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This chapter examines key drivers of variation in adaptive capacity of project network organizations (PNOs). PNOs are defined as strategically coordinated sets of longer-term, yet project-based relationships, which provide for both stability and change in volatile project businesses. While prior research has emphasized the adaptive role of flexible structures and agency, the author focuses on the role of project variety and contextual embedding and disembedding in building adaptive capacity. Comparing two PNOs in TV movie production, the author argues that differences in adaptive capacity are a function of inter-context connectivity, that is, the level of task and team linkages among diverse project contexts, and the degree to which network ties and relational practices have “dual quality” in being valuable both within and beyond specific project contexts. Findings have important implications for project, network, and organization research.

When first asked to write a chapter on “Corporate Networks,” I was flummoxed by the Stanford focus. Unlike many of the other theories in this volume, where a game of word association by theory results in a roster of current or emeritus Stanford faculty members, corporate network has roots in many institutions. Indeed, institutions such as University of Chicago or Stonybrook may make a claim for being at the forefront of research on corporate networks, and University of Michigan is the current home to three of the top researchers in the area. Yet, among the core network researchers, a good number of them either spent their early faculty years at Stanford (e.g., Pam Haunschild, Don Palmer, Joel Podolny) or completed doctoral training at Stanford (e.g., Jerry Davis, Henrich Greve, Toby Stuart, Christine Beckman). And this list does not include those that came to Stanford later in their careers (e.g., Mark Granovetter and Woody Powell). Furthermore, the history of corporate network research is intertwined with many of the theories developed at Stanford during the late 1970s. To understand this influence, I begin with a brief but broad history of research on corporate networks, a history that begins somewhat earlier than 1970 and continues to the present. Then I turn to the question of Stanford's role in supporting this research stream and intellectual life more broadly.

Intraday volatility characteristics throughout the trading week are examined at the emerging Borsa Istanbul (BIST) stock exchange. Using five-minute (and 15-minute) intervals, accentuated intraday volatility patterns at the microstructure level are examined during the stock market open and close in the morning and in the afternoon sessions. Volatility is highest when markets open in the morning. The second highest is during the afternoon open. The third highest is before the market closes for the day. Volatility before the market close has increased in recent years. These characteristics are seen every trading day. There are also differences: Monday returns are lowest, Friday returns are highest, and Monday morning volatility is highest of the entire trading week. Day-of-the-week and intraday accentuated volatility smile anomalies are jointly investigated using the longest intraday sample period in the emerging country stock exchange literature. Investment companies and professionals can utilize the results for risk management and hedging by avoiding highly volatile opening and closing periods. Arbitrageurs, speculators, and risk takers should trade during these highly volatile periods. Heightened volatility is increased difficulty in price discovery, thus inefficiency. Market participants, exchanges, and public prefer efficient markets. The research presents evidence of trading days, and periods during the trading day, when the exchange becomes more efficient. This is the first research that explores day-of-the-week effect from intraday volatility perspective in an emerging market, and provides useful recommendations in designing risk management strategies at market microstructure level.

Microstructure noise contaminates high-frequency estimates of asset price volatility. Recent work has determined a preferred sampling frequency under the assumption that the properties of noise are constant. Given the sampling frequency, the high-frequency observations are given equal weight. While convenient, constant weights are not necessarily efficient. We use the Kalman filter to derive more efficient weights, for any given sampling frequency. We demonstrate the efficacy of the procedure through an extensive simulation exercise, showing that our filter compares favorably to more traditional methods.

Certain elements of Hayek’s work are prominent precursors to the modern field of complex adaptive systems, including his ideas on spontaneous order, his focus on market processes, his contrast between designing and gardening, and his own framing of complex systems. Conceptually, he was well ahead of his time, prescient in his formulation of novel ways to think about economies and societies. Technically, the fact that he did not mathematically formalize most of the notions he developed makes his insights hard to incorporate unambiguously into models. However, because so much of his work is divorced from the simplistic models proffered by early mathematical economics, it stands as fertile ground for complex systems researchers today. I suggest that Austrian economists can create a progressive research program by building models of these Hayekian ideas, and thereby gain traction within the economics profession. Instead of mathematical models the suite of techniques and tools known as agent-based computing seems particularly well-suited to addressing traditional Austrian topics like money, business cycles, coordination, market processes, and so on, while staying faithful to the methodological individualism and bottom-up perspective that underpin the entire school of thought.

The purpose of this paper is to provide an extensive review of the monetary model of exchange rate determination which is the main theoretical framework on analyzing exchange rate behavior over the last 40 years. Furthermore, we test the flexible price monetarist variant and the sticky price Keynesian variant of the monetary model. We conduct our analysis employing a sample of 14 advanced economies using annual data spanning the period 1880–2012.

The theoretical background of the paper relies on the monetary model to the exchange rate determination. We provide a thorough econometric analysis using a battery of unit root and cointegration testing techniques. We test the price-flexible monetarist version and the sticky-price version of the model using annual data from 1880 to 2012 for a group of industrialized countries.

We provide strong evidence of the existence of a nonlinear relationship between exchange rates and fundamentals. Therefore, we model the time-varying nature of this relationship by allowing for Markov regime switches for the exchange rate regimes. Modeling exchange rates within this context can be motivated by the fact that the change in regime should be considered as a random event and not predictable. These results show that linearity is rejected in favor of an MS-VECM specification which forms statistically an adequate representation of the data. Two regimes are implied by the model; the one of the estimated regimes describes the monetary model whereas the other matches in most cases the constant coefficient model with wrong signs. Furthermore it is shown that depending on the nominal exchange rate regime in operation, the adjustment to the long run implied by the monetary model of the exchange rate determination came either from the exchange rate or from the monetary fundamentals. Moreover, based on a Regime Classification Measure, we showed that our chosen Markov-switching specification performed well in distinguishing between the two regimes for all cases. Finally, it is shown that fundamentals are not only significant within each regime but are also significant for the switches between the two regimes.

The results are of interest to practitioners and policy makers since understanding the evolution and determination of exchange rates is of crucial importance. Furthermore, our results are linked to forecasting performance of exchange rate models.

The present analysis extends previous analyses on exchange rate determination and it provides further support in favor of the monetary model as a long-run framework to understand the evolution of exchange rates.

We extend Diamond's (1989, 1991) life-cycle hypothesis to posit that, once they reach the stage of bank borrowing, firms begin with prime loans and evolve toward borrowing more cheaply at LIBOR as they grow larger, less risky and less characterized by asymmetric information. We conduct multinomial logit regressions to explain firms’ membership in one of three groups: prime only, prime and LIBOR, and LIBOR. We also examine spreads over prime and LIBOR and find that loans set up to allow borrowing at prime carry higher spreads than those allowing borrowing at LIBOR. Both sets of tests support the life-cycle hypothesis.

One area in which strategy and organizational ecology converge is organizational change. This essay weaves together salient themes in my (and my co-authors’) various writings on organizational change, and is anchored in the research literature of the last twenty years. Among other ideas developed here, I point out that there is now a convergence of agendas in strategy and ecology, with an important role being played by intraorganizational ecology. I develop the distinction between strong and weak selection approaches to organizational ecology. While the strong selection view does not find empirical support, there is stronger support for the weak selection view. I lay out some key features of an emerging evolutionary synthesis for the study of strategy and organization, and develop an evolutionary approach to organizational change.