A Conceptual Review of the Transaction Costs within a Distribution Channel (유통경로내의 거래비용에 대한 개념적 고찰)
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- Journal of Distribution Science
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- v.10 no.2
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- pp.29-41
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- 2012
This paper undertakes a conceptual review of transaction cost to broaden the understanding of the transaction cost analysis (TCA) approach. More than 40 years have passed since Coase's fundamental insight that transaction, coordination, and contracting costs must be considered explicitly in explaining the extent of vertical integration. Coase (1937) forced economists to identify previously neglected constraints on the trading process to foster efficient intrafirm, rather than interfirm, transactions. The transaction cost approach to economic organization study regards transactions as the basic units of analysis and holds that understanding transaction cost economy is central to organizational study. The approach applies to determining efficient boundaries, as between firms and markets, and to internal transaction organization, including employment relations design. TCA, developed principally by Oliver Williamson (1975,1979,1981a) blends institutional economics, organizational theory, and contract law. Further progress in transaction costs research awaits the identification of critical dimensions in which transaction costs differ and an examination of the economizing properties of alternative institutional modes for organizing transactions. The crucial investment distinction is: To what degree are transaction-specific (non-marketable) expenses incurred? Unspecialized items pose few hazards, since buyers can turn toalternative sources, and suppliers can sell output intended for one order to other buyers. Non-marketability problems arise when specific parties' identities have important cost-bearing consequences. Transactions of this kind are labeled idiosyncratic. The summarized results of the review are as follows. First, firms' distribution decisions often prompt examination of the make-or-buy question: Should a marketing activity be performed within the organization by company employees or contracted to an external agent? Second, manufacturers introducing an industrial product to a foreign market face a difficult decision. Should the product be marketed primarily by captive agents (the company sales force and distribution division) or independent intermediaries (outside sales agents and distribution)? Third, the authors develop a theoretical extension to the basic transaction cost model by combining insights from various theories with the TCA approach. Fourth, other such extensions are likely required for the general model to be applied to different channel situations. It is naive to assume the basic model appliesacross markedly different channel contexts without modifications and extensions. Although this study contributes to scholastic research, it is limited by several factors. First, the theoretical perspective of TCA has attracted considerable recent interest in the area of marketing channels. The analysis aims to match the properties of efficient governance structures with the attributes of the transaction. Second, empirical evidence about TCA's basic propositions is sketchy. Apart from Anderson's (1985) study of the vertical integration of the selling function and John's (1984) study of opportunism by franchised dealers, virtually no marketing studies involving the constructs implicated in the analysis have been reported. We hope, therefore, that further research will clarify distinctions between the different aspects of specific assets. Another important line of future research is the integration of efficiency-oriented TCA with organizational approaches that emphasize specific assets' conceptual definition and industry structure. Finally, research of transaction costs, uncertainty, opportunism, and switching costs is critical to future study.
The anthropomorphism of brands, defined as seeing human beings in brands (Puzakova, Kwak, and Rosereto, 2008) is the focus of this study. Specifically, the research objective is to understand the ways in which brands are rendered humanlike. By analyzing consumer readings of stories found on food product packages we intend to show how marketers and consumers humanize a spectrum of brands and create meanings. Our research question considers the possibility that a single brand may host multiple or single meanings, associations, and personalities for different consumers. We start by highlighting the theoretical and practical significance of our research, explain why we turn our attention to packages as vehicles of brand meaning transfer, then describe our qualitative methodology, discuss findings, and conclude with a discussion of managerial implications and directions for future studies. The study was designed to directly expose consumers to potential vehicles of brand meaning transfer and then engage these consumers in free verbal reflections on their perceived meanings. Specifically, we asked participants to read non-nutritional stories on selected branded food packages, in order to elicit data about received meanings. Packaging has yet to receive due attention in consumer research (Hine, 1995). Until now, attention has focused solely on its utilitarian function and has generated a body of research that has explored the impact of nutritional information and claims on consumer perceptions of products (e.g., Loureiro, McCluskey and Mittelhammer, 2002; Mazis and Raymond, 1997; Nayga, Lipinski and Savur, 1998; Wansik, 2003). An exception is a recent study that turns its attention to non-nutritional packaging narratives and treats them as cultural productions and vehicles for mythologizing the brand (Kniazeva and Belk, 2007). The next step in this stream of research is to explore how such mythologizing activity affects brand personality perception and how these perceptions relate to consumers. These are the questions that our study aimed to address. We used in-depth interviews to help overcome the limitations of quantitative studies. Our convenience sample was formed with the objective of providing demographic and psychographic diversity in order to elicit variations in consumer reflections to food packaging stories. Our informants represent middle-class residents of the US and do not exhibit extreme alternative lifestyles described by Thompson as "cultural creatives" (2004). Nine people were individually interviewed on their food consumption preferences and behavior. Participants were asked to have a look at the twelve displayed food product packages and read all the textual information on the package, after which we continued with questions that focused on the consumer interpretations of the reading material (Scott and Batra, 2003). On average, each participant reflected on 4-5 packages. Our in-depth interviews lasted one to one and a half hours each. The interviews were tape recorded and transcribed, providing 140 pages of text. The products came from local grocery stores on the West Coast of the US and represented a basic range of food product categories, including snacks, canned foods, cereals, baby foods, and tea. The data were analyzed using procedures for developing grounded theory delineated by Strauss and Corbin (1998). As a result, our study does not support the notion of one brand/one personality as assumed by prior work. Thus, we reveal multiple brand personalities peacefully cohabiting in the same brand as seen by different consumers, despite marketer attempts to create more singular brand personalities. We extend Fournier's (1998) proposition, that one's life projects shape the intensity and nature of brand relationships. We find that these life projects also affect perceived brand personifications and meanings. While Fournier provides a conceptual framework that links together consumers’ life themes (Mick and Buhl, 1992) and relational roles assigned to anthropomorphized brands, we find that consumer life projects mold both the ways in which brands are rendered humanlike and the ways in which brands connect to consumers' existential concerns. We find two modes through which brands are anthropomorphized by our participants. First, brand personalities are created by seeing them through perceived demographic, psychographic, and social characteristics that are to some degree shared by consumers. Second, brands in our study further relate to consumers' existential concerns by either being blended with consumer personalities in order to connect to them (the brand as a friend, a family member, a next door neighbor) or by distancing themselves from the brand personalities and estranging them (the brand as a used car salesman, a "bunch of executives.") By focusing on food product packages, we illuminate a very specific, widely-used, but little-researched vehicle of marketing communication: brand storytelling. Recent work that has approached packages as mythmakers, finds it increasingly challenging for marketers to produce textual stories that link the personalities of products to the personalities of those consuming them, and suggests that "a multiplicity of building material for creating desired consumer myths is what a postmodern consumer arguably needs" (Kniazeva and Belk, 2007). Used as vehicles for storytelling, food packages can exploit both rational and emotional approaches, offering consumers either a "lecture" or "drama" (Randazzo, 2006), myths (Kniazeva and Belk, 2007; Holt, 2004; Thompson, 2004), or meanings (McCracken, 2005) as necessary building blocks for anthropomorphizing their brands. The craft of giving birth to brand personalities is in the hands of writers/marketers and in the minds of readers/consumers who individually and sometimes idiosyncratically put a meaningful human face on a brand.
This study focused on digital music, which is the most valuable cultural asset in the modern society and occupies a particularly important position in the flow of the Korean Wave. Digital music was collected based on the "Gaon Chart," a well-established music chart in Korea. Through this, the changes in the ranking of the music that entered the chart for 73 weeks were collected. Afterwards, patterns with similar characteristics were derived through time series cluster analysis. Then, a descriptive analysis was performed on the notable features of each pattern. The research process suggested by this study is as follows. First, in the data collection process, time series data was collected to check the ranking change of digital music. Subsequently, in the data processing stage, the collected data was matched with the rankings over time, and the music title and artist name were processed. Each analysis is then sequentially performed in two stages consisting of exploratory analysis and explanatory analysis. First, the data collection period was limited to the period before 'the music bulk buying phenomenon', a reliability issue related to music ranking in Korea. Specifically, it is 73 weeks starting from December 31, 2017 to January 06, 2018 as the first week, and from May 19, 2019 to May 25, 2019. And the analysis targets were limited to digital music released in Korea. In particular, digital music was collected based on the "Gaon Chart", a well-known music chart in Korea. Unlike private music charts that are being serviced in Korea, Gaon Charts are charts approved by government agencies and have basic reliability. Therefore, it can be considered that it has more public confidence than the ranking information provided by other services. The contents of the collected data are as follows. Data on the period and ranking, the name of the music, the name of the artist, the name of the album, the Gaon index, the production company, and the distribution company were collected for the music that entered the top 100 on the music chart within the collection period. Through data collection, 7,300 music, which were included in the top 100 on the music chart, were identified for a total of 73 weeks. On the other hand, in the case of digital music, since the cases included in the music chart for more than two weeks are frequent, the duplication of music is removed through the pre-processing process. For duplicate music, the number and location of the duplicated music were checked through the duplicate check function, and then deleted to form data for analysis. Through this, a list of 742 unique music for analysis among the 7,300-music data in advance was secured. A total of 742 songs were secured through previous data collection and pre-processing. In addition, a total of 16 patterns were derived through time series cluster analysis on the ranking change. Based on the patterns derived after that, two representative patterns were identified: 'Steady Seller' and 'One-Hit Wonder'. Furthermore, the two patterns were subdivided into five patterns in consideration of the survival period of the music and the music ranking. The important characteristics of each pattern are as follows. First, the artist's superstar effect and bandwagon effect were strong in the one-hit wonder-type pattern. Therefore, when consumers choose a digital music, they are strongly influenced by the superstar effect and the bandwagon effect. Second, through the Steady Seller pattern, we confirmed the music that have been chosen by consumers for a very long time. In addition, we checked the patterns of the most selected music through consumer needs. Contrary to popular belief, the steady seller: mid-term pattern, not the one-hit wonder pattern, received the most choices from consumers. Particularly noteworthy is that the 'Climbing the Chart' phenomenon, which is contrary to the existing pattern, was confirmed through the steady-seller pattern. This study focuses on the change in the ranking of music over time, a field that has been relatively alienated centering on digital music. In addition, a new approach to music research was attempted by subdividing the pattern of ranking change rather than predicting the success and ranking of music.
People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.
Introduction As consumers' purchase behavior change into a rational and practical direction, the discount store industry came to have keen competition along with rapid external growth. Therefore as a solution, distribution businesses are concentrating on developing PB(Private Brand) which can realize differentiation and profitability at the same time. And as improvement in customer loyalty beyond customer satisfaction is effective in surviving in an environment with keen competition, PB is being used as a strategic tool to improve customer loyalty. To improve loyalty among PB users, it is necessary to develop PB by examining properties of a customer group, first of all, quality level perceived by consumers should be met to obtain customer satisfaction and customer trust and consequently induce customer loyalty. To provide results of systematic analysis on relations between antecedents influenced perceived quality and variables affecting customer loyalty, this study proposed a research model based on causal relations verified in prior researches and set 16 hypotheses about relations among 9 theoretical variables. Data was collected from 400 adult customers residing in Seoul and the Metropolitan area and using large scale discount stores, among them, 375 copies were analyzed using SPSS 15.0 and Amos 7.0. The findings of the present study followed as; We ascertained that the higher company reputation, brand reputation, product experience and brand familiarity, the higher perceived quality. The study also examined the higher perceived quality, the higher customer satisfaction, customer trust and customer loyalty. The findings showed that the higher customer satisfaction and customer trust, the higher customer loyalty. As for moderating effects between PB and NB in terms of influences of perceived quality factors on perceived quality, we can ascertain that PB was higher than NB in the influences of company reputation on perceived quality while NB was higher than PB in the influences of brand reputation and brand familiarity on perceived quality. These results of empirical analysis will be useful for those concerned to do marketing activities based on a clearer understanding of antecedents and consecutive factors influenced perceived quality. At last, discussions about academical and managerial implications in these results, we suggested the limitations of this study and the future research directions. Research Model and Hypotheses Test After analyzing if antecedent variables having influence on perceived quality shows any difference between PB and NB in terms of their influences on them, the relation between variables that have influence on customer loyalty was determined as Figure 1. We established 16 hypotheses to test and hypotheses are as follows; H1-1: Perceived price has a positive effect on perceived quality. H1-2: It is expected that PB and NB would have different influence in terms of perceived price on perceived quality. H2-1: Company reputation has a positive effect on perceived quality. H2-2: It is expected that PB and NB would have different influence in terms of company reputation on perceived quality. H3-1: Brand reputation has a positive effect on perceived quality. H3-2: It is expected that PB and NB would have different influence in terms of brand reputation on perceived quality. H4-1: Product experience has a positive effect on perceived quality. H4-2: It is expected that PB and NB would have different influence in terms of product experience on perceived quality. H5-1: Brand familiarity has a positive effect on perceived quality. H5-2: It is expected that PB and NB would have different influence in terms of brand familiarity on perceived quality. H6: Perceived quality has a positive effect on customer satisfaction. H7: Perceived quality has a positive effect on customer trust. H8: Perceived quality has a positive effect on customer loyalty. H9: Customer satisfaction has a positive effect on customer trust. H10: Customer satisfaction has a positive effect on customer loyalty. H11: Customer trust has a positive effect on customer loyalty. Results from analyzing main effects of research model is shown as