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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.

Foreign subsidiaries of multinational enterprises (MNEs) operate in complex and competitive international environments, implement market and non-market strategies, manage resources and value-added activities and contribute to the overall performance of their parent firms. Thus, the research question on the determinants of MNE foreign subsidiaries’ performance is of interest to managers and academic researchers. The empirical literature has flourished over the recent decades; however, the domains are fragmented, and the findings are inclusive. The purpose of this study is to systematically review, analyse and synthesize the empirical articles in this area, identify research gaps and suggest a future research agenda.

This study uses the qualitative content analysis method in reviewing and analysing 150 articles published in 24 scholarly journals during the period 2000–2023.

The literature uses a variety of theoretical perspectives to examine the key determinants of subsidiary performance which can be grouped into six major domains, namely, home- and host country-level factors; distance between home and host countries; the characteristics of parent firms and of subsidiaries; and governance mechanisms (the establishment modes and ownership strategy, subsidiary autonomy and the use of home country expatriates for transferring knowledge from the headquarters and controlling foreign subsidiaries). A range of objective and subjective indicators are used to measure subsidiary performance. Yet, the research shows a lack of broader integration of theories and presents inconsistent theoretical predictions, inconclusive empirical findings and estimation bias, which hinder our understanding of how the determinants independently and jointly shape the performance of foreign subsidiaries.

This study provides a comprehensive, nuanced and systematic review that synthesizes and clarifies the determinants of subsidiary performance, offers deeper insights from both theoretical, methodological and empirical aspects and proposes some promising avenues for future research directions.

In recent years, the trend of hiring external CEOs has become increasingly prevalent. However, the impact of these CEOs' prior experiences in different firms on the innovation of their successor firms has not received sufficient attention. Drawing on upper echelons theory and management power theory, this study explores the non-linear relationship between prior CEO experience and breakthrough innovation, as well as the moderating effects of different types of CEO power.

We selected China’s A-share listed manufacturing companies as samples and used zero-inflated Poisson regression to verify the hypothesis. We employed instrumental variable methodology to address potential endogeneity issues and conducted robustness tests by substituting core variables, changing measures, adding additional control variables, and shrinking the core variables.

We conclude that there exists an inverted U-shaped relationship between prior CEO experience and breakthrough innovation. Furthermore, we analyze the effects of formal and informal CEO power on the role of prior CEO experience in breakthrough innovation and find that the inverted U-shaped relationship is contingent upon the level of CEO power.

The findings extend research on CEO succession and offer a reference for firms aiming to hire external CEOs with prior experience to foster breakthrough innovation.

Theories are crucial for addressing research questions and advancing the boundaries of knowledge. However, in the field of strategic management, the existence of diverse schools of thought from various disciplines, including economics, politics, and sociology, poses significant challenges for researchers seeking to develop theories for argumentation and theorization. In this study, we have conceptualized a novel approach to selecting an appropriate theory for addressing specific research questions.

Thought experiment, disciplined imagination, and a conceptual examination of a diverse set of theories.

Because the central focus in the field of strategic management revolves around how firms achieve sustainable high performance, a research question should initially clarify the fundamental phenomenological issues it aims to address. Subsequently, the process of problematization should identify the ontological assumptions and premises that establish a connection between the research question and existing theories. Finally, the identification and abstraction of rhetorical concepts derived from these assumptions and premises lead to theory selection criteria, namely connectedness, reliability, parsimoniousness, and falsifiability.

Although we believe that our model for theory selection is generalizable to a wide range of management disciplines, we have primarily focused on its application in the field of strategic management. Future work could validate and further explore the applicability and effectiveness of this model in selecting appropriate theories for conceptual development in other domains.

While many researchers have proposed methods for writing theoretical papers, few have provided suggestions specifically focused on theory selection. This paper stands out as one of the few that not only attempts to address this gap but successfully develops a comprehensive model for theory selection.

This study investigates the profound impact of artificial intelligence (AI) capabilities on decision-making processes and organizational performance, addressing a crucial gap in the literature by exploring the mediating role of decision-making speed and quality.

Drawing upon resource-based theory and prior research, this study constructs a comprehensive model and hypotheses to illuminate the influence of AI capabilities within organizations on decision-making speed, decision quality, and, ultimately, organizational performance. A dataset comprising 230 responses from diverse organizations forms the basis of the analysis, with the study employing a partial least squares structural equation model (PLS-SEM) for robust data examination.

The results demonstrate the pivotal role of AI capabilities in shaping organizational decision-making processes and performance. AI capability significantly and positively affects decision-making speed, decision quality, and overall organizational performance. Notably, decision-making speed is a critical factor contributing significantly to enhanced organizational performance. The study further uncovered partial mediation effects, suggesting that decision-making processes partially mediate the relationship between AI capabilities and organizational performance through decision-making speed.

This study contributes to the existing body of literature by providing empirical evidence of the multifaceted impact of AI capabilities on organizational decision-making and performance. Elucidating the mediating role of decision-making processes advances our understanding of the complex mechanisms through which AI capabilities drive organizational success.

The paper tries to investigate the impact of applications of the resource-based view (RBV) theory in the management field to improve the firm’s profitability. Global firms are innovating and adopting new technology, paving the way to improve their performance.

We have adopted RBV in management practices such as marketing, strategy, finance, and human resources.

RBV has gained researchers' attention with the growing competitive world and new challenges to retaining customers and achieving their pre-defined targets. We attempt to identify the issues related to the usage of RBV in management.

Using RBV in management may help researchers create a competitive mindset and be prepared for uncertain challenges in the business world.

Prior research from transaction costs economics argued that central firms perform better because they have superior access to information to discipline their alliance partners. Central firms may also, however, face higher costs and risks of unintentional learning and weaken their competence through structural inertia. We propose that these costs and risks are influenced by the learning capacities of the firms in the network and can explain different outcomes for focal firm performance.

To test our predictions, we use instrumental variable–generalized method of moments estimation techniques on 15,517 firm-year observations from equity alliance portfolios in the global food industry across a 21-year window.

We find support for our predictions and show that the relationship between network degree centrality and firm performance is negatively influenced by partners’ learning capacity and positively influenced by focal firms’ learning capacity, while firms with low network degree centrality benefit less from their learning capacity.

Future developments in transaction cost economics may consider partner and focal firms’ learning capacity as moderators of the network degree centrality – firm performance relationship.

In alliance decisions, managers must consider that the combination of high network degree centrality and partners’ learning capacity can lead to high costs, risks of unintentional learning, and structural inertia, all of which have negative consequences for performance. In concentrated industries where network positions are controlled by a few large firms, policymakers must acknowledge that firms may face substantial barriers to collaboration with learning-intensive firms.

This study is the first to develop and test a comprehensive transaction cost analysis of the central firm’s unintended knowledge flows and structural inertia in alliance networks. It is also the first to incorporate theoretically and empirically the hazards of complex and unintended information flows on the relationship of network degree centrality to performance in equity alliance portfolios.

Scholars have underscored the importance of organizational authenticity, but it is unclear how it influences the links among market strategy, and nonmarket strategy (NMS) and firm performance. This study addresses this gap in the literature.

A survey of 294 managers in firms based in the United States investigates configurations among competitive strategy (e.g. cost leadership or differentiation), political and social nonmarket strategy (NMS), authenticity, and firm performance.

Cost leaders tend to engage in political nonmarket strategy (PNMS), but the interaction does not necessarily improve firm performance. Differentiators are more likely to pursue social nonmarket strategy (SNMS) and perform better, but neither market-nonmarket strategy configuration is inherently optimal.

The results support market-nonmarket strategy configurations but do not prescribe optimal combinations. However, the sample is cross-sector and employs self-reports for firm performance.

Political and social authenticity can enhance firm performance, but nonmarket activity can compromise a firm’s ability to be politically and socially authentic. Authenticity can drive performance, but a firm’s nonmarket activity can compromise its ability to be politically and socially authentic. Firms should view a prospective loss in authenticity as a potential cost of nonmarket activity.

This paper investigates how a firm’s emphasis on market (competitive) strategies, political and social nonmarket strategies, and political and social authenticity impact financial and non-financial performance. It also tests the veracity of two market-nonmarket configurations, cost leadership with political NMS and differentiation with social NMS.

This paper aims to examine the effects on firms' outcomes of a new government regulation on the private security industry that aimed to enhance the selection and training processes for armed-private security officers.

By using human capital theory and using a data set built from various public sources, this study analyzes the effects of a new regulation implemented in 2013–2014 in Brazil mandating psychological assessments for hiring private security armed officers. Firm-level data and a Difference-in-Differences (DiD) identification strategy are used to investigate the effects on turnover and human capital outcomes.

The study identifies substantial changes resulting from the new government regulation in private security firms. While it has led to increased turnover rates, the regulation has also facilitated firms in enhancing the human capital composition of their workforce by enabling the recruitment of more experienced personnel.

This research informs to current debates on the effects of policy interventions on firm's outcomes by showing how regulations aimed to improve the configuration of human capital can generate win-win situations for both firms and citizens, despite the short-term trade-offs between higher turnover rates and improved human capital outcomes.

Refining selection and training processes can enhance the workforce in private security firms by replacing less capable professionals with more experienced ones. Insights from this study offer guidance to policymakers and industry practitioners in shaping effective business and public policies.

This study underscores the role of training and psychological assessments in enhancing the composition of human capital in the private security industry.

By highlighting the role of policy interventions in establishing barriers to unskilled workers engaging in hazardous activities, this study contributes to the burgeoning literature in strategic management on the interaction between policy interventions and firm outcomes.

This study investigates the extent to which a firm’s centrality and autonomy in its supply network are associated with the intensity and complexity of its competitive actions.

Utilizing social network analysis and dynamic panel data models, this study analyzes a comprehensive panel dataset with 10,802 firm-year observations across various industries between 2011 and 2018 to test the hypotheses.

Our findings show that a firm’s level of centrality in its supply network has an inverted U-shaped relationship with both competitive intensity and competitive complexity. In addition, the turning points of these two inverted U-shaped relationships differ in that firms with a lower level of centrality tend to compete aggressively by launching more actions within fewer categories, while firms with a higher level of centrality tend to compete aggressively by launching fewer actions that cover a larger range of categories. Finally, we find that a firm’s structural autonomy has a positive relationship with competitive complexity.

This study bridges the gap between the supply chain management literature and strategic management literature and investigates how supply networks shape competitive aggressiveness. In particular, this research investigates how a firm’s structural position in its supply network affects its competitive actions, an important intermediate mechanism for competitive advantage that has been overlooked in the supply chain management literature.