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In business-to-business interactions, conflicts are inevitable, and conflict-handling strategies that consider different variables improve the decision-making process of actors. This study aims to reveal the role of power and criticality in conflict-handling research in logistics service networks.

A 2 × 2 between-subject experimental design with four different scenarios was used. One hundred sixty logistics service actors completed an online questionnaire. Data were analyzed with ANOVA and paired sample t-tests using the SPSS 28.0 program.

In comparative scenarios involving high and low power dynamics, individuals with high power and high criticality situations are more inclined to favor the dominating strategy compared to low-power and low-criticality contexts. However, when faced with specific circumstances characterized by both high power and high criticality, actors tend to prioritize the integrating strategy initially, followed by the dominating and obliging strategies in that order. Notably, the statistical analysis revealed no significant interaction effect between criticality and power concerning the integrating, obliging and dominating conflict-handling strategies.

This study used an experimental approach to investigate criticality and power as contextual elements in determining conflict-handling strategies in an inter-firm environment within logistics service networks. This study is particularly groundbreaking in its knowledge of the relationship among power dynamics, conflict criticality and conflict-handling strategies.

Assessing project criticality in a project portfolio (PP) is of great practical significance to improve robustness from damage. While project criticality assessment has increased diversity in approaches, the understanding of vulnerable project impacts is still limited. To promote a better understanding of assessing project criticality, a vulnerability measurement model is constructed.

First, integrating the tasks, projects and corresponding relationships among them, a project portfolio network (PPN) is constructed. Second, the project's vulnerability is measured by combining the topological structure and functional attributes. Third, project criticality is assessed by the vulnerability measurement results. Lastly, the proposed model is applied in a numerical example to illustrate its suitability and effectiveness.

For academia, this study provides a novel perspective on project vulnerability measurement and expands project criticality assessment tools. For practitioners, the straightforward model provides an effective tool for assessing project criticality and contributes to enhancing project portfolio management (PPM).

The impact of the task on the project is considered in this study. Topological structure and functional attributes are also integrated for measuring project vulnerability due to the impact of random attacks in an uncertain environment, providing a new perspective on the requirements of project criticality assessment and the measurement of project vulnerability.

The purpose of this paper is to identify the productivity improvement potentials from maintenance planning practices in manufacturing companies. In particular, the paper aims at understanding the connection between machine criticality assessment and maintenance prioritization in industrial practice, as well as providing the improvement potentials.

An explanatory mixed method research design was used in this study. Data from literature analysis, a web-based questionnaire survey, and semi-structured interviews were gathered and triangulated. Additionally, simulation experimentation was used to evaluate the productivity potential.

The connection between machine criticality and maintenance prioritization is assessed in an industrial set-up. The empirical findings show that maintenance prioritization is not based on machine criticality, as criticality assessment is non-factual, static, and lacks system view. It is with respect to these finding that the ways to increase system productivity and future directions are charted.

In addition to the empirical results showing productivity improvement potentials, the paper emphasizes on the need for a systems view for solving maintenance problems, i.e. solving maintenance problems for the whole factory. This contribution is equally important for both industry and academics, as the maintenance organization needs to solve this problem with the help of the right decision support.

The purpose of this paper is to increase productivity through smart maintenance planning by including productivity as one of the objectives of the maintenance organization. Therefore, the goals of the paper are to investigate existing machine criticality assessment and identify components of the criticality assessment tool to increase productivity.

An embedded multiple case study research design was adopted in this paper. Six different cases were chosen from six different production sites operated by three multi-national manufacturing companies. Data collection was carried out in the form of interviews, focus groups and archival records. More than one source of data was collected in each of the cases. The cases included different production layouts such as machining, assembly and foundry, which ensured data variety.

The main finding of the paper is a deeper understanding of how manufacturing companies assess machine criticality and plan maintenance activities. The empirical findings showed that there is a lack of trust regarding existing criticality assessment tools. As a result, necessary changes within the maintenance organizations in order to increase productivity were identified. These are technological advancements, i.e. a dynamic and data-driven approach and organizational changes, i.e. approaching with a systems perspective when performing maintenance prioritization.

Machine criticality assessment studies are rare, especially empirical research. The originality of this paper lies in the empirical research conducted on smart maintenance planning for productivity improvement. In addition, identifying the components for machine criticality assessment is equally important for research and industries to efficient planning of maintenance activities.

Organizational insiders play a critical role in protecting sensitive information. Prior research finds that moral beliefs influence compliance decisions. Yet, it is less clear what factors influence moral beliefs and the conditions under which those factors have stronger/weaker effects. Using an ethical decision-making model and value congruence theory, this study aims to investigate how moral intensity and organizational criticality influence moral beliefs and intentions to perform information protection behaviors.

The hypotheses were tested using a scenario-based survey of 216 organizational insiders. Two of the scenarios depict low criticality information security protection behaviors and two depict high criticality behaviors.

A major finding is that users rely more on perceived social consensus and magnitude of consequences when organizational criticality is low and on temporal immediacy and proximity when criticality is high. In addition, the moral intensity dimensions explain more variance in moral beliefs when organizational criticality is low.

The study is limited by its sample, which is organizational insiders at a mid-size university. It is also limited in that it only examined four of the six moral intensity dimensions.

The findings can guide management about which moral intensity dimensions are more important to focus on when remediating tone at the top and other leadership weaknesses relating to information security.

This study adds value by investigating the separate dimensions of moral intensity on information protection behaviors. It also is the first to examine moral intensity under conditions of low and high organizational criticality.

The purpose of this paper is to present a new hybrid approach based on criticality analysis and optimisation to deal with spare parts inventory management in the initial provisioning phase in the mining industry. Spare parts represent a significant part of mining companies' expenditures, so it is important to develop new approaches to reduce the total inventory value of these items.

This hybrid approach combines qualitative and quantitative methods based on VED (vital, essential and desirable) analysis, analytical hierarchical process (AHP), and e-constraint optimisation method to obtain the spare parts to be stocked. The study was applied to a large mining company. The mineral sector was chosen due to the great importance to the emerging Brazilian economy and the lack of researches in this sector. In addition, the spare parts have a relevant weight on the total inventory cost.

Present a novel approach combining multi-objective optimisation and multi-criteria evaluation approaches to tackle the inventory decision in spare parts management. This work also defines and classifies relevant criteria for spare parts management in the mineral sector validated by specialists. The proposed approach achieves an average increase of 20.2% in the criticality and 16.6% in the number of items to be stocked compared to the historical data of the surveyed company.

This paper applies the proposed approach to a mining company in Brazil. Future research in other companies or regions should analyse the adequacy of the criticality criteria, hierarchy and weights adopted in this paper.

The proposed approach is useful for mining industries that deal with a large variety of resource constraints as it helps in formulating appropriate spare part strategies to rationalise financial resources at both tactical and strategic levels.

The paper presents a new hybrid method combining the AHP a multi-criteria decision making (MCDM) approach coupled with e-constraint optimisation to deal with spare parts inventory management allowing for a better spare parts inventory analysis in the initial provisioning phase and providing managers with a systematic tool to analyse the trade-off between spare parts criticality and total inventory value.

This paper aims to enable the analysts of reliability and safety system to assess the criticality and prioritize failure modes perfectly to prefer actions for controlling the risks of undesirable scenarios.

To resolve the challenge of uncertainty and ambiguous related to the parameters, frequency, non-detection and severity considered in the traditional approach failure mode effect and criticality analysis (FMECA) for risk evaluation, the authors used fuzzy logic where these parameters are shown as members of a fuzzy set, which fuzzified by using appropriate membership functions. The adaptive neuro-fuzzy inference system process is suggested as a dynamic, intelligently chosen model to ameliorate and validate the results obtained by the fuzzy inference system and effectively predict the criticality evaluation of failure modes. A new hybrid model is proposed that combines the grey relational approach and fuzzy analytic hierarchy process to improve the exploitation of the FMECA conventional method.

This research project aims to reflect the real case study of the gas turbine system. Using this analysis allows evaluating the criticality effectively and provides an alternate prioritizing to that obtained by the conventional method. The obtained results show that the integration of two multi-criteria decision methods and incorporating their results enable to instill confidence in decision-makers regarding the criticality prioritizations of failure modes and the shortcoming concerning the lack of established rules of inference system which necessitate a lot of experience and shows the weightage or importance to the three parameters severity, detection and frequency, which are considered to have equal importance in the traditional method.

This paper is providing encouraging results regarding the risk evaluation and prioritizing failures mode and decision-makers guidance to refine the relevance of decision-making to reduce the probability of occurrence and the severity of the undesirable scenarios with handling different forms of ambiguity, uncertainty and divergent judgments of experts.

The purpose of this paper is to trial the application of a criticality framework for roads in an urban environment. The failure or disruption of critical transport routes can have substantial impacts on the economy and societal well-being. Determining the criticality of transport routes is thus of crucial importance for infrastructure providers, city planners and emergency management officials, as it enables appropriate resilience assessments and targeted improvement/intervention and investment strategies to be conducted.

The authors summarise the proposed criticality framework developed by Hughes (2016) for road networks and apply and validate the framework to an area containing 907 km of roads in the central Auckland area of New Zealand. Following an initial trial of the framework, alterations were made to the framework logic, which included the introduction of a new criticality level to account for some roads providing minimal direct societal and economic benefit and a rationalisation step to ensure that road sections always link to others with either an equal or higher criticality.

The modified framework and five-level criticality scale, when applied to the study area in central Auckland, is suitable for determining critical roads and can therefore assist with future assessments of road infrastructure resilience.

The framework also has the potential to be applied more widely and adapted so that it is applicable for determining the criticality of other infrastructure types and in other settings, which would allow improved assessments within and across sectors.

This work aims at integrating materials management with project management in the context of manufacturing of complex products which require a variety of items. To achieve this, we propose two prioritization measures of items: material criticality (MC) at activity level and overall criticality (OC) at project level by incorporating project network characteristic through activity criticality (AC) values.

The costs or penalties which determine criticality of items are hidden in nature and are difficult to measure and model mathematically. Hence, Fuzzy Inference System (FIS), which captures experts’ tacit knowledge in the form of linguistic If‐Then rules has been used.

OC obtained can be used as a measure to prioritize items for procurement aligned with on‐site build strategy and as a surrogate measure of shortage cost coefficient for inventory models. The analyses of output to observe the effect of AC on OC values of items, clearly demonstrate the novelty and importance of incorporating project network characteristics in materials management decision making.

In this work, we are able to leverage managerial tacit knowledge derived through years of experience and convert it into a readily usable quantitative parameter OC for prioritization of items to be procured. For identifying the input parameters for OC, we brought in the new perspective of including project network characteristics to align materials and project management.

The main purpose is to provide a demonstration of the utility of the DMG as a streamlined approach of a prescriptive-type model that can facilitate strategic and dynamic methodology to the decision-maker with respect to what policies, strategies or actions should be carried out.

This paper proposes a framework for an agile criticality assessment process using decision-making grid (DMG) to accommodate the needs of this dynamic environment.

The proposed new approach has delivered better results with more consistency when applied by different teams and achieved better distribution of assets over the criticality scale.

The proposed approach has been validated through an industrial case study related to a steam generation system (SGS).

The implementation of the proposed approach in a petroleum refinery to assess the criticality of steam generation system (SGS) has shown positive results in terms of time and effort optimization. This research contributes to production planning and control literature with respect to one of its core activities of maintenance, through an innovative, systematic and practical approach.