The Grind for Good Data: Understanding ML Practitioners' Struggles and Aspirations in Making Good Data

We thought data to be simply given, but reality tells otherwise; it is costly, situation-dependent, and muddled with dilemmas, constantly requiring human intervention. The ML community's focus on quality data is increasing in the same vein, as good data is vital for successful ML systems. Nonetheless, few works have investigated the dataset builders and the specifics of what they do and struggle to make good data. In this study, through semi-structured interviews with 19 ML experts, we present what humans actually do and consider in each step of the data construction pipeline. We further organize their struggles under three themes: 1) trade-offs from real-world constraints; 2) harmonizing assorted data workers for consistency; 3) the necessity of human intuition and tacit knowledge for processing data. Finally, we discuss why such struggles are inevitable for good data and what practitioners aspire, toward providing systematic support for data works

Efficiency versus Equality: Comparing Design Options for Indirect Emissions Accounting in the Korean Emissions Trading Scheme

The Korean emissions trading scheme (ETS) has one special characteristic that makes it different from other schemes, such as the EU ETS. While the other schemes consider only direct emissions from fossil fuels, the Korean ETS also regulates indirect emissions arising from the consumption of electricity. The problem of double counting arises under this setting, in which emissions from the power sector can be accounted for twice, when electricity is produced and consumed. This study aims to compare design options on indirect emissions accounting for the Korean ETS using a computable general equilibrium model. Four scenarios are generated for options accounting for direct and/or indirect emissions and are evaluated in terms of efficiency and equality. The result shows that the ETS operates most efficiently when only direct emissions are considered. However, the option that includes both direct and indirect emissions produces a competent result in terms of equality by spreading the economic burden of emissions reduction among industries. We conclude that this option can be an alternative to meet the key purposes of the Korean ETS

IT Adoption and Sustainable Growth of Firms in Different Industries—Are the Benefits Still Expected?

This study uses data from the Korea business activity survey panel from 2008 to 2016 to examine the effects on the sustainable growth of firms that initially adopted Information Technology (IT) applications during 2010 to 2012 compared to those that did not. The effects are examined for four years after adoption and divided into areas such as sales, labor productivity, profitability, increases in male and female employment, wages, and exports. Because the effects of IT adoption are known to vary greatly depending on the industry, the manufacturing industry is divided into traditional, medium-tech, and hi-tech manufacturing, and the service industry is divided into the materials service and information service sectors; the effects on each sector are then observed. In addition, the propensity score matching methodology is used to overcome selection bias arising from a simple comparison between firms that began using IT and firms that did not. The results show that, although there was little impact on productivity, there were impacts on sales and employment and large differences were found between the industrial sectors

Effect of Work-Family Balance Policy on Job Selection and Social Sustainability: The Case of South Korea

South Korea needs to actively implement work-family balance policies to increase both the low employment rate of women and the low total fertility rate. This study analyzes the quantitative benefits that the implementation of work-family balance policies provides to employees and employers. We conducted a choice experiment that asked 633 participants about their stated preferences for a hypothetical company with different work-family balance practices. The analysis was performed by using a hierarchical Bayesian model that considered preference heterogeneity according to the respondents’ characteristics. The results indicate that the availability of parental leave provides benefits equivalent to an increase of 5.80 million won in annual salary and that offering childcare in the workplace has an effect equivalent to an increase of 5.37 million won in annual salary. Further, low-income groups, women, the younger generation, and parents of preschool children are most sensitive to the policy. Finally, small and medium-sized enterprises are less desirable to work for than large companies, but the implementation of work-family balance policies could change this preference

Analysis of OTT Users’ Watching Behavior for Identifying a Profitable Niche: Latent Class Regression Approach

Over-the-top (OTT) firms must overcome the hurdle of the competitive Korean media market to achieve sustainable growth. To do so, understating how users enjoy OTT and analyzing usage patterns is essential. This research aims to empirically identify a profitable niche in the Korean OTT market by applying market segmentation theory. In addition, it investigates an effective content strategy to convert free users into paying customers belonging to profitable niche segments. The latent class regression model was applied to Korean Media Panel Survey data to divide Korean OTT customers into submarkets. According to an empirical analysis, Korean OTT users can be divided into three submarkets based on their OTT usage patterns, with the third segment serving as a profitable niche market. An additional analysis of the profitable niche market revealed that bundling content, such as foreign content, original content, and movies, is a crucial content strategy for increasing paying subscribers in a profitable niche segment

Analysis of product efficiency of hybrid vehicles and promotion policies

The key aim of this study is to evaluate the product efficiency of current hybrid vehicles and suggest effective policies to promote hybrid vehicles in the Korean automobile market and development trends of hybrid vehicles. The efficiency levels for car models sold in Korea, including hybrid ones, were measured using the recently developed discrete additive data envelopment analysis (DEA) model that reflects consumer preference. The result of the analysis shows that current hybrid vehicles on the market are still at lower competitive advantage than traditional car models with conventional combustion engines and we can suggest a mix of incentive policies to promote the competitiveness of hybrid vehicles. In addition, we also identify two distinctive trends of hybrid vehicle development: environment-oriented hybrid vehicles and performance-oriented hybrid vehicles. It implies that the government should take account of development trends of hybrid vehicles to achieve the policy goals in designing support schemes and automobile companies that are willing to develop hybrid vehicles can also gain some insights for making strategic decisions.Hybrid vehicles Data envelopment analysis Korea

Efficiency versus equality: Comparing design options for indirect emissions accounting in the Korean emissions trading scheme

The Korean emissions trading scheme (ETS) has one special characteristic that makes it different from other schemes, such as the EU ETS. While the other schemes consider only direct emissions from fossil fuels, the Korean ETS also regulates indirect emissions arising from the consumption of electricity. The problem of double counting arises under this setting, in which emissions from the power sector can be accounted for twice, when electricity is produced and consumed. This study aims to compare design options on indirect emissions accounting for the Korean ETS using a computable general equilibrium model. Four scenarios are generated for options accounting for direct and/or indirect emissions and are evaluated in terms of efficiency and equality. The result shows that the ETS operates most efficiently when only direct emissions are considered. However, the option that includes both direct and indirect emissions produces a competent result in terms of equality by spreading the economic burden of emissions reduction among industries. We conclude that this option can be an alternative to meet the key purposes of the Korean ETS

Impact and Interactions of Policies for Mitigation of Air Pollutants and Greenhouse Gas Emissions in Korea

Korea faces a challenging task of simultaneously reducing emissions of air pollutants and greenhouse gases (GHG). Since both are emitted from the same sources such as fossil fuel combustion and economic activities, there could be commonalities and interactions between the policies for reducing each of them. A static computable general equilibrium model is developed to observe the economic impact of policies for reducing air pollutants or GHG and the interactions between those policies in Korea. The results show that reducing one of the air pollutants, particulate matter 2.5 (PM2.5) emissions by 30% from the business-as-usual (BAU) in 2022 will lead to reduction of GHG emissions by 22.8% below the BAU level, exceeding the national GHG reduction target. Also, by achieving the domestic GHG reduction target, which is 32.5% below the BAU level by 2030, PM2.5 emissions will be reduced by 32.8%. The costs of reducing air pollutants and greenhouse gas are high, reaching from 0.34% to 1.75% of gross domestic product, and the reduction causes an asymmetrical damage to emission intensive industries. The sum of the benefits from air pollutants and GHG reduction is estimated to be 0.4 to 1.2 times greater than the costs, depending on the scenario