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In acquisitions of technology-based firms the focus is typically on the technology and the target firm's engineers and scientists. But a firm is a social entity with a range of important internal and external relationships that are essential to the exploitation of existing capabilities, and the development of new ones. These relationships need to be maintained, subsequent to acquisition, to preserve the target firm's ability to innovate and compete. I argue for the importance of the target firm's relationships with its customers, and show that the degree to which the acquisition creates or destroys value for the target firm's customers is a significant predictor of acquisition success.

In this paper, the knowledge-based view of the firm is applied to theoretically elucidate and empirically examine the influence of target industry growth on premium payments in cross-border acquisitions. This study aims to extend internally driven Mergers and Acquisitions research efforts of acquirers to industry contingencies of targets by analyzing cross-border acquirers located within the group of seven (G7) countries.

This study’s investigation covers 209 cross-border acquisitions from 2012 to 2019 undertaken by firms located within the G7 countries. This paper used generalized estimation equations method to test the hypotheses applying Gaussian distribution for the dependent variable, an identity link function, exchangeable correlation structure and robust standard errors.

This study’s results reveal that target industry growth determines premiums. Furthermore, this study shows that acquirer industry growth, as well as acquirer slack, moderates this relationship. This study is built on the notion that industry contingencies influence premiums even when target firms are based in foreign countries.

To the best of the authors’ knowledge, unlike other studies, this is the first to explicitly focus on premiums for multiple cross-border acquisitions by hand selecting nine years of industry sale figures for 53 industries separately in each of the G7 nation countries (leading to 371 separate downloads of data samples). This study contends that industry growth of cross-border targets matters for premium payments.

Fire smoke detection in petrochemical plant can prevent fire and ensure production safety and life safety. The purpose of this paper is to solve the problem of missed detection and false detection in flame smoke detection under complex factory background.

This paper presents a flame smoke detection algorithm based on YOLOv5. The target regression loss function (CIoU) is used to improve the missed detection and false detection in target detection and improve the model detection performance. The improved activation function avoids gradient disappearance to maintain high real-time performance of the algorithm. Data enhancement technology is used to enhance the ability of the network to extract features and improve the accuracy of the model for small target detection.

Based on the actual situation of flame smoke, the loss function and activation function of YOLOv5 model are improved. Based on the improved YOLOv5 model, a flame smoke detection algorithm with generalization performance is established. The improved model is compared with SSD and YOLOv4-tiny. The accuracy of the improved YOLOv5 model can reach 99.5%, which achieves a more accurate detection effect on flame smoke. The improved network model is superior to the existing methods in running time and accuracy.

Aiming at the actual particularity of flame smoke detection, an improved flame smoke detection network model based on YOLOv5 is established. The purpose of optimizing the model is achieved by improving the loss function, and the activation function with stronger nonlinear ability is combined to avoid over-fitting of the network. This method is helpful to improve the problems of missed detection and false detection in flame smoke detection and can be further extended to pedestrian target detection and vehicle running recognition.

Drawing on hegemonic masculinity theory, this study provides evidence supporting how gender, race and sexual identity, may shape the rates of sexual misconduct reporting, by keeping those targets who traditionally enjoy positions of power (i.e. white, cisgender men) silent.

Across 3,230 gender harassment, 890 sexual advance harassment and 570 sexual assault incidents that occurred within a traditionally masculine organization, the authors conducted tests of independence and hierarchical regression analyses to examine whether targets' social identity characteristics (i.e. sex, race, sexuality and gender alignment), predicted the reporting of sexual misconduct.

Although reporting rates varied based on the type of incident, white men were less likely than their colleagues to report workplace sexual misconduct. In general, men were approximately half as likely as women to report. Lower rates of reporting were similarly seen among all white (vs BIPOC) targets and all cisgender and heterosexual (vs LGBT) targets, when controlling for other identity characteristics.

Research on sexual misconduct has largely privileged the experiences of (white, heterosexual) women, despite knowledge that men, too, can experience this mistreatment. This research broadens this lens and challenges the notion that sexual misconduct reporting rates are uniform across employee groups. By articulating how the pressures of hegemonic masculinity serve to silence certain targets – including and especially white, cisgender men – the authors provide means of better understanding and addressing workplace sexual misconduct underreporting.

This study aims to develop a unified theoretical framework that presents a cohesive picture of workplace cyberbullying to better understand the interplay between cyberbullying, its effects on organizations and organizational controls enacted to contain these effects.

The study conducts a theoretical review of the workplace cyberbullying literature between 2005 and 2021 drawing upon existing literature and two important theories, the routine activities theory and control theory. The final sample of 54 empirical papers represents a comprehensive body of literature on cyberbullying published across various disciplines.

A theoretical model of workplace cyberbullying is developed, which highlights major antecedents to workplace cyberbullying and its impact on individual employees as well as organizations.

As firms increasingly rely on information and communication technologies (ICTs), the misuse of ICTs in the form of cyberbullying is also increasing. Workplace cyberbullying severely hurts an organization’s employees and compromises the efficacy of its information systems. Fortunately, various controls can be utilized by firms to minimize workplace cyberbullying and its attendant costs. In all, eleven propositions are offered, providing a robust agenda for future research. The authors also offer insights for practitioners on how to minimize cyberbullying in the workplace and its damaging effects.

The research of unmanned air/ground vehicle (UAV/UGV) cooperation has attracted much attention due to its potential applications in disaster rescue and target surveillance. This paper aims to focus on the UAV/UGV cooperative target tracking and enclosing, considering the limits of detection and sensor failures.

The UAV/UGV cooperation structure is designed, contributing to homogeneous consistency and heterogeneous communication. The target tracking of UAVs is converted into a constraint optimization problem involving tracking cost, and the target enclosing of UGVs is modeled as formation control.

The energy estimation pigeon-inspired optimization is developed to generate control inputs for UAVs. And the controller combined with switchable topology is proposed, where the switching rule is flexible in dealing with some emergencies.

The proposed structure and algorithms can be easily applied to practice and help design the UAV/UGV control system.

The energy estimation mechanism is proposed for the target tracking of UAVs, and the rules of switching topologies ensure the target enclosing process of UGVs.

We empirically investigate the hypothesis that the less transparent (more difficult to value) the target’s assets are the more likely it is that the acquiring firm can obtain higher short- and long-term returns. We analyze a sample of 1,538 friendly acquisitions partitioned in two separate dimensions: acquisitions of public versus private firms, and acquisitions of a firm’s assets versus acquisitions of a firm’s assets and its management. Using a sample of (nondiversifying) real estate transactions with a public REIT as the acquirer, we find that acquisitions of public firms have insignificant short-term abnormal returns. Acquisitions of private targets have positive and significant short-term abnormal returns. The acquirer’s abnormal returns are higher in both cases when the transactions involve acquisition of the target firm’s management. We find parallel results when analyzing the acquirer’s Q over the merger year and the three following years. Our conclusions are robust to the type of financing (cash, stock, or a combination) used in the acquisition.

We examine the market valuation of targets with multiple large shareholders (MLS) and single large shareholder (SLS) structures, in an international sample of M&A announcement in 19 countries outside North America. We find that the presence and power of MLS in these firms are negatively associated with abnormal returns and first-bid-to-merger-completion returns, suggesting that MLS mitigate agency problems in the target, and hence their acquisition is perceived as “a loss of good governance.” The negative association between MLS targets and returns is stronger in widely held firms suggesting that MLS indeed curb expropriation of minority shareholders. By contrast, when the second largest shareholder in the MLS structure of the target is a family, we find positive cumulative abnormal returns at the merger announcement, suggesting exacerbated agency problems in these firms that should benefit from the “acquisition of good governance.” Our evidence is robust to a battery of tests and to addressing potential endogeneity.

We consider conditions under which firms hire an intermediary advisor in acquisition deals. Although acquirers pay large advisory fees to investment banks for their assistance in acquisitions, we know little about the conditions under which acquirers form a relationship with an investment bank for an acquisition deal. Specifically, we examine the role of overall acquisition experience, acquisition experience specific to the target’s industry, prior relationship-specific experience, and deal size in relationship formation and continuation. We test their hypotheses using a dataset of US-based acquirers and targets between 1991 and 2015. Our findings provide nuanced insights into the role of acquisition experience for acquirer–investment bank pairing up on acquisition deals.

Building upon the framework of the tradeoff model of capital structure and motivated by the equity market timing theory, we examine whether equity misvaluation is a source of adjustment “costs” that will affect a firm’s leverage adjustment speed toward target. We also investigate whether the quality of a firm’s long-term growth options will influence the decisions of managers to exploit the mispriced equity to converge to the optimum. Using a sample of listed Taiwanese firms during 1992–2014 and employing the market-to-book decomposition as developed by Rhodes-Kropf, Robinson, and Viswanathan (2005), we find that overleveraged and overvalued firms demonstrate faster adjustment speed than overleveraged but undervalued firms. Furthermore, controlling for the misvaluation status, high-growth firms converge to target faster than their low-growth counterparts. The effect of growth options on the relation between equity mispricing and adjustment speed does not mirror the effect of financing deficits. With the detailed financial information of the local companies across a rather long time series, this study provides incremental inputs to the literature of capital structure from the determinants of target leverage, the estimation of leverage adjustment speeds, to the identification of the sources of adjustment costs in an emerging market where institutional environment is strikingly different from the US.