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This study aims to examine the illicit capital movement through trade misinvoicing in Burundi, at disaggregated levels by major trading partners and by major export and import commodities.

Trade misinvoicing is estimated by comparing the trade values declared by Burundi with those declared by trading partners in a bilateral international transaction, after adjusting for the cost of freight and insurance. Disaggregated trade misinvoicing by major trading partners is computed using the Direction of Trade Statistics database of the International Monetary Fund over the period 1970–2019. Disaggregated trade misinvoicing by major trading commodities is computed using the UN-COMTRADE database over the period 1993–2019.

Exports of Burundi to most of its major trading partners are found to be underinvoiced. The top destinations for export underinvoicing are United Arab Emirates, Belgium and Germany. However, exports to UK and Switzerland are found to be overinvoiced. The major export commodities considered, coffee and gold, are found to be affected by trade misinvoicing to a great extent. On the import side, the estimation results indicate that imports of Burundi from its major trading partners are in general overinvoiced. High import overinvoicing is observed in the trade with Saudi Arabia, China and Japan. At commodity level, for the top 6 commodities considered, imports were to a great extent found to be overinvoiced. Cases of illicit capital outflows and inflows through trade misinvoicing are highlighted.

Some policy implications are drawn from this study. First, in collaboration with its development partners, the Government of Burundi should put in place measures to reduce the trade misinvoicing phenomenon, which undermines poverty reduction efforts. The study has shown which trade partners are involved and which commodities are mostly affected. Policy efforts could then be focused in that regard. Investigations at the company and transaction levels can be made to identify the mechanisms of trade misinvoicing. Second, more effort is needed in ensuring systematic and transparent reporting of international trade transactions. To fight trade misinvoicing, transparency in international trade is key, through coordinated enforcement of reporting rules.

Previous studies analyzed the problem of trade misinvoicing at an aggregated level. However, this leaves out essential information on trading partners involved in the phenomenon as well as trading commodities affected. This study investigates trade misinvoicing at disaggregated levels, at product level and by trading partner.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.

The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.

This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.

The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.

This study aims to define a “technological statecraft” concept to distinguish tech-based measures/sanctions from an array of economic measures ranging from restrictions of rare earth elements and natural gas supplies to asset freezes under the wider portfolio of economic statecraft. This concept is practically intended to reveal the USA’s “logic of choice” in its employment of technology as an efficient instrument to deal with China in the context of the great power rivalry.

This study follows David A. Baldwin’s statecraft definition and conceptualization methodology, which relies on “means” rather than “ends.” In addition to Baldwin and as an incremental contribution to his economic statecraft analysis, this study also combines national political economy with statecraft analysis with a particular focus on the utilization of technological measures against China during the Trump administration.

The US rationale for choosing technology, namely, emerging and foundational technologies, in its rivalry against China is caused at least by two factors: the nature of the external challenge and the characteristics of the US innovation model based largely on radical innovations. To deal with China, the USA practically distinguished the role of advanced technology and followed a grammer of technological statecraft as depicted in the promulgated legal texts during the Trump administration.

Despite a growing volume of literature on economic statecraft and technological competition, studies focusing on countries’ “logic of choice” with regard to why and under what conditions they choose financial, technological or commodity-based sanctions/measures/controls are lacking. Inspired from Baldwin’s account on the “logic of choice” from among alternative statecrafts (i.e. diplomacy, military, economic statecraft, and propaganda). This study will contribute to the literature with a clear lens to demonstrate the “logic of choice” from among a variety of economic statecraft measures in the case of the US technological statecraft toward China.

The purpose of this study is to enhance the functional properties of Hessian fabric through resin finishing. Hessian bags made of lignocellulosic jute fiber are commonly used to pack, store and transport agro-commodities, including horticultural crops such as rice, potato, onion and wheat. However, because of high water affinity, these bags undergo degradation in properties due to moisture release by the stored commodities themselves. Exposure to natural elements, e.g. rain and dew, also causes moisture absorption in hessian bags. Once the bag gets moistened, degradation of jute bags starts due to microbial attack, leading to loss in tensile strength and change in extensibility, leading to ultimate breakage in warp and weft directions of the fabric.

To overcome the degradation in the functional properties of hessian fabric due to exposure to moisture and microbial attack, the application of semi-synthetic polymeric materials was carried out.

Tenacity, bursting strength, puncture resistance, tear strength and breaking load, as well as life cycle of resin-treated jute fabric was found to be better than control jute.

To the best of the authors’ knowledge, no recent reports of resin finishing on jute (hessian) fabric with semi-synthetic resins are presently available, other than coating with rubber.

This chapter aims to discuss the challenges facing these countries building productive capacity for development. This chapter makes use of data published by international organizations as indicators for measuring the state of development in the Arab region. Several indicators are presented to compare Arab countries with other world regions. The use of data identifies some of the gaps that countries in the Arab region need to close to strengthen capacity building for development and fostering economic growth. The findings from the data presented reveal that the productive structure in most Arab countries remains weak to generate production linkages and provide incentives for investment in nonenergy sectors. The failure of the export-led growth model to diversify output and promote development in energy producing countries has increased the dependence of these countries on global trade. Fluctuations in commodity prices and uncertainty about global demand for energy have influenced the ability of the state to construct strategies for rapid transformation. Except for the energy sector, the productivity of nonoil sectors remains low reflecting inadequate incentives and ineffective entrepreneurial capabilities. The study examines the challenges for building productive capacity in the Arab world. It illustrates the failure of the led-export model and its inability to prompted economic diversification, especially in the Gulf countries. The study contributes to the literature on capacity building in the Arab world so that to encourage researchers and students of development conducting studies concerning the main development challenges facing these countries.

COVID-19 has affected the economies adversely from all sides. The sudden halt in production has impacted both the supply and demand sides. It calls for analysis to quantify the impact of the reduction in economic activity on the economy-wide variables so that appropriate steps can be taken. This study aims to evaluate the sensitivity of various sectors of the Indian economy to this dual shock.

The eight-sector open economy general equilibrium Global Trade Analysis Project (GTAP) model has been simulated to evaluate the sector-specific effects of a fall in economic activity due to COVID-19. This model uses an economy-wide accounting framework to quantify the impact of a shock on the given equilibrium economy and report the post-simulation new equilibrium values.

The empirical results state that welfare for the Indian economy falls to the tune of 7.70% due to output shock. Because of demand–supply linkages, it also impacts the inter- and intra-industry flows, demand for factors of production and imports. There is a momentous fall in the demand for factor endowments from all sectors. Among those, the trade-hotel-transport and manufacturing sectors are in the first two positions from the top. The study recommends an immediate revival of the manufacturing and trade-hotel-transport sectors to get the Indian economy back on track.

The present study has modified the existing GTAP model accounting framework through unemployment and output closures to account for the impact of change in sectoral output due to COVID-19 on the level of employment and other macroeconomic variables.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

The purpose of this study is to propose and test an integrated model to explain how trust is built in sharing economy (SE) transactions.

Initially, prior literature was systematically selected and synthesized to develop a comprehensive framework applicable to multiple trust-building perspectives and categories of SE platforms. Then, a survey was conducted to validate the constructs and test the model with Airbnb guests. A sample of 351 responses was collected and analyzed using structural equation modeling.

The results indicate that the cues an individual assesses to infer their counterpart’s trustworthiness and the reasons the individual has for engaging in the SE transaction can explain a large variance in their trust in the counterpart. In addition, the individual’s propensity to trust moderates this relationship.

The proposed model can help identify the most effective trust-building mechanisms. It can be taken as a common knowledge base for scholars to compare the four trust-building perspectives and different categories of SE platforms, as well as to investigate the subject over time and across cultures.

This research can also help practitioners understand the complexity of building trust and design platform features to do so.

A unified model clarifies trust in the SE, aiding platform growth and community bonding. This insight guides platforms in feature enhancement and policymakers in drafting balanced regulations.

To the best of the authors’ knowledge, for the first time, there is a comprehensive and parsimonious model applicable to the four trust-building perspectives and different categories of SE platforms.