Agglomeration and clustering over the industry life cycle: Toward a dynamic model of geographic concentration

Liang, Wang; Madhok, Anoop; Li, Stan Xiao

doi:10.1002/smj.2141

Cited by 78 publications

(68 citation statements)

References 69 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Since the competitive variables have a geographic bias, as shown in the measurement section of this study, one can infer that this represents significantly within the analysis. Geographic concentration and growth have been proven drivers of growth in Europe (Martin & Ottaviano, 1999), and empirical studies prove that this is a driver for the structure of the industry's life cycle (Wang, Madhok & Xiao Li, 2014), and its competitiveness (Maskell & Malmberg, 1999).…”

Section: Results Analysismentioning

confidence: 99%

Relationship between competitiveness and operational and financial performance of firms: An exploratory study on the European brewing industry

Zanotti

Reyes

Fernández

2018

View full text Add to dashboard Cite

Purpose: The purpose of this paper is to provide the underlying constructs that connect the operational and financial performance of firms with the competitive environment surrounding the brewing industry in Europe. Design/methodology:The selected method of study is exploratory and confirmatory factor analysis, and subsequently applying structural equations modelling. We have sampled 214 brewing companies distributed in over 12 European economies. Findings:The study provides a comparison between different antecent studies, including contextual contrast in both an industry and a methodologic perspective. The study shoes that the competitive construct of the industry is significantly related with the financial performance of firms, however not necesarilly to the operational results. Additionally, the operational structure of the firm does not necesarilly provide significant relationship to the firms' financial results. Research limitations/implications:The research is segmented within the European brewing industry, hence we find potentian geographic delimiations in terms of the conclusions of this paper.Originality/value: Significant relationships between competitive variables and financial performance in the brewing industry remains evasive in research thus far. Additionally, sustained in the potential the brewing industry represents within Europe, it is significant to identify these relationships for readers on both an academic and industrial background.

show abstract

Section: Results Analysismentioning

confidence: 99%

Relationship between competitiveness and operational and financial performance of firms: An exploratory study on the European brewing industry

Zanotti

Reyes

Fernández

2018

View full text Add to dashboard Cite

show abstract

“…The life-stage of companies can impact the co-agglomeration pattern. As hypothesized and proved by Wang et al (2014), the early stage clusters attract more firms to agglomerate and at the mature stage, conversely dispersion forces prevail. In co-agglomeration measurement one could check individually the age of companies and clusters and assess its agglomeration and co-agglomeration degree as related to their life-stage.…”

Section: Firmmentioning

confidence: 62%

Comment to XCL co‐agglomeration index: Distance‐weighted improved DCL index

Kopczewska

2016

Papers in Regional Science

View full text Add to dashboard Cite

Howard, Newman and Tarp have recently developed a new index of co‐agglomeration, XCL, which improves the existing Ellison‐Glaser index. As this new measure is very sensitive to space fragmentation and fails with MAUP, an improvement based on distances between firms is being proposed here. Original Howard's XCL index is based on individual firm data and was constructed as a probabilistic measure. Data aggregation over territories makes it a cluster‐based measure. Proposed here distance‐weighted improvement, DCL index, is to use its potential to become distance‐based measure, resistant to MAUP and robust to space division.

show abstract

“…Additionally, ex ante selection mechanisms could be further investigated by taking into account that both agglomeration and survival of firms may be influenced by idiosyncratic characteristics of the locations (e.g., Hernandez, ), and/or vary according to the stage of the product lifecycle in an industry (Potter & Watts, ; Neffke, Svensson, Boschma, Lundquist, & Olander, ; Wang, Madhok, & Xiao Li, ). However, while this may be an intriguing investigation, examining the temporal boundaries of these mechanisms would require long inter–temporal and cross–sectional series…”

Section: Discussionmentioning

confidence: 99%

Location and survival of MNEs' subsidiaries: Agglomeration and heterogeneity of firms

Mariotti

Mosconi

Piscitello

2019

Strategic Management Journal

View full text Add to dashboard Cite

Research summary Our study provides a quasi–replication of Shaver and Flyer (2000), which was among the first studies that challenged the positive role of agglomeration in determining companies' location choice and performances, thus changing the way management scholars view companies' attitude towards agglomeration forces. We employ the same research design, specification and tests, and a different population, to discuss the generalizability of the original study. Building on the framework of Shaver and Flyer (2000), our findings offer intriguing new empirical evidence highlighting the importance of the differential between entering foreign firms and host country firms as a crucial condition in understanding agglomeration forces and adverse selection mechanisms. Managerial summary Our exercise confirms that agglomeration forces act differently on stronger versus weaker multinational enterprises (MNEs). However, we find that stronger MNEs tend to avoid location in highly specialized areas when they are afraid of knowledge leakages towards host country–based rivals that have enough absorptive capacity to benefit and improve their competitive advantages. Managerial implications are quite relevant. Indeed, when MNEs avoid co–location in highly specialized areas, they also limit their own access to local knowledge and other agglomeration economies, such as supply networks and qualified workforce. Thus, MNEs managers need to design and implement devices that, on the one hand prevent local leakages of their knowledge and, on the other, do not hinder their access to local unique knowledge and resources.

show abstract

Agglomeration and clustering over the industry life cycle: Toward a dynamic model of geographic concentration

Cited by 78 publications

References 69 publications

Relationship between competitiveness and operational and financial performance of firms: An exploratory study on the European brewing industry

Relationship between competitiveness and operational and financial performance of firms: An exploratory study on the European brewing industry

Comment to XCL co‐agglomeration index: Distance‐weighted improved DCL index

Location and survival of MNEs' subsidiaries: Agglomeration and heterogeneity of firms

Contact Info

Product

Resources

About