I dagens samhälle har digitalisering blivit en stor del av vår vardag. Med global digitalisering kommer förändringar i hur organisationer och företag fungerar, detta inkluderar även hälso- och sjukvården. En viktig aspekt av digitaliseringen är mängden data som den genererar. Det har blivit en viktig aspekt för framgång under de senaste åren har varit relaterad till hur organisationer använder data till sin egen fördel. Användningen av data har ökat dramatiskt på en global skala och vi kan nu se fördelarna med att ha dataanalys inte bara i organisationen som helhet utan också använda den utvunna data för beslutsfattande. Denna studie syftar till att klargöra hur datadrivet beslutsfattande uppfattas av anställda inom hälso-. och sjukvården. Samt hur de uppfattar användande, möjligheter, begränsningar och risker med att fatta datadrivna beslut. Denna studien är skriven på svenska och har utförts genom en kvalitativ metod. Det har genomförts en liten-n-studie där enskilda intervjuer med fyra stycken respondenter genomförts. Respondenterna upplever att användandet av datadrivet beslutsfattande som något positivt och ser framtida möjligheter för datadrivet beslutsfattande inom hälso- och sjukvården. Dem identifierar risker och begränsningar med att använda denna typ av beslutsfattande, trots detta är fördelarna samtliga respondenter uttrycker övervägande gentemot dem risker och begränsningar som detta medför. / In today's day and age digitalisation has become a big part of our society. With global digitalisation comes changes in how organizations and companies function, this also includes healthcare. An important aspect of digitization is the amount of data it generates. It has become an important aspect of success in recent years has been related to how organizations use data to their own advantage. The use of data has increased dramatically on a global scale and we can now see the benefits of having data analysis not only in the organization as a whole but also using the extracted data for decision making. This study aims to clarify how data-driven decision-making is perceived by health care employees. and healthcare. And how they perceive use, opportunities, limitations and risks in making data-driven decisions. This study is written in Swedish and has been performed using a qualitative method. A small-n study has been conducted in which individual interviews with four respondents were conducted. The respondents perceive the use of data-driven decision-making as something positive and see future opportunities for data-driven decision-making in the health care sector. They identify risks and limitations with using this type of decision-making, despite this the advantages all respondents express are predominantly positive compared to the negative factors regarding data-driven decision-making.

Tillverkningsindustrin blir alltmer digitaliserad samt att nya digitala verktyg implementeras inom företagen. Som följd av detta pågår en förändring av arbetssätt. Smart Maintenance är det senaste begreppet i hur underhåll borde utföras inom tillverkningsanläggningar med hjälp av digital teknik. Detta begrepp syftar på ett arbetssätt som ämna möjliggöra en resurseffektivare produktion och underhållsverksamhet, ur såväl organisatoriskt som tekniskt perspektiv. I detta examensarbete genomfördes intervjuer med företag, vilket utgjorde den centrala undersökningsmetoden för att förstå hur den svenska tillverkningsindustrin ser på Smart Maintenance (SM), vad deras tolkning är på begreppet samt ifall de har tillämpat detta, samt tillämpat aspekter eller dimensioner från SM i deras underhållsverksamhet. En intervju med en forskare genomfördes för att utöka projektgruppens kompetens kring begreppet och dess påverkan på lönsamhet, hållbarhet och konkurrenskraft. Med information från intervjuerna och en litteraturstudie som grund, erhölls slutsatser kring vilka de främsta fördelarna och utmaningarna är i utövandet av Smart Maintenance, samt dessas samband med hållbarhet. Dessutom resulterade projektet i slutsatser kring hur företagen tolkar begreppet och hur data kan används för investeringsplaner inom de intervjuade företagen. / The manufacturing industry is becoming increasingly digital and new digital tools are being implemented within companies. As a result, there is a change in working methods. Smart Maintenance is the latest concept in how maintenance should be performed in manufacturing facilities using digital technology. This concept refers to a way of working that aims to enable a more resource-efficient production and maintenance operation, from both an organizational and technical perspective. In this thesis, interviews were conducted with companies, which constituted the central research method for understanding how the Swedish manufacturing industry views Smart Maintenance (SM), what their interpretation is of the concept and if they have applied this, and applied aspects or dimensions from SM in their maintenance operations. An interview with a researcher was conducted to expand the project group's knowledge on the concept and its impact on profitability, sustainability and competitiveness. Based on information from the interviews and a literature study, conclusions were obtained about what the main benefits and challenges are in the practice of Smart Maintenance, as well as their connection with sustainability. In addition, the project resulted in conclusions about how the companies interpret the concept and how data can be used in order to make better decisions within the interviewed companies.

<p> </p> <p><em>This study examines data-driven contract design in the small data regime and large data regime respectively, and the implications from contract pricing in the pharmaceutical supply chain. </em></p>

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<p>Citizens’ interaction with governments is an area with unique implications for channel management. Governments need to take the citizens perspective into further consideration in order to be successful in delivering high-quality e-services. This paper aims to determine if a categorization of citizen-initiated contacts from a citizen-centric perspective can be a valuable basis for decisions regarding e-service development. The study consisted of three steps. The first step was an examination of the existing related literature, which resulted in the uncovering of the most important aspects of citizens channel choice. The second step consisted of an elaboration of a classification based on perceived task characteristics and a subsequent matching of the categories to desirable channel characteristics. The third and final step consisted of an application of the proposed categorization on a content management system containing all citizen-initiated contacts in a Swedish municipality. The application indicated that the proposed categorization could possibly be used to guide investments in e-services towards a channel-appropriate direction.</p>

Achieving the Dream is a national initiative focused on helping more community college students succeed, particularly students of color and low-income students. Achieving the Dream’s student-centered model of institutional improvement focuses on eliminating gaps and raising student achievement by helping institutions build a culture of evidence through institutional transformation. This interpretive case study employed a mixed methods approach and utilized a sequential explanatory strategy to gather detailed information related to the research questions. The study examined, from an insider’s perspective, the progress made by an Achieving the Dream college in implementing practices that reflect the principles of the Achieving the Dream model of institutional improvement. The four principles of the model are: committed leadership, use of evidence to improve programs and services, broad engagement, and systemic institutional improvement. The study was conducted in two phases and involved a quantitative survey of all college employees and semi- structured, individual interviews with members of the college’s Achieving the Dream team. The quantitative and qualitative data were given equal weighting in the study and were integrated to the extent that the qualitative data collected provided supportive insights into the findings derived from the quantitative analysis. This study found the college made progress in implementing the practices reflected by the Achieving the Dream model. The study findings also provide insights into underlying factors that existed at the college related to its implementation of the initiative. The findings will supplement current knowledge about the efficacy of change models designed to help community colleges build a student-centered model of institutional improvement and the knowledge gained should not only benefit the college, but also provide useful information to other institutions involved in this initiative. / text

Citizens’ interaction with governments is an area with unique implications for channel management. Governments need to take the citizens perspective into further consideration in order to be successful in delivering high-quality e-services. This paper aims to determine if a categorization of citizen-initiated contacts from a citizen-centric perspective can be a valuable basis for decisions regarding e-service development. The study consisted of three steps. The first step was an examination of the existing related literature, which resulted in the uncovering of the most important aspects of citizens channel choice. The second step consisted of an elaboration of a classification based on perceived task characteristics and a subsequent matching of the categories to desirable channel characteristics. The third and final step consisted of an application of the proposed categorization on a content management system containing all citizen-initiated contacts in a Swedish municipality. The application indicated that the proposed categorization could possibly be used to guide investments in e-services towards a channel-appropriate direction.

Customer insight is at the heart of the big data era. This revolution makesit possible to directly obtain high potential data and in large quantitiesabout customers. Thus we take note that, more than ever, a large volumeof big data is collected by companies.We observe that big data have become a necessary tool within marketing.More and more companies orient their decisions according to theinformations provided by data, with the aim of quickly having betterresults.Nevertheless, in order to integrate these big data in a better way and gaina competitive advantage, companies must face new challenges. Tomeasure and understand the impact of big data in marketing decisions,we propose, with the support of our scientific and theoretical resources, areasoning, demonstrating all the issues. Big data is increasinglyubiquitous and necessary for companies (I). Their impact in decisionsneeds to be taken into account (II) and their use is leading to amanagement revolution (III). Moreover, it modifies the close relationbetween decision and intuition. (IV). In this article, we present aperspective that study all these concepts. We close by offering a modeland a conclusion answering our problematic.

During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.

Over the past years, the value of data and DDDM have increased significantly as technological advancements have made it possible to store and analyze large amounts of data at a reasonable cost. This has resulted in completely new business models that has disrupt whole industries. DDDM allows businesses to rely their decisions on data, as opposed to on gut feeling. Up until this point, literature is eligible to provide a general view of what are the major challenges corporations encounter when implementing a DDDM strategy. However, as the field is still rather new, the challenges identified are yet very general and many corporations, especially B2B MNCs selling consumer goods, seem to struggle with this implementation. Hence, a single-case study on such a corporation, named Alpha, was carried out with the purpose to explore what are their major challenges in this process. Semi-structured interviews revealed evidence of four major findings, whereas, execution and organizational culture were supported in existing literature, however, two additional findings associated with organizational structure and consumer behavior data were discovered in the case of Alpha. Based on this, the conclusions drawn were that B2B MNCs selling consumer goods encounter the challenges of identifying local markets as frontrunners for strategies such as the one to become more data-driven, as well as the need to find a way to retrieve consumer behavior data. With these two main challenges identified, it can provide a starting point for managers when implementing DDDM strategies in B2B MNCs selling consumer goods in the future.