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In social marketplaces, follower ego networks are integral social capital assets for online sellers. While previous research has underscored the positive impact of the follower number on seller performance, little attention has been given to the structure of follower networks and their value implications. This research investigates two structural properties of follower networks—network centralization and density—and examines their main and contingent effects on sellers’ sales performance.

A 13-month panel dataset of 1,150 sellers in Etsy, a social marketplace for handmade and vintage products, was collected and analyzed. A fixed effects model was adopted to validate the hypotheses on the main effect of centralization and density, as well as the moderating effects of two store attributes: store age and product diversification.

We find that both network centralization and density negatively impact sellers’ sales performance, and these effects vary across store age and product diversification levels. Specifically, the negative effect of network centralization is less pronounced for older stores than young ones, whereas the negative effect of density is more severe for stores with high product diversification.

This research contributes to social commerce research by highlighting the significance of network structure, alongside network size, in assessing the value of followers and offers practical guidance for sellers in social marketplaces seeking to optimize their follower networks.

This work aims to analyse the relationship between public health efficiency and well-being considering a panel of 102 Italian provinces from 2000 to 2016 and evaluates if there are omitted variable biases and endogeneity biases and also evaluates if there are heterogeneous effects among provinces with different income levels.

We use a multi-input and output bootstrap data envelopment analysis to assess public health efficiency. Then, we measure well-being indices using the min-max linear scaling transformation technique. A two-stage least squares model is used to identify the causal effect of improving public health efficiency on well-being to account for time-invariant heterogeneity, omitted variable bias and endogeneity bias.

After controlling for important economic factors, the results show a significant effect of an accountable and efficient public health system on well-being. Those effects are concentrated in the North, the most economically, geographically and environmentally advantageous areas.

The use of the sample mean, probably the oldest and most used method for aggregating the indicators, could be affected by variable compensation, with consequent misleading results in the process of constructing the well-being index. Another limitation is the use of lagged values of the main predictor as an instrument in the instrumental variables setting because it could lead to information loss. Finally, the availability of data over a long period of time.

The findings could help policymakers adopt measures to strengthen the public health system, encourage private providers and inspire countries worldwide.

These results draw the attention of local authorities, who play an important role in designing and implementing policies to stimulate local public health efficiency, which puts individuals in the conditions of achieving overall well-being in their communities.

For the first time in Italy, a panel of well-being indices was constructed by developing new methodologies based on microeconomic theory. Furthermore, for the first time, the assessment of the relationship between public health efficiency and well-being is carried out using a panel of 102 Italian provinces.

The lightweight design of aircraft seats can significantly improve fuel efficiency and reduce greenhouse gas emissions. Metal additive manufacturing (MAM) can produce lightweight topology-optimized designs with improved performance, but limited build volume restricts the printing of large components. The purpose of this paper is to design a lightweight aircraft seat leg structure using topology optimization (TO) and MAM with build volume restrictions, while satisfying structural airworthiness certification requirements.

TO was used to determine a lightweight conceptual design for the seat leg structure. The conceptual design was decomposed to meet the machine build volume, a detailed CAD assembly was designed and print orientation was selected for each component. Static and dynamic verification was performed, the design was updated to meet the structural requirements and a prototype was manufactured.

The final topology-optimized seat leg structure was decomposed into three parts, yielding a 57% reduction in the number of parts compared to a reference design. In addition, the design achieved an 8.5% mass reduction while satisfying structural requirements for airworthiness certification.

To the best of the authors’ knowledge, this study is the first paper to design an aircraft seat leg structure manufactured with MAM using a rigorous TO approach. The resultant design reduces mass and part count compared to a reference design and is verified with respect to real-world aircraft certification requirements.

The purpose of this paper is to compare the influence of relative density (RD) and strain rates on failure mechanism and specific energy absorption (SEA) of polyamide lattices ranging from bending to stretch-dominated structures using selective laser sintering (SLS).

Three bending and two stretch-dominated unit cells were selected based on the Maxwell stability criterion. Lattices were designed with three RD and fabricated by SLS technique using PA12 material. Quasi-static compression tests with three strain rates were carried out using Taguchi's L9 experiments. The lattice compressive behaviour was verified with the Gibson–Ashby analytical model.

It has been observed that RD and strain rates played a vital role in lattice compressive properties by controlling failure mechanisms, resulting in distinct post-yielding responses as fluctuating and stable hardening in the plateau region. Analysis of variance (ANOVA) displayed the significant impact of RD and emphasised dissimilar influences of strain rate that vary to cell topology. Bending-dominated lattices showed better compressive properties than stretch-dominated lattices. The interesting observation is that stretch-dominated lattices with over-stiff topology exhibited less compressive properties contrary to the Maxwell stability criterion, whereas strain rate has less influence on the SEA of face-centered and body-centered cubic unit cells with vertical and horizontal struts (FBCCXYZ).

This comparative study is expected to provide new prospects for designing end-user parts that undergo various impact conditions like automotive bumpers and evolving techniques like hybrid and functionally graded lattices.

To the best of the authors' knowledge, this is the first work that relates the strain rate with compressive properties and also highlights the lattice behaviour transformation from ductile to brittle while the increase of RD and strain rate analytically using the Gibson–Ashby analytical model.

Additive Manufacturing (AM) conventionally necessitates an intermediary slicing procedure using the standard tessellation language (STL) data, which can be computationally burdensome, especially for intricate microcellular architectures. This study aims to propose a direct slicing method tailored for digital light processing-type AM processes for the efficient generation of slicing data for microcellular structures.

The authors proposed a direct slicing method designed for microcellular structures, encompassing micro-lattice and triply periodic minimal surface (TPMS) structures. The sliced data of these structures were represented mathematically and then convert into 2D monochromatic images, bypassing the time-consuming slicing procedures required by 3D STL data. The efficiency of the proposed method was validated through data preparations for lattice-based nasopharyngeal swabs and TPMS-based ellipsoid components. Furthermore, its adaptability was highlighted by incorporating 2D images of additional features, eliminating the requirement for complex 3D Boolean operations.

The direct slicing method offered significant benefits upon implementation for microcellular structures. For lattice-based nasopharyngeal swabs, it reduced data size by a factor of 1/300 and data preparation time by a factor of 1/8. Similarly, for TPMS-based ellipsoid components, it reduced data size by a factor of 1/60 and preparation time by a factor of 1/16.

The direct slicing method allows for bypasses the computational burdens associated with traditional indirect slicing from 3D STL data, by directly translating complex cellular structures into 2D sliced images. This method not only reduces data volume and processing time significantly but also demonstrates the versatility of sliced data preparation by integrating supplementary features using 2D operations.

This study aims to explore whether and how the two potential antecedents (i.e. relationship quality at the dyadic level and network density at the network level) affect firms’ internet-interactive capability (FIIC), referring to the capability of a specific firm to communicate and interact with the relevant partner firms on the basis of internet-interactive technologies in the internet environment and, at the same time, the following influence of FIIC on collaborative activities (i.e. joint planning and joint problem-solving).

This study designed a questionnaire and collected data on-site from 400 manufacturers. SmartPLS is used to validate the research model.

The results suggest that the dyadic relationship quality and network density of the partner group are both positively connected with a firm’s FIIC. Besides, FIIC is positively related to collaborative activities with its partners.

Given the nature of our data (i.e. cross-sectional), the authors can collect longitudinal or experimental data to retest the hypotheses.

This study gives certain guidance for firms to be aware of the factors that motivate FIIC and use their FIIC to influence their employees’ collaborative activities in their relationships with partners, thereby promoting cooperation performance.

This study attempts to extend the resource-based theory based on the logic of motivation-capability by exploring the potential antecedents of FIIC and makes contributions to the current studies on the antecedents of FIIC, which provides actionable insights for firms to play the role of FIIC in interfirm interactions.

Climate change is a bitter truth for the entire humanity, and it vehemently calls for thoughtful means for environmental protection along with sustainable economic growth. International trade blocs fundamentally represent amalgamation of countries to achieve unified goals like higher living standards, reduced trade barriers, freer labour mobility across member states, social and cultural upliftment, political allegiance to regional association, etc. Throughout the 1990s, these trade blocs have committed to reducing environmental pressures and shifting towards cleaner forms of energy. This chapter examines the relationship between rate of change in carbon dioxide (CO₂) emissions per capita and rate of change in per capita gross domestic product (GDP) in linear, quadratic and cubic polynomial forms with the other control variables like inflow of foreign direct investment (FDI), export of goods and services, population density, urban population percentage and location dummies for the 66 countries falling in seven regional trade blocs. Other than the European Union and North American Free Trade Agreement (NAFTA), the remaining five trade blocs in the study – Association of South-East Nations (ASEAN), South Asian Association for Regional Cooperation (SAARC), Common Market for Eastern and South Africa (COMESA), Mercado Común del Sur (MERCOSUR) and Commonwealth of Independent States (CIS) – contain mostly the developing and some of the fastest growing economies of the world. The panel regression result finds an inverse relationship between rate of change in per capita CO₂ emissions and rate of change in GDP per capita (in linear and cubic polynomial forms), exports and population density, while the other coefficients of the explanatory variables are positive. The study also establishes an Environmental Kuznets Curve (EKC) which is opposite to N-shape during 2005–2019, and that contradicts with the original EKC of inverted U-shaped. However, this shape admits the collective efforts of region-specific trade blocs towards achieving clean environment which is one of the important global goals.

Nowadays, there is a strong public interest in promoting transparency to be informed about the actions of the public sector. At the same time, there has been a significant change in society’s perceptions and concerns about sustainable development, with a marked increase in attention to this area. In this context, our main objective is to investigate the impact of transparency practices in local government on the implementation of the Sustainable Development Goals (SDGs) in Spanish municipalities.

We will analyse a sample of 84 municipalities, using the Dynamic Transparency Index published by Dyntra to measure transparency. For the level of implementation of the SDGs, we will use an index specifically created using data from the report “The SDGs in 100 Spanish Cities”, published by the Spanish Network for Sustainable Development in 2020.

Municipalities with a larger dependent population tend to achieve higher SDG levels. Municipalities with lower financial surpluses and more self-generated resources show better SDG implementation. Progressive political parties lean more towards sustainability, and coalition governments show higher SDG implementation than majority governments. Gender appears to play a minor role in SDG implementation, but male leadership is associated with higher levels. Factors such as population density and government transfers do not have a significant impact on SDG implementation levels.

This study seeks to address the lack of empirical research on the potential impact of transparency on the achievement of the SDGs, while also taking into account other socio-economic, financial and political aspects of the municipality. In doing so, it also contributes to the limited empirical literature on the determinants of the level of SDG implementation in local governments.

Firms embedded in networks of relations are theorized through Gnyawali and Madhavan’s (2001) (G&M) structural embeddedness model to gain competitive advantage from topological characteristics. Empirical studies to support their theory have never been executed in full. Our study provided a full empirical test of their model in a digital trading network to achieve a higher degree of certainty that those network structural characteristics can have a major impact on the degree to which certain firms lead to competitiveness in a digital trading network environment.

To examine how firms respond in competitive situations, we chose the hyper-active digital trading network, eBay as our empirical context. We used eBay auction data to analyze how the network characteristics of eBay resellers impact their competitive behaviors.

Our study found strong support for the G&M model of competitiveness. We offer explanations for where support was not as strong as the Gynawali and Madavan theory proposes.

Our research is limited by our chosen context and findings in support of part of G&M model. Future studies in other digital contexts are needed to enhance the modeling of network topologies and further study the impacts of network density and structural autonomy on competitive action.

Our study suggests that managers proceed cautiously in forming partnerships, weighing circumstances where the firm can find itself with increased information power and avoiding, to the greatest extent possible, situations where the playing field is roughly equal.

Theory-making in this domain has begun as well as initial empirical testing. Much more needs to be accomplished, though, before embeddedness modeling can be thought of as being well established.

The G& M Model of competitiveness is an SNA explanation of why some competitive units succeed and others do not. Our study is the first, full blown empirical analysis of the theory.