巴蜀文化元素视觉符号系统的构建研究

着力于巴蜀文化的显性(物质)层面,筛选出最能代表其特征的文化元素,分析其文化含义,抽绎其典型视觉符号,进而确定其形态、色彩、材质和风格等方面的特征,构建巴蜀文化元素的视觉传达符号系统,为当下四川土特产品包装设计的地域性表达提供可资借鉴的思路。     

In‐House Globalization: The Role of Globally Distributed Design and Product Architecture on Product Development Performance

Changes in the global economy and technological advances are stimulating increased geographic distribution of new product design and development efforts. For large organizations that design and develop complex products, this geographic distribution has added a new layer of complexity to product development operations. In this empirical study of a large auto manufacturer, we examine the operational performance implications of splitting the design of vehicle subsystems across multiple geographic locations. Our results indicate that global distribution diminishes the chance of completing tasks on time and degrades subsystem design quality. Finally, by examining the interplay between subsystem centrality and global distribution, we found that higher centrality in the product architecture amplifies the impact of global distribution on subsystem error rates.     

基于“真实意义”上的英语写作

过程写作法使写作教学关注点从写作成稿上转移到了写作过程上。随着实践和研究的深入,可以看到,在对写作过程关注的同时,更要对写作者加以关注。对于写作者来说,用于写作的意义必须是来自作者内心的真实意图。只有在这种真实意义基础上接触到的写作知识,才有可能转化为写作能力,才能在写作实践中运用得上,使用得好。     

论滇黔桂喀斯特地貌旅游产品的整合及开发

作者分析了滇黔桂喀斯特旅游资源的开发现状及特征 ,提出了滇黔桂喀斯特地貌旅游区这一跨区域旅游产品的整合及开发方向     

信息产品交易和知识产权保护

信息产品进入市场之所以可能出现盗版假冒等免费搭车行为,除了其复制成本低外,还因为其具有公共产品的特征。竞争性的市场机制在处理公共产品方面的困难是显而易见的,需要非市场机制的作用,特别是政府的干预。干预方式有三个方面:1.政府提供信息;2.对私人信息产品的生产提供补贴;3.信息产权的建立和保护。其中知识产权保护制度可以在制度上保障支付了信息成本的获得相应的收益,从制度上推动技术的进步。     

Scalable spatio‐temporal Bayesian analysis of high‐dimensional electroencephalography data

We present a scalable Bayesian modelling approach for identifying brain regions that respond to a certain stimulus and use them to classify subjects. More specifically, we deal with multi‐subject electroencephalography (EEG) data with a binary response distinguishing between alcoholic and control groups. The covariates are matrix‐variate with measurements taken from each subject at different locations across multiple time points. EEG data have a complex structure with both spatial and temporal attributes. We use a divide‐and‐conquer strategy and build separate local models, that is, one model at each time point. We employ Bayesian variable selection approaches using a structured continuous spike‐and‐slab prior to identify the locations that respond to a certain stimulus. We incorporate the spatio‐temporal structure through a Kronecker product of the spatial and temporal correlation matrices. We develop a highly scalable estimation algorithm, using likelihood approximation, to deal with large number of parameters in the model. Variable selection is done via clustering of the locations based on their duration of activation. We use scoring rules to evaluate the prediction performance. Simulation studies demonstrate the efficiency of our scalable algorithm in terms of estimation and fast computation. We present results using our scalable approach on a case study of multi‐subject EEG data.     

Product Reuse in Innovative Industries

Most models of product reuse do not consider the fact that firms might be required to innovate their products over time in order to continue to appeal to the tastes of customers. We consider how the rate of this required innovation, which might be fast or slow depending on the product, affects reuse decisions. We consider two types of reuse—remanufacturing to original specifications, and upgrading used items by replacing components that have experienced innovation since the item was originally produced. We find that optimal reuse decreases with the rate of innovation, implying that models that ignore innovation overestimate the optimal amount of reuse that a company should pursue. Furthermore, we show that reuse can be encouraged in two ways—the intuitive approach of increasing end‐of‐life costs, and the less intuitive approach of raising the cost to make items reusable. We also examine the environmental impact of reuse, measured in terms of virgin material usage, finding that reuse can actually increase total virgin material usage in some cases. In an extension, we show how the results and insights change when the rate of innovation is uncertain.     

Commercialization of Platform Technologies: Launch Timing and Versioning Strategy

Many emerging entrepreneurial applications and services connect two or more groups of users over Internet‐based information technologies. Commercial success of such technology products requires astute business practices related to product line design, price discrimination, and launch timing. We examine these issues for a platform firm that serves two markets—labeled as user and developer markets—such that the size of each market positively impacts participation in the other. In addition, our model allows for sequential unfolding of consumer and developer participation, and for uncertainty regarding developer participation. We demonstrate that product versioning is an especially attractive strategy for platform firms, that is, the trade‐off between market size and margins is tilted in the direction of more versions. However, when expanding the product line carries substantial fixed costs (e.g., marketing cost, cost of additional plant, increased distribution cost), then the uncertainty in developer participation adversely impacts the firm's ability to offer multiple versions. We show that for established firms with lower uncertainty about developer participation, the choice is essentially between an expanded or minimal product line. Startups and firms that are entering a new product category are more likely to benefit from a “wait and see” deferred expansion strategy.     

Multi‐Product Quality Competition: Impact of Resource Constraints

We study a multi‐product firm with limited capacity where the products are vertically (quality) differentiated and the customer base is heterogeneous in their valuation of quality. While the demand structure creates opportunities through proliferation, the firm should avoid cannibalization between its own products. Moreover, the oligopolistic market structure puts competitive pressure and limits the firm's market share. On the other hand, the firm has limited resources that cause a supply‐side fight for adequate and profitable production. We explicitly characterize the conditions where each force dominates. Our focus is on understanding how capacity constraints and competition affect a firm's product‐mix decisions. We find that considering capacity constraints could significantly change traditional insights (that ignore capacity) related to product‐line design and the role of competition therein. In particular, we show that when the resources are limited, the firm should offer only the product that has the highest margin per unit capacity. We find that this product could be the diametrically opposite product suggested by the existing literature. In addition, we show that for intermediate capacity levels, whereas the margin per unit capacity effect dominates in a less competitive market, proliferation and cannibalization effects dominate in a more competitive market.     

Joint Stocking and Product Offer Decisions Under the Multinomial Logit Model

This article studies a joint stocking and product offer problem. We have access to a number of products to satisfy the demand over a finite selling horizon. Given that customers choose among the set of offered products according to the multinomial logit model, we need to decide which sets of products to offer over the selling horizon and how many units of each product to stock so as to maximize the expected profit. We formulate the problem as a nonlinear program, where the decision variables correspond to the stocking quantity for each product and the duration of time that each set of products is offered. This nonlinear program is intractable due to its large number of decision variables and its nonseparable and nonconcave objective function. We use the structure of the multinomial logit model to formulate an equivalent nonlinear program, where the number of decision variables is manageable and the objective function is separable. Exploiting separability, we solve the equivalent nonlinear program through a dynamic program with a two dimensional and continuous state variable. As the solution of the dynamic program requires discretizing the state variable, we study other approximate solution methods. Our equivalent nonlinear program and approximate solution methods yield insights for good offer sets.