navigation and GPS (globalpositioning system), video communication, music players (Dunlop& Brewster, 2002; Jin & Ji, 2010). By converging a large variety offunctionalities, these devices are now transformed into multiplexmultifunctional devices that address different needs of its users(Jin & Ji, 2010).
Multifunctionality, as a key characteristic of mobile devices, hasnot formally pinpointed in IS literature. It is commonly associatedwith mobile hardware (Hoehle & Scornavacca, 2008) and the chal-lenges it creates for Human–Computer Interaction (HCI) designers(Dunlop & Brewster, 2002). Some researchers compare mobile de-vices to ‘‘Swiss Army Knife’’ and discuss that trying to cram asmuch functionalities as possible into a single device may impairefficiency and effectiveness of those functionalities provided bymobile device (Satyanarayanan, 2005), thus reducing its perceivedusefulness.
The effect of multifunctional use of mobile devices on individ-ual’s device usage behavior has been studied in previous research.In a study, Lin, Chan, and Xu (2012), tested multifunctionalitywithin the context of smartphones by combining hedonic aspectsof use and theory of planned behavior (TPB) (Ajzen, 1991) – whichis a widely used theory for predicting adoption of a single function-ality – to understand how it may impact adoption of multifunc-tional devices (Lin et al., 2012). They found that TPB and pleasuretogether can explain more than 50% of the variance in intentionto use while the effect of pleasure varied from function to function.In another study, Hong and Tam (2006) found that adoption deci-sion determinants for multipurpose information appliance are dif-ferent from those of the utilitarian systems and are dependent onthe context of use and the nature of the target technology. They de-fined multipurpose information appliances ‘‘as IT artifacts that (1)have a one-to-one binding with the user, (2) offer ubiquitous services
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and access, and (3) provide a suite of utilitarian and hedonic func-tions’’ (Hong & Tam, 2006, p. 162). They discussed that the ubiqui-tous and hedonic nature of multipurpose mobile devices sets themapart from other technologies in work settings.
Previous research views multifunctionality of a device based onits hardware/software features and potential uses rather than thedegree of its user’s multifunctional use. In other words, previousstudies mostly approached the concept of multifunctionality froma device vantage point (which we name as device-perspective ofmultifunctionality) rather than from the user’s viewpoint (whichwe name as user-perspective of multifunctionality).
To date, we are unaware of any study that measures multifunc-tionality based on user’s usage behavior and the degree to whichusers use various functionalities of their mobile device. To the ex-tent of our knowledge there are also no studies that explore the ef-fect of user’s multifunctional use of the device on device’sfunctionality fit with the user’s needs. In this study, we distinguishbetween the two views of multifuntionality (device-perspectiveand user-perspective) and address multifunctionality from user’sperspective.
2.4. Functionality fit
Theory of task–technology fit (TTF) (Goodhue & Thompson,1995) focuses on the fit between a task’s/user’s needs and a specifictechnology/functionality. TTF argues that users adopt a technologybased on the fit between their task requirements and technologycharacteristics and how it can improve their performance (Gebauer& Ginsburg, 2009; Goodhue, 1995; Goodhue & Thompson, 1995).TTF has been widely used along with other technology adoptionmodels such as TAM and UTAUT to explain user’s adoption of atechnology (Dishaw & Strong, 1999; Yen, Wu, Cheng, & Huang,2010; Zhou, Lu, & Wang, 2010). By combining attitudes towarduse and the fit between user’s needs and a technology’s functional-ities through TAM and TTF respectively, we can provide a betterexplanation for technology adoption (Dishaw & Strong, 1999).
Previous research within the context of wireless technologyadoption has shown that the fit between characteristics of taskand technology along with perceived usefulness and perceivedease of use are direct determinants of user’s adoption of wirelesstechnology in organizations (Yen et al., 2010). TTF has also beenused in previous studies to explain the adoption of internet ser-vices (Shang, Chen, & Chen, 2007), location-based systems (LBS)(Junglas et al., 2008), mobile insurance (Lee, Lee, & Kim, 2007),Knowledge management systems (KMS) (Lin and Huang (2008)),mobile banking (Zhou et al., 2010).
User’s characteristics can also affect the task technology fit (Leeet al., 2007). Therefore, the adoption of a technology is the productof both task’s and technology’s characteristics which consequentlyinfluence user’s performance and actual utilization (Zhou et al.,2010). This implies that a rich task technology fit will encourageuser’s adoption of a technology while a poor task technology fitwill negatively influence users’ intention to adopt a technology(Lee et al., 2007; Lin & Huang, 2008; Zhou et al., 2010). However,TTF falls short when it comes to operationalization of ‘‘fit’’ concept(Gebauer & Ginsburg, 2009). In an effort to operationalize the con-cept of ‘‘fit’’ within the context of mobile technology, Gebauer andGinsburg (2009) identified five factors of fit for mobile IS (i.e. sup-port for voice communication, support for mobile office, supportfor knowledge work, productivity support and versatility, wirelessfeatures and stability). However, these factors are more associatedwith utilitarian use of the device and account neither for hedonicuse (enjoyment) nor for multifunctional use of the device.
This is the first study within the context of mobile devices thatdelves into the user’s and device functionalities’ fit by accounting
for hedonic aspect of mobile device use (perceived enjoyment) aswell as multifunctional use of the device based on user’s usagebehavior (user-perspective of multifunctionality) rather than mo-bile device’s hardware/software characteristics (device-perspec-tive of multifunctionality).
3. Research model and hypotheses
As discussed in the literature review section, hedonic aspect ofIS is an important factor in user’s acceptance and use of the tech-nology (Heijden, 2004). These findings propose that providing afun and enjoyable environment can favorably increase users’ per-ceptions toward adoption of a technology (Davis et al., 1992; Venk-atesh, 1999) and encourages the usage of innovative technologies,especially for mobile technology and services. The users who haveexperienced enjoyment from utilizing a technology demonstratepositive attitudes toward using that technology (Davis et al.,1992). Previous research has also found that perceived enjoymentis a positive determinant of perceived usefulness (Liaw, 2002; Liaw& Huang, 2003; Norman, 2002) and perceived ease of use (Sun &ZhanG, 2006; Venkatesh, 2000).
We should note that sometimes the boundary between utilitar-ian and hedonic systems is not very clear. This is particularly truefor mixed systems, which can be used for both hedonic and utili-tarian purposes (Sun & ZhanG, 2006). Multifunctional mobile de-vices are an instance of mixed systems that can be used for bothhedonic and utilitarian purposes. The enjoyment associated withusing mobile devices can affect the perceived ease of use and per-ceive usefulness of these devices. We also believe that the hedonicaspects of mobile device can create a perception of fit betweenuser’s hedonic needs and their device’s functionality. Therefore,we posit that:
H1a. Perceived Enjoyment positively influences Perceived Ease ofUse.
H1b. Perceived Enjoyment positively influences PerceivedUsefulness.
H1c. Perceived Enjoyment positively influences Perceived Func-tionality Fit of mobile device.
TAM and UTAUT models have been widely used to explain anddiscuss users’ acceptance and use of various technologies. Thesemodels propose that perceived usefulness and perceived ease ofuse are important determinants of adoption and use of a technol-ogy (Venkatesh et al., 2003; Verkasalo, López-Nicolás, Molina-Castillo, & Bouwman, 2010). Previous studies have found that thatfunctionality fit is also a determinant of perceived usefulness andease of use (Dishaw & Strong, 1999; Larsen, Sørebø, & Sørebø,2009). In our study, we argue that this is not a unidirectional rela-tionship. Perceived ease of use and perceived usefulness can alsoinfluence users perception of device functionality fit with theirneeds.
We build our argument upon the process of imbrication thatLeonardi (2011) discusses in his proposed framework of socio-technical adaptations for flexible technologies and routines. He ar-gues that individuals construct a perception of a technology thateither constrains or affords their ability to complete their routinesand achieve their goals. When individuals perceive a higher degreeof affordance in a technology that helps them complete their rou-tines, they may even change their behavior in order to imbricatethe technology into their routines (Leonardi, 2011).
Multifunctional mobile devices (such as Smartphones) are flex-ible technologies that enable the users to personalize the device
78 A. Negahban, C.-H. Chung / Computers in Human Behavior 35 (2014) 75–84
functionalities based on their needs. Mobile users are no longer lim-ited to the functions that the device manufacturers build into thedevice. There are a huge number of mobile applications (‘‘mobileapps’’) available to the users that enable them to add various func-tions to their mobile devices and customize them to achieve theirgoals. This turns mobile devices into multifunctional devices withflexible functionalities that users tailor based on their require-ments. If the users find their mobile devices useful, they tend toimbricate them into their tasks and routines. As the mobile deviceintegrates into the users routines, users tend to perceive a higherdegree of fit between the functionalities of device and their needs.Users may even change the way they performed certain routinesbecause they perceive a higher degree of affordance in the mobiledevice, which in turn leads to a higher degree of perceived fit be-tween their mobile device functionalities and their needs. For in-stance, a user that used to note down his shopping list on paperand refer to the list on paper while doing grocery shopping, maynow save the list in his mobile device and use the mobile device in-stead of the list on paper. As the user imbricates the mobile deviceinto various routines, he finds that the device more aligned with hisneeds. Thus, he perceives a higher degree of fit between his mobiledevice functionalities and his needs. We hypothesize that:
H2. Perceived Ease of Use positively influences Perceived Func-tionality Fit of mobile device.
H3. Perceived Usefulness positively influences Perceived Function-ality Fit of mobile device.
Multifunctional mobile devices help people manage daily activ-ities covering work, communication, and entertainment. Multi-functionality factor has a significant relationship with intentionto use of mobile technology (Lin et al., 2012). Multifunctionalityfactor played an important role to explain people how to evaluateand adopt a product (Sääksjärvi & Samiee, 2010). In other words, amultifunctional mobile device would facilitate the acceptance anduse of mobile technology.
Contextual factors are important predictors of adoption and useof mobile technology (Liu & Li, 2011). These factors can be associ-ated with location, situational and social contexts. Different func-tions may be preferred by users in different contexts, for instanceusers tend to play mobile games in situations in which they arebored, have nothing else to do, or want to kill time (Liu & Li,2011). Multifunctional devices can to be used in more situations
Fig. 1. Researc
and contexts compared to single function devices. As a result, theymay fit better with users’ needs in a larger variety of contexts. Webelieve exploring the multifunctionality factor could help us devel-op a comprehensive mobile device-functionality fit model. Thus,we hypothesize that:
H4. Multifunctional Use positively influences Perceived Function-ality Fit of mobile device.
Mobile devices allow people maintain their access to variousservices as well as keep being connected to other people while onthe move. Nowadays, symbolic value has become a vital factor foradoption and use of new mobile devices. For instance, iPhone fansmay purchase and use iPhone not necessarily because of its utilitar-ian functionalities but also because of the descriptive norms and thesocial image that owning an iPhone creates. According to the studyof Pagani (2004), personalization is an important perceived benefitof mobile services. Interactions among informal social groups influ-ence user’s opinions, decisions, and behavior (López-Nicolás et al.,2008). People adopted mobile technologies and services for eitherfunctional or nonfunctional reasons (Pedersen, 2005). Mobile tech-nology has been regarded as a symbol of social value and being up-to-date, which can subsequently urge users adopt and use a mobiledevice. Viewing symbolic value as a feature of mobile device allowsus to posit that the alignment between the perceived image createdby the device and the image the users intend to build for themselvesin the society can influence the degree of users’ perceived function-ality fit of the device. Thus, we posit that:
H5. Symbolic Value positively influences Perceived FunctionalityFit of mobile device.
Our proposed research model is shown in Fig. 1.
4. Methodology
In order to validate our research model, we developed a surveyinstrument. Survey method has been widely used in previous re-search to measure user’s intention to use, continuance of use,and satisfaction, as well as service and system quality within infor-mation systems discipline. The focus of our study is to identify fac-tors associated with user’s perceived device functionality fit. Weused student samples, which are widely used by previous studiesto investigate factors associated with adoption and use of mobiledevices (Liao et al., 2007; Negahban, 2012; Phan & Daim, 2011).
h model.
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4.1. Measurement
We adapted the items for perceived enjoyment, perceived easeof use, perceived usefulness, and symbolic value from prior re-search and modified them to fit the context mobile of our studyin order to increase the reliability and validity of our survey instru-ment. We developed the items for perceived device functionalityfit construct. To measure multifunctional use of the device, weasked the respondents to answer the frequency that they use cer-tain features of their Smartphone as a mobile device. We listed 16functionalities provided by Smartphones which were: voice call-ing, video calling, text messaging, instant messaging, checking(receiving) emails, sending emails, web browsing, playing music,watching video, playing games, checking social network sites, post-ing on social network sites, reading electronic documents, creating/editing electronic documents, online shopping, using specializedsoftware applications. For each of the functionalities, respondentsanswered how often they use that certain functionality rangingfrom Never to every time. The degree of multifunctional use ofthe device was then calculated based on the number of functional-ities that the respondents used frequently or more (scored greaterthan or equal to 5) and the mean of all the scores for various func-tionalities. All the survey items were measured using 7-point Likertscale. A copy of the survey instrument is included in Appendix A.
4.2. Data collection
Data were collected over a five-month period using an onlinesurvey. The respondents were undergraduate and graduate stu-dents in a southern university of the United States. The survey linkwas sent to about 600 students out of which 430 responses werecollected (71% response rate). After discarding 85 invalid/incom-plete responses and 9 outliers, 336 responses were used for dataanalysis. In terms of gender, 45% of respondents were male and55% were female. The respondents’ age ranged from 18 to 65 whileabout 80% of respondents were between 20 and 26 years old.
5. Data analysis and results
We used Partial Least Squares (PLS) to test our research modelusing Smart-PLS software. PLS is a preferred method for multi-itemconstructs and small sample sizes (Chin, 1998; Hulland, 1999). Inthis section, we test our model in a two-step process. First, we as-sess the measurement model (Outer model) in order to examinevalidity and reliability of our measurement instrument. Second,we evaluate the structural model (Inner model) estimates in orderto test the significance of our hypotheses and the predictive powerof our model.
5.1. Measurement model
We analyzed the reliability, validity, correlations, and factorloadings to assess our measurement model. We dropped out oneof the items associated with perceived ease of use because of itslow loading as well as high cross loading with another construct.
Table 1AVE’s and reliabilities.
AVE Composite reliability R-square Cronbach’s al
MFU 1 1 0 1PDFF 0.78 0.93 0.57 0.91PEOU 0.75 0.90 0.30 0.84ENJ 0.80 0.94 0.00 0.92PU 0.68 0.90 0.28 0.84SV 0.78 0.95 0.00 0.93
The results of our analysis showed that the composite reliabilitiesof all constructs were above 0.89, the Cronbach’s alpha for all con-structs were greater than 0.83, and they all loaded highly undertheir respective construct with more than 0.75, which are indicat-ing the reliability of our multi-item constructs (Hair, Ringle, &Sarstedt, 2011).
The AVE’s (Average Variance Extracted) for all constructs werethan 0.75. This is an evidence for convergent validity (Hair et al.,2011). Checking Fornell–Larcker criterion for our study, AVE’s forall constructs were greater than the square of their associated cor-relations, which satisfies the requirements for discriminant valid-ity (Fornell & Larcker, 1981). The result of confirmatory factoranalysis (CFA) also shows that all the items have the highest load-ing under their respective construct (see Table 2).
Table 1 presents the descriptive statistics, AVE’s, correlations,Cronbach’s alpha, composite reliability, and square root of AVE’s(bolded) for each of the constructs.
5.2. Structural model
In order to address common methods variance (CMV), we usedHarman’s one-factor test, which is one of the most widely usedtechniques to verify whether common (Podsakoff, MacKenzie,Lee, & Podsakoff, 2003). The basic assumption of this technique isthat if a substantial amount of common method variance is pres-ent, the non-rotated factor analysis solution will result in one gen-eral factor that accounts for the majority of covariance amongmeasures (Podsakoff et al., 2003). After conducting Harman’s sin-gle-factor test for our study a single dimension accounted for0.37 total of variance explained which indicates that commonmethod bias is not problematic in our study.
Checking for multicollinearity, we computed VIF’s (VarianceInflation Factor) for different constructs in our model and we foundthat all the VIF’s were less than 3, which suggests that multicollin-earity is not a major issue in our study (Hair et al., 2011).
The result of the path analysis with a bootstrap sample numberof 5000 shows that all of our hypotheses, except H4, are supportedat 0.05 confidence interval. Fig. 2 summarizes the results of pathanalysis for our proposed model. The R-Square for perceived useful-ness and perceived ease of use constructs were 28% and 30% respec-tively, which shows that perceived enjoyment can explain aboutone-third of variance in these constructs. This also confirms thathedonic and utilitarian aspects of these devices affect each other.The resulted R-Square for perceived device functionality fit as thedependent construct was 0.57, which indicates that perceivedenjoyment, perceived ease of use, perceived usefulness, and symbolicvalue of mobile device can explain 57% of variance in perceived de-vice functionality fit of the mobile device.
6. Discussion
Our paper contributes to the IS literature by introducing theconcept of perceived device-functionality fit. We intended to iden-tify factors associated with individual’s perception of the extent towhich their mobile device meets their needs and requirements.
pha MFU PDFF PEOU ENJ PU SV
10.22 0.880.19 0.69 0.870.25 0.56 0.55 0.900.22 0.59 0.53 0.53 0.830.21 0.20 0.05 0.30 0.21 0.88
Table 2PLS loadings.
Construct Items Mean Std. dev ENJ PDFF PEOU PU SV MFU
Perceived enjoyment ENJ1 5.79 1.11 0.88 0.43 0.42 0.43 0.31 0.21ENJ2 6.14 0.94 0.93 0.53 0.54 0.48 0.24 0.25ENJ3 5.68 1.15 0.89 0.51 0.49 0.48 0.26 0.23ENJ4 6.18 0.89 0.89 0.52 0.51 0.50 0.26 0.19
Perceived device functionality fit PDFF1 6.24 0.92 0.49 0.89 0.62 0.54 0.25 0.26PDFF2 6.02 1.13 0.41 0.87 0.56 0.44 0.13 0.15PDFF3 6.24 0.92 0.54 0.86 0.64 0.60 0.11 0.19PDFF4 6.13 1.04 0.52 0.90 0.61 0.49 0.21 0.18
Perceived ease of use PEOU1 6.28 0.95 0.49 0.64 0.92 0.44 0.05 0.17PEOU3 5.92 1.20 0.34 0.43 0.75 0.37 �0.01 0.14PEOU4 6.25 0.83 0.57 0.68 0.93 0.54 0.07 0.18
Perceived usefulness PU1 6.00 1.10 0.49 0.49 0.43 0.85 0.23 0.22PU2 5.73 1.39 0.35 0.40 0.29 0.76 0.15 0.15PU3 6.53 0.71 0.45 0.51 0.50 0.82 0.16 0.17PU4 6.25 0.91 0.44 0.54 0.48 0.87 0.15 0.18
Symbolic value SV1 4.84 1.61 0.30 0.20 0.10 0.21 0.83 0.18SV2 4.83 1.65 0.32 0.17 0.06 0.19 0.89 0.18SV3 4.30 1.60 0.20 0.15 �0.01 0.20 0.89 0.15SV4 4.23 1.58 0.22 0.17 0.04 0.18 0.90 0.22SV5 4.37 1.64 0.25 0.16 0.00 0.14 0.89 0.19
Multifunctional use MFU 9.08 3.75 0.25 0.22 0.19 0.22 0.21 1.00
Fig. 2. Path analysis results.
80 A. Negahban, C.-H. Chung / Computers in Human Behavior 35 (2014) 75–84
The result of our study shows that about 60% of the variance inindividuals’ perceived device-functionality fit can be explained byfour factors: perceived enjoyment, perceived ease of use, perceivedusefulness, and symbolic value of the device. Among the four fac-tors, perceived ease of use and perceived usefulness are the mostsignificant and according to their coefficients, the effect of a spe-cific degree of change in individuals’ perceived ease of use on indi-viduals’ perceived device-functionality fit is twofold that ofperceived usefulness. One justification for this may be due to thefact that if individual’s cannot easily use their mobile device, theywill not be able to benefit from many functionalities that their mo-bile device provides them with, and this includes those featuresthat address part of their expectations and needs. Thus, low de-grees of perceived ease of use can significantly decrease the fit be-tween the device functionalities and the user’s requirements.
Perceived enjoyment is a significant predictor of perceived easeof use and perceived usefulness, explaining about 30% of variancein each of these constructs. This confirms the results of previous re-search and suggests that perceived enjoyment is affecting users’perceived usefulness and perceived ease of use in the context ofmultifunctional mobile devices. It also confirms that for mixed sys-
tems (i.e. systems that can be used for both hedonic and utilitarianpurposes), the boundary between utilitarian and hedonic use areblurry and the hedonic and utilitarian aspects affect each other.
Perceived enjoyment and symbolic value are also significantpredictors of perceived device-functionality fit with less signifi-cance compared to perceived ease of use and perceived usefulness.The effect of a single unit change in individuals’ perceived enjoy-ment on their perceived device-functionality fit is slightly morethan half of that of perceived usefulness and slightly less thantwice of that of symbolic value. This implies that when it comesto individual’s perception of the fit between functionalities of thedevice and their needs, perceived ease of use is the most importantfactor for the device to fit the user’s needs. This may be becausemobile devices are not purely used for utilitarian purposes. Onone hand, the mobility aspect of mobile devices along with theirversatility in terms of its functionalities allows users to use thesedevices for hedonic purposes. As the result of our study implies,part of the fit between the user’s needs and the device’s function-alities is associated with the perceived enjoyment. On the otherhand, the ubiquitous nature of the mobile devices can also shapepart of individual’s image among their peers or the people around
A. Negahban, C.-H. Chung / Computers in Human Behavior 35 (2014) 75–84 81
them. As a result, individuals may perceive mobile devices as aconstituent of their social status and try to use a device that isaligned with the social image they expect from themselves. Thisforms part of their expectations and needs from their mobile de-vice. The results of our study also confirm this by showing thatsymbolic value of the device is an antecedent of individuals’ per-ceived device-functionality fit.
Our study has several implications for both practitioners andresearchers. In terms of the theoretical contribution, our researchintroduces the concept of perceived device-functionality fit for mo-bile devices by accounting for both hedonic and utilitarian aspectsof these devices. Previous studies mainly focused on the concept oftask and technology from the utilitarian perspective. However, mo-bile devices combine both utilitarian and hedonic aspects in onedevice. We also suggested that the multifunctionality of mobile de-vices is not just an artifact of their hardware and software support.That is why we introduced the concept of multifunctional use bymeasuring usage patterns of different mobile device functionalitiesby their users. We suggested that these patterns vary from personto person which can create different levels of multifunctional useof mobile device per every single user.
In terms of practical implications, our study shows that in orderto manufacture mobile devices that fit best with the users require-ments, mobile device manufacturers should not only focus onenhancing the hardware and software specifications of their mo-bile devices. Our study shows that ease of use, enjoyment, andsymbolic value of the device are key factors that affect users’ per-ceptions of the degree to which the device addresses their needs.Mobile phone manufacturers need to pay special attention to thelook-and-feel aspects of their productions such as the user inter-face of their mobile devices, as well as the image their brand con-veys to their product users. This confirms the recent trends inSmartphone market, which shows that although Smartphones pro-duced by companies such as HTC and Samsung have higher hard-ware and software configurations compared to iPhone by Applecompany, but still iPhone enjoys a larger growth in sales. The rea-son may be because iPhone has established a higher symbolic va-lue in the society and many people perceive it as a symbol ofsocial status as well as it is providing a friendlier and an easier-to-use user interface to its users.
7. Limitations and future research
In this section, we discuss the limitations we that may impactthe results of our study and what the research questions future re-search can address to provide a more comprehensive understand-ing of perceived device functionality fit.
The first limitation of our research concerns with the generaliz-ability of our findings. Our samples were limited to undergraduateand graduate students, mainly aged between 20 and 26. Althoughstudent samples have widely been used previous research, the ex-tents to which they represent the general public have always beena question. We can argue that the young generation may have lowerresistance toward adopting new technologies. They are also moreconfident and efficient in using the various features mobile devicesprovided. Thus, they may perceive a higher level of ease of use andenjoyment using their mobile devices. Moreover, their perceptionof symbolic value may not only be limited to their image andhow important they look if using the mobile device. The youthmay also consider the extent to which using the device is a hip ortrendy among their peers. These may slightly skew the results ofour study. Future study can investigate how age and generationaldifferences may affect individual’s perception of ease of use, enjoy-ment, symbolic value and multifunctionality of mobile devices.
The second limitation of this study is associated with the oper-ationalization of mobile device. In our study, we focused on Smart-phones as multifunctional mobile devices. However, there areother multifunctional mobile devices such as tablets and notebookcomputers. We need to study if there are significant differences be-tween these devices in terms of the degree their functionalities fitindividual’s needs.
Finally, many features in mobile devices are dependent oninternet access as well as the quality of service provided by mobileservice carriers. Whether the user has mobile internet serviceavailable and the quality of that service can affect users’ perceivedusefulness of their mobile device, which based on the results of ourstudy, is the most significant predictor for individual’s perceiveddevice functionality fit. Future research can study the impact ofmobile carrier’s service quality on the perceived usefulness of mo-bile devices.
We also believe that we need to investigate how individual’smultifunctional use of mobile device can influence the fit betweendevice functionality and user’s requirements. We believe that asdevices become more mobile and versatile as well as more person-alizable in terms of allowing users to add various mobile applica-tions to their mobile devices, the better they fit with the users’expectations and needs. However, future research needs to developvalid and reliable scales for measuring multifunctional use of mo-bile (or even non-mobile) devices and test its impact of users’ de-vice-functionality fit.
Previous research have found technology-fit to be a significantpredictor of technology adoption and use (Dishaw & Strong,1999; Larsen et al., 2009; Lin, 2012). In our study, we focused onthe antecedents of users’ perception of fit between their needsand functionalities of their mobile devices. Future research caninvestigate the mediating effect of perceived functionality fit anduser’s adoption and use of mobile devices.
8. Conclusion
In recent years, there has been a sharp increase in the use of mo-bile devices. The ubiquitous and multifunctional nature of these de-vices provides their users with versatile functionalities, omnipresentinternet connectivity, and personalization features. This raises thequestion that what factors shape mobile users perception of theirmobile device functionality fit with their needs. In order to answerthis question, we proposed a research model incorporating four con-structs from technology adoption and use literature (perceivedenjoyment, perceived ease of use, perceived usefulness, and sym-bolic value) and introducing multifunctional use and perceived de-vice-functionality fit as two new constructs in our model. Thedegree of multifunctional use of mobile device measures user’s fre-quency of use of various functionalities of his/her mobile device.The perceived device-functionality fit measures the degree to whichfunctionalities of mobile device fits with user’s needs.
The results of our study shows that more than half of the vari-ance in individuals’ perceived device-functionality fit can be ex-plained by their perceived enjoyment, perceived ease of use,perceived usefulness, and symbolic value of the device. This hasseveral implications for both practitioners and researchers. Interms of the theoretical contribution, our research introduces theneed to revamp the concept of device-functionality fit when itcomes to mobile devices by accounting for both hedonic and util-itarian aspects. In terms of practical implications, our study high-lights the importance of brand equity for mobile devicemanufacturers and the image their productions create in the soci-ety as well as the importance of look-and-feel aspects mobile de-vices in shaping users perception of fit between functionalitiesprovided by their mobile device with their needs.
82 A. Negahban, C.-H. Chung / Computers in Human Behavior 35 (2014) 75–84
Appendix A. Survey items
We asked the respondents to answer the following questions for their Smartphones.
Construct and its anchors
ItemsPerceived Enjoyment (ENJ) (Strongly disagree, disagree, somewhatdisagree, neither agree nor disagree, somewhat agree, agree, stronglyagree)
ENJ1.
Using the device makes me feel good ENJ2. Using the device is enjoyable ENJ3. Using the device gives me a lot of joy ENJ4. I enjoy using the devicePerceived Ease of Use (PEOU) (Strongly disagree, disagree, somewhatdisagree, neither agree nor disagree, somewhat agree, agree, stronglyagree)
PEOU1.
The device is easy to use PEOU2. Using the device is frustrating. (DROPPED) PEOU3. Using the device does not require a lot ofeffort
PEOU4. It is easy for me to use this devicePerceived Usefulness (PU) (Strongly disagree, disagree, somewhat PU1.
disagree, neither agree nor disagree, somewhat agree, agree, stronglyagree)Using the device enhances myeffectiveness
PU2.
Using the device enhances myproductivityPU3.
I find the device useful in my daily life PU4. The device helps me accomplish thingsthat I want
Symbolic Value (SV) (Strongly disagree, disagree, somewhat disagree,neither agree nor disagree, somewhat agree, agree, strongly agree)
SV1.
Using the device enhances my image SV2. Using the device is a sign of status SV3. Using the device makes me look moreimportant
SV4. People who use the device have a highprofile
SV5. Using the device gives me a high profileamong my peers
Perceived Device-Functionally Fit (PDFF) (Strongly disagree, disagree, PDFF1.
somewhat disagree, neither agree nor disagree, somewhat agree,agree, strongly agree)The functionality of the device meets myneeds
PDFF2.
The device has all the functionality that Ifind necessaryPDFF3.
The functionality of the device is adequatefor accomplishing my everyday tasksPDFF4.
I am satisfied with the functionality of thedevice
Multifunctional Use (MFU) (Never, rarely, occasionally, sometimes,frequently, often, every time)
How often do you use your Smartphone for ____?
Voice calling Playing games Video calling Checking social network sites TextmessagingPosting on social network sites
Instantmessaging
Reading electronic documents
Checking/receivingemails
Creating/ editing electronic documents
Sendingemails
Online shopping
Webbrowsing
Using specialized software forprogramming, statistics, graphics design,etc.
Playing music
Watchingvideo
A. Negahban, C.-H. Chung / Computers in Human Behavior 35 (2014) 75–84 83
Do you own a Smartphone? r Yes s No.Do you regularly use a Smartphone? r Yes s No.Gender: r Female s Male.Age: r 18–23 s 24–29 t 30–35 u 36–41 v 42–47 w Morethan 48.Education:
r Undergraduate students Masters studentt PhD studentu Certificate/non-degree program studentv Other
How long have you been using a Smartphone?r More than 6 years s 3–6 years t 1–3 years u Less than1 year v Never before.
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