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The purpose of this paper is to analyze the time-allocation decisions of individuals who work from home (i.e. teleworkers), and compare them with their commuter counterparts.

Using data from the American Time Use Survey for the years 2003–2015, the authors analyze the time spent working, and the timing of work, of both commuters and teleworkers.

Results show that teleworkers devote 40 percent less time to market work activities than do commuters, and less than 60 percent of teleworkers work at “regular hours,” vs around 80 percent of their commuter counterparts. Using information from the Well-being Module for the years 2012 and 2013, the authors find that male teleworkers experience lower levels of negative feelings while working than do commuters.

This paper addresses the timing of work of workers working from home; and the instant well-being experienced, exploiting information at diary level.

This chapter analyzes detailed 24-hour diary data from the United States to provide evidence on the relationship between workers' effort and well-being while at work. In doing so, we first measure workers' effort in terms of the amount of on-the-job leisure, number of on-the-job leisure episodes, and the time working until consuming on-the-job leisure. Second, we link these three measures of worker effort to data on instantaneous well-being while at work. We find that the less time devoted to on-the-job leisure and the number of on-the-job leisure episodes, and the more time workers spend working until on-the-job-leisure, the higher the levels of stress during their work tasks. In analyzing workers' effort and stress during market work activities, we contribute to the scant literature on the determinants of worker happiness while at work, positing the consumption and the frequency of on-the-job leisure as affective factors.

Knowing the behavior of tourists visiting cultural destinations enables better management of tourist flows, a better understanding of areas with greater tourist density and an opportunity to decongest popular neighborhoods. The purpose of this study is to segment tourists according to their spatio-temporal behavior and identify the primary variables that characterize the resulting segments, which will help urban destinations prevent problems arising from the saturation of tourists in certain areas.

To do this, this paper analyzes the behavior of tourists visiting the southeastern Spanish city of Granada, one of the most highly visited cultural tourism destinations. The data analysis used the methodology of sequence alignment which is used to identify segments as a function of their contained elements and the order in which these appear.

The results demonstrate the existence of three segments with different behavioral patterns: the “explorer tourists” segment, the “non-traditional cultural tourists” segments and the “typical cultural tourists” segment. These segments show differences in the concentration of their visits. This study discovered that the segments that visit a greater number of destination areas are those with less cultural orientation, higher travel budgets and younger and more frequent visitors.

In the segmentation not only keep in mind the visited areas, but the order in which they were visited as well. In addition, one should consider the time that each tourist remains in each relevant zone of the destination, given that the visiting time is an important variable to assess the congestion of an area.

The overall tourist experience is changing because of the development of mobile devices, ubiquitous internet access and applications (apps) designed specifically for tourism. The aim of this study is to identify the determinants of continued use and recommendation of such apps (loyalty), framed within the unified theory of acceptance and use of technology (UTAUT2) model, considering innate user traits (innovativeness) and one of the principal attributes of mobile phones (portability).

The sample comprised 285 Spanish tourists who owned a smartphone and were using some kind of mobile app in connection with their stay.

The results show that the UTAUT2 model is effective in explaining loyalty toward tourism apps and that its variables mediate the effect of user and mobile device characteristics.

To ensure continued use of a tourism app, it should possess the following core attributes: deliver a positive cost–benefit trade-off, be fun to use, provide up-to-date and useful information and generate a degree of dependency in the user.

The present research is particularly relevant because of its focus on the use of apps during the stay, given that most of the extant literature centers on previous stages (such as service booking).

游客整体感受正在因为移动终端、全网覆盖网络、以及旅游APP应用的发展而改变着。本论文旨在找到对于移动APP持续使用和推荐行为的成因，本论文采用UTAUT2模型，考虑了用户本身的创新性特点，和移动手机其中一个核心特点（便捷携带性）。

研究样本为285名西班牙游客，他们均持有一部智能手机，并且在旅游途中使用过某种旅游APP。

研究结果表明UTAUT2模型在解释旅游APP忠诚度方面是有效的。此外，本论文还发现其模型变量是用户特性对移动终端特点作用的中介变量。

为了保证用户对旅游APP的持续使用，这个APP需要具体几点核心特点：性价比高；娱乐性；及时性；有用信息；对用户有依赖性。

本论文针对用户在旅游途中的APP使用进行了研究，这有别于之前大多数文献仅集中对旅游前期（比如服务预定）等方面的研究。

移动APP、忠诚度、旅游业、UTAUT2、游客行为

In this paper, the authors present an empirical framework that incorporates different factors of the impact of COVID-19 on small- and medium-sized enterprises (SMEs) in La Rioja, Spain, in relation to the value chain, gender and family business and allows the evaluation of these impacts on the SMEs' outcomes.

The authors conduct exploratory research based on phone interviews with 329 business managers from SMEs in La Rioja (Spain), from June 1 to June 30 2021, using ordinary least squares linear regression and matching procedures to test the study hypotheses.

The results show that the impact of COVID-19 related to primary activities in adding value, such as inbound logistics, operations and marketing, have a positive influence on innovation outcomes in SMEs, as do female managers. Family SMEs present poorer innovation outcomes.

At the organizational level, this paper may be of interest to management, and at the national and regional levels to policymakers, since it could help to develop policies that support SMEs' sourcing, operations and marketing in order to prepare for potential value chain disruptions. Additionally, this research may help decision-makers to foster and promote innovation in SMEs as a way of ensuring their resilience.

In this paper, the authors provide novel evidence about the effect of COVID-19 in SMEs. Moreover, it has been shown that the COVID-19 pandemic has triggered the redefinition of supply chains at the organizational level.

The purpose of this paper is to describe the specification language TML for adaptive mission plans that the authors designed and implemented for the open-source framework Aerostack for aerial robotics.

The TML language combines a task-based hierarchical approach together with a more flexible representation, rule-based reactive planning, to facilitate adaptability. This approach includes additional notions that abstract programming details. The authors built an interpreter integrated in the software framework Aerostack. The interpreter was validated with flight experiments for multi-robot missions in dynamic environments.

The experiments proved that the TML language is easy to use and expressive enough to formulate adaptive missions in dynamic environments. The experiments also showed that the TML interpreter is efficient to execute multi-robot aerial missions and reusable for different platforms. The TML interpreter is able to verify the mission plan before its execution, which increases robustness and safety, avoiding the execution of certain plans that are not feasible.

One of the main contributions of this work is the availability of a reliable solution to specify aerial mission plans, integrated in an active open-source project with periodic releases. To the best knowledge of the authors, there are not solutions similar to this in other active open-source projects. As additional contributions, TML uses an original combination of representations for adaptive mission plans (i.e. task trees with original abstract notions and rule-based reactive planning) together with the demonstration of its adequacy for aerial robotics.

This chapter examines the patterns of immigrants’ integration in a state of the Midwest of the United States, Indiana, which has experienced a growth of more than 250% of the foreign-born population in the last 20 years. The study, based on in-depth interviews and document analysis, examines the ways that immigrants blend into mainstream society in everyday life and in social interactions, as well as the obstacles they encounter in this process. The study reveals the cultural changes in the host culture as a result of the large number of immigrants who have established their residence in this state, the dichotomies that emerge between “natives” and “newcomers.” It also shows that immigrants stay connected to their country of origin through electronic media (in particular television and computers) and how this technology affects the process of integration. Finally, the study demonstrates that there is a process of segmented assimilation and variations in the immigrants’ sense of identity according to their socioeconomic status and ethnic background.