Subscribe Now Subscribe Today
Research Article
 

Factors Influencing Malaysian Consumers’ Intention Towards E-shopping



Muhammad Khalilur Rahman, Md. Abdul Jalil, Abdullah-Al-Mamun and S.D. Robel
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail
ABSTRACT

E-shopping is increasingly becoming most popular in Malaysia by supplanting the traditional store shopping behavior of the large number of customers. The main purpose of this study is to test the critical factors that are influencing the Malaysian consumers towards e-shopping. A total of 255 valid cases were selected for data analysis through self-administered questionnaires by using the random sampling method. The data were collected from those Malaysian consumers who had a minimum experience on e-shopping. Descriptive statistics was employed to identify the respondents’ demographic information. The data were examined using the associated principal components and exploratory factor analysis as well as computation on correlations to identify the factors that are influencing the Malaysian consumers on e-shopping, to determine the underlying dimensionality, convergent validity and discriminant validity. Importantly, this study employs the Structural Equation Modeling (SEM) technique to perform a confirmatory factor analysis and test the hypothesized positive correlation between the exogenous and the endogenous constructs. Based on the statistical analyses, the resultant findings revealed that cognitive, perceived usefulness and perceived ease of use had a positive impact on the e-shopping under the Malaysian context. The main contribution of this study is that it recommends a way to assess the integrity of the online vendors in order to frame further strategies that can conducively attract the Malaysian consumers to interact in the e-shopping activities. This study has proposed a hypothesized model that needs further investigation for future researches.

Services
Related Articles in ASCI
Similar Articles in this Journal
Search in Google Scholar
View Citation
Report Citation

 
  How to cite this article:

Muhammad Khalilur Rahman, Md. Abdul Jalil, Abdullah-Al-Mamun and S.D. Robel, 2014. Factors Influencing Malaysian Consumers’ Intention Towards E-shopping. Journal of Applied Sciences, 14: 2119-2128.

DOI: 10.3923/jas.2014.2119.2128

URL: https://scialert.net/abstract/?doi=jas.2014.2119.2128
 
Received: December 10, 2013; Accepted: March 14, 2014; Published: May 07, 2014



INTRODUCTION

The popularity of using e-shopping is rapidly increasing all over the world in which more than 60% of the people have been involved with e-shopping in the past two years (Admin, 2012). Malaysian people are increasingly becoming internet users in the present day world. Globalization and the advance of new technological developments have opened up a a new era of e-shopping (Ramayah and Ignatius, 2005) while the ease of obtaining information on goods and services, mostly through the internet, has considerably increased the growth of e-shopping globally, thus, opening the opportunity for further rapid changes in in the e-shopping industry to enable the trading system by way of facilitating to customize and distribute the products towards the customer-friendly trading industry while concurrently creating a healthy business competition among the online retailers (Al-Maghrabi et al., 2011), hence, the e-shopping customers can have a wider range of option to choose the products offered while the retailers are competing in an overcrowded market (Celik, 2011) with the subsequent result of mobilization of efforts by the retailers worldwide in consolidating their businesses in order to strengthen their scope of success in the online market and gain the advantage of the challenges that they can successfully overcome. However, in view of the low cost of managing the online retail business, it gives rise to a vast potential of possibilities to access the new and powerful channel of information and communication to both businesses and consumers (Al-Maghrabi et al., 2011), as well as to manufacturers and distributors through the internet as a tool for business entities to advertise their products more widely and effectively (Celuch et al., 2007). Furthermore, customers can have the flexibility on wider choices of products in terms of quality and price comparison through ease of access to information from different sources at their convenience without having to emcumber themselves with the restriction of time and space (Brynjolfsson and Smith, 2000). Hence, the new challenges facing the e-shopping industry are on maintaining the retention of loyalty by their customers for the online retailers and in order to attain this, it is important for the online retailers to specifically understand the factors that attract and encourage their consumers to repeat their online shopping as often as possible through various means, such as, price discount for purchase above certain amount or rewards on purchase certain nuber of goods in their e-shopping activities.

The acceptance of e-shopping varies between developed and developing countries (Celik, 2011), in which a number of research gaps need certain logical explanations in these countries (Alam et al., 2008). Ong (2010) stated that in the early 2010, the number of internet users was 17.5 million and internet buyers were 8.9 million according to the Malaysian online shopping statistics. Furthermore, the estimation on internet users was 18.3, 2011 and 18.9 million in 2012. Similarly, the estimation on internet buyers was 9.7, 2011 and 10.5 million in 2012. E-shoppers are distributed into five major job categories, such as, top management executives, business men, self-employed sector of the public, blue collar workers, retired and unemployed persons, housewives as well as other white collar workers (Ong, 2010), in which top management executives are the greatest online e-shoppers who are supposed willingly to use the internet for consumption of their chosen products and services, as a result of which they are quite proficient in accessing the internet for other various purposes. In fact, the understanding of the consumers' acceptance on the online shopping (Zhou et al., 2007) and assessing the driving forces behind the choice of virtual stores (Celik, 2011) are extremely important for the online retailers due to the intensive market competition. The development of marketing strategies on the online success is equally very important, especially, with respect to the achievement of success in the internet market. The understanding of acquiring knowledge on the e-shoppers' shopping behavior is essential for the customer relationship management (Zhou et al., 2007). Thus, having a clear understanding on how consumers influence the internet markets to make purchasing decisions in the electronic environment (Wu and Lin, 2006) would much help the marketing managers in deriving competitive and adequate marketing strategies for their respective e-businesses.

However, there is a series of researches on e-shopping but most of the researches are tailored to examine the customers’ attitudes and intentions towards e-shopping. This study is intended to provide data on the actual e-shopping behavior of the Malaysian internet users. The main objective of this study is to investigate the significant relationship of cognition, perceived usefulness and perceived ease of use in selecting e-shopping among the Malaysian consumers. The technology-oriented view of the consumers' acceptance of e-shopping is quite essential as without development of the associated technology, e-shopping business cannot expect to achieve its intended ultimate billion-dollar objective (Zhou et al., 2007). Internet users’ attitude towards perceived usefulness and perceived ease of use is highly significant, as it decides whether users are willing to use the internet as a tool for their shopping purpose. The technology’s usability and usefulness that can attract e-shoppers have been explained by a number of researchers (Celik, 2011; Ramayah and Ignatius, 2005) in which cognition has a positively significant impact on e-shopping (Rahman et al., 2013; Celik, 2011; Foucault and Scheufele, 2002; Limayem et al., 2000).

MATERIALS AND METHODS

Conceptual research framework
Cognition: Cognition is the ‘subjective act of the mind’ can be defined as the perceived opinion of others on the particular behavior in question (Chang and Chen, 2009; Chang et al., 2010) as cognition or the subjective act of the mind has a significant relationship on behavioral intention to e-shopping (Ramayah and Ignatius, 2005). Consumers are concerned on the risk and the uncertainty of the outcome when conducting transaction with e-shopping (Hansen et al., 2004), as the customer has no conclusive information on the trustworthiness of the online vendors and the authenticity of their products, thus, access to available reliable sources from the respective reference group is important for conducting e-shopping (Hansen et al., 2004), since the reference group can confidently influence the consumers who can get an accurate idea in performing their e-shopping without a lingering doubt. In addition, the reference group also can help consumers to confirm on the decision to buy the products from the e-shopping. Bosnjak et al. (2006) posited that youth consumers were more motivated than teenagers to engage in e-shopping, since teenagers’ decision could be favourably affected by their family when they were shopping online. Furthermore, consumers have more confident to use the internet for online shopping when their friends and relatives use the same medium of shopping (Foucault and Scheufele, 2002). Higher subjective act of the mind due to previous experiences can also influence consumers to make a decision on e-shopping (Chang et al., 2010). Malaysian consumers’ trend to rely on others and wait for suggestions with regards to doing something new can be a positive factor on the decicive intention of the consumers (Hasan and Rahim, 2008), hence, reference groups are the driving force for shoppers in e-shopping (Parsons, 2002). In view of the above preponderating factors, we have proposed the following hypothesis:

H1:Cognition has a significant relationship with the consumers’ intention to e-shopping

Perceived usefulness: Consumers usually prefer e-shopping to traditional store shopping (Rahman et al., 2013) and in this regard, Malaysian consumers are increasingly involved in e-shopping due to multifarious benefits, such as, free access of information, numerous choices made available with reasonable price quotations (Delafrooz et al., 2009), no necessity to move from place to place and not subjected to time constraints (Rahman et al., 2013; Shang et al., 2005), unlimited product order with a quick delivery system, thus, saving of time and money simultaneously (Hasan et al., 2009) and the benefits roll on and on. Absence of time constraint is highly emphasized in e-shopping, as consumers can conveniently access information and place orders to buy their chosen products at any time (McKinney, 2004; Rahman et al., 2013; Kim and Kim, 2004). Electronic shopping provides good service as compared to the competitive traditional stores since there is no wholesaler effect on it and as a result, the vendor can sell their products directly to the customers at a cheaper price (Hannah and Lybecker, 2010) and enhanced further by the reduction of shopping transportation cost (Zhou et al., 2007) which, incidentally makes it more convenient for the Malaysian consumers. Rahman et al. (2013) examined that perceived usefulness has a positive impact on e-shopping with standardized coefficient (beta) value of 0.106, based on the Malaysian consumers’ perspectives. Thus, the hypothesis test is proposed as follows:

H2:Perceived usefulness has a positive impact on consumers’ intention to e-shopping

Perceived ease of use: Perceived ease of use is the degree of essential effort in which consumers work with a stable physical and mental system (Rahman et al., 2013; Davis, 1989). In addition, perceived ease of use is defined as a person’s perception that using the new tools will be a free of effort activity to access the requuired information from the website (Davis, 1993). Perceived ease of use has a positive impact on consumers’ perceptions in e-shopping (Jun et al., 2004). Yulihasri et al. (2011) and Brown et al. (2007) posited that perceived ease of use has a positive and significant relationship with consumers’ behavioral perceptions on e-shopping. Rahman et al. (2013) analyzed that perceived ease of use is positively related with e-shopping with respect to standardized coefficient value of 0.154 and Chronbach’s alpha value of 0.834. In fact, perceived ease of use is a system through which the consumers can easily access information to make purchasing decision (Lin and Chou, 2009). Perceived ease of use is related to the intrinsic motivation with system experience in facilitating the expected outcome (Venkatesh and Davis, 2000). With regards to e-shopping, website plays an important role through the characteristics of search functions, download speed and navigation (Zeithaml et al., 2002). There are some important components of perceived ease of use which are pointed out by Rahman et al. (2013), such as, process, manageability, elasticity and speedy system mastery. Malaysian consumers can be motivated to experience e-shopping through easy access to detailed information on products and service facilities. Based on this we have proposed the following hypothesis:

H3:Perceived ease of use has a significant relationship with the consumers’ intention to e-shopping

Research design is the blueprint on how the study should be conducted wherein it includes the method (Alotaibi et al., 2013). In this stage, the main purpose of the research is to investigate factors that much influence the Malaysian consumers to e-shopping intention. Self-administered questionnaires had been prepared for distribution to the chosen respondents consisting of various races in order to obtain the relevant primary data by using a random sampling method (Malay, Chinese and Indian). The respondents were Malaysian citizens who had a minimum experience in e-shopping in the federal territory of Kuala Lumpur. In this survey, a 6-point likert-scale ranging from “strongly disagree” to “strongly agree” had been used. Malaysians are increasingly involved in e-shopping today. However, based on the previous study, this research has been developed on a conceptual model of critical factor influencing the e-shopping intention among Malaysian consumers. The proposed hypothesized model (Fig. 1) emphasizes on the constructs of cognition, perceived usefulness and perceived ease of use all of which have positive impacts on the e-shopping which is here with proposed for hypothesis testing.

Furthermore, invitations to participate in this survey in the form of 400 questionnaires had been sent to Malaysian consumers through online groups, social networks and e -mail messages.

Image for - Factors Influencing Malaysian Consumers’ Intention Towards E-shopping
Fig. 1: Proposed hypothesized model

A total sample size of 400 respondents from whom 345 questionnaires had been returned in which 255 valid cases had been considered for data analyses after the screening process which represented a success rate of 74% that was considered good in view of the time, cost and geographical constraints. The demographic information of the respondents had been accordingly analyzed by applying the frequency distribution method as well as the factor analysis method which had been used in this study for purposes of solving the analytical process of transforming measurement data into linear combination constructs (Jalil et al., 2013). Hair et al. (1992) and Jalil et al. (2013) stated that factor analysis was a reliable statistical method used for combining a large number of populations into a smaller number of factors with a minimal loss of information. In this study a Structural Equation Modeling (SEM) approach had been used to investigate the relationships between the constructs which may have influenced the Malaysian consumers’ intention to e-shopping through the internet.

RESULTS AND DISCUSSION

Demographic information: The demographic information of Malaysian consumers’ intention to e-shopping was examined by using the frequency distribution method. Table 1 shows that a total number of 255 respondents, approximately 56% of them were male and 44% were female. Among the large number of participants, 32% of them consisted of 24 to 34 years old. The 59.4% majority of the online users were married. In terms of ethnic group, Malay accounted for 39% followed by 36% Chinese and 26% Indians, respectively.

Table 1 shows that 49% of the respondents held bachelor degrees. The monthly income of 47% of the participants was between RM 1000 and RM 2400. Last but not least, with regards to e-shopping experience, 47% of the participants had 1 to 3 years of shopping experience. For the online product purchase behavior, the result shows that 39% of the respondents had purchased air tickets followed by 24% had purchased electronics items, 22% had purchased movie tickets and 10% had purchased book/DVD, respectively.

Reliability coefficient: Reliability coefficient had been applied to test on determining the internal stability and consistency of the survey questionnaires by using the likert-scale (Noor, 2009; Sekaran, 2003). In order to measure the reliability of a set of two or more factors, the Cronbach’s alpha is a commonly used method where values of alpha should be between 0 and 1, with higher values indicating higher reliability among the indicators (Hair et al., 1992). In accordance with the Cronbach’s alpha test, the total scale value was 0.872 for all constructs of the study which indicated an overall higher reliability coefficient (Table 2).

The level of ‘reliability' of all the items under consideration should be firstly measured before conducting the observed variables. Hair et al. (1992) pointed out that the more reliable the measure was, the greater would be the consistency. The reliability coefficients (Cronbach’s alpha) were estimated for the items of different variables which formed Table 2 in which three factors, namely, cognition, perceived usefulness and perceived ease of use reached the scale of 0.710, 0.808 and 0.793, respectively, thus, indicating the high reliability coefficient for measuring each construct, since a minimum Cronbach’s alpha value of 0.70 was recommended by the study (Nunnally and Bernstein, 2010; Jalil et al., 2013).

Factor analysis: The results obtained from the 255 respondents were thoroughly investigated and the outputs of the results were clearly established by applying the SPSS and the SEM approach in selecting the Principle Component Analyis (PCA) which was carried out to explore the underlying factors associated with the 15 items in this study. The constructs' validity was tested using the Bartlett’s Test of Sphericity and the Kaiser-Myer-Olkin measure of sampling adequacy to analyze the strength of assiciation among the constructs. The KMO measure of sampling adequacy was first performed to identify the accuracy and suitability of using the factor analysis. In order to achieve the rule, KMO value should be raised to 0.60 or greater to perform the analysis and in case the value was less than 0.60, KMO is then used to assess the drop to the lower anti image value from the model due to multicollinearity problem (Rahman et al., 2010; Jalil et al., 2013). The results of the tests are as shown in Table 3 which indicates that the KMO and Bartlett’s test of sphericity was highly significant, thus, it was suitable for the factor analysis. The higher values of the items are very important, as they indicate the strongly significant relationship with the factor.

Table 1: Demographic information of Malaysian e-shopping consumers
Image for - Factors Influencing Malaysian Consumers’ Intention Towards E-shopping

Table 2: Reliability test
Image for - Factors Influencing Malaysian Consumers’ Intention Towards E-shopping

Table 3: KMO and Bartlett’s test
Image for - Factors Influencing Malaysian Consumers’ Intention Towards E-shopping

The findings of the study indicate that there are three factors (cognition, perceived usefulness, perceived ease of use) which are consistently loaded to different factor solutions and all are proven to have signiciant relationships with the perception of e-shopping consumers. Hair et al. (2010) and Haque et al. (2012) recommended that variables with a loading greater than 0.50 are very significant. In this study, the criteria were acceptable for all of the items with the loading of 0.60 and greater (Table 4).

Structural Equation Modeling (SEM): SEM is a mathematical model that represents an objective state of affairs which can influence other objectives in a more congruent and scientific manner (Mulaik, 1994). Furthermore, SEM is the most popular and powerful statistical analytical tool that was specifically developed for analyzing multiple variables in a research model (Awang, 2012). The validity and reliability of the variables should be assessed before conducting any latent variable (Haque et al., 2012). The convergent validity and discriminant validity should also be assessed after conducting the unidimensionality and the reliability tests (Anderson and Gerbing, 1982). Unidimensionality measures the degree in which the items of constructs in a scale entirely measured the similar construct (Haque et al., 2012; Venkatraman, 1989). Confirmatory Factor Analysis (CFA) was used to assess unidimensionality. In this study, the CFA was used to measure 15 indicators of the three constructs whether they were assigned appropriately. To estimate the CFA model, maximum likelihood estimation was employed by using SEM 18. The CFA was used to evaluate the fitness of model (Measurement model and structural model) in which three fit indices (Absolute fit, incremental fit and parsimonious fit) were used by including at least one index from each category of model fit that was recommended by Holmes-Smith et al. (2006), Hair et al. (1995) and Awang (2012). Generally, the CFA is assessed by using the index categories, such as, Normed Chi-square, p-value, Root Mean Square of Error Approximation (RMSEA), Comparative Fit Index (CFI), Goodness of Fit Index (GFI) and Adjusted Goodness of Fit Index (AGFI). Content validity is associated with the degree in which the content of other indicators considers the proposed concept (Burns and Bush, 2000). Content validity provides the confidence that represents the perfect score (Hair et al., 2006). The selection of items of each variable in this study is based on a general literature review, giving a strong content validity to the constructs being assessed (Haque et al., 2012; Rahman et al., 2010). CFA can be used to evaluate convergent validity (Haque et al., 2012). Hair et al. (2006) stated that convergent validity was used throughout factor loadings, reliability and unidimensionality. In addition, the convergent validity can be achieved through the average variance extracted being greater or equal to 0.50 which is recommended by Awang (2012).

Table 4: Rotated component matrix of three-factor solutions
Image for - Factors Influencing Malaysian Consumers’ Intention Towards E-shopping
Extraction method: Principal component analysis based on three factors specification, Rotation method: Varimax with Kaiser normalization

Image for - Factors Influencing Malaysian Consumers’ Intention Towards E-shopping
Fig. 2: Measurement model

Measurement model: There are two options in the process of model refinement (Kline, 2005; Awang, 2012). The first option is the removal of ‘path’ with lower correlations while the second option is the elimination of observed variables which may have a multi-collinearity problem and the need to re-specify the measurement model. In this study, all items of each construct were derived from the Exploratory Factor Analysis (EFA) which specified the best fit the measurement model as shown in Fig. 2. In this measurement model, all path coefficients (COG, PU and PEU) are positively significant at p = 0.05. Furthermore, factor loadings for most of the items of the constructs are greater than 0.40 which indicates that the model is amplified. Moreover, each category of model fit has achieved the recommended level. For example, normed chi-square is 1.057 which indicates a very good fit, since normed chi-square should be less than 5 (Hair et al., 2010; Awang, 2012; Haque et al., 2012). The associated p-value is 0.339 which has also achieved the requirement level. Hair et al. (2010), Awang (2012) and Haque et al. (2012) recommended that p-value should be greater than 0.05. RMSEA value is 0.015 which also indicates the good fit of the model in relation to the degree of freedom (Hair et al., 2010; Awang, 2012; Haque et al., 2012). The CFI, GFI and AGFI values are 0.992, 0.953 and 0.935, respectively which prove a positively good fit of the model, as the values of CFI, GFI and AGFI are greater than 0.90 as the benchmark of a good fit (Hair et al., 2010; Awang, 2012; Haque et al., 2012) (Fig. 2 and Table 5).

Structural model: The structural model is developed to examine the direction of assumed relationship between latent variables (cognition, perceived usefulness and perceived ease of use).

Table 5: Reliability test
Image for - Factors Influencing Malaysian Consumers’ Intention Towards E-shopping

Table 6: Standard estimation of the structural model
Image for - Factors Influencing Malaysian Consumers’ Intention Towards E-shopping

Image for - Factors Influencing Malaysian Consumers’ Intention Towards E-shopping
Fig. 3: Structural Model. Degree of relationship between customers’ perception towards cognition (COG), perceived usefulness (PU), perceived ease of use (PEU) and consumers’ intention to e-shopping (CIE)

In this structural model, the arrows are assumed to support that cognition (COG), Perceived Usefulness (PU) and Perceived Ease of Use (PEU) all of which have significant impacts on the Consumers’ Intention to E-shopping (CIE) in the Malaysian context. The model indicates that perceived usefulness has a strong significant relationship with the customers’ intention to e-shopping with regards to a standardized path coefficient value of 0.67 in which the probability of getting a critical ratio as large as 5.857 in absolute value is less than 0.001 (Table 5). Cognition and perceived ease of use also have positive relationships with the e-shopping with standardized beta values of 0.53 and 0.39, respectively. Therefore, the results show that a significant positive coefficient exists between the importance of a dimension to the consumers and the perception to e-shopping in the Malaysian context (Fig. 3, Table 6).

This study has examined the relationships between the key elements of cognition, perceived usefulness and perceived ease of use and their impacts on the Malaysian consumers’ intention to e-shopping. According to the structural model as shown in Fig. 3, it is assumed that the default model is correct as the probability of getting a normed chi-square is 1.111 whereas the p-value is 0.142 which indicates a very good fit, since the discrepancy should be less than 5 and the p-value should be greater than 0.05 (Hair et al., 2010; Haque et al., 2012). With regards to RMSEA value of 0.021, it shows that it has achieved a level of acceptance indicating a good fit of the model, since RMSEA having a value of equal to or less than 0.08 proves a good fit in relations to the degree of freedom (Hair et al., 2010; Awang, 2012; Haque et al., 2012) and the CFI value of 0.973 proves to be a very good fit as well. Kline (2005), Awang (2012) and Haque et al. (2012) stated that a CFI value greater than 0.90 indicated a good fit of the model. GFI value of 0.927 and AGFI value of 0.909 have also achieved a level of acceptance, respectively (Table 5), since, GFI and AGFI having values greater than 0.90 are considered as a very good fit for the model (Joreskog and Sorbom, 1984; Hair et al., 2010; Awang, 2012; Jalil et al., 2013).

CONCLUSION

In the present day world, more and more people are becoming avid internet users wherein the usage of e-shopping is rapidly increasing throughout the associated technological development in Malaysia. In this study, based on the extant literature review, a hypothesized model is developed and tested by using the primary data through a self-administered questionnaire survey covering the principal attributes of the Malaysian consumers’ intention to e-shopping. The study employed SEM to statistically validate the proposed causal relationship between the constructs. The findings also help to create a clear understanding of the Malaysian consumers’ intention to e-shopping. In this study, it is found that the cognition or subjective act of the mind influences the Malaysian consumers’ intention to e-shopping; hence, e-shopping vendors should be more careful in promoting subjective act of the mind, because the tendency of the Malaysian consumers’ trend is to favorably rely on others for suggestions with regards to doing or purchasing something.

In the academic era, all studies cannot be achieved perfectly and this study is no exception beyond those limitations. The proposed hypothesized model for this study is validated by collecting primary data throughout via e-mail, social network and randomly distributed questionnaires to the e-shopping consumers in the federal territory in Kuala Lumpur and due to time constraint, it may, to a certain extent, impact the generalization, if any, of the findings from this study on the Malaysian consumers’ context. Furthermore, due to the small sample size and random sampling method of data collection, there is a possibility of biasness being present in the subsequent results of the research. Therefore, a larger sample size of the selected population is needed to obtain better results for future studies. For the managerial implication, the findings of the study can provide e-shopping vendors with drafting various managerial policies to increase influences on e-shopping entities as e-shopping vendors should prudently plan to develop cognition, perceived usefulness and perceived ease of use (ease website surfing, provide accurate information) for all levels of consumers. However, this study offers a coherent support for the proposed hypothesized model and statistical foundation for performance of comparative exercises in future researches.

REFERENCES
1:  Admin, 2012. Importance and popularity of online shopping websites in today's world. E-Commerce by Admin, BlazeMates, January 10, 2012. http://www.blazedream.com/blog/importance-and-popularity-of-online-shopping-websites-in-today%E2%80%99s-world/.

2:  Alam, S.S., Z. Bakar, H.B. Ismail and M. Ahsan, 2008. Young consumers online shopping: An empirical study. J. Internet Bus., 5: 81-98.

3:  Al-Maghrabi, T., C. Dennis and S.V. Halliday, 2011. Antecedents of continuance intentions towards e-shopping: The case of Saudi Arabia. J. Enterprise Inform. Manage., 24: 85-111.
CrossRef  |  

4:  Alotaibi, F., R.Z. Yusoff and R. Islam, 2013. Relationship between total quality management practices and contractors competitiveness. Am. J. Applied Sci., 10: 247-252.
CrossRef  |  Direct Link  |  

5:  Anderson, J.C. and D.W. Gerbing, 1982. Some methods for respecifying measurement models to obtain unidimensional construct measurement. J. Market. Res., 19: 453-460.
Direct Link  |  

6:  Awang, Z., 2012. A Handbook on SEM: Structural Equation Modeling. 4th Edn., Centre For Graduate Studies, Kuala Lumpur, Malaysia.

7:  Brown, D., G. Oleksik and D. Bisdee, 2007. Consumer attitudes review: Internet shopping-annexe E. Office of Fair Trading, London, UK., June 2007, pp: 1-147. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.106.2145&rep=rep1&type=pdf.

8:  Bosnjak, M., D. Obermeier and T.L. Tuten, 2006. Predicting and explaining the propensity to bid in online auctions: A comparison of two action‐theoretical models. J. Consum. Behav., 5: 102-116.
CrossRef  |  Direct Link  |  

9:  Brynjolfsson, E. and M.D. Smith, 2000. Frictionless commerce? A comparison of Internet and conventional retailers. Manage. Sci., 46: 563-585.
CrossRef  |  Direct Link  |  

10:  Burns, A.C. and R.F. Bush, 2000. Marketing Research. 3rd Edn., Prentice Hall Inc., New Jersey, USA.

11:  Celik, H., 2011. Influence of social norms, perceived playfulness and online shopping anxiety on customers' adoption of online retail shopping: An empirical study in the Turkish context. Int. J. Retail Distrib. Manage., 39: 390-413.
CrossRef  |  Direct Link  |  

12:  Celuch, K., S. Goodwin and S.A. Taylor, 2007. Understanding small scale industrial user internet purchase and information management intentions: A test of two attitude models. Ind. Market. Manage., 36: 109-120.
CrossRef  |  

13:  Chang, H.H. and S.W. Chen, 2009. Consumer perception of interface quality, security and loyalty in electronic commerce. Inform. Manage., 46: 411-417.
CrossRef  |  

14:  Chang, M.L., M. Lai and W.Y. Wu, 2010. The influences of shopping motivation on adolescent online-shopping perceptions. Afr. J. Bus. Manage., 4: 2728-2742.
Direct Link  |  

15:  Davis, F.D., 1989. Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quart., 13: 319-340.
CrossRef  |  Direct Link  |  

16:  Davis, F.D., 1993. User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. Int. J. Man Mach. Stud., 38: 475-487.
CrossRef  |  Direct Link  |  

17:  Delafrooz, N., L.H. Paim, S.A. Haron, S.M. Sidin and A. Khatibi, 2009. Factors affecting students' attitude toward online shopping. Afr. J. Bus. Manage., 3: 200-209.
Direct Link  |  

18:  Foucault, B.E. and D.A. Scheufele, 2002. Web vs campus store? Why students buy textbooks online. J. Consum. Market., 19: 409-423.
CrossRef  |  

19:  Hair, J.F., R.E. Anderson, R.L. Tatham and W.C. Black, 1992. Multivariate Data Analysis. 3rd Edn., MacMillan Publishing Company, New York, USA.

20:  Hair, J.F., W.C. Black, B.J. Babin and R.E. Anderson, 2010. Multivariate Data Analysis: A Global Perspective. 7th Edn., Pearson Education Inc., Upper Saddle River, NJ., USA., ISBN-13: 9780135153093, Pages: 800.

21:  Hair, J.F., R.E. Anderson, R.L. Tatham and W.C. Black, 1995. Multivariate Data Analysis with Readings. 4th Edn., Prentice-Hall Inc., Upper Saddle River, New Jersey, USA.

22:  Hair, J.F., R. Bush and D. Ortinan, 2006. Marketing Research within a Changing Information Environment. 3rd Edn., McGraw-Hill, New York.

23:  Haque, A., A.A. Sarwar, F. Yasmin, A. Anwar and Nuruzzaman, 2012. The impact of customer perceived service quality on customer satisfaction for private health centre in Malaysia: A structural equation modeling approach. Inform. Manage. Bus. Rev., 4: 257-267.
Direct Link  |  

24:  Hannah, B. and K.M. Lybecker, 2010. Determinants of recent online purchasing and the percentage of income spent online. Int. Bus. Res., 3: 60-71.

25:  Hansen, T., J.M. Jensen and H.S. Solgaard, 2004. Predicting online grocery buying intention: A comparison of the theory of reasoned action and the theory of planned behavior. Int. J. Inform. Manage., 24: 539-550.
CrossRef  |  

26:  Hasan, H.H. and S.A. Rahim, 2008. Factors affecting online purchasing behavior. Malaysian J. Commun., 24: 1-19.

27:  Holmes-Smith, P., L. Coote and E. Cunningham, 2006. Structural equation modeling: Form the fundamental to advanced topics. School Research, Evaluation and Measurement Services (SREAMS), Melbourne, Australia.

28:  Jalil, M.A., D.A. Razak and S.F. Azam, 2013. Exploring factors influencing Financial planning after retirement: Structural equation modeling approach. Am. J. Applied Sci., 10: 270-279.
Direct Link  |  

29:  Joreskog, K. and D. Sorbom, 1984. LISREL-VI User's Guide. Scientific Software, Mooresville, IN., USA.

30:  Jun, M., Z. Yang and D.S. Kim, 2004. Customers' perceptions of online retailing service quality and their satisfaction. Int. J. Qual. Reliabil. Manage., 21: 817-840.
CrossRef  |  

31:  Kim, E.Y. and Y.K. Kim, 2004. Predicting online purchase intentions for clothing products. Eur. J. Market., 38: 883-897.
CrossRef  |  

32:  Kline, R.B., 2005. Principles and Practice of Structural Equation Modeling. 2nd Edn., Guilford Press, New York.

33:  Limayem, M., M. Khalifa and A. Frini, 2000. What makes consumers buy from Internet? A longitudinal study of online shopping. IEEE Trans. Syst. Man Cybernet. Part A: Syst. Hum., 30: 421-432.
CrossRef  |  Direct Link  |  

34:  Lin, P.C. and Y.H. Chou, 2009. Perceived usefulness, ease of use and usage of citation database interfaces: A replication. Electr. Lib., 27: 31-42.
CrossRef  |  Direct Link  |  

35:  McKinney, L.N., 2004. Creating a satisfying internet shopping experience via atmospheric variables. Int. J. Consum. Stud., 28: 268-283.
CrossRef  |  

36:  Mulaik, S., 1994. Kant, Wittgenstein, Objectivity and Structural Equation Models. In: Cognitive Assessment: A Multidisciplinary Perspective, Reynolds, C.R. (Ed.). Plenum Press, New York, USA., ISBN-13: 9780306444340, pp: 209-236.

37:  Noor, A., 2009. Statistical Methods in Research. Pearson, Petaling Jaya, Malaysia.

38:  Nunnally, J.C. and I.H. Bernstein, 2010. Psychometric Theory. 3rd Edn., Tata McGraw-Hill Education, New Delhi, India.

39:  Ong, K., 2010. Online shopping statistics in Malaysia. http://humanwebsite.com.my/blog/online-shopping-statistics-in-malaysia.html.

40:  Parsons, A.G., 2002. Non-functional motives for online shoppers: Why we click. J. Consum. Market., 19: 380-392.
CrossRef  |  

41:  Rahman, M.S., A.H. Khan and N. Islam, 2013. An empirical study on revealing the factors influencing online shopping intention among Malaysian consumers'. J. Hum. Social Sci. Res., 1: 9-18.
Direct Link  |  

42:  Rahman, S., A. Haque and I.S. Ahmed, 2010. Exploring influencing factors for the selection of mobile phone service providers: A SEM approach on Malaysian consumers. Afr. J. Bus. Manage., 4: 2885-2898.
Direct Link  |  

43:  Ramayah, T. and J. Ignatius, 2005. Impact of perceived usefulness, perceived ease of use and perceived enjoyment on intention to shop online. ICFAI J. Syst. Manage., 3: 36-51.

44:  Sekaran, U., 2003. Research Methods for Business: A Skill-Building Approach. 4th Edn., John Wiley and Sons, Inc., New York, USA., ISBN-13: 9780471384489, Pages: 450.

45:  Shang, R.A., Y.C. Chen and L. Shen, 2005. Extrinsic versus intrinsic motivations for consumers to shop on-line. Inform. Manage., 42: 401-413.
CrossRef  |  Direct Link  |  

46:  Venkatesh, V. and F.D. Davis, 2000. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Manage. Sci., 46: 186-204.
CrossRef  |  Direct Link  |  

47:  Venkatraman, N., 1989. Strategic orientation of business enterprises: The construct, dimensionality and measurement manage. Manage. Sci., 35: 942-962.
CrossRef  |  

48:  Wu, L.L. and J.Y. Lin, 2006. The quality of consumers' decision-making in the environment of e-commerce. Psychol. Market., 23: 297-311.
CrossRef  |  Direct Link  |  

49:  Zeithaml, V.A., A. Parasurarnan and A. Malhotra, 2002. Service quality delivery through web sites: A critical review of extant knowledge. J. Acad. Market. Sci., 30: 362-375.
CrossRef  |  Direct Link  |  

50:  Zhou, L., L. Dai and D. Zhang, 2007. Online shopping acceptance model: A critical survey of consumer factors in online shopping. J. Elect. Commer. Res., 8: 41-62.
Direct Link  |  

51:  Yulihasri, M.A. Islam and K.A.K. Daud, 2011. Factors that influence consumer buying intention on shopping online. Int. J. Market. Stud., 3: 128-139.
Direct Link  |  

52:  Hasan, R., R. Sion and M. Winslett, 2009. The case of the fake Picasso: Preventing history forgery with secure provenance. Proceedings of the 7th USENIX Conference on File and Storage Technologies, February 24-27, 2009, San Francisco, CA., USA., pp: 1-14.

©  2021 Science Alert. All Rights Reserved