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The Russian export flow is highly concentrated on few trading partners that results in its high vulnerability to external shock. Furthermore, the Russian–Ukraine conflict and corresponding western sanctions has enhanced the need of export markets diversification for Russia. Therefore, this study is a baseline attempt to explore determinants of export flow along with identifying potential export markets. This objective is realized by employing an augmented version of gravity model on export flow of Russian Federation to 108 trading partners from 2000 to 2020.

The augmented gravity model of export flow is estimated by using employing contemporary panel econometrics such as panel generalized ordinary least square estimation technique with cross-sectional weight along with heteroskedasticity consistent white coefficients is employed to explore impact of selected macroeconomic and policy variables. Furthermore, the sensitivity analysis is performed by using panel random effect along with the Driscoll–Kraay standard errors with pooled ordinary least squares (OLS) regression and random effect generalized least square (GLS) estimator techniques. The estimated result of panel GLS technique is subjected to in-sampled forecasting technique to explore potential export markets.

The findings show that an increase in the income of trading partners and enhancement of domestic production capacity has significant positive impact on Russian export flow, whereas geographic distance has a significant negative impact. Income of trading partners emerged as major determinant of export flow with high explanatory power. Among augmented variables, the real exchange rate reveals a significant positive impact of lower intensity, whereas binary variables for the common border, common history and preferential/free trade agreement show a significant positive impact. The finding of export potential reveals a high concentration of export with existence of large potential for exports across the globe. For instance, many developing countries in Asia, Africa and America reveal high potential for Russian exports.

The findings urge Russian Federation to diversify its export markets by targeting potential export markets. Many emerging developing countries are witnessing a high potential for Russian exports, therefore attempts should be taken to diversify toward them. The expansion of existing transportation facilities along with development of cargo trade can be important policy instrument to realize objective of export diversification.

This study is the first comprehensive analysis that employs augmented gravity model to explore potential export markets for Russian Federation by using panel data of 108 global trading partners from 2000 to 2020. This finding of this study provides a framework of export diversification toward potential markets across the globe.

The purpose of the study is to investigate the relationship between international financial integration (IFI) index and democracy (DEM) in Pakistan by using long-time series data from 1975 to 2013.

The IFI index is constructed by principal component analysis. IFI consists of foreign direct investment (FDI), remittances (REM) and external debt (ED), whereas the Polity IV index is used for DEM. Johansen and the autoregressive distributed lag method for cointegration methods are used to find a long run relationship. Dynamic ordinary least square (DOLS), fully modified ordinary least square (FMOLS) and canonical regression (CR) have been used to find the nature of the relationship. Rolling window analysis has been done to find the year wise coefficients.

DOLS, FMOLS, canonical regression CR and cointegration results suggest a significant negative long-run relationship between IFI and DEM in Pakistan. Rolling windows analysis highlights that DEM has improved IFI in Pakistan from 2008 to 2013.

This study constructs an index for financial integration using principle component analysis on capital inflows, i.e. FDI, REM, ED, to explore the impact of DEM on IFI in Pakistan from 1975 to 2013. This study investigates for the first time ever the relationship between IFI index and DEM in Pakistan.

Pakistan’s natural endowment of labour and land is suitable for labour-intensive agriculture and manufacturing sector. This study aims to investigate international trade competitiveness of Pakistan in 14 major industries of agriculture and manufacturing sector, accounting more than 85 per cent of total export receipts.

The competitiveness of Pakistan in selected industries of agriculture and manufacturing sectors from 2003 to 2014 is investigated using the revealed comparative advantage (RCA) index, introduced by Balassa (1965) on HS data collected from the United Nations Commodity Trade database. The obtained indices in this study are then subjected to panel regression analysis to investigate the effect of domestic productivity growth and real exchange rate on international trade competitiveness of major industries.

The results show that the agriculture sector of Pakistan has higher comparative advantage in raw cotton, cereals, raw leather and fruits. The raw cotton shows the highest competitiveness of 54.46 which is followed by cereals (17.13), leather (9.83) and fruits (1.97). The RCA of the manufacturing sector shows that textile (54.85), carpets (10.72), sports goods (2.18) and beverages (1.47) have higher competitiveness. The RCA, in relatively capital-intensive industries, shows a high disadvantage. The trend analysis shows distorted competitiveness in labour-intensive, textile, carpet and footwear industries. The results of panel regression analysis show that the domestic productivity growth and real exchange rate depreciation have a significant positive impact on the international competitiveness of selected industries. The study urges Pakistan to make its macroeconomic environment investment-friendly and encourage investment in deteriorating labour-intensive industries.

Globalisation has significantly increased international competition, and Pakistan is losing its competitiveness in labour-intensive industries owing to lack of domestic value addition and development efforts. The major problem with the productivity of these industries is the lack of proper infrastructure, acute energy crisis, lack of domestic and foreign investment and overvaluation of real exchange rate. The domestic investors are shifting their capital either to other domestic sectors and/or other investment-friendly countries. Policymakers in Pakistan should address the problems of these important labour-intensive industries. The government needs to understand macroeconomic uncertainties and make investment-friendly policies to encourage domestic and foreign investment. The future studies should perform in-depth research to identify both microeconomic and macroeconomic variables responsible for deterioration in competitiveness of major labour-intensive industries in the agriculture and manufacturing sectors of Pakistan.

This study is a comprehensive examination into the nature and pattern of international competitiveness of Pakistan in 14 important industries of the agriculture and manufacturing sector which has seldom been investigated empirically. The obtained indices in this study are also subjected to panel regression analysis to explore the effect of domestic productivity growth and real exchange rate depreciation on the international competitiveness of Pakistan.

This paper aims to investigate the impact of trade liberalization on economic growth of selected developing and least developed economies by augmenting standard production function.

The panel fixed effect model is used to estimate impacts of macroeconomic variables on economic growth. Real GDP million US$ is taken as proxy for economic growth. The capital stock series for each cross-section is generated from gross fixed capital formation. The total trade to GDP is taken as proxy for trade liberalization.

The result shows significant positive impact of selected macroeconomic variables on economic growth, except trade liberalization index. The one unit increase in trade liberalization deteriorates economic growth, of developing countries by −280.86 million US$ and least developing by −3555.09 million US$.

The significant negative impact indicates the relatively greater share of import than exports. The developing nations should develop production side and adopt export promotion policies besides managing imports for the achievement of sustainable growth.

This study uses augmented production function and constructed capital stock for individual countries. The total trade to GDP is taken as index for trade liberalization and was found to have significant negative impact.

This study aims to examine the possible gains and challenges for the enhancement of bilateral trade ties between India and Pakistan. It is interested specifically in analyzing and deliberating an attempt to identify the key challenges and bottlenecks in cross-border trade.

This paper offers in-depth case study of trade between India and Pakistan using time-series data and through various stake holders' interviews. As further discussed in the paper, the data investigation and interviews highlight impediments in India–Pakistan trade from trade policy to other policies involved in this process.

Based on time series data and stakeholders’ interviews, the study concludes that poor trade logistics and abysmal transport infrastructure, high tariffs and non-tariff measures, lengthy customary procedures, heavy import duties, port restrictions, lack of appropriate storage facilities, strict visa regime, financial transaction barriers and lack of telecommunication facilities are the major challenges in the way of regional trade.

The study proposes some key reforms and policy measures to boost the formal trade to minimize the trade obstacles such as public–private partnerships and inclusion of private sector in a joint trade commission to strength the business relations between the two countries.

This chapter provides an in-depth look at how digital supply chain management (DSCM) can revolutionize supply chains in the post-COVID world. The COVID-19 pandemic exposed the vulnerabilities of traditional supply chains, highlighting the need for resilience and adaptability. The chapter begins by examining these COVID-induced disruptions, setting the foundation for the discussion on DSCM. DSCM, leveraging advanced technologies and data insights, offers a solution to these challenges, promoting agility, transparency, and sustainability in supply chain operations. This represents a significant shift from traditional practices, equipping organizations to cope with the dynamic postpandemic environment. Key capabilities of DSCM, such as resilience, integration, agility, and risk management, are discussed, supported by real-world examples from leading companies. These examples showcase the successful implementation of DSCM and its benefits in navigating the complexities of modern supply chains. However, the adoption of DSCM is not without challenges, including cybersecurity risks and integration difficulties. The chapter suggests strategies to overcome these challenges, emphasizing the importance of technology, collaboration, sustainability, and data-driven decision-making. By embracing these strategies, organizations can effectively manage their supply chains in the evolving global market, leveraging DSCM to withstand future uncertainties.

The advent of the digital technologies (DTs), coincided with the pandemic and global conflicts, has proven to be an unprecedented and transformative era for supply chain management (SCM). DTs are reshaping the way organizations plan, execute, and optimize their SC operations. Throughout this book, we posit that the adoption of digital supply chain management (DSCM) has become essential for staying competitive and responsive in a rapidly evolving business environment. However, amid technological advancements and digital solutions, there exists a critical factor that often goes overlooked – the significance of intangible assets, specifically intellectual capital (IC). This chapter comprehensively explores the role of an organization's IC in the adoption and performance of DSCM. We employ a comprehensive analytical approach, drawing upon existing literature from various sources to elucidate the relationship between IC and DSCM. Synthesizing insights from the literature, the chapter shows how each constituent of IC contributes to the adoption, operation, and performance improvement of DSCM. The discussion in the chapter shows that human capital (HC) forms foundations, as the knowledge, skills, and abilities (KSAs) of the employees are prerequisites essential for understanding, adopting, and capitalizing on DTs in SCM. The analysis also reveals that SC, which represents organizational processes, digital tools, and knowledge repositories, supports the seamless integration of DTs within SCs. Similarly, RC, by nurturing trust, open communication, and collaborative networks, plays an instrumental role in establishing ecosystems that help the adoption and effective functioning of DSCM. This chapter makes a convincing case to consider IC as the strategic component while DSCM adoption and performance.

The present chapter discusses evolution, definitions, dimensions, capabilities, and the present state of the art of digital supply chain management (DSCM). The objective of the chapter is to offer a detailed understanding of DSCM, by shedding light on its historical development, exploring its multipronged definitions, and highlighting its core dimensions and capabilities in the contemporary business landscape. The evolution of DSCM appears as a central theme, rooted in the background of industrial revolutions. It starts by relooking at the First Industrial Revolution (IR) with its mechanization and steam power, progresses through the Second IR with electrification and mass production, and arrives at the Third IR, characterized by the rise of computers and the internet. The pivoting transition into the Fourth IR, also called Industry 4.0, marks the start of DSCM with its fusion of digital technologies (DTs) in the supply chain (SC) processes. Analysis of key definitions of DSCMs unveils their role as an enabler of SC collaboration, customer-centric nature, having overarching reliance on DTs. Moreover, the chapter explores the core dimensions of DSCM, exposing its ability to improve SC resilience, sustainability, visibility, efficiency, and agility. These capabilities stem from seamlessly woven DT developments into SC: artificial intelligence (AI), machine learning, the Internet of Things (IoT), and advanced analytics. The chapter concludes by highlighting the present state of the art in DSCM, reflecting its indispensable role in the contemporary turbulent business dynamics. In short, this chapter offers a synthesized view of DSCM's definitions, dimensions, evolution, capabilities, and present status within the larger context of supply chain management (SCM) literature.

This final chapter delves into the future of digital supply chain management (DSCM) amid today's dynamic business environment, shaped by technological advancements and factors like automation, artificial intelligence (AI), sustainability, and resilience. It emphasizes the crucial role of digital technologies (DTs) such as AI, the Internet of Things (IoT), Industrial IoT, and the Internet of Everything (IoET), along with blockchain, in revolutionizing supply chain operations. These technologies enable agility, flexibility, efficiency, and responsiveness, crucial for supply chains to proactively adapt to market changes. The chapter explores the trends in DSCs, focusing on real-time data analytics, end-to-end visibility, sustainability, and resilience. It highlights the growing importance of transparency in supply chains, driven by consumer demand for sustainable practices and product origins. DSCM is identified as pivotal for prioritizing sustainability, leading organizations toward green practices. Despite the opportunities in DSCM, challenges like cybersecurity, data management complexities, geopolitical uncertainties, and talent shortages are acknowledged. To overcome these, the chapter stresses strategic foresight in DSCM and the importance of robust process management, risk management, and talent development. The future-readiness of supply chain professionals is discussed, highlighting the need for change management, development of social and deep work skills, collaboration, and ethical practices. The chapter concludes by underscoring the transformative potential of DTs in the digital era, urging organizations to embrace innovation, transparency, and sustainability in their supply chains, recognizing that the future of DSC is an imminent reality.

Economic costs and benefits are at the core while taking decision to adopt digitalization in the supply chain. The present chapter provides an in-depth exploration of the economic dimensions of digital supply chain management (DSCM) adoption in a firm. Drawing from a diverse source of literature, this chapter discusses the effect of economic outlook on DSCM adoption, the economic benefits of DSCM adoption and costs associated with it, and economic analysis and evaluation methodologies. The chapter also shares the case studies illustrating the real-world implications of economic considerations within DSCM initiatives. The chapter highlights how changing international socioeconomic and political dynamics can influence businesses across the globe. By analyzing the impacts of evolving market trends, changing consumer preferences, and geopolitical tensions, organizations can considerably forecast the possible impacts of these macroeconomic forces adeptly. The chapter also undertakes discussion on the economic cost and benefits associated with DSCM adoption. The economic analysis helps understand that the expected benefits outweigh economic costs, substantiating the economic viability of DSCM projects. The chapter concludes by discussing the examples of some real-world companies, highlighting how organizations have successfully applied economic analyses to their DSCM initiatives. This also highlights as to how showcasing how detailed economic assessments can justify substantial investments, deliver operational efficiencies, and reshape industries.