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This study is based on the Zeithaml¡¦s Means-End model. Moreover, this study examines how the on-line travel store image affects the perceived value of consumer. It adopts to evaluate the effect of perceived value by different store image dimensions, such as the store factors, the service, the design of websites, the merchandise, the promotion, the satisfaction after sale. The finding of the research is as followed. 1. The variables of age and income of demographic statistics can cause the difference of perceived value. 2. Different usage habits cause the difference of perceived value. 3. The attributes of store factors and merchandise of the on-line travel store image affect significantly to the perceived quality. 4. The attributes of the merchandise and the satisfaction after sale of the on-line travel store image has a negative affection on the perceived risk. 5. The perceived quality has a negative affection on the perceived risk. 6. The perceived quality has a positive affection on the perceived value; on the contrary, the perceived risk has a negative affection on perceived value.

To consumers, price promotion delivers economic incentive. Lower price means lower cost which consumers need to pay for products and services. That explains the reason that price promotion becomes a common short-term sales strategy. In the other hand, price promotion could be one negative signal to the quality. As a result, positive benefits in sales volume brought about by economic incentive of price promotion could be canceled out by the negative signal to quality, so far as to cause the decrease of sales volume. However, the positive relationship between prices and qualities is not necessarily tenable. When some outside factors exist, the negative effects which price promotion causes to the quality will be reduced. This will make price promotion work more effectively. According to Transaction Utility Theory, consumers¡¦ purchase intention depends on perceived acquisition value and perceived transaction value. Perceived acquisition value decides the percentage between perceived benefit and perceived cost. And perceived transaction value determines the difference between the fair price which consumers consider and the real price which they pay. The higher perceived acquisition value and perceived transaction value, the greater consumers¡¦ purchase intention. This research takes outbound package travel as the observation target and applies 2*2*2 experimental design method to analyze. The variables include price promotion range (fewer discount, larger discount); brand awareness (lower brand awareness, higher brand awareness) and information supply (shorter supply, richer supply). After taking questionnaires analysis, this research concludes: 1. When price promotion gets fewer, brand awareness higher and information supply richer, consumers¡¦ perceived quality and internal reference price will be higher. 2. When consumers¡¦ perceived quality gets higher, perceived transaction value higher, and perceived cost lower, their perceived acquisition value will become higher and so as their purchase intention. Based on conclusions of this research, when brand awareness is higher, price promotion will produce more significant effect on raising consumers¡¦ purchase intention. Secondly, marketing sectors can stop price promotion from becoming the negative signal to the quality by providing consumers with more related information. Thirdly, since perceived quality is the most important factor which will influence consumers¡¦ purchase intention, enterprises should concentrate efforts on raising the quality for effectively stimulating consumers¡¦ purchase intention.

This research addressed the question of how information technology (IT) tools influence the perceived risk of consumers in e-commerce transactions in three phases. First, an exposure-driven model of e-commerce transaction perceived risk was developed and tested, providing a theoretical and conceptual basis for this research. Nine salient risk beliefs were modeled as formative dimensions of three risk belief categories based on prior perceived risk research: information misuse risk, performance risk, and functionality inefficiency risk. The model was tested in an online survey of 565 internet users. The results support the proposed construct of e-commerce transaction perceived risk, modeled as formed by the three proposed risk categories, validating the measurement model and finding that the construct was associated as expected with accepted e-commerce constructs in a nomological network. In the second phase, this model was used to examine the ways in which IT tools influence those beliefs. Participants were asked to observe an example of one risk-reducing IT tool (RRIT) and to indicate their willingness to use the tool for reducing the probability of each risk category and risk dimension. This research confirmed that consumers do perceive RRIT as being useful in reducing the probabilities of risk categories, compared to their willingness to adopt a control IT tool or other RRIT for that purpose. The final phase of this research investigates the adoption and influence of RRIT. Participants were shown an example RRIT and were asked to compare a store providing the tool to an identical website that did not provide the tool. This research supported hypotheses that perceived improvements in the probability of one or more of the risk dimensions when an RRIT is provided would lead to an intention to adopt the RRIT, and that the intention to adopt the RRIT would be associated with an improvement in attitude toward buying from a web retailer and the subsequent improvement in intention to buy from a web retailer.

No description available.

No description available.

This research addressed the question of how information technology (IT) tools influence the perceived risk of consumers in e-commerce transactions in three phases. First, an exposure-driven model of e-commerce transaction perceived risk was developed and tested, providing a theoretical and conceptual basis for this research. Nine salient risk beliefs were modeled as formative dimensions of three risk belief categories based on prior perceived risk research: information misuse risk, performance risk, and functionality inefficiency risk. The model was tested in an online survey of 565 internet users. The results support the proposed construct of e-commerce transaction perceived risk, modeled as formed by the three proposed risk categories, validating the measurement model and finding that the construct was associated as expected with accepted e-commerce constructs in a nomological network. In the second phase, this model was used to examine the ways in which IT tools influence those beliefs. Participants were asked to observe an example of one risk-reducing IT tool (RRIT) and to indicate their willingness to use the tool for reducing the probability of each risk category and risk dimension. This research confirmed that consumers do perceive RRIT as being useful in reducing the probabilities of risk categories, compared to their willingness to adopt a control IT tool or other RRIT for that purpose. The final phase of this research investigates the adoption and influence of RRIT. Participants were shown an example RRIT and were asked to compare a store providing the tool to an identical website that did not provide the tool. This research supported hypotheses that perceived improvements in the probability of one or more of the risk dimensions when an RRIT is provided would lead to an intention to adopt the RRIT, and that the intention to adopt the RRIT would be associated with an improvement in attitude toward buying from a web retailer and the subsequent improvement in intention to buy from a web retailer.

This research addressed the question of how information technology (IT) tools influence the perceived risk of consumers in e-commerce transactions in three phases. First, an exposure-driven model of e-commerce transaction perceived risk was developed and tested, providing a theoretical and conceptual basis for this research. Nine salient risk beliefs were modeled as formative dimensions of three risk belief categories based on prior perceived risk research: information misuse risk, performance risk, and functionality inefficiency risk. The model was tested in an online survey of 565 internet users. The results support the proposed construct of e-commerce transaction perceived risk, modeled as formed by the three proposed risk categories, validating the measurement model and finding that the construct was associated as expected with accepted e-commerce constructs in a nomological network. In the second phase, this model was used to examine the ways in which IT tools influence those beliefs. Participants were asked to observe an example of one risk-reducing IT tool (RRIT) and to indicate their willingness to use the tool for reducing the probability of each risk category and risk dimension. This research confirmed that consumers do perceive RRIT as being useful in reducing the probabilities of risk categories, compared to their willingness to adopt a control IT tool or other RRIT for that purpose. The final phase of this research investigates the adoption and influence of RRIT. Participants were shown an example RRIT and were asked to compare a store providing the tool to an identical website that did not provide the tool. This research supported hypotheses that perceived improvements in the probability of one or more of the risk dimensions when an RRIT is provided would lead to an intention to adopt the RRIT, and that the intention to adopt the RRIT would be associated with an improvement in attitude toward buying from a web retailer and the subsequent improvement in intention to buy from a web retailer. / Business, Sauder School of / Graduate

No description available.

The research objects are Tickets Group Buying Websites, to explore the correlation between Perceived Risk and Purchase Intention, including website trust and perception of price. The main purpose is to investigate consumers' tickets group buying behavior, and to understand the consumers' perceived risk interactions with perceived price, trust in tickets group buying, and the impact of people¡¦s purchase intention. This research takes the questionnaire survey; we collect total 301 available samples. Use percentage, average, correlation analysis and regression analysis. The study result indicated that main consumer in ticket group buying are women; the major consumer age groups is 19-29 years old, their income per month is bellow fifty thousand; and most of consumer who lives in northern area in Taiwan. The main reasons that people who willing to use ticket group buying are cheapest price and easy to buy. The key reasons people who do not buy ticket group buying are using time limit and lower service quality. In this research, we found that when consumer has higher website trust, the perceived risk will be weaken; besides the purchase intention will be strengthen. The trust has significant effects on consumer¡¦s purchase decision in ticket group buying. This study also founds that consumer have lower perceived price having higher perceived risk and having lower purchase intention.