Abstract: Vegetable farmers face a number of challenges in marketing. Having first-hand information about vegetable marketing is essential to devise appropriate strategies aimed at enhancing the value of the vegetable chain. It was in line with this view that the study was conducted to characterize vegetable markets in Northern Ethiopia. In an effort to identify the factors influencing vegetable marketing among farmers, data were collected from 283 farm households who were selected using stratified random sampling. Furthermore, the data were triangulated through focus group discussion (FGD) and key informant interviews. Descriptive statistics and the binary logistic regression model were used to identify the variables and test the probability of their influence in regard to farmers decisions in vegetable marketing. From the 13 explanatory variables included in the binary logistic regression model, six predictors were found to be statistically significant in determining the effects of participation decision on vegetable market. These variables are as follows: household family size, total land holding of the household, amount of vegetable produced and marketed, use of irrigation technologies, contact with extension agents, and access to market information. Relying on a survey result and observations, the findings of the study indicated that vegetable marketing is significantly improving the livelihood of smallholder producers.

Abstract: Although Iran is one of the top 10 countries in the world that produce tomatoes, the level that they are exported into the global market is low. This issue may have resulted from a major problem within tomatoes supply chain management. This paper aims to develop an empirical model of the supply chain management (SCM) of tomato companies. Throughout the reviewed literature, a SCM construct with different six indicators has been developed, including information sharing, long-term relationship, cooperation, quality, flexibility, and delivery. In this study, the influence of the SCM components on tomato export was identified through the use of empirical data that were collected from 20 different tomato companies in Northeast Iran. Using structural equation modeling, the major elements of SCM were found to have significant impacts on the export of tomatoes. The results also showed that information sharing, cooperation, flexibility, quality, and delivery had significant positive effects on the export of tomatoes.

Abstract: Demand response (DR) can aid with grid integration of renewables, ensuring security of supply, and reducing generation costs. However, not enough is known about how residential customers’ perceptions of DR shape their response to such programs. This paper offers a deeper understanding of – and reveals the heterogeneity in – this relationship by conducting a quantile regression analysis of a Belgian DR trial, combining data on response with information on household attitudes towards smart appliances. Results overall suggest that improving response requires subtle shifts in electricity consumption behaviour, which can be achieved through changes in user perceptions. Specifically, if customers are inclined to be flexible, a stronger perception of smart appliances as being beneficial can greatly improve response. With those who are less flexible, the cost of smart appliances is a bigger concern. Thus, when designing DR programs, policymakers should aim to promote modest behaviour changes – so as to minimise inconvenience – in customers, by improving awareness on the benefits of smart appliances. Uptake of such DR programs may be improved by explaining the financial benefits or offering incentives to less flexible population segments. Lastly, improving response among older population segments will require a deeper investigation into their concerns.

Abstract: The study analysed the factors that affect the internal governance quality of corporations in Ethiopia. It performed an ordered logistic regression analysis on a randomly selected sample of 76 corporations to analyse the effect of the ownership structure, form of ownership (private or government), leverage, corporate size, and sales growth on the internal governance quality score (IGQS). The governance quality score was measured using 20 indices categorized into four perspectives: disclosure, board characteristics, ethics, and shareholder rights. In this study, a significant positive effect of the corporate size and sales growth on the IGQS was found. In addition, government-owned corporations were found to perform better than privately owned corporations. It is recommended that appropriate authorities and officials should encourage the use of the corporate governance system in privately owned corporations and the convergence of internal governance quality of the two groups of corporations to the highest level.

Abstract: It has been acknowledged that power is a fundamental aspect that needs to be considered when performing a value chain analysis. The structure of the value chain is indicative of the power distribution along the chain. By employing systems thinking the structure of the value chain can be further investigated and inferences on market power issues can be made. This novel approach connects value chain research with insights from Industrial Organization (IO) literature. Depending on the case, market power may not be measurable by traditional economic tools. Systems thinking offers an alternative tool, allowing the employment of qualitative and quantitative data, overcoming drawbacks of IO methods and providing more depth to value chain analysis. In this paper the valuable contribution of systems thinking to market power analysis is exemplified by the Belgian sugar beet case. The analysis showed that transportability and perishability of sugar beet are key causes of market failure in the Belgian sugar value chain. Systems thinking can support understanding potential future behavior of the market based on the thorough understanding of the current market structure. We illustrate how to integrate factors determining the market structure into causal loop diagrams. This novel approach allows a comprehensive evaluation and thus opens up market power analysis to interdisciplinary research.

Abstract: This paper conducts a meta-analysis of 32 electricity demand response programs in the residential sector to understand whether their success is dependent on specific characteristics. The paper analyses several regression models using various combinations of variables that capture the designs of the programs and the socio-economic conditions in which the programs are implemented. The analysis reveals that demand response programs are more likely to succeed in highly urbanized areas, in areas where economic growth rates are high, and in areas where the renewable energy policy is favorable. These findings provide useful guidance in determining where and how to implement future demand response programs.

Abstract: When two-dimensional (2D) atomic crystals are brought into close proximity to form a van der Waals heterostructure, neighbouring crystals may influence each other's properties. Of particular interest is when the two crystals closely match and a moire pattern forms, resulting in modified electronic and excitonic spectra, crystal reconstruction, and more. Thus, moire patterns are a viable tool for controlling the properties of 2D materials. However, the difference in periodicity of the two crystals limits the reconstruction and, thus, is a barrier to the low-energy regime. Here, we present a route to spectrum reconstruction at all energies. By using graphene which is aligned to two hexagonal boron nitride layers, one can make electrons scatter in the differential moire pattern which results in spectral changes at arbitrarily low energies. Further, we demonstrate that the strength of this potential relies crucially on the atomic reconstruction of graphene within the differential moire super cell.

Abstract: The dataset together with the corresponding Python scripts and Jupyter notebooks presented in this article are supplementary data for the work presented in Samaee et al., 2019 [1]. The data itself consists of two parts: the simulation data that was used in [1] to analyze the effect of a particular grain boundary on curved dislocations and the precession electron diffraction (PED) strain maps together with post-processed data for analyzing details of the observed dislocation vein structures. Additionally, the complete stress tensor components, which are not shown in [1], have also been included. The data sets are accompanied by Python code explaining the file formats and showing how to post-process the data. (c) 2019 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Abstract: Branched plasmonic nanocrystals (NCs) have attracted much attention due to electric field enhancements at their tips. Seeded growth provides routes to NCs with defined branching patterns and, in turn, near‐field distributions with defined symmetries. Here, a systematic analysis was undertaken in which seeds containing different distributions of planar defects were used to grow branched NCs in order to understand how their distributions direct the branching. Characterization of the products by multimode electron tomography and analysis of the NC morphologies at different overgrowth stages indicate that the branching patterns are directed by the seed defects, with the emergence of branches from the seed faces consistent with minimizing volumetric strain energy at the expense of surface energy. These results contrast with growth of branched NCs from single‐crystalline seeds and provide a new platform for the synthesis of symmetrically branched plasmonic NCs.

Abstract: Carbon capture and utilization (CCU) technologies capture CO2 waste emissions and utilize them to generate new products (such as fuels, chemicals, and materials) with various environmental, economic, and social opportunities. As most of these CCU technologies are in the R&D stage, their technical and economic viability are examined with less attention to the social aspect which is an important pillar for a holistic sustainability assessment. The lack of systematic social impact research is mainly due to the difficulty of identifying and quantifying social aspects through the entire life cycle of products. We will fill this gap for CCU technologies and identify the main social indicators. A multi-criteria decision making tool: TOPSIS (technique for order of preference by similarity to ideal solution) was applied to empirically determine which indicators are more relevant for assessing the social impact of a company operating CCU activities within a European context. First, seeing that social impact categories are linked to key stakeholder groups, we considered workers, consumers, and local communities as relevant stakeholders. Second, the main social impact categories and their potential performance indicators associated to each group of stakeholders were listed using the United Nations Environment Program/Society of Environmental Toxicology and Chemistry (UNEP/SETAC) guidelines. In the third step, an online questionnaire was distributed to identify the main social categories and indicators for CCU, to which 33 European CCU experts responded. Finally, a modified TOPSIS was applied to rank the indicators based on their relevance. We found that the indicators related to “end of life responsibility” and “transparency” within a CCU company achieved the highest rank affecting the consumers group, whereas “fair salary” and “equal opportunities/discriminations” were determined as the most relevant impact categories for the workers. For the local community group, “secure living conditions” and “local employment” received the highest priority from the experts’ point of view. Furthermore, “health and safety” considerations were identified as one of the most important criteria affecting all three groups of stakeholders. The ranking list of the main social indicators identified in our study provides the basis for the next steps in the social sustainability assessment of CCU technologies; that is, data collection and impact assessment. Our outcomes can also be used to inform the producers regarding the most and least relevant social aspects of CCU so that the potential social impacts caused by their production activities can be improved or prevented.

Abstract: The global climate is changing, and farmers must increase their adaptive capacity to avoid negative impacts. This study aimed to examine the adaptive capacity of farmers’ household to tolerate climate changes and identify factors affecting the climate in Hamadan province, Iran. The adaptive capacity was evaluated quantitatively by using 23 indicators and was categorized into high, moderate, low, and very low adaptive capacity. The study was based on a cross sectional survey and was conducted with a random sample of 280 household farmers distributed in five counties of Hamadan province in the west of the country whose climatic data revealed signs of climate change. The result showed that farmers’ negative perception toward climate change generally increases during dry seasons and decreases when the precipitation and water resources are more available. Regarding the available information, only 15% of farmers had a high level of adaptive capacity, while 10% of them were highly adapted, and 27.5% showed a very low level of adaptive capacity. Adaptive capacity in the current study was influenced by some socio-economic variables including total farm size, irrigated farm size, number of agricultural land plots, and perception and knowledge of climate change.