International Journal of Innovation and Technology Management

The orchestration approach has been gaining prominence and relevance in recent years, due to high competitiveness in the business context and the search for more efficient strategies to promote innovation. In light of this reality, this paper conducts a systematic literature review (SLR) aiming to contribute to the emerging theme of innovation orchestration. We examined the abstracts of 761 articles and found 75 that were relevant to the topic, which was analyzed using the biblioshiny tool. These documents were published between 2006 and January 2023 and were collected from two databases, Web of Science Core Collection and Scopus. We discovered that the highest number of articles was published in 2022. Furthermore, we identified the conceptual evolution of the theme, dividing it into three periods. Through the overall thematic map, we were able to uncover niche and emerging topics such as innovation orchestration in social entrepreneurship networks, innovation orchestration in ecosystems and orchestration mechanisms. Additionally, we contribute by pointing out pathways for future studies, which is a key aspect of advancing knowledge in the field.

Although the main reason governments offer subsidies is to guide production activities and enhance the competencies of individual firms, its economic effectiveness and influential mechanism remain unclear. In this study, based on dynamic capability perspective, we introduce knowledge flows (i.e. inflows and outflows) and examine their mediation roles in the relationship between government subsidies and total factor productivity (TFP) growth. Empirical analysis is conducted using panel data from 4,335 Chinese public listed firms during the period from 2007 to 2020. The regression results show that government subsidies have a positive influence on firms’ TFP growth. Further analysis confirms that government subsidies can positively affect TFP growth by influencing both knowledge inflows and outflows. This paper enriches the current literature by involving dynamic capability theory, providing novel insights into the influential mechanisms of government subsidies. Additionally, we introduce TFP as a more comprehensive measurement to avoid bias resulting from a one-sided assessment of performance. This study also provides practical inspiration for firms to design appropriate knowledge management systems and leverage the effectiveness of government subsidies in terms of firm growth.

The rapid pace of technological change has been pushing firms to make their innovation processes more open. However, both inbound and outbound processes are complex to manage, especially for small businesses. These firms have their innovation activities constrained by missing capabilities, financial resources, and market reach. However, the existence of innovation intermediaries may overcome these issues by fostering collaboration among different stakeholders and thus bridging the gap between technological opportunities and user needs. Therefore, the aim of this paper is to analyze how collaborative spaces intermediate small business innovation. A multiple case study comprising five collaborative spaces was carried out. Results indicate how each type of collaborative space may facilitate innovation according to their intermediation roles, type of governance, main members/users, type of knowledge produced, and the core elements of attraction they offer.

Electric Vehicles (EVs) are prominent for achieving sustainable mobility in the future. By drawing on extant literature, we propose a conceptual framework and develop hypotheses based on Novelty seeking (NS), Perceived Behavior Control (PBC), Openness to new Experience (ONE), Risk appetite (RA), and Adoption Intention (AI) of consumers in ABMs. The analysis of data reveals that both NS and PBC are positively related to the ONE which, in turn, impacts the AI of EVs in ABMs in a significantly positive manner. The study also proves that RA moderates the relationship between ONE and AI in such a manner that a higher level of RA makes the relationship between ONE and AI stronger. We contribute to the literature on sustainable mobility by exploring the role of psychological factors in determining AI of Indian customers towards EVs in ABMs and the study has important implications for researchers, practitioners, and policymakers.

This paper aims to propose a model based on blockchain and cloud computing technologies to support lean production techniques for industrial supply chain management, evaluating how the combination of these technologies provides improvement in the chain performance. The literature review contextualizes the state of the art in studies related to the application of blockchain technology to lean manufacturing processes, as well as identifies research gaps in this field. Besides, this study models and simulates an architecture based on both the Hyperledger Fabric network and a virtual machine in the cloud environment, assessing its applicability and performance in the industrial supply chain. The analysis addresses lean aspects identified as research gaps, including integration of stakeholders in the collaborative production of customized products, conditions of flexibility and adaptability to demand variations, coordinated relationship of networks involving small and medium-sized enterprises, and behavior of various players acting simultaneously and consensually. The proposed model reveals a decentralized and nonlinear information sharing concept that demonstrates a logic of simultaneous participation of all players involved in the supply chain. The low costs and processing times identified in the simulation indicate the robustness of the system even in transactions involving a large number of companies and a large amount of data. This architecture offers an integration solution between stakeholders to support operational processes, providing insights for researchers and specialists in the adoption of innovative, reliable and inclusive information technologies for companies of different sizes or levels of development, with a focus on lean manufacturing, reduction in resource consumption and cost reduction. The developed model, which combines blockchain and cloud computing technologies applied to stages of lean production systems, presents a differentiated solution on the planning of integrated production systems, indicating the differential in this work.

To stay competitive in today’s environment, characterized by changing customer requirements, digitalization, new technologies, etc., companies must deliver fast and continuous innovation. Manufacturing companies have therefore started to launch large-scale agile transformation initiatives. A specificity of manufacturing companies is their need for deeply specialized organizational units. Knowledge boundaries resulting from knowledge specialization tend to impact transformation initiatives. Therefore, this work examines the implications of knowledge boundaries between organizational units for a large-scale agile transformation initiative of a manufacturing company. The findings show that these knowledge boundaries imply a need for knowledge integration based on flexibility and dynamism as key aspects. A conceptual model that illustrates these aspects during the initial phase of implementation of these transformation initiatives is presented.

Successful implementation of disruptive innovation involves numerous challenges, especially for new entrants. This study tries to identify and analyze a set of critical challenges that might plague a new entrant to successfully implement disruptive innovation. Multicriteria decision-making (MCDM) technique of Interpretive Structural Modeling (ISM) was used to analyze the identified challenges, as well as to derive their interrelationship. The study was conducted in the context of the Indian manufacturing sector. The findings revealed that the lack of financial resources, lack of non-financial resources, and lack of top management support emerged as the three key challenges impeding disruptive innovation for manufacturing organizations in India. The motivation–opportunity–ability (MOA) model served as the basic theoretical underpinning for the study. The findings of the study are expected to help managers and policymakers to understand possible challenges associated with the implementation of disruptive innovation, and to develop counter strategies accordingly.

This study analyzes the drivers and constraints affecting enterprise capacity utilization (CU) in the Middle East and North Africa (MENA) region. We used data from the World Bank Enterprise Survey and a fractional logit model to examine the impacts of institutional, infrastructural, and sustainability factors on firms’ CU. Our analysis highlights corruption and competition in the informal sector as significant impediments to firms’ CU, alongside complex infrastructure barriers that hinder the optimization. Conversely, environmental responsibility and innovation emerge as critical drivers for enhancing CU. Surprisingly, top managers’ experience introduces a counteractive influence that negatively affects CU. Beyond the empirical findings, this study’s implications extend to various stakeholders, notably policymakers. Emphasizing the need to address corruption, foster an enabling business environment, strategically invest in infrastructure, promote sustainability initiatives, and foster innovation to enhance CU are paramount. Additionally, providing targeted managerial training to mitigate negative managerial influences is crucial. Implementing these recommendations promises to foster an environment conducive to improved CU, driving economic growth, and sustainable development in the MENA region and benefiting stakeholders across sectors.