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This study aims to develop an interrelation model between critical parameters for assessing the construction readiness (CR) of abandoned housing projects, using Malaysia as a case study. To achieve that aim, the study objectives are to (1) identify critical parameters for assessing the CR of abandoned housing projects; (2) develop underlying constructs to categorize interrelated critical parameters and (3) assess the influence of the underlying constructs on the CR of abandoned housing projects.

This study identifies potential parameters for assessing the CR of abandoned housing projects by reviewing existing literature and interviewing industry professionals. Then, the list was used to develop a questionnaire survey. The collected survey data were analyzed using normalized mean analysis to identify the critical parameters. Exploratory factor analysis (EFA) was used to develop underlying constructs to categorize interrelated critical parameters. Finally, the influence of the underlying constructs on the CR of abandoned housing projects was examined through partial least squares structural equation modeling (PLS-SEM).

The analyses suggest that 21 critical parameters are affecting the CR of abandoned housing projects. The critical parameters can be categorized into four underlying constructs: construction site evaluation, management verification, uncertainties mitigation and document approval. Finally, the analyses confirmed that all four constructs affect the CR of abandoned housing projects.

This study is a pioneering effort to quantitatively analyze the parameters for assessing the CR of abandoned housing projects. The findings significantly benefit researchers and industry professionals by providing a list of critical parameters associated with the CR of abandoned housing projects.

Through the use of the Markov Decision Model (MDM) approach, this study uncovers significant variations in the availability of machines in both faulty and ideal situations in small and medium-sized enterprises (SMEs). The first-order differential equations are used to construct the mathematical equations from the transition-state diagrams of the separate subsystems in the critical part manufacturing plant.

To obtain the lowest investment cost, one of the non-traditional optimization strategies is employed in maintenance operations in SMEs in this research. It will use the particle swarm optimization (PSO) algorithm to optimize machine maintenance parameters and find the best solutions, thereby introducing the best decision-making process for optimal maintenance and service operations.

The major goal of this study is to identify critical subsystems in manufacturing plants and to use an optimal decision-making process to adopt the best maintenance management system in the industry. The optimal findings of this proposed method demonstrate that in problematic conditions, the availability of SME machines can be enhanced by up to 73.25%, while in an ideal situation, the system's availability can be increased by up to 76.17%.

The proposed new optimal decision-support system for this preventive maintenance management in SMEs is based on these findings, and it aims to achieve maximum productivity with the least amount of expenditure in maintenance and service through an optimal planning and scheduling process.

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.

The purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values for the prominent risks and overall industry are determined based on the four risk parameters, which would help determine the most contributive risks for mitigation.

An extensive literature survey was done to identify the risks, which were also validated by industry experts. The finalized risks were then evaluated using the fuzzy synthetic evaluation (FSE) method, which is the most suitable approach for the risk assessment with parameters having a set of different risk levels.

The three most contributive sub-risks are counterfeit drugs, demand fluctuations and loss of customers due to partners' poor service performance, while the main risks obtained are demand, financial and logistics. Also, the overall risk value indicates that the industry faces medium to high risk.

The study identifies the critical risks which need to be mitigated for an efficient industry. The industry is most vulnerable to the demand risk category. Therefore, the managers should minimize this risk by mitigating its sub-risks, like demand fluctuations, bullwhip effect, etc. Another critical sub-risk, the counterfeit risk, should be managed by adopting advanced technologies like blockchain, artificial intelligence, etc.

There is insufficient literature focusing on risk quantification. Therefore, this work addresses this gap and obtains the industry's most critical risks. It also discusses suitable mitigation strategies for better industry performance.

This paper aims to illustrate the extensive benefits of qualitative data analysis as a rarely undertaken process in post-occupancy evaluation surveys. As a result, there is limited evidence of what occupants say about their buildings, especially for operational parameters, as opposed to how they rate them. While quantitative analyses provide useful information on how workers feel about workplace operational factors, qualitative analyses provide richer information on what aspects of the workplace workers identify as influential to their comfort, well-being and productivity.

The authors analysed 6,938 comments from office buildings worldwide on workers’ perception of workplace operational factors: design, storage, needs, space at desks and storage in their work environments. These factors were analysed based on the buildings’ design intent and use, and the associated comments were coded into positive, negative and balanced comments. The authors used a combination of coding, descriptive analysis, content analysis and word cloud to dissect the comments.

The findings showed that whereas workers rated these operational factors favourably, there were significantly more negative comments about each factor. Also, the Chi-square test showed a significant association (p < 0.01) between the satisfaction scale and the type of comments received for all the operational factors. This means that when a factor is rated high in the satisfaction score (5–7), there were fewer negative and more positive comments and vice versa. The word cloud analysis highlighted vital aspects of the office environment the workers mostly commented on, such as open plan design, natural lighting, space and windows, toilets, facilities, kitchens, meeting room booking systems, storage and furniture.

This study highlights the importance of dissecting building occupants’ comments as integral to building performance monitoring and measurement. These emphasise the richness and value of respondents’ comments and the importance of critically analysing them. A limitation is that only 6,938 comments were viable for analysis because most comments were either incomplete with no meaning or were not provided. This underlines the importance of encouraging respondents to comment and express their feelings in questionnaire surveys. Also, the building use studies questionnaire data set presents extensive opportunities for further analyses of interrelationships between demographics, building characteristics and environmental and operational factors.

The findings from this study can be applied to future projects and facility management to maintain and improve office buildings throughout their life cycle. Also, these findings are essential in predicting the requirements of future workplaces for robust workplace designs and management.

The authors identified specific comments on the performance of workplaces across the globe, showing similarities and differences between sustainable, conventional, commercial and institutional buildings. Specifically, the analysis showed that office workers’ comments do not always corroborate the ratings they give their buildings. There was a significantly higher percentage of negative comments than positive comments despite the high satisfaction scores of the operational factors.

The purpose of this study is to propose a methodological approach for modeling catastrophic consequences caused by black swan events, based on complexity science, and framed on Feyerabend’s anarchistic theory of knowledge. An empirical application is presented to illustrate the proposed approach.

Thom’s nonlinear differential equations of morphogenesis are used to develop a theoretical model of the impact of catastrophes on international business (IB). The model is then estimated using real-world data on the performance of multinational airlines during the SARS-CoV-2 (COVID-19) pandemic.

The catastrophe model exhibits a remarkable capability to simultaneously capture complex linear and nonlinear relationships. Through empirical estimations and simulations, this approach enables the analysis of IB phenomena under normal conditions, as well as during black swan events.

To the best of the author’s knowledge, this study is the first attempt to estimate the impact of black swan events in IB using a catastrophe model grounded in complexity theory. The proposed model successfully integrates the abrupt and profound effects of catastrophes on multinational corporations, offering a critical perspective on the theoretical and practical use of complexity science in IB.

The study responds to the common concerns of authors, reviewers, and editors on writing and publishing high-quality literature review (LR) studies. First, we evolved the background and decision elements on the five parameters of a quality LR paper: Planning, Operationalizing, Writing, Embedding, and Reflecting (POWER), from the editorials and guiding literature. Statistical procedure and refinement of 256 responses from writers, reviewers, and editors revealed 37 decision elements. Finally, a multicriteria-decision-making approach was applied to the detailed responses from the lead editors of ABDC, Scopus, ABS, and WoS journals, and 31 decision elements were found strong enough to represent these five parameters on the quality of LR studies. All five parameters are found important to be considered. However, a high priority is suggested for embedding (the results coming out of the review) and operationalizing (the process of conducting the review), whereas reflection, writing, and planning of LR papers still remain important. The purpose of the POWER framework is to overcome the challenges and decision dilemmas faced by writers and decision-makers. The POWER framework acts as a guiding tool to conduct LR studies in general and business management scholars in specific ways. In addition, this study provides a checklist (Table 6) and template (Appendix A1) of a quality LR study to its stakeholders.

Drawing from emotional geography framework promoted by Hargreaves (2000), our research sought to depict the emotional geography of two faculty members who engaged in a virtual teacher professional development (VTPD) sessions during the COVID-19 pandemic. This study aimed to focus on capturing participants’ emotional closeness or distance while they were engaging in VTPD.

This study employed narrative inquiry by exploring three-dimensional narrative inquiry space: temporality, personal-social interaction and place (Clandinin and Connelly, 2000). Following this step, the participants were interviewed online through Zoom meetings and WhatsApp to capture critical incidents of their emotional experience. All collected data were transcribed, and some data from Bahasa Indonesia were translated into English. Member checking was also done several times to ensure the accuracy of the data as well as to avoid misinterpretation. The data were analysed inductively to generate coding categories using systemic functional linguistics (SFL) language appraisal (Martin and White, 2007) and emotional geography parameter (Hargreaves, 2001b).

The findings of the study revealed that both participants experienced greater positive feeling than negative ones. The participants experienced positive feelings such as seriousness, happiness, successfulness and satisfaction. They also experienced negative feelings such as insecurity, unhappiness, dissatisfaction and impatience. Such positive and negative feelings create closeness and distance among participants, mentor and workshop organiser. This study indicates that maintaining positive feelings is a passport to succeed in VTPD.

The study has two limitations. First, its findings cannot be overgeneralised since the analysis was restricted to data gathered from a small number of participants. Second, the scope of investigation was limited in virtual situations.

The present study empirically showed that faculty members need to engage in constructing or maintaining positive emotional bond with the mentor and other participants and create conducive situations to understand their own and others’ emotions (Mayer, 2011). Practically, a mentor in VTPD may ask faculty members to voice and share their emotional experience as an evaluation tool to make VTPD programmes more successful. Future participants can benefit from these findings by engaging in emotional understanding and building a conducive situation during VTPD to develop their academic competence, agency and identity.

While previous research into VTPD in the context of higher education mainly focused on designs, attention to pedagogy of online teacher learning environments, trends toward innovation in teacher collaboration and communities of practice in online settings, the present study specifically looked into how participants emotionally engaged in VTPD, which is inevitably linked to physical, moral, sociocultural, professional and political geographies.

It is essential for developed nations to have adequate and functional infrastructure to sustain economic growth and well-being. Despite efforts to reduce the chances of infrastructure problems, several scholars have expressed concern about infrastructure standards deteriorating at an alarming rate and the need to ensure their sustainability. To achieve sustainable infrastructure development (SID), Sahely et al. (2005) proposed an uncomplicated strategy based on fundamental cooperation between infrastructure and ecological, economic, and social frameworks. Sustainable infrastructure is defined as the development and dependable management of a safe built environment based on efficient resource utilization and environmental standards. SID aims to mitigate or eliminate ecological problems and challenges while maximizing the potential social and economic benefits. United Nations Economic and Social Commission for Asia and the Pacific (UN-ESCAP, 2007) defines SID as infrastructure compatible with continued financial and environmental sustainability. Sustainable road development infrastructure (SRID) is a procedure for constructing infrastructure that incorporates all the essential sustainable development (SD) parameters and is complicated by the interdependence of multiple factors. Stakeholders are essential for the successful execution of infrastructure projects, and a comprehensive evaluation of stakeholder interests and requirements is necessary to achieve SRID goals while meeting the needs of all parties involved. To achieve SRID, it is necessary to understand the relationship between road infrastructure development (RID) processes and SD standards and to implement criteria and indicators that accurately depict the long-term viability of a development process. Al Sanad (2015) identified several factors that may impede the implementation of SD in the infrastructure sector. Shafii et al. (2006) identified insufficient knowledge of SID, lack of SID training, a perception of SID as expensive, acquisition concerns, administrative issues, expert capacities, and motivational factors for manufacturing local materials as potential obstacles. Serpell (2013) identified four categories of SID challenges, including knowledge, economic and financial, organizational, and go. Darko and Chan (2016) identified the most prevalent barriers as a lack of data, training, research, information, and expertise, high cost, government interest, premium and demand, and the absence of SID standards of practice. Azis et al. (2012) identified improved project efficiency, waste reduction in the construction industry, and energy efficiency as advantages of SID. Ametepey and Aigbavboa (2014) identified energy savings, environmental protection, contribution to a higher standard of living and a healthy work environment, resource preservation for future generations, reduction in lifecycle costs, promotion of sustainable economic development, and stakeholder satisfaction as the top benefits of sustainable construction (SC). Du Plessis (2007) identified technological factors, Al Sanad (2015) identified educational programmes, Serpell et al. (2013) identified transformation, economic, and stakeholder engagement as drivers of SC, and Hankinson and Breytenbach (2012) identified enhanced SC awareness. This chapter reviewed the literature on international infrastructure and sustainability development, discussing factors, and benefits promoting SID.

The future increase of chronic diseases in the world requires new challenges in the health domain to improve patients' care from the point of view of the organizational processes, clinical pathways and technological solutions of digital health. For this reason, the present paper aims to focus on the study and application of well-known clinical practices and efficient organizational approaches through an innovative model (TALIsMAn) to support new care process redesign and digitalization for chronic patients.

In addition to specific clinical models employed to manage chronic conditions such as the Population Health Management and Chronic Care Model, we introduce a Business Process Management methodology implementation supported by a set of e-health technologies, in order to manage Care Pathways (CPs) digitalization and procedures improvement.

This study shows that telemedicine services with advanced devices and technologies are not enough to provide significant changes in the healthcare sector if other key aspects such as health processes, organizational systems, interactions between actors and responsibilities are not considered and improved. Therefore, new clinical models and organizational approaches are necessary together with a deep technological change, otherwise, theoretical benefits given by telemedicine services, which often employ advanced Information and Communication Technology (ICT) systems and devices, may not be translated into effective enhancements. They are obtained not only through the implementation of single telemedicine services, but integrating them in a wider digital ecosystem, where clinicians are supported in different clinical steps they have to perform.

The present work defines a novel methodological framework based on organizational, clinical and technological innovation, in order to redesign the territorial care for people with chronic diseases. This innovative ecosystem applied in the Italian research project TALIsMAn is based on the concept of a continuum of care and digitalization of CPs supported by Business Process Management System and telemedicine services. The main goal is to organize the different socio-medical activities in a unique and integrated IT system that should be sustainable, scalable and replicable.