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This study focused on exploring the performance factors (PFs) that impact Infrastructure Sanitation Projects (ISSPs) in the construction sector. The aim was twofold: firstly, to identify these crucial PFs and secondly, to develop a robust performance model capable of effectively measuring and assessing the intricate interdependencies and correlations within ISSPs. By achieving these objectives, the study aimed to provide valuable insights into and tools for enhancing the efficiency and effectiveness of sanitation projects in the construction industry.

To achieve the study's aim, the methodology for identifying the PFs for ISSPs involved several steps: extensive literature review, interviews with Egyptian industry experts, a questionnaire survey targeting industry practitioners and an analysis using the Relative Importance Index (RII), Pareto principle and analytic network process (ANP). The RII ranked factor importance,  and Pareto identified the top 20% for ANP, which determined connections and interdependencies among these factors.

The literature review identified 36 PFs, and an additional 13 were uncovered during interviews. The highest-ranked PF is PF5, while PF19 is the lowest-ranked. Pareto principle selected 11 PFs, representing the top 20% of factors. The ANP model produced an application for measuring ISSP effectiveness, validated through two case studies. Application results were 92.25% and 91.48%, compared to actual results of 95.77% and 97.37%, indicating its effectiveness and accuracy, respectively.

This study addresses a significant knowledge gap by identifying the critical PFs that influence ISSPs within the construction industry. Subsequently, it constructs a novel performance model, resulting in the development of a practical computer application aimed at measuring and evaluating the performance of these projects.

It is widely known that fast-fashion retailers are struggling to keep up with consumer attention for quick responses within the fashion industry. With the advance of Internet and e-commerce, consumers prefer to purchase online. Online platform information has become an essential source for exploring consumer attention. However, there is often a mismatch between the information provided by retailers and the feedback received from consumers, leading to an imbalance between the supply side and demand side of online information. The purpose of this study is therefore to provide a unified approach to discover consumer attention from the design topic aspect by revealing the information imbalance between supply side and demand side.

To address the issue of online information imbalance and discover consumer attention, this study proposed an approach that focuses on the design topic perspective. The design topic is a collection of design elements that represent a clothing-design feature more comprehensively and accurately compared to a single design element. The proposed approach begins with generating design topics through topic modeling based on online information provided by retailers on e-commerce platforms. Two indicators, influence degree and attention degree, are then used to quantify the intensity of supply information and consumer attention related to design topics. Finally, design topic strategy diagrams are constructed to reveal information imbalance and discover consumer attention.

The experimental case demonstrates the existence of information imbalance, indicating that the intensity of supply information and consumer attention from the perspective of design topics is not uniform, although both follow the Pareto principle. The results of consumer attention distribution with heavy power-law tails are consistent with current research findings. This further demonstrates that the proposed approach is capable of discovering consumer attention in the design topic strategy diagrams.

The issue of information imbalance between retailers and consumers poses a challenge in keeping up with customer attention. The proposed approach offers a practical solution by visually identifying the symptoms of information imbalance and discovering consumer attention through design topic strategy diagrams. This approach provides fast-fashion retailers with a valuable reference to seize market opportunities, improve product design and adjust marketing or management strategies.

This study proposes a novel approach to disclose the issue of information imbalance between supply side and demand side and therefore to discover consumer attention from the perspective of design topics. In addition, guidelines for applying the proposed approach for fast-fashion marketing and management are presented.

The rise of the metaverse has brought profound changes to the economic and social operation models and injected new vitality into academic research. Although a large number of studies have emerged, there are few quantitative analyses of development frontiers and trends.

From a bibliometric perspective, this paper selects 183 pieces of metaverse-related literature in the WoS core database since 2000 as the object of analysis. This paper sums up the characteristics of the literature using the methods of descriptive statistical analysis, keywords analysis, thematic evolution analysis and summarizes the core themes and the laws of metaverse development in each stage.

The digital economy vision brought by the metaverse has led to an increasing number of researchers and achievements in this field. But the depth and breadth of research are still insufficient and unevenly distributed in the region, and the cross-fertilization fields need to be expanded. From the industry's point of view, VR games represented by Second Life and My World have contributed to the popularity of the metaverse. As technology progresses, the research hotspots in the field of metaverse gradually develop from conceptual research to artificial intelligence, blockchain, NFT and other technical applications. However, academic research has not yet caught up with the industry's pace and stays more in the concept discussion and preliminary application stage.

A systematic overview of the current status, knowledge structure and hot issues of metaverse research is shown, which provides a thematic axis for this field, enriches and improves the quantitative analysis of its literature and provides a clear picture for researchers to continuously promote the development of this field. At the same time, it is necessary to warn that technological development is a double-edged sword. The process of metaverse development should return to rationality, respect the laws of its development and guarantee the healthy development of the metaverse by strengthening legal regulation and the ethical review of science and technology.

Automation of detecting cracked surfaces on buildings or in any industrially manufactured products is emerging nowadays. Detection of the cracked surface is a challenging task for inspectors. Image-based automatic inspection of cracks can be very effective when compared to human eye inspection. With the advancement in deep learning techniques, by utilizing these methods the authors can create automation of work in a particular sector of various industries.

In this study, an upgraded convolutional neural network-based crack detection method has been proposed. The dataset consists of 3,886 images which include cracked and non-cracked images. Further, these data have been split into training and validation data. To inspect the cracks more accurately, data augmentation was performed on the dataset, and regularization techniques have been utilized to reduce the overfitting problems. In this work, VGG19, Xception and Inception V3, along with Resnet50 V2 CNN architectures to train the data.

A comparison between the trained models has been performed and from the obtained results, Xception performs better than other algorithms with 99.54% test accuracy. The results show detecting cracked regions and firm non-cracked regions is very efficient by the Xception algorithm.

The proposed method can be way better back to an automatic inspection of cracks in buildings with different design patterns such as decorated historical monuments.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

This paper aims to explore key management actions for implementing security on the cloud, which is a critical issue as many organizations are moving business processes and data on it. The cloud is a flexible, low cost and highly available technology, but it comes with increased complexity in maintaining the cloud consumer’s security. In this research, a model was built to assist strategic decision-makers in choosing from a diverse range of actions that can be taken to manage cloud security.

Published research from 2010 to 2022 was reviewed to identify alternatives to management actions pertaining to cloud security. Analytical hierarchical process (AHP) was applied to rate the most important action(s). For this, the alternatives, along with selection criteria, were summarized through thematic analysis. To gauge the relative importance of the alternatives, a questionnaire was distributed among cloud security practitioners to poll their opinion. AHP was then applied to the aggregated survey responses.

It was found that the respondents gave the highest importance to aligning information security with business needs. Building a cloud-specific risk management framework was rated second, while the actions: enforce and monitor contractual obligations, and update organizational structure, were rated third and fourth, respectively.

The research takes a general view without catering to specialized industry-based scenarios.

This paper highlights the role of management actions when implementing cloud security. It presents an AHP-based multi-criteria decision-making model that can be used by strategic decision-makers in selecting the optimum mode of action. Finally, the criteria used in the AHP model highlight how each alternative contributes to cloud security.

This paper analyzes the advance selling and pricing strategies of fresh products supply chain where the e-retailer provides wholesale contract or agency contract to the fresh products supplier.

This paper constructed a two-period sequential-move game of fresh products supply chain members.

This analysis showed that the supply chain members had different preferences for contracts under different market conditions. The advance selling of fresh products was not a decision of the seller, but also required the support of other supply chain members. And the advance selling strategy was not always beneficial to all supply chain parties. Under the two contracts, there were market conditions in which the profits of supply chain members were Pareto-improved through the implementation of advance selling.

The model presented in this study focuses solely on the context of monopoly, overlooking the competition from alternative suppliers or retailers. Consequently, exploring the competitive landscape within the fresh products supply chain, particularly in relation to pre-sale pricing, emerges as a crucial avenue for further investigation. By employing empirical research methods, valuable insights are gleaned, thereby significantly augmenting the existing body of relevant theories.

The decision to pre-sell fresh products should be based on market conditions. Supply chain members can control production costs and fresh products circulation losses to maximize profits.

From the perspective of game theory, this study analyzed the optimal advance selling and pricing strategies of fresh products supply chain members under two kinds of contracts. These results can provide practical implications for fresh products suppliers and e-retailers.

The author identifies the traits of consumer resilience in emerging markets, classifies these major traits into five categories and analyses the influence relationships among them with distinctive focus on the psychological and personal resilience aspects.

The influence relations among the traits of consumer resilience from an expert perspective were identified with typical focus on electronic supply chains, and later the same was analysed through an intelligent influence modelling method, the grey causal modelling (GCM).

The major traits were analysed using the GCM, where the cause–consequence relations were observed for various objectives and the situational effects are noted. By constructing a magnitude plot and further a causal magnitude table, the important influence traits of consumer resilience for the considered case were observed and the same were auxiliary validated using an interpretive structural modelling (ISM) based approach.

As perceived from the results, it is evident that social support and recommendations from customers emerge as the principal influence traits of consumer resilience from an expert perspective, considering the case. The study can be further extended empirically to validate the findings.

Altogether, the author can recommend for practitioners that the influence of family, society, friends, peers as well as ratings from the customers can determine the level of consumer resilience. Hence, practitioners of customer relationship management can focus on improving the product and brand awareness among customers, so that more customers may recommend for typical products.

Consumer resilience depend on several factors, where the author has identified 25 major traits of the same and classified them into five major categories, including individual psychological factors, individual attitudes, individual socio demographic factors, micro environmental factors and macro environmental factors and the influence relations among them were studied from an expert perspective.

The purpose of this study is to examine the impact of political relations on trade in strategic emerging industries (SEIs) in the Belt and Road initiative (BRI) associated countries. This investigation encompasses not only from the perspective of bilateral political relations but also the political intervention of third parties.

The study employs the temporal exponential random graphmodel to analyze the dynamic structure and influencing factor of SEIs trade network among 150 BRI-associated countries from 2015 to 2020.

The results indicate that the trade of SEIs in the BRI-associated countries exhibits a pattern of concentrated exporters and decentralized importers. Amicable bilateral political relations foster trade cooperations in SEIs, while political pressure from the United States has the opposite effect. Furthermore, compared with the influence of third parties, the BRI has created a more robust trade environment characterized by political mutual trust.

BRI-associated countries should strengthen their political communication, and endeavor to transform political consensus and shared vision into concrete collaborative projects, while mitigating geopolitical uncertainties through a sound risk evaluation system. Moreover, they should establish a more transparent and consistent consultation mechanism and leverage the BRI trade network to foster balanced and mutually beneficial partnerships that minimize rivalry and dependence on a single market.

This study goes beyond observed trade cost and incorporates the political factor into the determinants of the BRI trade, thereby expanding the theoretical boundaries of existing BRI research. Also, this study employs bilateral trade data to construct SEIs trade networks (SEITNs) along the BRI route. It provides a comprehensive understanding of the dynamic determinates of the SEITNs will provide valuable practical guidance for enhancing and expanding trade and cooperation among BRI-associated countries.

Unplanned urban mobility causes negative effects on the population and the environment. This study aims to understand how higher education institutions (HEIs) are managing the transportation issues related to their activities and how they are implementing actions towards more sustainable practices in this regard.

A systematic review and bibliometric analysis were performed using the Proknow-C method, and the bibliographic portfolio was evaluated to answer guiding questions about distribution of articles over the years and around the world, the most relevant and frequent topics, the travel behavior of university life and the main methodologies used. The meta-analysis was modeled using a programming language in R to execute Bibliometrix package.

Sharing systems, active transport, public transport, urban planning, car parking management and travel behavior are the most relevant topics related to sustainable mobility in HEIs. Different strategies to reduce car use are adopted, and the geographic location of the university and the availability of housing and shopping services in close proximity directly influence travel patterns. As a result, seven guidelines and strategic actions associated were proposed to promote the engagement of institutions in the development of sustainable transport and guide future studies about new solutions to promote sustainable university commutes.

This paper presents a new perspective by performing a critical literature review based on the experiences reported by several isolated studies on the subject. Initiatives of sustainable transport guidelines can be used by academics, urban planners, higher education administrators and other stakeholders to make universities more environmentally friendly, inclusive and accessible.