市场营销 (双语) Chapter 8 Marketing Engineering
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Chapter 8 Marketing Engineering
8.1 Origin and Development of the Marketing Engineering
The marketing engineering is a systematic one, which can raise the correctness of the decision making and the benefits of the marketing input by way of integrating marketing knowledge, its data, issues, decision-making models, management systems, information and case banks, etc. so as to help the marketing decision-maker realize the streamlining, quantification, science, and normalization of the decision. Its origin and development have seen the following stages: (1) Application of the mathematic models in the marketing, which is represented by the book “Quantitative Technologies in Analyzing the Marketing” written by R. Frank, etc.; (2) Management information systems (1965). They are mainly embodied in the “Design of the Marketing Neurological Centre for the Enterprise” written by Philip Kotler;
By simulating calculation of the marketing activities, users can obtain correspondent results under different independent variables so as to make it convenient for enterprises to screen and optimize the marketing project. Nevertheless, the models built on the mathematic approaches have their limits, for they are set upon some hypotheses by abstracting the concrete marketing issues. In this way, the decision models for the marketing are not completely the copy of the actual ቤተ መጻሕፍቲ ባይዱhenomenon, but ideal ones based on certain limited conditions.
He explains eight market phenomena with eight figures. In the figures, X represents “inputs”, i.e., levels of the marketing efforts or independent variables; Y represents “outputs”, i.e., outcomes of the marketing efforts or dependent variables. The definition of the different figures is presented as follows: P1 says that outputs are zero when inputs are zero; P2 says that the linear relationship exists between inputs and outputs; P3 says that the returns decrease with the rise of inputs; P4 tells us that outputs can’t surpass a certain level; P5 says that the returns increase progressively with the rise of inputs; P6 says that as inputs increase, the returns increase at first, and then decrease; P7 says that before outputs are produced, inputs must surpass a certain degree; P8 shows us that outputs begin to decrease when inputs have got to a level. 3. Mathematic Model It is an approach in which the quantitative tools are used to analyze the marketing phenomenon and solve the marketing problems. In the marketing engineering, mathematic models are applied frequently.
8.2.3 Marketing Practice and Engineering Software
The marketing engineering software consists of typical marketing decision models and their analysis. It is the main tool for the decision makers, and not simply the statistic analysis software. The popularization of the marketing engineering software depends on its maturity, which does not need the construction of the decision models by makers themselves, but provides a comparatively perfect platform for them to analyze the key marketing variables and solve the related results in order to give them the reference and advice.
8.2 Connotation and Elements of the Marketing Engineering
8.2.1 Theoretic Bases of Marketing Engineering
The marketing theories are the foundation of the marketing engineering and analyzing the actual marketing issues. Practically, numerous marketing decision models are all based on the marketing theories, especially those created by Philip Kotler that provide an overall theoretic support for the marketing engineering, for example, 4Ps theories, 4Cs, etc.
(3) Decision-making calculation (1970). ADBUDG systems by John Little and CALLPLAN ones by Lodish are the typical of it; (4) Econometric models (1975); (5) Marketing decision support systems (1980). STRATPORT by Srinivasan and BEII by Gary L. Lilien are typical; (6) Marketing expert systems (1987). INFER by Arvind Rangaswamy and ADVISORY by Gary L. Lilien are well established; (7) Application of artificial neural network (1991); (8) Data digging. Since the beginning of the 21th century, the experts and scholars in the United States, European and Australia have made a deep and extensive investigation and study in the marketplace. The result proves that the marketing engineering, as decision-supporting tools, is playing an important role in marketing decision making. However, a relatively perfect decision method system is still to be improved, for the marketing engineering approaches remain in the decision model stage that can only make an analysis of some decision tasks and can’t simulate the operation of the whole marketing system.
8.2.2 Marketing Decision Models
1. Conceptual Model It is a kind of structure that can reflect the relationships among different parts in words and qualitatively depict the marketing phenomenon. For example, in his marketing process model, Philip Kotler divides various marketing activities into two parts, namely creating value for customers and building relationship with them, acquiring the value from customers as returns. 2. Graphic Model It is a model that describes and analyzes the marketing phenomenon with figures or tables (see Table 8.1, Figure 8.3). Table 8.1 makes a comparison to the collection method of the basic data and their concrete activities, by which we can distinctly understand the differences among various approaches. Figure 8.3 tells us some market-response models set by Saunders (1997).
8.1 Origin and Development of the Marketing Engineering
The marketing engineering is a systematic one, which can raise the correctness of the decision making and the benefits of the marketing input by way of integrating marketing knowledge, its data, issues, decision-making models, management systems, information and case banks, etc. so as to help the marketing decision-maker realize the streamlining, quantification, science, and normalization of the decision. Its origin and development have seen the following stages: (1) Application of the mathematic models in the marketing, which is represented by the book “Quantitative Technologies in Analyzing the Marketing” written by R. Frank, etc.; (2) Management information systems (1965). They are mainly embodied in the “Design of the Marketing Neurological Centre for the Enterprise” written by Philip Kotler;
By simulating calculation of the marketing activities, users can obtain correspondent results under different independent variables so as to make it convenient for enterprises to screen and optimize the marketing project. Nevertheless, the models built on the mathematic approaches have their limits, for they are set upon some hypotheses by abstracting the concrete marketing issues. In this way, the decision models for the marketing are not completely the copy of the actual ቤተ መጻሕፍቲ ባይዱhenomenon, but ideal ones based on certain limited conditions.
He explains eight market phenomena with eight figures. In the figures, X represents “inputs”, i.e., levels of the marketing efforts or independent variables; Y represents “outputs”, i.e., outcomes of the marketing efforts or dependent variables. The definition of the different figures is presented as follows: P1 says that outputs are zero when inputs are zero; P2 says that the linear relationship exists between inputs and outputs; P3 says that the returns decrease with the rise of inputs; P4 tells us that outputs can’t surpass a certain level; P5 says that the returns increase progressively with the rise of inputs; P6 says that as inputs increase, the returns increase at first, and then decrease; P7 says that before outputs are produced, inputs must surpass a certain degree; P8 shows us that outputs begin to decrease when inputs have got to a level. 3. Mathematic Model It is an approach in which the quantitative tools are used to analyze the marketing phenomenon and solve the marketing problems. In the marketing engineering, mathematic models are applied frequently.
8.2.3 Marketing Practice and Engineering Software
The marketing engineering software consists of typical marketing decision models and their analysis. It is the main tool for the decision makers, and not simply the statistic analysis software. The popularization of the marketing engineering software depends on its maturity, which does not need the construction of the decision models by makers themselves, but provides a comparatively perfect platform for them to analyze the key marketing variables and solve the related results in order to give them the reference and advice.
8.2 Connotation and Elements of the Marketing Engineering
8.2.1 Theoretic Bases of Marketing Engineering
The marketing theories are the foundation of the marketing engineering and analyzing the actual marketing issues. Practically, numerous marketing decision models are all based on the marketing theories, especially those created by Philip Kotler that provide an overall theoretic support for the marketing engineering, for example, 4Ps theories, 4Cs, etc.
(3) Decision-making calculation (1970). ADBUDG systems by John Little and CALLPLAN ones by Lodish are the typical of it; (4) Econometric models (1975); (5) Marketing decision support systems (1980). STRATPORT by Srinivasan and BEII by Gary L. Lilien are typical; (6) Marketing expert systems (1987). INFER by Arvind Rangaswamy and ADVISORY by Gary L. Lilien are well established; (7) Application of artificial neural network (1991); (8) Data digging. Since the beginning of the 21th century, the experts and scholars in the United States, European and Australia have made a deep and extensive investigation and study in the marketplace. The result proves that the marketing engineering, as decision-supporting tools, is playing an important role in marketing decision making. However, a relatively perfect decision method system is still to be improved, for the marketing engineering approaches remain in the decision model stage that can only make an analysis of some decision tasks and can’t simulate the operation of the whole marketing system.
8.2.2 Marketing Decision Models
1. Conceptual Model It is a kind of structure that can reflect the relationships among different parts in words and qualitatively depict the marketing phenomenon. For example, in his marketing process model, Philip Kotler divides various marketing activities into two parts, namely creating value for customers and building relationship with them, acquiring the value from customers as returns. 2. Graphic Model It is a model that describes and analyzes the marketing phenomenon with figures or tables (see Table 8.1, Figure 8.3). Table 8.1 makes a comparison to the collection method of the basic data and their concrete activities, by which we can distinctly understand the differences among various approaches. Figure 8.3 tells us some market-response models set by Saunders (1997).