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Sustainability is a major challenge for India’s (Bharat’s) coal mining industry. The government has prioritized sustainable growth in the coal mining industry. It is putting forth multifaceted economic, environmental and social efforts to accomplish the Sustainable Development Goals (SDGs). This research aims to identify the factors for sustainable improvements in coal mining operations. Secondly, this study examines the intensity of causal relations among the factors. Thirdly, this study examines whether causal relations exist among the factors to be considered for sustainable improvement in coal mining operations. Lastly, the study aims to understand how the factors ensure sustainable improvement in coal mining operations.

An integrated three-phase methodology was applied to identify the critical factors related to coal mining and explore the contextual relationships among the identified factors. Fifteen critical factors were selected based on the Delphi technique. Subsequently, the fifteen factors were analyzed to determine the contextual and causal relationships using the total interpretive structural modelling (TISM) and DEMATEL methods.

The study identified “Extraction of Coal and Overburden” as the leading factor for sustainable improvement in coal mining operations, because it directly or indirectly influences the overall mining operation, environmental impact and resource utilization. Hence, strict control measures are necessary in “Extraction of Coal and Overburden” to ensure sustainable coal mining. Conversely, “Health Impact” is the lagging factor as it has very low or no impact on the system. Therefore, it requires fewer control mechanisms. Nevertheless, control measures for the remaining factors must be decided on a priority basis.

The proposed structural model can serve as a framework for enhancing sustainability in India’s (Bharat’s) coal mining operations. This framework can also be applied to other developing nations with similar sustainability concerns, providing valuable guidance for sustainable operations.

The current study highlights the significance of logical links and dependencies between several parameters essential to coal mining sustainability. Furthermore, it leads to the development of a well-defined control sequence that identifies the causal linkages between numerous components needed to achieve real progress towards sustainability.

This research paper aims to establish a comprehensive framework for the barriers to CER in the construction industry, assesses the barriers' relative degrees of hindrance and causal mechanisms.

Firstly, 26 carbon emission reduction (CER) barriers in the construction industry were identified based on a systematic literature review (SLR) and categorized into five dimensions: policy, economy, society, technology and organization (PEST + O model). Secondly, the Best–Worst Method (BWM) was used to clarify the degrees of hindrance of the CER barriers. Then, the Grey-Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) was used to visualize the directional cause–result relationship network among prominent barriers. Finally, the Boston matrix model was used to propose differentiated strategies to address CER barriers in the construction industry.

The calculated centrality and causality of the prominent barriers indicated that the lack of relevant legal policies and normative guidelines, the poor binding force and enforcement of existing relevant policies, the lack of effective economic subsidies and incentives and the difficulty in the operation, transformation and upgrading of existing construction CER are the key barriers that CER needs to address first in the construction industry. Considering the order of priority and the optimal path, differentiated countermeasures are proposed to address key, driving, independent and effect barriers.

This study develops a BWM–Grey-DEMATEL integrated multi-criteria decision-making model. An innovative C-shaped strategic map for addressing CER barriers in the construction industry is proposed by integrating the dual dimensions of time and space. This will guide practitioners, policymakers and decision-makers in developing CER strategies.

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

The purpose of this study is to investigate consumers’ cryptocurrency adoption through the unified theory of acceptance and use of technology (UTAUT) and complexity theory.

By using a purposive sampling method, a configurational model was developed and a questionnaire-based survey was conducted to gather responses from a Malaysian sample. A total of 223 responses were obtained. Partial least square structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) were adopted to analyze the data.

The PLS-SEM indicated that performance expectancy, effort expectancy, social influence and affinity for technology interaction were positive cryptocurrency adoption predictors, whereas regulation was a negative predictor. Based on the fsQCA, cryptocurrency adoption could be explained by six configurational paths, which comprised combinations of the proposed causal conditions: the UTAUT factors (performance expectancy, effort expectancy, facilitating condition and social influence), environmental factor (regulation) and individual factors (financial knowledge and affinity for technology interaction).

This study offers contributions to the theoretical body of knowledge by articulating the relevance of extended UTAUT and extending the established UTAUT model by integrating external environment and personal factors, also showing the linear and nonlinear interplays of performance expectancy, effort expectancy, facilitating conditions, social influence, regulation, financial knowledge and affinity for technology interaction.

The findings facilitated practitioners’ (cryptocurrency brokers, governments and businesses) fostering of cryptocurrency adoption through the joint consideration of different factors. The factors spanned technological attributes and individual characteristics to regulation. Practitioners should acknowledge that different combinations of the aforementioned antecedents can be equally effective to increase cryptocurrency adoption. The findings suggested that these causal conditions should be considered holistically and that there is no best predictor.

In social terms, the research is expected to contribute to the dissemination of cryptocurrencies and help governments and central banks to develop, regulate and supervise digital currencies, as well as in the implementation of a digital currency ecosystem aligned with sustainable development goals. Economically, the results might foster a high cryptocurrency adoption rate and stimulate crypto-token-based business models and investment opportunities that present new means of revenue generation at individual, organizational and national levels.

This study offers unique perspectives for the body of knowledge and practice in the cryptocurrency domain, using both symmetric and asymmetric methodologies, by delineating the configurational logic involving technological capabilities, social influences, regulation and individual characteristics in facilitating more efficacious dissemination of cryptocurrencies.

This study aims to develop an interface management risk interaction modeling and analysis methodology applicable to complex systems in high-speed rail construction projects, reveal the interaction mechanism of interface management risk and provide theoretical support for project managers to develop appropriate interface management risk response strategies.

This paper introduces the association rule mining technique to improve the complex network modeling method. Taking China as an example, based on the stakeholder perspective, the risk factors and significant accident types of interface management of high-speed rail construction projects are systematically identified, and a database is established. Then, the Apriori algorithm is used to mine and analyze the strong association rules among the factors in the database, construct the complex network, and analyze its topological characteristics to reveal the interaction mechanism of the interface management risk of high-speed rail construction projects.

The results show that the network is both scale-free and small-world, implying that construction accidents are not random events but rather the result of strong interactions between numerous interface management risks. Contractors, technical interfaces, mechanical equipment, and environmental factors are the primary direct causal factors of accidents, while owners and designers are essential indirect causal factors. The global importance of stakeholders such as owners, designers, and supervisors rises significantly after considering the indirect correlations between factors. This theoretically explains the need to consider the interactions between interface management risks.

The interaction mechanism between interface management risks is unclear, which is an essential factor influencing the decision of risk response measures. This study proposes a new methodology for analyzing interface management risk response strategies that incorporate quantitative analysis methods and considers the interaction of interface management risks.

Virtual kitchens are a new business phenomenon, and how customers react to the new business model is still a largely unexplored topic. The purpose of this study is to examine the underlying mechanisms of consumers’ different responses to their reasoning of the new and disruptive business model of the virtual kitchen.

Based on the attribution theory and situated focus theory of power, this study conducts three online experiments to test the proposed framework. A total of 487 US residents who had prior experience with restaurant food delivery participated in the studies.

The results indicate that external attribution (vs internal attribution) and ethnic cuisine (vs mainstream cuisine) are more likely to elicit customers’ empathy and justice, leading to higher purchase intentions with virtual kitchens. A mainstream virtual kitchen is better off attributing itself to external factors. The significant effects of causal attribution and cuisine type on purchase intention only exist with powerful customers and those with high moral identity.

The results of this study provide valuable insight to virtual kitchen businesses to better position and market themselves to gain customers’ support. The findings also suggest that ethnic and mainstream restaurants should strategize their marketing communications about virtual kitchens differently.

To the best of the authors’ knowledge, this study is one of the first to provide in-depth insight into the growing phenomenon of virtual kitchens. It also contributes to the extant literature on attribution theory and situated focus theory of power.

According to the Project Management Institute, 70% of projects fail globally. The causes of project failure in many instances can be identified as non-technical or behavioral in nature arising from interactions between participants. These intangible risks can emerge in any project setting but especially in project settings having diversity of cultures, customs, beliefs and traditions of various companies or countries. This paper provides an objective framework to address these intangible risks.

This paper presents a structured approach to identify, assess and manage intangible risks to enhance a project team’s ability to meet its objectives. The authors propose a user-friendly framework, Intangible Risk Assessment Methodology for Projects (IRAMP), to address these risks and the factors that cause them. Meta-network (e.g., a network of networks) simulation and established social network analysis (SNA) measures provide a quantitative assessment and ranking of causal events and their influence on the intangible behavior centric risks.

The proposed IRAMP and meta-network approach were utilized to examine the project delivery process of an international energy firm. Data were gathered using structured interviews, surveys and project team workshops. The use of the IRAMP to highlight intangible risk areas underpinned by the SNA measures led to changes in the company’s organizational structure to enhance project delivery effectiveness.

This work extends the existing project risk management literature by providing a novel objective approach to identify and quantify behavior centric intangible risks and the conditions that cause them to emerge.

Because family businesses are highly complex enterprises, researchers need appropriate theoretical and methodological tools to study them. The neoconfigurational perspective and its accompanying method, qualitative comparative analysis, are particularly well suited to phenomena characterized by complex causality, but their uptake in family business research has been slow and fragmented. To remedy this, the authors highlight their unique ability to address research questions for which other approaches are not well suited and discuss how they might be applied to family business phenomena.

The authors introduce the core tenets of the neoconfigurational perspective and how its set-theoretic epistemology differs from traditional approaches to theorizing and analysis. The authors then use a dataset of family firms to present a primer on conducting qualitative comparative analysis and interpreting the results.

The authors find that family firm resources can be combined in multiple ways to affect business survival, suggesting that resources are substitutable and complementary. The authors discuss how the unique features of the neoconfigurational approach, namely equifinality, conjunctural causation and causal asymmetry, can be fruitfully applied to break new ground in scholarly understanding of family businesses.

This article allows family business researchers to apply the neoconfigurational approach without first having to consult multiple and disparate sources often written for other disciplines. This article explicates how to leverage the theoretical and empirical advantages of the neoconfigurational approach in the context of family businesses, supporting a more widespread adoption of the neoconfigurational perspective in family business research.

Given the complexities in improving safety in the construction industry globally, which is exacerbated by the complex safety environment in developing countries (DCs), prevention through design (PtD) has been established to improve occupational safety and health (OSH) where applied. However, it has received very little attention in DCs and the extant literature with limitations. Using Nigeria as a case study, the current study advances the understanding of PtD in DCs by investigating the critical barriers to PtD and other potential OSH responsibilities of designers in the construction industry.

Twenty-eight semi-structured interviews and e-interviews of architects, builders and civil engineers in Nigeria were analysed using the six-phase thematic analysis. To improve the trustworthiness of the research, triangulation, peer-debriefing, refining the interview protocol and thick detailed description were done.

The study's findings question the extant general knowledge and understanding of PtD among clients and designers and its technical aspect among designers where it is skewed to structural safety and omitted in universities' curricula. This explains the inconclusive findings of existing studies on why there is a high level of awareness of PtD but a low level of implementation. There is little client support for PtD, and designers have limited influence on clients in terms of it. The fear of liability from PtD is exacerbated by the limited legal system and lack of adequate legislation in the country. The demotivating attitudes of clients and contractors towards designers in terms of PtD are also reported, just as there are project delivery barriers such as traditional procurement not supporting PtD as design and build procurement does.

For the sustainable growth in the practice of PtD, the increased and improved quality of education and awareness of PtD is needed but this must focus on instilling a robust understanding of it among designers based on the local context. This educational requirement can be supported by statute.

Through qualitative data, the findings explain and offer insight into the inconclusive findings in the extant studies on PtD in Nigeria. Also, it contributes to improving health and safety by advancing the understanding of the critical barriers to PtD and other potential OSH responsibilities of designers in D Nigeria's construction using qualitative data.

This study aims to attempt to investigate the time-varying causality and price spillover effects between crude oil and exchange rate markets in G7 economies during the COVID-19 and Russia–Ukraine crises.

This study uses time-varying Granger causality test and spillover index.

This study finds a time-varying causality between exchange rate returns and oil prices, implying that crude oil prices have the predictive power of the foreign exchange rate markets in G7 economies in their domain. Furthermore, the total spillover index is estimated to fall significantly around COVID-19 and war events. However, this index is relatively high – more than 57% during the first wave of COVID-19 and decreasing slightly during the Russia–Ukraine conflict.

This outcome supports the hypothesis that the majority of the time-varying interaction between exchange rates and oil prices takes place in the short term. As a result, the time-varying characteristics provide straightforward insight for investors and policymakers to fully understand the intercorrelation between oil prices and the G7 exchange rate markets.

First, this study has reexamined the oil–exchange rate nexus to highlight new evidence using novel time-varying Granger causality model recently proposed by Shi et al. (2018) and the spillover index proposed by Diebold and Yilmaz (2012). These approaches allow the author to improve understanding of time-varying causal associations and return transmission between exchange rates and oil prices. Second, compared to past papers, this paper has used data from December 31, 2019, to October 31, 2022, to offer a fresh and accurate structure between the markets, which indicates the unique experience of the COVID-19 outbreak and Russia–Ukraine war episodes. Third, this study analyzes a data set of seven advanced economies (G7) exhibiting significant variations in their economic situations and responding to global stress times.