European Journal of Economics, Finance and Administrative Sciences ISSN 1450-2887 Issue 19 (2010) © EuroJournals, Inc. 2010 http://www.eurojournals.com Preparation of Measurement Tools of the Effective Factors for the Acceptance of Online Stock Trading Alireza Abroud Faculty of Management, Multimedia University, Jalan Multimedia 63100 Cyberjaya, Selangor, Malaysia E-mail: Abrood_2006@yahoo.com Tel:+60173423578. Yap Voon Choong Faculty of Management, Multimedia University, Jalan Multimedia 63100 Cyberjaya, Selangor, Malaysia E-mail: Vcyap@mmu.edu.my Tel: +603-83125785 Saravanan Muthaiyah Faculty of Management, Multimedia University, Jalan Multimedia 63100 Cyberjaya, and Selangor, Malaysia E-mail: Saravanan.Muthaiyah@mmu.edu.my Tel: +603- 83125768 Abstract The purpose of this research is to prepare valid and reliable tools for the measurement of effective factors in the electronic technology to participate in stock trading and to evaluate a model proposed to initiate stock investors to use internet as a medium for trading. A pilot study was planned and carried out employing a questionnaire based on theory planned behavior and a technology acceptance model. Subsequent to designing the questionnaire and performing reliability tests by means of Cronbach Alpha and Richardson, statistical analysis was performed and the examination of the predictor and dependent variables of a relational model by standard and hierarchical regression methods were carried out on 34 investors at Tehran stock exchange. The results of this research showed that the variable, namely attitude, subjective norms, usefulness, knowledge, and self-efficiency had strong relationship with intention and other related variables. Furthermore, the risk variable had a negative relationship with attitude. Besides, the perceived behavioral control, social demography, and ease of use had weak relationship and proved to possess no effect on the intention of the investors to engage in internet stock trading at Tehran stock exchange. Keywords: Online stock trading, investor perspective, TPB, Iran stock market, Securities. 1. Introduction In the past two decades, the effects of technological development, especially in information technology on organization management, administration methods and modes of financial services in the world has been significant. These effects are considered a fundamental axis for economical development as a 35 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) service provider to other economical and managerial sectors. Also, there has been ever-increasing development of information technology via the internet which has proven to be an effective factor in financial sectors and their related services. As a result, there has been a surge in electronic financial services. The internet can be appropriately named as one of the most important human inventions in history. It has been one of the most effective, essential and indispensable technologies so far. Its multi- purpose use and potential profitability has influenced not only social development, health and economic programs but also stock exchange markets that drew a lot of investors, as a result. The extent of this phenomenon is not limited only to industrial countries and developed or emerging markets. This is due to the fact that even countries with undeveloped financial systems have taken a giant leap in their progress by merely taking advantage of electronic financing methods to compensate for their backwardness. With the introduction of electronically financial services, the sectors that were mostly affected were the investors' services and securities exchange agencies. Therefore, these agencies, by taking advantage of new markets expanded their businesses to several world financial centers. These electronic investment markets were also able to help investors by the enhancement of information transparency and speed in economic transactions. Brails found that the results obtained from internet stock, simultaneously increased the transactions and information exchanges by 77%(Brail sford 1999) . The development of the Internet in stock exchanges has created an explosion in the rate of exchanges at the world level in such countries such as the U.S.A, Hong Kong, South Korea, Thailand, Singapore, Taiwan, and other developed or developing countries. Most of the stockholders and investors unanimously confirm that internet stock exchanges are in fact one of the best and important sectors for the implementation of electronic commerce if the differences in duties and type of electronic activities were overlooked. Maybe, one of the most significant and exciting examples in recent growth of electronic commerce was in the U.S.A securities exchanges. It was estimated that 15% of private investors' accounts were performed through internet, and the number of the accounts through which exchanges performed by internet was more than 4.5 million people by the end of 1999 (Hong 2000). In 2007, the rate of public stock value exchanged amounted to 19.95 trillion dollars (CIA 2008) the total value of the stock exchanged through internet in U.S.A securities exchange in 2004 amounted to 64% (Kennickell 2000). With reference to the report by J.R., the number of the world internet accounts reached to 900,000 accounts in 6 mostly European countries by 1999. This figure increased to more than 8.3 million accounts by 2000 with a 20% increase for every 4 months (Hong 2000). Furthermore, the Internet stock exchange grew amazingly in Asia. For example, the value of stock exchanges in Cyber Space increased by about 234% for the first 7 months of 2000 in South Korea (Hong 2000). In 2008, South Korea ranked 18 among the world countries with a value of 623 billion dollars of stock exchanges (CIA 2008). In the same way, the rate of internet stock exchange in Hong Kong in 2005 had reached 46% (Adela and patrick 2001)and this figure was 40% for Singapore in 2003 (Lee. and Ho 2002)and 35% for Thailand in 2005 (Piotr and K 2005). Also, it is worth mentioning that the speed of internet exchanges performances has improved so significantly that stock purchase and sale is performed just by a ‘click’ throughout the world. Although it has been commonly accepted that the online stock exchange is an inevitable solution for economic development and improvement of new systems throughout the world, some investors and stock brokers avoid performing online transactions. They are doubtful whether this system will satisfy their needs in stock exchanges or not(Shi-Ming and H. Yu-Chung 2005).Some are undetermined as to whether stock electronic commerce can provide competitive advantages and commercial opportunities for them. 36 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) With the technological revolution and development in information exchanges, Iran also had partaken the arena in electronic commerce sectors such as stock exchanges and securities. Iran has created suitable conditions for the investors by providing the required substructures such as technical facilities and telecommunications, an electronic banking penetration expansion, strengthening of laws and regulations, educating and supporting investors for the use of internet in stock exchanges. On the basis of recent reports, the value of stock exchanges in Iran was 45 billion dollars in 2007 with an internet penetration rate of 34% raking 57 among the world countries for the value of stock exchanges (CIA 2008). But the electronic stock exchange rate was only 7% of the total stock exchanges in 2006 in Iran (Bagherian 2007). This figure was very low compared to other developing countries which necessitated the study of important and decision-making factors in stock exchanges in Iran. Due to the fact that online transactions were imperative and the growing need for the support of economic policy-makers for its increased use in financial transactions, especially in stock exchanges and securities, it is necessary that focus is given to the improvement and development of the above- mentioned substructures. Thus, the study of behavioral factors such as the attitude of the investors, subjective norms, knowledge, perceive behavioral control, risk, ease of use as well as simple understanding of the usefulness of modern technology by the investors and brokers are all inevitable. For this purpose, one of the theories and the models employed by the researchers in the previous related studies to help the acceptance of modern systems by the users is the theory acceptance model (TAM),theory reason action (TRA) and theory of planned behavior (TPB). 2. Literature Reviews The research models of technology adoption have thus been extensively used in the study of online customer behavior. (Christy and Gloria WW 2005)found that most authors depended heavily on theories from the TRA family; including the theory of reasoned action (TRA), the technology acceptance model (TAM) and the theory of planned behavior (TPB). 2.1. Theory of Reasoned Action Fishbein and Ajzen (1975) developed the TRA, which examines attitudinal and normative influences on behavior. According to TRA, a person’s performance of a specified behavior is determined by his behavioral intention (BI) to perform the behavior. Behavioral intention (BI) is jointly determined by the individual’s attitude (A) and subjective norm (SN) concerning the behavior .They also assign weights (w) to these attitude (A) and subjective norm (SN) determinants. The weights are indicative of the relative importance of each determinant and can vary with each situation and each person. They are typically estimated via linear regression. The relationships among behavior, intention, attitude, and subjective norm are depicted as: BI=W1 (A) +W2 (SN) (1) Where w1and w2 are the relative weights given to each component by (Ajzen and Fishbein 1980). 2.2. Technology Acceptance Model The Technology Acceptance Model (TAM), introduced by (Davis 1989), is an adaptation of the Theory of Reasoned Action (TRA) specifically modified for modeling user acceptance of information technology (Davis, 1986; Davis, 1989).TAM suggests that attitudes predict intentions, and intentions predict behavior. According to the TAM, adoption behavior is determined by the intention to use a particular system and the intention is determined by the attitude, which in turn is determined by the perceived usefulness and perceived ease of use of the system (Davis 1989). Davis stated that the main goal of TAM is to explain the determinants of IT acceptance across a broad range of information 37 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) technologies and user populations. Moreover, Davis proposed that acceptance of IT can be determined by two primary constructs: perceived usefulness and perceived ease of use of the technology. 2.3. Theory of Planned Behavior Ajzen (1991) refined and added an additional element to an earlier theory of reasoned action (Ajzen & Fishbein, 1975) to propose a new theory he termed theory of planned behavior. Theory of planned behavior describes an important fourth element of behavioral decision-making as the perception of behavioral control (PBC). A perceived behavioral control is defined as behavioral controls are perceptions of one's beliefs in their ability to perform a given behavior. They are defined operationally as the rate to the extent to which an individual has the ability to perform (how much the behavior is under their control) a specific behavior (Ajzen 2002). TPB defines intentions in terms of three belief structures: attitude (predisposition toward a particular object, event, or act, that is subsequently manifested in actual behavior), subjective norm (perceptions about social forces influencing a behavior), and behavioral control (perceptions of internal or external constraints affecting the behavior). These constructs are, in turn, determined by three sets of perceptual beliefs: attitudinal beliefs (Cognitive beliefs regarding the instrumentality of the intended behavior), normative beliefs (beliefs about the social desirability of that behavior), and control beliefs (beliefs about behavioral constraints affecting behavioral performance). 2.4. Conceptual Model for this Study Christy, Lei et al. (2003) identified the theories that are used by the authors of the 351 papers surveyed. Findings show that the Theory of Reasoned Action (TRA) and its family theories including the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) are the dominant theories in this area (online trading). The findings show Researchers, therefore, should try to extend theories and modified new models also new frameworks and investigate online customer behavior from different perspectives. Many studies also tested the TRA, TAM and TPB and found that TPB provided the better explanation to online customer behavior than what TAM and TRA did (Hansen et al. 2004, Hung and Chang, 2005). 2.5. Major Antecedents to Online Stock Trading Most researches done in the last decade on online investor behavior attempted to identify major antecedent factors to determine online investors behavior (Lee. and Ho 2002; KhaliL 2005),.this is due to the fact, previous studies portaged large numbers of antecedents on online stock trading. The factors of online trading consist primarily of personality, type of product, online service quality, website quality, investor experience, computer experience, related advantage, price sensitivity, and so on .since it is not feasible to consider all antecedents in one research model, in accordance with the principles of parsimony, researchers normally select a minimum of three constructs which are capable of evolving empirical results of high validity and reliability. 38 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) Figure 1: The proposed framework on the basis of TPB Perceived usefulness Perceived Risk Perceived Ease of use Self-efficacy K nowledge Attitude toward behavior Subjective norms Perceived behavioral control Intention to adopt online stock exchange Online stock exchange Demographi c control Variables Based on previous studies, it has been noted that three precluding factors namely, perceived risk, investment knowledge and demographic control variables which were not emphatically identified and empirically examined in priors’ stock market studies are conspicuously integrated and included in this research model. Since no study has been done so far on the recognition of behavioral and attitudinal factors in the securities stock exchanges of Iran, the aim of this research is therefore, to study the effective and decision-making factors for the acceptance and use of internet in the stock exchanges of Iran by the investors, while evaluating their attitudes . This research as a pilot study is a research which will be carried out on all subsets of the groups related to stock commerce including investors and brokers in the future. In addition to this, a questionnaire was prepared and verified its validity for the final research. 3. Methodology This is a pilot study based on the theory of planned behavior (TPB). The expected behavior under study in our research was the acceptance of the application of information technology within the framework of electronic commerce in the stock market by the people involved in this commerce. The measurement tools for the identification of the effective factors in the selection or the decisions made for the application of this technology was studied by the investors in the stock market. The population target study comprised of Tehran stock market investors and the time required for the study was a 4-month period as of May 2009. The unit under study was each of the people working as an investor at Tehran stock market within the specified period. The study comprised of two major stages; the first stage comprised all the activities leading to the planning of valid measurement tools for the execution of the research and the second stage comprised of reliable tests along with preliminary analysis of the behavioral model of the acceptance of electronic technology in the commerce of stock market performed on the small group of the population under study. In the first stage, a valid questionnaire was planned for the research. We had to divide our questionnaire into different sections so that each section was devoted to one of the main predictor variables or outcome variable in the planned behavior theories and in the technology acceptance. Therefore, the attached questionnaire (Appendix 1) is composed of 9 parts. Section 1 included information related to socio-demographic variables (including age, gender, education, etc.) and other sections were devoted to the study of behavioral variables. Since the structure of behavioral variables employed in this research was in the form of hidden variables and were not directly observable, we 39 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) therefore used the 5- type scale Likert variables for this study(Adela and patrick 2001).Because responses are graded, this method is more flexible and can be more useful than other methods in contrast to other one-section evaluation methods used for the variables. The behavioral variables related to our study were attitude, subjective norm, self-efficacy, risk and ease of use, perceived usefulness, perceived knowledge, and intention, respectively. Our standard for the measurement of the socio-demographic variables were nominal, but all the behavioral variables were calculated by interval standard. (Table 1) Table 1: Summary of the sample of questions use in this study Sections Constructs Sample questions/Items Definition No 1 Demographics variables How old are you? The socio-demographic determinants which can affect the relation between different constructs in behavioral model of adoption of online stock trading 6 2 Attitude I feel using Internet stock trading is a wise idea. General evaluation of a person is related to an action or a phenomenon 6 3 Subjective Norm Most people who are important to me would think that using the Internet stock trading is a wise idea. The study of personal perception against social pressures for the performance of a definite behavior 3 4 Self-Efficacy I could conduct my stock trading transactions using the Internet stock trading system if I had the system manuals for reference. Is a person’s beliefs in her capabilities and cognitive resources required to cope with given events, Ajzen (2001) 8 5 Perceived Risk I am not confident over the security aspects of Internet stock trading in Iran. Is belief about the likelihoods of gains or losses outside of considerations that involve the relationship with the particular trustee? 8 6 Perceived Ease of Use My interaction with the Internet stock trading system is clear and understandable. Is the degree to which the person thinks that using the IS will be free of effort. 5 7 Perceived Usefulness Using Internet stock trading system would save time. Is the degree to which a person believes that using a particular system would enhance his or her job performance? 5 8 Perceived Knowledge I think I have the proper knowledge of doing online stock trading. Investors' and Brokers' feeling of having the knowledge and ability of using online stock trading 6 9 Behavioral Intention I intend to use/continue using Internet stock trading in the next six month future. A measure of the strength of intention to perform a specific action. 6 10 Perceive behavioral control I would be able to operate Internet stock trading The perception of the availability of skills, resource and opportunities 4 After the preparation of the preliminary questionnaire, it was examined by 5 persons for transparency and clarity of the questions and the items were evaluated. It was also evaluated for its sentence structures and comprehensibility of the words. On the basis of the collected comments at this stage, a number of the questions were rewritten and some words were replaced with more unambiguous and more comprehensible words. In the second stage, 50 persons were chosen by simple random selection from the investors of Tehran stock market to complete the questionnaire. Besides that, the first two pages of the questionnaire were devoted to the information sheet and the consent of the company 34 out of 50 persons referred announced their readiness for participation with a response rate of 68% which was a good rate. To increase the response rate when referring to them, the questionnaire was completed in their free time and they were informed that the information they provided were to be kept confidential and only the statistical analysis of the completed questionnaire would be used for the improvement of practical policies of the stock market. In addition to that, a book under the title of, "An Introduction to 40 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) Electronic Commerce" was given to each participant as a gift for their cooperation. After collecting the complementary questionnaires and at the reliability analysis stage of measurement tools, sections of the questionnaire related to the dependent variable and predictor variables including attitude, subjective norm, PBC, self-efficacy, ease of use, usefulness, and perceived risk were examined by internal consistency through Cornbach Alpha for their reliability. The perceived knowledge variables were tested for their reliability with regard to Dichotomous variable through a special state of Cornbach Alpha named Kuder Richardson Test. The results of the reliability test on the variables are presented in Table 2. Table 2: The results of the reliability test on the questionnaire NO Construct Cronbach's Alpha (Number of Items) Action Cronbach's Alpha (Final) 1 Attitude .865 (7) No action 0.865 2 Subjective norm .651 (4) Item 1 deleted 0.742 3 Self-efficacy .915 (8) No action 0.915 4 (PBC) .798 (4) No action 0.798 5 Ease of use .709 (5) No action 0.709 6 Usefulness .823 (5) No action 0.823 7 Perceived risk .801 (7) No action 0.801 8 Perceived knowledge .899 (6) No action 0.899 9 Intention .845 (6) No action 0.845 After the reliability analysis, depending on the description of the collected statistical samples and analysis of the results obtained from the completion of the questionnaires, standard regression models and hierarchical regression were performed by SPSS Version 17 and through correlation tests. 4. Research Findings After a descriptive review and analysis of the data of the 34 cases under study, the following results were obtained. The descriptive statistics showed that the majority of the participants taking part in this study were males (88.2%) with an age average of 38.12 years (S.D. 11.31) from 24 to 62. According to Table 3, all the participants were educated with a minimum degree of high school diplomas and most of them were university graduates (79.4%) Table 3: Educational level frequency distribution of the investors at Tehran Stock market Frequency Percent Valid Percent Cumulative Percent Diploma 7 20.6 20.6 20.6 Bachelor 18 52.9 52.9 73.5 Master or PhD 9 26.5 26.5 100.0 Valid Total 34 100.0 100.0 In the study of the situation of the use of internet in stock exchanges, it was observed that the majority of these investors had never used internet for this purpose (Table 4). Table 4: Past record for the use of internet (years) in stock exchanges by the investors at Tehran stock market Frequency Percent Valid Percent Cumulative Percent Never 23 67.6 67.6 67.6 <3 8 23.5 23.5 91.2 >5 3 8.8 8.8 100.0 Valid Total 34 100.0 100.0 41 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) Statistical analysis performed by Student T-test showed that there was no difference between the average age of the adapter and non-adapters (t=.42, p<.05). Taking this into consideration, the sample under study was small; the performance of a valid statistical analysis to observe the relationship between the educational level of the group of adapters and the non-adapters was not possible. According to the proposed framework for the study, 4 regression models were considered among the variables under study. In these 4 models, the variables of intention, attitude and PBC, and intention were respectively set forth as the dependent variables which were tested as follows: 4.1. The First Model It included 3 variables of attitude, subjective norm, and PBC as well as the dependent variable of intention. The results of the standard regression analysis showed that the set of the three variables of predictors of this model could explain 49.7% of the variance in the intention variable. Because of the small volume of the sample, after adjusting the score was 44.7%, and still acceptable. The regression analysis showed that the above set of the three variables along with the intention variable were significant in the regression model (F=9.9, df=3, p<.001). In the next step, the Slope Hypothesis was tested to determine the presence or absence of each of the predictor variables and their power in the model. The results showed that the presence of the attitude variable (p<.01) and to some extent the subjective norm variable (p=.05) was significant, but there was not significant PBC variable in this model (table 5). Table 5: The results of the examination of Slope Hypothesis for the determination of the presence and the power of the presence of predictor variables in regression model No. 1 Non standardized Coefficients Standardized Coefficients B Std. Error Beta t Sig. (Constant) 5.574 4.337 1.285 0.209 Total attitude 0.513 0.168 0.541 3.064 .005* Total subjective norms 0.564 0.281 0.303 2.008 .054* 1 Total PBC -0.105 0.306 -0.058 -0.344 0.734 Dependent Variable: Total intention * significant at the .05 level (p < .05) ** significant at the .01 level (p < .01). The standardized coefficient correlation scores related to attitude and subjective norm variables showed that the attitude variable (Beta=.541) was about twice as much as the power of subjective norm variable (Beta=.303) in the prediction of the intention. According to table 5, the No. 1 standardized and non standardized regression equations are as follows: Intention Score= 5.574 + .541(Attitude Score) + .303(SN Score) - .058(PBC Score) (2) Intention Score= 5.574 + .513(Attitude Score) + .564(SN Score) - .105(PBC Score) (3) It is observed in the above model that no significant role was found for PBC, but as it is seen in table 6 that there is a meaningful relation among each of the attitude and subjective norm variables and even PBC on the one hand and the intention variable on the other hand.(table 6) 42 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) Table 6: The relation among the variables under study in the regression model No.1 Total intention Total attitude Total subjective norms Total PBC Total intention 1.000 .656 .549 .409 Total attitude .656 1.000 .498 .628 Total subjective norms .549 .498 1.000 .418 Pearson Correlation Total PBC .409 .628 .418 1.000 Total intention . .000 .000 .008 Total attitude .000 . .001 .000 Total subjective norms .000 .001 . .007 Sig. (1- tailed) Total PBC .008 .000 .007 . Total intention 34 34 34 34 Total attitude 34 34 34 34 Total subjective norms 34 34 34 34 N Total PBC 34 34 34 34 In order to answer the question whether the predictor variables are able to predict intention variable or not when the effects of age, gender, and educational level variables are deleted, the Hierarchical Regression Analysis was performed at the next stage. With a view to the fact that gender is dichotomous and age is continuous, but educational level was ordinal, it is therefore required to change it to a dichotomous variable (with two states of having higher education and lack of higher education) before controlling the educational level variable. By placing the mentioned control variables in a block and placing predictor variables in another block, the results of the regression analysis showed that by controlling these variables, still the attitude significantly predicts the intention variable, but the subjective norm variable situation is weaker than before in the model. But, the regression model was still significant and the set of the three variables of attitude, subjective norm, and PBC were able to explain 41% of the variance in the intention variable which was significant by deleting the effects of the control variables. 4.2. The Second Model This proposed model included the attitude variable as the dependent variable and the variables of ease of use, usefulness, and risk as the predictor variables. A similar analysis showed that on the whole, these three predictor variables explained only 26% of the variance in the attitude variable. Both the standard regression and hierarchical regression analysis showed that these variables were not placed in the model. However, as it is observed in table 7, the variables of ease of use and usefulness have a meaningful correlation with the attitude variable and the risk correlation of the attitude is also negative, but is not statistically at a meaningful level (table 7). 43 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) Table 7: Correlation among the variables of regression model No.2 Total attitude Total Ease of use Total Usefulness Total Risk Total attitude 1.000 .453 .429 142 Total Ease of use .453 1.000 .520 144 Total Usefulness .429 .520 1.000 348 Pearson Correlation Total Risk 142 144 348 1.000 Total attitude . .004 .006 .211 Total Ease of use .004 . .001 .208 Total Usefulness .006 .001 . .022 Sig. (1-tailed) Total Risk .211 .208 .022 . Total attitude 34 34 34 34 Total Ease of use 34 34 34 34 Total Usefulness 34 34 34 34 N Total Risk 34 34 34 34 The regression equations on the basis of standardized and non standardized correlation coefficients related to the analysis were respectively as the following: Attitude Score= 15.768 + .366(Ease of use score) + .356(Usefulness Score) - .004(Perceived risk Score) (4) Attitude Score= 15.768 + .315(Ease of use score) + .264(Usefulness Score) - .005(Perceived risk Score) (5) 4.3. The Third Model This proposed model included the PBC variables as the dependent variables and the two variables of self-efficacy and knowledge as the predictor variables. As it is seen in table 8, both of the variables of perceived knowledge and self-efficacy have good correlations and are statistically significant with PBC variable. The regression analysis showed that the self-efficacy and perceived knowledge variables on the whole explained 50.6% (47.6%, after adjusting the volume of the small sample) of the variance in the attitude variable and the regression model was significant at (F=16.001, df=2, p<0.001). Table 8: The Relation Among the Variables in the Regression Model No. 3 Total PBC Total self-efficacy Total knowledge Total PBC 1.000 .707 .290 Total self-efficacy .707 1.000 .288 Pearson Correlation Total knowledge .290 .288 1.000 Total PBC . .000 .048 Total self-efficacy .000 . .050 Sig. (1-tailed) Total knowledge .048 .050 . Total PBC 34 34 34 Total self-efficacy 34 34 34 N Total knowledge 34 34 34 However, the Slope Hypothesis test showed that only the self-efficacy variable and the constant were present in this model if they were statistically meaningful. The regression equation with standardized and unstandardized correlation coefficients was respectively obtained as follows: PBC Score= 7.711 + .257(Self-Efficacy score) + .034(Perceived knowledge Score) (6) PBC Score= 15.768 + .680(Self-Efficacy score) + .095(Perceived knowledge Score) (7) The results of the regression analysis for the control of the variables of age, gender, and educational level also showed that after the control of these variables, the regression model was again significant. Also, the only variable that could meaningfully predict PBC was the self-efficacy. [...]... think the use of internet stock trading transaction would save time for me… Using internet stock trading system makes it easer for me to conducting my stock trading transaction I fell the use of Internet in stock trading transactions can be very effective and useful … I think online stock trading enable me to complete my transaction activities more quickly conveniently … The use of Internet in stock trading. .. variables in the definition of intention, the results obtained from the relationship of the risk variable and attitudes were negative In other words, the more the degree of risk taking and lack of confidence in the investors in the modern system (online stock trading) , the less was the tendency Therefore, this relationship was also considered to be negative, in this study 6 Limitation and Suggestion for Future... with the factors that are effective in the attitude of stock market investors to accept a new behavior (acceptance of online stock trading) The statistical analysis on the set of 9 independent variables of which the 5 variables of attitude, subjective norm, usefulness, knowledge, and self-efficacy, showed effective relationships while the other 4 variables were identified as the factors with predicted... internet in the population of the investors at Tehran stock market These findings are very similar to the results of the studies performed by Adela Lou in 2001 on the training and implementation of the new technology on stock investors (Adela and patrick 2001) Another important point worth mentioning in the findings of this study as it was referred to before is that in the complementary analysis of the statistical... regression model for the analysis of the findings of the plan was that the regression model when compared with other methods of statistical analysis of behavioral models such as Structural Equation Model (SEM) can provide solutions for a pilot study with a limited number of findings Second, this study only covered the investors in the stock market With regard to the important roles of the brokers in stock transactions,... predicted that in other stock markets of the country, there might be significant differences pertaining to the intensity of access to internet, knowledge, awareness, and attitudes towards the internet and even the norms related to the acceptance of internet technology in stock market transactions Extending the size of the population under study to the entire stock markets in Iran can illuminate the different... 544(Usefulness Score) (9) The results of the analysis of the hierarchical regression for the deletion of the effective variables of age, gender, and educational level also showed that even after controlling these variables, the regression model was again significant and the three variables of predictor present in the model were able to explain 71% of the variance in the intention variable 5 Discussion... Malaysia stock exchange, the subjective norm has had meaningful effect on the intention of the investors for the acceptance of online stock trading (Gopi and Ramayah 2007) Also, in this study there was an 45 European Journal of Economics, Finance And Administrative Sciences - Issue 19 (2010) effective relationship between subjective norm and intention This relationship showed that the amount of subjective... subjective norms is effective on the investor’s intention for internet transactions Numerous studies performed in the domain of internet use in commerce unanimously agreed that one of the most important variables which could be effective in the continuation or acceptance, and performance of a modern system was the attitude variable (Ajzen 2002; Ajzen and Fishbein 2005)Therefore, according to these studies,... both the attitude and subjective norm had positive and significant effects on intention Of course, this theory was later extended in TPB theory and the PBC variable was later added to it Other studies also showed that attitude was one of the very important foundations for the definition of intention for the performance of new behavior (Fishbein and Ajzen 1975; Ajzen and Fishbein 2005), For example, the . securities stock exchanges of Iran, the aim of this research is therefore, to study the effective and decision-making factors for the acceptance and use of internet in the stock exchanges of Iran by the. application of information technology within the framework of electronic commerce in the stock market by the people involved in this commerce. The measurement tools for the identification of the effective. preliminary analysis of the behavioral model of the acceptance of electronic technology in the commerce of stock market performed on the small group of the population under study. In the first stage,