A Competition Model for A Brazilian Air Shuttle Market

This paper aims at developing a competition model for a relevant subset of the Brazilian airline industry: the air shuttle market on the route Rio de Janeiro Ð S*o Paulo, a pioneer service created in 1959. The competition model presented here contains elements of both vertical product differentiation and representative consumer. I also use the conduct parameter approach to infer about the behaviour of airlines in the market under three situations: a quasideregulation rocess (from 1998 on), two price war events (1998 and 2001), and a shock in costs due to currency devaluation (1999). Results permitted making inference on the impacts of liberalisation on competition and investigating an alleged collusive behaviour of 1999.air shuttle, competition, deregulation, product differentiation

Show Me The Money, Sooner! How Faster Payments Boost Gig Workers\u27 Efforts and Productivity

Despite their astounding growth in recent years, online gig platforms face key challenges to increase gig workers\u27 working commitment. This study aims to examine the impact of a fundamental organizational design element payout frequency, which refers to the intervals at which workers access the funds they have earned. Drawing on expectancy theory, we argue that a higher payout frequency enhances both the quantity and quality of gig work. To investigate this, we analyze proprietary data from a quasi-natural experiment that involved an unexpected reduction in the payout cycle for gig workers in a specific geographic region. By employing propensity score matching and a difference-in-differences approach, we demonstrate that a shorter payout cycle led to an increase in the effort among the impacted gig workers and also resulted in improved work quality. These findings contribute to our understanding of effectively motivating and managing gig workers, ultimately influencing customer engagement on platforms

2020 Culture Shift: Measuring COVID-19 Impact on San Diego Arts and Culture Nonprofits

To better understand the impacts of the pandemic on City-funded arts and culture nonprofits and their workforce, The Nonprofit Institute at the University of San Diego – on behalf of the City of San Diego Commission for Arts and Culture – conducted a survey of arts and culture organizations funded by the City in fiscal year 2020. In that year, the City invested $11.4 million in arts and culture organizations. In fiscal year 2021, the City was forced to reduced annual funding to approximately$5.7 million due to drastically reduced tax revenues. Eight months into the pandemic, many City-funded arts and culture organizations are experiencing unprecedented financial losses.https://digital.sandiego.edu/npi-arts/1000/thumbnail.jp

Faculty Publications 2018-2019

The production of scholarly research continues to be one of the primary missions of the ILR School. During a typical academic year, ILR faculty members published or had accepted for publication over 25 books, edited volumes, and monographs, 170 articles and chapters in edited volumes, numerous book reviews. In addition, a large number of manuscripts were submitted for publication, presented at professional association meetings, or circulated in working paper form. Our faculty\u27s research continues to find its way into the very best industrial relations, social science and statistics journal

Visual Decision Support System Model for Managing Unemployment by Hybrid Education

Hybrid education is an approach that helps in conducting face-to-face and online distance learning especially for formal education. However, during COVID-19 pandemic, formal education institutions including schools and universities as well as informal education through the media for communities and industries are practiced by the lawmakers to manage workplace distancing. Food supply chain are experiencing unexpected disruptions due to interrelated activities that will determine supply chain performance and efficiency. This article explores the challenges faced by food industry and related sectors due to emergence impact of COVID-19 in Malaysia. Food supply chain management (FSCM) is a complex task involving interconnected activities and numerous stakeholders for a specific food product from raw materials to final product before it reaches the end customers. An overview of COVID-19 scenarios, followed by the impact of pandemic towards the activities in food supply chain, and the management issues that need to be addressed are presented. Several challenges identified are including the worldwide implication of the pandemic scenarios to food supply chain management and food supply chain activities, and indirect impact of supply chain disruption to labour force; unemployment and retrenchment. Finally, a visual decision support system (VDSS) model is developed to illustrate the main impacts of the pandemic scenario on food supply chain as well as addressing the labour management and opportunities. It has potential to provide general guidelines to educators, policy-makers, and decision-makers  to deal with uncertainties after the pandemi

Labour Market Frictions, Social Policies, and Barriers to Technology Adoption

Barriers to technological changes have recently been shown to be a key element in explaining differences in output per worker across countries. This study examines the role that labour market features and institutions have in explaining barriers to technology adoption. I build a model that includes labour market frictions, capital market imperfections and heterogeneity in workers' skills. I found that the unemployment rate together with the welfare losses that workers experiment after displacement are key factors in explaining the existence of barriers to technology adoption. Moreover, I found that none of these factors alone is sufficient to build these barriers. The theory also suggests that welfare policies like the unemployment insurance system may enhance these kinds of barriers while policies like a severance payment system financed by an income tax seem to be more effective in eliminating them.Barriers to technology adoption; Unemployment; Unemployment insurance; Workers displacement; Welfare cost.

Algorithm as Boss or Coworker? Randomized Field Experiment on Algorithmic Control and Collaboration in Gig Platform

Without a doubt, the heavy use of artificial intelligence (AI) will be involved in the future of work. Pertinent to the deployment of AI in organizations, algorithmic control is the managerial use of intelligent algorithms as a means to align individual worker behaviors with organizational objectives. While algorithmic control may facilitate efficient management of workers, it also leads to intrusive and unilateral exertion of controls over workers, also known as “algorithm as boss” phenomenon. In this study, we attempt to understand the outcomes and tradeoffs that different configurations between the AI and gig workers would produce, by conducting a randomized field experiment with one of the largest delivery rider labor unions in Asia. Overall, our study suggests that providing collaborative algorithmic control not only increases gig workers’ utility in terms of monetary rewards but also enhances their intrinsic rewards, which has the potential to benefit the gig platform as well

Exploring Financial Literacy of Independent Musicians in the Gig Economy

The purpose of this study is to gain insight into the elements of the career of independent musicians. Specifically, how they overcome or fail to overcome the challenges of a gig economy through knowledge and ability to properly manage scarce financial resources. The research questions posed are as follows: (a) Does higher financial literacy allow independent musicians to sustain and improve their career in the gig economy? (b) How do independent musicians use financial literacy to sustain their career? (c) How does industry experience affect the ability of independent artists to effectively allocate financial resources? To answer these research questions, relevant literature is first reviewed. Then, the proposed exploratory study is outlined, where data collected through in-depth interviews is analyzed using single-coder methods of analysis. Following the explanation of methodology, the findings that result from this data are discussed. Finally, implications of results and limitations of the study are discussed

Probabilistic Representation of a Normal Generalized Inverse Gaussian Integral: Application to Option Pricing

An analytical probabilistic integral representation for the European call option price in the Hurst-Platen-Rachev subordinated asset price model with generalized inverse Gaussian subordinator is obtained. For the limiting gamma mixing case, the representation yields simpler closed-form formulas for the European risk-neutral call option price in the exponential variance-gamma process by Madan, Carr and Chang. An elementary state-price deflator derivation of the Hurst-Platen-Rachev option pricing formula is also included

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

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 a new extension 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. We demonstrate how changing market conditions result in distinct evolutionary patterns for gig-labor preferences across high and low skill work-forces, which we explain through their differing sensitivities to market-driven consumer demand and financial incentives among other considerations. 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. Finally, 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