Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective

Mikalef, Patrick; Islam, A. K. M. Najmul; Parida, Vinit; Singh, Harkamaljit; Altwaijry, Najwa

doi:10.1016/j.jbusres.2023.113998

Cited by 37 publications

(11 citation statements)

References 55 publications

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“…These technologies are diffused among organizations and are developed through inter-organizational cooperation (Burström et al, 2021;Fredström et al, 2021;Tagscherer & Carbon, 2023;Xu et al, 2022). For example, the deployment of AI is idiosyncratic, requiring collaborative efforts from various organizational entities to produce difficult-to-imitate AI applications (Mikalef et al, 2023). However, the fragmentation caused by technological advances often results in participants operating in isolated silos, necessitating an orchestrator to efficiently oversee and mediate (Leten et al, 2013).…”

Section: Ecosystem Technological Leveraging Practicesmentioning

confidence: 99%

Ecosystem orchestration practices for industrial firms: A qualitative meta-analysis, framework development and research agenda

Shen,

Shi,

Parida

et al. 2024

Journal of Business Research

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Section: Ecosystem Technological Leveraging Practicesmentioning

confidence: 99%

Ecosystem orchestration practices for industrial firms: A qualitative meta-analysis, framework development and research agenda

Shen,

Shi,

Parida

et al. 2024

Journal of Business Research

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“…As advanced application methods are being adopted in various fields, traditional manual operation approaches are gradually being replaced, presenting significant long-term growth prospects (3).…”

Section: Contextmentioning

confidence: 99%

Advancements in Artificial Intelligence for ECG Signal Analysis and Arrhythmia Detection: A Review

Kazemi Lichaee,

Salari,

Jalili

et al. 2024

Int J Cardiovasc Pract

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Context: With the widespread availability of portable electrocardiogram (ECG) devices, there is an increasing interest in utilizing artificial intelligence (AI) methods for ECG signal analysis and arrhythmia detection. The potential benefits of AI-assisted arrhythmia prognosis, early screening, and improved accuracy in arrhythmia classification are discussed. Evidence Acquisition: Artificial intelligence methods are a new way to classify different types of arrhythmias. For example, deep learning (DL) algorithms, including long short-term memory (LSTM) networks, convolutional neural networks (CNN), CNN-based autoencoders (AE), and convolutional recurrent neural networks (CRNN), have been extensively utilized for ECG signal analysis and arrhythmia detection. Results: This study explores different DL techniques for classifying arrhythmias. The two-dimensional (2D) CNN model achieved an accuracy of 97.42% in classifying five different arrhythmias. After classifying five types of ECG signals, an accuracy of 99.53% was achieved by the CNN-based AE and transfer learning (TL) models. The CNN-Bi-LSTM model achieved an accuracy of 98.0% in categorizing five categories of ECG signals. The CNN+LSTM model achieved an accuracy of 98.24% in classifying five classes of arrhythmias. The CNN-support vector machine (SVM) classifier model demonstrated an accuracy of 98.64% in detecting seventeen classes of heartbeats. The results indicated that the CNN-based AE and TL models perform exceptionally well with high accuracy in detecting ECG signals. Conclusions: The present study demonstrates the growing interest in utilizing DL for ECG signal detection in medical and healthcare applications over the past decade. Deep learning models have been shown to outperform experienced cardiologists, delivering state-of-the-art and more accurate results.

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“…First, they enhance connectivity and real-time communication across countries, thereby improving customer support, service delivery and relationship management on a global scale (Akter et al ., 2023). Similarly, through the Internet of Things (IoT), firms can monitor equipment, analyze performance data and offer proactive maintenance services to clients in different parts of the world (Mikalef et al ., 2023). This predictive maintenance enhances customer satisfaction and operational efficiency.…”

Section: The Contributions Of This Special Issue To the Literature On...mentioning

confidence: 99%

“…Finally, digital technologies enable servitized firms to customize services based on individual customer needs and preferences (Vendrell-Herrero et al ., 2017). Through data analytics and AI-driven insights, firms can tailor their offerings to different international markets, providing personalized experiences that resonate with local audiences (Mikalef et al ., 2023). In essence, digital technologies optimize operations, enhance customer engagement and provide valuable insights, allowing hybrid firms to navigate the complexities of international markets and position themselves for success.…”

Section: The Contributions Of This Special Issue To the Literature On...mentioning

confidence: 99%

Exploring the influence of hybrid product–service offerings on firm internationalization strategies: an international perspective

Liu,

Bustinza,

Vendrell-Herrero

et al. 2023

IMR

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PurposeThis paper aims to deepen the understanding of the interconnection between hybrid product–service offerings and firms' internationalization strategies, focusing on market entry, export performance and subsidiary strategy development.Design/methodology/approachThe approach involves reviewing and summarizing the existing body of research in the area. This is complemented by the analysis of the 10 published papers in the current issue.FindingsThe authors proposed a value-chain synergetic approach that ensures the international competitiveness of hybrid offerings. The authors’ conceptual framework encompasses four themes: (i) internal factors encompassing capabilities and governance, (ii) supply-side factors related to ecosystem formation, (iii) demand-side factors encompassing customization and co-creation and (iv) enhancing factors such as assets digitization. The authors’ analysis demonstrates how these synergistic value chain themes interrelate to empower hybrid offerings in the export market.Research limitations/implicationsWhile the conceptual development presented in this paper is not exhaustive, the model highlights important research avenues in the internationalization of product–service hybrid offerings that need exploration.Practical implicationsThe proposed framework hold practical implications for firms aiming to enhance their competitiveness in the export market through the integration of hybrid product–service offerings.Originality/valueThe authors’ framework bridges the gap in international marketing literature by focusing on the interplay between hybrid product–service offerings and internationalization strategies, providing valuable insights into the factors driving servitization-led innovations in foreign markets.

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Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective

Cited by 37 publications

References 55 publications

Ecosystem orchestration practices for industrial firms: A qualitative meta-analysis, framework development and research agenda

Ecosystem orchestration practices for industrial firms: A qualitative meta-analysis, framework development and research agenda

Advancements in Artificial Intelligence for ECG Signal Analysis and Arrhythmia Detection: A Review

Exploring the influence of hybrid product–service offerings on firm internationalization strategies: an international perspective

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