Search results

Organizations increasingly use knowledge arbitrage to stimulate innovation and achieve competitive advantage. However, in knowledge management its use in startups is yet unexplored. This study aims to examine the utilization of knowledge arbitrage by startups, specifically during COVID-19.

This study employed an open-ended essay methodology to explore the drivers and barriers that startups face in utilizing knowledge arbitrage. We collected data from 40 participants to understand the role of knowledge arbitrage in startups’ knowledge management practices.

This study’s findings highlight the significance of knowledge arbitrage for startups. The benefits identified include organizational benefits such as building networks, innovating new products and achieving competitive advantage and financial benefits such as cost reduction and sales growth. The study also identifies several technological and organizational drivers and barriers that startups confront during knowledge arbitrage.

This study contributes to the existing literature on knowledge management by extending our understanding of knowledge arbitrage’s role in startups. Additionally, it sheds light on the importance of knowledge arbitrage for startups and the challenges they face, particularly in a disrupted environment reared by COVID-19. The study provides insights for the scholars and practitioners interested in effective knowledge management in startups.

The aim of this research is to elucidate the correlation between open innovation, digital strategies and networking in enhancing agricultural enterprises within the new perspective of Agrifood 5.0. As such, it contributes to making businesses more competitive, especially in the Italian agricultural sector, where small and medium-sized enterprises are highly fragmented. Numerous studies have asserted that the competitiveness of actors operating within a specific territory is closely linked to local identity and image enhancement. Agricultural organizations are undergoing a profound transformation, with technological assets emerging as catalysts for new synergies. Advanced technologies such as robotics, the Internet of Things (IoT) and automation (AI) are emerging as differentiating elements capable of further advancing the agricultural sector, transitioning it from Agrifood 4.0 to Agrifood 5.0. The empirical analysis of the research shows a positive correlation between a collaborative attitude and a propensity for innovation. Indeed, the data demonstrated that digital strategies and open innovation positively influence competitiveness in agricultural SMEs.

The methodology employed in this study is mixed, incorporating both qualitative and quantitative approaches. The quantitative aspect involves analysis of the dataset from the Italian Statistical Institute (ISTAT) through logistic regression, while the qualitative component entails analysis of semi-structured interviews conducted with a sample of 174 agricultural cooperatives in southern Italian regions (Campania). This approach allows for a comprehensive understanding of the research topic, capturing both numerical trends and nuanced insights from interviews.

After analyzing the data from the 7th General Census of Agriculture conducted by ISTAT, a clear understanding of the sector has emerged, revealing several potential research avenues. It is evident that innovation in the agricultural sector is often driven by the largest and best-capitalized production entities, primarily located in Italy. Conversely, smaller agricultural entities can benefit from networking as new technological assets act as catalysts for new synergies, innovation and competitiveness.

Enhancing the relational contribution within the network and humanizing a fragmented sector are crucial elements for promoting open innovation. Network structuring facilitates the transmission of managerial knowledge, contributing to an overall increase in the intellectual and relational capital of the agricultural sector. These factors, combined with open innovation, enhance the competitiveness of individual firms and elevate the brand of the entire sector, creating a conducive environment for transitioning toward Agrifood 5.0. This transition is characterized by increased interconnection, continuous innovation and overall prosperity. Specific studies on this topic are lacking in Italy, particularly in the southern regions. Therefore, this contribution focuses on investigating the Campania region.

The novelty of this study lies in its investigation of the relationship between agricultural enterprises and innovation in the context of enterprises networking strategies (i.e. associationism and/or cooperation), promoting competitiveness. The limitations of this study are related to the dimension of the sample selected and its relationship with other productive sectors.

The purpose of this study is to explore the means by which exporters foster innovation via the learning-by-exporting effect and to appraise the moderating role of employee human capital in the export–innovation relationship.

Leveraging the linked-survey-secondary data from the Human Capital Corporate Panel (HCCP) spanning 2011–2017, with 890 observations from 228 Korean exporters, this study utilizes Generalized Least Squares (GLS) regression to empirically test the proposed hypotheses.

The results indicate that exporting significantly boosts a firm’s innovation performance by encouraging the generation of new concepts in products, services, technologies and/or production lines. Moreover, the presence of international talent and highly educated staff positively moderates the relationship between export intensity and innovation performance.

By integrating organizational learning and human capital theories, this study yields theoretical and managerial insights by elucidating the roles of exporting and human capital in advancing innovation performance, thereby guiding corporate export strategies and human resource policies.

Disruptive events caused by cyber incidents, such as supply chain (SC) cyber incidents, can affect firms’ SC operations on a large scale, causing disruptions in material, information and financial flows and impacting the availability, integrity and confidentiality of SC assets. While SC resilience (SCRES) research has received much attention in recent years, the purpose of this study is to investigate specific capabilities for building SCRES to cyber risks. Based on a nuanced understanding of SC cyber risk characteristics, this study explores how to build SC cyber resilience (SCCR) using the perspective of dynamic capability (DC) theory.

Based on 79 in-depth interviews, this qualitative study examines 28 firms representing 4 SCs in Central Europe. The researchers interpret data from semistructured interviews and secondary data using the DC perspective, which covers sensing, seizing and transforming.

The authors identify SCRES capabilities, in general, and SCCR-specific capabilities that form the basis for the realignment of DCs for addressing cyber risks in SCs. The authors argue that SCRES capabilities should, in general, be combined with specific capabilities for SCCR to deal with SC cyber risks. Based on these findings, 10 propositions for future research are provided.

Practitioners should collaborate specifically to address cyber threats and risks in SCs, integrate new SC partners and use new approaches. Furthermore, this study shows that cyber risks need to be treated differently from traditional SC risks.

This empirical study enriches the SC management literature by examining SCRES to cyber risks through the insightful lens of DCs. It identifies DCs for building SCCR, makes several managerial contributions and is among the few that apply the DC approach to address specific SC risks.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

This study aims to examine the underlying process through which learning organization culture positively influences knowledge sharing. It specifically explored the mediating role of social capital, underscoring its critical impact on enhancing both knowledge sharing and fostering learning organization culture.

To test the proposed hypotheses, structural equation modeling (SEM) analysis was conducted with a sample of 231 employees from a manufacturing firm in South Korea.

The results of this study indicate significant direct effects of learning organization culture on social capital. Also, social capital indicates a positive effect on knowledge sharing. Although learning organization culture had no direct effect on knowledge sharing, it indirectly affected learning organization culture and knowledge sharing by mediating social capital.

This study proposes that a learning organization culture will be interconnected with social capital and knowledge sharing. Organizations that can effectively harness the wealth of knowledge unlocked by social capital, and subsequently integrate this knowledge into their activities, are poised for competitive advantage.

First, this study places a special emphasis on the mediating role of social capital between learning organization culture and knowledge sharing. Despite extensive research exploring diverse knowledge-sharing factors (Wang and Noe, 2010), it is plausible that examining social capital as a mediator could offer insights for facilitating knowledge sharing through its structural, relational and cognitive dimensions. Second, while a plethora of literature examines knowledge sharing, this study also seeks to unravel the multifaceted pathways through which the learning organization culture influences knowledge sharing and how these processes could be optimized in organizations.

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

Despite the growing interest in blockchain technology (BCT) applications in the agri-food industry, evidence of their economic and strategic implications remains scarce. This study aims to contribute to filling this gap by jointly investigating how BCT adoption affects transactional relationships, and how it contributes to the firm’s strategic resources.

An explanatory case study is conducted based on a theoretical framework grounded on transaction cost economics and the resource-based-dynamic capabilities view. Six BCT implementations by agri-food firms are studied. Data were collected through semi-structured interviews and analysed using thematic analysis.

Findings reveal that BCT benefits depend on how companies integrate technology across their supply chains. In fact, the results suggest that overall transaction efficiency within the supply chain is enhanced only for those firms prioritising stakeholder engagement during technology implementation and leveraging existing trust relationships with economic agents. Moreover, the results suggest that BCT is not yet perceived as a strategic resource, but rather that it has the potential to enhance firms’ operational-adaptive, absorptive and innovative capabilities. When all supply chain actors clearly understand blockchain’s functionality and value, the development of these capabilities becomes more pronounced.

The study identifies two BCT adoption configurations. One primarily focuses on enhancing supply chain efficiency and transparency (dynamic BCT), while the other uses BCT mainly for marketing purposes (static BCT). These configurations lead to varied possibilities for leveraging BCT’s potential advantages. Furthermore, they show how a mismatch between a strategic approach and its chosen configuration could work against any positive impact and lead to disillusionment with the BCT. Thus, managers should assess carefully the impact of such different configuration choices on performance.

To the best of the authors’ knowledge, this is the first study to attempt to analyse the economic implications of adopting BCT in the food sector from both a firm and supply chain perspective. Additionally, it shows how interpreting these impacts is contingent on the diverse modalities for embedding BCT into existing supply chains.

Despite the proliferation of cyberthreats upon the supply chain (SC) at large, knowledge on SC cybersecurity is scarce and predominantly conceptual or descriptive. Addressing this gap, this research examines the effect of SC cyber risk management strategies on integration decisions for cybersecurity (with suppliers, customers, and internally) to enhance the SC’s cyber resilience and robustness.

A research model grounded in the supply chain risk management (SCRM) literature, with roots in the Dynamic Capabilities View and the Relational View, was developed. Survey responses of 388 SC managers at US manufacturers were obtained to test the model.

An impact of SC cyber risk management strategies on internal cyber integration was detected, which in turn impacted external cyber integration with both suppliers and customers. Further, a positive effect of internal and customer cyber integration on both cyber resilience and robustness was found, while cyber integration with suppliers impacted neither.

Industry practitioners may adapt certain risk management and integration strategies to enhance the cybersecurity posture of their SCs.

This research bridges between the established domain of SCRM and the emergent field of SC cybersecurity by forming and testing novel relationships between SCRM-rooted constructs tailored to an SC cyber risks context.

This study aims to present an innovative predictive methodology that transitions from traditional efficiency assessment techniques to a forward-looking strategy for evaluating working capital management(WCM) and its determinants by integrating data envelopment analysis (DEA) with artificial neural networks (ANN).

A slack-based measure (SBM) within DEA was used to evaluate the WCME of 1,388 firms in the Indian manufacturing sector across nine industries over the period from April 2009 to March 2024. Subsequently, a fixed-effects model was used to determine the relationships between selected determinants and WCME. Moreover, the multi-layer perceptron method was applied to calculate the artificial neural network (ANN). Finally, sensitivity analysis was conducted to determine the relative significance of key predictors on WCME.

Manufacturing firms consistently operate at around 50% WCME throughout the study period. Furthermore, among the selected variables, ability to create internal resources, leverage, growth, total fixed assets and productivity are relatively significant vital predictors influencing WCME.

The integration of SBM-DEA and ANN represents the primary contribution of this research, introducing a novel approach to efficiency assessment. Unlike traditional models, the SBM-DEA model offers unit invariance and monotonicity for slacks, allowing it to handle zero and negative data, which overcomes the limitations of previous DEA models. This innovation leads to more accurate efficiency scores, enabling robust analysis. Furthermore, applying neural networks provides predictive insights by identifying critical predictors for WCME, equipping firms to address WCM challenges proactively.