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The purpose of this paper is to identify variables and their effects on the value of technology transaction according to technology demand approach in Vietnam technology market, by testing the hypotheses including the effects of technology absorption capacity, internal research and development (R&D) productivity of firms and difficulties in external infrastructure on technology demand.

The technology transaction value and its impact factors are assessed using Vietnam annual enterprise survey and using technology in production survey from 2012 to 2016. The effects of factors on value of technology transaction are determined by using feasible generalized least squares model.

The results indicate three main points. First, companies having higher technology absorption capacity and higher dominance in the domestic or foreign markets tend to acquire higher technology demand in the technology market. Second, companies having lower internal R&D productivity tend to require higher external technology demand. Finally, higher level of difficulty from external infrastructure prevents enterprises in accessing technology demand.

The main limitation of the study is that data of firm’s R&D productivity are not available. The study also does not mention information flows from competitors that perhaps have potentially significant impacts on external technology demand of firms.

The paper includes policy implications for the government and industry managers to increase technology transaction value.

The focus of many previous research papers on technology transactions was generally to look at the decisive factors behind firm’s technology supply in both developed and developing countries. However, knowledge about firm’s technology demand is very limited, particularly in the context of developing countries. This paper clarifies the effect of factors on the decision buying external technology for innovation purpose and productivity improvement in Vietnamese manufacturing sector.

This paper aims to propose a comprehensive framework for prioritizing complexity criteria. The framework was validated by applying in infrastructure international development (ID) project as a case study.

A literature review highlighted the limitations of existing complexity prioritization methods. Then, a combination of the fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy analytic network process (ANP) was employed as a foundation to develop a three-stage complexity prioritization framework. Focus group discussion and questionnaire surveys were used to practically test the framework in the infrastructure ID projects.

The three-stage complexity prioritization framework was validated to be reliable and feasible. The findings showed ability of consultants, scope uncertainties, site compensation and clearance, communication between stakeholders, administrative procedure and project duration were the most significant complexity criteria of ID projects in the Vietnamese context.

The framework is a robust tool that enables the researchers to grasp the interaction of complexity criteria for complexity prioritization. Later studies can apply the proposed framework, with some minor revisions, to assess the interaction of criteria in other research topics in, and beyond, project complexity. Results of the case study suggest project stakeholders focusing on complex interactions among criteria to reduce project complexity.

This study contributes to the body of knowledge by providing a comprehensive complexity prioritization framework that grasps the interrelationship of complexity criteria. For stakeholders of ID projects, the findings provide insightful perspectives to understand complexity, which can help to enhance project performance.

This study aims to provide firm-level evidence on the relationship between the presence of financial services multinationals and indigenous counterparts’ performance, using a comprehensive sample of firms in the emerging financial industry in Vietnam.

This study uses the generalized method of moments with instrumental variables (IV/GMM) to deal with potential endogeneity problem. Of this technique, a pragmatic approach to constructing instruments is adopted, capitalizing on the geographical and industry segmentation of the local market. The empirical analyses also address statistical issues of the overall model significance, heteroskedasticity and multicollinearity.

The regression results reveal that foreign entrants have a positive and statistically significant association with indigenous firms’ labor productivity and the average wage, with a more pronounced impact on the latter. The increased entry of financial multinationals appears to be uncorrelated with indigenous firms’ profitability. The extended estimations also suggest that investor origin matters in determining spillover magnitude. The average estimate of Asian affiliates in the examined relationship is approximately half that of European affiliates, whereas foreign entrants originating from America show an insignificant role.

This study sheds light on the broader impacts of foreign financial affiliates by simultaneously exploring their impacts on three key dimensions of indigenous firm performance, namely, labor productivity, average wage and profitability. This paper also enriches the existing literature by disentangling the effects of foreign entrants from different regions of origin, which was largely neglected in the context of financial services multinationals.

Social commerce has brought about a significant transformation in consumer experience due to diverse factors. As a result, users often find themselves prone to impulsive buying behaviour when exposed to such an environment. Prior research was limited to demonstrating the expanding influence of celebrities on social media and the linkage between social engagement and impulse buying context. Furthermore, the impulse buying tendency of consumers on social media in the context of celebrity posts has yet to be validated. This paper aims to assess the influence of consumer awareness, consumer trust and observational learning on the latent state-trait (LST) theory regarding celebrity posts on impulse buying tendencies.

The empirical research builds on a sample survey involving 750 students from the “Big Four” economics universities in Hanoi. The proposed model was analysed using a partial least squares structural equation modelling technique.

The authors find that consumer trust and observational learning from celebrity’ posts positively affect impulse buying tendency. Yet celebrity influence awareness directly impacts trust in celebrity’ posts rather than directly impacting impulse buying tendency. Perceiving the importance of interactive and authentic posts by a celebrity in influencing consumers’ purchase behaviour on social media, this research offers valuable insights for stakeholders in the digital celebrity sphere of communication and marketing.

Perceiving the importance of interactive and authentic posts by a celebrity in influencing consumers’ purchase behaviour on social media, this research offers valuable insights for stakeholders in the digital celebrity sphere of communication and marketing.

From a theoretical perspective, this expands the applicability of the LST theory in social commerce to promote impulse buying tendencies. Second, this contributes to the literature on the emerging phenomenon of social media celebrities, as existing literature does not clarify their influence on impulse buying behaviour. Third, this research applies the concept of observational learning in online shopping through key features of social media platforms, namely, likes, shares and comments, to investigate their influence on the impulse buying tendency of consumers. Concerning managerial implications, the authors propose practical recommendations for practitioners, particularly those involved or interested in the commercial services industry and social media marketing (namely, celebrities and partner companies).

This paper aims to combine Eringen’s micromorphic and nonlocal theories and thus develop a comprehensive size-dependent beam model capable of capturing the effects of micro-rotational/stretch/shear degrees of freedom of material particles and nonlocality simultaneously.

To consider nonlocal influences, both integral (original) and differential versions of Eringen’s nonlocal theory are used. Accordingly, integral nonlocal-micromorphic and differential nonlocal-micromorphic beam models are formulated using matrix-vector relations, which are suitable for implementing in numerical approaches. A finite element (FE) formulation is also provided to solve the obtained equilibrium equations in the variational form. Timoshenko micro-/nano-beams with different boundary conditions are selected as the problem under study whose static bending is addressed.

It was shown that the paradox related to the clamped-free beam is resolved by the present integral nonlocal-micromorphic model. It was also indicated that the nonlocal effect captured by the integral model is more pronounced than that by its differential counterpart. Moreover, it was revealed that by the present approach, the softening and hardening effects, respectively, originated from the nonlocal and micromorphic theories can be considered simultaneously.

Developing a hybrid size-dependent Timoshenko beam model including micromorphic and nonlocal effects. Considering the nonlocal effect based on both Eringen’s integral and differential models proposing an FE approach to solve the bending problem, and resolving the paradox related to nanocantilever.

Presents a review on implementing finite element methods on supercomputers, workstations and PCs and gives main trends in hardware and software developments. An appendix included at the end of the paper presents a bibliography on the subjects retrospectively to 1985 and approximately 1,100 references are listed.

This study investigates the relationship between credit booms and bank risk in Association of Southeast Asian Nations (ASEAN) countries, with credit information sharing acting as a moderator.

The authors use a two-step System Generalized Method of Moments (SGMM) estimator on a sample of 79 listed banks in 5 developing ASEAN countries: Indonesia, Philippines, Malaysia, Thailand and Vietnam in the period 2006–2019. In addition, the authors perform robustness tests with different proxies for credit booms and bank risk. The data are collected on an annual basis.

Bank risk is positively related to credit booms and is negatively associated with credit information sharing. Further, credit information sharing reduces the detrimental effect of credit booms on bank stability. The authors find that both public credit registries and private credit bureaus are effective in enhancing bank stability in ASEAN countries. These results are robust to regression models with alternative proxies for credit booms and bank risk.

Banks in ASEAN countries tend to have strong lending growth to support the economy, but this could be detrimental to stability of the sector. Credit information sharing schemes should be encouraged because these schemes might enable growth of credit without compromising bank stability. Therefore, policymakers could promote private credit bureaus (PCB) and public credit registries (PCR) to realize their benefits. The authors' research focuses on developing ASEAN countries, but future research could provide more evidence by expanding this study to other emerging economies. In-depth interviews and surveys with bankers and regulatory bodies about these concerns could provide additional insights in the future.

The study is the first to examine the role of PCB and PCR in alleviating the negative impact of credit booms on bank risk. Furthermore, the authors use both accounting-based and market-based risk measures to provide a fuller view of the impact. Finally, there is little evidence on the link between credit booms, credit information sharing and bank risk in ASEAN, so the authors aim to fill this gap.

This study addresses the empirical results of the spillover effect with export as the primary economic activity that enhances local businesses' total factor productivity (TFP). A learning mechanism is expected to be generated and used as the basis for the policy implication.

This study adopted the Cobb–Douglas function and multiple estimation approaches, including the generalized method of moments, the Olley–Pakes and the Levinsohn–Petrin estimation techniques. The findings were estimated based on the panel data of a Vietnamese local businesses survey conducted by the General Statistics Office of Vietnam (GSO) from 2010 to 2019.

The results showed that the highest TFP belongs to the businesses in the Southeast region, the Mekong Delta region, the mining industry and the foreign-invested enterprises. The lowest impacted TFP are businesses in the Northwest region and agricultural, forestry and fishery sectors. In addition, the estimated results also show that the positive spillover effect on TFP is shown through forward and backward linkage. The negative spillover effect is expressed through the backward and horizontal channels.

This study offers original empirical evidence on the learning mechanisms via which exports contribute to productivity improvement in a developing Asian economy, so making a valuable contribution to the existing academic literature in this domain. The findings of this research make a valuable contribution to the advancement of understanding on the many ways via which spillover effects manifest such as horizontal, forward, backward and supplied-backward linkage.

The study's findings indicate that it is advisable for governments to give priority to the development and improvement of forward and supply chain linkages between exporters and local suppliers. This approach is recommended in order to optimize the advantages derived from export spillovers. At the organizational level, it is imperative for enterprises to strengthen their technological and managerial skills in order to efficiently incorporate knowledge spillovers that originate from overseas partners and trade counterparts.

This study sheds new evidence on the export spillover effect on productivity in emerging economies, with Vietnam as the case study. The paper contributes to the research's originality by adopting novel methodological aspects to estimate local businesses' impact on total factor productivity.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0373