A0350107

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A0350107

  1. 1. IOSR Journal of Computer Engineering (IOSRJCE)ISSN: 2278-0661 Volume 3, Issue 5 (July-Aug. 2012), PP 01-07www.iosrjournals.org Factors Influencing M-Commerce Transaction Satisfaction and Impact of Trust towards M-commerce Service Providers Avdhesh Gupta1, Dr. C.K.Jha2, Arvind Kumar Shukla3 1 Assistant Professor, College of Engineering Roorkee 2 Associate Professor, Banasthali University,Rajasthan 3 Associate Professor, IFTM University, MoradabadAbstract: The objective of this study is to provide the factors influencing satisfaction of B2C operations andtrust towards m-commerce service providers. The sample size consists of 200 respondents. The results analysisshows that customer satisfaction towards the vendor was significantly influenced by ease-of-use,responsiveness, and brand image. The customer trust towards the vendor in m-commerce is affected byresponsiveness, brand image and satisfaction towards the vendor in m-commerce. Based on the analysis, m-commerce service providers should focus on those factors, which can provide more satisfaction and trust fromthe customers. For m-commerce service providers, the results enable them to better develop the trust in m-commerce customers.Keywords: m-commerce, TAM, B2C, m-commerce service providers, trust I. Introductions The E-Commerce, or the buying and selling of goods and services on the Internet, has become a part ofdaily life for many people. As the Internet expands to every corner of the globe, it is becoming easier and easierto access it from a wide variety of devices. E-Commerce over mobile devices has now been termed Mobile-Commerce (M-Commerce). The M-Commerce by definition is the E-Commerce that is implemented usingwireless solutions such as cell phones, pocket PCs, and PDAs. It allows a user to purchase goods and serviceson the move, anytime, and anywhere. Mobile commerce, or e-commerce over mobile devices, has become amajor topic of interest for the IS research community and a key priority for many business organizations as it isbecoming increasingly evident that PC-based e-commerce has not lived up to the expectations and achievedtrue mass adoption (Ropers, 2001). One of the most recent and significant changes in the business environmenthas been the growing demand for mobility. This means that customers, partners and employees should be ableto access information resources and services of a company wherever and whenever they want (Steendern,2002). Recent research has identified trust as a research issue in both e- and m-commerce (Hsu & Lu, 2005;Hsu, Lu, & Hsu, 2007; Lai, 2004; Siau & Shen, 2003). Other recent studies examined a variety of topicsincluding the impact of satisfaction on loyalty in m-commerce (Lin & Wang, 2006), factors affectingsatisfaction in m- commerce (Choi, Seol, Lee, Cho, & Park, 2008) and the effect of culture on satisfaction (Cyr,Kindra, & Dash, 2008). It is relevant to the studies, Li and Yeh (2009) found that the level of satisfaction is akey determinant of gaining customer trust in m-commerce. Hence, this study aims to provide an explanation onthe factors that build customer trust towards m-commerce service providers. II. Literature Reviewed Wang and Liao (2007) included the construct of service quality as one of the dimensionsaffecting customer satisfaction in m-commerce. Feng, Hoegler, and Stucky (2006) suggested that m-commerceis more than e-commerce due to its different interaction style, usage pattern and value chain. Feng et al. (2006)stated that m- commerce is a new and innovative business opportunity with its own unique characteristics andfunctions, such as mobility and broad reach ability. Tiwari and Buse (2007) stated that m- commerce is anintegral subset of m-business since the services provided by m-business covered both commercial and non-commercial areas. Lai (2006) extended with perceived value and examined customer satisfaction in a mobilecommunication context. When performance is worse than expected, a low level of satisfaction occurs becauseof negative disconfirmation. When customers make transactions with the vendor, they may have differentreactions towards the transaction, thus affecting overall satisfaction (Spreng et al., 1996). Wang and Liao(2007) developed a four-dimensional measurement of satisfaction for users of m-commerce. Though customersatisfaction is different from customer acceptance, in some researches on success of e-commerce, measuringintent to adopt e-commerce was also proposed as a method to evaluate the success of e-commerce indirectly as www.iosrjournals.org 1 | Page
  2. 2. Factors Influencing M-Commerce Transaction Satisfaction and Impact of Trust towards M-well as customer satisfaction. In addition, customer acceptance leads customers to use m-Internet or m-commerce, and then customer satisfaction is built (Lee et al., 2007). Lee (2005) stressed the importance of responsiveness in leading to trust in m-commerce. According toSiau and Shen (2003) trust in m-commerce (m-trust) can be divided into two categories: trust in mobiletechnology and trust in mobile m-commerce service providers. Lee and Benbasat (2003) and Chae and Kim(2003) agreed that limited system resources (e.g. smaller screens and lower multimedia processing capabilities)can hinder the development of trust in m-commerce. Recent research has examined aspects of interface design such as the impact of task-relevant cues onshoppers‟ emotional and cognitive states, as well as their resultant behavior (Eroglu, Machleit, & Davis, 2003).Similarly, Park and Kim (2003) explored the effects of factors including interface quality and perceptions ofsecurity on outcomes like commitment to a web site and actual purchase behavior.. Mobile business applications that involve interactivity and customization provide new opportunitiesfor expansion and enhancement of markets. These two factors interact to influence customers‟ perceptions ofsatisfaction during the use of mobile technology (Liang and Wei, 2004). Lee (2005) argued that the interactivityis an influential source of trust. Interactivity and customization interact to influence customers‟ perceptionsof satisfaction during the use of mobile technology (Liang & Wei, 2004). Lee and Benbasat (2003) definedcustomization as a tailoring ability enhanced by users‟ mobile setting. Venkatesh et al. (2003) further suggestedthat customization‟s impact can be extended to enhance the mobile interface design and to improve mobileusability, thus raising the level of satisfaction. Accordingly, the study hypothesizes that: Usefulness and ease-of-use are the two vital elements in the Technology Acceptance Model (TAM)(Davis, 1989). In TAM the behavioral intention to use is jointly influenced by attitude and usefulness, wherethe latter directly affects the former. Information science and information technology has shown that these twofactors influence individuals‟ attitudes towards using the system. They were shown to be closely related to theacceptance of computer technologies and are of great importance for new users. Based on a review of empiricalevidence, usefulness and ease- of-use may positively affect satisfaction. Responsiveness can specifically represent an e-retailer‟s commitment to providing rapid feedback(Dholakia et al., 2000) or generally refer to being responsive to the service subscribers. Its recent applicationscan be found in different areas of e-commerce such as web-based services (Kuo, 2003), internet retailing(Barnes and Vidgen, 2001) and electronic banking. Previous studies suggest responsiveness is critical not onlyas a measure of service quality but also as a diagnostic tool for uncovering areas of service quality strengths andshortfalls. A high level of responsiveness, representing a trust cue, can convey the trustworthiness of the vendorin m-commerce to customers. Another possible source of vendor quality, brand image is more than a name given to a product. It canbe broken down into a whole set of physical and socio-psychological attributes and beliefs (Simoes and Dibb,2001), all of which affect customers‟ perceptions of the brand and the meaning they attribute to it.These two attributes can be formed from customers‟ own experience with the brand or through the imageportrayed via marketing channels (O‟Cass and Grace, 2004). In addition, Berry (2000) found that a strongbrand image increases customer trust and becomes a surrogate especially when the service is intangible. Based on Casalo´ et al.(2008) satisfaction refers to an affective consumer condition that result from aglobal evaluation of all the aspects that make up the consumer relationship. According to Geyskens et al. (1999)satisfaction can be raised by economic conditions (e.g. monetary benefits) or psychological factors (e.g.promise fulfillment or ease of relationships with retailers). Consequently, the consumers‟ post-trust level isaffected directly by the level of satisfaction. Past research has suggested that customer satisfaction is theantecedent of trust. Recent studies have validated the positive effect of satisfaction on trust in the e-commerceenvironment. III. Methodology The questionnaire is prepared using „Gmail‟ online service, and then the questionnaire was distributedto users of m-commerce. It took a month to complete the data collection. The scale items for web site quality(i.e. interactivity and customization) were adapted from Lee (2005) and Ribbink et al. (2004). The scale itemsfor mobile technology quality (i.e. usefulness and ease-of-use) were taken from Davis (1989). Items for vendorquality (i.e. responsiveness and brand image) were adapted from Parasuraman et al. (1991) and Hsieh and Li(2008). The constructs for satisfaction and trust were adapted from Lin and Wang (2006), Hsu et al. (2007) andHeijden et al. (2003). The questionnaires were constructed in five-point Likert scale where it ranges from 1(strongly disagree) to 5 (strongly agree). Data were analyzed using multiple regression analysis via theStatistical Package for Social Sciences (SPSS) version 16 computer program, when the focus is on therelationship between a dependent variable with one or more independent variables.H01. Interactivity affects satisfaction towards the vendor in m-commerce.H02. Interactivity affects trust towards the vendor in m-commerce.H03. Customization affects satisfaction towards the vendor in m-commerce. www.iosrjournals.org 2 | Page
  3. 3. Factors Influencing M-Commerce Transaction Satisfaction and Impact of Trust towards M-H04. Customization affects trust towards the vendor in m-commerce.H05. Usefulness affects satisfaction towards the vendor in m-commerce.H06. Ease-of-use affects satisfaction towards the vendor in m-commerce.H07. Responsiveness affects satisfaction towards the vendor in m-commerce.H08. Responsiveness affects trust towards the vendor in m-commerce.H09. Brand image affects satisfaction towards the vendor in m-commerce.H10. Brand image affects trust towards the vendor in m-commerce.H11. Satisfaction affects trust towards the vendor in m-commerce. IV. Analysis & Interpretation Table 1 summarizes the demographic profile of the sample collected. According to the table, therewere 200 customers, who had participated in the survey with 82 of them, are males and 118 are females. As 88percent of the customers which consist of 176 of them are between the age of 19-23 and the remaining 12percent of the customers which consist of 24 of them are from the age between 21-24 years. The data has 196respondents are undergraduate and 4 of them are Masters Degree. Other relevant information provided is thetype of wireless handheld equipment which is a cell phone, PDA phone and Smart phone. Table 1: Demographic Profile of Respondents Variable Frequency Percent Gender Male 82 41.0 Female 118 59.0 Age 19-23 176 88.0 24-28 24 12.0 Highest Education Level Undergraduate 196 98.0 Masters 4 2.0 Wireless Handheld Equipment Cell Phone 156 78.0 Type PDA Phone 32 16.0 Smart Phone 12 6.0 Number of M-Commerce 1-3 58 29.0 Experience 4-6 66 33.0 >7 76 38.0 In order to avoid redundancy, the data have been summarized into the number of m-commerceexperiences. Respondents were given 15 choices which are SMS, buy ticket, video calls, MMS, mobilepayment, ring tone, news, banking service, local map, email, weather forecast, wallpaper/screensaver, games,browsing the Internet and local information. The survey shows that, 29 percent have experienced 1-3 types ofm-commerce experiences, 33 percent have experienced 4-6 types, and 38 percent have experienced more than 7types of m-commerce.Reliability Analysis The research instrument was tested for reliability using Cronbach‟s coefficient alpha estimate. Thedegree of consistency of a measure is referred to as its reliability or internal consistency. A valueof 0.70 or greater is deemed to be indicative of good scale reliability (Hair, Black, Babin, Anderson, & Tatham,2010). The Cronbach‟s alpha for the five factors range from 0.816 to 0.937, suggesting that the constructsmeasures are deemed reliable. (Table 2). Table 2: Reliability Test Variable No of item Cronbach’s Alpha Interactivity 3 0.873 Customization 3 0.834 Responsiveness 3 0.816 Brand image 3 0.871 Satisfaction 3 0.905 Trust 3 0.841 Easy-of-use 3 0.893 Usefulness 2 0.937 www.iosrjournals.org 3 | Page
  4. 4. Factors Influencing M-Commerce Transaction Satisfaction and Impact of Trust towards M- Table 3: Correlation between the Factors 1 2 3 4 5 6 7 8 (1) Interactivity 1 (2) .615(**) 1 Customization (3) .561(**) .687(**) 1 Responsiveness .514(**) .558(**) .485(**) 1 (4) Brand image (5) Satisfaction .483(**) .594(**) .618(**) .631(**) 1 (6) Trust .530(**) .665(**) .638(**) .706(**) .759(**) 1 (7) Easy-of-use .340(**) .426(**) .373(**) .469(**) .549(**) .541(**) 1 (8) Usefulness .379(**) .425(**) .361(**) .468(**) .516(**) .562(**) .742(**) 1 Mean 3.270 3.287 3.113 3.240 3.185 3.287 3.373 3.380 Std. Deviation 0.828 0.894 0.893 0.764 0.884 0.789 0.861 0.836 Skewness -0.497 -0.573 -0.081 -0.726 -0.443 -0.616 -0.614 - Kurtosis 0.640 0.345 0.135 1.375 0.502 0.711 0.706 0.122 0.326Correlation Analysis The interrelationships between the seven variable measurements were examined throughcorrelation analyses. According to Simon (2008), correlation values at +0.01 and** Correlation is significant at the 0.01 level (2-tailed). above are significant but shows little association, values that are above +0.3 and are lesser than +0.7depicts weak positive association while values above +0.7 to +1.0 shows strong positive association.Table 3 describes that all of the Pearson‟s correlations between the variables are positively significant at 0.01level. The usefulness had the highest mean of 3.380 whereas the customization had the highest standarddeviation of 0.894. The skewness of all the items ranges from -0.081 to -0.726 below ±2.0. Similarly, the valuesfor kurtosis ranges from 0.135 to 1.375 well below the threshold of ±10. Both the skewness and kurtosis arelow for the most part, indicating that the scores approximate a “normal distribution” or “bell-shaped curve”.Multiple Regression Analysis To further testing the hypotheses of this study, multiple regression analysis was performed. Theanalysis revealed that the model significantly predicted a sizable proportion of variance in users‟ satisfactiontowards the vendor, F (3, 196) = 45.019, p<0.05. R2 for the model was 0.583, and adjusted R2 was 0.570.Table 4 displays the standardized regression coefficients (β), and t statistics for each variable. The level ofsignificance (α) was set at 0.05. Hypotheses 1, 3 and 5 postulate the associations between satisfaction towardsthe vendor in m-commerce and three antecedents of vendor‟s website quality: interactivity, customization andusefulness. As evident in Table 4, users‟ satisfaction towards the vendor in m-commerce is not significantlyinfluenced by usefulness (β5 = 0.081), interactivity (β1 = 0.001) and customization (β3 = 0.104). Hence, theproposed hypotheses are not supported, p>0.05. Table 4: Relationship between Independent Variables and Satisfaction towards the Vendor in M- commerce Variable Standardized beta t-value Interactivity 0.001 -0.721 Customization 0.104 0.018 Responsiveness 0.300 1.444* Brand image 0.299 4.511* Easy-of-use 0.192 4.873* Usefulness 0.081 2.691 F 45.019 R² 0.583 Adjusted R² 0.570 Standard Error .57974 *p< 0.05 Hypothesis 6, 7 and 9 explicate the associations between users‟ satisfaction towards the vendor in m-commerce and three antecedents of vendor‟s website quality: ease-of-use, responsiveness, and brand image. www.iosrjournals.org 4 | Page
  5. 5. Factors Influencing M-Commerce Transaction Satisfaction and Impact of Trust towards M-This study asserts that users‟ satisfaction towards the vendor in m-commerce includes three dimensions: ease-of-use, responsiveness, and brand image. Table 4 depicts that users‟ satisfaction towards the vendor in m-commerce is significantly influenced by ease-of-use, responsiveness, and brand image (β6 = 0.192, β7 = 0.300,β9 = 0.299, p<0.05). As a result, the hypotheses are supported. 58.3 percent of variance in users‟ satisfactiontowards the vendor in m-commerce is explained by the interactivity, customization, usefulness, ease-of-use,responsiveness, and brand image. Hypothesis 2 and 4 explains the impacts of interactivity and customization on trust towards the vendorin m-commerce. Results in Table 5 indicate that there is a statistical significant influence betweencustomization and trust towards the vendor in m-commerce (β4 = 0.175, p<0.05), demonstrating supportfor H4. However, hypothesis H2 is not satisfactorily demonstrated, confirming that there is no relationshipbetween interactivity and trust towards the vendor in m- commerce (β2 = 0.012, p>0.05). Hypothesis 2 and 4explicate the associations between responsiveness, brand image and satisfaction on users‟ trust towards thevendor in m-commerce. This study asserts that responsiveness (β8 = 0.131), brand image (β10 = 0.299) andsatisfaction (β11 = 0.379) significantly influences trust towards the vendor in m-commerce, supporting H8,H10, H11. Accordingly, 70.5 percent of the variance in trust towards the vendor in m-commerce is explained bythese five antecedents, indicating that the explanatory power of the model may be considered satisfactory andthat the model fits the data and is appropriate to test the hypotheses. Table 5: Relationship between Independent Variables and Trust towards the Vendor in M- commerce Variable Standardized beta t-value Interactivity 0.012 0.238 Customization 0.175 2.889* Responsiveness 0.131 2.243* Brand image 0.299 5.571* Satisfaction 0.379 6.614* F 92.867 R² 0.705 Adjusted R² 0.698 Standard Error .43401 V. Conclusion This research examines the factors that influence B2C m-commerce satisfaction and trust towards them-commerce service providers. This study confirms that customer satisfaction towards the m-commerce serviceproviders was significantly influenced by ease-of-use, responsiveness, and brand image. M-commerceapplications on B2C operations have trust towards the m-commerce service providers and it is affected byvendor‟s website quality elements such as responsiveness, brand image and satisfaction towards thevendor. Reminiscent of previous findings (Lee, 2005; Corritore et al., 2003) the results indicated thatresponsiveness did directly lead to trust development. This may be because m-commerce customers were moreconcerned with vendor service honesty or responsiveness. As in the studies by Liang and Wei (2004), Berry(2000), web site and vendor quality influenced customer satisfaction. Surprisingly, customers‟ satisfaction andtrust towards the vendor in m-commerce is not significantly influenced by the vendor‟s website quality in termsof interactivity. Vendor quality such as responsiveness and brand image does influence customers‟ satisfactionand trust towards the vendor in m-commerce. The findings also reveal that ease of use is the only mobile technology quality factor that influencetrust towards the vendor in m-commerce. Customers should be satisfied with the product or services they use inorder to gain trust on it. In this case, customers should be satisfied with m-commerce service experiences sothat they would have trusted to use the services without hesitation and remain loyal to it. Moreover, this studyhas validated the determinants of satisfaction and trust, leading the way for a detailed exploration of how toimprove customer satisfaction and trust towards the vendor in m-commerce. Despite the useful findings of thisstudy, this empirical study has several limitations that need to be acknowledged. Several factors wereexamined in this study. Future studies should attempt to draw profiles based on characteristics other than thesefactors. Next, the data were collected from a convenience sample of 200 respondents, from „Gmail‟ onlinequestionnaire. The snowball sampling approach has been used to find out the real users of m-commerce, sinceusage of m-commerce is still in the nascent stage in India. The questionnaire has been filled by the users, who isinvolved in m-commerce transaction or have shifted from manual and e-commerce activities to m-commerceactivities. However, a deliberate effort has been made to bring randomness in the sample chosen by selectingthe respondents based on random sampling from the list of m-commerce users made with the help of snowballsampling. www.iosrjournals.org 5 | Page
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