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During the supply chain disruptions caused by COVID-19, logistics service providers (LSPs) have invested heavily in innovations to enhance their supply chain resilience capabilities. However, only little attention has been given so far to the nature of these innovative capabilities, in particular to what extent LSPs were able to repurpose capabilities to build supply chain resilience. In response, using the concept of exaptation, this study identifies to what extent LSPs have discovered and utilized latent functions to build supply chain resilience capabilities during a disruptive event of high impact and low probability.

This conceptual paper uses a theory building approach to advance the literature on supply chain resilience by delineating the relationship between exaptation and supply chain resilience capabilities in the context of COVID-19. To do so, we propose two frameworks: (1) to clarify the role of exaptation for supply chain resilience capabilities and (2) to depict four different exaptation dimensions for the supply chain resilience capabilities of LSPs.

We illustrate how LSPs have repurposed original functions into new products or services to build their supply chain resilience capabilities and combine the two critical concepts of exploitation and exploration capabilities to identify four exaptation dimensions in the context of LSPs, namely impeded exaptation, configurative exaptation, transformative exaptation and ambidextrous exaptation.

As one of the first studies linking exaptation and supply chain resilience, the framework and subsequent categorization advance the understanding of how LSPs can build exapt-driven supply chain resilience capabilities and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the repurposing of capabilities.

The purpose of this paper is to analyse the role of quality management on the development of organisational exploration.

Partial Least Square was used on a sample of 350 companies within the Spanish organic agro-food industry.

The study results provide empirical evidence of the positive and significant impact that quality management has on the development of organisational exploration.

Causal relationships cannot be applied to this study due to cross-sectional data being used rather than longitudinal data.

Quality management must be considered by managers an essential tool to the development of organisational exploration. As a systematic approach, that moves towards to the development of policies, attitudes and behaviours which foster and boots the development of organisational exploration.

Quality management is a widely used management approach, which organisations use to improve the quality of their products, services and their overall performance. Organisational exploration is seen as a fundamental tool to ensure sustainability, profitability and the future survival of organisations; however, there is disagreement throughout previous research. Some authors point out the importance of quality management in developing activities that promote organisational exploration, whereas other authors see quality management as an inhibitor. Given the great controversy in previous research, our study clarifies the role of quality management in the development of organisational exploration.

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.

While previous research has demonstrated the positive effects of digital business strategies on operational efficiency, financial performance and value creation, little is known about how such strategies influence innovation performance. To address the gap, this paper aims to investigate the impact of a firm’s digital business strategy on its innovation performance.

Drawing on the dynamic capability view, this study examines the mechanism through which a digital business strategy affects innovation performance. Data were collected from 215 firms in China and analyzed using multiple regression and structural equation modeling.

The empirical analysis reveals that a firm’s digital business strategy has positive impacts on both product and process innovation performance. These impacts are partially mediated by knowledge-based dynamic capability. Additionally, a firm’s digital business strategy interacts positively with its entrepreneurial orientation in facilitating knowledge-based dynamic capability. Moreover, market turbulence enhances the strength of this interaction effect. Therefore, entrepreneurial-oriented firms operating in turbulent markets can benefit more from digital business strategies to enhance their knowledge-based dynamic capabilities and consequently improve their innovation performance.

This study contributes to the understanding of how a firm’s digital business strategy interacts with entrepreneurial orientation in turbulent markets to shape knowledge-based dynamic capability, which in turn enhances the firm’s innovation performance.

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.

Agile principles have been widely used in software development team practice since the creation of the Agile Manifesto. Studies have examined variables related to agile principles without systematically considering the relationships among key team, agile methodology, and process variables underlying the agile principles and how these variables jointly influence the achievement of software development agility. In this study, the authors tested a team/methodology–process–agility model that links team variables (team autonomy and team competence) and methodological variable (iterative development) to process variables (communication and collaborative decision-making), which are in turn linked to software development agility (ability to sense, respond and learn).

Survey data from one hundred and sixty software development professionals were analyzed using structural equation modeling methods.

The results support the team/methodology–process–agility model. Process variables (communication and collaborative decision-making) mediated the effects of team (autonomy and competence) and methodological (iterative development) variables on software development agility. In addition, team, methodology and process variables had different effects on the three dimensions of software development agility.

The results contribute to the literature on organizational IT management by establishing a team/methodology–process–agility model that can serve as a basis for developing a core theoretical foundation underlying agile principles and practices. The results also have practical implications for organizations in understanding and managing holistically the different roles that agile methodological, team and process factors play in achieving software development agility.

Exploration and exploitation have long been documented as prominent approaches to business management and organizational adaptation to external environment. Maintaining balance between these activities is a key to survival and prosperity. However, there is little direct evidence of the effect of such combined usage of both approaches on firm performance in times of crisis, especially within small- and medium-sized enterprises (SMEs). The purpose of this paper is to reveal the role of balanced ambidexterity in shaping firm performance during COVID-19 recession.

Based on a survey of 333 Russian SMEs, the authors test the proposed theoretical framework linking innovative ambidexterity to firm performance level and variability taking into account technological uncertainty.

The results show that innovative ambidexterity tends to increase level and decrease variability of performance outcomes, whereas technological uncertainty acts as a positive contingency for this impact.

The results provide an improved understanding of ambidexterity and organizational literatures by clarifying the contingent nature of the ambidexterity–firm performance relationship during COVID-19 recession.

This study aims to explore how to overcome and address the loss of exploratory innovation, thereby achieving greater success in exploratory innovation. This phenomenon of loss occurs when enterprises decrease their investment in and engagement with exploratory innovation, ultimately leading to an insufficient amount of such innovation efforts. Drawing on dynamic capabilities, this study investigates the relationship between organizational foresight and exploratory innovation and examines the moderating role of breakthrough orientation/financial orientation.

This study used survey data collected from 296 Chinese high-tech companies in multiple industries and sectors.

The evidence produced by this study reveals that three elements of organizational foresight (i.e. environmental scanning capabilities, strategic selection capabilities and integrating capabilities) positively influence exploratory innovation. Furthermore, this positive effect is strengthened in the context of a high-breakthrough orientation. Moreover, the relationships among environmental scanning capabilities, strategic selection capabilities and exploratory innovation become weaker as an enterprise’s financial orientation increases, whereas a strong financial orientation does not affect the relationship between integrating capabilities and exploratory innovation.

Ambidexterity is key to successful enterprise innovation. Compared with exploitative innovation, it is by no means easy to engage in exploratory innovation, which is especially important in high-tech companies. While the loss of exploratory innovation has been observed, few empirical studies have explored ways to promote exploratory innovation more effectively. A key research implication of this study pertains to the role of organizational foresight in the improvement of exploratory innovation in the context of high-tech companies.

This paper contributes to the broader literature on exploratory innovation and organizational foresight and provides practical guidance for high-tech companies regarding ways of avoiding the loss of exploratory innovation and becoming more successful at exploratory innovation.

This paper aims to systematically review and synthesize existing research on learning-driven strategic renewal and examines the findings to elucidate the dimensions, antecedents, mechanisms and consequences associated with learning-driven strategic renewal, thereby addressing gaps in the existing literature.

This research covers learning-driven strategic renewal from 1992 to 2022, using hybrid snowball sampling techniques and Boolean searches on the Scopus and Web of Science databases to extract 49 papers.

This review proposes an organizing framework for learning-driven strategic renewal, building upon existing literature. The framework identifies various dimensions of the process, including antecedents, mechanisms and consequences. The antecedents are categorized into individual, organizational and external factors. The mechanisms for learning-driven strategic renewal were explored within the context of Crossan’s established 4I framework, which serves as a lens for emphasizing the balance between exploratory and exploitative learning. Within this framework, intuiting, interpreting, integrating and institutionalizing are the four “Is” that guide the renewal process. These mechanisms require a robust system to enforce the prescribed processes effectively, thereby contributing to long-term firm performance and sustainability.

Despite using search terms similar to those in existing literature on strategic renewal, the scope and depth of this study may be limited. Further research may benefit from bibliometric screening or more refined inclusion criteria.

While there has been extensive research into both organizational learning and strategic renewal, no coherent framework links them. This study fills this gap by building a framework that identifies connections between these two concepts, providing valuable insights that may be used to foster successful strategic renewal efforts. The review offers valuable knowledge and understanding of the subject matter, serving as useful guidance for effectively driving renewal initiatives within organizations.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.