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Effect of timing on reliability improvement and ordering decisions in a decentralized assembly system

  • S.I.: Statistical Reliability Modeling and Optimization
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Abstract

In this study, we investigate a decentralized assembly system in which the suppliers are unreliable and have uncertain production capacities. We focus on the case in which a manufacturer deals with two suppliers that provide complementary products. We assume that the suppliers have the opportunity to improve their reliabilities through investments. The manufacturer determines her order quantities and the suppliers decide on their investment amounts in their capacities. The timing of the decisions has a substantial effect on the optimal behaviors of the players. We investigate the problem under four different settings based on the sequence of events: (1) simultaneous ordering and investment in which decisions are made concurrently, (2) ordering after observation of capacities in which the manufacturer orders after observing the suppliers’ capacities, (3) ordering before realization of capacities in which the manufacturer orders after the suppliers’ investment decisions, and (4) ordering before investments in which the suppliers invest after the manufacturer’s ordering decision. We demonstrate the existence of a Pareto optimal equilibrium in the first two scenarios. In addition, we show that in the fourth scenario, there exists a unique Nash equilibrium in the suppliers’ game. Based on the realized capacities of the suppliers, it may be beneficial for them to share their production information with the manufacturer. In addition, we indicate that using a sequential decision strategy can enhance the performances of the supply chain and the members. When the suppliers are the leaders, they implement investment inflation strategies to stimulate the manufacturer to place larger orders. When the manufacturer is the leader, she uses an order inflation strategy to increase the investment of the suppliers. Our numerical analysis revealed that in different situations, the players may prefer ordering before realization of capacities scenario or ordering before investments. Finally, we extended our results to a multiple-suppliers case in which the suppliers are identical.

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References

  • Arifoglu, K., & Özekici, S. (2010). Optimal policies for inventory systems with finite capacity and partially observed Markov-modulated demand and supply processes. European Journal of Operational Research, 204(3), 421–438.

    Google Scholar 

  • Atan, Z., Ahmadi, T., Stegehuis, C., de Kok, T., & Adan, I. (2017). Assemble-to-order systems: A review. European Journal of Operational Research, 261(3), 866–879.

    Google Scholar 

  • Bai, C., & Sarkis, J. (2016). Supplier development investment strategies: A game theoretic evaluation. Annals of Operations Research, 240(2), 583–615.

    Google Scholar 

  • Bansal, M., & Mathur, M . (2012). Ramping up supplier capacity in volatile times. ATKearney. Retrieved February, 2018, http://www.atkearney.com/paper/-/asset_publisher/dVxv4Hz2h8bS/content/ramping-up-supplier-capacity-in-volatile-times/10192.

  • Bernstein, F., & DeCroix, G. A. (2004). Decentralized pricing and capacity decisions in a multitier system with modular assembly. Management Science, 50(9), 1293–1308.

    Google Scholar 

  • Bernstein, F., & DeCroix, G. A. (2006). Inventory policies in a decentralized assembly system. Operations Research, 54(2), 324–336.

    Google Scholar 

  • Bernstein, F., Kök, A. G., & Meca, A. (2015). Cooperation in assembly systems: The role of knowledge sharing networks. European Journal of Operational Research, 240(1), 160–171.

    Google Scholar 

  • Broderick, S. (2015). CRT: Airbus , Boeing booked more orders than will be delivered. Aviation week. Retrieved April, 2018, http://aviationweek.com/commercial-aviation/crt-airbus-boeing-booked-more-orders-will-be-delivered.

  • Cachon, G. P., & Ma, Lariviere. (2001). Contracting to assure supply: How to share demand forecasts in a supply chain. Management Science, 47(5), 629–646.

    Google Scholar 

  • Cachon, G. P., & Netessine, S. (2006). Game theory in supply chain analysis. In Models, methods, and applications for innovative decision making, INFORMS (pp. 200–233).

  • Chao, X., Gong, X., & Zheng, S. (2016). Optimal pricing and inventory policies with reliable and random-yield suppliers: Characterization and comparison. Annals of Operations Research, 241(1–2), 35–51.

    Google Scholar 

  • Chen, W., & Tan, B. (2016). Dynamic procurement from multiple suppliers with random capacities. Annals of Operations Research. https://doi.org/10.1007/s10479-016-2285-2.

  • Chiu, C. H., & Choi, T. M. (2016). Supply chain risk analysis with mean-variance models: A technical review. Annals of Operations Research, 240(2), 489–507.

    Google Scholar 

  • Ciarallo, F. W., Akella, R., & Morton, T. E. (1994). A periodic review, production planning model with uncertain capacity and uncertain demand-optimality of extended myopic policies. Management Science, 40(3), 320–332.

    Google Scholar 

  • Erkoc, M., & Wu, D. S. (2005). Managing high-tech capacity expansion via reservation contracts. Production and Operations Management, 14(2), 232–251.

    Google Scholar 

  • Feng, Y., Li, G., & Sethi, S. P. (2018). Pull and push contracts in a decentralised assembly system with random component yields. International Journal of Production Research, 56(24), 7405–7425.

    Google Scholar 

  • Fu, H., Ma, Y., Ni, D., & Cai, X. (2017). Coordinating a decentralized hybrid push-pull assembly system with unreliable supply and uncertain demand. Annals of Operations Research, 257(1–2), 537–557.

    Google Scholar 

  • Golmohammadi, A., & Hassini, E . (2017). Investment strategies in supplier development under capacity and demand uncertainty. Working paper, DeGroote School of Business.

  • Granot, D., & Yin, S. (2008). Competition and cooperation in decentralized push and pull assembly systems. Management Science, 54(4), 733–747.

    Google Scholar 

  • Handfield, R. B., Krause, D. R., Scannell, T. V., & Monczka, R. M. (2000). Avoid the pitfalls in supplier development. Sloan Management Review, 41(1), 59–82.

    Google Scholar 

  • He, Y., & Yin, S. (2015). Joint selling of complementary components under brand and retail competition. Manufacturing & Service Operations Management, 17(4), 470–479.

    Google Scholar 

  • Ho, W., Zheng, T., Yildiz, H., & Talluri, S. (2015). Supply chain risk management: A literature review. International Journal of Production Research, 53(16), 5031–5069.

    Google Scholar 

  • Huang, X., Boyacı, T., Gümüş, M., Ray, S., & Zhang, D. (2016). United we stand or divided we stand? Strategic supplier alliances under order default risk. Management Science, 62(5), 1297–1315.

    Google Scholar 

  • Hwang, W., Bakshi, N., & Demiguel, V. (2014) . Simple contracts for reliable supply: Capacity versus yield uncertainty. Working paper, London Business School

  • Hymans, S. H. (1966). The price-taker: Uncertainty, utility, and the supply function. International Economic Review, 7(3), 346–356.

    Google Scholar 

  • Ji, Q., Wang, Y., & Hu, X. (2016). Optimal production planning for assembly systems with uncertain capacities and random demand. European Journal of Operational Research, 253(2), 383–391.

    Google Scholar 

  • Jiang, L., & Wang, Y. (2010). Supplier competition in decentralized assembly systems with price-sensitive and uncertain demand. Manufacturing & Service Operations Management, 12(1), 93–101.

    Google Scholar 

  • Kelleher, A . (2018) . Preparing our manufacturing network to support Intel’s expanding business. Retrieved on April, 2019 from https://newsroom.intel.com/editorials/preparing-manufacturing-network-support-intels-expanding-business/#gs.b12gfm

  • Krause, D. R., & Ellram, L. M. (1997). Success factors in supplier development. International Journal of Physical Distribution & Logistics Management, 27(1), 39–52.

    Google Scholar 

  • van der Laan, E., Salomon, M., & Dekker, R. (1999). An investigation of lead-time effects in manufacturing/remanufacturing systems under simple push and pull control strategies. European Journal of Operational Research, 115(1), 195–214.

    Google Scholar 

  • Lee, H. L., & Billington, C. (1993). Material management in decentralized supply chains. Operations Research, 41(5), 835–847.

    Google Scholar 

  • Leng, M., & Parlar, M. (2010). Game-theoretic analyses of decentralized assembly supply chains: Non-cooperative equilibria vs. coordination with cost-sharing contracts. European Journal of Operational Research, 204(1), 96–104.

    Google Scholar 

  • Li, C. (2013). Sourcing for supplier effort and competition: Design of the supply base and pricing mechanism. Management Science, 59(6), 1389–1406.

    Google Scholar 

  • Li, C., & Debo, L. G. (2009a). Second sourcing vs. sole sourcing with capacity investment and asymmetric information. Manufacturing & Service Operations Management, 11(3), 448–470.

    Google Scholar 

  • Li, C., & Debo, L. G. (2009b). Strategic dynamic sourcing from competing suppliers with transferable capacity investment. Naval Research Logistics, 56(6), 540–562.

    Google Scholar 

  • Li, G., Fan, H., Lee, P. K., & Cheng, T. (2015). Joint supply chain risk management: An agency and collaboration perspective. International Journal of Production Economics, 164, 83–94.

    Google Scholar 

  • Li, G., Zhang, L., Guan, X., & Zheng, J. (2016a). Impact of decision sequence on reliability enhancement with supply disruption risks. Transportation Research Part E: Logistics and Transportation Review, 90(1), 25–38.

    Google Scholar 

  • Li, G., Li, L., Zhou, Y., & Guan, X. (2017a). Capacity restoration in a decentralized assembly system with supply disruption risks. International Transactions in Operational Research, 24(4), 763–782.

    Google Scholar 

  • Li, G., Liu, M., & Guan, X. (2017b). Diversity of payment contracts in a decentralized assembly system. Annals of Operations Research, 257(1–2), 613–639.

    Google Scholar 

  • Li, G., Liu, M., & Guan, X. (2017c). Diversity of payment contracts in a decentralized assembly system. Annals of Operations Research, 257(1–2), 613–639.

    Google Scholar 

  • Li, G., Mao, H., & Xiao, L. (2017d). Impacts of leader-follower structure on pricing and production strategies in a decentralized assembly system. Asia-Pacific Journal of Operational Research, 34(01), 1740003.

    Google Scholar 

  • Li, G., Li, L., Liu, M., et al. (2018). Impact of power structures in a subcontracting assembly system. Annals of Operations Research. https://doi.org/10.1007/s10479-018-3041-6.

  • Li, X., Li, Y. J., & Cai, X. Q. (2009). Collection pricing decision in a remanufacturing system considering random yield and random demand. Systems Engineering - Theory & Practice, 29(8), 19–27.

    Google Scholar 

  • Li, Y., Zhen, X., Qi, X., & Cai, G. G. (2016b). Penalty and financial assistance in a supply chain with supply disruption. Omega, 61(1), 167–181.

    Google Scholar 

  • Lin, Y. K., Yeh, C. T., & Huang, C. F. (2016). A simple algorithm to evaluate supply-chain reliability for brittle commodity logistics under production and delivery constraints. Annals of Operations Research, 244(1), 67–83.

    Google Scholar 

  • Nagarajan, M., & Sošić, G. (2009). Coalition stability in assembly models. Operations Research, 57(1), 131–145.

    Google Scholar 

  • Ozer, O., & Wei, W. (2006). Strategic commitments for an optimal capacity decision under asymmetric forecast information. Management Science, 52(8), 1238–1257.

    Google Scholar 

  • Parker, A., & Shotter, J. (2012). Airbus and Boeing push supply mergers. Financial Times. Retrieved April, 2018, http://www.ft.com/intl/cms/s/0/2b66574a-c73b-11e1-849e-00144feabdc0.html#axzz3XVhvxOsD

  • Plambeck, E. L., & Taylor, T. A. (2007). Implications of renegotiation for optimal contract flexibility and investment. Management Science, 53(12), 1872–1886.

    Google Scholar 

  • Qi, A., Ahn, H. S., & Sinha, A. (2015). Investing in a shared supplier in a competitive market: Stochastic capacity case. Production and Operations Management, 51(4), 1537–1551.

    Google Scholar 

  • Qin, F., Rao, U. S., Gurnani, H., & Bollapragada, R. (2014). Role of random capacity risk and the retailer in decentralized supply chains with competing suppliers. Decision Sciences, 45(2), 255–279.

    Google Scholar 

  • Sako, M. (2004). Supplier development at Honda, Nissan and Toyota: Comparative case studies of organizational capability enhancement. Industrial and Corporate Change, 13(2), 281–308. https://doi.org/10.1093/icc/dth012.

    Article  Google Scholar 

  • Simchi-Levi, D., Snyder, L., & Watson, M. (2002). Strategies for uncertain times. Supply Chain Management Review, 6(1), 11–12.

    Google Scholar 

  • Tang, S. Y., Gurnani, H., & Gupta, D. (2014). Managing disruptions in decentralized supply chains with endogenous supply process reliability. Production and Operations Management, 23(7), 1198–1211.

    Google Scholar 

  • Taylor, T., & Plambeck, E. L. (2007). Simple relational contracts to motivate capacity investment: Price only vs. price and quantity. Manufacturing & Service Operations Management, 9(1), 94–113.

    Google Scholar 

  • Tomlin, B. (2003). Capacity investments in supply chains: Sharing the gain rather than sharing the pain. Manufacturing & Service Operations Management, 5(4), 317–333.

    Google Scholar 

  • Topkis, D. M. (1998). Spermodularity and complementarity. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Wagner, S. M., & Bode, C. (2008). An empirical examination of supply chain performance along several dimensions of risk. Journal of Business Logistics, 29(1), 307–325.

    Google Scholar 

  • Wang, Y. (2006). Joint pricing-production decisions in supply chains of complementary products with uncertain demand. Operations Research, 54(6), 1110–1127.

    Google Scholar 

  • Xiao, T., & Qi, X. (2016). A two-stage supply chain with demand sensitive to price, delivery time, and reliability of delivery. Annals of Operations Research, 241(1–2), 475–496.

    Google Scholar 

  • Xiao, T., & Yang, D. (2008). Price and service competition of supply chains with risk-averse retailers under demand uncertainty. International Journal of Production Economics, 114(1), 187–200.

    Google Scholar 

  • Yang, J., Qi, X., Xia, Y., & Yu, G. (2006). Inventory control with markovian capacity and the option of order rejection. European Journal of Operational Research, 174(1), 622–645.

    Google Scholar 

  • Yang, J. S., & Pan, J. C. H. (2004). Just-in-time purchasing: An integrated inventory model involving deterministic variable lead time and quality improvement investment. International Journal of Production Research, 42(5), 853–863.

    Google Scholar 

  • Yang, Z. B., & Murthy, N. (2014). Timing and signaling considerations for recovery from supply chain disruption. Working paper, Lundquist College of Business.

  • Zhang, F. (2006). Competition, cooperation, and information sharing in a two-echelon assembly system. Manufacturing & Service Operations Management, 8(3), 273–291.

    Google Scholar 

  • Zhu, S. X. (2015). Integration of capacity, pricing, and lead-time decisions in a decentralized supply chain. International Journal of Production Economics, 164, 14–23.

    Google Scholar 

  • Zsidisin, G. A., Panelli, A., Upton, R.,&,. (2000). Purchasing organization involvement in risk assessments, contingency plans, and risk management: An exploratory study. Supply Chain Management: An International Journal, 5(4), 187–198.

    Google Scholar 

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Appendix

Appendix

Proof of Proposition 1

Assume \({\hat{q}}_1 \ne {\hat{q}}_2\) and let \({\bar{q}} = \min \{ {\hat{q}}_1, {\hat{q}}_2 \}\). Then \({\bar{q}} \ne {\hat{q}}_1\) or \({\bar{q}} \ne {\hat{q}}_2\). So \(({\bar{q}}, {\bar{q}}) \ne ({\hat{q}}_1, {\hat{q}}_2)\). We show that for any values of \(r_1\) and \(r_2\), \(\varPi ^{\text {so}}({\bar{q}}, {\bar{q}}|r_1, r_2) \ge \varPi ^\text {so}({\hat{q}}_1, {\hat{q}}_2|r_1, r_2)\).

$$\begin{aligned} \varPi ^{\text {so}}({\hat{q}}_1, {\hat{q}}_2)&= pE \left[ \min \left\{ D, {\hat{q}}_1, {\hat{q}}_2, U_1(r_1^{\text {so}}), U_2(r_2^{\text {so}}) \right\} \right] - w_1E \left[ \min \left\{ {\hat{q}}_1, U_1(r_1^{\text {so}}) \right\} \right] \\&\ - w_2 E \left[ \min \left\{ {\hat{q}}_2, U_2(r_2^{\text {so}})\right] \right\} \\ \le&pE \left[ \min \left\{ D, {\bar{q}}, U_1(r_1^{\text {so}}), U_2(r_2^{\text {so}}) \right\} \right] - w_1E \left[ \min \left\{ {\bar{q}}, U_1(r_1^{\text {so}}) \right\} \right] \\&- w_2 E \left[ \min \left\{ {\bar{q}}, U_2(r_2^{\text {so}})\right] \right\} = \varPi ^{\text {so}}({\bar{q}}, {\bar{q}}) \end{aligned}$$

\(\square \)

Proof of Proposition 2

  1. (a)

    Let \(M=\min \{D,U_1(r_1^{\text {so}}),U_2(r_2^{\text {so}})\}\), then:

    $$\begin{aligned} Pr\left\{ M>u \right\}&= Pr\left\{ D>u \right\} Pr\left\{ U_1(r_1^{\text {so}})>u \right\} Pr\left\{ U_2(r_2^{\text {so}})>u \right\} \\&= {\bar{F}}(u) {\bar{G}}_1(u|r_1^{\text {so}}) {\bar{G}}_2(u|r_2^{\text {so}}) \end{aligned}$$

    Therefore, \(\min \{ D,q^{\text {so}},U_1(r_1^{\text {so}}),U_2(r_2^{\text {so}})\} = \min \{M, q^{\text {so}} \} \le q^{\text {so}}\), and

    $$\begin{aligned} E\left[ \min \left\{ M,q^{\text {so}} \right\} \right]&= \int _{0}^{q^{\text {so}}} Pr \left[ \min \left\{ M,q^{\text {so}} \right\}>u \right] du = \int _{0}^{q^{\text {so}}} Pr \left[ M >u \right] du \\&= \int _{0}^{q^{\text {so}}}{\bar{F}}(u) {\bar{G}}_1(u|r_1^{\text {so}}) {\bar{G}}_2(u|r_2^{\text {so}})du \end{aligned}$$

    Similarly, we have \(E \left[ \min \{D,U_i(r_i^{\text {so}})\} \right] = \int _{0}^{q^{\text {so}}} {\bar{G}}_i(u|r_i^{\text {so}})du\). So::

    $$\begin{aligned} \varPi ^{\text {so}}&= p\int _{0}^{q^{\text {so}}} {\bar{F}}(u) {\bar{G}}_1(u|r_1^{\text {so}}) {\bar{G}}_2(u|r_2^{\text {so}}) du - w_1 \int _{0}^{q^{\text {so}}} {\bar{G}}_1(u|r_1^{\text {so}}) du \nonumber \\&\quad - w_2 \int _{0}^{q^{\text {so}}} {\bar{G}}_2(u|r_2^{\text {so}}) du \end{aligned}$$
    (19)

    Similar to Eq. (19), we can simplify the objective functions of the suppliers as follows:

    $$\begin{aligned} \varTheta _1^{\text {so}}&= (w_1-c_1) \int _{{\underline{l}}_1}^{q^{\text {so}}} {\bar{G}}_1(u|r_1^{\text {so}}) du - v_1(r_1^{\text {so}}) \end{aligned}$$
    (20)
    $$\begin{aligned} \varTheta _2^{\text {so}}&= (w_2-c_2) \int _{{\underline{l}}_2}^{q^{\text {so}}} {\bar{G}}_2(u|r_2^{\text {so}}) du - v_2(r_2^{\text {so}}) \end{aligned}$$
    (21)

    Based on Eq. (19), the first derivative of \(\varPi ^{\text {so}}\) with respect to \(q^{\text {so}}\) is:

    $$\begin{aligned} \frac{\partial \varPi ^{\text {so}}}{\partial q^{\text {so}}} = p {\bar{F}}(q^{\text {so}}) {\bar{G}}_1(q^{\text {so}}|r_1^{\text {so}}) {\bar{G}}_2(q^{\text {so}}|r_2^{\text {so}}) - w_1 {\bar{G}}_1(q^{\text {so}}|r_1^{\text {so}}) - w_2 {\bar{G}}_2(q^{\text {so}}|r_2^{\text {so}}) \end{aligned}$$
    (22)

    Consider \({\hat{q}}^{\text {so}} = \underset{q}{\arg \max } \ \varPi \). Then, based on the first-order condition, we have:

    $$\begin{aligned} p {\bar{F}}({\hat{q}}^{\text {so}}) {\bar{G}}_2({\hat{q}}^{\text {so}} | r_2^{\text {so}}) - w_1 = \frac{w_2 {\bar{G}}_2({\hat{q}}^{\text {so}}|r_2^{\text {so}})}{{\bar{G}}_1({\hat{q}}^{\text {so}}|r_1^{\text {so}})}\end{aligned}$$
    (23)
    $$\begin{aligned} p {\bar{F}}({\hat{q}}^{\text {so}}) {\bar{G}}_1({\hat{q}}^{\text {so}} | r_1^{\text {so}}) - w_2 = \frac{w_1 {\bar{G}}_1({\hat{q}}^{\text {so}}|r_1^{\text {so}})}{{\bar{G}}_2({\hat{q}}^{\text {so}}|r_2^{\text {so}})} \end{aligned}$$
    (24)

    The second derivative of \(\varPi ^{\text {so}}\) with respect to \(q^{\text {so}}\) is:

    $$\begin{aligned} \frac{\partial ^2 \varPi ^{\text {so}}}{\partial q^{{\text {so}}^2}}&= - p f(q^{\text {so}}) {\bar{G}}_1(q^{\text {so}}|r_1^{\text {so}}) {\bar{G}}_2(q^{\text {so}}|r_2^{\text {so}}) - p {\bar{F}}(q^{\text {so}}) g_1(q^{\text {so}}|r_1^{\text {so}}) {\bar{G}}_2(q^{\text {so}}|r_2^{\text {so}}) \nonumber \\&\quad - p {\bar{F}}(q^{\text {so}}) {\bar{G}}_1(q^{\text {so}}|r_1^{\text {so}}) g_2(q^{\text {so}}|r_2^{\text {so}}) \nonumber \\&\quad + w_1 g_1(q^{\text {so}}|r_1^{\text {so}}) + w_2 g_2(q^{\text {so}}|r_2^{\text {so}}) \end{aligned}$$
    (25)

    By replacing Eqs. (23) and (24) in Eq. (25), we have:

    $$\begin{aligned} \frac{\partial ^2 \varPi ^{\text {so}}}{\partial q^{{\text {so}}^2}} ({\hat{q}}^{\text {so}})&= - p f({\hat{q}}^{\text {so}}) {\bar{G}}_1({\hat{q}}^{\text {so}}|r_1^{\text {so}}) {\bar{G}}_2({\hat{q}}^{\text {so}}|r_2^{\text {so}}) - \frac{w_2 g_1({\hat{q}}^{\text {so}}|r_1^{\text {so}}) {\bar{G}}_2({\hat{q}}^{\text {so}}|r_2^{\text {so}})}{{\bar{G}}_1({\hat{q}}^{\text {so}}|r_1^{\text {so}})} \\&- \frac{w_1 g_2({\hat{q}}^{\text {so}}|r_2^{\text {so}}) {\bar{G}}_1({\hat{q}}^{\text {so}}|r_1^{\text {so}})}{{\bar{G}}_2({\hat{q}}^{\text {so}}|r_2^{\text {so}})} \end{aligned}$$

    Because f(.), \(g_1(.)\), \(g_2(.)\), \({\bar{G}}_1(.)\) and \({\bar{G}}_2(.)\) are positive, then \(\frac{\partial ^2 \varPi }{\partial q^{{\text {so}}^2}} ({\hat{q}}^{\text {so}}) \le 0\), which implies \(\varPi ^{\text {so}}\) is quasi-concave and, therefore, \({\tilde{q}}^{\text {so}}(r_1^{\text {so}}, r_2^{\text {so}})\) is unique. The second derivatives of the suppliers’ objective functions are:

    $$\begin{aligned} \frac{\partial ^2 \varTheta _1^{\text {so}}}{\partial r_1^{{\text {so}}^2}}&= (w_1-c_1)\int _{{\underline{l}}_1}^{q^{\text {so}}} \frac{\partial ^2 {\bar{G}}_1(u|r_1^{\text {so}})}{\partial r_1^{{\text {so}}^2}} du - \frac{\partial ^2 v_1(r_1^{\text {so}})}{\partial r_1^{{\text {so}}^2}} \\ \frac{\partial ^2 \varTheta _2^{\text {so}}}{\partial r_2^{{\text {so}}^2}}&= (w_2-c_2)\int _{{\underline{l}}_2}^{q^{\text {so}}} \frac{\partial ^2 {\bar{G}}_2(u|r_2^{\text {so}})}{\partial r_2^{{\text {so}}^2}} du - \frac{\partial ^2 v_2(r_2^{\text {so}})}{\partial r_2^{{\text {so}}^2}} \end{aligned}$$

    Because \({\bar{G}}_1(.)\) and \({\bar{G}}_2(.)\) are concave and \(v_1(r_1^{\text {so}})\) and \(v_2(r_2^{\text {so}})\) are convex, then \(\varTheta _1^{\text {so}}\) and \(\varTheta _2^{\text {so}}\) are concave and, therefore, \({\tilde{r}}_1^{\text {so}}(q^{\text {so}},r_2^{\text {so}})\) and \({\tilde{r}}_2^{\text {so}}(q^{\text {so}},r_1^{\text {so}})\) are unique.

  2. (b)

    The second derivatives of \(\varPi ^{\text {so}}\) with respect to \(q^{\text {so}}\) and \(r_1^{\text {so}}\), and with respect to \(q^{\text {so}}\) and \(r_2^{\text {so}}\), are:

    $$\begin{aligned} \frac{\partial ^2 \varPi ^{\text {so}}}{\partial q^{\text {so}} \partial r_1^{\text {so}}}&= p {\bar{F}}(q^{\text {so}}) {\bar{G}}_2(q^{\text {so}}|r_2^{\text {so}}) \frac{\partial {\bar{G}}_1(q^{\text {so}}|r_1^{\text {so}})}{\partial r_1^{\text {so}}} - w_1 \frac{\partial {\bar{G}}_1(q^{\text {so}}|r_1^{\text {so}})}{\partial r_1^{\text {so}}}\end{aligned}$$
    (26)
    $$\begin{aligned} \frac{\partial ^2 \varPi ^{\text {so}}}{\partial q^{\text {so}} \partial r_1^{\text {so}}}&= p {\bar{F}}(q^{\text {so}}) {\bar{G}}_2(q^{\text {so}}|r_2^{\text {so}}) \frac{\partial {\bar{G}}_1(q^{\text {so}}|r_1^{\text {so}})}{\partial r_1^{\text {so}}} - w_2 \frac{\partial {\bar{G}}_2(q^{\text {so}}|r_2^{\text {so}})}{\partial r_2^{\text {so}}} \end{aligned}$$
    (27)

    By replacing Eqs. (23) and (24) in Eqs. (26) and (27), we have:

    $$\begin{aligned} \frac{\partial ^2 \varPi ^{\text {so}}}{\partial q^{\text {so}} \partial r_1^{\text {so}}}({\tilde{q}}^{\text {so}})&= \frac{\partial {\bar{G}}_1({\tilde{q}}^{\text {so}}|r_1^{\text {so}})}{\partial r_1^{\text {so}}} \cdot \frac{w_2 {\bar{G}}_2({\tilde{q}}^{\text {so}}|r_2^{\text {so}})}{{\bar{G}}_1({\tilde{q}}^{\text {so}}|r_1^{\text {so}})} \ge 0 \\ \frac{\partial ^2 \varPi ^{\text {so}}}{\partial q^{\text {so}} \partial r_2^{\text {so}}}({\tilde{q}}^{\text {so}})&= \frac{\partial {\bar{G}}_2({\tilde{q}}^{\text {so}}|r_2^{\text {so}})}{\partial r_2^{\text {so}}} \cdot \frac{w_1 {\bar{G}}_1({\tilde{q}}^{\text {so}}|r_1^{\text {so}})}{{\bar{G}}_2({\tilde{q}}^{\text {so}}|r_2^{\text {so}})} \ge 0 \end{aligned}$$

    The second derivatives of the \(\varTheta _1^{\text {so}}\) with respect to \(q^{\text {so}}\) and \(r_1^{\text {so}}\), and with respect to \(r_1^{\text {so}}\) and \(r_2^{\text {so}}\) are:

    $$\begin{aligned} \frac{\partial ^2 \varTheta _1^{\text {so}}}{\partial r_1^{\text {so}} \partial q^{\text {so}}} = (w_1-c_1)\frac{\partial {\bar{G}}_1(q^{\text {so}}|r_1^{\text {so}})}{\partial r_1^{\text {so}}} \ge 0, \text {and,} \ \ \frac{\partial ^2 \varTheta _1^{\text {so}}}{\partial r_1^{\text {so}} \partial r_2^{\text {so}}}=0. \end{aligned}$$

    Similarly, for the second supplier, we have:

    $$\begin{aligned} \frac{\partial ^2 \varTheta _2^{\text {so}}}{\partial r_2^{\text {so}} \partial q^{\text {so}}} = (w_2-c_2)\frac{\partial {\bar{G}}_2(q^{\text {so}}|r_2^{\text {so}})}{\partial r_2^{\text {so}}} \ge 0\; \text {and,} \ \ \frac{\partial ^2 \varTheta _2^{\text {so}}}{\partial r_2^{\text {so}} \partial r_1^{\text {so}}}=0. \end{aligned}$$

    Then, according to Topkis (1998), we have \(\frac{\partial {\tilde{q}}^{\text {so}}(r_1^{\text {so}},r_2^{\text {so}})}{\partial r_1^{\text {so}}} \), \(\frac{\partial {\tilde{q}}^{\text {so}}(r_1^{\text {so}},r_2^{\text {so}})}{\partial r_2^{\text {so}}} \), \(\frac{\partial {\tilde{r}}_1^{\text {so}}(q^{\text {so}},r_2^{\text {so}})^{\text {so}}}{\partial q^{\text {so}}} \), \(\frac{\partial {\tilde{r}}_1^{\text {so}}(q^{\text {so}},r_2^{\text {so}})}{\partial r_2^{\text {so}}} \), \(\frac{\partial {\tilde{r}}_2^{\text {so}}(q^{\text {so}},r_1^{\text {so}})}{\partial q^{\text {so}}} \), and \(\frac{\partial {\tilde{r}}_2^{\text {so}}(q^{\text {so}},r_1^{\text {so}})}{\partial r_1^{\text {so}}} \ge 0 \).

\(\square \)

Proof of Proposition 3

Clearly, \((q^{\text {so}}, r_1^{\text {so}}, r_2^{\text {so}}) = {\mathbf {0}}\) is a feasible strategy for the manufacturer and the suppliers. Hence, the strategy set is not empty. According to Proposition 2, Part (a), \(\varPi ^{\text {so}}\), \(\varTheta _1^{\text {so}}\), and \(\varTheta _2^{\text {so}}\) are quasi-concave. As a result, there exists a NE for the game ( Cachon and Netessine 2006). \(\square \)

Proof of Lemma 1

According to Proposition 2, Part (b), the optimal strategies of the players are increasing functions with respect to other players’ strategies. As a result, we cannot have a case in which an equilibrium does not dominate another one (which contradicts with the supermodularity of the game). \(\square \)

Proof of Proposition 4

The first derivative of \(\varPi ^{\text {so}}\) with respect to \(r_1^{\text {so}}\) is:

$$\begin{aligned} \frac{\partial \varPi ^{\text {so}}}{\partial r_1^{\text {so}}}&= p \int _{0}^{q^{\text {so}}} {\bar{F}}(u) {\bar{G}}_2(u|r_2^{\text {so}}) \frac{\partial {\bar{G}}_1(u|r_1^{\text {so}})}{\partial r_1^{\text {so}}} du - w_1 \int _{0}^{q^{\text {so}}} \frac{\partial {\bar{G}}_1(u|r_1^{\text {so}})}{\partial r_1^{\text {so}}} du\\&= \int _{0}^{q^{\text {so}}} \frac{\partial {\bar{G}}_1(u|r_1^{\text {so}})}{\partial r_1^{\text {so}}} \left[ p {\bar{F}}(u) {\bar{G}}_2(u|r_2^{\text {so}}) -w_1 \right] du \end{aligned}$$

Because \(\varPi ^{so}\) is quasi-concave, based on Eq. (22), for any value of \(u \le {\tilde{q}}^{\text {so}}(r_1^{\text {so}}, r_2^{\text {so}})\), we have \( p {\bar{F}}(u) {\bar{G}}_2(u|r_2^{\text {so}}) -w_1 \ge 0\). As a result, when \(q^{\text {so}} = {\tilde{q}}^{\text {so}}(r_1^{\text {so}}, r_2^{\text {so}})\), \(\varPi ^{\text {so}}\) is an increasing function of \(r_1^{\text {so}}\). Similarly, we can prove that when \(q^{\text {so}} = {\tilde{q}}^{\text {so}}(r_1^{\text {so}}, r_2^{\text {so}})\), \(\varPi ^{\text {so}}\) is an increasing function of \(r_2^{\text {so}}\). In addition, we can show that:

$$\begin{aligned} \frac{\partial \varTheta _1^{\text {so}}}{ \partial q^{\text {so}}} =(w_1-c_1) {\bar{G}}_1(q^{\text {so}}|r_1^{\text {so}}) \ge 0 \ \ , \ \ \frac{\partial \varTheta _1^{\text {so}}}{ \partial r_2^{\text {so}}}=0 \ \ , \ \ \frac{\partial \varTheta _2^{\text {so}}}{ \partial q^{\text {so}}} = (w_2-c_2){\bar{G}}_2(q^{\text {so}}|r_2^{\text {so}}) \ge 0, \end{aligned}$$

and \(\ \ \frac{\partial \varTheta _2^{\text {so}}}{\partial r_1^{\text {so}}}=0. \)

Therefore, the profit functions of the suppliers are increasing functions with respect to the order quantity of the manufacturer. In addition, a supplier’s profit function does not vary with respect to the other supplier’s investment. Consider \(({\bar{q}}^{\text {so}^{(i)}}, {\bar{r}}_1^{\text {so}^{(i)}}, {\bar{r}}_2^{\text {so}^{(i)}})\) and \(({\bar{q}}^{\text {so}^{(j)}}, {\bar{r}}_1^{\text {so}^{(j)}}, {\bar{r}}_2^{\text {so}^{(j)}}) \) as two NEs of the game, where \(({\bar{q}}^{\text {so}^{(i)}}, {\bar{r}}_1^{\text {so}^{(i)}}, {\bar{r}}_2^{\text {so}^{(i)}}){\ge } ({\bar{q}}^{\text {so}^{(j)}}, {\bar{r}}_1^{\text {so}^{(j)}}, {\bar{r}}_2^{\text {so}^{(j)}}) \). Then, we have:

$$\begin{aligned} \varPi ^{\text {so}}({\bar{q}}^{\text {so}^{(j)}}, {\bar{r}}_1^{\text {so}^{(j)}}, {\bar{r}}_2^{\text {so}^{(j)}}) \le \varPi ^{\text {so}}({\bar{q}}^{\text {so}^{(j)}}, {\bar{r}}_1^{\text {so}^{(i)}}, {\bar{r}}_2^{\text {so}^{(i)}}) \le \varPi ^{\text {so}}({\bar{q}}^{\text {so}^{(i)}}, {\bar{r}}_1^{\text {so}^{(i)}}, {\bar{r}}_2^{\text {so}^{(i)}}) \end{aligned}$$

Similarly, we have:

$$\begin{aligned} \varTheta _1^{\text {so}}({\bar{q}}^{\text {so}^{(j)}}, {\bar{r}}_1^{\text {so}^{(j)}}, {\bar{r}}_2^{\text {so}^{(j)}}) \le \varTheta _1^{\text {so}}({\bar{q}}^{\text {so}^{(i)}}, {\bar{r}}_1^{\text {so}^{(j)}}, {\bar{r}}_2^{\text {so}^{(i)}}) \le \varTheta _1^{\text {so}}({\bar{q}}^{\text {so}^{(i)}}, {\bar{r}}_1^{\text {so}^{(i)}}, {\bar{r}}_2^{\text {so}^{(i)}}) \\ \varTheta _2^{\text {so}}({\bar{q}}^{\text {so}^{(j)}}, {\bar{r}}_1^{\text {so}^{(j)}}, {\bar{r}}_2^{\text {so}^{(j)}}) \le \varTheta _2^{\text {so}}({\bar{q}}^{\text {so}^{(i)}}, {\bar{r}}_1^{\text {so}^{(i)}}, {\bar{r}}_2^{\text {so}^{(j)}}) \le \varTheta _2^{\text {so}}({\bar{q}}^{\text {so}^{(i)}}, {\bar{r}}_1^{\text {so}^{(i)}}, {\bar{r}}_2^{\text {so}^{(i)}}) \end{aligned}$$

These inequalities can be found using the fact that each player’s objective function is an increasing function with respect to the other players’ strategies. Because \(({\bar{q}}^{\text {so}^{(n)}}, {\bar{r}}_1^{\text {so}^{(n)}}, {\bar{r}}_2^{\text {so}^{(n)}}) \ge ({\bar{q}}^{\text {so}^{(i)}}, {\bar{r}}_1^{\text {so}^{(i)}}, {\bar{r}}_2^{\text {so}^{(i)}}) \), \(\forall i\), then \(({\bar{q}}^{\text {so}^{(n)}}, {\bar{r}}_1^{\text {so}^{(n)}}, {\bar{r}}_2^{\text {so}^{(n)}})\) is the dominant equilibrium. \(\square \)

To prove Proposition 5, first we need to prove the following lemma.

Lemma 2

The optimal order quantity of the manufacturer, \({\tilde{q}}^{\text {oc}}\), is less than or equal to the observed capacities of the suppliers.

Proof

We need to show that \({\tilde{q}}^{\text {oc}} \le \min \left\{ u_1(r_1^{\text {oc}}), u_2(r_2^{\text {oc}}) \right\} \). We use contradiction to prove the lemma. Assume \({\tilde{q}}^{\text {oc}} > \min \left\{ u_1(r_1^{\text {oc}}), u_2(r_2^{\text {oc}}) \right\} \). Consider \({\hat{q}}^{\text {oc}} = \min \left\{ u_1(r_1^{\text {oc}}), u_2(r_2^{\text {oc}}) \right\} \). We show that \(\varPi ^{\text {oc}}( {\hat{q}}^{\text {oc}}|r_1^{\text {oc}}, r_2^{\text {oc}}) \ge \varPi ^{\text {oc}}({\tilde{q}}^{\text {oc}} |r_1, r_2)\).

Case 1: Assume \(u_1(r_1^{\text {oc}}) \le u_2 (r_2^{\text {oc}})\).

$$\begin{aligned} \varPi ^{\text {oc}}({\tilde{q}}^{\text {oc}}|r_1^{\text {oc}}, r_2^{\text {oc}})&= pE \left[ \min \left\{ D, {\tilde{q}}^{\text {oc}}, u_1(r_1^{\text {oc}}), u_2(r_2^{\text {oc}}) \right\} \right] - w_1\min \left\{ {\tilde{q}}^{\text {oc}}, u_1(r_1^{\text {oc}}) \right\} \\&\quad - w_2\min \left\{ {\tilde{q}}^{\text {oc}}, u_2(r_2^{\text {oc}}) \right\} \\&= pE \left[ \min \left\{ D, u_1(r_1^{\text {oc}}) \right\} \right] - w_1 u_1(r_1^{\text {oc}}) - w_2\min \left\{ {\tilde{q}}^{\text {oc}} , u_2(r_2^{\text {oc}}) \right\} \\&\le pE \left[ \min \left\{ D, u_1(r_1^{\text {oc}}) \right\} \right] - w_1 u_1(r_1^{\text {oc}}) - w_2\min \left\{ {\hat{q}}^{\text {oc}}, u_2(r_2^{\text {oc}}) \right\} \\&= pE \left[ \min \left\{ D, {\hat{q}}^{\text {oc}}, u_1(r_1^{\text {oc}}), u_2(r_2^{\text {oc}}) \right\} \right] - w_1\min \left\{ {\hat{q}}, u_1(r_1^{\text {oc}}) \right\} \\&\quad -w_2\min \left\{ {\hat{q}}, u_2(r_2^{\text {oc}}) \right\} \\&= \varPi ^{\text {oc}}({\hat{q}}^{\text {oc}}|r_1^{\text {oc}}, r_2^{\text {oc}}) \end{aligned}$$

Case 2: Assume \(u_1(r_1^{\text {oc}}) \ge u_2 (r_2^{\text {oc}})\). The proof is analogous. \(\square \)

Proof of Proposition 5

According to Lemma 2, the problem of the manufacturer can be simplified as follows:

$$\begin{aligned} \underset{q^{\text {oc}} \ge 0}{\max } \ {\hat{\varPi }}^{\text {oc}} (q^{\text {oc}})&= p E \left[ \min \left\{ D, q^{\text {oc}} \right\} \right] - (w_1+w_2) q^{\text {oc}} \nonumber \\&s.t. \nonumber \\&q^{\text {oc}} \le \min \left\{ u_1(r_1^{\text {oc}}), u_2(r_2^{\text {oc}}) \right\} \end{aligned}$$
(28)

Because minimization preserves concavity, \({\hat{\varPi }}^{\text {oc}}(q^{\text {oc}})\) is concave with respect to \(q^{\text {oc}}\). Consider \({\hat{q}}^{{\text {oc}}^*}\) as the optimum solution of \({\hat{\varPi }}^{\text {oc}}(q^{\text {oc}})\) in the absence of Constraint (28). \({\hat{\varPi }}^{\text {oc}}(q^{\text {oc}})\) is the objective function of the classic news vendor problem and its optimum solution is \({\hat{q}}^{{\text {oc}}^*} = {\bar{F}}^{-1} \left( \frac{w_1+w_2}{p} \right) \), which is the critical fractile solution. Now, by considering Constraint (28) and the concavity of \({\hat{\varPi }}^{\text {oc}}(q^{\text {oc}})\), the optimum solution of the manufacturer is as follows:

$$\begin{aligned} q^{{\text {oc}}^*}(r_1^{\text {oc}}, r_2^{\text {oc}}) = \min \left\{ {\bar{F}}^{-1} \left( \frac{w_1+w_2}{p} \right) , u_1(r_1^{\text {oc}}), u_2(r_2^{\text {oc}}) \right\} . \end{aligned}$$

(b) Let \(Q= {\bar{F}}^{-1} \left( \frac{w_1+w_2}{p} \right) \). By replacing Q in Eq. (22), we have:

$$\begin{aligned} \frac{\partial \varPi ^{\text {so}}}{\partial q^{\text {so}}} (Q)&= (w_1+w_2) {\bar{G}}_1(Q|r_1^{\text {so}}) {\bar{G}}_2(Q|r_2^{\text {so}}) - w_1 {\bar{G}}_1(Q|r_1^{\text {so}}) - w_2 {\bar{G}}_2(Q|r_2^{\text {so}})\\&= - w_1 {\bar{G}}_1(Q|r_1^{\text {so}}) G_2(Q|r_2^{\text {so}}) - w_2 G_1(Q|r_1^{\text {so}}) {\bar{G}}_2(Q|r_2^{\text {so}}) \le 0 \end{aligned}$$

Because \(\varPi ^\text {so}\) is unimodal and \(\frac{\partial \varPi ^{\text {so}}}{\partial q^{\text {so}}} (Q) \le 0\), \(\forall r_1^{\text {so}}, r_2^{\text {so}}\), then we conclude that \(q^{{\text {so}}^*} \le Q\). \(\square \)

Proof of Proposition 6

  1. (a)

    To prove Proposition 6, first, we simplify the objective functions of the suppliers. Consider \(Q = {\bar{F}}^{-1} \left( \frac{w_1+w_2}{p} \right) \), which represents the optimal order quantity of the buyer without considering the capacities of the suppliers. Then, the explicit form of the first supplier’s objective function is:

    $$\begin{aligned} \varTheta _1^{\text {oc}}&= (w_1-c_1) \int _{{\underline{l}}_1}^{Q} \int _{{\underline{l}}_2}^{u_1} u_2g_2(u_2|r_2^{\text {oc}})g_1(u_1|r_1^{\text {oc}})du_2du_1 \\&\quad + (w_1-c_1)\int _{{\underline{l}}_1}^{Q} \int _{u_1}^{{\overline{l}}_2} u_1g_2(u_2|r_2^{\text {oc}})g_1(u_1|r_1^{\text {oc}})du_2du_1 \\&\quad + (w_1-c_1)\int _{Q}^{{\overline{l}}_1} \int _{{\underline{l}}_2}^{Q} u_2g_2(u_2|r_2^{\text {oc}})g_1(u_1|r_1^{\text {oc}})du_2du_1 \\&\quad + (w_1-c_1)\int _{Q}^{{\overline{l}}_1} \int _{Q}^{{\overline{l}}_2} Q g_2(u_2|r_2^{\text {oc}})g_1(u_1|r_1^{\text {oc}})du_2du_1 - v_1(r_1^{\text {oc}})\\ \end{aligned}$$

    By using partial integration, we are able to show that:

    $$\begin{aligned} \varTheta _1^{\text {oc}} = (w_1-c_1) \int _{0}^{Q} {\bar{G}}_1(u_1|r_1^{\text {oc}}) {\bar{G}}_2(u_1|r_2^{\text {oc}}) du_1 -v_1(r_1^{\text {oc}}) \end{aligned}$$
    (29)

    Similarly, the objective function of the second supplier is:

    $$\begin{aligned} \varTheta _2^{\text {oc}} = (w_2-c_2) \int _{0}^{Q} {\bar{G}}_1(u_1|r_1^{\text {oc}}) {\bar{G}}_2(u_1|r_2^{\text {oc}}) du_1 -v_2(r_2^{\text {oc}}) \end{aligned}$$
    (30)

    Considering Eq. (29), the second derivative of \(\varTheta _1^{\text {oc}}(r_1^{\text {oc}})\) with respect to \(r_1^{\text {oc}}\) is:

    $$\begin{aligned} \frac{\partial ^2 \varTheta _1^{\text {oc}}}{\partial r_1^{{\text {oc}}^2}} = (w_1-c_1) \int _{0}^{Q} \frac{\partial ^2 {\bar{G}}_1(u_1|r_1^{\text {oc}})}{\partial r_1^{{\text {oc}}^2}} {\bar{G}}_2(u_1|r_2^{\text {oc}})du_1- \frac{\partial ^2 v_1(r_1^{\text {oc}})}{\partial r_1^{{\text {oc}}^2}} \end{aligned}$$
    (31)

    Because \(G_1(u_1|r_1^{\text {oc}})\) is convex and \({\bar{G}}_1(u_1|r_1^{\text {oc}}) = 1 - G_1(u_1|r_1^{\text {oc}})\), then \({\bar{G}}_1(u_1|r_1^{\text {oc}})\) is concave. Additionally, it is assumed that \(v_1(r_1^{\text {oc}})\) is convex. Therefore, \(\frac{\partial ^2 {\bar{G}}_1(u_1|r_1^{\text {oc}})}{\partial r_1^{{\text {oc}}^2}} \le 0\) and \( \frac{\partial ^2 v_1(r_1^{\text {oc}})}{\partial r_1^{{\text {oc}}^2}} \ge 0\); thus, \( \frac{\partial ^2 \varTheta _1^{\text {oc}}}{\partial r_1^{{\text {oc}}^2}} \le 0\). This implies that \(\varTheta _1^{\text {oc}}\) is concave with respect to \(r_1^{\text {oc}}\) and \({\tilde{r}}^{\text {oc}}_1(r_2^{\text {oc}})\) is unique. The uniqueness of \({\tilde{r}}^{\text {oc}}_2(r_1^{\text {oc}})\) can be proved analogously.

  2. (b)

    We have:

    $$\begin{aligned} \frac{\partial ^2 \varTheta _1^{\text {oc}}}{\partial r_1^{\text {oc}} \partial r_2^{\text {oc}}} = (w_1-c_1) \int _{{\underline{l}}_1}^{Q} \frac{\partial {\bar{G}}_1(u_1|r_1^{\text {oc}})}{\partial r_1^{\text {oc}}}\frac{\partial {\bar{G}}_2(u_1|r_2^{\text {oc}})}{\partial r_2^{\text {oc}}} du_1 \ge 0 \end{aligned}$$
    (32)

    Inequality (32) is based on the fact that \({\bar{G}}_1(u_1|r_1^{\text {oc}})\) and \({\bar{G}}_2(u_1|r_2^{\text {oc}})\) are decreasing with respect to \(r_1^{\text {oc}}\) and \(r_2^{\text {oc}}\), respectively. Then, according to Topkis (1998), \(\frac{\partial {\tilde{r}}_1^{\text {oc}}(r_2^{\text {oc}})}{\partial r_2^{\text {oc}}} \ge 0\). The proof for \(\frac{\partial {\tilde{r}}_2^{\text {oc}}(r_1^{\text {oc}})}{\partial r_1^{\text {oc}}} \ge 0\) is analogous.

\(\square \)

Proof of Proposition 7

Clearly, \((r_1^{\text {oc}}, r_2^{\text {oc}}) = 0\) is a feasible strategy for the suppliers. Hence, the strategy set of the suppliers is not empty. In contrast, according to the proof of Proposition 6, \(\frac{\partial ^2 \varTheta _1^{\text {oc}}}{\partial r_1^{\text {oc}} \partial r_2^{\text {oc}}} \ge 0\) and \(\frac{\partial ^2 \varTheta _2^{\text {oc}}}{\partial r_1^{\text {oc}} \partial r_2^{\text {oc}}} \ge 0\). As a result, the game is supermodular, which proves the existence of an NE [see Cachon and Netessine (2006)].

According to Proposition 6, \(\varTheta _1^{\text {oc}}\) and \(\varTheta _2^{\text {oc}}\) are concave with respect to \(r_1^{\text {oc}}\) and \(r_2^{\text {oc}}\), respectively. As a result, the first-order conditions can be used to find the optimal solution. The first derivatives of \(\varTheta _1^{\text {oc}}\) and \(\varTheta _2^{\text {oc}}\) are:

$$\begin{aligned} \frac{\partial \varTheta _1^{\text {oc}}}{\partial r_1^{\text {oc}}} = (w_1-c_1) \int _{{\underline{l}}_1}^{Q} \frac{\partial {\bar{G}}_1(u_1|r_1^{\text {oc}})}{\partial r_1^{\text {oc}}} {\bar{G}}_2(u_1|r_2^{\text {oc}})du_1- \frac{\partial v_1(r_1^{\text {oc}})}{\partial r_1^{\text {oc}}} \\ \frac{\partial \varTheta _2^{\text {oc}}}{\partial r_2^{\text {oc}}} = (w_2-c_2) \int _{{\underline{l}}_1}^{Q} \frac{\partial {\bar{G}}_2(u_1|r_2^{\text {oc}})}{\partial r_2^{\text {oc}}} {\bar{G}}_1(u_1|r_1^{\text {oc}})du_1- \frac{\partial v_2(r_2^{\text {oc}})}{\partial r_2^{\text {oc}}} \end{aligned}$$

and that completes the proof. \(\square \)

To prove Proposition 8, first, we need to prove the following lemma.

Lemma 3

Assume \(({\bar{r}}_1^{\text {oc}},{\bar{r}}_2^{\text {oc}})\) and \((\bar{{\bar{r}}}_1^{\text {oc}},\bar{{\bar{r}}}_2^{\text {oc}})\) are two equilibriums of the suppliers’ game. Then, either \(({\bar{r}}_1^{\text {oc}},{\bar{r}}_2^{\text {oc}}) \ge (\bar{{\bar{r}}}_1^{\text {oc}},\bar{{\bar{r}}}_2^{\text {oc}})\) or \(({\bar{r}}_1^{\text {oc}},{\bar{r}}_2^{\text {oc}}) \le (\bar{{\bar{r}}}_1^{\text {oc}},\bar{{\bar{r}}}_2^{\text {oc}})\).

Proof

The proof follows Part (b) of Proposition 6. \(\square \)

Proof of Proposition 8

Based on Eq. (29), the first derivative of \(\varTheta _1^{\text {oc}}\) with respect to \(r_2^{\text {oc}}\) is:

$$\begin{aligned} \frac{\partial \varTheta _1^{\text {oc}}}{\partial r_2^{\text {oc}}} = (w_1-c_1) \int _{{\underline{l}}_1}^{Q} \frac{\partial {\bar{G}}_2(u_1|r_2^{\text {oc}})}{\partial r_2^{\text {oc}}} {\bar{G}}_1(u_1|r_1^{\text {oc}})du_1 \end{aligned}$$

Because \(\frac{\partial {\bar{G}}_2(u_1|r_2^{\text {oc}})}{\partial r_2^{\text {oc}}} \ge 0\), then \(\frac{\partial \varTheta _1^{\text {oc}}}{\partial r_2^{\text {oc}}} \ge 0\). As result, \(\varTheta _1^{\text {oc}}\) is an increasing function of \(r_2^{\text {oc}}\). Consider \(({\bar{r}}_1^{\text {oc}^{(i)}}, {\bar{r}}_2^{\text {oc}^{(i)}})\) and \(({\bar{r}}_1^{\text {oc}^{(j)}}, {\bar{r}}_2^{\text {oc}^{(j)}})\) as two NEs of the leader stage of the dynamic game where \(({\bar{r}}_1^{\text {oc}^{(i)}}, {\bar{r}}_2^{\text {oc}^{(i)}}) > ({\bar{r}}_1^{\text {oc}^{(j)}}, {\bar{r}}_2^{\text {oc}^{(j)}})\), then, we have:

$$\begin{aligned} \varTheta _1^{\text {oc}}({\bar{r}}_1^{\text {oc}^{(j)}}, {\bar{r}}_2^{\text {oc}^{(j)}}) \le \varTheta _1^{\text {oc}}({\bar{r}}_1^{\text {oc}^{(j)}}, {\bar{r}}_2^{\text {oc}^{(i)}}) \le \varTheta _1^{\text {oc}}({\bar{r}}_1^{\text {oc}^{(i)}}, {\bar{r}}_2^{\text {oc}^{(i)}}) \end{aligned}$$

This inequality can be found on the basis of the fact that \(\varTheta _1^{\text {oc}}(r_1^{\text {oc}}, r_2^{\text {oc}})\) is an increasing function of \(r_2^{\text {oc}}\), and \({\bar{r}}_1^{\text {oc}^{(i)}}\) maximizes \(\varTheta _1^{\text {oc}}(r_1^{\text {oc}}, {\bar{r}}_2^{\text {oc}^{(i)}})\). Because \(({\bar{r}}_1^{\text {oc}^{(n)}}, {\bar{r}}_2^{\text {oc}^{(n)}}) > ({\bar{r}}_1^{\text {oc}^{(i)}}, {\bar{r}}_2^{\text {oc}^{(i)}})\), \(\forall i\), then \(\varTheta _1^{\text {oc}}({\bar{r}}_1^{\text {oc}^{(n)}}, {\bar{r}}_2^{\text {oc}^{(n)}}) \ge \varTheta _1^{\text {oc}}({\bar{r}}_1^{\text {oc}^{(i)}}, {\bar{r}}_2^{\text {oc}^{(i)}})\), \(\forall i\).

The proof for \(\varTheta _2^{\text {oc}}({\bar{r}}_1^{\text {oc}^{(n)}}, {\bar{r}}_2^{\text {oc}^{(n)}}) \ge \varTheta _2^{\text {oc}}({\bar{r}}_1^{\text {oc}^{(i)}}, {\bar{r}}_2^{\text {oc}^{(i)}})\), \(\forall i\) is analogous.\(\square \)

Proof of Proposition 9

  1. (a)

    Similar to Proposition 2, Part (a), we can show that the profit function of the manufacturer is:

    $$\begin{aligned} \varPi ^{\text {ov}}&= p \int _{0}^{q^{\text {ov}}} {\bar{F}}(u) {\bar{G}}_1(u|r_1^{\text {ov}}) {\bar{G}}_2(u|r_2^{\text {ov}}) du - w_1 \int _{0}^{q^{\text {ov}}} {\bar{G}}_1(u|r_1^{\text {ov}}) du \\&\quad - w_2 \int _{0}^{q^{\text {ov}}} {\bar{G}}_2(u|r_2^{\text {ov}}) du \end{aligned}$$

    The remainder of the proof is similar to Proposition 2, Part (a).

  2. (b)

    The proof is similar to Part (b) of Proposition 2.

\(\square \)

Proof of Proposition 10

  1. (a)

    The explicit form of the first supplier objective function is:

    $$\begin{aligned} \varTheta _1^{\text {ov}}&= (w_1-c_1) \int _{{\underline{l}}_1}^{{\tilde{q}}^{\text {ov}}(r_1^{\text {ov}}, r_2^{\text {ov}})} {\bar{G}}_1(u|r_1^{\text {ov}}) du - v_1(r_1^{\text {ov}}) \end{aligned}$$

    By taking the first derivative of \(\varTheta _1^{\text {ov}}\) with respect to \(r_1^{\text {ov}}\), we have:

    $$\begin{aligned} \frac{\partial \varTheta _1^{\text {ov}}}{r_1^{\text {ov}}}&= (w_1-c_1) \int _{{\underline{l}}_1}^{{\tilde{q}}^{\text {ov}}(r_1^{\text {ov}}, r_2^{\text {ov}})} \frac{\partial {\bar{G}}_1(u|r_1^{\text {ov}})}{r_1^{\text {ov}}} du \\&\quad + {\bar{G}}_1({\tilde{q}}^{\text {ov}}(r_1^{\text {ov}}, r_2^{\text {ov}})|r_1^{\text {ov}}) \frac{\partial {\tilde{q}}^{\text {ov}}(r_1^{\text {ov}}, r_2^{\text {ov}})}{r_1^{\text {ov}}} - \frac{\partial v_1^{\text {ov}}(r_1^{\text {ov}})}{r_1^{\text {ov}}} \end{aligned}$$

    According to Proposition 9, Part (c), \(\frac{\partial {\tilde{q}}^{\text {ov}}(r_1^{\text {ov}}, r_2^{\text {ov}})}{r_1^{\text {ov}}} \ge 0\). As a result, based on Proposition 9, Part (b), we have:

    $$\begin{aligned} \frac{\partial \varTheta _1^{\text {ov}}}{r_1^{\text {ov}}}(r_1, r_2) \ge (w_1-c_1) \int _{{\underline{l}}_1}^{{\tilde{q}}^{\text {ov}}(r_1, r_2)} \frac{\partial {\bar{G}}_1(u|r_1)}{r_1} du - \frac{\partial v_1^{\text {ov}}(r_1)}{r_1} = \frac{\partial \varTheta _1^{\text {ov}}}{r_1^{\text {SO}}}(r_1, r_2) \end{aligned}$$
    (33)

    Based on Inequality (33), \(r_1^{\text {ov}^*} \ge r_1^{\text {so}^*}\). The proof for \(r_2^{\text {ov}^*} \ge r_2^{\text {so}^*}\) is analogous.

  2. (b)

    According to Proposition 9, Part (b), \({\tilde{q}}^{{\text {ov}}}(r_1, r_2) = q^{{\text {so}}^*}(r_1, r_2)\). Also based on Part (c) of this proposition, \(\frac{\partial {\tilde{q}}^{\text {ov}}(r_1^{\text {ov}},r_2^{\text {ov}})}{\partial r_1^{\text {ov}}} \ge 0\) and \(\frac{\partial {\tilde{q}}^{\text {ov}}(r_1^{\text {ov}},r_2^{\text {ov}})}{\partial r_2^{\text {ov}}} \ge 0\). As a result, \({\tilde{q}}^{\text {ov}}(.)\) is an increasing function with respect to \(r_1^{\text {ov}}\) and \(r_2^{\text {ov}}\). Because we have \(r_1^{\text {ov}^*} \ge r_1^{\text {so}^*}\) and \(r_2^{\text {ov}^*} \ge r_2^{\text {so}^*}\) from Part (a), \(q^{\text {ov}^*} \ge q^{\text {so}^*}\), which completes the proof.

  3. (c)

    Note \(\varPi ^{\text {ov}^*}(q, r_1, r_2) = \varPi ^{\text {so}^*}(q, r_1, r_2)\). Also, according to Proposition 4, \(\frac{\varPi ^{\text {ov}^*}}{r_1^{\text {ov}}} \ge 0\) and \(\frac{\varPi ^{\text {ov}^*}}{r_2^{\text {ov}}} \ge 0\). Because \((r_1^{\text {ov}^*}, r_2^{\text {ov}^*}) \ge (r_1^{\text {so}^*}, r_2^{\text {so}^*})\) from Part (a) of the proposition, we have \(\varPi ^{\text {ov}^*}(q^{\text {ov}^*}, r_1^{\text {so}^*}, r_2^{\text {so}^*}) \ge \varPi ^{\text {so}^*}(q^{\text {so}^*}, r_1^{\text {so}^*}, r_2^{\text {so}^*})\)

  4. (d)

    Because \({\tilde{q}}^{\text {ov}}(r_1, r_2) = q^{\text {so}^*}(r_1, r_2)\), then \(\varTheta _1^{\text {ov}}(r_1, r_2) = \varTheta _1^{\text {so}}(q^{\text {so}^*}, r_1, r_2)\). Based on Eq. (33), we have:

    $$\begin{aligned} \varTheta _1^{\text {ov}^*}(r_1^{\text {ov}^*}, r_2^{\text {ov}^*}) \ge \varTheta _1^{\text {ov}^*}(r_1^{\text {so}^*}, r_2^{\text {so}^*}) = \varTheta _1^{\text {ov}^*}(q^{\text {so}^*}, r_1^{\text {ov}^*}, r_2^{\text {ov}^*})\end{aligned}$$

    which completes the proof. The proof for the second supplier is analogous.\(\square \)

Proof of Proposition 11

  1. (a)

    The explicit form of the first supplier’s objective function is:

    $$\begin{aligned} \varTheta _1^{\text {os}}&= (w_1-c_1) \int _{{\underline{l}}_1}^{q_1^{\text {os}}} {\bar{G}}_1(u|r_1^{\text {os}}) du - v_1(r_1^{\text {os}}) \end{aligned}$$

    The second derivative of \(\varTheta _1^{\text {os}}\) with respect to \(r_1^{\text {os}}\) is:

    $$\begin{aligned} \frac{\partial ^2 \varTheta _1^{\text {os}}}{\partial r_1^{\text {os}^2}} = \int _{{\underline{l}}_1}^{q_1^{\text {os}}} \frac{\partial ^2 {\bar{G}}_1(u|r_1^{\text {os}})}{\partial r_1^{\text {os}^2}}du - \frac{\partial ^2 v_1(r_1^{\text {os}})}{\partial r_1^{\text {os}^2}} \le 0 \end{aligned}$$

    As a result, \({\tilde{r}}_1^{\text {os}}(q_1^{\text {os}})\) is unique. Also, \(\varTheta _1^{\text {os}}(q) = \varTheta _1^{\text {so}}(q)\), which implies that \({\tilde{r}}_1^{\text {os}}(q) = r_1^{\text {so}^*}(q)\). The proof for \({\tilde{r}}_2^{\text {os}}(q_2^{\text {os}})\) is analogous.

  2. (b)

    The second derivative of \(\varTheta _1^{\text {os}}\) with respect to \(r_1^{\text {os}}\) and \(q_1^{\text {os}}\) is:

    $$\begin{aligned} \frac{\partial ^2 \varTheta _1^{\text {os}}}{\partial r_1^{\text {os}} \partial q_1^{\text {os}}} = \frac{\partial {\bar{G}}_1(q_1^{\text {os}}|r_1^{\text {os}})}{\partial r_1^{\text {os}}} \ge 0 \end{aligned}$$

    As a result, \(\frac{\partial {\tilde{r}}_1^{\text {os}}(q_1^{\text {os}})}{\partial q_1^{\text {os}}} \ge 0\) ( Topkis 1998). The proof for \(\frac{\partial {\tilde{r}}_2^{\text {os}}(q_2^{\text {os}})}{\partial q_2^{\text {os}}} \ge 0\) is analogous.

  3. (c)

    Because the suppliers’ profit functions are concave, then there exists a NE for the game. Also, \(\frac{\partial \varTheta _1^{\text {os}}}{\partial r_2^{\text {os}}} = 0\) and \(\frac{\partial \varTheta _2^{\text {os}}}{\partial r_1^{\text {os}}} = 0\). Consequently, the investment decisions of the suppliers have no effect on one another. Because the optimal solution of the suppliers is unique, in this situation, the NE of the game is unique and can be found using first-order conditions.

\(\square \)

Proof of Proposition 12

  1. (a)

    Consider the following cases: the first derivative of \({\hat{\varPi }}^{\text {os}}\) with respect to \(q^{\text {os}}\) is:

    $$\begin{aligned} \frac{\partial {\hat{\varPi }}^{\text {os}}}{\partial q^{\text {os}}}&= p {\bar{F}}(q^{\text {os}}) {\bar{G}}_1(q^{\text {os}}|{\tilde{r}}_1^{\text {os}}(q^{\text {os}})) {\bar{G}}_2(q^{\text {os}}|{\tilde{r}}_2^{\text {os}}(q^{\text {os}})) - w_1 {\bar{G}}_1(q^{\text {os}}|{\tilde{r}}_1^{\text {os}}(q^{\text {os}})) \nonumber \\&\quad - w_2 {\bar{G}}_2(q^{\text {os}}|{\tilde{r}}_2^{\text {os}}(q^{\text {os}})) \nonumber \\&\quad + p \frac{\partial {\tilde{r}}_2^{\text {os}}(q^{\text {os}})}{\partial q^{\text {os}}} \int _{0}^{q^{\text {os}}} {\bar{F}}(u) {\bar{G}}_1(u|{\tilde{r}}_1^{\text {os}}(q^{\text {os}})) \frac{\partial {\bar{G}}_2(u|{\tilde{r}}_2^{\text {os}}(q^{\text {os}}))}{\partial {\tilde{r}}_2^{\text {os}}} du \nonumber \\&\quad + p \frac{\partial {\tilde{r}}_1^{\text {os}}(q^{\text {os}})}{\partial q^{\text {os}}} \int _{0}^{q^{\text {os}}} {\bar{F}}(u) {\bar{G}}_2(u|{\tilde{r}}_2^{\text {os}}(q^{\text {os}})) \frac{\partial {\bar{G}}_1(u|{\tilde{r}}_1^{\text {os}}(q^{\text {os}}))}{\partial {\tilde{r}}_1^{\text {os}}} du \nonumber \\&\quad - w_1 \frac{\partial {\tilde{r}}_1^{\text {os}}(q^{\text {os}})}{\partial q^{\text {os}}} \int _{0}^{q^{\text {os}}} \frac{\partial {\bar{G}}_1(u|{\tilde{r}}_1^{\text {os}}(q^{\text {os}}))}{\partial {\tilde{r}}_1^{\text {os}}} du \nonumber \\&\quad - w_2 \frac{\partial {\tilde{r}}_2^{\text {os}}(q^{\text {os}})}{\partial q^{\text {os}}} \int _{0}^{q^{\text {os}}} \frac{\partial {\bar{G}}_2(u|{\tilde{r}}_2^{\text {os}}(q^{\text {os}}))}{\partial {\tilde{r}}_2^{\text {os}}} du \end{aligned}$$
    (34)

    Based on Eqs. (22), (23), and (24) and the fact that \({\tilde{r}}_1^{\text {os}}(q) = r_1^{\text {so}^*}(q)\), \({\tilde{r}}_2^{\text {os}}(q) = r_2^{\text {so}^*}(q)\), \({\bar{F}}(u) {\bar{G}}_2(u|{\tilde{r}}_2^{\text {os}}(q^{\text {os}})) \ge 0\), \(\forall u \le q^{\text {so}^*}\), and \({\bar{F}}(u) {\bar{G}}_1(u|{\tilde{r}}_1^{\text {os}}(q^{\text {os}})) \ge 0\), \(\forall u \le q^{\text {so}^*}\), then we have \(\frac{\partial {\hat{\varPi }}^{\text {os}}}{\partial q^{\text {os}}}(q^{\text {so}^*}) \ge 0\). This implies that \(q^{\text {os}^*} \ge q^{\text {so}^*}\).

  2. (b)

    Because \({\tilde{r}}_1^{\text {os}}(q) = r_1^{\text {so}^*}(q)\), \(q^{\text {os}^*} \ge q^{\text {so}^*}\), and \(\frac{\partial {\tilde{r}}_1^{\text {os}}(q^{\text {os}})}{\partial q^{\text {os}}} \ge 0\), then \(r_1^{\text {os}^*} = {\tilde{r}}_1^{\text {os}} (q^{\text {os}^*}) \ge r_1^{\text {so}^*}\). The proof for \(r_2^{\text {os}^*} = {\tilde{r}}_2^{\text {os}} (q^{\text {os}^*}) \ge r_2^{\text {so}^*}\) is analogous.

  3. (c)

    The first derivative of \(\varTheta _1^{\text {os}}\) with respect to \(q^{\text {os}}\) is:

    $$\begin{aligned} \frac{\partial \varTheta _1^{\text {os}}}{q^{\text {os}}}&= (w_1-c_1) {\bar{G}}_1(q^{\text {os}}|r_1^{\text {os}}) du \ge 0 \end{aligned}$$

    As result, \(\varTheta _1^{\text {os}}\) is an increasing function of \(q^{\text {os}}\). Note that \(\varTheta _1^{\text {os}} (q, r_1) = \varTheta _1^{\text {so}} (q, r_1)\). Because \(q^{\text {os}^*} \ge q^{\text {so}^*}\), then \(\varTheta _1^{\text {os}^*}(q^{\text {os}^*}, r_1^{\text {os}^*}) \ge \varTheta _1^{\text {so}^*}(q^{\text {so}^*}, r_1^{\text {so}^*})\). The proof for \(\varTheta _2^{\text {os}^*}(q^{\text {os}^*}, r_2^{\text {os}^*}) \ge \varTheta _2^{\text {so}^*}(q^{\text {so}^*}, r_2^{\text {so}^*})\) is analogous.

  4. (d)

    Because \({\tilde{r}}_1^{\text {os}}(q) = r_1^{\text {so}^*}(q)\) and \({\tilde{r}}_2^{\text {os}}(q) = r_2^{\text {so}^*}(q)\), then \(\varPi ^{\text {os}^*}(q) = \varPi ^{\text {so}^*}(q)\). Based on Eqs. (22) and (34), we have:

    $$\begin{aligned} \varPi ^{\text {os}^*}(q^{\text {os}^*}) \ge \varPi ^{\text {os}^*}(q^{\text {so}^*}) = \varPi ^{\text {so}^*}(q^{\text {so}^*}), \end{aligned}$$

    which completes the proof.

\(\square \)

Proof of Proposition 13

  1. (a)

    Since the suppliers are similar to each other, in the equilibrium, \(r_1^{\text {so}^*}=r_2^{\text {so}^*}=\cdots =r_n^{\text {so}^*}\). Similar to Lemma 3 and Proposition 4, it is fairly easy to show that the optimal decisions of the players are supermodular with respect to each other and the objective functions of the players are increasing functions with respect to each others decisions. Therefore. there exists an equilibrium which is greater than all the other possible equilibriums that results in higher profits for all the players.

  2. (b)

    Similar to Proposition 10 Part (a), we can show that \(\frac{\partial \varTheta _i^{\text {ov}}}{\partial r_i^{\text {ov}}}(r_1, \ldots , r_n) \ge \frac{\partial \varTheta _i^{\text {so}}}{\partial r_i^{\text {so}}}(r_1, \ldots , r_n) \). Therefore \(r_i^{\text {ov}^*} \ge r_i^{\text {so}^*}\), \(\forall i\). In addition, similar to Proposition 10 Part (b), we can show that for similar suppliers’ investments, the manufacturer’s optimal order quantities in simultaneous ordering and investment and ordering before realization of capacities scenarios are equal. Since \(r_i^{\text {ov}^*} \ge r_i^{\text {so}^*}\), \(\forall i\) and the problem is supermodular, then \(q^{\text {ov}^*} \ge q^{\text {so}^*}\).

  3. (c)

    The proof is similar to Proposition 10 Part (c).

  4. (d)

    The proof is similar to Proposition 10 Part (d).

  5. (e)

    Similar to Proposition 11 Part (a), we can show that \(\frac{\partial \varPi ^{\text {os}}}{\partial q^{\text {os}}}(q^{\text {so}^*}) \ge 0\). As a result, \(q^{\text {os}^*} \ge q^{\text {so}^*}\). In addition, it is easy to show that manufacturer’s and the suppliers’ objective functions are supermodular and consequently, \(r_i^{\text {os}^*} \ge r_i^{\text {so}^*}\), \(\forall i\).

  6. (f)

    The proof is similar to Proposition 11 Part (c)

  7. (g)

    The proof is similar to Proposition 11 Part (d)

\(\square \)

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Golmohammadi, A., Tajbakhsh, A., Dia, M. et al. Effect of timing on reliability improvement and ordering decisions in a decentralized assembly system. Ann Oper Res 312, 159–192 (2022). https://doi.org/10.1007/s10479-019-03399-5

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