The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness

Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. The results of this research could provide valuable insights to researchers, policymakers, and industry leaders in order to enhance digitalization, which supports supply chain resilience, performance, and inclusiveness. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Damtew, Alie Wube [verfasserIn] Goshu, Yitagesu Yilma

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Digital vision Inclusive development AWS as digital enabler Supply chain resilience Supply chain performance

Anmerkung:	© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: The international journal of advanced manufacturing technology - London : Springer, 1985, 130(2024), 9-10 vom: 19. Jan., Seite 4821-4834
Übergeordnetes Werk:	volume:130 ; year:2024 ; number:9-10 ; day:19 ; month:01 ; pages:4821-4834

Links:	Volltext

DOI / URN:	10.1007/s00170-023-12919-4

Katalog-ID:	SPR054514908

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allfields	10.1007/s00170-023-12919-4 doi (DE-627)SPR054514908 (SPR)s00170-023-12919-4-e DE-627 ger DE-627 rakwb eng Damtew, Alie Wube verfasserin (orcid)0000-0001-7599-7704 aut The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. The results of this research could provide valuable insights to researchers, policymakers, and industry leaders in order to enhance digitalization, which supports supply chain resilience, performance, and inclusiveness. Digital vision (dpeaa)DE-He213 Inclusive development (dpeaa)DE-He213 AWS as digital enabler (dpeaa)DE-He213 Supply chain resilience (dpeaa)DE-He213 Supply chain performance (dpeaa)DE-He213 Goshu, Yitagesu Yilma aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 130(2024), 9-10 vom: 19. Jan., Seite 4821-4834 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:130 year:2024 number:9-10 day:19 month:01 pages:4821-4834 https://dx.doi.org/10.1007/s00170-023-12919-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 130 2024 9-10 19 01 4821-4834
spelling	10.1007/s00170-023-12919-4 doi (DE-627)SPR054514908 (SPR)s00170-023-12919-4-e DE-627 ger DE-627 rakwb eng Damtew, Alie Wube verfasserin (orcid)0000-0001-7599-7704 aut The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. The results of this research could provide valuable insights to researchers, policymakers, and industry leaders in order to enhance digitalization, which supports supply chain resilience, performance, and inclusiveness. Digital vision (dpeaa)DE-He213 Inclusive development (dpeaa)DE-He213 AWS as digital enabler (dpeaa)DE-He213 Supply chain resilience (dpeaa)DE-He213 Supply chain performance (dpeaa)DE-He213 Goshu, Yitagesu Yilma aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 130(2024), 9-10 vom: 19. Jan., Seite 4821-4834 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:130 year:2024 number:9-10 day:19 month:01 pages:4821-4834 https://dx.doi.org/10.1007/s00170-023-12919-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 130 2024 9-10 19 01 4821-4834
allfields_unstemmed	10.1007/s00170-023-12919-4 doi (DE-627)SPR054514908 (SPR)s00170-023-12919-4-e DE-627 ger DE-627 rakwb eng Damtew, Alie Wube verfasserin (orcid)0000-0001-7599-7704 aut The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. The results of this research could provide valuable insights to researchers, policymakers, and industry leaders in order to enhance digitalization, which supports supply chain resilience, performance, and inclusiveness. Digital vision (dpeaa)DE-He213 Inclusive development (dpeaa)DE-He213 AWS as digital enabler (dpeaa)DE-He213 Supply chain resilience (dpeaa)DE-He213 Supply chain performance (dpeaa)DE-He213 Goshu, Yitagesu Yilma aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 130(2024), 9-10 vom: 19. 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allfieldsGer	10.1007/s00170-023-12919-4 doi (DE-627)SPR054514908 (SPR)s00170-023-12919-4-e DE-627 ger DE-627 rakwb eng Damtew, Alie Wube verfasserin (orcid)0000-0001-7599-7704 aut The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. The results of this research could provide valuable insights to researchers, policymakers, and industry leaders in order to enhance digitalization, which supports supply chain resilience, performance, and inclusiveness. Digital vision (dpeaa)DE-He213 Inclusive development (dpeaa)DE-He213 AWS as digital enabler (dpeaa)DE-He213 Supply chain resilience (dpeaa)DE-He213 Supply chain performance (dpeaa)DE-He213 Goshu, Yitagesu Yilma aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 130(2024), 9-10 vom: 19. Jan., Seite 4821-4834 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:130 year:2024 number:9-10 day:19 month:01 pages:4821-4834 https://dx.doi.org/10.1007/s00170-023-12919-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 130 2024 9-10 19 01 4821-4834
allfieldsSound	10.1007/s00170-023-12919-4 doi (DE-627)SPR054514908 (SPR)s00170-023-12919-4-e DE-627 ger DE-627 rakwb eng Damtew, Alie Wube verfasserin (orcid)0000-0001-7599-7704 aut The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. The results of this research could provide valuable insights to researchers, policymakers, and industry leaders in order to enhance digitalization, which supports supply chain resilience, performance, and inclusiveness. Digital vision (dpeaa)DE-He213 Inclusive development (dpeaa)DE-He213 AWS as digital enabler (dpeaa)DE-He213 Supply chain resilience (dpeaa)DE-He213 Supply chain performance (dpeaa)DE-He213 Goshu, Yitagesu Yilma aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 130(2024), 9-10 vom: 19. Jan., Seite 4821-4834 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:130 year:2024 number:9-10 day:19 month:01 pages:4821-4834 https://dx.doi.org/10.1007/s00170-023-12919-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 130 2024 9-10 19 01 4821-4834
language	English
source	Enthalten in The international journal of advanced manufacturing technology 130(2024), 9-10 vom: 19. Jan., Seite 4821-4834 volume:130 year:2024 number:9-10 day:19 month:01 pages:4821-4834
sourceStr	Enthalten in The international journal of advanced manufacturing technology 130(2024), 9-10 vom: 19. Jan., Seite 4821-4834 volume:130 year:2024 number:9-10 day:19 month:01 pages:4821-4834
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Digital vision Inclusive development AWS as digital enabler Supply chain resilience Supply chain performance
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container_title	The international journal of advanced manufacturing technology
authorswithroles_txt_mv	Damtew, Alie Wube @@aut@@ Goshu, Yitagesu Yilma @@aut@@
publishDateDaySort_date	2024-01-19T00:00:00Z
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author	Damtew, Alie Wube
spellingShingle	Damtew, Alie Wube misc Digital vision misc Inclusive development misc AWS as digital enabler misc Supply chain resilience misc Supply chain performance The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness
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topic_title	The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness Digital vision (dpeaa)DE-He213 Inclusive development (dpeaa)DE-He213 AWS as digital enabler (dpeaa)DE-He213 Supply chain resilience (dpeaa)DE-He213 Supply chain performance (dpeaa)DE-He213
topic	misc Digital vision misc Inclusive development misc AWS as digital enabler misc Supply chain resilience misc Supply chain performance
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title	The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness
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title_full	The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness
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title_sort	impacts of aws from digital visions to action for supply chain resilience, performances, and inclusiveness
title_auth	The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness
abstract	Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. The results of this research could provide valuable insights to researchers, policymakers, and industry leaders in order to enhance digitalization, which supports supply chain resilience, performance, and inclusiveness. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstractGer	Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. The results of this research could provide valuable insights to researchers, policymakers, and industry leaders in order to enhance digitalization, which supports supply chain resilience, performance, and inclusiveness. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstract_unstemmed	Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. The results of this research could provide valuable insights to researchers, policymakers, and industry leaders in order to enhance digitalization, which supports supply chain resilience, performance, and inclusiveness. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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title_short	The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness
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up_date	2024-07-04T01:59:04.495Z
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This study aims to investigate digital vision strategies and develop an Amazon Web Services (AWS)–enabled model that contributes to enhancing supply chain resilience, supply chain performances, and inclusiveness in the manufacturing industry. Both qualitative and quantitative mixed-approach methods have been employed in these investigations. An intensive literature review of relevant studies and descriptive research analysis were employed for the investigations. Also, empirical investigations through descriptive statistics analysis employed aim to explore the impacts of digital vision and AWS technology adoption on supply chain resilience, performance, and inclusive developments. The result reveals that manufacturing industries predominantly operate based on traditional supply chain beliefs rather than actively embracing the concepts of digital vision strategies. It further shows that as the propagation of innovation and digital technologies continues to disrupt market segments and industries, adopting AWS can help you transform organizations to meet changing business conditions and evolving customer needs. The result also shows that for the enhancement of digital vision strategies, the development of innovative AWS models on the cloud platform has great positive impacts on supply chain resilience, supply chain performance, and inclusive developments in manufacturing industries. The results of this digital vision, primarily focused on helping to optimize costs, reduce business risks, improve operational efficiency, and provide more agile, innovative, and faster business practices to each segment of the supply chain process. Based on the results and investigations, a digital model AWS was developed and proposed. This study represents an innovative effort in developing a new digital vision strategy model that aligns with sustainability and performance goals and emphasizes supply chain resilience, inclusive development, and supply chain performance in the manufacturing industries. 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