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This paper aims to propose a data mining approach to evaluate a conceptual model in tourism, encompassing a large data set characterized by dimensions grounded on existing literature.

The approach is tested using a guest satisfaction model encompassing nine dimensions. A large data set of 84 k online reviews and 31 features was collected from TripAdvisor. The review score granted was considered a proxy of guest satisfaction and was defined as the target feature to model. A sequence of data understanding and preparation tasks led to a tuned set of 60k reviews and 29 input features which were used for training the data mining model. Finally, the data-based sensitivity analysis was adopted to understand which dimensions most influence guest satisfaction.

Previous user’s experience with the online platform, individual preferences, and hotel prestige were the most relevant dimensions concerning guests’ satisfaction. On the opposite, homogeneous characteristics among the Las Vegas hotels such as the hotel size were found of little relevance to satisfaction.

This study intends to set a baseline for an easier adoption of data mining to evaluate conceptual models through a scalable approach, helping to bridge between theory and practice, especially relevant when dealing with Big Data sources such as the social media. Thus, the steps undertaken during the study are detailed to facilitate replication to other models.

Virtual reality (VR) and augmented reality (AR) are two technological breakthroughs that stimulate reality perception. Both have been applied in tourism contexts to improve tourists’ experience. This paper aims to frame both AR and VR developments during the past 15 years from a scientific perspective.

This study adopts a text mining and topic modelling approach to analyse a total of 1,049 articles for VR and 406 for AR. The papers were selected from Scopus, with the title, abstract and keywords being extracted for the analysis. Formulated research hypotheses based on relevant publications are then evaluated to assess the current state of the broader scope of the large sets of literature.

Most of research using AR is based on mobile technology. Yet, wearable devices still show few publications, a gap that is expected to close in the near future. There is a lack of research adopting Big Data/machine learning approaches based on secondary data.

As both AR and VR technologies are becoming more mature, more applications to tourism emerge. Scholars need to keep pace and fill in the research gaps on both domains to move research forward.

论旅游业中AR和VR的近期发展

摘要

研究目的 – VR和AR是两种提高人们现实感知的科技突破。二者均被运用到旅游场景中提高游客体验。本论文旨在建立一个模型来描述过去15年内AR和VR的发展轨迹。

本论文采用文本挖掘和主题建模方法来分析1049篇有关VR和406篇有关AR的文章。样本库采样于Scopus, 通过题目、摘要、和关键词来检索。根据检索结果, 本论文提出研究假设, 并且审视延展更大范围的相关文献。

本论文发现大多数AR文章都是以移动技术为本。然而, 可穿戴设备始终有很少的文章。因此, 文献缺口预计在不久的将来会得以补上。研究还发现, 基于二手数据而运用大数据/机器学习方法的文章少之又少。

随着AR和VR技术越来越成熟, 旅游业更多的运用案例随之出现。学者需要紧随脚步, 填补AR和VR的文献缺口, 推进研究进程。

关键词：虚拟现实、增强现实、文献分析、旅游业

The purpose of this paper is to offer an insight into the fundamental changes taking place in Port wine production value chains. Specifically, the authors examine two distinct production regimes: when Port is aged and sold in the Greater Oporto and, alternatively, when it is produced, aged and sold in Douro.

The authors apply a tri-regional input–output model (Douro, Greater Oporto and rest of the country) for Portugal’s economy. This framework comprises a significant level of detail, with 431 products and 136 industries, the corresponding supply and demand for the products, by industry (for intermediate consumption) and final demand.

This study shows that the two regimes generate noteworthy, but quite heterogeneous, regional impacts. In both cases, the distribution of value added generates international and interregional trade flows. Moreover, the study reveals a greater capacity to capture national value added by getting the supply chain more intensive in localised services and by using state-of-the-art production techniques.

Using detailed regional data, the authors use disaggregated information, both for industries as well for territories, overcoming a common limitation in similar works that are grounded in international databases. Additionally, the approach integrates the trade interactions among industries and regions, which proves essential to uncovering spillovers resulting from the (direct and indirect) use of inputs from other regions and other countries.

While scales were developed to measure individual adaptive performance (IAP), fewer contributions have been done to assess the construct at the team level of analysis. This issue is addressed through two related studies: Study 1 builds on Pulakos et al. (2000) to develop a measure of IAP. Study 2 follows from the results in Study 1 and tests a measure of team adaptive performance (Chan, 1998).

Scale development was done adopting a single level (Study 1) and multi-level (Study 2) structural equations modeling approach.

Results suggest that both measures of individual and team adaptive performance are reliable and show evidence supporting the adequacy of adopting referent-shift methodologies to the measurement and aggregation of team members’ rating of team adaptive performance.

The study offers a reliable, parsimonious and easy to apply measure of individual and team adaptive performance in organizational work environments.

The purpose of this paper is to develop a new method for detection and classification of power quality disturbances such as transients, waveform distortions, sags, swells and interruptions.

For the purposes of the proposed method, the power quality disturbances are divided into two groups. Different algorithms are applied to detect and classify the disturbances from each of the two groups. For the processing of transients and waveform distortions, digital high‐pass filter and the mathematical morphology closing are used. Calculation of the RMS value is used for detection of sags, swells and interruptions.

The proposed method was implemented in a PC‐based measuring setup. The measuring setup was used in a seven‐months‐long monitoring of a single‐phase power system. In the course of the monitoring, the proposed method was verified on over 19,000 transients, 3,500 waveform distortions, 77 sags and 18 interruptions.

The classification stage of the proposed method does not differentiate between individual types of waveform distortions (harmonics, interharmonics, noise…).

The described approach is simpler and more reliable than, for example, methods based solely on wavelet transform. The proposed method is suitable for real‐time monitoring of power systems.

The paper describes a new and efficient way of detection and classification of disturbances (especially of transients and waveform distortions). It shows that mathematical morphology operations, which are normally used in image processing, represent a useful tool also in the field of power quality measurements.

The 2008 global financial crisis showed that the ability to innovate is a key management skill and that approaches to assessing the innovation capability of small- and medium-sized enterprises (SMEs) need to be as realistic as possible. This study aims to address the latter practical need through a sociotechnical approach.

Based on a combined use of cognitive mapping and the Decision EXpert (DEX) technique, and grounded on the insights generated by a panel of SME managers and entrepreneurs in two intensive group meetings, a knowledge-based assessment system for evaluating SMEs’ innovation capability was created, tested and validated.

The knowledge-based assessment system identified the most innovative SMEs in a sample of companies. The “plus-minus-1” and dominance analyses carried out provided further support for the results.

The proposed system is extremely versatile but process-oriented and idiosyncratic in nature, meaning that extrapolations to other contexts need to be done with due caution.

The panel of SME decision makers agreed that the system improves the current methods used to evaluate SMEs’ innovation capability, contributing to a more informed perspective on management issues. The panel members also noted that the proposed system functions as a learning mechanism, facilitating the development of well-focused suggestions for improvements SMEs can make.

The integrated use of cognitive maps and rule-base decisions contributes to a better understanding of how to assess SMEs’ innovation capability. No prior work reporting the integrated use of these two techniques in this study context has been found.

There is an increasing interest in visiting protected areas in the Algarve (Portugal). Tourists are interested in contact with nature activities. However, protected areas are quite sensitive to human pressure and are limited in their carrying capacity. The purpose of this study is to fill a literature gap concerning which features attract tourists who visit saltpans via a pedestrian tour and what sort of pressure they inflict on waterbirds’ behaviour.

The tour consists of a predefined path with interpretive boards and guides who provide explanations to visitors. This study is threefold: to find out if waterbirds are disturbed by the presence of tourists, if tourists prefer to learn more about saltpans instead of finding waterbirds and if tourists have any preferred waterbird species. The methods used are direct observations with binoculars of the saltpan area and a short questionnaire. With the data collected, three hypotheses are tested.

The results show that the occurrence of waterbirds does not vary according to the presence or absence of tourist visits, tourists prefer visiting saltpans rather than watching waterbirds and there is some waterbird species preference.

Few people can visit the saltpan while keeping disturbance of both waterbirds and workers to a minimum. This study gives insights into sustainable ecotourism practices and how to articulate them with saltpan works.

The value of this study can be demonstrated by the interconnection between traditional salt production, waterbirds’ habitat, visitors’ interest and their interaction.

The aim of this paper is to analyze relationships of cooperation and conflict between a mining company and the involved communities, focusing on the presence of the mining company (MSX) in Cerro de San Pedro, Mexico.

The paper focuses on the co‐operation and conflict between firms, communities, new social movements and the role of government.

The presence of the mining company has caused a severe social conflict among the inhabitants of San Pedro, Soledad y San Luis, alerting all who are concerned with historic heritage, cultural and environmental issues. At the center of the controversy is the cheap and efficient technology. Federal and state laws were violated. It is quite evident that there was a lack of sensitivity of foreign mining companies toward the consequences of their activities upon the communities and environment. This case also shows the lack of negotiation between firms, communities, new social movements and governments. Information about externalities and future costs of company activities is crucial but more crucial is formulation and implementation of more sensitive policies to avoid damage to the environment, biodiversity and health of the population. Governmental institutions must be aware that their decisions may affect the quality of life of present and future generations for the sake of a small increment in economic growth and large increase in private benefits of a small group of investors. More informed citizens tend to be more active protestors, such as the case of the students in San Luis. Contact between informed individuals of diverse groups and organizations helps to exchange experiences and create public opinion in favor of mobilization. Community participation and involvement in decision‐making of community development planning is quite limited by the lack of critical information. This fact is critical when the local government cannot provide the right information because there are other interests affecting the process.

The paper highlights the lack of sensitivity of foreign mining companies towards local communities.

This research aims to understand the learning with regard to didactic knowledge of an early childhood teacher who participated in a Lesson Study (LS) on the topic of patterns, as well as her perspective about LS as a teacher education process.

This is a qualitative case study of an early childhood teacher who participated in a LS alongside three other colleagues and a facilitator. Data collection was made by participant observation with elaboration of a research journal, audio recording of sessions and a collective interview. Data analysis was made by content analysis based on the conceptual framework.

This case study shows that early childhood teachers may become aware of the importance of working with their children mathematical ideas. It also shows that they may develop their didactic knowledge in several dimensions such as school mathematics, curriculum, children and their learning, and teaching practice and that they may appreciate LS as a means of professional development.

This study shows the potential of LS for the professional development of early childhood teachers, a scarcely researched area. It also shows that their learning may include dimensions related to specific curricular areas such as mathematics.