Industrial carbon emission intensity: a comprehensive dataset of European regions.

The dataset has been developed within the framework of the EU EIT-Climate Kic Flagship Project “Re-Industrialise” and it includes data of Carbon Emission Intensity (CEI) from industrial sources for the European Regions. CEI is considered as a proxy for analysing the Industrial Sustainability Transition pathways and is calculated as the ratio between CO2 equivalent emissions (CO2e) and Gross Domestic Product (GDP) of the industrial sector over a nine-year timespan, i.e. from 2008 to 2016. CO2e data at plant level have been retrieved from EU Emission Trading System (EU ETS) register and aggregated at different geographical scales, corresponding to the nested structure of NUTS (Nomenclature of Territorial Units for Statistics), proposed by EUROSTAT. Industrial GDP data have been selected from EUROSTAT database to match the industrial sectors covered by EU ETS

Business performance analytics: exploring the potential for performance management systems

Business Performance Analytics (BPA) entails the systematic use of data and analytical methods (mathematical, econometric and statistical) for performance measurement and management. Although potentially overcoming some traditional diagnostic issues related to Performance Management Systems (PMS), such as information overload, absence of cause-effect relationships, lack of a holistic view of the organisation, research in the field is still in its infancy. A comprehensive model for operationalising analytics for diagnostic and interactive PMS is still lacking. Adopting an action research approach, this paper addresses this gap and develops a five-step framework applied to a company operating in the construction industry. The results show that in addition to encouraging dialogue, BPA can contribute to identifying critical performance variables, potential sources of risk and related interdependencies. A number of critical issues in implementing data-based approaches are also highlighted, including data quality, organisational competences and cultural shifts

Multilevel-growth modeling for the study of sustainability transitions.

Sustainability Transitions (ST) is a complex phenomenon, encompassing environmental, societal and economic aspects. Its study requires a proper investigation, with the identification of a robust indicator and the definition of a suitable method of analysis. To identify the most informative geographical boundaries for analysing ST pathways, we consider the Carbon Emission Intensity (CEI) and estimate a four-level growth model to study its pattern over time for all the EU regions. We apply this model to a novel longitudinal dataset that covers CEI data of European regions at four different geographical scales (state, areas, regions, and provinces) over a nine-year timespan. This approach aims at supporting the decision-makers in developing more effective sustainability transitions policies across Europe, especially focusing on regions and overcoming the well-known “one-size fits all” approach. • The unconditional growth model has been applied to a multi-level structure considering four levels, defined by three geographical scales and time. • The ideal structure of the model would have required five levels, but the sample size of the dataset made the application computationally unfeasible; • The application of the model allowed to identify patterns of stability and change over time of the variable amongst different geographical units

Treatment Of Steroid-Refractory Acute GVHD With Mesenchymal Stem Cells Improves Outcomes In Pediatric Patients; Results Of The Pediatric Subset In A Phase III Randomized, Placebo-Controlled Study

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Innovative value-based price assessment in data-rich environments: Leveraging online review analytics through data envelopment analysis to empower managers and entrepreneurs

This work introduces, develops, and empirically applies an innovative approach aimed at assessing selling prices based on the value perceived by the customers, as measured by electronic word-of-mouth (eWOM) in the guise of online reviews. To achieve this aim, it applies a constant return to scale Data Envelopment Analysis (DEA) approach where the price is the input, and the value attributes are the outputs measured through eWOM in the form of online reviews. We empirically apply the model to the hotel sector by considering both the prices and the service attributes (i.e., staff, location, cleanliness, comfort, facilities and free wi-fi) of 364 hotels based in two leading Italian tourism destinations: Milan and Rome. Our findings suggest that online review analytics can be suitably embedded into analytical models to assess prices. The index developed innovatively supports value-based pricing by means of online review analytics and it is easy-to-perform, and parsimonious as it is based on widely available information on the Internet

Supplier's total cost of ownership evaluation: a data envelopment analysis approach

Supplier Total Cost of Ownership (TCO) is a widely-known approach for determining the overall cost generated by a supplier relationship, but its adoption is still limited. The complex calculations involved - and in particular the activity-based costing procedure for computing the cost of managing the relationship - pose a major obstacle to widespread TCO implementation. The purpose of this work is to formulate a Data Envelopment Analysis application (denoted 'TCO-based DEA') that can act as a proxy for TCO, and to test its ability to approximate the results of TCO with less effort. The study is based on the analysis of two categories of suppliers (74 in total) of a medium-sized Italian mechanical engineering company. The results show that TCO-based DEA is able to significantly approximate the outcomes of TCO, for both the efficiency indexes and rankings of suppliers, whilst requiring substantially less effort to perform the analysis. To our knowledge, this is the first study to develop a DEA-based tool for approximating TCO and to test it in a real-world setting. The research shows significant potential within the supply chain management field. In particular, TCO-based DEA can be used for analysing suppliers' performance, rationalising and reducing the supplier base, assisting the negotiation process

Esempio di pianificazione economico-finanziaria

Il contributo approfondisce un'analisi combinata e comparata di due modelli di previsione economico-finanziaria applicata ad un medesimo caso, evidenziandone e motivandone le differenze nei risultati. Evidenzia anche modelli di simulazione what if e goal seeking applicati alle dimensioni economico-finanziarie aziendali

Applying business analytics for performance measurement and management. The case study of a software company

The concept of Business Performance Analytics (BPA) represents the adoption of analytical methods to support strategy control and (re)formulation. The purpose of the paper is to explore the potential support that BPA can provide for performance management systems. The study, through an interventionist approach, empirically tests a 5-step BPA framework (Raffoni et al. \u2013 forthcoming -) and provides insights for further developments. The longitudinal study, conducted at a company operating in the data-security industry, supported the analysis of BPA potential and offered a number of insights to refine the framework and shed light on critical organisational issues. This paper offers both theoretical and practical suggestions. It is one of the few attempts to investigate the potential of Business Analytics in enhancing strategic control. It provides insights in a practical framework that could be used to guide further research in the area and provides an account of potential challenges faced by businesses when trying to move to strategic control with a data-driven approach

Output diretti e indiretti dello sviluppo di un sistema di cost accounting tra teoria e pratica

sistemi di cost accounting sono sistemi afferenti alla contabilit\ue0 analitica aziendale che hanno lo scopo di determinare il costo di uno specifico oggetto (cost object): un prodotto, una commessa, un servizio. Chiunque abbia frequentato almeno un Corso di Laurea triennale in Economia, si sar\ue0 sentito raccontare che la contabilit\ue0 analitica ha tre fondamentali finalit\ue0: il supporto alla contabilit\ue0 generale; il supporto al controllo di gestione e il supporto alle decisioni manageriali. Scopo del presente articolo \ue8 quello di declinare queste tre finalit\ue0 (\u201coutput diretti\u201d) in maniera approfondita, cercando di comprenderne anche frequenti deformazioni che rischiano di limitare pesantemente l\u2019efficacia del sistema. Dall\u2019altra parte, si vuole mostrare come nell\u2019ambito del processo di definizione o revisione del sistema di cost accounting si generi una note- vole quantit\ue0 di altre conoscenze manageriali (\u201coutput indiretti\u201d). Gli output indiretti, specie in aziende moderatamente managerializzate e che quindi presentano varie zone prive di controllo, con dati limitati e procedure basate sull\u2019empiri- smo, possono risultare anche molto pi\uf9 significativi degli stessi output diretti

L'analisi economico-finanziaria dei fornitori: gestione di rischio e performance della Supply Chain

Gli acquisti di materie e servizi mediamente erodono oltre il 70% dei ricavi aziendali, per cui una efficace gestione delle relazioni di fornitura è evidentemente un fattore critico di generazione di vantaggio competitivo. In tale ottica, il bilancio del fornitore è spesso una delle poche fonti di informazioni disponibili per supportare le azioni di buyer e responsabili acquisti. In tale contesto, un’approfondita analisi economico-finanziaria, partendo dal bilancio del fornitore, può fornire indicazioni fondamentali circa le più opportune azioni da intraprendere: richiesta di dilazioni, sconto, difesa di un fornitore critico e in difficoltà, assegnazione di nuovi componenti, ecc.. L’articolo presenta un modello teorico e interessanti casi applicativi che evidenziano come l’analisi economico-finanziaria del fornitore possa supportare il processo decisionale nell’ambito del Supply Chain Management. Nello specifico, i modelli di analisi e gli indicatori utilizzati vengono differenziati in funzione delle caratteristiche di dimensione e rischio della fornitura, per evidenziare come relazioni di fornitura differenti richiedano approcci e valutazioni differenti