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Aim of the present study is to describe our robot-assisted simple prostatectomy technique and to report 6-month surgical and clinical outcomes.Eighty men were consecutively submitted to robot-assisted simple prostatectomy in our institution from October 2019 to October 2020. All procedures were performed by the same surgical team. Diagnostic preoperative assessment was based on history, symptoms evaluation by International Prostate Symptom Score, digital rectal examination, flowmetry with post-void residual volume measurement by abdominal ultrasound, prostatic volume estimation by MRI, PSA dosage. Under combined general and subarachnoid anesthesia, surgery was performed via a transperitoneal approach using a Da Vinci Si system in the four-arm configuration. Operative time, blood loss, hospital stay, catheterization time, intraoperative and postoperative complications were assessed. Clinical postoperative 6 months of evaluation was based on physical examination, flowmetry with post-void residual volume measurement, PSA dosage, and International Prostate Symptom Score.Mean operative time was 105.29 min, mean hospital staying 5.4 days. Blood loss was low in all cases and only 2 patients received transfusion. Catheterization time was 7 days. According to the Clavien-Dindo classification, only minor (grade I and grade II) intraoperative and postoperative complications were observed. At 6-month postoperative assessment, a statistically significant increase of urinary flow indexes and bladder capacity was recorded, as a significant reduction of urinary residual volume. No patient experienced stress urinary incontinence and the mean postoperative IPSS score was significantly reduced to 4.3. Two patients were diagnosed with incidental prostatic cancer at the histopathological examination.Data collected in our experience on a large cohort confirm efficacy and safety of Robot-Assisted Simple Prostatectomy. This procedure allows both short operative time and hospital staying, with low incidence of perioperative complications. This surgical technique can therefore be considered a valid alternative to other procedures for the surgical treatment of large volume prostates. Randomized prospective and comparative studies are warranted in the future to assess if different RASP techniques provide similar surgical and functional outcomes.

PurposeIn times of crisis, innovation management and specifically Research and Development (R&D) investments are critical to temper company losses and stimulate higher revenues. Environmental policies, for their potential to stimulate environmental innovations and efficient management of resources, may hold a magnifying role in this relationship. By relying on the distinction between regulatory policies and institutional incentives, this paper argues about the moderating role of environmental policies between a firm's R&D expenses and its performance.Design/methodology/approachHypotheses are tested on data collected from a sample of small and medium-sized Chinese enterprises after the 2008 financial crisis.FindingsFindings reveal positive moderating effects of both regulatory pressures and institutional incentives, with a more significant effect of government support. The highest impact is reached when both these types of policies are present.Originality/valueThe theoretical and methodological relevance of this distinction, the importance of an appropriate mix of environmental policies in policymaking and their resilience building role in stimulating environmental innovations in the aftermath of crises are discussed.

PurposeFactors such as stakeholder requirements, emergence of exponential technologies, global business operations and pressures for sustainability increase the complexity of modern projects. This article aims to contribute by developing a systems view of project elements and relations among the same.Design/methodology/approachThe article is based on a design science process and uses business management, project management and the system dynamics literature to support the construction of a conceptual framework, which is preliminary validated using practitioner feedback.FindingsThe project management model includes: (a) a systems view of a project in terms of 5 subsystems, 9 components and 27 dimensions; (b) a flow diagram showing 11 key relations among project attributes and (c) a discussion of ten system archetypes which can be identified in the management of a project.Research limitations/implicationsWhereas the application of systems thinking in project management has been mostly addressed to build system dynamics tools, this article advances the discussion by providing a framework useful to support theory development and contextual knowledge construction in project management activities.Practical implicationsThe article provides (project) managers with an articulated project management model and insights to address the complexity of modern project activities.Originality/valueThe main value of the research stays in the integrative nature of the presented framework, along with its twofold focus on components and flows (dynamic view).

The affirmation of open innovation and collaborative systems is enabling unprecedented opportunities to create business value while facilitating multistakeholder conversation on sustainability issues. In particular, platform-based models are emerging as organization archetypes able to facilitate cooperative dynamics among industrial actors, policy makers, academicians, scientists, and citizens. In this article, we use interdisciplinary business management and collaborative innovation literature to build the conceptual framework of a multisided platform as a collaboration environment gathering actors willing to define responses to sustainable development challenges. We present five dimensions or “genes,” that is, the focus and strategic intent or orientation of the platform (what), the participating sides, actors and groups (who), the actions, flows and coordination mechanisms (how), and the value drivers, benefits and externalities (why), and the rules regulating the affiliation and interaction processes (governance). We also present and discuss 30 subtopics or management items that are associated with the five dimensions defined. We then apply the conceptual model to analyze a case in the climate change endeavor and to show how competitive and cooperative dynamics can be virtuously integrated to provide individual- and company-driven responses to a timely socioenvironmental issue. The article provides a new perspective on collaboration to enhance social development, and it offers theoretical and practitioner insights for a broad interdisciplinary audience including scholars, practitioners, business, and platform managers.

PurposeIn recent years, the penetration of digital technologies in the financial industry determined the arising of Fintech, which generated a dynamic and rapid change that business operators and supervisory authorities in the banking industry are struggling to follow it. This is especially due to issues affecting financial intermediaries and customers, and potential risks of stability of the financial system. The aim of this paper is to provide a review of Fintech in the banking industry thus to update the knowledge about technology innovation in the banking sector, identify the major trends in the domain and delineate future research directions.Design/methodology/approachThe study reviews 377 articles indexed on Scopus from 2014 to 2021 that focus on Fintech and the banking industry. The methodology adopted is structured in two steps: the keywords selection and the analysis of the documents extracted. The first step identified “Fintech” and “bank” as keywords to be searched within the title, abstract or keywords of documents indexed on Scopus; whereas the second step combined R and VOSviewer to provide a descriptive analysis of the dataset and the analysis of keywords and occurrences, respectively.FindingsResults achieved in the study allow providing a systemic view of the Fintech in the banking industry, including the emergent phenomenon of digital banking. In particular, it is provided with a general overview and descriptive information on the entire sample of documents analyzed, their authors, the keywords used and the most cited works. Besides, a deepening on the model of digital banking is provided, by delineating the six dimensions of the key effects generated by the digital bank model.Originality/valueTwo main elements of originality characterize this study. The first one is related to the fact that few review studies have been published on Fintech in the banking industry, and the second one concerns the multiple dimensions of the impact of Fintech in the banking sector, which includes customer, company, bank, regulation authority and society.

In the last years, Blind Deconvolution methods demonstrated their effectiveness for the diagnostics of rotating machines through the extraction of impulsive signatures directly from noisy observations. Recently, in this scenario the explicit combination between Blind Deconvolution and cyclostationary theory strongly improved the fault detection ability of this diagnostic tool. This work presents a novel criterion based on the Fourier–Bessel series expansion instead of the common Fourier transform. This idea comes from the comparison between the mathematical nature of the Fourier–Bessel and the Fourier series, based on modulated and constant amplitude sinusoidal functions, respectively. The two criteria are compared through the analysis of both simulated and real vibration signals of faulty bearings. The results highlight the ability of the proposed criterion to detect the fault-related source with a lower number of characteristic cyclic frequency harmonics, strongly reducing the computational time required by the algorithm.

Purpose This paper aims to highlight how big social data (BSD) and analytics exploitation may help destination management organisations (DMOs) to understand tourist behaviours and destination experiences and images. Gathering data from two different sources, Flickr and Twitter, textual and visual contents are used to perform different analytics tasks to generate insights on tourist behaviour and the affective aspects of the destination image. Design/methodology/approach This work adopts a method based on a multimodal approach on BSD and analytics, considering multiple BSD sources, different analytics techniques on heterogeneous data types, to obtain complementary results on the Salento region (Italy) case study. Findings Results show that the generated insights allow DMOs to acquire new knowledge about discovery of unknown clusters of points of interest, identify trends and seasonal patterns of tourist demand, monitor topic and sentiment and identify attractive places. DMOs can exploit insights to address its needs in terms of decision support for the management and development of the destination, the enhancement of destination attractiveness, the shaping of new marketing and communication strategies and the planning of tourist demand within the destination. Originality/value The originality of this work is in the use of BSD and analytics techniques for giving DMOs specific insights on a destination in a deep and wide fashion. Collected data are used with a multimodal analytic approach to build tourist characteristics, images, attitudes and preferred destination attributes, which represent for DMOs a unique mean for problem-solving, decision-making, innovation and prediction.

The strategic relevance of innovation and scientific research has amplified the attention towards the definition of quality in research practice. However, despite the proliferation of evaluation metrics and procedures, there is a need to go beyond bibliometric approaches and to identify, more explicitly, what constitutes good research and which are its driving factors or determinants. This article reviews specialized research policy, science policy and scientometrics literature to extract critical dimensions associated with research quality as presented in a vast although fragmented theory background. A literature-derived framework of research quality attributes is, thus, obtained, which is subject to an expert feedback process, involving scholars and practitioners in the fields of research policy and evaluation. The results are represented by a structured taxonomy of 66 quality attributes providing a systemic definition of research quality. The attributes are aggregated into a three-dimensional framework encompassing research design (ex ante), research process (in-process) and research impact (ex post) perspectives. The main value of the study is to propose a literature-derived and comprehensive inventory of quality attributes and perspectives of evaluation. The findings can support further theoretical developments and research policy discussions on the ultimate drivers of quality and impact of scientific research. The framework can be also useful to design new exercises or procedures of research evaluation based on a multidimensional view of quality.

PurposeThe paper aims to propose a knowledge visualization approach and algorithm to support public decision makers to define the inner areas, which represents a strategic topic in the European debate about territorial inequality and development.Design/methodology/approachThe study has been developed by following the design science research, which includes six steps: problem identification and motivation; identification of the objectives for a solution; design and development; demonstration; evaluation; and communication. As for the design and development step, the proposed approach and algorithm ground on association mining to discover hidden relationships existing among municipalities. They have been applied to analyse the 97 municipalities of the Lecce province, and each municipality has been described through 30 multi-domain indicators organized into seven categories, whose data have been collected from institutional datasets, local sources or web-scraping process.FindingsA set of complementary analyses has been generated through the construction of dynamic and interactive knowledge maps that show “similar” municipalities according to the indicators selected.Originality/valueThe approach and algorithm proposed allow discovering similarities existing among distinct municipalities, based on the analysis of a set of multi-domain indicators. The approach may complement or completely substitute the existing ones used to define inner areas, thus overcoming both the methodological limits of the “top-down” line imposed by the central legislator, and the “bottom-up” paradox consisting in the illusion that single (and often small) towns have the economic and cognitive resources necessary to implement effective territorial mapping and development strategies. In such a way, policy makers can be aware on similarities existing among distinct towns and can thus share cognitive and financial resources to define a common plan and a set of practices for territorial development.

Highlights • COVID-19 emergency forced the Italian Universities to reorganize teaching in entrepreneurship education. • Digital technologies can support the development of entrepreneurial mindset. • Building an entrepreneurship education curriculum through distance learning technologies is critical. • Digital technologies can enhance successfully education ‘about’ entrepreneurship. • Digital technologies present some critical issue when used in educating students ‘for’ entrepreneurship. • CLab@Salento offered a favourable environment to experiment the use of digital tools for the creation of entrepreneurial mindset using a blended learning approach., The COVID-19 crisis has forced universities worldwide to seek urgent solutions to reconfigure traditional education programs for distance learning. The transformation process faces a number of complexities deriving from both institutional and contextual factors. It may generate threats and as well as opportunities to enhance the education system and prepare for potential future emergencies. In this article, we adopted a combined research approach to describe the experience of the Contamination Lab of the University of Salento (CLab@Salento), an entrepreneurship education program focused on innovative and technology-based entrepreneurship for university students. Moving from the analysis of the main challenges the pandemic generated for the institution, students and faculty, we illustrate the process of redesigning the entrepreneurial learning program by leveraging digital technologies. We show a new approach to entrepreneurial storytelling, pitching and business planning and development through digital technologies. We also report the outcomes of a student survey to highlight the strengths of the redesigned program and some weaknesses, especially associated with digital technologies’ limitations in education, which represent areas for future improvement. The study contributes at theory level with a new discussion on digital-supported entrepreneurship education. At practitioner level, it offers insights on redesigning traditional university programs to effectively address emergencies.

Purpose This study aims to investigate the Big Social Data (BSD) paradigm, which still lacks a clear and shared definition, and causes a lack of clarity and understanding about its beneficial opportunities for practitioners. In the knowledge management (KM) domain, a clear characterization of the BSD paradigm can lead to more effective and efficient KM strategies, processes and systems that leverage a huge amount of structured and unstructured data sources. Design/methodology/approach The study adopts a systematic literature review (SLR) methodology based on a mixed analysis approach (unsupervised machine learning and human-based) applied to 199 research articles on BSD topics extracted from Scopus and Web of Science. In particular, machine learning processing has been implemented by using topic extraction and hierarchical clustering techniques. Findings The paper provides a threefold contribution: a conceptualization and a consensual definition of the BSD paradigm through the identification of four key conceptual pillars (i.e. sources, properties, technology and value exploitation); a characterization of the taxonomy of BSD data type that extends previous works on this topic; a research agenda for future research studies on BSD and its applications along with a KM perspective. Research limitations/implications The main limits of the research rely on the list of articles considered for the literature review that could be enlarged by considering further sources (in addition to Scopus and Web of Science) and/or further languages (in addition to English) and/or further years (the review considers papers published until 2018). Research implications concern the development of a research agenda organized along with five thematic issues, which can feed future research to deepen the paradigm of BSD and explore linkages with the KM field. Practical implications Practical implications concern the usage of the proposed definition of BSD to purposefully design applications and services based on BSD in knowledge-intensive domains to generate value for citizens, individuals, companies and territories. Originality/value The original contribution concerns the definition of the big data social paradigm built through an SLR the combines machine learning processing and human-based processing. Moreover, the research agenda deriving from the study contributes to investigate the BSD paradigm in the wider domain of KM.