Operation Management and Supply Chain
Author Vikas Awari
The shortage economy and its implications for supply chain and operations management:
IVANOV and DOLGUI (2022) elaborated on the implications of the shortage economy on supply chain and operation management in their conceptual paper. In this paper they presented some major literature streams on supply chain and operation management which deal with resource shortages. To study the literature, they select authors who published research papers based on the resources like material, capital, energy and workforce which deals with the resource shortages. Using a classification into supply, demand and production activities authors structured the possible managerial implications of scarce resources and inflation on supply chains.at the end they state that the new context of the shortage economy is very challenging, but also very interesting and will certainly motivate development of new management solutions and research methods.
Data-driven operations and supply chain management: established research clusters from 2000 to early 2020:
NGUYEN et al. (2022) discusses the evolution and significance of data-driven decision-making in operations and supply chain management (OSCM) since the early 2000s, particularly focusing on the adoption of big data analytics (BDA) and its impact on enhancing supply chain efficiency, sustainability, and competitiveness. It highlights empirical research showing the positive correlation between data-based tools and OSCM efficacy and discusses various frameworks and models proposed to develop data-driven supply chains. Authors examines 580 selected papers published across 229 peer-reviewed journals on data-driven operations and supply chain management (OSCM). Notably, there is no dominant journal in terms of published articles, indicating the interdisciplinary nature of the field. The paper discusses the most highly cited papers, noting a correlation between Google Scholar and Web of Science (WOS) citation indices. However, there’s a discrepancy in citation patterns between globally and in-sample cited research, suggesting varying attention from scholars in different fields. They apply different methodologies to analyse data Six clusters of research emerge from the analysis, predominantly focusing on areas such as big data analytics in OSCM, transportation and traffic flow prediction, demand forecasting, and system integration in manufacturing. These clusters underscore the close association between OSCM and production research, with increasing emphasis on machine learning (ML) and big data analytics (BDA) techniques in addressing operational challenges. The paper synthesizes these clusters as essential reference points for both production research and practice, emphasizing the importance of developing staff’s data analysis capabilities and fostering organizational support for successful BDA adoption. It anticipates further highly-cited research clusters in ML and BDA for various aspects of inventory control, supply management, and distribution planning, enriching the knowledge base available to scholars and practitioners.
5G in digital supply chain and operations management:
DOLGUI and IVANOV (2022) highlights the critical role of supply chain engineering and management in the modern economy, emphasizing the transformative impact of technological advancements on supply chain designs, management, and operations. It discusses the influence of Industry 4.0 technologies such as big data analytics, blockchain, and additive manufacturing on shaping highly flexible and adaptable supply chain networks. The authors underscores 5G technology as a significant enabler of end-to-end connectivity, real-time data exchange, and flexibility in supply chain operations. It discusses the various capabilities of 5G, such as facilitating edge computing, enabling blockchain applications, and supporting the development of digital twins.
Blockchain adoption in operations and supply chain management:
QUEIROZ et al (2021) examines blockchain technology (BCT) adoption behavior in the Brazilian operations and supply chain management (OSCM) context, focusing on driving factors and barriers. Using a modified version of the unified theory of acceptance and use of technology (UTAUT), the study proposes and validates a model for understanding BCT adoption behavior. Through partial least squares structural equation modeling (PLS-SEM) and data collected from Brazilian OSCM professionals, the study provides insights into the unique challenges and opportunities for BCT adoption in emerging economies. The findings underscore the importance of cultural considerations in predicting BCT adoption intentions and suggest avenues for future research.
Big Data in operations and supply chain management:
TALWAR et al. (2021) In this research paper author (SLR) synthesized existing research on Big Data applications in operations and supply chain management (OSCM), addressing four research questions (RQs). The study offered theoretical implications by profiling research trends, identifying themes, and proposing a conceptual framework (DAB model). Managerially, it emphasized leveraging Big Data for demand forecasting, customer insights, supply chain agility, supplier management, and infrastructure development. Limitations included scope constraints and exclusion of non-English publications. Future research directions involve exploring specific service verticals, conducting empirical studies, reviewing BDA techniques, and examining adoption challenges in developing economies, aiming to enrich the literature and address critical research gaps.
Social media in operations and supply chain management:
HUANG et al. (2021) States tha while acknowledging the practical implications and theoretical insights of utilizing social media in operations and supply chain management (OSCM), in this paper author highlights several limitations. It emphasizes the need to address risks such as data security and reputation management arising from social media use in OSCM. Additionally, it suggests exploring strategies to mitigate these risks and optimize the integration of social media with existing information technologies. Despite reviewing 152 papers and proposing a framework connecting social media functions with OSCM activities, the paper underscores the continued need for further research to fully harness the value of social media and enhance company performance in OSCM.
The use of recycled materials in manufacturing:
FIELD and SROUFE (2007) In this study authers examines the separate design of forward and reverse supply chains in the corrugated cardboard industry, particularly focusing on the integration dynamics between independent and integrated firms. It showcases how the adoption of recycled materials, especially through mini-mills, reshapes supplier relationships and supply chain structures. The findings authers in this paper suggest that non-integrated firms benefit more from the use of recycled materials, leading to potential shifts in market dynamics and operations strategies. While the research acknowledges limitations in generalizability and causality due to its case study approach, it proposes valuable insights applicable to industries utilizing recycled materials, emphasizing the importance of understanding both environmental and non-environmental implications in supply chain management and operations strategy.
An Empirical Investigation on the Appointments of Supply Chain and Operations Management Executives:
HENDRICKS (2015) In this paper authers examines 681 SCOME appointments, finding positive stock market reactions, especially for outsider appointments in new positions. Newly created SCOME roles signal future performance improvement, while replacing existing SCOMEs with outsiders suggests addressing prior poor performance. Post-appointment, stock performance stabilizes, with relative improvements seen. Factors influencing insider vs. outsider appointments include firm size, industry concentration, and prior performance. Future research could explore SCOME characteristics’ impact on performance and theorize the positive market reaction to creating new SCOME positions.
Frameworks for Continuous Development in Operations and Supply Chain Management Analytics:
BENDOLY (2016) State that the academic discourse on modern data visualization is still evolving, with a lack of comprehensive guidelines leading to ambiguity in practice. Different contexts, ranging from data completeness to communication of insights, necessitate varied visualization approaches, yet subjective biases can hinder effective communication. The absence of structured norms exacerbates this issue, requiring awareness and integration of theory and practice to mitigate biases and align visual techniques with contextual needs for meaningful visualization.This discussion emphasizes the importance of methodical data visualization in supply chain management and operations research, cautioning against biases and premature conclusions. It highlights core principles applicable across theoretical perspectives, advocating for collaborative efforts to debias and improve visualization practices. The aim is to foster shared understanding and facilitate fruitful discussions for advancing research and practice in the field.
Optimizing Manufacturing and Supply Chain Operations in Logistics Management:
KADADEVARAMATH et al. (2008) State that supply chain management integrates business planning concepts dating back to the 1950s, now enabled by information technology. Despite this, many companies struggle to implement new analytical tools effectively. The supply chain encompasses geographically dispersed facilities for sourcing, transforming, and distributing goods. The primary objective is to add value to products and deliver them efficiently to diverse markets. Traditional objectives include reducing total supply chain costs, comprising various elements such as acquisition, transportation, facility, manufacturing, distribution, inventory, and transportation costs.In this paper authers evaluates PSO algorithm performance in optimizing a four-stage supply chain model, considering capacity, inventory, and demand constraints. Mathematical formulation, solved with PSO algorithm and exterior penalty method for constraints, demonstrates effective modeling and optimization of the supply chain network.
Conclusion:
The discussed papers encompass a wide array of topics within operations and supply chain management (OSCM), highlighting the evolving landscape driven by technological advancements and shifting economic paradigms. From exploring the implications of shortage economies on supply chain management to delving into the adoption of data-driven decision-making, blockchain technology, and 5G in OSCM, the literature underscores the critical role of innovation in reshaping industry practices. Additionally, studies on social media integration, recycled material utilization, and executive appointments provide insights into addressing emerging challenges and leveraging opportunities in supply chain and operations. Collectively, these papers emphasize the need for continuous development, strategic optimization, and interdisciplinary collaboration to navigate the complexities of modern supply chains effectively.
References:
IVANOV, D.; DOLGUI, A. The shortage economy and its implications for supply chain and operations management. International Journal of Production Research, [s. l.], v. 60, n. 24, p. 7141–7154, 2022. DOI 10.1080/00207543.2022.2118889. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=d5f05b22-5e71-35e5-8353-b9edf3ca6c83. Acesso em: 21 fev. 2024.
NGUYEN, D. T. et al. Data-driven operations and supply chain management: established research clusters from 2000 to early 2020. International Journal of Production Research, [s. l.], v. 60, n. 17, p. 5407–5431, 2022. DOI 10.1080/00207543.2021.1956695. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=9733abbf-0282-3b67-a863-2202ef107359. Acesso em: 21 fev. 2024.
DOLGUI, A.; IVANOV, D. 5G in digital supply chain and operations management: fostering flexibility, end-to-end connectivity and real-time visibility through internet-of-everything. International Journal of Production Research, [s. l.], v. 60, n. 2, p. 442–451, 2022. DOI 10.1080/00207543.2021.2002969. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=59e3f56e-43fd-3a04-b5ae-019e0b785332. Acesso em: 21 fev. 2024.
QUEIROZ, M. M. et al. Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy. International Journal of Production Research, [s. l.], v. 59, n. 20, p. 6087–6103, 2021. DOI 10.1080/00207543.2020.1803511. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=3c8b52e9-b7de-3551-8822-017d3b156379. Acesso em: 21 fev. 2024.
TALWAR, S. et al. Big Data in operations and supply chain management: a systematic literature review and future research agenda. International Journal of Production Research, [s. l.], v. 59, n. 11, p. 3509–3534, 2021. DOI 10.1080/00207543.2020.1868599. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=e86deb03-bbd4-3968-88b2-405ae9ba1b0e. Acesso em: 21 fev. 2024.
HUANG, S.; POTTER, A.; EYERS, D. Social media in operations and supply chain management: State-of-the-Art and research directions. International Journal of Production Research, [s. l.], v. 58, n. 6, p. 1893–1925, 2020. DOI 10.1080/00207543.2019.1702228. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=7f1eec25-bc69-39c5-b53b-0b9b03cf502d. Acesso em: 21 fev. 2024.
FIELD, J. M.; SROUFE, R. P. The use of recycled materials in manufacturing: implications for supply chain management and operations strategy. International Journal of Production Research, [s. l.], v. 45, n. 18/19, p. 4439–4463, 2007. DOI 10.1080/00207540701440287. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=b91b0c3a-37df-302d-80c5-a2983bab3400. Acesso em: 21 fev. 2024.
HENDRICKS, K. B.; HORA, M.; SINGHAL, V. R. An Empirical Investigation on the Appointments of Supply Chain and Operations Management Executives. Management Science, [s. l.], v. 61, n. 7, p. 1562–1583, 2015. DOI 10.1287/mnsc.2014.1987. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=5e6a5fcb-a8a2-3b35-8215-7a94fc430bcd. Acesso em: 21 fev. 2024.
BENDOLY, E. Fit, Bias, and Enacted Sensemaking in Data Visualization: Frameworks for Continuous Development in Operations and Supply Chain Management Analytics. Journal of Business Logistics, [s. l.], v. 37, n. 1, p. 6–17, 2016. DOI 10.1111/jbl.12113. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=eef2a5c3-f12e-3d1c-b599-6a60e5b59344. Acesso em: 21 fev. 2024.
KADADEVARAMATH, R. et al. Optimizing Manufacturing and Supply Chain Operations in Logistics Management. ICFAI Journal of Supply Chain Management, [s. l.], v. 5, n. 1, p. 54–68, 2008. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=c2630c68-e521-3a66-9a2a-efad701a4e3f. Acesso em: 22 fev. 2024.
