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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 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.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

The purpose of this paper is to demonstrate the relevance of business intelligence (BI) in businesses in general and tourism firms in particular. BI has been hailed as an innovation that can propel businesses that adopt the system to high productivity and efficiency. This paper confirms that view but further adds that BI also enhances a business’s competitiveness.

This paper reviews literature on the use of BI in tourism. Although current literature is largely fragmented, focusing on BI, the tourism industry and the notion of competitiveness separately, this paper makes an attempt to bring the three sub-themes in the same study and highlights their interconnectedness. The study adopts two environmental analysis models to better analyze this matter. First is the environmental analysis model as based on Downes’s modification of Porter’s five forces framework. The second model used is the resource-based view approach to business environmental analysis.

This paper affirms that the tourism industry is one of those industries that continue to benefit from the advantages that come with the adoption of a BI system. Literature shows that the tourism industry was one of those that first adopted BI in order to benefit from the benefits that come with its adoption. Such advantages include flexible and user friendly tourists’ data capture, storage, retrieval, processing and analytical capabilities.

This was a largely literature review-based study. There is, therefore, room for strengthening its findings by conducting field work and mixed methods research for more robust results.

This study will surely benefit the tourism industry and business in general from its highly favorable conclusions to the benefits that come with the adoption of a BI system. It can also be used as a reference in to the tourism field, especially aggregating important concepts and literature that can help future practical studies.

Society will also benefit from this study in terms of the new knowledge that has been generated. Members of society will then be in a position to demand products and services that are a result of innovation and informed decision making.

Although this paper is largely based on literature, the conclusions reached are those of the authors. A close assessment of the literature in BI and the tourism industry was done, resulting in the conclusions reached by the authors.

Roadmapping has been used as an approach to support market, product and technology-integrated planning, resulting in a document commonly known as a roadmap. Despite the gains made in relation to the technique, recent studies indicate that most users leave or have difficulties in sustaining the process (i.e. maintaining the updated roadmaps). This paper aims to present a framework for continuous roadmap updating that incorporates principles from agile management fields.

The framework was developed through action research in a manufacturing firm in the construction industry.

The results demonstrate a positive impact on the degree of continuous information monitoring, roadmap credibility and use of the roadmap during innovation strategy decisions.

The key contribution of this framework is the demonstration of a new strategy for carrying out the maps in which information is internalized by the organization itself, using agile teams, without commissioned specialists and as part of the work standards.

The purpose of this paper is to focus on an information technology (IT) deployment project in the specific field of agricultural cooperatives. It also aims to underline the importance of the IT implementation phase, but also the pre-implementation phase.

A four-year canonical action research project was conducted within a network of more than 300 agricultural cooperatives. Research was carried out both during the IT implementation and after deployment. Key information was gathered through unstructured and unofficial interviews, observations, field notes, meetings, focus groups, and documentary analysis.

Despite user resistance behavior, the findings show that information systems (IS) implementation may lead to unexpected results that extend beyond the tool’s initial objectives. Indeed, four hidden facets of the tool were revealed: inductor, symbol, pretext, and reference.

Although the research is limited to one single-case study, it puts the emphasis on in-depth research, vs cross-sectional data collection, to analyze the relationship between IT implementation initiatives and organizational intelligence. Furthermore, the authors argue that while IS literature has separately developed related theories (actor-network theory, competitive intelligence), the authors conceptualize a whole theoretic system interrelating the two above-stated theories.

The implication for IS practitioners is that, by focusing only on experiences that have occurred during IT implementation, one may disregard critical information, behaviors and knowledge from unforeseen effects that have occurred after implementation. In future IT projects, IS managers therefore need to capitalize on post-implementation knowledge, through sociology of translation and competitive intelligence, in order to anticipate potential diversions from the initial objectives. Finally, while most IT implementation methods tend naturally to manage resistance maximize users’ satisfaction and to reduce potential resistance, the authors support an alternative approach. It consists into enhancing resistance in order to anticipate and resolve latent resistance behaviors directly or indirectly related to the project.

Despite widespread literature on resistance, appropriation or acceptance during IT projects, there is little research that addresses the impact of IT projects on organizational intelligence, and the kind of behaviors that lead to its failure or success. In the case, the implemented IT tool revealed hidden structural and organizational roles, which were unanticipated by IT designers and managers.

Digital transformation affected modern society influencing how businesses cooperate and produce value. In this context, Artificial Intelligence plays a critical role. This study aims to explore the role of Artificial Intelligence in organisational positioning within the market, influencing firms' competitiveness. In this vein, this research seeks to respond to the following research question: How does AI impact the competitive advantage of healthcare organizations?.

To tackle the research question, an explorative analysis using the case study method to investigate an international healthcare center in Dubai was conducted. Nine semi-structured interviews were conducted with the head and the members of the robotic surgery team in CMC Dubai to thoroughly understand what the components of the robotic approach are and how the arrangement before the introduction of this innovative technique while shedding light on the added value and the advantages of adopting such technique on both patient safety and patient satisfaction. Additionally, archival data and online documentation (e.g. industry reports, newspaper articles and internal documents) were analyzed to obtain data triangulation.

The results highlight three primary outcomes influenced by implementing AI in organizational processes: clinical, financial and technological outcomes. The study will offer interesting non-studied insights about the implementation of Artificial Intelligence tools in the healthcare sector and specifically robotic surgeries, and to which extent this will contribute and represent a competitive advantage. Results will hopefully insert a brick in the wall of the impact of AI tools on the quality and the results of surgical operations while emphasizing the benefits of integrating AI in surgical practice.

This study offers interesting theoretical and practical implications. It opens a new perspective to understand and manage AI tools in service. This research is not without limits providing valuable insights for future research.

This study aims to examined the impact of business intelligence (BI) and supply chain ambidexterity (SCA) on operational performance (OP), contributing to dwarf knowledge in small- and medium-sized enterprises (SMEs) in the context of emerging economies. The mediating role of SCA was considered in the proposed model.

The study used the quantitative method to investigate the interdependencies between variables. As a result, 216 senior and middle managers/owners of SMEs in Ghana were surveyed using a purposive and convenient sampling method. SPSS version 23 and Smart PLS version 3 were used to conduct the research.

While the direct link among BI, SCA and OP was confirmed. The outcome also showed that SCA plays a significant mediating role between BI and OP among SMEs.

The outcome of the study indicates that SCA encourages the use of BI to generate superior OP among SMEs. This knowledge will improve the performance of SMEs and their ability to withstand the competition in the global market.

With the discovery of this study, the theory of a resource-based view now has some empirical evidence behind it. As a result, SMEs prioritize aspects that could improve their operations and implement tactics that would nurture better performance and competitive advantages.

The purpose of the study is to identify and analyze critical mediating and moderating market intelligence challenges faced by the SMEs when implementing corporate social responsibility (CSR) based on an applied market-oriented business model (MOBM).

Focusing on developing CSR-integrated market intelligence, this study uses an action research method by analyzing four case studies. Data is collected through interviews, interactive and knowledge-sharing meetings and on-site observations. The study is part of a larger European Union project using the developed MOBM to follow the four companies' CSR implementation and learning process over a 14-month period. The action research includes seven meetings; between these, the researchers introduced the SMEs to different business focus areas, where CSR is a vital part of the MOBM.

This study shows that the SMEs are too technology-focused and have little initial idea of how to integrate CSR advantages for market intelligence into their internationalization. The MOBM model offers insights and knowledge on the strength and weakness of the internal organization to meet challenges in internationalization.

Via case study and action research, this study spotlights the challenges that SMEs face in the CSR implementation process and how they deal with those challenges to develop market intelligence competence internally. Instead of following a traditional research approach, the current study applies a CSR-based method where the SMEs go through a knowledge development process that originated from a theoretically designed MOBM.

This paper aims to explore how artificial intelligence (AI) technologies have redefined the hospitality industry. It develops a theoretical framework to evaluate its impact on employee engagement, retention and productivity levels, stemming from its potential implications for service quality and customer satisfaction.

Based on the exploration of relevant literature, role theory and service-profit chain were used to develop – role-service-profit chain.

Role-service-profit chain is an analytical tool which has strong implications for investment and deployment analysis of the new technologies in hospitality and tourism businesses. It proposes how managers can evaluate how the role expectation of technological innovations relate to service quality and customer satisfaction through its impact on employee-related outcomes (such as employee engagement, retention and productivity), and assess the corresponding impact on profitability and growth, in the context of their own unique internal environment and position in the market.

Although an empirical assessment of the hypothesised relationships in the model is required to evaluate and validate it in the hospitality industry, role-service-profit chain presents promising implications for tourism and hospitality practice and future research.

Role-service-profit chain is an analytical tool from which managers can make improvements on talent and talent management practices and adjust expectations and behaviours in ways that facilitate improvements in service quality and customer satisfaction.

This paper makes an important contribution to hospitality and tourism literature, as it explores how AI technologies implemented to improve on talent and talent management practices impact on service quality and customer satisfaction, and develops analytical tools by which this may be evaluated.