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In 2008, a phenomenon emerged in online retail that attracted the attention of many people, creating a new virtual model of commerce. This phenomenon was called online group buying and arrived in Brazil in 2010. The purpose of this study was to identify the factors that affect satisfaction and loyalty to group buying sites.

Through structural equation modeling, the relationships between the attractiveness of discount rates, service quality, popularity, online brand image, antecedent word of mouth (WOM), creativity and trust in relation to consumer general satisfaction, declared loyalty, repurchase intention and positive WOM were observed. A total of 727 valid questionnaires were collected from online group buyers to test the 11 hypotheses proposed in this study.

The main contribution of this study was that it identified the strong influence of service quality, popularity and online brand image on consumer general satisfaction, and the influence of service quality, trust and general satisfaction on repurchase intention. It also identified the influence of trust, creativity and general satisfaction on declared loyalty, and finally, the influence of trust and general satisfaction on positive WOM.

Because of the extensive and robust model, other statistical interactions among the constructs were gauged. It is possible that new structures and paths for alternative models can be proposed in the future with the inclusion of new relationships not analyzed in the present study. Furthermore, future studies should consider testing the generated model in other countries, as the particular features of collective purchasing in Brazil should be taken into account.

In addition to being concerned with the attractiveness of discounts, marketing managers of group buying sites should concentrate their efforts on strengthening perceived quality, image, trust and the creativity of the site to ensure customer loyalty.

The online group buying business model that was established in Brazil differs significantly from the American and European models. As many online group buying studies have been conducted in these markets, Brazilian consumers will enjoy substantial gains in the quality of the service provided by collective purchasing sites through the development of actions that focus on improving the factors that affect these consumers.

The originality of this study lies in the development of a single model that tests a set of factors gauged separately in other studies related to online purchase behavior in a broader perspective.

Background: The annual average daily traffic (AADT) data from road segments are critical for roadway projects, especially with the decision-making processes about operations, travel demand, safety-performance evaluation, and maintenance. Regular updates help to determine traffic patterns for decision-making. Unfortunately, the luxury of having permanent recorders on all road segments, especially low-volume roads, is virtually impossible. Consequently, insufficient AADT information is acquired for planning and new developments. A growing number of statistical, mathematical, and machine-learning algorithms have helped estimate AADT data values accurately, to some extent, at both sampled and unsampled locations on low-volume roadways. In some cases, roads with no representative AADT data are resolved with information from roadways with similar traffic patterns.

Methods: This study adopted an integrative approach with a combined systematic literature review (SLR) and meta-analysis (MA) to identify and to evaluate the performance, the sources of error, and possible advantages and disadvantages of the techniques utilized most for estimating AADT data. As a result, an SLR of various peer-reviewed articles and reports was completed to answer four research questions.

Results: The study showed that the most frequent techniques utilized to estimate AADT data on low-volume roadways were regression, artificial neural-network techniques, travel-demand models, the traditional factor approach, and spatial interpolation techniques. These AADT data-estimating methods' performance was subjected to meta-analysis. Three studies were completed: R squared, root means square error, and mean absolute percentage error. The meta-analysis results indicated a mixed summary effect: 1. all studies were equal; 2. all studies were not comparable. However, the integrated qualitative and quantitative approach indicated that spatial-interpolation (Kriging) methods outperformed the others.

Conclusions: Spatial-interpolation methods may be selected over others to generate accurate AADT data by practitioners at all levels for decision making. Besides, the resulting cross-validation statistics give statistics like the other methods' performance measures.

The purpose of this paper is to investigate tourists’ representations of the Arctic through the lens of the photo-sharing social network Instagram. The study focuses on the particular tourist experience of crossing the Arctic Circle in Rovaniemi, Finland, as in tourism, it represents the “official” entry to the Arctic. The study also aims at drawing assumptions about the future experiences of crossing the Arctic Circle, with the development of new technologies such as augmented and virtual realities.

Data were gathered with netnography methodologies on the Instagram social network. The first stage was the observational part and consisted of “lurking” at specific hashtags and locations, both referring to the Arctic Circle in Rovaniemi. Data were gathered in December 2018 and consisted of images and descriptions of Instagram posts published by users between June 1, 2018 and December 31, 2018, so data collection encompassed both summer and winter seasons. The second stage was the analysis part and involved interpretive understanding, and especially phenomenological sociology.

Results show that three dominant representations of the Arctic emerge when tourists cross the Arctic Circle. The region is either seen as a frozen fairytale wonderland due to the close proximity of the Christmas industry, as a far and northern destination participating in the realization of the self, and as a territory where summer weather conditions are not necessarily synonymous with the Arctic. In addition, the study acknowledges the future challenges of conceptualizing “Arctic tourism” due to the development of virtual reality technologies that could provide immersive Arctic experiences outside the region.

The paper investigates connections between social media studies and tourist experiences in the Arctic context. It also questions the future of Arctic tourist experiences with the development of new technologies enhancing experiences and, thus, potentially threatening the exceptionalism of the Arctic and what makes the region a unique tourism destination.

The purpose of this paper is to understand the factors that enable and inhibit WhatsApp users' discontinuance intention (DI) following the change in WhatsApp's privacy policy.

Using the enabler-inhibitor model as a framework, a research model consisting of discontinuation enabler distrust (DT) and the DT's antecedents [(negative electronic word of mouth (NEWOM), negative offline word of mouth (NOWOM) and privacy invasion (PI)], discontinuation inhibitor inertia (INR) and INR's antecedents (affective commitment, switching cost and use habit) and moderator structural assurance was proposed and tested with data from 624 WhatsApp users using partial least square structure equational modeling (PLS-SEM).

The results show that DT created due to NEWOM and a sense of PI significantly impact DI. However, INR has no significant impact on DI. Structural assurance significantly moderates the relationship between DT and DI.

The paper collected data when many WhatsApp users switched to other platforms due to the change in WhatsApp's terms of service. The timing of data collection allowed for collecting the real impact of the sense of PI compared to other studies where the effect is hypothetically induced. Further, the authors acknowledge social media providers' efforts to address privacy criticism and regain users’ trust, an area that has received little attention in prior literature.

This work aims to explore why people review their experienced online shopping in such a manner (promptness), and what is the potential relationship between the users’ review promptness and review motivation as well as reviewed contents.

To evaluate the customers’ responses regarding their shopping experiences, in this paper, the “purchase-review” promptness is studied to explore the temporal characteristics of users’ reviewing behavior online. Then, an aspect mining method was introduced for assessment of review text. Finally, a theoretical model is proposed to analyze how the customers’ reviews were formed.

First, the length of time elapsed between purchase and review was found to follow a power-law distribution, which characterizes an important number of human behaviors. Within online review behaviors, this meant that a high frequency population of reviewers tended to publish relatively quick reviews online. This showed that the customers’ reviewing behaviors on e-commerce websites may have been affected by extrinsic motivations, intrinsic motivations or both. Second, the proposed review-to-feature mapping technique is a feasible method for exploring reviewers’ opinions in both massive and sparse reviews. Finally, the customers’ reviewing behaviors were found to be mostly consistent with reviewers’ motivations.

First, the authors propose that the “promptness” of users in posting online reviews is an important external manifestation of their motivation, product experience and service experience. Second, a semi-supervised method of review-to-aspect mapping is used to solve the data quality problem in mining information from massive text data, which vary in length, detail and quality. Finally, a huge amount of e-commerce customers’ purchase-review promptness are studied and the results indicate that not all product features are responsible for the “prompt” posting of users’ reviews, and that the platform’s strategy to encourage users to post reviews will not work in the long term.

The future construction site will be pervasive, context aware and embedded with intelligence. The purpose of this paper is to explore and define the concept of the digital skin of the future smart construction site.

The paper provides a systematic and hierarchical classification of 114 articles from both industry and academia on the digital skin concept and evaluates them. The hierarchical classification is based on application areas relevant to construction, such as augmented reality, building information model-based visualisation, labour tracking, supply chain tracking, safety management, mobile equipment tracking and schedule and progress monitoring. Evaluations of the research papers were conducted based on three pillars: validation of technological feasibility, onsite application and user acceptance testing.

Technologies learned about in the literature review enabled the envisaging of the pervasive construction site of the future. The paper presents scenarios for the future context-aware construction site, including the construction worker, construction procurement management and future real-time safety management systems.

Based on the gaps identified by the review in the body of knowledge and on a broader analysis of technology diffusion, the paper highlights the research challenges to be overcome in the advent of digital skin. The paper recommends that researchers follow a coherent process for smart technology design, development and implementation in order to achieve this vision for the construction industry.

This study aimed to investigate positive associations between three main motivations (social interaction, information and entertainment) for the use of social network sites (SNSs) and users' well-being, as well as the multiple mediating effects of perceived social support, positive and honest self-presentation.

A sample of 759 active users of SNSs (WeChat Moments, Qzone and Weibo) aged 14–43 years was measured with online questionnaires. Correlation analysis and structural equation modeling were implemented to examine the corresponding hypotheses.

The results showed the overall intensity of motivations was positively associated with users' well-being; perceived social support and positive self-presentation played intermediary roles and honest self-presentation and perceived social support had a chain mediation effect. However, the motivations of social interaction, information and entertainment indirectly affected users' well-being through three different mediation paths.

Although some studies have investigated the effects of motivations (including social interaction, information and entertainment) for SNS use on users' well-being, there has not been a consistent conclusion. The findings may shed light on the motivations for SNS use and how they may affect people's well-being in the digital era, thereby promoting their healthy use of SNSs as well as improved interface design and user management of SNSs.

Simulation-based optimisation (SO) is a popular optimisation approach for building and civil engineering construction planning. However, in the framework of SO, the simulation is continuously invoked during the optimisation trajectory, which increases the computational loads to levels unrealistic for timely construction decisions. Modification on the optimisation settings such as reducing searching ability is a popular method to address this challenge, but the quality measurement of the obtained optimal decisions, also termed as optimisation quality, is also reduced by this setting. Therefore, this study aims to develop an optimisation approach for construction planning that reduces the high computational loads of SO and provides reliable optimisation quality simultaneously.

This study proposes the optimisation approach by modifying the SO framework through establishing an embedded connection between simulation and optimisation technologies. This approach reduces the computational loads and ensures the optimisation quality associated with the conventional SO approach by accurately learning the knowledge from construction simulations using embedded ensemble learning algorithms, which automatically provides efficient and reliable fitness evaluations for optimisation iterations.

A large-scale project application shows that the proposed approach was able to reduce computational loads of SO by approximately 90%. Meanwhile, the proposed approach outperformed SO in terms of optimisation quality when the optimisation has limited searching ability.

The core contribution of this research is to provide an innovative method that improves efficiency and ensures effectiveness, simultaneously, of the well-known SO approach in construction applications. The proposed method is an alternative approach to SO that can run on standard computing platforms and support nearly real-time construction on-site decision-making.

Authenticity has been studied from a variety of disciplinary perspectives, leading to a rich but confused literature. This study, a review, aims to compare the psychology and sociology/tourism definitions of authenticity to clarify the concept. From a psychological perspective, authenticity is a mental appraisal of an object or experience as valued leading to feelings and summative judgements (such as satisfaction or perceived value). In objective authenticity, a person values the object due to belief in an expert’s opinion, constructive authenticity relies on socially constructed values, while existential authenticity is based on one’s self-identity. The resultant achievement of a valued goal, such as seeing a valued object, leads to feelings of pleasure. Sociological definitions are similar but based on different theoretical antecedent causes of constructed and existential authenticity. The paper further discusses the use of theory in tourism and the project to develop tourism as a discipline. This project is considered unlikely to be successful and in turn, as argued, it is more useful to apply theory from other disciplines in a multidisciplinary manner. The results emphasise that it is necessary for tourism researchers to understand the origins and development of the concepts they use and their various definitions.

This conceptual article outlines the known effects of employee monitoring on employees who are working remotely. Potential implications, as well as practitioner suggestions, are outlined to identify how practitioners can create more supportive employee experiences as well as apply these to workplace health management scenarios.

This overview is based on a selective and practically oriented review of articles that hitherto considered the health implications of remote workers being monitored electronically over the last two years. This overview is subsequently complemented by a discussion of more recent findings that outline the potential implications of monitoring for remote employees, employees' work experience and workplace health management.

Several practitioner-oriented suggestions are outlined that can pave the way to a more supportive employee experience for remote workers, who are monitored electronically by their employers. These include the various health and social interventions, greater managerial awareness about factors that influence well-being and more collaboration with health professionals to design interventions and new workplace policies. Organizations would also benefit from using audits and data analytics from monitoring tools to inform their interventions, while a rethink about work design, as well as organizational reviews of performance and working conditions further represent useful options to identify and set up the right conditions that foster both performance as well as employee well-being.

The article outlines practitioner-oriented suggestions that can directly and indirectly support employee well-being by recognizing the various factors that affect performance and experience.