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The purpose of this paper is to demonstrate the impact of the welding sequence on the substrate plate distortion during the wire and arc additive manufacturing (WAAM) process. This paper also aims to show the capability of finite element simulations in the prediction of those thermally induced distortions.

An experiment was conducted in which solid aluminum blocks were manufactured using two different welding sequences. The distortion of the substrates was measured at predefined positions and converted into bending and torsion values. Subsequently, a weakly coupled thermo-mechanical finite element model was created using the Abaqus simulation software. The model was calibrated and validated with data gathered from the experiments.

The results of this paper showed that the welding sequence of a part significantly affects the formation of thermally induced distortions of the final part. The calibrated simulation model was able to capture the different distortion behavior attributed to the welding sequences.

Within this work, a simulation model was developed capable of predicting the distortion of WAAM parts in advance. The findings of this paper can be used to improve the design of WAAM welding sequences while avoiding high experimental efforts.

The paper aims to present an integrated foresight framework and method to support decision-makers who are confronted with today’s complex and rapidly changing world. The method aims at reducing the degree of uncertainty by addressing the inertia or duration of unfolding trends and by placing individual trends in a broader context.

The paper presents a three-layered framework and method for assessing megatrends based on their inertia or duration. It suggests that if long-term trends and key future uncertainties are studied in conjunction at a meta-level and placed in a broader multi-layered framework of trends, it can result in new insights.

The application of the proposed foresight method helps to systematically place a wide range of unrelated trends and key uncertainties in the context of a broader framework of trends, thereby improving the ability to understand the inertia, direction and mutual interaction of these trends.

The elaboration of identified trends and key uncertainties is partly case-specific and subject to interpretation. It is aimed at illustrating the potential use of the framework.

The paper presents a new approach that may, by itself or in combination with existing foresight methods, offer new means for anticipating future developments.

The use of the proposed framework has potential to provide better insight in the complexity of today’s rapid-changing world and the major transitions taking place. It aims to result in sharper foresight by reducing epistemic uncertainty for decision-makers.

The paper demonstrates how megatrends, Kondratieff waves and century-long trends can be placed in an integrated framework and analysed in conjunction.

A firm's ability to cascade sustainability requirements further down to lower-tier suppliers might be affected by inter-firm power relations. This study aimed to identify the power sources of focal firms and first- and lower-tier suppliers and to investigate how they may affect their ability to cascade sustainability requirements along multi-tier supply chains.

A multiple case study of 24 companies was conducted to investigate the sources of power in multi-tier supply chains. In total, 42 informants from five focal companies, ten first-tier suppliers and nine lower-tier suppliers were interviewed.

Differences were found between the sources from which focal firms and first- and lower-tier suppliers drew power. Findings revealed that firms' power sources may increase or impair their ability to cascade sustainability requirements to lower supply chain tiers. Furthermore, multi-tier supply chain-level power sources constitute a significant determinant of firms' ability to disseminate sustainability requirements to lower-tier suppliers.

The results can help companies and purchasing managers understand how their own and suppliers' power may affect their ability to cascade sustainability agendas to lower-tier suppliers. In particular, the results can be useful for supplier selection and the development of supplier relationship management strategies for fostering sustainability in multi-tier supply chains.

This study places traditional power perspectives in the context of multi-tier sustainable supply chain management, broadening the view beyond dyadic relationships that have traditionally been the focus of the supply management literature.

Carbon trading mechanism has been adopted to foster the green transformation of the economy on a global scale, but its effectiveness for the power industry remains controversial. Given that energy-related greenhouse gas emissions account for most of all anthropogenic emissions, this paper aims to evaluate the effectiveness of this trading mechanism at the plant level to support relevant decision-making and mechanism design.

This paper constructs a novel spatiotemporal data set by matching satellite-based high-resolution (1 × 1 km) CO₂ and PM_2.5 emission data with accurate geolocation of power plants. It then applies a difference-in-differences model to analyse the impact of carbon trading mechanism on emission reduction for the power industry in China from 2007 to 2016.

Results suggest that the carbon trading mechanism induces 2.7% of CO₂ emission reduction and 6.7% of PM_2.5 emission reduction in power plants in pilot areas on average. However, the reduction effect is significant only in coal-fired power plants but not in gas-fired power plants. Besides, the reduction effect is significant for power plants operated with different technologies and is more pronounced for those with outdated production technology, indicating the strong potential for green development of backward power plants. The reduction effect is also more intense for power plants without affiliation relationships than those affiliated with particular manufacturers.

This paper identifies the causal relationship between the carbon trading mechanism and emission reduction in the power industry by providing an innovative methodology for identifying plant-level emissions based on high-resolution satellite data, which has been practically absent in previous studies. It serves as a reference for stakeholders involved in detailed policy formulation and execution, including policymakers, power plant managers and green investors.

The similarities between the developments of the United States (U.S.) and China into global powers (countries with global economic, military, and political influence) can be analyzed through big data analysis from both countries. The purpose of this paper is to examine whether or not China is on the same path to becoming a world power like what the U.S. did one hundred years ago.

The data of this study is drawn from political rhetoric and linguistic analysis by using “big data” technology to identify the most common words and political trends over time from speeches made by the U.S. and Chinese leaders from three periods, including 1905-1945 in U.S., 1977-2017 in U.S. and 1977-2017 in China.

Rhetoric relating to national identity was most common amongst Chinese and the U.S. leaders over time. The differences between the early-modern U.S. and the current U.S. showed the behavioral changes of countries as they become powerful. It is concluded that China is not a world power at this stage. Yet, it is currently on the path towards becoming one, and is already reflecting characteristics of present-day U.S., a current world power.

This paper presents a novel approach to analyze historical documents through big data text mining, a methodology scarcely used in historical studies. It highlights how China as of now is most likely in a transitionary stage of becoming a world power.

Microbusinesses are better able to assist many disadvantaged groups in finding employment and breaking the cycle of poverty because they require less initial capital and employ a large number of poor people in developing economies. Women run and own the majority of micro-businesses in urban Ethiopia. This study aims to investigate women’s microbusiness participation decisions and the effect on poverty in the Wolaita zone southern Ethiopia.

A cross-sectional study was carried out using a mixed-methods research approach. A total of 384 women who owned micro-businesses were chosen using a systematic random sampling technique, while 36 women were purposefully chosen for qualitative data analysis. Data were gathered through survey questionnaires, in-depth interviews and focus group discussions. The collected data were analyzed by using a propensity score matching technique as well as contextual analysis.

The study discovered that women’s participation in registered micro-businesses had a higher and more beneficial impact on their food, non-food and overall consumer spending than women’s participation in unregistered microbusinesses, which helped to reduce poverty. Besides, overall women’s participation in micro-business increased their decision-making power and enabled them to provide resources for their families food and non-food consumption, with registered micro-business participants reaping the greatest benefits.

This research focused on the effects of women’s micro-entrepreneurship on poverty in low-income communities. Rather than providing food, clothing and/or other aid to women in disadvantaged communities, the authors asserted that assisting women and their micro-businesses allows them to be self-sufficient in terms of food and clothing as a long-term solution to poverty reduction. As a result, policymakers can use our findings to gain a better understanding of how women’s micro-entrepreneurship affects poverty reduction, allowing them to develop more effective anti-poverty initiatives. This study’s findings are novel and add to the body of knowledge in Ethiopia and the sub-Saharan African region.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.

Green energy as a transportation supply trend is irreversible. In this paper, a highway energy supply system (HESS) evolution model is proposed to provide highway transportation vehicles and service facilities with a clean electricity supply and form a new model of a source-grid-load-storage-charge synergistic highway-PV-WT integrated system (HPWIS). This paper aims to improve the flexibility index of highways and increase CO₂ emission reduction of highways.

To maximize the integration potential, a new energy-generation, storage and information-integration station is established with a dynamic master–slave game model. The flexibility index is defined to evaluate the system ability to manage random fluctuations in power generation and load levels. Moreover, CO₂ emission reduction is also quantified. Finally, the Lianhuo Expressway is taken as an example to calculate emission reduction and flexibility.

The results show that through the application of the scheduling strategy to the HPWIS, the flexibility index of the Lianhuo Expressway increased by 29.17%, promoting a corresponding decrease in CO₂ emissions.

This paper proposed a new model to capture the evolution of the HESS, which provides highway transportation vehicles and service facilities with a clean electricity supply and achieves energy transfer aided by an energy storage system, thus forming a new model of a transportation energy system with source-grid-load-storage-charge synergy. An evaluation method is proposed to improve the air quality index through the coordination of new energy generation and environmental conditions, and dynamic configuration and dispatch are achieved with the master–slave game model.

Emergency humanitarian medical cold chains (HMCCs) depend heavily on their supporting energy services due to end-to-end temperature requirements in volatile disaster situations. Most energy sources powering emergency HMCCs are fossil-based due to well established processes, regardless of their environmental impact. In response to the recent energy crisis and climate change, a solution to tackle this issue relies on renewable energy sources (RES), whose use has increased to promote climate resilient development. Nevertheless, RESs’ capacity to replace conventional energy services in emergency HMCCs remains poorly understood. This study aims to investigate opportunities for, and barriers to, increasing the use of RESs in emergency HMCCs, thereby enhancing their environmental sustainability.

Based on a review of academic and practice literature, interviews with expert practitioners on emergency HMCCs and sustainable energy, and case study examples, this research aimed to analytically generalise the phenomenon by investigating opportunities for, and barriers to, increasing the use of RESs in emergency HMCCs. The phenomenon is illustrated in a novel framework of typical HMCC, that forms a contextual basis for future research.

A conceptual framework of typical emergency HMCC shows energy-consuming sections where RES can best be increased. This research is put forth in four propositions to manage the opportunities and barriers of the transition.

This research is, to the best of the author’s knowledge, the first attempt to operationalise sustainability by linking energy with HMCCs’ logistical activities in complex emergency settings. The cross-findings from literature, example cases and interviews together demonstrate the need to increase the use of RES in HMCCs, and how to do it.