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Journal of Operational and Strategic Analytics
JISC
Journal of Operational and Strategic Analytics (JOSA)
JOTE
ISSN (print): 2959-0094
ISSN (online): 2959-0108
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2023: Vol. 1
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Journal of Operational and Strategic Analytics (JOSA) is a distinguished academic journal, specializing in operational and strategic analytics. It uniquely bridges rigorous academic research with practical applications, making it a valuable resource for both scholars and industry practitioners. JOSA covers a diverse range of topics, including data analysis, strategic decision-making processes, and the application of analytics in various organizational contexts. The journal is particularly noted for its exploration of how emerging technologies like artificial intelligence and machine learning are influencing strategic analytics. This focus not only provides insights into current trends but also into future challenges and opportunities in the field. Published quarterly by Acadlore, the journal typically releases its four issues in March, June, September, and December each year.

  • Professional Service - Every article submitted undergoes an intensive yet swift peer review and editing process, adhering to the highest publication standards.

  • Prompt Publication - Thanks to our proficiency in orchestrating the peer-review, editing, and production processes, all accepted articles see rapid publication.

  • Open Access - Every published article is instantly accessible to a global readership, allowing for uninhibited sharing across various platforms at any time.

Editor(s)-in-chief(1)
seyyed ahmad edalatpanah
Ayandegan Institute of Higher Education, Iran
s.a.edalatpanah@aihe.ac.ir | website
Research interests: Mathematical Programming; Operational Research; Numerical Modeling; Strategic Analytics; Decision Support Systems; Uncertainty Theories; Soft Computing

Aims & Scope

Aims

Journal of Operational and Strategic Analytics (JOSA) is a premier open-access journal that specializes in data-driven analysis and decision-making in the fields of statistics, computer programming, and operations research. Its mission is to enhance theoretical and practical understanding of problem-solving in various contexts, including individual, business, organizational, governmental, and societal levels. JOSA welcomes diverse submissions like reviews, research papers, and short communications, including Special Issues on specific topics. The journal is distinct for its comprehensive approach, offering insights into the application of analytics across various organizations and entities.

JOSA encourages in-depth publication of both theoretical and experimental results, with no constraints on paper length to ensure detailed and reproducible findings. Unique features of the journal include:

  • Every publication benefits from prominent indexing, ensuring widespread recognition.

  • A distinguished editorial team upholds unparalleled quality and broad appeal.

  • Seamless online discoverability of each article maximizes its global reach.

  • An author-centric and transparent publication process enhances submission experience.

Scope

JOSA offers a broad and comprehensive scope that distinctively positions it within the academic community, encompassing a wide array of topics in operational and strategic analytics:

  • Operational and Strategic Analysis: Exploring advanced methodologies in operational research and strategic analytics, focusing on optimizing business processes and decision-making strategies.

  • Strategic Planning and Management: Covering aspects of strategic planning, including formulation, implementation, and evaluation within various organizational contexts.

  • Business Analytics and Management: Delving into the application of analytics in business management, including performance analysis, market trends, and consumer behavior.

  • Problem Structuring Methods (PSMs): Investigating methodologies for identifying, structuring, and analyzing complex decision-making scenarios in organizational settings.

  • Knowledge and Information Management: Focusing on effective management of knowledge resources and information systems in organizations to enhance decision-making and strategic planning.

  • Decision Analytics and Systems: Examining systems and tools designed to improve the quality and efficiency of decision-making processes in businesses and organizations.

  • Data-Driven Analysis: Emphasizing the role of data in quantitative and qualitative analysis to guide operational and strategic decisions.

  • Digitalizing and Emerging Technologies: Exploring the impact of digital transformation and emerging technologies like AI, IoT, and blockchain on operational and strategic planning.

  • Accounting and Quantitative Finance: Applying quantitative methods to accounting and financial decision-making, including risk assessment, investment analysis, and financial modeling.

  • Health and Tourism Management: Investigating the application of operational and strategic analytics in the health and tourism sectors, focusing on improving service delivery and customer satisfaction.

  • Project and Risk Management: Covering the principles and practices of effective project management and risk mitigation strategies in various industries.

  • Complexity and Uncertainty Management: Addressing methods for managing complexity and uncertainty in business operations and strategic planning.

  • Performance Efficiency: Analyzing strategies and tools for enhancing organizational performance, productivity, and operational efficiency.

  • Innovative Applications of Decision Science: Showcasing novel applications of decision science in emerging areas and new themes, expanding the boundaries of operational and strategic analytics.

Articles
Recent Articles
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Open Access
Research article
Strategic Application of Cooperative Game Theory in Mitigating Labor Shortages in Post-Pandemic Logistics: A Case Study of Poland
eric munyeshuri ,
lilian kuyiena song ,
john ayieko akoko ,
janet awino okello ,
killian yuh nfu
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Available online: 12-30-2023

Abstract

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The onset of the global pandemic has underscored the pivotal role of logistics, bolstered by information and communication technologies, in the resilience of supply chain networks. This study investigates the transformative impact of the COVID-19 pandemic on these networks, with a focus on the resultant operational challenges and labor shortages experienced in Poland – a critical hub in European supply chains. The research delves into how cooperative game theory can be strategically applied to address workforce deficits, particularly in sectors vital to Poland's economy, such as food and healthcare. In the context of reduced operations triggered by illness, fatalities, and preventive measures, including travel restrictions, this study elucidates the operational dynamics within supply chain networks through game theory frameworks. It scrutinizes the strategies implemented by major corporations, including Amazon, DHL, Post Office, KFC, and McDonald's, to navigate these challenges. The methodology encompasses an analysis of the network structure of supply chain game theory, tailored to the operational confines of Poland's logistics sector, acknowledging its role as Europe's breadbasket. The findings reveal various approaches to counteract labor shortages exacerbated by the pandemic, drawing parallels with similar challenges in regions like Africa, Asia, Ukraine, Turkey, and India. The study highlights the diverse impacts of workforce disruptions on commodity prices and the revenues of logistics companies within the supply network economy. These insights contribute to a broader understanding of the financial and operational implications of cooperative game theory in the context of global health emergencies. Conclusively, this research augments existing literature by demonstrating the applicability of cooperative game theory in addressing labor shortages under pandemic-induced constraints. It presents a comprehensive analysis of the strategies employed by key players in the logistics sector, offering valuable perspectives on mitigating operational disruptions in times of crisis.

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In the context of the free trade port initiative, an in-depth investigation into the pricing strategies of Hainan's travel agencies was conducted, focusing on the pivotal role of customer value. This study employed empirical analytical methods, including questionnaire surveys and data analysis, to rigorously test hypotheses related to customer value-oriented pricing strategies. It was discovered that customers exhibit a predominant preference for pricing strategies anchored in their value perceptions, notwithstanding the variations in their assessments of diverse tourism products. Strategies grounded in customer value were found to be more effective in fulfilling customer requirements and augmenting satisfaction levels. The research accentuates the crucial importance of aligning pricing strategies with customer value in the context of tourism product pricing. This approach holds significant theoretical relevance and practical utility for the evolution of Hainan's tourism industry. The findings offer fresh perspectives and strategic directions for the tourism sector in Hainan, contributing to its sustainable growth and the enhancement of its competitive stature.

Abstract

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Reducing the devastating effects of earthquakes is the main objective of planning for earthquake response. The decision-making process is essential to this attempt. However, it is particularly difficult because of the inherent uncertainties. A sophisticated methodological approach was proposed to handle these uncertainties in this study. The approach makes use of Fermatean probabilistic hesitant fuzzy sets (FePHFSs), and emphasizes the resilience of algebraic operations and their crucial role in improving the effectiveness of decision-making. In particular, a noteworthy development in the field of multiple attribute decision making (MADM) is the introduction of novel probabilistic hesitant fuzzy sets (PHFSs) aggregation operators, which are created by carefully synthesizing algebraic operations with the Combined Compromise Solution (CoCoSo) method. A key component of this technique is the application of the CoCoSo strategy, which is well known for its resilience in optimal goal selection and uses various aggregation strategies to effectively navigate the complex, multicriteria decision-making environment. A thorough numerical case study illustrates the adaptability and efficacy of this method and highlights its potential in practical settings. Decision-makers now have a new and effective tool that helps them make better informed and trustworthy decisions even in the face of uncertainty by combining PHFS with the CoCoSo technique. This method offers real-world implications for improving disaster response plans in addition to advancing the theory of decision support systems.

Abstract

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In the realm of managerial decision-making, particularly within the last few decades, the process has emerged as a formidable challenge. This paper focuses on strategic decision-making, crucial in determining organizational success or failure amidst prevailing uncertainties. To address this, the Matrix Approach to Robustness Analysis (MARA), a recent innovation, is integrated with the established Strengths-Weaknesses-Opportunities-Threats (SWOT) matrix. This integration aims to deliver robust outcomes in strategic planning for travel agencies. The methodology involves a comprehensive analysis of internal and external factors pertinent to a travel agency, applying the analytical rigor of the SWOT matrix. Subsequent to this analysis, a series of strategies are formulated. Central to this study is the identification of key environmental indicators, as perceived by stakeholders, which influence strategic outcomes. Through these indicators, various future scenarios are constructed, culminating in nineteen plausible scenarios. Each strategy, totalling twelve, is then evaluated against these scenarios to ascertain the conditions under which they are most effective, resulting in a performance matrix. The final phase involves calculating the robustness analysis scores for each strategy under two different assessment conditions: rigorous and lenient. These scores provide a basis for strategy prioritization in both scenarios. The analysis reveals that the strategy of expanding new pilgrimage tours holds the greatest promise, while the employment of relatives within the agency is deemed least effective. This study contributes to the field by offering a structured methodology for travel agencies to navigate uncertain environments, using a combination of MARA and SWOT. The findings underscore the importance of scenario-based strategic planning and robustness analysis in enhancing decision-making processes.
Open Access
Research article
Interplay of Cryptocurrencies with Financial and Social Media Indicators: An Entropy-Weighted Neural-MADM Approach
jéfferson augusto colombo ,
tanzina akhter ,
peter wanke ,
md. abul kalam azad ,
yong tan ,
seyyed a. edalatpanah ,
jorge antunes
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Available online: 12-03-2023

Abstract

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In the rapidly evolving domain of digital finance, the interplay between cryptocurrencies and external variables such as financial and social media indicators warrants thorough examination. This investigation employs a novel, entropy-weighted Multiple Attribute Decision Making (MADM) model to decipher these intricate relationships. The study's foundation is an expansive dataset, meticulously compiled to encompass a broad spectrum of financial data alongside diverse social media indicators. Central to this analysis is the employment of the Stepwise Weight Assessment Ratio Analysis (SWARA) method, meticulously applied to ascertain the relative importance of various social media indicators. Complementing this, the Complex Proportional Assessment (COPRAS) methodology is adeptly utilized to derive utility functions for each cryptocurrency under scrutiny. The analytical prowess of neural network regressions is harnessed to delineate the influence exerted by a multitude of financial indicators on these utility functions. The findings of this research are pivotal in understanding the dynamics within the cryptocurrency market. Bitcoin and Ripple emerge as pivotal entities, primarily functioning as primary conduits for market shocks. In contrast, Ethereum is identified as a stabilizing force, predominantly absorbing such fluctuations. A nuanced aspect of this study is the differential impact of social media indicators on various cryptocurrencies. Bitcoin and Ethereum display a negative correlation with these indicators, suggesting a complex, possibly inverse relationship with social media dynamics. Conversely, Litecoin, Dogecoin, and Ripple exhibit a positive responsiveness, indicating a heightened susceptibility to social media attention, sentiment, and prevailing uncertainty.

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The imperatives of occupational health and safety (OHS) are increasingly recognised as critical components of business operations, particularly within logistics where manual tasks such as item picking and transportation present notable hazards. This study employs the Fine-Kinney method to conduct a risk analysis of internal transport activities in logistics systems. Hazards associated with various internal transport mediums are systematically identified and categorised. An illustrative case study involves a logistics provider based in Serbia, scrutinising the risks prevalent within warehouse operations. Through application of the Fine-Kinney method, the analysis determines the predominant risk to be collisions involving pedestrians. In response, the study advocates targeted preventive and corrective strategies to diminish these risks. Theoretical and practical contributions arise from addressing these identified risks, offering valuable insights for logistics enterprises. The emphasis on preemptive safety measures underscores their significance in safeguarding worker welfare and enhancing the efficiency of logistics operations.

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In the quest to reduce occupational accidents and diseases, the ergonomic performance levels of industries remain pivotal. Within this context, the metal industry in Türkiye, notorious for ergonomic challenges, was scrutinised regarding its occupational health and safety (OHS) indicators. Five pivotal criteria were employed to delineate the industry's performance: the incidence of occupational accidents, the occurrence of fatal occupational accidents, the reporting rate of occupational diseases, the cumulative days of temporary incapacity, and the overall count of insured individuals obtaining permanent incapacity benefits. A decadal period, spanning 2013-2022, served as the temporal backdrop for this examination. Utilising the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, an esteemed Multiple-Criteria Decision-Making (MCDM) technique, an assessment was conducted to ascertain the years marred by sub-optimal ergonomic performance. Notably, 2014, 2013, and 2020 were identified as the least problematic years, whereas 2022 emerged as the most critical year. This investigation underscores the imperative for strategic planning to augment ergonomic conditions in professional settings in light of OHS, particularly in recent times.

Abstract

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In the rapidly evolving industrial landscape, the decision-making process concerning which products to manufacture, their quantity, and the methods of their production has become pivotal. This study endeavors to address this need by advocating the most apt functional form of the production process for predominant manufacturing sectors. The central objective has been the maximization of output through the application of the Cobb-Douglas production function, investigated separately for both two-input and three-input scenarios. It is ascertained which of the two models exhibits greater efficacy. Subsequently, parameters of the production function are estimated utilizing advanced optimization subroutines.

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Ordering of quotients is a critical aspect of cost-efficiency problems, which hold significant interest and importance for suppliers of goods and services as well as consumers. Comparisons (ordering) are straightforward when dealing with ordinary numbers, yet in many instances, the data are imprecise, vague, or subject to seasonal variations. Consequently, such data may be unknown or derive from expert opinions. Unlike ordinary numbers, fuzzy data render quotients only partially ordered. This study examines the linear ordering of quotients with fuzzy data, expressed in terms of confidence intervals, $\alpha$-cuts, or piecewise quadratic fuzzy numbers (PQFNs), within the context of cost-efficiency problems. Moreover, the challenges associated with quotient ordering in cost-efficiency problems are introduced.

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Investigation into the nexus between financial crises and the current account deficit within Iran’s economy was conducted, utilising time-series data spanning from 1989 to 2022. Augmented Dickey-Fuller (ADF) test validations endorsed stationarity of all variables upon first differencing. Through the deployment of Johansen's cointegration methodology, a long-term positive impact of real exchange rate oscillations on the trade deficit was discerned. Furthermore, the implementation of an error correction model (ECM) furnished additional perspectives regarding the dynamic interplay amongst the variables under consideration. The findings elucidate the repercussions of financial crises on Iran’s current account deficit, revealing a palpable influence of exchange rate volatilities on economic stability and providing insights into the nuanced macroeconomic relationships amidst periods of fiscal turmoil. The research underscores the exigency for robust fiscal and monetary strategies to navigate the intricacies of economic vulnerabilities and fortify against ensuing financial perturbations.

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IT, increasingly recognized as a vital contributor to competitive advantage, plays an indispensable role in augmenting business value. Effective implementation of IT Governance (ITG) mechanisms, comprising structures of responsibility, control processes, communication protocols, and decision rights, has been found to foster alignment between IT and business objectives. Such alignment is particularly critical for Small and Medium-sized Enterprises (SMEs), where the amplified business value can be realized. Yet, SMEs often grapple with challenges in implementing ITG, owing to resource constraints, communication hurdles, resistance to change, and technological complexity. The present study delves into this complex dynamic within a medium-sized industry located in southern Minas Gerais, Brazil, investigating the deployment of ITG mechanisms as a means to enhance business value through IT. An interpretivist approach characterizes the qualitative, inductive study, drawing on a case study to probe the links between ITG mechanisms, IT capabilities, and business value. Four hypotheses are put forth in the discourse, shedding light on the intricate relationships that these elements share. The findings indicate that ITG mechanisms exert a positive impact on IT business value, albeit with identifiable weaknesses and potential areas for enhancement. More effective alignment between IT and business can be achieved by addressing these shortcomings, thereby mitigating risks such as demotivation among IT professionals and resistance to change.

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This study emphasizes the limitations observed in the prevailing neutrosophic AHP group decision-making model. To address these limitations, an augmented neutrosophic AHP group decision-making model has been established, leveraging the potential of neutrosophic trapezoidal numbers. A comprehensive exploration of a key property of the neutrosophic trapezoidal pairwise comparison matrix is performed in this research, revealing that the current model inadequately maintains the reciprocal property of the neutrosophic trapezoidal pairwise comparison matrix. A real-world decision-making problem is resolved utilizing the introduced model, and a comparative analysis is furnished between the pre-existing neutrosophic AHP group decision-making model and the revised version. The results unequivocally demonstrate the superiority of the enhanced model.

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The prevalence of decision-making methodologies catering to quantitative attributes considerably overshadows those designed for qualitative attributes. This study seeks to address this gap by extending the traditional Ideal Solutions with Constraint on Values (ISOCOV) method to a fuzzy environment, thereby enhancing its capability to handle optimal decision-making based on qualitative attributes. In this improved method, $\alpha$-cut representations are employed for managing linguistic value constraints in performance-oriented data. The proposed approach is then utilized for the selection of nanomaterials, evaluated based on five essential criteria. By subjecting the performance-based decision matrix to the modified fuzzy method, a ranking of alternatives is derived. Compared to its traditional counterpart, this fuzzy-enhanced ISOCOV method demonstrates enhanced efficiency in processing qualitative data, promising its potential compatibility and utility for decision makers dealing with performance-oriented decision-making.

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The prevalent economic principle of weak disposability has been the foundation for studies in environmental assessment using Data Envelopment Analysis (DEA). Recently, a shift from classical free disposability to weak disposability has been observed as an emerging trend for treating undesirable factors in research. Weak disposability is perceived to have significant analytical power in measuring the efficiency of Decision-Making Units (DMUs). Addressing the increment of undesirable inputs, a non-radial model grounded on a non-uniform augment factor is presented. The application of this proposed model anticipates a suitable quantity for the increment of undesirable inputs. Concurrently, the model ensures a corresponding reduction in desirable inputs. Numerical instances illuminate the practicality and robustness of the proposed model and demonstrate its superior performance over its original counterpart.

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