• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.1-16
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• 2023

Due to imbalances in supply and demand within the labor market, start-ups have emerged as crucial players in the generation of high-quality employment opportunities, particularly in stagnant job markets. In response to this trend, governments are allocating substantial financial and human resources to initiatives that support start-up development. This has led to an increasing rate of engagement in start-up ventures across diverse age groups, not limited to younger individuals. Start-ups are enterprises focused on the commercialization of innovative ideas with the aim of achieving profitability in the marketplace. Research concerning the successful market integration of new products and the attainment of sustainable growth is pivotal. Such research is instrumental not only for the success of start-ups but also for realizing the broader social functions and contributions that these enterprises can offer. Previous research has often examined new product market-entry strategies, often referred to as new product marketing, particularly for large companies and SMEs. However, there is a gap in studies focusing on prototype marketing strategies specific to start-ups. Thus, this study aims to examine the impact of Pre-announcing marketing strategies on the market attention garnered by start-ups with low recognition and limited infrastructure, and how such attention contributes to their sustainable growth. Specifically, the study aims to uncover the causal relationship between information attributes like relevance, vividness, and novelty in building customer relationships, and their impact on purchase intentions influenced by performance expectations and hedonic motivations. In terms of Pre-announcing information attributes, relevance, vividness, and novelty positively influence performance expectations and hedonic motivations as outlined in the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). These factors, in turn, positively impact the purchase intention for pre-announced new products from start-ups. These findings are expected to provide both theory and practical insights into the factors influencing market entry through the use of Pre-announcing marketing strategies for start-up new products.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.87-104
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• 2023

Recently, concerns are growing over small and medium-sized companies holding out on debt as domestic loan interest rates have risen sharply due to the prolonged impact of COVID-19 and soaring raw material prices. In addition, loans from small and medium-sized enterprises, which are difficult in the business environment, are increasingly being rejected due to high loan interest rates and excessive submission documents and financial statements-oriented screening of loans by the financial sector. Therefore, since it is necessary to discuss ways to promote financing and investment by SMEs, this study intends to suggest ways to promote investment through the use of SMEs' ESG systems. The purpose of this study is to suggest that the use of ESG evaluation indicators used as non-financial indicators helps predict the corporate value of SMEs and the importance of SMEs actively participating in ESG information disclosure. This study suggests the necessity of introducing and practicing ESG by SMEs where financing is important, and aims to analyze as an empirical result that the use of non-financial indicators helps predict corporate value. As a result of the study, the ESG performance and corporate value of SMEs showed a positive (+) relationship. It can be seen that both the grades and corporate value of SMEs by ESG sector have a positive (+) influence relationship. The total ESG rating was confirmed to have a positive effect on corporate value, and it was confirmed that SMEs with higher ESG environment, social, and governance ratings were evaluated higher. According to the research results, it is suggested that SMEs also need to use ESG evaluation indicators, and in order to promote the growth of SMEs, it is suggested that research on ways to re-examine the corporate value of SMEs is necessary. Therefore, this study suggests that the use of ESG should be actively recommended and implemented as a way to establish a management strategy for SMEs, and that efforts to disclose ESG information can soon help SMEs solve information asymmetry. In addition, SMEs want to understand the investment mechanism that the introduction and practice of ESG can lead to the improvement of the value of SMEs and suggest the necessity of SME-type ESG policies in the future.

• Information Systems Review
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• v.20 no.2
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• pp.39-62
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• 2018

Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.103-122
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• 2011

Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.

• (The) Research of the performance art and culture
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• no.38
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• pp.349-383
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• 2019

This discussion is focused on Donghaeanbyulsingut's 'gutchum-pan to pray'. 'Gutchum-pan to pray' is repeated in almost all of the geori in Byulsingut, so it is a crucial chum-pan that can never be disregarded in understanding Byulsingutchum. Meanwhile, it supposes that Donghaeanbyulsingut is grounded on the activity of producing 'praying (words) and dance (motions)' within its relationship with the structure of capitalistic society along with the context of traditional rituals. The motion that is newly generated as a response to the concrete expression of 'praying' conducted by a mudang (a shaman), that is, the expression coming from the inside associated with the praying is seen as gutchum. This dance is bound to be in competition and interest among shaman groups, and they tend to influence one another. If praying leads to dance, a mudang can gain profits from capital as well as the value of labor. When the mudang succeeds in forming a bigger bond of sympathy with her praying, the object of praying gets more eager to select byulbi and dances a heoteunchum (impromptu dance) more vigorously. This means that a mudang's ability to perform a ritual is associated with the object of praying's consumption. With his impromptu motions, the object of praying comes to go into 'the field of consumption' within the structure of capitalistic competition before he is aware of it. Behind the communication that praying leads to dance, a lot of things are associated with one another organically. 'Gutchum-pan to pray' is generated by the continuous movement of diversity and unity that the time has within the ritual of the mudang and the object of praying. It continues to create the future 'self' that is different from the present 'self', and it means that he expects variability from the present 'self' through 'gutchum-pan to pray'. The mudang also prays for him arranging the variability of the other (the object of praying) inside her labor. In a big picture, of course, the mudang expects the variability of herself, too, which is connected to the value of her labor. The variability that they expect forms a crucial axis that determines where the flow of time and space that the 'gutchum-pan to pray' has is directed to. The contents of praying are directly related with the villagers' lives, and what leads to dance is mostly related with their jobs. This implies that what the mudang experiences in her everyday consuming activity is directly associated with the villagers' activity for earning money. In other words, the contents of that praying change constantly according to the flow of capitalistic economy. Also, those striving to respond to it before anyone else also expect better life for them by substituting their self to the 'gutchum-pan to pray' eagerly. If so, who are the ones that generate 'gutchum-pan to pray'? This can be understood through relationship among mudangs, relationship between the mudang and villagers, and also relationship among villagers. Their relationships can never be free from the concepts like labor in capitalistic society, consumption and expenditure, or time; therefore, they come to compete with the other, the present self, or the better self within the diverse relationships. This gets to be expressed in any ways, words or motions. And the range that covers the creation of either group or individual 'gutchum-pan to pray' in the village is the village community. Outside the range, it is upsized to the competition of the village unit, so individual praying may become diminished more easily. Although mudangs pray in each geori, it does not mean all praying leads to dance. Within various relationships between mudangs and villagers, 'gutchum-pan to pray' comes to be generated, repeated, and extinct. As it is mitigated to more positive competition, it does not lead to gutchum any longer. In other words, repeating 'gutchum-pan to pray' previously created has turned the object of praying into the state different from the former. Also, the two groups both have experienced the last step of Byulsingut, and at that point, praying does no longer lead to dance. In other words, from the position of the shaman group, it is the finish of their labor time and ritual performance, and from the perspective of the villagers, it means the finish of consuming activity and participation in a ritual. The characteristics of 'gutchum-pan to pray' can be summarized as follows. First, it goes through the following process: competition in the village group → competition in the group → competition among individuals. Second, repeated praying does not lead to 'gutchum'. Third, in the cases of praying for each of the occupation groups, the mudang can induce a bond of sympathy from the objects of praying directly, and this lead to dance. Fourth, the group that fails in being included in the category of praying gets to be alienated from 'gutchum-pan to pray' repeatedly.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.191-204
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• 2015

According to the '2013 Performance Assessment Report on the Financial Program' from the National Assembly Budget Office, the unfilled recruitment ratio of Software(SW) Developers in South Korea was 25% in the 2012 fiscal year. Moreover, the unfilled recruitment ratio of highly-qualified SW developers reaches almost 80%. This phenomenon is intensified in small and medium enterprises consisting of less than 300 employees. Young job-seekers in South Korea are increasingly avoiding becoming a SW developer and even the current SW developers want to change careers, which hinders the national development of IT industries. The Korean government has recently realized the problem and implemented policies to foster young SW developers. Due to this effort, it has become easier to find young SW developers at the beginning-level. However, it is still hard to recruit highly-qualified SW developers for many IT companies. This is because in order to become a SW developing expert, having a long term experiences are important. Thus, improving job continuity intentions of current SW developers is more important than fostering new SW developers. Therefore, this study surveyed the job continuity intentions of SW developers and analyzed the factors associated with them. As a method, we carried out a survey from September 2014 to October 2014, which was targeted on 130 SW developers who were working in IT industries in South Korea. We gathered the demographic information and characteristics of the respondents, work environments of a SW industry, and social positions for SW developers. Afterward, a regression analysis and a decision tree method were performed to analyze the data. These two methods are widely used data mining techniques, which have explanation ability and are mutually complementary. We first performed a linear regression method to find the important factors assaociated with a job continuity intension of SW developers. The result showed that an 'expected age' to work as a SW developer were the most significant factor associated with the job continuity intention. We supposed that the major cause of this phenomenon is the structural problem of IT industries in South Korea, which requires SW developers to change the work field from developing area to management as they are promoted. Also, a 'motivation' to become a SW developer and a 'personality (introverted tendency)' of a SW developer are highly importantly factors associated with the job continuity intention. Next, the decision tree method was performed to extract the characteristics of highly motivated developers and the low motivated ones. We used well-known C4.5 algorithm for decision tree analysis. The results showed that 'motivation', 'personality', and 'expected age' were also important factors influencing the job continuity intentions, which was similar to the results of the regression analysis. In addition to that, the 'ability to learn' new technology was a crucial factor for the decision rules of job continuity. In other words, a person with high ability to learn new technology tends to work as a SW developer for a longer period of time. The decision rule also showed that a 'social position' of SW developers and a 'prospect' of SW industry were minor factors influencing job continuity intensions. On the other hand, 'type of an employment (regular position/ non-regular position)' and 'type of company (ordering company/ service providing company)' did not affect the job continuity intension in both methods. In this research, we demonstrated the job continuity intentions of SW developers, who were actually working at IT companies in South Korea, and we analyzed the factors associated with them. These results can be used for human resource management in many IT companies when recruiting or fostering highly-qualified SW experts. It can also help to build SW developer fostering policy and to solve the problem of unfilled recruitment of SW Developers in South Korea.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Journal of Distribution Research
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• v.17 no.1
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• pp.37-63
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• 2012

In franchise business, exclusive sales territory (sometimes EST in table) protection is a very important issue from an economic, social and political point of view. It affects the growth and survival of both franchisor and franchisee and often raises issues of social and political conflicts. When franchisee is not familiar with related laws and regulations, franchisor has high chance to utilize it. Exclusive sales territory protection by the manufacturer and distributors (wholesalers or retailers) means sales area restriction by which only certain distributors have right to sell products or services. The distributor, who has been granted exclusive sales territories, can protect its own territory, whereas he may be prohibited from entering in other regions. Even though exclusive sales territory is a quite critical problem in franchise business, there is not much rigorous research about the reason, results, evaluation, and future direction based on empirical data. This paper tries to address this problem not only from logical and nomological validity, but from empirical validation. While we purse an empirical analysis, we take into account the difficulties of real data collection and statistical analysis techniques. We use a set of disclosure document data collected by Korea Fair Trade Commission, instead of conventional survey method which is usually criticized for its measurement error. Existing theories about exclusive sales territory can be summarized into two groups as shown in the table below. The first one is about the effectiveness of exclusive sales territory from both franchisor and franchisee point of view. In fact, output of exclusive sales territory can be positive for franchisors but negative for franchisees. Also, it can be positive in terms of sales but negative in terms of profit. Therefore, variables and viewpoints should be set properly. The other one is about the motive or reason why exclusive sales territory is protected. The reasons can be classified into four groups - industry characteristics, franchise systems characteristics, capability to maintain exclusive sales territory, and strategic decision. Within four groups of reasons, there are more specific variables and theories as below. Based on these theories, we develop nine hypotheses which are briefly shown in the last table below with the results. In order to validate the hypothesis, data is collected from government (FTC) homepage which is open source. The sample consists of 1,896 franchisors and it contains about three year operation data, from 2006 to 2008. Within the samples, 627 have exclusive sales territory protection policy and the one with exclusive sales territory policy is not evenly distributed over 19 representative industries. Additional data are also collected from another government agency homepage, like Statistics Korea. Also, we combine data from various secondary sources to create meaningful variables as shown in the table below. All variables are dichotomized by mean or median split if they are not inherently dichotomized by its definition, since each hypothesis is composed by multiple variables and there is no solid statistical technique to incorporate all these conditions to test the hypotheses. This paper uses a simple chi-square test because hypotheses and theories are built upon quite specific conditions such as industry type, economic condition, company history and various strategic purposes. It is almost impossible to find all those samples to satisfy them and it can't be manipulated in experimental settings. However, more advanced statistical techniques are very good on clean data without exogenous variables, but not good with real complex data. The chi-square test is applied in a way that samples are grouped into four with two criteria, whether they use exclusive sales territory protection or not, and whether they satisfy conditions of each hypothesis. So the proportion of sample franchisors which satisfy conditions and protect exclusive sales territory, does significantly exceed the proportion of samples that satisfy condition and do not protect. In fact, chi-square test is equivalent with the Poisson regression which allows more flexible application. As results, only three hypotheses are accepted. When attitude toward the risk is high so loyalty fee is determined according to sales performance, EST protection makes poor results as expected. And when franchisor protects EST in order to recruit franchisee easily, EST protection makes better results. Also, when EST protection is to improve the efficiency of franchise system as a whole, it shows better performances. High efficiency is achieved as EST prohibits the free riding of franchisee who exploits other's marketing efforts, and it encourages proper investments and distributes franchisee into multiple regions evenly. Other hypotheses are not supported in the results of significance testing. Exclusive sales territory should be protected from proper motives and administered for mutual benefits. Legal restrictions driven by the government agency like FTC could be misused and cause mis-understandings. So there need more careful monitoring on real practices and more rigorous studies by both academicians and practitioners.

• Journal of Distribution Research
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• v.17 no.1
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• pp.1-36
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• 2012

Service failure is one of the major reasons for customer defection. As the business environment gets tougher and more competitive, a single service failure might bring about fatal consequences to a service provider or a firm. Sometimes a failure won't end up with an unsatisfied customer's simple complaining but with a wide-spread animosity against the service provider or the firm, leading to a threat to the firm's survival itself in the society. Therefore, we are in need of comprehensive understandings of complainants' attitudes and behaviors toward service failures and firm's recovery efforts. Even though a failure itself couldn't be fixed completely, marketers should repair the mind and heart of unsatisfied customers, which can be regarded as an successful recovery strategy in the end. As the outcome of recovery efforts exerted by service providers or firms, recovery of the relationship between customer and service provider need to put on the top in the recovery goal list. With these motivations, the study investigates how service failure and recovery makes the changes in dynamics of fundamental elements of customer-firm relationship, such as customer affection, customer trust and loyalty intention by comparing two time points, before the service failure and after the recovery, focusing on the effects of recovery satisfaction and the failure severity. We adopted La & Choi (2012)'s framework for development of the research model that was based on the previous research stream like Yim et al. (2008) and Thomson et al. (2005). The pivotal background theories of the model are mainly from relationship marketing and social relationships of social psychology. For example, Love, Emotional attachment, Intimacy, and Equity theories regarding human relationships were reviewed. As the results, when recovery satisfaction is high, customer affection and customer trust that were established before the service failure are carried over to the future after the recovery. However, when recovery satisfaction is low, customer-firm relationship that had already established in the past are not carried over but broken up. Regardless of the degree of recovery satisfaction, once a failure occurs loyalty intention is not carried over to the future and the impact of customer trust on loyalty intention becomes stronger. Such changes imply that customers become more prudent and more risk-aversive than the time prior to service failure. The impact of severity of failure on customer affection and customer trust matters only when recovery satisfaction is low. When recovery satisfaction is high, customer affection and customer trust become severity-proof. Interestingly, regardless of the degree of recovery satisfaction, failure severity has a significant negative influence on loyalty intention. Loyalty intention is the most fragile target when a service failure occurs no matter how severe the failure criticality is. Consequently, the ultimate goal of service recovery should be the restoration of customer-firm relationship and recovery of customer trust should be the primary objective to accomplish for a successful recovery performance. Especially when failure severity is high, service recovery should be perceived highly satisfied by the complainants because failure severity matters more when recovery satisfaction is low. Marketers can implement recovery strategies to enhance emotional appeals as well as fair treatments since the both impacts of affection and trust on loyalty intention are significant. In the case of high severity of failure, recovery efforts should be exerted to overreach customer expectation, designed to directly repair customer trust and elaborately designed in the focus of customer-firm communications during the interactional recovery process to affect customer trust rebuilding indirectly. Because it is a longer and harder way to rebuild customer-firm relationship for high severity cases, low recovery satisfaction cannot guarantee customer retention. To prevent customer defection due to service failure of high severity, unexpected rewards as a recovery will be likely to be useful since those will lead to customer delight or customer gratitude toward the service firm. Based on the results of analyses, theoretical and managerial implications are presented. Limitations and future research ideas are also discussed.