doi: 10.3934/jimo.2021136
Online First

Online First articles are published articles within a journal that have not yet been assigned to a formal issue. This means they do not yet have a volume number, issue number, or page numbers assigned to them, however, they can still be found and cited using their DOI (Digital Object Identifier). Online First publication benefits the research community by making new scientific discoveries known as quickly as possible.

Readers can access Online First articles via the “Online First” tab for the selected journal.

Effects of channel encroachment on the software and service decisions in it supply chains

1. 

School of Business Administration, Guizhou University of Finance and Economics, Guiyang 550001, China

2. 

School of Economics and Management, Harbin Engineering University, Harbin 150001, China

* Corresponding author: Tinghai Ren

Received  December 2020 Revised  May 2021 Early access August 2021

Currently, many upstream software developers not only sell software through downstream service providers, but also directly sell it to clients. However, in the field of IT service supply chain management, there is a lack of research on the channel encroachment of software developers. In this study, we consider an IT service supply chain with a software developer, a service provider and client enterprises. Clients can either purchase the software (developed by the software developer) from the provider with a high price and additional pre-sale services, or directly purchase it from the developer with a low price but without pre-sale service. After purchasing the software, the clients can also purchase the extended warranty service from the developer. The study shows that the market size occupied by the developer and the intensity of competition between the two parties will neither affect the developer's product and service pricing decisions, nor influence the total demand for software products and extended warranty services, and thus will not impact his own profit. However, these factors will impact the provider's decisions for pre-sale service quality and software sales price, thereby affecting the provider's software demand and profit, and thus impact the performance of the supply chain. In addition, as the intensity of competition between both parties increases, the provider will simultaneously choose to reduce the pre-sales service quality and the software sales price to compete with the developer. Different from conclusions of the existing research on competition, we surprisingly observe that as the sensitivity of client enterprises to the extended warranty services price increases, both parties will increase the software price to compete. The encroachment of the developer will reduce the provider's software demand and profit, and thus lead to a decline in the performance of the supply chain. Therefore, the encroachment of the developer is an act of squeezing out partners by decreasing the profit of the provider, but without affecting his own profit.

Citation: Tinghai Ren, Nengmin Zeng, Dafei Wang, Shuwei Cheng. Effects of channel encroachment on the software and service decisions in it supply chains. Journal of Industrial & Management Optimization, doi: 10.3934/jimo.2021136
References:
[1]

H. Akkermans and B. Vos, Amplification in service supply chains: An exploratory case study from the telecom industry, Production and Operations Management, 12 (2003), 204-223.  doi: 10.1111/j.1937-5956.2003.tb00501.x.  Google Scholar

[2]

S. S. Ali, R. Kaur, D. J. Persis, R. Saha, M. Pattusamy and V. R. Sreedharan, Developing a hybrid evaluation approach for the low carbon performance on sustainable manufacturing environment, Annals of Operations Research, (2020), 1-33. doi: 10.1007/s10479-020-03877-1.  Google Scholar

[3]

F. Bernstein and A. Federgruen, Coordination mechanisms for supply chains under price and service competition, Manufacturing & Service Operations Management, 9 (2007), 242-262.  doi: 10.1287/msom.1070.0159.  Google Scholar

[4]

E. BolandifarP. Kouvelis and F. Zhang, Delegation vs. control in supply chain procurement under competition, Production and Operations Management, 25 (2016), 1528-1541.  doi: 10.1111/poms.12566.  Google Scholar

[5]

S. Boon-ittC. Y. Wong and C. W. Y. Wong, Service supply chain management process capabilities: Measurement development, International Journal of Production Economics, 193 (2017), 1-11.  doi: 10.1016/j.ijpe.2017.06.024.  Google Scholar

[6]

T. Boyaci and G. Gallego, Supply chain coordination in a market with customer service competition, Production and Operations Management, 13 (2004), 3-22.  doi: 10.1111/j.1937-5956.2004.tb00141.x.  Google Scholar

[7]

G. P. Cachon and M. A. Lariviere, Capacity allocation using past sales: When to turn-and-earn, Management Science, 45 (1999), 686-702.  doi: 10.1287/mnsc.45.5.685.  Google Scholar

[8]

J. Y. T. ChangE. T. G. WangJ. J. Jiang and G. Klein, Controlling ERP consultants: Client and provider practices, Journal of Systems and Software, 86 (2013), 1453-1461.  doi: 10.1016/j.jss.2013.01.030.  Google Scholar

[9]

Y.-K. Che and I. Gale, Optimal design of research contests, American Economic Review, 93 (2003), 646-671.  doi: 10.1257/000282803322157025.  Google Scholar

[10]

M. G. ChenQ. Y. Hu and H. Wei, Interaction of after-sales service provider and contract type in a supply chain, International Journal of Production Economics, 514 (2017), 1-527.  doi: 10.1016/j.ijpe.2017.04.001.  Google Scholar

[11]

X. ChenN. Wan and X. Wang, Flexibility and coordination in a supply chain with bidirectional option contracts and service requirement, International Journal of Production Economics, 193 (2017), 183-192.  doi: 10.1016/j.ijpe.2017.07.013.  Google Scholar

[12]

China Industry Information, Research report on SAP industry Operation status quo and Development Strategy in China, 2020-2026, https://www.chyxx.com/research/202003/843843.html, (2020). Google Scholar

[13]

D. W. ChoY. H. LeeS. H. Ahn and M. K. Hwang, A framework for measuring the performance of service of service supply chain management, Computers & Industrial Engineering, 62 (2012), 801-818.  doi: 10.1016/j.cie.2011.11.014.  Google Scholar

[14]

Cniteyes, Research center for mobile informatization, http://www.cniteyes.com/, (2018). Google Scholar

[15]

S. K. Das, M. Pervin, S. K. Roy and G. W. Weber, Multi-objective solid transportation-location problem with variable carbon emission in inventory management: A hybrid approach, Annals of Operations Research, (2021), 1-27. doi: 10.1007/s10479-020-03809-z.  Google Scholar

[16]

S. K. Das and S. K. Roy, Effect of variable carbon emission in a multi-objective transportation-p-facility location problem under neutrosophic environment, Computers & Industrial Enginee- ring, 132 (2019), 311-324. doi: 10.1016/j.cie.2019.04.037.  Google Scholar

[17]

S. K. DasS. K. Roy and G.-W. Weber, Application of type-2 Fuzzy logic to a multiobjective green solid transportation-location problem with dwell time under carbon tax, cap, and offset policy: Fuzzy Versus Nonfuzzy techniques, IEEE Transactions on Fuzzy Systems, 28 (2020), 2711-2725.  doi: 10.1109/TFUZZ.2020.3011745.  Google Scholar

[18]

P. S. DesaiO. Koenigsberg and D. Purohit, Forward buying by retailers, Journal of Marketing Research, 47 (2010), 90-102.  doi: 10.1509/jmkr.47.1.90.  Google Scholar

[19]

D. DeyM. Fan and C. Zhang, Design and analysis of contracts for software outsourcing, Information Systems Research, 21 (2010), 93-114.  doi: 10.1287/isre.1080.0223.  Google Scholar

[20]

Q. Feng and J. G. Shanthikumar, How research in production and operations management may evolve in the era of big data, Production and Operations Management, 27 (2018), 1670-1684.  doi: 10.1111/poms.12836.  Google Scholar

[21]

B. C. Giri and B. R. Sarker, Coordinating a two-echelon supply chain under production when retailers compete with price and service level, Operation Research, 16 (2016), 71-88.  doi: 10.1007/s12351-015-0187-8.  Google Scholar

[22]

Z. Guan, X. Zhang, M. Zhou and Y. Dan, Demand information sharing in competing supply chain with manufacturer-provided service, International Journal of Production Economics, 220 (2020), 107450. doi: 10.1016/j.ijpe.2019.07.023.  Google Scholar

[23]

H. HaoR. PadmanB. Sun and R. Telang, Quantifying the impact of social influence on the information technology implementation process by physicians: A hierarchical Bayesian learning approach, Information Systems Research, 29 (2018), 25-41.  doi: 10.1287/isre.2017.0746.  Google Scholar

[24]

B. HeG. Li and M. Liu, Impacts of decision sequences on a random yield supply chain with a service requirement, Annals Operation Research, 680 (2018), 469-495.  doi: 10.1007/s10479-016-2275-4.  Google Scholar

[25]

Y. Hong and P. A. Pavlou, On buyer selection of service providers in online outsourcing platforms for IT services, Information Systems Research, 28 (2017), 547-562.  doi: 10.1287/isre.2017.0709.  Google Scholar

[26]

X. HongL. WangY. Gong and W. Chen, What is the Role of value-added service in a remanufacturing closed-loop supply chain?, International Journal of Production Research, 58 (2020), 3342-3361.  doi: 10.1080/00207543.2019.1702230.  Google Scholar

[27]

S. HuangX. Guan and Y. J. Chen, Retailer information sharing with supplier encroachmen, Production and Operations Management, 1 (2018), 1-15.  doi: 10.1111/poms.12860.  Google Scholar

[28]

K. KangJ. Hahn and P. De, Learning effect of domain, technology, and customer knowledge in information systems development: An empirical study, Information Systems Research, 28 (2017), 797-811.  doi: 10.1287/isre.2017.0713.  Google Scholar

[29]

C. G. KorpeogluE. Körpeoǧlu and S.-H. Cho, Supply chain competition: A market game approach, Management Science, 66 (2020), 5648-5664.  doi: 10.1287/mnsc.2019.3511.  Google Scholar

[30]

H. Kurata and S.-H. Nam, After-sales service competition in a supply chain: Does uncertainty affect the conflict between profit maximization and customer satisfaction?, International Journal of Production Economics, 144 (2013), 268-280.  doi: 10.1016/j.ijpe.2013.02.014.  Google Scholar

[31]

N. LangerS. A. Slaughter and T. Mukhopadhyay, Project managers' practical intelligence and project performance in software offshore outsourcing: A field study, Information Systems Research, 25 (2014), 364-384.  doi: 10.1287/isre.2014.0523.  Google Scholar

[32]

G. LiF. F. HuangT. C. E. ChengQ. Zheng and P. Ji, Make-or-buy service capacity decision in a supply chain providing after-sales service, European Journal of Operational Research, 239 (2014), 377-388.  doi: 10.1016/j.ejor.2014.05.035.  Google Scholar

[33]

K. LiY. LiQ. Gu and A. Ingersoll, Joint effects remanufacturing channel design and after-sales service pricing: An analytical study, International Journal of Production Research, 57 (2019), 1066-1081.  doi: 10.1080/00207543.2018.1500722.  Google Scholar

[34]

X. Li and Q. Liu, Contract unobservability and downstream competition, Manufacturing & Service Operations Management, (2020), accept. doi: 10.1287/msom.2020.0905.  Google Scholar

[35]

Z. LiS. Gilbert and G. Lai, Supplier encroachment under asymmetric information, Management Science, 60 (2014), 449-462.  doi: 10.1287/mnsc.2013.1780.  Google Scholar

[36]

J. MaD. ZhangJ. Dong and Y. Tu, A supply chain network economic model with time-based competition, European Journal of Operational Research, 280 (2020), 889-908.  doi: 10.1016/j.ejor.2019.07.063.  Google Scholar

[37]

D. Mani, A. Barua and A. B. Whinston, Outsourcing contracts and equity prices, Information Systems Research, 24 (2013), 1028-1049. doi: 10.1287/isre.2013.0478.  Google Scholar

[38]

S. M. Miranda and C. B. Kavan, Monments of governance in is outsourcing: conceptualizing effects of contracts on value capture and creation, Journal of Information Technology, 20 (2005), 152-169.  doi: 10.1057/palgrave.jit.2000045.  Google Scholar

[39]

T. Paksoy, C. G. Kochan and S. S. Ali, Logistics 4.0: Digital Transformation of Supply Chain Management, CRC Press| Taylor & Francis Group, (2020), https://www.routledge.com/Logistics-40-Digital-Transformation-of-Supply-ChainManage-ment/Paksoy-Kochan-Ali/p/book/9780367340032. doi: 10.1201/9780429327636.  Google Scholar

[40]

X. QinQ. SuS. H. HuangU. J. Wiesma and M. Liu, Service quality coordination contracts for online shopping service supply chain with competing service providers: Integrating fairness and individual rationality, Operation Research, 19 (2019), 269-296.  doi: 10.1007/s12351-016-0288-z.  Google Scholar

[41]

K. RavindranA. SusarlaD. Mani and V. Gurbaxani, Social capital and contract duration in buyer-supplier networks for information technology outsourcing, Information Systems Research, 26 (2015), 379-397.  doi: 10.1287/isre.2015.0572.  Google Scholar

[42]

S. SarkerS. SarkerA. Sahaym and N. Bj$\phi$rn-Andersen, Exploring value cocreation in relationships between an ERP vendor and its partners: A revelatory case study, Mis Quarterly, 36 (2012), 317-338.  doi: 10.2307/41410419.  Google Scholar

[43]

S. Sen and T. S. Raghu, Interdependencies in IT infrastructure service: Analyzing service processes for optimal incentive design, Information Systems Research, 24 (2013), 822-841.  doi: 10.1287/isre.2013.0475.  Google Scholar

[44]

Shanghai Dashi Information Co., LTD. https://www.routledge.com/Logistics-40-Digital-Transformation-of-Supply-ChainManage-ment/Paksoy-Kochan-Ali/p/book/9780367340032, (2018). Google Scholar

[45]

K. SinghalQ. FengR. GaneshanN. R. Sanders and J. G. Shanthikumar, Introduction to the special issue on perspectives on big data, Production and Operations Management, 27 (2018), 1639-1641.  doi: 10.1111/poms.12939.  Google Scholar

[46]

E. Stavrulaki and M. M. Davis, A typology for service supply chains and its implications for strategic decisions, Service Science, 6 (2014), 34-46.  doi: 10.1287/serv.2014.0064.  Google Scholar

[47]

X. T. TangS. J. Fang and F. Cheng, Strategic interactions in service supply chain with horizontal competition, TOP, 22 (2014), 469-488.  doi: 10.1007/s11750-012-0265-5.  Google Scholar

[48]

A. A. Tsay and N. Agrawal, Channel dynamics under price and service competition, Manufacturing & Service Operations Management, 2 (2000), 372-391. doi: 10.1287/msom.2.4.372.12342.  Google Scholar

[49]

V. VenkateshA. Rai and L. M. Maruping, Information systems projects and individual developer outcomes: Role of projects managers and process control, Information Systems Research, 29 (2018), 127-148.  doi: 10.1287/isre.2017.0723.  Google Scholar

[50]

Y. WangS. W. WallaceB. Shen and T.-M. Choi, Service supply chain management: A review of operational models, European Journal of Operational Research, 247 (2015), 685-697.  doi: 10.1016/j.ejor.2015.05.053.  Google Scholar

[51]

J. B. WindelerL. Maruping and V. Venkatesh, Technical systems development risk factors: The role of empowering leadership in lowering developers' stress, Information Systems Research, 28 (2017), 775-796.  doi: 10.1287/isre.2017.0716.  Google Scholar

[52]

T. Xiao and D. Yang, Price and service competition of supply chains with risk-averse retailers under demand uncertainty, International Journal of Production Economics, 114 (2008), 187-200.  doi: 10.1016/j.ijpe.2008.01.006.  Google Scholar

[53]

W. Xiao and Y. Xu, The impact of royalty contract revision in a multistage strategic R & D alliance, Management Science, 58 (2012), 2251-2271.  doi: 10.1287/mnsc.1120.1552.  Google Scholar

[54]

W. XieZ. JiangY. Zhao and X. Shao, Contract design for cooperative product service system with information asymmetry, International Journal of Production Research, 52 (2014), 1658-1680.  doi: 10.1080/00207543.2013.847293.  Google Scholar

[55]

W. XieY. ZhaoZ. Jiang and P.-S. Chow, Optimizing product service system by franchise fee contracts under information asymmetry, Annals Operation Research, 240 (2016), 709-729.  doi: 10.1007/s10479-013-1505-2.  Google Scholar

[56]

D. Yang and T. Xiao, Coordination of supply chain with loss-averse consumers in service quality, International Journal of Production Research, 55 (2017), 3411-3430.  doi: 10.1080/00207543.2016.1241444.  Google Scholar

show all references

References:
[1]

H. Akkermans and B. Vos, Amplification in service supply chains: An exploratory case study from the telecom industry, Production and Operations Management, 12 (2003), 204-223.  doi: 10.1111/j.1937-5956.2003.tb00501.x.  Google Scholar

[2]

S. S. Ali, R. Kaur, D. J. Persis, R. Saha, M. Pattusamy and V. R. Sreedharan, Developing a hybrid evaluation approach for the low carbon performance on sustainable manufacturing environment, Annals of Operations Research, (2020), 1-33. doi: 10.1007/s10479-020-03877-1.  Google Scholar

[3]

F. Bernstein and A. Federgruen, Coordination mechanisms for supply chains under price and service competition, Manufacturing & Service Operations Management, 9 (2007), 242-262.  doi: 10.1287/msom.1070.0159.  Google Scholar

[4]

E. BolandifarP. Kouvelis and F. Zhang, Delegation vs. control in supply chain procurement under competition, Production and Operations Management, 25 (2016), 1528-1541.  doi: 10.1111/poms.12566.  Google Scholar

[5]

S. Boon-ittC. Y. Wong and C. W. Y. Wong, Service supply chain management process capabilities: Measurement development, International Journal of Production Economics, 193 (2017), 1-11.  doi: 10.1016/j.ijpe.2017.06.024.  Google Scholar

[6]

T. Boyaci and G. Gallego, Supply chain coordination in a market with customer service competition, Production and Operations Management, 13 (2004), 3-22.  doi: 10.1111/j.1937-5956.2004.tb00141.x.  Google Scholar

[7]

G. P. Cachon and M. A. Lariviere, Capacity allocation using past sales: When to turn-and-earn, Management Science, 45 (1999), 686-702.  doi: 10.1287/mnsc.45.5.685.  Google Scholar

[8]

J. Y. T. ChangE. T. G. WangJ. J. Jiang and G. Klein, Controlling ERP consultants: Client and provider practices, Journal of Systems and Software, 86 (2013), 1453-1461.  doi: 10.1016/j.jss.2013.01.030.  Google Scholar

[9]

Y.-K. Che and I. Gale, Optimal design of research contests, American Economic Review, 93 (2003), 646-671.  doi: 10.1257/000282803322157025.  Google Scholar

[10]

M. G. ChenQ. Y. Hu and H. Wei, Interaction of after-sales service provider and contract type in a supply chain, International Journal of Production Economics, 514 (2017), 1-527.  doi: 10.1016/j.ijpe.2017.04.001.  Google Scholar

[11]

X. ChenN. Wan and X. Wang, Flexibility and coordination in a supply chain with bidirectional option contracts and service requirement, International Journal of Production Economics, 193 (2017), 183-192.  doi: 10.1016/j.ijpe.2017.07.013.  Google Scholar

[12]

China Industry Information, Research report on SAP industry Operation status quo and Development Strategy in China, 2020-2026, https://www.chyxx.com/research/202003/843843.html, (2020). Google Scholar

[13]

D. W. ChoY. H. LeeS. H. Ahn and M. K. Hwang, A framework for measuring the performance of service of service supply chain management, Computers & Industrial Engineering, 62 (2012), 801-818.  doi: 10.1016/j.cie.2011.11.014.  Google Scholar

[14]

Cniteyes, Research center for mobile informatization, http://www.cniteyes.com/, (2018). Google Scholar

[15]

S. K. Das, M. Pervin, S. K. Roy and G. W. Weber, Multi-objective solid transportation-location problem with variable carbon emission in inventory management: A hybrid approach, Annals of Operations Research, (2021), 1-27. doi: 10.1007/s10479-020-03809-z.  Google Scholar

[16]

S. K. Das and S. K. Roy, Effect of variable carbon emission in a multi-objective transportation-p-facility location problem under neutrosophic environment, Computers & Industrial Enginee- ring, 132 (2019), 311-324. doi: 10.1016/j.cie.2019.04.037.  Google Scholar

[17]

S. K. DasS. K. Roy and G.-W. Weber, Application of type-2 Fuzzy logic to a multiobjective green solid transportation-location problem with dwell time under carbon tax, cap, and offset policy: Fuzzy Versus Nonfuzzy techniques, IEEE Transactions on Fuzzy Systems, 28 (2020), 2711-2725.  doi: 10.1109/TFUZZ.2020.3011745.  Google Scholar

[18]

P. S. DesaiO. Koenigsberg and D. Purohit, Forward buying by retailers, Journal of Marketing Research, 47 (2010), 90-102.  doi: 10.1509/jmkr.47.1.90.  Google Scholar

[19]

D. DeyM. Fan and C. Zhang, Design and analysis of contracts for software outsourcing, Information Systems Research, 21 (2010), 93-114.  doi: 10.1287/isre.1080.0223.  Google Scholar

[20]

Q. Feng and J. G. Shanthikumar, How research in production and operations management may evolve in the era of big data, Production and Operations Management, 27 (2018), 1670-1684.  doi: 10.1111/poms.12836.  Google Scholar

[21]

B. C. Giri and B. R. Sarker, Coordinating a two-echelon supply chain under production when retailers compete with price and service level, Operation Research, 16 (2016), 71-88.  doi: 10.1007/s12351-015-0187-8.  Google Scholar

[22]

Z. Guan, X. Zhang, M. Zhou and Y. Dan, Demand information sharing in competing supply chain with manufacturer-provided service, International Journal of Production Economics, 220 (2020), 107450. doi: 10.1016/j.ijpe.2019.07.023.  Google Scholar

[23]

H. HaoR. PadmanB. Sun and R. Telang, Quantifying the impact of social influence on the information technology implementation process by physicians: A hierarchical Bayesian learning approach, Information Systems Research, 29 (2018), 25-41.  doi: 10.1287/isre.2017.0746.  Google Scholar

[24]

B. HeG. Li and M. Liu, Impacts of decision sequences on a random yield supply chain with a service requirement, Annals Operation Research, 680 (2018), 469-495.  doi: 10.1007/s10479-016-2275-4.  Google Scholar

[25]

Y. Hong and P. A. Pavlou, On buyer selection of service providers in online outsourcing platforms for IT services, Information Systems Research, 28 (2017), 547-562.  doi: 10.1287/isre.2017.0709.  Google Scholar

[26]

X. HongL. WangY. Gong and W. Chen, What is the Role of value-added service in a remanufacturing closed-loop supply chain?, International Journal of Production Research, 58 (2020), 3342-3361.  doi: 10.1080/00207543.2019.1702230.  Google Scholar

[27]

S. HuangX. Guan and Y. J. Chen, Retailer information sharing with supplier encroachmen, Production and Operations Management, 1 (2018), 1-15.  doi: 10.1111/poms.12860.  Google Scholar

[28]

K. KangJ. Hahn and P. De, Learning effect of domain, technology, and customer knowledge in information systems development: An empirical study, Information Systems Research, 28 (2017), 797-811.  doi: 10.1287/isre.2017.0713.  Google Scholar

[29]

C. G. KorpeogluE. Körpeoǧlu and S.-H. Cho, Supply chain competition: A market game approach, Management Science, 66 (2020), 5648-5664.  doi: 10.1287/mnsc.2019.3511.  Google Scholar

[30]

H. Kurata and S.-H. Nam, After-sales service competition in a supply chain: Does uncertainty affect the conflict between profit maximization and customer satisfaction?, International Journal of Production Economics, 144 (2013), 268-280.  doi: 10.1016/j.ijpe.2013.02.014.  Google Scholar

[31]

N. LangerS. A. Slaughter and T. Mukhopadhyay, Project managers' practical intelligence and project performance in software offshore outsourcing: A field study, Information Systems Research, 25 (2014), 364-384.  doi: 10.1287/isre.2014.0523.  Google Scholar

[32]

G. LiF. F. HuangT. C. E. ChengQ. Zheng and P. Ji, Make-or-buy service capacity decision in a supply chain providing after-sales service, European Journal of Operational Research, 239 (2014), 377-388.  doi: 10.1016/j.ejor.2014.05.035.  Google Scholar

[33]

K. LiY. LiQ. Gu and A. Ingersoll, Joint effects remanufacturing channel design and after-sales service pricing: An analytical study, International Journal of Production Research, 57 (2019), 1066-1081.  doi: 10.1080/00207543.2018.1500722.  Google Scholar

[34]

X. Li and Q. Liu, Contract unobservability and downstream competition, Manufacturing & Service Operations Management, (2020), accept. doi: 10.1287/msom.2020.0905.  Google Scholar

[35]

Z. LiS. Gilbert and G. Lai, Supplier encroachment under asymmetric information, Management Science, 60 (2014), 449-462.  doi: 10.1287/mnsc.2013.1780.  Google Scholar

[36]

J. MaD. ZhangJ. Dong and Y. Tu, A supply chain network economic model with time-based competition, European Journal of Operational Research, 280 (2020), 889-908.  doi: 10.1016/j.ejor.2019.07.063.  Google Scholar

[37]

D. Mani, A. Barua and A. B. Whinston, Outsourcing contracts and equity prices, Information Systems Research, 24 (2013), 1028-1049. doi: 10.1287/isre.2013.0478.  Google Scholar

[38]

S. M. Miranda and C. B. Kavan, Monments of governance in is outsourcing: conceptualizing effects of contracts on value capture and creation, Journal of Information Technology, 20 (2005), 152-169.  doi: 10.1057/palgrave.jit.2000045.  Google Scholar

[39]

T. Paksoy, C. G. Kochan and S. S. Ali, Logistics 4.0: Digital Transformation of Supply Chain Management, CRC Press| Taylor & Francis Group, (2020), https://www.routledge.com/Logistics-40-Digital-Transformation-of-Supply-ChainManage-ment/Paksoy-Kochan-Ali/p/book/9780367340032. doi: 10.1201/9780429327636.  Google Scholar

[40]

X. QinQ. SuS. H. HuangU. J. Wiesma and M. Liu, Service quality coordination contracts for online shopping service supply chain with competing service providers: Integrating fairness and individual rationality, Operation Research, 19 (2019), 269-296.  doi: 10.1007/s12351-016-0288-z.  Google Scholar

[41]

K. RavindranA. SusarlaD. Mani and V. Gurbaxani, Social capital and contract duration in buyer-supplier networks for information technology outsourcing, Information Systems Research, 26 (2015), 379-397.  doi: 10.1287/isre.2015.0572.  Google Scholar

[42]

S. SarkerS. SarkerA. Sahaym and N. Bj$\phi$rn-Andersen, Exploring value cocreation in relationships between an ERP vendor and its partners: A revelatory case study, Mis Quarterly, 36 (2012), 317-338.  doi: 10.2307/41410419.  Google Scholar

[43]

S. Sen and T. S. Raghu, Interdependencies in IT infrastructure service: Analyzing service processes for optimal incentive design, Information Systems Research, 24 (2013), 822-841.  doi: 10.1287/isre.2013.0475.  Google Scholar

[44]

Shanghai Dashi Information Co., LTD. https://www.routledge.com/Logistics-40-Digital-Transformation-of-Supply-ChainManage-ment/Paksoy-Kochan-Ali/p/book/9780367340032, (2018). Google Scholar

[45]

K. SinghalQ. FengR. GaneshanN. R. Sanders and J. G. Shanthikumar, Introduction to the special issue on perspectives on big data, Production and Operations Management, 27 (2018), 1639-1641.  doi: 10.1111/poms.12939.  Google Scholar

[46]

E. Stavrulaki and M. M. Davis, A typology for service supply chains and its implications for strategic decisions, Service Science, 6 (2014), 34-46.  doi: 10.1287/serv.2014.0064.  Google Scholar

[47]

X. T. TangS. J. Fang and F. Cheng, Strategic interactions in service supply chain with horizontal competition, TOP, 22 (2014), 469-488.  doi: 10.1007/s11750-012-0265-5.  Google Scholar

[48]

A. A. Tsay and N. Agrawal, Channel dynamics under price and service competition, Manufacturing & Service Operations Management, 2 (2000), 372-391. doi: 10.1287/msom.2.4.372.12342.  Google Scholar

[49]

V. VenkateshA. Rai and L. M. Maruping, Information systems projects and individual developer outcomes: Role of projects managers and process control, Information Systems Research, 29 (2018), 127-148.  doi: 10.1287/isre.2017.0723.  Google Scholar

[50]

Y. WangS. W. WallaceB. Shen and T.-M. Choi, Service supply chain management: A review of operational models, European Journal of Operational Research, 247 (2015), 685-697.  doi: 10.1016/j.ejor.2015.05.053.  Google Scholar

[51]

J. B. WindelerL. Maruping and V. Venkatesh, Technical systems development risk factors: The role of empowering leadership in lowering developers' stress, Information Systems Research, 28 (2017), 775-796.  doi: 10.1287/isre.2017.0716.  Google Scholar

[52]

T. Xiao and D. Yang, Price and service competition of supply chains with risk-averse retailers under demand uncertainty, International Journal of Production Economics, 114 (2008), 187-200.  doi: 10.1016/j.ijpe.2008.01.006.  Google Scholar

[53]

W. Xiao and Y. Xu, The impact of royalty contract revision in a multistage strategic R & D alliance, Management Science, 58 (2012), 2251-2271.  doi: 10.1287/mnsc.1120.1552.  Google Scholar

[54]

W. XieZ. JiangY. Zhao and X. Shao, Contract design for cooperative product service system with information asymmetry, International Journal of Production Research, 52 (2014), 1658-1680.  doi: 10.1080/00207543.2013.847293.  Google Scholar

[55]

W. XieY. ZhaoZ. Jiang and P.-S. Chow, Optimizing product service system by franchise fee contracts under information asymmetry, Annals Operation Research, 240 (2016), 709-729.  doi: 10.1007/s10479-013-1505-2.  Google Scholar

[56]

D. Yang and T. Xiao, Coordination of supply chain with loss-averse consumers in service quality, International Journal of Production Research, 55 (2017), 3411-3430.  doi: 10.1080/00207543.2016.1241444.  Google Scholar

Figure 1.  The structure of IT service supply chain
Figure 2.  Timeline of the events
Figure 3.  Monotonicity of ($ p_{pm}^{\ast} $, $ p_{s}^{\ast} $, $ s^{\ast} $, $ p_{pr}^{\ast} $) on $ \alpha $
Figure 4.  Monotonicity of ($ p_{pm}^{\ast} $, $ p_{s}^{\ast} $, $ s^{\ast} $, $ p_{pr}^{\ast} $) on $ \sigma $
Figure 5.  Monotonicity of ($ D_{pm} $, $ D_{pr} $, $ D_{p} $, $ D_{s} $) on $ \alpha $
Figure 6.  Monotonicity of ($ D_{pm} $, $ D_{pr} $, $ D_{p} $, $ D_{s} $) on $ \sigma $
Figure 7.  Monotonicity of ($ \pi_{m} $, $ \pi_{r} $, $ \pi $) on $ \alpha $
Figure 8.  Monotonicity of ($ \pi_{m} $, $ \pi_{r} $, $ \pi $, $ D_{s} $) on $ \sigma $
Table 1.  The relationship between the equilibrium decision ($ p_{pm}^{\ast} $, $ p_{s}^{\ast} $, $ s^{\ast} $, $ p_{pr}^{\ast} $) and exogenous parameters ($ \alpha $, $ c_{1} $, $ \sigma $, $ \eta $)
Equilibrium decisions Exogenous parameters
Monotoni- city on $ \alpha $ Monotoni- city on $ c_{1} $ Monotoni- city on $ \sigma $ Monotoni- city on $ \eta $
$ p_{pm}^{\ast} $ - $ \uparrow $ - $ \uparrow $
$ s^{\ast} $ $ \downarrow $ $ \downarrow $ $ \downarrow $ $ \downarrow $
$ p_{s}^{\ast} $ - $ \uparrow $ - $ \downarrow $
$ p_{pr}^{\ast} $ $ \downarrow $ $ \uparrow $ $ \downarrow $ $ \uparrow $
Note: "$ \uparrow $" represents "increasing", "$ \downarrow $" represents "decreasing", and "-" represents irrelevance.
Equilibrium decisions Exogenous parameters
Monotoni- city on $ \alpha $ Monotoni- city on $ c_{1} $ Monotoni- city on $ \sigma $ Monotoni- city on $ \eta $
$ p_{pm}^{\ast} $ - $ \uparrow $ - $ \uparrow $
$ s^{\ast} $ $ \downarrow $ $ \downarrow $ $ \downarrow $ $ \downarrow $
$ p_{s}^{\ast} $ - $ \uparrow $ - $ \downarrow $
$ p_{pr}^{\ast} $ $ \downarrow $ $ \uparrow $ $ \downarrow $ $ \uparrow $
Note: "$ \uparrow $" represents "increasing", "$ \downarrow $" represents "decreasing", and "-" represents irrelevance.
Table 2.  The relationship between the demands ($ D_{pm} $, $ D_{pr} $, $ D_{p} $, $ D_{s} $) and exogenous parameters ($ \alpha $, $ c_{1} $, $ \sigma $, $ \eta $)
Software and service demand Exogenous parameters
Mono- toni- city on $ \alpha $ Mono- toni- city on $ c_{1} $ Mono- toni- city on $ \sigma $ Monotonicity on $ \eta $
$ D_{pm} $ $ \uparrow $ $ \downarrow $ $ \uparrow $ $ \downarrow $
$ D_{pr} $ $ \downarrow $ $ \downarrow $ $ \downarrow $ $ \downarrow $
$ D_{p} $ - $ \downarrow $ - $ \downarrow $
$ D_{s} $ - $ \downarrow $ - $\downarrow, \text{if} ~~\left\{\begin{array}{l}1 / 2 <\eta <1, \\ (1-\eta) / \eta <c_{1} <1 /[4 \eta(1-\eta)]\end{array}\right\}, \\ \uparrow, \text{if} ~~\left\{\begin{array}{l}1 / 2 <\eta <1 \\ 1 /[4 \eta(1-\eta)] <c_{1} <c_{0}\end{array}\right\}, \\ \downarrow, \text{if} ~~\left\{\begin{array}{l}\eta>1, \\ (1-\eta) / \eta <c_{1} <c_{0}\end{array}\right\} .$
Note: "$ \uparrow $" represents "increasing", "$ \downarrow $ " represents "decreasing", "-" represents irrelevance, and $ c_{0} =\min \frac{({3-4\alpha} )\eta +2\alpha -1}{\eta}, \frac{1}{2(1-\eta)} $.
Software and service demand Exogenous parameters
Mono- toni- city on $ \alpha $ Mono- toni- city on $ c_{1} $ Mono- toni- city on $ \sigma $ Monotonicity on $ \eta $
$ D_{pm} $ $ \uparrow $ $ \downarrow $ $ \uparrow $ $ \downarrow $
$ D_{pr} $ $ \downarrow $ $ \downarrow $ $ \downarrow $ $ \downarrow $
$ D_{p} $ - $ \downarrow $ - $ \downarrow $
$ D_{s} $ - $ \downarrow $ - $\downarrow, \text{if} ~~\left\{\begin{array}{l}1 / 2 <\eta <1, \\ (1-\eta) / \eta <c_{1} <1 /[4 \eta(1-\eta)]\end{array}\right\}, \\ \uparrow, \text{if} ~~\left\{\begin{array}{l}1 / 2 <\eta <1 \\ 1 /[4 \eta(1-\eta)] <c_{1} <c_{0}\end{array}\right\}, \\ \downarrow, \text{if} ~~\left\{\begin{array}{l}\eta>1, \\ (1-\eta) / \eta <c_{1} <c_{0}\end{array}\right\} .$
Note: "$ \uparrow $" represents "increasing", "$ \downarrow $ " represents "decreasing", "-" represents irrelevance, and $ c_{0} =\min \frac{({3-4\alpha} )\eta +2\alpha -1}{\eta}, \frac{1}{2(1-\eta)} $.
Table 3.  The relationship between the profits ($ \pi_{m} $, $ \pi_{r} $, $ \pi $) and the exogenous parameters ($ \alpha $, $ c_{1} $, $ \sigma $, $ \eta $)
Profit Exogenous parameters
Monotoni- city on $ \alpha $ Monotoni- city on $ c_{1} $ Monotoni- city on $ \sigma $ Monotoni- city on $ \eta $
$ \pi_{m} $ - $ \downarrow $ - $ \downarrow $
$ \pi_{r} $ $ \downarrow $ $ \downarrow $ $ \downarrow $ $ \downarrow $
$ \pi $ $ \downarrow $ $ \downarrow $ $ \downarrow $ $ \downarrow $
Note: "$ \uparrow $" represents "increasing", "$ \downarrow $ " represents "decreasing", and "-" represents irrelevance.
Profit Exogenous parameters
Monotoni- city on $ \alpha $ Monotoni- city on $ c_{1} $ Monotoni- city on $ \sigma $ Monotoni- city on $ \eta $
$ \pi_{m} $ - $ \downarrow $ - $ \downarrow $
$ \pi_{r} $ $ \downarrow $ $ \downarrow $ $ \downarrow $ $ \downarrow $
$ \pi $ $ \downarrow $ $ \downarrow $ $ \downarrow $ $ \downarrow $
Note: "$ \uparrow $" represents "increasing", "$ \downarrow $ " represents "decreasing", and "-" represents irrelevance.
[1]

Zonghong Cao, Jie Min. Selection and impact of decision mode of encroachment and retail service in a dual-channel supply chain. Journal of Industrial & Management Optimization, 2020  doi: 10.3934/jimo.2020167

[2]

Dingzhong Feng, Xiaofeng Zhang, Ye Zhang. Collection decisions and coordination in a closed-loop supply chain under recovery price and service competition. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021117

[3]

Yeong-Cheng Liou, Siegfried Schaible, Jen-Chih Yao. Supply chain inventory management via a Stackelberg equilibrium. Journal of Industrial & Management Optimization, 2006, 2 (1) : 81-94. doi: 10.3934/jimo.2006.2.81

[4]

Fei Cheng, Shanlin Yang, Ram Akella, Xiaoting Tang. An integrated approach for selection of service vendors in service supply chain. Journal of Industrial & Management Optimization, 2011, 7 (4) : 907-925. doi: 10.3934/jimo.2011.7.907

[5]

Tinghai Ren, Kaifu Yuan, Dafei Wang, Nengmin Zeng. Effect of service quality on software sales and coordination mechanism in IT service supply chain. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021165

[6]

Suresh P. Sethi, Houmin Yan, Hanqin Zhang, Jing Zhou. Information Updated Supply Chain with Service-Level Constraints. Journal of Industrial & Management Optimization, 2005, 1 (4) : 513-531. doi: 10.3934/jimo.2005.1.513

[7]

Xiaohui Ren, Daofang Chang, Jin Shen. Optimization of the product service supply chain under the influence of presale services. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021130

[8]

Qiang Lin, Ying Peng, Ying Hu. Supplier financing service decisions for a capital-constrained supply chain: Trade credit vs. combined credit financing. Journal of Industrial & Management Optimization, 2020, 16 (4) : 1731-1752. doi: 10.3934/jimo.2019026

[9]

Jing Shi, Tiaojun Xiao. Service investment and consumer returns policy in a vendor-managed inventory supply chain. Journal of Industrial & Management Optimization, 2015, 11 (2) : 439-459. doi: 10.3934/jimo.2015.11.439

[10]

Bin Dan, Huali Gao, Yang Zhang, Ru Liu, Songxuan Ma. Integrated order acceptance and scheduling decision making in product service supply chain with hard time windows constraints. Journal of Industrial & Management Optimization, 2018, 14 (1) : 165-182. doi: 10.3934/jimo.2017041

[11]

Jun Tu, Zijiao Sun, Min Huang. Supply chain coordination considering e-tailer's promotion effort and logistics provider's service effort. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021062

[12]

Weihua Liu, Xinran Shen, Di Wang, Jingkun Wang. Order allocation model in logistics service supply chain with demand updating and inequity aversion: A perspective of two option contracts comparison. Journal of Industrial & Management Optimization, 2021, 17 (6) : 3269-3295. doi: 10.3934/jimo.2020118

[13]

Amin Aalaei, Hamid Davoudpour. Two bounds for integrating the virtual dynamic cellular manufacturing problem into supply chain management. Journal of Industrial & Management Optimization, 2016, 12 (3) : 907-930. doi: 10.3934/jimo.2016.12.907

[14]

Jun Li, Hairong Feng, Kun-Jen Chung. Using the algebraic approach to determine the replenishment optimal policy with defective products, backlog and delay of payments in the supply chain management. Journal of Industrial & Management Optimization, 2012, 8 (1) : 263-269. doi: 10.3934/jimo.2012.8.263

[15]

Hongxia Sun, Yao Wan, Yu Li, Linlin Zhang, Zhen Zhou. Competition in a dual-channel supply chain considering duopolistic retailers with different behaviours. Journal of Industrial & Management Optimization, 2021, 17 (2) : 601-631. doi: 10.3934/jimo.2019125

[16]

Bin Chen, Wenying Xie, Fuyou Huang, Juan He. Quality competition and coordination in a VMI supply chain with two risk-averse manufacturers. Journal of Industrial & Management Optimization, 2021, 17 (5) : 2903-2924. doi: 10.3934/jimo.2020100

[17]

Jiuping Xu, Pei Wei. Production-distribution planning of construction supply chain management under fuzzy random environment for large-scale construction projects. Journal of Industrial & Management Optimization, 2013, 9 (1) : 31-56. doi: 10.3934/jimo.2013.9.31

[18]

Jun Wu, Shouyang Wang, Wuyi Yue. Supply contract model with service level constraint. Journal of Industrial & Management Optimization, 2005, 1 (3) : 275-287. doi: 10.3934/jimo.2005.1.275

[19]

Zhiping Zhou, Xinbao Liu, Jun Pei, Panos M. Pardalos, Hao Cheng. Competition of pricing and service investment between iot-based and traditional manufacturers. Journal of Industrial & Management Optimization, 2018, 14 (3) : 1203-1218. doi: 10.3934/jimo.2018006

[20]

Juliang Zhang, Jian Chen. Information sharing in a make-to-stock supply chain. Journal of Industrial & Management Optimization, 2014, 10 (4) : 1169-1189. doi: 10.3934/jimo.2014.10.1169

2020 Impact Factor: 1.801

Metrics

  • PDF downloads (76)
  • HTML views (149)
  • Cited by (0)

Other articles
by authors

[Back to Top]