Site Information Influencing on Purchase Intention - Example
Organic Agricultural Products
Tsui-Ying Huang1*, Ting-Han Wang2, Tsai-Yu Hsaio3, Yu-Ying Tseng3, Hsin-Yi
Lin3
1.2.3
Department of Bio-Industry and Agribusiness Administration, National Chiayi University
No.580, Xinmin Rd., West Dist., Chiayi City 600, Taiwan (R.O.C.)
*Corresponding Author: tyhuang2882@gmail.com
ABSTRACT
The purpose of this paper is to investigate the integrity of site information related to
consumers’ purchase intention to buy organic products. By using questionnaire
investigation, we surveyed 362 subjects and received 362 questionnaires. EKB model
is used as configuration to prove the causal relationship among constructs. As a result,
the findings showed that before buying organic products, people had to search for
information, which had a positive relationship with the integrity of site information
and purchase motivation. In conclusion, E-business is important for customers to buy
organic products and the integrity of site information has a positive relationship with
purchase motivation. In addition, purchase motivation has a positive relationship with
purchase intention.
Keyword: E-business, Information Search, Purchase Motivation, Purchase Intention
1. INTRODUCTION
In recent years, the ratios that consumers use the Internet are getting higher. In
addition, many enterprises have also set up on-line shops to sell or advertise products
in real shops. Recently, because of the change of lifestyle of Taiwanese consumers,
they make choices of their own when it comes to health-oriented organic products.
Under the rapid development of the Internet, consumers have increasingly
focused on other consumers’ “ratings". Information search has become important and
contributes to the willingness of purchase intention; that is, product information
regarding the containment as complete as possible tends to enhance purchase intention.
Overall, the format that contains product information as thorough as possible is able
to meet purchasers’ requirements immediately and increase instant effect on site
1
viewer counts(Doll & Torkzadeh, 1988) [6].
The purpose of this paper is to explore the ways to construct the e-commerce
system of the organic agricultural industry and to propose methods of strengthening
website content to reduce barriers of consumers. Through purchasers’ search for
agricultural knowledge, it can affect the purchase intention as to increase purchase
amount. It is believed that purchase intention serves as a predictor of purchase
behavior. This study aims to understand consumers’ viewpoints. Quantity which is
increased out of the willingness of consumers results from the thoroughness of its
content and conditions provided along with the product (Lin & Chen, 2006) [15].
2. LITERATURE REVIEW
(1). Information Research
On the one hand, Information search can be divided into internal information
search and external information search (Blackwell, Miniard, & Engel, 2006) [3].On
the other hand, sources of information can also be divided into active information
search and passive information
searches (Wilson, 2000) [23].As consumers make
decisions, they usually memorize their previous purchase experience or cognition
before (Murray, 1991) [18].
When consumers purchase products, they are used to searching information
about environmental investigations; background knowledge and pay attention to the
information which generates the perception and the degree of effort (Beatty & Smith,
1987) [2]. External information searches sources of information available. This means
that commercial and interpersonal matrix analysis can be divided into four major
categories (Blackwell et al., 2006) [3].
Format1: External Information Search
Interpersonal Relationship
Strong
Interpersonal Relationship
Week
Commercial
Nature
Sales Person
Manufacturers to Provide
Information
No Commercial
Nature
No Related Commodity
Business Staff
General Media
Based on the above literature, our study defines information search that
2
influences consumers’ purchase intention plays a major role in their purchase decision
making.
(2). On-line Shopping
According to different scholars, network shopping have many interpretation
methods; online shopping, for example, can also be called as network marketing
(Sohn et al., 1997) [20]. It means the way in which the Internet conveys advertising
messages or publishes promotional activities in order to attract consumers to complete
transactions, andpayment procedures.
Hsin (2001) [10] defined the On-line shopping that consumers conducted as the
Internet’s fucntions to receive the message as well as to contact with manufacturers
directly online or indirectly through other network. We define network shopping as
consumers’direct or indirect access to the relevance information and thus behavior
patterns lead to intention of purchasing goods or services.
(3). Website Information Integrity
A. Site Information
Spieß, Büchel, & Frick (2000) [21] and Chen & Tan (2004) [5] proposed that
information is uncertain. In order to reduce the uncertainty of consumers' purchasing
decisions, it is important for e-commerce sellers to have well-developed operating
strategies. For consumers, when it comes to the behavior of Internet shopping,
available information signifies an important way to communicate with sellers.
One of the goals of the present study is to show that based on the strengthened
quality of website information, information integrity can thereby increase consumers’
willingness to buy.. Network transfer transaction does not subject to time and place
restrictions, which thus
allows for more instant,new, and interactive nature (Bloch,
1996) [4]. As Kalakota & Whinston (1999) suggested, the more communication
between buyers and sellers the more cost can be reduced effectively. the enhance the
quality of goods and speed up the service of delivery ( [11] This, in return, helps to
extend new markets and provide more opportunities to sell services (Hornback, 1995
[9]; Kosiur, 1997) [13].
Scholars(Aladwani & Palvia, 2002) [1] who aimed to have good quality of
Internet shopping site reminded us to consider four dimensions: (a) technical
adequacy (Technical Adequacy): that includes for example, good functional
3
interaction mechanisms (message boards, forum, etc.), security trading mechanism,
convenient payment pickup mechanism; (b) the quality of the content (Web Content):
Website content is accurate and up-to-date; (c) the specific content of Web Content:
detailed product information, service information, clear price bids, company
information and contact information, and customer policy information (such as:
Privacy Policy, etc.); (d) appearance (Web Appearance): Web fonts, colors, layout.
We value that site information and trading platform of the site maintain transaction
security, good interactive features (message board), timeliness, detailed product
information, and streamlined layout configuration.
B.
Organic Knowledge
In our study, we define organic products as two-fold: sas
(1) void of chemical
fertilizers and pesticides,and (2) following the laws of nature and the ecological
mechanisms of the production of agricultural crops, including, e.g., organic rice, fruits
and vegetablesWe devide fruits and tea into four categories: organic produce;
products packaging, (they must be accompanied with CAS organic agricultural
products mark as the certification mark.)
(4). Purchase Motivation
Stone (1954) [22] is the first one to study Motives, and afterwards many scholars
have also joined the ranks of the research motivation since Stone cultivated this area
of research. Hawkins et al. (2001) [8] believed that the purchase motivation was the
reason that drove consumers to buying behavior. Blackwell et al., (2006) [3] proposed
that the purchase motivation was the driving force to meet the physical and
psychological needs of consumers to purchase products and services.
Rohm and Swaminathan (2004) [19] studied how “convenience” was an
important factor in online shopping communities, Consumers does not have to go out
to buy products and/or services since convenience means time saving.
Morganosky
and Cude’s (2000) [16] study once again confirmed that the primary factors of
convenience and time efficiency are crucial for online shopping.
(Li et al., (1999) [14] studied that consumers are very sensitive to the price – the
lower the price of products, the higher the chance of the success of the purchase.
Korgaonkar (1981) [12] expressed his appreciation of the advantages that online
shopping and could offer. As it can be removed from the fixed prices of store business,
4
a more favorable price is offered to attract the online shoppers. In our study, we define
purchase motivation as consumers’ purchase to meet their wants. We also discuss the
factors of convenience-orientedness and economic-orientedness.
(5). Purchase Intention
Fishbein and Ajzen (1975) [7] defined willingness (Intention) as the personal
subjective awareness of the probability of a particular behavior. By extending the
same concept, the intention to purchase (Purchase Intention) is the size of the
probability of the specific consumers’ subjective awareness buying behavior.
Morwitz and Schmittlein (1992) showed that the purchase intention could predict
actual purchase behavior, marketing research, and the willingness to buy, which is
often used to measure and predict the buying behavior construct. Our study defines
purchase intention as measuring the possibility of consumers in the Internet to buy
organic produce – the higher the purchase intention to buy the greater the probability.
3. MATH
According to the research framework and review of the literature, there are thus
four hypotheses in our study:
Web
Information
nnnnnn
H1
Information
Search
H3
Purchase
Motivation
H4
Purchase
Intention
H2
H1: Information search has positive influence on the Website information integrity;
H2: Information search has positive influence on the purchase motivation;
H3: Website information integrity has positive influence on the purchase intention;
H4: Purchase motivation has positive influence on purchase intention.
For the saje of prudence, this study had issued 45 pre-test questionnaires so as to
adjust the questionnaires in accordance with the opinions given by the subjects.
In our study, consumers in Taiwan are the target of respondents. The sample
selection we used was non-random network questionnaire and field work. The time
5
when we distributed the questionnaires was from July 2011 to August 25, 2011. We
received 400 questionnaires in total; among them 392 questionnaires delete invalid
questionnaires whereas 362 were valid questionnaires; the effective rate was 90.5%.
4. DATA ANALYSIS
(1). Reliability and Validity Analysis
In our study, we used Cronbach’s α coefficient reliability analysis. Cronbach’s α
breakdowns if more than 0.7, credibility is very high, ranging from 0.5 to 0.7, as a
trusted; 0.35 to 0.5 between said slightly credible. Website information integrity,
purchase motivation, information search and purchase intention construct reliability
0.840;0.701;0.757 and 0.881, respectively, which are more than 0.7, indicating very
high credibility constructs, which suggests our questionnaire have consistency and
reliability.
The validity of our study is the use of confirmatory factor analysis to determine
the construct validity and to test the model fit test. Table II shows after MI value of
the adjustment, the model has a good fit, and does not need to be adjusted.
(2). Research Model Results Analysis
In our study, all of the four assumptions were verified.
Table 2: Indicators Measure the Construct Validity of Dimension Reference and
Analysis
Independent Variable
Website Information
Integrity
A6
A7
A8
A9
Purchase Motivation
B1
B2
B3
A5
MLE
Factor Loading
Error
CR
AVE
CFI
0.80
0.63
0.73
0.81
0.83
0.53
0.65
0.70
CMIN/DF=0.623
GFI=0.998
AGFI=0.991
CFI=1.000
0.80
0.63
RMSEA=0.000
0.77
0.75
0.83
0.44
0.25
0.57
0.69
0.19
0.06
6
0.38
CMIN/DF=0.951
GFI=0.991
AGFI=0.987
CFI=1.000
RMSEA=0.000
Information Search
C1
C2
C3
C5
Purchase Intention
D1
D2
D3
A1
0.80 0.42
0.73
0.70
0.60
0.56
0.53
0.49
0.36
0.31
GFI=0.997
AGFI=0.984
CFI=0.999
RMSEA=0.024
0.77
0.87
0.92
0.74
0.21
CMIN/DF=1.201
0.55
0.76
0.85
0.55
0.04
CMIN/DF=0.710
GFI=0.998
AGFI=0.990
CFI=1.000
RMSEA=0.000
In the structure of model fit analysis CMIN / DF = 1.39, GFI = 0.962, AGFI =
0.945, CFI = 0.986, RMSEA = 0.033. it demonstrated the model fit is good.
Information search has positive influence on the Website information integrity;
information search has positive influence on the purchase motivation; website
information integrity has positive influence on the purchase intention; and purchase
motivation has positive influence on purchase intention.
5. CONCLUSION
In our research, we found organic produce market is an emerging market that
consumers tend to show a high sense of distrust. However, as consumers began to
search information, such as media reports, recommendations from experts, and
scholarly journals. In shops, consumers may compare and contrast products to
increase purchase intention to buy organic produce.
We also found that the consumers who had experience in buying organic product
through the Internet possessed richer organic knowledge than their real-shop
counterparts. When consumers considered time and price on which they spend in
e-shops,, consumers’ purchase intention would become higher.
At least, our study indicates that consumer’s search for information made by
themselves exerted a positive effect on the purchase decision process. If consumers
did not get the results they expect, it may weaken their intention to buy organic
produce.
REFERENCES
7
[1]. Aladwani, A. M., & Palvia, P. C. (2002). Developing and validating an
[2].
[3].
[4].
[5].
instrument for measuring user-perceived web quality. Information &
Management, 39(6), 467-476.
Beatty, S. E., & Smith, S. M. (1987). External search effort: An investigation
across several product categories. Journal of consumer research, 83-95.
Blackwell, R. D., Miniard, P. W., & Engel, J. F. (2006). Consumer behavior, 10.
Aufl., Mason.
Bloch, I. (1996). Information combination operators for data fusion: A
comparative review with classification. Systems, Man and Cybernetics, Part A:
Systems and Humans, IEEE Transactions on, 26(1), 52-67.
Chen, L.-D., & Tan, J. (2004). Technology Adaptation in E-commerce:: Key
Determinants of Virtual Stores Acceptance. European Management Journal,
22(1), 74-86.
[6]. Doll, W. J., & Torkzadeh, G. (1988). The measurement of end-user computing
satisfaction. MIS quarterly, 12(2), 259-274.
[7]. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An
introduction to theory and research.
[8]. Hawkins, D. I., Best, R., & Coney, K. (2001). Consumer Behavior-Building.
[9]. Hornback, R. (1995). Electronic commerce in the 21st century. Journal of
Systems Management, 46, 28-28.
[10]. Hsin, Y.-F. (2001). A study of shopping environment, product attribute and
perceived risk in Internet shopping behavior.
[11]. Kalakota, R., & Whinston, A. B. (1999). Frontiers of electronic commerce:
Addison Wesley Longman.
[12]. Korgaonkar, P. K. (1981). Shopping orientations of catalog showroom patrons.
Journal of Retailing, 57(1), 78-90.
[13]. Kosiur, D. (1997). Understanding electronic commerce: Microsoft press.
[14]. Li, H., Kuo, C., & Rusell, M. G. (1999). The impact of perceived channel
utilities, shopping orientations, and demographics on the consumer's online
buying behavior. Journal of Computer‐Mediated Communication, 5(2), 0-0.
[15]. Lin, J.-S., & Chen, M. Y. (2006). Consumers' Evaluation of External Cues on
Farm Resorts. Tourism Management Research, 6(2), 185-201.
[16]. Morganosky, M. A., & Cude, B. J. (2000). Consumer response to online grocery
shopping. International Journal of Retail & Distribution Management, 28(1),
17-26.
[17]. Morwitz, V. G., & Schmittlein, D. (1992). Using segmentation to improve sales
forecasts based on purchase intent: Which" intenders" actually buy? Journal of
Marketing Research, 391-405.
8
[18]. Murray, K. B. (1991). A test of services marketing theory: consumer information
acquisition activities. The Journal of Marketing, 10-25.
[19]. Rohm, A. J., & Swaminathan, V. (2004). A typology of online shoppers based on
shopping motivations. Journal of Business Research, 57(7), 748-757.
[20]. Sohn, D.-W., Chai, I.-H., Lee, D.-J., Kim, H.-C., Kim, H.-S., Oh, B.-H., . . . Seo,
J.-D. (1997). Assessment of mitral annulus velocity by Doppler tissue imaging in
the evaluation of left ventricular diastolic function. Journal of the American
College of Cardiology, 30(2), 474-480.
[21]. Spieß, C. K., Büchel, F., & Frick, J. R. (2000). Kinderbetreuung in West-und
Ostdeutschland: sozioökonomischer Hintergrund entscheidend. Wochenbericht,
69(31), 518-524.
[22]. Stone, R. (1954). Linear expenditure systems and demand analysis: an
application to the pattern of British demand. The Economic Journal, 64(255),
511-527.
[23]. Wilson, T. D. (2000). Human information behavior. Informing science, 3(2),
49-56.
9