International Journal of Innovation and Technology Management

Artificial intelligence (AI) is being used in our daily lives, in all situations and in particular those concerning service systems. However, there is an absence of the ability of the conceptual structure, thematic structure, intellectual structure, and research trends of AI and disruptive technologies in service systems. The main purpose of this study was to carry out a bibliometric analysis of the scientific production of AI and disruptive technologies in service systems based on Elsevier’s Scopus database. To do so, keywords were chosen and then data outputs such as the number of published documents, top authors and citations, top journals, countries, and affiliations with the highest number of productions, and network analysis using R-based “biblioshiny” software. The main results showed the growing interest in the subject in the last five years, pointed out current themes and research trends, and revealed the intellectual structure of the field, namely the importance of smart services, cloud computing, and smart sustainable cities. The number of articles for this study reached 1,323, the growth rate has increased in the last five years and the main sources have been reported. China, South Korea and the USA were the leading countries on the subject, and the top 10 authors of influence showed. The word cloud and word growth were presented, as well as the co-citation clusters and co-occurrence network revealed important aspects, and finally the thematic map and the thematic evolution of the subject showed the important concepts. It is hoped that this research will supply future directions for researchers in the area while highlighting the potential of quantitative methods.

This study aims to explore the dynamic capabilities (DCs) framework (with sensing, seizing, and reconfiguration dimensions) by exploring the fulfilment layer and underlying processes and structures employed in business model innovation (BMI) process within both new and established entrepreneurial firms. We employed exploratory and descriptive qualitative research method and gathered data through semi-structured interviews with entrepreneurs of nine firms operating in the science-park settings in Istanbul, Türkiye. This study uncovered rich insights about the DCs, as categorized in this study under 10 sub-dimensions. In addition, three different fulfilment layers of DCs emerged at the entrepreneurial firms: (i) the entrepreneurial capabilities at the individual layer, (ii) the entrepreneurial team’s complementary capabilities at the top managerial layer, and (iii) the mechanisms and routines at the organizational layer. DC sub-dimensions suggested in our study are clues for entrepreneurs to develop BMIs. Practitioners are recommended to consider their primary responsibility for BMIs processes independent of the size of the firms, to build entrepreneurial teams with partners having the complementary skill set and concentrate on the employees’ selection, as well as their adaptation to the firm routines. Additionally, the study complements Teece’s theoretical DC framework on BMI extending it into fulfilment layer and opens a fruitful research area for scholars.

The widespread permeation of social media platforms into organizations is changing the way employees communicate and work. To understand the role of enterprise social media in shaping employee job performance, we adopted the technology affordance lens to examine how various affordances of enterprise social media impact employee job performance. By conducting a multi-wave multi-source survey, we found that the association and visibility affordances of enterprise social media can enhance job performance via psychological empowerment, while the editability and persistence affordances of enterprise social media can improve job performance via structural empowerment. This study contributes new insights into the influence of enterprise social media on worker outcomes. The findings suggest that to achieve effective regulation and utilization of enterprise social media in the workplace, managers should pay more attention to its key affordances, besides the usage frequency and usage purpose of enterprise social media.

Mobile applications (apps) have grown drastically since their birth in 2008. Acquiring more app users as quickly as possible after the app is released in the app stores is one of the key rules for app developers to survive in this emerging and competitive digital market. This paper uses cumulative weekly downloading data from the US Apple App Store during a two-year period of 2015 and 2016 to study the early expansion curves and diffusion patterns of mobile apps in the app market. Downloading payment methods (free or paid to download an app) and hedonic or utilitarian value-orientated app types (games and productivity apps) are considered when we study the diffusion pattern of mobile apps. The Bass model is used as the baseline model, and the logistic model and Gompertz model are used to conduct a robustness check. Nonlinear least squares (NLS) is the measurement to obtain parameters of diffusion models. The results show that the Bass model is the best-fitting model compared with the other two models, and the diffusion pattern of mobile apps is S-shaped at the market level. The first 35 weeks are essential for the app developers to attract app users’ downloads. More app data from different app stores and more diffusion models can be tested for mobile app diffusion and early expansion patterns in future research.

Nowadays, the concept of business model is considered as a competitive advantage because of its impact on the challenges that companies face in a changing environment. Industry structure and competitive pressures are some of the external factors that play an important role in the evolution of business model innovation and determine the company’s performance. Previous research shows different results about the relationship between competition and innovation, so some researchers describe a negative relationship and others a positive relationship between these two variables. This study aims to investigate how industry evolution and competitive pressure affect the innovation intensity of a business model. Manufacturers from the pharmaceutical and food industries were selected to investigate the hypothesis. The research model was tested using structural equation modeling and partial least squares (PLS) method. The results show that innovation intensity differs among industries that undergo different evolution. Moreover, the results have shown a positive relationship between competitive pressure and innovation intensity.

In this study, we explore the factors influencing the successful IoT adoption. Based on the technology–organization–environment (TOE) theory and literature analysis, 14 propositions were formulated, and their validity was explored through three cases in the German manufacturing sector. The research shows that successful IoT adoption involves more than just introducing new technology; it requires organizational changes that create customer value through IoT solutions. Companies should anchor IoT adoption in their digitalization strategy and develop service-based business models before addressing technological aspects. A hybrid IoT adoption model, comprising organizational and technological factors, assists practitioners in preparing for IoT initiatives.

Management research has examined environmental and organizational antecedents for firms’ exploration. We complement this research by applying a network perspective to explain how firms adjust exploration strategies based on their interorganizational network positions. We particularly focus on two network constructs, closeness centrality and local cohesion. Closeness centrality captures a firm’s independent access to network knowledge and resources, and local cohesion reveals the connections between a focal firm’s associates. Combining network and survey data for 64 firms in two Norwegian regional industry clusters reveals exploration strategies’ association with network position. The positive effect of local cohesion is stronger than closeness centrality’s. Our findings indicate that network drivers act as antecedents of exploration.

The adoption of digital technology has become a critical factor in the context of innovation management. The process of digital transformation leads to the realization of concrete business improvements that promote the innovation of entire business models. So far, it has remained unexplored what drives this business model innovation, especially when looking at digitally savvy firms from the manufacturing industry. This study aims to identify the key drivers of digital transformation of business models based on a systematic literature review. A four-step review approach draws on the findings from a core sample of 51 articles from two databases and results in the description of four key drivers for digital transformation of business models, namely ubiquitous connectivity, functional dematerialization, relational decentralization, and flexible scalability. Finally, a conceptual framework of four digital business model archetypes (lighthouse supplier, service enthusiast, data scientist, and platform owner) is proposed that considers a manufacturing firm’s business model exposure to the identified digital transformation drivers. While this study is limited to theoretical findings, it likewise provokes valuable follow-up thoughts for empirical academic work and practitioners from the manufacturing industries.

This research provides empirical insights to reveal how value convergence occurs within Uber’s sharing economy. Uber’s business model is built on a digital platform that links private vehicle owners and their under-utilized assets to be economic revenue generating units for on-demand transport requests from potential clients. By analyzing adoption values for drivers and users of Uber, we identify antecedent operational and behavioral values for Uber adoption. We add to extant Industry 4.0 research and show value convergence emanating from economic and convenience motives. On the basis of our findings, we develop propositions for value convergence leveraging on cyber-physical systems embedded in Industry 4.0, and its application for theory and practice within the broader domains of the sharing economy.