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The unprecedented growth in the volume, variety and velocity with which data is generated and collected over the last decade has led to the spread of big data phenomenon. Organizations have become increasingly involved in the collection and analysis of big data to improve their performance. Whereas the focus thus far has mainly been on big data collected from customers, the topic of how to collect data also from those who are not yet customers has been overlooked. A growing means of interacting with non-customers is through crowd-based phenomena, which are therefore examined in this study as a way to further collect big data. Therefore, this study aims to demonstrate the importance of jointly considering these phenomena under the proposed framework.

This study seeks to demonstrate that organizations can collect big data from a crowd of customers and non-customers through crowd-based phenomena such as crowdsourcing, citizen science and crowdfunding. The conceptual analysis conducted in this study produced an integrated framework through which companies can improve their performance.

Grounded in the resource-based view, this paper argues that non-customers can constitute a valuable resource insofar as they can be an additional source of big data when participating in crowd-based phenomena. Companies can, in this way, further improve their performance.

This study advances scientific knowledge of big data and crowd-based phenomena by providing an overview of how they can be jointly applied to further benefit organizations. Moreover, the framework posited in this study is an endeavour to stimulate further analyses of these topics and provide initial suggestions on how organizations can jointly leverage crowd-based phenomena and big data.

This study aims to analyze how, under the stakeholder theory, corporate social responsibility (CSR) might favor the emergence of circular economy (CE) in the Agri-food sector, which is a relevant context, as it is technologically dynamic and requires paying attention to all the stakeholders.

An exploratory, qualitative research design has been adopted to study the phenomenon in detail, as it facilitates the understanding of complex phenomena such those under investigation and helps enrich existing theory with new insights from real-world cases to add theoretical generalizations to the existing body of research in the field.

The results of this study highlight that companies adopting CSR models are oriented toward circularity.

This study provides useful indications to managers and policymakers as to how to favor the two approaches (CSR and CE) and benefit all the stakeholders.

While there is wide scholarly and managerial interest toward CSR and CE, previous research has mainly analyzed CE and CSR as two independent phenomena. Therefore, there is a lack of understanding about how the two areas are linked. Following previous studies that have started to theoretically argue an interconnection between CSR and CE, in this research, it has been empirically investigated, and further explored theoretically, whether CSR can implicitly encourage the emergence of CE approaches.

The purpose of this paper is to explore the role of the digitalization phenomenon in the development of innovative business models that are sustainability oriented. Thus, the authors aim to understand whether the presence of digitalization forces companies to create, capture and deliver value in new ways, focusing on their social impact.

Through the analysis of a case study in the automotive sector, the authors provide evidence that both digitalization and sustainability need to be considered to adequately innovate business models. Moreover, these two dimensions are interrelated, and therefore digitalization sustains sustainability and vice versa.

By inductively investigating the evolutionary path along which companies tend to adapt their business models to digitalization and sustainability trends, the authors found that this innovative transformation needs to be as sustainable as possible in order to offer benefits to organizations, customers and society at large. Furthermore, the authors revealed that, at least in the automotive sector, companies and customers are aware of the remarkable consequences of digitalization; however, they are still uncertain regarding the actual adoption of new technologies.

The literature on business model innovation is quite extensive. However, the role of digitalization in developing sustainable business models to achieve a competitive advantage has been overlooked. This study suggests that, within a specific context, forging a value network of stakeholders is helpful when innovating a business model with a sustainability orientation.

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.

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.

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.

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.

This is the first study to systematise and discuss the literature concerning the relationship between big data and firm strategy.

The paper offers a comprehensive understanding of how digital transformation affects business models and how firms operate and compete effectively and successfully in a digital economy.

The research adopted an abductive approach (Dubois and Gadde, 2002) through constant movement between theory and empirical evidence. A systematic literature review led the first conceptual development and examples of practices from cultural heritage sectors were used in the theorizing process.

This paper depicts a digital model framework through a set of assumptions about how an organization creates and delivers value in an interconnected way by orchestrating new interactive processes, and providing experience propositions to customers, and about how value is framed in terms of economic, social and cultural outcomes.

The study contributes to the scientific debate by discussing the role of digital business models as enhancements more rather than replacements of traditional business models; it frames a digital business model as consisting of three main pillars: value orchestration, experience propositions and value sharing.

This paper gives a review of the finite element techniques (FE) applied in the analysis and design of machine elements; bolts and screws, belts and chains, springs and dampers, brakes, gears, bearings, gaskets and seals are handled. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of this paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An Appendix included at the end of the paper presents a bibliography on finite element applications in the analysis/design of machine elements for 1977‐1997.

This paper aims to present the application and critical reflection on the effects of a intervention for children with autism spectrum disorder (ASD): the Soundbeam Imitation Intervention (SII). The intervention is based on the imitation of meaningless body gestures supported by a musical feedback. The rationale underlying SII is that mirror neurons deficit may represent the cause for the incomplete development of social and motor functioning in children with ASD. Following this assumption, it is possible to hypothesise that a systematic activation of this a system through the simultaneous observation-execution of meaningless body gestures may affect functional changes of mirror-related functions.

A sample of 14 children, who were between 5 and 9 years of age, with a diagnosis of ASD were involved in a six weeks’ SII programme. The programme is designed as a three-step progression, where each step includes exercises that focus on an activity: synchronous/one arm imitation, synchronous/two arms imitation and delayed imitation. Exercises are based on repeated movements-melodies associations of increasing difficulty. Motor imitation and social attention were assessed using a synchronous video-modelling task pre and post intervention.

Data highlight significant improvements in imitation accuracy and duration of social sustained attention were achieved.

Data reported in this paper provide preliminary and promising evidence that imitation and social attention skills acquired through SII can be generalised to a video-modelling imitation setting. The SII ordinal execution has included meaningless gestures, usually excluded from previous interventions, and this adds further validity to the training.