1,721,005 research outputs found
Managing complexity in knowledge-intensive manufacturing firms in big data era. The importance of internet of things and artificial intelligence
No full textFirms are by definition characterized by a high degree of complexity. Indeed, firms are complex systems whose success is strictly related to several different internal and external involved players and contexts. This is particularly true for knowledge-intensive manufacturing firms, which increasingly need huge amount of data and a wide spectrum of information flows spanning the whole organization. Hence the need to explore more deeply the impact of digital technologies on this category of firms. The aim of this research is to investigate whether and how information systems based on internet of things (IoT) and artificial intelligence (AI) may allow managers of knowledge-intensive manufacturing firms to better manage complexity
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
The relationship between knowledge management and leadership: mapping the field and providing future research avenues
Full text linkPurpose: Effectively handling knowledge is crucial for any organization to survive and prosper in the turbulent environments of the modern era. Leadership is a central element for knowledge creation, acquisition, utilization and integration processes. Based on these considerations, this study aims to offer an overview of the evolution of the literature regarding the knowledge management-leadership relationship published over the past 20 years. Design/methodology/approach: A bibliometric analysis coupled with a systematic literature review were performed over a data set of 488 peer-reviewed articles published from 1990 to 2018. Findings: The authors discovered the existence of four well-polarized clusters with the following thematic focusses: human and relational aspects, systematic and performance aspects, contextual and contingent aspects and cultural and learning aspects. The authors then investigated each thematic cluster by reviewing the most relevant contributions within them. Research limitations/implications: Based on the bibliometric analysis and the systematic literature review, the authors developed an interpretative framework aimed at uncovering several promising and little explored research areas, thus suggesting an agenda for future knowledge management-leadership research. Some steps of the paper selection process may have been biased by the interpretation of the researcher. The authors addressed this concern by performing a multiple human subject reading process whose reliability was confirmed by a Krippendorf’s alpha coefficient value >0.80. Originality/value: To the best knowledge, this is the first study to map, systematize and discuss the literature concerned to the topic of the knowledge management-leadership relationship
Rethinking SME default prediction: a systematic literature review and future perspectives
Full text linkOver the last dozen years, the topic of small and medium enterprise (SME) default prediction has developed into a relevant research domain that has grown for important reasons exponentially across multiple disciplines, including finance, management, accounting, and statistics. Motivated by the enormous toll on SMEs caused by the 2007–2009 global financial crisis as well as the recent COVID-19 crisis and the consequent need to develop new SME default predictors, this paper provides a systematic literature review, based on a statistical, bibliometric analysis, of over 100 peer-reviewed articles published on SME default prediction modelling over a 34-year period, 1986 to 2019. We identified, analysed and reviewed five streams of research and suggest a set of future research avenues to help scholars and practitioners address the new challenges and emerging issues in a changing economic environment. The research agenda proposes some new innovative approaches to capture and exploit new data sources using modern analytical techniques, like artificial intelligence, machine learning, and macro-data inputs, with the aim of providing enhanced predictive results
New Product Development during the Last Ten Years: The Ongoing Debate and Future Avenues
Full text linkResearch on new product development (NPD) has grown considerably over the last 30 years interweaving with serval fields of study such as strategy, marketing, supply chain management, and project management. This article offers an overview of the development of the NPD management literature published over the last ten years (2008 to 2018) in 1226 peer-reviewed articles. By applying bibliometric analysis, we have discovered the existence of five research clusters focused on the following main thematic areas: the NPD process, the integration of diverse knowledge sources for NPD optimization, the relationship between NPD and corporate strategy, the role of users and consumers in the NPD process, and the supplier involvement in the NPD activities. In respect of each area, we selected and reviewed the most relevant contributions and presented the emerging theoretical approaches and best practices. Also, the analysis has helped us to uncover the existence of promising research areas that have been scarcely explored. As a result, we formulated some suggestions for further research to fill in the existing gaps
Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation
Full text linkBig Data Analytics Capabilities (BDAC) represent critical tools for business competitiveness in highly dynamic markets. In this connection, by leveraging on the Dynamic Capabilities View (DCV) this study analyses the relationship between BDAC and Business Model Innovation (BMI). It argues that the impact of BDAC (a lower-order dynamic capability) on BMI is mediated by Entrepreneurial Orientation (EO; a higher-order dynamic capability). The proposed model is assessed by PLS-SEM (symmetric) and fuzzy-set Qualitative Comparative Analysis (asymmetric) methods using survey data from 253 UK firms. Our findings demonstrate that BDAC have both direct and indirect positive effects on BMI, with the latter being mediated by EO. These results enrich the innovation management literature on Big Data (BD) by showing that BDAC influence company strategic logics and objectives, rather than depending on them, thus playing a significant role in creating value for companies and their stakeholders
The big data-business strategy interconnection: a grand challenge for knowledge management. A review and future perspectives
Full text linkPurpose: Designing knowledge management (KM) systems capable of transforming big data into information characterised by strategic value is a major challenge faced nowadays by firms in almost all industries. However, in the managerial field, big data is now mainly used to support operational activities while its strategic potential is still largely unexploited. Based on these considerations, this study proposes an overview of the literature regarding the relationship between big data and business strategy. Design/methodology/approach: A bibliographic coupling method is applied over a dataset of 128 peer-reviewed articles, published from 2013 (first year when articles regarding the big data-business strategy relationship were published) to 2019. Thereafter, a systematic literature review is presented on 116 papers, which were found to be interconnected based on the VOSviewer algorithm. Findings: This study discovers the existence of four thematic clusters. Three of the clusters relate to the following topics: big data and supply chain strategy; big data, personalisation and co-creation strategies and big data, strategic planning and strategic value creation. The fourth cluster concerns the relationship between big data and KM and represents a ‘bridge’ between the other three clusters. Research limitations/implications: Based on the bibliometric analysis and the systematic literature review, this study identifies relevant understudied topics and research gaps, which are suggested as future research directions. Originality/value: This is the first study to systematise and discuss the literature concerning the relationship between big data and firm strategy
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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