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This study aims to identify the perception of people in a Portuguese company regarding the main barriers to the effectiveness of the existing performance measurement system (PMS) and whether those perceptions are dependent of people’s hierarchical levels, education levels, work shifts, gender and department.

Primary data was collected through structured interviews (adapted to three levels of interviewees in the company hierarchy) and Likert scale questionnaires. Descriptive statistical analysis of the collected data was performed as well as a chi-square test.

The results provide an insight on the perception of barriers to the PMS effectiveness in the company. After performing interviews and questionnaires it was possible to identify that the main perceived barriers were: poor communication system and issues on target definition, lack of trained resources, employee involvement, indicators understanding and use for improvement.

This study is the starting point to develop actions aiming to eliminate, or at least mitigate, the impact of the barriers on the PMS effectiveness.

PMSs play an essential role in an organization, so it is essential to identify what hinders its effectiveness. This study opens the discussion by diagnosing the company’s perception of the barriers to PMS effectiveness.

This study aims to determine and evaluate the artificial intelligence (AI) development and competitiveness of the top 20 countries that receive the highest number of tourists with the entropy technique for order of preference by similarity to the ideal solution (TOPSIS)-integrated method.

This study is based on Global AI Index data published by Tortoise Media. Based on this index, according to the World Tourism Organization (UNWTO) report, the top 20 destinations that will host the highest number of tourists in 2022 were evaluated in seven different subpillars, which are talent, infrastructure, operating environment, research, development, government strategy and commercial. These seven subpillars of the index were considered as criteria, and the top 20 tourist destinations were included in the research as decision alternatives.

The analysis results show that the three most important AI criteria are operating environment, infrastructure and government strategy. Furthermore, the first three countries with the best AI performance according to the weighted criteria were the USA, China and the UK, respectively.

Considering that AI technologies will direct tourist behavior in a world where technology is rapidly developing, it is recommended that the countries that receive the highest number of tourists improve their AI performance.

When the relevant literature is examined, there is a limited number of studies examining the AI development and competitiveness of the top tourist destinations and weighting the Global AI Index values. Therefore, this study contributes to the gap in the relevant literature.

The purpose of this paper is to systematically analyze existing studies related to the adoption of smart technologies in cruise tourism services, particularly robots, artificial intelligence, service automation and virtual reality. More specifically, the authors intend to highlight the current state of research on this topic, present the findings within a conceptual framework and propose a research agenda.

The relevant literature was extracted using two major electronic databases, web of science (WoS) and Scopus. The authors identified 31 articles from high-quality journals and used a systematic review and the VOSviewer software to analyze them.

Since 2014, there has been an increase in the number of studies related to smart technologies in cruise tourism services. At first, researchers focused on Royal Caribbean’s robotic bartender arm, whereas other technologies such as digital signage, self-service options, facial recognition and virtual culinary experiences received less attention. However, the interest in exploring these last smart technologies has grown significantly since 2019. The adoption of RAISA in the cruise tourism service (ASCT) framework was proposed, identifying five major domains: cruise robotic technology, technology innovation, cruise passengers’ engagement behavior, cruise passengers’ technology readiness and privacy perception and knowledge expertise. These domains provide valuable guidance for future research in this field.

To the best of the authors’ knowledge, this is the first study to systematically analyze literature on the adoption of new technologies in cruise tourism services, specifically focusing on the major technologies available on cruise ships.

本文的主要目标是系统地分析与邮轮旅游服务中智能技术采用（RAISA）相关的现有研究, 特别是关于机器人、人工智能、服务自动化和虚拟现实等方面。具体而言, 我们意图突出此主题的当前研究现状, 将研究结果呈现在一个概念框架中, 并提出一个研究议程。

我们使用了两个主要的电子数据库 WoS 和 Scopus 提取相关文献。我们从高质量期刊中找到了 31 篇文章, 并采用系统综述和 VOSviewer 软件对它们进行了分析。

自 2014 年以来, 与邮轮旅游服务中智能技术相关的研究数量不断增加。最初, 研究人员着重关注皇家加勒比邮轮公司的机器人调酒师臂, 而其他技术, 如数字标识、自助选项、面部识别和虚拟烹饪体验等, 得到的关注较少。然而, 自 2019 年以来, 探索这些智能技术的兴趣显著增长。提出了 ASCT 框架, 识别了五个主要领域：邮轮机器人技术; 技术创新; 邮轮旅客参与行为; 邮轮旅客技术准备度; 以及隐私感知和专业知识。这些领域为该领域的未来研究提供了有价值的指导。

这是第一篇系统分析邮轮旅游服务中新技术采用文献的研究, 特别聚焦于邮轮上的主要技术。

To solve the obstacle detection problem in robot autonomous obstacle negotiation, this paper aims to propose an obstacle detection system based on elevation maps for three types of obstacles: positive obstacles, negative obstacles and trench obstacles.

The system framework includes mapping, ground segmentation, obstacle clustering and obstacle recognition. The positive obstacle detection is realized by calculating its minimum rectangle bounding boxes, which includes convex hull calculation, minimum area rectangle calculation and bounding box generation. The detection of negative obstacles and trench obstacles is implemented on the basis of information absence in the map, including obstacles discovery method and type confirmation method.

The obstacle detection system has been thoroughly tested in various environments. In the outdoor experiment, with an average speed of 22.2 ms, the system successfully detected obstacles with a 95% success rate, indicating the effectiveness of the detection algorithm. Moreover, the system’s error range for obstacle detection falls between 4% and 6.6%, meeting the necessary requirements for obstacle negotiation in the next stage.

This paper studies how to solve the obstacle detection problem when the robot obstacle negotiation.

This study is carried out to evaluate how well legal knowledge can be demonstrated by a built environment professional via the scenario-based approach to the learning of law modules.

A Delphi analysis of the advice provided by an MSC quantity surveying student, on a scenario-based legal problem arising due to a property contract, is carried out. The tendered legal advice was submitted as part of the assessment requirements for an MSc law module, following the university criteria, after the teaching of a law module. The student report, which attained an A-grade, and the assessment criteria used for marking/grading by the university were subsequently sent to 18 practicing lawyers, who were selected to constitute an expert panel, to independently judge the extent of legal knowledge demonstrated in the student report.

The Delphi analysis outcome showed that the expert panel holds a similar consensus view to the university on the level of legal knowledge demonstrated and by extension the effectiveness of the law module in imparting legal knowledge to a non-lawyer. The study outcome shows how well legal knowledge can be acquired and applied by a non-lawyer, within the context of the built environment, via scenario-based teaching of a law module.

This study serves as a preliminary step necessary to arouse further research toward empirically profiling the current outlook of a wider range of graduating students receiving scenario-based legal education in the built environment.

Online collaboration in today's world is a topic of genuine interest to Internet researchers. The purpose of this paper is to explore the role of group knowledge heterogeneity (GKH) in open collaboration performance using the mediating mechanisms of group cognition (GC) and interaction to understand the determinants of the success of online open collaboration platforms.

Study findings are based on partial least squares structural equation modeling (PLS-SEM), the formal mediation test and moderating effect analysis from Wikipedia's 160 online open collaborative groups.

For online knowledge heterogeneous groups, open collaboration performance is mediated by both GC and collaborative interaction (COL). The mediating role of GC is weak, while the mediating role of COL is strengthened when knowledge complexity (KC) is higher. By dividing group interaction into COL and communicative interaction (COM), the authors also observed that COL is effective for online open collaboration, whereas COM is limited.

These findings suggest that for more heterogeneous large groups, group interaction would explain more variance in performance than GC, offering an in-depth understanding of the relationship between group heterogeneity and open collaboration performance, answering what determines the success of online open collaboration platforms as well as explaining the inconsistency in prior findings. In addition, this study expands the application of Interactive Team Cognition (ITC) theory to the online open collaboration context.

This study is a targeted review of some of the major changes in European regulation that guided energy policy decisions in the Iberian Peninsula and how they may have aggravated the problem of lack of flexibility. This study aims to assess some of the proposed short-term solutions to address this issue considering the underlying root causes and suggests a different course of action, that in turn, could help alleviate future market strains.

The evolution of the most important (macro) energy and price-related variables in both Portugal and Spain is assessed using market and grid operator data. In addition, the authors present critical viewpoints on some of the most recent EU and national regulation changes (official document analysis).

The Iberian energy policy and regulatory agenda has successfully promoted a rapid adoption of renewables (main goal), although with insufficient diversification of generation technologies. The compulsory closings of thermal plants and an increased tax (mainly carbon) added pressure toward more environmentally friendly thermal power plants. However, inevitably, this curbed the bidding price competitiveness of these producers in an already challenging market framework. Moving forward, decisions must be based on “a bigger picture” that does not neglect system flexibility and security of supply and understands the specificities of the Iberian market and its generation portfolio.

This work provides an original account of unprecedented spikes in energy prices in 2021, specifically in the Iberian electricity market. This acute situation worries consumers, industry and governments. Underlining the instability of the market prices, for the first time, this study discusses how some of the most important regulatory changes, and their perception and absorption by involved parties, contributed to the current environment. In addition, this study stresses that if flexibility is overlooked, the overall purpose of having an affordable and reliable system is at risk.

This study aims to explore the impact of architecture on digital communication mediums, focusing on how social media shapes the public perception and discussion of architectural spaces. It specifically examines the case of the Basilica Cistern/Istanbul, analysing social media interactions post-restoration.

Using newspaper archive scanning and survey technique, this study observed public content on Instagram focusing on the post-restoration period of the Basilica Cistern. 406 (283 valid) people who visited the Cistern and shared their experiences on Instagram between August 2022 and January 2023 participated in a survey. The analysis utilized Python for advanced correlation studies, enabling an in-depth exploration of the interplay between architectural features and social media sharing behaviours.

The analysis revealed that historical significance, lighting elements, role as a photographic backdrop significantly influenced sharing behaviours. Correlations were found between specific spatial features of the cistern and various sharing motivations, such as communication with people, personal gain, and popularity. The study highlights a diverse spectrum of motivations among users, emphasizing the relationship between these motivations and spatial features.

This study underscores the necessity for further inquiry into the intricate dynamics among digital communication, architectural spaces, and user motivations. Limitations include potential challenges in gathering data from social media due to concerns of cyber fraud and the misuse of hashtags.

This research offers novel insights into the interplay between digital communication and architecture. It underscores the potential of digital platforms as valuable data sources for architectural theorizing and practice, particularly in understanding how restorations and architectural changes are perceived and discussed in the digital space.