Acquisition and Disclosure of Operational Information*

We study a firm's strategy for acquisition and disclosure of operational information by establishing linkages among information quality, managerial self‐interest, and production planning. We develop a multistage model in which a manager of a publicly traded firm first receives private information about the product demand and then uses it to make production and disclosure decisions. We consider two prevalent disclosure models employed in the accounting literature: all‐or‐nothing and cheap‐talk models. In the all‐or‐nothing model, it is assumed that any disclosure must be truthful, but the manager can strategically withhold information. We show that the manager commits to acquire the value‐added operational information if (i) the managerial self‐interest in the interim share price is low or (ii) the managerial self‐interest in the interim share price is high, but the fixed disclosure cost is either sufficiently low or sufficiently high. We demonstrate that the firm is better off if the production level is observable to the financial market because multidimensional signaling reduces costs. In the cheap‐talk model, we assume that the manager's disclosure may not be truthful. We show that the manager's incentive to acquire value‐added operational information increases along with the penalty cost for misleading investors. Therefore, a high penalty cost for misleading investors can encourage the manager to obtain more precise information, which in turn improves the firm's cash flow.     

Information Aggregation in Dynamic Markets With Strategic Traders

This paper studies information aggregation in dynamic markets with a finite number of partially informed strategic traders. It shows that, for a broad class of securities, information in such markets always gets aggregated. Trading takes place in a bounded time interval, and in every equilibrium, as time approaches the end of the interval, the market price of a “separable” security converges in probability to its expected value conditional on the traders' pooled information. If the security is “non‐separable,” then there exists a common prior over the states of the world and an equilibrium such that information does not get aggregated. The class of separable securities includes, among others, Arrow–Debreu securities, whose value is 1 in one state of the world and 0 in all others, and “additive” securities, whose value can be interpreted as the sum of traders' signals.     

An investigation of the attention effects of venture capitalist backing on entrepreneurial firms

In this paper, we predict that venture capital (VC) backed initial public offerings (IPOs) will attract more attention than non-VC-backed IPOs, as VCs offer important signals to investors searching for information about entrepreneurial firms. We use a measure developed by Google (i.e., Trends) to capture the spikes in investors' attention experienced by firms in the time period surrounding their IPOs. Our results demonstrate that firms backed by VCs enjoy a far greater spike in attention than their counterparts. Furthermore, we find that firms with more prominent VCs, a larger number of VCs, and VCs situated at farther geographic distances exhibit significantly greater spikes in investors’ attention during the week of their IPO. Combined, the findings show a clear demarcation between entrepreneurial firms with or without VC backing, they bring to the fore new upshots stemming from the relationship between VCs and entrepreneurial firms, and they raise new potential questions on this relationship and beyond.     

Consolidation and fragmentation in environmental scanning: A review and research agenda

Environmental scanning is a broadly defined concept, having first received attention from scholars in the late 1960s. Over the years a number of similar and overlapping constructs have emerged in management literature. The aim of this study, via a systematic review and thematic analysis of relevant empirical research, is to consolidate foundation environmental scanning knowledge, demonstrate how scanning research has developed and fragmented over time, and propose an agenda for future research. The first contribution of our review is a new typology of environmental scanning research made up of five discrete research views, which provides a more comprehensive and contemporary overview of the field than previous studies. The second is a proposed agenda for future research that explicitly acknowledges the role of technology, an area that is presently underdeveloped in foundation scanning literature. The third contribution is to signpost future directions for research on scanning and organisational performance using a number of theoretical perspectives. The overall outcome of our review is to move scanning research on from increasingly incremental contributions concerned with context to a place where the changing role of technology and the mechanisms through which environmental scanning contributes to competitive advantage can be more thoroughly understood.     

实报还是谎报——双边信息激励与供应链效率

探讨了双边不对称信息下供应链信息真实分享和谎报对效率的影响。首先,给出完全信息下的最优商品交易量和供应链利润作为比较基准。其次,构建双方信息真实分享的激励模型。研究发现激励双方信息真实共享所需的信息租金降低交易量和供应链利润。再次,构建允许信息谎报的交易量谈判模型。研究发现,供销双方都偏好高报自己的信息类型。个体谎报信息的幅度随着谈判力增加而减小。拥有绝对谈判力的一方不会谎报信息。供应链效率与谎报信息的幅度、成本上界以及销售价格相关。最后,通过数值算例对实报信息和谎报信息下交易量、供应链个体利润及效率进行对比分析。研究结果为管理实践提供一定的洞见:供应链企业是否激励双边信息分享可根据双方成本大小进行选择。     

青岛一套表的实践与经验

 企业统计一套表一直是统计制度方法改革和实践中的焦点问题。本文通过对青岛市统计局企业一套表制度实施情况的案例分析,系统界定了企业一套表的概念和内涵,全面展现了企业一套表的运作过程,客观分析了制约企业一套表实施的主要原因,并提出了在现阶段实施企业统计一套表的条件和要求。     

The Pacific Rim Library: A Surprising Pearl

The Pacific Rim Library (PRL) is an initiative of the Pacific Rim Digital Library Association (PRDLA). The project began in 2006 using the OAI-PMH paradigm and now holds over 300,000 records harvested from OAI data provider libraries around the Pacific. PRL's goal is to enable the sharing of digital collections amongst PRDLA members and the world, but greater unexpected benefits have been discovered. Through mirroring their metadata, PRL increases the chance that their data will be discovered in Google and other general search engines. With its many disparate collections, PRL is not a repository for traditional information discovery and retrieval. Initially users will bounce from a Google hit to the PRL metadata record in Hong Kong and then begin an intensive search on the original site which hosts the full digital object, in Vancouver, Honolulu, Wuhan, Singapore, or other PRDLA member location.     

Optimal Information Processing and Bayes's Theorem

In this article statistical inference is viewed as information processing involving input information and output information. After introducing information measures for the input and output information, an information criterion functional is formulated and optimized to obtain an optimal information processing rule (IPR). For the particular information measures and criterion functional adopted, it is shown that Bayes's theorem is the optimal IPR. This optimal IPR is shown to be 100% efficient in the sense that its use leads to the output information being exactly equal to the given input information. Also, the analysis links Bayes's theorem to maximum-entropy considerations.     

Optimal Designs for Binary Logistic Regression with a Qualitative Classifier with Independent Levels

Dose response studies arise in many medical applications. Often, such studies are considered within the framework of binary-response experiments such as success-failure. In such cases, popular choices for modeling the probability of response are logistic or probit models. Design optimality has been well studied for the logistic model with a continuous covariate. A natural extension of the logistic model is to consider the presence of a qualitative classifier. In this work, we explore D-, A-, and E-optimal designs in a two-parameter, binary logistic regression model after introducing a binary, qualitative classifier with independent levels.     

A Variable Selection Method for Analyzing Supersaturated Designs

Supersaturated designs are a large class of factorial designs which can be used for screening out the important factors from a large set of potentially active variables. The huge advantage of these designs is that they reduce the experimental cost drastically, but their critical disadvantage is the confounding involved in the statistical analysis. In this article, we propose a method for analyzing data using several types of supersaturated designs. Modifications of widely used information criteria are given and applied to the variable selection procedure for the identification of the active factors. The effectiveness of the proposed method is depicted via simulated experiments and comparisons.