Research Decisions Research Articles

The Role of Marketing Research in Managerial Decision–making: A case study of Harare-based Food–Manufacturing Organisations in Zimbabwe

In recent years, a market oriented organisational culture has increasingly been considered a key element of superior organisational performance. Marketing research has an integrative marketing function of helping ensure that all departments in an organisation work together towards consumer satisfaction. The study sought to investigate the role of marketing research in managerial decision-making in Harare-based food manufacturing organisations. The investigation employed a quantitative research design. The research population comprised all marketing managers in Harare-based Food–manufacturing organisations. The population had a total of 19 organisations, 6 of which did not have marketing managers in post. This reduced the population to 13. Using a simple random sampling procedure, 10 marketing managers were randomly selected to participate in the research. Data were collected through a structured questionnaire with both open-ended and closed-ended questions, in which marketing managers indicated their views on the key roles of marketing research in managerial decision-making in Harare-based Food–manufacturing organisations. Marketing managers perceived and were in agreement that the role of providing information that can be used in facilitating making informed, quality marketing decisions was central to marketing research. Findings revealed that key roles of marketing research in managerial decision-making included roles in aiding satisfaction of consumer needs and wants; market segmentation; targeting and positioning; identifying and assessing threats from environmental forces. Given the central role of marketing and marketing research in managerial decision-making, organisations in the food-manufacturing industry are urged to adopt a market-led approach and achieve market leadership through superiority in aiding satisfaction of customer needs and wants through a co-ordinated set of activities that enhance attainment of organisational goals and strategic objectives.

530 Understanding Strengths and Weaknesses of Clinical Research Operations in Regional Settings

OBJECTIVES/GOALS: An environmental scansoughtto understand research processes, areas for improvement, and opportunities for collaborative quality improvement (QI)across the Northwest Participant and Clinical Interactions Network (NW PCI). METHODS/STUDY POPULATION: NW PCI site champions were invited for semi-structured single and group Zoom-based interviews. Interviewers asked participants about local research processes, strengths and weaknesses, existing infrastructure to support QI, and interest in collaborative QI across the Network. Audio transcripts were coded using Dedoose and analyzed with deductive and inductive coding. RESULTS/ANTICIPATED RESULTS: Between February and April 2023, 10 interviews collected data from 7 research decision makers and 7 staff members across 7 sites. Most participants (n=13, 92%) agreed the diagram shown during the interview was representative of the local process. Organizations consistently identified strengths and weaknesses within the domains of study start-up, recruitment, budgets, and compliance. QI infrastructure was inconsistent (n=5, 36%) and all (n=14, 100%) saw potential for success in multisite QI initiatives to enhance efficiency. DISCUSSION/SIGNIFICANCE: NW PCI sites use similar processes, share common strengths and weaknesses, and universally reported interest in collaborating on QI. Study startup was reported as both a strength and weakness within the same organization, requiring unpacking of key elements before pursuing QI initiatives.

Multi-attribute decision-making research on investment suitability assessment of hydropower-wind-photovoltaic-storage complementary system based on dynamic social network

The hydropower-wind-photovoltaic-storage (HWPS) complementary system is one of the essential ways for China to build a new type of power system and to realize the dual-carbon goal. However, China's HWPS complementary system is still in the exploratory stage, and it is important to propose a rational multi-attribute decision-making (MADM) framework for investment suitability assessment based on completed hydropower plants. Therefore, this study first established a limitation indicator system for preliminary screening hydropower plants and an HWPS investment suitability assessment indicator system containing six dimensions: nature, market, infrastructure, land, society, and environment. Second, the weights among experts were determined based on the dynamic social network, and a mechanism for updating expert weights was proposed. Again, triangular intuitionistic fuzzy number (TIFN) was used to quantify the qualitative indicators and combined the weights according to the best-worst method (BWM) and criteria importance through intercriteria correlation (CRITIC) methods. Finally, the TODIM (an acronym in Portuguese for interactive and MADM) method was used for scheme suitability assessment with sensitivity analysis and method comparison. The results show that 62 eligible hydropower plants were preliminarily screened out of 647 completed medium- and large-scale hydropower plants in China by combining GIS technology. Natural factors are the most important of the six dimensions, followed by social factors. According to the suitability assessment results of TODIM, #23 hydropower station has the highest suitability for HWPSCS investment, which provides a reference for the layout of China's HWPS complementary system. With different decision makers' risk preferences and different MADM methods, #23 hydropower plant is still the best investment option, which proves the effectiveness of the MADM framework proposed in this study.

Exploring the dependability of Combined Ratio Estimators in Stratified Ranked Set Sampling: Insights from COVID-19 data

In this study, we introduce a novel combined ratio type estimator within the framework of Stratified Ranked Set Sampling to estimate the population mean of the study variable by incorporating bivariate auxiliary information. We conduct a comprehensive comparative analysis, including traditional combined ratio, combined regression, Shabbir and Khan [13], and Bhushan and Kumar [37] estimators. We assess the bias and mean squared error of the proposed estimator under the initial degree of approximation. The data source consists of COVID-19 data up to July 2023. Through empirical investigation and simulation studies, our proposed estimator consistently demonstrates superior performance compared to its counterparts, exhibiting the highest relative efficiency. These findings underscore the practical significance of our research in public health and decision-making, emphasizing the potential of this estimator to provide more accurate and reliable estimates in various applications involving ranked set sampling and auxiliary information.

Ship collision avoidance decision-making research in coastal waters considering uncertainty of target ships

Ship collision avoidance has always been a concern and it is crucial for achieving safe navigation of ships at sea. There are many studies on ship collision avoidance in open water, but less attention on coastal waters considering the uncertainty of target ships due to the complexity of the environment and traffic flow. In this paper, collision avoidance decision-making research in coastal waters considering the uncertainty of target ships was proposed. Firstly, accurate ship trajectories are obtained by preprocessing the raw Automatic Identification System (AIS) data. Subsequently, the processed trajectories are clustered using the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm and Hausdorff distance, acquiring a dataset for trajectory prediction of target ships. Then, a mixed Gaussian model is utilized to calculate the prior probability distribution of the prediction model, thus establishing a trajectory prediction model that considers the uncertainty of the target ship. Finally, ship maneuverability is simulated using the Mathematical Model Group (MMG) and Proportion Integration Differentiation (PID) models, and a collision avoidance decision-making model for ships is constructed. The proposed algorithm has been tested and verified in a case study. The results show that the approach effectively predicts the trajectory of the target ship and facilitates informed collision avoidance decision-making.

Integration of environmental indicators into the management decision-making system

Climate change demands integrating environmental indicators into management decision-making systems, highlighting shifts towards environmental safety and stricter emissions regulations. This research develops a scheme for such integration, filling the gap in literature on the relationship between environmental factors and management decisions. Literature analysis and data examination through scientific and mathematical methods, including linear and multicriteria analysis, have led to a model emphasizing the importance of embedding environmental considerations into decision-making. The findings highlight the role of multi-criteria decisions in various conditions and establish a comprehensive model for the interplay between economic and environmental indicators, enhancing eco-efficiency in management practices. This approach introduces a novel method for incorporating environmental sustainability into management strategies, underscoring its significance for ongoing research and application in eco-efficient management decision-making.

2005 How do emergency ambulance clinicians decide what to do for older adults who have fallen? An analysis of qualitative survey data

Abstract Introduction Around 10% of calls received by English ambulance services are for older adults who have fallen1; with an ageing population there are significant care provision needs. Decision-making on the treatment for people who fall, can impact their future physical and mental health. Previous research in decision-making of ambulance staff found perception of role, confidence, service demands and training to be key drivers2. The previous work highlighting drivers, but not the experiences that explain why they occur, leads this study aim to determine the experiences and confidence of frontline emergency clinicians in attending older adults who have fallen. Method Online cross-sectional survey of frontline emergency clinicians from one English ambulance service in May 2023. Open questions generated qualitative data for thematic analysis3. Ethical and regulatory approvals, and informed consent, were obtained. Results: 81 participants completed the survey. Analysis identified three themes. Care Provision: Provision of hospital avoidance pathways varies throughout the region. Concerns arose from not knowing what different areas had and reduced accessibility out of hours. Communication: Decision-making confidence was impacted by the participants’ experiences; positive experiences encouraged use of hospital avoidance pathways, whilst negative experiences impeded willingness to avoid hospital for fear of repercussion. Shared Decision-Making: Patients, family and clinicians were all valued as part of shared decision-making, with past feedback on decision-making informing future practice. Conclusion Confidence of frontline ambulance staff was impacted by the challenge of a regional and 24/7 ambulance service not having consistent pathways available. This variation led to concerns when responding to patients outside of the clinician’s usual area, and further challenges ambulance clinicians must balance in their practice.

Unravelling Deconstruction: A Comprehensive Examination of its Qualitative Research Method and Application in Historical Texts

This research endeavors to delve into the qualitative research method of deconstruction and its profound application in deciphering the nuanced meanings within historical texts. Utilizing a review methodology, this study takes the form of a comprehensive review article. Deconstruction, as both a theory and practical approach to text reading, challenges the prevailing notion that language systems inherently establish coherence or unity in literary texts, aiming to uncover definitive meanings. The primary objective of deconstruction is to express concepts qualitatively and analytically. Research questions are tailored to the type of text under consideration, guided by the researcher's decisions. For instance, the groundbreaking concept of "explanatory and inquiry" emerged in the literary domain, maintaining its relevance within academic institutions and expanding to encompass various conceptual frameworks. Deconstruction extends its reach into social thinking and speeches, involving critical re-examination of historical texts to glean insights into historical facts. Essentially akin to metaphysical criticism, the deconstruction method was founded by Jacques Derrida, an Algerian philosopher of French origin, whose theories significantly influenced postmodern philosophy and literary criticism.

테크놀로지융합 체육수업 도입을 위한 교사양성방안 탐구 및 제언

The purpose of this study is to identify the reasons behind the slow adoption of technology in physical education(PE) and to suggest strategies to prepare PE teachers who can integrate technology into PE class. To achieve this, the study utilizes theories from teacher beliefs and decision-making research to analyze these underlying reasons and introduces a new framework called C.O.P.S. The C.O.P.S. framework is developed based on decision-making research and is aimed at facilitating the adoption of technology. In order to effectively promote PE teacher’s technology adoption, an understanding of the fundamental reasons why they may hesitate to embrace technology and the challenges they may face during the adoption process is necessary. The C.O.P.S. framework proposed in this paper can provide crucial guidance and principles for concretely shaping and designing technology adoption plans.

Cognitive chicken or the emotional egg? How reconceptualizing decision-making by integrating cognition and emotion can improve task psychometrics and clinical utility.

Decision-making is an executive function, tapping into cognitive, emotional, and personality-based components. This complexity, and the varying operational definitions of the construct, is reflected in the rich array of behavioral decision-making tasks available for use in research and clinical settings. In many cases, these tasks are "subfield-specific," with tasks developed by cognitive psychologists focusing on cognitive aspects of decision-making and tasks developed by clinical psychologists focusing on interactions between emotional and cognitive aspects. Critically, performance across different tasks does not consistently correlate, obfuscating the ability to compare scores between measures and detect changes over time. Differing theories as to what cognitive and/or emotional aspects affect decision-making likely contribute to this lack of consistency across measures. The low criterion-related validity among decision-making tasks and lack of consistent measurement of the construct presents challenges for emotion and decision-making scholars. In this perspective, we provide several recommendations for the field: (a) assess decision-making as a specific cognitive ability versus a taxonomy of cognitive abilities; (b) a renewed focus on convergent validity across tasks; (c) further assessment of test-retest reliability versus practice effects on tasks; and (d) reimagine future decision-making research to consider the research versus clinical implications. We discuss one example of decision-making research applied to clinical settings, acquired brain injury recovery, to demonstrate how some of these concerns and recommendations can affect the ability to track changes in decision-making across time.

Decision-making in nursing research and practice-Application of the Cognitive Continuum Theory: A meta-aggregative systematic review.

To explore how the Cognitive Continuum Theory has been used in qualitative nursing research and to what extent it has been integrated in the research process using the Qualitative Network for Theory Use and Methodology (QUANTUM). Theory, research and nursing are intrinsically linked, as are decision-making and nursing practice. With increasing pressure on nurses to improve patient outcomes, systematic knowledge regarding decision-making is critical and urgent. A meta-aggregative systematic review. DATABASES: CINAHL, Medline, PsycINFO, Embase and PubMed were searched from inception until May 2022 for peer-reviewed research published in English. Seven studies were included and assessed for methodological quality using the Joanna Briggs Institute checklist for qualitative research. A meta-aggregative synthesis was conducted using Joanna Briggs methodology. The QUANTUM typology was used to evaluate the visibility of the Cognitive Continuum Theory in the research process. The review identified five synthesised findings, namely: 1. the decision-making capacity of the individual nurse, 2. nurses' level of experience, 3. availability of decision support tools, 4. the availability of resources and 5. access to senior staff and peers. Only two of seven studies rigorously applied the theory. The included studies were mainly descriptive-exploratory in nature. The transferability of the Cognitive Continuum Theory was demonstrated; however, evolution or critique was absent. A gap in the provision of a patient-centric approach to decision-making was identified. Education, support and research is needed to assist decision-making. A new Person-Centred Nursing Model of the Cognitive Continuum Theory has been proposed to guide future research in clinical decision-making. Nurses make numerous decisions every day that directly impact patient care, therefore development and testing of new theories, modification and revision of older theories to reflect advances in knowledge and technology in contemporary health care are essential.

IMPROVING THE ECONOMIC EFFICIENCY OF THE DEVELOPMENT OF INNOVATIVE INTEGRATED STRUCTURES IN THE REAL SECTOR IN KAZAKHSTAN

Purpose of the research. The present research is devoted to the study of the relationship between scientifi c capabilities and innovation eff orts. The purpose of the study is to assess the eff ectiveness of the development of innovative integrated structures in the real sector in Kazakhstan. Scientifi c research makes it possible to study the importance of innovative integrated structures and contributes to the literature on research and development and economic growth.The research methodology was implemented by mathematical modeling. The assessment of the eff ectiveness of the development of innovative integrated structures includes the analysis of indicators refl ecting the results of the activities of the participants of the integrated structure, in particular universities in the form of scientifi c articles, innovative enterprises in the form of the volume of innovative products and scientifi c organizations in the form of patents.The originality / value of the study is confi rmed and justifi ed by the lack of research on the calculation of the eff ectiveness of innovative integrated structures in the regions of Kazakhstan.Findings. Innovative integrated structures are necessary to support the real sector of the economy, which is most prone to crises. To solve many of the challenges that our economy has faced in recent years, it requires the use of research in public policy and decision-making, not based on blind faith in scientifi c recommendations.

Two important strategies to attenuate consumer purchase hesitation☆

Based on collective cognitive dissonance theory and self-affirmation theory, this study examines the methods of attenuating purchase hesitation and retaining consumers’ original purchase intention of luxury goods by offering advertising messages. Two experiments were conducted to examine how purchase hesitation caused by negative feedback from peers at the purchase stage can be resolved. The results indicate that collective cognitive dissonance and self-threat at the purchase stage decreases purchase intention. Offering advertising messages containing information that supports consumer choice mitigates the negative influence of purchase hesitation on purchase intention and information search intention. Moreover, providing promotional messages to enhance self-esteem reduces consumer intention to search for additional information, but does not restore already reduced purchase intention. This study provides meaningful implications for consumer decision-making research. The findings contribute to the theoretical development of new media and future research on consumer decision-making.

Young adults' reasoning for involving a parent in a genomic decision-making research study.

Young adults have increasing genomic testing opportunities; however, little is known about how equipped they feel about making decisions to learn personal genomic information. We conducted qualitative interviews with 19 young adults, ages 18-21 years old, enrolled in a research study where they made decisions about learning personal genomic risk for developing preventable, treatable, and adult-onset conditions and carrier status for autosomal recessive conditions. Participants had the option to include a parent in their study visit and the decision-making process. The goal of this project was to explore young adults' reasons for involving or not involving a parent in the study and to assess young adults' perspectives about parental roles in their healthcare. Nine participants included a parent in the study and ten did not include a parent. Eleven participants received genomic test results before the interview, while eight participants had not yet received their results at the time of the interview. The study team developed a coding guide and coded interview transcripts inductively and deductively using an interpretive descriptive-analytic approach. Logistical issues dominated solo participants' reasons for not involving a parent in the study, whereas those who involved a parent often cited a close relationship with the parent and the parent's previous involvement in the participant's healthcare as reasons for involving them. Both groups of participants described gradually transitioning to independent healthcare decision-making with age and felt their comfort in medical decision-making depends on the severity of and their familiarity with the situation. Participants recommended that future genomic researchers or clinicians give young adults the option to involve a parent or friend as a support person in research or clinical visits. Although young adults may have different journeys toward independent healthcare decision-making, some may benefit from continued parental or peer involvement after reaching the age of legal adulthood.

A survey on uncertainty reasoning and quantification in belief theory and its application to deep learning

An in-depth understanding of uncertainty is the first step to making effective decisions under uncertainty. Machine/deep learning (ML/DL) has been hugely leveraged to solve complex problems involved with processing high-dimensional data. However, reasoning and quantifying different uncertainties to achieve effective decision-making have been much less explored in ML/DL than in other Artificial Intelligence (AI) domains. In particular, belief/evidence theories have been studied in Knowledge representation and reasoning (KRR) since the 1960s to reason and measure uncertainties to enhance decision-making effectiveness. Based on our in-depth literature review, only a few studies have leveraged mature uncertainty research in belief/evidence theories in ML/DL to tackle complex problems under different types of uncertainty. Our present survey paper discusses major belief theories and their core ideas dealing with uncertainty causes and types and quantifying them, along with the discussions of their applicability in ML/DL. Particularly, we discuss three main approaches leveraging belief theories in Deep Neural Networks (DNNs), including Evidential DNNs, Fuzzy DNNs, and Rough DNNs, in terms of their uncertainty causes, types, and quantification methods along with their applicability in diverse problem domains. Through an in-depth understanding of the extensive survey on this topic, we discuss insights, lessons learned, limitations of the current state-of-the-art bridging belief theories and ML/DL, and future research directions. This paper conducts an extensive survey by bridging belief theories and deep learning in reasoning and quantifying uncertainty to help researchers initiate uncertainty and decision-making research.

Moral judgments under uncertainty: risk, ambiguity and commission bias

Previous research on moral dilemmas has mainly focused on decisions made under conditions of probabilistic certainty. We investigated the impact of uncertainty on the preference for action (killing one individual to save five people) and inaction (saving one but allowing five people to die) in moral dilemmas. We reported two experimental studies that varied the framing (gain vs loss), levels of risk (probability of gain and loss) and levels of ambiguity (imprecise probability information) in the choice to save five individuals by sacrificing one. We found that participants preferred actions with uncertainty (risk/ambiguity) over inaction. Specifically, we found that participants preferred actions with precise probability information (risk) over inaction, and they preferred actions with modest or high levels of ambiguity over actions with precise probabilities, especially when moral dilemmas had a loss frame. We also observed commission bias in Study 2. We discussed the implications for research in moral decision-making.

Decision-making in international marketing: past, present and future

PurposeThis special issue seeks to create an interdisciplinary community of researchers applying decision-making theory to the international marketing context. The articles published in this special issue contain cutting-edge conceptual and empirical studies that enhance existing knowledge on international marketing decision-making.Design/methodology/approachThirty-six (36) manuscripts were submitted to the editorial office focusing on a broad range of international marketing decision-making. Following a thorough review process, a collection of five original empirical studies on different facets of international marketing decision-making from multiple theoretical, contextual and methodological perspectives are included in this Special Issue.FindingsOverall, the combined evidence presented in this Special Issue shows that the general field of international marketing decision-making is starting to mature. Evidence from the contributors to this Special Issue shows that researchers have taken inspiration from both the past and the present when designing and crafting their research and, by doing so, they have collectively contributed to new knowledge in terms of international marketing decision-making principles, decision-maker personality traits, the consequences of international marketing decisions and cross-cultural differences with regards to decision-making influences and behavior.Originality/valueWith few exceptions, not much is known about how international marketing decisions are made. Yet, the way international marketing decisions are made is critical for international marketing success. This sphere of international marketing decision-making research, while relatively anemic, is typically underpinned by behavioral economic theories of decision-making, such that a duality in decision-making processes is identified. Nevertheless, international marketing and management studies are dominated by the planning paradigm, while in practice, managers often see the attempt to deviate from planning as irresponsible and dangerous. The articles included in this special issue have addressed major unanswered questions regarding the content and processes of international marketing decision-making.

Collaborative privacy-preserving analysis of oncological data using multiparty homomorphic encryption

Real-world healthcare data sharing is instrumental in constructing broader-based and larger clinical datasets that may improve clinical decision-making research and outcomes. Stakeholders are frequently reluctant to share their data without guaranteed patient privacy, proper protection of their datasets, and control over the usage of their data. Fully homomorphic encryption (FHE) is a cryptographic capability that can address these issues by enabling computation on encrypted data without intermediate decryptions, so the analytics results are obtained without revealing the raw data. This work presents a toolset for collaborative privacy-preserving analysis of oncological data using multiparty FHE. Our toolset supports survival analysis, logistic regression training, and several common descriptive statistics. We demonstrate using oncological datasets that the toolset achieves high accuracy and practical performance, which scales well to larger datasets. As part of this work, we propose a cryptographic protocol for interactive bootstrapping in multiparty FHE, which is of independent interest. The toolset we develop is general-purpose and can be applied to other collaborative medical and healthcare application domains.

An RFID Tag Movement Trajectory Tracking Method Based on Multiple RF Characteristics for Electronic Vehicle Identification ITS Applications.

Intelligent transportation systems (ITS) urgently need to realize vehicle identification, dynamic monitoring, and traffic flow monitoring under high-speed motion conditions. Vehicle tracking based on radio frequency identification (RFID) and electronic vehicle identification (EVI) can obtain continuous observation data for a long period of time, and the acquisition accuracy is relatively high, which is conducive to the discovery of rules. The data can provide key information for urban traffic decision-making research. In this paper, an RFID tag motion trajectory tracking method based on RF multiple features for ITS is proposed to analyze the movement trajectory of vehicles at important checkpoints. The method analyzes the accurate relationship between the RSSI, phase differences, and driving distances of the tag. It utilizes the information weight method to obtain the weights of multiple RF characteristics at different distances. Then, it calculates the center point of the common area where the vehicle may move under multi-antenna conditions, confirming the actual position of the vehicle. The experimental results show that the average positioning error of moving RFID tags based on dual-frequency signal phase differences and RSSI is less than 17 cm. This method can provide real-time, high-precision vehicle positioning and trajectory tracking solutions for ITS application scenarios such as parking guidance, unmanned vehicle route monitoring, and vehicle lane change detection.

Examining Financial Behavior and Decision-Making: A Bibliometric Study of Trends and Insights

This research paper presents a comprehensive bibliometric analysis of trends and insights related to behavioral finance and decision making. Utilizing bibliometric methods and VOSviewer software, this research examines publication trends, key themes, influential authors and institutions, research methodologies, and emerging trends in the field. The findings highlight the growing interest in behavioral finance and decision-making research, with publications increasing over time. Key themes include behavioral biases and heuristics, risk perception and decision making, financial literacy and education, socio-economic factors, and the impact of technology. Influential authors and institutions are identified, and various research methodologies, such as quantitative, qualitative, and mixed methods, are observed. Emerging trends include the application of machine learning, consideration of environmental and social factors, and behavioral interventions using digital platforms. Insights from this bibliometric study contribute to the understanding of the current state of knowledge in behavioral finance and decision-making, informing researchers, practitioners, and policymakers in their efforts to achieve better financial outcomes.