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The purpose of this study is to propose an extended reliability method for an industrial motor drive by integrating the physics of failure (PoF).

Industrial motor drive systems (IMDS) are currently expected to perform beyond the desired operating conditions to meet the demand. The PoF of the subsystem affects its reliability under such harsh operating circumstances. It is crucial to estimate reliability by integrating PoF, which helps in understanding its impact and to develop a fault-tolerant design, particularly in such an integrated drive system. An integrated PoF extended reliability method for industrial drive system is proposed to address this issue. In research, the numerical failure rate of each component of industrial drive is obtained first with the help of the MIL-HDBK-217 military handbook. Furthermore, the mathematically deduced proposed approach is modeled in the GoldSim Monte Carlo reliability workbench.

From the results, for a 15% rise in integrated PoF, the reliability and availability of the entire IMDS dropped by 23%, resulting in an impact on mean time to failure (MTTF).

The integrated PoF of the motor and motor controller affects industrial drive reliability, which falls to 0.18 with the least MTTF (2.27 years); whose overall reliability of industrial drive drops to 0.06 if it is additionally integrated with communication protocol.

Through the use of the Markov Decision Model (MDM) approach, this study uncovers significant variations in the availability of machines in both faulty and ideal situations in small and medium-sized enterprises (SMEs). The first-order differential equations are used to construct the mathematical equations from the transition-state diagrams of the separate subsystems in the critical part manufacturing plant.

To obtain the lowest investment cost, one of the non-traditional optimization strategies is employed in maintenance operations in SMEs in this research. It will use the particle swarm optimization (PSO) algorithm to optimize machine maintenance parameters and find the best solutions, thereby introducing the best decision-making process for optimal maintenance and service operations.

The major goal of this study is to identify critical subsystems in manufacturing plants and to use an optimal decision-making process to adopt the best maintenance management system in the industry. The optimal findings of this proposed method demonstrate that in problematic conditions, the availability of SME machines can be enhanced by up to 73.25%, while in an ideal situation, the system's availability can be increased by up to 76.17%.

The proposed new optimal decision-support system for this preventive maintenance management in SMEs is based on these findings, and it aims to achieve maximum productivity with the least amount of expenditure in maintenance and service through an optimal planning and scheduling process.

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.

As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.

Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.

It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

In today’s information and knowledge society, it is indispensable for citizens to acquire the requisite digital and information literacy (IL) skills to search information independently to meet their multiple and diverse information needs. As a result of digitalisation in the world, development and acquisition of digital and information skills is critical even for students and learners to retrieve digitised and online information to meet or achieve their curriculum-related accomplishments. The purpose of this study is to investigate the status of the digital and information literacies in South Africa from 2016 to 2022.

This qualitative study used a scoping review approach to collect data from research articles, conference articles and textbooks on digital literacy and IL – published in the years ranging between 2016 and 2022 from Google Scholar.

The major findings revealed that majority of the citizens especially students and learners lack digital and IL skills to recognise when information is needed, to find, locate, evaluate and use the retrieved information to meet an information need in a particular situation or context. Practical implications of this study include the alignment of curricula towards information and communication technologies to face the everchanging digital information technologies.

The study used scoping literature review research where empirical studies were retrieved and selected to address the objectives. This study provided significant approaches regarding promoting information and digital literacies in developing countries such as South Africa.

The current paper extends previous studies on the match between CEO and firm and explores whether certain characteristics of young CEOs make them more desirable to young firms. Results in this paper will provide useful information to startup companies when they need to find managers leading the firms.

This study use a large sample of panel regression to study the match between CEOs and firm via a difference-in-differences approach.

The author finds that young firms hire a disproportionately higher percentage of young CEOs than established firms. Young firms led by young CEOs exhibit higher growth rates in sales and assets and invest more in capital expenditure and R&D activities than similar firms led by older CEOs. Young CEOs in young firms also receive higher compensation than both older CEOs working in young firms and young CEOs working in established firms.

There are many studies examining how CEO age affect their decision-making process. There are also many studies examining the differences between young firms and established firms. However, there is no study so far examining the intersection of the two questions above. Specifically, whether the differences between young vs established firms make certain characteristics of young CEOs beneficial to young firms.

This paper aims to identify the combination of innovation determinants driving the creation of innovative products amongst market leaders and market followers in food and beverage (F&B) firms.

This research is based on the case study methodology by using two types of data sources: (1) semi-structured interviews with industry experts and (2) in-depth interviews with managers. In addition, a questionnaire adapted from prior research was used to consider market and firm types.

Suggesting an integrated theoretical framework based on firm-based factors and market-based factors, this study identified a combination of determinants significantly impacting innovative products in the market. Specifically, these determinants are competition intensity and innovation capability (a combination of research and development (R&D) investment and marketing capabilities). The study also examined how these determinants vary depending on whether the firms are market leaders or market followers.

This research provides practical insights for managers working in the F&B industry by using case studies and exploring the determinants of developing innovative products. In doing so, suitable strategies can be selected according to the market and firm situations.

The originality of the study is shown by focussing on how different combinations of market and firm factors could be applied in creating successful innovative products in the food sector.

Cyber security has never been more important than it is today in an ever more connected and pervasive digital world. However, frequently reported shortages of suitably skilled and trained information system (IS)/cyber security professionals elevate the importance of delivering effective Security Education,Training and Awareness (SETA) programmes within organisations. Therefore, the purpose of this study is the questionable effectiveness of SETA programmes at changing employee behaviour and an absence of empirical studies on the critical success factors (CSFs) for SETA programme effectiveness.

This exploratory study follows a three-stage research design to give voice to practitioners with SETA programme expertise. Data is gathered in Stage 1 using semi-structured interviews with 20 key informants (the emergence of the CSFs), in Stage 2 from 65 respondents to a short online survey (the ranking of the CSFs) and in Stage 3 using semi-structured interviews with nine IS/cyber security practitioners (the emergence of the guiding principles). Using a multi-stage research design allows the authors to propose and evaluate the 11 CSFs for SETA programme effectiveness.

This study conducted a mean score analysis to evaluate the level of importance of each CSF within two independent groups of IS/cyber security professionals. This multi-stage analysis produces a ranked list of 11 CSFs for SETA programme effectiveness, while the difference in the rankings leads to the emergence of five CSF-specific guiding principles (to increase the likelihood of delivering an effective SETA programme within an organisational context). This analysis also reveals that most of the contradictions/differences in CSF rankings between IS/cyber security practitioners are linked to the design phase of the SETA programme life cycle. While two CSFs, “maintain quarterly evaluation of employee performance” (CSF-DS6) and “build security awareness campaigns” (CSF-EV1), represent the most significant contradiction in this study.

The 11 CSFs for SETA programme effectiveness, along with the five CSF-specific guiding principles, provide a greater depth of knowledge contributing to both theory and practice and lays the foundation for future studies. Therefore, the outputs of this study provide valuable insights on the areas that practice needs to get right to deliver effective SETA programmes.

Organizational resilience, defined by a firm’s speed in reaching a dynamic equilibrium after a shock and after the shocks are absorbed, and crisis management are critical in a global crisis. The concept of resilience is increasingly used in the economic press; nevertheless, few studies demonstrate empirically how firms became resilient and the lessons to be learned from it. Traditionally, the concept of resilience is approached as resistance in the face of a crisis. The authors go further by showing three-loop learning, which is part of a logic of innovation and regeneration. This study aims to examine how a business can regenerate itself by effectively managing the external threats and disruptions caused by a crisis. Also, this study deepens knowledge on learning process. The double-loop learning process is known in the literature as enabling firms to learn from unexpected events and react accordingly. The findings point out a third loop implying the co-invention of a new business model and a collective mindfulness of changes made.

Using longitudinal data, the authors investigate how the global crisis affects merger negotiations between two companies. This study analyzes the period of dialogue (negotiation) between the two entities with a view to carrying out a merger and then their withdrawal from the project during the pandemic, reshuffling the cards for each company. The negotiation period is not normally disclosed because of its highly confidential and strategic nature and it is therefore difficult for researchers to access merger operations at the negotiation stage. From this viewpoint, this case study was chosen because of the availability of generally inaccessible documentation.

This in-depth case study provides new insights on organizational resilience and the recovery capacity of a firm. The results underline four main triggers that a firm should develop in facing a major crisis: skills; credits; previous and historical relationships; and corporate culture. Recovery capacity depends on reactivity, flexibility, learning and regeneration. Finally, this study points out a three-loop learning experience that can be understood as a learning process in two steps to generate lasting and adaptive changes.

The limitations are those concerning a single case study.

This study highlights the ability to deal with unexpected events. First, this work identifies concrete items that can be perceived by managers as elements enabling a firm to develop resilience. Second, the results show main elements enabling this capacity as reactivity – both companies react quickly and effectively to disturbances to limit the impact on their performance; or flexibility – firms adapt their business model to deal with disruptions. Third, this work underlines a learning capacity process in three steps to recover capacity. This process stimulates creativity and innovation by the teams and stakeholders by placing them at the heart of the change.

This case provides a vivid illustration of firms’ adaptation to a rapidly evolving context because of a global crisis. Theoretical concepts and empirical findings from the literature are combined to present a single consistent picture.