Innovation system of a metropolitan region: a case study of the Yangtze River Delta

Xie, Fei; Du, Hongwei

doi:10.1504/ijil.2008.015949

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…Frohlich and Dixon (2001), Takala et al (2003) and Xie and Du (2008) suggested that strategies and performance were closely interrelated. In other words, performance areas should be consistent with a set of strategies at the organizational and operational levels.…”

Section: Indicated Informationmentioning

confidence: 99%

“…and supplierselection and information and communication technology would play an important role in creating a robust decision-making process and a learning organization. Frohlich andDixon (2001), Takala et al (2003) and Xie and Du (2008) suggested that strategies and performance were closely interrelated. In other words, performance areas should be consistent with a set of strategies at the organizational and operational levels.…”

Section: Manufacturingmentioning

confidence: 99%

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When to measure productivity: lessons from manufacturing and supplier‐selection strategies

Phusavat

Jaiwong

Sujitwanich

et al. 2009

Industrial Management &Amp; Data Systems

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Purpose -This study aims to identify the set of circumstances that requires productivity information. It is part of an effort to improve productivity measurement. For this research, when to measure productivity is addressed by linking with manufacturing and supplier-selection strategies. Design/methodology/approach -A survey is developed in order to gain insights into three areas: manufacturing strategies, supplier-selection strategies for maintenance services (MS), and productivity. The development and distribution of a survey are conducted jointly with the Federation of Thai Industries. There are 40 companies completed the survey. The analysis on top executives' opinions, by the correlation analysis, is based on a two-stage manner. The first stage is to list a circumstance that indicates the positive relationships between manufacturing and supplier-selection strategies. The second stage is to match each circumstance with productivity information. Findings -Altogether, they are nine circumstances that need productivity information. For example, when delivery is selected as a manufacturing strategy and quality is chosen as a supplier-selection strategy for MS, productivity measurement is required for an effective management process. Practical implications -Awareness of the relationship between strategic decisions and productivity information helps strengthen performance measurement and subsequently a management process. A strong management process can drive organizational policies and objectives. Originality/value -The more insights into when to measure productivity have been urged by several prominent researchers. A research methodology in this study is also perceived to be useful for possible future applications.

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Section: Indicated Informationmentioning

confidence: 99%

Section: Manufacturingmentioning

confidence: 99%

When to measure productivity: lessons from manufacturing and supplier‐selection strategies

Phusavat

Jaiwong

Sujitwanich

et al. 2009

Industrial Management &Amp; Data Systems

View full text Add to dashboard Cite

show abstract

“…Geographical proximity and cultural similarities between cities are helpful in promoting innovation diffusion at a faster speed and lower cost. Long‐term cooperation in the UA can mitigate the barriers between cities, thereby accelerating the transfer of innovation and decreasing the exchange cost (Xie & Du, ). Consequently, innovation development in a whole UA is greater than the sum of those of its cities benefiting from the positive spatial spillover (Meijers, ; Xie, ).…”

Section: Introductionmentioning

confidence: 99%

Innovation efficiency and spatial spillover in urban agglomerations: A case of the Beijing‐Tianjin‐Hebei, the Yangtze River Delta, and the Pearl River Delta

et al. 2019

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Based on panel data of innovation inputs and outputs in 53 cities of the three major Chinese urban agglomerations (UAs) spanning the 2001–2015 period, this study examines the influence of the spatial spillover effect among cities on innovation efficiency in UAs using the SFA method and a spatial econometric model. Three main conclusions can be draw from the empirical results. First, the innovation efficiency in the three UAs has increased over the research period, but there is enormous potential for improvement. Second, owing to the close socioeconomic linkages and the flow of innovation resources, there is a significantly positive spatial spillover effect between cities on innovation efficiency in the three UAs. In other words, innovation efficiency in a local city was positively influenced by the other cities in the UA. Particularly, the innovation efficiency in a local city is influenced by factors related to not only the city itself but also other cities in the UA. Third, as the geographical distance increases, the spillover effect on innovation efficiency shows nonlinear variations, indicating that the excessive expansion in UAs may not be attributed to innovation development.

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ICT risk for government financial management information system

Phusavat

Anussornnitisarn

Sukhasem

et al. 2010

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Innovation system of a metropolitan region: a case study of the Yangtze River Delta

Cited by 3 publications

References 6 publications

When to measure productivity: lessons from manufacturing and supplier‐selection strategies

When to measure productivity: lessons from manufacturing and supplier‐selection strategies

Innovation efficiency and spatial spillover in urban agglomerations: A case of the Beijing‐Tianjin‐Hebei, the Yangtze River Delta, and the Pearl River Delta

ICT risk for government financial management information system

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