Radioactive source terms are important factor in design, licensing and operation of SMR (Small Modular Reactor). In this study, regulatory requirements and evaluation methodology for normal operation on NuScale SMR, which received standard design certification approval on September 11, 2020 from US NRC, are reviewed. The radioactive waste management system of nuclear power reactor should be designed to limit radionuclide concentration in effluents and keep radioactive effluents at restricted area boundary ALARA according to 10 CFR 20 and 10 CFR 50 Appendix I. Also, in general, the coolant source term to calculate the off-site radiological consequences for normal operation of SMR should be determined by using models and parameters that are consistent with regulatory guide 1.112, NUREG- 0017 and the guidance provided in ANSI/ANS-18.1-1999, and the result should be corrected by reflecting the design characteristics of SMR. The coolant source term of NuScale, unlike the case of large NPPs, cannot rely solely on empirical source term data, because the NuScale source term is based on first principle physics, operational experience from recent industry, and lessons learned from large PWR operation. Fission products in reactor coolant are conservatively calculated using first principle physics in SCALE Code assuming 60 GWD/MTU. The release of fission products from fuel to primary coolant based on industry operational experience is determined as fuel failure fraction of 0.0066% for normal operation source term and 0.066% for design basis source term while coolant source term of large NPP is calculated by using ANSI/ANS-18.1 for normal operation and fuel failure fraction of 1% for design basis source term. Water activation products in reactor coolant are calculated from first principles physics and corrosion activation products are calculated by utilizing current large PWR operating data (ANSI/ANS 18.1- 1999) and adjusted to NuScale plant parameters. Also, because ANSI/ANS 18.1-1999 is not based on first principle physics models for CRUD generation, buildup, transport, plate-out, or solubility, NuScale has incorporated lessons learned by using ERPI’s primary water chemistry and steam generator guidelines to ensure source term is conservative and design of materials used cobalt reduction philosophy to help ensure the coolant source term are conservative. Based on the coolant source term calculated according to the above-described method, the annual releases of radioactive materials in gaseous and liquid effluents from NuScale reactor are evaluated. Currently, Small Modular Reactors such as ARA, SMART 100 are under review for licensing in Korea. This study will be helpful to understand how the reactor coolant system source terms are defined and evaluated for SMR.

Because non-point source pollution is very closely related to hydrological characteristics, its importance is highly emphasized nowadays along with accelerating climate change. Especially for Korea, the non-point source pollution and its control are entirely depending on runoff, precipitation, drainage, land use or development, based on geographical and topographical reasons of Korea. Many studies reported the physical (e.g., apparatus- and natural-type facilities, etc.) and chemical methods (e.g., organic and inorganic coagulants, etc.) of controling non-point pollutant source pollution, however, those are needed to be reconsidered along with climate change causing the unexpected patterns and amounts of precipitation and strengthen complexity of social community. The objectives of this study are to assess recent situations of non-point source pollution in Korea and its control means and to introduce possible effective ways of non-point source pollution against climate change in near future.

Introduction User-generated online reviews have become an essential part of consumer decisionmaking process (Mayzlin, Dover, & Chevalier, 2014) affecting product attitudes (Schlosser, 2005), purchase intentions (Ba & Pavlou, 2002), sales (Babić Rosario, Sotgiu, De Vlack, & Bijmolt, 2016), as well as price and quantity of transactions (Berger, Sorensen, & Rasmussen, 2010). For instance, 58% of consumers prefer sites with peer reviews, and nearly all consumers (98%) reported reading peer review before making purchases online (eMarketer, 2010). Given the reach and influence of user-generated content (UGC), it is unsurprising that companies offer numerous incentives such as coupons, rebates, free samples, and monetary payments to encourage user-generated online reviews. In 2012, Tesco, a British multinational grocery and general merchandise retailer, ran a “Share & Earn” scheme where the retailer gave loyalty points to Facebook fans sharing products. Since such reviewers are more like friends than random strangers, how does the review source and incentives affect reviewer trustworthiness and purchase intentions? Would these effects differ across individualistic and collectivistic cultures? Our research examines the cross-cultural differences in the effects of review source and incentives on reviewer trustworthiness and purchase intentions between Americans and Taiwanese. Review Source and Trustworthiness Extant research has shown that reviews from friends are usually more persuasive than reviews from strangers (Huang, Zhang, Liu, & Liang, 2014). Dubois et al. (2016) revealed that high levels of interpersonal closeness increased the negativity of reviews shared, whereas low levels of interpersonal closeness increased the positivity of reviews shared. Correspondingly, individuals tend to perceive friendly review sources as being more trustworthy and honest (Ben-Ner & Halldorsson, 2010). The circulation for UGC online reviews on social media platforms such as YouTube, Facebook, Twitter, and Instagram could also make the review source appear like a friend. Since user-generated online reviews appear on the user’s own profile page as well as newsfeeds of each friend connected to that user (Chatterjee, 2011), individuals could easily perceive review sources as friendly and trustworthy. Given that online trust often increases purchase intention (Bart, Shankar, Urban, & Sultan, 2005), we posit that reviews from friends increase reviewer trustworthiness, which, in turn, increase purchase intentions. Incentives While online reviews from friends could be deemed as more trustworthy, incentives could muddy the waters. Sterling (2013) showed that over 40% of consumers in a survey reported some level of doubt in the credibility of UGC, fueled by reports of firms posting “fake” positive reviews, deleting negative reviews, or manipulating consumers into making positive statements that might not be a true representation of their options (Mayzlin et al., 2014). Given the level of distrust, the Federal Trade Commission sent out more than 90 letters reminding influencers and marketers that they required to clearly and conspicuously disclose their relationships with brands when promoting or endorsing products on social media (FTC, 2017). Relatedly, in 2012, the UK Advertising Standards Authority ruled that travel website TripAdvisor must cease claiming that it offers “honest, real, or trusted” reviews from “real travelers” since they are unable to assure consumers that all review content was genuine. Even when incentives are disclosed, incentivized reviews are often viewed with suspicion and are discounted as a means of correcting for presumed reviewer bias, even if the reviewer was not biased by the incentive (Du Plessis, Stephen, Bart, & Gonclaves, 2016). Taken together, we argue that incentivized reviews will decrease reviewer trustworthiness, and consequently, purchase intentions. Cultural Differences Existing work on the effects of review source and incentives have, at least implicitly, assumed that its effects hold globally and failed to consider individual or cultural moderating factors. In particular, individualistic and collectivistic cultures differ in their perceptions of trust violations: collectivists tend to become less trusting after experiencing a violation from in-group rather than out-group members; individualists’ trust levels are less affected by violations from in-group members (Fulmer, Gelfand, 2010; van Hoorn, 2015). In the context of our research, incentivized reviews could be regarded as trust violation, where reviewers no longer act altruistically to provide honest reviews. Thus, we posit that incentives could moderate the effects that reviews from friends have on perceived trustworthiness, and consequently, purchase intention in collective cultures (i.e. Taiwanese participants). In contrast, we expect to replicate the results of previous research where reviews from friends increases reviewer trustworthiness and purchase intentions; while incentivized reviews decreases reviewer trustworthiness and purchase intentions. Formally, we hypothesize that: Hypothesis 1a (H1a): Reviews from friends will be considered as more trustworthy than review from strangers amongst American participants. Hypothesis 1b (H1b): American participants will be more likely to purchase products reviewed by friends than strangers. Hypothesis 2a (H2a): Amongst American participants, reviewers providing incentivized reviews will be perceived as less trustworthy than reviewers providing non-incentivized reviews. Hypothesis 2b (H2b): American participants will be less likely to purchase products from incentivized reviews than non-incentivized reviews. Hypothesis 3a (H3a): Amongst Taiwanese participants, when reviews are not incentivized, reviews from friends will be considered more trustworthy than reviews from strangers. The effect will be attenuated when reviews are incentivized. Hypothesis 3b (H3b): Taiwanese participants will be more willing to purchase products reviewed by friends than strangers when the reviews are not incentivized. The effect will be attenuated when reviews are incentivized. Method Participants and Design Three hundred and sixteen participants (50% female, 18-85 years old) were recruited on Qualtrics for nominal payment. Half of the participants were American and completed the survey in English while the rest were Taiwanese and completed the survey in Mandarin. A 2 (review source: stranger vs. friend) x 2 (incentive: no incentive vs. incentivized review) x 2 (nationality: USA vs. Taiwan) mixed design was adopted with source and incentive manipulated within-subject and nationality manipulated between-subjects. Procedure All participants were instructed to assume that they were travelling to London, and was searching for a hotel to stay for a couple of days. They were then presented with four hotel reviews. Both source and incentive were manipulated within-subjects. Source of the reviews was either a friend or a stranger. Reviews were either not incentivized or incentivized where the reviewer was given discount on their stay for leaving a review. To prevent order effects, the reviews were presented in random order. All reviews were 4 out 5 stars reviews, were generally positive, and were dated at a similar time. Measures After every review, participants indicated purchase intention on two items (e.g. “After reading this review, I feel like booking this hotel.”; “If there is a chance, I will book this hotel.”) on a 7-point scale (1 = strongly disagree, 7 = strongly agree)(Kim, Park, & Lee, 2013). Participants also rated how much they trusted the reviewer on a 7-point scale (1 = strongly disagree, 7 = strongly agree) on three items (e.g. “I trust this reviewer to choose a hotel for me.”; “I have confidence in this reviewer.”; “I believe this reviewer is being honest.”) (Smith, Menon, & Sivakumar, 2005). Individualism/collectivism as well as uncertainty avoidance was assessed using a 3-item measure (e.g. “Individuals should stick with the group even through difficulties.”; “It’s important to closely follow instruction and procedures.”) (Yoo, Donthu, & Lenartowicz, 2011) with a 7-point Likert scale (1= strongly disagree, 7 = strongly agree) Results Outliers were removed using Stem and Leaf plots, leaving 295 participants, 148 Taiwanese participants and 149 American participants (50% female, 18 to 85 years old). Contrary to previous research (Hofstede Insights, 2018), American participants (M = 6.07, SD = 0.96) scored significantly higher on the uncertainty avoidance scale than their Taiwanese counterparts (M = 5.56, SD = 1.01). In addition, American participants (M = 5.00, SD = 1.35) did not score significantly higher on the individualism/collectivism scale than their Taiwanese counterparts (M = 5.08, SD = 1.23). As predicted in Hypothesis 1a, a 2 (review source: stranger vs. friend) x 2 (incentive: no incentive vs. incentivized review) on reviewer trustworthiness revealed a significant main effect of review source, F(1, 146) = 25.34, p =.00, where friends (M = 5.34, SD = 1.19) were significantly more trustworthy than strangers (M = 4.97, SD =1.24) amongst USA participants. In line with H2a, there was also a significant main effect of incentive, where non-incentivized reviews (M = 5.24, SD = 1.21) were considered more trustworthy than incentivized reviews (M = 5.07, SD = 1.22), F(1,146)=6.43, p =.01. There was no significant interaction effect, F <1. Amongst the Taiwanese participants, a 2 (review source: stranger vs. friend) x 2 (incentive: no incentive vs. incentivized review) on reviewer trustworthiness revealed a significant main effect of review source, F(1, 147) = 13.02, p =.00, and incentive, F(1,147)=6.43, p =.01, qualified by the predicted interaction, F(1,147)=3.77, p =.05. Consistent with our predictions (H3a), when reviews were not incentivized, friends (M = 5.41, SD = 1.08) were significantly more trustworthy than strangers (M = 5.15, SD = 1.10), F(1,147)=15.63, p=.00. However, when reviewers were incentivized, friends (M = 5.20, SD = 1.05) were just as trustworthy as strangers (M = 5.09, SD = 1.15, F(1,147) = 1.85, p =.18. As predicted (H1b), amongst USA participants, a 2 (review source: stranger vs. friend) x 2 (incentive: no incentive vs. incentivized review) on purchase intention revealed a significant main effect of review source, F(1, 146) = 4.46, p =.04, where reviews from friends (M = 5.40, SD = 1.20) elicited higher purchase intentions than reviews from strangers (M = 5.27, SD =1.20). Contrary to Hypothesis 2b, there was no main effect of incentive, F(1,146) = 1.34, p =.25, nor interaction, F<1. Amongst Taiwanese participants, a 2 (review source: stranger vs. friend) x 2 (incentive: no incentive vs. incentivized review) on purchase intention revealed a significant main effect of incentive where non-incentivized reviews (M = 5.49, SD = 0.94) elicited greater purchase intentions than incentivized reviews (M = 5.39, SD = 0.98), F(1,147) =3.74, p=.06. There was no main effect of source, F(1,147)= 2.31, p = .13 nor an interaction effect, F(1,147) = 1.81, p =.18. In line with our hypothesis (H3b), planned contrasts revealed that when reviews are not incentivized, friends (M = 5.55, SD = 0.96) elicited significantly higher purchase intention than strangers (M = 5.42, SD = 0.95), F(1,147) = 5.73, p =.01. In contrast, when reviews were incentivized, friends (M = 5.40, SD = 0.94) elicited as much purchase intention as strangers (M = 5.38, SD = 1.02), F<1. Discussion Given the ever-important role of user-generated online reviews in consumer decisionmaking, it is necessary to understand how review sources and incentives affects perceptions of trust and purchase intentions, especially across cultures. Our study demonstrates how review sources and incentives affect reviewer trustworthiness and purchase intentions differently across individualistic versus collectivistic cultures. Specifically, review source and incentives affect reviewer trustworthiness independently in Americans. Friends are considered more trustworthy than strangers, and non-incentivized reviews are considered more trustworthy than incentivized reviews. In contrast, the effect of review source on reviewer trustworthiness is moderated by incentive in Taiwanese participants. In particular, friends are considered more trustworthy than stranger only when reviews are not incentivized. When reviews are incentivized, trust seems to be violated, and friends are regarded as just as trustworthy as random strangers. Our contributions to the UGC literature are twofold. To date, research on UGC have largely ignored the role of culture and nationality (as well as individual differences, more broadly) can play. This potentially concerning since the proliferation of UGC are not limited to a Western sample. Our work highlights how culture can complicate findings in the UGC literature, and suggests a need to better consider the role culture plays. In addition, our research specifies the specific mechanism through which culture might influence the effect of review source and incentives affect purchase intention, trustworthiness. Additional studies will be conducted to examine how and why incentives are deemed as trust violations and reduce purchase intentions when accepted by friendly reviewers in collectivist cultures. Moreover, we will attempt to detangle trust in the reviewer versus review.

The advances of the Internet open consumers new opportunities to share their consumption experiences, opinions and feelings with others. Online customer reviews (OCRs) are a crucial source of information for consumers and are regarded as one of the most influential types of electronic word-of-mouth (eWOM) in shaping consumer attitudes and facilitating purchase decisions (Plummer, 2007). Prior research has produced a number of valuable insights on OCRs (e.g., Dellarocas, Gao, & Narayan, 2010; Hennig-Thurau et al., 2004; Mayzlin, Dover, & Chevalier, 2014). Especially the influence of OCR valence (positively vs. negatively framed information) has received considerable attention both from practitioners and from scholars (e.g., Xue & Zhou, 2010; Yang & Mai, 2010; Lee et al., 2009). However, we argue that scientific insights on the influence of OCR valence remain limited. Specifically, this paper shows that the level of source credibility (high vs. low) as well as the type of product (search vs. experience good) are important moderators of the influence of OCR valence on several consumer OCR reactions (product attitude, product quality, and product trust) under specific circumstances only. Four hundred and sixteen respondents (70% females, average age 24 years) participated in an experiment with a 2×2×2 between-subjects full factorial design manipulating the OCR valence (positive vs. negative), the source credibility (high vs. low) and the product type (search vs. experience good). Results demonstrate that the effect of positive OCRs from highly credible sources on diverse outcome variables is larger than from low credible sources. By acknowledging Chaiken et al.’s (1989) theoretical extension of the heuristic-systematic model (Chaiken, 1980) we provide empirical evidence that source credibility intensifies the impact of positive OCRs due to the additivity effect. In contrast, credible negative information is not more influential than incredible information. A similar mechanism becomes operational when considering product type. Here, positive OCRs about experience goods have a stronger influence on product evaluations than similarly valenced information about search goods. This research provides further support for the crucial role of credible, positive OCRs in affecting consumer behavior in contrast to their negative counterparts. From a practical perspective, marketers should consider including highly credible OCRs from trustworthy and experienced customers’ peers as decision aids. This can be achieved, for instance, by including personal postings from Facebook. Such a strategy is particularly efficient as positive OCRs increase the consumer’s confidence towards the product while credible negative OCRs are not more harmful than incredible ones.

발산형 바닥 경사 생성항(DFB, Divergence Form for Bed slope source term)을 엄밀하게 유도하였으며, DFB 중에서 격자의 변에서 평균 수 심을 이용하는 mDFB의 오차를 명백하게 입증하였다. 또한, DFB 기법은 바닥 경사 생성항에 대해 정확한 방법임을 밝혔다. 완전히 잠기기 않은 격 자에 대한 기존의 체적-수심 관계의 오류를 수정하였으며, C-특성의 충족을 위해 완전히 잠기지 않은 변에 대한 처리가 필요함을 검토하였다. 이 연 구를 통해 근사 Riemann 해법으로 천수방정식을 해석할 때 보다 정확한 수단을 제공할 수 있을 것으로 기대한다.