Attitude Influencers in c2c E-commerce. Buying and Selling. - Leonard

Spring 2012 Journal of Computer Information Systems 11

ATTITUDE INFLUENCERS IN C2CE-COMMERCE: BUYING AND SELLING

LORI N. K. LEONARDUniversity of TulsaTulsa, OK 74104

Received: April 4, 2011 Revised: September 26, 2011 Accepted: October 15, 2011

ABSTRACT

C2C e-commerce is a growing area for interactions, and ultimately, transactions. However, very little is known about buyers and sellers in these transactions. This study examines the risk and trust of buyers and sellers by developing two attitudinal models — attitude towards purchasing (for buyers) and attitude towards selling (for sellers). Collecting 248 survey responses from undergraduate students, the results indicate that both trust of the seller and risk of the seller influence the buyer’s attitude towards purchasing, but the model changes for seller’s attitude towards selling, trust and attitude are combined into one variable and risk is not found to be an influence. A discussion of the implications of these findings is provided along with conclusions. Keywords: C2C, electronic commerce, trust, risk, attitude

INTRODUCTION

Consumers that use the web have a ‘wired lifestyle’ and are starved for time [2]. Therefore, they seek new ways to interact, and transact, where their ‘wired lifestyle’ can be utilized. The time consumers spend online influences the amount of money they spend online [14]. Additionally, participation in online auctions influences the amount consumers spend online [14]. Online auctions are one medium for consumer-to-consumer electronic commerce (C2C e-commerce). C2C e-commerce opens the realm to developing new relationships and forming new interactions. These interactions do not have to occur through the traditional online C2C auctions, but can occur in other settings such as discussion forums and chat rooms, with some of those interactions ultimately leading to transactions. Therefore, the interactions and relationships are crucial to C2C e-commerce success [4]. When consumers interact online, they share ideas, but more importantly, they have interpersonal exchange [9]. While many individuals have good intentions when interacting, fraudulent activity occurs every day on the Internet. In fact, a significant amount of fraudulent activity has been found to occur in online auctions [10]. This leads one to wonder about the risk and trust perceived in C2C e-commerce. The lack of trust between businesses and consumers is nothing new [16], yet whether this trust absence transfers over to C2C transactions is yet to be seen. Trust has been examined for online commercial transactions with regards to the seller-buyer relationship [30]. However, that research assessed the importance of trust constructs (institutional, calculative, and relational) only in the seller-buyer relationship and did not focus on the C2C e-commerce realm. Seller and buyer factors in an e-marketplace have also been studied, with customers

(buyers) being found to value trust in the sellers differentially based on the level of buyer experience [21]. Seller expertise plays a key role in buyer trust of the seller and the e-market [21]. Additionally, the buyer’s perspective in C2C online auctions has been studied and found to be influenced by many factors, such as C2C website auction content, format, ease of use, timeliness, security, transactions, and product varieties influence buyers [29]. While that research only assessed buyers and online auctions, it does show the complexity of influence when considering C2Ce-commerce. This study seeks to examine trust and risk for buyers and sellers in a C2C e-commerce environment. In order to do this, two research models are proposed, one for attitude toward purchasing and one for attitude toward selling in C2C e-commerce. By examining both perspectives, researchers can begin to understand buyer and seller behaviors and why they are different in C2C e-commerce.

RESEARCH MODEL

New methods for consumers to facilitate their transactions are increasing. With the advent of the Internet and various portable devices, C2C e-commerce is growing. C2C e-commerce is defined in this study as consumers transacting (buying and selling) electronically. Since the C2C area does not have many foundation studies at this point, this study builds on the work of previous researchers in the e-commerce arena. In particular, Verhagen et al.’s [34] work is examined. They empirically researched the perceived risk and perceived trust associated with C2C electronic marketplace purchasing, and measured attitude towards purchasing through intermediary risk, intermediary trust, seller risk, and seller trust. The results of their study indicate that seller risk and seller trust directly affect attitude toward purchasing from an electronic marketplace. Trust and risk have been extensively examined in thee-commerce arena, as will be shown in the below discussion; yet little is known about trust and risk in C2C e-commerce or trust and risk for the buyer and seller in said transactions. However, previous research does support the notion that trust and risk will play a role in influencing attitude in the C2C e-commerce environment for both buyers and sellers. Therefore, this study goes beyond the work of Verhagen et al. [34] by examining attitudes towards purchasing/selling in a C2C e-commerce environment for both buyers and sellers. Instead of focusing on intermediaries, this study examines buyer risk and buyer trust and seller risk and seller trust. More specifically, for those purchasing using C2Ce-commerce, their attitude toward purchasing is assessed through risk of the seller and trust in the seller. For those selling using C2C

12 Journal of Computer Information Systems Spring 2012

e-commerce, their attitude toward selling is assessed through risk of the buyer and trust in the buyer. Figure 1 depicts the research models to be tested. Trust in e-commerce has been defined as the belief that the other person will behave in a socially responsible manner, fulfilling expectations and not taking advantage of vulnerabilities [25] [26], and has been cited as a key determinant in adoption of e-commerce [17] and in purchase intentions via the web [12] [24] [35]. Components of C2C e-commerce trust have been proposed and tested [20], with seller trustworthiness beingnoted as an important factor for C2C online buyers [32]. Additionally, trust has been found to be an influence on customer loyalty in e-commerce [23], and trust from online social activities can transfer to trust in terms of transactions on social networking sites [13]. Risk has been defined as the person’s belief regarding inherent risks in the online transaction [26]. Risk includes concerns about fraud, lack of product delivery, and so forth [6], and has been found to negatively affect e-commerce use intention [1]. Attitude can be defined as one’s salient beliefs about behavioral consequences [27]. Attitude towards online shopping has been found to be influenced by risk [36] and trust [27]. The relationship between risk and trust is unavoidable, yet the concepts are treated separately [6]. For example, Gefen et al. [11] examined the antecedents of trust in online shopping and discovered that trust is influenced by many factors; Einwiller [8] examined B2C e-commerce and found one’s trusting intention to be most strongly influenced by one’s trusting attitude toward the vendor; Belkhamza and Wafa [1] studied risk as a determinant of behavioral intention in e-commerce and found risk to negatively affect intention to use e-commerce; Jarvenpaa and Todd [18] found risk to be a barrier to online shopping; Van der Heijden et al. [33] examined the perspectives of 228 potential online shoppers at particular websites in order to determine influences on consumer intentions to purchase from an e-commerce website and found perceived risk to play a part in influencing consumer attitude towards purchasing online; and Chen and Barnes [3] examined initial trust and online buyer behavior in the context of online bookstores in Taiwan and found the perceived good reputation of the website, among others, to be an important influence on online initial trust for buyers. Additionally, many researchers examine trust and risk in the same study but still treat them as separate constructs. For example, Pavlou [26] studied the role of trust and risk in consumer acceptance of e-commerce. Through

a survey collection of 155 online consumers, he found both risk and trust to have an influence on consumer intention to transact using e-commerce. Jarvenpaa et al. [19] examined trust and risk as separate influences on consumer attitudes toward an Internet store and intended shopping behavior. Utilizing a survey with 184 participants, they found both trust in the store and risk perception to influence attitude. Kim et al. [22] gathered 468 responses from Web-based surveys in the U.S. in order to assess the success of B2C e-commerce relationships. They found both risk and trust to affect a consumer’s purchase decision. Therefore, given the previous studies’ findings, the following hypotheses are proposed:

H1: Trust in the seller will influence an individual’s attitude toward purchasing in C2C e-commerce.

H2: Risk of the seller will influence an individual’s attitude toward purchasing in C2C e-commerce.

H3: Trust in the buyer will influence an individual’s attitude toward selling in C2C e-commerce.

H4: Risk of the buyer will influence an individual’s attitude toward selling in C2C e-commerce.

METHODOLOGY

Undergraduate students located in a Southwestern university in the United States of America were used for this study. They were solicited based on their enrollment in introduction to management information systems courses. Drennan et al. [7] argue that University students are “representative of a dominant cohort of online users” (p.6). College students represent the most connected (online) segment of the U.S. population, shopping online and spending online. Therefore, they are experienced and frequent users of the Internet. Participants were given questions specifically designed for buyers using C2C e-commerce and for sellers using C2Ce-commerce. If a participant had not bought an item using C2C e-commerce, he/she was not asked to complete that portion of the survey but was instead asked to comment on why he/she had not bought using that medium. Participants who had bought were asked to indicate how many items they had bought using this method, how recently they had bought, and the types of C2C e-commerce that were utilized during their buying experiences. The same applied to the section designed for sellers using C2C e-commerce. Additionally, each section had a set of questions regarding risk, trust and attitude. These questions were modified versions of the instruments utilized by Verhagen et al. [34] (see individual statements listed in Tables 3 and 4). Participants were asked to indicate on a seven-point Likert scale the degree to which they agreed with those C2C e-commerce statements. The participants were informed that the survey was completely voluntary and their responses would be kept anonymous and only reported in the aggregate. They were asked to answer the questions regarding their buying and selling experiences with C2C e-commerce. In addition to these questions, participants were asked to fill out a brief demographics survey. The majority of the respondents (71.8%) had participated in C2C e-commerce (such as online auctions, email groups, web-based discussion forums, and/or chat rooms) as the buyer and 66.3% had made a purchase in the last six months. Twenty-eight percent had participated in C2C e-commerce as the seller, with 47% selling in the last six months. Table 1 provides a breakdown of the participants who had bought and sold using C2C e-commerce.

FIGURE 1. Predictors of Attitude towards Purchasing/Selling using C2C E-Commerce


The table indicates that 64 participants had both bought and sold using C2C e-commerce, 111 had bought but not sold, six had sold but not bought, and 61 had neither bought nor sold. More than 96% of those respondents who had purchased an item using C2C e-commerce had done so more than once, and more than 77% of those respondents who had sold had done so more than once. Table 2 summarizes the type of C2C e-commerce method utilized by the respondents for buying and selling. Online auctions were the most utilized method for both buyers (70.2%) and sellers (64.3%), however, third-party consumer listings were also greatly utilized (59% for buyers and 47.1% for sellers). The sample consisted of 248 respondents, with 52.7% male and 46.3% female (and 2% not indicated). The majority (93.1%) of the respondents were between the ages of 18 and 24, with the second largest group being 25 to 31 year olds with 5.2%. The sample signified many races, with the largest representation being Caucasian (60.5%), followed by African American (11.3%), Asian (10.5%), Native American (5.2%), Hispanic (4%), and Middle Eastern (2%). The sample also contained representation from all student classes (Freshman 20.2%; Sophomore 23.4%; Junior 41.5%; Senior 12.1%; and Graduate 2.8%). A survey of American adults by Pew Internet & American Life Project [28] found that 67% of Internet users studied had made a purchase online using either B2C or C2C, that the largest age group of Internet users is between the ages of 18 and 29, and that a larger percentage of Internet users have some college education versus only a high school education. Therefore, the demographics of our sample are consistent with the demographics of Internet users. Respondents gave very similar reasoning for not participating in C2C e-commerce as a buyer and as a seller. In particular, for those respondents who had never bought using C2C e-commerce, responses such as “distrust”, “risky”, and “no need/desire” where commonly indicated. Also, there were a few responses that the participant did not have a credit card, did not like the time lag, or had heard of previous bad experiences from friends. Respondents

who had never sold using C2C e-commerce indicated “distrust”, “no need/desire”, “inconvenient or time consuming”, and “too much hassle” as common reasons for not participating. Also, there were a few responses indicating that the participants preferred to donate unneeded items instead of trying to sell them.

DATA ANALYSIS AND RESULTS

Validity and Reliability of Measures

Harman’s single-factor test was used to test for common method variance [15]. When entering all variables together, this test assumes a high level of common method variance is present when all variables load on one factor accounting for all of the variance or one factor will account for a majority of the variance. Exploratory factor analysis (EFA) was performed twice, once for each research model. The EFA for the attitude toward purchasing model yielded three factors with an Eigenvalue greater than one. The variance explained ranged from 11.60% to 44.81% of the total variance. The EFA for the attitude toward selling model yielded two factors with an Eigenvalue greater than one. The variance explained ranged from 25.67% to 46.49% of the total variance. This provides evidence that common method variance is not a concern in either model. Construct validity and reliability were tested for the multi-item constructs used in the research models. Factors were extracted using principal component analysis (PCA), and Varimax rotation was utilized to indicate high correlations, using a cutoff point of .50. Table 3 shows the results of the factor analysis for the attitude toward purchasing model. Each of the construct items loaded on their designated factor. The risk construct yielded a Cronbach’s alpha score of .87 and the percent of variation explained was 44.81%, the trust construct generated a Cronbach’s alpha score of .90 with 20.62% of the variation explained, and the attitude construct generated a Cronbach’s alpha score of .86 with 11.60% of the variation explained. Variables for each of the constructs were calculated for each participant as the average of those items. Table 4 shows the results of the factor analysis for the attitude toward selling model. All of the risk items loaded together. However, the trust and attitude factors did not load separately; they all loaded together on one factor. The risk construct yielded a Cronbach’s alpha score of .87 and the percent of variation explained was 25.67%, and the trust and attitude construct (combined) generated a Cronbach’s alpha score of .92 with 46.49% of the variation explained. Variables for each of the constructs were calculated for each participant as the average of those items. Since trust and attitude loaded as one variable, those items were included together. Additionally, the attitude toward selling model was changed to reflect the combination of trust and attitude. Therefore, risk was measured as to its influence on trust/attitude. Given that trust disposition and attitude have been used together to explain the variance in trust [31], attitude and trust being a combined factor for sellers in C2C e-commerce is logical.

Model Testing

Regression analysis was performed to test the relationships between the construct variables and attitude toward purchasing/selling. Residual plots were reviewed for non-random scatter about the zero line, and no heteroscedasticity was found in the

TABLE 1. Buying and Selling Using C2C E-commerce1

SELLER

BUYER Yes No

Yes 64 111

No 6 61

1These numbers do not reflect missing entries; therefore, the actual total sample of buyers is 178 and sellers is 70.

TABLE 2. Method for Buyingand Selling Using C2C E-commerce

BUYING1 SELLING2

Online Auctions 70.2% 64.3%

Email Groups 5.1% 2.9%

Web-Based Discussion Forums 8.4% 10.0%

Chat Rooms 1.1% 1.4%

Third Party Consumer Listing 59.0% 47.1%

1 Percent represents participants who had bought using C2C e-commerce.

2 Percent represents participants who had sold using C2C e-commerce.


TABLE 3. Attitude toward Purchasing Factor Analysis

RISK

As I consider purchasing a product through C2C electronic commerce, I become concerned about whether sellers will commit fraud. .83

As I consider purchasing a product through C2C electronic commerce, I become concerned about whether sellers will deceive. .89

As I consider purchasing a product through C2C electronic commerce, I become concerned about whether sellers offer products that will not perform as expected. .81

As I consider purchasing a product through C2C electronic commerce, I become concerned about whether sellers will behave opportunistically. .77

TRUST

Sellers of products in C2C electronic commerce are in general dependable. .89

Sellers of products in C2C electronic commerce are in general reliable. .88

Sellers of products in C2C electronic commerce are in general trustworthy. .85

ATTITUDE

I am optimistic regarding buying a product using C2C electronic commerce. .76

The thought of buying a product using C2C electronic commerce is appealing to me. .87

I think it is a good idea to buy a product using C2C electronic commerce. .87

Cronbach’s alpha .87 .90 .86

Eigenvalue 4.49 2.06 1.16

Variance Explained 44.81% 20.62% 11.60%

Note: Factor loadings <.50 are not shown to improve readability.

TABLE 4. Attitude toward Selling Factor Analysis

RISK

As I consider selling a product through C2C electronic commerce, I become concerned about whether buyers will commit fraud. .78

As I consider selling a product through C2C electronic commerce, I become concerned about whether buyers will deceive. .80

As I consider selling a product through C2C electronic commerce, I become concerned about whether buyers will not pay for products as expected. .77

As I consider selling a product through C2C electronic commerce, I become concerned about whether buyers will behave opportunistically. .53

TRUST

Buyers of products in C2C electronic commerce are in general dependable. .81

Buyers of products in C2C electronic commerce are in general reliable. .87

Buyers of products in C2C electronic commerce are in general trustworthy. .87

ATTITUDE

I am optimistic regarding selling a product using C2C electronic commerce. .74

The thought of selling a product using C2C electronic commerce is appealing to me. .78

I think it is a good idea to sell a product using C2C electronic commerce. .76

Cronbach’s alpha .92 .87

Eigenvalue 4.65 2.57

Variance Explained 46.49% 25.67%

Note: Factor loadings <.50 are not shown to improve readability.


data. Variance inflation factors (VIF) were examined for each of the independent variables in the model, with all values being small (below 2) for both models suggesting there is no problem with multicollinearity in the data. No violations of regression assumptions were found. Table 5 presents the regression results for the attitude toward purchasing model. Two hypotheses were proposed. H1 posed that an individual’s trust in the seller would influence his/her attitude toward purchasing in C2C e-commerce, and H2 posed that an individual’s risk of the seller would influence his/her attitude toward purchasing in C2C e-commerce. Both H1 and H2 were found to be significant. Table 6 shows the regression results for the attitude toward selling model. Two hypotheses were proposed. However, given the factor analysis results, H3 is dropped from the analysis and

H4 is modified to assess if an individual’s risk of the buyer would influence his or her trust/attitude toward selling in C2C e-commerce. H4 was not supported. After the hypotheses were tested, additional analyses were performed to check for differences between buyers and sellers in C2C e-commerce. Table 7 summarizes the findings for those participants who have both bought and sold using C2C e-commerce, excluding those that have only bought or who have only sold. The findings do not change for the attitude towards purchasing model; however, the attitude towards selling model does change from the previous findings, with risk being found to influence the individual’s trust/attitude toward selling. Table 8 summarizes the findings for those participants who have bought using C2C e-commerce but have never sold. The results indicated that trust in the seller does affect an individual’s

TABLE 5. Regression on Attitude toward Purchasing

Dependent Variable: Attitude toward Purchasing

Independent Variable Standardized Beta Standard Error t p

Risk of Seller -.138 .065 -1.996 .048* H2 supported

Trust in Seller .484 .075 7.017 .000** H1 supported

R2 = .30; **p<.001, *p<.05

TABLE 6. Regression on Trust/Attitude toward Selling

Dependent Variable: Trust/Attitude toward Selling


Risk of Buyer -.219 .097 -1.847 .069 H4 not supported

R2 = .05; **p<.001, *p<.05

TABLE 7. Regression for Participants that have Both Bought and Sold



Risk of Seller -.318 .112 -2.660 .012* Supported

Trust in Seller .312 .138 2.606 .010* Supported

R2 = .28; **p<.001, *p<.05

Dependent Variable: Attitude toward Selling


Risk of Buyer -.293 .082 -2.410 .019* Supported

R2 = .09; **p<.001, *p<.05

TABLE 8. Regression for Participants that have Bought but never Sold



Risk of Seller -.059 .081 -.704 .483 Not supported

Trust in Seller .566 .090 6.707 .000** Supported

R2 = .34; **p<.001, *p<.05


attitude toward purchasing but risk does not when the participants have only bought. The last analysis sought to examine those participants who have sold using C2C e-commerce but have never bought. The sample size for this analysis consisted of only six participants, because most individuals who have sold using C2C e-commerce have also bought. Given the extremely small sample size, the results could not be assessed. Additional data is needed before real conclusions can be reached.

DISCUSSION AND CONCLUSION

This study sought to examine risk and trust of buyers and sellers in C2C e-commerce by testing two research models, one for attitude toward purchasing and one for attitude toward selling in C2C e-commerce. The results indicate that a buyer’s trust in the seller and risk of the seller influence his/her attitude toward purchasing in C2C e-commerce. Given previous study findings, this is not surprising. A buyer decides whether to utilize a seller based on risk and trust factors, such as reputation, so it would seem obvious that both are significant. What may be more surprising are the findings for attitude toward selling. Given the factor analysis results, trust and attitude are combined into one factor. The results indicate that a seller’s trust/attitude toward selling is not influenced by risk in the buyer. Therefore, a seller in C2C e-commerce is not concerned with, or is unaware of, any risk. This could be due to the nature of C2C e-commerce transactions. Regardless of the method, online auctions, discussion forums, or so forth, most sellers are utilizing a reliable payment mechanism such as PayPal; they may, therefore, not feel any risk associated with the transaction. Many times IS researchers discuss trust and risk in systems, e-commerce, or more specifically, C2Ce-commerce, but fail to specifically address “whose” trust and risk is being assessed. This study shows that the participant in the C2C e-commerce transaction is important. Therefore, sellers will want to alleviate risk and establish trust with buyers if they wish to make a sell in this environment. Additionally, system designers must work to include mechanisms that will help to eliminate poor perceptions in C2C environments, and IS researchers should identify “who” is being assessed in studies so that more accurate models may be developed. Additional analyses were also performed to examine differences in buying and selling with C2C e-commerce. Analysis of participants who had bought and sold using C2C e-commerce (excluding those that had only bought or only sold) produced identical results for the attitude toward purchasing model. This seems realistic given that all individuals analyzed had at least had a purchasing experience with C2C e-commerce. However, the attitude toward selling model changes, with risk of the buyer being found to influence a seller’s attitude/trust toward selling. The elimination of the consumers who had only bought or only sold has a huge impact on the findings. When a consumer has experience with both buying and selling in C2C e-commerce, he/she understands the risk and that risk plays into attitude/trust when selling using that means. There are differences in a consumer’s trust both before and after one has gained experience with the electronic shopping means [5]. Therefore, it is the experience of having been both a buyer and a seller in the C2C e-commerce medium that accounts for the differences in findings. When analysis of only those participants who had bought (but not sold) was performed, trust in the seller was found to influence attitude toward purchasing, but risk was not found to be significant. This

finding indicates that when an individual has never sold using C2C e-commerce, they are not aware of any risk of the seller either. The individual still needs to trust the seller, but one does not perceive risk in doing so. Therefore, it is the experience of being a seller that plays into the assessment or acknowledgement of risk. Therefore, knowing a consumer’s previous experience with being a seller or a buyer in a C2C e-commerce environment can be used to improve said relationships. IS researchers should seek to assess experience levels in C2C e-commerce. Not simply years or number of purchases, but the types of experiences, the number of positive and negative (as buyer and as seller), medium used (online auction, third party listing service, etc.), and so forth should be part of the analysis. C2C system designers can again seek to improve mechanisms that lead to greater trust or reduced risk. For example, reviews of previous sells or previous purchases could be modified to allow ratings on multiple dimensions. Those dimensions could be specifically designed to address areas of risk and trust. Researchers should seek to develop scales/dimensions that can be used to address these areas so that they can be implemented in the C2C e-commerce world. These findings are a first step in understanding buyer and seller behavior in C2C e-commerce. Additional research is needed to examine differences in buyer and seller risk and trust, and to gather additional data so that further models in this realm may be examined. C2C e-commerce research is in its infant stage; there is still much to be learned.

LIMITATIONS ANDFUTURE RESEARCH

A limitation of this study lies in the sample being from one University. An additional, more diverse, sample should be examined. Also, this study did not seek to address influences on trust and risk. Many additional factors could be proposed as influences on trust and risk and should be studied in the future. In particular, one’s experience level or number of years of involvement in C2C e-commerce could be used to explain one’s attitude toward buying and/or selling. This study also measures perceptions and not true behaviors. Therefore, future studies should seek to gather data regarding actual consumer behaviors in C2C e-commerce. Finally, given the combination of trust and attitude in the attitude toward selling model, further research is needed to examine why a consumer’s attitude and trust might be combined in certain situations or environments. A new model for sellers in C2C e-commerce should be developed since clearly sellers and buyers do not have the same attitude, trust, or risk assessment when C2C e-commerce is involved.

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Attitude Influencers in c2c E-commerce. Buying and Selling. - Leonard

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