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The purpose of this paper is to explore the impact of the Kijima Type II imperfect repair model on the availability of repairable systems (RS). Since many individuals are interested in measuring the extent to which the system will be available after it has been run for a long time, the specific interest in this study is in the steady-state (limiting) availability behavior of such systems. Furthermore, the authors study the impact of age-based preventive maintenance (PM) on the RS performance.

Because of the complexity of the underlying assumptions of the Kijima Type II model, the authors use simulation modeling to estimate the system availability. Based on preliminary simulation results, the availability function achieves a steady-state value greater than zero. The system steady-state availability is then estimated from the simulation output by computing the average of the availability estimates beyond the initial transient period. Next, the authors develop a meta-model to convert the system reliability and maintainability parameters into the coefficients of the limiting availability estimate without the simulation effort. Using a circumscribed central composite experimental design, the authors confirm the accuracy of the meta-model.

The results show that the meta-model is robust, and provides good estimates of the system limiting availability. Also, the authors find that when using a Kijima Type II model for a system repair process, age-based PM can improve the steady-state availability value. Therefore, an optimal age-based PM policy that maximizes the system’s steady-state availability can be identified.

In practice, it is important to study the system steady-state availability because many individuals, i.e. engineers, are more interested in measuring the extent to which the system will be available after it has been run for a long time. Therefore, this study represents a significant addition to the body of knowledge related to virtual age modeling, in that it incorporates a Kijima type II model and considers system steady-state availability.

While steady-state analysis is useful, it does not consider the inherent transient characteristics of repairable systems' behavior, especially in systems that have relatively short life spans, or when their transient behavior is of special concern such as the motivating example used in this paper, military systems. Therefore, a maintenance policy that considers both transient and steady-state availability and aims to achieve the best trade-off between high steady-state availability and rapid stabilization is essential.

This paper studies the transient behavior of system availability under the Kijima Type II virtual age model. While such systems achieve steady-state availability, and it has been proved that deploying preventive maintenance (PM) can significantly improve its steady-state availability, this improvement often comes at the price of longer and increased fluctuating transient behavior, which affects overall system performance. The authors present a methodology that identifies the optimal PM policy that achieves the best trade-off between high steady-state availability and rapid stabilization based on cost-availability analysis.

When the proposed simulation-based optimization and cost analysis methodology is applied to the motivating example, it produces an optimal PM policy that achieves an availability–variability balance between transient and steady-state system behaviors. The optimal PM policy produces a notably lower availability coefficient of variation (by 11.5%), while at the same time suffering a negligible limiting availability loss of only 0.3%. The new optimal PM policy also provides cost savings of about 5% in total maintenance cost. The performed sensitivity analysis shows that the system's optimal maintenance cost is sensitive to the repair time, the shape parameter of the Weibull distribution and the downtime cost, but is robust with respect to changes in the remaining parameters.

Most of the current maintenance models emphasize the steady-state behavior of availability and neglect its transient behavior. For some systems, using steady-state availability as the sole metric for performance is not adequate, especially in systems that have relatively short life spans or when their transient behavior affects the overall performance. However, little work has been done on the transient analysis of such systems. In this paper, the authors aim to fill this gap by emphasizing such systems and applications where transient behavior is of critical importance to efficiently optimize system performance. The authors use military systems as a motivating example.

A common tactic employed by retailers to enhance shoppers' purchase intentions is to promote a special offer product for purchase only at certain selected stores. This research aimed to identify the specific processes by which restricting the outlets drives intention to buy.

Three between-subjects experiments examined the effect on purchasing intention of outlet selectivity, as mediated by participants' perceptions of temporal accessibility and geographic accessibility (study 1), and investigated the extent to which decisions to buy might be moderated by the limited number of stores where the item would be available (study 2) and by “limited market,” in which the right to buy a product is restricted to a limited set of consumers (study 3).

The study findings are that joint consideration of the perceived temporal and geographic accessibility of a product generates two possible ways in which availability limited to certain stores makes the product seem hard to get and motivates consumer purchase decisions. However, such effect is confined to conditions in which the distribution of those outlets is low-density. When there was no change in those scores if restrictions were lower, participants' responsiveness to decreased availability was significantly raised by announcing that the chance to buy the product is further limited to “eligible” customers.

This research focused on consumer responses to outlet selectivity, a branch of inquiry that treats an overlooked facet of limited availability and provides useful assistance for developing methods to stimulate consumers' desire to purchase.

Discusses the relationship between plant availability and maintenance expenditure and their limiting features. Achieving higher plant availability always necessitates a higher maintenance budget and may not be economically feasible in many cases. Through a mathematical modelling the variation of net income with respect to plant availability has been studied and the limiting availability values have been established. Expressions for optimum availability and maintenance cost have also been obtained. An illustrative example has been worked out.

The system encountering dormant failure subject to sequential inspections is modeled and the emphasis is made on determining the availability and long-run average cost rate for the model. The derived results are then utilized to obtain the optimal inspection period minimizing the cost.

Explicitly, a system with a functional and a failed state is taken into account. Inspections are performed to reveal the dormant failures and are assumed to be carried out at time T, T + aT, T + aT+a² T, … where 0 < a = 1 in each cycle. Perfect repairs taking random times are performed if the system is found in a failed state during any inspection.

Some theorems on the point availability, limiting availability and long-run average cost rate are obtained in the study. An illustration is shown to explain the results obtained in the proposed work. The effect of inspection time on the availability and cost rate is also analyzed graphically.

The availability and cost rate for a system with dormant failure under a sequential inspection policy are figured out unlike previous research.

In certain environments, the system may not fail completely, but undergoes degradation, and the system productivity might decrease. Meanwhile, at the same time, the system may be vulnerable to shocks. A single-unit system prone to degradation and shocks is proposed in this study, and emphasis is placed upon determining its availability and cost rate.

The considered single-unit system is expected to have three states, namely, normal, degraded and failed. As the system enters the degraded state, it is said to be partially failed. The degraded state incurs higher degradation than the normal state and is more prone to shocks. Inspections are used to determine the state and failure type of the system. Inspections are predetermined to be carried out sequentially at time I, I+aI, I+aI+a2I,… where 0 < a ≤ 1, until the detection of degradation/failure. Perfect repairs are conducted instantly on spotting the partial/complete failure. Two cases have been considered of repair taking constant times and random times.

Explicit results on the reliability, availability (both point and limiting availability) and long-run average cost rate (LRACR) of a sequentially inspected single-unit system prone to degradation and shocks under constant and random repair times are given. Numerical example of an oil pipeline system is taken to clarify the acquired results.

A sequentially inspected single-unit system prone to degradation and shock is studied unlike done previously.

Prior to e‐commerce, tourists could only purchase souvenirs at a destination. The goal of this research is to develop and test a theory to explain how adding a retail web site affects tourists' decision‐making for souvenir purchases.

The researcher conducts two experiments using scenarios to simulate a souvenir purchase. The researcher manipulates item type and web site availability, and then measures purchase intent, attitudes toward the souvenir, and regret.

Purchase limitation increases initial purchase intent by increasing the souvenir's reminder value, regardless of item type. Non‐purchase regrets are greater than purchase regrets, which in turn increases purchase intent at a later time.

The stimuli are necklaces, and although the findings do not show gender effects, the stimuli could limit the generalizability to other souvenir types. The research tests hypotheses using scenarios and less‐experienced travelers. Future research should examine different types of souvenirs in a naturalistic setting.

Retailers should not mention web sites until after a tourist decides not to buy in‐store and should do so subtly.

This research contributes to souvenir research by identifying a purchase limitation, available in‐store only, as a new determinant of a souvenir's reminder value. The research also contributes to scarcity research by identifying reminder value as a new and qualitatively different type of valuation affected by scarcity. Lastly, the research extends the regret literature by reversing inaction inertia at a later purchase opportunity while maintaining a regret minimization goal.

This paper aims to assess the design of national-level flexible work arrangement (FWA) policies, evaluating their potential to serve as an effective resource for employees to work flexibly depending on how they set the stage for flexibility claims that will be subject to industrial and workplace dynamics.

Using a capability approach, the authors conceptualize and operationalize two aspects of FWA policy design, namely accessibility and availability. The authors' analysis allows for an understanding of how the availability and accessibility of national FWA policies explicitly and implicitly restrict or facilitate flexible working in a structural manner. The study focuses on countries with differing working time regimes and gender norms on work and care: the Netherlands, Spain and Slovenia.

The authors' findings highlight how FWA accessibility is broader when national policy is specified and FWA availability is not conditional to care. In Spain and Slovenia, access to FWAs depends on whether employees have care responsibilities, which reduces accessibility and reinforces gender imbalances in care provision. In contrast, the Netherlands provides FWAs universally, resulting in wider availability and accessibility of FWAs for employees regardless of their care responsibilities. Despite this universal provision, gender imbalances remain.

The originality of this paper lies in its conceptualization and operationalization of FWAs at the national level using a capability approach. The study adds to the existing literature on flexible working and provides insights for policymakers to design more effective FWAs.

Many fashion brands employ growth strategies that involve strategically aligning with a retailer to offer exclusive co-brands that vary in duration and perceived fit. While growth and publicity are enticing, pursuing collaboration may change consumers' evaluation of the brand. Utilising commodity and categorisation theory, this research tests how a brand may successfully approach a co-brand with a retailer.

Three experimental studies manipulate and test the effect of co-brand duration (limited edition vs ongoing) (Study 1), the degree of brand-retailer fit (high vs low) (Study 2), and its combined effect (Study 3) on changes in consumers' brand evaluation.

Results reveal that consumers' evaluations of brands become more favourable when: (1) brand-retailer co-brand make products available on a limited edition (vs ongoing) basis (Study 1), (2) consumers perceive a high (vs low) degree of brand-retailer fit (Study 2) and (3) both conditions are true (Study 3).

In light of commodity and categorisation theory, this study helps to understand the effectiveness of a brand-retailer co-branding strategy.

To increase brand evaluations, brands should engage in a limited edition strategy, rather than ongoing when collaborating with retailers. It is also important to select an appropriately fitting retailer for a strategic partnership when creating a co-brand.

While previous studies highlight the importance of perceived fit upon extension, perceived fit between brand and retailer co-brand had yet to be investigated. Additionally, this research investigates changes in brand evaluations to more accurately understand how co-branding strategies impact the brand.

In repetitive projects, repetition offers more possibilities for activity scheduling at the sub-activity level. However, existing resource-constrained repetitive scheduling problem (RCRSP) models assume that there is only one sequence in performing the sub-activities of each activity, resulting in an inefficient resource allocation. This paper proposes a novel repetitive scheduling model for solving RCRSP with soft logic.

In this paper, a constraint programming model is developed to solve the RCRSP using soft logic, aiming at the possible relationship between parallel execution, orderly execution or partial parallel and partial orderly execution of different sub activities of the same activity in repetitive projects. The proposed model integrated crew assignment strategies and allowed continuous or fragmented execution.

When solving RCRSP, it is necessary to take soft logic into account. If managers only consider the fixed logic between sub-activities, they are likely to develop a delayed schedule. The practicality and effectiveness of the model were verified by a housing project based on eight different scenarios. The results showed that the constraint programming model outperformed its equivalent mathematical model in terms of solving speed and solution quality.

Available studies assume a fixed logic between sub-activities of the same activity in repetitive projects. However, there is no fixed construction sequence between sub-activities for some projects, e.g. hotel renovation projects. Therefore, this paper considers the soft logic relationship between sub-activities and investigates how to make the objective optimal without violating the resource availability constraint.