BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Klumpp M. Automation and artificial intelligence in business logistics systems: human reactions and collaboration requirements. International Journal of Logistics Research and Applications 2018;21:224-42. [DOI: 10.1080/13675567.2017.1384451] [Cited by in Crossref: 57] [Cited by in F6Publishing: 10] [Article Influence: 11.4] [Reference Citation Analysis]
Number Citing Articles
1 Shank DB, Bowen M, Burns A, Dew M. Humans are perceived as better, but weaker, than artificial intelligence: A comparison of affective impressions of humans, AIs, and computer systems in roles on teams. Computers in Human Behavior Reports 2021;3:100092. [DOI: 10.1016/j.chbr.2021.100092] [Reference Citation Analysis]
2 Toorajipour R, Sohrabpour V, Nazarpour A, Oghazi P, Fischl M. Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research 2021;122:502-17. [DOI: 10.1016/j.jbusres.2020.09.009] [Cited by in Crossref: 63] [Cited by in F6Publishing: 23] [Article Influence: 63.0] [Reference Citation Analysis]
3 Yadav A, Noori MT, Biswas A, Min B. A Concise Review on the Recent Developments in the Internet of Things (IoT)-Based Smart Aquaculture Practices. Reviews in Fisheries Science & Aquaculture. [DOI: 10.1080/23308249.2022.2090228] [Reference Citation Analysis]
4 Zhou X, Yang Z, Hyman MR, Li G, Munim ZH. Guest editorial: Impact of artificial intelligence on business strategy in emerging markets: a conceptual framework and future research directions. IJOEM 2022;17:917-29. [DOI: 10.1108/ijoem-04-2022-995] [Reference Citation Analysis]
5 Benzidia S, Ageron B, Bentahar O, Husson J. Investigating automation and AGV in healthcare logistics: a case study based approach. International Journal of Logistics Research and Applications 2018;22:273-93. [DOI: 10.1080/13675567.2018.1518414] [Cited by in Crossref: 13] [Cited by in F6Publishing: 1] [Article Influence: 3.3] [Reference Citation Analysis]
6 Lopes BDM, Silva LCB, Blanquet IM, Georgieva P, Marques CAF. Prediction of fish mortality based on a probabilistic anomaly detection approach for recirculating aquaculture system facilities. Rev Sci Instrum 2021;92:025119. [PMID: 33648149 DOI: 10.1063/5.0045047] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Di Vaio A, Boccia F, Landriani L, Palladino R. Artificial Intelligence in the Agri-Food System: Rethinking Sustainable Business Models in the COVID-19 Scenario. Sustainability 2020;12:4851. [DOI: 10.3390/su12124851] [Cited by in Crossref: 59] [Cited by in F6Publishing: 3] [Article Influence: 29.5] [Reference Citation Analysis]
8 Remondino M, Zanin A. Logistics and Agri-Food: Digitization to Increase Competitive Advantage and Sustainability. Literature Review and the Case of Italy. Sustainability 2022;14:787. [DOI: 10.3390/su14020787] [Reference Citation Analysis]
9 Kilpi V, Solakivi T, Kiiski T. Maritime sector at verge of change: learning and competence needs in Finnish maritime cluster. WMU J Marit Affairs 2021;20:63-79. [DOI: 10.1007/s13437-021-00228-0] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Fracarolli Nunes M, Lee Park C, Shin H. Corporate social and environmental irresponsibilities in supply chains, contamination, and damage of intangible resources: A behavioural approach. International Journal of Production Economics 2021;241:108275. [DOI: 10.1016/j.ijpe.2021.108275] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
11 Klumpp M, Zijm H. Logistics Innovation and Social Sustainability: How to Prevent an Artificial Divide in Human–Computer Interaction. J Bus Logist 2019;40:265-78. [DOI: 10.1111/jbl.12198] [Cited by in Crossref: 28] [Cited by in F6Publishing: 5] [Article Influence: 9.3] [Reference Citation Analysis]
12 Faccio M, Ferrari E, Gamberi M, Pilati F. Human Factor Analyser for work measurement of manual manufacturing and assembly processes. Int J Adv Manuf Technol 2019;103:861-77. [DOI: 10.1007/s00170-019-03570-z] [Cited by in Crossref: 19] [Cited by in F6Publishing: 3] [Article Influence: 6.3] [Reference Citation Analysis]
13 Herold DM, Ćwiklicki M, Pilch K, Mikl J. The emergence and adoption of digitalization in the logistics and supply chain industry: an institutional perspective. JEIM 2021;34:1917-38. [DOI: 10.1108/jeim-09-2020-0382] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
14 Sowa K, Przegalinska A, Ciechanowski L. Cobots in knowledge work. Journal of Business Research 2021;125:135-42. [DOI: 10.1016/j.jbusres.2020.11.038] [Cited by in Crossref: 12] [Cited by in F6Publishing: 10] [Article Influence: 12.0] [Reference Citation Analysis]
15 Fox S. Behavioral Ethics Ecologies of Human-Artificial Intelligence Systems. Behavioral Sciences 2022;12:103. [DOI: 10.3390/bs12040103] [Reference Citation Analysis]
16 Cadden T, Dennehy D, Mantymaki M, Treacy R. Understanding the influential and mediating role of cultural enablers of AI integration to supply chain. International Journal of Production Research. [DOI: 10.1080/00207543.2021.1946614] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
17 Ali SS, Kaur R. Exploring the Impact of Technology 4.0 Driven Practice on Warehousing Performance: A Hybrid Approach. Mathematics 2022;10:1252. [DOI: 10.3390/math10081252] [Reference Citation Analysis]
18 Di Vaio A, Palladino R, Hassan R, Escobar O. Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research 2020;121:283-314. [DOI: 10.1016/j.jbusres.2020.08.019] [Cited by in Crossref: 105] [Cited by in F6Publishing: 45] [Article Influence: 52.5] [Reference Citation Analysis]
19 Polas MRH, Raju V. Technology and Entrepreneurial Marketing Decisions During COVID-19. Glob J Flex Syst Manag 2021;22:95-112. [DOI: 10.1007/s40171-021-00262-0] [Cited by in Crossref: 19] [Cited by in F6Publishing: 5] [Article Influence: 19.0] [Reference Citation Analysis]
20 Ciliberto C, Szopik‐depczyńska K, Tarczyńska‐łuniewska M, Ruggieri A, Ioppolo G. Enabling the Circular Economy transition: a sustainable lean manufacturing recipe for Industry 4.0. Bus Strat Env 2021;30:3255-72. [DOI: 10.1002/bse.2801] [Cited by in Crossref: 5] [Article Influence: 5.0] [Reference Citation Analysis]
21 Klumpp M. Innovation Potentials and Pathways Merging AI, CPS, and IoT. ASI 2018;1:5. [DOI: 10.3390/asi1010005] [Cited by in Crossref: 7] [Article Influence: 1.8] [Reference Citation Analysis]
22 Loske D, Klumpp M. Intelligent and efficient? An empirical analysis of human–AI collaboration for truck drivers in retail logistics. IJLM 2021;32:1356-83. [DOI: 10.1108/ijlm-03-2020-0149] [Reference Citation Analysis]
23 Winkelhaus S, Grosse EH, Glock CH. Job satisfaction: An explorative study on work characteristics changes of employees in Intralogistics 4.0. J of Business Logistics. [DOI: 10.1111/jbl.12296] [Reference Citation Analysis]
24 Cong C, Fu D, Saravanan V. An AI based research on optimization of university sports information service. IFS 2021;40:3313-24. [DOI: 10.3233/jifs-189371] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
25 Olan F, Liu S, Suklan J, Jayawickrama U, Arakpogun EO. The role of Artificial Intelligence networks in sustainable supply chain finance for food and drink industry. International Journal of Production Research. [DOI: 10.1080/00207543.2021.1915510] [Cited by in Crossref: 7] [Cited by in F6Publishing: 2] [Article Influence: 7.0] [Reference Citation Analysis]
26 Nitsche B, Straube F, Wirth M. Application areas and antecedents of automation in logistics and supply chain management: a conceptual framework. Supply Chain Forum: An International Journal 2021;22:223-39. [DOI: 10.1080/16258312.2021.1934106] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
27 Casazza M, Gioppo L. A playwriting technique to engage on a shared reflective enquiry about the social sustainability of robotization and artificial intelligence. Journal of Cleaner Production 2020;248:119201. [DOI: 10.1016/j.jclepro.2019.119201] [Cited by in Crossref: 6] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
28 Sui J, Mo T. Morality in the era of smart devices. IJOEM 2021;17:1107-22. [DOI: 10.1108/ijoem-06-2021-0917] [Reference Citation Analysis]
29 Klumpp M, Hesenius M, Meyer O, Ruiner C, Gruhn V. Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future. Int J Adv Manuf Technol 2019;105:3691-709. [DOI: 10.1007/s00170-019-03785-0] [Cited by in Crossref: 36] [Cited by in F6Publishing: 9] [Article Influence: 12.0] [Reference Citation Analysis]
30 Wang Y, Skeete J, Owusu G. Understanding the implications of artificial intelligence on field service operations: a case study of BT. Production Planning & Control. [DOI: 10.1080/09537287.2021.1882694] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
31 Mahroof K. A human-centric perspective exploring the readiness towards smart warehousing: The case of a large retail distribution warehouse. International Journal of Information Management 2019;45:176-90. [DOI: 10.1016/j.ijinfomgt.2018.11.008] [Cited by in Crossref: 41] [Cited by in F6Publishing: 2] [Article Influence: 13.7] [Reference Citation Analysis]
32 Uusitalo K, Laine P. Testbed simulation modelling in an open business ecosystem context – benchmarking logistics network performance. International Journal of Logistics Research and Applications 2022;25:181-202. [DOI: 10.1080/13675567.2020.1806993] [Reference Citation Analysis]
33 Pandian DAP. ARTIFICIAL INTELLIGENCE APPLICATION IN SMART WAREHOUSING ENVIRONMENT FOR AUTOMATED LOGISTICS. JAICN 2019;2019:63-72. [DOI: 10.36548/jaicn.2019.2.002] [Cited by in Crossref: 29] [Cited by in F6Publishing: 3] [Article Influence: 9.7] [Reference Citation Analysis]
34 Balakrishnan J, Dwivedi YK, Hughes L, Boy F. Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model. Inf Syst Front. [DOI: 10.1007/s10796-021-10203-y] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
35 Sadowski A, Wojciechowski P, Engelseth P. The contingent nature of warehouse flexibility. IJPPM 2021. [DOI: 10.1108/ijppm-05-2020-0250] [Reference Citation Analysis]
36 Kulkov I. Next-generation business models for artificial intelligence start-ups in the healthcare industry. IJEBR 2021. [DOI: 10.1108/ijebr-04-2021-0304] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
37 Wang L, Liu Z, Liu A, Tao F. Artificial intelligence in product lifecycle management. Int J Adv Manuf Technol 2021;114:771-96. [DOI: 10.1007/s00170-021-06882-1] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 7.0] [Reference Citation Analysis]
38 Wang X, Wong YD, Chen T, Yuen KF. Adoption of shopper-facing technologies under social distancing: A conceptualisation and an interplay between task-technology fit and technology trust. Computers in Human Behavior 2021;124:106900. [DOI: 10.1016/j.chb.2021.106900] [Cited by in Crossref: 6] [Article Influence: 6.0] [Reference Citation Analysis]
39 Behl A, Dutta P, Luo Z, Sheorey P. Enabling artificial intelligence on a donation-based crowdfunding platform: a theoretical approach. Ann Oper Res. [DOI: 10.1007/s10479-020-03906-z] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
40 Qin M, Zhu W, Zhao S, Zhao Y. Is Artificial Intelligence Better than Manpower? The Effects of Different Types of Online Customer Services on Customer Purchase Intentions. Sustainability 2022;14:3974. [DOI: 10.3390/su14073974] [Reference Citation Analysis]
41 Nayal K, Raut RD, Queiroz MM, Yadav VS, Narkhede BE. Are artificial intelligence and machine learning suitable to tackle the COVID-19 impacts? An agriculture supply chain perspective. IJLM 2021;ahead-of-print. [DOI: 10.1108/ijlm-01-2021-0002] [Cited by in Crossref: 5] [Article Influence: 5.0] [Reference Citation Analysis]
42 Wilson M, Paschen J, Pitt L. The circular economy meets artificial intelligence (AI): understanding the opportunities of AI for reverse logistics. MEQ 2021;33:9-25. [DOI: 10.1108/meq-10-2020-0222] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 5.0] [Reference Citation Analysis]
43 Lin W. Automated infrastructure: COVID-19 and the shifting geographies of supply chain capitalism. Prog Hum Geogr 2022;46:463-83. [PMID: 35400791 DOI: 10.1177/03091325211038718] [Reference Citation Analysis]