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The current study focuses on many risk categories that have emerged in the digital ecosystem of the financial technology industry, which has dramatically changed traditional financial systems as a result of innovations in financial technology.

The Web of Science Core Collection database was used to find a data set of 719 pertinent papers on the subject encompassing the year 2015–2023. The sample procedure was carried out utilising the PRISMA approach. The keywords were first gathered relating to technological risks in banking sectors and after confirming the keywords, the authors performed the search by the “topic” which covers “title” in the search bar. On February 15, 2023, the Web of Science database was searched using the terms “Cyber security risk OR data theft OR financial crimes OR financial stability risk OR operational risk OR default risk OR money laundering OR financial terrorism AND FinTech AND banking sector”. Two-step approach is applied in this study. First, descriptive analysis is applied using RStudio to highlight prominent authors, countries and affiliations. Furthermore, relationship among authors, countries and keywords is shown by using three fields plot. Second, using VOSviewer, co-occurrence of keyword analysis is used to determine the most influential themes.

The findings show that 2,611 documents have been published from 2016 to 2023. Year 2021 is the most productive year in terms of number of publications. The results also show that WANG XC is tied for the position of most prolific contributing author. In a similar vein, the United States leads the world in publication output. Furthermore, Southwestern University of Finance and Economics in China is leading the list with 15 articles. The results from the co-occurrence of keywords reveal that “default risk”, “operational risk”, “money laundering”, “credit risk”, “corporate governance”, “systematic risk”, “financial stability risk”, “risk management” and “crises” are the frequently keywords.

The results of this study are beneficial to academia and industry in order to advance their current understanding of FinTech and associated concerns. This work expands the understanding of the technology hazards facing the banking industry from a broad perspective.

The purpose of this study is to analyze and map the terrain of human resource management (HRM) in higher education (HE) contexts, with the aim of uncovering potential gaps within the existing knowledge base.

This study employs a unique, in-depth bibliometric analysis of 945 publications from the Web of Science database over the past 40 years between 1981 and 2022.

Based on the bibliometric analysis, the authors retrospectively examined the dominant research themes in HRM within the HE sphere, tracing their evolution over time. Four central clusters emerged: the theoretical foundations of HRM, strategic HRM, organizational culture and human capital development. Furthermore, the authors pinpointed critical research gaps and proposed areas for future inquiry, such as the impact of HRM on productivity, leadership dynamics, sustainable growth development, international staffing strategies and knowledge transfer mechanisms.

This study demonstrates how academics can use bibliometric techniques to systemize literature, expose potential gaps and suggest fruitful lines of inquiry in the field of investigation. The findings of this study can also help improve the decision-making processes of managers and human resource professionals.

This study provides readers with a systematic understanding of the development of HRM in HE settings and presents forward-looking perspectives, highlighting future research possibilities. Moreover, it validates the significance of bibliometric analysis as an efficient technique for discovering gaps in the existing literature.

The countryside population has always been depended on the revenues earned from agricultural yields. These yields often suffer losses in the absence of coordination guidelines in the post-yield supply chains (PYSC). This study aims to identify, address and mitigate the post-yield supply chain impediments (PYSCIs) that lead to enormous amounts of waste and revenue losses. These are the parameters that require government and stakeholders’ attention for alleviation from losses.

Structural equation modelling (SEM) was performed to categorise the identified PYSCIs as “standard measures”. The motive for SEM results is to attract the stakeholders’ attention toward PYSCIs for business sustainability. The PYSCIs were clustered into three “standard measures” (i.e. strategic, tactical and operational measures) for revenue generation and reduced fresh produce spoilage in the countryside.

The SEM results suggest that the focus should be on revising minimum support prices and government support for initiatives, subsidy schemes and incentives at the strategic level. Tactical initiatives focus on linking markets including exports, research and development, attitude towards certification, value addition process adoption and reduced number of stages in the supply chain. The operational initiatives are attitudes towards agriculture and entrepreneurship, transportation infrastructure, supply chain coordination, information visibility, scientific design for packaging and handling and storage space availability for both long and short term at the village level.

This study was performed in India; thus, the research outcomes of this study are restricted to adaption into the developing sub-continents with sub-tropical climates.

The existing level of losses in the PYSC demands introspection and policy changes at the farm level. In the era of cold chains, the Internet of Things, and other advanced mechanisms, a few elementary parameters must be worked upon to reduce PYSC losses. These parameters were identified as impediments to PYSC, requiring public, government and stakeholders’ attention. There is an urgent need for guidelines to be issued to mitigate losses. SEM was performed to attract the public, government and stakeholders’ attention toward impediments to fresh produce spoilage, opportunity generation and business sustainability.

This study uses a novel SEM approach where the PYSCIs were identified and empirically validated in an Indian context. The SEM approach will help in effective decision-making. Similar studies to manage the PYSCIs to reduce fresh produce spoilage with standard measures have not been reported in the literature.

The purpose of this study is to explore multiple stakeholders managing the different type of knowledge in a flood-prone area. Different stakeholders hold different types of knowledge in their area of interest, and both knowledge streams have their intrinsic potentials and limitations. In this paper, the issue of knowledge complementarity is explored in the context of flood hazards. Hazards such as floods may appear messy, unpredictable, with unsorted and unorganised forms of data, information and knowledge on the part of diverse stakeholders.

Case study design had been used in this study to explore how stakeholders: Orang Asli, Malay, and humanitarian organisations manage the differences in terms of type of knowledge each of them have. To illicit the response from participants from each of the stakeholders, in-depth interviews had been used.

This research has led to the development of a conceptual framework based on the case study. The lessons learned from the framework is discussed, together with the barriers to their implementation.

This paper presents a research case study on multiple stakeholders in the district of Pekan, the state of Pahang, Malaysia, and how these multiple stakeholders manage flood hazards with their different types of knowledge.

The purpose of this study was conducted at an enterprise that produces fasteners and is one of the leading companies in the sector in terms of market share. Possible defects in the coating of bolts and nuts either lead to products being scrapped or all of the coating process being repeated from beginning to end. In both cases, the enterprise faces a waste of time and excessive costs. Through this project, the six sigma theory and its means were effectively used to improve the efficiency and quality management of the company. The selection of the six sigma project has also contributed to the creation of various documents to be used for project screening and evaluation of financial results.

Six sigma is an optimization strategy that is used to improve the profitability of businesses, avoid waste, scrap and losses, reduce costs and improve the effectiveness of all activities to meet or exceed customers’ needs and expectations. Six sigma’s process improvement model, known as Definition-Measurement-Analysis-Improvement-Control, contributes to the economic and technical achievements of businesses. The normal distribution of a process should be within ±3 sigma of the mean. This represents a scale of 99.7% certainty. However, improving the process through the utilization of the six sigma rule, which accepts normal variabilities of processes twice as strict, will result in an error rate of 3.4 per million instead of 2,700 per million for each product or service.

Using six sigma practices to reduce the costs associated with low quality and to increase economic added value became a cultural practice. With this, the continuation of six sigma practices throughout the Company was intended. The annual cost reduction achieved with the utilization of six sigma practices can be up to $21,780. When time savings are also considered, a loss reduction of about $30,000 each year can be achieved. The coating thickness efficiency increased from 85% to 95% after the improvements made through the six sigma project. There is a significant increase in the efficiency of coating thickness. In addition, the coating thickness efficiency is also close to the target value of 95%–97%.

The results of the study were optimized with the help of deep learning. The performance of the model created in deep learning was quite close to the actual performance. This result implicates the validity of the improvement work. The results may act as a guide for the use of deep learning in new projects.

The pupose of this study is to systematically review the current literature on the value stream mapping (VSM) application in the construction industry to investigate the evolution observed over time and the results obtained by adopting this tool. In addition, special attention was given to the potential of VSM in identifying loss and waste, as well as their main causes.

The study analyses papers in literature using Preferred Reporting Items for Systematic Reviews and Meta-Analyses research protocol. As a result, 383 papers were initially identified, and 47 papers were selected.

It was observed that the number of studies addressing this topic has been increasing over the past decade and findings related to the evolution, application and the benefits obtained from the VSM application in context of construction were presented. Additionally, the authors found that the two most cited lean wastes were waiting and defects in the production chain. The main causes of this waste and loss were also identified in this work.

This paper contributes by presenting the applicability of VSM as a tool in the construction as found in the literature. For academics, it will be possible to clearly observe research gaps and for industry managers, to identify the main sources of waste and assess the performance of the tool’s application.

The study uses a systematic review to analyze the application of the VSM tool in the construction industry and provides guidance for future research by identifying research gaps, in addition to conducting an extensive analysis of the tool’s potential in waste identification in the studied papers and their primary causes.

The scientific community shares a heritage of knowledge generated by several different fields of research. Identifying how scientific interest evolves is relevant for recording and understanding research trends and society’s demands.

This article presents SciBR-M, a novel method to identify scientific interest evolution from bibliographic material based on Formal Concept Analysis. The SciBR-M aims to describe the thematic evolution surrounding a field of research. The method begins by hierarchically organising sub-domains within the field of study to identify the themes that are more relevant. After this organisation, we apply a temporal analysis that extracts implication rules with minimal premises and a single conclusion, which are helpful to observe the evolution of scientific interest in a specific field of study. To analyse the results, we consider support, confidence, and lift metrics to evaluate the extracted implications.

The authors applied the SciBR-M method for the Educational Data Mining (EDM) field considering 23 years since the first publications. In the digital libraries context, SciBR-M allows the integration of the academy, education, and cultural memory, in relation to a study domain.

Cultural changes lead to the production of new knowledge and to the evolution of scientific interest. This knowledge is part of the scientific heritage of society and should be transmitted in a structured and organised form to future generations of scientists and the general public.

The method, based on Formal Concept Analysis, identifies the evolution of scientific interest to a field of study. SciBR-M hierarchically organises bibliographic material to different time periods and explores this hierarchy from proper implication rules. These rules permit identifying recurring themes, i.e. themes subset that received more attention from the scientific community during a specific period. Analysing these rules, it is possible to identify the temporal evolution of scientific interest in the field of study. This evolution is observed by the emergence, increase or decrease of interest in topics in the domain. The SciBR-M method can be used to register and analyse the scientific, cultural heritage of a field of study. In addition, the authors can use the method to stimulate the process of creating knowledge and innovation and encouraging the emergence of new research.

This study developed two presentation modes of scientific articles and evaluated their usability with user experiments.

Two presentation modes of scientific articles, simply referred to as “genre presentation mode” and “argument presentation mode”, were constructed based on their genre structure and argument structure respectively. Their usability was evaluated by being compared against the existing RichHTML presentation mode in the experiments using eye-tracking and questionnaire methods.

The participants who were going to find the specific information of scientific articles rated the genre presentation mode higher than they did with either the argument or the RichHTML presentation mode for effectiveness. In contrast, those who were going to understand the general idea of scientific articles rated both the genre and argument presentation mode higher than they did with the RichHTML mode. In terms of efficiency, the participants took less reading time when the articles of non-native language were presented with the genre mode than they did when the articles were presented with the argument mode. When reading the articles in native language to understand the general idea, the participants took less reading time for the articles presented with the argument mode than they did for the articles presented with the genre mode. In comparison, they took less reading time when the articles were presented with the argument mode if they were going to find specific information. For satisfaction, the genre presentation mode was more popular than the argument mode and the RichHTML mode. However, the participants were less satisfied with the argument presentation mode than the other two when reading in native language and intending to find specific information.

The two presentation modes of scientific articles are found to improve the accuracy of information acquisition, shorten the total reading time and be more acceptable by readers.

This paper improves the evaluation index system of green building operation effect and establishes the evaluation model of green building operation effect. It is expected to promote energy saving and emission reduction and provide a more scientific evaluation method for green building operation effect evaluation.

First, 20 key evaluation indexes are selected to establish the operation effective evaluation index system. Then, the combined weight method is proposed to determine the weight of each evaluation index. Next, the gray clustering-fuzzy comprehensive evaluation method is used to construct the green building operation effective evaluation model. Finally, the feasibility and validity of the selected model were verified by taking Shenzhen Bay One green building in Shenzhen as an example.

This paper establishes the evaluation system of green building operational effect, and evaluates green building from the angle of operational effect. Taking Shenzhen Bay One project as an example, the rationality and applicability of the model are verified.

In this paper, for the first time, relevant indexes of user experience are included in the evaluation system of green building operational effect, which makes the evaluation system more perfect. In addition, a more scientific fuzzy gray clustering method is used to evaluate the operational effect of green building, and a new evaluation model is established.

The purpose of this research is to determine the competitive advantages of higher education institutions (HEIs) and create a new methodology to rank universities according to the competitive advantages.

The research determines the competitive advantages of HEIs by analysing expert opinions through a semi-structured interview form, matches codes and themes to performance indicators using Saldana's two-cycle coding methods, evaluates content validity through Lawshe and reveals the item weights of the ranking with analytical hierarchy process (AHP). Simple additive weighting (SAW) and Technique for Order of Preference by Similarity (TOPSIS) methods were used for ranking universities.

Seven dimensions stand out in regard to what should be considered while ranking HEIs: research and publication, education, management, infrastructure, financial resources, human resources and social and economic contribution. Under the 7 dimensions, 69 indicators were determined.

The research provides a scientific reference point where HEIs can compare themselves with other HEIs regarding where they are in the sector, especially in terms of competitive advantages.

Although there are many different ranking methods that rank universities in the national and international literature, almost all these methods are largely based on the outputs of the university such as the number of publications, the number of patents, the number of projects, etc. A framework which ranks universities by considering different aspects of the institution, such as management, human resources and financial resources, has not been developed yet. In this respect, this research aims to fill this gap in the literature.