How to extend the flexibility of the budget control to adapt for need of strategy management and management control is a difficult and very important problem. The purpose of this paper is to study tentatively this pro...How to extend the flexibility of the budget control to adapt for need of strategy management and management control is a difficult and very important problem. The purpose of this paper is to study tentatively this problem based on the extant results of controllability principle and budgeting in management control system of organization. In this paper, three main results are as follows： （1） To disclose that the controllability of an organization is one characteristic of the budgeting systems and the controllability is not impartial and not single personal action. （2） To discuss tentatively an improved budgeting system to improve the several weaknesses of traditional budgeting control that Otley （1999） summarized from the academic and practitioner literatures in order to improve the controllability of strategy management with budget flexibility. （3） To build the new model of flexible budget with three new features： it makes strategy objectives easily achievable and controllable; it makes controllers have a more strategic role; it can balance these multiple goals when they cannot be achieved simultaneously and external conditions are more demanding.展开更多
Design for six sigma （DFSS） is a powerful approach of designing products, processes, and services with the objective of meeting the needs of customers in a cost-effective maimer. DFSS activities are classified into ...Design for six sigma （DFSS） is a powerful approach of designing products, processes, and services with the objective of meeting the needs of customers in a cost-effective maimer. DFSS activities are classified into four major phases viz. identify, design, optimize, and validate （IDOV）. And an adaptive design for six sigma （ADFSS） incorporating the traits of artifidai intelligence and statistical techniques is presented. In the identify phase of the ADFSS, fuzzy relation measures between customer attributes （CAs） and engineering characteristics （ECs） as well as fuzzy correlation measures among ECs are determined with the aid of two fuzzy logic controllers （FLCs）. These two measures are then used to establish the cumulative impact factor for ECs. In the next phase （ i. e. design phase）, a transfer function is developed with the aid of robust multiple nonlinear regression analysis. Furthermore, 1this transfer function is optimized with the simulated annealing （ SA ） algorithm in the optimize phase. In the validate phase, t-test is conducted for the validation of the design resulted in earlier phase. Finally, a case study of a hypothetical writing instrument is simulated to test the efficacy of the proposed ADFSS.展开更多
文摘How to extend the flexibility of the budget control to adapt for need of strategy management and management control is a difficult and very important problem. The purpose of this paper is to study tentatively this problem based on the extant results of controllability principle and budgeting in management control system of organization. In this paper, three main results are as follows： （1） To disclose that the controllability of an organization is one characteristic of the budgeting systems and the controllability is not impartial and not single personal action. （2） To discuss tentatively an improved budgeting system to improve the several weaknesses of traditional budgeting control that Otley （1999） summarized from the academic and practitioner literatures in order to improve the controllability of strategy management with budget flexibility. （3） To build the new model of flexible budget with three new features： it makes strategy objectives easily achievable and controllable; it makes controllers have a more strategic role; it can balance these multiple goals when they cannot be achieved simultaneously and external conditions are more demanding.
基金Shanghai Leading Academic Discipline Project,China(No.B602)
文摘Design for six sigma （DFSS） is a powerful approach of designing products, processes, and services with the objective of meeting the needs of customers in a cost-effective maimer. DFSS activities are classified into four major phases viz. identify, design, optimize, and validate （IDOV）. And an adaptive design for six sigma （ADFSS） incorporating the traits of artifidai intelligence and statistical techniques is presented. In the identify phase of the ADFSS, fuzzy relation measures between customer attributes （CAs） and engineering characteristics （ECs） as well as fuzzy correlation measures among ECs are determined with the aid of two fuzzy logic controllers （FLCs）. These two measures are then used to establish the cumulative impact factor for ECs. In the next phase （ i. e. design phase）, a transfer function is developed with the aid of robust multiple nonlinear regression analysis. Furthermore, 1this transfer function is optimized with the simulated annealing （ SA ） algorithm in the optimize phase. In the validate phase, t-test is conducted for the validation of the design resulted in earlier phase. Finally, a case study of a hypothetical writing instrument is simulated to test the efficacy of the proposed ADFSS.
