International Journal of Management and Decision Making (10 papers in press)

Regular Issues

• Exploring the data analytical capabilities of generative AI tools ChatGPT and Google Bard (Gemini): a comparative analysis of GenAI tools with excel and python  
  by Nikhat Afshan, Vikram Chandramouli Rayadurgam, Angappa Gunasekaran, Girish H. Subramanian 
  Abstract: ChatGPT and Google Bard (now renamed as Google Gemini), the latest iterations of real-time generative artificial intelligence (GenAI), are being extensively used across discipline including education. There has been growing interest amongst academicians to integrate GenAI into teaching to create personalised learning experience for students. Though the recent versions of GenAI have been designed to tackle complex natural language and data analytical problems, concerns have been raised regarding the reliability of the outputs generated by these GenAI tools. This paper tries to explores the data analytical capabilities of ChatGPT 4.0 and Bard and understand its suitability to teach data analytics courses. The study conducts and compares three statistical analyses viz. regression analysis, classification analysis and linear programming problem using GenAI tools (ChatGPT 4 and Google Bard) and traditional software (Python and Excel). The study discusses the nuances of using these tools effectively by students, educators, and practitioners.
  Keywords: ChatGPT data analytics; generative AI; Google Bard; forecasting prediction; transportation problem; systematic literature review.
  DOI: 10.1504/IJMDM.2025.10069969
   
  
• Does the research done by the institutional investors stimulate or inhibit the management's opportunistic behaviours?  
  by Fateh Saci  
  Abstract: Based on the data from China A-share listed companies from 2014 to 2019, this paper examines the impact of the change of institutional investor research activities (frequency, research quality, research behaviour) on management opportunistic behaviour. Based on two types of agency costs as indicators : owner and management agency costs (AC1) and the controlling shareholder acts (AC2), the results show that institutional investor research activities have a significant stimulating effect on management opportunistic behaviour, while investors on-site visits have a more significant stimulating effect on management opportunistic behaviour, both of which have improved the first and second type of agency costs. The depth of the investigation stimulates the opportunistic behaviour of management by influencing the second type of agency costs. This paper has certain reference significance for the improvement of investor behaviour, corporate governance structure and protection of investors' interests.
  Keywords: management opportunistic behaviour; institutional investor research; agency cost; on-site visits; Shenzhen listed companies.
  DOI: 10.1504/IJMDM.2026.10072151
   
  
• From tradition to technology: understanding the key barriers of Agriculture 4.0 adoption in Bangladesh  
  by Mir Ramisha Bari, A.I.M Johurul Islam, Rifath Mahmud Uday, Sheak Salman 
  Abstract: The agricultural sector is crucial for the economic growth of developing countries like Bangladesh, where many rely on farming. Agriculture significantly contributes to global food security but faces challenges such as economic instability and environmental degradation. Agriculture 4.0 integrates digital technologies like the Internet of Things, big data analytics, artificial intelligence, and robotics, promising enhanced productivity, sustainability, and efficiency. This study explores Agriculture 4.0's potential in Bangladesh, identifies key adoption barriers, and analyses their interrelations using the single-valued neutrosophic decision-making trial and evaluation laboratory (SVN-DEMATEL) method with neutrosophic logic. It pinpoints 15 major challenges, emphasising inaccessibility to technology, high costs, and lack of management support as main obstacles. The result suggests "Intrinsic drive of farmers," "Insufficient management support," and "Inaccessibility to modern technology" as the most significant barriers, with values 0.542447, 0.354056, and 0.351115. The findings call for strategic policymaking and collaboration to promote smart, sustainable agriculture and food security.
  Keywords: Agriculture 4.0; barriers; multi-criteria decision making; MCDM; Delphi method; Bangladesh.
  DOI: 10.1504/IJMDM.2026.10072200
   
  
• A bounded rationality integrated decision-making approach for supplier selection in lean practice: a case study of Vietnam garment industry  
  by Thi-Ly Nguyen, Chia-Nan Wang, Nhat-Luong Nhieu 
  Abstract: Lean manufacturing focuses on eliminating waste across production. In supplier selection, applying lean principles helps identify partners that minimise waste in the supply chain. This study proposes an integrated multi-criteria decision-making (MCDM) approach for supplier selection in Vietnam’s garment industry. It combines stepwise weight assessment ratio analysis (SWARA) with a regret theory-based evaluation based on distance from average solution (EDAS) under spherical fuzzy conditions. The SF SWARA method determines evaluation criteria weights, while the regret-based SF EDAS ranks suppliers by proximity to the ideal solution. Findings show the hybrid approach enhances accuracy and reliability in lean supplier selection, supporting cost reduction and quality improvement. The study also offers a roadmap for practitioners and policymakers to optimise supplier evaluation, strengthen supply chain performance, and advance sustainable lean practices. Overall, it enriches decision-making methodologies within lean supply chain management and extends relevance to other industries facing similar challenges.
  Keywords: spherical fuzzy; stepwise weight assessment ratio analysis; SWARA; regret theory; EDAS; lean manufacturing; garment industry; Vietnam.
  DOI: 10.1504/IJMDM.2026.10073331
   
  
• Analysing the impact of perceived quality on the consumer purchase behaviour and decision-making from the perspective of a marketing mix  
  by Runumi Das  
  Abstract: The marketing strategy mix consists of advertising tools businesses use to influence customer responses and shape service characteristics. This study investigates how marketing mix elements affect consumer purchasing decisions in retail and e-commerce. A stratified sampling method was used to select 616 respondents, divided into customers and non-customers. Data was collected through a self-administered questionnaire, focusing on hedonic factors like entertainment, mental imagery, and aesthetics, which influence consumer satisfaction, defined as the extent to which products or services meet customer expectations. Using SPSS and a 5% significance level, results showed a strong link between marketing mix and consumer behaviour, with an unstandardised coefficient of 14.576. The study also revealed that convenience, simplicity, and lower prices are primary drivers for online shopping. These findings highlight how businesses can enhance consumer satisfaction by refining marketing strategies and maintaining consistent product quality, especially in a competitive online environment.
  Keywords: consumer purchase behaviour; self-administered questionnaire; one-stage stratified sampling technique; decision-making; marketing mix; purchase decision.
  DOI: 10.1504/IJMDM.2026.10073332
   
  
• Role of capability and professional marketing control in business results  
  by Paola Andrea Ortiz-Rendón, Jose Luis Munuera- Aleman, Luz Alexandra Montoya Restrepo 
  Abstract: Managers today increasingly demand proof that marketing decisions influence business results. This study explores the link between capability and professional marketing control, examining their effects on both non-financial and financial outcomes. We conducted a cross-sectional survey of 301 marketing managers and analysed the data using partial least squares structural equation modelling (PLS-SEM) via SmartPLS 4. The results reveal the mediating role of professional control in explaining how capability control influences financial outcomes. Moreover, the findings offer evidence of the positive effect of capability control on non-financial results. This work advances the understanding of marketing control across industries and its impact on business performance, with a specific emphasis on professional and capability control.
  Keywords: marketing capability control; marketing professional control; non-financial results; financial results.
  
  
• Leveraging data analytics in management accounting for enhanced decision making in the sharing economy  
  by Sumona Bhattacharya, Disha Sharma, Alka Pandey 
  Abstract: Data analytics plays a crucial role in management accounting within the sharing economy by enabling better decision making through insights from vast data sources. By employing advanced analytics techniques, organisations can optimise resource allocation, improve operational efficiency, and enhance strategic planning. Key benefits include an improved understanding of consumer behaviour, more accurate demand forecasting, and the implementation of dynamic pricing strategies. Data analytics helps reduce risks like fraud, and disruptions and enhances financial performance. The integration of analytics fosters real-time financial insights (25% effectiveness) and optimised cost management (18%), promoting agile, data-driven strategies for growth and competitive advantage. Python software is key in implementing these advancements, leading to more personalised customer experiences and flexible pricing models.
  Keywords: data analytics; decision making; sharing economy; key performance indicators; data visualisation.
  DOI: 10.1504/IJMDM.2025.10070932
   
  
• Regulatory focus theory and psychological decision making: a systematic literature review and future outlook  
  by Sradhanjali Samal, Saurabh Gupta 
  Abstract: Psychological theories have been extensively applied in consumer psychological literature to understand the elements that influence user intentions and decision-making processes. Regulatory focus theory (RFT) explores the ways in which decision-making is shaped by an emphasis on promotion and prevention. This study aims to perform a systematic literature review (SLR) of the existing literature to consolidate the current understanding of RFT. Therefore, this investigation aims to provide an in-depth analysis of the foundations of RFT and its connections with other relevant concepts in the realm of psychological theories. Furthermore, it provides an in-depth review of the most recent findings, significant topics, practical implications, and possible future directions in the realm of RFT literature. The findings highlight the important influence of the promotion focus and prevention focus framework in forecasting psychological decision-making processes. The analysis provides valuable insights for scholars and practitioners seeking to expand their comprehension of RFT. It addresses RFT's advantages and disadvantages, focuses on how it is used in different situations, and emphasises the need for methodological improvements in decision making research.
  Keywords: regulatory focus theory; RFT; promotion focus; prevention focus; decision making; systematic literature review; SLR.
  DOI: 10.1504/IJMDM.2025.10071923
   
  
• An integrated fuzzy Delphi-DEMATEL and analytic network process for sustainable operations and evaluations in process mining  
  by Mohammad Salehi, Raouf Khayami, Mirpouya Mirmozaffari 
  Abstract: This study examines the evolving role of process mining in monitoring real-world processes through advanced discovery algorithms like alpha, PSO miner, and genetic miner. Traditionally, these algorithms have been evaluated using precision, consistency, simplicity, and generalisation. However, the IEEE task force on process mining called for new dimensions and refined priorities. Using the fuzzy Delphi method, the study evaluated 12 dimensions and 20 criteria, narrowing them to 6 dimensions and 10 key criteria. The decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (DANP) method was applied to prioritise and weigh these factors. Key additions include the new dimensions of explainability and robustness. The study identifies consistency, cyclomatic complexity, and density as major performance influencers, with simplicity receiving the highest weight (0.175) and consistency the lowest (0.153). These findings aim to enhance process discovery algorithms by addressing both traditional and newly identified dimensions.
  Keywords: sustainable discovery algorithm; process mining; multi-criteria decision-making; MCDM; DEMATEL-based analytic network process; DANP; fuzzy Delphi; discovery algorithm's performance dimensions.
  DOI: 10.1504/IJMDM.2025.10069645
   
  
• Integrated mathematical model to optimise workstations in garment assembly line balancing  
  by Nhat Quyen Phan, Thi Diem Chau Le 
  Abstract: The study presents an integrated approach that combines ant colony optimisation (AntCO) and dynamic Min-Max normalisation (DMMN), namely the DMMN-AntCO, to address the assembly line balancing problem (ALBP) in the textile industry. The primary objective is to develop a practical approach for decision-making support by minimising workstation processing time deviation from takt time (TT) and reducing operational and setup costs. AntCO generates solutions iteratively using pheromone trails, while DMMN dynamically updates objective function values, allowing unbiased solution comparisons. Experimental outcomes show that the DMMN-AntCO significantly improves workload balance through the smooth index, decreasing from 8.72 to 6.01, and lowers production costs by over 360 USD compared to traditional methods. This study has provided a robust algorithm to optimise production line balancing, reduce costs, and enhance resource utilisation. The results confirm the effectiveness of the DMMN-AntCO method, thereby strengthening the fast response and competitive advantage of companies in the textile industry.
  Keywords: ant colony optimisation; dynamic Min-Max normalisation; DMMN; multi-objective optimisation; assembly line balancing; task allocation; meta-heuristic algorithm; textile industry; workload balance.
  DOI: 10.1504/IJMDM.2026.10072449