scholarly journals Emergence of a digital cluster in east London: birth of a new hybrid firm

2019 ◽  
Vol 29 (3) ◽  
pp. 253-266 ◽  
Author(s):  
Graeme Lorenzo Evans
Keyword(s):  
Spatial Data ◽  
Technological Development ◽  
Spatial Data Analysis ◽  
Gis Mapping ◽  
Online Questionnaire ◽  
Location Quotient ◽  
Firm Level ◽  
Local Cluster ◽  
Cluster Theory ◽  
Content Type

PurposeThis paper aims to investigate the composition and geography of an emerging “creative digital” cluster in London, in the context of cluster theory and emerging creative cluster concepts. This argues that this cluster cannot be divorced from the wider regional creative and digital economy and that its inter-dependence with a small number of “content” industries is critical to its formation. The significance of the “creative digital” firm blending design, communications and technological development is highlighted, as is its unique position in enabling such firms to flourish.Design/methodology/approachThe research combines both quantitative with qualitative methods, based on cluster analysis of firm-level business data using GIS mapping software at a regional level; location quotient (LQ) analysis to reveal firm concentration at a local cluster level; an online questionnaire survey of firms within this cluster; participant observation of firm meet-ups over a three-year period; and face-to-face interviews with a sample of firms/owners.FindingsThe evidence generated from this research confirms the distinctive nature of this digital cluster and the benefits of co-location in an industrial district with proximities to a range of advanced producer services and cultural content provision. This has revealed an emerging “techno-creative habitus” (Scott 2010), which has been able to take advantage of market fluidity through a network of communities of interest firms, which have reshaped an existing global hub locally anchored by a highly porous locale.Originality/valueThe research is novel in combining spatial data analysis with qualitative research into firm behaviour and place-based factors that support the growth of this cluster. This has revealed new insights into the hybrid nature of tech firms that integrate content with both hardware and software applications and who innovate and grow through inter-personal cluster networks. This contributes to cluster theory and extends the range of proximities – social, institutional and cultural – that enhance the geographic advantages of clustering in this case.

Industry 4.0 and clusters: complementaries or substitutes in firm’s knowledge creation?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nils Grashof ◽  
Alexander Kopka ◽  
Colin Wessendorf ◽  
Dirk Fornahl
Keyword(s):  
Industry 4.0 ◽  
Substitution Effect ◽  
Interaction Effects ◽  
Ordinary Least Squares ◽  
Knowledge Generation ◽  
Firm Level ◽  
Cluster Theory ◽  
Content Type ◽  
Industrial Iot ◽  
Key Enabling Technologies

Purpose This paper aims to show the interaction effects between clusters and cluster-specific attributes and the industrial internet of things (IoT) knowledge of a firm on the innovativeness of firms. Cluster theory and the concept of key enabling technologies are linked to test their effect on a firm’s incremental and radical knowledge generation. Design/methodology/approach Quantitative approach at the firm-level. By combining several data sources (e.g. ORBIS, PATSTAT and German subsidy catalogue) the paper relies on a unique database encompassing 8,347 firms in Germany. Ordinary least squares (OLS)-regression techniques are used for data analysis. Findings Industrial IoT is an important driver of radical patents, mediated positively by firm size. For incremental knowledge, a substitution effect occurs between a cluster and IoT effects, which is bigger for larger firms and dependent on cluster attributes and firms’ outside connections. Research limitations/implications The paper opens up new research paths considering long-term disruptive effects of the industrial IoT compared to short-term effects on the innovativeness of firms within clusters. Additionally, it enables further research enriching the discussion about cluster attributes and how these affect ongoing processes. Practical implications Linking cluster theory and policy with Industry 4.0 raises awareness for being considerate in terms of funding and scrutinising one-size-fits-all approaches. Originality/value Connecting the concepts of a cluster and advanced manufacturing technologies as a proxy for industrial IoT, specifically focussing on both radical and incremental innovations is a new approach. Especially, taking into account the interaction effects between cluster attributes and the influence of industrial IoT on the innovativeness of firms.

Cluster identification

2019 ◽  
Vol 29 (4) ◽  
pp. 401-415
Author(s):  
Reinaldo Belickas Manzini ◽  
Di Serio Carlos Luiz
Keyword(s):  
Spatial Data ◽  
Regional Analysis ◽  
Spatial Association ◽  
Spatial Dimension ◽  
Spatial Data Analysis ◽  
Industry Concentration ◽  
Spatial Effects ◽  
Temporal Dimension ◽  
Content Type ◽  
Concentration Statistics

Purpose This paper aims to contribute to the approaches based on traditional industry concentration statistics for identifying clusters by complementing them with the techniques of exploratory spatial data analysis (ESDA). Design/methodology/approach Using a sample with 34,500 observations retrieved from the social information annual report released by Brazil Ministry of Labor and Employment, the methodology was designed to make a comparison between the application of industry concentration statistics and ESDA statistics. Findings As the results show, the geographic distribution measures proved to be fundamental for longitudinal studies on regional dynamics and industrial agglomerations, and the local indicator of spatial association statistic tends to overcome the limitation of the industry concentration approach. Research limitations/implications In the period considered, due to economic, structural and circumstantial questions, activities linked to the transformation industry have been losing ground in the value creation process in Brazil. In this sense, the study of other industries may generate other types of insights that should be considered in the process of regional development. Originality/value This paper offers a critical analysis of empirical approaches and methodological advances with an emphasis on the treatment of special effects: spatial dependence, spatial heterogeneity and spatial scale. However, the regional dynamic presents a temporal dimension and a spatial dimension. The role of space has increasingly attracted attention in the analysis of economic changes. This work has identified opportunities for incorporating spatial effects in regional analysis over time.

Video data image retrieval using – BRICH

2017 ◽  
Vol 14 (4) ◽  
pp. 318-323
Author(s):  
Saravanan Devaraj
Keyword(s):  
Data Mining ◽  
Image Retrieval ◽  
Spatial Data ◽  
Clustering Algorithms ◽  
Video Data ◽  
Spatial Data Analysis ◽  
Multidimensional Data ◽  
Economic Science ◽  
Data Set ◽  
Content Type

Purpose Data mining is the process of detecting knowledge from a given huge data set. Among the data set, multimedia is the data which contains diverse data such as audio, video, image, text and motion. In this growing field of video data, mining the video data plays vital role in the field of video data mining. In video data mining, video data are grouped into frames. In this vast amount of video frames, the fast retrieval of needed information is important one. This paper aims to propose a Birch-based clustering method for content-based image retrieval. Design/methodology/approach In image retrieval system, image segmentation plays a very important role. A text file, normally, is divided into sections, that is, piece, sentences, word and character for this information which are organized and indexed effectively like in a video, the information is dynamic in nature and this information is converted to static for easy retrieval. For this, video files are divided into a number of frames or segments. After the segmentation process, images are trained for retrieval process, and from these, unwanted images are removed from the data set. The noise or unwanted image removal pseudo-code is shown below. In the code image, pixel value represents the value of the difference between the two adjacent image pixel values. By assuming a threshold for the image value, the duplicate images are found. After finding the duplicate image, it is removed from the data set. Clustering is used in many applications as a stand-alone tool to get insight into data distribution and as a pre-processing step for other algorithms (Ester et al., 1996). Specifically, it is used in pattern recognition, spatial data analysis, image processing, economic science document classification, etc. Hierarchical clustering algorithms are classified as agglomerative or divisive. BRICH uses clustering attribute (CA) and clustering feature hierarchy (CA_Hierarchy) for the formation of clusters. It perform multidimensional data objects. Every BRICH algorithm based on the memory-oriented information, that is, memory constrains, is involved in the processing of the data sets. This information is represented in Figures 6-10. For forming clusters, they use the amount of object in the cluster (A), the sum of all points in the data set (S) and need the square value of the all objects (P). Findings The proposed technique brings an effective result for cluster formation. Originality/value BRICH uses a novel approach to model the degree of inter-connectivity and closeness between each pair of clusters that takes into account the internal characteristics of the clusters themselves.

Financial inclusion across major Indian states: some spatial panel econometric evidence

2021 ◽  
Vol 48 (3) ◽  
pp. 419-436
Author(s):  
Kamal Sai Sadharma Erra ◽  
Debashis Acharya
Keyword(s):  
Spatial Data ◽  
Financial Inclusion ◽  
Spatial Data Analysis ◽  
Indian States ◽  
Content Type ◽  
Spatial Panel ◽  
Econometric Evidence ◽  
Spatial Convergence ◽  
Banking Institutions ◽  
And Gender

PurposeThis paper aims to test for spatial convergence in financial inclusion across major Indian states and union territories.Design/methodology/approachAfter initially building an Index of Financial Inclusion (IFI) for major Indian states between 2003 and 2016, exploratory spatial data analysis (ESDA) is employed to draw inferences about mean and variance of IFI. The paper then seeks to confirm the ESDA results through spatial panel regression techniques. Finally, spatial results are correlated with results from aspatial convergence measures.FindingsThe study finds that there is no evidence of spatial convergence in financial inclusion over the study period, suggesting that those states that were relatively less financially included remained so through the study period. The study also asserts the relevance of certain important determinants, namely, per capita income, infrastructure, industrialization and gender.Research limitations/implicationsThis study has two limitations. First, only banking institutions are considered in measuring financial inclusion. Second, due to lack of a consistent indicator of gender participation across states, we had to employ sex ratio as a proxy.Practical implicationsThe study suggests that policies to expand financial inclusion in Indian states, especially those with low inclusion levels are likely to benefit neighbouring states also, thereby accelerating the financial inclusion drive across states.Originality/valueThe study is a first in the Indian context to estimate the spatial dependence of financial inclusion and provides relevant implications for policymakers and bankers to target financial inclusion schemes in backward states.

Understanding decoupling in response to corporate governance reform pressures

2015 ◽  
Vol 23 (4) ◽  
pp. 369-382 ◽  
Author(s):  
Mario Krenn
Keyword(s):  
Corporate Governance ◽  
Design Methodology ◽  
Good Governance ◽  
Regulatory Change ◽  
Compliance Monitoring ◽  
Governance Reform ◽  
Firm Level ◽  
Content Type ◽  
Good Corporate Governance ◽  
Actual Use

Purpose – The purpose of this article is to explain under what circumstances firm-level adoption of codes of good corporate governance will more likely be superficial rather than substantive in nature. The article contains lessons for any agency or country that attempts to implement deep and lasting changes in corporate governance via codes of good corporate governance. Design/methodology/approach – The article reviews the literature on compliance with codes of good corporate governance and develops a conceptual model to explain why some firms that have formally adopted a code of good governance decouple this policy from its actual use. Findings – Decoupling in response to the issuance of codes of good corporate governance will be more attractive to firms and also more sustainable under the following conditions: firms’ compliance costs are relatively high firms’ costs of outright and visible non-compliance are relatively high and outsiders’ compliance monitoring costs are relatively high. Originality/value – The article contributes to the debate on compliance and convergence and provides policymakers with a conceptual framework for assessing the likelihood of successful regulatory change in corporate governance.

scholarly journals Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model

2021 ◽  
Vol 18 (3) ◽  
pp. 1056
Author(s):  
Yu Chen ◽  
Mengke Zhu ◽  
Qian Zhou ◽  
Yurong Qiao
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Correlation ◽  
Spatial Data ◽  
Central Area ◽  
Urban System ◽  
Entropy Method ◽  
Driving Factors ◽  
Spatial Data Analysis ◽  
Eastern Region ◽  
Urban Resilience

Urban resilience in the context of COVID-19 epidemic refers to the ability of an urban system to resist, absorb, adapt and recover from danger in time to hedge its impact when confronted with external shocks such as epidemic, which is also a capability that must be strengthened for urban development in the context of normal epidemic. Based on the multi-dimensional perspective, entropy method and exploratory spatial data analysis (ESDA) are used to analyze the spatiotemporal evolution characteristics of urban resilience of 281 cities of China from 2011 to 2018, and MGWR model is used to discuss the driving factors affecting the development of urban resilience. It is found that: (1) The urban resilience and sub-resilience show a continuous decline in time, with no obvious sign of convergence, while the spatial agglomeration effect shows an increasing trend year by year. (2) The spatial heterogeneity of urban resilience is significant, with obvious distribution characteristics of “high in east and low in west”. Urban resilience in the east, the central and the west are quite different in terms of development structure and spatial correlation. The eastern region is dominated by the “three-core driving mode”, and the urban resilience shows a significant positive spatial correlation; the central area is a “rectangular structure”, which is also spatially positively correlated; The western region is a “pyramid structure” with significant negative spatial correlation. (3) The spatial heterogeneity of the driving factors is significant, and they have different impact scales on the urban resilience development. The market capacity is the largest impact intensity, while the infrastructure investment is the least impact intensity. On this basis, this paper explores the ways to improve urban resilience in China from different aspects, such as market, technology, finance and government.

Determining the structure of pharmaceutical industry in Iran

2019 ◽  
Vol 13 (1) ◽  
pp. 101-115
Author(s):  
Sara Emamgholipour ◽  
Lotfali Agheli
Keyword(s):  
Pharmaceutical Industry ◽  
Economies Of Scale ◽  
Monopolistic Competition ◽  
Pharmaceutical Market ◽  
Data Availability ◽  
Market Demand ◽  
Firm Level ◽  
Content Type ◽  
Measure Concentration ◽  
Pharmaceutical Industries

Purpose As the pharmaceutical industry is one of the key sectors of the health-care system, the identification of its structure is of particular importance. This paper aims to determine the structure of the pharmaceutical industry in Iran to provide appropriate solutions for pricing and regulation by policymakers. Iran is a growing pharmaceutical market with over $4bn in sales, so the supply side needs to be examined to meet the domestic consumption. Design/methodology/approach This research is a descriptive and retrospective analytical study which examines the Iranian pharmaceutical industry through library studies and using pharmaceutical data of the country’s Food and Drug Administration during 1992-2016. Due to data availability in firm level, the concentration ratio of N leading firms and the Herfindahl–Hirschman index are used to measure the concentration of the pharmaceutical market in 2014 and 2016. Findings The results show that pharmaceutical manufacturing, importing companies and distributing companies play roles in monopolistic competition market, loose oligopoly market and oligopoly market, respectively. For all companies, the magnitudes of Herfindahl–Hirschman indices indicate non-competitive settings. As a result, these companies set their own prices, and market demand affects their sales. In addition, demand for medicines is shaped in the form of supply-induced demand. Research limitations/implications This research was accomplished with no computational limitation. However, it was confined to only one country, one industry and the mentioned period of study. Practical implications The pharmaceutical manufacturers have no influence on medicine prices, and government pricing regulations lessen the market power of such market agents. However, the easy entry to and exit from market stimulate producers to participate in manufacturing activities. The pharmaceutical importers may expand their imports in response to entry new actors; however, the new entrants weaken the coordination on pricing decisions. Social implications As pharmaceutical distributers act in an oligopoly market, they can collude, reduce competition and lower the welfare of pharmaceutical consumers. In such conditions, high investment requirements and economies of scale may discourage the entry of new firms. Originality/value Although there are various studies on market structure in non-pharmaceutical industries, this study is a new effort to measure concentration in the Iranian pharmaceutical market and to determine its structure.

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