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51.
52.
关于“数据权益的刑法保护”问题,在理论层面上,可从“刑法解释论”和“刑法立法论”两种路径进行探讨。“刑法解释论”探讨路径以现行《刑法》罪名体系为出发点,主要任务是揭示哪些罪名的犯罪构成之设置是以“数据权益”为规范保护目的;“刑法立法论”探讨路径是在刑法立法层面上探讨立法者为在刑法政策上实现数据权益的刑法保护这一目的,动用刑罚禁止何种行为类型才具正当性的问题。然而,两种探讨路径都将依赖于“数据权益”的内涵确定以及法益格的认定问题,换言之,是刑法法益理论在数据权益刑法保护问题上的具体运用。《民法典》第127条并非是关于数据的确权性规定,且在民法理论界关于数据权益的法律属性存在诸多争议的状况下,“数据权益”内涵不明、法律属性不清导致其并不具备作为刑法保护客体的“法益”格。当前刑法理论界存在的关于“数据权益”的刑法类法益保护模式探讨路径,是对刑法法益保护方式的误读,并未触及“数据权益刑法保护”之规范层面问题的实质。“数据安全”法益观的探讨路径则不仅混淆了现象层面与规范层面上的“数据犯罪”概念的界分,也由于没有论证“数据安全”如何能够构成刑法的保护法益,而导致结论过于武断。在理论探讨上,应该明确作为行为客体的物理层面上的“数据”概念与作为保护客体的法益层面上的“数据权益”概念之间的区别,据此明确“数据权益的刑法保护”在规范层面上是否构成新问题。 相似文献
53.
《International Journal of Forecasting》2022,38(1):240-252
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. 相似文献
54.
Retailing strategy is one of the most crucial factors for industries. A proper retailing strategy can help to enhance consumer service and increase the industry's profit. An improved approach to retailing is suggested in this research to deliver superior customer service while maximizing profits in a dynamic system. The study analyzes a retailing strategy for a demand with cross-price elasticity upon the retail price. A product's cross-price elasticity and the system reliability are critical factors in retailing. Understanding the cross-price elasticity of demand between products helps retailers to make pricing decisions that maximize profits by maintaining demand. Imperfect products are produced due to an imperfect production system. The imperfect ones must be adjusted with some costs to make them perfect for better retailing. The system failure rate is crucial for retailing under cross-price elasticity of demand patterns. Production system reliability, cross-price elasticity of demand, and consumer service are all essential factors that can impact a company's success in the market. The production rate is considered time- and system failure rate-dependent. Contradictory to the literature, a dynamical system is proposed for improved retail management, which is solved using the Euler-Lagrange theory. Finally, one can achieve the expected maximum profit for this retail system with optimum selling prices for different products by reducing the system failure rate. Some numerical illustrations with graphical representations are provided to validate the current study. Numerical examples show that applying cross-price elasticity of demand for more than two identical products provides 35% more profit for the retail industry than a single type of product. 相似文献
55.
《International Journal of Research in Marketing》2022,39(2):522-540
Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain. 相似文献
56.
以277家中小板和创业板上市公司2012-2017年平衡面板数据为样本,利用泊松模型,实证分析知识型员工冗余与企业二元创新的关系,并探讨外部环境特征(要素市场发育程度和市场不确定性)的调节机理。研究表明:企业应保持一定的知识型员工冗余,促进企业二元式创新,过多或过少的知识型员工冗余均不利于企业开展创新活动;不同的环境特征对二者间关系的调节作用存在异质性,要素市场发育程度会减弱知识型员工冗余与探索式创新、利用式创新间关系,而市场不确定性会加强知识型员工冗余与探索式创新、利用式创新间关系。 相似文献
57.
在全面实施创新驱动发展战略的时代背景下,揭示中国高端装备制造业自主技术创新效率稳定性,测度相关因素的影响强度与方向,对揭示中国高端装备制造业自主技术创新规律,制定其发展策略具有重要指导意义。聚焦中国高端装备制造业自主技术创新效率稳定性及影响因素,采用DEA-Malmquist指数方法和Tobit回归模型进行实证研究,结果表明,中国高端装备制造业自主技术创新效率存在一定波动性,且各细分行业技术创新效率内部稳定性较差,产业自主技术创新效率整体稳定性不高;自主技术创新投入因素和环境影响因素对产业自主技术创新效率的影响具有较高的异质性,其中创新资金投入和人力资源投入对自主技术创新综合效率、纯技术效率及规模效率具有正向影响,而新产品开发投入和企业规模对自主技术创新综合效率、纯技术效率和规模效率的影响具有异质性,政策因素与市场因素分别具有显著和非显著负向影响,外源性创新因素具有显著正向影响,且影响强度较大。在此基础上,提出调整政府对高端装备制造业创新支持模式、加强外源性创新与智力引进等策略建议。 相似文献
58.
《International Journal of Forecasting》2022,38(4):1546-1554
The M5 competition uncertainty track aims for probabilistic forecasting of sales of thousands of Walmart retail goods. We show that the M5 competition data face strong overdispersion and sporadic demand, especially zero demand. We discuss modeling issues concerning adequate probabilistic forecasting of such count data processes. Unfortunately, the majority of popular prediction methods used in the M5 competition (e.g. lightgbm and xgboost GBMs) fail to address the data characteristics, due to the considered objective functions. Distributional forecasting provides a suitable modeling approach to overcome those problems. The GAMLSS framework allows for flexible probabilistic forecasting using low-dimensional distributions. We illustrate how the GAMLSS approach can be applied to M5 competition data by modeling the location and scale parameters of various distributions, e.g. the negative binomial distribution. Finally, we discuss software packages for distributional modeling and their drawbacks, like the R package gamlss with its package extensions, and (deep) distributional forecasting libraries such as TensorFlow Probability. 相似文献
59.
[Objective] This study aims to investigate how place attachment and the quality of experience affect consumers' intention to repurchase Geographical Indication (GI) agricultural products. [Methodology] Based on the special functional value and symbolic meaning of GI agricultural products, we constructed a five-dimensional model of place attachment for GI agricultural products consumers. Expanding on the original two-dimensional place attachment model, we introduced three connection concepts: nature, society, and emotion. We also combined this model with the quality of experience model and consumer purchase intention model to form a research model of repurchase intention for GI agricultural products. A questionnaire survey was used to collect data (n = 340), and a partial least squares structural equation model was used to test the empirical evidence. [Research results] (1) Place attachment to Geographical Indication agricultural products significantly affects the quality of experience. (2) Quality of experience significantly affects consumer trust and repurchase intention. (3) Consumer trust significantly affects repurchase intention. (4) There is a mediating effect of experience quality between place attachment and repurchase intention; there is a mediating effect of trust in the relationship between quality of experience and repurchase intention. (5) There is a chain mediating effect of “place attachment→quality of experience→consumer trust→repurchase intention” in the model. 相似文献
60.
《Food Policy》2019
In recent years, labor-intensive agricultural products from developing countries have exhibited inferior performance in international trade due to quality and safety incidents, among which pesticide residue is a major issue. Aiming to improve food quality and safety in the context of cooperatives, we introduced three categories of control measures: outcome control, process control and social control. Based on the Pre-Harvest Interval Standard (PHIS), we selected three indices, farmers’ implementation rate of PHIS, absolute distance to PHIS and relative distance to PHIS, to evaluate appropriateness of pesticides use, reduction of pesticide residue and safety improvements of agricultural products. By using random sampling survey data, we empirically analyzed the marginal effects of control measures and their combinations on food quality and safety standards. The empirical results show that implementing process control, namely, unified production standards or supply of unified agricultural inputs, can comprehensively improve farmers’ implementation rate of PHIS, absolute distance and relative distance to PHIS respectively by 34.9%, 3.2 days and 46.0% on average. While the effects of outcome control (safety inspection) and social control (bonus-penalty incentive or training) are restricted to other measures. Therefore, we suggest cooperatives should take farmers’ features, implementation conditions and the effects of control measures into consideration in order to make a sustainable management plan for improving food quality and safety and enhancing competitiveness in international markets. 相似文献