International Journal of Intelligent Enterprise (11 papers in press)

Regular Issues

• Consumer acceptance of smart speakers - smart enterprise perspective  
  by K.A. Asraar Ahmed, Varadarajan Sowmya Damodharan, A.K. Kranthi 
  Abstract: According to Statista (2025) report, the revenue of the global smart speaker market is expected to be 25 billion USD by 2029. This study examines the Indian users acceptance of smart speakers (SSPA) on the basis of the unified theory of acceptance and use of technology 2 (UTAUT2) theory. A purposive sample of 633 was collected and data was analysed using partial least squares structural equation modelling (PLS-SEM) with Smart PLS 4 software. This research study seeks to identify drivers of behavioural intentions and usage behaviour towards SSPA. This study identified the significant role of perceived interaction, performance expectancy, external social influence, task technology fit, perceived innovativeness, trust, smart speaker self-efficacy, facilitating conditions, hedonic motivation, habit, perceived risk, and social influence towards SSPA among Indian users. This study contributes to the UTAUT2 theory in the context -of SSPA. The proposed model of this study yielded strong explanatory power and medium predictive power.
  Keywords: smart speaker acceptance; SSPA; partial least squares; structural equation modelling; UTAUT2; task technology fit.
  DOI: 10.1504/IJIE.2025.10075006
   
  
• Adoption of digital technology and customer relationships in the Indian banking industry: Exploring the mediating effect of workforce agility  
  by Anuva Choudhury, Ashutosh Muduli 
  Abstract: The global banking industry has undergone a major change as a result of digital transformation Banks have leveraged digital technologies to offer products and services aimed at improving the customer experience and bank performance This research explores the correlation between technology adoption and customer relationships The study, rooted in social exchange theory and the resource-based view, also tries to identify the mediating effect of workforce agility between adoption of digital technology and customer relationships Data was gathered from both senior and junior executives working in banks AMOS-SEM 27 was executed to assess the correlation Hayes PROCESS macro (Version 4 3 1; 2023) was employed to assess the mediation The results are valuable for fintech professionals, leaders, policymaking bodies, marketing teams seeking to enhance digital systems and operations Future studies could investigate other factors related to agile behavior and the effects of digital technology on outcomes like management, sales, and profitability.
  Keywords: workforce agility; adoption of digital technology; ADT; digital transformation; banking industry; customer relationship; banks’ performance; India.
  DOI: 10.1504/IJIE.2025.10075202
   
  
• Data-driven review of business intelligence applications: a text mining approach  
  by Sandeep Singh 
  Abstract: This research extensively delves into business intelligence (BI) and its applications within the current global market. Employing a structural topic modelling approach, the study aimed to uncover latent topics that evolve in BI. A meticulous analysis was conducted on 5,306 articles from the Scopus database from 2020 to 2023. The investigation identified publication patterns, influential journals, authors, and prominent institutions within this field. Nine distinct thematic clusters emerged, covering diverse topics such as urban energy and transport development, decision support system modelling price optimisation in manufacturing and supply chain, socialisation in the online and tourism market, big data mining and processing, big data analytics for business, data analytics in healthcare and pandemics, digital technology development for industry using big data and algorithm-based predictive learning mechanisms.
  Keywords: business intelligence; structural topic modelling; text mining; COVID-19.
  DOI: 10.1504/IJIE.2025.10075357
   
  
• Leveraging technology adoption to enhance SME enterprise performance: mediating effect of behavioural intention and satisfaction with perceived risk as a moderator  
  by E. Rebekah, Mohd Afjal 
  Abstract: This study examines continuance intention in technology adoption among small and medium enterprises (SMEs) in India and its influence on financial performance. Drawing on the extended expectation-confirmation model and UTAUT2, the study investigates key adoption determinants perceived usefulness, performance expectancy, habit, and behavioural intention while considering perceived risk as a moderating factor in mobile banking usage. Primary data were collected from 325 SME owners and managers using convenience and snowball sampling techniques. The data were analysed using partial least squares structural equation modelling (PLS-SEM) with SmartPLS 3.0. The findings reveal that perceived usefulness, performance expectancy, habit, and behavioural intention significantly drive mobile banking adoption among SMEs. Perceived risk also plays a critical role in shaping both behavioural and continuance intentions. Moreover, sustained adoption of mobile banking enhances operational efficiency, improves cash flow management, reduces transaction costs, and supports better financial decision-making, ultimately strengthening SME financial performance. The study offers valuable implications for financial institutions and policymakers aiming to promote digital banking adoption and long-term SME engagement.
  Keywords: technology adoption; m-banking; small and medium enterprises; SMEs; financial performance; extended expectancy-confirmation model; business sustainability.
  DOI: 10.1504/IJIE.2026.10075971
   
  
• Traceability in sustainable food supply chain: foundations, trends and a conceptual framework  
  by Nainsy Gupta, Man Mohan Siddh, Mangey Ram, Gunjan Soni 
  Abstract: This paper presents an analysis of food supply chain traceability literature and its role in attaining sustainable development goals. Literature review and content analyses have been performed to understand the evolution of food supply chain traceability. The Scopus database utilised to make the corpus. Subsequently, the literature on food supply chain traceability is scrutinised to show prominent sources of publications, annual scientific productions, author statistics, author keywords, word tree maps, search trends, top-cited articles, global collaboration maps, and food components traceability in supply chain systems. The proposed framework reveals the four core areas of research, i.e., sustainability, transparency, information systems, and decision support systems. The research consequently contributes to mapping the key merging research areas in food traceability for future work.
  Keywords: food supply chain; traceability; transparency; sustainable development.
  DOI: 10.1504/IJIE.2026.10076845
   
  
• Influences on financial institutions mobilisation of investment capital for road transport infrastructure construction in Vietnam under public-private partnerships  
  by Mai Dinh Lam 
  Abstract: This study adopts a mixed-methods approach, integrating qualitative expert interviews with quantitative analyses, including Cronbachs alpha, exploratory factor analysis (EFA), and structural equation modelling (SEM), to identify and validate the key determinants influencing financial institutions capacity to mobilise private investment capital for road transport infrastructure projects under public-private partnerships (PPPs). SEM results indicate that six groups of factors significantly influence institutional performance: the socio-economic environment; the roles and responsibilities of the state; the organisation and capacity of public agencies; preferential policies and risk allocation mechanisms; private partners capacity; and social participation. Among these factors, preferential policies and risk allocation mechanisms exert the strongest direct impact, while the states role affects project outcomes both directly and indirectly through the organisational capacity of public agencies. In addition, the capacity of private partners enhances institutional effectiveness by fostering greater social participation, underscoring the importance of transparency and stakeholder engagement in PPP projects. Overall, the study provides an empirically grounded analytical framework to strengthen institutional conditions and enhance private capital mobilisation for road transport infrastructure development under PPPs in Vietnam.
  Keywords: financial institutions; road transport infrastructures; public-private partnership; PPP method; Vietnam; exploratory factor analysis; EFA; structural equation modelling; SEM.
  DOI: 10.1504/IJIE.2026.10077101
   
  
• Industry 4.0, HPWS, change resistance and business outcomes: a mediating and moderating study  
  by Tanya Sharma, Ashutosh Muduli 
  Abstract: The increased demand for Industry 4.0 adoptions for higher business outcomes requires understanding the facilitators and barriers for higher effectiveness. Following the technology-organisation-environment framework, the research seeks to examine the mediating role of high-performance work systems (HPWS), and moderating the role of change resistance between Industry 4.0 and business outcomes. The study has been conducted in the manufacturing and service sectors of India. Using validated instruments, AMOS-SEM as well as process macro software was used to conduct path analysis, mediations, and moderation analysis respectively. All the data collected were subjected to reliability and validity tests using Cronbach alpha, average variance extracted and composite reliability. The result found that Industry 4.0 significantly relates to HPWS and business outcomes. Further, HPWS fully mediates between Industry 4.0 and business outcomes. The change resistance does not moderate the relationship amid HPWS and business outcomes.
  Keywords: Industry 4.0; high-performance work systems; HPWS; business outcomes; change resistance; mediation; moderation.
  DOI: 10.1504/IJIE.2026.10077394
   
  
• Technology-driven customer intelligence and organisational strategies for sustainable mutual fund investing among young Indians: a SOM-SEM mixed-methods approach  
  by Meenakshi Sharma, Mobin Anwar, Rakesh Kumar, Vikrant Shokeen, Ajay Kumar Moodadla, P. Srinivasa Rao, Varadarajan Sowmya Damodharan 
  Abstract: This research goal is to investigate the perception of young investors in India, with a primary emphasis on sustainable investing and the use of new fintech tools in increasing mutual fund popularity. Its aim is to explore common challenges posed by market volatility and a general financial literacy. The study proposes a risk mitigation framework that combines self-organising maps (SOM) of data analysis approach with fintech tools to build a smarter and safer investment plan, which importantly improves decision making. The paper finds that fintech tools help youth reduce risks and illiteracy. The study used SOM-based portfolio optimisation enhances effective decision making and reducing losses for young investors. The result contributes the mixed methodology approach with stratified sampling of young Indian investors. It provides questionnaires validated through statistical testing. This study uses various statistical methods (ANOVA, regression), and advanced methods (SOM, SEM) to understand how young investors view mutual funds and financial technology-tools.
  Keywords: sustainable investing; mutual funds; young investors; fintech adoption; risk mitigation; customer intelligence; self-organising maps; SOM; structural equation modelling; SEM; organisational strategy.
  DOI: 10.1504/IJIE.2026.10078200
   
  
• Evaluation of chatbot integration for the purpose of raising participation in distance education  
  by Firas Tayseer Mohammad Ayasrah 
  Abstract: This study examines how distance education chatbots affect student engagement. We used a descriptive survey design to survey 300 undergraduate and postgraduate students, faculty, and administrators from chosen universities. A structured questionnaire covered demographics, chatbot perceptions, SCEQ-adapted engagement metrics, and chatbot efficacy. The instruments Cronbachs alpha was 0.87 after expert validation. SPSS was used to examine quantitative data using descriptive statistics, t-tests, and ANOVA to find significant differences. Correlation investigation assessed chatbot integration and student engagement. Findings revealed high student awareness and positive perceptions of chatbots (M = 3.81). Chatbot integration positively influenced student engagement (M = 3.76), particularly in performance-related (M = 3.95) and skills engagement (M = 3.85). Students reported high benefits in academic support, timely feedback, and personalised learning (M = 4.03), especially regarding 24/7 accessibility (M = 4.20) and real-time support (M = 4.15). Hypothesis testing indicated significant positive relationships between chatbot awareness and engagement (r = 0.54, p < 0.001), chatbot integration and participation/motivation (r = 0.61, p < 0.001), and chatbot use and improved academic support services (r = 0.67, p < 0.001). The study shows that chatbots improve distance education student engagement and academic support, providing educators and technology developers with useful insights.
  Keywords: measuring the effectiveness; chatbot integration; increasing student engagement in remote learning; Jordan; student course engagement questionnaire; SCEQ.
  DOI: 10.1504/IJIE.2026.10078693
   
  
• Empowering IoT with edge AI: efficient edge computing using ONNX and quantisation  
  by Abhishek Sharma, Dilip Kumar Sharma 
  Abstract: The rapid growth of internet of things (IoT) devices has intensified the demand for processing data in real time at the network edge. Traditional cloud-centric models face challenges such as latency, bandwidth limitations, and privacy concerns, making edge-computing a vital component of modern IoT networks. However, deploying complex machine learning models on resource-constrained edge devices presents substantial hurdles due to limited memory, computational power, and energy resources. This paper explores quantisation strategies as a means to empower IoT devices by reducing model size and computational complexity without substantially sacrificing accuracy. We propose a novel quantisation framework tailored for edge computing environments, incorporating both uniform and non-uniform quantisation techniques to optimise neural network models for IoT devices. Our results highlight how quantisation reconciles state-of-the-art machine learning with edge device constraints, reducing cloud dependency, latency, and improving data privacy.
  Keywords: cloud computing; edge computing; internet of things; IoT; quantisation; security; edge AI.
  DOI: 10.1504/IJIE.2026.10079847
   
  
• Transfer learning approach for plant disease classification for small datasets  
  by C. Preethi, N.C. Brintha 
  Abstract: The size of the dataset affects the performance of machine learning models. When the dataset is small, techniques like data augmentation and transfer learning can be applied. This work focuses on a transfer learning approach for plant disease classification. In the first phase, six machine learning models, namely logistic regression, K-nearest neighbour, decision tree classifier, random forest classifier, Naive Bayes, and support vector machine, are evaluated for classifying healthy and diseased leaves. Among them, the random forest classifier performs best. When tested with a small pepper bell leaf dataset, the validation accuracy is 73%. To improve performance, the random forest classifier trained with tomato leaves is used for validating pepper leaves, achieving 83% accuracy. Further, a convolutional neural network combined with transfer learning and random forest classification improves the accuracy to 87%. The results demonstrate the effectiveness of transfer learning for small datasets.
  Keywords: machine learning; deep learning; transfer learning; plant disease classification.
  DOI: 10.1504/IJIE.2026.10080125