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Purpose: The purpose of this paper is to describe a decision support tool based on various types of contracts in a two‐level supply chain. A supply chain (SC) consists of disparate but interdependent members, dependent on each other to manage various resources (inventory, money and information). The conflicting objectives between these members may cause uncertainties in supply and demand, which can be managed by adopting coordination with the help of contracts (such as buyback, revenue sharing and quantity flexibility). Design/methodology/approach: A decision support tool for SC coordination using contracts (DSTSCCC) has been developed to explore the applicability of contracts and to compare different types of contracts in various situations. The DSTSCC is comprised of an analytical module, which is an extension of the classical newsboy problem and a simulation module. Findings: DSTSCCC helps in determining decision variables for different scenarios of contracts in the best interest of all SC members as well as whole SC. Practical implications: DSTSCCC is a simple‐to‐use and easy‐to‐implement decision making tool which helps in taking decisions prior to the actual start of SC activities. The prior decisions may help to handle future exceptions. SC members may jointly select the most profitable contract to share risks and rewards. Originality/value: DSTSCCC comprised of analytical module and simulation module presents an Integrative framework which cannot be dealt in isolation. The output of analytical module becomes input for simulation to quantify performance measures. The improvement in performance measures after satisfying the objectives of all SC members helps in realizing coordination in SC.

Energy use in buildings needs to be reduced to meet political goals; however, reducing energy use can conflict with heritage preservation objectives. The purpose of this paper is to demonstrate a method that combines quantitative and qualitative analyses of the potential of energy savings in an historic building stock. Specifically, this study examines how requirements of historic building preservation affect the energy saving potential on a building stock level.

Using the World Heritage Town of Visby, Sweden as a case study, this paper illustrates a step-by-step method as a basis for implementing energy savings techniques in an historic building stock. The method contains the following steps: categorisation of a building stock, definition of restriction levels for energy renovation scenarios and life cycle costs optimisation of energy measures in archetype buildings representing the building stock. Finally, this study analyses how different energy renovation strategies will impact heritage values and energy saving potentials for different categories of buildings.

The outcome of the study is twofold: first, the method has been tested and proven useful and second, the results from the application of the method have been used to formulate differentiated energy renovation strategies for the case study.

The study shows that it is possible to integrate techno-economic analysis with assessment of heritage values in a given building stock in order to facilitate a strategic discussion balancing policies and targets for energy savings with policies for the preservation of heritage values. The findings will contribute to sounder policy development and planning for historic building stocks.

This paper considers carbon abatement in a competitive supply chain that is composed of a manufacturer and two retailers under vertical shareholding. The authors emphasize the equilibrium decision problem of stakeholders under vertical shareholding and different power structures.

A game-theoretic approach was used to probe the influence of power structure and retailer competition on manufacturers' carbon abatement under vertical shareholding. The carbon abatement decisions, environmental imp4cacts (EIs) and social welfare (SW) of different scenarios under vertical shareholding are obtained.

The findings show that manufacturers are preferable to carbon abatement and capture optimal profits when shareholding is above a threshold under the retailer power equilibrium, but they may exert a worse negative impact on the environment. The dominant position of the held retailer is not always favorable to capturing the optimal SW and mitigating EIs. In addition, under the combined effect of competition level and shareholding, retailer power equilibrium scenarios are more favorable to improving SW and reducing EIs.

This paper inspects the combined influence of retailer competition and power structure on manufacturers' carbon abatement. Distinguishing from previous literature, the authors also consider the impact of vertical shareholding and consumer preferences. In addition, the authors analyze the SW and EIs in different scenarios.

The paper aims to investigate the optimal service quality and pricing for a mobile application (App) service supply chain (SSC) and analyze the impact of network externality on App SSC members' utilities. After that, the corresponding management inspirations and suggestions are put forward.

The paper developed a SSC consisted of an App service supplier and an App service operator. Our models aim to maximize the SSC members' utilities. By utilizing the game theory, equilibrium solutions are obtained. Numerical examples are used to manifest the impact of parameters on decisions by Matlab. Some management enlightenment could be obtained by comparison analysis.

Cooperating with an App service operator that asks for a lower revenue sharing ratio will enable the App service supplier to have sufficient funds to provide high-quality update service. With the increase of network externality, adopting a high-quality service strategy can bring higher utility to the App service operator and users. Pouring attention into consumer welfare moderately will improve the App service supplier's utility. Scenario CRS can achieve a win–win goal for App SSC members and consumers.

The innovations of this paper are as follows: Firstly, the authors investigate the optimal service quality and pricing for the App SSC, which has been discussed little in previous literature. Secondly, the authors discuss how network externality and enterprises' attention to consumer welfare affect the optimal decisions and utilities of App service supply chain members. Thirdly, this paper considers four different circumstances and determines the optimal operation scenario for App SSC through comparative analysis.

This paper aims to analyze the potentials of dynamic, commitment and revenue-sharing contracts; that a nonrebate offering manufacturer can use to safeguard his profit while his competitor offers customer rebates in a supply chain consisting of two manufacturers and a common retailer.

We consider a two-period supply chain model to explore optimal decisions under eight possible scenarios based on the contract and rebate offering decisions. Because the manufacturers are selling substitutable products, therefore, a customer rebate on one of the products negatively impacts the selling quantity of other. Optimal price, rebate, and quantities are examined and compared to explore the strategic choice for both the rebate offering and non-rebate offering manufacturer. Comparative evaluation is conducted to pinpoint how the parameters such as contract parameters and its nature affect the members.

The results demonstrate that all these contracts instigate the rebate offering manufacturer to provide a higher rebate, but do not ensure a higher profit. If the revenue sharing contract is offered to the common retailer, the effectiveness of the rebate program might reduce significantly, and the rebate offering manufacturer might receives lower profits. A non-rebate offering manufacturer might use a commitment contract to ensure higher profits for all the members and make sure the common retailer continues the product.

The effect of customer rebate vs. supply chain contract under competition has not yet been explored comprehensively. Therefore, the study contributes to the literature regarding interplay among pricing decision, contract choice and rebate promotion in a two-period setting. The conceptual and managerial insights contribute to a better understanding of strategic decision-making for both competing manufacturers under consumer rebates.

Motivated by the wide application of procurement strategies in retailing, this paper aims to examine the effect of procurement strategies on decisions and profits and strategic inventory (SI) is considered.

The game-theoretic models are developed under a two-period fresh product supply chain (FSC), and consist of the mode of purchasing products only in the first period without SI (Scenario S), the mode of purchasing products in every period without SI (Scenario T) and the mode of purchasing products in every period with SI (Scenario TS).

Conducting the calculating and comparing, some major findings can be concluded. In general, two-period purchasing strategies (Scenarios T and TS) promote a higher freshness-keeping effort than the single buying strategy (Scenario S). Regarding the pricing strategy, SI and Scenario S can both contribute to obtaining a lower wholesale price, the retailer's pricing is relatively complicated and hinges on the consumer's sensitivity to freshness-keeping effort and the holding cost. Besides, comparing the sales quantity and the profit, the authors find that Scenario TS stimulates more demands and brings more profits for the manufacturer. However, Scenario TS is not the optimal selection for the reason that SI sometimes hurts the retailer and even the whole supply chain. Whereas, when the holding cost is in a certain range, Scenario TS will lead to a win-win situation.

The main findings of this study can give the enterprises some advice on the procurement strategies of fresh products and the decisions of pricing and the freshness-keeping effort.

The purpose of this study is to address the efficiency of power losses representation while still reducing the computational burden of an optimal power flow (OPF) model in transmission expansion planning (TEP) studies.

A modified TEP model is formulated with inclusions of linearized approximation of power losses for a large-scale power system with renewable energy sources. The multi-objectives function determines the effect of transmission line losses on the optimal power generation dispatch in the power system with and without inclusion of renewable energy sources with emphasis on minimizing the investment and operation costs, emission and the power losses.

This study investigates the impact of renewable energy sources on system operating characteristics such as transmission power losses and voltage profile. Sensitivity analysis of the performance for the developed deterministic quadratic programming models was analyzed based on optimal generated power and losses on the system.

In the future, a comparison of the alternating current OPF and direct current (DC) OPF models based on the proposed mathematical formulations can be carried out to determine the efficiency and reduction of computation process of the two models.

This paper proposed an accurate way of computing transmission losses in DC OPF for a TEP context with a view of achieving a minimal computation time.

This paper addresses the following objectives: develop a modified DC OPF with a linearized approximation of power losses in TEP problem with large integration of RES. Investigate the impact of RES on system operating characteristics such as transmission power losses and voltage profile.

With tower cranes being the site hubs, thoroughly planning and managing their operations can result in better construction performance. As urban spaces become more constricted, overlapping working radii of tower cranes becomes inevitable. While project planners are concerned with safety hazards, research has not comprehensively addressed workload distribution and synchronization of overlapping cranes. Therefore, this study aims at exploring the impact of overlapping cranes, used on high-rise buildings, on operational flexibility which is the balance between schedule duration, crane utilization and safety.

A simulation model was developed and applied on a real project to analyze and compare the impacts of different overlap sizes. Seven scenarios of different overlap sizes, i.e. different number of tasks falling in the overlap space, were executed in the model; their results were plotted and analyzed.

The outcomes result from several compounded factors such as the experience of planners and crane operators, the sequencing of critical versus non-critical activities and the overall effort and care taken when planning operations of overlapping cranes. Increasing overlap size can be beneficial or unfavorable depending on how properly planners allocate overlapping cranes to workload demand, keeping in mind that there are certain trade-offs while achieving operational flexibility.

While project planners are concerned with safety hazards associated with crane overlaps, research has not been comprehensively nor proactively addressing the workload distribution and synchronization of overlapping crane processes. This study contributes to science by addressing the need to harness the flexibility in using overlapping tower cranes while minimizing the resulting interruptions and safety risks. This study sheds light on the potential benefits of allowing cranes to overlap while considering their collision free operations. Operational flexibility is seen as the balance between achieving shorter schedule durations and higher crane utilizations while maintaining collision free motion paths.

The purpose of this study is to analyze the problem of optimal product line design in marketing channels.

This paper develops a game theoretic model, in which a firm markets a line of a limited number of products at different quality levels to serve a market composed of multiple consumer segments. The consumer segments are modeled as clusters of somewhat heterogeneous consumers as typically observed in the real world. These model characteristics allow us to consider a broader set of targeting strategies such as sub-segmentation and partial cannibalization which have not been considered previously. By considering both a vertically integrated channel and a decentralized channel, we investigate how channel structure influences optimal product line design. We analyze the model mathematically with supplemental numerical analyses.

Our analysis shows that “quality distortion” in product line design is not limited to the low-end product, as previously reported, but can happen to the high-end product. The direction of these quality distortions may be downward or upward, leading to either increased or decreased differentiation between the two products. Furthermore, channel decentralization makes it more likely for the firm to strategically choose upward partial cannibalization or sub-segmentation. Consequently, contrary to previous studies, we demonstrate that there exist conditions under which channel decentralization leads to higher product quality.

Our model reflects a more realistic market environment and a firm’s practical constraints than previous studies, which typically assume perfect homogeneity within each segment and/or the feasibility of offering an infinite number of products. This extension produces interesting new results and insights that provide more practical implications for a firm’s optimal product line design strategy.

The purpose of this paper is to develop a simple deterministic model that quantifies previously adopted preventive measures driven by the trend of the reported number of deaths in both Italy and India. In addition, the authors forecast the spread based on some selected quantified preventive measures. The optimal exiting policy is derived using the inverse dynamics of the model. Furthermore, the model developed by the authors is dependent on the daily number of deaths; as such, it is sensitive to the death rate but remains insensitive to trends in deaths.

In the wake of COVID-19, policymakers and health professionals realized the limitations and shortcomings of current healthcare systems and pandemic response policies. The need to revise global and national pandemic response mechanisms has been thrust into the public spotlight. To this end, the authors devise an approach to identify the most suitable governmental non-pharmaceutical intervention (NPI) policies, previously adopted in a community, country or region that serve as the foundation for most pandemic strategies.

Leveraging Italy, the authors compare the aftermath by considering three scenarios: (a) recently adopted preventive measures, (b) strictest preventive measures previously adopted, and (c) the optimal exiting policy. In comparison to the second scenario, the authors estimate about twice the number of recoveries and deaths within five months under the first scenario and about 80 times more under the optimal scenario. Whereas in India, the authors applied one scenario of recently adopted preventative measures to showcase the rapid turnaround of their model. According to the new timeline, almost 90% of all deaths in India could have been prevented if the policies implemented in April 2021 were put in place three months prior, i.e. in January 2021.

The novelty of the proposed approach is in the use of inverse dynamics of a simple deterministic model that allows capturing the trend of contact rate as a function of adopted NPIs, regardless of pandemic type.