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Due to land resource scarcity, sustainable urban development in high-density cities has long been challenging. As such, many cities are formulating plans to “dig deep”, resulting in more citizens working and/or staying underground for longer periods of time. However, owing to the particularities of underground space, the factors involved in the creation of a healthy environment are different from those involved in aboveground developments. This study thus aims to investigate the influences of various underground environment factors on users' health through a holistic approach.

To achieve this aim, 12 underground sites and 12 corresponding aboveground sites are selected for a large-scale questionnaire survey, resulting in 651 survey samples. The survey covers post-occupancy evaluation of health (physical and psychosocial), underground environmental quality (visual, thermal, acoustic comfort, indoor air quality and ventilation), space design and greenery. Independent-sample T-test, Pearson correlation, multiple regression modelling and structural equation modelling are used to investigate whether significant differences exist between health of underground and aboveground users, and to develop an underground environment-health model for unveiling the significant associations between underground environment factors and users' health. To cross validate the results, an objective field measurement study is further conducted on six underground sites. The objective measurement results are used to cross validate the survey results.

The questionnaire results provide the following evidence: (1) health of underground users is significantly poorer than that of their aboveground counterparts; (2) underground development users' health is significantly affected by space design, greenery and environmental quality in terms of thermal comfort, indoor air quality, ventilation and acoustic comfort but not visual comfort; and (3) amongst the various identified factors, space design has the strongest predicting effects on human health. The field study echoes the survey findings and further unveils the relationships between different environmental factors and human health.

The results shed light on the importance of distinguishing between underground developments and aboveground ones in various guidelines and standards, especially those related to space management.

The negative effects of job stress and burnout on construction professionals (CPs) at the construction site have been widely concern in the construction industry. The purpose of this study is committed to explore the impact of job stress on CPs on the construction site, especially in the context of the widespread use of social media to express their emotions.

This study developed a job-related stress-burnout-health conditions-turnover intention (S-B-HT) framework to explore the direct and lagged effects of job stress, we also examined the moderating effects of online emotions, operationalized in terms of emotional intensity and expression pattern, on the relationship between job stress with job burnout under two evolution paths (i.e. health conditions or turnover intention). This study collected 271 samples through a survey questionnaire for empirical testing, and introduced structural equation models to validate the proposed conceptual model.

The results show that job stress has a significant positive effect on job burnout, and job burnout maintains a positive relationship with health conditions (or turnover intention) under the interference mechanism. Simultaneously, the online emotions expressed in social media have a positive moderating effect in two stages of the evolution path.

The findings of this study remind the project manager need to timely find and solve the job burnout characteristics of CPs due to excessive job stress, especially to prevent the accidental consequences caused by job burnout.

On this basis, this study provides an important value of using social media to express emotions for the project team to alleviate the adverse of professionals under job stress.

This paper presents an analytical framework for modeling and measuring strategic alignment. The resource-product-market (RPM) model is introduced as a means of representing the alignment of the firm's internal resources with its product lines and external markets. A strategic alignment index is defined to measure the degree of alignment represented by a model.

The RPM model is derived as an extension of prior research on diversification indexes. The strategic alignment index is mathematically defined and the properties of the model are characterized using graph theory. The approach is illustrated for two example firms.

The RPM model is flexible and can be used with different types and measures of resources, products and markets. The model represents strategy in a structural manner addressing a vertical type of alignment. The index ranges continuously from 0 to 1.0, providing a useful scale for measurement and comparison.

Practitioners may use RPM modeling to assess the current alignment of their respective firms and to identify strategic alternatives which increase alignment through a taxonomy of 13 strategic moves. The results of applying the model to ten firms are summarized.

The paper contributes to the literature by providing a new method for modeling firm strategy which integrates resource and industry views, thereby enabling a measurement of their alignment. The paper is also novel in the application of graph theory to management.

This study aims to outline the influence of various combinations of antecedent conditions for startups being accepted into business incubators in Italy and Romania. The degree to which these conditions affect acceptance is referred to here as the Business Ideas Acceptance Degree (BIAD). The antecedent conditions considered are business idea potential, business plan quality, entrepreneurial team features, business project progress stage, available financial resources, debts of potential incubated companies, commitment to apply for national/EU funds, business area related to incubator mission, proposed technological content level, technological transfer from university/research centres and spin-off of a partner-entity of the incubator.

The methodological toolkit used was mixed: correlation-based analysis (CBA), machine learning (ML) techniques and fsQCA. Principal component analysis enabled the selection of the most representative antecedent conditions from both business incubator samples in Italy and Romania, further used in fsQCA analyses. XGBoost algorithm has been also used. K-Means clustering, an unsupervised learning algorithm that groups unlabeled dataset into different clusters, led to the configuration of two clusters associated to each of the countries involved in this study (Romania and Italy).

The findings reveal the differences between the different antecedent conditions that can contribute to startups being accepted into business incubators in Italy and Romania. The validation of the fsQCA equifinality principle in both samples shows that the selected antecedent conditions, mixed in combinations of “causal recipes”, lead to a high BIAD by business incubators from both countries.

This study reveals the differences between different antecedent conditions, capable to contribute to the start-up acceptance within business incubators from Italy and Romania. Furthermore, the validation of fsQCA equifinality principle in both samples highlight that the selected antecedent conditions, mixed in combinations of causal recipes, lead to a high degree of business ideas' acceptance in business incubators.

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.