فرایند ارتباط استراتژیک و سیستم ارزش محور : تجزیه و تحلیل پویا از شرکت های با تکنولوژی بالا در کشور تازه صنعتی شده
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|355||2009||10 صفحه PDF||سفارش دهید||7546 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 36, Issue 2, Part 2, March 2009, Pages 3965–3974
The current balanced scorecard literature suggests that a link should exist between lagging and leading measurements of non-financial performance perspectives and financial performance measures. This work designed a dynamic integrated model for examining the influence of strategic links on the Taiwanese high-tech industry, and to examine the relationships among the strategic perspectives of the balanced scorecard (BSC). This work studied the descriptive validity of the balanced scorecard as a causal model for leading and lagging measurements of non-financial and financial performance in relation to time-lag effects. Structural equation modeling (SEM) and dynamic analysis were used to empirically examine the relations among strategic linkages and value drivers within the model. The analytical results demonstrate the existence of directly positive driver effects between the learning–growth, customer, and financial perspectives; also the internal process (leading measurements) mediates the relationship between learning–growth (leading measurements) and financial perspective (lagging measurements). The results indicated that time tag positively influenced the non-financial and financial perspectives, and that they were strongly correlated with the strategic linkage process.
The high-tech industry is a fastest growing industry in many newly-industrialized countries (NICs) such as Taiwan, Korea, and India. Taiwanese government has viewed the high-tech industry as a driver of economic growth, and used various resources to support its development, including building the Hsin-chu Science-based Industrial Park and legislating the “Statute for Encouraging Investment” and the “Statute for Upgrading Industry” (Chen and Huang, 2004, Chen et al., 2006, Shyu and Chiu, 2002 and Wu et al., 2006). Furthermore, the Ministry of Economic Affairs (MOEA) launched technology development programs to accelerate the development of industrial innovation technology and to stimulate domestic economic growth in Taiwan. Since the early 1980s, the active involvement of the government and private enterprises in developing the electronic information and high-tech industries has yielded excellent results. The high-tech industry has grown rapidly and become a significant industrial sector in Taiwan, with a sharply increasing number of firm establishments (Tseng & Goo, 2005). Furthermore, during the past decades, globalization has enhanced global competition and placed considerable pressures for multinational corporations to lower costs and to increase efficiency as well as profitability. Consequently, many multinational corporations shifted some of their manufacturing and design activities abroad and performed strategic outsourcing in Taiwan. Taiwan was chosen mainly because of its combination of low manufacturing costs, skillful work forces, and tax breaks provided by the local government (Hu & Schive, 1998). Furthermore, high-tech firms that realize economies of location by dispersing each of its value creation activities to the optimal location for that activity should enjoy a competitive advantage over a firm that bases all of its value creation activities at a single location (Hu & Schive, 1998). The electronics, information and high-tech industries in Taiwan are dominated by OEM/ODM (original equipment manufacturing/original design manufacturing) manufacturers, and firms in these industries face dynamic changes in terms of technological environment and market competition. Given the growing challenges and competition from local and international environments, domestic high-tech firms must adopt appropriate strategies to enhance their competitive advantages and profitability, and the issue of how to drive the performance of high-tech firms has thus become increasingly important in Taiwan. During the past decade academicians and researchers in strategic management and managerial accounting areas have devoted increasing attention to the influence of non-financial measurements on financial performance (Banker et al., 2004 and Banker et al., 2000). The balanced scorecard developed by Kaplan and Norton (1992) uses a sequence of four perspectives that reflects the value creation activities of firms. The sequence begins with the learning and growth perspective, followed by the internal/business process, then the customer perspective in third place, and finally the financial perspective. Core outcome (performance) measures within each perspective are taken as leading indicators of the core outcome measures in the next perspective. Kaplan and Norton argued for the existence of a secondary set of associations besides the links among the four balanced scorecard perspectives (Kaplan and Norton, 1993, Kaplan and Norton, 1996a, Kaplan and Norton, 1996b, Kaplan and Norton, 1996c, Kaplan and Norton, 2001a, Kaplan and Norton, 2001b, Kaplan and Norton, 2001c, Kaplan and Norton, 2001d, Kaplan and Norton, 2004a, Kaplan and Norton, 2004b, Kaplan and Norton, 2004c, Kaplan and Norton, 2004d and Kaplan and Norton, 2006). Within each of the four perspectives of the BSC, performance drivers (performance measures) are expected to be the leading indicators of core outcome measures. The BSC view of the firm indicates that strategic linkages and value drivers provide firms with competitive advantages and improved performance. Since being developed by Kaplan and Norton, the BSC concept has been widely adopted by manufacturing and service companies, nonprofit organizations, government entities, and other industries around the world. A considerable number of research has employed the BSC concept to study the performance of manufacturing firms and manufacturing strategies, for example Blundell et al., 2003, Bryant et al., 2004, Duh et al., 2006, Fernandes et al., 2006, Hoque and James, 2000, Huang et al., 2006, Knotts et al., 2006, Lee et al., 2008, Maltz et al., 2003 and Sohn et al., 2003. Based on the existing literature, this work has three aims: (a) to examine the relationships between non-financial measurements and financial performance; (b) to examine the relationships between lagging and leading measurements; and (c) to present a conceptual framework for linking non-financial measurements and financial performance regarding time-lag effects (that is, the dynamic BSC framework). By using the structural equation model (SEM) as the analytical tool, this work attempted to answer the following questions: (a) How do learning/growth and internal/business process drive the customer and financial perspectives in the high-tech industry? (b) What are the relationships between lagging and leading measurements? (c) How do time-lag effects influence value creation and organizational performance (that is, customer and financial performance)? (d) How do high-tech firms translate their learning/growth perspective into increased financial performance, whether in terms of productivity, increased growth sales, product acceptance rate, or other organizational performance indicators? This research thus attempts to enhance understandings of how and to what extent the time-lag effect influences the dynamic BSC framework. The structure of this paper is organized as follows. Section 2 briefly reviews the BSC theory and summarizes the theoretical foundations of the research, with two sets of hypotheses developed. The conceptual framework of the research is then presented in Section 3, along with the research methodology, including the instrument, samples, variables and analytic models. Section 4 then described the empirical analysis methods, including correlation and SEM analyses, followed by the empirical results; a framework of dynamic BSC framework was then developed. Finally, summary, practical implications and suggestions for future research conclude this paper.
نتیجه گیری انگلیسی
This work examined four research questions: (a) how do the learning/growth and internal/business processes drive customer and financial perspectives in the high-tech industry? (b) What are the relationships between lagging and leading measurements? (c) Do time-lag effects influence value creation and improve organizational performance (that is, customer and financial performance)? (d) How can a high-tech firm translate its learning/growth perspective into increased financial performance, whether in terms of productivity, sales growth, product acceptance rate or other indicators of organizational performance? This work used an analytical tool to address these questions, namely the SEM model. This work referred to the BSC literature to identify a set of variables that reflected perspectives and performance. This study examines whether the causal relationships among the strategic perspectives and performance indicators of the balanced scorecard framework exist in high-tech firms. This work empirically tests the descriptive validity of the balanced scorecard as a causal model of leading and lagging measurements of non-financial and financial performance in relation to time-lag effects. A dynamic integrated model was established to investigate the impact of the balanced scorecard on the Taiwanese high-tech industry, and to examine the relationships among different perspectives of the balanced scorecard. The main findings of this work are summarized as follows. This work developed five hypotheses that identified the important objectives and strategic linkages among different perspectives of the balanced scorecard. The analytical results strongly supported four of the hypotheses. Moreover, the results of the SEM analysis identified significant causal relationships among four perspectives in the dynamic integrated model. Notably, the results demonstrated the existence of a direct positive driver effect between the learning–growth and both the customer and financial perspectives, as well as that the internal process (leading measurements) mediated the relationship between learning–growth (leading measurements) and financial perspective (lagging measurements). The analytical results indicated that time tag positively influenced the non-financial and financial perspectives, and that these perspectives were markedly correlated with strategic linkages. Successful implementation of BSC requires an optimal understanding of the strategic links among the non-financial and financial perspectives. This work designed an empirical model for exploring the relationships among contextual constructs, including the learning–growth, internal process, customer and financial perspectives.