There are two parts of this research, both related to the channel strategy of firms.

Part 1: Strategic Value of Capacity Commitment with Asymmetric Channel Competition

Motivated by the growing dominance of large retailers, we examine the strategic value of capacity commitment when a dominant retailer in a centralised channel competes against a small retailer in a decentralised channel.

In this research, we develop a stylised model with two asymmetric channels, namely, one centralised and one decentralised, both of which order from the same manufacturer to sell to downstream consumers. In the centralised channel, the dominant retailer orders directly from the manufacturer and has the option to commit its capacity. The decentralised channel comprises of a wholesaler which orders directly from the manufacturer and sells to a small retailer, which in turn sells to downstream consumers. The wholesaler in the decentralised channel also has the option to commit its capacity. The objective of this research is to determine the extent in which the channel structure affects the strategic value of capacity commitment for firms.

Part 2: Distribution and After-Sales Service Channel: Strategies under Asymmetric Retailer Competition

Current voices from marketing scholars and practitioners have predominantly focused on the cost benefits when production of goods or provision of service is outsourced to lower-cost providers.

In this research, we study the dual effects of distribution channel and after-sales service channel strategies when firms do not have any advantage on service provision costs. We examine the strategic interaction between the manufacturer’s distribution and after-sales service channel strategies. We seek to understand how the channel structure affects after-sales provision and the possibility of outsourcing.

This project currently consists of two sub-projects. In the first, I examine the labour supply response of individuals to child support, and relate that to an important labour supply elasticity used by labour and macro economists. Specifically, child support in many countries is set as a function of income, and child support liabilities end when the children involved reach emancipation age. Exploiting these two features, I estimate the intertemporal elasticity of labour supply (Frisch elasticity) in an event study design using individual-level panel data from four countries.

In the second, my co-author and I investigate the effect of seasonal unemployment on individual behavioural and other outcomes. In most economies, the unemployment rate varies across months of the year, generally for reasons unrelated to the current macroeconomic conditions and outside the control of individuals. This seasonality in the unemployment rate also varies across industries and occupations, motivating a difference-in-differences strategy. Exploiting this, we examine the effect on various behavioural outcomes, including drug use, consumption, time use, and program participation.

There is growing evidence that economic events – such as economic policies, bankruptcies, and production disruptions – may create cascading effects in the economy. More surprising is the evidence from the networks literature that even small and firm-specific shocks can propagate and become relevant in the aggregate.

Despite this evidence, we still understand very little about the factors that drive these spill-overs in the economy. If economic agents could easily adjust to these small shocks, then we would not observe the amplification of these shocks through the economy.

I investigate cases of such transmission of shocks and spill-overs in customer supply chains and bank credit portfolios. More importantly, I propose possible mechanisms that prevent agents from fully compensating these shocks. One of them might be the set of laws and institutions that govern the enforcement of debt contracts and business contracts.

The widespread use of credit reports to screen finance employees has recently garnered significant attention. Several studies show that credit screening has real effects on employment decisions and hiring, but the relation between credit screening and job performance has not been tested. This research project will create and analyse a dataset of personal credit histories merged with detailed information on financial advisors’ career transitions.

We will combine this data with state-level implementations of laws banning credit screening by potential employers to examine whether credit screening is a useful tool for addressing one aspect of job performance – professional misconduct by financial advisors. Recent research shows that misconduct by financial advisors is prevalent and that misconduct does not have severe labour market consequences.

Given the importance of this industry in ensuring households’ financial well-being and the current changing legal landscape concerning the permissibility of pre-employment credit checks, understanding their potential ability to enhance customer protection is vital to ensure proper policy in this industry.

With the rapid development in technologies in recent years, artificial intelligence (AI) is gradually making an appearance in the workplace. Although researchers from multiple disciplines have started to pay more attention to AI, they tend to focus on the technical aspects and ethical issues of the application, leaving employees’ adaptive attitudes and behaviours not fully addressed. As direct users and collaborators, employees’ adaptive attitudes and behaviours are crucial for organisations to gain sustainable benefits from AI applications to meet important organisational goals. As such, there is a strong desire from organisations to understand how employees perceive AI and how to promote their adaptive attitudes and behaviours. The purpose of this study is to examine the potential influence of AI on employees from two aspects—employees’ perceptions toward AI and their perception towards jobs post AI adoption.

We plan to validate the AI function measurement and test the relationships between AI functions and AI perceptions/job characteristics in our study. To enhance causal interpretations, we will conduct an experiment where we will manipulate the different AI functions and evaluate participants’ perceptions toward AI, job characteristics and work outcomes after experiment. Finally, we test the full theoretical model using employees from organisations that have adopted AI. Our study will address the critical issue regarding the workforce reactions toward AI applications by examining employees’ psychological responses to AI and to their jobs. Our study underlines that AI’s impact may differ depending on its functions. We also caution against conceptualising AI in a widely-used and oversimplified manner without considering its different functions.

The study is a collaboration with Associate Professor Chi Wei from Tsinghua University School of Economics and Management, and is funded by a grant from Ng Teng Fong Charitable Foundation.

The daily commute to work is an inevitable part of organisational life and is often considered one of the most stressful and least meaningful part of the workday (Stone & Schneider, 2016). A recent survey by Moovit Public Transportation Index (2018) showed that the average Singaporean spent about 84 minutes a day on public transportation, with over 85 per cent reporting that they spent more than two hours commuting every day. Majority of these people are working adults who commute to and from work by public transportation on a daily basis. Given that the daily commute to and from work consumes a large part of employee’s time, it is imperative to examine the impact of the commute experience on employees’ work-related outcomes and well-being.

The topic of commuting is especially critical at this point in time where COVID-19 has made commute safety a concern. While measures have been put in place to allow employees to work from home, those working in essential services still need to commute as part of their daily routine, making commute safety a concern. Travelling on public transportation puts them at risk of infection as they are exposed to other commuters. This may increase their commute stress, which in turn has implications for work. The present research seeks to address these issues. Data will be collected using qualitative interviews and experience sampling methodology. Results of this project will provide a more nuanced understanding of how the daily commute impacts employees’ attitudes and behaviours at work and at home.

The anxiety and fear associated with the COVID-19 pandemic have posed a psychological trauma for people around the globe. Our study draws on clinical psychology perspective to explore how employees sharing their COVID-19 experiences on social media can enhance their feelings of empathy and perceptions of social support, which in turn, influence their task performance and helping behaviour. Analysing this from a clinical psychology perspective further suggests that the benefits of social sharing are greater when employees impart their experiences with those from similar demographics due to the greater relevance and closeness.

Immediately after the government ended the nationwide social distancing rules in South Korea (6 May 2020), we collected data from 84 full-time office workers for ten consecutive workdays starting from the first day when they returned to work. The results from our experience-sampling study (Level 1 N = 815, Level 2 N = 84) provide general support for our predictions. Our research responds to urgent calls for understanding employees’ experiences after returning to work as businesses and countries have started relaxing their social-distancing rules to revive the economy.

This study reveals that organisations would benefit from employees’ social sharing about COVID-19, which boosts their productivity through empathy and social support among co-workers. We suggest organisations encourage their employees to support each other and, ultimately, accomplish a successful transition during this pandemic.

This project studies the uses of financial technology (fintech) on corporate finance and household investment behaviour. For corporate finance, expanding access to small riskier firms can stimulate economic growth and innovation. However, there are also more information asymmetry. For household investment behaviour, fintech has the potential to increase financial market participation and improve risk-sharing through access to cheaper information and financial services. However, it can also be used by companies to exploit individual behavioural biases. Using a combination of observational as well as experimental data, I study the impact of fintech on existing market participants and new entrants.

There are three main questions in this area. First, what role do alternative lenders play in the financial system in terms of the allocation of credit, amount, and quality of entrepreneurship in the economy? Second, how does access to data and high-frequency financial affect well-documented behavioural biases in terms of consumption, savings, and investments? On the one hand, more information access should improve the quality of decision-making along various dimensions. On the other hand, having a high throughput of information may also exacerbate overreactions to news. Finally, what is the role and impact of financial regulation on the functioning of lending and equity markets?

As fintech solutions burgeon in various settings in the financial services industry, understanding the impact of such developments on the functioning of the financial markets becomes increasingly important to avoid market failures, anti-competitive effects, and privacy issues.

This project is part of a large multi-cluster Future Resilient Systems 2 (FRS 2) proposal funded by the National Research Foundation in 2020. It will use interdisciplinary approaches to model firm networks and online investor networks so that we can better understand how individual/firm networks affect the resilience of financial systems.

Due to the outbreaks of major political, economic, and natural disasters (e.g., the 2008 global financial crisis and the ongoing COVID-19 pandemic), the resilience concept has been widely and enthusiastically embraced by policy-makers, practitioners and academics. Financial systems are critical for developing, maintaining, and fostering the resilience of many high-density urban systems (HD-US). At the same time, HD-US are critical for the functioning and development of financial systems.

I propose to develop relevant research methodologies that will be useful to market players who wish to better understand the resilience of corporate decisions, and to policymakers who can rely on such models to deal with systemic risks and recovery.

My research focuses on emerging markets, with a particular interest in strategy and policy questions that have implications for firm performance. The global microfinance industry, with a unique business model aimed at improving access to finance for people at the base of the pyramid, has been widely documented as being impressive in terms of loan repayment rates.

This is often attributed to its unique business model that despite not involving any asset as collateral can ensure a high likelihood of loan repayment by taking advantage of the high social capital that poor people often have within their communities. What is less well documented is that lending organisations’ over-reliance on a community’s social capital could pose a serious risk: if some borrowers decide to default on their repayments, this loan default behaviour is likely to diffuse rapidly through the tightly-knit social networks.

My research empirically examines this possibility by examining how two negative policy shocks affected the microfinance organisations in India:

1. An unexpected crisis in 2010 in the Indian state of Andhra Pradesh, when a string of farmer suicides led the regional policymaker to take unexpected and very stern actions that proved bad for the business and viability of microfinance institutions;
2. An unexpected drop in liquidity in the Indian economy in end-2016, when the government implemented the 2016 demonetisation policy that led to a cash crunch wherein people suddenly had a lot less valid cash from which to make repayments.

Another project in the research stream focusing on strategy in emerging markets seeks to understand (a) why some firms gain while others lose market share in the wake of a sudden increase in global demand, and (b) how subnational heterogeneity by geography may influence this competitive dynamic.

This research project seeks to investigate whether the differential opportunity cost of firms is an important mechanism that may provide an answer to these questions.

Leveraging the 2009-10 H1N1 influenza pandemic as a source of exogenous increase in global demand for influenza vaccines, the project investigates how subnational heterogeneity in economic resources, industry infrastructure, and political alignment may differently affect the performance of incumbent MNEs and rival domestic firms following the pandemic.

This research project aims to provide evidence-based insights on the interplay between subnational heterogeneity and firm behaviour in the wake of a global pandemic. The findings are likely to have important implications for a contemporary problem at the business-societal interface.