Operations Management in the Age of the Sharing Economy: What Is Old and What Is New?

Benjaafar, Saif; Hu, Ming

doi:10.1287/msom.2019.0803

Cited by 209 publications

(82 citation statements)

References 66 publications

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“…ML can be considered a subset of AI, and both ML and AI can be considered part of BDA (Marr, 2017). Benjaafar and Hu (2019) provide a comprehensive review of BDA research and stipulate that machines using AI capabilities will substitute humans for many activities in the future. They call for research investigating the implications of large-scale smart machines.…”

Section: Disruptive Technologiesmentioning

confidence: 99%

Disruptive Technologies and Sustainable Supply Chain Management: A Review and Cross-Case Analysis

Ajmal¹,

Wang²

2021

JMS

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This study examines the relationship between disruptive technologies and their potential impacts on sustainable supply chain management (SSCM), with a focus on the following technologies: Big Data Analytics / Artificial Intelligence / Machine Learning, Blockchain, Industry 4.0 / Internet of Things (IoT), 3D Printing / Additive Manufacturing, and P2P / Sharing Economy. Based on a comprehensive literature review on both theoretical and practical roles of these disruptive technologies in SSCM, we conduct a cross-case study to analyze the impacts of disruptive technologies on sustainability performance. From 100 application cases of 41 companies in key supply chain management and sustainability journals, we develop a classification scheme based on implementation complexity and sustainability performance of disruptive technologies. The implementation complexity and sustainability performance matrix show that all the cases examined have a positive overall sustainability performance score which indicates that investment in disruptive technologies improves the sustainability performance of firms. However, the impact of each disruptive technology on sustainability performance varies with the types of technology and sustainability dimensions. We also utilize the cases to illustrate how disruptive technologies are applied to key areas of SSCM and identify opportunities for future research.

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Section: Disruptive Technologiesmentioning

confidence: 99%

Disruptive Technologies and Sustainable Supply Chain Management: A Review and Cross-Case Analysis

Ajmal¹,

Wang²

2021

JMS

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“…Optimal investment strategy for sharing platform; e.g., [48][49][50] Development of analytical framework to select business modes under the sharing economy; Description of classical operations management theory and models, which can be used to study applications of sharing economy.…”

Section: Operations Research and Management Science 75mentioning

confidence: 99%

Challenges of the Sharing Economy for SMEs: A Literature Review

Šoltysová

Modrák

2020

Sustainability

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The sharing economy is becoming increasingly popular in many sectors also thanks to the fact that not only young generation, but people of almost all ages are digitally literate, and therefore they readily participate in sharing economy practices. A very important part of their motivation comes from the knowledge that it is a great way to save money, but a no less important reason is the philosophical aspect, which is consistent with efforts to promote more sustainable consumption practices that prioritize access over ownership. The sharing economy has become a subject of interest not only among researchers and practitioners but also among policymakers and stakeholders who are concerned about the further extension of digital ecosystems. Fortunately, theorists from many fields, such as the commercial economy, gift economy, entrepreneurship, digital transformation, etc., pay due attention to this phenomenon. However, there is still room for focused exploration of this entrepreneurial and innovative approach from specific views in order to bring useful findings and insights on given issues. The intention of this study is to analyze the existing related literature and categorize sharing economy-based business models in relation to traditional business models. Potentially, this study can also contribute to a better understanding of the perspectives of the sharing economy in the transition of SMEs towards the Industry 4.0 paradigm.

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“…In recent decades, contract or 'gig' work has emerged as a commanding employment category in the United States, having captured more than one third of the labor market by 2018 [3]. At the cornerstone of this development are online labor marketplaces that facilitate the exchange of talent and capital between firms and workers, effectively decreasing hiring frictions and increasing labor liquidity [4][5][6]. The result of this infrastructure furtherance takes form in a novel, complementary contract-based labor market monikered the sharing, collaborative or gig economy [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…On the one hand, there is an expectation that the gig economy will continue to grow with the introduction of new sharing platforms and businesses [10,19]. On the other hand, there exists a growing accord in scholarship that artificial intelligence (AI) will displace many human operators [4], especially those with commodity skills [20]. The rapid acceleration of AI may implicate the displacement of gig workers, for instance, the substitution of ride-sharing drivers with the introduction of autonomous vehicles [4].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, there exists a growing accord in scholarship that artificial intelligence (AI) will displace many human operators [4], especially those with commodity skills [20]. The rapid acceleration of AI may implicate the displacement of gig workers, for instance, the substitution of ride-sharing drivers with the introduction of autonomous vehicles [4]. A question remains as to whether these displaced workers will reenter the workforce as employees or gig workers.…”

Section: Introductionmentioning

confidence: 99%

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Evolutionary Dynamics of Gig Economy Labor Strategies under Technology, Policy and Market Influence

2021

Games

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The emergence of the modern gig economy introduces a new set of employment considerations for firms and laborers that include various trade-offs. With a game-theoretical approach, we examine the influences of technology, policy and markets on firm and worker preferences for gig labor. Theoretically, we present new conceptual extensions to the replicator equation and model oscillating dynamics in two-player asymmetric bi-matrix games with time-evolving environments, introducing concepts of the attractor arc, trapping zone and escape. While canonical applications of evolutionary game theory focus on the evolutionary stable strategy, our model assumes that the system exhibits oscillatory dynamics and can persist for long temporal intervals in a pseudo-stable state. We demonstrate how changing market conditions result in distinct evolutionary patterns across labor economies. Informing tensions regarding the future of this new employment category, we present a novel payoff framework to analyze the role of technology on the growth of the gig economy. Regarding governance, we explore regulatory implications within the gig economy, demonstrating how intervals of lenient and strict policy alter firm and worker sensitivities between gig and employee labor strategies. Finally, we establish an aggregate economic framework to explain how technology, policy and market environments engage in an interlocking dance, a balancing act, to sustain the observable co-existence of gig and employee labor strategies.

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Operations Management in the Age of the Sharing Economy: What Is Old and What Is New?

Cited by 209 publications

References 66 publications

Disruptive Technologies and Sustainable Supply Chain Management: A Review and Cross-Case Analysis

Disruptive Technologies and Sustainable Supply Chain Management: A Review and Cross-Case Analysis

Challenges of the Sharing Economy for SMEs: A Literature Review

Evolutionary Dynamics of Gig Economy Labor Strategies under Technology, Policy and Market Influence

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