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Drawn from the push–pull perspective, this research aims to identify the determinants of Chinese technology's outward foreign direct investments (OFDI) into the Eurasian region.

The authors argue that contrary to the extant literature, technology-driven OFDI from emerging-market multinationals (EMNEs) do not always seek developed countries, and EMNEs' technology investments in emerging economies are rising indicating that there are factors in these economies that can prove attractive. The authors recognize the influence of the macroeconomic environment and the interaction of home and host-country institutional contexts that influence the location choice of EMNEs technology-driven OFDI into other emerging economies, mediated by the industry sector and firm's ownership structure. The authors test our hypotheses using a sample of 1,656 observations of Chinese MNEs' tech-investments in the Eurasian region from 2005 to 2019.

The study results indicate that bilateral diplomatic relations pave the way of the host-country institutional environment for Chinese MNEs uncovering the role of the Chinese government as an OFDI facilitator. This study also unveils a lower technology level of the Chinese MNEs' investments in the Eurasian region connoting an interest in market opportunities exploitation through their existing technologies – through its comparative advantage in the global markets – rather than strategic assets acquisition aiming at augmenting their technological capabilities. This trend is similar to that of other major foreign direct investment (FDI) source countries.

This research contributes to a better understanding of the characteristics and the location choice of technology investments from EMNEs into other emerging economies that have received scant attention in the literature. In addition, it extends the institutional theory by analyzing how home-country institutions, through bilateral diplomatic relations, may smooth the host country institutional environment for home-country MNEs' foreign investments and contributes as well to the debate on the applicability of the existing theoretical framework in the case of emerging-market MNEs.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

Recent scholarship has explored higher education institutions’ (HEIs) role in transitioning to a sustainable society, but empirically, questions remain regarding their impact on the sustainability of surrounding areas. This study aims to examine the correlation between HEIs’ sustainability actions and local sustainability performance.

This study uses a linear regression model and principal component analysis to examine the sustainability performance of 105 US metropolitan statistical areas (MSAs) using the US cities sustainable development goal (SDG) index, which hosts 427 HEIs known for sustainability efforts. The weighted HEI sustainability performance score is calculated based on the QS sustainability universities ranking.

The correlation between MSA and HEI sustainability performance exhibits a mix of positive and negative associations, with individual and interlinked SDGs serving as proxies. These correlations encompass a wide range of goals, from economic aspects of SDG 1, 2, 3, 7, 9, social aspects of SDG10 and 16, to socio-environmental aspects of SDG12.

Further exploration is needed to identify the causal mechanisms behind associations between SDG measures and HEI sustainability performance, whether influenced by the institution, the individual or both.

This study suggests that HEIs are already associated with some aspects of community sustainability, but greater contributions to a broader array of sustainability measures are possible.

The correlation found between HEI sustainability actions and SDG10, 12 and 16 index performance in an MSA highlights a connection between HEIs and the attainment of societal goals.

To the best of the authors’ knowledge, this study is the first to examine the correlation between HEI and MSA sustainability performance in the US through individual and interlinked SDG proxies. It provides novel empirical evidence that demonstrates an association between HEI and some aspects of community sustainability performance.

The purpose of this study is to examine the impact of political relations on trade in strategic emerging industries (SEIs) in the Belt and Road initiative (BRI) associated countries. This investigation encompasses not only from the perspective of bilateral political relations but also the political intervention of third parties.

The study employs the temporal exponential random graphmodel to analyze the dynamic structure and influencing factor of SEIs trade network among 150 BRI-associated countries from 2015 to 2020.

The results indicate that the trade of SEIs in the BRI-associated countries exhibits a pattern of concentrated exporters and decentralized importers. Amicable bilateral political relations foster trade cooperations in SEIs, while political pressure from the United States has the opposite effect. Furthermore, compared with the influence of third parties, the BRI has created a more robust trade environment characterized by political mutual trust.

BRI-associated countries should strengthen their political communication, and endeavor to transform political consensus and shared vision into concrete collaborative projects, while mitigating geopolitical uncertainties through a sound risk evaluation system. Moreover, they should establish a more transparent and consistent consultation mechanism and leverage the BRI trade network to foster balanced and mutually beneficial partnerships that minimize rivalry and dependence on a single market.

This study goes beyond observed trade cost and incorporates the political factor into the determinants of the BRI trade, thereby expanding the theoretical boundaries of existing BRI research. Also, this study employs bilateral trade data to construct SEIs trade networks (SEITNs) along the BRI route. It provides a comprehensive understanding of the dynamic determinates of the SEITNs will provide valuable practical guidance for enhancing and expanding trade and cooperation among BRI-associated countries.

This study seeks to explicate how institutional disruptions impact multinational corporation (MNC) subsidiary control choices. It uses institutional theory to understand the influence of formal and informal institutions across countries on the type of control system employed in an MNC manufacturing subsidiary.

This study’s sample is based on a unique dataset from five trustworthy sources. We use multi-level models to account for the hierarchical nature of the sample of 1,630 multinational subsidiaries spread across 26 host countries by firms from 21 home countries.

The institutional distance between the host and the home country has a negative relationship with strategic control. In contrast, the home country’s power distance has a positive relationship with strategic control.

Study findings indicate the need to incorporate formal and informal institutional elements in the control system’s conceptual framing and design. This notion complements existing visualizations of optimizing MNC controls through extant articulations of minimizing governance costs through organizational design choices or strategic needs.

The principal aim of this study is to examine the relationship between financial development and income inequality in India using the financial Kuznets curve (FKC) hypothesis.

This study uses the autoregressive distributed lag (ARDL) model and the Toda–-Yamamoto causality test to investigate the long-run and short-run relationship and causality between financial development and income inequality. In addition, this study employs a principal component analysis (PCA) to construct a comprehensive financial development index.

The study found a long-run relationship between financial development and income inequality in India for the period under consideration. Trade is found to improve the income distribution, while inflation worsens income distribution. Moreover, the empirical results revealed a feedback causality between financial development and income inequality. The study results confirm an inverted U-shaped relationship between financial sector development indicators and income inequality, thus validating the FKC hypothesis for the Indian economy.

The study draws attention of the government and policymakers, urging them to focus on building a strong financial sector by improving its efficiency. This, in turn, will lead to enhanced financial stability and a reduction in income inequality. They should prioritise the development of high-quality and sustainable financial products and services to ensure the robust growth of the financial sector.

To the best of our knowledge, this study is the latest of its kind to empirically test the financial development on income inequality and the FKC hypothesis simultaneously for the Indian economy using financial proxy variables from financial institutions (FIs) and financial markets (FMs) for the measurement of financial depth.

This paper aims to investigate the performance of OECD countries' long-term productivity during the period of 1975–2018.

This study employed different approaches to evaluate how efficiency scores vary with changes in inputs and outputs: Data Envelopment Analysis (CRS, VRS and FDH), TOPSIS and TOPSIS of these scores.

The findings suggest that, during the period of this study, countries with higher freedom of religion and with Presidential democracy regimes are positively associated with higher productivity.

To the best of the authors’ knowledge, this is the first study that uses efficiency models to assess the productivity levels of OECD countries based on several contextual variables that can potentially affect it.

The purpose of this article is to develop relationships between many major issues relevant to the agriculture supply chain.

With the purpose of gaining an all-encompassing understanding of the agriculture supply chain, this work uses 233 filtered research articles and three bibliometric analysis tools, namely VOSviewer, term frequency-inverse document frequency (TF-IDF) and Person correlation. The collected research publications were also catalogued using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA).

Using analytic techniques, a total of 12 keywords were obtained. The study found that agri-products are in dire need of digitisation via Internet of things (IoT) and blockchain due to the usage of economic variables and comprehensive management of total food waste throughout transportation, anchoring quality and the predominant variable.

The study was limited to the Scopus and Web of Science (WoS) indexing in order to assess the viability of the linked idea and problem.

This study aims to generate vital knowledge in the field of horticulture-focused agriculture supply chain based on previous justification and relationship formation.

Numerous research tools exist but their usage among researchers across the different phases of the research cycle of scholarly communication remains unknown. This research aims to address this knowledge gap by mapping the research tools frequently used by global researchers against the various phases of the research cycle of scholarly communication.

This research adopts a descriptive research design and conducts a cross-tabulation of secondary data consisting of 20,663 useable responses in a global survey of research tools for scholarly communication. This research also administered a survey to academic experts to classify the research tools according to traditional, modern, innovative and experimental categories.

This research reveals the six phases of the research cycle (i.e. discovery, analysis, writing, publication, outreach and assessment) and the research tools of scholarly communication frequently used by researchers worldwide in each phase as a whole and by roles, disciplines, regions and career stages. Notably, this research indicates that most of the research tools used by researchers are classified as “modern” and “innovative”.

The original insights herein should be useful for both established and early career researchers to gain and share research insights, as well as policymakers and existing and aspiring service providers who wish to improve the utility and usage of research tools for scholarly communication. Notably, this research represents a seminal endeavor at enhancing a global survey (secondary research) using a follow-up expert survey (primary research), which enabled the organization of research tools for scholarly communication into four refined categories. In doing so, this research contributes finer-grained insights that showcase the importance of keeping up with the advancement of technology through the use of modern, innovative and experimental research tools, thereby highlighting the need to go beyond traditional research tools for scholarly communication.