Browsing by Department "Tieto- ja palvelujohtamisen laitos"
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Item 21st Century Cottage Industry - A cross-case synthesis of freelancer intermediary platforms(2018) Suvivuo, Sampsa; Tuunainen, Virpi; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessThe purpose of this study was to identify possible archetypes of freelancer intermediary platforms. Though there is growing interest towards platforms, classification of platforms stops when it is classified as a transaction, innovation, integrated or some other platform. However, this approach doesn’t account for the variation within these categories. Given the young population's interest towards freelancing and the estimated size of the platform economy as a whole ($4300 Bn.) and the number of freelancer intermediaries (250-300), attempting to identify the subtypes of freelancer intermediary platforms was deemed a worthy endeavor. Finding these subtypes of intermediary platforms or archetypes of freelancer intermediaries has both academic and practical implications. For academics, these archetypes will contribute to the growing body of platform literature by giving it new units of analysis and by creating reasonable categorization. For people interested in utilizing a freelancer intermediary platform either as a seller or a buyer, this thesis offers solid knowledge of the intermediary platforms functions and features as well as what to expect when joining one. The research design is built on principles of embedded and flexible multiple-case study and cross-case synthesis. When describing a contemporary phenomenon, a multiple-case study produces more robust results when the weight of one case decreases. The cross-case synthesis was one of the few viable options given the study’s lack of dependent and independent variables. These variables were unavailable because no beforehand information on what the archetypes could be was available. For this reason, this study adapted analytical methods of grounded theory. The study identified four archetypes of freelancer intermediary platforms: the locals, two for the price of one, the middle child and the global juggernauts. Locals focus on physical services that are dependent on freelancers’ location. Two for the price of one are small platforms that charge only one side be it, seller or buyer. The middle child is very similar to global juggernauts in other aspects but the size and is a necessary phase in the platform’s maturation. Global juggernauts are the biggest platforms and the industry leaders that have significant network and trust management systems in place. Archetypes form a solid foundation on which future research on freelancer intermediaries can be based on.Item A pragmatic web design process(2022) Hokkanen, Matias; Rossi, Matti; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessItem A review of challenges in the implementation of cloud-based ERP systems(2021) Eurasto, Frans; Bragge, Johanna; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessItem Äänimediasisältöihin perustuvan liiketoiminnan alueellisuus ja skaalautuvuus(2020-12-15) Tiilikainen, Sanna; Tuunainen, Virpi; Arminen, Ilkka; Muotoilun laitos; Tieto- ja palvelujohtamisen laitos; University of HelsinkiItem Acceptance of AI-based diagnostic tools in neuroimaging(2022) Nenonen, Iida; Penttinen, Esko; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessArtificially intelligent (AI) methods are employed in many areas of medical sciences, while they are still under-utilized in functional neuroimaging methods like magnetoencephalography (MEG). This study was performed to obtain prerequisite information of the acceptance and potential adoption of AI-based analysis methods among prominent MEG clinicians and research scientists. The study was conducted as a technology case study focusing on MEGIN Oy (Espoo, Finland) who is the global leader for MEG technology. In the future products, AI-based methods and cloud computing are strategically important for widening the clinical applications of MEG in larger patient populations and expanding the MEG market. Semi-structured interviews were conducted with MEG users in three different hospitals in the US and three in Europe. The interviews directly probed the opinions and perspectives of the clinicians and researchers of the AI methods on MEG. The study utilized the Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology frameworks, both to formulate interview questions and to account for the factors that emerged from the interview data. All interviewees showed very positive attitude towards automated and AI-based data processing methods in MEG. They also want to widen the applicability of MEG in larger patient populations. Time-efficiency of AI methods was considered the biggest advantage, along with multi-dimensionality of the interpretation. Therefore, the AI tools could advance learning of the development phases of brain disorders. Opinions on the transparency of algorithms varied, but all interviewees agreed that the validation process should have maximal transparency. New AI tools should be developed considering multiple empirical evidence and AI model training with data specific to the brain disorders. The clinical experts need to know what data is put in the tool, what data has been used in the tool validation, and how the tool’s accuracy and reliability has been proven. They also want visualization methods to assess the quality of the data and the results. Besides user acceptance, factors were discussed that in general explain the lagging adoption of AI. They include limited access to patient data, questions of data security and ownership, and regulatory barriers.Item Achieving Sustainability through Circular Supply Chain Management(2023) Leino, Oliver; Kim, Seongtae; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessClimate change is a global problem, which actively drives companies to look for sustainable solutions in everyday operations. Consumers are also becoming more environmentally conscious and purchase products that are manufactured and transported in a sustainable way. This has led to the implementation of sustainable solutions in supply chains becoming more important not only for the climate but to maintain a positive image in the consumer’s eyes. This thesis analyses the advantages and disadvantages of implementing a circularity in supply chain operations. The theory of circular supply chain management seeks to shrink resource consumption and waste, and to minimize harmful environmental effects with the aid of the circular economy model. In these circular supply chains products and materials are recycled at the end of their lifespan so that the resources are kept in use for a longer period. The goal of the review is to provide information about the benefits of circular supply chain management and explore already existing literature on just how it can have a positive effect. The thesis analyses the benefits from an economic, social, and environmental perspective. The circular economy model aims to maintain resources in use for as much time as viable by maximizing their utilization and it is a key concept in achieving sustainability through circular supply chain management. The concept of circular supply chain management has surfaced as a solution to reach more sustainable resource management. This thesis highlights the significance of adopting circular models in supply chain management and the benefits that it can yield to both businesses and the environment.Item Action design research: Developing a robotic process automation tool for data migration(2024) Karhila, Joonas; Ghanbari, Hadi; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessOrganizations undergoing digital transformation have a growing need for automation solutions. These solutions save time and resources by replacing human manual labour with automated workflows. One example of these solutions is Robotic Process Automation (RPA). The rising level of adoption in such technologies has realized the multitude of ways such technologies can be integrated to be leveraged in digital transformation. One of these use cases is data migration, a cornerstone in successfully upgrading digital systems. Since the research of the subject is minimal but there is a lot of potential for use case, this thesis will try to find out, if there is potential for more efficient processes in data migration via usage of RPA. In this thesis, an RPA tool is developed by using Action Design Research, a frame-work which dedicates itself to continuous improvement and close co-operation between stakeholders. This RPA tool is implemented in a client project, where data migration is done for Field Service Management-system transformation. The result was that there was a lot of processes inside data migration that could be made more efficient with RPA usage. It was also evident that the adoption of RPA was something that needed to be bought-in at an organizational level for the benefits to be fully realized. It was also discovered that continuous improvement during the development session was vital and stakeholders are essential to be kept in loop straight from the starting point. The findings of this research are also something that create multiple possibilities for further research around the subject, for example on how AI could be implemented to be part of RPA tools.Item An Activity-based Branch-and-Price Method for the Continuous-Time Resource-Constrained Project Scheduling Problem with Flexible Resource Profiles(2020) Ngô, Lan; Liesiö, Juuso; Naber, Anulark; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessThe resource-constrained project scheduling problem (RCPSP) is an optimization problem that involves the scheduling of a set of activities over time, where each activity consumes a set of renewable resources, and there are dependent relationships among activities. The objective of the RCPSP is to minimize the project makespan, i.e., the total duration of the project. Specifically, this thesis aims at devising a new solution approach for a variant of the RCPSP in which resource allocations can vary throughout the activities' processing time, and the system time is continuous. This variant is termed the resource-constrained project scheduling problem with flexible resource profiles in continuous-time (CT-FRCPSP). Branch-and-Price (BAP) is the solution approach adopted for solving the CT-FRCPSP. BAP is a hybrid method between Branch-and-Bound (BAB) and column generation. BAB is a well-known method for solving mixed-integer programming problems by solving the LP-relaxation of the problem and then branching on the variables with fractional solutions. In BAP, instead of solving the LP-relaxation with the full set of variables at each node of the BAB tree, column generation is used to solve the LP-relaxation by iteratively adding improving columns to the problem until it reaches optimality. The goal of this thesis is to implement the Branch-and Price (BAP) algorithm to solve a simplified version of the CT-FRCPSP and evaluate the effectiveness of the algorithm in solving instances of the CT-FRCPSP. Moreover, in order to reduce the symmetries in the CT-FRCPSP, we propose two symmetry breaking constraints: left-shift and pattern-breaking symmetry breaking constraints. The computational experiment involves evaluating the improvement of the LP-relaxation at the root node and identifying the effectiveness of symmetry breaking constraints in improving the reformulated formulation. In addition, the results from the implemented algorithm are compared with the results from CPLEX's Branch-and-Cut to evaluate how well our BAP implementation can solve instances of the CT-FRCPSP.Item Adapting to the Digital Revolution: Analyzing the Impact of FinTech Innovations on the Banking Industry(2023) Al-Rubaye, Ali; Bragge, Johanna; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessTechnology has rapidly transformed various industries, and the banking sector is no exception. Banks are facing fierce competition from the Financial Technology (FinTech) industry, which is revolutionizing traditional banking and providing customers with innovative and efficient financial services. However, this also presents significant challenges for banks. The study will focus on various perspectives such as the effects of an increased competitiveness from the FinTech industry to the banking business, the impact of banks adopting FinTech tools and innovations, and the customer experience and satisfaction in the banking sector in relation to these developments. The research will also investigate potential risks and rewards for bank customers, including data privacy and security concerns. The study will further investigate the role and effectiveness of regulations in shaping the FinTech landscape and how they influence traditional banking. It will examine how regulators are leveraging RegTech, or Regulatory Technology, to keep pace with FinTech innovations and ensure compliance with regulations. The research will also analyze the impact of regulatory arbitrage, which has led to the rise of shadow banks and the potential risks associated with it. This study contributes to the existing body of knowledge on FinTech in banking and provides valuable insights for regulators, financial institutions, and customers alike.Item Addictive design of social media(2021) Lahtinen, Tuure; Bragge, Johanna; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessItem Addressing blockchain scalability issues – case: Lightning Network(2021) Vuorinen, Marko; Rossi, Matti; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessItem Adopting digital and ERP processes and analyzing the critical success factors of ERP implementation on SMEs(2023) Santamäki, Aarne; Bragge, Johanna; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessDigital transformation is a prevailing trend shaping companies worldwide. This paper delves into a detailed examination of digital transformation through the lens of critical success factors (CSFs) in ERP implementation projects within small and mid-size companies. The research introduces digital transformation frameworks, contextualizes ERP as a business tool, and explores the distinctive landscape of SME-specific business fields. Additionally, it elucidates the nuances of ERP system characteristics pertinent to SMEs and scrutinizes these SME-specific attributes. By drawing upon existing literature and conducting a bibliometric analysis, this work systematically reviews the most recognized existing CSFs. Furthermore, it presents an inductive framework tailored to SME companies' ERP CSFs, aligning with their unique operational contexts.Item The Adoption of Ar of Ar by Consumers in the Tourism Industry(2024) Müftüoglu, Meyra; Movarrei, Reza; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessIn this new, rapidly evolving technological era, the tourism industry is no exception to the transformative potential of new technologies. In a world where travelers increasingly are looking for different and personalized journeys, advancements in augmented reality (AR) offer the potential to create self-sufficient tourists. This thesis aims to understand how new technologies have affected and will affect the tourism industry in the future. This research will primarily focus on augmented reality, which develops tourists to be more self-sufficient, and its benefits and challenges to the consumers. The research will analyze the motivation behind the actual use of AR. This study seeks to fill the research gap in consumers’ growing self-sufficiency by adopting AR applications. Qualitative research was chosen for this study to reach the research objectives. Interview questions considered the following concepts: perceived usefulness, perceived ease of use, autonomy and competence, perceived risk and trust. The findings of this study show a positive transformation in the tourism industry as a result of augmented reality (AR) applications. AR technologies significantly enhanced consumers’ travel experiences by providing timely and contextually relevant information. The ease of using AR applications played a crucial role in influencing tourists to adopt these technologies, with respondents highlighting the user-friendly nature of such tools. Moreover, the examination of autonomy and competence demonstrated a favorable connection between tourists’ ability to be self-sufficient and their engagement with AR tools. Participants expressed a feeling of empowerment in customizing their travel experiences. Despite these positive aspects, challenges such as perceived risk and trust emerged, indicating concerns related to data security and the reliability of information provided by AR.Item The adoption of in-store mobile payment in Finland(2021) Karesoja, Maria; Hekkala, Riitta; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessPayment industry is rapidly evolving but consumers are still hesitant towards current payment trends, like mobile payment. Finland is behind otherwise similar Nordic countries in the adoption of in-store mobile payment. The objective of this thesis is to find out, what are the key factors influencing the adoption of in-store mobile payment among young, specifically generation Z, consumers. It also aims to find out if the ongoing Covid-19 pandemic has had an impact on attitudes towards in-store mobile payment. A qualitative research in the form of three interviews was conducted to reach the research objectives. Three different kinds of in-store mobile payment users between the ages of 18 and 25 were interviewed. One has never used in-store mobile payment, one uses it occasionally and one on a daily basis. The questions considered the following factors, drawn from previous research: perceived ease of use, perceived usefulness, social influence, personal innovativeness, intention to recommend, perceived risk and perceived hygiene. Perceived risk was found to be the largest inhibitor of in-store mobile payment adoption. Security concerns like the device getting lost or stolen as well as hackers and misuse came up the most. Additionally, uncertainty about the performance of mobile payment was a barrier for one interviewee. Another significant barrier for mobile payment adoption is the attitude towards contactless card payment, which is seen as convenient enough, reducing the will to try mobile payment. Social influence, and specifically the recommendation of others was found significant as a motivator for use. Personal innovativeness was found to be somewhat significant but less so than social influence. This is among the first mobile payment adoption research to consider perceived hygiene and the context of Covid-19. While perceived hygiene was found insignificant in mobile payment adoption in this research, it should be studied more with a larger sample. The most valuable measures mobile payment service providers can take, is to market the advantages of mobile payment over contactless card payment and raise consumer knowledge about the method. As security concerns make consumers hesitant towards in-store mobile payments, service providers should also increase awareness of the security measures taken. It was also found that additional services like bonus cards and consumption tracking would motivate consumers to use in-store mobile payment more.Item ADOPTION OF SELF-SERVICE BUSINESS INTELLIGENCE TO BOOST CROSS-SELLING IN A TECHNOLOGY COMPANY(2021) Dinh, Khoa; Penttinen, Esko; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessItem Advanced Analytics Success Factors - A Case Study(2018) Mattila, Olli-Pekka; Liesiö, Juuso; Vilkkumaa, Eeva; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessCompanies are increasingly taking into use advanced analytics solutions. Advanced analytics solutions are computer programs that analyze data, make predictions on the future, and give optimization-based recommendations on courses of action for achieving pre-determined business goals. Analytics solutions employ sophisticated statistical and mathematical models, and are often offered by third parties. Companies use analytics solutions to improve the efficiency of their operations. This thesis studies whether the distinction between analytics and advanced analytics made in literature is well-founded. The second aim of this study is to find out, what contributes to an analytics initiative’s success. The study begins with a literature review synthesizing the findings of previous analytics research. The resulting synthesis identifies four distinct stages in an analytics project. They are acquiring data, transforming it into insights, communicating the insights, making business decisions, and finally implementing the decisions. Factors that contribute to each stage’s success are identified. The hypotheses that were developed in the theoretical part of the thesis are subsequently tested empirically using the single case study method and semi-structured interviews. The case study confirms the findings of earlier research. Analytics can be viewed as a process with clearly identifiable stages. Specific measures can be taken to improve the success of each stage. The results obtained suggest that an analytics initiative should always be preceded by a thorough goal definition stage. This is a finding that earlier research has not emphasized sufficiently. The study offers business executives a clear roadmap for managing analytics initiatives. It formulates clear action points and allocates parties the responsibility for executing them. The study also highlights some ordinary pitfalls preventing companies from fully benefitting from the results of analytics initiatives. Finally, the study points out new interesting research opportunities in the intersection of information systems science and cognitive science. A key difficulty in using analytics effectively is that the reasoning behind the insights created by the solutions are often complex. Cognitive science could provide us tools for making the insights easier to digest. Lastly, the study highlights that process decoupling will eventually be applied to analytics initiatives. Future studies should research how the stages of an analytics initiative can be separated from each other, and outsourced to parties performing them the most effectively.Item Agile business intelligence: How can organizations improve their BI agility?(2022) Lilja, Dora; Liu, Yong; Lin, Yanqing; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessItem AI in CRM Systems: Evaluating the Prerequisites for Successful Adoption(2020) Paju, Roope; Penttinen, Esko; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessArtificial intelligence (AI) technologies have advanced greatly during the recent years. Previously the use of these technologies has demanded difficult to get internal capabilities for developing machine learning algorithms and implementing them in applications such as social media platforms and virtual assistants. Today the idea of implementing these novel technologies also in enterprise systems (ES) has aroused the interest of many companies. One of the most important enterprise system categories is the CRM (customer relationship management) system, which is constantly growing its significance as the companies in different industries aim to become more customer centric. Different CRM system providers, such as Salesforce, Oracle and companies operating in their ecosystems have begun to offer various AI-CRM applications for their customer companies to utilize in enhancing their own business operations. Even though the topic is growing interest, companies’ experience of these applications is limited and there are few available roadmaps to follow. This thesis aims to offer organizations planning on implementing AI-CRM applications a tool to analyze the potential prerequisites to be fulfilled to maximize the chances of successful adoption. The fit-viability model (FVM) has been previously used to analyze different IT initiatives. This study aims to develop it further and tests it in the context of AI-CRM applications. The study consists of two parts, first of which is a background research focusing on collecting insights about implementation of AI-CRM applications from expert sources and recognizing different applications on market through an Internet research. The second part is a multi-case study testing the FVM to analyze the selected AI-CRM applications in the context of various companies. The results of this thesis indicate that using the FVM to analyze AI-CRM applications provides meaningful insights and can help in recognizing and fulfilling the potential prerequisites for successful implementation. The model provides the insights in clearly understandable and visually presentable form that can be used to help decision-making processes. As the CRM system market is growing and the biggest providers on the market have a strong focus on providing AI-CRM applications, the significance of these solutions is not expected to decrease. Nevertheless, the topic is still in its early maturity and cases of successful adoption are limited. The research conducted in this thesis provides viewpoints for future research, and organizations can utilize the tested FVM in their own decision-making and implementation processes regarding AI-CRM applications.Item AI in process development and automation, case Finnish tax admistration(2021) Berg, Laura; Penttinen, Esko; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessItem AI powered m-health apps empowering smart city citizens to live a healthier life –The role of trust and privacy concerns(2022) Klossner, Sara; Ghanbari, Hadi; Tieto- ja palvelujohtamisen laitos; Kauppakorkeakoulu; School of BusinessThe rapidly growing world population is concentrating increasingly in urban areas, creating the need for smart city innovations. Smart healthcare is a central part of smart city services. In smart healthcare, Artificial Intelligence (AI) is of growing importance, as it enables healthcare to be more personalized, as AI can collect and analyze vast amounts of data more effectively than a human physician is able to. AI powered mobile health (m-health) applications have the potential to lower healthcare cost and empower individuals to take better care of their health in a preventive manner. For the m-health applications to reach their full potential, they need to gather and analyze the users’ health data, which enables the offering of highly personalized services. However, with the continuous data collection from users to be able to offer personalized services, the question on privacy and trust concerns arise. In this Thesis I’m researching the privacy and trust concerns users have towards m-health apps to better understand people’s behaviors and the constructs affecting their behavior. The empirical part of the research was done conducting an online survey. The study confirmed TAM in a new setting. The privacy paradox was also present, as privacy concerns did not have a negative effect on behavioral intention or self-disclosure. The personalization-privacy paradox was partly present. Self-efficacy was found to have a significant impact on decreasing privacy concerns and increasing self-disclosure, while self-disclosure had a positive effect on behavioral intention. The main contribution of the research was testing the new constructs of self-disclosure and digital self-efficacy together with previously tested constructs in a new setting in Finland. The findings indicate that companies should concentrate creating easy to use, useful and trustworthy applications so people would adopt and use them. On a societal level, it is important to achieve a high level of digital self-efficacy and self-disclosure to facilitate the adoption and use of m-health apps.
