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Trust or doubt : accuracy of determining factors for supply chain performance

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Zaufanie lub wątpliwość : dokładność ustalania czynników dla wydajności łańcucha dostaw
Języki publikacji
EN
Abstrakty
EN
The aim of the research is to determine the accuracy of defining factors for supply chain performance. The most used factors in the literature are: sharing information, responding to challenges, cooperation among members, relationships, and trust. The method of the study is meta-analysis. Our results suggest that the effect of the examined factors on the performance is not complete, and the inclusion of other factors in later studies is indispensable because the results obtained indicate the presence of unknown influencing factors. The effect of the examined factors in the whole population is likely to be positive, but weak or moderate.
PL
Celem badań jest określenie dokładności definiowania czynników dla wydajności łańcucha dostaw. Najczęściej używane czynniki w literaturze to: dzielenie się informacjami, reagowanie na zapytania, współpraca między członkami, relacje i zaufanie. Metodą badania jest metaanaliza. Rezultaty studium sugerują, że wpływ badanych czynników na wydajność nie jest kompletny, a włączenie innych czynników do późniejszych badań jest niezbędne, ponieważ uzyskane wyniki wskazują na obecność nieznanych czynników wpływających. Wpływ badanych czynników na całą populację będzie prawdopodobnie pozytywny, ale słaby lub umiarkowany.
Rocznik
Strony
283--297
Opis fizyczny
Bibliogr. 58 poz., rys., tab.
Twórcy
  • Institute of Applied Informatics and Logistics, Faculty of Economics and Business, University of Debrecen, Hungary
  • Institute of Applied Informatics and Logistics, Faculty of Economics and Business, University of Debrecen, Hungary, MSc Sudent
autor
  • Institute of Sectoral Economics and Methodology, Faculty of Economics and Business, University of Debrecen, Hungary
  • Institute of Economics, Law and Methodology, Szent István University, Gödöllő, Hungary
autor
  • Institute of Applied Informatics and Logistics, Faculty of Economics and Business, University of Debrecen, Hungary
Bibliografia
  • 1. Arnold V., Benford T., Canada J., Sutton S., 2015, Leveraging integrated information systems to enhance strategic flexibility and performance: The enabling role of enterprise risk management, “International Journal of Accounting Information Systems”, 19.
  • 2. Ataseven C., Nair A., 2017, Assessment of supply chain integration and performance relationships: A meta-analytic investigation of the literature, “International Journal of Production Economics”, 185.
  • 3. Bhosale V., Kant R., 2016, Metadata analysis of knowledge management in supply chain: Investigating the past and predicting the future, “Business Process Management Journal”, 22(1).
  • 4. Chan A., Ngai E., Moon K., 2017, The effects of strategic and manufacturing flexibilities and supply chain agility on firm performance in the fashion industry, “European Journal of Operational Research”, 259(2).
  • 5. Chen D., Preston D., Xia W., 2013, Enhancing hospital supply chain performance: A relational view and empirical test, “Journal of Operations Management”, 31(6).
  • 6. Dong M., Ju M., Fang Y., 2016, Role hazard between supply chain partners in an institutionally fragmented market, “Journal of Operations Management”, 46.
  • 7. Daugherty P., Chen H., Mattioda D., Grawe S., 2011, Marketing/Logistics Relationships: Influence on Capabilities and Performance, “Journal of Business Logistics”, 30(1).
  • 8. Eng T.-Y., 2006, An investigation into the mediating role of cross-functional coordination on the linkage between organizational norms and SCM performance, “Industrial Marketing Management”, 35(6).
  • 9. Ellinger A., 2000, Improving Marketing/Logistics Cross-Functional Collaboration in the Supply Chain, “Industrial Marketing Management”, 29(1).
  • 10. Felföldi J., 2011, Ellátási lánc és a termelői szerveződések kapcsolata, [In:] Nagy, Adrián; Nábrádi, András (szerk.) Farmgazdálkodás, Budapest, Magyarország: Szaktudás Kiadó Ház.
  • 11. Felföldi J., Szőllősi L., 2011, Chain Performance and Balance Relations through the Operation of a Product Chain: A Case Study on the Broiler Product Chain in Hungary, [In:] 5th International European Forum (Igls-Forum) on System Dynamics and Innovation in Food Networks, pp. 1-13.
  • 12. Field A., 2001, Meta-analysis of correlation coefficients: A Monte Carlo comparison of fixed- and random-effects methods, “Psychological Methods”, 6(2).
  • 13. Field A., Gillett R., 2010, How to do a meta‐analysis, “British Journal of Mathematical and Statistical Psychology”, 63(3).
  • 14. Floyd K., Freling R., Alhoqail S., Cho H., Freling T., 2014, How Online Product Reviews Affect Retail Sales: A Meta-analysis, “Journal of Retailing”, 90(2).
  • 15. Flynn B., Huo B., Zhao X., 2010, The impact of supply chain integration on performance: A contingency and configuration approach, “Journal of Operations Management”, 28(1).
  • 16. Ghobakhloo M., Azar A., 2018, Business excellence via advanced manufacturing technology and lean-agile manufacturing, “Journal of Manufacturing Technology Management”, 29(1).
  • 17. Grawe S., Daugherty P., Roath A., 2011, Knowledge Synthesis and Innovative Logistics Processes: Enhancing Operational Flexibility and Performance, “Journal of Business Logistics”, 32(1).
  • 18. Green K., Whitten D., Inman R., 2012, Aligning marketing strategies throughout the supply chain to enhance performance, “Industrial Marketing Management”, 41(6).
  • 19. Gunasekaran A., Papadopoulos T., Dubey R., Wamba S. F., Childe S.J., Hazen B., Akter S., 2017, Big data and predictive analytics for supply chain and organizational performance, “Journal of Business Research”, 70.
  • 20. Hedges L.V., Olkin I., 1985, Statistical methods for meta-analysis, Orlando, FL: Academic Press.
  • 21. Hunter J., Schmidt F., 2004, Methods of Meta-Analysis: Correcting Error and Bias in Research Findings, (2. kiadás), SAGE Publications Ltd.
  • 22. Huo B., Zhang C., Zhao X., 2015, The effect of IT and relationship commitment on supply chain coordination: A contingency and configuration approach, “Information & Management”, 52(6).
  • 23. Kim K., Ryoo S., Jung M., 2011, Inter-organizational information systems visibility in buyer-supplier relationships: The case of telecommunication equipment component manufacturing industry, “Omega”, 39(6).
  • 24. Kliestik T., Misankova M., Valaskova K., Svabova L., 2018, Bankruptcy prevention: new effort to reflect on legal and social changes, “Science and Engineering Ethics”, 24(2).
  • 25. Kumar V., Chibuzo E., Garza-Reyes J., Kumari A., Rocha-Lona L., Lopez-Torres G., 2017, The Impact of Supply Chain Integration on Performance: Evidence from the UK Food Sector, “Procedia Manufacturing”, 11.
  • 26. Kovacova M., Kliestik T., Kubala P., Valaskova K., Radišić M., Borocki J., 2018, Bankruptcy models: verifying their validity as a predictor of corporate failure, “Polish Journal of Management Studies”, 18(1).
  • 27. Lai K.-H., Wong C., Cheng T., 2008, A coordination-theoretic investigation of the impact of electronic integration on logistics performance, “Information & Management”, 45(1).
  • 28. Lee H., Kim M., Kim K., 2014, Interorganizational information systems visibility and supply chain performance, “International Journal of Information Management”, 34(2).
  • 29. Lin Y., Wang Y., Yu C., 2010, Investigating the drivers of the innovation in channel integration and supply chain performance: A strategy orientated perspective, “International Journal of Production Economics”, 127(2).
  • 30. Luo H., Sha S., Huang G., 2013, The Impact of Information and Knowledge sharing on the Buyer-supplier Relationship and Performance in Electronics Industry, “IFAC Proceedings Volumes”, 46(9).
  • 31. Mandal S., Bhattacharya S., Korasiga V.R., Sarathy R., 2017, The dominant influence of logistics capabilities on integration: Empirical evidence from supply chain resilience, “International Journal of Disaster Resilience in the Built Environment”, 8(4).
  • 32. Meyer D.F., Meyer N., Neethling J.R., 2016, Perceptions of business owners on service delivery and the creation of an enabling environment, “Administratio Publica”, 24(3).
  • 33. Meyer D.F., Meyer N., 2017, Management of small and medium enterprise (SME) development: An analysis of stumbling blocks in a developing region, “Polish Journal of Management Studies”, 16(1).
  • 34. Mishra D., Sharma R., Kumar S., Dubey R., 2016, Bridging and buffering: Strategies for mitigating supply risk and improving supply chain performance, “International Journal of Production Economics”, 180.
  • 35. Oláh J., Karmazin Gy., Fekete Farkasné M., Popp J., 2017a, An examination of trust as a strategical factor of success in logistical firms, “Business Theory and Practise”, 18(1).
  • 36. Oláh J., Bai A., Karmazin Gy., Balogh P., Popp J., 2017b, The Role Played by Trust and Its Effect on the Competiveness of Logistics Service Providers in Hungary, “Sustainability”, 9(12).
  • 37. Oláh J., Sadaf R., Máté D., Popp J., 2018, The influence of the management success factors of logistics service providers on firms’ competitiveness, “Polish Jounal of Management Studies”, 17(1).
  • 38. Panayides P., Lun Y., 2009, The impact of trust on innovativeness and supply chain performance, “International Journal of Production Economics”, 122(1).
  • 39. Papp G., 2015, A meta-analízis módszertana, [In:] Pszichológiai módszertani tanulmányok, (Szerk. Balázs K. - Kovács J. - Münnich Á.), pp. 143-16, Debreceni Egyetemi Kiadó.
  • 40. Qrunfleh S., Tarafdar M., 2014, Supply chain information systems strategy: Impacts on supply chain performance and firm performance, “International Journal of Production Economics”, 147.
  • 41. Rajaguru R., Matanda M., 2013, Effects of inter-organizational compatibility on supply chain capabilities: Exploring the mediating role of inter-organizational information systems (IOIS) integration, “Industrial Marketing Management”, 42(4).
  • 42. Rexhausen D., Pibernik R., Kaiser G., 2012, Customer-facing supply chain practices - The impact of demand and distribution management on supply chain success, “Journal of Operations Management”, 30(4).
  • 43. Roh J., Hong P., Min H., 2014, Implementation of a responsive supply chain strategy in global complexity: The case of manufacturing firms, “International Journal of Production Economics”, 147.
  • 44. Rosenberg M., 2005, The File-Drawer Problem Revisited: A General Weighted Method for Calculating Fail-Safe Numbers in Meta-Analysis, “Evolution”, 59(2).
  • 45. Rosenthal R., Rubin D.B., 1982, A simple general purpose display of magnitude and experimental effect, “Journal of Educational Psychology”, 74.
  • 46. Ryoo S., Kim K., 2015, The impact of knowledge complementarities on supply chain performance through knowledge exchange, “Expert Systems with Applications”, 42(6).
  • 47. Singh A., Teng J., 2016, Enhancing supply chain outcomes through Information Technology and Trust, “Computers in Human Behavior”, 54.
  • 48. Sroka W., 2011, Problem of trust in alliance networks, “Organizacija”, 44(4).
  • 49. Sroka W., Hittmar S., 2013, Management of alliance networks: formation, functionality and post-operational strategies, Heidelberg-New York: Springer Verlag.
  • 50. Um J., Lyons A., Lam H., Cheng T., Dominguez-Pery C., 2017, Product variety management and supply chain performance: A capability perspective on their relationships and competitiveness implications, “International Journal of Production Economics”, 187.
  • 51. Vörösmarty G., Dobos I., 2019, The Role of Personal Motivation in Sustainable Purchasing Practices, “Amfiteatru Economic”, 21(50).
  • 52. Wang E., Chou F., Lee N., Lai S., 2014, Can intrafirm IT skills benefit interfirm integration and performance?, “Information & Management”, 51(7).
  • 53. Wei H.-L., Wong C., Lai K.-H., 2012, Linking inter-organizational trust with logistics information integration and partner cooperation under environmental uncertainty, “International Journal of Production Economics”, 139(2).
  • 54. Wong C., Lai K.-H., Bernroider E., 2015, The performance of contingencies of supply chain information integration: The roles of product and market complexity, “International Journal of Production Economics”, 165.
  • 55. Wu I.-L., Chuang C.-H., Hsu C.-H., 2014, Information sharing and collaborative behaviors in enabling supply chain performance: A social exchange perspective, “International Journal of Production Economics”, 148.
  • 56. Yang C.-C., Marlow P., Lu C.-S., 2009, Assessing resources, logistics service capabilities, innovation capabilities and the performance of container shipping services in Taiwan, “International Journal of Production Economics”, 122(1).
  • 57. Yang J., 2014, Supply chain agility: Securing performance for Chinese manufacturers, “International Journal of Production Economics”, 150.
  • 58. Zhou H., Benton W., 2007, Supply chain practice and information sharing, “Journal of Operations Management”, 25(6).
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-05c54d06-e845-4a62-afd8-c7d0230ea221
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