Management Science Applications Research Articles

Wetting dynamics and heat transfer of droplet evaporation around boiling point: Facile manipulation by surface roughness

The evaporation of water–ethanol droplets on solid surfaces has vast potential for applications in thermal management, microfluidics, and biomedical sciences, while the approach of manipulating wetting dynamics and heat transfer of droplet evaporation around the boiling point remains open for investigations. The present study proposes a facile approach: fabricating solid surfaces with diverse roughness by sandpaper milling with different grit densities, which can alter the wetting and heat transfer characteristics of droplet evaporation. We discover that when the temperature of the heated surface exceeds the droplet boiling point, the existence of bubbles affects the solid–liquid wetting state; surface roughness alters the ability of bubble departure, thus determining the solid–liquid contact and the contact line retraction time. Consequently, in this case, the solid–liquid contact area and the heat absorbed from heated surfaces for droplets changes with surface roughness, altering the droplet evaporation time and the average heat flux at the solid–liquid interface. Bridged by droplet wetting dynamics, the heat transfer of droplet evaporation above the boiling point can be manipulated by adjusting surface roughness, offering a facile approach to tuning the process of droplet evaporation in the related industrial applications.

Non-Classical Heat Transfer and Recent Progress

Abstract Heat transfer in solids has traditionally been described by Fourier's law, which assumes local equilibrium and a diffusive transport regime. However, advancements in nanotechnology and the development of novel materials have revealed non-classical heat transfer phenomena that extend beyond this traditional framework. These phenomena, which can be broadly categorized into those governed by kinetic theory and those extending beyond it, include ballistic transport, phonon hydrodynamics, coherent phonon transport, Anderson localization, and glass-like heat transfer, among others. Recent theoretical and experimental studies have focused on characterizing these non-classical behaviors using methods such as the Boltzmann transport equation, molecular dynamics, and advanced spectroscopy techniques. In particular, the dual nature of phonons, exhibiting both particle-like and wave-like characteristics, is fundamental to understanding these phenomena. This review summarizes state-of-the-art findings in the field, highlighting the importance of integrating both particle and wave models to fully capture the complexities of heat transfer in modern materials. The emergence of new research areas, such as chiral and topological phonons, further underscores the potential for advancing phonon engineering. These developments open up exciting opportunities for designing materials with tailored thermal properties and new device mechanisms, potentially leading to applications in thermal management, energy technologies, and quantum science.

Network reliability evaluation and management science applications in resource allocation for police organizations

The effective allocation of resources within police patrol departments is crucial for maintaining public safety and operational efficiency. Traditional methods often fail to account for uncertainties and variabilities in police operations, such as fluctuating crime rates and dynamic response requirements. This study introduces a fuzzy multi-state network (FMSN) model to evaluate the reliability of resource allocation in police patrol departments. The model captures the complexities and uncertainties of patrol operations using fuzzy logic, providing a nuanced assessment of system reliability. Virtual data were generated to simulate various patrol scenarios. The model’s performance was analyzed under different configurations and parameter settings. Results show that resource sharing and redundancy significantly enhance system reliability. Sensitivity analysis highlights critical factors affecting reliability, offering valuable insights for optimizing resource management strategies in police organizations. This research provides a robust framework for improving the effectiveness and efficiency of police patrol operations under conditions of uncertainty.

Penerapan Ilmu Manajemen Keuangan untuk Meningkatkan Pendapatan Masyarakat Melalui Pemberdayaan Ekonomi di Desa Ciwalat Kecamatan Pabuaran Kabupaten Sukabumi

This service is entitled Application of Financial Management Science to Increase Community Income Through Economic Empowerment in Ciwalat Village, Pabuaran District, Sukabumi Regency. The general aim of this community service activity is to provide practical training and knowledge of financial management in increasing community income through economic empowerment which has an impact on community welfare. The methods used are survey methods and direct delivery of material as well as simulations and discussions regarding management, financial management, product marketing and the application of HRM in increasing community income through economic empowerment which has an impact on community welfare. The conclusion of this community service is that management assistance will be provided in developing community knowledge to increase income through economic empowerment by establishing financial management through family financial reports in an effort to realize the welfare of the people of Ciwalat Village, Pabuaran District, Sukabumi Regency.

Penerapan Ilmu Manajemen untuk Meningkatkan Sumber Daya Manusia Melalui Potensi yang Ada dalam Hal Sikap Peduli Lingkungan dan Menjadi Masyarakat Edukatif agar Tercapainya Pembangunan yang Berkelanjutan Desa Ciwalat Kec. Pabuaran, Kab. Sukabumi

This community service project is titled "The Application of Management Science to Improve Human Resources through Existing Potentials in Environmental Awareness and Becoming an Educative Society to Achieve Sustainable Development in Ciwalat Village, Pabuaran District, Sukabumi Regency." This project was conducted on Sunday, June 2, 2024, and was attended by 20 students and 6 supervising lecturers from Pamulang University. The general objective of this community service activity is the application of management science to improve human resources (HR) through existing potentials in terms of environmental awareness and becoming an educative society in sustainable village development. Empowering village resource potentials to enhance the village economy and creating Ciwalat Village as a smart village and a leading village in Sukabumi Regency. The methods used include surveys, direct material delivery, as well as simulations and discussions on management, financial management, product marketing, and the application of human resource management (HRM). This community service activity successfully provided understanding to the community, especially MSMEs, regarding product marketing conducted through digital marketing via the marketplace (Shopee) in an effort to develop the businesses or enterprises of the Ciwalat Village Community.

Advancing interdisciplinary management science: A pathway to sustainable development goals

The Interdisciplinary Journal of Management Sciences (IJMS) plays a crucial role in advancing the understanding and application of management science in various fields. This editorial paper explores the intersection between interdisciplinary research and management science, emphasising the Journal's contribution to the Sustainable Development Goals (SDGs). IJMS encourages innovative research that addresses complex managerial issues, discourses, and challenges by incorporating principles from economics, engineering, social sciences, and technology. This paper highlights key areas of focus, such as decision-making, supply chain management, innovation, human resources, financial management, marketing, sustainability, educational management, conflict management, and governance. The relevance of each area to specific SDGs is discussed, showcasing how interdisciplinary approaches can provide comprehensive understanding and solutions to global issues. Despite the cognitive obstacles posed by disciplinary boundaries, methodological disparities, and pedagogical peculiarities inherent in interdisciplinary research, there are ample opportunities to leverage technological advancements and foster collaborative research for effective knowledge advancement. The IJMS's commitment to bridging theory and practice not only advances knowledge in management science but also makes a significant contribution to achieving the SDGs. This editorial calls for increased support from scholars, practitioners, and policymakers to further recognise interdisciplinary research in line with the Journal's vision for a future where management science drives sustainable development.

Strategi Manajemen untuk Keunggulan Kompetitif di Bidang Pendidikan

Strategic management is an analysis, decisions and actions taken by an organization to create and maintain a competitive advantage. This research method uses literature review research conducted by collecting and analyzing related literature from international and national sources in the form of books, journals, and articles. Based on this research, the application of strategic management science in educational institutions can face various challenges due to continuous change and competition and produce educational products (outputs) that are able to display high performance. The purpose of this research is to conduct an analysis related to the understanding and implementation of strategic management in creating a competitive advantage in the field of education, this research also aims to provide an in-depth understanding of the concept of strategic management and how its application can help educational institutions face the challenges of globalization and improve the quality of education. This research also highlights the urgency of implementing strategic management in educational institutions, given the challenges faced due to globalization and increasingly fierce competition. Strategic management is considered the key to creating a competitive advantage for educational institutions, enabling them to control their schools effectively and efficiently and produce superior quality graduates.

How AI Changes the Game in Finance Business Models

Purpose: This paper aims to examine the impact of AI on finance, including banking, risk management, and business models, while introducing AI-based tools. By exploring these applications, one can gain insights into the benefits of artificial intelligence in enhancing efficiency, productivity, and fostering innovation within financial sectors. Methodology: The research methodology employed in this study is a literature review. Various sources have been explored, studied, and analyzed within the financial domain to highlight the utilization of artificial intelligence. This includes risk management, identity verification, asset management, and data science applications. Furthermore, specific cases have been examined as part of case studies. Findings: The findings indicate that AI is transforming the finance industry by reshaping traditional business models and creating new growth opportunities. The integration of AI in finance has empowered companies to enhance decision-making processes, improve customer experiences, boost operational efficiency, and lower costs. AI-driven tools like predictive analytics, machine learning, and natural language processing are revolutionizing financial institutions' operations and customer interactions. As AI advances, it will play a crucial role in shaping the future of financial business models, driving competitiveness, and unlocking new industry potentials. Embracing AI technology is imperative for companies seeking to stay competitive and thrive in the dynamic financial landscape. Originality/Value: This research introduces various applications of artificial intelligence across different financial sectors alongside practical tools that can enhance the significance of this paper.

Optimizing the Strategic Application of Management Science: An Urban Case Study for the Sustainability of MSMEs in Bintaro, South Tangerang City

The objective of this study is to explore the most effective ways to apply Management Science strategically within Micro, Small, and Medium Enterprises (MSMEs/UMKM) located in the Bintaro area of South Tangerang City, West Java, Indonesia. Through a combination of mathematical analysis and technology utilization in a case study framework, the research evaluates the management science strategies employed by MSMEs in Bintaro and their effects on business performance and sustainability. The outcomes of this investigation are anticipated to offer valuable perspectives for stakeholders, business professionals, and scholars aiming to enhance MSME management techniques for better outcomes.

PERKEMBANGAN ILMU MANAJEMEN: DITINJAU DARI ILMU FILSAFAT

Philosophically, management is a collection of knowledge and beliefs that provide a basis for determining solutions to managerial problems. Every science cannot be separated from philosophy because philosophy is the root of all human knowledge, both scientific and non-scientific knowledge. Management philosophy and science have a close correlation. The practice and science of management has a very deep philosophical dimension. Management cannot be separated from philosophy because without philosophy management does not have a strong foundation. Based on the philosophy of science from an ontological perspective, the essence of management theory in business organizations is a science that offers a management process so that business organizations can achieve their goals. The final goal to be achieved through this management process is the achievement or fulfillment of the goals that have been set. Based on an epistemological point of view, management theory in business organizations introduces methods or ways of making decisions or solving problems that can be used by managers in running business organizations. Apart from that, management science introduces various management theories to be practiced in business activities. In an axiological perspective, ethical values and social responsibility must be taken seriously in the application of management science to business organizations. In management theory, business orientation is not only about seeking profit but also paying attention to the norms that apply in society and paying attention to the interests and welfare of all parties. Because management theory has an ontological, epistemological and axiological perspective, management theory is actually a philosophy of science. Therefore, management theory needs to be developed to be applied in business organizations.

Book Reviews

In Book Reviews, we review an extensive and diverse range of books. They cover theory and applications in operations research, statistics, management science, econometrics, mathematics, computers, and information systems. In addition, we include books in other fields that emphasize technical applications. The editor will be pleased to receive an email from those willing to review a book with an indication of specific areas of interest. If you are aware of a specific book that you would like to review or that you think should be reviewed, please contact the editor. The following books are reviewed in this issue of INFORMS Journal on Applied Analytics: The Spirit of Green: The Economics of Collisions and Contagions in a Crowded World (author: William D. Nordhaus; reviewer: Amitrajeet A. Batabyal) and Supply Chain Scheduling (authors: Zhi-Long Chen and Nicholas G. Hall; reviewer: Chelliah Sriskandarajah).

The solution of a type of absolute value equations using two new matrix splitting iterative techniques

Finding the solution of an absolute value vector equation (AVE) of the form Ax-\vert x\vert= b is an important subject in scientific computing, operations research, engineering, management science, and economic applications. This paper proposes two new iterative techniques to solve such AVEs. Both techniques are based on a decomposition of the coefficient matrix and a fixed-point principle. The convergence of the proposed techniques under appropriate assumptions is examined. We present results of numerical simulations to verify our theoretical findings and demonstrate the efficiency of our techniques.

How the Drafting of the Clayton Antitrust Act Helped Spread the Managerial Approach to Efficiency

Managerial sciences are generally considered to be the art of efficiently running business. Their influence, though, extends far beyond the corporate sphere, and they play an important part in public administration and in particular in its dialog with society at large. Here, from the viewpoint of historical institutionalism, we document one of the earliest successful examples of the wider application of management science: the 1914 antitrust rules (the Clayton Antitrust and Federal Trade Commission Acts) from the perspectives of economic scholars as technical experts, the early years of the Wilson administration, and the spheres of business and society. The societal debate about business and efficiency and the successive implementation of scientific managerial ideas in the administrative sphere, saw management science permeate the whole of American society and become an almost irrefutable aspect of everyday life and representations, thereby enabling it to spread well beyond the boundaries of the firm.

Algorithmic Study of Online Multi-Facility Location Problems.

Facility location (FL) is a well-known optimization problem that asks to optimally place facilities so as to serve clients at various locations, requesting a facility service, with minimum possible costs. Many variants of FL have been known, appearing as sub-problems in many applications in computer science, management science, and operations research. Most FL models studied thus far assume that clients need to be served by connecting each to one facility. To overcome facility failures and provide a robust solution, we investigate in this paper FL problems that require each client to be connected to multiple facilities, represented by an additional input parameter. The aim of the algorithm is then to provide a robust service to all clients while minimizing the total connecting and facility purchasing costs. This is known as the Multi-Facility Location problem (MFL) and has been studied in the offline setting, in which the entire input sequence is given to the algorithm at once. In this paper, we study MFL in the online setting, in which client requests are not known in advance but are revealed to the algorithm over time. We refer to it as the online multi-facility location problem (OMFL) and study its metric and non-metric variants. We propose the first online algorithms for these variants and measure their performance using the standard notion of competitive analysis. The latter is a worst-case analysis that compares the cost of the online algorithm to that of the optimal offline algorithm that is assumed to know all demands in advance. We further study OMFL in the leasing setting, in which facilities are leased, rather than bought, for different durations and prices, and each arriving client needs to be connected to multiple facilities leased at the time of its arrival. The aim is to minimize the total connecting and facility leasing costs.

Book Reviews

In Book Reviews, we review an extensive and diverse range of books. They cover theory and applications in operations research, statistics, management science, econometrics, mathematics, computers, and information systems. In addition, we include books in other fields that emphasize technical applications. The editor will be pleased to receive an email from those willing to review a book, with an indication of specific areas of interest. If you are aware of a specific book that you would like to review, or that you think should be reviewed, please contact the editor. The following book is reviewed in this issue of INFORMS Journal on Applied Analytics, 52(3), May–June: Give Yourself a Nudge: Helping Smart People Make Smarter Personal and Business Decisions, Ralph Keeney.

Riparian Zone DEM Generation From Time-Series Sentinel-1 and Corresponding Water Level: A Novel Waterline Method

Topography data are essential for land management, hydrology, and earth science applications. The topography in a riparian zone varies with time. Available global digital elevation models (GDEMs) do not satisfy the hydrological and environmental modeling requirements for riparian zones. In this study, a novel waterline method was proposed to acquire the digital elevation model (DEM) of riparian zones. Synthetic aperture radar (SAR) images are used to extract waterlines and corresponding water level is applied to acquire the elevation. The uneven water surfaces are considered to acquire the elevation of waterlines and Shuttle Radar Topography Mission (SRTM) DEM is used to interpolate the elevation of pixels without waterlines. The proposed method is applied in the riparian zone of Three Gorges Reservoir and Dongting Lake to test its feasibility. More than 80 Sentinel-1 SAR images at different water levels within three years are used to detect waterlines. Based on corresponding water level of hydrological stations, the elevation of waterlines are acquired via inverse distance weighting method. The distance layer and slope derived from the original SRTM DEM are used to interpolate the elevation of pixels between waterlines. The DEM generated by the proposed method is compared against the DEM derived in 2017, SRTM DEM, the DEM which does not include the uneven effects, and Ice, Cloud and land Elevation Satellite -2 (ICESat-2) ATL08. The good performance of the proposed method implies its high efficiency in revealing riparian zone topography.

Bayesian Meta-Prior Learning Using Empirical Bayes

Adding domain knowledge to a learning system is known to improve results. In multiparameter Bayesian frameworks, such knowledge is incorporated as a prior. On the other hand, the various model parameters can have different learning rates in real-world problems, especially with skewed data. Two often-faced challenges in operation management and management science applications are the absence of informative priors and the inability to control parameter learning rates. In this study, we propose a hierarchical empirical Bayes approach that addresses both challenges and that can generalize to any Bayesian framework. Our method learns empirical meta-priors from the data itself and uses them to decouple the learning rates of first-order and second-order features (or any other given feature grouping) in a generalized linear model. Because the first-order features are likely to have a more pronounced effect on the outcome, focusing on learning first-order weights first is likely to improve performance and convergence time. Our empirical Bayes method clamps features in each group together and uses the deployed model’s observed data to empirically compute a hierarchical prior in hindsight. We report theoretical results for the unbiasedness, strong consistency, and optimal frequentist cumulative regret properties of our meta-prior variance estimator. We apply our method to a standard supervised learning optimization problem as well as an online combinatorial optimization problem in a contextual bandit setting implemented in an Amazon production system. During both simulations and live experiments, our method shows marked improvements, especially in cases of small traffic. Our findings are promising because optimizing over sparse data is often a challenge. This paper was accepted by Hamid Nazerzadeh, Management Science Special Section on Data-Driven Prescriptive Analytics.

Book Reviews

In Book Reviews, we review an extensive and diverse range of books. They cover theory and applications in operations research, statistics, management science, econometrics, mathematics, computers, and information systems. In addition, we include books in other fields that emphasize technical applications. The editor will be pleased to receive an email from those willing to review a book, with an indication of specific areas of interest. If you are aware of a specific book that you would like to review, or that you think should be reviewed, please contact the editor. The following books are reviewed in this issue of INFORMS Journal on Applied Analytics, 51(4), July–August: Applications of Operations Research and Management Science for Military Decision Making, William P. Fox, Robert Burks; Behavioral Operational Research: A Capabilities Approach, Leroy White, Martin Kunc, Katharina Burger, Jonathan Malpass.

On Entropy-type Measures and Divergences with Applications in Engineering, Management and Applied Sciences

In this work we review Entropy-type measures and Divergences, discuss their properties and unfold their diverse applicability. In addition, we compare distances between populations and distributions via weighted Entropy-type measures relying mainly on Relative Entropy and Jeffrey’s Distance with weights. Finally, we introduce the Absolute Weighted Relative Entropy and the Absolute Weighted Jeffrey’s Distance. Two applications are presented for illustration, one from Geosciences and one from Financial Mathematics.

Book Reviews

In Book Reviews, we review an extensive and diverse range of books. They cover theory and applications in operations research, statistics, management science, econometrics, mathematics, computers, and information systems. In addition, we include books in other fields that emphasize technical applications. The editor will be pleased to receive an email from those willing to review a book, with an indication of specific areas of interest. If you are aware of a specific book that you would like to review, or that you think should be reviewed, please contact the editor. The following books are reviewed in this issue of INFORMS Journal on Applied Analytics, 51(3), May–June: Optimization and Control for Systems in the Big-Data Era: Theory and Applications, Tsan-Ming Choi, Jianjun Gao, James H. Lambert, Chi-Kong Ng, Jun Wang; Pricing Lives: Guideposts for a Safer Society, W. Kip Viscusi.