International Journal of Intelligent Enterprise (15 papers in press)

Regular Issues

• Leveraging data-driven decision-making for medicine supply chain resilience during health crisis  
  by Rahul Sharma, Surya Prakash, Sudhir Arora, Ashok Kumar Peepliwal, Sudhinder Singh Chowhan 
  Abstract: The study was conducted to identify medicine and its therapeutic segments which had suffered sourcing and stockout challenges at the grass-root level during the pandemic time. An exploratory and descriptive study was conducted using primary data from sampled private retail pharmacy business stores. Factors like the name of the medicine, their therapeutic segment, geographical location, and the timeline of the events, were captured to analyse drug shortage along. The study indicated an acute shortage of medicine including antibiotics, antiviral, and supplements during the pandemic, due to disruption in the medicine supply. There was a high correlation between the incidence of infection cases and the drug shortage, which suggests the rise in demand for essential medicine especially antibiotics and supplements following the rise in the cases. The study provides a recommendation to pharmaceutical organisations, suppliers, and policymakers, to effectively handle sourcing and supplies to counter stockout situations.
  Keywords: stockout; pharmaceutical supply chain; drug retail; inventory control.
  
  
• Navigating the shift in brand loyalty: the impact of social media influencers  
  by M. Sivakoti Reddy, Sangeeta Malhotra, Laxmi Srinivas Samayamantri, Sangeeta Singhal, Sanjeev Kumar Saxena, Niharika Singh 
  Abstract: This study delves into the dynamic landscape of brand loyalty in the age of social media, focusing on the evolving influence of social media personalities. In the digital era, where social media has become integral to our lives, consumers increasingly rely on influencers for product recommendations and brand associations. We thoroughly analysed quantitative and qualitative research methods to gain a comprehensive understanding. The total sample size for the survey was 1,248 respondents, selected based on demographic distribution. Data analysis was performed using Microsoft Excel and MATLAB tools, ensuring precise and accurate insights. Our study shows that authenticity, trust, and engagement are key in the brand-consumer connection with social media celebrities. Consumer behaviour, marketing effectiveness, and customer satisfaction depend on these characteristics. Marketers and organisations can use the study’s findings to utilise social media personalities in this changing marketplace. Understanding the primary determinants of brand loyalty in the digital era helps organisations adjust to changing consumer engagement and brand trust paradigms and succeed in a social media-driven market.
  Keywords: brand loyalty; social media personalities; consumer behaviour; social media-driven market; marketers and organisations; customer satisfaction; brand associations.
  
  
• Scientific competence and acquisition challenges in education managed by analytics  
  by K.K. Ramachandran, Budhi Sagar Mishra, Himani Oberai, Gazala Masood, Ila Mehrotra Anand, Nidhi Shukla 
  Abstract: Integration of instructional, informational, and communication technology underpins modern higher education. After decades without computer networks, these technologies have transformed learning. E-learning has transformed the education sector, solving its problems. The similarities between technology and cognition make this change noteworthy. Artificial intelligence-inspired model-based reinforcement learning lets agents predict states and outcomes across activities and settings to modify their behaviour. The human brain has similar mechanisms, especially in model selection, which is a fascinating mystery. This study examined the brain’s model selection process and found that sensory prediction errors motivate the brain to choose between computational models. The theory was contrasted with internal modelling and incentive predictive performance to show how prediction errors influence computational model selection. The brain can choose an internal validation learning model based on incentive prediction mistakes, as empirical evidence demonstrates that the policy gradient method matches these models. These models were intended to address higher education issues like administration, academic delivery, instructional design, and ethics. The report also suggested that e-learning could help solve industry issues like student concentration on campuses, brain drain, and resource shortages. This research shows how technology can change higher education and the future of learning.
  Keywords: education learning; infrastructure administration; academic delivery; instructional design; e-learning model; human resource; education management; education policy.
  
  
• Digital era: the effect of electronic word of mouth, online communities, and online advertising on brand image and loyalty  
  by M. Deepa, Moli Ghosh, R. Jeya Rani, D. Joel Jebadurai, Bandit Aroman 
  Abstract: The Indian virtual world is growing rapidly, offering advertisers and internet users many options. Online advertising can boost brand awareness, buying intent, and risk reduction. Digital communications help businesses succeed and retain customers. This communication may be word-of-mouth via digital platforms, advertisements, and virtual communities. This research examines digital marketing opportunity elements affecting e-commerce brand image and loyalty. EWOM, online advertising, and online communities let senders disseminate information via social media, email, or SMS with specified populations. The digital influential model’s impact is framed by observational learning theory. The descriptive research design and quantitative survey method were used to investigate Chennai internet users’ brand-related electronic device purchases. 234 respondents were surveyed online. The study compares EWOM, online advertising, online communities, brand image, and brand loyalty. It shows that EWOM positively impacts brand image and loyalty. This study shows that online communities improve brand image and online advertising quality improves customer decision-making. Brand characterisation depends on social media. The study found that letting customers participate in non-commercial activities, exchange experiences, and establish relationships would boost brand image and loyalty.
  Keywords: online advertising; OA; online communities; OC; electronic word of mouth; EWOM; brand image; BI; brand loyalty; BL; customer decision-making power; non-commercial promotions.
  
  
• An empirical study on foreign institutional investors in Indian capital market  
  by J. Sai Sudha, V.S. Prasad Kandi, K. Ravi Kiran Yasaswi 
  Abstract: The stock market plays a significant role in national economic growth by stimulating industry and overall development. Developed countries stock markets tend to be more efficient than emerging markets. As one of the worlds emerging economies, India is improving its stock market standards to attract foreign investment. This foreign investment helps supplement funds for domestic companies, contributing to the countrys economic growth. Emerging stock markets have become attractive to foreign investors due to their high growth potential and corporate earnings, which often exceed those of developed markets. These markets are more volatile than developed ones. This study examines how FIIs affect sector-wise market returns. It also analyses FII shareholdings and their impact on BSE Sensex company market capitalisation. The study examines how FIIs/FPIs affect sector-wise market returns and the market capitalisation of selected BSE Sensex companies through their shareholding patterns. Net FII inflows, chosen indexes return, FII investments in companies, and BSE Sensex company market capitalisation are studied. They used linear regression from April 2010 to March 2021.
  Keywords: foreign institutional investors; FIIs; Sensex and market capitalisation; domestic companies; emerging economies; Indian capital market; capital goods and technology; banking and finance sectors.
  
  

Special Issue on: Digital Technologies for Enterprise Transformation

• Modelling fluctuating market size based adoption of technological products: an alternative formulation  
  by Jyotish N. P. Singh, Adarsh Anand, Deepti Aggrawal, Chanchal 
  Abstract: Customers in the ever-changing digital advanced marketplace often demonstrate unpredictable behaviours that can significantly impact the potential market size. Some satisfied customers may exhibit loyalty and choose to repurchase the product, while others may be driven by indecision and impatience, resulting in lost sales. These contrasting actions of repeat purchasing and balking behaviour can result in fluctuating market size, underscoring the importance of considering such scenarios when studying technological adoption models. The authors have proposed an alternative formulation of the innovative technological product adoption model to address these ever-changing market dynamics. Notably, this formulation simultaneously accounts for customers balking and repurchasing behaviour. By incorporating these factors, managers can gain insights into predicting market performance amidst fluctuations and navigate market volatility more effectively. The proposed alternative formulation is validated using real-life datasets and the obtained results support its practical application in predicting market outcomes. These findings lend credibility to the application of the alternative formulation, empowering managers with the means to anticipate and adapt to market fluctuations with greater precision.
  Keywords: balking behaviour; market dynamics; technological adoption; repeat purchase.
  
  
• An interdisciplinary examination of the evolution of e-commerce recommendation systems: perspectives from management, social science, and psychology  
  by Aman Mathan, Deepak Verma, Divesh Kumar 
  Abstract: The rapid incorporation of digital technologies in businesses poses significant challenges for businesses entrenched in traditional approaches. Conventionally, e-commerce gained popularity for its extensive customer reach, which is no longer sufficient in the current digital era. Nowadays, most e-commerce platforms utilise recommendation systems (RS) supported by complex algorithms and models that influence customers’ online product searching and purchase experiences. RS is predominantly associated with information systems (IS) and computer science (CS) research, despite it being a multi-disciplinary field. The majority of the research on RS is concentrated in IS and CS, with a primary focus on methodology and algorithms. This study examines the existing literature on RS in the domains of management, social sciences, and psychology to identify developments that extend beyond methodology and algorithms. The aim is to broaden the scope of the research domain.
  Keywords: recommendation systems; recommender agents; e-commerce; product recommendation systems; thematic evolution; literature review; bibliometrics.
  
  
• Data-driven approach for analyzing the impact of external factors on pearl millet and stover yield  
  by Nikita Dhankar, Srikanta Routroy, Satyendra Kr. Sharma 
  Abstract: The objective of the study is to explore the relationship between external factors such as linkage with self-help groups (SHGs), crop diseases, ground water quality, soil testing, rainfall, and temperature during cultivation impact with pearl millet yield and Stover yield. The responses from 473 farmers are collected through structured survey questionnaire. The outcomes reveal that the relationship of all external factors is statistically significant for both yields except the temperature during cultivation. The analysis of variance (ANOVA) and Pearson coefficient of correlation indicates a statistically significant positive correlation between pearl millet yield and Stover yield. The current study is first of its kind related to impact of external factors on pearl millet yield and Stover yield. The outcomes of the study will help policymakers in developing strategies for enhancing pearl millet and Stover yield which in turn will increase farmer income. In addition to having access to an incentive scheme for free testing of their ground water quality and soil health, the farmers have to be linked to self-help groups (SHGs).
  Keywords: pearl millet supply chain; analysis of variance; ANOVA; pearl millet yield; Stover yield; self-help group linkage; soil testing; Pearson coefficient of correlation.
  
  
• Artificial intelligence and vaccine supply chain: analysis of the adoption challenges in the Indian context  
  by Ambuj Kumar, Om Ji Shukla, Shailesh Mani Pandey 
  Abstract: Integrating artificial intelligence (AI) with the vaccine supply chain (VSC) can generate a robust VSC model, making it easier to supply chain live-saving vaccines and drugs. This study aims to explore challenges in integrating VSC and AI through an extensive literature survey and then validation by a team of experts through the Delphi method. The study takes into account the opinions of important groups, such as government agencies, hospitals, drug companies, and tech companies. The challenges are modelled by a multi-criteria decision-making method integrated with a fuzzy method named as fuzzy decision-making trial and evaluation laboratory (FDEMATEL) technique. The results indicate that long-term sustainability, adoption and skill gap and cost and resource constraints are the most prominent challenges that must be addressed for the successful integration of AI in VSC. The information learned from this study can help the supply chain for vaccines in India.
  Keywords: artificial intelligence; AI; vaccine supply chain; VSC; DEMATEL; robust model.
  
  
• Use of machine learning for classifying manufacturing companies based on their digital transformation levels  
  by Ece Acar, Gorkem Sariyer 
  Abstract: The transformative role of machine learning technology in promoting technological innovation leading sustainable growth is becoming increasingly significant in todays business era. In this study, we implemented machine learning technology to classify the companies according to their digital transformation levels. We used manufacturing companies in Borsa Istanbul (BIST) index as the sample. We constructed a digital transformation level index based on text analysis to measure the frequency of keywords related to digital transformation. We used the sampled companies financial, sustainability, corporate governance performance and research & development (R&D) expenditures to model their digitalisation levels. We observed that between the various machine learning algorithms, with 82% accuracy, Random Forest outperformed the others. We also showed that while R&D expenditure was the most important feature, financial performance-related features were also significant. Thus, we concluded that companies with higher financial performances, especially those making more expenditures for R&D activities, have higher digital transformation levels.
  Keywords: digital transformation; financial performance; R&D expenditure; machine learning; classification.
  
  
• Predicting emotional intelligence, creative performance and knowledge management in higher education using multiple regression  
  by Amar Kumar Mishra, Megha Ojha, Saumya Sharma, Smita Jain, Mayank Kumar, Archana Singh 
  Abstract: Higher education institutions are paramount in emerging nations like India. Post-globalisation, India witnessed the growth of HEIs, especially in the private sector. However, today most of the institutions are struggling for their existence. One of the most vital reasons for such a staggering performance is the absence of creativity. It will not be an exaggeration to say that the present era is the era of creativity and performance and organisations that cant perform are bound to perish. Creativity can be nurtured and yield success only if it is supported by the emotional intelligence (EI) of the employees and knowledge management (KM) processes. The current paper explored the nexus between emotional intelligence, knowledge management processes and creative performance in HEIs in India and implied that though emotional intelligence affects creative performance, the impact gets manifolded in the presence of the knowledge management process.
  Keywords: emotional intelligence; creative performance; knowledge management process; higher educational institutions.
  
  
• Interpretive structural modelling approach for barrier analysis in agent technology enabled smart manufacturing system  
  by Om Ji Shukla, Devesh Kumar, Bharti Ramtiyal, Abhijeet Joshi 
  Abstract: Over the past some years global challenge, flexibility, robustness, re-configurability and customised production have become the most desired needs of the modern manufacturing system. Thus, the utilisation of agent technology (AT) can have a crucial role in developing manufacturing systems that are exceptionally adaptable. The present study analyses the barriers for the implementation of AT which consists of two phases; identification of barriers and qualitative analysis. This research consists of three steps: 1) identification of most relevant barriers for AT implementation from the literature; 2) survey of Indian steering wheel manufacturing industry, rank the identified barriers; 3) establish the interrelationships among barriers. Interpretive structural modelling (ISM) and MICMAC analysis were embraced to understand the interdependency among barriers. This study seeks to identify the most dominant barrier for AT implementation in Indian manufacturing industry.
  Keywords: barriers; interpretive structural modelling; ISM; MICMAC analysis; manufacturing system; agent technology.
  
  
• Advancing sustainable e-waste management systems integrated with artificial intelligence in developing countries  
  by Varun Kumar, Om Ji Shukla 
  Abstract: Industry 5.0 represents a paradigm shift in manufacturing and industrial processes, fostering collaboration between humans, robots, and smart devices. This evolution leverages advanced technologies such as artificial intelligence to boost productivity. In the context of e-waste management in developing countries, this study addresses the various influencing factors as drivers for enhancing the efficiency. These drivers were refined through an inter-consistency test and categorised using Fuzzy-DEMATEL. Notably, public awareness and technological advancement emerged as the most influential factors in integrating AI for sustainable e-waste management. Among these drivers, training and empowerment was found to be the most effective in driving positive change, while government policy and regulation played a pivotal role as the primary causal driver. This research offers valuable insights that can empower policymakers and environmental agencies to facilitate the adoption of AI and promote cleaner and more efficient e-waste management in developing countries.
  Keywords: artificial intelligence; Cronbach’s alpha; DEMATEL; e-waste management; influencing factors; sensitivity analysis.
  DOI: 10.1504/IJIE.2024.10063448
   
  
• Artificial intelligence in higher education: the challenges, opportunities and the road ahead  
  by Maureen Primrose Lal, Ramji Nagariya, Man Mohan Siddh 
  Abstract: This paper investigates to deliver an overview of literature from 2012 to 2023 on the phenomena of implementing artificial intelligence in education (AIEd). With the help of the Scopus indexing database, data from 441 articles were extracted, analysed based on the keywords and preliminary reading and synthesised according to explicit inclusion and exclusion criteria and article compilation was on the parameters of scientific procedures and rationales for systematic literature review protocol (SPAR4SLR). Drawing on the recent literature depicts that the inception of artificial intelligence in education is still in its initial stage and much research is required. This article implies that although there are benefits and challenges talked about in the article delving into the application of AIEd in higher education’s system of teaching and learning that shall lead the education system to newfound intelligence and automation, however, things are at the very initial stage and filled with conjectures. The findings demonstrate that the artificial intelligence-based teaching and learning phenomenon has a bright future as educational institutes understand its upcoming impact. The greatest challenge for educational institutes now is to start planning, designing, developing and implementing artificial intelligence-based courses for multidisciplinary and holistic training for future employees.
  Keywords: artificial intelligence; higher education; education; systematic literature review protocol; SPAR4SLR; artificial intelligence in education; AIEd.
  DOI: 10.1504/IJIE.2024.10063894
   
  
• Leveraging social media to mitigate information asymmetry during humanitarian relief operations  
  by Deepak Srivastav, Anand Gurumurthy 
  Abstract: This study investigates social media’s role in mitigating information asymmetry during humanitarian relief operations (HROs). The 2015 Chennai Flood is used as a case study, and social media analytics (SMA) is utilised to understand how social media can be leveraged to engage people with high social capital for rapid and accurate information diffusion. It uses well-established techniques for SMA, such as topic modelling, sentiment analysis, etc., to gain critical insights from the text corpus obtained from Twitter (now called X). The results show that affected people in a disaster use social media to communicate their concerns/needs to the government or humanitarian organisations (HO) through celebrities and media, which is a unique finding. Moreover, this study shows that organisations serving disaster-affected populations, such as HO and the government, can utilise celebrities not only to get feedback about HROs from the affected people but also to disseminate crucial information, such as alerts, to the affected population at increased speed. Hence, this study recommends that the HO and the government explore utilising the services of celebrities effectively during HROs, as they possess significant social influence.
  Keywords: social media; information asymmetry; 2015 Chennai Floods; celebrities; humanitarian supply chain management; HSCM; relief/response; case study.