Seung Kyoon Shin

An empirical investigation of socio-cultural factors of information sharing in China

Understanding information sharing is an important challenge to modern organizations, and is likely to be increasingly considered when IT investment decisions are made world-wide. Our research study investigated the influence of cultural factors on information sharing in China. It was postulated that social network structures such as guanxi, Confucian dynamism, and collectivism could explain the degree to which information sharing took place between people in China. It was found that guanxi, Confucian dynamism, and collectivism all had a significant influence on information sharing.

Global software piracy revisited

Determining why the roots of the disparity in national piracy levels lie beyond economics.

Manufacturing performance: evaluation and determinants

– Many studies examine manufacturing performance along individual benchmarking dimensions. This study aims to develop a performance metric based on quality and output volume among other variables to assess a firms manufacturing competitiveness in relation to its major rivals., – The relative manufacturing performance is measured by data envelopment analysis (DEA). Several key manufacturing practices are examined for their impact on performance. They are research and development (R&D) commitment, time compression during production, and degree of outsourcing. The results are based on a sample from the world automobile industry., – The empirical results suggest that a strong R&D commitment and ability to compress production time explain 37 percent of the manufacturing performance differences among major volume automobile producers. A nonlinear convex relationship is also found between outsourcing rate and manufacturing performance. The results show how the resulting performance ratings can then be utilized to assess the effects of a selected group of practices on manufacturing performance., – Since, there is a common basis for the sources of competitiveness among industries, the findings derived from this study are probably transportable to other industries. Also, the proposed metric and analytic approaches are generic and thus can be broadly applied to other industries. The results also suggest the need for further analysis of where improvements can be made within a given company, according to its firm‐specific characteristics., – Examines manufacturing performance along individual benchmarking dimensions and develops a performance metric based on quality and output volume to assess a firms manufacturing competitiveness in relation to its major rivals.

Denormalization effects on performance of RDBMS

Presents a practical view of denormalization, and provides fundamental guidelines for incorporating denormalization. We have suggested using denormalization as an intermediate step between logical and physical modeling, to be used as an analytic procedure for the design of the applications requirements criteria. Relational algebra and query trees are used to examine the effect on the performance of relational database management systems (RDBMS). The guidelines and methodology presented are sufficiently general, and they can be applicable to most databases. It is concluded that denormalization can enhance query performance when it is deployed with a complete understanding of application requirements.

Denormalization strategies for data retrieval from data warehouses

In this study, the effects of denormalization on relational database system performance are discussed in the context of using denormalization strategies as a database design methodology for data warehouses. Four prevalent denormalization strategies have been identified and examined under various scenarios to illustrate the conditions where they are most effective. The relational algebra, query trees, and join cost function are used to examine the effect on the performance of relational systems. The guidelines and analysis provided are sufficiently general and they can be applicable to a variety of databases, in particular to data warehouse implementations, for decision support systems.

Impact of International Information Technology Transfer on National Productivity

Researchers have widely postulated that the adoption of information technology (IT) products enhances global competitiveness and production efficiency as successful technological innovation replaces and improves traditional inputs and modes of production. This study suggests that when IT products are traded across borders, IT investment in an economy has a positive influence on the productivity of its import partner country. We provide empirical evidence for the positive effect of global IT diffusion on productivity through international trading of IT products. The results show a positive effect of foreign IT transfer on the recipient countrys productivity. In addition, we find that the effect of transferred IT is only significant when the source country is an IT-intensive or hi-tech export country. The results and implications are robust, even controlling for other important factors such as openness, innovative capacity, and IT infrastructure in addition to the transferred IT. Finally, a panel cointegration test---a recently developed advanced econometric method---is used to address the common problems of spurious relations that arise in regressions with nonstationary time-series data.

The Intensity and Externality Effects of Information Technology Investments on National Productivity Growth

This study investigates the relation between information technology (IT) expenditures and national productivity based on a production estimation approach by using a pooled time-series country-level data set for the period from 1992 to 2000. The results, which confirm the findings of earlier studies on country-level IT investment effect, show IT has significant and positive effects on national productivity growth. We find that IT intensity improves the positive effect of IT investment on national productivity growth and that the existence of IT externalities, through which spillovers of knowledge and innovation occur, may eventually lead to long-run persistent national productivity growth.

Can knowledge be more accessible in a virtual network?: Collective dynamics of knowledge transfer in a virtual knowledge organization network

Virtual knowledge organizations (VKOs) produce and embrace priceless, and often, unique knowledge assets within the boundary of each virtual community. An important question is how do we maximize the benefits from these valuable assets at the entire VKO network level? Relying on the graph theory, this study is to investigate how the structure of virtual knowledge networks formed by knowledge agents and knowledge profile of each VKO influence the dynamics of knowledge transfer in a virtual knowledge organization network (VKON). We develop a network model through which knowledge will be efficiently disseminated when knowledge agents are uniformly distributed across the network. Using this models intrinsic capability to assess global effects of local transformations in a network, we found that VKON complexity, a measure for efficiency of knowledge transfer, is optimized when a new knowledge agent is placed between two communities with the minimum knowledge transfer capacity. The results of this study will help understand the inter-community knowledge transfer dynamics in virtual knowledge community networks.

Customer Relationship Management and Knowledge Discovery in Database

Customer relationships are increasingly central to business success (Kotler, 1997; Reichheld & Sasser, 1990). Acquiring new customers is five to seven times costlier than retaining existing customers (Kotler, 1997). Simply by reducing customer defections by 5%, a company can improve profits by 25% to 85% (Reichheld & Sasser, 1990). Relationship marketing—getting to know customers intimately by understanding their preferences—has emerged as a key business strategy for customer retention (Dyche, 2002). Internet and related technologies offer amazing possibilities for creating and sustaining ideal customer relationships (Goodhue, Wixom, & Watson, 2002; Ives, 1990; Moorman, Zaltman, & Deshpande, 1992). Internet is not only an important and convenient new channel for promotion, transactions, and business process coordination; it is also a source of customer data (Shaw, Subramaniam, Tan, & Welge, 2001). Huge customer data warehouses are being created using advanced database technologies (Fayyad, PiatetskyShapiro, & Smyth, 1996). Customer data warehouses by themselves offer no competitive advantages: insightful customer knowledge must be extracted from such data (Kim, Kim, & Lee, 2002). Valuable marketing insights about customer characteristics and their purchase patterns, however, are often hidden and untapped (Shaw et al., 2001). Data mining and knowledge discovery in databases (KDD) facilitate extraction of valuable knowledge from rapidly growing volumes of data (Mackinnon, 1999; Fayyad et al., 1996). This article provides a brief review of customer relationship issues. The article focuses on: (1) customer relationship management (CRM) technologies, (2) KDD techniques, and (3) Key CRM-KDD linkages in terms of relationship marketing. The article concludes with the observations about the state-of-the-art and future directions. Background

The Effects of Community Characteristics and Member Retention of Virtual Communities

This paper investigates the antecedents of member retention for virtual communities. This research theorizes the motivating mechanism from both perspectives of the information seekers and providers. Four antecedents-communication breadth, depth, responsiveness, and cross-posting-have a statistically significant influence on member retention. Furthermore, we have found that communication breadth and depth have a diminishing effect on the marginal impact on member retention as well as the interaction between these factors has a negative impact on member retention although each of them separately has a positive impact. The implications of this study help understand the dynamics of knowledge sharing in virtual communities.