The Sharing Economy is an innovative social, economic and technological paradigm which is shaping worldwide production and consumption patterns of many industries. Its strength relies on factors of competitiveness such as the use of idle capacity, temporary access to resources without transfer of ownership, the flexibility and adaptability of its models, and the participation of a growing number of players allowed by peer-to-peer digital platforms. From the management perspective, the conditions for lasting competitiveness lies on sustainability, the paradigm integrating the supply, demand, and technological dimensions in a holistic, or ecosystem, perspective. Tourism is among the industries making extensive use of sharing digital platforms and experiencing changes that foster the sustainability debate. The PhD Thesis aims to investigate the relationships between competitiveness and sustainability in the tourism and hospitality accommodation industry in the Sharing Economy Era. Its investigation is multifaced and is addressed through three studies adopting a post-modernist perspective that builds on qualitative approaches and strategies for data collection and analysis. The Part I of the Thesis explores the Sharing Economy concept’s evolution and the sustainability issues through an in-depth review of the literature. Results reveal the leading economic-technological evolution of the paradigm over the social one, and its dual links with sustainability in relation to the extensive use of peer-to-peer digital platforms. Therefore, the evolution of the Sharing Economy activities have shown that today competitiveness is built on the interactions of an ever-increasing number of actors and factors, both off-line and on-line, within a complex ecosystem for the creation of – shared – value. The tourism industry strongly challenges this relationship between extended competition and sustainability. The Part II evaluates the competitiveness model and its evolution during the Sharing eTourism Era in the tourism and hospitality accommodation sector introducing an ecosystem perspective for the creation and distribution of shared value. Specifically, it investigates how the non-traditional and informal tourist services have affected the structure of the industry and have altered the competition among the actors, through semi-structured in-depth interviews. Results show that competitiveness is given by the balance among the complex interactions of internal and external ecosystem’s actors and factors. On a micro level this imply that businesses must adopts an ecosystem vision compensating for negative externalities which translate into the adoption of Business Models promoting sustainability for the creation of sustainable shared value. Therefore, the Part III investigates through the use of an illustrative case study how peer-to-peer digital platforms in the tourist accommodation service can boost profitability while strengthening economic, social and environmental sustainability by applying the innovative Business Model for Sustainability. The research sheds light on the complex Sharing Economy literature and lays the theoretical foundations for the implementation of managerial strategies aimed at promoting extended sustainable competition-cooperation.

Artificial Intelligence has recently attracted attention due to its rapid advancement in various industries such as the healthcare and finance industry. The intersection between AI and entrepreneurship is still being studied, and this study explores the impact of AI-tools on startups, with a focus on Swedish startups. The study explores the utilization of AI- tools to optimize their operations or capture new opportunities. It also examines their alignment to The Lean Startup Development, designed to help entrepreneurs to navigate through challenges they face when launching a product or a service. The primary contribution is of qualitative nature, using semi-structured interviews with individuals from startups implementing AI-technologies. Interpretation of the data is done through thematic analysis, which involves identifying themes and core categories.  The startups use the AI-tools for strategic internal planning and operations. The findings suggest that the AI- tools are commonly used to minimize costs, automate certain tasks, saving time to focus more on complex tasks and thereby enhancing efficiency which gradually leads to strengthened competitiveness. Interestingly, the participating startups show a consideration for ethical risks making more careful decisions on the information provided by the AI-tools.

The drastic growth in the tourism industry is continuously raising questions for destinations regarding competitiveness in today's global market share. For small island destinations, destination management in the terms of marketing is a crucial factor that defines the competitiveness and success of smaller islands in order to remain competitive and economically benefit in the fast growing tourism industry. The purpose of this study was to uncover specific marketing strategies that needed to be incorporated within small island tourism destinations. To fill in the knowledge gap within the marketing of small island tourism, a case study was conducted by examining the challenges and opportunities in two small islands, Öland and Gotland, located in Sweden. The findings of the case study revealed the significance of cultural tourism and its role in the marketing of the destinations. The cultural attributes include the importance of heritage and nature; by providing unique travel attributes that step out of the typical 3S (sea, sun, sand). The findings were looked upon from local residents, businesses, and local tourism organizations which both concluded that cultural attributes are important factors to consider to solve the seasonality challenges with a clear market segmentation in order to continually remain competitive.

The continued growth of regions in a state of economic expansion is often stunted by their inability to assess, maintain and expand logistics infrastructure. The need for a comprehensive, detailed and intuitively understandable logistics capability model to aid in the assessment phase of logistics maintenance and expansion provides motivation for this thesis. Logistics benchmarking can also be presented to attract prospective clients and provide basis for further development. Through the process of extensive literature review, we perform objective evaluations and provide a single recommendation for regional logistics capability modeling within a limited research scope. We recommend a 12 category logistic evaluator model with an interview process and expert scoring. The scoring is performed on the basis of logistics data and statistics. An implementation of the model is performed on Gävle, Sweden and is partially validated with a case study on GEVALIA Coffee. Implementations on SWOT and a discussion of the similarities of the 12 category logistics evaluator model and AHP will be given.

Throughout history, a number of financial centers have risen and fallen. While the significance of some centers have deteriorated, a small number of centers have emerged as today's leading financial centers by meeting a specific set of necessary conditions needed to successfully address the growing financial needs of the regions they are located. Furthermore, an even smaller number of financial centers have been able to sustain and expand their initial dominance in the financial industry by continuously satisfying a more focused set of conditions and factors. This thesis focuses on adapting Michael Porter's Diamond Model in determining, clustering, and expanding key factors that have historically given cities such as London, New York, Hong Kong, Singapore, and Tokyo their current status at the pinnacle of the financial centers of the world. This thesis begins by taking Porter's model that addresses national competitive advantage nations from a macroeconomic point of view, and adapting it to the development of financial centers at a microeconomic level. It utilizes Michael Porter's established grouping corners for identifying a vast array of macroeconomic and microeconomic factors that have historically played critical roles in increasing productivity and efficiency within a center's financial industry. Additionally, this thesis categorizes these factors into parameters that form a theoretical model designed to showcase the path to global financial dominance for an aspiring financial center. With the adaptation of Porter's model outlined in this thesis, financial centers are given a figurative blueprint of what constitutes a successful financial center. The theoretical model analyzes the necessary conditions and environments that a center needs to recreate within itself, or are endowed with, in order to be a globally competitive financial center.

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This thesis develops an econometric model of the Canadian clothing and textile industry for the purpose of investigating its structure, the market it faces, linkages between the market and the industry and the sensitivity of the industry to external factors. Using the model, several simulation experiments are conducted with the primary focus centered on the issues of protection accorded the industry. The future prospects of the industry under various alternative scenarios are evaluated. Empirical support is indicated for most of the hypotheses underlying the specification of the model. Some of the hypotheses are: the firms in the industry engage in imperfect competition; the industry operates under constant return to scale; price competitiveness is a significant factor in explaining the level of imports; domestic production capacity has an influence on imports. It is found in the thesis that clothing imports respond with a relatively high elasticity to changes in price as well as income, revealing a source of instability inherent in the clothing industry. As a system, the model is found to trace the history of the industry with reasonable accuracy. The model is also found to display a considerable degree of consistency and stability in its responses throughout the simulation experiments. The thesis thus provides a dynamic, structural and simultaneous economic system that can be validly used either as a forecasting tool or frame of reference in analyses. An ex-ante simulation intended as a reference forecast of the industry suggests that despite the present quota protection, the past downward trend observed in the clothing industry will likely continue in the future, while the textile industry will maintain a status quo. A simulation with a complete removal of tariff protection appears to support the argument that consumer gains will outweigh losses on the labour and production side. Another simulation suggests that there are policy options available that may be considered as effective means of stimulating the industry. / Thesis / Doctor of Philosophy (PhD)

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Las mypes constituyen un sector muy importante en el desarrollo de la economía del país por lo cual en la presente investigación se planteó como objetivo determinar el nivel de competitividad que tienen las mypes exportadoras de la región Lambayeque. Para lo cual se empleó un enfoque cuantitativo, de tipo básica, de nivel descriptivo y diseño no experimental, corte transversal, para lo cual se tuvo una población de 110 mypes y un muestreo tipo juicio de 49 mypes agroexportadoras de la región Lambayeque, empleándose como instrumento el mapa de competitividad proporcionado por el BID, y se obtuvo en los resultados que las empresas en estudio poseen un nivel muy bajo con un 53.1%, seguido de un nivel bajo con un 38.8%. Concluyendo así que, pese a la importancia del sector, este se ve afectado y no ha logrado incrementar su crecimiento en el mercado puesto que presenta diversas deficiencias. / The mypes constitute a very important sector in the development of the country's economy, which is why in the present investigation the objective was to determine the level of competitiveness that the exporting mypes of the Lambayeque region have. For which a quantitative, basic type, descriptive level and non-experimental design, cross-sectional approach was used, for which a population of 110 mypes and a type of proven trial of 49 agro-exporting mypes from the Lambayeque region were used, using As an instrument, the competitiveness map provided by the IDB, and it was obtained in the results that the companies under study have a very low level with 53.1%, followed by a low level with 38.8%. Thus, concluding that despite the importance of the sector, it is affected and has not been able to increase its growth in the market since it presents various deficiencies.

The objective of this study is to determine Virginia dairy producers’ competitiveness in an industry that is experiencing changing policy and marketing conditions. The competitiveness of Virginia dairy producers is examined in a National Dairy Model that compares both producers’ cost of production across market areas and spatial relationships among producers and consumers. The National Dairy Model (NDM) is a mathematical programming model that minimizes the total costs of producing milk and the assembly costs of shipping dairy products to the final consumer. A state's cost of production in the NDM is determined with a translog cost function. The cost functions are estimated with data collected in the 1989 and 1993 dairy versions of the Farm Costs and Returns Survey (FCRS). The supply and demand information in the NDM is annual data for 1994. Transportation costs are determined with current hauling rates and actual mileage between supply and demand points. Once the costs of production and spatial components of the NDM are formulated, the NDM is solved using the General Algebraic Modeling System (GAMS). The NDM is evaluated under the guidelines of several different scenarios. For example, some alternative marketing scenarios that provide important information about the future of the dairy industry are (1) simulations where the hauling rates are varied, (2) scenarios in which the U.S. becomes a major participant in the export market, and (3) situations where the marketing environment leads to increasing costs of production. Another alternative scenario involves only the spatial dimension of the NDM. Given the current marketing conditions in the dairy industry, the results of the NDM indicate that Virginia dairy producers are competitive in a marketing environment where the location of milk production is determined by a producer's costs of production and location advantages. Using Virginia's translog cost function, the cost per cwt. at the mean of the FCRS production data is $10.60. The cost estimate applies to Virginia's representative dairy farm where the average herd size is 91 cows and annual production per cow is 14,160 pounds. With these estimates and the fact that Virginia producers are near large population centers, the results of the NDM show that Virginia dairy farms are competitive in a deregulated market. / Ph. D.