Transportation agencies engage in extensive data collection activities in order to support their decision processes at various levels. However, not all the data collected supply transportation officials with useful information for efficient and effective decision-making. This thesis presents research aimed at formally identifying links between data collection and the supported decision processes. The research objective identifies existing relationships between Asset Management data collection and the decision processes to be supported by them, particularly in the project selection level. It also proposes a framework for effective and efficient data collection. The motivation of the project was to help transportation agencies optimize their data collection processes and cut down data collection and management costs. The methodology used entailed two parts: a comprehensive literature review that collected information from various academic and industrial sources around the world (mostly from Europe, Australia and Canada) and the development of a web survey that was e-mailed to specific expert individuals within the 50 U.S. Departments of Transportation (DOTs) and Puerto Rico. The electronic questionnaire was designed to capture state officials' experience and practice on: asset management endorsement and implementation; data collection, management and integration; decision-making levels and decision processes; and identified relations between decision processes and data collection. The responses obtained from the web survey were analyzed statistically and combined with the additional resources in order to develop the proposed framework and recommendations. The results of this research are expected to help transportation agencies and organizations not only reduce costs in their data collection but also make more effective project selection decisions. / Master of Science

Kreditbedömning är ett viktigt verktyg för de svenska storbankerna i rollen som kapitalförmedlare för företag. Den kan baseras på de 5 C’na och genomföras på flera olika beslutsinstanser. Det finns ett praktiskt och ett teoretiskt problem i hur bankerna skall organisera kreditbedömningen då tidigare forskning är oense om prioriteringen i kreditbedömningen på olika beslutsinstanser och vad som förklarar det. Studiens huvudsyfte är då vad beslutsinstanserna i de svenska storbankerna prioriterar i kreditbedömning av företag, inom ramen för de 5 C’na, och vilka faktorer som förklarar det. Med en kvalitativ metod har vi intervjuat chefer och företagsansvariga som representerar högsta och lägsta beslutsinstans på lokal nivå medan sekundärdata i form av bankernas riskrapporter har representerat central nivå och högsta beslutsinstans. Resultatet är att central nivå och cheferna prioriterar kapaciteten och de företagsansvariga karaktären. Faktorer som förklarar det är lagar och kreditpolicy som central nivå respektive cheferna uppger som mer styrande kring att prioritera kapaciteten. Vidare består ratingen av såväl finansiella nyckeltal som subjektiva bedömningar. Annan faktor är storleken på företaget där företagsansvariga hanterar mindre företag vilka lämpligast bedöms med utgångspunkt i karaktären. / Credit assessment is an important tool for the Swedish major banks in the role as capital intermediaries for companies. It can be based on the 5 C’s and used on several different decision levels. There is a practical and a theoretical problem in how the banks should organize the credit assessment since earlier research disagree regarding the prioritising in the credit assessment on different decision levels and what explains it. The main purpose of the study is then what the decision levels in the Swedish major banks prioritize in the credit assessment of companies, within the frame of the 5 C’s and which factors that explains that. With a qualitative method we have conducted interviews with managers and business advisors who represent the highest and the lowest decision levels on the local level, whilst secondary data in terms of the banks risk management reports have represented central level and the highest decision level. The result is that central level and the managers prioritize the capacity and the business advisors prioritize the character. Explaining factors is laws and credit policies which central level and managers sees as more controlling regarding prioritizing the capacity. Further on the rating consists of both financial ratios as well as subjective judgements. Another factor is the size on the company where business advisors handle smaller companies, which are easiest judged with base in the character.