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To foster the grid integration of both electric vehicles (EV) and renewable generators, the purpose of this paper is to investigate the possible synergies between these players so as to jointly improve the production predictability while ensuring a green mobility. It is here achieved by the mean of a grid commitment over the overall power produced by a collaborative system which here gathers a photovoltaic (PV) plant with an EV fleet. The scope of the present contribution is to investigate the conditions to make the most of such an association, mainly regarding to the management strategies and optimal sizing, taking into account forecast errors on PV production.

To evaluate the collaboration added value, several concerns are aggregated into a primary energy criterion: the commitment compliance, the power spillage, the vehicle charging, the user mobility and the battery aging. Variations of these costs are computed over a range of EV fleet size. Moreover, the influence of the charging strategy is specifically investigated throughout the comparison of three managements: a simple rule of thumb, a perfect knowledge deterministic case and a charging strategy computed by stochastic dynamic programming. The latter is based on an original modeling of the production forecast error. This methodology is carried out to assess the collaboration added value for two operators’ points of view: a virtual power plant (VPP) and a balance responsible party (BRP).

From the perspective of a BRP, the added value of PV-EV collaboration for the energy system has been evidenced in any situation even when the charging strategy is very simple. On the other hand, for the case of a VPP operator, the coupling between the optimal sizing and the management strategy is highlighted.

A co-optimization of the sizing and the management of a PV-EV collaborative system is introduced and the influence of the management strategy on the collaboration added value has been investigated. This gave rise to the presentation and implementation of an original modeling tool of the PV production forecast error. Finally, to widen the scope of application, two different business models have been tackled and compared.

Most local authorities now offer a telecare service to people who are eligible for community services under Fair Access to Care Services (FACS). Others also offer telecare in a prevention mode to people with lower levels of risk alongside traditional social (or community) alarm systems. A survey of local authorities, mainly members of the Centre for Usable Home Technologies (CUHTec), was performed to gauge the service provision options available and the charging strategies that have been adopted. Results from 39 authorities across the UK indicate significant differences between English shire counties and the unitary authorities elsewhere in the country in terms of eligibility and provision. The majority of authorities have yet to confirm a charging policy, using the principle of ‘pilot project’ to delay a decision until their Preventative Technology Grant (PTG) or telecare grants have run out. Some authorities with more mature services have chosen to make telecare free to particular groups on the grounds that they will reduce costs elsewhere in the health and/or social care economy. Most are introducing charges in the range of £5 to £10 per week indicating a generous subsidy from the council.

The purpose of this study is to develop an optimization method for charging plans with the implementation of time-of-day (TOD) electricity tariff, to reduce electricity bill.

Two optimization models for charging plans respectively with fixed and stochastic trip travel times are developed, to minimize the electricity costs of daily operation of an electric bus. The charging time is taken as the optimization variable. The TOD electricity tariff is considered, and the energy consumption model is developed based on real operation data. An optimal charging plan provides charging times at bus idle times in operation hours during the whole day (charging time is 0 if the bus is not get charged at idle time) which ensure the regular operation of every trip served by this bus.

The electricity costs of the bus route can be reduced by applying the optimal charging plans.

This paper produces a viable option for transit agencies to reduce their operation costs.

This research intends to investigate the determinants that affect consumers’ purchase intention of electric vehicles (EVs) in Malaysia using an extended theory of planned behaviour (TPB).

Survey data were collected with a sample size of 306. The research used SmartPLS 4.0 structural equation modelling tool to analyse the data. Reliability and validity tests (discriminant and convergent validity) were used and subsequently assessed the measurement and structural models. Mediation analysis was conducted to identify the role of the latent constructs.

The findings indicated that a green purchase attitude plays a complete mediation role in the effect of environmental knowledge on the purchase intention of EVs. In the same notion, the effect of price perception and availability of charging facilities on the purchase intention of EVs passes completely through perceived behavioural control. However, the subjective norm was an insignificant mediator of the impact between government support and EV purchase intention.

This paper helps to examine the latent constructs that impact purchase intention using environmental knowledge, government support, price perception and the availability of charging facilities. Successful green marketing and a sustainable consumerism framework are seen as a booster to promote the usage of EVs in Malaysia.

An extended TPB model has been employed in this research to study the effects of the above-mentioned constructs. The results show that most of the extended constructs are significant in explaining the purchase intention. The empirical results address the gap in the consumer green attitude and provide insight into this area of study.

The purpose of this paper is to optimize the design of charging station deployed at the terminal station for electric transit, with explicit consideration of heterogenous charging modes.

The authors proposed a bi-level model to optimize the decision-making at both tactical and operational levels simultaneously. Specifically, at the operational level (i.e. lower level), the service schedule and recharging plan of electric buses are optimized under specific design of charging station. The objective of lower-level model is to minimize total daily operational cost. This model is solved by a tailored column generation-based heuristic algorithm. At the tactical level (i.e. upper level), the design of charging station is optimized based upon the results obtained at the lower level. A tabu search algorithm is proposed subsequently to solve the upper-level model.

This study conducted numerical cases to validate the applicability of the proposed model. Some managerial insights stemmed from numerical case studies are revealed and discussed, which can help transit agencies design charging station scientifically.

The joint consideration of heterogeneous charging modes in charging station would further lower the operational cost of electric transit and speed up the market penetration of battery electric buses.

The ongoing urbanization and decarbonization require deployment of energy storage in the urban energy system to integrate large-scale variable renewable energy (VRE) into the power grids. The cost reductions of batteries enable private entities to invest energy storage for energy management whose operating strategy may differ from traditional storage facilities. This study aims to investigate the impacts of energy storage on the power system with different operation strategies. Two strategies are modeled through a simulation-based regional economic power dispatch model. The profit-oriented strategy denotes the storage system operated by private entities for price arbitrage, and the nonprofit-oriented strategy denotes the storage system dispatched by an independent system operator (ISO) for the whole power system optimization. A case study of Jiangsu, China is conducted. The results show that the profit-oriented strategy only has a very limited impact on the cost reductions of power system and may even increase the cost for consumers. While nonprofit-oriented energy storage performs a positive effect on the system cost reduction. CO₂ emission reduction can only be achieved under a high VRE scenario for energy storage. Integrating energy storage into the power system may increase CO₂ emissions in the near term. In addition, the peak-valley spread is crucial to trigger operations of profit-oriented energy storage, and the profitability of energy storage operator is observed to be decreasing with the total storage capacity. This study provides new insights for the energy management in the smart city, and the modeling framework can be applied to regions with different resource endowments.

The authors characterize two battery storage operating strategies of profit- and nonprofit-oriented by adopting a simulation-based economic dispatch model. A simulation from 36 years of hourly weather data of wind and solar output from case study of Jiangsu, China is conducted.

The results show that the profit-oriented strategy only has a very limited impact on the cost reductions of power system and may even increase the cost for consumers. While nonprofit-oriented energy storage performs a positive effect on the system cost reduction. CO₂ emission reduction can only be achieved under high VRE scenario for energy storage. Integrating energy storage into the power system may increase CO₂ emissions in the near term. In addition, the peak-valley spread is crucial to trigger operations of profit-oriented energy storage, and the profitability of energy storage operator is observed to be decreasing with the total storage capacity.

This study provides new insights for the energy management in the smart city, and the modeling framework can be applied to regions with different resource endowments.

Omnichannel has become increasingly important with the development of e-commerce. In omnichannel, merchants expect customers to get the products and services at anytime, anywhere and in any way, and the same is true for customers. This drives multihoming in online platforms for both merchants and customers. Thus, once both customers and merchants are multihomed, what price and subsidy decisions should be made between platforms to compete to obtain optimal profits? The main purpose of this paper is to solve these problems and provide decision-making for two-sided platforms in omnichannel.

This study builds a dual Hotelling model to capture the utility and network effects of customers and merchants on two-sided platforms. This study introduces the exposure effect and convenience effect of multihomed customers and merchants in the model and analyzes the impact of these effects in the market with multihoming on one side. Then, this study extends the model to the market with multihoming on both sides and makes the pricing decision for two-sided platform when considering the exposure effect and convenience effect through an equilibrium solution. Finally, this study also uses numerical analysis to simulate the decision and profit of the platform.

This paper finds that the convenience effect will only increase social welfare when customers are single-homed and merchants are multihomed. In addition, when both users are multihomed, the platform will subsidize to attract merchants and customers if the convenience effect and exposure effect are relatively high. This study also finds that network effects come not only from the same platform but also from another platform in the case with multihoming on both sides. And network effects in the heterogeneous platform will be reduced by the convenience effect and exposure effect.

According to the behavioral characteristics of merchants and customers in omnichannel, this paper first adopts the dual Hotelling model to study the pricing of two-sided platforms with multihoming on both sides. This paper shows that network effects originate not only from the same platform but also from another platform and that the exposure effect and the convenience effect can exist as cross-platform network effects, which provides a new explanation for network effects in markets with multihoming on both sides. This research extends the theory of network effects and plays an important role in the development of two-sided platforms in omnichannel.

The learning outcomes of this case study are as follows: It presents an opportunity for the instructors to introduce the concept of decision-making on matters involving risk (like scaling the business) using in-depth market research techniques. The case’s central idea is to make the students understand the growth of the online service delivery model, with a specific example of home-cooked food that also improves social welfare. It is expected to provide the participants with an opportunity to understand the decision-making by the leaders in newly established companies. It enables future managers to analyze a venture’s pros and cons before deciding to expand.

Chef Junction is an online food delivery platform that allows customers to order hygienic home-cooked food prepared by handpicked home chefs in Bhubaneswar. This city in eastern India is one of the fastest-growing metros, is regarded as a study hub, and provides ample employment opportunities making it one of the sought-after destinations for the migrant youth population. The idea behind Chef Junction is to cater to the healthy food needs of the young by utilizing the culinary productivity of the home cooks, empowering the latter by opening up an extra source of income. These chefs prepare delicious healthy food, usually not listed for sale with online food delivery apps. Chef Junction earned revenues by adding an order-dependent commission on the price quoted by chefs and accepting a flat delivery charge from the customers. This offer was very lucrative for home chefs who could join the platform with zero investment and flexible working hours. The customer’s pockets were also handled when several offers and discounts were rolled out through an attractive pricing strategy. Chef Junction expected to improve its patrons’ health quotient by ensuring the nutrition of the home-cooked food, thus contributing to social welfare. With food being delivered from home to home amalgamated with social welfare and empowerment of home chefs, especially women, this case study is an apt example of a sustainable work-from-home model that has proved effective in crisis times. The pertinent question is: “How feasibly can CJ’s business model grow towards an expansion as the demand increases?”

This case study has been prepared keeping in mind the teaching pedagogy for graduate and postgraduate management programs in strategic management, operations research, entrepreneurship and marketing management. It is also expected to be useful for training courses such as management development programs, faculty development programs and executive programs, in discussing service operations in general and online delivery logistics, in particular for working executives and industry practitioners.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

The purpose of this paper is to aid understanding of the changes in Basel Committee on Banking Supervision (BCBS) regulatory strategies after the global financial crisis.

The author uses the credit valuation adjustment (CVA) charge reform as a test case for inquiring whether BCBS has departed from its pre-crisis facilitative regulatory strategy path. The regulatory strategy of the CVA charge is discussed.

The charge exhibits a new regulatory strategy that BCBS has adopted. It seeks to manipulate market structures by imposing risk-insensitive capital charge methodologies.

The paper offers a new heuristic to analyse regulatory initiatives and their significance. The CVA charge has not been subject to a regulatory theory-based analysis in prior literature.

Pricing strategies for subscriptions and licenses to CDROM are amazingly complex. In general the supplier seeks to achieve as high a revenue as possible from a given product. CDROM pricing strategies have two distinct aspects: prices charged for single user use and prices charged for network use. Examples are given of different pricing strategies available from different suppliers for both single user use and network use. Pricing strategies are currently very complex. Market forces and increased maturity of the market‐place are likely to lead to simpler pricing strategies.