Iowa Department of Administrative Services Customer Council Archives, 2005

Archive of meeting agendas and minutes for 2005 for the DAS-General Services Enterprise Customer Council.

Iowa Department of Administrative Services Customer Council Archives: Human Services, 2004

Archive of meeting agendas and minutes for 2004 for the DAS-Human Resources Enterprise Customer Council.

Iowa Department of Administrative Services Customer Council Archives: Human Services,2005

Archive of meeting agendas and minutes for 2005 for the DAS-Human Resources Enterprise Customer Council.

Iowa Department of Administrative Services Customer Council Archives: State Accounting, 2004

Archive of meeting agendas and minutes for 2004 for the DAS-I/3 Customer Council.

Iowa Department of Administrative Services Customer Council Archives: State Accounting, 2005

Archive of meeting agendas and minutes for 2005 for the DAS-I/3 Customer Council.

Assessment of needs, health-related quality of life, and satisfaction with care in breast cancer patients to better target supportive care.

BACKGROUND: This study assessed whether breast cancer (BC) patients express similar levels of needs for equivalent severity of symptoms, functioning difficulties, or degrees of satisfaction with care aspects. BC patients who did (or not) report needs in spite of similar difficulties were identified among their sociodemographic or clinical characteristics. PATIENTS AND METHODS: Three hundred and eighty-four (73% response rate) BC patients recruited in ambulatory or surgery hospital services completed the European Organisation for Research and Treatment of Cancer Quality of Life questionnaire (EORTC QLQ)-C30 quality of life [health-related quality of life (HRQOL)], the EORTC IN-PATSAT32 (in-patient) or OUT-PATSAT35 (out-patient) satisfaction with care, and the supportive care needs survey short form 34-item (SCNS-SF34) measures. RESULTS: HRQOL or satisfaction with care scale scores explained 41%, 45%, 40% and 22% of variance in, respectively, psychological, physical/daily living needs, information/health system, and care/support needs (P < 0.001). BC patients' education level, having children, hospital service attendance, and anxiety/depression levels significantly predicted differences in psychological needs relative to corresponding difficulties (adjusted R(2) = 0.11). Medical history and anxiety/depression levels significantly predicted differences in information/health system needs relative to degrees of satisfaction with doctors, nurses, or radiotherapy technicians and general satisfaction (adjusted R(2) = 0.12). Unmet needs were most prevalent in the psychological domains across hospital services. CONCLUSIONS: Assessment of needs, HRQOL, and satisfaction with care highlights the subgroups of BC patients requiring better supportive care targeting.

Customer Focus Newsleter, January/February, 2008, Vol. 5, no. 1

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsletter, March/April, 2008, Vol. 5, no. 2

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsletter, July/August, 2008, Vol. 5, no. 4

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsletter, May/June, 2008, Vol. 5, no. 3

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Proving the performance of a new revenue management system

Revenue management (RM) is a complicated business process that can best be described ascontrol of sales (using prices, restrictions, or capacity), usually using software as a tool to aiddecisions. RM software can play a mere informative role, supplying analysts with formatted andsummarized data who use it to make control decisions (setting a price or allocating capacity fora price point), or, play a deeper role, automating the decisions process completely, at the otherextreme. The RM models and algorithms in the academic literature by and large concentrateon the latter, completely automated, level of functionality.A firm considering using a new RM model or RM system needs to evaluate its performance.Academic papers justify the performance of their models using simulations, where customerbooking requests are simulated according to some process and model, and the revenue perfor-mance of the algorithm compared to an alternate set of algorithms. Such simulations, whilean accepted part of the academic literature, and indeed providing research insight, often lackcredibility with management. Even methodologically, they are usually awed, as the simula-tions only test \within-model" performance, and say nothing as to the appropriateness of themodel in the first place. Even simulations that test against alternate models or competition arelimited by their inherent necessity on fixing some model as the universe for their testing. Theseproblems are exacerbated with RM models that attempt to model customer purchase behav-ior or competition, as the right models for competitive actions or customer purchases remainsomewhat of a mystery, or at least with no consensus on their validity.How then to validate a model? Putting it another way, we want to show that a particularmodel or algorithm is the cause of a certain improvement to the RM process compared to theexisting process. We take care to emphasize that we want to prove the said model as the causeof performance, and to compare against a (incumbent) process rather than against an alternatemodel.In this paper we describe a \live" testing experiment that we conducted at Iberia Airlineson a set of flights. A set of competing algorithms control a set of flights during adjacentweeks, and their behavior and results are observed over a relatively long period of time (9months). In parallel, a group of control flights were managed using the traditional mix of manualand algorithmic control (incumbent system). Such \sandbox" testing, while common at manylarge internet search and e-commerce companies is relatively rare in the revenue managementarea. Sandbox testing has an undisputable model of customer behavior but the experimentaldesign and analysis of results is less clear. In this paper we describe the philosophy behind theexperiment, the organizational challenges, the design and setup of the experiment, and outlinethe analysis of the results. This paper is a complement to a (more technical) related paper thatdescribes the econometrics and statistical analysis of the results.

Customer Focus Newsletter, September/October, 2008, Vol. 5, no. 5

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsletter, November-December, 2008, Vol. 5, no.

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsletter, January-February, 2009, Vol. 6, no.1

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Ownership structure, customer satisfaction and brand equity

This paper studies the interaction between ownership structure, taken as a proxy for shareholders commitment, and customer satisfaction - the main driver of consumer loyalty - and their impact on a firm s brand equity. The results show that customer satisfaction has a positive direct effect on brand equity but an indirect negative one because of reductions in ownership concentration. This latter effect emerges when managers are mainly customer-oriented. Such result gives out a warning signal that highlights the perverse effect of implementing policies, focused excessively on satisfying customers at the expense of shareholders, on a firm s brand equity. The empirical analysis uses an incomplete panel data comprising 69 firms from 11 nations, for the period 2002-2005.