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Business intelligence (BI) systems and tools are deemed to be a transformative source with the potential to contribute to reshaping the way different healthcare organizations’ (HCOs) services are offered and managed. However, this emerging field of research still appears underdeveloped and fragmented. Hence, this paper aims to reconciling, analyzing and synthesizing different strands of managerial-oriented literature on BI in HCOs and to enhance both theoretical and applied future contributions.

A literature-based framework was developed to establish and guide a three-stage state-of-the-art systematic literature review (SLR). The SLR was undertaken adopting a hybrid methodology that combines a bibliometric and a content analysis.

In total, 34 peer-review articles were included. Results revealed significant heterogeneity in theoretical basis and methodological strategies. Nonetheless, the knowledge structure of this research’s stream seems to be primarily composed of five clusters of interconnected topics: (1) decision-making, relevant capabilities and value creation; (2) user satisfaction and quality; (3) process management, organizational change and financial effectiveness; (4) decision-support information, dashboard and key performance indicators; and (5) performance management and organizational effectiveness.

To the authors’ knowledge, this is the first SLR providing a business and management-related state-of-the-art on the topic. Besides, the paper offers an original framework disentangling future research directions from each emerged cluster into issues pertaining to BI implementation, utilization and impact in HCOs. The paper also discusses the need of future contributions to explore possible integrations of BI with emerging data-driven technologies (e.g. artificial intelligence) in HCOs, as the role of BI in addressing sustainability challenges.

The present study shows that the implementation and development of enterprise resource planning (ERP) systems as a technological innovation provide a competitive advantage that helps to improve the functionality of business intelligence (BI) systems in the digital transformation of manufacturing companies, in addition to improving overall firm performance.

The research uses the structural equation approach based on PLS-SEM technique with a sample of 120 firms in the manufacturing industry in Coahuila, Mexico.

The paper provides empirical insights into how the interaction of ERP systems and innovation significantly affects the functionality of BI Systems and has a substantial effect on overall firm performance.

Empirical evidence of how advanced digital management systems (ERP and BI) impact digitalization processes in organizations by improving performance is still scarce.

The study investigates the influence of perceived security (PS) on behavioral intention (BI) via the trust attitude process and explores the moderating effects of gender. PS in mobile wallets enhances user trust (TR), attitude (ATT) and intention (INT). Using a multiple and serial mediation model, both TR and ATT were found to mediate the relationship between PS and BI.

Drawing on the stimulus-organism-response (S-O-R) theory, the proposed conceptual model comprises PS, TR, ATT and BI. An online survey was conducted with a cross-sectional sample of 744 mobile wallet users in India. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the hypothesized relationships and test the mediation effects.

Results show that the stimulus, PS, has a positive and significant influence on TR and ATT, which eventually has a positive influence on BI. The research model explains 64.4 percent of the variance in BI. Further, both TR and ATT independently and parallelly mediate the relationship PS and BI. Lastly, gender is found to moderate the relationship between TR and BI and ATT and BI.

The research showed the importance of PS, TR and ATT towards mobile wallet adoption INTs. Further, the findings support the idea that developing TR and ATT is essential for shaping INTs. This suggests that mobile wallet service providers should invest in methods that not just enhance user TR but also reinforce a positive ATT towards the platform. To demonstrate TR, mobile wallet providers must ensure the confidentiality and privacy of user data, keep customer interests in mind and fulfill commitments. Lastly, for strengthening customer TR, excellent customer support is extremely important.

While prior researchers have majorly used technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) models to explain adoption INTs, this study examines the relationship between PS, TR, ATT and BI through the lens of the SOR framework.

This study aims to investigate the influence of corporate social responsibility (CSR) on corporate sustainable performance (CSP) of small- and medium-sized enterprises (SMEs) by looking into the significance of mediating factors, namely, brand image (BI) and brand loyalty (BL), within the context of an emerging economy.

The authors conduct an extensive literature study on the subjects of CSR, BI and BL to assess their influence on the sustainable performance of SMEs in an emerging market. The study adopts a quantitative methodology. A total of 438 answers were obtained from a sample size of 513. The data of the SMEs in Vietnam was analyzed using the smart partial least squares structural equation modeling software, specifically version 3.3.2.

The results of the authors demonstrate notable and favorable correlations between CSR and CSP, CSR and BI and CSR and BL. Importantly, the findings contribute to existing knowledge by looking into the mediating influence of BI and BL in the relationship between CSR and CSP.

According to the authors’ understanding, a number of research have investigated the correlation between CSR and CSP within the realm of SMEs. Nevertheless, there is a scarcity of scholarly research examining the mediating function of BI and BL in this association. The study’s findings have important implications for entrepreneurs and senior management in effectively guiding their enterprises and improving their business strategies with an emphasis on sustainability in emerging markets. The outcome of this study has the potential to significantly contribute to SMEs in Vietnam as well as other emerging countries.

Drawing on the UTAUT-2 model, the study attempts to accentuate the role of augmented reality (AR) and virtual reality (VR) based tourism products and services in enhancing responsible travel behaviour (RTB). This paper aims to examine the emergence of AR- and VR-based tourism in emerging economies, outlines the issues and contributing factors and discusses possible mitigation measures.

Following the triangulation method of research, a dual study involving both focus group discussions and questionnaire-based surveys were undertaken. The grounded theory approach was adopted to develop a structural framework followed by an empirical validation process.

Critical dimensions such as performance anticipation, effort anticipation, referent power, facilitating factors, perceived value and perceived risk were found as antecedents of behavioural intentions (BIs) towards adopting AR- and VR-based tourism products. Moreover, cultural involvement and marketing stimuli emerged as moderating factors driving the BI towards RTB.

This paper outlines key elements that contribute to the adoption of AR- and VR-based tourism products and services in emerging economies, which would enable marketers and practitioners to strategize their tourism offerings.

The study takes a dual perspective of both tourists and tour operators and presents a critical overview of the AR- and VR-based tourism industry, taking an emerging economies’ perspective. The study further attempted both the triangulation method and grounded study approach for establishing a hypothetical framework, which is a unique attempt in itself.

ChatGPT is an advanced artificial intelligence (AI) form that can generate human-like text based on large amounts of data. This paper aims to empirically examine the ChatGPT adoption level among Indian individuals by considering the key factors in determining individuals’ attitudes and intentions toward newly emerged AI tools.

This paper used “partial least square structural equation modeling” (PLS-SEM) to investigate the relation among several latent factors by applying a representative sample of 351 individuals.

This study found that trialability, performance expectancy and personal innovativeness significantly influence individuals' attitudes, while compatibility and effort expectancy do not significantly impact attitudes. Additionally, trialability, performance expectancy, effort expectancy, personal innovativeness and attitude significantly influence behavioral intentions. However, compatibility has an insignificant impact on behavioral intention. Moreover, the research highlights that attitude and behavioral intention directly correlate with actual use. Specifically, the absence of compatibility makes people hesitate to use technology that does not meet their specific needs.

These unique findings provide valuable insights for technology service providers and government entities. They can use this information to shape their policies, deliver timely and relevant updates and enhance their strategies to boost the adoption of ChatGPT.

This paper is one of the pioneering attempts to exhibit the research stream to understand the individual acceptance of ChatGPT in an emerging country. Moreover, it gained significant attention from individuals for delivering a unique experience and promising solutions.

This study aims to establish a comprehensive satisfaction analysis framework by mining online restaurant reviews, which can not only accurately reveal consumer satisfaction but also identify factors leading to dissatisfaction and further quantify improvement opportunity levels.

Adopting deep learning, Cross-Bidirectional Encoder Representations Transformers (BERT) model is developed to measure customer satisfaction. Furthermore, opinion mining technique is used to extract consumers’ opinions and obtain dissatisfaction factors. Furthermore, the opportunity algorithm is introduced to quantify attributes’ improvement opportunity levels. A total of 19,133 online reviews of 31 restaurants in Universal Beijing Resort are crawled to validate the framework.

Results demonstrate the superiority of Cross-BERT model compared to existing models such as sentiment lexicon-based model and Naïve Bayes. More importantly, after effectively unveiling customer dissatisfaction factors (e.g. long queuing time and taste salty), “Dish taste,” “Waiters’ attitude” and “Decoration” are identified as the three secondary attributes with the greatest improvement opportunities.

The proposed framework helps managers, especially in the restaurant industry, accurately understand customer satisfaction and reasons behind dissatisfaction, thereby generating efficient countermeasures. Especially, the improvement opportunity levels also benefit practitioners in efficiently allocating limited business resources.

This work contributes to hospitality and tourism literature by developing a comprehensive customer satisfaction analysis framework in the big data era. Moreover, to the best of the authors’ knowledge, this work is among the first to introduce opportunity algorithm to quantify service improvement benefits. The proposed Cross-BERT model also advances the methodological literature on measuring customer satisfaction.

This present study aims to investigate the mediating effect of halal label perceived importance (HPI) on buying intention (BI) of small and medium enterprises (SME) food products in a Muslim-majority environment by involving attitude (ATT), subjective norms (SN) and perceived behavioral control (PBC) as the antecedents.

A self-administered survey was conducted with 437 Muslim respondents who shop at an SME shopping center. Subsequently, the structural equation modeling technique was used to test the hypotheses.

The findings showed that ATT and PBC significantly influence the BI of halal-labeled food products. On the other hand, HPI partially mediates the relationship between ATT, PBC and BI.

The results provided insights that SME actors will be benefited from selling halal-labeled products as the label amplifies Muslim consumers’ BI. Moreover, the government must intensify the halal campaign to strengthen public awareness and social pressure on purchasing halal-labeled brands.

As SMEs are the major contributor to the national economy, this sector’s business growth will benefit the Indonesian people. Moreover, as the most Muslim-populated country, halal product development will contribute significantly to the whole national economy.

This study provides empirical evidence on the halal labeling mediation role in the relationship between consumer motivation and halal buying intention in a major Muslim setting.

The study aims to draw on the self-congruity theory to investigate the relationship among destination personality (DP), self-congruity and tourists’ pro-environmental behavioral intention (BI) among Guangzhou citizens who have experienced nature-based tourism (NBT).

The survey-based quantitative research was divided into two rounds, namely, a preliminary study exploring the dimensions of DP and the verification of whether the DP dimensions that significantly affect pro-environmental BI in step one would be selected for the main research to validate the conceptual model.

The results suggest that wholesome, one of the destination personalities, strongly predicts tourists’ pro-environmental BI, while actual self-congruity plays a mediating role between sincere, another DP, and tourists’ pro-environmental BI.

In practice, it offers multidimensional knowledge and robust evidence-based recommendations for the sustainable development and destination branding of NBT destinations in the post-epidemic era.

The study presents pioneering work that reveals previously underestimated factors influencing pro-environmental BI.

Business excellence relies heavily upon sustainable innovation. Still, sustainable innovation is an emerging concept in business practices and has yet to reach a common perception among small- and medium-sized enterprises (SMEs). This study aims to address sustainable innovation in SMEs and the factors driving sustainable innovation development.

An exploratory study was conducted to gain insight into the emerging concept of sustainable innovation in the SMEs’ context. Empirical evidence was collected from five case studies. Twenty-five interviews were conducted.

This study findings show that SMEs have different ways of understanding sustainable innovation, resulting in different approaches to integrate sustainable innovation into their business. In SMEs, sustainable innovation may not be a fixed concept due to its ambiguous boundaries and various ways of understanding. External and internal factors are driving SMEs’ sustainable innovation. It depends mainly on organizational culture and the capabilities of SMEs and their members in terms of cooperation and integration in work teams, conditions to achieve consensus, articulation of activities, coherence and commitment to the firms’ objectives. These factors collide and enhance each other and positively impact SMEs’ sustainable innovation.

The scientific relevance of this study lies in the integration of sustainable innovation research in the context of SMEs. There has been limited exploration of how SMEs perceive and engage in sustainable innovation and the factors that drive sustainable innovation development outside of large firms. This study empirically explored the concept of sustainable innovation in the context of SMEs to understand underlying factors related to sustainable innovation.