• 마케팅과학연구
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• 제20권2호
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• pp.188-198
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• 2010

此研究旨在考察负口碑(即NWOM)对在线行销的影响, 着重分析服务失败的描述以及通信服务商的意向是如何影响消费者对企业竞争力的评估, 对企业的态度, 以及积极的口碑行销和行为意向. 对通信说服力的研究着重于 "谁说了什么; 对谁;通过何渠道;有何影响(Chiu 2007)". 在此我们研究了电子网络发布, 尤其是 "什么" 的两个方面: 通信服务失败的等级以及个人发布的知觉意向. 电子负口碑看似正在毁掉产品或企业的声誉, 这也就不难理解为什么人们总对它带有偏见, 认为其不可靠. 根据归因理论, 人们总会寻求事件的原因, 尤其是那些消极的意外的事件(Weiner 2006). Hennig-Thurau和Walsh (2003)提出 "既然读者的知识和对在线信息的作者信任度都很有限, 可以把电子口碑当做是表达-行为关系的有效调节. 此据此我们提出以下假设: 假设1. 在衡量(a)企业竞争力, (b)人们对企业的态度, (c)积极的口碑, 以及(d)行为意向时, 面临高等级服务失败电子负口碑的对象得分低于面临低等级服务失败电子负口碑的对象. 假设2. 在衡量(a)企业竞争力, (b)人们对企业的态度, (c)积极的口碑, 以及(d)行为意向时, 面临警告意向电子负口碑的对象得分低于面临报复意向电子负口碑的对象假设3. 在电子负口碑中, 服务失败的等级和知觉意向互相影响, 因此在衡量(a)企业竞争力, (b)人们对企业的态度, (c)积极的口碑, 以及(d)行为意向时, 警告意向的电子负口碑的平均反应值大于报复意向的电子负口碑. 主要研究包括一个2 (服务失败的严重性) x 2(警告意向VS报复意向的负口碑)的析因实验. 将通过模拟的在线网络发布信息刺激在线对象. 这一方案描述的服务失败是在传统的零售机构不接受礼物卡, 通过一家在线的研究公司从全国抽样. 共有113个对象参与此研究, 共分析了104份调查问卷. 研究对象认为该方案很现实, 92.3%对此反应强烈. 方案的运作相当令人满意, 所有的措施都经预先的测试验证, 各个项目也经分析证实可靠并有效. 多变量方差分析结果显示多变量间无明显的互相影响, 因此我们只研究主要影响-后倾向和服务失败的严重性. 后倾向主要影响对企业的态度, 积极的口碑和行为意向. 服务失败的严重性主要影响4个因变量: 企业的竞争力, 对企业的态度, 积极的口碑和行为意向. 需特别指出的是, 当电子负口碑描述为严重的服务失败时, 企业的竞争力低于电子负口碑描述为较轻的服务失败时. 当电子负口碑描述为严重的服务失败时, 对企业的态度差于电子负口碑描述为较轻的服务失败时. 当电子负口碑描述为严重的服务失败时, 企业的口碑差于电子负口碑描述为较轻的服务失败时. 当电子负口碑描述为严重的服务失败时, 行为意向低于电子负口碑描述为较轻的服务失败时. 因此, 假设1中的abcd都得到了支持. 另外, 衡量对企业的态度时, 警告意向的电子负口碑得分低于报复意向的电子负口碑. 衡量企业的口碑时, 警告意向的电子负口碑得分低于报复意向的电子负口碑. 衡量行为意向时, 警告意向的电子负口碑得分低于报复意向的电子负口碑. 因此与假设2中的a项不符, 尽管结果指向的是假设方向. 除此之外, 在假设的三个变量中, 后倾向对服务失败的严重性无明显的多变量或单变量影响. 因此, 假设3被推翻. 此研究有研究和管理的双重蕴涵, 如之前的研究一样, 此研究结果证实了服务失败的严重性影响消费者知觉, 态度, 积极的口碑以及行为意向(Weun et al. 2004). 关于进一步的相关性, 在线内容证实了该反应, 这意味着企业需要努力进行服务补救. 至于电子负口碑的知觉意向, 如之前的研究一样, 此研究结果意味着读者对原始资料的意向影响其对知觉, 态度, 积极口碑和行为意向的作用大小. 对管理者的蕴涵在于, 当消费者发现在线交流可靠且有影响力时, 不是所有的交流都同等重要. 电子口碑的好处在于它可以监测潜在的问题并提供纠正的可能性, 即使有潜在的危害.

• 자원환경지질
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• 제28권6호
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• pp.635-646
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• 1995

동양활석광상의 광화대는 옥천누층군에 속하는 향산리 돌로마이트의 최하부 돌로마이트층준에 발달하며 광체는 이 지역 지층 중에 밥달하는 $N85^{\circ}{\sim}90^{\circ}W$에 $40^{\circ}$ 로 플란지하는 작은 습곡축에 따라 파이프상으로 배태되어 있다. 이 광상의 모든 광체들의 상반이나 하반에 각섬질암이나 녹니석편암을 수반한다(김옥준 등, 1963; 박희인과 김기태, 1966). 동양활석광상의 활석광화작용은 돌로마이트의 재결정작용과 규화작용에 이어 투각섬석과, 판상, 엽편상활석(I), 미립질 활석 (II)의 생성 순으로 이루어졌다. 활석(I)은 돌로마이트와 $SiO_2$ 성분이 풍부한 유체와의 반응으로 생성되었고 활석 (II)는 돌로마이트와 유세와의 반응과 이마 생성된 투각섬석과 유체와의 반응으로 생성되었다. 광화기간중 유체는 초기에는 $H_2O-CO_2$계의 것으로 $CO_2$가 풍부한 것이었으나, 말기로 가며 $H_2O-NaCl-CO_2 $계를 거쳐 $H_2O-NaCl $계의 것으로 변하였다. 투각섬석과 활석(l) 생성기의 온도 및 압력조건은 각각 1,640~2,530 bar, $440{\sim}480^{\circ}C$ 였고, 활석 (II) 생성기의 온도 및 압력조건은 1,400~2,200 bar와 $360{\sim}390^{\circ}C$였다. 이 값은 동양활석광상 북쪽 약 5km에 분포하는 문주리층 구성암석의 변성온도 및 압력값에 비하여 현저하게 낮다. 활석광상의 모암인 돌로마이트의 ${\delta}^{13}C$과 ${\delta}^{18}O$값은 각각 2.9~5.7‰ (PDB)과 -7.4~16.8‰ (PDB)로서 기 보고된 태백산지역의 석회암의 값에 비하여 높으나 변질받지 않은 퇴적원 돌로마이트가 갖는 값의 범위내에 든다. 동양활석광상의 활석의${\delta}^{18}O$와 ${\delta}D$값은 각각 +8.6-15.8‰ (vs SMOW)와 -65~-90‰ (vs SMOW)로서 마그마 기원의 물의 값을 갖는다. 이 값은 이 지역의 문주리층과 계명산층을 구성하는 변성암류의 ${\delta}^{18}O$과 ${\delta}D$ 값과는 판이하다. 경석고의 ${\delta}^{34}S$ 값은 22.4‰ (CDT)로서 고생대초의 황산염의 ${\delta}^{34}S$의 값(30‰ vs CDT)보다 낮아 화성기원의 S가 첨가되었을 가능성이 있다. 활석광석에는 약하게 염리와 파랑벽개 등이 발달하고 있어 활석광상은 옥천대가 겪은 여러 차례의 변형작용중 최후기상이 적어도 끝나가 이전에 마그마 기원의 유체에 의하여 생성된 열수교대 광상이라 사료된다.

• 치위생과학회지
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• 제12권6호
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• pp.675-681
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• 2012

본 연구는 구강보건센터 미설치 지역의 보건소 치과위생사를 대상으로 2012년 4월부터 7월까지 구강보건센터 미설치 이유와 설치 시 필요사항에 대해 설문조사를 실시하고 총 293부를 수거하였다. 그 중 주요 문항에 대한 응답이 불충분한 87부를 제외하고 217부를 분석하여 다음과 같은 결과를 얻었다. 1. 구강보건센터 미설치 이유는 우선순위부족(72.4%), 공간부족(71.4%), 예산부족 (70.5%), 구강보건사업에 관한 의지부족(70.5%), 인력부족(62.7%) 순으로 나타났다. 2. 구강보건센터 설치, 운영 시 필요사항은 공간확충, 예산확충, 실적위주 사업과 형식적 행정업무의 감소, 구강보건사업에 대한 기관장 또는 상급자의 이해, 인력확충, 구강보건센터 이외의 과중한 업무감소, 지역사회 민간자원 활용확충, 구강보건사업 종류의 간결화, 사업지침의 명확성, 대상자별 프로그램 개발, 활용 가능 매체 제작, 신규 프로그램개발, 유관기관과의 협력 체계 강화, 보건소 내 타부서와의 연계성 강화, 직무교육 기회제공 순으로 조사되었다. 3. 구강보건센터 미설치 이유로 예산부족과 인력부족 항목에서 특별 광역시 지역이 시 군지역에 비해 더 높게 나타났다(p<0.05). 4. 구강보건센터 설치를 논의하지 않은 집단은 논의한 집단에 비해 구강보건센터 미설치 이유의 모든 항목에서 더 높게 나타났다(p<0.05). 따라서, 구강보건센터 설치의 확대를 위해서는 구강보건사업의 중요성을 지역주민과 관련 기관장, 상급자 및 보건소 내 타 사업 인력에게 홍보하여 구강보건사업의 우선순위를 높여야 하며 특별 광역시 지역 또한 건강불평등 해소를 위해 구강보건사업이 수행될 수 있는 충분한 예산과 인력이 지원되어야 한다.

• 마케팅과학연구
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• 제20권2호
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• pp.199-207
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• 2010

"对我们而言, 成为一名负责的公民和一份成功的事业之间没有区别.....他们对今天的沃尔玛是完全一样的." Lee Scott, 沃尔玛的CEO在2005年卡崔琳娜飓风灾难之后(Esty and Winston 2006) Lee Scott的声明标志着可持续发展的一个新的时代. 作为一个被全球生产商和零售商所关注的全世界最大规模的经销商确认了他们的可持续发展的意图. 近十年来, 环保运动不断增长, 并扩展到全世界. 公司已经诞生, 产品已被创造, 学术期刊 已经展开, 政府已经承诺—所有这一切都在追求可持续发展(Peattie and Crane 2005). 虽然进展的确比一些人渴望的慢了一些, 但是很多大规模的经销商已经为环保做出了可持续发展的努力. 为了更好的理解这个运动我们同时提供高管和消费者参与的有包装的消费品产业的角度. 该研究依赖于三个潜在主题: (1)概念和证据表明,公司为很多理由进行可持续发展 (2)在有包装的消费品行业中, 可持续发展活动的数量在持续增长 (3), 因此, 必须探索可持续发展在消费者意识中起的作用. 根据这些主题, 143名大学生和101名企业高管参加了调查来评估一系列的有关可持续发展的变量包括愿意支付, 行为意图, 态度和偏好. 结果显示高层管理者相信可持续发展的三个最主要的原因是(1)盈利能力的机会; (2)以实现对环境的义务; (3)对顾客和股东负责. 大学生的三大原因: (1)对环境的责任; (2)为子孙后代负责, 和(3):一种有效的管理资源. 虽然企业高管和大学生对支持可持续发展的理由不同, 但是企业高管和消费者的报告显示了对剩下大部分的可持续发展问题的相似性. 另外, 当我们要求消费者去评估6个关键问题的重要性时(医疗保健, 经济, 教育, 犯罪, 政府支出, 和环境), 保护环境仅排在第四位(Carlson 2005). 这6个问题都被认为是重要的, 三个最重要的是(1)改善教育;(2)本地区的经济发展,以及(3)卫生保健. 为了可持续发展的持续性, 我们也将预期结果. 反映社会, 企业利益表现的新定义和执行期的延长同样被揭示出来(Ehrenfeld 2005; Hitchcock and Willard 2006). 基于文献我们发现了三个基本范畴的结果:(1)改进组成的满意度, (2)分化的机会, 以及(3)金融奖励. 在每一种分类中, 我们发现从可持续发展活动中导致11种不同结果的几个特定的结果. 我们的调查结果表明,最有可能的结果最高的前五项依序为公司的可持续发展追求的是:(1)绿色的消费者将会更令人满意;(2)公司形象会更好, (3)公司的责任将得到加强, (4)会降低能源成本;(5)产品将会更多的创新. 另外, 为更好的理解消费者的环境 "身份" 和在市场购买中愿意显示出这个 "身份" 的有趣的交集, 我们扩展了以前Experian Research(2008) 的研究. 因此,受访者分为四个不同类型的绿色消费者(行为绿色,想法绿色, 潜在绿色, 或真正褐色)来获得更好的理解绿色消费者. 我们评估这些消费者愿意从事环保行为评估三种选择. (1)购物零售商支持环保措施;(2)支付更多来保护环境, 以及(3)支付更高的税收,政府可以支持环保措施. 想法绿色消费者表示最愿意改变, 紧随其后的是行为绿色消费者, 潜在绿色消费者和褐色消费者. 这些差异都是显著的(p<.01). 结论和启示我们采用描述性研究, 旨在促进我们理解战略领域的可持续性. 确切地说, 该研究以特定的偏好, 意图, 愿意支付, 行为和态度填补了进行比较与对比的持续性的商业管理者和消费者意见的文献的空白, 对从业人员, 能获得一个战略观点. 此外, 许多结果已经说明, 受访者愿意为产品付出更多来保护环境. 其他特定的结果表明, 女性受访者始终比男性强愿意交流, 为这些产品付更多的钱, 在环保的零售商. 了解这些额外的信息, 实践者现在有了更多的特定市场, 对目标和交流他们为可持续发展所做出的努力. 虽然这项研究仅仅是最初的一步了解实践者和消费者对于可持续发展的异同, 我们的结果对实践与研究都有帮助. 未来的研究应向测试其他变量的影响关系, 以及其他特殊行业.

• Asia pacific journal of information systems
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• 제18권3호
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• pp.123-145
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• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.