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Adoption of Clinical Decision Support Systems (CDSS) is a crucial step towards the digital transition of the healthcare sector. This review aims to determine and synthesise the influential factors in CDSS adoption in inpatient healthcare settings in order to grasp an understanding of the phenomenon and identify future research gaps.

A systematic literature search of five databases (Medline, EMBASE, PsycINFO, Web of Science and Scopus) was conducted between January 2010 and June 2023. The search strategy was a combination of the following keywords and their synonyms: clinical decision support, hospital or secondary care and influential factors. The quality of studies was evaluated against a 40-point rating scale.

Thirteen papers were systematically reviewed and synthesised and deductively classified into three main constructs of the Technology–Organisation–Environment theory. Scarcity of papers investigating CDSS adoption and its challenges, especially in developing countries, was evident.

This study offers a summative account of challenges in the CDSS procurement process. Strategies to help adopters proactively address the challenges are: (1) Hospital leaders need a clear digital strategy aligned with stakeholders' consensus; (2) Developing modular IT solutions and conducting situational analysis to achieve IT goals; and (3) Government policies, accreditation standards and procurement guidelines play a crucial role in navigating the complex CDSS market.

To the best of the authors’ knowledge, this is the first review to address the adoption and procurement of CDSS. Previous literature only addressed challenges and facilitators within the implementation and post-implementation stages. This study focuses on the firm-level adoption phase of CDSS technology with a theory refining lens.

In a dual-robot system, the relative position error is a superposition of errors from each mono-robot, resulting in deteriorated coordination accuracy. This study aims to enhance relative accuracy of the dual-robot system through direct compensation of relative errors. To achieve this, a novel calibration-driven transfer learning method is proposed for relative error prediction in dual-robot systems.

A novel local product of exponential (POE) model with minimal parameters is proposed for error modeling. And a two-step method is presented to identify both geometric and nongeometric parameters for the mono-robots. Using the identified parameters, two calibrated models are established and combined as one dual-robot model, generating error data between the nominal and calibrated models’ outputs. Subsequently, the calibration-driven transfer, involving pretraining a neural network with sufficient generated error data and fine-tuning with a small measured data set, is introduced, enabling knowledge transfer and thereby obtaining a high-precision relative error predictor.

Experimental validation is conducted, and the results demonstrate that the proposed method has reduced the maximum and average relative errors by 45.1% and 30.6% compared with the calibrated model, yielding the values of 0.594 mm and 0.255 mm, respectively.

First, the proposed calibration-driven transfer method innovatively adopts the calibrated model as a data generator to address the issue of real data scarcity. It achieves high-accuracy relative error prediction with only a small measured data set, significantly enhancing error compensation efficiency. Second, the proposed local POE model achieves model minimality without the need for complex redundant parameter partitioning operations, ensuring stability and robustness in parameter identification.

The paper introduces ethical and aesthetical implications emerging from participative forms of adaptive heritage reuse. Its aim is to depict the overall framework to contextualize the investigations explored in the Special Issue titled “Ethics and aesthetics of adaptive heritage reuse in Europe.” Therefore, the article confronts with potentialities and contradictions of “open” heritage processes, introducing key critical elements to recode heritage practices and planning in today’s conjuncture of global change.

The paper drawn on a literature review, which combines different bodies of studies: heritage, urban studies, care studies and recent policy documents. A photographic essay, moreover, serves to “augment” the presented argumentations through a visual apparatus resulting from one of Gaia Ginevra Giorgi’s artwork, which develops in the intersection between performative art, participation and territorial reuse.

The author argues that for adaptive heritage reuse to be really sustainable, ethical and aesthetical heritage codes need to be reassessed and reoriented toward the present socio-ecological priorities, multiplicating the ways cultural heritage is conceived, valued and reused. The paper suggests proceeding along the creative paths of uncertainty, providing the first elements to develop political projects of abundance and enjoyment for current urban settlements.

The presented argumentations can be used as a baseline by heritage managers and policymakers to experiment with participative processes of adaptive heritage reuse and to identify more environmentally and socially just trajectories of urban development.

The paper expands the concept of adaptive heritage reuse, considering the active participation of both human and non-human agents. Treating heritage in a laic way, namely free from absolute and preordered judgments of value, it deals with uncomfortable heritage materiality and contexts, illuminating the quality of unpleasant or odd forms of beauty.

This study aims to analyze the content on corporate social responsibility (CSR) of Gucci, Prada and Ermenegildo Zegna on the social networks Instagram, Facebook and TikTok in order to examine the focus of the publications of these luxury brands, what type of content is more frequent and which ones generate more interaction and engagement.

An interpretive content analysis of a sample of 92 posts on CSR published between December 2021 and June 2022 is used. For this purpose, an analysis sheet validated through theoretical constructs and pilot testing is used.

Most of the social responsibility content of the fashion brands analyzed is linked to the use of sustainable materials, the protection of natural spaces and, in the particular case of Prada, the protection of the oceans. The posts that achieve the highest interactions are videos and photo reels. Although the strategies that significantly increase brands' reach on social networks are collaborations and joint posts with other fashion brands, as is the case of Gucci with NorthFace and Prada with Adidas. Also, one of the main findings of this research has been to identify that brands may be using TikTok – perhaps experimentally – to reach stakeholders in Asian countries, especially China, where other platforms such as Instagram or Facebook may have a more limited reach.

This research shows that the social responsibility activities of luxury fashion brands leverage the content marketing strategy in social networks. It also demonstrates the importance of the Asian market (mainly Chinese) in the outreach strategies of brands, as is the case of Gucci and Prada, which bet on CSR activities for the protection of the Asian tiger in the framework of the year of the tiger in the Chinese horoscope, as well as the publication of certain content on TikTok.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

Lean implementation has become popular over the past three decades in the industry and is becoming more prevalent in, service organizations. The objective of this study is to evaluate the impact of social and technical Lean practices on sustainable performance (i.e. economic, environmental and social) in service organizations.

The methodology includes the analysis of global results obtained from 139 managers from the service sector.

The results demonstrate that Lean practices have a positive effect on the three perspectives of sustainable performance, regardless of the company size and duration of Lean implementation. Furthermore, both social and technical Lean practices have a similar impact on environmental and economic performance, but their impact on social performance differs, since social Lean practices have a stronger impact on social performance.

This study has a significant contribution to Lean practitioners in service sectors, as it demonstrates that efforts to apply Lean practices can benefit economic results as well as environmental and social performance.

Majority of existing studies focused on the isolated impact of Lean on one of the triple bottom line performance aspects and with a scarcity of studies within the context of services. The intersection of these three strategic areas – Lean, sustainability and services – has not been extensively addressed. There is also a lack of studies that observe sustainability in environmental, social and economic performance, mainly in the service sector.

The variance between the winning bid and the owner's estimated cost (OEC) is one of the construction management risks in the pre-tendering phase. The study aims to enhance the quality of the owner's estimation for predicting precisely the contract cost at the pre-tendering phase and avoiding future issues that arise through the construction phase.

This paper integrated artificial neural networks (ANN), deep neural networks (DNN) and time series (TS) techniques to estimate the ratio of a low bid to the OEC (R) for different size contracts and three types of contracts (building, electric and mechanic) accurately based on 94 contracts from King Saud University. The ANN and DNN models were evaluated using mean absolute percentage error (MAPE), mean sum square error (MSSE) and root mean sums square error (RMSSE).

The main finding is that the ANN provides high accuracy with MAPE, MSSE and RMSSE a 2.94%, 0.0015 and 0.039, respectively. The DNN's precision was high, with an RMSSE of 0.15 on average.

The owner and consultant are expected to use the study's findings to create more accuracy of the owner's estimate and decrease the difference between the owner's estimate and the lowest submitted offer for better decision-making.

This study fills the knowledge gap by developing an ANN model to handle missing TS data and forecasting the difference between a low bid and an OEC at the pre-tendering phase.

Based on social cognitive theory, this study aims to explore the psychological mechanism behind consumer verification behavior following tourism e-commerce live-streaming.

Based on grounded theory, data were collected through 20 semi-structured in-depth interviews and analyzed.

This study identified that companies commonly use reminder messages and secondary promotions to facilitate the verification of tourism live-streaming products. Throughout this process, consumers undergo various psychologies related to verification. Specifically, they experience four positive verification psychologies: fear of missing out, anticipated emotions, status self-esteem and promotional perception. They also encounter two negative verification psychologies: psychological reactance and invasiveness. In addition, environmental factors such as the type of tourism live-streaming products and tourism destinations, along with individual trait factors like cognitive miserliness, tourism experience, autonomy, regulatory mode and impulsiveness, play significant roles in shaping verification behavior. These factors collectively influence the formation of verification behavior.

This study can provide recommendations for tourism companies to conduct marketing events following live-streaming. It is one of the earlier comprehensive studies discussing how to promote verification behavior following tourism e-commerce live-streaming. It helps to understand the psychological mechanism underlying the formation of verification behavior.