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This study aims to examine the impact of “space-as-a-service” (SAAS) provision on office rents in the UK and quantify premia to office rents.

Using hedonic modelling techniques the authors are able to quantify the impact of a number of SAAS features on office rents in the City of London using CoStar data. The authors control for the quality of the buildings by focussing on five-star buildings, rated by CoStar, as these buildings are more likely to incorporate SAAS features.

Using data on 317 transactions in 37 City of London Office buildings over the period 1 November 2004–15 July 2020, the authors find that tenant exclusive mobile applications (MAPPS) and a public terrace or rooftop command a rent premium of around £13 and £6.5 per sq. ft per annum, respectively. However, other SAAS features such as conferencing facilities, on-site fitness centre and touch down space have no significant impact on office rents. The impact of exclusive MAPPS varies with size of net lettable area.

The SAAS real estate model is an emerging trend in the office market. As it grows in importance more research questions will have to be investigated. The present study raises awareness of the need to specify SAAS features and form a rating system that will facilitate future research on the subject.

The conclusion from the present investigation is that only two SAAS features have a positive impact on office (tenant exclusive mobile apps and a public terrace or rooftop), which suggest that these two features may form the basis of any future SAAS rating system. These two SAAS components should carry more weight in valuations and pricing.

To the best of the authors’ knowledge, this is the first study that attempts to quantify the impact of SAAS features on office rents.

This paper addresses a significant research gap in the study of Rayleigh surface wave propagation within a piezoelectric medium characterized by piezoelectric properties, thermal effects and voids. Previous research has often overlooked the crucial aspects related to voids. This study aims to provide analytical solutions for Rayleigh waves propagating through a medium consisting of a nonlocal piezo-thermo-elastic material with voids under the Moore–Gibson–Thompson thermo-elasticity theory with memory dependencies.

The analytical solutions are derived using a wave-mode method, and roots are computed from the characteristic equation using the Durand–Kerner method. These roots are then filtered based on the decay condition of surface waves. The analysis pertains to a medium subjected to stress-free and isothermal boundary conditions.

Computational simulations are performed to determine the attenuation coefficient and phase velocity of Rayleigh waves. This investigation goes beyond mere calculations and examines particle motion to gain deeper insights into Rayleigh wave propagation. Furthermore, this investigates how kernel function and nonlocal parameters influence these wave phenomena.

The results of this study reveal several unique cases that significantly contribute to the understanding of Rayleigh wave propagation within this intricate material system, particularly in the presence of voids.

This investigation provides valuable insights into the synergistic dynamics among piezoelectric constituents, void structures and Rayleigh wave propagation, enabling advancements in sensor technology, augmented energy harvesting methodologies and pioneering seismic monitoring approaches.

This study formulates a novel governing equation for a nonlocal piezo-thermo-elastic medium with voids, highlighting the significance of Rayleigh waves and investigating the impact of memory.

The purpose of this study is, to compare laser-based additive manufacturing and subtractive methods. Laser-based manufacturing is a widely used, noncontact, advanced manufacturing technique, which can be applied to a very wide range of materials, with particular emphasis on metals. In this paper, the governing principles of both laser-based subtractive of metals (LB-SM) and laser-based powder bed fusion (LB-PBF) of metallic materials are discussed and evaluated in terms of performance and capabilities. Using the principles of both laser-based methods, some new potential hybrid additive manufacturing options are discussed.

Production characteristics, such as surface quality, dimensional accuracy, material range, mechanical properties and applications, are reviewed and discussed. The process parameters for both LB-PBF and LB-SM were identified, and different factors that caused defects in both processes are explored. Advantages, disadvantages and limitations are explained and analyzed to shed light on the process selection for both additive and subtractive processes.

The performance of subtractive and additive processes is highly related to the material properties, such as diffusivity, reflectivity, thermal conductivity as well as laser parameters. LB-PBF has more influential factors affecting the quality of produced parts and is a more complex process. Both LB-SM and LB-PBF are flexible manufacturing methods that can be applied to a wide range of materials; however, they both suffer from low energy efficiency and production rate. These may be useful when producing highly innovative parts detailed, hollow products, such as medical implants.

This paper reviews the literature for both LB-PBF and LB-SM; nevertheless, the main contributions of this paper are twofold. To the best of the authors’ knowledge, this paper is one of the first to discuss the effect of the production process (both additive and subtractive) on the quality of the produced components. Also, some options for the hybrid capability of both LB-PBF and LB-SM are suggested to produce complex components with the desired macro- and microscale features.

The purpose of this paper is to propose a decision support framework that can be used by decision-makers to identify the most convenient disruption analysis (DA) methods for megaprojects and their stakeholders.

The framework was initially developed by conducting a comprehensive literature review to obtain extensive knowledge about disruption management and megaprojects. Focus group discussion (FGD) sessions with the participation of the construction practitioners were then organized to validate and strengthen the findings of the literature review. Consequently, 17 selection factors were identified and categorized as requirement, ability and outcome. Lastly, the most convenient DA methods for megaprojects were identified by performing integrated fuzzy analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) analysis. Additionally, consistency analysis was also conducted to verify the reliability of the results.

The results revealed that the measured mile method is the most appropriate DA method for megaprojects. In case the measured mile method cannot be adopted due to various technical and contractual reasons, the decision-makers are proposed to consider program analysis, work or trade sampling, earned value analysis and control chart method, respectively. Second, the selection factors such as “Comprehensible analysis procedure,” “Existing knowledge and experience about a particular DA method,” “Ability to resolve greater number of disruption events,” “Ability to resolve complex disruption events,” “Ability to exclude factors that are not under the owner's responsibility” and “General acceptance by practitioners, courts, and arbitration, etc.” were given the top priority by the experts, highlighting the critical aspects of the DA methods.

Disruption claims in megaprojects are very critical for the contractors to compensate for the losses stemming from disruption events. Although the effective use of DA methods maximizes the accuracy and reliability of disruption claims, decision-makers can barely implement these methods adequately since past studies neglect to present extensive knowledge about the most convenient DA methods for megaprojects. Thus, developing a decision support framework for the selection of DA methods, this study is the earliest attempt that examines the mechanisms and inherent differences of DA methods. Additionally, owing to the robustness and versatility of this research approach, the research approach could be replicated also for future studies focusing on other project-based industries since disruption is also a challenging issue for many other industries.

Paid digital campaigning tools play an increasingly pivotal role in individual election campaigns worldwide. Extant literature often juxtaposes the equalization theory, which argues that these tools create a level playing field, and the normalization theory, which contends that strong and resource-rich politicians benefit most from digital tools. This article aims to inform this debate by looking at it from a campaign expenditure perspective beyond the Anglo-American bias of most research on the subject.

The authors use an original dataset on campaign expenditures and resources of 1,798 candidates running for 13 Belgian parties in the 2019 federal parliamentary election. Relying on multilevel statistical models, the authors link the candidates' digital campaign expenses to their incumbency status, which is expected to affect digital campaigning.

While earlier work on majoritarian cases often showed contradicting results, this study on the Belgian flexible-list proportional representation (PR) case provides strong support for the equalization theory by demonstrating that incumbents are not only less inclined to spend on digital tools than challengers, but also spend a smaller part of their budget on these tools.

This paper contributes to the literature by exploring the equalization versus normalization debate from a campaign expenditure perspective using a made to purpose dataset in a non-Anglo-American context.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2021-0679