Big data analytics is critical in modern operations management (OM). In this study, we first explore the existing big data‐related analytics techniques, and identify their strengths, weaknesses as well as major functionalities. We then discuss various big data analytics strategies to overcome the respective computational and data challenges. After that, we examine the literature and reveal how different types of big data methods (techniques, strategies, and architectures) can be applied to different OM topical areas, namely forecasting, inventory management, revenue management and marketing, transportation management, supply chain management, and risk analysis. We also investigate via case studies the real‐world applications of big data analytics in top branded enterprises. Finally, we conclude the study with a discussion of future research.
Objective: This study examines how different research and development (R&D) funding sources—business enterprise R&D (BERD), higher education R&D (HERD), and government-financed R&D (GOVERD)—influence national innovation and competitiveness, measured by the Global Innovation Index (GII) and Global Competitiveness Index (GCI). This study addresses a critical gap by moving beyond aggregate R&D spending to examine how funding composition shapes innovation capacity. Methodology: Ordinary least squares (OLS) regression analysis was conducted on a sample of 47 countries using data from OECD R&D Statistics, World Bank Development Indicators, and GII/GCI reports. Missing values (< 3%) were imputed using mean substitution. Diagnostic tests were applied to verify normality, minimal multicollinearity, and compliance with heteroscedasticity assumptions. Two models were subsequently estimated with GII and GCI as dependent variables.Results: For the GII model (R² = 0.601, F = 12.37, p < 0.001), overall GERD intensity was significantly positive (β = 10.54, p = 0.040), while disaggregated components (BERD, HERD, GOVERD) showed no individual significance due to multicollinearity. GDP per capita was robust (β = 8.78e-05, p = 0.019). For the GCI model (R² = 0.651, F = 15.31, p < 0.001), GERD was non-significant; GDP per capita remained the strongest predictor (β = 0.0003, p < 0.001). Regression assumptions were satisfied (Jarque-Bera p > 0.44; Durbin-Watson ≈ 2.1).Conclusion: Overall R&D intensity significantly influences innovation, but relationships with disaggregated sources are complex. The importance of GDP per capita shows that the quality of institutions and the ability to absorb new ideas are both important for turning R&D spending into innovation and competitiveness benefits. Policymakers should prioritize both R&D funding levels and the institutional environment enabling effective R&D utilization.
Abstract To mitigate the environmental challenges posed by pollution and climate change, researchers are increasingly focused on developing highly efficient, emission-free transportation and energy systems. Electric Vehicles (EVs) implementation resolves the need for emission-free transportation, contributing to reduced air pollution and greenhouse gas emissions. Evs are utilized with advanced Brushless Direct Current (BLDC) motor for their efficiency and reliability, offering improved performance. For the purpose of decarbonized energy production, to power-up the BLDC motor, Renewable Energy Source (RES) based solar Photovoltaic (PV) system is equipped. However, to meet load demand due to insufficient DC output voltage attained from PV panels, this paper proposes a novel converter with an advanced Machine Learning (ML) based Maximum Power Point Tracking (MPPT) controller. A Quadratic Double Extended (QDE) DC-DC converter is proposed to improve voltage engendered from PV system, resulting with reduced voltage stress and improved gain. Moreover, for tracking of maximum power from PV, Sea Turtle Foraging optimized Radial Bias Function Neural Network (STFO-RBFNN) is introduced, ensuring tracking of most available power. The system incorporates supplementary sources including grid and battery to power BLDC motor of EV. The bidirectional converter together with battery enables flexible energy management by allowing for charging/discharging operations. A 3-phase Voltage Source Inverter (VSI) performs AC-DC conversion to drive the BLDC motor of EV. The simulation is done by MATLAB/Simulink and the results validate that introduced methodology significantly enhances performance, achieving improved converter efficiency (95.43%) with reduced Total Harmonic Distortion (THD) (1.14%) compared to state of art topologies.
Service quality is a critical issue in the healthcare sector due to its vital importance and significant impact on people’s lives. Therefore, organizations should continuously improve their service quality to ensure providing an optimal healthcare service as possible. In this study, healthcare service quality assessment methodology was proposed to investigate and assess the level of patient’s satisfaction through analysis and measure the gap between the perception service quality and the expectation services quality from patients point view. The proposed methodology integrates Percent Point Score method and Stepwise Weight Assessment Ratio Analysis Method SWARA Method and based six SERVQUAL dimensions namely; Tangible, Responsiveness, Reliability, Assurance, Empathy and, Administrative Procedure with 42 service quality criteria. Questionnaire was developed to capture the perception and the expectation service quality from patients point view was assessed. The perception and the expectation service quality have assessed by Percent Point Score method. SWARA Method was used to identified the weight of significant of each criterion. The proposed methodology was verified in real life at a healthcare center located in Baghdad and opinion of 100 patients have obtained for two months from 1/10/2024 to 1/12/2024. Results showed that waiting time for receiving the medical service (D22) and the booking system (D53) are the weakest service quality criteria that led to patients unsatisfaction, while protecting patients’ privacy, criteria (D46) achieved a high level of patient satisfaction (-0.23). The proposed methodology can help the medical center to investigate the level of quality of their various services to focus their resources in the improvement process to improve the weak services to achieve a high level of patients’ satisfaction. Various dimensions of quality service can be addressed for future works; in addition, a road map of improvement for the weak dimensions can be proposed to increase patient satisfaction.
Farhan Furqan, Christian Haposan Pangaribuan, Santo Tjhin
et al.
Purpose – This research examines the relationship between intrinsic religiosity, financial literacy, intention to use BNPL, and their combined effect on the growing purchasing behavior of Jakarta’s youth.
Design/methodology/approach – The study used a quantitative method with self-administered questionnaires provided to the target demographic in Jakarta. We also proposed a conceptual model that examines the connection between financial literacy and unrestrained purchasing behavior, intrinsic religiosity, and intention to use BNPL. Statistical techniques are applied to the collected data and for hypothesis testing.
Findings – Initial results indicate that intrinsic religiosity and financial literacy are positively correlated, and research found a favorable correlation between the likelihood of unconstrained buying behavior and the intention to use BNPL.
Research limitations/implications – Because a student sample was used and only a few respondents were included in the study, the findings may have wider applicability.
Practical implications – The study emphasizes how important financial literacy is among young consumers, especially with relation to religious values and beliefs.
Originality/value – While existing research rarely considers the specific influence of religious values, the novelty of the research lies in its focus on combining intrinsic religiosity and financial literacy when unrestrained buying behavior with Buy-Now-Pay-Later (BNPL) services.
Production management. Operations management, Management. Industrial management
Ambulance offload delays occur when emergency medical service (EMS) personnel are unable to promptly transfer patients to overwhelmed emergency departments. These delays postpone necessary care for the patient and hinder the EMS system from attending to new emergencies. This study introduces a real-time multi-priority patient transfer policy aimed at reducing these delays. We model the patient transfer problem as a stochastic dynamic program based on post-decision states, and develop approximate dynamic programming approaches to overcome the curse of dimensionality. Additionally, we derive a lower bound for the optimal solution through information relaxation. We evaluate the proposed method using both synthetic and real EMS data from St. Paul, Minnesota. Our solution is close to the lower bound, and the resulting policy results in a triple-win situation. For patients, our policy reduces hospital wait times by 80%; for hospitals, our policy alleviates emergency department congestion, and we find that even partial compatibility leads to notable system-wide improvements; for the EMS system, ambulance utilization is reduced by more than 30%, and ambulances could handle more calls per day, with a reduction in lost calls exceeding 80%.
Mohd Javaid, Abid Haleem, Ravi Pratap Singh
et al.
Lean 4.0, a fusion of lean manufacturing and digital technologies, is a powerful tool for implementing Industry 4.0. Its widespread use across sectors is driven by its ability to eliminate waste, reduce errors, boost revenue, and enhance customer care and efficiency. In the healthcare sector, this fourth lean revolution is particularly beneficial, as it helps to curb wastage and enhance efficiency, leading to more effective outcomes. Lean 4.0, a globally recognized best practice for industrial organisations, has proven its worth in enhancing performance and competitiveness. Its success has led to its adoption not only in manufacturing but also in non-manufacturing sectors such as Healthcare, finance, telecommunications, construction, and logistics. Its ease of use and effectiveness make it a superior alternative to traditional medical waste management techniques. Relevant papers on Lean 4.0 for Healthcare in the current literature are identified and studied to evaluate the impact of Lean 4.0 principles in Healthcare. This review-based research studies Lean 4.0 technologies and their needs in Healthcare. It discusses sustainable support for the healthcare sphere through Lean 4.0. Paper briefs several modalities of Lean 4.0 for the healthcare domain. Finally, the paper identifies and discusses the significant applications of Lean 4.0 in Healthcare. Lean 4.0 is essential to lowering errors that lead to medical mistakes since this business deals with life-or-death situations. Healthcare institutions need to reduce their overall waste reduction. With Lean 4.0, staff members working in quality management, clinical operations, consulting, and patient experience can progress into leadership roles in the healthcare sector. Lean 4.0 technologies can reduce waste production, including employing reusable medical equipment or cutting down on packaging waste. The possible difficulty of integrating digital technologies with healthcare systems and practices is Lean 4.0's limitations for the healthcare industry. Healthcare institutions can use refillable syringes and other disposable items to reduce waste rather than disposable plastic syringes. In future, healthcare institutions may save costs and lessen their environmental effect by minimising trash by using lean 4.0 technologies.
Miguel-Ángel Rangel-Sánchez, José-De-Jesús Urbina-González, José-Luis Carrera-Escobedo
et al.
The automotive industry is increasingly focused on waste management, elimination, and reduction to achieve sustainability and cost reduction. This focus drives the industry towards resource-efficient operations that minimize environmental impact while exceeding customer expectations. Meeting these demands necessitates the adoption of more efficient production methodologies, such as the PDCA cycle. This work presents a case study that illustrates the application of the PDCA methodology to minimize scrap generation due to process variability in a multinational company that manufactures electric motors for the automotive industry. The aim was to demonstrate how the PDCA methodology can improve quality standards by minimizing scrap generated during the manufacture of electrical armatures. Notably, the organization in this case study set a waste target of 0.7%, which was significantly exceeded. Finally, the implementation of this methodology can deliver significant economic benefits, with a total annual cost reduction of approximately USD 135,000.
Purpose – The purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process. Design/methodology/approach – The network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions. Findings – The selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions. Originality/value – This study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.
Industrial engineering. Management engineering, Production management. Operations management
Sushil Gupta, Martin K. Starr, Reza Zanjirani Farahani
et al.
We have reviewed disaster management research papers published in major operations management, management science, operations research, supply chain management and transportation/logistics journals. In reviewing these studies, our objective is to assess and present the macro level “architectural blue print” of disaster management research with the hope that it will attract new researchers and motivate established researchers to contribute to this important field. The secondary objective is to bring this disaster research to the attention of disaster administrators so that disasters are managed more efficiently and more effectively. We have mapped the disaster management research on the following five attributes of a disaster: (1) Disaster Management Function (decision‐making process, prevention and mitigation, evacuation, humanitarian logistics, casualty management, and recovery and restoration), (2) Time of Disaster (before, during and after), (3) Type of Disaster (accidents, earthquakes, floods, hurricanes, landslides, terrorism and wildfires etc.), (4) Data Type (Field and Archival data, Real data and Hypothetical data), and (5) Data Analysis Technique (bidding models, decision analysis, expert systems, fuzzy system analysis, game theory, heuristics, mathematical programming, network flow models, queueing theory, simulation and statistical analysis). We have done cross tabulations of data among these five parameters to gain greater insights into disaster research. Recommendations for future research are provided.
In this study, we employ system dynamics to study the combined effect of extended payment terms and a buyer's supply risk management practices on two outcomes: the supplier's bankruptcy risk and the buyer's financial bottom line. In conjunction with payment terms, we model the impact of two commonly recommended supply chain risk management (SCRM) practices: quick response to supply disruptions and use of a secondary (backup) source. Among other results, we uncover a feedback mechanism that contributes to the negative effect of extended payment terms on a supplier's finances and show that longer payment terms can worsen buyer outcomes, especially when the supplier faces a higher risk of disruptions. We also show that, when considered alongside extended payment terms, common SCRM practices may not always be beneficial for buyer firms. Our research suggests decisions related to SCRM and extended payment terms should not be made independently.
This paper focuses on the critical roles of knowledge workers when a firm pursues a major innovation project. In this context, we consider knowledge workers as those who contribute to a firm's performance at the executive, management, and technical specialist levels. Technical specialists include persons with advanced skills in engineering, analytics, statistics, science, and economics. By analyzing a series of case studies and personal interviews, we demonstrate that alignment (i.e., coordination, integration, and collaboration) among these knowledge workers is critical for the success of an innovation project. The paper concludes with a discussion of the responsibilities of knowledge workers at the executive, management, and technical specialist levels to ensure the necessary alignment occurs for successful innovation.
Mino Sportelli, Christian Frasconi, Marco Fontanelli
et al.
Organic vegetable production is particularly affected by weed pressure and mechanical weeding is the major tactic implemented by growers to keep weeds under economic thresholds. Living mulch (LM) has been shown to provide several environmental services; however, LM management is required to avoid competition between service crops and cash crops. The aim of this trial was to evaluate two innovative LM-based management systems: a system that provided LM growth regulation by means of flaming (LM-FL) and a system where the LM was regularly mowed by an autonomous mower (LM-AM), both compared with a control without LM and based on standard tillage operations (TILL). The three management systems were evaluated in terms of crop production, weed control, and energy consumption on a 2 yr organic crop rotation of cauliflower (<i>Brassica oleracea</i> L. var <i>botrytis</i>) and eggplant (<i>Solanum melongena</i> L.). LM-AM produced an acceptable fresh marketable yield for both vegetable crops. Moreover, the weed dry biomass obtained in LM-AM-managed plots was lower compared to the LM-FL plots and ranged approximately from 200 to 300 kg ha<sup>−1</sup>. Furthermore, LM-AM management resulted in lower energy consumption (−2330 kWh ha<sup>−1</sup> with respect to the TILL system and −7225 kWh ha<sup>−1</sup> with respect to the LM-FL system). The results of this trial suggest that autonomous mowers have a great potential to improve LM management and help with implementing sustainable organic vegetable systems.
With supply chains becoming increasingly extended, the uncertainties in the upstream production process can greatly affect the material flows that aim toward meeting the uncertain demands at the downstream. We analyze a two‐location system in which the upstream production facility experiences random capacities and the downstream store faces random demands. Different from the widely used approach that seeks the decomposition of the profit function based on the echelon inventories, our approach builds on the notions of stochastic functions, in particular, the stochastic linearity in midpoint and the directionally concave order. With these notions, we establish the concavity and submodularity of the profit functions in the transformed decision variables. In general, it is optimal to follow a two‐level state‐dependent threshold policy such that an order is issued at a location if and only if the inventory position of that location is below the corresponding threshold. In the special case where the salvage values are linear in the ending inventories, the profit function becomes separable in the inventory positions, and the optimal policy reduces to the echelon base‐stock policy. The effect of the uncertain capacity and demand depends critically on whether the production capacity is limited or ample in relation to the demand. Only when the capacity and the demand do not differ much, the upstream facility carries positive inventory; otherwise, all units produced are shipped immediately toward the downstream. We further extend our analysis to systems with general stochastic production functions and with multiple locations.
In the era of growing competitiveness on the labour market, it has become common for students and graduates of higher education institutions to participate in various types of training courses and obtain various types of certificates, which are an additional asset when applying for employment. The interaction of a university with the environment requires constant monitoring of the expectations of labour market. Therefore, the main objective of the paper is to analyse of labour market requirements on additional certified competences of graduates during their studies. The paper attempts to answer the question: whether, and if so, to what extent the training received and the certificates obtained by the potential employee are important from the employer's point of view. The matters raised in it are a contribution to the discussion on the issue of needs and preferences of employers, including the most important aspects that guide them during the recruitment process. The study presents the results of surveys aimed at analysing the preferences of entrepreneurs and other entities in relation to the competences of graduates of universities. The survey method was chosen from among the empirical research methods used, which is characterized by a nomothetical approach, aimed at seeking generalized judgments, laws and rules for a certain class of situations or events. The survey covered not only entrepreneurs, but also representatives of other entities. Random sample selection was adopted for the conducted surveys. Setting the acceptable margin of statistical error at e=5.5%, for confidence level a=0.80 (Z=1.28), response distribution f=0.5 and population size Np=107.798. It has been calculated that the minimum research sample should consist of Nmin=136 employers. The draw was conducted on the basis of a list of all entities of the Swietokrzyskie Region in Poland. The collected quantitative data were analysed. The survey results indicated that employers pay attention to certificates, qualifications, courses and trainings obtained by university graduates. Additionally, graduates should demonstrate some professional experience, therefore student apprenticeships and practical profiles of education are also important. Respondents emphasized the problem of the deficit of the skills of applying knowledge in practice by university graduates, stating the ubiquitous excess of theory over practice.
Production management. Operations management, Personnel management. Employment management
Donors and governments are increasingly calling for more collaborative relationships between humanitarian organizations (HOs), to improve the efficiency and effectiveness of humanitarian operations by exchanging information, knowledge, and resources. This study examines the relative efficacy of partners' characteristics (i.e., compatibility and resource complementarity) and partners' relationship management capability on collaborative relationships, incorporating mutual trust and reciprocal commitment as two mediator constructs. We use Partial Least Squares to examine the proposed hypotheses using a sample of 191 respondents. Data are collected through a web‐survey of international humanitarian non‐governmental organizations (NGOs) in countries across Africa, Asia, and South America. The results reveal that (i) resource complementarity and relationship management capability are significant factors influencing collaborative performance through their effects on partners' mutual trust and reciprocal commitment, and that (ii) partners' compatibility (i.e., missions, values, and operational methods) does not significantly drive success or failure of collaboration between international NGOs. These results suggest that given the present diversity of HOs' characteristics, the success of collaboration is associated with the partners' level of understanding of each other's objectives, operations, and values, and to the extent to which organizations efficiently communicate and coordinate their joint activities. The managerial implications of the findings are also discussed.
Corporate Political Activities (CPA) and Corporate Public Relations (CPR) are both non-market communication strategies that effect market positioning, brand strength and the business success of a company. In this study, the use of CPA and CPR by several companies are analyzed based on their economic and brand strength metrics, which confirms the hypothesis that use of these strategies has a positive impact on their market position and brand stability. Using the Multi-Value Comparative Quality Analysis (mvCQA), the research strives to measure the synergistic influence of CPA and CPR on a company's performance. Building on the existing literature for the uses and implementation of mvCQA, this research reinforces the role mvCQA plays in delivering quality and comparative findings of correlation between CPR and CPA toward market strength. This study confirms that the synergy between CPR and CPA improves corporate strategic development. It is inferred that CPR and CPA maintain non-linear correlation with industry and market niches, specific cultural and business environments, as well as overall corporate strategy goals.
Production management. Operations management, Personnel management. Employment management
The decision made by top management to form an internal audit should be aimed at improving the security of
the entire company. This ensures the safety of top management in all enterprises, especially in agricultural enterprises
that rely on primary agriculture and processing of agricultural products with the aim of producing production that is
more valuable than primary agricultural products.
Internal audit should be introduced in the regular course of business of the enterprise with the aim of improving
the overall security of the business of the enterprise. One form of implementation is to improve internal controls
already in place by giving internal management advice and advice to top management on how to improve the controls
already in place.
The contribution of the authors who made this study is to emphasize and emphasize the importance of
implementing internal audit, which, after the decision of top management to introduce internal audit in the processes of
business operations of the company. The aim of such a decision is to increase the security of the business of the
enterprise and, together with the existing internal control, to build a more secure business system in order to contribute
to the improvement of the performance of the agricultural enterprise. The process was emphasized by the authors as
being continuous and not carried out in the short term because the postulates of setting up and setting up a business
are presumably permanent and long-term.
Commercial geography. Economic geography, Economics as a science
Past research (along with our experience) suggests that a firm's supply chain (i.e., value chain) plays an integral role in its ability to not only reduce cost via process innovation, but also in its ability to develop new products and services. Evidence suggests the value chain is playing an ever‐more‐important role, with greater prevalence of distributed product development (spanning geographic, organizational, or firm boundaries) and open innovation (performed outside the firm). We discuss some of the trends with regard to supplier and customer involvement in the innovation process, and summarize some of the research exploring the rationale behind those trends and the research offering advice on how firms can use external resources to further improve their innovation performance. We present a number of examples that illustrate some best practices.
The interaction between science and policy is affected by increasingly dissolving boundaries whereby a number of issues arise, such as, what should political advice for national parliaments consist of in the face of global socio-technical developments? The Internet of Things in relation to Big Data resulting in enormously fast analysis of huge amounts of data, accelerates the dissolution of boundaries between science, society and policy at global level. This type of “globalization” raises questions that concern very diverse and intimate areas of life, ranging from food to health to work automation. How can access to science and technology in very different societal settings can be enabled, while also accounting for global developments? The article deals with the assumption that global effects of science and technology as well as global challenges lead to an urgent need to develop methodologies for analyzing and also shaping these developments. Under the umbrella term “Global Technology Assessment” (Global TA) it is argued that the problem-oriented, interdisciplinary methodology of technology assessment offers a promising frame to deal with cultural and ethical questions in relation to emerging technologies. This framework is needed in order to be able to develop meaningful national comparisons, but also in order to be able to approach the analysis of common future challenges on equal footing.