Financing energy efficiency retrofits in Chilean households: The role of financial instruments,savings and uncertainty in energy transition

High firewood consumption for heating produces high levels of pollution in cities in central and southern Chile, with serious consequences for health and quality of life. Energy efficiency measures (EEMs) have been identified as the best strategy to reduce air pollution and maximize social benefits. However, their adoption has been slow. The objective of this article is to investigate household preferences for financial incentives needed to promote private investments in EEMs in Central-Southern Chilean households and study the role of energy savings and the uncertainty about potential savings in the investment decision, with the aim of finding solutions to increase the adoption of these technologies. We use a choice experiment to explore the trade-off between the investment costs, financial instruments, energy savings, and the uncertainty about achieving the theoretical savings provided by engineering and architectural models. The results show that financial instruments play the most important role in this decision, followed by the savings achieved by the retrofit. Householders prefer to finance their investments with a mix of their personal resources and medium-term credits, trying to avoid long-term commitments. Although uncertainty was found to be a significant variable, it seems to play a small role in the investment decision.     

东部地区十省市规模以上工业企业研发投入绩效评价

选取2021年度数据，采用数据包络分析（DEA）方法对中国东部地区10个省份规模以上工业企业的研发投入绩效进行评价，并采用灰关联分析方法分析确定各项研发投入产出指标相对于DEA效率的灰色关联度。研究结果表明，80%的省份规上工业企业研发投入产出处于非DEA有效状态，存在不同程度的投入冗余或产出不足；规上工业企业发明专利申请数与研发投入产出效率的关联度最高，其次是新产品销售收入和R&D经费内部支出。     

Post-script—Retail forecasting: Research and practice

This note updates the 2019 review article “Retail forecasting: Research and practice” in the context of the COVID-19 pandemic and the substantial new research on machine-learning algorithms, when applied to retail. It offers new conclusions and challenges for both research and practice in retail demand forecasting.     

Green consumption behavior prediction based on fan-shaped search mechanism fruit fly algorithm optimized neural network

Predicting consumption behavior is very important for adjusting supplier production plans and enterprise marketing activities. Conventional statistical methods are unable to accurately predict green consumption behavior because it is characterized by multivariate nonlinear interactions. The paper proposes an optimized fruit fly algorithm (FOA) and extreme learning machine (ELM) model for consumption behavior prediction. First, to address the problem of uneven search direction of FOA leading to insufficient search ability and low efficiency, the paper proposes a sector search mechanism instead of a random search mechanism to improve the global search ability and convergence speed of FOA. Second, to address the issue that the initial weights and hidden layer bias values of the ELM are randomly generated, which affects the learning efficiency and generalization of the ELM, the paper uses an improved FOA to optimize the weights and bias values of ELM for improving the prediction accuracy. Taking the green vegetable consumption behavior of Beijing residents as an example, the results show the optimization of the initial weight and threshold of ELM by the GA, PSO, FOA, and SFOA, the prediction accuracy of the GA-ELM, PSO-ELM, FOA-ELM, and SFOA-ELM models all surpass those of ELM. Compared with BPNN, GRNN, ELM, GA-ELM, PSO-ELM, and FOA-ELM models, the RMSE value of SFOA-ELM was decreased by 9.45%, 8.40%, 11.89%, 5.84%, 2.22%, and 2.69%, respectively. These findings demonstrate the effectiveness of the SFOA-ELM model in green consumption behavior prediction and provide new ideas for the accurate prediction of consumption behaviors of other green products with similar characteristics.     

游客感知视角下乡村旅游质效提升维度研究——以西双版纳傣族园为例

发展乡村旅游是实施乡村振兴战略的重要途径，对促进乡村经济发展具有重要作用。以西双版纳傣族园为案例研究地，通过SPSS和AMOS实证探究游客感知视角下乡村旅游质效提升的维度。结果表明：游客感知视角下的乡村旅游质效提升包含旅游地感知、地方认同感、主观幸福感、环境责任行为4个维度；地方认同感和旅游地感知对乡村旅游质效提升的影响力较强，其次是主观幸福感和环境责任行为。     

Exploring the multi-dimensionality of authenticity in dining experiences using online reviews

The quest for authenticity in dining experiences has become increasingly important. This paper explores authenticity dimensions that are of value to customers in dining experiences, and by that gains a multi-dimensional understanding of authenticity in this context. Following an integrated learning approach using text mining and classification techniques, this paper explores and confirms different dimensions of authenticity by identifying and classifying authenticity judgements in online restaurant reviews. The results suggest that authenticity is a multi-dimensional concept encompassing Authenticity of the Other, Authenticity of the Producer, and Authenticity of the Self as first-level dimensions. Additionally, besides historical and categorical authenticity which have been previously explored in the literature, a new type of authenticity - Deviated Authenticity - emerged as a second-level dimension falling under Authenticity of the Other. This paper enhances existing conceptualisations of authenticity and establishes avenues for exploring the multi-dimensionality of other consumer research concepts using user-generated content.     

IFRS adoption and stock misvaluation: Implication to Korea discount

Analyzing publicly traded stocks in Korea surrounding IFRS adoption in 2011, we find that the gap between stock price and firm value, value-to-price (V/P) ratio, narrows following the IFRS adoption and that this narrowed gap is observed only for higher V/P firms. We further find that the return predictability of V/P decreases in the post-IFRS period. Using a path analysis, we report further evidence that mandatory IFRS adoption decreases idiosyncratic volatility and improves trading volume and market liquidity, thereby contributing to the narrowed gap between value and price. We conclude that IFRS adoption contributes to resolution of Korea discount.     

Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic

Since the level of markets’ information efficiency is key to profiteering by strategic players, Shocks; such as the COVID-19 pandemic, can play a role in the nature of markets’ information efficiency. The martingale difference and conditional heteroscedasticity tests are used to evaluate the Adaptive form of market efficiency for four (4) major stock market indexes in the top four affected economies during the COVID-19 pandemic (USA, Brazil, India, and Russia). Generally, based on the martingale difference spectral test, there is no evidence of a substantial change in the levels of market efficiency for the US and Brazilian stock markets in the short, medium, and long term. However, in the long term, the Indian stock markets became more information inefficient after the coronavirus outbreak while the Russian stock markets become more information efficient. Intuitively, these affect the forecastability and predictability of these markets’ prices and/or returns. Thereby, informing the strategic and trading actions of stock investors (including arbitrageurs) towards profit optimization, portfolio asset selection, portfolio asset adjustment, etc. Similar policy implications are further discussed.     

中部六省碳排放效率与产业结构优化的耦合协调度及影响因素分析

采用SBM-Undesirable模型测算了1999—2017年中部六省的碳排放效率,分别计算了产业结构合理化指数和高级化指数,利用耦合协调模型考察了碳排放效率与产业结构优化的耦合协调度,并对其影响因素进行了实证分析。结果表明:中部六省碳排放效率和产业结构合理化的耦合协调度较低,处在中度失调和中度协调之间,碳排放效率和产业结构高级化的耦合协调度处在中度失调和中度协调之间,但有明显上升的趋势。人力资本、财政支出对中部六省碳排放效率和产业结构合理化的协调发展起到了促进作用,而环境规制、能源结构产生了抑制的作用。人力资本对碳排放效率和产业结构高级化的耦合协调度有正向作用,而外商投资、人均资本、制度质量和能源结构产生了抑制作用。