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This paper focuses on the application of a robotic technique for modeling a three-wheeled mobile robot (WMR), considering it as a multibody polyarticulated system. Then the dynamic behavior of the developed model is verified using a physical model obtained by Simscape Multibody.

Firstly, a geometric model is developed using the modified Denavit–Hartenberg method. Then the dynamic model is derived using the algorithm of Newton–Euler. The developed model is performed for a three-wheeled differentially driven robot, which incorporates the slippage of wheels by including the Kiencke tire model to take into account the interaction of wheels with the ground. For the physical model, the mobile robot is designed using Solidworks. Then it is exported to Matlab using Simscape Multibody. The control of the WMR for both models is realized using Matlab/Simulink and aims to ensure efficient tracking of the desired trajectory.

Simulation results show a good similarity between the two models and verify both longitudinal and lateral behaviors of the WMR. This demonstrates the effectiveness of the developed model using the robotic approach and proves that it is sufficiently precise for the design of control schemes.

The motivation to adopt this robotic approach compared to conventional methods is the fact that it makes it possible to obtain models with a reduced number of operations. Furthermore, it allows the facility of implementation by numerical or symbolical programming. This work serves as a reference link for extending this methodology to other types of mobile robots.

This study aims to systematically review the current academic literature on the role of technologies in low-carbon supply chain management (SCM), identify and analyse critical themes and propose an integrated conceptual model.

A systematic literature review of 48 papers published between 2010 and 2022 was conducted. A conceptual model was advanced.

Based on the analysis and synthesis of the reviewed papers, this review provides an initial attempt to integrate technology adoption and low-carbon SCM by developing a diffusion of innovation model of technology-enabled low-carbon SCM within the technology–organisation–environment (TOE) framework, in which drivers, enablers and barriers to technology adoption practices are identified. The environmental, economic and social outcomes of adoption practices are also identified.

This study provides a novel and comprehensive roadmap for future research on technology-enabled low-carbon SCM. Furthermore, policy, as well as managerial implications, is presented for policymakers and managers.

Cause-related B2B marketing programs involve sponsoring organisations working with B2B suppliers with the help of non-profit organisations (NPOs) on practises relating to environmental friendliness, workforce diversity, human rights, safety, philanthropy and business ethics. The study aims to identify the combinatory factors driving the adoption of Digital B2B platforms for managing cause-related B2B marketing programs.

The study adopts an innovative approach of fuzzy-set qualitative comparative analysis (fsQCA) on data collated from top corporations in India supporting cause-related B2B marketing programs. Sponsoring organisations and NPO dyads (i.e. survey both) filled out an email survey on 264 cause-related B2B marketing programs.

The study establishes that the combination of technological, organisational and environmental factors would lead to the adoption of Digital B2B platforms in managing cause-related B2B marketing programs. The study identifies six combinations of these factors for adopting Digital B2B platforms within and across sponsoring organisations and NPOs.

The study findings would aid cause-related B2B marketers in developing Digital B2B platforms’ capabilities by understanding the different combinations of factors driving adoption. Digital B2B platforms’ capabilities can improve market performance if developed as core competencies.

The study findings would enable improvements in the implementation and performance of cause-related B2B marketing programs. Better management of cause-related B2B marketing programs would help increase beneficiary coverage and the realisation of societal goals.

To the author’s knowledge, this is the first study to apply the TOE framework in conjunction with complexity theory to explain the diffusion of adoption of Digital B2B platforms for managing cause-related B2B marketing programs.

The goal of this work is to evaluate how digital transformation disclosure in corporate news and press releases affects stock prices. We examine American and Chinese companies from the energy and industry sectors for two periods: pre-COVID-19 and during the COVID-19 pandemic.

To estimate the effects of disclosure of information related to digital transformation, we applied the bag-of-words (BOW) method. As the benchmark dictionary, we used Kindermann et al. (2021), with the addition of original dictionaries created via Latent Dirichlet allocation (LDA) analysis. We also employed panel regression analysis and random forest.

For USA energy sector, all aspects of digital transformation were insignificant in pre-COVID-19 period, while sustainability topics became significant during the pandemic. As for the Chinese energy sector, digital strategy implementation was significant in pre-pandemic period, while digital technologies adoption and business model innovation became relevant in COVID-19 period. The results show the greater significance of digital transformation aspects for industrials sectors compared to the energy sector. The result of random forest analysis proves the efficiency of the authors’ dictionary which could be applied in practice. The developed methodology can be considered relevant.

The research contributes to the existing literature in theoretical, empirical and methodological ways. It applies signaling and information asymmetry theories to the financial markets, digital transformation being used as an instrument. The methodological contribution of this article can be described in several ways. Firstly, our data collection process differs from that in previous papers, as the data are gathered “from investor’s point of view”, i.e. we use all public information published by the company. Secondly, in addition to the use of existing dictionaries based on Kindermann et al. (2021), with our own modifications, we apply the original methodology based on LDA analysis. The empirical contribution of this research is the following. Unlike past works, we do not focus on particular technologies (Hong et al., 2023) connected with digital transformation, but try to cover all multi-dimensional aspects of the transformational process and aim to discover the most significant one.

This study aims to investigate the impact of digital leadership (capabilities, experience, predictability and vision) and green organizational culture on firms' digital transformation and financial performance. Additionally, the research aims to evaluate the mediating role of digital transformation in the relationship between digital leadership and firms' financial performance.

A purposive sampling technique was employed to identify and select individuals with relevant expertise and experiences in the field of digital transformation. A total of 164 responses were collected, and the questionnaire was designed based on a five-point Likert-type scale. The data were analyzed using SmartPLS 4 (Statistical Software for Structural Equation Modeling).

The findings indicate that digital leadership capabilities, experience, predictability and vision do not directly impact firms' performance. However, there is an indirect influence on firms' performance through digital transformation. While both digital transformation and green organizational culture (GOC) positively influence firms' financial performance, GOC, leader predictability and leader vision positively influence digital transformation. The results confirm that digital transformation mediates the relationship between capabilities, experience, predictability and vision and firms' financial performance.

The study highlights that strategic capabilities can enhance value-added processes during digital transformation, contributing to sustainability in the digital era. Overall, this research significantly advances both theoretical understanding and practical applications in the context of digital leadership and its impact on firms. Limited digital transformation stages among Malaysian firms impact the research, with some entities cautious about data disclosure and having limited cooperation with researchers. Gathering data from diverse sources would have strengthened the findings and methodological rigor of this multilevel study. Despite these limitations, the research offers fresh insights into the role of GOC, different facets of digital leadership and their influence on digital transformation and financial performance. This enhances existing knowledge and challenges assumptions of the transformational leadership theory (TLT) framework.

The study opens the door to further research into distinct leadership components and their effects in a similar context. By highlighting the positive influence of capabilities, experience, predictability and vision on digital transformation, it expands the theoretical and empirical scope in the realm of digital leadership. These findings encourage critical examination, refinement and evolution of TLT, providing insights for leaders and managers as they navigate digitalization, financial performance and digital leadership within organizations. In an era of digital transformation, leaders play a central role in building a psychologically safe environment and nurturing digitally skilled teams capable of managing technological changes. Leaders should possess the digital capabilities, experience, vision and predictability necessary to drive digital transformation, mitigate potential threats and adapt to the dynamic digital landscape.

These findings support government initiatives to accelerate digitalization and Industry 4.0 implementation. Collaboration between the government and private organizations is essential to create policies and practices that facilitate broad participation in digital transformation programs. Policymakers must adopt a proactive approach to address issues related to Internet accessibility, trade barriers, financing access and resource reallocation. These policies aim to ensure a high-quality and affordable digital infrastructure, cultivate trust in digital technologies and equip organizational leaders with the necessary digital skills.

This research provides valuable insights for practitioners to enhance firms' digital transformation. As a practical contribution, this study’s findings can inform how firms can better manage their key digital leadership resources and GOC to foster digital transformation and improve their financial performance.

Using 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.

In 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.

Based 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.

The 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.

This study can provide to practitioners the most important concepts and future directions to deal with for using big data analytics to improve their competitiveness.

This 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.

The authors propose a conceptual model related to big data and firms' competitiveness from the outputs of a bibliometric study.

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

This paper aims to identify and model barriers to internationalising automotive small and medium-sized enterprises (SMEs) from emerging market perspectives using the interpretive structural modelling (ISM) approach.

In this paper, 13 critical barriers are identified through an exhaustive literature review and the Delphi method. The ISM tool is then used to establish interrelationships among the identified barriers to expose and discuss the key barriers having high-driving power.

It was found that barriers such as trade agreements and export documentation, exchange rates and material inadequacies were relatively less challenging than the other barriers. At the next level, there are barriers such as supply chain, high international quality standards, legal barriers, skilled labour marketing capacity and information and logistics and infrastructure. Finally, barriers such as government policies, entrepreneurial orientation and technology and finance availability posed the most significant challenge for the internationalisation of Indian SMEs. These barriers warrants immediate and considerable attention.

This study developed a model based on experts’ opinions, which may be biased and influence the final model as proposed in this study. This research will help the owners/managers of the SMEs and policymakers identify and understand the significance and relevance of automotive sector barriers while strategizing.

To the best of the authors’ knowledge, this is the first time an attempt has been made to apply ISM methodology to explore the interdependencies among the critical barriers of internationalisation for SMEs of Indian automotive industries. This study will guide the owner–managers management practices to overcome ineffective practices and move towards successful internationalisation.

The present study aimed to assess performance of Industry 4.0 (I4.0) in case organization by considering potential performance measures and analysis using scoring approach.

50 performance measures grouped into five dimensions namely manufacturing management, manufacturing economics, manufacturing strategy, manufacturing technology and workforce were considered for the analysis. The study had been done with relevance to automotive component manufacturing organization. Further, questionnaire for each performance measure was developed to gather expert inputs regarding different performance aspects of I4.0 in case organization. Reliability of the expert responses towards questionnaire was assessed by computing Cronbach's alpha (a) using Statistical Package for the Social Sciences (SPSS) software.

Findings of the study revealed overall I4.0 performance index (OIPI) of 0.71, i.e. 71% signifying improvement scope of 29% pertaining to I4.0 adoption. Gap analysis was performed across dimensions and performance measures to realize the weaker areas. Gap analysis revealed workforce dimension with highest gap and manufacturing management with lowest gap. The gaps that obstruct performance of I4.0 are being recognized and proposals for improvement were provided to the industrial practitioners. Based on further analysis, dimensions and performance measures found to be weaker.

The study helped industrial practitioners and managers to create the foundation for evaluating performance of I4.0-focused organization. Industry practitioners can employ the study to understand different performance measures with respect to different dimensions and realize the significance of I4.0 adoption.

The identification of performance dimensions and measures for I4.0 performance measurement and assessment using scoring approach is the original contribution of the authors.

This study proposes an innovative concept of green digital transformation capability (GDTC) and explores the interrelationships among GDTC, ambidextrous green learning (AGL) and sustainability performance (SP) from multiple perspectives.

Survey questionnaires were distributed to Taiwanese firms engaged in various sectors, including electrical and information, metal and precision machinery, rubber material, chemical, daily necessity and food and beverage manufacturing, resulting in 306 valid responses. Structural equation modeling in SPSS v26 was used to test the hypotheses. Furthermore, we analyzed the mediating effects using SPSS PROCESS.

The results demonstrated that GDTC affected SP both directly and indirectly through exploratory and exploitative green learning. Furthermore, this study revealed the pathways through which GDTC influenced the SP of Taiwanese manufacturing firms.

This study is limited to Taiwanese manufacturing firms. Future studies should expand their sample size to explore digital transformation (DT) practices in various regions and industries.

The DTs in manufacturing have profound social implications, emphasizing that companies should consider economic, social and environmental sustainability during digitalization.

This study introduces a novel concept of GDTC and provides important theoretical insights and practical implications for the intersection of DT and sustainability perspective. These findings will offer valuable guidance to companies seeking sustainable development in the digital era.