Tackling the global challenges using data-driven innovations

被引:0
|
作者
Akter, Shahriar [1 ]
Sultana, Saida [1 ]
Gunasekaran, Angappa [2 ]
Bandara, Ruwan J. [3 ]
Miah, Shah J. [4 ]
机构
[1] Univ Wollongong, Sch Business, Wollongong, NSW 2522, Australia
[2] Penn State Harrisburg, Sch Business Adm, Middletown, PA 17057 USA
[3] Univ Wollongong Dubai, Fac Business, Dubai Knowledge Pk, Dubai, U Arab Emirates
[4] Univ Newcastle, Newcastle Business Sch, Callaghan, NSW 2308, Australia
关键词
Data-driven innovation; Capabilities; Market orientation; Infrastructure orientation and talent orientation; BIG DATA ANALYTICS; DYNAMIC CAPABILITIES; MARKET ORIENTATION; HEALTH-CARE; SUSTAINABILITY; MANAGEMENT; PERFORMANCE; INDUSTRY; MODEL; MICROFOUNDATIONS;
D O I
10.1007/s10479-024-05875-z
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
The data revolution transforms operations, innovation, and society through artificial intelligence and advanced analytics. Data-driven innovations (DDI) have the most potential to tackle global challenges, including poverty, healthcare, climate actions, disaster management, gender inequality, peace and justice and others. This paper identifies the sources of DDI capabilities to address various global challenges. The findings show three major foundations of DDI capabilities: market orientation, infrastructure orientation, and talent orientation. Theoretically, these findings highlight the role of dynamic DDI capabilities to sense, seize and transform global challenges. Practically, we present guidelines for developing DDI in an agile and efficient manner that is fair and inclusive.
引用
收藏
页码:517 / 532
页数:16
相关论文
共 50 条
  • [21] Designing semiconductor materials and devices in the post-Moore era by tackling computational challenges with data-driven strategies
    Xie, Jiahao
    Zhou, Yansong
    Faizan, Muhammad
    Li, Zewei
    Li, Tianshu
    Fu, Yuhao
    Wang, Xinjiang
    Zhang, Lijun
    [J]. NATURE COMPUTATIONAL SCIENCE, 2024, 4 (05): : 322 - 333
  • [22] Challenges using data-driven methods and deep learning in optical engineering
    Buquet, Julie
    Parent, Jocelyn
    Lalonde, Jean-Francois
    Thibault, Simon
    [J]. CURRENT DEVELOPMENTS IN LENS DESIGN AND OPTICAL ENGINEERING XXIII, 2022, 12217
  • [23] Data-driven technologies for global healthcare practices and COVID-19: opportunities and challenges
    Ogbuke, Nnamdi
    Yusuf, Yahaya Y. Y.
    Gunasekaran, Angappa
    Colton, Nora
    Kovvuri, Dharma
    [J]. ANNALS OF OPERATIONS RESEARCH, 2023,
  • [24] Ethical Challenges in Data-Driven Dialogue Systems
    Henderson, Peter
    Sinha, Koustuv
    Angelard-Gontier, Nicolas
    Ke, Nan Rosemary
    Fried, Genevieve
    Lowe, Ryan
    Pineau, Joelle
    [J]. PROCEEDINGS OF THE 2018 AAAI/ACM CONFERENCE ON AI, ETHICS, AND SOCIETY (AIES'18), 2018, : 123 - 129
  • [25] Data-driven Roadmapping Turning Challenges into Opportunities
    Pora, Ummaraporn
    Thawesaengskulthai, Natcha
    Gerdsri, Nathasit
    Triukose, Sipat
    [J]. 2018 PORTLAND INTERNATIONAL CONFERENCE ON MANAGEMENT OF ENGINEERING AND TECHNOLOGY (PICMET '18): MANAGING TECHNOLOGICAL ENTREPRENEURSHIP: THE ENGINE FOR ECONOMIC GROWTH, 2018,
  • [26] Data-Driven Usability Refactoring: Tools and Challenges
    Garrido, Alejandra
    Firmenich, Sergio
    Grigera, Julian
    Rossi, Gustavo
    [J]. 6TH INTERNATIONAL WORKSHOP ON SOFTWARE MINING (SOFTWAREMINING), 2017, : 52 - 55
  • [27] Opportunities and Challenges of Data-Driven Virus Discovery
    Lauber, Chris
    Seitz, Stefan
    [J]. BIOMOLECULES, 2022, 12 (08)
  • [28] Challenges of data-driven methods in product development
    Mehlstäubl, Jan
    Gadzo, Emir
    Atzberger, Alexander
    Paetzold, Kristin
    [J]. Konstruktion, 2022, 74 (06): : 60 - 66
  • [29] DATA-DRIVEN GLOBAL DYNAMICS OF THE INDIAN OCEAN
    Li, Zigang
    Yan, Wang
    Kang, Jiaqi
    Jiang, Jun
    Hong, Ling
    [J]. Lixue Xuebao/Chinese Journal of Theoretical and Applied Mechanics, 2021, 53 (09): : 2595 - 2602
  • [30] A data-driven model of the global calcite lysocline
    Archer, D
    [J]. GLOBAL BIOGEOCHEMICAL CYCLES, 1996, 10 (03) : 511 - 526