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Ship chandlers’ trucks are now facing challenges owing to their job characteristics, which will lead to low productivity of trucks, congestions and pollutions at the port. The aim of this paper is to identify important causes and the effects of low truck productivity at the port under the demand of sustainable development.

Based on the literature review, potential causes and relevant analysis are developed and carried out by using a systematic approach, incorporating in-depth interviews with experts, cause analysis and risk management process.

Results from the research framework showed that a lack of communication with the port, late arrival of ships, truck congestion and fragmented deliveries are the most important factors that led to low truck productivity at the port. A solution that combines an integrated system that shares real-time information with the port, a consolidation hub and a truck-pooling platform is proposed to comply with green port concepts, together with factors considerations.

Although the operation of ship chandlers’ trucks is a derived business in overall port operations, it is an indispensable element at the port. The findings present a new insight to the relationship between ship chandlers’ trucks productivity and port operation efficiency for industry practitioners and port policymakers.

This article examines how excellence in customer service and satisfaction can be a major source of competitive advantage and profits for small businesses. The costs and causes of poor service and satisfaction are discussed and special emphasis is given to the value of the lifelong customer. Methods to pursue the goal of completely satisfying customers 100 percent of the time are examined. Leadership, aggressive problem solving, problem-solving teams, and assessment of customer service are among the topics reviewed.

This exploratory study investigates causes and consequences of internationalization launched by new ventures.

This study aims to explore the factors influencing electrical accidents. Here, the authors aim to understand and model the causes of electrical accidents at multiple levels.

In the study, the authors have tried to put causes of accidents in the electricity distribution segment, in the framework of the Swiss Cheese model. Delphi kind of expert survey was conducted to find the Cheese Slice (level) and the causes (holes) for electrical accidents. Inputs from a hundred experts having more than five years of experience in electrical utility companies have been used to find Cheese Slice and holes, to explain the occurrence of an electrical accident.

Effective training for safe work practices, safe knowledge and closer supervision would go a long way to plug the holes in the Cheese Slice in human factors. The difference in perception of managers, supervisors and workers on the importance of various causes of electrical accidents are also presented and discussed.

This research is based on expert opinion and survey where respondent perception is reported. Actual accident data has not been used here.

The holes or causes of accidents at different levels (Cheese Slice) have been identified for plugging or removal for better safety.

Electrical energy is widely used, and therefore, electrical safety is a social concern and also improving it is a social need.

The study contributes to electrical safety issues in the electrical utility sector.

The purpose of this paper is to reveal the main causes of delays in the projects are from the client (relative importance index (RII)=0.716), labor and equipment (RII=0.701) and contractor (RII=0.698). Hence determining the contractual responsibility of delay is the most likely source of dispute in construction projects and many techniques have been used in the courts to demonstrate the criticalities of a delay event on the project schedule. Therefore, authors try to investigate all process-based techniques of delay claims and evaluated and conformed them with principles by Society of Construction Law (SCL) protocol and Association for the Advancement of Cost Engineering International (AACEI) in order to choose the best techniques based on the specific circumstances of each project.

This section is divided into two distinct parts: refers to the methods used to assess the perceptions of clients, consultants, and contractors on the relative importance of causes of delay in construction industry; and refers to advantages and disadvantages of various techniques used to analyze delays and their conform with SCL protocol. A questionnaire was developed to assess the perceptions of clients, consultants, and contractors on the relative importance of causes of delay in Iranian construction industry. The respondents were asked to indicate their response category on 78 well-recognized construction delay factors identified by authors.

In total, 78 causes of delay were identified through research. The identified causes are combined into seven groups. The field survey included 58 contractors, 55 consultants, and 62 client. Data collected were analyzed by RII and Statistical Package for Social Sciences (SPSS). The authors identified main causes of delay and ten most important causes, according to Table AII, from the perspective of three major groups of participants (clients, consultants and contractors). The ranking of categories of causes of delay, according to Table I, were: client-related causes (RII=0.716); labor and equipment category causes (RII=0.701); contractor-related causes (RII=0.698); material-related causes (RII=0.690); design-related causes (RII=0.666); external causes (RII=0.662); and consultant-related causes (RII=0.662). But according to the discussions and given that determining the contractual responsibility of delay is the most likely source of dispute in construction industry and many techniques have been used in the courts to demonstrate the criticalities of a delay event on the project schedule.

All process-based techniques of delay analysis have been present in this paper and categorized in 11 groups. In order to understand the advantages and disadvantages of them by clients, contractor and consultant, a thorough review conducted to reveal the nature of techniques. In the next step, given that selecting the most appropriate technique based on constraints and specific conditions of each project is one of the most important steps to carry out a successful delay analysis. The authors conformed, all process-based techniques of delay analysis, by SCL protocol and AACEI principles. Finally, the result of this match was brought in order to choose the best technique based on the specific circumstances of each project.

Schizophrenia is a devastating illness with a chronic and relapsing course. While Western countries may endorse, biological and psychosocial causes more commonly than supernatural causes, non-western cultures like Nigeria in contrast, tend to endorse supernatural causes. Belief in supernatural causes has been reported to have consequences for treatment seeking behavior. This study aimed to examine the causes of schizophrenia reported by family members of outpatients with schizophrenia in a neuropsychiatric hospital in Midwestern Nigeria. In this study, we recruited a convenient sample of 200 consecutive caregivers of patients visiting the outpatient department of the Psychiatric Hospital, Benin City, Nigeria. These primary caregivers were unpaid relatives who provided support to patients. The patients were service users who fulfilled the diagnostic criteria of the International Classification of Disease [ICD-10; World Health Organization 1993] for schizophrenia and had been on treatment for at least two years. Majority (72.0%) of caregivers endorsed supernatural causes as most important in the etiology of schizophrenia, while 28.0% endorsed natural causes. Every participant without formal education endorsed supernatural attribution. In our study, it was evident that participants embraced multiple causal attributions for schizophrenia.

The purpose of this paper is to develop a structural relationship model to study the relationship between causes and effects of poor communication and information exchange in construction projects using Smart-PLS.

The first method of this research is to identify the causes and effects factors of poor communication in construction projects from the extant of literature. The data used to develop the model was collected using a questionnaire survey, which targeted construction practitioners in the Malaysian construction industry. A five-point Likert type scale was used to rate the significance of the factors. The factors were classified under their relevant construct/group using exploratory factor analysis. A hypothetical model was developed and then transformed into Smart-PLS in which the hypothetical model suggested that each group of the cause factors has a direct impact on the effect groups. The hypothesis was tested using t-values and p-values. The model was assessed for its inner and outer components and achieved the threshold criterion. Further, the model was verified by engaging 14 construction experts to verify its applicability in the construction project setting.

The study developed a structural equation model to clarify the relationships between causes and effects of poor communication in construction projects. The model explained the degree of relationships among causes and effects of poor communication in construction projects.

The published academic and non-academic literature introduced many studies on the issue of communication including the definitions, importance, barriers to effective communication and means of poor communication. However, these studies ended up only on the general issue of communication lacking an in-depth investigation of the causes and effects of poor communication in the construction industry. The study implemented advanced structural modeling to study the causes and effects. The questionnaire, the data and concluding results fill the identified research gap of this study. The addressed issue is also of interest because communication is considered one of the main knowledge areas in construction management.

Statistics show that the construction sector has the second-highest number of accident cases in Malaysia. A total of 100, 000 construction workers suffer from work-related bad health each year. Scaffolding accidents are the second cause of accidents on construction sites. Therefore, this present research provided answers to the following questions: (1) what are the causes of scaffolding accidents and (2) what are the possible measures to reduce scaffolding accidents?

The research developed a questionnaire instrument that included 24 causes of scaffolding accidents and 21 remedial actions. The research was based on a cross-sectional survey questionnaire administered to 129 members of construction organizations.

Data revealed that scaffolding-related cases caused a total of 70% of the deaths/injuries on sites. Furthermore, scaffolding accidents were mainly caused by a lack of guard rails on scaffoldings, poor inspections, improper assembly, a poor safety culture, poor attitudes towards safety, poor footing of scaffoldings and unsecured planking. To reduce scaffolding accidents, there must be a lifeline on scaffolding, proper guardrails and proper assembling of scaffoldings, and preventing access to incomplete or defective scaffoldings. The 24 causes are structured into six factors through factor analysis and the 21 remedial actions into six factors.

This research serves as the first attempt to conduct broad research on the causes and remedial actions concerning scaffolding accidents on construction sites in Malaysia. Theoretically, the research has provided fresh insights into the impact of scaffolding accidents.

The railway signal equipment failure diagnosis is a vital element to keep the railway system operating safely. One of the most difficulties in signal equipment failure diagnosis is the uncertainty of causality between the consequence and cause for the accident. The traditional method to solve this problem is based on Bayesian Network, which needs a rigid and independent assumption basis and prior probability knowledge but ignoring the semantic relationship in causality analysis. This paper aims to perform the uncertainty of causality in signal equipment failure diagnosis through a new way that emphasis on mining semantic relationships.

This study proposes a deterministic failure diagnosis (DFD) model based on the question answering system to implement railway signal equipment failure diagnosis. It includes the failure diagnosis module and deterministic diagnosis module. In the failure diagnosis module, this paper exploits the question answering system to recognise the cause of failure consequences. The question answering is composed of multi-layer neural networks, which extracts the position and part of speech features of text data from lower layers and acquires contextual features and interactive features of text data by Bi-LSTM and Match-LSTM, respectively, from high layers, subsequently generates the candidate failure cause set by proposed the enhanced boundary unit. In the second module, this study ranks the candidate failure cause set in the semantic matching mechanism (SMM), choosing the top 1st semantic matching degree as the deterministic failure causative factor.

Experiments on real data set railway maintenance signal equipment show that the proposed DFD model can implement the deterministic diagnosis of railway signal equipment failure. Comparing massive existing methods, the model achieves the state of art in the natural understanding semantic of railway signal equipment diagnosis domain.

It is the first time to use a question answering system executing signal equipment failure diagnoses, which makes failure diagnosis more intelligent than before. The EMU enables the DFD model to understand the natural semantic in long sequence contexture. Then, the SMM makes the DFD model acquire the certainty failure cause in the failure diagnosis of railway signal equipment.

The purpose of this study is to determine the distraction factors based on their contributions in affecting seafarers’ physical and psychological well-being.

A systematic average mean value technique incorporated with quantitative data collection is applied to determine the contributions of the involved factors in establishing the distraction problems among seafarers.

Element of “Food and nutrition” is recorded as the highest contributing factor to Malaysian seafarers, for deck and engine department, respectively, in establishing the distraction-related problem among five other factors involved.

This paper is only providing a scope of knowledge regarding the contribution of potential distraction factors existing on board the offshore ships. However, the potential distraction factors and their contributions, respectively, are very dynamic and may vary, depending on the situation of a particular area and who are being involved.

The result assists the shipping industry in recognizing the actual causes of the occurrences of marine casualties and incidents related to human factors.

The benefits are addressed to seafarers’ community where their well-being and work performances could be enhanced, thus reducing the occurrences of marine casualties and incidents. Local community at the shores also will be less threatened by marine pollution caused by the accidents of ships at sea.

The result provides a scope of knowledge regarding distraction-related factors in shipboard operation and also the introduction to a systematic assessment approach to determine and rank the parameters by using the systematic average mean value technique which is also a straightforward method and can be applied in any other circumstances.