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Under the background of coexistence of information overload and information fragmentation, it is of great significance to identify influencing factors and reveal the evolution logic of public opinion for public opinion governance.

Taking 24 hot social events as research cases, firstly, the evolution process of public opinion was divided into initial stage and response stage. Secondly, eight antecedent variables were extracted for qualitative comparative analysis of fuzzy sets. Finally, the configuration path of public opinion evolution results was summarized.

The research showed that compared with the initial stage, the influencing factors in the reaction stage played a key role in the continuous evolution of public opinion. The influencing factors in the initial stage and response stage played an indispensable role in promoting the evolution of public opinion to calm down.

This research can provide reference for regulators to timely grasp the initiative, discourse power and leadership of public opinion development.

Research on the two-stage configuration path of public opinion evolution is helpful to clarify the key factors affecting the evolution trend of online public opinion of hot events.

The objective is to develop an empirical model estimating the relationship and interaction amongst the factors affecting and enhancing green finance (GF) in developing economies like India.

Around nine growth-accelerating enablers of green financing were found through literature and unstructured interviews and analysed using the total interpretive structural modelling (TISM) method. The hierarchical link between each factor is established using TISM, and further to evaluate the driver-dependent relationship the Matriced’ Impacts Croises Appliquee Aaun Classement (MICMAC) approach is utilised.

The findings demonstrate an interrelationship between growth-accelerating factors, where the political environment and information and communication technology (ICT), have minimal dependency but a strong driving force. Political environment and ICT are found as strategic-level factors lying at the bottom of the model driving towards the dependent variables. The government should focus on enacting effective policies such as the green credit guarantee scheme and carbon credit and establishing a regulatory framework to enhance green financing.

This study examines the literature to generalise the findings and focus on the primary motivators for developing green financing. To increase green financial activity, practitioners must concentrate on aspects with significant driving forces. Furthermore, it makes organisations more profitable, efficient and competitive and promotes long-term growth.

The study is the first in the literature which identifies the growth-accelerating factors of green financing using the TISM and MICMAC-based hierarchical models.

Mega construction projects (MCPs), which play an important role in the economy, society and environment of a country, have developed rapidly in recent years. However, due to frequent social conflicts caused by the negative social impact of MCPs, social risk control has become a major challenge. Exploring the relationship between social risk factors and social risk from the perspective of risk evolution and identifying key factors contribute to social risk control; but few studies have paid enough attention to this. Therefore, this study aims to systematically analyze the impact of social risk factors on social risk based on a social risk evolution path.

This study proposed a social risk evolution path for MCPs explaining how social risk occurs and develops with the impact of social risk factors. To further analyze the impact quantitatively, a social risk analysis model combining structural equation model (SEM) with Bayesian network (BN) was developed. SEM was used to verify the relationship in the social risk evolution path. BN was applied to identify key social risk factors and predict the probabilities of social risk, quantitatively. The feasibility of the proposed model was verified by the case of water conservancy projects.

The results show that negative impact on residents’ living standards, public opinion advantage and emergency management ability were key social risk factors through sensitivity analysis. Then, scenario analysis simulated the risk probability results with the impact of different states of these key factors to obtain management strategies.

This study creatively proposes a social risk evolution path describing the dynamic interaction of the social risk and first applies the hybrid SEM–BN method in the social risk analysis for MCPs to explore effective risk control strategies. This study can facilitate the understanding of social risk from the perspective of risk evolution and provide decision-making support for the government coping with social risk in the implementation of MCPs.

This paper aims to identify the critical project management success factors and analyze those factors to achieve a sustainable construction industry in Bangladesh.

This study identified 41 major problematic factors from the related literature. In this research, a detailed questionnaire survey was conducted among the experts and stakeholders of the construction industry of Bangladesh. The survey was carried out on a Likert scale and ranked the critical factors using the relative importance index (RII). The 41 problematic factors were divided into five group factors and ranked by the RII index to prioritize the factors. Finally, stakeholders' opinions were analyzed with the critical assessed factors, which was a very effective technique to eliminate the risks and uncertain occurrences in the construction industry of Bangladesh.

The factors analysis revealed that cost overrun, traffic jam, low wedges, slow payment for completed works and financial issues of the owner were leading critical factors in construction projects. Moreover, the critical factors are divided into five-factor groups, namely, financial management, monitoring and feedback, competency management, communication and coordination management, and risk management, which exhibit 0.767, 0.720, 0.711, 0.710 and 0.658 RII values. After all, the stakeholders' opinion suggested that implementing modern tools and techniques can help to avoid the critical situation in the construction industry of Bangladesh.

The construction industry of Bangladesh is moving away from stable construction work day by day. Previously, the potential CSFs were discussed unstructured way. Hence, detecting early warning signals in a structured way has become necessary for the building firm's survival.

Though some scattered critical issues are discussed in different literature, the critical issues of the Bangladeshi construction industry were not investigated extensively. Therefore, this study finds out the potential critical issues of the construction industry of Bangladesh to accumulate such harmful construction issues in a single platform so that the construction industry can have an overview of them with the help of innovative technologies.

Construction delay always causes massive damage to the advancing construction industries, which is no different in the case of Bangladeshi construction industries. This paper aims to investigate the major delay factors causing construction delays in public-funded, mixed and private-funded construction projects of Bangladesh. Also, it offers preventive suggestions from expert stakeholders to reduce the recurrence of delays.

At first, an extensive literature review was conducted to identify the thirty-seven major delay factors categorized under seven groups. A questionnaire was then developed for survey at ongoing construction projects at a different division of Bangladesh. Next, data from 110 respondents were collected, and the delay factors were ranked based on the Relative Importance Index (RII); lastly, probable solutions were suggested for top-ranked delay factors based on opinions from expert stakeholders in the construction sector of Bangladesh.

The overall RII ranking of the 37 delay factors showed “Construction mistakes and defective work,” “Contract modifications by the client” and “Adverse weather condition” as the top three factors causing the delay. For public-funded projects, “Construction mistakes and defective work” and “Slow decision making by a consultant” are the top delay factors. For mixed projects, “Slow decision making of the client” and “Construction mistakes and defective work ranked top, and for private-funded projects, “Financial problems and payment delay of the client” and “Adverse weather condition” ranked top. These nuances of ranking in individual project types ascertain that the causes of delay vary in terms of project features.

The outcome of this project will help identify the significant delay factors based on their severity of effectiveness associated with public-funded, mixed and private-funded projects in Bangladesh. The suggestions regarding preventing these delay factors obtained through the opinions of expert stakeholders can help reduce the effect of these delays in the context of Bangladesh and in countries where the similarity in construction environment prevails.

Previously, studies on construction delays in Bangladesh focused mainly on identifying the delays using qualitative analysis techniques. This study is based on a unique methodology of integrating quantitative research on delay factor identification and qualitative research on preventive measures following the opinions gathered from expert stakeholders in the construction sector.

The present study investigates the impact of opinion leadership and spirituality from three types of social media influencers (SMIs) on individuals’ intentions to conduct recycling. This research is driven by the opinion leadership theory demonstrated by influencer marketing.

This research applies a between-subject experiment to measure the impact of the proposed model. Each participant was exposed to a different influencer: an attractive influencer (Treatment 1, n = 101), an expert influencer (Treatment 2, n = 94), a religious influencer (Treatment 3, n = 99) and a control condition (Treatment 4, n = 102). An ANOVA post-hoc analysis was conducted to further assess the impact dynamics of each influencer based on different demographics such as age, income and level of education. More than 95% of the samples consist of Muslims.

Findings revealed the different dynamics of the effect of opinion leadership and spirituality on the intention to recycle from utilising different types of influencers. Samples derived from a high socio-economic background and exposed to the religious influencer (Treatment 3) have a relatively higher mean score. In general, younger participants with lower incomes and levels of education have less tendency to conduct recycling.

This research attempts to fill the gap in the impact of influencer marketing on green behaviour adoption with the inclusion of spirituality, which has been largely ignored in this context. It offers insights from the perspective of a developing economy that has one of the largest percentages of social media users in the world and from a country that regards a relationship with God as important.

Open innovation has attracted the attention of experts and business entities for the sustainable survivability of firms, especially in the post-COVID-19 era. The food and beverage industry has been facing sustainable survivability problems. It is important to identify and evaluate the factors of open innovation from the perspectives of the food and beverage industry. This study serves that purpose by identifying and evaluating the factors of open innovation in the post-COVID-19 era with a special reference to Pakistan's economy.

The present study integrates the Fuzzy Delphi Method (FDM), Interpretive Structural Modelling (ISM) and Matrice d’ Impacts Croises Multiplication Applique a Classement (MICMAC) methods to analyze the factors involved in the adoption of open innovation in the food and beverage industry in Pakistan. Firstly, based on an extensive literature review of the most relevant studies, the factors affecting open innovation have been identified and finalized using FDM and experts' opinions. Secondly, the hierarchical framework has also been prepared by implementing the ISM approach. Thirdly, the MICMAC approach was employed to evaluate the factors to examine the driving and dependence powers of the factors of open innovation adoption.

The study identified 17 factors of open innovation adoption in Pakistan's food and beverage industry and 16 factors were finalized using FDM. The ISM-MICMAC matrix unveiled that awareness seminars and training, along with a lack of executive commitments, were strong factors with high driving power, but these factors proved to be weakly dependent powers regarding the other factors. Moreover, a lack of innovation strategy, R&D and non-supportive organizational culture exhibited low driving power but strong dependent power.

The findings of the study could help firms and business entities understand the driving and dependent factors involved in open innovation for the sustainable survivability of the food and beverage industry. The study provides strong reasons to believe that an open innovation strategy, along with stakeholder collaboration, the adoption of rules and regulations and managerial commitment, could stimulate open innovation. Moreover, governments should promote the business sector, especially the food and beverage industry, to facilitate the sector while also providing awareness seminars and training, creating environments conducive to reducing innovation costs.

Some previous studies have analyzed the factors involved in green innovation from the perspective of the manufacturing industry and environmental protection. The present study is a pioneer study to examine the factors involved in the adoption of open innovation in the food and beverage industry in Pakistan from the perspective of the post-COVID-19 era. For this purpose, the present study uses an integrated Fuzzy Delphi-ISM-MICMAC approach for the analysis.

This study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.

This research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.

The results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.

This study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

This study aims to assess the readiness of both citizens and the government for digital participatory planning (DDP) as a contribution to the undergoing transformative shift toward smart and sustainable cities to address the challenges posed by rapid urbanization. While much attention has been devoted to leveraging technology to mitigate these challenges, there has been a relative lack of emphasis on engaging stakeholders in the planning process in a smart and inclusive manner. DPP stands as a cornerstone for the development of sustainable and smart cities. However, before DPP can be effectively implemented on the ground, it is crucial to assess the city readiness for DPP to ensure its success. This assessment is undertaken as part of Oman's broader initiative to transition into sustainable smart cities in alignment with the goals outlined in Oman Vision 2040.

A generic evaluation framework was identified, validated and customized to the local context by experts using the pile sorting technique based on the social constructivism theory. Then, the revised framework was used to evaluate the readiness of a sample of local citizens and government officials in Oman for the DPP concept.

The inferential statistical analysis revealed that citizens are willing to participate in DPP when trust and transparency with policymakers are enhanced. On the government side, the results showed that there is adequate infrastructure that can enable DPP, and planners have a positive attitude toward DPP provided that trust in citizens' opinions is strengthened. This study concludes with a roadmap for preparation for DPP implementation in smart sustainable cities mandated by Oman Vision 2040. The findings and roadmap can inform policy development, decision-making and urban planning practices toward more inclusive, participatory and technologically enabled urban environments.

The study contributes to the existing body of knowledge by emphasizing the significance of stakeholders' smart involvement in planning processes, social sustainability, evaluating city readiness for DPP and providing practical recommendations for DPP implementation in the context of smart sustainable cities. At a theoretical level, the study contributes a framework for assessing readiness for DPP and emphasizes that mutual trust is not only important for conventional participation practices but it is also essential for smart citizens. This study argues that a building or a city is not sustainable unless it is seen as such by its stakeholders, including the end users. Therefore, effective and smart involvement of the citizens in smart city planning is a precondition for the success of the future cities.

Staffing is one of the most influential human resource (HR) activities and is the primary method of hiring and retaining human resources. Among staffing’s several activities, recruitment and selection are one of the most crucial activities. It is possible to rehire former firm employees using the talent management strategy known as “boomerang recruitment”. The boomerang recruitment trend has tremendously grown because many employees who believe they are qualified for the position now wish to return to their old employers. According to data, boomerang employees can be 50% less expensive than conventional ways of hiring. The purpose of this study is to identify the generic critical factors that play a role in the boomerang hiring process based on the literature review. Next, the objective is to determine the relative weight of each of these factors, rank the candidates, and develop a decision-making model for boomerang recruitment.

This paper focuses on the grey-based multicriteria decision-making (MCDM) methodology for recruiting some of the best candidates out of a few who worked for the organization earlier. The grey theory yields adequate findings despite sparse data or significant factor variability. Like MCDM, the grey methods also incorporate experts' opinions for evaluation. Furthermore, sensitivity analysis is also done to show the robustness of the suggested methodology.

Seven (7) recruitment criteria for boomerang employees were identified and validated based on the opinions of industry experts. Using these recruitment criteria, three candidates emerged as the top three and created a pool out of six. In addition, this study finds that Criteria 1 (C1), the employee's past performance, is the most significant predictor among all other criteria in boomerang hiring.

Since the weights and ratings of attributes and alternatives in MCDM methods are primarily based on expert opinion, a significant difference in expert opinions (caused by differences in their knowledge and qualifications) may impact the values of the grey possibility degree. However, enough attention was taken while selecting the experts for this study regarding their expertise and subject experience.

The proposed method provides the groundwork for HR management. Managers confronted with recruiting employees who want to rejoin may use this model. According to experts, each attribute is not only generic but also crucial. In addition, because these factors apply to all sectors, they are industry-neutral.

To the best of the authors’ knowledge, this is the first study to apply a grey-based MCDM methodology to the boomerang recruitment model. This study also uses an example to explain the computational intricacies associated with such methods. The proposed system may be reproduced for boomerang recruiting in any sector because the framework is universal and replicable. Furthermore, the framework is expandable to include new criteria for different work.