• Journal of Information Technology Services
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• v.12 no.3
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• pp.273-287
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• 2013

The objective of this study is to empirically develop performance evaluation measures for LIS (logistics information systems) based upon BSC (balanced scorecard) model and determine the relative importance among four perspectives of BSC using AHP (analytic hierarchy process) methodology. Above all, forty nine probable measures for evaluating LIS performance were identified through reviewing the previous research related with SCM (supply chain management), logistics management, and information systems evaluation. And then, these probable measures were examined by means of coincidence analyses using three mutually exclusive criteria(validity of content, ease of measurement and reliability of measurement). Data for conducting the coincidence analyses were collected from LIS users and LIS development personnel. As the results of the coincidence analyses, it was found that 31 ones among 49 probable performance evaluation measures theoretically derived could be qualified for LIS performance evaluation. And AHP analysis showed that the weight of each perspective was respectively as follows : 46.8% for financial perspective, 31.3% for customer perspective, 14.8% for internal business process perspective, and 7.1% for learning and growth perspective. The academic contribution of this study is that performance evaluation measures for LIS could be systematically and empirically developed on the basis of BSC. Also, the results of this study are expected to be used as a practice guideline of evaluating and improving LIS.

• The Journal of Information Systems
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• v.13 no.2
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• pp.1-22
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• 2004

Internet commerce has the potential to propel a company to "break out" of existing strategic constraints and radically alter business processes, strengthen customer and supplier ties, and open up new markets. Therefore, many firms have rushed into internet commerce to conduct business more efficiently, create new business opportunities, and generate business value. Since internet shopping mall not only become a valuable channel for selling goods to customers, but also offer companies an important vehicle for attaining competitive advantages in the new digital economy, the design and content of internet shopping mall must reflect its business goals and customers' needs. However, as little empirical evidence on the effect of internet shopping mall contribution of firm performance exist, the functionality of a firm's internet shopping mall has been decided voluntarily from its business experience. The purpose of this study is to examine the relationship between the marketing functional characteristics of internet shopping mall and its performance. 125 questionnaires from internet shopping malls which sell physical goods direct to an individual end consumer were collected. The results showed that some factors(price, product recognition, reliability enhancement) affect positive effects on the performance of internet shopping mall.

• Journal of Distribution Science
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• v.18 no.11
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• pp.61-67
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• 2020

Purpose: This paper aims to examine the interaction effect of customers relationship management (CRM) on the competitive advantage (CA) of small and medium-scale enterprises (SMEs) in Yemen. Research design, data and methodology: This study applied a quantitative approach in dealing with the interaction effect of CRM dimensions and SMEs' competitive advantage in Yemen. The research uses a sample of 247 manufacturing SMEs surveyed in Yemen. Results: The results indicate that only three dimensions of CRM, namely (TCM), (KM) and (CRMO), have a significant effect on SMEs' competitive advantage, but not that between (KCF) and SMEs' competitive advantage. Conclusions: The findings of this study offer important insights for owners and managers of SMEs, researchers and policymakers to further understand the effects of CRM on SMEs' competitive advantage. SMEs should also be encouraged to develop their CRM to improve their competitive advantage. Lastly, this study makes several contributions to the literature, the first of which is the provision of evidence concerning the major role of CRM as a dependent variable and competitive advantage as an independent variable. The second contribution pertains to its pioneering status in examining the direct relationship between CRM dimensions and the competitive advantage of SMEs in a Middle Eastern country.

• Culinary science and hospitality research
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• v.14 no.2
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• pp.138-152
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• 2008

This study suggested a theoretical research system on the effects of the corporate social responsibility in family restaurants upon corporate image, corporate preference and revisit intention. Based on total 342 university students from the empirical research, this study confirmed the reliability and fitness of research model and verified total 4 hypotheses with structural equation modeling(SEM) by Amos program. SEM results showed that the corporate social responsibility of family restaurants had positively significant influence on corporate image(legal and economic aspect 0.203-p<0.05; philanthropy aspect 0.318-p<0.001; ethical aspect 0.203-p<0.05), and corporate image had positively significant influence on corporate preference(0.979-p<0.001) and revisit intention(0.258-p<0.05) as well. Also, corporate preference had positively significant influence on revisit intention(0.844-p<0.001). The findings of this study verified a hypothetical ground that the corporate social responsibility of family restaurants has positive effects upon revisit intention. Additionally, regarding the activity of social responsibility in the foodservice industry, it is proved that the practices in the activities of philanthropy and contribution to society rather than the practices in the legal and economic aspect had significant relations with the customer's favorable behaviors.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.137-152
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• 2012

As social media such as facebook and twitter is widespread, social commerce appears as a new way of e-commerce. Social commerce is a subset of electronic commerce that involves using social media that supports social interaction and user contributions. From the understanding of social commerce and literature review, we deduced the research model that relationship, collectivism, convenience, usefulness, low price, reputation, and rapidness have influence on satisfaction and repurchase intention. As a result of data analysis, relationship, convenience, usefulness, low price, and rapidness had influence on satisfaction and repurchase intention. And collectivism had influence on relationship. But reputation did not have influence on satisfaction. The focus of this study is on the effect of relationship and collectivism on satisfaction and repurchase, because relationship and collectivism is the major feature of social commerce. Succinctly speaking, collectivism affects relationship among users, in turn, relationship affects satisfaction and repurchase intention. This study gives a contribution to business. Business related with social commerce has to make a business strategy for managing relationship and consider collectivism tendency for selecting target customer.

• Management & Information Systems Review
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• v.3
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• pp.257-285
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• 1999

Korea Postal Service(KPS) nowadays lies in competitive environment with alternative business such as door-to-door delivery service. Customers began to complain about postal service quality and ask the government to reform a public firm through management innovation. But, Korea Postal Service has not met the break-even point between it's revenue and expenditure because the service is under the government system and cannot independently make major decisions on products, pricing, services, personnel management, financial policies and etc. The objective of this study is to provide marketing planners and practitioners with some guidelines when they establish marketing strategies and to help marketers on theories and practical instructions about postal service marketing when they interact with customers. I. A field survey on both customer satisfaction and internal staff satisfaction was conducted to get some ideas for the marketing strategy planning. II. Practical guidelines and instructions were made for marketers to communicate with customers in various areas such as pricing, product, service demand, marketing channel, promotion, and etc. III. Some suggestions on marketing policies for planners and mangers in the marketing strategy were described including personnel resource as well as physical resource. IV. Special issues on small packet market and direct mail market were discussed and some alternative solutions were proposed. V. Database marketing strategy was emphasized to get new business opportunities such as direct mail, and to provide differential services to customers as much as their contribution into the profitability for KPS. VI. Cyber Post Office should be constructed on Internet to provide new services which are combined with physical material flow and information technologies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.523-531
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• 2021

This study aims to examine the role of social media marketing on the performance of micro-, small and medium-sized enterprises (MSMEs) during the COVID-19 pandemic. This research method uses a quantitative approach and the analytical tool used is Structural Equation Modeling (SEM) based on Partial Least Square. The sampling technique used purposive sampling and the sample in this study was MSMEs who use social media for marketing. The social media used are Facebook, Instagram, and Whatsapp. The number of samples in this study was 254 MSMEs. Data collection used online questionnaires. The research findings show that the use of social media marketing is influenced by compatibility, perceived usefulness, and perceived ease-of-use. The results of this study indicate that the use of social media for marketing has a positive effect on the performance of MSMEs, especially in increasing sales, customer relationships, productivity, and creativity. This means that the better the management of social media for marketing, the better the performance of MSMEs will be. The theoretical contribution to this research is built on the TAM and UTAUT theories and their impact on social media marketing on MSMEs in developing countries that are living through the COVID-19 pandemic.

• Journal of Distribution Science
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• v.20 no.8
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• pp.59-67
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• 2022

Purpose: This study identifies how twelve key success factors of distribution strategies for community enterprises in Thailand achieve higher performances. Research design, data, and methodology: The samples in this study were 400 entrepreneurs throughout the country. The instrument for data elicitation was a questionnaire. The descriptive and inferential statistics for data analysis were percentage, mean, standard deviation, T-Test, F-Test, multiple regression, and multiple correlations. Results: The results revealed that, overall, the samples showed high opinions on online distribution strategies in all aspects. In detail, the three highest factors were as follows: 1) electronic satisfaction, 2) product characteristics and electronic trust, and 3) the quality and success in online distribution. In detail, the three highest aspects of online distribution success were customer loyalty, financial performance, and work management, respectively. The online distribution strategies influencing community enterprises' success were electronic trust, electronic loyalty, social information, electronic satisfaction, and online distribution tools, which had a statistical significance of 71. Conclusions: This research has made an essential contribution to community enterprise entrepreneurs should focus on and adopt these 8P+4ODS concepts to increase sales, maintain brand loyalty of existing customers, get new customers, develop learning, and improve the working potentials of community enterprise entrepreneurs.

• Corrosion Science and Technology
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• v.23 no.2
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• pp.131-138
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• 2024

This paper introduces Primetals Technologies' Through-Process Optimization (TPO) Services and Through-Process Quality Control (TPQC) System, which integrate domain knowledge, software, and automation expertise to assist steel producers in achieving operational excellence. TPQC collects high-resolution process and product data from the entire production route, providing visualizations and facilitating quality assurance. It also enables the application of artificial intelligence techniques to optimize processes, accelerate steel grade development, and enhance product quality. The main objective of TPO is to grow and digitize operational know-how, increase profitability, and better meet customer needs. The paper describes the contribution of these systems to achieving operational excellence, with a focus on quality assurance. Transparent and traceable production data is used for manual and automatic quality evaluation, resulting in product quality status and guiding the product disposition process. Deviation management is supported by rule-based and AI-based assistants, along with monitoring, alarming, and reporting functions ensuring early recognition of deviations. Embedded root cause proposals and their corrective and compensatory actions facilitate decision support to maintain product quality. Quality indicators and predictive quality models further enhance the efficiency of the quality assurance process. Utilizing the quality assurance software package, TPQC acts as a "one-truth" platform for product quality key players.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.