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We study the inter-temporally optimal innovation strategies of incumbent manufacturing firms that compete in an established market and can extend their product line through product innovation. Firms invest in production capacity and R&D knowledge stock, where the R&D knowledge stock and the current R&D investment determine the hazard rate of innovation. Our findings show that the firms’ optimal R&D strategies are driven by a subtle interplay between the relative positions of their R&D knowledge stocks and their current relative positions on the established market. First, we find that under symmetric investment costs the knowledge leader should spend more on R&D than the knowledge laggard only if it has a substantially smaller market share on the established market. If the knowledge leader’s market share is sufficiently large, its optimal investment in R&D is so small that its innovation rate is lower than the knowledge laggard’s. Second, optimal investment in R&D knowledge is negatively affected by the opponent’s production capacity on the established market if the competitor has not innovated yet. However, we find that this effect is reversed after the competitor has successfully introduced the new product on the submarket. Third, the manufacturing firm with higher costs of adjusting production capacity for the established product has a higher incentive to engage in product innovation and might even achieve a higher total discounted profit than its more efficient competitor.

The governmental subsidy is an important instrument for catalyzing the early adoption of Electric Vehicles (EVs)}. A sustainable subsidy policy must balance between promoting EVs and expanding the charging infrastructure. This paper proposes a dynamic game approach to accelerate the adoption of EV technology. The government observes two correlated processes - the penetration of the EV market and the expansion of the charging infrastructure. It finds an optimal strategy that maximizes the cumulative social benefit in the face of uncertainty. A case study of China's EV industry finds that \blue{the established EV subsidy policies are inadequate to support EVs' growth over the next decades}. In contrast, the optimal subsidies will achieve \blue{the target EV market share and ensure the accessibility to charging infrastructure by 2030}. This non-myopic strategy can prioritize the infrastructure expansion, eliminate policy enforcement's monitoring costs, prevent compensation evasion, and help achieve long-term targets by making proactive regulatory policies.

Reverse logistics programs to support end-of-life product management strategies are becoming more prevalent as firms respond to stricter regulations and increasing consumer expectations. Despite a growing body of theoretical literature on this topic, many firms struggle to implement efficient and effective reverse logistics systems. This research identifies common strategic, tactical, and operational considerations needed to design reverse logistics programs, and offers industry examples to show how organizations have excelled in these areas. Through a synthesis of literature and examples, key takeaways are provided across a range of reverse logistics activities. In doing so, this paper illustrates ways in which managers can implement best practices in reverse logistics that not only benefit the environment but also generate societal and stakeholder value, augment and improve customer service and loyalty, and increase market share and revenue capabilities.

This study proposes a novel approach to forecast a transhipment port's competitiveness on the basis of market share. The potential reasons for escalating or diminishing competitiveness are explored by utilising a multi-criteria decision-making (MCDM) methodology. We assess the competitiveness of transhipment ports by seven major components: connectivity, port facility, efficiency, cost factor, policy and management, information systems and green port management, and contribute to the understanding of the interdependence among the components. We investigate the Bangladesh container market due to the uniqueness of its regional context and dimensions of competitiveness. Bangladesh has direct connections to four regional hubs, namely, Singapore, Colombo, Port Klang and Tanjung Pelepas. These regional hubs compete to grasp a significant volume of container movements in line with the rapid growth of Bangladesh's industrialisation and national economy. We find that Singapore outperforms others in terms of competitiveness, but all ports perform below expectations in green port management practices. These findings would benefit port authorities for improving their competitiveness, and liner shipping companies and shippers in making strategic port choice decisions.

Our understanding of airline passengers' perception of safety and its association with their satisfaction and airline service quality measures is limited in the literature. This study aims to conduct a systematic examination of airline passengers’ perception of safety and its association with demographics attributes, service quality measures, overall satisfaction and loyalty by using Vietnam to Australia route as a case study. We conducted a questionnaire survey of 436 respondents travelling on a full-service airline flying from Vietnam to Australia. Only 53.4% of respondents feel safe while travelling in the airline while 28.9% feel neutral safe and 17.7% feel unsafe. We found that the four service quality measures of SERVQUAL model (Tangibles, Reliability, Assurance and Empathy) and airline specific measures (Flight Experience, Ground Service, Airline Employees and Flight Schedule) had significant effects on the passengers' perception of safety. Also, respondents' differences in educational qualification, frequency of travel, ticket types and the membership of frequent flyer program (FFP) had a significant effect on their perception of safety. Likewise, passengers’ overall satisfaction and loyalty to the airline also had a significant effect on the perception of safety. No effects on the perception of safety were found for differences in gender, age, nationality, income and purpose of travel. Although all airlines flying in and out of Australia must meet Australia's Safety Management System regulations and requirements, our findings emphasize the importance of understanding the relationship between passengers' perception of safety and their satisfaction. There is an opportunity for the airline operator to secure a lead in the market share of air travel by improving service quality measures that can influence passengers' perception of safety.

We consider a large group of consumers who decide whether or not to buy a durable good offered by a firm. Without previous experience with the product, consumers rely on the ratings of past purchasers to evaluate the product goodwill and make optimal decisions. The consumers have heterogeneous intrinsic rating behaviors and preferences. For example, the population may include avid fans who tend to purchase at early stages and over-rate the product. What are the firm’s optimal pricing and marketing strategies in the face of such heterogeneous market? To answer this question, we model the problem as a Stackelberg mean-field game, with the firm acting as leader and the consumers as followers. We determine the conditions under which a Stackelberg equilibrium exists and provide a numerical scheme to compute the optimal prices, marketing activities, aggregate rating, and market share. We provide some numerical examples to illustrate the type of insights that can be obtained with our model. For instance, we show that it is useful to compare the fairness of different rating aggregators, and can anticipate herding behavior triggered by biased raters.

Using a large sample of securities class action lawsuits, we examine the association of law firm market share with litigation outcomes. We find lawsuits with top market share plaintiff law firms are less likely to be dismissed and take longer to be dismissed and to reach settlement. In contrast, lawsuits with top defendant law firms reach settlement faster. Top market share defendant law firms are neither associated with suit dismissal nor with speed of dismissal. Finally, neither top plaintiff nor top defendant law firms are associated with the cash and/or total settlement amount. These results suggest plaintiff and/or defendant law firm market share is an important factor in securities class action litigation outcomes. The results favor the view that plaintiff and defendant law firms with a higher market share are more reputable and better serve the interests of their respective clients in securities class action litigations.

In this paper, we study Nash equilibria for real R&D options in a context of non-cooperative oligopoly under fuzzy uncertainty in market shares and revealed information. In particular, we consider a duopoly fuzzy game in which each firm has two available strategies, that is to invest or to defer its research investment. The deferring option gives the benefit of the information revelation about market reaction but, on the other hand, the disadvantage of a lower market share. Since these two effects are not easily to quantify, we describe the revealed information and the market shares as fuzzy numbers. As shown by numerical examples, the proposed fuzzy framework allows to reach different firms' strategic behaviours and new Nash equilibria with respect to the crisp case.

Frequency competition is critical for a full-service airline in gaining market share, and adopting a proper strategy can improve an airline’s profits. This study proposes a new equilibrium programming model with flow balance to address frequency competition on airports network with time slot constraints. We first show that a pure-strategy Nash equilibrium may not always exist, and thus forming a pure strategy profile in frequency competition among airlines may naturally lead to deviation from current frequency. Therefore, we formulate the problem as a programming model with a mixed-strategy Nash equilibrium. To avoid shocks from dramatic frequency changes across the network, airlines tend to fine-tune frequencies on select segments during each adjustment. We propose a procedure to generate a computationally tractable amount of representative strategies from a finite set of feasible strategies to demonstrate mixed-strategy Nash equilibrium. We conduct an empirical analysis using an example in which industry profitability increased by as much as 7.89%. We then extend the model to formulate frequency competition among metal-neutral alliances. The results show that forming metal-neutral alliances can improve total industry profits by 10.59%. In particular, a sensitivity analysis with real data on the tolerance of flow imbalance demonstrates that deducting the potential costs due to the relaxation of flow balance between congested airports may earn additional total industry profits in a frequency competition.

Introduction Orthodontics is evolving with advances in 3D imaging, additive fabrication, digital scanning, and treatment planning. With digital tools, orthodontic treatment may become more predictable, efficient, and effective while reducing side-effects. These technologies are affecting patient care, but knowledge of their adoption patterns and influence is incomplete. We aimed to identify adoption decision makers, information sources, perspectives, incentives, and barriers. Methods Twenty-four privately practicing orthodontists were interviewed in a semistructured format following a topic guide. Interview transcripts were analyzed to identify factors in technology adoption and its perceived influence on practice. Thematic patterns were established through iterative systematic analysis, and qualitative validity was ensured with researcher triangulation. Results Qualitative interviews revealed that orthodontists make purchasing decisions independently from staff, after consulting other dentists and company representatives. Meetings, residency training, and continuing education courses are influential information sources, whereas research literature is not. Early and middle adopters are integrating digital imaging, planning, and fabrication technologies into practice and view enhanced ease of use, capabilities, performance, and procedural efficiency as primary incentives to adoption. Improving outcomes and patient comfort are not frequently cited as incentives, and all interviewees view cost as the largest barrier. Orthodontists positively perceive the influence of technology on their practices, but are concerned that further innovation and direct-to-consumer products will cause loss of market share. Conclusions CAD/CAM appliances, 3D imaging, and digital treatment planning are viewed as future standards of care and are increasingly being incorporated into the orthodontic office. Understanding the technology adoption process can guide innovation to improve treatment and ease the transition into a digital workflow.

This paper contributes to the literature on firms’ export pricing by assessing whether and to what extent firms take into account the expected future evolution of the exchange rates while setting their prices. Using French micro-level trade data, our empirical analysis reveals that by adjusting their export prices, firms partly absorb information about future exchange rate variations. The extent to which individual exporters absorb future exchange rate fluctuations is found to depend on their market power, in accordance with theoretical dynamic demand-side models encompassing mechanisms creating an inter-temporal relationship between current market shares and future profits. The analysis also shows that the strength of such expectation-related mechanism is considerably reduced with greater future exchange rate uncertainty, in line with an interpretation of pricing-to-market as an investment decision under uncertainty. In a comparative perspective our results are shown to drive asymmetric responses across destinations of aggregate bilateral export flows to expected exchange rate movements.

The global outbreak of COVID-19 has further exposed deficiencies in city logistics based on human and ground roads, such as poor emergency response capacity and high risk of infection during transportation. Metro-based underground logistics system (M-ULS) may be an innovative approach to deal with this city-level disaster due to its efficient operation, contactless and driverless characteristics. However, the market evolution process and the quantitative calculation framework of comprehensive benefits after the application of M-ULS are still unclear, which has become a problem of mutual restriction with the extensive application of M-ULS. This paper attempts to use the system dynamics method, based on the real-world simulation, to analyze the quantitative relationship between the M-ULS implementation and the city logistics performance under epidemic outbreaks. Wuhan city in China was selected as the empirical background, and five simulation scenarios were set under different implementation strategies of M-ULS in response to the epidemic. Six variables were selected to measure city logistics performance and M-ULS operation status, including demand fill-rate, unit delivery time, total deprivation cost, total transportation cost, total number of susceptible people, and utilization rate of M-ULS. The results show that M-ULS is effective in improving the performance of city logistics and responding to the epidemic. The delivery time and transportation cost have a strong impact on the market share of M-ULS. Finally, a set of incentive policies was designed to promote the adoption of M-ULS. The findings not only provide a method for evaluating the overall performance of M-ULS, but also provide a unique perspective for promoting the implementation of M-ULS and responding to the transportation challenges brought by the epidemic.

Multiple studies employ consumers’ intentions rather than actual purchases when assessing organic food consumption. These studies typically suggest a green bias in organic market share. Employing reactance and construal level theory, this research investigates the impact of one’s social distance to the character depicted in ads (animal vs. human) and the temporal distance (present vs. future) toward organic animal husbandry on consumers’ purchase responses directly; indirectly, as related to the portrayed character; and generally to organic foods. Three 2 (temporal distance: low, high) × 2 (social distance: low, high) between-subjects experiments demonstrate that low social distance depicting humans rather than animals induces psychological reactance, which impedes purchase intentions of organic groceries, whereas ads featuring high social and temporal distance (depicting animals in an ideal future husbandry state) increase consumers’ purchase intentions and actual purchase behavior, even for products with no direct connection to the depicted character in the ads.

The current situation and the prospects for an increase in the biodiesel market share in Ecuador were analyzed. The substitution of up to 15% of diesel (4.88 million barrels) would be possible using the surplus of African palm oil and the pinion crop expansion (1000 times). This would decrease the emitted CO2 (611,303 tons/year). Despite in Ecuador the biodiesel cost is 53% higher than diesel cost, the social and economic co-benefits at the pinion producer level must also be considered. To reduce the pinion oil costs, it is necessary to improve its performance (use sophisticated technologies). The use of other raw materials (e.g. lignocellulosic waste) could be another alternative.

This paper models autonomous ridesharing — multiple travelers simultaneously riding one shared autonomous vehicle (SAV) — in a network equilibrium setting with mixed SAV and human-driven vehicle (HV) traffic. We make two major methodological contributions. First, a novel one (SAV)-to-many (riders) matching is proposed to characterize the waiting times of an SAV and multiple travelers who share rides in the SAV during online matching, which is a nontrivial generalization of the one-to-one matching without ridesharing. Our matching characterization considers the possibilities of a traveler matched with an SAV starting from the same origin, whereto the SAV moved unoccupied as a result of either pickup or relocation, or with an in-service SAV that goes through the traveler's origin. Second, a section-based formulation for SAV ridesharing user equilibrium is introduced to characterize the SAV traveler flow, which accommodates the possibility that an SAV traveler's itinerary (OD pair) is different from that of the serving SAV and other travelers in the SAV. Unlike the existing link and route based ridesharing formulations, the notion of section both prevents undesired traveler en-route transfer(s) and allows travelers of multiple ODs to share rides, meanwhile respecting the SAV seat capacity constraint. In addition to the above two methodological contributions, the optimal SAV fleet size, fare, routing, and allocation (to in-service, pickup, and relocation states) decisions of a transportation network company (TNC) are formulated. The TNC decisions anticipate traveler reactions as characterized by a new multimodal autonomous ridesharing user equilibrium (MARUE), which is put forward with a proof of its existence and finds the endogenous market shares and road congestion effects of SAV/HV. Original insights are obtained from model implementation, including substantial systemwide benefit of ridesharing, marginal benefit of relocation in the presence of ridesharing, and diminishing economies of SAV size.

The need for green energy and minimization of emissions has pushed automakers to cleaner transportation means. Electric vehicles market share is increasing annually at a high rate and is expected to grow even more. This paper aims to review the energy management systems and strategies introduced at literature including all the different approaches followed to minimize cost, weight and energy used but also maximize range and reliability. Current requirements needed for electric vehicles to be adopted are described with a brief report at hybrid energy storage. Even though various strategies and controlling modules are simplified, there is still option for improvement due to the complexity and quantity of calculated values. Driver behavior, traffic, storage characteristics and power splitting must be taken into consideration to prevent battery aging, oversizing and power losses. Hence battery lifetime will be extended and efficiency can be maximized.

This research presents a retail analytics application which uses machine learning (ML) to identify and predict under- and overperforming consumer packaged goods (CPGs) using retail scanner data. Essential to measuring market performance at the SKU level is the relationship between distribution and market share (the velocity curve). We validate that ML can reproduce the velocity curve, and ML is further used to predict underperforming, in-line performing, and overperforming SKUs relative to the velocity curve, based on a range of variables (SKU features) at a point in time. Our ML approach can correctly predict 83% of SKUs as under-, in-line-, or overperforming based on their characteristics. The research analyzes 9,321 SKUs of 2,565 brands across seven product categories of CPGs which were sold in 8,117 stores from 49 different retail chains of five different retail channels located in the US states of California, New York, Texas, and Wisconsin. The retail stores comprise convenience stores, drug stores, food stores, liquor stores, and mass merchandise retail stores. The data is Nielsen retail store scanner data for the calendar year 2014. The relationship between distribution and market share is a market-wide proxy for the ratio of relative sales in a category to, for example, aggregate shelf space, a key retail productivity metric. We further find indications that the distribution of SKUs across different store sizes, the stores’ category specialization, the line length of the brands, the overall performance of the parent brand, and sales consistency are the most important characteristics for the prediction of market share performance beyond the velocity curve. The methods and results presented will help CPG marketers (suppliers and retailers) understand which SKUs are under-, in-line-, or overperforming and the potential factors contributing to that performance. Optimizing assortments and portfolios is essential to decrease failure rates of individual SKUs. ML approaches can evolve to complementary support tools for such management problems.

Retail distribution is one of the major challenges in emerging economies. These economies are volatile and filled with inefficiencies, and the representativeness of unstructured retail increases the complexity of distribution systems for consumer packaged-goods companies. We analyze 644 brands to extend the existing literature by modeling the retail distribution and market share in an emerging market according to the type of retail channel (full- and self-service channels), moderated by economic fluctuations and the market position of a brand (high- and low-share brands). Our model controls for endogeneity using instrumental variables (IVs) and accommodates heterogeneity across brands and categories by means of a fixed-effects robust regression. Our study highlights that the relationship between distribution and market share exhibits greater convexity in the self-service channel than in the full-service channel. Further, we contribute to the existing research in distribution effectiveness in emerging markets by showing the convex effect of distribution on market share could vary when the economy changes. Distribution gains are more effective in the self-service channel than in the full-service channel in times of economic decline. Also, the results indicate the higher degree of convexity in the relationship between distribution and market share for the self-service channel compared with the full-service channel is increased further for high-share brands than for low-share brands.

Public transport is a pivotal utility in increasing the long-term sustainability of cities. Consequently, there has been a growing interest in promoting a sustainable modal shift that reduces dependence on private vehicle use. This strategy has involved several specific actions, among them employing price differentiation between the two substitutes considered in this research – public transport and private cars. Governments can influence fares in different ways. However, fiscal policy governing applicable taxes is one that is often neglected in the literature. This paper investigates the relationship between the market share of public transport and taxation – in particular, value added tax (VAT), which is levied on three main products: public transport fares, fuel, and vehicle ownership. The results show that taxes matter, but not all taxes are determinant. A lower VAT rate on public transport fares and a higher tax rate on vehicle ownership can lead to an increase in public transport's market share. Taxing car utilization through VAT on fuel does appear to be significant.

Despite the growing market share of electric scooter-style motorcycles (e-scooters), only limited insight into the role of environmental concern with respect to their adoption is available. The purpose of this study was to investigate the psychological and contextual factors that associate with a switch from fossil fuel scooters to e-scooters. To model these factors, we conducted two studies in Taiwan. In Study 1, we elicited context-specific reasons for and against purchasing an e-scooter in a series of semi-structured interviews. In Study 2, we analyzed data from a survey among consumers (N = 320) using structural equation modelling. We consider the most important reasons from Study 1 together with environmental concerns (egoistic, altruistic, biospheric) in their relationship with intentions to switch to an e-scooter using the framework of Behavioral Reasoning Theory (BRT). In doing so, we provide unique insights for marketers and policymakers who seek to encourage the switch to this more sustainable form of mobility. We found environmental concerns among users of fossil-fueled scooters to be associated with attitude toward as well as reasons for and against switching to an e-scooter. But only a biospheric concern appeared to relate to both reason types and attitude, whereas egoistic and altruistic concerns only associated with reasons for the switch. The study also provides researchers and marketers in the e-scooter industry with a framework for understanding the role of environmental concern and contextual factors on purchase intention for a sustainable mobility product.

While researchers have stressed the potential of automated vehicle (AV) technology in improving mobility and accessibility for a range of people, only a few attempts have been made to examine the impact of this new technology on different segments of the population in a realistic setting using high-fidelity simulation. To fill this gap, we analyze the equity implications of Automated Mobility-on-Demand (AMoD) in three full-scale prototype cities using SimMobility, a state-of-the-art activity- and agent-based framework. The prototype cities were developed based on two auto-dependent typologies, representing cities largely in the US/Canada, and a dense transit-oriented typology. We perform equity analyses at the individual and income-group level, in order to reveal the winners and losers from the introduction of AVs under two scenarios: (1) AMoD Intro, in which a low-cost AMoD service competes with mass transit, and (2) AMoD Transit Integration, where AMoD complements mass transit, via access/egress connectivity service to rapid transit stations. We evaluate the following outcomes: induced demand by age and income groups, mode share by income levels, individual kilometers traveled by different modes and income levels, and the spatial distribution of change in fare and accessibility. Outcomes are considered as equity-oriented if they reduce accessibility gaps, particularly among disadvantaged populations. Our results indicate that in large population-dense and transit-oriented cities, the most equity-oriented outcomes can be achieved, due to extensive mass transit usage, which depresses car usage and restricts induced demand for AMoD. Such cities provide greater opportunities for low-income groups. Specifically, the AMoD Transit Integration scenario results in the best outcomes and implies a new market share, as disadvantaged groups, such as children and low-income individuals, were able to travel more using the integrated AMoD-transit service. Nevertheless, in car-dependent cities, where accessibility gaps are much larger, AMoD Intro scenario performs better compared to AMoD Transit Integration, as it serves the less accessible population and significantly improves their opportunities.

With the ongoing increase of variable renewable energy sources (VRES), such as wind or solar power, weather dependent production profiles induce uncertainty on the supply side and drastically change operations in power markets. In this paper, we study how an increasing market share of VRES affects spot power price dynamics and the forward price premium. Using data from simulated power markets, we analyse the forward premium in three identical power markets with a varying market share of VRES supplied to the system. We demonstrate that markets with a high share of supply from VRES yield a significantly lower forward premium than markets with a low market share of wind or solar supply. Where our results confirm that, regardless of the market share of supply from VRES, forward power prices contain information about future spot power prices, the study also provides evidence for a shift in the sign of the forward premium, from positive in a market with no VRES to negative when the share of VRES is high. These insights generate important implications for producers, retailers and other market participants exposed to wholesale price risk.

Banks' role as underwriters has gained relevance, fostering competition for market share in this traditional investment banking activity. This paper explores the effects of competitive pricing and non-pricing factors on banks’ market share as underwriters. Using a panel of active-underwriters in the European corporate bond markets during a highly competitive period (2007–2013), we find that pricing factors are of second-order importance in explaining changes in market shares. Providing joint lending and underwriting services, hiring star-analysts, and being the leader in placing bonds within an industry positively affect market share. These results explain how banks have developed their underwriting businesses.

With the boom of e-commerce, express delivery has been increasingly regarded as a bottleneck and key factor for achieving success. Additionally, whether to include such express delivery service or not is an important yet outstandingly unsolved problem for online retailers. In this regard, this paper uses a game-theoretic framework to investigate the channel structure, in which an offline retailer competes with an online retailer selling products to consumers through its partner express company. The consumers purchase from either an online or offline channel considering the delivery service as well as the inconvenience of shopping from physical stores. We consider three power structures: online retailer Stackelberg game, offline retailer Stackelberg game and Nash game. Under each power structure, we characterize the channel integration strategy for the online retailer. Interestingly, our results show that the online channel integration is not beneficial for the online retailer in most cases. Online retailers prefer to use express companies as intermediaries to avoid large logistics operations costs in the offline retailer Stackelberg game and Nash game. Only in the online retailer Stackelberg game, where the online retailer has the first-move advantage in the market, together with a moderate store-visiting inconvenience cost and a delivery service cost coefficient, will vertical integration improve the online channel’s profit. Dominant market power ensures sufficient profit to cover the logistics cost, and the moderate inconvenience cost and service cost coefficient promise a moderate logistics cost. Under this condition, the online retailer will choose the vertical integration strategy. We show in the extension that this strict condition can be relaxed when the online retailer owns a mixed channel. The online retailer with a mixed channel has more incentive to integrate than a pure online retailer does, as the mixed channel adds his power and helps to gain more market shares and profit. Our analysis generates managerial insights into the relationship between online retailers and express companies and provides a guide for implementing the vertical integration strategy in the online retailing industry.

Environmental issue such as global warming caused serious natural disasters such as flood and drought due to CO2 emission. Global countries cooperate to address the global warming represented by Paris Agreement, which encouraged actions to restrict CO2 emission and global average temperature increase. H2 has been received more attention than before due to its eco-friendly property. Fuel cell and fuel cell electric vehicle (FCEV) are the widely used H2 application in terms of energy and transportation sector. However, most of the researches were carried out related to H2 supply chain. In hence, in this study, economic analysis considering total cost of ownership (TCO) of FCEV was conducted and correlation between TCO and market share of FCEV was figured out by drawing a regression curve. Finally, an optimization model was developed to obtain the optimal H2 fueling station arrangement model in case of 2022, 2030, and 2040 depending on learning rate (8, 13, and 18%). The $ 46,444.2 of TCO was computed considering three years of ownership length. In addition, 4.3, 31.7, and 94.0% of maker share in 2040 were reached in case of 8, 13, and 18% of learning rate, respectively. Finally, it was unveiled that H2 fueling station is preferred to construct equally in nation and the construction region will be shifted to a higher population density region as time passed.

As an emerging technology that does not rely on the construction of several parking facilities and effectively relieves the pressure of urban parking, shared parking is widely promoted. However, users may turn to conventional parking mode because of concerns about the performance of shared parking modes. Therefore, to determine why users change parking mode and to improve the behavior patronage rate of shared parking mode, studying the factors influencing users’ behavior intentions is very important. Technology acceptance model and satisfaction–loyalty model are combined to construct a comprehensive framework for analyzing the key factors that affect the behavioral intentions of shared parking mode and to describe the multidimensional characteristics of the behavioral intentions. The hypotheses were tested and analyzed on the basis of the empirical data of Harbin and the structural equation model (SEM). Eventually, a multigroup SEM analysis, which takes gender as a moderating variable, is used. Results show that the re-patronage of shared parking is significantly affected by its technology acceptance and that the perceived risk is the key variable leading to change parking mode. In addition, the factor invariance of the identified model framework is examined against gender, and few significant differences are found. The framework is expected to contribute to operators in increasing their market share of shared parking services and to governments in promoting new transportation technologies in cities.

To generate continuing profits as well as to retain market share, companies need to regularly introduce new products into the market, replacing outdated products and enticing buyers to purchase new products. Thus, planning the product transition from the phase-out of a product to the phase-in of a product is a challenging task for both production planners and marketing managers. One significant concern in particular is how to account for the learning effect associated with the production of two successive products that share a single type of production resource. To address this problem of designing production plans for two successive products, we develop an MINLP (Mixed-Integer Non-Linear Programming) model that minimizes the total operating cost for managing the product transition. In doing so, we consider the number of production resources, the lengths of the product production periods, and the number of setups for both products during the ramp-down and ramp-up periods. We study the behaviors of the proposed model with the help of numerical experiments by varying the values of key parameters, including the learning effect and its impact on performance under different operational scenarios. Leveraging the results from the sensitivity analyses, the operational characteristics for managing the product transition are discussed.

In-store displays aim to boost sales of both utilitarian and hedonic products. Noting typical differences in the information processing and purchase behavior evoked by these product types, and building on congruency theory principles, the authors propose that different types of in-store displays (i.e., island, end-of-aisle, or shelf signage) are more appropriate for utilitarian versus hedonic products, and the use of price or product promotions might reinforce these effects. With a database that combines three data sources (scanner, observational, and survey), this article presents an analysis of a market share model at the SKU level. The results confirm that in-store displays have differential effects on sales, depending on their characteristics; congruency between the decision-making process of utilitarian versus hedonic products and the characteristics of in-store display types moderates their effectiveness in terms of SKU sales. Shelf signage strongly increases the sales of utilitarian products, whereas island and end-of-aisle displays increase sales of hedonic product categories more effectively. The use of congruent promotions creates synergistic influences that reinforce these effects. In particular, price promotions improve the impact of shelf signage on utilitarian products, and product promotions strengthen the impacts of island and end-of-aisle displays on hedonic products. These results extend prior research on in-store marketing actions and the nature of utilitarian versus hedonic products, as well as providing recommendations for retailers and manufacturers seeking to optimize their retail space and commercial budgets.

We propose a model to design bundles’ composition under competition, quantifying its effect in terms of profit and market share in a game among competing firms. According to our literature review, no previous models on optimal bundle composition can handle the competition as we do in this paper. Besides, we explain how a firm designing multiple bundles with equal price obtains a replication of identical bundles and an artificially increased estimation of the firm’s profit and market share, which is a consequence of the well-known Independence of Irrelevant Alternatives Property. To mitigate this effect, we use the Constrained Multinomial Logit Model, which induces differentiation in composition through soft constraints that represent the minimum quantity of the attributes offered in bundles. Although this methodology helps, its use implies more effort to estimate its parameters; nevertheless, these are feasible to be assessed. Firms can use our model to identify the bundles in which they should focus their commercial efforts, given the characteristics of their consumers.

In view of mitigating the threat of climate change due to emissions from transportation sector and to reduce the dependency on foreign countries for oil, many countries have started to develop policies for promoting sustainable and innovative transport technologies. Electric Vehicles (EVs) are considered as one of the best sustainable alternatives to Internal Combustion (IC) engine vehicles. In order to develop fiscal and non-fiscal policy measures for EVs, a thorough understanding about its public acceptability is inevitable for its successful penetration. Even though many policies are purposefully made for improving the EV adoption in developing countries such as India, its market share is still negligible compared to conventional vehicles. Therefore, a case study was conducted in a representative town in India by using a questionnaire survey. Structural Equation Modeling (SEM) was adopted to evaluate the influence of various attitudinal factors on EV purchase intention of the individuals. The results of the study revealed that, the attitudinal factors such as perceived benefits, social influence, price acceptance, performance, technological consciousness, and marketing, distribution and after-sales have positive effect on EV purchase intention. But, the factors like perceived barriers, policy attributes and perceived usefulness and ease of use causes an impeditive effect on EV adoption. People traveling short distances, having lower income, higher education and more experience with driving conventional vehicles is found to favor the adoption of EVs.

Much of the trading in U.S. equities has moved to off-exchange venues. This study examines the pecking order hypothesis of trade venue selection by analyzing the amount of off-exchange trade volume in periods of uncertainty. During the sample period, there were over two billion shares per day reported to the Nasdaq TRF-Carteret, which maintained more than 29 percent of the total market share of volume in U.S. securities. The TRF-NYSE captures more market share in Nasdaq-listed securities than NYSE-listed stocks. This study also sheds light on the introduction of the Nasdaq TRF-Chicago and its ability to attract volume. Ultimately, there is evidence that the amount of off-exchange volume decreases during periods of heightened volatility. The findings are of interest to market participants, exchange officials, and regulators.

We theorize that industry conditions of collaboration intensity and innovation intensity drive the development of competence exploitation and exploration in manufacturer-manufacturer collaborations, and that such competencies can be leveraged to increase firm-level new product sales and market share, contingent on the firm's establishment of non-proprietary knowledge transfer capability. We test our model using a survey of 224 manufacturer-manufacturer collaborations. Our findings indicate that collaboration intensity drives firms to build both competence exploration and exploitation while innovation intensity drives neither. We also find that while non-proprietary knowledge capability enhances the influence of competence exploration on a firm's new product sales and market share, it dampens the firm's ability to leverage competence exploitation for firm-level new product success.

A 2006 rule change in the United States mandated that publicly traded firms provide more detailed disclosures about executives’ compensation plans. In response to the new disclosure requirements, Cournot firms with large market shares add revenue-based pay to their CEOs’ pay packages. This change in pay practices coincides with a shift towards more aggressive product market equilibria, characterized by greater production expenditures and lower margins. Jointly, these patterns are consistent with predictions from the theory of “strategic delegation,” and suggest that the new disclosure requirements enhanced the viability of committing through executive incentives. After adopting the new disclosure requirements, many firms appear to restructure their executives’ pay packages as strategic devices designed to make rivals curtail their competitive actions.

This analysis applies a novel learning-curve methodology with uncertainty through Monte Carlo simulation to forecast market share of competing renewable fuel production technologies from 2025 through 2050. The analysis incorporates uncertainty in technology learning rate within Wright's Law, market rate of growth, and project-specific bidding to develop build-out scenarios for renewable hydrogen production capacity to serve the global market through 2050 with California as a proxy. Two major hydrogen production technologies are included: electrolyzers (with proton exchange membrane electrolytic cells as proxies) and thermochemical devices (with gasifiers as proxies). The method provides a quantitative foundation to forecasting technology shares in emerging sectors, overcomes the weakness of point estimates of relative cost that generally lead to binary behavior, and can support policy development and assessment of community impacts associated with the large-scale facility build-out needed to serve the growing demand for renewable hydrogen in transportation and other applications. Results show that biomass gasifiers are the dominant technology in the early market but the higher learning rate of electrolyzers and long-term trend of price decline for renewable electricity leads to equal shares for new installations by the mid-term and eventually to electrolyzers having the dominant share of new facilities. Electricity, biomass, and initial gasifier technology costs are the three primary factors impacting 2050 renewable hydrogen market composition.

Companies with manufacturing systems that are more responsive and resilient will be able to survive or even gain market shares in the face of the unpredicted variable of an outbreak similar to the COVID-19 pandemic. Motivated by an industrial company restructuring its manufacturing system with the layout of fixed-position assembly islands (FPAI) during the COVID-19 pandemic, this paper introduces the synchronization-oriented reconfiguration of FPAI under Graduation Intelligent Manufacturing System (GiMS). Inspired by the graduation ceremony, a novel manufacturing mode-Graduation Manufacturing System (GMS) with ticket-based reconfigurable structures, is designed for organizing production operations with simplicity and resilience for the layout of FPAI. The IIoT and digital twin-enabled GiMS is developed for transforming real-time visibility in operations to support the reconfiguration of the manufacturing system. A synchronization-oriented reconfiguration mechanism is proposed to achieve the synchronous interaction among changing customer demand, island configuration, and production activities allocation rapidly and cost-effectively. Cloud services integrating the proposed reconfiguration mechanism are developed for managers and onsite operators for supporting the successful reconfiguration implementation with enhanced operational visibility. Through the case study of an industrial company, the effectiveness of the proposed concept and approach is verified.

To achieve carbon targets, the European Union (EU) aims to promote nearly zero-energy buildings (nZEB). To enable the necessary transition, technical solutions need to converge with socio-economic factors, such values and awareness of stakeholders involved in the decision-making process. In this light, the aim of this paper is to characterise perceived drivers and barriers to nine energy-efficient technologies (EET), according to key decision-makers' and persuaders of the technology selection in the EU residential building context. Results are collected across eight EU countries, i.e. Belgium (BE), Germany (DE), Spain (ES), France (FR), Italy (IT), Netherlands (NL), Poland (PL), and United Kingdom (UK). The stakeholders’ selected are architects, construction companies, engineers, installers and demand-side actors. Data from a multi-country survey is analysed to calculate the share of 15 drivers and 21 barriers (aggregated to 5 groups), being selected for each EET and country. The 5 groups considered to analyse drivers and barriers are environmental, technical, economic, social, legal. The perceived barriers and drivers were further studied for their association across the countries using the Pearson's Chi2 and a Cramer's V tests. The results demonstrate that across all EETs and countries, the technical and economic driver groups are perceived to have the highest potential to increase the implementation rate of EET. In terms of barriers, economic aspects are seen as the foremost reason that EET are not scaling faster. In both drivers and barriers legal aspects are the least often selected. In overall the barrier groups show significant variation across countries compared to driver groups. These findings provide an evidence-basis to better understand arguments in favour and against specific EETs and, in this way, support policy makers and other interested parties to increase the market share of the selected solutions.

This case study investigates consumer preferences and stakeholders’ interests regarding hybrid electric vehicles (HEVs) and electric vehicles (EVs) in the Greater Beirut Area (GBA) in Lebanon where the market for these vehicle types is still nascent. A mixed logit model incorporating financial and technical attributes of common mid-size Internal Combustion Engines (ICE), HEVs, and EVs is estimated then used to compute Willingness to Pay (WTP) measures and evaluate the effectiveness of different monetary incentives in promoting these vehicle types. The study also uses qualitative research methods to capture the perspectives of different stakeholders regarding electric mobility in Lebanon. Data collected in 2018 through a stated preference survey reveals a WTP for a 100-km increase in driving range equal to 705 $ and for a 1 $ reduction in driving costs per 100 km equal to 305 $, values that are generally lower than several values found in the literature. A policy testing exercise suggests that doubling fuel taxes could increase the potential market shares of HEVs and EVs from 9.25% to 9.59% and from 4.98% to 5.84%, respectively. The provision of charging incentives to consumers could raise the market share of EVs up to 6.96%. A combination of both policies could further increase the proportion of EVs to 7.22%. In parallel, a stakeholder analysis draws attention to a multitude of challenges regarding the HEVs and EVs uptake as well as the public charging infrastructure rollout, namely excessive delays in establishing the enabling institutional and regulatory environment and shortcomings in the electricity supply. This research shows that it is more likely for HEVs than EVs to take off in the short term and that a solid transition to electric mobility in Lebanon necessitates further planning, especially in terms of instituting a clear and effective incentives scheme.

On-demand mobility services such as bikesharing, scooter sharing, and transportation network companies (TNCs, also known as ridesourcing and ridehailing) are changing the way that people travel by providing dynamic, on-demand mobility that can supplement public transit and personal-vehicle use. Adoption of on-demand mobility has soared across the United States and abroad, driven by the flexibility and affordability that these services offer, particularly in urban areas where population density and land use patterns facilitate a reliable balance of supply and demand. The growth of app-based ridesharing, microtransit, and TNCs presents a unique opportunity to reduce congestion, energy use, and emissions through reduced personal vehicle ownership and increased vehicle occupancy, the latter of which is largely dependent on the decisions of individual travelers to pool or not to pool. This research provides key insights into the policy levers that could be employed to reduce vehicle miles traveled and emissions by incentivizing the use of pooled on-demand ride services and public transit. We employ a general population stated preference survey of four California metropolitan regions (Los Angeles, Sacramento, San Diego, and the San Francisco Bay Area) to examine the opportunities and challenges for drastically expanding the market for pooling, taking into account the nuances in emergent travel behavior and demand sensitivity across on-demand mobility options. Although high-frequency TNC users – those that use TNCs once a week or more - are more likely to consider pooling than less frequent users and reflect more multimodal travel behavior than other travelers, we find that the most captive and price sensitive TNC users are often the most vulnerable. Heavy TNC users – those using TNCs more than three days per week - are disproportionately low income, more likely not to own or lease a car and more likely to use TNCs for essential trip purposes than are less frequent users. Pooling demand sensitivity varies significantly across trip contexts, metropolitan regions, socio-demographics, travel behavior, and attitudes and perceptions toward sharing. We estimate the time and price tradeoffs in choosing between ride alone and shared on-demand service options, finding significant differences across values that travelers place on each component of travel time (wait time, access/egress walking time, and in-vehicle time) by geography and income level. We discuss the potential to leverage these insights to develop policies that combine pricing, curb management, and promotional strategies to increase the pooling market share.

Introduction: The market share of e-scooters in the United States has proliferated in cities: 86 million trips were made on shared e-scooters in 2019, a more than 100% increase compared to 2018. However, the interaction of e-scooters with other road users and infrastructure remains uncertain. Method: This study scrutinized 52 e-scooter and 79 bicycle police-reported crashes in Nashville, Tennessee, from April 2018 to April 2020 from the Tennessee Integrated Traffic Analysis Network (TITAN) database. We used descriptive analysis and a recent prototype version of the Pedestrian and Bicycle Crash Analysis Tool (PBCAT) to classify crashes based on the locations of the crashes relative to roadway segments or intersections, as well as the maneuver of the motor vehicle and e-scooter/bicycle relative to the motor vehicle. Results: Two crash typologies can explain the majority of e-scooter crashes, while bicycle crashes are distributed over several crash typologies. Additionally, 1 in 10 e-scooter- and bicycle-motor vehicle crashes leads to the injury or fatality of the e-scooter rider or bicyclist. Furthermore, we noted statistically significant differences in spatial and temporal distribution, demographics, lighting conditions, and crash distance from home for e-scooter and bicycle crashes. Conclusions: The police crash report provides a comprehensive picture of e-scooter safety complementing existing literature. We found that e-scooter crash characteristics do not fully overlap with features of bicycle crashes. Practical Implications: A generalized engineering, education, and enforcement treatment to reduce and prevent e-scooter and bicycle crashes, injuries, and fatalities might not result in equal outcomes for each mode. More rigorous enforcement could be implemented to deter e-scooters riders under the age of 18 years and e-scooter safety campaigns could target female riders.

The investment decision on second-hand vessels is a critical strategy in capacity management for shipping companies. Unlike the newbuilding and demolition markets, where newbuilding or demolition activities can influence the actual fleet in the shipping industry, transactions in the sales and purchases market only affect the capacity of related companies. Investment in second-hand vessels has been a critical approach to obtaining sustainable growth and company competitiveness in a competitive market environment. However, few studies have analyzed the investment incentives of second-hand vessels. This study fills the research gap with an empirical analysis of the investment decisions of individual buyers. This study uses a unique dataset of 6,806 transactions for second-hand vessels over the last 15-year period (January 2005 to July 2019) in the bulk and container markets. As the investment decision variable is a discrete variable and a vessel can be sold multiple times, we employ the Cox Proportional Hazards model taking various time-invariant and time-variant variables into consideration. To the best of our knowledge, this is the first study to use the survival analysis model to explore investment in second-hand vessels. The estimated result of this study suggests that investment decisions for bulk and container vessels are different, but are both driven by market conditions, maintaining market shares, and competitors’ capacity expansion. The detailed discussion of various types of vessels and shipping companies could provide valuable insights on the investments of shipping companies and stakeholders.

Prior literature has provided little insight into how counterfeit dominance—consumers’ perception that counterfeit brands possess over 50% of market share for authentic and counterfeit brands combined—influences luxury fashion brand owners’ perceptions of their brands across cultures. Our research shows that counterfeit dominance negatively affects the perceived quality and purchase intention of luxury fashion brands across product categories for Anglo-American, but not for Asian, consumers. A social-adjustive attitude underlies this difference. Therefore, counterfeit dominance has stronger negative impacts on luxury fashion brand owners’ perceptions of their brands for those with a weak (Anglo-Americans), but not with a strong (Asians), social-adjustive attitude. Perceived quality mediates the effect of counterfeit dominance on luxury fashion brand owners’ purchase intention in different cultures. This investigation contributes to both theory and practice through examining an understudied phenomenon and also offering strategies to offset the inimical effects of counterfeit dominance.

We use strategic interactions to analyze the role of China's state-subsidized production expansion in the recent downturn in solar photovoltaics innovation. To that end, we develop a dynamic game model in which N solar panel manufacturers compete in price and invest in cost-reducing research. The resulting Nash equilibrium reveals an inverted U relationship between a manufacturer's market share and her research effort. In the duopoly case, with a local firm competing against a foreign state-subsidized one, we obtain analytical and numerical results that are consistent with a set of stylized facts, namely (i) the foreign manufacturer progressively expands to become the dominant player (ii) competition and innovation bring marginal costs down to zero (iii) each manufacturer's research effort follows an increasing-then-decreasing curve. At a policy level, these theoretical results suggest that national technology-push policies can affect foreign innovation, by changing the structure of global competition.

Corporate social responsibility (CSR) has become increasingly important. From the perspective of operations management, traditional non-CSR-compliant operations are less costly than CSR compliant operations but may be subject to the risk of being exposed to the public by third-party organizations such as Non-Governmental Organizations (NGOs) through external scrutiny. This exposure can negatively affect firms’ market share when customers are concerned about firms’ CSR compliance. This paper studies firms’ endogenous CSR compliance strategies, i.e., the incentive to adopt CSR compliant operations. We first consider a single firm's CSR compliance strategies, and then, we extend the analysis to the case of competition. We analyze how exogenous parameters, including the risk of exposure and cost premium, determine equilibrium CSR compliance strategies. We find that CSR compliant operations will be implemented either when the exposure risk is sufficiently high or when the cost premium is sufficiently low. We also discuss how competition affects firms’ CSR compliance strategies and whether firms perform better with CSR compliant operations in equilibrium. Our results show that, by adopting CSR compliant operations, firms will engage in a win-win equilibrium if the external risk is high or if the cost premium is low. Besides, we also conduct the analysis under Bertrand (price) competition. Based on these results, we provide managerial insights into when CSR compliant operations should be adopted in practice and how such adoption affects firms’ performance. Our results also imply that the practice of sustainability requires firms to consider both the external risk of exposure and cost premium.

When a concentrated market for differentiated products exhibits dynamic demand effects due to inertia, contagion, or network externalities, forward-looking firms consider the strategic impact of investment, pricing, and other conduct that can tip the market by grabbing market share. When the contested market provides a line of defense for a more lucrative core market, a firm can have a powerful strategic incentive to capture and control the contested market, as a “loss leader” if necessary. We use this framework to analyze the browser war between Netscape and Microsoft. Adopting a Markov Perfect Equilibrium model to capture firms’ strategic behavior, we discuss the steps needed for such analysis. We compare as-is market trajectories with but-for trajectories under a counterfactual without “anticompetitive acts” deemed in violation of anti-trust law. Our empirical analysis uses incomplete and noisy public data. Consequently, specifications and results should be viewed only as illustrating the method in a highly parametrized model with restrictions that might not be robust. Access to complete and confidential firm data would result in a less restricted model with potentially different results.

In this paper, we study the hub location problem of an airline that wants to set up its hub and spoke network, in order to maximize its market share in a competitive market. The market share is maximized under the assumption that customers choose amongst competing airlines on the basis of utility provided by the respective airlines. We provide model formulations for the airline’s problem for two alternate network settings: one in the multiple allocation setting and another in the single allocation setting. Both these formulations are non-linear integer programs, which are intractable for most of the off-the-shelf commercial solvers. We propose two alternate approaches for each of the formulations to solve them optimally. The first among them is based on a mixed integer second order conic program reformulation, and the second uses Kelley’s cutting plane method within Lagrangian relaxation. On the basis of extensive numerical tests on well-known data-sets (CAB and AP), we conclude that the Kelley’s cutting plane within Lagrangian relaxation is computationally the best for both the single and multiple allocation settings, especially for large instances. We are able to solve instances upto 50 nodes from AP data-set within 120 and 10 minutes of CPU time for single and multiple allocation settings, respectively, which were unsolved by mixed integer second order cone based reformulation or Kelley’s cutting plane algorithm in the maximum allowed CPU time (3 hours for single allocation and 1 hour for multiple allocation).

Understanding how new technologies such as on-demand ride hailing and vehicle automation may affect travel behavior is important to craft better policy. This study uses a 2018 survey of 1,684 employed respondents from vehicle-holding households residing in Southern Ontario, Canada. Stated preference choice experiments are administered and mixed logit models are estimated to explore consumer interest in adopting driverless on-demand vehicles, shared on-demand vehicles, transit plus on-demand vehicles, and driverless public transit shuttles. Monetized generalized costs of each of these choice attributes are estimated. Results indicate generalized costs from combining transit with on-demand ride hailing (a frequently contemplated “last-mile” solution), while users are relatively ambivalent about the generalized cost of shared on-demand ride-hailing. Results indicate that consumers view driverless public transit shuttles and driverless cars as conferring higher generalized costs than vehicles with drivers. Overall, results suggest that the market shares of these modes depend on the potential for service providers to capitalize on heterogenous preferences among consumers. As such, insofar that public transit agencies and the public sector appear less well-suited to nimbly meet heterogeneous consumer demand, the private sector appears poised to play the most direct role in leveraging these new technologies towards meeting user needs. In turn, these findings suggest that the best role for the public sector with respect these new services lies in establishing incentives by engaging with private industry and/or regulating downstream impacts of new mobility services.

Rapid growth in pharmaceutical expenditures and high prices have greatly hampered access to medicines, especially targeted anticancer medicines. Confronted with such difficulties, the Chinese government has put more effort into supporting local research and development of cancer medicines, resulting in locally developed me-too drugs. Since 2016, the government has implemented a central reimbursement-linked drug price negotiation policy aimed at reducing the prices of expensive medicines. Locally developed me-too drugs marketed at lower prices may inject price competition and help negotiate reduced prices of similar internationally-developed products. As an example, we selected 3 tyrosine kinase inhibitors (TKIs) developed for the therapy of advanced non-small cell lung cancer harboring mutations in the epidermal growth factor receptor (EGFR). Descriptive analysis was applied to data from the Chinese Medical Economic Information database to describe the impact on the price and utilization of three TKIs after the introduction of icotinib, a locally developed me-too TKI and two national negotiations regarding the price of EGFR-TKIs in China. After two national negotiations, the daily costs of all three EGFR-TKIs were reduced to around $30. From the first quarter of 2013 to the second quarter of 2016, the market share of the purchasing volume of icotinib, China's locally developed TKI, increased from 13% to 40%, while the market shares of two internationally developed TKIs decreased from 35% to 15% and from 52% to 45%, for erlotinib and gefitinib, respectively. The prices of EGFR-TKIs decreased and China's locally developed TKI accounted for a considerable proportion of market share. Locally developed me-too drugs aid price negotiation by injecting price competition and helping negotiate reduced prices of similar internationally-developed products. Through efforts to develop me-too drugs, combined with national drug price negotiation and reimbursement policies, developing countries might improve access to more affordable targeted cancer therapies.

The objective of this paper is to explore the effects of the influencing factors on the intercity travel mode competition and evaluate their dynamic effects across the travel distance. Passengers’ activity data over the whole process of intercity travel were collected for analysis. A Bayesian binary logistic model was developed to identify the significant factors associated with the intercity travel mode competition. An elasticity analysis was applied to quantitatively analyze the dynamic effects of the significant factors on the intercity travel mode competition. The Bayesian binary logistic models results showed that factors such as the travel distance, intercity travel cost, intercity travel time, safety, comfort, punctuality, access time, and departure time have significant impacts on the intercity travel mode competition. Moreover, the elasticity analysis results showed that the elasticity of the factors varies across the travel distance, and each factor has a heterogeneous effect on the travel mode market share across the travel distance. These findings can help in the implementation of more effective management strategies for intercity travel mode planning.

Electric vehicles have become a trend as a replacement to gasoline-powered vehicles, and been promoted by worldwide policy makers as a solution to combat environmental problems and stimulate economy. Whereas the current market share of electric vehicles is still low, one main obstacle is no enough extreme fast charging, which requires high capital costs and strategic planning. Proper placement of extreme fast charging stations can maximize investment utility, promote public acceptance of electric vehicles, minimize adverse effects on transportation and power networks, and improve penetration market rate for electric vehicles. As such, the research on extreme fast charging station siting and sizing has received considerable attention in the past decade, where optimization modeling has become the main approach. This survey is to review various optimization models, examine their characteristics and evaluate their applications. We also discuss challenges/limitations of the optimization modeling approach for the extreme fast charging location planning, and point out future research directions. Our study can serve as a tutorial/reference to the extreme fast charging location optimization modeling, and attempts to attract more talents and research interests in this exciting field.

We examine the role of firms’ market power in affecting the link between firm-specific uncertainty and corporate investment decisions in a small open economy with a pronounced degree of concentration and mark-ups. Using firm-level data from South African-listed firms, we find that corporate investment of firms with low market power and market share responds positively to idiosyncratic uncertainty. A high degree of market power, however, moderates this positive relationship, allowing for delayed investment under conditions of uncertainty. The results are robust to alternative measures of firm-specific uncertainty and firms’ competitive position. The finding of an association between firms’ market power/market share and their capital budgeting decisions under uncertainty calls for effective competition policies.