Search results

Novel and emerging technologies such as cognitive analytics attract a lot of hype among academic researchers and practitioners. However, returns on investments in these technologies are often poor. So, identifying mechanisms through which cognitive analytics can add value to firms is a critical research gap. The purpose of this paper is to theorize how cognitive analytics technologies can enable the dynamic capabilities of sensing, seizing and reconfiguring for an organization.

This conceptual paper draws on the extant academic literature on cognitive analytics and related technologies, the business value of analytics and artificial intelligence and the dynamic capabilities perspective, to establish the role of cognitive analytics technologies in enabling the sensing, seizing and reconfiguring capabilities of an organization.

Through arguments grounded in existing conceptual and empirical academic literature, this paper develops propositions and a theoretical framework linking cognitive analytics technologies with organizations’ dynamic capabilities (sensing, seizing and reconfiguring).

This paper has critical implications for both academic research and managerial practice. First, the authors develop a framework using the dynamic capabilities theoretical perspective to establish a novel pathway for the business value of cognitive analytics technology. Second, cognitive analytics is proposed as a novel antecedent of the dynamic organizational capabilities of sensing, seizing and reconfiguring.

To the best of the authors’ knowledge, this is the first paper to theorize how cognitive analytics technologies can enable dynamic organizational capabilities, and thus add business value to an organization.

Digital transformations of business processes are on the rise and the result is a need for a better understanding of how the elements of intellectual capital (IC) play a role in achieving successful digital project outcomes. New structural capital in the form of digital technologies must be identified and understood. Evolving skills of human capital in assimilating digital elements must also be considered, while collaboration within the development process involving relational capital provides a critical integration among these IC elements. This study illustrates the importance of identifying and managing the integration of IC components within an agile project management framework that are essential to achieving success for a digital initiative. More specifically, this study describes the process by which a multinational technology-based products company successfully developed a dynamic decision support platform utilizing an agile approach to guide a project management team to better manage the company's operations.

This study focuses on a case analysis approach of a multinational commercial and consumer products company. The paper presents existing research on the evolving state of project management for digital initiatives and focuses on agile methods. This study then delves into the case analysis that illustrates how IC played an integral role in the company successfully developing effective decision support involving an interactive dashboard using agile Project Management (PM), which enabled the project management team to better manage resources.

An examination at the case level illustrates that effective management and integration of IC has positive effects on project outcomes. While a balanced approach is evident as a requirement, the unique characteristics of the agile project management approach entails greater emphasis on select elements to adapt to a more dynamic development process.

This work depicts the complexities in providing analytic-based decision support in an agile/flexible project management scenario. This work adds to existing research by illustrating elements within IC categories and the elements' interdependencies that play an essential role in achieving success in this more flexible project environment.

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

The purpose of the study is to identify how knowledge management processes impact innovation performance in the Jordanian medical sector (private hospitals) as well as identify how big data analytics moderates this performance.

Two hundred ninety-one questionnaires were analyzed for the purpose of this study. A structural equation model (SEM) was used to test convergence validity, discriminant validity and reliability. In order to analyze the data, bootstrapping was used.

The empirical results showed that all knowledge management processes are statistically significant in influencing innovation performance. Furthermore, big data analytics moderates the relationship between knowledge management processes and innovation performance.

The results of this cross-sectional study are limited to one country and one industry due to methodological limitations, and the results represent a snapshot at a particular point in time.

Jordan's medical leaders will benefit from this study, since it emphasizes the importance of knowledge management processes to enhance innovation performance, especially given the importance of big data analytics in the field, increasing innovation capabilities in the medical field, thereby increasing innovation levels.

This paper aims to identify, synthesise and critically examine the extant academic research on the relation between big data analytics (BDA), corporate accountability and non-financial disclosure (NFD) across several disciplines.

This paper uses a structured literature review methodology and applies “insight-critique-transformative redefinition” framework to interpret the findings, develop critique and formulate future research directions.

This paper identifies and critically examines 12 research themes across four macro categories. The insights presented in this paper indicate that the nature of the relationship between BDA and accountability depends on whether an organisation considers BDA as a value creation instrument or as a revenue generation source. This paper discusses how NFD can effectively increase corporate accountability for ethical, social and environmental consequences of BDA.

This paper presents the results of a structured literature review exploring the state-of-the-art of academic research on the relation between BDA, NFD and corporate accountability. This paper uses a systematic approach, to provide an exhaustive analysis of the phenomenon with rigorous and reproducible research criteria. This paper also presents a series of actionable insights of how corporate accountability for the use of big data and algorithmic decision-making can be enhanced.

This paper discusses how NFD can reduce negative social and environmental impact stemming from the corporate use of BDA.

To the best of the authors’ knowledge, this paper is the first one to provide a comprehensive synthesis of academic literature, identify research gaps and outline a prospective research agenda on the implications of big data technologies for NFD and corporate accountability along social, environmental and ethical dimensions.

ChatGPT is a versatile technology with practical use cases spanning many professional disciplines including marketing. Being a recent innovation, however, there is a lack of academic insight into its tangible applications in the marketing realm. To address this gap, the current study explores ChatGPT’s application in marketing by mining social media data. Additionally, the study employs the stages-of- growth model to assess the current state of ChatGPT’s adoption in marketing organizations.

The study collected tweets related to ChatGPT and marketing using a web-scraping technique (N = 23,757). A topic model was trained on the tweet corpus using latent Dirichlet allocation to delineate ChatGPT’s major areas of applications in marketing.

The topic model produced seven latent topics that encapsulated ChatGPT’s major areas of applications in marketing including content marketing, digital marketing, search engine optimization, customer strategy, B2B marketing and prompt engineering. Further analyses reveal the popularity of and interest in these topics among marketing practitioners.

The findings contribute to the literature by offering empirical evidence of ChatGPT’s applications in marketing. They demonstrate the core use cases of ChatGPT in marketing. Further, the study applies the stages-of-growth model to situate ChatGPT’s current state of adoption in marketing organizations and anticipate its future trajectory.

The purpose of this study is to conduct a systematic literature review of the adoption of immersive marketing technology (IMT) in terms of strategic planning of its adoption, resource requirements and its implications and challenges.

This study categorizes and contextualizes qualitative approaches to evaluate the literature, with Scopus databases serving as the primary source of 90 selected articles in the areas of information technology, business and marketing strands. Theme analysis was carried out using thematic techniques and grounded approach principles to facilitate thematic coding and generate theme analysis.

The analysis was supported by the three concepts of business flexibility, agility and adaptability, which were drawn as a strategy for IMT adoption. The findings presented three main themes: proactive flexibility, responsive agility and reactive adaptability that enable business owner–managers to craft a strategy for IMT adoption.

The novel contribution of this study is the inclusion of key implications related to IMT as a starting point of the next level of innovative marketing for all academics, practitioners and business owner–managers.

The study aims to provide insights in the sensemaking process and the use of business analytics (BA) for project selection and prioritisation in start-up settings. A major focus is on the various ways start-ups can understand their data through the analytical process of sensemaking.

This is a comparative case study of two start-ups that use BA in their projects. The authors follow an interpretive approach and draw from the constructivist grounded theory method (GTM) for the purpose of data analysis, whereby the theory of sensemaking functions as the sensitising device that supports the interpretation of the data.

The key findings lie within the scope of project selection and prioritisation, where the sensemaking process is implicitly influenced by each start-up's strategy and business model. BA helps start-ups notice changes within their internal and external environment and focus their attention on the more critical questions along the lines of their processes, operations and business model. However, BA alone cannot support decision-making around less structured problems such as project selection and prioritisation, where intuitive judgement and personal opinion are still heavily used.

This study extends the research on BA applied in organisations as tools for business development. Specifically, the authors draw on the literature of BA tools in support of project management from multiple perspectives. The perspectives include but are not limited to project assessment and prioritisation. The authors view the decision-making process and the path from insight to value, as a sensemaking process, where data become part of the sensemaking roadmap and BA helps start-ups navigate the decision-making process.

The paper aims to reveal the impact of relationship marketing (RM) practices adopted by companies in emerging markets on their market and financial performance (FP) over a long-term, 13-year perspective.

The research design combines primary empirical data from 229 Russian companies, based on the Contemporary Marketing Practices (CMP) survey, and objective FP data from official statistical databases for 2008–2020 to verify the impact of RM practices on market and FP in the long term.

The research underlines the significant impact of RM practices. It is important to notice that the effect of product development (PD) on marketing performance is mediated by competitor orientation. PD affects market and FP, whose roles vary with the return on assets (ROA).

Research design supplements the subjective survey data with the objective FP data on the ROA to avoid common method bias.

Implementation of RM practices by Russian companies can increase their effectiveness of performance in the long term.

This research shows the positive impact of RM practices on the FP of Russian firms over the past 13 years.