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This paper aims to contribute significantly to the empirical investigations on adopting Industry 4.0–circular economy in the Malaysian palm oil industry. The paper also aims to theorise and empirically assess a comprehensive model incorporating three aspects and 51 criteria.

A two-stage methodology is proposed using the fuzzy Delphi method and the fuzzy-based analytical network process. Twenty-seven criteria on adoptability of industry 4.0–circular economy were selected for the first-stage methodology, followed by identifying each criteria's intersection with the overall objectives.

The findings indicate that financial constraints, the lack of a collaborative I4.0–CE model, laws and policy, low management support and the training of dedicated employers in I4.0–CE-application are the top five criteria requiring critical attention from the POI.

The overall sustainability advantages of the POI are identified and discussed in depth to establish criteria for industry 4.0–circular economy applications.

This study fills the previous research gap by theoretically explaining POI's industry 4.0 adoption–circular economy from the perspective of two underpinning theories. Due to the pressure towards sustainability, the industry must be ready to adopt industry 4.0–circular economy applications, and resources must be managed appropriately and effectively by sharing and integrating. Advanced industry 4.0 technologies and pragmatic practices such as a circular economy are needed to achieve optimal sustainable development while retaining commercial success.

This paper aims to explore the role of perceived organizational injustice (POI) leading to workplace conflict in determining organizational performance (OP) among healthcare employees. This paper also examines the serial mediating effects of moral disengagement (MD) and knowledge hiding (KH).

In all, 244 public and private hospital employees in Pakistan provided the data set.

According to partial least squares-structural equation modeling findings, the negative association between POI and OP was serially mediated by KH and MD. The recovery process underlying the linkage between POI and OP is tested and highlighted in this paper as a first step in unraveling it.

The findings highlight the significance of taking moral and KH models into account when attempting to understand the moral cognitive processes that employees go through when they see injustice. Organizations should guarantee the equitable distribution of incentives and resources, as distributive and procedural justices are concerned with organizations.

By directing actions meant to prevent MD and KH, the findings may potentially inspire new, more focused treatments to safeguard patient safety and avoid losses in the healthcare industry. One way to reduce unethical conduct and MD is to have people declare or agree to a code of ethics.

The purpose of this study is to identify the knowledge gap and future opportunities for developing mobile recommender system in tourism sector that lead to comfortable, targeted and attractive tourism. A recommender system improves the traditional classification algorithms and has incorporated many advanced machine learning algorithms.

Design of this application followed a smart, hybrid and context-aware recommender system, which includes various recommender systems. With the recommender system's help, useful management for time and budget is obtained for tourists, since they usually have financial and time constraints for selecting the point of interests (POIs) and so more purposeful trip planned with decreased traffic and air pollution.

The finding of this research showed that the inclusion of additional information about the item, user, circumstances, objects or conditions and the environment could significantly impact recommendation quality and information and communications technology has become one part of the tourism value chain.

The application consists of (1) registration: with/without social media accounts, (2) user information: country, gender, age and his/her specific interests, (3) context data: available time, alert, price, spend time, weather, location, transportation.

The study’s social implications include connecting the app and registration through social media to a more social relationship, with its textual reviews, or user review as user-generated content for increasing accuracy.

The originality of this research work lies on introducing a new content- and knowledge-based algorithm for POI recommendations. An “Alert” context emphasizing on safety, supplies and essential infrastructure is considered as a novel context for this application.

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.

To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.

In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.

This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.

In this study, to investigate tourist mobility (i.e. hotel visits) during the COVID-19 pandemic, the authors developed three objectives with reference to protection motivation theory: (1) to examine changes in travel distances in the USA before and during the pandemic, (2) to identify distinct travel patterns across different regions during the pandemic; and (3) to explore threat- and coping-related factors influencing tourist mobility.

The authors used two primary sources of data. First, smartphone data from SafeGraph provided hotel-specific variables (e.g. location and visitor counts) and travel distances for 63,610 hotels in the USA. Second, state-level data representing various factors associated with travel distance were obtained from COVID-19 Data Hub and the US Census Bureau. The authors analyzed changes in travel distances over time at the state and regional levels and investigated clinical, policy and demographic factors associated with such changes.

The findings reveal actual travel movements and intraregional variances across different stages of the pandemic, as well as the roles of health-related policies and other externalities in shaping travel patterns amid public health risks.

To the best of the authors’ knowledge, this study is the first to empirically examine changes in travel distances to hotels as destinations using smartphone data along with state-level data on COVID-19 and demographics. The findings suggest that tourism enterprises and stakeholders can proactively adapt their strategies by considering threat appraisals and coping mechanisms, both of which are influenced by externalities such as health-related policies.

在我们的研究中, 为了调查COVID-19大流行期间的旅游出行（例如：酒店访问）, 我们根据保护动机理论制定了三个目标：（1）研究在COVID-19大流行前后美国的旅行距离的变化, （2）在大流行期间识别不同地区的不同旅行模式; 以及（3）探讨影响旅游出行的威胁和应对因素。

我们利用了两个主要数据源。首先, 来自SafeGraph的智能手机数据提供了63,610家美国酒店的酒店特定变量（例如位置和访客计数）以及旅行距离数据。其次, 代表与旅行距离相关的各种因素的州级数据来自COVID-19数据中心和美国人口普查局。我们分析了州级和地区级的旅行距离随时间的变化, 并调查了与这些变化相关的临床、政策和人口因素。

我们的研究结果揭示了不同阶段的实际旅行动态和地区内的差异, 以及在公共卫生风险中塑造旅行模式的健康相关政策和其他外部因素的作用。

我们的研究是第一个利用智能手机数据以及与COVID-19和人口统计数据相关的州级数据, 经验性地研究了旅行距离到酒店作为目的地的变化。我们的研究结果表明, 旅游企业和利益相关者可以通过考虑威胁评估和应对机制来主动调整他们的策略, 这两者都受到健康相关政策等外部因素的影响。

The purpose of this study is to provide the location of natural disasters that are poured into maps by extracting Twitter data. The Twitter text is extracted by using named entity recognition (NER) with six classes hierarchy location in Indonesia. Moreover, the tweet then is classified into eight classes of natural disasters using the support vector machine (SVM). Overall, the system is able to classify tweet and mapping the position of the content tweet.

This research builds a model to map the geolocation of tweet data using NER. This research uses six classes of NER which is based on region Indonesia. This data is then classified into eight classes of natural disasters using the SVM.

Experiment results demonstrate that the proposed NER with six special classes based on the regional level in Indonesia is able to map the location of the disaster based on data Twitter. The results also show good performance in geocoding such as match rate, match score and match type. Moreover, with SVM, this study can also classify tweet into eight classes of types of natural disasters specifically for the Indonesian region, which originate from the tweets collected.

This study implements in Indonesia region.

(a)NER with six classes is used to create a location classification model with StanfordNER and ArcGIS tools. The use of six location classes is based on the Indonesia regional which has the large area. Hence, it has many levels in its regional location, such as province, district/city, sub-district, village, road and place names. (b) SVM is used to classify natural disasters. Classification of types of natural disasters is divided into eight: floods, earthquakes, landslides, tsunamis, hurricanes, forest fires, droughts and volcanic eruptions.

The purpose of this research is to increase academic understanding of the relationship between systems' political identity and their viability, and to contribute to anarchist-cybernetics by examining the idea of organization proposed by Malatesta using Viable Systems. The research also develops the understanding of the relationship between Viable Systems and the environment.

The author developed a content analysis method that uses dynamic analysis, identifying how some variables affect others, and data is analysed using the Viable Systems Model. The author used Dynamic Causal Diagrams and the Viable System Model to draw conclusions and build theory. The author examined 137 documents produced by Errico Malatesta, studying in detail 39 documents containing the researched concepts.

The article identifies the literature, proposes an organizational theory for society and for cooperatives, strongly grounded in both, self-management and control. It presents a theory of self-management as a balancing effort to the control exercised by the external economic, political and societal forces of the environment. The literature also shows a form of organization that can be interpreted using the VSM framework. The ideas about self-management found in the literature, extend to economics, social theory, ethics, organizations, management and even operations management. The article finishes proposing a set of committees linked to the VSM structure, and successfully bridges anarchism and organizational cybernetics.

The article presents a novel method of systems analysis for the study of literature. It discovers the theory proposed by Malatesta not identified previously. Using the VSM framework, the ideas presented by the author, are translated into the organizational identity, and the operation of cooperatives. It makes an important contribution to anarchist-cybernetics.

The paper aims to present a literary itinerary inspired in Julio Dinis’ novel An English Family (Uma Família Inglesa) through a comparative analysis of the places identified in the novel and the touristic attraction proposed by Visit Porto website. This novel is representative of the cultural identity and society of Porto city in the 19th century. Developing an itinerary based on this novel can facilitate the reading and understanding of the historical and cultural development of Porto.

This case study is based on the reading of the Julio Dinis’ novel An English Family (Uma Família Inglesa), whose storyline takes place in Porto city, Portugal in the 19th century. It used QGIS v. 3.12 software, a geographical information system to identify the places, to produce the maps and to create the itinerary.

The comparison between the places identified in the novel and the tourist attraction in Visit Porto website revealed that only 6 points in the novel are referenced on Visit Porto website. These points correspond to the ones in the historical city centre of Porto. However, the creation of an itinerary that brings together all the points mentioned by Julio Dinis in his novel, will allow the development of a new touristic itinerary, alternative to existing itineraries in the city and that can be seen as a distinguish offer that allows a different view of the urban space of Porto.

There are some limitations to this study that can be highlighted. First, it was difficult to find the correct location of some points identified in the novel, due to difficulty of finding historical maps with quality of the data. At the same time, as tourist information is dispersed by several sources, and most of those data is not georeferenced, it was time consuming the integration of all the information in the same geodatabase. The choice of the shortest path can also be considered as a limitation, rather than the route followed by the author in the novel, but geographic information systems operates on spatial and temporal scale, which can present a limitation in tourism analysis. In the case of this project, we have chosen the shortest path, assuming that tourist would prefer that.

This research allowed to address two areas of knowledge that are emerging in the study of urban centres as tourist areas: the use of GIS and literary tourism. Despite the fact that there are already articles on this subject, the originality focuses on the approach made around one of the greatest writers of Portugal in the 19th century, allowing to present a tourist itinerary about one of his literary works, and the comparison made between the places identified in the novel and the tourist points identified on the Visit Porto website.

Free guided walking tours are one of the most successful tourism segments in the digital platform economy. It is beginning to be associated with negative impacts in some of the destinations where it is spreading rapidly. Although the platform economy is generating increasing academic interest, the free tour model remains largely unexplored area in the literature. This study aims to examine how such activity affects cultural destinations.

Focussing on the largest Free Tours platform operating in Spain, GuruWalk, the methodology used analyses its impact in six cultural destinations on two of the sustainability dimensions: the territorial dimension and the governance, through an exploratory study.

The findings help to understand the differences that such activity generates in each destination depending on the phase of its life cycle, and to implement, if necessary, corrective measures. The research confirms that the impacts differ according to the tourist destination’s maturity, concluding that such activity contributes to the increase of tourist agglomerations and the overcrowding of cultural destinations in their middle and mature life cycles. The findings highlighted the importance of the role of local governance on free tour activity.

The main contribution is the association of the impacts they produce (especially in terms of massification) with destination life cycle phases. There were no similar precedents with a spatial or territorial analysis to reliably demonstrate not only that this activity has an impact on the territory but also what type of impact is produced.