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Although exponential technologies promise to bring unprecedented value at the socio-economic and policy levels, the social acceptability and preparedness for the technological “singularity” should be carefully considered. In particular, whereas digital innovation is able to drive an extraordinary development of entrepreneurial ventures, a number of challenging issues and the ongoing pandemic crisis have increased the need to investigate how technological breakthrough and human capital can be effectively combined in order to build resilient socio-technical and entrepreneurial ecosystems. This paper offers a synopsis of the major investigation areas and a reflection on the themes associated with the emergence of a digital society and the affirmation of digital entrepreneurship ecosystems. The research process follows a systematic literature review and a conceptual development approach aimed to introduce both the concept and a model of the digital society “incubator”. The proposed model identifies the actors, values, flows, and processes that are required to support the construction of a resilient entrepreneurial ecosystem. In this perspective, the study proposes a new focus by hybridizing and integrating both entrepreneurial and technology-related dimensions into a single unifying model. The study also lays the groundwork for further studies aimed at identifying the environmental and institutional factors required to support a smooth and effective transition towards a resilient entrepreneurial and technology-driven society.

Digital transformation is driving the emergence of a new breed of organisations able to scale quickly, innovate throughout their processes, and lead industries and markets. In particular, the increasing adoption of cognitive technologies, like artificial intelligence, advanced analytics, high-performing computing and cyber-physical systems, allow organisations to create new value based on increased reactivity and resilience, situational awareness, agility and operational excellence. Although the idea of cognitive enterprise is rapidly emerging in the practitioner discussion, a theoretical framing of the concept is still not present in literature. We conduct a systematic review of extant contributions and we extract elements related to two key dimensions represented by the cognitive technological infrastructure (i.e. technologies and data) and the cognitive organizational architecture (i.e. processes and capabilities). We use the outcomes of the review work to define: (a) the pillars of the cognitive enterprise; (b) a framework of cognitive maturity stages; and (c) the enhanced value creation capabilities of the cognitive enterprise. The article provides a literature-derived definition of the cognitive enterprise and guidelines to support managers in the cognitive transformation of their organisations.

Purpose Differently from traditional approaches that rely on the analysis of single dimensions of the tourism phenomenon, this study aims to experiment a systemic approach based on structured and unstructured data sources to elaborate a composite index to measure the tourist competitiveness of marginal areas, with the final aim to design and plan proper socio-economic development strategies. Design/methodology/approach The methodology adopted to carry out the study follows a four-step process and relies on indicators that are both relevant and accessible. The first step concerns the analysis of the literature about the existing approaches to calculate a tourism index. The second step concerns the definition of the indicators and the collection of data by using both structured and unstructured sources. The third step focuses on the population of the data set. Finally, the fourth step aims at calculating the tourism index through a composite-based methodology and using it for a pilot application in a Southern Italy province. Findings The study calculates a synthetic tourism index for each of the 97 municipalities of the Province of Lecce (a city located in the southeast of Italy). The proposed index combines administrative, institutional and open data sources to derive a single indicator for each municipality, thus supporting decision-makers in understanding the complex reality and competitiveness level of territories in the tourism industry. Originality/value The main elements of originality of the study are the breadth and typology of data sources considered to calculate the composite indicator of tourism competitiveness (both structured and unstructured); and the use of weighting and aggregation procedures in the methodological issues.

Purpose The generation of new ventures within established companies, also known as corporate entrepreneurship (CE), is a process influenced by a set of individual and organizational factors. This paper aims to focus on creativity and human resource management enablers of CE, with the purpose to define an integrative framework and draw a set of related research propositions. Design/methodology/approach The paper relies on a multidisciplinary literature review in the fields of CE, creativity and organizational innovation. Findings The effectiveness of CE depends on a set of individual factors, distinguished into professional and psychological characteristics, and organizational factors, which include the system of values of the organization and the management practices applied in the same. Research limitations/implications From a theoretical point of view, the paper develops an integrative framework of conditions that impact on CE and outlines a set of propositions and alternative research methods to test. Practical/implications From a practitioner perspective, the study provides managers with a comprehensive set of factors enabling CE by leveraging the creativity of individuals and make it flourish through consistent human resource management practices. Originality/value The value of the paper stays in the integration of individual-related and organizational-related determinants of entrepreneurial performance.

The industrial progress has reached a level in which it is necessary to understand the behavior of mechanical components and to monitor their conditions without disassembling them. Nowadays, a suitable methodology is based on vibrational analysis usually performed through acceleration signals measured directly on the system to be tested. However, in the last years, the industrial scenario has deeply changed due to the need for time reduction, in particular, for the control operations at the end of the productive line. The genuine methods based on acceleration measurements, for example, through piezoelectric accelerometers, came into conflict with the industrial need as the sensors used for the quality control have to be easily and fastly mounted and unmounted. A valid alternative is represented by the exploitation of laser triangulation sensors that are able to measure the dynamic displacement in a contactless way, strongly reducing the (un)mounting time. The target of this paper is to highlight pros and cons of the contactless displacement analysis through laser triangulation sensors with respect to the contact one through genuine accelerometers by means of a comparison between the results obtained both for experimental modal analysis and vibrational diagnostics of rotating machines.

This paper proposes a tool for the generation of synthetic mechanical signatures of faulted gears and bearings in non-stationary conditions. Synthetic signals are commonly used to provide early validation of vibration-based diagnostics techniques. In the absence of a standard tool, each researcher builds his/her own model keeping into account the characteristic features expected in a faulted condition. This approach implies two main consequences. The first one is that the complexity of simulated signals strictly depends on the researcher skills that could lead to excessively simple models that compromises the validation process. The second one is that there is not a widely accepted algorithm, or tool, for the generation of synthetic signals. This lack hinders simpler and consistent comparisons among signal processing techniques. Hence, the main goal of this paper is to supply to the scientific community a standard tool for the generation of synthetic mechanical signatures. The tool is provided under Creative Commons license and it allows to simulate different possible situations: from the basic case of a single bearing fault to the case of a multi-stage gearbox having either a localized fault and a distributed bearing fault. Among several features, the proposed tool could take also into account variable speed profiles of the input shaft, cyclostationary contributions and effects of linear time-invariant systems.

In the last decades, academic and managerial literatures have paid great attention by about the notion of the business model (BM). Accordingly, a wide range of literature was created to identify and acknowledge the capacity to create and renew organizational BM as one of the fundamental sources of competitiveness and value creation. However, until now, the notion and application of business model innovation (BMI) research has mostly been developed in relation to large companies and organizations. Very limited studies have explored what and how context-specific characteristics and knowledge asset management may have effects on BM development and organizations’ sustainability. This latter aspect is particularly true for technological start-ups. Until now, research and managerial practice have been not aligned with national and international policies’ great emphasis on technological start-ups, as well as about the role of the BMI to support organizational performance improvement and stimulate entrepreneurship. From this perspective, technological start-ups represent an interesting basis for analyzing business model mapping and BMI along a knowledge-based perspective. The creation, survival, development, and market success of such organizations are mainly based on the identification, acquisition, and exploitation of their knowledge-based assets. Therefore, it can be relevant to study and analyze how such knowledge assets significantly drive organizational performance and value creation by leveraging innovative technology breakthroughs, highly qualified and distinctive competencies, and implicit knowledge embedded into valuable networks of relationships.

Big Data has been heralded as a key agent of the third industrial revolution, and currently represents a promising area for value creation and frontier research. The potential to extract actionable insights from Big Data has gained increasing attention of both academics and practitioners operating in several industrial sectors. However, the adoption of Big Data solutions does not always generate effective value for the adopters. Therefore, the gap existing between the potential of value creation embedded in the Big Data paradigm and the current limited exploitation of this value represents an area of investigation that this paper aims to explore. In particular, this study aims at investigating the following research question: “Which are the multiple value directions that the Big Data paradigm can generate for organizations?”. In this vein, the article presents the result of a systematic literature review aimed at defining a framework that identifies the possible directions of value creation for an organization that may decide to implement the Big Data paradigm. By adopting a systematic literature review, the framework leverages and extends a previous contribution of Wamba et al. (2015) on the same topic. A further element of originality is related to the introduction of a further phase in the analysis, consisting in the application of text mining algorithms to analyse the selected resources, in the final aim to highlight possible terms and concepts remained hidden or latent in the human-led analysis.

The paper focuses on virtual brand community (VBC) as new management tool for open innovation. Existing research on the intersection between brand communities and innovation management shows how the knowledge of the brand communities’ members and their engagement in product-related discussions represent a relevant source of innovation for the companies. However, how do companies implement open innovation through the VBC and how do they implement purposeful practices represent an unexplored research area. By adopting a value-oriented perspective of open innovation, this study interprets the VBC as a co-creation space where undertaking opportunity identification and resource mobilization for value creation and value capture. The paper presents a single case study of a multinational company operating in the semiconductor industry that has recently implemented a VBC as a tool for peer-to-peer support and knowledge sharing. Results show the features of this VBC and the set of practices designed to realize the open innovation strategies. By adopting an open innovation perspective, the article presents a model of VBC as a collaborative space for innovation. For practitioners, the article provides evidences and insights about the use of VBC to support the implementation of open innovation strategies.

Digital technologies have nowadays a significant impact on how new business ventures are imagined and created. The arising technology paradigm is leveraging the potential of collaboration and collective intelligence to design and launch more robust and sustainable entrepreneurial initiatives. However, although the topic of digital entrepreneurship is relevant and timely, there is a limited literature discussion on the real impact of digital technologies and collaboration on the entrepreneurial process. Further research is needed to describe the nature and characteristics of the entrepreneurial ecosystem enabled by the new socio-technical paradigm. Based on extant literature, this article proposes a definition of digital entrepreneurship ecosystem by highlighting the integrated digital-output and digital-environment perspectives. A collective intelligence approach is then adopted to define a descriptive framework and identify the distinguishing genes of a digital entrepreneurship ecosystem. Four dimensions associated to digital actors (who), digital activities (what), digital motivations (why), and digital organization (how) are defined and discussed. The framework was also applied to describe 9 real cases of companies and initiatives, which are analyzed as digital entrepreneurship ecosystems along the four key dimensions presented. The article ends with a discussion about the results and a research agenda for future studies.

The paper proposes an analytical procedure for the generalization of the rattle index in any type of ordinary transmission layouts, single or multiple branch, both in idle and loaded conditions. Its definition is obtained by a recursive analytical formulation of the rotational dynamics of gears. Numerical analytical studies are exploited to examine the effectiveness and reliability of the introduced index. Several geartrain layouts are investigated and results show its capability to instantaneously describe the vibro-impact events related to any gear pair of the driveline. Moreover, the general definition is shown to be a proper indicator of the potential presence of mutual interactions between different gear pairs pertaining to the same driveline. The analysis of the results reveals an excellent agreement with the expected behavior of the outlined parameter.

The gear fault diagnosis on multistage gearboxes by vibration analysis is a challenging task due to the complexity of the vibration signal. The localization of the gear fault occurring in a wheel located in the intermediate shaft can be particularly complex due to the superposition of the vibration signature of the synchronous wheels. Indeed, the gear fault detection is commonly restricted to the identification of the stage containing the faulty gear rather than the faulty gear itself. In this context, the paper advances a methodology which combines the Empirical Mode Decomposition and the Time Synchronous Average in order to separate the vibration signals of the synchronous gears mounted on the same shaft. The physical meaningful modes are selected by means of a criterion based on Pearson’s coefficients and the fault detection is performed by dedicated condition indicators. The proposed method is validated taking into account simulated vibrations signals and real ones.

In modern industry, the wide use of reliable and sophisticated sensors with their connection to internet has introduced the phenomena of Big Data, especially in the field of condition monitoring systems (CMSs) in e-maintenance applications. In particular, in the case of vibration signals, high-performance acquisition systems are required, characterized by anti-aliasing filtering and high uniform sampling rate, in order to properly digitalize the meaningful frequency content of the signals. In this context, the capability of non-uniform random sampling (RS) is assessed in this work. While in different fields, such astronomy, structural and biomedical studies, the RS is a problem to be resolved, due to the unavailability of samples at specific instants (missing data problem), in the field of fault detection & diagnosis (FDD), RS can be a chosen sampling method thanks to its advantages: anti-aliasing property and low average sampling rate. Therefore, this paper focuses on studying the anti-aliasing property of the random sampled data, verifying the criterion proposed in literature for establish the Nyquist frequency, and analyzing its sensitivity to the sampling parameters. This study is carried out using simulated signals and computing the spectral window, giving the Nyquist frequency for different random sampling parameters; moreover, a spectral analysis method, the Schuster periodogram, is used to verify when the spectrum is actually free of alias. The results show that the Nyquist frequency depends on the numerical accuracy of the randomly generated time instants.

Established companies operating within highly competitive environments, with strong regulatory issues, new competitors, technological changes and market saturation, have a continuous pressure to pursue innovation and improve their competitive positioning. Corporate Entrepreneurship (CE) and Open Innovation (OI) revealed as very effective and valuable strategies to achieve this goal. This paper describes how the Italian National Railways group (here after FSI group - Ferrovie dello Stato Italiane) has undertaken a path to explore new business models by designing and launching an initiative to find new ideas, support them in the development, and promote them in the final aim to launch new products and services. The ideas that have been researched and explored are not those directly related to the core corporate business, but aim to explore new boundaries that include assets available within the organization, leverage the advantages coming from market positionings and find additional resources already existent within the organization as potential sources of additional value. To achieve these goals, the FSI Group has built in 2017 (and developed in 2018) the Innovate Project, which is the first experimentation of CE process within the FSI Group, by adopting an OI approach.

So far, the study of gear contacts in lightly loaded gears by means of vibration analysis has not been sufficiently addressed in the literature. Indeed, the complex nature of the physical phenomena involved makes the vibration analysis extremely challenging. This paper deals with the development and the validation of an approach for the contact pattern assessment in straight bevel gears within a pass/fail decision process. The proposed methodology is based on blending vibration-based condition indicators with classification algorithms in order to discriminate proper contact patterns from improper ones. Specifically, three different classification algorithms have been investigated: the Naive Bayes classifier, the weighted k-Nearest Neighbors classifier and a novel classifier proposed by the authors. The classifier accuracies are evaluated with a MC cross-validation that includes an extended experimental campaign consisting of more than one hundred different straight bevel gear pairs. The results show that the proposed classifier is superior to the other considered classifiers in terms of average accuracy. Finally, this manuscript proposes an original methodology that provides a reliable and quick assessment of the contact pattern in straight bevel gears considering different speeds, gear parameters and surface finish.

Nowadays, huge emphasis is given to research on diagnostic tools in order to prevent and monitor the health status of gears and bearings. However, the link between advanced signal processing techniques and ease of use is still missing in commercial software tools. Actually, softwares that implement advanced signal processing techniques leak in ease user interaction and automated diagnostic procedures. Authors have developed a commercial software tool, called UniVibe, that attempts to fill the gap between high sensitivity in the diagnostics of faults in complex geared transmission and user-friendly interface. This work focuses on the description of the UniVibe core, highlighting its diagnostic capabilities on the basis of a real industrial case. Specifically, the automated procedure that shepherds the user to the successfully fault diagnosis of a complex geared transmission is pointed out.

Wet compression is a strategy adopted to increase the power output of gas turbines, with respect to dry conditions, usually also incrementing the operating range of the compressor. However, stall and surge are two aerodynamic instabilities which depend on many factors, and they are expected to occur even in wet compression at low flow rates. Despite the many studies carried out in the last 80 years, literature does not offer many works concerning these instability phenomena in wet compression. In this paper, an experimental analysis of stall and surge in wet compression conditions is carried out on an axial-centrifugal compressor installed in an existing test rig at the Engineering Department of the University of Ferrara. Some modifications of the test rig were necessary. The intake duct was implemented with a water injection system which, by means of water spray injectors, allows the uniform mixing of air and water before the compressor inlet. The control and data acquisition system of the test bench was updated with new hardware and software to obtain faster data sampling. Transient and steady-state tests were carried out to make a comparison with the experimental results in dry conditions. The analysis was carried out using traditional thermodynamic sensors, by means of both classic post-processing techniques, and cyclostationary analysis. The aim is to i) evaluate the influence of wet compression on the stable performance of the compressor ii) qualitatively identify the characteristics of stall and surge in wet compression by means of sensors which were shown to capture these phenomena well and iii) demonstrate the reliability of cyclostationary analysis in wet compression conditions for stall and surge analysis.

This paper addresses the use of first- and second-order cyclostationary (CS1 and CS2) tools to process the vibration signals picked up from internal combustion (IC) engines during cold tests. This type of analysis is needed in order to detect and diagnose irregular operations for quality control purposes. The effectiveness of indicators such as Mean Instantaneous Power (MIP), Degree of Cyclostationarity ( D C S α ) and Indicator of Cyclostationarity ( I C S n x ) in detecting assembly faults has been tested on real signals concerning three faulty conditions: inverted piston, connecting rod with incorrectly tightened screws, connecting rod without one bearing cap. In the past several authors have mainly used cyclostationary metrics for diagnostics purposes in rolling bearings and gear systems. Moreover, a signal model, qualitatively reproducing the features of actual cold test signals, has been formulated and used in order to preliminarily study the influence of signal parameters on the Indicators of Cyclostationarity. The results indicate that the cyclostationary tools – mainly CS2 tools – are effective in detecting and diagnosing all tested faulty conditions. In particular, indicator I C ⌢ S 2 x is highly sensitive to faults and it is suitable as pass/fail tool in quality control at the end of the engine assembly line. As a further second-order cyclostationary metric, the MIP is effective for detection, as well for fault identification, since it is able to localize regular and fault events within the engine cycle. In addition D C S α effectively characterizes the CS2 periodicities, giving the cyclic order distribution. Since these CS2 tools require a moderate computation cost, they can be considered ready for on-line industrial applications.

In the field of condition monitoring the availability of a real test-bench is not so common. Furthermore, the early validation of a new diagnostic technique on a proper simulated signal is crucial and a fundamental step in order to provide a feedback to the researcher and to increase the chances of getting a positive result in the real case. In this context, the aim of this paper is to detail a step-by-step analytical model of faulted bearing that the reader could freely and immediately use to simulate different faults and different operating conditions. The vision of the project is a set of tools accepted by the community of researchers on condition monitoring, for the preliminary validation of new diagnostics techniques. The tool proposed in this paper is focused on ball bearing, and it is based on the well-known model published by Antoni in 2007. The features available are the following: selection of the location of the fault, stage of the fault, cyclostationarity of the signal, random contributions, deterministic contributions, effects of resonances in the machine and working conditions (stationary and non-stationary). The script is provided for the open-source Octave environment. The output signal is finally analysed to prove the expected features.

International audience; Blind deconvolution algorithms prove to be effective tools for fault identification, being able to extract excitation sources from noisy observations only. In this scenario, the present paper introduces a novel blind deconvolution method based on the generalized Rayleigh quotient and solved by means of an iterative eigenvalue decomposition algorithm. This approach not only is characterized by a weighting matrix that drives the deconvolution process, but can also be easily adapted to arbitrary criteria. Based on this framework, a novel criterion rooted on the maximization of the cyclostationarity of the excitation – as typically encountered with machine faults – is proposed and compared with other blind deconvolution methods existing in the literature. The comparisons involve both synthesized and real vibration signals, taking into account a gear tooth spall and an outer race bearing fault. The results reveal superior capability to recover impulsive cyclostationary sources with respect to other blind deconvolution methods, even in the presence of impulsive noise or under non-constant speed.

Purpose Successful businesses demand high-performing human resource management practices (HRMP) and effective knowledge management capacity (KMC) to enhance the overall organizational performance. Rapid growth of both local and multinational companies operating in knowledge-intensive industries has increased the global competition in the labor market, also for the developing economies. Therefore, attracting valuable human capital, retaining talents and managing effectively knowledge to deliver on the latest technologies and innovative solutions and services are the biggest challenges in the modern IT industry. The purpose of this paper is to examine the influence of HRMP on KMC through a cross-case analysis including four companies operating in Indian IT sector. Based on the existing studies in this field, five key HRMP have been identified (i.e. recruitment and selection, training and development, compensation and reward, employee retention and career development), as well as two key processes supporting the KMC (i.e. knowledge acquisition and knowledge sharing). Design/methodology/approach The paper adopts a qualitative research method based on a multiple case study, and it uses primary and secondary data collected through desk research and field interviews. Findings Results show the existence of HRMP aiming to enhance the individual learning, motivation and retention of employees for knowledge acquisition and knowledge sharing, in the strategic perspective to improve the organizational performance. Research limitations/implications The paper presents some limitations, which may provide scope for future research. First, being the study a qualitative multiple case analysis, a more extensive research is needed to generalize the results and investigate further relationships existing between HRMP and KMC. Moreover, a deep investigation on the organizational performance dimensions (e.g. sales growth, cash turnover, financial goal achievement) is required to verify the existence of possible links. Finally, a further limit consists in considering only knowledge acquisition and knowledge-sharing processes, excluding another crucial knowledge management (KM) process such as knowledge application. As for the research implications, the paper contributes to investigate the role of HRMP in supporting KMC in Indian IT companies, which represents a context of research not so much investigated. Practical implications From a practitioner point of view, the study can be helpful to HR and KM managers for motivating employees to undertake learning processes and enhance their performance, as well as to acquire and share knowledge resources that are useful for the organization to remain innovative and stay competitive. Originality/value As the influence of HRMP on KMC has not been widely studied in the Indian IT industry, the study may open the field for further studies on a deeper investigation of the relationships existing between human resources management (HRM), KM and organizational performance in knowledge-intensive industries in India and, more in general, in developing economies.

This paper aims at identifying common patterns that technological startups follow during their Business Model Innovation (BMI) process, trying to understand which are the enabling conditions at strategic and operational level, as well as at individual, organizational level and environmental, which can be associated to the Intellectual Capital (IC) dimensions and that may activate, support and sustain the overall process. The research is carried out by using a semi-structured questionnaire submitted through a web survey to a sample of technological startups located in Italy. The main insights of the research lie in a framework presenting a set of possible trajectories that technological startups can follow to innovate their business model by leveraging the components of their IC. Besides, the analysis has also revealed a set of enabling conditions associated to each trajectory in order to support technological startups in the identification of the most promising trajectory according to their internal conditions.

Wicked problems are complex and multifaceted issues that have no single solution, and are perceived by different stakeholders through contrasting views. Examples in the social context include climate change, poverty, energy production, sanitation, sustainable cities, pollution and homeland security. Extant research has been addressed to support open discussion and collaborative decision making in wicked scenarios, but complexities derive from the difficulty to leverage multiple contributions, coming from both experts and non-experts, through a structured approach. In such view, we present a conceptual framework for the study of wicked problem solving as a complex and multi-stakeholder process. Afterwards, we describe an integrated system of tools and associated operational guidelines aimed to support collective problem analysis and solution design. The main value of the article is to highlight the relevance of collective approaches in the endeavor of wicked problem resolution, and to provide an integrated framework of activities, actors and purposeful tools.

Il volume fornisce un modello di contenuti complementare rispetto agli standard internazionali di conoscenza e certificazione in ambito di project management. Pensato come manuale per gli studenti di economia e management, ingegneria e degli altri ambiti in cui si svolgono corsi sulla gestione di progetti e dell’innovazione, è un testo fondamentale anche per tutti coloro che si vogliono avvicinare al project management o siano interessati a una sistematizzazione delle conoscenze già possedute.

Purpose – Big Data has been heralded as a key agent of the third industrial revolution, and currently represents a promising area for value creation and frontier research. The potential to extract actionable insights from Big Data has gained increasing attention of both academics and practitioners operating in several industrial sectors. However, the adoption of Big Data solutions does not always generate effective value for the adopters. Therefore, the gap existing between the potential of value creation embedded in the Big Data paradigm and the current limited exploitation of this value represents an area of investigation that this paper aims to explore. In particular the present study aims at investigating the following research question: “Which are the multiple value directions that the Big Data paradigm can generate for organizations?”. In this vein, the article presents the result of a systematic literature review aimed at defining a framework that identifies the possible dimensions of value creation for an organization that may decide to adopt the Big Data paradigm. Design/methodology/approach – The research methodology adopted in this study is based on a Systematic Literature Review, and consists in four key steps such as search, selection, analysis, and synthesis. The result of the search process was a list of 481 resources. Then, by adopting the exclusion criteria, a subset of 91 resources was obtained. The analysis allowed to highlight the different types of value created through the adoption of Big Data paradigm within the organizations. Through the synthesis step, 12 value directions were defined and grouped into 5 key value dimensions. Originality/value – This paper introduces and describes a framework highlighting the possible value creation dimensions associated to the adoption of the Big Data paradigm by the organizations. By adopting a systematic literature review, the framework leverages and extends a previous contribution of Wamba et al. (2015) on the same topic. A further element of originality is related to the introduction of a further phase in the analysis, consisting in the application of text mining algorithms to analyse the selected resources, in the final aim to highlight possible terms and concepts remained hidden or latent in the human-led analysis. Practical implications – From a research perspective, the proposed framework aims at providing a twofold contribution: the more general one consists in the development of the debate on how organization can generate value by adopting the Big Data paradigm; the more specific one refers to the extension of the framework previously proposed by Wamba et al. (2015) on the same topic. From a practitioner point of view, the proposed framework may support managers and executives to understand better and define the strategic perspective of innovative projects based on the Big Data paradigm, which can be promoted and sponsored by the organizations.

Corporate entrepreneurship is a process of strategic renewal and development of an existing business through the creation of new products, services, and activities, as well as new competitive postures and independent ventures. The performance of this process, which leverages the creativity and the initiative spirit of employees and managers, thus relies on the capacity of the organization to create favorable conditions for the emergence of such latent entrepreneurial potential. The development of participatory innovation models and collective intelligence offers new insights for conducting research on factors enabling corporate entrepreneurship. In particular, the internal company ‘crowd’ can be investigated with the purpose of studying the conditions under which the corporate entrepreneurship process can be successfully nurtured and conducted. In such view, this article moves from an extended review of corporate entrepreneurship and organizational innovation literature to define the concept of crowdventuring and to present an assessment tool aimed at evaluating the maturity of the crowdventuring process within an organization. The tool, which captures both individual and organization-related factors, is also used for an illustrative application into a multinational IT company. Some implications are drawn at the theory and practitioner levels.

The monitoring of rolling element bearings through vibration-based condition indicators plays a crucial role in the modern machinery. The kurtosis is a very efficient indicator being sensitive to impulsive components within the vibration signature that often are symptomatic of localized faults. In order to improve the diagnostic performance of the kurtosis, blind deconvolution algorithms can be exploited in order to detect bearing faults and, most importantly, their position. In this scenario, this paper focuses on the development of a novel condition indicator specifically designed for the damage assessment in rolling element bearings. The proposed indicator allows to track the bearing degradation process taking into account three different possible positions: outer race, inner race, and rolling element. This indicator fits real-time monitoring procedures allowing for the automatic detection and identification of the bearing fault. The validation of the proposed indicator has been carried out by means of both simulated signal and a run-to-failure experiment. The results highlight that the proposed indicator is able to detect more efficiently the fault occurrence and, most importantly, quicker than other established techniques.

A wind turbine is a very well-known archetype of energy conversion system working at non-stationary regimes. Despite this, a deep mechanical comprehension of wind turbines operating in complicated conditions is still challenging, especially as regards the analysis of experimental data. In particular, wind turbines in complex terrain represent a very valuable testing ground because of the possible combination of wake effects among nearby turbines and flow accelerations caused by the terrain morphology. For these reasons, in this work, a cluster of four full-scale wind turbines from a very complex site is studied. The object of investigation is vibrations, at the level of the structure (tower) and drive-train. Data collected by the on-board condition monitoring system are analyzed and interpreted in light of the knowledge of wind conditions and operating parameters collected by the Supervisory Control And Data Acquisition (SCADA). A free flow Computational Fluid Dynamics (CFD) simulation is also performed, and it allows one to better interpret the vibration analysis. The main outcome is the interpretation of how wakes and flow turbulences appear in the vibration signals, both at the structural level and at the drive-train level. Therefore, this wind to gear approach builds a connection between flow phenomena and mechanical phenomena in the form of vibrations, representing a precious tool for assessing loads in different working conditions.

Nowadays, the operative range limit of compressors is still a key aspect of the research into turbomachinery. In particular, the study of the mass flow rate lower limit represents a significant factor in order to predict and avoid the inception of critical working conditions and instabilities such as stall and surge. The importance of predicting and preventing these dangerous phenomena is vital since they lead to a loss of performance and severe damage to the compression system and the compressor components. The identification of the typical precursors of these two types of compressor unstable behaviors can imply many advantages, in both stationary and aeronautic applications, such as i) avoiding the loss of production (in industry) and efficiency of systems and ii) reducing the cost of maintenance and repairing. Many approaches can be adopted to achieve this target, but one of the most fascinating is the vibro-acoustic analysis of the compressor response during operation. At the Engineering Department of the University of Ferrara, a test bench, dedicated to the study of the performance of an aeronautic turboshaft engine multistage compressor, has been equipped with a high frequency data acquisition system. A set of triaxle accelerometers and microphones, suitable for capturing broad-band vibration and acoustic phenomena, were installed in strategic positions along the compressor and the test rig. Tests were carried out at different rotational speeds, and with two different piping system layouts, by varying the discharge volume and the position of the electric control valve. Moreover, two different methodologies were adopted to lead the compressor towards instability. This experimental campaign allowed the inception of compressor stall and surge phenomena and the acquisition of a great amount of vibro-acoustic data which were firstly processed through an innovative data analysis technique, and then correlated to the thermodynamic data recorded. Subsequently, the precursor signals of stall and surge were detected and identified demonstrating the reliability of the methodology used for the study of compressor instability. The results of this paper can provide a significant contribution to the knowledge of the inception mechanisms of these instabilities. In particular, the experimental data can offer a valid support to the improvement of surge and stall avoidance (or control) techniques since it presents an alternative way of analyzing and detecting unstable compressor behavior characteristics by means of non-intrusive measurements.

Tendo por pano de fundo a análise da natureza da emergência e do fortalecimento da Cooperação Sul-Sul (CSS) nas últimas décadas, quando comparada com a Ajuda Oficial ao Desenvolvimento (AOD), o objetivo geral desta dissertação consiste em analisar a Cooperação Brasileira para o Desenvolvimento Internacional, conhecida como Cobradi, no setor agrícola africano, especificadamente, em Moçambique. Utilizou-se na pesquisa uma metodologia qualitativa, que buscou apresentar algumas contribuições teóricas ao tema em tela. Amparada nesse referencial teórico, a pesquisa traz uma análise dos investimentos e das trocas comerciais entre Brasil e África, durante os governos de Luiz Inácio Lula da Silva (2003-2010) e de Dilma Rousseff (2011-2016), bem como um estudo de caso limitado a Moçambique. Neste pais foram transferidas algumas políticas públicas brasileira sobre Segurança Alimentar e Nutricional (SAN), sendo em fase de implementação o Programa de Cooperação Tripartida para o Desenvolvimento Agrícola da Savana Tropical em Moçambique (ProSAVANA). Baseadas na teoria de Nicos Poulantzas e nos aportes auxiliares da abordagem estratégico-relacional de Bob Jessop, as considerações finais desta dissertação levam a afirmar que a natureza da Cobradi, transferida a Moçambique, por meio do programa ProSAVANA e de outras políticas públicas brasileiras transferidas a esse país, é ambígua no tocante aos princípios e às práticas defendidos pela CSS; é caracterizada por uma unidade contraditória, no que diz respeito ao caráter da estrutura institucional do setor agrícola; e reproduz, em Moçambique, o modelo de desenvolvimento baseado na articulação das estratégias de acumulação entre mineração, agronegócio e logística, que resultou no ProSAVANA. Este programa atende prioritariamente aos interesses do bloco no poder do Japão, secundariamente, aos interesses do bloco no poder do Brasil e, por último, aos interesses do bloco no poder de Moçambique. Enfim, as políticas públicas sobre segurança alimentar, que tiveram êxito no Brasil e foram bem acolhidas pelos trabalhadores rurais em Moçambique, não aparentam se tornar programas prioritários, pois o bloco no poder em Moçambique subordina estes programas ao modelo de desenvolvimento levado a cabo neste pais. Having the emergence and strengthening of South-South Cooperation (SSC) as the main background, compared to Official Development Assistance (ODA), the general objective of this dissertation aimed to analyze the Brazilian Cooperation for International Development (CID), known as Cobradi, in the African agricultural sector, specifically in Mozambique. A qualitative methodology was used in the research, which sought to present some theoretical contributions to the subject. Supported by this theoretical reference, the research carries out an analysis of the investments and commercial exchanges between Brazil and Africa during the government of Luiz Inácio Lula da Silva (2003-2010) and Dilma Rousseff (2011-2016), as well as a case study limited to Mozambique. In this country, some brazilian public policies on Food and Nutrition Security (FNS) were transferred, and the Triangular Co-operation Programme for Agricultural Development of the Tropical Savannah in Mozambique (ProSAVANA) is in the process of being implemented. Based on Nicos Poulantzas' theory and Bob Jessop's Strategic Relational Approach (SRA) contributions, the conclusions of this dissertation led to the assertion that the nature of Cobradi, transferred to Mozambique through ProSAVANA program and other Brazilian public policies, is ambiguous in relation to the principles and practices advocated by SSC; is characterized by a contradictory unity, with respect to the character of the agricultural sectors institutional structure; and reproduces in Mozambique the development model based on the articulation of the accumulation strategies of mining, agribusiness and logistics, which resulted in ProSAVANA. This program primarily serves the interests of the power bloc of Japan, secondarily the interests of the power bloc of Brazil, and finally the interests of the power bloc in Mozambique. Finally, public policies on food security, which were successful in Brazil and were welcomed by rural workers in Mozambique, do not appear to be priority programs, as power bloc subordinate these programs to the development model carried out in Mozambique.

Purpose – This paper aims at proposing a performance measurement system (PMS) for academic entrepreneurship. Design/methodology/approach – The PMS has been developed through action research carried out within an Italian higher education and research centre on the basis of the literature background, focus groups and interviews. Findings – The study presents a new PMS based on an input–output model for academic entrepreneurship. As a result, a multidimensional framework for measuring technology entrepreneurship is proposed together with a set of key performance indicators (KPIs) to assess the “third mission” of universities. The application of the framework allows demonstration of its validity in public settings. Research limitations/implications – Because the research was conducted in a specific organisation, the possibility of generalizing the results to similar institutions is a key issue. Hence, it is important to distinguish between what is general in scope and what is case-specific. Practical implications – This study contributes to the extant literature on performance measurement of entrepreneurship process within research and higher education institutes that is traditionally focussed at the firm level. From a practitioner perspective, the model can be used both by universities which are interested in measuring their entrepreneurial capital and by other stakeholders who are interested in evaluating the value generation performances of universities. Implications for the society are clarified as well. Social implications – As for the society, the proposed model allows evaluation of the university’s pivotal role in the social and economic development of the region where it is located, especially in terms of new employments and new technology-intensive firms. Originality/value – The PMS is developed according to a process-oriented perspective of the academic entrepreneurship by identifying, for each step, a set of KPIs to meet the information needs of different stakeholders. The proposed PMS allows monitoring each phase of the technology entrepreneurship and managing the results in terms of social and economic impact developed. Contributions in PMS and intellectual capital literature are identified.

This paper proposes an experimental methodology for the analysis of the lubrication regime and wear that occur between vanes and pressure ring in variable displacement vane pumps. The knowledge of the lubrication regime is essential for the improvement of the performance of high pressure vane pumps by reducing wear, increasing the volumetric efficiency and decreasing maintenance costs. Tests using pressure rings of different materials were carried out in order to identify the best material in terms of wear and friction. The proposed methodology is based on Archard's law and takes advantage of wear experimental measurements, an empirical model for the estimation of contact pressure forces and hardness standard tests. The results of the analysis state that low wear and reduced friction can be obtained if elasto-hydrodynamic lubrication between vanes and pressure ring is established. Results have been also verified by an analytical elasto-hydrodynamic model.

Innovation and competition take place increasingly between Business Models (BM), and not just among products, processes, and technologies. Therefore, Business Model Innovation (BMI) becomes the key process to unleash value creation for both established and new companies, and, among these latter, particularly for technological spin-offs. For their constituent characteristics, it emerges that BMI in technological spin-offs appears to be related to the effective management of the Intellectual Capital (IC). Despite this, current research has paid little attention to decline BMI through the lenses of IC. This study aims to provide a contribution in this direction by investigating how technological spin-offs innovate their BM by leveraging their IC dimensions. A review of relevant literature on BMI has been carried out. Then, a case study methodology has been adopted to analyze seven technological spin-offs. The analysis highlighted three main trajectories of BMI, defined in terms of the BMI scope and the main exploited IC dimension. The discussion of findings from a research and practical perspective contributes to the debate on BMI, by providing a new interpretative key based on the relevance of the IC dimensions.

Purpose – Big Data constitute both a recent technological paradigm and an emerging business opportunity through which the adopters of Big Data solutions can implement and experiment the benefits of the open innovation strategy. In such scenario, the ICT companies have the opportunity to leverage the Big Data paradigm to stimulate their customers to undertake open innovation processes. However, the firms operating in the ICT industry have not often any standard way for implementing Big Data projects, and usually resort to agile approaches or ad-hoc development roadmaps that may generate critical issues related to the delivery strategy, software engineering techniques, and team capability. Drawing inspiration from the Open Innovation paradigm and exploiting the results coming from the analysis of the implementation of several Big Data projects, this paper proposes a roadmap for implementing Big Data initiatives. The roadmap proposed allows to solve the above mentioned critical points, and generate value from four key dimensions such as time efficiency in the solution delivery, cost effectiveness in the resources usage, functional efficacy in the business process execution, and full exploitation of the value embedded into the data sources. Design/methodology/approach – Considering the exploratory nature of the research, the complexity and novelty of the topic, the research methodology adopted is based on the grounded theory. The authors analysed ten Big Data initiatives related to several industrial domains, implemented by a multinational company operating in the ICT industry. For each initiative, the authors have examined the technical documentation and made semi-structured interviews to both project managers and technical leaders involved. Originality/value – This paper proposes a roadmap specifically designed for implementing Big Data projects, which draws inspiration from the Open Innovation paradigm. This roadmap allows for overcoming the critical issues characterizing the agile approaches or the ad-hoc development roadmaps currently adopted in Big Data projects, such as delivery strategy, software engineering techniques, and team capability. At the same time, the proposed roadmap may contribute to generate value by ensuring time efficiency, cost effectiveness, functional efficacy and data value exploitation. In such a way, the proposed roadmap is a first methodological contribution that ICT companies can adopt to enhance the success rate of Big Data projects. Practical implications – From a research perspective, the proposed roadmap aims at contributing to the debate on how Open Innovation strategy can fertilise Big Data paradigm. From a practitioner perspective, the results presented represents a first attempt to formalize a structured roadmap for supporting the implementation of Big Data initiatives.

This paper aims to discuss the importance of Living Labs as an effective mechanism that can support the creation of dynamic innovation ecosystems and networks. The analysis of literature related to regional innovation and based on the Quadruple Helix framework, is integrated with exploratory research analysis of 20 cases of Italian Living Labs. The field study is realized through a web-based content analysis and questionnaires. The paper contributes to study how the Living Lab can constitute an effective mechanism supporting the creation of dynamic innovation ecosystems and networks, in the final aim to explore its relevance for setting regional strategies for smart growth, which valorize the internal and external knowledge assets. The paper provides important implications, both at research and policy levels, related with the knowledge-based innovation processes that could be activated at territorial level.

Digital technologies have enabled the emergence of a new breed of business ventures and introduced the concept of digital entrepreneurship as a transformative trend in the study of entrepreneurial processes and their outcomes. In particular, open innovation and collective intelligence have contributed to create a new techno-organizational system - or ecosystem - in which entrepreneurial activities are conceived and conducted. However, despite the significance of the phenomenon, the idea and archetype of Digital Entrepreneurship Ecosystem (DEE) is still largely undertheorized. In particular, there is a need to build a comprehensive definition and define the modalities required to successfully design and govern such kind of ecosystem. This article propose a conceptual breakdown of digital entrepreneurship ecosystem with the purpose to identify the founding constructs and elaborate a definition and the foundations of a management approach. A governance model is defined which includes four key dimensions (how, what, why, how) and six fundamental processes. An illustrative application of the model is finally presented to describe a case of DEE.

Before marketing external gear pumps are subjected to a running in process to increase their efficiency. However, this is one of the most time-consuming tasks of the entire manufacturing process. Therefore, a mathematical model for optimizing the running in process can be a useful tool for time-to-market reduction. In particular, in this paper a model for the analysis of the dynamic behaviour of external gear pumps, developed by the authors in previous works, is modified and used for simulating the running in process. The modified model is presented and validated via experimental data. A good correlation between simulation and test results guarantees the effectiveness of the model in determining the amount and the distribution of the removed material during the running in process. A meaningful reduction (16%) of the global running in time has been achieved with the introduction of a modified running in process drawn from simulation results.

This paper describes the design and application of a dashboard for visualising the interaction of content providers and online users with cultural objects within digital environments. The dashboard combines social network analysis metrics and content analysis indicators and relies on two-mode networks where nodes can be cultural heritage objects, institutional providers (galleries, museums) or individual digital content providers (experts and content aggregators). The links provide information about the digital resources associated to each object. The dashboard offers insights on the evolution of the most central providers, the most sought-after digital resources, and the most popular cultural objects over time. We applied the dashboard to an Italian living lab focused on cultural heritage and to a European platform for sharing cultural digital objects. Results show the emergence of clusters of interest around specific digital resources, and detect contributors sharing new topics of discussion and promoting innovative ways of organising the content.

The pervasiveness of scientific developments has raised the role of entrepreneurship as a driver of socio-economic value. Higher education institutions are thus asked to create entrepreneurial mindset and competencies with the purpose to make students people able to proactively identify opportunities and transform them in market solutions. In particular, engineering education programs can be of relevance to develop technology entrepreneurship competencies through hands-on and experiential approaches. In such vein, this paper proposes a model of entrepreneurship education as an "activation" process which uses four critical levers with the purpose to infuse the essence of entrepreneurship in tomorrow's engineering professionals. The application of the model is exemplified through the analysis of a research training program grounded in the aerospace domain. The key features of the initiative are discussed in the perspective of exploring new models of entrepreneurial engineering education.

PurposeThis paper aims to discuss the role of intangible assets in higher education and research institutions and to present a measurement framework, along with an illustrative application.Design/methodology/approachA review of existing theories and practical experiences is undertaken to build the core conceptual model and a dashboard of indicators. The model is then applied to investigate the mission and performance angles of intellectual capital with reference to an Italian higher education and research institution.FindingsCreating intangible assets is at the core of the mission of education and research organizations. The identification and measurement of intellectual capital are thus an operational priority to evaluate the alignment between strategic orientation and performance within such institutions.Research limitations/implicationsThe research has to be considered as exploratory and presents a single case, resulting in the need for further applications. However, the dashboard of metrics proposed is comprehensive and can thus represent a useful ground for refinements, mostly related to the links between indicators and management/strategy issues.Practical implicationsThe dashboard can be used as a stakeholder communication tool and a tableau de bord to support the strategic decisions related to the human, social and structural capital of education and research organizations.Originality/valueThe paper presents a first discussion on the systematic identification, classification and reporting of intellectual capital indicators in higher education and research.

Wind turbines commonly undergo non-stationary flow and, not rarely, even rather extreme phenomena. In particular, rough terrains represent a challenging testing ground, because of the combination of terrain-driven flow and wakes. It is therefore crucial to assess the impact of dynamic loads on the turbines. In this work, tower and drive-train vibrations are analyzed, from a subcluster of four turbines of a wind farm sited in a very complex terrain. The main outcome of the study is that it is possible to start from the analysis of wind conditions and interpret how wakes manifest in the vibrations of the turbines, both at structural level (tower vibrations) and at the drive-train level. This wind to gear approach therefore allows to build a connection between a flow phenomenon and a mechanical phenomenon (vibrations) and can be precious to assess loads in different working conditions.

Communities of innovation (CoI) was introduced at organisational level to pursue collaboratively innovation activities. By extending this concept at territorial level, they may become government's tools to undertake innovative projects for local development. This work investigates whether and, if so, to what extent local governments support the development of CoI. We focused our attention on two different institutional settings, one in Italy and one in China. We performed a quantitative and qualitative investigation, relying on official data and web sources. With the first, we developed a measure to synthesise the intensity in promoting CoI; with the second, we highlighted the main programs' characteristics and objectives supporting CoI. Results show that in both settings, local governments make significant policy efforts in promoting CoI, focusing on similar objectives and relying on similar tools. This highlights the engagement of governments and the relevance of their industrial policies to support the development of CoI.

According to the Open Innovation approach, collaborative relationships between cultural and creative organisations and business are consistently growing in the last few years. This paper first develops a typology of these relationships. Then, adopting a multiple case-study research method and using a selected sample of Italian manufacturing and services companies, these kinds of collaborative relationships are empirically investigated. Motivations, practices as well as factors enabling or hampering these collaborative relationships are identified and analyzed.

Entrepreneurship and innovation are engines of economic growth and societal progress (Allen 2009; Wennekers and Thurik 1999). In particular, technology-based entrepreneurship has gained relevance as a driver of economic development and the renewal of regions and territories (Phan and Der Foo 2004; Venkataraman 2004). Its potential lies in the transformation of technology-grounded ideas into artefacts and technology applications with market value (Kirzner 1997; Venkataraman and Sarasvathy 2001).

The concept of entrepreneurship is traditionally associated with the initiative of individuals who transform promising business ideas into successful new ventures. In the Schumpeterian view, the most innovative individuals are able to drive sustainable change and creative destruction in specific markets and industries, acting alone or within large companies (Schumpeter 1934, 1949). However, the entrepreneurial process is also engaged in by established organisations, which are able to address the asymmetries between market demand and the potential of socio-technical innovation. On such an extended scale (from individuals to corporations), corporate entrepreneurship is activated as a means of achieving organisational innovation and increasing financial and market performance, with exemplary cases such as Apple, 3M, Procter & Gamble and Google.

The concept of ecosystem has been largely used to indicate the network of complementary actors, resources and relationships required to succeed in knowledge-intensive entrepreneurial initiatives. The development of ecosystems has been mostly considered as a region and industry-independent issue. This paper discusses the relevance of fostering the creation of more entrepreneur-centric ecosystems (“EGO-Systems”) to support an effective idea-to-venture process. A model is presented which includes five components (entrepreneurial actor, stakeholders, project, roadmap, flows) and it is addressed to support technology entrepreneurship initiatives through an innovative approach which is glocal, project-specific and dynamic.