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The Role of Information Usage Between Information Sharing and Performance

Abdurrezzak Sener

https://orcid.org/0000-0003-0554-3285

Department of Project and Supply Chain Management, Penn State University, 100 University Drive, Monaca, PA 15061, USA

E-mail Address: aks6310@psu.edu

Corresponding author.

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Mutlu Yuksel Avcilar

https://orcid.org/0000-0001-5621-2377

Department of Management Information Systems, Faculty of Economics and Business Administration, Osmaniye Korkut Ata University, Karacaoglan Yerleskesi, 80000 Osmaniye, Turkey

E-mail Address: myukselavcilar@osmaniye.edu.tr

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Mehmet Barut

https://orcid.org/0000-0001-9882-8540

Department of Finance, Real Estate, and Decision Sciences, Barton School of Business, Wichita State University, 1845 North Fairmount Street, Wichita, KS 67260-0077, USA

E-mail Address: Mehmet.Barut@wichita.edu

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, and

Mehmet Bayram Yildirim

https://orcid.org/0000-0003-2900-3769

Department of Industrial, Systems and Manufacturing Engineering College of Engineering, Wichita State University, 1845 North Fairmount Street, Wichita, KS 67260-0035, USA

E-mail Address: Bayram.Yildirim@wichita.edu

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https://doi.org/10.1142/S0219649224500965Cited by:0 (Source: Crossref)

Abstract

The purpose of this study was to provide a holistic approach to establishing dyadic relationships between information sharing and operational performance as well as between operational and organisational performances into an extended relationship between ultimate suppliers and ultimate customers from the suppliers’ point of view. We introduced mediating impacts of information usage between information sharing and operational performance and perceived logistics performance between operational and organisational performances. The empirical data obtained from 209 retailers via a survey reveals that the integrated relationships are valid and significant. The mediating impacts of both information usage and perceived performance of logistics play a significant role in performance relationships and are paramount to the success of organisations.

Keywords:

References

Abubakar, AM, H Elrehail, MA Alatailat and A Elçi (2019). Knowledge management, decision-making style and organizational performance. Journal of Innovation & Knowledge, 4(2), 104–114. Crossref, Web of Science, Google Scholar
AlShakhs, BH and NK Agarwal (2022). Information-seeking behaviour and knowledge transfer: A case study of family business owners in Kuwait. Journal of Information & Knowledge Management, 21(3), 2250038. Link, Google Scholar
Anvari, A, N Zulkifli and RM Yusuff (2013). A dynamic modeling to measure lean performance within lean attributes. The International Journal of Advanced Manufacturing Technology, 66(5–8), 663–677. Crossref, Web of Science, Google Scholar
Altay, N, A Gunasekaran, R Dubey and SJ Childe (2018). Agility and resilience as antecedents of supply chain performance under moderating effects of organizational culture within the humanitarian setting: A dynamic capability view. Production planning & control, 29(14), 1158–1174. Crossref, Web of Science, Google Scholar
Aramyan, LH, AG Oude Lansink, JG Van Der Vorst and O Van Kooten (2007). Performance measurement in agri-food supply chains: A case study. Supply Chain Management: An International Journal, 12(4), 304–315. Crossref, Web of Science, Google Scholar
Arbós, LC (2002). Design of a rapid response and high efficiency service by lean production principles: Methodology and evaluation of variability of performance. International Journal of Production Economics, 80(2), 169–183. Crossref, Web of Science, Google Scholar
Armstrong, CE and K Shimizu (2007). A review of approaches to empirical research on the resource-based view of the firm. Journal of Management, 33(6), 959–986. Crossref, Web of Science, Google Scholar
Asrol, M, M Marimin, M Yani, and E Taira (2021). Risk management for improving supply chain performance of sugarcane agroindustry. Industrial Engineering Management System, 20(1), 9–26. Crossref, Web of Science, Google Scholar
Autry, CW, WJ Rose and JE Bell (2014). Reconsidering the supply chain integration–performance relationship: In search of theoretical consistency and clarity. Journal of Business Logistics, 35(3), 275–276. Crossref, Web of Science, Google Scholar
Baker, WE and JM Sinkula (1999). The synergistic effect of market orientation and learning orientation on organizational performance. Journal of the Academy of Marketing Science, 27(4), 411–427. Crossref, Web of Science, Google Scholar
Barut, M, W Faisst and JJ Kanet (2002). Measuring supply chain coupling: An information system perspective. European Journal of Purchasing & Supply Management, 8(3), 161–171. Crossref, Google Scholar
Beamon, BM (1999). Measuring supply chain performance. International Journal of Operations and Production Management, 19(3), 275–292. Crossref, Web of Science, Google Scholar
Benton, W and M Maloni (2005). The influence of power driven buyer/seller relationships on supply chain satisfaction. Journal of Operations Management, 23(1), 1–22. Crossref, Web of Science, Google Scholar
Beretta, S (2002). Unleashing the integration potential of ERP systems: The role of process-based performance measurement systems. Business Process Management Journal, 8(3), 254–277. Crossref, Google Scholar
Bhosale, VA and R Kant (2020). Analysing the interrelationship among supply chain knowledge flow barriers: A DEISMI approach. Journal of Information & Knowledge Management, 19(4), 2050028. Link, Web of Science, Google Scholar
Birch-Jensen, A, I Gremyr and Á Halldórsson (2021). Absorptive capacity as enabler for service improvement — The role of customer satisfaction information usage. Total Quality Management & Business Excellence, 32(15–16), 1651–1665. Crossref, Google Scholar
Blanchard, D (2021). Supply Chain Management Best Practices. John Wiley & Sons. Crossref, Google Scholar
Bobbitt, LM (2004). An examination of the logistics leverage process: Implications for marketing strategy and competitive advantage. Ph.D. Dissertation, University of Tennessee, Knoxville. Google Scholar
Boon-itt, S and H Paul (2006). A study of supply chain integration in Thai automotive industry: A theoretical framework and measurement. Management Research News, 29(4), 194–205. https://doi.org/10.1108/01409170610665059. Crossref, Google Scholar
Bourne, M, J Mills, M Wilcox, A Neely and K Platts (2000). Designing, implementing and updating performance measurement systems. International Journal of Operations and Production Management, 20(7), 754–771. Crossref, Web of Science, Google Scholar
Bryson, JM, BC Crosby and MM Stone (2006). The design and implementation of cross-sector collaborations: Propositions from the literature. Public Administration Review, 66(Suppl. 1), 44–55. Crossref, Google Scholar
Busse, C, J Meinlschmidt and K Foerstl (2017). Managing information processing needs in global supply chains: A prerequisite to sustainable supply chain management. Journal of Supply Chain Management, 53(1), 87–113. Crossref, Web of Science, Google Scholar
Cachon, GP and MA Lariviere (2001). Contracting to assure supply: How to share demand forecasts in a supply chain. Management Science, 47(5), 629–646. Crossref, Web of Science, Google Scholar
Caplice, C and Y Sheffi (1994). A review and evaluation of logistics metrics. The International Journal of Logistics Management, 5(2), 11–28. Crossref, Google Scholar
Carr, AS and H Kaynak (2007). Communication methods, information sharing, supplier development and performance: An empirical study of their relationships. International Journal of Operations and Production Management, 27(4), 346–370. Crossref, Web of Science, Google Scholar
Chan, FT (2003). Performance measurement in a supply chain. The International Journal of Advanced Manufacturing Technology, 21(7), 534–548. Crossref, Web of Science, Google Scholar
Chan, FT and HJ Qi (2003). An innovative performance measurement method for supply chain management. Supply Chain Management: An International Journal, 8(3), 209–223. Crossref, Web of Science, Google Scholar
Chen, M (2023). The effect of big data capability and market-oriented knowledge integration on product speed-to-market. Journal of Information & Knowledge Management, 2350024. Link, Web of Science, Google Scholar
Chen, M, H Liu, S Wei and J Gu (2018). Top managers’ managerial ties, supply chain integration, and firm performance in China: A social capital perspective. Industrial Marketing Management, 74, 205–214. Crossref, Web of Science, Google Scholar
Chen, IJ and A Paulraj (2004). Understanding supply chain management: Critical research and a theoretical framework. International Journal of Production Research, 42(1), 131–163. Crossref, Web of Science, Google Scholar
Chin, WW (1998). Commentary: Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), vii–xvi. Web of Science, Google Scholar
Chow, G, TD Heaver and LE Henriksson (1994). Logistics performance: Definition and measurement. International Journal of Physical Distribution & Logistics Management, 24(1), 17–28. Crossref, Google Scholar
Cohen, J (1988). Statistical Power Analysis: A Computer Program. Routledge. Google Scholar
Cohen, WM and DA Levinthal (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. Crossref, Web of Science, Google Scholar
Croson, R and K Donohue (2005). Upstream versus downstream information and its impact on the bullwhip effect. System Dynamics Review, 21(3), 249–260. Crossref, Web of Science, Google Scholar
Cucchiella, F, L Koh, C Bai, J Sarkis and X Wei (2012). Evaluating ecological sustainable performance measures for supply chain management. Supply Chain Management: An International Journal, 17(1), 78–92. Crossref, Google Scholar
Dal Forno, AJ, FA Pereira, FA Forcellini and LM Kipper (2014). Value stream mapping: A study about the problems and challenges found in the literature from the past 15 years about application of lean tools. The International Journal of Advanced Manufacturing Technology, 72(5–8), 779–790. Crossref, Web of Science, Google Scholar
Daugherty, PJ, AE Ellinger and CM Gustin (1996). Integrated logistics: Achieving logistics performance improvements. Supply Chain Management: An International Journal, 1(3), 25–33. Crossref, Google Scholar
Demeter, K, H Forslund and P Jonsson (2007). The impact of forecast information quality on supply chain performance. International Journal of Operations and Production Management, 27(1), 90–107. Crossref, Google Scholar
Devaraj, S, L Krajewski and JC Wei (2007). Impact of eBusiness technologies on operational performance: The role of production information integration in the supply chain. Journal of Operations Management, 25(6), 1199–1216. Crossref, Web of Science, Google Scholar
De Vass, T, H Shee and SJ Miah (2018). The effect of “Internet of Things” on supply chain integration and performance: An organisational capability perspective. Australasian Journal of Information Systems, 22. https://journal.acs.org.au/index.php/ajis/article/view/1734. Crossref, Google Scholar
Dobson, G and EJ Pinker (2006). The value of sharing lead time information. IIE Transactions, 38(3), 171–183. Crossref, Google Scholar
Droge, C, J Jayaram and SK Vickery (2004). The effects of internal versus external integration practices on time-based performance and overall firm performance. Journal of Operations Management, 22(6), 557–573. Crossref, Web of Science, Google Scholar
Dubiel, A, S Banerjee, H Ernst and M Subramaniam (2018). International-market-information use across new-product-development stages: Antecedents and performance implications. International Marketing Review, 35(5), 760–784. https://doi.org/10.1108/IMR-05-2015-0128. Crossref, Web of Science, Google Scholar
Dyer, JH and H Singh (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23(4), 660–679. Crossref, Web of Science, Google Scholar
El-Kassar, AN and SK Singh (2019). Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices. Technological Forecasting and Social Change, 144, 483–498. Crossref, Web of Science, Google Scholar
Esper, TL, BS Fugate and B Davis-Sramek (2007). Logistics learning capability: Sustaining the competitive advantage gained through logistics leverage. Journal of Business Logistics, 28(2), 57–82. Crossref, Google Scholar
Fawcett, SE and GM Magnan (2002). The rhetoric and reality of supply chain integration. International Journal of Physical Distribution & Logistics Management, 32(5), 339–361. Crossref, Google Scholar
Fleisch, E and C Tellkamp (2005). Inventory inaccuracy and supply chain performance: A simulation study of a retail supply chain. International Journal of Production Economics, 95(3), 373–385. Crossref, Web of Science, Google Scholar
Flynn, BB, B Huo and X Zhao (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of Operations Management, 28(1), 58–71. Crossref, Web of Science, Google Scholar
Fornell, C and DF Larcker (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. Crossref, Web of Science, Google Scholar
Frohlich, MT and R Westbrook (2001). Arcs of integration: An international study of supply chain strategies. Journal of Operations Management, 19(2), 185–200. Crossref, Web of Science, Google Scholar
Frohlich, MT and R Westbrook (2002). Demand chain management in manufacturing and services: Web-based integration, drivers and performance. Journal of Operations Management, 20(6), 729–745. Crossref, Web of Science, Google Scholar
Fugate, BS, JT Mentzer and TP Stank (2010). Logistics performance: Efficiency, effectiveness, and differentiation. Journal of Business Logistics, 31(1), 43–62. Crossref, Web of Science, Google Scholar
Ganeshan, R, T Boone and AJ Stenger (2001). The impact of inventory and flow planning parameters on supply chain performance: An exploratory study. International Journal of Production Economics, 71(1), 111–118. Crossref, Web of Science, Google Scholar
Gilmour, P (1999). A strategic audit framework to improve supply chain performance. Journal of Business & Industrial Marketing, 14(5/6), 355–366. Crossref, Google Scholar
Gleason, JM and DT Barnum (1982). Toward valid measures of public sector productivity: Performance measures in urban transit. Management Science, 28(4), 379–386. Crossref, Web of Science, Google Scholar
Gligor, DM and M Holcomb (2014). The road to supply chain agility: An RBV perspective on the role of logistics capabilities. The International Journal of Logistics Management, 25(1), 160–179. Crossref, Web of Science, Google Scholar
Goldsby, TJ and R Martichenko (2005). Lean Six Sigma Logistics: Strategic Development to Operational Success. J. Ross Publishing. Google Scholar
Graham, G, S Zailani and P Rajagopal (2005). Supply chain integration and performance: US versus East Asian companies. Supply Chain Management: An International Journal, 10(5), 379–393. Crossref, Google Scholar
Green, Jr, KW, D Whitten and RA Inman (2008). The impact of logistics performance on organizational performance in a supply chain context. Supply Chain Management: An International Journal, 13(4), 317–327. Crossref, Web of Science, Google Scholar
Green, Jr, KW, D Whitten and RA Inman (2012). Aligning marketing strategies throughout the supply chain to enhance performance. Industrial Marketing Management, 41(6), 1008–1018. Crossref, Web of Science, Google Scholar
Griffis, SE, TJ Goldsby, M Cooper and DJ Closs (2007). Aligning logistics performance measures to the information needs of the firm. Journal of Business Logistics, 28(2), 35–56. Crossref, Google Scholar
Gunasekaran, A and B Kobu (2007). Performance measures and metrics in logistics and supply chain management: A review of recent literature (1995–2004) for research and applications. International Journal of Production Research, 45(12), 2819–2840. Crossref, Web of Science, Google Scholar
Gunasekaran, A, C Patel and E Tirtiroglu (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations and Production Management, 21(1/2), 71–87. Crossref, Web of Science, Google Scholar
Hair, Jr, JF, GTM Hult, C Ringle and M Sarstedt (2021). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications. Crossref, Google Scholar
Hall, DC and C Saygin (2012). Impact of information sharing on supply chain performance. The International Journal of Advanced Manufacturing Technology, 58(1–4), 397–409. Crossref, Web of Science, Google Scholar
Hallavo, V (2015). Superior performance through supply chain fit: A synthesis. Supply Chain Management: An International Journal, 20(1), 71–82. Crossref, Web of Science, Google Scholar
Hariharan, R and P Zipkin (1995). Customer-order information, leadtimes, and inventories. Management Science, 41(10), 1599–1607. Crossref, Web of Science, Google Scholar
Harman, HH (1976). Modern Factor Analysis. University of Chicago Press. Google Scholar
Henseler, J, CM Ringle and RR Sinkovics (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(1), 277–319. Crossref, Google Scholar
Hsu, C-C, VR Kannan, K-C Tan and G Keong Leong (2008). Information sharing, buyer–supplier relationships, and firm performance: A multi-region analysis. International Journal of Physical Distribution & Logistics Management, 38(4), 296–310. Crossref, Web of Science, Google Scholar
Hui, L and Z Lingrong (2012). Supply chain information sharing differences between high and low performers: Perspectives from both supply and demand information. In 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE). IEEE. Crossref, Google Scholar
Huo, B, X Zhao and H Zhou (2014). The effects of competitive environment on supply chain information sharing and performance: An empirical study in China. Production and Operations Management, 23(4), 552–569. Crossref, Web of Science, Google Scholar
Iacobucci, D, N Saldanha and X Deng (2007). A meditation on mediation: Evidence that structural equations models perform better than regressions. Journal of Consumer Psychology, 17(2), 139–153. Crossref, Web of Science, Google Scholar
Jain, AK and A Moreno (2015). Organizational learning, knowledge management practices and firm’s performance: An empirical study of a heavy engineering firm in India. The Learning Organization, 22(1), 14–39. Crossref, Google Scholar
Johnson, M and S Templar (2011). The relationships between supply chain and firm performance: The development and testing of a unified proxy. International Journal of Physical Distribution & Logistics Management, 41(2), 88–103. Crossref, Web of Science, Google Scholar
Jones, DT, P Hines and N Rich (1997). Lean logistics. International Journal of Physical Distribution & Logistics Management, 27(3/4), 153–173. Crossref, Google Scholar
Jonsson, P and P Myrelid (2016). Supply chain information utilisation: Conceptualisation and antecedents. International Journal of Operations & Production Management, 36(12), 1769–1799. https://doi.org/10.1108/IJOPM-11-2014-0554. Crossref, Web of Science, Google Scholar
Joong-Kun Cho, J, J Ozment and H Sink (2008). Logistics capability, logistics outsourcing and firm performance in an e-commerce market. International Journal of Physical Distribution & Logistics Management, 38(5), 336–359. Crossref, Web of Science, Google Scholar
Kaplan, RS and DP Norton (1996). Balanced Scorecard — Translating Strategy into Action. Boston: Harvard Business School Press. Google Scholar
Karaesmen, F, G Liberopoulos and Y Dallery (2004). The value of advance demand information in production/inventory systems. Annals of Operations Research, 126(1–4), 135–157. Crossref, Web of Science, Google Scholar
Kazancoglu, Y, E Ekinci, SK Mangla, MD Sezer and Y Kayikci (2021). Performance evaluation of reverse logistics in food supply chains in a circular economy using system dynamics. Business Strategy and the Environment, 30(1), 71–91. Crossref, Web of Science, Google Scholar
Khan, H and JD Wisner (2019). Supply chain integration, learning, and agility: Effects on performance. Journal of Operations and Supply Chain Management, 12(1), 14. Crossref, Google Scholar
Kennerley, M and A Neely (2002). A framework of the factors affecting the evolution of performance measurement systems. International Journal of Operations and Production Management, 22(11), 1222–1245. Crossref, Web of Science, Google Scholar
Kim, SW (2009). An investigation on the direct and indirect effect of supply chain integration on firm performance. International Journal of Production Economics, 119(2), 328–346. Crossref, Web of Science, Google Scholar
Klein, R and A Rai (2009). Interfirm strategic information flows in logistics supply chain relationships. MIS Quarterly, 33(4), 735–762. Crossref, Web of Science, Google Scholar
Kochan, CG, DR Nowicki, B Sauser and WS Randall (2018). Impact of cloud-based information sharing on hospital supply chain performance: A system dynamics framework. International Journal of Production Economics, 195, 168–185. Crossref, Web of Science, Google Scholar
Krauth, E, H Moonen, V Popova and MC Schut (2005). Performance measurement and control in logistics service providing. In International Conference on Enterprise Information Systems, Vol. 3, pp. 239–247. SCITEPRESS. Google Scholar
Kulp, SC, HL Lee and E Ofek (2004). Manufacturer benefits from information integration with retail customers. Management Science, 50(4), 431–444. Crossref, Web of Science, Google Scholar
Kumar, S, BB Kadow and MK Lamkin (2011). Challenges with the introduction of radio-frequency identification systems into a manufacturer’s supply chain — A pilot study. Enterprise Information Systems, 5(2), 235–253. Crossref, Web of Science, Google Scholar
Lambert, DM and R Burduroglu (2000). Measuring and selling the value of logistics. The International Journal of Logistics Management, 11(1), 1–18. Crossref, Google Scholar
Larson, PD, RF Poist and A Halldorsson (2007). Perspectives on logistics vs. SCM: A survey of SCM professionals. Journal of Business Logistics, 28(1), 1–24. Crossref, Google Scholar
Lee, HL, V Padmanabhan and S Whang (1997). The bullwhip effect in supply chains. Sloan Management Review, 38(3), 93–102. Web of Science, Google Scholar
Lee, HL and S Whang (2000). Information sharing in a supply chain. International Journal of Manufacturing Technology and Management, 1(1), 79–93. Crossref, Google Scholar
Lenuwat, P and S Boon-itt (2021). Information technology management and service performance management capabilities: An empirical study of the service supply chain management process. Journal of Advances in Management Research, 19(1), 55–77. Crossref, Web of Science, Google Scholar
Leuschner, R, DS Rogers and FF Charvet (2013). A meta-analysis of supply chain integration and firm performance. Journal of Supply Chain Management, 49(2), 34–57. Crossref, Web of Science, Google Scholar
Li, S, B Ragu-Nathan, T Ragu-Nathan and SS Rao (2006). The impact of supply chain management practices on competitive advantage and organizational performance. Omega, 34(2), 107–124. Crossref, Web of Science, Google Scholar
Lin, F-r, S-h Huang and S-c Lin (2002). Effects of information sharing on supply chain performance in electronic commerce. IEEE Transactions on Engineering Management, 49(3), 258–268. Crossref, Web of Science, Google Scholar
Lohmoeller, J-B (1989). Latent Variable Path Analysis with Partial Least Squares. New York: Springer-Verlag. Crossref, Google Scholar
Lynch, DF, SB Keller and J Ozment (2000). The effects of logistics capabilities and strategy on firm performance. Journal of Business Logistics, 21(2), 47–67. Google Scholar
Malhotra, NK, SS Kim and A Patil (2006). Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research. Management science, 52(12), 1865–1883. Crossref, Web of Science, Google Scholar
Mani, V, A Gunasekaran and C Delgado (2018). Enhancing supply chain performance through supplier social sustainability: An emerging economy perspective. International Journal of Production Economics, 195, 259–272. Crossref, Web of Science, Google Scholar
Martin, PR and JW Patterson (2009). On measuring company performance within a supply chain. International Journal of Production Research, 47(9), 2449–2460. Crossref, Web of Science, Google Scholar
Matsuno, K and JT Mentzer (2000). The effects of strategy type on the market orientation–performance relationship. Journal of Marketing, 64(4), 1–16. Crossref, Web of Science, Google Scholar
Melnyk, SA, R Narasimhan and HA DeCampos (2014). Supply chain design: Issues, challenges, frameworks and solutions. International Journal of Production Research, 52(7), 1887–1896. Crossref, Web of Science, Google Scholar
Melville, N, K Kraemer and V Gurbaxani (2004). Review: Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 282–322. Crossref, Web of Science, Google Scholar
Mentzer, JT and BP Konrad (1991). An efficiency/effectiveness approach to logistics performance analysis. Journal of Business Logistics, 12(1), 33–62. Google Scholar
Mentzer, JT, S Min and L Michelle Bobbitt (2004). Toward a unified theory of logistics. International Journal of Physical Distribution & Logistics Management, 34(8), 606–627. Crossref, Google Scholar
Min, S, AS Roath, PJ Daugherty, SE Genchev, H Chen, AD Arndt and R Glenn Richey (2005). Supply chain collaboration: What’s happening? The International Journal of Logistics Management, 16(2), 237–256. Crossref, Google Scholar
Munir, M, MSS Jajja, KA Chatha and S Farooq (2020). Supply chain risk management and operational performance: The enabling role of supply chain integration. International Journal of Production Economics, 227, 107667. Crossref, Web of Science, Google Scholar
Moazzam, M, P Akhtar, E Garnevska and NE Marr (2018). Measuring agri-food supply chain performance and risk through a new analytical framework: A case study of New Zealand dairy. Production Planning & Control, 29(15), 1258–1274. Crossref, Web of Science, Google Scholar
Morash, EA and SR Clinton (1997). The role of transportation capabilities in international supply chain management. Transportation Journal, 36(3), 5–17. Web of Science, Google Scholar
Narasimhan, R, M Swink and SW Kim (2006). Disentangling leanness and agility: An empirical investigation. Journal of Operations Management, 24(5), 440–457. Crossref, Web of Science, Google Scholar
Neely, A, M Gregory and K Platts (1995). Performance measurement system design: A literature review and research agenda. International Journal of Operations and Production Management, 15(4), 80–116. Crossref, Web of Science, Google Scholar
Neely, A, H Richards, J Mills, K Platts and M Bourne (1997). Designing performance measures: A structured approach. International Journal of Operations and Production Management, 17(11), 1131–1152. Crossref, Web of Science, Google Scholar
Omar, A, B Davis-Sramek, MB Myers and JT Mentzer (2012). A global analysis of orientation, coordination, and flexibility in supply chains. Journal of Business Logistics, 33(2), 128–144. Crossref, Web of Science, Google Scholar
Özer, Ö and W Wei (2006). Strategic commitments for an optimal capacity decision under asymmetric forecast information. Management Science, 52(8), 1238–1257. Crossref, Web of Science, Google Scholar
Pang, K and CS Lu (2018). Organizational motivation, employee job satisfaction and organizational performance: An empirical study of container shipping companies in Taiwan. Maritime Business Review, 3(1), 36–52. Crossref, Google Scholar
Patnayakuni, R, A Rai and N Seth (2006). Relational antecedents of information flow integration for supply chain coordination. Journal of Management Information Systems, 23(1), 13–49. Crossref, Web of Science, Google Scholar
Peng, DX and F Lai (2012). Using partial least squares in operations management research: A practical guideline and summary of past research. Journal of Operations Management, 30(6), 467–480. Crossref, Web of Science, Google Scholar
Podsakoff, PM, SB MacKenzie, J-Y Lee and NP Podsakoff (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. Crossref, Web of Science, Google Scholar
Podsakoff, PM and DW Organ (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531–544. Crossref, Web of Science, Google Scholar
Porter, ME and VE Millar (1985). How information gives you competitive advantage. Harvard Business Review, 63(4), 149–160. Web of Science, Google Scholar
Powell, D, E Alfnes, JO Strandhagen and H Dreyer (2013). The concurrent application of lean production and ERP: Towards an ERP-based lean implementation process. Computers in Industry, 64(3), 324–335. Crossref, Web of Science, Google Scholar
Prajogo, D and J Olhager (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration. International Journal of Production Economics, 135(1), 514–522. Crossref, Web of Science, Google Scholar
Prajogo, D, J Toy, A Bhattacharya, A Oke and TCE Cheng (2018). The relationships between information management, process management and operational performance: Internal and external contexts. International Journal of Production Economics, 199, 95–103. Crossref, Web of Science, Google Scholar
Qrunfleh, S and M Tarafdar (2014). Supply chain information systems strategy: Impacts on supply chain performance and firm performance. International Journal of Production Economics, 147, 340–350. Crossref, Web of Science, Google Scholar
Rafele, C (2004). Logistic service measurement: A reference framework. Journal of Manufacturing Technology Management, 15(3), 280–290. Crossref, Google Scholar
Rai, A, R Patnayakuni and N Seth (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly, 30(2), 225–246. Crossref, Web of Science, Google Scholar
Ramanathan, U (2013). Aligning supply chain collaboration using analytic hierarchy process. Omega, 41(2), 431–440. Crossref, Web of Science, Google Scholar
Randall, T and K Ulrich (2001). Product variety, supply chain structure, and firm performance: Analysis of the US bicycle industry. Management Science, 47(12), 1588–1604. Crossref, Web of Science, Google Scholar
Ringle, C, S Wende and J Becker (2015). SmartPLS 3. Boenningstedt. Google Scholar
Rodrigues, AM, TP Stank and DF Lynch (2004). Linking strategy, structure, process, and performance in integrated logistics. Journal of Business Logistics, 25(2), 65–94. Crossref, Google Scholar
Rodrigues, EC, FL Lizarelli and CF Poltronieri (2023). Perception about applying acquired knowledge and the relationship with work performance. Journal of Information & Knowledge Management, 22(4), 2350038. Link, Google Scholar
Rosenzweig, ED, AV Roth and JW Dean (2003). The influence of an integration strategy on competitive capabilities and business performance: An exploratory study of consumer products manufacturers. Journal of Operations Management, 21(4), 437–456. Crossref, Web of Science, Google Scholar
Sahin, F and EP Robinson (2002). Flow coordination and information sharing in supply chains: Review, implications, and directions for future research. Decision Sciences, 33(4), 505–536. Crossref, Web of Science, Google Scholar
Salamai, AA (2022). A review of collaboration and secure information-sharing for supply chain management. Journal of Information & Knowledge Management, 21(4), 2250047. Link, Google Scholar
Sanders, NR (2007). An empirical study of the impact of e-business technologies on organizational collaboration and performance. Journal of Operations Management, 25(6), 1332–1347. Crossref, Web of Science, Google Scholar
Schniederjans, DG, C Curado and M Khalajhedayati (2020). Supply chain digitisation trends: An integration of knowledge management. International Journal of Production Economics, 220(c), 107439. Crossref, Google Scholar
Schramm-Klein, H and D Morschett (2006). The relationship between marketing performance, logistics performance and company performance for retail companies. International Review of Retail, Distribution and Consumer Research, 16(2), 277–296. Google Scholar
Shaw, S, DB Grant and J Mangan (2021). A supply chain practice-based view of enablers, inhibitors and benefits for environmental supply chain performance measurement. Production Planning & Control, 32(5), 382–396. Crossref, Web of Science, Google Scholar
Shou, Y, Y Li, Y Park and M Kang (2018). Supply chain integration and operational performance: The contingency effects of production systems. Journal of Purchasing and Supply Management, 24(4), 352–360. Crossref, Web of Science, Google Scholar
Sener, A, M Barut, A Dag and MB Yildirim (2021). Impact of commitment, information sharing, and information usage on supplier performance: A Bayesian belief network approach. Annals of Operations Research, 303(1), 125–158. Crossref, Web of Science, Google Scholar
Sener, A, M Barut, A Oztekin, MY Avcilar and MB Yildirim (2019). The role of information usage in a retail supply chain: A causal data mining and analytical modeling approach. Journal of Business Research, 99, 87–104. Crossref, Web of Science, Google Scholar
Sim, J and CC Wright (2005). The kappa statistic in reliability studies: Use, interpretation, and sample size requirements. Physical Therapy, 85(3), 257–268. Crossref, Web of Science, Google Scholar
Simatupang, TM, AC Wright and R Sridharan (2002). The knowledge of coordination for supply chain integration. Business Process Management Journal, 8(3), 289–308. Crossref, Google Scholar
Sobel, ME (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13(1982), 290–312. Crossref, Google Scholar
Stank, TP, MR Crum and M Arango (1999). Benefits of interfirm coordination in food industry supply chains. Journal of Business Logistics, 20, 21–41. Google Scholar
Stank, TP, SB Keller and DJ Closs (2001a). Performance benefits of supply chain logistical integration. Transportation Journal, 41, 32–46. Web of Science, Google Scholar
Stank, TP, SB Keller and PJ Daugherty (2001b). Supply chain collaboration and logistical service performance. Journal of Business Logistics, 22(1), 29–48. Crossref, Google Scholar
Stevens, GC (1989). Integrating the supply chain. International Journal of Physical Distribution & Materials Management, 19(8), 3–8. Crossref, Google Scholar
Swaminathan, JM, NM Sadeh and SF Smith (1995). Effect of sharing supplier capacity information. Working paper, Haas School of Business, University of California, Berkeley. Google Scholar
Swink, M, R Narasimhan and C Wang (2007). Managing beyond the factory walls: Effects of four types of strategic integration on manufacturing plant performance. Journal of Operations Management, 25(1), 148–164. Crossref, Web of Science, Google Scholar
Tan, KC, VR Kannan and RB Handfield (1998). Supply chain management: Supplier performance and firm performance. International Journal of Purchasing and Materials Management, 34(3), 23 pp. Google Scholar
Tarí, JJ, JF Molina-Azorín, J Pereira-Moliner, MD López-Gamero and EM Pertusa-Ortega (2014). Quality management and performance in the hotel industry: A literature review. In Action-based Quality Management: Strategy and Tools for Continuous Improvement, pp. 1–12. Switzerland: Spring International Publishing. Crossref, Google Scholar
Tenenhaus, M (2008). Component-based structural equation modelling. Total Quality Management, 19(7–8), 871–886. Crossref, Google Scholar
Theeranuphattana, A and JC Tang (2007). A conceptual model of performance measurement for supply chains: Alternative considerations. Journal of Manufacturing Technology Management, 19(1), 125–148. Crossref, Google Scholar
U.S. Department of Agriculture Foreign Agriculture Service (2015). Turkey: Retail foods report. http://www.fas.usda.gov/data/turkey-retail-foods. Google Scholar
U.S. Department of Agriculture Foreign Agriculture Service (2021). Turkey: Retail foods report. https://www.fas.usda.gov/data/turkey-retail-foods-4. Google Scholar
Van der Vaart, T and DP van Donk (2008). A critical review of survey-based research in supply chain integration. International Journal of Production Economics, 111(1), 42–55. Crossref, Web of Science, Google Scholar
Venkatraman, N and V Ramanujam (1986). Measurement of business performance in strategy research: A comparison of approaches. Academy of Management Review, 11(4), 801–814. Crossref, Web of Science, Google Scholar
Vickery, SK, J Jayaram, C Droge and R Calantone (2003). The effects of an integrative supply chain strategy on customer service and financial performance: An analysis of direct versus indirect relationships. Journal of Operations Management, 21(5), 523–539. Crossref, Web of Science, Google Scholar
Vinzi, VE, L Trinchera and S Amato (2010). PLS path modeling: From foundations to recent developments and open issues for model assessment and improvement. In Handbook of Partial Least Squares, pp. 47–82. Springer. Crossref, Google Scholar
Waggoner, DB, AD Neely and MP Kennerley (1999). The forces that shape organisational performance measurement systems: An interdisciplinary review. International Journal of Production Economics, 60, 53–60. Crossref, Web of Science, Google Scholar
Williams, P and E Naumann (2011). Customer satisfaction and business performance: A firm-level analysis. Journal of Services Marketing, 25(1), 20–32. Crossref, Web of Science, Google Scholar
Wisner, JD (2003). A structural equation model of supply chain management strategies and firm performance. Journal of Business Logistics, 24(1), 1–26. Crossref, Google Scholar
Wisner, JD and SE Fawcett (1991). Linking firm strategy to operating decisions through performance measurement. Production and Inventory Management Journal, 32(3), 5–11. Google Scholar
Wong, CY, S Boon-Itt and CW Wong (2011). The contingency effects of environmental uncertainty on the relationship between supply chain integration and operational performance. Journal of Operations Management, 29(6), 604–615. Crossref, Web of Science, Google Scholar
Wu, Z, J Xu and Z Xu (2016). A multiple attribute group decision making framework for the evaluation of lean practices at logistics distribution centers. Annals of Operations Research, 247, 735–757. Crossref, Web of Science, Google Scholar
Yao, D-Q, X Yue and J Liu (2008). Vertical cost information sharing in a supply chain with value-adding retailers. Omega, 36(5), 838–851. Crossref, Web of Science, Google Scholar
Yu, W, MA Jacobs, WD Salisbury and H Enns (2013). The effects of supply chain integration on customer satisfaction and financial performance: An organizational learning perspective. International Journal of Production Economics, 146(1), 346–358. Crossref, Web of Science, Google Scholar
Yu, Z, H Yan and T Edwin Cheng (2001). Benefits of information sharing with supply chain partnerships. Industrial Management & Data Systems, 101(3), 114–121. Crossref, Web of Science, Google Scholar
Zaid, A, M Sleimi, MW Saleh and M Othman (2021). The mediating roles of knowledge transfer and supply chain quality management capabilities on organizational performance. VINE Journal of Information and Knowledge Management Systems, 53(6), 1041–1064. Crossref, Google Scholar
Zhang, C, G-W Tan, DJ Robb and X Zheng (2006). Sharing shipment quantity information in the supply chain. Omega, 34(5), 427–438. Crossref, Web of Science, Google Scholar
Zhang, ZJ, PR Srivastava, P Eachempati and Y Yu (2021). An intelligent framework for analyzing supply chain resilience of firms in China: A hybrid multicriteria approach. The International Journal of Logistics Management, 34(2), 443–472. Crossref, Web of Science, Google Scholar
Zhao, G, JH Hormazabal, S Elgueta, JP Manzur, S Liu, H Chen, C Lopez, D Kasturiratnea and X Chen (2021). The impact of knowledge governance mechanisms on supply chain performance: Empirical evidence from the agri-food industry. Production Planning & Control, 32(15), 1313–1336. Crossref, Web of Science, Google Scholar
Zhao, L, B Huo, L Sun and X Zhao (2013). The impact of supply chain risk on supply chain integration and company performance: A global investigation. Supply Chain Management: An International Journal, 18(2), 115–131. Crossref, Web of Science, Google Scholar
Zhao, M, C Dröge and TP Stank (2001). The effects of logistics capabilities on firm performance: Customer-focused versus information-focused capabilities. Journal of Business Logistics, 22(2), 91–107. Crossref, Google Scholar
Zhao, X, BB Flynn and AV Roth (2007). Decision sciences research in China: Current status, opportunities, and propositions for research in supply chain management, logistics, and quality management. Decision Sciences, 38(1), 39–80. Crossref, Web of Science, Google Scholar
Zhao, X, J Xie and W Zhang (2002). The impact of information sharing and ordering co-ordination on supply chain performance. Supply Chain Management: An International Journal, 7(1), 24–40. Crossref, Google Scholar
Zidi, S, N Hamani and L Kermad (2021). New metrics for measuring supply chain reconfigurability. Journal of Intelligent Manufacturing, 33, 2371–2392. Crossref, Web of Science, Google Scholar