Sesil Lim

This paper investigates the anthropological and ethical roots of the global ecological and social crisis, centered on Pope Francis’s critique of the “throwaway culture” (Laudato Si’, LS). While LS identifies this crisis in the linear “take–make–dispose” model and the technocratic paradigm—which prioritizes efficiency over moral reflection—this research argues that these macro-societal failures originate in a foundational spiritual pathology: concupiscence. Drawing upon St. John Paul II’s Theology of the Body (TOB), we analyze concupiscence as “appropriation,” the direct antithesis to the human vocation of the “sincere gift of self.” This study aligns LS’s socio-economic critique with Karol Wojtyła’s personalist anthropology, asserting that the systemic exploitation of nature and the marginalization of the vulnerable are structural extensions of the human failure to reread the “language of the body” in truth. The throwaway culture is thus revealed as an axiological reduction—a societal manifestation of lust that reduces both the body and creation to mere objects of utility. Consequently, a genuine ecological conversion (LS) necessitates embracing the “ethos of redemption” (TOB). This transformation of desire is essential to restoring the harmony between humanity and nature, recognizing that the ‘cry of the earth’ and the ‘cry of the poor’ are inextricably linked within an integral ecology.

Algorithmic transparency is widely considered essential for fostering trust in AI-based financial e-commerce services. However, empirical evidence remains limited on whether transparency benefits all consumers uniformly and how it is evaluated relative to other service attributes in realistic decision contexts. This study examines how consumers trade off transparency, personalization, and user control in robo-advisor (RA) services across different consumer segments. Through a discrete choice experiment and latent class logit modeling, two distinct segments are identified: selective high-expertise investors, who prioritize personalization and user control over transparency, and receptive general consumers, who respond strongly to enhanced explainability. These findings indicate that algorithmic transparency does not serve as a universal design solution but operates conditionally based on consumer expertise and attribute interactions. Simulation results further show that while a regulation-compliant, uniform service design may facilitate market entry, it constraints long-term expansion in heterogeneous markets. In contrast, a segment-based service portfolio calibrated to the distinct preferences of each group significantly increases overall adoption under the same regulatory constraints. These results suggest that sustainable AI diffusion in financial e-commerce requires a nuanced approach that balances disclosure with functional autonomy to address the diverse needs of both sophisticated and novice users.

Estimating the shadow price of undesirable outputs is an important topic in production and environmental economics, as it provides information on the economic cost of environmental regulation. Directional distance function (DDF) approaches have been widely employed for this purpose; however, conventional DDF estimation methods are largely limited to point estimation, which constrains statistical inference. This study proposes a bootstrap procedure integrated into a parametric linear programming-based DDF framework that explicitly incorporates undesirable outputs. The proposed methodology is applied to Korean firm-level data. By allowing interval estimation of DDF values, the approach makes it possible to conduct statistical inference on the estimated parameters. The empirical results indicate that DDF estimates obtained using the bootstrap approach differ from those derived from the non-bootstrap method. The resulting shadow prices of CO₂ are economically interpretable and comparable in magnitude to observed emission permit prices, suggesting their relevance for policy analysis. The results indicate that incorporating bootstrapping into a parametric DDF framework enhances statistical inference in the estimation of shadow prices for undesirable outputs.

Digital technology in financial services is helping consumers gain wider access to investment funds, acquire these funds at lower costs, and customize their own investments. However, direct digital access also creates new challenges because consumers may make suboptimal investment decisions. We address the challenge that consumers often face complex investment decisions involving multiple funds. Normative optimal asset allocation theory prescribes that investors should simultaneously optimize risk–returns over their entire portfolio. We propose two behavioral effects (mental separation and correlation neglect) that prevent consumers from doing so and a new choice architecture of virtually integrating investment funds that can help overcome these effects. Results from three experiments, using general population samples, provide support for the predicted behavioral effects and the beneficial impact of virtual integration. We find that consumers’ behavioral biases are not overcome by financial literacy, which further underlines the marketing relevance of this research.

Disclosing the energy performance information for buildings has been expected to become an important policy for controlling energy demand and reducing CO₂ emissions, but its effectiveness remains controversial. This study investigates the effect of energy performance information on consumer residential choice by using a discrete choice experiment in South Korea. The estimation results confirmed that the energy efficiency level of the given housing has a significant effect on consumer residential choice when the related information is actually delivered. Combined with evidence from the simulation study, we suggest that obligating the owners to provide energy performance information to potential buyers/tenants would be necessary for enhancing the use of the information during the consumer decision-making process. Additionally, the simulation result implies that the effectiveness of the policy can be underestimated by the price premium related to energy efficiency. Therefore, we suggest that the government should control the price premium for high-efficiency buildings at the early stage so that the policy related to disclosing the energy performance can be on track.

Social acceptance of nuclear power has become a decisive factor in framing a sustainable energy policy. This study examines social acceptance for cancelling the construction of planned nuclear power plants (NPPs) and replacing them with other energy sources. The contingent valuation method (CVM) and cost–benefit analysis (CBA) are used to access the social acceptance and financial feasibility of such projects. Empirical analysis is based on the case of South Korea, where a similar policy is in progress under the new government. The CVM results show that a Korean household was willing to pay an additional KRW 1922.45/month (USD 1.80/month) for replacing seven 1-Gigawatt NPPs with other energy sources, which is about 3.5% of a household’s current electricity bill. The CBA suggests that the annual costs of replacing this amount of nuclear power capacity with renewables or liquefied natural gas is KRW 1291.40 billion (USD 1.21 billion) or KRW 1180.38 billion (USD 1.11 billion) larger than its benefits, which amounts to about 3% of total annual electricity generation costs in South Korea. As the additional costs of nuclear power replacement cannot be fully covered by the mean willingness-to-pay of the current acceptance level, moderate levels of social resistance are expected if all the additional costs are passed on to the end-users.

Discrete choice experiments (DCEs) are increasingly used for health state valuations. However, the values derived from initial DCE studies vary widely. We hypothesize that these findings indicate the presence of unknown sources of bias that must be recognized and minimized. Against this background, we studied whether values derived from a DCE are sensitive to how well the DCE design spans the severity range.