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Economic theories on structural change focus on factors such as fluctuations in relative prices and income growth. In addition, China’s reform and opening up has also been accompanied by increasing openness, significant fluctuations in investment rates, and frictions in the labor market. Existing literature lacks a unified theoretical framework to assess the relative importance of all these determinants. The paper aims to discuss these issues.

To incorporate all of the potential determinants of China’s structural change, the authors build a two-country four-sector neoclassical growth model that embeds the multi-sector Eaton and Kortum (2002) model of international trade, complete input-output structure, non-homothetic preference and labor market frictions. The authors decompose the sectoral employment shares into six effects: the Baumol, Engel, investment, international trade, factor intensity and labor market friction effects. Using the data of Chinese economy from 1978 to 2011, the authors perform a quantitative investigation of the six determinants’ effects through the decomposition approach and counterfactual exercises.

Low-income elasticity of demand, high labor intensity, and the existence of the switching costs are the reasons for the high employment share in the agricultural sector. Technological progress, investment and international trade have comparatively less influence on the proportion difference of employment in the three sectors.

Therefore, to examine the impact on China’s structural change, in addition to Baumol effect and the Engel effect, it is also necessary to consider the impact of three more factors: international trade, investment and switching costs. Therefore, the authors decompose the factors that may influence China’s structural change into the Baumol, Engel, investment, international trade, factor intensity effect and switching cost effects. The authors evaluate these six effects using the decomposition approach and counterfactual exercises.

This chapter provides some concluding reflections on the different experiences of structural change encountered by the TARGET partners. The various TARGET partners had different roles in the structural change processes: seven organisations designed, implemented and monitored gender equality plans (GEPs) for the first time, two organisations provided tailored support to implementing institutions and one organisation evaluated GEP implementation. This edited volume provides an account of these diverse experiences of engaging with and catalysing structural change in very different research organisations operating in extremely different contexts both within the EU and beyond. The volume thus contributes to the growing body of literature generated from structural change projects by offering a specific focus on the TARGET approach. The TARGET process of structural change – undertaken through the development and implementation of tailored, evidence-based GEPs – was found to be strengthened through formal top management commitment and by taking a reflexive approach that was powered by communities of practice and supported by financial resources, gender expertise as well as gender and organisational change competences. Engaged institutions thus managed to overcome unfavourable conditions and implement tailor-made, context-specific interventions, some of them in areas at the cutting edge of topics and issues linked to gender equality in research and innovation such as tackling sexual harassment, sustainability and integrating the gender dimension into research content and curricula.

Poverty alleviation has been a major theme of China's modernization process since the founding of New China. This paper points out that China's poverty alleviation process presents three stylized facts: “Miraculous” achievements of poverty alleviation have been made on a global scale; the poverty alleviation achievements mainly occurred in the high growth stage after reform and opening up; the poverty alleviation process is accompanied by the structural transformation of the urban–rural dual economy.

Therefore, a logically consistent analytical framework should form among the structural transformation of the dual economy, economic growth and the achievements in poverty alleviation. In logical deduction, the structural transformation of the dual economy affects rural poverty alleviation through the effects of labor reallocation, agricultural productivity improvement, demographic change and fiscal resource allocation.

The first two refer to economic growth, and the latter two are alleviation policies. The combination of economic growth and poverty alleviation policies is the main cause for poverty alleviation performance. China's empirical evidence can support the four effects by which the structural transformation of the dual economy affects poverty alleviation.

China's socialist system and its economic system transformation after reform and opening up provide an institutional basis for the effects to come into play. After 2020, China's poverty alleviation strategies will enter the “second-half” phase, namely, the phase of solving the problems of relative poverty in urban and rural areas by adopting conventional methods and establishing long-term mechanisms. This requires the facilitation of the reconnection between poverty alleviation strategies and the structural transformation of the dual economy in terms of development ideas and policy directions.

This paper aims to investigate the influence of air and rail transportation on pollution in Turkey from 1970 to 2020.

Fourier Autoregressive Distributive Lags (ADL) and Fourier Fractional ADL cointegration tests (Banerjee et al., 2017; Ilkay et al., 2021) are employed to analyze the relationship be-tween the variables. Cointegration tests that take into account soft transitions under structural changes are implemented. Structural change issues are crucial for this topic since the changes in countries’ environmental policies and transportation habits are shaped by the decisions taken in relation to environmental regulations. Finally, for robustness purposes, we tested the estimated equation with a completely different methodology. Thus, a Machine Learning (ML) analysis is conducted, through a Ridge Regression (RR).

The findings obtained by applying Fourier Autoregressive Distributive Lags (FADL) and Fourier Fractional ADL cointegration tests, which can control for structural changes, reveal the existence of a long-term relationship between the variables. In addition, FMOLS estimates emphasize that economic growth and air transport can lead to increased pollution in the long run, while rail transport reduces it. Moreover, the statistically significant trigonometric terms indicate the existence of a smooth structural change among the variables. Robustness checks are performed through a Machine Learning (ML) analysis, which roughly confirms the previous results.

To our knowledge, existing research in Turkey focuses mainly on road transport, while the impact of rail and air transport on pollution has not yet been investigated. As such, this study will be a significant addition to the academic literature.

Currently, China’s economy is in the critical phase of transforming economic development patterns and replacing old growth drivers with new ones. Whether it can successfully overcome the “middle-income trap” has become a significant issue attracting wide attention.

Driven by underlying digital technologies such as artificial intelligence, blockchain, cloud computing and big data, the fourth industrial revolution featuring the booming digital economy has provided significant opportunities for China’s economy to “overtake” and overcome the “middle-income trap”. The transformation of economic development pattern, the optimization of industrial structure, and the change of growth drivers, brought by the deep integration of digital and real economies are the keys to leaping over the “middle-income trap”.

From the supply side, the digital economy can improve the quality and efficiency of the supply side and promote the supply-side structural reform and economic growth from the following three aspects: First, promote the quality, efficiency and diversification of the supply system; second, promote networking, opening-up and synergy in the innovation system and third, promote the socialization, modularization and flexibility of production pattern. From the demand side, the digital economy can boost the new drivers of the “troika” of economic growth consisting of consumption, exports and investment by changing the market investment direction, promoting consumption upgrade and fostering export strengths. However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

To overcome the “middle-income trap”, it is necessary to adapt to the laws of economic evolution and promote a fundamental change in economic growth drivers; boost the high-quality development of the digital economy by strengthening the support role of data in the digital economy; and accelerate digital industrialization and industrial digitalization to realize the integration of digital and real economies.

The purpose of this paper is to establish and implement a direct topological reanalysis algorithm for general successive structural modifications, based on the updating matrix triangular factorization (UMTF) method for non-topological modification proposed by Song et al. [Computers and Structures, 143(2014):60-72].

In this method, topological modifications are viewed as a union of symbolic and numerical change of structural matrices. The numerical part is dealt with UMTF by directly updating the matrix triangular factors. For symbolic change, an integral structure which consists of all potential nodes/elements is introduced to avoid side effects on the efficiency during successive modifications. Necessary pre- and post processing are also developed for memory-economic matrix manipulation.

The new reanalysis algorithm is applicable to successive general structural modifications for arbitrary modification amplitudes and locations. It explicitly updates the factor matrices of the modified structure and thus guarantees the accuracy as full direct analysis while greatly enhancing the efficiency.

Examples including evolutionary structural optimization and sequential construction analysis show the capability and efficiency of the algorithm.

This innovative paper makes direct topological reanalysis be applicable for successive structural modifications in many different areas.

This study aims to critically discuss and reorient the diversity, equity and inclusion (DEI) debate toward the idea of addressing and rectifying the pervasive structural inequalities that DEI, in its undiluted form rooted in social justice (SJ), aims to combat. Drawing on Bourdieu, the study first examines the diffusion and contestation of DEI into international business (IB). It then proposes a Bourdieu-inspired agenda to advance the transposition of SJ principles into IB.

The study interpretively reconstructs the process of DEI’s ideational diffusion. It examines how the interplay between ideas and field dynamics in IB shapes ideational processes and outcomes.

In response to rising global inequalities – to which multinational enterprises (MNEs) have significantly contributed – SJ movements have propelled DEI into the wider social and political arena, including corporate boardrooms. Within IB, a diluted version of DEI – IB-DEI – emerged as a paradigm to improve MNEs’ performance, but failed to address underlying structural inequalities. As the social impacts, utility and legitimacy of DEI have been challenged, the DEI debate has come to a flux. The study proposes conceptual and contextual extension of DEI within IB and advancing socially engaged research and practice that help reinforce DEI’s core SJ purpose – tackling structural inequalities.

The study is one of the few to openly tackle SJ-IB contradictions on DEI, while advancing the application of Bourdieu to critical studies of IB.

The purpose of this paper is to examine performance change in the Irish state-owned port sector over the 2000-2016 period using a case study approach.

For analysis, qualitative sources are used to construct an explanatory account for the quantitative measures of productivity, profitability and traffic shift-share change across the major ports within the system.

The results show that overall change in performance largely follows that of the macro-economic performance of the region, characterised by pre-recession growth, decline during the recession and post-recession recovery. Across the ports, however, there was a notable divergence in performance post-recession. Identified factors affecting performance change across the period include demand-side structural change, labour rationalisation and degree of private sector participation.

This study addresses a gap in the formal evaluation of port performance in Ireland. The study further demonstrates the potential of in-depth case study analysis for uncovering insights into the drivers of performance across a number of dimensions, thus allowing for the contextualisation of results. The study of a small number of cases enables the use of rich qualitative sources to create strong narratives, which combined with quantitative measures of performance, can lead to new insights.

The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.