Business Metrics Research Articles

Global Metrics for Terrestrial Biodiversity

Biodiversity metrics are increasingly in demand for informing government, business, and civil society decisions. However, it is not always clear to end users how these metrics differ or for what purpose they are best suited. We seek to answer these questions using a database of 573 biodiversity-related metrics, indicators, indices, and layers, which address aspects of genetic diversity, species, and ecosystems. We provide examples of indicators and their uses within the state–pressure–response–benefits framework that is widely used in conservation science. Considering complementarity across this framework, we recommend a small number of metrics considered most pertinent for use in decision-making by governments and businesses. We conclude by highlighting five future directions: increasing the importance of national metrics, ensuring wider uptake of business metrics, agreeing on a minimum set of metrics for government and business use, automating metric calculation through use of technology, and generating sustainable funding for metric production.

Nonstationary A/B Tests: Optimal Variance Reduction, Bias Correction, and Valid Inference

We develop an analytical framework to appropriately model and adequately analyze A/B tests in presence of nonparametric nonstationarities in the targeted business metrics. A/B tests, also known as online randomized controlled experiments, have been used at scale by data-driven enterprises to guide decisions and test innovative ideas to improve core business metrics. Meanwhile, nonstationarities, such as the time-of-day effect and the day-of-week effect, can often arise nonparametrically in key business metrics involving purchases, revenue, conversions, customer experiences, and so on. First, we develop a generic nonparametric stochastic model to capture nonstationarities in A/B test experiments, where each sample represents a visit or action associated with a time label. We build a practically relevant limiting regime to facilitate analyzing large-sample estimator performances under nonparametric nonstationarities. Second, we show that ignoring or inadequately addressing nonstationarities can cause standard A/B test estimators to have suboptimal variance and nonvanishing bias, therefore leading to loss of statistical efficiency and accuracy. We provide a new estimator that views time as a continuous strata and performs poststratification with a data-dependent number of stratification levels. Without making parametric assumptions, we prove a central limit theorem for the proposed estimator and show that the estimator attains the best achievable asymptotic variance and is asymptotically unbiased. Third, we propose a time-grouped randomization that is designed to balance treatment and control assignments at granular time scales. We show that when the time-grouped randomization is integrated to standard experimental designs to generate experiment data, simple A/B test estimators can achieve asymptotically optimal variance. A brief account of numerical experiments are conducted to illustrate the analysis. This paper was accepted by Baris Ata, stochastic models and simulation. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.01205 .

AI-driven Business Model Innovation - Where Technology Meets Strategy

Business Model Innovation (BMI) involves redefining how organizations create, deliver, and capture value. With the advent of Artificial Intelligence (AI), businesses are increasingly leveraging these technologies to transform their models. The current research investigates the impact of AI on BMI using primary data collected from various industries. It employs statistical analyses to understand the extent of AI adoption, its effects on business model components and various key business metrics. The study identifies key trends in AI adoption across functions and industries. Key findings reveal significant correlations between AI usage and improvements in key business metrics such as operational efficiency, customer engagement, and revenue streams thus resulting in an organization’s competitive advantage. Businesses can make better-informed decisions, establish more effective workflows, and produce more powerful marketing campaigns as a result of AI adoption. It also provides a competitive edge and lays the framework for future growth. This academic work makes a substantial contribution to the discourse on AI for business model innovation, where technology is leveraged to optimize strategy.

ANALSIS KOMPARASI KINERJA KEUANGAN BANK MEGA SYARIAH MENGGUNAKAN METODE RGEC PADA MASA SEBELUM DAN SELAMA PANDEMI COVID-19

The COVID-19 pandemic has had an impact on all industrial sectors in Indonesia, one of which is the sharia banking sector. During the pandemic, banking performance experienced fluctuations in terms of deposits and debt financing; Bank Mega Syariah also experienced fluctuations in financial ratios and deposits, which could have an impact on the bank's financial performance. The purpose of this study is to evaluate Bank Mega Syariah's financial results utilizing the RGEC approach both before and after the COVID-19 epidemic. This study used quantitative research using a descriptive methodology. Data was acquired through the use of documentation methods. Financial ratio analysis utilizing the RGEC method is the data analysis method employed. The findings demonstrate that Bank Mega Syariah's financial performance, as measured by the RGEC technique, was superior to its pre-COVID-19 pandemic financial performance during the pandemic-affected period. This is shown by Bank Mega Syariah's ability to continue turning in a profit despite the COVID-19 pandemic's negative impact on the business environment. This accomplishment is demonstrated by the growth in several key business metrics, which were maintained, including bank profitability, finance distribution, and Third Party Funds.Keywords: Financial Performance; Bank Health Level; RGEC Method

Developing national cancer survivorship standards to inform quality of care in the United States using a consensus approach

PurposeTo develop United States (US) standards for survivorship care that informs (1) essential health system policy and process components and (2) evaluation of the quality of survivorship care.MethodsThe National Cancer Institute and the Department of Veterans Affairs led a review to identify indicators of quality cancer survivorship care in the domains of health system policy, process, and evaluation/assessment. A series of three virtual consensus meetings with survivorship care and research experts and advocates was conducted to rate the importance of the indicators and refine the top indicators. The final set of standards was developed, including ten indicators in each domain.ResultsPrioritized items were survivor-focused, including processes to both assess and manage physical, psychological, and social issues, and evaluation of patient outcomes and experiences. Specific indicators focused on developing a business model for sustaining survivorship care and collecting relevant business metrics (e.g., healthcare utilization, downstream revenue) to show value of survivorship care to health systems.ConclusionsThe National Standards for Cancer Survivorship Care can be used by health systems to guide development of new survivorship care programs or services or to assess alignment and enhance services in existing survivorship programs. Given the variety of settings providing care to survivors, it is necessary for health systems to adapt these standards based on factors including age-specific needs, cancer types, treatments received, and health system resources.Implications for Cancer SurvivorsWith over 18 million cancer survivors in the United States, many of whom experience varied symptoms and unmet needs, it is essential for health systems to have a comprehensive strategy to provide ongoing care. The US National Standards for Survivorship Care should serve as a blueprint for what survivors and their families can anticipate after a cancer diagnosis to address their needs.

Exploring the Dynamics of Innovation Antecedents and Outcomes in Business Performance

The current research critically addresses a significant gap in understanding the intricate dynamics between the drivers and outcomes of innovation within various organizational contexts. While innovation is widely recognized as a crucial driver for growth and competitiveness in the rapidly evolving business landscape, the specific mechanisms through which these drivers influence outcomes remain underexplored. This lack of detailed insight is a substantial barrier to effective strategy development and implementation, underscoring the importance of this study. The research aims to thoroughly explore key antecedents such as organizational culture, leadership, financial strategies, and external environmental conditions that promote an innovative environment. It also evaluates the extensive impact of these innovations on business performance, focusing particularly on market competitiveness, operational efficiency, and customer loyalty. By examining the connections between these factors, the study seeks to outline the pathways through which innovation enhances business performance across various industries and market conditions. The formulated research questions are designed to identify the principal antecedents of innovation, assess their broad impacts on business metrics, and ascertain under which circumstances these effects are maximized. This comprehensive analysis intends to bridge the theoretical and empirical gaps, providing insights that could guide both academic research and practical business strategy development in the realm of innovation management.

Distributionally-Informed Recommender System Evaluation

Current practice for evaluating recommender systems typically focuses on point estimates of user-oriented effectiveness metrics or business metrics, sometimes combined with additional metrics for considerations such as diversity and novelty. In this article, we argue for the need for researchers and practitioners to attend more closely to various distributions that arise from a recommender system (or other information access system) and the sources of uncertainty that lead to these distributions. One immediate implication of our argument is that both researchers and practitioners must report and examine more thoroughly the distribution of utility between and within different stakeholder groups. However, distributions of various forms arise in many more aspects of the recommender systems experimental process, and distributional thinking has substantial ramifications for how we design, evaluate, and present recommender systems evaluation and research results. Leveraging and emphasizing distributions in the evaluation of recommender systems is a necessary step to ensure that the systems provide appropriate and equitably distributed benefit to the people they affect.

A novel approach to optimizing customer profiles in relation to business metrics

<span lang="EN-US">Business is very closely related to customers. Each user owns the data, and the data is used to identify cross-selling opportunities for each customer. For example, the type of product or service purchased, the frequency of purchases, geographic location, and so on. By doing so, you can gain the ability to manage and analyze customer data, allowing you to create new opportunities in industries that were previously difficult to enter. The purpose of optimizing user profiles is to determine minimum or maximum business value and improve efficiency by determining user needs. In this study, multivariate adaptive regression spline (MARS) is a statistical model used to explain the relationship between the response variable and the predictor variable. Robust is used to find variable relationships to make predictions. To improve classification performance, the model is validated using a confusion matrix. The results show an accuracy value of 84.5%, with better time management (period management) reflected in the number of hours spent by merchants as well as discounts during that time period, which has a significant impact on any business. In addition, the distance between customers and merchants is also important, as customers prefer merchants who are closer to them to save time and transportation costs.</span>

Optimizing Forest-Biomass-Distribution Logistics from a Multi-Level Perspective—Review

Forest and wood biomass represent a sustainable reservoir of raw materials and energy, offering a viable alternative to fossil fuels. These resources find extensive use in producing bioproducts, including solid wood and wood materials. The judicious exploitation of forest and wood biomass can be pivotal in reducing carbon emissions and securing material and energy independence. The business viability of producing valuable goods from woody biomass hinges on ensuring its sustained availability. This necessitates access to high-quality biomass at a minimal cost, demanding the efficient design of wood-biomass-distribution logistics. Furthermore, it is imperative to give equal weight to social and ecological considerations in shaping the forest- and wood-biomass-distribution logistics, thereby ensuring the sustainable utilization of this renewable raw material source. This article presents research focused on the business optimization of distribution logistics for specific forms of forest biomass used in wood material production. While most studies have primarily concentrated on the business or ecological issues of biomass utilization, this article offers a comprehensive insight by addressing business, ecological, and social facets in assessing and optimizing wood-biomass-distribution logistics. Multi-stakeholder life-cycle-assessment optimization takes into account the reduction of greenhouse gases as an ecological metric, with production costs and capital expenditure forming the business metrics. At the same time, the generation of employment opportunities is commonly regarded as the pivotal social criterion. There remains a necessity for further exploration into the potential social impacts of forest biomass utilization. Additionally, developing enhanced methodologies and decision-support tools for scheduling wood-biomass-distribution logistics that holistically consider business, ecological, and social criteria is an essential ongoing task.

Perceived Impacts of the COVID-19 Pandemic on Private-Sector Urban and Community Forestry in the Southern United States

AbstractBackgroundPrivate-sector urban and community forestry (U&CF) is a major segment of the green industry with substantial socio-ecological and economic contributions to urban and sub-urban communities. The COVID-19 pandemic reportedly caused heterogeneous impacts on businesses, the workforce, and various sectors of the overall economy. The purpose of this study was to evaluate the perceived impacts of the COVID-19 pandemic on private businesses carrying out U&CF activities in the Southern United States.MethodsUsing data collected through an online survey distributed across the Southern USA in 2021, we developed and estimated an empirical model to evaluate the factors describing the perceived impacts of the COVID-19 pandemic on U&CF businesses in the region.ResultsResults suggest that COVID-19 had, on average, a neutral impact on the U&CF activities performed by the private sector in the study region, but the perceived impacts varied by the industry types. Results from the ordered logistic regression suggest that nursery and garden supply stores were more likely than other businesses to have a positive impact of COVID-19 on the U&CF segment of their business. Similarly, business metrics such as the size of the company in terms of annual sales and revenues or longevity in the business were found to be significant factors explaining the COVID-19 impacts on U&CF business.ConclusionOur study findings are useful for U&CF decisionmakers for better planning, preparedness, and programming of U&CF activities and businesses in the southern USA.

Использование тепловых карт для оптимизации образовательных бизнес процессов в компании Скилбокс

<p>The article addresses data analysis methods for solving the problem of choosing the best solution in order to optimize resources using the example of Skillbox company. The problems of choosing information resources are considered and solved, taking into account market offers. The author considers various methods of data analysis with an emphasis on minimizing the resources required for their processing. In the article, the author describes the practical application of the "Digital Assistant" program, which was developed by the Skillbox company to measure product metrics and analyze the behavior of students. Using the big data analysis methods described by the author, ways to optimize educational business processes that lead to an increase in the profitability of educational courses are considered. Heat maps are considered as one of the main ways to analyze big data, and their practical application is described. The author describes the relationship between business metrics and changes occurring with the educational product and suggests methods and frequency of surveys and feedback processing about the educational path of students.</p>

Measuring the business value of generative AI

Generative artificial intelligence (GenAI) can deliver tangible and intangible values that can be calculated to decide which projects benefit from GenAI and which do not. This paper is intended to be a guide for businesses just starting to build traction for their ideas. The focus is on evaluating and leveraging GenAI’s potential to innovate faster and compete effectively in a rapidly evolving digital economy. The paper specifies the many ways GenAI can have an impact on a business and considers how to measure that impact. It starts with standard business metrics (revenue, profit, customer satisfaction, etc.) and then turns to the more esoteric task of measuring the impact on creativity, inspiration and innovation, followed by business disruption and process metrics. It finishes with a look at improving process improvement.

Overview of the economic activity of cloud providers and research on the theoretical foundations of cloud computing

Introduction. Cloud services have become an integral part of all modern companies, contributing to business development, providing flexibility and scalability and accelerating business operations, the need to use cloud services will only grow in an environment where everything is constantly changing. With services such as data storage, computing power, and application hosting on the Internet, companies of all sizes can gain a competitive advantage.Providers that provide cloud services offer enterprises several advantages over the traditional approach in the organization of IT infrastructure. For example, one of the main types of cloud services is SaaS, or Software-as-a-Service, this model allows companies to pay only for what they use. This gives certain advantages over the use of its own iron, which requires a significant initial investment and ongoing costs to maintain the system in working order. The flexibility that can be provided by using the services of cloud providers is the ability to scale as needed both vertically, improving cloud hardware configurations, and horizontally, increasing the number of computing machines, it is obvious that such scaling attempts in companies that use their own architecture await significant investments and costs.The purpose of the study is to review the economic activities of cloud service providers, research and study the main aspects of cloud services and describe the basic definitions of cloud computing.Methods are based on the system-logical generalization of the content essence of theoretical aspects regarding the use of cloud services.Results. As a result of the study, definitions and recommendations for using the services of cloud providers were provided. The impact of cloud technologies on business and key performance metrics of software product development were analyzed. The practice of using the services of cloud providers by companies from the IT sector and other industries was studied. In addition, an example of the practical use of a cloud database was developed, using the example of database initialization, which demonstrates the practicality and speed of the process.Prospects. Further research will be aimed at the practical development of an application that uses cloud computing and services of cloud functions, such as authorization and authentication of system and database users.

Ekologiczny łańcuch dostaw: narzędzia do oceny E-odpadów – globalna perspektywa

When a company's supply chain has achieved a desirable degree of eco-friendliness in all regards, from a sustainability perspective, its performance will be satisfactory. Since the closed-loop e-waste supply chain's operations are primarily focused on achieving sustainability objectives related to the manufacturing, distribution, reusing, and discarding electrical components, it is crucial to evaluate its success in this area. In order to monitor the performance of supply chains and enhance the processes, the supply chain operations reference model offers suggestions and benchmarking tools. In this study, a conceptual framework is illustrated to show how these standards could be used in the E-waste supply chain to link business processes, metrics, industry standards, and technology in order to enhance the relationship and coordination between the supply chain members and to increase sustainability throughout the supply chain. Insufficient attention so far has been paid to the SCOR model's sustainability criteria, according to an assessment of the literature. Consequently, in the wake of portraying the structure of Supply Chain Operation Reference model, we make sense of which credits should be included in Supply Chain Operation Reference so to reflect manageability and which cycles and practices are related with every standard or should be remembered for Supply Chain Operation Reference to lay out the connection between execution, cycles, and practices.

How E-learning Is Correlated with Competitiveness and Innovation and Critical Success Factors

E-learning has gained a prominent role in the education scenario, either because of its capacity for extraterritorial coverage, or because of the scale it offers for free and academic courses. How e-learning is being managed and identifying opportunities for improvement in this process is a challenge for managers. A systematic review of the literature on e-learning was carried out from the perspective of process management. The Scimat and VOSviewer software were used together to make it possible to understand the volume of publications, terms, density, and perspectives of studies on the subject on the indexing platforms, as well as pointing out challenges and trends in the area. The term e-learning does not appear as a trend driver in published articles. When related to the terms critical success factors (CSFs) and competitiveness and innovation, the greatest concentration of articles is directed to the e-learning infrastructure or technologies applied to it. As a result, it is possible to observe that the co-occurrence of e-learning with critical success factors and competitiveness and innovation is in its early stages, with scarce research in this area indicating room for future growth. E-learning entails unique business metrics that require specific tools and knowledge of technology, concepts, and the organizational environment. However, there is a dearth of publications addressing these aspects and proposing relevant methodologies and processes.

Impact of Cloud-Based HR Systems on Business Performance Metrics

Human resource (HR) systems and cloud computing technologies have both become integral to modern businesses, and their fusion can have significant impacts on business metrics.
 The goal of this paper is to systematically study the impact of implementing cloud infrastructure on the Human Resource systems of an organization, leveraging which, an organization attains sustainable growth and thus helps the country in achieving its economic goals. 
 The study examines the impact of cloud-based HR systems on key business metrics such as employee productivity, turnover, and profitability. The paper also provides insights into the different phases of implementation, challenges, and benefits of implementing cloud-based HR systems apart from the conceptual framework of the study and offers recommendations for organizations considering adopting such systems.
 And further research can be done on risk issues associated with adopting cloud computing like data privacy (due to data breaches), Compliance issues.

Gamification as a Catalyst for Business Engagement: Insights from Case Studies and Technological Innovations

This paper provides an in-depth examination of the effectiveness of gamification techniques across various business functions, illustrating its transformative potential in today's competitive landscape. Gamification, defined as the integration of game-like elements—such as points, levels, rewards, and challenges—into non-gaming contexts, has gained significant traction as a tool for boosting engagement, motivation, and productivity among employees and customers alike. This study employs a comprehensive mixed-methods approach, drawing on qualitative interviews, extensive literature reviews, and detailed case study analyses to uncover the nuanced ways in which gamification strategies are applied within diverse industries. The findings aim to provide actionable insights into the mechanics of successful gamification implementations and offer a framework for organizations seeking to leverage these techniques to improve key business metrics. Furthermore, this paper explores the role of emerging technologies—specifically Augmented Reality (AR), Virtual Reality (VR), and Artificial Intelligence (AI)—in enhancing the gamification experience, pushing the boundaries of user interaction, personalization, and immersive engagement. The implications of this research highlight how gamification, when thoughtfully and ethically implemented, can become a powerful component of an organization’s strategy to foster sustainable engagement, support behavior change, and drive long-term productivity.

Neurophysiological markers of emotion regulation predict efficacy of entrepreneurship education

Recent evidence shows that programs targeting the socio-emotional dimensions of entrepreneurship—e.g., resilience, personal initiative, and empathy—are more highly correlated with success along with key business metrics, such as sales and survival, than programs with a narrow, technical bent—e.g., accounting and finance. We argue that programs designed to foster socio-emotional skills are effective in improving entrepreneurship outcomes because they improve the students’ ability to regulate their emotions. They enhance the individuals’ disposition to make more measured, rational decisions. We test this hypothesis studying a randomized controlled trial (RCT, RCT ID: AEARCTR-0000916) of an entrepreneurship program in Chile. We combine administrative data, surveys, and neuro-psychological data from lab-in-the-field measurements. A key methodological contribution of this study is the use of the electroencephalogram (EEG) to quantify the impact of emotional responses. We find that the program has a positive and significant impact on educational outcomes and, in line with the findings of other studies in the literature, we find no impact on self-reported measures of socio-emotional skills (e.g., grit and locus of control) and creativity. Our novel insight comes from the finding that the program has a significant impact on neurophysiological markers, decreasing arousal (a proxy of alertness), valence (a proxy for withdrawal from or approachability to an event or stimuli), and neuro-psychological changes to negative stimuli.

Economic Contribution Analysis of Urban and Community Forestry in the Southern United States in 2019

Abstract As populations in developing areas continue to increase in recent years, urban and community forestry (U&CF) has received considerable attention due to the ecological, social, and economic significance of trees and green landscapes in urban and semi-urban settings. Based on a regional survey of private, public, and nonprofit businesses and agencies involved in U&CF, we first developed a complete profile of the U&CF sector in the southern United States (SUS) and then estimated the economic contribution of U&CF businesses and activities to the thirteen-state regional economy. We estimated that, in 2019, U&CF in the SUS contributed about $23.2 billion in value added with a total jobs support of over 349,200. Based on the current economic contributions and the number of cities and towns in each state, we also categorized thirteen states into four different tiers. Results not only underscore the economic significance of U&CF businesses and activities in the SUS, but also serve as a baseline to track future trends and performance of U&CF in terms of various business metrics.

Financial institutions digital transformation: the stages of the journey and business metrics to follow

AbstractThis paper examines the stages of the digital transformational path that lies in front of incumbent banks in their conversion into digitally driven institutions and contributes by providing clarity in the parameters that define each stage and the key metrics to be tracked. It is a general review paper, with main tools employed the relevant scholar and grey literature & field observations. The paper identifies three phases for banking institutions’ digital transformation and proceeds with defining the characteristics of the phases and the distinct actions required for an institution to progress through them, employing a set of proposed key tracking indicators. The outcome adds to the, rather limited, academic literature on the subject and can be applied to all relevant banking institutions. Research needs further insides to articulate better the findings and expand them on a cross-examination of relevant theories and approaches. This paper aims at contributing to a growing, contemporary discussion, hopefully assisting in greater collaboration between practitioners and academics.