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This paper aims to develop a dynamic civil facility degradation prediction model to forecast the reliability performance tendency and remaining useful life under imperfect maintenance based on the inspection records and the maintenance actions.

A real-time hidden Markov chain (HMM) model is proposed in this paper to predict the reliability performance tendency and remaining useful life under imperfect maintenance based on rare failure events. The model assumes a Poisson arrival pattern for facility failure events occurrence. HMM is further adopted to establish the transmission probabilities among stages. Finally, the simulation inference is conducted using Particle filter (PF) to estimate the most probable model parameters. Water seals at the spillway hydraulic gate in a Taiwan's reservoir are used to examine the appropriateness of the approach.

The results of defect probabilities tendency from the real-time HMM model are highly consistent with the real defect trend pattern of civil facilities. The proposed facility degradation prediction model can provide the maintenance division with early warning of potential failure to establish a proper proactive maintenance plan, even under the condition of rare defects.

This model is a new method of civil facility degradation prediction under imperfect maintenance, even with rare failure events. It overcomes several limitations of classical failure pattern prediction approaches and can reliably simulate the occurrence of rare defects under imperfect maintenance and the effect of inspection reliability caused by human error. Based on the degradation trend pattern prediction, effective maintenance management plans can be practically implemented to minimize the frequency of the occurrence and the consequence of civil facility failures.

First is to develop the time truncated median control chart for the Rayleigh distribution (RD) and generalized RD (GRD), respectively. Second is to evaluate the performance of the proposed attribute control chart which depends on the average run length (ARL) and third is to include real life examples for application purpose of the proposed attribute control chart.

(1) Select a random sample of size n from each subgroup from the production process and put them on a test for specified time t, where t = ? × µe. Then, count the numbers of failed items in each subgroup up to time t. (2) Step 2: Using np chart, define D = np, the number of failures, which also a random variable follows the Binomial distribution. It is better to use D = np chart rather than p chart because the authors are using number of failure rather than proportion of failure p. When the process is in control, then the parameters of the binomial distribution are n and p0, respectively. (3) Step 3: The process is said to be in control if LCL = D = UCL; otherwise, the process is said to be out of control. Hence, LCL and UCL for the proposed control chart.

From the findings, it is concluded that the GRD has smaller ARL values than the RD for specified values of parameters, which indicate that GRD performing well for out of control signal as compared to the RD.

This developed control chart is applicable when real life situation coincide with RD and GRD.

Researcher can directly use presented study and save consumers from accepting bad lot and also encourage producers to make good quality products so that society can take benefit from their products.

This article dealt with time truncated attribute median control chart for non-normal distributions, namely, the RD and GRD, respectively. The structure of the proposed control chart is developed based on median lifetime of the RD and GRD, respectively.

This study explores whether herd behavior exists for equity crowdfunding investors in China and whether this herding is rational.

Based on signaling theory and social learning theory, two hypotheses were proposed. This study employed two approaches to collect data. First, this paper analyzed 3,041 investments on an equity crowdfunding platform in China using Python programming and built a panel data model. Second, based on a unique experiment design, this study conducted several relevant herd behavior simulation experiments.

We found that investors in the Chinese equity crowdfunding market exhibit herd behavior and that this herding is rational. Project attributes play a negative role in moderating the relationship between the current investment amount and cumulative investments. Experimental results further support our findings.

This study contributes to the emerging literature on herding in crowdfunding by focusing on equity crowdfunding in China. We are the first to explore whether Chinese equity crowdfunding investors exhibit rational herding behavior. The study is also original in applying social learning theory to equity crowdfunding and in using both actual crowdfunding campaigns and experimental approaches to collect data. This study has valuable implications to practice.

Users often struggle to select choosing among similar online services. To help them make informed decisions, it is important to establish a service reputation measurement mechanism. User-provided feedback ratings serve as a primary source of information for this mechanism, and ensuring the credibility of user feedback is crucial for a reliable reputation measurement. Most of the previous studies use passive detection to identify false feedback without creating incentives for honest reporting. Therefore, this study aims to develop a reputation measure for online services that can provide incentives for users to report honestly.

In this paper, the authors present a method that uses a peer prediction mechanism to evaluate user credibility, which evaluates users’ credibility with their reports by applying the strictly proper scoring rule. Considering the heterogeneity among users, the authors measure user similarity, identify similar users as peers to assess credibility and calculate service reputation using an improved expectation-maximization algorithm based on user credibility.

Theoretical analysis and experimental results verify that the proposed method motivates truthful reporting, effectively identifies malicious users and achieves high service rating accuracy.

The proposed method has significant practical value in evaluating the authenticity of user feedback and promoting honest reporting.

The purpose of this study is to investigate whether repeated alliances between two members of a patent pool boost enterprise innovation. Furthermore, this paper intends to determine whether the innovation performance becomes higher or lower based on the partnership characteristics.

In this empirical study, hierarchical regression is used to analyze the longitudinal data obtained from 12 patent pools managed by MPEG LA during a time period ranging from 2006 to 2018. The members of patent pools comprise research institutions, firms and universities. Research analyses are performed based on a sample of 68,400 member pairs who had established repeated alliances. The information regarding such pairs is gathered from public databases.

Repeated alliances positively correlate with enterprise innovation performance in patent pools; this performance is higher when the two enterprises have exploratory collaborations. Conversely, the performance is lower when the partners have a similar technology base and are engaged in a technological competition (competitive learning and patent litigation). Moreover, the performance is lower when one partner demonstrates higher network centrality and richer structural holes than the other partner.

Patent pools play an instrumental role in eliminating patent-licensing barriers, thereby allowing mutual acquisition of complementary technologies, and cooperatively strengthening technology development. From the perspective of theories of coopetition, knowledge management and social network, this study explores the impact of patent pools on enterprise innovation performance and ascertains the moderating roles of technology coopetition, technology similarity and network position, thereby expanding the scope of innovation effect in the context of patent pools.

To adapt to the rapidly changing market environment, firms must constantly adjust and change their knowledge base to develop new technologies. The purpose of this paper is to analyze the improvement path of firms’ breakthrough innovation from the perspective of knowledge recombination in the context of dynamic change in the knowledge base. By analyzing the influencing mechanism of environmental dynamism on the relationship between the two, this paper provides a theoretical foundation for managers to make knowledge recombination decisions under a dynamic external environment while further enriching the firm’s innovation achievements.

Using data from 220 manufacturing firms listed on the Shanghai and Shenzhen A-share stock from 2010 to 2018, an extensive panel data set was constructed to investigate the effect of knowledge recombination, which was divided into recombination creation and recombination reuse, on firms’ breakthrough innovation. In addition, the authors differentiated environmental dynamism as market dynamism and technological dynamism and then examined its moderating role in the above relationships.

The research results show that various recombination behaviors of knowledge elements have a differentiated effect on firms’ breakthrough innovation presented as follows: Knowledge recombination creation is significantly positively correlated with firms’ breakthrough innovation, while knowledge recombination reuse is significantly negatively correlated with firms’ breakthrough innovation. In addition, environmental dynamism has a considerable moderating effect between knowledge recombination and firms’ breakthrough innovation further, emphasizing that the moderating effect on different types of knowledge recombination behaviors is significantly distinct.

First, given that this study refers to several Chinese noted databases to collect second-hand data for empirical analysis, future research could use first-hand data by collecting questionnaire survey and interview to provide a more practical and detailed research conclusion. Second, the authors focused on the contextual variable to explore the moderating role of environmental dynamism on the relationship between knowledge recombination and breakthrough innovation. Nevertheless, the indirect effects of other internal factors were not discussed. The authors advocate future studies to involve other moderators from employee social and phycological perspectives, such as trust in colleagues in the proposed theoretical models in this study.

This study is conducive for managers to attach great attention to knowledge management practices in the firm and to understand the critical role of knowledge recombination in affecting innovation performance under dynamic environmental changes. Moreover, this study provides practical guidance and serves as a reference for firms to strengthen their knowledge recombination ability as full utilization of existing knowledge elements and exploration of new knowledge values.

Primarily, from the perspective of dynamic changes in the knowledge base, this paper explores how the knowledge recombination behaviors affect firms’ breakthrough innovation, thereby enriching and extending the relationship theory between knowledge recombination capabilities and breakthrough innovation, while new and valuable ideas are provided in the study of issues related to the firms’ breakthrough innovation; Moreover, this study analyzes the moderating effects of diverse types of environmental dynamism on the relationship between knowledge recombination and firms’ breakthrough innovation from a multi-dimensional perspective proposing that the moderating effects of environmental dynamism on different knowledge recombination behaviors are distinct.

Spare Parts Management (SPM) and Industry 4.0 has proven their importance. However, employment of Industry 4.0 solutions for SPM is at emerging stage. To address the issue, this article is aimed toward a systematic literature review on SPM in Industry 4.0 era and identification of research gaps in the field with prospects.

Research articles were reviewed and analyzed through a content-based analysis using four step process model. The proposed framework consists of five categories such as Inventory Management, Types of Spares, Circularity based on 6Rs, Performance Indicators and Strategic and Operational. Based on these categories, a total of 118 research articles published between 1998 and 2022 were reviewed.

The technological solutions of Industry 4.0 concepts have provided numerous opportunities for SPM. Industry 4.0 hi-tech solutions can enhance agility, operational efficiency, quality of product and service, customer satisfaction, sustainability and profitability.

The review of articles provides an integrated framework which recognizes implementation issues and challenges in the field. The proposed framework will support academia and practitioners toward implementation of technological solutions of Industry 4.0 in SPM. Implementation of Industry 4.0 in SPM may help in improving the triple bottom line aspect of sustainability which can make significant contribution to academia, practitioners and society.

The examination uncovered a scarcity of research in the intersection of SPM and Industry 4.0 concepts, suggesting a significant opportunity for additional investigative efforts.

In the extant research on online knowledge communities (OKCs), little attention has been paid to the influence of membership fluidity on the coevolution of the social and knowledge systems. This article aims to fill this gap.

Based on the attraction-selection-attrition (ASA) framework, this paper constructs a simulation model to study the coevolution of these two systems under different levels of membership fluidity.

By analyzing the evolution of these systems with the vector autoregression (VAR) method, we find that social and knowledge systems become more orderly as the coevolution progresses. Furthermore, in communities with low membership fluidity, the microlevel of the social system (i.e. users) drives the coevolution, whereas in communities with high membership fluidity, the microlevel of the knowledge system (i.e. users' views) drives the coevolution.

This paper extends the application of the ASA framework and enriches the literature on membership fluidity of online communities and the literature on driving factors for coevolution of the social and knowledge systems in OKCs. On a practical level, our work suggests that community administrators should adopt different strategies for different membership fluidity to efficiently promote the coevolution of the social and knowledge systems in OKCs.

The “chiralisation” of Euclidean polygonal tessellations is a novel, recent method which has been used to design new auxetic metamaterials with complex topologies and improved geometric versatility over traditional chiral honeycombs. This paper aims to design and manufacture chiral honeycombs representative of four distinct classes of 2D Euclidean tessellations with hexagonal rotational symmetry using fused-deposition additive manufacturing and experimentally analysed the mechanical properties and failure modes of these metamaterials.

Finite Element simulations were also used to study the high-strain compressive performance of these systems under both periodic boundary conditions and realistic, finite conditions. Experimental uniaxial compressive loading tests were applied to additively manufactured prototypes and digital image correlation was used to measure the Poisson’s ratio and analyse the deformation behaviour of these systems.

The results obtained demonstrate that these systems have the ability to exhibit a wide range of Poisson’s ratios (positive, quasi-zero and negative values) and stiffnesses as well as unusual failure modes characterised by a sequential layer-by-layer collapse of specific, non-adjacent ligaments. These findings provide useful insights on the mechanical properties and deformation behaviours of this new class of metamaterials and indicate that these chiral honeycombs could potentially possess anomalous characteristics which are not commonly found in traditional chiral metamaterials based on regular monohedral tilings.

To the best of the authors’ knowledge, the authors have analysed for the first time the high strain behaviour and failure modes of chiral metamaterials based on Euclidean multi-polygonal tessellations.

This study aims to examine the impact of corporate governance (CG) on anti-corruption disclosure (A-CD), paying particular attention to the FTSE 100. Notably, it examines how board and audit committees’ characteristics affect the quantity and quality of anti-corruption disclosure.

Data from FTSE 100 firms, spanning the period from 2014 to 2020, were analysed using the regression of the Poisson fixed effect and GEE analyses.

The findings show that gender diversity, audit committee expertise and the independence of the audit committee are positively associated with both quantity and quality of anti-corruption disclosure. Notably, no statistically significant relationships were identified between anti-corruption disclosure and factors such as board size, role duality or board meetings.

The findings provide valuable insights for decision-makers and regulatory bodies, shedding light on the elements that compel UK companies to enhance their anti-corruption disclosure and governance protocols to alleviate corruption and propel efforts towards ethical behaviour.

This study makes a notable contribution to the sparse body of evidence by examining the influence of board and audit committee attributes on anti-corruption disclosure subsequent to the implementation of the UK Bribery Act in 2010. Specifically, to the best of the authors’ knowledge, this study assesses for the first time the impact of board and audit committee mechanisms on both the quantity and quality of anti-corruption disclosure.