The Call of the Pandemic: Rethinking Global Value Chains

The effect of the COVID-19 pandemic on global value chains has been pervasive. An all-time-high demand for ventilators, personal protective equipment such as masks and gowns, medicines, and other essential health supplies collided with supply shortages. Stringent lockdowns enforced by different countries at different times led to severe consequences for industrial supply chains. As the pandemic spread, few countries have been resilient enough to cope well with the pace of transformed supply and demand requirements. This policy brief explains how firms and countries need to critically evaluate their upstream supply chains and how public policy should support creating domestic core manufacturing capabilities that can help mitigate the effects of disasters

Supply chain network structure and environmental information disclosure

Recognizing that supply network structure has implications for a focal firm’s ability to access environmental information embedded in its supply network, this paper draws on structural, environmental, and financial data from Bloomberg to test the relationship between a focal firm’s supply network structure and its extent of environmental information disclosure.First author draf

Essays on Environmental Spillovers in Supply Chains

abstract: The phenomenon of global warming and climate change has increasingly attracted attention by researchers in the field of supply chain and operations management. Firms have developed efficient plans and intervention measures to reduce greenhouse gas (GHG) emissions. While a majority of research in supply chain management has adopted a firm-centric view to study environmental management, this dissertation focuses on the context of GHG emissions reduction by considering a firm’s vertical and horizontal relationships with other parties, and the associated spillover effects. A theoretical framework is first proposed to facilitate the field's understanding of the possible spillover effects in GHG emissions reduction via vertical and horizontal interactions. Two empirical studies are then presented to test the spillover effect in GHG emissions reduction, focusing on the vertical interactions - when firms interact with their supply chain members. Drawing data from Bloomberg Environmental Social and Governance, and Bloomberg SPLC, this study conducts econometric analyses using various models. The results suggest that first, a higher level of supply chain GHG emissions is associated with the adoption of emissions reduction programs by a firm, and that this supply chain leakage contributes to the firm’s financial performance. Second, a firm's supply base innovativeness can contribute to its internal GHG emissions reduction, and this effect is contingent on a firm's supply base structure. As such, this dissertation answers the recent call in the field of supply chain and operations management for more empirical research in socially and environmentally responsible value chains. Further, this study contributes to the literature by providing a better understanding of the externalities that value chain members can impose on one another when pursuing sustainability goals.Dissertation/ThesisDoctoral Dissertation Business Administration 201

Essays on employee management in service operations

This dissertation takes an employee-oriented approach to the within-firm OM decisions and investigates the effects of interventions focusing on employees on the process outcomes. Through a series of three essays, we handle three management tools; rank-based performance feedback, knowledge transfer via the adoption of best practices, and algorithmic real-time feedback and coaching; each has potential adverse effects on employees yet could be very rewarding once successfully implemented. We seek to gain a profound understanding of employee behavior and stimulate engagement, thereby fostering more efficient and productive systems. In the first chapter, we conduct a series of experiments to study the impact of three different types of relative performance feedback (RPF) on middle-ranked workers' output on a skill-based task. We find that receiving any type of feedback reduces performance compared to no feedback. We conduct mediation analysis and show that receiving feedback changes employees' feelings associated with general performance, which explains the performance reduction. Aligned with theory, delivering feedback increases the focal employee's social comparison involvement (SCI), which measures the focal individual's tendency to compare themselves to others while performing the task, and their shame. The second chapter concentrates on enhancing performance through fostering internal knowledge transfer and promoting the adoption of best practices. Through a series of experiments, we assess the effects of providing performance feedback in conjunction with best practices on knowledge-seeking behavior, best practice adaptions, and operational performance. Our study poses an exciting finding by showing that RPF's previously documented negative effect on middle-ranked workers could be mitigated, and performance improvement could be attained when combined with best practices. The concluding chapter focuses on the effect of using algorithmic feedback and coaching as management tools in service operations within call center environments. Companies are deploying artificial intelligence applications into service settings in a variety of ways, from automating agent tasks to replacing human servers altogether. This study examines how artificial intelligence-based feedback (AI) impacts customer service agent employee productivity as measured by three key performance indicators: call-handle time, customer satisfaction, and call service quality. Our field partner, a North American outsourced call center deployed the AI software to monitor calls during a bill collection campaign and provide visible cues to remind agents of their service script requirements. In this way, the AI acts as a real-time supervisor, assessing agent performance and offering real-time feedback during and after the call. Using international call center data, we provide evidence that agents with access to the AI feedback are indeed more likely to comply with scripts and in so doing, deliver increased operational efficiency with lower call handle time. Moreover, calls conducted with AI feedback show an increase in two service quality metrics not commonly associated with technology-assisted communication: respect and rapport. In summary, through three studies, we offer theoretical and practical implications about the use and challenges associated with various management tools and provide ways to improve employee behavior to stimulate engagement and foster more efficient and productive systems

Strategic decisions under uncertainty: Supplier quality improvement and exit in duopoly

This dissertation consists of three interrelated essays on firm-level decision problems when the exterior environment (e.g. product quality or market prospect) is uncertain and there are strategic interactions with other firms (e.g. competitors). The first essay (Chapter 2) studies a buyer’s decision to improve its supplier’s quality when the focal supplier is shared by another buyer who competes in the same market. Each buyer’s investment is a way to outperform the other buyer. However, the investment opportunity comes with spillover risk via the shared supplier. Given this risk-benefit tradeoff, we characterize the conditions under which the optimal timing of the first investment in shared suppliers is earlier (or later) than in sole suppliers. Also, we find that learning moderates the impact of competition and spillover on investment decisions, which suggests that the interplay between learning, spillover, and competition should be carefully examined to build sound investment strategies. The second essay (Chapter 3) also examines buyers’ investment decisions in a buyer-supplier-buyer triad. However, we consider the case when market competition is not an integral part of the problem so that a buyer strives to free-ride on the other buyer’s investment in the shared supplier. Moreover, because the improved quality deteriorates over time by organizational forgetting, buyers should make such an investment decision repeatedly. This problem is thus a repeated free-rider problem. The main finding of this essay is that each buyer delays its investment in the hope of free-riding on the other only if the game is repeated and there is a unique equilibrium entailing inefficient delays. Due to this uniqueness of the equilibrium, we are able to construct the well-defined measure for the inefficiency from free-riding incentives and estimate this inefficiency by using primary data from a field study of an automotive manufacturer. The results from this estimation indicate that the inefficiency can be substantial although it greatly varies depending on the supplier sectors. The third essay (Chapter 4) investigates firms’ exit decision problems under uncertainty by employing the similar mathematical framework used in the second essay: The first firm to exit the market concedes the monopolist’s profit to the remaining firm. The extant literature in economics has predicted that the firms stay in the market longer than necessary. We revisit this problem with two realistic perturbations – firms are asymmetric in their exit barriers and the market evolves stochastically. In contrast to the findings of the previous literature, we find that this perturbed model does not admit an MPE (Markov perfect equilibrium) resulting in inefficient (i.e. longer than necessary) stays. Therefore, this asserts the instability of an equilibrium with inefficient stays, which provides a novel rationale for selecting an equilibrium over the others