Sanford, Donald G.

This study was designed to determine what the areas of conflict were
in the relationships between sales and production personnel in companies
who are members of the Composite Can and Tube Institute. A
questionnaire consisting of three parts was used to gather data. The
first part consisted of thirty modified Likert Scale questions to
measure the respondents' feelings toward items reflective of typical
industrial situations. The second part incorporated the respondents'
value rankings of Rokeach-Clare-Sanford terminal and instrumental
values and their perceived value rankings of relevant other people in
their job environments. The third part involved certain demographic
information about the respondents and that relationship to conflict
areas. Chi-square and the Spearman Coefficient were used in analyzing
the results.

This study attempts to explain the motivation for a voluntary financial gift
through the analysis of individual value systems. Contributors and non-contributors to a fraternal association are compared by value rankings.
Certain socioeconomic information was also collected and compared. It
is anticipated that the study will be a base of information for more detailed
study into the complex field of motivation to contribute financially to
not-for-profit organizations.

This thesis uses the Dynamo Language and Modeling Techniques to show the
effects of unpredictable delays on manufacturing facilities using a job
shop production strategy. These delays affect productivity in that they
cause increased work-in-process inventories and underutilized resources.
Two models are developed, a macro model treating the plant floor as an
entity and a micro model which shows the day-to-day operation of four
work centers. The same basic assumptions are made in each model so the
results may be used to complement each other.

This is a study of intraurban rail rapid transit
systems in relation to possible implications for an urban
area over a period of 250 years. Two digital computer
simulation models using the DYNAMO computer language are
integrated to explore the results of assumed relationships
between intraurban rail rapid transit usage and an urban
area under highly pure conditions that are also assumed.
One computer simulation model is developed for use as a
rail rapid transit sector with Forrester's urban model and
is then integrated with the urban model as a sector.
The conclusions reached in the study are related
to the simulation results and state that an intraurban rail
rapid transit system may serve as a catalyst for an urban
area's revival under conditions where it is used in place
of automobiles to a high degree. However, it is also concluded
that the rail transit usage may need to be accompanied
by other specific policies in order to produce any tangible
long run changes in the urban area equilibrium conditions.

This thesis was prepared as an introductory text in business systems
simulation using the General Purpose Simulation System/360 computer
programming language. The material requires no background in computer
programming or simulation. A knowledge of elementary probability and
statistics and a course in operations research would be prerequisites.
A number of examples illustrate an approach to simulation problems
and the use of the computer language.

The research questions of this study were: (1) Can non-randomness
be identified in the movement of commodity futures prices which would indicate
that the random walk theory is not fully applicable? (2) What model or models demonstrate this non-randomness? and (3) Are characteristics
of non-randomness uniformly present in different commodity types?
A data base of commodity futures price history was assembled
covering wheat, corn, oats, and soybeans. Considering the four commodity
types and the various delivery months for each commodity, a total of 215
years of price history was available. The historical data was used to test two methods of technical
analysis: (1) a moving average model and (2) a seasonal model. The models
simulate on a digital computer various decision rules in trading commodity
futures using the price history data as input. The models were evaluated
by comparing the resulting net profits from trading against the net profit
from a simple buy-and-hold policy.
Moving average and seasonal strategies were found which would
produce more profitable results than the buy-and-hold strategy. The moving
average model produced best results with wheat and corn. Oats showed the
poorest results and soybeans was in an intermediate position. Oats,
however, was the only commodity of the four tested which exhibited consistently better results using the seasonal model compared to the moving
average model.
Recommendations were made on areas of possible further study based
on the research results.