External Engagements and Innovation of Firms: Evidence from Vietnamese Manufacturing SMEs.

This study explores the effect of external engagements on innovationoutputs of firms using a cross-sectional survey data set on Vietnamese privatemanufacturing SMEs conducted in 2009.For theoretical framework, we use the the knowledge production functionmodel (PKF) (Griliches, 1979, 1990) and the network models of innovation(NMI) (OECD, 2005; Osamu, 2008).Based on PKF and NMI models, we found that there was generally apositive impact of international engagements (export, import of equipment/machinery, and the supports from foreign donors/NGOs) and other domesticengagements (subcontracting, purchasing outside business service, and beingmember of business association activities) on innovation outputs. This may bebecause externally engaged firms invested more in innovation, and/or becausethese firms were able to learn from their worldwide partners or access to a widersource of knowledge flows.Our study gives some theoretical and managerial implications. Fortheoretical implications, the findings support KPF and NMI. Firm innovationbecomes open and interconnected to external factors. For managerialimplication, increasing external engagements is a good strategy for firms toovercome their weaknesses of limited internal resources. Increasing externalengagements can also force firms to innovate more

Empirical Applications of Network and Random Matrix Theories to Economic and Financial Complex Systems

This thesis contributes to the existing literature on the empirical applications of network theory and Random Matrix Theory to economic and financial complex systems. It is based on six essays which can be structured in two parts. The first part consists of four essays (from chapter 2 to chapter 5), which are devoted to various applications of network theory to large data sets of credit relationships in the interbank market and between banks and other sectors of the economy. They study various properties in different structures of different financial networks. More specifically, the second and the third chapters respectively analyze structural correlations and structural similarities in one-mode networks. The fourth chapter deals with topological and structural properties in bipartite networks, and the fifth chapter is devoted to overlaps and correlations between layers in the multilayer structure of networks. Two essays in the second part (respectively in chapter 6 and chapter 7), based on the methods of Random Matrix Theory, analyze the structure of the cross-correlation matrices of banks' loan portfolios and the structure of the cross-correlation matrix of worldwide economic sentiment indices

The evolution of Vietnamese industry

The transfer from an import-substitution to an export-orientation strategy has been in effect in Vietnam since the reform process, Doi Moi, necessitating the reformulation of macroeconomic, trading and sectoral policies. As a result, the industry sector has experienced gradual growth as the country's economy is becoming more open and gaining deeper integration with regional and the world economies, as exemplified by membership in the ASEAN Free Trade Area (1995) and World Trade Organization (2006). To support this integration process, the structure of the industrial sector has been changed to more appropriate since the Doi Moi. Many export processing zones, industrial zones and economic zones have been set up to attract the interest of multi-sectors, including foreign and non-state investors. Consequently, the capacity, output and productivity of the industrial sector have improved considerably. But certain policy issues also arose during the industrial development process. These can be summarized into three main problems: minimal contribution from current policies to improving competitiveness, policy failure to encourage firm restructuring, and lack of a well-coordinated framework for industrial policy

interbank network; structural correlations; clustering coefficients; configuration models; network reconstruction

We study the structural correlations in the Italian overnight money market over the period 1999–2010. We show that the structural correlations vary across different versions of the network. Moreover, we employ different configuration models and examine whether higher-level characteristics of the observed network can be statistically reconstructed by maximizing the entropy of a randomized ensemble of networks restricted only by the lower-order features of the observed network. We find that often many of the high order correlations in the observed network can be considered emergent from the information embedded in the degree sequence in the binary version and in both the degree and strength sequences in the weighted version. However, this information is not enough to allow the models to account for all the patterns in the observed higher order structural correlations. In particular, one of the main features of the observed network that remains unexplained is the abnormally high level of weighted clustering in the years preceding the crisis, i.e., the huge increase in various indirect exposures generated via more intensive interbank credit links

Collateral Unchained: Rehypothecation networks, concentration and systemic effects

We study how network structure affects the dynamics of collateral in presence of rehypothecation. We build a simple model wherein banks interact via chains of repo contracts and use their proprietary collateral or re-use the collateral obtained by other banks via reverse repos. In this framework, we show that total collateral volume and its velocity are affected by characteristics of the network like the length of rehypothecation chains, the presence or not of chains having a cyclic structure, the direction of collateral flows, the density of the network. In addition, we show that structures where collateral flows are concentrated among few nodes (like in core-periphery networks) allow large increases in collateral volumes already with small network density. Furthermore, we introduce in the model collateral hoarding rates determined according to a Value-at-Risk (VaR) criterion, and we then study the emergence of collateral hoarding cascades in different networks. Our results highlight that network structures with highly concentrated collateral flows are also more exposed to large collateral hoarding cascades following local shocks. These networks are therefore characterized by a trade-off between liquidity and systemic risk.Comment: 39 pages, 7 figure

USING A MULTI-CRITERIA DECISION-MAKING MODEL TO EVALUATE AND SELECT AN E-COMMERCE PLATFORM

The COVID-19 pandemic has led to disruptions in consumers' lifestyles and purchases, as well as businesses' online business models. Online platforms are increasingly used for shopping purposes. To evaluate and choose an e-commerce platform requires using many criteria and decision makers. Therefore, the process of evaluating and selecting an e-commerce platform is viewed as a multi-criteria decision-making problem. The objective of this study is to develop a multi-criteria decision-making model to help consumers evaluating the e-commerce platforms. In the proposed model, the ratings of alternatives and the weights of the criteria are evaluated using the linguistic variable. Simulation examples are used to show the effectiveness of the model in practice.  Keywords: Fuzzy TOPSIS, E-Commerce Platform, Mcdm, Fuzzy Sets

Stable isotopes as an effective tool for N nutrient source identification in a heavily urbanized and agriculturally intensive tropical lowland basin

© 2020, Springer Nature Switzerland AG. We present the application of dual stable isotope analyses of NO3 (δ15N-NO3 and δ18O-NO3) to provide a comprehensive assessment of the provenance, partitioning, and conversion of nitrate across the Day River Basin (DRB), Vietnam, which is heavily impacted by agriculture and urbanization. Stable isotope compositions of river water δ18O-H2O, in addition to their δ15N-NO3 and δ18O-NO3 signatures, were sampled at 12 locations in the DRB. Sample collection was conducted during three different periods to capture changes in regional weather and agricultural fertilization regimes; April (the dry season and key fertilization period), July (the rainy season and another key fertilization period) and October (the rainy season with no regional fertilization). Ranges of NO3 stable isotopes are − 7.1 to + 9.2‰ and − 3.9 to + 13.2‰ for δ18O and δ15N, respectively. Interpretation of the stable isotope data characterizes 4 main sources of NO3 in the DRB; (1) nitrified urea fertilizer derived from an intensive agricultural irrigation network, (2) soil and groundwater leaching from within the basin (3) manure and sewage inputs (which is more prevalent in downstream river sections) and (4) upstream inflow from the Red River which discharges into the Day River through the Dao River. We applied a mixing model for the DRB consisting of 4 variables, representing these 4 different sources. The partition calculation shows that during the fertilization and rainy period of July, more than 45% of river NO3 is derived from nitrified urea sources. During the other sampling periods (April and October), manure and sewage contribute more than 50% of river NO3 and are derived from the middle portion of the DRB, where the Day River receives domestic wastewater from the Vietnamese capital, Hanoi. Stable isotope data of O and N reveal that nitrification processes are more prevalent in the rainy season than in dry season and that this predominantly takes place in paddy field agricultural zones. In general, data demonstrate that nitrate loss in the DRB is due to denitrification which takes place in polluted stretches of the river and dominates in the dry season. This study highlights that (i) domestic waste should be treated prior to its discharge into the Day River and (ii) the need for better catchment agricultural fertilization practices as large portions of fertilizer currently discharge into the river, which greatly impacts regional water quality

NĂNG SUẤT SƠ CẤP Ở ĐẦM THỊ NẠI, TỈNH BÌNH ĐỊNH

Experiments of photosynthesis assessment of phytoplankton and seaweed had been carried out in Thi Nai lagoon in rainy season (October, 2013) and dry season (May, 2014). The results showed that primary productivity of phytoplankton was 8 - 149 mgC/m3/day, and that productivity of seaweed Gracilaria verrucosa was 0.139 - 0.197 mg C/g seaweed/day. During photosynthesis process of phytoplankton, an amount of 1.42 - 1.6 tons mineral nitrogen/day and 0.14 - 0.17 tons phosphate/day was consumed in the whole lagoon. The photosynthesis process of seaweed also consumed an amount of 0.74 - 0.83 tons/day of inorganic nitrogen (including nitrate, nitrite, and ammonium), and 0.041 - 0.045 tons/day of phosphate in the whole lagoon.Các thí nghiệm đánh giá khả năng quang hợp của thực vật nổi và rong biển đã được thực hiện tại đầm Thị Nại (Bình Định) vào mùa mưa (tháng 10/2013) và mùa khô (tháng 5/2014). Kết quả nghiên cứu cho thấy năng suất sơ cấp của thực vật nổi và rong câu chỉ vàng Gracilaria verrucosa nằm trong khoảng 8 - 149 mgC/m3/ngày và khoảng 0,135 - 0,197 mgC/g rong/ngày. Trong quá trình quang hợp, thực vật nổi làm tiêu hao khoảng 1,42 - 1,6 tấn khoáng nitơ/ngày và 0,14 - 0,17 tấn phôtphat/ngày. Tương tự, quần xã rong trong đầm cũng làm tiêu hao khoảng 0,74 - 0,83 tấn/ngày các dinh dưỡng nitơ vô cơ và 0,041 - 0,045 tấn phôtphat/ngày trên toàn đầm Thị Nại