Visitor Trends Research Articles

How SEO and Analytics are Connected

Search Engine Optimisation (SEO) is essential for online presence and success in the digital world. Because SEO is dynamic, making informed decisions requires a data-driven strategy, which makes analytics an essential component. This study explores the deep relationship between analytics and SEO, highlighting the critical function analytics plays in developing, executing, and evaluating effective SEO efforts. This paper, breaks down important elements including keyword research, website traffic analysis, and content optimisation. It shows how analytics may help us understand target audience behaviour, website performance, and the effectiveness of SEO techniques. The first section of the paper outlines the foundations of SEO and emphasizes that improving organic search ranks is its main goal. It highlights how SEO algorithms are constantly changing and how maintaining online presence requires constant adaptability. The study then discusses analytics as a way to measure the effectiveness of SEO efforts. Thoughtful choice of keywords that appeal to a target audience is essential to SEO success. This study emphasizes how important analytics are for identifying search volume, trends, and competitive keyword analysis. Analytics enables data-driven keyword selections that optimize a website's chances of attracting relevant traffic. There is also a thorough examination of analytics' capacity to monitor website visitor trends. Extensive indicators like bounce rates, visitor demographics, and traffic sources offer valuable insights into how well SEO campaigns are working. This data makes it possible to spot possible problems, highlight effective strategies, and direct strategic adjustments. Understanding website user behaviour is a key component of search engine optimisation. Analytical tools like page views, time on site, and navigation pathways are essential for identifying patterns in user behaviour. When it comes to improving internal linking and content organization to increase user engagement and conversions, these insights are priceless. Content must closely match search intent to optimize SEO potential. This study explores the ways analytics can uncover search terms that direct users to a website. Optimizing content for these targeted search terms reinforces SEO efforts and allows them to more accurately meet customer requirements.

Application of Data Mining for Visit Prediction at Amikom Creative Economy Park

A creative economy park is a place designed with strategic goals for technology skills collaboration, information and knowledge transfer, creation of innovative high-tech enterprises and entrepreneurs, introduction of new technology industries in creative economy enterprises to promote economic development. Yogyakarta Amikom University has been declared a Creative Economy Park and is known as Amikom Creative Economy Park (ACEP). ACEP includes multiple multimedia environments for targeting businesses such as software development, film, television, games, radio, animation, advertising, investment consulting, and project design. Every year, the number of institutions visiting Amikom Yogyakarta University carries the slogan Amikom Creative Economy Park with a fairly busy program of visits. The agenda for accepting this visit was carried out by Amikom's Public Relations Department (DKUI, Directorate of Public Relations and International Affairs). The evolution of visitor numbers from year to year, forecasts must be made to support the planning and preparation process when receiving visits. This research will discuss the trend of visitors having a comparative study in Amikom Creative Economy Park in the future. The data used in this study is visitor data from January 2019 to December 2019. This predictive data analysis uses the Autoregressive Integrated Moving Average (ARIMA) method and Exponential Smoothing as a comparison for the accuracy of the prediction. With the forecast of this visit, the planning and preparation for the Directorate of Public Relations and International Affairs and for the University AMIKOM Yogyakarta is to be done.

Short-term prediction of parking availability in an open parking lot

Abstract The parking of cars is a globally recognized problem, especially at locations where there is a high demand for empty parking spaces. Drivers tend to cruise additional distances while searching for empty parking spaces during peak hours leading to problems, such as pollution, congestion, and driver frustration. Providing short-term predictions of parking availability would facilitate the driver in making informed decisions and planning their arrival to be able to choose parking locations with higher availability. Therefore, the aim of this study is to provide short-term predictions of available parking spaces with a low volume of data. The open parking lot provides parking spaces free of charge and one such parking lot, located beside a shopping center, was selected for this study. Parking availability data for 21 days were collected where 19 days were used for training, while multiple periods of the remaining 2 days were used to test and evaluate the prediction methods. The test dataset consists of data from a weekday and a weekend. Based on the reviewed literature, three prediction methods suitable for short-term prediction were selected, namely, long short-term memory (LSTM), seasonal autoregressive integrated moving average with exogenous variables (SARIMAX), and the Ensemble-based method. The LSTM method is a deep learning-based method, while SARIMAX is a regression-based method, and the Ensemble method is based on decision trees and random forest to provide predictions. The performance of the three prediction methods with a low volume of data and the use of visitor trends data as an exogenous variable was evaluated. Based on the test prediction results, the LSTM and Ensemble-based methods provided better short-term predictions at multiple times on a weekday, while the Ensemble-based method provided better predictions over the weekend. However, the use of visitor trend data did not facilitate improving the predictions of SARIMAX and the Ensemble-based method, while it improved the LSTM prediction for the weekend.

Discovering the ‘heart’ in heartland tourism

ABSTRACT The emergence of the Singapore heartland as a tourist environment is explored. The ‘heartland’ refers to suburban residential neighbourhoods, often sited away from mainstream attractions and iconic landmarks, and seldom visited by mass tourists. The increasing trend of visitors to the heartlands and companies offering heartland tours is studied. Applying the concepts of ‘frontstage’ (featuring mainstream attractions) and ‘backstage’ (offering alternative sites), the production and consumption of heartland spaces are interrogated. The notion of ‘tourism place making’ is also introduced as we look at how tour companies attempt to ‘make places’ in the heartlands that appeal to visitors, and how tourists in turn ‘place make’ as they experience the landscapes. We argue, however, that there are limits to place making. Just as tour companies are incapable of transforming spaces into affective landscapes of tourism, likewise travellers encounter cultural shocks and other difficulties that mitigate against their place attachment. Further research on tourism place making in non-mainstream sites is required if we are to fully appreciate the complex relations between tourism, people and places.

Dynamic Partitioning Strategies for Multi-Robot Patrolling Systems

In this paper, the mission for mobile patrolling robots is to detect as many incoming visitors as possible by monitoring the environment. For multi-robot mobile patrolling systems, task assignment in the common environment is one of the problems. For this problem, we use a territorial approach and partition the environment into territories. Thus, each robot is allowed to patrol a separate territory regardless of the others. In this regard, however, the workload balancing of the patrolling tasks in the territories is a challenge. For this challenge, we propose dynamic partitioning strategies focusing on visitor trends. The system transfers a part of the territory with the maximum workload to others so as to equalize the workloads. As a result, while the sizes of the territories without visitor trends increase, others with the trends decrease. Therefore, the territorial approach enables robots to intensively monitor areas in accordance with the number of the visitors. This is the main contribution of this paper. Simulation experiments show that the patrolling robots successfully detect visitors through workload balancing.

Dark Tourism: A Preliminary Study of Barpak and Langtang as Seismic Memorial Sites of Nepal

Dark tourism is about more than a simple fascination with death, it is also a powerful lens that allows contemporary life and death to be witnessed and relationships with broader societies and culture recognized (Stone, 2013; Allman, 2017). Information about disasters and their effects to the human being draws attention to the people whoever interested to death and disaster and play very important role to attract and motivate the visitors to those places. So far, disaster tourism is also popular as dark tourism because historical and cultural identity is devasted and violent death of a large number of people occurs in the seismic memorial sites. Individuals who are participating in disaster tour are very much curious to see the impact of disaster. This article focuses on Dark Tourism: A Preliminary Study of Barpak and Langtang as Seismic Memorial Site of Nepal. Barpak was the epicentre of earthquake 2015 which caused huge suffering in the western and middle part of Nepal. Langtang is also the place which was doubly devastated. The earthquake struck, landslides and avalanches that destroyed the settlements. Through three data sources: document review, interview and direct observation, this article assesses theoretical understanding of the dark tourism, the society and culture of the seismic memorial sites, the motivation of the visitors, changing trend of visitors in Barpak and Langtang over pre, during and post-Earthquake 2015 and prospects and challenges of dark tourism in Barpak and Langtang. The study finds that the motivation and benefit to visit Barpak and Langtang are; black spot, history & heritage, cultural values, heritage & identity, survivors’ guilt, death and dying, disaster and identity, acts of memory, people’s resiliency, empathy, remembrance, education, entertainment and edutainment which are very much important in promoting dark tourism in Barpak and Langtang.

Generation Y and protected areas: A scoping study of research, theory, and future directions

Over the past two decades, there has been anecdotal reporting of declines in young people’s engagement with natural environments. This article focuses on Generation Y, also commonly referred to as the Millennials. Through a scoping study of published research to 2017, we explore how Generation Y experiences, views, and is influenced by natural areas of high conservation value. A key finding is that the body of empirical and theoretical research that has examined Generation Y’s engagement with national parks and protected areas is very small. Four distinct topic areas emerged: “generational differences,” “outdoor recreation and well-being,” “environmental responsibility,” and “visitor trends.” Findings suggest that Generation Y may differ from other generations, including how they value well-being and their perceptions of environmental responsibility. The article explores the implications for how protected area agencies promote, create, and manage experiences.

Lessons in Managing Visitors Experience: The Case of Future Music Festival Asia (FMFA) 2014 in Malaysia

Abstract From religious celebrations to massive music festival, Malaysia is always known as a very festive country. Being one of the fastest growing sectors in tourism industry, music festival is celebrated lively everywhere in this region. However, not much research has been done to identify factors that visitors view as important for a good festival experience. This study analyzes visitor trends and motivational factors in attending the Future Music Festival Asia (FMFA 2014) as well as visitors’ insights on facilities and services especially on safety concerns on the event that was held in Kuala Lumpur, Malaysia in 2014. A questionnaire survey was used as the primary method of data collection and was distributed throughout the two days during the festival. The findings highlighted the visitors’ priority in selecting facilities and services and learn more about better arrangements on facilities and services that have the most impact toward future attendees. It would also enable festival organizers to better understand the impact of events landscape for Malaysia's tourism industry.

Trend and Variability of Visitor in Bangladesh

This study was investigated with the time series data to know the trend of foreign visitors in Bangladesh. To estimate the trend of visitors, data was used for the year 1976–2008. The several growth models were used and found that semi-log trend model was more suitable for foreign visitors. It is also found that the number of foreign tourists visiting Bangladesh has registered a significantly upward trend with a growth rate of 5.79 percent per annum. The monthly arrivals data reveal pronounced seasonality. The best arrival month is January with seasonal index of 122.99 percent which implies that seasonally arrivals are increased by 22.99 percent in that month. September is the slower or worse month with seasonal index 81.81 percent which implies that seasonally arrivals are decreased by 18.19 percent in the month.

Human visitation rates to the Apostle Islands National Lakeshore and the introduction of the non-native species Lymantria dispar (L.)

The introduction of non-native species has accelerated due to increasing levels of global trade and travel, threatening the composition and function of ecosystems. Upon arrival and successful establishment, biological invaders begin to spread and often do so with considerable assistance from humans. Recreational areas can be especially prone to the problem of accidental non-native species transport given the number of visitors that arrive from geographically diverse areas. In this paper, we examine camping permit data to the Apostle Islands National Lakeshore in northwestern Wisconsin, USA, from 1999 to 2007 relative to gypsy moth distribution, phenology and outbreak data. During this time, gypsy moth populations became established in this area ahead of the moving population front of the gypsy moth, suggesting anthropogenic introduction. The permit data revealed that the majority of visitors arrived from outside of the gypsy moth established area. However, there was a consistent yearly trend of visitors that arrived from areas of high gypsy moth populations and who arrived during the gypsy moth life stage (egg masses) most likely to be successfully introduced. Using available data on the gypsy moth and its relationship to camping permit data, we describe how recreational managers could optimize park strategies to mitigate unwanted introductions of the gypsy moth as well as develop analogous strategies for managing other biological invaders in recreational areas.

Icons under threat: Why monitoring visitors and their ecological impacts in protected areas matters

Summary Visitation levels are on the rise in protected areas throughout the world. In response, many icon sites are showing signs of overuse and more protected‐area managers report tourism and recreation as threats to sustainable management. Clearly, there is a growing need to assess (monitor) and manage visitors to mitigate their impacts. In this paper, we articulate why targeted visitor‐impact monitoring matters and highlight how existing monitoring programmes fail to deliver the necessary information to protected‐area managers. We suggest that the availability and quality of visitor data are currently insufficient to facilitate the development of proactive management strategies in most protected areas. We call for more scale‐sensitive (time and space) collection of visitor load and environmental (response) data. Specifically, since icon sites (like waterfalls and mountain peaks) are the focus of visitor motivations and activities, we highlight the case for proactive assessment, management and reporting of condition at these sites. Ultimately, visitor trends will be influenced by visitor management. If visitor activities degrade the icon, the financial benefits of tourism and recreation to a protected area may not be sustainable. In addition, the conservation and protection objectives of the protected area will also not be met.

Business Intelligence from Web Usage Mining

The rapid e-commerce growth has made both business community and customers face a new situation. Due to intense competition on the one hand and the customer's option to choose from several alternatives, the business community has realized the necessity of intelligent marketing strategies and relationship management. Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, creating adaptive Web sites, business and support services, personalization, network traffic flow analysis and so on. This paper presents the important concepts of Web usage mining and its various practical applications. Further a novel approach called "intelligent-miner" (i-Miner) is presented. i-Miner could optimize the concurrent architecture of a fuzzy clustering algorithm (to discover web data clusters) and a fuzzy inference system to analyze the Web site visitor trends. A hybrid evolutionary fuzzy clustering algorithm is proposed to optimally segregate similar user interests. The clustered data is then used to analyze the trends using a Takagi-Sugeno fuzzy inference system learned using a combination of evolutionary algorithm and neural network learning. Proposed approach is compared with self-organizing maps (to discover patterns) and several function approximation techniques like neural networks, linear genetic programming and Takagi–Sugeno fuzzy inference system (to analyze the clusters). The results are graphically illustrated and the practical significance is discussed in detail. Empirical results clearly show that the proposed Web usage-mining framework is efficient.

The built heritage in England: Properties open to the public, visitors and visitor trends

The built heritage in England: Properties open to the public, visitors and visitor trends

North American visitor trends to the UK — Is it time for a review of the product?

Tourists from the USA have been an important feature of the UK tourism business for many years. However, the number for 1994 are less than that of a decade earlier, with a peak figure, prior to 1995, occurring back in 1985. Certain special factors affecting US tourism to the UK are well known, such as the Libyan crisis or the Gulf War, but the trend over the last decade is very flat especially when viewed in relation to other generating countries. After an overview of the development of US tourism to the UK the paper argues that this trend may be a combination of features. Demographic trends ill the USA and newer competing destinations mean that the UK and even Europe is no longer an automatic prime choice for the US tourist. Furthermore the lack of innovation by the UK tourist industry may be compounding the problem. Many US visitors perceive the UK as a historic and heritage destination — traditionally a strength of the UK product. However, even here it is possible the UK is not making the best of its assets and tailoring the product to the growing demands of the repeat visitor market. Examples of destinations largely ignored by the mainstream market are highlighted following research into the historical roots of one of the original 13 states of the USA.