The quest for business value drivers: applying machine learning to performance management

The paper explores the potential role of Machine learning (ML) in supporting the development of a company's Performance Management System (PMS). In more details, it investigates the capability of ML to moderate the complexity related to the identification of the business value drivers (methodological complexity) and the related measures (analytical complexity). A second objective is the analysis of the main issues arising in applying ML to performance management. The research, developed through an action research design, shows that ML can moderate complexity by (1) reducing the subjectivity in the identification of the business value drivers; (2) accounting for cause-effect relationships between business value drivers and performance; (3) balancing managerial interpretability vs. predictivity of the approach. It also shows that the realisation of such benefits requires a combined understanding of the ML techniques and of the performance management model of the company to frame and validate the algorithm in light of the context in which the organisation operates. The paper contributes to the literature analysing the role of business analytics in the field of performance management and it provides new insights into the potential benefits of introducing an ML-based PMS and the issues to consider to increase its effectiveness

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

Embedding eWOM into efficiency DEA modelling: an application to the hospitality sector

This paper develops and tests an innovative DEA model in the hospitality sector, by originally embedding online customer ratings among the outputs of the model. Based on a sample of 268 independent hotels located in Rome (Italy), we test a eWOM-informed DEA model and find that the introduction of online ratings among the outputs of the model significantly affects the assessment of hotels’ efficiency regardless of hotel category. The efficiency rankings generated by the DEA models embedding eWOM are radically different compared to those resulting from DEA models exclusively based on financial variables. The number of hotels improving their position in the efficiency rankings is lower than the number of hotels decreasing in the ranking. However, the average efficiency variation is positive and higher for 2- and 3- stars hotels than for 4- and 5- stars hotels. Implications for researchers in hospitality and tourism, managers and practitioners are discussed

The Semantics of Natural Objects and Tools in the Brain: A Combined Behavioral and MEG Study

Current literature supports the notion that the recognition of objects, when visually pre-sented, is sub-served by neural structures different from those responsible for the semantic processing of their nouns. However, embodiment foresees that processing observed objects and their verbal labels should share similar neural mechanisms. In a combined behavioral and MEG study, we com-pared the modulation of motor responses and cortical rhythms during the processing of graspable natural objects and tools, either verbally or pictorially presented. Our findings demonstrate that conveying meaning to an observed object or processing its noun similarly modulates both motor responses and cortical rhythms; being natural graspable objects and tools differently represented in the brain, they affect in a different manner both behavioral and MEG findings, independent of presentation modality. These results provide experimental evidence that neural substrates responsible for conveying meaning to objects overlap with those where the object is represented, thus supporting an embodied view of semantic processing

Low-dose lenalidomide plus cytarabine induce complete remission that can be predicted by genetic profiling in elderly acute myeloid leukemia patients

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Paramagnetic reentrant effect in high purity mesoscopic AgNb proximity structures

We discuss the magnetic response of clean Ag coated Nb proximity cylinders in the temperature range 150 \mu K < T < 9 K. In the mesoscopic temperature regime, the normal metal-superconductor system shows the yet unexplained paramagnetic reentrant effect, discovered some years ago [P. Visani, A. C. Mota, and A. Pollini, Phys. Rev. Lett. 65, 1514 (1990)], superimposing on full Meissner screening. The logarithmic slope of the reentrant paramagnetic susceptibility chi_para(T) \propto \exp(-L/\xi_N) is limited by the condition \xi_N=n L, with \xi_N=\hbar v_F/2 \pi k_B T, the thermal coherence length and n=1,2,4. In wires with perimeters L=72 \mu m and L=130 \mu m, we observe integer multiples n=1,2,4. At the lowest temperatures, \chi_para compensates the diamagnetic susceptibility of the \textit{whole} AgNb structure.Comment: 4 pages, 4 figures (color

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

Role of microRNAs in the main molecular pathways of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignant neoplasia. HCC is characterized by a poor prognosis. The need to find new molecular markers for its diagnosis and prognosis has led to a progressive increase in the number of scientific studies on this topic. MicroRNAs (miRNAs) are small noncoding RNA that play a role in almost all main cellular pathways. miRNAs are involved in the regulation of expression of the major tumor-related genes in carcinogenesis, acting as oncogenes or tumor suppressor genes. The aim of this review was to identify papers published in 2017 investigating the role of miRNAs in HCC tumorigenesis. miRNAs were classified according to their role in the main molecular pathways involved in HCC tumorigenesis: (1) mTOR; (2) Wnt; (3) JAK/STAT; (4) apoptosis; and (5) MAPK. The role of miRNAs in prognosis/response prediction was taken into consideration. Bearing in mind that the analysis of miRNAs in serum and other body fluids would be crucial for clinical management, the role of circulating miRNAs in HCC patients was also investigated. The most represented miRNA-regulated pathway in HCC is mTOR, but apoptosis, Wnt, JAK/STAT or MAPK pathways are also influenced by miRNA expression levels. These miRNAs could thus be used in clinical practice as diagnostic, prognostic or therapeutic targets for HCC treatment

Diamagnetic response of cylindrical normal metal - superconductor proximity structures with low concentration of scattering centers

We have investigated the diamagnetic response of composite NS proximity wires, consisting of a clean silver or copper coating, in good electrical contact to a superconducting niobium or tantalum core. The samples show strong induced diamagnetism in the normal layer, resulting in a nearly complete Meissner screening at low temperatures. The temperature dependence of the linear diamagnetic susceptibility data is successfully described by the quasiclassical Eilenberger theory including elastic scattering characterised by a mean free path l. Using the mean free path as the only fit parameter we found values of l in the range 0.1-1 of the normal metal layer thickness d_N, which are in rough agreement with the ones obtained from residual resistivity measurements. The fits are satisfactory over the whole temperature range between 5 mK and 7 K for values of d_N varying between 1.6 my m and 30 my m. Although a finite mean free path is necessary to correctly describe the temperature dependence of the linear response diamagnetic susceptibility, the measured breakdown fields in the nonlinear regime follow the temperature and thickness dependence given by the clean limit theory. However, there is a discrepancy in the absolute values. We argue that in order to reach quantitative agreement one needs to take into account the mean free path from the fits of the linear response. [PACS numbers: 74.50.+r, 74.80.-g]Comment: 10 pages, 9 figure

Rough Surface Effect on Meissner Diamagnetism in Normal-layer of N-S Proximity-Contact System

Rough surface effect on the Meissner diamagnetic current in the normal layer of proximity contact N-S bi-layer is investigated in the clean limit. The diamagnetic current and the screening length are calculated by use of quasi-classical Green's function. We show that the surface roughness has a sizable effect, even when a normal layer width is large compared with the coherence length $\xi =v_{\rm F}/\pi T_{\rm c}$. The effect is as large as that of the impurity scattering and also as that of the finite reflection at the N-S interface.Comment: 12 pages, 3 figures. To be published in J. Phys. Soc. Jpn. Vol.71-