Conceptual Framework Model Research Articles

The effects of brands posts on social media: conceptual framework and application method

Purpose- Many forms of brands’ posts such as cointaining web links, images, photos and videos can be used for marketing research. The aim of this study is to present an approach to gather and analyze social media data and shows how marketers can derive useful outcomes from these data. Methodology- The impacts of media types (link, text, video, photo), length, time (day-of-week and time-of-day) of brands' posts on customers’ engagement are investigated. For this purpose, we propose a conceptual framework and mathematical model. Findings- According to the conceptual framework and mathematical model given in this research, it is recommended to determine the effects of the content of the brands’ posts on social media users. Conclusion- Brands may determine the most effective content of the social media posts by applying the proposed mathematical model in this study.

Analysis of groundwater resources in densely populated urban watersheds with a complex tectonic setting: Shenzhen, southern China

Shenzhen is the major financial and high-tech center in southern China. The megacity has grown rapidly in the last 40 years with the population increasing from about 30,000 in 1979 to 20 million in 2016. The study area (2,015 km2) is about 42% urban and 58% undeveloped land. The rapid development of the megacity has resulted in severe degradation of the groundwater and surface-water resources and has created a nearly insatiable demand for water, with an average consumption of 2000 × 106 m3/year. Groundwater is an important component of the baseflow of the many streams in the area and is used for potable water supply and irrigation in some of the rural parts of the municipality. This study develops a conceptual model and quantitative framework for assessing the groundwater resources of Shenzhen. The groundwater system consists of shallow aquifers of alluvium and weathered bedrock overlying low permeability igneous and sedimentary rocks. The complex geologic setting was conceptualized as a block structure with blocks bounded by high-angle faults. The water budget in Shenzhen was quantified. The estimated average groundwater discharge is about 12% of annual precipitation. The study provides a starting point to investigate how a megacity such as Shenzhen should manage and protect its groundwater as a strategic resource and environmental asset. It is also a basic management tool for analyzing and contributing to urban drainage concepts such as the “sponge city”.

Indoor environmental quality performance and occupants’ satisfaction [IEQPOS] as assessment criteria for green healthcare building rating

A building as shelter is designed to provide an indoor environmental quality (IEQ) that is comfortable and appealing to its users. Having the understanding of the relationship between IEQ performance in buildings and the overall satisfaction derivable from the environment by the building occupants are necessary variables that will enhance the formulation of the requirements for architectural and building systems design and control. This study is aimed at developing a conceptual framework model for evaluating the performance of IEQ and occupants' satisfaction in hospital ward buildings. This conceptual framework is based on hypothesised model constructs, using Confirmatory Factor Analysis (CFA) and Structural Regression Models (SRM). The data were analysed, using Structural Equation Modelling (SEM). The analysis of the different specified model constructs in the framework resulted in an evaluation model for IEQ performance (IEQPM) and occupants' satisfaction (IEQPOS) in hospital ward buildings. The IEQPM model indicated that thermal quality, acoustic quality, visual quality, and indoor air quality (IAQ) are significant determinants of IEQ performance indirectly measured through the interrelationship among ten different indoor environment indicators. However, the level of importance of the four parameters of the IEQ performance differed, having different weighting factors of 0.61, 0.53, 0.40, and 0.47. The significant relationship between IEQ performance and occupants' satisfaction as established by the IEQPOS model resulted into a single index score value called ‘Comprehensive Occupant Satisfaction’ Index (COSI) which can be used for the assessment of occupancy comfort survey aspect of IEQ criteria in green building rating system.

Cognitive Factories: Modeling Situated Entropy in Physical Work Carried Out by Humans and Robots.

Entropy in factories is situated. For example, there can be numerous different ways of picking, orientating, and placing physical components during assembly work. Physical components can be redesigned to increase the Information Gain they provide and so reduce situated entropy in assembly work. Also, situated entropy is affected by the extent of knowledge of those doing the work. For example, work can be done by knowledgeable experts or by beginners who lack knowledge about physical components, etc. The number of different ways that work can be done and the knowledge of the worker combine to affect cognitive load. Thus, situated entropy in factories relates to situated cognition within which knowledge is bound to physical contexts and knowing is inseparable from doing. In this paper, six contributions are provided for modelling situated entropy in factories. First, theoretical frameworks are brought together to provide a conceptual framework for modelling. Second, the conceptual framework is related to physical production using practical examples. Third, Information Theory mathematics is applied to the examples and a preliminary methodology in presented for modelling in practice. Fourth, physical artefacts in factory production are reframed as carriers of Information Gain and situated entropy, which may or may not combine as Net Information Gain. Fifth, situated entropy is related to different types of cognitive factories that involve different levels of uncertainty in production operations. Sixth, the need to measure Net Information Gain in the introduction of new technologies for embodied and extended cognition is discussed in relation to a taxonomy for distributed cognition situated in factory production. Overall, modelling of situated entropy is introduced as an opportunity for improving the planning and control of factories that deploy human cognition and cognitive technologies including assembly robotics.

The Digital Divide and Older Adult Population Adoption, Use and Diffusion of Mobile Phones: a Quantitative Study

Due to the changing demographics of societies around the world, ageing has become a major concern for governments and policy makers alike. What has also become clear is that the older adult consumer group and the factors affecting this age group have been studied relatively less in the literature. In this paper, we aim to investigate the adoption, usage, and diffusion of smartphones within the UK older adults so as to identify the factors encouraging or inhibiting smartphone usage and service provision within this age group. To this end, we propose a conceptual framework (Model of Smartphone Acceptance) based on a set of well-known theories of adoption and diffusion. We collected data from 984 participants living in north London and applied the Partial Least Square Structural Equation Modelling (PLS-SEM) technique to analyse the data. Our research can contribute towards reducing some of the existing digital divide within UK older adults. Moreover, businesses can benefit from our research by understanding the significant factors affecting the adoption of smartphones among the UK older population and to adapt their policies accordingly.

Spatial and temporal variation of benthic macroinvertebrate assemblages during the glacial melt season in an Italian glacier-fed stream

The biodiversity of glacier-fed streams is particularly threatened by climate change, emphasising the need of monitoring these sentinel systems. The glacier-fed Saldur stream is an International Long Term Ecological Research (ILTER) site in the Italian Central Eastern Alps. Here, we sampled benthic macroinvertebrates and measured environmental variables (discharge, suspended solids, conductivity, water temperature, and channel stability) five times at six sites (5–11 km from the glacier) during an entire glacial melt season (April–September). Our main objectives were (1) to elucidate relationships between the abiotic variables and the faunal composition, (2) to quantify and compare the spatial and temporal variability of the faunal community, and (3) to assess the composition of the benthic macroinvertebrate community in relation to conceptual models. Hosting a higher number of individuals and more diverse communities at sites with reduced glacial influence, the Saldur stream fitted well in the framework of conceptual models. Nevertheless, the spatial variability of the fauna was higher than the temporal variability. This study presents an initial characterisation of the benthic faunal assemblages in the Saldur stream, constituting a reference point for future analyses dealing with potential disruptive factors introduced by climate change and upcoming hydroelectric power production on this stream.

Designing Business Analytics Solutions

The design and development of data analytics systems, as a new type of information systems, has proven to be complicated and challenging. Model based approaches from information systems engineering can potentially provide methods, techniques, and tools for facilitating and supporting such processes. The contribution of this paper is twofold. Firstly, it introduces a conceptual modeling framework for the design and development of advanced analytics systems. It illustrates the framework through a case and provides a sample methodological approach for using the framework. The paper demonstrates potential benefits of the framework for requirements elicitation, clarification, and design of analytical solutions. Secondly, the paper presents some observations and lessons learned from an application of the framework by an experienced practitioner not involved in the original development of the framework. The findings were then used to develop a set of guidelines for enhancing the understandability and effective usage of the framework.

GEDMod – Towards a generic toolkit for emergency department modeling

The design of generic models, or generic building blocks, for health care operations has been discussed in depth and identified as one of the grand challenges for researchers in the field of Modeling and Simulation. In this paper we provide an investigative basis for answering recently raised research questions for a specific sub-domain of health care facilities and a specific Modeling and Simulation paradigm, i.e. Discrete Event Simulation Models of Emergency Departments. We perform a detailed analysis of a large set of published Emergency Department models. This analysis is executed following a structured conceptual modeling framework to ensure the coverage of key conceptual modeling aspects: objectives; input scenarios; output definitions, i.e. commonly used performance indicators; structural components such as physical resources and human resources (including expertise and skill levels); patient classifications (arrival modes, triage grades, complaint categories); patient pathways including triage, treatment (which possibly includes resuscitation or special care) and admission phases; and organizational structures including control policies. The resulting collection and classification of modeling archetypes are used as the basis for an initial generic modeling toolkit for Emergency Department operations. Thereby, the modeler is guided through the main steps of conceptual modeling of Emergency Departments and generic building blocks for each step are provided. The paper concludes with a discussion on the applicability and benefits of the resulting GEDMod framework along with the potential to combine the toolkit into a single generic Emergency Department model.

Modeling of flame extinction/re-ignition in oxygen-reduced environments

The present work aims to evaluate a flame extinction/re-ignition model that considers the interaction of the non-premixed flame with flow turbulence. Turbulence can disturb the flame surface and initiate mixing between fuel, air, and combustion products. Near extinction, pockets of pre-mixture in the form of mixed eddies can be formed. The evolution of such a mixed eddy is determined by the competition of the heat release and heat loss rates, which are linked to the eddy size, the local flame thickness, and the turbulent Karlovitz number. Radiation from the reacting flame sheet is modeled considering the gaseous combustion products and soot. Based on this conceptual flame extinction modeling framework, a re-ignition model is also developed to describe the downstream, piloted re-ignition of the mixed, quenched fuel. The flame extinction/re-ignition model is implemented in FireFOAM and is evaluated using gaseous-pool fires in an enclosure with CH4, C3H8 and C2H4 diluted with nitrogen in air flow. The model predictions are compared with test data for combustion efficiency, flame height and global radiant fraction.

Job Stress and Productivity: A Conceptual Framework

The Indian IT industry has seen an increase of 1.3 million women employees in 2016. The study is about job Stress and employee productivity. From the various review of literature we have identified the factors affecting Job Stress and Productivity. The literature is collected from the year 1974 to 2016 on various areas like the definition of the concepts to various factors influencing the Job Stress and productivity. The various sectors covered on which job stress and productivity factors are studied include construction, banking sector, education institution, financial institution, IT, Call center, and Private hospital. The variables/indicators that can be identified in the existing literature to study job stress are workload, role ambiguity, gender discrimination, interpersonal relationship. The variables/indicators for measuring employee productivity are identified as work schedule/timings, competence of supervisor, compensation, systems and procedures, group dynamics, absenteeism and presenteeism. The paper also throws light on meaning of various indicators mentioned above. In addition, the conceptual framework models the relationship between job stress and productivity.

Sustainable and Resilient Design of Interdependent Water and Energy Systems: A Conceptual Modeling Framework for Tackling Complexities at the Infrastructure-Human-Resource Nexus

A modeling framework was conceptualized for capturing the complexities in resilience and sustainability associated with integration of centralized and decentralized water and energy systems under future demographic, climate, and technology scenarios. This framework integrates survey instruments for characterizing individual preferences (utility functions) related to decentralization of water and energy infrastructure systems. It also includes a spatial agent-based model to develop spatially explicit adoption trajectories and patterns in accordance with utility functions and characteristics of the major metropolitan case study locations as well as a system dynamics model that considers interactions among infrastructure systems, characterizes measures of resilience and sustainability, and feeds these back to the agent-based model. A cross-scale spatial optimization model for understanding and characterizing the possible best case outcomes and for informing the design of policies and incentive/disincentive programs is also included. This framework is able to provide a robust capacity for considering the ways in which future development of energy and water resources can be assessed.

Task Allocation in Spatial Crowdsourcing: Current State and Future Directions

Spatial crowdsourcing (SC) is an emerging paradigm of crowdsourcing, which commits workers to move to some particular locations to perform spatio-temporal-relevant tasks (e.g., sensing and activity organization). Task allocation or worker selection is a significant problem that may impact the quality of completion of SC tasks. Based on a conceptual model and generic framework of SC task allocation, this paper first gives a review of the current state of research in this field, including single task allocation, multiple task allocation, low-cost task allocation, and quality-enhanced task allocation. We further investigate the future trends and open issues of SC task allocation, including skill-based task allocation, group recommendation and collaboration, task composition and decomposition, and privacy-preserving task allocation. Finally, we discuss the practical issues on real-world deployment as well as the challenges for large-scale user study in SC task allocation.

The Mediating Effect of Total Productive Maintenance (TPM) Between Total Quality Management (TQM) and Business Performance

Total quality management (TQM) concepts are paramount importance for every industry in the pursuit of competitiveness in the global market. However, based on previous TQM literature reported that ambiguous or mixed relationship between TQM and business performance lead to inconsistent results. Furthermore, there lack of study of Total preventive maintenance (TPM) as mediator in previous works. Therefore, it is important to obtain successful TQM paradigm. TPM acted as a prominent paradigm to improve the manufacturing performance to gain further competitive advantage. Hence, the purpose of this study is to propose research and conceptual framework model of TQM practices in relation to business performance with mediator effect of TPM. The developed model for further study will be tested and validate by collecting primary data. The Structural Equation Modeling (SEM) approach will be used for hypotheses testing and determine the relationship of mediators effect in TQM practices and business performance.

Implementing complex task allocation in a cytology lab via HCCM using Flexsim HC

Healthcare processes contain various complexities which make them difficult to model. These include: multiple-participant activities with flexible resourcing; dynamic task priorities; hierarchical skill levels of resources; and regular task pre-emption. Deciding which task in a care pathway a clinician next performs directly impacts on the performance of the healthcare process. The Hierarchical Control Conceptual Modeling (HCCM) approach has recently been proposed by Furian et al. [1] to provide a conceptual modelling framework purpose-built to explicitly model the decision-making structure in complex systems. Existing software packages for Discrete Event Simulation (DES) have been designed for conceptual models that consist of systems of queues. In particular, the lack of a module specifically designed to account for HCCM’s control structure makes the implementation of a HCCM conceptual model in an off-the-shelf simulation package problematic. This research applies the HCCM framework to a real-world Cytology lab (with complex decision making for task allocations) and demonstrates how the resultant conceptual model can be implemented within an off-the-shelf healthcare simulation package (Flexsim HC). The primary goal is a proof-of-concept that the control mechanism, particular to the HCCM framework, can be implemented using such a simulation package.

A Conceptual Design and Modeling Framework for Integrated Additive Manufacturing

Modeling and simulation for additive manufacturing (AM) is commonly used in industry. Nevertheless, a central issue remaining is the integration of different models focusing on different objectives and targeting different levels of details. The objective of this work is to increase the prediction capability of characteristics and performances of additively manufactured parts and to co-design parts and processes. The paper contributes to this field of research by integrating part's performance model and additive technology process model into a single early integrated model. The paper uses the dimensional analysis conceptual modeling (DACM) framework in an AM perspective to generate causal graphs integrating the AM equipment and the part to be printed. DACM offers the possibility of integrating existing knowledge in the model. The framework supported by a computer tool produces a set of governing equations representing the relationships among the influencing variables of the integrated model. The systematic identification of the weaknesses and contradictions in the system and qualitative simulation of the system are some of the potential uses of the model. Ultimately, it is a way to create better designs of machines and parts, to control and qualify the manufacturing process, and to control three-dimensional (3D) printing processes. The DACM framework is tested on two cases of a 3D printer using the fused filament fabrication (FFF) powder bed fusion. The analysis, applied to the global system formed of the 3D printer and the part, illustrates the existence of contradictions. The analysis supports the early redesign of both parts and AM process (equipment) and later optimization of the control parameters.

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data.

ObjectiveTo develop a conceptual prediction model framework containing standardized steps and describe the corresponding open-source software developed to consistently implement the framework across computational environments and observational healthcare databases to enable model sharing and reproducibility.MethodsBased on existing best practices we propose a 5 step standardized framework for: (1) transparently defining the problem; (2) selecting suitable datasets; (3) constructing variables from the observational data; (4) learning the predictive model; and (5) validating the model performance. We implemented this framework as open-source software utilizing the Observational Medical Outcomes Partnership Common Data Model to enable convenient sharing of models and reproduction of model evaluation across multiple observational datasets. The software implementation contains default covariates and classifiers but the framework enables customization and extension.ResultsAs a proof-of-concept, demonstrating the transparency and ease of model dissemination using the software, we developed prediction models for 21 different outcomes within a target population of people suffering from depression across 4 observational databases. All 84 models are available in an accessible online repository to be implemented by anyone with access to an observational database in the Common Data Model format.ConclusionsThe proof-of-concept study illustrates the framework’s ability to develop reproducible models that can be readily shared and offers the potential to perform extensive external validation of models, and improve their likelihood of clinical uptake. In future work the framework will be applied to perform an “all-by-all” prediction analysis to assess the observational data prediction domain across numerous target populations, outcomes and time, and risk settings.

A Conceptual Framework for an Extension Access Control Models in Saudi Arabia Healthcare Systems

This article aims to develop an extension access control models framework in Saudi Arabian healthcare systems. The conceptual framework acts as an ascendency structure to organize and support the efforts of several health care standards which reflect on the coherent of confidentiality; integrity; and availability triads in order to achieve the strategic business objectives of Saudi Arabian healthcare institutions. It is considered to be three common access control models developed by ACM institute and extended to other criteria identified by the National Institute of Standards and Technology. While literature explains that an easy-to-use access control model can lead to success healthcare system, understanding the extension of access control systems is vital for Saudi Arabian healthcare institutions to protect resources against unauthorized use. This article has taken a step in this direction.

Model-Based Interoperability Engineering in Systems-of-Systems and Civil Aviation

Interoperability is the capability of multiple parties and systems to collaborate and exchange information and matter to obtain their objectives. Interoperability challenges call for a model-based systems engineering approach. This paper describes a conceptual modeling framework for model-based interoperability engineering (MoBIE) for systems of systems, which integrates multilayered interoperability specification, modeling, architecting, design, and testing. Treating interoperability infrastructure as a system in its own right, MoBIE facilitates interoperability among agents, processes, systems, services, and interfaces. MoBIE is founded on ISO 19450 standard—object-process methodology, a holistic paradigm for modeling and architecting complex, dynamic, and multidisciplinary systems—and allows for synergistic integration of the interoperability model with system-centric models. We also discuss the implementation of MoBIE with the unified modeling language. We discuss the importance of interoperability in the civil aviation domain, and apply MoBIE to analyze the passenger departure process in an airport terminal as a case-in-point. The resulting model enables architectural and operational decision making and analysis at the system-of-systems level and adds significant value at the interoperability engineering program level.

Adopting a Strategic Approach to Matching People to Jobs

This conceptual analysis explores recruiters’ ability to utilize the practice of strategic foresight to scan internal and external environments as a strategic plan to matching people to jobs. In today’s volatile market, it is no longer useful for recruiters to attract and hire talent with a desultory mindset when filling open positions without considering internal and external factors. Today’s recruiters must become more deliberate in who they hire by having a tactical plan to attract and retain the most qualified people in an unpredictable global market. Through the process of developing a conceptual framework model, this paper aims to present three strategic foresight competencies required for recruiters to match people to jobs. Also, this conceptual analysis will argue the need for recruiters to possess a strategic mindset to attract and hire the most qualified people to an organization. Furthermore, discuss the implications of recruiters who lack strategic foresight competencies. The practice of strategic foresight is now a requirement for recruiters to become cognizant of internal and external factors such as competitive behavior, technological change, political and economic conditions and human capital, which can influence their approach to matching people to jobs. Overall, when recruiters match talent based on the company’s strategic drivers rather than blindly fill open positions without a tactical plan, organizations can better achieve its performance potential.

The Green Silk Road Economic Belt and the Governance of the Aral Sea

Central Asia has a fragile ecological environment. In particular, one of the most challenging environmental concerns in the region is the Aral Sea crisis. Despite the global attention received on the governance of the Aral Sea, the crisis remains unresolved. This article presents a novel conceptual framework and dynamic model for the governance of the Aral Sea. The authors suggest that a key aspect of agricultural modernisation in Central Asia should entail returning water to the Aral Sea to gradually ease the Aral Sea crisis. The authors argue that China's recent proposal to construct a Silk Road Economic Belt provides an opportunity for initiating effective water governance of the Aral Sea, as corroborated in their framework and model. The authors recommend the development of a "green Silk Road Economic Zone" as a cooperative and sustainable joint initiative of the countries concerned that would benefit Central Asia and China, as well as the Aral Sea.