netrashetty
Netra Shetty
Dean Foods (NYSE: DF) is an American food and beverage company with two operating divisions: Fresh Dairy Direct and WhiteWave-Morningstar.[2] The company maintains plants and distributors in the United States and the United Kingdom. Dean Foods products are sold throughout the USA.
nning of management science.
World War II posed many military, strategic, logistic, and tactical problems. Operations research teams of engineers, mathematicians, and statisticians were developed to use the scientific method to find solutions for many of these problems.
Nonmilitary management science applications developed rapidly after World War II. Based on quantitative methods developed during World War II, several new applications emerged. The development of the simplex method by George Dantzig in 1947 made application of linear programming practical. C. West Churchman, Russell Ackoff, and Leonard Arnoff made management science even more accessible by publishing the first operations research textbook in 1957.
Computer technology continues to play an integral role in management science. Practitioners and researchers are able to use ever-increasing computing power in conjunction with management science methods to solve larger and more complex problems. In addition, management scientists are constantly developing new algorithms and improving existing algorithms; these efforts also enable management scientists to solve larger and more complex problems.
BREADTH OF MANAGEMENT SCIENCE
TECHNIQUES
The scope of management science techniques is broad. These techniques include:
mathematical programming
linear programming
simplex method
dynamic programming
goal programming
integer programming
nonlinear programming
stochastic programming
Markov processes
queuing theory/waiting-line theory
transportation method
simulation
Management science techniques are used on a wide variety of problems from a vast array of applications. For example, integer programming has been used by baseball fans to allocate season tickets in a fair manner. When seven baseball fans purchased a pair of season tickets for the Seattle Mariners, the Mariners turned to management science and a computer program to assign games to each group member based on member priorities.
In marketing, optimal television scheduling has been determined using integer programming. Variables such as time slot, day of the week, show attributes, and competitive effects can be used to optimize the scheduling of programs. Optimal product designs based on consumer preferences have also been determined using integer programming.
Similarly, linear programming can be used in marketing research to help determine the timing of interviews. Such a model can determine the interviewing schedule that maximizes the overall response rate while providing appropriate representation across various demographics and household characteristics.
In the area of finance, management science can be employed to help determine optimal portfolio allocations, borrowing strategies, capital budgeting, asset allocations, and make-or-buy decisions. In portfolio allocations, for instance, linear programming can be used to help a financial manager select specific industries and investment vehicles (e.g., bonds versus stocks) in which to invest.
With regard to production scheduling, management science techniques can be applied to scheduling, inventory, and capacity problems. Production managers can deal with multi-period scheduling problems to develop low-cost production schedules. Production costs, inventory holding costs, and changes in production levels are among the types of variables that can be considered in such analyses.
Workforce assignment problems can also be solved with management science techniques. For example, when some personnel have been cross-trained and can work in more than one department, linear programming may be used to determine optimal staffing assignments.
Airports are frequently designed using queuing theory (to model the arrivals and departures of air-craft) and simulation (to simultaneously model the traffic on multiple runways). Such an analysis can yield information to be used in deciding how many runways to build and how many departing and arriving flights to allow by assessing the potential queues that can develop under various airport designs.
MATHEMATICAL PROGRAMMING
Mathematical programming deals with models comprised of an objective function and a set of constraints. Linear, integer, nonlinear, dynamic, goal, and stochastic programming are all types of mathematical programming.
An objective function is a mathematical expression of the quantity to be maximized or minimized. Manufacturers may wish to maximize production or minimize costs, advertisers may wish to maximize a product's exposure, and financial analysts may wish to maximize rate of return.
Constraints are mathematical expressions of restrictions that are placed on potential values of the objective function. Production may be constrained by the total amount of labor at hand and machine production capacity, an advertiser may be constrained by an advertising budget, and an investment portfolio may be restricted by the allowable risk.
LINEAR PROGRAMMING
Linear programming problems are a special class of mathematical programming problems for which the objective function and all constraints are linear. A classic example of the application of linear programming is the maximization of profits given various production or cost constraints.
Linear programming can be applied to a variety of business problems, such as marketing mix determination, financial decision making, production scheduling, workforce assignment, and resource blending. Such problems are generally solved using the "simplex method."
MEDIA SELECTION PROBLEM.
The local Chamber of Commerce periodically sponsors public service seminars and programs. Promotional plans are under way for this year's program. Advertising alternatives include television, radio, and newspaper. Audience estimates, costs, and maximum media usage limitations are shown in Exhibit 1.
If the promotional budget is limited to $18,200, how many commercial messages should be run on each medium to maximize total audience contact? Linear programming can find the answer.
SIMPLEX METHOD
The simplex method is a specific algebraic procedure for solving linear programming problems. The simplex method begins with simultaneous linear
Exhibit 1
Constraint Television Radio Newspaper
Audience per ad 100,000 18,000 40,000
Cost per ad 2,000 300 600
Maximum usage 10 20 10
equations and solves the equations by finding the best solution for the system of equations. This method first finds an initial basic feasible solution and then tries to find a better solution. A series of iterations results in an optimal solution.
SIMPLEX PROBLEM.
Georgia Television buys components that are used to manufacture two television models. One model is called High Quality and the other is called Medium Quality. A weekly production schedule needs to be developed given the following production considerations.
The High Quality model produces a gross profit of $125 per unit, and the Medium Quality model has a $75 gross profit. Only 180 hours of production time are available for the next time period. High Quality models require a total production time of six hours and Medium Quality models require eight hours. In addition, there are only forty-five Medium Quality components on hand.
To complicate matters, only 250 square feet of warehouse space can be used for new production. The High Quality model requires 9 square feet of space while the Medium Quality model requires 7 square feet.
Given the above situation, the simplex method can provide a solution for the production allocation of High Quality models and Medium Quality models.
mutually rewarding relationships with customers achieved via the total integration of information and quality management systems, service support, business strategy and organisational mission in order to delight the customer and secure profitable lasting business (Bennett, 1996). Relationship marketing is concerned with the development and maintenance of mutually beneficial relationships with strategically significant markets (Buttle, 1996) and whereby firm builds long term alliances with both prospective and current customers so that both buyer and seller work towards a common set of specified goals (Evans and Laskin, 1994). There give impetus to the necessary process of integrating the relationship marketing in order to identify and establish, maintain and enhance and when necessary also to terminate relationships with customers and other stakeholders, at the profit and make objectives of involved parties are met as done by means of mutual exchange and fulfillment of promises (Grönroos, 1994). The melting pot of relationship marketing draws on great variety of market theories and schools with marketing valence. In the long term, there improves market value and strength as interactive exchange with selected customers is engaged in relationship marketing.
Inter-relationships
The inter-relationship is enabled by the creation of trust in an electronic environment (Chadwick, 2001) from where better IMC process and relationship marketing is being recognize and business operations is most effective when marketing is of strength beyond what the three issues can give to make business worthwhile. Aside, as indicated by Allan and Chudry (2000, p. 82), that the Internet is an excellent channel for communicating with customers on an individual basis because of its immediate and direct interaction capability.
Henceforth, the integration of the issues in marketing is as important in electronic marketing as it is in the non-virtual world. The ultimate role of direct marketing is to gain effective response. The Internet has the advantage of being able to solicit such responses in real time and enables providers to interact with potential and actual consumers as well as enabling intra-customer communications. This interaction has sparked further debate on the possibility of one on one marketing (Caccavale, 2000) with view to developing strong and lasting relationships with loyal customers (Agrawal et al., 2001). Hence, interactive information-giving is essential as precursor to the transaction and be logical to suppose that the individualized and tailored messages/offers which are made possible by the Internet (Peppers and Rogers, 1993), the facility for better and stronger inter-relationship building. Chadwick (2001) suggests that the human factor in e-commerce is present in such communications from which trust can be gained, going as far as saying that “if consumers think they see signs of trust on e-marketing web sites, they will likely reciprocate with trust” (p. 657). Furthermore, people who wish to purchase using electronic marketing exhibit similar purchase behaviour to those who purchase in traditional environments. Having established a need, they search for information on products to satisfy that need. In today's environment, the trend is towards information excess, which can aid consumer's decision-making processes. Customers may use the Internet pre-purchase in an attempt to find unbiased information about their prospective purchase as found from company sponsored web pages. Like, information relating to the variety of products available, their relative quality and stock levels are important determinants in stimulating product and/or brand awareness (Luk et al., 2002). Indeed, most of the market-driven companies need to mine the data they obtain from customers as form of marketing research to better determine customer needs respectively. They also need to use click-stream data to learn how customers use their sites and why sales are abandoned and analyze the effectiveness of individual promotions.
Conclusion
Marketing success is driven by integrating concept functions within business organisation into production, sales and distribution, services, advertising, sales promotion, product planning and market research, achieving measurable business objectives as designed by top management to middle managers, all the way down to the workers. Therefore, it is important that market operations in the organisation can see the inter-relations among IMC, E-marketing and RM knowing such impact on the potential customers. Indeed, creating and aligning market relationships is necessary to improve performance of the company and business cycles. Companies must gain an understanding of how to develop and manage the relationships from boundaries of internal markets, such as suppliers and distributors. There requires considerable investigation as relational approach provides an alternative framework to the transactional marketing approach that has underpinned much of IMC thinking. So, the challenge for marketing practitioners and academics is to understand the linkages between antecedent factors affecting the implementation of marketing and appropriate managerial behaviours for successful market-based outcomes.
nning of management science.
World War II posed many military, strategic, logistic, and tactical problems. Operations research teams of engineers, mathematicians, and statisticians were developed to use the scientific method to find solutions for many of these problems.
Nonmilitary management science applications developed rapidly after World War II. Based on quantitative methods developed during World War II, several new applications emerged. The development of the simplex method by George Dantzig in 1947 made application of linear programming practical. C. West Churchman, Russell Ackoff, and Leonard Arnoff made management science even more accessible by publishing the first operations research textbook in 1957.
Computer technology continues to play an integral role in management science. Practitioners and researchers are able to use ever-increasing computing power in conjunction with management science methods to solve larger and more complex problems. In addition, management scientists are constantly developing new algorithms and improving existing algorithms; these efforts also enable management scientists to solve larger and more complex problems.
BREADTH OF MANAGEMENT SCIENCE
TECHNIQUES
The scope of management science techniques is broad. These techniques include:
mathematical programming
linear programming
simplex method
dynamic programming
goal programming
integer programming
nonlinear programming
stochastic programming
Markov processes
queuing theory/waiting-line theory
transportation method
simulation
Management science techniques are used on a wide variety of problems from a vast array of applications. For example, integer programming has been used by baseball fans to allocate season tickets in a fair manner. When seven baseball fans purchased a pair of season tickets for the Seattle Mariners, the Mariners turned to management science and a computer program to assign games to each group member based on member priorities.
In marketing, optimal television scheduling has been determined using integer programming. Variables such as time slot, day of the week, show attributes, and competitive effects can be used to optimize the scheduling of programs. Optimal product designs based on consumer preferences have also been determined using integer programming.
Similarly, linear programming can be used in marketing research to help determine the timing of interviews. Such a model can determine the interviewing schedule that maximizes the overall response rate while providing appropriate representation across various demographics and household characteristics.
In the area of finance, management science can be employed to help determine optimal portfolio allocations, borrowing strategies, capital budgeting, asset allocations, and make-or-buy decisions. In portfolio allocations, for instance, linear programming can be used to help a financial manager select specific industries and investment vehicles (e.g., bonds versus stocks) in which to invest.
With regard to production scheduling, management science techniques can be applied to scheduling, inventory, and capacity problems. Production managers can deal with multi-period scheduling problems to develop low-cost production schedules. Production costs, inventory holding costs, and changes in production levels are among the types of variables that can be considered in such analyses.
Workforce assignment problems can also be solved with management science techniques. For example, when some personnel have been cross-trained and can work in more than one department, linear programming may be used to determine optimal staffing assignments.
Airports are frequently designed using queuing theory (to model the arrivals and departures of air-craft) and simulation (to simultaneously model the traffic on multiple runways). Such an analysis can yield information to be used in deciding how many runways to build and how many departing and arriving flights to allow by assessing the potential queues that can develop under various airport designs.
MATHEMATICAL PROGRAMMING
Mathematical programming deals with models comprised of an objective function and a set of constraints. Linear, integer, nonlinear, dynamic, goal, and stochastic programming are all types of mathematical programming.
An objective function is a mathematical expression of the quantity to be maximized or minimized. Manufacturers may wish to maximize production or minimize costs, advertisers may wish to maximize a product's exposure, and financial analysts may wish to maximize rate of return.
Constraints are mathematical expressions of restrictions that are placed on potential values of the objective function. Production may be constrained by the total amount of labor at hand and machine production capacity, an advertiser may be constrained by an advertising budget, and an investment portfolio may be restricted by the allowable risk.
LINEAR PROGRAMMING
Linear programming problems are a special class of mathematical programming problems for which the objective function and all constraints are linear. A classic example of the application of linear programming is the maximization of profits given various production or cost constraints.
Linear programming can be applied to a variety of business problems, such as marketing mix determination, financial decision making, production scheduling, workforce assignment, and resource blending. Such problems are generally solved using the "simplex method."
MEDIA SELECTION PROBLEM.
The local Chamber of Commerce periodically sponsors public service seminars and programs. Promotional plans are under way for this year's program. Advertising alternatives include television, radio, and newspaper. Audience estimates, costs, and maximum media usage limitations are shown in Exhibit 1.
If the promotional budget is limited to $18,200, how many commercial messages should be run on each medium to maximize total audience contact? Linear programming can find the answer.
SIMPLEX METHOD
The simplex method is a specific algebraic procedure for solving linear programming problems. The simplex method begins with simultaneous linear
Exhibit 1
Constraint Television Radio Newspaper
Audience per ad 100,000 18,000 40,000
Cost per ad 2,000 300 600
Maximum usage 10 20 10
equations and solves the equations by finding the best solution for the system of equations. This method first finds an initial basic feasible solution and then tries to find a better solution. A series of iterations results in an optimal solution.
SIMPLEX PROBLEM.
Georgia Television buys components that are used to manufacture two television models. One model is called High Quality and the other is called Medium Quality. A weekly production schedule needs to be developed given the following production considerations.
The High Quality model produces a gross profit of $125 per unit, and the Medium Quality model has a $75 gross profit. Only 180 hours of production time are available for the next time period. High Quality models require a total production time of six hours and Medium Quality models require eight hours. In addition, there are only forty-five Medium Quality components on hand.
To complicate matters, only 250 square feet of warehouse space can be used for new production. The High Quality model requires 9 square feet of space while the Medium Quality model requires 7 square feet.
Given the above situation, the simplex method can provide a solution for the production allocation of High Quality models and Medium Quality models.
mutually rewarding relationships with customers achieved via the total integration of information and quality management systems, service support, business strategy and organisational mission in order to delight the customer and secure profitable lasting business (Bennett, 1996). Relationship marketing is concerned with the development and maintenance of mutually beneficial relationships with strategically significant markets (Buttle, 1996) and whereby firm builds long term alliances with both prospective and current customers so that both buyer and seller work towards a common set of specified goals (Evans and Laskin, 1994). There give impetus to the necessary process of integrating the relationship marketing in order to identify and establish, maintain and enhance and when necessary also to terminate relationships with customers and other stakeholders, at the profit and make objectives of involved parties are met as done by means of mutual exchange and fulfillment of promises (Grönroos, 1994). The melting pot of relationship marketing draws on great variety of market theories and schools with marketing valence. In the long term, there improves market value and strength as interactive exchange with selected customers is engaged in relationship marketing.
Inter-relationships
The inter-relationship is enabled by the creation of trust in an electronic environment (Chadwick, 2001) from where better IMC process and relationship marketing is being recognize and business operations is most effective when marketing is of strength beyond what the three issues can give to make business worthwhile. Aside, as indicated by Allan and Chudry (2000, p. 82), that the Internet is an excellent channel for communicating with customers on an individual basis because of its immediate and direct interaction capability.
Henceforth, the integration of the issues in marketing is as important in electronic marketing as it is in the non-virtual world. The ultimate role of direct marketing is to gain effective response. The Internet has the advantage of being able to solicit such responses in real time and enables providers to interact with potential and actual consumers as well as enabling intra-customer communications. This interaction has sparked further debate on the possibility of one on one marketing (Caccavale, 2000) with view to developing strong and lasting relationships with loyal customers (Agrawal et al., 2001). Hence, interactive information-giving is essential as precursor to the transaction and be logical to suppose that the individualized and tailored messages/offers which are made possible by the Internet (Peppers and Rogers, 1993), the facility for better and stronger inter-relationship building. Chadwick (2001) suggests that the human factor in e-commerce is present in such communications from which trust can be gained, going as far as saying that “if consumers think they see signs of trust on e-marketing web sites, they will likely reciprocate with trust” (p. 657). Furthermore, people who wish to purchase using electronic marketing exhibit similar purchase behaviour to those who purchase in traditional environments. Having established a need, they search for information on products to satisfy that need. In today's environment, the trend is towards information excess, which can aid consumer's decision-making processes. Customers may use the Internet pre-purchase in an attempt to find unbiased information about their prospective purchase as found from company sponsored web pages. Like, information relating to the variety of products available, their relative quality and stock levels are important determinants in stimulating product and/or brand awareness (Luk et al., 2002). Indeed, most of the market-driven companies need to mine the data they obtain from customers as form of marketing research to better determine customer needs respectively. They also need to use click-stream data to learn how customers use their sites and why sales are abandoned and analyze the effectiveness of individual promotions.
Conclusion
Marketing success is driven by integrating concept functions within business organisation into production, sales and distribution, services, advertising, sales promotion, product planning and market research, achieving measurable business objectives as designed by top management to middle managers, all the way down to the workers. Therefore, it is important that market operations in the organisation can see the inter-relations among IMC, E-marketing and RM knowing such impact on the potential customers. Indeed, creating and aligning market relationships is necessary to improve performance of the company and business cycles. Companies must gain an understanding of how to develop and manage the relationships from boundaries of internal markets, such as suppliers and distributors. There requires considerable investigation as relational approach provides an alternative framework to the transactional marketing approach that has underpinned much of IMC thinking. So, the challenge for marketing practitioners and academics is to understand the linkages between antecedent factors affecting the implementation of marketing and appropriate managerial behaviours for successful market-based outcomes.
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