Exponential technological expansion creates opportunities for competitive advantage by applying new data-oriented approaches to digital marketing practices. Machine learning (ML) can predict future developments and support decision-making by extracting insights from large amounts of generated data. This functionality greatly impacts and streamlines the strategic decision-making process of organizations. The research gap analysis revealed that little is known about marketers’ attitude towards, and knowledge about, ML tools and their adoption and utilization to support strategic and operational management. The research presented here focuses on the selection and adoption of ML-driven analytical tools by three distinct groups, namely marketing agencies, media companies, and advertisers. Qualitative and quantitative research was conducted, on a sample of these organizations operating in Slovakia. The findings highlight 1) the important role of intelligent analytical tools in the creation and deployment of marketing strategies, 2) the lack of knowledge about emerging technologies such as ML and artificial intelligence (AI), 3) the potential application of ML tools in marketing, as well as 4) the low level of adoption and utilization of ML-driven analytical tools in marketing management. A framework consisting of enablers and a process map was developed to help organizations identify the opportunities and successfully execute projects oriented towards the deployment and adoption of analytical ML tools in digital marketing.

This paper describes the impact of big data and machine learning (ML) on digital transformation of the marketing industry and the challenges it faces from a data and information management perspective. To do this, the study identified areas of digital transformation in marketing that have not yet been sufficiently covered by existing peer-reviewed academic research. Research papers were retrieved from five databases, namely Web of Science, Scopus, ScienceDirect, Emerald, and ProQuest. Screening of 214 articles resulted in 69 articles being selected for this literature review. A gap in the existing research was identified, with five areas directly related to digital transformation in marketing. Another five potential opportunities for future research in the area of big data utilisation and application of ML-driven technologies in the marketing field were also identified. An investigation of the prospects of digital transformation in marketing can benefit both academic researchers and business practitioners working in the domain of information technologies (IT), information systems (IS), business, and marketing, by identifying areas needing primary research, systemisation, follow-up research, validation or gathering of empirical data.

The research on chatbots has gained momentum over the past few years. Academics and practitioners investigate how these tools for communication with customers or internal team can be improved in terms of their performance, acceptance, and deployment. Although there is a plethora of recent studies available, not all of them deal with the digital business transformation implications of chatbots. The main aim of the research presented in this paper was to conduct a systematic literature review of high-quality journal research papers in order to summarise the current state of research on chatbots, identify their role in digital business transformation and suggest the areas warranting further attention. 74 papers were included in the research. Topical (focus and applications), methodological (methods used, sample size, sample type, and countries studied) and bibliometric (publication outlet, citations, and Altmetric Attention Score) aspects are evaluated and described. Scholars and practitioners can use the results to identify topics, areas, and applications that are intensely discussed in the literature and require further attention, select a methodology for their research that is well established in the field or is emerging, identify the most influential publications not to be missed in their research or identify publication outlets for publishing their research on chatbots.

University-Industry collaboration as a driver of digital transformation ultimately depends on the engagement and relationship between individual academics and industry practitioners as partners in a trust relationship. This paper describes the personal (‘lived’) experiences of academics and industry practitioners. The types, benefits, and enablers of the collaboration were investigated during semi-structured face-to-face interviews with industry partners and academic staff from the Science, Technology, Engineering and Mathematics (STEM) unit at the University of Enterprise in Australia. The types of collaboration included research activities, sharing facilities and equipment, innovation and commercialisation, collaboration involving students projects, collaborative teaching and learning, and sharing facilities and equipment. The benefits of the collaboration include access to valuable resources, validation of work, learning and teaching opportunities, financial benefits, improved reputation and career progression. The enablers of collaboration have been clustered into institutional, output, framework, and relationship factors. In this paper we focus on relationship factors and institutional enablers such as stakeholder engagement. The research is represented in a UA-IP Collaboration Model indicating the types (what), benefits (why), and enablers (how) of academic-practitioner collaboration. Universities and businesses from a variety of industries can benefit from the results of the presented research.

Mining companies use environmental sustainability reporting to inform their stakeholders about their position in relation to environmental sustainability. This paper explores how these companies include topics related to the environment and its protection in their annual reports. The 100 largest mining companies listed on the Australian Stock Exchange (ASX) were included in the research sample, using market capitalisation as the size indicator. The investigation was performed by means of quantitative and qualitative content analysis of annual reports to identify relevant keyword occurrences. Results revealed that topics related to protection of the environment, emissions, carbon footprint, and climate change are addressed in companies’ annual reports. In line with research in other industries, this study confirmed that the intensity of communication about these topics varies with company size. A new methodology was developed to assess the extent to which mining companies inform the stakeholders about their environmental protection initiatives and to address the limited applicability of the GRI G3 disclosure checklist for sustainability reporting, thereby enhancing the theory of social licence to operate.

Achieving economic development of the enterprise is enabled by the efficient use of resources, efficient processes and, last but not least, a suitable corporate culture. Under the influence of a dynamically changing business environment, corporate culture is gaining in importance and justification. It needs to be monitored and evaluated together with “hard” business indicators. The research explores the key values that should be applied in corporate culture at the strategic level to support the economic development of small and medium-sized enterprises. The differences between small and medium-sized enterprises operating in the industrial sector in Slovakia are defined. As managers have a direct impact on the creation of corporate culture, their preferences regarding corporate culture are examined, using the methodology of Cameron and Quinn. The results of the research prove the preference for applying key values typical for a clan culture. Following the results, it is recommended managers to focus on supporting a clan culture that develops employees. It is the employees who create and build values, bring new, innovative ideas, and with their abilities and skills influence the performance, competitive advantage, economic development, and success of the entire enterprise as well as economic development of small and medium-sized enterprises.