Opportunities and challenges of content marketing as a way of digital marketing communications

Tämän tutkimuksen tavoitteena on tunnistaa sisältömarkkinoinnin mahdollisuuksia ja haasteita digitaalisessa markkinointiviestinnässä. Lisäksi tavoitteena on antaa yksiselitteinen määritelmä sisältömarkkinoinnille sekä selvittää, miten se eroaa muista markkinointiviestinnän keinoista. Sisältömarkkinointi on strateginen markkinointiviestinnän keino, johon kuuluu asiakkaan kannalta mielenkiintoisen ja hyödyllisen sisällön tuottaminen ja jakaminen. Sisältömarkkinointi tarjoaa keinon muodostaa brändimielikuvia luonnollisin keinoin ilman mainoksen leimaa, jota osa kuluttajista välttelee tietoisesti jopa mainosten esto-ohjelmien avulla. Perinteiset markkinointiviestinnän keinot pyrkivät usein lyhyen aikavälin myyntituloksiin, kun taas sisältömarkkinointi pyrkii maksimoimaan asiakkaan koko elinkaaren arvon. Onnistunut sisältömarkkinointi vaatii yrityksiltä kärsivällisyyttä sekä asiakkaiden kokonaisvaltaista tuntemista.

A Research of Resource Scheduling Algorithm Based on Hadoop

With the development of electronic devices, more and more mobile clients are connected to the Internet and they generate massive data every day. We live in an age of “Big Data”, and every day we generate hundreds of million magnitude data. By analyzing the data and making prediction, we can carry out better development plan. Unfortunately, traditional computation framework cannot meet the demand, so the Hadoop would be put forward. First the paper introduces the background and development status of Hadoop, compares the MapReduce in Hadoop 1.0 and YARN in Hadoop 2.0, and analyzes the advantages and disadvantages of them. Because the resource management module is the core role of YARN, so next the paper would research about the resource allocation module including the resource management, resource allocation algorithm, resource preemption model and the whole resource scheduling process from applying resource to finishing allocation. Also it would introduce the FIFO Scheduler, Capacity Scheduler, and Fair Scheduler and compare them. The main work has been done in this paper is researching and analyzing the Dominant Resource Fair algorithm of YARN, putting forward a maximum resource utilization algorithm based on Dominant Resource Fair algorithm. The paper also provides a suggestion to improve the unreasonable facts in resource preemption model. Emphasizing “fairness” during resource allocation is the core concept of Dominant Resource Fair algorithm of YARM. Because the cluster is multiple users and multiple resources, so the user’s resource request is multiple too. The DRF algorithm would divide the user’s resources into dominant resource and normal resource. For a user, the dominant resource is the one whose share is highest among all the request resources, others are normal resource. The DRF algorithm requires the dominant resource share of each user being equal. But for these cases where different users’ dominant resource amount differs greatly, emphasizing “fairness” is not suitable and can’t promote the resource utilization of the cluster. By analyzing these cases, this thesis puts forward a new allocation algorithm based on DRF. The new algorithm takes the “fairness” into consideration but not the main principle. Maximizing the resource utilization is the main principle and goal of the new algorithm. According to comparing the result of the DRF and new algorithm based on DRF, we found that the new algorithm has more high resource utilization than DRF. The last part of the thesis is to install the environment of YARN and use the Scheduler Load Simulator (SLS) to simulate the cluster environment.

Life cycle management of TVO nuclear power plant

Tämä diplomityö tutkii eri elinkaarihallinnan menetelmiä ja vertaa niitä TVO:n menetelmiin. Lisäksi TVO:n prosessin ongelmakohdat tunnistetaan ja niihin esitetään ratkaisuja. Vertailukohteina toimii ydinvoimateollisuuden lisäksi vesivoima, fossiiliset voimalaitokset sekä paperiteollisuus. Sähkön hinnan jatkaessa laskuaan on elinkaariajattelusta tullut ajankohtaista myös ydinvoimayhtiöille. Ydinvoimalaitoksien pitkän suunnitellun käyttöiän ansiosta laitoksen elinkaaren aikana voi tapahtua useita asioita, jotka vaikuttavat laitoksen investointitarpeisiin. Turvallisen sähköntuotannon varmistamiseksi eri laitososia on joko muokattava tai uusittava. Elinkaariajatteluun kuuluu tehokas laitoksen kunnon valvonta, laitoksen ikääntymiseen vaikuttavien ilmiöiden tunnistaminen, sekä ikääntymistä hillitsevien toimenpiteiden pitkän tähtäimen suunnittelu. Hyvällä ennakkosuunnittelulla pyritään varmistamaan se, että laitoksella voidaan tuottaa sähköä koko sen jäljellä olevan käyttöiän aikana. Kun tarpeiden tunnistus ja suunnittelu tehdään hyvissä ajoin mahdollistetaan myös investointien optimointi. Paras hyöty pyritään saamaan ajoittamalla oikeat investoinnit oikeaan aikaan.

Team characteristics beneficial for Open Innovation projects

This study discusses the importance of creating Open Innovation (OI) teams for optimizing costs of Research and Development (R&D), dividing risks and maximizing profits. The purpose of this study is to determine team characteristics beneficial for successful OI project, with the emphasis on the fact that such teams are formed of professionals belonging to different organizations, both private and state-owned, with different educational and professional backgrounds and personal qualities. This purpose is supported by three sub-objectives: to observe the phenomenon of OI and its implementation in emerging economies, particularly in Russia; to specify professional and personal competencies of OI team members essential for the successful collaboration; and to identify the role of the leader in OI teams. The theoretical part of this study consists of knowledge from academic literature related to OI, cross-functional and innovation teams and leadership in innovation. The practical part of the study is presented in the form of multiple case study, and the empirical research is based on six semistructured interviews collected in October 2014 from the CEOs, Innovation Managers and Technical Directors of innovation companies participating actively in OI projects. The findings of the study demonstrate that many of the necessary competencies are equal for innovation or cross-functional teams and OI teams, such as professionalism and communication skills. However, due to the specific nature of OI, additional personal characteristics were recognized as beneficial for OI teams, such as flexibility, empathy and success-orientation. The role of the leader is also considered as a critical success factor for OI teams, with the emphasis on flexibility and autonomy. The findings of the study contribute to understanding the connection between notions of team member, team climate and team leader, and its influence on OI project success. Thus, the main purpose of the study is providing support for existing knowledge on OI teams and developing new insights into this newly emerged topic.

Developing smart services by Internet of Things in manufacturing business

Manufacturing companies have passed from selling uniquely tangible products to adopting a service-oriented approach to generate steady and continuous revenue streams. Nowadays, equipment and machine manufacturers possess technologies to track and analyze product-related data for obtaining relevant information from customers’ use towards the product after it is sold. The Internet of Things on Industrial environments will allow manufacturers to leverage lifecycle product traceability for innovating towards an information-driven services approach, commonly referred as “Smart Services”, for achieving improvements in support, maintenance and usage processes. The aim of this study is to conduct a literature review and empirical analysis to present a framework that describes a customer-oriented approach for developing information-driven services leveraged by the Internet of Things in manufacturing companies. The empirical study employed tools for the assessment of customer needs for analyzing the case company in terms of information requirements and digital needs. The literature review supported the empirical analysis with a deep research on product lifecycle traceability and digitalization of product-related services within manufacturing value chains. As well as the role of simulation-based technologies on supporting the “Smart Service” development process. The results obtained from the case company analysis show that the customers mainly demand information that allow them to monitor machine conditions, machine behavior on different geographical conditions, machine-implement interactions, and resource and energy consumption. Put simply, information outputs that allow them to increase machine productivity for maximizing yields, save time and optimize resources in the most sustainable way. Based on customer needs assessment, this study presents a framework to describe the initial phases of a “Smart Service” development process, considering the requirements of Smart Engineering methodologies.