Analyzing industry stakeholders using open-source competitive intelligence – a case study in the automotive supply industry

Lutz, Corinna Juliane; Bodendorf, Freimut

doi:10.1108/jeim-08-2019-0234

Cited by 8 publications

(4 citation statements)

References 66 publications

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“…Market structures characterized by high competition and simultaneous coopetition are increasingly dynamic and cohesive, and the automotive industry, in particular, is characterized by high interdependencies and has been more affected by value chain restructuring (Lutz and Bodendorf, 2020). Thus, we selected global automobile manufacturing firms from 2014 to 2018 in the Factiva database (the classification standard in the Factiva database is automobile) as samples to build coopetition network.…”

Section: Methodology and Data Collectionmentioning

confidence: 99%

The synergistic effect of ego-network stability and whole network position: a perspective of transnational coopetition network

Guan

Wang

Sun

et al. 2021

JEIM

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PurposeThe authors selected global automobile manufacturing firms whose sales ranked within 100 in the five years from 2014 to 2018 in the Factiva database to examine how the characteristics of a firm's whole network and ego-network in a transnational coopetition network influence network performance.Design/methodology/approachThe authors analyzed the public news of the sample firms about the coopetition by structural content analysis to build the coopetition networks and access to data on the competitive actions of firms. Then, to measure the variables associated with the coopetition network, such as the structural hole, centrality and ego-network stability, the authors use UCINET 6 that is a widely used piece of software for social network analysis to establishing five undirected binary adjacency matrices.FindingsThe authors find that a firm's competitive aggressiveness mediates the relationship between a firm's whole network position and network performance that emphasizes the need for integrating competitive dynamics research and coopetition research and shows how valuable insights can be gained through such integration. And the interaction of structural hole and centrality impacts competitive aggressiveness and network performance, and the interaction is different under high and low ego-network stability. The integration of whole network and ego-network literature studies provides new insights into firm network literature.Practical implicationsIn the process of cooperation, firms should consider whether they can occupy the structural hole and center as important indicators for partner selection. Too stable relationship will prevent firms from obtaining new resources. Firms should weigh the period of cooperation according to specific situation.Originality/valueThese results indicate that ego-network stability, as an important complementary characteristic of coopetition network, has a significant synergistic effect with structural holes and centrality on competitive aggressiveness and network performance. And these findings expand the current literature on the relationship between characteristics of network, competitive aggressiveness and network performance.

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Section: Methodology and Data Collectionmentioning

confidence: 99%

The synergistic effect of ego-network stability and whole network position: a perspective of transnational coopetition network

Guan

Wang

Sun

et al. 2021

JEIM

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“…Thus, in this paper, we are interested in the relationship between big data and firms' competitiveness. Basically, using analytics to enable firms' competitiveness refers more generally to competitive intelligence (Bredrup, 1995;Lutz and Bodendorf, 2020;Maune, 2014;Ranjan and Foropon, 2021). One of the most adopted definition of competitive intelligence presents this concept as "a systematic program for gathering and analyzing information about your competitor's activities and general business trends to further your own company's goals" (Kahaner, 1997;Madureira et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

One decade of big data for firms' competitiveness: insights and a conceptual model from bibliometrics

Tchuente

Haddadi

2023

JEIM

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PurposeUsing analytics for firms' competitiveness is a vital component of a company's strategic planning and management process. In recent years, organizations have started to capitalize on the significant use of big data for analyses to gain valuable insights to improve decision-making processes. In this regard, leveraging and unleashing the potential of big data has become a significant success factor for steering firms' competitiveness, and the related literature is increasing at a very high pace. Thus, the authors propose a bibliometric study to understand the most important insights from these studies and enrich existing conceptual models.Design/methodology/approachIn this study, the authors use a bibliometric review on articles related to the use of big data for firms' competitiveness. The authors examine the contributions of research constituents (authors, institutions, countries and journals) and their structural and thematic relationships (collaborations, co-citations networks, co-word networks, thematic trends and thematic map). The most important insights are used to enrich a conceptual model.FindingsBased on the performance analysis results, the authors found that China is by far the most productive country in this research field. However, in terms of influence (by the number of citations per article), the most influential countries are the UK, Australia and the USA, respectively. Based on the science mapping analysis results, the most important findings are projected in the common phases of competitive intelligence processes and include planning and directions concepts, data collection concepts, data analysis concepts, dissemination concepts and feedback concepts. This projection is supplemented by cross-cutting themes such as digital transformation, cloud computing, privacy, data science and competition law. Three main future research directions are identified: the broadening of the scope of application fields, the specific case of managing or anticipating the consequences of pandemics or high disruptive events such as COVID-19 and the improvement of connection between firms' competitiveness and innovation practices in a big data context.Research limitations/implicationsThe findings of this study show that the most important research axis in the existing literature on big data and firms' competitiveness are mostly related to common phases of competitive intelligence processes. However, concepts in these phases are strongly related to the most important dimensions intrinsic to big data. The use of a single database (Scopus) or the selected keywords can lead to bias in this study. Therefore, to address these limitations, future studies could combine different databases (i.e. Web of Science and Scopus) or different sets of keywords.Practical implicationsThis study can provide to practitioners the most important concepts and future directions to deal with for using big data analytics to improve their competitiveness.Social implicationsThis study can help researchers or practitioners to identify potential research collaborators or identify suitable sources of publications in the context of big data for firms' competitiveness.Originality/valueThe authors propose a conceptual model related to big data and firms' competitiveness from the outputs of a bibliometric study.

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“…A city seeking progress and facing challenges can seize it with the help of an integrated collection of technologies and tools that modify collaborations between its stakeholders (Nam and Pardo, 2011). Enterprises can collaborate with their stakeholders and meet existing demands and challenges by leveraging technology and innovations (Lutz and Bodendorf, 2020), such as software solutions, commercial accommodations, digital safety, network connectivity and data capacity (Lee, 2019). Since the benefits an enterprise provides to its stakeholders determine its worth (Perrey et al ., 2004), by exploring cities from an enterprise and community perspective, stakeholders can learn much about expanding their operations, improving their bottom line and positively impacting the environment and society.…”

Section: Introductionmentioning

confidence: 99%

A contemplative overview of smart communities: a hybrid analytical approach

Sakshi,

Srivastava,

Mangla

et al. 2023

JEIM

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PurposeThis study aims to uncover and develop explicit knowledge of existing smart communities (SCs) to guide services and business solutions for enterprises and serve community users in a well-thought-out manner. These sagacious frameworks will assist in analyzing trends and reaching out to pre-existing setups with different degrees of expertise.Design/methodology/approachA systematic overview is provided in this paper to unify insights and competencies toward building SCs; a hybrid analytical approach is used consisting of machine learning and bibliometric analysis. Scopus and Web of Science (WoS) are the primary databases for this purpose.FindingsSCs implement cutting-edge technologies to enhance mobility, elevating information and communication technology (ICT) skills and data awareness while improving business processes and efficiency. This system of SC is an evolution of the conventional method. It provides a foundation for intelligent community services based on individual users and technologies such as the Internet of Things (IoT), artificial intelligence, cloud computing and big data. Manufacturing-based, service-based, retail-based, resource management and infrastructure-based SCs exist in the literature.Originality/valueThe paper summarizes a conceptual framework of SCs based on existing works around SCs. To the best of the authors’ knowledge, this is the first systematic literature review that uses a hybrid approach of topic modeling and bibliometric analysis to understand SCs better.

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Analyzing industry stakeholders using open-source competitive intelligence – a case study in the automotive supply industry

Cited by 8 publications

References 66 publications

The synergistic effect of ego-network stability and whole network position: a perspective of transnational coopetition network

The synergistic effect of ego-network stability and whole network position: a perspective of transnational coopetition network

One decade of big data for firms' competitiveness: insights and a conceptual model from bibliometrics

A contemplative overview of smart communities: a hybrid analytical approach

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