Intensive Resources Research Articles

Design of a serious game for participatory planning of nature-based solutions: The experience of the Edible City Game

Serious games have been proposed by several studies as a tool to foster civic participatory processes. However, such an endeavour is often prone to failure due to lack of funding or lack of skills on designing serious games. In response to this problem, this paper provides a novel framework for the design of serious games for participatory planning of nature-based solutions, which provides guidance for the definition, content, and evaluation steps. The usefulness of the framework is illustrated with the design of the Edible City Game (ECG), a digital serious game for participatory planning of edible city solutions (urban nature-based solutions with a food component). The designed ECG was then implemented in Tygron, a platform which provides a graphical interface for serious games for urban planning. However, although Tygron provides a user-friendly software to design serious games, our thesis is that the final product still needs a proper design-orientated process to fulfil its purpose. We believe that this framework, as well as our experience using the Tygron platform, can be of great utility to both researchers and practitioners that have considered using serious games in their projects but discarded the idea because of the foreseen resource intensity of the endeavour.

How does natural resource price volatility affect economic performance? A threshold effect of economic policy uncertainty

The correlation between natural resource price volatility and economic performance has been broadly examined in recent decades. Policymakers and scholars have focus on the adverse implication of economic policy uncertainty (EPU) on economic performance. In the meantime, the sound institutions play a substantial role in mitigating the negative effect of economic policy uncertainty. Therefore, our study examines the threshold effect of economic policy uncertainty between natural resource price volatility and economic performance. The panel threshold models were used to capture the time-variant characteristic of natural resource price volatility, panel threshold models were utilized to conduct heterogeneous analyses on various groups of countries. The endogeneity effect was controlled through the panel least square estimators’ approach, which treated endogenous variables. Our empirical outcomes signify that economic policy uncertainty has a threshold effect between natural resource price volatility and economic performance. There is a positive association between natural resource price volatility and economic performance. Under the lower threshold value of economic policy uncertainty, the effect of natural resource price volatility on economic performance is higher than the above threshold value of the economic policy uncertainty regime. Natural resource price volatility heterogeneous impacts economic performance across developed and emerging economies under the high and lower threshold parameters. Emerging economies are more vulnerable to the threshold effect of economic policy uncertainty. Our empirical results possess important policy implications.

Structural opportunities for the development of the Russian economy

Subject. This article discusses the issues of formation of the mobilization economy in Russia. Objectives. The article aims to determine the parameters of the Russian economy's development, most affecting its stability in the context of sanctions. Methods. For the study, I used the methods of statistical, neural network, and cluster analyses. Results. The article argues that in order to increase the stability of the Russian economy, it is necessary to focus on the development of bank lending, the pension system, the dynamics of prices for energy resources and refined petroleum products. Relevance. The results of the study can be used when developing measures to strengthen Russia's economic security.

Digitalization in the Processes of Classification of the Country’s Budget Expenditures

The study of the processes of planning and accounting of budget expenditures in the context of digitalization and the development of the processes of classification and coding of costs is an important urgent task of improving public financial management. The purpose of the study is to generalize the classification of the country’s budget expenditures to justify the need for changes in the order of planning and cost accounting on digital platforms. The research methods included: analysis and synthesis; regression analysis; modeling; scientific abstraction; logical method. The novelty lies in the proposed logical justification of the provisions of the theory of financial informatics as a synthesis of two scientific disciplines — the theory of finance and the theory of computer science. The author’s view on the digital content of the classification of budget expenditures is proposed, which represents a multi-dimensional hierarchical system for constructing a graph of budget expenditures. Regression models of the dependence of the resource intensity of the conditional classification budget code of expenditures on the quality of financial management of the GRBS have been developed. The conclusions of the study confirmed the hypothesis that the more detailed the differentiation (classification) of budget expenditures, the more opportunities there are for competent organization and management of their financing processes, which is facilitated by the development of ICT. The recommendations are reduced to the need for further research of the scientific and applied provisions of the development and organization of the functioning of digital platforms in the system of public financial management to improve the efficiency of the use of the country’s budget resources. Further development of scientific and applied methodological provisions for the development of the electronic budget is required in order to turn it into a form of the digital budget of the country.

Time-varying impact of geopolitical risk on natural resources prices: Evidence from the hybrid TVP-VAR model with large system

In this paper, we investigate the time-varying effects of geopolitical risks on various natural resources prices from October 1992 to October 2022. We divided natural resources into three groups: minerals, precious metals and industrial metals. The hybrid TVP-VAR model is utilized in order to solve the over-computation problem of the large-scale system with 20 variables. The model provides a more flexible and accurate approach to identify and determine whether geopolitical risk has a time-varying effect on certain resource price from data itself. The results showed that geopolitical risks have relatively obvious time-varying effect on most minerals, time-invariant effect on gold, platinum and industrial metals. Gold can act as a safe-haven to hedge the increase in geopolitical risk. The impulse intensity of geopolitical risk on resource price is generally stronger in the short term and much weaker in the long term. Under different historical time points, the impacts of geopolitical risk on some of the resources show different trends. The results indicate that regulations, early risk warning mechanisms and emergency plans should be established to ensure the stable supply of domestic resources and the smooth operation of the market when geopolitical events occur.

Automatic classification of construction safety reports using semi-supervised YAKE-Guided LDA approach

Literature on supervised Machine-Learning (ML) approaches for classifying text-based safety reports for the construction sector has been growing. Recent studies have emphasized the need to build ML approaches that balance high classification accuracy and performance on management criteria, such as resource intensiveness. However, despite being highly accurate, the extensively focused, supervised ML approaches may not perform well on management criteria as many factors contribute to their resource intensiveness. Alternatively, the potential for semi-supervised ML approaches to achieve balanced performance has rarely been explored in the construction safety literature. The current study contributes to the scarce knowledge on semi-supervised ML approaches by demonstrating the applicability of a state-of-the-art semi-supervised learning approach, i.e., Yet, Another Keyword Extractor (YAKE) integrated with Guided Latent Dirichlet Allocation (GLDA) for construction safety report classification. Construction-safety-specific knowledge is extracted as keywords through YAKE, relying on accessible literature with minimal manual intervention. Keywords from YAKE are then seeded in the GLDA model for the automatic classification of safety reports without requiring a large quantity of prelabeled datasets. The YAKE-GLDA classification performance (F1 score of 0.66) is superior to existing unsupervised methods for the benchmark data containing injury narratives from Occupational Health and Safety Administration (OSHA). The YAKE-GLDA approach is also applied to near-miss safety reports from a construction site. The study demonstrates a high degree of generality of the YAKE-GLDA approach through a moderately high F1 score of 0.86 for a few categories in the near-miss data. The current research demonstrates that, unlike the existing supervised approaches, the semi-supervised YAKE-GLDA approach can achieve a novel possibility of consistently achieving reasonably good classification performance across various construction-specific safety datasets yet being resource-efficient. Results from an objective comparative and sensitivity analysis contribute to much-required knowledge-contesting insights into the functioning and applicability of the YAKE-GLDA. The results from the current study will help construction organizations implement and optimize an efficient ML-based knowledge-mining strategy for domains beyond safety and across sites where the availability of a pre-labeled dataset is a significant limitation.

Natural resource rents and public debts nexus in African resource-rich and most indebted nations: Issues with aggregation bias

The relationship between natural resource of a country and its public debt profile has been a point of contention. Due to credit limits, countries endowed with natural resources employ their supposed resource huge windfalls as collateral. As a result, they are unable to settle their loans during these resource price fluctuations, particularly when the price lowers. Those countries who failed to implement adequate policies to address the commodity price boom-bust cycle suffer the consequences of the debt overhang, stifling their search for economic progress and trapping them in debt. In addition, aggregation bias, which can lead to incorrect estimation of aggregate relationships and mislead policymakers, is also a concern with aggregate estimations. The long-run relationship between total natural resource rents and public debt among the top African countries endowed with natural resources as well as the most indebted is examined. The study also makes efforts to determine whether or not aggregation bias exists. Trade openness, GDP per capita, and unemployment are among the other control variables included in the public debt model based on theoretical underpinning. The findings of a robust empirical estimation show that the relationship is negative at the aggregate level but positive at the disaggregated level, implying that the estimation of the public debt-resource rent relationship at the aggregate level is prone to aggregation bias. As a result, governments of resource-rich countries should engage in responsible borrowing and prudent fiscal management to minimize debt overhang. On the subject of estimating aggregation bias, policy could be drawn as follows: aggregation bias may lead to an incorrect total debt-resource rents postulation where policymakers may be misled by the incorrect evidence, resulting in poor resource-debt policies. Therefore, while formulating fiscal and growth strategies, policymakers should examine the resource-debt nexus at both the aggregate and country level.

Changes in the Price Policy of the Trading Company as a Result of the Global Economic Crisis After Covid-19 and the War in Ukraine

In the conditions of changes in the economic situation, which led to inflation, trade companies are put to the test of transforming their pricing strategy and at the same time remaining competitive on the goods market. Rising resource prices lead to significant increases in inflation rates internationally. Those who offer goods to their consumers must take a position for a longer-term and sustainable change in their pricing strategy, so that they generate a profit with which they manage to cover the costs of producing or selling their products. In addition to changes in profit management, it will be necessary to include marketing methods to promote products and inform customers about their qualities. Increasing the market share of the companies will not be the only goal if they desire the long-term of their business, but they will have to create strategies to increase their revenue without it being dependent on the volume of sales.

A64 THE UPTAKE AND IMPACT OF AN ELECTRONIC CIRRHOSIS ADMISSION ORDER SET: AN EARLY EXPERIENCE AT A SINGLE CENTRE

Abstract Background Cirrhosis is a chronic disease that confers high morbidity and mortality. It is a leading cause for hospital admissions and leads to significant healthcare resource utilization. Several guidelines outline recommendations to provide best practice to hospitalized patients with cirrhosis. Despite studies supporting a reduction in mortality when guideline based care is followed, this is achieved in less than 50% of hospitalized patients with cirrhosis1. Standardized electronic order sets can be a potential tool to improving clinical outcomes and bridging this gap in care. Purpose Since March 2021, an electronic cirrhosis admission order set has been available for at our hospital site. Using administrative data, we aimed to describe our early experience with: a) order set uptake by various services, b) characteristics of the population in which the order set was used versus not used, and explore c) the impact of order set use on in-hospital mortality. Method In this single centre cohort study, patients with cirrhosis were identified based an administrative data algorithm containing codes for cirrhosis and complications. This data was used to retrieve parameters such as patient age, sex, primary admitting service, resource intensity weight (RIW), Charlson comorbidity index (CCI) and in-hospital mortality. The chi-squared test and independent samples t-test were used to compare characteristics of patients in whom the order set was used versus not used. Multivariable logistic regression was used to determine the impact of order set use on in-hospital mortality. P value significance was established at <0.05. Result(s) A total of 825 patients were included in the analysis. The overall mean age (standard deviation) of patients was 58.5 (14.2) years with 57.5% being male. Average length of stay was 11.3 days with a mean CCI of 3.2 (2.3) and RIW of 3.3 (7.2). The primary admitting service was Gastroenterology in 36.1%, Internal Medicine in 35.6% and other services in 28.3% of cases. Of those admitted, the order set was used in 27.2% of cases. The overall in-hospital mortality of patients was 14.2%. Mean age, sex and CCI were not significantly different in patients admitted with the order set versus without. In patients admitted with the order set compared to without, RIW was significantly lower (2.06 (2.62) versus 3.80 (8.2), p<0.001), as was length of stay (9.5 (11.8) days compared to 12.0 (18.6) days, p =0.03) and in-hospital mortality (8.5% versus 16.3%, p =0.003). On multivariable regression analysis (Table 1), after adjustment for age, RIW and CCI, use of the order set was associated with lower in-hospital mortality (odds ratio 0.53 (95% CI 0.3 to 0.9), p=0.02). Image Conclusion(s) Uptake of the electronic cirrhosis admission order set was modest at only 27% of eligible admissions. Although it appears to be associated with lower in-hospital mortality, a chart review is in process to assess if this association still holds after accounting for the impact of additional confounders. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared

Varieties and resource-saving elements of winter wheat growing technology as a west of grain production

Topicality. Ukraine is a world known producer of high-quality grain. Actually, the potential for grain production of all grain crops, especially, winter wheat is quite powerful, especially in the southern region of Ukraine. At the same time, grain yield levels largely depend on influence of many factors: the moisture supply of plants during the growing years, the agricultural background of nutrition, the selection of varietal composition, the tillage method and measures, the plant protection, the weed infestation, and other factors. There are no trifles in plant cultivation, because strict compliance with all the necessary technological requirements will allow you to obtain constant productivity and ensure a gross harvest of grain every year. This is significantly important both for the state's own needs and for exports. Currently, it is not possible to successfully cultivate crops in all fields and agricultural lands due to military operations in Ukraine. The Ukrainian manufacturers should implement previously developed elements of technology and improve new less-known and resource-saving measures. The last aspect also becomes significant in term of the weakening the economic capacity of farms, the increase in the price of material resources and a certain decrease in soil fertility. Under such conditions, the most effective measure is to review of the list of agricultural crops and select the most unpretentious to environmental conditions crops for cultivation, and among them, it is necessary to select crops highly adapted to biotic and abiotic factors of the environment, and varieties that are able to show their genetically programmed biological and eco-nomically valuable characteristics. Purpose. We attempt to achieve a significant increase in both grain yield and its quality by means of selection and involvement of new varieties in the production, and improvement of certain elements of growing technology. Materials and Methods. Setting up and conducting field experiments was carried out in accordance with the generally accepted methodology of the research case. The experimental part of the work was carried out during 2007–2021 at the research field of the NNPC of the National Academy of Sciences. Results. It was determined that winter wheat responds to predecessors, increases grain productivity against the background of fertilization. With regard to the selection of the varietal composition of soft winter wheat bred by Ukrainian breeding institutions in the last decades, it was established that most varieties are adapted to cultivation in the conditions of the Southern Steppe of Ukraine, and are able to form a stable level of harvest, which does not clearly fluctuate over the years. Conclusions. We substantiated that winter wheat should be planted after more favorable predecessors, a moderate dose of mineral fertilizers should be applied, and the most productive varieties should be selected, which have the best characteristics in the conditions of the growing zone. Keywords: winter wheat, selection of adapted varieties, grain harvest, weather and climate conditions, elements of cultivation technology

Edge Resource Pricing and Scheduling for Blockchain: A Stackelberg Game Approach

Blockchain came to prominence as the distributed ledger underneath Bitcoin, which protects the transaction histories in a fully-connected, peer-to-peer network. The blockchain mining process requires high computing power to solve a Proof-of-Work (PoW) puzzle, which is hard to implement on users’ mobile devices. So these miners may leverage the edge/cloud service providers (ESPs/CSP) to calculate the PoW puzzle. The existing edge-assisted blockchain networks assumed that all ESPs have a uniform propagation delay, which is unrealistic. In this article, we consider a more practical scene where ESPs locate in diverse positions of the blockchain network, which causes different propagation delays when supporting the computation of the PoW puzzle. Additionally, these ESPs connect to a remote CSP for resource scheduling when the computing tasks exceed their maximum capacity. The blockchain mining process generally involves complicated competition and games among CSP, ESPs, and miners. Each service provider focuses on how to determine his resource price so that he can maximize his utility. According to the set resource price, each miner concentrates on scheduling his resource requests for each ESP to maximize individual personal utility, which depends on ESPs’ resource price and propagation delays. We first model such a resource pricing and scheduling problem as a three-stage multi-leader multi-follower Stackelberg game and aim at finding the Stackelberg equilibrium. Then, we analyze the subgame optimization problem in each stage and propose an iterative algorithm based on backward induction to achieve the Nash equilibrium of the Stackelberg game. Finally, extensive simulations are conducted to verify the significant performance of the proposed solution.

Transformative resilience: Transformation, resilience and capacity of coastal communities in facing disasters in two Indonesian villages

This study aims to identify the transformation process of coastal village communities in building resilience to disasters. We develop our theoretical framework based on the concepts of socio-ecological resilience, transformative resilience, panarchy systems and resilience capacities. Using the qualitative research methods, we examine two cases of coastal villages in Indonesia that represent differing levels of socio-economic vulnerability and community responses to disasters. The findings of this study highlight that the building of transformative resilience is affected by the transformation phases, the heterogeneity and interdependence of capacities, and the intensity of resources used as capacity. The building process of transformative resilience cannot happen instantly but requires an ideal timeframe for transitional phase navigation in which communities form valley and peak waves to create a perfect phase in each regime. This condition triggers the achievement of high resilience conditions in the face of disasters. Although endogenous capacities, in the form of local social networks and agents of change, have become the key aspects of resilience, openness to external conditions and collaborations are also essential in nurturing transformation. Our findings suggest an important implication for policy, in that a long-term transformation process should be taken into account in policymaking. Further, in enhancing the resilience of coastal communities it is important to build their innovative capacities, among other things, by nurturing their networks through various opportunities and exposures to external parties which enable collaborations and exchanges of knowledge.

Strategic Resource Pricing and Allocation in a 5G Network Slicing Stackelberg Game

We consider a marketplace in the context of 5G network slicing, where Application Service Providers (ASP), <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.,</i> slice tenants, providing heterogeneous services, are in competition for the access to the virtualized network resource owned by a Network Slice Provider (NSP), who relies on network slicing. We model the interactions between the end users (followers) and the ASPs (leaders) as a Stackelberg game. We prove that the competition between the ASPs results in a multi-resource Tullock rent-seeking game. To determine resource pricing and allocation, we devise two innovative market mechanisms. First, we assume that the ASPs are pre-assigned with fixed shares (budgets) of infrastructure, and rely on a trading post mechanism to allocate the resource. Under this mechanism, the ASPs can redistribute their budgets in bids and customise their allocations to maximize their profits. In case a single resource is considered, we prove that the ASPs’ coupled decision problems give rise to a unique Nash equilibrium. Second, when ASPs have no bound on their budget, we formulate the problem as a pricing game with coupling constraints capturing the shared resource finite capacities, and derive the market prices as the duals of the coupling constraints. In addition, we prove that the pricing game admits a unique variational equilibrium. We implement two online learning algorithms to compute solutions of the market mechanisms. A third fully distributed algorithm based on a proximal method is proposed to compute the Variational equilibrium solution of the pricing game. Finally, we run numerical simulations to analyse the market mechanism’s economic properties and the convergence rates of the algorithms.

Развитие молочного скотоводства в Арктической зоне республик Карелия и Коми, Архангельской области: возможности и формы поддержки

The Arctic Zone of the Russian Federation is a region with special business support conditions. In 2020, it included the municipal districts of the republics of Karelia, Komi and the Arkhangelsk region, where dairy farming was a traditional activity. Since early 1990s, agriculture in these areas has been in a deep crisis and unable to overcome it. The analysis revealed a close relationship between the reduction in the number of cows and the decrease in the area of cultivated arable land in municipal districts. The number of cows decreased by 25 times in 3 regions, by 15 times in 5 regions, the areas under crops in all categories of farms — by 36 and 15 times, respectively. The shallow contour of the fields, the spread of agricultural land across the territory, the lack of a developed transport infrastructure in the Arctic zone do not allow realizing economies of scale and reducing costs through large investment projects, such as mega-complexes with a conveyor type of production being built in the central and Southern regions of Russia. Automation of production processes, digitalization of management increase productivity and quality, reduce resource intensity and operating costs. Mastering digital technologies for monitoring, modeling and control in operational management and planning increase the efficiency of using agro-climatic and natural potential, reduce production and investment risks. The regional specifics of fodder and milk production in the Northern regions determines the expediency of preferential support for the innovative development of dairy farming in small and medium-sized enterprises, family farms, which makes it necessary to improve the forms of state support for investments.

Hotelling and recycling

We study the exploitation of recyclable exhaustible resources such as metals that are crucial for the energy transition or phosphorus that is crucial for agricultural production. We use a standard Hotelling model of resource exploitation that includes a primary sector and a recycling sector. We study two polar cases: competitive and monopolistic extraction. We show that, when the primary sector is competitive, the Hotelling’s rule holds and the price of the recyclable resource increases over time. We then show a new reason why the price of an exhaustible resource may decrease: when the primary sector is monopolistic, the primary producer has incentives to delay its production activities in order to delay recycling. As a consequence, the price path of the recyclable resource may be U-shaped. Numerical simulations reveal that the monopolist has an incentive to delay extraction when the recoverability rate is high (because more recycled goods are produced) or when the recoverability rate is low (when fewer recycled goods are expected to be produced in the future). As a consequence, the date of exhaustion of the virgin resource is further away in time for high and low levels of recoverability than for intermediate levels.

Corrigendum to ‘Green innovation, resource price and carbon emission during the COVID-19 times: New findings from wavelet local multiple correlation analysis’ [Technol. Forecast. Soc. Change, 184 (2022) 121957

Corrigendum to ‘Green innovation, resource price and carbon emission during the COVID-19 times: New findings from wavelet local multiple correlation analysis’ [Technol. Forecast. Soc. Change, 184 (2022) 121957

A Delphi study examining risk and uncertainty management in circular supply chains

Circular supply chains (CSCs) have attracted increasing attention in the supply chain management literature due to their role in increasing the circularity of materials, components, and products. However, surprisingly little attention has been paid to risk and uncertainty management in CSCs, with this aspect experiencing limited theoretical development thus far. Drawing on contingency theory, this paper aims to identify the risks and uncertainties that impede the implementation of CSCs and related management strategies and thus help practitioners mitigate them. A three-round Delphi study was conducted with a panel of industry, governmental, nongovernmental, and academic actors from 18 countries across five continents to analyze their views regarding risk and uncertainty management in CSCs. The results reveal critical risks and uncertainties at the organizational, supply chain, and external levels, including uncertain financial costs; a lack of knowledge and expertise; operational and technological risks; uncertain quality, availability, and delivery of secondary resources; market competition with linear-oriented companies and supply chains; a lack of adequate regulatory frameworks and indicators; and unstable prices for virgin and secondary resources. In effect, appropriate countermeasures are necessary to manage risks and uncertainties, which are comprised of reducing and coping strategies. Reducing strategies consist of inter-firm collaboration and circular product design, and coping strategies consist of information sharing, flexibility, and financial risk management. Moreover, the analysis revealed related contingency factors affecting CSCs, such as regulatory requirements. This paper develops a theoretical framework and a set of propositions regarding contingency factors and risk and uncertainty management in CSCs, helping theorists and practitioners to comprehend the challenges of circular economy implementation.

Theory and Method of Ecological Value Accounting of Forest Resources

&lt;p&gt;Forest resources, as one of the most important natural resources, have high ecological value. The calculation of their ecological value is an important part of improving the accounting of natural resources assets. Based on the analysis of the basic situation of China&amp;#39;s forest resources, this paper starts from the economic theory of forest resources, discusses the principle of forest resources in national economic operation, analyzes the output, value, price and other issues of forest resources, and probes into the necessity of studying forest resources. Then, based on the purpose of compiling the balance sheet of natural resources, the forest resources accounting theory was studied from the aspects of subject and object, scope, table design and so on. On the basis of relevant theoretical research, the main ecological functions of different types of forest resources are discussed. In practical calculation, the parameters of some accounting methods are adjusted to adapt to the local situation. Some methods of ecological value calculation such as soil conservation and water conservation are put forward, and some ideas for further improvement are put forward. Finally, taking Qiandao Lake as an example, the ecological value of its forest resources is calculated. Through calculation, the annual soil conservation value of Qiandao Lake forest resources was obtained. Combined with the research conclusion and practice progress, the future research prospect is put forward.&lt;/p&gt;

A credible and adjustable load resource trading system based on blockchain networks

In recent years, the residents’ demands for power supply is increasing. The load resource trading system responds to the demands through intelligent scheduling, which can effectively relieve the severe power load pressure. The load resource trading system is a type of nonlinear system because the trading price is adjustable with user’s credit, instead of being linear to the power trading volume. The adjustable load resource trading is faced with the challenges of large demands, strong user autonomy, and secure and tamper-proof transaction data. The blockchain technology has been widely concerned by industrial and academic domains due to its decentralization, strong encryption of account information, and traceability of transaction behaviour. In this paper, we propose a credible and adjustable load resource trading framework based on blockchain, which uses blockchain to achieve credible grid load resource trading. Firstly, we propose a two-layer blockchain architecture based on the alliance chain. The main chain maintains all the data of the system, and the station-area nodes constitute the alliance chain. We design a distributed trading processing mechanism based on hybrid consensus and sharding technologies, which promotes the speed of cross-station transaction consensus. Next, we propose a two-level bidding model, which determines the trading price of load resources based on the maximum benefit of users and the lowest cost of grid companies. The results of extensive experiments shows that our proposed framework can achieve the promising result.

Slack Resources and Export Intensity: New Empirical Evidence from Vietnam

The paper explored the effects of financial and human resource slacks on firms’ export intensity. Using longitudinal data of Vietnamese firms with a random effect model, the study found that financial slack had an inverted-U shaped effect; meanwhile, human resource slack had no consistently significant effect on firms’ export intensity. The empirical findings could have managerial practice implications at the firm level. Too few—or too many—slack resources are bad for export intensity. Therefore, firm managers need to consider the necessary level of redundancy for slack resources to avoid prodigality while doing business. This study contributed new insights to international business and slack literatures. First, our findings contributed to the international business literature. In classic internalization studies, it has generally been believed that firms with access to greater resources are more likely to exploit foreign markets. However, our research showed that, when there were too many slack resources, business activities in firms’ foreign markets, such as exports, could be reduced due to complacency among firm managers. Second, the research results contributed to literature on slack resources, providing a new insight on their effects on firms’ export intensity. Aside from linear or U-shaped effects, slack resources could have inverse U-shaped relationships with firms’ export intensity.