A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a production possibility frontier with a model of technical inefficiency. The model addresses both spatial dependence and heteroskedastic technical inefficiency. This study applies maximum likelihood methods considering the endogenous spatial lag term. The proposed model nests several existing models. Further, an empirical analysis using data on the Japanese manufacturing industry is conducted and the existing models are tested against the proposed model, which is found to be statistically supported. The findings suggest that estimates in the existing spatial and non-spatial models may exhibit bias because of lack of determinants of technical inefficiency, as well as a spatial lag. This bias also affects the technical efficiency score and its ranking.     

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.     

Determination of derived importance of a tourism destination: A comparison of indirect methods

Two types of attribute importance, stated and derived, have been studied in marketing and tourism studies using Importance-Performance Analysis (IPA). Derived importance is thought to have an advantage over stated importance in reducing survey fatigue and social desirability biases, and thus is more predictable to an outcome variable. Derived importance is also used in a Relevance-Determinance Analysis to determine higher-impact core attributes or in an Importance Grid Analysis to explore the asymmetric relationship between attributes and overall satisfaction. Since derived importance is usually estimated through statistical methods, it is necessary to determine which method is the most appropriate. However, few studies have examined the appropriateness of indirect methods. To fill this research void, this paper judges the appropriateness of three statistical methods (i.e. multiple regression, partial correlation, and simple regression) based on data collected from Savannah, GA, using a new approach by which results of derived importance were compared against diagnostic attributes in the “keep up the good work” quadrant of IPA. Diagnostic attributes are attributes with higher stated importance and higher predictability of an outcome variable. Results show that urban forests and cultural heritage are such attributes, and simple regression is the best to infer attribute importance.     

Identifying Worldviews on Corporate Sustainability: A Content Analysis of Corporate Sustainability Reports

Companies commonly issue sustainability or corporate social responsibility (CSR) reports. This study seeks to understand worldviews of corporate sustainability, or the corporate message conveyed regarding what sustainability or CSR is and how to enact it. Content analysis of corporate sustainability reports is used to position each company report within stages of corporate sustainability. Results reveal that there are multiple coexisting worldviews of corporate sustainability, but the most dominant worldview is focused on the business case for sustainability, a position anchored in the weak sustainability paradigm. We contend that the business case and weak sustainability advanced in corporate sustainability reports and by the Global Reporting Initiative are poor representations of sustainability. Ecological embeddedness, or a locally responsive strategy that is sensitive to local ecosystems, may hold the key to improved ecological sensemaking, which in turn could lead to more mature levels of corporate sustainability worldviews that support strong sustainability and are rooted in environmental science. This must be supported by government regulation. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

Capital market integration in ASEAN: A non-stationary panel data analysis

Motivated by the establishment of ASEAN Economic Community (AEC) at the end of 2015, we examine saving-investment relationship in various subgroups of ASEAN to assess their capital market integration. The results from second generation panel unit-root and cointegration tests that account for cross-sectional dependence as well as estimates of long-run saving-retention rate provide some evidence of market integration in ASEAN. The analysis of short-run dynamics suggests that capital mobility in ASEAN during 1980–2014 appears similar to that in OECD countries during 1970–1999. More importantly, across different panel estimators and subgroups of membership, there is considerable heterogeneity among the member countries. The saving-investment association is very weak, thereby implying very high capital mobility, in more developed members such as Singapore, Malaysia, and Brunei; the association is very strong, implying very low capital mobility, for much less developed members such as Laos, Myanmar, and Cambodia. The results call for renewed effort to develop capital markets in less developed nations and integrate them with the rest of the membership in ASEAN. In this paper, we also address several major shortcomings of the original Feldstein-Horioka framework.     

Chinese banking reforms in perspective: towards global alignment or national specificity?

The reforms of the banking sector in China conducted so far have been seeking to accomplish, simultaneously, two conflicting goals. On the one hand, the objective was to prepare Chinese banks for international competition and put them at the pace with the transformations observed in its overall economy. On the other, there is a social-driven agenda concerning employment and regional inequalities. Using principal component analysis, this article explores the impact of the ongoing reforms in the Chinese banking sector on the performance of individual banks. The results show that despite identical regulation, business practices can be dissimilar at the individual level. Taken collectively, the results also show the increasing influence of Western management standards in the Chinese banking sector.     

生态旅游视域下的岷江上游贫困山区生态安全评价

[目的]构建科学合理的评价指标体系,准确评价生态旅游影响下的区域生态安全状况,是推动少数民族山区实现旅游资源环境与区域社会、经济协同发展的前提和基础。[方法]以岷江上游贫困山区为例,应用灰色系统理论与熵值赋权法相结合,基于压力—状态—响应模型,构建生态旅游视域下的区域生态安全评估指标体系,并将评估指数与经济收入状况及贫困人口分布进行空间耦合。[结果](1)区域当前处于较安全水平,生态旅游开发适度;(2)综合评估指数与城镇居民可支配收入增长率、旅游收入对国民经济增长的贡献率呈正相关,且城镇居民在旅游开发中受益与机会较农牧民多;(3)综合评估指数与贫困人口比重呈负相关,与农牧民纯收入增长率没有必然联系。[结论]区域脱贫能够改善当地的生态安全状况,适度生态旅游开发是区域脱贫的有效手段,但应注重扶持农牧民在旅游业中的参与度,增加其旅游收益。     

水源地突发水污染政府应急预留水量需求预测

近年来,随着工业化和产业化的快速发展,水源地突发水污染事件频发。为应对紧急情况下的水资源非常规需求,保障经济社会稳定发展,政府需要安排一部分应急预留水量。如何合理预测政府应急预留水量的规模是一个值得探讨的课题。提出了一种基于案例推理技术的政府应急预留水量需求预测方法,具体思路是:借助于案例库,利用主成分分析法从众多影响水源地突发水污染事件的因素中提取出两两不相关的因子,以此作为案例的特征属性,基于加权曼哈顿距离测算相似度,依此得到匹配案例,进而测算政府应急预留水量。以太湖流域常州地区水源地为例,进行政府预留水量需求量的预测与分析。该方法可以为政府应急预留水量的配置、储备等提供相关理论知识。     

Secrets to design an effective message on Facebook: an application to a touristic destination based on big data analysis

The objective of this research is to identify which are the key variables for designing a message in a social network that can be used by an advertiser to generate Positive/Negative Engagement. The message’s design variables have been classified into four main groups: (i) Message Tools (presence of text, images, video, labels, applications, interactive games and events calendar or others), (ii) Appropriate Message Structure (length and intelligibility), (iii) Informative Cues (links to the brand, orientation towards the product or the brand, topics relevant to the audience, and a remuneration’s promise) and (iv) Persuasive and Emotional Cues (emotional signals, valence, endorsement and influencer mentions). The focus has been a tourist destination: Brand Spain that is advertised through Facebook. A content analysis was carried out and regression analysis with optimal scaling was used on 180 Spain brand’s publications; 57,626 audience reactions to such publications; and 1361 audience comments on the Brand Spain Official Fan Page. According to our results, from the four blocks of predictive variables, only two of them are useful to predict Positive/Negative Engagement: (i) the use of Message Tools (videos), and (ii) the use of informative cues (relevant topics, links on posts, and post’s orientation towards product).     

Evolution of FDI flows in the global network: 2003–2012

As one type of international capital flow, FDI maintains its important role in globalization. This article attempts to investigate the evolution of the FDI flows from a network perspective. Based on the bilateral FDI flows data between countries from 2003 to 2012, we construct the global FDI flows network for each year and thus quantify network measures (such as flow volumes and connections); further by analysing the tendency and changes of these network measures during the past 10 years, we delineate the features and dynamics of the FDI flows in the global network. We have the following findings: (a) the flows network changes during and after the crisis, i.e. flow volume fallen down and recovered, and flow connection restructured with more diversity; (b) the global FDI flows network is getting more loosely connected; (c) individual countries vary in different patterns.