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Collaboration between university and industry can improve knowledge exchange and innovation, which is required for driving digital business transformation in organisations. This paper discusses the results of a case study that was conducted to investigate the personal (‘lived’) experiences of both industry practitioners and academics from the STEM academic unit at the University of Enterprise in Australia, regarding the barriers to building trusting knowledge-related collaborative relationships. Semi-structured face-to-face interviews were conducted with sixteen academics and industry representatives to elicit their views. We found that university and business leaders must overcome barriers to establish higher numbers of University-Industry Collaboration (UIC) agreements, including limited resources, lack of capabilities and the absence of university support. However, they must also address the challenges facing individual academics and industry professionals, such as conflicting interests and expectations, and limitations to academics’ career progression. The paper discusses how the recently established Enterprise Hub at the University supports collaboration and fostering healthy relationships between academic staff and industry partners. The findings will provide guidance to other universities and businesses to establish such supportive entities at their institutions to drive innovation and digital business transformation initiatives.

Digital business transformation (DBT) is a significant trend in all industries, and affects all businesses, large and small. Companies that resist digitalisation and systemic transformation risk losing market share or even completely going out of business. Effective communication, both internal and external, and collaboration are vital for transformation success. This paper investigates executives’ perceptions of the disruptions leading to the need for DBT, whether such a transformation is considered a challenge or even a crisis by company executives, and the communication strategies that are implemented for DBT in various pipe extrusion companies in Germany. This research adopts a qualitative approach and semi-structured interviews were used in our research to gather data from experts in the companies. The research found that most companies in the pipe extrusion industry in Germany acknowledge and can articulate disruptions, both current and future. However, they but do not regard digital transformation of their business as a crisis and most companies have not prepared strategies for effectively communicating their response to digital transformation challenges.

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.

This paper describes the lived experiences of experts who have taken a holistic approach to driving transformation in various organizations. The primary goal of the paper is to outline, at a high level, key insights and observations that are critically important to implementing Digital Business Transformation (DBT). The authors have undertaken primary interviews in which interviewees were asked to share their experience and opinions regarding organizational prerequisites for embarking on DBT, misconceptions about DBT, and the challenges to implementing DBT. These insights were analyzed and clustered and this paper articulates six lessons they have learned during the transformations. These lessons relate to Chief Executive Officer (CEO) commitment and the need for change leadership, the best team to drive the implementation successfully, the perception and behavior of stakeholders before, during and after the transformation, the importance of choosing the best digital platform to suit the business and the increased importance of relationships in the business ecosystem. We present the findings in a holistic framework and organizations seriously considering DBT implementation in their own business may consider these insights to be a good starting point.

The complex process of online information search has been of great interest to academics and practitioners, regarding its motivation, triggers, phases, and various aspects of user search behavior. Web search spanning multiple sessions has been studied, including users switching between devices. The study presented in this paper aims to critically analyze two decades (2000 – 2020) of research on cross-session and cross-device search. A systematic literature review of 29 journal papers and peer reviewed academic conference proceedings was conducted. The main results were extracted, synthesized, and presented. Topical (focus and terminology), methodological (data collection, sample size, sample type, and countries studied) and bibliometric (publication outlet and citations) aspects of online information search were evaluated and described. The paper identifies keywords for effective literature searches and adds new insights about effective research methods and sampling, the most cited publications and most influential authors in this field and the possibility of conducting interdisciplinary research. Both scholars and practitioners can use this study to gain a deeper understanding of the cross-session and cross-device search research agenda. Future research suggestions inform researchers about issues that warrant further attention.

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.

Abstract Background The objective of the study described in this article was to examine whether, and to what extent, Australian public hospitals use knowledge terminology, i.e. a body of knowledge-related terms, on their websites. The paper also discusses the difference in the level of such communication between large and small hospitals, the factors affecting the use of the knowledge-related terms in the communication and the similarities/differences between the use of knowledge terms in Australian public hospitals and large/small companies in Australia. Methods 151 Australian public hospitals were included in the research sample: 51 large and 100 small hospitals. Using the method of content analysis, websites mentioning knowledge creation, knowledge sharing, knowledge implementation, and knowledge retention were identified, along with the number of these mentions. Descriptive statistics and chi square test of independence were used to provide answers to four research questions. Results Of the 151 hospitals included in the sample, 30 had no website and 62 (50 small and 12 large) had a single page website. The study found that there are differences between Australian public hospitals regarding the level of their knowledge communication on their websites, both between small and large hospitals and between the individual hospitals within the large and small hospital groups. Conclusions A well-known saying goes “For the mouth speaks what the heart is full of”. Effective communication of knowledge-related terminologies to both internal and external stakeholders, i.e. the parties who access the websites, is therefore an indication of a knowledge focus in the public hospitals. Large hospitals are generally more active in communicating knowledge terms, although there are some exceptions. Some of the small hospitals can lead by example, but most of them do not include knowledge terminology in their communication on websites.

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 viewers' response to television advertising has changed dramatically over the past years. Search visibility of advertisers has become of paramount importance to ensure that communication messages are followed up appropriately, and that the specific brand is considered in the customer decision-making process. This paper examines the effectiveness of communication campaigns that include TV advertisements. Specifically, it determines if, and to what extent, the advertisers of selected Australian TV advertising campaigns are visible in full-text searches on Google for a variety of relevant keywords. The visibility of advertisers is measured as the number of keyword searches that result in a high ranking on the search engine results page, average ranking, and site visibility. The results revealed notable differences in the visibility of advertisers in searches. Enhancing their visibility represents a challenge for companies striving to optimise the delivery of their communication message(s) across the entire spectrum of traditional and online media.

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.

Project management uses many tools, techniques, and methodologies in project development. PRINCE2 methodology set documentation which must be tailored to suit the occasion project. Since software projects may often fail due to lack of well-structured project management method, it is necessary to identify the key success factors of PRINCE2 method in software development project. The purpose of this research study is to identify key success factors of PRINCE2 project management method in software development project. The researcher undertakes a case study in an organisation where software project is implemented in PRINCE2 project management method. Data has been collected from questionnaires and face-to-face interviews. Documents review, and observation techniques were used as secondary data collection sources. The researcher has conducted template analysis with interview data and excels analysis with the questionnaires data. The researcher has then triangulated the data to get authentic and accurate findings. 20 factors have been identified as key success factors in this research study such as defined roles & responsibilities, scope management, manage by stages, well planning, top management support, time management, risk management, monitor project progress, change management, communication management, quality management, project team competency, managing product delivery, cost management, learn from experience, prioritizing task, assign work to right person, benefit realisation and being agile.

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 a little is known about marketers' attitude toward, 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 the ML-driven analytical tools by three distinct groups: 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 the ML tools in marketing, and; 4) the low level of adoption and utilization of the 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 that are oriented toward the deployment and adoption of the analytical ML tools in digital marketing.

Decision making is an inherent, complex and vital component of the work of managers. Its importance and role in operationalizing the activities of an organisation are well-evidenced in management literature. Yet, there is a dearth of literature about the processes used by nurse managers to make decisions. The principal aim of this paper is to identify the different types of decisions made by nurse managers and explore the related decision-making processes. A ‘dependency model’ is proposed, which illustrates the factors affecting the art of decision making. Structured interviews were conducted to identify types of decisions made by nurse managers in different health-care settings and the factors underpinning these decisions. The research focused on an intensive study of a small group of nurse managers working in rural and regional health institutions in South Australia. The sample included nurse unit managers, after-hours coordinators and directors of nursing. Hermeneutic principles and interpretive research were used to conduct interviews with nurse managers who make numerous and varied types of decisions, though often without following a step-by-step approach. The study identified dependency factors that influence how decisions are made, and developed a model based on eight key variables: (1) the situation to be addressed; (2) the time period in which the decision has to be made; (3) required inputs from colleagues; (4) complexity of the task and the environment, (5) the duration and time it takes to make a decision, (6) availability of resources, (7) the decision-making environment, and (8) personal characteristics. These eight variables are interrelated and have both direct and indirect impacts on how decisions are made. Nurse managers make pragmatic decisions reflecting the complexity of their roles and responsibilities. Awareness of the factors on which decisions depend helps understanding of how they navigate through decision-making processes. The findings are presented as a model that can be used to support decision making by nurse managers in various health settings.