About

Anníbal Sodero is an Assistant Professor at the Fisher College of Business, specializing in Supply Chain Management and Logistics. His research and teaching interests lie at the intersection of Economics, Marketing, and Information Systems, focusing on areas such as information technology management, logistics management, and innovation management. His scholarly work has been published or is forthcoming in reputable journals including the Journal of Operations Management, Journal of Business Logistics, Decision Sciences Journal, International Journal of Physical Distribution and Logistics Management, and Supply Chain Management Review. Notably, his study utilizing consumer sentiments from online forums to enhance demand planning for flash sales was selected for the 'Research for the Real World' series in a special issue of Supply Chain Quarterly. Dr. Sodero's courses are project- and case-based, emphasizing practical application of logistics and supply chain concepts. He serves as an Associate Editor for the Journal of Operations Management, the Decision Sciences Journal, and the International Journal of Physical Distribution and Logistics Management, and is a member of the Editorial Review Board at the Journal of Supply Chain Management and the Journal of Business Logistics. Prior to his academic career, he founded and led Ad Hoc Informática, an IT business in Brazil that provided software and consulting services for logistics providers, which is now part of Benner Sistemas, a leading ERP and BPO provider in Brazil.

Research topics

• Computer Science
• Marketing
• Business
• Industrial organization
• Process management
• Mathematics
• Telecommunications

Selected publications

• Designing scenario-based experiments in retail SCM: methodological approaches and practical insights

  International Journal of Physical Distribution & Logistics Management · 2025-01-24 · 13 citations

  articleSenior author

  Purpose Considering the transformational impact of technological advances in modern retail on the consumer experience and the associated growth of experimental studies in consumer-centric supply chain management (SCM) research, this paper presents a practical overview of key steps in the design of scenario-based experiments (SBEs) in the context of retail SCM. Design/methodology/approach Following a conceptual approach, this paper discusses essential aspects in the designing process, including the connection to theory, vignette design considerations, experimental checks and ensuring managerial relevance. Findings This paper presents a resource for SCM researchers in their pursuit of designing rigorous, context-focused SBEs in consumer-centric retail SCM research. Major design considerations and potential pitfalls are highlighted. Practical implications A well-designed experiment, including its vignettes, manipulations and checks, offers strong potential to inform actionable guidance for managers in the feasibility, strategy design, customization and consumer segmentation of retail SCM strategies. Originality/value This paper connects the steps in the design of SBEs to consumer-centric retail SCM questions, supporting future research in this realm.

  PublisherDOI

• Last Mile Delivery Capacity Planning With Two‐Sided Uncertainty

  Journal of Business Logistics · 2025-10-01 · 3 citations

  article

  ABSTRACT Crowdsourced delivery (CD) is increasingly combined with private delivery (PD) to respond to last mile delivery (LMD) demand uncertainty. As independent contractors, CD drivers self‐schedule, which simultaneously creates labor supply uncertainty. Consequently, such LMD capacity planning requires addressing both uncertainties concurrently, a duality we term “two‐sided uncertainty.” In this setting, two key questions emerge: what is the optimal level of PD capacity when CD is available? How does two‐sided uncertainty impact the PD capacity decision? To that end, we adapt a two‐stage newsvendor model to explore the impact of two‐sided uncertainty on optimal PD capacity when CD is available. We combine Monte Carlo simulation and optimization in empirically grounded experiments using data from a Brazilian prepared meals company. We find a positive relationship between two‐sided uncertainty and PD capacity. We also reveal nuance in the relationship by identifying moderating effects due to correlation in driver availability across CD price tiers and failed delivery costs. The results also indicate that optimal delivery capacity typically combines PD and CD sources rather than relying on a single source. We show that managerial decisions based solely on lowest unit delivery cost while assuming away two‐sided uncertainty can lead to suboptimal decisions.

  PublisherDOI

• Reconceptualizing E‐Logistics Service Quality (E‐LSQ) in Emerging Contexts: The Case of Crowdsourced Delivery

  Journal of Business Logistics · 2024-11-25 · 11 citations

  articleOpen accessSenior author

  ABSTRACT E‐logistics service quality (e‐LSQ) has been one of the primary constructs used in the logistics literature to capture customers' appraisals of delivery service performance in the business‐to‐consumer (B2C) context. While e‐LSQ comprises key operational aspects of delivery performance, we posit that it overlooks other elements that are now present in emerging delivery models, such as crowdsourced delivery (CD). In this study, we follow a middle‐range theory approach to capture the facets of delivery performance that are considered by customers in their assessments of e‐LSQ during CD encounters. Using a large dataset consisting of customers' reviews of their delivery service experiences with Amazon Prime Now prior to and post‐CD incorporation, we find that customers value a more nuanced operational dimension as well as relational and societal dimensions in their assessments of the delivery service. The findings of our qualitative analyses enrich the current understanding of customers' appraisals of delivery service encounters and lay the groundwork for reassessing e‐LSQ, particularly in light of emerging delivery models like CD in online retailing.

  PublisherOA PDFDOI

• Crowdsourced delivery and customer assessments of<scp>e‐Logistics</scp>Service Quality: An appraisal theory perspective

  Journal of Business Logistics · 2023 · 40 citations

  Senior authorCorresponding
  • Computer Science
  • Business
  • Marketing

  Abstract Thanks to increased technological advancements, retailers have progressively incorporated crowdsourcing into their delivery service portfolios to offer customers an enhanced last‐mile delivery experience. Yet, while studies have explored the unique operational attributes of the crowdsourced delivery (CD) model in online retailing, the literature remains scant on how customers respond to the usage of this emerging delivery service. Building on the cognitive appraisal theory and e‐Logistics Service Quality (e‐LSQ) literatures, this study applies middle‐range theorizing to examine differences between customers' appraisals of e‐LSQ dimensions of CD and traditional delivery methods, and what types of products being delivered make such differences more pronounced. Our analysis of a large sample of customers' reviews across multiple retailers reveals that customers exhibit higher appraisal levels of timeliness, price, and reliability of delivery services when CD is used. Results also indicate that appraisals are more pronounced for timeliness and price of deliveries of high‐turnover products that require minimal time and effort to purchase. Our findings, as such, underscore the power of CD as a tool to enhance customer experience and unveil potential opportunities for effective CD use in customer segmentation strategies.

  PublisherDOI

• Good cause, not so good business? Sales and operations performance of cause‐related marketing

  Journal of Business Logistics · 2022-02-14 · 14 citations

  article1st authorCorresponding

  Abstract Building on prior literature on sales and operations planning, corporate social responsibility, and marketing campaigns, we investigate cause‐related marketing (C‐RM) effects on sales and operations performance across the retail supply chain. C‐RM is a corporate social responsibility marketing campaign, in which a for‐profit firm donates proceeds from consumer purchases of a promoted product to a designated nonprofit cause. Using a unique, rich, and proprietary dataset from an actual CR‐M campaign, we conduct a quasi‐experiment analysis. Our findings suggest positive C‐RM effects on retail store sales during the campaign, coupled with enduring negative effects on forecast bias and service levels upstream in the retail supply chain. Although academic studies and the specialized media have thoroughly documented the benefits of C‐RM to corporate branding, our findings point to trade‐offs in sales and operations performance across the retail supply chain. These findings call for firms to carry out holistic assessments of the strategic value of C‐RM involving all of its stakeholders, including sales and operations planners and the nonprofit cause, as well as investments in the development and improvement of their forecasting management competence.

  PublisherDOI

• The strategic drivers of drop-shipping and retail store sales for seasonal products

  Journal of Retailing · 2021 · 25 citations

  1st authorCorresponding
  • Computer Science
  • Business
  • Marketing
  PublisherDOI

• Everything Old is New Again: The Age of Consumer‐Centric Supply Chain Management

  Journal of Business Logistics · 2020 · 90 citations

  • Marketing
  • Business
  • Industrial organization

  Over the past several decades, the disciplines of marketing and logistics grew apart from their common historical origins as marketing became more behavioral and more quantitative, while logistics leaned toward a more operational orientation. We argue in this editorial that social and technological changes in the past 20 years, coupled with the effects of the COVID pandemic, have created the conditions for the two disciplines to reconnect. We propose that scholars and practitioners consider a consumer‐centric approach to supply chain management. Such an approach advocates that the entire supply chain should focus on consumer experience rather than mere customer service and that experiences might include issues such as last‐mile delivery, supply chain visibility, and consumer values. We also introduce the papers appearing in this issue of the journal.

  PublisherOA PDFDOI

• Data and Predictive Analytics Use for Logistics and Supply Chain Management

  e-Publications@Marquette (Marquette University) · 2019-01-01

  articleOpen access1st authorCorresponding

  Purpose The purpose of this paper is to explore the social process of Big Data and predictive analytics (BDPA) use for logistics and supply chain management (LSCM), focusing on interactions among technology, human behavior and organizational context that occur at the technology’s post-adoption phases in retail supply chain (RSC) organizations. Design/methodology/approach The authors follow a grounded theory approach for theory building based on interviews with senior managers of 15 organizations positioned across multiple echelons in the RSC. Findings Findings reveal how user involvement shapes BDPA to fit organizational structures and how changes made to the technology retroactively affect its design and institutional properties. Findings also reveal previously unreported aspects of BDPA use for LSCM. These include the presence of temporal and spatial discontinuities in the technology use across RSC organizations. Practical implications This study unveils that it is impossible to design a BDPA technology ready for immediate use. The emergent process framework shows that institutional and social factors require BDPA use specific to the organization, as the technology comes to reflect the properties of the organization and the wider social environment for which its designers originally intended. BDPA is, thus, not easily transferrable among collaborating RSC organizations and requires managerial attention to the institutional context within which its usage takes place. Originality/value The literature describes why organizations will use BDPA but fails to provide adequate insight into how BDPA use occurs. The authors address the “how” and bring a social perspective into a technology-centric area.

  Publisher

• The social process of Big Data and predictive analytics use for logistics and supply chain management

  International Journal of Physical Distribution & Logistics Management · 2019-08-20 · 67 citations

  article1st authorCorresponding

  Purpose The purpose of this paper is to explore the social process of Big Data and predictive analytics (BDPA) use for logistics and supply chain management (LSCM), focusing on interactions among technology, human behavior and organizational context that occur at the technology’s post-adoption phases in retail supply chain (RSC) organizations. Design/methodology/approach The authors follow a grounded theory approach for theory building based on interviews with senior managers of 15 organizations positioned across multiple echelons in the RSC. Findings Findings reveal how user involvement shapes BDPA to fit organizational structures and how changes made to the technology retroactively affect its design and institutional properties. Findings also reveal previously unreported aspects of BDPA use for LSCM. These include the presence of temporal and spatial discontinuities in the technology use across RSC organizations. Practical implications This study unveils that it is impossible to design a BDPA technology ready for immediate use. The emergent process framework shows that institutional and social factors require BDPA use specific to the organization, as the technology comes to reflect the properties of the organization and the wider social environment for which its designers originally intended. BDPA is, thus, not easily transferrable among collaborating RSC organizations and requires managerial attention to the institutional context within which its usage takes place. Originality/value The literature describes why organizations will use BDPA but fails to provide adequate insight into how BDPA use occurs. The authors address the “how” and bring a social perspective into a technology-centric area.

  PublisherDOI

• Omnichannel Assortment Decisions in a Fashion Retailing Supply Chain

  Springer series in supply chain management · 2019-01-01 · 5 citations

  book-chapter1st authorCorresponding
  PublisherDOI

Frequent coauthors

• Elliot Rabinovich

  Arizona State University

  9 shared

• Terry L. Esper

  The Ohio State University

  9 shared

• Mark Barratt

  Marquette University

  5 shared

• Adriana Rossiter Hofer

  4 shared

• Ha Ta

  Florida International University

  4 shared

• Thomas Kull

  Arizona State University

  2 shared

• Yao Jin

  2 shared

• Thomas J. Goldsby

  1 shared

Education

• Ph.D. Supply Chain Management, Department of Supply Chain Management

  Arizona State University

  2012

• Ms.C. Supply Chain Management, Warwick Manufacturing Group

  University of Warwick

  2002

• BS.C. Computer Sciences, Ciência da Computação (Computer Sciences)

  Universidade Federal de Minas Gerais

  1996