No description available.

Thesis. 1977. Ph.D.--Massachusetts Institute of Technology. Alfred P. Sloan School of Management. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY. / Includes bibliographical references. / Ph.D.

Photocopy of typescript. / Digitized by Kansas Correctional Industries

Digitized by Kansas Correctional Industries

by Tang Shui-yan. / Bibliography: leaves 92-103 / Thesis (M.Ph.)--Chinese University of Hong Kong, 1984

published_or_final_version / Public Administration / Master / Master of Public Administration

Thesis submitted to the Faculty of Commerce, Law and Management, University of the Witwatersrand, in partial fulfilment of the requirements for the Degree of Master of Management in the Field of Public Policy April 2017 / The study examined the legal framework establishing Kampala Capital City Authority (KCCA) as well as actor interactions within the agency policy process, with an ultimate aim of ascertaining the extent of public decision-making. The study was structured around three main components: an in-depth investigation of the literature on agencification; an application of the institutionalism theoretical framework; and an applied case study approach to examine the extent and context of policy decision making within KCCA. The major finding and indeed central argument is that despite the creation of a central policy-making role enshrined in the law establishing KCCA, the policy outcomes are not influenced by the elected leaders but rather by the central government and as such, there is limited public decision-making. This study has empirically shown that the creation of a matrix agency structure with multiple reporting and accountability centres was a symbolic move intended to dupe elected leaders with superficial status and authority, but in essence, without any real powers to demand policy changes, let alone, be able to sanction bureaucrats for their actions or inaction. The study further affirms that bureaucrats managing KCCA affairs, to a great extent, not only play a policy implementation function, but also disproportionately influence the shape of policy as a consequence of the discretionary powers bestowed upon them by the KCC Act (2010). The paper concludes by highlighting that agencification as one of the new public management (NPM) approaches has increased institutional and policy complexities that alienate citizens and citizen groups from the decision-making process. This reality challenges the existing literature on agencification and New Public Management which claims that once we structurally disaggregate and create semi-independent agencies, then we see bureaucrats who are more accountable to citizens. / MT 2017

No description available.

Public policy and program implementation has come to be regarded as a significant problem area in the governance process. Research has provided insights but falls short of totally satisfactory prescriptions for operational success. The literature on policy and program implementation reflects a dichotomy of means between centralized control and delegation of substantial discretionary authority. The resulting theory leaves a gap with practice. Scenario writing is one of the techniques available to practitioners that might be employed to assist in the execution of their responsibilities. Scenarios can be useful tools, but their preparation is costly and time consuming. It was hypothesized that computer modeling techniques and artificial intelligence could be applied to scenario generation to create an effective, practical instrument to permit wider and more effective use of scenarios for planning and management. A computer supported procedure is presented for generating scenarios which describe alternative sequences of future events for a given situation and proposed policy. The generator design reflects a three-way compromise between processing flexibility, data-base structure, and user workload requirements. This prototype generator was subjected to exploratory trials. The lessons learned highlight some potentially valuable program improvements, the importance of focusing the scenario at a level useful to the reader, and the need for a common set of definitions. / Ph. D.

Thesis (MPA)--University of Stellenbosch, 2004. / ENGLISH ABSTRACT: The traditional skills required in government-wide local knowledge, sound political judgment and concern for the welfare of people-are still essential in the global information society. But, to be more effective, these skills now have to be supported by the new decision-making techniques of operations research and decision support systems. The capacity of the human mind to handle complex issues is limited. This situation of complexity and incapacity makes the application of operations research techniques and electronic DSS essential for good governance outcomes. Operations research is a multidisciplinary discipline that requires a team approach to decision making. It is based on systems analysis approach because of its preoccupation with interconnections among parts rather than within the parts themselves. This systems approach allows the optimization of an organization's overall goals, not just those of isolated departments. Optimization is one of the functions of operations research techniques. Linear programming models are most effective at the operational level of decision making with a single objective where scarce or limited resources must be allocated or used in an optimal manner. At the policy level where there are many uncertainties and conflicting objectives, multiobjective programming is more suitable. On the other hand, dynamic programming is flexible and is particularly applied whenever a sequence of decisions must be made and the goal is to find the combination of decisions that optimizes the overall effectiveness of the entire set of decisions. However, when a problem is too complex to be treated by numerical optimization techniques, simulation is used. That is when the problem either cannot be formulated for optimization, because the formulation is too large, there are too many interactions among the variables, or the problem is stochastic (probabilistic) in nature. Despite the analytical power of operations research, many real-world problems are not amenable to direct analytical solution by known mathematical techniques. Hence, in the absence of exact methods to solutions, we usually resort to heuristics, i.e. finding a good but not necessarily the best solution. Other problems encountered by public sector agencies include service stations (waiting lines), inventory levels, forecasting, and project scheduling, which all need decision support systems. To reduce the adverse impact of waiting to acceptable levels one has to minimize costs associated with providing service and those associated with waiting time. For smooth operations, inventory of goods must be kept to an acceptable level to minimize setup or ordering, inventory holding, and shortage (public complaints, and loss of good will and sales) costs. Forecasting is crucial as most managerial decisions are based on projected information and policy analysis is almost always about future outcomes. Many government policies and programs are implemented through projects. Project managers must know how long a specific project will take to finish, what the critical tasks are, and what the probability of completing the project within a given time span is. Successful applications of operations research and decision support systems in the public sector have been recorded including in the areas of the military, transportation, crime and justice, police units, energy, natural resources, facility location, and land use planning. However, operations research applications are not without impediments. Technical and institutional barriers are some of the problems encountered in the effort to apply operations research in the public sector. Similarly, reasons for the slow growth of decision support systems include lack of user demand, lack of system designer motivation, lack of system designer expertise, reluctance to change, and increased risk of failure In the Eritrean public sector, the low level of awareness of operations research and decision support systems is reflected in the inadequacy of addressing multicriteria decision processes, the lack and lor inappropriate selection of decision support systems, improper project management techniques, suboptimal facility locations and service stations, the low level of multidisciplinary approach, and the absence of national standards for pollution control. In general, constraints such as the lack of capacity, awareness, know-how, and software, are rampant. The study concludes that policy-making processes should incorporate opportunities to exercise choices and explore rational options. These rational options are the results of appropriate interface of human, operations research and decision support systems. / AFRIKAANSE OPSOMMING: Die tradisionele vaardighede wat van 'n regering verwag word - wye kennis van plaaslike omstandighede, goeie politieke oordeel en besorgdheid oor die welvaart van mense - was nog altyd belangrik in die moderne wêreld. Hierdie vaardighede moet egter ondersteun word deur die nuwe besluitnemingstegnieke van operasionele navorsing en besluitnemings ondersteuningstelsels om effektief te wees. Die vermoë van die menslike brein om komplekse kwessies te hanteer, is beperk. Hierdie situasie van kompleksheid aan die een kant en onvermoë aan die ander kant maak die aanwending van operasionele navorsingstegnieke en elektroniese besluitneming nodig vir goeie regeringsuitkomste. Operasionele navorsing is 'n multidisiplinêre disipline wat 'n spanbenadering tot besluitneming benodig. Dit is baseer op die sisteemanalise benadering omdat dit gaan oor interkonneksies tussen onderdele en nie soseer oor die onderdele self nie. Hierdie sisteembenadering maak die optimisering van die sisteem se oorhoofse doelwitte moontlik, nie net die doelwitte van geïsoleerde departemente nie Optimisasie is een van die funksies van operasionele navorsing. Liniêre programmeringsmodelle is meer effektief op die operasionele vlak van besluitneming met 'n enkel doelwit waar skaars of beperkte bronne toegewys of gebruik moet word op 'n optimale wyse. Op die beleidsvlak waar baie onsekerhede en botsende doelwitte voorkom, is multi-doelwit programmering meer geskik. Aan die ander kant is dinamiese programmering meer toepaslik en buigsaam, veral as dit toegepas word waar 'n reeks besluite geneem moet word en die doel is om 'n kombinasie van besluite te vind wat die oorhoofse effektiwiteit van die hele stel besluite optimiseer. Sekere probleme is egter te kompleks om met numeriese optimisering op te los, omdat die probleem nie geprogrammeer kan word vir optimisering nie, omdat die formulasie te groot is, daar te veel interaksies tussen die veranderlikes is, of die probleem stogasties van aard is. Dan kan simulasies oorweeg word om oplossings te probeer vind. Ten spyte van die analitiese krag van operasionele navorsing, kan baie werklike probleme nie direk deur analitiese wiskundige tegnieke opgelos word nie - altans nie deur bekende wiskundige tegnieke nie. As 'n presiese oplossing nie moontlik is nie, kan kan 'n heuristiese oplossing ondersoek word, d.w.s. 'n goeie, maar nie noodwendig die beste oplossing nie. Ander probleme wat deur die openbare sektor ondervind word, sluit in diensstasies, inventarisvlakke, voorspellings, en projekskedulering. Hulle benodig almal besluitnemingsstelsels vir effektiewe oplossings. Om die wagtydperk te verminder tot 'n aanvaarbare vlak moet die koste verbonde aan die verskaffing van die diens en die koste verbonde aan wagtydperke minirniseer word. Om 'n operasie glad te laat verloop moet die inventaris van goedere op 'n aanvaarbare vlak gehou word om die koste van bestellings, die byhou van voorrade en tekorte (klagtes van die publiek, die verlies aan vertroue en verkope) te minirniseer. Voorspelling is van die uiterste belang vir hierdie doel, omdat bestuursbesluite baseer is op geskatte syfers en beleidsontleding betrekking het op toekomstige uitkomste. Baie regeringsbeleide en -programme word deur projekte geïmplementeer. Projekbestuurders moet weet hoe lank dit sal neem om 'n projek te voltooi, wat die belangrike take is en hoe waarskynlik dit is dat die projek betyds voltooi sal word. Operasionele navorsing en besluitnemingsondersteuning stelsels is al suksesvol aangewend in die volgende openbare sektore: militêre funksies, vervoer, misdaad en justisie, die polisie, energie, natuurlike hulpbronne, en die beplanning van grondgebruik. Tegniese en ander hindernisse word egter soms ondervind by die gebruik van operasionele navorsingstegnieke in die openbare sektor. Redes hoekom die gebruik van sulke stelsels so stadig toeneem, sluit in die gebrek aan aanvraag van verbruikers, die gebrek aan stelselontwerp motivering, die gebrek aan stelselontwerp vaardighede, onwilligheid om te verander en die groter risiko van mislukking. In die openbare sektor van Eritrea word die lae vlak van bewustheid van operasionele navorsing en besluitnemingsondersteuning stelsels gereflekteer in 'n onvermoë om dit te gebruik, die gebrek aan of verkeerde keuse van sulke hulpmiddels, verkeerde bestuurstegnieke, suboptimale plasing van dienspunte, die afwesigheid van multi-disiplinêre benaderings, en die afwesigheid van nasionale standaarde vir die beheer van besoedeling. Beperkings soos 'n gebrek aan kapasiteit, bewustheid, kennis en sagteware kom algemeen voor. In hierdie studie word daar tot die gevolgtrekking gekom dat beleidmakende prosesse die geleentheid behoort in te sluit om keuses te maak en om verskillende opsies te toets. Hierdie rasionele opsies is die gevolg van die regte interaksie tussen die mens, operasionele navorsing en besluitnemingsondersteuning stelsels.