Search results

Supply chain (SC) professionals are increasingly working alongside business partners of diverse backgrounds, which has been argued to engender both innovation and creativity but also found as potentially detrimental to SC relationships and performance. To reconcile these views, this study explores two mechanisms – supplementary (similarity) and complementary fits – at the surface (observable traits) and deep (unobservable characteristics) levels and their impact on a focal firm representative’s perception of a SC partner’s trustworthiness.

Model was tested using survey data from 285 managers involved in interorganizational SC relationships.

Results indicate that a focal firm representative’s perception of supplementary and complementary fits with a SC partner positively impacts their perception of the partner’s trustworthiness. However, the effects of similarity at both surface and deep levels and complementarity weaken each other.

Understanding the mechanisms of diversity in SC relationships is crucial for fostering trustworthiness and achieving organizational objectives. Firms should evaluate both supplementary and complementary fits when hiring or assigning roles. Embracing a complementary fit not only promotes diversity but also mitigates the negative impact of similarity bias, ultimately strengthening trustworthiness within the organization's SC ecosystem.

By simultaneously examining individual and combined effects of two unique mechanisms of supplementarity and complementarity at the surface and deep levels, this study sheds light on inconsistent findings of the effects of diversity in the SCM literature.

Drawing on resource orchestration theory, this paper aims to empirically investigate the relationships between digital transformation (DT), triple-A supply chain capabilities (i.e. agility, adaptability and alignment) and sustainable performance. The research focuses on the pharmaceutical industry, which best represents a business environment characterized by volatility, uncertainty, complexity and ambiguity.

Data were collected at different echelons of a globally oriented pharmaceutical supply chain, with the focal company located in the Netherlands. Empirical data were analyzed with partial least squares – structural equation modelling.

The findings reveal that DT enhances the triple-A supply chain capabilities. Nevertheless, not all three capabilities are necessary to improve overall sustainable performance. The results highlight that, among the three, only supply chain agility and adaptability significantly mediate the relationship between DT and sustainable performance.

This research supports the literature affirming that not all the triple-A supply chain capabilities equally affect sustainable performance. Moreover, it deepens the understanding of how orchestrating the triple-A capabilities at a firm level fosters overall sustainable performance, facing resource scarcity and investments in DT.

This study presents new empirical evidence to the relatively scarce number of research papers on the correlation between eco-innovation and company growth. It sheds light on the causal relationship between these two variables.

Data from the Spanish Technological Innovation Panel from 2008 to 2016. Propensity Score Matching is applied to avoid self-selection problems.

The study found that engaging eco-innovation has no statistically significant impact on employment and sales growth. Therefore, the main benefits of transitioning to green innovations are in the environmental aspect.

The research findings provide a clear direction for policymakers. Such directions suggest the design of instruments that make the adoption of eco-innovations mandatory with the firm promise of substantial environmental benefits.

The paper explores an important issue for environmental policy. If being an eco-innovator is positively or at least neutrally related to growth, policymakers could create measures that encourage this type of green innovation. This would benefit the environment, and if the impact is positive, it would also have a positive social effect.

The economic, financial and social crisis has heightened researchers' interest in the importance of organizational sustainability and resources (e.g. work engagement and psychological capital) for performance. Despite some studies demonstrating the significance of resources, such as work engagement and psychological capital, for workers’ performance, there is limited knowledge regarding the role of organizational sustainability practices (OSP) in the relationship mentioned above. Therefore, this study drew upon the social identity theory to conceptualize and test the mediating role of work engagement in the relationship between OSP and performance (both task and adaptive). Based on the conservation of resources theory, it was hypothesized that a worker's resource – psychological capital – would moderate the indirect relationship between social responsibility practices and performance (both task and adaptive).

To test the proposed model, 304 adults participated in a two-wave study.

The results supported the hypotheses, revealing that OSP had a positive and significant relationship with task and adaptive performance, occurring through work engagement. Furthermore, the indirect relationship between OSP and performance task and adaptive through work engagement was moderated by psychological capital, such that the relationship became stronger for workers with lower levels of psychological capital.

The relevance of this research lies in its ability to identify the conditions and mechanisms in which corporate social responsibility initiatives are most effective, thereby enabling a more nuanced application of these practices across different sectors and organizational cultures. This study's theoretical and practical implications may assist organizations in devising strategies for implementing social responsibility practices to enhance their outcomes.

Through the theoretical lens of social practice theory, the aim of this research is to investigate how business-to-business (B2B) high-tech startups build their brands in an omni-digital environment, particularly by focusing on the most important digital touchpoints implemented to interact with stakeholders.

A qualitative analysis was performed by conducting 36 semi-structured interviews with key informants operating in B2B high-tech startups, including founders, CEOs, managing directors, marketing managers and other actors from this sector.

The results reveal the enablers, inhibitors and specific objectives of startups in their brand-building processes across digital touchpoints in an omni-digital environment.

This study offers new theoretical insights into new ventures’ brand management strategies through the development of a theoretical framework in which the enablers, inhibitors and specific objectives of the brand-building process of startups are identified. Although the recent literature has addressed the topic of startup brand building, this is the first study, to the authors’ knowledge, focused on the brand-building process of B2B high-tech startups in an omni-digital environment.

In today’s highly competitive world, the purpose of this research is to emphasize the increasing significance of management education and advocate for the adoption of innovative teaching approaches, specifically focusing on artificial intelligence (AI)-driven personalized learning (PL). This study aims to explore the integration of self-determination theory (SDT) principles into management education, with a primary focus on enhancing student motivation, engagement and academic performance (AP).

This interdisciplinary research adopts a multifaceted approach, combining perspectives from AI, education and psychology. The design and methodology involve a thorough exploration of the theoretical foundations of both AI-driven education and SDT. The research demonstrates how these two elements can synergize to create a holistic educational experience. To substantiate the theoretical claims, empirical data-driven analyses are employed, showcasing the effectiveness of AI-enabled personalized learning (AIPL). The study integrates principles from SDT, such as autonomy, competence and relatedness, to create an environment where students are intrinsically motivated, receiving tailored instruction for optimal outcomes.

The study, rooted in SDT, demonstrates AIPL’s transformative impact on management education. It positively influences students’ autonomy, competence and relatedness, fostering engagement. Autonomy is a key driver, strongly linked to improved AP. The path analysis model validates these relationships, highlighting AI’s pivotal role in reshaping educational experiences and intrinsically motivating students.

This study holds substantial significance for educators, policymakers and researchers. The findings indicate that the AIPL model is effective in increasing student interest and improving AP. Furthermore, this study offers practical guidance for implementing AI in management education to empower students, enhance engagement and align with SDT principles.

Contribute original insights through an interdisciplinary lens. Synthesize AI and SDT principles, providing a roadmap for a more effective educational experience. Empirical data-driven analyses enhance credibility, offering valuable contributions for educators and policymakers in the technology-influenced education landscape.