Contextual impacts on industrial processes brought by the digital transformation of manufacturing: a systematic review

The digital transformation of manufacturing (a phenomenon also known as "Industry 4.0" or "Smart Manufacturing") is finding a growing interest both at practitioner and academic levels, but is still in its infancy and needs deeper investigation. Even though current and potential advantages of digital manufacturing are remarkable, in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies has already developed ad hoc strategies necessary to achieve a superior performance. Through a systematic review, this study aims at assessing the current state of the art of the academic literature regarding the paradigm shift occurring in the manufacturing settings, in order to provide definitions as well as point out recurring patterns and gaps to be addressed by future research. For the literature search, the most representative keywords, strict criteria, and classification schemes based on authoritative reference studies were used. The final sample of 156 primary publications was analyzed through a systematic coding process to identify theoretical and methodological approaches, together with other significant elements. This analysis allowed a mapping of the literature based on clusters of critical themes to synthesize the developments of different research streams and provide the most representative picture of its current state. Research areas, insights, and gaps resulting from this analysis contributed to create a schematic research agenda, which clearly indicates the space for future evolutions of the state of knowledge in this field

Effects of Local Specialization of Investment Subsides in Italy

In Italy we currently have a lot of national and regional instruments for financial aids to enterprises. Most of them are not specialized, as syntethetized in the following points: 1. they are refferred to the whole Italian territory; 2. they have generic objects (increase of GNP, reduction of growth differences among regions, employment); 3. they are applied to all the sectors of production; 4. they have common methods of application (automatic, discretional,negotiated). This means that we establish general purposes without further specialization even if we fall into particular purposes.In addition to this types of subsides, there are anymore that are specialized both at territorial and at sectorial level. Among these, the most important are distributed by the Territorial Pacts that are one of the instruments of concerted planning. In this paper we firstly define the specialization of some forms of subsidies; then we analize the performance of two samples of enterprises, that are located in the Apulia Region (NUTS III), the first of which has been benefiting from the state support provided by law n.488/92 (Financial support of the productive activities in depressed zones), and the second one that has been benefiting from the support provided by Territorial Pacts. The enterprises performance have been assessed through quantitative index measured by three main relations: 1. Sales / Assets, that is an indicator measuring the firms efficiency. So it indicates if the total value of sales they?ve carried out, can account for the effectuated investments. 2. Profit / Sales, that estimate the enterprise ability to obtain profits, aging in the market, and let us having indications about prospects of success. 3. Profit / Assets, that assess, in a better way, the capacity in terms of global income of the enterprise. Comparing the average of the three indicators considered, related to supported enterprises, with the same indexes of Mediobanca sample about not-supported enterprises, we obtain interesting results. They have proved that: A. the enterprises having supports are, generally, less efficient than those having no support; B. the firms subsided by Territorial Pacts are more efficient than the other ones subsided by law n.488/92. From the investigation it emerges that the subsides territorially oriented are more efficient than the general support, referred to the same area. So, if we privilege efficiency results, putting the effectiveness ones in a secondary position, we probably should prefer an automatic but specialized aid system, at least from the territorial, dimensional and productive point of view according to preference scales. But, if we want to obtain effectiveness standards too, it is necessary to specialize the interventions and determine specific goals and result indicators.

Determinants of tourism destination competitiveness in the countries most visited by international tourists: Proposal of a synthetic index

Tourism destination competitiveness is a multidimensional concept that is widely studied in the academic literature, but multiple factors make its measurement a difficult task. In this article, we design a synthetic index to rank the 80 countries that attract the majority of international tourists by level of tourism competitiveness. In order to do this, we use all of the simple variables included in the 2017 Travel & Tourism Competitiveness Index, proposing a new methodology for the construction of this synthetic index, which it solves the problems of aggregation of variables expressed in different measures, arbitrary weighting and duplicity of information; issues that remain unresolved by the TTCI. Likewise, we analyse the most influential dimensions in tourism competitiveness. Air transport infrastructures, cultural resources and ICT readiness are the key dimensions that explain the main disparities.Funding Agency Spanish Ministry of Economy, Industry and Competitiveness State Research Agency (SRA) European Union (EU) ECO2017-86822-Rinfo:eu-repo/semantics/publishedVersio

IAMM: A maturity model for measuring industrial analytics capabilities in large-scale manufacturing facilities

Industrial big data analytics is an emerging multidisciplinary field, which incorporates aspects of engineering, statistics and computing, to produce data-driven insights that can enhance operational efficiencies, and produce knowledgebased competitive advantages. Developing industrial big data analytics capabilities is an ongoing process, whereby facilities continuously refine collaborations, workflows and processes to improve operational insights. Such activities should be guided by formal measurement methods, to strategically identify areas for improvement, demonstrate the impact of analytics initiatives, as well as deriving benchmarks across facilities and departments. This research presents a formal multi-dimensional maturity model for approximating industrial analytics capabilities, and demonstrates the model’s ability to assess the impact of an initiative undertaken in a real-world facility