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Educational policies, integrated practices, obliged strategies and notable benchmarks are always required by the higher educational institutions (HEIs) for operating business ventures into competent boundaries and to preside toward the overall new business density. The same are needed to be evaluated based on student's concerns for road-mapping sustainability. Accordingly, authors conducted present study to identify crucial quality characteristics (measures) under the origins of HEIs based on student's concerns using qualitative medium under Indian economy. The study is presenting critical dimensions and quality characteristics, which are seeking by the students for selecting HEIs for their studies.

Kano integrated-Grey-VIKOR approach is utilized in present study for road-mapping sustainability based on the determination of priority index and ranking. The study utilized three segments of methodology, where in the first segment, Kano technique is implicated to define priority index of quality characteristics. In the second segment, grey sets theory is implicated to capture the perceptions of the respondents. In the third segment, VIKOR technique is implicate to rank the HEIs.

The findings of the study will assist administrators in planning the prominent strategies that can embrace performance traits under HEI, which in turn will participate in growth and development of an economy. The findings have revealed “PPCS, ICMC, TSTR, PICM, AFEP, IMIS as Attractive performance characteristics,” “IEAF, OIAR, INET as One dimensional performance characteristics,” “QTCS, PORE, SIRD as Must-be performance characteristics” and “PQPE, PCTM as Indifferent performance characteristics.” Additionally, “Professional and placement characteristics of institute” is found as the most significant measure inspiring students for admiring engineering institutes. It is found that “Observance of institutional affiliation and recognition” and “Infrastructure, classroom management and control methods” are found as the second significant measures. “Patterns of question papers and evaluation medium” and “Personal characteristics of teacher and management” are found as the least competent characteristics admiring stakeholders for selecting HEI.

The present study can assist administrators in drafting refined policies and strategies for practising quality outputs by HEI. The study suggested critical quality characteristics, which in respond will aid in attracting more number of students toward educational institutes. A study under Indian context is demonstrated for presenting critical facts and attaining higher student's enrolment rates.

Within the context of an open innovation business environment, the frequent interaction and coordination activities among heterogeneous partners have a significant impact on enterprises' business model. Nevertheless, fewer empirical research has been made to explore how to match external partners and update organizational dynamic capabilities at an ecosystem level. Therefore, this paper attempts not only to investigate the direct impact of partner match on different business model innovation (BMI) themes (efficiency-centered BMI and novelty-centered BMI) but only to shed light on the pivotal mediating role of interfirm dynamic capabilities.

This paper utilized the methodology of Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the impact of diverse partner selection criteria and interfirm dynamic capabilities on two distinctive themes of BMI. More than 20 industry clusters with multiple industries were selected as representatives of the creative ecosystem, predominantly from the Yangtze River Delta region. Valid data were collected from 254 managers by both online questionnaires and offline interviews.

The findings of the study show that different partner match criteria have distinct direct impacts on BMI themes. Partner complementary and partner synergy, deriving from the “task-related criteria”, are significantly correlated with both EBMI and NBMI. Conversely, partner compatibility, deriving from “Partnering-related Criteria”, shows a positive correlation with EBMI but not NBMI. Furthermore, compare the indirect effect on EBMI, the paper’ results demonstrate interfirm dynamic capabilities as mediator can more maximize external benefits to promote NBMI.

The study findings effectively help enterprises implement different BMI themes. From a management perspective, whether pursuing EBMI or NBMI, enterprises should consciously seek partners who can provide complementary support or share mutual goals across diverse industries. This strategic approach can significantly enhance the opportunities for sustainable and innovative business development. Furthermore, to successfully accomplish NBMI, enterprises must cultivate interfirm dynamic capabilities encompassing a comprehensive range of cross-organizational innovation capacities, such as bolstering organizational learning capability, establishing interactive network platforms to enhance coordination capabilities and engaging in integrative activities to foster a collective mindset.

This paper contributes to the match theory by introducing three critical matching criteria, enabling enterprises to discern partners based on diverse organizational characteristics. Additionally, this paper broadens the scope of the dynamic capability literature by adopting a network perspective to strengthen interaction and relationship mechanisms. The authors primarily elucidate the concept of interfirm dynamic capabilities as a formative higher-order model formed by three sub-capabilities (absorptive capacity, coordination capability and collective mind). Finally, this paper combines matching theory with dynamic capacity theory to the field of BMI, which adds depth and complexity to the existing ecosystem innovation research.

The repatriation process often involves challenging and unexpected readjustment issues, leading to high turnover amongst repatriates. However, research has focussed on the re-entry decisions and experiences of company-assigned (CA) repatriates, whilst studies on self-initiated expatriates (SIEs) that repatriate back to their home countries (i.e. self-initiated repatriates (SIRs)) are limited, particularly in emerging transition economies. This study develops and tests a model to explain the factors influencing professional SIRs' turnover intentions and how repatriation readjustment affects their intentions in Vietnam.

The data was collected from 445 Vietnamese professional SIRs who worked and/or studied for extended periods overseas and subsequently returned to Vietnam. Structural equation modelling (SEM) was used to analyse the data.

Results indicate that both work and life repatriation adjustment difficulties have significant positive effects on turnover intentions, whilst only repatriation life adjustment difficulties have an indirect effect via life dissatisfaction. Further, cultural distance positively influences repatriation adjustment difficulties and turnover intentions. SIRs' on-the-job and off-the-job embeddedness negatively moderate the influence of repatriation work and life adjustment difficulties on turnover intentions, respectively.

The study develops a theoretical model explaining how repatriation difficulties impact the turnover intentions of SIRs, considering contextual factors including cultural distance and embeddedness. The research highlights the importance of job embeddedness as a form of social and organisational support for SIRs in managing psychological challenges related to repatriation, which can help reduce turnover and retain highly skilled talent. Additionally, the study extends repatriation research on an under-researched subgroup of SIEs, SIRs, in an under-researched emerging transition economy context.

This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news articles. This study displays the developmental status of each subject based on the interrelationships of each topic cluster by analyzing high-frequency keywords extracted from the collected data. Moreover, applying above methodologies will help understanding top research topics, authors, venues, institutes and countries. The differences of blockchain research and new are identified.

To identify and find blockchain development linkages, researchers have used search terms such as co-occurrence, bibliographic coupling, co-citation and co-authorship to help us understand the top research topics, authors, venues, institutes and countries. This study also used text mining analysis to identify blockchain articles' primary concepts and semantic structures.

The findings show the fundamental topics based on each topic cluster's links. While “technology”, “transaction”, “privacy and security”, “environment” and “consensus” were most strongly associated with blockchain in research, “platform”, “big data and cloud”, “network”, “healthcare and business” and “authentication” were closely tied to blockchain news. This article classifies blockchain principles into five patterns: hardware and infrastructure, data, networking, applications and consensus. These statistics helped the authors comprehend the top research topics, authors, venues, publication institutes and countries.

Since Web of Science (WoS) and LexisNexis Academic data are used, the study has few sources. Others advise merging foreign datasets. WoS is one of the world's largest and most-used databases for assessing scientific papers.

This study has several uses and benefits. First, key concept discoveries can help academics understand blockchain research trends so they can prioritize research initiatives. Second, bibliographic coupling links academic papers on blockchain. It helps information seekers search and classify the material. Co-citation analysis results can help researchers identify potential partners and leaders in their field. The network's key organizations or countries should be proactive in discovering, proposing and creating new relationships with other organizations or countries, especially those from the journal network's border, to make the overall network more integrated and linked. Prominent members help recruit new authors to organizations or countries and link them to the co-authorship network. This study also used concept-linking analysis to identify blockchain articles' primary concepts and semantic structures. This may lead to new authors developing research ideas or subjects in primary disciplines of inquiry.

This study aimed to identify and assess the barriers to implementing modular construction systems (MCS) in developing country's architecture, engineering and construction (AEC) industry, targeting built environment professionals from Nigeria and South Africa.

The study adopted a quantitative research method, using a structured questionnaire to seek the opinions of the professionals on the identified categories of barriers.

Results indicated that all identified categories of barriers were statistically significant using a one-sample t-test at p = 0.05 significance level which indicates they are critical towards the implementation of MCS in developing countries. Assessment of the opinion of the professionals using the Kruskal–Wallis scale showed that they hold similar views on the barriers to the adoption of MCS. Pearson correlation shows a high correlation coefficient amongst the barrier categories and an acceptable level of significance (p = 0.05).

This study is limited to two significant African countries (Nigeria and South Africa) selected based on the gross domestic product (GDP). Further studies can consider developing countries outside Africa and investigate broader respondents.

The study provides implications on the barriers affecting MCS in developing countries for the academia, industry and government to have an insight into the barriers and make informed decisions and policies.

The research satisfies the need to study the barriers affecting the MCS in developing countries that can mitigate housing deficits. This innovative construction method has been adopted and implemented in developed countries, and the result has been positive.

Retail investors are prone to be affected by information dissemination in social media with the rapid development of Web 2.0. The purpose of this study is to recognize the factors that may impact users' retweet behavior, namely information dissemination in the online financial community, through machine learning techniques.

This paper crawled data from the Chinese online financial community (Xueqiu.com) and extracted author-related, content-related, situation-related, stock-related and stock market-related features from the dataset. The best information dissemination prediction model based on these features was determined by evaluating five classifiers with various performance metrics, and the predictability of different feature groups was tested.

Five prevalent classifiers were evaluated with various performance metrics and the random forest classifier was proven to be the best retweet prediction model in the authors’ experiments. Moreover, the predictability of author-related, content-related and market-related features was illustrated to be relatively better than that of the other two feature groups. Several particularly important features, such as the author's followers and the rise and fall of the stock index, were recognized in this paper at last.

This study contributes to in-depth research on information dissemination in the financial domain. The findings of this study have important practical implications for government regulators to supervise public opinion in the financial market.

Modular integrated construction (MiC) is an innovative and effective manufacturing-based method of construction that has become the mainstream development direction of projects in Hong Kong (HK). However, large-scale promotion of MiC practice still needs efforts. A pressing concern is that the impact of relevant policies on stakeholders during project implementation is rarely explored in depth. Therefore, to fill the research gap, this study aims to investigate the influence of policies on stakeholders to drive the successful implementation of MiC in HK.

This study uses a strategy of multiple methods. First, a comprehensively literature review and survey were adopted to identify critical policies and stakeholders. Second, semi-structured interviews with 28 experts were conducted to quantify their relationships. Third, three policy–stakeholder networks at initiation, planning and design and construction stages were established using social network analysis.

Environmental protection policy, COVID-19 pandemic policy and environmental protection policy and quality acceptance standard for project completion are found to be the most important policies of the three stages, respectively. The HK government and developers are highlighted as prominent stakeholders influencing policy implementation at all three stages. The dynamics of the influence stakeholders receive from critical policies at different stages of MiC are discussed. Valuable recommendations are accordingly proposed to enhance the successful implementation of MiC projects from the perspective of various stakeholders.

This study contributes to the body of knowledge by considering the mediating influence of stakeholders during policy implementation in the MiC uptake, and is valuable in helping policymakers to deeply understand the influence of policies to further forward successful MiC implementation and practicality in HK.

This paper aims to attempt to examine some of the unique features of cryptocurrency and the reasons for its growing market acceptability. Given the expanding size of cryptocurrency markets, the present study strives to identify whether it can be used as an alternative financial asset in place of traditional financial assets to meet firms' financial constraints. It also provides issues for future research in the area of cryptocurrency markets.

This paper analysed 94 research papers from databases such as ScienceDirect, Proquest, EBSCO, Emerald Insight and Web of Science. Articles connected to cryptocurrency, financial assets and corporate financial constraints research were explored. VOSviewer software has been used to visualise the specified body of literature and identify eight clusters in previous literature using keyword and abstract analysis.

Studies reveal that cryptocurrency markets are independent of traditional financial markets and cryptocurrency returns have less correlation with traditional financial asset classes. This can be an advantage to firms, especially during times of crisis when traditional financial assets are impacted by significantly lower returns, while cryptocurrencies can serve as an alternative. Realtime data reveals that during the pandemic, cryptocurrencies had the maximum growth in returns which also happened to be a time when firms faced severe cash constraints. While accepting cryptocurrency as a means of exchange is still under review by regulatory authorities, it can be considered an alternative asset for investment purposes. Firms can take advantage of it to overcome financial constraints and thus reap the gains from holding crypto assets for precautionary reasons.

The present study investigates using cryptocurrency as an alternative financial asset to solve the financial constraint problem in corporates. The issues regarding volatility, cyber securities, gold returns, long-term and short-term returns have been some of the most prominent studies in the area of cryptocurrency. The present study uses eight theme-based clusters to identify the role of cryptocurrency as an alternative investment class and examines evidence-based research regarding the financial returns from holding cryptocurrency over certain traditional asset classes such as gold, currency or stocks. In recent years, it has been found that investors' growing interest in holding cryptocurrency as part of their financial portfolio has led to the substantial appreciation of cryptocurrency prices. To the best of the authors’ knowledge, the study will be a novel attempt to identify the role of cryptocurrency as an antidote to the companies’ financial constraints and liquidity issues.

The purpose of this paper is to explore the factors that influence migrant workers' household registration transfer willingness at both individual and urban levels and to provide empirical evidence on adjusting the household registration system to accommodate economic development and migrant workers' imbalances.

This paper adopts a hierarchical nonlinear model and examines individual and urban influencing factors of migrant workers' household registration transfer willingness, based on the data from China Migrants Dynamic Survey (CMDS) and the Urban Statistical Yearbooks.

This paper shows that: (1) multi-factors, such as age, education, marital status, household demographics, industry and migrant workers' contract coverage, have significant effects on migrant workers' household registration transfer willingness; (2) The urban public service equalization indicators, such as regional economic, educational resources, medical care and ecological quality, have significant effects on migrant workers' willingness to transfer household registration; (3) The heterogeneity of migrant workers' willingness to transfer household registration is significant in central, eastern and western China.

The authors provide a fresh perspective on population migration research in China and other countries worldwide based on the pull–push migration theory, which incorporates both individual and macro (urban) factors, enabling a comprehensive examination of the factors influencing household registration transfer willingness. This hierarchical ideology and approach (hierarchical nonlinear model) could be extended to investigate the influencing factors of various other human intentions and behaviors.

Micro approaches (individual perspective) have dominated existing studies examining the factors influencing migrant workers' household registration transfer willingness. The authors combine individual and urban perspectives and adopt a more comprehensive hierarchical nonlinear model to extend the empirical evidence and provide theoretical explanations for the above issues.

Promoting electric vehicles (EVs) is an effective way to achieve carbon neutrality. If EVs are widely adopted, this will undoubtedly be good for the environment. The purpose of this study is to analyze the impact of network externalities and subsidy on the strategies of manufacturer under a carbon neutrality constraint.

In this paper, the authors propose a game-theoretic framework in an EVs supply chain consisting of a government, a manufacturer and a group of consumers. The authors examine two subsidy options and explain the choice of optimal strategies for government and manufacturer.

First, the authors find that the both network externalities of charging stations and government subsidy can promote the EV market. Second, under a relaxed carbon neutrality constraint, even if the government’s purchase subsidy investment is larger than the carbon emission reduction technology subsidy investment, the purchase subsidy policy is still optimal. Third, under a strict carbon neutrality constraint, when the cost coefficient of carbon emission reduction and the effectiveness of carbon emission reduction technology are larger, social welfare will instead decrease with the increase of the effectiveness of emission reduction technology and then, the manufacturer’s investment in carbon emission reduction technology is lower. In the extended model, the authors find the effectiveness of carbon emission reduction technology can also promote the EV market and social welfare (or consumer surplus) is the same whatever the subsidy strategy.

The network externalities of charging stations and the subsidy effect of the government have a superimposition effect on the promotion of EVs. When the network effect of charging stations is relatively strong, government can withdraw from the subsidized market. When the network effect of charging stations is relatively weak, government can intervene appropriately.

Comparing previous studies, this study reveals the impact of government intervention, network effects and carbon neutrality constraints on the EV supply chain. From a sustainability perspective, these insights are compelling for both EV manufacturers and policymakers.