“中国丹霞”福建泰宁世界自然遗产地社区居民点发展模式评价模型研究

为科学优选自然保护地社区居民点发展模式，构建客观评价模型对社区居民点发展模式进行定量评价显得尤为重要。基于“中国丹霞”福建泰宁世界自然遗产地9个社区居民点的调研数据，采用序关系分析法，以居民点人口结构、居民点景观风貌与传统文化、居民点产业发展模式，以及居民点位于遗产地的位置4个一级指标和相应二级指标为评价准则，构建该遗产地社区居民点发展模式优劣评价模型。研究表明，该遗产地9个社区居民点发展模式中，4个为疏解型，3个为搬迁型，2个为控制型，没有发展型。研究结果可为该遗产地社区居民点科学遴选发展模式提供定量评价依据，也可为生态价值高的自然保护地社区居民点发展模式的遴选提供参考。     

家庭生命周期对农户土地规模经营的影响分析——基于福建农村的调查数据

基于福建农村的调查数据资料,从家庭生命周期这一全新的角度出发,运用有序Prob-it模型就家庭生命周期对农户土地规模经营的影响进行实证分析,结果显示:家庭生命周期对农户土地规模经营具有显著的影响,并且在家庭生命周期的不同阶段,各类家庭土地规模经营的意愿强度不同。总体而言,成长中的核心家庭土地规模经营的意愿要强于其他类型家庭,扩大家庭的土地规模经营意愿最弱。     

Entrepreneurial innovativeness and growth ambitions in thick vs. thin regional innovation systems

Research in economic geography has paid increasing attention to regional innovation systems (RISs) as a potential vehicle for growth and development. Yet despite an increasing amount of research studying RISs in particular and economic regions in general, we have limited knowledge about their influence on entrepreneurs and entrepreneurship. We respond to this knowledge gap and study if entrepreneurs’ localization in thick vs. thin RISs affects their innovativeness and growth ambitions. Thick RISs are predominately urbanized spaces that include organizations of higher-level education, R&D intensive milieus, and an ample industry sector, while thin RISs to a lesser degree encompass these features. Empirically, we analyse 870–917 entrepreneurial firms in Agder of Southern Norway. Based on trade and labour markets, as defined by the EU’s classification of local administrative units (LAU1), we identify two thick and six thin RISs in Agder. Econometric analyses show that entrepreneurs located in thick RISs are more innovative than entrepreneurs located in thin RISs, but there are no significant differences concerning entrepreneurs’ growth ambitions. In light of our findings, we discuss the potential agency role played by entrepreneurial firms at a micro level on path dependent features of RISs at a macro level.     

乡村旅游低碳化发展影响因素分析——基于北京市300户乡村旅游经营者的调查

本研究构建了乡村旅游经营者实施旅游低碳化发展决策的理论模型,并通过对北京市10个郊区县乡村旅游经营者的实地调研数据,采用有序logistic模型,探析了乡村旅游低碳化发展的影响因素。研究认为,经营者的受教育水平、家庭收入水平等个体因素,其对乡村旅游前景预期和乡村旅游低碳化发展对经济可持续发展的影响等经营信息诉求动机因素,以及大众媒体、政府渠道、企业宣传推广和亲朋好友等传播渠道因素,显著影响经营者实施低碳乡村旅游的意愿。     

Selection of influential variables in ordinal data with preponderance of zeros

Presence of excess zero in ordinal data is pervasive in areas like medical and social sciences. Unfortunately, analysis of such kind of data has so far hardly been looked into, perhaps for the reason that the underlying model that fits such data, is not a generalized linear model. Obviously some methodological developments and intensive computations are required. The current investigation is concerned with the selection of variables in such models. In many occasions where the number of predictors is quite large and some of them are not useful, the maximum likelihood approach is not the automatic choice. As, apart from the messy calculations involved, this approach fails to provide efficient estimates of the underlying parameters. The proposed penalized approach includes ?₁ penalty (LASSO) and the mixture of ?₁ and ?₂ penalties (elastic net). We propose a coordinate descent algorithm to fit a wide class of ordinal regression models and select useful variables appearing in both the ordinal regression and the logistic regression based mixing component. A rigorous discussion on the selection of predictors has been made through a simulation study. The proposed method is illustrated by analyzing the severity of driver injury from Michigan upper peninsula road accidents.     

A categorical modeling approach to analyzing new product adoption and usage in the context of the building-materials industry

A high proportion of non-adopters is prevalent in any market where the product under consideration is relatively new or has a low acceptance rate. This results in a low proportion of adopters in a representative sample. In adoption or product usage modeling such high proportion of zeros in the dependent variable may be addressed by zero-inflated models, by modeling the product adoption and usage as a function of two latent processes. This paper considers a zero-inflated ordinal-probit model for investigating adoption and usage of innovative wall-cavity insulation materials among residential homebuilders in the US. This study assumes a three-step adoption process of innovative housing materials, namely, trial adoption, intermediate adoption and complete adoption. The study uses 5757 responses from a combined ‘Annual Builder Practices Survey’ dataset comprising ten cross-sectional yearly surveys, undertaken by the NAHB Research Center, from 1996 to 2005. The research results indicate that though a higher proportion of large firms are more likely to adopt innovative insulation material, they continue using established products while slowly increasing their use of the innovative material over time. However, when smaller homebuilders adopt an innovative insulation material, it replaces the existing product from their material usage portfolio at a faster rate.     

天津设施蔬菜种植户的生产决策行为及其影响因素分析

[目的]目前我国蔬菜已经超过粮食总产值,成为我国第一大农产品。蔬菜产业对促进农民增收,提高国民生活质量具有重要的战略意义。天津把"减粮增菜"作为"十三五"现代都市农业发展的重要目标之一,这一目标实现的关键是设施蔬菜种植户的经营决策行为。通过对天津32个村的223户设施蔬菜种植户的实地调研,掌握了天津设施蔬菜经营现状。[方法]构建了农户生产经营决策的评价指标体系,运用有序Logistic回归模型,分析蔬菜种植户的经营决策行为,并得出各影响因素的重要程度。[结果]农户年龄、生产年限、技术培训和政府的农业规划对农户设施生产决策行为具有显著性影响,而其他因素均不显著。[结论]文章得出政府应在农业技术培训、新型农业经营主体培育、财政支农政策、蔬菜产业发展规划等方面加大投入力度,以期推进设施蔬菜的规模化、科技化和专业化,从而促进农民增收、农业增效。     

新疆棉农对农业面源污染防治的态度和支付意愿研究

农业面源污染问题已经成为我国面临的最严重的环境污染问题之一,农户对农业面源污染防治的态度和支付意愿研究,对于政府制定相关政策措施意义重大。分别采用李克特五点量表、条件价值评估法、多元有序Logistic模型回归等方法对(1)棉农对农业面源污染防治的态度,(2)棉农对农业面源污染防治的支付意愿(WTP),(3)影响棉农支付意愿的社会经济因素进行研究。结果表明:新疆棉农对农业面源污染防治的态度非常积极,但是当与自身利益相冲突时,则趋向于以牺牲环境为代价;新疆每户棉农对农业面源污染防治的支付意愿是113.96元/年,49.64%的被调查者选择的支付区间是[12,60)元/年,累计百分比占70.65%;农户的教育水平和是否参加过农业专业合作组织是新疆农户农业面源污染防治支付意愿的主要影响因素。基于此,得出结论并提出相应的对策建议。     

Estimating Mann–Whitney‐type Causal Effects

Mann–Whitney‐type causal effects are generally applicable to outcome variables with a natural ordering, have been recommended for clinical trials because of their clinical relevance and interpretability and are particularly useful in analysing an ordinal composite outcome that combines an original primary outcome with death and possibly treatment discontinuation. In this article, we consider robust and efficient estimation of such causal effects in observational studies and clinical trials. For observational studies, we propose and compare several estimators: regression estimators based on an outcome regression (OR) model or a generalised probabilistic index (GPI) model, an inverse probability weighted estimator based on a propensity score model and two doubly robust (DR), locally efficient estimators. One of the DR estimators involves a propensity score model and an OR model, is consistent and asymptotically normal under the union of the two models and attains the semiparametric information bound when both models are correct. The other DR estimator has the same properties with the OR model replaced by a GPI model. For clinical trials, we extend an existing augmented estimator based on a GPI model and propose a new one based on an OR model. The methods are evaluated and compared in simulation experiments and applied to a clinical trial in cardiology and an observational study in obstetrics.