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This research has the potential to contribute to the understanding of the sustainable ground handling operations framework. Ramp operations as the main system of ground handling include critical services for aircraft/airlines. The purpose of this study is to identify the risk factors in ramp operations for all related stakeholders’ awareness to enhance flight safety. Classifying risk factors, the four main performance fields under risk taxonomy is determined. Thus, managers may allocate resources effectively to handle related threats for corporate sustainability.

New taxonomy with human performance value indicators, which sources from the environment is developed. New developed taxonomy is entitled as “environmental value approach,” which represents environmental value-based approach. The developed new risk factors taxonomy is divided into groups such as ramp personnel, organizational, sustainability-based risk factors: triple view and ergonomics obtained from an extensive literature review and experts’ opinions in the field of human performance.

The findings of this research show that managers need a risk management-oriented approach to manage the human factor affecting performance and sustainability. The newly developed taxonomy offers not only identifying the sources of unsafe operational risk factors but also using as a decision-support tool to manage risks for achieving their sustainability goals. When managerial decisions are made according to risk taxonomy and managing these risks, then corporate performance and individual performance may improve.

The new taxonomy presents the performance-based management of the human factor with a holistic and systematic risk management-based approach. There is no risk taxonomy study designed considering ramp operations and sustainability-based human factor performance.

The purpose of this paper is to systematically develop a delay risk terminology and taxonomy. This research also explores two external and internal dimensions of the taxonomy to determine how much the taxonomy as a whole or combinations of its elements are generalisable.

Using mixed methods research, this systematic literature review incorporated data from 46 articles to establish delay risk terminology and taxonomy. Qualitative data of the top 10 delay risks identified in each article were coded based on the grounded theory and constant comparative analysis using a three-stage coding approach. Word frequency analysis and cross-tabulation were used to develop the terminology and taxonomy. Association rules within the taxonomy were also explored to define risk paths and to unmask associations among the risks.

In total, 26 delay risks were identified and grouped into ten categories to form the risk breakdown structure. The universal delay risks and other delay risks that are more or less depending on the project location were determined. Also, it is realized that delays connected to equipment, sub-contractors and design drawings are highly connected to project planning, finance and owner slow decision making, respectively.

The established terminology and taxonomy may be used in manual or automated risk management systems as a baseline for delay risk identification, management and communication. In addition, the association rules assist the risk management process by enabling mitigation of a combination of risks together.

The purpose of this paper is to identify the technological risks in the context of open source software (OSS) and suggest an integrative OSS risk taxonomy.

The authors conducted an extensive literature review followed by expert interviews and applied the method for taxonomy development.

This research has identified an integrative OSS risk taxonomy composed of 8 categories with 51 risk items.

This taxonomy is a very useful tool for practitioners during the decision-making process when evaluating, assessing and calculating risks related to OSS adoption. Moreover, researchers can use it as a starting point for future studies to better understand the OSS phenomenon.

In this study, research problem has been designed as a fleet-based optimization problem. This paper aims to present fleet modelling with risk taxonomy. Fleet modelling has been assumed as strategic multi-criteria decision-making problem to capacity building. Capacity building risk management is an essential element within the scope of its strategy to ensure sustainable corporate performance. Optimization is a fundamental target in aviation business’ strategy and management since the manager make decisions in their multi-interrelated criteria environment. Also, aviation is a highly regulated sector, and its operational and business procedures have certain limits by both national and international authorities. For this reason, companies implement risk management for strategic optimization while performing operations in compliance with the legislation. Risk management with capacity building and resource dependency perspective applied for strategic optimization aims to capture opportunities and result in threats with minimum accidents and incidents.

The taxonomy and analytical hierarchy process (AHP) have been identified as methodologies in this research. The type of training in the high organizational performance of an approved training organization, strategy, resources and allocations with the corporate objectives, the amount and qualifications of the flight crew, their professionalism, maintenance team and licenses, hangar conditions and capacity, authority requirements and limits, region conditions, altitude and meteorology, student profile, together with a multi-criteria decision are to be considered. For each criterion, there are resources and thus resource dependence. In this study, the analytical network process method was used. In the construction of new taxonomy, specific criteria have been considered, and the analysis has been accomplished as multi-criteria decision-making problem because of the relationship and interaction between them. A number of professionals with high knowledge of the pilots and manager from Air Traffic Organization participated in the study.

The fleet modelling is both strategic and operational decision issue for training organizations. In this issue, there is a vital problem as which aircrafts should include fleet? Main criteria and sub-criteria are analyzed by AHP method and sorted according to their priorities and the fleet qualifications consisting of the most suitable aircraft/aircraft are presented. The finding and suggestions will contribute to establish sustainable organization in based on capacity building and resource dependency for managers. While analyzing main criteria, the important criteria which were found were strategic and then operational. After ordering main criteria, sub-criteria were analyzed and were multiplicated with their items. According to study findings, aircraft suitability for training model is the most important item. It follows respectively aircraft maintenance sustainability, cost of aircraft supply and faculty budget adequacy. However, operation characteristics of the square that is less important item was found. It was seen that the strategies used to manage dependencies used the bridge strategy. The results we obtained with the interviews with pilot managers are very significant in terms of resource dependence on the subject of fleet optimization. While first criterion is operational, it continues with strategic and financial criteria. After interviews with pilot managers, it was figured out that maintenance is also very important criteria. For managing this dependency, university has acquisitions, which is one of the strategy to manage dependency, rather than outsourcing. For this reason, maintenance criterion has lower importance than others. When thinking of other criteria, strategic and financial criteria have played an important role. University has tried to decrease dependency and increase sustainability.

Aircraft selection is a strategic decision of fleet modelling in both aviation business and also training organizations via influencing their corporate performance, operational performance, capacity building and their sustainability. There are some factors that limit the criteria, as research problem has been developed for approved training organizations not airlines. For this reason, our research is limited with fleet of training organizations. Our findings and suggestions may be useful for flight schools to managing their resource dependency and also to their capacity building. In this research, new taxonomy has been developed depending on training organizations’ qualifications. Airlines may improve this taxonomy to use in their decision-making process.

The fleets, which were established considering the taxonomy in this study, will be able to manage the risk of resource dependency more successfully. Pilot candidates will be able to provide a more ergonomic and higher quality education. This research and its findings will contribute to the development of organizations’ accurate and timely decision-making skills. Resource dependency may threat organizational sustainability in our research, New taxonomy and our holistic approach will support organizational efforts to achieve sustainable strategies.

New taxonomy to modelling fleet that has been developed in this research may provide contribution to approved training organizations for both managing resource dependency-based risks and to capacity building-related decision-making process. This research may serve organizations as strategic decision-making tool. And also this kind of study may contribute to improve sustainability of organizations and serve more good fleet for their pilot candidates. For these reasons, this research may create social implications, as both resource using and capacity building will make contribution for society and add value.

This research presents new risk taxonomy and criteria. Also new taxonomy and its criteria are analysed with AHP. It is thought that this research shows risk management-based approach for fleet modelling creates benefits for approved training organizations to using their limited sources effectively and efficiently. The article includes risk management and capacity building-related approach to decision-making. also, this research presents modeling which will contribute to the management field besides literature. In developing taxonomy process, the analysis has been conducted, based on expert opinions and referred to for these pairwise comparisons. Airlines managers and risk managers may examine their fleet modelling according to our taxonomy which is based on risk management.

Contemporary management and strategy mean optimization of ingredient factors such as human factors, systems, operations and equipment. With system approach in management and strategy, human risk factor as input has considerable potential to change results as airworthiness in aviation management. The managers of aviation business also optimize their functions to act safe while making contribution to development in triple of sustainability as economic development and its sustainability; social development and its sustainability; and environmental development and its sustainability. Corporate sustainability can be accomplished via supporting workforce which is the human risk factor. To support (empowerment) workforce, researchers should identify human risk or error factors which are important to this research. The purpose of this study is to suggest holistic framework for working environment system of aircraft maintenance technicians (AMTs) within two respects such as human performance (ergonomics) and corporate performance (sustainability). The secondary purpose of this system is to develop human risk taxonomy by determining the factors affecting both human and work by taking ergonomic aspects in aviation.

In this study, a taxonomy of human risk factors for AMTs is developed. These human factors divided into groups and subfactors are obtained from an extensive literature review and experts’ opinions in the field of human performance in aviation. Taxonomy developed will be useful to both sharing and using corporate sources in sustainable way.

Human risk factors can be considered or accepted as factors that cause human error. This may result in the optimum way to managing human risk factor via minimizing human-based error. Personality, hazardous attitudes, individual characteristics, physical/psychological condition of AMTs and corporate social responsibility factors are human-related risk variables in this study. The risks and error can be reduced by recognizing these factors and revealing their relation to ergonomic design.

The results of this study are intended to constitute a guide for managers to manage risk factors and to take corrective and preventive actions for their maintenance operations. It is believed that this study is highly important for the aviation sector in terms of raising awareness or providing awareness for similar practices. As taxonomy of the risk factors contributes to the managing human error, corrective actions related to these factors must be taken by managers.

Identifying and prioritizing the risks are considered as critical issues in risk management; otherwise, non-considering the risks will lead to the problems such as delays in project implementation, increased costs, loss of reputation, loss of clients, reduced revenue and liquidity and even bankruptcy. The paper aims to discuss these issues.

In this paper, the factors influencing the organization risk tolerance level were identified. Then, the factors increasing and decreasing the risk tolerance level were determined by a decision-making model. Finally, a comprehensive model was considered for risk measuring and preparing a risk failure structure chart, in order to determine the factors influencing it as well as the measurement criteria and then they were ranked using the taxonomy method. In this study, the size of the statistical population was 130 (six small and medium manufacturer and service provider companies). Based on Cochran’s sample size formula, 97 questionnaires containing 30 questions were randomly distributed among the population. Validity and reliability of the questionnaire were confirmed. The data were analyzed by SPSS 22.

Given the hypotheses of this study, the first hypothesis was rejected and the other hypotheses were accepted. The final ranking was done using the taxonomy method; the personality of the project manager was ranked at first; income, credit and capital were ranked second and the number of personnel was ranked third. Moreover, the TOPSIS method was used for ranking to compare the results.

In this research, the identification and ranking of these factors have taken place in several small- and medium-sized organizations; in addition, the rankings are conducted using the taxonomy decision-making method.

Globally expanding supply chains (SCs) have grown in complexity increasing the nature and magnitude of risks companies are exposed to. Effective methods to identify, model and analyze these risks are needed. Risk events often influence each other and rarely act independently. The SC risk management practices currently used are mostly qualitative in nature and are unable to fully capture this interdependent influence of risks. The purpose of this paper is to present a methodology and tool developed for multi-tier SC risk modeling and analysis.

SC risk taxonomy is developed to identify and document all potential risks in SCs and a risk network map that captures the interdependencies between risks is presented. A Bayesian Theory-based approach, that is capable of analyzing the conditional relationships between events, is used to develop the methodology to assess the influence of risks on SC performance

Application of the methodology to an industry case study for validation reveals the usefulness of the Bayesian Theory-based approach and the tool developed. Back propagation to identify root causes and sensitivity of risk events in multi-tier SCs is discussed.

SC risk management has grown in significance over the past decade. However, the methods used to model and analyze these risks by practitioners is still limited to basic qualitative approaches that cannot account for the interdependent effect of risk events. The method presented in this paper and the tool developed demonstrates the potential of using Bayesian Belief Networks to comprehensively model and study the effects or SC risks. The taxonomy presented will also be very useful for managers as a reference guide to begin risk identification.

The taxonomy developed presents a comprehensive compilation of SC risks at organizational, industry, and external levels. A generic, customizable software tool developed to apply the Bayesian approach permits capturing risks and the influence of their interdependence to quantitatively model and analyze SC risks, which is lacking.

Large-scale projects are the typical delivery model in the engineering and construction industry, with their very own characteristics. Even though well established, only 1 in 1,000 large-scale projects is successful (Flyvbjerg, 2011). A lack of effective supply chain risk management (SCRM) has repeatedly been identified as one of the main causes. While the SCRM body of knowledge seems increasingly well established, a lack of effective methods meeting the specific requirements of large-scale projects can be observed.

This paper presents a structured and prioritized view on the supply chain risk portfolio in this sector: first, the authors identified and categorized the key supply chain risks in the recent literature. Next, the authors surveyed large-scale project managers across multiple industries, mainly coming from the domains of supply chain management and project management. Finally, the authors provide a contextualized risk taxonomy for engineering, procurement and construction (EPC) projects.

The identified risk portfolio deviates from generic projects significantly and shows a very high inherent risk exposure of large-scale projects. In particular, behavioral risks are identified as crucial. Additionally, a bias to considerably underestimate risks at project beginning is found.

The contextualized SCRM taxonomy offers a systematic and structured view on the key supply chain risks in EPC large-scale projects. The identified risks are considerably different in their characteristics compared to generic projects or classical SCRM approaches. The authors thus provide a new perspective on SCRM in this specific setting and complement traditional risk and project risk management techniques.

A large number of organisations are moving towards adopting Industry 4.0 (I4.0), and simultaneously, the emphasis on attaining sustainability development goals is also increasing. Hence, it is imperative to understand the interplay between I4.0 and sustainability. However, the literature addressing the same is still in infancy. Accordingly, the purpose of this study is to fill this gap in the literature by exploring the potential sustainability impacts of I4.0 on the organisations and society in terms of sustainability risks.

To gain an understanding of sustainability aspects in the I4.0 context, relevant literature is gathered using Scopus and Web-of-Science database. An in-depth review of 51 research papers is performed to determine the sustainability risks associated with I4.0.

From the study, a total of 16 sustainability risks are identified, and I4.0 sustainability risk taxonomy is developed. The proposed taxonomy extends the sustainability implications of I4.0 beyond the triple bottom line umbrella and includes the organisational perspective as well. Furthermore, the study provides future research avenues to scholars by positing five potential research questions under different risk management stages.

The study provides an understanding of sustainability risks associated with the adoption of I4.0. The findings will help practitioners streamline their production and operation processes by finding out possible solution to the sustainability risks of their smart factories in advance. The present research will act as a stepping stone towards I4.0 sustainability. The proposed research questions will assist the future researchers in extending the field of I4.0.

To the best of the authors’ knowledge, this is one of the first studies to address the topic of sustainability risks in the context of I4.0.

Knowledge is a critical factor for health-care organizations’ sustainability in today’s hyperconnected and technology reliant environment, which presents additional challenges and responsibilities for managing knowledge and its risks in medical practices. This paper aims at developing a taxonomy of knowledge risks (KR) within a health-care context, with relevant descriptions and discussion of their possible impact on health-care organizations.

As KRs have not been discussed yet within a health-care context, the authors reviewed relevant literature on KRs and challenges to knowledge practices in general contexts and in other industries. In addition, the authors reviewed literature on knowledge management (KM) in health care. The authors synthesized their findings and combined it with authors’ insights based on their experience in the health-care and KM fields to develop the taxonomy of KR, with contextual explanations and expounded on their potential effects on health-care organizations.

The authors propose and explain 25 types of KRs in health-care organizations and organized them into three categories: human, operational and technology.

Proper identification of clinical and administrative KRs plays a critical role in their effective management and remediation, thus improving the quality of care, promoting efficiency savings and ensuring health-care organizations’ sustainability. This paper will raise the awareness of KR among health-care professionals and offer researchers solid ground for more rigorous research in the field of KR and their management, within the health-care context in specific.

To the best of the authors’ knowledge, this paper is the first to comprehensively discuss issues of KRs within a health-care context.