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Management and risk techniques within industries have been studied from various disciplines in nondefense-affiliated industries. Given the assumption that these techniques, strategies and mitigations used in one industry apply to other similar industries, this paper examines the defense industry for risk assessment. We characterize interactions for onward application to risk identification in the defense industry.

This research employs a systems theory approach to the characterization of industry interactions, using three dimensions including environment, boundaries and relationships. It develops a framework for identifying relationship types within system-of-systems (SoS) environments by analyzing the features of interactions that occur in such environments.

The study’s findings show that different systems environments within the defense industry SoS exhibit different interaction characteristics and hence display different relationship patterns, which can indicate potential vulnerabilities.

By employing interaction as a means for evaluating potential risks, this research emphasizes the role played by relationship factors in reducing perceived risks and simultaneously increasing trust.

This paper intends to develop an initial snapshot of the relationship status of the Swedish defense industry in light of the global consolidation in this industry, which is a relevant contextual contribution.

In this paper we examine the validity of the J-curve hypothesis in four Southeast Asian economies (Indonesia, Malaysia, the Philippines and Thailand) over the 1980–2017 period.

We employ the linear autoregressive distributed lags (ARDL) model that captures the dynamic relationships between the variables and additionally use the nonlinear ARDL model that considers the asymmetric effects of the real exchange rate changes.

The estimated models were diagnostically sound, and the variables were found to be cointegrated. However, with the exception of Malaysia, the short- and long-run relationships did not attest to the presence of the J-curve effect. The trade flows were affected asymmetrically in Malaysia and the Philippines, suggesting the appropriateness of nonlinear ARDL in these countries.

The previous research tended to examine the effects of the real exchange rate changes on the agricultural trade balance and specifically the J-curve effect (deterioration of the trade balance followed by its improvement) in the developed economies and rarely in the developing ones. In this paper, we address this omission.

The Polish economy has undergone major challenges and changes over the past few decades. The country's trade flows, in particular, have become more firmly tied to the country’s Western neighbors as they have grown in volume. This study examines Poland's trade balances in ten Standard International Trade Classification (SITC) sectors versus the United States of America, first testing for and isolating structural breaks in each time series. These breaks are then included in a set of the cointegration models to examine their macroeconomic determinants.

Linear and nonlinear and nonlinear autoregressive distributed lag models, both with and without dummies corresponding to structural breaks, are estimated.

One key finding is that incorporating these breaks reduces the significance of the real exchange rate in the model, supporting the hypothesis that this variable already incorporates important information. It also results in weaker evidence for cointegration of all variables in certain sectors.

This study looks only at one pair of countries, without any third-country effects.

An important country pair's trade relations is examined; in addition, the real exchange rate is shown to incorporate economic information that results in structural changes in the economy. The paper extends the existing literature by conducting an analysis of Poland's trade balances with the USA, which have not been studied in such a context so far. A strong point is a broad methodology that lets compare the results the authors obtained with different kinds of models, both linear and nonlinear ones, with and without structural breaks.

This study investigates the optimum size for manufacturing firms and the impact of subcontracting on firms' likelihood of achieving their optimal scale in Vietnam.

Using data from the enterprise census in 2017 and 2021, the paper first estimates the production function to identify the optimum firm size for manufacturing firms and then applies the logit model to investigate factors associated with the optimal firm size.

The study reveals that medium-sized firms exhibit the highest level of productivity. Nevertheless, a consistent trend emerges, indicating that nearly 90% of manufacturing firms in Vietnam operated below their optimal scale in both 2017 and 2021. An analysis of the impact of subcontracting on firms' likelihood to achieve their optimal scale emphasizes its crucial role, especially for foreign firms, exerting an influence nearly five times greater than that of the judiciary system.

The paper's findings offer crucial policy implications, suggesting that initiatives aimed at enhancing the overall productivity of the manufacturing sector should prioritise facilitating contract arrangements to encourage firms to reach their optimal size. These insights are also valuable for other countries with comparable firm size distributions.

This paper provides the first empirical evidence on the relationship between firm size and productivity as well as the role of subcontracting in firms' ability to reach their optimal scale in a country with a right-skewed distribution of firm sizes.

This study aims to examine foreign direct investment (FDI) factors and develops a rational framework for FDI inflow in Western European countries such as France, Germany, the Netherlands, Switzerland, Belgium and Austria.

Data for this study were collected from the World development indicators (WDI) database from 1995 to 2018. Factors such as economic growth, pollution, trade, domestic capital investment, gross value-added and the financial stability of the country that influence FDI decisions were selected through empirical literature. A framework was developed using interpretable machine learning (IML), decision trees and three-stage least squares simultaneous equation methods for FDI inflow in Western Europe.

The findings of this study show that there is a difference between the most important and trusted factors for FDI inflow. Additionally, this study shows that machine learning (ML) models can perform better than conventional linear regression models.

This research has several limitations. Ideally, classification accuracies should be higher, and the current scope of this research is limited to examining the performance of FDI determinants within Western Europe.

Through this framework, the national government can understand how investors make their capital allocation decisions in their country. The framework developed in this study can help policymakers better understand the rationality of FDI inflows.

An IML framework has not been developed in prior studies to analyze FDI inflows. Additionally, the author demonstrates the applicability of the IML framework for estimating FDI inflows in Western Europe.

This paper aims to investigate the direct and combined impacts of entrepreneurial orientation (EO) and conservative orientation (CO) on perceived business performance (PBP) of small- and medium-sized enterprises (SMEs) under strategic-hybrid orientation (SHO) theory.

The data collected from the SABI NEO international database has 90 companies in 13 medium-to-high and high-tech activity sectors. The authors used partial least squares structural equation modelling to test the research model.

Business strategies match a SHO that includes both orientations, i.e. EO and CO. Moreover, as expected, the authors found evidence that each orientation produces performance-related sign-opposite significant impacts. Finally, the hypothesis regarding the positive synergistic effect of both orientations (EO and CO) on PBP was also supported.

One stems from the study’s cross-sectional nature, requiring a longitudinal approach. Another one resides in the absence of further examinations concerning multigroup analysis. Another restraint is the limitedness of data, focused on firms with med/high-tech intensity. For last, while the use of results in the initial stages of theory development can be beneficial, it is important to note that such results cannot be simply extrapolated or generalized to other industrial sectors without careful consideration of the contextual factors at play.

This study humbly endeavours to contribute to the finality of SMEs’ more steady and prosperous existence concerning the consciousness of the need to improve labour stability and wage fairness, conditions such as requiring a continuous commitment.

In this study, the authors aimed to investigate the impact of SHO on SMEs’ PBP. To this end, the authors simultaneously used two different strategic orientations (SOs): EO, which is widely studied in the literature, and CO, which has been less researched. The authors also examined their synergistic effects on PBP. The authors’ approach is based on Venkatraman’s strategic orientation of business enterprises model and the comparative paradigm of SOs.