Search results

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 article focusses on the hybrid strategy, a simultaneous combination of cost leadership and differentiation strategy. The study aims to examine the impact of hybrid strategy on firm performance through its anticipated positive effects on process and product innovation. In addition, we study the moderating role of adaptive capacity in the direct relationships of hybrid strategy with process and product innovation.

Structural equation modelling was used to analyse 1,842 Spanish firms with fewer than 250 employees. We randomly selected small and medium-sized enterprises (SMEs) operating in Spain from the Spanish Central Business Directory (2021) database. The overall sample design was based on stratified sampling.

We found that hybrid strategy is positively related to firm performance and to process and product innovation. Additionally, in firms implementing hybrid strategies, process innovation fostered firm performance. Finally, adaptive capacity strengthened the relationships of hybrid strategy with process and product innovation. This sheds light on how and when hybrid strategy is most effective in fostering SME performance.

We highlight that SMEs need to establish strategies that use diverse resources and capabilities and not just generate competitive advantage using one strategy (cost leadership or differentiation strategy). This requires an agile and flexible systems and structures.

Our research provides novel results by proposing the adoption of hybrid strategies instead of pure strategies (cost leadership and differentiation strategy) as a way for SMEs to survive during crises. Unlike “stuck in the middle” strategies, our study demonstrates the importance of hybrid strategies in a comprehensive model that links them to innovation and firm performance, with adaptive capacity being a determining factor.

This paper aims to examine the interrelation between two innovating strategies (product and process) on total factor productivity (TFP) growth and the dynamic linkages between these strategies, for Colombia. The authors first explore whether ex ante more productive firms are those that introduce innovations (the self-selection hypothesis) and if the introduction of innovations boosts TFP growth (the returns-to-innovation hypothesis). Second, the authors study the firm’s joint dynamic decision to implement process and/or product innovations. The authors use Colombian manufacturing data from the Annual Manufacturing and the Technological Development and Innovation Surveys.

This study uses a four-stage procedure. First, the authors estimate TFP using a modified version of Olley and Pakes (1996) and Levinsohn and Petrin (2003), proposed by De Loecker (2010), that implements an endogenous Markov process where past firm innovations are endogenized. This TFP would be estimated by GMM, Wooldridge (2009). Second, the authors use multivariate discrete choice models to test the self-selection hypothesis. Third, the authors explore, using multi-value treatment evaluation techniques, the life span of the impact of innovations on productivity growth (returns to innovation hypothesis). Fourth, the authors analyse the joint likelihood of implementing process and product innovations using dynamic panel data bivariate probit models.

The investigation reveals that the self-selection effect is notably more pronounced in the adoption of process innovations only, as opposed to the adoption of product innovations only or the simultaneous adoption of both process and product innovations. Moreover, our results uncover distinct temporal patterns concerning innovation returns. Specifically, process innovations yield immediate benefits, whereas implementing both product innovations only and jointly process and product innovations exhibit significant, albeit delayed, advantages. Finally, the analysis confirms the existence of dynamic interconnections between the adoption of process and product innovations.

The contribution of this work to the literature is manifold. First, the authors thoroughly investigate the relationship between the implementation of process and product innovations and productivity for Colombian manufacturing explicitly recognising that firms’ decisions of adopting product and process innovations are very likely interrelated. Therefore, the authors start exploring the self-selection and the returns to innovation hypotheses accounting for the fact that firms might implement process innovations only, product innovations only and both process and product innovations. In the analysis of the returns of innovation, the fact that firms may choose among a menu of three innovation strategies implies the use of evaluation methods for multi-value treatments. Second, the authors study the dynamic inter-linkages between the decisions to implement process and/or product innovations, that remains under studied, at least for emerging economies. Third, the estimation of TFP is performed using an endogenous Markov process, where past firms’ innovations are endogenized.

Food sustainability is a world-acknowledged issue that requires urgent integrated solutions at multi-levels. This study aims to explore how food firms can improve their sustainability performance through digital traceability practices, considering the mediating effect of sustainability-oriented innovation (SOI) and the moderating effect of supply chain learning (SCL) for the food supply chain therein.

Hierarchical regression with a moderated mediation model is used to test the proposed hypotheses with a sample of 359 food firms from four provinces in China.

Digital traceability has a significant positive impact on the three pillars of sustainability performances among food firms. SOI (product innovation, process innovation and organisational innovation) mediates the relationship between digital traceability and sustainability performance. SCL plays moderating roles in the linkage between digital traceability and both product and process innovation, respectively.

This paper contributes as one of the first studies to develop digital traceability practices and their sustainability-related improvements for Chinese food firms; it extends studies on supply chain traceability to a typical emerging market. This finding can support food sustainability practice in terms of where and how to invest in sustainability innovation and how to improve economic, environmental and social performance.

This study attempts to explore the linkages between reliable big and cloud data analytics capabilities (RB&CDACs) and the comparative advantage (CA) that applies in the manufacturing sector in the countries located in North Africa (NA). These are considered developing countries through generating green product innovation (GPI) and using green process innovations (GPrLs) in their processes and functions as mediating factors, as well as the moderating role of data-driven competitive sustainability (DDCS).

To achieve the aim of this study, 346 useable surveys out of 1,601 were analyzed, and valid responses were retrieved for analysis, representing a 21.6% response rate by applying the quantitative methodology for collecting primary data. Convergent validity and discriminant validity tests were applied to structural equation modeling (SEM) in the CB-covariance-based structural equation modeling (SEM) program, and the data reliability was confirmed. Additionally, a multivariate analysis technique was used via CB-SEM, as hypothesized relationships were evaluated through confirmatory factor analysis (CFA), and then the hypotheses were tested through a structural model. Further, a bootstrapping technique was used to analyze the data. We included GPI and GPrI as mediating factors, while using DDCS as a moderated factor.

The empirical findings indicated that the proposed moderated-mediation model was accepted due to the relationships between the constructs being statistically significant. Further, the findings showed that there is a significant positive effect in the relationship between reliable BCDA capabilities and CAs as well as a mediating effect of GPI and GPrI, which is supported by the proposed formulated hypothesis. Additionally, the findings confirmed that there is a moderating effect represented by data-driven competitive advantage suitability between GPI, GPrI and CA.

One of the main limitations of this study is that an applied cross-sectional study provides a snapshot at a given moment in time. Furthermore, it used only one type of methodological approach (i.e. quantitative) rather than using mixed methods to reach more accurate data.

This study developed a theoretical model that is obtained from reliable BCDA capabilities, CA, DDCS, green innovation and GPrI. Thus, this piece of work bridges the existing research gap in the literature by testing the moderated-mediation model with a focus on the manufacturing sector that benefits from big data analytics capabilities to improve levels of GPI and competitive advantage. Finally, this study is considered a road map and gaudiness for the importance of applying these factors, which offers new valuable information and findings for managers, practitioners and decision-makers in the manufacturing sector in the NA region.

This paper aims to investigate sustainability-led innovation, focusing on the interplay between product and process innovation for sustainability goals and the underlying supplier–customer relationships. Thus, the paper delves into sustainability-led innovation and how it affects supplier–customer relationships, and vice versa, thus providing a twofold perspective.

The textile industry is the empirical context of this study, which is exploratory research based on in-depth, semi-structured interviews with entrepreneurs, managers and experts in the textile industry.

In the textile industry, sustainability-led product innovation concerns mainly product durability and performance, product recyclability and the use of waste for new product development. Process innovation deals with circular economy, traceability and water and chemical use minimization. The paper also shows how sustainability-led innovation is implemented in more technical terms and regarding supplier–customer relationships.

The paper adopts an original perspective on how processes take place in the relationships between suppliers and customers, where there is no dominance of one actor, but innovation emerges from interdependence and interaction. Such perspective allows to provide an in-depth analysis of the supplier–customer relationships and underlying dynamics that affect sustainability-led innovation; moreover, the authors study how such innovation impacts supplier–customer relationships and the underlying relational dynamics. The value of the paper also stands in delivering a real representation of the innovation processes grounded in the textile industry.

Manufacturers increasingly resort to digital transformation to shape their competitiveness in the digital economy era, while supply chain (SC) collaborative innovation helps them cope with market uncertainties. However, whether and how digital transformation can facilitate SC collaborative innovation remain unclear. To address this gap, we aims to investigate the effects of digital transformation (strategy and capability) on SC collaborative (process and product) innovation and market performance.

We use partial least squares-structural equation modelling (PLS-SEM) with a sample of 210 Chinese manufacturers to investigate the effects of digital transformation (strategy and capability) on SC collaborative (process and product) innovation and market performance.

The results show that digital strategy and capability positively impact SC collaborative process and product innovation, which enhances market performance. In addition, SC collaborative innovation mediates the relationship between digital transformation and market performance.

This study contributes to the literature by identifying how digital transformation drives SC collaborative innovation towards improving market performance and providing practical guidance for enterprises in promoting digital transformation and SC collaborative innovation.

Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to identify key service- and digital technology-driven B2B innovation modes and proposes a research agenda for further exploration.

This conceptual paper adopts a techno-demarcation view on service innovation, encompassing three core dimensions: service offering (the service product, or the “what”), service process (the “how”) and service ecosystem (the “who/for whom”). It delineates the implications of three digital technologies – the internet-of-things (IoT), intelligent automation (IA) and digital platforms – for service innovation across these core dimensions in B2B markets.

Digital technology has immense potential ramifications for value creation by reshaping all three core dimensions of service innovation. Specifically, IoT can transform physical resources into reconfigurable service products, IA can augment and automate a rapidly expanding array of service processes, while digital platforms provide the technical and organizational infrastructure for the integration of resources and stakeholders within service ecosystems.

This study suggests an agenda with six themes for further research, each linked to one or more of the three service innovation dimensions. They are (1) new recurring revenue models, (2) service innovation in the metaverse, (3) scaling up service innovations, (4) ecosystem innovations, (5) power dependency and lock-in effects and (6) security and responsibility in digital domains.

Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.

This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.

Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.

The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.

The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.

The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.

The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.

Digital service innovation (DSI) is a type of technological innovation that is recognized in practice in the innovation structure of companies. Given the breadth of digital technologies that enable digital services and the variety of these services, analysis is needed to discern the nature of these services, as well as the process that culminates in co-innovation. The literature on DSI is fragmented and spread across multiple research areas. This fragmentation impedes conceptualization of the elements that constitute DSI. This paper describes the nature of DSI through the process and elements of initiation, adoption and routinization of DSI in the context of digital service platforms (DSPs).

This paper presents a single exploratory case study of a provider of a leading digital solution in customer relations. The data analysis is based on abductive reasoning.

The paper conceptualizes the nature of DSI and describes the process and elements of DSI (phases, actors, functions and interactions). It contributes to building a common language for DSI research in service management. The analysis shows that DSI in DSPs is synonymous with co-innovation. This paper offers insight into how co-innovation occurs, using hybrid agile methodologies with the coordination of multiple actors and multilateral interactions.

The originality and value of the study reside in its conceptualization and analysis of what is meant by DSI. The components of the service and the technological requirements for not only provision but also ideation and development appear to be inseparable. The study unveils the mechanisms that turn a digital service solution into a co-innovative proposal. This knowledge can facilitate scalability in digital services.