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Computer Science
Medicine

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Positive Emotion Amplification by Representing Excitement Scene with TV Chat Agents

This paper proposes emotion amplification for TV chat agents allowing users to get more excited in TV sports programs, and a model that estimates the excitement level of TV programs based on the number of social comment posts. The proposed model extracts the exciting intervals from social comments to the program scenes. By synchronizing recorded video streams and the intervals, the agents may talk with the user dynamically changing the frequency and volume of upbeat utterances, increasing the excitement of the user. To test these agents, participants watched TV content under three conditions: without an agent, with four agents that utter with a flat voice, and with four agents with emotion amplification. Results from 24 young adult Japanese individuals showed that their arousal of participants’ subjective and physiological emotional responses were boosted because of the agents, enhancing their motivation to interact with the agent in the future. With empirical evidence, this paper supports these expectations and demonstrates that these agents can amplify the positive emotions of TV watchers, enhancing their motivation to interact with the agent in the future.

proposed for users lacking natural communication [4][5][6]. Kanda et al. [7] stated that humans and robots need to build a friendly relationship. If an agent, represented by a dialog robot, can build a trusting relationship with a user, it can encourage behavioral changes and provide independent support to the user. Current developments of user-interactive agents have focused on behaviors that elicit amusement, gestures, and speech synthesis [8][9][10]. However, understanding the context of a user's utterance and providing a flexible reply are difficult tasks for agents because their dialog is typically controlled on a per-scenario scenario basis. Moreover, monotonous utterance content and lack of interest are thought to demotivate the continued use of a dialog agent.
To overcome the existing limitations in communication agents, researchers have focused on the continuous dialog to maintain the user's desire to use the agent. Here, using TV chat agents, we propose a lively mood presentation system.

Dialog Agents
Dialog agents employ one of two categories of dialog systems (task-oriented dialog systems, such as traffic guidance and seat reservation that perform purpose-driven utterances, and non-task-oriented dialog systems, in which the dialog itself is the objective). In non-task-oriented dialogs, such as chat, the dialog must be continued by motivating the user's willingness to interact with the agent. Many studies have attempted to continue the dialog by semantically connecting the utterances. For example, Tsunomori et al. [11] proposed a system that analyzes human dialog and web data, prepares a large-scale dialog database, and outputs the sentences judged as the most natural responses to user input.
The dialog between the user and the agent is not sustained by semantic consistency alone. If the robot's utterances maintain semantic consistency, users may get tired, and thus, long-term interaction will eventually fail. Therefore, the agent must arouse the motivation of the user to talk with it. Miyazawa et al. [12] presented information with unexpectedness and novelty, and introduced humanity and other social aspects into the dialog. These high-level social skills are expected to promote continued use of the dialog system. They highlighted the importance of introducing the two novel features in their system.
To improve the sociality and novelty of interactive agents, Minami et al. [13] developed a TV chat agent system that uses comments on social networking services (SNS), which designed for chatting while watching TV programs. The agent reads out the SNS comments and repeats the user's utterances. By reading the SNS comments, the agent speaks in a context that matches the content of the TV program. However, behaviors such as appropriate utterance intervals of agents were not discussed.
Iio et al. [14] considered the sociality of agents and investigated the effect of multiple dialog robots on the user's sense of dialog. After talking with one, two, or three robots, the users evaluated their impression of the robot. A conversation with three robots was considered as "establishing a dialog", and "thinking about the contents of the robot" was rated more positively than having a conversation with one robot.

Possibility of Emotion Amplification by Empathy between Humans and Robots
The feelings and impressions of users with the presence of agents were investigated. Matsumoto et al. [15] assessed the subjective evaluations of a participant watching a movie alongside an agent. The participants recorded more amplified emotions than after watching the movie by themselves. The movie was known to invoke certain emotions, which were reflected in the body movements and prosody information provided by the agent. It was suggested that the user's emotion tends to become higher when watching the movie with the agent than when watching the movie alone. When the robot matches the human emotions invoked by the video, the resulting sense of empathy may improve the impression that a user feels not only for the robot but also for other phenomena.

Analysis of Comments on Social Media
Generally, when a TV program arouses viewers, the number of comments on SNS often increases rapidly. Accordingly, some researchers have estimated the emotional arousal level of TV programs from the number of comments on SNS [16][17][18]. Shamma et al. [19] proposed a method, in which it divides a TV-broadcasted debate into topic units and estimates the arousal points in each topic, detecting the climax point from the average and standard deviation of the number of comments in several sections before and after the peak point of transition of the number of SNS comments. However, it requires information on the number of comments for judging the peak points in future. Thus, the climax point cannot be detected in real time.

The Goal of the Present Study
We propose the method "emotion amplification by representing an emotive mood related to a TV scene" that is designed for TV chat agents aiming to improve the sociality of the agents proposed by Minami et al. [13], in which agents watch TV programs alongside with the users. For example, when watching live sports, such as a football game, the agent reacts positively to scores and fine play, creating a sense of affective empathy and presence with the user. As multiple agents improve the sense of dialog (Section 2.1), a lively mood is expected. We expect the agent continues short chats rather than continuing to talk about one topic with a user, and emotions and cheers can be mainly exchanged about common content.
We also propose an estimation model that can detect the climax point of TV in real time using the transitions in the number of comments posted on SNS. The agent can dynamically change its behavior to present the degree of excitement level to the user. The degree of excitement falls into four levels. These levels allow the agent to change its behavior during the climax in stages.
To evaluate our proposal, we asked participants to evaluate their impression of an agent implementing the proposed system and measured their subjective and objective (physiological) emotional responses while watching TV programs.

Proposed Method Implementation
From an emotional perspective, a high-positive and high-arousal state is the excited state while watching TV [20]. Valence (the qualitative component) and arousal (the intensity of the positive or negative emotion) represented the subjective emotional experience. Furthermore, when excitement is amplified, the arousal of positive emotional states is enhanced. Meanwhile, the excitement aroused by TV programs is assumed similar to the excitement aroused by SNS activity. To present the same excited mood as a user, we propose the following two requirements of an agent.
1. The agent estimates the degree of excitement elicited by a TV program in real time. 2. The agent decides and operates its behavior from the estimated degree of excitement.
When multiple agents express an excited mood, the agents' behavior must respond to the changing degree of the user's excitement. In this study, the agents were four robots named RoBoHoN [21] (SHARP, Sakai, Japan). Each robot is a 19.5-cm-high easily carried robot, which is considered as a suitable daily-use agent. The agent utterances were created in the speech synthesis software VoiceText [22]. In this implementation, the agent neither recognizes the user's natural language voice nor implements an automatic response.

Estimating the Degree of Excitement
As mentioned in Section 2.4, we propose an estimation model detecting the degree of excitement on TV in real time. By analyzing the number of SNS comments posted within a certain period, we estimated the degree of excitement. The comments sourced from Twitter [23] and Nico-nico Jikkyo (live Bulletin Board System in Japan) [24] are the comment source. Groups of 5 s are treated in sections because 5 s is the boundary frequency below which an application programming interface restricts access to SNS comments. Our estimation model inputs the number of SNS comments posted in 5 s intervals and then outputs the degree of excitement. The degree of excitement E(%) is a function of SNS comments C i in the last 5 s and the average number of comments µ during the last 30 min: less than min threshold) Figure 1 shows the process flow of the model. To elicit different behaviors in the agents, we divided the degrees of excitement into four levels. Figure 2 shows the output of the model and the criteria for classifying the levels.

Validation of the Estimation Model
To verify the accuracy of the created model, we compared its output with the correct degrees of the excitement elicited by TV programs, which were manually created in advance. For the accuracy verification, we used the TV content of the match between the National Football Team of Japan and Paraguay broadcasted on 5 September 2019. We selected 10 min from the first half (20 min) and 47 s of the relayed game in the same first half (30 min). The 10 min period, which includes two goals and one decisive chance, was considered as a suitable ground truth. The ground truth data were created by 10 male adults aged 23-30 years. In every second, the TV scene was judged by a binary value: 1 (exciting) or 0 (unexciting). However, in every interval (where one interval is equal to 5 s), the degree of excitement was scored on a scale from 0 to 50. Figure 3 compares the degrees of excitement estimated by our model and the ground truth. As shown in Figure 4, the rising edge of the ground truth was detected 10 s earlier than the estimated degree of excitement. Two possible causes of this lag are detection of the degree of excitement after a delay of up to 5 s the time interval of one section and the difference in the evaluation timing between people and SNS users. The ground truth excitement evaluation was inputted manually, and the assessors tended to judge the excited mood when a ball pass would likely achieve a chance. However, many SNS users commented once a series of soccer games was finished. These different judgment tendencies in the manual and SNS data probably delayed the excitement degrees in the model from those of the human evaluation. However, provided that the degree of excitement is correctly estimated, the degrees of excitement in the TV program can be synchronized with the estimated excitement degrees by time-shifting the playback of the recorded program. Figure 4 compares the correct data and the data obtained after shifting the estimated degree of excitement by 10 s.
When the two datasets were synchronized, the timings of their rising edges were consistent at multiple locations. In a statistical investigation of the estimated versus ground truth data, the correlation coefficient was 0.714, confirming a strong correlation. Therefore, the proposed method can estimate the degree of excitement with a delay of 10 s.

Determining the Behavior of the Agents
There are two classifications of behavioral factors of TV chat agents: those related to speech and motion. Here, we focused on the factors related to speech. After analyzing how people gain excitement from TV programs, we determined the speech behavior parameters of TV chat agents. To analyze the excited moods of people, we video-recorded the behaviors of five male adults watching a soccer match, that is, the FIFA World Cup Japan vs Poland game held on 18 June 2018, for the first time. A snapshot of the video recording is presented in Figure 5. We took the videos behind and in front (built-in camera of the laptop) of the participants and also used the build-in microphone of the laptop to record the speech of the participants. We then extracted the utterance frequency and prosody information (utterance interval, speech rate, volume, and pitch). These parameters are defined and calculated as follows: utterance interval: length of the silent section between utterances by the same participant speech rate: mean number of moras per second, obtained by dividing the number of mora by the utterance interval length volume: mean value of the power spectrum of the voice section pitch: The fundamental frequency ( f 0 ) of the speech was extracted and averaged over the logarithmic domain. The average f0 after removing the unvoiced sections was determined as the pitch.
In Japan, mora means a "beat", and each mora is temporally equivalent. It has the structure of "(consonant) and vowel", but there are exceptions such as "n", which has no vowels, and "tsu", which is applied to the sound itself [25]. Through video analysis, we confirmed that the speech rate significantly depended on the strength of the positive emotion. In this study, we considered that the number of comments on SNS increased when the degree of excitement was raised in the TV program. Therefore, we focused only on the arousal dimension on the affect grid ( Figure 6) [26] and ignored the strengths of pleasant and unpleasant emotions. Thus, the speech rate of the TV chat agent was fixed, and the VoiceText parameter was set to its default value (100). It was confirmed that the there were differences in utterance intervals, volumes, and pitches between the excited and non-excited moods. Thus, using the previous method [27], we converted volume and pitch to VoiceText-specific parameters for use with VoiceText. Table 1 listed the behavior parameters obtained by the analysis. To represent levels 3 and 0, we computed the mean values of the participants in the excited and non-excited moods, respectively. The parameters at levels 1 and 2 were obtained by linear interpolation between those of levels 0 and 3. The agents dynamically change their parameters according to the estimated degree of excitement, and their speech reflects the excitement level of the user.
Since the comment of the robot is randomly selected from a group of comments made by SNS users who watched the TV content, the mainstream comments are generally selected according to the TV content at that time. In this experiment, we selected SNS sources that are used by users whose favorite teams are the same as the robot users, so the comments of SNS users who watched the TV content will have the same tendency as the users. Therefore, even if we randomly select a speech comment from that group of comments, a comment that is generally appropriate for TV content will be selected.

Experimental Conditions
To verify the amplification of emotions and motivation of human-agent interactions of our TV chat agents, we evaluated the emotional responses of a user while watching TV programs with the agents. Specifically, using the football game contents, we evaluated the subjective and objective responses. Using the affect grid, the subjective valence, and the arousal (which reflects the energy level of the emotion [26]), we qualitatively assessed the subjective emotion responses. To complement the subjective rating, which can be biased by factors such as the demand characteristics [28,29], we measured some physiological responses related to emotion, namely, the electromyography (EMG) signals from the corrugator supercilii (i.e., brow lowering) and zygomatic major (i.e., lip-corner pulling) muscles, and the skin conductance level (SCL). The muscle signals and SCL reflect the emotional valence and arousal responses, respectively. Psychophysiological evidence indicates that relative to emotionally neutral events, positively arousing events reduce the activity of brow lowering, increase the activity of lip-corner pulling, and raise the SCL [20,30].

Participants
One of the factors that may affect the impression evaluation is the participants' interest in a TV program. Thus, we only recruited participants who met the experimental criterion: "being interested in soccer". A total of 24 Japanese volunteers (4 women, 19 men, and 1 unknown gender; all aged in their twenties) was recruited for the study. We determined the required sample size in an a priori power analysis using G*Power software ver. 3.1.9.2 [31] based on a preliminary experiment, in which a similar procedure and facial EMG recordings were implemented on a different sample (n = 5). From the results, the effect size was estimated at an α level of 0.05 with power (1 − β) of 0.80 was assumed. The power analysis revealed that 24 participants were needed for a meaningful study. This study was conducted under the Declaration of Helsinki and was approved by the Ethics Committee of the Nara Institute of Science and Technology. Written informed consent was obtained from all participants, and all participants received a detailed explanation of the experimental procedure.

Agent Conditions
The experimental results were acquired and compared under the following three conditions: No agent: the participants watched the video alone. Neutral agents: the participants watched the video with four agents speaking with mixed behavior parameters. Excited agents (proposed method): the participants watched the video with four agents responded to an exciting scene in the video, enhancing the participants' excitement level.
Under the neutral agent condition, the speech rate, pitch, and volume of the agents' utterance were fixed at 100 in VoiceText.
It is expected that the arousal level and user's motivation to use the agents to be highest during interactions with the excited agents, lower with the neutral agents, and lowest with no agent. The agents recited the SNS comments with the utterance parameters explained in Section 3.3, which depended on the estimated degree of excitement. The agents then uttered the voice generated in advance based on the degree of excitement. As the agent was operated in real time, the timing of our estimation model was shifted by 10 s.

TV Content
To convey the exciting scenes to the participants, The titles of the selected games are as follows. These contents included exciting scenes at well-clarified timings, such as chance scenes, fine plays, and goal scenes, which are expected to increase arousal and pleasant emotions on the affect grid. We applied the proposed model that estimates the degree of excitement to the SNS comments related to the game broadcasts and then selected the scenes determined to elicit an excited mood. We prepared 1.5-to 2-min 12 videos that captured these exciting scenes. Figure 7 shows the examples of the agent's utterance for each level of excitement and the expected interaction with a participant.

Procedure
The experiment was conducted individually in a soundproof room (Science Cabin, Takahashi Kensetsu, Tokyo, Japan), where each participant wore a physiological measuring device while watching the video (Figure 8). Three trials (one under each condition) were performed in each session, and each participant underwent four sessions. We randomized the order of TV programs and conditions among the participants. After each trial, participants rated their emotional experiences on a 9 × 9 affect grid. Using the seven-point Likert scale (1: not at all, 7: very much), we also evaluated the agent by answering the following two questions: "Were the agents in an excited mood?" and "Did you feel empathy with the agents?" Thus, for subjectively evaluating the user's impression of the agents were created by a proprietary methodology. The aim was to reduce the work burden on the participant by acquiring the minimum required information for evaluating the agents of the experiment. To support the subjective results obtained in the experiment, we acquired the biological information of the participants-skin conductance and facial EMG-as objective indexes. After each session, the participants also selected one among the three conditions that they would care to repeat. Finally, the participants were asked to briefly and freely describe their responses during the session.

Analysis
In every participant, the mean ratings and selection percentages were calculated under each condition. The physiological data were sampled for 10 s during the pre-stimulus baseline period, which is immediately before the presentation and duration of the stimulus period. We excluded the data from one participant because of equipment error. After rectifying the EMG data, the SCL and EMG data of each trial were baseline-corrected to their average values over the pre-stimulus period, and then averaged. The data outside >|3|SD in each participant were removed as outliers.
Our hypotheses were tested by independent t-tests (one-tailed), in which we detected differences between the no agent and neutral agent conditions, and between the no agent and excited agent conditions. We also exploratorily compared other directions and conditions using dependent t-tests (two-tailed). All results were considered significant at p < 0.05.

Emotional Ratings
Among the subjective ratings of valence and arousal while watching the TV contents (Figure 9), only the arousal ratings were significantly different between the no-agent and excited agent conditions (t(23) = 2.99, p < 0.005).

Physiological Activity
Among the physiological activity ratings, while watching the TV contents (Figure 10), only the SCL responses were significantly different between the no-agent and excited agent conditions (t(22) = 1.65, p < 0.05).  Figure 11 shows the excitement and empathy degrees rated by the participants interacting with the neutral and excited agents. Only the excitement ratings significantly differed between the two conditions (t(23) = 4.84, p < 0.001), indicating that excited agents were perceived as more excited than neutral agents.   Figure 12 shows the percentages of the conditions selected for reuse by the participants at the end of each session. There were significant differences between the no-agent and the proposed method (t(23) = 2.98, p < 0.005) and between the no-agent and neutral conditions (t(23) = 2.26, p < 0.05). These results indicate that watching TV contents alongside both the proposed and neutral agents motivated further use of the TV chat agent.

Enhanced Emotional Arousal Watching TV Alongside Excited Agents
Relative to the no agent case, the subjective ratings ( Figure 9) and physiological measures ( Figure 10) demonstrated that the excited agents significantly enhanced the subjective and physiological emotional signals of the participants. However, the valence measures were not significantly affected by the agents, indicating that the agents presenting an excited mood can amplify the arousal level of users without qualitatively changing their emotional experience. These results are consistent with previous findings, which reported that dialog agents could improve the positive experience of people watching TV or movies [14,15]. However, these studies did not manipulate the shared excitement levels in the agents nor assess the physiological aspects of the emotional responses, which likely introduce less bias than subjective ratings [28,29]. To our knowledge, we present the first evidence that agents sharing human excitement can amplify users' subjective and physiological emotional arousal while a user is watching TV.

Enhanced Excitement Recognition in Excited Agents
According to the impression ratings ( Figure 11), participants interacting with the excited agents became significantly more excited than participants interacting with the neutral agents. Therefore, our proposed agents conveyed excitement in their prosody. In contrast to our expectation, affective empathy was not significantly enhanced by the excited agents. To interpret this result, we reverted to the free responses of the participants. Some participants mentioned that the agents' comments were generally disappointing and discouraging. Based on these opinions, we speculated that SNS-based comments might not effectively induce empathy in general. Figure 12, shows that the participants were significantly more motivated to reuse the excited agent than the neutral agent, or to re-watch the video alone. It was considered that the emotional evaluation in the proposed system significantly enhanced the arousal level of participants, and that the dynamic behavior of the agents gave the impression of excited mood. Consistent with this interpretation, some participants mentioned that when watching TV without the agents, they missed the excited agents. Collectively, these data support our proposal, that agents presenting an excited mood can inspire the reuse of those agents.

Limitation
A limitation of this study should be acknowledged. The result of this study is that it was obtained under the condition that the delay of 10 s was not considered. This delay is possible to affect the user's impression of the robot, so a method that resolves the delay may be needed. To remove the delay, we could control the excitement timing of the agents through the time-shift playback function of the TV program. We can play back the recorded video while recording a TV program by the time-shift playback. Alternatively, we could give (in advance) the agent a fixed phrase appropriate for the situation, which could be spoken when the situation was detected.

Conclusions
We proposed TV chat agents that learn an excited mood based on SNS comments related to TV programs, and present the same mood to users watching the same TV contents. The aim was to improve the user's motivation to interact with the agents. We also proposed that the degree of excitement is determined from the number of SNS comments per second, and is classified into one of the four levels. Based on the estimated degree of excitement, the agent dynamically changes the interval, pitch, and volume of its utterances and presents an excited or non-excited mood to users. To verify the effectiveness of the excited agents, we compared the reactions of participants under the excited agent, no agent, and neutral agent conditions. We performed subjective evaluations using affect grid and a questionnaire and objective evaluations using physiological responses.
The arousal level becomes significantly higher in participants interacting with the excited agent than under the other experimental conditions; however, participants' emotional experiences were not significantly different among the conditions.
The participants also expressed more desire to reuse the excited agents than to reuse the neutral agents or re-watch the TV contents alone. Providing a lively mood with no delay might further amplify the user's emotions and enhance their motivation to interact with the agent.
During the present experiment, the participants watched a video recording of a soccer game targeting the arousal-pleasure dimensions of the affect grid. The mood presentation target of the TV chat agents in this experiment was excitement. In future work, we must comprehensively investigate whether the agent can enhance the user's emotions while watching other TV programs such as variety programs and news. This exploration would confirm the generality of the agent to any TV program. Another perspective is the impression of moods other than excitement; for example, we could evaluate whether the agents can enhance laughter. SNS comments include language and slang representative of laughter, which can be inputted to the model. Like excitement, the presentation of laughter might increase the user's emotions and motivation to interact with the agent. In this way, the moods of TV programs presented by TV chat agents can be comprehensively evaluated. At this time, the content uttered by the agents is randomly selected, so comments that are favorable to the user should be filtered to enhance the user's impression of the agent by the latest SNS analysis.


Domestic Tourism in Indonesia: Another Story of Inequality between Java and Non-Java

This study aimed to examine the pattern of movement of domestic tourists within one country, in this case, in Indonesia. Although many scholars had been addressed by tourism in their research, both international and domestic tourism, there was a limited study that examined the spatial pattern of domestic tourism, especially in developing countries. Therefore, this study intended to do so.This study employed a descriptive analysis of the new data set gathered from the Study of Domestic Tourism Market 2017. The result of this study showed that, although visitors can travel either inside one province or to many other provinces in Indonesia, however, the majority of visitors prefer to travel within one province, which might be related to several factors such as cost and transportation facilities. The data also showed evidence of inequality, especially when comparing Java and Non-Java Provinces. One of the reasons for those disparities can be explained by the fact that people living in Java tend to travel only to other provinces around Java Islands. Another reason is that the level of economic development differs from Java and the outer islands. Transportation access has also affected the disparities since all provinces in Java get benefited from the sophisticated and interconnected transportation systems. On the contrary, Non-Java Provinces are hindered by the limited access to transportation modes or by the expensive transportation cost. A big difference in the average income per capita between Java and Non-Java residents also contributed to the inequality in the number of tourists among the provinces. The individual with high income, of course, has more opportunity to do traveling to many places and to visit attractive sites.

INTRODUCTION *
The positive impact of the tourism sector on economic development has been widely recognized by many scholars [1]. Early findings by Pearce in 1981 classified the impact of tourism for the national economy closely related to balance of payment, regional development, and diversification of the economy, income levels, state revenue, and employment opportunities [2].
Foreign tourism allows the flow of money into the national economy that positively influences the country's trade balance and the government account [3]. Countries then could utilize the additional receipt from abroad to fund their national projects. As concerning regional development, tourism industries also establish in the peripheral area, sometimes remote, hence helps to advance and to spread the economic activities across the national boundary. Furthermore, tourism triggers diversification of the economy since there are lots of sectors involve in fulfilling the needs of visitors such as accommodation, transportation, restaurants, and tourist attractions.
Tourism positively influences not only tertiary sectors but also primary and secondary sectors [4]. When tourists buy the product of the tertiary * Correspondence address: Wini Widiastuti E-mail : wini.widiastuti@gmail.com Address : BPS-Statistics of Nusa Tenggara Barat Province, Mataram sector, it then increases the demand for raw or intermediate materials needed to manufacture such a product. For example, if many tourists ordered fried rice at a restaurant, then the demand for fried rice will increase. In order to fulfill the increase of consumer demand on fried rice, the restaurant will have to order more rice from supplier, which means there will be an increase in demand of rice as well.
Based on the origin of visitors, there are two types of tourist i.e. international tourists and domestic tourists. Some argue that international visitors could give high benefits to the economy because it is related to the inflow of foreign money. Inbound tourists from overseas could benefit the national economy through the inflow of money spent by foreign visitors while traveling. It can be pre-paid, during, or after the traveling take place. Aggregation of spending money by foreign tourists gives positive impact on the trade balance and government accounts [3]. Although the initial receipt could be lower for the fee that flows to foreign tour operators and for the cost of the foreign campaign, Pearce explained tourism allows the inflow of foreign currencies [2].
However, domestic tourism is also important because it can give more sustainable socioeconomic development in a region. Moreover, the money of domestic tourists will stay within the country, instead of flowing out of the country by traveling abroad. Although domestic tourism only utilizing the existing national economic resources, the impact of domestic tourism on national development is also as important as international tourism. First, countries with a high number of inhabitants provide an abundant supply of potential domestic visitors. Second, domestic tourism is arguably more sustainable than international tourism. Unlike international visitors that required submitting special permits prior to their traveling journey, the country's residents can travel around as they wish. Moreover, international tourism also subject to political tension, for example, travel warning issued by origin countries could prevent potential foreign visitors to come. In fact, travel advice has a negative impact on inbound tourism [5].
Third, it is true that on average spending by domestic visitors usually lower compared to international visitors. However, domestic visitors spend more than international tourists. The previous study found similar expenditure behavior and linkages between international and domestic tourists in Melaka [6]. They also noted the differences between those two types of tourists. The first type of tourist spends more money on luxurious accommodation, food, and beverages compared to the latter. It might be related to the length of stay as well as preferences. Therefore, the local economy could gain more comprehensive economic benefits by promoting both types of tourism.
Fourth, Zaei [7] argued that by encouraging domestic tourism could lead to strengthening national integration. The research stresses the importance of domestic tourism in Indonesia since the country put national integration as the objective of national development. Although many touristic places in one country usually offer quite similar amenities such as natural and cultural attractions, one place might have slightly differed from the others. Moreover, cultural attraction between provinces are different, even there is also apparent cultural differences within one province. Such differences could trigger people to visit another place.
Given the intriguing advantage of tourism, a lot of countries set tourism as a leading sector of their economic policy. It is not limited to developed countries but also developing countries, including Indonesia. Based on the Medium-Term Development Plan 2015-2019 [8], Indonesian tourism industry also labeled as one of the country's leading sectors. Unfortunately, many countries heavily based their tourism policy in favor of international visitors, while domestic visitors still underrepresented [9]. The action that they need to do is to promote both international and domestic visitors equally [10].
Although previous research attempts to study domestic tourism, especially in developing countries, is abundant, there have been only a few studies that include the spatial matter in their analysis. Therefore, this study aims to examine the pattern movement of domestic tourist within one country, in this case, in Indonesia.

MATERIAL AND METHOD
This study employed a descriptive analysis of domestic tourism data at the provincial level in Indonesia. All provinces included in the analysis, including North Kalimantan, the newest province in the country. The data were retrieved from the result of the Study of Domestic Tourism Market 2017 conducted by the Ministry of Tourism and BPS-Statistics of Indonesia. Besides the total number of travelers from each province, the data also disaggregated into two types of domestic tourists, who travels within the province and the other one who travels between provinces in Indonesia. Therefore, the study examined three types of domestic tourists, which are total, within the province, and between provinces.
Apart from that, this study also analyzes differences in domestic tourism between Java and Non-Java. The first-category includes provinces located in Java Island, which are Jakarta, West

RESULT AND DISCUSSION
Indonesia's domestic tourists travel inside their province as well as to other provinces. In 2017, the number of domestic tourists reached 270,82 million travelers. Most of them trip within a province, with the percentage slightly above 70%, while the other 30% travel to places located in another province (Fig. 1). It suggests that travelers prefer to travel inside a province compared to outside the province.  Looking at the regional pattern, the majority of domestic travelers were coming from West Java as many as 43.78 million tourists, followed closely by East Java, with only less than 9 thousand travelers at 43.69 million tourists. Meanwhile, the smallest number of domestic tourists come from the eastern part of the country, which is North Maluku and West Papua, with 0.51 million tourists and 0.58 million tourists, respectively. In other words, there is evidence of a high gap in the number of domestic tourists among provinces in Indonesia.
The trend also persistent when examining domestic tourists based on their destination, whether they conducted the trip inside or outside one province. The differences between provinces were considerably high for both types of tourists. As can be seen ain Table 1, for the first type of traveling, the maximum number reached 37.34 million travelers, and the minimum number documented at 0.39 million travelers. As for the latter, the maximum number reached 19.97 million travelers and the minimum number only 0.11 million travelers.
Which province position at the top and the bottom of the rank, however, differs from the aggregate. Figure 1 showed that the highest number of tourists traveling within their province observed in East Java, and the lowest number has occurred in North Maluku. Meanwhile, the highest number of travelers visiting another province is coming from Jakarta, and the lowest number is coming from Bangka Belitung Islands.
Even though Java only consists of six provinces, the vast majority of domestic tourists are from Java, which was 62.7%, while the rest of the 28 provinces were shared, the remaining 37.3%. This feature (not surprising), since almost all Java provinces except for Yogyakarta, has a high number of domestic tourists that are above the national average (7.96 million). Meanwhile, only three out of twenty-eight Non-Java provinces surpass the national average, namely North Sumatera, South Sulawesi, and Bali. Moreover, only 15.7% of domestic tourists from non-java province travel to another province. It is far below the percentage of domestic tourists from java travel to another province that is 35.8%.
The matrix in Table 2 demonstrated that when they travel to the area outside their province, Java's domestic tourists mostly travel to another province around Java Island. The percentage was quite remarkable, which is 90% or 54.7 million travelers. In which West Java, Central Java, and Yogyakarta are among the most favorable  The behavior of Non-Java's domestic tourists was different from Java's domestic tourists. Instead of traveling amongst Non-Java province, the top two destinations are Java provinces, which were DKI Jakarta and East Java. In total, 35.3% of Non-Java's domestic tourists go to Java, while the majority of 64.7% visited Non-Java's province.
Disparities of domestic tourists among Java and Non-Java provinces might be related to several reasons. First is the availability of sophisticated and well-connected transportation infrastructure in Java. Moreover, the type of transportation also varied, such as planes, cars, as well as trains. It gives a wide range of options to choose from for potential travelers. Valek [11] suggested that the expenditure level could varied based on mode of transportation as well as time of traveling. The variety of transportation also influences the cost of traveling. Therefore, the one who traveling not only those who have high disposable income but also those who have moderate disposable income since they could choose cheaper mode of transportation.
Meanwhile, transportation infrastructures in Non-Java Provinces are less developed not only in terms of connection but also the variation of a mode of transportation. Some provinces, especially island provinces, are connected to another province by limited transport facilities, which is also costly such as plane. If they choose to travel using a cheaper mode of transportation, it takes a lot of time to reach the destination province. The abundant and cheap mode transport that available in Java pulls the potential domestic tourists to visit another province. Meanwhile, the limited and (sometimes) expensive mode of transportation in Non-Java provinces, hinders domestic tourists to visit other provinces Second, income inequality between Java and Non-Java provinces also plays important role in shaping the pattern of domestic tourism in Indonesia. Tourism activity is often seen as a leisure activity, in which one would pursue their passion for traveling if they already fulfill their basic needs. Less income household tend to spend their income on food and other important needs than on tourism and other leisure-related activities [12]. Therefore, tourism behavior is closely related to the income of an individual or household. The higher the income, the higher is the probability of individual or household to travel. Based on monthly expenditure per capita, the average expenditure per capita of Java is 16% higher than of Non-Java. Therefore, Java residents are more likely to conduct trips within their province as well as between provinces.
Third, the number of inhabitants in Java was slightly higher compared to Non-Java Provinces. In 2017, 57% of Indonesian population lived in Java, while the remaining 43% lived outside Java. It could be seen as the supply of potential domestic tourists in Java was also higher.

CONCLUSION
Tourism, as the engine of growth and the booster of economic development, has been widely recognized. Many countries, including Indonesia, set the tourism sector as a center of their economic policies.
The result showed that tourists travel either inside a province or travel to many other provinces in Indonesia. However, the majority of tourists prefer to travel only within one province. The data showed that there was an inequality in the number of domestic tourists among the provinces. Some provinces have a high number of tourists, while others have lesser. The data also showed evidence that the disparities in the number of domestic tourists were very prominent, especially when comparing Java and Non-Java Provinces.
One of the reasons for those disparities was explained by the fact that people living in Java tend to travel only to other provinces around Java Island. Another reason was due to the fact that the level of economic development differs from one province to another. Transportation access has also affected the disparities since all provinces in Java benefited from the sophisticated and interconnected transportation systems.
On the contrary, Non-Java Provinces are hindered by the limited access to transportation modes or by the expensive transportation cost. A big difference in the average income per capita between Java and Non-Java residents also contributes to the inequality in the number of tourists among the provinces. The individual with high income, of course, has more opportunity to do traveling to many places and to visit attractive sites.
In conclusion, to optimally utilize the potential of domestic tourism in Indonesia, this study recommends both the central and local governments to promote not only tourist destinationz in Java but also outside Java. It is also important to provide a cost-effective and interconnected transportation system among provinces between Java Island and other Islands. These policies could boost the number of domestic travelers visiting Non-Java provinces, which in turn also reduces inequality not only in terms of tourism but also in economic development. Along with traveling, domestic tourists were also transferring wealth from Java to other Provinces.


Effects of Moonlighting on Job Satisfaction in Public Institutions in Southwest Nigeria (A Comparative Analysis)

This study investigated the effects of moonlighting on job satisfaction between academic staff and medical doctors in Southwest Nigeria. The study employed descriptive research design and multi-stage sampling technique to select the respondents. Questionnaire was adopted as the research instrument and it was administered to 393 academic staff and 348 medical doctors respectively across various Universities and hospitals in Southwest, Nigeria. The returned questionnaire were coded in Excel and IBM SPSS 23 version respectively and were further analysed through t-test, analysis of variance (ANOVA), and multivariate analysis of variance (MANOVA). The study revealed that moonlighting has positive and significant effect on job satisfaction whereas the academic staffs moonlight more often than medical doctors. The study concluded that It was suggested that Management of Universities and hospitals should develop Human Resources Management practices that has potency of satisfying their employees with the aim of getting them more committed to their primary duties and assignments. In this way, moonlighting will be drastically reduced among academic staff and medical doctors.

addressing the effects that moonlighting has on employee job satisfaction. More so, while studies have focused on Universities and farmers, Abiodun-Oyebanji, (2012);Adebo, (2013); there is sparse of literature on health sector. It is against this that the study focused on addressing the dependent variables of commitment, retention and job satisfaction.

Methodology Research Design
In this study, descriptive research design was employed. Descriptive research designis a scientific method which involves observing and describing the behaviour of a subject without influencing it in any way. Descriptive research studies are concerned with describing the characteristics of a particular individual, or of a group. These types of studies which are concerned with specific predictions, with narration of facts, and characteristics concerning individual, group or situation are all examples of descriptive research studies.

Population
The population of the study consisted of all academic staff of selected public Universities and medical doctors of selected public hospitals in the six states of Southwest zone. However, the target population of the study covered all selected six Federal Universities as well as the six State Universities in Southwest zone. More importantly, a Federal Hospital and a State Hospital were chosen from each state in the study. The total number of population is 24,161

Sampling techniques
The study estimated the sample size through Taro-Yamane (1967) statistical formula cited in Isreal (2009) was considered and consequently applied to determine the appropriate sample size from the population of the study as follows: Where; n = anticipated total sample size; N = population size; e = acceptable error term 0.05 = level of statistical significance. Therefore, the total sample size is computed as: Academic staff = n= 393 medical Doctors = n=348 Employing Taro-Yamane formula implies that 393 and 348 would be the sample size for academic staff and medical doctors respectively as used in the study.

Variable measurement
Comparative effects of moonlighting on job satisfaction will not be significantly different between academic staff and medical doctors of public institutions in Southwest Nigeria.
Job satisfaction (JS) is the dependent variable which will be measured by job autonomy (JA), advancement opportunity (AO), salary (SR), rate of pay (RP), personal objective (PO), job flexibility (JF) and workload and management tools (WP) whereas moonlighting is the independent variable measured by addition to income (AI), skill diversity (SD), job autonomy (

Method of data Analysis
To estimate the comparative effects of moonlighting on job satisfaction between academic staff and medical doctors of public institutions in Southwest Nigeria. ANOVA test was employed.

Results
The table 4.8 presented the result of moonlighting effect on the job satisfaction for academic staff and medical doctors across the various institutions under consideration in this study. The result revealed that the mean and the variance of academic staff and medical doctors as a result of moonlight effect on job satisfaction were 873.8 and 48501.29 and 807.1; and 24098.32 respectively. The F-stat value of 0.613 < 4.414 the F-critical value and the probability value of 0.444 > 0.05 revealed the statistical insignificant difference between the academics and medical doctors across various institutions based on the moonlight effect on job retention of the professions under investigation.
Journal of Economics and Sustainable Development www.iiste.org ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online) Vol.11, No.4, 2020  The table 4.9 presented the result of moonlighting effect and job satisfaction for academic staff and medical doctors across the various institutions under consideration in this study. The result revealed the mean and the variance of the moonlight effect and job commitment for the academic and medical doctors respectively. The Fstat value of 10.220 > 3.020 the F-critical value and the probability value of 0.001 < 0.05 revealed the statistical significant difference between the moonlighting effect and job satisfaction for academics and medical doctors across various institutions under investigation. The table 4.10 presented the result of moonlighting effect on the job satisfaction for the academic and medical doctors across the various institutions under consideration in this study. The result revealed that the mean and the variance of academic and medical doctors as a result of moonlight effect on job satisfaction were 873.8 and 48501.29 and 807.1 and 24098.32 respectively. The F-stat value of 4.549 < 5.117 the F-critical value and the probability value of 0.062 > 0.05 revealed the statistical insignificant difference between the academics and medical doctors across various institutions based on the moonlight effect on job satisfaction for the professions under investigation. However, the F-stat value of 13.847 > 3.179 the F-critical value and the probability value of 0.000 < 0.05 revealed the statistical significant difference between the moonlight effect and job satisfaction for the academic and medical doctors across various institutions under investigation.  Summary of findings revelation from the study explicitly showed that the mean and the variance of academic staff and medical doctors as a result of moonlighting effect on job satisfaction were 873.8 and 48501.29; 807.1 and 24098.32 respectively which indicated that academic staff moonlights more often than medical doctors as a result of blocked promotion, job autonomy, additional income and skill diversity. Other variables accounted for moonlighting as a result of job satisfaction were salary, rate of pay, advancement opportunity, workload and management tool, and personal objectives. Furthermore, the study made it clear that there is significant difference between moonlighting effect and job satisfaction for academic staff and medical doctors across various institutions under investigation. Nonetheless, it is evidently revealed from the study that F-stat value of 4.549169 is less than 5.117355 F-critical value, this therefore implies that there is no significant difference between the academics staff and medical doctors across various public Universities and hospital in Southwest Nigeria, as such both academic staff and medical doctors of public institution engage in multiple jobs respectively. To ascertain the difference between moonlighting and job satisfaction, the F-stat value of 13.8472 is greater than 3.178893 the F-critical value and the probability value of 0.000 < 0.05 implies that there is statistical significant difference between moonlighting effect and job satisfaction for academics and medical doctors across various institutions under investigation. Based on this, the study concluded that effect of moonlighting on job satisfaction is positively and significantly different between academic staff and medical doctors of public Universities and hospital in Southwest Nigeria. Hence, this implies that moonlighting contributed to job satisfaction of academic staff and medical doctors. However, since, the mean of 873.8 for academic staff is greater than 807.1 for medical doctors, the study concluded that academic staff moonlight more often than medical doctors though not significant. The finding of this study is connected with Ara and Akbar (2016) who found notable impact of moonlighting on job satisfaction.
It has been empirically identified that job autonomy, advancement opportunity, salary, rate of pay, personal objective and workload and management tool were the influencing variables of job satisfaction leading to employee moonlighting. Therefore, all these factors should be well considered by the management of public Universities and hospital in order to reduce rate of moonlighting in the education and health sector respectively. This is because, if all these factors were not properly put in place and not in commensurate with the hours the employees gave to the institutions, there is possibility of moonlighting which will affect job commitment on students and patients respectively.

Conclusion and Recommendation
Based on the findings, the study concluded that moonlighting significantly affect job satisfaction with an increasing rate of moonlighter found in academic staff than the medical doctors in Southwestern region of Nigeria. With this evidence, moonlighting may be a hedging strategy against job insecurity and pay insecurity in the primary job. This could be attributed to the flexibility of the work schedule, the perceived level of job satisfaction from the secondary employment, and the entrepreneurial opportunities which were important determinants of individuals' decision to hold a second job.

Recommendation
Lecturers and medical Doctors as human resources play a significant role in the development of the nation but are among the most neglected public servants. Unlike machines, lecturers and medical doctors are complex beings; they have got needs, values and aspirations and react to situations around them. It is therefore recommended that Ministry of Education and Vocational Training, Nigeria Medical Association and government should ensure that they offer best terms and conditions of service, including attractive pay package comparable to other professions requiring similar qualifications. This will not only make their services more attractive but shall be instrumental in curbing growing cases of moonlighting especially in public Universities and hospital.