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We examine how experiential learning from both previous technology transfer experience and the disclosure of discoveries impact universities’ technology transfer outcomes, in terms of the number of spinoffs created and licenses granted, while acknowledging that TTOs provide specialized resources that support technology transfer processes. By using panel data models on a sample of public Spanish universities for the 2006–2011 period, our model introduces discovery disclosures as an instrument to account for the endogenous nature of the scientific research process. Results show that spinoff creation and license granting depend on their own experiential learning and on the number of discovery disclosures, which in turn depends on its own experiential learning. Technology transfer is influenced by two learning processes connected to technology transfer outcomes and discovery disclosures. Also, the effect of TTOs’ specific resources appears as not significant. In the context of Spanish universities, the findings support the view that, compared to TTOs’ staff specialization, accumulated knowledge from their own experience adds more value for generating technology transfer outcomes., Peer Reviewed, Postprint (published version)

Supply disruption has been recognized as one of the most important risks of a supply chain and decision-makers are prone to be overconfident in making judgments with uncertainty. In such a situation, we investigate the impact of suppliers’ overconfidence (over-estimation and over-placement) on the buyer’s choice between two widely adopted auction formats, namely, the first-score and second-score. Addressing this problem, we build a reverse auction model where unreliable suppliers are overconfident about their supply probability. For benchmark, we analyze the case when suppliers are cognitively unbiased and show that both auctions generate the same expected payoff for the buyer, and both auctions are socially efficient and optimal. When suppliers are overconfident, we show that the two auctions are not necessarily equivalent and optimal and we give the conditions under which the two reverse auctions are equivalent and socially efficient, i.e., the buyer or a social planner can freely choose either format. We also show that suppliers’ over-estimation and over-placement have different impacts on their bidding strategies and the auction performance, and they have opposite influences on the buyer and suppliers. Ascertaining the impacts of overconfidence on auction performance, our findings help managers choose a better auction format when facing overconfident unreliable suppliers, Postprint (author's final draft)

Several studies have investigated whether there is a relationship between diversity on a company's board of directors and its performance. The diversity considered has been mainly gender and ethnicity, with a few studies also investigating that of education and age. The results obtained varied, with some studies finding no relationships and others finding positive or negative ones. This study will focus on the Italian region of Piedmont, which is characterized by the presence of hi-tech and low-tech firms (such as wineries) and aims to investigate and verify the existence of a link between gender and ethnic diversity and firm performance in terms of ROA and ROE. To do so, three data sets were analysed: one with startups only, one with manufacturing companies, and the last one combining the previous two. The analysis technique used is that of linear regression. Diversity was modelled as Blau indices and represents the independent variables. ROA and ROE, on the other hand, are the dependent variables. Company size, modelled as the logarithm of revenue, is instead used as the control variable. The models analyse the independent variables first individually and then jointly. The results report the nonexistence of a relationship in almost all cases, evidenced by very high p-values and very low adjusted R squares. These findings are also reflected in the literature reviewed. In contrast, the mixed sample reports a negative relationship between ethnic diversity and ROA and ROE, with very negative coefficients and highly significant p-values; however, the R square remains quite low. These results may be due to three main reasons: nationality mix increases transaction and communication costs, greater innovation by mixed boards leads to worse results in the short run and nationality mix does not add value to the company

This thesis focuses on the development of a Predictive Business Analytics tool tailored for the real estate sector, driven by the crucial need to accurately estimate property prices. Leveraging sophisticated data analysis techniques using R programming language, the tool serves as a conduit for transforming the complex dynamics of the real estate market into clear and actionable insights. By aggregating comprehensive data from one of the leading real estate websites, Idealista, and integrating essential property features, the tool establishes a predictive model with high precision in estimating property prices. The primary objective is to empower stakeholders in the real estate sector with an easy-touse and robust solution. Expanding its scope beyond merely assessing the fairness of the listed price, the tool functions as a mechanism to identify potential buying opportunities, thereby fostering a more informed decision-making process. The study begins with an in-depth analysis of the real estate market in Catalonia, recognizing its dynamic nature influenced by various factors. Subsequently, focusing on the city of Terrassa, the thesis strategically refines the predictive model through meticulous data analysis, achieving high precision, with an error margin of approximately €4,000 in almost all cases. In conclusion, the developed tool significantly enhances transparency and aids in the decision-making process, contributing to the creation of a fairer real estate market. The inclusion of real property listings in the dataset facilitates user actions with the Idealista website, and the tool's adaptability to new listings ensures continuous relevance and updates. This project successfully achieves its stated objectives and serves as a testament to the transformative potential of predictive analytics in the real estate industry.

Digitalization has played a key role in enabling the delivery of service-based solutions by facilitating customer-oriented needs-finding and personalized problem-solving capabilities. Artificial intelligence (AI) and Internet-of-Things (IoT) are decisive technologies in this process. This study evaluates how the use AI and IoT platforms impact solution delivery business models among servitized and non-servitized businesses. By running regression models on a sample of 213 businesses for 2023, it was found that the use of IoT platforms, rather than AI platforms, significantly assist companies down all four solution delivery continuums. Additionally, results indicate that the combined use of IoT platforms when servitizing leads to greater customer embeddedness, whereas the use of AI platforms among servitized firms significantly contributes to improving operational adaptiveness, Preprint

Flight delays are one of the most discussed, yet not fully understood, topics in the aviation industry. In this paper, we shed more light into propagation of flight delays by providing a spatio-temporal analysis of flight departure delays of the US domestic air network for the year 2017. The analysis focuses on four US air carriers (full-service and low-cost) and two time events characterized by extreme weather conditions, in addition to a baseline case free of extreme weather conditions. We constructed a Delay Propagation Network (DPN) for each (time event, airline) pair detecting patterns of causality between hourly delays in airports using a Granger Causality approach. In addition, we identified four (time event, airline) pairs with a volume of cancellations large enough to construct a Cancellation Propagation Network (CPN), analogously to DPNs. For the baseline case, we observed that central nodes of the airport network (i.e., hubs) usually act as absorbers or intermediary nodes in the DPN. DPNs were more homogeneously distributed in space for point-to-point than for hub-and-spoke networks. For extreme weather events, we observed that the size of a DPN increases with the percentage of canceled flights as long as this stays below 10\%. Conversely, it suddenly decreases when the percentage exceeds such tipping point because most causal relationships among delays are lost due to the volume of cancellations. We also observed that some airports located in the region of the extreme weather event were among the central nodes of the DPN. Those airports, together with the hub airports, acted as the top generators, absorbers, or intermediary nodes of the DPN. On the other hand, CPNs monotonously increased in size with the proportion of canceled flights. CPNs are less noisy and therefore easier to interpret than DPNs, as cancellations stem primarily from the extreme weather event only. In CPNs, hubs act as cancellation absorbers, due to the larger volume of resources that, Peer Reviewed, Postprint (published version)

The aim of this manuscript is to detect recent trends in air transport research through a bibliometric analysis. We have retrieved all articles published between 2013 and 2022 in the Q1 of the Transportation ranking of the Social Sciences Citation Index published in the Journal Citations Reports (Q1-T), and in the Journal of Air Transport Management. Among these records, we retained for the analysis the articles related with air transport. Analysing the author keywords of articles and retaining the Top 10 cited articles in each of the samples, we have identified six research topics for each of the samples. Both samples share the topics Industry Analysis, Air Traffic Management and COVID-19 and Air Transport. The specific topics of Q1-T sample are High Speed Rail and Air Transport, Environmental Impact of Air Transport and UAV and Urban Air Mobility. We have also found that materials of Q1-T are mainly written from the regulator perspective, and JATM materials from the perspective of airport and airline managers. We believe that this results are useful for administrators evaluating air transport academics, air transport academics themselves looking for new avenues of research and stakeholders of the air transport industry interested in evidence-based decision making., Peer Reviewed, Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura, Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura::9.1 - Desenvolupar infraestructures fiables, sostenibles, resilients i de qualitat, incloent infraestructures regionals i transfrontereres, per tal de donar suport al desenvolupament econòmic i al benestar humà, amb especial atenció a l’accés assequible i equitatiu per a totes les persones, Postprint (published version)

In modern business, Artificial Intelligence (AI) and Machine Learning (ML) have affected strategy and decision-making positively in the form of predictive modeling. This study aims to use ML and AI to predict arrival flight delays in the United States airport network. Flight delays carry severe social, environmental, and economic impacts. Deploying ML models during the process of operational decision-making can help to reduce the impact of these delays. A literature review and critical appraisal were carried out on previous studies and research relating to flight delay prediction. In the literature review, the datasets used, selected features, selected algorithms, and evaluation tools used in previous studies were analyzed and influenced the decisions made in the methodology for this study. Data for this study comes from two public sets of domestic flight and weather data from 2017. Data are processed and split into training, validation, and testing data. Subsequently, these ML models are evaluated and compared based on performance metrics obtained using the testing data. The predictive model with the best performance (in choosing between logistic regression, random forest, the gradient boosting machine, and feed-forward neural networks) is the gradient boosting machine., Peer Reviewed, Postprint (published version)

El desarrollo del mercado inmobiliario en Lima provincia hasta 2015 tuvo un comportamiento que animaba a nuevas inversiones. Con los cambios políticos y económicos del país desde el 2016 y el Covid-19 en el 2020, se hizo fundamental el análisis de indicadores antes de embarcarse en una inversión. Este es el motivo que da inicio al presente trabajo cuyo objetivo es conocer y analizar la evolución temporal de los indicadores del mercado inmobiliario de departamentos en Lima, en los distritos de ingresos económicos altos y medios, por ser el segmento con información para el estudio. Se hace un análisis descriptivo de los datos secundarios cuantitativos existentes y recopilados de fuentes oficiales del estado peruano, mediante el uso de la herramienta de programación RStudio, de donde se obtienen las estadísticas y gráficas. Los resultados alcanzados nos permiten conocer la evolución de los indicadores y afirmar entre otros, que el Covid-19 y el contexto político del país influyen en el precio de alquiler por m2 muchos más que en el precio de venta, que el precio de venta de departamentos en los distritos de ingresos medios se mantuvo al alza y que, para invertir nuevamente con menor riesgo, es necesario una mayor estabilidad política y una disminución de la inflación, o al menos esto último.

I explored the potential of Sentiment Analysis (SA) infore casting successful initial coin offerings (ICOs). The aim is to determine if the SA and Twitter data alone, and in combination with TORD, a publicly available database Paul P. 2021, can evaluate the success of ICOs. Hence, I provided background information on the initial coin offering (ICO) market and cryptocurrencies, followed by a thorough literature review on SA and the main success factors of ICOs.Then, I finally presented the research project results, including the use of SA methodologies, data cleaning, graphical, and predictive analysis. Along with the conclusions with personal insights on the results

The connectivity of the rail transit stations is an effective way to evaluate the economic value of the station. In order to explore the influence of the local structure in the complex system of urban rail transit, this paper constructs complex network models based on the Beijing rail transit real network by using the space P and space L methods. The topological structure and global characteristics of the line and station networks are analyzed, and all motifs from 3 to 8 nodes of both networks are obtained using the motif detection algorithm. A subgraph decomposition algorithm for complex network motifs is designed based on five typical subgraphs. The results show that both networks of Beijing rail transit have different typical numbers and distributions of subgraphs, with Y-shaped subgraphs and line subgraphs being the most common for high-node and low-node motifs, respectively. This research proposes a way to assess the connectivity of the rail transit system and has significant reference value for optimizing network functions in the design and planning of rail transit networks. The findings also contribute to the ongoing discussions on network reliability and resilience, as the subgraphs identified in this study could potentially have implications for the network’s performance under different scenarios., Peer Reviewed, Postprint (published version)

This study focuses on the development of a code capable of generating a 2D route (a series of waypoints with latitude and longitude coordinates) between two airports inside Eurocontrol Area, that minimizes the total cost of navigation charges and fuel. To achieve it, the code utilizes as database EUROCONTROL’s DDR2, to obtain the geographical frontiers of En-route Charging Zones and its Unit Rates, the airways and waypoints defining the air network and the historical traffic data to obtain general aircraft performances and to compare and validate results. A wind model is also applied, as the shortest route will be always the most fuel efficient in no wind conditions. To find the optimal route, the model first generates a graph representing the airway network, and generates several different connection paths between the airport of origin and the destination. Next, for each path obtained it is calculated the en-route charges and fuel estimated its fuel consumed. It is needed to create a vertical profile to compute fuel, and it is based on historical flight data. The result obtained is the list of waypoints that constitutes the route, its distance, time required and the costs calculated. This tool developed provides an easy approximation of two most important direct operating costs of an Airspace Operator when contemplating a new route, while also providing the route itself.

Big Data Analytics (BDA) solutions are increasingly applied in marketing, with the aim of transforming data available online to market information and competitive intelligence. When businesses encounter risky situations (calculated risks) complex models using BDA are often the go-to solution. However, there is a still a debate if BDA is the best solution in uncertain situations when unexpected phenomena arise. The present study begins to fill this gap using the Colombian context as evidence and a Fuzzy-Set Qualitative Comparative Analysis method (fs-QCA). The focus shifts from a single cause leading to performance to an analysis of different associations of conditions. There are three major findings-first, in a risky environment, BDA is not a unique condition; a combination of data maturity levels, data skills and a data-driven mindset and culture are necessary to obtain good business performance. Second, even in the era of Big Data, large companies still use simple rules (heuristics) to make decisions which improve their performance. Finally, the environmental state (uncertain, certain, risky) is a moderating factor in the choice between BDA or Heuristics. The results indicate marketing managers should use a multi-model approach incorporating both BDA and heuristics, Peer Reviewed, Postprint (author's final draft)

During the current and last century, leisure flight has been an increasing market, especially in the last 30 years, the growth rate has been increasing substantially, only stopped by the episodes of global recessions. However, this aviation crisis has had no similar fact in all its history. On this project, a study of the drivers and possible lacks aviation market currently has is carried out. For this, an analysis of the facts that brought people to leisure travel that much before the global pandemic is required, to realize how people’s priorities have changed from the last year. To see this, both practical and technical studies are performed. The first will consist in reading a series of reports related to the leisure travel inner causes, while the second will consider people’s thoughts by interviewing them, using a set of questions that will be extracted from the technical studies. Once a sample of results is obtained, statistics are used to get insights on given structures and correlations between the leisure aviation drivers. These results are then compared to the ones obtained in the reviewed literature, trying to understand the reasons behind the obtained differences, broadening the general knowledge about these drivers, while discussing what things could be improved in the leisure flight industry to recover market share.

Aquesta tesi se centra en transformar un negoci familiar de xocolata artesana per adaptar-lo a la indústria 4.0, tot mantenint l'artesania i els valors de l'empresa. En primer lloc, s'ha desenvolupat i implementat una aplicació Android. D'altra banda, s'han modificat diverses tècniques de producció i rutines cap a un ús més intel·ligent del temps, els recursos i la planificació. I finalment, s'han programat i instal·lat diversos dispositius IoT al llarg de la fàbrica per tal de poder fer un seguiment exhaustiu de les instal·lacions. Pel que fa a l'aplicació Android, aquesta incorpora tres característiques principals que són: un receptari dels productes, la planificació de la producció i el control d'equips. L’app, per tant, permet a tots els treballadors accedir als recursos necessaris en totes les fases de la producció, com ara temporitzadors automàtics i alarmes, la planificació del sistema Kanban i avisos en cas de temperatura o consum fora del rang especificat. El següent pas s’enfoca als mètodes de producció de la fàbrica, aplicant un sistema de planificació Kanban a la zona de brioxeria. Aquesta metodologia contribueix a tenir una millor organització in-situ i menys possibilitats de passar per alt les comandes especials, també facilita la traçabilitat dels ingredients i l’operari, així com el progrés de la producció. D’altra banda, mitjançant models matemàtics es prepara la planificació de la demanda pel proper any 2022, utilitzant dades d'anys anteriors i paràmetres externs. A més, tant l'optimització com la gestió de l'inventari es transformen per satisfer les necessitats de provisió. Finalment, s'han connectat una sèrie d'aparells IoT a l'equipament existent de la fàbrica, que van des de les neveres i forns fins l’escomesa principal d’electricitat de 3 fases, proporcionant un seguiment en temps real de les temperatures i les lectures de consum d'energia per a cada àrea de producció. En conclusió, totes les seccions esmentades es combinen dins de l'APP., This master’s thesis focuses on transforming a family owned chocolate firm into an industry 4.0 ready business, whilst maintaining the craft and values of the company. Firstly, a dedicated multi-purpose Android application has been developed and implemented. On the other hand, several production techniques and routines have been modified towards a smarter use of time, resources and planning. And lastly, multiple IoT devices along the factory have been programmed and installed in order to keep track of the facilities. Regarding the Android APP, it incorporates three main features which are; product recipes’, production planning and equipment monitoring. Thanks to those, it supports and enables every employee to access the necessary resources at every stage of production, such as automatic timers and triggers, Kanban system scheduling and warnings for abnormal temperature or consumption. The next step targets the factory production methods, a Kanban scheduling system is implemented in the bakery production area. This methodology contributes to having a better in-place organisation and less chance of overlooking custom orders, it also grants traceability of ingredients and handlers as well as the production progress. Furthermore, mathematical models are used to prepare demand planning for the next year 2022, using data from previous years and external parameters. In addition, both trips’ optimization and inventory management are transformed to satisfy provision needs. Finally, an array of IoT apparatus has been plugged into the existing equipment in the factory, ranging from walk-in fridges and ovens to the main 3-phase power service drop, providing real-time monitoring of temperatures and power consumption readings for every production area. In conclusion, all of the previously mentioned sections are combined within the APP, simplifying control over the production from the palm of the hand.

La motivación del presente trabajo consiste en la aplicación del conocimiento tecnológico a través del software RStudio para la obtención de gráficas y estadísticas que permitan conocer el desarrollo del mercado inmobiliario de vivienda en Lima durante los últimos años, así como mostrar las ventajas que brinda el manejo de datos inmobiliarios para la obtención de estos resultados y puedan ser empleados como herramientas de decisión en beneficio del desarrollo profesional y del sector. Para esta investigación, llevada a cabo mediante un análisis descriptivo, se han empleado datos secundarios que pertenecen a fuentes confiables y que garantizan la veracidad y un escaso margen de error de los resultados obtenidos. Como base informativa se presenta un marco histórico que permite conocer cómo se conformaron los diferentes distritos de Lima y el porqué de las características urbanas que hoy presentan y que condicionan su participación en el mercado de vivienda actual. Los resultados obtenidos muestran que la oferta de vivienda en Lima se caracteriza por una distribución irregular en perjuicio de la población más alejada del centro y, a su vez, la de menores recursos. De esta forma, es necesaria la redistribución de esta oferta en beneficio de más familias y, además, continuar propiciando el desarrollo de un mercado de vivienda libre de especulación y que disminuya progresivamente la demanda efectiva de vivienda., The motivation of this work consists in the application of technological knowledge through the RStudio software to obtain graphs and statistics that allow to know the development of the housing real estate market in Lima during the last years, as well as to show the advantages that offers the management of real estate data to obtain these results and can be used as decision tools for the benefit of professional development and the sector. For this research, carried out through a descriptive analysis, secondary data have been used that belong to reliable sources and that guarantee the veracity and a small margin of error of the results obtained. As an informative base, a historical framework is presented that allows knowing how the different districts of Lima were formed and the reason for the urban characteristics that they present today and that condition their participation in the current housing market. The results obtained show that the supply of housing in Lima is characterized by an irregular distribution to the detriment of the population furthest from the center and, in turn, the population with fewer resources. In this way, it is necessary to redistribute this supply for the benefit of more families and, furthermore, continue promoting the development of a housing market free of speculation and that progressively reduces the effective demand for housing.

This chapter starts with a systematic review of the academic state of art about the trending topics that deal with data-driven approaches in an urban environment. Then, we select a specific example and analyze recent progress in the use of data to improve the urban process, which is as strategic and a priority as the resilience process. In this vein, we then use the case of the Philippines and show their data-driven policy to cope with disasters that drastically affect their urban areas., Peer Reviewed, Postprint (published version)

This thesis centers on analyzing SHEIN, one of the giant technology commercial companies all over the world. It is from China but only develops business abroad. SHEIN has got an extraordinary achievement in this decade and that is inextricably linked to its unique operating model which is composed of six important parts that are the business gene of SHEIN, the supply chain, the modern digital system, the marketing methods, the logistics and the industry environment. These six different parts are interlocked and closely linked to each other. Specially, different from other leading brands in the industry such as ZARA and Amazon, SHEIN has quickly captured the fast-fashion market of the younger generation with cheaper prices and faster logistics supply chain. So far, SHEIN has its own design line of products on the website and has also expanded other categories of products like household products. However, a large part of SHEIN’s success has been brought about by this era. With the development of the Internet economy, people from the younger generation have an increasing pursuit of fashion. The rapid rise of online marketing and social media make it easier to promote the brand reputation all over the world. In conclusion, it can be said that SHEIN is in line with the trend of this era and this era has achieved SHEIN’s business model. However, one corn has two sides, there is a voice of doubt here. How far can SHEIN go in the future? Whether it is to make quick money in a few years? It is undeniable that SHEIN does have a lot of problems, and although they have been well solved so far, if the solutions are sustainable in the long run or not and SHEIN would face them positively with their young and energetic company culture

E-commerce is an ever-growing field that has undergone steeper growth resulting from the Covid-19 pandemic. Due to this and consumer expectations guiding/following this trend, small to medium sized enterprises (SMEs) are forced to enter the space that was previously only dominated by large corporations. With technological improvements and supply chain advances, companies are now able to enter the space with far less friction leveraging tools such as e-commerce platforms (for example: Shopify, Magento, Salesforce Commerce Cloud, WooCommerce). These platforms enable companies to manage portions of an e-commerce business more easily such as inventory, order management, parcel carrier setup, and online storefronts very accessible to many offered in scalable packages for the business. Considering what these tools provide as base solutions and the previously researched elements in other studies, this study focused on elements that are not inherent to these platforms, requiring investment and consideration otherwise, such as: additional high-quality pictures, user reviews, free returns, free shipping, promotional offers. Then, these elements were tested by monitoring the change in respondent perception of various pages via a survey AB. The data was then analyzed with 4 hypothesis tests and a few other analyses to answer some key hypotheses that were synthesized following a literary review. The takeaways suggest the following: an e-commerce platform-based site provides the key base site elements and meets consumer expectations relative to their previous shopping experiences. Free shipping and free returns advertised on a site page (welcome page for this study) has a positive impact on conversion. Additional high quality product images, special offers, and displaying product reviews were not associated with a statistically significant increase in conversion in this study. As conversion rate optimization (CRO) methods should not be applied as a list of best practices in all s

The aviation industry has recently experienced a fast move toward the hybridization of airline business models. This has remarkably affected airline network structures, moving from a neat contraposition between hub-and-spoke networks (typical of full-service carriers) and point-to-point networks (typical of low-cost carriers) to more hybrid architectures. While literature has widely documented the ongoing restructuring of airline networks, the development of decision support systems in this respect has been rather scant. In this paper, we develop an optimization-based approach—referred to Integrated Connection Planning and Passenger Allocation Model (ICPPAM)—to support low-cost airlines in the early stage of connection planning, encompassing the definition of the most promising transfer airports and the set of optimal connecting itineraries to be rolled out over an existing network of flights. The ICPPAM solves the passenger mix problem on every flight segment, leveraging endogenous demand estimates based on an empirical discrete choice model. We demonstrate the applicability of the proposed approach to the large-scale network of Ryanair in 2019. Results highlight that the proposed approach can significantly aid airlines’ decision-making, leading to significant revenue improvements (up to 4.4%) and shedding insights into network development alternatives, Peer Reviewed, Postprint (author's final draft)

The aim of this project is to analyse the role of dividend policy as a tool to mitigate conflicts between majority and minority shareholders or whether it is used by majority shareholders to behave opportunistically towards minority shareholders and favour their expropriation in the context o f Italian listed companies. The study was conducted through an empirical analysis, in which several regressions were studied, to also test the robustness of the model, using a data sample of Italian non listed companies in the years between 2000 and 2017. financial After a careful theoretical excursus in which the main theoretical foundations regarding the relationship between majority and minority shareholders and regarding the models inherent to the dividend policy were reported, private firms of a famil y nature were considered for each regression, considering an individual or a set of individuals holding more than 50% as a family, according to a narrower definition, while according to a broader definition those holding more than 30% of shares. Notably, a ll the regressions constructed led to the same result and, in addition, confirmed the nature of the relationships between the dependent variable, the percentage of dividends distributed relative to net income, and several independent variables selected for the study. The main findings of the study suggest that majority shareholders use dividend policy to reduce conflict with minority shareholders rather than using dividend policy to behave opportunistically towards minority shareholders. Furthermore, it was noted that the propensity of majority shareholders to distribute dividends has a negative relationship with return on equity and has a positive relationship with risk, company size, growth, corporate liquidity and market value

Even in this inauspicious situation, marked by a global pandemic, the need for connections between countries is not just a service required by the demanding side, but is a powerful tool for companies, institutions and even Nations to grow and create welfare. Today, the fastest but most challenging way to connect one State to the other is through the air. Aviation is indeed the first way of transportation either when it is necessary to move valuable goods from point A to B or when there are customers willing to travel medium-to-long distances in very short times. However, the real challenge arises in those markets where, due to economic, political or organizational issues, is extremely difficult to build a resilient, efficient and safe network to allow people to fly freely. The first and most evident case in our era is Africa, where historical backgrounds are still restricting the economic development: the lack of reliable structures and an incomplete air liberalisation is causing the continent’s backwardness. Africa is a continent with an untapped potential, especially in the transportation field. Both intra-Africa and International connections would enable its States members to flourish in this globalized world. It is unquestionable that improving the existing air transportation system would increase in several ways each African Nation’s welfare. In this situation, alliances find virgin soil to proliferate, at least in theory. The very nature of this agreement is to extend the existing network of each of the undertakings, to have access to more resources that could be used for the advantage of the entire group increasing the efficiency of the combined operations. 3o million km2 , 54 states and thousands of domestic and international routes could be served better if only foreign carriers could overcome the plethora of issues which characterise the actual state of things. But why has the situation come to this? Why have alliances not yet penetrated the market? and wh

The main objective of this thesis is to develop and perform an analysis of optimization based on applying a Graph Theory approach on manufacturing systems, throughout which fundamental information about the structure and connectivity behaviour of the studied networks will be obtained, allowing to determine the most efficient ways of improving the security and the quality of the production flow. As a guidance for the study, the following two hypotheses are presented at the introduction of the project: the first and more general one, The application of a Graph Theory approach to analyse and study manufacturing systems offers suitable information that can be used to optimize the production flow; the second and more specific one, A Local Clustering Coefficient (LCC) approach can be used to cluster processes of a manufacturing system. To prove the veracity of both hypotheses and pursuit the main objective of the study, several procedures based on parameters and theoretical aspects of the Graph Theory are applied to different manufacturing system’s equivalent graphs. Concretely, the suitability of this approach is tested in three different manufacturing systems: in first instance, two toy model networks are used to observe the response and the coherence of some of the proposed analysis procedures in front of relatively simple and not large manufacturing systems; in second and final instance, some of the procedures implemented and polished in toy model’s chapter are tested in front of a far more large and complex manufacturing system’s equivalent network. The methods of which the Graph Theory approach mainly consist of are based on the analysis of centrality measures from different perspectives such as its evolution throughout the network, synergies and robustness analysis mainly based on sequential targetted centrality attacks. The results obtained from the application of the Graph Theory approach on manufacturing systems are positive and promising, as the information gat

Cascading failure phenomena can appear in complex networks that distribute flows of information, people or goods, when flow going through nodes or edges exceeds the capacity of network nodes or edges. Cascading failure models from previous research are not adequate for airport networks, as flow is not continuous, and load has to be redistributed among close airports, rather than previously existing connections. With these constraints in mind, we have defined an algorithm to simulate the management of cascading failures in airport networks. We use the algorithm to evaluate the effectiveness of several selection rules of alternative departure and arrival airports to affected flights to reduce the impact of the cascading failure. We have applied the algorithm to the Oceanic Airport Network to assess the impact of several incidents. Results show that selection rules of arriving airports have significant impact in reducing the effect of incidents affecting central airports, Peer Reviewed, Postprint (author's final draft)

Cities play a relevant role in economic and social development. According to data from the United Nations, 55% of the global human population lives in cities, amounting to 4.2 billion people. From the same source, we learn that this fraction amounts to 78.5% in more developed countries. On the other hand, cities are estimated to consume 2% of land, generate around 70% of global GDP, and use 60% of global energy. As much of the growth of urban population is coming from less developed cities, it is safe to predict that the weight of cities in the global social landscape will increase in the coming years., Peer Reviewed, Postprint (published version)

The COVID-19 pandemic is having a large social and economic impact worldwide. At the present stage, in this project, I will use publicly available data to assess strategies undertaken by governments to mitigate impacts while preserving the health of the population. This paper consists of two parts connected with a current state of data taken from open public sources. In the first part, I implement D models to the real data to forecast a future state of death numbers in Spain. In the second part, I use Oxford COVID-19 Government Response Tracker with the real data to evaluate the effects of different policies on death numbers and daily new cases. I will show that the most effective policies to mitigate the effects of COVID-19 will be restrictions on gathering policy, facial mask protection policy and stay at home policy. Overall, this paper suggests that the government anti-pandemic responses have substantial effects on preserving the health of the population

L’objectiu principal d’aquest Treball de Fi de Màster és el d’explicar el problema del moviment a terra de les aeronaus en aeroports, quines conseqüències poden originar-se a partir d’una mala gestió de les operacions terrestres dels avions per les zones de rodatge y quines solucions es poden crear per tal d’optimitzar tots aquests moviments en un aeroport a través de la creació d’un programa informàtic. Primerament es donarà un contingut teòric sobre el problema. Seguidament es proposarà un mètode per resoldre l’optimització dels moviments a terra d’aeronaus basat en la creació d’una xarxa de nodes i línies interconnectades entre sí. Per fer-ho s’exposarà un exemple en concret, en aquest cas el de l’aeroport Josep Tarradellas Barcelona-El Prat. En aquest exemple s’utilitzaran una sèrie de dades que s’aniran explicant al llarg de la memòria. A continuació es passarà a explicar l’estructura del programa i la seva funcionalitat per implementar el problema. Finalment, s’aplicarà el programa creat per fer l’estudi dels moviments a terra d’un dia concret a l’aeroport de l’exemple per poder extreure’n conclusions sobre ell

The present study aims to assess the actual performance of flight operations in the Spanish airspace and evaluate the possible deployment of the Free Routing Airspace concept in order to optimize air traffic routes, according to SESAR expectations. Free Routing is an operational concept that foresees the air navigation within an airspace unconstrained by the current existing air routes and fixed points. That will allow airspace users to perform more efficient routes according to their preferences and, consequently, reduce fuel consumptions and delays. Although, free routing implementation requires a set of operational and technical changes in all the actors involved in order to ensure a safe transition from the actual procedures, especially in the regions with high volumes of traffic or complex situations regarding Air Traffic Control.Taking in consideration the characteristics of Spanish airspace and the degree of maturity of the upcoming free routing, which implementation is still on course in several European countries, this study is focused on the En-Route airspace, excluding of its scope Terminal Areas where, due to the complexity of air operations and their individual particularities, a more detailed and constrained approach should be adopted.The first sections of the study describe the current state of the air navigation in Europe and the effort, research and measures adopted regarding Free Routing. Aiming to clarify the technical background to the general public, general air navigation concepts and FRA specific definitions are included.Then, a revision of European and Spanish airspace is performed, including traffic performance statistics and the description of the Spanish particular air structure, mentioning the regulatory framework and responsible bodies.The study is completed with a traffic simulation performed with real flight data, from where safety and efficiency in Spain are evaluated through key parameters. Within this process, a general analysis of

Most complex network analyses of transportation systems use simplified static representations obtained from existing connections in a time horizon. In static representations, travel times, waiting times and compatibility of schedules are neglected, thus losing relevant information. To obtain a more accurate description of transportation networks, we use a dynamic representation that considers synced paths and that includes waiting times to compute shortest paths. We use the shortest paths to define dynamic network, node and edge measures to analyse the topology of transportation networks, comparable with measures obtained from static representations. We illustrate the application of these measures with a toy model and a real transportation network built from schedules of a low-cost carrier. Results show remarkable differences between measures of static and dynamic representations, demonstrating the limitations of the static representation to obtain accurate information of transportation networks, Peer Reviewed, Postprint (published version)

Air transport deregulation has lead to an increase of air traffic, together with a reduction of air fares. Air fare reduction has narrowed operational margins of airlines, bringing financial and employment instability. This has brought airlines to pay increasing attention to flying costs reduction. Two important components of flying costs airlines can try to cut modifying the planned flight are en route charges and operational costs. We rely on Demand Data Repository (DDR2) data to calculate deviations from planned flight trajectories to analyse the extent to what airlines try to cut operational costs making shorter flights than planned if possible, and cut en route charges providing a planned flight with lower en route charges than the planned flight. Our findings show that there is no generalised strategy among airlines to reduce en-route charges asking for deviations of the planned route. On the other hand, airlines are achieving savings of operational costs regularly. Higher savings per nautical mile are obtained in night flights, with longer planned distance and operated by low cost carriers, Peer Reviewed, Postprint (author's final draft)

The concentration of spacecraft residual parts in Low Earth Orbits, known as Space Debris is of the main concernsof future space flights. Cascading process known as Kessler syndrome predicts 30% increase in space junks in thenext 200 years.The primary objective of this thesis is to study some of the optimization methods for debris removal. A review studyof measurement techniques, mitigation and remediation methods to overcome the growing number of space junks inLow Earth Orbit (LEO) will be conducted., The develpment of the Master Thesis will include the following tasks:1- Brief review of policies and regulations of Inter-Agency Space Debris Coordination Committee. 2- Study of Orbital Debris Measurements such as ground based radars, optical based telescopes and space-basedtelescopes.3- Study and discussion of the methods for mitigation and remediation of space debris to reduce the risk to the current fleet spacecrafts 4- Study and developement of Debris Removal optimization models to find the optimal trajectory that minimizes fuel consumption. 5 - Generation and developement of optimization algorithmes for Traveling Salesman Problem (TSP) for active space debris removal.

This study analyses deviations from planned flights in the European space network by studying economical motivations of airlines as triggering factors. For that reason, planned and performed historical traffic data from EUROCONTROL’s DDR2 have been used to examine 579,243 flights of December 2018 by calculating their savings in terms of operational costs and en-route charges. Results show that aircraft operators are systematically achieving savings on account of reducing planned distance when performing the flight and not by cutting en-route charges, which have a significantly lower weight in comparison to pure operational costs. This seems to be triggered by a combination of three factors: the intrinsic nature of flights that are performed during low traffic conditions; the interaction of pilots and air traffic controllers that look for a more efficient operation; and what seem to be distinct legitimate internal policies of airlines that would lead pilots to behave distinguishably when facing possibilities of reducing planned distance when performing the flight. The latter has been observed by introducing a new metric called dsTS, which measures the savings achieved by an airline per nautical mile, and by appreciating a relevant disparity among their values.

The flowshop problem is a scheduling problem where a set of jobs is processed by the same set of units or machines in the same order. A solution this problem specifies the order in which jobs are processed on each unit, to minimize a performance parameter, usually the time needed to process all tasks. In the variant of flowshop problem to be analyzed in this study, the time to process each job in each machine is stochastic, is a random varaible following a probability distribution. The aim of this study is to find an effective and efficient heuristic to solve this problem.

The scheduling process on every production line is of principal importance as it directly affects the productivity of a company. For decades now, operational research has offered managers tools to automate their scheduling process and cope with the increase on product demand and variability. However, generally small and medium size companies do not have access to such solutions, widely incorporated on the workflow of more industrialized operations and other large companies. On this thesis, an automatic task scheduling service is developed, by implementing a GRASP algorithm with first descent local search to solve a combinatorial optimization problem known as the Job Shop Problem (JSP), along with one of its variants for considering job priorities and due dates based on total weighted tardiness (JSPTWT). This work reviews their mathematical formulation and several solution approaches and also performs a series of computational experiments to determined best set of parameters for the solver. Finally, a user interface powered by Shiny package in R is presented to offer the end users a friendly platform to support their scheduling processes, and a preliminary economic model for the first year of operation for this service is introduced.

This editorial presents the papers selected from the ATRS 2018 conference to be published in the Journal of Airline and Airport Management.

Although supply disruption is ubiquitous because of natural or man-made disasters, many firms still use the price-only reverse auction (only the cost is considered) to make purchase decisions. We first study the suppliers’ equilibrium bidding strategies and the buyer’s expected revenue under the first- and second-price price-only reverse auctions when the suppliers are unreliable and have private information on their costs and disruption probabilities. We show that the two auctions are equivalent and not efficient. Then we propose two easily implementable reverse auctions, namely the first-price and second-price format announced penalty reverse auction (APRA), and show that the “revenue equivalence principle” holds, i.e., the two auctions generate the same ex ante expected profit to the buyer. We further show that the two reverse auctions are efficient and “truth telling” is the suppliers’ dominant strategy in the second-price format APRA. We conduct numerical studies to assess the impacts of some parameters on the bidding strategies, the buyer’s profit and social profit, Peer Reviewed, Postprint (author's final draft)

Mining is an important industry in Peru, but local communities where mining takes place do not perceive its benefits. Mining corporations need to achieve legitimacy within these communities. The main objective of this study is to identify the factors that determine the provision of social licenses to operate in Peru’s mining regions. We conducted this research using a case study of two Peruvian mining companies. Our study concludes with the identification of four essential factors needed to achieve a social license to operate within these communities: a deep understanding of the socioeconomic environment, a strong commitment to the community, an active presence of Government, and effective communication between the actors involved in mining activities. The combination of these elements can result in improved trust levels between companies and society, enabling all agents to recognize the costs and benefits resulting from mining, Peer Reviewed, Postprint (author's final draft)

Air transport is one of the key infrastructures of today’s global economy. Connections between airports define airport networks, where nodes are cities served by airports, connected by edges if there is at least one direct flight connecting them. The aims of this research are to relate structural properties of airport networks which explain how these networks respond to isolation of critical nodes, and to gain insight into relevant socio-economic factors that influence the development of airport networks. We split the world airport network (WAN) into seven global region airport networks (GRANs), using the divisions established by OAG database. We gather information about structural properties of each GRAN determining core cities through k-core decomposition, and critical cities through robustness analysis. We find that differences of robustness across GRANs can be explained by the fraction of core cities relative to total cities. Furthermore, analysis of multilevel structure reveal relevant differences between GRANs, rooted on geographical and socio-economic factors, and give insight about how network robustness in airport networks can be enhanced, Peer Reviewed, Postprint (author's final draft)

The objective is to show the importance of customer orientation by concentrating on downstream activities. The paper shall outline possibilities and tools for manufacturing companies to concentrate on their customers’ needs. - There are a lot of current topics which add possibilities to businesses, using latest accomplishments. These are e.g. (automated) data analysis, interconnectivity of production environment, so called Internet of Things, Big Data and many others. - The paper asks the question which one of them are „useful“ and add value to the main goal: customer orientation by concentrating on downstream activities. - At the end, the result should be an evaluation of current possibilities and recommendations/suggestions for businesses how to approach this., How to grow and earn more money with the existing products, as production and cost optimization is almost used to full capacity? And how to benefit from the fast developing digital evolution? These are two of the most critical out of several challenges today’s companies are faced with. On one hand, the importance of customer orientation by concentrating on downstream activities is often disregarded due to concentration on upstream production strategies. Therefore, the paper shall outline possibilities and tools for manufacturing companies to concentrate on their customers’ needs by downstream activities. On the other hand, digital technology and data science made enormous steps in the past years and they are continuing in a tremendous pace. These offers a huge potential of enhancements for businesses, using these latest technological accomplishments. These are, just to name the most famous, the so called Internet of Things, big data and interconnectivity of production environments. Introducing and sharpening these often blurry and interchanged names will be one important task of this paper as well. The core question is which one of them are – or could be – useful and add value to the defined main goal: customer orientation by concentrating on downstream activities. This means the goal is to summarize an evaluation of current possibilities and to give recommendations for businesses, how they can approach these options and develop strategies. Ideally and finally, suggestions how to implement them into their companies are given.

How much labour action and it’s subsequent negative influences (loss of brand value, customer’s loyality, profits for that time, etc) are worth sustaining for a company, until this would exceed the intended savings of lower labour cost?. The background of this is, that with a few recent airline labour disputes, there were some public discussions on whether there were actually savings in the end or the decisions of the management have been more emotional than rational. (Lufthansa over 4 years intermittend strikes, Avianca with a two-week full strike, …) The objective of this thesis is to analyze The effect of labour actions applied by an airline -mostly in order to obtain long-term savings- in customer’s buying behaviour and loyalty as well as negative development of brand value. How labour disputes within the airline affect to the company's savings and benefits, This thesis investigates the short- and long-term effects of labour disputes in airlines. First off, an overview of the airline market and pilot working conditions is given, alongside with some examples of labour disputes and strikes. The thesis then concentrates on the dispute between the pilot union “Vereinigung Cockpit” and Lufthansa between 2014-2017. Short-term effects are analyzed in form of a Cost/Benefit analysis, making out all the savings achieved by implementing a new collective labour agreement as opposed to its costs. Different from comparable studies, the entirety of expenses, not only the costs of the strikes themselves are minded. Long-term effects include the observation of brand equity, booking numbers and profits. It is proven that the short-term effects are very positive, resulting in substantial savings. Long-term effects include a crucial loss of brand equity, which however does not seem to have an influence on the company’s performance as measured by its adjusted EBIT, capacity and booking numbers. This suggests that brand equity might not be the driving force for customer buying decisions in traditional network airlines such as Lufthansa.

Purpose: The purpose of this paper is to define a model that both describes the evolution of the emotional stages of individuals during perceived negative organizational change and explains the evolution of their behavioral patterns and the effects on relationships with social environments (family, friends, co-workers, supervisor and organization). Design/methodology/approach: A qualitative methodological research design was adopted, using individual interviews as the primary method of qualitative data collection. In total, 15 people who experienced perceived negative organizational changes participated in this research. Findings: Through empirical qualitative research, an adapted Kübler (1969) model was used as a starting point. Co-occurrence analysis of the interviews led to the combination of the first two stages (denial and anger) of this model because they always appeared together. Two new stages (revising and deserting), based on the research of Schalk and Roe (2007), complete the model. Subsequently, the model comprised six emotional stages: denial and anger, bargaining, depression, revising, deserting and acceptance. The results show that individuals can move freely between the first four stages, but deserting and acceptance are always the final stages. Experiencing these emotional stages can influence the relationships between individuals and their social environments. During “denial and anger” and “bargaining,” the relationships with family, friends and co-workers improve; but during depression, the relationships with family and friends deteriorate, but because co-workers become much more important, those relationships improve. Relationships with supervisors deteriorate during denial and anger and depression but remain stable during bargaining. Research limitations/implications: Time’s passage became an inconvenience accounted for during data collection. Over time, separate events can be confused, and nuances that were once determinants can be eliminated., Peer Reviewed, Postprint (author's final draft)

The main objective, is to analyze how to develop a new service, internally or externally to improve the production processes, the final product or the business model- using the IoT and new communication technologies., We live in rapidly changing times, especially for businesses. Consider that, in a single generation, businesses have had to adapt to entirely new marketing channels (web and social), decide how to invest in and utilize new technologies, and compete on a global stage — things that were barely imaginable to our parents’ and grandparents’ generations. The world we live in is getting smaller day after day ―thanks to‖ the era of conectivity. There is no difference for industrial companies. The digital revolution or fourth industrial revolution is already present and companies have to prepare and adapt rapidly to the constant current and coming changes. On one hand, globalization has made any company in the world a direct competitor. So, what could companies make in order to afford it? How can they compete against China´s or other Asian countrie’s the manufacturing and production costs? On the other hand, the industrial digitalization is the cutting edge of technology. Make all the proceses interconnected, is one of the opportunities that the new technologies offer to the companies. So, how the industrial companies should face these constant and fast changes in order to keep moving forward? The core question is the process that companies have to follow in order to overcome and even take advantage of the changes that are coming (or those ones already here). The following document could be a guide or a bussiness plan for those industrial companies that want prepare themselves for the challenges that technology brigs with it.

This study contains about decision making, sunk cost effect in monetary and nonmonetary in both consumer and managerial domains. The present work focuses on understanding the decision making process, sunk cost types, different factors that affect decision making in sunk cost fallacy, looking for differences between customers and managers. At the end, it contains a survey experiment to understand the decision making differences and sunk cost effect between consumers and managers.