Are You a Chocolate Lover? An Investigation of the Repurchase Behavior of Chocolate Consumers

This study aimed to understand the factors affecting repurchase behavior of chocolate brands and, consequently, customer retention and acquisition. The study adopted a qualitative, inductive approach using in-depth interviews with 31 Australian consumers. The factors identified in the extant literature as antecedents of customers’ repurchase intention in the chocolate industry, including brand recognition, sales promotion, product price value, variety, taste, texture, size, packaging, and customer satisfaction, were confirmed. The results also indicated that functional value, product selection value, self-gratification value, socialization value, and transactional value were also considered during the consumer decision-making process. Implications for practitioners are provided.     

A proposed configurable approach for recommendation systems via data mining techniques

This study presents a configurable approach for recommendations which determines the suitable recommendation method for each field based on the characteristics of its data, the method includes determining the suitable technique for selecting a representative sample of the provided data. Then selecting the suitable feature weighting measure to provide a correct weight for each feature based on its effect on the recommendations. Finally, selecting the suitable algorithm to provide the required recommendations. The proposed configurable approach could be applied on different domains. The experiments have revealed that the approach is able to provide recommendations with only 0.89 error rate percentage.     

Revealed preferences of individual players in sequential games

This paper studies rational choice behavior of a player in sequential games of perfect and complete information without an assumption that the other players who join the same games are rational. The model of individually rational choice is defined through a decomposition of the behavioral norm assumed in the subgame perfect equilibria, and we propose a set of axioms on collective choice behavior that characterize the individual rationality obtained as such. As the choice of subgame perfect equilibrium paths is a special case where all players involved in the choice environment are each individually rational, the paper offers testable characterizations of both individual rationality and collective rationality in sequential games.     

妇女家庭地位与代际人力资本投资

代际人力资本投资是经济增长的重要源泉。但实证显示，相较于男性而言女性更愿意将家庭资源配置在子女教育上。通过构建人力资本代际传递模型，从劳动生产率折旧率的角度解释女性对子代人力资本投资的偏好，并利用2014年中国家庭追踪调查数据、工具变量两阶段实证发现劳动生产率折旧率更高的女性当其家庭决策地位提升时，该家庭的代际人力资本投资比重将显著增加，且存在城乡差异。但是，不论城乡，男孩因未来劳动生产率更高而获得更多的人力资本投资，这表明针对妇女开展扶贫项目，提高妇女在家庭中的地位将更加有助于增加子代人力资本投资。     

社会互动对规模养殖户环保饲料支付意愿的影响研究*——基于改进的目标导向理论模型分析框架

［目的］通过引入社会互动变量改进目标导向行为理论框架，探讨生猪规模养殖户对环保饲料的支付意愿及其影响因素，为完善畜禽养殖污染防治政策提供参考借鉴。［方法］以湖北省生猪规模养殖户为研究对象，应用Heckman两阶段模型，研究规模养殖户对环保饲料的支付意愿。［结果］大多数规模养殖户（8134%）愿意采用环保饲料，且平均意愿支付水平为每头生猪饲料成本的669%（4680元/头）。社会互动中的干群互动、同行互动均能显著提升规模养殖户对环保饲料的支付意愿，但同时同行互动不利于其意愿支付水平的提升。进一步的异质性分析表明，在环保饲料支付意愿决策上，社会互动较少的规模养殖户更容易受到制度规范的约束，而社会互动较多的规模养殖户则更易受到感知养殖热情的影响。［结论］政府部门应加大生态环保宣传力度，并借助多种方式推动规模养殖户进行社会互动； 同时可依据社会互动程度的不同，分别制定相应措施以促进规模养殖户对环保饲料支付意愿的提升。     

Financing the sustainable management of Rwanda's protected areas

Rwanda's Nyungwe National Park is a biodiversity hotspot with the most endemic species in the ecoregion and the highest number of threatened species internationally. Nyungwe supplies critical ecosystem services to the Rwandan population including water provisioning and tourism services. Tourism in the Park has strong potential for financing enhanced visitor experiences and the sustainable management of the Park. This paper explores quantitatively the economic impacts of adjustment in Park visitation fees and tourism demand as a source of revenues to improve Park tourism opportunities and ongoing operations and maintenance. The methods developed in this paper are novel in integrating the results of stated preference techniques with a regional computable general equilibrium modelling approach to capture multisectoral, direct, indirect and induced impacts. Such methods have strong potential for assessing revenue generation alternatives in other contexts where park managers are faced with the need to generate additional revenue for sustainable park management while facing diminishing budget allocations. Results of this analysis demonstrate that adjustment of Park fees has a relatively small impact on the regional economy and well-being when compared with a strategy aimed at generating increased tourism demand through investment in improving the visitor experience at Nyungwe National Park.     

Policy lessons from spatiotemporal enrollment patterns of payment for ecosystem service programs in Argentina

Payment for ecosystem services schemes (PES) are lauded as a market-based solution to curtail deforestation and restore degraded ecosystems. However, PES programs often fail to conserve sites under strong long-term deforestation pressures. Underperformance, in part, is likely due to adverse selection. Spatial adverse selection occurs when landowners are more likely to enroll parcels with low deforestation pressure than parcels with high deforestation pressure. Temporal adverse selection arises when parcels are enrolled for short time periods. In both cases, financial resources are allocated without having a sizeable impact on long-term land use change. Improving program performance to overcome these shortcomings requires understanding attributes of landowners and their parcels across large scales to identify spatial and temporal enrollment patterns that drive adverse selection. In this paper, we examine these patterns in Argentina’s PES program in Chaco forest, a global deforestation hotspot. Our study area covers 252,319 km². Results from multinomial logistic regression models showed that large parcels of enrolled land and parcels owned by absentee landowners exhibit greater evidence of spatiotemporal adverse selection than smaller parcels or parcels owned by local landowners. Furthermore, parcels managed under land use plans for conservation and restoration are more likely to be associated with adverse selection than parcels managed for financial returns such as harvest of non-timber forest products, silviculture, and silvopasture. However, prior to recommending that PES programs focus on land uses with higher potential earnings, a greater understanding is needed of the degree to which these land uses meet ecological and biodiversity goals of PES programs. We suggest that increased spatial targeting of enrollment, along with enrollment of local landowners and further incentives for land uses that support conservation and restoration, could promote long-term conservation of forest lands.     

Accounting for diverse risk attitudes in measures of risk perceptions: A case study of climate change risk for small-scale citrus farmers in Indonesia

Climate change is likely to generate severe impacts on smallholder farmers in developing countries. As key drivers of adaptation, climate risk perceptions are highly heterogeneous, varying both across people and context, and are complex, being defined as behaviour which varies across both impact and likelihood dimensions in non-linear ways. Yet most studies examining risk perceptions are unable to disentangle the role of perceptions regarding impacts from those regarding the likelihood of climate-related events taking place. This paper presents a decomposition and associated analysis of survey-based ‘risk perception’ measures. The decomposition we apply allows independent accounting for perceptions over frequencies and impacts linking to behavioural patterns of risk attitude. The approach presented here draws on a detailed 2017 survey of 500 farmers in rural Indonesia to generate insights into the relationship between risk perceptions and extension services, accessibility of information, and other factors. Results show that risk perceptions are generated from complex interaction between perceived future frequencies and outcomes of climate events and indicate differential impacts of extension services across these perceptions. This paper also presents empirical support for the use of information and communication technology based extension as an efficient extension tool to reach more farmers than in traditional methods.     

The trade-offs between economic efficiency and job creation in olive grove smallholdings

Cooperation among farmers is an effective alternative to reduce production costs in smallholdings of traditional olive groves and increase their low profitability. However, an increase in efficiency reduces working hours and the labour required for the management of farms. This fact can lead to negative effects in rural areas, especially considering the importance of the social aspect of the crop. Therefore, to contribute to the global discussion on the transition towards more sustainable farming, it is important to know, ex ante, what level of employment is generated by olive groves and what could be lost under more competitive and efficient scenarios. The purpose of the work is to quantify the expected impact on employment by the implementation of cooperative management methods in order to generate true and accurate information that can be used in the design of future policies that aim to increase the economic profitability of small olive farms. The results make clear that this way of managing farms, by increasing the efficiency of agricultural work, has a significant negative impact on employment. However, this management formula does encourage the professionalisation of the sector by generating quality employment, in addition to contributing to the preservation of small farms and the socio-cultural and territorial benefits they generate.     

An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.