Strategic enablers of business intelligence in marketing: Insights from the digital transformation of Jordanian firms

Although Business Intelligence (BI) is one of the most essential technologies to be purchased, the implementation of many BI applications fails. The reasons for this failure are not clear and still not well investigated. Resource-based View (RBV) and dynamic capability theory could help to overcome this gap and to provide an appropriate theoretical basis for future research in BI area. It is considered that BI capabilities may be critical functionalities that help organizations to improve their performance and adopt to environmental change. The research objectives for this study are: (1) conceptualization and discussion on BI dynamic capability, (2) building the comprehensive framework of BI capabilities. In order to address these objectives, the remainder of the paper is structured as follows: The first sections provide the theoretical foundations of BI, RBV and dynamic capability theory. Next, the BI capability was conceptualized. Finally, a model of BI as a dynamic capability, was proposed. The study was based mainly on: (1) a critical analysis of literature, (2) an observation of different BI initiatives undertaken in various organizations, as well as on (3) interviews with managers and experts in BI. The results of this study can be used by IT and business leaders as they plan and develop BI capabilities in their organizations.

This study investigates how business intelligence capabilities (BIC) influence competitive performance (COP) in the Thai hotel industry, with a particular focus on the mediating role of innovation capability (INC). Drawing on the Resource-Based View and Dynamic Capabilities Theory, the study develops a structural model proposing that BIC improves COP both directly and indirectly through INC. Using stratified random sampling based on classifications from the Tourism Grading Council of Thailand, data were collected from 180 hotel managers through a structured questionnaire. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to test the proposed relationships. The results show that BIC does not directly affect COP, but has a strong and significant indirect effect through INC, indicating that innovation capability fully mediates this relationship. These findings highlight the importance of strengthening innovation to convert business intelligence insights into a competitive advantage. The study adds to the literature on business intelligence and innovation management by providing empirical evidence from the hospitality sector in an emerging market. It also stresses the strategic need to align business intelligence systems with innovation activities to achieve sustainable performance. The study offers originality by demonstrating that innovation capability fully mediates the link between business intelligence capabilities and competitive performance in the underexplored context of Thai hotels.

Scholars and practitioners have trumpeted business intelligence (BI) capability as a game-changer due to its significant impact on firm performance. Despite these claims, the amplifying and underlying mechanisms governing the relationship between BI capability and organizational performance are still in their infancy. This research examines the nexus between BI capability, decision-making speed, comprehensiveness, and organizational performance. This study, drawing on knowledge-based theory, proposes a conceptual model to explain how BI capability influences organizational performance through decision-making speed and comprehensiveness and the moderating role of firm size. The proposed moderated-mediated model was tested using survey data from 236 respondents occupying leadership positions in various Jordanian industries. Partial least squares structural equation modeling (PLS-SEM) was used to diagnose the proposed model. BI capability indirectly affects firm performance through decision-making speed and comprehensiveness. These mediating effects do not vary by company size. This paper contributed theoretically and practically to the BI framework considering decision-making, firm performance, and firm size. Implications for theory-building and practice are described.

Purpose This article investigates the effect of business intelligence (BI) capacity on the adoption of circular economy (CE) practices. Drawing on the quality of decision-making as a mediator and innovation climate (IC) and continuous improvement (CI) as moderators, it takes the research on open innovation process practices further. Through the resource-based view (RBV)/dynamic capabilities (DC) view, the study explains a conditional-process model that separates the bundles of BI capabilities (sensing, transforming and driving). In this model, decision-making quality (DMQ) is the middle link. IC and CI are the outside conditions that influence the results. Design/methodology/approach The study employed a quantitative research design. The data was derived from a sample of 360 employees in governmental organizations throughout the United Arab Emirates (UAE). Structural equation modeling using partial least squares was employed for data analysis. The model examines three types of pathways: direct effects, indirect effects where BI influences CE outcomes through DMQ, and moderated effects, in which IC shapes the relationship between BI and DMQ, while CI influences the link between DMQ and CE outcomes. This analytical structure provides theory-driven evidence that extends beyond mere correlation. Findings The results reveal that those BI capabilities, particularly driving and transforming capabilities, positively influence CE implementation by enhancing DMQ. Sensing capability showed no meaningful effect. This result shows that just having good information awareness is not enough. It needs support from action-focused capabilities, like transforming and driving, to produce outcomes linked to CE. Additionally, an innovation-supportive climate strengthens the relationship between BI capabilities and DMQ, while CI practices amplify the link between DMQ and CE implementation. Taken together, the results show a pathway that moves from capability to process to outcome. They also explain where the moderators play a role: IC works at the early stage, while CI acts at the later stage, all within the UAE public sector context. Originality/value This study contributes to the literature by integrating BI capabilities, decision-making processes and organizational climate factors in the context of CE. The new value of this paper comes from three points. First, it separates BI capability bundles from the wider ideas of big data analytics. Second, it identifies DMQ as a small but key foundation that connects BI to CE results. Third, it sets IC and CI as the outside conditions that stretch RBV/DC beyond simple consolidation. All of this is shown with public-sector evidence from the UAE. It underscores the strategic value of aligning technological and cultural enablers to drive sustainable practices in public sector organizations.

In today’s dynamic business environment, business organisations are driven by uncertainties and turbulence in market trends, in developed and emerging economies alike. Strategic agility allows businesses to adapt fast to changes and to be cost-effective in vigorous business settings. Industry Revolution 4.0 has created new challenges for Business Intelligence (BI) to analyse and solve problems efficiently, thus allowing senior managers to make fast decisions. The value of such BI projects on businesses depends largely on the BI capabilities. Previous researches have shown that BI capabilities have been considered an important function that enhances organisational performance, however, the impact of BI capabilities on organisational performance remains poorly understood in emerging economies such as Malaysia. The main objective of this paper is to present an integrated conceptual model which first examines the influence of Information Technology (IT) governance on BI capabilities moderated by risk management; and consequently the impact of BI capabilities on organisational performance moderated by the business strategy alignment. This conceptual model is developed by synthesising previous-related studies and is based on the Dynamic Capabilities Theory. This paper contributes to the field of organisational performance in the context of BI capabilities, while examining the interplay of IT governance, risk management as well as business strategy alignment in this context. Practically, this paper suggests the importance of IT governance as well as risk management on BI capabilities. It also justifies the crucial role of BI capabilities and business strategy alignment which impact the performance of business organisations in emerging economies.

Business intelligence has emerged as a crucial topic in contemporary business research, with various factors being addressed across multiple domains.This study aims to investigate the relationship between business intelligence capabilities and business outcomes, as well as the moderating role of competitive intelligence in this association.Employing a quantitative research approach, data was gathered from small and medium-sized enterprises (SMEs) in Jordan, with 319 participants, comprising owners and managers, contributing to the sample.The partial least squares structural equation modeling (PLS-SEM) method was utilized for key analytical procedures.The findings revealed significant effects of all hypothesized relationships, demonstrating a substantial moderating influence of competitive intelligence on the association between business intelligence capabilities and business outcomes.Additionally, the results highlighted the significant moderation of competitive intelligence within this relationship.This research not only corroborates existing evidence in the literature but also addresses knowledge gaps in the field by proposing a novel conceptual framework that incorporates new factors for a more comprehensive understanding of the subject matter.

This study examines how Business Intelligence (BI) capabilities influence environmental performance (EP) in manufacturaing supply chains, with a focus on the mediating roles of Green Supply Chain Management (GSCM) and Supply Chain Integration (SCI) and the moderating role of Blockchain Integration (BCI). Addressing a critical research gap in digital sustainability, particularly in emerging markets, this study integrates the Resource-Based View (RBV) theory, Natural Resource-Based View (NRBV) theory, and Dynamic Capabilities View (DCV) theory to develop a theoretically grounded framework. Data were collected via a cross-sectional survey of 231 managers in 65 firms in Jordan and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings reveal that while BI does not directly enhance EP, it significantly improves GSCM and SCI, which in turn mediate its influence on EP. GSCM fully mediates this relationship, while SCI provides partial mediation. BCI did not demonstrate a significant moderating effect. These results suggest that BI must be embedded within green and integrative operational systems to drive sustainability outcomes. This study contributes novel insights into how digital capabilities translate into environmental gains in underrepresented contexts and provides actionable guidance for firms and policymakers aiming to align digital transformation with environmental objectives.

This paper intends to conduct a study review and propose a conceptual framework to be used in the implementation of POS system targeted for Small and Medium Enterprises in Indonesia. The study covers THREE domain areas which includes review on similar systems, software & tools utilizations together with system architecture and design. The utilization of appropriate POS system with Business Intelligence capability will enable better decision making through insight analysis. Thus, this paper develops a conceptual framework in which leads towards the implementation of the POS System with Business Intelligence capability and uses an existing SME in Indonesia as the subject of the study

There are ongoing predictions that business intelligence (BI) capabilities will lead to the improved performance of new service products (NSPs). However, theoretical and empirical research have yet to explain the nature of this contribution. Based on dynamic capability theory, the current research suggests a model explaining how BI capabilities could impact the performance of NSPs. Specifically, it suggests that BI capabilities could lead to better NSP performance by facilitating proximal conditions of NSP, including customer value anticipation capacity, NSP innovativeness capacity and new product speed to market capacity. The results, based on responses by 583 service firms’ marketing and sales directors, indicated that benefits from BI capabilities could be realised indirectly via their intermediate impact on proximal conditions, which in turn influence the outcome of the impact of variables on NSP performance. The contribution of this research is a better theoretical understanding and advanced managerial insight into practices on the use of BI as a tool to enhance NSP performance instead of relying on the prevailing anecdotal evidence.

The study's objective is to investigate the business intelligence (BI) capabilities of public sector organizations as well as the essential success variables associated with those skills. The research was carried out due to the fact that there has been a growth in the usage of BI, and a large number of the tools that are utilized in its operations are not reviewed, despite the fact that the influence of the user is considered to be one of the primary concerns associated with it. The study used a quantitative research method to look at Malaysian organizations and come up with some hypotheses to test the variables related to BI's capabilities in the public sector of an organization. There were good, reasonable samples of people who took part in the research. A questionnaire was used to get the information. When examined, the findings confirmed the correctness of every hypothesis made. Therefore, there is a connection between elements involving infrastructure, teams, data, top-level support, and user participation in data quality. The findings of this study helped determine whether or not there is a correlation between data quality and the speed with which business data is updated across geographies, the precision with which data is captured, the timeline with which it is processed and reported, and the ease with which key performance measures can be established at various operational levels within the company.

ObjectivePopulation health management (PHM) is a promising data-driven approach to address the challenges faced by health care systems worldwide. Although Business Intelligence (BI) systems are known to be relevant for a data-driven approach, the usage for PHM is limited in its elaboration. To explore available scientific publications, a systematic review guided by PRISMA was conducted of mature BI initiatives to investigate their decision contexts and BI capabilities.Materials and MethodsPubMed, Embase, and Web of Science were searched for articles published from January 2012 through November 2023. Articles were included if they described a (potential) BI system for PHM goals. Additional relevant publications were identified through snowballing. Technological Readiness Levels were evaluated to select mature initiatives from the 29 initiatives found. From the 11 most mature systems the decision context (eg, patient identification, risk stratification) and BI capabilities (eg, data warehouse, linked biobank) were extracted.ResultsThe initiatives found are highly fragmented in decision context and BI capabilities. Varied terminology is used and much information is missing. Impact on population’s health is currently limited for most initiatives. Care Link, CommunityRx, and Gesundes Kinzigtal currently stand out in aligning BI capabilities with their decision contexts.Discussion and ConclusionPHM is a data-driven approach that requires a coherent data strategy and understanding of decision contexts and user needs. Effective BI capabilities depend on this understanding. Designing public-private partnerships to protect intellectual property while enabling rapid knowledge development is crucial. Development of a framework is proposed for systematic knowledge building.

Purpose This study aims to investigate the relationship between Technological Readiness (TR) and Job Performance (JP), mediated by Digital Health Transformation (DHT) and nurses’ Innovative Work Behavior (IWB). Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5,000 bootstrap resamples, the authors assess direct relationships as well as two sequential mediations. The authors present standardized coefficients (β), explained variance (R²), effect sizes (f²) and mediation strength (variance accounted for [VAF]) to quantify practical significance. Design/methodology/approach A quantitative, cross-sectional design was used, with data gathered from 300 registered nurses through a structured survey. The research model was analyzed using PLS-SEM. Constructs were grounded in the Technology–Organization–Environment (TOE) framework and Social Cognitive Theory (SCT). Findings The results substantiate all eight hypothesized relationships. TR is found to significantly predict both DHT and IWB and directly influence JP. Furthermore, DHT positively affects both IWB and JP, while IWB exhibits a robust predictive relationship with JP. Mediation analysis indicates that DHT mediates the relationship between TR and IWB, and IWB mediates the relationship between DHT and JP. These findings validate the proposed integrated model and highlight the importance of behavioral mechanisms in digital transformation. Practical implications Hospital administrators and policymakers should prioritize the enhancement of technological readiness and the fostering of an innovative culture among nursing staff. Effective digital transformation requires both systemic investment and the empowerment of individual behaviors. For health systems in developing countries, infrastructure deficiencies (e.g. intermittent internet and power supply) may weaken downstream connections (DHT → IWB; IWB → JP). The authors delineate strategies for mitigation – including tiered technology readiness-based training, low-bandwidth and offline-first deployment and workflow-integrated enablement – aimed at transforming digital investments into innovative work behaviors and enhanced performance. Originality/value This study contributes a novel, empirically validated model that links technological readiness and innovative behavior to job performance within the digital health-care framework. This study examines an empirically grounded behavioral pathway that connects technological readiness, digital health transformation, innovative work behavior and job performance among nurses in public hospitals. By transcending traditional adoption-intention models, such as the Technology Acceptance Model (Davis, 1989), and enhancing implementation frameworks like the Nonadoption, Abandonment, Scale-up, Spread IT Information Technology (NASSS) framework (Greenhalgh et al., 2017), this research addresses the paucity of empirical evidence regarding the integration of digital innovations into routine practice within resource-constrained health systems (Dionisio et al., 2023).

The concept of Business Intelligence (BI) was first proposed in the late 1980-s. Since then the field of BI has experienced the rapid extension and development. More than 50 billion dollars have already been invested in different BI tools and application software, such as new desktop data analysis tools, data warehousing technologies, data extraction middleware and many other tools and techniques into the market. But not all the BI initiatives are successful. This paper posits that a key antecedent of BI success is having the right BI Capabilities, and right BI Capabilities depend on the Decision Environment in which the BI is used. Research suggests that a lack of fit between an organization and its BI is one of the reasons for lack of success. The match between the Decision Environment and what a BI provides has been studied as an indicator of success. The theoretical framework is proposed in this paper to study relationship between BI Capabilities, BI Success and Decision Environment

Business intelligence ability to enhance organizational performance and performance evaluation capabilities by improving data mining systems for competitive advantage

This study examines the influence of information technology (IT) infrastructure capabilities, business and IT planning capabilities, proactive attitudes toward IT on digital transformation, and their impact on the sustainable competitive performance of MSMEs in Indonesia. This study uses a quantitative approach with data collection through a questionnaire with 783 MSME respondents. Data analysis uses the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The results show that IT infrastructure capabilities, business and IT planning capabilities, and proactive attitudes toward IT have a positive and significant influence on digital transformation. Furthermore, digital transformation has also been shown to have a significant influence in improving sustainable competitive performance, such as productivity, operational efficiency, and customer relationships. These findings emphasize the importance of synergy between strategic planning and technological readiness, as well as a proactive digital culture in the MSME environment. This study provides empirical contributions from the context of developing countries and offers practical recommendations for stakeholders in promoting MSME digital readiness.