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1 – 10 of over 2000Yassine Talaoui and Marko Kohtamäki
The business intelligence (BI) research witnessed a proliferation of contributions during the past three decades, yet the knowledge about the interdependencies between the BI…
Abstract
Purpose
The business intelligence (BI) research witnessed a proliferation of contributions during the past three decades, yet the knowledge about the interdependencies between the BI process and organizational context is scant. This has resulted in a proliferation of fragmented literature duplicating identical endeavors. Although such pluralism expands the understanding of the idiosyncrasies of BI conceptualizations, attributes and characteristics, it cannot cumulate existing contributions to better advance the BI body of knowledge. In response, this study aims to provide an integrative framework that integrates the interrelationships across the BI process and its organizational context and outlines the covered research areas and the underexplored ones.
Design/methodology/approach
This paper reviews 120 articles spanning the course of 35 years of research on BI process, antecedents and outcomes published in top tier ABS ranked journals.
Findings
Building on a process framework, this review identifies major patterns and contradictions across eight dimensions, namely, environmental antecedents; organizational antecedents; managerial and individual antecedents; BI process; strategic outcomes; firm performance outcomes; decision-making; and organizational intelligence. Finally, the review pinpoints to gaps in linkages across the BI process, its antecedents and outcomes for future researchers to build upon.
Practical implications
This review carries some implications for practitioners and particularly the role they ought to play should they seek actionable intelligence as an outcome of the BI process. Across the studies this review examined, managerial reluctance to open their intelligence practices to close examination was omnipresent. Although their apathy is understandable, due to their frustration regarding the lack of measurability of intelligence constructs, managers manifestly share a significant amount of responsibility in turning out explorative and descriptive studies partly due to their defensive managerial participation. Interestingly, managers would rather keep an ineffective BI unit confidential than open it for assessment in fear of competition or bad publicity. Therefore, this review highlights the value open participation of managers in longitudinal studies could bring to the BI research and by extent the new open intelligence culture across their organizations where knowledge is overt, intelligence is participative, not selective and where double loop learning alongside scholars is continuous. Their commitment to open participation and longitudinal studies will help generate new research that better integrates the BI process within its context and fosters new measures for intelligence performance.
Originality/value
This study provides an integrative framework that integrates the interrelationships across the BI process and its organizational context and outlines the covered research areas and the underexplored ones. By so doing, the developed framework sets the ground for scholars to further develop insights within each dimension and across their interrelationships.
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Angelo Cavallo, Silvia Sanasi, Antonio Ghezzi and Andrea Rangone
This paper aims to examine how competitive intelligence (CI) relates to the strategy formulation process of firms.
Abstract
Purpose
This paper aims to examine how competitive intelligence (CI) relates to the strategy formulation process of firms.
Design/methodology/approach
Due to the novelty of the phenomenon and to the depth of the investigation required to grasp the mechanisms and logics of CI, a multiple case study has been performed related to four companies located in Brazil that adopted CI practices within dedicated business units to inform and support strategic decision-making.
Findings
The authors provide detailed empirical evidence on the connection and use of CI practices throughout each stage of the strategy formulation process. Moreover, the study suggests that CI practices, despite their strategic relevance and diffusion, are still extensively adopted for tactical use.
Originality/value
This study sheds light on how CI practices may inform, support, and be integrated in the strategy formulation process, as few studies have done before.
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Alberto Cavazza, Francesca Dal Mas, Paola Paoloni and Martina Manzo
Artificial Intelligence (AI) is a growing technology impacting several business fields. The agricultural sector is facing several challenges, which may be supported by the use of…
Abstract
Purpose
Artificial Intelligence (AI) is a growing technology impacting several business fields. The agricultural sector is facing several challenges, which may be supported by the use of such a new advanced technology. The aim of the paper is to map the state-of-the-art of AI applications in agriculture, their advantages, barriers, implications and the ability to lead to new business models, depicting a future research agenda.
Design/methodology/approach
A structured literature review has been conducted, and 37 contributions have been analyzed and coded using a detailed research framework.
Findings
Findings underline the multiple uses and advantages of AI in agriculture and the potential impacts for farmers and entrepreneurs, even from a sustainability perspective. Several applications and algorithms are being developed and tested, but many barriers arise, starting from the lack of understanding by farmers and the need for global investments. A collaboration between scholars and practitioners is advocated to share best practices and lead to practical solutions and policies. The promising topic of new business models is still under-investigated and deserves more attention from scholars and practitioners.
Originality/value
The paper reports the state-of-the-art of AI in agriculture and its impact on the development of new business models. Several new research avenues have been identified.
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Assunta Di Vaio, Badar Latif, Nuwan Gunarathne, Manjul Gupta and Idiano D'Adamo
In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management…
Abstract
Purpose
In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.
Design/methodology/approach
Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.
Findings
The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.
Research limitations/implications
The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.
Practical implications
This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.
Originality/value
This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.
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Osamudiamen Kenneth Otasowie, Clinton Ohis Aigbavboa, Ayodeji Emmanuel Oke and Peter Adekunle
The circular economy business models (CEBMs) provide ways for firms operating in the construction industry to move from a linear to a circular approach. Thus, this study aims to…
Abstract
Purpose
The circular economy business models (CEBMs) provide ways for firms operating in the construction industry to move from a linear to a circular approach. Thus, this study aims to explore CEBM research within the construction sector to show the focus area of studies, highlighting new areas that require attention.
Design/methodology/approach
This study adopted a bibliometric approach, using the Scopus database as the data source. The keywords used for paper extraction from the database were “circular economy business” OR “circular business” AND “model” OR “models” AND “construction industry” OR “building industry”. The VOSviewer software was then used to prepare a co-occurrence and co-authorship map based on the bibliographic data gathered.
Findings
The study’s findings reveal five research clusters in the construction industry. These clusters include circular construction intelligence, modular business modelling, eco-construction, sustainable construction economics and smart energy-efficient buildings. The two most cited scholars had two publications each, while the top journals are the Journal of Cleaner Production and Sustainable Production and Consumption. This study concludes that there is a need for research within the construction sector to focus on CEBMs’ archetypes and frameworks. This will enable a smooth transition from linear to circular business models in the sector.
Research limitations/implications
The information was gathered from a single database, Scopus; hence, using other databases, including Web of Science, Google Scholar and Dimensions, might produce more articles for examination and, consequently, different findings on the subject under investigation.
Practical implications
These findings would assist researchers in considering the areas mentioned, which are yet to receive attention, and, by extension, enhance economic development while maintaining environmental sustainability.
Originality/value
This paper made a significant contribution to the body of knowledge by identifying scholars and platforms that have been instrumental in advancing CEBM research and highlighting new areas that require attention in the construction sector.
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Alex Zarifis, Christopher P. Holland and Alistair Milne
The increasing capabilities of artificial intelligence (AI) are changing the way organizations operate and interact with users both internally and externally. The insurance sector…
Abstract
The increasing capabilities of artificial intelligence (AI) are changing the way organizations operate and interact with users both internally and externally. The insurance sector is currently using AI in several ways but its potential to disrupt insurance is not clear. This research evaluated the implementation of AI-led automation in 20 insurance companies. The findings indicate four business models (BM) emerging: In the first model the insurer takes a smaller part of the value chain allowing others with superior AI and data to take a larger part. In the second model the insurer keeps the same model and value chain but uses AI to improve effectiveness. In the third model the insurer adapts their model to fully utilize AI and seek new sources of data and customers. Lastly in the fourth model a technology focused company uses their existing AI prowess, superior data and extensive customer base, and adds insurance provision.
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Paavo Ritala, Mika Ruokonen and Laavanya Ramaul
This paper aims to demonstrate how the new generative artificial intelligence (AI) tool ChatGPT changes knowledge work for individuals and what are the implications of this change…
Abstract
Purpose
This paper aims to demonstrate how the new generative artificial intelligence (AI) tool ChatGPT changes knowledge work for individuals and what are the implications of this change for companies.
Design/methodology/approach
Based on 22 interviews from informants across different industries, the authors conducted an inductive analysis on the use and utility of ChatGPT in knowledge work. Based on this initial analysis, they discovered different ways in which ChatGPT either augments human agency, makes it redundant or lacks capability in that regard.
Findings
The authors develop a 2 × 2 framework of algorithmic assistance, which demonstrates four ways in which ChatGPT (and generative AI in general) interacts with knowledge workers, depending on the usefulness of ChatGPT in particular tasks and the type of the task (routine vs creative).
Practical implications
Based on the insights from the interviews, the authors propose a set of actionable questions for individual knowledge workers and companies from four viewpoints: skills and capabilities; team structure and workflow coordination; culture and mindset; and business model innovation.
Originality/value
To the best of the authors’ knowledge, this study is among the first to identify and analyze the use of ChatGPT by knowledge workers across different industries.
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Rodrigo Rabetino, Marko Kohtamäki and Tuomas Huikkola
This paper studies the Digital Service Innovation (DSI) concept by systematically reviewing earlier studies from various scholarly communities. This study aims to recognize how…
Abstract
Purpose
This paper studies the Digital Service Innovation (DSI) concept by systematically reviewing earlier studies from various scholarly communities. This study aims to recognize how recent advances in DSI literature from different research streams complement and can be incorporated into the growing digital servitization literature to define better and understand DSI.
Design/methodology/approach
After systematically identifying 123 relevant articles, this study employed complementary methods, such as author bibliographic coupling, linguistic text mining/textual analysis and qualitative content analyses.
Findings
This paper first maps the intellectual structure and boundaries of the DSI-related communities and qualitatively assesses their characteristics. These communities are (1) Innovation for digital servitization, (2) Service innovation in the digital age and (3) Adoption of novel e-services enabled by information system development. Next, the composition of the DSI concept is examined and depicted to comprehend the notion's critical dimensions. The findings discuss the range of theories and methods in the existing research, including antecedents, processes and outcomes of DSI.
Originality/value
This study reviews, extends the understanding of origins and critically evaluates DSI-related research. Moreover, the paper redefines and clarifies the structure and boundaries of the DSI-concept. In doing so, it elaborates on the substance of DSI and identifies the essential themes for its understanding and conceptualization. Thus, the study helps the future development of the concept and allows knowledge accumulation by bridging adjacent research communities. It helps researchers and managers navigate the foggy emerging research landscape.
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Nadeem Ali El-Adaileh and Scott Foster
The purpose of this paper is to present a systematic literature review to determine the factors that relate to successful business intelligence (BI) system implementation.
Abstract
Purpose
The purpose of this paper is to present a systematic literature review to determine the factors that relate to successful business intelligence (BI) system implementation.
Design/methodology/approach
The study has a collection of literature that highlights potential references in relation to factors for system implementation in relation to BI. There is the employment of “content analysis”, given that the study purpose is the achievement of deep understanding of the variety of factors of implementation that other researchers have previously identified.
Findings
An initial investigation of 38 empirical studies on the implementation of BI led to ten factors being compiled. Difficulties in implementation were found to exist in relation to the operationalisation of large numbers of factors within organisations. The implementation factors were analysed and then sorted into a descending order based upon their frequency of occurrence.
Research limitations/implications
The research is limited to consider BI implementation factors. Moreover, literature is collected from selected databases and journals from 1998 to 2018.
Practical implications
Researchers of BI may, within the future, develop models for the measurement of the implementation level of BI within industries along with the sustaining of them. Moreover, work-based learning industries can benefit by adopting the results of this study for the effective implementation of BI. The implementation factors can be seen as key constructs upon which there may be the undertaking of more statistical analyses.
Originality/value
The original output from this research can help researchers’ in the future in enhancing identification of studies that are relevant for the review of literature for their research.
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Sami Rusthollkarhu, Pia Hautamaki and Leena Aarikka-Stenroos
Digital ecosystemic business environments challenge dyadic approaches to value creation and particularly to business-to-business (B2B) sales. This paper aims to offer a novel…
Abstract
Purpose
Digital ecosystemic business environments challenge dyadic approaches to value creation and particularly to business-to-business (B2B) sales. This paper aims to offer a novel conceptualization of the connection between value creation and B2B sales, which indicates practical implications and builds an agenda for future research.
Design/methodology/approach
This conceptual paper integrates theoretical insights on service-dominant logic, service ecosystems, interactional value co-creation and B2B sales. This paper uses anecdotal evidence from the field of B2B sales to illustrate theoretical concepts developed in the paper.
Findings
The paper develops the concept of value idea emergence (VIE), the process through which B2B entities become aware of a pursuable benefit. The paper further proposes that value (co-)creation in ecosystems happens through VIE’s intertwinement with the process of value proposition creation, a process, which includes all activities needed to bring a value proposition to a customer. The paper then discusses the role of B2B in these processes and proposes an agenda for future research.
Practical implications
The novel conceptualizations of value (co-)creation can help B2B sales managers to understand the ecosystemic nature of the interactions that affect sales and value creation in the current business environment.
Originality/value
The paper contributes to the literature on B2B sales and value creation by proposing a novel concept of VIE, introducing a conceptual model of interactive value (co-)creation in ecosystems and reformulating the role of B2B sales in value creation. These theory-developing insights can be used to guide both academic and managerial attention to interactions happening in the ecosystem outside of the buyer-seller dyad.
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