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The rise of emerging economies in the innovation landscape has often been attributed to the positive spillovers of innovation capabilities from multinational corporations (MNCs). However, it is less certain that their innovative capabilities imported from the home country function effectively in the host country from the outset. This study examines the performance of the innovation capabilities of MNC subsidiaries in emerging economies over time by considering the gradual process of their learning about host countries.

We employed stochastic frontier analysis to measure innovation capabilities, our focal construct. For regression analysis, we applied the Mundlak estimator, a variant of the fixed-effects panel estimator, to a sample comprising subsidiaries of MNCs from technologically advanced nations operating in Korea between 2006 and 2016.

Our results indicate that the innovation capabilities of MNC subsidiaries initially underperform those of local firms but improve over time, eventually surpassing the capabilities of their local counterparts. Furthermore, our findings reveal that institutional distance amplifies the underperformance of the innovation capabilities of MNC subsidiaries.

This study contributes to the literature by extending both theoretical development and empirical measurement of innovation capabilities in cross-national settings. Additionally, it deepens our understanding of whether and how MNC subsidiaries adapt their innovation capabilities to the local market environment.

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 paper aims to investigate the link between internal capabilities, innovation strategies and export performance (EP), considering the corporate social responsibility (CSR) principle as a moderator.

The statistical population of the current study is the food and agricultural products exporting small- and medium-sized enterprises (SME) which participated in the 27th International Agrofood Exhibition (2021) in Tehran, Iran. A sample of 296 managers was selected, using systematic random sampling, to answer the questionnaire. To analyze the data, we used structural equation modeling (SEM) and Hayes PROCESS in SPSS.

Results show that just manufacturing capabilities affect both exploratory and exploitative innovation, in contrast to marketing capabilities that does not have any significant impact on these two innovation strategies. Moreover, the impact of both explorative and exploratory innovation on EP is supported in the context of food and agricultural SMEs. However, CSR positively moderates the impact of exploratory innovation on EP, showing it has a negative effect on the impact of exploitative innovation on EP.

By addressing the research gap on the link between internal capabilities, innovation strategies, EP and CSR among SMEs, the current research provides valuable body of research that later studies in the literature can leverage or build upon.

To examine the development of research into the relationship between business process outsourcing (BPO) and innovation, a bibliometric methodology utilizing quantitative analytical methodologies was used. With the aid of a visualization analysis of scientific publications, this study also assessed the state of BPO and innovation practices.

Using the Web of Science database, articles on BPO and innovation that published between 1992 and 2022 were retrieved. Records that had been extracted were examined in terms of publication year, nation, journal, subject area, authors and affiliations with organizations. The research on acupuncture for pain relief was visualized using the VOSviewer application.

An analysis of 219 original and review papers found that during the past 30 years, the overall number of publications has fluctuated constantly. The London University, the Copenhagen Business School and the London School of Economics were the institutions that produced the most articles in this topic. The three main categories of research that emerged from a network analysis based on the co-occurrence of keywords are innovation, outsourcing and performance.

A BP-innovation model must be created, and BPO must go beyond operational duties to incorporate management-wide shared strategic decisions in order to ensure improved performance of the firms. BPO enables a company's management to share knowledge and expertise about the strategic difficulties of outsourcing. A variety of technological and non-technological resources must also be considered when integrating an information technology (IT) infrastructure into BPO decisions in order to achieve greater performance.

Validity of the paper can be justified by it contribution to the existing knowledge. First, linking BPO and innovation – by integrating the arguments of various academics, the study unifies the disparate components and contentious discussions in the relationship between BPO and innovation. Second, this study highlights a research trend, significant studies, relevant terms and concepts in the real world. Third, the study provides future researchers with a tip for statistically analyzing BPO, particularly in light of innovation.

This study aims to develop a model of learning-by-hiring in which knowledge gains may occur at the time of recruitment but also after recruitment when other incumbent organizational members assimilate a recruit’s knowledge. The author’s model predicts that experienced recruits are more likely to catalyze change to their organization’s core technological capabilities.

The continuous-time parametric hazard rate regressions predict core technological change in a long panel (1970–2017) of US biotechnology industry patent data. The author uses over 140,000 patents to model the evolution of knowledge of over 52,000 scientists and over 4,450 firms. To address endogeneity concerns, the author uses the Heckman selection method and does robustness tests using a difference-in-difference analysis.

The author finds that a hire’s prior research and development (R&D) experience helps overcome inertia arising from her or his new-to-an-organization “distant” knowledge to increase the likelihood of core technological change. In addition, while the author finds that incumbent organizational members resist technological change, experienced hires may effectively induce them to adopt new ways of doing things. This is particularly the case when hires collaborate with incumbents in R&D projects. Understanding the effects of hiring on core technological change, therefore, benefits from an assessment of hire R&D experience and its effects on incumbent inertia in an organization.

First, the author does not recommend managers to hire scientists with considerable distant knowledge only as this may be detrimental to core technological change. Second, the author recommends organizations striving to effectuate technological change to hire people with considerable prior R&D experience as this confers them with the ability to influence other members and socialize incumbent members. Third, the author recommends that managers hire people with both significant levels of prior experience and distant knowledge as they are complements. Finally, the author recommends managers to encourage collaboration between highly experienced hired scientists and long-tenured incumbent organizational members to facilitate incumbent learning, socialization and adoption of new ways of doing things.

This study develops a model of learning-by-hiring, which, to the best of the authors’ knowledge, is the first to propose, test and advance KM literature by showing the effectiveness of experienced hires to stimulate knowledge diffusion and core technological change over time after being hired. This study contributes to innovation, organizational learning and strategy literatures.

This paper aims to identify the combination of innovation determinants driving the creation of innovative products amongst market leaders and market followers in food and beverage (F&B) firms.

This research is based on the case study methodology by using two types of data sources: (1) semi-structured interviews with industry experts and (2) in-depth interviews with managers. In addition, a questionnaire adapted from prior research was used to consider market and firm types.

Suggesting an integrated theoretical framework based on firm-based factors and market-based factors, this study identified a combination of determinants significantly impacting innovative products in the market. Specifically, these determinants are competition intensity and innovation capability (a combination of research and development (R&D) investment and marketing capabilities). The study also examined how these determinants vary depending on whether the firms are market leaders or market followers.

This research provides practical insights for managers working in the F&B industry by using case studies and exploring the determinants of developing innovative products. In doing so, suitable strategies can be selected according to the market and firm situations.

The originality of the study is shown by focussing on how different combinations of market and firm factors could be applied in creating successful innovative products in the food sector.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This study aims to examine the dimensions of technological innovation capability (TIC) and associated factors from the perspectives of sustainability.

The authors have systematically reviewed publications by synthesizing and comparing the findings and arguments from previous studies.

The study locates a wide-ranging advance of sustainable TIC as a construct by demonstrating the leading dimensions and key factors interrelated to the sustainable TIC. The foremost IC that has been addressed includes process, product, marketing, R&D and knowledge ICs.

Future research should test the extent of the contribution of TIC in intensifying the determining factors toward enhancing performance and sustainability. Besides, the undermined external aspects such as social responsibility and the natural environment should be addressed by future researchers to develop a comprehensive sustainable TIC.

This study reviews the various researches in the subject matter of sustainable TIC to show the developments as well as to provide comprehensive understandings in the subject.

Joint research is pointed out by the literature as a potentially virtuous cooperation scheme to generate learning in the public sphere and beneficial effects in society. The purpose of this study, based on the Argentine experience in the COVID-19 pandemic, is to analyze the network of capacities, relationships and effects generated, over time, by a series of projects financed by the State in 2010, to clarify the link between learning effects and social effects.

A qualitative methodology focused on the multiple case study method was used. Each case covers joint R&D projects financed 10 years ago by the state that subsequently led to different solutions for COVID-19.

The work identifies a public learning process that integrates both industry’s contributions and the intellectual dimension of economic benefits and their translation into specific capabilities; conceptualizes the capacities accumulation process as a multiplier of social effects (direct and indirect) that emerge as knowledge is reused; identifies the articulation between different schemes as a condition for learning effects and social effects to manifest over time.

An aspect not studied in the literature is addressed, the relationship between the learning process induced by joint research, in terms of capabilities, and the social effects specifically generated over time. This is taking place in a context, such as the COVID-19 pandemic, where calls from the scientific and academic community to promote science–industry cooperation are multiplying.

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.