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The purpose of this paper is to suggest to the conflict study scholars a new instrument – the “conflict volcano” that could be an effective and appropriate tool for conflict analysis.

The “conflict volcano” model was designed as a qualitative method for conflict analysis with a focus on cause analysis. It was developed on the basis of “conflict tree” which underwent modifications.

The benefit of the “conflict volcano” is that it covers all aspects of conflict starting from root cause to catalysts and can reveal a wide range of causes: material, immaterial, institutional. It clearly frames factors; this helps practitioners to determine what should be considered as causes and effects. Moreover, the “conflict volcano” reflects major theoretical representations of the conflict and its aspects. While the “conflict volcano” model can study conflict phases from latent until open violence, it cannot reflect the dynamic of conflict and cannot demonstrate its evolution to post-conflict phases.

The “conflict volcano” can be used as a conflict analysis tool by practicing experts and scholars. Academicians can use it in order to understand conflict and especially to reveal its causes. Practicing experts can use it in order to design a conflict transformation strategy.

This instrument does not pretend to be a new invention in the field of conflict studies, but rather a new conceptualization, schematization of old concepts and instruments.

The application of lean and quality improvement methods is very common in process improvement projects at organisational levels. The purpose of this research is to assess the adoption of Lean Six Sigma™ approaches for addressing a complex process-related issue in the coal industry.

The sticky coal problem was investigated from the perspective of process-related issues. Issues were addressed using a blended Lean value stream of supply chain interfaces and waste minimisation through the Six Sigma™ DMAIC problem-solving approach, taking into consideration cross-organisational processes.

It was found that the tendency to “solve the problem” at the receiving location without communication to the upstream was, and is still, a common practice that led to the main problem of downstream issues. The application of DMAIC Six Sigma™ helped to address the broader problem. The overall operations were improved significantly, showing the reduction of sticky coal/wagon hang-up in the downstream coal handling terminal.

The Lean Six Sigma approaches were adopted using DMAIC across cross-organisational supply chain processes. However, blending Lean and Six Sigma methods needs to be empirically tested across other sectors.

The proposed methodology, using a framework of Lean Six Sigma approaches, could be used to guide practitioners in addressing similar complex and recurring issues in the manufacturing sector.

This research introduces a novel approach to process analysis, selection and contextualised improvement using a combination of Lean Six Sigma™ tools, techniques and methodologies sustained within a supply chain with certified ISO 9001 quality management systems.

The international energy agency states that the world’s primary energy needs are expected to grow to 55 per cent until 2030. Therefore, oil and gas industry as the main energy source will be more crucial where building or advancing new capacities is required. Because the reports highlight the delay as a recurring problem, thereby, more in-depth investigation to find out the main contributing causes is needed.

Root cause analysis (RCA) was applied to identify, rank, analysis and categorize the main sources of this problem.

Based on RCA procedure; Pareto analysis showed that 84.7 per cent of the delay is because: the radar chart indicated no difference in perception of the participants regarding the importance of the root causes, correlation analysis suggested strong relationship among the participants and the cause-and-effect diagram emphasized more on operational, human and equipment categories, which in total account for 51.86 per cent of the delay.

The risk planners of large-scale projects can consider these root causes as the main items to analysis, monitor and control, as they are vitally important for project success.

Limited research on root cause analysis exists in educational leadership. Accurately diagnosing and detailing root causes—the why—of organizational failure, as is relatively common in other fields, could improve principals' ability to devise situationally- and contextually-responsive solutions in their improvement plans. In this study, the authors analyze school improvement plans to provide insight into how principals use root cause analysis to identify their and their school's failures as a way to respond strategically with goals and action steps.

In this exploratory qualitative study, the authors develop coding schemes and leverage an existing rubric of school improvement plan quality to assess what principals identify as root causes for 216 priorities across 111 school improvement plans.

The overall quality of root causes submitted by principals was low, typically between “beginning” and “developing” stages. The majority of root causes aligned with priorities and desired outcomes, but fewer than one-third had a systems focus. Moreover, less than half of root causes suggested that school leaders played a part in the organizational failures. The vast majority of plans instead identified teachers as the root cause, foundational fault or “why” of the problem.

An increased understanding of root cause analysis conceptualization and development seems necessary if improvement planning is to be a strategic response to a school's most serious organizational challenges. The predominant approach to school improvement planning has focused almost exclusively on how to succeed or become better with little investment in identifying root causes of organizational decline or failure. This initial study of root cause quality in school improvement planning is a key first step in critically thinking about how improvement is to be achieved when failure is unconceived.

The purpose of this paper is to go a step further from the traditional 5 Whys technique by adding three more legs during the root cause analysis stage – occurrence, human and systemic issues that contribute toward the problem, hence the term 3 × 5 Whys. Performing individual 5 Whys for these three components enables to identify deeper root cause(s) that may spawn across multiple groups within an organization.

Cause-and-effect analysis used during traditional root cause investigations within an 8D or Lean six sigma project is used as a theoretical foundation. Examples from different industries are presented showing the 3 × 5 Why’s framework and advantages it brings to the organization along with identifying shortcomings and suggestions to make it more effective.

If properly used this integrated methodology will reveal higher order systemic causes (e.g. policies or management decisions) stemming from lower lever symptoms (e.g. defective parts, procedural errors). Effective execution of this methodology can provide tremendous results in defect reduction, yield improvement, operational efficiency improvement and logistics management type of projects. Resolving higher level sources of problems allows an organization to evolve itself and maintain a competitive edge in the market.

Adopting this quality management technique in start-up companies entails some challenges and other implications have been discussed with SWOT analysis.

Examples from various sectors using 3 × 5 Why approach have been presented that show that this methodology provides deeper insight into root causes which could be affecting multiple groups in an organization. Using this technique effectively is found to be beneficial to resolve issues in operations management, logistics, supply chain, purchasing, warehouse operations, manufacturing, etc.

This methodology has a human component which often results in some sort of resistance as not all working professionals think alike when it comes to accountability and ownership of issues. This may hinder root cause analysis and subsequent corrective actions implementation.

This study is unique in its in-depth real-world case studies demonstrating the need for taking a deep dive approach to root cause analysis by understanding specific, system and human components responsible for causing the failure mode.

In implementing Six Sigma and/or Lean Six Sigma, a practitioner often faces a dilemma of how to select the subset of root causes from a superset of all possible potential causes, popularly known as root cause analysis (RCA). Generally one resorts to the cause and effect diagram for this purpose. However, the practice adopted for identification of root causes is in many situations quite arbitrary and lacks a systematic, structured approach based on the rigorous data driven statistical analysis. This paper aims at developing a methodology for validation of potential causes to root causes to aid practitioners.

Discussion has been made on various methods for identification and validation of potential causes to root causes with the help of a few real life examples for effective Lean Six Sigma implementation.

The cause and effect diagram is the frequently adopted method for identifying potential causes out of a host of methods available for such identification. The method of validation depends on the practitioners’ knowledge on the relationship between cause and effect and controllability of the causes.

The roadmap thus evolved for the validation of root causes will be of great value to the practitioners as it is expected to help them understand the ground reality in an unambiguous manner resulting in a superior strategy for cause validation and corrective actions.

This paper presents nine different methods and approaches useful for performing human reliability and error analysis in health care. These methods are failure modes and effect analysis (FMEA), root cause analysis (RCA), fault tree analysis (FTA), cause and effect diagram (CAED), hazard operability study (HAZOP), probability tree method, error cause removal program (ECRP), man‐machine systems analysis (MMSA), and the Markov method. The applications of many methods are demonstrated through nine solved examples.

In Bangladesh (BD), delays in infrastructure are common. Many previous studies have explored the causes of infrastructure delays. However, this study investigated the causes of delays by taking responses from the stakeholders who are responsible for planning, design, funding, approval and implementation. There are few studies that have related infrastructure project delays to heterogeneity in stakeholders’ perceptions.

A structural equation (SE) model is developed with 350 normally distributed data points to understand the heterogeneity in stakeholders’ perceptions regarding delays in infrastructure projects in BD. Additionally, the relative importance index (RII) approach is used to assess the responses, validating the SE model.

The study finds that among the three latent variables, “Project itself related delay” has more influence on delays in infrastructure projects. Among the observed variables under the “project itself related delay” latent variable, “DPP approval process” has the most significance. From the heterogeneity analysis, the study found differences in responses among the stakeholders from “the Engineering Department,” “the Planning Office” and “the Construction Firm/Industry.” An important class of stakeholders believes that their stage is not being delayed and that other stages require attention.

The data sample is 350. More data can improve the accuracy of the findings. Most of the respondents are civil engineers (74%) and represent the owner of the project. Sample data from more stakeholders’ will enhance the accuracy of the result.

This study addresses the requirements of Bangladeshi project stakeholders and how their interactions cause delays in projects. Furthermore, the opinions of other stakeholders are taken into consideration when determining the specific factors of individual stakeholders that are causing delays. Practically, the distance between stakeholders should be reduced. A project manager can play a role in this regard. Initiatives should be taken on how to complete the project quickly by eliminating the requirements discussed among the stakeholders and bureaucratic complications. Instead of placing blame on one another, stakeholders should take the initiative to figure out how to work together to finish the project on schedule. The Planning Commission’s approval of the Development Project Proposal (DPP) and Revised Development Project Proposal (RDPP) should be obtained as soon as possible by owner stakeholders. In order to avoid frequently changing the DPP, owners should also exercise greater caution when choosing contractors. Contractor stakeholders should use efficient and proper manpower and equipment so that unexpected delays are not created during the execution of work. Since the role of the contractor stakeholder is the most important among the three types of stakeholders, the contractor should raise awareness and urge the owners to get the RDPP approved quickly.

The findings from the study can help mitigate delays in infrastructure projects in BD, taking into account the perceptions of various stakeholders.

The purpose of this paper is to expand understandings of how logistics can reduce food waste in food supply chains (FSCs).

Using a research framework that associates causes of food waste with logistics solutions, a multiple-case study was conducted in three Swedish FSCs of meat, fruit and vegetables, and ambient products, respectively, and involving industrial producers, wholesalers, and retailers. Data were collected during 19 semistructured interviews and four site visits, and logistics solutions were analysed according to logistics activities, actors involved and their stages in the FSC, and coordination mechanisms.

A joint analysis of nine logistics solutions revealed that to efficiently reduce food waste in FSCs, solutions have been implemented at three stages of FSCs, as well as that those solutions differ in their integration of six logistics activities and four coordination mechanisms. The findings moreover indicate that the solutions are interlinked, thereby implying that coordination is necessary both within solutions as well as among them.

The chief limitation is that the potential of the identified logistics solutions is not quantified.

The paper makes recommendations for reducing food waste in FSCs by developing new solutions and modifying existing ones.

The paper suggests ways to reduce significant environmental impacts of food waste.

By building upon previous research explaining causes of food waste, this paper focusses on logistics solutions for reducing such waste.

Mediating effects are often tested using hierarchical multiple regression (HMR) procedures. Typical of the HMR-based strategies is the very frequently cited and widely used procedure described by Baron and Kenny (1986). Unfortunately, there are several important problems with it. More specifically, as we demonstrate below, it: (a) is of virtually no value for buttressing claims of mediating effects for data from non-experimental research; (b) produces erroneous inferences about the existence of mediating effects for misspecified mediation models; and (c) is incapable of providing credible evidence of such effects in a large proportion of cases, even for properly specified mediation models. We detail a number of important implications of our analyses.