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This study proposes a dynamic performance evaluation model to support the material availability of the public institution under performance- based logistics (PBL) and to select the most appropriate service provider.

The model consists of four stages. In the first stage, a criteria set to evaluate alternatives is created. In the second stage, the DEA-MTFP index method is applied for performance evaluation of the alternatives by using crisp data. In the third stage, IFS theory is utilized for aggregating decision-maker judgments on alternatives, and in the last stage, the results of both methods are turned into single value, and it is selected as the most suitable alternative.

It is verified that the proposed approach can be implemented to the real-life dynamic multi-criteria decision-making (MCDM) problem that have crisp and fuzzy data under the PBL strategy.

This paper offers an integrated approach for performance analysis of service providers in a dynamic MCDM problem in which crisp and fuzzy data are used together. To illustrate applicability and validity of the proposed model, it is applied to a real-life problem.

This paper utilizes the DEA-MTFP index method and IFS theory in an integrated way.

The utilisation of emerging technologies for the inspection of bridges has remarkably increased. In particular, non-destructive testing (NDT) technologies are deemed a potential alternative for costly, labour-intensive, subjective and unsafe conventional bridge inspection regimes. This paper aims to develop a framework to overcome conventional inspection regimes' limitations by deploying multiple NDT technologies to carry out digital visual inspections of masonry railway bridges.

This research adopts an exploratory case study approach, and the empirical data is collected through exploratory workshops, interviews and document reviews. The framework is implemented and refined in five masonry bridges as part of the UK railway infrastructure. Four NDT technologies, namely, terrestrial laser scanner, infrared thermography, 360-degree imaging and unmanned aerial vehicles, are used in this study.

A digitally enhanced visual inspection framework is developed by using complementary optical methods. Compared to the conventional inspection regimes, the new approach requires fewer subjective interpretations due to the additional qualitative and quantitative analysis. Also, it is safer and needs fewer operators on site, as the actual inspection can be carried out remotely.

This research is a step towards digitalising the inspection of bridges, and it is of particular interest to transport agencies and bridge inspectors and can potentially result in revolutionising the bridge inspection regimes and guidelines.

Despite an emerging trend in the higher education sector toward sustainable campuses, comparative analyses that span multiple themes across multiple campuses are still limited. The purpose of this paper is to reduce such a gap by comparing universities that are members of the International Sustainable Campus Network across themes that are related to environmental quality.

In total, 34 universities are included in the sample. Indicators are systematically reviewed and clustered into ten themes. Common indicators (CIs) are identified in seven themes for at least seven and at most 20 campuses. At the absence of CIs, the given theme is assessed based on the measures applied. The results indicate the average levels of performance in the sample and/or the scope of the measures that are undertaken.

According to related values, an average campus spent 233,402 MWh of energy in buildings, 838,317 m³ of water on campus, generated 4,442 tonnes of waste, and emitted 75,354 tonnes of CO₂ emissions. The average recycling rate was 50 percent, the average single occupancy vehicle rate in campus commuting was 34 percent, and on average, there were 152 sustainability-oriented courses. Best practices from the measures included energy audits for data centers, retrofit of water intense laboratories, and on-site renewable energy projects.

In addition, a unified monitoring framework is proposed to improve subsequent comparative analyses of campuses. Universities must focus on the use of the campus as a living laboratory to guide society toward a more sustainable future.

This study aims to assess the effectiveness of a scale measuring artificial intelligence capabilities by using the resource-based theory. It seeks to examine the impact of these capabilities on the organizational-level resources of dynamic capabilities and organizational creativity, ultimately influencing the overall performance of government organizations.

The calibration of artificial intelligence capabilities scale was conducted using a combination of qualitative and quantitative analysis tools. A set of 26 initial items was formed in the qualitative study. In the quantitative study, self-reported data obtained from 344 public managers was used for the purposes of refining and validating the scale. Hypothesis testing is carried out to examine the relationship between theoretical constructs for the purpose of nomological testing.

Results provide empirical evidence that the presence of artificial intelligence capabilities positively and significantly impacts dynamic capabilities, organizational creativity and performance. Dynamic capabilities also found to partially mediate artificial intelligence capabilities relationship with organizational creativity and performance, and organizational creativity partially mediates dynamic capabilities – organizational creativity link.

The application of artificial intelligence holds promise for improving decision-making and problem-solving processes, thereby increasing the perceived value of public service. This can be achieved through the implementation of regulatory frameworks that serve as a blueprint for enhancing value and performance.

There are a limited number of studies on artificial intelligence capabilities conducted in the government sector, and these studies often present conflicting and inconclusive findings. Moreover, these studies indicate literature has not adequately explored the significance of organizational-level complementarity resources in facilitating the development of unique capabilities within government organizations. This paper presents a framework that can be used by government organizations to assess their artificial intelligence capabilities-organizational performance relation, drawing on the resource-based theory.