Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Information and Knowledge as Antecedents of Consumer Attitudes and Intentions to Buy and Recommend Fair-Trade Products

The authors propose and empirically test a causal model to understand how the availability of fair-trade information and consumer knowledge about this issue affect consumers’ attitudes and intentions toward fair-trade products. The model is built upon the attitude-behavior paradigm and the premises of agency theory. It is tested through structural equation modeling with a sample of 292 Spanish consumers. The findings are that consumers do not have good knowledge about fair trade and that this is significantly determined by the lack of information about this in the market. It is also observed that consumers’ perceptions about the availability of fair-trade information have negative effects on their concern about this issue and that such information as is available is not effective in reducing consumer skepticism. The research represents an extension of previous fair-trade literature because the role of information and communication in improving consumer attitudes and buying intentions has rarely been explored in the case of ethical products.     

Application of collective knowledge diffusion in a social network environment

ABSTRACT

We present a group dynamics model that shows knowledge integration as a process occurring over time. As each individual in the group contact others, his own knowledge changes, and over time the collective knowledge is obtained. This allows modeling knowledge diffusion in a social network and while the models presented in this paper are not competitive in that area, they approach the problem from previously unconsidered direction. We test the behavior of the model in a multi-agent simulation and we test a simple advertisement campaign in a social network. We provide discussion of elements needed for making model more competitive.     

Organizational versus Market Knowledge: From Concrete Embodiment to Abstract Representation

Synopsis In contrast to the neoclassical economic presumption in favor of markets, we argue that organizations, not markets should be taken as our default assumption. We do so on information processing grounds. We distinguish between Zen and market Knowledge. The first is embodied and hard to articulate and the second abstract-symbolic. In human evolution, the first type of knowledge came first, and, on any pragmatic definition of knowledge, it still incorporates most of what we mean by the term. We take codification and abstraction as the two data processing activities that lead to the articulation of knowledge into an abstract-symbolic form. We develop a conceptual framework, the Information-Space (I-Space) to show how far the articulation of knowledge leads to its being shared. Whereas an unlimited sharing of information and knowledge leads to market-oriented outcomes, a more limited sharing leads to organizational outcomes. A market-oriented economics has tended to look to physics for its models; the field of organization theory has tended to look to biology. A more organization-oriented economics would thus look more to biology for its models.     

Relative risk aversion, relative prudence and comparative statics under uncertainty: The case of (μ, σ)‐preferences

From the expected‐utility approach, relative risk aversion being smaller than one and relative prudence being smaller than two emerge as preference restrictions that fully determine the optimal responses of decisions under uncertainty to certain shifts in probability distributions. We characterize the magnitudes of relative risk aversion and relative prudence in terms of the two‐parameter, mean‐standard deviation approach. We demonstrate that this characterization is instrumental in obtaining comparative static results in the two‐parameter setting. We further relate our findings to the results in the expected‐utility framework.     

考虑供给与需求波动性的安全库存定量研究

本文以商业企业和MTS模式下生产企业的安全库存为研究对象,将供给与需求的变动程度作为两个动态指标研究四种不同战略与运营环境下的安全库存模型,并进一步分析了降低安全库存所需的管理杠杆.     

关于教育测量的要素分析

教育测量是指对教育现象的测量。教育测量的基本手段是存在失真范围的数量化分析。其数量化的语言是效度、信度等。效度分为效标效度与内容效度等,信度是表明测量可靠性的数量指标。     

企业知识管理绩效综合评价案例研究

知识管理是现代企业管理的重要内容。正确分析和评价企业的知识管理绩效，对于促进企业知识管理、提高企业知识管理水平以及增强企业竞争优势，具有重要的现实意义。文章构建了企业知识管理绩效评价的指标体系，并运用模糊综合评价模型对企业知识管理绩效进行了综合评价。