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Since 2012, with the Growth Decree 2.0, the Italian Government has been engaged in promoting the establishment and the growth of new innovative startups with a high technological value. The general objective of the policy is to promote sustainable growth, technological advancement and innovation. In the Decree framework, startups have to own an innovative character that is identified by at least one of the following three criteria: investments in research and development, qualified workforce, holding patents or registered software. Such three characteristics can be considered as innovation inputs able to create the conditions for a competitive advantage and greater economic performance. The research objective is to analyze how innovation inputs in innovative startups affect their economic performance. Each input factor can have a different impact on the company profitability. To this end, we apply the methodology SMAA for strategic management analysis and assessment (or SMAA-S) to detect the relation between innovation and profitability in Italian startups.

Evaluating information systems has proven to be a most difficult task. Methodologies of analytical frameworks for evaluating information systems can be placed into four categories:

There are many phenomena in information science which, when quantified, yield variants of the hyperbolic frequency distribution and are characterized by long straggling tails. Conventional statistical sampling theory offers no general techniques for the confident analysis of finite discrete distributions of this kind. A sampling theorem, based on the binomial probability distribution, but otherwise distribution‐free, is derived and some of its applications are illustrated numerically. One application answers Kendall's question: How many additional periodicals would be found on doubling the period of publication within which periodicals contributing to a specified topic are enumerated? The effects of sampling truncated distributions are also briefly discussed.

That part of human behaviour which is not rigidly determined by external constraints can be considered as a sequence of more or less free choices. One can talk of a choice only if it is one of several alternatives, and of a free choice only in so far as it is not determined by conditions over which the individuals have no control. Moreover, we recognise an alternative only if it is actually elected by at least a fraction of a population. This leads to the concept of statistical freedom. Postulates are formulated which must be satisfied by any numerical measures of statistical freedom, and certain mathematical expressions are proposed which are shown to conform to these postulates. Statistical freedom has two fundamental features, which appear as factors in its numerical measure: diversity and independence. The measures of diversity and independence are derived in the first place front a certain model of society, but once they are obtained, the model is discarded, and the statistical coefficients are justified by their mathematical properties. Safeguards against arbitrary manipulation of statistical material are discussed, and the potential use of the new measures is illustrated by application to the problem of choice of profession.

Recent work has shown that potentially useful predictions of the circulation of library materials can be made which do not require very restrictive assumptions about underlying probability distributions. In the same spirit, we here consider one of the classic problems of bibliometrics, viz. predicting the number of ‘new’ journals carrying ‘relevant’ articles in the future, using both established parametric approaches and the newer, empirical methods.

In community question answering (CQA), people who answer questions assume readers have mastered the content in the answers. Nevertheless, some readers cannot understand all content. Thus, there is a need for further explanation of the concepts that appear in the answers. Moreover, the large number of question and answer (Q&A) documents make manual retrieval difficult. This paper aims to alleviate these issues for CQA websites.

In the paper, an algorithm for recommending explanatory Q&A documents is proposed. Q&A documents are modeled with the biterm topic model (BTM) (Yan et al., 2013). Then, the growing neural gas (GNG) algorithm (Fritzke, 1995) is used to cluster Q&A documents. To train multiple classifiers, three features are extracted from the Q&A categories. Thereafter, an ensemble classification model is constructed to identify the explanatory relationships. Finally, the explanatory Q&A documents are recommended.

The GNG algorithm shows good clustering performance. The ensemble classification model performs better than other classifiers. The both effect and quality scores of explanatory Q&A recommendations are high. These scores indicate the practicality and good performance of the proposed recommendation algorithm.

The proposed algorithm alleviates information overload in CQA from the new perspective of recommending explanatory knowledge. It provides new insight into research on recommendations in CQA. Moreover, in practice, CQA websites can use it to help retrieve Q&A documents and facilitate understanding of their contents. However, the algorithm is for the general recommendation of Q&A documents which does not consider individual personalized characteristics. In future work, personalized recommendations will be evaluated.

A novel explanatory Q&A recommendation algorithm is proposed for CQA to alleviate the burden of manual retrieval and Q&A overload. The novel GNG clustering algorithm and ensemble classification model provide a more accurate way to identify explanatory Q&A documents. The method of ranking the explanatory Q&A documents improves the effectiveness and quality of the recommendation. The proposed algorithm improves the accuracy and efficiency of retrieving explanatory Q&A documents. It assists users in grasping answers easily.

This study aims to identify the critical success factors of public private partnership (PPP) power projects in Ghana and further evaluates the most significant critical success factors (CSFs) influencing both the public and private sector participation in PPP power projects.

Ranking-type Delphi survey in two rounds was conducted to establish a comprehensive list of critical success factors of PPP power projects. Using purposive and snowball sampling techniques, experts were targeted for the Delphi survey. Mean score ranking, Cronbach’s alpha coefficient and Kendall’s concordance were used for analysis.

From the list of 37 critical success factors, 9 CSFs were deemed to be extremely significant. The five topmost CSFs were as follows: shared authority, trust and communication between public and private sectors; necessity of power project; debt guarantee to enable private partner to raise funds from the local or international financial markets; appropriate risk allocation and risk sharing; and thorough and realistic assessment of cost, projections and benefits.

The CSFs identified and prioritized in this study have the propensity to trigger policy development towards the PPP power sector in Ghana and developing countries that shares similar context. This is because the study has wide implications for financing, politics, procurement, regulations, legal and capacity building.

The coronavirus disease 2019 (COVID-19) pandemic drastically changed work arrangements, but COVID-19's impact on employee leave utilization is unclear. The authors sought to understand how sick leave and vacation leave utilization changed during the pandemic among clinical and non-clinical departments at an academic medical center (AMC).

Clinical departments were defined as work units with a primary mission of providing direct patient care. Per-person, per-month leave utilization data were obtained from the AMC's time-keeping system for 3 clinical departments and 4 non-clinical departments in the first 12 months of the pandemic and the preceding 12 months. Monthly data for each department were analyzed with mixed-effects regression.

Available data represented 402 employees from 3 clinical departments and 73 employees from 4 non-clinical departments. The authors found no statistically significant change in sick leave utilization among either clinical or non-clinical departments. Vacation leave utilization decreased during the pandemic by 5.9 h per person per month in non-clinical departments (95% confidence interval [CI]: −8.1, −3.8; p < 0.001) and by 3.0 h per person per month in clinical departments (95% CI: −4.3, −1.7; p < 0.001).

Among employees in clinical departments, the authors found no increase in sick leave utilization and a decrease in vacation utilization. These findings are concerning for presenteeism, risk of burnout or understaffing resulting in workers' inability to take time away from work in clinical departments.

Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences has received much attention. In this work we make a surprising claim. Clustering of time series subsequences is completely meaningless. More concretely, clusters extracted from these time series are forced to obey a certain constraint that is pathologically unlikely to be satisfied by any dataset, and because of this, the clusters extracted by any clustering algorithm are essentially random. While this constraint can be intuitively demonstrated with a simple illustration and is simple to prove, it has never appeared in the literature. We can justify calling our claim surprising, since it invalidates the contribution of dozens of previously published papers. We will justify our claim with a theorem, illustrative examples, and a comprehensive set of experiments on reimplementations of previous work.

Objective and study design: to assess quality of a quick and early diagnosis route (QED) by determining effectiveness and cost‐ effectiveness of five clinics compared with three conventional outpatient clinics. Prospective economic evaluation. Six‐month cohort of all referrals (November 1996‐April 1997). Subjects: all referrals for suspected cancers of: upper gastro‐intestinal tract; urinary tract, prostate and testis; skin. Effectiveness: median days saved between GP referral and date of: diagnostic appointment; consultant decision; intervention. Results: GP referral to diagnostic appointment: QED was effective (median days) for all clinics. Diagnostic appointment to consultant decision: QED was effective for testicular and haematuria clinics. Consultant decision to intervention: QED was effective for haematuria, testicular and melanoma clinics. Cost‐effectiveness: extra (incremental) NHS cost per patient diagnosed. Results: Less than £5 per day saved between GP referral and diagnostic appointment for: endoscopy; haematuria; prostate; testicular; melanoma. Less than £3 per day saved between GP referral and consultant decision for: testicular; haematuria. Less than £3 per day saved between GP referral and intervention for: endoscopy; haematuria; testicular; melanoma. Conclusion: A “quick and early” diagnostic route provides a higher quality service through improved effectiveness and cost‐effectiveness compared to conventional outpatients.