The market-based dissemination of energy-access technologies as a business model for rural entrepreneurs: Evidence from Kenya

Improving access to more modern forms of energy requires supply chains that reach further into rural areas. This paper studies a supply-side intervention intended to foster last-mile distribution of energy-access technologies through local small-scale entrepreneurship. We use a staggered-implementation evaluation design to assess the impact on employment and income outcomes of the intervention, which is a large-scale program in Kenya that supports the diffusion of improved cookstoves and small solar products. The results demonstrate how trained entrepreneurs intensify and diversify their income-generating activities, often by shifting away from subsistence farming as a main source of income. For cookstove entrepreneurs, this goes along with improvements in individual and household incomes as well as perceived economic well-being. Our estimates suggest that impacts do not only differ between the two technologies but also across subgroups including gender, age, and baseline occupation. Our findings substantiate that market-based interventions can foster energy access in rural areas by supporting the establishment of local businesses. We highlight several contextual factors that are of relevance when considering the adoption of this approach.     

The social process of internet appropriation: Living in a digitally advanced country benefits less well-educated Europeans

We generalize and extend the sequential model proposed by the resources and appropriation theory to explain the digital divide in the European Union plus the United Kingdom (EU27+UK). We measure the theoretical constructs of the model with data provided by the EU and test the theoretical predictions using a partial least squares structural equation model. We find support for the hypothesized relationships but find that the effects vary depending on the digital development level of countries. While education overall is the primary determinant of the social production of digital inequalities, a country's digital development level is crucial for less well-educated Europeans. These findings have theoretical and practical implications: (1) they call into question the homogeneity of the effect of causal relationships and the assumption that individuals differ only in terms of motivation, access, and digital skills, and (2) they indicate that socially disadvantaged Europeans benefit from living in more digitally developed countries.     

Probabilistic access forecasting for improved offshore operations

Improving access is a priority in the offshore wind sector, driven by the opportunity to increase revenues, reduce costs, and improve safety at operational wind farms. This paper describes a novel method for producing probabilistic forecasts of safety-critical access conditions during crew transfers. Methods of generating density forecasts of significant wave height and peak wave period are developed and evaluated. It is found that boosted semi-parametric models outperform those estimated via maximum likelihood, as well as a non-parametric approach. Scenario forecasts of sea-state variables are generated and used as inputs to a data-driven vessel motion model, based on telemetry recorded during 700 crew transfers. This enables the production of probabilistic access forecasts of vessel motion during crew transfer up to 5 days ahead. The above methodology is implemented on a case study at a wind farm off the east coast of the UK.     

Time preference and international trade

We first consider a closed model, where households' time discount depends on externality in consumption. We can prove that there is a unique steady state, which is a saddle point. Then we extend the model to a two‐country world, and derive the condition on the effects of consumption externality under which there is a unique free trade steady state with saddle‐point stability.     

基于模糊多属性群决策的维护方式选择研究

维护方式选择是维护管理中的重要工作之一,合理的维护方式既能达到保障设备的稳定运行,又能同时兼顾其它各个方面的要求。由于对维护方式的评价涉及多个部门、人员和属性,有些指标只是一个模糊的概念,因而采用模糊多属性群决策的方法对维护方式进行优先抉择。本文结合A公司的设备维护方式选择问题,尝试使用模糊多属性群决策折衷算法求解最佳的维护方式。     

The legacy of state socialism on attitudes toward immigration

Does the politico–economic system affect preferences for immigration? In this study, I show that individuals exposed to life under state socialism have formed and persistently hold different attitudes toward immigration. By exploiting the division and reunification of Germany, I estimate the influence of state socialism on attitudes toward immigration. Drawing on rich individual panel data, I find that East Germans who lived under state socialism, are 15 percent more likely to oppose immigration than West Germans who spent their entire life in a democratic, capitalist country. This difference in attitudes toward immigration is persistent over time and across space, and largest for cohorts born and raised under state socialism. This gap in attitudes can be traced back to a longer-term deterioration in trust. Evidence from members of a group that opposed the authoritarian system highlights the importance of state socialist ideology for attitude formation.     

闽侯县闲置农地生态安全评价研究

[目的]根据闽侯县农用地闲置情况,结合当地社会经济及生态环境发展情况,深入分析闽侯县闲置农地的生态安全发展水平。[方法]建立闽侯县闲置农地生态安全评价指标体系,分别从农村垃圾处理点数量、财政支农资金、外部进入农村投资、农业生产总值、种粮补贴、自然灾害、农业技术水平、农村生物的多样性程度、农村家庭收入结构、农村生态补偿金额、农地的整理规模及环保支出占GDP比重共确定12个指标进行深入研究,运用普通最小二乘法对设计的多元线性回归模型进行回归,进一步对闽侯县闲置农地的生态安全水平进行评价。[结果]农村垃圾处理点数量、财政支农资金、种粮补贴、环保支出占GDP比重、生态补偿金额、生物多样性程度对闽侯县闲置农地生态安全水平起到促进作用,呈正相关趋势;自然灾害则与闲置农地生态安全水平呈负相关趋势。[结论]整体看来,闽侯县闲置农地的生态安全水平主要受到当地经济、环境及生态基础三大因素的影响。     

Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting

Wind power forecasts with lead times of up to a few hours are essential to the optimal and economical operation of power systems and markets. Vector autoregression (VAR) is a framework that has been shown to be well suited to predicting for several wind farms simultaneously by considering the spatio-temporal dependencies in their time series. Lasso penalisation yields sparse models and can avoid overfitting the large numbers of coefficients in higher dimensional settings. However, estimation in VAR models usually does not account for changes in the spatio-temporal wind power dynamics that are related to factors such as seasons or wind farm setup changes, for example. This paper tackles this problem by proposing a time-adaptive lasso estimator and an efficient coordinate descent algorithm for updating the VAR model parameters recursively online. The approach shows good abilities to track changes in the multivariate time series dynamics on simulated data. Furthermore, in two case studies it shows clearly better predictive performances than the non-adaptive lasso VAR and univariate autoregression.     

Customer Experience in Online Shopping: A Structural Modeling Approach

Online retail's rapid growth in India has triggered both untapped growth opportunities and challenges to maintain consumer “stickiness” to retailer websites. In this context, online customer experience (OCE) has emerged as a strategic differentiator for sustainable competitive edge. However, there is a paucity of empirical research in this field. Therefore, drawing on extant literature and qualitative research of online shoppers, this study proposes an integrated model of OCE with antecedents, components, and outcome variables. Data for this study were collected from Indian online shoppers; the data are empirically tested along with the moderating effect of time availability on OCE. Results of the study largely support the model and contribute to knowledge creation on OCE in the Indian context and to strategy development for online retailers.     

Assessing the Reliability of Self‐reported Income Information in Informal Small Business Lending through a Bogus Pipeline Experiment

Coping with asymmetric information plays a major role in successful small business lending. Our purpose is to determine if small business applicants report their income information correctly when requesting a loan. We use a randomised controlled trial bogus pipeline experiment, established during a typical cash‐flow analysis of a bank for small businesses in the Philippines. The bogus pipeline approach is commonly applied in social science and aims to increase the rate of truth telling by informing participants that answers will be verified by a lie detector. The experimental data, which include 243 observations of credit clients that are mainly from the agricultural and food value chain, served to identify asymmetric information. Additionally, debtors’ repayment behaviour for approved loans was observed by the bank. Our results indicate that loan applicants of the treatment group report lower incomes, an effect which is most pronounced in lower income quantile. Our analyses also reveal higher loan delinquencies in the control group.