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This study aims to examine a large, non-disclosed production contract awarded to Lockheed Corp. in the context of a trade-off between a contractually required non-disclosure clause and the need (as a publicly traded firm) to disclose material information to its shareholders. This production contract generated significant cash flows to the firm as evidenced by growth in its earnings. However, the existence of the production contract and its contribution to Lockheed’s earnings, was not disclosed by the firm to shareholders and potential investors while the production contract was being executed.

The authors examine the market reaction to several key contract events which were not disclosed at the time they occurred, in compliance with the contractually required non-disclosure clause.

A statistically significant stock price reaction around the time of the award of this non-public contract, indicative of trading by some capital market participants using non-public information was documented.

Because similar large non-public contracts funded by the government are common in the industrial economy, we conclude by discussing implications for organizational structure, firm’s cost of capital, equity-based compensation and market efficiency.

This paper aims to deal with the human activity recognition using human gait pattern. The paper has considered the experiment results of seven different activities: normal walk, jogging, walking on toe, walking on heel, upstairs, downstairs and sit-ups.

In this current research, the data is collected for different activities using tri-axial inertial measurement unit (IMU) sensor enabled with three-axis accelerometer to capture the spatial data, three-axis gyroscopes to capture the orientation around axis and 3° magnetometer. It was wirelessly connected to the receiver. The IMU sensor is placed at the centre of mass position of each subject. The data is collected for 30 subjects including 11 females and 19 males of different age groups between 10 and 45 years. The captured data is pre-processed using different filters and cubic spline techniques. After processing, the data are labelled into seven activities. For data acquisition, a Python-based GUI has been designed to analyse and display the processed data. The data is further classified using four different deep learning model: deep neural network, bidirectional-long short-term memory (BLSTM), convolution neural network (CNN) and CNN-LSTM. The model classification accuracy of different classifiers is reported to be 58%, 84%, 86% and 90%.

The activities recognition using gait was obtained in an open environment. All data is collected using an IMU sensor enabled with gyroscope, accelerometer and magnetometer in both offline and real-time activity recognition using gait. Both sensors showed their usefulness in empirical capability to capture a precised data during all seven activities. The inverse kinematics algorithm is solved to calculate the joint angle from spatial data for all six joints hip, knee, ankle of left and right leg.

This work helps to recognize the walking activity using gait pattern analysis. Further, it helps to understand the different joint angle patterns during different activities. A system is designed for real-time analysis of human walking activity using gait. A standalone real-time system has been designed and realized for analysis of these seven different activities.

The data is collected through IMU sensors for seven activities with equal timestamp without noise and data loss using wirelessly. The setup is useful for the data collection in an open environment outside the laboratory environment for activity recognition. The paper also presents the analysis of all seven different activity trajectories patterns.

Gated communities, residential enclaves that offer upscale housing and a variety of recreational and communal facilities within a walled area with controlled entrances, are proliferating in many of India's large metropolitan cities. In this paper, we analyze the images of place and identity that are evoked in online advertisements for gated communities in the city of Bangalore in southern India. Since the 1990s, Bangalore has become known as India's premier information technology (IT) hub and a magnet for multinational corporations and high-skill personnel. The latter include Non-Resident Indians (NRIs) who lived and worked abroad for several years and have returned to partake of new opportunities offered in the country. We explore the intersection of notions of identity, home and community in a globalised world through an examination of the graphic and textual images encoded in the advertisements of thirteen prominent developers in Bangalore whose upscale gated developments cater to NRIs. The advertisements depict high-end gated communities as places of luxury, exclusiveness, high security and convenience which also offer a range of recreational facilities for individuals and families. Additionally, those who live in the gated enclaves are portrayed as persons of distinction and class who are global and cosmopolitan in their outlook and identity.

Given that several publicly announced international merger and acquisition deals have been abandoned in recent years, the purpose of this paper is to present a synthesis of influential articles that examine organizational characteristics of cross-border acquisition transactions. The synthesis is framed through general traits and resources, learning and prior acquisition experience, and top-level management and governance attributes. Specifically, the paper conceptualizes key organizational attributes influencing the propensity of cross-border negotiations, and the most common characteristics and post-deal effects by illustrating several case examples from around the world.

Owing to fairness and integrity principles of the literature survey studies, the paper adopts an exploratory review design to present a synthesis of several influential articles published in strategy, international business and corporate finance journals. Since case method and storytelling are the best qualitative approaches to conceptualizing extant theoretical contributions, a number of case examples—successful, delayed and abandoned—from around the world have been discussed by leveraging the case information from archival sources.

Drawing on resource-based view, organizational learning, upper echelons and agency theory perspectives, the paper underscores three observations. First, organizational characteristics such as firm age, firm size, ownership structure, slack resources, marketing resources, technological intensity, export intensity and business group affiliation have different impacts on the propensity of publicly announced cross-border deals. Second, firm’s prior acquisition experience and firm’s acquisition experience in the target country have positive or moderating effects on the success of a cross-border merger. Third, top-level management characteristics such as CEO foreign nationality and CEO international career experience, and governance characteristics such as board size, the number of independent directors and directors with overseas experience, have mixed effects on the incidence of cross-border acquisitions.

The paper puts forth several recommendations for top-level managers participating in cross-border acquisition negotiations, such as learning from peers in the same industry, learning from predecessors in the target country and learning from failure negotiations in the same industry and other industries.

Nested within the organizational, international business strategy and corporate finance literature, the paper presents a synthesis of influential publications that study organizational characteristics affecting the propensity of cross-border acquisitions. The cases discussed in this paper are unique examples from around the world.