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This study aims to determine the factors and dynamic systems behaviour of essential medicine stockout in public health-care supply chains. The authors examine the constraints and effects of mental models on medicine stockout to develop a dynamic theory of medicine availability towards saving patients’ lives.

This study uses a mixed-method approach. Starting with a survey method, followed by in-depth interviews with stakeholders within five health-care supply chains to determine the dynamic feedback leading to stockout and conclude by developing a network mental model for medicines availability.

The authors identified five constraints and developed five case mental models. The authors develop a dynamic theory of medicine availability across cases and identify feedback loops and variables leading to medicine availability.

The need to include mental models of stakeholders like manufacturers and distributors of medicines to understand the system completely. Group surveys are prone to power dynamics and bias from group thinking. This survey’s quantitative output could minimize the bias.

This study uniquely uses a mixed-method of survey method and in-depth interviews of experts to assess the essential medicine stockout in Nigeria. To improve medicine availability, the authors develop a dynamic network mental model to understand the system structure, feedback and behaviour driving stockouts. This research will benefit public policymakers and hospital managers in designing policies that reduce medicine stockout.

The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

This paper aims to study the reliability of the high-speed train operation control system in the Chinese Train Control System Level 3 (CTCS-3) operating mode.

Dynamic fault tree and Bayesian network method are adopted to analyze the reliability and weakness of the CTCS-3 system.

First, a physical architecture and data flow diagram of the CTCS-3 system are established according to the typical structure and functions of the CTCS-3 system. Second, the dynamic fault tree of the CTCS-3 system is constructed. Considering the prior probability of the bottom event and the existence of dynamic redundancy, the dynamic fault tree is transformed into a Bayesian net. The reliability of the CTCS-3 system is carried out based on the prior probability and the weakness that affects the reliability of the system based on the posterior probability is also analyzed by the Bayesian network. Finally, it is disclosed that the impact of the on-board subsystem on the reliability of the CTCS-3 system is generally greater than that of the ground subsystem. The two weakest modules in the onboard subsystem are the driver-machine interface (DMI) and balise transmission module (BTM) and the weakest one in the ground subsystem is Balise. The analysis results are generally consistent with the malfunctions in the field operation of China’s high-speed railway.

(1) By reasoning, the reliability of the train operation control system in the CTCS-3 operating mode meets the standard requirements.

(2) Through backward reasoning, it is found that the failure of the onboard subsystem leads to a greater probability of failure of the train control system.

(3) The DMI, BTM and automatic train protection computer unit modules are weak components in the onboard subsystem. Vital digit input&output, train interface unit and train security gateway are rarely involved in previous research, the result in this paper shows that these three modules are also weak components in the subsystem, which requires attention.

Lean Thinking is an operation management discipline which aims to identify, map and analyse the activities forming a process to detect “value waste” and outline the most effective flow of activities to execute in sequence. Process mapping is often developed in lean projects through the use of the Value Stream Map (VSM). Like many other management tools, the VSM adopts a static and non-systemic perspective in the representation of an organizational process. This may result in the implementation of Lean projects inconsistent with the overall organizational long-term strategy, thus leading to dysfunctional performance. In order to overcome this limit, the paper suggests combining VSM with System Dynamics (SD) modelling.

The paper is based on a review of the literature on VSM. This review is matched with an analysis of SD modelling principles aimed at explaining the practical and theoretical contribution of this approach to operation and strategic management practices. An illustrative case study is then provided to explore the practical implications of the proposed approach.

Our results show that SD modelling provides robust methodological support to VSM and Lean Thinking due to its inner characteristics, namely: simulation, systemic view, explicit link between system structure and behaviour and effective visual representation.

This research proposes a novel approach to design VSMs aimed at fostering a strategic perspective in Lean Thinking applications. Such an approach connects two fields of research and practice – i.e. VSM and SD modelling – which have traditionally been kept separated or, at least, partially combined for specific organizational sub-systems, thereby neglecting a broader strategic view of the entire process system.

This study aims to investigate how dynamic tensions between performance measurement system (PMS) uses enable organizations to achieve both exploitation and exploration and enhance firm performance.

The authors collected survey data on 153 Italian companies. Scales for each construct were validated through an exploratory factor analysis. Data on firm performance were cross-validated by using lagged accounting data. The authors tested our hypotheses using hierarchical ordinary least squares regressions, together with bootstrapping procedures for the test on mediation.

A diagnostic use of PMS has a positive association with both exploitation – e.g. reductions in total costs and lead times – and exploration, e.g. introduction of new products and extension of product ranges. The dynamic tension created by a joint diagnostic and interactive use has the strongest association with organizational ambidexterity, measured as the multiplicative interaction between exploration and exploitation.

If an organization or business unit is mainly pursuing exploitative goals, a mainly diagnostic use of PMS would be most suitable. If goals are both exploitative and explorative, a mix of diagnostic and interactive uses would be most effective.

This research helps reconcile conflicting views in the literature. The diagnostic use of PMS, far from acting as a “negative force,” appears to be necessary to guide opportunity search and to establish an appropriate scope for exploration-related activities. The authors’ focus on the uses of PMSs shows that ambidexterity is achieved through managerial capability, rather than just through the introduction of systems and structures.

The purpose of this paper is to propose a new simplified numerical model, based on a very compact semi-empirical formulation, able to simulate the fluid dynamics behaviors of an electrohydraulic servovalve taking into account several effects due to valve geometry (e.g. flow leakage between spool and sleeve) and operating conditions (e.g. variable supply pressure or water hammer).

The proposed model simulates the valve performance through a simplified representation, deriving from the linearized approach based on pressure and flow gains, but able to evaluate the mutual interaction between boundary conditions, pressure saturation and leak assessment. Its performance was evaluated comparing with other fluid dynamics numerical models (a detailed physics-based high-fidelity one and other simplified models available in the literature).

Although still showing some limitations attributable to its simplified formulation, the proposed model overcomes several deficiencies typical of the most common fluid dynamic models available in the literature, describing the water hammer and the nonlinear dependence of the delivery differential pressure with the spool displacement.

Although still based on a simplified formulation with reduced computational costs, the proposed model introduces a new nonlinear approach that, approximating with suitable precision the pressure-flow fluid dynamic characteristic of a servovalve, overcomes the shortcomings typical of such models.

This study examines unexplored horizontal accountability types between public, private and third sector actors within a hybrid organization. The case organization was applying a novel alliance model to generate service paths for heterogeneous clientele consuming cultural, educational, health and social services. It was first to do so in Finland.

This research is on a case study that used documents and interviews to examine the design of the horizontal accountability. The descriptive analysis focused on identifying what type of formal accountability system was designed (i.e. who is the account holder, and who is accountable and for what and why).

An imbalanced accountability system was identified because accountability obligations were unevenly distributed between public, private and third sector actors. The private sector was the most accountable for performance, and the third sector (i.e. voluntary sector) was the least accountable. As account holders, the public, private and third sector actors were judging their conduct as account providers. This created a biased horizontal accountability system. The hybrid's accountability system was dynamic because the contracts made to establish the hybrid included opportunities to change horizontal accountability if future changes to the external environment affect too drastically the potential to achieve the hybrid's goals.

Three new concepts are proposed for studying dysfunctional accountability systems: dynamic, biased and horizontally imbalanced accountability.

Transport logistics systems in companies with additional public service roles are complex and could benefit from new approaches to performance management. Existing approaches tend to be fragmented; thus, the purpose of this paper is to integrate balanced performance measures, a dynamics model, and the problem-solving method into a new model.

An integrated framework is developed by reviewing literature and synthesising attributes of performance measurement systems, system dynamics and problem-solving methods. The framework is then applied to a multiple-role company’s sea transportation system. The study uses statistical methods to identify performance indicators, management interviews with document study to develop a dynamics model, and simulation methods to formulate an improvement plan.

The performance measurement design stage allowed for the identification of balanced, aligned performance indicators, while the system dynamics model illuminated the impact of the system components’ interrelationships on performance output. The problem-solving method allowed for analysis of system performance, identification of constraints and formulation of a performance improvement plan.

This framework can help transport logistics system stakeholders in multiple-role companies avoid silo thinking, misaligned performance objectives, local optima and short-term solutions.

This study contributes to the existing body of research by introducing a novel framework integrating performance measurement, system dynamics and the problem-solving method. It also addresses a theoretical gap by showing how interconnecting components of sea transportation systems affect transport logistics performance.