• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.555-569
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• 2020

This study examines the impact of corporate tax, a fiscal measure along with trade liberalization and research and development on total factor productivity for a panel of 153 industrial firms listed on the Pakistan Stock Exchange over the period 1997-2017. For empirical analysis, we employ the system generalized method of moment estimator. In the first step, we estimate industrial production function and the results reveal that raw material, industrial labour force and energy play vital role in enhancing industrial production. Whereas, industrial capital exerts negative impact on industrial output. We also measured total factor productivity using the production elasticities. In the second step, we examine the impact of corporate tax, trade liberalization and research and development on total factor productivity. The results indicate that higher level of corporate tax exerts negative impact on total factor productivity. The findings reveal that higher corporate taxation discourages industrial firms to undertake research and development thereby exerting adverse impact on total factor productivity of firms. The impact of trade liberalization proxied by average tariff is positive while customs duty and sales tax negatively impact firm-level total factor productivity. These findings provide useful insights for managers, investors and policy makers in Pakistan.

• Korea Trade Review
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• v.41 no.4
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• pp.61-90
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• 2016

This study aims to identify the sources of productivity change in export manufacturing firms. After estimating the Malmquist productivity index, a panel regression was used to calculate the source of productivity change. Upon conducting a literature review of this field, six variables were selected as explanatory variables. The results of an analysis of 355 export manufacturing firms operating from 2009 through 2015 are as follows: First, both innovation activity and total assets had a positive impact on productivity change. However, employment cost intensity, equity ratio, and current ratio had a negative impact on productivity change in export manufacturing firms. Second, innovation activity and intangible assets had a positive impact on productivity change, but employment cost intensity, selling expense intensity, and equity ratio had a negative impact on productivity change in large export manufacturing firms. Third, innovation activity had a positive impact on productivity change, but employment cost intensity and equity ratio had a negative impact on productivity change in small and medium export manufacturing firms. Fourth, intangible assets had a positive impact on productivity change, but employment cost intensity, selling expense intensity, and current ratio had a negative impact on productivity change in export manufacturing firms listed on the Korea Composite Stock Price Index. Fifth, innovation activity and total assets had a positive impact on productivity change, but employment cost intensity and equity ratio had a negative impact on productivity change in manufacturing firms listed on the Korean Securities Dealers Automated Quotations. The managerial implications of this study are also discussed.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.311-314
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• 2003

This study takes a statistical approach to quantify tile impact of wort stopped on the following day's site productivity. Therefore, this study is aimed to verify this null hypothesis: 'A work stopped in a construction field does not impact on the following day's productivity and productivity achievement ratio'. For the purpose, work, stopped is presumed as a dummy variable impacting site productivity in multiple linear regression analysis. Moreover, the quantified impact of work slopped on productivity achievement ratio is identified based on this study. This study shows that construction managers should persevere in their efforts to secure the work continuity in order to improve site productivity and productivity achievement ratio.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.113-129
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• 2024

Purpose - This study aims to empirically identify the quantitative effects of work from home (WFH) on employee productivity using field data. Design/methodology/approach - Based on large-scale field data from a South Korean company which introduced the WFH arrangement in 2020, we conducted fixed effect and moderating effect analyses using individual-level panel data over sixty-three weeks. Findings - The empirical analysis generated several findings. It was found that overall, WFH has a positive effect on productivity. However, the productivity impact of WFH was found to vary depending on task characteristics. Specifically, WFH led to over 20% increase in productivity for simple and repetitive tasks. On the other hand, no significant productivity impact was observed for professional and knowledge-based tasks. Research implications or Originality - As the first study based on field data from South Korea, this study offers convincing causal evidence of the moderating impact of task characteristics on the relationship between WFH and productivity. Further, the above findings provide managers with practical insights concerning their work arrangement decisions.

• Journal of the Korea Institute of Building Construction
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• v.11 no.2
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• pp.100-107
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• 2011

As construction duration significantly influences the performance and the success of construction projects, it is necessary to appropriately manage the impact factors affecting construction duration. Recently, interest in the construction industry has been rising due to the recent change in the construction legal system, and the competition among the construction companies on construction time. However, the impact factors are extremely diverse. The existing productivity data on impact factors is not sufficient to properly identify the impact factor and measure the productivity from various perspectives, such as subcontractor, time, crew, work and so on. In this respect, a multidimensional analysis by a data warehouse is very helpful in order to view the manner in which productivity is affected by impact factors from various perspectives. Therefore, this research proposes a method that effectively takes the diverse productivity data of impact factors, and generates a multidimensional analysis. Decision tree analysis, a data mining technique, is also applied in this research in order to supply construction managers with appropriate productivity data on impact factors during the construction management process.

• Korean Journal of Construction Engineering and Management
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• v.6 no.5 s.27
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• pp.69-77
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• 2005

Change is inevitable and is a reality of construction projects. Most construction contracts include change clauses and allowing contractors an equitable adjustment to the contract price and duration caused by change. However, the actions of a contractor can cause a loss of productivity and furthermore can result in disruption of the whole project because of a cumulative or ripple effect. Because of its complicated nature, it becomes a complex issue to determine the cumulative impact (ripple effect) caused by single or multiple change orders. Furthermore, owners and contractors do not always agree on the adjusted contract price for the cumulative Impact of the changes. A number of studies have attempted to quantify the impact of change orders on project costs and schedule. Many of these attempted to develop regression models to quantify the loss. However, regression analysis has shortcomings in dealing with many qualitative or noisy input data. This study develops ANN models to classify and quantify the labor productivity losses that are caused by the cumulative impact of change orders. The results skew that ANN models give significantly improved performance compared to traditional statistical models.

• Journal of Korea Trade
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• v.25 no.3
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• pp.48-64
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• 2021

Purpose - This study examined the effect of tariff cuts on productivity in Korea's manufacturing industries and the effect of initial productivity level before tariff cuts on productivity improvement after tariff cuts. We also attempted to identify whether import-driven or export-driven factors are more important for productivity improvement, especially in low productivity industries. Design/methodology - Since tariff reduction is a policy decision that can affect cross-industry, its impact is spread across all industries beyond the scope of a single firm through the input and output network of industry structure. Accordingly, we proposed a new method to measure the change in productivity to reflect the impact of tariff cuts across industries. Through an Armington CGE analysis, changes in endogenous variables can be directly measured after the exogenous shock of tariff reduction, and the amount of movements in productivity triggered by tariff cuts can also be calculated. We can thus assess the effectiveness of exogenous policy, such as tariff cuts, through the difference between the benchmark and counterfactual values of endogenous variables. Findings - This study confirmed that tariff reduction positively affected productivity improvement in Korea's manufacturing industries. It also confirmed that productivity gains occur in Korea's leading export industries. Finally, greater productivity gains were recorded in the group with additional high-export-share or high-import-share conditions for low productivity industries. These results are, in a limited sense, consistent with the existing studies that emphasize the importance of exports and imports on productivity improvement, especially for low productivity industries. Originality/value - The results of our experiments are different from those of non-CGE studies, which measure the industry-level change in productivity with dummy coefficients, in terms of directly calculating the amount of change in productivity. In addition, we propose that the Armington CGE model is more appropriate than the Melitz CGE model to directly measure the productivity after tariff cuts. This is because the Melitz CGE model assumes the given specific productivity density, which does not change after an overall drop of tariffs. To the best of our knowledge, this approach to directly calculating productivity by reflecting the impact of tariff reduction across industries through CGE analysis, is unprecedented in this literature.

• Korea Trade Review
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• v.46 no.3
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• pp.25-44
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• 2021

This paper analyzes the impact of the recent change in global value chain on the productivity of manufacturing sectors and firms in Chungnam area using ADB MRIO. Forward participation significantly increases sector productivity in Chungnam area and backward participation affects the sector productivity after 2015. In the analysis for firm productivity in Chungnam area, GVC participation does not enhance the productivity of firms in Chungnam area. However, firms in the top 25% of productivity in 2007 improved their productivity with higher GVC participation and the productivity of firms in the top 25% of asset in 2007 was positively affected by forward pariticipation and negatively affected by backward participation. The productivity of firms that were in international market in 2007 was significantly worsened by GVC participation.

• The Journal of Industrial Distribution & Business
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• v.11 no.4
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• pp.7-18
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• 2020

Purpose: This research investigates the impact of technology adoption on organisation productivity. The framework has three independent variables viz. technological change, information technology (IT) infrastructure, and IT knowledge management and one dependent variable as organisational productivity. Research design, data and methodology: An explanatory research design with a quantitative research method was employed, and data was collected using a self-administered questionnaire using online as well as an offline survey. The sample consisted of 300 IT managers and senior-level executives (production as well as service team) in leading IT companies in Malaysia selected using snowball sampling. Normality and reliability assessment was performed in the first stage utilising SPSS 22, and Confirmatory Factory Analysis (CFA) was performed with maximum likelihood estimation to assess the internal consistency, convergent validity, and discriminant validity. Finally, Structural Equation Model (SEM) and path analysis are conducted using AMOS 22. Results: The research findings demonstrated that technological change and IT infrastructure positively and significantly impact the organisation's productivity while IT knowledge management has significant but negative impact on organizational productivity of IT companies in Malaysia. Conclusion: The research concludes that all three factors plays important role in deciding organizational producvity. Recommendations, implications, limitations and future research avenues are discussed.

• Journal of Information Technology Application
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• v.3 no.2
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• pp.25-48
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• 2001

This Study intends to Investigate the economic impact of information technology investment. Six countries in OECD are selected and analyzed to understand the empirical relationship between informatization level and productivity Correlation test and regression analysis are executed, using macro data concerning informatization index, total factor productivity and real output per worker hour The impact of informatization level on productivity is characterized by the time lag effect which is used to explain the productivity paradox in precedent studies. Empirical analysis shows that the higher informatization level and information intensity, the lower time lag effect. The result indicates that IT investment has characteristic as sunk cost and the economic impact is appeared after a certain period of time.