International Journal of Management and Decision Making (12 papers in press)

Regular Issues

• Unleashing potential for SMEs in resource-constrained economies through decision making practice: the mediating role of organisational learning and IT adoption  
  by Mugaahed Abdu Kaid Saleh, Fozi Ali Belhaj, Harold Andrew Patrick, Abdullah Yahia Al Gharsi 
  Abstract: Managers and owners of small and medium enterprises (SMEs) invest in their competences, organisational learning and utilising information technology to promote their businesses. Covering this aspect in the context of lower income countries is lacking in the literature. Further, the role of organisational learning and utilising information technology in facilitating the effect of decision making practices (DMPs) on SMEs performance. The current study fills this gap by exploring the aspect of manufacturing SMEs in Yemen as a lower income economy. By relying on cross-sectional design and primary data collected conveniently from 400 SMEs managers/owners in Yemen, the findings confirm a significant and positive direct effect of adopting DMPs on SMEs performance, and this effect is significantly mediated by utilising information technology and not by organisational learning. The results also show a direct effect of entrepreneurial competencies on SMEs performance. The implications and future directions of this study’s findings are discussed.
  Keywords: decision making; small and medium enterprises; SMEs; organisational learning; IT adoption; performance; decision making practices; DMPs.
  DOI: 10.1504/IJMDM.2025.10068041
   
  
• Reducing Muda with Industry 4.0: a case study on ERP system enhancement  
  by Hedayat Ebrahimi, Zahra Hassani, Sajjad Jalali, Vahid Hajipour 
  Abstract: This paper is to explore the integration of Industry 4.0 (I4.0) technologies into a customised enterprise resource planning (ERP) system, with a specific focus on reducing Muda in the manufacturing environment. As a fresh perspective, assessing the catalyst role of ERP is not limited to a certain module of the ERP but contains the main streams of functionality in the core business processes of the given context. The methodology involves conducting interviews with experts plus using ranking and inferencing approaches. This leads to pre-selecting, prioritising, and measuring the effectiveness of I4.0 enablers in reducing Muda besides justifying the implication of ERP’s applicability in the given context. Results demonstrate the contribution of enablers in reducing Muda while signalling the most substantial ones. Leveraging the core business processes of the ERP across the interaction between I4.0 enablers and Muda, the adaptability of the ERP to embrace the enablers is also conveyed.
  Keywords: Industry 4.0; lean practices; enterprise resource planning; ERP; waste management; best-worst method; BWM; integration.
  DOI: 10.1504/IJMDM.2025.10068403
   
  
• To investigate the influence of strategic factors on e-business adoption in small and medium enterprises: a multivariate analysis  
  by Ifrah Malik, Noman Sohail, Bin Hu, Fuqing Li 
  Abstract: This study explores the impact of strategic factors on e-business adoption by Chinese SMEs, focusing on innovation orientation, competitive pressure, and corporate strategy alignment. Using Rogers’ diffusion of innovation theory and the technology organisation evolution model, the research employs a multivariate approach to predict adoption patterns. Results show a strong link between technical organisation evolution traits and e business adoption. Organisations with explicit and advanced technological capabilities better absorb new technologies and transfer knowledge effectively. The study also emphasises that e-business adoption enhances company performance. It highlights policy implications to boost e-business adoption in China, benefiting SMEs, policymakers, and academics. As online shopping grows, its positive impact on people’s lives expands. The findings provide insights to foster e-business integration, enhance SME competitiveness, and promote socio-economic development through digital transformation in China.
  Keywords: e-business; small and medium enterprises; developing countries; technology adoption; diffusion of innovation; DOI; technology organisation evolution.
  DOI: 10.1504/IJMDM.2025.10068965
   
  
• Factors affecting customer relationship digital transformation strategies in airline industry: a grounded theory approach  
  by Parvaneh Assari 
  Abstract: The purpose of this study is to examine the factors which influence digital transformation (DT) strategies in customer relationship management (CRM) focusing on airlines in UAE using three key airlines as statistical population. Applying grounded theory (GT), the first phase took a qualitative approach using a methodological framework adapted from Corbin and Strauss (1990). This involved 13 CRM experts with deep understanding of digitisation processes within the airline sector who were subjected to intensive interviews during this stage. The participants were chosen using the snowball sampling approach, with theoretical saturation based on all important topics and ideas being investigated during the interview process. The qualitative analysis showed that successful CRM digital transformations have two essential phenomena: strategic digital transformation alignment with CRM objectives, technological adaptation and innovation. Besides, some causal and intervening conditions, strategies and outcomes have also been found outlining how these elements interact.
  Keywords: customer relationship; digital transformation; DT; airline industry; grounded theory.
  DOI: 10.1504/IJMDM.2025.10069422
   
  
• 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 Generalization. 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 prioritize 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; decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process; DANP; fuzzy Delphi; discovery algorithm’s performance dimensions.
  DOI: 10.1504/IJMDM.2025.10069645
   
  
• An analytics-based integrated decision tool for evaluating faculty workloads  
  by Steven F. Siconolfi 
  Abstract: This paper examines the integration of traditional teaching course loads (three courses in the fall plus three courses in the spring or four courses in the fall plus four courses in the spring) expressed as direct teaching hours, with percent effort distribution (Teaching, Scholarship, and Service). Sixteen analyses showed 70% Teaching, 20% Scholarship, and 10% Service with a 3+3 teaching load yielded a 40-hour academic workweek, 90% Teaching, 0% Scholarship, and 10% Service with a 4+4 teaching load yielded a 41-hour academic workweek. Adding administrative load as a percent, not equal to a course release, produced a six-day academic workweek. The addition of experiential learning only provided a marginal increase in workload. We recommend tenure track faculty teach and produce adequate scholarship and service with a 3+3 teaching load, and non-tenure track faculty teach and produce adequate service with a 4+4 teaching load. Departments should consider adjusting promotion and tenure guidelines to reflect the amount of available time.
  Keywords: workloads; teaching load; percent effort; academic workweek.
  DOI: 10.1504/IJMDM.2025.10069736
   
  
• 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
   
  
• 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
   
  
• Customer knowledge management, organisational ambidexterity, and firm performance: an organisational driving triangle perspective  
  by Fatemeh Khorasanchi, Ali Reza Hashemi Nekoo 
  Abstract: This paper examines the impact of customer knowledge management (CKM) on ambidexterity and firm performance. For this purpose, the authors propose a theoretical framework that examines how ambidexterity mediates the relationship between customer knowledge management and firm performance. The scope of this study encompasses 96 creative Iranian startups. This study is cross-sectional, and the data was collected within a month. To test hypotheses, we used partial least squares-structural equation modelling with Smart PLS-SEM v.3.2.8. The findings show that ambidexterity has a notable mediating function in the association between customer knowledge management and firm performance. The study conducted is one of the first to use mediation analysis to determine how organisational performance is affected by ambidexterity as a mediator. The findings show the important role of ambidexterity in the impact of customer knowledge management on business performance. It makes a significant contribution to the theoretical perspective of managing customer knowledge. The authors suggest practical decision-making recommendations for decision-makers adopting customer knowledge management.
  Keywords: customer knowledge management; CKM; firm performance; ambidexterity; partial least square; startup.
  DOI: 10.1504/IJMDM.2025.10069793
   
  
• Empowering innovation in Malaysian manufacturing SMEs: the influence of organisational resources and knowledge sharing with HRM practices as a moderator  
  by Haniruzila Hanifah, Hasliza Abdul Halim, Ali Vafaei-Zadeh, Syafrizal 
  Abstract: This study examines how structural capital, human capital, internal and external relational capital, and entrepreneurial orientation influence knowledge sharing, which impacts innovation performance in Malaysian manufacturing SMEs. It also investigates the role of human resource management practices in moderating this relationship. Analysing data from 133 manufacturing SMEs in Malaysia via partial least squares, the research reveals that structural, internal, and external relational capital, and entrepreneurial orientation, are positively linked to knowledge sharing. Surprisingly, human capital and international relational capital do not mediate between knowledge sharing and innovation performance. However, knowledge sharing positively correlates with innovation performance and is further enhanced by human resource management practices. These findings indicate the significance of intellectual capital and knowledge sharing in driving innovation, highlighting the crucial role of effective human resource management practices in this process. This study offers valuable insights for practitioners, policymakers, and scholars, informing strategic organisational decisions and future research.
  Keywords: intellectual capital; entrepreneurial orientation; knowledge sharing; innovation performance; HRM practices; manufacturing SMEs.
  DOI: 10.1504/IJMDM.2025.10065312
   
  
• Deep learning-based hybrid traffic flow prediction model for freight transport  
  by Anıl Utku, Sema Kayapinar Kaya, Umit Can 
  Abstract: Urban freight transportation is crucial to sustaining domestic and international trade and fulfilling the regular requirements of community companies and customers. Therefore, this study developed an efficient convolutional neural network (CNN) and long short-term memory (LSTM) based hybrid deep learning model for predicting traffic flow in freight transportation. The number of freight trucks that would travel along 663 Street in Anderlecht, Belgium, and their average speed was predicted. The created model was compared with support vector machine (SVM), linear regression (LR), multilayer perceptron (MLP), random forest (RF), LSTM, and CNN using the success measures. The critical finding of this study is that combining the feature extraction ability of the 1D CNN model with the learning ability of the LSTM model from multivariate traffic data increases the traffic density prediction success compared to other traditional methods. Based on the results of the experiments, the CNN-LSTM model outperformed all the other models employed in this study. With this model, freight density can be successfully predicted, assisting in planning freight transport activities.
  Keywords: deep learning; freight transportation; machine learning; traffic flow; traffic prediction.
  DOI: 10.1504/IJMDM.2025.10065663
   
  
• Assessment of performance indicators for sustainable agri-retail sector  
  by Murat Ulgu, Yesim Deniz Ozkan-Ozen 
  Abstract: The value of the agriculture sector is becoming even more pronounced due to increase in consumption. Therefore, ensuring sustainability in the agriculture sector is critical for the future of humanity. With the increasing power of retailers in the supply chain, they have gained importance in sustainability efforts in the sector. To achieve social, environmental, and economic sustainability in the agriculture sector, retailers need to enhance their own sustainability practices. Therefore, the agri-retail sector becomes one of a crucial area. In this study, social, environmental, and economic sustainability criteria were examined in the agri-retail sector through a sample study. The importance of the criteria was determined using the fuzzy criteria importance through intercriteria correlation (CRITIC) method, and total interpretive structural modelling (TISM) method is used for determining interrelations between the criteria. Based on the results, the prominent sustainability criteria for the agri-retail sector were identified and evaluated.
  Keywords: agricultural retail; sustainability; performance assessment; supply chain management; total interpretive structural modelling; TISM.
  DOI: 10.1504/IJMDM.2025.10067339