Adoption des Politiques de Protection de l'Environnement et performance des Entreprises Camerounaises

The objective of this paper is to evaluate the effect of the environmental protection policies of by Cameroonian firms on their performance. It uses the endogenous switching regression technique and propensity scores applied to micro-data from 639 firms in Cameroon. The results show that only 17% of firms adopt these measures, while on average 85% of firms produce solid, gaseous or liquid waste. The results also indicate that the adoption of these environmental protection policies increases operating costs while significantly improving the turnover and the performance of the productive capacity of the company. These increases are 39.11%, 58.6%, and 38.63% for operating costs, turnover and return on productive capacity of the company, respectively. However, firms can also suffer significant losses resulting from the non-adoption of environmental policies. In fact, firms that do not adopt environmental protection policies have their performance reduced by an average of 1.625 percentage points.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Higher Intensity,Higher Profit? Empirical Evidence from Dairy Farming in New Zealand

Over the last two decades there have been significant and well‐documented changes in the nature and structure of New Zealand dairy production. One particular feature has been a marked shift in the ‘input intensity’ of dairy farming systems through increased use of supplementary feed. These changes have generated debate about the impact of dairy farm intensity on the performance of farm businesses and the competitiveness of the New Zealand dairy sector. Using a novel econometric approach, we assess statistically the impact of three types of dairy farming systems on milk production and financial performance, using farm business data provided by DairyBase^®. Our empirical results show that higher input systems perform significantly better physically than lower input systems, but not financially. The disaggregated analysis suggests that the average treatment effects differ by region and performance quantiles.     

Efficiency,economy and effectiveness—but what about ethics? Supreme audit institutions at a critical juncture

Ethics is increasingly recognized as one of several important dimensions of performance. Yet, performance audit, or value-for-money audit, as conducted by supreme audit institutions (SAIs), does not typically include this dimension. Instead, the focus is on the classical ‘three Es’ (efficiency, economy and effectiveness). The reluctance to address issues of ethical misconduct has taken the audit practice of SAIs to a critical juncture, where the legitimacy of these audits ultimately is at stake. This paper explains why SAIs need to add a fourth ‘E’— ethical audit. Possible implications are discussed.     

我国出境旅游相关研究的特点分析

以SCI来源期刊、核心期刊和CSSCI来源期刊1992年至2016年国内发表的与出境旅游有关的共752篇期刊论文进行综合研究。首先，从时间和空间两个维度分析了我国出境旅游的发展特点，其次，归纳了我国出境旅游主要研究内容的六个方面，即出境旅游者、出境旅游市场、出境旅游消费特点、出境旅游的影响因素、出境旅游的贡献、出境旅游政策。最后，指出了我国出境旅游市场发展中存在的主要问题，提出应关注出境旅游新领域重视微观层面进行精细化研究。     

The major determinants of logistic performance in a global perspective: evidence from panel data analysis

The global logistics industry has grown significantly and logistics has become an important sector of the business economic system and a major global economic activity in recent years. Logistics activities accelerate economic and productivity growth. Efficient logistics is also important to a country’s competitiveness and source of employment. The purpose of this paper is to uncover and understand the major determinants of logistics performance (LP) to further lift the LP of countries. Using unbalanced panel data of 93 selected countries from 2007 to 2014, the present research attempts to critically investigate the major determinants of LP. In estimating the model, this study prefers to use static panel data approach owing to limited data. The findings of the present study reveal that (a) countries with low level of corruption and stable political environment are likely to yield a high level of LP; (b) improvement in resources supply such as infrastructure, technology, labour, and education also have a significant positive effect on LP. Therefore, institutional reforms and upgrading resources will effectively accelerate LP.     

The effect of mandatory CSR disclosure on firm profitability and social externalities: Evidence from China

We examine how mandatory disclosure of corporate social responsibility (CSR) impacts firm performance and social externalities. Our analysis exploits China's 2008 mandate requiring firms to disclose CSR activities, using a difference-in-differences design. Although the mandate does not require firms to spend on CSR, we find that mandatory CSR reporting firms experience a decrease in profitability subsequent to the mandate. In addition, the cities most impacted by the disclosure mandate experience a decrease in their industrial wastewater and SO₂ emission levels. These findings suggest that mandatory CSR disclosure alters firm behavior and generates positive externalities at the expense of shareholders.     

Endogeneity in survey research

Endogeneity is a crucial problem in survey-based empirical research on marketing strategy (MS) and inter-organizational relationships (IORs); if not addressed, it can cause researchers to arrive at flawed conclusions and to offer poor advice to practitioners. Although the field is increasingly cognizant of endogeneity-related issues, many authors fail to properly address it, particularly in survey-based research. Emphasizing the role of essential heterogeneity, this article develops an overarching framework to help improve the understanding of endogeneity problems and how to tackle them when researchers use cross-sectional survey-based data. The authors provide explanations of and advice for how MS and IOR researchers can address six “painful” and sometimes hidden decisions: 1) Do you have an endogeneity problem? 2) What technique/estimator is appropriate? 3) What instrumental variables (IVs) should be chosen? 4) How should IVs be evaluated empirically? 5) How should the results be interpreted and evaluated? and 6) What results should you report? The authors provide a practical flowchart to guide researchers in their efforts to address endogeneity-related concerns.     

基于生态位理论的浙江省区域农产品质量竞争力评价研究

[目的]把握区域农产品质量竞争力不仅是促进区域农产品富有竞争力的积极方法,也是稳步提升农产品质量安全的重要做法。[方法]文章运用生态位态势理论,构建了以区域为评价主体的农产品质量竞争力评价体系,并从两个层面对浙江省各地级市农产品质量竞争力进行研究。在纵向层面上,测算了各地级市农产品质量竞争力生态位宽度,对各地级市农产品质量竞争力状态进行了评价和排序。在横向层面上,测算了各地级市农产品质量竞争力生态位重叠度,对各地级市农产品质量竞争力的合作程度进行了评价与区分。最后整合运用生态位协同、生态位扩充等理论,提出浙江省各地级市提升农产品质量竞争力发展策略。[结果]通过区域农产品质量竞争力生态位宽度研究发现,杭州和宁波的农产品质量竞争力较强,其生态位宽度分别为0.103 6和0.103 2,而丽水和舟山农产品质量竞争力相对居后,其生态位宽度分别为0.079 0和0.075 6;通过区域农产品质量竞争力生态位重叠度研究发现,可将全省划分为西北平原区域、东南部沿海区域和西南部山地区域等3个区域,各区域内部地级市可通过协同合作提升农产品质量竞争力。[结论]根据各地级市生态位宽度和生态位重叠度的差异,应采取生态位扩充、生态位协同、生态位分离的策略,从而因地制宜提升区域农产品质量竞争力。