All three main categories that emerge when speaking about COT could again be identified in the user generated comments on Facebook. Users are again discussing the environmental impact of COT to a destination like Lucerne, mostly commenting regarding pollution and overtourism. References to overtourism often speak of the lack there of. An example for a comment regarding pollution states that a terrible virus like Covid-19 can have positive effects and that the climate benefits from it, thanks to the limited mobility of millions. The environmental comments are discussed most dominantly, which are then followed by topics relating to economic impacts of COT, specifically, when it comes to the impact of COT on the national tourism industry in comparison to the local industry. The comments posted underneath this article relating to tourism behavior of COT are less discussed in absolute terms. This presents a difference to comments published before the COVID-19 outbreak. Moreover, there seem to be more comments linking to other topics that are not related to COT to Switzerland, for example, commenting on the nature of the Swiss tourism industry in general.

Table 2. Themes & Sub-themes Article Luzerner Zeitung

## 5 Conclusions

The results of this preliminary study show that there are three major themes that can be identified within the public discourse around COT in "old" and "new" media. Moreover, sub-themes of these three major topics can be found in articles and UGC on social media. Interestingly, so far there seem to be differences of the dominance of themes and sub-themes addressed in the mass media and addressed in the comments reacting to the articles on social media. All in all, Fig. 2 (see below) shows all the themes and subthemes that have emerged from the analysis of the two articles and their UGC, no matter the time frame (before or during Covid-19).

Fig. 2. Themes & Sub-themes

In the past years a major emerging topic within tourism has been so-called "overtourism". The results of this preliminary study show that the issue is not only a topic for researchers and policy makers but has become a hot issue within the public debate and that Covid-19 has dramatically impacted such discussions. The question that also arises from this research is: how are we planning on dealing with so-called "undertourism"?

Due to the preliminary nature of the empirical research, it has clear limitations regarding selected time frame, sample size, scaling and possibility of generalizing its results. Moreover, given that daily and weekly press has different editorial proposals, the authors are considering in future studies to separate these media outlets due to the nature of their publication frequency. The reason why they were considered as part of a single material in this study was due to the selection of newspapers based on their distribution numbers and not publication frequency. Additionally, quantitative methods will potentially also be integrated within this research (e.g. text mining using R) to enable an analysis of much larger corpora.

Nonetheless, the exploratory identification of major themes is crucial for the broader context of the research project related to the analysis of the public discourse around COT to Switzerland, because, in the end, these collected blocks of thematic references will serve as the basis for the critical analysis of different sentiments, narratives and arguments presented in the public discourse about COT to Europe. Of course, due to the current pandemic, it is unclear when and to what extend COT will return. Nonetheless, the authors believe that this kind of research will contribute to the "responsible and safe restart of tourism" [40], pushing for new findings in the field of "tourism-host-relationship" research, which will not only benefit academia but should present important results for any kind of political or private stakeholders that are concerned with the sustainable development of the tourism industry in Europe.

All kinds of stakeholders in the tourism sector (including DMO's) could greatly benefit from the results of this kind of research because even though they will not show the opinions of their locals, they will show which kind of narratives (including racist stereotypes), might currently polarize parts of the public agenda and, that could influence public opinion on tourism and COT. The knowledge gained from this research project should not only help to put in place the right kind of communication strategy to tourists but maybe even more importantly to the locals, minimizing stereotyped views, especially after Covid-19.

## References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

### A Model to Predict Users' Intentions to Adopt Contact-Tracing Apps for Prevention from COVID-19

Imane Ezzaouia1(&) and Jacques Bulchand-Gidumal2(&)

1 Economics, Business, and Tourism School, University of Las Palms de Gran Canaria, Las Palmas, Spain<EMAIL_ADDRESS>2 TIDES Institute of Sustainable Tourism and Economic Development, University of Las Palms de Gran Canaria, Las Palmas, Spain<EMAIL_ADDRESS>
Abstract. Technological advances are increasingly progressing and have brought unprecedented solutions for real-world problems for various domains, particularly, when it comes to a health-related domain. This study aims to examine the predictors of users' intentions to adopt contact-tracing apps for prevention from COVID-19. Based on the extended unified theory of acceptance and use of technology (UTAUT2), our research model incorporates the following eight constructs: performance expectancy, effort expectancy, social influence, facilitating conditions, perceived privacy, perceived value, safety and accuracy. The empirical results were obtained from a sample of 93 questionnaires (currently still in course). We used the partial least squares approach to test our hypotheses. The results reveal that performance expectancy has the strongest impact on the intentions to use contact-tracing apps. The accuracy, effort expectancy and social influence are also important, followed by perceived value, safety and perceived privacy. Facilitating condition is listed as much less important. The theoretical and managerial implications of these results are discussed.

Keywords: COVID-19 Contact-tracing apps Intentions to use

## 1 Introduction

The novel Corona Virus Disease (COVID-19) outbreak was declared by the World Health Organization as a global emergency on January 30, 2020. It is one of the major public health threats the humanity has faced over the last century.

Countries all over the world have tried to manage this challenging situation. Solutions implemented have been lockdowns, closing of borders and social/physical distancing, among others. However, these solutions have led, in most cases, to major socio-economic problems. Many jobs have been lost, the workforce of almost all economic sectors has reduced, the daily life has been dramatically disrupted, and frustration has increased among people [1]. However, this will not guarantee that the spread of the disease will stop once these measures are removed.

Therefore, new insights have been thought to track the pandemic and keep in quarantine only the infected people and those that came in contact with. This is the case of contact-tracing apps (CTA) that are considered as an important tool for measuring, preventing and reducing the spread of infectious diseases such as COVID-19 [2].

CTA have begun to gain attention from academic researchers. However, most of the available researches are focused on features, content, and technical characteristics [3]. Therefore, available studies have not analyzed users' behavioral intentions to use these types of applications.

Given their importance in preventing and stopping the spread of COVID-19, this paper seeks to develop a comprehensive model to examine the predictors of users' intentions to use CTA. In this study, we have adopted the extended unified theory of acceptance and use of technology (UTAUT2).

## 2 Literature Review and Development of Hypotheses

#### 2.1 Contact-Tracing Apps

CTA are mobile applications that can be installed on smartphones. CTA use the Bluetooth technology that helps to detect the nearest devices which had contacts with the infected individual's device. The Bluetooth technique operates by exchanging random tokens between the apps installed on smartphones of nearby people (i.e., less than two meters) and for a certain amount of time (i.e., 15 min or more). These tokens do not show the individual's identity and are time-varying strings (i.e., every 10– 20 min) for more privacy protection. The tokens are also sent to a central database of health officials, without private information of the users (e.g. GPS location). If later someone tests positive for COVID-19, the health officials will ask the infected person to release its data on the app (i.e., all the tokens the app has received from all nearby phones). Then, the app sends alert to the apps of those that the infected person has been in contact with and invites them to follow the required safety instructions [2].

As the adoption of CTA has given satisfactory outcomes in China and South Korea, more and more countries tend to use these types of apps once the lockdowns are lifted. For example, "TraceTogether" in Singapore, "Immuni" in Italy, "WIQAYTNA" in Morocco, and "Radar COVID" in Spain, among others.

#### 2.2 The UTAUT2 Model

The UTAUT was developed as a summary of eight technology acceptance models. UTAUT first proposed four constructs and four moderators. Venkatesh [4] further added three constructs and extended UTAUT to UTAUT2 to study the intentions and usage of technology in a consumer context.

UTAUT2 has been widely used on researches studying user adoption of technology in various contexts such as health and fitness apps [5]. We will now explain each of the constructs that form part of UTAUT2, and how we tailored them to suit the purpose of our study.

Performance Expectancy (PE). Performance expectancy is defined as the degree to which using a novel technology can bring benefits to users in performing particular activities [4]. This construct has proved to be a strong antecedent in consumer apps adoption studies [5].

Effort Expectancy (EE). Generally, users prefer a technology that responds to their needs with less effort [5].

Social Influence (SI). Social influence refers to the degree to which users perceive that important people (i.e. friends, family and colleagues) to them believe that they should use a technology [4]. Studies on apps have confirmed a positive relationship between social influence and usage intentions [6].

Facilitating Condition (FC). Prior studies on the acceptance of apps [6] revealed that user's perception of facilitating conditions (i.e., to be in possession of the resources and support to use a technology) directly influences the behavioral intentions to use a technology.

Furthermore, we will not include in our model the following three UTAUT2 constructs: hedonic motivation, price value, and habit for many reasons. First, CTA are conceived to help in preventing from the spread of COVID-19. Thus, there is no hedonic aspect as in games. Second, CTA are developed by authorities and they are free of charge. Therefore, price value does not suit our purpose. Third, habit refers to the degree to which consumers tend to use a particular technology. As this is an emerging pandemic, people are not used to use these types of apps.

However, we believe that there are four specific drivers of usage intentions tailored to the context of CTA for preventing from COVID-19. We will explain them in the following sub-sections.

Perceived Privacy (PPRI). Despite the wide use of apps for different contexts, the data privacy poses a threat to use and the continuous intentions of usage [7].

Perceived Value (PVAL). When consumers perceive that the benefits received outweigh the sacrifices, they may consider that the app is worthwhile and thus will adopt it [8].

Safety (SAF). Safety is considered as a key factor toward the use or continuous usage of apps specifically those dedicated for health care [9].

Accuracy (ACR). When users were not confident about the accuracy of the data, they tend to not adopt the app or abandon the use after their initial interaction [10].

## 3 Methodology

Due to the required safety instructions that have been applied by several countries worldwide, we conducted an online survey in English and French version. All items were measured by a 5-point Likert scale regarding the level of agreement, a total of 34 questions to test the constructs. The questionnaire also comprises general information of respondents (i.e., gender, age, approximate average daily use of apps, education level, and country of residence).

The target population is smartphones' users in general. Data are in progress of being collected, having started in July 2020. A total of 93 responses have been collected up to now.

We used the structural equation model (SEM) with partial least squares (PLS) method and PLS-Graph Software Version 3.3.2., to test the hypotheses and analyze the measurement and structural model. In our case, we used reflective measurement scales, since all indicators of a construct are interchangeable.

The sample size of 93 responses is considered appropriate for a proper PLS-SEM analysis (i.e., we used the "10-times rule", 10 times the largest number of indicators used to measure a construct within the model).

## 4 Findings

#### 4.1 Measurement Model

The results show that the convergent validity is confirmed, since all of the indicators have indicator reliability values that are close to the preferred level of 0.7 for an exploratory research. All values of composite reliability are larger than 0.6. Thus, demonstrating high levels of internal consistency reliability among all reflective latent variables (LVs). All of the average variance extracted (AVE) values are greater than the acceptable threshold of 0.5.

Additionally, all constructs have Cronbach's alpha values above 0.6, showing that all dimensions exhibited internal consistency. Furthermore, the discriminant validity is well established, since the square root of AVE of each LV is larger than the correlation values included in the row and column of such variable.

#### 4.2 Structural Model

Based on Fig. 1, hypotheses H1–H8, which predicted a positive relationship of the intentions to use CTA for prevention from COVID-19 were verified with significant evidences at the level of p < .001.

The Stone-Geisser's (Q2) is equal to 0.744, thus confirming that the measurement model is adequate and that the structural model has a large predictive relevance for the usage intentions of CTA.

The coefficient of determination, R2, is 0.874 for the usage intentions endogenous LV (see Fig. 1), which means that 87.4% of the variance of usage intentions is explained by the eight LVs (PE, EE, SI, FC, PPRI, PVAL, SAF, and ACR).

Fig. 1. Estimated causal relationships in the structural model

## 5 Conclusions

The purpose of this study is to examine the predictors of users' intentions to use CTA for prevention from COVID-19. We tested the impact of eight factors: performance expectancy, effort expectancy, social influence, facilitating condition, perceived privacy, perceived value, safety and accuracy, currently using a sample of 93 users' responses.

The major conclusion of this study is that the main factor that impacts the intentions to use CTA is the performance expectancy, which means that the expected benefits from using CTA could increase users' intentions to adopt these types of applications. The accuracy, effort expectancy and social influence are also important, followed by perceived value, safety and perceived privacy. Facilitating condition is listed as much less important.

## References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

### A Comparison of Hotel Guest Experience Before and During Pandemic: Evidence from Online Reviews

Irene Cheng Chu Chan1(&) , Jing Ma2 , Huiyue Ye2 , and Rob Law2

1 School of Hospitality Management, Macao Institute for Tourism Studies, Macao S.A.R., China<EMAIL_ADDRESS>2 School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hong Kong S.A.R, China<EMAIL_ADDRESS><EMAIL_ADDRESS>
Abstract. This paper compares the determinants of guest experience at luxury hotels in Mainland China before and during the pandemic—COVID-19. In particular, 740 Chinese reviews posted before the pandemic outbreak, and 1283 reviews posted during the pandemic were collected. Text analytics were applied to segment and count the frequency of words in these online reviews. The results show that the core dimensions of guest experiences at luxury hotels include services, room quality and settings, hotel facilities, dining, location, and environment. These core dimensions do not change regardless of the period before or during the pandemic. However, guests have higher expectations on hotel services such as late check-out and delivery service of takeaway during the pandemic. Online reviews amid-pandemic also contain words related to pandemic prevention and control measures, such as guest traffic and body temperature. Suggestions on operations and management are provided for hotel practitioners to improve their services during the critical period.

Keywords: COVID-19 Pandemic Guest experiences Hotel Online reviews

## 1 Introduction

Most, if not all, industries have been facing unprecedented challenges since the outbreak of the Novel Coronavirus (COVID-19), and tourism has been the hardest hit among all [11]. The United Nations World Tourism Organization [20] estimated a 98% drop in international tourist arrivals in May 2020. According to STR [19], China has experienced a slump in tourism demand and a 20.6% decline in domestic tourism revenue in year 2020. Besides, the overall hotel occupancy in China has decreased by 89% from early to mid-January and the overall revenue per available room witnessed a year-on-year drop of over 85%.

Crisis affects the macro-environment and brings about changes in customer behaviors and hotel performances [3, 18]. The outbreak of COVID-19 may have brought about changes in guest experiences at hotels [8, 25]. Customers normally describe their experiences and emotions after their hotel stay in the form of usergenerated content, such as online reviews [1]. Therefore, online reviews are frequently used by practitioners to understand the nature and structure of guest experiences, thereby devise useful reactive strategies [20].

Hotels are customer-centric that should keep up with customer preferences and requirements. Thus, it is essential to track the potential changes of guest experiences caused by the impact of COVID-19. In view of that, this study seeks to reveal the differences in guest experiences at luxury hotels before and during the pandemic as reflected in the online reviews posted in those two periods. A text analytic approach is used to transform unstructured data and identify factors in online reviews to compare the determinants of hotel guest experiences before and during the pandemic. The results of this study will offer practical suggestions to hotel managers to develop effective operational and marketing strategies to improve guest experiences at luxury hotels during the challenging situation. Future research opportunities are also provided.

## 2 Literature Review

#### 2.1 Hotel Guest Experience and Online Reviews

Guest experience refers to the cognitive and affective responses derived from the interactions between the guest and a product or service [10, 21]. It is co-produced by service providers and consumers [5]. Xiang, Schwartz, Gerdes Jr, and Uysal [22] identified 80 guest experience-related words, including room, quality, and service. Knutson, Beck, Kim, and Cha further identified the guest experience dimensions by developing a four-factor model of Hotel Experience Index (HEI) [14]. The 18-item index consists of four dimensions, namely environment, accessibility, driving benefit, and incentive [14]. According to Xiang et al. [22], guest experience is used to measure hotel guest satisfaction. Satisfaction with and repurchase of a hotel product may be driven by a set of attributes, such as staff service quality, room quality, amenities, value, and security [6].

With the popularity of sharing experiences through online platforms, online reviews represent a legitimate source for hotel managers to understand customers' evaluations of hotel service and products [15, 22]. Research on textual reviews in hospitality mainly focus on identifying the hotel attributes and sentiments expressed in the reviews [e.g., 7, 12] and examining the relationships between specific attributes in the textual reviews and the overall review ratings [15, 16]. Comparisons of hotel attributes and guest experiences are mainly done among different hotel guest segments [12] and hotel types [1]. Hong et al. [13] found out that guests placed more emphasis on natural and safe experience associated with the bed & breakfast (B&B) after COVID-19, and provided practical suggestions for the industry to survive the disaster, such as avoid using central air-conditioning and adopting semi-self-service technologies. The current study contributes to existing literature by identifying the changes in hotel guest experience and its determinants before and during a pandemic situation.

## 3 Methodology

#### 3.1 Data Collection

Online reviews were collected from the luxury hotels in Shanghai for two reasons. First, Shanghai is one of the top destinations in Mainland China, with 8.94 million tourist arrivals in 2018 [4]. The large number of visitors fueled the development of the hotel industry in the city [24]. Second, Shanghai has swiftly overcome its semilockdown amid the pandemic, unlike the other worst-hit cities, which was under fulllockdown for over one month, such as Wuhan. As a resilient tourism destination, Shanghai shows signs of recovery in March 2020 and has even become the most popular destination in Mainland China after going through the peak of the pandemic in May 2020 [17]. Thus, data before and during the pandemic are more readily available for luxury hotels in Shanghai, considering that travel activities are still present during the pandemic.

Online reviews for 20 luxury hotels in Shanghai that were posted from August 2019 to July 2020 were collected using Google Sheets in August 2020. These 20 hotels were randomly selected based on the list of luxury hotels in Shanghai that is available on Ctrip. Mainland China announced the lockdown measures to control the spread of COVID-19 around the country in late January 2020 [2]. Thus, online reviews posted from August 2019 to January 2020 are categorized into the pre-COVID-19 group (740 reviews), while those posted from February 2020 to July 2019 are in the amid-COVID-19 group (1238 reviews). There is a significant difference in the number of reviews between these two periods. A closer look into the distribution shows that a very small amount of reviews has been posted in September and October 2019 before the outbreak of the pandemic. However, a lot of reviews have been posted in June and July 2020 during the pandemic. This suggests that consumers have a higher motivation to share their experiences with and help the others amid-crisis.

#### 3.2 Data Analysis

The online reviews were analyzed using the Chinese Text Analyzer software, which helps to perform segmentation and frequency count of the words. The authors then reviewed and verified that all retained words are related to guest experiences with hotel, i.e., both the tangible and non-tangible aspects of hotel products [22]. In the first step, frequency analysis using the Chinese Text Analyzer generated a list of words describing hotel guest experiences. In the next step, the primary coder reviewed each word and combine synonyms together (e.g., "writing desk" and "table", "hygiene", and "cleanliness"), so as to reduce the number of words. At the same time, words that are irrelevant to hotel guest experiences were eliminated. This iterative coding process seeks to establish a dictionary of terms relevant to hotel guest experiences. The manual coding was done with reference to other similar research [1, 23].

## 4 Findings

#### 4.1 Comparison Between Pre- and Amid-Pandemic

A total of 3,558 and 5,034 words have been segmented from the pre-pandemic and amid-pandemic online reviews respectively. Table 1 shows the proportion of each identified determinants in hotel guest reviews both before and during the pandemic. The results show that the core determinants of hotel guest experience are the same in both periods, and they include services, room quality and settings, hotel facilities, dining, location, and environment. All these six factors have been mentioned more than 10% in the online reviews of the sampled luxury hotels in Shanghai.

The proportions for these factors are similar in the pre- and amid-pandemic periods, except for services. Hotel guests mentioned much more about services during the pandemic (21.8%) compared to the time before (17.3%). A closer look at the review content shows that the significant rise in the proportion of reviews describing the service dimension is mainly due to two items, including check-out time and takeaway services. A few reviews mentioned that the hotel actively offered late check-out during the pandemic. For example, "The hotel management is very nice, they extended the check-out time for us without extra charges. Superb!" On the other hand, some guests stated that the hotel does not help with delivering the takeaway that they have ordered. For example, one guest mentioned "Overall the hotel is nice, the facilities are smart, but they refused to help send the take-away up to the room. They should improve on this service."

As anticipated, the proportion of reviews mentioning about health measures increases from 0.8% before the outbreak of the pandemic to 3.2% during the pandemic. Words that most frequently appeared in the online reviews related to this dimension include guest traffic (59 times), pandemic prevention and control (46 times), and the impact of pandemic (24 times).

Table 1. Frequencies of hotel guest experience determinants before and during pandemic

(continued)

Table 1. (continued)

## 5 Conclusions

#### 5.1 Implications

The findings of this study reveal that most dimensions of guest experiences at luxury hotels, including room quality and settings, hotel facilities, location, environment, value/price, bathroom, amenities, and hotel design, show a minuscule decrease in frequencies, whereas the remaining determinants, conversely, show an increase. What is worth noticing is that "services" show an increase in proportions, indicating that hotel guests expect to receive additional services, such as delivery service of takeaway and late check-out services amid-pandemic. Besides, guests become more concerned about whether the hotel is taking preventive measures and control during the pandemic, such as controlling the number of guests at the hotel, measuring body temperature. This can be explained by the fact that people are more concerned about public health and personal safety during the pandemic. Social distancing prevents the virus from further spreading [9]. While it is important for hotels to maintain their standard quality of products and services as usual, hotel managers may provide more proactive or even extra services to guests during this critical period. As reflected in this study, offering late check-out and assisting with the delivery of takeaways may maintain customers' perceived service quality of the hotel. In order to reduce interactions between service employees and guests, robots may be used to take and delivery takeaways and room services to guestrooms. Furthermore, self-service kiosk and express check out services may be offered to reduce the waiting time of guests, thereby avoid gathering large crowds at the hotel lobby. Any measures taken by the hotel in preventing the pandemic should be carefully communicated with hotel guests on the hotel websites or during the booking stage, so as not to create any inconveniences during the service experience.

#### 5.2 Limitations and Future Research

The findings of this study are based on descriptive analysis of online reviews from 20 luxury hotels in Shanghai. The focus on luxury hotels and small samples size may limit the generalizability of the findings. Besides, ratings and sentiments in the online reviews have not been considered. Nevertheless, this study sheds lights on the potential differences in hotel guest experiences caused by the outbreak of the pandemic. Future studies may build on the idea of this study and expand the scope of the study to include all luxury hotels, or even all hotels across different categories in Shanghai and other cities of China. The dictionary developed in this study may be used for machine learning so that a larger amount of reviews may be analyzed. Analysis on the ratings and sentiments in the review text may be performed to reveal further insights into the differences in guests' sentiments before and during the pandemic.

## References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

### How COVID-19 Impacts Chinese Travelers' Mobility Decision-Making Processes: A Bayesian Network Model

Junyi Wang, Xueting Zhai, and Qiuju Luo(&)

Sun Yat-Sen University, Zhuhai 519082, People's Republic of China<EMAIL_ADDRESS><EMAIL_ADDRESS>
Abstract. The outbreak of the COVID-19 pandemic has a multi-faceted impact on the mobility of travelers. Current research has not yet explained the internal mechanisms of travelers' mobility changes during the pandemic. The Bayesian network is considered to be an effective method to describe the causality between the factors and output of a system. Thus, this paper established a Bayesian network model to analyze the impact of COVID-19 on Chinese travelers' mobility decision–making processes. The model for the traveler mobility decision-making process is built on both a qualitative and quantitative analysis of travelers' self-narration articles. Results show that official information, traffic information, family structure, and social interaction networks are the key factors affecting Chinese travelers' mobility.

Keywords: COVID-19 Traveler mobility Decision-Making process Bayesian network model

## 1 Introduction

The large scale of travelers' flow has been a major risk during the COVID-19 pandemic. Travelers' emotions and mobile behaviors have become more changeable and anomalous, even resulting in disorder flow or chaos due to fear and uncertainty. Some factors that impact travelers' mobility decision making during the COVID-19 pandemic include government policies (e.g. border closures), accessibility (e.g. flight cancellations), and social media information. In addition to such general factors, family and culture are influencers that are particularly found in Chinese travelers' mobility patterns. Since the COVID-19 outbreak in China happened during the Chinese Spring Festival—the most important traditional festival in China, when people are expected to return to their hometowns—Chinese travelers' mobility decisions are not only affected by their own needs but also their families, customs, and morals. Therefore, it is interesting and significant to explore the decision-making process concerning Chinese travelers' mobility during COVID-19.

Travelers' mobility and decision making have always been hot topics in tourism research [1, 2]. Current research has demonstrated that the traveler mobility decisionmaking process is complex, determined by a wide range of factors stemming from the economy, sociology, geography, and psychology [3]. Thus, it is still a challenge to predict how travelers' mobility behaviors and their underlying mechanisms will change. Undoubtfully, COVID-19 will impact travelers' mobility decisions, but how?

Certain studies have constructed spatiotemporal diffusion models to reveal the relationship between public flow and the spread of disease [4]. Some have discussed the impact of the epidemic on traveler mobility behavior, thus revealing particular abnormal mobility behaviors [5, 6]. However, most of the existing research has been based on epidemiological statistics, which may visualize the general flow while failing to explain the underlying mechanisms. Moreover, current research has not explained the behavior changes of heterogeneous travelers during the pandemic.

To fill the gaps, this study used the Bayesian network method to establish a causal model of Chinese travelers' mobility decision-making processes during the COVID-19 pandemic and identify key influential factors.

## 2 Method

### 2.1 Data Collection

We collected 60 non-fictional self-narration articles released on WeChat—one of the most popular social media platforms in China—from Jan. 28, 2020, to Jun. 4, 2020. In these sampled articles, the authors recalled and stated their mobility routines from Jan. 18, 2020, to Mar. 31, 2020. This exact time period covers the outbreak and spread of COVID-19 in China [7], including two important Chinese traditional festivals: the Spring Festival on Jan. 25, 2020 and the Lantern Festival on Feb. 8, 2020. This period is typically a peak of mobility for Chinese travelers because it is a traditional custom for Chinese people to return to their hometowns during the Spring Festival until the Lantern Festival. Thus, it is interesting to reveal how Chinese travelers negotiated information about the pandemic, travel risks, and cultural customs in their traveling decisions. These articles involved 63 individuals' mobile behaviors in total, including 24 men and 39 women. In accordance with their publication time, the self-narration articles were divided into two sample sets, with 30 articles each.

### 2.2 Bayesian Network Model

The Bayesian network is a directed acyclic graphical model that represents the probability dependence between variables [8]. Bayesian network modeling consists of the following steps: (1) Structure determination. We used NVivo 12 software to code the self-narration articles in Sample 1 to identify the elements and topics that affect travelers' mobile decisions. Then, cross-comparison was conducted by the three authors to discuss and recode the inconsistent codes. Finally, we identified the specific relationship between the elements and themes and constructed a directed acyclic network structure. (2) Parameter determination. We used GeNIe software to draw a Bayesian network model. Then, we employed experts to assign the initial conditional probability. (3) Parameter learning. We coded the elements in Sample 2 in accordance with the coding rules as Sample 1 to establish a quantitative data set. Then, based on the Bayesian network built in Step 2 and the quantitative data set, we used the EM algorithm method to adjust the model. (4) Sensitivity analysis. We used sensitivity analysis to evaluate the Bayesian network model and identify key influential factors.

### 3 Bayesian Network Modeling

#### 3.1 Structure Determination

Six main factors and 16 specific nodes were identified to construct a Bayesian network model of travelers' mobility changes (Table 1).

Table 1. Variables of traveler mobility changes

Information Sources. After the outbreak of COVID-19, complex and uncertain information directly and immediately affected travelers' mobile decisions, resulting in sudden route changes. For example, "…a friend sent me a road closure notice in Tianmen, Hubei. Out of intuition, I decided to pack my things immediately, set off after New Year's Eve dinner, and returned early."

Social Environment. Social environment is a relatively stable external influence in mobile decision making [9]. However, during the COVID-19 pandemic, the social environment deviated from the normal state, making it difficult to predict. The mobile behavior of travelers is influenced by—and sometimes contended with—the social environment and Chinese culture. For example, "According to the custom of my hometown, we must visit our relatives and friends on the first day of the first lunar month. My uncle did not think it necessary to be so careful (regarding COVID-19), while my mother stood firm on her principles and refused to let anyone visit her."

Personal Factors. Previous experience, family structure, social interaction networks and customs are the main personal factors that affect traveler mobility. Travelers' previous experiences not only affect their risk perception but also arouse their previous emotional experience, consequently strengthening self-protection and impacting mobility decisions. For example, "…those experiences (during SARS) are vivid. So, I… cancelled my wife's and children's train tickets and returned to Wuhan alone." Travelers also consider their family structure, customs, and relationships when making decisions. For example, "When the elderly pass away, it is an especially important and serious custom for relatives to worship on the first day of the new year. A sudden cancellation is too abrupt. I dare not make that decision."

Emotional Experience. Most sampled travelers experienced negative emotions during the COVID-19 pandemic with a high or medium level of emotional arousal. Panic and worry are the driving forces leading to sudden changes of travelers' mobility behavior. For example, "There are two old people and one young child in my hometown. What are their conditions? These worries have made me restless for several days. On January 22, I returned home from Shenzhen alone."

Decision Process. The decision-making process includes two factors that are key in ultimately determining if and how the mobility decision changes: decision orientation and risk perception. Travelers show different attitudes and preferences when they make decisions taking various aspects into consideration [10]. For example, "COVID-19 became serious at the time, and I felt that traveling to the UK might cause discomfort to the locals to some extent, so I asked for a refund for my ticket."

#### 3.2 Parameter Learning

Combining both expert assignments and quantitative data, we assigned the confidence of the original parameters to 30, equal to the sample size. Then we used the EM algorithm method to conduct parameter learning to accommodate the missing data. Genie2.0 was used for Bayesian network parameter learning. Finally, a Bayesian model was built to simulate travelers' mobility decision-making processes (Fig. 1).

Fig. 1. The Bayesian network model and sensitive analysis of travelers' decision making

#### 3.3 Sensitivity Analysis

Since the travelers' decision-making behaviors are affected by multiple factors, sensitivity analysis was used to explore the influence of each factor (set) and then figure out the most important ones. Figure 1 showed that information sources are the most important factor impacting changes in travelers' mobility behavior. Among them, official information has the highest sensitivity value, which means that travelers' mobility behavior is highly sensitive to the official information released. Social environment and personal factors also greatly impacted traveler mobility.

Further, we drew a sensitivity tornado of the increased and decreased states of mobility behavior and compared the sensitivity of each factor (Fig. 2). The top five factors (set) that may enhance the possibility of travelers to change their mobility include official information, departure place environment, family structure, traffic information, and social interaction network. While the official information from the destination may decrease the possibility of travelers increasing their mobility, official information from the departure place might enhance the possibility of travelers reducing their mobility.

Fig. 2. Sensitivity tornado of mobility behavior

## 4 Conclusions

This research constructed a Bayesian network model to simulate Chinese travelers' mobility decision-making processes during the COVID-19 pandemic. The Bayesian network is widely applied to explain highly complex phenomena and decision-making processes. Results show that official information, traffic information, family structure and social interaction networks are the key factors (set) affecting the mobility of travelers. In addition, information sources and social environment not only directly affect the changes of travelers' mobility, but they also have indirect effects through travelers' decision processes and emotions. As a result, Chinese travelers' mobility decision-making processes are not only influenced by information about the pandemic but also culture, customs, and morals.

Acknowledgments. This work was supported by the National Natural Science Foundation of China [grant number 41971176];

## References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

## Examining Post COVID-19 Tourist Concerns Using Sentiment Analysis and Topic Modeling

Sreejith Balasubramanian, Supriya Kaitheri, Krishnadas Nanath, Sony Sreejith, and Cody Morris Paris(&)

Middlesex University Dubai, Dubai, UAE {s.balasubramanian,s.kaitheri,k.nanath,s.sreejith<EMAIL_ADDRESS>
Abstract. The COVID-19 pandemic has had a destructive effect on the tourism sector, especially on tourists' fears and risk perceptions, and is likely to have a lasting impact on their intention to travel. Governments and businesses worldwide looking to revive and revamp their tourism sector, therefore, must first develop a critical understanding of tourist concerns starting from the dreaming/planning phase to booking, travel, stay, and experiencing. This formed the motivation of this study, which empirically examines the tourist sentiments and concerns across the tourism supply chain. Natural Language Processing (NLP) using sentiment analysis and Latent Dirichlet Allocation (LDA) approach was applied to analyze the semi-structured survey data collected from 72 respondents. Practitioners and policymakers could use the study findings to enable various support mechanisms for restoring tourist confidence and help them adjust to the'new normal.'

Keywords: Tourism supply chain Emotions Lexicon-based approach

## 1 Introduction

Travel and tourism are among the most affected sectors due to the worldwide outbreak of the COVID-19 pandemic. According to United Nations World Tourism Organization (UNWTO), the sector which witnessed an unprecedented decline of around 98% in international tourists in May 2020, compared to the same time last year, is likely to face a drop of up to 1.1 billion international tourists and US\$ 1.2 trillion in revenues in 2020, putting 100 to 120 million jobs at risk [1]. Many countries, especially those most reliant on travel and tourism revenue, are implementing a wide range of measures for the reopening of the tourism economy and stimulate the recovery of the sector [2]. However, considerable challenges remain ahead, starting with the unknown duration of the pandemic itself and the global economic recession.

While immediate measures such as lifting travel restrictions, adjusting or simplifying visas requirements, and cutting tourist taxes could support the sector in the short term, for the long-term recovery, it is critical to restore consumer confidence and rebuild demand. This is because, although the COVID-19 started as a physical health crisis, there is growing evidence that COVID-19 is having a profound detrimental effect on the mental health of the general population, including tourists, which needs to be addressed urgently [3, 4]. The impact of the pandemic on people's mental health, especially fear of falling ill and dying, fear of infecting others, anger, and anxiety are extremely concerning and may have a far more significant and lasting impact on the tourists' intention to travel. Hence, we must develop a critical understanding of tourist sentiments and concerns across the supply chain so that various support mechanisms can be put in place for restoring tourist confidence and rebuilding demand.

This formed the motivation of this study, which aims to examine tourists' sentiments and concerns across the tourism supply chain starting from the dreaming/ planning phase to booking, travel, stay, experiencing, and departure. The specific objectives are as follows:

In the next section, the research methodology adopted in this study is detailed. The findings are discussed in section three, with the final/concluding section covering the implications and suggestions for future research.

### 2 Research Methodology

The primary data was collected from participants belonging to different nationalities using qualitative, semi-structured surveys (an ideal tool for exploratory research) using Qualtrics. The survey link was sent to participants via email. The questions focused on capturing tourists' COVID-19 concerns during the phases of the tourist supply chain. The final data set for analysis included 72 responses from participants from nine countries, of which 64% was male, and 36% was female. In line with our research objectives, Natural Language Processing (NLP) using sentiment analysis and the LDA approach was applied for analyzing tourist concerns across the different phases of the tourism supply chain. Previous studies have shown that applying both sentimental analysis and LDA on the dataset provides rich and meaningful insights on public opinion [5]. Figure 1 explains the research methodology and its procedure.

Fig. 1. Research methodology

The survey data was first cleaned to remove stop words, meaningless characters such as HTML tags, punctuation, numbers, and emoticons. It is important to understand the tourist concerns and their associated emotions. Sentiment analysis can help us understand the polarity (negative or positive) or the extent of emotions (joy, anger, and others) in a language, and it was used to uncover the various hidden emotions (related to concerns) of tourists [6, 7]. A lexicon-based approach, which involves calculating the sentiment from the semantic orientation of words or phrases that occur in a text, was used for sentiment analysis [8]. Each response for the questions in the survey was considered as a document in the dataset, and then analysis was performed for each of those responses. The lexicon-based emotion analysis package "syuzhet"- which is available in R (Version 3.6.2), was used for identifying the emotions contained in each response. Although both positive (e.g., trust, joy) and negative emotions (e.g., anger, fear) could be computed, given the focus of this study was to explore the concerns expressed by the tourists, only negative emotions were considered. The count of specific emotions in a comment was used for the analysis.

The next objective was to uncover the distinct themes/reasons in the tourist concerns. Topic modeling encompasses different algorithms that process text data to identify dominant themes based on the similarity of co-occurrences of the words [7, 9]. This research uses the Latent Dirichlet allocation (LDA) algorithm for topic modeling because of its ability to control the number of words and topics so that an empirical model can be developed. One of the prime objectives of this exercise was to understand if there are a few dominant topics in the dataset corresponding to each of the travel phases. Microsoft Azure Machine Learning Studio software was used for the LDA analysis.

## 3 Results and Discussions

This section discusses the results of sentiment analysis and topic modeling.

#### 3.1 Tourist Emotions (Sentiment Analysis)

The five negative emotions, namely anticipation of uncertain/undesirable events, fear, sadness, anger, and disgust hidden in the tourist concerns related to different phases of the tourist supply chain was computed and ranked. The rank of emotions across each supply chain stage is given in Fig. 2.

Fig. 2. Results of sentiment analysis

As seen in the figure, the emotions related to anticipation of uncertain/undesirable events (ranked 1st in dreaming, booking, and stay phase) and fear (ranked 1st in traveling and experiencing stage) dominate the tourist concerns across the different stages of travel. The anticipation of uncertain/undesirable events was mostly attributed to the dynamic changes in the travel rules and regulations in different countries, such as changes in quarantine rules. In the words of one of the respondents, "Changes in quarantine restrictions to and from the destination is a concern." Similarly, in the words of another participant, "I would never book without being fully sure that I could travel. Will the country remain open? Will I be able to return home?" Emotion of fear was mostly related to the fear of getting infected/re-infected and infecting others. People are mainly worried about their safety and that of their loved ones. In the words of a participant, "Fear of catching infections at the airport as it is the main hub where you tend to be around people from different parts of the world." This is mostly in line with the findings of World Economic Forum [10].

#### 3.2 Key Tourist Concerns (Topic Modeling)

Table 1 presents the topic modeling results based on the bi-gram analysis under LDA.

Table 1. Topic modeling results.

Planning to travel while restrictions are still in place and relevance of technology (or lack thereof) such as smart COVID-19 applications such as contact tracing to detect nearby cases emerged as the two distinct concerns during the dreaming/planning phase. The latter further reiterates the significance of technological advances in improving tourist experiences. Cancellation and refund issues and availability of flights to destinations and hotels are the main concerns that worry people in the booking phase. For the travel and stay phase, the majority of the concerns are related to COVID protocols, hygiene, health & safety, availability of good accommodation, restaurants, COVID testing facility, PPE kit in flight, etc. For instance, one of the participants mentioned the following concern "How good is the hotel sanitation and cleanliness. How trained is the staff at the hotel to deal with COVID19 related issues?" The concerns in the experiencing phase are mainly related to the destination itself, such as the social distancing measures in place, the number of active cases in the destination, and the availability of decent healthcare facilities in case of any infection. In the words of one of the respondents, "Reaching the location, I would concern about the measures the country employs to prevent the spread of the virus and how strict the people in that country are aware of and comply with those measures." Some of these tourist concerns topics identified are similar to the ones specified in the recent COVID-19 tourism literature [11, 12].

## 4 Conclusion

The preliminary findings of this study provides insights into the tourists' post-COVID-19 travel concerns. Given the heightened uncertainty in the tourism sector due to the pandemic, the study provides valuable insights for practitioners and policymakers to gauge better and manage tourist confidence levels, perception of travel as a risk, and any changes in their preference and behavior. Moreover, the study is timely as countries are faced with challenges of containing the second or third wave of spread and, at the same time, manage the reopening of the tourism economy [2]. Primary research on tourist sentiment analysis and modeling the tourist concerns during COVID-19 could prove to be an important tool in both assessing and monitoring the recovery of the industry. However, given the early stages of the paper, there are limitations. The small sample size of the study limits the generalizability of the findings. Also, the concerns were understood only from tourist perspectives, and concerns of other stakeholders were not considered. Future studies could adopt a multi-stakeholder approach. Further, future research could attempt triangulating the primary findings using secondary data such as from travel websites and social media.

## References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

### Enhancing the Visitor Experience in the Time of COVID 19: The Use of AI Robotics in Pembrokeshire Coastal Pathway

Katarzyna Minor(&) , Emmet McLoughlin, and Vicky Richards

> Welsh Centre for Tourism Research, Cardiff Metropolitan University, Cardiff, Wales, UK<EMAIL_ADDRESS>
Abstract. AI and Robots represent a major innovation opportunity for the tourism sector, and their potential impact and application offer several new opportunities to enhance and develop the visitor experience. Nevertheless, there has been limited academic research on the use of robots, together with a limited number of destinations embracing this technology. Focusing on the Pembrokeshire Coastal Path, this research paper outlines how a multi methodological approach could be utilised to examine the use of AI and robotics in helping to enhance the visitor experience during the ongoing COVID-19 pandemic. The researchers anticipate that outcomes from such a study could not only provide theoretical contributions in the area of addressing concerns about accessibility in tourism and leisure settings, but also serve to inform both academia and the wider tourism industry to the benefits such technology can have towards enhancing the visitor experience within social distancing parameters.

Keywords: COVID-19 Visitor experience AI and robotics Accessibility Wales

## 1 Introduction

The tourism industry has found itself operating in most unprecedented times, where the challenges of yesterday are compounded by the outbreak of global pandemic. This means a lot of destinations, particularly the ones which rely on tourism as a substantial percent of the economic outputs, fight not only the relatively short to mid-term effects related to COVID-19 travel restrictions but also long-term problems of underfunding, seasonal trade variations, attractiveness and inclusivity.

Pre COVID-19, both the Welsh and UK Economies considered tourism as a foundation sector for growth, with the overall tourism value in Wales rising from £4.5bn to £6.3bn in 2017 [4]. Tourism's impact was never more evident in Pembrokeshire, an area of Wales (see Fig. 1) known for its historical legends, walking trails and international sporting events. Tourism in Pembrokeshire is highly seasonal and generates over 75% of its trade during the months from March to October [4]. Unfortunately, funding for tourism has 'flatlined' [4], with the tourism economy being brought to stop due to the COVID-19 pandemic in March 2020. This regrettably coincided with the beginning of the busy tourism season. Thus, the indirect impacts from Brexit funding cuts and over-night closure of all tourism during the pandemic has decimated the local industry which ultimately could take several years to recover, due to both travel restrictions and social distancing regulations [6, 21, 32].

Rebuilding the tourism trade in post pandemic world may be problematic for Pembrokeshire and Wales in general, as 16% of domestic visitors to Wales have identified themselves as having a long-term illness or disability, and further 28% of domestic visitors are also in the age bracket of 55 plus [31]. Wales as a destination is highly reliant on domestic tourism, this puts over a quarter of domestic tourists' arrivals in the 'at-risk category', therefore, less likely to go on holiday. This puts additional pressure on destinations to reopen and operate with an increased safety and social distancing as an underlying principle in order to enable all possible tourist groups a safe return and enjoyment of Welsh countryside.

One of the ways to enable the safe tourism interactions is introduction of AI and robotics to the day-to-day operations. Indeed many countries, such as the Netherlands and Singapore amongst others, have successfully utilised robots in hospitality and healthcare settings with the aim to reduce human to human contact, thus, helping to both mitigate the spread of the virus and as a means to getting back to 'normal' [33]. This conceptual research paper is aimed to bring together Universal Design principles, robotics and novel tourism visitor attractions together in one research study. Central to it is the use of purposely coded, humanoid robot tourist guides, which will be placed along Pembrokeshire Coastal path (see Fig. 1). It is anticipated that this study will contribute to the body of knowledge in the areas of the utilisation of Accessibility to All in robot design, empirical evidence of tourist – robot interactions and enhancement of visitor experience, as well as the effectiveness of robots to support social distancing requirements.

Fig. 1. Pembrokeshire Coastal Pathway (Source: National Trails, 2020)

## 2 Research Background

This anticipated study comes at a time when the tourism and leisure industry in Pembrokeshire is primarily made up from micro and small enterprises, with visitor economy contributing £585m annually [4]. Whilst the region's main strategy is to focus value in opposition to volume of tourists, there are growing calls from the Welsh Government "to be putting our energies into thinking innovatively for the future" [17]. Pembrokeshire as a destination, therefore, aims to maximise behaviour, wellbeing, health and the use of technology as strategic goals for 2020–2025. Thus, the use of latest technologies, such as AI and robots could tie in with the overall goal of enhancement of experience [4]. AI and Robots represent a major innovation opportunity for the tourism sector, and their potential impact and use may offer many new avenues to enhance and develop the visitor experience [2, 16, 26].

Pembrokeshire as a destination identified its main weakness as fragmented marketing, characterised by lack of joint 'Pembrokeshire narrative' and uncoordinated information provision. Pembrokeshire's fragmented tourism industry makes it difficult to coordinate those marketing efforts, especially considering lack of external funding. Particularly, under current economic climate the businesses are likely to concentrate on strategies of survival and safe operations, rather than long-term strategic destination management efforts. Yet, according to [22] AI has now entered the tourism and hospitality setting and is being consumed by both organisations and destinations in order to gain a competitive advantage, in what is a highly dynamic market. Indeed, [29, 30] theorise that the future of the sector is likely to be dominated by automated and robotic smart solutions, particularly robot use for information-giving functions has been reported as welcome [8, 29]. Therefore, utilisation of Robot tourist guides would enable the creation of sense of place by providing a robust, customised and coordinated tourist information fitting with the 'Pembrokeshire narrative' of a place of natural beauty and rich cultural heritage.

Both [7] and later [20] argue that tourist experiences are reflective and inherently personal, there is a need to provide opportunities to travellers to interact with the technology. This spans from the belief that travel often is considered a sense-making process whereby traveller's construct the touristic experience by learning, understanding, and feeling the places visited [11, 28]. In other words, lack of real time experience of robots in natural tourist setting is likely to affect the attitudes and perceptions of this technology. Indeed, [12] point out not a lot of travellers have had actual interactions with robots and the existing research to date does not typically use actual interactions between humans and robots for the basis of the studies; majority of research is either conceptual (e.g. [14]), engineering (e.g. [5]), experimental (e.g. [18]) or survey based (e.g. [9]). Yet, despite its increasing importance, there has been limited academic research on the use of robots in tourism, and even fewer empirical research focusing on travel interactions with robots. In fact, [10] note, in their literature review of 131 tourism-related papers, just over half of those focused on the adaptions of robots by companies, with less attention paid to human-robot interactions. Furthermore, restaurants, hotels, airports and bars dominated the sector focus of the reviewed studies, indicating relative lack of broader tourism application of robotics. This may be caused by only a few destinations embracing this technology, mostly concentrated in Asia and commercialisation of the technologies in places such as Hen na Hotel in Nagasaki or FlyZoo Hotel in Hangzhou. This in part may be explained by a greater acceptance of automation rooted in Eastern cultures when compared with Western cultures [3].

Last consideration should be given to the tourist base of the area. The focus here is two-fold- on actual and potential tourist base for the region. First, as identified over a quarter of tourists are identified as 'at risk' due to COVID- 19; as people must avoid physical interaction, [23] argue that service robots can be a useful tool to ensure a high level of physical social distancing. Therefore, the use of robotics could potentially mean human to human contact frequency could be reduced, while also ensuring the recommended social distancing is maintained. However, more research is required to help determine how AI and robotics can help contribute to enhancing the visitor experience in tourism setting, particularly now in the time of COVID-19.

Second, existing research conducted by Visit England in 2018 suggests that 430,000 British adults with disabilities did not take a domestic holiday as a result of accessibility issues [27]. Despite legal requirements set out in the UK through the Equality Act (2010), the industry is still working towards equal participation for disabled people. Thus, whilst the industry talks of the value of the 'purple pound' (disabled people); disabled citizens still encounter barriers to their participation in tourism experiences as amongst other areas of life. It is anticipated that this study will help in addressing many of the concerns about accessibility in tourism and leisure settings and bias issues related to technologies and AI. This is in line with [24] observations that technology and visitor information alike must be accessible to people with a wide range of disabilities, as well as Welsh Government policies aimed at accessibility to all. As [27] research argues that the industry is missing out on a potential £116.7 million as a result of inaccessible infrastructure, the accessible nature of the project creates an opportunity for the Pembrokeshire destination to tap into new tourist markets, thus providing a much-needed economic advantage.

## 3 Proposed Methodology

In order to examine the use of AI and robotics to help enhance the visitor experience during a time of COVID-19, this research paper suggests a multi method approach, thus having the benefit of combining different approaches and research methods [13, 19]. The researchers therefore assume a three -stage study: 1) development, 2) implementations, 3) evaluation, and envisages a use of 10–15 small humanoid robots, positioned along the Pembrokeshire coastal path.

Accessibility for all is embedded into the project as a whole- from conception to the execution, by ensuring the technology as well as the information are accessible to people with a wide range of disabilities. This will be achieved by consulting different stakeholder groups, to include disability groups, with regards to functionalities of the robots, formats of information and type of information which the robots should have to maximise the benefit and access to all.

In stage one of the studies the researchers suggest a series of focus groups with four distinct groups (visitors, tourism organisations, visitors identifying as having a disability and a mixed group consisting of all three) to determine how their visitor experiences could be enhanced. Since focus groups are 'particularly useful for exploratory research where rather little is known about the phenomenon of interest' [26:15] the aim here would be to stimulate some discussions with a use of a pilot robot. The findings will inform the development and design of the specific functionalities of the robots.

It is suggested that research on enhancing the visitor experience through the use of AI should use humanoid robots, in line with [34] and [15] study recommending humanlike behaviours to be programmed onto the robots for greater acceptance. Whilst [25] note that the physical form of the robot does not affect the trust towards them; [34] found that the 'gender' of the robot is likely to affect acceptance of it. Furthermore, since [35] highlight that, in line with Media Equation theory, people tend to interact with technology in a social way. Therefore, researchers would need to have a variety of robot-personas developed to account for all possible outcomes and maximise the potential of positive interactions.

Implementation stage would naturally involve the installation of robots in tourist hot spots, such as check-in desks, cafes, tourist information centres, and other places of tourist interest where access to secure WIFI can be obtained. It is envisioned that this is where the robots will supply, when promoted, specific information to visitors and walkers. A variety of suitable methods could be employed during this stage, from direct observations by the research team, pre- and post- encounter interviews (to gauge emotions [35]), and data observed through the robots (e.g. facial expressions/ movement, types of interactions, commands used, information requested, length of interactions, distance, ease of use [35]). Therefore, the researchers argue that such characteristics could contribute to creating a unique and safe visitor experience.

A significant aspect of such a project would be ongoing consultation and collaboration with relevant stakeholders. Such an approach would be invaluable to help grow the interaction with the local stakeholder base. Furthermore, the businesses where robots were to be located would need to be consulted with the regards to the perceived usefulness and drawbacks of having this technology on the premises.

The researchers acknowledge that such research carries substantial ethical implications which need to be addressed. For example, as visual data would need to be generated to analyse the interactions, the researchers note the need for a carefully considered consent process to be implemented. Furthermore, all interactions recorded without the necessary consent of the participants will have to be removed and all other recordings would need be stored securely in line with current GDPR guidelines. Since such technology would be operated remotely using existing WIFI infrastructure, there is a potential risk of hacking and security. Other potential limitations and ethical considerations acknowledged by the researcher would relate to robot capabilities and design. For example, the robots cannot detect and interpret human emotions, therefore, will not be able to deal with and react to anger or frustration, thus there will be a need for people to deal with enquires in these situations. Furthermore, such robots would not have the ability to prioritise if faced with multiple requests/interactions at the same time, as such this could lead to frustration and anger [1].

## 4 Concluding Remarks

Artificial Intelligence and technology have helped to revolutionise various industries around the world [22]. And such innovative inventions are needed now more than ever when it comes to enhancing the Visitor Experience in the time of COVID 19. Therefore, this research paper outlines a methodological proposal to analyse how the use of AI robotics along the Pembrokeshire Coastal Pathway could help contribute to greater levels of visitor satisfaction by providing a unique and novel experience. The main theoretical contributions of this proposed study include addressing the concerns about accessibility in tourism and leisure settings, where the researchers have prioritised addressing these issues in developing the robot technology, thus, making the methodology unique and original.

Furthermore, it is envisaged that findings of such a proposed study could also be used to inform both academia and industry with regards to the potential of the use of purposely designed, accessible, AI powered technologies to maximise visitor experience within social distancing setting. As such a project would be the first to examine the feasibility of incorporating AI technology to help contribute to greater levels of visitor satisfaction as a result of COVID 19, it should be noted that there is limited research to draw comparisons. Therefore, data generated could enable the improved future design of technology and maximise the benefits it can offer. Such baseline information will benefit and inform future long-term studies around what type of interactions are desirable by all visitors, what type of information is mostly requested. Particularly it will inform to what extent the use of technology minimises the staff's exposure when faced with frequently asked questions, thus, highlighting the potential of creating safe working environment for tourism-related businesses.

### References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.


**4. Effective geometries**

We now discuss the possibility of a gauge theory to be mapped into a gravity theory. We first discuss the map between gauge and coframe bundles and then we generalize the results for moduli bundles.


**5.2. Sensitivity to noise**

Experimental studies on the human AML show that it is sensitive to noise and humans are not as good as machines in selecting queries from an unlabeled dataset of artificial visual stimuli [21]. Thus, human AML performance declines with higher noise levels. Humans perform relatively well in at least some noise settings, suggesting that they took the experiment seriously [30].


**8. Conclusions**

Whether or not a sex biased milk production in dairy cows exists, this bias can vary, favoring one sex or the other and, sometimes, none. It seems to favor females in intensive production systems, while in other less intensive systems this was not observed.

The conflictual results obtained in different studies considering the cow may influence the sex of offspring suggest that the systems were cows are generally in good and competitive condition produce more milk for bull calves. They also seem to indicate that cows in a worse condition, or of a genetically diverging strain, apparently invest more milk in heifer calves. Up to now, conflicting reports have been presented to the scientific society, but differences among the models used make difficult to establish a clear relation between the gender of the offspring and the productivity of the cow. The different results observed are probably due to differences in the methodological approach, and the different influencer parameters used to calculate a lactation milk production, and in possible confounding factors that may not be completely identified. Also, other factors, such as different housing and feedings can have impact in calf-sex milk production bias in pathways still to be understood.

To further explore this theory, additional research is needed that includes other cattle populations and correlating the investment strategy with an animal welfare index. If the calf sex effect in milk production is present in a population, selection of bull mothers and progeny tested bulls may be biased due to the offspring sex, increasing the genetic progress towards more profitable cows, if this calf-gender bias is accounted for in breeding value estimation.


*Edited by Donald S. Silverberg*

This book provides an up- to- date summary of many advances in our understanding of anemia, including its causes and pathogenesis, methods of diagnosis, and the morbidity and mortality associated with it. Special attention is paid to the anemia of chronic disease. Nutritional causes of anemia, especially in developing countries, are discussed. Also presented are anemias related to pregnancy, the fetus and the newborn infant. Two common infections that cause anemia in developing countries, malaria and trypanosomiasis are discussed. The genetic diseases sickle cell disease and thalassemia are reviewed as are Paroxysmal Nocturnal Hemoglobinuria, Fanconi anemia and some anemias caused by toxins. Thus this book provides a wide coverage of anemia which should be useful to those involved in many fields of anemia from basic researchers to epidemiologists to clinical practitioners.

ISBN 978-953-51-0138-3

Anemia

Photo by solvod / iStock


**1. Introduction**

Cervical cancer was formerly the second most common cancer killer of women worldwide. Following widespread adoption of Papanicolau cytologic screening (Pap test) for cervical cancer in the 1950s, this began to change. Today, advanced cervical cancer is rare in screened populations.  In global terms, this ranks second only to breast cancer as a cause of cancer-specific mortality. Over the past three decades the scientific community has witnessed spectacular advances in the understanding of the underlying pathophysiology of cervical cancer, with the most profound discovery being in 1983 of the identification of the human papillomavirus (HPV) within cervical cancer (a discovery that earned Harold Zur-Hausen, M.D the Nobel prize for Medicine and Physiology in 2008). A viral etiology for cervical cancer implied that it may be possible to eradicate cervical cancer through vaccination. This promise was partially fulfilled in 2006 when the United States Food and Drug Administration approved an HPV vaccine for the prevention of HPV-induced cervical dysplasia and/or cancer.  Furthermore, due to the pervasiveness of HPV infection and the timeline of disease progression, it will be a few decades before we will be able to determine the impact preventive practices are having on cancer incidence and prevalence. In addition, those for whom preventative measures are not a solution, including HIV+ individuals as well as women already infected with HR-HPV, await an answer.

Over the past several years, developments in innovative imaging, superior surgical technolo‐ gies, immunotherapies, and molecular therapies have surfaced, making the eradication of

© 2013 Evans et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

cervical cancer a much more achievable goal than in the past. Several areas of cervical cancer research continue to address the challenges posed by the need for appropriate therapeutic alternatives, and progress is occurring at each level of clinical management ranging from detection to the development of small molecule antiviral leads. Because the field is evolving rapidly in all directions and related disciplines, it is helpful to summarize the status of our growth, and to recognize those pioneering efforts that may ultimately contribute to achieving our goal of eliminating cervical cancer. This review seeks to survey the current understanding of cervical cancer etiology and treatment and to review areas requiring additional progress.

UNESCO (United Nations Educational, Scientific, and Cultural Organization) has demon‐ strated the effectiveness of sex education in the global fight against HIV/AIDs. Although HPV does not currently compare to HIV/AIDs in terms of mortality and global magnitude, the need for HPV awareness has grown tremendously and it is speculated that such a plan may prove useful here as well. An increase in consciousness may decrease sexual risk behaviors if populations at high-risk for contracting HPV were actively targeted for education [16, 17]. However, it should be considered that gender inequalities experienced by women in locations like Sub-Saharan Africa, as reported by the Global Health Corps and UNESCO, may negatively impact these initiatives. Furthermore, the cost of such programs compared to other interven‐ tional methods has not been determined. But in general, education can be used as a powerful tool in preventing HPV-mediated diseases such as cervical cancer. Ideally, these programs would emphasize risk-perception in both men and women leading to lifestyle modifications, and a further reduction in the incidence of HPV-mediated carcinoma might be realized.

Modern Molecular and Clinical Approaches to Eradicate HPV-Mediated Cervical Cancer

http://dx.doi.org/10.5772/55810

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*Prophylactic Immune Strategies:* Presently, the most effective protective factor against the most prevalent and high-risk types of HPV infection is prophylactic vaccination [18]. It has been seven years since the introduction of the first HPV vaccine [19]. Since then, two vaccines, Gardasil and Cervarix, have been made available to the public to protect against the more common HPV strains [20]. The vaccines induce the production of neutralizing antibodies against HPV L1 capsid virus-like proteins (VLPs), which do not contain virus genetic material. The quadrivalent vaccine, Gardasil, protects against low- and high-risk HPV (LR- and HR-HPV, respectively) types 6, 11, 16, and 18 following full vaccination of all three doses at 0, 1, 2 and 6 months. Alternatively, the bivalent vaccine, Cervarix, prevents infection by HR-HPV types 16 and 18. Both vaccines have been documented to possess compelling prophy‐ lactic efficacy in preventing cervical, genital, and anal diseases. This protection is expected to persist for 7 years, or at least during the years of high infection risk for most individuals

HPV infections of types other than the four mentioned above are not reliably prevented by vaccination. Also, studies are warranted regarding the vaccine's long-term effects and how they might impact the occurrence of infections by other HPV types. It has already been noted that quadrivalent and bivalent vaccines may exhibit cross-protection against HPV 31 and other types by 75 to 80 percent [23]. However, concerns are emerging that relate to HPV typereplacement. Type-replacement is an increased prevalence of other HPV strains that are not included in the vaccines, while vaccine-type HPV prevalence is decreased. It was recently reported that vaccine-type HPV has been reduced in vaccinated and nonvaccinated women, while nonvaccine-type HPV has slightly increased overall [24]. Researchers do not expect typereplacement to occur frequently. However, studies are becoming more attentive to changes in the prevalence of various HPV types, which are expected to surface first within the sexually experienced population. Such discoveries could encourage the research community to continue seeking multivalent solutions to as many HPV types as possible without eliciting additional harmful results. To date, clinical trials have revealed that the most common adverse response to both vaccines are injection site reactions, which occur more frequently in vaccine

groups rather than in participants given placebos [25].

[20-22].


Data Pre-Processing

The accuracy of the NRT ZTDs, derived from the AUTh GNSS network, was examined by comparing the data against high-quality reference ZTD data provided by EPN. Based on the availability of the EPN weekly combined ZTD solutions, the validation was performed over the AUT1 station (Figure 1b) using concurrent data of the 2018 dataset. Following previous studies [60–62], the accuracy of the ZTD observations was defined as the standard deviation of the difference between the AUT1 and EPN ZTDs. The analysis resulted in an accuracy of 7.6 mm, which is between the optimal (5 mm) and

target (10 mm) accuracy value according to the E-GVAP standards for NRT ZTDs used in the NWP models [63]. This outcome was a strong indication that the accuracy of the AUTh GNSS ZTD data was sufficient to assimilate them into the WRF modeling system.

Further, the observations in the 3D-var system are considered to have unbiased errors with respect to the WRF model. To meet this assumption, a statistical bias correction was applied to the ZTD data for each studied precipitation episode. More specifically, the differences between the observed and modeled ZTDs were computed for each GNSS receiver during a 10 day period prior to each event using the WRF simulations conducted for the model background errors covariance matrix specification (see Section 2.2.1). Then, the corrections were estimated as the mean values of the ZTD differences and they were subtracted from the ZTD observations that were lined up for data assimilation. Even though this method provides statistical corrections, this is a standard bias correction approach for ZTD data that proved to be successful in reducing the observations-model divergences and capturing the systematic errors between the ZTD observations and model forecasts [16,18–25,28]. The last stage of the ZTD data pre-processing included a selection algorithm based on the following conditions: (a) The formal ZTD error to be lower than the standard deviation of the difference between the observed and modeled ZTD, (b) the ZTD difference between observations and model output to be lower than five times the ZTD formal error, and (c) the difference between the receiver height and the model's orography to be below 100 m. Similar criteria have been applied in previous studies [19–25]. Based on data availability and the above selection algorithm, the number of GNSS reference stations used per event ranged from 48 to 56. The assimilated ZTD observations had the same range, since assimilation was performed once (at 0000 UTC or 0600 UTC) during the conducted experiments. The locations of the 55 stations used for the event of 27 November 2019 are shown in Figure 1b, demonstrating a sufficient and homogeneous spatial coverage of the Greek territory.


*Article* **Capturing Neuroplastic Changes after iTBS in Patients with Post-Stroke Aphasia: A Pilot fMRI Study**

**Shuo Xu 1,† , Qing Yang 1,† , Mengye Chen 1 , Panmo Deng 2 , Ren Zhuang 3 , Zengchun Sun 4 , Chong Li 5 , Zhijie Yan 6 , Yongli Zhang 7 and Jie Jia 1, \***

**Abstract:** Intermittent theta-burst stimulation (iTBS) is a high-efficiency transcranial magnetic stimulation (TMS) paradigm that has been applied to post-stroke aphasia (PSA). However, its efficacy mechanisms have not been clarified. This study aimed to explore the immediate effects of iTBS of the primary motor cortex (M1) of the affected hemisphere, on the functional activities and connectivity of the brains of PSA patients. A total of 16 patients with aphasia after stroke received iTBS with 800 pulses for 300 s. All patients underwent motor, language, and cognitive assessments and resting-state functional MRI scans immediately before and after the iTBS intervention. Regional, seed-based connectivity, and graph-based measures were used to test the immediate functional effects of the iTBS intervention, including the fractional amplitude of low-frequency fluctuation (fALFF), degree centrality (DC), and functional connectivity (FC) of the left M1 area throughout the whole brain. The results showed that after one session of iTBS intervention, the fALFF, DC, and FC values changed significantly in the patients' brains. Specifically, the DC values were significantly higher in the right middle frontal gyrus and parts of the left parietal lobe (*p* < 0.05), while fALFF values were significantly lower in the right medial frontal lobe and parts of the left intracalcarine cortex (*p* < 0.05), and the strength of the functional connectivity between the left M1 area and the left superior frontal gyrus was reduced (*p* < 0.05). Our findings provided preliminary evidences that the iTBS on the ipsilesional M1 could induce neural activity and functional connectivity changes in the motor, language, and other brain regions in patients with PSA, which may promote neuroplasticity and functional recovery.

**Keywords:** stroke; aphasia; iTBS; fMRI; neuroplasticity; rehabilitation


2.5.1. Elevated Plus Maze Test

The EPM apparatus is a plus-shaped platform 50 cm above the ground. The maze consists of four arms (50 cm × 10 cm each): two opposing open arms and two closed arms enclosed by a 10 cm high wall. The test is based on two conflicting motivations of rodents: to avoid open, brightly lit spaces and to explore novel environment. The avoidance of open arms reflects anxiety-like behavior [51]. 30 min after icv. treatment the rats were placed in the maze facing one of the open arms, then their behavior was recorded by a camera suspended above the maze for 5 min. The time spent in each arm, as well as the number of entries per arm were registered by an observer blind to the experimental groups. The percentage of entries into the open arms and the percentage of time spent in the open arms were also calculated. The experiments were conducted between 8 a.m. and 10 a.m. and the apparatus was cleaned with 96% ethyl-alcohol after each session.


**Abstract**

Rice is an important staple food crop across the world. It is mainly cultivated under irrigated lowland and also rain-fed upland conditions where drought stress is often noticed. Global climate change predicts an intensification of drought stress in future due to uneven rainfall which was witnessed for the last few years. Confronting drought stress can deliver fruitful crop returns in rice and scope for research extents. Drought stress affects the overall plant growth and yield. A prominent improvement has been made during last two decades in our understanding of the mechanisms involved in adaptation and tolerance to drought stress in rice. In order to achieve the marked crop returns from rainfed areas, there is a requisite of drought tolerant rice varieties, and genetic improvement for drought tolerance should be a prime area of concern in the future. A huge rice germplasm is available and good number of the germplasm possess drought tolerance and these genomic regions have been exploited in developing some drought tolerant rice varieties. The application of available genotyping methodologies, the identification of traits of interest, and key genetic regions associated with the drought tolerance have opened new prospects to successfully develop new drought tolerant varieties. This chapter deals with the importance of drought tolerance in rice crop followed by the evolution of molecular markers and breeding techniques in identifying drought tolerant QTL's/ genes and their utilization in the improvement of drought tolerant rice varieties.

**Keywords:** Rice, Drought tolerance, Markers, QTLs, Varieties

## **1. Introduction**

Rice is a staple cereal consumed by more than half of the world's population. It is cultivated in wide agro-ecological conditions including rain-fed conditions where drought stress is often evident due to erratic rainfall. Rice crop consumes around 3000 L water to produce 1 Kg rice. Drought stress is one of the major factors that leads to decreased rice production [1] and it can expand to above 50% of the global arable land by 2050 [2] due to loss of ground water, global climate change leading to decreased water sheds. Drought stress was noted in approximately 42 Mha of riceproducing area [3]. It is of two types, terminal and intermittent [4].

Drought stress is usually a dry condition where the water availability is less than a threshold level which causes damage to plants [5].

Lack of water for a long time leading to the death of plants is terminal drought while lack of water for a short time that leads to improper growth is intermittent drought [6].

Drought stress tolerance varies among the plant species and is defined as the ability of a plant to grow, develop and produce significant yield as well as economic benefit [7]. It is also defined as the ability of plant to survive at minimum water level in the fresh tissue (23%) [6].

Drought stress leads to morphological, physiological and biochemical changes in plants which ultimately lead to decreased yields. In response, plants synthesize reactive oxygen species (ROS), proteins and osmolytes to maintain turgor pressure. This osmotic adaptation provides dehydration tolerance to tissues [8–10]. But, this did not show yield benefit in rice [11].

The first landmark achievement in drought rice tolerance study was the identification of a small region on chromosome 8 homologous to chromosome 7 of wheat [12]. A marker based selection was proposed and this region was worked out to identify QTL's for vegetative leaf rolling and root traits- thickness and root to shoot ratio [13].

Historically, upland-adapted germplasm was of Japonica type while lowlandadapted germplasm was of Indica type [14]. In general, Japonica genotypes were dehydration avoidant while Indica types were dehydration tolerant. Geographically separated evolution and sterility problems have limited hybridization between the two types [15]. If breeding for both osmotic adjustment and rooting capacity is considered desirable, then the linkage between high osmotic adjustment and poor root traits needs to be broken.

RG1 QTL was identified while working with 52 recombinant inbred (RI) lines (F 7), a randomly sampled subset of a population originally developed to study the genetics of resistance to rice blast (*Pyricularia oryzae*) [16].

## **2. First generation markers**

#### **2.1 Restriction fragment length polymorphism (RFLP)**

Rice RFLP maps developed at Cornell University [17, 18] and Japan [19, 20] is the basis of gene mapping research. In the 1988 wet season at IRRI, Co39 (maternal), a lowland, Indica cultivar developed in India, and Moroberekan, a traditional upland, Japonica cultivar originally developed in Guinea. Moroberekan is considered to be resistant to drought while Co39 is drought susceptible. About 50 F1 seeds were obtained from the cross and only 15 F1 seeds were randomly chosen and grown in a greenhouse to obtain an F2 population. About 300 F2 seeds were randomly selected and planted in the Rapid Generation Advance (RGA) [21] greenhouse from F2 to F6 using single seed descent (SSD). All panicles were bagged at each generation and F7 seeds were used for genotype analysis [16].

DNA was extracted from the leaves of the two parents and digested with restriction enzymes DraI, EcoRI, EcoRV, HindIII and Scal. The digested DNAs were electrophoresed on 0.9% agarose gels and transferred to Hybond N+ membranes (Amersham Corp., Chicago) according to the manufacturer's instructions. 280 DNA clones distributed throughout the 12 chromosomes of rice (184 rice genomic clones, coded RG; 62 rice cDNAs, coded Rz; and 28 oat cDNAs, coded CDO) were linearized and labeled with 32PdCTP by the random hexamer method [22]. Hybridized filters were washed once in 1.5 X SSPE and once in 0.5 X SSPE at 65° for 15–20 min. Filters were exposed to X-ray film −80° at with one intensifying screen for 1–4 days. 127 informative probes were used for segregation analysis of the RI lines using the procedures outlined above. Mapmaker [23] and Map Manager [24] were used to establish the RFLP map.

Since the *indica* × *japonica* crosses suffer from sterility, distorted segregation, etc., [16], breeders chose to work on the accessions of *indica or japonica* sub-species, RFLP was considered laborious over RAPD which gained popularity among researchers [25].