Impact of the MICE Industry on Overseas Tourism Income: A Case of Korea

Executive Summary

The MICE (Meetings, Incentives, Conventions, and Exhibitions or events) industry is a new growth industry, and known as a major contributor to the economic revitalization of a venue.

Major countries including Korea have tried to support the MICE industry. This paper analyzes whether the Korean MICE industry has a significant impact on overseas tourism income of Korea by correlation and ANCOVA (Analysis of covariance).

The results of correlation indicate that the number of overseas general tourists of Korea, the number of foreign attendees of MICE of Korea, the number of MICE of Korea, and the expenditure of a foreign attendees of MICE of Korea have significant positive relationships with overseas tourism income of Korea.

However, the results of ANCOVA with controlling the number of overseas general tourists of Korea are slightly different from the results of correlation. The results show that only the number of foreign attendees of MICE of Korea and the number of MICE held in Korea affects overseas tourism income of Korea positively when the number of overseas general tourists of Korea is controlled.

These results can be a reference for future policies of the MICE industry in Korea. First of all, the policies for the MICE industry should be focused on attracting a large number of MICE events and many foreign participants by effective marketing strategies. Second, from a long-term point of view, it will be necessary to enhance the attractiveness of Korea as a MICE destination and tourist spot to increase the number of MICE events and foreign attendees.

The MICE (Meetings, Incentives, Conventions, and Exhibitions or events) industry is a new growth industry, and MICE activity contributes greatly to the economic revitalization of a venue. It is also one of the fastest growing sector in tourism industry today globally and nationally (Kim, Chon, & Chung, 2003). The MICE industry is well known for its significant economic benefit for the region or nation where MICE events happen. For example, the per capita spending of MICE participants in Korea was 3,127 dollars as of 2015, which is 1.8 times more than 1,715 dollars of general tourists (Ministry of Culture, Sports, and Tourism in Korea, 2017). This is because the MICE industry is linked to diverse industries such as tourism and leisure industry, hotels, entertainment, food, transportation, as well as improving the image of the venue.

Major countries recognize the MICE industry as a high-value-added industry with a large impact on national economic growth, income and job creation; and establish policies and strategies for the development of the MICE industry (UN World Tourism Organization, 2006). According to the Union of International Associations (UIA), there were 11,000 international conferences held worldwide in 2016. Top five conference holding countries were Korea (997), Belgium (953), Singapore (888), USA (702), France (523) and Japan (523). Also, Singapore identified the 10 major areas of MICE such as design, education, healthcare, and sports, and has been focusing on attracting MICE in these areas to Singapore. Japan announced plans to foster the MICE industry in 2015 and has continued to strengthen brand marketing as a MICE destination. Major convention centers in Orlando, Houston, New Orleans, and Las Vegas in the United States are spurring the attraction of MICE through innovative renovations and expansion in 2017 (Lee, 2017).

In particular, the Korean government has tried to support the MICE industry since the Korean government selected the MICE industry as one of the new growth engines in 2009. In Korea, the convention centers were constructed after the Korean government passed a law in 1996 to foster the convention industry. A total of 13 convention centers was built and renovated in Korea including COEX in Seoul where the 3rd ASEM Summit in 2000, the 5th G20 Summit in 2010, and the 2nd Summit on Nuclear Security in 2012 were held (Association of Korean Exhibition Industry, 2018). Currently the Korean MICE industry has grown from 95,000 participants in 2011 to 1.56 million in 2015, up from $2,585 spending per participant in 2011 to $3,127 in 2015 (Ministry of Culture, Sports, and Tourism in Korea, 2017). In addition, the Korean government announced its plans to foster the MICE industry as a national strategic industry in February 2017 to gain competitiveness in the global competition for becoming attractive MICE destinations.

This paper will analyze whether the Korean MICE industry has a significant impact on overseas tourism income of Korea by correlation and ANCOVA (Analysis of covariance). The MICE industry has been seen as a major contributor to regional and national economies by many researchers and professionals. This economic importance of MICE works as a justification for spending public fund on MICE facilities and the bid processes so many countries invest in developing MICE facilities to get more economic benefit (Lee, 2007). The full support of the Korean government for the MICE industry is also due to the assumption that the MICE industry is a highly profitable industry compared to the other sector of tourism industry and will positively affect the national tourism income and further the national economy. The tourism administration is part of the public administration, and the ultimate goal of the public administration is to benefit the lives of citizens by supporting the will of them (Kettl, 2015). To achieve this goal, it is important to make the best of the limited government resources and the economic effect of the industry often becomes the one of criteria of budget allocation. Therefore, analyzing whether the rise of the MICE industry has a meaningful relationship with the tourism income will give meaningful insight to future direction of the MICE industry.

Literature Review

The literature review focused to find appropriate indicators to represent the attributes of the MICE industry and suggest the reasons that why MICE matters. In order to find the relationship between the MICE industry and overseas tourism income, it is necessary to provide representative indicators for measuring the MICE industry as well as measures for overseas tourism income. The literature review consists of three parts; the importance of the MICE industry, indicators to represent the MICE industry, and economic model and strategies for the MICE industry.

Why MICE matters

Reason for importance

Most literatures pointed out that the MICE industry is growing rapidly and profitable. The reasons that the convention industry creates high economic impact were explained well in some studies. First, usually the large number of delegates for one convention participate. Second, delegates stay longer and spend more than general tourists. Third, delegates tend to participate in pre- or post-tours. Fourth, industries affected by convention are various and interrelated such as food, lodging and shopping (Kim, Chon, & Chung, 2003). Also, meeting activities are high value added because they are connected with business tourism which has higher daily consumption by attendants and is more related with other sectors such as transportation and food services (Zhang, 2014).

The MICE industry also creates many non-economic impacts including image improvement, cultural exchange as well as great economic effect (Kim, Park & Lee, 2010). For example, the MICE industry is a vital part of the tourism industry within the Auckland, New Zealand because MICE attendees are recognized as a highly beneficial industry with small negative environmental and socio-cultural impact (Locke, 2010). Also, the MICE industry produces business networks and promotes delivery of knowledge, science and technology development as well as accelerates inflow of tourists to destinations which have seasonal changes in visitor numbers so destinations can overcome their seasonality (Dwyer & Forsyth, 1997).

Analysis of economic effects

Some literatures estimated and analyzed the economic effects of the MICE industry in specific regions to show the economic importance of the MICE industry.

A study suggested that the MICE industry is significantly important in several countries. An estimate of the direct economic impact of MICE activity in the UK in 2011 was suggested in the study, following TSA (tourism satellite account) approaches developed by United Nations World Tourism Organization (UNWTO) (Jones & Li, 2015). It was suggested that MICE in the UK directly supported £20.6bn of gross value added in the UK, with around 39% within the MICE industry itself. Also, tourism expenditure accounted for 10% of GDP and 9% of all employment in Auckland in 2007 (Locke, 2010).

The economic impact of the MICE industry in Korea was considered as quite significant. It was estimated by an input–output model (Kim et al, 2003). The study suggested that total expenditures by foreign delegates and convention hosts were estimated to be about US$130 million in 2000. This US$130 million created US$217 million of output, 13,702 full time equivalent jobs, and US$47.4 million of personal income to the residents. These results mean that the convention industry can be a high- value-added area. Also, the economic impact of the exhibition industry of Korea was estimated by calculating the exhibition industry’s total expenditure by hosts, exhibitors and foreign attendees through multiplier effect and an input-output (I-O) model (Kim & Chon, 2009). This study suggested that expenditure by foreign attendees was the highest, second highest was expenditure of exhibitors and then hosts. The total expenditure was approximately US$684.7 million constituted 0.0953% of the Korean gross domestic product in 2004. In addition, there was a study which examined the economic impact of the Daejeon convention center in Korea based on surveys and a regional input–output (I–O) model (Lee, C., Lee, M. & Yoon, 2013). The results of the I–O model presented that the Daejeon Convention Center created US$488 million of output impact, US$102 million of income impact, US$233 million of value added impact, and 10,211 jobs.

Also, conferences and conventions in a rural region was regarded as a facilitator to bring new money to the regions (Grado, Strauss & Lord, 1997). This topic was explored by analyzing expenditures of conference and convention participants and vendors (Grado et al., 1997). The study concluded that all visitors to conferences and conventions spent $114.53 per activity day as well as non-residents spending 85% more than residents. The result showed that most of the conference and convention attendees were non-residents and this led to a new money inflow into the region as they spent an average of $134.20 per a day.

The mega events were also considered as means for generating great economic effects. The economic effects of Rotary International 2016 Convention Seoul, Korea was estimated by using the multiplier effect of an input–output model with the data of expenditures of conference hosts, exhibition host, exhibitors, and foreign attendees (Kim et al., 2010). The result showed that the total expenditures by the four sources were US$70.2 million and this US$70.2 million produces US$132.8 million in output, 1,320 full-time-equivalent jobs, US$23.9 million in personal income for residents. In addition, this study showed that the average of the output, value-added, income, employment, and tax multipliers for the convention industries was higher than the average of other industries. This can be interpreted that the economic impact of the convention industry is greater than others’.

Literatures showed that the MICE industry is significantly important for the economy as well as for the society, by analyzing the reasons for importance and estimating real economic effects in some regions.

Indicators to represent the MICE industry

Expenditures of attendees

Many literature reviews agreed that the total expenditure of the participants would be the important indicator of the MICE industry and basis for the analysis of economic effects.

The expenditure generated by MICE events has been the basis for analyzing economic effects (Dwyer & Forsyth, 1997). Delegate expenditures were included as an important measure to assess the MICE industry in Pearlman’s study even though he doubted that no researcher agree that which measurement is the most appropriate one for ranking destinations’ performance (Pearlman, 2008). Spending of exhibition attendees was used as a significant factor used to estimate the economic effect of Exhibition industry (Kim & Chon, 2009). Also, expenditure by foreign delegates were suggested as major consideration for estimating the economic impact of the convention industry (Kim et al., 2010) and the data of higher expenditure of convention delegates was considered as an important factor for the high-yield nature of convention industry (Yoo, 2005). In addition, the expenditure of the non-local visitors to the events was considered as important factors to local benefits because non-local visitors are twice as beneficial for the host destination as residents who attend the local events because this group spends more and their expenditures cause a gain to the local economy (Kwiatkowski, Diedering & Oklevik, 2018).

As literatures suggested, the expenditure of attendees is an important indicator of the attributes of the MICE industry because it is found that participants of MICE spend more than general tourists.

Number of attendees

One of the characteristics that differentiates the MICE industry from other industries is that it attracts a huge number of participants in large MICE events (Ministry of Culture, Sports, and Tourism in Korea, 2017). These attendees spend on various related fields such as lodging, transportation, food and beverage, and shopping during their stay. Therefore, the number of attendees can be considered as one of the main indicators of the MICE industry.

The number of delegates in conventions was considered as an important factor to estimate the economic effect of the Korean convention industry (Kim et al, 2003). Also, a large data set including the total number of delegates and the number of companions travelling with delegates was used as a vital data to estimate the direct economic effect of the MICE industry (Jones & Li, 2015). Hodur and Leistritz (2007) explained that researchers should carefully deal with estimating attendance as well as attendee’s motivation to participate in the events when measuring economic impact of the MICE events. In addition, the number of attendance was considered as one of the basic elements for economic analysis to be collected through various surveys on convention attendees, exhibition visitors, exhibitors, convention organizers, and exhibition organizers (Lee, C et al., 2013).

Generally it is true that the more money flows to the host region if the number of attendance increases in MICE. So, the number of attendance can be a one of basic indicators for estimating the economic effect of the MICE industry.

Number of MICE

As UIA announces the number of international conferences held in each country annually, the number of the MICE can be an important measurement for representing the attributes of the MICE industry.

Number of the MICE has been used as an indispensable indicator in many literatures. The number of conferences and conventions was researched to estimate the economic effect of conventions and conferences (Grado et al., 1997). Also, Zhang (2014) conducted the venue survey to estimate the economic impact of the meeting industry in Denmark and the venue survey provides information regarding the number of meetings. In addition, the importance of attracting great number of conventions and meeting was emphasized as the final goal of destination marketing which generate benefits to the venues (Lee & Back, 2005).

These literatures showed that number of MICE is the one of significant indicators to represent the attributes of the MICE industry.

Number of nights stayed

According to Korea Tourism Organization (KTO), the attendees of the MICE held in Korea stay two days longer than general tourists. This is presumably because pre and after tours are often performed related to the MICE event.

The longer stay of MICE attendees than just pleasure travelers has been explained as the reason that the MICE industry attracts attention (Jones & Li, 2015). Also, the behaviors of attendees such as nights stayed was considered as major attributes of MICE. Lee and Back (2005) explained the importance of participation decision behavior of meeting attendees.

Tourism Income

MICE has been regarded a significant contributor to the tourism income of a nation or region. The expenditure of meeting industry accounted for 28% of total yearly tourism expenditure in Denmark (Zhang, 2014). Also, the Office for National Statistics (2014) estimated that the MICE industry accounts for around 40% of gross value added of tourism sector (Jones & Li, 2015). These literatures show that the MICE industry may be an important factor to increase overseas tourism income.

Economic models and other strategies for MICE 

Review of the economic model

The input-output (I-O) model has been widely used in economic analysis of MICE in most literatures but it has some issues to be careful (Lee, 2007). First, there are restrictive assumptions in the model such as no constraints on resources and it may result in inaccurate estimation of the real economic impact. Second, including expenditure by tourists not related to the convention or event in estimating the economic impact can result in overestimation. Third, the public investment required to host conventions and events should not be included as economic benefit to prevent a significant overestimation in result. Fourth, using employment multipliers in the model can be problematic because jobs created by special events or conventions are mostly short-term (Lee, 2007).

Attendee attributes and their motivation for attending are regarded as key issues for reliable estimation of economic impacts of events by the input-output (I-O) model (Hodur & Leistritz, 2007). First, researchers should consider factors that can change attendee attributes as well as getting enough samples to provide the desired level of confidence. Second, researchers should properly distinguish between the direct economic impact and the total expenditure of events by event visitors and participants. To accurately estimate the direct economic impact of an event, it is important to find out participants’ motivation for attending as well as find out what attendees would have done in the absence of the event because direct economic impacts represent new spending that would not have occurred without the event.

Other strategies for MICE analysis

There were several researches regarding various aspects of the MICE industry. Key performance indicators (KPIs) in the MICE industry were researched in Pearlman’s study (Pearlman, 2008). After analyzing surveys of 111 CVBs in US and Canada and industry secondary data such as labor rates, he made a selection of MICE KPIs such as exhibit hall and meeting room supply, labor rates, and attendance and delegate expenditures.

The characteristics and spending patterns of visitors in the local events were examined by data from 1011 attendees in 2013. This study suggested that researchers should understand visitors’ motivation, composition of visitors and average spending to estimate accurate economic impact of events (Kwiatkowski, Diedering & Oklevik, 2018).

The rapid growth of convention industry in Korea was explored by Yoo (Yoo, 2005). She provided a history of the development of the convention industry in Korea and assessed current convention market by SWOT analysis and suggested that Korea had great potentials to become a major destination in the future.

Most literatures suggested that the MICE industry accounts for significant part of the tourism industry and has great economic effect. However, there was no literature review which analyzed if the MICE sector had a statistically significant relationship with overseas tourism income with actual data set. In other words, there was no statistical analysis of the time series data for a certain period of time to see whether overseas tourism income of a certain country actually increased as the MICE industry improved.

Research Questions

This paper will empirically analyze whether the MICE industry actually affected the increase or decrease of overseas tourism incomes by using official time series data from Korean government. There are two research questions regarding this analysis:

1. Does the MICE industry have a significant relationship with overseas tourism income of Korea?
2. What aspects of the MICE industry contribute to increase or decrease overseas tourism income of Korea?

Regarding the first research question, literature review suggested that the MICE industry has a greater economic impact on the related industries such as lodging, food, and shopping than the general tourism industry, and participants of the MICE events spend more than general tourists. Therefore, it is meaningful to analyze empirically whether the MICE industry has a statistically significant impact on overseas tourism income when economic impact from general tourists is removed.

Regarding the second research question, some indicators that can represent the MICE industry were identified in literature review, and these indicators will be analyzed if they have a significant relationship with the increase or decrease of overseas tourism income. It is expected to be able to find the best indicator for the economic effect of the MICE industry through this analysis.

Hypotheses

Based on the literature review, expenditures of a foreign attendee, number of foreign attendees, number of MICE, and number of nights stayed by a foreign attendee can be selected as indicators that represent the attributes of the MICE industry. Also, it can be assumed that overseas tourism income will be increased when these indicators become positively higher with the number of overseas general tourists being controlled:

1. Controlling the number of overseas general tourists, there will be a significant difference in means of overseas tourism income of Korea between groups with different levels of expenditure of a foreign attendee of MICE held in Korea.
2. Controlling the number of overseas general tourists, there will be a significant difference in means of overseas tourism income of Korea between groups with different levels of number of foreign attendees of MICE held in Korea.
3. Controlling the number of overseas general tourists, there will be a significant difference in means of overseas tourism income of Korea between groups with different levels of number of MICE held in Korea.
4. Controlling the number of overseas general tourists, there will be a significant difference in means of overseas tourism income of Korea between groups with different levels of number of nights stayed by a foreign attendee of MICE held in Korea.

Research Design

Methodology

Correlation is used to find out if there are significant relationships between variables. After finding relationships between variables, ANCOVA (Analysis of covariance) is used to compare means of overseas tourism income between groups with different levels of each variable while the number of overseas general tourists is set as covariate to find the impact of the MICE industry on overseas tourism income of Korea, excluding the effects from overseas general tourists. ANCOVA is appropriate because auto-correlation errors occur in time series data and regression may not be the best methodology with auto-correlation errors.

Measurement

A dependent variable is the overseas tourism income of Korea, which is presented in numbers. The higher the number, the higher overseas tourism income.

Following founding in literatures, independent variables are set as the expenditure of a foreign attendee of MICE held in Korea, the number of foreign attendees of MICE, the number of MICE held in Korea, and the number ofnights stayed by a foreign attendee of MICE held in Korea. Four independent variables that are expressed in numbers in the original data set are re-coded to fit the ANCOVA analysis while they are used in form of numbers in correlation. Variables are categorized based on distribution[1]. The expenditure of a foreign attendee, the number of MICE and the number ofnights stayed by a foreign attendee were categorized into 1 (low), 2 (medium), and 3 (high). The number of foreign attendees was categorized into 1 (low), 2 (medium), 3 (medium-high), and 4 (high).

The control variable is the number of overseas general tourists of Korea and expressed in numbers. The higher the number, the higher the number of tourists.

Data Collection

For the independent variables, the publications of the Korea Tourism Organization were used. Specifically, for the expenditure of a foreign attendee of MICE and the number of nights stayed by a foreign attendee of MICE held in Korea, surveys on MICE participants by KTO from 2011 to 2016 were used. Also, for number of foreign attendees and MICE held in Korea, the MICE industry surveys by KTO from 2011 to 2016 were used. Data was collected in monthly form. However, monthly data for the expenditure and the number of nights was not available and the average for a year was put in every month for the expenditure and the number of nights.

For the dependent variable, statistical data of monthly overseas tourism income of Korea from 2011 to 2016 of Bank of Korea was used. For the control variable, statistical data of number of monthly overseas tourists of Korea from 2011 to 2016 of KTO was used. The data was modified by subtracting the number of foreign attendees of MICE from the total number of overseas tourists of Korea. The measurement of variables is shown in Table 1.

Table 1. Measurement table

Variables			Measurement	Level of Measurement	Data   Source
Dependent Variable		Tourism Income	number	Nation (Korea)	Bank of Korea
Independent Variables	Hypothesis 1	Spending	Categories   (1-3)	Nation (Korea)	Korea Tourism Organization
	Hypothesis 2	Attendee Number	Categories   (1-4)	Nation (Korea)	Korea Tourism Organization
	Hypothesis 3	MICE Number	Categories   (1-3)	Nation (Korea)	Korea Tourism Organization
	Hypothesis 4	Nights   Stayed	Categories   (1-3)	Nation (Korea)	Korea Tourism Organization
Control Variable		Tourists   Number	number	Nation (Korea)	Korea Tourism Organization

Data Analysis

Regarding correlation analysis, p-values will answer if there is a significant relationship between variables. Also, r-values will tell how strong a relationship is in a positive or negative way. Generally, a correlation of r =

±0.1 is a weak relationship, r =

±0.3 is a moderate relationship, and r =

±0.5 is a strong relationship.

Regarding ANCOVA analysis, p-values from ANCOVA (analysis of covariance) analysis with each IV will answer if there is at least one statistically significant difference in means of overseas tourism income with different levels of each IV while controlling the number of overseas tourists. That is, if p-value is smaller than 0.05, it means there is at least one statistically significant difference in means of overseas tourism income Also, if the result from ANCOVA is significant, Tukey’s Honest Significant Difference (HSD) test will be done to determine which of the pairs group means differ significantly. Eta-squared square test will be used to find out the relationship strength.

Results

CORRELATION

Table 2 displays basic descriptive statistics for correlation. There are 72 observations for each variable. Regarding the dependent variable, the mean monthly overseas tourism income of Korea is 1,263 million dollars with a standard deviation of 240. Also, subjects are all between 696.4 (the minimum) and 1,781 (the maximum) million dollars. Also, regarding the control variable, the mean monthly number of overseas general tourists of Korea is 958,222 with a standard deviation of 236,419. Also, subjects are all between 556,857 (the minimum) and 1,586,981 (the maximum).

There are four independent variables. The mean expenditure of a foreign attendee of MICE held in Korea is 2,771 dollars with a standard deviation of 329, and subjects are all between 2,501 dollars (the minimum) and 3,308 dollars (the maximum). Other descriptive statistics of independent variables are found in table 2 below.

Table 2. Descriptive statistics for Correlation (µ²=72)

Variables	Mean	Std. Dev.	Min	Max
Tourism Income	1262.7	240.2	696.4	1781
Spending	2770.92	329.19	2501.25	3308.02
Attendee Number	122130.7	51100.94	29295	241316
MICE Number	18537.92	5173.26	5389	29387
Nights Stayed	7.04	.55	6.38	7.77
Tourists Number	958221.6	236419.3	556857	1586981

Table 3 shows that the expenditure of a foreign attendee of MICE of Korea, the number of foreign attendees of MICE of Korea, the number of MICE of Korea, and the number of overseas general tourists of Korea have significant positive relationships with overseas tourism income of Korea. The number of nights stayed by a foreign attendee of MICE of Korea has no significant relationship with overseas tourism income of Korea.

The r = 0.71 between the number of overseas general tourists of Korea and overseas tourism income of Korea indicates that these two variables are strongly related in the positive direction. The r = 0.56 between the number of foreign attendees of MICE held in Korea and overseas tourism income of Korea and the r = 0.47 between the number of MICE held in Korea and overseas tourism income of Korea also indicate the strong and positive relationships. The r = 0.32 between the expenditure of a foreign attendee of MICE held in Korea and overseas tourism income of Korea indicates a moderate and positive relationships.

Table 3. The result of correlation

	Tourism Income	Spending	Attendee Number	MICE Number	Nights   Stayed	Tourists   Number
Tourism Income	1.0000
Spending	0.3201*   0.0061	1.0000
Attendee Number	0.5551*   0.0000	0.2610*   0.0268	1.0000
MICE Number	0.4693*   0.0000	0.3372*   0.0038	0.6530*   0.0000	1.0000
Nights   Stayed	0.0428   0.7211	-0.1794   0.1316	-0.2050   0.0841	-0.3910*   0.0007	1.0000
Tourists   Number	0.7110*   0.0000	0.5769*   0.0000	0.3939*   0.0006	0.3704*   0.0014	-0.1199   0.3159	1.0000

Through this correlation analysis, it is found out that the expenditure of a foreign attendees of MICE of Korea, the number of foreign attendees of MICE of Korea, the number of MICE of Korea, and the number of overseas general tourists of Korea are positively related with the overseas tourism income of Korea. However, correlation can only analyze the relation between two variables and cannot set control variables. In order to accurately understand the impact of the MICE industry on overseas tourism income, it is essential to control the impact of overseas general tourists on overseas tourism income because the impact of overseas general tourists on overseas tourism income can be quite substantial. ANCOVA is appropriate for this because auto-correlation errors occur in time series data and regression may not be suitable with auto-correlation errors.

ANCOVA

Table 3 displays basic descriptive statistics for ANCOVA. Each independent variable has 72 observations and 3 or 4 categories according to its distribution.

Table 4. Descriptive statistics for ANCOVA (µ²=72)

Variables		Frequency		%	Range
Independent Variables	Spending	low	48	66.7	1-3
		medium	12	16.7
		high	12	16.7
	Attendee Number	low	6	8.3	1-4
		medium	27	37.5
		med-high	35	48.6
		high	4	5.6
	MICE Number	low	14	19.4	1-3
		medium	45	62.5
		high	13	18.1
	Nights Stayed	low	36	50.0	1-3
		medium	12	16.7
		high	24	33.3

*Descriptive statistics for dependent variable and control variable are same as Table 2.

Expenditure of a foreign attendees

Regarding the equal-variance assumption of ANOVA, the data does not meet the assumption because the result of Bartlett’s test for equal variances shows p=0.045 < 0.05. However, given that the difference between the largest mean income 1,444 and the smallest one 1,216 is less than two times of the smallest income and ANOVA is a too robust test to violate the equal variance assumption, it is likely that the results of STATA may be interpreted as meaningful.

Table 5-2 shows that there is no statistically significant difference between the means of tourism income corresponding to each MICE number category with F=1.47 when the number of overseas general tourists is controlled. So, we cannot accept the hypothesis 1 that controlling the number of overseas tourists, there will be a significant difference in means of overseas tourism income of Korea between groups with different levels of the expenditure of a foreign attendee of MICE held in Korea.

This means that controlling the number of overseas general tourists, the overseas tourism income of Korea is not affected by the expenditure of a foreign attendee of MICE of Korea.

Table 5-1. The mean of overseas tourism income for each MICE number category

Categories	Low	Medium	High	Total
Means	1,216	1267.9	1444.3	1262.7

 

Table 5-2. The result of ANCOVA for expenditure of a foreign attendees

Source	Partial SS	df	MS	F	Prob > F
Model	2154862.9	3	718287.65	25.16***	0.0000
Spending	84085.168	2	42042.58	1.47	0.2366
Tourists   Number	1654164.9	1	1654164.9	57.94***	0.0000
Residual	1941417.8	68	28550.26
Total	4096280.7	71	57694.09

R-squared = 0.5261, Adj R-squared = 0.5051

Number of foreign attendees

Regarding the equal-variance assumption of ANOVA, the data meets the assumption because the result of Bartlett’s test for equal variances shows p=0.98 > 0.05.

Table 6-2 shows that there is at least a statistically significant difference between the means of overseas tourism income of Korea corresponding to each attendee category with F=4.95** when the number of overseas general tourists is controlled. So, we can accept hypothesis 2 that controlling the number of overseas tourists, there will be a significant difference in means of overseas tourism income between groups with different levels of number of foreign attendees of MICE held in Korea.

Table 6-1. The mean of overseas tourism income for each number of foreign attendees category

Categories	Low	Medium	Medium-High	High	Total
Means	911.28	1189.95	1351.01	1508.2	1262.7

 

Table 6-2. The result of ANCOVA for number of foreign attendees

Source	Partial SS	df	MS	F	Prob > F
Model	2438472	4	609618	24.64***	0.0000
Attendees	367694.21	3	122564.74	4.95**	0.0036
Tourists   Number	1040578.3	1	1040578.3	42.05***	0.0000
Residual	1657808.7	67	24743.414
Total	4096280.7	71	57694.094

R-squared = 0.5953, Adj R-squared = 0.5711

 

Also, table 6-3 shows that there are significant differences in mean overseas tourism income between low attendees category and medium one, medium-high one, and high one. Also, there are significant differences in mean overseas tourism income between medium attendees category and both medium-high one and high one. There is no significant difference in mean overseas tourism income between medium-high attendees category and high one. Table 6-4 shows that the number of foreign attendees of MICE of Korea explains about 18% of variability in overseas tourism income of Korea with the value of Eta-Squared .18.

Table 6-3. The result of Tukey’s Honest Significant Difference for number of foreign attendees

Attendees   categories	Contrast	Std.Err.	Tukey		Tukey
			t	P > | t |	[95% Conf. Interval]
2 vs 1	278.6638	88.90775	3.10	0.015	41.87178	515.4579
3 vs 1	439.7252	88.01971	5.00	0.000	207.9048	671.5457
4 vs 1	596.9167	128.5855	4.64	0.000	258.2567	935.5766
3 vs 2	161.0604	51.02436	3.16	0.012	26.67585	295.445
4 vs 2	318.2519	106.7251	2.98	0.020	37.16636	599.3373
4 vs 3	157.1914	105.1395	1.50	0.446	-119.718	434.1009

*1: low attendees category, 2: medium, 3: medium-high, 4: high

Table 6-4. The result of Eta-squared square test for number of foreign attendees

 

Source	Eta-Squared	df	[95% Conf. Interval]
Model	.5952893	4	.4142647	.6795394
Attendees	.1815323	3	.0241827	.3138027
Tourists   Number	.3856298	1	.2052057	.5237979

 

These results means that controlling the number of overseas general tourists, the overseas tourism income of Korea increases as the number of foreign attendees of MICE in Korea increases by more than a certain amount.

Number of MICE

Regarding the equal-variance assumption of ANOVA, the data meets the assumption because the result of Bartlett’s test for equal variances shows p=0.94 > 0.05.

Table 7-2 shows that there is at least a statistically significant difference between the means of overseas tourism income of Korea corresponding to each MICE number category with F=3.3* when the number of overseas general tourists is controlled. So, we can accept hypothesis 3 that controlling the number of overseas tourists, there will be a significant difference in means of overseas tourism income between groups with different levels of number of MICE held in Korea.

Table 7-1. The mean of overseas tourism income for each number of MICE category

Categories	Low	Medium	High	Total
Means	1047.29	1293.91	1386.64	1262.7

 

Table 7-2. The result of ANCOVA for number of MICE

Source	Partial SS	df	MS	F	Prob > F
Model	2250628.6	3	750209.54	27.64***	0.0000
MICE Number	179850.84	2	899925.419	3.31*	0.0424
Tourists   Number	1357499.6	1	1357499.6	50.01***	0.0000
Residual	1845652.1	68	27141.942
Total	4096280.7	71	57694.094

R-squared = 0.5494, Adj R-squared = 0.5296

 

Also, Table 7-3 shows that there are significant differences in mean overseas tourism income between low MICE number category and both the medium one and high one. There is no significant difference in mean overseas tourism income between medium MICE number category and high one. Table 7-4 shows that the number of MICE explains about 9% of variability in overseas tourism income of Korea with the value of Eta-Squared .09.

Table 7-3. The result of Tukey’s Honest Significant Difference for number of MICE

Tourism Income	Contrast	Std.Err.	Tukey		Tukey
			t	P > | t |	[95% Conf. Interval]
2 vs 1	246.6183	65.9356	3.74	0.001	88.68193	404.5546
3 vs 1	339.3456	82.98706	4.09	0.000	140.5657	538.1255
3 vs 2	92.72735	67.84225	1.37	0.364	-69.77601	255.2307

*1: low attendees category, 2: medium, 3: high

Table 7-4. The result of Eta-squared square test for number of MICE

Source	Eta-Squared	df	[95% Conf. Interval]
Model	.5494322	3	.3670587	.6465472
MICE Number	.0887932	2	.	.2161951
Tourists   Number	.4238012	1	.2052057	.555012

These results means that controlling the number of overseas general tourists, the overseas tourism income of Korea increases as the number of MICE held in Korea increases by more than a certain amount.

Number of nights stayed by a foreign attendee

Regarding the equal-variance assumption of ANOVA, the data does not meet the assumption because the result of Bartlett’s test for equal variances shows p=0.01 < 0.05. However, given that the difference between the largest mean income 1,263 and the smallest one 1,261 is less than two times of the smallest income and ANOVA is a too robust test to violate the equal variance assumption, it is likely that the results of STATA may be interpreted as meaningful.

Table 8-2 shows that there is no statistically significant difference between the means of overseas tourism income of Korea corresponding to each MICE number category with F=1.49 when the number of overseas general tourists is controlled. So, we cannot accept the hypothesis 4 that controlling the number of overseas tourists, there will be a significant difference in means of overseas tourism income between groups with different levels of number of nights stayed by a foreign attendee of MICE held in Korea.

 

Table 8-1. The mean of overseas tourism income for each number of nights stayed category

Categories	Low	Medium	High	Total
Means	1260.8	1267.86	1262.97	1262.7

 

Table 8-2. The result of ANCOVA for number of nights stayed by a foreign attendee

Source	Partial SS	df	MS	F	Prob > F
Model	2156054.3	3	718684.78	25.19***	0.0000
MICE Number	85276.575	2	42638.288	1.49	0.2317
Tourists   Number	2155603.8	1	2155603.8	75.55***	0.0000
Residual	1940226.4	68	28532.74
Total	4096280.7	71	57694.094

R-squared = 0.5263, Adj R-squared = 0.5054

This means that controlling the number of overseas general tourists, overseas tourism income of Korea is not affected by number of nights stayed by a foreign attendee of MICE held in Korea.

Discussion and Recommendations

The results of correlation indicate that the number of overseas general tourists of Korea, the number of foreign attendees of MICE of Korea, the number of MICE of Korea, and the expenditure of a foreign attendees of MICE of Korea have significant positive relationships with overseas tourism income of Korea. It means that overseas tourism income of Korea will be increased as the number of overseas general tourists of Korea go up. The same is true for the number of foreign attendees of MICE of Korea, the number of MICE of Korea, and the expenditure of a foreign attendee of MICE of Korea. The number of nights stayed by a foreign attendee of MICE of Korea has not a significant relationship with overseas tourism income of Korea.

However, the results of ANCOVA with controlling the number of overseas general tourists of Korea are slightly different from the results of correlation. The results show that there are statistically significant differences between the means of overseas tourism income of Korea corresponding to each categories of the number of foreign attendees of MICE of Korea and the number of MICE. However, there is no statistically significant difference between the means of tourism income corresponding to each categories of the expenditure of a foreign attendee of MICE of Korea and the number of nights stayed by a foreign attendee of MICE of Korea. It means that only the number of foreign attendees of MICE of Korea and the number of MICE held in Korea affects overseas tourism income of Korea positively when the number of overseas general tourists of Korea is controlled. This results from ANCOVA is meaningful because the impact of general overseas tourists of Korea on overseas tourism income of Korea is separated from the impact of MICE on overseas tourism income of Korea by setting the number of overseas general tourists of Korea as a covariate.

With these results from ANCOVA, the research questions can be answered. First, the MICE industry has a significant relationship with overseas tourism income of Korea in some ways because some indicators of the MICE industry have significant relationships with overseas tourism income of Korea. Second, the number of foreign attendees of MICE of Korea and the number of MICE of Korea contribute to increase overseas tourism income of Korea.

The results can be important references to future policy directions of Ministry of Culture, Sports and Tourism of Korea. First of all, the policies for the MICE industry should be focused on attracting a large number of MICE events and many foreign participants by effective marketing strategies. In particular, the growth rate of number of international conferences in the world over the past decade has slowed from 3.5% to 1.1%, while Asia has increased 5.5% and competition to attract international conferences among Asian countries is fierce (Union of International Association, 2015). In this situation, marketing strategies based on thorough market analysis are urgently required to attract more MICE events and foreign participants. According to Policies for the MICE industry announced by the Ministry of Culture, Sports and Tourism in 2017, the Ministry of Culture, Sports and Tourism of Korea will continue to strengthen collaboration with global MICE specialist organizations, expand the support for attracting important MICE events, and pursue specialized marketing that matches the characteristics of each international market of MICE (Ministry of Culture, Sports and Tourism of Korea, 2017). It is necessary to actively pursue these policies because they are in the right direction to attract more MICE events. In addition, considering that the brand ‘Korea’ is more known in the world market than local brands such as Busan, integrated marketing under the name of Korea should be actively promoted along with individual marketing of the convention bureaus by region.

Second, from a long-term point of view, it will be necessary to enhance the attractiveness of Korea as a MICE destination and tourist spot to increase the number of MICE events and foreign attendees. According to the 2015 Convention Competition Survey, the first reason for selecting the venue for international conferences is the support from the government or organizations and the second one is the attractiveness of the venue (Ministry of Culture, Sports and Tourism of Korea, 2017). So, the special space with the history and culture of the host country can be a crucial factor for attracting MICE events. As a part of strategy for the expansion of unique venues, the Ministry of Culture Sports, and Tourism of Korea is considering opening public cultural spaces such as the National Museum of Korea and the National Center for Korean Traditional Performing Arts to MICE events. This policy is meaningful to attract more international MICE events and promote Korean culture. In the case of cultural heritages such as Gyeongbok Palace, it is necessary to consider to open the venue to international MICE events within a range that does not harm cultural heritages. Also, it will be helpful to develop distinctive tourism programs which are specialized for each MICE events for increasing overseas tourism income as well as for increasing the attractiveness of Korea as a tourists spot. It is because that the ratio of foreign MICE participants who accompany companions reaches about 21% and most of foreign participants want to enjoy some tours with their companions in their free time (Ministry of Culture, Sports and Tourism of Korea, 2017).

Conclusion

The findings of this study are meaningful because it presents the direction of the future MICE policy by empirically analyzing the relationship between the indicators representing the MICE industry and overseas tourism income of Korea.

However, there are some limitations in this study. First, there is the limit of the data used in this study. Official statistics related to the Korean MICE industry were available only since 2011, so research has been conducted on a relatively small number of observations. Especially, there was no monthly statistical data for the expenditure of a foreign attendee of MICE and the number of nights stayed by a foreign attendee of MICE of Korea, so annual statistical data was used instead. To overcome these limitations, it would be meaningful to study again when data accumulates over time. Also, some literatures point out that it is better to separate the expenditure of MICE participants who would have visited the MICE venue in the absence of MICE events from the total expenditure to calculate the accurate direct economic impacts. It is because direct economic impacts represent new spending that would not have occurred without the event. However, the expenditure of a foreign attendee in this study does not reflect this motivation of participants so the result related to the expenditure of a foreign attendee may have some errors. It would be better to consider the motivation for participating the MICE events in future studies.

Second, there is the limit of ANCOVA itself. This study was analyzed using the ANCOVA methodology instead of regression because auto-correlation errors occur in time series data. ANCOVA can only set one covariate and the number of overseas general tourists of Korea which is most likely to affect overseas tourism income of Korea was set as a covariate. However, other factors other than the number of overseas general tourists of Korea may affect overseas tourism income of Korea. To overcome this limitation, time series regression with larger samples is recommended as the following study.

Despite these limitations, this study is meaningful in that it demonstrates that the MICE industry has some positive correlation with overseas tourism income even when the number of overseas general tourists is controlled. In particular, this study offers a reference for policies of the MICE industry in Korea. In other words, future policies should focus on increasing the number of MICE and the number of foreign participants rather than increasing the expenditure of a foreign attendee of MICE and the number of nights stayed by a foreign attendee of MICE to contribute to overseas tourism income of Korea.

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