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To date, the literature has usually assumed that a universal approach to resilience is appropriate in which different resilience capabilities are equally important for all organizations independent of contextual characteristics. In contrast this study investigates if production process characteristics affect resilience capabilities in terms of redundancy, flexibility, agility and collaboration.

An in-depth exploratory multiple case study was carried out in eight companies across different industries. Data were gathered through multiple interviews with key informants in each company.

The authors find differences in, and trade-offs between, resilience capabilities and practices related to redundancy, agility and collaboration induced by the different configurations of production system characteristics: especially between discrete and process industries. Further, a major influential characteristic is the production strategy employed (make-to-stock or make-to-order) which stresses or limits collaboration and redundancy.

This is one of the first studies to explore the effects of production system characteristics as a major contingency factor on the resilience capabilities of an organization. As such it provides valuable insights into the development of a more nuanced contingency approach to how organizations can build resilience and employ specific practices that fit their situation.

This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected environment.

In this paper, an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed for connected EVs. The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving. Moreover, this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.

To illustrate the performance for the EEDC-HRL, the controlled EV was trained and tested in various traffic flow states. The experimental results demonstrate that the proposed technique can effectively improve energy efficiency, without sacrificing travel efficiency, comfort, safety and lane-changing performance in different traffic flow states.

In light of the aforementioned discussion, the contributions of this paper are two-fold. An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs. A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

Motivated to know more about the internal means through which accountability for sustainability takes shape within organisations (in what ways and by whom), this paper aims to explore how accountability for sustainability is constructed within an organisation during a process of establishing a control system for sustainability.

This paper adopts a qualitative case study approach of a decentralised industrial group, operating mainly in Scandinavia, between 2017 and 2020. Both primary and secondary data are used (e.g. document analyses, semi-structured interviews, informal conversations and site visits) to inform the findings and analysis.

The findings reveal a multi-faceted path towards accountability for sustainability that involves several concerns and priorities at organisational and individual levels, resulting in a separate sustainability control systems within each subsidiary company. Although hierarchical structures for accountability exist, socialising accountability activities are needed to (further) mobilise sustainable accounts.

Successful sustainable control systems require employees making sense of formalised accountability instruments (e.g. policies and procedures) to establish their roles and responsibilities in organisations.

This paper proposes socialisation processes as important for driving forward sustainability solutions.

This study elaborates on the internal accountability dynamic for the construction of sustainable accounts. Its novelty is built upon the interaction of hierarchical and socialising accountability forms as necessary for establishing a control system for sustainability. It furthermore illustrates the relationship between the external and internal pathways of accountability.

This study aims to address how the ISO 14001 standardisation and certification process improves substantive performance in small to medium-sized enterprises (SMEs) through the development of an environmental management control system (EMCS).

A qualitative cross-case interview design with those responsible for the implementation of an environmental management system (certified to ISO 14001) in SMEs is adopted to inductively “theorise” the EMCS.

The design and monitoring of environmental controls are often beyond the scope of the SMEs’ top management team and include extra-organisational dimensions such as the external audit and institutional requirements. This suggests more complex control pathways for SMEs to produce EMCS that primarily function as packages and are broader than the analytical level of the firm. Here, controlling for environmental performance exists at strategic and operational levels, as well as beyond the SMEs’ boundaries.

Various internal controls are put forward for SME owner-managers to meet environmental targets (e.g. gamification and interpersonal communication strategies). This builds upon a broader accountability perspective wherein formalised hierarchical control is only one route for ensuring sustainable action within the ISO 14001-certified SMEs.

This study contributes to a more sustainable society through developing an understanding of how environmental sustainability is substantively managed by SMEs to improve performance for current and future generations.

This paper, to the best of the author’s knowledge, is one of the first to establish how SMEs control for environmental sustainability from empirically derived evidence. In doing so, it provides an example of the EMCS for the SME context.

This modeling facilitates the determination of control responses (or possibly reconfiguration) upon such events and the identification of which segments of the pipeline can continue to function uninterrupted. Based on this modeling, an algorithm is presented to implement the control responses and to establish this determination. In this work, the authors propose using Message Queuing Telemetry Transport (MQTT), which is an integrated method to perform the system-wide control based on message exchanging among local node controllers (agents) and the global controller (broker).

Complex manufacturing lines in industrial plants are designed to accomplish an overall task in an incremental mode. This typically consists of a sequence of smaller tasks organized as cascaded processing nodes with local controls, which must be coordinated and aided by a system-wide (global) controller. This work presents a logic modeling technique for such pipelines and a method for using its logic to determine the consequent effects of events where a node halts/fails on the overall operation.

The method uses a protocol for establishing communication of node events and the algorithm to determine the consequences of node events in order to produce global control directives, which are communicated back to node controllers over MQTT. The algorithm is simulated using a complex manufacturing line with arbitrary events to illustrate the sequence of events and the agents–broker message exchanging.

This approach (MQTT) is a relatively new concept in Cyber-Physical Systems. The proposed example of feed-forward is not new; however, for illustration purposes, it was suggested that a feed-forward be used. Future works will consider practical examples that are at the core of the manufacturing processes.

This paper aims to identify the interaction of different intervention strategies implemented in Malaysia towards flattening the curve of COVID-19 cases. Since the outbreak of COVID-19, many approaches were adopted and implemented by the Malaysian government. Some strategies gained quick wins but with negative unintended consequences after execution, whereas other strategies were slow to take effect. Learning from the previous strategies is pivotal to avoid repeating mistakes.

This paper presents the cause, effect of and connection among the implemented COVID-19 intervention strategies using systems thinking through the development of a causal loop diagram. It enables the visualisation of how each implemented strategy interacted with each other and collectively decreased or increased the spread of COVID-19.

The results of this study suggested that it is not only essential to control the spread of COVID-19, but also to prevent the transmission of the virus. The Malaysian experience has demonstrated that both control and preventive strategies need to be in a state of equilibrium. Focusing only on one spectrum will throw off the balance, leaving COVID-19 infection to escalate rapidly.

The developed feedback loops provided policy makers with the understanding of the merits, pitfalls and dynamics of prior implemented intervention strategies before devising other effective intervention strategies to defuse the spread of COVID-19 and prepare the nation for recovery.

The optimisation of forest fuels supply chain involves several entities actors, and particularities. To successfully manage these supply chains, efficient tools must be devised with the ability to deal with stakeholders dynamic interactions and to optimize the supply chain performance as a whole while being stable and robust, even in the presence of uncertainties. This work proposes a framework to coordinate different planning levels and event-based models to manage the forest-based supply chain. In particular, with the new methodology, the resilience and flexibility of the biomass supply chain is increased through a closed-loop system based on the system forecasts provided by a discrete-event model. The developed event-based predictive model will be described in detail, explaining its link with the remaining elements. The implemented models and their links within the proposed framework are presented in a case study in Finland and results are shown to illustrate the advantage of the proposed architecture.