Interpretive structural model of trust factors in construction virtual project teams

Purpose Organisational dependence on virtual project teams (VPTs) is growing dramatically due to the substantial benefits they offer, such as efficiently achieving objectives and improving organisational performance. One of the major issues that influence the effectiveness of VPTs is trust building. This study aims to determine the key factors of trust in VPTs and design a model by identifying the interrelationships among the trust factors. Design/methodology/approach Focus group discussion was used to gather data on factors affecting trust in VPTs and their interrelationships. Interpretive structural modelling (ISM) was used to establish the relationship among the factors. Cross-impact matrix multiplication applied to classification analysis was conducted to identify the driving power and the dependence power towards effective VPTs in the construction sector. Findings The finding revealed that “characteristics of team members” (such as ability, integrity, benevolence, competence, reliability and professionalism) is the most significant factor for building trust in virtual team members. Some factors were further identified as having high driving power, while others were defined as having high dependence variables. Practical implications The findings will assist construction managers and practitioners dealing with VPTs identify the factors influencing trust among team members. Taking cognisance of the factors that influence trust will enable them to design more effective virtual team arrangements. Originality/value As the first research of its kind using ISM technique, the study offers insights into interrelationships between trust factors in the construction VPTs. It provides guides for construction managers on the effective management of trustworthy VPTs.

Triple-strength model of female auditors empowerment in Iran

Purpose As one of the dominant features in developing countries, gender inequality has driven individual development and the promotion of skills, behavioral and social competencies largely based on the male gender. The audit profession is considered one of the jobs where gender inequality exists, especially in developing countries. This has made educational programs more inclined toward enhancing masculine abilities, followed by less well-regarded feminine functions in the field. This study aims to present a triple-strength model of female auditors empowerment in Iran. Design/methodology/approach This is a goal-oriented, descriptive-applied developmental research and a mix of data types. In the qualitative section, the three-dimensional empowerment proposition of women working in the field of internal auditing (IA) were identified based on the Dacum model approach participated by 15 research experts, using cross-sectional and Delphi analyses. A total interpretive structural model analysis was performed with the participation of 20 women as internal auditors of companies listed on the Tehran Stock Exchange (TSE). Findings The purpose of this analysis was to prioritize the spectrum of the most influential indices of empowerment of female auditors in educational planning to the least effective ones in the form of the research model and to examine the relationships between them based on matrix comparisons. According to the results, 17 indices reached theoretical adequacy during the 2 rounds of Delphi analysis out of the initial 19 indices in the cross-mix analysis. Originality/value The results of the interpretive/structural analysis indicated that educational planning was selected to balance the other roles of women as internal auditors, and the most influential Dacum proposition was to enhance the capabilities of women in IA in listed companies in TSE.

Artificial Intelligence Is Reshaping Healthcare Amid Covid-19: A Review in the Context of Diagnosis & Prognosis

Preventing respiratory failure is crucial in a large proportion of COVID-19 patients infected with SARS-CoV-2 virus pneumonia termed as Novel Coronavirus Pneumonia (NCP). Rapid diagnosis and detection of high-risk patients for effective interventions have been shown to be troublesome. Using a large, computed tomography (CT) database, we developed an artificial intelligence (AI) parameter to diagnose NCP and distinguish it from other kinds of pneumonia and traditional controls. The literature was studied and analyzed from diverse assets which include Scopus, Nature medicine, IEEE, Google scholar, Wiley Library, and PubMed. The search terms used were ‘Covid-19’, ‘AI’, ‘diagnosis’, and ‘prognosis’. To strengthen the overall performance of AI in COVID-19 diagnosis and prognosis, we segregated several components to perceive threats and opportunities, as well as their inter-dependencies that affect the healthcare sector. This paper seeks to pick out the crucial fulfillment of factors for AI with inside the healthcare sector in the Indian context. Using critical literature review and experts’ opinion, a total of 11 factors affecting COVID-19 diagnosis and prognosis were detected, and we eventually used an interpretive structural model (ISM) to build a framework of interrelationships among the identified factors. Finally, the matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis resulted the driving and dependence powers of these identified factors. Our analysis will help healthcare stakeholders to realize the requirements for successful implementation of AI.

An interpretive structural model for factors affecting the tax compliance of professional athletes: a case study of football players

PurposeTax revenues are becoming one of the crucial tax policy segments in developing countries. Governments intend to collect more funds in the budget. The study aimed to identify the dimensions and factors influencing tax compliance in Iranian professional football players.Design/methodology/approachBased on interpretive structural modelling (ISM), the required information was collected using a literature review and a pairwise comparison questionnaire from eleven sport academic and executive participants. Content validity index of the questionnaire was >0.7 and its inconsistency index was <0.1.FindingsThe influential factors put in six levels. Results showed “new technologies for implementing regulations” and “clear tax regulations” were the lowest level's most independent factors. Simultaneously, the “possibility of identifying violating taxpayers” and “transparency of the clubs' financial data” were the most dependent factors at the model's first level. Moreover, “legal” was the greatest, and “technological” dimensions had at least importance, and the “amount and manner of fines” was the influential factor. The findings can use for policymaking to improve the professional player's and society tax compliance.Originality/valueThe authors identified the most independent, dependent, influential and minor essential football players' tax compliance factors and the relations between these factors. Recognising each of the factors' role and level of importance can help governments and policymakers in tax legislation in sport.

Validating Circular Performance Indicators: The Interface between Circular Economy and Stakeholders

The development and application of appropriate Circular Economy indicators is an issue that concerns both the scientific and the business community, as well as decision makers. The existing gap between research, policy and practice could be bridged by using a dynamic indicators selection approach that combines both expert and participatory practices. This study aims to develop such a novel approach for the selection of indicators based on views and needs of practitioners, whilst considering the complex interdependencies of the indicators and determining their importance. Twenty circularity indicators for the Water-Energy-Food-Ecosystems nexus are selected and ranked by different stakeholders. The interrelationships of the indicators are identified using the Interpretive Structural Model, resulting in six levels of importance. Cross-impact matrix multiplication applied to classification (MICMAC) analysis further enabled the classification of the twenty indicators into four categories based on their driving and dependence power. The results indicate that seven indicators—one related to regeneration of natural environment principle, four related to keep resources in use, and two related to design out negative externalities—are the driving indicators to Circular Economy. The approach can be applied to other sets of indicators as well, enabling their prioritization and implementation with other systems.

Factors Affecting the Lut Desert Tourism in Iran: Developing an Interpretive-Structural Model

The Lut desert is one of the largest and most attractive deserts in Iran. The value of desert tourism remains unclear for Iran’s economy and has only recently been taken into consideration by the authorities, although its true national and international value remains unclear. This study was aimed at investigating the factors that influence tourism development in the Lut desert. Data collected through the purposive sampling method was analyzed using Interpretive Structural Modeling and the MICMAC Analysis. According to the results, cost-effective travel expenses, security, and safety provided in the desert, together with appropriate media advertising and illustration of the Lut desert (branding) are the leading factors that influence tourism in the Lut desert in Iran. This paper highlighted the importance of desert tourism, especially in this region.

Analyzing glacial lake outburst flood triggers for sustainable disaster risk mitigation: an interpretive structural modelling based approach

PurposeClimate change and global warming pose a serious threat to the community as deglaciating environments trigger glacial lake outburst floods (GLOFs). The Sendai framework underpins the role of disaster risk reduction (DRR) for sustainable development, thereby calling for the development of GLOF hazard and risk assessment procedures. This study aims to delineate the enablers of GLOF risk and establish a contextual relationship between them.Design/methodology/approachThe risk enablers are identified from the extant GLOF literature, and the experts from disaster management area are consulted to explore the underlying contextual relationship among them. An interpretive structural model is developed from the responses to analyze the contextual relationships among the risk enablers.FindingsThe interpretive structural modeling results manifest that seismic activity, temperature and precipitation events, and proximity are key drivers that trigger flash floods from the lakes and an effective assessment of these triggers may contribute significantly to GLOF risk mitigation.Originality/valueThe study models the complex relationship among the risk enablers for a glacial flood hazard that find commonality across all geographic contexts. The findings provide the practitioners of DRR useful insights into these factors and their subsequent impact on others, while conducting hazard assessment of glacial lakes that may contribute to the sustainable development of settlements lying downstream to glacial lakes.

Analysis of factors affecting the realization of right to adequate housing in Iran: developing an interpretive-structural model

Purpose Access to adequate housing represents a right entitled to any individual, as has been acknowledged by all states around the world. In Iran, despite the declaration of this right as per the Article 31 of Iran’s Constitution, it is yet to be realized. The purpose of this study is to developing a model for realization of the right to the adequate housing. Design/methodology/approach The present research was performed through a guided qualitative method. Structural-interpretative modeling was performed to present the model of right to adequate housing, and Mic Mac analysis was conducted for clustering the identified factors. Statistical population was composed of housing experts, with the samples taken via purposive sampling technique. Findings Based on the findings, the following factors were found to impose the largest effects on the realization of the right to adequate housing: alignment with ideology and beliefs of society; governance structure related arrangements; social structure related arrangements; improving security of tenure; justice in tenure; and local requirements. Practical implications Findings of this research contributes to increasing the awareness of the housing officials about their policies, reminding them the necessity of revisiting their routines for policy-setting. Indeed, they must switch from centralized policymaking to localized (provincealization) policymaking. Originality/value To the best of authors’ knowledge, this research is the first to investigate the right to adequate housing in Iran, elaborating on the relationship between relevant theories and practical issues.