doi: 10.3934/jimo.2021158
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Outsourcing contract design for the green transformation of manufacturing systems under asymmetric information

Business School, SiChuan University, Chengdu 610065, China

* Corresponding author: Dong Cai

© 2021 The Author(s). Published by AIMS, LLC. This is an Open Access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Received  March 2021 Revised  June 2021 Early access September 2021

Fund Project: This research was funded by [National Natural Science Foundation of China] grant number [71871150] and [Project of Sichuan University Innovation Spark Project Library] grant number [2021CXC22]

Accepting that suppliers' capability for green transformation of manufacturing systems is private information and that the efforts made in the process of transformation invisibly involve private actions of buyers, we construct an outsourcing model including transformation services before project delivery and maintenance services within the warranty period after project delivery and research the optimal outsourcing contract design for buyers. We find that the buyer can design a set of contract menus, including fixed compensation and variable compensation related to the quantity of energy conservation and emission reduction (ECER), to identify suppliers with different transformation capabilities and encourage them to make the best efforts under asymmetric information. Second, to identify the suppliers' transformation capability, the buyer needs to pay information rent to the supplier with high transformation ability. Meanwhile, the existence of asymmetric information will make the supplier with low transformation ability exert insufficient effort, and the existence of asymmetric information will always reduce the buyer's expected utility. In addition, the example analysis shows that asymmetric information always reduces the expected number of ECERs of the buyer. Therefore, it is suggested that the government should consider screening the transformation ability of green technology suppliers, disclose to the market and recommend suppliers with high transformation ability to reduce the negative impact caused by asymmetric information.

Citation: Chun-xiang Guo, Dong Cai, Yu-yang Tan. Outsourcing contract design for the green transformation of manufacturing systems under asymmetric information. Journal of Industrial & Management Optimization, doi: 10.3934/jimo.2021158
References:
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A. Maccormack and A. Mishra, Managing the performance trade-offs from partner integration: Implications of contract choice in R & D Projects, Production and Operations Management, 24 (2015), 1552-1569.  doi: 10.1111/poms.12374.  Google Scholar

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Q. QiuL. CuiJ. Y. Shen and Y. Li, Optimal maintenance policy considering maintenance errors for systems operating under performance-based contracts, Computers and Industrial Engineering, 112 (2017), 147-155.  doi: 10.1016/j.cie.2017.08.025.  Google Scholar

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W. H. TsaiH. C. ChenJ. Y. LiuS. P. Chen and Y. S. Shen, Using activity-based costing to evaluate capital investments for green manufacturing systems, International Journal of Production Research, 49 (2011), 7275-7292.  doi: 10.1080/00207543.2010.537389.  Google Scholar

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C. WangG. Schmidt and V. D. R. Bo, Stage-gate contracts to screen agents with inside information, Decision Sciences, 49 (2018), 1156-1186.  doi: 10.1111/deci.12308.  Google Scholar

show all references

References:
[1]

L. Athias and S. Saussier, Are public private partnerships that rigid? And why? Evidence from price provisions in French toll road concession contracts, Transportation Research Part A: Policy and Practice, 111 (2018), 174-186.  doi: 10.1016/j.tra.2018.02.011.  Google Scholar

[2]

S. P. Chuang and C. L. Yang, Key success factors when implementing a green-manufacturing system, Production Planning and Control, 25 (2014), 923-937.  doi: 10.1080/09537287.2013.780314.  Google Scholar

[3]

B. Cao and J. Gao, Quality incentive contract with asymmetric process design quality information, Chinese Journal of Management Science, 26 (2018), 145-153.   Google Scholar

[4]

A. M. Deif, A system model for green manufacturing, Journal of Cleaner Production, 19 (2011), 1553-1559.  doi: 10.1016/j.jclepro.2011.05.022.  Google Scholar

[5]

A. Goli, E. B. Tirkolaee and N. S. Aydin, Fuzzy integrated cell formation and production scheduling considering automated guided vehicles and human factors, IEEE Transactions on Fuzzy Systems, (2021). doi: 10.1109/TFUZZ.2021.3053838.  Google Scholar

[6]

A. Goli and M. Alinaghian, A new mathematical model for production and delivery scheduling problem with common cycle in a supply chain with open-shop system, International Journal of Manufacturing Technology and Management, 34 (2020), 174-187.  doi: 10.1504/IJMTM.2020.10027948.  Google Scholar

[7]

K. L. HuiP. F. KeY. X. Yao and W. T. Yue, Bilateral liability-based contracts in information security outsourcing, Information Systems Research, 30 (2019), 411-429.  doi: 10.1287/isre.2018.0806.  Google Scholar

[8]

H. Huang and M. H. Hu, Contract design for IT outsourcing under asymmetric information, Chinese Journal of Management Science, (2020). Google Scholar

[9]

H. HuangL. M. LiuG. ParkerY. Tan and H. Y. Xu, Multi-attribute procurement auctions in the presence of satisfaction risk, Production and Operations Management, 28 (2019), 1206-1221.  doi: 10.1111/poms.12979.  Google Scholar

[10]

T. Jain, J. Hazra and T. C. E. Cheng, IT outsourcing and vendor cost improvement strategies under asymmetric information, Decision Sciences, (2020). doi: 10.1111/deci.12446.  Google Scholar

[11]

K. LiX. ZhangY. T. Leung and S. L. Yang, Parallel machine scheduling problems in green manufacturing industry, Journal of Manufacturing Systems, 38 (2016), 98-106.  doi: 10.1016/j.jmsy.2015.11.006.  Google Scholar

[12]

G. LiM. K. Lim and Z. Wang, Stakeholders, green manufacturing, and practice performance: Empirical evidence from Chinese fashion businesses, Annals of Operations Research, 290 (2020), 961-982.  doi: 10.1007/s10479-019-03157-7.  Google Scholar

[13]

H. M. LiuX. Y. Zhang and M. Y. Hu, Game-theory-based analysis of Energy Performance Contracting for building retrofits, Journal of Cleaner Production, 231 (2019), 1089-1099.   Google Scholar

[14]

C. LiuW. Chen and J. Mu, Retailer's multi-tier green procurement contract in the presence of suppliers' reference point effect, Production and Operations Management, 131 (2019), 242-258.  doi: 10.1016/j.cie.2019.03.013.  Google Scholar

[15] D. Li and L. B. Zhu, Guidelines for Cleaner Production in Industrial Enterprises, Science Press, Beijing, 2019.   Google Scholar
[16]

R. LotfiG. W. WeberS. M. Sajadifar and N. Mardani, Interdependent demand in the two-period newsvendor problem, Journal of Industrial and Management Optimization, 16 (2016), 117-140.  doi: 10.3934/jimo.2018143.  Google Scholar

[17]

R. LotfiZ. YadegariS. H. HosseiniA. H. Khameneh and G. W. Weber, A robust time-cost-quality-energy-environment trade-off with resource-constrained in project management: A case study for a bridge construction project, Journal of Industrial and Management Optimization, 13 (2020), 1-22.   Google Scholar

[18]

R. LotfiY. Z. MehrjerdiM. S. PishvaeeA. Sadegheih and G. W. Weber, A robust optimization model for sustainable and resilient closed-loop supply chain network design considering conditional value at risk, Numer. Algebra Control Optim., 11 (2021), 221-253.  doi: 10.3934/naco.2020023.  Google Scholar

[19]

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), 64-87.  doi: 10.4018/IJAL.2017010104.  Google Scholar

[20]

J. J. Laffont and J. Tirole, A Theory of Incentives in Procurement and Regulation, MIT Press Books, 1993. Google Scholar

[21]

V. Martínez-de-Albéniz and D. Simchi-Levi, A portfolio approach to procurement contracts, Production and Operations Management, 14 (2010), 90-114.   Google Scholar

[22]

A. Maccormack and A. Mishra, Managing the performance trade-offs from partner integration: Implications of contract choice in R & D Projects, Production and Operations Management, 24 (2015), 1552-1569.  doi: 10.1111/poms.12374.  Google Scholar

[23]

T. Paksoy and E. Ozceylan, Environmentally conscious optimization of supply chain networks, Journal of the Operational Research Society, 65 (2014), 855-872.  doi: 10.1057/jors.2012.95.  Google Scholar

[24]

T. PaksoyN. Y. Pehlivan and E. Ozceylan, Fuzzy multi-objective optimization of a green supply chain network with risk management that includes environmental hazards, Human and Ecological Risk Assessment, 18 (2012), 1120-1151.  doi: 10.1080/10807039.2012.707940.  Google Scholar

[25]

Q. QiuL. CuiJ. Y. Shen and Y. Li, Optimal maintenance policy considering maintenance errors for systems operating under performance-based contracts, Computers and Industrial Engineering, 112 (2017), 147-155.  doi: 10.1016/j.cie.2017.08.025.  Google Scholar

[26]

W. H. TsaiH. C. ChenJ. Y. LiuS. P. Chen and Y. S. Shen, Using activity-based costing to evaluate capital investments for green manufacturing systems, International Journal of Production Research, 49 (2011), 7275-7292.  doi: 10.1080/00207543.2010.537389.  Google Scholar

[27]

E. B. Tirkolaee and N. S. Aydn, A sustainable medical waste collection and transportation model for pandemics, Waste Management and Research, (2021). doi: 10.1177/0734242X211000437.  Google Scholar

[28]

E. B. TirkolaeeP. Abbasian and G. W. Weber, Sustainable fuzzy multi-trip location-routing problem for medical waste management during the COVID-19 outbreak, Science of The Total Environment, 10 (2020), 143607.   Google Scholar

[29]

C. WangG. Schmidt and V. D. R. Bo, Stage-gate contracts to screen agents with inside information, Decision Sciences, 49 (2018), 1156-1186.  doi: 10.1111/deci.12308.  Google Scholar

Figure 1.  Sequence of outsourcing events
Figure 2.  The influence of the probability that the contractor is a high type on the employer's expected number of ECERs
Figure 3.  The influence of the probability of the high-type contractor on the optimal incentive intensity and effort of the low-type contractor
Figure 4.  The influence of the gap of the contractor's transformation ability on the expected number of ECERs of the employer
Figure 5.  The influence of the gap of the transformation ability of the contractor on the optimal incentive intensity and optimal effort of the low-type contractor
Table 1.  Overview of the literature
Reference Objective Solution Conclusion
Deif [4] Design and improve green manufacturing systems A new model A comprehensive qualitative answer to the question.
Tsai et al. [26] Assist the justification of capital investments for green manufacturing systems (GMSs) Activity-based costing Provide insight into the value of capital investments for a GMS based ABC
Chuang et al. [2] Evaluate the performance of a green manufacturing system A new model The three-layer assessment model is practical
Li et al. [11] Scheduling problems that arise in green manufacturing companies Efficient heuristics Find a schedule that minimizes the total completion time
Li et al. [12] Enhance environmental awareness and green manufacturing practices Questionnaire investigation The importance of corporate stakeholders should be promoted
Lotfi et al. [16,17,18,19] Considers a closed-loop supply chain by taking into account sustainability, resilience, robustness, and risk aversion. Two stage mixed-integer linear programming model The robust counterpart provides a better estimation of related factors.
Goli et al. [5,6] Design a flexible-responsive manufacturing system with automatic material handling systems. A fuzzy mixed integer linear programming model Proposed algorithms have a high performance compared to CPLEX and other two well-known algorithms
Paksoy et al. [23,24] The optimization of supply chain structures considering both economic and environmental performances An integer nonlinear programming model Help decision makers find the optimal solution
Tirkolaee et al. [27,28] Try to explain and formulate the sustainable medical waste management problem for pandemics Proposed a biobjective MILP model Discuss the practical implications of the results
Cao et al. [3] Solve asymmetry information in outsourcing of production Contract theory Design a quality incentive contract
Wang et al. [29] Solve asymmetry information in outsourcing of R & D Stage-gate contracts The stage-gate contract can help offset the information asymmetry
Hui et al. [7] Solve asymmetry information in outsourcing of managed security services Bilateral liability-based contracts Bilateral liability-based contracts can work in the real world
Huang et al. [8] Contract design problem of IT service outsourcing Contract theory The optimal contract is designed to regulate IT suppliers effectively
This research Contract design problem of green transformation of manufacturing system outsourcing Outsourcing contract design Design a set of contract menus to resolve asymmetric information
Reference Objective Solution Conclusion
Deif [4] Design and improve green manufacturing systems A new model A comprehensive qualitative answer to the question.
Tsai et al. [26] Assist the justification of capital investments for green manufacturing systems (GMSs) Activity-based costing Provide insight into the value of capital investments for a GMS based ABC
Chuang et al. [2] Evaluate the performance of a green manufacturing system A new model The three-layer assessment model is practical
Li et al. [11] Scheduling problems that arise in green manufacturing companies Efficient heuristics Find a schedule that minimizes the total completion time
Li et al. [12] Enhance environmental awareness and green manufacturing practices Questionnaire investigation The importance of corporate stakeholders should be promoted
Lotfi et al. [16,17,18,19] Considers a closed-loop supply chain by taking into account sustainability, resilience, robustness, and risk aversion. Two stage mixed-integer linear programming model The robust counterpart provides a better estimation of related factors.
Goli et al. [5,6] Design a flexible-responsive manufacturing system with automatic material handling systems. A fuzzy mixed integer linear programming model Proposed algorithms have a high performance compared to CPLEX and other two well-known algorithms
Paksoy et al. [23,24] The optimization of supply chain structures considering both economic and environmental performances An integer nonlinear programming model Help decision makers find the optimal solution
Tirkolaee et al. [27,28] Try to explain and formulate the sustainable medical waste management problem for pandemics Proposed a biobjective MILP model Discuss the practical implications of the results
Cao et al. [3] Solve asymmetry information in outsourcing of production Contract theory Design a quality incentive contract
Wang et al. [29] Solve asymmetry information in outsourcing of R & D Stage-gate contracts The stage-gate contract can help offset the information asymmetry
Hui et al. [7] Solve asymmetry information in outsourcing of managed security services Bilateral liability-based contracts Bilateral liability-based contracts can work in the real world
Huang et al. [8] Contract design problem of IT service outsourcing Contract theory The optimal contract is designed to regulate IT suppliers effectively
This research Contract design problem of green transformation of manufacturing system outsourcing Outsourcing contract design Design a set of contract menus to resolve asymmetric information
Table 2.  The symbols involved
Symbols Definition
Decision variables
$ F $ Fixed remuneration provided by the employer to the contractor
$ f $ Unit reward of ECER exceeding the benchmark after system transformation
Parameters
$ \beta $ Capability parameters of the contractor's transformation system
$ i $ The types of contractors: high type (with higher transformation capacity $ {\beta _H} $) and low type (with low transformation capacity $ {\beta _L} $), $ i = H\;or\;L $
$ \rho $ The probability that the contractor is high
$ e $ Contractor's efforts to transform the system
$ r $ Number of ECERs achieved after system transformation
$ {r_0} $ The benchmark number of ECERs required by the employer according to relevant government or industry standards
$ n $ Failure number in warranty period after system transformation
$ \varepsilon $ The maximum number of failures in the warranty period after the completion of system transformation
$ c $ Total cost of the contractor's modification of the system
$ w $ The single maintenance cost
$ u $ Value coefficient of ECER quantity to the employer
$ v $ Sensitivity coefficient of the employer to the number of failures in the warranty period
Symbols Definition
Decision variables
$ F $ Fixed remuneration provided by the employer to the contractor
$ f $ Unit reward of ECER exceeding the benchmark after system transformation
Parameters
$ \beta $ Capability parameters of the contractor's transformation system
$ i $ The types of contractors: high type (with higher transformation capacity $ {\beta _H} $) and low type (with low transformation capacity $ {\beta _L} $), $ i = H\;or\;L $
$ \rho $ The probability that the contractor is high
$ e $ Contractor's efforts to transform the system
$ r $ Number of ECERs achieved after system transformation
$ {r_0} $ The benchmark number of ECERs required by the employer according to relevant government or industry standards
$ n $ Failure number in warranty period after system transformation
$ \varepsilon $ The maximum number of failures in the warranty period after the completion of system transformation
$ c $ Total cost of the contractor's modification of the system
$ w $ The single maintenance cost
$ u $ Value coefficient of ECER quantity to the employer
$ v $ Sensitivity coefficient of the employer to the number of failures in the warranty period
Table 3.  Optimal outsourcing contract of the employer in different situations
Situations High type Low type
Symmetric information $ \left\{ {F_H^{S{\rm{*}}}, f_H^{S{\rm{*}}}} \right\} $ $ \left\{ {F_L^{S*}, f_L^{S*}} \right\} $
Asymmetric information $ 0< u + v \le x $ $ \left\{ {F_H^{A{\rm{*}}}, f_H^{A{\rm{*}}}} \right\} $ $ \left\{ {F_L^{A{\rm{*}}}, f_{L1}^{A{\rm{*}}}} \right\} $
$ x< u + v $ $ \left\{ {F_L^{A{\rm{*}}}, f_{L2}^{A{\rm{*}}}} \right\} $
1 Among them, $f_{L1}^{A{\rm{*}}}{\rm{ = }}0$, $f_{L2}^{A{\rm{*}}}{\rm{ = }}\frac{{\left({1 - \rho } \right){\beta _L}\left({u{\rm{ + }}v} \right) - \rho \left({{\beta _H}{\rm{ + }}w{\beta _H} - {\beta _L} - w{\beta _L}} \right)}}{{\left({1 - \rho } \right){\beta _L}{\rm{ + }}\rho {\beta _H} - \rho {\beta _L}}}$, $x = \frac{{\rho {\beta _L}\left({{\beta _H}{\rm{ + }}w{\beta _H} - {\beta _L} - w{\beta _L}} \right)}}{{1 - \rho }}$
Situations High type Low type
Symmetric information $ \left\{ {F_H^{S{\rm{*}}}, f_H^{S{\rm{*}}}} \right\} $ $ \left\{ {F_L^{S*}, f_L^{S*}} \right\} $
Asymmetric information $ 0< u + v \le x $ $ \left\{ {F_H^{A{\rm{*}}}, f_H^{A{\rm{*}}}} \right\} $ $ \left\{ {F_L^{A{\rm{*}}}, f_{L1}^{A{\rm{*}}}} \right\} $
$ x< u + v $ $ \left\{ {F_L^{A{\rm{*}}}, f_{L2}^{A{\rm{*}}}} \right\} $
1 Among them, $f_{L1}^{A{\rm{*}}}{\rm{ = }}0$, $f_{L2}^{A{\rm{*}}}{\rm{ = }}\frac{{\left({1 - \rho } \right){\beta _L}\left({u{\rm{ + }}v} \right) - \rho \left({{\beta _H}{\rm{ + }}w{\beta _H} - {\beta _L} - w{\beta _L}} \right)}}{{\left({1 - \rho } \right){\beta _L}{\rm{ + }}\rho {\beta _H} - \rho {\beta _L}}}$, $x = \frac{{\rho {\beta _L}\left({{\beta _H}{\rm{ + }}w{\beta _H} - {\beta _L} - w{\beta _L}} \right)}}{{1 - \rho }}$
Table 4.  Optimal strategies of the employer under different circumstances
Circumstances Strategies
The information of contractor's transformation capability is symmetric Make the optimal outsourcing contract according to the type of contractor
The information of contractor's transformation capability is asymmetric Make a set of optimal outsourcing contract menu for contractors to choose from
Circumstances Strategies
The information of contractor's transformation capability is symmetric Make the optimal outsourcing contract according to the type of contractor
The information of contractor's transformation capability is asymmetric Make a set of optimal outsourcing contract menu for contractors to choose from
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