Olympic Advertisers Win Gold, Experience Stock Price Gains During and After the Games (오운선수작위엄고대언인영득금패(奥运选手作为广告代言人赢得金牌), 비새중화비새후적고표개격상양(比赛中和比赛后的股票价格上扬))
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- Journal of Global Scholars of Marketing Science
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- v.20 no.1
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- pp.80-88
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- 2010
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There has been considerable research examining the relationship between stockholders equity and various marketing strategies. These include studies linking stock price performance to advertising, customer service metrics, new product introductions, research and development, celebrity endorsers, brand perception, brand extensions, brand evaluation, company name changes, and sports sponsorships. Another facet of marketing investments which has received heightened scrutiny for its purported influence on stockholder equity is television advertisement embedded within specific sporting events such as the Super Bowl. Research indicates that firms which advertise in Super Bowls experience stock price gains. Given this reported relationship between advertising investment and increased shareholder value, for both general and special events, it is surprising that relatively little research attention has been paid to investigating the relationship between advertising in the Olympic Games and its subsequent impact on stockholder equity. While attention has been directed at examining the effectiveness of sponsoring the Olympic Games, much less focus has been placed on the financial soundness of advertising during the telecasts of these Games. Notable exceptions to this include Peters (2008), Pfanner (2008), Saini (2008), and Keller Fay Group (2009). This paper presents a study of Olympic advertisers who ran TV ads on NBC in the American telecasts of the 2000, 2004, and 2008 Summer Olympic Games. Five hypothesis were tested: H1: The stock prices of firms which advertised on American telecasts of the 2008, 2004 and 2000 Olympics (referred to as O-Stocks), will outperform the S&P 500 during this same period of time (i.e., the Monday before the Games through to the Friday after the Games). H2: O-Stocks will outperform the S&P 500 during the medium term, that is, for the period of the Monday before the Games through to the end of each Olympic calendar year (December 31st of 2000, 2004, and 2008 respectively). H3: O-Stocks will outperform the S&P 500 in the longer term, that is, for the period of the Monday before the Games through to the midpoint of the following years (June 30th of 2001, 2005, and 2009 respectively). H4: There will be no difference in the performance of these O-Stocks vs. the S&P 500 in the Non-Olympic time control periods (i.e. three months earlier for each of the Olympic years). H5: The annual revenue of firms which advertised on American telecasts of the 2008, 2004 and 2000 Olympics will be higher for those years than the revenue for those same firms in the years preceding those three Olympics respectively. In this study, we recorded stock prices of those companies that advertised during the Olympics for the last three Summer Olympic Games (i.e. Beijing in 2008, Athens in 2004, and Sydney in 2000). We identified these advertisers using Google searches as well as with the help of the television network (i.e., NBC) that hosted the Games. NBC held the American broadcast rights to all three Olympic Games studied. We used Internet sources to verify the parent companies of the brands that were advertised each year. Stock prices of these parent companies were found using Yahoo! Finance. Only companies that were publicly held and traded were used in the study. We identified changes in Olympic advertisers' stock prices over the four-week period that included the Monday before through the Friday after the Games. In total, there were 117 advertisers of the Games on telecasts which were broadcast in the U.S. for 2008, 2004, and 2000 Olympics. Figure 1 provides a breakdown of those advertisers, by industry sector. Results indicate the stock of the firms that advertised (O-Stocks) out-performed the S&P 500 during the period of interest and under-performed the S&P 500 during the earlier control periods. These same O-Stocks also outperformed the S&P 500 from the start of these Games through to the end of each Olympic year, and for six months beyond that. Price pressure linkage, signaling theory, high involvement viewers, and corporate activation strategies are believed to contribute to these positive results. Implications for advertisers and researchers are discussed, as are study limitations and future research directions.
In the early 21st century, the global COVID-19 pandemic, which has arisen during the development of the technological science of the Fourth Industrial Revolution, has been a great challenge in all fields including politics, economy, industry, education and religion in Korean society. To prevent the spread of the COVID-19 epidemic, the Korean government announced 'social distancing guidelines,' focused on the 'prohibition of three conditions'(crowd, closeness, airtight) for safety reasons. These quarantine guidelines made it more difficult for Korean churches and Sunday schools to operate. In general, looking at the statistical data of the major denominations of the Korean Church in the second half of the 20th century, shows that the Church has entered a period of stagnant or declining growth. Data also show that the number of students attending Sunday School is decreasing. The researcher identified four causes of the crisis faced by the Korean church and Korean Sunday school entering the 21st century. These trends are influenced by the tendencies of postmodernism, the deconstruction of modern universalism, the certainty and objectivity of knowledge, and the grand narrative and worldview of diffusion. Moreover, it is a phenomenon in which the young population decreases in contrast to the increasing elderly population in the age of population cliff in Korean society. Sunday Schools are also facing a crisis, as the youth population, who will become the future heroes of the Korean church, is declining. Finally, constraints of Church and Sunday school education activities are due to COVID-19 Pandemic. As analysis shows the loss of the Church's educational vision and a decrease in the passion for education. Accordingly, the researcher suggests four new strategies for the next generation of Korean Sunday schools, whose ranges from 200 members or less; this range covers the majority of Sunday School program run by churches in Korea. First, in the age of postmodernism, a time of uncertainty and relativism, Christian Societies requires teachers who are certain of absolute Christian truth and faith. Second, in an era of declining population cliffs for younger generations, a shift to a home-friendly Sunday school paradigm is needed. Third, during the COVID-19 pandemic, educational activities must appropriately utilize face-to-face and non-face-to-face communication. Finally, even in difficult times, Korean Sunday school should nevertheless remember the Lord's great commandment(Matthew 28:18-20) and restore the vision and passion of education to announce and teach the gospel. The researcher hopes that this study will provide small, positive steps in rebuilding Korean Sunday school educational activities for future generations in difficult times.
The Sensor technology and portable device capability able to collect recent user information and the information about the surrounding environment haven been highly developed. A user can be made use of various contents and the option is also extending with this technology development. In particular, the initial portable device had simply a call function, but now that has evolved into 'the 4th screen' which including movie, television, PC ability. also, in the past, a portable device to provided only the services of a SMS, in recent years, it provided to interactive video service, and it include technology which providing various contents. Also, it is rising as media which leading the consumption of contents, because it can be used anytime, anywhere. However, the contents available for the nature of user's handheld devices are limited. because it is very difficult for making the contents separately according to various device specification. To find a solution to this problem, the study on one contents from several device has been progressing. The contents conversion technology making use of the profile of device out of this study comes to the force and profile study has been progressing for this. Furthermore, Demand for a user is also increased and the study on the technology collecting, analyzing demands has been making active progress. And what is more, Grasping user's demands by making use of this technology and the study on the technology analyzing, providing contents has been making active progress as well. First of all, there is a method making good use of ZigBee, Bluetooth technology about the sensor for gathering user's information. ZigBee uses low-power digital radio for wireless headphone, wireless communication network, and being utilized for smart energy, automatic home system, wireless communication application and wireless sensor application. Bluetooth, as industry standards of PAN(Personal Area Networks), is being made of use of low power wireless device for the technology supporting data transmission such as drawing file, video file among Bluetooth device. With analyzing the collected information making use of this technology, it utilizes personalized service based on network knowledge developed by ETRI to service contents tailor-made for a user. Now that personalized service builds up network knowledge about user's various environments, the technology provides context friendly service constructed dynamically on the basis of this. The contents to service dynamically like this offer the contents that it converses with utilizing device profile to working well. Therefore, this paper suggests the system as follow. It collects the information, for example of user's sensitivity, context and location by using sensor technology, and generates the profile as a means of collected information as sensor. It collects the user's propensity to the information by user's input and event and generates profile in the same way besides the gathered information by sensor. Device transmits a generated profile and the profile about a device specification to proxy server. And proxy server transmits a profile to each profile management server. It analyzes profile in proxy server so that it selects the contents user demand and requests in contents server. Contents server receives a profile of user portable device from device profile server and converses the contents by using this. Original source code of contents convert into XML code using the device profile and XML code convert into source code available in user portable device. Thus, contents conversion process is terminated and user friendly system is completed as the user transmits optimal contents for user portable device.
It is generally agreed that the country's population will grow up to the level of 52 million by the year of 2000 and that due the active growth of industry, urbanization and road constructions, sizable portion of existing arable lands will be utilized for other purposes than agriculture in near future. From 1966 to 1977, it was estimated that, the average annual conversion of arable lands to other uses, was 12,909 ha. If this trend persists, it is predicted that from 1978 to 1991 when the 6th Five Years Economic Development Plan will terminate, approximately 181,000 ha of arable lands will be converted for other uses again. On the other hand, it is certain that the increased population (39 million in 1981, 45 million in 1991, 52 million in 2001) and the changes in food pattern along with the enhancement of living standards will bring about the phenomenal increase in demands for not only the staple food but also the livestock products such as meat, milk and eggs, vegetables and fruits. These future increased demands for various foods, naturally mean the increased needs for the expansion of arable lands at the same time. It is predicted that, if more activities than present scale are not taken for the expansion of arable lands, the national food self sufficiency level will drop from 79% in 1977 down to 62% in 1991. To meet the increased food demands in future, there are several ways and means. These will include the increased land use intensity, elevation of unit area yield levels, minimization of conversion of arable lands to other uses and expansion of arable lands through the reclamations of idle hillside lands and tidal lands. Among these, the expansion of arable lands through reclamations of idle hillside lands and tidal lands are more positive measures to cope with the increased production of foods in future. The reclamation of hillside lands demands more attention because it needs more advanced technologies in agronomical and engineering aspects, larger scale fundings and integrated socioeconomic considerations. In agromical aspects, the thechniques for early improvement of chemical and physical properties of soils, proper soil conservation measures and rational cropping systems are of particular importance. As to the financial supports to encourage the farmings in hillside land, much bold fund inputs are essential for the construction of roads, installation of irrigation and drainage facilities, soil conservation mechanisms, which will ensure the stabilized farming with reasonable incomes in the newly reclaimed lands.
Statement of problem : Today's market economy has been changed more and more to consumer concerned. It is owing to not only consumers ' rising standard of living and education, but also purchasers' easy accessibilities to products through various mass media. The consumer centered market system, where customer can choose items with diverse alternatives to satisfy their self esteem, is also applied to the field of medical business, and accelerated by an increasing income level of shoppers and introducing the whole nations' medical insurance system. Today, the medical industry has become competitive due to increasing number of medical institutions and medical personnel, and this offers wide choices to consumers in the medical market place. At this point of time, it is essential to survey on the primary factor of gratification for the patient in the Dental clinic, as well as on the problems and suggestions in medical service. Purpose : The analysis in this study shows essential factors and expected influential elements in satisfaction of the patient in the Dental Hopsital, and strategic suggestions for the provider of dental service, which can be of benefit to the prospective customer as well as can make improvement in the quality of dental treatment service. Material and method : This study had been researched by collecting and analyzing the organized questionnaires, which were filled in directly from 784 patients, who visit Dental Hospital, Yonsei University in Seoul, from January 23rd to April 15th. Result : It can be summarized like the followings. 1. The social and demographical peculiarities of respondents are as follows. Samples of gender and marital status are adequately extracted, but data on occupation and treatment are are under a bias toward students, undergraduates and graduate students, and orthodontics. 2. 74% of patients who answer the questionnaire were highly satisfied with the service of dental clinic in the section of overall satisfaction. 3. The survey result about specific service of dental treatment, within sections of independent variables, is like the followings; Patients are highly gratified with service system, kindness, explanation, explanation on expected waiting hours, reservation system, emergency measures, expert treatment, existence of knowledge of dentistry, size of hospital, disinfection, equipment and parking, but lowly satisfied with expense of treatment, preparatory hours for treatment, waiting hours, treatment hours and the period of subscription. 4. The correlation analysis showed that there is no significant linear relationship between the independent variables. 5. The probit regression analysis showed that 8 out of 34 independent variables explained the dependent variables at the level of 0.01. 6. It shows that 8 independent variables, which can affect customers 'satisfaction, are clearing up of inconvenience, service system, kindness, explanation, treatment hours per attendance, reservation system, existence of knowledge of dentistry, and contentment of equipment in the hospital. Conclusion : The consumer's satisfaction totally relies on subjective evaluations of customers. Providing appropriate service, which can meet the criteria for the customer who demands various wares, pursues luxury goods, and expects high quality of medical service, is essential to fulfill patients' satisfaction. Many medical institutions do their best to satisfy their customer, touch their consumer, and offer patience centered services, and it is also applied to the field of dentistry. Establishing brand new strategic managements and elevating the quality of dental service based on this survey are required to improve the satisfaction of patience in the Dental Hospital.
The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.