Outsourcing software development has many advantages as well as inevitable risks. Of these risks, outsourcee se-lection is one of the most important. A wrong outsourcee selection may have severe adverse influence on t...Outsourcing software development has many advantages as well as inevitable risks. Of these risks, outsourcee se-lection is one of the most important. A wrong outsourcee selection may have severe adverse influence on the expected outcome of the project. We analyzed the risks involved in outsourcee selection and also provided methods to identify these risks. Using the principles of Analytical Hierarchy Process (AHP) and Cluster Analysis based on Group Decision Making, we established an index evaluation system to evaluate and select outsourcees. Real world applications of this system demonstrated its effectiveness in evaluating and selecting qualified outsourcees.展开更多
The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmu...The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmust be tailored to meet the dynamic needs of enterprises. However, internal research and development can beprohibitively expensive, driving many enterprises to outsource software development and upgrades to externalservice providers. This paper presents a software upgrade outsourcing model for enterprises and service providersthat accounts for the impact of market fluctuations on software adaptability. To mitigate the risk of adverseselection due to asymmetric information about the service provider’s cost and asymmetric information aboutthe enterprise’s revenues, we propose pay-per-time and revenue-sharing contracts in two distinct informationasymmetry scenarios. These two contracts specify the time and transfer payments for software upgrades. Througha comparative analysis of the optimal solutions under the two contracts and centralized decision-making withfull-information, we examine the characteristics of the solutions under two information asymmetry scenarios andanalyze the incentive effects of the two contracts on the various stakeholders. Overall, our study offers valuableinsights for firms seeking to optimize their outsourcing strategies and maximize their returns on investment insoftware upgrades.展开更多
Software maintenance is the process of fixing,modifying,and improving software deliverables after they are delivered to the client.Clients can benefit from offshore software maintenance outsourcing(OSMO)in different w...Software maintenance is the process of fixing,modifying,and improving software deliverables after they are delivered to the client.Clients can benefit from offshore software maintenance outsourcing(OSMO)in different ways,including time savings,cost savings,and improving the software quality and value.One of the hardest challenges for the OSMO vendor is to choose a suitable project among several clients’projects.The goal of the current study is to recommend a machine learning-based decision support system that OSMO vendors can utilize to forecast or assess the project of OSMO clients.The projects belong to OSMO vendors,having offices in developing countries while providing services to developed countries.In the current study,Extreme Learning Machine’s(ELM’s)variant called Deep Extreme Learning Machines(DELMs)is used.A novel dataset consisting of 195 projects data is proposed to train the model and to evaluate the overall efficiency of the proposed model.The proposed DELM’s based model evaluations achieved 90.017%training accuracy having a value with 1.412×10^(-3) Root Mean Square Error(RMSE)and 85.772%testing accuracy with 1.569×10^(-3) RMSE with five DELMs hidden layers.The results express that the suggested model has gained a notable recognition rate in comparison to any previous studies.The current study also concludes DELMs as the most applicable and useful technique for OSMO client’s project assessment.展开更多
The internal development and outsourced development of information systems have been studied intensively, but little research has been conducted on the joint development mode. This paper describes the benefits and pro...The internal development and outsourced development of information systems have been studied intensively, but little research has been conducted on the joint development mode. This paper describes the benefits and problems encountered in the joint development of accounting management information systems based on a real case. The case illustrates some distinct advantages, such as full control over the development schedule, the flexibility with resource allocation, and insurance for sustained active participation by the end-users. However, this development mode also involves potential problems, e.g., potential conflicts arising from diverse backgrounds and cultures of the various stakeholders and challenges to manage personnel from outside partners.展开更多
基金Project supported by the National Natural Science Foundation of China (No. 70571025), and Modern Information Management Re-search Center of Hubei Key Station for Humanities and Social Sci-ence (No. 200603), China
文摘Outsourcing software development has many advantages as well as inevitable risks. Of these risks, outsourcee se-lection is one of the most important. A wrong outsourcee selection may have severe adverse influence on the expected outcome of the project. We analyzed the risks involved in outsourcee selection and also provided methods to identify these risks. Using the principles of Analytical Hierarchy Process (AHP) and Cluster Analysis based on Group Decision Making, we established an index evaluation system to evaluate and select outsourcees. Real world applications of this system demonstrated its effectiveness in evaluating and selecting qualified outsourcees.
文摘The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmust be tailored to meet the dynamic needs of enterprises. However, internal research and development can beprohibitively expensive, driving many enterprises to outsource software development and upgrades to externalservice providers. This paper presents a software upgrade outsourcing model for enterprises and service providersthat accounts for the impact of market fluctuations on software adaptability. To mitigate the risk of adverseselection due to asymmetric information about the service provider’s cost and asymmetric information aboutthe enterprise’s revenues, we propose pay-per-time and revenue-sharing contracts in two distinct informationasymmetry scenarios. These two contracts specify the time and transfer payments for software upgrades. Througha comparative analysis of the optimal solutions under the two contracts and centralized decision-making withfull-information, we examine the characteristics of the solutions under two information asymmetry scenarios andanalyze the incentive effects of the two contracts on the various stakeholders. Overall, our study offers valuableinsights for firms seeking to optimize their outsourcing strategies and maximize their returns on investment insoftware upgrades.
基金fully funded by Universiti Teknologi Malaysia under the UTM Fundamental Research Grant(UTMFR)with Cost Center No Q.K130000.2556.21H14.
文摘Software maintenance is the process of fixing,modifying,and improving software deliverables after they are delivered to the client.Clients can benefit from offshore software maintenance outsourcing(OSMO)in different ways,including time savings,cost savings,and improving the software quality and value.One of the hardest challenges for the OSMO vendor is to choose a suitable project among several clients’projects.The goal of the current study is to recommend a machine learning-based decision support system that OSMO vendors can utilize to forecast or assess the project of OSMO clients.The projects belong to OSMO vendors,having offices in developing countries while providing services to developed countries.In the current study,Extreme Learning Machine’s(ELM’s)variant called Deep Extreme Learning Machines(DELMs)is used.A novel dataset consisting of 195 projects data is proposed to train the model and to evaluate the overall efficiency of the proposed model.The proposed DELM’s based model evaluations achieved 90.017%training accuracy having a value with 1.412×10^(-3) Root Mean Square Error(RMSE)and 85.772%testing accuracy with 1.569×10^(-3) RMSE with five DELMs hidden layers.The results express that the suggested model has gained a notable recognition rate in comparison to any previous studies.The current study also concludes DELMs as the most applicable and useful technique for OSMO client’s project assessment.
基金Supported partially by the National Natural Science Foundation of China (No. 70671103) a special grant from the Renmin Uni-versity of China
文摘The internal development and outsourced development of information systems have been studied intensively, but little research has been conducted on the joint development mode. This paper describes the benefits and problems encountered in the joint development of accounting management information systems based on a real case. The case illustrates some distinct advantages, such as full control over the development schedule, the flexibility with resource allocation, and insurance for sustained active participation by the end-users. However, this development mode also involves potential problems, e.g., potential conflicts arising from diverse backgrounds and cultures of the various stakeholders and challenges to manage personnel from outside partners.