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Drawing on the literature on technological acquisition and the knowledge-based view , this study examines how technological overlap between acquiring and target firms influences acquisition premiums. We further explore how the resulting synergies are contingent on the dynamic characteristics of the target firm, specifically its technology clockspeed and industry munificence. Technology clockspeed indicates the pace of technological evolution, reflecting internal dynamic resources, while industry munificence represents the abundance of external resources. These boundary conditions illustrate the dynamics of synergies, explaining their moderation effects on acquisition premiums.

We analyze a sample of 369 technological acquisitions by publicly traded U.S. firms between 1990 and 2011. To test our hypotheses, we used the ordinary least squares regression model with robust standard errors clustered by acquiring firms. In the robustness checks, we applied the generalized estimating equations to account for non-independent observations in our sample and verified that the results were robust to an alternative two-way clustering approach.

We suggest that a low level of technological overlap between an acquiring firm and its target firm leads the acquiring firm to offer a high acquisition premium because of the expected synergistic potential that evolves from combining two distant technological bases. We further find that this effect is contingent on the target firm's technology clockspeed and industry munificence. Specifically, the negative effect is amplified when target firms exhibit a rapid pace of technological evolution, whereas it is weakened when target firms operate in highly munificent industries characterized by robust growth and abundant resource flows.

This study has several limitations, but it offers opportunities for future research. First, our sample is limited to domestic acquisitions between U.S. publicly traded firms, which may restrict generalizability. Cross-border acquisitions could reveal different dynamics, as technology leakage and national security concerns might make technological overlap a more sensitive factor. Additionally, private firms were not included, and their distinct strategic considerations could provide further insights. Future research could explore post-acquisition data to validate these synergies and expand the scope to include international contexts and private firms for a comprehensive analysis.

Our findings highlight important implications for managers in technology sector acquisitions. This study underscores the need for a thorough evaluation of target firms to avoid misjudging synergies. Low technological overlap can heighten expectations for value creation, making it crucial for executives to accurately assess potential synergies to prevent overestimation. Managers should consider both internal resources and external industry conditions when evaluating synergies. Ultimately, these insights help managers offer informed prices that reflect true strategic synergies, adopting effective valuation practices to mitigate risks of financial overpayments and poor post-merger performance.

The social implications of our findings emphasize the broader impact of acquisition decisions on innovation and competition within the technology sector. By ensuring accurate valuation and avoiding overpayment, companies can allocate resources more efficiently, fostering sustainable growth and innovation. This diligent approach can reduce the risk of corporate failures.

This study makes two key theoretical contributions. First, it identifies technological overlap as a critical determinant of acquisition premiums in technological acquisitions, addressing gaps in the literature that focused on CEO characteristics and managerial attention. Second, it expands the theoretical framework by highlighting the dynamic nature of synergies, influenced by the target firm's technology clockspeed and industry munificence. By integrating both acquiring and target firm characteristics, this study provides a relational perspective on value creation, explaining why firms pay high premiums and offering a more comprehensive understanding of the strategic motivations in technological acquisitions.

The study aims to understand the phenomenon of workplace ostracism from multiple perspectives (target, perpetrator and observer). The understanding of the phenomenon is used to thematically analyse the antecedents of workplace ostracism and identify appropriate strategies for each antecedent.

The study findings are based on face-to-face semi-structured interviews with thirty-three senior and medium-level employees from various public and private sector organizations in India. The interview transcripts were systematically analyzed to identify antecedents of ostracism, which were inductively grouped together based on similarity.

The antecedents of workplace ostracism were grouped into four major heads: perceived non-alignment with organizational needs; emotional reaction; unconscious social processes and structural and demographic differences. Based on interview transcripts, strategies to reduce the effect of each of the broad antecedents of ostracism were identified.

Workplace ostracism has been linked with multiple negative outcomes including increased stress and turnover intention. The study provides managers with a framework that enables them to evaluate and understand incidences of ostracism among their subordinates. The study also equips managers with the knowledge of specific strategies for dealing with specific antecedents of ostracism.

The study answers the need to look at the phenomenon of ostracism through multiple perspectives. It identifies multiple potentially new antecedents and strategies to deal with workplace ostracism and groups them in a coherent manner. It is among the few studies on ostracism in India and extends the generalizability of the construct.

In conducting acquisitions, acquirers often hire financial advisors as independent third parties and ask for their endorsement, aiming to assuage their shareholders’ concerns. The market for financial advisors is status-based as acquirers seek higher-status advisors (rather than lower-status advisors) assuming that higher-status advisors can better discern good from poor acquisitions because they are more trustworthy and competent. The authors challenge such an assumption by suggesting that the status-based market for advisors may fail among middle-status advisors. Middle-status advisors experience strong competition from higher-status advisors in attracting and retaining clients. Such pressure incentivizes middle-status advisors to endorse even risky deals that are more likely to result in acquisition failure. In contrast, high-status advisors have little incentive to endorse risky deals; low-status advisors are overlooked by acquirers needing strong external endorsement. Based on 828 deals by US acquiring firms, the authors find advisors’ status and the acquisition premium their clients pay to have an inverted U-shaped relationship, suggesting that middle-status advisors have the greatest likelihood to endorse overvalued acquisition deals.

The human body has the same basic size data but has different surface morphology, resulting in the unfitness even under the same size specification. The purpose of this study was to solve the local fitness problems by representing and quantifying the human surface morphological difference.

Firstly, the 3D point cloud for 323 female students was scanned, and the cross-section layers of the “waist-to-thigh” zone were determined. Secondly, the space vector based on the space Euclidean distance was extracted to represent and quantify the surface morphological difference. And the Principal Component Analysis and K-means were adopted to subdivide the target zone. Thirdly, the pattern based on the subdivision results and surface flattening was generated. Additionally, the fitness was evaluated by the subjective and objective assessments, separately.

The space vector could represent and quantify the shape morphology of the “waist-to-thigh” zone. It had successfully achieved the human body subdivision and corresponding pattern generation for the “waist-to-thigh” zone. And the pattern based on the shape subdivision and surface flattening of the space vector could effectively improve the wearing fitness. Particularly in the waist and crotch area of trousers, the obvious wrinkles had been solved because the space vector is more in line with the shape morphology characteristics.

The proposed method could represent and quantify the difference in human surface morphology in a 3D manner. It solved the unfitness problem caused by the same body size but different shape surface morphology. And it will contribute to the fitness improvement of the trousers.

This study investigated how the Covid-19 pandemic impacted cross-border acquisitions. Though literature suggests that cross-border investments decreased during the pandemic, there is little conclusive evidence on specific characteristics in the execution of particular acquisitions during such times. We applied the case study format to conduct our investigation by (1) providing a classification of influences on cross-border procedures and (2) highlighting critical characteristics during three phases of acquisitions, namely, search, negotiation and integration periods.

The grounded theory approach was applied to three in-depth case studies of German companies that acquired Japanese targets during the Covid-19 pandemic. Data were supplemented by information received through additional case studies of German subsidiaries in Japan and interviews with consultants.

Firms had already intended to acquire their respective targets, with their decisions having been made prior to the Covid-19 pandemic. Thus, the pandemic had no impact on target selection in the case firms. Owing to travel restrictions, information exchange was limited which inevitably led to higher usage of digitalization. While several barriers led to delays in negotiations, prevailing mutual trust and assistance from consultants helped to reduce difficulties. During the integration period, we found delays in synergy creation and increases in remote communication. Nevertheless, the digital workflow improved the efficiency.

Our study provides novel insights into the execution of cross-border acquisitions impacted by the Covid-19 pandemic. We discuss new implications for mergers and acquisitions (M&A) research and practice for the post-pandemic era, focusing on German firms acquiring Japanese targets.

This study examines how corporate litigation, both securities-related and not, is affected by hedge fund (HF) activism.

We use a difference-in-differences (DiD) method, along with propensity score matching and firm fixed effects and a comparison of HF and non-HF activists for identification.

We find that companies that are targeted by HFs face operation-related lawsuits, mainly from stakeholders or competitors. This effect does not seem to be caused by targets' higher tendency to settle the cases. Our evidence shows that HF activists increase firm value for the target firms that are prone to litigation.

Therefore, our evidence supports the idea that the higher operation litigation risks are unintended consequences of improving firm efficiency through cost savings or restructuring of target firms by the activists.

Extending the springboard perspective with the resource dependence theory, the authors posit that cross-border mergers and acquisitions (M&As) are a new channel for emerging economy firms (EEFs) to enhance their technology capabilities. This study aims to examine the impact of cross-border M&As initiated by EEFs on their technology augmentation vis-à-vis matched domestic M&A cases and investigate the factors influencing the difference in post-merger innovation capability.

This paper estimates the post-acquisition innovation capability of acquirers from emerging economies (EEs) that engage in cross-border M&As. To remove possible selection bias, the authors leverage a difference-in-difference-style approach in combination with a matched sample constructed by pairing each cross-border M&A case with a similar domestic deal. The data set contains 266 cross-border M&As and 266 matched domestic M&A deals between 2003 and 2011, whereby acquirers are based in 6 EEs and targets are in 36 countries consisting of both EEs and advanced economies (AEs).

The present empirical results show that cross-border M&As engaged by EEFs are an important engine for improving EEFs’ innovation capability through technology augmentation. The main empirical results are as follows. First, compared with matched domestic acquirers with similar characteristics, EE cross-border M&As have a positive effect on innovation capability. Second, the positive effect of the EEFs’ cross-border M&As relative to the matched domestic M&As on innovation capability is driven largely by cross-border M&As with targets in AEs. Third, the increase in post-M&A innovation capability of the EE cross-border acquirers comes mainly from deals where targets are based in countries with relatively superior human capital and innovation capability than those of the acquirers.

To the best of the authors’ knowledge, this study is the first systematic study of whether cross-border M&As serve as an effective channel of technology augmentation for EE acquirers compared to matched domestic acquirers with similar characteristics.

This study aims to examine the effects of payment methods used in mergers and acquisitions (M&A) conducted by UK companies spanning the period from 2007 to 2019.

The study used the estimated expected returns method to identify abnormal returns during the deal announcement period, applying event study analysis with both univariate and multivariate regression models to detect cumulative abnormal returns around the announcement timeframe.

The results show a short-term positive return increase for acquiring firms, controlling for deal-specific characteristics like target firm location and payment methods. The authors observed a preference for cash financing across domestic and cross-border transactions. Multivariate analysis revealed insignificance between payment methods and deal characteristics like cross-border acquisitions and diversification.

The study’s focus on publicly traded firms in the UK and the absence of a comparative analysis across different regions and markets limits the sample size and may impact the generalizability of findings.

The study proposes three practical implications. Firstly, firms should tailor payment methods to each transaction, aligning with strategic goals to optimize value and mitigate risks. Secondly, decision-makers must prioritize comprehensive due diligence and strategic alignment throughout M&A processes to enhance success and maximize synergies. Finally, analysing broader strategic contexts and regulatory landscapes when structuring transactions enables goal attainment, such as market expansion or value creation.

The study’s findings can promote transparency and accountability among corporate decision-makers in M&A transactions. Stakeholders can advocate for transparent decision-making processes, enhancing trust in corporate governance.

This study provides valuable insights into the impact of payment methods on shareholder value in M&A transactions involving UK companies, informing strategic decision-making and contributing to the understanding of corporate finance dynamics.

This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

The purpose of this paper is to propose a whole set of methods for underwater target detection, because most underwater objects have small samples, low quality underwater images problems such as detail loss, low contrast and color distortion, and verify the feasibility of the proposed methods through experiments.

The improved RGHS algorithm to enhance the original underwater target image is proposed, and then the YOLOv4 deep learning network for underwater small sample targets detection is improved based on the combination of traditional data expansion method and Mosaic algorithm, expanding the feature extraction capability with SPP (Spatial Pyramid Pooling) module after each feature extraction layer to extract richer feature information.

The experimental results, using the official dataset, reveal a 3.5% increase in average detection accuracy for three types of underwater biological targets compared to the traditional YOLOv4 algorithm. In underwater robot application testing, the proposed method achieves an impressive 94.73% average detection accuracy for the three types of underwater biological targets.

Underwater target detection is an important task for underwater robot application. However, most underwater targets have the characteristics of small samples, and the detection of small sample targets is a comprehensive problem because it is affected by the quality of underwater images. This paper provides a whole set of methods to solve the problems, which is of great significance to the application of underwater robot.