A carefully planned software development process helps in maintaining the quality of the software.In today’s scenario the primitive software development models have been replaced by the Agile based models like SCRUM,...A carefully planned software development process helps in maintaining the quality of the software.In today’s scenario the primitive software development models have been replaced by the Agile based models like SCRUM,KANBAN,LEAN,etc.Although,every framework has its own boon,the reason for widespread acceptance of the agile-based approach is its evolutionary nature that permits change in the path of software development.The development process occurs in iterative and incremental cycles called sprints.In SCRUM,which is one of the most widely used agile-based software development modeling framework;the sprint length is fixed throughout the process wherein;it is usually taken to be 1–4 weeks.But in practical application,the sprint length should be altered intuitively as per the requirement.To overcome this limitation,in this paper,a methodical work has been presented that determines the optimal sprint length based on two varied and yet connected attributes;the cost incurred and the work intensity required.The approach defines the number of tasks performed in each sprint along with the corresponding cost incurred in performing those tasks.Multi-attribute utility theory(MAUT),a multi-criterion decision making approach,has been utilized to find the required trade-off between two attributes under consideration.The proposed modeling framework has been validated using real life data set.With the use of the model,the optimal sprint for each sprint could be evaluated which was much shorter than the original length.Thus,the results obtained validate the proposal of a dynamic sprint length that can be determined before the start of each sprint.The structure would help in cost as well as time savings for a firm.展开更多
Strategic innovation diffusion converts newly created knowledge into increasing a firm’s value primarily through innovative product offerings.In this paper,we present a time-based adoption pattern with pricing and pr...Strategic innovation diffusion converts newly created knowledge into increasing a firm’s value primarily through innovative product offerings.In this paper,we present a time-based adoption pattern with pricing and promotional expenditure as a three-dimensional innovation diffusion model(3D-IDM).In our proposed 3D-IDM,we assume that value of the product plays a crucial role of being the major driver of diffusion,and is classified into the following three main factors:(1)continuation time of the product in the market–representing goodwill of the product;(2)price of the product–indicating consumers’buying behaviour;and(3)marketing efforts of the firm.A special form of the Cobb–Douglas production function is used to design the three-dimensional framework.An empirical study is performed on number of consumer-durable sales data to validate and compare the proposed model.Various performance measures are treated uniquely using the Mahalanobis distance-based approach(DBA)to determine the relative strength of each model.展开更多
The current research elucidates the advertising scheme of automotive innovation by incorporating the various stages of the product life cycle.The study proposes an empirical model for the automotive industry to evalua...The current research elucidates the advertising scheme of automotive innovation by incorporating the various stages of the product life cycle.The study proposes an empirical model for the automotive industry to evaluate a time-point known as a switch-point or a take-off point at which firms should modify the advertising and sales promotion strategies to boost sales volume.The problem applies a time-series innovation diffusion model wherein adoption rate changes when a product enters a growth stage and then again when the company stops the advertising campaign in the maturity stage.The present paper develops a profit maximization problem,which optimizes the overall advertising duration and advertising take-off point.A numerical illustration is provided using the actual sales data of automobile industries,and sensitivity analysis is further performed to validate the effect of critical parameters on the optimization problem.展开更多
文摘A carefully planned software development process helps in maintaining the quality of the software.In today’s scenario the primitive software development models have been replaced by the Agile based models like SCRUM,KANBAN,LEAN,etc.Although,every framework has its own boon,the reason for widespread acceptance of the agile-based approach is its evolutionary nature that permits change in the path of software development.The development process occurs in iterative and incremental cycles called sprints.In SCRUM,which is one of the most widely used agile-based software development modeling framework;the sprint length is fixed throughout the process wherein;it is usually taken to be 1–4 weeks.But in practical application,the sprint length should be altered intuitively as per the requirement.To overcome this limitation,in this paper,a methodical work has been presented that determines the optimal sprint length based on two varied and yet connected attributes;the cost incurred and the work intensity required.The approach defines the number of tasks performed in each sprint along with the corresponding cost incurred in performing those tasks.Multi-attribute utility theory(MAUT),a multi-criterion decision making approach,has been utilized to find the required trade-off between two attributes under consideration.The proposed modeling framework has been validated using real life data set.With the use of the model,the optimal sprint for each sprint could be evaluated which was much shorter than the original length.Thus,the results obtained validate the proposal of a dynamic sprint length that can be determined before the start of each sprint.The structure would help in cost as well as time savings for a firm.
文摘Strategic innovation diffusion converts newly created knowledge into increasing a firm’s value primarily through innovative product offerings.In this paper,we present a time-based adoption pattern with pricing and promotional expenditure as a three-dimensional innovation diffusion model(3D-IDM).In our proposed 3D-IDM,we assume that value of the product plays a crucial role of being the major driver of diffusion,and is classified into the following three main factors:(1)continuation time of the product in the market–representing goodwill of the product;(2)price of the product–indicating consumers’buying behaviour;and(3)marketing efforts of the firm.A special form of the Cobb–Douglas production function is used to design the three-dimensional framework.An empirical study is performed on number of consumer-durable sales data to validate and compare the proposed model.Various performance measures are treated uniquely using the Mahalanobis distance-based approach(DBA)to determine the relative strength of each model.
基金The research work presented in this paper is supported by the grants to the first and third authors from DST,via DST PURSE phase II,India.
文摘The current research elucidates the advertising scheme of automotive innovation by incorporating the various stages of the product life cycle.The study proposes an empirical model for the automotive industry to evaluate a time-point known as a switch-point or a take-off point at which firms should modify the advertising and sales promotion strategies to boost sales volume.The problem applies a time-series innovation diffusion model wherein adoption rate changes when a product enters a growth stage and then again when the company stops the advertising campaign in the maturity stage.The present paper develops a profit maximization problem,which optimizes the overall advertising duration and advertising take-off point.A numerical illustration is provided using the actual sales data of automobile industries,and sensitivity analysis is further performed to validate the effect of critical parameters on the optimization problem.
