A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition

This work presents key insights on the model development strategies used in our cross-learning-based retail demand forecast framework. The proposed framework outperforms state-of-the-art univariate models in the time series forecasting literature. It has achieved 17th position in the accuracy track of the M5 forecasting competition, which is among the top 1% of solutions.     

Verification results for age-structured models of economic–epidemics dynamics

In this paper we propose a macro-dynamic age-structured set-up for the analysis of epidemics/economic dynamics in continuous time.The resulting optimal control problem is reformulated in an infinite dimensional Hilbert space framework where we perform the basic steps of dynamic programming approach.Our main result is a verification theorem which allows to guess the feedback form of optimal strategies. This will be a departure point to discuss the behavior of the models of the family we introduce and their policy implications.     

Large agricultural investments in Kenya’s Nanyuki Area: Inventory and analysis of business models

Many experts agree that more agricultural investment is needed in the global South to improve local food security and reduce poverty. However, there is a lack of consensus about the types of investment needed to achieve these goals. This paper contributes to the literature on large agricultural investments and corresponding business models by inventorying and analysing such investments in Kenya’s Nanyuki area. We identify four clusters of business models that differ primarily by type of production and other distinct determinants, namely: demand from markets; access to land; land tenure regime and colonial history; actors involved; biophysical context; labour availability; and governance of the value chain via private standards. The study results shed light on the factors that help or hinder implementation of large agricultural investments and shape their impacts in the context of African land use systems. The way land is accessed represents one of the most-decisive factors determining the risks and opportunities associated with such projects. We find that most investments in the Nanyuki area occur on land bought or leased from private owners.     

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.     

Circular business model implementation: A capability development case study from the manufacturing industry

Circular business models (CBMs) have huge potential to deliver economic, social, and environmental benefits, but CBMs have yet to be implemented widely in industrial settings. One reason is that they are often presented as one-size-fits-all solutions, but this is misplaced because product-specific criteria and company capabilities determine the correct choice and implementation of CBMs. Therefore, the purpose of this paper is to investigate how CBM selection and capability development facilitates the implementation of CBMs. For this purpose, we have adopted a qualitative research approach and undertaken 25 explorative interviews in three large Swedish manufacturing companies. In this paper, a CBM implementation framework consisting of two parts has been developed. The first part addresses the choice of the appropriate CBM based on tactical configurations. The second part provides a capability development path by explicating underlying routines that need to be progressively developed in order to move smoothly to more advanced CBMs.     

Forecasting upon a star: Forecasting or wishful thinking?

The purpose of this paper was to perform a detailed analysis of the challenges faced while developing and using econometric models to forecast future transportation demand. To this end, a comparative analysis of the state of practice and state of the art was undertaken on a concrete example – Viracopos Airport in Brazil. A review of relevant technical and scientific literature identified a number of approaches and each representative example was synthesized into a specification “template”. We then compared the performance of each “template” with the observed demand, through an intra-series forecast. A general finding was that econometric model specifications proved to be somewhat homogenous and simpler in nature, with results indicating a relatively small difference in fit and forecast capability across models. Even with the elimination of what is typically considered the main culprit for deviations – the forecast uncertainty of the explanatory (input) variables – the forecast is still subject to sizeable deviation. To address this issue, we proposed developing some sanity check indexes, particularly relevant for long-term forecasts. We conclude that the challenges faced at the Viracopos Airport Concession were far from econometric ones, that the success of the demand forecast and the concession itself required more than a well estimated econometric model. Finally, regarding investment obligations within the concession agreement, we strongly recommend making them conditional to meeting demand milestones, given the inherent unpredictability in forecasts.     

Analysis of Bitcoin prices using market and sentiment variables

This paper proposes an empirical model for analysing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010–17 and 2010–19. Price discovery is achieved through the Gonzalo–Granger permanent‐transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period, a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalised by individuals' search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018–19 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.     

我国绿色创新研究的知识图谱可视化分析

低碳经济背景下,绿色创新作为缓解经济增长过程中资源环境约束问题的重要举措,受到学术界广泛关注。以中国知网收录的绿色创新核心文献为样本,综合运用CiteSpace、SATI、Excel等计量可视化工具绘制知识图谱,对国内绿色创新研究领域的文献年代分布、发文作者、科研机构、关键词以及突现词等进行分析。分析结果表明:我国绿色创新研究大致经历了三个阶段,分别是探索期(1994—2009年)、初步发展期(2010—2015年)、繁荣期(2016—2019年);研究热点主要集中在基础理论与相关概念研究、影响因素与激励机制研究、效率测度与评价体系构建研究三个层面;未来的研究趋势则是朝着绿色金融、环境规制、绿色创新效率、绿色全要素生产率等方向发展。通过对现有文献进行梳理、总结,揭示当前研究进展及演变趋势,为后续开展相关研究提供参考。     

Designing a Model for Competitiveness Measurement of Selected Tourism Destinations of Iran (The Model and Rankings)

Destination competitiveness is the ability to sustain or improve market position and market share of a destination over a period of time. Different markets have different expectations which increase the importance of features a destination should provide in order to achieve competitive advantage. The results of this study show that the domestic model of Iran’s destinations competitiveness comprises 9 major indices. These indices are made of 64 variables which have been derived from literature reviews and qualitative surveys. The results of running the model for all selected destinations are consistent with the destinations’ tourist statistics except for one destination (Qom).