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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.

This study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers.

The emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert's imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis.

A real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures.

This study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account.

Our contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.

This study delves into how corporations make decisions about influencer marketing. Specifically, it examines the differences between human influencers, who carry the risk of scandals, and virtual influencers, a new and unpredictable realm, regarding their integration with social media platforms.

Using game theory and empirical data, the study explores crucial factors in influencer marketing, including influencer quality, reputation repair costs and the probability of R&D failures.

This study suggests that companies favor human influencers when the risk of scandal is low. However, competing companies switch to virtual influencers at different intervals as this risk increases. The costs, likelihood of scandals and competition intensity all play a role in a company's decision-making regarding technology management. Additionally, a higher chance of R&D failure can motivate a company to invest more in R&D to gain a competitive advantage over rivals that may suffer failures.

This study provides insights into how corporations manage social media influencer marketing in the digital age. It contributes to marketing theory and technology management decisions by offering a fresh perspective on the relationship between corporate reputation and influencer marketing strategy.

This study offers valuable perspectives into a relatively uncharted area of marketing strategy. It employs game theory and empirical analysis to introduce a fresh method of comprehending the dynamics of influencer marketing, its impact on corporate reputation management and its interaction with social media.

A progressive hybrid censoring scheme (PHCS) becomes impractical for ensuring dependable outcomes when there is a low likelihood of encountering a small number of failures prior to the predetermined terminal time T. The generalized progressive hybrid censoring scheme (GPHCS) efficiently addresses to overcome the limitation of the PHCS.

In this article, estimation of model parameter, survival and hazard rate of the Unit-Lindley distribution (ULD), when sample comes from the GPHCS, have been taken into account. The maximum likelihood estimator has been derived using Newton–Raphson iterative procedures. Approximate confidence intervals of the model parameter and their arbitrary functions are established by the Fisher information matrix. Bayesian estimation procedures have been derived using Metropolis–Hastings algorithm under squared error loss function. Convergence of Markov chain Monte Carlo (MCMC) samples has been examined. Various optimality criteria have been considered. An extensive Monte Carlo simulation analysis has been shown to compare and validating of the proposed estimation techniques.

The Bayesian MCMC approach to estimate the model parameters and reliability characteristics of the generalized progressive hybrid censored data of ULD is recommended. The authors anticipate that health data analysts and reliability professionals will get benefit from the findings and approaches presented in this study.

The ULD has a broad range of practical utility, making it a problem to estimate the model parameters as well as reliability characteristics and the significance of the GPHCS also encourage the authors to consider the present estimation problem because it has not previously been discussed in the literature.

The purpose of this paper is to examine the antecedents of organizational ambidexterity of foreign ventures in an emerging market. Organizational ambidexterity, the simultaneous pursuit of exploration and exploitation, represents a key innovation strategy. Yet, the driving factors of such innovation strategies for foreign ventures competing in emerging markets have been underresearched. In this study, unpacking the construct of organizational ambidexterity into two dimensions (i.e. the combined dimension [CD] and the balance dimension [BD]), the authors aim to investigate how firm-level and industry-level factors drive foreign ventures in pursuing exploration and exploitation and maximizing the benefits of both.

This study adopts the hierarchical multiple regression approach using a sample of foreign ventures operating in high-tech manufacturing industries in China.

The authors find that the firm-level factor of strategic flexibility leads positively to the CD of organizational ambidexterity, whereas the industry-level factor of technological turbulence has a significantly positive impact on the BD.

This study provides important insights into the driving factors of organizational ambidexterity for foreign ventures competing in emerging markets.

Drawing on the social exchange theory, the authors extend the high-reliability literature by examining employees' subjective experience of working in contexts engaging in mindful organizing (MO). Ultimately, they ask the question about how MO affects employees' attitudes and behavior toward work and organization, such us organizational commitment (OC), motivation to work and organizational citizenship behavior (OCB), in ordinary business settings. The purpose of this paper is to address this issue.

The authors surveyed 307 employees from various industries, using paper-and-pencil questionnaires. A series of hierarchical regression analyses and structural equation modeling were performed to test our hypotheses.

The authors found that MO is positively related to employees' affective and normative commitment to an organization, and that affective commitment is positively related to motivation to work and OCB. The study also reveals that the affective commitment has a partially mediating role in the MO – motivation and MO – OCB relations. Although several researchers argue that the effectiveness of MO may be higher in an uncertain environment, the authors’ study indicates that the environment does not moderate the relationship between MO and OC.

To the best of the authors’ knowledge, this study is one of the first attempts to explore the effects of MO in a traditional (i.e. nonhigh reliability) business context. Furthermore, their findings prove that MO not only leads to higher reliability and greater safety, as previous studies show, but it also positively affects performance-related attitudes and behavior.

International construction joint ventures (ICJVs) implementation is plagued with several barriers, full understanding of which is still lacking due to a lack of an in-depth exploration of them, particularly in developing countries. To fill this knowledge gap, this study aims to investigate the critical barriers to the success of ICJVs hosted in developing countries by examining the Ghanaian case.

This study builds on a previous study that identified 37 barriers factors to ICJVs success via a systematic literature review. Through expert interviews, 34 potential barriers were identified, and a two-round survey was conducted with 84 ICJVs practitioners in Ghana. The data collected was analyzed using the combination of a multidimensional fuzzy logic method and confirmatory factor analysis.

Results showed that 22 barriers were critical. The top five most critical barriers were “lack of preparedness to accept company philosophy,” “competing objectives,” “opportunistic behavior of parties,” “conflicts” and “lack of management control.” Furthermore, the results uncovered and confirmed five significant underlying components for the 22 critical barriers, namely, organizational-related, cultural-related, knowledge-related, individual-related and logistics-related barriers.

The findings could be useful to ICJVs practitioners and policymakers in developing suitable strategies for the successful implementation of ICJVs. Further, foreign firms aiming to execute and promote ICJVs in Ghana could have prior knowledge of the critical barriers and prepare for them.

This study empirically analyzed the individual levels of barriers criticalities in ICJVs context and from a specific-country perspective – the developing country of Ghana – rather than in the context of construction joint ventures and from a cross-country perspective in extant studies.

Organizations working in high-hazard environments contribute significantly to modern society and the economy, not only for the valuable resources they hold but also for the indispensable products and services they provide, such as power generation, transportation and defense weapons. Therefore, the main purpose of this study is to develop a framework that outlines future research on systems safety and provides a better understanding of how organizations can effectively manage hazard events.

In this research, we developed the high hazard theory (HHT) and a theoretical framework based on the grounded theory method (GTM) and the integration of three established theoretical perspectives: normal accident theory (NAT), high reliability theory (HRT) and resilience engineering (RE) theory.

We focused on the temporal aspect of accidents to create a timeline showing the progression of hazard events and the factors contributing to safety and hazards in organizations. Given the limitations of the previous theories in providing a coherent explanation of hazard event escalation in high-hazard organizations (HHOs), we argue that the highlighted theories can be more complementary than contradictory regarding their standpoints on disasters and accident prevention.

A proper appreciation of the hazard nature of organizations can help reduce their susceptibility to failure, prevent outages and breakdowns of systems, identify areas for improvement and develop strategies to enhance performance.

By developing HHT, we contribute to systems safety research by developing a new, refined theory and enrich the theoretical debate. We also expand the understanding of scholars and practitioners about the characteristics of organizations working in high-hazard environments.

This research aims to investigate critical success factors, barriers and initiatives of total productive maintenance (TPM) implementation in selected manufacturing industries in Addis Ababa, Ethiopia.

This study built and looked into a conceptual research framework. The potential barriers and success factors to TPM implementation have been highlighted. The primary study techniques used to collect relevant data were a closed-ended questionnaire and semi-structured interview questions. With the use of SPSS version 23 and SmartPLS 3.0 software, the data were examined using descriptive statistics and the inferential Partial Least Square Structural Equation Modeling (PLS-SEM) techniques.

According to the results of descriptive statistics and multivariate analysis using PLS-SEM, the case manufacturing industries' TPM implementation initiative is in its infancy; break down maintenance is the most widely used maintenance policy; top managers are not dedicated to the implementation of TPM; and there are TPM pillars that have been weakly and strongly addressed by the case manufacturing companies.

The small sample size is a limitation to this study. It is therefore challenging to extrapolate the research findings to other industries. The only manufacturing KPI utilized in this study is overall equipment effectiveness (OEE). It is possible to add more parameters to the manufacturing performance measurement KPI. The relationships between TPM and other lean production methods may differ from those observed in this cross-sectional study. Longitudinal experimental studies and in-depth analyses of TPM implementations may shed further light on this.

Defining crucial success factors and barriers to TPM adoption, as well as identifying the weak and strong TPM pillars, will help companies in allocating their scarce resources exclusively to the most important areas. TPM is not a quick solution. It necessitates a change in both the company's and employees' attitude and their values, which takes time to bring about. Hence, it entails a long-term planning. The commitment of top managers is very important in the initiatives of TPM implementation.

This study is unique in that, it uses a new conceptual research model and the PLS-SEM technique to analyze relationships between TPM pillars and OEE in depth.