Permit markets,carbon prices and the creation of innovation clusters

Innovation clusters combining public and private effort to develop breakthrough technologies promise greater technological advances to slow down climate change. We use a multi-country model with an emission trading system to examine whether and how international climate policy can incentivize countries to create such innovation clusters. We find that a minimal carbon price is needed to attract applied research firms, but countries may nevertheless fail to invest in complementary research infrastructure. We construct a mechanism that leads to innovation clusters when emissions targets are set before uncertainty surrounding technological developments is resolved. It is a combination of low permit endowments for the country with the lowest costs to build the needed infrastructure, compensation for this country by profits from permit trade, and maximal possible permit endowments for the remaining countries. We outline how the EU-ETS can be further refined according to this mechanism.     

The impact of research collaboration on academic performance: An empirical analysis for some European countries

The aim of this paper is to investigate the impact of internal and external research collaborations on the scientific performance of academic institutions. The data are derived from the international SCOPUS database. We consider both quantity (the number of publications) and quality indicators (the field-weighted citation impact and the share of publications in the 10% most-cited articles) to evaluate universities' performance in some European countries (Germany, France, Italy, the UK and Russia). To this end, we develop a non-overlapping generations model to evidence the theoretical idea of research externalities between academic institutions. Moreover, we implement an empirical model to determine the extent to which the impact of internal and external collaborations on universities' performance is sensitive to the geographical dimension of the data.     

Is it U.S. GAAP or IFRS? Understanding how R&D costs affect ratio analysis

While financial reporting standards under U.S. GAAP and IFRS are fundamentally similar, differences do exist that may affect our analysis of company financial statements. This is particularly true when comparing a U.S. company following U.S. GAAP to a firm that uses IFRS. To illustrate, we compare research and development (R&D) accounting methods under both sets of standards and illustrate how they affect the analysis of financial results of firms in a specific industry—automotive manufacturers. Our results provide insight into settings in which differences in R&D accounting may have the greatest impact on financial analysis.     

就业结构调整对水库移民土地流转的影响研究*——以南水北调中线工程移民为例

[目的]为促进水库移民的生计恢复及转型,探寻就业结构和土地流转间的交互机制,分析两者间耦合作用对当前移民安置模式及政策的影响。[方法]文章从移民就业结构变迁出发,通过超边际理论构建了安置区移民土地的流转机制模型,推演了从业决策对土地流转行为的影响路径,并运用南水北调农业安置移民数据进行实证检验。[结果]大面积转出土地是移民搬迁后土地处置的主要行为,移民中土地转入户有所增加,但土地集中度却有所减少。移民非农就业较搬迁前有明显上升,并有向当地兼业转移的趋势,但与土地流转间并不互为因果,农村社保还难以弱化其对土地养老的依赖。劳动力数量、非农就业时间、非农收入占比、土地政策等对移民土地流转行为和规模均有显著影响,而外出就业前景和地租水平在促进土地流转行为的同时,却不一定能增加土地流转面积。[结论]移民外迁中可以采用无土安置代替农业安置,推动移民土地流转的关键在于技能培训、政策保障和地租补贴,简单的就业推荐和土地权属划分的作用有限。而对于移民中的农业大户,则需在满足土地转入面积的基础上,保障其在安置区的各项土地权益。     

Researcher perceptions and choices of interview media: the case of accounting research

This study offers foundational insights into the ways in which perceptions of different interview media—principally, face‐to‐face, telephone and videoconferencing channels of communication—may influence researcher choices and practices. Informed by the reflections of 23 senior accounting researchers, our evidence identifies a duality of practices in the usage of different interviewing media, influenced primarily through the role played by experience, which informs perceptions upon which practices are based. We discuss this duality of practices in terms of information richness theory and channel expansion theory and offer further insights into the factors that influence and shape researchers’ perceptions of the contextual suitability of particular media available to interview‐based accounting research.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

Research engagement,impact and sustainable tourism

In this editorial, we reflect on how the Journal of Sustainable Tourism can contribute towards sustainable tourism researchers achieving more impact with their research. We propose some changes that can be tested in, and introduced gradually and collaboratively with, the community of the editorial board and authors. To support impactful mind sets, we will promote research that reflects diverse academic communities. To promote impactful research topics, we will encourage authors to frame their submitted articles against the Sustainable Development Goals, while research that is time sensitive will be fast tracked so it can contribute to current debates. To promote impactful methodologies, we shall favour articles that use mixed methods and action research, and those that conduct longitudinal, experimental, and evaluative research. To promote impactful partnerships, we will favour multidisciplinary approaches and research that has been co-created with stakeholders. To promote impactful communication and dissemination, we will continue to build an online community on social media for sustainable tourism researchers, we will promote articles in social media to raise their visibility, and we will provide free access to those articles that are deemed to have the greatest potential to impact positively on society.     

Beyond the boundaries: Challenges for business,policy and society

This editorial article introduces the papers presented at the ITS Seoul 2018 and seven papers selected for the special issue of ITS Seoul 2018. Specifically, this article provides the results of keyword networks, research agendas and coauthor networks of ITS Seoul 2018. A summary of the seven papers accepted for the special issue of ITS Seoul 2018 is also included. Finally, this article concludes by introducing another paper that empirically explores the value of special issues by analyzing the characteristics of special issues of Telecommunications Policy.     

“引洮工程”引发的受水区污染治理研究

[目的]为了解决甘肃中部安定区、陇西县、渭源县、临洮县、榆中县和会宁县的人畜饮水、工业用水、生态用水及农业灌溉用水问题,引洮工程通过九甸峡水利枢纽抬高水位将黄河上游洮河支流水资源引入受水区。在受水区,在调水增加本区供水总量的同时,相应增加了增量水资源使用后带来的废污水,客观上对污染治理工作水平提出了更高要求,轻视排污问题将加剧受水区乃至下游的水系污染程度,影响受水区经济社会的可持续发展。[方法]文章采用文献研究法从理论上探讨了环境容量、排污权及其关系。采用定额计量法计算了调水带来的COD和氨氮增量。[结果]调水使得受水区COD和氨氮每年分别增加6 914. 30t和1 440. 48t。就COD而言,受水区平均排放量占该区环境容量的51. 12%,似有较多的容量结余,但区内排放极不平衡,榆中和会宁已经超排。就氨氮而言,受水区平均排放量将占该区环境容量的151. 55%,总体超排很严重。区内除临洮以外,其余5县区均超排,其中,榆中和会宁超排1倍以上。[结论]排污量是假定增量污水符合二级排放标准的前提下计算的,如果处理率低、排放达标率低,则超排现象会更为严重。对此,要从宏观上进行综合治理,诸如完善政府、社会与市场共同治污机制、排污权配置的过渡性制度安排、污水处理企业改革及引导受水区进行产业结构调整等。     

Modelling the iron ore price index: A new perspective from a hybrid data reconstructed EEMD-GORU model

As iron ore is the fundamental steel production resource, predicting its price is strategically important for risk management at related enterprises and projects. Based on a signal decomposition technology and an artificial neural network, this paper proposes a hybrid EEMD-GORU model and a novel data reconstruction method to explore the price risk and fluctuation correlations between China’s iron ore futures and spot markets, and to forecast the price index series of China’s and international iron ore spot markets from the futures market. The analysis found that the iron ore futures market in China better reflected the price fluctuations and risk factors in the imported and international iron ore spot markets. However, the forward price in China’s iron ore futures market was unable to adequately reflect the changes in the domestic iron ore market, and was therefore unable to fully disseminate domestic iron ore market information. The proposed model was found to provide better market risk perceptions and predictions through its combinations of the different volatility information in futures and spot markets. The results are valuable references for the early-warning and management of the related enterprise project risks.