Abstract

Keywords

1. Introduction and motivation

2. What is SI?

3. Theoretical framework for SI

4. Practical framework for SI

5. Conclusions and limitations

Declaration of Competing Interest

Acknowledgements

References

Abstract

In the age of big data, intelligence, and Industry 4.0, intelligence plays an increasingly significant role in management or, more specifically, decision making; thus, it becomes a popular topic and is recognised as an important discipline. Hence, safety intelligence (SI) as a new safety concept and term was proposed. SI aims to transform raw safety data and information into meaningful and actionable information for safety management; it is considered an essential perspective for safety management in the era of Safety 4.0 (computational safety science—a new paradigm for safety science in the age of big data, intelligence, and Industry 4.0). However, thus far, no existing research provides a framework that comprehensively describes SI and guides the implementation of SI practices in organisations. To address this research gap and to provide a framework for SI and its practice in the context of safety management, based on a systematic and comprehensive explanation on SI from different perspectives, this study attempts to propose a theoretical framework for SI from a safety management perspective and then presents an SI practice model aimed at supporting safety management in organisations.

1. Introduction and motivation

Safety management is regarded as the process of realising certain safety functions (Li and Guldenmund, 2018), and it has become an important topic both in academia and in practice over the past decades (Denton, Journal Pre-proof 2 1980; Hale, 2003; Wang et al, 2017). From an organisational perspective, safety management aims to promote organisational safety and protect people and property within the organisation from unacceptable safety risks (Li and Guldenmund, 2018). Recently, with the increasing global economic uncertainties and owing to global economy in the doldrums, safety management in most organisations is under growing pressure to perform more with less. In addition, there is a constant need to find better approaches to guarantee that safety resources are allocated as effectively as possible while maintaining good organisational safety performance (Wang et al, 2017). Thus, safety information is critical to achieving these targets; it is considered as the lifeblood of organisational safety management because safety information is necessary for effective safety risk prevention and informed safety decision making (Yang, 2012; Huang et al, 2019; Wang et al, 2019).

1- Introduction

2- WL/SL properties

3- Background: CDFs for link failure time, link property value at link failure, and time at which LOAS occurs

4- CDFs for failure time margins

5- CDFs for system property values at LOAS

6- CDFs for margins based on WL and SL property values

7- CDFs for margins involving only SL property values

8- Summary discussion

References

Abstract

Representations for margins associated with loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems involving multiple time-dependent failure modes are developed. The following topics are described: (i) defining properties for WLs and SLs, (ii) background on cumulative distribution functions (CDFs) for link failure time, link property value at link failure, and time at which LOAS occurs, (iii) CDFs for failure time margins defined by (time at which SL system fails) − (time at which WL system fails), (iv) CDFs for SL system property values at LOAS, (v) CDFs for WL/SL property value margins defined by (property value at which SL system fails) − (property value at which WL system fails), and (vi) CDFs for SL property value margins defined by (property value of failing SL at time of SL system failure) − (property value of this SL at time of WL system failure). Included in this presentation is a demonstration of a verification strategy based on defining and approximating the indicated margin results with (i) procedures based on formal integral representations and associated quadrature approximations and (ii) procedures based on algorithms for sampling-based approximations.

Introduction

Representations for margins associated with loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems [1-6] involving multiple time-dependent failure modes are developed. As described in Ref. [7], the descriptor “loss of assured safety” for the performance under accident conditions (e.g., a fire) of a high consequence system with multiple WLs and SLs is used for the situation in which (i) a necessary set of SL failures places the system in a potentially operational condition before (ii) an appropriate set of WL failures places the system in an inoperable state. In contrast, safety is “assured” if (i) an appropriate set of WL failures places the system in an inoperable state before (ii) a necessary set of SL failures places the system in a potentially operational condition. Consistent with the preceding description, LOAS does not mean that the accident will progress to operation of the high consequence system; rather, it only signifies that certain conditions exist that could contribute to this progression.

1- Introduction

2- Literature review

3- An integrated maintenance model

4- An improved PSO

5- Computational experiments

6- Conclusions

References

Abstract

To decrease the over-maintenance and under-maintenance phenomenon, this paper examined the relationship between facility reliability and lifespan so as to generate the optimal maintenance plan which includes the proper combination of maintenance time and maintenance modes. An age reduction maintenance model is built to describe the deterioration situation of the port facility, and a particle swarm optimization (PSO) based integrated approach is used to solve the model. The sensitivity analysis helps to determine the maintenance mode combination from which the total maintenance cost is minimized. The result shows that taking multiple maintenance modes into account would help optimize the total maintenance cost. In addition, the obvious difference between the reliability thresholds would assist in providing discrepant maintenance service. The results have indicated that when the thresholds of different maintenance mode are overlapped, the total maintenance cost is the highest.

Introduction

In recent years, the port economy gains a prosperous development, and the life cycle of port devices are designed to be longer, making facility management a critical part among the port management stream. The environmental and economic concerns become high, among which, the facility maintenance plays an important role. Most of the port facilities are exposed to a mixed environment of the windy, sunny, salty and high load operation. Any facility is a necessary link in the port operation chain, and the interruption of any link will cause a great damage to the port operation efficiency. Every year, about 11% of operating cost is used for maintenance, and this number has been increasing at an annual rate of 4% in recent years with the increase of port throughput [7]. Furthermore, according to the report on China port development [2], around twelve percent of the port machine OEM’s revenue is coming from the maintenance activities, where the maintenance costs for crane are growing at double-digit rate annually [13]. To deal with these growing cost, an appropriate facility maintenance scheduling becomes essential both for port operators and port machine manufacturers. Normal overcapacity often characterizes port operation due to the high facility cost. This causes port facilities are always operated either far beyond or below their full capacity subjected to the resilient loading plan. Such overcapacity or under-capacity usually results from various facility type and fluctuating workload. The variable facility type results in the wear and tear at varying degrees even when they are assigned the same workload. The workload fluctuation, either due to field dynamics or demand dynamics, leads to strong fluctuation in tear mix and deterioration extent. Different types of facilities support smooth port operation, while outdoor environments intensifies serious wear and tear on the facility. A common practice is, therefore, to apply maintenance whenever possible to postpone or avoid excessive wear and tear [8]. Since maintenance recovers the reliability in some measures, their consideration has attracted increased attention with highlighted focus on reasonable maintenance mode. Various maintenance modes influence aging rates and thus impacts the next maintenance activities, such as maintenance interval, technique, and cost.

1. Introduction

2. Methodology

3. Implementation

4. Results

5. Conclusions and recommendations

Acknowledgments

Appendix A. Supplementary material

References

Abstract

Currently, there are both methodological and practical barriers that together preclude the use of theoretically sound approaches for network screening as part of a traffic safety management process. Methodological barriers include, among others, lack of a comprehensive framework for corridor-level network screening. Existing corridor screening methodologies use observed crash frequency as a performance measure. In practice, corridorlevel screening is extremely important because traffic safety engineers prefer to deploy countermeasures and provide homogenous conditions throughout corridors to meet drivers’ expectations and avoid confusion. On the other hand, practical barriers that limit the use of sound approaches for traffic safety include (1) significant data integration requirements, (2) a particular data schema is needed to enable analysis using specialized software, (3) time-consuming and intensive processes are involved, (4) substantial technical knowledge is needed, (5) visualization capabilities are limited, and (6) coordination across various data owners is required. This research proposes a systematic methodology for corridor-level network screening. The solution algorithm is implemented within a Business Intelligence (BI) platform to address, to the extent possible, the practical barriers listed above. BI provides methods and mechanisms to integrate and process data, generate advanced analytics, and visualize results by using intuitive and interactive web-based dashboards and maps. Experiments and results illustrate the advantage of using the proposed framework for corridor-level network screening implemented within a BI platform.

Introduction

Ensuring traffic safety is the focus of such federal legislation as the Transportation Equity Act for the 21st Century (TEA-21), the Safe Accountable Flexible and Efficient Transportation Equity Act – A Legacy for Users (SAFETEA-LU), and the Moving Ahead for Progress in the 21st Century (MAP-21). SAFETEA-LU and MAP-21 both require that states develop comprehensive Highway Safety Improvement Plans (HSIPs) (FHWA, 2013). One of the critical programs of HSIPs is the traffic safety management process, which involves annual reporting of the highway locations that exhibit the most severe traffic safety needs. By identifying the most hazardous roadway site locations, specific countermeasures can be implemented to improve safety conditions. In a traffic safety management process, identifying locations with the potential for safety improvements is known as network screening. Network screening is critical because a detailed engineering study for all network sites is expensive. The purpose of network screening is to review the entire roadway network, or portions, and identify and prioritize corridors and sites with potential for safety improvements. These identified corridors are recommended for further investigation and a detailed safety engineering study.

For network screening, despite the availability of approaches such as the Empirical Bayes (EB) method recommended by the Highway Safety Manual (HSM) (AASHTO, 2010) and those that deal with unobserved heterogeneity (Mannering et al., 2016; Mannering, 2018), practitioners continue using very simplistic methodologies which rely only on observed crash frequency or crash rates. For HSIP reports submitted to the Federal Highway Administration in fiscal year 2014, only four states used the EB for network screening as described in the HSM (FHWA, 2015).

This essay argues that: (1.) The concepts of both “safety” and “safety culture” are under-developed in organizational analysis. This has led to ambiguity and confusion in our understanding of the causal connection of both to specific elements of organizational structure. (2.) There is more complexity in the link between structure and safety culture as features of organization than might be supposed. The actual content of structural elements such as roles and rules, functional lines and limits of authority, accountability and communication – can themselves require closely supporting cultural norms of acceptance to actually function as formally described. Otherwise a formal organization chart can be a highly misleading picture, as they often are, of actual transactions occurring within a functioning organization. (3.) But the relationship between structure and safety culture can be different in the different phases of (1) the initial change of cultural or sub-culture features that undermine safety, (2) safety culture development and finally, (3) the challenge of the continued maintenance of a safety culture over time in an organization. (4.) Both specific safety management structures and a reinforcing safety culture are essential within an organization to reach across the scope of activities and time frames necessary for reliable safety performance. The implications of these points are explored for both future safety research and regulatory practice concerning organizational structure and safety culture and, ultimately, to connecting both to the improvement of safety performance.

In December of 2018 the California Public Utilities Commission (CPUC), the major utility regulator in the state of California issued an order to investigate the Pacific Gas and Electric Company (PG&E), one of its largest regulated utilities, to “determine whether PG&E’s organizational culture and governance are related to PG&E’s safety incidents and performance record, and if so, to what extent.” (CPUC, 2018). The underlying idea was to investigate whether restructuring the utility in both its overall corporate organization (as a single integrated investorowned utility) as well as its internal governance and corporate management structure would allow PG&E “to develop, implement, and update as necessary a safety culture of the highest order.” Structural options to be considered included breaking up the utility into separate smaller, regional entities; or separate electric and gas utilities; or even reconstituting PG&E as a publicly owned utility or utilities. Governance restructuring questions to be asked in the investiation included should the utility’s Board of Directors be accountable for safety apart from its other fiduciary responsibilities?

1. Introduction

2. Theory and hypothesis development

3. Method

4. Results

5. Discussion

6. Potential limitations and future research

7. Implications for practice

8. Conclusion

Acknowledgments

Appendix A. Supplementary material

References

Abstract

Ability to influence within organizations has been identified as a key capability for occupational health and safety (OHS) professionals. By utilising aspects of intra-organizational influence theory, this study explores the specific behaviors that OHS professionals use to influence organizational decision-makers. Survey data was collected from OHS professionals (n = 385) on proactive influence tactics used and the perceived outcomes of influencing attempts. The results show that certain individual factors (i.e. gender, age, OHS experience) and organizational factors (i.e. level of safety maturity and organisation size) impact on tactics used and influencing effectiveness. The use of influence tactics explains a significant amount of variation in OHS professionals’ effectiveness in influencing organizational decision-makers, and certain tactics (rational persuasion and inspirational appeal) were positively associated with influencing effectiveness, while others (legitimating and exchange) had a negative association. This study extends existing research in the upward influencing context by exploring how OHS professionals exert influence at a granular level and proposes implications for professional practice.

Introduction

Since Swuste and Arnoldy’s (2003) suggestion in this journal that personal effectiveness and the ability to influence is as critical to safety as formal management systems, there has been increasing recognition that the ability to influence organizational decision-making is a key capability for occupational health and safety (OHS) professionals (INSHPO, 2017; Provan et al, 2017). Influence by definition, is any action or behaviours that cause a change in the attitude or behavior of another person or group (Yukl, 2013). Influence behavior in the workplace can be distinguished according to the direction of influence i.e. upward, lateral, or downward (Lee et al, 2017)

Upward influencing, defined as “attempts to influence someone higher in the formal hierarchy or authority in the organization” (Porter et al, 1983, p.409), is of particular interest to the OHS profession. This is because OHS professionals are often embedded as middle level managers, advisors or consultants in organizational systems. Since the mid1990’s, the role of the OHS professional has been evolving from that of the traditional OHS specialist who shouldered the responsibility for OHS to that of a change agent, who influences others to enact change in both organizational and management practices (Blewett and Shaw, 1996). Although it is acknowledged that decisions that impact on health and safety occur within all levels of an organisation (Bofinger et al, 2015), the key decisions relating to objectives, strategies, operational procedures and the allocation of resources are largely made by managers within organizations. From an OHS perspective, these key management decisions include making informed choices; prioritising actions; and distinguishing among alternative courses of action to minimise risk and optimise worker health, safety, and well-being. Since these critical decisions may ultimately affect health and safety outcomes, it is essential that OHS professionals are able to influence in an upward direction.

1- Introduction

2- Related work

3- Methodology

4- Case study

5- Conclusions

References

Abstract

Civil infrastructure system maintenance planning is to determine which facility should be repaired, when and how maintenance should be carried out, and what treatment should be used under budget and other resource constraints. In the existing literature, various simulation and optimization models have been developed to help select the optimal maintenance plan. However, the developed models overlooked the deterioration propagation between adjacent connected facilities of the network infrastructure system. For instance, a facility receiving zero maintenance or having a failure of maintenance treatment affects not only the condition of itself, but also the deterioration rate of its neighboring facilities. This raises the call for taking the deterioration propagation into consideration when developing optimization models and capture to which extent it can affect the optimal maintenance plan. Therefore, in this paper, an infrastructure maintenance planning model considering the deterioration propagation between facilities is formulated as a mixed integer linear programming problem. A heuristic algorithm was proposed to solve the problem efficiently. Example networks were tested for the performance comparison between CPLEX and the heuristic algorithm. The proposed model performs better than models without the deterioration propagation.

Introduction

Civil infrastructure systems (e.g., roads, bridges, water supply, and wastewater) are exposed to aging effects and eventually subject to failure if no maintenance intervention is carried out. To prevent/delay failures, maintenance treatments need to be applied periodically. In order to optimize the allocation of resources for maintenance of the facilities, maintenance planning is needed. The primary objective of maintenance planning is to help decision makers schedule maintenance actions and determine which facility need to be maintained when maintenance should be carried out and which treatments should be used. As transportation infrastructure systems are spatially distributed assets covering large regions, they are specially characterized by the interdependence and interaction within and between different systems. Researchers have developed maintenance planning models addressing different relationships between facilities/systems from functional, economic, and other perspectives. For example, Bernhardt and McNeil (2004) stated that pavements are interconnected through geography, which implied the economies of scale in contracting long stretches of pavement for rehabilitation and the diseconomies of scale in terms of the disruption to users. Gao and Zhang (2013b) also pointed out that road sections selected for maintenance by traditional optimization approach are usually distributed spatially across the network. The authors suggested that, to take advantage of economies of scale, adjacent pavement sections with similar maintenance needs should be maintained within a single project. Rasmekomen and Parlikad (2013) conducted a study on optimizing maintenance plans for industrial assets by considering degradation and performance interaction between them.

1- Motivation

2- Flow of materials and components

3- Logistics simulation

4- Maintenance management plan

5- Summary and conclusions

References

Abstract

The DEMO Oriented NEutron Source (DONES) is the dedicated facility for testing and enabling of the qualification for different materials to be utilized in the future fusion reactor DEMO. The neutron irradiation damages not only the material samples to be tested but also impacts the plant hardware in and around the Test Cell which makes regular maintenance mandatory.
In order to keep the plant availability high, a short as possible downtime for maintenance is the overarching goal. Logistics helps enabling this with analyzing the flow of parts and components with special emphasis on the building layout, suggest improvements and optimization potentials. Transportation processes are then modelled and simulated to find an optimum. Taking into account warehouse locations and spare part policy, realization may lead to an optimum Availability-to-Cost-Ratio from the logistics point of view.
In this paper an overview on the different methods of logistics optimization, the individual approaches and goals as well as on their interdependencies is given. Input and output data, boundary conditions, description of the process of integration complement the paper.

Motivation

Due to very high neutron flux in dedicated areas (over 1e10n/cm²/ s) [1] and Gamma irradiation matter that is used in the TC (Test Cell) and also in some of the related systems as e.g. Accelerator System, Lithium Loop is deeply impacted and damaged in its structural integrity. Extrapolating this excerpt, it is evident that preventive and predictive maintenance activities must be scheduled regularly for the entire facility to avoid critical failures during the neutron irradiation tests. In order to keep the availability high [2], the overarching goal is a short as possible downtime. Firstly the Flow of Material has to be carefully analyzed considering all related boundary conditions of parts and components like sizes, shapes, weights and etc. with the aim for an optimum plant layout. Secondly the transportation processes have to be modelled and subsequently simulated in order to find an optimum arrangement. Thirdly the previous results are taken into account in order to design a maintenance management plan described herein by the two example aspects of finding an optimum warehouse location and optimum spare part policy. The latter helps e.g. avoiding stock-outs by optimizing aspects of safety stock level, reorder points, replenishment processes and etc. These three major aspects are enlightened herein and concluded in an integrated manner that may lead to an optimum Availability-to-CostRatio from the logistics point of view.

In recent years, safety problems in oil drilling have obtained many concerns. As the drilling industry involves complex and hazardous activities, it is of great importance to assess attendant risks in which human factors make up a large proportion. The hoisting and lifting systems are one of the most important components in oil drilling industry; measures should be taken to lower the risk of human factors (Zhou et al., 2017). Many safety studies have been done in drilling industry. AmirHeidari et al. (2015) carried out a case study to assess the human factors, which are identified by what-if and structured brainstorming. Zhao et al. (2011) assessed the qualification of human factor risks associated with the drilling process based on Delphi method. Strand and Lundteigen (2016) studied classification of the human factors and put forward a relative importance of assessment criteria in each risk influencing factor. Abimbola et al. (2015) analyzed the shortcomings existing in overbalanced and underbalanced drilling technique, and proposed a Bayesian network model for managed pressure drilling risk assessment. Ataallahi and Shadizadeh (2015) studied the blowout in onshore Iranian drilling industry, and provided fuzzy method to develop the consequence of blowout for Iranian onshore drilling industry. Ramzali et al. (2015) carried out a survey on a leakage event in production phase, and assessed the barriers of the initiating event by using Event Tree Analysis. Pranesh et al. (2017) analyzed the case study of deep water horizon offshore oil platform accident, in which failures in oil and gas cementing operation exists, and concluded that this tragedy is due to complete human errors and employee’s poor leadership abilities. Researchers studied human factors from different views of classification, while the hierarchical and interactional study of human factors in drilling industry is still incomplete; moreover, there are rare studies in the safety assessment considering the interdependences between human factors in the hoisting and lifting system in oil drilling industry. It has been acknowledged that accident analysis must rely on systemic and organizational models (Rasmussen, 1997; Reason, 1997). And it is essential to choose a model before starting the investigations, according to the characteristics of the system and the nature of the accident (Chauvin et al., 2013). Human Factors Analysis and Classification System (HFACS) is a generic human error framework originally developed for US military aviation as a tool for the analysis of the human factors aspects of accidents. The HFACS is perhaps the most widely used human factors accident analysis framework, including shipping accidents (Akyuz, 2017), mining (Patterson and Shappell, 2010), and construction (Garrett and Teizer, 2009). Wiegmann and Shappell (2001) suggested that the HFACS framework bridges the gap between theory and practice by providing safety professionals with a theoretically based tool for identifying and classifying human errors. In HFACS, factors in higher level affect factors in lower levels.

Historically, organisations have emphasised a technological approach in order to protect the security of their information assets. However, as many attackers have started to include social means in their malicious efforts, e.g. social engineering, the need for a holistic approach in addressing information security issues has emerged. The domain of behavioural information security (InfoSec) research highlights the importance of taking into consideration the “human” element when ensuring information security throughout the organisation. Research and practice have shown that technical tools are powerless when it comes to the enforcement of behavioural rules such as password sharing, reporting of security incidents, adherence to a clear desk policy, and the secure disposal of confidential documents. Rather, compliance with these rules entirely depends on employees’ motivation to conform. Therefore, it is essential to understand factors that lead to compliant behaviour or that prompt employees to break organisational information security rules. This study provides new insights about security behaviour in selected U.S. and Irish organisations by investigating how organisational culture and procedural security countermeasures influence security actions. Crossler et al. (2013, p.90) note that “although a predominant weakness in properly securing information assets is the individual user within an organization, much of the focus of extant security research is on technical issues”. In response, our work takes its place amongst the small number studies to date that focus on behavioural as opposed to technical issues. Generally, Behavioural InfoSec research falls into two broad categories: (1) those that focus on the effects of cognitive processes on employee security behaviour (Bulgurcu et al., 2010), and (2) the effect of social controls (Cheng et al., 2013). This study concentrates on the latter. The two basic forms of social controls are formal and informal (Ross, 1896). Formal social controls refer to rules and regulations against deviant behaviour (Cheng et al., 2013). Organisational sanctions, rewards, security education and training, and information security policies are all forms of formal organisational controls.

Despite considerable efforts made in recent years, the industrial accident rate (defined as the number of injuries and deaths per 100 workers or employees) and the fatality rate (defined as the number of deaths per 100,000 workers or employees) in the Republic of Korea are much higher than those in most developed countries in Europe and North America [1]. Statistical analysis further revealed that 76.92% of all industrial accidents associated with industrial machines (hereafter referred to as “items”) were caused by technical reasons in the Republic of Korea. For ease of interpretation, the term “industrial accidents” was used to indicate all industrial accidents that involved injuries or deaths or both in this study. Fig. 1 depicts a flow chart for cause analysis of industrial accidents associated with items. Causes of industrial accidents are first classified into technical ones, managerial ones, and educational ones at the highest level. These causes are further classified at subsequent levels. In 2009, 28,441 cases of industrial accidents associated with items were analyzed to classify their causes according to the flow chart in Fig. 1. Most of the industrial accidents caused by technical reasons were mainly due to defects of items, items without safety devices, or malfunctioning of safety devices attached to them, as shown in Table 1. Malfunction or defects of personal protection equipment account for only a small portion of those cases. Statistical analysis also showed that 59.66% (16,968 cases) among them were preventable. Managerial causes and educational causes were responsible for only 21.03% and 0.44% of all cases, respectively. Most of the technical causes can be resolved at the stage of manufacture, and subsequent elimination of sources of danger appear to be more effective than any other means for prevention of industrial accidents associated with items. Safety certification is, therefore, thought to play a key role in preventing industrial accidents associated with items. The importance of safety function of industrial machines was also important in other countries. A 2014 survey commissioned by the European Union Occupational Safety and Health Agency in collaboration with the Health and Safety Executive in the UK, e.g., explores how health and safety risks are managed at the workplace. The most common reported workplace risk was “machines or tools.” Compared with what we know about causes of injury, one in five of all fatal injuries in the sector over the past 5 years were due to contact with machinery and it accounts for over 10% of employerreported nonfatal injuries within the manufacturing sector [3]. Around 5% of employer-reported fatal and nonfatal injuries were due to contact with machinery within the construction sector [4].

مقاله سال 2017

Sustainable Structures of Civil Engineering and Building Materials

پژوهش‌های متعددی روی حوادث و رخدادهای اصلی اشتغال نقش بسیار مهم مؤلفه‌های سازمانی را بیش‌ازپیش بارز کرده‌اند. بررسی‌ها و شواهد دال براین هستند که «دلایل ریشه‌ای و بنیادی به‌مراتب بیشتر از شکست‌های انسانی و فنی با این پدیده در ارتباط می‌باشند» [1] . درنتیجه، تمرکز روی مؤلفه‌های سازمانی ازجمله مسائل مهم در امنیت به‌عنوان یک ابزار پیشگیری از رخدادها در محل کار می‌باشد. اولین گام برای ارزیابی تأثیر مؤلفه‌های سازمانی شناسایی و مشخص کردن مؤلفه‌های سازمانی مرتبط است. از میان 22 مؤلفه شناخته‌شده در مبانی نظری(پیشینه تحقیق)، 7 مؤلفه مهم برای صنعت ساخت‌وساز تایلند شناسایی و نهایی سازی شد: ارتباطات، فرهنگ، تعهد مدیریت ، رهبری، یادگیری سازمانی، توسعه و بهبود و سیستم پاداش. در مرحله پایانی، رویکرد شبکه Bayesian Belief برای رویاروی با پیچیدگی‌های رایج و ارائه استراتژی‌هایی به‌منظور بالا بردن رفتارهای کاری ایمن بکار گرفته شد. مطابق با اولین شق(پیشنهاد)،73.3% رفتار کاری ایمن به‌طور هم‌زمان از سوی متغیرهای تعهد مدیریت، مشارکت، یادگیری و رهبری تحت تأثیر قرارگرفته شد. دومین شق با ضریب 74.6% رفتار کاری ایمن به اتمام رسید وقتی رهبری، تعهد مدیریت، مشارکت، و نیت و قصد در یک وضعیت مطلوب قرارگرفته شدند. برای سومین شق، حدود 77.7% رفتار کاری ایمن از طریق کنترل و نظارت رهبری، تعهد مدیریت، مشارکت و کنترل رفتار درک شده حاصل گشت.

مقاله سال 2016

In 1987 an open sky policy was implemented in the airline industry (Chang and Chiu, 2009) and this business freedom for flight operations resulted in increased competition among airlines. Consequently, in most parts of the world, the deregulation of the airline business has affected industry competition. During the past decade, two major airline business models were classified according to their strategic plans. The traditional model covered the comprehensive service package and the other concerned low cost airlines offering reduced prices with minimum extras (Tiernan et al., 2008a, b). Full service airline criteria include seats with space to recline, leg room, in-flight entertainment, baggage processing, meal service, in-flight amenities, a choice of first, business or economy class travel and partners such as Star Alliance, Sky Team and Oneworld. Air carriers identified the major strengths and weaknesses of their services related to their brand positioning (Wen and Chen, 2010). Competition in the airline business caused airlines to resort to different strategies such as intensive marketing, advertising and promotions combined with price and ticketing sales. In the airline business regulatory safety requirements are the top priority; air safety records reflect airline image, while high quality service is associated with passenger expectation (Liou et al., 2008). Airline businesses have consolidated their images, using integrated methods to manage the improvement of passenger satisfaction.

This paper examined the effect of airline image on passenger perception of service quality and safety operations. Part two reviewed the literature on service quality management, airline service criteria and SERVQUAL measurement, the Kano model and customer satisfaction coefficient analyses, airline safety criteria and rankings and TRIZ application tools. Part three examined three airline service quality case studies and Part four presented and discussed the conclusions.