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User-generated content (UGC) refers to semantic and behavioral traces created by users on various social media platforms. While several waves of platforms have come and gone, the long-term sustainability of UGC activities has become a critical question that bears significance for theoretical understanding and social media practices.

Based on a large and lengthy dataset of both blogging and microblogging activities of the same set of users, a multistate survival analysis was applied to explore the patterns of users' staying, switching and multiplatforming behaviors, as well as the underlying driving factors.

UGC activities are generally unsustainable in the long run, and natural attrition is the primary reason, rather than competitive switching to new platforms. The availability of leisure time, expected gratification and previous experiences drive users' sustainability.

The authors adopted actual behavioral data from two generations of platforms instead of survey data on users' switching intentions. Four types of users are defined: loyal, switcher, multiplatformer and dropout. As measured by the transitions among the four states, the different sustainability behaviors are thereby studied via an integrated framework. These two originalities bridge gaps in the literature and offer new insights into exploring user sustainability in social media.

The purpose is to theorize and empirically estimate the impact of the gendered nature of the offender-victim dyad and crime type on time to arrest.

Predictions regarding the impact of gendered offender-victim dyads and crime type on time to arrest are constructed by extending role congruity theory and tested using data from the FBI's National Incident-Based Reporting System across five crime types using dyadic-based event history methods.

The authors find strong empirical support that role expectations derived from the gender composition of offender-victim dyads and the masculinity of the crime type affect time to clearance.

This research is the first to theorize and empirically test the relative impact of role congruency and the relational nature of the offender-victim dyad in the adjudication process. Furthermore, the research shows that the construction of “normal crime” can be enhanced by applying a gendered and relational approach, based on social psychological theory, which is predictive of crime clearance.

Future research is required to validate the results for crimes where law enforcement has less discretion and are feminine typed.

The results imply that by accounting for the expectations generated by gender roles when applied to offender-victim dyads a casual mechanism is established that better organizes previously inconsistent results with respect to the impact of gender on time to clearance. Thus, the authors' utilization of role congruity theory of gender provides a more consistent explanation for inequalities in time to clearance that may be fruitful for evaluating other steps in the adjudication process.

The purpose of this study is to find the reliability of the three-component three-phased mission system, which can be repaired by considering the exponential distribution for repair and failure rates in the transitions between the phases based on states with Markov approach. Also, multilevel-phased mission systems are calculated based on states for partially working states.

The reliabilities of the repairable two-level and three-level three-component three-phased mission systems based on states are calculated with the Markov approach. The structure functions are obtained for each phase of the systems, and differential equations are created by the failure and repair of each working state component. These equations are solved using Laplace method.

Reliability values of two-level and three-level three-component three-phased systems with different failure, repair, and time intervals are calculated and compared. The intermediate states that multilevel systems handle differently from two-level systems provide a better investigation of the systems. So, these repairable systems offer transparent information in complex systems like transportation and energy, ensuring appropriate timing and cost for repair operations.

This study is original in terms of calculating the reliability of the repairable phased mission system based on the states using Markov method. It is also important in calculating the reliability of the repairable multilevel phased mission system based on states and making reliability comparisons according to different repair and failure rates, equal and different time intervals.

This study aimed to investigate how enteric pathogens and their biofilm populations on fresh produce survive according to time that contamination has occurred on leaves and contamination route: seed irrigation water.

Cress was contaminated in two different ways: contamination of seeds and irrigation water with 8-log MPN/mL bacterial load, Salmonella Newport, Escherichia coli O157:H7, O104:H4 or O78:H2. While contaminated seeds were cultivated for seed contamination, contaminated irrigation was applied at the end of each week to separate groups of samples obtained from cultivated surface-sterile seeds to understand how long these pathogens could survive until harvest.

The results indicated these pathogens survived until harvest, and formed biofilms on cress leaves grown using both contaminated seeds and irrigation water. No significant difference was observed among populations of Salmonella and E. coli groups in terms of survival (∼4.5–6.0 log MPN/g) and biofilm formation (∼4.4–5.7 log MPN/g) for contamination by seed. Also, SEM images revealed biofilm-like structures, the proofs of the attachment of these pathogens on leaf surfaces.

From our knowledge this is the first study focusing on the survival and biofilm formation of one Salmonella serotype (Newport) and three E. coli serotypes (O157:H7, O104:H4, and O78:H2), representing enterohemorrhagic and enteroaggregative E. coli pathogenic subgroups, under the same irrigation and growth schemes. Furthermore, this study mimics the contamination of seeds and irrigation water with sewage or wastewater and may shed light on contamination of fresh produce grown using poor wastewater treatment.

As an alternative poverty analysis approach, the purpose of this paper is to map the patterns of multiple deprivation in all 13 administrative regions of Namibia using the National Household Income and Expenditure Survey data.

Unsupervised statistical learning methods including the principal component analysis, k-means clustering and bivariate analysis were applied.

The results show that the multiple deprivation approach is a useful alternative in characterising poverty dynamics in the country. Specifically, the mapping shows that other dimensions of poverty such as access to utilities and services among other things are equally useful welfare indicators as they scored higher than income and consumption on discriminant ability.

Unpacking the multi-dimensionality aspect of poverty has drawn significant attention from development economists and continues to play a major role in policy formulation for developing countries. The study recommends buttressing of conventional income poverty measures with multiple deprivation approaches for a comprehensive picture on poverty issues.

The purpose of this paper is to provide a mapping of financial distress among consumers in Zimbabwe. To inform policy, it nuances the understanding of the level of financial distress and the precise location of the most distressed consumers in the country.

The study mapped financial distress among consumers on the ten provinces of Zimbabwe using credit repayment behavioural indicators from retail consumer loans data.

Findings showed widespread financial distress among consumers across the country with Matabeleland North and Matabeleland South provinces being the most affected, whilst Harare and Manicaland were better off. The study underscores the urgent need for an overhaul of the Zimbabwe’s haemorrhaging economy in order to restore dignity among consumers and relieve them of financial hardships.

The paper provides vital input for policy. Policy measures aimed at invigorating sustained economic growth, troubleshooting and revamping productivity, enhancing external competitiveness and creating employment across the country are desperately needed. Also, there is need for a functional consumer education and counselling entity to roll-out financial literacy programmes and counselling financially distressed obligors across this economically beleaguered country.

This research investigated the impacts of COVID-19 on construction enterprises and good practices adopted by the enterprises in reducing COVID-19 risks. The Sendai Framework (TSF) is widely accepted as a strategic roadmap to reduce disaster risks throughout the life cycle of a disaster. As such, with the aim of enhancing the resilience of Australian construction enterprises, the identified good practices were mapped with TSF priorities to consolidate COVID-19 risk reduction practices that can be adopted by Australian construction enterprises.

Case study research approach was used, and three case studies were conducted with small, medium and large construction enterprises. Small, medium and large enterprises were selected based on the Australian Bureau of Statistics classification of the business size. Data were collected through semi-structured interviews conducted with three executive members from the three enterprises. Data were analysed using content analysis.

The study found that construction enterprises faced demand and supply side impacts. Infrastructure projects, funded by public sector clients and larger enterprises were least affected. Investments and demand for residential and other building projects were reduced by private sector clients, affecting small and medium enterprises. Findings also show that the construction enterprises adopted good practices in identifying, managing, investing on resilience and recovery that align with TSF priorities. All three enterprises agreed on some common good practices on risk identification, risk management and effective recovery. Different views were shared on investments related to disaster resilience.

This study contributes to mitigate the COVID-19 impacts on construction enterprises and subsequent economic and social impacts.

This research found how Australian construction enterprises survived during COVID-19. The study adopted TSF to construction and COVID-19 context while consolidating COVID-19 risk reduction practices.

While steady-state analysis is useful, it does not consider the inherent transient characteristics of repairable systems' behavior, especially in systems that have relatively short life spans, or when their transient behavior is of special concern such as the motivating example used in this paper, military systems. Therefore, a maintenance policy that considers both transient and steady-state availability and aims to achieve the best trade-off between high steady-state availability and rapid stabilization is essential.

This paper studies the transient behavior of system availability under the Kijima Type II virtual age model. While such systems achieve steady-state availability, and it has been proved that deploying preventive maintenance (PM) can significantly improve its steady-state availability, this improvement often comes at the price of longer and increased fluctuating transient behavior, which affects overall system performance. The authors present a methodology that identifies the optimal PM policy that achieves the best trade-off between high steady-state availability and rapid stabilization based on cost-availability analysis.

When the proposed simulation-based optimization and cost analysis methodology is applied to the motivating example, it produces an optimal PM policy that achieves an availability–variability balance between transient and steady-state system behaviors. The optimal PM policy produces a notably lower availability coefficient of variation (by 11.5%), while at the same time suffering a negligible limiting availability loss of only 0.3%. The new optimal PM policy also provides cost savings of about 5% in total maintenance cost. The performed sensitivity analysis shows that the system's optimal maintenance cost is sensitive to the repair time, the shape parameter of the Weibull distribution and the downtime cost, but is robust with respect to changes in the remaining parameters.

Most of the current maintenance models emphasize the steady-state behavior of availability and neglect its transient behavior. For some systems, using steady-state availability as the sole metric for performance is not adequate, especially in systems that have relatively short life spans or when their transient behavior affects the overall performance. However, little work has been done on the transient analysis of such systems. In this paper, the authors aim to fill this gap by emphasizing such systems and applications where transient behavior is of critical importance to efficiently optimize system performance. The authors use military systems as a motivating example.

The purpose of this paper is to identify the critical components of a complex system by using survival signature. First, a complex system is abstracted with varying scales and generates a multi-levels model. Then reliability evaluations can be conducted by survival signature from rough to fine for tracing and identifying them. Finally, the feasibility of the proposed approach is demonstrated by an actual production system.

The paper mainly applies a multi-level evaluating strategy for the reliability analysis of complex systems with components of multiple types. In addition, a multi-levels model of a complex system is constructed and survival signature also used for evaluation.

The proposed approach was demonstrated to be the feasibility by an actual production system that is used in the case study.

The case study was performed on a system with simple network structure, but the proposed approach could be applied to systems with complex ones. However, the approach to generate the digraphs of abstraction levels for complex system has to be developed.

So far the approach has been used for the reliability analysis of a machining system. The approach that is proposed for the identification of critical components also can be applied to make maintenance decision.

The multi-level evaluating strategy that was proposed for reliability analysis and the identification of critical components of complex systems was a novel method, and it also can be applied as index to make maintenance planning.