• Korean Management Science Review
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• v.25 no.3
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• pp.101-122
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• 2008

A wide variety of convergent digital products are emerging through the combination of multiple independent digital technologies. Digital convergence provides new revenue sources for businesses and new ways of satisfying individual needs of consumers. Despite its business and consumer implications, little research has addressed how people perceive or evaluate convergent products. This study aims at understanding how consumers interpret and evaluate convergent digital products by conducting two consecutive studies. Firstly, a survey was conducted to understand how people interpret convergent products in three ways suggested by the conceptual combination theory based in cognitive science. Secondly, an experiment was conducted to investigate the impact of combination strategies and product similarities on user evaluation of convergent products. Study results indicate that similarity of constituent products has a substantial effect on the interpretation of concept combination strategies. Moreover, combination strategy and product similarity were found to have substantial effects on user comprehension, perceived newness, and preferences for convergent products. This paper ends with an examination of the implications and limitations of the study results.

• Journal of Distribution Science
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• v.22 no.3
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• pp.59-70
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• 2024

Purpose: This study aimed to develop a strategic business conceptual model for large state plantations in West Java Province and Banten Province, Indonesia. The model was built through causal relationships and interrelationships between marketing strategies and business strategies that affect business performance on large state plantations. The plantation sector provides the largest contribution to gross domestic product and is an important part of national food distribution efforts. Research design, data, and methodology: This study used a literature review adapted from Pret and Logan (2019), which followed the guidelines of Tranfield et al. (2003), derived from the Scopus website with Q1/Q2 quartiles and inclusion/exclusion criteria published from 2012 to 2021. Results: Based on a systematic literature review approach, we constructed the strategic business conceptual model for large state plantations based on a combination of four causal and interrelationship variables that affect business performance, namely, industry attractiveness, unique capabilities, innovation management, and collaboration strategy. Conclusions: This research explains the relationship between industry attractiveness variables and unique capability as independent variables that can affect business performance through collaboration strategy and innovation management as intervening variables in the plantation sector, especially large state plantations, which have not been found in previous studies.

• Journal of Distribution Science
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• v.11 no.9
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• pp.25-29
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• 2013

Purpose - This study aimed to examine how the integration of IT systems was applied in the merger and acquisition (M&A) process in a Korean retail industry, based on the conceptual framework of a combination of related, existing literature. Research design, data, methodology - We employed the case study method, which involved literature reviews and interviews. We conducted a documentary survey and interviews regarding the M&A case for company A. Results - Company A had an integration strategy and plan with IT expertise before it began integrating both IT systems in D-Day. The IT integration of both systems was completed efficiently and effectively. Company A utilized not just one but all integration options, which was done in stages and according to situation. Conclusions - Companies should develop an integration strategy and have a clear integration plan with IT expertise in order to achieve successful integration. Companies trying to integrate IT systems during an M&A process can utilize all integration options in consideration of their business context and IT system conditions.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.525-543
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• 1998

This paper proposes a conceptual taxonomy of architectures far workflow management systems. The systematic classification work is based on a framework for workflow architectures. The framework, consisting of generic-level, conceptual-level and implementation-level architectures, provides common architectural principles for designing a workflow management system. We define the taxonomy by considering the possibilities for centralization or distribution of data, control, and execution. That is, we take into account three criteria. How are the major components of a workflow model and system, like activities, roles, actors, and workcases, concretized in workflow architecture？ Which of the components is represented as software modules of the workflow architecture？ And how are they configured and operating in the architecture？ The workflow components might be embodied, as active (processes or threads) modules or as passive (data) modules, in the software architecture of a workflow management system. One or combinations of the components might become software modules in the software architecture. Finally, they might be centralized or distributed. The distribution of the components should be broken into three: Vertically, Horizontally and Fully distributed. Through the combination of these aspects, we can conceptually generate about 64 software Architectures for a workflow management system. That is, it should be possible to comprehend and characterize all kinds of software architectures for workflow management systems including the current existing systems as well as future systems. We believe that this taxonomy is a significant contribution because it adds clarity, completeness, and "global perspective" to workflow architectural discussions. The vocabulary suggested here includes workflow levels and aspects, allowing very different architectures to be discussed, compared, and contrasted. Added clarity is obtained because similar architectures from different vendors that used different terminology and techniques can now be seen to be identical at the higher level. Much of the complexity can be removed by thinking of workflow systems. Therefore, it is used to categorize existing workflow architectures and suggest a plethora of new workflow architectures. Finally, the taxonomy can be used for sorting out gems and stones amongst the architectures possibly generated. Thus, it might be a guideline not only for characterizing the existing workflow management systems, but also for solving the long-term and short-term architectural research issues, such as dynamic changes in workflow, transactional workflow, dynamically evolving workflow, large-scale workflow, etc., that have been proposed in the literature.

• The Journal of Information Technology and Database
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• v.5 no.1
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• pp.97-108
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• 1998

This paper proposes a conceptual taxonomy of architectures for workflow management systems. The systematic classification work is based on a framework for workflow architectures. The framework, consisting of generic-level, conceptual-level and implementation-level architectures, provides common architectural principles for designing a workflow management system. We define the taxonomy by considering the possibilities for centralization or distribution of data, control, and execution. That is, we take into account three criteria. How are the major components of a workflow model and system, like activities, roles, actors, and workcases, concretized in workflow architecture. Which of the components is represented as software modules of the workflow architecture\ulcorner And how are they configured and operating in the architecture\ulcorner The workflow components might be embodied, as active (processes or threads) modules or as passive (data) modules, in the software architecture of a workflow management system. One or combinations of the components might become software modules in the software architecture. Finally, they might be centralized or distributed. The distribution of the components should be broken into three: Vertically, Horizontally and Fully distributed. Through the combination of these aspects, we can conceptually generate about 64 software Architectures for a workflow management system. That is, it should be possible to comprehend and characterize all kinds of software architectures for workflow management systems including the current existing systems as well as future systems. We believe that this taxonomy is a significant contribution because it adds clarity, completeness, and global perspective to workflow architectural discussions. The vocabulary suggested here includes workflow levels and aspects, allowing very different architectures to be discussed, compared, and contrasted. Added clarity is obtained because similar architectures from different vendors that used different terminology and techniques can now be seen to be identical at the higher level. Much of the complexity can be removed by thinking of workflow systems. Therefore, it is used to categorize existing workflow architectures and suggest a plethora of new workflow architectures. Finally, the taxonomy can be used for sorting out gems and stones amongst the architectures possibly generated. Thus, it might be a guideline not only for characterizing the existing workflow management systems, but also for solving the long-term and short-term architectural research issues, such as dynamic changes in workflow, transactional workflow, dynamically evolving workflow, large-scale workflow, etc., that have been proposed in the literature.

• Information Systems Review
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• v.12 no.1
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• pp.107-130
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• 2010

Knowledge management strategy is considered a key determinant of successful knowledge management. However, theoretical and empirical researchers disagree on how knowledge management strategies improve firms' performance. The inconsistent results of prior studies may be attributed to the fact that complementary relationships among knowledge management strategies have not been adequately taken into consideration. While the previous literature has focused on investigating the impact of knowledge sourcing strategies on firms' performance one-at-a-time, in reality firms adopt several different knowledge management strategies together. By drawing on complementarity theory, this study revisits this research problem and develops three complementarity hypotheses. Surveys collected from 139 firms in Korea were analyzed to test the hypotheses by using super modularity function. The results confirmed complementary relationships between system- and person-oriented, and between internal- and external-oriented knowledge management strategies. Our results found no complementarity among the four different knowledge management strategies. This study sheds new light on knowledge management research by developing a new conceptual framework and using advanced analytical approaches to explore the relationship between knowledge management strategies and firms' performance. Implications for practice highlight that a successful knowledge management strategy requires a judicious combination of system- and person-oriented, or of internal- and external-oriented knowledge management strategies.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.17-40
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• 2007

Most research on web site design has focused on technological factors, while visual aesthetic factors have been considered less important. In contrast, this study focuses on visual aesthetic factors in web site design. Findings of this study can be summarized as follows : (1) The result of SPSS-factor analysis shows that there are 3 distinct factors, 'classical aesthetics', 'expressive aesthetics', and 'usability' 'Classical aesthetics' and 'expressive aesthetics' can be described by visual aesthetic design, 'Visual aesthetic design' can be distinguished from 'usability'. This conceptual confusion relating to 'usability' and 'visual aesthetic design' can be clarified by these findings. (2) As a result of multiple regression analyses, 'classical aesthetics', 'expressive aesthetics', and 'usability' have a positive influence on 'interactivity' and 'web site evaluation'. This research clarifies the concepts of 'expectations' of Grier [18] and 'engagement' of Rosen and Purinton [33] as the 'interactivity' between users and web sites. Furthermore, this research suggests a valid model with high $R^2$(interactivity, 48% : web site evaluation, 68%). (3) Empirical tests show that the differences among users in 'entry point' are related to the characteristics of web sites and the personal characteristics of users. The differences among users in terms of 'scanning time' are closely related to the attitudes and evaluation tendencies of users with respect to web sites. These findings could contribute to the 'search phase' of the Faraday model [16], enabling it to be more precise and extensible. The managerial implication of this study is that customers' preferences regarding web site designs are differences, as their preferences are based on their individual characteristics. Therefore, marketing managers should consider promotional tools on web sites that are relevant to the target market. An optimal strategy for web design could be a carefully-selected combination of factors that are relevant to the 'interactivity' and 'evaluation' of web sites. Additionally, if marketing managers want to attract more favorable attitudes and more affirmative evaluations from users, web sites should be designed so that they are understood more quickly by users. finally, this study suggests that 'good design' for web sites depends on understanding how to attain the appropriate balance between 'classical aesthetics' and 'expressive aesthetics', based on the target customer.

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.