Organizational Decision Research Articles

Формирование цифровой модели угольного месторождения в горно-геологической информационной системе МАЙНФРЭЙМ

Digitalization of enterprise management using Russian software is the main trend in the development of the country's mining sector. Sharp fluctuations in demand and prices in the mineral markets, as well as the development of technical tools for mechanization and automation of technological processes along with a systematic increase in their cost affect the financial performance of mining companies. This determines the need for a rapid adoption of technical, technological and organizational decisions, which, along with the requirements of the company's owners and regulators to obtain prompt, reliable and the most complete information about the production process explains the urgent need for the prompt introduction of digital control systems for mining operations. In the article the authors describe an algorithm to design a digital model of the mining and geological system, including a digital geological model of the deposit, digital models of mine workings and the surface topography, based on the experience of creating three-dimensional digital models of complex-structured coal deposits. The basic software suite for designing a digital management system for mining operations is the MINEFRAME mining and geological information system developed at the Mining Institute of the Kola Scientific Center of the Russian Academy of Sciences. MINEFRAME allows to perform a full range of tasks aimed at creation of a digital 3D model of the mining and geological system for a coal deposit with the possibility to account for the complex bedding in the modelling. High accuracy and correctness of the input geological sampling data is achieved by means of tools to check for errors in the tables of borehole collar coordinates, inclinometry and sampling. The wireframe modelling methods implemented in MINEFRAME provide the possibility to create wireframe models of seams with high detail in the fracture zones.

Identifying and hierarchizing factors that affect the choice of transport routes in land ferry transport chains

Motives: The choice of a transport route has long been the subject of research because it is regarded as one of the most crucial decisions in transport organizations. However, there is a lack of studies addressing this issue in the context of land-ferry supply chains, where two transport modes have to be integrated. Therefore, analyses of multimodal transport should involve a holistic approach to account not only for seaborne transport, but also for the land leg before and after the ferry trip. This knowledge gap should be urgently addressed due to the importance of land-ferry supply chains in the transport system. Aim: The aim of this study was to identify and hierarchize factors that determine the choice of a multimodal transport route combining ferry and road transport. Results: The factors that determine the choice of ferry routes were identified and hierarchized according to their importance as primary, supplementary, and additional routes. The study demonstrated that the cost and time of transport are the main determinants in the decision-making process, with time being marginally more important than cost.

Leadership and its relationship to the effectiveness of decision-making in an economic organization

Leadership is the nexus between the human resources of an organisation and its future plans and visions. It is regarded as the crucible through which all administrative concepts and strategies are melted and interact, supporting the positive forces within the organisation and reducing the negative aspects to the greatest extent possible.

Is ChatGPT a source to enhance firms’ strategic value and business sustainability?

Purpose This study aims to investigate the effects of three dimensions of ChatGPT strategic value – organization support (OS), managerial productivity (IM) and decision aids (DA) – on the business sustainability (BS) of Malaysian public universities. Design/methodology/approach A quantitative methodology was adopted for this study to examine the relationships between ChatGPT strategic value and the BS of Malaysian public universities. Findings The study found that two dimensions of ChatGPT strategic value, namely, OS and IM, influence BS, whereas DA do not. Research limitations/implications To the best of the author’s knowledge, this study is the first to address the relationship between ChatGPT strategic value and BS in a specific context – Malaysian public universities – providing new contributions to theory by extending the literature on the topic. Practical implications The findings are expected to guide universities in Malaysia in leveraging ChatGPT strategic value for enhancing BS. Originality/value To the best of the author’s knowledge, this empirical study is the first in the literature to examine the relationships between ChatGPT strategic value and BS in the education sector. Supported by an original conceptual model, the insights provided should extend the literature dedicated to ChatGPT strategic value and BS in the context of a South Asian economy.

Developing a customised set of evidence-based quality indicators for measuring workplace violence towards healthcare workers: a modified Delphi method

BackgroundWorkplace violence (WPV) is a complex global challenge in healthcare that can only be addressed through a quality improvement initiative composed of a complex intervention. However, multiple WPV-specific quality indicators...

Multiple Pathways of Influence for Tightly and Loosely Structured Organizations: Implications for Systems Resilience

AbstractOrganizations play a key role in supporting various societal functions, ranging from environmental governance to the manufacturing of goods. The behaviors of organization are impacted by various influences, including information, technology, authority, economic leverage, historical experiences, and external factors, such as regulations. This paper introduces a generalized framework, focused on the relative structure of an organization (tight vs. loose), that can be used to understand how different influence pathways can impact decision‐making within differently structured organizations. This generalized framework is then translated into a modeling and simulation platform to support and assess implications of these structural differences in resilience to disinformation (measured by organizational behaviors of timeliness and inclusion of quality information) using a systems dynamics approach Preliminary results indicate that a tightly structured organization may be less timely at processing information but could be more resilient against using poor quality information in organizational decisions compared to a loosely structured organization. Ongoing work is underway to understand the robustness of these findings and to validate current model design activities with empirical insights.

Integrating Analytics in Enterprise Systems: A Systematic Literature Review of Impacts and Innovations

Recent advancements in Enterprise Information Systems (EISs) have transitioned from primarily supporting operational and tactical processes to enabling strategic decision-making through integrated analytics. This systematic review critically examines global literature from 2010 to 2023, focusing on the factors influencing the adoption of analytical components in EISs and assessing their impact on strategic decision-making in organizations. Following the PRISMA 2020 guidelines, we meticulously selected and reviewed articles from the Scopus database, employing a robust taxonomy based on the technology–organization–environment (TOE) framework to categorize findings. Our methodology involved a thorough screening of 234 studies, leading to a final analysis of 45 peer-reviewed articles that met our stringent criteria. These studies collectively underscore a significant gap in organizational capabilities, notably in the business ecosystems surrounding EISs, which hampers the effective adoption and utilization of advanced analytics. The results highlight a distinct need for improved understanding and implementation strategies for integrated analytics within EISs to enhance strategic decision-making processes. This review identifies critical factors for integrating analytics into Enterprise Information Systems (EISs), emphasizing technological, organizational, and environmental dimensions. It highlights a significant gap in models guiding ERP systems with Business Intelligence (BI) capabilities and underscores the need for robust research to enhance strategic decision-making through analytics.

A Hybrid Approach for Hierarchical Forecasting of Industrial Electricity Consumption in Brazil

The Brazilian industrial sector is the largest electricity consumer in the power system. Energy planning in this sector is important mainly due to its economic, social, and environmental impact. In this context, electricity consumption analysis and projections are highly relevant for the decision-making of the industrial sectorand organizations operating in the energy system. The electricity consumption data from the Brazilian industrial sector can be organized into a hierarchical structure composed of each geographic region (South, Southeast, Midwest, Northeast, and North) and their respective states. This work proposes a hybrid approach that incorporates the projections obtained by the exponential smoothing and Box–Jenkins models to obtain the hierarchical forecasting of electricity consumption in the Brazilian industrial sector. The proposed approach was compared with the bottom-up, top-down, and optimal combination approaches, which are widely used for time series hierarchical forecasting. The performance of the models was evaluated using the mean absolute percentage error (MAPE) and root mean squared error (RMSE) precision measures. The results indicate that the proposed hybrid approach can contribute to the projection and analysis of industrial sector electricity consumption in Brazil.

Dynamic adaptive decision support for strategic decision-making in healthcare organizations

PurposeThe main objective of this study was to design a dynamic adaptive decision support model for healthcare organizations facing deep uncertainties by considering promising dynamic adaptive approaches. The main argument for this is that healthcare organizations have to make strategic decisions under deep uncertainty, but lack an approach to deal with this.Design/methodology/approachA Dynamic Adaptive Decision Support model (DADS) is designed using the Design Science Research methodology. The evaluation of an initial model leads, through two case studies on ongoing and strategic decision-making, to the final design of this needed model for healthcare organizations.FindingsThe research reveals the relevance of the designed dynamic and adaptive tool to support strategic decision-making for healthcare organizations. The final design of DADS innovates Decision Making under Deep Uncertainty (DMDU) approaches in an organizational context for ongoing and strategic decision-making.Originality/valueThe designed model applies the Dynamic Adaptive Policy Pathways approach in an organizational context and more specifically in health care organizations. It further integrates Corporate Real Estate Management knowledge and experience to develop a most needed tool for decision-makers in healthcare. This is the first DADS designed for an organization facing deep uncertainties in a rapidly changing healthcare environment and dealing with ongoing and strategic decision-making.

Natural Experiments and Causation in Strategy Research

Research to inform organizational strategy decisions studies the impact of specific managerial decisions on performance. While links from decisions to outcomes can be convincingly identified in individual, specific circumstances, trying to do the same with a larger set of decisions and outcomes can be problematic. In a situation with a substantive sample, relying on standard metrics such as financial statements, the link to particular outcomes can be difficult to establish. Especially when trying to choose metrics not already correlated in some way. Our research is generally in the field of knowledge management (KM). The discipline has an extensive history of attempts to link better management of knowledge and other intangibles to performance outcomes. While the performance outcomes are fairly straightforward (financial success such as profitability or return on investment, innovation success, etc.), the metric for knowledge management is harder to pin down. The literature shows dozens of approaches. Some are for single firms or a small sample, but even if focusing only on metrics for a larger sample of firms, disagreement exists. But even when a KM metric is chosen for a larger sample, there is often a direct tie between input and output measures, making correlation difficult to establish, let alone causation. If profitability is part of both the input and output measures, of course they are correlated. The most advanced statistical techniques don’t establish anything more than what the researcher should already know from a cursory look at the logic of the study and the specifics of the variables. As a result, whether KM actually results in better organizational performance is still an open and much debated question in the field. One research approach that can get around this issue is the natural experiment. Pioneered by Nobel winner David Card and others, the natural experiment uses two measurements with a clear, consequential event separating the two—minimizing the impact of samples that might otherwise be connected contemporaneously. The event, such as a change in law, provides a change in circumstances delinking the measures. Whether structured as a pre/post experiment (measuring before or after the intervening event) or control/experimental group experiment (one group exposed to the event, the other not), the outcome can provide convincing results and can even suggest causation. This paper will cover our work with natural experiments in relation to KM and performance outcomes for merger and acquisition (M&A) activity. Can KM metrics before an M&A event predict the success of the event? Success can be defined by the change in financial performance after the event takes place.

Use of Oral and Emergency Contraceptives After the US Supreme Court’s Dobbs Decision

The US Supreme Court Dobbs v Jackson Women's Health Organization decision allowed states to strengthen restrictions on abortion access, triggering the closure of family planning clinics and leading to confusion about the legality of emergency contraceptives (ECs). To evaluate the association between the Dobbs decision and fills for oral and emergency contraceptives in states that enacted the most restrictive abortion policies after Dobbs. This cohort study used data on contraceptive fills for women of reproductive age (15-49 years) in the US from IQVIA's National Prescription Audit PayerTrak and data from the Guttmacher Institute were used to categorize changes in abortion restrictions in each state. A difference-in-differences analysis compared changes in monthly fill rates for daily oral contraceptive pills (OCPs) and ECs in states that became most restrictive (implemented a full abortion ban after Dobbs) and comparison states (kept a medium level of abortion restrictions after Dobbs) before (March 2021 to November 2021) and after (July 2022 to October 2023) the Dobbs decision. State-level abortion restrictions. Monthly fills of OCPs and ECs per 100 000 women of reproductive age. Between March 2021 and October 2023, 142.8 million prescriptions for OCPs and 904 269 prescriptions for ECs were dispensed at US retail pharmacies. Before Dobbs, trends in monthly fill rates were similar for OCPs and ECs between the most restrictive and comparison states. After the Dobbs decision, states that became the most restrictive experienced an additional 4.1% decline in OCP fills with 285.9 fewer fills per 100 000 (95% CI, -495.8 to -6.8; P = .04). In contrast to OCPs, fills for ECs increased during the first year after Dobbs (July 2022 to June 2023) in both groups of states. However, 1 year after Dobbs (July 2023 to October 2023), the most restrictive states experienced an additional 65% decrease in emergency contraceptive fills with 13.2 fewer fills per 100 000 (95% CI, -27.2 to -4.1; P = .01). In this cohort study of prescriptions filled at US pharmacies, the Dobbs decision was associated with declines in oral contraceptives, particularly ECs, in states enacting the most restrictive abortion policies. Given the important role of OCPs and ECs in preventing pregnancy and the need for abortion, efforts to improve access may be needed, especially in states where legal abortion is no longer an option.

The emergence and organizational choices of patient advocacy associations: Evidence from the Italian context.

Within many advanced healthcare systems, patient advocacy associations are gaining a more relevant role in healthcare policy decisions. These associations provide help, representation, and voice to patients and citizens. However, although their role is important, a paucity of research exists analyzing their foundation dynamics, including their organizational decision, from a managerial perspective. To fill this knowledge gap, we formulated two research questions to investigate the motivations underlying the foundation of patient advocacy associations and the institutional pressures influencing the changes that have occurred in these associations throughout their evolution. Using a semi-structured questionnaire developed as part of a larger research project, we collected data about 31 patient advocacy associations operating within the Italian National Health Service. We employed qualitative analysis to examine the associations' birth and evolution as well as the motivations and influences driving change within the sampled organizations. Questionnaire responses provided information about the patient advocacy associations' histories and highlighted their close links with the Italian National Health Service. Our results indicated the motivations for the associations' establishment could be grouped into five categories: support at the system level, patient protection and support, actions to increase awareness, actions for improving patients' health and quality of life, and dissemination of knowledge. We also identified the frequency and nature of the changes within the associations and explored the institutional pressures that influenced these organizational changes. The results can be interpreted considering the organizational theories that focus on organizations' establishment decisions and how external pressures impact organizations' dynamics and evolution.

Accounting Information System and Environmental Uncertainty among Agri-Related Cooperatives in Davao del Norte

The primary purpose of this study was to explore the relationship between the variables covered in this study - the Accounting Information System and environmental uncertainty among agri-related cooperatives- and provide personal knowledge and a framework for the contingency theory. The research advocates that most entities need to modernize their business operations due to the emergence of technological advances to support organizational change and decision-making. The study's findings aim to benefit agri-related cooperatives, such as the Board of Directors, the Management, the Entrepreneurs, and future researchers seeking insights. The study focused on agri-related cooperatives in Davao del Norte, targeting accountants or bookkeepers. The selection of respondents was made in a complete enumeration involving seventy-four (74) respondents for the survey as per the data provided by the Cooperative Development Authority. The methodology aims for more reliable insights into the Accounting Information System and environmental uncertainty representing the agri-related cooperative sector. The findings indicate that adequately using a reliable Accounting Information System helps businesses deal with uncertainties. However, the greater the likelihood of environmental uncertainty, the greater the possibility that the Accounting Information System is unlikely to capture operational issues useful for decision-making. Thus, this study concludes that the Agri-related cooperatives in Davao del Norte are highly uncertain, and the usage of the Accounting Information system did not significantly affect the decision-making process.

Poverty Governance in the Delegated Welfare State: Privatization, Commodification, and the U.S. Health Care Safety Net

Abstract Due to forces of retrenchment and fiscal austerity in the contemporary U.S. welfare state, the federal government has increasingly delegated the funding of public programs to private entities. How does privatization influence the way marginalized populations experience the social safety net? To develop insights on delegated poverty governance, this study examines a longstanding public-private program—Federally Qualified Health Centers (FQHCs)—which comprise a nationwide network of clinics serving over thirty million predominantly low-income patients in medically underserved areas. I conducted a case study drawing on in-depth interviews with patients and staff in a small-town FQHC in the Rust Belt. Unlike other social welfare programs, I found a pronounced absence of stigma associated with the FQHC, largely due to features of the delegated policy design, the blended institutional setting, and strategic organizational decisions. However, low-income patients were also unaware of their rights to treatment when encountering paternalistic enforcement of overdue billing rules, which resulted in delayed or foregone health care. Due to underlying tensions surrounding commodification, I argue that privatization of the safety net may quell the stigma of government programs among the poor while simultaneously disentitling individuals from their rights of social citizenship.

The role of relationship marketing in the consumer purchase decision An exploratory study of the opinions of a sample of customers of Golden Mall in the city of Mosul

The current research aims to explain the impact of relationship marketing on consumers' purchasing decisions because of the great importance of relationship marketing in attracting new customers and the retention of the current ones .The customers of Golden Mall in Mosul city were selected as samples of the research. Questionnaire forms have been randomly given to 120 Golden Mall customers for data collection. The researcher has used the ready-made statistical software package (SPSS V26) to analyze the impact and correlation relationships between the research variables .After the statistical analysis, the research has found out that relationship marketing has great impact on and effective role in enhancing the consumers' purchasing decisions in business organizations. The results have also shown that there is a correlation between relationship marketing and consumers' purchasing decisions which means that adopting relationship marketing can greatly contribute in directing the customers' decisions to depend on the company's services. Within that framework, a number of recommendations have been suggested. One of the most important recommendations is the necessity of enhancing the dimensions of relationship marketing in the sample of this research for its vital role in consolidating the purchasing decisions of the customers.

The role of data science and data analytics for innovation: a literature review

ABSTRACT Data science and data analytics (DS/DA) have been quickly adopted by decision-makers in organisations. Their relation to specific functions within organisations, however, remain unclear. Therefore, this study focuses on their relationship to innovation and aim to clarify the role of DS/DA relative to innovation and decision-making. To this end, we conducted a literature review. Based on a systematic query in the Web of Science, we identified 172 relevant articles, which address DS/DA and innovation. Our findings suggest a prevalence of different understandings of DS/DA relative to innovation and decision-making. Specifically, we identified three distinct categories of articles: (1) “Innovation as a result of DS/DA”, (2) “DS/DA as a result of innovation”, (3) “Diffusion of DS/DA technology”, and sorted the remaining in a fourth category “Miscellaneous”. Our study contributes to the understanding of DS/DA and its ambiguous relationship to innovation and decision-making. We outline implications for academics, practitioners, and educators.

Assessment of quality indicators in construction

Introduction. Ensuring proper quality of construction is one of the pressing challenges of our time. Consumers expect cheap products from developers in the form of commercial or residential real estate that meet all the required quality indicators. Most accidents in monolithic construction occur due to non-compliance with technological procedures at low temperatures. The purpose of the study is to develop a framework for assessing the quality of concrete work at subzero temperatures (during winter work) based on the results of studies of technological parameters of winter concreting, their impact on the quality and safety of erected monolithic structures of industrial and civil buildings (structures).Materials and methods. The study used the method of approximating distributions of random variables, expert estimates, the theory of multiple principles, and mathematical statistics. The experiments were carried out in the laboratories of the Don State Technical University, as well as in the conditions of actual concrete work on a construction site in winter. The work uses a correlation-regression analysis of the dependence of the organizational and technological causes of inconsistencies (factors) and quality indicators of concrete work production. Statistical information on structural damage and collapse of buildings during their operation was processed. To make organizational and technological decisions to improve the quality of concrete work, it is proposed to take the influence of defects on the load-bearing capacity of buildings as an indicator of the quality level.Results. Using practical and expert methods, the most significant reasons (factors) for the occurrence of inconsistencies in the level of quality of concrete work production have been established. Factors have been identified that have the greatest influence on the change in the load-bearing capacity and reliability of buildings and structures being erected when performing the main types of construction and installation work. The nomenclature of technological quality indicators during winter production of concrete work, their influence on quality substantiated, and methods for assessing the quality of winter concreting technology are developed. Quantitative indicators of the quality of construction of monolithic reinforced concrete structures were obtained.Discussion and conclusions. The practical value of the work lies in the development of a methodological tool for creating a regulatory framework for operational construction control of the production of monolithic and prefabricated monolithic construction and installation works under conditions of exposure to low temperatures, as well as for acceptance control of compliance of completed construction projects with quality requirements. Proposals are given for establishing regulatory tolerances, ways to improve the manufacturability of the equipment used, a new method for designing winter concreting technology, and a quality control method focused on ensuring structural safety have been developed. By developing the research, it is further possible to develop methods for calculating technology parameters taking into account technological variability, as well as establish new indicators to regulate the required level of quality and safety of buildings being built.

Developing a framework for understanding policy decision-making behaviors in the transition of an HIV prevention program towards sustainability: a case study from Zambia’s voluntary medical male circumcision program

Faced with declining donor funding for HIV, low- and middle-income countries must identify efficient and cost-effective ways to integrate HIV prevention programs into public health systems for long-term sustainability. In Zambia, donor support to the voluntary medical male circumcision (VMMC) program, which previously funded non-governmental organizations as implementing partners, is increasingly being directed through government structures instead. We developed a framework to understand how the behaviors of individual decision-makers within the government could be barriers to this transition. We interviewed key stakeholders from the national, provincial, and district levels of the Ministry of Health, and from donors and partners funding and implementing Zambia’s VMMC program, exploring the decisions required to attain a sustainable VMMC program and the behavioral dynamics involved at personal and institutional levels. Using pattern identification and theme matching to analyze the content of the responses, we derived three core decision-making phases in the transition to a sustainable VMMC program: 1) developing an alternative funding strategy, 2) developing a policy for early-infant (0–2 months) and early-adolescent (15–17 years) male circumcision, which is crucial to sustainable HIV prevention; and 3) identifying integrated and efficient implementation models. We formulated a framework showing how, in each phase, a range of behavioral dynamics can form barriers that hinder effective decision-making among stakeholders at the same level (e.g., national ministries and donors) or across levels (e.g., national, provincial and district). Our research methodology and the resulting framework offer a systematic approach for in-depth investigations into organizational decision-making in public health programs, as well as development programs beyond VMMC and HIV prevention. It provides the insights necessary to map organizational development and policy-making transition plans to sustainability, by explaining tangible factors such as organizational processes and systems, as well as intangibles such as the behaviors of policymakers and institutional actors.

“Nudging towards excellence: Harnessing behavioral insights for organizational learning”

Purpose In dynamic business environments, organizations must constantly adapt and learn. Nudging, a concept from behavioral economics, offers a novel approach to influence organizational behavior and learning. This article explores the integration of nudging within organizational learning, drawing from Thaler and Sunstein’s work and organizational learning theories. Also, To investigate nudging’s role in organizational learning and propose a practical nudging framework, while addressing ethical considerations. Design/methodology/approach The article combines theoretical insights from behavioral economics (Thaler and Sunstein; Kahneman) with organizational learning theories (Argyris and Schön). It discusses real-world nudging applications, like Google's health initiatives, and examines the ethical aspects of workplace nudging. Findings Nudging effectively influences organizational decisions and strategies by targeting rapid cognitive processes. It finds application in training, performance management, and decision-making, with a critical focus on ethical implications, especially regarding autonomy and non-manipulation. Research limitations/implications This study highlights the potential of behavioral economics in reshaping organizational learning, emphasizing the importance of ethical application in developing adaptive, learning-focused organizational cultures. Originality/value Nudging offers a promising method for enhancing organizational learning. Applied ethically, it can improve workforce engagement, performance, and adaptability. Future research should focus on nudging's long-term organizational impacts and ethical boundaries.

Artificial intelligence capability and organizational performance: unraveling the mediating mechanisms of decision-making processes

PurposeThis study investigates the profound impact of artificial intelligence (AI) capabilities on decision-making processes and organizational performance, addressing a crucial gap in the literature by exploring the mediating role of decision-making speed and quality.Design/methodology/approachDrawing upon resource-based theory and prior research, this study constructs a comprehensive model and hypotheses to illuminate the influence of AI capabilities within organizations on decision-making speed, decision quality, and, ultimately, organizational performance. A dataset comprising 230 responses from diverse organizations forms the basis of the analysis, with the study employing a partial least squares structural equation model (PLS-SEM) for robust data examination.FindingsThe results demonstrate the pivotal role of AI capabilities in shaping organizational decision-making processes and performance. AI capability significantly and positively affects decision-making speed, decision quality, and overall organizational performance. Notably, decision-making speed is a critical factor contributing significantly to enhanced organizational performance. The study further uncovered partial mediation effects, suggesting that decision-making processes partially mediate the relationship between AI capabilities and organizational performance through decision-making speed.Originality/valueThis study contributes to the existing body of literature by providing empirical evidence of the multifaceted impact of AI capabilities on organizational decision-making and performance. Elucidating the mediating role of decision-making processes advances our understanding of the complex mechanisms through which AI capabilities drive organizational success.