• Title/Summary/Keyword: 구매활동

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Eurasian Naval Power on Display: Sino-Russian Naval Exercises under Presidents Xi and Putin (유라시아 지역의 해군 전력 과시: 시진핑 주석과 푸틴 대통령 체제 하에 펼쳐지는 중러 해상합동훈련)

  • Richard Weitz
    • Maritime Security
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    • v.5 no.1
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    • pp.1-53
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    • 2022
  • One manifestation of the contemporary era of renewed great power competition has been the deepening relationship between China and Russia. Their strengthening military ties, notwithstanding their lack of a formal defense alliance, have been especially striking. Since China and Russia deploy two of the world's most powerful navies, their growing maritime cooperation has been one of the most significant international security developments of recent years. The Sino-Russian naval exercises, involving varying platforms and locations, have built on years of high-level personnel exchanges, large Russian weapons sales to China, the Sino-Russia Treaty of Friendship, and other forms of cooperation. Though the joint Sino-Russian naval drills began soon after Beijing and Moscow ended their Cold War confrontation, these exercises have become much more important during the last decade, essentially becoming a core pillar of their expanding defense partnership. China and Russia now conduct more naval exercises in more places and with more types of weapons systems than ever before. In the future, Chinese and Russian maritime drills will likely encompass new locations, capabilities, and partners-including possibly the Arctic, hypersonic delivery systems, and novel African, Asian, and Middle East partners-as well as continue such recent innovations as conducting joint naval patrols and combined arms maritime drills. China and Russia pursue several objectives through their bilateral naval cooperation. The Treaty of Good-Neighborliness and Friendly Cooperation Between the People's Republic of China and the Russian Federation lacks a mutual defense clause, but does provide for consultations about common threats. The naval exercises, which rehearse non-traditional along with traditional missions (e.g., counter-piracy and humanitarian relief as well as with high-end warfighting), provide a means to enhance their response to such mutual challenges through coordinated military activities. Though the exercises may not realize substantial interoperability gains regarding combat capabilities, the drills do highlight to foreign audiences the Sino-Russian capacity to project coordinated naval power globally. This messaging is important given the reliance of China and Russia on the world's oceans for trade and the two countries' maritime territorial disputes with other countries. The exercises can also improve their national military capabilities as well as help them learn more about the tactics, techniques, and procedures of each other. The rising Chinese Navy especially benefits from working with the Russian armed forces, which have more experience conducting maritime missions, particularly in combat operations involving multiple combat arms, than the People's Liberation Army (PLA). On the negative side, these exercises, by enhancing their combat capabilities, may make Chinese and Russian policymakers more willing to employ military force or run escalatory risks in confrontations with other states. All these impacts are amplified in Northeast Asia, where the Chinese and Russian navies conduct most of their joint exercises. Northeast Asia has become an area of intensifying maritime confrontations involving China and Russia against the United States and Japan, with South Korea situated uneasily between them. The growing ties between the Chinese and Russian navies have complicated South Korean-U.S. military planning, diverted resources from concentrating against North Korea, and worsened the regional security environment. Naval planners in the United States, South Korea, and Japan will increasingly need to consider scenarios involving both the Chinese and Russian navies. For example, South Korean and U.S. policymakers need to prepare for situations in which coordinated Chinese and Russian military aggression overtaxes the Pentagon, obligating the South Korean Navy to rapidly backfill for any U.S.-allied security gaps that arise on the Korean Peninsula. Potentially reinforcing Chinese and Russian naval support to North Korea in a maritime confrontation with South Korea and its allies would present another serious challenge. Building on the commitment of Japan and South Korea to strengthen security ties, future exercises involving Japan, South Korea, and the United States should expand to consider these potential contingencies.

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Development of Yóukè Mining System with Yóukè's Travel Demand and Insight Based on Web Search Traffic Information (웹검색 트래픽 정보를 활용한 유커 인바운드 여행 수요 예측 모형 및 유커마이닝 시스템 개발)

  • Choi, Youji;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.155-175
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    • 2017
  • As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

The Effects of Perceived Quality Factors on the Customer Loyalty: Focused on the Analysis of Difference between PB and NB (지각된 품질요인이 고객충성도에 미치는 영향: PB와 NB간의 차이분석)

  • Ye, Jong-Suk;Jun, So-Yon
    • Journal of Distribution Research
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    • v.15 no.2
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    • pp.1-34
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    • 2010
  • Introduction As consumers' purchase behavior change into a rational and practical direction, the discount store industry came to have keen competition along with rapid external growth. Therefore as a solution, distribution businesses are concentrating on developing PB(Private Brand) which can realize differentiation and profitability at the same time. And as improvement in customer loyalty beyond customer satisfaction is effective in surviving in an environment with keen competition, PB is being used as a strategic tool to improve customer loyalty. To improve loyalty among PB users, it is necessary to develop PB by examining properties of a customer group, first of all, quality level perceived by consumers should be met to obtain customer satisfaction and customer trust and consequently induce customer loyalty. To provide results of systematic analysis on relations between antecedents influenced perceived quality and variables affecting customer loyalty, this study proposed a research model based on causal relations verified in prior researches and set 16 hypotheses about relations among 9 theoretical variables. Data was collected from 400 adult customers residing in Seoul and the Metropolitan area and using large scale discount stores, among them, 375 copies were analyzed using SPSS 15.0 and Amos 7.0. The findings of the present study followed as; We ascertained that the higher company reputation, brand reputation, product experience and brand familiarity, the higher perceived quality. The study also examined the higher perceived quality, the higher customer satisfaction, customer trust and customer loyalty. The findings showed that the higher customer satisfaction and customer trust, the higher customer loyalty. As for moderating effects between PB and NB in terms of influences of perceived quality factors on perceived quality, we can ascertain that PB was higher than NB in the influences of company reputation on perceived quality while NB was higher than PB in the influences of brand reputation and brand familiarity on perceived quality. These results of empirical analysis will be useful for those concerned to do marketing activities based on a clearer understanding of antecedents and consecutive factors influenced perceived quality. At last, discussions about academical and managerial implications in these results, we suggested the limitations of this study and the future research directions. Research Model and Hypotheses Test After analyzing if antecedent variables having influence on perceived quality shows any difference between PB and NB in terms of their influences on them, the relation between variables that have influence on customer loyalty was determined as Figure 1. We established 16 hypotheses to test and hypotheses are as follows; H1-1: Perceived price has a positive effect on perceived quality. H1-2: It is expected that PB and NB would have different influence in terms of perceived price on perceived quality. H2-1: Company reputation has a positive effect on perceived quality. H2-2: It is expected that PB and NB would have different influence in terms of company reputation on perceived quality. H3-1: Brand reputation has a positive effect on perceived quality. H3-2: It is expected that PB and NB would have different influence in terms of brand reputation on perceived quality. H4-1: Product experience has a positive effect on perceived quality. H4-2: It is expected that PB and NB would have different influence in terms of product experience on perceived quality. H5-1: Brand familiarity has a positive effect on perceived quality. H5-2: It is expected that PB and NB would have different influence in terms of brand familiarity on perceived quality. H6: Perceived quality has a positive effect on customer satisfaction. H7: Perceived quality has a positive effect on customer trust. H8: Perceived quality has a positive effect on customer loyalty. H9: Customer satisfaction has a positive effect on customer trust. H10: Customer satisfaction has a positive effect on customer loyalty. H11: Customer trust has a positive effect on customer loyalty. Results from analyzing main effects of research model is shown as

    , and moderating effects is shown as
    . Results This study is designed with 16 research hypotheses, Results from analyzing their main effects show that 9 of 11 hypotheses were supported and other 2 hypotheses were rejected. On the other hand, results from analyzing their moderating effects show that 3 of 5 hypotheses were supported and other 2 hypotheses were rejected. H1-1: (SPC: Standardized Path Coefficient)=-0.04, t-value=-1.04, p>. 05). H1-2: (${\Delta}\chi^2$=1.10, df=1, p> 0.05). H1-1 and H1-2 are rejected, so it is prove that perceived price is not a significant decision variable having influence on perceived quality and there is no significant variable between PB and NB in terms of influence of perceived price on perceived quality. H2-1: (SPC=0.31, t-value=3.74, p<. 001). H2-2: (${\Delta}\chi^2$=3.93, df=1, p< 0.05). H2-1 and H2-2 are supported, so it is proved that company reputation is a significant decision variable having influence on perceived quality and, in terms of influence of company reputation on perceived quality, PB has relatively stronger influence than NB. H3-1: (SPC=0.26, t-value=5.30, p< .001). H3-2: (${\Delta}\chi^2$=16.81, df=1, p< 0.01). H3-1 and H3-2 are supported, so it is proved that brand reputation is a significant decision variable having influence on perceived quality and, in terms of influence of brand reputation on perceived quality, NB has relatively stronger influence than PB. H4-1: (SPC=0.31, t-value=2.65, p< .05). H4-2: (${\Delta}\chi^2$=1.26, df=1, p> 0.05). H4-1 is supported, but H4-2 is rejected, Therefore, it is proved that product experience is a significant decision variable having influence on perceived quality and, on the other hand, there is no significant different between PB and NB in terms of influence of product experience on product quality. H5-1: (SPC=0.24, t-value=3.00, p<. 05). H5-2: (${\Delta}\chi^2$=5.10, df=1, p< 0.05). H5-1 and H5-2 are supported, so it is proved that brand familiarity is a significant decision variable having influence on perceived quality and, in terms of influence of brand familiarity on perceived quality, NB has relatively stronger influence than PB. H6: (SPC=0.91, t-value=19.06, p< .001). H6 is supported, so a fact that customer satisfaction increases as perceived quality increases is proved. H7: (SPC=0.81, t-value=7.44, p<. 001). H7 is supported, so a fact that customer trust increases as perceived quality increases is proved. H8: (SPC=0.57, t-value=7.87, p< .001). H8 is supported, so a fact that customer loyalty increases as perceived quality increases is proved. H9: (SPC=0.08, t-value=0.76, p> .05). H9 is rejected, so it is proved influence of customer satisfaction on customer trust is not significant. H10: (SPC=0.21, t-value=4.34, p< .001). H10 is supported, so a fact that customer loyalty increases as customer satisfaction increases is proved. H11: (SPC=0.40, t-value=5.68, p< .001). H11 is supported, so a fact that customer loyalty increases as customer trust increases is proved. Implications Although most of existing studies have used function, price, brand, design, service, brand name, store name as antecedent variables for perceived quality, this study used different antecedent variables in order to analyze and distinguish purchase group PB and NB through preliminary research. Therefore, this study may be used as preliminary data for a empirical study that is designed to be helpful for practical jobs. Also, this study is made to be easily applied to any practical job because SEM(Structural Equation Modeling), most strongly explaining the relation between observed variable and latent variable, is used for this study. This study suggests a new strategic point that, in order to increase customer loyalty, customer's perceived quality level should satisfied for inducing customer satisfaction, customer trust, and customer loyalty. Therefore, after finding an effective differentiating factors in perceived quality in order to increase customer loyalty through increasing perceived quality, this factor was made to be applied to PB and NB. Because perceived quality factors which is recognized as being important by consumers is different between PB and NB, this study suggests how to efficiently establish marketing strategy by enhancing a factor. Companies have mostly focused on profitability in terms of analyzing customer loyalty, but this study included positive WOM(word of mouth). Hence, this study suggests that it would be helpful for establishing customer loyalty when consumers have cognitive satisfaction and emotional satisfaction together. Limitations This study used variables perceived price, company reputation, brand reputation, product experience, brand familiarity in order to determine whether each constituent factor has different influence on perceived quality between purchase group PB and NB. These characteristic variables are made up on the basis of the preliminary research, but it is expected that more precise research result would be obtained if additional various variables are included in study. This study selected a practical product that is non-durable, low-priced and bestselling product in a discount store through the preliminary research because it can be easily estimated by consumers. Therefore. generalization of study would be more easily obtained if more various product characteristics is included. Regarding a sample used in this study, it was only based on consumers who purchase products in a large-scale discount store located in Seoul and in the capital area. Accordingly, this sample has some geographical limitation, If a study is expanded by including more areas, more representative research results may be produced. Because this study is only designed to analyze consumers who purchase a product in a large-scale discount store, some difference may be found according to characteristics of each business type. In other words, there is certainly some application limitation, so research result from this study may not be applied to other business types. Future research may have fruitful results if it adjusts a variable to each business type.

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