This study aims to investigate online commerce repertoire-based clusters and their characteristics with shopping values and commerce attributes. This study analyzes Nielsen panel log data that recorded nearly 6,000 panelists’ use of 48 major commerce websites and mobile applications. In addition, a survey was conducted with a sample of the panelists, which supplemented the behavioral data and provided cognitive and attitudinal data. Six commerce clusters were identified: “Social commerce centric,” “Secondhand centric,” “PC centric,” “scattered,” “Home-shopping centric,” and “Fashion centric". Also, “Hedonic” was statistically significant and “Quick delivery,” “Membership” are perceived to be effective. Also, there were discrepancies between the log and survey on usage. As online marketing and advertising driving conversion becomes critical, the understanding of online commerce repertoires and related consumer perceptions and characteristics should offer significant implications.

최근 글로벌 정치․경제 환경의 대전환으로 미국과 유럽 국가들은‘재산업화 전략’으로 제조업 회복을 추진하고 있고, 중국도 ‘중국제조 2025’를 통해 제조업의 질적 발전과 고도화에 집중하고 있다. 이러한 상황에서 본 연구는 외국인직접투자(Inward Foreign Direct Investment, IFDI)가 중국 제조업 고도화에 미치는 영향에 대해 실 증적 분석을 통해 검증해 보고자 하였다. 제조업 가운데 첨단기술 산업의 비중을 중국 제조업 고도화의 지표로 이용하여 2004년부터 2020년까지의 17개년도 중국 31개 성(省)별 패널데이터로 고정효과 모형과 FGLS 모형 을 활용하여 실증분석을 하였다. 분석 결과, 중국 전체와 중국의 동부, 중부, 동북 지역, 장강경제벨트는 IFDI가 중국 제조업 고도화에 긍정적인 영향을 미치는 것으로 나타났지만, 서부지역에 대해서는 영향을 미치지 않는 것 으로 나타났다. 이러한 결과를 통해 IFDI가 중국 제조업 고도화에 미치는 영향은 지역별로 다소 차이가 존재 하고 있음을 입증하였다. 분석 결과는 중국 정부의 IFDI를 통한 지역 균형 발전정책이 중부와 동북 지역에 대 해서는 효과적이었음을 알 수 있었던 반면 중국 서부지역에 대해서는 IFDI를 통한 첨단기술 산업 고도화의 정 책 목표와 전략을 수정할 필요가 있음을 시사한다. 한편 통제변수로 활용된 변수인 수출과 수입으로 측정된 개 방정도와 첨단기술에 대한 연구개발 투자는 제조업 고도화에 매우 긍정적인 영향을 미치는 것으로 일관되게 나 타나고 있다.

Deforestation and poverty in developing countries are critical ongoing issues. Forests provide a broad spectrum of benefits and services to millions of people, and more than $14 billion has been globally spent on the Forestry Official Development Assistance 2000-2019. The purpose of this study was to empirically analyze the effect of forestry ODA on the economic development and forest conservation policies of 87 major recipient countries, using panel data from the OECD DAC CRS, and the World Bank WBI 2003-2018. Herein, fixed effect and random effect models were applied, to 1,392 observed panel data using the R software. Results are as follow. First, results show that the forestry ODA has a positive and statistically significant effect on forest conservation. The higher the forest-dependent country, the greater the positive effect. On the other hand, the forestry ODA does not have a positive effect on the economic development of the recipient country. As the positive effect of the forestry, ODA has been verified; it is necessary to continuously increase international cooperation projects as well as financial support, in line with these international trends. Additionally, results suggest a joint and integrated project with the agriculture as well as forestry sectors because forest areas and farmlands area have a close negative ( ) relationship. Thus, the results provide substantial evidence for supporting as well as establishing, a solid momentum of international cooperation policies in the forest sector.

The purpose of this study is to identify economic situation on scale of tuna distant longline fishery by analyzing its economies of scale using the cost function. To analyze its economics of scale, the deep-sea fishing statistics were used from 2012 to 2016. In detail, the number of panels for estimating the cost function was 68 tuna distant longline vessels from 2012 to 2016, and the total number of observations over the five years were 340. As a final model, the two-way fixed effect model based on the translog cost function was adopted through the F test, the Breusch-Pagan test and the Hausman test. As a result of the analysis, it was found that tuna distant longline fishery between 2012 and 2014 was diseconomies of scale, the fishery between 2015 and 2016 was economies of scale. However, the economic indicators of the scale from 2012 to 2016 were almost close to zero, indicating that the constant returns to scale, the optimal scale, were reached. Therefore, in the situation where the amount of fishery resources in the world continues to decrease, it is necessary to prepare a method to obtain economic benefits through scale maintenance and reduction rather than indiscriminate scale expansion.

The purpose of this paper is to analyze factors affecting the net income of regional and industrial fisheries cooperatives in South Korea using panel data. This paper utilizes linear or GLS regression models such as pooled OLS model, fixed effects model, and random effects model to estimate affecting factors of the net income of regional and industrial fisheries cooperatives. After reviewing various tests, we eventually select random effects model. The results, based on panel data between 2013 and 2018 year and 64 fisheries cooperatives, indicate that capital and area dummy variables have positive effects and employment has negative effect on the net income of regional and industrial fisheries cooperatives as predicted. However, debt are opposite with our predictions. Specifically, it turns out that debt has positive effect on the net income of regional and industrial fisheries cooperatives although it has been increased. Additionally, this paper shows that the member of confreres does not show any significant effect on the net income of regional and industrial fisheries cooperatives in South Korea. This study is significant in that it analyzes the major factors influencing changes in the net income that have not been conducted recently for the fisheries cooperatives by region and industry.

The research model of panel data analysis in this study was used as the dependent variables and the business characteristics of the welding industry were reflected in the research model for systematic analysis of the effect of welding technology on the welding industry. As a result of the existing research, the domestic welding technology is seriously encroaching on the domestic welding industry between the United States, Japan and China. There is no quantitative statistical analysis on this aspect. In this study, the panel data analysis is used to indicate differences in explanatory power by numerical values of POLS model, fixed effect and random effect. And the prior studies on the current status of welding industry related to arc welding, special welding, multiple welding, welding and bonding technology are applied by the panel data analysis. Therefore, the problems of existing research are diagnosed while presenting the future research directions.

Introduction The concept of brand equity has been receiving considerable interest from academia and practice in the past decades. While mutual understanding exists on the importance of establishing high-equity brands, less agreement among academics and practitioners prevails regarding its conceptualization and operationalization. Many approaches have been proposed to measure brand equity in academic literature and numerous competing companies such as Millward Brown, Interbrand, or Young & Rubicam offer commercial metrics and brand evaluations, which are likely to estimate different values to a specific brand. This study reflects a consumer-based perspective on brand equity, which resides in the heart and mind of the consumer and captures the value a brand endows beyond the attributes and benefits its products imply. Growing calls for the accountability of marketing has resulted in increasing interest in marketing metrics, which includes mind-set metrics to address the “black box” between marketing actions and consumer actions in the market. Theoretical Development One of the most prominent conceptualizations of brand equity is based on the premise that brand equity is “the differential effect of brand knowledge on consumer response to the marketing of the brand” consisting of brand awareness and brand image as the predominant dimensions that shape brand knowledge. In this model, a crucial role is ascribed to consumer’s associations with a brand as a reflection of its image. Accordingly, brand building and differentiation is based on establishing favorable, strong, and unique associations. Human associative network theory is a widely accepted concept to explain the storage and retrieval of information and has been largely applied in the context of brands. Associative network theory suggests that brand information is stored in long-term memory in a network of nodes that are linked to brand associations such as attributes, claims or evaluations. Consumers use brand names as cues to retrieve associations. Once cues activate corresponding nodes and consumers retrieve information from memory, the activation spreads to related nodes. Consequently, a transfer of associations can also occur through associative chains in a process of attitude formation. Consumer response to a brand can be of attitudinal and behavioral character and research on attitudes supports the general notion that both, affective and cognitive structures, explain attitude formation. The predictive properties of attitudes regarding actual behavior have been acknowledged by prior research and the attitude-behavior relationship has been established. Research Design Operationalization of Brand Equity This study distinguishes between attitudinal and behavioral measures of brand equity. The behavioral measures of brand equity should reflect the attitudinal brand equity components in predicting product-market outcomes. High brand equity should lead to a willingness to pay a price premium, purchase intention and willingness to recommend. Survey Brand equity measures are tested with two waves of data collection2 from online surveys conducted in 2015 and 2016. Respondents were recruited from a professional panel provider to ensure that the same respondents participated in wave two after a year from the first wave. Participants were selected according to a quota regarding age and gender to increase representativeness and were then randomly assigned to one of the three industries beer, insurance, and white goods capturing brand equity from different perspectives and allowing for a more holistic view. Sample The sample for the first wave consists of 2.798 respondents. The sample was matched with the response from wave two and only those respondents were selected who participated in both waves. Given the panel mortality rate, the final sample size for longitudinal analysis is 1.292 observations. The respondents’ age ranges from 18 to 74 with 52 percent being male and 48 percent female. Analysis Panel regression is used to estimate models assessing the relative importance of various brand equity metrics regarding the three outcome variables for the three categories included. The results suggest that no universal brand equity metric dominates that can be applied to predict behavioral outcomes across categories. Yet, category-specific brand equity metrics prevail across outcomes. Consumers seem to evaluate a strong brand as an entity they can personally connect to in the insurance category. In the beer category, consumers’ evaluation of strong brands reflects deep affect and the perception of product quality. High equity brands relate to loyal consumers with strong affective evaluations in the category of durable household products. Moreover, the results indicate that brand equity measurement can be simplified to a small subset of metrics without risking loss of model fit and predictive power. Discussion While a plethora of brand equity metrics exists, the results of this study suggest that brand managers can apply a small subset of available metrics to track their brands’ equity and predict behavior without implementing long surveys that require considerable time and effort from increasingly overloaded consumers. Yet, adjustments to the composition of brand equity metrics might be inevitable in light of category-specific effects. Moreover, the results reveal that a consideration of metrics capturing affective components such as brand self-connection and deep feelings such as brand love is indispensable for brand equity measurement. Including emotional measures and extending established brand equity metrics that are deeply rooted in extant research might provide a considerable advantage when it comes to measuring brand value in different product categories. References are available upon request.

When evaluating effectiveness of a program, there is a tendency to simply compare the performances of the treated before and after the program or to compare the differences in the performances of the treated and the untreated before-after the program. However, these ways of evaluating effectiveness have problems because they can’t account for environmental changes affecting the treated and/or effects coming from the differences between the treated and the untreated. Therefore, in this paper, panel data analysis (fixed effects model) is suggested as a means to overcome these problems and is utilized to evaluate the effectiveness of fusion technology program conducted by Ministry of Trade, Industry and Energy, Korea. As a result, it turns out that the program has definitely positive impacts on the beneficiary in terms of sales, R&D expenditure, and employment.

본 연구는 1970 ~ 2000년 기간 세계 148개국으로 구성된 패널자료를 이용해 세계 식량생산함수를 추정하였다. 생산함수의 결정요인으로는 노동, 물적자본, 인적자본 및 경작면적 등 경제적 생산요소뿐만 아니라 강수량과 기온 등 기후적인 요인까지 포함하였다. 또한 권역 간의 차이를 명확하게 확인하기 위해 권역더미변수를 고려해 권역 간 설명변수별 추정계수에 대한 동일성 검정을 실시하였다. 실증분석 결과, 다음과 같은 시사점을 얻을 수 있었다. 첫째, 설명변수 중 노동, 물적자본 및 인적자본 등 경제적 요인들의추정계수가 유의하고 그 부호도 경제이론과 일치하는 것으로나타나 분석의 타당성을 확인할 수 있었다. 둘째, 생산요소 중경작면적의 탄력성이 가장 크게 나타나는데, 이는 식량생산이기본적으로 토지를 기반으로 한다는 점에서 당연히 예상할 수있는 결과라 하겠다. 이를 통해 식량생산의 증가를 위해 경작면적의 확대가 긴요함을 확인할 수 있다. 이는 또한 기후온난화와 더불어 사막화로 인한 경작면적의 감소가 장기적으로 식량위기의 원인으로 대두될 수 있으며 이에 대비하기 위해 관개시설 및 간척 등을 통해 장기적으로 경작면적을 확보해 나가야 할 당위성을 입증한다 하겠다. 셋째, 각 설명변수가 식량생산에 미치는 영향은 권역별로 상당한 차이를 나타내었다. 특히, 식량생산에서 규모에 대한 수익은 경제발전이 심화된 [북미 및 유럽]에서는 감소하는 반면, 대부분의 국가가 개발도상에 있는 [남·동아시아 및 오세아니아]와 [중앙·서아시아 및 북아프리카]에서는 증가하는 것으로 나타났다. 권역별 특성을 나타내는 이와 같은 분석결과는 세계적인 식량위기의 원인을 찾고 그 해결방안을 모색하는 과정에서 상당한 중요성을 갖는다. 식량위기가 전 세계적인 현상으로 동시적으로 발생하는 경우에도, 생산요소의 탄력성이 권역별로 상이한 만큼 식량위기의 발생 원인도 권역별로 다를 수 있다는 것이다. 이에 따라식량위기의 해결방안 역시 권역의 특성에 따라 상이하게 적용되어야 할 것이며, 이는 식량위기에 대처하려는 국제기구와 각국의 정부가 반드시 고려해야 할 사항인 것으로 판단된다. 한편 식량생산의 규모수익이 개도국에서 크게 나타난다는 분석결과는 노동, 물적자본 및 인적자본과 경작면적 등 생산요소를 일정비율로 확충할 때에 식량생산은 그 비율 이상으로 크게 증가한다는 의미를 갖는다. 이는 식량생산 확대를 위한 국제적 협력의 과정에서 권역별 우선순위에 대한 정보를 제공하게 된다. 넷째, 강수량의 추정계수는 [사하라이남 아프리카]에서는 유의하게 나타났으며, 관개수로 확대, 저수지 확보 등을통한 물관리가 이 권역의 식량생산을 증가시키는 데에 상당한역할을 할 수 있음을 보여준다. 다른 권역에서는 강수량의 추정계수가 유의하지 않은 것으로 나타났는데, 이는 [사하라이남아프리카]를 제외한 대부분의 권역에는 이미 관개수로가 어느정도 발달해 있기 때문에 강수량의 변화가 식량생산에 미치는영향이 비교적 작기 때문인 것으로 풀이된다. 다섯째, 기온이생산에 미치는 영향은 권역별로 차이를 보였다. [남미 및 캐리비안], [사하라이남 아프리카]와 [남·동아시아 및 오세아니아]에서 유의하였으며, [북미 및 유럽]과 [중앙·서아시아 및북아프리카]에서는 유의하지 않았다. 특히 [남미 및 캐리비안],[사하라이남 아프리카]와 [남·동아시아 및 오세아니아]의 경우 추정계수 부호가 반대로 나타났는데, 이는 후자의 권역에서는 이미 관개수로가 어느 정도 정비되어 있어 기온이 높아지더라도 2기작 혹은 3기작을 통하여 쌀의 생산을 늘릴 수 있음을 반영하는 것으로 볼 수 있다. 이는 기온의 변화가 농업생산에 미치는 영향의 다양성을 보여주는 좋은 예라고 할 수있다. 즉, 각 권역의 식량생산은 재배작물의 재배방식과 관개시설 등 여러 가지 요인에 의하여 종합적으로 영향을 받기 때문에 기온변화의 영향만을 분리하여 식별하기가 쉽지 않다는것이다. 기존 문헌에 대한 본 연구의 기여는 다음과 같다. 첫째, Lee et al. (2012)에서 보이는 바와 같이 식량위기가 전 세계적인 규모로 발생할 수 있다는 점에 유의하여, 148개국을 망라하는 패널자료를 이용하여 관련문헌에서는 처음으로 세계적규모의 식량생산함수를 추정하였다. 둘째, 식량생산에 절대적영향을 미치는 기후적 요인을 고려하기 위해 강수량과 기온을 설명변수로 추가하여 식량생산함수를 추정하였다. 셋째, 기후및 생산되는 식량 등의 특성에 따라 대상국가들을 5개 권역으로 분류하여 권역별로 식량생산함수를 추정하였다. 본 연구의 한계점으로는 다음을 들 수 있다. 첫째, 기후요인 및 식량생산의 특성을 고려해 대상국가들을 권역으로 구분하여 분석하였으나, 주요 식량을 좀 더 세분하여 고려하지는 못하였다. 식량의 종류에 따라 요구되는 생산요소와 적합한 기후조건이 많이 다를 수 있으므로, 이를 더 세분하여 분석함으로써 더 유의한 분석결과를 얻을 수 있을 것으로 기대된다. 둘째, 본 연구에서는 식량생산과 설명변수들과의 관계를 선형함수로 상정하였으나, 이를 비선형함수로 확대한다면 기후변수 및 생산요소들이 식량생산에 미치는 영향을 더 다양하게파악할 수 있을 것이다. 셋째, 전 세계적으로 식량생산함수를추정하고자 하였으나 자료획득의 어려움으로 인해 일부 국가가 빠졌으며 불균형 패널자료를 사용할 수밖에 없었다. 특히 강수량 및 기온의 국가별 시계열 자료가 제한적이었던 점이 큰 영향을 미쳤으며, 따라서 본 연구의 분석기간도 1970 ~ 2000년으로 축소되었다. 향후 더 많은 국가로부터 더 장기간의 시계열 자료를 확보함으로써 더 흥미로운 연구결과를 얻을수 있을 것으로 생각된다. 위와 같은 한계점들을 보완함으로써 향후의 후속연구를 통해 관련연구의 지평을 더 넓힐 수 있기를 기대한다.

This study analyzes human development convergence and the impact of funds transfer to the regions using σ and β-convergence analysis method. Observations were made in all Indonesia’s provinces in the period 2010-2019. The coefficient of variation calculation shows a dispersion in the inequality of human development, which means that convergence occurred. This is also documented by the clustering analysis results developed in the study. The results are in line with the hypothesis of neoclassical theory, which shows the tendency for provinces with lower human development levels to grow relatively faster. The dynamic panel data approach with the GMM model shows that a model built with explanatory variables for transfer of funds to regions may lead to the process of convergence of human development – 2.21% per year or 31 years to cover the half-life of convergence. This is a consequence of the Special Allocation Fund and the Village Fund, which positively impact the convergence process, and the General Allocation Fund and the Revenue Sharing Fund with negative signs slowing the convergence process. This evidence opens opportunities to review the justification of the weighting component in determining the amount of funds transferred to the region to accelerate the convergence process of human development.

This paper examines how macroeconomic variables, such as interest rate differences, inflation, exchange rates, economic growth and external debt growth, affect capital flight in the ASEAN-8 countries. We apply a panel data model with fixed effect estimation for the data for eight countries from the period 1994 to 2018. We use the residual approach used by the World Bank to measure the value of capital flight. The results show that the interest rate differences, exchange rates, economic growth and foreign debt growth had a positive and significant effect on outward capital flight. A further implication of this finding is that the interest rate differences, exchange rate, economic growth and foreign debt growth are factors that trigger an increase in capital outflow in the ASEAN-8 countries. Nonetheless, inflation rate is not considered to be the main factor influencing capital flight, as average inflation in the ASEAN-8 countries remains relatively stable. This paper will be beneficial for policymakers in the ASEAN-8 countries and encourage them to constantly pay attention to these four variables, as they significantly influence capital flight, whereas they can disregard the impact of the inflation variable that is not significant in influencing capital flight.

This paper examines how human capital and other economic variables, such as private investment, economic growth, government investment, inflation, and unemployment influence inequality in Indonesia’s provinces. We apply panel data model with fixed effect estimation for the data of 34 provinces from the period 2013 to 2019. We develop a new index for human capital using the education index approach. The results show that human capital has a negative and significant effect on income inequality. An increase in human capital is related to an increase in knowledge and competence due to the longer average school year and expectations of the school year. Human capital has increased the possibility of a person being accepted into the job market and earning a higher income; hence, it lowers income inequality. We also find that inflation leads to a higher gap of income distribution. A further implication of this situation is that the rise in inflation causes an increase in low-income people, and as a consequence, makes their lives worse off. This paper will be beneficial for policy-makers for whom human capital, which is measured using an education index, is an important factor that significantly affects income inequality, in addition to other economic factors.

This study aims to investigate the main factors that affected the government health expenditures in Gulf Cooperation Council (GCC) countries (Kingdom of Saudi Arabia (KSA), United Arab Emirates (UAE), Oman, Qatar, Bahrain and Kuwait), during the period from 2005 to 2019. The study employs a panel data technique in order to monitor the pooled determinant variables of healthcare expenditures in these countries. The study’s results indicate, by using FMOLS approach for panel data, that the average healthcare expenditures per capita in GCC countries have a positive and a significant relationship with the government revenues, the size of the population, and the governments’ public debt. The positive and the significant relationships of governments’ public debt may be explained even if the governments of the GCC countries suffer from a budget deficit; the GCC countries continue to increase the healthcare expenditure. The study suggests that the policymakers of the GCC countries must take into consideration those variables when they develop their healthcare policies. Also, the GCC countries urgently need to have high levels of foreign exchange reserves to maintain the expected level of spending on the healthcare sector, because their public revenues depend mainly on the oil revenues, which are fluctuating continuously.

The paper aims to investigate the impact of foreign direct investment (FDI) on private investment with a sample having 49 developing countries in Asia (17 countries) and Africa (32 countries) during the period of 1990-2017. Unlike previous studies, we split the data into three groups for further analysis, including the Asian, African and the full-panel samples. The results confirm a crowding-in effect which shows that foreign direct investment promotes private investment on all three research samples. Besides, the lagged private investment has a positive and significant effect on itself in the next period which reflects the inertia in the trend of private investment in recipient countries. In the full-panel sample, there are some macro factors such as GDP per capita, trade openness, and electricity that also have a positive and statistically significant impact on private investment. Besides, when more deeply estimate with smaller samples, we find that trade openness and labour force have a positive and significant in Africa, on the other hand, not in Asia. However, the domestic credit variable has a negative and significant effect on private investment only in Asian developing countries. Furthermore, there is only a positive and significant impact of the electricity variable on private investment in Asia.

In this study, we examine the relationship between climate change and food productivity using empirical econometric methods. The existing literature shows that natural hazard caused by climate change has a negative impact on food productivity since the natural disaster devastates farmers and food supply. The conventional study however considered only the correlation between food productivity change and climate condition such as optimum air temperature rather than the association between food productivity and climate change. Agricultural area, crop per unit area and crop productivity are known as the most important factors in food productivity. Thus, we explore the relationship between the three factors and climate change. We analyze the carbon dioxide concentration level in the atmosphere as a proxy for the climate change since the level of carbon dioxide in the atmosphere affects global temperature. We found that agricultural area, crop per unit area and crop productivity are negatively associated with climate change.

Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements and using the Lagrange multipliers method, the fixed-effects model for the production of five types of food crop and the seven meteorological elements were analyzed. Results showed that the key factors effecting increases in production of rice grains were average temperature, average relative humidity and average ground surface temperature, while wheat and barley were found to have positive correlations with average temperature and average humidity. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the production of food crops. Second, when compared to existing studies, the study was not limited to one food crop but encompassed all five types, and went beyond other studies that were limited to temperature and rainfall to include various meterological elements.

본 연구는 패널자료(15개 시도의 20년간 자료)를 이용하여 홍수피해 비용과 복구비와의 상관관계에 대한 분석을 시도하였다. 패널 분석은 자료의 성격에 따라 고정효과모형 또는 확률효과모형을 사용하지만 본 분석은 두 모형을 함께 추정하였다. 예상대로 모든 변수들은 복구비와 정의 상관관계를 보였지만 사망자수와 이재민 수는 유의하지 않거나 오히려 음의 상관관계를 보이기도 하였다. 그리고 공공시설의 피해가 가장 중요한 인자였다. 무엇보다 중요한 것은 우리나라의