Journal of Innovation & Knowledge最新文献

This study examines the influence of participative leadership and cultural factors on employees’ speaking-up behaviour and knowledge-sharing in supplier development initiatives in the garment industry. Specifically, this study investigates the impact of leadership effectiveness, cultural dimensions, and individual characteristics using surveys and interviews. Our findings indicate that participative leadership positively correlates with employee speaking-up behaviour. However, the analysis of variance (ANOVA) results show that language proficiency and region significantly influence employees’ willingness to speak up, although the differences in knowledge-sharing scores across cultural groups are statistically insignificant. Mediation analysis further reveals that perceived leadership effectiveness partially mediates the relationship between participatory leadership and knowledge-sharing intentions. The interview findings provide deeper insights into the roles of cultural intelligence, communication barriers, and social identity in shaping knowledge flow. These findings offer practical implications for organisations seeking to enhance supplier development initiatives. To foster an inclusive environment that empowers employee voice and encourages collaborative knowledge sharing, organisations can adopt participative leadership, accommodate cultural and linguistic diversity, and promote effective leadership perceptions. We anticipate that future research will explore the generalisability of these findings across industries and examine additional cultural dimensions that influence knowledge-sharing dynamics.

Higher education plays a central role in the current digital revolution. This sector is experiencing a constant process of digital transformation (DT) that is expected to produce substantial instabilities in the currently used business tools. However, the literature still lacks research investigating how the business tools are innovated from the perspective of “higher education institutions (HEIs)” while considering the impact of DT on this process. To deal with the concern, this paper identifies the major impressions of DT on the business model provided by HEIs, using means of a fuzzy decision-making tool. To this end, the current paper integrated three previously-proposed methods, i.e., the “intuitionistic fuzzy sets (IFSs)”, the “method based on the removal effects of criteria (MEREC)”, the “rank sum (RS)”, and the “additive ratio assessment (ARAS)” into a new decision-making framework called IF-MEREC-RS-ARAS. In the proposed hybrid method, IF-MEREC-RS is responsible for computing the objective-subjective weighting of the key DT challenges that arise for “business model innovation (BMI)” in the perspective of HEIs. In addition, IF-ARAS evaluates the HEIs’ preferences over various DT challenges for BMI in the context of HEIs. This research also involves an empirical case study for the assessment of the major DT challenges that arise for BMI in HEIs. To end, a number of comparisons and sensitivity discussions were carried out to compare the performance of the introduced model with that of other models. The findings confirmed the higher effectiveness of the developed model in terms of the tasks defined.

Official online stores and online marketplaces present distinct challenges and opportunities for retail brands, impacting their control over the customer experience, pricing, and brand presentation. Understanding consumer intentions in online channel selection is crucial, especially given the rise of online shopping and the impact of the COVID-19 pandemic on consumer behavior. This study explores the factors influencing channel selection intention within official online stores and online marketplaces, focusing on customers who have purchased Apple electronics. A quantitative questionnaire facilitated data collection, resulting in responses from 490 individuals and 606 samples. Those who shopped through both channels were requested to complete the questionnaire twice. The respondents were divided into two groups based on their purchasing experience, and structural equation modeling was employed for hypothesis testing. In official online stores, cross-channel searching negatively impacts channel selection intention, whereas brand loyalty and channel pricing advantage have positive effects. In contrast, no significant relationships between these variables were observed in online marketplaces. Channel satisfaction was found to positively influence channel selection intention across official online stores and online marketplaces, while perceived risk demonstrated a negative impact. Based on these findings, several recommendations are proposed to aid in developing effective sales channel strategies.

Research on the correlations between design leadership, work values and ethics, and workplace innovation is lacking, especially in non-Western regions. This study aimed to investigate the mediating role of design leadership in the relationship of work values and ethics with workplace innovation in Asian small- and medium-sized enterprises (SMEs). Five hypotheses were established to explore the proposed model. Data were obtained from 995 SMEs in Japan, Thailand, China, and Vietnam and were examined using partial least squares analysis. The findings indicated a correlation between work values and ethics and design leadership, with the latter influencing workplace innovation across its four dimensions. This demonstrated the significant association between work values and ethics and workplace innovation. Design leadership was also shown to fully mediate the relationship between work values and ethics and workplace innovation in Asian SMEs. This study provides a deeper understanding of the emerging literature on the associations of design leadership, work values and ethics, and workplace innovation. It emphasizes the importance of design leadership and its correlations with various aspects of workplace innovation and work values and ethics, which have not received adequate attention in the existing literature. Asian SME entrepreneurs can improve the innovation capabilities of their organizations by focusing on and implementing design leadership behaviors, which may thereby help their organizations establish a competitive advantage and promote long-term sustainability.

This study exposes relevant tensions between deep-tech startups’ sound technological solutions, confronted with lack of marketing skills to communicate their unique value proposition for targeted customers. Incorporating technological foresight as an essential component of strategic foresight, this study explores how the interplay between firm internal technological, environmental, and market features influences enhanced foresight capabilities. The model is tested with Partial Least Square-Structural Equation Modelling (PLS-SEM) and uses survey data from managers of European deep-tech companies. PLS-SEM findings reveal a significant correlation between market features, tech features and environmental features jointly influencing enhanced foresight capabilities. The strong correlation between tech features and enhanced foresight capabilities give promising insight for upgrading this managerial capability as it influences successful scaling from laboratory to pilot customers. In turn, the lack of correlation between firm internal features and enhanced foresight capabilities proves that rapid technological advances outpace market readiness or customer adoption, claiming to replace “learning from the past” with “learning from the future”. The findings enrich the current body of knowledge, while the practical implication highlights how enhanced foresight capabilities enable deep tech firms to leverage technology dominance with desirable business agility, in order to adopt a virtuous cycle of capturing-market maker opportunities towards a future shaping builder.

Artificial intelligence (AI) technology has significantly transformed corporate behavior in the energy sector by enhancing the capacity and efficiency of information transmission and big data analysis. However, there is still a limited understanding of how AI influences new market entry mode strategies in overseas energy investments. Drawing on information processing theory, we propose that firms with advanced AI technology exhibit superior data processing capabilities, which can help energy companies mitigate the uncertainties associated with entering a foreign market and encourage them to choose a wholly-owned entry mode. We further hypothesize that the state ownership of firms, the political affinity between home and host countries, and the risk preferences of firm executives serve as moderating factors. Using a sample of Chinese-listed multinational firms in the energy sector from 2010 to 2021, our empirical results strongly support these predictions. These findings contribute to the emerging and crucial literature on the impact of AI technology on firms’ overseas investment behavior, particularly in the energy sector.

Social Customer Relationship Management (SCRM) has revolutionized the interaction between companies and customers, creating new opportunities and challenges for both parties. This study aims to present an innovative model for identifying the dimensions and components of SCRM. The data were collected based on a qualitative research design utilizing the meta-synthesis method, following the seven steps outlined by Sandelowski and Barroso (2007). Considering the relevance to the research topic and the quality of sources, 31 studies were selected for the final evaluation. To assess the reliability of the findings, the kappa coefficient for inter-coder agreement was used, resulting in a kappa value of 0.79. The results, analyzed using MAXQDA20 software, 2 dimensions, 6 categories, and 16 concepts identified. The company-focused dimension included 3 categories: factors influencing adoption, inhibitors, and outcomes of implementation. Similarly, the customer-focused dimension identified 3 categories: factors influencing adoption, inhibitors, and outcomes of implementation. Ultimately, a comprehensive model for SCRM was developed. The results of this research can be utilized by academic references as well as companies and consumers.

The subject of this article is an analysis of the hackathon concept as an educational approach and its role in the development of students' knowledge and skills. The goal is to conduct an in-depth examination of the effectiveness and achievements of the hackathon, with special reference to the attitudes of students and teachers involved in this educational methodology. The key emphasis is placed on participants' perception of the possibilities of hackathons providing long-term results and hackathons' impact as an educational format. Through a specific blockchain hackathon jointly organized by the University of Belgrade, Serbia, and the University of Florida, USA, the research examines participants' perspectives and their expectations, experiences, and overall impressions. The research focuses on the readiness of hackathon participants to incorporate new technical skills through this form of learning, knowledge acquisition, attitudes, and motivational drivers. Furthermore, the research examines how participants' views change before and after the event. The paper contains the insights of educators who, relying on their experiences at the hackathon, emphasize the importance of measuring and monitoring the outcome of the hackathon. Their perspectives highlight the motivation for promoting experimental learning methods in academic settings. This comprehensive research sheds light on multiple impacts of hackathon participation, which extend beyond knowledge acquisition to include changes in technological interests, success in specific domains, and the broader implications of hackathons as a transformative learning experience. The research contributes to the ongoing discussion about innovative approaches to learning. It provides a foundation for a better understanding of how hackathons shape attitudes and contribute to long-term outcomes for both students and teachers, establishing a conceptual framework for hackathon-based learning approaches and opportunities to monitor the effects of hackathons.

The essence of the evolution of the green innovation ecosystem is the process by which the positive strategy of green innovation spreads in a complex network. In this study, the "Object-Technology-Environment-Management-Culture (OETMC)" structure paradigm of innovation ecosystems is presented, and a causal analysis framework of green innovation ecosystem evolution based on green innovation behavior strategy, supported by green innovation efficiency and focused on green innovation ecosystems is developed. Based on this framework, the structure of the green innovation ecosystem and the diffusion process of positive green innovation in the network are discussed. The results reveal the following. (1) The complexity of the green innovation ecological network has visibly improved, but numerous blank connections remain. These are the key constraints that hinder structural evolution. (2) The appearance of a large number of long-range connections weakens the constraint of geographical distance but also hinders edge nodes from joining the network. (3) The existence of preference attachment and power law distribution of the green innovation ecological network leads to the incomplete convergence of positive green innovation strategy at any initial strategy ratio. (4) Default cost and pollution tax rate ensure the enthusiasm of green innovation actors to seek innovation cooperation by increasing opportunity costs, thus accelerating the formation and reconstruction of the green innovation ecological network. These conclusions provide a decision-making reference for governments to encourage green innovation subjects to formulate targeted policies.

There is a growing recognition that firms increase their collaboration breadth by opening their boundaries to more innovation partners, sourcing and integrating complementary knowledge, skills, and resources and, in turn, improving their innovation performance. However, not all firms benefit equally from collaboration breadth. We argue that the literature has not considered important contingency factors that can mitigate such benefits. This paper enhances understanding of the relationship between collaboration breadth and innovation performance by contending, and empirically confirming, that the magnitude and direction of this association depend on the type of constraints the firm faces. Drawing on organizational learning theory, it is argued that firms encountering financial, knowledge, and institutional innovation constraints will compromise the effects of their openness. The empirical findings suggest that innovative firms face challenges balancing trade-offs between a broad collaboration network and high financial, knowledge, and institutional constraints.