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The purpose of this paper is to extract the optimal time allocation of weekly hours among work, sleep, sports, and internet use for 16 different demographic groups.

The agent wishes to minimize the gap between his or her actual and optimal allocation for each activity. His or her actual allocation of time for each activity is affected by his or her allocations for other activities and by exogenous variables. A system of simultaneous equations is constructed, with the four levels of time allocation as the endogenous variables. Using a cross-section database of 928 Israel residents, the authors estimate the system and predict the actual allocation of time. Inserting the forecast equations into the agents’ target function and differentiating by each actual time allocation, the authors extract the optimal time allocation for 16 different demographic groups.

The results make it clear that the optimal desired level of sleep hours is highest among married Jews and non-Jews of both genders, whereas the desired level of work hours is highest among female non-Jews whose children have a computer and among married males, Jewish and non-Jewish alike. Female Jews and non-Jews wish to allocate the most hours to internet use, while married males of both nationalities wish to allocate the fewest. The desired level of sports hours is highest among married and non-married Jews. Examining the effect of age on time allocation, the main findings show a very significant cutback in allocation of hours for sleep among agents at age 20.8 and an increase of about 2.5 hours of sleep among agents aged 60.8, both relative to those aged 40.8.

The original model presented here brings a non-traditional approach to the analysis of time allocation. The authors believe that each agent wishes that he or she could allocate his or her time for personal benefit on the basis of a theoretical apportionment determined on the basis of experience and tendencies. Even though an agent’s actual time allocation may be affected by many factors, he or she still has a sense of disutility when the actual allocation deviates from selected optimum.

Investigates the trade‐off between the average throughput rate and the average systems time using kanban discipline. Considers a multistage serial production line system with materials in the system controlled by kanban discipline. Presents simulation results to evaluate the production system performance in terms of the average throughput rate and the average system time for a fixed total number of kanbans over a given number of serial workstations. Constructs and compares efficient allocation sets for three and four workstations that are generated by kanban discipline for two processing time distributions, namely, uniform and exponential distributions. Based on the simulation results from three and four work‐stations, develops a general design rule to maximize the average throughput rate and to minimize the average system time. Analyses five and six workstations using the general design rule. Tests the validity of the general design rule by considering five and six workstations with a different number of kanbans. The results show that most of the efficient sets generated by the design rule are identical to those generated by enumerating all combinations of kanban allocations. However, using the general design rule reduces the simulation work tremendously.

A variety of buffer allocation methods exist to distribute an aggregated time buffer among project activities. However, these methods do not pay simultaneous attention to two key attributes of disruptive events that may occur during the construction phase: probability and impact. This paper fills this research gap by developing a buffer allocation method that takes into account the synergistic impact of these two attributes on project activities.

This paper develops a three-step method, calculating the probability that project activities are disrupted in the first step, followed by measuring the potential impact of disruption on project activities, and then proposing a risk-informed buffer allocation index by simultaneously integrating probability and impact outputs from the first two steps.

The proposed method provides more accurate results by sidestepping the shortcomings of conventional fuzzy-based and simulation-based methods that are purely based on expert judgments or historical precedence. Further, the paper provides decision-makers with a buffer allocation method that helps in developing cost-effective buffering and backup strategies by prioritizing project activities and their required resources.

This paper develops a risk-informed buffer allocation method that differs from those already available. The simultaneous pursuit of the probability and impact of disruptions distinguishes our method from conventional buffer allocation methods. Further, this paper intertwines the research domains of complexity science and construction management by performing centrality analysis and incorporating a key attribute of project complexity (i.e. the interconnectedness between project activities) into the process for buffer allocation.

The negative framing and context of performance has received significant attention in decision research. At the same time, historical success appears to reduce openness to radical learning and the exploration of new, alternative approaches. This study elicited individuals’ implicit paradigms within a historically successful, progressive decision situation. Individuals, given the opportunity to re‐allocate time, gave more time to below performing ventures and took time away from above performing ventures. “Illusion of control” and “satisficing” theories were used to explain the individuals’ implicit paradigms.

Multi-robot coalition formation (MRCF) refers to the formation of robot coalitions against complex tasks requiring multiple robots for execution. Situations, where the robots have to participate in multiple coalitions over time due to a large number of tasks, are called Time-extended MRCF. While being NP-hard, time-extended MRCF also holds the possibility of resource deadlocks due to any cyclic hold-and-wait conditions among the coalitions. Existing schemes compromise on solution quality to form workable, deadlock-free coalitions through instantaneous or incremental allocations.

This paper presents an evolutionary algorithm (EA)-based task allocation framework for improved, deadlock-free solutions against time-extended MRCF. The framework simultaneously allocates multiple tasks, allowing the robots to participate in multiple coalitions within their schedule. A directed acyclic graph–based representation of robot plans is used for deadlock detection and avoidance.

Allowing the robots to participate in multiple coalitions within their schedule, significantly improves the allocation quality. The improved allocation quality of the EA is validated against two auction schemes inspired by the literature.

To the best of the author's knowledge, this is the first framework which simultaneously considers multiple MR tasks for deadlock-free allocation while allowing the robots to participate in multiple coalitions within their plans.

The retail revolution swing from traditional distribution to e-tailing services and unprecedented increase in internet adoption insist practitioners to diversely plan warehousing strategies. More than practically required storage space has been identified as wastes, and also it does not improve performance. An organized framework integrating storage design policies, operational performance and customer value improvement for retail-distribution management is lacking. Therefore, the purpose of this paper is to develop broad guidelines to design the “just-right” amount of forward area, i.e., “lean buffer” answering the following questions: “What should be lean buffer size? How effective the forward area is? As per demand variations, which storage waste (SKU) should be allocated with how much storage space? What is the amount of storage waste (SW)? How smooth the material flow is in between reserve-forward area?” for storage allocation in cosmetics distribution centers.

After forecasting static storage allocation between two planning horizons, if a particular SKU is less or non-moving, then it will cause SW, as the occupied location can be utilized by other competing SKUs, and also it impedes material flow for an instance. A dynamically efficient and self-adaptive, knapsack instance based heuristics is developed in order to make effective storage utilization.

The existing state-of-the-art under study is supported with a distribution center case, and the study investigates the need of a model adopting lean management approach in storage allocation policies along with test results in LINGO. The sensitivity analysis describes the impact of varying demand and buffer size on performance. The results are compared with uniform and exponential distributed demands, and findings reveal that the proposed heuristics improves efficiency and reduce SWs in forward-reserve area.

The presented model demonstrates a novel thinking of lean adoption in designing storage allocation strategy and its performance measures while reducing wastes and improving customer value. Future research issues are highlighted, which may be of great help to the researchers who would like to explore the emerging field of lean adoption for sustainable retail and distribution operations.

Allocation of individuals' resources among multiple goals is an increasingly prominent theoretical and practical issue. Despite several theoretical perspectives that highlight the potential role of affect in this resource allocation process, empirical work on the topic is quite limited with little focus on the activation dimension of affect. This study aimed to provide further insight into this issue.

The current research explored the role of the activation dimension of affect in a multiple-goal environment. Specifically, 118 individuals participated in a 21-day longitudinal study in which they reported on affect and resource allocation related to two real-life goals.

Multilevel-modeling analyses indicated that activation positively relates to allocation of resources (effort, intended effort, and intended time devoted to a goal). The results also illustrate that task-related negative valence is a significant predictor for two of the three indicators of resource allocation (intended effort was the exception).

This research informs theory and practice at the intersection of emotion and work motivation by investigating a relatively understudied dimension of affect and provides results that help clarify the role of affect during the pursuit of multiple, competing goals.

Research, teaching and service are usually regarded as an academic’s main responsibilities. One of the most hotly debated issues in the international arena is what academics should devote their time to, since time is a limited commodity for academics and tradeoffs are necessary. The aim of this study was to establish the perceptions of South African accounting academics with regard to how they spend their academic time. Managers can use this information in efficiency planning and individuals can use this information to compare their effort allocations to those of their colleagues. A descriptive study was conducted in which a questionnaire was used to test, inter alia, the perception of how South African accounting academics at every SAICA‐accredited university use their academic time. Nine activities were tested that relate to management, teaching, research and service. It was found that South African accounting academics spent 10% of their time on management tasks, 78% on teaching, 5% on research and 7% on service. Half (50%, median) of the respondents spent 5% of their time on management tasks, 65% on tuition and 5% on enhancing their own knowledge. It appears as if excessive time is spent on teaching, whilst inadequate time is allocated to research activities. Time spent on service activities appears to be reasonable. An Accounting academic’s qualification appears to be the best indicator against which to measure time allocation. A clear pattern emerged in a comparison between qualification and time allocation in seven of the nine activities tested. The higher the respondent’s qualification, the more time is spent on management tasks, research for both non‐accredited and accredited journals, acting as external examiner and community work. The inverse is true for subject‐related administration and tuition.

This paper aims to present a concise review on the variant state-of-the-art dynamic task allocation strategies. It presents a thorough discussion about the existing dynamic task allocation strategies mainly with respect to the problem application, constraints, objective functions and uncertainty handling methods.

This paper briefs the introduction of multi-robot dynamic task allocation problem and discloses the challenges that exist in real-world dynamic task allocation problems. Numerous task allocation strategies are discussed in this paper, and it establishes the characteristics features between them in a qualitative manner. This paper also exhibits the existing research gaps and conducive future research directions in dynamic task allocation for multiple mobile robot systems.

This paper concerns the objective functions, robustness, task allocation time, completion time, and task reallocation feature for performance analysis of different task allocation strategies. It prescribes suitable real-world applications for variant task allocation strategies and identifies the challenges to be resolved in multi-robot task allocation strategies.

This paper provides a comprehensive review of dynamic task allocation strategies and incites the salient research directions to the researchers in multi-robot dynamic task allocation problems. This paper aims to summarize the latest approaches in the application of exploration problems.

This article aims to explore three facets of the historical performance of a sample of actively managed unit trusts available to New Zealand investors: asset allocation, style analysis, and return attribution.

Because New Zealand does not require unit trusts to disclose their security holdings, the paper used returns‐based style analysis to infer how these trusts have allocated their funds among asset classes.

The research has found that, for unit trusts available to New Zealand investors, asset allocation can explain a significant amount of the differences in return across time and between trusts. Across time, asset allocation accounts for about 80 per cent of the variation in actual return. Between trusts, asset allocation explains about 60 per cent of the variation in returns. From either perspective, the choice of asset allocation is an important factor in explaining returns.

The paper suggests that active management barely earns its fees and that passive investments might do as well or better.