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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.

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.

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.

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.

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.

This paper aims to examine how competitive intelligence (CI) relates to the strategy formulation process of firms.

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.

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.

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.

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.

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.

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.

The research is limited to consider BI implementation factors. Moreover, literature is collected from selected databases and journals from 1998 to 2018.

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.

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.

This study examines the effect of resources (e.g. tangible resources, human skills and intangible resources) that are utilized as a bundle of standard practices on sustainable net zero economy implementation and their further impact on financial, environmental and social performance among small- and medium-level enterprises in business markets. The moderating effect of big data analytical intelligence is also examined.

The samples were selected from the paper and chemical manufacturing industries of South Africa. The data analysis was performed using variance-based structural equation modeling.

The results show that tangible resources, human skills and intangible resources positively influence sustainable net zero economy adoption. However, intangible resources have a more substantial influence on sustainable net zero economy implementation. This shows that adopting a sustainable net zero economy depends more on a bundle of common practices, including sustainability culture, employee training and knowledge management, and managers must create the necessary action plans accordingly. In addition, sustainable net zero economy adoption positively influences financial performance, environmental performance and social performance. However, sustainable net zero economy adoption has a more substantial influence on social performance. Therefore, implementing a net zero economy will be more advantageous to society and to local communities.

To achieve a sustainable net zero economy, managers should recognize the significance of resource management. While managing tangible resources and human skills is crucial, intangible resources, such as culture and organizational learning, require more attention. Additionally, the ability of small- and medium-sized enterprises to explore, store, share and apply knowledge is crucial to achieving net zero. Therefore, managers should make use of Industry 4.0-based digital technologies for effective knowledge management. Moreover, net zero economy adoption can significantly enhance societal performance. Hence, while making budgeting decisions, managers must consider the potential of the firm's resources to improve social performance.

This study is the first to investigate the impact of human skills and tangible and intangible resources on the adoption of a sustainable net zero economy by companies, using empirical evidence. The research expands on the concept of the practice-based view (PBV) in the implementation of sustainable net zero economies by small- and medium-sized business-to-business enterprises.

The purpose of this study is to determine the effect of business intelligence on job satisfaction in the Saudi Electricity Company in the Asir. It aims to evaluate employee job satisfaction after adopting a BI system for job practices.

A mixed-method including descriptive, questionnaire for data collection and analytical approach was used. The random sample population consists of 354 employees out of 3,000.

It is found that the implementation of a BI system and the associated practices have a statistically significant effect on employee job satisfaction. The study recommends the adoption of BI systems for organizational activities. Such organizations must consider the latest BI tools for solving business problems.

To the best of authors' knowledge, the current study is the first attempt to evaluate the performance of BI practices in the region and in context of employee job satisfaction. This will contribute to understanding the job satisfaction in similar organizational environment.

This paper expands theory on strategists by investigating how non-executive strategy professionals in multi-business firms strategize. In focus is the strategizing of two groups of non-executive strategy professionals: a corporate strategy team and eleven business strategists employed in each of the incorporated units.

A case study design was employed to explore privileged accessed data to gain first-hand in-depth qualities of strategists' work. The design was characterized by phenomenon driven immersed participatory insider research with retrospective reflection and theorizing. Data includes strategies, interview data, calendars, meeting minutes, workshop material and observational field notes.

Non-executive strategy professionals in multi-business firms are either employed at the corporate center or in the peripheral businesses. Based on this location and their individual experiences they assume an exclusive content or an inclusive process strategizing orientation. In practice, the groups strategize tightly together.

Case studies are useful in explorative research providing thick descriptions. While empirically rich, the results of this study are limited by the context of one single case. Future research is encouraged to confirm, contradict and refine the results presented.

The insights from this study can help organizations regarding how to employ strategy professionals in multi-business firms.

This paper contributes to a recognized need to explore strategists' work. In contrary to the majority of existing research, focusing on senior management and/or strategy formulation, this paper highlighted non-executive strategy professionals' strategizing.

This study aims to provide a picture of the current state of art in the use of big data for decision-making processes for the management of health-care organizations.

A systematic literature review was carried out. The research uses two analyses: descriptive analysis, describing the evolution of citations; keywords; and the ten most influential papers, and bibliometric analysis, for content evaluation, for which a cluster analysis was performed.

A total of 48 articles were selected for bibliographic coupling out of an initial sample of more than 5,000 papers. Of the 48 articles, 29 are linked on the basis of their bibliography. Clustering the 29 articles on the basis of actual content, four research areas emerged: quality of care, quality of service, crisis management and data management.

Health-care organizations believe strongly that big data can become the most effective tool for correctly influencing the decision-making processes. Thus, more and more organizations continue to invest in big data analytics, and the literature on this topic has expanded rapidly. This study seeks to provide a comprehensive picture of the different streams of literature existing, together with gaps in research and future perspectives. The literature is mature enough for an analysis to be made and provide managers with useful insights on opportunities, criticisms and perspectives on the use of big data for health-care organizations. However, to date, there is no comprehensive literature review on the big data analysis in health care. Furthermore, as big data is a “sexy catchphrase,” more clarity on its usage may be needed. It represents an important tool to be investigated and its great potential is often yet to be discovered. This study thus sheds light on emerging issues and suggests further research that may be needed.

This study is focused to support an ongoing development project of the case company's current state and the challenges of the order-to-cash (O2C) process. The O2C process is the most visible process to the customer, and therefore, its punctual and fluent order management is vital. It is observed that the high degree of manual work in the O2C process causes mistakes, delays and rework in the process. The purpose of this article is therefore to analyze the case company's current state of the O2C process as well as to identify the areas of development in this process by deploying the means of Lean Six Sigma tools such as value stream mapping (VSM).

The study was conducted as a mix of quantitative and qualitative analysis. Based on both the quantitative and qualitative data, a workshop on VSM was organized to analyze the current state of the O2C process of a case company, engaged in the energy and environment sector in Finland.

The results found that excessive manual work was highly connected to inadequate or incorrect data in pricing and invoicing activities, which resulted in canceled invoices. Canceled invoices are visible to the customer and have a negative impact on the customer experience. This study found that by improving the performance of the O2C process activities and improving communication among the internal and external stakeholders, the whole O2C process can perform more effectively and provide better customer value.

The O2C process is the most visible process to the customer and therefore its punctual and fluent order management is vital. To ensure that the O2C process is operating as desired, suitable process performance metrics need to be aligned and followed. The results gathered from the case company's data, questionnaire interviews, and the VSM workshop are all highlighted in this study. The main practical and managerial implications were to understand the real-time O2C process performance, which is necessary to ensure strong performance and enhance continuous improvement of the O2C process that leads to operational excellence and commercial competitiveness of the studied case company.

Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a metaphor to introduce process mining as an essential tool for data scientists and business analysts. The purpose of this paper is to illustrate that process mining can do with events what spreadsheets can do with numbers.

The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example, the different types of process mining are explained. Where spreadsheets work with numbers, process mining starts from event data with the aim to analyze processes.

Differences and commonalities between spreadsheets and process mining are described. Unlike process mining tools like ProM, spreadsheets programs cannot be used to discover processes, check compliance, analyze bottlenecks, animate event data, and provide operational process support. Pointers to existing process mining tools and their functionality are given.

Event logs and operational processes can be found everywhere and process mining techniques are not limited to specific application domains. Comparable to spreadsheet software widely used in finance, production, sales, education, and sports, process mining software can be used in a broad range of organizations.

The paper provides an original view on process mining by relating it to the spreadsheets. The value of spreadsheet-like technology tailored toward the analysis of behavior rather than numbers is illustrated by the over 20 commercial process mining tools available today and the growing adoption in a variety of application domains.

The purpose of this paper is to develop Delphi methodology toward a holistic method for forecasting market change. Delphi methodology experienced its culmination in marketing research during the 1970s–1980s, but still has much to offer to both marketing scholars and practitioners in contexts where future market changes are associated with ambiguity and uncertainty.

This study revives the Delphi methodology by exemplifying how a recently developed framework on market change can be combined with the Delphi technique for data collection to support forecasting activities and research. The authors demonstrate the benefits of the improved methodology in an empirical study on the impact of the fifth generation of wireless communications technologies (5G) on the Finnish media market.

The developed methodological approach aids marketing scholars in categorizing and analyzing the data collected for capturing market change; and better guiding experts/respondents to provide holistic projections of future market change. The authors show that using a predefined theoretical framework in combination with the Delphi method for data collection and analysis is beneficial for studying future market change.

This paper develops Delphi methodology and contributes with a novel methodological approach to assessing market change.