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The purpose of this paper is to try to reach the main factors that could put national security at risk as a result of government cloud computing programs.

The paper adopts the analytical approach to first lay foundations of the relation between national security, cybersecurity and cloud computing, then it moves to analyze the main vulnerabilities that could affect national security in cases of government cloud computing usage.

The paper reached several findings such as the relation between cybersecurity and national security as well as a group of factors that may affect national security when governments shift to cloud computing mainly pertaining to storing data over the internet, the involvement of a third party, the lack of clear regulatory frameworks inside and between countries.

Governments are continuously working on developing their digital capacities to meet citizens’ demands. One of the most trending technologies adopted by governments is “cloud computing”, because of the tremendous advantages that the technology provides; such as huge cost-cutting, huge storage and computing capabilities. However, shifting to cloud computing raises a lot of security concerns.

The value of the paper resides in the novelty of the topic, which is a new contribution to the theoretical literature on relations between new technologies and national security. It is empirically important as well to help governments stay safe while enjoying the advantages of cloud computing.

With the rapid development of railway-intelligent video technology, scene understanding is becoming more and more important. Semantic segmentation is a major part of scene understanding. There is an urgent need for an algorithm with high accuracy and real-time to meet the current railway requirements for railway identification. In response to this demand, this paper aims to explore a variety of models, accurately locate and segment important railway signs based on the improved SegNeXt algorithm, supplement the railway safety protection system and improve the intelligent level of railway safety protection.

This paper studies the performance of existing models on RailSem19 and explores the defects of each model through performance so as to further explore an algorithm model dedicated to railway semantic segmentation. In this paper, the authors explore the optimal solution of SegNeXt model for railway scenes and achieve the purpose of this paper by improving the encoder and decoder structure.

This paper proposes an improved SegNeXt algorithm: first, it explores the performance of various models on railways, studies the problems of semantic segmentation on railways and then analyzes the specific problems. On the basis of retaining the original excellent MSCAN encoder of SegNeXt, multiscale information fusion is used to further extract detailed features such as multihead attention and mask, solving the problem of inaccurate segmentation of current objects by the original SegNeXt algorithm. The improved algorithm is of great significance for the segmentation and recognition of railway signs.

The model constructed in this paper has advantages in the feature segmentation of distant small objects, but it still has the problem of segmentation fracture for the railway, which is not completely segmented. In addition, in the throat area, due to the complexity of the railway, the segmentation results are not accurate.

The identification and segmentation of railway signs based on the improved SegNeXt algorithm in this paper is of great significance for the understanding of existing railway scenes, which can greatly improve the classification and recognition ability of railway small object features and can greatly improve the degree of railway security.

This article introduces an enhanced version of the SegNeXt algorithm, which aims to improve the accuracy of semantic segmentation on railways. The study begins by investigating the performance of different models in railway scenarios and identifying the challenges associated with semantic segmentation on this particular domain. To address these challenges, the proposed approach builds upon the strong foundation of the original SegNeXt algorithm, leveraging techniques such as multi-scale information fusion, multi-head attention, and masking to extract finer details and enhance feature representation. By doing so, the improved algorithm effectively resolves the issue of inaccurate object segmentation encountered in the original SegNeXt algorithm. This advancement holds significant importance for the accurate recognition and segmentation of railway signage.

In recent years, the robotic process automation (RPA) technology, a software-based method to automate routine tasks in business processes, has gained significant interest and adoption. However, many implementation projects fail and current literature lacks a synthesis and comprehensive overview of factors that challenge the implementation of RPA, have an impact on success or failure of projects, or, play an enabling role in an RPA project. Hence, the purpose of this research is to identify key factors that should be considered by organizations when conducting an RPA project.

The paper adopts a qualitative methodology based on data collected in a systematic literature review (SLR) and interviews with 10 RPA experts. Using inductive coding, an integrated framework of key factors is developed.

The results suggest that the key factors for a successful RPA introduction can be divided into human, organizational and technical factors. Important aspects include for example project management techniques, capabilities and skills of employees, as well as data security considerations.

The paper contributes to knowledge by synthesizing previously dispersed knowledge into an integrated framework, as well as by complementing previous results with new qualitative, empirical data. Additionally, the RPA-specific factors are put into the perspective of persistent problems in information systems development.

This study aims to investigate city branding as a post-pandemic COVID-19 outcome factor on brand satisfaction, brand experience, perceived risk and revisit intention. In addition, this research contributes to the discussion of post-COVID-19 city branding that needs to be considered in the development of future tourism marketing.

A quantitative approach was used with PLS-SEM statistical analysis and a 263-tourist sample. The study was conducted on tourists from Malang Regency in Indonesia by distributing questionnaires modified from previous studies in a similar context.

The results of this study found that there were significant influences of city brand personality on brand experience, brand satisfaction, brand experience on perceived risk, brand satisfaction on revisit intention and perceived risk on revisit intention. This study also presents the mediating role.

The study was only conducted on a small regency in Indonesia, and therefore the results cannot be generalized for other cities over the world.

The proposed study model suggests that stakeholders must seek to socialize services to potential tourists, so that tourists can understand the description of tourism activities that can be enjoyed during the COVID-19 pandemic and the way they travel in the future.

Understanding the determinant factors of city branding post-COVID-19 was valuable for developing marketing strategies to cope with intense competition among the city.

This study emphasizes the determinants of COVID-19 perceived risk and revisit intentions as explained in the tourism marketing literature by considering the role of brand satisfaction, brand experience and city brand personality which significantly contribute to build the city competitiveness. Therefore, various creative strategies should be implemented to promote the city as well as escalate tourist visits without ignoring the pandemic’s risks.

Previous studies have postulated that an advance payment system (APS) positively impacts the contractor's working capital and is paramount to ensuring an efficient and effective project cash flow process. However, scant research has been undertaken to empirically establish the cash flow performance and domino effect of APS on project and organisational performance.

The epistemological design adopted a positivist philosophical stance augmented by deductive reasoning to explore the phenomena under investigation. Primary quantitative data were collected from 504 Construction Industry Development Board (CIDB) registered contractors (within the grade bandings 1–9) in South Africa. A five-point Likert scale was utilised, and subsequent data accrued were analysed using structural equation modelling (SEM).

Emergent findings reveal that the mandatory use of an APS does not guarantee a positive project cash flow, an improvement in organisational performance or an improvement in project performance.

The ensuing discussion reveals the contributory influence of APS on positive cash flow and organisational performance, although APS implementation alone will not achieve these objectives. Practically, the research accentuates the need for various measures to be concurrently adopted (including APS) towards ensuring a positive project cash flow and improved organisational and project performance.

There is limited empirical research on cash flow performance and the domino effect of APS on project and organisational performance in South Africa, nor indeed, the wider geographical location of Africa as a continent. This study addresses this gap in the prevailing body of knowledge.

Studies showed that construction digitalisation could prevent or mitigate accidents rate on sites. Digitalisation applications may prevent or mitigate building project collapse (BPC) but with some encumbrances, especially in developing countries. There is a paucity of research on digital technologies application to prevent or mitigate BPC in Nigeria. Thus, the research aims to explore the perceived barriers that may hinder digital technologies from preventing or mitigating building collapse and recommend measures to improve technology applications during development.

The study is exploratory because of the unexplored approach. The researchers collected data from knowledgeable participants in digitalisation and building collapse in Nigeria. The research employed a phenomenology approach and analysed collected data via a thematic approach. The study achieved saturation at the 29th interviewee.

Findings show that lax construction digitalisation implementation, absence of regulatory framework, lax policy, unsafe fieldworkers' behaviours, absence of basic infrastructure, government attitude, hesitation to implement and high technology budget, especially in developing countries, are threats to curbing building collapse menace via digitalisation. The study identified technologies relevant to preventing or mitigating building collapse. Also, it proffered measures to prevent or mitigate building collapse via improved digital technology applications during development.

This research contributes to the construction digitalisation literature, especially in developing countries, and investigates the perceived barriers that may hinder digital technologies usage in preventing or mitigating building collapse in Nigeria.

This study aims to examine the tourists' visit intention by watching deepfake destination videos, using Information Manipulation and Media Richness Theory.

This study conducted a primary survey utilizing a structured questionnaire. In total, 1,360 tourists were surveyed, and quantitative data analysis was done using PLS-SEM.

The results indicate that the factors that affect the tourists' visit intention after watching deepfake videos include information manipulation tactics, trust and media richness. This study also found that perceived deception and cognitive load do not influence the tourists' visit intention.

The originality/salience of this study lies in the fact that this is possibly among the first to combine the Media Richness Theory and Information Manipulation for understanding tourists' visit intention and post-viewing deepfake destination videos.

The organizational digital transformation (ODT) in companies presents small and medium-sized enterprises (SMEs) – who remain at the beginning of this transformation – with the challenge of offering digital services based on sensor technologies. Against this backdrop, the present paper identifies ways SMEs can enable digital servitization through sensor technology and defines the possible scope of the organizational transformation process.

Around 21 semi-structured interviews were conducted with experts from different hierarchical levels across the German manufacturing SME ecosystem. Using the Gioia methodology, fields of action were identified by focusing on influencing factors and opportunities for developing these digital services to offer them successfully in the future.

The complexity of existing sensor offerings must be mastered, and employees' (data) understanding of the technology has increased. Knowledge gaps, which mainly relate to technical and organizational capabilities, must be overcome. The potential of sensor technology was considered on an individual, technical and organizational level. To enable the successful implementation of service offerings based on sensor technology, all relevant stakeholders in the ecosystem must network to facilitate shared value creation. This requires standardized technical and procedural adaptations and is an essential prerequisite for data mining.

Based on this study, current problem areas were analyzed, and potentials that create opportunities for offering digital sensor services to manufacturing SMEs were identified. The identified influencing factors form a conceptual framework that supports SMEs' future development of such services in a structured manner.

Research on online user privacy shows that empirical evidence on how privacy literacy relates to users' information privacy empowerment is missing. To fill this gap, this paper investigated the respective influence of two primary dimensions of online privacy literacy – namely declarative and procedural knowledge – on online users' information privacy empowerment.

An empirical analysis is conducted using a dataset collected in Europe. This survey was conducted in 2019 among 27,524 representative respondents of the European population.

The main results show that users' procedural knowledge is positively linked to users' privacy empowerment. The relationship between users' declarative knowledge and users' privacy empowerment is partially supported. While greater awareness about firms and organizations practices in terms of data collections and further uses conditions was found to be significantly associated with increased users' privacy empowerment, unpredictably, results revealed that the awareness about the GDPR and user’s privacy empowerment are negatively associated. The empirical findings reveal also that greater online privacy literacy is associated with heightened users' information privacy empowerment.

While few advanced studies made systematic efforts to measure changes occurred on websites since the GDPR enforcement, it remains unclear, however, how individuals perceive, understand and apply the GDPR rights/guarantees and their likelihood to strengthen users' information privacy control. Therefore, this paper contributes empirically to understanding how online users' privacy literacy shaped by both users' declarative and procedural knowledge is likely to affect users' information privacy empowerment. The study empirically investigates the effectiveness of the GDPR in raising users' information privacy empowerment from user-based perspective. Results stress the importance of greater transparency of data tracking and processing decisions made by online businesses and services to strengthen users' control over information privacy. Study findings also put emphasis on the crucial need for more educational efforts to raise users' awareness about the GDPR rights/guarantees related to data protection. Empirical findings also show that users who are more likely to adopt self-protective approaches to reinforce personal data privacy are more likely to perceive greater control over personal data. A broad implication of this finding for practitioners and E-businesses stresses the need for empowering users with adequate privacy protection tools to ensure more confidential transactions.

Mainland Tanzania has seen two decades of significant social policy reforms and transformations in its social and economic structures, whilst the country continues to grapple with persisting gender inequalities. This article examines Tanzania's social policy developments from a gender perspective. The authors analyse the level, reach and quality of social policy delivery to working-age women across the areas of health policy, social protection and employment policy during 2000–2021.

The article draws on qualitative research deploying the scoping review method. The data consist of diverse secondary materials, including academic publications, government policy documents, relevant statistics and other types of “grey” literature.

Tanzania has made significant advancements in the legal frameworks around welfare provision and has instituted increasingly gender-responsive government policy plans. The health and social protection sectors, in particular, have witnessed the introduction of large-scale measures expanding social policy implementation. However, social policy delivery remains two-tiered, with differences in provisions for women in the formal and informal sectors.

Social policy delivery and implementation have increased and diversified in Sub-Saharan Africa (SSA) during the new millennium, with a growing integration of gender-specific policy objectives. However, limited social policy scholarship has focused on the gendered effects of broader social policy models in SSA. The article remedies the concomitant knowledge gaps by examining various social policies and their impacts on working-age women in Mainland Tanzania. The authors also engage with the theoretical welfare regime literature and present an analytical framework for gender-sensitive assessment of emerging social policy models in the Global South.