Commitment Model Research Articles

Decision-Making under Group Commitment

Coordination is essential for establishing and sustaining teamwork. Agents in a team must agree on their tasks and plans, and thus, group decision-making techniques are necessary to reach agreements in teams. For instance, to agree on a joint task, the agents can provide their preferences for the alternative tasks, and the best alternative could be selected by majority. Previous works assumed that agents only provide their preferences for the alternatives. However, when selecting a joint task for teamwork, it is essential to consider not only the preferences of the agents, but also the probability of the agents being able to execute the task if it is selected. In this paper, we propose a novel model, the decIsion-MAking under Group commItmeNt modEl (IMAGINE), for computing the optimal decision for a team considering several parameters. Each agent provides: (1) the utility of each alternative for the team, (2) the associated cost for the agent by executing the alternative, and (3) the probability that the agent will be able to execute the alternative task. The IMAGINE gathers these data from the agents, as well as the requisite quorum for each alternative task, which is the minimum number of agents required to complete the task successfully. Given this information, the IMAGINE determines the optimal decision for the group. We evaluated the IMAGINE by comparing it to a baseline method that does not consider the quorum requirement. We show that the IMAGINE generally comes up with a better decision than the baseline method and that the higher the quorum, the better the decisions the IMAGINE makes are.

Integrated electricity and gas system modelling with hydrogen injections and gas composition tracking

Despite the direct physical coupling between them, electricity and gas networks were traditionally modelled and operated independently. However, the heavy reliance on gas-fired generators to balance intermittent generation from renewable energy sources (RES), and the promising role of green hydrogen in decarbonising the natural gas system, have prompted a paradigm shift towards integrated electricity and gas system (IEGS) modelling. While many previous studies investigated the role of hydrogen in future low-carbon energy systems, a detailed assessment of hydrogen system integration into the electricity and gas transmission networks is still not addressed. Therefore, this paper presents a novel IEGS model with green hydrogen injections and gas composition tracking. The electricity system is modelled as a unit commitment model, formulated as a mixed-integer linear programming problem, and the gas system is modelled as a steady-state optimal gas flow (OGF). The developed model is demonstrated on two sets of case studies. The first case study validates the proposed OGF methodology on a small meshed gas test network, whereas the second case study demonstrates the applicability of the overall IEGS model with green hydrogen injection on the large-scale, real-world electricity and gas transmission networks of the state of Victoria (Australia). Results show that the proposed methodology can accurately capture the variations in gas flow direction while maintaining the hydrogen molar fraction within limits under hydrogen injections from multiple locations. Moreover, the amount of injected hydrogen not only depends on the level of RES curtailment, but also on local gas network constraints and local demand.

Why Committed Employees May or May Not Engage in UPB: The Central Role of Future Time Perspective

Taking the future time perspective, we proposed and tested a theoretical model of organizational commitment and unethical pro-organizational behavior (UPB) in which affective (organizational) commitment and continuance (organizational) commitment induces different considerations of future consequences, which in turn influence unethical pro-organizational behavior. Based on analyses of one time-lagged field study and one vignette-based experimental study, we found that affective commitment is positively related to consideration of long-term future consequences but continuance commitment is positively related to consideration of short-term immediate consequences. Furthermore, we found a negative indirect relationship between affective commitment and UPB via the mediation of consideration of long-term consequences but a positive indirect relationship between continuance commitment and UPB via the mediation of consideration of short-term consequences. The paper concludes with discussions of theoretical and practical implications.

The economic and reliability impacts of grid-scale storage in a high penetration renewable energy system

• Long-duration, synchronously connected storage systems better support grid inertia. • Building storage in zones with renewable energy increases inertia and decreases cost. • Compressed air energy storage systems generate the highest system value. • Inertia prices do not generate attractive revenues, so other solutions will be needed. • Natural gas peaking plants might become stranded assets when built alongside storage. As variable renewable energy generation in Texas increases over the next decade, flexibility and system inertia needs are likely to increase. Although natural gas peakers and combined cycle plants have met these demands in the past, grid-scale energy storage might be able to provide similar benefits. We compare the capacity for different energy storage technologies to provide grid inertia to maintain grid reliability and meet peak energy demand with a linearly-relaxed unit commitment and dispatch model of the Electric Reliability Council of Texas (ERCOT) grid that features fifteen transmission zones and sub-hourly intervals (i.e. 15 minutes). In this model, three energy storage technologies—Lithium-ion batteries, flywheels, and compressed air energy storage—are represented with different storage durations, ramp rates, and costs. Single-zone, 1 GW penetrations of each energy storage technology were modeled with a renewable energy penetration greater than 50% to identify the transmission zones where energy storage might have the greatest impact on the total cost of energy generation. Then, scenarios with 10 GW of energy storage either divided across the five transmission zones or concentrated in one zone at a time were modeled to analyze the impact of energy storage on inertia prices (reliability support) and total system costs (flexibility support) at scale. Energy storage built in transmission zones with high penetrations of variable renewable energy generation brought about the greatest reductions in system costs, so the 10 GW of storage were divided between five storage zones —transmission zones where building energy storage was most favorable—according to each zone’s economic impact. Our model showed that compressed air energy storage generated the lowest average inertia price and produced the lowest system costs. With deep penetrations of grid-scale energy storage, new peakers built in transmission zones where energy storage was added might become stranded assets in a high renewable energy future. In conclusion, compressed air energy storage systems most effectively supported the grid’s system inertia while simultaneously meeting the grid’s flexibility needs. Therefore, grid-scale energy storage offers a low-carbon solution to the variability of renewable energy generation.

Research on the Relationship Between Cross-Level Motivation, Integrated Emotion, and Virtual Knowledge Community Commitment.

Community commitment is the key to the success of virtual communities. Under the background of virtual knowledge community, based on motivation hierarchy model and integrated emotion theory, this paper takes “motivation-emotion-community commitment” as the main framework, and introduces multiple mediation and regulation functions to establish the relationship model of motivation hierarchy, integrated emotions, and community commitment. The results show that the user motivation follows the hierarchical structure of the layer-by-layer influence from the situational level to the personality level, that is, knowledge-seeking motivation and entertainment-seeking motivation at a situational level will positively affect social- interaction motivation at the contextual level, thereby enhancing user self-efficacy at personality level. Users have abundant integrated emotions toward the virtual knowledge community, namely, satisfaction, attachment, and identity, and such multi-integrated emotional model is more conducive for promoting community commitment of users. At the same time, attachment, identity, and satisfaction have an interactive complement, that is, when satisfaction is low, attachment and identity will complement and strengthen community commitment.

Scheduling heat and power microgrids with storage systems, photovoltaic, wind, geothermal power units and solar heaters

Combined heat and power (CHP) microgrids (MGs) are a set of CHP units, boilers, power-only distributed generation (DG) units and storage systems that simultaneously supply heat and power demand. In this research, the objective is to provide a comprehensive mixed integer linear programming (MILP) model for unit commitment (UC) in CHP MGs including fossil-fueled power-only DGs, boilers, CHP units, photovoltaic, wind and geothermal power units, solar heater, battery charging station (BCS), adjustable thermal loads, battery energy storage (BES) and thermal energy storage (TES) units. In the proposed model, all operational constraints of CHP units, boilers and power-only units such as minimum up/down time and start-up/ shut-down ramp rate limits are considered and the commitment history of generation units prior to operation horizon is considered. In the proposed model, type II CHPs with non-convex feasible operating region (FOR) are used and their non-convex FOR is transformed into two convex FORs. The proposed model is solved with CPLEX solver in general algebraic modeling system (GAMS) which guarantees the achievement of the global optimum. The model is solved for different scenarios wherein the effect of BCS, effect of storage systems as well as the effect of adjustability of loads on MG operation is investigated. According to the results, BES and TES respectively decrease MG operation cost by 7.4% and 1.82%.and BCS adds 20.19% to the MG operation cost. The results also show that with replacement of adjustable thermal loads with evenly distributed loads, MG operation cost increases by 0.6%.

Determining the potential of informal savings groups as a model for formal commitment saving devices

Background: Saving behaviour has attracted research attention over the past 20 years. Typically, individual and household saving rates among low-income groups are inadequate. Research suggests that informal savings groups are effective vehicles for encouraging saving among low-income individuals. Yet little is known about the drivers of positive saving behaviour among informal savings groups, which makes it difficult for formal providers to design interventions that promote higher levels of saving.Aim: This study aimed to explore both the rational and non-rational drivers of saving behaviour among low-income members of informal savings groups, the attributes of informal savings groups that positively influence their collective saving behaviour, and to identify the valued features of savings groups that encourage the adoption of informal commitment saving devices (CSDs).Methods: The study was informed by a literature review followed by field research in which semi-structured interviews were conducted with 10 savings groups and 10 individual members of savings groups. The participants’ perspectives were analysed and compared within the context of behavioural economic theory.Results: The study revealed seven characteristics of informal savings groups that potentially serve as interventions to explain non-rational saving behaviour. It also identified seven features valued by users of informal CSDs (including flexibility, restricted access to savings and no transaction fees) which could be salient to providers of formal CSDs.Conclusion: On the basis of the findings, a behavioural design framework was proposed to inform the design features of formal CSDs that may ensure customer retention and improved saving outcomes.

Optimal Combination Control Technology of Demand Side Resources of Distributed Renewable Energy Power Generation

The paper proposes a new unit commitment model that can promote car-bon emission reduction in distributed renewable energy power systems. Themodel first comprehensively considers the optimal combination of low-carbon demand-side resources such as supply-side resources and demandresponse, electric vehicles, and distributed renewable energy power gener-ation. Secondly, the model unit scheduling rules fully consider the carbonemission target and the economic target and propose a fuzzy dual-objectiveoptimization method that can consider the relative priority of the target. Whensolving the optimization model, we improved the particle swarm optimizationalgorithm. We introduced the “cross” and “mutation” operators in the geneticalgorithm to improve the particle swarm algorithm’s global optimizationcapability. The paper verifies the effectiveness of the model and algorithmthrough the analysis of a ten computer system.

Hubungan Parasosial dan Perilaku Loyalitas Fans dalam Fandom KPop di Indonesia

This paper investigates fandom as a phenomenon of communication science through an interdisciplinary perspective, especially in relation to the psychology discipline of communication and consumer behavior. The researcher seeks to investigate the correlation between parasocial relationships (Parasocial relationships/PSR) and fan loyalty behavior, specifically the consumption behavior of the brands and products associated with their idols. The research will be carried out using survey methods, with PSI Process Scale to measure parasocial relationship variables, and commitment models to measure fan loyalty behavior. From the questionnaires distributed online, 271 valid questionnaires were obtained which were analyzed using mean analysis, correlation test, and cross tabulation analysis. The results showed that there was a significant relationship between parasocial relationships and fan loyalty. The results also show that the closest relationship is shown by the behavioral dimension with the interaction dimension, while the relationship with the lowest score is shown by the relationship between the perceptual-cognitive dimension and desire to acquire.

Spiritual leadership on organizational commitment and organizational commitment on organizational performance

Purpose: This research was administered to investigate the influence of spiritual leadership on organizational commitment and organizational commitment on organizational performance seen through multidimensions where spiritual leadership is in three dimensions namely vision, faith/hope, and altruistic love; organizational commitment in three dimensions namely affective, normative, and continuity, while organizational performance is in two dimensions which are financial and nonfinancial performance. Design/Method: The population selected in this study included 1,422 members of Village Credit Institution (LPD) in Bali Province including the chairman, secretary, and treasurer. Samples were selected by using the probability sampling technique which is a simple random sampling in which the sample size [Formula: see text] was drawn from a population of magnitude [Formula: see text], allowing each unit to have the same chance of being selected. The obtained data were then analyzed using a Structural Equation Modeling based on analysis of moment structure (AMOS), with multidimensions in each research variable. Findings: The results of the analysis show that vision, faith/hope, and altruistic love have a significant influence on affective commitment, normative commitment, and continuity commitment. On the other hand, affective, normative, and continuity commitment share a certain influence on financial performance. However, it is only the normative commitment that influences nonfinancial performance. Originality: The novelty of this research is in the effort to reconstruct the previous research model to obtain a new one that combines two research models; the spiritual leadership model and the A-Three Component Model of Organizational Commitment. The new model is expected to solve the inconsistencies of previous research results and solve various problems related to leadership and organizational commitment as variables that influence LPD performance.

Human resource management practices in creating a committed workforce for fostering knowledge transfer: a theoretical framework

PurposeThis paper aims to review existing literature on the role of human resource management (HRM) practices in nurturing employee’s organisational commitment (OC), which subsequently promoting knowledge transfer (KT) within an organisation and propose a conceptual framework for future empirical research.Design/methodology/approachAn extensive review of existing literature was undertaken in an attempt to build the conceptual model for KT.FindingsThe proposed conceptual framework illustrates the role of OC as a focal mediating mechanism in fostering KT. This paper identifies “high commitment” HRM (HCHRM) (e.g. staffing, job design, training and development, performance appraisal and reward system) as the factors influencing the development of OC, which subsequently affecting KT (i.e. knowledge sharing and application). Also, this paper integrates the potential moderating roles of leader-member exchange (LMX) between HCHRM practices-OC, as well as information and communication technology support in the OC-KT linkage into the proposed framework.Research limitations/implicationsThis paper presents a comprehensive view of fostering KT. However, the major limitation of this paper is that it remains at a conceptual level. Further empirical investigations would be helpful to test propositions, hence validating the proposed conceptual framework.Practical implicationsThe proposed conceptual framework could serve as practical guidance for managers and/or practitioners in developing policies that will facilitate KT in business organisations.Originality/valueWhile KT is often viewed as a single phenomenon, this paper considers the KT into two components (i.e, sharing and application) in accordance with the practice-based perspective on knowledge and behavioural approach to KT. In addition, the adoption of the general workplace commitment model in conceptualising KT could further validate its applicability in knowledge management research. Also, the integration of LMX as a moderator in the proposed framework could contribute to the scant research on LMX-related moderation models upon validation.

Unit Commitment with Ancillary Services in a Day-Ahead Power Market

This paper integrates Discrete Particle Swarm Optimization (DPSO) and Sequential Quadratic Programming (SQP) to propose a DPSO-SQP method for solving unit commitment problems for ancillary services. Through analysis of ancillary services, including Automatic Generation Control (AGC), Real Spinning Reserve (RSR), and Supplemental Reserve (SR), the cost model of unit commitment was developed. With the requirements of energy balance, ancillary services, and operating constraints considered, DPSO-PSO was used to calculate the energy supply of each source, including the associated AGC, RSR, and SR, and the operating cost of a day-ahead power market was calculated. A study case using the real data from thermal units of Taipower Company (TPC) and Independent Power Producers (IPPs) demonstrated effective results for the “summer” and “non-summer” seasons, as classified by TPC for the two charging rates. According to the test cases in this research, costs without ancillary services in non-summer and summer seasons are higher than those with ancillary services. The simulation results are also compared with the Genetic Algorithm (GA), Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Simulated Annealing (SA). DPSO-PSO shows effectiveness in solving unit commitment problems with enhanced sorting efficiency, and a higher probability of reaching the global optimum.

Understanding volunteer commitment to a project: testing a conceptual model

PurposeIn Australia, it is estimated that volunteers provide over $14.6 billion of unpaid labour to not-for-profit organisations. Much of the work that volunteers undertake is within a project context, yet the impact of a project and its environment on volunteer commitment is unknown. A conceptual model proposes three categories of factors that impact volunteer commitment to a project: purposeful, emotional and contextual. The purpose of this research is to empirically explore the conceptual model of volunteer commitment with volunteers working on projects in order to seek support for, and refine, the model.Design/methodology/approachThe research design was exploratory and Q methodology was used as a framework to collect and analyse data. Forty-one Australian volunteers engaged in project-based tasks participated in the study.FindingsRefinement of the initial conceptual model of volunteer commitment is required. The three categories that influence volunteer commitment to a project should be labelled “my contribution”, “relationships” and “the project”. The revised model shows early evidence that the project itself is the main commitment building factor.Originality/valueWhilst volunteer retention is not a new field of knowledge, research such as this further informs not-for-profit organisations in their volunteer recruitment and retention practices.

Clinical Ethics Consultation during the First COVID-19 Lock Down in France: The “Commitment Model”: Balancing General Questions and Individual Cases

During the first outbreak of COVID-19, the French governmental advisory council on bioethics suggested the need to support healthcare providers with ad hoc "ethical support units." Several units engaged in such endeavors across the country. This article outlines some methodological considerations made by the Cochin Hospital Clinical Ethics Center (the Cec). The Cec was founded in 2002 to provide clinical ethics support services. While its approach was inspired by North American models, it was shaped by and adapted to the French context. This approach is called the "Commitment Model," as it draws upon societal engagement in all phases of its service and places the perspectives of individual patients at its core. During the first outbreak of COVID-19 pandemic, the Cec received a greater number of requests about recurring care practices or ethical guidelines and recommendations than single clinical ethics dilemmas. Through the presentation of an illustrative consultation, this article describes how, while the Cec made some adjustments to its service for the emergency situation, it preserved its case-by-case approach rather than engaging in what it calls organizational and institutional ethics. Such an approach allowed the Cec to refocus attention to individual patients and their unique circumstances and to support decision makers by the use of case-by-case, problematized, ethical reflections.

The Effect Of Leadership In Education Administrative Learning And Knowledge On Organization Commitments Of Early Children Education Unit In Medan City

Along with the transition from the New order era to the Reformation era, the central government is committed to providing regional autonomy to district and city governments to manage regional potential, including the potential for education. After the central government gave regional autonomy to district and city governments, the Medan City Government gave autonomy to the head of the Early Childhood Education unit to manage the potential of Early Childhood Education to the maximum, but in reality the management was not optimal. The purpose of this study is to find a model of organizational commitment and to determine the influence between research variables. This research method is a quantitative research method using a survey approach. The study population was 750 people and the sample of this study was 238 people with an error rate of 5%. Sampling is non-probability sampling with a purposive sampling technique based on the provisions of the sample from the population developed by Isaac and Michael. The data collection technique for this research is a questionnaire instrument using a Likert scale and a test instrument using Merriam Webster's New Collegiate Distionary technique. The results of the descriptive analysis show that 235 or 98.74% of the Educational Administrative Knowledge variable tends to be in the low category, while the other variables tend to be in the high category. Furthermore, the results of the calculation of the total direct effect show that the Educational Administrative Knowledge variable on the Organizational Commitment variable is 0.2642 or 26.42%, while the total effect of other variables is low. Furthermore, the direct and indirect proportional, sporious and unanalyzed effect caused by these three variables is 66.02% and the influence of other variables is 33.98%. Furthermore, the research results of the path coefficient test show that all the path diagram coefficients are significant. Furthermore, the results of model testing indicate that the proposed model is fit with empirical data. Therefore, based on the results of this study it is suggested that the Head of the Medan City Education Office can apply this model so that 66.02% of the organizational commitment of the head of the Children's Education unit can be maximally realized.

Advantages of Applying Large-Scale Energy Storage for Load-Generation Balancing

The continuous development of energy storage (ES) technologies and their wider utilization in modern power systems are becoming more and more visible. ES is used for a variety of applications ranging from price arbitrage, voltage and frequency regulation, reserves provision, black-starting and renewable energy sources (RESs), supporting load-generation balancing. The cost of ES technologies remains high; nevertheless, future decreases are expected. As the most profitable and technically effective solutions are continuously sought, this article presents the results of the analyses which through the created unit commitment and dispatch optimization model examines the use of ES as support for load-generation balancing. The performed simulations based on various scenarios show a possibility to reduce the number of starting-up centrally dispatched generating units (CDGUs) required to satisfy the electricity demand, which results in the facilitation of load-generation balancing for transmission system operators (TSOs). The barriers that should be encountered to improving the proposed use of ES were also identified. The presented solution may be suitable for further development of renewables and, in light of strict climate and energy policies, may lead to lower utilization of large-scale power generating units required to maintain proper operation of power systems.

Profiles of global and target-specific work commitments: Why compatibility is better and how to achieve it

Employees can develop multiple commitments at work. These commitments can combine in different ways, with implications for organizations and employees themselves. In this study we conducted latent profile analyses (LPA) to identify different configurations of commitment to the organization, supervisor, work group, and citizens among a sample of employees from a police organization (N = 2090). The LPA were estimated while differentiating between employees' global and target-specific commitments in accordance with Perreira et al.'s (2018) hierarchical model of commitment. We identified six profiles, which demonstrated differential relations with theoretical antecedents (organizational support and values fit) and outcomes (turnover intention, organizational citizenship behavior, and well-being). The optimal profile from an outcome perspective was characterized by a strong global commitment accompanied by balanced above-average commitments to the four specific targets. Employees with this profile also reported the greatest support and values fit. The remaining profiles with lower global commitment and differentiated commitments to specific targets demonstrated more varied relations with both the antecedents and outcomes. Implications for theory pertaining to the compatibility and combined effects of multiple commitments are discussed along with implications for management.

A Distributionally Robust AC Network-Constrained Unit Commitment

This paper presents a distributionally robust network-constrained unit commitment (DR-NCUC) model considering AC network modeling and uncertainties of demands and renewable productions. The proposed model characterizes uncertain parameters using a data-driven ambiguity set constructed by training samples. The non-convex AC power flow equations are approximated by convex quadratic and McCormick relaxations. Since the proposed min-max-min DR-NCUC problem cannot be solved directly by available solvers, a new decomposition algorithm with proof of convergence is reported in this paper. The master problem of this algorithm is solved using both primal and dual cuts, while the max-min sub-problem is solved using the primal-dual hybrid gradient method, obviating the need for using duality theory. Also, an active set strategy is proposed to enhance the tractability of the decomposition algorithm by ignoring the subset of inactive constraints. The proposed model is applied to a 6-bus test system and the IEEE 118-bus test system under different conditions. These case studies illustrate the performance of the proposed DR-NCUC model to characterize uncertainties and the superiority of the proposed decomposition algorithm over other decomposition approaches using either primal or dual cuts.

Three-Stage Robust Unit Commitment Considering Decreasing Uncertainty in Wind Power Forecasting

To ensure powersupply–demand balance under the increasing penetration of wind power, the existing nonanticipative robust unit commitment models (NRUCs) co-optimize the commitment status and the dispatch policy of power sources. Exploiting the fact that the wind power uncertainty reduces over time, this article proposes an NRUC where determining the dispatch policy is delayed until the uncertainty decreases. The proposed NRUC features three decision-making problems sequentially solved under different degrees of uncertainty. The first decision-making problem is formulated as an intractable three-stage robust optimization problem. To solve this problem, a suboptimal approach is developed where a constraint is imposed on the dispatch policy so that the transmission capacity constraint is met regardless of the dispatch level. Results of simulations on a 24-bus and a 300-bus test system show that the proposed NRUC outperforms existing NRUCs regarding feasibility and optimality under currently severe but decreasing wind power uncertainty.

Stochastic Market Operation for Coordinated Transmission and Distribution Systems

This paper proposes a three-stage unit commitment model for the market operation of transmission and distribution coordination under the uncertainties of renewable generation and demand variations. The first stage is for the independent system operator (ISO) that determines the commitment decisions of the transmission-level generators and the distribution-level system reconfiguration; the second stage optimizes the transmission economic dispatch; then distribution system operators (DSOs) in the third stage perform their economic dispatch and exchange information with the ISO at the boundary nodes. Between the transmission and distribution networks, not only conventional thermal generators but renewables and variable demands are considered, which are tackled via a multi-stage stochastic programming approach. The model adopts a convexified AC branch flow formulation in the distribution system. We devise a generalized nested L-shaped algorithm to solve the proposed framework in an efficient manner. Numerical experiments on multi-scale test systems corroborate the efficacy of this strategy.