Andrea Sestino, Adham Kahlawi and Andrea De Mauro
The data economy, emerging from the current hyper-technological landscape, is a global digital ecosystem where data is gathered, organized and exchanged to create economic value…
Abstract
Purpose
The data economy, emerging from the current hyper-technological landscape, is a global digital ecosystem where data is gathered, organized and exchanged to create economic value. This paper aims to shed light on the interplay of the different topics involved in the data economy, as found in the literature. The study research provides a comprehensive understanding of the opportunities, challenges and implications of the data economy for businesses, governments, individuals and society at large, while investigating its impact on business value creation, knowledge and digital business transformation.
Design/methodology/approach
The authors conducted a literature review that generated a conceptual map of the data economy by analyzing a corpus of research papers through a combination of machine learning algorithms, text mining techniques and a qualitative research approach.
Findings
The study findings revealed eight topics that collectively represent the essential features of data economy in the current literature, namely (1) Data Security, (2) Technology Enablers, (3) Business Implications, (4) Social Implications, (5) Political Framework, (6) Legal Enablers, (7) Privacy Concerns and (8) Data Marketplace. The study resulting model may help researchers and practitioners to develop the concept of data economy in a structured way and provide a subset of specific areas that require further research exploration.
Practical implications
Practically, this paper offers managers and marketers valuable insights to comprehend how to manage the opportunities deriving from a constantly changing competitive arena whose value is today also generated by the data economy.
Social implications
Socially, the authors also reveal insights explaining how the data economy features may be exploited to build a better society.
Originality/value
This is the first paper exploring the data economy opportunity for business value creation from a critical perspective.
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Andrea Mastrorilli, Ferdinando Paolo Santarpia and Laura Borgogni
Team-based work is increasing within organizations nowadays. Despite calls for differentiation between individual and team levels of analysis, research on leadership effects at…
Abstract
Purpose
Team-based work is increasing within organizations nowadays. Despite calls for differentiation between individual and team levels of analysis, research on leadership effects at multiple levels is still limited. By integrating the Conservation of Resources and Social Cognitive theories, this paper aims to analyze the relationships between coaching leadership, team collective efficacy and individual exhaustion via multilevel modeling.
Design/methodology/approach
This paper opted for an exploratory study testing a 2-2-1 multilevel mediational model, positing team collective efficacy as a key factor in mediating the relationship between coaching leadership at the team level and exhaustion at the individual level. The hypotheses were tested on a sample of 311 employees, nested in 72 teams (Msize = 5.70, SDsize = 2.82 team members) of a large Italian company that provides financial services.
Findings
Results supported the positive association between coaching leadership and team collective efficacy, which, in turn, was negatively associated with team members’ average score in exhaustion and fully mediated the effect of coaching leadership on exhaustion, even controlling for team design features (i.e. task interdependence and team virtuality). The association between coaching leadership and exhaustion was only indirect, explained by team collective efficacy.
Research limitations/implications
Because of the self-report nature of the measures and the cross-sectional nature of the data, this research results might raise problems of variance in common methods and not allow causal conclusions to be drawn. Therefore, researchers are encouraged to test the proposed propositions further.
Practical implications
This paper includes several practical implications for enhancing group efficacy beliefs, which have an impact on individual well-being within the team.
Originality/value
This paper addresses the lack of empirical findings on the multilevel nature of the relationship between coaching-based leadership, collective team effectiveness and individual exhaustion.
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Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Suhaiza Zailani and Mohammad Iranmanesh
Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general…
Abstract
Purpose
Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general overview of the academic landscape concerning PPP.
Design/methodology/approach
To offer a nuanced perspective, the study adopts the Latent Dirichlet Allocation (LDA) methodology to meticulously analyse 3,057 journal articles, mapping out the thematic contours within the PPP domain.
Findings
The analysis highlights PPP's pivotal role in harmonising public policy goals with private sector agility, notably in areas like disaster-ready sustainable infrastructure and addressing rapid urbanisation challenges. The emphasis within the literature on financial, risk, and performance aspects accentuates the complexities inherent in financing PPP and the critical need for practical evaluation tools. An emerging focus on healthcare within PPP indicates potential for more insightful research, especially amid ongoing global health crises.
Originality/value
This study pioneers the application of LDA for an all-encompassing examination of PPP-related academic works, presenting unique theoretical and practical insights into the diverse facets of PPP.
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Colin Donaldson, Sascha Kraus, Andreas Kallmuenzer and Cheng-Feng Cheng
This study aims to explore which relational factors are crucial for accelerator-based start-ups to achieve high financial performance and whether innovation levels influence this…
Abstract
Purpose
This study aims to explore which relational factors are crucial for accelerator-based start-ups to achieve high financial performance and whether innovation levels influence this relationship. Utilizing fsQCA and drawing from the resource-based view (RBV), we analyze 128 start-ups in a Spanish accelerator, split by innovativeness, to understand the impact of relational and human capital factors on performance.
Design/methodology/approach
The study uses fuzzy-set qualitative comparative analysis (fsQCA) to investigate conditions leading to high financial performance among 128 start-ups in a Spanish accelerator, divided by innovativeness. Four key factors are analyzed: social capital, social competence, resource mobilization and entrepreneurial ecosystem support. fsQCA examines complex relationships between these factors and financial performance.
Findings
Relational and human capital factors significantly impact start-up financial performance, varying with innovativeness. Highly innovative start-ups benefit from social competence and networked support, while less innovative but profitable start-ups rely on resource mobilization skills. The study highlights the contingent value of these factors, showing that unique configurations drive financial success.
Research limitations/implications
The paper enhances the RBV in entrepreneurial contexts by highlighting the critical role of relational resources and their configurations. It suggests social competence and networked support are crucial for highly innovative start-ups, while resource mobilization is key for less innovative ones. These findings encourage nuanced theorizing of start-up success strategies, considering varying innovativeness levels and their impact on performance.
Originality/value
This study enhances understanding of the relationship between relational factors and financial performance in accelerator-based start-ups, considering innovation levels. It provides insights into how different configurations of social capital, competence, resource mobilization and ecosystem support lead to success. It underscores the importance of considering the contingent value of relational factors for start-up growth.