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Within critical-infrastructure industries, bow-tie analysis is an established way of eliciting requirements for safety and reliability concerns. Because of the ever-increasing digitalisation and coupling between the cyber and physical world, security has become an additional concern in these industries. The purpose of this paper is to evaluate how well bow-tie analysis performs in the context of security, and the study’s hypothesis is that the bow-tie notation has a suitable expressiveness for security and safety.

This study uses a formal, controlled quasi-experiment on two sample populations – security experts and security graduate students – working on the same case. As a basis for comparison, the authors used a similar experiment with misuse case analysis, a well-known technique for graphical security modelling.

The results show that the collective group of graduate students, inexperienced in security modelling, perform similarly as security experts in a well-defined scope and familiar target system/situation. The students showed great creativity, covering most of the same threats and consequences as the experts identified and discovering additional ones. One notable difference was that these naïve professionals tend to focus on preventive barriers, leading to requirements for risk mitigation or avoidance, while experienced professionals seem to balance this more with reactive barriers and requirements for incident management.

Our results are useful in areas where we need to evaluate safety and security concerns together, especially for domains that have experience in health, safety and environmental hazards, but now need to expand this with cybersecurity as well.

Purpose – The purpose of this paper is to develop prototype of the web-based home fire early warning system using Wiznet W5500 Ethernet module. This system protocol helps users in sending information of fire through the internet with the internet of things (IoT) method using Wiznet Ethernet module as communication media to the user.

Design/Methodology/Approach – This paper presents the design of web-based home fire early warning system using Wiznet W5500 Ethernet module. The system prototype is built using flame sensors, MQ-02 smoke sensors, and LM35 temperature sensors as input components. While on the processor side using Arduino Uno microcontroller as sensor data processing. Processed data is sent to the Ethernet module as a web server resulting in a web-based early warning information system with an alarm notification on the browser along with home location status information and sensor data.

Findings – This research produces a prototype of the web-based home fire early warning system using Wiznet W5500 Ethernet module that has been able to provide notification to the security officer housing.

Research Limitations/Implications – In the implementation of measurement, the information system only accesses one house detector or one fire location.

Practical Implications – This research produces a prototype of the web-based home fire early warning system using Wiznet W5500 Ethernet module that has been able to distribute data of temperature, smoke, and fire.

Originality/Value – The development of fire monitoring systems using flame sensors, smoke sensors and integrated temperature sensors in internet-based communication systems of things via the Internet W5500 does not appear to have been published yet.

The purpose of this paper is to examine the extent to which HTTPS encryption and Google Analytics services have been implemented on academic library websites, and discuss the privacy implications of free services that introduce web tracking of users.

The home pages of 279 academic libraries were analyzed for the presence of HTTPS, Google Analytics services and privacy-protection features.

Results indicate that HTTPS implementation on library websites is not widespread, and many libraries continue to offer non-secured connections without an automatically enforced redirect to a secure connection. Furthermore, a large majority of library websites included in the study have implemented Google Analytics and/or Google Tag Manager, yet only very few connect securely to Google via HTTPS or have implemented Google Analytics IP anonymization.

Librarians are encouraged to increase awareness of this issue and take concerted and coherent action across five interrelated areas: implementing secure web protocols (HTTPS), user education, privacy policies, informed consent and risk/benefit analyses.

Third-party tracking of users is prevalent across the web, and yet few studies demonstrate its extent and consequences for academic library websites.

Although we have achieved a greater understanding of cryptomarket specifics, evidence on the consumer side of cryptomarkets is still needed – not only regarding the role of cryptomarkets on individual drug-using careers but also on the motives for buying illicit drugs from cryptomarkets. Moreover, research has indicated that national differences exist regarding different variables relating to cryptomarket use and prevalence, as well as to why users are drawn to these markets. In this chapter, the author presents the results of a Belgian case study focusing on drug cryptomarket buyers. Using an online quantitative survey (N = 99) and semi-structured interviews (N = 10), we gain exploratory insight into the motives of Belgian buyers sourcing illicit drugs from cryptomarkets and how they believe these cryptomarkets affect their drug-using careers. Results indicate that most of the respondents had bought drugs offline before buying them from cryptomarkets and that the frequency of their drug use did not change once cryptomarkets were accessed. Almost 60% of our respondents, however, consumed different drugs or a wider range of drugs following their cryptomarket use. Furthermore, most of the respondents purchased from cryptomarkets for their personal consumption, and some of them also shared their supply with friends, that is, social supply. The alternative drug offer was the principal reason why they were using cryptomarkets, followed by curiosity and the price and the quality of the drugs. Although the respondents in this study were well aware of different risks related to market vendors, market administrators, and law enforcement, these risks were considered to be minimal and part of the cryptomarket environment. The results of this case study are informative and highlight areas requiring further research.

The purpose of this paper is to introduce Google Analytics as a format suitable for advanced tracking of reading behavior within web books, set the metrics for measuring the reading behavior of web books and describe the first results of a pilot study. This paper offers suggestions for further deployment of web books and web analytics in digital libraries and evaluating web books' performance.

To understand the reading behavior of web book users, researchers use quantitative research methods based on custom and advanced metrics at Google Analytics.

Google Analytics is a valuable tool for tracking access to individual books and tracking entire web book collections, mainly if researchers use the combination of unique custom and advanced metrics. A pilot study with 190 users uncovered significant results on reading behavior, for example, the strong preference for scrolling over navigation buttons.

This pilot study is limited to measuring two web books and 190 users. This study demonstrated a workable setup of metrics for measuring reading behavior; it would be helpful to continue measurement with a larger sample of books and users.

Researchers in library and information science currently use web analytics mainly to understand user behavior on the website and in the catalog. This paper presents the possibilities of deploying Google Analytics directly in web books to understand reading behavior.

The purpose of this paper is to investigate how well hotel website load time performance compared against customer expectation benchmarks. In a competitive market, service interactions are important. As customers move to mobile devices, the time to load a website is a critical part of the service delivery. Long load times can lead to poor service experiences, customer frustration and lost business. Hotel website load times on both mobile and desktop devices were examined and compared to service expectations.

The study used an online service to assess and compare website load performance using both desktop and mobile devices for 259 international hotel company and sub-brand websites.

The time to load hotel websites was significantly slower on mobile devices compared to desktops. Load times on both platforms exceeded 3 s, which is considered best practice. Long load times represent a service gap and can cause dissatisfaction resulting in a potential customer abandoning the website for a competitor’s site, thus affecting sales.

While the population for the study was robust in size and contained most of the major hotel companies worldwide, it was not exhaustive. Data also represent a snapshot and will change over time. Load times vary based on test location, access device and network traffic. Additionally, web page load times and customer expectations will change as technology evolves.

Increased use of mobile devices for hotel reservations increases the importance of mobile service delivery. This is the first known study to measure hotel website load times for mobile devices, and to examine both mobile and desktop performance against best practice. The results of this study highlight a service gap, which can lead to loss of business. Given the consistency of the results, the authors suspect that this is an issue that has not been recognized within the industry. This study is valuable because it exposes an issue of website design not generally addressed in the hospitality industry, even though tools are available to monitor site performance.

The aim of this study is to examine the behavioral intention (BI) to adopt the Coinbase Wallet by Spanish users.

A survey was administered to individuals residing in Spain between March and April 2021. There were 301 questionnaires analyzed. This research applies a new predictive model based on technology acceptance model (TAM) 2, the unified theory of acceptance and use of technology (UTAUT) model, the theory of perceived risk and the commitment trust theory. A mixed partial least squares structural equation modeling (PLS-SEM)/fuzzy-set qualitative comparative analysis (fsQCA) methodology was employed for the modeling and data analysis.

The results showed that all the variables proposed have a direct and positive influence on the intention to use a Coinbase Wallet. The findings present clear directions for traders, investors and academics focused on improving their understanding of the characteristics of these markets.

First, this study addresses important concerns relating to the adoption of crypto-wallets during the global pandemic. Second, this research contributes to the existing literature by adding electronic word of mouth (e-WOM), trust, web quality and perceived risk as new drivers of the intention to use the Coinbase Wallet, providing unique and innovative insights. Finally, the study offers a solid methodological contribution by integrating linear (PLS) and nonlinear (fsQCA) techniques, showing that both methodologies provide a better understanding of the problem and a more detailed awareness of the patterns of antecedent factors.

This paper aims to describe the development of a knowledge management system (KMS) for the Nadir and Occultation for Mars Discovery (NOMAD) instrument on board the ESA/Roscosmos 2016 ExoMars Trace Gas Orbiter (TGO) spacecraft. The KMS collects knowledge acquired during the engineering process that involved over 30 project partners. In addition to the documentation and technical data (explicit knowledge), a dedicated effort was made to collect the gained experience (tacit knowledge) that is crucial for the operational phase of the TGO mission and also for future projects. The system is now in service and provides valuable information for the scientists and engineers working with NOMAD.

The NOMAD KMS was built around six areas: official documentation, technical specifications and test results, lessons learned, management data (proposals, deliverables, progress reports and minutes of meetings), picture files and movie files. Today, the KMS contains 110 GB of data spread over 11,000 documents and more than 13,000 media files. A computer-aided design (CAD) library contains a model of the full instrument as well as exported sub-parts in different formats. A context search engine for both documents and media files was implemented.

The conceived KMS design is basic, flexible and very robust. It can be adapted to future projects of a similar size.

The paper provides practical guidelines on how to retain the knowledge from a larger aerospace project. The KMS tool presented here works offline, requires no maintenance and conforms to data protection standards.

This paper shows how knowledge management requirements for space missions can be fulfilled. The paper demonstrates how to transform the large collection of project data into a useful tool and how to address usability aspects.

This study investigates perceptions of the use of online tracking, a passive data collection method relying on the automated recording of participant actions on desktop and mobile devices, for studying information behavior. It scrutinizes folk theories of tracking, the concerns tracking raises among the potential participants and design mechanisms that can be used to alleviate these concerns.

This study uses focus groups composed of university students (n = 13) to conduct an in-depth investigation of tracking perceptions in the context of information behavior research. Each focus group addresses three thematic blocks: (1) views on online tracking as a research technique, (2) concerns that influence participants' willingness to be tracked and (3) design mechanisms via which tracking-related concerns can be alleviated. To facilitate the discussion, each focus group combines open questions with card-sorting tasks. The results are analyzed using a combination of deductive content analysis and constant comparison analysis, with the main coding categories corresponding to the thematic blocks listed above.

The study finds that perceptions of tracking are influenced by recent data-related scandals (e.g. Cambridge Analytica), which have amplified negative attitudes toward tracking, which is viewed as a surveillance tool used by corporations and governments. This study also confirms the contextual nature of tracking-related concerns, which vary depending on the activities and content that are tracked. In terms of mechanisms used to address these concerns, this study highlights the importance of transparency-based mechanisms, particularly explanations dealing with the aims and methods of data collection, followed by privacy- and control-based mechanisms.

The study conducts a detailed examination of tracking perceptions and discusses how this research method can be used to increase engagement and empower participants involved in information behavior research.

This study aims to investigate the preferences of 96 educational researchers on the use of digital technologies in scientific research.

The study was designed as a quantitative-dominant sequential explanatory mixed-method research.

Despite the spreading use of advanced technologies of big data and data mining, the most preferred digital technologies were found to be data analysis programs, databases and questionnaires. The primary reasons of using digital technology in scientific research were to collect data easily and quickly, to reduce research costs and to reach a higher number of participants.

The use of digital technologies in scientific research is considered a revolutionary action, which creates innovative opportunities. Through digitalized life, probably for the first time in history, the educational researchers have analytical information, which we can benefit from more than the individual's own statements in research involving human factor. However, there are a few studies that investigated the preferences of educational researchers who use digital technologies in their scientific research.