Defining inventory control points in multiproduct stochastic pull systems

Multistage pull production systems have been widely implemented in recent years and constitute a significant aspect of lean manufacturing. One of the important considerations in such systems is identifying the control points, i.e. where in the multistage sequence to locate the output buffers. Allowable container/batch sizes, optimal inventory levels, and ability of systems to automatically adjust to stochastic demand depend on the location of these control points yet the issue of optimal location has not been widely addressed. This paper considers a multiproduct pull setting where part types compete with each other for common production resources. In this environment it is important to consider factors such as lead time variability and to include the corresponding queuing aspects into the model. Each workstation is modeled as a GI/G/1 queue. Waiting times spent by parts at workstations are approximated using a decomposition/recomposition algorithm. Necessary and sufficient conditions are provided for the optimality of a single control point. Conditions under which multiple control points are optimal are investigated along with the impact of product mix and utilization parameters on the number of control points. Analytical model results are validated by simulation.     

Does complexity deter customer‐focus?

Economic models suggest that firms use a simple cost‐benefit calculation to evaluate customer requests for new product features, but an extensive organizational literature shows the decision to implement innovation is more nuanced. We address this theoretical tension by studying how firms respond to customer requests for incremental product innovations, and how these responses change when the requested innovation is complex. Using large sample empirical analyses combined with detailed qualitative data drawn from interviews, we find considerable variance in the relationship between customer demands, complexity, and investments in incremental innovations. The qualitative study revealed the importance of organization structures, competitive pressures, and incentives for resource allocation processes. Copyright © 2011 John Wiley & Sons, Ltd.     

Heterogeneous Beliefs,IPO Valuation,and the Economic Role of the Underwriter in IPOs

We empirically analyze the economic role of the underwriter in initial public offerings (IPOs), distinguishing between the “certification” and “market power” hypotheses. We find that equity in high‐reputation underwriter backed IPOs is priced higher and further away from intrinsic value than that in low‐reputation underwriter backed IPOs. Our results are robust to controlling for the endogenous selection of firms to take public by underwriters. Overall, our results support the market power hypothesis and reject the certification hypothesis, indicating that the role of underwriters is to obtain the highest possible valuation for the IPOs that they back rather than to price the equity close to intrinsic value.     

Understanding spread in the electronic futures markets: financial crisis perspective

This article analyses bid–ask spreads in U.S. electronic futures markets around the recent financial crisis. We decompose the bid–ask spread into three components – order processing, inventory holding and adverse selection costs – and show that adverse selection costs increased the most during the crisis while order processing costs are the largest cost component. Volume significantly affects inventory holding and order processing costs, whereas volatility only influences inventory holding costs. The crisis period had a significant effect on these relations. This study extends the existing literature on liquidity in equity to futures markets.     

Where do capabilities come from and how do they matter? A study in the software services industry

Recent years have witnessed a surge of interest in the notion of capabilities as an important source of competitive advantage. This recognition has, in turn, placed emphasis on the question of where and how these capabilities emerge and how they influence firm performance. The present paper is an attempt to address this question. Using a large sample of detailed project‐level data from a leading firm in the global software services industry, we attempt to empirically study the importance of capabilities. We find that two broad classes of capabilities are significant. The first class, which we label client‐specific capabilities, is a function of repeated interactions with clients over time and across different projects. This learning from repeated interactions with a given client reduces project execution costs and helps improve project contribution. The second class, termed project management capabilities, is acquired through deliberate and persistent investments in infrastructure and systems to improve the firm's software development process. Our empirical results suggest that the marginal returns to acquiring different capabilities may be different and an understanding of such trade‐offs can improve firm decisions to improve and/or acquire such capabilities. We discuss the key contributions of our paper and the implications for future research on capabilities. Copyright © 2004 John Wiley & Sons, Ltd.     

Top finance journals: Do they add value?

This paper develops a methodology for determining the value added by journals to articles they publish and uses this methodology to study five leading finance journals in the period 1990 through 2002. The quality of an article is disaggregated into two components—a component inherent to the article and a component added by the journal. Inherent article quality is proxied by author reputation and the reputation of the author's school, while journal value added is proxied by editorial board quality, journal age, and journal readership characteristics. Our Tobit regression analysis results show that theJournal of Finance, theJournal of Financial Economics, and theReview of Financial Studies add significant value over and above inherent article quality.     

Random parameters and self-selection models

Most empirical work employs models with fixed parameters. In contrast, I discuss the specification of self-selection models with random parameters. I demonstrate that in a self-selection model, mis-specification of the parameter structure as constant causes biased estimates, especially of the selectivity effect. I estimate a self-selection model of moonlighting with random parameters and find that the selectivity effect, which was almost absent in the constant parameter version of the model, is indeed significant.     

The new meaning of quality in the information age

Software applications are now a mission-critical source of competitive advantage for most companies. They are also a source of great risk, as the Y2K bug has made clear. Yet many line managers still haven't confronted software issues--partly because they aren't sure how best to define the quality of the applications in their IT infrastructures. Some companies such as Wal-Mart and the Gap have successfully integrated the software in their networks, but most have accumulated an unwidely number of incompatible applications--all designed to perform the same tasks. The authors provide a framework for measuring the performance of software in a company's IT portfolio. Quality traditionally has been measured according to a product's ability to meet certain specifications; other views of quality have emerged that measure a product's adaptability to customers' needs and a product's ability to encourage innovation. To judge software quality properly, argue the authors, managers must measure applications against all three approaches. Understanding the domain of a software application is an important part of that process. The domain is the body of knowledge about a user's needs and expectations for a product. Software domains change frequently based on how a consumer chooses to use, for example, Microsoft Word or a spreadsheet application. The domain can also be influenced by general changes in technology, such as the development of a new software platform. Thus, applications can't be judged only according to whether they conform to specifications. The authors discuss how to identify domain characteristics and software risks and suggest ways to reduce the variability of software domains.     

Financial Distress Costs and Delayed Calls of Convertible Bonds: An Empirical Analysis

Theoretical analysis implies that optimal call policy would be to call the bonds as soon as the conversion value equals the call price. Empirical studies, however, report that firms appear to systematically delay the call and the difference between the conversion value and the call price is large at the time of the call. This study examines convertible bond calls between 1977 and 1993, with a view to explain the large difference between the conversion value and the call-price at the time of the call. A large majority of the firms calling the bonds have cash-flow incentive to call the bonds in that the after-tax interest payments are higher than the dividends on the converted shares. The large difference between the conversion value and the call price is positively related to the risk characteristics of the firm. Evidence seems to support the view that risk aversion and fear of potential financial distress may explain the large difference at the time of call between the conversion value and the call price.