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Mental health problems are a grave concern in construction. Although the distinction between high job demands and low job resources, as reflected in the Job Demands-Resources (JD–R) model, has been used to examine the extent to which psychosocial hazards influence mental health for construction practitioners, limited research has reflected on the nature of these psychosocial hazards by exploring experiences of site-based construction practitioners.

This study adopted a phenomenological approach to examine people’ experiences and thoughts of the complex phenomena of psychosocial hazards and mental health in construction. In total, 33 semi-structured interviews were undertaken with site-based construction practitioners in Australia to unveil construction-focused psychosocial hazards and their effects on mental health. The data were analysed via content analysis, employing an interpretation-focused coding strategy to code text and an individual-based sorting strategy to cluster codes.

Eighteen psychosocial hazards were identified based on the JD–R model. Six of these represented a new contribution, describing salient characteristics inherent to the construction context (i.e. safety concerns, exposure to traumatic events, job insecurity, task interdependency, client demand and contract pressure). Of particular importance, a number of interrelationships among psychosocial hazards emerged.

The significance of this qualitative research lies in elucidating psychosocial hazards and their complex interrelatedness in the context of the mental health of construction practitioners, enriching the understanding of this central health and safety issue in the high-risk setting of construction work. The findings contribute to addressing mental health issues in the Australian construction industry by identifying higher order control measures, thereby creating a mentally healthy workplace.

The present study aims to examine the moderating impact of governance quality on the tourism poverty nexus using a panel of six South Asian Association for Regional Cooperation (SAARC) countries during the period 2002 to 2019.

For the soundness of the results, fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) econometric models were applied to determine the long-run relationship.

The findings confirmed the positive and significant impact of tourism development (international tourism arrival) and governance quality (effectiveness of governmental services) on poverty (per capita household consumption) reduction. Interestingly results confirm that governance quality and tourism development have complementary impacts on poverty reduction.

The present study has twofold contributions; First, despite the high potential of SAARC tourism, research remains limited in studies examining the role of tourism and governance quality on poverty reduction within the SAARC region. As a result, the present paper presents critical insights into the impact of tourism inflow and governance quality on poverty reduction in South Asian countries. Second, to the best of the author's knowledge, this is the first attempt to conduct an econometric analysis to examine the role of governance quality on the relationship between tourism inflow and poverty reduction in SAARC countries.

Employment exchanges have been playing a significant role in the worldwide labor market for more than a hundred years now. In India, since 1946, millions of aspiring Indian youths have registered themselves with the government-run employment exchanges to find a job. About four million job seekers got registered at 1,000 employment exchanges in India, it is important to analyze the placement statistics of these exchanges. In recent years, new methods of job search have evolved. This study examines whether employment exchanges are effective in the changed scenario?

Using state-level employment exchange data for the period 2010–2011 to 2019–2020, this study analyzes the determinants of job placement at employment exchanges in India. A critical analysis of the functioning of employment exchanges along with recommendations to improve the job search ecosystem in India is also presented in the study.

This study found that increased share of service sector in the state economy negatively impacts placement at employment exchanges.

The absence of focus on the service sector requires policy intervention if Indian employment exchanges are to remain relavant.

The government administration should rethink that ignoring service sector employment potential is unaffordable for an emerging economy and employment exchanges should be aligned accordingly.

About 30 million people are unemployed in India. If employment exchanges are transformed, it can have far-reaching socio-economic advantages.

This study is the first sub-country level study on the institution of employment exchanges. This study comprehensively maps the landscape of career services in India. Empirically establishing the impact of sectoral structure of economy on efficacy of employment exchanges, and makes the case for policy intervention that is needed to keep the employment exchanges relevant in India.

The authors study how cloud adoption decision making unfolds in organizations and present the dynamic process leading to a decision to adopt or reject cloud computing. The authors thus complement earlier literature on factors that influence cloud adoption.

The authors adopt an interpretive epistemology to understand the process of cloud adoption decision making. Following an empirical investigation drawing on interviews with senior managers who led the cloud adoption decision making in organizations from across Europe. The authors outline a framework that shows how cloud adoptions follow multiple cycles in three broad phases.

The study findings demonstrate that cloud adoption decision making is a recursive process of learning about cloud through three broad phases: building perception about cloud possibilities, contextualizing cloud possibilities in terms of current computing resources and exposing the cloud proposition to others involved in making the decision. Building on these findings, the authors construct a framework of this process which can inform practitioners in making decisions on cloud adoption.

This work contributes to authors understanding of how cloud adoption decisions unfold and provides a framework for cloud adoption decisions that has theoretical and practical value. The study further demonstrates the role of the decision-leader, typically the CIO, in this process and identifies how other internal and external stakeholders are involved. It sheds light on the relevance of the phases of the cloud adoption decision-making process to different cloud adoption factors identified in the extant literature.

The purpose of this article is to develop a new model called strategy segmentation methodology (SSM) by combining the Kraljic portfolio matrix (KPM) and the supplier relationship model (SRM) so that the buyer company can effectively conduct its relations with its suppliers.

The importance weights of the criteria defining the dimensions of each model are calculated with the single-valued neutrosophic analytical hierarchy process (SVN-AHP) method. Subsequently, the derived importance weights are employed in the single-valued neutrosophic technique for order preference by similarity to ideal solution (SVN-TOPSIS) method to obtain the scores of the suppliers and their supplied items. In order to illustrate the feasibility of the proposed methodology, a case study in the machinery industry is performed with the related comparative analysis.

The implementation of SSM enables to formulate various strategies to manage suppliers taking into account the items they procure, their capabilities and performance and the supplier–buyer relationship strength. Based on the proposed strategies, it is concluded that the firm in the case study should terminate its relationship with six of its suppliers.

Although KPM has become the basis of purchasing strategies for various businesses, it neglects the characteristics of suppliers and the buyer–supplier relationship. In this study, KPM is integrated with the SRM approach presented by Olsen and Ellram (1997) to overcome these disadvantages of KPM. The novel integration of the two approaches enables the realization of a robust and reliable supplier classification model.

Sustainable construction deficits are common in developing economies, and resolutions are constrained by the failure to prioritise the plethora of available indicators. This study aims to report on overlapping indicators for benchmarking sustainable construction for construction organisations.

Online survey data were collected from construction professionals, academics and senior managers in government bodies. Pearson chi-squared tests and overlapping analysis were used to determine significant indicators. Kruskal–Wallis tests were used to determine statistically significant differences among the dimensions.

Overlapping analysis determined indicators significant for economic, environmental and social performance. Environmental protection and reporting (pollution and emissions) were significant for all three performance dimensions. The most significant indicators are economic performance (adequate competence of key project staff), environmental performance (environmental protection and reporting – pollution and emissions) and social performance (adequate sustainability expenditure by construction organisations). Significant differences due to dimensions existed for adequate competence of key project staff, sustainable construction and eco-design, adequate governance and organisational excellence of construction projects and satisfactory workers’ morale.

Determining overlapping indicators enables prioritised implementation that ensures sustainable construction. Excluding construction workers was a significant limitation for a holistic interrogation.

To the best of the authors’ knowledge, this is the first study to determine overlapping indicators for sustainable construction performance in Zimbabwe.