心理帳戶對產品選擇的影響:以跨期消費和產品熟悉度的為調節變數

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(1)國立臺灣師範大學管理學院管理研究所碩士論文 Graduate Institute of Management College of Management National Taiwan Normal University Master’s Thesis 心理帳戶對產品選擇的影響：以跨期消費和產品熟悉度的為調節變數 The Impact of Mental Accounting in Product Decision: The Moderating Roles of Intertemporal Discount Rate & Product Familiarity.. 陳品儒 Chen, Pin-Ru. 指導教授：沈永正博士 Advisor: Yong-Zheng Shen, Ph.D.. 中華民國 109 年 7 月 July 2020.

(2) ABSTRCT In near years, as the trend of 5G and artificial intelligence, “Subscribe” become a new payment format in diverse industry. No matter software, retail, sport, streaming, or Ecommerce business all started to promote customers becoming their “member”. In order to test the differentiation between the payments of the membership charging, the preference of payment on streaming websites becomes the main question in the research. Pay by years and pay by months, as the most common membership payment in Taiwan, are defined as two extremes to represent integrate loss and segregate loss. Kahneman and Tversky (2003) had proposed the value function, confirm that with a defined reference point, people are generally showing the value in a concave way for gains and commonly convex for losses. The theory was extended to Thaler’s Mental Accounting Theory, which claims that people are usually segregate gains and integrate losses. Regarding intertemporal substitution and product awareness differences in the payment preference question, we took a discount rate and product familiarity included as moderating variables. The variables are expected to explain the inconsistency between mental accounting theory’s integrating preference in loss and the questionnaire results. Monthly payment preference is proved as a preferred choice in research’s phenomenon. Though product familiarity can not show any significant result, this study gives the evidence that discount rate can somehow explain payment decision making preference. These results imply the existence of other potential parameters in payment preference. Based on the results, it can be reasonably questionable that when extending loss and gain rules to a consuming choice, risk becomes a more priority factor in decision making process. In other words, under this phenomenon, the integrate loss preference in Mental Accounting Theory cannot inference yearly payment preference in transactions.. Keywords: Mental accounting, integrate loss preference, streaming website, discount rate, product familiarity.. I.

(3) TABLE OF CONTENTS ABSTRACT......................................................................................................................I LIST OF TABLES.......................................................................................................... IV LIST OF FIGURES .........................................................................................................V CHAPTER I INTRODUCTION.....................................................................................1 Background...................................................................................................................... 1 Trend of Premium Membership.................................................................................... 1 Trend of Streaming....................................................................................................... 3 Motivation........................................................................................................................4 Purpose.............................................................................................................................5 CHAPTER II THEORY ............................................................................................... 6 Mental Accounting Decision Making............................................................................. 6 The Value Function ..................................................................................................... 6 Hedonic Framing in Mental Accounting...................................................................... 7 Product Familiarity ......................................................................................................... 8 The Failure of The Hedonic Editing Hypothesis........................................................ ..8 Acquisition Utilities & Transaction Utility................................................................... 9 Product Familiarity ..................................................................................................... 10 Product Familiarity Measure....................................................................................... 10 Intertemporal Consuming Decision Making.................................................................. 11 Time Discounting ....................................................................................................... 11 Discounting Rate Measure.......................................................................................... 12 CHAPTER III METHOD……………… ..................................................................... 14 Product and Subject ........................................................................................................ 15 Product ......................................................................................................................... 15 Subject ......................................................................................................................... 16 Data Collection ............................................................................................................... 16 Questionnaire Design...................................................................................................... 16 Payment Preference..................................................................................................... .17 Product Familiarity...................................................................................................... .17 Discount Rate……...................................................................................................... .18 Demographics….......................................................................................................... 18 II.

(4) CHAPTER IV ANALYSIS ........................................................................................ 19 Demographic Data ........................................................................................................ 19 Preference of Payments................................................................................................. .22 Payment Preference Hypothesis Test......................................................................... .22 Discount Rate ............................................................................................................... .23 Discount Rate Descriptive Statistics.......................................................................... .23 Discount Rate Hypothesis Test.................................................................................. .24 Product Familiarity ...................................................................................................... .26 Product Familiarity Descriptive Statistics.................................................................. 26 Product Familiarity t-test............................................................................................ 26 Product Familiarity Hypothesis Test.......................................................................... 29 CHAPTER V CONCLUSIONS AND DISCUSSIONS ............................................... 32 Summary ....................................................................................................................... 32 Evaluation...................................................................................................................... 32 Inconsistent Result of Integrate Loss Hypothesis....................................................... 32 Moderator Role of Discount Rate............................................................................... 33 Moderator Role of Product Familiarity...................................................................... 34 Future Work................................................................................................................... 34 REFERENCES .............................................................................................................. 36 APPENDIX 1 – QUESTIONNAIRE............................................................................. 38 APPENDIX 2 – GRADING SCHEME FOR FAMILIARITY SCALE........................ 42. III.

(5) LIST OF TABLES Table 4.1 Sample descriptive statistics...…....……….…………………………………..20 Table 4.2 T-test of payment decision versus demographic data……….………….……..21 Table 4.3 Binary logistic regression– payment decision versus demographics ….….......21 Table 4.4 Descriptive statistic – integrate loss preference….…………………….….…..22 Table 4.5 T-test of integrate loss preference versus payment decision ….........….……..24 Table 4.6 Descriptive statistic – discount rate ………………...………………………...23 Table 4.7 ANOVA – integrate loss preference versus discount rate …..…………....…. 24 Table 4.8 Binary Logistic Regression – Payment Decision Versus Discount Rate……...24 Table 4.9 χ-test of preference of yearly payment versus discount rate..…………......…. 25 Table 4.10 Descriptive statistic – familiarity score…………...…..…………..…….…...26 Table 4.11 T-test of payment decision versus familiarity score…..…………..….……...26 Table 4.12 T-test of payment decision versus familiarity score question……..………...27 Table 4.13 Correlation of preference intensity and familiarity score………..….……....29 Table 4.14 Multinomial logistic regression - preference intensity and familiarity score.30 Table 4.15 χ -test - preference intensity and familiarity score.…..…………..…….…....30. IV.

(6) LIST OF FIGURES Figure 1.1 Comparison of keywords searching trends on Google trends………………....4 Figure 2.1 Prospect theory value function………………………………………………...6 Figure 3.1 Research Architecture………………………………………………………..14 Figure 3.2 Question format of the payment preference...………………………………..17. V.

(7) CHAPTER I INTRODUCTION Background Trend of Premium Membership For brands, membership has always been a way to maintain customer relationships and further build brand communities. A sense of membership (SOM) is also defined as a represents of the sense of belonging (Luo, 2015). The concept is broadly used to illustrate how individuals appraisal themself with a group, and how people evaluate themselves as members of different communities. In the goal to build a deep connection between customer and brand, marketers find that membership coincides with the direct method to build a brand community, which they are trying to create in brand equity. As a result, membership strongly links to the need of belonging and being recognized by the brand. Luo (2015) claimed that although SOM was originally defined in brick-and-mortar communities, various scholars believe that it can also apply to online virtual communities. The advent of the Internet has greatly improved the efficiency of the membership system. The war is not a plastic card in a physical store anymore, it has already extended from the real world to online communities. Thus, an online community becomes another filed for brands to build a connection with consumers. A virtual community becomes a neoteric form of social entity in which members seeking problem-solving and share information for mutual learning through the Internet (Luo, 2015). For a broadly experience example in our daily life,. is is remarkablethat the trend of membership has already diffused from. traditional retail stores to E-commerce applications. Sundry ® memberships burst out in Taiwan during 2019. Being taken as the most popular way to connect consumers, no matter retail, technology, entertainment or sports business launched their membership policies. Under these circumstances, consumers’ decision making of membership charge payment becomes an important consideration for a marketer. But before that, what is the difference between a free membership and a membership needed to pay a fee? Premium membership, as an upgraded concept of membership, has kept booming in recent years. It is specific mention the payment that form in a limited membership charge. As technology advance, base on the development of 5G and cloud services, the paid-up membership, also known as premium membership, has become another very successful type of payment. For example, Microsoft and Adobe have turned their software selling method into a premium membership chargeinstead of the former buyout system. The 1.

(8) service should offer a more stable way that both company and customers benefit in blocking piracy activities and software update matters. Premium membership does not mean that the member can get premium service, it is a different payment term which Thaler (1999) illustrated with telecommunications and health club examples : generally speaking, consumers don't like having the meter running, known as“the rate bias in telecommunications”. As Train (1991) says, most telephone customers select a fixed payment for a period’s service even though paying by the call would cost them less. Thaler (1999) says, similarly, rather thanpaying by times, health clubs typically charge members by the month or year. The point of this strategy is making the marginal cost of a visit close to zero. This payment method can be really attractive to those who feel they should exercise more but usually fail to so. Owing to build a rule for themself, a period’s payment becomes a self-control tool that has the incentive to decrease the lost feeling of the fee, as a sunk cost, which can be depreciated by using the service (Thale, 1999). Extend on such a concept, some retail, software, and streaming company launched their premium membership in recent years. As a pioneer of premium membership, Amazon started Prime service from 2005, which was quoted as “ one of the most bizarre good business ideas ever ” by WIRED. There are several reasons for the success of this kind of premium membership. First, it promises special and usually unlimited services for a certain period of time with a fixed fee. Moreover, as a new concept of payment, , brands tried their best to propose the most cost-effective services to attract consumers to buy paid-up membership with the goal to catch as much as customers and thus create a new industry-standard. In fact, we have also verified the effectiveness of this payment from the success of Amazon and NetFlix for instance. In view of the fact that paid-up membership has only just been developed for a few years, we are currently seeing payment divided by the term of the period length that guaranteed the service. In Taiwan, the most common payment methods are monthly payments and annual payments, as in the case of telecommunications companies and gyms. Therefore, the trade-off between these two payments becomes the focus of our research in this study.. Trend of Streaming Since its introduction in the early 1990s, the concept of streaming media has experienced an impressive growth and transformation from a novel technology into a mainstream mode in which people experience the Internet today. We record for example 2.

(9) an extraordinary number of more than 350 000 hours of live sports, music, news, and entertainment broadcast over the Internet every week (Conklin, Greenbaum, et al. 2001). Broadly speaking, we can see the products of streaming video every day, such as live broadcasts, serials, Internet TV, and Internet radio. For Taiwan, the most popular include: 17, househouse.in, and foreign platforms like Twitch, Meerkat, Periscope, and social networking sites such as Facebook, YouTube, and LINE. This situation has created many streaming celebrities and led to the rise of various real-time APP platforms. According to market estimattions, the size of the Taiwan live broadcast market is about 25 billion yuan. Another evidence is that, according to statistics from the 1111 Human Resources Bank (one of the famous recruitment websites in Taiwan), 44% of office workers in Taiwan want to become online celebrities as new business opportunities for online celebrities continue to increase. The scale of the Taiwan streaming market has grown rapidly from NT $ 500 million in 2014 to NT $ 12 billion in 2017. In 2019, the revenue is estimated to exceed 10 billion. This impressive growth rate speaks for itself. Costa and Cunha (2004) mentioned that the three key characteristics of streaming media are: high bandwidth requirements, real-time media delivery, and the possibility of partial or interactive access. The high bandwidth requirements and the possibility of partial or interactive access motivated the development of not only new scalable streaming protocols but also challenge the devices’ efficiency. In addition to technical aspects, the real-time constraints on media delivery also fundamentally changed the traditional media industry and stimulated the transformation of the media to the content industry. To sum up, as a booming industry, various business models are also valued by marketers in the whole market. In this study, we target the streaming industry is trying to show the particularity customer decision making of emerging industries, and also expect to test the traditional consumer behavior principles whether still be complied with the market environment that has a fuzzy online and offline distinction line.. Motivation Checking the shopping category of searching trends in Taiwan on google trends, there is a gradual increase in “membership” during the past decade. To illustrate more, it is also can find a dramatic increase in “ watch online” in Sep. 2013 and Jan. 2017, then “Netflix” pop up in Jan. 2016 and cross over “watch online” in Dec. 2018. 3.

(10) Figure1.1 Comparison of Membership (blue), Watch online (red), and Netflix(yellow) searching trends on Google trends, with the set (1) location in Taiwan (2) period from 2004-2019 (3) shopping category.. Video streaming platforms have become a trend in recent years. It is also a very. successful paid-up membership system outside of Costco's retail industry. In order to understand people's payment behaviors on video streaming platforms, we design this research base on several behavioral economics theory. These trends not only became the motivation for this research but also show the significance and interestingness of this research topic.. Purpose As an authoritative theory, the principles in behavioral economics theory have been regarded as a source of theoretical foundation that must be referred to in recent consumer behavior research. Much research has defined behavioral economics working on the study of the allocation of behavior within a system of constraint (Bickel, Green & Vuchinich, 1995). The main two fundamental concepts that are taken into considerasion,as provided. 4.

(11) by behavioral economics, are the elasticity of demand and time discount (Bickel, Madden & Petry, 1998). In this research, the discount rate of customers will be tested as a moderator variable in the payment’s decision-making process. This idea stems from the increasingly important influence of mental accounting theory in recent years. However, the research on payment decision making of the behavioral economics field are scarce. Therefore, we organized our research based on research related to consumer behavior bias in the behavioral economics field. Though we do effort on the relationship between intertemporal consumption and the hedonic framing, we develop hypotheses based on the theory of behavioral economics and mental accounting. Tahler (1999) consolidated mental accounting matters, the paper mentioned in a short paragraph to illustrate the relationship between payment methods and mental accounting. We find that mental accounting focuses on the development of the current compound choice problem, and does not much consider the impact of intertemporal consumption in the decision-making process. In such cases, we believe that our research can attempt to answer some questions that have been overlooked in mental accounting theory. On the other hand, streaming platforms are a service that is booming, this studyaims to find out if there are some different consumer behaviors from traditional industry other than those proposed by previous researches.. 5.

(12) CHAPTER II THEORY Mental Accounting Decision Making The Value Function Traditional economic analyses of decision making under risk generally believe that consumer will try their best to maximize final expected utility. Several empirical research stand by, however, consumers broadly violate expected utility theory in their routine decision making (Camerer 1995, Starmer 2000). For example, measure result of utility that under expected utility is often result in a contradictory (Hershey & Schoemaker 1985). Obviously, using biased utilities to predict decisions will be distorted. (Abdellaoui, Bleichrodt, et al. 2007) The latest research on human consumption behavior judgment and decision-making comes from cognitive psychology and behavioral economics, which have reconceived completely rational homogeneous economics into less ideal sapiens (Tversky and Kahneman 1981). To make utility theory more rigorous, Kahneman and Tversky (2003) had proposed the value function, confirm that with a defined reference point, people are generally showing the value in a concave way for gains and commonly convex for losses. In other words, value decline steeper for losses than incline for gains. The concept is similar to an individual’s aversion to losses that may increase sharply near the loss. Researchers point out that in the specific range, for example, 10 dollars, the value decrease of losing 10 dollars will obviously larger than the value increase of gaining 10 dollars.. Figure 2.1 prospect theory value function. Adapted from “Kahneman and Tversky (2013), Prospect theory: An analysis of decision under risk, Econometrica, 47, 279.”. 6.

(13) The role of the value function in mental accounting is to describe how events are perceived and coded in making decisions (Thaler 1999). Continuing this concept, prospect theory is widely regarded as more suitable for predicting the behavior of irrational human beings. One important reason that prospect theory is more proper in mental accounting than expected theory is loss aversion: When people expound decision-making outcomes as gains and losses that comparative to a reference point, it is apparently more sensitive to losses than to commensurate gains (Abdellaoui, Bleichrodt, et al. 2007). An important reason why prospect theory is more suitable for mental accounting evaluating than expected utility theory is loss aversion. That is, when the decision result is interpreted as a gain or loss compared to a reference point, it is clear that losses are more sensitive than equivalent gains. Therefore, researchers must consider people's perceptions of the difference between loss and gain when predicting consumer behavioral decisions.. Hedonic Framing in Mental Accounting Base on the prospect theory value function, it is possible to build a model of how people code combinations decisions (Kahneman & Tversky, 1979). As the assumption of expected theory, researchers who use prospect theory also assume customers will try their best to maximize utility. Kahneman and Tversky (1979) formulated the idea of prospect theory, clarifies that consumers are naturally risk-averse. The discussion is specifically being significant when addressing situations with potential gains and of course risk-seeking when making decisions with potential losses. Given the shape of the value function, Thaler (1999) advocate the following principles of hedonic framing, which is taken as an important part in mental accounting to evaluate joint outcomes to maximize utility: (1) Segregate gains and integrate losses (because the gain function is concave and the loss function is convex). (2) Integrate smaller losses with larger gains (in order to offset loss aversion). (3)Segregate small gains from larger losses (suggested by the gain function is steepest at the origin) (Thaler, 1999). This prediction is supported in several experimental studies, for instance, Thaler (1985), Thaler and Johnson (1990), and Lim (2006). For example, Lim (2006) mentioned that as money has different meanings over time, monetary losses and gains also imply differ meaning such that investors frame losses and gains inconsistently. The hedonic frame principals illustrate the way of evaluating the decision-making process with joint outcomes and explore the informative of loss aversion during the process.. 7.

(14) Following prefer review, the change of utility in pay a payment will steeper then gain something. And people will prefer to integrate small losses to a bigger loss. In this research, the more frequently but small losses will be the form of paying by months, and paying by years will represent the integration and bigger loss. As hedonic frame suggests (Thaler, 1999), and an obvious preference for paying by years is in our expectation. H1: Consumers should prefer to pay by years than pay by months, as a smaller but more frequent loss payment.. Product Familiarity The Failure of The Hedonic Editing Hypothesis Researchers doubt the principles of hedonic framing can be applied in any situation. Thaler and Johnson (1990) test the hedonic editing hypothesis in a series of experiments, One method they use is to ask people about their time delay preferences. In their questionnaire, subjects were asked to select two designated financial results. The question is which option implies more enjoyable, receiving two additional rewards on the same day, or two events separated by a week or two? The question is testing the subject's perception of the time interval. So if the respondent wants to separate the results, then he wants the results to happen at different times, and if he wants to integrate the results, then he wants the results to happen at the same time. The focus of Thaler and Johnson's research is that if the hedonic editing hypothesis is supported, then under the premise of the need for integration, if the assumption requires separation and time is close, then subjects will prefer time separation. As a result, the hedonistic editor's hypothesis was supported in order to gain revenue. Most subjects thought that the temporal separation of gains made them happier. However, subjects thought separating losses was also a good idea, which is in contrast to the hedonic editing hypothesis. The concept of the hypothesis that people would want to integrate losses comes from the point that the loss function displays diminishing sensitivity (Thaler and Johnson, 1990). In other words, the result shows that respondents think they are unable to simply add one loss to another. On the contrary, they prefer the losses should be felt one by one that bearing one loss makes one more sensitive to the next. Sum up, the evidence presents the principles of hedonic framing when focusing on gains. But loss aversion persuades that the pain of losing is psychologically about twice as. 8.

(15) powerful as the pleasure of gaining. And people are naturally more focusing on loss then the gains can be taken at the same time (Kahneman and Tversky, 1979). Moreover, Thaler concludes that loss aversion is even more important than the prospect theory value function would suggest, as it is difficult to combine losses to diminish their impact. At the same time, hedonic framing will not always correspond with consumer behavior when they are not that kind sure of their loss. In our research, in order to weaken the descriptive framework of gains and loss, we present the product and price at the same time and give the product a specific description. Also, we consider other moderating variables in our research architecture.. Acquisition Utility & Transaction Utility When decide to buy something, it means trading money for some object. To extend the hedonic frame to routine consuming behavior, Thaler (1999) argued that code the acquisition of the product as a gain and the forgone money as a loss is not proper, due to loss aversion makes the frame hedonically inefficient. This thinking has been supported by both Kahneman and Tversky (1984) and Thaler (1985) to reject the idea that costs are generally viewed as losses. Instead, researchers propose that consumers get two kinds of utility from a purchasing transaction: acquisition utility and transaction utility. Acquisition utility is relative to the price that consumers need to pay for a transaction of the good, similar to the economic concept of consumer surplus. In other words, acquisition utility is the value that consumers receiving the good as a gift minus the price paid. Transaction utility measures the perceived value of the clinch. First, there must be a reference price, which might be the mean of the price that consumers purchase before. That is the regular price consumer expects to pay for this product. Contract to the reference price, consumers may increase the price acceptance in different cases. One famous example followed by Thaler (1985) is that consumers will agree to pay more for a bottle of beer in a villa’s shop, cause it is the only place to sell beers around. The addition of transaction utility, some goods are purchased only because they are especially good deals. In contrast, because of substantial negative transaction utility, some purchases would be refused even seem to make the consumer better (Thaler 1999).. 9.

(16) Product Familiarity In this research, for paying a payment, the behavior means a loss in money account and also a gain in a specific product or service entity account. For the loss side, pay by years is an integrated and bigger loss compare to pay by months. On the other hand of the gain side, pay by months is that you own unlimited usage in one month, and pay by years is the full service for one year. For the purpose to adjust the bias of hedonic framing, product familiarity is taken as a moderator variable during the decision making process. Previous work has documented the relationship between product familiarity and consumer decision. Park & Lessic (1981) declare that decision-maker at a moderate level of familiarity shows significantly less confidence than the decision-maker at a high level of familiarity. Also, as an indicative variable, product familiarity is easily operating. Conclude with several previous research, Prentice (2004) mentioned familiarity can be informational from written, audio and visual sources or experiential from first-hand experiences. Include consumers' knowledge, experience and the absorbance of influences information, product familiarity influences consumers’ decision making (Brucks, 1985; Lynch et al., 1988; Tasci and Knutson, 2004). Authoritative, three prior behaviors that were broadly used in testing product familiarity are (a)search experience (b)usage experience (c)ownership status. (Park & Lessic, 1981). Furthermore, product familiarity is considered an important reference to check subjects’ accuracy of their imagination decision-making. It has been believed that is related to the decision maker’s knowledge and experience of the product and it shows a moderator effect during a consumer’s decision-making process. H2: People who have higher product familiarity will be more clear about their willingness to make the decision between pay by years or pay by months, than those have lower product familiarity.. Product Familiarity Measure Previous research has indicated certain factors that affect product familiarities, such as product involvement, product knowledge, and previous experience. Two major methods are available for operationalizing and measuring product familiarity: one is to measure in terms of how much a person knows about the product; the other is to measure how much a person thinks s/he knows about the product (Park & Lessic, 1981). Generally speaking,. 10.

(17) there have been considerable effects in terms of knowledge on consumers’ involvement with products. In addition, if the customer does not have an interest in the product, they will likely have a knowledge deficiency regarding the product and consequently will feel uncertain about purchasing the product (Lin & Chen, 2006). Rao and Monroe (1988) launched the research examined the dissimilar use of product information cues in product evaluations by differentially familiar subjects. In the research, offered a complete questionnaire to test product familiarity, which included the previous using experience, information searching experience, owing status, and product knowledge. Rather than simply asking the respondent's self-evaluation of their familiarity, a series of questions, like a test sheet, containing experience and knowledge can more objectively reflect the subject's product familiarity level. Thus, in this study, research also designs the questionnaire as a approach to test subjects’ product familiarity, which can be expected to be more conservatively.. Intertemporal Consuming Decision Making Time Discounting Frederick and Loewenstein et al (2002) declare a clear definition of distinguishing time discounting from time preference. They take the term time discounting to extensively involve any reason for caring less about a future consequence, factors that diminish the expected utility generated by a future consequence are included, such as uncertainty or preference changing. And use the term time preference to much more specifically catch sight of the preference for immediate utility over delayed utility. In our research, what we are trying to show is the difference between consumers paying for the length of the year and month cycles. Therefore, time discounting is a point we pay more attention to. Rae (1834) believed that intertemporal-choice behavior was the joint effect of factors that either encourage or limit the effective desire of accumulation. Frederick and Loewenstein, et al (2002) give another step of contracting the anticipatory-utility and abstinence perspectives that thought share the same core aspect that intertemporal tradeoffs depend on the immediate pleasure of anticipation and the immediate discomfort of selfdenial. However, two perspectives clarified the variability in intertemporal choice behavior in different approaches. The anticipatory-utility perspective constitutes the variations in intertemporal-choice behavior with the differences in consumers' ability to illustrate the 11.

(18) future and to differences in circumstances that promote or inhibit such mental images. On the other hand, abstinence perspective expresses variations in intertemporal- choice behavior on the basis of individual and situational differences in the psychological discomfort associated with self-denial (Frederick, Loewenstein, et al. 2002). To sum up, in this view, one should observe high rates of time discounting by people who feel painful to delay gratification and specifically feel uncomfortable in the situation which deferral. As Rae (1834) infers, the one is "actual presence of the immediate object of desire." In our research, subjects will be asked to choose between pay by months or years. To extend the time discount aspect to loss, a consumer who has a high immediate desire implies the preference to have cash. In contrast, the one has a low immediate desire implies a low sensitivity of pay immediately or pay intertemporal. H3: People who have a lower Intertemporal discount ratio will be less willing to pay by years then pay by months.. Discount rate measure Several studies test the intertemporal discount rate in different ways. Bohm-Bawerk treats intertemporal choice as an allocation of consumption which among time periods was formalized a decade later by the American economist. Fisher (1930) use another economical approach that plotted the intertemporal consumption decision on a two-good indifference diagram, with consumption in the current year on the abscissa, and consumption in the following year on the ordinate. This method is praised as a clear representation of a person's marginal rate of time preference and the marginal rate of substitution at the chosen consumption bundle. The method depends on two considerations: time preference and diminishing marginal utility (Kirby, Petry, et al. 1999). However, many economists discomfort with using the term "time preference" to include the effects of differential marginal utility emerging with unequal consumption levels during time periods (Olson and Bailey 1981). Subsequently, a method with 27 questions launched by Kirby (1999) is broadly applied in behavioral economics.. The estimate of a participant's discounting-rate. parameter is made from the participant's pattern of choices across the 27 questions on the monetary-choice questionnaire. The delay discounting degree was determined by using the hyperbolic equation V = A/(1 + kD), in which k is a free parameter describing the degree of discounting (Kirby, Petry, et al. 1999). The question, for example, offered participants. 12.

(19) a choice between "$33 today" and "$80 in 14 days." Follow Kirby’s definition, a participant with a discount rate of 0.10 would be indifferent between these two options. Therefore, a participant chose the immediate reward on this question could be inferred that this person had a discount rate greater than 0.10 (Kirby, Petry, et al. 1999) Although for Taiwan participants, 27 alternative questions will make the questionnaire more likely to be abandoned by the testee, though might to face the difficulty motivates participants to answer, this study still decided to use this design. While following Kirby's research design, we do our best to collect credible responses.. 13.

(20) CHAPTER III METHOD Based on the theory of mental accounting, this study explores the differences in consumer choices between pay by year and pay by months. Tahler (1999) consolidated mental accounting matters, the paper mentioned in a short paragraph to illustrate the relationship between payment methods and mental accounting. This study finds that mental accounting focuses on the development of the current compound choice problem, and does not much consider the impact of intertemporal consumption in the decision-making process. In order to simplify the variability and increase the operability of this study, the annual payment and monthly payment are used as the payment option, and the intertemporal discount rate is used as the moderator variable. In the literature review section, we found that the consideration of losses in mental accounting does not only represent the cost of money, but also the transaction utility. In order to explore the impact of transaction utility in this decision-making process, product familiarity is set as the second adjustment variable. With the support of the hedonic framing in mental accounting, we expect to see the subject's preferences for pay by years and to illustrate the impact that due to the above two moderator variables of the decision-making process. In summary, the research architecture diagram proposed in this study is as follows:. Figure 3.1 Research Architecture. 14.

(21) Product and Subject Product We can find that in recent years, researchers have done a lot of research on whether people behave consistently online and offline. Though there are some research claims that the behaviors are consistent. For example, Gosling and Augustine(2011) believed that consistent with socialization in offline contexts, extraverts people seek out virtual social contact and engaged during the online social experience. High openness subjects are also expressed as it is in the offline-world with evidence of exploring new activities, experiencing new people, and changing the photographic scenery. Thus, rather than being an escape from reality, online social network sites exist as a microcosm of people's larger social worlds. However, in the market research report, we always find the difference between behavior online and offline. That is a big reason that the Omni-channel model is advocated. The advent of online channels and new other digital channels such as mobile channels and social media has changed the retail business model and the behavior of shoppers. (Verhoef, Kannan, et al. 2015) In order to simplify the bias of consumers' inconsistent online and offline behaviors, this research will study the field structure on a streaming platform, a payment and use online transaction behavior. In the field of behavioral economics, research is often difficult due to the variability of the consumer environment. Based on this research design, we can more accurately measure consumer behavioral decisions. To illustrate more, online streaming website, as a young service in recent years, is because of video content as entertainment broadly shows in our life, is easy to imagine. In our study, subjects were asked to imagine a specific scenario, a product that was easier to imagine would make the answers more correspond to realistic decision making. The other reason is to reduce the error due to preference. Website, as a platform with compared neutral preferences, should be less variation of consumer preference. This attribute helps us reduce the variation in consumer willingness caused by consumer preferences. On the other hand, streaming platforms are a service that is booming, this study, in the results, expects to find out if there are some different consumer behaviors from traditional industry those are proposed by previous research.. 15.

(22) Subject To enhance maneuverability, the questionnaire is written in Chinese and takes Taiwanese as the main research subject. Thought the research involves some professional knowledge, there has no restriction on subjects. Because our research is focused on a living consumer decision making that anyone may have to face.. Data Collection In this study, convenience sampling was used to collect questionnaires. In order to increase the randomness of sampling, the questionnaire launched as an online questionnaire and diffusion through sundry social media includes Facebook, Instagram, PTT, and Line. After our effort, a total of 237 replies was collected during the one-week distribution period.. Questionnaire Design To illustrate a streaming website, an introduction and scenario are written at the beginning of the questionnaire: Please imagine that you are considering buying a membership for an “ online streaming website”. The website offers sundry TV programs, movies, animations, and documentaries those launched in Taiwan and abroad, including Japan, Korean, American, and China. You can enjoy profuse wonderful content just in one stop! Now, you can enjoy yourself anytime, anywhere and unlimited with a no-addisturbed watching time, as long as paying a cost-effective membership fee. Our website offers two kinds of payment: pay by years and pay by months. Year fee means to pay NT$3600 in one time, and month fee indicates pay NT$300 every month. Honestly, this questionnaire is hard for subjects. Especially, for example, be asked to answer the country of origin of specific series. Thus, the order of the topics is arranged by importance and complexity. After the scenario, the questionnaire composes of four 16.

(23) topics. At the beginning of the questions first asks the preference of subjects’ payment choices, which is the most important question of the research. Following, a series question of product familiarity appeared in the form of cloze and multiple-choice, which is the most complicated part of the questionnaire. Third, the alternative discount rate question group needs to be answered. Finally, demographic-related questions are the last part of the questionnaire.. Payment Preference Different from alternative monthly and annual fee choices, a six-scale linear multiple-choice question was designed to allow the subjects to present how much their preferences of the payment choice.. Figure 3.2 Question format of the payment preference. This design allows our analysis can both run in a constant and inconstant way. Also, as a materiality level question, the degree implies the specific level of the subject’s tradeoff between the two payments.. Product Familiarity Reference by the questionnaire that Rao and Monroe (1988) launched. In our research, product familiarity test by the subject’s previous experience, information searching experience, owing status, and product knowledge. There are twelve questions about product familiarity. Including three questions about previous experience, three questions about knowledge of streaming, three questions about knowledge of streaming service environment, and three questions about knowledge of streaming content. For example, subjects are asked to choose the right definition of OTT (over-the-top media service, another name of streaming service ). These questions, like test papers, accumulate subjects' familiar scores. However, unlike the exam, we encourage participants to do their best to answer but do not guess the answer.. 17.

(24) Discount Rate For intertemporal discounting, the divergence might since using a different measure. In our experiment, participants being asked to do the trade-off between a series of alternative choices. Picked between "today" and "a specific later" options in 27 scenarios with varying rewards and delays. The method is launched by Kirby et al. in 1999. In our scenario, we changed the unit from USD to NT with a currency exchange rate: 30.67. Follow the test rules from Kirby, there is only one question on one page that restricts the subject can only consider the conditions of one question, and also, they are required do not modify the previous answer once after making the choice.. Demographics There is evidence that the discount rate varies with income and other personal characteristics. Both Gilman and Black found that personal discount rates decline with income, education, and age (Warner & Pleeter, 2001). In our research, reference from previous studies, four demographics information be collected: age, education level, average monthly income, and job occupation.. 18.

(25) CHAPTER IV ANALYSIS Demographic Data Based on previous studies, we test four demographic variables in our research: age, education level, average monthly income, and job occupation. Before further analysis, we first use descriptive statistics to describe the image of the whole sample, and for facilitating subsequent analysis and interpretation. Table 4.1 is the descriptive statistics of all data arranged by demographic variables. It gives a clear framework of the subject’s image. After one week’s online questionnaire distribution, 237 samples were collected. Roughly view of the table, it is easily told that the most replies are from 20~25 years old, bachelor degree students with limited income. Although we try our best to reach different classifications people to sampling broadly, the samples do not seem comprehensive overall. Also, in table 4.1, we show the differentiates between the subjects who finally chose yearly payment and those chose monthly payment. In terms of payment decisions, only 52 samples choose to make annual payments, while the number of people who chose monthly payments is about 3.5 times the former. The result is obviously inconsistent with our first hypothesis, and more detailed analysis relate to hypothesis 1 will be tested and presented in the next section. Table 4.2 is the t-test of demographic data versus payment decisions. We try to figure out if there is any differentiation between the subjects in two payment decisions. In the four demographic variables, only average monthly income level has a statistically significant difference between the two payment decisions. But if we take back to check the detail number in Table 1, we can find that there is only 6% of subjects’ who have an average income level above 50k, and only one subject of them chose yearly payment. Given the small sample size, the significant result is not strong evidence and very likely is caused by the defect of the sample comprehensive. Furthermore, other insignificant results imply that the three demographic variables do not influence the payment decision questions in this research. In other words, we don’t need to concern any potential influence those might from demographic differences.. 19.

(26) Table 4.1. Sample Descriptive Statistics. 20.

(27) Table 4.2. T-test of Payment Decision Versus demographic Data. To illustrate more, we run a binary logistic regression with payment decision versus demographic variables, the result is shown in table 4.3. There is no statistical significant differences between the subjects chose yearly payment and monthly payments. The results show that demographics variables can not be take to explain payment preference and won’t be a problem in the payment decision question. Table 4.3. Binary Logistic Regression – Payment Decision Versus Demographics. 21.

(28) Preference of Payments Payment Preference Hypothesis Test To more specific mention out how strongly people preferred integrate loss, the payment decision question which formed six options within monthly payment and yearly payment is recoding into 0 to 5, as 5 represent the most strong preference to choose yearly payment. Table 4 shows the distribution of integrate loss preference, with mean 1.32 it is obviously weak evidence to support our first hypothesis. H1: Consumers should prefer to pay by years than pay by months, as a smaller but more frequent loss payment. Table 4.4. Descriptive statistic – integrate loss preference. 22.

(29) It is easy to say that we should reject H1. As table 4 shows, 50.6% of subjects had no doubt to choose the monthly payment when there was only 13.1 people chose yearly payment surely. This inconsistent with the hypothesis is beyond our original suppose. We try to find some possible explanations for this result, but the result may imply an uncompleted frame of the questionnaire. Further discussion will include in Chapter 5. Table 4.5. T-test of Integrate Loss Preference Versus Payment Decision. To illustrate more, a t-test with payment decision versus yearly payment preference is shown on table 5. The test showed two groups of payment decision are statistically significant different on intergrate loss preference.. Discount Rate From Kirby’s research, we give each subject a k value to represent their intertemporal preference which is counted from the answers of 27 alternative questions. To fulfill homogeneity test, we recoding k into ln(k*1000) and also classified them into ten levels which are suggested from Kirby.. Discount Rate Descriptive Statistics Table 4.6. Descriptive statistic - Discount Rate. 23.

(30) Table 4.6 is the descriptive statistic of whole data’s discount rate. Following the former research, we can give each subjects one k value to represent their discount rate, and also we can sign them into ten scaled discount rate level.. Discount Rate Hypothesis Test For the purpose of testing if there exist moderator effect from discount rate, we further recording subjects those who have discount rate rank under 3 as low and those above 7 as high. H3: People who have a lower Intertemporal discount ratio will be less willing to pay by years than pay by months. To test H3, we first run ANOVA of payment decision versus discount rate 3 classes and it shows a statistic significant result. That is, we can say there are difference between three classes of discount rate in integrate loss preference. Table 4.7. ANOVA – Integrate Loss Preference versus Discount Rate. Second, we run binary logistic regression of 10 ranks discount rate versus payment decision. As table 8 shows, the result support H3 that discount rate can somehow explained the payment decision, and discount rate showed the explanation 0.314 in the regression. Table 4.8. Binary Logistic Regression – Payment Decision Versus Discount Rate. 24.

(31) Finally, we provide the evidence to support H3 that discount rate can somehow explained the payment decision, and discount rate with medium bonus showed the highest explanation 2.565 in the regression. To further understand the distribution of discount rate and yearly payment preference, we use χ-test to show the distributions. The original discount rate data is in form of k-value and related level from zero to ten, for the data present needs, we recode ten levels into five levels. In the vertical site is 5 level discount rate, and the horizon site is 6 level of yearly payment preference. Although we got a significant results here, the distribution is not strictly follow any rules or show any trend. Table 4.9. χ-test of Preference of Yearly payment versus Discount Rate. See table 4.9, the percentage under n. column first, the percentage is show the preference of yearly payment within five discount level. In yearly payment preference 0, we can find a obviously rather high percentage compared to total data in discount rate level. 25.

(32) 2, and a rather low percentage in level 4. Then take a look in the column 5 of yearly payment preference, compared to total data, it can also find a obviously rather low percentage in discount rate level 2 and a rather high percentage in level 4. Those numbers support our hypothesis that lower discount rate people will less preferred yearly payment. Second, the percentage in the right of n. column is the distribution within yearly payment preference in the specific discount level. The distribution within yearly payment preference is no big different in different discount rate level.. Product familiarity Product Familiarity Descriptive Statistics Following the former research, each subject got their familiarity score from their answer, the score is between 0 to 40, and the mean of data is 20.3 and the median is 21. To take a closer look, whole data was recoding into 4 levels. Each level contains ten scores, and the distribution is shown in Table 10. The data that distincted by two payments decision is also presented in table 10. Table 4.10. Descriptive Statistic – Familiarity Score. Product Familiarity t-test Table 11 is the T-test of payment decision and familiarity score, unfortunately it shows insignificant differentiation between two groups.. 26.

(33) Table 4.11. T-test of Payment Decision versus Familiarity Score. To further illustrate, we also run t-test on each question in familiarity questions, and we find significant only in question five and question eight. Familiarity question 5: When speak to streaming, you will think yourself is? a. Totally unfamiliar b. Unfamiliar c. Ordinary d.Familiar e. Specially familiar Familiarity question 8: Please do your best to list at most 4 brands of streaming services.. Table 4.12. T-test of Payment Decision versus Familiarity Score Question. 27.

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(35) Product Familiarity Hypothesis Test H2: People who have higher product familiarity will be more clear about their willingness to make the decision between pay by years or pay by months, then those have lower product familiarity. Before testing the H2 we first test correlations between preference intensity and familiarity score. Preference intensity is the data recoding from payment decision question. In the 6 options which are chosen between monthly and yearly payment, the two options that most near two extremes are recoding into 3, and following two are 2, and the last two options in the middle represent the weakest intensity are recode into 1. Table 4.13. Correlation of Preference Intensity and Familiarity Score. Based on the Pearson correlation analysis, preference intensity and familiarity score have positive relationship [r (235) =0.110, p < 0.05]. P-value under 0.05 means there are correlations between familiarity scores and preference intensity.. 29.

(36) Table 4.14. Multinomial Logistic Regression - Preference Intensity and Familiarity Score χ -test - Preference Intensity and Familiarity Score. To test H2, we classified whole subjects into three levels of familiarity scores, and run multinomial logistic regressions. As table 4.14 shows, the results are not statistically significant. The result reject H2 that implies familiarity scores can not somehow explain the distribution of preference intensity. Table 4.15. χ -test - Preference Intensity and Familiarity Score. 30.

(37) Finally, we try χ -test to make sure there is difference distribution between familiarity scores and preference intensity. Unfortunately, the result on table x still insignificant.. 31.

(38) CHAPTER V CONCLUSIONS AND DISCUSSIONS Summary Following the phenomenon observed in this study, we could not corroborate the integrate loss hypothesis. To explain this inconsistency, we can infer three reasons : sampling defect, question framing and product attribute. And in the discount rate hypothesis, we show the evidence that it can somehow explain payment preference. But we don’t have strong evidence to prove that if people with lower discount rate would have lower preference in yearly payment. Finally, for product familiarity hypothesis, there is no statistic significant result either. In this research, we do not have a big contribution in hypothesis test result, but the method approach and the variables derived are a good attempt in this area, which aims to apply mental accounting on real business industry. We believe the multiple-choice question in six scaling boxes within two extremes is an informative form in testing payment preference and in testing integrate loss preference.. Evaluation Inconsistent Result of Integrate Loss Hypothesis The test result from integrate loss hypothesis, are on the contrary of the initialy assumed theory. Indeed people chose monthly payment in this research which proves that integrate loss preference might not be the main factor in considering the question within the yearly and monthly payment in our phenomenon. Also, the result may imply that Mental accounting theory cannot be followed in a rather new internet industry such as streaming websites. We infer three reasons for these inconsistencies: sampling defect, questioning framing and product attribute. As table 1 shows, our subjects are almost exculively belonging the 20~25 years old age group, those are bachelor degree students with limited income., If the demographic distinctions within the sampled group are too similar, the results may no be wellrepresentative of the overall Taiwanese population. However, Most of users of streaming websites fall into this age 20~25 group, making our current research results still valuable. Further evaluation, the consumers separated by this demographic area, are mainly young 32.

(39) student groups who may also violate the integrate loss hypothesis due to budget considerations or the inclination that they are more willing to try different products. The three main reasons to choose streaming websites as the research testing field are: streaming is the trend of new service industry, streaming is a relatively complete industry charging by premium membership, and streaming is easily on operating research. After our analysis, we conversely found that this rather new industry actually has some potential uncontrollable factors. According to the feedback from some subjects, they thought pay by months means that they can make purchase decision every months, and it seems they never try the product before, so monthly payment is a more proper choice in this question. Actually, we didn’t mention how long the contract is, we do not want to emphasize that no matter you chose yearly payment or monthly payment the total payment amount just 3,600 NT dollars. The emphasize above we think is too instructive for subjects to guess that the researcher want them choose yearly payment. The question of payments is no longer a loss preference question for those misunderstanding subjects, but a question about the affordability of loss aversion. Thaler (1985) had already found that the effect of loss aversion is bigger than integrate loss preference. Another potential uncontrollable factor is, in a rather new service, lose aversion affects much strongly than in traditional industries. Because the product is invisible and untouchable at once, even for the subjects, the product familiarity score will be higher.It is hard to tell the quality in an experiment product. Furthemore, based on Philip Nelson’s (1970) classification, streaming websites as a content provider, can be called postexperience good. The category mentioned out the value of product is hard to be told even be used. The value might need to be evaluate during a long-term using experience. To summarize, even though the explanation we gave above, there still subjects choose yearly payment in our test, so we think in a more rigorous questionnaire design, the consequence might be different with ours.. Moderator Role of Discount Rate In the discount rate hypothesis testing, we can only prove that discount rate can partially explain payment preference. According to Kirby’s research, we collect the data in mean 4.3, which is a rather low level in 11 degree ( 0 to 10 ) also conform the result that majority of subjects chose monthly payment. Owing to our first hypothesis is not being. 33.

(40) proved, the moderate effect from discount rate can not be test in our original hypothesis either. But, the correlation test proved the relationship between this two variables.. Moderator Role of Product Familiarity Finally, in the product familiarity hypothesis testing, the regression between payment preference intensity and product familiarity is not significant. As the regression result, product familiarity moderating effect cannot be accepted either. Though the hypothesis is not significant in moderate effect, the normal distribution of data shows the “exam sheet“ of streaming websites is reliable on testing familiarity level.. Future Work Based on the experience of this research, we suggest that future research can be improved in several directions: product selection, phenomenon assumptions, and expanded sampling for instance. For future researches advice, four products respectively from experient and search product which both from old industries and both from new industries can be tested at the same time and same scale. From this research, it can be clearly found that different products have different evaluations of product value. We recommend selecting four products for the same test according to product attributes, including experience products and search products, as well as rising industries and traditional industries. By studying the payment preferences of those products with different attributes, it should provide different and more interesting results. In our questionnaire phenomenon, the problem of integrate loss is potentially directed to the problem of loss aversion. In future research, it is recommended to do pretests for phenomenon of each product, and collect feedback from the subjects to ensure that it can prevent the subject from over-deriving the problem and there will not be excessive guidance of questioning framing. This study is hindered by the insufficient funding for student research and cannot be sampled through large institutions. It can only collect data through convenient sampling, which is slightly insufficient in the comprehensiveness of the sample. It is recommended. 34.

(41) that future researchers can conduct more appropriate sampling for the products or fields they are researching to obtain more representative data.. 35.

(42) REFERENCES Abdellaoui, M., et al. (2007). "Loss aversion under prospect theory: A parameter-free measurement." Management Science 53(10): 1659-1674. Barberis, N., et al. (2001). "Prospect theory and asset prices." The quarterly journal of economics 116(1): 1-53. Bickel, W. K., et al. (1998). "The price of change: The behavioral economics of drug dependence." Behavior Therapy 29(4): 545-565. Bickel, W. K. and L. A. Marsch (2001). "Toward a behavioral economic understanding of drug dependence: delay discounting processes." Addiction 96(1): 73-86. Chen, J. V., et al. (2011). "The interaction effects of familiarity, breadth and media usage on web browsing experience." Computers in Human Behavior 27(6): 2141-2152. Conklin, G. J., et al. (2001). "Video coding for streaming media delivery on the Internet." IEEE Transactions on Circuits and Systems for Video Technology 11(3): 269-281. Costa, C. P., et al. (2004). Analyzing client interactivity in streaming media. Proceedings of the 13th international conference on World Wide Web. Frederick, S., et al. (2002). "Time discounting and time preference: A critical review." Journal of economic literature 40(2): 351-401. Gosling, S. D., et al. (2011). "Manifestations of personality in online social networks: Self-reported Facebook-related behaviors and observable profile information." Cyberpsychology, Behavior, and Social Networking 14(9): 483-488. Hershey, J. C. and P. J. Schoemaker (1985). "Probability versus certainty equivalence methods in utility measurement: Are they equivalent?" Management Science 31(10): 1213-1231. Kahneman, D. and A. Tversky (2013). Prospect theory: An analysis of decision under risk. Handbook of the fundamentals of financial decision making: Part I, World Scientific: 99-127. Kirby, K. N., et al. (1999). "Heroin addicts have higher discount rates for delayed rewards than non-drug-using controls." Journal of Experimental psychology: general 128(1): 78. Luo, C., et al. (2015). "Examining the moderating role of sense of membership in online review evaluations." Information & Management 52(3): 305-316. Olson, M. and M. J. Bailey (1981). "Positive time preference." Journal of Political Economy 89(1): 1-25. Park, C. W. and V. P. Lessig (1981). "Familiarity and its impact on consumer decision biases and heuristics." Journal of consumer research 8(2): 223-230. 36.

(43) Rao, A. R. and K. B. Monroe (1988). "The moderating effect of prior knowledge on cue utilization in product evaluations." Journal of consumer research 15(2): 253-264. Starmer, C. (2000). "Developments in non-expected utility theory: The hunt for a descriptive theory of choice under risk." Journal of economic literature 38(2): 332382. Thaler, R. H. (1999). "Mental accounting matters." Journal of Behavioral decision making 12(3): 183-206. Thaler, R. H. and E. J. Johnson (1990). "Gambling with the house money and trying to break even: The effects of prior outcomes on risky choice." Management Science 36(6): 643-660. Tversky, A. and D. Kahneman (1979). "Prospect theory: An analysis of decision under risk." Econometrica 47(2): 263-291. Tversky, A. and D. Kahneman (1981). "The framing of decisions and the psychology of choice." science 211(4481): 453-458. Verhoef, P. C., et al. (2015). "From multi-channel retailing to omni-channel retailing: introduction to the special issue on multi-channel retailing." Journal of retailing 91(2): 174-181. Warner, J. T. and S. Pleeter (2001). "The personal discount rate: Evidence from military downsizing programs." American Economic Review 91(1): 33-53. Philip Nelson (1970). "Information and Consumer Behavior", 78 Journal of Political Economy 311, 312. 37.

(44) APPENDIX 1 – QUESTIONNAIRE 《線上串流影音平台問卷》引言（在您填答之前，請先閱讀以下資訊。）您好，我是台師大管理所的學生。此份問卷將用於我的碩士論文研究，您所提供的資料將僅用於學術研究，請預留約 15 分鐘不會被打擾的填答時間。問卷中並沒有對與錯的答案，依據您的考量填答即可，請放心填寫～另外，部分題組需「避免返回修改答案」，非常感謝您的配合！最後，請詳細閱讀「情境設定」後再填答，非常感謝您的協助！請閱讀以下情境，並在此情境下填答本問卷，非常感謝您！請假設您目前正在考慮購買一個「線上串流服務網站」的會員，這個網站提供各種電視節目、電影、動畫、紀錄片，包含台灣、日本、韓國、美國、中國、國內外各類影劇精彩內容，一站看足！只要支付一筆經濟實惠的會員費，就能隨時隨地、不限次數地盡情觀賞、享受一段完全不受廣告打擾的觀賞時光！網站保證時時都有新的內容上架，每星期都會加入新的節目與電影供您探索！本網站現在提供兩種付費方式：付年費、付月費。可選擇： (1) 年費: 一次繳清 NT$3,600 元 (2) 月費: 每月付費 NT$300 元 -------------------------------------------------------------------------------------------------------------一、請問在兩個付費方式中，您會偏好以哪一種方式付費？請在表格中的框框依照您的偏好程度勾選付費方式。月費--------------------------------------------------------年費 ⛍ ⛍ ⛍ ⛍ ⛍ ⛍ -------------------------------------------------------------------------------------------------------------二、請依照您對串流影音網站的了解回答以下題目。 1. 請盡您所能列出，在台灣可以使用的串流影音服務平台名稱（最多 4 個即可）。＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿ 2. 請盡您所能列出，可以使用的串流影音服務的裝置（最多 3 個即可）。＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿. 38.

(45) 3. 請問您曾經購買過串流影音網站的會員嗎？ 🗆 Yes 🗆 No 4. 請問您現在擁有串流影音網站的會員嗎？ 🗆 Yes No 5. 請盡您所能列出，您所知道的串流影音服務平台的品牌名稱（最多 4 個即可）。＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿ 6. 請回答以下影劇的來源國，如果不知道請回答不知道。 (a) 飛龍在天＿＿＿＿ (b)順風婦產科＿＿＿＿ (c)黑鏡＿＿＿＿ (d)庫洛魔法史＿＿＿＿ 7. 請列出您挑選串流影音平台會員時，所會注重比較的三項平台特性。＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿ 10. 請盡您所能列出，您認為在串流影音服務平台上可以找到的內容種類（最多 3 個即可）。＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿ 11. 《冰與火之歌：權力遊戲》是由哪一間公司製作？＿＿＿＿＿＿＿＿ 12. 串流 OTT(over the top)代表什麼意思？ 🗆 (a)過頂傳球 🗆 (b)超越頂尖的流暢影音享受 🗆 (c)通過互聯網向用戶提供各種應用服務 🗆 (d)將會十分火熱的新科技雲端應用服務 🗆 (e)不清楚 13. 串流影音與有線電視的差別，以下何者為對？ 🗆 (a) ott 為全球開放性網路，有線為區域閉鎖性網路。 🗆 (b) 有線電視可以在電視和行動裝置上觀看。 🗆 (c) 串流影音(ott)屬於網路電視(IPTV)的一種 🗆 (d) 都不知道 14. 說到影音串流，您會人為您自己(請選擇一個):. 39.

(46) 🗆 完全不熟悉 🗆 不熟悉 🗆 普通 🗆 熟悉 🗆 特別熟悉 --------------------------------------------------------------------------------------------------------------三、以下題組，每次會出現兩個選項，請勾選您偏好的選項，回答後請不要回頭修改答案。（一次顯示一題） (01)您會傾向 🗆 今天獲得 1043 元或是 🗆 186 天後獲得 1073 元 (02)您會傾向 🗆 今天獲得 1656 元或是 🗆 117 天後獲得 1687 元 (03)您會傾向 🗆 今天獲得 2392 元或是 🗆 162 天後獲得 2453 元 (04)您會傾向 🗆 今天獲得 859 元或是 🗆 179 天後獲得 920 元 (05)您會傾向 🗆 今天獲得 1441 元或是 🗆 160 天後獲得 1533 元 (06)您會傾向 🗆 今天獲得 2453 元或是 🗆 157 天後獲得 2607 元 (07)您會傾向 🗆 今天獲得 675 元或是 🗆 136 天後獲得 767 元 (08)您會傾向 🗆 今天獲得 1656 元或是 🗆 111 天後獲得 1840 元 (09)您會傾向 🗆 今天獲得 2055 元或是 🗆 119 天後獲得 2300 元 (10)您會傾向 🗆 今天獲得 767 元或是 🗆 80 天後獲得 920 元 (11)您會傾向 🗆 今天獲得 1053 元或是 🗆 89 天後獲得 1840 元 (12)您會傾向 🗆 今天獲得 2116 元或是 🗆 91 天後獲得 2607 元 (13)您會傾向 🗆 今天獲得 583 元或是 🗆 53 天後獲得 767 元 (14)您會傾向 🗆 今天獲得 1227 元或是 🗆 62 天後獲得 1687 元 (15)您會傾向 🗆 今天獲得 1687 元或是 🗆 61 天後獲得 2300 元 (16)您會傾向 🗆 今天獲得 736 元或是 🗆 29 天後獲得 1073 元 (17)您會傾向 🗆 今天獲得 1043 元或是 🗆 30 天後獲得 1533 元 (18)您會傾向 🗆 今天獲得 1656 元或是 🗆 30 天後獲得 2453 元 (19)您會傾向 🗆 今天獲得 429 元或是 🗆 19 天後獲得 767 元 (20)您會傾向 🗆 今天獲得 828 元或是 🗆 21 天後獲得 1533 元 (21)您會傾向 🗆 今天獲得 1257 元或是 🗆 20 天後獲得 2300 元 (22)您會傾向 🗆 今天獲得 460 元或是 🗆 13 天後獲得 1073 元 (23)您會傾向 🗆 今天獲得 767 元或是 🗆 14 天後獲得 1840 元 (24)您會傾向 🗆 今天獲得 1012 元或是 🗆 14 天後獲得 2453 元 (25)您會傾向 🗆 今天獲得 337 元或是 🗆 7 天後獲得 920 元 (26)您會傾向 🗆 今天獲得 613 元或是 🗆 7 天後獲得 1687 元 (27)您會傾向 🗆 今天獲得 951 元或是 🗆 7 天後獲得 2607 元 --------------------------------------------------------------------------------------------------------------四、人口統計變數 (選項） (1) 年齡 40.

(47) 🗆 20 以下 🗆 20-25 🗆 25-30 🗆 30-35 🗆 35-40 🗆 40-45 🗆 45-50 🗆 50 以上 (2) 教育程度 🗆 國中以下 🗆 高中職 🗆 大專院校 🗆 碩博士 (3) 每月可支配所得 🗆 2 萬以下 🗆 2~3 萬 🗆 3~4 萬 🗆 4~5 萬 🗆 5~6 萬 🗆 6 萬以上 (4) 職業 🗆 學生 🗆 公務員 🗆 金融業 🗆 農林漁牧業 🗆 服務業 🗆 科技業 🗆 行銷傳播業 🗆 家庭管理 🗆 醫療夜 🗆 其他＿＿＿＿＿本問卷至此已全部結束，非常感謝您的耐心填答！真的！非常感謝！. 41.

(48) APPENDIX 2 – GRADING SCHEME FOR FAMILIARITY SCALE. 42.

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