THFSlS IIHWWIIHIWI WI! llllill H W 1_2__9_3 10712 O374__7 MAAAA y?“ fihhjgm Sam 1 UWX‘] ' This is to certify that the thesis entitled A THEORETICAL ISOMORPHIC SYSTEMS APPROACH TO THE DESIGN OF A MODEL FOR MECHANIZATION OF AGRICULTURE FOR ADULTS presented by Hooshang Iravani has been accepted towards fulfillment of the requirements for Ph.D. Administration 6 degree in _ Higher Education Major professor d/M/ AW // Date 7-16-80 0-7639 OVERDUE FINES: 25¢ per day per item RETURNING LIBRARY MTERIALS: Place in book return to remve charge from circulation records {KI-mk- ‘» ‘_'f 2‘30 5/011: (is) 2-“ jwfiw A THEORETICAL ISOMORPHIC SYSTEMS APPROACH TO THE DESIGN OF A MODEL FOR MECHANIZATION OF AGRICULTURE FOR ADULTS BY Hooshang Iravani A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Administration and Higher Education 1980 ii <:) Copyright by HOOSHANG IRAVAN I 1980 ABSTRACT A THEORETICAL ISOMORPHIC SYSTEMS APPROACH TO THE DESIGN OF A MODEL FOR MECHANIZATION OF AGRICULTURE FOR ADULTS By Hooshang Iravani The main purpose of this study was to design a theoretical isomorphic system for mechanization of agriculture for adults, to be represented in conceptual-graphical models. The second purpose was to explore, identify, and describe a methodology for the design of such a system. The third purpose was to use Tel-Plan Computer Program 70 to develop a theoretical model budget for production of soybeans, wheat, and corn, based on average prices in Michigan. Systems approach, based on the application of General Systems Theory, was identified as a methodology to conduct this study. The study was creative library reference materials oriented, where the procedure was: (1) the identification of the problem; (2) the identification and definition of goals/objectives; (3) the preliminary collection of pertinent information and facts; (4) the use of systems approach to define a system for mechanization of agriculture; (5) the formulation of a preliminary model of the proposed system; (6) the statements of research Questions based on the applica- tion of General Systems Theory; (7) the review of pertinent literature and collecting facts; (8) the itemizing of inputs, throughputs, and Hooshang Iravani Aims in a theoretical isomorphic system for mechanization of agriculture were identified as: (l) establishing new mechanized farms, (2) providing on-the-job training, (3) financing the farms with reasonable monthly payments, (4) supervising for maintenance, (5) communicating about innovations, and (6) facilitating marketing. Inputs were identified as: (1) land, (2) capital, (3) machin- ery, (4) technology, (5) materials, (6) methods, (7) animals, (8) ideas, (9) personnel, (10) adults, (11) goals, (12) objectives, (13) seeds, (14) plants, (15) fertilizers, (l6) chemicals, (17) water, (18) time schedule, (19) priorities, (20) structure, (21) content, (22) learning aids, (23) facilities, (24) mechanized farms, (25) farm mangers, (26) buildings, (27) equipment, (28) tools, (29) products, (30) educa- tional technology, (31) extension methods, and (32) extension materials. Throughputs were identified as: (1) assessment, (2) diagnosis, (3) intervention, (4) development, (5) selection, (6) evaluation, (7) reporting, (8) recommendation, (9) implementation, (10) refinement, (ll) trial, (12) communication, (13) prediction, (l4) regulation, (15) preparation, (16) processing, (17) searching, (18) coordination, and (19) accountability. Outputs were identified as: (1) grain, (2) dairy, (3) poultry, (4) vegetables, (5) beef, (6) sheep, (7) agricultural products, (8) well maintained farms, (9) trained farm managers, (10) farm owners, and (11) farm income. Hooshang Iravani outputs; (9) the formative testing of the model, and (10) the development of conceptual-graphical models of the proposed system, using the creative approach. Conceptually, a system is defined as a set of interrelated, interdependent elements in continuous action, interaction, and trans- action within the system and with its environment, exchanging matter, energy, and information in the form of inputs, throughputs, outputs, and feedback. The system has both subsystems and suprasystems, characterized by supersummation, meaning that the whole is greater than the sum of its parts. Models are used to represent the patterns of a system. The conceptual model theory is characterized by four distinctive functions: (1) the organizing, (2) the heuristic, (3) the predictive, and (4) the mensurative. A dimension of evaluation of models is based on four factors: (1) the importance of a model's generality or organizing power, (2) the fruitfulness or heuristic value, (3) the significance of verifiable predictions which it yields, and (4) the accuracy of the operations of measurement that can be developed with its aid. Other characteristics of a good model include: (1) originality, (2) simplicity, and (3) realism. Specific objectives were to explore, identify, and describe aims, inputs, throughputs, outputs, feedback, constraints, boundaries, environment, etc., of a system for the Mechanization of Agriculture. Subsystems were identified as: (l) farm establishment, (2) training, (3) financing, (4) maintenance, (5) extension. and (6) marketing. Hooshang Iravani Constraints were predicted as lack of: (1) capital, (2) favorable agricultural policies, (3) necessary resources, (4) proper management, (5) proper skills, (6) time, (7) timing, (8) facilities, (9) machinery, (10) equipment, (11) communication channels, and (12) favorable environment. Linkages were identified with: (l) agricultural colleges, (2) ministry of agriculture, and (3) other remote resources specialized in agriculture and rural development. The Tel-Plan Computer Program 70 was employed to analyze the cost of the production of soybeans, wheat, and corn, based on 1979 Michigan prices. DEDICATION To my gathen Vahya liavani and my mothen Fahhaomofiuh AzanmL-Inavani 1980 iii ACKNOWLEDGMENTS I would like to extend special thanks to several people for their support and encouragement at various stages in the completion of this dissertation. I am grateful to Dr. Carroll H. Wamhoff, Director of the Agriculture and Natural Resources Education Institute, for having faith in my ability and for providing me with the necessary encouragement toward completion of the requirements. Appreciation is extended to Dr. Richard L. Featherstone for being the epitome of professionalism, and for providing practical guidance along with support and encouragement. Appreciation is also extended to Dr. James L. Page for his support, advice, and encouragement from the very beginning of the study and for his dedication to creativity based on individual interest and performance. A special thanks to Dr. S. J. Levine, Director of Programs in Adult and Continuing Education for his unfailing interest in observing the standards of professional study. iv TABLE OF CONTENTS Page LIST OF TABLES . LIST OF FIGURES CHAPTER I. PURPOSE, PROBLEM, THEORIES, LIMITATIONS, AND DEFINITION OF TERMS l Purposes of the Study 1 Introduction to the Problem 2 What Should Be Done? . 3 Accountability . . 5 Definition of a System . 7 The Systems Approach . 7 General Systems Theory . 7 Characteristics of General Systems Theory 8 Characteristics of Model Theory 9 Learning Theories . . . . . . . . . . . . . 9 Toward a Theory of Creativity . . . . . . . . . . . . . 13 Assumptions . . . . . . . . . . . . . . . . . . . . . . 15 Procedure . . . . . . . . . . . . . . . . . . . . . . . 16 Limitations . . . . . . . . . . . . . . . . . . . . 17 Operational Definitions . . . . . . . . . . . . . . . . 18 Overview of the Study . . . . . . . . . . . . . . . . . 24 II. REVIEW OF THE LITERATURE . . . . . . . . . . . . . . . . . 27 Introduction . . . . . . . . . . . . . . . . . . . . . . 27 Systems Thinking . . . . . . . . . . . . . . . . . . . . 28 Definition of a System . . . . . . . . . . . . . . . . . 30 Subsystems . . . . . . . . . . . . . . . . . . . . . 31 Boundary of a System . . . . . . . . . . . . . . . . . . 32 General Systems Theory . . . . . . . . . . . . . . . . . 35 Systems Constructs . . . . . . . . . . . . . . . . . . . 38 Throughputs . . . . . . . . . . . . . . . . . . . . . . 41 Outputs . . . . . . . . . . . . . . . . . . . . . . . . 42 Linkages . . . . . . . . . . . . . . . . . . . . . 42 Institutional Linkages . . . . . . . . . . . . . . . . . 43 Relationships and Attributes . . . . . . . . . . . . . . 44 Systems Approach . . . . . . . . . . . . . . . . . . . . 44 Chapter Page World of Models . . . . . . . . . . . . . . . . . . . . 48 Motivation for Modeling . . . . . . . . . . . . . . . . 53 Iconic Models . . . . . . . . . . . . . . . . . . . . . SS Analogue Models . . . . . . . . . . . . . . . . . . . . S6 Conceptual Models . . . . . . . . . . . . . . . . . . . 57 Graphic Models . . . . . . . . . . . . . . . . . . . . . 48 Symbolic Models . . . . . . . . . . . . . . . . . . . . 59 Use of Models . . . . . . . . . . . . . . . . . . . . . 60 Model Theory . . . . . . . . . . . . . . . . . . . 61 Disadvantages of Models . . . . . . . . . . . . . . . . 66 Behavioral Systems Design . . . . . . . . . . . . . . . 68 Toward a Theory of Experience . . . . . . . . . . . . . 71 Criteria of Experience . . . . . . . . . . . . . . . . . 72 Cooperative Extension Service . . . . . . . . . . . . . 75 Extension Worker's Creed . . . . . . . . . . . . . . . . 78 Demand for Technical Know-How . . . . . . . . . . . . . 80 Communication of Innovations . . . . . . . . . . . . . . 81 Characteristics of Change . . . . . . . . . . . . . . 83 Participants in the Change Process . . . . . . . . . . . 84 Types of Strategies . . . . . . . . . . . . . . . . 85 The Need for Adult Education . . . . . . . . . . . . . . 88 Views on Development . . . . . . . . . . . . . . . . . . 90 The Adult as a Learner . . . . . . . . . . . . . . . . 92 The Role of the Adult Educator . . . . . . . . . . 95 Principles Pertaining to the General Socio- Psychological Conditions for Effective Formal Instruction . . . . . . . . . . . . . 98 Principles Pertaining to Interactions . . . . . . . . . 98 Problems of Adult Education . . . . . . . . . . . . . . 101 Summary . . . . . . . . . . . . . . . . . . . . . . . . 102 III. DESIGN OF THE STUDY--SYSTEMS APPROACH BASED ON THE APPLICATION OF GENERAL SYSTEMS THEORY . . . . . . . . . 107 A Procedure for Systems Approach . . . . . . . . . . . . 107 Research Questions . . . . . . . . . . . . . . . . . . . 108 Assumptions . . . . . . 109 Application of the Procedure to the Design of a System for the Mechanization of Agriculture . . . . . 110 Tel-Plan Computer Program 70 . . . . . . . . . . . . . . 114 IV. SYSTEMS THINKING AND GENERAL SYSTEMS THEORY . . . . . . . 116 Systems Thinking . . . . . . . . . . . . . . . 116 A Definition of Systems Approach . . . . . . . . . . . . 117 General Systems Theory as a Methodology . . . . . . . . 118 Characteristics of General Systems Theory . . . . . . . 119 vi Chapter Page Conceptual Model Theory . . . . . . . . . . . . . . . . 126 Evaluations of Models . . . . . . . . . . . 127 A Diagrammatical Presentation of a System . . . . . . . 129 V. FUNCTIONAL APPLICATION OF GENERAL SYSTEMS THEORY TO THE MECHANIZATION OF AGRICULTURE . . . . . . . . . . . . 132 A Theoretical Isomorphic System for the Mechanization of Agriculture for Adults . . . . . . . 132 Goal . . . . . . . . . . . . . . . . . . . . . . . . 134 Linkage . . . . . . . . . . . . . . . . . . . . . . 134 Inputs . . . . . . . . . . . . . . . . . . . . . . . 13S Throughputs . . . . . . . . . . . . . . . . . . . . 135 Outputs . . . . . . . . . . . . . . . . . . . . . . 136 Feedback . . . . . . . . . . . . . . . . . . . . . . 136 Systems Boundary . . . . . . . . . . . . . . . . . . 137 Constraints . . . . . . . . . . . . . . . . . . . . 137 Environment . . . . . 137 Subsystem l--A Subsystem for the Mechanization of Agriculture for the Production of Soybeans, Wheat, and Corn . . . . . . . . . . . . . . . . . . . 138 Goal . . . . . . . . . . . . . . . . . . . . . . . . 138 Linkage . . . . . . . . . . . . . . . . . . . . . . 138 Inputs . . . . . . . . . . . . . . . . . . . . . . . 138 Throughputs . . . . . . . . . . . . . . . . . . . 140 Throughputs on a Farm . . . . . . . . . . . . . . . 140 Outputs . . . . . . . . . . . . . . . . . . . . . . 141 Constraints . . . . . . 141 Subsystem 2--The Subsystem for On- the- Job Training . . . 142 Goals . . . . . . . . . . . . . . . . . . . . . . . 142 Linkage . . . . . . . . . . . . . . . . . . . . . . 142 Inputs . . . . . . . . . . . . . . . . . . . . . . . 142 Throughputs . . . . . . . . . . . . . . . . . . . . 144 Outputs . . . . . . . . . . . . . . . . . . . . . . 144 Constraints . . . . . . . . . . . . . . . . . . . 144 Training Objectives . . . . . . . . . . . 144 Subsystem 3-—The Subsystem for Financing . . . . . . . . 147 Goals . . . . . . . . . . . . . . . . . . . . . . . 147 Linkage . . . . . . . . . . . . . . . . . . . . . . 147 Inputs . . . . . . . . . . . . . . . . . . . . . . . 147 Throughputs . . . . . . . . . . . . . . . . . . . . 149 Output . . . . . . . . . . . . . . . . . . . . . . . 149 Constraints . . . . . . . 149 Subsystem 4--The Subsystem for Proper Maintenance . . . 150 Goals . . . . . . . . . . . . . . . . . . . . . . . 150 Linkage . . . . . . . . . . . . . . . . . . . . . . 150 Inputs . . . . . . . . . . . . . . . . . . . . . . . 150 Throughputs . . . . . . . . . . . . . . . . . . . . 150 vii Chapter Outputs Constraints Objectives . . Subsystem 5--The Subsystem for Extension (Communication of Innovations) Goals Linkage Inputs . Throughputs Outputs Constraints Objectives . . . Subsystem 6--The Subsystem for Marketing . Goals . . . . . . . . . Linkages . Inputs . Throughputs Output . Constraints Discussion . . Theoretical Considerations and Assumptions . VI. CONCLUSIONS, IMPLICATIONS, DISCUSSION, AND RECOMMENDATIONS . . . . . . . Conclusions Implications . Discussion . Recommendations . . Management Goals and Objectives Appraisal Input Analysis . Throughput Analysis Output Analysis Attitude Analysis Appendix A. COST ANALYSIS FOR THE PRODUCTION OF CORN, WHEAT, AND SOYBEANS . . . . . . . . . . . . . . . . . B. PUBLICATIONS RELEVANT TO A SYSTEM FOR THE MECHANIZATION OF AGRICULTURE FOR ADULTS C. MANAGEMENT PROCESS . BIBLIOGRAPHY . RELATED BIBLIOGRAPHY . viii Page 152 152 152 153 153 153 155 155 155 155 156 157 157 157 157 159 159 159 159 159 164 164 168 171 172 172 173 173 174 174 176 185 202 212 LIST OF TABLES Total Farm Summary——Tel-Plan Computer Program 70 Schedule F Summary for Soybeans, Wheat, and Corn Enterprise Budget for Soybeans Sold, Medium Yield, 120 Acres . . . . . . . . . . . . . . . . . . . . Enterprise Budget for Corn Sold, Medium Yield, 120 Acres . . Enterprise Budget for Wheat Sold, Medium Yield, 120 Acres . Overhead Costs, Soybeans, 120 Acres . Overhead Costs, Wheat, 120 Acres Overhead Costs, Corn, 120 Acres . ix Page 176 177 179 180 181 182 183 184 .10 .11 LIST OF FIGURES The Organization, Its Resources and Its Environment Serial or In-Line Input Random Inputs Diversity of Models Diversity of Methods Used in Modeling Objectives of Modeling . The System, the Model, and the Real Phenomenon . Sample Definitions of Social Change Types of Social Change . Concepts in Communication of Innovations . Strategies for Communication of Innovations Evolution of a Successful Model A Diagrammatical Presentation of a System's Parameters, Boundary and Environment . A Conceptual-Graphical Model of a System for the Mechanization of Agriculture for Adults Subsystem l--A Conceptual-Graphical Model of the Subsystem for the Mechanization of Soybeans, Wheat, and Corn Subsystem 2--A Conceptual-Graphical Model of the Subsystem for Training . . . . . Subsystem 3—-A Conceptual-Graphical Model of the Subsystem for Financing . . . . Page 34 39 40 51 52 54 69 85 86 87 128 130 133 139 143 148 Figure Page 5.5 Subsystem 4--A Conceptual-Graphical Model of the Maintenance Subsystem . . . . . . . . . . . . . . . . 151 5.6 Subsystem 5--A Conceptual-Graphical Model of the Extension Subsystem . . . . . . . . . . . . . . . . . 154 5.7 Subsystem 6--A Conceptual-Graphical Model of the Marketing Subsystem . . . . . . . . . . . . . . . . . 158 C.1 A Diagram of the Management Process in a Three Dimensional Model . . . . . . . . . . . . . . . . . . 203 C.2 How Five Different Types of Managers Behave in Performing Basic Management Functions . . . . . . . . 205 C.3 The Instructional Development System . . . . . . . . . 208 C.4 A Functional Model . . . . . . . . . . . . . . . . . . 211 xi In the name 05 the Atmc'ghtzj, the Beneétcent, the Me/tctéut. mm: the aglulcufltahat 62.01504. with what tmp/Loves the conditions 05 its peopte. The tmpnovement 05 the tand and the con- Won 05 the game/us 0.5 an t'mpnouement to the nut 05 Isocx'ety which cannot truty pro/5pm Whoa/t the gum/1'15 phospe/u'tg. The Imam Att ABDOELUAHABELUAHEED xii CHAPTER I PURPOSE, PROBLEM, THEORIES, LIMITATIONS, AND DEFINITION OF TERMS The major thrust of this chapter is to present the reader with the following information: the purpose of the study, an introduction to the problem, and possible recommendations for the solution of the problem. This chapter also includes a brief discussion of some of the basic terms used in the paper such as: accountability, definition of a system, systems approach, General Systems Theory, characteristics of General Systems Theory, learning theories, working toward a theory of creativity, limitations, assumptions, procedure , operational defini- tions, and an overview of the study. Purposes of the Study The main purpose of this study is to design a theoretical isomorphic system for mechanization of agriculture for adults to be represented in conceptual-graphical models. The second purpose is to explore, identify and describe a methodology for designing such a system. The third purpose is to use the Tel-Plan Computer Program 70 to develop a theoretical cost model for production of soybeans, wheat, and corn, based on Michigan prices. Introduction to the Problem The world population at the present time is 4.2 billion, and the facts are: (1) population is increasing, and (2) poverty is increasing in spite of the world attention and awareness for solving the problem. Most indications point to 7 billion individuals living on earth by the year 2000. Three overwhelming and highly visible dangers are threat- ening the future of mankind: (1) nuclear warfare, (2) the population explosion, and (3) the hunger gap. They are imtimately related . . . life for more than two-thirds of 4.2 billion humans, on earth, is highly precarious. They are short of most of the necessities of life: food, water, shelter, fuel and metals. Available land for tillage and forestry is inadequate. In a few words: they exist in various degrees of poverty and misery. . . . All estimates and projections agree that there is little likelihood the globe will have fewer than 6 billion people by year 2000. Even this figure is predicted upon the assumption that some degree of success can be attained in current mea- sures to curb the population growth. This estimate is highly conjectural, and most indications point to 7 billion.‘ At the present time 30 to 35 percent of the world pOpulation is astonishingly poor, and 15 percent is starving. In other words, 50 percent or 2,100,000,000 individuals have incomes of less than 200 dollars per year. In an overview in alternatives for balancing world food production and needs, Brown indicates that: the food problem has been characterized as a race between food and people. In fact, it is a race between world food demand and population. Food shortages will continue over the years ahead as the population juggernaut continues to gain momentum in the less developed world, and as incomes 1George Borgstrom, Harvesting the Earth (New York: Abelard- Schuman, 1973), pp. 1 and 169. continue the rapid rise of recent years in the more advanced countries.1 The natural question arises as to what should be done to solve the problem and also to help people to learn to participate in the production processes. Possible recommendations for the solution of the problem might be as indicated in the following section. What Should Be Done? 1. More food must be produced to reduce starvation. This is only possible if mechanization of agriculture is introduced and successfully implemented. 2. Increased education must be provided for poor people in order to help them to help themselves. This calls for continuing adult education in all its forms. 3. Research must be increased, based on systems perspectives to design systems, strategies, and models in order to be imple- mented, evaluated, and held accountable for its success. Developing countries are very much impressed by the advancement of science, technology, industry, and agriculture in developed coun- tries, and fully see the value of development as destiny for better quality of life, but the development of a country does not just happen by accident. 1Lester R. Brown, Alternatives for Balancing World Food Production and Needs (Ames: The Iowa State University Press, 1967). Rodinelli points out that projects are the basic building blocks of development. Without successful project identification, preparation, and implementation, development plans are no more than wishes, and developing nations would remain stagnant or regress.1 Gerlach and Hines make a fine differentiation between two types of social change. They consider developmental social change and revolutionary social change with the following definitions: Developmental social change is change within an ongoing social system, adding to it or improving it, rather than replacing some of its key elements. Revolutionary social change is change that replaces existing goals with an entirely different set of goals, steering society in a very different direction.2 It is valuable to point out the application of these two definitions to the fields of Extension, Adult Education, and Mech- anization. If the intention in a given developing country is to develop existing cultural practices, we are indeed aiming at devel- opmental social change, where non-systematic approaches can be of value in being designed and implemented, in order to improve and develop local practices. But, if the intention is to introduce new methods and replace the old cultural practices, then our aim is revolutionary social change, and one can assume that only systematic 1Denis A. Rodinelli, "Why Development Projects Fail, Problems of Project Management in Developing Countries," Project Management Quarterly, March 1976, p. 10. 2Garlach and Hines, in Strategies for Planned Change, ed. G. Zaltman and R. Duncan (New York: John Wiley 8 Sons, Inc., 1977), p. 8. approaches to change would lead to success for differentiation, reintegration, and adaptation of the introduced innovation. Accountability The request for accountability in the sense of holding the rural development systems responsible for the successful achievement of improving rural areas in developing countries is crucial and must be considered. The concept of accountability in a system for mechanization of agriculture has several primary concerns: (1) the responsibility of the Mechanization Enterprise to provide a mechanized base for agricultural productions, (2) the provision of programs which will effectively develop the human potential for management of mechanized farms in a wide variety of agricultural products, (3) the responsi- bility of the enterprise to efficiently utilize the various resources available, and (4) the responsibility for optimal attainment of objectives and goals. Lopez indicates that: accountability refers to the process of expecting each member of an organization to answer to someone for doing specific things according to specific plans and against certain timetables to accomplish tangible performance results. It assumes that everyone who joins an organi- zation does so presumably to help in the achievement of its purposes; it assumes that individual behavior, which contributes to these purposes, is functional and that which does not, is dysfunctional. Accountability is intended, therefore, to insure that the behavior of 1 every member of an organization is largely functional. 1M. Felix Lopez, Accountability in Education in Emerging Patterns of Administrative Accountability, ed. Lesley H. Browder, Jr. (New York: McCutcheon Publishing Co., ), p. 197. Cunningham points out that accountability and evaluation are not synonymous. Accountability is dependent upon evaluation, obviously, but it is a broader concept. The accountability responsibility extends beyond appraisal; it includes informing constituents about the per- formance of the enterprise. Similarly, it implies responding to feedback.1 Lovett constructs the following questions for viewing accountability within a system: 1. Who is accountable? 2. To whom is he accountable? 3. For what is he responsible? 4. What if it does not work?2 Alkin defines accountability in the following manner: "Accountability means (1) a negotiated relationship, (2) designed to produce increased productivity, (3) in which the participants agree in advance to accept specified rewards and costs, (4) on the basis of evaluation findings on the attainment of specified ends."3 1L. Luvern Cunningham,"0ur Accountability Problems," in Accountability in American Education, ed. Frank J. Sciara and Richard J. Kantz (Boston: Allyn and Bacon, Inc., 1972), p. 78. 2Robert Lovett, "Professional Accountability in Schools,” in Accountability in American Education, ed. Frank J. Sciara and Richard J. Kantz (Boston: Allyn and Bacon, Inc., 1972), p. 129. 3Marvin C. Alkin, Accountability, A State, A Process or a Product?" ed. Gephart J. William (New York: Phi Delta Kappa, Inc., 1975), p. 24. Definition of a System According to Hall and Hagen, a system is a set of objects together with relationships between the objects and their attributes. 0 Objects are simply the parts of components of a system, and these parts are unlimited in variety. 0 Attributes are properties of objects. 0 Relationships are those that "tie the system together.” It is, in fact, these relationships that make the notion of "system" useful.1 The Systems Approach The systems approach is a methodology aiming at the under- standing of the totality of a phenomena in order to explain the viable parts and their interrelationships. According to Schoderbek et al., the systems approach is a Gestalt type of approach, attempting to view the whole with all its interrelated and interdependent parts in interaction. The systems oriented researcher employs the holistic method. This approach forces him to acquire an adequate knowledge of the whole before he proceeds to an accurate knowledge of the workings of its parts.2 General Systems Theory Bertalanffy postulated a new discipline called General Systems Theory. The subject matter of General Systems Theory is the formulation and derivation of those principles which are valid for "systems" in general. He states that, 1A. D. Hall and R. E. Hagen, "Definition of a System," in Organizations, Systems, Control and Adaptation, ed. Joseph A. Litterer (New York: John Wiley 8 Sons, Inc., 1969), p. 31. 2Peter P. Schoderbek et al., Management Systems Conceptual Consideration, Business Publications, Inc., 1975, p. 13. there exists models, principles, and laws that apply to generalized systems or their subclasses, irrespective of their particular kind, the nature of their component ele- ments, and the relations or 'forces' between them. It seems legitimate to ask for a theory, not of systems of a more or less special kind, but of universal principles applying to systems in general.1 According to Boulding, General Systems Theory is the label given to describe a level of theoretical model-building which lies somewhere between the highly generalized constructions of pure mathe- matics and the specific theories of specialized disciplines.2 Immegart and Pilecki, in regard to General Systems Theory, state that, General Systems Theory, as first set forth by Bertalanffy, forms 'the skeleton of a science,‘ and seeks to integrate all of the sciences within a common conceptual framework using uniform and systematically derive terminology. Of interest to General Systems scholars are the nature of systems, the universality of systems properties and states, and the generalization of scientific findings from one kind of system to another. The perspective and methodology of this emphasis ranges from the purely descriptive to the most rigorous of mathematical formulations. The dynamics, functions, development, and composition of systems are studied to generate further research as well as a universal scientific theory.3 Characteristics of General Systems Theory According to a number of systems theorists, characteristics of General Systems Theory are: (l) interrelationship and interdependence 1Ludwig Von Bertalanffy, General System Theopy Foundations, Development Applications (New York: George Braziller, 1968), p. 32. 2Kenneth E. Boulding, General Systems Theory, The Skeleton of Science in Management Systems, ed. Peter P. Schoderbek (New York: John Wiley 8 Sons, Inc., 1967), p. 7. 3Glenn L. Immegart and Francis J. Pilecki, An Introduction to Systems for Educational Administrator (Reading, Mass.: Addison Wesley Publications, 1973), p. 9. of objects, attributes, events and the like, (2) holism, (3) goal seeking, (4) inputs, (5) throughputs, (6) outputs, (7) entropy, (8) negentropy, (9) regulation, (10) hierarchy, (11) differentiation, (12) equifinality, (l3) existence in time and space, (14) boundaries, (15) environment, (16) dynamic interaction, (17) structure, (18) pro- gressive mechanization.1 Characteristics of the Model Theory According to Deutsch, characteristics of the model theory are four distinct functions: (1) the organizing, (2) the heuristic, (3) the predictive, and (4) the mensurative. Learning Theories Some of the most prevalent learning theories are stated by John Dewey, B. F. Skinner, Jerome S. Brunner, Jean Piaget, and Robert M. Gagne. Dewey, in his theory of experience, states that educative experience in a certain sense, is an experience that does something to prepare a person for later experience of a deeper and more expansive quality, and that is the very meaning of growth, continuity, and 1For example, Ludwig Von Vertalanffy, General Systems Theory Foundations, Development, Applications (New York: George Braziller, 1968); Kenneth T. Berrion, General and Social Systems (New Bruswick, N.J.: Rutgers University Press, 1968); G. J. Miller, "Living Systems, Basic Concepts," Behavioral Science, July 1965, pp. 193-234; and Ervin Laszlo, The Systems View of the World (New York: Braziller, 1972), p. 11. 2Karl W. Deutsch, The Evaluation of Models in Management Systems, ed. Peter P. Schoderbek (New York: John Wiley 8 Sons, Inc., 1967), p. 338. 10 reconstruction of experience. He further states that the experiential continuum, experiential interaction, and value judgment of experience are important to consider.1 The experiential continuum is characterized in the Dictionary of Education as a series of ongoing experiences with the following conditions: (a) the present experience gains meaning from and enhances the meaning of previous experiences, (b) the present experience is a potential for more enriching future experience, and (c) thinking occurs within and following the experience which reconstructs the individual's value and alters the direction of future experiences.2 Experiential continuum expresses the first chief principle for interpreting an educative experience. According to Dewey, all human experiences are ultimately social, in the sense that they involve contact and communication. The word interaction expresses the second chief principle for interpreting an experience in its educational function and force. . . . Every experience is a moving force. Its value can be judged only on its ground of what it moves toward, and into. Each experience of the learner can be evaluated in a way in which the one having the less mature experience cannot do.3 Continuous reconstruction of experience for physical, intel- lectual and moral development should be a concern in regard to the outcome of the education process. 1John Dewey, Experience and Education (New York: Collier Macmillan Publishers, 1977), p. 47. 2Carter V. Good, ed., Dictionary of Education (New York: McGraw-Hill Book Co., 1973), p. 227. 3Dewey, pp. 42 and 43. 11 Skinner believed that an individual enters this world without any knowledge and experience. It was his theory that learning is achieved within and from the environment; therefore, a person should be rewarded for his correct responses. When a person accumulates enough experiences in the environment, he is ready to learn. Pro- grammed instruction should be provided for learners, whereby they can work at their own rate.1 Bruner stated the hypothesis that any subject can be taught effectively in some intellectually honest form to any child at any stage of development. To put it into other words, the desired content should be offered in terms that the learner can comprehend.2 Gagne believed in a hierarchy of skills. As one masters or gains a mastery of more difficult skills, he becomes motivated. The mastery of the difficult tasks becomes a source of satisfaction for a learner, and this generates a desire for improvement.3 Piaget believed in stages of development. The major factors in cognitive deveIOpment are the interaction of maturation, experience, social interactions, and equilibration. The implication of Piaget's theory for educators is that curriculum sequences should be designed with the student's cognitive status in mind. If curricula does not 1F. B. Skinner, Beyond Freedom and Dignity (New York: Random House, 1971). 2Jerome S. Bruner, The Process of Education (New York: Random House, 1960). 3Robert M. Gagne, The Conditions of Learning (New York: Holt, Rinehart 6 Winston, Inc., 1970), pp. 83, 237-276. 12 consider the student's levels of conceptual development, learning will be ineffective.1 Bloom indicates that the cognitive domain is characterized by the following stages: 0 Knowledge--Primarily recall, requires the learner to store information and to remember it at a later time. 0 Comprehension--Understanding the literal message contained in a communication, basic understanding, does not require seeing fullest implications. - Application--Using abstractions in concrete situations, will use the abstraction correctly even though no mode of solution is specified. - Analysis--Breakdown of a function into constituent parts, intended to clarify a communication, to indicate how the communication is organized, and the way in which it manages to convey its effects, as well as its basis and arrangement. - Sypthesis--Putting together elements so as to form a whole, arranging and combining elements in such a way as to constitute a pattern or structure not clearly there before. 0 Evaluation--Judgments about the value of materials or methods, quantitative or qualitative judgments about the extent to which material and methods satisfy criteria.2 The Gestalt theory of learning originated in GermanyiJithe early twentieth century; introduced into the United States in the 19205, it defines learning as the reorganization of the learner's perceptual or 1Barry Wadsworth, Piaget's Theory of Cognitive Development (New York: David McKay Co., Inc., 1971). 2Benjamin S. Bloom et a1. Taxonomy of Educational Objectives, Handbook 1: Cognitive Domain (New York: David McKay Co., 1956), pp. 190-193. psychological world.1 Gestalt is a term designating an undivided articulate whole that cannot be made up by the mere addition of independent elements, the nature of each element depending on its relationship to the whole. As a theory of perception, it places stress upon structural unity, the wholeness by which consciousness gives order to experience.2 Toward a Theory of Creativity A creative approach to understanding a system for mechanization of agriculture also has important implications for this kind of study. Most researchers, in the area of creativity, have pointed out the need for ideation and reconceptualization as relevant to understanding a phenomena, that which seems to have no previous pattern of recognition. According to Muller, the creator is he who defies existing notions in search of the unknown. The creator has an unexplainable faith in change and the fact of originality. Whether an artist or a scientist, the creator searches for skeletons in the cupboard, areas where loose ends exist, need for change.3 Rogers has identified a significant relationship existing between the creative individual and his openness to experience, operation at a level of evaluation and ability to reorganize concepts. 1Carter V. Good, ed., Dictionary of Education (New York: McGraw—Hill Book Co., 1973), p. 333. 2Ibid., p. 261. 3Robert E. Muller, Inventivity, How Man Creates in Art and Science (New York: The John Day Co., 1963), p. 81. 14 He has given emphasis to qualities that are characteristic of a potentially creative person. 1. Openness to experience: ”extensionality." This is the opposite of psychological defensiveness, when to protect the organization of the self certain experiences are prevented from coming into awareness except in distorted fashion. In a person who is open to experience, each stimulus is freely relayed through the nervous system, without being distorted by any process of defensiveness. . . . This means that instead of perceiving in predeter- mined categories, the individual is aware of the existen- tial moment as it is, thus being alive to many experiences which fall outside the usual categories. An internal locus of evaluation. Perhaps the most funda- mental condition of creativity is that the source or locus of evaluative judgment is internal. The value of his product is, for the creative person, established not by the praise or criticism of others, but by himself. Have I created something satisfying to me? Does it express a part of me--my feeling or my thought, my pain or my ecstasy? These are the only questions which really matter to the creative person, or to any person when he is being creative. The ability to toy with elements and concepts. . . Associated with the openness and lack of rigidity is the ability to play spontaneously with ideas, colors, shapes, relationships--to juggle elements into impossible juxta- position, to shape wild hypotheses, to make the given problematic, to express the ridiculous, to translate from one form to another, to transform into improbable equivalents. It is from this spontaneous toying and exploration that there arises the hunch, the creative seeing of life in a new and significant way. 1 Intuition, imagination, visualization, supporting some experience or observation provides potential for creativity. Barnes has indicated that, 1C. R. Rogers, "Towards a Theory of Creativity," in Creativity and Its Cultivation, ed. H. H. Anderson (New York: Harper 8 Brofhers, 1959), pp. 75-76. 15 it is when we think or describe an event, that we fill in the gaps between a series of otherwise disconnected sense- impressions with an imagined continuity . . . to observe-- to take notice of—-is in some measure to experience, and observation, therefore, implies imagination. No knowledge is possible without an act of synthesis on the part of the knower, some kind of putting together, the imagining of a relationship--there can be no such thing as a "mere” observation, a passive mind receiving an imprint. We bring something of ourselves to the discrimination of the most trivial object in the outside world.1 The very meaning of creativity implies that one is willing to break from a traditional point of view, and to rearrange or reorganize symbols and concepts in order to solve a problem.2 It seems logical to assume that a creative approach, along with a systems approach based on the application of General Systems Theory, facilitates the process of understanding the nature of a theoretical isomorphic system for mechanization of agriculture for adults. In an attempt to eliminate much of the ambiguity presently associated with mechanization of agriculture in developing countries, this study is concerned with a systems approach based on an application of General Systems Theory to design a theoretical isomorphic system, to be represented in conceptual-graphical models. Assumptions 1. A general systems perspective provides conceptual links between relevant disciplines to mechanization of agriculture by pre— senting professionals with a common language, unrestricted to subject 1Kenneth C. Barnes, The Creative Imagination (London: Swathmore College Press, 1960), p. 9. 2H. H. Anderson, ed., Creativity and Its Cultivation (New York: Harper 8 Brothers, 1959), p. 23. 16 matter boundaries, thus allowing for meaningful dialogue in the midst of increasing specialization and fragmentation of knowledge. This aspect is important for the mechanization of agriculture, since supporting services such as training, supervision, maintenance, financing, extension, and marketing are important in a system for mechanization of agriculture. 2. A general systems perspective permits the organization of a vast number of theories, and concepts into a meaningful framework as a basis for making planning judgment. This aspect is very important for developing countries, where national planning for development has taken momentum in recent years. 3. A general systems perspective, with its focus on systems inputs, throughputs, and outputs facilitates a process orientation to mechanization, training, supervision, marketing, and extension, which is dynamic and applicable in a wide variety of food production. Procedure The following steps are identified for conduting this study. For further understanding of the procedure, the publications listed in footnote are recommended.1 1. Identification of the problem. 2. Identification and definition of goals, objectives. 1Harry H. Goode and Robert E. Machole, Systems Engineering (New York: McGraw-Hill Book Co., 1957), pp. 305-306; P. P. Schoderbek et a1. Management Systems Conceptual Considerations, Business Publica- tions, Inc., 1975, pp. 237-263; and V. Vemuri, Modeling of Complex Systems, An Introduction (New York: Academic Press, 1978), p. 9. 17 3. Preliminary collection of pertinent information and data. 4. Defining a system (systems approach). 5. Identifying the structure of the model. 6. Statements of research questions based on an application of General Systems Theory (GST). 7. Reviewing pertinent literature and collecting relevant facts. 8. Itemizing inputs, throughputs, and outputs. 9. Formative testing of the model. 10. Developing a conceptual-graphical model (creative approach). Limitations The GST makes use of the process of analogy. One must keep in mind that analogizing is a very tempting but a potentially dangerous enterprise. Therefore, the usual dangers are inherent in the use of GST application to the mechanization of agriculture for adults. Systems, when represented in models, are subject to the dangers typi- cally inherent in abstraction, where important factors may be left out, and less important factors being given higher priorities. There is no guarantee that investment of time and effort in constructing a model will pay dividends in the form of satisfactory results. The model designer may become so devoted to his model that he may insist that this model is the real world. The study is at macro level, and the scope of the system to be simulated and visualized and studied is so wide that exhaustive efforts are needed to conceptualize a system for mechanization of agriculture to be represented in models. 18 The system designer is not expert in all the related fields which contributes to the totality of a system for mechanization of agriculture for adults and, therefore, some important factors for success of such a system may have been overlooked. The maximum strength of a chain is equal to the weakest part of a chain. This also applies to a system; the maximum strength in the performance of a system is equal to the weakest performance of a subsystem within the system. This indicates another limitation of a system in that if a subsystem is not doing its job it has an effect on the total system, and if a subsystem is poorly designed, it will weaken the results of the overall system design. Operational Definitionsl AccommodatLMIis a sytem-environment interaction or process by which the environment satisfies the changing requirements of the system. Adaptive systems are capable of adjusting themselves to meet changing requirements. Adjustment is a systems-environment interaction or process by which the system responds to the changing requirements of its environment. Adjustments are changes brought about within a system in order to modify its behavior, structure, and characteristics, so that it can produce improved system output or system state. 1See, for example, Bela H. Banathy, Developing a Systems View of Education, Lear Siegler, Inc., 1973, where these operational definitions are being quoted; and Carter V. Good, ed., Dictionary of Education (New York: McGraw-Hill Book Co., 1973), p. 16. 19 Adnlp is a person who has come into that stage of life in which he has assumed responsibility for himself and usually for others. Boundaries of a system delimit the system space and set aside from the environment all those entities that make up the system. Components are integral parts of a system, selected on the basis of their potential to carry out functions required for the achievement of the system's goal. Constraints are known limitations or restrictions imposed upon a system that curtail resources or operations. Entity is a definable element of a system. Environment is the context within which a system exists. It is composed of all the things that surround the system, and it includes everything that may affect the system and that may be affected by the system. Feedback is a process by which information concerning the state of the output and the operation of the system is introduced into a system. Feedback and adjustment provide for the analysis and interpretation of information about the assessment of the output and the operation of the system. This information is used for introducing adjustments into the system in order to bring about more adequate output and improved system Operations. Functions are activities that have to be carried out in order to achieve the goal of the system. General system functions are functions that are characteristic of systems in general. 20 General systems research identifies elements that are common to systems in general, and it develops and tests models that represent systems in general. General Systems Theory presents concepts, principles, and models that are common to systems in general, and it identifies structural similarities between systems. Goal seeking is a characteristic of systems by which they are directed toward the achievement of goals. Hierarchical relationship is one in which one subsystem is superior to others. Inpp£_includes information, people, energies, and materials that enter into the system from the environment. It is also the process by which such entry occurs. Input processing refers to operations that provide for (l) the interaction between the system and its environment, (2) the identification of systems-relevant input, and (3) the intro- duction of system-relevant input into the system. Interdependence of components within a system means that change in one component brings about changes in others. Model may be (1) a representation or abstraction of a real system or (2) a theoretical projection or display of a possible system. Model building is the strategy by which a conceptual representation of a system or a solution is constructed and from which specified outcomes can be determined. 21 Model theoretical isomorphic is a theoretical model which maintains the existence of one-to-one correspondence between the con- cepts and assumptions of the theoretical model and the observed world; the relationships in each also take the same form. Multisystem is a complex of several related systems. 9p 2 refers to a state in which a system is continuously interacting and interchanging with its environment. Output is whatever the system produces and sends back into its environment. Patterned relationships are connections between the components of a system. These relationships make up the interactive functions that components carry out by design and that display the structure of the system. Peer systems are related systems that make up a larger system. Progressive integration fuses the components of a system into increasingly more wholeness. Resources are information, people, materials, money or other means that are at the disposal of a system. Self-regulating systems are able to modify their own behavior in order to enhance the production of the desired output. Social systems are adaptive and complex systems composed of casually related components. The interrelationship of the components constitutes the structure of social systems and provides for their wholeness. 22 Subject (of a system) is the entity around which the system is organized and which has to be transformed by the system from an input state to a specified output state. Subsystem is a component part of a system. It is made up of two or more components. With a goal of its own, it interacts with its peer subsystems, in order to achieve the overall goal of the system. Suprasystem is a system that is made up of a number of component systems. Svstem 15 an 1nteract1ng group of ent1t1es forming an organlzed whole. System concept refers to an aspect of systems, such as "input" or "transformation." System control is a process by which the system regulates itself or by which the behavior of the system is regulated. System design aims at the construction of a model or a "blueprint" of a system to be developed. System development involves the formulation, testing, revision, and validation of a system. System-environment coactions are processes by which the system adjusts to the changing requirements of its environment, and the environment accommodates to the changing requirements of the system. System requirements are the specific demands and conditions that the system is to satisfy. 23 System space is the domain that the system occupies as defined by its boundaries. Systemization is a transformation process by which components of Systems a system are fused and become increasingly more system-like. models organize and present in a scheme, system concepts and Systems principles. operations are components of the major systems processes of Systems inputs, transformation, output, and feedback and adjustment. principles are constructed from related system concepts. Systems They display the laws that regulate and describe systems. For example, the more complex the input, the more complex the system. research studies the structure, organization, and behavior Systems of systems, and it develops and tests generalizations derived from such studies. theory presents concepts, principles, and models that describe Systems the structure, organization, and behavior of systems. thinking is thinking that is influenced and guided by systems Systems concepts, principles, and models. view develops as systems concepts, principles, and models become integrated into one's own thinking. Transformation is the process by which the input is changed into output. 24 Transformation control and adjustment are operations whereby transformation is monitored. The information gathered through monitoring is analyzed and interpreted in order to introduce adjustments by which to improve transformation. Wholeness (of system) refers to the integrated, fused state of the components of a system by which the system becomes indivisible. Overview of the Study Chapter I includes an overview of: the purpose of the study, the significance of the problem, suggestions on what should be done, accountability, the definition of a system, systems approach, General Systems Theory, model theory, some learning theories, a theory of creativity, limitations, assumptions, procedure, and operational definitions. In Chapter II, the review of relevant literature to development of a theoretical isomorphic system-for mechanization of agriculture for adults is presented. Topics of concern in this chapter include: system sciences, system thinking, definition of a system, open system, sub- systems, boundary of a system, General Systems Theory, systems con- structs, linkages, relationships, environment of a system, a modern systems approach, world of models, definition of a model, taxonomy of model types, motivation for modeling, theoretical models, physical models, analogue models, conceptual models, graphic models, symbolic models, use of the models, model theory, disadvantages of model design, systems approach and modeling, behavioral systems design, a theory of 25 experience,cooperative extension service, communication of innovation, demand for technical know-how, adult education, the adult as a learner, the role of adult educators, assumptions in non-formal adult education, and principles for guiding formal adult instruction. In Chapter III, the design of the study is presented. This chapter is concerned with systems thinking, a definition of systems approach, General Systems Theory as a methodology, characteristics of General Systems Theory, interrelatedness and interdependence of objects, attributes and events, holism, goal seeking, inputs, through- puts, outputs, negentropy, entropy, regulation, hierarchy, suprasystem, differentiation, equifinality, boundaries, environment, feedback, model theory, evaluation of models, evolution of a successful model, a diagrammatical presentation of a system, assumptions, research questions, procedure, Tel-Plan Computer Program 70. In Chapter IV, the results of the study are presented, including: (1) a conceptual-graphical model of a system for mech- anization of agriculture in general; (2) a conceptual-graphical model of a system for mechanization of soybeans, wheat, and corn; (3) a conceptual-graphical model of a training subsystem; (4) a conceptual- graphical model of a financing subsystem; (5) a conceptual-graphical model of a supervision subsystem; (6) a conceptual-graphical model of extension subsystem; and (7) a conceptual-graphical model of a marketing subsystem. Aims, linkages, inputs, throughputs, outputs, feedback, boundary, constraints, and environment are given extraordinary attention. 26 In Chapter V, conclusions, implications, discussion, and recommendations are presented. The study is a design to develop a theoretical isomorphic system for the mechanization of agriculture for adults, to be repre- sented in conceptual-graphical models, for bringing into focus, ideas and methods suggested by numerous educational and agricultural mech- anization researchers, scientists, and innovators, for providing a conceptual link between relevant disciplines to the mechanization of agriculture, and for presenting professionals with a common language, unrestricted by subject matter boundaries, thus allowing for meaningful dialogue in viewing the mechanization of agriculture in its totality. CHAPTER II REVIEW OF THE LITERATURE In this chapter, the major thrust is to consider the review of the literature pertinent to the design of a system and the development of a model based on the systems approach and General Systems Theory. This review is concerned with topics such as system thinking, definition of a system, subsystems, boundary, environment of a system, General Systems Theory, characteristics of General Systems Theory (GST), linkages, relationships, systems approach, world of models, diversity of models, motivation for modeling, types of models, conceptual model theory, advantages and disadvantages of models, systems approach and modeling, behavioral system design, a theory of experience, cooperative extension service, communication of innovations, types of strategies, the need for adult education, views of development, the adult as a learner, and the role of the adult educator. Introduction A system is a set of interrelated interdependent elements in continuous action, interaction, and transaction within the system and with its environment, exchanging matter, energy, and information in the forms of inputs, throughputs, outputs, and feedback. The system has both a subsystem and a suprasystem, characterized by supersummation, meaning the whole is greater than the sum of its parts. 27 28 According to Schoderbek et al., System sciences represent a direction in the intellectual universe that has changed the general frame of reference, resulting in viewing physical and social phenomena as systems, i.e., organized complexities that exhibit (1) organization, (2) wholeness, (3) openness, (4) self-regulation, and (S) teleology.1 According to Immegart and Pilecki, the major approaches to systems thinking are the following: "(1) general systems theory, (2) cybernetics, (3) holism, (4) operations research, (5) systems design, (6) information theory, (7) systems analysis, (8) systems engineering, (9) output analysis, (10) mathematical programming, and (11) computer science."2 Systems Thinking As it has been defined in the Dictionary of Education, A system is the structure of an orderly whole, showing interrelationships and interrelatedness of the parts to each other and to the whole itself. . . . Thinking is an unregulated flow of ideas or stream of images, impressions, recollections, and hopes.3 Therefore, systems thinking is that activity of the mind aiming at the comprehension of the system's patterns which can be identified within the context of a totality or a phenomena. 1Peter P. Schoderbek et al., Management Systems Conceptual Consideration, Business Publications, Inc., 1975. 2Glenn L. Immegart and Francis J. Pilecki, An Introduction to Systems for Educational Administrator (Reading, Mass.: Addison- Wesley Publications, 1973). 3Carter V. Good, ed., Dictionary of Education (New York: McGraw-Hill Book Co., 1973), pp. 580 and 608. 29 According to Schoderbek et al., the main objective of systems thinking is to reverse the subdivision of the sciences into smaller and more highly specialized disciplines, through an interdisciplinary synthesis of existing scientific knowledge. He states that the world of the systems thinker is based upon four major pillars: l. Organicism, i.e., the philosophy of putting the organism at the center of one's conceptual scheme. 2. Holism, in viewing phenomena as organisms that exhibit order, openness, self regulation, and teleology (goal- directiveness), one focuses on the whole rather than the parts. 3. Modeling, instead of breaking the whole into arbitrary parts, one attempts to map his conception of the real phenomena onto the real phenomena. This can be done by abstracting from the real phenomena those characteristics that are relevant, and by disregarding those features of the real phenomena that are not needed for the explanation or predicted of the system's behavior. 4. Understanding, i.e., realizing (a) that life in an orga- nismic system is an ongoing process, (b) that one gains knowledge of the whole, not by observing the parts, but by observing the processes taking place within the whole, and (c) that what is observed is not reality itself, but rather the observer's conception of reality.1 The systems oriented researcher, therefore, is aiming at an adequate knowledge of the whole, rather than an accurate knowledge for the totality of a given phenomena. The latter is an ideal he can never hope to achieve. Systems thinking is a more meaningful way of under- standing and approaching the study of complex organized wholes.2 1Peter P. Schoderbek et al., Management Systems Conceptual Considerations, Business Publications, Inc., 1975, p. 8. 2Ibid. 30 Definition of a System A system is here defined as: "a set of objects together with relationships between the objects and between their attributes, con— nected or related to each other and to their environment in such a ”1 In order to reduce the manner as to form an entirety or yhplp, vagueness inherent in this definition, the terms set, objects, attri- butes, relationships, environment, and whole, will be explained. Set means any collection of objects which need have no common property, other than that of belonging to a set.2 Objects are simply the parts of components of a system, and these parts are unlimited in variety. Attributes are properties of objects. Relationships to which we refer are those that "tie the system together." It is, in fact, these rela- tionships that make the notion of "system” useful.3 Environment is everything which is outside of the system's boundary. Environment, then, is contingent on the definition of the system and may vary as the system's boundary varies.” The whole in a universe, a phenomena, a situation, and a problem, constitutes all relevant entities and subentities which are viable and the interrelated parts, conducive to the totality of the given phenomena. 1This is a commonly accepted definition. See, for example, A. D. Hall and R. E. Hagen, "Definition of System," in Organizations, Systems, Control and Adaptation, ed. Joseph A. Litterer (New York: John Wiley a Sons, Inc., 1969), p. 31; and S. Optner, Systems Analysis for Industrial and Business Problem Solving (Englewood Cliffs, N.J.: Prentice-Hall, Inc., 1965). 2Carter V. Good, Dictionary of Education, p. 530. 3Hall and Hagen, p. 31. “Immegart and Pilecki, p. 36. 31 According to Leadley and Pignone, a system is a distribution of members in a dimensional domain. A system is, roughly speaking, a bundle of relationships. A system is an organized or complex whole. A system is a configuration of components interconnected for purposes according to a plan. In other words, when a number of activities take place, such that each activity directly or indirectly is related to at least some other activity or activities in a seemingly more or less stable way within a specified period of time, we say we have a system. With respect to what constitutes a system, Bertalanffy had the following comments: A system is a model of general nature; that is, a con- ceptual analog of certain rather universal traits of observed entities. A system may be defined as a set of elements standing in interaction among themselves and with the environment.2 Buckley, Bertalanffy, and other system theorists hold the same concept that in an open system there is interchange of matter, information, and energy between the system and the environment.3 Subsystems Any given system can be divided into subsystems. In other words, every system is an entity composed of subentities, which are 1S. M. Leadley and M. M. Pignone, eds., Systems Analysis for Rural Community Services (Washington, D.C.: Cooperative State Research Service (DOA), ED 110262, 29 July 1972, p. 5. 2Ludwig Von Bertalanffy, Perspectives on General Systems Theory (New York: George Braziller, 1975), p. 159. 3W. Buckley, Sociology and Modern Systems Theory (Englewood Cliffs, N.J.: Prentice-Hall, 1967); and Ludwig Von Vertalanffy, Perspectives on General System's Theory, p. 39. 32 interrelated and interdependent within the context of its boundary. According to Hall and Hagen, objects belonging to one subsystem may well be consid- ered as part of the environment of another subsystem. Bertalanffy refers to the property hierarchical order of systems. This is simply the partition of system into subsystems. Alternatively, we may say that the elements of a system may themselves be systems of a lower order.1 Boundary of a System The purpose of the boundary of a system is to delimit whatever is within the system from whatever is outside the system, in order to control the rate of exchange of matter, energy, and information which is needed as input to the system. According to Miller, "Boundary is a region where energy and information exchange is significantly less than inside or outside the system."2 According to Leadley and Pignone, one of the most important concepts in the systems thinking is that the burden is on the observer to define the system and determine a boundary for that system. He states that, the determination of and the extent of a system depends solely upon the observer and his ability to make order of perceived matter and energy in a universe. What this is saying is that there is no a priori system out there. By definition or assumption, everything in the universe is 1A. D. Hall and R. E. Hagen, "Definition of System," in Organizations, Systems, Control and Adaptation, ed. Joseph A. Litterer (New York: John Wiley 8 Sons, Inc., 1969), p. 34. 2James G. Miller, "Toward a General Theory for Behavioral Sciences," in Opganizations, Systems, Control, and Adaptation, ed. Joseph A. Litterer (New York: John Wiley 8 Sons, Inc., 1969). interrelated. The design of a system depends on our ability to determine the number of activities, objects, relationships, and span of time.1 Hall and Hagen, in regard to delimitation of a system from its environment, make the following observation: One may have the natural question of when an object belongs to a system and when it belongs to the environment; for, if an object reacts with a system in the way described, should it not be considered a part of the system? The answer is by no means definite. In a sense, a system, together with its environment, makes up the universe of all things of interest in a given context. Subdivision of this universe into two sets, system and environment, can be done in many ways which are, in fact, quite arbitrary.2 According to Banathy, systems exist in their environment, from which they are set apart by their boundaries. Some systems are rather closed and are isolated from their environment by their boundaries. However, at this time we are considering systems that are somewhat open, systems that have breaks in their boundaries, enabling exchange with their environment through input- output interactions. Systems of this kind are adaptive. They maintain compatibility by adjusting to the demands and expectancies of their environment. This adjustment is made possible through self-regulating feedback control, which activates changes in order to ensure that the system output will be acceptable to the environment. Figure 2.3 attempts to further clarify the relationship between a system and its environment, in regard to what constitutes a system of production, and how it is related to the factors of 1S. M. Leadley and M. M. Pignone, eds. Systems Analysis for Rural Community Services (Washington, D.C.: Cooperative State Research Service (DOA), ED 110262, 29 July 1972, p. 6. 2Hall and Hagen, "Definition of System," p. 33. 3Bela H. Banathy, Developing a Systems View of Education. The Systems Model Approach, Lear Siegler, Inc., 1973. 34 .mv .m «Emma ..No no «mcamfiocom "moszow .ucoscogfl>:m mum can moop36mom mu~ .coflumuflcmwpo oze ~.m ogsmfim u:oE:0Hw>:m one mpoufiuomsou _ ofifinsm Hmwocoo .................................. xmogoccoob A ‘ I I I I I I I l I l I I I l l l I I l I I & Succeed b muzauzo maouucou xomnvoom 4—-———————----—-———-——-+ u:oE:po>oo xmodoom mommoooum ----------------------Dn-n-wwwwwwwwwwwm.wmwuu musmzfl _ acoEQwacm can flagpopmz gonna . “ muoEOHmsu 1 ................................ L production, within the environment. There are three categories of factors: (1) relatively high controllable, (2) semi-controllable, and (3) low controllable. As can be seen in Figure 2.1, Schoderbek et al. have indicated that, the four major inputs of the organization, that is, the so—called major factors of production (labor, material and equipment, capital, and land) are relatively highly controllable by the organization. On the other hand, the degree of control of the four major external factors depicted in the right-hand side of Figure 2.1 (ecology, government, general public, and competitors), is very low. These are, therefore, the organization's major environmental factors. Between these two extremes of the largely controllable factors (resources) and the largely uncontrollable variables (environment), lie two additional sets of factors which are relatively less controllable than resources but relatively more controllable than environment. These factors are consumers and technology.1 General Systems Theory General Systems Theory is a theory aiming at universal properties applicable to systems in general. It is an orderly arrangement of general truths drawn from experience. Bertalanffy states that, its task is to study general system characteristics and to concentrate on those aspects of reality which are inacces- sible to conventional scientific treatment, organization, hierarchy, differentiation, competition, finality, and equifinality--these are some of the concepts in question.2 1Peter P. Schoderbek et al., Management Systems Conceptual Considerations, Business Publications, Inc., 1975, p. 42. 2Ludwig Von Bertalanffy, Perspectives on General Systems Theory (New York: George Braziller, 1975), p. 122. 36 Mann advanced the notion that in terms of the General Systems Theory, a school can be recognized as a system, since it has the fol- lowing six elements, which all systems have: (1) sets of interrelated objects, (2) an environment, (3) inputs, (4) process, (5) output, and (6) feedback. He further stated that component subsystems are generally utilized to regulate the responses of open systems to the demands of the environment.1 Authors, Bertalanffy, Buckley, and Mann, advanced the concept of equifinality as a principle of the General Systems Theory. Buckley further indicated that within the General Systems Theory, there inheres also the concept of multifinality.2 According to Mann, the concepts of equifinality and multifinal- ity are fundamental to systems approach research, and the underlying principle of these concepts may be stated accordingly, in the following manner: "Different initial conditions lead to similar end effects, or similar initial conditions lead to different end effects."3 In a philosophical mode, Bertalanffy stated that, isomorphic structured uniformities can be sensitized from the total observable events of different levels. Thus, speaking in what has been called the "formal" mode, i.e., looking at the conceptual constructs of science, this means structural uniformities of the schemes we are applying. Speaking in "material" language, it means 1D. Mann, Policy Decision Making in Education (New York: Teachers College Press, 1975). 2Ludwig Von Bertalanffy, The Relevance of General Systems Theory (New York: George Braziller, 1972), p. 122; W. Buckley, Sociology and Modern Systems Theory (Englewood Cliffs, N.J.: Prentice Hall, 1967; and Mann. 3Mann, p. 78. 37 that the world, i.e., total observable events, show structured uniformities manifesting themselves by iso- morphic traces of order in different levels of realms.1 Bertalanffy also indicates that, the goal of General Systems Theory is clearly circumscribed. It aims at a general theory of wholeness, of entire systems in which many variables interact and in which their orga- nization produces strong interactions. It does not deal with isolated processes, with relations between two or few variables or with linear causal relations. These are the domain of classical science.2 The characteristics attributed to General System Theory by the systems theorist are: (l) interrelationship and interdependence of objects, attributes, events and the like, (2) holism, (3) goal seeking, (4) inputs and outputs, (5) transformation, (6) entropy, (7) regulation, (8) hierarchy, (9) differentiation, (10) equifinality.3 Kaufman, commenting on the goals of the General Systems Theory, indicated that, the technique enables a continuous identification of the elements which are feasible for the solution of the problem. The information provided is pertinent, insofar as it indi- cates what must be undertaken, thus providing a data base of suitable alternatives to be utilized in system synthesis where specific determinations are made. Therefore, the use of systems approach virtually eliminates the possibility of solutions being introduced before the problem has been identified.“ 1Ludwig Von Bertalanffy, General Systems Theory (New York: George Braziller, 1968), pp. 48-49. 2Ludwig Von Bertalanffy, Pegppectives on General System's Theory (New York: George Braziller, 1975), p. 122. 3Joseph A. Litterer, Organizations, Systems, Control, and Adaptation (New York: John Wiley 8 Sons, Inc., 1969), pp. 3-6. l’R. A. Kaufman, "A Systems Approach to Education--Derivation and Definition," A. V. Communication Review, 1968, p. 421. 38 Sy§tems Constructs It will be of value to further define objects, inputs, throughputs, input-output linkage, relationships, attributes, environment of a system. Objects are the components of a system. From the static viewpoint, the objects of a system would be the parts of which the system consists. From the functional viewpoint, however, a system's objects are the basic functions performed by the system's parts. Thus, the objects of a system are: the input(s), the process(es), the out- put(s), and the feedback control.1 According to Schoderbek et al., inpppg to a system may be matter, energy, humans, or simply information. Inputs may vary from raw materials to specific tasks performed by people. Inputs can be of different kinds: (1) serial, (2) random, and (3) feedback inputs. Serial input is the result of a previous system with which the focal system (system in question) is serially or directly related. They present little problem to the researcher because their absence would be felt immediately as the lack of movement in the system. Figure 2.2 is a graphical presentation of serial or in—line input. Random inputs are the most interesting kind of inputs for any researcher or observer to study. The reason for this is that their presence or absence is not as conspicuous as in the case of serial inputs: they usually affect the degree of operation of a system (i.e., its efficiency). Figure 2.3 is a graphical presentation of random inputs where the focal system is the purchasing subsystem of 1Schoderbek et al., p. 32. The Sales Subsystem Input >Process‘ .L———————d The Production Subsystem Process A Output Feedback Input I Figure 2.2 Serial or In-Line Input. Source: Schoderbek et al., 1975, p. 33. Available Suppliers FLO S I H I 1 4 (I) L'fllc “I 0| v F-—- Source: 40 I = Input = Process 0 = Output The Purchasing Subsystem .L. J Feedback Figure 2.3 Random Inputs. Schoderbek et al., 1975, p. 34. To Another System 41 an organization. Its purpose is to secure the inputs (i.e., raw material, office supplies, machines) necessary for the transformation process. The left hand side of the graph (Figure 2.3) represents the available sources of these inputs. The purchasing subsystem depicted in the right-hand side of the graph is faced with the decision of choosing one or more of the available outputs, which will become the inputs to the production process. This decision situation is represented in the graph by a question mark inside the diamond. For example, the purchasing department will design a list of preferences, on the basis of the purchasing subsystem's knowledge of the specifica- tions and the quality, timeliness, and general past experience of the production department with the potential suppliers. These preferences will reflect the purchasing department's satisfaction with each one of the suppliers in the form of the likelihood of choosing one or more of them.1 Feedback input represents only a very small portion of the system's output. This portion is identified as the difference between a desired state of affairs (i.e., a goal) and the actual performance (Ap) thus, Goal - Ap = id. Throughputs Throughputs are processes which transform the input to an output. As such, it may be a machine, an individual, a computer, a chemical or equipment, tasks performed by members of the organization, 1Schoderbek et al., pp. 32-36. 42 and so on. In the transformation of inputs into outputs, we must always know how this transformation takes place, for the purpose of planning and higher efficiency. Outputs Outputs are the results which a system produces after inputs are processed, according to the throughputs which are functioning within the context of a given system. Outputs can be (1) serial, (2) recycle, and (3) waste. Schoderbek et al. have indicated that, Outputs like inputs, may take the form of products, services, information such as a computer printout, or energy, such as the output of a hydroelectric plant. Outputs are the results of the operation of the process, or alternatively, the purpose for which the system exists. Serial output is output which is directly consumed by other systems. The main output of a business manufacturing firm, for instance, is sold to the customers for either consumption or further processing. Recycle output is the portion of the output which is consumed by the same system in the next production cycle. Defective products of a manufacturing process, for example, are usually reintroduced into the same production process. Waste output is the portion of the total output which is consumed neither by other systems nor by the system itself, but rather, is disposed of as waste which enters the ecological system as an input. Linkages According to Immegart and Pilecki, to ensure most functional output, attention must be given to input-output linkage or to the processing of input variables. In open systems, inputs are linked to, or processed into, outputs by the structures and processes of these systems. These structures and processes are appropriately conceived as functional subsystems. As such, subsystems 1Schoderbek et al., p. 36. 43 are input-output processing systems in and of themselves, but as linked in functional activity they are the compo- nents of the larger system, of which they are a part. As noted earlier, open systems operate and maintain themselves through the functional interplay and interrelationship of their subsystems. . . . Whenever more than one subsystem is utilized in processing system work, a functional linkage between the subsystems (beyond individual subsystem functionality) is necessary.1 Institutional Linkages Axinn has identified four kinds of institutional linkages: (l) enabling, (2) functional, (3) normative, and (4) diffuse. Enabling linkaggg provide authority to operate and access to essential resources. Enabling linkages may also be used to protect the organization against attack and to guarantee its access to resources during the critical period, when it is developing its capabilities but is not yet strong enough to deal with its external environment on its own terms. Functional linkages provide the needed input into the organization and take away its output. This category of linkages includes relations with those institutions which are the real or potential competitors, which perform or seek to perform similar functions and services. Normative 1inkagg§_provide relationships with other organizations which share overlapping interests in the objectives or the methods of the institution. These may be reinforcing or hostile. A faculty of agriculture at a university might have normative linkage with an agri- cultural research institute which has similar personnel, and which, from time to time, shares the same problems. Diffuse linkagg§_are relationships with individuals or groups who are not organized in a formal organization, but who do influence the standing of the institution it- self. An example of this might be the farm population served by a faculty of agriculture. 1Glenn L. Immegart and Francis J. Pilecki, An Introduction to Systems for Educational Administrators (Reading, Mass.: Addison-Wesley Publication Co., 1973), pp. 90, 92. 2H. George Axinn, New Strategies for Rural Development, Rural Life Associates, 1978, p. 160. 44 Thus, systems linkages should be given attention, and proper linkages between relevant social systems must be encouraged and provided. For example, in the case of agricultural development, social systems, such as agricultural colleges, ministry of agriculture, ministry of education, can contribute to success of a new proposed system. Relationships and Attributes According to Schoderbek et al., Relationships are the bonds that link the objects together. In complex systems, in which each object or parameter is a subsystem, relationships link these subsystems together. Relationships can be symbiotic, synergistic, and redundant. Symbiotic relationships are those in which the connected systems cannot continue to function alone. Synergistic relationshipp are those in which the cooperative action of semi-independent subsystems taken together, produces a total output greater than the sums of their outputs taken independently. Redundant relationships are those that duplicate other relationships. The reason for having redundancy is reli- ability. Redundant relationships increase the probability that a system will operate all of the time and not just some of the time. Attributes are properties of objects and of relationships. Attributes are of two general kinds: defining and accompanying. Defining attributes are those without which an entity would not be designated or defined as it is. Accompanying attributes are those whose presence or absence would not make any difference with respect to the use of the term describing it.1 Systems Approach Sensitivity to the totality, the wholeness, of a given phenomena, situation, or problem is the fundamental aim of systems 1Schoderbek et al., pp. 37-38. 45 approach in order to promote understanding and explanation of whatever constitutes an organized complexity. According to Rudner, it is an ideal of science to organize the disjointed concepts related to a phenomena, to be represented in an orderly fashion. He states that, system is no mere adornment of science, it is the very heart. To say this is not merely to assert that it is not the business of science to heap up unrelated, haphazard, disconnected bits of information, but to point out that it is an ideal of science to give an organized account of the universe-—to fit together in logical relations the concepts and statements embodying whatever knowledge has been acquired. Such organization is, in fact, a necessary condition for the accomplishments of two of science's chief functions: explanation and production.1 According to Schoderbek et al., Organizations come into existence, change, and disappear and the man's role is basically that of a controller, a steerman of the structure, the function, and the evolution of these organizations. To fulfill that role, he needs a logically consistent and generalizable set of concepts which will make intelligible the changing structure and behavior of organizations, as well as, their effective control. The general philosophical and conceptual predisposi- tion underlying modern systems thinking is "organicism." Organicism is the philosophy or viewpoint that puts the organism at the center of one's conceptual scheme. The term "organicism" has often been replaced by the term ”organized complexities" or "organized systems," defined as entities composed of many subentities which are inter- related and interconnected with respect to each other and, more importantly, with respect to their environment and to the whole.2 In an attempt to understand the totality of a given phenomenon or organized complexity, the systems oriented researcher employs a 1Richard S. Rudner, "An Introduction to Simplicity,” Philosophy of Science 28 (1961): 112. 2Schoderbek et al., p. 116. 46 holistic method based on systems principles, in order to acquire an adequate knowledge of the whole before he proceeds to an accurate knowledge of the workings of its parts. Chinal has summarized the following about the teachable contents of the systems approach, which can be seen at three levels of formalization, those of principles, methods, and techniques. 1. Principles 0 Conduct analysis and design while constantly keeping in view the system as a whole. 0 Assume a priori existence of internal relationships between elements, subsystems, and external relation- ships with the system environment. Be ready for unexpected or latent relationships, other than those suggested by routine, experience, plain common sense and intuition. ' Give explicit recognition to assumptions or axioms influencing system design. Beware of hidden assumptions left out as a result of mental inertia or blurred on purpose to hide deficiencies. Subject them to mental experiments to avoid omitting important assumptions which would be belatedly revealed by technological or managerial crises. 2. Methods . Methods or procedures express in relatively normative style the best known rules of the art, available, feasible, and applicable to the nature of the problem. 3. Technigues - Select those techniques which are the most typically systems oriented in that they relate behavior of complex structures to those of the elements and to the existing interactions.1 1Jean P. Chinal, "The Systems Approach: A French Experience,” Interfaces 5 (February 1975): The Institute of Management Sciences. 47 The major problems, which are the focus of the systems approach, are summarized by Buckley: Wholes and how to deal with them as such; the general analysis of organization--the complex and the dynamic relations of parts, especially when the parts are them- selves complex and changing and the relationships are non-rigid, symbolically mediated, often circular, and with many degrees of freedom; problems of intimate inter- change with an environment, of goal seeking, of continual elaboration and creation of structure, or more or less, adaptive evolution; the mechanic of ”control," of self regulation or self—direction.1 Krippendorff argues that, systems approaches provide a methodology for dealing, not with one communication link at a time, but with a large number of them simultaneously; not with binary relations among a single sender and a single receiver of information, but with many-valued and dynamic depen- dencies among a possibly large number of communicators; not with one-way processes of communication, but with interaction and with circular flows.2 Buckley stated: Modern systems approach aims to replace the older, analytic, atomic Laplacian technique with a more holistic orientation to the problem of complex organizations.3 In short, the approach attempts to examine the "whole” by identifying and studying the interrelated interdependent system's components instead of its separate parts. Thus, the system is treated within 1W. Buckley, Sociology and Modern Systems Theory (Englewood Cliffs, N.J.: Prentice-Hall, 1967). 2K. Krippendorff, Scope of the Information Systems Division, ed. 0. R. Monge, Systems Letter, 1972, p. 1. 3Buckley, p. 38. 48 the context of a flexible structure in relation to inputs, processes, outputs, and feedbacks. World of Models Models are abstracts of a system which retain those charac- teristics of the system which are relevant and viable. A model helps scientists to understand and communicate the totality of a system within the abstracted frame of reference. Authors McFarland, Rudwick, Massie and Douglas, Haynes and Henry, Morris, Albanese, and Buffa have defined models, respectively, as follows: 1. A model is a way of representing a situation or set of conditions so that behavior within it can be explained. Understanding, prediction, and control are enhanced in the real situation if it can be explained in terms of the model.1 2. A model can be defined as an explicit representation of some phenomenon or problem area of interest, in- cluding the various factors of interest and their relationship, and is used to predict the outcome of actions. Thus, a model is some analog or imitation of a real world. Note that this definition is a rather broad one, and so includes both qualitative and quanti- tative models.2 3. Models are simply defined as abstractions of real-world situations.3 1Dalton E. McFarland, Management Principles and Practices, 2nd ed. (New York: The Macmillan Co., 1974), p. 201. 2Bernard H. Rudwick, Systems Analysis for Effective Planning: Principles and Cases (New York: John Wiley 8 Sons, Inc., 1973), pp. 48-49. 3Joseph L. Massie and John Douglas, Managing; A Contemporary Iptroduction (Englewood Cliffs, N.J.: Prentice-Hall, 1977), p. 257. 49 Models are abstractions from reality that capture important relationships, allowing the analyst to understand, explain, and predict. The purpose of a model is to represent characteristics of a real system in a way that is simple enough to understand and manipulate, and yet similar enough to the more complicated operating system that satisfactory results are obtained when the model is used in decision making.1 By the broadest possible definition of the notion, a model is an attempt to impose a conceptual order on the perceptual confusion in which experience first comes to us. Everybody works with schemes for organi- zing the data of experience, but these schemes must be made explicit, their vagueness reduced to the point where they can be written down and expressed in a language that allows one to talk about them and teach them. As has been suggested, it is not entirely neces- sary that all the concepts in a model be operational in a strict sense. It is necessary, however, that the model produce some predictions both varifiable and interesting in the context of a management decision.2 A model is an abstraction of reality. Its purpose is to improve understanding and/or prediction of the reality. Modeling is a valuable managerial skill. Its essence is in abstracting only those components of reality that are important to the model's purpose. Models are invariably abstractions to some degree of the actual systems for which we wish to predict per- formance. A prominent example is the aerodynamicist's model used in conjunction with wind tunnels. Since the individual is primarily interested in aerodynamic per- formance, shape is the main characteristic of concern, and other factors in flight, such as weight, strength of individual parts, etc., are ignored.“ 1Warren W. Haynes and William R. Henry, Managerial Economics Analysis and Cases, Business Publications, 1978, pp. 12-13. 2William T. Morris, Management Science in Action (Homewood, Richard D. Irwin, Inc., 1963). 3Robert Albanese, Management Toward Accountability for Performance (Homewood, 111.: TRichard D. Irwin, Inc., 1975). I‘Elwood S. Buffa, Models for Production and Operation Management (New York: John Wiley & Sons, Inc., 1963), p. 9. 50 According to Bertalanffy, a theoretical model is a conceptual construction, reflecting in a clear simplification manner, certain aspects of a natural phenomenon and permitting deductions and predictions which may be tested. In a wider sense, any scientific theory may be regarded as a conceptual model. In a narrower sense, a model is an auxiliary concept illustrating certain relations and facilitating working with them. And here, we may distinguish with Nagel, two types of the theoretical models. Substantive models relate elements of the system under investigation to corresponding similar elements in a known system. In formal models, the component parts are different, but their laws possess a similar formal structure. According to Vemuri, there are great and viable differences between theories and models. A theory could state that the subject matter has a structure, but it is a well conceived model that reveals the structure. A model can be constructed as a specific form of a theory. A model is a representation of a system, it is the interpretation that a scientist gives to observed regu- larities and facts. One should keep in mind that facts remain unchanged, but models change. . . . In a descrip- tive model the attempt is to describe an observed, organized complexity or regularity, without necessarily seeking recourse to an explanation for the observation made. Description is the first stage of rationalization, generalization, and theory building, expressed in a native language. The major disadvantage is that the method of prediction is internal, but the advantage is that the cost of production is extremely low. . . . On the other hand, prescriptive models are normative. Normative science does not stop at describing and generalizing observations, since the term "normative" implies the establishment of standards of correctness, a normative model is more suitable for predictive purposes.2 1Ludwig Von Bertalanffy, Perspectives on General Systems Theory (New York: George Braziller, 1975), pp. 104-105. 2V. Vemuri, Modeling of Complex Systems, An Introduction (New York: Academic Press, 1978), pp. 67, 68, 69. 51 Every concern of man is represented in some form of a model. A diversity of models is represented in Figure 2.4. Models are also diverse in methods which have been used to construct and present them in a formal language. Diversity of methods used in modeling is presented in Figure 2.5. 1. Model airplane 22. Clay models 2. Model cars 23. Patent models 3. Model cities 24. Machinery models 4. Model networks 25. Engineering models 5. Model ordinance 26. Hydrologic models 6. Model railroad 27. Linguistic models 7. Model ships 28. Communication models 8. Model soldiers 29. Economic models 9. Model space vehicles 30. Sociological models 10. Model auto racing 31. Education models 11. Acoustic models 32. Management models 12. Architectural models 33. Land use models 13. Fashion models 34. Hybrid models 14. Astronomical models 35. Market demand models 15. Biological models 36. Market supply models 16. Chemical models 37. Urban growth models 17. Hydraulic models 38. Retail growth models 18. Mechanical models 39. Retail location models 19. Military models 40. Historical models 20. Nuclear models 41. Geographical models 21. Zoological models 42. Political models Figure 2.4 Diversity of Models O‘DCDVO‘U‘IAUINt—i Analytical models Prediction models Poliometric models Simulation models Linear interaction models Decision oriented models Time oriented models Rasch models Causal models Computer based feedback models Decision models Information models Hypothetical models Digital simulation models Empirical models Flow models Theoretical models Theoretical isomorphic models Integrated models Systems models Sampling models» Econometric models Diagnostic testing models Evaluation models 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. Performance satisfaction models Structural models General linear models Continuum models Cost-effectiveness models Cost models Conceptual models Synoptic models Cybernetic models Cost benefit models Rasch simple logistic models Procedural models Diffusion models Electric models Ontological models Pluralistic models Synergistic evaluation models Circuit models Time series forecasting models Generic models Consensus models System design models Operational flow models Systems approach models Functional models General systems theory models Figure 2.5 Diversity of Methods Used in Modeling. Motivation for Modeling According to Morris, the role of models is to express the links of reason which bind concepts into a system, for, as Sir James Jeans insisted, a heap of facts is no more science than a heap of bricks is a house.1 Buffa points out that, models are bases of the prediction systems, and are vital to the formal decision making process. Indeed, they are vital to an intellectual attack on any problem. Models come to us from scientific methods, the scientist attempts to duplicate, in some kind of a model, the behavior of the system or subsystem with which he is working. Once he has achieved this parallelism between the real phenomena and his model, it is usually easier to manipulate the model to study its characteristics in which he is interested than it is to try to work with the real phenomena or the system in question.2 According to Vemuri, the reasons for constructing a model and the ultimate use of the model, differ markedly. He indicates these differences through the use of different shades of gray as shown in Figure 2.6. As one proceeds from the light end of the spectrum to the dark end, there is a gradual but steady shift from the quantitative to the qualititative. Near the ”white box" end of the spectrum, models are an impor- tant tool for design. For example, in electrical circuit design, models permit experimentation with various combinations of circuit elements to obtain optimum filter characteristics. Closer to the "black box" side 1William T. Morris, Management Science in Action (Homewood, 111.: Richard D. Irwin, Inc., 1965), p. 84. 2Elwood S. Buffa, Models for Production and Operation Management (New York: John Wiley 8 Sons, Inc., 1963), p. 9. 54 .mm .& .msmwmmw Rummspuuwo mchowcz «wassms .> noosxom .m:«~ocoz mo mo>wuoomno o.m owzwflm xon xon SE: 5.83 3588 .5 283:8 fir.) :wflmou,/ mofiEm:xw owpuoofio \codcflmo uu: chm 0A :Q . i ”Amt...“ hm. . .. a”... / meOOA w. . a .. c \ // \unwwm:w / \ 5mm :0wuowponm/. s. at.w».. \\\ oucmsuompoa /./ :ofiusfifiom \\ / me \ /.// \\ mofluoocu / \ $3 :ofluom now ./.11 \\ \\ :ofluowuona I: I. it \\ I.MmemMWAum Monacou saw: :oflumucoawhomxo 55 of the spectrum, models play an entirely different role. Frequently they are used to provide a general insight into system behavior. Occasionally, the primary objective of the model is to arouse public opinion and promote political action by suggesting that the current trends lead to disaster in the not too distant future.1 Iconic Models Authors Buffa, Hull et al., and Massie and Douglas have defined an iconic model as a physical representation of certain characteristics 2 Iconic models also of the real system, usually scaled up or down. graphically or pictorially represent certain important characteristics of the real world. According to Buffa, good examples of iconic models are "aero- dynamicist's models, planetariums, engineering blue prints, globe of the world, photographs, and three-dimensional models of physical facilities."3 Bross's iconic models are called physical models. In his definition of physical models he exemplifies model aircrafts and states, 1V. Vemuri, Modeling of Complex Systems, An Introduction (New York: Academic Press, 1978), pp. 81-82. 2Elwood S. Buffa, Models for Production and Operation Manggement (New York: John Wiley 5 Sons, Inc., ), pp. 10-11; D. A. Hull, John Mapes and Brian Wheeler, Model Building Techniques for Management (Saxon House: Cranfield Institute Press, 1976), p. 7; and Joseph L. Massie and John Douglas, Managing: A Contemporary Introduction (Englewood Cliffs, N.J.: Prentice Hall, 1977), p. 257. 3Buffa, p. 10. 56 there are several kinds of model aircraft: (1) solid scale models resemble the actual planes in general appearance (shape, markings, etc.), (2) the flying model aircraft not only resembles the originals in appearance, but to some extent, in function as well (i.e., they are capable of free flight), (3) some very elaborate models are essen- tially simplified versions of real aircraft; they have gasoline engines, operable controls, and may even have radio-control mechanisms which allow the plane to be directed from the ground. . . . The model aircraft is easier to study than a full-size aircraft; it is more convenient to handle and manipulate. It is also simpler than the original and principles of operation may be more apparent. There is some danger of oversimplification, of course, but adult scientists use model aircraft to learn about the performance of full-sized aircraft. This particular type of abstraction, the construction of a physical model, is used in various branches of science, engineering, and industry.1 Analogue Models According to Hull et al., an analogue model is one in which certain aspects of the behavior of the real system are produced in a different medium. A popular form of analogue model involves the use of flows of electricity as an analogue for flows of material or infor— mation in a system. Such models are expensive to construct, so that they are only feasible for applications where the model will be used on a regular basis for planning purposes.2 Buffa points out that, analogue models establish a relationship between a variable in the system and an analogous variable in the model. Thus a graph of sales by months uses the length of lines as 1Irwin D. J. Bross, Models in Management Systems, ed. Peter Schoderbek (New York: John Wiley 6 Sons, Inc., 1968), p. 327. 2John Hull, John Mapes and Brian Wheeler, Model Building Techniques for Management (Saxon House: Cranfield Institute.Press, 1976), p. 8. S7 analogous to the magnitude of sales and time. Various kinds of flow charts use lines as analogous to material flow. Analogue computers establish a relationship between variables in a real world problem and an electrical system. Analogue models are often useful for the study of dynamic situations. Usually, changes in an analogue model can be made more easily than in an iconic model, so they can fit more different situations, and thus have greater generality.l Conceptual Models In understanding a structure, a process, or a complexity, scientists attempt to develop a conceptual model. This is usually done when the phenomena under consideration would otherwise be incomprehensible. McFarland indicates that, a description of the duties and responsibilities of a particular job is actually:1model depicting the organi- zation's expectation as to what work shall be done. Such intangibles as time, employer satisfactioné or customer preference may be components of the model. All of us are accustomed to using verbal models in our thinking processes and we do it intuitively. Verbal models have played an important role in science, especially in the preliminary exploration of a topic and presentation of results.3 Bross exemplifies a conceptual model as the following: 1Elwood S. Buffa, Models for Production and Operation Management (New York: John Wiley 6 Sons, Inc., ), p. 11. 2Dalton E. McFarland, Management Principles and Practices (New York: The Macmillan Co., 1974), p. 201. 3W. Warren Haynes and Joseph L. Massie, Management Analysis, Concepts, and Cases (Englewood Cliffs, N.J.: Prentice Hall, Inc., 1975), p. 442. 58 The solar model, which you can see in a planetarium has had a very interesting history. Nowadays, we think of the sun as a giant globe with a large family of little spheres circling around it. We locate ourselves on the third little sphere (counting out from the sun), and this notion does not cause us any mental anguish. In earlier days, the picture was quite different and the earth was regarded as the center of the system. Of course, if we go back still further, there are all sorts of fabulous models which involve giants, turtles, and sea serpents. The history of astronomy is the story of evolution of a model. Did you notice that in describing the solar model, I was actually taking a further step in abstraction? I was going from a physical model to a verbal model. The little balls were replaced by their symbols, the words "little balls."1 Graphic Models Graphical models are being used as a convenient abstraction of reality (i.e., a phenomena, a situation, a problem), by many managers, even though most managers would not express what they were doing in model building terms. A very simple example of a graphical model is the breakeven chart.2 A breakeven chart shows graphically the relationship between fixed costs, total costs, and sales revenue. The chart shows the point or area of operations that allows a business firm to neither make a profit nor a loss.3 A flow chart model is a graphic analogue showing the total structure, organization, and interrelationships of a process, event, 1Irwin D. J. Bross, Models in Management Systems, ed. Peter Schoderbek (New York: John Wiley 5 Sons, Inc., 1968), p. 328. 2John Hull, John Mapes and Brian Wheeler, Model Building Technigues for Management (Saxon House: Cranfield Institute Press, 1976), p. 7. 3Robert Albanese, Management Toward Accountability for Per- formance (Homewood, 111.: Richard D. Irwin, Inc., 1975), p. 107. 59 or other phenomenon. Flow chart symbols represent ideas, information flow, and human action with narrative explanation provided for each symbol. The LOGOS symbol system (Language for Optimizing Graphically Ordered Systems) developed by Silvern can be used, in developing a flow chart model.1 Symbolic Models According to Buffa, symbolic models substitute symbols for components or variables in the real world system, and the symbols are generally related mathematically. The symbolic system, then, is a model of some aspect of the real situation. For example, Newton's second law of motion, F==MA, states a relationship between three variables, force, mass, and acceleration. The symbolic model is the most difficult and expensive to construct, yet it is usually more general in application than other types of models and yields the most information.2 Massie and Douglas use symbolic and mathematical models synonymously and specify that, the most generally used type of model in decision making is a symbolic or mathematical model that uses symbols to specify important properties to be considered. Symbolic models can be constructed to show the relationships among variables; these symbols can be expressed as equations. According to Turban and Meredity, the complexity of relation- ships in some systems cannot be represented physically. Therefore, 1Leonard C. Silvern,"LOGOS: A System Language for Flowchart Modeling," Educational Technology 9 (June 1969): 18-23. 2Elwood S. Buffa, Models for Production and Operations Manage- ment (New York: John Wiley 8 Sons, Inc., 1963), p. 11. 3Joseph L. Massie and John Douglas, Managing: A Contemporary Introduction (Englewood Cliffs, N.J.: Prentice Hall, 1977), p. 257. 60 a more abstract model is used with the aid of symbols. These models are usually general rather than specific and can describe diverse situations. 1 Use of Models According to Hull et al., there are three main reasons for constructing a model: (1) description, (2) prediction, and (3) analysis. In defining each, respectively, he states that, 1. A descriptive model helps us to understand rapidly the salient features of the systems being modeled. If a model is to be used purely for descriptive pur- poses, it can be much simpler than corresponding predictive and analytical models. For example, an organization chart is a typical descriptive model. It can be used to determine rapidly who reports to whom in a large organization. If, however, we wish to estimate the effects of altering the organizational structure, a much more complex model would be necessary, incorporating informal communication channels, the competence of existing managers and a host of other factors. Prediction. A number of models are constructed in order to make predictions about the future behavior of the real system. Such models will vary considerably in complexity, depending on the required accuracy of the prediction. Graphical extrapolation of past data in order to forecast future sales is an example of a simple predictive model. Analysis. Usually, the model builder wishes to manip- ulate the model in order to determine the best method of achieving specified objectives. Clearly, use of a model for this purpose will still involve elements of description and prediction but it will also require a 1Turban and Meredity, Fundamentals of Management Science (Dallas, Texas: Business Publications, 1977), p. 21. 61 greater understanding of the interrelationships between the variables in the model.1 Model Theory According to Deutch, a model is a structure of symbols and operating rules which is supposed to match a set of relevant points in an existing structure or process. In order to understand complex processes, models are being made. The only alternative to their use would be an attempt to consider a system with all its interrelated interdependent elements directly, and to match it completely, point for point. This is manifestly impossible. Each model implies a theory asserting a structural corre- spondence between the model and certain aspects of the thing supposed to be modeled. It also implies judgments of relevance; it suggests that the particular aspect to which it corresponds are in fact the important aspects of the thing for the purposes of the model makers or users.2 Conceptual model theory is characterized more or less imper- fectly by four distinct functions. These functions are (1) the orga- nizing, (2) the heuristic, (3) the predictive, and (4) the measuring or mensurative. According to Deutch, the definitions of each function can be stated as follows: By the organizing function, is meant the ability of a model to order and relate disjointed data, and to show similarities or connections between them which had previously remained unperceived. To make isolated pieces of information fall 1John Hull, John Mapes and Brian Wheeler, Modeling Building Techniques for Management (Saxon House: Cranfield Institute Press, 1976), p. 10. 2Karl W. Deutch, The Evaluation of Models in Management Systems ed. Peter P. Schoderbek (New York: John Wiley 8 Sons, Inc., 1967), p. 337-338. 62 suddenly into a meaningful pattern is to furnish an aesthetic experience.1 Heuristic is defined as having to do with the art of discovery. It pertains to those methods by which one finds and applies strategies that may transfer across tasks.2 The heuristic function helps one to discover new facts and new methods even though these novel facts and methods cannot be verified by the techniques which are available. The heuristic function of a model may be independent to a considerable degree from its orderliness or organizing power, as well as, from its predictive and mensurative performance.3 Predictive function of a model is a probability state- ment of the degree of success likely to be achieved.“ There are different kinds of predictions. At one extreme, we find simple yes and no predictions: at higher degrees of specificity, we get qualitative predictions of similarity or matching, where the result is predicted to be of this kind or of that kind, or of this particular delicate shade, and at the other extreme, we find com- pletely quantitative predictions which may give us elaborate time series which may answer the questions of when and how much.5 The mensurative function of a model would provide us with an indicant and a measure. (1) If the model is related to the things modeled by laws, which are not clearly understood, the data it yields may serve as indicants. (2) If it is connected to the things modeled by processes clearly understood, we may call the data obtained with its help a measure--and measures 1Ibid., p. 339. 2Carter V. Good, Dictionary of Education (New York: McGraw- Hill Book Co., 1973), p. 280. 3Deutch, p. 338. “Good, p. 433. sDeutch, p. 338. 63 again may range all the way from simple rank orderings to full fledged ratio scales.1 Deutch also points out that, a dimension of evaluation corresponds to each of these four functions of a model, and users of the model must address the following questions to each function. 1. How great is a model's generality or organizing power? : 2. What is its fruitfulness or heuristic value? 3. How important or strategic are the verifiable predictions which it yields? 4. How accurate are the operations of measurement that can be developed with its aid?2 If we collect the answers to these four questions under the heading of the "performance" of a model, we may then evaluate the model still further in terms of the three additional considerations of (l) originality, (2) simplicity, and (3) realism. Originality of a model. We mean its improbability. Any idea, scheme or model may be thought of as the product of the recombination of previously existing elements, and perhaps of a subsequent process of abstraction omitting some of the traces of its combinational origin. The greater the probability or obviousness or triteness, of a model, the more frequent is this particular recombination in the ensemble of combinatorial possibilities at the immediately preceding stage. Originality or improb- ability is the reverse of this value:T Models should be evaluated for their simplicity or economy of means. Simplicity is tantamount to economy, and it was compared to efficiency in economics by Deutch when he declared that efficiency in economics denotes the attainment of a given result with the greatest 1Ibid., p. 339. 2Ibid. 3Ibid. 64 economy in the employment of these means which are shortest in supply at each particular time, place, or situation. The last consideration for evaluating a model or a conceptual scheme, is its realism, that is, the degree of reliance which we may place on it, representing some approximation to physical reality.1 Promulgating the idea that a model can be an effective change agent, Chin constructed five questions he felt a model must answer: 1. Does the model account for the stability and continuity in the events studied at the same time that it accounts for changes in them? How do processes of change develop, given the innerlocking factors in the situation that make for stability? Where does the model locate the source of change? What place among these sources do the deliberate and conscious effort of the client-system and change—agent occupy? What does the model assume about how goals and directions are determined? What or who sets the direction for movement of the processes of change? Does the model provide the change agent with levers or handles for affecting the direction, tempo, and quality, of these processes of change? How does the model "place" the change-agent in the scheme of things? What is the shifting character of his relationship to the client-system, initially and at the termination of relationship, that affects his perceptions and actions? The question of relationship of change-agent to others need to be part and parcel of the model, since the existential relationship of the change-agent engaged in processes of planned change becomes "part of the problem" to be investigated.2 'Ibid. 2Robert Chin, "The Utility of Systems Models and Developmental Models for Practitioners," in Planning Change, ed. William G. Bennis Kenneth Benne and Robert Chin (New York: Holt, Rinehart G Winston, Inc., 1961), pp. 201-214. 65 Bross said that models have various advantages, among which he listed (1) their remarkable record of prediction in the past history of mankind, (2) their use as a frame of reference on which to ”hang the problem," (3) their use in fruitful avenues of research, (4) their simplification of the problem by employing only the significant attributes abstracted from the real world, (5) their use of symbolic language for both manipulation of the model and for purposes of easy communication, and (6) finally, their economical approach to the costs of prediction.1 Chin indicated these advantages of a model: 1. The model provides "mind-holds" to the practitioner in diagnosis. 2. A model lessens the danger of overlooking the indirect effects of a change of relationship. 3. The identification of and analysis of how tension operates in a system are by all odds the major utility of system analysis for practitioners of change. 4. A model can be used for a diagnosis of persons, groups, organizations and communities for the purpose of change. 5. A model can provide directional focus for analysis and action and a temporal frame of reference.2 1Irwin D. J. Bross, Models in Management Systems, ed. Peter P. Schoderbek (New York: John Wiley 8 Sons, Inc., 1968), pp. 330—331. 2Robert Chin, "The Utility of Systems Models and Developmental Models for Practitioners," in Planning Change, ed. William G. Bennis, Kenneth Benne and Robert Chin (New York: Holt, Rinehart 8 Winston, Inc., 1961), p. 421. 66 Disadvantages of Models The use of models also has some drawbacks. Bross indicated these disadvantages of models as the following: 1. The model is subject to the usual dangers inherent in abstraction. A mathematically feasible model may require gross oversimplifications. There is no guarantee that an investment of time and effort in constructing the model will pay dividends in the form of satisfactory predictions. No process, how- ever, can provide such a guarantee. The symbolic language is also subject to limitations. It may be beyond the ability of mathematicians to manipulate the symbolic language so as to obtain useful results. After a scientist plays for a long time with a given model, he may become attached to it, just as a child may become, in the course of time, very attached to a doll (which is also a model). A child may become so devoted to the doll that she insists that her doll is a real baby, and some scientists become so devoted to their model (especially if it is a brain child), that they will insist that this model is the real world. The same sort of things happen with verbal models, as the semanticists point out, when a word and its counterpart in the real world are regarded as the same thing. This identification in the world of words has led to unhappy results which are reflected in the real world.1 Systems Approach and Modeling According to Schoderbek et al., the application of the systems approach to management can be conceived as consisting of the following three steps: 1Irwin D. J. Bross, Models in Management Systems, ed. Peter P. Schoderbek (New York: John Wiley 8 Sons, Inc., 1968), p. 331. 67 1. Viewing the organization as a system. 2. Building a model. 3. Using information technology as a tool both for model building and for experimentation with the model; i.e., simulation. Developing a system viewpoint of an organization is primarily a matter of the manager's adopting a new philosophy of the world. . . . A systems-oriented manager is a manager of the whole. Every manager can be a systems manager as long as his approaches are governed by the two following principles formulated by B. Fuller. 1. I always start with the universe: an organization of regenerative principles frequently manifest as energy (and/or information) systems of which all our experiences and possible experiences are only local instances. 2. Whenever I draw a circle, I immediately want to step out of it.1 He further states that the manager whose style is directed by these two principles begins his investigation of the world about him in order to identify his universe and to gain the ability to view his department as a system functioning within its environment. He then continues his investigation by gathering and analyzing the facts pertaining to happenings within ”his” department. This definition of a manager's department, along with its environment, will provisionally determine the boundary of his system. About this system, the manager will want to know its inputs, throughputs, outputs, feed-backs, relationships, as well as their attributes. His search for these system 1Peter P. Schoderbek et al., Management Systems Conceptual Consideration, Business Publications, Inc., 1975, p. 239; and B. Fuller, I Seem to Be a Verb, Management Systems, Business Publi- cations, Inc. (New York: Bantam Books, 1970). 68 determinants begins with construction of a conceptual model. Thus, the model becomes the link between the real phenomenon, and the manager's system. Figure 2.7 depicts the relationship between the real phenomenon (RP), the Model (ML) and the System (SY). The systems-oriented investigator, who looks at phenomena from the holistic viewpoint, perceives them as an orderly summary of these features of the physical and/or social world that affect his behavior, thus, the box labeled "real phenomenon" (RP) represents the observer's interpretation of what is really out there.1 Behavioral Systems Design Good and Machol have suggested that the design process for a behavioral system consists of: l. A statement of the problem. 2. The formulation of a model. 3. The collection and application of data.2 In stating the problem, one would sketch the proposed system either by starting with an existant system or beginning anew. The next step in the design process is to formulate a model or representation of the proposed system. The key to effective design is the ability to simulate the system in its present state as well as any modification that would be made. Such a representation can take a variety of forms from a relatively simple flow diagram to a highly sophisticated mathematical model. However, the block diagram, or flow chart, is one of the basic tools in systems design. Whether or not the model is descriptive or mathematical, at this early model building stage, one would only have an approximation 1Schoderbek et al., p. 239. 2Harry H. Goode and Robert Machol, System Engineering (New York: McGraw-Hill Book Co., 1957), pp. 305-306. 69 THE SYSTEM (SY): A Set of Objects Together with a Set of Relationships between the Objects and Their Attributes. A system (SY) represents an organized presentation of the real phenomenon expressed in terms of system parameters (viz., inputs, processes, outputs, and feedbacks) and system relationships (viz., information flows or channels of communication). Systems must be isomorphic to the real phenomenon. I THE MODEL (ML): An Abstraction of the Real Phenomenon. A Conceptual Framework. A A formal model represents the investigator's efforts to fit the real phenomenon (RP) into a logical scheme. Thus, the model (ML) is the conceptual framework of the real phenom- enon (RP) or reality. ‘V THE REAL PHENOMENON (RP): An Orderly Summary of Those Features of the Physical and Social World that Affect Behavior. Figure 2.7 The System, the Model, and the Real Phenomenon. Note: The Model (ML) is always "smaller" than the Real Phenomenon, or the system, the System must be as complex as the Real Phenomenon. There is a homomorphism between the model and reality but an isomorphism between the system and reality. (Source: Schoderbek et al., p. 240.) 70 of its operation. Additional data would have to be acquired. One must determine what additional data is required and how it is to be obtained. For the most part, a constant feedback should exist between the collection and analysis of data and the completeness of the model. With this data, one would be able to assign realistic values to listed parameters. Guidelines in Behavioral System Design specified by Goode and Machol are as follows: 1. Output is the final product expected from the system. 2. Payoff is the human utility or satisfaction that will result from system operation or that which the system is to optimize. 3. Requirements are standards of performance which the system must meet. 4. Stability would mean the continuity of output. 5. Reliability refers to consistency of operation of components. 6. Description of the environment, general area of permissible or acceptable solutions and measures of effectiveness must be considered. 7. Description of the environment would involve noting the different expected inputs that will either enter or affect the system. 8. The area of acceptable solutions would relate essen- tially to a review of the present technology relative to the operation of the system.1 1Harry H. Goode and Robert Machol, System Engineering (New York: McGraw-Hill Book Co., 1957), p. 306. 71 Toward a Theory of Experience Experience, learning by doing, is identified as a meaningful way of learning in a system for mechanization of agriculture. There- fore, in this study, understanding the theory of experience will be of great value. According to Dewey, experience is a single dynamic, unified whole in which everything is ultimately interrelated. He thought of experience as interaction between the individual and his environment, subjective and objective elements, or inner and outer elements.1 He insisted that life consists of a series of overlapping and interpenetrating experiences, each of which has its own internal qual- itative integrity. The individual experience is the primary unit of life, and experience is all inclusive in the sense that man is involved in continuous transactions with his environment, and through systematic inquiry he can come to understand the essential characteristics of nature and his environment. Furthermore, within an experiential transaction, we can institute distinction between what is subjective and what is objective, but such distinctions are relative to and dependent on the context in in which they are made. All experiences are not equally educative, and some experiences may even be miseducative. To differentiate between what constitutes an educative experience and what constitutes a miseducative experience, one must have a set of rules, definitions, 1John Dewey, Experience and Education (New York: Collier, Macmillan Publishers, 1977), pp. 26, 27, 47. 72 and principles. According to Dewey, educative and miseducative experiences can be defined as follows: 1. Educative Experience: In a certain sense every experience should do something to prepare a person for later experiences of a deeper and more expansive quality. This is the very meaning of growth, continuity, reconstruction of experience. 2. Quality of Experience: It is not enough to insist upon the necessity of experience, nor even of activity in experience. Everything depends upon the quality of experience. The quality of experience has two aspects: (1) immediate aspect of agreeableness or disagreeable- ness, and (2) its influence upon later experience. Miseducative Experience: Any experience is miseducative that has the effect of arresting or distorting the growth of further experience. It may produce a lack of sensi- tivity and of responsiveness. Then the possibilities of having richer experiences in the future are restricted. An experience may be immediately enjoyable and yet pro- mote the formation of a slack and careless attitude.1 (A Criteria of Experience The experiential continuum, and the experiential interaction are the two principles stated by Dewey as inseparable elements of an educative experience. Principle 1. The Experiential Continuum. The expe- iential continuum or the category of continuity attempts to discriminate between experiences that are worthwhile educationally and those that are not. . . . This principle rests upon the fact of habit, when habit is interpreted biologically. The basic characteristic of habit is that every experience enacted and undergone modifies the one who acts and undergoes. The principle of habit so under- stood obviously goes deeper than the ordinary conception of a habit as a more or less fixed way of doing things, although it includes the latter as one of its special cases. It covers the formation of attitudes, both emo- tional and intellectual; it covers our basic sensitivities 'Ibid., pp. 26-27. 73 and ways of meeting and responding to all the conditions which we meet in living. Growth or growing as developing, not only physically but intellectually and morally, is one exemplification of the principle of continuity. . . . Growth is not enough; we must also specify the direction in which growth takes place, the end towards which it tends. Growth as educa- tion and education as growth should create conditions for further growth in new directions.1 Principle II. Experiential Interaction. The word interaction expresses the second chief principle for interpreting an experience in its educational function and force. It assigns equal rights to both factors in experience--objective and internal conditions. Any normal experience is an interplay of these two sets of conditions, taken together or in their interaction, they form what we call a situation. . . . The statement that individuals live in a world means in the concrete, that they live in a series of situations. . . . The conceptions of situation and of interaction are inseparable from each other. An experience is always what it is because of a transaction taking place between an individual and what, at the time, constitutes his environment. All human experiences are ultimately social, in that they involve contact and communication. Also, the two principles of continuity and interaction are not separate from each other. They intercept and unite. They are, so to speak, the longitudinal and lateral aspects of experience.2 In regard to value judgment of experience, Dewey indicates that, every experience is a moving force. Its value can be judged only on the ground of what it moves toward and into. Each experience of the learner can be evaluated in a way in which the one having the less mature experience cannot do.3 In other words, what an individual has learned in the way of knowledge and skill in one situation becomes an instrument for 1Ibid., pp. 35, 36. 2Ibid., pp. 43-43. 3Ibid., p. 31. 74 understanding and dealing effectively with the situation which follows. This process goes on as long as life and learning continue. Therefore, education as growth or enhancing maturity should be an ever-present process.1 Formation of the proper attitudes of the individual is the main concern in an educative experience. One must realize that ability to train thought is not achieved merely by knowledge of the best forms of thought. Possession of this information is no guarantee for ability to think.2 The attitudes that need to be cultivated in order to secure their adoption and use, according to Dewey, are: l. Open-Mindedness. This attitude may be defined as freedom from prejudice, partisanship, and such other habits as close the mind and make it unwilling to consider new problems and entertain new ideas. 2. Whole-Heartedness. When anyone is thoroughly inter- ested in some subject and cause, he throws himself into it; he does so, as we say, heartily, or with a whole heart. The importance of this attitude or disposition is generally recognized in practical and moral affairs. But it is equally important in intellectual development.3 To summarize Dewey's thoughts on experience, he argues that education should be a continuous reconstruction of experience toward perfection of that experience founded with the skills and habits of intelligence. 1Ibid., pp. 44, 50. 2John Dewey, Selected Writings on Education, ed. Reginald Archambaalt (New York: The Modern Library, 1959), p. 223. 3Ibid., pp. 224, 235. One of the dispositions having high value is the disposition to share: the sharing of viewpoints and opinions, the sharing of experiences, and the sharing of cooperative help in working out the learning projects, supported by new sources of information for growth and development of individuals. Dewey said that the function of education should be to encourage those habits and dispositions that constitute intelligence and he placed great stress on creating the proper type of environment for experiences which would lead the individual to these attitudes and habits. Cooperative Extension Service In a system for Mechanization of Agriculture, Extension certainly has an important role and can be identified as a subsystem aimed at communication of innovations with the goal of higher quality inputs, throughputs, and ultimately outputs from the system. Therefore, it will be of value to understand the Cooperative Extension Service and the concepts related to this form of non-formal education. In a report of the joint USDA-NASULGC1 study committee, it defines the Cooperative Extension Service as "that organizational entity of the Department of Agriculture, and the Land Grant system created under provisions of the Smith Lever Act and subsequent related 1USDA, United States Department of Agriculture; and NASULGC, National Association of State University and Land Grant Colleges. 76 legislation which conducts educational programs of an informal non-resident, problem-oriented nature."1 Lincoln and Cannon define extension work as, an out of school system of education in which adults and young people learn by doing. It is a partnership between the government, the land grant colleges, and the people, which provides services and education designed to meet the needs of the people. Its fundamental objective is the development of people.2 Agricultural progress depends upon people for true progress. People must know, must understand, must act. How far people progress depends largely upon their access to accurate and reliable information they can use to help solve their problems.3 An agricultural extension service has one main job, to get helpful information and innovation to people. Extension is the connecting link between the sources of knowledge and the receiver of knowledge. Agricultural research and education is based upon these principles.- Science investigates problems and builds a store of knowledge; classroom and extension teaching transmit the knowledge to people who want and need it.“ Extension phiIOSOphy is to help people identify their own problems and opportunities, and then to 1A People and A Spirit, a report of the joint USDA-NASULGC Study Committee on Cooperative Extension, Colorado State University, Fort Collins, November 1968, p. 17. 2D. K. Lincoln and C. H. Cannon, Cooperative Extension Work (Ithaca, N.Y.: Comstock Publishing Co., 1963), p. 1. 3Bryant Kearl and Hardle Read, Agricultural Communication Service, p. 8. “Ibid., p. 7. 77 provide practical research-based information that will help them overcome the problems and take advantage of opportunities.1 An extension agent is expected to: (1) plan programs, (2) work closely with people, and (3) deal with important problems of people and communities with the accent on action. To help people to help themselves through education is the guiding principle of extension. Extension educators do this by assisting people to: (1) identify their needs, problems, and opportunities, (2) evaluate their resources, (3) determine alternative solutions, and (4) follow a suitable course of action. An extension agent brings available research information to people and interprets and demonstrates its application.2 In addition to their own knowledge of agricultural technology, extension agents depend upon extension specialists and other resource persons for the latest research. As an extension specialist, the individual would: 1. Assist extension agents and advisory groups in planning educational programs designed to meet specific needs and interest of the people. 2. Keep extension agents posted on research findings and their application to practical problems. 3. Provide on-the-job training for extension agents, teach people through farm and home visits, meetings, tours, demonstrations, etc., in a way that will strengthen the position of extension personnel in the counties. lAustin Vines and Marvin A. Anderson, eds., "Heritage Horizons, Extension's Commitment to People," Journal of Extension, 1976, p. 50. 2A Career with Cooperative Extension Service, Michigan State University, East Lansing, Michigan, 1P 3R-4-69-3M. 4. Conduct studies of county and state situations-- assembling, analyzing, and interpreting facts, clarifying problems in the field of specialization and working out appropriate solutions for the people and groups involved. 5. Support county programs with teaching aids such as bulletins, newspaper stories, radio, and television programs, films, slides, exhibits, charts, etc. 6. Become a recognized authority and leader in his or her professional field.1 Extension agents will have unequaled opportunity for on-the-job training as they plan, analyze, and conduct extension programs. An annual extension conference, special training meetings, and workshops of many different types are held each year for the benefit of the staff. A constant flow of the latest findings of scientific research from many resources are sent to agricultural extension agents.2 The extension worker's creed is considered to be the philosophical guide for the extension worker. Extension Worker's Creed I believe in people and their hopes, their aspirations, and their faith, in their right to make their own plans and arrive at their own decisions; in their ability and power to enlarge their lives and plan for the happiness of those they love. I believe that education, of which extension work is an essential part, is basic in stimulating individual initiative, self-determination, and leadership, that these are the keys to democracy and that peOple, when given the facts they understand, will act, not only in their self-interest, but also in the interest of society. 1A Career With Cooperative Extension Service, Michigan State University, East Lansing, Michigan, 1P-9z78-4M-st. 2A Career With Cooperative Extension Service, Michigan State University, East Lansing, Michigan, 1P 3R-4-G9-3M. 79 I believe that education is a lifelong process and the greatest university is the home; that my success as a teacher is proportional to those qualities of mind and spirit that give me welcome entrance to the homes of the families I serve. I believe that the extension service is a link between the people and the ever-changing discoveries in the laboratories. I believe in the public institutions of which I am a part. I believe in my own work and in the opportunity I have to make my life useful to mankind. Because I believe these things, I am an extension worker.1 In regard to advisory groups and their roles, Gordon Guyer, Director of Cooperative Extension Service at Michigan State University, indicates that, traditionally, extension programs have been guided by local citizens who serve in an advisory capacity and direct efforts in areas of greatest need. Such groups work closely with county commissioners. This has enabled extension work to be focused upon the common concerns and needs of people, their families and their communities.2 "Cooperative" in the case of extension service, refers to the joint financing by federal, state, and county government of non-formal problem-oriented programs, based on local needs of the individuals, groups, and communities.3 Some characteristics of the cooperative extension system are: 1. The federal, state, and local government cooperatively share in its financial support and program direction. 1A Career With Cooperative Extension Service, Michigan State University, East Lansing, Michigan, IP-9z784 M-ST. 2The CBS: A Guide Prepared for County Boards of Commissioners, Michigan State University, East Lansing, Michigan. Gordon E. Guyer, Director. 3Ibid. 80 2. It is administered by the Land Grant universities as designated by the state legislature through an extension director. 3. Extension programs are objective and based on factual information. 4. It provides practical, problem-oriented education for people of all ages. 5. It utilizes research from university, government, and other sources to help people make their own decisions. 6. It dispenses no funds to the public. 7. The extension staff educates people through personal contact, meetings, demonstrations, and mass media. 8. Specialists, agents, aides, and volunteers are helping people to help themselves. Demand for Technical Know-How In a study done by Webb and Knotts, duty areas of work in which grain farmers performed the tasks were: Following legal practices in grain operations. Following general safety precautions. Maintaining equipment and vehicles. Using and maintaining hand and power tools. Testing soil and plant tissues. Fertilizing grain crops. Operating powered equipment and vehicles. Controlling insects and diseases. Controlling weeds. Constructing and maintaining grain operations, buildings and structures. 11. Assembling and installing grain operation equipment. 12. Establishing grain cr0ps. 13. Marketing and shipping grain crops. 14. Harvesting. 15. Storing grain crops.1 OKOCDVOWQ-MNH 1Earl S. Webb and Clifton Don Knotts, Agricultural Mechanical Skills Needed by Farmers in Texas, Texas A 5 M University College Station, Department of Agricultural Education, ED 084460, September 1970. 81 The above list can be used as a guideline by extension departments to provide necessary services for the grain farmers. Other needed information and technical know-how by grain farmers are as follows: Selection of a cropping system. Selection of proper certified seeds. Planning tillage system. Determining plant nutrient requirements. . Diagnosing nutrient requirements. Soil tests. Lime requirement tests. Water management. Drainage maintenance. Planting specifications. Handling materials. Keeping records. H OOWNO‘UI-fi-MIUH I-‘H NH A commercial farmer needs both formal and non-formal education in order to keep up with ever changing technology and research findings. Non-formal education in the form of cooperative extension has, and always will have, an important role in helping adult farmers to adapt new practices. The extension aim in this study is identified as the commu- nication of innovations. Therefore, it is important to understand some of the more important concepts related to social change and communication of innovations. Communication of Innovations Many authors have defined social change. A sample definition of social change developed by Zaltman and Duncan is represented in Figure 2.8.1 1Gerald Zaltman and Robert Duncan, Strategies for Planned Change (New York: John Wiley 8 Sons, Inc., 1977), p. 8. 82 Author Definition Gerlach and Hines Hamblin, Jacobsen, and Miller Abcarian Rogers Etzioni Lippitt Smith Triandis Lenski Dobny, Boskoff, and Pendleton Niehoff Schien Developmental social change is change within an ongoing social system, adding to it or improving it rather than replacing some of its key elements. Revolutionary social change is change that replaces existing goals with an entirely different set of goals, steering society in a very different direction. Quantitative processes that occur through time. Structural tensions that result in widespread patterns of deviant norms and behavior. Alteration in the structure and function of a social change. Reformulation of a social structure involving disequilibrium, forces for establishing equilibrium and the occurrence of a new equilibrium. Anyyplanned or unplanned alteration in the status quo in an organism, situation, or process. Differentiation, reintegration, and adaptation. A new set of social relationships and social behavior that is most likely to lead to rewards. Innovation through discovery or invention or diffusion or alteration. Alterations in the patterns of interactions or social behavior among individuals and groups within a society. The implementation of a plan as mediated by actions of change agents and reactions of the community of (potential) adopters. The induction of new patterns of action, belief, and attitudes among substantial segments of a population. Figure 2.8 Sample Definitions of Social Change Source: Zaltman and Duncan, Strategies for Planned Change, p. 8. The Characteristics of Change According to Zaltman and Duncan, the characteristics of change are identified as: relative advantage, impact on social relations, divisibility reversibility, complexity, compatibility, communicability, and 0 time and timing.1 Relative advantage. This dimension refers to the unique benefit the change provides that other ideas, practices, or things do not provide at all or as well. Impact on social relations. Many changes may have a persuasive impact on social relationships within the target system and those between the target system and persons and groups in the outside environment. An organizational development program may create entirely new relationships and alter communication patterns within a group. Divisibility. Divisibility refers to the extent to which a change can be implemented on a limited scale. Reversibility. The reversibility dimension is closely related to divisibility. It refers to the ease with which the status quo ante can be established if a change is introduced but is later rejected. Complexity. The greater the degree of difficulty in using and understanding a change, the less likelihood that it will be adapted voluntarily. 1Ibid., pp. 13-23. 84 Compatibility. The "goodness of fit" a change has with the situation in which it is to be used is very important. The situation includes psychological, sociological, and cultural factors. Communicability. The ease with which information about a change can be disseminated is another critical dimension. Time and timing, The speed with which a change is introduced is an important dimension. It is necessary to think in terms of optimal time. Timing for introducing change is also important. Participants in the Change Process Participants in the change process are: change agent, change target, and client system. The change agent is a professional who influences innovation decisions in a direction deemed desirable by a change agency. The client system is a specific social system that requests a change agent to assist in altering its organization with the objective of improved performance. There is a difference between "client system" and "change target system." The change target system is the unit which the change agent is trying to alter the status quo in such a way that the individual, group, or organization must relearn how to perform its activities, while unwilling to do so and/or when it has made no request to do so. In contrast, the "client system" has requested and is willing to support the change. Change efforts may have three basic instrumental goals or objectives. They may be to (1) change attitudes, (2) change behavior, or (3) change both attitude and behavior. The types of social change are shown in Figure 2.9. 85 MICRO INTERMEDIATE MACRO Short term Behavior Normative change Innovation change Invention Administrative Revolution change Long term Life cycle Organizational Sociocultural change change evolution Figure 2.9 Types of Social Change. Concepts relevant to the communication of innovations are identified in Figure 2.10. For understanding and clarification of concepts in the communication of innovation presented in Figure 2.11, Zaltman and Duncan's, Rogers and Shoemaker's and Havelock's writings are recommended.1 Types of Strategies According to Zaltman and Duncan, there are five types of strategies for the communication of innovations: (l) facilitative, (2) re-educative, (3) persuasive, (4) power, and (5) multiple. In Figure 2.11 a comparative analysis of the four main strategies is made, where awareness, initial degree of commitment, 1Ibid.; Everett M. Rogers and Floyd F. Shoemaker, Communication of Innovations, A Cross-Cultural_5pproach, 2nd ed. (New York: Collier Macmillan Publishers, 1971); and Ronald G. Havelock, The Change_Agent's Guide to Innovation in Education, Educational Technology Publications, 1978, pp. 90-224. 86 social change change agent status quo client system rationalistic bias technocratic bias performance gap attributes of innovation relative advantages compatibility complexity triability observability pitfalls in social change poorly defined change goals change goals attitude change behavior change normative change change target social change differentiation reintegration adaptation micro-social change intermediate social change macro-social change short run social change cultural values cultural beliefs cultural ethnocentrism saving face incompatibility of cultural trait with change organizational barrier to change threat to power threat to influence behavior of top level admin. climate for change technological barriers psychological barriers perception homostasis personality factors commitment long run social change open system perspective historical background organizational structure organizational processes individual characteristics problems of innovation nature of the problem symptoms of the problem location of the problem past remedial effort policy problems organizational structure problems person problems production process problems product problems categories of problems recurrent problems re-recognized problems current problems refashioned problems unrecognized problems strategies for change educative strategies persuasive strategies power strategies cultural barriers to change social barriers to change group solidarity rejection of outsider conformity to norms conflict group insight resistance to change ideologies health conditions traditional heritage social relationships personality needs peer and authority relation personal attitude physical and temporal arrangements conformity environment Figure 2.10 Concepts in Communication of Innovations. 87' .Suawxogt .33an «new 53983.5 33m. 843.33 £5.33ng so 9.8.536me $5398: «.334 ma Eastman $34 .mozomoacoucanmgmk «Marin 3.553 so... 3338?. .5555 236% ~85 5.533 3qu 89:5,». .m:o_u=>o=:_ mo aonuaumzallou how moaaouahum ~_.~ cuss“; oazago sow>agoa oa=agu acq>sson a:a casuauu< mzouuaqom 3:: w19.90aa mo amoeoaaz< usolooaouzmoa uzIOH; mo>muuoaac o» ~a=oguuoa0ba ago» uaosm anon lswaox she» «:04 show «:64 mu=osoumzrou olmh o_nmuuou 3:: o—aa>homao use vanguwmuwunwo «sauna: o—zlwm ou=azu mo ocauaz o—aauaanueu--xo~alou . u gum: and: gum:tlsmao: 304 oaeazo oa ou:aum_moz o~aa~«a>a bosom __alm Inmvox cauaa ou:a:u mo oszuu=aex unseen: =0wmwooa 9:» we measum u:ohoma_1 “a muouhau neonomm«1 o» azas< oaaum a:«xal =ommmoov sea soumxm uoauau mo :oauau:oaaom .3mMu:o.z xao> soamlqa u:olumilou crap aco— uou xu=o_m azauuozzzmuu_om .«uez ozcau:oo «an scuulaa aeoaa oa:m;u o_aeaua>a mouuzonoz xuamnooo: on sea x5. moowaemou we souaouu aeomoam ac: «a mo.o>ou engage emaumam o» acquauw_aouuimo> on eqzosm--oz 0» were... on 6.:osm u=o«.u 0:» mo x~.uaaau .3...qu new“... gauge “New...“w... 3:4 304 :o— x—o>«u=_o¢ and: vowu:wuwmuwwoa zed sea :0. he ~eauzoz Lasau a“ u:ouum mo connwuufluuwm=_ u:auuoa1« uoz oz munmuolom no» «meanness xaouacum auto; m>_m<=m¢ua m>~hzo::m-ma m>.b SYMBOLIC , , , _ .J. 1053) _ _ Evaluation: {Evaluation}- Evaluation; REAL No Good Poor 0.x. WORLD ‘ lData I [New Datag}-—— [New Data}-——w [New Data_}———v Figure 4.1 Evolution of a Successful Model. The first shots are often very wide of the mark, but by gradual stages, the scientist zeroes in on his target. There is really no end to the sequence. Even after years of successful usage of a model, a situation may come along which will not be adequately predicted by the model. 1Irwin D. J. Bross, Models in Management Science, ed. P. P. Schoderbek (New York: John Wiley 8 Sons, Inc., 1967), p. 334. 129 A Diggrammatical Presentation of a System A diagrammatical presentation of a system should embody such parameters as input, process, output, feedback, boundary, and environ- ment. Figure 4.2 represents a diagrammatical model of a system in general. According to Schoderbek et al., The first thing that one should notice when looking at Figure 4.2 is that the input to one system is the output to another system, and that the output to one system becomes the input to another system. Secondly, the line demarcating the system from its environment [which is called system boundary], is not solid. There are two reasons for this: (1) such a line indicates that there is a continuous interchange of matter, energy, and information between the open system and the environment, and (2) the broken line indicates that the boundary's actual position is more or less arbitrarily determined by designer, investigator, or observer of the system's structure. Thirdly, the control function has been incorporated into the feedback component. Finally, the lines connecting the system's parameters to each other, as well as the system to its environment, represent the system relationship.1 Summary Systems thinking is an approach to the study of complex problems, situations, and phenomena. Emphasis is on the totality at the macro level in order to understand the interrelated, inter- dependent parts in interaction, realizing that the whole is greater than the sum of its parts. The systems approach then is a Gestalt type of approach in order to acquire an adequate knowledge of the whole before proceeding to an accurate knowledge of the entities and the subentities' functions. 1Schoderbek et al., pp. 31-33. .mm .m ..No no «magowoxom noonzom .u:oE=oum>:m n:m.>umo=:om.mnouoawumd m.Eoumxw a mo :0wumucomoha fimofiumeemhwmqn < N.v ousmflm ------------------------------Nmmmmmmmw-mmmmmmwm .............................. 4 130 G. l l mmoUOAa uzmcu o AIIIIIII V mEoumxm pocuo oh maoumxm honuo scum Q. Q. uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu --c xgmocsom m.Eoumxm O acosaogfi>cm m.Eoumxm 131 General Systems Theory can be used as a methodology whenever system approach to a given organized complexity is in concern. Characteristics of General Systems Theory are: interrelatedness and interdependence of objects, attributes and events, holism, goal seeking, inputs, throughputs, outputs, negentropy, entropy, regulation, hierarchy, suprasystem, differentiation, equifinality, boundaries, environment, feedback, etc. Models are the abstracts of a system and conceptual model theory has four distinct features: the organizing, the heuristic, the predictive and the mensurative. A dimension of evaluation corre- sponds to each of these four functions of the conceptual model theory in order to realize its organizing power, its fruitfulness, its stra— tegic value and its usability. Other characteristics of a good model are originality, simplicity and realism. Evolution of a successful model undergoes various stages where a line of communication between the real world and the symbolic world is necessary to understand a system within its environment and then represent it in the desired model. The line of communication in the design of a theoretical isomorphic system, represented in conceptual graphical models, can be between existing facts and information about the relevant inputs, throughputs, outputs, linkages, constraints, etc. to the system in question. A diagrammatical presentation of a system would include inputs, throughputs, outputs, boundary, environment, linkages, and subsystems. CHAPTER V FUNCTIONAL APPLICATION OF GENERAL SYSTEMS THEORY TO THE MECHANIZATION OF AGRICULTURE In this chapter the functional application of the systems approach, based on General Systems Theory to the Mechanization of Agriculture, is the concern. Seven conceptual-graphical models of a theoretical isomorphic system for the Mechanization of Agriculture for adults have been developed. Included in this chapter are the following six subsystems: l. The the 2. The 3. The 4. The 5. The 6. The subsystem for the Mechanization of Agriculture for production of soybeans, wheat, and corn; training subsystem; financing subsystem; maintenance subsystem; extension subsystem; and marketing subsystem. A Theoretical Isomorphic System for the Mechanization of Agriculture for Adults Figure 5.1 is a conceptual-graphical model of a theoretical isomorphic system for the Mechanization of Agriculture for adults. A systems approach based on the application of General Systems Theory 132 .mu~:u< you okay—sowum< mo :ouuauwaasoox you Ioumxm a mo dove: ~aowggauusqaauaou:ou < _.m ouzamm aeoleouq>cm _|. 1111111111111 Hagandumxwl II .II II .I.-J _ guaaaooa h . _ _, 133 An uzmuoxuaz ouau¢~auau M. : unisex» m_ang:< . nuances: than. . XIV ESE—us: . maoguo . An caumzouxm oeu>oua.\V. «soon . _o:=Oauoa . manna amass . AHHH‘ occasou:aaz usaguoz . o no em >uon: ouauqaouuu< use moouaomoa manna moogm m a m I we gawuaumeaguox madam“ H cacao: . mouse xuunzom . AHHHII » one 0 >0“; you noucoo < m~auuouox . u=ol=uo>ou . 0 > o «luau moon . «a cu , xmo—oeguob . «guano a== .auumao . manna sauce . ”gauges: can; . mined o—aauoao> . luau no mu~3s< swank no>quoonac . u—QS o moan". 595 . any: i? 6.436410% nougedgoo: 30: smauaaunm _ whamhzo mmmmmuoaa mp: :— 134 and Conceptual Model Theory is used to develop this theoretical system, which is comprised of six subsystems. In this theoretical system, inputs are transformed into outputs in order to establish a variety of new mechanized farms, along with supporting services. Attention is given to the goal, linkages, inputs, throughputs, outputs, feedbacks, constraints, boundary, and environment of such a system. Goal The goal for this proposed theoretical isomorphic system is the systematic Mechanization of Agriculture by mobilization of inputs, throughputs, and outputs to: 1. Establish new mechanized farms; 2. Train adults as farm managers, using the methods, on-the-job training and learning by doing; 3. Finance the farms in such a way that each adult may be able to buy a farm with reasonable monthly payments; 4. Supervise the farms for proper maintenance as long as needed; 5. Provide extension as life-long, non-formal education for adults; and 6. Facilitate marketing. Linkage The concept of linkage here is defined as the association of two or more systems, called systems co-actions, meaning related systems supporting each other toward their specific goals. In addition, the linkages of subsystems within a system themselves must be considered. 135 Universities, government, and international agencies, interested in agricultural and rural development, are other systems identified in this study which can make significant contributions to the success of the proposed system for the Mechanization of Agriculture for adults. Universities can contribute both in conducting relevant research, and by educating the necessary personnel for implementing such a system. The government can contribute by financing, introducing favorable agricultural policies, improving the roads, electrification of rural areas, providing land, storage facilities, fertilizers, etc., to facilitate the success of such a system in less developed areas. Inputs Inputs are everything that is ”put into" any given system, generally. Inputs are in the form of matter, energy, and information. Matter is anything that occupies space and constitutes the substance of the physical universe. Inputs identified in the system are: goals, objectives, land, capital, technology, materials, adults, ideas, methods, personnel, seeds, machinery, and animals. Throughputs Troughputs are processes which transform the inputs, according to a plan and procedures of operation, in order to attain desired out- puts by achieving’short-run objectives toward long-run goals. Through- puts in the system will be realized in (l) a center for Mechanization of Agriculture and (2) on the newly established mechanized farms under such a system. 136 Throughputs, in the center for the Mechanization of Agriculture, were identified as: (1) assessment, (2) diagnosis, (3) purchasing, (4) intervention, (5) development, (6) selection, (7) evaluation, and (8) accountability. In this system each input would be processed according to these eight criteria for decision making, and ultimately to the outputs. Outputs Outputs are whatever the system produces and sends back into its environment. Outputs can be in the form of matter, energy, information, trained individuals, products, etc. Outputs of the system under study were identified as: (1) grain farms, (2) dairy farms, (3) vegetable farms, (4) beef farms, (5) poultry farms, (6) sheep farms, (7) fruit farms, etc., and (8) farm managers. Feedback Sources of feedback may be from within and without the system. Feedback is the literal feeding back into the system, into its structure and processes, necessary evaluative information about the system, its activities, and its effect. Feedback enables the system to adjust and to correct its functions, based on the evaluations of its past performance toward equilibrium. Systems Boundary The systems boundary would separate whatever is within the system and whatever is without the system. The exchange of matter, energy, and information, are at their minimum level at the system's boundary. The system's boundary is identified by dotted lines in Figure 5.1. Constraints The constraints can be in two forms: internal and external. The internal constraints include misusing inputs and low quality transformation which ultimately downgrades the output. External constraints include the lack of inputs, socioccultural resistance to change, the lack of favorable national policies for the Mechani- zation of Agriculture, the lack of communication channels, etc. Possible constraints against the system under study were identified as the lack of capital, the lack of proper management, the lack of favorable policies, socio-cultural resistance to change, and an unfavorable environment. Environment The environment of the system will depend on where this system will be utilized and implemented. The environment certainly affects the inputs, throughputs, and outputs of the system; therefore; pre- liminary studies must be conducted to make planning judgments for implementing such a system in a given environment. The titles, authors, and publishers of some relevant literature are given in Appendix B. 138 Subsystem l--A Subsystem for the Mechanization of Agriculture for the Production of Soybeans, Wheat, and Corn Figure 5.2 is a conceptual-graphical model of the mechanization subsystem. Inputs are transformed into outputs in order to establish new mechanized farms for the production of soybeans, wheat, and corn, along with the supporting services. It can be viewed as a system in itself but when it is considered as part of the system for the Mechanization of Agriculture, it is a subsystem. 9221: Goals for this subsystem are (l) the systematic Mechanization of Agriculture for the production of soybeans, wheat, and corn. These three agricultural commodities are being chosen as a possible rotation, necessary when selecting a cropping system; and (2) to receive problem messages from the farms and to conduct solution messages to the farms. Linkages Linkages in this subsystem would be local resources and also other remote resources which can provide the necessary inputs as needed by this subsystem. Inputs Inputs are identified as objectives, capital, land, machinery, equipment, seeds, fertilizers, chemicals, water, adults, and a time schedule. 139 2:00 25 .32.: .mfixfixom we .5232203‘ no... loumxmgm as» .«o ~25: 33.330-34.30250 (-4 1393.15 ~.m 9.3a: 2.0.25.5 35 1.111111111111111 111111 [Saidmnmmmwlllltllllulllld guesses; _ awo<.mw: :UonCQ:::: — ....... A 9.33.3: 33:32\ 0 Au 333.-om 0% 3M... A :32.3xm 033.; V on; . a. o =qu 35 .32.: 35539.. . 0.... Eco 1.3 .32.: . oh . 33:35:: . «:32 . 8w. fiaonxom mo .8333: M A new onguozam ‘ .m 23213” “.0 .3326?!— 333 o «3.533. F .3". 1.3m 331.23: N ha 5.331.283. 23305 . 39.3.. .. 2333.5". . 3953.3. . 2: 3.6.5 03.5.5 2: 259m . 4% 392.33 . . A 30323: 53:29:: . 1.3". m: 32.3 chap... 3:3 . «auumuu o «In: ........ 3:39.30 . 131.209: 392 23333 JOQ fawc:: auassooa 1:25 xuo_o=:uob uacouuauzum xuo~o=sooh nanny—zu«~u< mound—aqua neu< u3u=uaoa uzou=ou 0.:eosum 91‘? ousuuzuum mu~31< moququogum mo>uuuomao mlw< 20auauasm WA 3 03< 2593. on e hogan. :33 . u:woa x; a:«:haoa . n moomuoaum Inna . m m fi. ‘ . u, a=mzqaak non o:u =0 . “OUhSOMQZ Qua-.08 o u=o§=o>ou o mouuwmuo>«:= . mc2“ zagwuv:xo IE“: I muoaa=ax o “macaw uo moouzom spam w to: you 2.20.3.5 . muzoaxamox bagauox . muaaa< eocaaah.. a3 3.5.5 3533.:— . was; . songs—.00: . _o==omuoa . ~auunao. v. at:- o o mxzaa . u=oa=Ao>oo . mouuwmuo>a:= . 305.... ms. 20: 30¢ mummmoczm Ollillllllllll'llll‘| 8:2: 149 Throughputs The throughputs are identified as assessment, processing of the applications, regulations, searching for new sources of money, keeping records, preparing financial statements, the evaluation of activities, and the reporting of the progress. The throughputs on the farm are identified as the planning, organizing and preparing for payments, predicting the time and problems, preparing the financial statements, making the payments, keeping the records, and evaluating the results. Output The output of this subsystem is identified as the farm owners managing a mechanized farm with reasonable monthly payments. Constraints The constraints against this subsystem's proper functioning may be identified as the lack of capital, the lack of proper management, socio-cultural resistance, and an unfavorable environment. The sub- system's boundary and feedback also are considered in the design of the training subsystem. Authors, titles, and publishers of some relevant literature to the credit subsystems are given in Appendix B. 150 Subsystem 4--The Subsystem for Proper Maintenance Figure 5.5 is a conceptual-graphical model of the subsystem for supervising the farms established within the context of the system for proper maintenance. Goals The goals in the maintenance subsystem are: (l) to supervise the farms for proper maintenance, and (2) to receive problem messages from the farms and conduct solution messages to the farms. Linkage The linkages in this subsystem are identified as local resources and remote resources for providing the necessary inputs for this subsystem. Inputs The inputs are identified as land, farm machinery, farm buildings, equipment, shop tools, farm records, and farm products. Throgghputs The throughputs in the maintenance subsystem are identified as assessment, observation, production, taking preventive action, the evaluation, the recommendations and reporting in order to see that on each farm land, the machinery, equipment, buildings, tools, records, and products are properly used, stored, maintained, repaired, replaced, recorded, and evaluated. 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