International Journal of Innovation and Technology Management

The importance of leadership is increasingly recognized in relation to digital transformation. Therefore, middle management and top management must have the competencies required to lead such a transformation. The purpose of this paper is to investigate the relationship between the digital leader competencies as set out by the European e-competence framework (e-CF) and the digital transformation of organizations. Also, the relationship between digital leadership competency (DLC) and IT capability is examined. An empirical investigation is presented based on a sample of 433 respondents, analyzed using PLS-SEM. The results strongly support our hypotheses. DLC has a strong impact on organizational digital transformation. A post-hoc analysis showed this is predominantly the case for the e-CF competencies of business plan development, architecture design, and innovating while business change management and governance do not seem to affect organizational digital transformation. This is the first empirical study to conceptualize, operationalize and validate the concept of DLC, based on the e-competence framework, and its impact on digital transformation. These findings have significant implications for researchers and practitioners working on the transformation toward a digital organization.

In order to achieve successful open innovation partnerships, small- and medium-sized enterprises (SMEs) need to choose very carefully whom they partner with. Open innovation has gained significant attention as a strategy for organizations to leverage external knowledge and resources to foster innovation and competitiveness. However, few studies have examined the dynamics of open innovation partnerships between startups and SMEs. This study adopts a qualitative research approach, employing multiple case studies to gather data. We mapped the reasons German medium-sized enterprises chose to partner with startups, enumerated the benefits and challenges they encountered during the projects, and uncovered the keystones of successful open innovation partnerships. Furthermore, our findings led to the discovery that startups can help SMEs to become more digital. Finally, we suggest future research topics in this field.

Even though Indonesia has a large number of hospitals and has experienced significant progress in realizing Universal Health Coverage (UHC), service performance is still relatively low, so many patients seek treatment abroad. The performance of services and care systems in hospitals is often associated with low use of digital technology. The complexity of adopting digital technology in a hospital environment is not an easy thing to do, with the majority of users carrying out digital technology functions being health officers and professionals. This research aims to explore the influence of Digital Leadership in encouraging the adoption of digital technology and its influence on Hospital Performance. Survey data conducted on 285 leaders of Class C and D hospitals spread throughout Indonesia, through Structural Equation Modeling (SEM) analysis using Lisrel 8.80, it was found that there was a positive and significant influence on the role of Digital Adoption Capability as a mediation on Hospital Performance. It was found that Digital Leadership has a positive and significant influence on hospital performance both directly and through the mediation of Digital Adoption Capability. Environmental Dynamism factors have also been proven to significantly influence hospital management’s desire to improve performance through the adoption of digital technology. The model resulting from this research provides a comprehensive view of hospital management in developing effective digital technology adoption strategies in facing an ever-changing environment.

Innovative firms are threatened by price-based generic competition, particularly following patent expiration. To combat the so-called “patent cliff” that occurs at patent expiry, some firms are turning to a strategic approach known as value transference. This integrative intellectual property strategy involves transferring the value of a limited life right, such as from a patented invention, to other forms of intellectual property rights, like trademarks. If utilized appropriately, these trademarks can preserve this value indefinitely. The theoretical considerations in my study suggest that an integrated intellectual property rights strategy can enhance financial performance following generic entry. With this paper, I derive propositions to model this effect of strategic intellectual property rights integration. Further, my model extends the analysis of value transference to successor products. It indicates that expanding intellectual property integration strategies beyond its original boundaries to successor offerings amplifies this positive effect. Further, time is identified as imperative for successful intellectual property integration.

This study aims to analyze the opportunities and main directions of international cooperation for the activation of startups. To achieve this goal, the authors developed and implemented a comprehensive multi-stage research project based on a quantitative approach. The research used both the results of statistical observations and primary information obtained by online questionnaires. The questionnaires involved economically active people demonstrating an active interest in the organization of startups (408 questionnaires). The results of study may be valuable for public administration specialists in the field of innovation and entrepreneurship, specialists in business incubators and venture funds, as well as academic researchers.

The manufacturing Industry in Europe plays a significant role in economic growth and development. Given the increased role of technology in this sector, the Industrial Internet of Things (IIoT) is one of the technological advancements that improve the Business Model (BM) efficacy in various manufacturing industries. However, research into the role of IIoT as a BM in the manufacturing industry is limited despite its contribution to the success and performance of the firms. Therefore, this study explores the role that IIoT plays as a BM in various manufacturing industries. A survey was conducted utilizing open-ended questionnaires across 60 manufacturing firms in Europe including automotive suppliers, information and communication, machine and plant engineering, electrical engineering, and medical engineering. The findings indicate that IIoT as a BM has different levels of contribution across the manufacturing industry with glaring variations in terms of performance between information and communication firms as well as automotive. This study can act as a guideline for further research on the complex relationship between IIoT as a BM and firms’ performance to influence decision-making processes within the manufacturing industry. Given that this is a pre-study, the limitations, and recommendations for future research are highlighted.

In recent years, many companies have been involved in the development of machine learning systems. However, developing machine learning systems presents unique challenges compared with the traditional IT system development. In software engineering, research has been conducted on software development methodologies for machine learning systems, but most of these studies focused on the development process of individual machine learning systems, and limited research has investigated the exploitation process of continuously enhancing machine learning systems after their development and deployment. Thus, this paper focuses on the exploitation process, in which the collaboration between the machine learning systems and humans evolves gradually. Specifically, four stages of the exploitation process are proposed: visualization for machine learning, human-centered machine learning assistance, machine learning-centered human assistance, and autonomy without human involvement. Then, the characteristics and challenges of each stage are clarified. In addition, this paper examines the important aspect of trust in this context. The findings of this study are expected to provide guidelines for advancing machine learning systems incrementally in collaboration with humans from the perspective of the exploitation process rather than focusing on the development process.

Despite the increased confidence in e-commerce, consumers remain skeptical when shopping online and therefore rely on electronic word-of-mouth generated by other consumers to aid their brand or store choice. Because eWOM can have detrimental or beneficial effects on brands and is beyond the control of firms, measuring the extent to which consumers use this information source to inform their decisions is a major challenge facing scholars and practitioners. This study examines the influence of eWOM on customers’ behavioral intentions and tests the role of brand familiarity. Five hypotheses are developed and tested based on the accessibility-diagnosticity theory and the elaboration likelihood model. A sample of 432 participants was recruited from a university in Southeastern Nigeria to participate in a $2\times 3$ between-subject factorial experiment. The results show that the positive or negative sentiments conveyed in eWOM messages and the familiarity of a brand affect customers’ behavioral intentions independently, and that the volume of eWOM messages interacts with brand familiarity to impact these behavioral intentions such that unfamiliar brands benefit more from high volume than familiar retailers do. The implication is that firms can overcome the problem of familiarity and performance risk by motivating and displaying as many eWOM communications as possible in their social media and advertisements.