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doi: 10.3934/jimo.2021165
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Effect of service quality on software sales and coordination mechanism in IT service supply chain

1. 

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

2. 

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

*Corresponding author: Tinghai Ren

Received  April 2021 Revised  July 2021 Early access September 2021

Currently, the upstream software developer usually cooperates with the downstream service provider to sell software and related services to client enterprises. Furthermore, the quality of pre-sale services provided by the provider has significant impact on software sales and on the performance of IT service supply chain (ITSSC). However, the existing research on IT service supply chain management (ITSSCM) lacks attention to this issue. In this study, we consider an ITSSC with a software developer, a service provider and client enterprises. Two scenarios are discussed in this study. Our study finds that the quality of pre-sale services provided by the provider and the price of extended warranty service (EWS) provided by the developer (in centralized decision-making (CDM)) are both higher than those in decentralized decision-making (DDM); when the sensitivity of clients to the software price is lower than a certain critical value, the software sales price (in CDM) is unexpectedly higher than that in DDM; however, when it is higher than the certain value, the software sales price (in CDM) is lower than that in DDM. Due to the double marginal effect between the developer and the provider, the total profit of ITSSC (in DDM) is always lower than that in CDM. By providing a combined coordination contract based on "guiding price $ + $ service cost sharing $ + $ product revenue sharing", not only the total profit of ITSSC can be increased, but also the profit of ITSSC members can be Pareto improved.

Citation: 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, doi: 10.3934/jimo.2021165
References:
[1]

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

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

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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.   Google Scholar

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X. ChenL. Li and M. Zhou, Manufacturer's pricing strategy for supply chain with warranty period-dependent demand, Omega, 40 (2012), 807-816.   Google Scholar

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X. ChenN. N. Wang and X. J. Wang, Flexibility and coordination in a supply chain with bidirectional option contracts and service requirement, International Journal of Production Economics, 193 (2017), 183-192.   Google Scholar

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B. DanS. G. Zhang and M. S. Zhou, Strategies for warranty service in a dual-channel supply chain with value-added service competition, International Journal of Production Research, 56 (2018), 5677-5699.   Google Scholar

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D. DebabrataF. Ming and Z. Conglei, Design and analysis of contracts for software outsourcing, Information Systems Research, 1 (2010), 93-114.   Google Scholar

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M. DeepaB. Anitesh and B. W. Andrew, Outsourcing contracts and equity prices, Information Systems Research, 24 (2013), 1028-1049.   Google Scholar

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B. EhsanK. Panos and F. Zhang, Delegation vs. control in supply chain procurement under competition, Production and Operations Management, 25 (2016), 1528-1541.   Google Scholar

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X. P. HongL. WangY. M. Gong and W. Y. 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.   Google Scholar

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K. KeumseokH. Jungpil and D. Prabuddha, Learning effect of domain, technology, and customer knowledge in information systems development: An empirical study, Information Systems Research, 28 (2017), 797-811.   Google Scholar

[19]

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

[20]

K. P. LiY. LiQ. N. 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.   Google Scholar

[21]

R. LotfiN. Mardani and G. W. Weber, Robust bi-level programming for renewable energy location, International Journal of Energy Research, 45 (2021), 7521-7534.   Google Scholar

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R. LotfiY. Z. Mehrjerdi and N. Mardani, A multi-objective and multi-product advertising billboard location model with attraction factor mathematical modeling and solutions, International Journal of Applied Logistics, 7 (2017), 64-86.   Google Scholar

[23]

R. LotfiM. NayeriS. Sajadifar and N. Mardani, Determination of start times and ordering Plans for two-period projects with interdependent demand in project-oriented organizations: A case study on molding industry, Journal of Project Management, 2 (2017), 119-142.   Google Scholar

[24]

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.   Google Scholar

[25]

L. NishthaA. S. Sandra and M. Tridas, Project managers' practical intelligence and project performance in software offshore outsourcing: A field study, Information Systems Research, 25 (2014), 364-384.   Google Scholar

[26]

A. K. SangaiahE. B. TirkolaeeA. Goli and S. Dehnavi-Arani, Robust optimization and mixed-integer linear programming model for LNG supply chain planning problem, Soft Computing, 24 (2020), 7885-7905.  doi: 10.1007/s00500-019-04010-6.  Google Scholar

[27]

S. SuprateekS. Saonoe and S. Arvin, Exploring value cocreation in relationships between an ERP vendor and its partners: A revelatory case study, Mis Quarterly, 1 (2012), 317-338.   Google Scholar

[28]

E. B. Tirkolaee, A. Goli, A. Faridnia, M. Soltani and G.-W. Weber, Multi-objective optimization for the reliable pollution-routing problem with cross-dock selection using Pareto-based algorithms, Journal of Cleaner Production, 276 (2020). doi: 10.1016/j.jclepro.2020.122927.  Google Scholar

[29]

V. ViswanathR. Arun and M. M. Likoebe, Information systems projects and individual developer outcomes: Role of projects managers and process control, Information Systems Research, 29 (2018), 127-148.   Google Scholar

[30]

B. WeberT. Fischer and René Riedl, Brain and autonomic nervous system activity measurement in software engineering: A systematic literature review, J. Systems & Software, 178 (2021), 1-51.   Google Scholar

[31]

Y. L. WangW. WallaceB. Shen and T. M. Choi, Service supply chain management: A review of operational models, European Journal of Operational Research, 247 (2015), 685-697.   Google Scholar

[32]

T. Xiao and T. Xu, Coordination price and service level decisions for a supply chain with deteriorating under vendor manange inventory, International J. Production Economics, 145 (2013), 743-752.   Google Scholar

[33]

W. Q. Xiao and Y. Xu, The impact of royalty contract revision in a multistage strategic research and development, Management Science, 12 (2012), 2251-2271.   Google Scholar

[34]

W. B. XieZ. B. JiangY. Zhao and X. Shao, Contract design for cooperative product service system with information asymmetry, International J. Production Research, 52 (2014), 1658-1680.   Google Scholar

[35]

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

[36]

H. Yili and A. P. Paul, On buyer selection of service providers in online outsourcing platforms for IT services., Information Systems Research, 28 (2017), 547-562.   Google Scholar

[37]

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

[38]

Cniteyes (2018). http://www.cniteyes.com/archives/33379. Google Scholar

[39]

Research Center for Mobile Informatization (2018). http://www.cniteyes.com/. Google Scholar

show all references

References:
[1]

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

[2]

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

[3]

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.   Google Scholar

[4]

X. ChenL. Li and M. Zhou, Manufacturer's pricing strategy for supply chain with warranty period-dependent demand, Omega, 40 (2012), 807-816.   Google Scholar

[5]

X. ChenN. N. Wang and X. J. Wang, Flexibility and coordination in a supply chain with bidirectional option contracts and service requirement, International Journal of Production Economics, 193 (2017), 183-192.   Google Scholar

[6]

B. DanS. G. Zhang and M. S. Zhou, Strategies for warranty service in a dual-channel supply chain with value-added service competition, International Journal of Production Research, 56 (2018), 5677-5699.   Google Scholar

[7]

D. DebabrataF. Ming and Z. Conglei, Design and analysis of contracts for software outsourcing, Information Systems Research, 1 (2010), 93-114.   Google Scholar

[8]

M. DeepaB. Anitesh and B. W. Andrew, Outsourcing contracts and equity prices, Information Systems Research, 24 (2013), 1028-1049.   Google Scholar

[9]

B. EhsanK. Panos and F. Zhang, Delegation vs. control in supply chain procurement under competition, Production and Operations Management, 25 (2016), 1528-1541.   Google Scholar

[10]

M. EsmaeiliN. S. Gamchi and E. Asgharizadeh, Three-level warranty service contract among manufacture, agent and customer: A game-theoretical approch, European J. Oper. Res., 239 (2014), 177-186.  doi: 10.1016/j.ejor.2014.04.045.  Google Scholar

[11]

Q. Feng and G. J. Shanthikumar, How research in production and operations management may evolve in the era of big data, Production and Operations Management, 9 (2018), 1670-1684.   Google Scholar

[12]

H. HaijingP. RemaS. Baohong and T. Rahul, 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.   Google Scholar

[13]

B. HeG. Li and M. Q. Liu, Impacts of decision sequences on a random yield supply chain with a service level requirement, Ann. Oper. Res., 268 (2018), 469-495.  doi: 10.1007/s10479-016-2275-4.  Google Scholar

[14]

J. Heydari, Coordination supplier's reorder point: A coordination mechanism for supply chains with long supplier lead time, Comput. Oper. Res., 48 (2014), 89-101.  doi: 10.1016/j.cor.2014.03.011.  Google Scholar

[15]

X. P. HongL. WangY. M. Gong and W. Y. 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.   Google Scholar

[16]

B. W. JaimeM. Likoebe and V. Viswanath, Technical systems development risk factors: The role of empowering leadership in lowering developers' stress, Information Systems Research, 28 (2017), 775-796.   Google Scholar

[17]

S. KalyanQ. Feng and G. Ram, Introduction to the special issue on perspectives on big data[J], Production and Operations Management, 9 (2018), 1639-1641.   Google Scholar

[18]

K. KeumseokH. Jungpil and D. Prabuddha, Learning effect of domain, technology, and customer knowledge in information systems development: An empirical study, Information Systems Research, 28 (2017), 797-811.   Google Scholar

[19]

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

[20]

K. P. LiY. LiQ. N. 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.   Google Scholar

[21]

R. LotfiN. Mardani and G. W. Weber, Robust bi-level programming for renewable energy location, International Journal of Energy Research, 45 (2021), 7521-7534.   Google Scholar

[22]

R. LotfiY. Z. Mehrjerdi and N. Mardani, A multi-objective and multi-product advertising billboard location model with attraction factor mathematical modeling and solutions, International Journal of Applied Logistics, 7 (2017), 64-86.   Google Scholar

[23]

R. LotfiM. NayeriS. Sajadifar and N. Mardani, Determination of start times and ordering Plans for two-period projects with interdependent demand in project-oriented organizations: A case study on molding industry, Journal of Project Management, 2 (2017), 119-142.   Google Scholar

[24]

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.   Google Scholar

[25]

L. NishthaA. S. Sandra and M. Tridas, Project managers' practical intelligence and project performance in software offshore outsourcing: A field study, Information Systems Research, 25 (2014), 364-384.   Google Scholar

[26]

A. K. SangaiahE. B. TirkolaeeA. Goli and S. Dehnavi-Arani, Robust optimization and mixed-integer linear programming model for LNG supply chain planning problem, Soft Computing, 24 (2020), 7885-7905.  doi: 10.1007/s00500-019-04010-6.  Google Scholar

[27]

S. SuprateekS. Saonoe and S. Arvin, Exploring value cocreation in relationships between an ERP vendor and its partners: A revelatory case study, Mis Quarterly, 1 (2012), 317-338.   Google Scholar

[28]

E. B. Tirkolaee, A. Goli, A. Faridnia, M. Soltani and G.-W. Weber, Multi-objective optimization for the reliable pollution-routing problem with cross-dock selection using Pareto-based algorithms, Journal of Cleaner Production, 276 (2020). doi: 10.1016/j.jclepro.2020.122927.  Google Scholar

[29]

V. ViswanathR. Arun and M. M. Likoebe, Information systems projects and individual developer outcomes: Role of projects managers and process control, Information Systems Research, 29 (2018), 127-148.   Google Scholar

[30]

B. WeberT. Fischer and René Riedl, Brain and autonomic nervous system activity measurement in software engineering: A systematic literature review, J. Systems & Software, 178 (2021), 1-51.   Google Scholar

[31]

Y. L. WangW. WallaceB. Shen and T. M. Choi, Service supply chain management: A review of operational models, European Journal of Operational Research, 247 (2015), 685-697.   Google Scholar

[32]

T. Xiao and T. Xu, Coordination price and service level decisions for a supply chain with deteriorating under vendor manange inventory, International J. Production Economics, 145 (2013), 743-752.   Google Scholar

[33]

W. Q. Xiao and Y. Xu, The impact of royalty contract revision in a multistage strategic research and development, Management Science, 12 (2012), 2251-2271.   Google Scholar

[34]

W. B. XieZ. B. JiangY. Zhao and X. Shao, Contract design for cooperative product service system with information asymmetry, International J. Production Research, 52 (2014), 1658-1680.   Google Scholar

[35]

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

[36]

H. Yili and A. P. Paul, On buyer selection of service providers in online outsourcing platforms for IT services., Information Systems Research, 28 (2017), 547-562.   Google Scholar

[37]

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

[38]

Cniteyes (2018). http://www.cniteyes.com/archives/33379. Google Scholar

[39]

Research Center for Mobile Informatization (2018). http://www.cniteyes.com/. Google Scholar

Figure 1.  The ITSSC structure
Figure 2.  The cooperation process and decision sequence
Figure 3.  The relationship between $ s^{C\ast} $, $ s^{D\ast} $ and $ b $
Figure 4.  The relationship between $ p_{p}^{C\ast} $, $ p_{p}^{D\ast} $ and $ b $
Figure 5.  The relationship between $ p_{s}^{C\ast} $, $ p_{s}^{D\ast} $ and $ b $
Figure 6.  The relationship between $ D_{p}^{C\ast} $, $ D_{p}^{D\ast} $ and $ b $
Figure 7.  The relationship between $ \pi^\text{TC} $, $ \pi^\text{TD} $ and $ b $
Figure 8.  The relationship between $ p^\text{D1}_{\text{g}} $ and $ \sigma $
Figure 9.  The relationship between ($ \pi^\text{TD} $, $ \pi^{TD1} $), ($ \pi ^\text{MD} $, $ \pi^{MD1} $, $ \pi^\text{RD} $, $ \pi^{RD1} $) and $ \sigma $
Table 1.  The literature related to IT service supply chain management
Topic type Reference Problem Research Method
ITSSCM Miranda and Kavan (2005) CPEO Optimization
Debabrate et al. (2010) CDO and CPEO. Optimization
Deepa et al. (2013) CDO and CSO. Empirical study
Yili and Paul (2017) Partner selection. Empirical study
Jamie et al. (2017) CPEO and SMM. Empirical study
Suprateek et al. (2012) Partner selection and VCR. Case study
Nishtha et al. (2014) CPEO and VCR. Field study
Keumseok et al. (2017) CPEO and VCR. Empirical study
Viswanath et al. (2018) CPEO and VCR. Empirical study
Haijing et al. (2018) CPEO and VCR. Empirical study
Topic type Reference Problem Research Method
ITSSCM Miranda and Kavan (2005) CPEO Optimization
Debabrate et al. (2010) CDO and CPEO. Optimization
Deepa et al. (2013) CDO and CSO. Empirical study
Yili and Paul (2017) Partner selection. Empirical study
Jamie et al. (2017) CPEO and SMM. Empirical study
Suprateek et al. (2012) Partner selection and VCR. Case study
Nishtha et al. (2014) CPEO and VCR. Field study
Keumseok et al. (2017) CPEO and VCR. Empirical study
Viswanath et al. (2018) CPEO and VCR. Empirical study
Haijing et al. (2018) CPEO and VCR. Empirical study
Table 2.  The literature related to optimization and mechanism design of PSSC
Topic type Reference Problem Research Method
Li et al. (2014) Service delivery model Optimization
Chen et al. (2017) Service delivery model; Product and service decision. Optimization
Dan et al. (2018) Service delivery model; Service decision. Optimization
Esmaeili et al. (2014) Product and service decision. Optimization
Li et al. (2019) Channel design; Service decision; Channel selection. Optimization
Hong et al. (2019) Service delivery model; Supply chain performance evaluation. Optimization
Xie et al. (2016) Demand information asymmetry; Product and service decision. Optimization
He et al. (2018) The random output; Constraint of service level; Service decision. Optimization
Chen et al. (2017) Product and service decision; PSSC coordination. Optimization; Coordination
Xiao and Xu (2013) R&D capability information asymmetry; PSSC coordination. Optimization; Coordination
Heydari (2014) Service decision; PSSC coordination. Optimization; Coordination
Xie et al. (2014) Service cost information asymmetry; Product and service decision. Optimization; Coordination
Topic type Reference Problem Research Method
Li et al. (2014) Service delivery model Optimization
Chen et al. (2017) Service delivery model; Product and service decision. Optimization
Dan et al. (2018) Service delivery model; Service decision. Optimization
Esmaeili et al. (2014) Product and service decision. Optimization
Li et al. (2019) Channel design; Service decision; Channel selection. Optimization
Hong et al. (2019) Service delivery model; Supply chain performance evaluation. Optimization
Xie et al. (2016) Demand information asymmetry; Product and service decision. Optimization
He et al. (2018) The random output; Constraint of service level; Service decision. Optimization
Chen et al. (2017) Product and service decision; PSSC coordination. Optimization; Coordination
Xiao and Xu (2013) R&D capability information asymmetry; PSSC coordination. Optimization; Coordination
Heydari (2014) Service decision; PSSC coordination. Optimization; Coordination
Xie et al. (2014) Service cost information asymmetry; Product and service decision. Optimization; Coordination
Table 3.  The relationship between the developer's decisions ($ p_{\text{g}}^{\ast} $) and ($ p_{s}^{D\ast} $, $ p_{s}^{C\ast} $) and parameters ($ c_{1} $, $ \gamma $)
Decisions Monotonicity on $ c_{1} $ Monotonicity on $ \gamma $
$ p_{\text{g}}^{\ast} $ $ \uparrow $ $ \uparrow $
$ p_{s}^{D\ast} $ $ \uparrow $ $ \downarrow $
$ p_{s}^{C\ast} $ $ \uparrow $ $ \downarrow $
Note: "$ \uparrow $" represents "increasing" and "$ \downarrow $" represents "decreasing".
Decisions Monotonicity on $ c_{1} $ Monotonicity on $ \gamma $
$ p_{\text{g}}^{\ast} $ $ \uparrow $ $ \uparrow $
$ p_{s}^{D\ast} $ $ \uparrow $ $ \downarrow $
$ p_{s}^{C\ast} $ $ \uparrow $ $ \downarrow $
Note: "$ \uparrow $" represents "increasing" and "$ \downarrow $" represents "decreasing".
Table 4.  The relationship between the provider's decisions ($ s^{C\ast } $, $ s^{D\ast} $) and ($ p_{p}^{C\ast} $, $ p_{p}^{D\ast} $) and parameters ($ c_{1} $, $ \gamma $)
Decisions Monotonicity on $ c_{1} $ Monotonicity on $ \gamma $
$ s^{C\ast} $ $ \downarrow $ $ \downarrow $
$ s^{D\ast} $ $ \downarrow $ $ \downarrow $
$ p_{p}^{C\ast} $ $ \downarrow, $ if $ {1}/{2}<b<1 $ $ \uparrow, $ if $ 1<b<{2}/{c_{1}} $ $ \downarrow, $ if $ {1}/{2}<b<1 $ $ \uparrow, $ if $ 1<b<{2}/{c_{1}} $
$ p_{p}^{D\ast} $ $ \downarrow, $ if $ {1}/{2}<b<1 $ $ \uparrow, $ if $ 1<b<{2}/{c_{1}} $ $ \downarrow, $ if $ {1}/{2}<b<1 $ $ \uparrow, $ if $ 1<b<{2}/{c_{1}} $
Note: "$ \uparrow $" represents "increasing" and "$ \downarrow $" represents "decreasing".
Decisions Monotonicity on $ c_{1} $ Monotonicity on $ \gamma $
$ s^{C\ast} $ $ \downarrow $ $ \downarrow $
$ s^{D\ast} $ $ \downarrow $ $ \downarrow $
$ p_{p}^{C\ast} $ $ \downarrow, $ if $ {1}/{2}<b<1 $ $ \uparrow, $ if $ 1<b<{2}/{c_{1}} $ $ \downarrow, $ if $ {1}/{2}<b<1 $ $ \uparrow, $ if $ 1<b<{2}/{c_{1}} $
$ p_{p}^{D\ast} $ $ \downarrow, $ if $ {1}/{2}<b<1 $ $ \uparrow, $ if $ 1<b<{2}/{c_{1}} $ $ \downarrow, $ if $ {1}/{2}<b<1 $ $ \uparrow, $ if $ 1<b<{2}/{c_{1}} $
Note: "$ \uparrow $" represents "increasing" and "$ \downarrow $" represents "decreasing".
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