Supply chain resilience in Finnish SME family firms

Paper delivered at the 21st Logistics Research Network annual conference 2016, 7th-9th September 2016, Hull. Abstract Purpose: The challenging economic landscape in Finland has brought about a stronger need among firms to manage risk and uncertainty in order to maintain operational performance and supply chain continuity. Given this turbulent environment, the contribution and commercial activities that small and medium sized family firms provide for the Finnish economy require them to have knowledge of drivers of risk and the tools to mitigate it. The purpose of this paper is to analyze how resilient small- and medium-sized (SME) family firm supply chains are operating during the current economic turbulence in Finland. Research Approach: The empirical study for this paper took an inductive research approach by devising a framework from the literature on family firm capabilities and supply chain risk and resilience, and then investigating the strength of the framework through qualitative data collection. Multiple-case studies were conducted including pilot and semi-structured interviews with respondents representing six SME family firms active in Finland. Findings and Originality: Risk drivers and key capabilities connected to SME family firms have been identified. The subject of supply chain resilience was perceived as an abstract subject by several firms, but gained increased interest throughout the research. Several resilience-promoting activities are already being conducted by some firms, nevertheless areas of improvement have also been identified. Despite the growing interest of SMEs in risk and resilience not many studies have been conducted on how SME family firms manage their supply chain resilience; thus this study bridges a gap by combining these two elements. Research Impact: There are many different studies on SME family firms but research on how capabilities of the family firm influences supply chain resilience has not received a great degree of academic interest. Further, prior empirical research on how SME family firms manage supply chain risk and resilience in practice is scarce. This study thus informs the literature on these aspects. Practical Impact: The findings of this study contribute valuable insights to managers active in SME family firms when evaluating their level of business risk and uncertainty, particularly relating to their supply chain activities. Further, the findings offer practical guidelines to help improve supply chain continuity and resilience

A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain

[EN] The challenges of global economies foster supply chains to have to increase their processes of collaboration and dependence between their nodes, generating an increase in the level of vulnerability to possible impacts and interruptions in their operations that may affect their sustainability. This has developed an emerging area of interest in supply chain management, considering resilience management as a strategic capability of companies, and causing an increase in this area of research. Additionally, supply chains should deal with the three dimensions of sustainability (economic, environmental, and social dimensions) by incorporating the three types of objectives in their strategy. Thus, there is a need to integrate both resilience and sustainability in supply chain management to increase competitiveness. In this paper, a systematic literature review is undertaken to analyze resilience management and its connection to increase supply chain sustainability. In the review, 232 articles published from 2000 to February 2020 in peer-reviewed journals in the Scopus and ScienceDirect databases are analyzed, classified, and synthesized. With the results, this paper develops a conceptual framework that integrates the fundamental elements for analyzing, measuring, and managing resilience to increase sustainability in the supply chain. Finally, conclusions, limitations, and future research lines are exposed.This study was supported by the Valencian Government in Spain (Project AEST/2019/019).Zavala-Alcívar, A.; Verdecho Sáez, MJ.; Alfaro Saiz, JJ. (2020). A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain. Sustainability. 12(16):1-38. https://doi.org/10.3390/su12166300S1381216Roberta Pereira, C., Christopher, M., & Lago Da Silva, A. (2014). Achieving supply chain resilience: the role of procurement. Supply Chain Management: An International Journal, 19(5/6), 626-642. doi:10.1108/scm-09-2013-0346Pettit, T. J., Fiksel, J., & Croxton, K. L. (2010). ENSURING SUPPLY CHAIN RESILIENCE: DEVELOPMENT OF A CONCEPTUAL FRAMEWORK. Journal of Business Logistics, 31(1), 1-21. doi:10.1002/j.2158-1592.2010.tb00125.xPettit, T. J., Croxton, K. L., & Fiksel, J. (2013). Ensuring Supply Chain Resilience: Development and Implementation of an Assessment Tool. Journal of Business Logistics, 34(1), 46-76. doi:10.1111/jbl.12009Ponis, S. T., & Koronis, E. (2012). Supply Chain Resilience: Definition Of Concept And Its Formative Elements. Journal of Applied Business Research (JABR), 28(5), 921. doi:10.19030/jabr.v28i5.7234Seuring, S., & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699-1710. doi:10.1016/j.jclepro.2008.04.020Qorri, A., Mujkić, Z., & Kraslawski, A. (2018). A conceptual framework for measuring sustainability performance of supply chains. Journal of Cleaner Production, 189, 570-584. doi:10.1016/j.jclepro.2018.04.073Verdecho, M.-J., Alarcón-Valero, F., Pérez-Perales, D., Alfaro-Saiz, J.-J., & Rodríguez-Rodríguez, R. (2020). A methodology to select suppliers to increase sustainability within supply chains. Central European Journal of Operations Research, 29(4), 1231-1251. doi:10.1007/s10100-019-00668-3Edgeman, R., & Wu, Z. (2016). Supply chain criticality in sustainable and resilient enterprises. Journal of Modelling in Management, 11(4), 869-888. doi:10.1108/jm2-10-2014-0078Marchese, D., Reynolds, E., Bates, M. E., Morgan, H., Clark, S. S., & Linkov, I. (2018). Resilience and sustainability: Similarities and differences in environmental management applications. Science of The Total Environment, 613-614, 1275-1283. doi:10.1016/j.scitotenv.2017.09.086Ahern, J. (2012). Urban landscape sustainability and resilience: the promise and challenges of integrating ecology with urban planning and design. Landscape Ecology, 28(6), 1203-1212. doi:10.1007/s10980-012-9799-zRamezankhani, M. J., Torabi, S. A., & Vahidi, F. (2018). Supply chain performance measurement and evaluation: A mixed sustainability and resilience approach. Computers & Industrial Engineering, 126, 531-548. doi:10.1016/j.cie.2018.09.054Shashi, Centobelli, P., Cerchione, R., & Ertz, M. (2019). Managing supply chain resilience to pursue business and environmental strategies. Business Strategy and the Environment, 29(3), 1215-1246. doi:10.1002/bse.2428Ivanov, D. (2017). Revealing interfaces of supply chain resilience and sustainability: a simulation study. International Journal of Production Research, 56(10), 3507-3523. doi:10.1080/00207543.2017.1343507Fahimnia, B., & Jabbarzadeh, A. (2016). Marrying supply chain sustainability and resilience: A match made in heaven. Transportation Research Part E: Logistics and Transportation Review, 91, 306-324. doi:10.1016/j.tre.2016.02.007Ruiz-Benitez, R., López, C., & Real, J. C. (2019). Achieving sustainability through the lean and resilient management of the supply chain. International Journal of Physical Distribution & Logistics Management, 49(2), 122-155. doi:10.1108/ijpdlm-10-2017-0320Pavlov, A., Ivanov, D., Pavlov, D., & Slinko, A. (2019). Optimization of network redundancy and contingency planning in sustainable and resilient supply chain resource management under conditions of structural dynamics. Annals of Operations Research. doi:10.1007/s10479-019-03182-6Khot, S. B., & Thiagarajan, S. (2019). Resilience and sustainability of supply chain management in the Indian automobile industry. International Journal of Data and Network Science, 339-348. doi:10.5267/j.ijdns.2019.4.002Roostaie, S., Nawari, N., & Kibert, C. J. (2019). Sustainability and resilience: A review of definitions, relationships, and their integration into a combined building assessment framework. Building and Environment, 154, 132-144. doi:10.1016/j.buildenv.2019.02.042Davoudabadi, R., Mousavi, S. M., & Sharifi, E. (2020). An integrated weighting and ranking model based on entropy, DEA and PCA considering two aggregation approaches for resilient supplier selection problem. Journal of Computational Science, 40, 101074. doi:10.1016/j.jocs.2019.101074Carvalho, H., Duarte, S., & Cruz Machado, V. (2011). Lean, agile, resilient and green: divergencies and synergies. International Journal of Lean Six Sigma, 2(2), 151-179. doi:10.1108/20401461111135037Wang, Z., & Zhang, J. (2019). Agent-based evaluation of humanitarian relief goods supply capability. International Journal of Disaster Risk Reduction, 36, 101105. doi:10.1016/j.ijdrr.2019.101105Alikhani, R., Torabi, S. A., & Altay, N. (2019). Strategic supplier selection under sustainability and risk criteria. International Journal of Production Economics, 208, 69-82. doi:10.1016/j.ijpe.2018.11.018Zahiri, B., Zhuang, J., & Mohammadi, M. (2017). Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study. Transportation Research Part E: Logistics and Transportation Review, 103, 109-142. doi:10.1016/j.tre.2017.04.009Aboah, J., Wilson, M. M. J., Rich, K. M., & Lyne, M. C. (2019). Operationalising resilience in tropical agricultural value chains. Supply Chain Management: An International Journal, 24(2), 271-300. doi:10.1108/scm-05-2018-0204Statsenko, L., & Corral de Zubielqui, G. (2020). Customer collaboration, service firms’ diversification and innovation performance. Industrial Marketing Management, 85, 180-196. doi:10.1016/j.indmarman.2019.09.013Duong, L. N. K., & Chong, J. (2020). Supply chain collaboration in the presence of disruptions: a literature review. International Journal of Production Research, 58(11), 3488-3507. doi:10.1080/00207543.2020.1712491Bhamra, R., Dani, S., & Burnard, K. (2011). Resilience: the concept, a literature review and future directions. International Journal of Production Research, 49(18), 5375-5393. doi:10.1080/00207543.2011.563826Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain risk – Definition, measure and modeling. Omega, 52, 119-132. doi:10.1016/j.omega.2014.10.004Hohenstein, N.-O., Feisel, E., Hartmann, E., & Giunipero, L. (2015). Research on the phenomenon of supply chain resilience. International Journal of Physical Distribution & Logistics Management, 45(1/2), 90-117. doi:10.1108/ijpdlm-05-2013-0128Kamalahmadi, M., & Parast, M. M. (2016). A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research. International Journal of Production Economics, 171, 116-133. doi:10.1016/j.ijpe.2015.10.023Ali, A., Mahfouz, A., & Arisha, A. (2017). Analysing supply chain resilience: integrating the constructs in a concept mapping framework via a systematic literature review. Supply Chain Management: An International Journal, 22(1), 16-39. doi:10.1108/scm-06-2016-0197Umar, M., Wilson, M., & Heyl, J. (2017). Food Network Resilience Against Natural Disasters: A Conceptual Framework. SAGE Open, 7(3), 215824401771757. doi:10.1177/2158244017717570Stone, J., & Rahimifard, S. (2018). Resilience in agri-food supply chains: a critical analysis of the literature and synthesis of a novel framework. Supply Chain Management: An International Journal, 23(3), 207-238. doi:10.1108/scm-06-2017-0201Colicchia, C., Creazza, A., Noè, C., & Strozzi, F. (2019). Information sharing in supply chains: a review of risks and opportunities using the systematic literature network analysis (SLNA). Supply Chain Management: An International Journal, 24(1), 5-21. doi:10.1108/scm-01-2018-0003Annarelli, A., & Nonino, F. (2016). Strategic and operational management of organizational resilience: Current state of research and future directions. Omega, 62, 1-18. doi:10.1016/j.omega.2015.08.004Behzadi, G., O’Sullivan, M. J., Olsen, T. L., & Zhang, A. (2018). Agribusiness supply chain risk management: A review of quantitative decision models. Omega, 79, 21-42. doi:10.1016/j.omega.2017.07.005Kochan, C. G., & Nowicki, D. R. (2018). Supply chain resilience: a systematic literature review and typological framework. International Journal of Physical Distribution & Logistics Management, 48(8), 842-865. doi:10.1108/ijpdlm-02-2017-0099Hosseini, S., Ivanov, D., & Dolgui, A. (2019). Review of quantitative methods for supply chain resilience analysis. Transportation Research Part E: Logistics and Transportation Review, 125, 285-307. doi:10.1016/j.tre.2019.03.001Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. British Journal of Management, 14(3), 207-222. doi:10.1111/1467-8551.00375Rousseau, D. M., Manning, J., & Denyer, D. (2008). 11 Evidence in Management and Organizational Science: Assembling the Field’s Full Weight of Scientific Knowledge Through Syntheses. Academy of Management Annals, 2(1), 475-515. doi:10.5465/19416520802211651Zimmer, K., Fröhling, M., & Schultmann, F. (2015). Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. International Journal of Production Research, 54(5), 1412-1442. doi:10.1080/00207543.2015.1079340Natarajarathinam, M., Capar, I., & Narayanan, A. (2009). Managing supply chains in times of crisis: a review of literature and insights. International Journal of Physical Distribution & Logistics Management, 39(7), 535-573. doi:10.1108/09600030910996251Tang, C., & Tomlin, B. (2008). The power of flexibility for mitigating supply chain risks. International Journal of Production Economics, 116(1), 12-27. doi:10.1016/j.ijpe.2008.07.008Kleindorfer, P. R., & Saad, G. H. (2009). Managing Disruption Risks in Supply Chains. Production and Operations Management, 14(1), 53-68. doi:10.1111/j.1937-5956.2005.tb00009.xChristopher, M., & Peck, H. (2004). Building the Resilient Supply Chain. The International Journal of Logistics Management, 15(2), 1-14. doi:10.1108/09574090410700275Wu, T., Huang, S., Blackhurst, J., Zhang, X., & Wang, S. (2013). Supply Chain Risk Management: An Agent-Based Simulation to Study the Impact of Retail Stockouts. IEEE Transactions on Engineering Management, 60(4), 676-686. doi:10.1109/tem.2012.2190986Fang, H., & Xiao, R. (2013). Resilient closed-loop supply chain network design based on patent protection. International Journal of Computer Applications in Technology, 48(1), 49. doi:10.1504/ijcat.2013.055566Gong, J., Mitchell, J. E., Krishnamurthy, A., & Wallace, W. A. (2014). An interdependent layered network model for a resilient supply chain. Omega, 46, 104-116. doi:10.1016/j.omega.2013.08.002Mari, S., Lee, Y., & Memon, M. (2014). Sustainable and Resilient Supply Chain Network Design under Disruption Risks. Sustainability, 6(10), 6666-6686. doi:10.3390/su6106666Bueno-Solano, A., & Cedillo-Campos, M. G. (2014). Dynamic impact on global supply chains performance of disruptions propagation produced by terrorist acts. Transportation Research Part E: Logistics and Transportation Review, 61, 1-12. doi:10.1016/j.tre.2013.09.005Costantino, F., Gravio, G. D., Shaban, A., & Tronci, M. (2014). Replenishment policy based on information sharing to mitigate the severity of supply chain disruption. International Journal of Logistics Systems and Management, 18(1), 3. doi:10.1504/ijlsm.2014.062119Kristianto, Y., Gunasekaran, A., Helo, P., & Hao, Y. (2014). A model of resilient supply chain network design: A two-stage programming with fuzzy shortest path. Expert Systems with Applications, 41(1), 39-49. doi:10.1016/j.eswa.2013.07.009Raj, R., Wang, J. W., Nayak, A., Tiwari, M. K., Han, B., Liu, C. L., & Zhang, W. J. (2015). Measuring the Resilience of Supply Chain Systems Using a Survival Model. IEEE Systems Journal, 9(2), 377-381. doi:10.1109/jsyst.2014.2339552LOH, H. S., & THAI, V. V. (2015). Cost Consequences of a Port-Related Supply Chain Disruption. The Asian Journal of Shipping and Logistics, 31(3), 319-340. doi:10.1016/j.ajsl.2015.09.001Torabi, S. A., Baghersad, M., & Mansouri, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 79, 22-48. doi:10.1016/j.tre.2015.03.005Cardoso, S. R., Paula Barbosa-Póvoa, A., Relvas, S., & Novais, A. Q. (2015). Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty. Omega, 56, 53-73. doi:10.1016/j.omega.2015.03.008Salehi Sadghiani, N., Torabi, S. A., & Sahebjamnia, N. (2015). Retail supply chain network design under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 75, 95-114. doi:10.1016/j.tre.2014.12.015Dixit, V., Seshadrinath, N., & Tiwari, M. K. (2016). Performance measures based optimization of supply chain network resilience: A NSGA-II + Co-Kriging approach. Computers & Industrial Engineering, 93, 205-214. doi:10.1016/j.cie.2015.12.029Liu, F., Song, J.-S., & Tong, J. D. (2016). Building Supply Chain Resilience through Virtual Stockpile Pooling. Production and Operations Management, 25(10), 1745-1762. doi:10.1111/poms.12573Fahimnia, B., Jabbarzadeh, A., & Sarkis, J. (2018). Greening versus resilience: A supply chain design perspective. Transportation Research Part E: Logistics and Transportation Review, 119, 129-148. doi:10.1016/j.tre.2018.09.005Hasani, A., & Khosrojerdi, A. (2016). Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study. Transportation Research Part E: Logistics and Transportation Review, 87, 20-52. doi:10.1016/j.tre.2015.12.009Azhmyakov, V., Fernández-Gutiérrez, J. P., Gadi, S. K., & Pickl, S. (2016). A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization. IFAC-PapersOnLine, 49(31), 137-142. doi:10.1016/j.ifacol.2016.12.175Ivanov, D., Sokolov, B., Solovyeva, I., Dolgui, A., & Jie, F. (2016). Dynamic recovery policies for time-critical supply chains under conditions of ripple effect. International Journal of Production Research, 54(23), 7245-7258. doi:10.1080/00207543.2016.1161253Jabbarzadeh, A., Fahimnia, B., Sheu, J.-B., & Moghadam, H. S. (2016). Designing a supply chain resilient to major disruptions and supply/demand interruptions. Transportation Research Part B: Methodological, 94, 121-149. doi:10.1016/j.trb.2016.09.004Babich, V., Burnetas, A. N., & Ritchken, P. H. (2007). Competition and Diversification Effects in Supply Chains with Supplier Default Risk. Manufacturing & Service Operations Management, 9(2), 123-146. doi:10.1287/msom.1060.0122Bogataj, D., Aver, B., & Bogataj, M. (2016). Supply chain risk at simultaneous robust perturbations. International Journal of Production Economics, 181, 68-78. doi:10.1016/j.ijpe.2015.09.009Wang, X., Herty, M., & Zhao, L. (2015). Contingent rerouting for enhancing supply chain resilience from supplier behavior perspective. International Transactions in Operational Research, 23(4), 775-796. doi:10.1111/itor.12151Zeng, B., & Yen, B. P.-C. (2017). Rethinking the role of partnerships in global supply chains: A risk-based perspective. International Journal of Production Economics, 185, 52-62. doi:10.1016/j.ijpe.2016.12.004Lücker, F., & Seifert, R. W. (2017). Building up Resilience in a Pharmaceutical Supply Chain through Inventory, Dual Sourcing and Agility Capacity. Omega, 73, 114-124. doi:10.1016/j.omega.2017.01.001Fattahi, M., Govindan, K., & Keyvanshokooh, E. (2017). Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers. Transportation Research Part E: Logistics and Transportation Review, 101, 176-200. doi:10.1016/j.tre.2017.02.004Kırılmaz, O., & Erol, S. (2017). A proactive approach to supply chain risk management: Shifting orders among suppliers to mitigate the supply side risks. Journal of Purchasing and Supply Management, 23(1), 54-65. doi:10.1016/j.pursup.2016.04.002Li, H., Pedrielli, G., Lee, L. H., & Chew, E. P. (2016). Enhancement of supply chain resilience through inter-echelon information sharing. Flexible Services and Manufacturing Journal, 29(2), 260-285. doi:10.1007/s10696-016-9249-3Otto, C., Willner, S. N., Wenz, L., Frieler, K., & Levermann, A. (2017). Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate. Journal of Economic Dynamics and Control, 83, 232-269. doi:10.1016/j.jedc.2017.08.001Rezapour, S., Farahani, R. Z., & Pourakbar, M. (2017). Resilient supply chain network design under competition: A case study. European Journal of Operational Research, 259(3), 1017-1035. doi:10.1016/j.ejor.2016.11.041Ledwoch, A., Yasarcan, H., & Brintrup, A. (2018). The moderating impact of supply network topology on the effectiveness of risk management. International Journal of Production Economics, 197, 13-26. doi:10.1016/j.ijpe.2017.12.013Al-Othman, W. B. E., Lababidi, H. M. S., Alatiqi, I. M., & Al-Shayji, K. (2008). Supply chain optimization of petroleum organization under uncertainty in market demands and prices. European Journal of Operational Research, 189(3), 822-840. doi:10.1016/j.ejor.2006.06.081Ivanov, D., Dolgui, A., & Sokolov, B. (2017). Scheduling of recovery actions in the supply chain with resilience analysis considerations. International Journal of Production Research, 56(19), 6473-6490. doi:10.1080/00207543.2017.1401747Das, K. (2019). Integrating Lean, Green, and Resilience Criteria in a Sustainable Food Supply Chain Planning Model. International Journal of Mathematical, Engineering and Management Sciences, 4(2), 259-275. doi:10.33889/ijmems.2019.4.2-022Das, K. (2018). Integrating resilience in a supply chain planning model. International Journal of Quality & Reliability Management, 35(3), 570-595. doi:10.1108/ijqrm-08-2016-0136Arora, V., & Ventresca, M. (2018). Modeling topologically resilient supply chain networks. Applied Network Science, 3(1). doi:10.1007/s41109-018-0070-7Almeida, J. F. de F., Conceição, S. V., Pinto, L. R., de Camargo, R. S., & Júnior, G. de M. (2018). Flexibility evaluation of multiechelon supply chains. PLOS ONE, 13(3), e0194050. doi:10.1371/journal.pone.0194050Mancheri, N. A., Sprecher, B., Deetman, S., Young, S. B., Bleischwitz, R., Dong, L., … Tukker, A. (2018). Resilience in the tantalum supply chain. Resources, Conservation and Recycling, 129, 56-69. doi:10.1016/j.resconrec.2017.10.018Namdar, J., Li, X., Sawhney, R., & Pradhan, N. (2017). Supply chain resilience for single and multiple sourcing in the presence of disruption risks. International Journal of Production Research, 56(6), 2339-2360. doi:10.1080/00207543.2017.1370149Rozhkov, M., & Ivanov, D. (2018). CONTINGENCY PRODUCTION-INVENTORY CONTROL POLICY FOR CAPACITY DISRUPTIONS IN THE RETAIL SUPPLY CHAIN WITH PERISHABLE PRODUCTS. IFAC-PapersOnLine, 51(11), 1448-1452. doi:10.1016/j.ifacol.2018.08.311Sabouhi, F., Pishvaee, M. S., & Jabalameli, M. S. (2018). Resilient supply chain design under operational and disruption risks considering quantity discount: A case study of pharmaceutical supply chain. Computers & Industrial Engineering, 126, 657-672. doi:10.1016/j.cie.2018.10.001Zavitsas, K., Zis, T., & Bell, M. G. H. (2018). The impact of flexible environmental policy on maritime supply chain resilience. Transport Policy, 72, 116-128. doi:10.1016/j.tranpol.2018.09.020Mitra, K., Gudi, R. D., Patwardhan, S. C., & Sardar, G. (2009). Towards resilient supply chains: Uncertainty analysis using fuzzy mathematical programming. Chemical Engineering Research and Design, 87(7), 967-981. doi:10.1016/j.cherd.2008.12.025Lücker, F., Seifert, R. W., & Biçer, I. (2018). Roles of inventory and reserve capacity in mitigating supply chain disruption risk. International Journal of Production Research, 57(4), 1238-1249. doi:10.1080/00207543.2018.15041

Building Information Modeling as Tool for Enhancing Disaster Resilience of the Construction Industry

As frequencies of the disasters are increasing, new technologies can be used to enhance disaster resilience performance of the construction industry. This paper investigates the usage of BIM (Building Information Modeling) in enhancing disaster resilience of the construction industry and in the establishment of the resilient built environment. In-depth literature review findings reveal BIM’s contribution to the disaster resilience in the pre-disaster and post-disaster phases especially through influencing the performance of the supply chain, construction process, and rescue operations. This paper emphasises the need for BIM’s integration to the education and training curriculums of the built environment professionals. Policy makers, construction professionals, professional bodies, academics can benefit from this research

The impact of nonlinear dynamics on the resilience of a grocery supply chain

Purpose of this paper: In an effort to improve operational and logistical efficiencies, UK grocery retailers combined primary and secondary distribution increasing the importance of designing resilient replenishment systems in the distribution centre. This paper has the purpose to analyse the resilience performance of the distribution centre stock ordering system within a grocery retailer. Design/methodology/approach: A system dynamics approach is used for framing and building a credible representation of the real system. Mathematical analysis of the nonlinear model based on nonlinear control engineering techniques in combination with system dynamics simulation have been used to understand the behaviour of stock and shipment output responses in the distribution centre given step and periodic demand signals. Findings: Preliminary mathematical analysis through nonlinear control theory techniques has been undertaken in order to gain initial insights in the understanding of the replenishment control model. This practice allowed the researcher to identify specific behaviour change in the DC stock and shipment responses, which are key indicators for assessing supply chain resilience, without going through a time-consuming simulation process. Transfer function analysis and describing function serve as a guideline for undertaking system dynamics simulation. Value: This paper aims to fill the gap in the literature of supply chain resilience by using quantitative system dynamics methods to assess the resilience performance of a grocery retailer. In this way, we also supplement the literature with empirical data. Moreover, we explore different analytical methods since simulation is the predominant method for quantitative analysis of system dynamics. Research limitations/implications (if applicable): This research is limited to the dynamics of single-echelon supply chain systems. Although the EPOS sales data and the store replenishment system have been considered in the validation process, this study has focused on analysing the resilience performance of the DC replenishment system only. Considering the multi-echelon supply chain is intended for further research activities. Practical implications (if applicable): The findings suggest that the distribution centre replenishment system can be re-designed in order to improve the supply chain resilience performance. The ‘As Is’ scenario produces slow response of stock levels and inventory targets are never recovered due to a permanent offset

GResilient index to assess the greenness and resilience of the automotive supply chain

Purpose: The purpose of this paper is to suggest an Index entitled GResilient Index to assess the greenness and resilience of the automotive companies and corresponding supply chain. Design/methodology/approach: An integrated assessment model is proposed based on Green and Resilient practices. These practices are weighted according to their importance to the automotive supply chain competitiveness. The Delphi technique is used to obtain the weights for the focused supply chain paradigms and corresponding practices. The model is then tested using a case study approach in the automotive supply chain. Findings: The case study results confirmed the applicability of this Index in a real-world supply chain. The results show that the Resilient supply chain management paradigm is the one considered as the one that more contributes for the automotive supply chain competitiveness. Research limitations/implications: The proposed Index was developed in the automotive sector context therefore it could not be adjusted to a different one. Future research could consider other aggregation methods for the Index construction. Practical implications: Supply chain participants will be able to evaluate the performance of their companies or supply chain in terms of Green and Resilient paradigms. Also, the Index can be effectively employed for functional benchmarking among competing companies and supply chains.Green; resilient; supply chain management; index; automotive industry

Supply chain uncertainty:a review and theoretical foundation for future research

Supply-chain uncertainty is an issue with which every practising manager wrestles, deriving from the increasing complexity of global supply networks. Taking a broad view of supply-chain uncertainty (incorporating supply-chain risk), this paper seeks to review the literature in this area and develop a theoretical foundation for future research. The literature review identifies a comprehensive list of 14 sources of uncertainty, including those that have received much research attention, such as the bullwhip effect, and those more recently described, such as parallel interaction. Approaches to managing these sources of uncertainty are classified into: 10 approaches that seek to reduce uncertainty at its source; and, 11 approaches that seek to cope with it, thereby minimising its impact on performance. Manufacturing strategy theory, including the concepts of alignment and contingency, is then used to develop a model of supply-chain uncertainty, which is populated using the literature review to show alignment between uncertainty sources and management strategies. Future research proposed includes more empirical research in order to further investigate: which uncertainties occur in particular industrial contexts; the impact of appropriate sources/management strategy alignment on performance; and the complex interplay between management strategies and multiple sources of uncertainty (positive or negative)

An integrated approach to supply chain risk analysis

Despite the increasing attention that supply chain risk management is receiving by both researchers and practitioners, companies still lack a risk culture. Moreover, risk management approaches are either too general or require pieces of information not regularly recorded by organisations. This work develops a risk identification and analysis methodology that integrates widely adopted supply chain and risk management tools. In particular, process analysis is performed by means of the standard framework provided by the Supply Chain Operations Reference Model, the risk identification and analysis tasks are accomplished by applying the Risk Breakdown Structure and the Risk Breakdown Matrix, and the effects of risk occurrence on activities are assessed by indicators that are already measured by companies in order to monitor their performances. In such a way, the framework contributes to increase companies' awareness and communication about risk, which are essential components of the management of modern supply chains. A base case has been developed by applying the proposed approach to a hypothetical manufacturing supply chain. An in-depth validation will be carried out to improve the methodology and further demonstrate its benefits and limitations. Future research will extend the framework to include the understanding of the multiple effects of risky events on different processe

Supply Chain Resilience: Antecedents and Driver in Global Competition

En el actual entorno altamente competitivo, las empresas de todo el mundo buscan formas innovadoras de incrementar la resiliencia de sus cadenas de suministro sin perder eficiencia operacional y ventaja competitiva. En esta tesis doctoral se analiza la creación de resiliencia atendiendo a dos aspectos. En primer lugar, estudiamos el novedoso concepto de sincromodalidad en el mundo del transporte y su efecto sobre la resiliencia y la eficiencia. En segundo lugar, examinamos el efecto que la Gestión de Riesgos en la Cadena de Suministro(SCRM) tiene sobre la resiliencia, cuantificando la reducción de eventos disruptivos.La sincromodalidad es un concepto de transporte novedoso que integra el uso de diversos modos de transporte en base a información en tiempo real. La sincromodalidad se entiende como un planteamiento operativo para mejorar los objetivos de desempeño en cuanto a eficiencia y resiliencia, con el potencial añadido de generar ventaja competitiva mediante la diferenciación logística. No obstante, el trabajo existente al respecto se encuentra todavía en una etapa incipiente, no existiendo todavía un consenso acerca de los mecanismos que propician el desarrollo de una cadena de suministro sincromodal. Asimismo, sus resultados no se han analizado empíricamente. Para salvar esta brecha, presentamos un análisis pormenorizado de sincromodalidad y de sus dimensiones subyacentes. Mediante la aplicación de una metodología en cuatro etapas, se desarrolla el constructo multidimensional de sincromodalidad, formado por 4 dimensiones (visibilidad, flexibilidad, integración y sistema operativo). Un modelo de ecuaciones estructurales confirma su relación con la diferenciación logística como medida de la ventaja competitiva. Este análisis supone un enfoque del concepto de sincromodalidad respecto a la literatura existente, para comprenderlo mejor desde una perspectiva de gestión de operaciones y sentar las bases de las capacidades de la cadena de suministro que deben desarrollar aquellas empresas que adopten la sincromodalidad.Utilizando esta investigación como punto de partida, analizamos los efectos que la implantación de la sincromodalidad tiene en la cadena de suministro, medidos en términos de eficiencia y resiliencia. Utilizando información proveniente de 157 empresas logísticas que trabajan con expedidores de carga que aplican actualmente la sincromodalidad en Europa, presentamos un modelo de ecuaciones estructurales para analizar la relación entre sincromodalidad, eficiencia y resiliencia. Además, adoptamos un enfoque configuracional y realizamos un análisis de clústeres para seguir avanzando en la comprensión del vínculo eficiencia-resiliencia mediante distintos contextos sincromodales medidos por las cuatro dimensiones de sincromodalidad identificadas. Nuestros hallazgos indican que las empresas que fomentan un entorno sincromodal en sus operaciones no sólo son más eficientes desde el punto de vista de la logística y el transporte, sino que además son menos propensas a las disrupciones. Sin embargo, los niveles de eficiencia y resiliencia difieren según el grado de sincromodalidad alcanzado por la cadena de suministro.En segundo lugar, el estudio de la resiliencia ha suscitado el interés de los investigadores por el análisis de determinadas prácticas de gestión de riesgos en la cadena de suministro, tales como la colaboración y la formalización de procesos. Con todo, son escasas las investigaciones que cuantifican los efectos de estas prácticas, lo que nos animó a examinar en qué medida la Gestión de Riesgos en la Cadena de Suministro (SCRM) colaborativa y formal puede contribuir a reducir la propensión a sufrir un evento disruptivo. Para estimar estos efectos, desarrollamos una metodología de efecto de tratamiento multivariable basada en análisis experimentales y la aplicamos a una base de datos global consistente en 1.461 encuestados procedentes de 69 países. Para terminar, analizamos el efecto moderador que tiene el tamaño de la empresa y el tipo de industria sobre el enfoque de gestión del riesgo adoptado para abordar distintas disrupciones. Nuestra investigación sugiere que los enfoques colaborativos de SCRM son máseficaces en grandes empresas manufactureras que operan en entornos de mercado volátiles, mientras que las estructuras formales de SCRM benefician sobre todo a pequeñas y medianas empresas que afrontan riesgos operativos.In the current highly competitive environment, companies around the globe are looking for innovative ways to increase their supply chain resilience while maintaining their operational efficiency and competitive advantage. In this dissertation, we analyze the creation of resilience focusing on two aspects. First, we study the novel transportation concept of synchromodality and its effect on resiliency and efficiency. Secondly, we explore the resiliency effect Supply Chain Risk Management (SCRM) quantifying the reduction of disruptive events. Synchromodality is a novel transportation concept that integrates the use of different transport modes based on real time information. Synchromodality is envisioned as an operational approach to improve performance targets in terms of efficiency and resilience, with the added potential to create a competitive advantage through logistics differentiation. However, the existing research is in an incipient stage, there is no consensus on the mechanisms that create a synchromodal supply chain and its results have not been empirically studied. To fill this gap, we present a thorough analysis of synchromodality and its underlying dimensions. Subsequently, using a four-stages methodology, synchromodality is operationalized as a multidimensional construct formed by 4 dimensions (visibility, flexibility, integration and operating system). A structural equation model confirms its relationship with logistics differentiation as a measure of competitive advantage. This analysis provides a holistic approach of the concept of synchromodality, advancing in its understanding from an operations management perspective and setting the foundations of the supply chain capabilities that companies pursuing synchromodality should develop. Building on the developed research of synchromodality, we analyze the effect that its implementation has in the supply chain in terms of efficiency and resilience. Based on data from 157 logistics companies involved with a shipper currently implementing synchromodality in Europe, we present a structural equation model that analyzes the relationship between synchromodality, efficiency and resilience. Additionally, we use a configurational approach and a cluster analysis to further advance on the understanding of the efficiency-resilience relationship based on different synchromodal contexts measured by the four identified dimensions of synchromodality. Our findings indicate that that companies that promote a synchromodal environment in their operations are not only more efficient from a logistics and transportation perspective, but they are also less prone to disruptions. However, the levels of efficiency and resilience will differ based on the level of synchromodality achieved by the supply chain. Secondly, the study of resilience has drove the attention of researchers towards the analysis of certain supply chain risk management practices, such as collaboration and process formalization. However, there is a lack of research presenting a quantification of the effects of these practices, which lead us to explore how collaborative and formal Supply Chain Risk Management (SCRM) can contribute to a reduction of the propensity to suffer a disruptive event. To estimate these effects, we develop a multivalued treatment effect methodology based on experimental analysis and apply it to global dataset of 1,461 respondents from 69 countries. To conclude, we analyze the moderation effect that firm size and industry type has on the type of risk management approach when dealing with different disruptions. Our research suggests that collaborative SCRM approaches are more effective on large manufacturing firms operating in volatile market environments, while formal SCRM structures benefits the most small and medium companies dealing with operational risks.<br /

Review of Quantitative Methods for Supply Chain Resilience Analysis

Supply chain resilience (SCR) manifests when the network is capable to withstand, adapt, and recover from disruptions to meet customer demand and ensure performance. This paper conceptualizes and comprehensively presents a systematic review of the recent literature on quantitative modeling the SCR while distinctively pertaining it to the original concept of resilience capacity. Decision-makers and researchers can benefit from our survey since it introduces a structured analysis and recommendations as to which quantitative methods can be used at different levels of capacity resilience. Finally, the gaps and limitations of existing SCR literature are identified and future research opportunities are suggested