Clusters Of Firms Research Articles

Learning and capability building in firms of a developing economy: A study of Ludhiana machine tools manufacturing cluster

Frontier and laggard firms are always engaged in the process of building capabilities through continuous ‘learning’ to compete in the technologically driven world. Firms focus on ‘learning by Doing, Using and Interacting’ (DUI) and/ or ‘learning by Science, Technology, and Innovation’ (STI) modes. Usually, in the initial stages, firms learn through the DUI mode; subsequently they upgrade through combining DUI with the STI mode of learning, followed with an advanced stage where they increasingly invest in the STI mode of learning. In this context, it is important to determine how ‘learning’ happens within the clustered firms in a developing economy. Therefore, we have taken the case of machine-tools firms located in the district of Ludhiana in the north Indian state of Punjab. We draw data through self-structured questionnaires from 101 machine-tools manufacturing firms and employed exploratory factor analysis to identify the factors through which the industrial advances are ‘learned’ by the firms. It was found that in the sample firms the five important factors that affect ‘learning’ are ‘networking’, ‘imitation’, ‘industrial institutions’, ‘customer feedback’ and ‘codified knowledge’, in that order of the importance. It was observed that the firms are mainly, ‘technology adopters’ and ‘technology modifiers’ rather than ‘technology developers’.

Contribution of female inventors to technological collaboration between high-tech firms and university in close proximity: Effect of innovative firm's characteristics

Understanding the patterns of innovative technological collaboration between universities and clusters of high-tech firms, along with the involvement of female inventors, is crucial for both regional and national development. Here, we explore the technological collaboration between Silicon Fen (SF) firms and University of Cambridge (UoC) as a cluster of high-tech businesses and a main research university located in close proximity, respectively, focusing on the involvement of female inventors, based on the evaluation of join patent ownership, and examination of technological collaboration strength (TCS), with respect to the characteristics of firms such as age, size and sector. A quantitative bibliometric approach is utilised to analyse more than 93,000 patents generated by UoC and SF firms. According to the results obtained, smaller and older businesses exhibit greater collaboration bonds with the university, accommodating a greater proportion of collaborative female inventors. Pharma/Biotech sector of Silicon Fen has a greatest value of TCS (1.6 × 10–2), and accommodates the greatest ratio of female inventors (20.8 %). Our findings suggest the need to encourage younger and larger businesses, and those beyond the Pharma/Biotech sector to involve more female inventors in their technological collaboration with university, given that university policies can have a positive impact in addressing the gender gap in technology and innovation. Theoretical and managerial implications of the results are discussed.

Emerging industry classification based on BERT model

Accurate industry classification is central to economic analysis and policy making. Current classification systems, while foundational, exhibit limitations in the face of the exponential growth of big data. These limitations include subjectivity, leading to inconsistencies and misclassifications. To overcome these shortcomings, this paper focuses on utilizing the BERT model for classifying emerging industries through the identification of salient attributes within business descriptions. The proposed method identifies clusters of firms within distinct industries, thereby transcending the restrictions inherent in existing classification systems. The model exhibits an impressive degree of precision in categorizing business descriptions, achieving accuracy rates spanning from 84.11% to 99.66% across all 16 industry classifications. This research enriches the field of industry classification literature through a practical examination of the efficacy of machine learning techniques. Our experiments achieved strong performance, highlighting the effectiveness of the BERT model in accurately classifying and identifying emerging industries, providing valuable insights for industry analysts and policymakers.

How Innovative Activities Impact Firm Performances in Latecomer Countries? An Analysis of Five Manufacturing Clusters from Indian Punjab

Firms engage in innovative activities, either to maintain the status quo or to catch up with the front-runners. Innovation is difficult to comprehend as it may include efforts to introduce something ‘new to the world’ or it may include simply the efforts to introduce something ‘new to the firm’. It is equally difficult to comprehend how the clustered firms located in latecomer countries are coping with the fast technological changes happening within the industry at the global level. Therefore, taking the case of five manufacturing clusters belonging to the Indian state of Punjab, an attempt is made to comprehend the impact of innovative activities on firm performances. We have done a survey for collecting the primary data for different variables reflecting four types of innovations and four types of performance indicators from the firms belonging to bicycles, hand tools & machine tools, pharmaceuticals, sports goods and textile clusters located in the north Indian state of Punjab. The focus on different clusters belonging to a particular region was done with intent to control the broad social, economic, cultural, political and historical aspects of the different clusters. Estimating the structural equation model with partial least-squares method, we found that the impact of process innovation, organizational innovation and marketing innovation is significant for firm innovative performances, production performance, market performance and financial performance. Specifically, we found that the introduction of new machines with advanced production systems, improvements in the manner of doing routine activities, improving product quality and modernization of human management systems within the firms have a positive impact on firm performance.

Analyst network centrality, forecast accuracy, and persistent influence

ABSTRACT This paper explores how analysts’ forecasting behaviour is related to their centrality within a dynamic information network. In this network, analysts who issued coverage reports on the same listed firms in clusters are connected. The social learning hypothesis and social capital theory suggest that financial analysts could learn from other analyst forecasts and obtain information from analyst reports. Employing a dynamic complex network methodology, we focus on analysts’ network centrality – degree, betweenness, and closeness – to represent their information access based on a sample of 819,539 analyst forecasts in the Chinese A-share market from 2018 to 2022. Our findings suggest that analysts with more central positions in the network produce more accurate earnings-per-share forecasts and have a longer persistent influence on other analysts. Our results support the perspective that the diffusion of information among analysts affects their forecasts and reporting behaviour.

Exploring innovation and collaboration in the leather processing industry through the case study of the KIWANGO Leather Cluster

In the era of Industry 4.0, fostering innovation through strong collaboration among universities, industry, and government is crucial. However, the Tanzanian economy has faced challenges due to, among others, weak links between these entities. To address this, Sida initiated the Innovation Systems and Cluster Development Program (ISCP-Tz) in partnership with the University of Dar es Salaam. This was followed by a program at COSTECH focused on fostering innovation for socio-economic development. As part of these programs, 15 clusters, including KIWANGO Leather, were selected for documentation of their experiences. KIWANGO Leather exemplifies successful collaboration between cluster firms, the university, local government, and research institutions. Operationalizing guidelines for collaboration led to cooperative innovations, knowledge exchange, internships, and long-term partnerships established through Memorandum of Understanding (MoU). The cluster's experiences highlight a less-linear, inclusive innovation process with positive outcomes. Thus, this paper not only illustrates a less linear, inclusive innovation process, but also its results can motivate actors in emerging innovation ecosystems in the Global South to adopt and scale up suggested approaches for knowledge co-creation benefitting sustainable development. By adopting these approaches and fostering collaborative networks, countries can leverage their resources and expertise to drive innovation, create economic growth, and address societal challenges.

Tech hubs within cities—determinants and dynamics

AbstractThis paper explores the microgeographic determinants of firm birth activity and relocation patterns in the digital economy simultaneously. The study investigates the spatial dynamics of young firms within Berlin, Hamburg, and Munich using geo-coded data of firm births and relocation from 2009 to 2016 aggregated at a 1 × 1 km2 grid level. The panel fixed effect regression models examine the impact of changes within persistent city structures on the location choices using several control variables. The findings suggest that firm clustering, commercial building density, and higher rent prices positively influence firm births, while the impact of knowledge institutions in the neighborhood is mixed. Relocation patterns highlight the role of proximity to competitors, with higher prices in areas not deterring relocations. These findings contribute to understanding firm location choices within cities by considering the two avenues of growth and highlight the future need for further investigations on the microgeography of firm growth dynamics.

An empirical examination of financial performance and distress profiles during COVID-19: the case of fishery and food production firms in Vietnam

Purpose Financial ratios are often used to classify firms into different clusters of financial performance. This study aims to classify firms using financial ratios with advanced techniques and identify the transition matrix of firms moving clusters during the COVID-19 period. Design/methodology/approach This study uses compositional data (CoDa) analysis based on existing clustering methods with transformed data by weighted logarithms of financial ratios. The data include 66 listed firms in Vietnam’s food and beverage and fishery sectors over a three-year period from 2019 to 2021, including the COVID-19 period. Findings These firms can be classified into three clusters of distinctive characteristics, which can serve as benchmarks for solvency and profitability. The results also show the migration from one cluster to another during the COVID-19 pandemic, allowing for the calculation of the transition probability or the transition matrix. Practical implications The findings indicate three distinct clusters (good, average and below-average firm performance) that can help financial analysts, accountants, investors and other strategic decision-makers in making informed choices. Originality/value Clustering firms with their financial ratios often suffer from various limitations, such as ratio choices, skewed distributions, outliers and redundancy. This study is motivated by a weighted CoDa approach that addresses these issues. This method can be extended to classify firms in multiple sectors or other emerging markets.

Inertia, Progress, or Regress? Observing and Explaining Heterogenous Tech Firm Demographic Diversity Trajectories

Tech firms are under strong pressure to increase their demographic diversity. While activists and scholars have tended to treat the sector as homogenously hostile to women and racialized minorities, recent theory on organizational inequalities stresses heterogeneity in firm-level inequality regimes. Beginning with an inductive exploration of variation in executive, managerial, and professional workforce trajectories, we find that between 2008 and 2016 most Tech firms show little change, but that there are also significant clusters of firms that were becoming either much more or much less diverse for all three occupational levels. We model these trajectories as a function of firm visibility, the regulation of federal contractors by the U.S. Department of Labor, and leadership composition. Multinomial logistic regression models show that firms with an increasing (decreasing) diversity pattern in managerial and executive positions are also more likely to become more (less) diverse in their much more numerous professional jobs. Managers are more influential than executive in this regard. Regulatory pressure is associated with increased executive diversity trajectories, but not with managerial or professional trajectories. We conclude that increased Tech diversity is possible but requires leadership, particularly at the middle manager level. In addition, regulatory and visibility pressures primarily produce symbolic shuffles in top jobs.

Poverty reduction and migration in rural Vietnam: Role of local firm clusters

AbstractFirm clusters are considered as a contributing factor to local economic development. However, there are limited studies on the effect of firm clusters on the well‐being of rural communities, particularly in terms of income improvement, poverty reduction, and migration. Our research aims to shed light on these relationships at both the household and commune levels. For empirical analysis, we employ the propensity score matching method to mitigate endogeneity bias. Our results reveal the role of firm clusters in increasing income and reducing poverty. Firm clusters also contribute to decreasing labor emigration and attracting immigrants. However, the magnitude of these impacts is relatively small, with moderate effects on income and modest effects on poverty and migration. In particular, firm clusters reduce the commune poverty rate by around 2.36%–2.51% and enhance household annual income by approximately 16.46–17.08 million VND (725–752 USD). Furthermore, analyses at the household level highlight the significance of larger clusters in improving household income. Our research underscores policy implications for rural development with a specific emphasis on firm clusters.

Unveiling the impact of foreign investment entry in industrial clusters: the case of Castelló and Sassuolo

ABSTRACT This paper explores the impact of foreign investment, through acquisitions and mergers of local firms, on leading industrial clusters. While previous research has highlighted the increasing involvement of cluster firms in internationalization and knowledge globalization, the role of foreign investment requires further investigation. Power asymmetries between MNEs and partner firms are prevalent in global value chains, joint ventures, and strategic alliances, shaping the contemporary global economy. By analysing two clusters specialized in ceramic tile production (Castelló, Spain, and Sassuolo, Italy), this study aims to evaluate the impact of foreign investment on leading clusters, specifically distinguishing between multinational enterprises (MNEs) and investment funds. The research examines the perceived effects through a qualitative analysis, capturing the subjective impressions of local actors involved in acquired firms, independent local firms, technological suppliers, and supporting institutions. This paper contributes to the literature by addressing contradictory findings and providing insights into the balance between knowledge absorption and spillovers from MNEs or investment funds to local firms.

Small and Medium Enterprises Amidst the Pandemic and Reopening: Digital Edge and Transformation

Using administrative universal business registration data as well as primary offline and online surveys of small businesses (including unregistered self-employments) in China, we examine (i) whether digitization helps small and medium enterprises (SMEs) better cope with the COVID-19 pandemic and (ii) whether the pandemic has spurred digital technology adoption. We document significant economic benefits of digitization in increasing SMEs’ resilience against such a large shock, as seen through mitigated demand decline, sustainable cash flow, ability to quickly reopen, and positive outlook for growth. After the January 2020 lockdown, firm entries exhibited a V-shaped pattern, with entries of e-commerce firms experiencing a less pronounced immediate drop and a quicker rebound. Moreover, the pandemic has accelerated the digital transformation of existing firms and the industry in multiple dimensions (e.g., altering operation scope to include e-commerce, allowing remote work, and adopting electronic information systems). The effect persists more than one year after reopening, and it is more pronounced for certain sectors, firms in industrial clusters, and areas with more digital inclusion but less financial efficiency, constituting initial evidence for the long-term impact of the pandemic and the supposedly transitory mitigation policies. This paper was accepted by David Simchi-Levi, finance. Funding: This research was funded in part by the China Natural Science Foundation [Grants 71874008, 71441008, 71873121, and 72192844], Peking University, the Kauffman Foundation [Junior Fellowship], and the FinTech Chair at Paris–Dauphine University–Université Paris Sciences et Lettres. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.02424 .

Trade in services related to intangibles and the profit shifting hypothesis

This paper focuses on the international trade in services related to intangible assets and intellectual property products (IPP), and it explores to what extent they might be used as a channel to shift the profits of multinational firms to tax havens. Using survey data on Italian firms, we first provide a geographical and sectoral analysis of Italy's trade in IPP services. We then estimate the amount of profit shifted abroad by foreign‐owned firms in our sample, applying at various levels of aggregation a methodology recently put forward in the literature. Finally, we look for a correlation at the firm level between estimated shifted profits and imports of IPP services. We find that while the overall correlation is very low, there is a small cluster of firms displaying a positive correlation between these two variables.

Optimizing digital transformation paths for industrial clusters: Insights from a simulation

Digital technologies have revolutionised industrial clusters, implementing digital transformation without careful consideration can lead to higher risks and ineffective investments. However, the existing research often focuses on enterprises in a specific position, whereas the entire supply chain or end-to-end research is rarely conducted. To fill this gap, this study proposes a sectoral innovation system. It conducts a simulation model to study the digital transformation process by considering the behaviour, knowledge learning, and innovation of upstream and downstream enterprises in different cluster types. The simulation dynamically presents production and productivity changes during the transformation process of the entire industrial cluster. The results reveal that an orderly transformation path is the most effective for Marshallian clusters, whereas a simultaneous transformation works best for central satellite clusters. In addition, the social network simulation before and after the digital transformation of the two industrial clusters shows that enterprises in central-satellite clusters communicate more frequently during digital transformation, which is ultimately conducive to a better performance of the digital transformation of industrial clusters. These findings emphasise the need for tailored digital transformation strategies based on cluster type to maximise benefits, underscoring the importance of leading firms in industrial clusters. It also guides the government's industrial policy formulation and management enlightenment regarding the digital transformation of enterprises.

Demonstration of enhanced long-range cosmic time synchronization for wireless and secure dissemination of standard time

Accurate traceability of time is prerequisite to the proper functioning of many necessary aspects of our modern life including making financial transactions, managing automated technology and navigating the transport of goods and human beings. One of the most reliable international time references is the Coordinated Universal Time (UTC) that can be distributed wirelessly in principle. However, this wireless option is currently limited to GPS and other global navigation satellite systems. GPS signals are weak and easily affected by environmental conditions. Moreover, since GPS signals are unencrypted, the possibility of a signal spoofing attack remains a continuous threat. Prior works showed the potential of the alternative wireless time synchronization technique called Cosmic Time Synchronization (CTS), in which, clocks are located 50 m apart were wirelessly synchronized with a sub-microsecond level accuracy, and its operation time was limited to 20 min. However, for the actual implementation of CTS to real-life situations, these distance and stability values are not sufficient. In this study, we constructed a dedicated CTS facility and conducted a long-haul (180 m) CTS demonstration. As a result, it was verified that this long-range CTS is capable of maintaining stable sub-microsecond time synchronization for 3 days with a granularity of 148.8 ns (SD) and an offset of 22.97 ns. Since the current version of CTS can now operate over an area that has been enlarged by more than one order of magnitude, it is possible to utilize for more diverse applications, and the application to a banking synchronization system is proposed. As a case study, it is shown that CTS now has the capability to offer wireless time synchronization service to large clusters of financial firms in large cities. With its accurate time dissemination (the metrological traceability to UTC), its reasonable cost, and its hack-proof, stable design, this latest CTS model has the capacity to improve the accuracy of timing for a wide variety of sectors.

Export motivation and clustering of Greek yogurt firms

Export motivation and clustering of Greek yogurt firms

Contrasting innovation dynamics of professional-technological knowledge intensive business services in metropolitan areas

Formulation of the problem. The study examines knowledge-intensive business services (KIBS) firms' capability to access, process, and transform information into innovation. KIBS are defined as facilitators, carriers of knowledge, and sources of innovation for other sectors. KIBS play an important role in the production, use, and transfer of knowledge to the manufacturing sector. KIBS activities do not demonstrate a uniform structure within themselves, so a dual classification as professional services (P-KIBS) and technological services (T-KIBS) based on functioning and input has been developed. KIBS activities are concentrated in large cities. Major cities or capitals have well-developed infrastructure, public administration centers, advanced social activities, and numerous research institutes and universities. All of them attract a highly skilled population. Regarding metropolitan city economic growth, KIBS stand out because of their high added value, high income, high innovation returns, and high financial capacity, and they contribute to development. The purpose. The present study aims to reveal the innovative capacities and dynamics of P-KIBS and T-KIBS firms operating in the metropolitan area of Ankara, Turkey's capital city. To reach this aim, Turkey's capital city Ankara is analyzed by using the results of a questionnaire applied to 410 small and medium-sized (SMEs) KIBS firms, 146 of which are P-KIBS firms and other 264 are T-KIBS firms. Methods. In the course of the research and preparation of the article, the authors used several scientific methods, both philosophical and general scientific, as well as specific scientific methods. In particular, the methods of analysis and synthesis, induction and hypothetical-deductive method, mathematical-statistical and spatial analysis, methods of grouping and classification, questionnaires and surveys, etc., were used. The results. There are notable differences between the P-KIBS and T-KIBS firms, considering their spatial distribution patterns and the dynamics of their innovation processes. The spatial distribution patterns of the KIBS firms were revealed. While T-KIBS activities demonstrate a spatial clustering tendency independent of the CBD, the P-KIBS firms prefer to locate within the CBD or its vicinity. KIBS sectors generally prefer to be situated by high-income residents, new settlements, secure and prestigious areas close to large public institutions such as ministries and general directorates. It was revealed that the T-KIBS firms are most densely located in the CBD and newly developing business districts of Balgat and Söğütözü, and in the Technology Development Zones of Ankara. P-KIBS firms, on the other hand, are more widely spread in the Çankaya and Yenimahalle districts. It was found that advances in information and communication technologies have a varied impact on the location selection preferences of P-KIBS and T-KIBS enterprises. According to the research results, the factors influencing the clustering of P-KIBS companies and T-KIBS firms were identified and determined. There is a significant relationship between the innovative P-KIBS and T-KIBS firms and their collaboration with other institutions. As a result of the the study, it has been determined that there is a significant relationship between collaboration, R&D, intrafirm and extrafirm social relationships on the innovation of KIBS firms and also contrasting innovation dynamics related to different classes of KIBS in metropolitan areas.

Innovation systems, value chains and industrial clusters in developing economies: Case of Jalandhar’s sports goods industry

The paper explores the relationship between innovation systems (IS) and participation in value chains (VCs) to understand the challenges concerning upgrading of an industrial cluster in a developing country. It is argued that the inter-linkages of various actors, organizations and institutions at one or more levels (MLs), viz., micro level (local), meso level (national) and macro level (global) led the firms in the industrial cluster to participate in one or more VCs, i.e., local, regional and global VCs, upgrading the cluster over time, which we termed as ‘Cluster Upgrading System’ (CUS). In this context, a case of one of the oldest industrial cluster producing sports goods in Jalandhar, India is examined. The analysis is based upon the information gathered through a primary survey of 45 firms. It was found that the cluster is largely labour intensive in nature and is facing challenges of competing with both low-cost clusters and technological advanced clusters, raising fears of it slipping into a low value-added trap. We found a lack of inter-linkages amongst firms, and their relationship with training and financial institutes that hampers mutual learning for upgrading the whole cluster, indicating some necessary policy implications.

Risk Return Analysis of FTSE Listed Select Stocks with FTSE100 Index

This paper analyses the stock returns of FTSE 100 and a sample of selected companies within the index to determine the existence of interdependence and magnitude of the same. The companies are selectively chosen from certain primary sectors based on their influence on the economy. The idea is to understand if large firms have significant effect on the index. The study involves statistical analysis representing data over a 10-year period spanning 1st November 2011 to 31st October 2021), the data points include adjusted closing values of the index and the selected companies. Correlation and regression analysis is performed by taking the index as the dependent variable and the companies as the independent variable. The results are then analyzed from a variety of perspectives including Skewness, Kurtosis, Correlation Coefficients and Coefficient of Determination. Skewness and Kurtosis reveals the performance of returns as compared to the average. The results of the study reveal a net positive correlation is observed between the index and the companies. additionally, the regression analysis results showcase how certain sectors like defense have a significant relation with the index while others like supermarkets do not. Other interesting facts uncovered relate to how a certain cluster of firms compare as opposed to a single firm when analyzed in conjunction with the index. The results are summarized to come up with a conclusion on the relationship an index has with its constituents.

Трансформация социально-трудовой сферы под воздействием мегатрендов

The article examines the main consequences of megatrends for the Russian social and labor sphere: the labor market, the personnel management system in Russian organizations, in particular, shows how the Russian historical, political and cultural context leads to differences in the impact of megatrends, outlines practical solutions that Russian companies have implemented in the recruitment and selection process, training and development, organization of labor, motivation and consolidation of personnel management activities within the framework of corporate systems. It is shown that in recent years the Russian practice of personnel management has undergone a complex transformation in response to new technologies and markets, as well as to the changing political and social environment in the country. In a diverse business landscape (characterized by significant diversity in terms of the type of industry, form of ownership and access to resources), a special cluster of firms has formed that adhere to the “investing in people” approach. Companies in this cluster use digitalization and IT technologies to perform key personnel management functions, look for talents for effective management of knowledge workers, revise motivation methods and labor organization, and adjust their business models to solve social, demographic, environmental and other problems.