Search results

This study aims to explore the strategic decisions at innovation level implemented by firms to thrive and transform themselves during crises. This study also aims to provide insights to answer the question: Why do some firms decide to implement certain types of innovation during a crisis?

This research was carried out through a multiple case study involving 22 firms. The methods were implemented in three steps to increase rigor and the replication of the study: identification and selection of cases, data collection through interviews triangulated with online information and analysis based on aggregating themes and finding patterns.

In the face of the COVID-19 pandemic, the companies analyzed focused their activities mainly on developing new features or functionalities for their products or services. Most of the firms implemented innovations across nearly all ten categories outlined by Keeley et al. (2013). Many of the implemented innovations involved personalized and superior service enhancements, process efficiency optimizations, channel diversification initiatives and new ways to collaborate to generate value. In general, the main drivers that led firms to decide to implement these innovations include reducing costs, enhancing operational efficiency, generating new revenue streams, augmenting sales and enhancing client relationships.

This research significantly advances the convergence of innovation, strategy and crisis in three impactful ways. First, it constructs a pragmatic and evidence-based framework, consolidating the primary catalysts, innovation categories and strategies adopted by firms in response to the challenges posed by the COVID-19 crisis. Second, it offers insights for guiding decision-making processes related to innovation, presenting actionable recommendations derived from the study’s findings. Thirdly, this study highlights critical perspectives that can guide governmental intervention, facilitating the formulation of more tailored and effective policies to assist companies during crisis periods.

This study centers on developing countries, specifically examining Colombian firms, considering their unique characteristics and priorities. Surprisingly, there is a scarcity of studies delving into the innovation and transformation of firms during the COVID-19 crisis in nations sharing cultural, economic and political similarities with Colombia.

Coordinating low-carbonization and digitalization is a practical implementation pathway to achieve high-quality economic development. Regions are under great emission reduction pressure to achieve low-carbon development. However, why and how regional emission reduction pressure influences enterprise digital transformation is lacking in the literature. This study empirically tests the impact of emission reduction pressure on enterprise digital transformation and its mechanism.

This article takes the data of non-financial listed companies from 2011 to 2020 as a sample. The digital transformation index is measured by entropy value method. The bidirectional fixed effect model was used to test the hypothesis.

The research results show that emission reduction pressure forces enterprise digital transformation. The mechanism lies in that emission reduction pressure improves digital transformation by promoting enterprise innovation, and digital economy moderates the nexus between emission reduction pressure and digital transformation. Furthermore, the effect of emission reduction pressure on digital transformation is more significant for non-state-owned, mature and high-tech enterprises.

This paper discusses the mediating role of enterprise innovation between carbon emission reduction pressure and enterprise digital transformation, as well as the moderating role of digital economy. The research expands the body of knowledge about dual carbon targets, digitization and technological innovation. The author’s findings help update the impact of regional digital economy development on enterprise digital transformation. It also provides theoretical guidance for the realization of digital transformation by enterprise innovation.

The purpose of this study is to investigate the influence of design for lean six sigma (DFLSS) on operational functions of the innovation management model by appraising an innovation management assessment framework.

An empirical approach for evaluating causal relationships among various constructs in the model phases that identify optimum pathways in achieving commercial success was adopted. A quantitative analysis of survey data were collected from large, medium and small organiations, including incubators in ANZ (Australia, New Zealand) and TMSV (Thailand, Malaysia, Sri Lanka and Vietnam).

The structural equation modelling recursive path analysis results of the model provide empirical evidence and pathways through the various constructs considered in the model. All these pathways lead to delivering optimum commercialization success (CS). Furthermore, DFLSS is confirmed as an enabler and has direct one-to-one and indirect influence on all the operational function constructs of the model including commercial success.

This study had a relatively small sample size of completed responses obtained from the population and a constrained ability to compare commercialization success (CS) between the two regions in the dataset. Future studies could be conducted on a global scale to increase responses.

The research findings enabled the development of important and practical guidelines for managers and innovation practitioners engaged in planning and management of innovation.

This research offers a holistic approach for integrating DFLSS with stage gate phases of innovation management assessment framework, supported by empirical evidence, to aid organizations in effectively managing the innovation process and achieving greater success in commercialization.

Compressing project timelines represents a prevalent temporal tactic aimed at accelerating the innovation process. However, empirical evidence on the impact of such time constraints on innovation remains inconclusive. This study aims to investigate the relationship between a prevalent organizational time mechanism—Performance Appraisal Interval (PAI)—and employee exploratory innovation behavior. Additionally, we explore the boundary conditions that may influence this relationship: the moderating effects of future work self salience and supervisory developmental feedback.

Using online survey data collected in two waves from 426 employees working in hi-tech companies in China, we tested all the hypotheses.

(1) PAI demonstrates an inverted U-shaped influence on employees exploratory innovation behavior; (2) Employees’ future work self salience serves as a moderator that enhances the positive nature of this inverted U-shaped relationship; (3) Supervisory developmental feedback amplifies the moderating role of future work self salience, and the synergistic effect of PAI, future work self salience, and supervisory developmental feedback significantly enhances exploratory innovation behavior.

By providing insights that are attuned to the temporal aspects of performance appraisal, this study aids organizations in making more informed, strategic decisions that enhance both the effectiveness of performance assessments and the cultivation of an environment that encourages exploratory innovation. Additionally, it is recommended that organizational leaders incorporate future-oriented interventions and developmental feedback into their management practices to further promote employees' engagement in exploratory innovation.

Drawing on the interactive theory of performance, this study introduces a novel perspective on how an organizational temporal mechanism influences exploratory innovation and advances our understanding of the non-linear link between time constraints and employees' innovative behaviors.

This study offers practical insights into how generative artificial intelligence (AI) can enhance responsible manufacturing within the context of Industry 5.0. It explores how manufacturers can strategically maximize the potential benefits of generative AI through a synergistic approach.

The study developed a strategic roadmap by employing a mixed qualitative-quantitative research method involving case studies, interviews and interpretive structural modeling (ISM). This roadmap visualizes and elucidates the mechanisms through which generative AI can contribute to advancing the sustainability goals of Industry 5.0.

Generative AI has demonstrated the capability to promote various sustainability objectives within Industry 5.0 through ten distinct functions. These multifaceted functions address multiple facets of manufacturing, ranging from providing data-driven production insights to enhancing the resilience of manufacturing operations.

While each identified generative AI function independently contributes to responsible manufacturing under Industry 5.0, leveraging them individually is a viable strategy. However, they synergistically enhance each other when systematically employed in a specific order. Manufacturers are advised to strategically leverage these functions, drawing on their complementarities to maximize their benefits.

This study pioneers by providing early practical insights into how generative AI enhances the sustainability performance of manufacturers within the Industry 5.0 framework. The proposed strategic roadmap suggests prioritization orders, guiding manufacturers in decision-making processes regarding where and for what purpose to integrate generative AI.

The present research aims to explore the drivers of generative artificial intelligence (GEN AI)-based innovation adoption in the hospitality industry in Jordan.

To address the research gap and achieve the research work objectives, the Technology-Organization-Environment (TOE) lens and the structural equation modeling (SEM) approach were employed to analyze the sample data collected (n = 221) from the hospitality industry.

The findings indicate that relative advantage, top management support, organizational readiness, organizational culture, competitive pressures, government regulations support and vendor support significantly influence the GEN-AI-based innovation adoption, while the technological complexity is negatively associated with GEN-AI-based innovation adoption. Furthermore, the results showed there is no significant effect of cost on GEN-AI-based innovation adoption.

The paper analyses the TOE framework in a new technological setting. The paper also provides information about how GEN-AI-based innovation adoption may influence hospitality industry performance. Overall, this article provides new insights into the literature concerning AI technologies and through the TOE lens.

Chinese firms are winning market share from foreign multinational enterprises in domestic markets. The international business literature suggests that this is happening because these firms are developing non-traditional firm-specific advantages (FSAs). Strategic factor market (SFM) theory provides a good basis for explaining how this is happening. However, it is underdeveloped in terms of analysing unique resources and unique access to those resources by Chinese firms in their domestic markets. This paper aims to develop a framework to understand how Chinese firms have developed non-traditional FSAs.

The case study method is adopted to explore how Chinese firms develop non-traditional FSAs. Specifically, the authors compare paired case studies of a Chinese firm and a foreign multinational in each of two industries.

The authors find that Chinese firms have developed non-traditional FSAs because of more relevant experience, better adapted strategies and privileged relationships. This has enabled Chinese firms to develop non-traditional FSAs.

The authors propose a framework that conceptualises non-traditional FSA development in Chinese firms as a product of superior access to unique and valuable resources in their domestic SFMs.

Effective management of risk and knowledge is critical to ensure the success of industry–university collaboration (IUC) projects. However, the intricate dynamics through which these factors influence the performance of IUC projects have yet to be fully investigated. The purpose of this study is to explore the interplay between risk management and knowledge management capabilities and their impact on IUC project performance.

A model was constructed and evaluated through the examination of a sample of 188 collaborative innovation projects located in the United Arab Emirates (UAE), utilizing structural equation models (SEM) and hierarchical regression analysis.

The findings indicate that social system risk, technical system risk and project management risk have a negative impact on the performance of university–industry collaboration (UIC) projects, while cultural, technical and structural knowledge management capabilities can mitigate the negative impact of these risks on the performance of IUC projects.

The study concludes with three recommendations aimed at improving the management of UIC projects, including the establishment of a distinct and precise management strategy, the deployment of a comprehensive and systematized management methodology and the adoption of a balanced management framework.

The originality and value of this study lie in its exploration of the interplay between risk management and knowledge management capabilities in IUC projects. While previous studies have examined either risk management or knowledge management in IUC projects separately, this study provides a comprehensive analysis of both factors and their combined impact on project performance. The study also contributes to the literature by highlighting the specific risks and knowledge management capabilities that are most relevant to the context of IUC projects in the UAE. The practical recommendations offered by the study can help project managers and stakeholders to improve the success of collaborative innovation projects.

In the realm of innovation systems and technology transfer (TT), the emergence of open innovation and complex market dynamics has amplified innovation intermediaries’ prominence of their role and involvement in TT projects. This study delves into private consultants’ involvement in TT projects, namely in what got them involved by the project’s key stakeholders.

An iterative two-phased research approach was followed, including exploratory interviews and a quantitative case study of a consultancy firm engaged in 219 TT projects.

Five main key motivators were found to lead TT stakeholders to involve private consultants in their TT projects, being the most relevant, the proactivity of private consultants.

The case study and results provide an alternative perspective of TT endeavours, emphasising the importance given by TT stakeholders (mostly recipient companies) to private consultants’ involvement as innovation intermediaries.

The study examines the effect of human and social capital-supporting human resource (HR) practices and structural capital-supporting culture on innovativeness and the mediating role of knowledge management (KM) processes in the knowledge-intensive Indian IT sector.

Using a quantitative approach, the authors collected data from 387 employees in 30 IT organizations via a questionnaire survey. The authors analyzed data using structural equational modeling using AMOS 26.

The results indicate complete mediation of KM processes between human capital-HR (HCHRP), social capital HR (SCHRP), bureaucratic culture (BOC) space and innovativeness. KM processes partially mediated the effect of innovative-competitive culture (IOC) on innovativeness. KM processes have a robust predictive capacity for innovativeness, suggesting that human capital-supporting HR and innovative-competitive culture significantly contribute to KM Processes and innovativeness, respectively.

This study provides practical insights to HR and knowledge managers to leverage their HR practices and organizational culture for improving innovation performance in KISO.

The paper adds to the intellectual capital and KM literature by exploring the mediating role of the KM process in the underlying mechanism suggesting that intellectual capital can enhance HR and culture, leveraging a firm's knowledge resources for innovativeness. It fills a research gap by providing original evidence based on primary data collected from India's IT sector.