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This paper conceptually aims to discuss the dual role of knowledge management (KM) and technological innovation, which brings about innovations, although it can be limited by psychological and emotional ownership.

This study examines the real impact of the paper on KM and technological innovation in family small to medium enterprises (FSMEs). This is a unique context affected by psychological and emotional ownership. However, COVID-19 has forced FSMEs to consider new strategies and practices to preserve their competitive advantage.

In this scenario, knowledge exchange, knowledge absorption and technology adoption appear relevant to the innovation process. This study offers a framework for how the duality of KM and technological innovation affects innovation.

Although extant research has explored technological innovation outcomes, a literature review reveals that accumulated studies on the drivers of technological innovation and KM in the context of FSMEs require further inquiry. Family members’ emotional ownership may foster KM because identification with organizational goals enhances individuals’ willingness to access and share information and stimulates new products and technological development.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

This study aims to analyse the intellectual property rights (INPR), foreign direct investment (FDI) inflows and technological exports of 32 developing and developed countries for the period of 2006–2020.

Diagnostic tests were used to confirm the panel least squares, fixed effect, random effect, feasible general least squares, dynamic ordinary least squares and fully modified ordinary least squares estimator results as well as to increase the robustness.

According to the findings for the developing countries, trademark, patent and industrial design applications, each had a significant positive long-run effect on FDI inflows. In addition, there was a significant positive long-run relationship between patent applications and medium- and high-technology exports. Meanwhile, trademark and industrial design applications had a significant negative long-term effect on medium- and high-technology exports. In developed countries, patent and industrial design applications each have a significant negative long-term on medium- and high-technology exports. Furthermore, patent and trademark applications each had a significant negative long-run effect on FDI inflows.

This study contributes significantly to the focus that host countries evaluate the technology gaps between domestic and foreign investors at different industry levels to select the best INPR rules and innovation process by increasing international cooperation. Furthermore, the host countries should follow the structure–conduct–performance paradigm based on analysis of the market structure, strategic firms and industrial dynamics systems.

This study aims to investigate the influence of information and communication technology (ICT) capabilities on supply chain fraud and sustainability within the context of Ghana’s small and medium-sized enterprises (SMEs). Additionally, the research explores the mediating role of supply chain fraud in the relationship between ICT capabilities and supply chain sustainability.

Data were collected from 102 respondents within Ghana’s SME sector, and the research employed the dynamic capability theory as the conceptual framework. The study utilized partial least squares-structural equation modeling (PLS-SEM) to develop and analyze the proposed model.

The results of the study reveal a significant reduction in supply chain fraud attributable to enhanced ICT capabilities within Ghanaian SMEs. Moreover, ICT capabilities exert a significant positive influence on supply chain sustainability. Importantly, supply chain fraud emerges as a mediator, elucidating its role at the nexus of supply chain sustainability and ICT capabilities.

This research contributes to the limited body of evidence on the interconnectedness of ICT capabilities, supply chain fraud and supply chain sustainability, particularly within the context of Ghanaian SMEs. Notably, this study pioneers an examination of the mediating impact of supply chain fraud on the relationship between ICT capabilities and supply chain sustainability.

Effective green supply chain management (GSCM) has become a potentially valuable tool of securing competitive advantage and improving operational performance (OP) as competition is no longer exists between the firms but within green supply chains. The aim of this empirical study is to determine the link between GSCM practices (GSCMPs) and OP within the manufacturing sector of Bangladesh mediated by perceived competitive advantage (PCA). GSCMPs were divided into three further dimensions: green eco-design (GED), green supply chain partnering (GSCP) and internal green orientation (IGO).

The study selected 376 individuals as respondents who work as the top-level managers and the members of the Board of Directors at different Bangladeshi manufacturing firms through purposive sampling. A partial least square-based structural equation modeling (PLS-SEM) was utilized to identify the relationships between the three dimensions of, GSCMPs, and the single dependent variable, OP.

The study identified that two factors, GED and GSCP, have significant positive relationships with OP. On the other hand, another factor, IGO has a statistically insignificant relationship with OP. Regarding the mediating effects, the study identified that PCA can fully mediate the insignificant relationship between IGO and OP, and partially mediate the significant relationship between GSCP and OP. On the contrary, PCA has no mediating effect on the relationship between GED and OP.

This empirical study is an effort that examined the role of GSCMPs on the OP in the Bangladeshi manufacturing context. It is believed that this empirical investigation will prompt future theoretical studies and empirical experiments to enrich academia. Further, the findings of this study can serve as foundational guidance for policymakers and/or managers studying the formulation and implementation of GSCMP-related policies and strategies.

This study aims to answer the question of how incumbent firms cultivate dynamic capabilities through knowledge management so that they can efficiently adapt to the changing external environment.

This study adopts a case study approach and collects data through interviews and secondary public information on the lighting industry and two lighting firms in Lin'an, China. It qualitatively examines the challenges and strategic recommendations for incumbent firms in the context of discontinuous technological change from a knowledge management perspective.

Incumbent firms often face a variety of challenges when responding to discontinuous technological change. These challenges include identifying opportunities, overcoming path dependence and dealing with employee resistance to change. To overcome these difficulties, three strategies have been proposed to enhance the dynamic capabilities of incumbent firms through knowledge management: cross-border search helps firms improve their knowledge acquisition capabilities and better understand their environment to identify opportunities; building strategic leadership overcomes path dependence and improves knowledge integration capabilities; organizational learning deepens employees’ understanding of change and enhances organizational knowledge application capabilities.

Previous research attributes a firm's ability to cope with discontinuous technological change solely to its general resources, which weakens the importance of knowledge management in this context. This study emphasizes the importance of knowledge as a crucial strategic resource in developing the essential dynamic capabilities for incumbent firms to cope with discontinuous technological change.

This study provides an in-depth analysis of incumbent firms' coping strategies in the new context of discontinuous technological change and further promotes cross-disciplinary research.

This study provides an in-depth analysis of coping strategies in the new context of discontinuous technological change, furthermore theoretically advancing the interdisciplinary research of firm transformation and knowledge management. Meanwhile, it is crucial to identify the preconditions for cultivating dynamic capabilities, especially from a knowledge-based view, which enhances the depth of knowledge management research.

This study aims to examine how the knowledge breadth and depth of a patent affect its likelihood of being pledged. It also seeks to explore whether these relationships change diversely in different technological environments.

A complementary log-log model with random effects was conducted to test the hypotheses using a unique data set consisting of 348,927 invention patents granted by the China National Intellectual Property Administration from 1985 to 2015 belonging to 74,996 firms.

The findings reveal that both knowledge breadth and depth of a patent positively affect its likelihood of being pledged. Furthermore, the knowledge breadth and depth entail different degrees of superiority in different technological environments.

This study focuses on the effect of an individual patent’s knowledge base on its likelihood of being selected as collateral. It does not consider the influence of the overall knowledge characteristics of the selected patent portfolio.

Managers need to pay attention to patents’ knowledge characteristics and the changes in technological environments to select the most suitable patents as collateral and thus improve the success rate of pledge financing.

This study explores the impact of multidimensional characteristics of knowledge base on patent pledge financing within a systematic theoretical framework and incorporates technological environments into this framework.

This study aims to develop a model of learning-by-hiring in which knowledge gains may occur at the time of recruitment but also after recruitment when other incumbent organizational members assimilate a recruit’s knowledge. The author’s model predicts that experienced recruits are more likely to catalyze change to their organization’s core technological capabilities.

The continuous-time parametric hazard rate regressions predict core technological change in a long panel (1970–2017) of US biotechnology industry patent data. The author uses over 140,000 patents to model the evolution of knowledge of over 52,000 scientists and over 4,450 firms. To address endogeneity concerns, the author uses the Heckman selection method and does robustness tests using a difference-in-difference analysis.

The author finds that a hire’s prior research and development (R&D) experience helps overcome inertia arising from her or his new-to-an-organization “distant” knowledge to increase the likelihood of core technological change. In addition, while the author finds that incumbent organizational members resist technological change, experienced hires may effectively induce them to adopt new ways of doing things. This is particularly the case when hires collaborate with incumbents in R&D projects. Understanding the effects of hiring on core technological change, therefore, benefits from an assessment of hire R&D experience and its effects on incumbent inertia in an organization.

First, the author does not recommend managers to hire scientists with considerable distant knowledge only as this may be detrimental to core technological change. Second, the author recommends organizations striving to effectuate technological change to hire people with considerable prior R&D experience as this confers them with the ability to influence other members and socialize incumbent members. Third, the author recommends that managers hire people with both significant levels of prior experience and distant knowledge as they are complements. Finally, the author recommends managers to encourage collaboration between highly experienced hired scientists and long-tenured incumbent organizational members to facilitate incumbent learning, socialization and adoption of new ways of doing things.

This study develops a model of learning-by-hiring, which, to the best of the authors’ knowledge, is the first to propose, test and advance KM literature by showing the effectiveness of experienced hires to stimulate knowledge diffusion and core technological change over time after being hired. This study contributes to innovation, organizational learning and strategy literatures.

High-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.

This paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.

The findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.

This study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

Effective inventory management is crucial for SMEs due to limited resources and higher risks like cash flow, storage space, and stockouts. Hence, the aim is to explore how technology and know-how can be integrated with inventory practices and impact operational performance.

The basis of the analysis was collecting papers from a wide range of databases, which included Scopus, Web of Science, and Google Scholar. In the first phase of the process, a search string with as many as nine related keywords was used to obtain 175 papers. It further filtered them based on their titles and abstracts to retain 95 papers that were included for thorough analysis.

The study introduced innovative methods of measuring inventory practices by exploring the impact of know-how. It is the first of its kind to identify and demonstrate how technical, technological, and behavioral know-how can influence inventory management practices and ultimately impact the performance of emerging SMEs. This study stands out for its comprehensive approach, which covers traditional and modern inventory management technologies in a single study.

The study provides valuable insights into the interplay between technical, technological, and behavioral know-how in inventory management practices and their effects on the performance of emerging SMEs in Industry 5.0 in the light of RBV theory.

The RBV theory and the Industry 5.0 paradigm are used in this study to explore how developing SMEs' inventory management practices influence their performance. This study investigates the effects of traditional and modern inventory management systems on business performance. Incorporating RBV theory with the Industry 5.0 framework investigates firm-specific resources and technological advances in the current industrial revolution. This unique technique advances the literature on inventory management and has industry implications.