• Asia Marketing Journal
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• v.11 no.1
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• pp.39-72
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• 2009

With the growing importance of accountability, it is getting necessary to test the impact of marketing expenditure on marketing performance. Including recent ROM, we can find a few researches about marketing accountability. But there are a few problems about definitions and metric of marketing expenditure and marketing performance. Therefore, by defining and analyzing the impact of marketing expenditure on marketing performance, we are going to set the classification scheme of marketing expenditure and marketing performance. Based on research findings, new definitions and metrics are proposed as follows. First, we suggest the classification scheme of marketing expenditure. Marketing expenditure is defined as expense accounts in the balance sheet for doing marketing tasks. Marketing expenditures includes many accounts, for example, marketing research, advertising, sales promotion, foreign market development, physical distribution, after services. Among these marketing investment, advertising expenses have a positive effect on marketing performance. Second, we suggest the classification scheme of marketing performance. Already, marketing performance has been defined as financial metrics, customer metrics, market metrics, and corporate social responsibility. But, in this study, we find that the process model is not relevant for explaining association between the performance metrics. The process model is a virtuous cycle: "customer metrics→market metrics→financial metrics→firm valuation metrics." But, in this study, it is not supported or a little significant association between these metrics. Based on these results, we suggest the balance model or flower model as the classification scheme of marketing performance.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.365-370
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• 2023

Royalty contributed to the development of the non-fungible token (NFT) ecosystem as a reward system that pays a portion of the sales to the creator whenever transactions occur. This study quantitatively analyzes the impact of the abolition of royalties, which is being expanded by some NFT marketplaces, on the NFT market, and qualitatively analyzes the results of the impact. The analysis results are as follows. First, the number of NFT mints is decreasing by causing creators to leave the NFT market and reducing new entry. Second, major NFT projects have refused to trade with marketplaces that have abolished royalties, leading to a decrease in the number of transactions. Third, the abolition of royalties has undermined the motivation of NFT creators to continue to develop their projects, leading to a drop in NFT floor prices. This study is expected to contribute to reducing the current negative impact in the short term by suggesting how the NFT community provides incentives to owners who voluntarily pay royalties independently of the policy of the NFT marketplace. In addition, it suggests that in the long run, fundamental solutions to the problem of abolishing royalties require improvements in technology related to royalty payments, cooperation between NFT marketplaces and NFT creators, and institutional support related to royalties.

• Journal of Digital Convergence
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• v.22 no.2
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• pp.1-9
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• 2024

The purpose of this study is to verify whether companies residing in industry-academic convergence zones designated by the government are achieving policy goals and to seek policy implications and directions for improvement through analysis. For the study, business activities targeting resident companies were divided into infrastructure, business content, management, and system aspects, and business performance indicators, resident company satisfaction surveys, and differences in sales increase between resident companies and non-resident companies were analyzed through t-test. Based on statistical analysis results, performance indicators, and corporate survey analysis results, we track joint industry-academia R&D projects to maximize the effectiveness for companies, develop and operate human resources management for teams, and provide financial support for ordinances of metropolitan local governments. Improvements such as stipulation, antenna facilities at the corporate research center, and improvement of the researcher's residential environment were suggested. This study is the first to quantitatively verify policy performance targeting companies residing in industry-academic convergence zones, a large-scale government project, and future follow-up research is needed, including analysis of policy effects based on various variables such as employment indicators and corporate financial indicators.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.4
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• pp.258-265
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• 2024

Purpose: To date, there is no region-specific guideline for pediatric endoscopy training. This study aimed to illustrate the current status of pediatric endoscopy training in Asia-Pacific region and identify opportunities for improvement. Methods: A cross-sectional survey, using a standardized electronic questionnaire, was conducted among medical schools in the Asia-Pacific region in January 2024. Results: A total of 57 medical centers in 12 countries offering formal Pediatric Gastroenterology training programs participated in this regional survey. More than 75% of the centers had an average case load of <10 cases per week for both diagnostic and therapeutic endoscopies. Only 36% of the study programs employed competency-based outcomes for program development, whereas nearly half (48%) used volume-based curricula. Foreign body retrieval, polypectomy, percutaneous endoscopic gastrostomy, and esophageal variceal hemostasis, that is, sclerotherapy or band ligation (endoscopic variceal sclerotherapy and endoscopic variceal ligation), comprised the top four priorities that the trainees should acquire in the autonomous stage (unconscious) of competence. Regarding the learning environment, only 31.5% provided formal hands-on workshops/simulation training. The direct observation of procedural skills was the most commonly used assessment method. The application of a quality assurance (QA) system in both educational and patient care (Pediatric Endoscopy Quality Improvement Network) aspects was present in only 28% and 17% of the centers, respectively. Conclusion: Compared with Western academic societies, the limited availability of cases remains a major concern. To close this gap, simulation and adult endoscopy training are essential. The implementation of reliable and valid assessment tools and QA systems can lead to significant development in future programs.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.139-160
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• 2017

Technology commercialization creates effective economic value by linking the company's R & D processes and outputs to the market. This technology commercialization is important in that a company can retain and maintain a sustained competitive advantage. In order for a specific technology to be commercialized, it goes through the stage of technical planning, technology research and development, and commercialization. This process involves a lot of time and money. Therefore, the duration and cost of technology commercialization are important decision information for determining the market entry strategy. In addition, it is more important information for a technology investor to rationally evaluate the technology value. In this way, it is very important to scientifically estimate the duration and cost of the technology commercialization. However, research on technology commercialization is insufficient and related methodology are lacking. In this study, we propose an evaluation model that can estimate the duration and cost of R & D technology commercialization for small and medium-sized enterprises. To accomplish this, this study collected the public data of the National Science & Technology Information Service (NTIS) and the survey data provided by the Small and Medium Business Administration. Also this study will develop the estimation model of commercialization duration and cost of R&D performance on using these data based on the market approach, one of the technology valuation methods. Specifically, this study defined the process of commercialization as consisting of development planning, development progress, and commercialization. We collected the data from the NTIS database and the survey of SMEs technical statistics of the Small and Medium Business Administration. We derived the key variables such as stage-wise R&D costs and duration, the factors of the technology itself, the factors of the technology development, and the environmental factors. At first, given data, we estimates the costs and duration in each technology readiness level (basic research, applied research, development research, prototype production, commercialization), for each industry classification. Then, we developed and verified the research model of each industry classification. The results of this study can be summarized as follows. Firstly, it is reflected in the technology valuation model and can be used to estimate the objective economic value of technology. The duration and the cost from the technology development stage to the commercialization stage is a critical factor that has a great influence on the amount of money to discount the future sales from the technology. The results of this study can contribute to more reliable technology valuation because it estimates the commercialization duration and cost scientifically based on past data. Secondly, we have verified models of various fields such as statistical model and data mining model. The statistical model helps us to find the important factors to estimate the duration and cost of technology Commercialization, and the data mining model gives us the rules or algorithms to be applied to an advanced technology valuation system. Finally, this study reaffirms the importance of commercialization costs and durations, which has not been actively studied in previous studies. The results confirm the significant factors to affect the commercialization costs and duration, furthermore the factors are different depending on industry classification. Practically, the results of this study can be reflected in the technology valuation system, which can be provided by national research institutes and R & D staff to provide sophisticated technology valuation. The relevant logic or algorithm of the research result can be implemented independently so that it can be directly reflected in the system, so researchers can use it practically immediately. In conclusion, the results of this study can be a great contribution not only to the theoretical contributions but also to the practical ones.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.16-28
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• 2016

The study was conducted to compare and analyze the importance and performance of leisure destination selection attributes of persons who use recreational forests and rural tourism villages. This researcher investigated the use patterns of users to identify the ground for connection between recreational forest and rural tourism village, analyzed their recognition differences in physical selection attribute, program selection attribute, and service selection attribute in order for leisure destination selection, and conducted importance-performance analysis(IPA analysis) to draw a plan for connection. The main results and suggestions are presented as follows. First, recreational forests were visited by family users in order for rest and emotional cultivation and provided experience programs using simple public interest function of forest, whereas rural tourism villages were visited by family users, friends and co-workers, groups and club members to experience a variety of annual programs and understand regional cultures. It was found that it was necessary to connect natural forest with rural tourism village in order to meet the leisure needs of the people changed in diversified ways. Secondly, it was found that the connection between rural tourism village and recreational forest visited mainly for simple rest led to positive visit intention of users. It was expected that there will be various kinds of uses, including experience program participation, child education, and safe accommodations security. In other words, the connection between recreational forest and rural tourism village is an alternative to trigger actual demands and recreational forest activities with high quality. Thirdly, in the case of users of recreational forests, their performance of all selection attributes was lower than their importance of them. Therefore, overall improvements were needed. In particular, needed were the diversity, benefit, and promotion of programs, improvements in locality(themes), supply of lodges and convenient facilities, booking system, the purchase system of local special products, and professional skills of operators and managers. On contrary, the performance of program selection attribute of rural tourism village was high. Therefore, it was found that program attribute of rural tourism village was the main connection factor to activate recreational forest use. Fourthly, according to IPA analysis, the proper connections between loges, convenient facilities, and nearby touristattractions, which give high expectations and satisfaction to users, needed to remain. And it was required to make common efforts to accomplish the goal (income creation) of rural tourism village and improve booking system for visitors and performance of local special products sales opportunity. In addition, the essential factors to induce users' leisure destination selection were found to be maintenance of the use fee system of recreational forest, diversity of rural tourism village program, and retention of locality.

• Asia pacific journal of information systems
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• v.24 no.1
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• pp.31-50
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• 2014

The ubiquitous accessibility of information through mobile devices has led to an increased mobility of workers from their fixed workplaces. Market researchers estimate that by 2016, 350 million workers will be using their smartphones for business purposes, and the use of smartphones will offer new business benefits. Enterprises are now adopting mobile technologies for numerous applications to increase their operational efficiency, improve their responsiveness and competitiveness, and cultivate their innovativeness. For these reasons, various organizational aspects concerning "mobile work" have received a great deal of recent attention. Moreover, many CIOs plan to allocate a considerable amount of their budgets mobile work environments. In particular, with the consumerization of information technology, enterprise mobile applications (EMA) have played a significant role in the explosive growth of mobile computing in the workplace, and even in improving sales for firms in this field. EMA can be defined as mobile technologies and role-based applications, as companies design them for specific roles and functions in organizations. Technically, EMA can be defined as business enterprise systems, including critical business functions that enable users to access enterprise systems via wireless mobile devices, such as smartphones or tablets. Specifically, EMA enables employees to have greater access to real-time information, and provides them with simple features and functionalities that are easy for them to complete specific tasks. While the impact of EMA on organizational workers' productivity has been given considerable attention in various literatures, relatively little research effort has been made to examine how EMA actually lead to users' job performance. In particular, we have a limited understanding of what the key antecedents are of such an EMA usage outcome. In this paper, we focus on employees' perceived job performance as the outcome of EMA use, which indicates the successful role of EMA with regard to employees' tasks. Thus, to develop a deeper understanding of the relationship among EMA, its environment, and employees' perceived job performance, we develop a comprehensive model that considers the perceived-fit between EMA and employees' tasks, satisfaction on EMA, and the organizational environment. With this model, we try to examine EMA to explain how job performance through EMA is revealed from both the task-technology fit for EMA and satisfaction on EMA, while also considering the antecedent factors for these constructs. The objectives of this study are to address the following research questions: (1) How can employees successfully manage EMA in order to enhance their perceived job performance? (2) What internal and/or external factors are important antecedents in increasing EMA users' satisfaction on MES and task-technology fit for EMA? (3) What are the impacts of organizational (e.g. organizational agility), and task-related antecedents (e.g., task mobility) on task-technology fit for EMA? (4) What are the impacts of internal (e.g., self-efficacy) and external antecedents (e.g., system reputation) for the habitual use of EMA? Based on a survey from 254 actual employees who use EMA in their workplace across industries, our results indicate that task-technology fit for EMA and satisfaction on EMA are positively associated with job performance. We also identify task mobility, organizational agility, and system accessibility that are found to be positively associated with task-technology fit for EMA. Further, we find that external factor, such as the reputation of EMA, and internal factor, such as self-efficacy for EMA that are found to be positively associated with the satisfaction of EMA. The present findings enable researchers and practitioners to understand the role of EMA, which facilitates organizational workers' efficient work processes, as well as the importance of task-technology fit for EMA. Our model provides a new set of antecedents and consequence variables for a TAM involving mobile applications. The research model also provides empirical evidence that EMA are important mobile services that positively influence individuals' performance. Our findings suggest that perceived organizational agility and task mobility do have a significant influence on task-technology fit for EMA usage through positive beliefs about EMA, that self-efficacy and system reputation can also influence individuals' satisfaction on EMA, and that these factors are important contingent factors for the impact of system satisfaction and perceived job performance. Our findings can help managers gauge the impact of EMA in terms of its contribution to job performance. Our results provide an explanation as to why many firms have recently adopted EMA for efficient business processes and productivity support. Our findings additionally suggest that the cognitive fit between task and technology can be an important requirement for the productivity support of EMA. Further, our study findings can help managers in formulating their strategies and building organizational culture that can affect employees perceived job performance. Managers, thus, can tailor their dependence on EMA as high or low, depending on their task's characteristics, to maximize the job performance in the workplace. Overall, this study strengthens our knowledge regarding the impact of mobile applications in organizational contexts, technology acceptance and the role of task characteristics. To conclude, we hope that our research inspires future studies exploring digital productivity in the workplace and/or taking the role of EMA into account for employee job performance.

• Journal of Distribution Research
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• v.15 no.5
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• pp.217-235
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• 2010

In franchise industry, territorial restraint is a system that imposes exclusive right to franchisers in a certain business area. To the franchisers, this system guarantees monopoly profits in a local market and exclusive rights during the contract periods. In such a way, franchisee generates a big revenue at once on the basis of franchiser's initial investment such as interior cost and franchise fee, it must have supervised franchiser's moral hazard for the territorial restraint agreement. Rather than territorial restraint can be a system to give exclusive right to franchiser's so that they neglect their own sales and too much rely on headquarter's brand and marketing activities without their own efforts. This paper assesses the implication of territorial restraint by examining the effect on brand extension, degree of contract termination. Drawing on research in transaction cost agreement and opportunism, the authors suggest that franchisee is highly likely to launch similar brand which is not effected on previous contract when territorial restraint is set out in the contract system. Moreover, the authors find that the degree of contract termination will be high in the existence of territorial restraint due to the franchisee's opportunism. The results imply that territorial restraint induces franchisee's opportunistic strategy more aggressively so that the possibility of brand extension or new brand launching will be increased. At the same time, franchisee is aggressively seeking for the reason for contract termination due to the pursuit of its profit maximization. Based on some empirical findings, this paper concludes with policy implications and some necessary fields of future studies desirable.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.195-211
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• 2010

An exhibition is defined as market events for specific duration to present exhibitors' main product range to either business or private visitors, and it also plays a key role as effective marketing channels. Especially, as the effect of the opinions of the visitors after the exhibition impacts directly on sales or the image of companies, exhibition organizers must consider various needs of visitors. To meet needs of visitors, ubiquitous technologies have been applied in some exhibitions. However, despite of the development of the ubiquitous technologies, their services cannot always reflect visitors' preferences as they only generate information when visitors request. As a result, they have reached their limit to meet needs of visitors, which consequently might lead them to loss of marketing opportunity. Recommendation systems can be the right type to overcome these limitations. They can recommend the booths to coincide with visitors' preferences, so that they help visitors who are in difficulty for choices in exhibition environment. One of the most successful and widely used technologies for building recommender systems is called Collaborative Filtering. Traditional recommender systems, however, only use neighbors' evaluations or behaviors for a personalized prediction. Therefore, they can not reflect visitors' dynamic preference, and also lack of accuracy in exhibition environment. Although there is much useful information to infer visitors' preference in ubiquitous environment (e.g., visitors' current location, booth visit path, and so on), they use only limited information for recommendation. In this study, we propose a booth recommendation methodology using Sequential Association Rule which considers the sequence of visiting. Recent studies of Sequential Association Rule use the constraints to improve the performance. However, since traditional Sequential Association Rule considers the whole rules to recommendation, they have a scalability problem when they are adapted to a large exhibition scale. To solve this problem, our methodology composes the confidence database before recommendation process. To compose the confidence database, we first search preceding rules which have the frequency above threshold. Next, we compute the confidences of each preceding rules to each booth which is not contained in preceding rules. Therefore, the confidence database has two kinds of information which are preceding rules and their confidence to each booth. In recommendation process, we just generate preceding rules of the target visitors based on the records of the visits, and recommend booths according to the confidence database. Throughout these steps, we expect reduction of time spent on recommendation process. To evaluate proposed methodology, we use real booth visit records which are collected by RFID technology in IT exhibition. Booth visit records also contain the visit sequence of each visitor. We compare the performance of proposed methodology with traditional Collaborative Filtering system. As a result, our proposed methodology generally shows higher performance than traditional Collaborative Filtering. We can also see some features of it in experimental results. First, it shows the highest performance at one booth recommendation. It detects preceding rules with some portions of visitors. Therefore, if there is a visitor who moved with very a different pattern compared to the whole visitors, it cannot give a correct recommendation for him/her even though we increase the number of recommendation. Trained by the whole visitors, it cannot correctly give recommendation to visitors who have a unique path. Second, the performance of general recommendation systems increase as time expands. However, our methodology shows higher performance with limited information like one or two time periods. Therefore, not only can it recommend even if there is not much information of the target visitors' booth visit records, but also it uses only small amount of information in recommendation process. We expect that it can give real?time recommendations in exhibition environment. Overall, our methodology shows higher performance ability than traditional Collaborative Filtering systems, we expect it could be applied in booth recommendation system to satisfy visitors in exhibition environment.