Balancing today and tomorrow: the role of analytics, automation, and digital readiness in digital transformation for accounting functions

This study aims to examine the relationship between digital readiness, perceived usefulness of Generative Artificial Intelligence (GenAI), and academic resilience among university students in the digital learning era. The research involved 45 undergraduate students from Universitas Negeri Surabaya as respondents, selected to represent learners who actively engage in technology-supported academic activities. Using a quantitative approach, data were collected through a structured questionnaire measuring digital readiness, perceived usefulness of GenAI, and academic resilience, adapted from validated instruments in previous studies. The data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) to evaluate both the measurement and structural models. The results show that digital readiness has a significant positive effect on academic resilience, indicating that students with higher digital preparedness tend to possess better adaptability and persistence when facing academic challenges. Digital readiness also significantly influences perceived usefulness of GenAI, suggesting that students who are more digitally prepared are more likely to view GenAI as beneficial for learning. However, perceived usefulness of GenAI does not significantly affect academic resilience and does not mediate the relationship between digital readiness and academic resilience. These findings underscore that digital readiness serves as a direct and dominant predictor of academic resilience, while the perceived usefulness of GenAI has not yet functioned as a psychological mechanism that strengthens students’ adaptive capacity. The study highlights the importance of improving students’ digital competencies to foster resilience in technology-driven learning environments.

The rapid acceleration of digital transformation has changed the business landscape worldwide, but micro, small, and medium enterprises (MSMEs) in developing regions continue to face structural gaps in digital readiness and inclusion. In Medan, Indonesia, where MSMEs are the backbone of the economy, limited digital adoption and uneven readiness hinder their ability to maintain competitiveness and contribute to inclusive economic growth. This phenomenon highlights the importance of analysing how digital transformation variables interact with innovation processes and collaborative ecosystems to generate sustainable economic outcomes. The objective of this study is to investigate the indirect effects of digital readiness, digital inclusion, and digital transformation on sustainable local economic development through the dual mediation of innovation business models and ecosystem business models. Using an explanatory quantitative design, data were collected from 200 SMEs in Medan that had been involved in digitalisation for at least two years. Structural Equation Modelling–Partial Least Squares (SEM-PLS) was applied to test the proposed Digital Ecosystem Innovation Model (DEIM). The results show that digital readiness, inclusion, and transformation do not have a direct effect on sustainable economic growth. Instead, their impact becomes significant when mediated by innovation and ecosystem business models. Digital readiness strongly drives innovation, while digital inclusion enhances both innovation and ecosystem collaboration. Furthermore, the ecosystem business model emerges as the strongest predictor of sustainable local economies, highlighting the importance of coordinated value creation among stakeholders. This study concludes that digital transformation should not be viewed as an end goal, but rather as a systemic process requiring business model adaptation and the development of collaborative ecosystems. This research contributes theoretically by expanding the Technology–Organisational Environment (TOE) framework through the DEIM model, integrating readiness, inclusion, and innovation into a holistic approach. Practically, this research provides policy insights to improve the resilience of MSMEs through digital literacy, innovation capacity, and cross-sector collaboration.

Background: The culinary sector within SMEs in Bogor District has experienced rapid digital transformation. Key advancements include the adoption of digital payments, enhanced operational efficiency, and increased use of social media for marketing, supported by training initiatives aimed at improving service quality.Purpose: This study aims to analyze the factors that influence technology adoption among culinary SMEs in Bogor District and assess the impact of digital transformation on their performance.Design/methodology/approach: Utilizing the Technology-Organization-Environment (TOE) framework, this study evaluates factors affecting digitalization in culinary SMEs. Data were collected from 125 culinary SME respondents in Bogor District through online and in-person surveys, with purposive sampling. Analysis was conducted using Structural Equation Modeling - Partial Least Squares (SEM-PLS).Findings/Results: Out of four tested hypotheses, two yielded significant results. Organizational factors were positively associated with digitalization, while technological factors were not. Although environmental factors were not significant, digitalization demonstrated a positive impact on SME performance. Critical factors in the digital transformation process include the use of digital promotional media and digital payment systems, with sales growth and profitability emerging as indicators of SME success.Conclusion: Organizational factors, along with digital tools such as promotional media and payment systems, play a pivotal role in the successful digital transformation of culinary SMEs. Despite the non-significance of certain factors, digitalization remains a key driver of performance improvement.Originality/value: This study contributes to the understanding of digital transformation in the culinary SME sector, highlighting the role of organizational support and digital strategies in fostering growth and competitive advantage in the digital economy. Keywords: Culinary SMEs, Digital Transformation, Environment, Organization, Technology

Background: Innovation in Small and Medium Enterprises (SMEs) in Indonesia is essential for business development, requiring SMEs to foster innovative work behavior. However, some Indonesian SMEs still struggle to implement innovative work behavior, especially in utilizing digital technology for innovation in this digital era.Purpose: This study aims to explore the role of digital readiness in mediating organizational culture’s impact on the innovative work behavior of SME employees in Indonesia. Design/methodology/approach: The research employed a quantitative approach using Structural Equation Modeling - Partial Least Squares (SEM-PLS) analysis. The survey was distributed to SME employees in Indonesia. This research used 185 respondents for further data analyzing.Findings/results: The results reveal that digital readiness only mediates the relationship between market culture and innovative work behavior. On the other hand, digital readiness does not mediate adhocracy and clan culture to innovative work behavior. Conclusion: Results interestingly suggest that digital readiness significantly mediates market culture to innovative work behavior. Adhocracy and clan cultures may directly instill innovative work behavior, as confirmed by previous studies.Originality/value (State of the art): This is the first study to investigate how types of culture are associated with innovative work behavior mediated by digital readiness. Keywords: Innovation, innovative work behavior, organizational culture, digital readiness, SME

Purpose Tourism destinations increasingly pursue digital transformation, yet most initiatives remain efficiency-focused. Existing research provides a limited empirical explanation of how digital capability, environmental literacy and ethical artificial intelligence (AI) jointly enable regeneration beyond sustainability. To address this gap, this study aims to develop and test a smart regenerative tourism transformation model explaining how digital readiness, organizational capability and ethical governance support net-positive destination renewal. Design/methodology/approach Survey data were collected from 543 tourism managers in Malaysia, Singapore and Thailand. Partial least squares structural equation modeling (PLS-SEM) was used to test eight hypothesized relationships linking smart tourism infrastructure, digital accessibility and inclusion, eco-literacy and net-zero commitment and regenerative destination governance to tourism digital transformation capability (TDTC), regenerative tourism innovation and regenerative destination transformation, with AI and data-ethics climate as a moderator. Findings The results indicate that smart infrastructure, inclusivity and governance strengthen TDTC, which, in turn, supports regenerative tourism innovation and regenerative destination transformation. A strong AI and data-ethics climate amplifies these relationships. These findings are based on managerial perceptions and suggest, rather than confirm, destination-level regenerative progress. Research limitations/implications This study’s cross-sectional design limits causal inference, as relationships remain correlational despite procedural and statistical checks. Future research should adopt longitudinal, experimental or panel data approaches to track TDTC over time. Additionally, incorporating objective indicators, such as AI ethics audits and digital investment records, can enhance validity. Expanding the sample to include diverse cultural contexts and adopting multi-stakeholder approaches will provide richer insights. Finally, dynamic-system modeling can better capture feedback loops between digitalization, governance and regeneration, advancing the understanding of regenerative tourism in evolving destinations. Practical implications This study provides evidence for advancing regenerative digital transformation in Southeast Asian tourism. It confirms that smart tourism infrastructure, digital accessibility, eco-literacy and regenerative governance collectively enhance digital transformation outcomes. AI and data ethics climate play a crucial moderating role, ensuring ethical digital progress. Tourism boards must invest in inclusive digital ecosystems, ensuring that technology empowers local communities and businesses. Governments should integrate eco-literacy and sustainability into programs, while transparent AI frameworks should be adopted to ensure fairness. The findings support the creation of an Association of Southeast Asian Nations (ASEAN) regenerative tourism data network to align digital standards and promote sustainable, inclusive tourism. Social implications This study highlights the role of digital transformation in fostering social inclusion and community well-being. By ensuring that technology enhances accessibility and empowers local communities, destinations can reduce socioeconomic inequalities and promote equitable growth. Regenerative governance frameworks and AI ethics are crucial for building trust and accountability in digital tourism, ensuring that innovations benefit all stakeholders. The integration of eco-literacy and sustainability practices further supports societal regeneration, encouraging active participation in conservation efforts and sustainable tourism practices. The proposed ASEAN regenerative tourism data network offers a model for fostering inclusive, responsible digital engagement across tourism destinations. Originality/value This study offers a tri-country empirical examination of how ethical AI conditions the transformation of digital capability into regenerative value creation. It advances tourism theory by positioning digital transformation as a morally governed organizational capability that supports socio-ecological renewal rather than efficiency or harm reduction alone.

This study aims to examine the influence of digital readiness on innovation behavior in manufacturing companies in West Java, considering the role of technology adoption as a mediating variable and organizational agility as a moderating variable. Using a quantitative approach and the Partial Least Squares Structural Equation Modeling (PLS-SEM) method, the findings reveal that digital readiness positively influences innovation behavior directly and is also associated with higher levels of technology adoption within organizations. However, technology adoption is not found to significantly mediate the relationship between digital readiness and innovation behavior. On the other hand, organizational agility strengthens this relationship, indicating that organizations responsive to change are better equipped to translate digital readiness into innovative actions. Theoretically, these findings extend the literature on digital transformation and innovation management by demonstrating that the integration of digital readiness with organizational agility provides a stronger explanatory framework for how firms achieve innovation outcomes in dynamic environments. These findings imply that in fostering a sustainable culture of innovation, companies should not only focus on enhancing digital readiness and technology adoption capabilities but also prioritize strengthening organizational agility to effectively respond to dynamic changes.

This study aims to analyze the influence of intrinsic motivation on students’ digital readiness in the post-pandemic era using the framework of Self-Determination Theory (SDT). The research employed a quantitative approach with a descriptive-verificative survey method. The respondents consisted of 230 undergraduate students from various public and private universities in Indonesia who had participated in online and hybrid learning. Data were collected through an online questionnaire and analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0 software. The results indicate that intrinsic motivation has a significant effect on students’ digital readiness (R² = 0.62). All three SDT dimensions—competence, autonomy, and relatedness—positively influence digital readiness, with competence showing the strongest effect (β = 0.39), followed by autonomy (β = 0.27) and relatedness (β = 0.21). These findings emphasize that students’ digital readiness is shaped not only by technical skills but also by psychological factors related to intrinsic motivation.

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).

Digital transformation is a strategic element in increasing the competitiveness of Micro and Small Enterprises (MSEs), especially through the adoption of digital payment systems such as QRIS. However, the low level of digital readiness and financial literacy is still the main obstacle in the use of financial technology in Indonesia. This study aims to analyze the influence of financial literacy and the use of QRIS on the performance of MSEs in Denpasar, as well as test the role of digital readiness as a moderation variable. The research method uses a quantitative approach with a survey of 95 MSE actors who use QRIS. Data analysis was carried out using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results of the study show that financial literacy has a positive and significant effect on the performance of MSEs, while the use of QRIS and digital readiness has a positive but not significant effect. Digital readiness negatively moderates the relationship between financial literacy and MSE performance, as well as moderates positively but not significantly the relationship between QRIS utilization and MSE performance. These results confirm that digital readiness that is not balanced with good financial literacy can weaken the positive influence on business performance.

Despite the significant benefits of e-commerce for Small and Medium-Sized Enterprises (SMEs), adoption rates remain relatively low among engineering SMEs in Nigeria. This study aims to examine the determinants of e-commerce adoption mong engineering SMEs in Nigeria and its implications for digital transformation. rounded in the Technology-Organization-Environment (TOE) framework, the study nvestigates technological, organizational, and environmental factors that facilitate or inder adoption. A stratified random sampling technique was employed to select a epresentative sample of 600 respondents from diverse engineering sectors and egions in Nigeria. Data were collected using a structured online questionnaire and nalyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). he results indicate that technological factors, such as ICT infrastructure, internet onnectivity, logistics and supply chain efficiency, along with environmental factors ike economic conditions and socio-cultural influences, significantly facilitate e-ommerce adoption. Conversely, technological barriers, including cybersecurity hallenges and inadequate electronic payment systems, and environmental barriers uch as regulatory constraints, market dynamics, and technological advancements, inder progress. Notably, all organizational factors such as organizational readiness, op management support, innovation culture, and employee training were found to ave no significant influence. The study concludes that technological and nvironmental factors serve as key enablers of e-commerce adoption among ngineering enterprises in Nigeria, whereas organizational factors act as barriers. his study offers theoretical contributions to the TOE framework by highlighting ector-specific and regional nuances in e-commerce adoption. Additionally, it rovides managerial and policy implications to address technological, organizational, nd environmental barriers, enabling engineering SMEs in Nigeria to thrive in the igital economy.

The digital transformation of Chinese construction enterprises is crucial for achieving sustainable and high-quality development in the construction industry. However, there is still a lack of in-depth research on the impact mechanism of digital transformation in construction enterprises. The purpose of this study is to explore the multiple influencing factors and complex causal relationships of digital transformation in construction enterprises and promote the deep integration of digitalization and construction enterprises. To this end, based on the dual-effect perspective (net effect perspective of a single influencing factor and configuration effect perspective of multiple influencing factors), using the “technology–organization–environment” framework (TOE framework) to construct a research model of influencing factors for digital transformation in construction enterprises. A sample of 236 construction enterprise managers was surveyed, and partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) methods were used to empirically analyze the dual effects of influencing factors for digital transformation in construction enterprises. The results show that: (1) from the net effect perspective, there are seven factors that significantly impact digital transformation in construction enterprises; (2) from the configuration effect perspective, there are three paths that can achieve high-level digital transformation in construction enterprises, and one path that leads to low-level digital transformation; (3) from the dual-effect perspective, top management support and policy support are key factors for digital transformation in Chinese construction enterprises. The research results enrich the relevant research on digital transformation in construction enterprises and provide a reference basis for promoting digital transformation in construction enterprises.

In an era defined by rapid digital transformation, project-based organizations face increasing pressure to modernize and digitalize their operational frameworks to ensure competitive advantage and Project Management Success. However, only limited research has examined how foundational pillars of digital infrastructure interact and jointly influence project outcomes, leaving a gap in understanding the structural pathways that link digital infrastructure to Project Management Success and informed decision-making. This study investigates how the three pillars of digital infrastructure (Digital Readiness, Digital Fitness, and Digital Tools) jointly and individually influence Project Management Success through applying Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data collected from experienced project management professionals who possess appreciable experience in digital technology systems and digital transformation leadership. The developed model captures both direct effects of the Digital Infrastructure Pillars on Project Management Success and the moderation effects between them. The results show that all three pillars significantly enhance Project Management Success, with Digital Readiness emerging as the most influential strategic enabler. Moreover, Digital Readiness positively moderates the effect of Digital Tools on Project Management Success, indicating that digital technology investments are more effective when supported by foundational digital preparedness. These findings offer a validated framework for assessing digital maturity in project environments and provide strategic and leadership guidance for organizations seeking to enhance project performance and achieve Project Management Success through balanced investment in digital infrastructure, integrated digital transformation strategies, digital technology adoption, and digital competencies.

This investigation explores the structural linkages between agile frameworks, digital readiness, and the achievement of sustained competitive advantage among Thai SME-sized spirits producers. As traditional industries adapt to the digital era, the ability to respond quickly to change and integrate digital tools has become essential for sustained competitiveness. The investigation centers on three primary internal determinants: digital literacy, digital transformation, and organizational agility. Utilizing a structured survey, empirical data were gathered from 190 SME distilleries across Thailand and subsequently analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings reveal that organizational agility serves as the most potent direct driver of competitive advantage, with digital transformation also yielding a positive impact. While digital literacy is a crucial precursor to digital transformation, its influence on competitive advantage—both direct and indirect—did not reach statistical significance. These conclusions imply that digital competencies are inadequate on their own; they must be leveraged via agile frameworks to bolster strategic responsiveness. This study extends existing research on SME competitiveness by highlighting the importance of combining digital readiness and organizational agility for achieving success, particularly in highly regulated industries such as alcohol production. It also provides practical insights for SME leaders and policymakers.

The use of partial least squares structural equation modelling (PLS-SEM) in management accounting research: Directions for future theory development

Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)In view of its essential role in knowledge creation, multivariate data analysis prevails in the social sciences literature. The field of tourism is not an exception, specifically in the widely adoption of structural equation modeling (SEM), a multivariate technique, by tourism researchers over the past decade. While there are two major types of SEM including covariance-based SEM (CB-SEM) and variance-based SEM (PLS-SEM), the former dominated previous tourism research. However, increasing use of PLS-SEM in tourism research has been witnessed in recent years. This upward trend is likely to persist in the near future given the growing popularity of PLS-SEM in other social sciences domains like marketing, strategic management, and management information system, as specified in the preface of the book. Indeed, PLS-SEM, in relative to CB- SEM, provides more flexibility in handling of data. For instance, PLS-SEM is well-suited for accommodating small sample sizes and complex model, fortesting a model containing both formative and reflective constructs, and for handling single-item measures. To this end, the timely introduction of the book A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) helps tourism researchers stand at the front edge of the SEM technique and make effective use of the PLS-SEM in data analysis. Additionally, the book illustrates the application of PLS-SEM with a free downloadable software namely SmartPLS which is essential to extend the application of PLS-SEM in tourism research.Authored by Hair, Hult, Ringo, and Sarstedt, the book consists of eight chapters. To equip the readers with the basic knowledge of PLS- SEM, Chapter 1 delineates the meaning of SEM and its relationship with multivariate data analysis, followed by a description of the major elements in multivariate data analysis. Then the basic elements of PLS-SEM are explained. Finally, PLS-SEM is distinguished from its counterpart namely CB-SEM while the major characteristics of PLS-SEM and the conditions where the PLS-SEM are more adequate than CB-SEM and vice versa are discussed. To step in the application of PLS- SEM, Chapter 2 firstly explicates the concepts in structural model specification including mediation, moderation, and higher-order models. Then specification of measurement model is explained with a special focus on the differences between reflective and formative measures. After that, the issues that need to be addressed after data collection are discussed. The chapter ends by creating the model in the SmartPLS is illustrated. With an established model, Chapter 3 focuses on model estimation. The chapter explains the algorithm underpinning the estimation and the statistical properties of the PLS-SEM method, as well as the options and parameter settings for running the algorithm. Following that, the issues about interpretation of results are explained. The final section illustrates the execution of model estimation in the SmartPLS.Based on the model estimation, empirical measures of the measurement and structural models are derived, where evaluation of the models takes place. Chapter 4 exhibits the major steps in model evaluation in the beginning. Thereafter, the chapter explains the evaluation of reflective measurement models according to three major criteria including internal consistency reliability, convergent validity, and discriminant validity, followed by an illustration with the SmartPLS. Chapter 5 explains the assessment of formative measurement models with respect to the criteria of convergent validity, collinearity, and significance and relevance of the formative indicators. The chapter also elucidates the basic concepts of bootstrapping which is used to examine the statistical significance of estimates in PLS- SEM. An illustration of the assessment of formative measurement model in the SmartPLS follows. Chapter 6 continues the topic on model evaluation by focusing on the assessment of structural model. …