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We examine the role of financial and nonfinancial performance measures in managing revenues derived from life cycles of a type of intellectual property products − motion pictures.

Our study focuses on the first two markets in which audiences can watch a motion picture – the upstream theatrical market and the downstream home video market. We combine data collected from numerous public and proprietary sources and form a final sample of 654 motion pictures. Then we perform regression analysis on the data.

First, three measures of a movie’s performance in the theatrical market, opening box office revenue, peak rank, and weeks at the peak rank, have positive effects on subsequent revenues in the home video market. Second, the same set of performance measures also predicts the motion picture’s life span in the theatrical market. Third, when the actual life span of a motion picture in the theatrical market deviates from its predicted value, the total return on investment in the motion picture decreases.

We do not have data on other downstream markets related to motion pictures, such as pay-per-view and online video streaming.

This study suggests that the public and proprietary data can be used to inform managerial decisions regarding intellectual property product life cycles.

This is the first accounting study that directly examines life cycle revenues of intellectual property products. We also extend literature on revenue driver and revenue management research to the product level.

This chapter introduces the argument that pervades the collection that families are in motion both conceptually and in practice. It articulates the motion of family and families, which are made through space and time, and explains the ways in which the book develops current thinking on family. It also situates the concept and practices of family within wider debates and contexts. The chapter then details the contribution of each of the chapters to this argument, which are organised around three thematic parts: moving through separation and connection; uneven motion and resistance; and traces and potentialities. The chapter draws out six conclusions from the chapters in the collection.

This chapter develops Lefebvre’s concept of rhythmanalysis to investigate the ways super-diversity comes to life in the everyday city through the intersection of the spatial and temporal. The chapter explores the multicultural intimacies of streets in a London neighbourhood through a close ethnographic focus on rhythms and atmospheres using slow-motion video. The research contributes to an emerging field of visual ethnographic scholarship by presenting slow-motion video as a method to explore the ‘presence’ (Lefebvre, 2004) of super-diversity and conviviality on the street.

I argue that in slowing down the encounters of the street, slow-motion video shows the often overlooked sensible and affective elements of super-diverse urban space, the mundane interactions between bodies, materials and technologies that create a form of ‘convivial affect’. I argue that these everyday encounters are shaped by a situated politics of difference and yet are also mediated by wider rhythms and atmospheres, contributing to a sense of ‘social time’. I draw attention to both the human and non-human elements of the streets. These material and technological elements can uncover the wider discourses and circulatory regimes of atmospheres in urban super-diverse neighbourhoods, focussing on their relation to broader flows of capital, forms of postcolonial culture and translocality.

This research has implications for how we understand super-diversity and its manifestations in urban space. It encourages policymakers and academics to recognise the affective human and non-human encounters that are a crucial aspect of conviviality, the everyday ways we live together with difference.

SD is defined as a failure to sense correctly the attitude, motion, and/or position of the aircraft with respect to the surface of the earth (Benson, 2003). The types of SD are generally thought to be “unrecognized” and “recognized” (Previc & Ercoline, 2004). Although a third type has been reported (incapacitating), this type seems irrelevant to UAV operations. Unrecognized SD occurs when the person at the controls is unaware that a change in the motion/attitude of the aircraft has taken place. The cause is often the result of a combination of sub-threshold motion and inattention. This type of SD is known to be the single most serious human factors reason for aircraft accidents today, accounting for roughly 90% of all known SD-related mishaps (Davenport, 2000). Recognized SD occurs when a noticeable conflict is created between the actual motion/attitude of the aircraft and any one of the common physiological sensory mechanisms (e.g., visual, vestibular, auditory, and tactile). Recognized SD is the most common type of SD, accounting for the remaining SD-related accidents.

This chapter details a practice-based investigation of a 19th-century astronomical device known as ‘Janssen’s apparatus’. It questions traditional narratives of linear technological advancement and ‘sole inventor’ to reframe the historical artefact as a site which makes visible a network of technological knowledge interconnecting astronomy and visual culture. Approached from this perspective, the Janssen artefact is reframed as an ‘intersite of knowledge’, exploring how the various know-how contained within the device is located across disciplines rather than within a single field. Originally developed to calculate the Astronomical Unit during the 1874 Transit of Venus, Janssen’s apparatus failed in its endeavour as a measuring instrument, but its motion mechanism was successfully adapted into early cinema technologies. This chapter applies praxis through the development of a prototype artwork and the concept of ‘techne’ as speculative means of understanding how this mechanism was transferred from astronomy to the Western cultural realm. It proposes that the development of the apparatus was partially gleaned from moving image techniques already in use within 19th-century visual culture. The development of the prototype artwork is discussed in relation to the specific timing mechanism of the Janssen apparatus and how it establishes its own ‘intersite of knowledge’ relevant to its contemporary context. Finally, this chapter elaborates on how witnessing the Janssen mechanism in motion provided unique insight and how creating a dialogue between historical and contemporary apparatus facilitates a reconsideration of how galleries, libraries, archives, and museums [GLAM] and other host institutions that contain artefacts might share their hidden stories.

The time series of the federal funds rate has recently been extended back to 1928, now including several episodes during which interest rates remained near the lower bound of zero. This series is analyzed, using the method of indirect inference, by applying recent research on bounded time series to estimate a set of bounded parametric diffusion models. This combination uncouples the specification of the bounds from the law of motion. Although Louis Bachelier was the first to use arithmetic Brownian motion to model financial time series, he has often been criticized for this proposal, since the process can take on negative values. Most researchers favor processes such as geometric Brownian motion (GBM), which remains positive. Under this framework, Bachelier's proposal remains valid when specified with bounds and is shown to compare favorably when modeling the federal funds rate.

This chapter presents a novel human arm gesture tracking and recognition technique based on fuzzy logic and nonlinear Kalman filtering with applications in crane guidance. A Kinect visual sensor and a Myo armband sensor are jointly utilised to perform data fusion to provide more accurate and reliable information on Euler angles, angular velocity, linear acceleration and electromyography data in real time. Dynamic equations for arm gesture movement are formulated with Newton–Euler equations based on Denavit–Hartenberg parameters. Nonlinear Kalman filtering techniques, including the extended Kalman filter and the unscented Kalman filter, are applied in order to perform reliable sensor fusion, and their tracking accuracies are compared. A Sugeno-type fuzzy inference system is proposed for arm gesture recognition. Hardware experiments have shown the efficacy of the proposed method for crane guidance applications.

It has long been challenged that the distributions of empirical returns do not follow the log-normal distribution upon which many celebrated results of finance are based including the Black–Scholes Option-Pricing model. Borland (2002) succeeds in obtaining alternate closed form solutions for European options based on Tsallis distribution, which allow for statistical feedback as a model of the underlying stock returns. Motivated by this, we simulate two distinct time series based on initial data from NIFTY daily close values, one based on the Gaussian return distribution and the other on non-Gaussian distribution. Using techniques of non-linear dynamics, we examine the underlying dynamic characteristics of both the simulated time series and compare them with the characteristics of actual data. Our findings give a definite edge to the non-Gaussian model over the Gaussian one.